INFORMATION TO USERS This manuscript has been reproduced from the microfilm master. UMI films the text directly from the original or copy submitted. Thus, some thesis and dissertation copies are in typewriter face, while others may be from any type o f computer printer. The q u ality o f this reproduction is dependent upon the quality of the copy su b m itted . Broken or indistinct print, colored or poor quality illustrations and photographs, print bleedthrough, substandard margins, and improper alignment can adversely affect reproduction. In the unlikely event that the author did not send UMI a complete manuscript and there are missing pages, these will be noted. Also, if unauthorized copyright material had to be removed, a note will indicate the deletion. Oversize materials (e.g., maps, drawings, charts) are reproduced by sectioning the original, beginning at the upper left-hand com er and continuing from left to right in equal sections with small overlaps. Each original is also photographed in one exposure and is included in reduced form at the back o f the book. Photographs included in the original manuscript have been reproduced xerographically in this copy. Higher quality 6” x 9” black and white photographic prints are available for any photographs or illustrations appearing in this copy for an additional charge. Contact UMI directly to order. UMI A Bell & Howell Information Company 300 North Zeeb Road, Aim Arbor M l 48106-1346 USA 313/761-4700 800/521-0600 AN ANALYSIS OF BASELINE DATA TO ASSESS STRUCTURAL SHIFTS, TRENDS AND LINKAGES OF MICHIGAN'S PRODUCTION AGRICULTURE ECONOMY DURING THE 1 9 7 0 ' s AND 1 9 8 0 ' s VOLUME I By J o h n Frederick W him s A DISSERTATION S ub mitted to Michigan S ta te University in partial fulfillment of th e re quire m en ts for th e d e g r e e of DOCTOR OF PHILOSOPHY D e p a r tm e n t of Agricultural Economics 1995 UMI Number: 9619924 Copyright 1995 by Whims, John Frederick All rights reserved. UMI M icroform 9619924 C opyright 1996, by UMI C om pany. All rights reserved. This m icroform edition is protected against unauthorized copying under Title 17, United States Code. UMI 300 N orth Zeeb Road Ann A rbor, M I 48103 ABSTRACT AN ANALYSIS OF BASELINE DATA TO ASSESS STRUCTURAL SHIFTS, TRENDS, AND LINKAGES OF MICHIGAN'S PRODUCTION AGRICULTURE ECONOMY DURING THE 1 9 7 0 s AND 1 9 8 0 s By J o h n F. Whims M ichigan 's agriculture e c o n o m y an d it's par ticipants will f ace man y oppor tun ities an d c h all en g es in th e future. It w a s t h e p u r p o s e of this disser tatio n to a s s e m b l e a c o m p r e h e n s i v e collection of Michigan production agriculture baseline d a t a a n d to apply th e statistical m e t h o d s of ordinary least s q u a r e s r eg re ssion, s hift-sha re analysis, and in put-o utput modeling, to d e t e r m in e th e trends, shifts, and linkages of the s e c t o r during t h e d e c a d e s of th e 1 9 7 0 ' s an d 1 9 8 0 ' s . This r e se a r c h effort is o n e of th e m o s t e x tens iv e historical review s of Michigan production agriculture ev e r g e n e r a t e d . Over thirty eight different c o m m o d iti e s from th e field crop, livestock, fruit and v e g e ta b l e s e c t o r s w e r e an al yze d. The analysis of baseline d a t a will aid individuals involved in s t a t e farm organizations, farm e n te r p ris es, a g r ib u s in e s s e s , food p ro c e s s in g c o m p a n ie s , gov e r n m e n ta l a gencies , universities, environ mental g r o u p s and input suppliers, in making their future decisions. The following is a brief highlight of s o m e of th e findings: Trend Highlights: ■ The n u m b e r of Michigan fa rm s declined 3 5 . 7 % , from 8 4 , 0 0 0 in 1 9 7 0 to 5 4 , 0 0 0 in 1 9 9 0 . ■ S t a t e s o y b e a n p roductio n e x p a n d e d m or e th a n a n y o th e r cr op (fruit, field, food or vegetab le), increasing from approxim ate ly 10 million bus hels a yea r to over 4 0 million b u s h e ls a year , up 3 0 0 % . ■ Dry b e a n produ ction fell precipitously, d o w n approxim ate ly 3 3 % from 6 . 7 0 million C w t. per year to 4 . 4 5 million Cw t. per year. ■ Significant g r o w t h o c c u r re d in turk ey pro duc tion; from 1 9 7 3 to 1 9 9 0 , p roduction e x p a n d e d from 2 0 million p o u n d s a yea r to over 125 million p o u n d s a year, up 5 2 5 % . Shift-Share Highlights: ■ Michigan lagged t h e c o m p a r a t iv e U.S. g r o w t h rate s of c a s h re ce ipts for livestock, fruit, and v e g e ta b le cr o p s from 1 9 7 0 to 1 9 9 0 . Only s t a t e field cr op c a s h rec ei pts e x p a n d e d at a f aster rate th a n U.S. receipts. ■ Th e com m odities with th e largest co m peti tive gains in c a s h rece ip ts we re ; h o g s , turk e ys, corn, s o y b e a n s , blueberries, s n a p b e a n s an d a s p a r a g u s . M ost Michigan fruit an d v e g e ta b l e c o m m o d it ie s c a s h receipt rates lagged t h e U.S. rates. Economic (Linkages) Highlights: ■ On a v e r a g e , for e a c h job in production a gric ultu re,1 t h e r e are 1.31 additional jobs linked to th e industry in o t h e r s e c t o r s of the economy. ■ On a v e r a g e , for e a c h dollar increase in final d e m a n d for production agricultural c om m oditi es (output), an additional $ 1 . 0 6 of o u t p u t is c r e a t e d in o th e r s e c t o r s of the e c o n o m y . 1 Includes th e cr op an d livestock s e c to rs . Copyright by J o h n Frederick Whims 1 995 ACKNOWLEDGMENTS M any individuals h a v e e n c o u r a g e d me during my doctora l prog ra m e n d e a v o r s . W i th out their help and insights this diss er ta tio n would n o t h av e b e c o m e a reality. I would like to especially th a n k Lester M anders cheid, c o m m i t t e e chairm an, for his g u id a n c e an d e n c o u r a g e m e n t t h r o u g h o u t my a c a d e m i c c a r e e r at Michigan S t a t e University. It w a s an hon or and privilege to m atu re both intellectually an d as a p er so n while un der his tu tel ag e. To J o h n Ferris, o n e of th e r e a s o n s for c om ing to Michigan S t a te , t h a n k you for th e op portu nit y to learn from you both a s a s t u d e n t and an a s s o c i a t e in th e field of agricultural e c o n o m ic s . I also th a n k Larry Co nnor for his brief but seminal role a s my disser ta tion advisor. To t h e o th e r m e m b e r s of my g u id an ce c o m m i t t e e including J a m e s Bonnen an d MaryLee Davis, you r c o m m e n t s c o n cernin g t h e diss er ta ti on and o p en door policies w e r e greatly app r e c ia te d . To my p a r e n t s Fred an d A n n e t te , t h a n k you for yo ur prayers an d cou ns el. And to W inston, a b e s t friend, w h o h a s given so g en er o u sly and a s k e d so little in return. vi TA BL E O F C O N T E N T S I. INTRODUCTION.............................................................................................................. 1 P u r p o s e of th e S t u d y ......................................................................................... 1 Evolution of th e S tu d y ...................................................................................... 1 F utu re s T e a m 2 0 2 0 ................................................................................... 2 S t a t u s an d Potential of Michigan Agriculture ( S A P M A ) ................. 3 R es e a r c h Identification and Re sea rc h A p p r o a c h ...................................... 5 R es e a r c h Identification ............................................................................. 5 R e s e a r c h A p proach ................................................................................ 11 15 Organization of t h e S t u d y ............................................................................. II. REVIEW OF THE LITERATURE............................................................................. A Review of R ec en t Michigan S t a te University an d D e p a r tm e n t of Agricultural Economics , Production Agriculture A s s e s s m e n t P u b l i c a t i o n s ........................................................................ S u m m a r y .............................................................................................................. 16 26 III. M E T H O D S ................................................................................................................. Time Series Trend A n a l y s i s .......................................................................... Explanation of t h e Time Series Method of A n a l y s i s ................... Shift S h a r e M ethod of Analysis ................................................................. Explanation of Shift-Share Method of Analysis .............................. I np ut-Output Analysis (Linkages) .............................................................. Explanation of Input-Output Method of A n a l y s i s ........................... 27 27 30 38 38 40 40 IV. MICHIGAN PRODUCTION AGRICULTURETRENDANALYSIS ................ General Farming Overview .......................................................................... N u m ber of F a r m s ...................................................................................... Land in Farms ............................................................................................ A v e r a g e Size of Farms .......................................................................... General Field Crop O v e r v i e w ....................................................................... B a r l e y .............................................................................................................. Corn for G r a i n ............................................................................................ Corn S i l a g e .................................................................................................. Dry B e a n s ..................................................................................................... Hay ................................................................................................................. O a t s ................................................................................................................. All P o t a t o e s .................................................................................................. S o y b e a n s ..................................................................................................... S u g a r b e e t s .................................................................................................. W h e a t ........................................................................................................... 51 51 51 51 52 55 60 64 68 71 75 79 82 86 90 94 16 viii Genera! Livestock Overview ........................................................................ 9 8 Dairy ................................................................................................................. 101 Hogs an d P i g s ................................................................................................1 0 6 All Cattle an d Calves .................................................................................1 1 0 S h e e p and L a m b s ..........................................................................................11 5 Layers .............................................................................................................. 1 1 8 C h i c k e n s ........................................................................................................... 1 2 2 B r o i l e r s .............................................................................................................. 12 5 Turkey s ........................................................................................................... 1 2 8 General Fruit O v e r v i e w .......................................................................................1 3 2 Apples .............................................................................................................. 1 3 6 G r a p e s .............................................................................................................. 1 4 0 P e a c h e s ........................................................................................................... 14 5 P ea rs ................................................................................................................. 1 4 9 P runes and P l u m s ..........................................................................................1 5 3 S w e e t Cherries ............................................................................................ 1 5 7 Ta rt C h e r r i e s ...................................................................................................161 General Ve getab le O v e r v i e w ...........................................................................1 6 6 A s p a r a g u s (Dual Purpose) ........................................................................1 7 0 Ca rrots (Dual P ur po se ) ..............................................................................1 7 3 Cauliflower (Dual P u r p o s e ) ........................................................................1 7 7 Celery (Dual P u r p o s e ) .................................................................................1 8 0 C u c u m b e r s (Processing) ...........................................................................1 8 4 Le ttuce (Fresh Market) ..............................................................................1 8 7 M u s h r o o m s ..................................................................................................... 191 Onions (Fresh M a r k e t ) .................................................................................1 9 4 S n a p Bea ns ( P r o c e s s i n g ) ...........................................................................1 9 8 S tra w berr ies (Dual P u r p o s e ) .................................................................... 201 S w e e t Corn (Fresh Market) .................................................................... 2 0 5 T o m a t o e s (Fresh M a r k e t ) .......................................................................... 2 0 8 T o m a t o e s (Processing) ............................................................................. 2 1 2 V. THE APPLICATION OF SHIFT-SHARE ANALYSIS TO FARM CASH RECEIPTS, TO ASSES S THE SHIFTS IN MICHIGAN'S COMPETITIVE POSITION IN PRODUCTION AGRICULTURE RELATIVE TO THE UNITED S T A T E S ........................................................... 2 1 7 Introduction ........................................................................................................... 2 1 7 Th e S tru c tu r e of th e Basic Shift-Share model .......................................2 1 9 The S t r u c t u r e of t h e Arcelus (I), Shift-Share Model ...........................2 2 2 An Example of Shift-Share Analysis Applied to Michigan Dry B e a n s ................................................................................................................. 2 2 6 Dry Beans C ash Receipts from M a r k e t i n g s .......................................2 2 6 Identification of Variables for Shift-Share A n a l y s i s ........................2 2 6 Calculation of th e Arcelus Model C o m p o n e n t s for Dry Bea ns 2 2 7 ix Interpretation of th e Shift-Share Results for Dry B e a n s ...............2 2 8 Highlights of t h e Arcelus Shift-Share Model Results ...........................2 3 4 Livestock a n d P r o d u c ts 1 9 7 0 - 1 9 8 0 ................................................... 2 3 4 Livestock an d P r o d u c ts 1 9 8 0 - 1 9 9 0 ................................................... 2 3 5 Livestock a n d P r o d u c ts 1 9 7 0 - 1 9 9 0 ................................................... 2 3 7 Field C rop s 1 9 7 0 - 1 9 8 0 ........................................................................... 2 3 8 Field Crops 1 9 8 0 - 1 9 9 0 ........................................................................... 2 3 9 Field C rop s 1 9 7 0 - 1 9 9 0 ........................................................................... 2 4 0 Fruit and Oth er 1 9 7 0 - 1 9 8 0 .................................................................. 2 4 2 Fruit a n d Other 1 9 8 0 - 1 9 9 0 .................................................................. 2 4 4 Fruit and O ther 1 9 7 0 - 1 9 9 0 .................................................................. 2 4 5 V e g e t a b le s an d Melons 1 9 7 0 - 1 9 8 0 ................................................... 2 4 6 V e g e t a b l e s an d Melons 1 9 8 0 - 1 9 9 0 ................................................... 2 4 8 V e g e t a b l e s an d Melons 1 9 7 0 - 1 9 9 0 ................................................... 2 4 9 VI. THE APPLICATION OF INPUT-OUTPUT MODELING TO ASSESS THE LINKAGES AND IMPACT OF PRODUCTION AGRICULTURE ON THE STATE OF MICHIGAN'S ECONOMY ..........................................2 6 9 Introduction ........................................................................................................... 2 6 9 Employm ent, Out put, and Personal Inco me Multipliers Explained . 2 7 2 Em ploym en t M u l t i p l i e r s ............................................................................. 2 7 2 O u t p u t M u l t i p l i e r s ......................................................................................... 2 7 3 Total Inco m e Multipliers ...........................................................................2 7 5 R ev iew of l-O Model Results: t h e Multipliers ..........................................2 7 6 Em ploym en t Multiplier Review ...............................................................2 7 6 O u t p u t Multiplier R e v i e w .......................................................................... 2 7 8 Total Inco me Multiplier R e v i e w ...............................................................2 7 9 Supply, D em an d , an d Trade A c c o u n t s Explained .................................2 8 7 Supply-Side A c c o u n t Definitions: Table V I I .......................................2 8 8 D em and-S id e A c c o u n t Definitions: Table VIII .................................2 8 9 Balance of Trad e A c c o u n t Definitions: Table I X ..............................2 9 0 Rev iew of l-O Model Results: Supply, D em an d, an d Trade Flow A c c o u n t s ........................................................................................................ 2 9 2 Supply-Side A c c o u n t R e v i e w ................................................................. 2 9 2 Dem an d-S id e A c c o u n t R e v i e w ...............................................................2 9 3 Balance of Trad e A c c o u n t ....................................................................... 2 9 5 VII. MAJOR FINDINGS AND SYNTHESIS ...............................................................3 0 3 Major F i n d i n g s ........................................................................................................ 3 0 4 General F a r m i n g ............................................................................................ 3 0 4 Trend Analysis Highlights ......................................................3 0 4 Field C rop s ..................................................................................................... 3 0 5 Trend Analysis Highlights ..................................................... 3 0 5 Shift-Share Analysis H i g h l i g h t s .............................................3 0 7 X Shift-Share Analysis H i g h l i g h t s ............................................ 3 0 7 Input-O utput Analysis H i g h l i g h t s ......................................... 3 1 0 Livestock an d P o u l t r y ................................................................................3 1 0 Trend Analysis Highlights ..................................................... 3 1 0 S hift-Share Analysis H i g h l i g h t s ............................................ 3 1 2 In pu t-O utput Analysis H i g h l i g h t s ......................................... 3 1 5 Fruit an d Other ............................................................................................3 1 5 Trend Analysis Highlights ..................................................... 3 1 5 Shift-Share Analysis Highlights for Fruit and Other . 3 1 7 Input-Output Analysis H i g h l i g h t s ......................................... 3 2 0 V e g e ta b le s .....................................................................................................321 Trend Analysis Highlights ..................................................... 321 Shift-Share Analysis Highlights for V egetable s : . . . . 3 2 4 Input-O utput Analysis Highlights ...........................3 2 6 S y n t h e s i s .................................................................................................................3 2 7 R e s e a r c h C o n s i d e r a t i o n s ................................................................................... 3 3 0 APPENDICES Appendix A, Data S e t for C h apter IV, Trend Analysis ........................3 3 2 Appendix B, Regression Results for C hap ter I V .......................................3 5 5 Appendix C, Data S e t for C h a p te r V, Shift-Share A n a l y s i s 370 BIBLIOGRAPHY 382 LIST OF FIGURES Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure 1 Number of Farms, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ............................ 2 Total Land in Farms, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ...................... 3 A verage Farm Size, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 .......................... 4 All Field Crops Value of Production, 2 1 -Year Trend, 1 9 7 0 1990 5 All Field Crops Acres H ar ves ted , 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 . 6 Barley Value of Production, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 . . . . 7 Barley Acres Har vest ed, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ................. 8 Barley Production, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ............................ 9 Barley Yield, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ........................................ 10 Barley Price, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ....................................... 11 Corn for Grain Value of Production, 2 1 -Year Trend, 1 9 701 9 9 0 ....................................................................................................................... 12 Corn-All P u r p o s e s Acres Har vest ed, 2 1 -Year Trend, 1 9 7 0 1 9 9 0 ....................................................................................................................... 13 Corn for Grain Production, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 . . . . 14 Corn for Grain Yield, 21-Year Trend, 1 9 7 0 - 1 9 9 0 .................... 15 Corn for Grain Price, 21-Year Trend, 1 9 7 0 - 1 9 9 0 ................... 16 Corn Silage Acres H ar ves ted , 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 . . 17 Corn Silage Production, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ............... 18 Corn Silage Yield, 21-Year Trend, 1 9 7 0 - 1 9 9 0 ........................... 19 Dry Beans Value of Production, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 . 2 0 Dry Be ans Acres H ar ve sted , 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 . . . 21 Dry Beans Production, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ................. 2 2 Dry Be ans Value Yield, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ................ 2 3 Dry Beans Price, 21-Year Trend, 1 9 7 0 - 1 9 9 0 ............................ 2 4 All Hay Value of Production, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 . . . 25 All Hay Acres H ar ves ted , 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ............ 2 6 All Hay Production, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ........................ 2 7 All Hay Yield, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 .................................... 2 8 All Hay Price, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 .................................... 2 9 O ats Value of Production, 21 -Year Trend, 1 9 7 0 - 1 9 9 0 ............ 3 0 O a ts Acr es H ar ves te d, 2 1 -Year Trend, 1 9 7 0 - 1 9 3 0 .................. 31 O ats Production, 21-Year Trend, 1 9 7 0 - 1 9 9 0 .............................. 3 2 O a ts Yield, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 .......................................... 3 3 O ats Price, 21-Year Trend, 1 9 7 0 - 1 9 9 0 .......................................... 3 4 P o t a t o e s Value of Production, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 . . 3 5 P o t a t o e s Acres H ar ve sted , 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 . . . . 3 6 P o t a t o e s Production, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ..................... 3 7 P o t a t o e s Yield, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ................................. 3 8 P o t a t o e s Price, 21- Year Trend, 1 9 7 0 - 1 9 9 0 ................................. xi 53 53 54 59 59 61 62 62 63 63 66 66 67 67 68 69 70 70 72 73 73 74 74 76 77 77 78 78 80 80 81 81 82 84 84 85 85 86 xii Figure Figure Figure Figure Figure Figure 3 9 S o y b e a n s Value of Production, 21- Year Trend, 1 9 7 0 - 1 9 9 0 . 4 0 S o y b e a n s Pro duction , 21-Year Trend, 1 9 7 0 - 1 9 9 0 .................. 41 S o y b e a n s Acres H a r v este d , 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 . . . 4 2 S o y b e a n s Yield, 21 Year Trend, 1 9 7 0 - 1 9 9 0 .............................. 4 3 S o y b e a n s Price, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 .............................. 4 4 S u g a r b e e t s Value of Production, 21-Y ear Trend, 1 9701 9 9 0 ....................................................................................................................... Figure 4 5 S u g a r b e e t s Acr es H a r v ested , 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 . . Figure 4 6 S u g a r b e e t s Production, 21-Year Trend, 1 9 7 0 - 1 9 9 0 ............... Figure 4 7 S u g a r b e e t s Yield, 21-Y ear Trend, 1 9 7 0 - 1 9 9 0 ........................... Figure 4 8 S u g a r b e e t s Price, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ........................... Figure 4 9 W h e a t Value of Production, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 . . . Figure 5 0 W h e a t Acres H a r v e st e d , 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ............... Figure 51 W h e a t P ro du ction, 21-Year Trend, 1 9 7 0 - 1 9 9 0 ........................... Figure 5 2 W h e a t Yield, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ....................................... Figure 5 3 W h e a t Price, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ....................................... Figure 5 4 Total Livestock Value of Production, 18 Year Trend, 19731 9 9 0 ....................................................................................................................... Figure 55 Total Milk Value of Production, 18 Year Trend, 1 9 7 3 - 1 9 9 0 . Figure 5 6 Milk C o w N u m b er s, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ........................ Figure 5 7 Total Milk P r o d u c e d , 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ..................... Figure 5 8 A v erage O u t p u t per Cow , 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ............ Figure 5 9 All Milk W h o le s a l e Price, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ............ Figure 6 0 All Hogs & Pigs Value of Production, 18 Year Trend, 19731 9 9 0 ....................................................................................................................... Figure 61 All Hogs & Pigs N u m b er s, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 . . . . Figure 6 2 All Hogs & Pigs P roduction, 18 Year Trend, 1 9 7 3 - 1 9 9 0 . . . Figure 6 3 All Hogs & Pigs Price, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 .................. Figure 6 4 Cattle & Calves Value of Production, 18 Year Trend, 1 9 731 9 9 0 ....................................................................................................................... Figure 6 5 All Cattle & Calves Number s, 21-Y ear Trend, 1 9 7 0 - 1 9 9 0 . . Figure 6 6 All Cattle & Calves Production, 18 Year Trend, 1 9 7 3 - 1 9 9 0 . Figure 6 7 Cattle Price, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ....................................... Figure 6 8 Calves Price, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 Figure 6 9 Beef C o w N u m b er s, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ........................ Figure 7 0 S h e e p & Lambs Value of Production, 18 Year Trend, 197 31 9 9 0 ....................................................................................................................... Figure 71 S h e e p & Lamb N u m b er s, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ............ Figure 7 2 S h e e p & Lambs Production, 18 Year Trend, 1 9 7 3 - 1 9 9 0 . . . Figure 7 3 S h e e p & Lambs Price, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 .................. Figure 7 4 Eggs Value of Pro duc tion, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 . . . . Figure 7 5 Hens & Pullets of Laying Age, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 . . Figure 7 6 Egg Production, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 .............................. Figure 7 7 A v e r a g e O u tp u t per Layer, 21-Year Trend, 1 9 7 0 - 1 9 9 0 . . . . 88 88 89 89 90 92 92 93 93 94 95 96 96 97 97 98 104 104 105 105 106 108 108 109 109 112 112 113 113 114 11 4 116 11 6 117 117 119 120 120 121 xiii Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure Figure 7 8 Price of Eggs, 21-Year Trend, 1 9 7 0 - 1 9 9 0 .................................... 121 7 9 Chickens Value of Production, 17-Year Trend, 1 9 7 4 - 1 9 9 0 . . 1 2 3 8 0 Num be r of Chickens Sold, 21- Year Trend, 1 9 7 0 - 1 9 9 0 . . . . 123 81 Chicken Production, 1 7-Year Trend, 1 9 7 4 - 1 9 9 0 124 8 2 Price of Chickens , 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ........................... 1 2 4 8 3 Broilers Value of Production, 17-Year Trend, 1 9 7 4 - 1 9 9 0 . . . 1 2 6 8 4 N um ber of Broilers P r o d u ced , 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 . . 1 2 7 8 5 Broiler Production, 1 7-Year Trend, 1 9 7 4 - 1 9 9 0 ........................... 127 8 6 Price of Broilers, 21-Year Trend, 1 9 7 0 - 1 9 9 0 .............................. 128 8 7 Tu rkey s Value of Production, 18-Year Tren d, 1 9 7 3 - 1 9 9 0 . . 1 3 0 8 8 Num ber of Turk ey s, 18-Year Trend, 1 9 7 3 - 1 9 9 0 ........................ 1 3 0 8 9 Turkey Production, 18-Year Trend, 1 9 7 3 - 1 9 9 0 ........................ 131 9 0 Price of Turk ey s, 1 8-Year Trend, 1 9 7 3 - 1 9 9 0 .............................. 131 91 Total Fruit Value of Production, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 . 135 9 2 Total Fruit Acres H arvested, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 . . . 135 9 3 Apples Value of Production, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 . . . 1 3 7 9 4 Apples Acres H arvested, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ........... 138 9 5 Apples Num ber of Trees, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ........... 13 8 9 6 Apples Production, 21-Year Trend, 1 9 7 0 - 1 9 9 0 ........................ 13 9 9 7 Apple Yields, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ................................... 13 9 9 8 Apples Price, 21-Year Trend, 1 9 7 0 - 1 9 9 0 ................................... 1 4 0 9 9 G rap es Value of Production, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 . . . 14 2 1 0 0 G rap es Acr es H arvested, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 . . . . 142 101 Grap es Number of Vines, 21-Year Trend, 1 9 7 0 - 1 9 9 0 . . . . 1 4 3 1 0 2 Grape Production, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ....................... 14 3 1 0 3 Grape Yields, 21-Y ea r Trend, 1 9 7 0 - 1 9 9 0 ................................ 1 4 4 1 0 4 G r apes Price, 21-Year Trend, 1 9 7 0 - 1 9 9 0 ................................ 1 4 4 1 0 5 P e a c h e s Value of Production, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 . 1 4 6 1 0 6 P e a c h e s Acr es H arv ested, 21-Year Trend, 1 9 7 0 - 1 9 9 0 . . . 1 4 6 1 0 7 P e a c h e s Number of Trees , 21-Y ear Trend, 1 9 7 0 - 1 9 9 0 . . . 147 1 0 8 P e a c h e s Production, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ................. 1 4 7 1 0 9 P e a c h e s Yield, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ............................. 148 1 1 0 P e a c h e s Price, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ............................. 1 4 8 111 Pear s Value of Production, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 . . . 150 1 1 2 Pear s Acres H ar ves te d, 21- Year Trend, 1 9 7 0 - 1 9 9 0 ........... 1 5 0 1 1 3 Pear s Number of Trees, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ........... 151 1 1 4 Pear s Production, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ....................... 151 1 1 5 Pear s Yields, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ................................... 152 1 1 6 Pears Price, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ................................... 1 5 2 1 1 7 Prunes & Plums Value of Production, 2 1 -Year Trend, 1 9 7 0 1 9 9 0 ....................................................................................................................... 1 5 4 Figure 1 1 8 Pru ne s & Plums Acres Har vest ed , 2 1 -Year Trend, 1 9 7 0 1 9 9 0 ....................................................................................................................... 1 5 4 Figure 1 1 9 Prunes & Plums Number of Trees, 2 1 -Year Trend, 1 9 7 0 1 9 9 0 ....................................................................................................................... 155 xiv Figure Figure Figure Figure 1 2 0 P runes & Plums Production, 2 1 -Year Tren d, 1 9 7 0 - 1 9 9 0 . . 121 P runes & Plums Yield, 21-Yea r Trend, 1 9 7 0 - 1 9 9 0 ............... 122 Prun es & Plums Price, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ............... 1 2 3 S w e e t Cherries Value of P roduction, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ............................................................................................................ Figure 1 2 4 S w e e t Cherries Acres H a r v ested , 2 1 -Year Trend, 1 9 7 0 1 9 9 0 ........................................................................................................................ Figure 12 5 S w e e t Cherries Num be r of Trees , 2 1 - Y e a r Trend, 1 9 701 9 9 0 ........................................................................................................................ Figure 1 2 6 S w e e t Cherries Production, 21 -Y ea r T r e n d , 1 9 7 0 - 1 9 9 0 . . . Figure 1 2 7 S w e e t Cherries Yield, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 .................. Figure 12 8 S w e e t Cherries Price, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 .................. Figure 1 2 9 Tart Cherries Value of P roduction, 2 1 -Year Trend, 1 9 701 9 9 0 ........................................................................................................................ Figure 1 3 0 Tart Cherries A cres H arveste d, 2 1 -Y ear Trend, 1 9 7 0 - 1 9 9 0 Figure 131 Tart Cherries N um b er of Trees , 2 1 -Year Tren d, 1 9 701 9 9 0 ........................................................................................................................ Figure 1 3 2 Tart Cherries Production, 21-Y ea r T ren d, 1 9 7 0 - 1 9 9 0 . . . . Figure 1 3 3 Tart Cherries Yield, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 .................... Figure 1 3 4 Tart Cherries Price, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 .................... Figure 135 Total V e g e ta b l e s Value of Production, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ........................................................................................................................ Figure 1 3 6 Total V e g e ta b le s Acres H a r v e s te d , 2 1 -Year Trend, 1 9 701 9 9 0 ................................................................................... Figure 1 3 7 A s p a r a g u s (Dual Purpose) Value of Productio n, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ............................................................................................. Figure 1 3 8 A s p a r a g u s (Dual Purpose) Acr es H a r v e s te d , 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ............................................................................................. Figure 1 3 9 A s p a r a g u s (Dual Purpose) P roduction, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ............................................................................................................ Figure 1 4 0 A s p a r a g u s (Dual Purpose) Yield, 2 1 -Year T ren d, 1 9 7 0 1 9 9 0 ........................................................................................................................ Figure 141 A s p a r a g u s (Dual Purpose) Price, 21-Y ea r Trend, 1 9 7 0 1 9 9 0 ........................................................................................................................ Figure 1 4 2 Ca rrots (Dual Purpose) Value of P r o ducti on, 21-Year Trend, 1 9 7 0 - 1 9 9 0 ............................................................................................. Figure 1 4 3 Carrots (Dual Purpose) Acr es H a r v e s te d , 21- Yea r Trend, 1 9 7 0 - 1 9 9 0 ............................................................................................................ Figure 1 4 4 Ca rrots (Dual Purp ose) Production, 2 1 -Year Trend, 1 9 7 0 1 9 9 0 ........................................................................................................................ Figure 145 Carrots (Dual Pu rp ose) Yield, 2 1 -Year Tren d, 1 9 7 0 - 1 9 9 0 . Figure 1 4 6 Carrots (Dual Purp ose) Price, 21- Year T rend, 1 9 7 0 - 1 9 9 0 . Figure 1 4 7 Cauliflower (Dual Purpose) Value of P ro du ction, 21-Year Trend, 1 9 7 0 - 1 9 9 0 ............................................................................................. 155 156 156 15 8 159 159 160 160 161 163 163 164 164 16 5 165 169 169 171 171 172 172 173 174 175 175 176 176 178 XV Figure 1 4 8 Cauliflower (Dual Purpose) Acres H arvested, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ............................................................................................... Figure 1 4 9 Cauliflower (Dual Purpose) Production, 21-Year Trend, 1 9 7 0 - 1 9 9 0 ........................................................................................................... Figure 1 5 0 Cauliflower (Dual Purp ose) Yield, 2 1 -Year Trend, 1 9 701 9 9 0 ....................................................................................................................... Figure 151 Cauliflower (Dual Purpose) Price, 21-Year Trend, 1 9 701 9 9 0 ....................................................................................................................... Figure 1 5 2 Celery (Dual Purpose) Value of Production, 21-Year Trend, 1 9 7 0 - 1 9 9 0 ........................................................................................................... Figure 1 5 3 Celery (Dual Purpose) Acres Har vest ed, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ........................................................................................................... Figure 1 5 4 Celery (Dual Purpose) Production, 2 1 -Year Trend, 1 9 701 9 9 0 ....................................................................................................................... Figure 1 5 5 Celery (Dual Purp ose) Yield, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 . . Figure 1 5 6 Celery (Dual Purpose) Price, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 . . Figure 1 5 7 C u c u m b e r s (Processing) Value of Production, 21-Year Trend, 1 9 7 0 - 1 9 9 0 ............................................................................................. Figure 1 5 8 C u c u m b e r s (Processing) Acres Har vest ed, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ........................................................................................................... Figure 1 5 9 C u c u m b e r s (Processing) Production, 2 1 -Year Trend, 1 9 7 0 1 9 9 0 ....................................................................................................................... Figure 1 6 0 C u c u m b e r s (Processing) Yield, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 Figure 161 C u c u m b e r s (Processing) Price, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 Figure 1 6 2 Le ttuce (Fresh Market) Value of Production, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ............................................................................................ Figure 1 6 3 Le ttu ce (Fresh Market) Acres H ar ves ted , 21-Year Trend, 1 9 7 0 - 1 9 9 0 ........................................................................................................... Figure 1 6 4 Le ttu ce (Fresh Market) Production, 2 1 -Year Trend, 1 9701 9 9 0 ....................................................................................................................... Figure 1 6 5 Le ttu ce (Fresh Market) Yield, 21-Y ear Trend, 1 9 7 0 - 1 9 9 0 . Figure 1 6 6 Le ttu ce (Fresh Market) Price, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 . Figure 1 6 7 M u s h r o o m s Value of Production, 10 Year Trend, 1 9 811 9 9 0 ....................................................................................................................... Figure 1 6 8 M u s h r o o m s Acr es H ar ves ted , 10 Year Trend, 1 9 8 1 - 1 9 9 0 . Figure 1 6 9 M u s h r o o m s Production, 10 Year Trend, 1 9 8 1 - 1 9 9 0 ............ Figure 1 7 0 M u s h r o o m s Yield, 10 Year Trend, 1 9 8 1 - 1 9 9 0 ........................ Figure 171 M u s h r o o m s Price, 10 Year Trend, 1 9 8 1 - 1 9 9 0 ........................ Figure 1 7 2 Onions (Fresh Market) Value of Production, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ............................................................................................ Figure 1 7 3 Onions (Fresh Market) Acres H ar ves ted, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ........................................................................................................... Figure 1 7 4 Onions (Fresh Market) Production, 2 1 -Year Trend, 1 9701 9 9 0 ....................................................................................................................... 17 8 179 179 180 181 182 182 183 183 185 185 186 186 187 188 189 189 190 190 192 192 193 193 194 195 196 196 xvi Figure 1 7 5 Onions (Fresh Market) Yield, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 . . Figure 1 7 6 Onions (Fresh Market) Price, 21-Year Trend, 1 9 7 0 - 1 9 9 0 . . Figure 1 7 7 S n a p Beans (Processing) Value of Production, 21- Year Trend, 1 9 7 0 - 1 9 9 0 ............................................................................................ Figure 1 7 8 S n a p Beans (Processing) Acres H a r v ested , 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ........................................................................................................... Figure 1 7 9 S n a p Beans (Processing) Production, 21-Y ear Trend, 1 9 7 0 - 1 9 9 0 ........................................................................................................... Figure 1 8 0 S n a p Beans (Processing) Yield, 21-Year Trend, 1 9 7 0 1 9 9 0 ....................................................................................................................... Figure 181 S n a p Beans (Processing) Price, 21-Year Trend, 1 9 7 0 - 1 9 9 0 Figure 1 8 2 S tr aw b err ie s (Dual Purpose) Value of Production, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ............................................................................................ Figure 1 8 3 S tra w berr ies (Dual Purpose) Acres Har vest ed, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ............................................................................................ Figure 1 8 4 S traw b err ies (Dual Purpose) Production, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ........................................................................................................... Figure 18 5 S tr aw b err ie s (Dual Purpose) Yield, 2 1 -Year Trend, 1 9 7 0 1 9 9 0 ....................................................................................................................... Figure 1 8 6 S tr aw b err ie s (Dual Purpose) Price, 2 1 -Year Trend, 1 9 7 0 1 9 9 0 .............................................................. Figure 1 8 7 S w e e t Corn (Fresh Market) Value of Production, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ............................................................................................ Figure 1 8 8 S w e e t Corn (Fresh Market) Acres Har vest ed, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ............................................................................................ Figure 1 8 9 S w e e t Corn (Fresh Market) Production, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ........................................................................................................... Figure 1 9 0 S w e e t Corn (Fresh Market) Yield, 2 1 -Year Trend, 1 9 7 0 1 9 9 0 ....................................................................................................................... Figure 191 S w e e t Corn (Fresh Market) Price, 2 1 -Year Trend, 1 9 701 9 9 0 ....................................................................................................................... Figure 1 9 2 T o m a t o e s (Fresh Market) Value of Production, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ............................................................................................ Figure 1 9 3 T o m a t o e s (Fresh Market) Acres H arvested, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ........................................................................................................... Figure 1 9 4 T o m a t o e s (Fresh Market) Production, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ........................................................................................................... Figure 19 5 T o m a t o e s (Fresh Market) Yield, 2 1 -Year Trend, 1 9 7 0 1 9 9 0 ....................................................................................................................... Figure 1 9 6 T o m a t o e s (Fresh Market) Price, 2 1 -Year Trend, 1 9 7 0 1 9 9 0 ....................................................................................................................... Figure 1 9 7 T o m a t o e s (Processing) Value of Production, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ............................................................................................ Figure 1 9 8 T o m a t o e s (Processing) Acres Har vest ed, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 ........................................................................................................... 197 197 199 199 200 200 201 202 203 203 204 204 206 206 207 207 208 209 210 210 211 211 213 213 xvii Figure 1 9 9 1990 Figure 2 0 0 Figure 201 T o m a t o e s (Processing) Production, 2 1 -Year Trend, 1970..........................................................................................................................2 1 4 T o m a t o e s (Processing) Yield, 21-Year Trend, 1 9 7 0 - 1 9 9 0 . 2 1 4 T o m a t o e s (Processing) Price, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 . 2 1 5 LIST OF TABLES Table I S tr u ctu r e of I nput- Output T r a n s a c tio n s Table ................................. Table II Trend S u m m a ry for Crops, Com m od it y Rank by A ver ag e Annual % C h a n g e for 2 1 -Years, 1 9 7 0 - 1 9 9 0 ....................................... Table II (Continued), Trend S u m m a r y for Crops, C o m m o d it y Rank by Ave ra ge Annual % C h a n g e for 2 1 -Years, 1 9 7 0 - 1 9 9 0 ...................... Table III Trend S u m m a r y for Livestock & Poultry, C o m m o d it y Rank by A ver ag e Annual % C h a n g e for 21-Years, 1 9 7 0 - 1 9 9 0 ...................... Table III (Continued) Trend S u m m a ry for Livestock & Poultry, Com m odit y Rank by Aver ag e Annual % C h a n g e for 2 1 -Years, 1 9 7 0 - 1 9 9 0 ........................................................................................................... Table IV Trend S u m m a r y for Fruit Crops, Com m odity Rank by A ver ag e Annual % C h a n g e for 21-Years, 1 9 7 0 - 1 9 9 0 ...................... Table IV (Continued) Trend S u m m a ry for Fruit Crops, Com m odity Rank by A ver ag e Annual % C h an g e for 21-Years, 1 9 7 0 - 1 9 9 0 . . Table V Trend S u m m a ry for Veg et ab le Crops, Com m odity Rank by A verage Annual % C h a n g e for 2 1 -Years, 1 9 7 0 - 1 9 9 0 ..... Table V (Continued) Trend S u m m a r y for Veg et ab le Crops, C om m od ity Rank by A ver ag e Annual % C h a n g e for 21-Years, 1 9 7 0 - 1 9 9 0 ........................................................................................................... Table VI Shift-Share Analysis of Livestock & P r o d u c ts C ash Receipts, 1 9 7 0 - 1 9 8 0 ........................................................................................................... Table VII Shift-Share Analysis of Livestock & P r o d u c ts C ash Receipts, 1 9 8 0 - 1 9 9 0 ........................................................................................................... Table VIII Shift-Share Analysis of Livestock & P r o d u c ts Ca sh Receipts, 1 9 7 0 - 1 9 9 0 ...................................................................................... Table IX Shift-Share Analysis of Field Crops C ash Receipts, 1 9 701 9 8 0 ....................................................................................................................... Table IX (Continued) Shift-Share Analysis of Field Crops Ca sh Receipts, 1 9 7 0 - 1 9 8 0 ...................................................................................... Table X Shift-Share Analysis of Field Crops C ash Receipts, 1 9 8 0 1 9 9 0 ....................................................................................................................... Table X (Continued) Shift-Share Analysis of Field Crops C ash Receipts, 1 9 8 0 - 1 9 9 0 ...................................................................................... Table XI Shift-Share Analysis of Field Crops C a s h Receipts, 1 9 701 9 9 0 ....................................................................................................................... Table XI (Continued ) Shift-Share Analysis of Field Crops C ash Receipts, 1 9 7 0 - 1 9 9 0 ...................................................................................... Table XII Shift-Share Analysis of Fruit & Other C a s h Receipts, 1 9 701 9 8 0 ....................................................................................................................... xviii 43 57 58 99 100 133 134 167 16 8 251 252 253 254 255 256 257 258 259 260 xix Table XIII Shift-Share Analysis of Fruit & Other C a s h Receip ts, 1 9 8 0 1 9 9 0 ....................................................................................................................... 261 Table XIV Shift-Share Analysis of Fruit & Other C a s h Receipts, 1 9 7 0 1 9 9 0 ....................................................................................................................... 2 6 2 Table XV Shift-Share Analysis of V e g etab les & Melons C a s h Rec eipts, 1 9 7 0 - 1 9 8 0 ....................................................................................... 2 6 3 Table XV (Continued) Shift-Share Analysis of V e g e ta b le s & Melons C a s h Receipts, 1 9 7 0 - 1 9 8 0 ........................................................................... 2 6 4 Table XVI Shift-Share Analysis of V e g etab le s & Melons C a s h Rec eipts, 1 9 8 0 - 1 9 9 0 ....................................................................................... 2 6 5 Table XVI (Continued) Shift-Share Analysis of V e g e t a b le s & Melons C a s h Receipts, 1 9 8 0 - 1 9 9 0 ........................................................................... 2 6 6 Table XVII Shift-Share Analysis of V e g e ta b l e s & Melons C ash Rec eipts, 1 9 7 0 - 1 9 9 0 ....................................................................................... 2 6 7 Table XVII (Continued) Shift-Share Analysis of V e g e ta b le s & Melons C a s h Receipts, 1 9 7 0 - 1 9 9 0 ........................................................................... 2 6 8 Table XVII 1 9 9 2 Michigan Type I and T ype III Em ploym en t Multipliers for Production Agriculture an d Rest of th e E c o n o m y ...........................281 Table XVIII Analysis of Michigan Employmen t Multiplier Effects for Produ ction Agriculture and Rest of th e E c onom y .................. 2 8 2 Table XIX 1 9 9 2 Michigan T ype I and T ype III O u t p u t Multipliers for Produc tion Agriculture and Rest of t h e E c onom y .................. 2 8 3 Table XX Analysis of Michigan O u t p u t Multiplier Effects for Pr odu ction Agriculture and Rest of th e Ec onomy .................. 2 8 4 Table XXI 1 9 9 2 Michigan T ype I and Typ e III Total Inco m e Multipliers for P r od uction Agriculture and Rest of t h e E c o n o m y ...........................2 8 5 Table XXII Analysis of Michigan Total Inco m e Multiplier Effects for Pro duction Agriculture and Rest of th e Ec on omy ................................. 2 8 6 Table XXIII 1 9 9 2 Supply-Side A c c o u n t for Michigan P r oduc tion Agriculture and A gg r e g a te d Industries ......................................................2 9 7 Table XXIII (Continued) 1 9 9 2 Supply-Side A c c o u n t for Michigan Produc tion Agriculture and A g g r e g a t e d I n d u s t r i e s ................................. 2 9 8 Table XXIV 1 9 9 2 Demand- Side A c c o u n t for Michigan P r od uction Agriculture and A g g r e g a t e d Industries ......................................................2 9 9 Table XXIV (Continued) 1 9 9 2 Demand- Side A c c o u n t for Michigan Pro duction Agriculture and A g g r e g a te d I n d u s t r i e s ................................. 3 0 0 Table XXV 1 9 9 2 Balance of Trad e A c c o u n t for Michigan Production Agriculture an d A g g r e g a te d Industries ......................................................301 Table XXV (Cont.) 1 9 9 2 Balance of Trad e A c c o u n t for Mich. Production Agriculture and A g g r e g a te d Industries ..............................3 0 2 Table XXVI United S t a t e s C om mod ity Ca sh Rec eipts for t h e Years 1 9 6 9 , 1 9 7 0 , an d 1971 .................................................................................... 3 7 0 Table XXVI Continued , United S t a t e s Com m odity C a s h Rec ei pts for th e Years 1 9 6 9 , 1 9 7 0 , and 1971 ............................................................... 371 XX Table XXVII United S t a t e s C om mod ity C ash Receipts for th e Years 1 9 7 9 , 1 9 8 0 , a n d 1981 ............................................................................. Table XXVII Continued, United S t a t e s C om mod ity C a s h Rec eipts for t h e Years 1 9 7 9 , 1 9 8 0 , and 1981 ............................................................... Table XXVIII United S t a t e s Com mod ity C a s h Rec eipts for t h e Years 1 9 8 9 , 1 9 9 0 , a n d 1991 ................................................................................... Table XXVIII Continued, United S t a t e s C om mod ity C a s h Rec eipts for t h e Years 1 9 8 9 , 1 9 9 0 , and 1991 ............................................................... Table XXIX Michigan C om m odity C ash Receipts for t h e Years 1 9 6 9 , 1 9 7 0 , an d 1971 Table XXIX Continued, Michigan Com m odity Ca sh Receipts for the Years 1 9 6 9 , 1 9 7 0 , and 1971 Table XXX Michigan Com m odity C ash Receipts for th e Years 1 9 7 9 , 1 9 8 0 , an d 1981 Table XXX Con tinue d, Michigan C o m m odity C ash Receipts for th e Years 1 9 7 9 , 1 9 8 0 , an d 1981 Table XXXI Michigan C om m o dit y C ash Rec eipts for th e Years 1 9 8 9 , 1 9 9 0 , an d 1991 Table XXXI Continued, Michigan C o m m odity C a s h Rec eipts for t h e Years 1 9 8 9 , 1 9 9 0 , an d 1991 372 373 374 375 376 377 378 379 380 381 I. I N T R O D U C T I O N P u r p o se of th e S tu dy The p u r p o s e of this disser tatio n w a s to a s s e m b l e a c o m p r e h e n s i v e collection of Michigan pr oduction agriculture baseline d a t a and to apply the statistical m e t h o d s of ordinary least s q u a r e s re gression, shift-shar e analysis, and in put-o u tp ut modeling, to d eter m in e th e tre n d s, shifts, an d linkages of th e s e c t o r during th e d e c a d e s of t h e 7 0 ' s an d 8 0 ' s . This r e s e a r c h effort is o n e of th e m o s t e x tens iv e historical re view s of Michigan pr oduction agriculture g e n e r a t e d to d a t e . Th e s tu d y w a s d e s ig n e d t o a s s i s t decis ion m a k e r s in Michigan farm organizations, farm enterpri s es, a g r ib u s in e s s e s , food p ro c e s s in g c o m p a n i e s , go v e r n m e n ta l a g e n c ie s , universities, en viro nme ntal gr oup s, and input suppliers. Evolution of the S tu dy The im pe tus for this disser tation evolved from th e a u t h o r 's participation in t w o str ategic planning p r o c e s s e s c o n cer n in g M ich igan 's food an d agriculture industry; as th e staff e c o n o m i s t for t h e Michigan D e p a r t m e n t of Agriculture "F uture s T e a m 2 0 2 0 " project, and as a r esear ch a s s o c i a t e for t h e Michigan S t a t e University (MSU), Agricultural Experiment S tatio n (AES) "SAPMA "(S tatu s an d Potential of Michigan Agriculture) project. The co nceptu alization of this r e s e a r c h e n d e a v o r w a s greatly influenced by th e re se a r c h t e c h n i q u e s us ed in th e SAPMA project. Although th e SAPMA l 2 project g e n e r a t e d a sizeable a m o u n t of pr oduction d a ta , th e r e w e r e still missing pie ce s. However, since t h e a uthor played an im po rta nt role in th e e x e c u t i o n s of both efforts it s e e m e d meaningful to inves tigat e thoro ug hly bo th of t h e s e efforts as well a s several oth er s, for p u r p o s e s of creating a more c o m p r e h e n s i v e fra m ew ork t h a t could be u s e d for on going planning efforts. Sinc e t h e "Futures Team 2 0 2 0 " an d th e SAPMA project c o n c e p t s contr ib ute d in a significant w a y to this r esear ch effort, t h e special na ture of their contribution d e s e r v e s consideration. F ut ure s T e a m 2 0 2 0 In 1 9 8 9 th e Governor of th e S tate of Michigan an d th e Michigan D e p a r t m e n t of Agriculture organized a t a s k force of appr oximate ly 4 0 a c a d e m ic , co r p o rate, entrepreneurial, and g o v er n m en tal lea der s t o develop a s tr ate g ic plan for Michigan's food and agriculture s y s t e m . 1 For t w o years, th e F u tu r e 's T e a m c o n v e n e d eleven major group m eeti n g s and m a n y s u b c o m m i t t e e mee tings. At th e conclusion of th e deliberations, a final report w a s p r o d u c e d "Reaching 2 0 2 0 : Michigan's Food an d Agriculture Industry in t h e 2 1 s t C en tury." This report analy zed an d r e c o m m e n d e d policy a c t io n s (specifically for th e S t a te of Michigan) in s u c h a r e a s as: increasing international trade, marketing s tr a te g i e s aimed at U.S. c o n s u m e r s , 1 As staff economist it was my responsibility to prepare briefing papers, make presentations, facilitate discussions and advise the Futures Team members about the status of the food and agriculture industry in Michigan the U.S. and abroad, and to help write the final report. 3 developing rural Michigan, as suring environmental quality, achieving ex ce ll ence in e d u cati o n and r es ea rch , and ex p a n d in g food an d agriculture prod uc tion and processing. S t a t u s and Potential of Michigan Agriculture (SAPMA) The SAPMA project w a s funded by th e MSU AES. Th e p u r p o s e w a s to review an d a s s e s s ex per im ent station r esear ch n e e d s an d priorities, identify key t r e n d s and future s cenari os of Michigan agriculture and e v alu ate t h e potential for growth. From m id -1 9 9 0 to late 1 9 9 1 , s o m e 7 0 faculty m e m b e r s an d g r a d u a t e s t u d e n t s prepared special reports t h a t w e r e re viewed by 1 0 0 o th e r faculty me mbe rs. T h e s e individuals w e r e joined by nearly 1 5 0 industry r e p res en tativ es at a tw o - d a y c o n f e r e n c e during M S U 's Agriculture a n d Natural R e s o u r c e s We ek in March 1 9 9 2 . 2 The SAPMA project w a s organized into thre e s ta g e s . T h e first s ta g e , 2 My participation in the project was two fold: first, as a contributing author in phase I, and second, as a member of the project advisory committee. The phase I special reports were as follows: Whims, John F. A Review of Michigan's Past and Forecasted Trends for the Food and Agriculture Industry. Michigan State University, Agricultural Experiment Station, East Lansing, Michigan , Special Report 36, December 1992. Whims, John F.; Connor, Larry J. Michigan Agriculture in the Eighties - A Decade in Review. Michigan State University, Agricultural Experiment Station, East Lansing, Michigan , Special Report 33, November 1992. Whims, John F.; McVeigh, Paul C.; Connor, Larry J. A Comparative Trend Analysis of Funding Sources for Michigan State University's Agricultural Experiment Station and Cooperative Extension Service. Michigan State University, Agricultural Experiment Station, East Lansing, Michigan , Special Report 41, December 1992. 4 p h a s e I, pr o d u c e d app ro ximately 10 special rep or ts t h a t a s s e s s e d M ich ig an's food and agriculture industry from a m acro point of view (analyzing s u c h a s p e c t s a s agricultural inputs, food p r o c e ss in g and marketin g, an d c o m m u n it y r e s o u r c e s and restraints). P h a s e II of th e SAPMA project f o c u s e d on issues an d c o n c e r n s related to specific c om m odities (e.g., p o t a t o e s , poultry, an d dairy). Th e first t w o s t a g e s of SAPMA hav e b e e n c o m p l e t e d . T he third p h a s e of SAPMA builds on th e sp ecial reports g e n e r a t e d in t h e first t w o s t a g e s . P h a s e III w a s d e s ig n e d to be a continual p r o c e s s w h e r e r esear ch allocation and funding priorities ar e d e v e lo p e d by the AES director and his staff. Th e first special repo rt entitled "Michigan Agriculture in t h e Eighties A D e c a d e in R e v ie w , ” w a s c o a u th o r e d with p r o fe s s o r Larry C o n n o r . 3 C o nnor rev iew ed t h e final publication and provided editorial advice. This publication w a s a c o m p r e h e n s i v e time series an d c r o s s sectional a s s e s s m e n t of Michigan production agriculture from 1 9 8 0 to 1 9 8 9 . Th e report ex am in ed s u c h s t a t e d a ta a s farm financial c haracte ris ti cs (balance s h e e t and net inco me s ta t e m e n t ) , t h e tre nd review of cr o p s an d livestock, an d th e identification of s t a t e w id e agricultural activity by c o m m o d ity for e a c h c o u n ty (displayed in graphical d en s it y maps). Th e final AES special report w a s entitled "A Review of Michigan 's P a s t and F o r e c a s te d Employm en t T rend s for t h e Food and Agriculture 3 Currently the Dean of the College of Agriculture, The University of Florida. 5 Industry." Michigan food an d agriculture em p lo y m e n t t r e n d s by industry s e c t o r w e r e analyzed ov er th e last t w e n t y years. Each industry s e c t o r (e.g., agricultural services , m e a t p r o c e s s o r s , an d food stores ) w a s ev a lu a t e d by calculating an nual e m p l o y m e n t g r o w th ra tes an d linear sh ift-sha re ra tes c o m p a r e d to th e U.S. s ecto ral tre n d s . F o r e c a s t e d an n ual e m p l o y m e n t g r o w t h ra tes g e n e r a te d by th e Bureau of Labor Statistics for e a c h U.S. industry s e c to r , w e r e th en applied to e a c h Michigan s e c t o r to provide a pos sible v iew of th e s t a t e ' s food and agriculture e c o n o m y in t h e yea r 2 0 0 0 . It is th e culmination of t h e s e r e se a r c h activities and o th e r intere sts t h a t has led to th e identification of th e need for this rese arch. R es earch Identification an d Re sea rc h A p p r o a c h Res earch Identification Michigan pro du ction agriculture h a s f ac ed m a n y f o r c e s of c h a n g e t h r o u g h o u t t h e d e c a d e s of t h e s e v e n tie s and eighties, s o m e t h a t had never b een e x p e r ie n c e d before. T h e s e cha llen ge s o c curre d in th e form of drought, floods, com pe tition from d o m e s t ic an d foreign m ar ket s, enviro nmental regulations, m a c r o e c o n o m ic fluctuations, tra d e polices, a n d technological a d v a n c e m e n t s , a m o n g o th e r s . Mich igan 's agricultural decis ion m a k e r s and influencers (academ ic, private and go ver nm en ta l, etc.) w e r e required to break old par ad igm s and deve lo p n e w models for t h e future. Several t a s k fo rces (e.g., "F utures T e a m ," "Enriching Michigan's Future," "Project 8 0 and 5 , ” an d "SAPMA") w e r e c o n v e n e d to g e n e r a t e s tr a te g ie s and blueprints for t h e food and agriculture industry. M ichigan 's e c o n o m ic b a s e is typically a s s o c i a t e d with industries t h a t ar e heavily invested in fixed capital (durable a s s e t s with relatively long useful lives). A prime ex a m p le is t h e a u tom o ti ve industry and its m a n y linked suppliers. T h e s e firms generally require t h e fixed capital (the inputs of land, buildings and machinery) to pr o d u c e durable g o o d s and p r o d u c ts . A durable g o o d is a piece of e q u i p m e n t for either c o n s u m e r s or p r o ducers , w h ic h in normal u s e will last more t h a n th re e years. Historically, th e general e c o n o m y of Michigan h a s b een significantly influenced by t h e cyclical f luctua tio ns of t h e du rable g o o d s industries like furniture m a n u f a c t u r e s (e.g., Steel C a s e and Her man Miller) app lian ce m a n u f a c t u r e Whirlpool, an d th e big t h r e e a u to c o m p a n i e s of Ford, Chrysler, and General Motors. Durable g o o d s ar e usually large ticket item s and are interest rate sensitive. Often in a climate of falling intere st r a te s c o n s u m e r s and p r o d u c e rs will e x p a n d their p u r c h a s e s of durable g o o d s . Th e falling in tere st ra tes r e d u c e s c o s t of doing b u s in e s s . Conversely, in per iods of rising interest rates c o n s u m e r s an d p r o d u c e r s usually c o n t r a c t their p u r c h a s e s of durable g o o d s . It has b een said t h a t w h e n th e r est of t h e c o u n tr y c a t c h e s a cold (an e c o n o m i c re c e ss io n or contrac tion ) Michigan c a t c h e s pneu m onia. Th e saying highlights M ich igan 's s u b stan tial e x p o s u r e to th e durable g o o d s industries and th e g r e a te r variation in t h e level of e c o n o m ic activity (e.g., u n em p lo y m en t) c o m p a r e d with th e 7 r e s t of th e co untry. A major buffer to t h e s t a t e ' s e c o n o m ic gyrations h a s b e e n th e food an d agriculture in dust ry.4 T he food and agriculture industry provides a stabilizing ef fe ct to th e e c o n o m y b e c a u s e it is closely linked with the product io n of no nd urab le g o o d s (so m et im es called s o ft go ods). Nondurable g o o d s are t h o s e c o n s u m e r or p r o ducer items t h a t last for only a s h o r t while a n d are typically p u r c h a s e d a s n e e d e d , like food for h u m a n c o n s u m p tio n . C o n s u m e r s m u s t m a k e food p u r c h a s e s on a c o n s is t e n t basis for either h o m e or a w a y from h o m e c o n s u m p t i o n b e c a u s e of its perishable natur e. A g g r e g a t e food c o n s u m p t i o n remain s fairly c o n s t a n t over time e v e n during per iods of ec o n o m ic co n tr acti o n . In a rece ss ion c o n s u m e r s c o n tin u e to p u r c h a s e food but a s in co m es decline, s ubstitution e f f e c ts occ ur. The s ubst itution ef fe c t m e a n s t h a t s o m e c o n s u m e r s would shift their p u r c h a s e s of e x p e n s iv e items (such a s steak) to more econ omical items (such as ground chuck ). Ultimately, a reg io n 's ex p e n d itu r e s on food positively co r relates with its population b a s e an d income level.5 4 In this case the food and agriculture industry is a comprehensive definition which includes; the input sector, production agriculture, wholesale operations, retail operations, manufacturing, food processing, forestry, agricultural services, and agribusiness. 5 In 1992 Michigan's resident population was approximately 9.4 million placing the state 8th in the country in size. Also in 1 992, Michigan ranked 20th in the country for disposable personal income per capita in current dollars at $17,154. 8 R es e a r c h by Pr of es so r J o h n Ferris6 and th e a u th o r h a s bee n c o n d u c t e d t o discern t h e ec o n o m ic impact of th e food an d agriculture industry on th e s t a t e ' s e c o n o m y . It w a s e s tim a te d t h a t in 1 9 9 2 Michigan's food a n d agriculture industry employed ap proximately 6 0 0 , 0 0 0 w o r k e rs (over 1 5 % of th e total w ork force) and g e n e r a te d gross s ale s of ap pr oximately 3 0 to 3 5 billion dollars. The food and agriculture industry is clearly positioned a s o n e of th e s t a t e ' s m o s t importa nt industries. A vital link in th e food and agriculture industry chain is production agriculture. Michigan production agriculture is o n e of th e m o s t diver se in the co u n t r y - ranging from the W e s te r n co unties w h e r e th e moder at in g w e a t h e r influenc es of Lake Michigan and s a n d y loam soils are ideal for growing fruit, to t h e S a g i n a w Bay and T hu m b region with it's high organic soil c o n t e n t are ideal for growing field c r o p s like s o y b e a n s an d s u g a r bee ts . In t e r m s of pro du ction by com m odit y, Michigan ranked te n th or higher in th e c o u n tr y in 1 9 9 2 for 5 6 com m od ities, with nine of t h o s e com m odities ranked first.7 Very f e w s t a t e s , with th e excepti on of California, p r o d u c e a s m a n y diverse com m odit ie s. In 1 9 9 0 c a s h receipts totaling over 3.1 billion dollars w a s 6 Agricultural economics professor, Michigan State University, and doctoral committee member. 7 The commodities ranked first were; Cranberry Beans, Black Turtle Beans, Tart Cherries, Navy Beans, Blueberries, Cucumbers for Pickles, Potted Geraniums, Potted Easter Lilies, and Flowering Hanging Baskets. 9 g e n e r a t e d from th e sale s of c r o p s , 8 and livestock p r o d u c ts placing it 2 2 n d in t h e nation. Production agriculture also em ploye d approximately 8 5 , 0 0 0 w o r k e r s in 1990. Since production agriculture is critical to th e S ta te of Michigan' s e c o n o m y , decision m ak er s in g o v e r n m e n t, p r o fe s s o r s in universities, en t r e p r e n e u r s , a n d c o r p o r a te leaders are involved in n u m e r o u s projects and c o m m i t t e e s to a s s e s s its role an d potential. Typically, th e publications and r ep o rts hav e a s k e d th e following ques tio ns ; w h e r e h a v e w e be en, w h a t c h a n g e s ar e likely to o c c u r in th e future, an d h o w should Michigan try to influence and position production agriculture going into th e n e w millennium? A c o m p r e h e n s i v e and s y s t e m a t i c review of m any key rep orts an d their r e c o m m e n d a t i o n s h a s led to the identification of seve ral r e s e a r c h oppor tunities t h a t would enrich future p rodu ction agriculture projects. T h e s e oppor tunities an d o b s e rv a tio n s for r e s e a r c h are a s follows: 1. Evaluations a b o u t th e linkages and ec o n o m ic contribution (e.g., em p lo y m e n t impacts) of prod uction agriculture to th e s t a t e ' s e c o n o m y w e r e often limited b e c a u s e of s p a r s e d a t a and th e nee d for co mplex co m puta ti onal r equ irem en ts . N ow m a n y of t h e s e q u e s ti o n s c a n be a d d r e s s e d in more definitive an d interactive w a y s with t h e aid of s u c h 8 Crops included; Field crops, vegetables, fruit, and greenhouse and nursery ornamentals. 10 powerful person al c o m p u t e r s o f t w a r e a s Micro IMPLAN (an inputo u t p u t model). 2. Often th e d ata (concerning yields, prices, a c r e s h a r v e s t e d , etc.) used t o analyze pro ductio n agriculture f o c u s e d only on "major" c o m m o d iti e s s u c h a s corn, hogs , and s o y b e a n s . Many so-called "minor" com m oditi es, especially fruits and v e g e t a b l e s , 9 w e r e not included. With th e aid of c o m p u t e r s , d a ta retrieval an d a n a ly s e s hav e b e c o m e more r obus t. R e s e a r c h e r s 10 h av e m o v e d m a s s iv e a m o u n t s of hard c o p y d a t a 11 to t h e personal c o m p u t e r level. T h e s e d a t a b a s e s ar e n o w being s h a r e d by t h e r esear ch er s, and ar e being e x p a n d e d to include m a n y of th e minor comm od ities. 3. Not only hav e t h e d a t a b a s e s and s p r e a d s h e e t s b e e n e x p a n d e d to include m ore co m m odities, but time series d a t a is also more ex h a u s tiv e . T w o o fte n as ked q u e s tio n s are " h o w did w e get here" an d " w h e r e h av e w e b e e n ? " Many of t h e s e q u e s tio n s ar e n o w being a d d r e s s e d with gr e a te r s p e e d and detail b e c a u s e of t h e e x t e n s iv e 9 Some of these commodities may not be as significant in terms of their proportion of total state cash receipts, but they are quite significant in their national ranking. 10 Especially in the College of Agriculture and Natural Resources. 11 For example, the Michigan Agriculture Statistics Annual Report. 11 collection d a t a b a s e s and s p r e a d s h e e t s . R es earch can be c o n d u c t e d quickly and with minimal c o s t using s u c h statistical m e t h o d s as shifts h a r e analysis to look at th e c hanging s tr u c tu r e of Michigan's p roduction agriculture e c o n o m y . 4. N e w personal c o m p u t e r s o f t w a r e provides ea s ier a c c e s s to co m p le x statistical an d graphical te c h n i q u e s . Many s o p h is ticated a n a l y s e s an d p r e s e n t a t i o n s c a n be us ed th a t might h av e b een over lo ok ed b e c a u s e of limited time, or b u d g e t c o n s tr a i n ts in p a s t research endeavors. Decision m ak er s n o w h av e bet ter a c c e s s to information b a s e s from which to d r a w m ore a c c u r a t e inferences a b o u t th e s t a t u s an d potential of Michigan pro duc tion agriculture. Th e use of personal c o m p u t e r s h a s s t r e n g t h e n e d this analytical p r o c e ss . This r e s e a r c h e n d e a v o r is an a t t e m p t to utilize m any of th e c o m p u t e r ' s powerful capabilities to facilitate an e x p a n d e d an d c o m p r e h e n s i v e review of th e tre nds, shifts, and linkages in Michigan pro du ction agriculture. Using t h e pr o p o se d analytical te c h n i q u e s t h e r e s e a r c h results should s e rv e a s a useful found ation for future decision making activities. 12 Res e a r c h A p p r o a c h In this s tu d y an analysis of baseline d a t a is per fo rmed during th e d e c a d e s of t h e 7 0 ' s an d 8 0 ' s . The r e se a r c h a d d r e s s e s s u c h prod uction agricu ltu re12 c a t e g o r i e s a s farm c a s h receip ts, prices, yields an d quan tity p r o d u c e d . The d a t a is analyz ed using th e statistical m e t h o d s of time series graphing, c r o ss se ct io nal mapping, ordinary least s q u a r e s regression, shift-share analysis, and in p u t-o u tp u t analysis. Each of t h e s e analytical m e t h o d s has b e e n specifically s e le c t e d to p r o d u c e a c o m p r e h e n s i v e body of k n o w le d g e co n c e r n in g Michigan pro duct io n agriculture tre n d s, shifts and linkages. The r e se a r c h a p p r o a c h and th e m e t h o d s us ed in th e s t u d y are des cr ibed a s follows: 1. Th e r e se a r c h includes a c o m p r e h e n s i v e graphical p r e s e n ta ti o n of time s er ie s d a t a 13 for m a n y of th e s t a t e ' s c o m m o d itie s an d their pro ductio n ch a r a c t e r is ti c s from 1 9 7 0 to 1 9 9 0 . 2. Ordinary least s q u a r e s re gres sion is used to a d d r e s s t h e long-term se c u la r t r e n d s of th e different production related c a t e g o r ie s. Estimated tre nd fu nc tions are fitted to th e actual time series d a t a and are displayed in g r a p h s to highlight th e direction of c h a n g e for e a c h c a te g o r y . 12Note: select data is also included from other states and the U.S. for comparative purposes. 13 Such as; price, yield, output, and number of head animal livestock. 13 3. Ordinary least s q u a r e s regres sion is also used to estim ate annual ra t e s of c h a n g e coefficients for e a c h of th e c ateg o r ies. The es ti m a te d a v e r a g e an nual rate of c h a n g e yields th e m ag n itu d e of c h a n g e for e a c h c a t e g o r y ' s trend. 4. Shift-share analysis is us ed to identify structural c h a n g e s in th e pro du ction agriculture e c o n o m y ' f r o m 1 9 7 0 to 1 9 9 0 . Michigan c o m m o d i ty c a s h rece ip ts and United S t a t e s c o m m o d it y cash receipts ar e t h e basis of th e c o m par ative analysis. The d a ta is cross sectional, tak en from th e years of 1 9 7 0 , 1 9 8 0 , and 1 9 9 0 . y ear c e n t e r e d av e r a g e , (e.g., ( 1 9 6 9 + 1 9 7 0 + 1 9 7 0 1 / 3 ] A thre e is used for e a c h of th e c r o s s sectional time periods. The th re e -y e a r av er ag e r e d u c e s t h e var iance of agricultural c a s h receipts usually a s so ciated with shifts in w e a t h e r p a t te r n s (e.g., floods an d drought). This a p p r o a c h should c a p tu r e th e appro priate long term tr e n d s for analysis. 5. Th e m e t h o d of input-output (1-0) analysis is us ed to ascertain t h e linkages (e.g., em p lo y m e n t multipliers and o u t p u t multipliers) of Michigan production agriculture. The agricultural multipliers a r e t h e n c o m p a r e d to th e o th e r major s e c t o r s (e.g., m anufacturi ng and constr uct ion) s t a t e ' s e c o n o m y . Also, g e n e r a te d in th e 1-0 analysis are t ra d e flow d a t a and c o n s u m p t io n p atte r ns of Michigan agricultural 14 com m odit ie s. Note t o th e reader: th e inpu t-o utpu t analysis g e n e r a t e d in this s tu d y u s e s a s o f t w a r e p a c k a g e called Micro IMPLAN. Micro IMPLAN is an analytical in strum ent specifically d ev elo p ed for the policy/decision maker, ("I" s t a n d s for input, "M" s t a n d s for ou tp u t, a n d PLAN d e n o t e s planning). This s tu d y is t h e first k n o w n application of Micro IMPLAN to analyze Michigan' s pro du ction agriculture s ecto r. T he collection of ap p r o p riate baseline d a t a and t h e application of suitable statistical m e t h o d s should u ncover meaningful tr e n d s, shifts and linkages co n c e r n in g Michigan's pro ductio n e c o n o m y during th e d e c a d e s of t h e 7 0 ' an d 8 0 ' s . The s t u d y ' s results will benefit decision m a k e r s in Michigan farm organizations, farm enterpri s es, ag r ib u s i n e s s e s , food p ro c e s s i n g c o m p a n ie s , gov e r n m e n ta l a gencies , universities, en viro nm ental g r oups, an d input suppliers. 15 Organization of the Study Th e diss erta tion is laid o u t in the following format; I. INTRODUCTION II. REVIEW OF THE LITERATURE III. METHODS IV. MICHIGAN PRODUCTION AGRICULTURE TREND ANALYSIS V. THE APPLICATION OF SHIFT-SHARE ANALYSIS TO FARM CASH RECEIPTS, TO ASSESS THE SHIFTS IN MICHIGAN'S COMPETITIVE POSITION IN PRODUCTION AGRICULTURE RELATIVE TO THE UNITED STATES VI. THE APPLICATION OF INPUT-OUTPUT MODELING TO ASSESS THE LINKAGES AND IMPACT OF PRODUCTION AGRICULTURE ON THE STATE OF MICHIGAN'S ECONOMY VII. SYNTHESIS AND IMPLICATIONS II. R E V I E W O F T H E LIT ER AT U RE A R e view o f R ecent Michigan S ta te University and D epartm ent of Agricultural E co n o m ics, Production Agriculture A s s e s s m e n t Publications T h e analysis of Michigan agricultural baseline d ata h a s b een a critical t a s k for n u m e r o u s faculty m e m b e r s in th e D e p a r t m e n t of Agricultural E c o n o m ics a t Michigan S t a t e University t h ro u g h th e yea rs. Many d o c u m e n t s , reports, an d publications hav e b een p r o d uced for th e C o o perative Extension Services, Agricultural Experiment Station, and the D e p a r t m e n t of Agricultural Economics conc er ning th e s t a t u s of pro du ction agriculture in th e s ta t e . T w o Pro fessors, Karl T. Wright an d J o h n N. Ferris, h a v e played critical roles in th e gen er ation of m a n y of t h e s e publications. The publications 14 reviewed in this c h a p t e r include n u m e r o u s w o r k s related to t h e descriptive analysis of Michigan production agriculture baseline data during t h e 5 0 ' s , 6 0 ' s , 7 0 ' s , and early 8 0 ' s . T h e Ch an ging S c e n e in Michigan Agriculture: This w a s t h e title of a Co op er ative Extension bulletin t h a t w a s a u t h o r e d by Wright in O cto ber 1 9 7 8 . The bulletin relies heavily on graphical p r e s e n t a t i o n s an d tables to c o n v e y to th e re ad er m any of t h e long-term Michigan pro du ction agricultural tre nds. Th e g r a p h s used in t h e publication 14 Note: the publications reviewed in this section are identified in the bibliographic section at the end of the thesis. 16 17 are bar, line, area , and m a p s . 15 Th e bulletin c o n s i s t s of t w o primary s e c tio n s (excluding th e introduction). T he first s ectio n an al yze s long-term s t a t e t r e n d s 16 for four major ca te g o r i e s : c r o p s , livestock, e c o n o m ic f acto rs and general. Time seri es d a t a s tar ting in 1 9 5 0 an d ending in t h e late 1 9 7 0 ' s is u s e d t o de scribe t h e long-term tr e n d s . For s o m e Michigan c o m m o d itie s their long-term trend is c o m p a r e d a g a i n s t t h e national c o m m o d i ty trend. T w o primary d ata s o u r c e s are u s e d in this se ctio n, th e first is th e Michigan Statistical Service a n d t h e s e c o n d is th e United S t a t e s D e p a r tm e n t of Agriculture: Economic R e s e a r c h Service. T he s e c o n d s e c tio n looks at th e s t a t e ' s nine cr op reporting d istr ic ts 17 an d c h a n g e s in c o u n t y specific d ata. This s ectio n u s e s c r o s s sectiona l d ata for t h e y e a r s of 1 9 6 4 , 1 9 6 9 , 1 9 7 4 , and 1 9 7 7 . M ap s are us ed to s h o w th e c o n c e n t r a t i o n of different t y p e s of farming activity in th e c o u n tie s an d tables a c c o m p a n y th e m a p s to s h o w t h e p e r c e n t c h a n g e s in th e crop reporting districts. T w o d a t a s o u r c e s ar e used in this s ection. Th e first is t h e 15 Note: the generation of these figures and graphs occurred before the proliferation of powerful micro computer software packages. A graduate student (Daniel A. Dueweke) in the department of geography assisted Dr. Wright by producing the figures and graphs as part of his graduate program. 16 Some of the trends covered are livestock numbers, field crops acres harvested and yields, farm real es tate values and cash from farm marketings. 17 The nine crop reporting districts in the state are: 1. Upper Peninsula, 2. Northwest, 3. Northeast, 4. West Central, 5. Central, 6. East Central, 7. Southwest, 8. Southern, 9. Southeast. 18 Michigan Statistical Reporting Service an d their Crop Reporting Board d ata a n d their d a t a es tim ati o n s an d th e s e c o n d s o u rc e are th e United S ta te s D e p a r t m e n t of C o m m e r c e a n d th e C e n s u s of Agriculture for Michigan. Michigan Agriculture - Going Into th e Eighties: This publication w a s jointly au t h o r e d by Wright and Ferris for the C o o perative Extension Service in March 1 9 8 1 . The publication is similar to th e publication a b o v e , th e difference ho w ev er , is th e analysis of long-term t r e n d s is not as ex tensiv e . "Going Into th e Eights," thor oughly ex am ines t h e linkages of Michigan pro ductio n agriculture with th e s t a t e ' s e c o n o m y and e v a l u a t e s var ious c o m m odit ie s and their potential ec o n o m ic impact. As with "The C ha ng in g S c e n e in Michigan Agriculture," "Going into th e Eighties" m a k e s e x te n s iv e use of figures an d tables to de scri be Mich igan 's production agricultural e c o n o m y . The publication begins by giving a brief o v ervie w of th e many contrib utions t h a t production agriculture m ak es to th e s t a t e ' s e c o n o m y . The contribution s ectio n flows into a general analysis of th e "c ur rent" d ata for t h e 1 9 7 8 C e n s u s of Michigan Agriculture. Topics s u c h as th e p e r c e n ta g e b r e a k d o w n of th e ty p e of farm e n te rpri s es (e.g., family or partnership) and th e p e r c e n t of fa rm s by th e sale s per farm are d i s c u s s e d . T he n e x t section p r e s e n t s an analysis of th e long-run t re n d s for livestock production, crop p r oduc tion, pr oduct io n efficiency, financial factors, and n u m ber and 19 char a c te r is ti c s of farms. Th e trend review c o v e r s the time period from 1 9 6 0 t o 1 9 8 0 . Th e previous s e c t io n s form the fo und at io n for looking at the potential g r o w t h for var io us Michigan co m m odit ie s. To a d d r e s s t h e issue of potential g r o w t h , th e a u t h o r s as k an d a n s w e r t h e following six q u e s tio n s : 1) W h a t are th e p r o s p e c t s for d o m e s tic an d e x p o r t d e m a n d s for U.S. farm p r o d u c t s ? 2) W h a t are th e c o m p a r a t iv e a d v a n t a g e s and d i s a d v a n t a g e s for Michigan agriculture c o m p a r e d with o th e r produ cing ar e a s? 3) H ow will our c o m p a r a tiv e a d v a n t a g e (d is a d v a n ta g e c h a n g e in the future? 4) W h a t c h a n g e s will t a k e place in th e infrastructur e for agriculture? 5) W h a t is M ic higan's physical potential to e x p a n d pro duct io n? 6) H o w m u c h c a n be acc o m p l ish e d by leader ship an d or ganized efforts within t h e s t a t e to e n h a n c e our production capabilities? All of th e key tre n d s , s t a t u s , an d p r o s p e c t s for Michigan agriculture are th en highlighted in a s u m m a r y s e c tio n with brief bullet s t a t e m e n t s . A D e c a d e of C h a n g e s in Michigan Agriculture: "A D e c a d e of C h a n g e s in Michigan Agriculture" w a s a u t h o r e d by Wright in r e s p o n s e to th e 1981 G o v e r n o r ' s 18 C o n f e r e n c e on Agriculture. 18 William G. Milliken. 20 Th e publication w a s d e v e l o p e d 19 to s e rv e a s a "d ata book" to a s s is t th e G o v e r n o r ' s t a s k force m e m b e r s as t h e y m e t for th e nex t f e w ye ars. The publication re view ed Michigan pro du ction agriculture during th e d e c a d e of th e 7 0 ' s . T w o primary s o u r c e s of d a t a are utilized (1) th e Michigan C e n s u s of Agriculture Repor ts from 1 9 6 9 , 1 9 7 4 , 1 9 7 8 for s e le ct c o u n t y a n d district d a t a an d, (2) annual c o u n t y d a t a an d district from th e Michigan Agricultural Reporting Service. Th e p r e s e n ta tio n of d a ta in this publication is exclusively ta b u l a r , 20 with t e x t t h a t highlights th e analysis of th e various d a t a series. T he report is laid o u t into five s e c tio n s . The first s ectio n is an in tr od uctor y ov e r v ie w of t h e report. The s e c o n d sec tio n is a general s u m m a t i o n of th e highlights for s ta t e d a ta totals for s u c h c a t e g o r ie s as n u m b e r of farms, p e r c e n t a g e by ty pe of organization, and s ale s per farm. Th e third se ct io n g o e s to th e next level of d a t a di sa ggregation by summar izin g th e highlights of th e key tre n d s by s t a t e district. Th e fourth s e c tio n is a con tinua tion of s ectio n th re e regarding district d a ta , h o w e v e r , more e x t e n s iv e detail is provided c o n cerning th e different c a te g o r ie s in e a c h district. Th e final se ction is a compilation of C e n s u s d a t a displayed in 12 t a b le s describing th e c h a n g e s an d c o n c e n t r a ti o n of key agricultural activities a t th e c o u n t y level. 19 Per the suggestion of the screening committee members. Note: the publication was released via the Cooperative Extension Service at Michigan State University. 20 There were no figures as in the other publications. 21 Compar ing Mich ig an 's Agriculture with t h a t of Nearby S t a t e s . 1 9 6 0 - 1 9 8 2 : Of t h e publications d i s c u s s e d in t h e rev iew of th e literature, this is th e only o n e t h a t c o m p a r e s Michigan production agricultural t r e n d s v e r s e s other s t a t e s an d their production agricultural tre n d s. Wright a u th o r e d this publication in 1 9 8 4 a s a C oop er at ive Extension Service bulletin, compar ing d a t a for Michigan v e r s e s th e five s t a t e s of Minnesota, Wisc onsin, Illinois, Indiana, an d Ohio. T he publication is s e g m e n t e d into t w o major s e c t io n s plus a brief s u m m a r y an d a bibliographic appen dix. The first s ectio n an alyzes time series d a t a from 1 9 6 0 to 1 9 8 0 for all of th e s t a t e s (six in total). Section o n e includes figures t h a t d e s c rib e linear t r e n d s for the h e a d i n g s of crop pr oduction, livestock production, farm income an d land in farms. Each of t h e s e h e a d i n g s is divided into detail a b o u t specific c o m m odities and e c o n o m ic classifications. For ex am ple, on p ag e 8, is th e c a t e g o r y of h a r v e s te d a c r e a g e of principal cr o p s t h a t falls und er t h e head ing of cr op pr oduction. This c a te g o r y is a c c o m p a n i e d by figure n u m b e r four entitled, " H arvested A c r e a g e of Principal Crops: Michigan an d Five Nearby S t a t e s , by 5- year A v e r a g e s, 1 9 6 0 - 8 2 , ” an d te x t t h a t re views th e t r e n d s an d p e r c e n t c h a n g e s of all six s t a t e s . Th e s e c o n d sec tio n an al yze s th e c h a n g e s in farm ente rpri s e size distribution for th e periods of 1 9 6 8 and 1 9 7 8 . 21 Farm d ata 21 Note: most of the data used in this section comes from the Census of Agriculture (state reports) which were conducted in the years of 1 969 and 1978. 22 for e a c h s t a t e are s e g m e n t e d into size classifications b a s e d on a c r e a g e , n u m b e r of he ad, or c a s h receipts. N u m e r o u s ta b le s are e m ployed to c o m p a r e and c o n t r a s t th e d a t a for th e h e a d in g s of c r o p s, livestock an d farm characte ris ti cs. The ta bles include n u m b e r s of farms, proportions, p e r c e n t c h a n g e s an d five s t a t e a v e r a g e for the c o m m o d i ty an d farm ch aracteris ti cs. M ost of th e d ata u s e d in t h e publication c o m e s either from t h e C e n s u s of Agriculture or s t a t e reporting se rv ic e s s u c h a s M ic higan's Agricultural Statistic Service. A Look at M ichig an's Chan ging Agriculture 1 9 7 4 - 1 9 8 2 : This Coo perative Extension bulletin w a s published in 1 9 8 5 in r e s p o n s e to t h e release of th e C e n s u s of Agriculture for 1 9 8 2 . 22 Wright analyzed d a t a for th e c e n s u s per iods of 1 9 7 4 , 1 9 7 8 , an d 1 9 8 2 . T h e publication also u s e s o th e r d ata provided by th e Michigan Statistical Service, but not as ex tens ively a s th e c e n s u s dat a. Th e publication follows a similar patt ern to t h e o th e r "Wright" reports. T h e first s ection is highlight and s u m m a r y 23 of t h e c h a n g e s in Michigan Agriculture at t h e s t a t e level from 1 9 7 4 - 1 9 8 2 , c o m p l e t e with bullet s t a t e m e n t s , tables, an d figures. The s e c o n d s ection re view s th e c h a n g e s in 22 Note: there is usually a delay of three years from the time the Census is taken and when it is released. 23 This could be considered to be an executive summary of the publication. 23 p roduction agriculture from district level24 p er sp ecti v e. T h e district analysis f o c u s e s on th e c h a n g e s in c r o p a c r e a g e , livestock n u m b e r s, and a general (e.g., total c a s h sales) ca te g o r y . The third se ctio n , an d largest s ectio n , u s e s 3 6 different m a p s of Michigan with c o u n t y bo u n d ar ie s coupled with c o u n t y d a t a to display c h a n g e s in pro duct io n agriculture from 1 9 7 4 to 1 9 8 2 . Each m a p h a s t e x t to highlight t h e findings of th e analysis an d s u m m a r y ta b le s to point o u t leading, lagging, an d to p c o u n ty activity. The c o u n t y review analysis looks at m a n y of t h e s a m e c a te g o r ie s a s in t h e s e c o n d s e c t i o n ' s district level of analysis (e.g., livestock num ber s) . S e lected C h a r ts on Tren ds in Agriculture in Michigan and S h a r e of U.S. Total: This is a report p r o d u c e d by a u th o r Ferris, which is review ed in an un published format. Th e report is a collection of t w e n t y figures t h a t display time-series d a t a for different Michigan c o m m o d i t i e s . 25 All of the c o m m o d it ie s h av e var ious d a t a series ranging from 1 9 6 0 to 1 9 8 8 . Each figure is a line graph of t w o variables. Th e first variable is t h e Michigan c o m m o d ity for ex am ple, h ead of dairy c o w s an d the s e c o n d variable is th e Michigan proportion (or sh are) of total U.S. dairy c o w s . Th e line g r a p h s s h o w t h e t r e n d s for e a c h Michigan c o m m o d i ty an d their relative c h a n g e in 24 Note: see the review of "The Changing Scene in Michigan Agriculture" above for an explanation of Michigan crop reporting districts. 25 Note: the paper reviews trends for such categories as acres harvested, livestock numbers, and cash receipts. 24 position to t h e re sp ective U.S. co m m odit y. This report provided an import an t fou ndation for using th e m e th o d of shift-sh are analysis in this diss er tatio n, to investigate c o m m o d ity tr e n d s b e t w e e n Michigan and the United S t a t e s . Michigan Agriculture in th e Eighties: A D e c a d e in R ev iew :26 In 1 9 9 2 I w r o t e this publication for th e Agricultural Experiment Station (SAPMA) project. The publication w a s an analysis of Michigan production agriculture during th e d e c a d e of th e 8 0 ' s . Its p u r p o s e w a s to s erv e a s a " data book " t o as s is t the var ious a u t h o r ' s an d participan ts in th e SAPMA project, m u c h in th e s a m e m a n n e r a s W right's publication "A D ecad e of C h a n g e s in Michigan Agriculture" did for th e 7 0 ' s The s tr u c t u r e and format of th e publication h av e m a n y similarities to W right's publications. The first s ection c o v e r s key s t a t e tre n d s related to farm ch a r a c te r is ti c s, s u c h as farm n u m b e r s and a c r e a g e in farms. Each tre nd is displayed in a figure, either line g r a p h s or bar g r a p h s. The figures are a c c o m p a n i e d with t e x t and d ata t h a t highlight th e highs, lows, a v e r a g e s , and s ta n d a r d deviation for e a c h c a t e g o r y . Th e s e c o n d se ct io n is an ex te n s iv e rev iew of th e livestock, field crops, fruit cr op s, v egeta ble, an d nu rsery a n d g r e e n h o u s e crops. The t r e n d s of over 3 8 c o m m o d ities plus th e g r e e n h o u s e an d n ursery p r o d u c ts ar e 26 Note: this publication w as produced for the Michigan State University Agricultural Experiment Station project "Status and Potential of Michigan Agriculture" (SAPMA). For a detailed explanation of the project see the section in Chapter I of this dissertation entitled "Evolution of the Study." 25 all analy zed by de nsit y m a p s , line trend figures, bar c h ar ts , and tables. Text is also inte gra te d with th e figures highlighting th e c h a n g e s in the 8 0 ' s . The third s e c tio n re views th e e c o n o m ic a s p e c t s of Michigan pro du ction agriculture. The ec o n o m ic review has four par ts of tre nd analysis for s t a t e totals of: (1) farm h o u s eh o ld income, (2) b al an ce s h e e t , (3) c a s h receipts, an d (4) em p lo y m e n t. As with th e o th e r s e c tio n s , figures an d t e x t are used to identify an d d e s cri be the different t re n d s. Th e last s ectio n is a d a ta ap p e n d ix t h a t re views c h a n g e s in c o u n ty d a ta , an d lists d a t a s e t s for c a s h r ece ipts, farm hou seh old inco m es , and farm b al an ce s h e e t s . The d a ta us ed in th e publication c o m e s from several s o u r c e s . The m o s t critical d a t a w a s th e time-ser ies d a t a t h a t th e Michigan Agricultural Statistical Service publishes annually, this provided th e basis for all line trend figures and th e c o u n t y d a t a ap p en dix tables. The s e c o n d key s o u r c e of d a t a w a s th e C e n s u s of Agriculture for th e years of 1 9 7 2 , 1 9 8 2 , an d 1 9 8 7 . Oth er import an t s o u r c e s of information us ed, c a m e from th e U.S.D.A. Economic R es e a r c h Service and th e Bureau of Economic Analysis both in W a s h in g to n , D.C. 26 S u m m a ry As men ti on ed in c h a p t e r I th e p u r p o s e of this disser tation is to further de v e lo p t h e "base line" publications t h a t w e r e reviewed a b o v e . This disser ta tion e x t e n d s t h e s e publications in n u m e r o u s w a y s while maintaining a "Wright ty p e " style an d format. A n u m b e r of th e unique a s p e c t s of t h e dis ser ta ti on are identified a s follows: This is t h e first publication to extensively rev iew th e d e c a d e s of th e 7 0 ' s and 8 0 ' s for Michigan pr oduction agriculture.27 Secondly, t h e dissertation t a k e s a d v a n t a g e of powerful perso nal c o m p u t e r (PC) applications. T h e s e PC ap p li cations28 h av e b e e n used to g e n e r a t e all figures, tables, statistical re gre ssi ons, s p r e a d s h e e t s , inputo u t p u t analysis an d w ord p r o c e ss in g a s p e c t s of th e diss er tation. Thirdly, several analytical m e t h o d s h av e nev er been applied to Michigan production agriculture d a ta before. This is the first k n o w n r e s e a r c h application of th e shift-sh are m e th o d of analysis to d e c o m p o s e th e co m peti ti v e shifts and tr e n d s in Michigan production agriculture b a s e d on c o m m o d i ty c a s h receipts. This diss er ta ti on is also t h e first to apply th e input-ou tput model (Micro-IMPLAN) to ex a m in e t h e e c o n o m ic s tr u c t u r e and linkages of pr oduct io n agriculture with Mich igan 's general e c o n o m y . T h e s e m e t h o d s an d o th e r s used in t h e disser ta tion are all d es crib ed in g r eater detail in th e following " M e th o d s " c h a p t e r III. 27 Note: the dissertation relies heavily on the publication the researcher authored entitled "Michigan Agriculture in the Eighties: A Decade in Review." 28 Note: such applications used were Borland's Quattro Pro for Windows and WordPerfect for Windows. III. METHODS Time Series Trend Analysis T h e time seri es m e t h o d of analysis w a s s e le c te d b e c a u s e of t h e ability to disco v e r an d identify th e direction an d p a tte r n s of key bas eline d a t a for various M ichiga n' s pr oduct io n agricultural c o m m o d itie s over time. Time se rie s an aly sis w h e n coupled with a graphical display is a powerful tool for uncover ing specific t r e n d s an d telling a story in a "picture is w o r th a t h o u s a n d w o r d s , " format. This time se rie s analytical a p p r o a c h h a s b een greatly facilitated by th e c o n tin u ed d e v e l o p m e n t of in teg ra te d per so nal c o m p u t e r p r o g r a m s t h a t c a n easily m e r g e d a t a b a s e s tr u c t u r e s , statistical calculations, w ord p r o c e ss in g , and graphical o u t p u t into a c o m p r e h e n s i v e package. A time se rie s is a s e t of ordered o b s e r v a ti o n s of a particular variable ta k e n at different points in time. The time se rie s c a n be r e p r e s e n t e d by a m a th e m a t ic a l e q u atio n listing t h e value s of t h e r e s p o n s e a s a function of time or, equivalently, as a figure on a grap h w h o s e vertical c o o r d in a te gives t h e value of th e historical d a t a plotted a g a in s t time on th e horizontal axis. Th e historical d a t a c a n also be displayed in a tabular f o rm a t of r o w s an d co lu m n s, h o w e v e r , th e tr e nd pattern over time can be easily o b s c u r e d . It is th e tre nd p a tte r n g e n e r a t e d by th e time series analysis t h a t offers th e planning m e c h a n i s m and n o t neces sarily t h e individual valu es th e m s e l v e s . 27 The time se rie s is o f te n a s s u m e d to h av e th re e different c o m p o n e n t s . The M c G ra w Hill Dictionary of Modern E conom ics def in es a time series a s being c o m p o s e d of th re e mutually exclusive an d e x h a u s t iv e c o m p o n e n t s : "(1) T h e tre nd cycle c o n s is t s of cumulative and reversible m o v e m e n t s ch ar a c t e r iz e d by rec urr en t an d aperiodic intervals of ex p a n s io n an d c o n tr a c tio n (the cycle) and by longer-run drifts underlying t h e e c o n o m y (the trend). Th e tre nd is usually ch ar acteriz e d by longer m o v e m e n t s th a n t h o s e of t h e cycle. (2) Th e s e a s o n a l tre nd r e p r e s e n t s th e c o m p o s i t e effe ct of climatic an d institutional f a c to rs and is r e p r e s e n t e d by flu ctuations th a t are r e p e a t e d a lm o st regularly e a c h year. (3) The irregular, th e residual t h a t is left w h e n t h e tre nd cycle an d th e s e a s o n a l hav e both b e e n r e m o v e d from the original e c o n o m i c time series, c o n s is t s of erratic real-world o c c u r r e n c e s and m e a s u r e m e n t errors and is c haracteriz e d generally by m o v e m e n t s of less th a n six m o n t h s ' d u r a t io n . " 29 The time series trend c o m p o n e n t c a n be further elucidated by introducing an d defining th e term "secular trend." A s ecular tre nd d e n o t e s th e regular long-term m o v e m e n t of a series of e c o n o m i c d a t a . The se c u la r trend of m o s t e c o n o m ic series is positive, or u p w a r d s h o w in g g r o w th , h o w e v e r , in a f e w c a s e s , 30 t h e s ec ular tre nd is nega tive . Th e slope of th e calcu lated trend indicates th e t e n d e n c y (up or 29 Greenwald, Douglas, and Associates, The McGraw-Hill Dictionary of Modern Economics: A Handbook of Terms and Organizations. (New York: McGrawHill, 1984), pp.355-6. 30 Note: in a number of cas es the calculated trends are negative for different variables. 28 29 d o w n ) of t h e trend an d h o w fa st or h o w s lo w th e g r o w t h (positive, negative, or flat) rate is. The g r o w th or decline of th e tre nd is an indication of c h a n g e s or shifts t h a t h av e ta ken place in either supply-side f acto rs or d e m a n d - s id e d e te r m in a n ts from a theoretical p erspective. A s u g g e s t i v e list of th e f acto rs affecting Michigan (applicable to ot her s ta te s ) pr oduction agriculture is a s follows: • T he adop ti on of n e w production te c hnology • Restrictive or sla c k e n e d environ mental legislation • C h a n g e s in c o n s u m e r t a s t e s and p r efer en ces • C h a n g e s in ta x policies • Shifts in foreign a n d d o m estic tra d e policies • C h a n g e s in c o m m o d it y price s u p p o r t progra m s • C h a n g e s in s e t as ide pro gram s. T h e re are t h re e primary r e a s o n s for analyzing tre nd p a tte r n s in the time series dat a. "First, a s t u d y of tre nd allows us to d e s cri be a historical p atter n in t h e d a t a . " 31 Often this information is a useful b e n c h m a r k w h e n evaluating th e s u c c e s s or failure of previously implemen ted public or administrative policies. " S e c o n d , a s tu d y of trend p a t te r n s permits us to project p a s t p a tte r n s or t r e n d s into th e f u tu r e . " 32 W h e n t h e s ec ular tre nd is 31 Bails, Dale G., and Peppers, Larry C. Business Fluctuations: Forecasting Techniques and Applications. (Englewood Cliffs, New Jersey: Prentice Hall, 1993), p. 75. 32 Ibid. 30 identified, th e g r o w t h rate c a n be utilized to e x tr ap o late a f o r e c a s t e d trend, w h i c h e n h a n c e s th e de cision m a k e r s ' point of r e fe rence for formulating policies. T he third r e a s o n is, "by studying th e tre nd p a tte r n of a time series d a ta , w e c a n isolate or r e m o v e th e trend c o m p o n e n t from t h e ac tu al (Yt> d a t a . " 33 By removing t h e tre nd c o m p o n e n t it is easier to isolate an d anal yze th e residual c o m p o n e n t s of a time series, w hich is t h e s ea s o n a l , cyclical and residual ef fe c ts . In c h a p t e r IV, th e analytical goal is to graphically display th e time series d a ta of n u m e r o u s Michigan agricultural c o m m o d it ie s an d their prices, value of production, yields, and a c r e s h a r v e s t e d , etc . , an d their long-run secu lar tre n d s , during t h e 1 9 7 0 ' s and 80's. Explanation of the Time Series M ethod of Analysis: N u m e r o u s trend p a t t e r n s can be identified from time se rie s dat a. From a m a t h em ati cal perspective, m any of t h e s e tr e n d s are d e s c rib e d in t e r m s of linear, quadratic, exponential, logarithmic, polynomial, s q u a r e root, or parabolic func tio ns , to n a m e a fe w. The r e s e a r c h e r m u s t identify th e function t h a t b e s t d e s c ri b e s the trend pattern for t h e specific time s e r i e s . 34 33 Ibid. 34 Note: The methods and processes used by the econometrician to practice his or her trade is often an eclectic combination of both art and science. The researchers' selection of a specific function used to describe a trend pattern, can range on the continuum from highly subjective to highly objective measures. The econometrician, must therefore, rely heavily on experience when performing the analysis and on his or her ability to judge the reasonableness of their assumptions in 31 W h e n s e le c t e d , t h e m athem atic al function b e c o m e s an appro ximation of the gener al t e n d e n c y 35 or th e tre n d pattern of th e time series d a ta . In this s t u d y I h a v e confined th e analysis to calculating only t w o tre nd p atter n s; the linear an d expon en tial function. T h e s e t w o functional forms h av e bee n s e le c te d for four primary reasons : (1) Th e e a s e of interpreting th e statistical o u tput, i.e., th e coefficients, and t h e ability to calculate annual ra tes of c h a n g e from th e functions. (2) Th e ability to c o m p a r e the t w o fu nct io ns to e a c h o th e r b a s e d on their statistical g o o d n e s s of fit (R2) and, ther efore, s e le c t th e ’’b e s t fitting tre n d " f u n c tio n . 36 (3) Th e limitation of time to explore other trend func tions. The specification of th e t w o fu nctions will g e n e r a t e clos e to 4 0 0 least s q u a r e s regression runs, for all th e different c o m m o d i ty variables. (4) O ther more co m plex functions (e.g., functions which incor porate sin or c o s properties an d c h a n g e signs) could be u s e d to maximize the g o o d n e s s of fit of th e tre nd, ho w ev er , t h e long-run s ecula r trend light of all surrounding circumstances related to the time series under investigation. 35 The general tendency is the direction of the trend pattern up or down, and the rate of change or steepness of the function. It should be noted, for example, that complex functions such as third degree-polynomials are not as clearly analyzed, and are the exception rather than the rule. 36 Note: the properties of goodness of fit and it's limitations (comparability between different functions) will be discussed forth coming. 32 would be less clear b e c a u s e of th e gy rations of th e e s tim a t e d pattern . Th e m a th em ati cal function t h a t d e s c rib e s t h e linear tre nd p atter n is a s follows: Y c = a +JbT (1) T h e variables ar e defined a s follows: Yt T a b = th e value of t h e d e p e n d e n t variable in time period (t) of t h e time series being analyzed. = t h e time variable (in depen den t variable) which is in c r e m e n te d annually from 0, 1, 2, T. For m o s t of t h e time series analy zed in t h e study, th e time variable (T) g o e s from (0, 1, 20), r ep res en tin g t h e 21 y e a r s from 1 9 7 0 to 1 9 9 0 . 37 = th e y intercept, and a derived coefficient. = th e slope of t h e line, an d th e a m o u n t by w hich Y, c h a n g e s for a unit in c r e a se in T, it is also a derived coefficient. Th e m a them atical function t h a t d e s c ri b e s t h e expon en tial trend patt ern is a s follows: Yt = a b T (2) The variables are defined a s follows: Yt T a b = is t h e value of t h e d e p e n d e n t variable in time period (t) of t h e time series being analyzed. = th e time variable, in cr em en ted annually from 0, 1 , 2 , ..., T . 38 = c o n s t a n t multiple = t h e positive c o m p o u n d rate of g r ow th raised to th e p o w e r T. 37 Note: some time series are broken or shortened because of missing data. 38 Note: the sign of variable T is positive when (Yt) is increasing over time, or the sign is negative when (V,) is decreasing over time. 33 The statistical m e th o d of least s q u a r e s re gre ssi on is u s e d to d eter m in e t h e g o o d n e s s of fit an d th e coefficients of t h e e s ti m a te d tre nd e q u a t i o n s . 39 This is w h a t is of ten called th e cu rv e fitting p r o c e s s . Equations th re e t h r o u g h six explain m athem atically h o w th e linear an d expone ntial eq u a tio n s w e r e e s ti m a te d . All of t h e statistical a n a ly s e s w e r e per fo rmed in th e s p r e a d s h e e t Q uattro Pro for W i n d o w s . 40 Th e e s ti m a te d f unctio ns w er e t h e n m e r g e d with th e ac tual d a t a into a graphical format. The e s ti m a te d coefficients for the linear function ar e calcu lated as follows: a = Yc - b T (3) b , E T2 - n T 2 Th e e s tim a t e d coefficients for th e ex ponential f u n c tio n 41 are calculated as follows: 39 Note: In order to perform least squares regression on the exponential function, the function (the data) must be transformed logarithmically. This procedure turns the function into a line equation which is estimable using least squares regression. log Yt=log a + rlogi? 40 Note: Quattro Pro has the capability to calculate least squares regression. 41 Note: the equations used to estimate the exponential coefficients reflect the line logarithmic transformation, mentioned in the previous footnote. 34 log a = ( E log Yt / n) - T log b (5) (6) Th e regression o u t p u t of Qua tt ro Pro c o n ta in s all th e n e e d e d coefficients to c o n s t r u c t th e linear and ex ponential tre nd p a t te r n fu nctions for e a c h time series. T h e s e calculated fu nctions are located in a p pendix B. It is of particular im p o rtan ce to k n o w t h a t th e exp one ntial f unctio ns located in a ppendix B are th e es tim a te d logarithmic42 coefficients, tr a n sla te d bac k to b a s e 10 by taking t h e antilog of e a c h coefficient. The c o n v e r s i o n m a k e s th e exp on en tial coefficients more easily u n d e r s t o o d and c o m p a r a b l e to th e linear coefficients. Th e es tim a te d coefficients s e rv e t w o im po rt an t p u r p o s e s . T he first, is th e c o n s tr u c tio n of the historic tre nd p a tte r n for e a c h of t h e time series. By overlaying th e e s tim a te d trend pattern on t h e historical d a t a set, a long-run sec ular tre nd c a n be identified. The o th e r im port an t p u r p o s e is t h e utilization of t h e slope coefficient to calcu late an a v e r a g e annual rate of c h a n g e 43 of th e tre nd pat ter n. Th e rate of c h a n g e highlights th e d e g r e e of g r o w th or decline of th e long-run trend, 42 Remember that the exponential function requires the translation into a logarithmic format in order to utilize the technique of least squares regression. 43 Note: an average annual change can also be calculated in absolute numerical terms. 35 an d th e r a te s of c h a n g e c a n also be c o m p a r e d b e t w e e n c o m m o d i ty variables. Th e e c o n o m e t r ic s t e x t by Pindyck and Rubinfeld def ines R2 a s th e proportion of t h e total variation in Y explained by t h e r egre ssi on of Y on X.44 In this s tu d y th e i n d e p e n d e n t variable X is actually th e i n d e p e n d e n t time variable (T). The calculated R2 statistic is us ed a s t h e g o o d n e s s of fit proxy to identify which tre nd had the cl o se t m a tc h to t h e actual time series da ta . T he higher the R2 v alu e4& of the e s ti m ated function t h e bett er th e fit. In order to s e le c t t h e b e s t fitting function for th e tre nd analysis s o m e modifications for t h e exponential function w a s n e c e s s a r y to ca lculate R2. Th e modifications c e n t e r e d around the previously mentioned tra nslation of th e e s ti m a t e d logarithmic coefficients b ack to b a s e 10 (the ac tual d a t a scale) by taking t h e antilog. In t h e s a m e m an n er the tre nd line m u s t also be co n v e r t e d into b a s e 10 units. The least s q u a r e s c o m p o n e n t s of equat ion s e v e n (TSS, RSS, ESS) are th en recalculated. With th e d e c o m p o s it io n of Y, com plete, a n e w R2 is calcu lated for th e exponential function. Then t h e best fitting tre nd function (linear or exponential) is s e le c t e d b a s e d on th e hi g hest R2 for Yt. The b e s t fitting tre nd pattern is t h e n re ady to be fitted with th e actual d a t a se rie s Yt. 44 Pindyck, Robert S., and Rubinfeld, Daniel L., Econometric Models and Economic Forecasts. (McGraw-Hill Book Company: New York, 1981), p 62. 45 Note: the R2 value ranges from 0 to 1, with 1 being a perfect fit of the estimated trend to actual data, and 0 no correlation between the estimated function and actual data. 36 The following is a brief description of th e p r o c e s s of calculating R2. Th e e q u ati o n is t h e d eco m p o s itio n of V, w h e n least s q u a r e s r eg re ssi on is applied. This d e c o m p o s it io n of Y, leads to t h e nex t s t e p of calculating th e g o o d n e s s of fit (R2): e ( y , - y )2 TSS TSS = ESS RSS = e (Y,-yf = E SS ^ ( y , - y )2 + + (7) RSS t h e total variation of Y (or total s u m of s quare s ). = t h e residual variation of Y (or error s u m of s q u ares ). = th e explained variation of Y (or regression s u m of s q u ares ). Y = th e a v e r a g e o b s e r v e d value or m e a n value of Y, Yt = th e predicted value Y, = th e actual or o b s e r v e d value Equation eight is th e definition of (R2), derived from e q u a ti o n s e v e n ab ove: R2 = 1 - E SS = RSS TSS TSS Below is an exa m ple of t h e ty p e of graphical integration of th e actual time series d a ta (Yt) and t h e fitted trend pattern ( Yt )« in this c a s e expon en tial tre nd , found in c h a p te r IV. Also, included with t h e grap h is a s u m m a r y table of statistical highlights of t h e time series da ta : a v e r a g e , high, 37 low, a n d th e a v e r a g e an nu al rate of c h a n g e . 46 SOYBEANS; YIELD 21 YR TREND 1970 TO 1990 YIELD 40 21 - YEAR LU tr o 1 2UJ M- i a. UU UJ YEAR A c tu a l o A verage: 29 High: 38 L ow : 21 A v g. A nl. C hg: E x p o n e n tia l T r e n d 46 Note: the method used to calculate the average annual rate of change is mentioned above. 2 .3 0 % 38 Shift Share M ethod o f A nalysis Explanation o f Shift-Share M eth od 47 o f Analysis: This s e c tio n is a general o v erview of th e shift-share m e t h o d of analysis. A s h o r t historical explana tion of shift-shar e an d th e justifications for its r e s e a r c h application is d ev elo p ed here. A c o m p r e h e n s i v e des cr ip tion of th e sh ift-sha re te c h n i q u e an d t h e m o d els' results and an interpretation of t h e results is lo cated in c h a p t e r V of th e thes is . The disciplines of regional e c o n o m i c s an d labor e c o n o m i c s d ev elo p ed t h e statistical m e t h o d of shift-share analysis app ro ximately thirty-five y e a r s ag o to a d d r e s s diffe re nce s (w hat w a s called "locational shifts") in regional e m p l o y m e n t p a tt e r n s over time. Later t h e m e th o d w a s in co rpora ted into s tu d ie s t h a t f o c u s e d on regional income levels an d their shifts an d c h a n g e s . Sin ce its inception, t h e original shift-share t e c h n i q u e h a s b e e n significantly modified and e x t e n d e d . In c h a p t e r V th e basic shift-share model is reviewed and t h e n a d justed into th e more robu st and n e w e r Arcelus (I) shift-sh are te ch n iq u e. T h e sh ift-sha re m e t h o d is a des criptive statistical t e c h n i q u e t h a t does not explain t h e r e a s o n s for th e shifts and c h a n g e s in e m p l o y m e n t or income, but is a tool t h a t identifies th e shifts an d c h a n g e s . Th e regional analysis 47 For reference to a comprehensive review of the shift-share literature see the bibliographic notation for the authors Selting and Loveridge. The University of Minnesota staff paper covers the academic contributions, criticisms, defenses and the extension of the original shift-share technique. 39 a p p r o a c h to th e shift-share m e t h o d allows th e r e se a r c h e r to s elect a base region an d local region for c o m p a r a ti v e p u r p o se s . Various regions s u c h as s t a t e s , c o u n tie s , rural a r e a s , urban ar eas, ethnic b a c k g r o u n d s , et c., c a n be s e l e c t e d for t h e analysis. G r o w th rates (per ce nt c h a n g e s ) for a b a s e region a n d a local region are c a lc u l a te d 48 and t h e n d e c o m p o s e d into various c o m p o n e n t s s u c h a s e x p e c t e d national g r o w t h ef fects an d differential national g r o w t h ef fe cts. T h e d e c o m p o s e d e l e m e n ts form th e basis for identifying th e t y p e s of "shifts" (em plo ym en t or income) in a particular region. Th e shift-share te c h n iq u e allows th e r e s e a r c h e r to as k such q u e s ti o n s as: "are w e gaining or losing jobs in an industry," " w h a t industries in our region are co n s id e red fa st g r o w th em p lo y m e n t in dustries," " w h a t industries ar e w e specializing in," and " w h a t industries do w e h av e a com petit iv e a d v a n t a g e in?" For p u r p o s e s of this s t u d y th e Arcelus (I) model has bee n s e le c te d to ana ly ze pr oduct io n agriculture shifts 49 b e t w e e n th e b a s e U.S. region and th e local Michigan region. Farm c a s h receipts are us ed a s the basis for th e sh ift-sha re analysis instead of t h e usual em p lo y m e n t or income proxies. By using c o m m o d i ty c a s h rece ipts a s th e basis, th e Arcelus m e t h o d is able to 40 Typically the employment (or income) data is grouped into respective industrial classifications, (e.g. Standard Industrial Classification codes) to compare the local region against the base region. 49 Shifts in economic activity that are predicated on changes in the cash marketings of Michigan production agriculture commodities compared to the U.S. cash receipts for the same commodities. 40 d e c o m p o s e all c o m m o d i tie s into co m p a r a tiv e g r o w th p a tte r n s . N o w th e q u e s ti o n s t h a t w e r e a s k e d a b o v e m a y be rep hra sed : o v e r time is Michigan gaining or losing in th e val ue of pro du ction for a specific c o m m odity, w h a t c o m m o d it ie s in our region ar e c o n s id e re d "fast g r o w th " com m odities, w h a t c o m m o d it ie s are w e specializing in, and w h a t c o m m o d i tie s do w e h a v e a c o m petitive a d v a n t a g e in? Upon reviewing the literature, ther e w a s no e v id e n c e t h a t the shift-share te c h n i q u e has ever b e e n used to e x am in e agricultural c a s h rece ip ts in this m an ner . This m e th o d should provide a solid analytical ap p r o a c h to help baseline th e direction of Michigan pro du ction agriculture during th e d e c a d e s of t h e 7 0 ' s and 8 0 ' s . In pu t- O utpu t Analysis (Linkages) Explanation of I nput- O utput Method of Analysis: I np ut-ou tput (1-0) analysis is cons id e re d part of th e field of e c o n o m e t r ic s . Most 1-0 a p p r o a c h e s integrate ec o n o m ic theory, m a t h e m a t i c s , and statistical analysis into an analytical model of a well defined e c o n o m y (e.g., c o u n t y , s ta te , or country). In t h e 1 9 3 0 ' s , The Russian e c o n o m i s t Wassily Leontief w a s credited with t h e d e v e l o p m e n t of a general theory of p rodu ctio n t h a t c o n c e n t r a t e d on th e in t e r d e p e n d e n c e (linkages) of industries in an e c o n o m y . His first American empirical model w a s c o n s t r u c t e d in 1 9 3 6 of th e United S t a t e s e c o n o m y . Over time, t h e l-O m e t h o d gained m o m e n t u m in th e U.S. Th e g r ow th in l-O modeling w a s 41 greatly e n h a n c e d by t h e a g g r eg ativ e national a c c o u n tin g influence of t h e National Bureau of Economic R es earch (NBER). The d e v e l o p m e n t of c o m p r e h e n s i v e m ac ro ec o n o m ic d ata (National A ccounts ) by th e U.S. g o v e r n m e n t fit ideally within th e l-O modeling fram ew ork . For p u r p o s e s of this s t u d y an l-O personal c o m p u t e r s o f t w a r e p a c k a g e n a m e d "Micro IMPLAN" is u s e d to bet ter u n d e r s t a n d th e s tr u c tu r e and linkages of Michigan's pro duction agriculture e c o n o m y . The IMPLAN s o f t w a r e u s e s Michigan specific d a t a 50 to g e n e r a te th e statistical results. Th e final l-O res ults51 include ec o n o m ic multipliers ( em plo ym en t, ou tp u t, an d personal income) and p a tt e r n s of tra de an d c o n s u m p t i o n ta bles with special a tten tio n being paid to Michigan pr oduction agriculture. This section is a brief ov e r v i e w of th e " m e c h a n i c s " of th e 1-0 m e t h o d of an a ly s is . 52 The model s ta r t s with th e simplifying a s s u m p t i o n s of linear production f unctio ns within industries, equilibrium in th e e c o n o m y an d h o m o g e n e o u s o u t p u t t h a t is p r oduced by e a c h industry. The im portant variables are th e o u t p u t s t h a t e a c h industry (industrial catego ries) is divided into in th e r e p re s e n t a tiv e e c o n o m y . Each industr y's o u tp u t is a p r o d u c t of the s u m m a t i o n of sale s to all o th e r industries and to final d e m a n d . The e c o n o m y 50 Note: latter in this section is a description of the data elements used in the IMPLAN model. 51 The 1-0 model results are found in chapter IV. 52 It should be noted that at the beginning of chapter IV key variables and terms are defined to assist the reader with the interpretation of the 1-0 results. 42 is in equilibrium w h e n e a c h i ndustr y's o u t p u t equ als its total p u r c h a s e s (from o th e r industries) which are deter mined by th e o u t p u t of all th e other industries. Th e basic theoretical s tr u c tu r e of the 1-0 model us ed in IMPLAN is s h o w n in table I, this is called th e " tra n s a c t io n s " table. Table I c o n s is t s of four matrix q u a d r a n t s t h a t reflect th e t r a n s a c tio n s b e t w e e n t h e pu rchasi ng a n d producing s e c t o r s of a re pre sentati v e e c o n o m y . The first q u a d r a n t I, is t h e in term ed iate tr a n s a c t i o n s matrix. This is the flow of g o o d s and services t h a t are both c o n s u m e d an d pr od uced in the c u rre nt pr oduction pr o cess . Q u a d r a n t II is th e final d e m a n d s e c t o r an d reflects th e "ultimate c o n s u m e r s ' " p u r c h a s e s from th e producing industries. Final d e m a n d c o n t a i n s four major p u rchasing institutions (1) househ old c o n s u m p t io n , (2) g o v e r n m e n t e x p e n d itu r e s , (3) g r o ss d o m e s ti c capital formation an d (4) exports. Q u a d r a n t III r e p r e s e n t s the primary inputs to production. This includes th e labor supplied by h o u s e h o ld s , depreciation, imports, and th e g o v e r n m e n t. Th e final q u a d r a n t IV is th e e c o n o m y in equilibrium, w h e r e th e primary inputs equal final d e m a n d s . Below is th e m athem atical r e pre s entati on of th e IMPLAN l-O model s tr u c tu r e co r re s p o n d in g to Table I: 43 Table I S t r u c tu r e of I nput- O utput T r a n s a c ti o n s Table f P urch asin g S e c to rs T n t s r a s d l a c s Deaand I I n t s r a s d l a t s Pro­ d u c t i o n 6 C o n su a p tlo n Producing Sector* m •O ii ? 0 2. C 0H 0 H A g ricu ltu re M in in g M a n u fa c tu rin g T rade S srv lc ss F in an ce j ; ; j ; n *11-* ****1J*• • • • *^ln * • •• •• *11........ X i j . . . . . . X j Q • s * * * o l ........ * n j ...........*nn III P rln A ry In p u t* ca P ro d u c tio n . a 2 • u m 0 a a o o ^ ^ « rn ta m 2a* U 3 m o o o s u *• • m 4w J 2. H M Cross Output i •u a 2L 2 50 m. • u•0 ma « 9 S 3 3 ** ta Total M M ua u W «ad ^ • •a „ « « « 3 5 • 2 a w a 3 -S C 3 S S 2 £ 5 s1 ............3 .............. .. • PlOAl D e a a n d • II F in a l O u tp u ts o f P ro d u c in g S e c to rs Cl •# s Cl • • Cl • • Cn *1 s • El s *1 • • Cl . • Ii • • s Ei s• Cn In En s• *1 • • *n IV P r l a a r y I n p u t s t o F i n a l D e aand P a y a e n ts to H ouseholds ®1 • • • • » Hj * • • • • «Hq HC HC «i he K Cove m a s n t I j • • * *Tj • • • » «Tq TC TC Tl tk T s s D e p re c ia tio n « » • * • Dj Dq DC DC Dj °E D Z a p o rts s # • s • Hj • • • • • • Mq HC HC Hi he M • • • ■ Xj • • • • • • Xq C C I E X T o ta l C ross O u tlsy t » 44 By s u m m i n g a c r o s s a row, in q u a d r a n t I (table I) in termediate d e m a n d plus final d e m a n d equa ls th e Total Gross O u t p u t for industry "i" th e co mbining of interm ediate d e m a n d plus final d e m a n d in an "n" - industry model: */ = £ * * H Where: Xi = = + ( C t+ Gf+ 1,+ Ej) Total Gr oss O utput of Industry i Intermediate Demand for the o u t p u t of Industry i ( C; + Gj + Ij + Ej ) = Final Dem and for th e o u t p u t of industry i The variables of Final Dem and are a s follows: Cj = Personal C o n s u m p tio n Expenditures G| = S ta t e an d Local an d G o v e r n m e n t Expenditures and Com m odit y Credit l; = Gross Do m es tic Capital Formation Plus Inventory Purchases E, = Foreign Exports By s u m m in g d o w n a column, intermediate inputs (quadra nt I) plus primary inputs ( quad ra nt III) p r o d u c e s th e Total Gross Outlays of industry j. As follows: •*; = E M X ,* Tj +D j + M.) 45 W here: Xj = Total Gross Outlays of Industry j Zjj = Intermediate Inputs for Industry j ( Hj + Tj + Dj + Mj ) = Primary Inputs for industry j Th e variables of Primary Inputs are a s follows: Hj = Per sonal C o n s u m p tio n Expenditures T; = S t a t e and Local and G overnm ent C om m odity Credit Dj = Depreciation Mj = Foreign Imports E xp end itu res an d By s u m m i n g a c r o s s t h e totals r ow or d o w n th e totals colum n, th e totals (Gross O u t p u t an d Gross Outlays) for th e whole e c o n o m y are derived. n x = £ M x i + (h + t +d +m ) X = £ 7-i x i + ( C + G + I+ E) T he t w o a g g r e g a t e s co m bined , by definition, s h o w s t h a t th e e c o n o m y is in position of equilibrium. n n E */ = E /- i y-1 The d a t a us ed in th e IMPLAN model is s e p a r a t e d into t w o major 46 d a t a b a s e s e c tio n s . The first sec tio n is a national-level te c h n o lo g y matrix an d th e s e c o n d se ct io n is a grouping of e s ti m a t e s of sec to ral activity. The national te c h n o lo g y matrix is th e collection of production function coefficients for th e different s e c t o r s t h a t are applied to regional multiplier an d impact an a ly s e s . It is ther efore , an a s s u m p t i o n of t h e IMPLAN model t h a t M ic higan's e c o n o m y is r ep res en ta tiv e of th e U.S. in t e r m s of t h e m e t h o d s of production used . The s e c o n d d a t a b a s e se ct io n is s e p a r a t e d into five major g roups. The major gr oups are final d e m a n d , sa les, value a d d e d , em p lo y m e n t, an d total industry ou tp u t. S o m e of th e major gr o u p s are further s e p a r a t e d into more specific ca te g o r ie s th a t relate to th e individual c o m m o d it ie s (i.e., th e industry s e c t o r s s u c h a s dairy p r o d u c ts an d cattle and calves). The following is an outline s u m m a r y of the d a t a b a s e elem en ts: I. Final D e m a n d : Is th e final d e m a n d for th e o u t p u t pr o d u c e d by e a c h s e c to r. It is divided an d subdivided into 11 d a t a e lem en ts. Th e 12th e l e m e n t is Total Final D em an d an d is derived from t h e o th e r 11 el em ents . A. Per sonal C ons u m p tio n Expenditures (PCE): t h e industry o u tp u t p u r c h a s e d by individuals or h o u s e h o ld s for personal c o n s u m p t io n . There are th re e levels of ex p e n d itu r e s included in t h e d a t a b a s e t h a t are b a s e d upo n a h o u s eh o ld income level of: 1. Low 2. Medium 3. High < $15,000 > $ 1 5 , 0 0 0 but > $40,000 < $40,000 47 B. S t a t e a n d Local G o v e r n m e n t Expe nditures {SLG PUR): The e x p e n d it u r e s on g o o d s and s er vice s required to provide g o v e r n m e n t s erv ices . SLG p u r c h a s e s hav e b een divided into th e following d a ta ele m e n t s: 1. S t a t e an d local g o v e r n m e n t e d u catio n ex p e n d i tu r e s (ED). 2. S t a t e and local g o v e r n m e n t non- ed u catio n ex p e n d it u r e s (NonED). C. Federal G o v e r n m e n t Expenditures (FG PUR): Expenditures for goo d s a n d s er vice s required to provide federal g o v e r n m e n t ser vice s. The federal g o v e r n m e n t is s e p a r a t e d into: 1. Non-military ex p e n d itu r e s (Non MiL) 2. Military ex p e n d it u r e s (MiL) D. C om modity Credit (CCC): Excess g o o d s t h a t are b o u g h t by the federal g o v e r n m e n t Comm od ity Credit Corporation. E. Inventory P u r c h a s e s (INV PURCH): G oods t h a t are not d is pers ed in a particular year t h a t are sto re d for sale in th e ne xt period. Values in this co lumn reflect additions to inventory a m o u n t s for th e year. F. Gross Private Capital Formation (CAPITAL FORM): G o o d s t h a t are sold to industries w h o u s e th e g o o d s a s capital e q u ip m e n t. The sale s of t h e s e g o o d s provides industries with their capital s tructure. 48 G. Foreign Exports (FE): Exports of c o m m o dit ies to foreign cou ntries. H. Total Final Dem an d (TTL Final Demand): This is a s u m m a t i o n of all t h e final d e m a n d c ateg o r ies. II. S ales A. S t a t e an d Local G o v e r n m e n t Sales (SLG Sales): Sales of g o o d s and s erv ices t h a t h av e b e e n p r o duced or stockpiled by s t a t e an d local governments. B. Federal G o v e r n m e n t Sales (FG Sales): Sales of g o o d s an d ser vices t h a t h av e b een p r o d u c e d or stockpiled by th e federal g o v e r n m e n t. C. Inventory S ales (INV Sales): Inventory stored in a previous year (Inventory Pu r ch ases ) a n d sold in th e cu rre nt period. III. Value A d d e d : T h o s e c o s t s th a t are a d d e d to t h e interm ed iate c o s t s of pr od ucing g o o d s an d service s. There are four c o m p o n e n t s of th e value a d d e d c a t e g o r y plus a fifth derived d a ta e le m en t "total value a d d e d " : A. Employee C o m p e n s a ti o n : W a g e s an d salaries paid to e m p l o y e e s by industries plus th e value of benefits, and an y con tributions to social 49 s ec ur ity an d pen sion fun d s by th e e m p lo yee and employer. B. Property Income: Inco m e of sole proprietorships, w h ic h includes selfem p l o y e d income. C. Indirect Bu sines s Ta xes: Include all sale s, excis e, an d value ad d ed taxes. D. O th er Property Income: Dividend, interest, co r p o rate , and rental income. E. Total Value A dded (TTL Value Added): This d a t a e le m e n t is a total of th e a b o v e four value a d d e d d ata el em en ts. IV. E m p lo y m e n t: Th e e m p l o y m e n t e s ti m a t e s are pr o d u c e d from a n u m b e r of s o u r c e s t h a t include C ounty Business P attern s and Dunn and Bradstreet. - Total Industrial Em ploym ent (TTL Employment): This figure is e x p r e s s e d in t h o u s a n d s and r e p r e s e n ts th e n u m b e r of jobs of both full a nd part-time e m p lo y m e n t to pr o d u c e total ou tp u t. 50 V. Industrial O u t p u t : A. Total Industrial O u t p u t (TTL Industrial Output): This r e p r e s e n t s gr oss industry sale s from production. IV. MICHIGAN PRODUCTION AGRICULTURE TREND ANALYSIS General Farming Overview This s e c t io n is an historical o verview of thre e primary m a c r o t r e n d s in Michigan p roductio n agriculture during th e d e c a d e s of th e 7 0 ' s and 8 0 ' s . The th r e e c a te g o r ie s r evie w ed ar e th e n u m b e r of farms, total land in farms, and th e a v e r a g e size per farm in acr es. Nu m b er of Farms: M ic higan's farm n u m b e r s h a v e t re n d e d gradually lower in th e 7 0 ' s a n d 8 0 ' s , s e e Figure 1. In 1 9 7 0 t h e r e w e r e 8 4 , 0 0 0 farm s in the s t a t e , by 1 9 9 0 th e n u m b e r of farms had declined to 5 4 , 0 0 0 , a loss of ap proxima te ly 3 6 % . of 2 . 0 7 % . For t h e 21 yea r period, farms fell an a v e r a g e annual rate W h e n t h e tre nd ho w ev er , is s e g m e n t e d into th e 7 0 ' s vs. t h e 8 0 ' s , t w o different p a t t e r n s e m e r g e . W h a t a p p e a r s is a very slight dro p in th e rate of decline in t h e n u m b e r of farms. In th e 7 0 ' s , farms d r o p p e d a t an a v e r a g e an nual r ate of 2 . 5 3 % , for a total reduction of 1 9 , 0 0 0 . During t h e 8 0 ' s the rate s lo w e d to an an nual decline of 1 . 8 4 % with only 1 1 , 0 0 0 farms leaving pro du ction. Land In Farms: As e x p e c t e d , the a m o u n t of land in Michigan farm s had a similar tre nd p att ern, s e e Figure 2. In th e 7 0 ' s , land fell at an a v e r a g e annual rate of 1 . 0 7 % , for a total red uction of 1.3 million a c r e s . During t h e 8 0 ' s the 51 52 a v e r a g e rate s lo w e d to an an nu al drop of 0 . 5 4 % , an d a total decline of 6 0 0 t h o u s a n d a c r e s . Overall, total land in farm s fell from 1 2 . 7 million a c r e s in 1 9 7 0 to 1 0 . 8 million a c r e s in 1 9 9 0 , a drop of 1 5 % . A v era g e Size o f Farms: Many rep or ts 53 hav e highlighted th e nation wide trend t o w a r d consolidation and g r o w t h of farms into larger en ter pri ses . Michigan is no different. From 1 9 7 0 to 1 9 9 0 , th e av er ag e Michigan farm g r e w in size from 151 to 2 0 0 acr es , s e e Figure 3. The farm size g r o w th trend w a s an a v e r a g e an nu al rate of 1 . 3 9 % . This trend d o e s not s h o w t h e s a m e kinds of s tr o n g bifurcated patter nin g a s d iscus s ed ab ove. The g r o w th trend is more c o n s t a n t . Th e a v e r a g e farm picked up 2 4 ac r e s during th e 7 0 ' s and a n o th e r 2 5 a c r e s in th e 8 0 ' s , no red uction in absolute terms. 63 An example of the types of reports that are addressing this issue is as follows: U.S. Department of Agriculture, Economic Research Service, Structural Change in U.S. Farmland, by Robert C. Reining, Agricultural Economic Report 617, (Washington D.C.: Government Printing Office, issued June 1990). 53 NUMBER OF FARMS 21 YR T R E N D 1970 TO 1990 100 00 NUMBER OF FA RM S 21 - YEAR - A verage: 6 6 ,8 1 0 60 - High: 8 4 .0 0 0 20 L ow : 5 4 .0 0 0 -■ A v g . Anl. C hg: -2 .0 7 % YEAR Actual - o - E xponential Trend F ig u re 1 N u m b e r o f F a rm s , 2 1 -Y e ar T r e n d , 1 9 7 0 - 1 9 9 0 TOTAL LAND IN FARMS 21 YR TREND 1970 TO 1990 T O T A L LAND IN FA R M S 15 12 21 - YEAR g A verage: 1 1 .5 1 9 .0 0 0 6 High: 1 2 .7 0 0 .0 0 0 3 L ow : 1 0 .8 0 0 .0 0 0 0 Avg. Anl. Chg: -0 .7 0 % YEAR Actual Exponential Trend Figure 2 Total Land in Farms, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 54 AVERAGE FARM SIZE 21 YR T R E N D 1970 TO 1990 AVERAGE SIZE O F FA R M S 240 192 - 21 - YEAR 2 A verage: 174 ^ 144 - 0 in1 High: 200 48 - Low : 151 82 YEAR Actual - o - Exponential T rend Figu re 3 A v e r a g e F a rm Size, 2 1 -Y e a r T r e n d , 1 9 7 0 - 1 9 9 0 A v g . Anl. Chg: 1 .3 9 % 55 General Field Crop Overview This s e c tio n re view s th e important crop t r e n d s of price, yield, a c r e s h a r v e s t e d , value of pr oduction, and quantity p r o d u c e d for e a c h of Michigan's t o p te n field c r o p s . 54 Th e sec tio n also d i s c u s s e s s o m e of th e e c o n o m ic forces and w e a t h e r p a tte r n s t h a t h av e significantly influenced cr op produc tion. Of special n o te is t h e w e a t h e r disas ter of 1 9 8 8 , th e ef fects of which w e r e similar to t h e 1 9 3 0 ' s d r o u g h t th a t affe cted m uch of th e U.S. During t h e m o n t h s of May an d J u n e , n u m e r o u s s t a t e w e a t h e r s ta tio n s re cord ed record low rainfall. Many of t h e s e s ta ti o n s registered rainfall t h a t w a s half to o n e third below normal. This late spring an d early s u m m e r moisture s h o r t a g e severely h a m p e r e d cr op d e v e l o p m e n t t h r o u g h o u t m o s t of th e s ta t e . To make m a t te r s w o r s e , t h e fall w a s excee dingly w e t , bringing yearly precipitation totals to near normal levels. Th e deluge of rain in s u c h a s h o r t time period c a u s e d s u c h w e t field co nditions t h a t t h e a b a n d o n m e n t rate s o a r e d and m u c h of th e harves ting w a s delay ed until winter. Ultimately, t h e s e t w o w e a t h e r o b s ta c le s led to lo ws in field cr op production t h a t had not b een s e e n s in ce th e 1 9 3 0 ' s . Table II is a tre nd s u m m a r y of field cr o p s ranked by th e a v e r a g e annual p e r c e n t c h a n g e s for e a c h c a t e g o r y (yields, price, etc. ). Figures 4 and 5 are t h e a g g r e g a ti o n of all field cr o p s for t h e c a te g o r i e s of value of pro du ction and a c r e s h a r v e s te d . Field cr op ac r e s h a r v e st e d h av e e x p a n d e d at a fairly s lo w rate of 0 . 8 7 % per year, increasing from just be l o w 5 . 4 million a c r e s to just 54 The Michigan field crops selected for analysis were the top ten based on value of production. be lo w 6 . 0 million a c r e s in 1 9 9 0 . Value of produ ction h a s in creased at a fas ter annu al rate of 4 . 4 0 % . T he total field c r o p value has e x p a n d e d from ap pr oxi m ate ly $ 4 0 0 million in 1 9 7 0 t o a l m o s t $ 1 . 6 billion in 1 9 9 0 , a four fold inc rea se , s e e Figure 2. 57 T a b le II T r e n d S u m m a r y fo r C r o p s , C o m m o d i ty R a n k b y A v e r a g e A n n u a l % C h a n g e fo r 2 1 Y ears, 1 9 7 0 - 1 9 9 0 TREND SU M M A R Y FOR C R O P S CO M M O D ITY RANK BY AVERAGE ANNUAL % CHAN G E FOR 2 1 -Y earS FROM 1 9 7 0 - 9 0 A cres H arv ested P r o d u c ti o n Rank C om m odity % C hg. R ank C o m m o d ity % C hg. 1 2 3 4 5 6 7 8 9 10 Barley Soybeans S u g arb eets Hay C orn P o tato es W heat C o rn S ilage O ats Dry B e a n s 4 .7 4 % 4 .1 0 % 3 .0 5 % 1 .3 2 % 0 .9 5 % 0 .6 2 % 0 .3 5 % -0 .9 8 % -1 .9 6 % -3 .3 8 % 1 2 3 4 5 6 7 8 9 10 Soybeans Barley H ay S u g arb eets C o rn W heat P otato es C o rn S ilag e O ats Dry B e a n s 5 .9 8 % 5 .6 8 % 3 .2 6 % 3 .2 6 % 2 .6 8 % 2.1 1 % 1 .3 2 % -0 .5 9 % -1 .3 3 % -1 .9 9 % A verage 0 .8 8 % A verage Yield 2 .0 4 % Price Rank C o m m o d it y % C hg. Rank C o m m o d ity % Chg. 1 2 3 4 5 6 7 8 9 10 Soybeans H ay W heat C orn Dry B e a n s Barley P otato es C o rn S ilage O ats S u g arb eets 2 .3 0 % 1 .9 8 % 1 .9 6 % 1 .8 6 % 1 .4 8 % 1 .0 5 % 0 .6 2 % 0 .4 6 % 0 .4 1 % 0 .2 0 % 1 2 3 4 5 6 7 8 9 H ay P o tato es S u g arb eets O ats Dry B e a n s Barley Soybeans W heat C orn 4 .6 3 % 3 .3 1 % 3 .2 1 % 2 .5 0 % 2 .3 5 % 1 .9 7 % 1 .5 9 % 1 .4 0 % 1 .3 2 % A verage 1 .2 3 % A verage 2 .4 8 % 58 T a b le II (C o n tin u e d ) , T r e n d S u m m a r y fo r C r o p s , C o m m o d it y R a n k b y A v e r a g e A n n u a l % C h a n g e fo r 2 1 -Y e a rs, 1 9 7 0 - 1 9 9 0 TREND SU M M A R Y FOR C R O P S C O M M O D IT Y RANK BY AVERAGE ANNUAL % CHAN G E FOR 2 1 -Y earS FROM 1 9 7 0 - 9 0 V alue o f P r o d u c tio n Rank C o m m o d ity % Chg. 1 2 3 4 5 6 7 8 9 S u g arb eets Hay Barley Soybeans P o tato es C o rn W heat O ats Dry B e a n s 7 .6 9 % 7 .3 6 % 6 .7 5 % 6 .7 2 % 4 .4 5 % 3 .3 8 % 2 .8 7 % 0 .9 5 % 0 .3 1 % A verage 4 .5 0 % 59 ALL FIELD CROPS; VALUE OF PRODUCTION 21 Y R T R EN D VALUE OF PRO DU CTIO N 1970 TO 1990 $2,000 21 - YEAR $1,600 ~ $ r y ia os A verage: $ 1 ,1 3 8 ,3 8 1 ,8 2 7 1,200 ' $000 High: $ 1 ,6 4 4 ,9 9 5 ,6 5 0 $400 Low : $ 3 7 6 ,4 4 8 ,5 0 0 $0 90 A v g . Anl. C h g: 4 .4 0 % YEAR — Figure 4 A ctual - o - U n e ar T rend All Field C r o p s V a lu e o f P r o d u c t io n , 2 1 -Y e a r T r e n d , 1 9 7 0 - 1 9 9 0 ALL FIELD CROPS; ACRES HARVESTED 21 YR TREND 1970 TO 1990 A C R ES HARVESTED 90 21 - YEAR 7.2 -• A verage: 6 ,5 4 4 ,8 9 0 oID o s< ?o High: 7 ,6 9 8 ,8 0 0 Low: 5 ,2 4 1 ,9 0 0 YEAR — Actual - o - U n e ar T rend Figure 5 All Field C rops A c res H a rv ested , 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 Avg. Anl. Chg: 0 .8 7 % 60 Barley: Most barley g row n in Michigan is us ed for feed, h o w e v e r , a small portion is sold for malting. Barley production is confined pr edo minantly to th e th re e c o u n tie s of Huron, Sanilac, and Tuscola. T h e s e th re e c o u n t ie s a c c o u n t for app ro ximately 4 0 % of t h e s t a t e ' s production. Huron c o u n t y alone p r o d u c e s 2 5 % of th e barley. Although barley is not t h o u g h t of a s a major field cr op in Michigan, it h a s quietly inc rea se d in production. Acres h a r v e s t e d h av e doubled in t h e 21 ye a r s of analysis, growing at an a v e r a g e annual rate of 4 . 7 4 % , 55 first for all Michigan field cro ps, s e e s u m m a r y Table II. Acres in produ ction h av e e x p a n d e d from 2 0 , 0 0 0 in t h e 7 0 ' s to well over 4 0 , 0 0 0 a c r e s in th e 8 0 ' s . The a m o u n t of barley a c r e s h a r v e s te d is n o w c o m p a r a b le to all th e s t a t e ' s p o t a t o e s area h a r v e s te d . M ost of this g r o w t h has oc c u r re d during th e d e c a d e of t h e eighties, s e e Figure 7. Yields hav e also improved, at an a v e r a g e annual rate of 1 . 0 5 % . The higher yields cou pled with th e rise in a c r e s h a r v e s t e d has provided a significant incr ea se in th e quantity of barley p r o d u c e d . Production of barley incr ea se d from an a v e r a g e of app ro ximately o n e million bus hels a yea r for m uch of th e 7 0 ' s , to co nsis tently over 2 . 5 million b u s h e ls a y ear in th e late 8 0 ' s . Th e only field crop with a higher tre nd rate in t e r m s of total quantity pr o d u c e d are s o y b e a n s . 66 The price per bu shel tre nd is steadily 55 N o t e : t h e t r e n d f o r b a r l e y is e x p o n e n t i a l r a t h e r t h a n l i n e a r , s e e F i g u r e 7 , t h i s h i g h l i g h t s t h e r a p i d g r o w t h in a c r e s h a r v e s t e d . 56 S o y b e a n p r o d u c t i o n i n c r e a s e d a t a n a v e r a g e a n n u a l r a t e o f 5 . 9 8 % . 61 u p w a r d , 57 but highly variable. Barley prices have ranged from a low of $ 0 . 7 9 in 1 9 7 0 , to a high of $ 3 . 7 5 in 1 9 8 0 . Given the rise in prices a n d t h e rapid incr ea se in th e quantity p r o d u c e d , it is not surprising to disc ove r t h a t t h e value of pro du ction has g r o w n a s well. Barley value of pr oduct io n in creased at an a v e r a g e annual rate of 6 . 7 5 % , just behind s u g a r b e e t s and hay. Total value has incr ea se d from below $1 million per year to o v e r $5 million per year. By far th e sm allest value of pro du ction for the field c r o p s studied , but th e g r o w t h in p e r c e n t a g e t e r m s is o n e of th e largest. BARLEY; VALUE OF PRODUCTION 21 YR T R EN D 1970 T O 1990 VALUE OF PRO DU CTIO N $8 0 $64 21 - YEAR - A verage: $ 3 ,5 3 6 ,4 3 2 High: $ 6 ,7 2 8 ,0 0 0 $1 6 L ow : $ 8 7 0 ,3 2 0 - $0 0 88 YEAR ^ — Actual F ig ure 6 90 A v g . Anl. C hg: 6 .7 5 % - o - L in e a r Trend Barley V a lu e o f P r o d u c ti o n , 2 1 -Y ear T r e n d , 1 9 7 0 - 1 9 9 0 57 The average annual growth rate is 1.97% for the barley price per bushel. 62 BARLEY; ACRES HARVESTED 21 YR TREND 1970 TO 1990 A C R ES HARVESTED 21 - YEAR 52 -• A verage: 2 9 ,8 5 7 High: 5 5 .0 0 0 Low : 1 9 .0 0 0 A v g . Anl. C h g: 4 .7 4 % YEAR Actual F ig u re 7 - o - Exponential Trend Barley A c r e s H a r v e s t e d , 2 1 -Y ear T r e n d , 1 9 7 0 - 1 9 9 0 BARLEY; PRODUCTION 21 YR T REN D 1970 TO 1990 PRO DU CTIO N 3,500 21 - YEAR 2,800 - A verage: 1 ,5 7 7 ,5 2 4 x -o 2,100 -• V) c 3 ro m ^ High: 3 .2 4 5 .0 0 0 _j o £ (5 1,400 - Low : 8 9 3 .0 0 0 700 - c YEAR —— Actual - o - Exponential T rend Figure 8 Barley Production, 2 1 -Y ear Trend, 1 9 7 0 - 1 9 9 0 A v g . A nl. C hg: 5 .6 8 % 63 BARLEY; YIELD 21 YR TRE N D 1970 TO 1990 YIELD 72 0 21 - YEAR 57 6 - A verage: 51 LU 43 2 - ■ High: 68 cn w 28 8 - Low : 32 14 .4 - A v g . Anl. C hg: 1 .0 5 % 00 YEAR ■Actual F ig u re 9 - o - Linear T rend Barley Yield, 2 1 -Y e ar T r e n d , 1 9 7 0 - 1 9 9 0 BARLEY; PRICE PER BUSHEL 21 YR TREND 1970 TO 1990 PRICE $4.0 21 - YEAR $3.2 -• A verage: $ 2 .3 1 3 $2.4 - High: $ 3 .7 5 uj LU $1.6 -■ $ 0.8 Low : $ 0 .7 9 - Avg. Anl. Chg: 1 .9 7 % $0 0 YEAR — Actual - o - Linear Trend Figure 1 0 Barley Price, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 64 Corn for Grain: Corn for all p u r p o s e s is o n e of M ichigan 's m o s t a b u n d a n t an d im po rt an t livestock feed grains.58 The corn is used primarily in t h e dairy and c attle industries. The rest of t h e corn is either sh ip ped to export m a r k e ts, dry milled, w e t milled, distilled or us ed a s s e e d . It's g r o w n in a lm o st ev ery co u n t y in t h e lower peninsula. Sixty-six of th e sixty-eight c o u n tie s in th e lower peninsula h a r v e s t ov er 5 0 0 a c r e s or more of corn a year. In 1 9 9 0 th e to p five producing co u n tie s w e r e Huron, L ena wee , St. J o s e p h , Sanilac, an d Branch. T h e s e five c o u n ti e s a c c o u n t for app ro ximately 2 4 % of th e s t a t e ' s total a c r e s h a r v e s t e d annually. During th e 21 years of analysis, o n e y ea r 1 9 8 3 , requires di sc ussio n. In 1 9 8 3 th e U.S. D e p a r tm e n t of Agriculture instituted th e P a y m e n t in Kind (PIK) prog ra m . By participating in PIK farmers a g r eed to r e m o v e a c r e a g e from p rod uction an d receive a specified a m o u n t of corn or w h e a t a s a p a y m e n t for n ot planting. The p rogra m w a s de sig ne d a s a supp ly m a n a g e m e n t tool to control a nation wide surplus of corn. Michigan' s enr ollment in th e p rogra m r e d u c e d pro du ction a c r e a g e by 3 4 p e r c e n t or 9 4 0 , 0 0 0 a c r e s , s e e Figure 12. O n c e t h e progra m w a s lifted in 1 9 8 4 , a c r e a g e planted returned to normal pre p ro g r a m levels. Th e o th e r yea r of note is 1 9 8 8 and t h e e f f e c t s of a d rought. Th e d r o u g h t of 1 9 8 8 w a s th e w o r s t w e a t h e r co nditions e x p er ien ced by Michigan fa rm er s sin ce th e 1 9 3 0 ' s . Many w e a t h e r s ta t io n s re cord ed record low rainfall during May and J u n e , generally o n e half to o n e third be lo w 58 T h e o t h e r m a j o r f e e d s o u r c e s a r e h a y a n d c o r n s i l a g e . 65 normal rainfall a m o u n t s t h r o u g h o u t th e s ta te . Th e lack of mo is ture severely d a m a g e d critical plant d ev elo p m en t. To c o m p o u n d problems further, th e fall w a s e x ceedingly w e t , bringing yearly precipitation totals to near normal levels. The result w a s w e t field conditions, a b a n d o n m e n t , delayed har ves ting until freeze -up, an d plummeting yields. The 2 1 -year tre nd for Michigan corn pro ductio n is gradually upw ar d d e s p it e th e significant interruptions m entione d a b o v e . M os t of t h e g r o w th oc c u r re d in t h e first d e c a d e and the early 8 0 ' s . Acres h a r v e s t e d inc rea se d from 1 . 4 million a c r e s to a record high of 2 . 8 million a c r e s 59 in 1 9 8 1 . During th e 8 0 ' s h a r v e s te d ac r e s h a v e retreated to a c o n s is t e n t level of 2 . 0 million a c r e s . Yields h av e e x p a n d e d an a v e r a g e annual rate of 1 . 8 6 % , 4 t h for all Michigan field c r o p s. Michigan rec or ded it's hi ghest s t a t e a v e r a g e yield per ac r e of 1 1 5 bus hels of corn in 1 9 9 0 . The incr ea se in yields plus an ex p an s io n in a c r e s h a r v e s te d has m e a n t t h a t th e quantity of corn p r o d u c e d h a s also gr ow n. Th e co rn pro du ctio n trend is an a v e r a g e an nua l increase of 2 . 6 8 % , 5th for all field crops. In 1 9 8 2 Michigan s e t a production record for 2 9 3 million bu shels, s e e Figure 13. The s t a t e is currently 8th in t h e c o u n t r y in corn pr oduction, producing 3 . 0 % of th e share, Iowa is first. 59 T h e 1 9 8 1 s t a t e r e c o r d o f 2 . 8 m illio n a c r e s w a s t h e h i g h e s t a m o u n t r e c o r d e d s i n c e y e a r l y e s t i m a t e s b e g a n in 1 9 2 4 . 66 CORN FOR GRAIN; VALUE OF PRODUCTION 21 YR T R EN D 1970 T O 1990 VALUE OF PRO D UCTIO N $900 21 - YEAR $720 A verage: $ 4 3 5 ,6 8 0 ,4 0 7 < Q — $540 ir In Zj 2 □ '■■$360 High: $ 7 4 7 ,6 0 9 ,0 0 0 $180 Low: $ 1 2 2 ,9 5 1 ,1 0 0 $0 A v g . Anl. C hg: 3 .3 8 % YEAR — F ig u re 11 Actual Linear T rend C o rn f o r Grain V alue o f P r o d u c tio n , 2 1 -Y ear T r e n d , 1 9 7 0 - 1 9 9 0 CORN - ALL PURPOSES; ACRES HARVESTED 21 YR TREND 1970 TO 1990 3,200 A C R ES HARV ESTED 21 - YEAR 2.560 - A verage: 2 ,1 7 1 ,4 7 6 High: 2 ,8 0 0 ,0 0 0 Low : 1 ,4 2 9 ,0 0 0 640 - YEAR Actual - o - Linear Trend Figure 1 2 Corn-All P u rp o s e s A c res H arv ested , 2 1 -Year Trend, 1 9 7 0 1990 Avg. Anl. Chg: 0 .9 5 % 67 CORN FOR GRAIN; PRODUCTION 21 Y R T R E N D PRODUCTION 1970 T O 1990 350 21 - YEAR 280 - A verage: 1 9 5 ,0 3 0 ,7 1 4 High: 2 9 3 .1 8 0 .0 0 0 Low: 1 1 0 .4 1 0 .0 0 0 70 - A v g . Anl. Chg: 2 .6 8 % YEAR ■Actual F ig u re 1 3 -© - Linear T rend C o rn fo r G rain P r o d u c tio n , 2 1 -Y ear T r e n d , 1 9 7 0 - 1 9 9 0 CORN FOR GRAIN; YIELD 21 YR TREND 1970 TO 1990 YIELD 120 21 - YEAR 96 -■ A verage: 89 LU tr a w a 72- High: 115 cn w < zn > CD 48 -■ L ow: 61 24 - Avg. Anl. Chg: 1 .8 6 % YEAR — A ctual -© - Linear T rend Figure 1 4 Corn for Grain Yield, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 68 CORN FOR GRAIN; PRICE PER BUSHEL PRICE 21 YR TREND 1970 TO 1990 $3.5 21 - YEAR A verage: $2.20 UJ 3 $ 2.1 m - High: $ 3 .2 0 - c o: lli Q_ LU $ 1 .4 - - Low: $ 1 .0 3 $0 7 - ■ A vg . Anl. Chg: 1 .3 2 % $0.0 YEAR Actual Linear T rend F ig u re 1 5 C o rn f o r G ra in Price, 2 1 - Y e a r T r e n d , 1 9 7 0 - 1 9 9 0 Corn Silage: Corn silage is a critical input for Michigan's dairy and cattle industries. It's not surprising t h a t t h e s t a t e ' s leading dairy co unties; Sanilac a n d Huro n, 60 are first in the in the production of corn silage. T h e s e t w o c o u n t ie s a c c o u n t for over 1 8 % of th e s t a t e ' s total a c r e s h a r v e s te d . In 1 9 9 0 Huron c o u n t y h a r v e s t e d 2 6 , 0 0 0 a c r e s an d Sanilac h a r v e ste d 2 5 , 0 0 0 acr es . Total s t a t e produ ction of corn silage has b e e n declining for th e last t w o d e c a d e s . Acr es h a r v e s te d h a v e fallen an av erage annual rate of 0 . 9 8 % . 61 Th e trend for yields s h o w s minor im pro vem ents increasing a t an a v e r a g e an nua l rate of 0 . 4 6 , 8th for all field crops. In 1 9 9 0 an a v e r a g e s ta te 60 In 1 9 9 0 S a n i l a c c o u n t y h a d 2 5 , 7 0 0 m ilk c o w s a n d H u r o n c o u n t y h a d 1 7 , 3 0 0 m ilk c o w s . 6' N o t e : o a t s a n d d r y b e a n s w e r e t h e o n l y o t h e r c r o p s t o h a v e a d e c l i n i n g a c r e a g e tre n d . 69 yield record w a s s e t for 1 4 . 5 t o n s per acre, s e e Figure 18. Given th e faster rate of decline for a c r e s h a r v e s t e d c o m p a r e d to t h e gradual rise in yields, th e qu an ti ty p r o d u c e d has s u b s e q u e n t l y dr o p p ed . Production has tr e n d e d d o w n w a r d at an a v e r a g e annual rate of 0 . 5 9 % . Production p eak ed in 1 9 7 7 w h e n a record of 5 . 6 million t o n s w a s esta blishe d. Since 1 9 7 7 , th e quantity of silage h a r v e s t e d h a s co nsis tently fallen be low 4 . 0 million to n s. Michigan w a s ranked 8th in t h e c o u n t r y in production, in 1 9 9 0 , producing 4 . 7 % of th e s h are, W is c onsi n is t h e leading s ta te. CORN SILAGE; ACRES HARVESTED 21 YR TREND 1970 TO 1990 A C R ES HARVESTED 600 21 - YEAR 4B0 - - A verage: 3 7 9 ,3 3 3 CO a. S' 360 - - Q£ High: 4 9 8 .0 0 0 12 0 L ow : 2 8 0 .0 0 0 -• Avg. Anl. Chg: - 0 .9 8 % YEAR Actual Linear T rend Figure 1 6 Corn Silage A c re s H arv ested , 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 70 CORN SILAGE; PRODUCTION PRODUCTION 21 YRTREND 1970 TO1990 21 - YEAR 5 2 -• A verage: 4 ,6 3 8 ,0 9 5 High: 5 .5 6 5 .0 0 0 26 - Low : 3 .3 7 5 .0 0 0 A v g . Anl. C hg: -0 .5 9 % YEAR Actual F ig u re 1 7 - o - L in e a r Trend C o rn S ilage P r o d u c tio n , 2 1 -Year T r e n d , 1 9 7 0 - 1 9 9 0 r CORN SILAGE; YIELD 21 YR TREND 1970 TO 1990 YIELD 160 12.0 21 - YEAR -■ 9 .6 -- A verage: 1 2 .4 6.4 -■ High: 1 4 .5 3.2 - Low: 7 .5 00 Avg. Anl. Chg: 0 .4 6 % LU QL ^ K LU cz/> o Ia. YEAR ----- Actual - o - Linear Trend ) Figure 1 8 Corn Silage Yield, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 71 Dry B eans: Michigan has b een called th e dry bea n capital of th e World. Most of th e dry b ean pr oduction is located in th e fertile soils of th e Bay-Thumb area in th e s ta t e . The t w o c o u n t ie s of Huron an d Tu scola a c c o u n t for a pp rox imate ly 4 0 % of t h e total production. The s t a t e ' s co m petit iv e position h o w e v e r , has b e e n declining t h r o u g h o u t th e d e c a d e s of t h e 7 0 ' s an d 8 0 ' s . In t h e early 7 0 ' s Michigan pr o d u c e d over 3 0 % of th e United S t a t e s total dry b e a n pro ductio n an d for s o m e varieties s u c h a s navy b e a n s , th e s t a t e p r o d u c e d 9 0 % of t h e total. By 1 9 9 0 h o w e v e r , Michigan's national s h a r e of total dry b ean pro du ction had declined to 1 6 . 8 % and 5 3 . 8 % for navies. W h a t d o e s t h e tre nd analysis reveal? Acr es h a r v e s t e d of all dry b e a n s h a s been on a d o w n w a r d trajecto ry for m o s t of th e 21 y e a r s of analysis. The only significant deviation from t h e trend o c c u r re d from 1 9 8 0 to 1 9 8 2 . In 1 9 8 0 an u n e x p e c te d l y large e x p o r t market for colored b e a n s e m e r g e d with Mexico. Given th e n e w b e a n market, a c r e s h a r v e s t e d e s c a la t e d to o v e r 5 7 0 , 0 0 0 a c r e s (up 2 4 % in o n e year), pro ductio n increase d to over 7 . 7 5 million hund red w e ig h t (up 2 0 % in o n e year), an d value of pro duction s o a re d to $ 2 0 4 million (up 7 2 % in on e year), t h e different sp ikes are s h o w n in e a c h of th e re sp ective figures. By 1 9 8 2 , th e Mexican e x p o r t m ar ket for colored b e a n s , primarily black turtle a n d pinto b e a n s deter iora ted an d Michigan dry b ean pro du ction had returned to p r e - 1 9 8 0 levels. Th e 2 1 -year tre nd for b ean a c r e s h a r v e st e d s h o w s an a v e r a g e annual decline of 3 . 3 8 % . Dry b e a n s are last a m o n g th e te n field cr o p s an alyzed, only 72 o a t s a n d c o r n silage p o s t e d a negative a c r e s h a r v e s te d tre nd. T he tre nd for th e qua ntit y of b e a n s pr o d u c e d w a s also significantly ne ga tive . Dry b e a n s h a v e declined an a v e r a g e an nu al a m o u n t of 1 . 9 9 % , last for all field c r o p s, s e e s u m m a r y Table II. Th e tre nd for th e price of b e a n s per Cw t. per si ste d higher. Dry b e a n prices ro se annually at an a v e r a g e of 2 . 3 5 % , fifth for all field crops. The increase in b e a n prices cou pled with th e declines in produ ction h a s m e a n t t h a t t h e valu e of pr oduction trend is flat, s e e Figure 19. Th e 2 1 -year tre nd for b e a n value of pro ductio n is an a v e r a g e annual increase of only 0.31 %, last for all field cr op s. ALL DRY BEANS; VALUE OF PRODUCTION 21 YRTREND 1970 TO1990 $220 VALUE OF PR OD U CTIO N $176 -■ 21 - YEAR A verage: $ 1 0 2 ,4 7 8 ,4 5 7 <£> — $132 O 2 $BB - High: $ 2 0 4 ,6 5 2 ,8 0 0 $44 - L ow : $ 5 9 ,6 8 4 ,1 0 0 Avg. Anl. Chg: 0 .3 1 % YEAR — Actual Exponential Trend Figure 19 Dry B eans Value of P roduction, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 73 ALL DRY BEANS; ACRES HARVESTED A CRES HARVESTED 21 YR TREND 1970 TO 1990 700 21 - YEAR 560 - A verage: 4 6 8 ,5 7 1 (ft _ a -a 420 - y< !§ M High: 6 1 5 .0 0 0 Low : 1 7 0 .0 0 0 140 - 80 90 A vg . Anl. C hg: -3 .3 8 % YEAR Actual Figure 2 0 - o - Linear T rend Dry B e a n s A c r e s H a r v e s t e d , 2 1 -Y ear T r e n d , 1 9 7 0 - 1 9 9 0 ALL DRY BEANS; PRODUCTION 21 YRTREND 1970 TO1990 PRODUCTION 21 - YEAR 7 2 -■ A verage: 5 ,5 5 7 ,6 6 7 High: 7 .9 7 5 .0 0 0 Low : 2 .1 4 2 .0 0 0 YEAR — Figure 21 Actual o - Linear Trend Dry B eans Production, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 Avg. Anl. Chg: -1 .9 9 % 74 ALL DRY BEANS; YIELD YIELD 21 YR TREND 1970 TO 1990 1.800 21 - YEAR A verage: 1,201 £ 1,080 High: 1 ,6 5 0 L ow : 800 360 - .................................... A v g . Anl. C hg: 1 .4 8 % 70 72 74 76 78 80 82 84 86 88 90 YEAR ■Actual F ig u re 2 2 Linear T rend D ry B e a n s V alue Yield, 2 1 -Y ear T re n d , 1 9 7 0 - 1 9 9 0 ALL DRY BEANS; PRICE PER Cwt. 21 YR TREND 1970 TO 1990 PRICE $36 0 21 - YEAR $28.8 - A verage: $ 1 9 .2 O $ 2 1 .6 - High: $ 3 1 .9 Low: $ 8 .7 $ 7 .2 - Avg. Anl. Chg: 2 .3 5 % $00 YEAR Actual -© - Linear Trend Figure 2 3 Dry B eans Price, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 75 Hay: Michigan ha y is usually cu t th re e times a yea r d ep e n d in g on w e a t h e r cond itions. The Michigan Agricultural Statistics Service e s t i m a t e s t h a t 8 5 % of t h e s t a t e ' s hay is c o n s u m e d on location with th e remaining 1 5 % sold as a c a s h crop. Th e n u m ber of p roducers growing ha y a s a c a s h cr op is increasing to m e e t t h e feed n e e d s of th e s t a t e ' s dairy and bee f cattle industries. The hay is either sold directly to livestock farmers or to hay bro kers t h r o u g h auctions. Hay pro ductio n has incre ased rapidly in th e 7 0 ' s an d 8 0 ' s . This g r ow th is a function of more a c r e s h ar v ested and improved yields. Hay pro du ction 62 h a s in c r e a se d an annual a v e r a g e of 3 . 2 6 % 63 for th e last 21 y e a r s . Production h a s in creased from just below 3 . 0 million t o n s per y ear to well over 5 . 0 million t o n s a year, placing Michigan 10th in th e c o untry in 1 9 9 0 with a s h a r e of 3 . 6 % . T he 2 1 -year yield per ac re trend w a s the s e c o n d largest for Michigan field c r o p s at an a v e r a g e annual incr ease of 1 . 9 8 % , s e e s u m m a r y Table II. Acr es h a r v e s t e d h av e e x p a n d e d from 1.3 million a c r e s per year to a c o n s is t e n t level of 1.5 million a c r e s per year. One year of special note is 1 9 8 8 , w h e n a c r e s h a r v e s t e d swelled to 1.9 million up from 1 . 4 million a c r e s in 1 9 8 7 . This large in creased w a s a direct result of set-as id e and c o n s e rv a tio n reserve a c r e a g e being released for haying and grazing b e c a u s e of the 1 9 8 8 dr ou gh t. Prices ju m p ed dramatically in 1 9 8 8 to a record high of $ 9 4 per ton, from $ 6 0 a to n in 1 9 8 7 , a s d e m a n d greatly e x c e e d e d a limited supply. T h r o u g h o u t th e 82 Only soybeans (5.98%) and barley (5.68%) had a faster annual production growth rate. 63 Hay is tied for third with sugarbeets 76 t w o d e c a d e s hay prices in crease d more th a n an y o th e r field crop increasing an a v e r a g e an nu al a m o u n t of 4 . 6 3 % . Cons istently higher hay prices coupled with e x p a n d e d production greatly in crease d th e value of production. Value of pr od uct io n h a s quad ru pled from approximately $75 million per y ear to over $ 3 3 6 million, s e e Figure 2 4 . Hay is n o w t h e s t a t e ' s s e c o n d largest field crop b a s e d on value of production, corn is first. In 1 9 9 0 Michigan w a s 5th in th e c o u n tr y for th e quantity pr o d u c e d of alfalfa hay ( 5 . 8 % of t h e share) and 10th for all hay ( 3 . 6 % of th e share), Wisconsin ranked first in both ca tegor ies. ALL HAY; VALUE OF PRODUCTION 21 YR T RE N D 1970 TO 1990 VALUE OF PRODUCTION $420 21 - YEAR $336 - A verage: $ 2 0 7 ,4 2 4 ,6 1 9 £ — $252 - High: $ 3 9 6 ,6 8 0 ,0 0 0 L ow: $ 7 3 ,8 2 2 ,5 0 0 $84 Avg. Anl. Chg: 7.3 6 % YEAR — Actual Linear T rend Figure 2 4 All Hay Value of Production, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 77 ALL HAY; ACRES HARVESTED 21 YR TREND 1970 TO 1990 ACRES HARVESTED 2,000 21 - YEAR 1,600 - A verage: 1 ,4 3 6 ,6 6 7 High: 1 .9 0 0 .0 0 0 L ow : 1 .2 4 0 .0 0 0 400 - A v g . Anl. Chg: YEAR ■Actual F ig u re 2 5 1 .3 2 % Exponential Trend All H a y A c r e s H a r v e s t e d , 2 1 -Y ear T r e n d , 1 9 7 0 - 1 9 9 0 ALL HAY; PRODUCTION 21 YR TRE N D 1970 T O 1990 PRO D UCTIO N 60 2 1 - YEAR 48 - A verage: 4 ,0 3 6 ,2 8 6 O i- ew High: 5 .7 4 3 .0 0 0 2 .4 - L ow : 2 .6 7 7 .0 0 0 Avg. Anl. Chg: 3 .2 6 % 00 YEAR — Actual - o - Linear Trend Figure 2 6 All Hay Production, 2 1 -Year T rend, 1 9 7 0 - 1 9 9 0 78 ALL HAY; YIELD 21 YR T R E N D YIELD 1970 T O 1990 21 - YEAR 3.2 -- A verage: 2 .7 9 UJ a. ^ 2 .4 CL High: 3 .6 8 ^ 1.6 O t- Low : tLUr 2.00 0.0 - A v g . Anl. C hg: 1 .9 8 % 0.0 86 YEAR ■Actual F ig u re 2 7 - o - Linear T rend All H a y Yield, 2 1 - Y e a r T r e n d , 1 9 7 0 - 1 9 9 0 ALL HAY; PRICE PER TON 21 YR TREN D 1970 T O 1990 PRICE $100 2 1 - YEAR $80 -■ or LU A verage: $ 4 9 .6 $60 - CL LU High: $ 9 4 .0 y $40 -• a. CL $20 L ow : $ 2 2 .5 - YEAR —— Actual - o - Linear T rend Figure 2 8 All Hay Price, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 Avg. Anl. Chg: 4 .6 3 % 79 Oats: O ats ar e g r o w n alm o s t exclusively a s a s o u r c e of livestock feed. Typically, th e y are raised a n d c o n s u m e d on site with s o m e sold for pr oce ss ing. Th e eq uine industry (p leasure h orses , working horse s, or race ho rses ) is o n e of M ichigan 's largest c o n s u m e r s of o ats. Production in th e s t a t e is confined primarily to th e e a s t ce ntra l region, which includes t h e c o u n tie s of Sanilac, Huron, an d Tuscola. T h e s e th re e c ounties usually a c c o u n t for 2 5 % of th e s t a t e ' s total a c r e s h a r v e s te d . In 1 9 9 0 Michigan ranked 9 th in th e c o u n tr y for n u m b e r of b u s h e ls p r o d u c e d , producing 3 . 7 % of th e total. Oat p rod uction h a s tre n d e d steadily d o w n w a r d during th e d e c a d e s of t h e 7 0 ' and 8 0 ' s . The decline in the quantity of o a t s p r o d u c e d is a direct function of a re d uct io n in a c r e s h a r v e s te d . Both a c r e s h a r v e s t e d an d quantity of o a t s p r o d u c e d s h o w e d negative a v e r a g e annual c h a n g e s , th e former 1 . 9 6 % an d th e latter 1 . 3 3 % . This placed o a t s in ninth place in e a c h c a t e g o r y for the t e n Michigan field cr o p s an alyze d, s e e s u m m a r y Table II. Total a c r e s h a r v e s t e d r e a c h e d a low of 2 0 0 , 0 0 0 ac r e s during t h e d r o u g h t of 1 9 8 8 and th e high in a c r e a g e h a r v e s t e d oc c u r re d in 1 9 7 0 , at a level of 4 6 7 , 0 0 0 . Even with t h e decline in o a t prod uc tion, yields have s h o w n small gains, increasing an an nu al a v e r a g e of 0.41 %. Price per bushel h a s also exhibited a p er sis te n t g r o w th of an an nual a v e r a g e rate of 2 . 5 0 % . This is fourth a m o n g all field c r o p s. The value of pro du ction trend s h o w e d slight in c r e a s e s of 0 . 9 5 % per year, d e s p it e th e declines in th e quantity of o a t s p r o d u c e d . Michigan p r o d u c e s o a t s at an a v e r a g e value of $ 2 7 million a year. 80 OATS; VALUE OF PRODUCTION 21 YR TREN D VALUE OF PRODUCTION 1970 TO 1990 $50 21 - YEAR $40 -• A verage: $ 2 7 ,1 3 8 ,6 7 9 High: $ 4 2 ,2 4 1 ,5 0 0 $10 Low: $ 1 3 ,8 4 8 ,5 5 0 - A v g . Anl. C hg: 0 .9 5 % YEAR Actual F ig u re 2 9 - o - Exponential Trend O a t s V a lu e of P r o d u c tio n , 2 1 -Y ear T re n d , 1 9 7 0 - 1 9 9 0 OATS; ACRES HARVESTED 21 YR TREND 1970 TO 1990 A C R ES HARVESTED 500 400 -■«= 21 - YEAR A verage: 3 4 0 ,8 1 0 a -3 300 - Q£ High: 4 6 7 .0 0 0 100 - Low : 2 0 0 .0 0 0 Avg. Anl. Chg: -1 .9 6 % YEAR ------Actual -© - Linear T rend ) Figure 3 0 O a ts A c re s H arv ested , 21-Y ear Trend, 1 9 7 0 - 1 9 9 0 81 OATS; PRODUCTION 21 YR TREND 1970 TO 1990 PRODUCTION 35 21 - YEAR 28 -■ A verage: 1 9 ,4 0 4 ,5 7 1 High: 2 8 ,3 5 0 ,0 0 0 L ow : 6 , 000,000 A v g . Anl. C hg: -1 .3 3 % YEAR — F ig u re 3 1 Actual -© - Linear Trend O a t s P r o d u c tio n , 2 1 -Y ear T r e n d , 1 9 7 0 - 1 9 9 0 OATS; YIELD 21 Y R TREND 1970 TO 1990 YIELD 21 - YEAR 60 -• LU A verage: 56 45 UJ High: 67 w 30 in r> m L ow : 30 YEAR ■Actual -© - Linear T rend Figure 3 2 O a ts Yield, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 Avg. Anl. Chg: 0 .4 1 % 82 OATS; PRICE PER BUSHEL 21 YR TREN D 1970 T O 1990 PRICE $30 21 - YEAR $2.4 - A verage: $ 1 .4 5 3 $ 1 .B - 00 High: $ 2 .6 5 LU o $ 1.2 -• L ow : $ 0 .7 0 $ 0.6 - A v g . Anl. Chg: 2 .5 0 % $0 0 YEAR — F ig u re 3 3 Actual -© - Linear T rend O a t s P rice, 2 1 -Y e ar T r e n d , 1 9 7 0 - 1 9 9 0 All P o ta t o e s : Mich igan 's p o t a t o e s are g r o w n during t w o s e a s o n s , th e fall and s u m m e r . Appr oximately 8 0 % of total p o t a t o pro ductio n is p r o d u c e d in th e fall with th e rem ainder coming during th e s u m m e r har ve st . M ost of th e S t a t e ' s pro duct io n is limited to t w o varieties, th e white an d russ et . White p o t a t o e s are g r o w n for table c o n s u m p t i o n an d chips while r u s s e t s are us ed for french fries and pr ocess ing. P o ta to production is co nfined to a s e le ct n u m b e r of c o u n t i e s with M on tca lm an d Bay producing ov er o n e third of th e total. Michigan p o ta to p ro duction has t re n d e d gradually higher for t h e p a s t 21 y ear s. Both a c r e s h a r v e s t e d and yields h av e g r o w n an a v e r a g e an nua l rate of 0 . 6 2 % , with th e quantity of p o t a t o e s increasing on a v e r a g e 1 . 3 2 % per year. In t h e late eighties Michigan fa rm er s w e r e f aced with a n u m b e r of significant 83 ch all enges. In 1 9 8 6 h e a v y rains and flooding per sisted in central Michigan from m id -S e p te m b e r to mid-Oc tober. The result w a s an a b a n d o n m e n t of alm o s t one -fo urth of th e S t a t e ' s planted p o ta to a c r e a g e . Total a c r e s h a r v e s t e d declined from 5 7 , 8 0 0 a c r e s in 1 9 8 5 to only 4 2 , 0 0 0 a c r e s in 1 9 8 6 , this drop is highlighted in Figure 35. Then just before th e 1 9 8 7 planting s e a s o n t h e S t a t e ' s largest p ro c e s s i n g plant w a s close d in M ontca lm c o unty. As e x p e c t e d a c r e a g e planted declined sharply, d o w n 2 0 % from 1 9 8 6 , a s c o n t r a c t s w e r e no longer available for m a n y farmers. The yea r following th e plant closing, pr od uct io n w a s negatively im pacted by th e s t a t e w i d e d r o u g h t of 1988. Even with th e s e t b a c k s of th e late eighties, Michigan p o t a t o e s hav e m aintained a c o n s i s t e n t position of ranking 10th nationally with approximately 2 . 5 % of t h e market. P o t a t o e s w e r e 5 th in value of pro du ction g r o w t h for all Michigan field c r o p s. Value of pro du ction in creased steadily from a low of $ 2 3 million in 1 9 7 1 , to a p eak in 1 9 8 4 of $ 8 6 million, and to a level of $ 8 0 million in 1 9 9 0 . M os t of t h e g r o w t h in value of pro duct io n is at tributable to higher price per h u n dred weight. Price per h u n dred w e ig h t of all p o t a t o e s tr e n d e d higher at an annual a v e r a g e of 3 . 3 % for th e d e c a d e s of th e 7 0 ' s and 8 0 ' s . 84 ALL POTATOES; VALUE OF PRODUCTION 21 Y R T R E N D VALUE OF PRODUCTION 1970 TO 1990 $100 21 - YEAR $80 -- A verage: $ 5 5 ,8 3 4 ,6 2 8 High: $ 8 6 ,0 7 0 ,0 0 0 $20 L ow : $ 2 3 ,4 8 7 ,2 3 0 - A vg. Anl. C hg: 4 .4 5 % YEAR Actual F ig u re 3 4 - o - Linear T rend P o t a t o e s V a lu e o f P r o d u c tio n , 2 1 -Y ear T r e n d , 1 9 7 0 - 1 9 9 0 POTATOES; ACRES HARVESTED 21 Y R T R EN D 1970 TO 1990 A CRES H ARV ESTED 52 -• 21 - YEAR A verage: 4 4 ,3 1 4 High: 5 7 ,8 0 0 13 - Low : 3 3 ,0 0 0 88 Avg. Anl. Chg: 0 .6 2 % YEAR — Actual - o - Linear T rend ) Figure 3 5 P o ta to e s A c re s H a rv e s te d , 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 85 POTATOES; PRODUCTION PRODUCTION 21 YR TREND 1970 TO 1990 21 - YEAR 12 8 -• A verage: 1 0 .6 9 8 ,9 0 5 f \ (/> 0 6 - C _J o ,< ?= High: 1 5 .1 3 6 .0 0 0 64 - L ow : 8 .0 7 6 .0 0 0 32 - A vg . Anl. C hg: 1 .3 2 % 00 YEAR — Figure 36 Actual P o t a t o e s P r o d u c tio n , -© - Linear T rend 21 -Y ear T rend, 1970-1990 POTATOES; YIELD 21 YR T R E N D 1970 TO 1990 YIELD 300 21 - YEAR 240 UJ a. A verage: 240 y < 100UJ D. (f) § High: 272 120 - • o Q- Low: 60 - 211 90 YEAR — A ctual - o - Linear Trend Figure 3 7 P o ta to e s Yield, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 Avg. Anl. Chg: 0 .6 2 % 86 ALL POTATOES; PRICE PER Cwt. 21 YR TREND 1970 TO 1990 PRICE $0 5 21 - YEAR $6.8 - A verage: $ 5 .2 1 High: $8.20 L ow : $ 2 .4 7 $1.7 - A v g . Anl. C hg: 3 .3 1 % $ 0.0 YEAR — F ig u re 3 8 Actual - o - Linear Trend P o t a t o e s Price, 2 1 -Y e ar T r e n d , 1 9 7 0 - 1 9 9 0 Soybeans: S o y b e a n s are o n e of th e f a s t e s t growing field c r o p s in Michigan. Of t h e ten c r o p s reviewed in this section, s o y b e a n s w e r e first in t h e a v e r a g e an nu al p e r c e n t c h a n g e tre nd for quantity p r o duced 5 . 9 8 % , yield per a cr e 2 . 3 0 % , an d s e c o n d in t e r m s of ac r e s h a r v e s te d 4 . 1 0 % . S o y b e a n s are gro w n for their oil c o n t e n t an d utilization of the c r u s h e d by- pro duct for livestock feed b e c a u s e of th e high protein c o n t e n t . One 60 -p o u n d bushel of b e a n s normally yields a b o u t 12 p o u n d s of oil and 4 8 p o u n d s of meal for feed. Th e soy oil is u s e d in cook ing oils, margarine, salad oils, m e a t s u b s titu te s , paints, var nishes, a d h e s i v e s , an d m a n y other p r o d u c t s. Michigan e x p o r t s all of it's b e a n s to o th e r s t a t e s or o v e r s e a s b e c a u s e ther e ar e no p r ocess ing facilities in th e s ta te . S o y b e a n production g r e w at a fa st er p a c e during th e 7 0 ' s th a n th e mid 87 8 0 ' s but h a s regained it's m o m e n t u m in r e c e n t years. Total produc tion r e a c h e d a low of 10 million bu s hels in 1971 an d a high of 4 3 million bus he ls in 1 9 9 0 . Part of th e incr ea se in pr oduction oc c u r re d a s result of more ac r e s being planted. Acr es h a r v e s t e d g r e w from appro ximately 5 0 0 , 0 0 0 a c r e s in t h e early 7 0 ' s t o c o ns is tently over 1. 0 million a c r e s h a r v e s t e d t h r o u g h o u t th e 8 0 ' s . The yield per ac re in cr ea se d from an a v e r a g e of 21 b u s h e ls per acr e in 1971 to 3 8 b u s h e ls per acr e in 1 9 9 0 , an 8 1 % in crease. This w a s t h e largest ab s o lu t e p e r c e n t a g e yield incr ea se for all field c r o p s. Value of produc tion g r e w dramatically in th e 7 0 ' s from a low of $31 million in 1971 to over $ 2 3 9 million in 1 9 8 0 a 671 % incr ea se . In the 8 0 ' s value of pro duct io n leveled off reaching a high of $ 2 6 4 million in 1 9 8 3 an d $ 2 4 3 million in 1 9 9 0 . Soybeans are third in t e r m s of total value of pro duction behind c o r n and ha y in Michigan. The 2 1 -year g r o w th trend for value of pro du ction is an a v e r a g e an nu al increase of 6 . 7 2 % . 88 SOYBEANS; VALUE OF PRODUCTION 21 YR T R EN D 1970 T O 1990 VALUE OF PRODUCTION 21 - YEAR $240 -■ A verage: $ 1 5 3 ,8 5 4 ,2 1 5 High: $ 2 6 4 ,3 1 6 ,0 0 0 L ow : $ 3 1 ,2 6 2 ,5 0 0 $60 - - A v g . Anl. C hg: YEAR Linear T rend ■Actual Figure 3 9 6 .7 2 % S o y b e a n s V alu e o f P r o d u c t io n , 2 1 -Y ear T r e n d , 1 9 7 0 - 1 9 9 0 SOYBEANS; PRODUCTION 21 YR TREND 1970 TO 1990 PRO DU CTION 21 - YEAR 40 -• A verage: 2 6 ,4 3 2 ,3 3 3 n -■ X — n30 W 'fi 3 g CD = 20 High: 4 3 .3 2 0 .0 0 0 - L ow : 1 0 .2 5 0 .0 0 0 YEAR Actual - o - Linear T rend Figure 4 0 S o y b e a n s Production, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 Avg. Anl. Chg: 5 .9 8 % 89 SOYBEANS; ACRES HARVESTED 21 YR TREND 1970 TO 1990 A C R ES HARVESTED 1.350 ,000 21 - YEAR - A verage: 8 8 7 ,2 3 8 010-■ _ c < 8 3! o High: 1 , 2 1 0 ,0 0 0 L ow : 5 0 0 ,0 0 0 270 - A v g . Anl. C hg: 4 .1 0 % YEAR ■Actual F ig u re 4 1 Linear T rend S o y b e a n s A cres H arv ested , 21-Y ear T rend, 1 9 7 0 - 1 9 9 0 SOYBEANS; YIELD 21 YR TREND 1970 TO 1990 YIELD 21 - YEAR 32 -• 24 - A verage: 29 - UJ High: 38 L ow : 0- 21 YEAR — Actual - o -E x p o n e n tia l Trend Figure 4 2 S o y b e a n s Yield, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 Avg. Anl. Chg: 2 .3 0 % 90 SOYBEANS; PRICE PER BUSHEL 21 Y R T R EN D 1970 TO 1990 PRICE $9 5 21 - YEAR $ 6.8 3 $5.1 m UJ CL uj - A verage: $ 5 .6 2 - High: $ 7 .8 2 $3.4 -• Low: $ 2 .8 4 CL SI 7 - A v g . Anl. C hg: 1 .5 9 % $0 0 YEAR — F ig u re 4 3 Actual - o - Linear Trend S o y b e a n s Price, 2 1 -Y e ar T r e n d , 1 9 7 0 - 1 9 9 0 Sugarbeets: S u g a r b e e t s ar e g r o w n primarily for their s u g a r c o n t e n t in Michigan. H owev er , a small portion of t h e b e e t s is used a s feed in livestock o p e r a tio n s. S u c r o s e is s p u n from th e b e e t s in a centrifu ge leaving a pulp b y ­ p r o d u c t t h a t is co m b in e d with o t h e r feed ingredients. Almost all b e e t s in Michigan are pr o d u c e d under c o n tr actu al a g r e e m e n t s with p r o c e ss in g plants. The t o p five pro du ction c o u n ti e s are Tuscola, Huron, Gratiot, S aginaw , and Bay all in th e T h u m b an d Bay regions of t h e s ta t e . T h e s e five c o u n tie s a c c o u n t for over 8 0 % of t h e s t a t e ' s annual s u g a r b e e t o u t p u t. In t h e United S t a t e s , t h e pro du ction of s u g a r c a n e and s u g a r b e e t s , is split a b o u t half and half. Th e s u g a r b e e t industry in Michigan co n ti n u e s to g r o w at a record pace. 91 In 1 9 9 0 Michigan p a s s e d North Dakota as th e fourth largest produ cing s ta t e a c c o u n t i n g for a lm o st 12 p e r c e n t of th e national o u tp u t. Th e t r e n d 64 for s u g a r b e e t pro du ction has b e e n steadily u p w a r d during t h e d e c a d e s of th e 7 0 ' s a nd 8 0 ' s . In t e r m s of Michigan field cr op production, s u g a r b e e t s tied hay with th e third f a s t e s t a v e r a g e annual g r o w th rate of 3 . 2 6 % , just behind s o y b e a n s a nd barley. Production in total t o n s incre ased from b e lo w 1.5 million in the early 7 0 ' s to a b o v e 3 . 2 million in 1 9 9 0 . Th e incr ea se in pro du ction is due a lm o st exclusively to a rise in a c r e s h a r v e s t e d . Acres h a r v e s t e d h a s e x p a n d e d an a v e r a g e of 3 . 0 5 % per ye ar for th e last 21 ye ar s. Yields for s u g a r b e e t s h av e remained flat, growing an a v e r a g e of only 0 . 2 0 % per year , last a m o n g th e te n field crops. S u g a r b e e t s hav e n o w p a s s e d w h e a t an d dry b e a n s with reg ar ds to total value of production. Given a s t e a d y rise in b e e t prices per ton and t h e ex p a n s i o n of a c r e s harvested, th e value of produc tion has incr eased rapidly. T he 2 1 -year g r o w th trend for value of prod uction is expon en tial, s e e Figure 4 4 , increasing at an a v e r a g e annual rate of 7 . 6 9 % , first for all field cr ops . Total value of production has incr ea se d from a low of app ro xima tely $ 1 9 million in 1971 to a high of over $ 1 2 5 million in 1 9 9 0 . 64 Note: the production trend for sugarbeets is exponential. 92 SUGARBEETS; VALUE OF PRODUCTION 21 Y R TRE N D 1970 TO 1990 VALUE OF PRODUCTION $150 21 - YEAR $120 - A verage: $ 6 0 ,8 3 5 ,9 7 6 $60 -■ $30 - High: $ 1 2 5 ,0 8 7 ,8 0 0 Low : $ 1 8 ,9 6 1 ,0 0 0 A v g . Anl. C h g: 7 .6 9 % YEAR — Fig u re 4 4 Actual -o -E x p o n e n tia l T rend S u g a r b e e t s V a lu e o f P r o d u c tio n , 2 1 -Y ear T r e n d , 1 9 7 0 - 1 9 9 0 SUGARBEETS; ACRES HARVESTED 21 YR TREND 1970 T O 1990 ACRES H A RV ESTED 180 21 - YEAR £ - 3 108 A verage: 1 0 4 ,8 1 4 - High: 1 5 7 ,0 0 0 36 - L ow : 8 0 ,4 0 0 YEAR Actual -© - E xponential Trend Figure 4 5 S u g a r b e e t s A c res H a rv ested , 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 Avg. Anl. Chg: 3 .0 5 % 93 SUGARBEETS; PRODUCTION 10 YR TR EN D 1980 TO 1989 PRODUCTION 3,500 21 - YEAR 2,000 -• A verage: 1 ,9 9 3 ,9 5 2 g - S 2.100 - I—w High: 3 .2 6 6 .0 0 0 L ow : 1 .3 6 4 .0 0 0 700 - A v g . Anl. C hg: 3 .2 6 % YEAR Actual F ig u re 4 6 -o- Exponential Trend S u g a r b e e t s P r o d u c ti o n , 2 1 -Y ear T r e n d , 1 9 7 0 - 1 9 9 0 SUGARBEETS; YIELD 21 YR TREND 1970 TO 1990 YIELD 20 21 - YEAR - - A verage: 19 LU U £LL High: z 21 10 - Low : 17 YEAR — Actual - o - Linear T rend Figure 4 7 S u g a r b e e ts Yield, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 Avg. Anl. Chg: 0 .2 0 % 94 SUGARBEETS; PRICE PER TON 21 YR T R E N D PRICE 1970 TO 1990 $60 21 - YEAR $48 -• A verage: $ 2 9 .8 High: $ 4 7 .5 O $24 - • aCL Low : $ 12. 2 $12 - A v g . Anl. C hg: 3 .2 1 % YEAR ■Actual F ig u re 4 8 - o - Linear T rend S u g a r b e e t s Price, 2 1 -Y e a r T r e n d , 1 9 7 0 - 1 9 9 0 W h e a t: Michigan g r o w s t w o primary varieties of w h e a t , sof t white w in ter and s o f t red. Soft white winter w h e a t a c c o u n t s for ap proxim a te ly 8 0 % of th e w h e a t g r o w n while sof t red a c c o u n t s for th e remaining 2 0 % . Soft red w h e a t is us ed primarily by m a n u f a c t u r e s for hea vy d o u g h found in c a k e mixes, d o u g h n u t s , an d cookies. T h e sof t wh ite winter w h e a t is milled into a lightte x tu r e d d o u g h u s e d in b r e a k f a s t cereals, pie crust, an d pastries. W h e a t is g r o w n in a l m o s t ever y c o u n t y in th e s ta te . Th e t h u m b ar ea is t h e major pro duction region. Four counties, Sanilac, Huron, Lapeer, and T u s co la a c c o u n t for appr oximate ly o n e sixth of th e s t a t e ' s o u tp u t . During the d e c a d e s of th e 7 0 ' s an d 8 0 ' s w h e a t production t re n d e d slowly u p w a r d , at an average annual rate of 2.11 %. Acres h a r v e s t e d vacillated greatly, ranging 95 from a high of 9 4 0 , 0 0 0 a c r e s in 1 9 7 4 to a low of 4 0 0 , 0 0 0 in 1 9 8 7 , s e e Figure 50. Th e calculated trend for a c r e s h a r v e s te d is an a v e r a g e annual c h a n g e of 0 . 3 5 % . The major influence for th e i ncrease in pro du ction c o m e s from higher yields. W h e a t yields improved co n s is te n t ly during t h e 7 0 ' s and 8 0 ' s . W h e a t yields in crease d in 12 of th e 21 y e a r s of analysis. The 21 year tre nd is an a v e r a g e an nual rate of 1 . 9 6 % , which w a s third a m o n g field crop s Price per bu shel h o w e v e r , did not kee p p a c e with o t h e r field crops. A bushel of w h e a t in crease d at an a v e r a g e annual rate of 1 . 4 0 % , only corn incr ea se d mor e slowly a t 1 . 3 2 % . T h e tre nd for value of pr oduct io n w a s gradually up, c e n t e r e d a r o u n d wide an n u al flu ctuations s e e Figure 4 9 . Value of production g r e w at an a v e r a g e annual rate of 2 . 8 7 % , ranked s e v e n t h for field cr op s. WHEAT; VALUE OF PRODUCTION 21 Y R T R E N D 1970 TO 1990 $160 $120 21 - YEAR -■ A verage: $ 9 1 ,5 9 8 ,4 1 4 (/> $96 - eo O 2 VALUE OF PRO DU CTIO N High: $ 1 4 5 ,0 0 8 ,0 0 0 $64 L ow : $ 2 3 ,8 7 8 ,8 0 0 $32 - Avg. Anl. Chg: 2 .8 7 % YEAR — Actual Linear T rend Figure 4 9 W h e a t Value of P rodu ction, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 96 WHEAT; ACRES HARVESTED 21 YR TRE N D 1970 TO 1990 ACRES HARVESTED 1,000 21 - YEAR 800 -■ a -S A verage: 6 8 1 ,8 1 0 600 - y** tA S High: 9 4 0 .0 0 0 kfc. 400' i200 Low: 4 0 0 .0 0 0 - A vg . Anl. Chg: 0 .3 5 % YEAR — w — M in Actual -© - Exponential Trend ..n Figure 5 0 W h e a t A c r e s H a r v e s t e d , 2 1 -Y ear T r e n d , 1 9 7 0 - 1 9 9 0 WHEAT; PRODUCTION 21 YR TREND 1970 TO 1990 PRODUCTION 21 - YEAR 40 -• in _i LU 30 - A verage: 3 0 ,5 1 0 ,7 1 4 20 -■ High: 4 5 .6 0 0 .0 0 0 10 - o Low : 1 6 .4 0 0 .0 0 0 YEAR Actual - o - Linear T rend Figure 51 W h e a t Production, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 Avg. Anl. Chg: 2.11 % 97 WHEAT; YIELD 21 Y R T REN D 1970 T O 1990 YIELD 21 - YEAR 52 -• A verage: 44 £39- High: 60 LD CL m uj 26 -■ L ow : 35 A v g . Anl. C hg: 1 .9 6 % YEAR — F ig u re 5 2 Actual -© - Linear Trend W h e a t Yield, 2 1 -Y ear T re n d , 1 9 7 0 - 1 9 9 0 WHEAT; PRICE PER BUSHEL 21 Y R T REN D 1970 T O 1990 PRICE 21 - YEAR $4 -■ A verage: $ 2 .9 4 3 $3 CD High: $ 4 .3 0 a. UJ CL ill $2 - $1 L ow: $ 1 .3 4 - Avg. Anl. Chg: 1 .4 0 % YEAR ■Actual - o - Linear T rend Figure 5 3 W h e a t Price, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 98 General Livestock Overv iew This s e c t io n re view s th e important livestock t r e n d s of price, yield, value of prod uction , n u m bers, an d quantity pr o d u c e d for e a c h of M ichigan 's t o p livestock s e c t o r s . 65 Figure 5 4 is an a g g regation of all livestock s e c t o r s and their value of production. Livestock value of pro du ction h a s g r o w n at an a v e r a g e an nu al rate of 3 . 7 2 % during th e d e c a d e s of t h e 7 0 ' s and 8 0 ' s . The $1 billion barrier w a s broken in 1 9 7 9 , by 1 9 9 0 value of p roductio n had risen to $ 1 . 3 7 billion. Following Figure 5 4 is Table III. Table III is a tre nd s u m m a r y of t h e livestock s e c t o r s ranked by the a v e r a g e an nua l p e r c e n t c h a n g e s for e a c h c a t e g o r y (price, n u m b e r of head , etc.). TOTAL LIVESTOCK; VALUE OF PRODUCTION 21 YR TREND 1970 TO 1990 VALUE OF PR OD U CTIO N $ t ,500 1 8 - YEAR $ v) _ Oz 1,200 - $900 - A verage: $ 1 ,0 5 6 ,0 5 5 ,5 6 1 $600 - High: $ 1 ,3 6 5 ,9 0 6 ,0 0 0 $300 - L ow : $ 6 7 8 ,4 0 0 ,9 0 6 A v g . Anl. Chg: 3 .7 2 % YEAR Note: d a ta s e r ie s s ta r ts in 1973 ■Actual Linear Trend F ig ure 5 4 T o ta l L iv e s to c k V alue o f P r o d u c tio n , 1 8 Y e a r T r e n d , 1 9 7 3 1990 65 The top Michigan livestock sectors selected for analysis were based on their value of production. Note: the category of "honey" which is considered to be livestock, was not selected for analysis because of large gaps in Michigan Agricultural Statistical Service time series data. 99 T a b le III T r e n d S u m m a r y fo r L iv e s to c k & Po u ltry , C o m m o d i t y R a n k b y A v e r a g e A n n u a l % C h a n g e for 21-Y ears, 1 9 7 0 - 1 9 9 0 TREND S U M M A R Y FOR LIVESTOCK & POULTRY C O M M O D IT Y RANK BY AVERAGE ANNUAL % CHANGE FOR 2 1 -Y e a rS FROM 1 9 7 0 - 9 0 N u m b e r of H e a d Rank 1 2 3 4 5 6 7 8 9 P r o d u c tio n C o m m o d ity % C hg . Rank T urkeys H ogs-pigs Broilers C h ic k e n s H e n s - p u lle ts Milk c o w s All C a ttle B eef S h eep -lam b s 9 .4 3 % 3 .5 4 % 1 .0 2 % -0 .3 6 % -0 .4 1 % -1 .0 2 % -1 .2 8 % -1 .9 5 % -4 .0 7 % 1 2 3 4 5 6 7 8 A verage 1 2 1 0 .7 4 % 5 .1 0 % 0 .9 0 % 0 .5 1 % 0 .3 2 % 0 .1 1 % -0 .6 1 % -1 .6 4 % A verage 1 .9 3 % Price C o m m o d it y % Chg. R ank Milk p e r c o w E g g s p e r layer 1 .9 7 % 0 .7 5 % 1 2 3 4 5 6 7 8 9 A v erage % Chg. T urkeys H o g s - p ig s Milk S h eep -lam b s H e n s - p u l le ts (e g g s) C h ic k e n s All C a ttle Broilers 0 .5 4 % Yield Rank C o m m o d ity 1 .3 6 % C o m m o d it y % C hg. C a lv e s Milk S h eep -lam b s C a ttle Broilers T urkeys Eggs H o g s - p ig s C hickens 3 .8 4 % 3 .8 1 % 3 .6 2 % 3 .4 3 % 2 .6 7 % 1 .5 1 % 1 .4 1 % 1 .0 7 % -0 .3 8 % A v e rag e 2 .3 3 % 10 0 T a b le III ( C o n tin u e d ) T rree n d S u m m a r y fo r L iv e s to c k & P o u ltry , C o m m o d i t y R a n k by A v e r a g e A n n u a l % C h a n g e fo r 2 1 -Y ears, 1 9 7 0 - 1 9 9 0 TREND S U M M A R Y FOR LIVESTOCK & POULTRY C O M M O D ITY RANK BY A VERAGE ANNUAL % CHAN G E FOR 2 1 -Y e a rS FROM 1 9 7 0 - 9 0 V alue o f P ro d u c tio n Rank C o m m o d ity % Chg. 1 2 3 4 5 6 7 8 T urkeys H ogs-pigs Milk S h eep -lam b s All C a ttle Eggs B roilers C h ick en s 1 2 .5 7 % 6 .0 3 % 3 .8 2 % 2 .6 2 % 2 .3 3 % 1 .6 7 % 0 .5 6 % -1 .0 8 % A verage 3 .5 6 % 101 Dairy: Dairy is clearly Michig an 's m o st important farm enterprise. T h r o u g h o u t t h e 7 0 ' s and 8 0 ' s dairy c a s h rece ipts c o n s is te n tl y a c c o u n t e d for on e - fo u r th of the s t a t e ' s total farm receipts. Nationally; Michigan ranks 7th in c o w n u m b e r s and milk o u t p u t , 66 an d 10th in pro du ction per c o w . 67 Not surprisingly, Michigan is also a national leader in p r o c e s s e d milk p r o d u c t s s u c h as, c h e e s e s ranking 13th, ice cre a m 10th, butt er an d ice milk 8th, an d nonf at dry milk an d dry buttermilk 4t h. Six c o unti es in Michigan p roduce ap proxim a te ly one-third of th e s t a t e ' s total o u tput. The t o p producing c o u n t i e s ar e S h i a w a s e e , Huron, Clinton, Allegan, Ionia, an d O t ta w a . The dairy industry nationwide has bee n under going significant structural c h a n g e s . Milk pro duct io n levels have steadily incr ea se d while th e n u m b e r of c o w s h a s declined. In Michigan since 1 9 7 0 th e n u m b e r of c o w s h a s dr op ped from 4 3 3 , 0 0 0 to 3 4 4 , 0 0 0 in 1 9 9 0 (a decline of 2 0 . 6 % ) , t h e l o w e s t level s in ce 1 8 8 2 . Meanwhile total o u t p u t h a s incr eased an a v e r a g e an nual a m o u n t of 0 . 9 0 % , ex p a n d in g from approximately 4 . 6 billion p o u n d s of fluid milk per y ear in t h e early 7 0 ' s to over 5 . 3 billion p o u n d s in th e late 8 0 ' s . Th e re aso n for t h e no ticeable production d ivergen ce is the rem arkable s u rg e in yield per c o w . Th e 21 ye a r tre nd for Michigan o u t p u t per c o w is exponential, increasing at an a v e r a g e annual rate of 1 . 9 7 % , s e e Figure 58. Over t h e last t w o d e c a d e s yields h av e increase d in 1 7 of th e 2 0 year s, t w o of th e d o w n 66 A n a t i o n a l p r o d u c t i o n s h a r e r a n g i n g f r o m 3 . 5 % t o 4 . 0 % . 67 M i c h i g a n ' s m ilk o u t p u t p e r c o w is s e c o n d o n l y t o C a l i f o r n i a a m o n g t h e t o p p ro d u c in g s t a te s . 102 y e a r s o c c u r re d in 1 9 7 3 an d 1 9 7 4 , w h e n P.B.B. w a s found in dairy feed. In 1 9 7 0 t h e per c o w yield w a s 1 0 , 6 2 8 p o u n d s of milk per year , by 1 9 9 0 the yield had e x p a n d e d to 1 5 , 2 1 2 p o u n d s of milk, a g r o w t h of 4 3 . 1 % . Several f a c to r s h a v e influenced the higher milk pro ductio n per c o w . Three of th e m ost im port ant r e a s o n s are gen et ic im pro vem en ts , m a n a g e m e n t an d technological innovations. Breeding pra ctices have b een us ed to improve a c o w s ability to c o n v e r t feed ration c o n c e n t r a t e more efficiently. C o w s are n o w able to tr a n s f o r m higher levels of c o n c e n t r a t e into co rre spondingly higher levels of milk pr oduc tion. The Michigan Agricultural Statistic Service rep or ts that, " c o n c e n t r a t e s in feed rations hav e bee n incre ased by m or e t h a n 4 0 pe rcent s in ce 1 9 7 0 . " During this time period th e conce ntrate- milk o u t p u t ratio has rem ained s ta b le a s total milk o u tp u t rose. T w o im po rta nt e v e n t s occurred in th e 8 0 ' s which im p a c te d Michigan's dairy industry. Th e first e v e n t w a s the e n a c t m e n t of th e Dairy Termination Program (DTP), April 1, 1 9 8 6 . The prog ram w a s initiated by t h e federal g o v e r n m e n t in th e 1 9 8 5 Food Security Act (Farm Bill). The goal of th e U.S.D.A. w a s to r ed u ce th e U.S. milk surplus by 12 billion p o u n d s by Octob er 1, 1 9 8 7 . Th e DTP im pac ted all s e g m e n t s of th e s t a t e ' s industry; milk haulers, pro c e s s in g plants, inputs suppliers, service firms and of c o u r s e t h e farmers. T he n u m b e r of Michigan c o w s declined approximately 1 0 % during th e 1 8 - m o n th progra m . Michigan Grade A dairy h erds also d r o p p e d from 6 , 8 0 0 in 1 9 8 5 to only 5 , 3 0 0 in 1 9 8 7 . Even with th e large drop in milk c o w s and farm 103 n u m b e r s , total milk pro duction fell only 6 % from 1 9 8 5 68 to 1 9 8 7 . Th e oth er im port ant fac tor t h a t influenced th e dairy industry w a s th e d r o u g h t of 1 9 8 8 . As m en tio n ed ab o v e , th e n u m b e r of c o w s an d farm s declined a s a result of t h e DTP, th e 1 9 8 8 d r o u g h t led to an additional culling of less productive cows. S hort su pplies of feed ration inputs s u c h a s corn, o a t s and hay, and higher feed c o s t s initiated t h e culling p r o c e ss . Th e U.S. C o n g r e s s p a s s e d the Dis as ter A s s i s ta n c e Act of 1 9 8 8 in late A u g u s t to provide relief to the farm ers. Fluid milk value of production of increased steadily t h r o u g h the 7 0 ' s an d into t h e early 8 0 ' s . H ow ever, from 1 9 8 3 to 1 9 8 8 value of production fell a p proxim a te ly 1 3 . 7 % , from $ 7 5 4 million to $ 6 5 0 million. During this period both t h e price of milk per Cw t. and total quantity of milk p r o d u c e d declined. T h e s e declines o c c u r re d during th e federal g o v e r n m e n t s dairy diversion and dairy termination pr ogra m s. O n ce th e p ro g ram s w e r e lifted, th e previous t r e n d s for value of production, price and qu an tity of milk pr o d u c e d regained their trajectory. By 1 9 9 0 , th e who le sale price of milk per h u n d r e d w e i g h t 69 r e a c h e d an all-time high of $ 1 4 . 1 0 an d pr oduction w a s only 9 . 9 % from th e all-time s e t in 1 9 6 4 . 68 In 1 9 8 5 p r o d u c t i o n r e a c h e d 5 . 5 7 b illio n p o u n d s o f m ilk , j u s t s h y o f t h e a l l - t i m e r e c o r d o f 5 . 7 5 r e a c h e d in 1 9 6 4 . 69 N o t e : t h e 2 1 y e a r g r o w t h r a t e t r e n d f o r m ilk p r i c e s w a s a n a v e r a g e a n n u a l r a t e o f 3 . 8 1 % , t h i s w a s t h e s e c o n d l a r g e s t g r o w t h r a t e f o r all l i v e s t o c k p r i c e s . 104 TOTAL MILK; VALUE OF PRODUCTION 21 YR TREND 1970 TO 1990 VALUE OF PRODUCTION $900 1 8 - YEAR $720 - A verage: $ 5 9 9 ,1 0 5 ,3 8 9 High: $ 7 5 3 ,5 7 8 ,0 0 0 Low : $ 3 3 3 ,3 2 8 ,0 0 0 $180 -■ A v g . Anl. Chg: 3 .8 2 % YEAR Note: d a ta s e n e s s ta r ts in ■Actual 1973 Linear Trend F ig u re 5 5 T o ta l Milk V a lu e of P r o d u c tio n , 1 8 Y ear T r e n d , 1 9 7 3 - 1 9 9 0 MILK COWS; NUMBERS 21 YR T R E N D 1970 T O 1 9 9 0 NUMBER 21 - YEAR 384 - A verage: 3 9 5 ,5 7 1 288 §LLI High: 4 3 3 .0 0 0 I Low: 3 4 4 .0 0 0 96 - Avg. Anl. Chg: -1 .0 2 % YEAR Actual - o - Linear Trend Figure 5 6 Milk C o w N u m b ers, 21-Y ear Trend, 1 9 7 0 - 1 9 9 0 105 TOTAL MILK PRODUCED 21 YRTREND 1970 TO1990 PRODUCTION 21 - YEAR 56 -- A verage: 4 ,9 9 0 ,5 7 1 ,4 2 9 High: 5 ,5 6 8 ,0 0 0 ,0 0 0 Low : 4 ,3 5 0 ,0 0 0 ,0 0 0 CL A v g . Anl. C hg : 0 .9 0 % YEAR — Actual - o - Linear T rend F ig u re 5 7 T o ta l Milk P r o d u c e d , 2 1 -Y ear T re n d , 1 9 7 0 - 1 9 9 0 AVERAGE OUTPUT PER COW 21 YEARTREND 1970 TO1990 YIELD 21 - YEAR 96 A verage: 1 2 ,6 9 8 - O ro IT) % High: 1 5 ,2 1 2 a o ! h 64 - o D. 32 L ow : 1 0 ,4 0 7 - 00 YEAR Actual -© - Exponential Trend Figure 5 8 A verage O u tp u t per C ow , 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 Avg. Anl. Chg: 1 .9 7 % 106 ALL MILK WHOLESALE; PRICE PER Cwt. 21 YEAR TREND 1970 TO 1990 PRICE $16.0 21 - YEAR $ 12 .0 -■ A verage: $ 1 0 .9 3 5 <-> $ 9 .8 - tt High: $ 1 4 .1 0 LU CL UJ y cc $8.4 -■ L ow : $ 5 .8 1 CL $3.2 - A vg . Anl. C hg: 3 .8 1 % $0 0 YEAR Actual -©- Linear Trend Fig u re 5 9 All Milk W h o le s a le Price, 2 1 -Y e a r T re n d , 1 9 7 0 - 1 9 9 0 H ogs an d Pigs: Th e hog an d pig industry is th e o n e of th e f a s t e s t 70 growing livestock s e c t o r s in th e s t a t e in te r m s of g r o w t h in animal n u m b e r s, value of pr odu ction, an d level of o u tput. From 1 9 7 0 to 1 9 9 0 th e trend for hog an d pig n u m b e r s e x p a n d e d exponentially at an a v e r a g e annual rate of 3 . 5 4 % , s e e Figure 61. Th e u p w a r d tre nd in hog n u m b e r s is highlighted by a 21 year high r e a c h e d in 1 9 8 7 of 1 . 3 5 million head . This w a s th e s e c o n d largest hog total reco rd ed , c o m p a r e d to th e all-time high s e t in 1 9 4 4 of 1 . 4 0 million head . The p o u n d a g e of pork pr o d u c e d also increased proportionally. P o u n d s pr o d u c e d 70 T h e t u r k e y i n d u s t r y is t h e f a s t e s t g r o w i n g l i v e s t o c k s e c t o r in M i c h i g a n f o r t h e d e c a d e s of th e 7 0 's a n d 8 0 's . 107 g r e w at an a v e r a g e an nu al rate of 5 . 1 0 % . 71 Total pork p o u n d s doub led from a level of 2 4 0 million p o u n d s in the mid 1 9 7 0 ' s to 4 8 0 million p o u n d s in 1 9 9 0 . Hog prices h a v e t re n d e d gradually higher, increasing at an an nual rate of 1 . 0 6 % , n e x t to last for th e livestock co mmod ities ranked. Price per Cwt. ranged from a low of $ 2 4 . 5 0 to a high of $ 6 1 . 0 0 , o f te n following th e classic four y e a r hog; price-production cycle. The m o d e s t trend to w a r d higher hog prices coupled with higher p o u n d a g e output, yielded a c o m m e n s u r a t e incr ea se in t h e value of pr oduction. Value of production climbed from a level of $ 8 9 million in 1 9 7 4 to a 21 y e a r high of $251 million in 1 9 9 0 , up 1 8 2 % . Almost one-half of th e s t a t e ' s hogs and pigs are g r o w n in th e S o u t h w e s t region. J u s t th re e c o unti es in th e S o u t h w e s t region, Cass, Allegan, an d O t t a w a a c c o u n t for approximately 3 0 % of th e s t a t e total. In 1 9 9 0 Michigan ranked 1 1th in th e county for t h e n u m b e r of h ead of h o g s and pigs with 2 . 3 % of th e total, Iowa is the leading s ta t e . Michigan is even more p rom in ent in t e r m s of t h e a m o u n t of pork sla u g h te r e d , ranking 5th nationally. Hogs ar e ship ped to Michigan from Canada and t h r o u g h o u t t h e m id-w e st to be processed. 71 S e c o n d in p e r c e n t a g e g r o w t h r e l a t i v e t o t u r k e y s . 108 ALL HOGS & PIGS; VALUE OF PRODUCTION 21 YR TREND 1970 TO 1990 VALUE OF PRODUCTION $275 $220 1 8 - YEAR - A verage: $ 1 5 3 ,0 0 0 ,7 2 2 High: $ 2 5 1 ,3 5 9 ,0 0 0 L ow : $ 8 8 ,9 0 3 ,0 0 0 $55 -• A v g . Anl. C hg: 6 .0 3 % YEAR Note: d a ta s e r ie s s ta r ls in ■Actual 1973 F ig u re 6 0 1990 - o - Exponential Trend All H o g s & P igs V a lu e of P ro d u c tio n , 1 8 Y e a r T re n d , 1 9 7 3 - ALL HOGS AND PIGS; NUMBERS 21 YR T R EN D 1970 TO 1990 NUMBER 1,500 1,200 21 - YEAR - • 900 - A verage: 9 6 9 ,1 0 0 600 -■ High: 1 .3 5 0 .0 0 0 x o £. L ow : 6 4 0 .0 0 0 300 -• YEAR Actual Figure 61 - o - Exponential T rend All H og s & Pigs N um bers, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 Avg. Anl. Chg: 3 .5 4 % 109 ALL HOGS AND PIGS; PRODUCED 21 YR T R E N D 1970 TO 1990 PRODUCTION 600 1 8 - YEAR 480 - A verage: 3 3 9 ,4 5 7 ,7 7 8 UJ 360 - High: 4 8 0 .8 0 9 .0 0 0 ac 5 z 240 Low: 2 0 8 .1 2 4 .0 0 0 120 - A vg . Anl. C hg: 5 .1 0 % Note YEAR d a ta s er ie s s ta r ts in 1979 — F ig u re 6 2 Actual -o-Exponential Trend All H o g s & P igs P r o d u c t io n , 1 8 Y ear T re n d , 1 9 7 3 - 1 9 9 0 ALL HOGS & PIGS; PRICE PER Cwt. 21 YEAR TREND 1970 TO 1990 PRICE $75 21 - YEAR $60 - A verage: $ 4 4 .1 6 High: $ 6 1 .0 0 UJ y $3D -■ Low: $ 2 4 .5 0 $15 - Avg. Anl. Chg: 1 .0 7 % YEAR ■Actual Linear T rend Figure 6 3 All H ogs & Pigs Price, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 110 All Cattle an d C a l v e s :72 As descri bed in th e f o o tn o t e belo w, t h e cattle and ca l v e s classification includes a n u m b e r of s u b g r o u p s s u c h a s milk c o w s 73 and b e e f c o w s . T h e n u m b e r of cattle an d calves in th e s t a t e h a v e b e e n steadily falling. T he 2 1 - y e a r trend is an a v e r a g e annual decline of 1 . 2 8 % , s e e Figure 65. In 1 9 9 0 total cattle a n d calve num bers s to o d at 1.2 million h e a d , this w a s th e l o w e s t level since 1 9 0 2 . The num ber of hea d record high w a s s e t in 1 9 4 4 74 at 2 . 0 4 million. Beef c o w num be rs h av e also b e e n in a d o w n w a r d tra jector y in th e d e c a d e s of th e 7 0 ' s and 8 0 ' s . In th e early 7 0 ' s th e nu m ber of b e e f c o w s ro se rapidly from 1 7 0 , 0 0 0 head in 1 9 7 0 to a p e a k of 2 3 9 , 0 0 0 75 h ead in 1 9 7 7 . Since 1 9 7 7 , beef c o w num bers fell 4 5 % , to 1 3 1 , 0 0 0 in 1 9 9 0, s e e Figure 6 9 . Total pr od uction , in pound s, declined for all c attl e and calves but not as rapidly a s th e n u m b e r of head. Production fell an a v e r a g e annual rate of 0 . 6 1 % , only broilers p o s te d a larger pro du ction rate decline, s e e Table III. Prices for both cattle a n d ca lv es rose. Calve prices in c r e a se d an a v e r a g e ann ua l a m o u n t of 3 . 8 4 % , hig h est for all of th e com m odities. Th e price per 72 The cattle and calves classification includes the following categories; (1) cows and heifers that have calved (beef cows and milk cows), (2) heifers, 500 pounds and over, (3) steers, 500 pounds and over, (4) bulls, 500 pounds and over, (5) calves, less than 500 pounds. 73 Milk co ws are described in greater detail in the dairy section. As a proportion of the number of cattle and calves in the state, dairy cows constitute approximately 29% of the total. 74 This was during World War II when the U.S. and it’s Allies required larger amounts of food supplies to feed the troops. 75 This is a all-time high. 111 C w t. climbed from t h e $ 3 5 rang e in th e early 7 0 ' s to alm o s t $ 1 0 0 in 1 9 9 0 . Cattle prices ro se from t h e $ 2 5 per Cw t. range, to a b o v e $ 6 0 per Cw t. in 1990. Th e value of pr oduct io n in cr eased m o destly, d u e to th e higher prices, d e s p i t e t h e decline in livestock n u m b e r s. Value of pr odu ct io n e x p a n d e d an a v e r a g e an nu al a m o u n t of 2 . 3 3 % , to a p proxim a te ly $ 2 5 0 million a y e a r in the late 1 9 8 0 ' s . Cattle and calve op er atio n s are primarily c o n c e n t r a t e d in th e East Central (Huron an d Sanilac counties) an d S o u t h w e s t (Allegan and O t t a w a co unties) regions of t h e s ta t e . T h e s e four c o u n t i e s a c c o u n t e d for 2 0 % of th e s t a t e ' s total n u m b e r of animals in 1 9 9 0 . Michigan is not c o n s id e re d a significant p r o d u c e r in th e cattle and calve industry. Th e s t a t e ranks 3 0 t h in th e c o u n t r y in te r m s of c a s h receipts from cattle an d calves, with only 0 . 8 8 % of a s h a r e of th e total. 112 CATTLE & CALVES; VALUE OF PRODUCTION 21 YR TREND 1970 TO 1990 VALUE OF PRODUCTION $300 1 8 - YEAR $240 - A verage: $ 2 1 2 ,8 1 6 ,6 1 1 High: $ 2 6 2 ,0 9 0 ,0 0 0 Low: $ 1 5 9 ,5 6 9 ,0 0 0 $60 - A vg . Anl. C hg: 2 .3 3 % YEAR Note, d a ta s c r i e s s ta r ts in 1973 ■Actual Figure 6 4 1990 Linear Trend C a ttle & C a lv e s V a lu e of P r o d u c tio n , 1 8 Y e a r T re n d , 1 9 7 3 - ALL CATTLE AND CALVES; NUMBERS 21 Y R TREN D 1970 TO 1990 NUMBER 1,800 21 - YEAR 1,440 - • A verage: 1 ,4 2 1 ,0 4 8 ,080 - High: 1 .5 8 0 .0 0 0 9 UJ X i= 720 Low : . 1 200.000 360 - Avg. Anl. Chg: -1 . 2 8 % YEAR ^ — Actual - o - Linear T rend Figure 6 5 All Cattle & C alves N um bers, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 113 ALL CATTLE AND CALVES; PRODUCED 21 YR T R EN D PRODUCTION 1970 T O 1990 BOO 1 8 - YEAR 460 - - A verage: 4 5 2 ,2 0 6 ,3 8 9 UJ 360 - (OS H igh: 5 1 3 .7 1 5 .0 0 0 240 -■ Low: 3 5 6 .8 6 5 .0 0 0 120 - A v g . Anl. Chg: -0 .6 1 % YEAR Note; d a ta s e r ie s s ta r ts in ^ — Actual F ig ure 6 6 - o - L in e a r Trend All C a ttle & C a lv e s P r o d u c tio n , 1 8 Y ear T r e n d , 1 9 7 3 - 1 9 9 0 CATTLE; PRICE PER Cwt. 21 YR TREND 1970 TO 1990 PRICE $66 0 21 - YEAR $52 0 - A verage: $ 4 4 .3 2 <-> $39.6 - QL UJ CL High: $ 6 3 .2 0 Hi y $26 4 - L ow : $ 2 5 .8 0 $13.2 - - $00 88 YEAR Actual - o - Linear Trend Figure 6 7 Cattle Price, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 Avg. Anl. Chg: 3 .4 3 % 114 C A L V E S ; P R IC E P E R Cwt. 21 YR TREND 1970 TO 1990 PRICE $120 21 - YEAR $96 t C t LU u A verage: $ 6 0 .1 0 $72- - High: $ 9 9 .0 0 Q. UJ y $48-- o; a. c Low: $ 3 0 .4 0 $24 -• A vg . Anl. Chg: 3 .8 4 % 82 YEAR Actual F ig u re 6 8 - o - Exponential Trend C a lv e s Price, 2 1 -Y ear T re n d , 1 9 7 0 - 1 9 9 0 BEEF COWS; NUMBERS 21 YRTREND 1970 TO1990 NUMBER 250 21 - YEAR 200 - A verage: 1 7 2 ,7 6 2 150 X High: 2 3 9 .0 0 0 o Low: 50 - 1 2 5 .0 0 0 YEAR — Figure 6 9 Actual -© - Linear T rend Beef C o w N um bers, 21 -Y e ar Trend, 1 9 7 0 - 1 9 9 0 Avg. Anl. Chg: -1 .9 5 % 115 S h e e p and Lambs: The s t a t e ' s s h e e p and lamb n u m b e r s declined th ro u g h o u t th e 7 0 ' s an d 8 0 ' s , 78 s e e Figure 71, falling from ap proxima te ly 2 6 4 , 0 0 0 in 1 9 7 0 to 1 2 1 , 0 0 0 in 1 9 9 0 , a drop of 5 4 % . a record lo w 77 of 1 0 5 , 0 0 0 hea d in 1 9 8 8 . S h e e p an d lamb n u m b e r s rea ch ed The 21 y ear a v e r a g e an nual decline is 4 . 0 7 % , last for all livestock com m od ities. Production in p o u n d s of meat h o w e v e r , h a v e tre n d e d gradually higher. The 21 year tre nd is an a v e r a g e an nual in c r e a se of 0 . 5 1 % . s e e Figure 7 3 . Price of lamb per C w t. h a s also b e e n increasing, Lamb prices ran ged from a low of $ 2 6 . 6 0 per C w t. in 1971 , to a high of $ 7 5 . 0 0 per C w t. in 1 9 8 7 . The combination of higher lamb prices an d ou tp u t, p r oduced s t e a d y i n cr eases th e value of production. Total value of s h e e p an d lamb production av e r a g e d only $ 5 . 0 million a year , in th e late eighties. Production in t h e s t a t e is c o n c e n t r a t e d in four co unties: W a s h t e n a w , J a c k s o n , L e naw ee, and Ingham. Th e four co u n tie s a c c o u n t for approximately 3 1 % t h e total. W a s h t e n a w c o u n t y alone has app ro ximately 1 6 % of the s t a t e ' s s h e e p an d lamb population. 70 T h i s is a c o n t i n u a t i o n o f a m u c h l o n g e r d o w n w a r d t r e n d . 77 T h e all t i m e h i g h w a s s e t in 1 8 6 7 , o f 3 , 1 0 0 , 0 0 0 s h e e p a n d l a m b . 116 SHEEP & LAMBS; VALUE OF PRODUCTION 21 YR TREND 1970 TO 1990 VALUE OF PRODUCTION $7 0 1 8 - YEAR $5 6 - A verage: $ 4 ,2 9 9 ,7 7 8 High: $ 5 ,8 9 4 ,0 0 0 O 2 Q — $2 8 - $1 4 - Low : $ 3 ,1 2 2 ,0 0 0 $0 0 A v g . Anl. Chg: 2 .6 2 % YEAR Note: d a la s er ie s s ta r ts in ■Actual 1973 F ig u re 7 0 1990 Linear Trend S h e e p & L a m b s V alu e of P r o d u c tio n , 1 8 Y e a r T re n d , 1 9 7 3 - ALL SHEEP & LAMBS; NUMBERS 21 YR TREND NUMBER 1970 TO 1990 280 21 - YEAR A verage: 1 4 6 ,8 1 0 224 - High: 2 6 4 .0 0 0 Low : 1 0 5 .0 0 0 56 -• A v g . Anl. C hg: -4 .0 7 % YEAR —— Actual Figure 71 - o - E xponential!rend S h e e p & Lamb N um bers, 21-Y ear Trend, 1 9 7 0 - 1 9 9 0 117 ALL SHEEP & LAMBS; PRODUCED 21 YR TREN D 1970 TO 1990 PRODUCTION 1 8 - YEAR 8.6 -• 66 - A verage: 8 ,8 8 3 ,4 0 0 UJ O O£ o: o CL = H igh: 9 .3 9 9 .0 0 0 44 - z L ow : 7 .3 8 5 .0 0 0 22 - A v g . Anl. C hg: 0 .5 1 % 00 YEAR Note: d a ta s a il e s s ta r ts in 1973 Actual F ig u re 7 2 -© - Exponential Trend S h e e p & L a m b s P r o d u c t io n , 1 8 Y ear T r e n d , 1 9 7 3 - 1 9 9 0 LAMBS; Avg. PRICE PER Cwt. 21 YR TREND 1970 TO 1990 PRICE $80 21 - YEAR U $40 -■ A verage: $ 5 2 .6 0 y $32 High: $ 7 5 .0 0 CL Low : $ 2 6 .6 0 $16 -• YEAR Actual - o - Linear T rend Figure 7 3 S h e e p & Lam bs Price, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 Avg. Anl. Chg: 3 .6 2 % 118 Layers: Th e layer industry is th e largest poultry s e c t o r in th e s ta t e . Annual s ale s from e g g s ar e in the $ 6 0 to $ 7 0 million range. Th e n u m b e r of h e n s and pullets of laying a g e h a s gradually declined t h r o u g h o u t th e d e c a d e s of the 7 0 ' s and 8 0 ' s . Th e n u m b e r of birds has declined from th e low six million ra n g e to th e high five million level. The 2 1 -year tre nd is an a v e r a g e annual decline of 0 . 4 1 % , s e e Figure 75. Layer eg g pro du ction h a s tr e n d e d mo des tly higher, ranging from a low of 1.3 billion e g g s in 1 9 7 5 , to 1.7 billion e g g s in 1985. O ne r e a s o n for t h e rise in production is t h e g r o w t h in e g g s laid per bird. The a v e r a g e layer in 1 9 7 0 yielded 2 2 3 e g g s , by 1 9 9 0 , t h e n u m b e r of e g g s per bird r ose to 2 5 7 , an incr ease of 1 5 % . 78 The price far m er s receive per doze n e g g s e x p a n d e d a t an a v e r a g e annual rate of 1.41 %. Egg prices ranked 7th in th e annual tre nd g r o w t h rate for t h e Michigan livestock p r oduct prices an alyzed, s e e Table III. The m o d e s t gains in both prices an d o u tput, co m b in e to g e n e r a t e a higher value of production for e g g s during th e 21 year s. Value of pr od uct io n e x p a n d e d at an a v e r a g e an nu al rate of 1 . 6 7 % . A high of $ 7 5 million w a s r e a c h e d in 1 9 8 4 , 79 and a low $ 3 4 million o c c u r re d in 1 9 71. Production is primarily located in th e T h u m b an d S o u t h w e s t e r n regions of th e s ta t e . Five co u n t ie s alone a c c o u n t for o v e r 8 0 % of th e h e n s an d pullets of laying a g e in Michigan, th e y are; Huron, O t t a w a , Ionia, Allegan, and Kalamazoo. In 1 9 9 0 , O t t a w a c o u n ty had t h e largest n u m b e r of h e n s and 70 N o t e : t h e y ie ld g r o w t h t r e n d is e x p o n e n t i a l , s e e F i g u r e 7 7 . 79 T h e v a l u e o f p r o d u c t i o n h i g h c o i n c i d e s w i t h a 2 1 y e a r h i g h o f $ 0 . 6 0 p e r d o z e n e g g s , re c e iv e d by fa rm e rs. 119 layers, 1. 6 million birds, or 3 0 % of Michigan 's total. In t e r m s of egg p r oduc tion, Michigan ran ke d 16th in th e c o u n tr y in 1 9 9 0 . EGGS; VALUE OF PRODUCTION* 21 YR TREND 1970 TO 1990 VALUE OF PRO D UCTIO N $85 21 - YEAR $68 - A verage: $ 5 8 ,2 4 1 ,0 0 0 High: $ 7 5 ,3 5 0 ,0 0 0 OS D —$34 Low : $ 3 4 ,4 7 9 ,0 0 0 $17 - Avg. Anl. Chg: 1 .6 7 % ’ N o te v a lu e of p ro d u c tio n is measured by cash receipts YEAR ■Actual -® - Linear T rend Figure 7 4 Eggs Value of Production, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 120 HENS & PULLETS OF LAYING AGE 21 YR TREND 1 970T 0 1990 NUMBER BO 21 - YEAR 64 - A verage: 6 ,3 6 6 ,5 2 4 LL c Oo CD High: 7 ,1 0 0 ,0 0 0 32 - L ow : 5 ,5 0 0 ,0 0 0 A vg . Anl. Chg: - 0 .4 1 % 00 YEAR Actual F ig u re 7 5 - o - L in e a r T rend H e n s & P ullets of Laying A ge, 2 1 -Y ear T r e n d , 1 9 7 0 - 1 9 9 0 E G G PRODUCTION 21 Y R T R EN D 1970 T O 1990 PRO DU CTIO N 2,000 21 - YEAR 1.600 - 1.200 A verage: 1 ,5 0 8 ,2 8 6 ,7 1 4 - m ~ 600 - High: 1 .6 9 3 .0 0 0 .0 0 0 400 - Low: 1 .3 0 3 .0 0 0 .0 0 0 lus 90 YEAR Actual - o - Linear Trend Figure 7 6 Egg Production, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 Avg. Anl. Chg: 0 .3 2 % 121 AVERAGE OUTPUT PER LAYER YIELD 21 YEAR T RE N D 1970 T O 1990 300 21 - YEAR 240 -■ A verage: 237 fj 100 - H igh: 268 oLU : CL 55 120 -■ L ow : LU 2 02 60 - A v g . Anl. C hg: 0 .7 5 % YEAR ■Actual F ig u re 7 7 Exponential T rend A v e r a g e O u t p u t p e r L ay er, 2 1 -Y ear T r e n d , 1 9 7 0 - 1 9 9 0 PRICE OF EGGS; PER DOZEN 21 YR TREND 1970 TO 1990 PRICE $0.70 21 - YEAR $0.56 - 8 $0.42 A verage: $ 0 .4 6 8 $0 28 - -- High: $ 0 .6 0 Low : $ 0 .2 7 $ 0 14 -■ $0 00 83 YEAR Actual -o - Linear Trend Figure 7 8 Price of Eggs, 2 1 -Y ear Trend, 1 9 7 0 - 1 9 9 0 Avg. Anl. Chg: 1 .4 1 % 122 Ch icken s: The n u m b e r of ch ic k e n s sold in th e s t a t e is closely related to the culling of h e n s from t h e layer industry. As m en tioned a b o v e in th e layer s ectio n , th e n u m b e r of h e n s and pullets of laying a g e h a s declined an a v e r a g e an nual rate of 0 . 4 1 % in t h e 7 0 ' s and 8 0 ' s . The n u m b e r of ch ic k e n s sold has also declined a similar a m o u n t , an a v e r a g e annual rate of 0 . 3 6 % , s e e Figure 80 . A low of 3 . 9 million ch ic k e n s sold oc curre d in 1 9 8 9 while t h e high w a s 6 . 0 million in 1 9 7 5 . Th e tre nd for p o u n d a g e of c h ic k e n s sold is d o w n w a r d but at a s lo w er rate th a n th e nu m b er of birds sold. P o u n d s of ch icke n sold fell an a v e r a g e an nual rate of only 0.11 %. Total w e ig h t of th e c h ic k e n s sold a v e r a g e d 2 1 . 5 million p o u n d s per year. The price tre nd of ch icken per pou nd in c r e a se d slightly for th e t w o d e c a d e s , increasing an a v e r a g e 0 . 4 0 % . Chicken prices fluctu ate d widely within a ra nge of 8 . 0 c e n t s an d 1 5 . 0 c e n t s per pou nd , a v eraging 10 c e n t s for th e time period. The total value of production for Michigan ch icken sale s a v e r a g e d only $2 . 28 million a y e a r ,80 s e e Figure 79. Th e 21 ye a r tre nd is an a v e r a g e annual rate of decline is 1 . 0 8 % last for all livestock analyz ed , s e e Table III. 80 Of the commodities analyzed for value of production, chicken is second to last in terms of total amount. 123 CHICKENS; VALUE OF PRODUCTION 21 YR TREND 1970 TO 1990 VALUE OF PRODUCTION $4,000 17 - YEAR $3,2 0 0 - A verage: $ 2 ,2 8 3 ,3 5 3 £ $2,100 O o Q P $1 ,4 0 0 - High: $ 3 ,0 2 2 ,0 0 0 L ow : $ 7 0 2 ,0 0 0 $ 700 - 8B 80 YEAR Note: d a t a s e r ie s s ta r ts in 1974 ■Actual Exponential Trend Figure 8 3 Broilers Value of Production, 17-Year Trend, 1 9 7 4 - 1 9 9 0 90 Avg. Anl. Chg: 0 .5 6 % 127 BROILERS; NUMBER PRODUCED 21 YR TREND 1970 TO 1990 NUMBER 3.00D 21 - YEAR 2,400 A verage: 9 7 3 ,4 0 5 m -g 1.800 vO ££ K H igh: 2 .5 7 0 .0 0 0 g 3 L ow : 5 1 0 .0 0 0 800 A v g . Anl. Chg: 1 .0 2 % BB 90 YEAR ■Actual F ig u re 8 4 Exponential T rend N u m b e r of Broilers P r o d u c e d , 2 1 -Y ear T r e n d , 1 9 7 0 - 1 9 9 0 BROILERS; PRODUCED 21 Y R TREN D 1970 TO 1990 PRO D UCTION 120 1 7 - YEAR 9.6 -• UJ A verage: 4 ,4 1 3 ,4 1 2 3 o O£ a: o 2 3 High: 1 0 .7 9 4 .0 0 0 4 8 -• L ow : 2 .5 2 0 .0 0 0 2 4 -• 90 YEAR Note 1974 d a ta s e r ie s s ta r ts in — Actual -© - Linear T rend Figure 8 5 Broiler P roduction, 1 7-Year Trend, 1 9 7 4 - 1 9 9 0 Avg. Anl. Chg: -1 .6 4 % 128 BROILERS; PRICE PER POUND 21 YR TREND 1970 TO 1990 PRICE $0.40 21 - YEAR $0 32 A v e ra g e : $ 0 .2 8 High: $ 0 .3 7 UJ Qw $ 0 16 Low: $ 0 .1 7 $ 0 08 A vg . Anl. C h g : 2 .6 7 % $0 00 YEAR • Actual Figure 8 6 Linear Trend Price of Broilers, 2 1 -Y ear T re n d , 1 9 7 0 - 1 9 9 0 T u r k e y s :81 T urkeys w er e th e f a s t e s t growing82 livestock s e c t o r in Michigan during t h e d e c a d e s of th e 7 0 ' s and 8 0 ' s . The excep tion al g r ow th is exemplified by t h e fac t t h a t the n u m b e r tu rk e y s raised incre ased every ye a r e x c e p t t w o , 1 9 7 4 and 1 9 7 8 . The calculated trend for tu rk ey num be rs raised is an a v e r a g e annual i ncr ea se of 9 . 4 3 % . 83 In 1 9 7 3 over 1. 0 million birds w e r e raised in t h e s ta t e , by 1 9 9 0 over 4 . 3 million birds w e r e raised, an increase of 8’ Note: the data for turkey analysis starts in 1973 instead of 1970, this is when the Michigan Agricultural Statistics Service started comprehensive collection. 82 Note: every category analyzed for turkeys has a calculated trend that is exponential. This highlights the ever increasing growth rates for the turkey sector. 83 The closest livestock commodity was hogs and pigs with a growth rate of 3.54%. 129 a lm o st 3 0 0 % . In th e s a m e man ne r, th e p o u n d s of tu rk ey p r o d u c e d g r e w a t an e x trem ely fast p a c e . In 1 9 7 3 ap proximately 2 6 million p o u n d s of turkey w e r e p r o d u c e d in Michigan, this e x p a n d e d to over 1 2 4 million p o u n d s in 1 9 9 0 , a rise of 3 7 7 % . Th e calculated trend for prod uction is an a v e r a g e an nual g r o w t h rate of 1 0 . 7 4 % , s e e Figure 89. The price of t u r k e y s also e x p a n d e d but at a m u c h s lo w er rate th an th e other c ateg o r ies. Th e trend for price w a s an increase of an a v e r a g e an nua l rate of 1 . 5 1 % , this w a s sixth out of nine co m m odities. The com bination of higher prices an d pro du ction o u t p u t lead to ex p a n d in g v alues of pro du ction in th e 7 0 ' and 8 0 ' s . Value of p roduction e x p a n d e d from just over $ 1 0 million in 1 9 7 3 to over $51 million in 1 9 9 0 , s e e Figure 87. The g r o w t h trend w a s an a v e r a g e an nu al rate of 1 2 . 5 7 % , t h e h ig h est for all co mmodities. The major c o n c e n tr a tio n of turkey production in t h e s t a t e is loca ted in Kent c o u n t y . In 1 9 9 0 , Michigan p r o duced 1 . 5 % of n a ti o n 's total m ar ke t tu rk e y s , ranking 13th, with perennial leader North Carolina n u m b e r one. 130 TURKEYS; VALUE OF PRODUCTION 21 YR TREND 1970 TO 1990 VALUE OF PRODUCTION $60 1 8 - YEAR $48 - A verage: $ 1 9 ,9 1 3 ,7 1 2 High: $ 4 2 ,6 3 0 ,0 0 0 O Z O “ $24 - $12 Low : $ 5 ,0 0 7 ,9 0 6 -■ 80 YEAR 8? A v g . Anl. C hg: 1 2 .5 7 % Note: d a ta s e n e s s ta r ts in Exponential T rend ■Actual 1973 F ig ure 8 7 T u r k e y s V alue of P ro d u c tio n , 1 8 -Y e a r T re n d , 1 9 7 3 - 1 9 9 0 TURKEYS; NUMBER RAISED 21 YR TREND 1970 TO 1990 NUMBER 50 1 8 - YEAR 40 - (/>— « 30 20 A verage: 1 ,1 9 2 ,7 2 2 - High: 4 .3 0 0 .0 0 0 - L ow : 7 0 0 .0 0 0 Avg. Anl. Chg: 9 .4 3 % YEAR Note: d a ta s e rie s w as slatted in 1973 ■Actual Exponential Trend Figure 8 8 N u m b er of Turkeys, 1 8-Year Trend, 1 9 7 3 - 1 9 9 0 131 TURKEYS; PRODUCED 21 Y R T R EN D 1970 TO 1990 PRODUCTION 150 1 8 - YEAR 120 - A verage: 5 1 ,4 6 9 ,1 6 7 LU O £ a. o CL = VI 2 High: 1 2 4 .7 0 0 .0 0 0 60 -• Low : 1 6 .1 0 0 .0 0 0 30 - A v g . Anl. Chg: 1 0 .7 4 % 80 N ote, d a ta s e rie s s ta r ts in 1973 Figure 8 9 YEAR Exponential Trend Actual T u r k e y P r o d u c ti o n , 1 8 -Y e a r T r e n d , 1 9 7 3 - 1 9 9 0 TURKEYS*; PRICE PER POUND 21 YR TREND 1970 TO 1990 PRICE $0 60 1 8 - YEAR $0 48 - A verage: $ 0 .4 1 lit High: $ 0 .5 3 $0 24 - $ 0 .1 2 - Low : $ 0 .2 8 $000 Avg. Anl. Chg: 1 .5 1 % YEAR * D ata s e rie s s ta r ts in 1973 •Actual -o - Exponential Trend Figure 9 0 Price of Turkeys, 1 8-Year Trend, 1 9 7 3 - 1 9 9 0 132 General Fruit Ov ervie w 84 This s e c t io n re vie w s t h e im po rta nt crop t r e n d s of price, yield, a c r e s h a r v e s t e d , n u m b e r of fruit bearing tre es , quantity p r o d u c e d , and value of produc tion, for e a c h of Michigan 's top s e v e n fruit c r o p s . 85 Table IV is a trend s u m m a r y of fruit c r o p s ranked by th e a v e r a g e annual p e r c e n t c h a n g e s for each c a t e g o r y (yields, price, etc.). Figures 91 and 9 2 ar e th e ag g r e g a tio n of all fruit cr o p s for th e ca te g o r ie s of value of pr oduction and a c r e s h a r v e s te d . Total Michigan fruit crop a c r e s h a r v e s te d hav e tre nded lower during th e last t w o d e c a d e s , declining at an a v e r a g e annual rate of 1 . 7 5 % , s e e Figure 92 . The actual p a tte r n of fruit a c r e s h a r v e s te d s h o w s t w o different s e g m e n t s . The first s e g m e n t is a decline from 1 5 6 t h o u s a n d a c r e s in 1 9 7 0 d o w n to 101 t h o u s a n d a c r e s in 1 9 8 2 . Th e s e c o n d s e g m e n t is a re bo und from th e 101 t h o u s a n d a c r e level in 1 9 8 2 to 1 1 9 t h o u s a n d a c r e s in 1 9 9 0 , a rise of 1 8 % . T he value of fruit production rose steadily for t h e 7 0 ' s an d 8 0 ' s . Total crop value in crease d an a v e r a g e annual a m o u n t of 3 . 6 1 % . A high of $171 million w a s record in 1 9 7 8 an d th e low oc curre d in 1 9 7 0 at $ 5 9 million. 84 N o t e : M i c h i g a n is c o n s i s t e n t l y r a n k e d e i t h e r n u m b e r 1 o r n u m b e r 2 in t h e c o u n t r y in t h e p r o d u c t i o n o f b l u e b e r r i e s . T h e i m p o r t a n c e o f b l u e b e r r i e s t o t h e s t a t e is w e l l u n d e r s t o o d b y t h e a u t h o r o f t h i s d i s s e r t a t i o n . T h e c r o p h o w e v e r , is n o t i n c l u d e d in t h e d i s s e r t a t i o n a n a l y s i s . B l u e b e r r y d a t a c o l l e c t i o n b y t h e M i c h i g a n A g r i c u l t u r a l S t a t i s t i c a l S e r v i c e h a s b e e n s p o r a d i c d u r i n g t h e t i m e p e r i o d o f a n a l y s i s . It w a s th e r e f o r e d e t e r m i n e d to le a v e b lu e b e r rie s o u t of t h e fruit tr e n d a n a ly s is s e c tio n . B l u e b e r r i e s a r e h o w e v e r , d i s c u s s e d in t h e s h i f t - s h a r e c h a p t e r w h e n t i m e s e r i e s d a t a is n o t r e q u i r e d a n d c r o s s s e c t i o n a l d a t a is u s e d . 85 T h e s e l e c t i o n o f t h e t o p s e v e n M i c h i g a n f r u i t c r o p s f o r t h e a n a l y s i s is p r e d i c a t e d o n t h e v a lu e o f p r o d u c t i o n for e a c h c r o p . 133 T a b le IV T r e n d S u m m a r y fo r Fruit C r o p s , C o m m o d i ty R a n k b y A v e r a g e A n n u a l % C h a n g e f o r 2 1 - Y e a rs , 1 9 7 0 - 1 9 9 0 TREND SU M M A R Y FOR FRUIT C R O P S CO M M O D ITY RANK BY AVERAGE ANNUAL % CHA N GE FOR 2 1 -Y e a rS FROM 1 9 7 0 - 9 0 A cres H arv ested Rank 1 2 3 4 5 6 7 P r o d u c t io n C o m m o d it y % C hg. A p p le s T a r t C h e rr ie s S w e e t C h e rr ie s G rapes Peaches P r u n e s & P lu m s P ears - 0 .5 1 % -0 .8 3 % -1 .7 4 % -2 .2 0 % -4 .7 4 % -4 .9 6 % -1 1 .9 4 % A verage R ank 1 2 3 4 5 6 7 1 2 3 4 5 6 7 C om m odity P ears Peaches A p p le s G rapes P r u n e s & P lu m s S w e e t C h e r rie s T a rt C h e r r ie s A v e rag e % C h g. A p p le s T a r t C h e rrie s G rapes S w e e t C h e rrie s Peaches P r u n e s & P lu m s P ears 1 .9 9 % 0 .8 4 % 0 .3 6 % 0 .3 0 % -1 .0 9 % -2 .7 0 % - 6 .1 1 % -3 .8 5 % A verage Yield Rank C o m m o d ity -0 .9 2 % Price % C hg. R ank 5 .2 7 % 3 .2 5 % 2 .3 6 % 2 .0 5 % 2 .0 4 % 1 .9 5 % 1 .6 5 % 1 2 3 4 5 6 7 2 .6 5 % C o m m o d it y S w e e t C h e r r ie s P ears P r u n e s & P lu m s Peaches A p p le s G rapes T a r t C h e rrie s A v e rag e % Chg. 4 .6 0 % 3 .8 6 % 3 .8 6 % 3 .5 0 % 2 .8 0 % 2 .7 2 % 2 .0 0 % 3 .3 3 % 134 T a b le IV (C o n tin u e d ! T r e n d S u m m a r y fo r Fruit C r o p s , C o m m o d i ty R a n k b y A v e r a g e A n n u a l % C h a n g e f o r 2 1 -Y ea rs, 1 9 7 0 - 1 9 9 0 TREND SU M M A R Y FOR FRUIT C R O P S C O M M O D IT Y RANK BY AVERAGE ANNUAL % CHANGE FOR 2 1 -Y e a rS FROM 1 9 7 0 - 9 0 V alue o f P r o d u c tio n Rank 1 2 3 4 5 6 7 C om m o d ity % Chg. A p p le s S w e e t C h e r rie s Peaches G rapes T a r t C h e r r ie s P r u n e s & P lu m s Pears A verage 4 .8 2 % 4 .5 7 % 3 .4 8 % 2 .9 6 % 1 .9 2 % 0 .8 7 % -1 .2 7 % 2 .4 8 % Fruit T r e e s of B earing A g e Rank 1 2 3 4 5 6 7 C o m m o d i ty % Chg. A p p le s S w e e t C h e rrie s Peaches G rapes T a r t C h e r r ie s P r u n e s & P lu m s P ears A ve rag e 3 .2 8 % 0 .3 6 % -1 .4 8 % -2 .6 6 % -3 .5 4 % -4 .3 3 % -1 1 .2 6 % -2 .4 8 % 135 TOTAL FRUIT; VALUE OF PRODUCTION 21 YR TREND 1970 TO 1990 VALUE OF PRODUCTION $190 21 - YEAR $152 A verage: $ 1 1 9 ,8 2 5 ,5 2 4 O o High: $ 1 7 1 ,6 2 2 ,0 0 0 $76 Low: $ 5 8 ,5 6 5 ,0 0 0 $38 A vg . Anl. C hg: 3 .6 1 % YEAR — F ig u re 9 1 Actual - o - Linear T rend T o ta l Fruit V alu e of P ro d u c ti o n , 2 1 -Y ear T r e n d , 1 9 7 0 - 1 9 9 0 TO TA L FRUIT: ACRES H AR VESTED 21 YR TREND 1970-90 180 144 - A CRES HARVESTED 21 - YEAR a-S 108 -• Q£ A verage: 1 2 2 ,7 3 3 High: 1 5 6 ,3 0 0 36 - L ow : 1 0 0 ,9 0 0 Avg. Anl. Chg: - 1 .7 5 % YEAR Actual Exponential Trend Figure 9 2 Total Fruit A c res H arv ested , 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 136 Apples: Michigan apple production tr e n d e d higher t h r o u g h o u t th e d e c a d e s of th e 7 0 ' s and 8 0 ' s . The incr ea se in pro du ction o c c u r re d d es pit e a 21 ye ar n eg ativ e trend for a c r e s h ar v este d , an a v e r a g e an nual decline of 0 .5 1 %. The a c r e s h a r v e s te d trend c a n be split into t w o different s e g m e n t s , s e e Figure 94 . T he first tre nd s e g m e n t is an a c r e a g e decline for ev ery y ear from 1 9 7 0 to 1 9 7 9 of 5 6 , 0 0 0 a c r e s to 4 2 , 5 0 0 acr es. And th e s e c o n d tre nd s e g m e n t is an in c r e a se in a c r e a g e of 4 2 , 5 0 0 ac res to 5 2 , 1 0 0 acr es, up ev ery yea r from 1 9 7 9 to 1 9 9 0 . One ex planation in th e increase in overall pr oduction c a n be explained by th e g r o w e rs shift a w a y from s ta n d a r d tr e e s to w a r d n e w d w a r f an d se m i - d w a r f varieties. Th e nu m b er of tr e e s per ac re climbed from 5 2 in 1 9 7 0 to 1 0 6 in 1 9 9 0 . Total Michigan apple t r e e s e x p a n d e d from 2 . 9 million in 1 9 7 0 to 5 . 5 million in 1 9 9 0 . The 21 year tre nd for th e n u m b e r of fruit bearing tr e e s is an a v e r a g e annual i ncr ea se of 3 . 2 8 % , s e e Figure 95. Given t h e m a n a g e m e n t shift to more apple tr e e s (the smaller d w a r f varieties) per acr e, pro du ction yields per ac re hav e increase d an a v e r a g e annual rate of 2 . 3 6 % . Th e f aster g r o w t h in yields c o m p a r e d to th e smaller decline in a c r e s h a r v e s te d , tra n slated into higher total pr oduction levels. Apple o u t p u t g r e w at an a v e r a g e annual rate of 1 . 9 9 % 86 for th e t w o d e c a d e s . Prices for all apples improved steadily in t h e 7 0 ' s and 8 0 ' s . Th e com binat ion of higher prices and e x p a n d e d pro duc tion p u s h e d the value of produc tion tre nd c o n s is te n tly higher. 88 See Table IV, the increase in apple production trend was greater than all the fruit sectors analyzed. Note: tart cherries, grapes, and sweet cherries were the only other fruits to post positive gains. 137 Value of pro du ction tripled from $ 2 5 million to over $ 7 5 million87 at th e end of th e eighties, s e e Figure 93 . Th e larg est a r e a s of apple pro du ction in th e s ta t e are th e c o unties of Kent, Van Buren, an d Berrien. The top apple varieties gro w n are Red Delicious (with over 2 5 % of t h e market), J o n a t h a n , Golden Delicious, and Ida Red. M ost of t h e apples ar e u s e d for process ing with th e remainder going to th e fresh m ar ket s. In 1 9 9 0 Michigan ranked 3rd in th e c o u n t r y in term of th e a m o u n t of p o u n d s p r o d u c e d . Michigan p r o d u c e s approximately 9 . 5 % of th e total U.S. apple market, th e s t a t e s ' of W a s h in g to n and N ew York are th e other perennial leaders in production. APPLES; VALUE OF PRODUCTION 21 YR TREND 1970 TO 1990 VALUE OF PRODUCTION S100 1-----------------------------------------------------------------21 - YEAR $75 - A verage: $ 5 5 ,5 8 1 ,0 9 5 $50 - High: $ 7 9 ,8 6 0 ,0 0 0 $25 - A v g . Anl. C hg: 4 .8 2 % 00 YEAR s - Linear T rend F ig u re 9 3 A p p le s V alu e o f P r o d u c tio n , 2 1 -Y ear T re n d , 1 9 7 0 - 1 9 9 0 87 Apple production is the largest fruit sector in the state in terms of value of production. 138 APPLES; ACRES HARVESTED 21 YR TREND 1970 TO 1990 ACRES HARVESTED 62 0 21 - YEAR 49 6 - A verage: 4 8 ,7 3 3 ^ a -S 37 2 O£ High: 5 6 ,0 0 0 ££.24 8 - L ow : 4 2 ,5 0 0 124 - A v g. Anl. C hg: - 0 .5 1 % YEAR Actual F ig ure 9 4 -© - Exponential Trend A p p l e s A c r e s H a r v e s t e d , 2 1 -Y ear T r e n d , 1 9 7 0 - 1 9 9 0 APPLES; NUMBER OF TREES 21 YR TREND 1970 TO 1990 NUMBER OF TREES 60 1<1D 1 4 8- 21 - YEAR A verage: 3 ,6 5 3 ,3 3 3 36 - ul “ 2 4 - High: 5 .5 0 0 .0 0 0 L ow: 2 .8 0 0 .0 0 0 Z> 00 YEAR Actual -® - Exponential Trend Figure 9 5 A pples N um b er of T rees, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 Avg. Anl. Chg: 3 .2 8 % 139 APPLES; PRODUCTION 21 YRTREND 1970 TO1990 PRODUCTION 1,200 21 - YEAR < / > - |I 2^ 960 - 720 - - . 480 -• A verage: 7 6 4 ,2 8 5 ,7 1 4 High: 1 , 1 0 0 , 0 0 0 ,0 0 0 L ow : 4 7 0 ,0 0 0 ,0 0 0 240 - A v g . Anl. C hg: 1 .9 9 % YEAR Actual F ig u re 9 6 - o - Linear T rend A p p l e s P r o d u c tio n , 2 1 -Y ear T re n d , 1 9 7 0 - 1 9 9 0 APPLES; YIELD 21 YRTREND 1970 TO1990 YIELD 21 - YEAR LU cc 12 -■ LU 9 A verage: 7 .9 4 - zZ> High: 1 1 .9 0 CL L ow : 4 .3 9 3- YEAR — Actual - o - Linear T rend Figure 9 7 Apple Yields, 21 -Y ear Trend, 1 9 7 0 - 1 9 9 0 Avg. Anl. Chg: 2 .3 6 % 140 APPLES; PRICE 21 YR T R EN D 1970 T O 1990 PRICE SO 12 21 - YEAR A verage: $ 0 ,0 7 3 a $o.o7 CL (O High: $ 0 ,1 0 3 $0.0 5 - Low: $ 0 ,0 3 6 $ 0.02 - A v g . Anl. Chg: 2 .8 0 % $0 00 YEAR Actual Fig u re 9 8 ~o- U n e ar Trend A p p l e s P rice, 2 1 -Y e a r T re n d , 1 9 7 0 - 1 9 9 0 G r ap es: During th e last t w o d e c a d e s , Michigan grap e p r o d u c t io n 88 has tr e n d e d slightly d o w n w a r d . Acres h a r v e st e d fell an annual a v e r a g e of 2.20% . Th e n u m b e r of vines of fruit bearing a g e also declined a t a similar p a c e . Total fruit bearing vines d e c r e a s e d from 7 . 9 million in 1 9 7 0 to 5.1 million in 1 9 9 0 , a drop of 3 5 % , s e e Figure 101. Yields on th e o th e r hand s h o w e d m o d e s t increase s. The 21 year trend for gr a p e yields w a s an a v er ag e an nu al i n c r e a s e of 2 . 0 5 % . Even with th e u p w a r d yield tre nd, yields fluctuated greatly in th e 7 0 ' s an d 8 0 ' s , ranging from a low of 0 . 9 7 million p o u n d s per a c r e in 1 9 7 6 to a high of 5.31 million p o u n d s per a c r e in 1 9 8 7 , s e e Figure 1 0 3 . T h e higher grap e yields per acr e helped to offs et t h e declines in the 88 Note: grape production can be highly variable do to it's sensitivity to weather changes. 141 a c r e s harv ested and total pro du ctio n tr e n d e d slightly higher at an a v e r a g e annual rate of 0 . 3 6 % . Production of grap e varieties used for wine making incre ased steadily while pr oduction of gr ape varieties u s ed for t h e juice pr oc es sing s e c t o r e x p er ien ced c o n s is t e n t sh ri nkag e.89 For th e 21 yea r period Michigan has a v e r a g e d 9 9 million p o u n d s of g r a p e s per year . Gra pe prices improved steadily, increasing at an a v e r a g e annual rate of 2 . 7 2 % . The pea k price for grapes w a s in 1 9 8 9 w h e n th ey sold for $ 1 , 3 2 5 per po und. The value of production climbed higher given th e fas ter g r ow th in prices c o m p a r e d to t h e slight decline in production, s ee Figure 99. Grape value of pro du ction g r e w a t the fourth f a s t e s t rate of th e fruits analyzed, s e e Table IV. The s o u t h w e s t region of th e s ta t e pr o d u c e d m o st of th e g r a p e s . T w o c o u n ti e s in this region pr o d u c e d nearly all of th e grapes, Berrien an d Van Buren. In 1 9 9 0 Michigan ranked 5 t h 90 in t h e countr y in t o n s of g r a p e s p ro d u ced , with a s hare of 8 . 3 % of the total. 89 Some production declines occurred for the Concord variety of grape which is used in grape juices. 90 Michigan is 5th behind California, Washington, New York, and Pennsylvania. 142 GRAPES; VALUE OF PRODUCTION 21 YR TREND VALUE OF PRODUCTION 1970 TO 1990 $100 21 - YEAR $144 - A verage: $ 1 0 ,2 0 8 ,0 9 5 High: $ 1 5 ,6 0 9 ,0 0 0 $72 - $3 6 Low: $ 2 ,2 1 9 ,0 0 0 - $0 0 A v g . Anl. Chg: 2 .9 6 % 86 YEAR Actual F ig u re 9 9 -o - Linear Trend G r a p e s V alue o f P r o d u c tio n , 2 1 -Year T re n d , 1 9 7 0 - 1 9 9 0 GRAPES; A C R ES HARVESTED 21 YR TREND 1970 TO 1990 A C R ES H A RV ESTED 21 - YEAR Q5 A verage: 1 3 ,4 1 0 10 8 - High: 1 5 ,9 0 0 Low: 3 6 -• 11,000 00 90 YEAR Actual - o - Exponential T rend Figure 1 0 0 G ra p e s A c res H a rv ested , 21 -Y ear Trend, 1 9 7 0 - 1 9 9 0 Avg. Anl. Chg: -2 .2 0 % 143 GRAPES; NUMBER OF VINES 21 YR TREND 1970 TO 1990 NUMBER OF VINES LU 21 - YEAR 72 - 54 - A verage: 6 ,5 1 1 ,9 0 5 “ 36 - High: 7 .9 0 0 .0 0 0 Low: 5 .1 0 0 .0 0 0 m A vg . Anl. Chg: 00 YEAR — F ig u re 1 0 1 Actual -2.66% - o - Linear Trend G r a p e s N u m b e r o f V in e s, 2 1 -Y ear T r e n d , 1 9 7 0 - 1 9 9 0 G RAPES; PR O DUCTIO N 21 Y R T R EN D 1970 T O 1990 PRODUCTION 150 21 - YEAR 20 -■ A verage: 9 9 .0 0 0 .0 0 0 V) — 90 - O £ z o High: 1 3 8 .0 0 0 .0 0 0 ZD = “ 60 - Low : 2 9 .0 0 0 .0 0 0 30 - Avg. Anl. Chg: 0 .3 6 % YEAR ■Actual o - Exponential Trend Figure 1 0 2 G rap e P roduction, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 144 GRAPES; YIELD 21 YRTREND 1S70 TO1990 YIELD 60 21 - YEAR A verage: 3 .7 6 Q- 3.6 - co High: 5 .3 1 9 2 .4 - Low: 0 .9 7 A v g . Anl. C h g: 2 .0 5 % 00 YEAR Actual F ig u re 1 0 3 - o - Linear Trend G r a p e Yields, 2 1 -Y ear T r e n d , 1 9 7 0 - 1 9 9 0 GRAPES; PRICE 21 YRTREND 1970 TO1990 PRICE $1 50 21 - YEAR $ 1.20 -■ A verage: $ 1 ,0 3 0 High: $ 1 ,3 2 5 O o $0.6 0 -• Low: $ 0 ,6 0 0 $0.3 0 - Avg. Anl. Chg: 2 .7 2 % $0 00 YEAR ----- Actual -© - L inear T rend Figure 1 0 4 G ra p e s Price, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 145 P e a c h e s: P e a c h e s h a v e a similar tre nd pattern of a c r e a g e h a r v e s t e d a s do ap ples . Th e tre nd c a n be broken into t w o d is cr ete s e g m e n t s , s e e Figure 106. T he first s e g m e n t is a rapid decline during t h e 7 0 ' s an d th e s e c o n d s e g m e n t is a reco v ery and an in cr ea se in ac r e s h a r v e s t e d in th e 8 0 ' s . Acr es h a r v e s te d declined ev ery yea r from a high of 1 6 . 5 t h o u s a n d in 1971 to a low of 4.1 t h o u s a n d in 1 9 8 1 , a drop of 7 5 % . The tre nd th e n re v e rs e s with a c r e a g e climbing from th e low of 4.1 t h o u s a n d in 1981 to 8 . 0 t h o u s a n d in 1 9 9 0 , an in c r e a se of a lm o st 1 0 0 % . For th e p a s t t w o d e c a d e s , th e trend for th e num ber of fruit bearing t r e e s follows a similar p atter n to th e a c r e s h a r v e s te d trend. Th e n u m b e r of fruit bearing t re e s declined an a v e r a g e annual rate of 3 . 5 4 % . Offsetting th e decline in a c r e s h a r v e s te d is th e solid rise in p e a c h yields. P e a c h yields in crease d an a v e r a g e annual rate of 3 . 2 5 % , s e c o n d hi ghest rate for all fruit crops. P each prod uc tion gradually fell a t an a v e r a g e an nua l rate of 1.09% . For th e 21 y e a r s total production a v e r a g e d 5 0 million p o u n d s . The price of p e a c h e s tr e n d e d higher in th e 7 0 ' s an d 8 0 ' s , ex p a n d in g a t an a v e r a g e annu al rate of 3 . 5 % . The value of pro du ction in crease d similarly, increasing an a v e r a g e an nual rate of 3 . 4 8 % . In 1 9 9 0 p e a c h value of pro du ction eq ualed $ 9 . 4 million. Th e major prod uction region in the s t a t e is located in th e s o u t h w e s t . Th e principal produ ction c o u n ti e s are Berrien and Van Buren. Th e Red Haven an d H arm ony varieties a c c o u n t for m o s t of th e p e a c h e s grow n. In 1 9 9 0 Michigan ranked 6 t h in th e c o untr y in total o u t p u t of p e a c h e s in pounds , pr od uc ing 2 . 0 % of th e U.S. total. 146 PEACHES; VALUE OF PRODUCTION 21 YR TREND VALUE OF PRODUCTION 1970 TO 1990 $130 21 - YEAR $104 - A verage: $ 7 ,6 7 2 ,8 5 7 c o High: $ 1 1 ,5 1 5 ,0 0 0 $5 2 - $2 6 Low: $ 1 ,0 7 0 ,0 0 0 - A vg . Anl. C hg: 3 .4 8 % $0 0 YEAR Actual F ig u re 1 0 5 - o - Linear Trend P e a c h e s V alu e o f P r o d u c tio n , 2 1 -Y ear T r e n d , 1 9 7 0 - 1 9 9 0 PEACHES; ACRES HARVESTED 21 YR TREND 1970 TO 1990 A C R ES HARVESTED 21 - YEAR 14 4 - (f) a -8 108 -• Q£ A verage: 9 ,0 7 1 _ High: 1 6 ,5 0 0 Low: 4 ,1 0 0 B8 76 YEAR ^ — Actual - o - Exponential Trend Figure 1 0 6 P e a c h e s A cres H a rv ested, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 Avg. Anl. Chg: -4 .7 4 % 147 PEACHES; NUMBER OF TREES 21 YR TREND NUMBER OF TREES 1970 TO 1990 1,000 V) LU LU K 21 - YEAR 1,440 - 1,000 A verage: 9 5 0 ,4 7 6 - High: 1 ,6 0 0 ,0 0 0 LU L ow : 4 2 5 ,0 0 0 360 - 86 90 A v g . Anl. C hg: -3 .5 4 % YEAR Actual F ig u re 1 0 7 - o - E>ponential Trend P e a c h e s N u m b e r of T r e e s , 2 1 -Y ear T r e n d , 1 9 7 0 - 1 9 9 0 PEACHES; PRODUCTION 21 YR T RE N D 1970 TO 1990 PRO DU CTION 21 - YEAR 72 - a£ A verage: 5 0 ,3 3 3 ,3 3 3 54 - - High: 8 2 ,0 0 0 ,0 0 0 z 5 =>= 9s 36 -■ Low: 10 , 000,000 18 - 86 YEAR — Actual - o - L in e a r T rend Figure 1 0 8 P e a c h e s P roduction, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 Avg. Anl. Chg: -1 .0 9 % 148 PEACHES; YIELD 21 Y R TREN D YIELD 1970 TO 1990 B.O 21 - YEAR O' 4.8 - UJ o- 3.6 A verage: 3 .2 0 - High: 5 .3 2 Low: 0 .3 2 A v g . Anl. C hg: 3 .2 5 % 0.0 86 YEAR ^ — Actual F ig u re 1 0 9 - o - Linear Trend P e a c h e s Yield, 2 1 -Y ear T r e n d , 1 9 7 0 - 1 9 9 0 PEACHES; PRICE 21 YR TREN D 1970 TO 1990 PRICE $0 30 21 - YEAR $0 24 - A verage: $ 0 ,1 5 8 3 £ $ 0 18 -• Q_ High: $ 0 ,2 1 5 (n O Q $0.12 - Low : $ 0 ,0 5 8 $0 06 Avg. Anl. Chg: 3 .5 0 % $0 00 YEAR Actual -© - Linear Trend Figure 1 1 0 P e a c h e s Price, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 149 Pea rs: P ea rs s h o w e d th e m o s t significant declines for an y of th e fruit crops. A cres h a r v e s te d p lu m m eted from a high of 1 0 . 6 t h o u s a n d in 1 9 7 0 , to a low of 1. 4 t h o u s a n d in 1 9 9 0 , a dro p of 8 7 % . Th e tre nd w a s an a v e r a g e annual decline of 1 1 . 4 4 % , s e e Figure 112. The n u m b e r of t r e e s of fruit bearing ag e followed a similar d o w n w a r d pattern . T he tre nd for pe a r t r e e s w a s an a v e r a g e an nual decline of 1 1 . 2 6 % , last for all crops, s e e Table IV. Pear production declined rapidly but not a s fast as th e drop in tree n u m b e r s a n d a c r e s h a r v e s t e d . Total production fell at an a v e r a g e an nu al decline of 6.11 %. Ho w ev er , pears p o s te d th e largest trend inc re as e for yields. Pear yields e x p a n d e d a t an a v e r a g e an nual rate of 5 . 2 7 % , s e e Figure 115. One e x planation for the rising yield trend is th e shifting a w a y from marginal quality land. As t h e a c r e s of pears h a r v e s te d declines , th e higher quality land remains in produ ction, an d yields improve. Pear prices tripled from 1 9 7 0 to 1 9 9 0 , increasing to a high of $ 1 . 3 4 per poun d in 1 9 9 0 . Pear prices in creased at an a v e r a g e an nual rate of 3 . 8 6 % , tied with p r u n e s and plums for t h e s e c o n d h ig h est g r o w t h rate. Even with th e rise in pea r prices, p e a r s w e r e t h e only fruit crop to h a v e a neg at ive a v e r a g e an nu al g r o w th rate for t h e value of pr odu ction, s e e Table IV. P ear value of pr oduction fell an a v e r a g e an nu al rate of 1 . 2 7 % in th e t w o d e c a d e s analyzed. Th e w e s t side of t h e s t a t e p r o d u c e s m o s t of th e p ear s. O c e a n a , Allegan, a n d Berrien co u n t ie s a c c o u n t for m o s t of th e pr odu ction. The p r e d o m in a te variety is th e Bartlett t h a t a c c o u n t s for approxi mate ly 8 3 % of th e s t a t e ' s pea r a c r e a g e . In 1 9 9 0 Michigan ranked 7th in th e c o u n tr y in t o n n a g e pro d u ced , producing 0 . 3 % of th e U.S. total. 150 PEARS; VALUE OF PRODUCTION 21 YR TREND VALUE OF PRODUCTION 1970 TO 1990 $3,200 21 - YEAR $ 2 ,4 0 0 - A verage: $ 1 ,7 6 2 ,4 2 9 (/>-o ” $ 1,600 - High: $ 2 ,7 6 0 ,0 0 0 Low : $800 - $668,000 A v g . Anl. C h g: -1 .2 7 % YEAR — F ig u re 1 1 1 Actual -o - Linear Trend P e a r s V a lu e o f P r o d u c ti o n , 2 1 -Y ear T r e n d , 1 9 7 0 - 1 9 9 0 PEARS; ACRES HARVESTED 21 YR TREND A C R ES HARVESTED 1970 TO 1990 120 21 - YEAR A verage: 4 ,4 6 7 High: 1 0 ,6 0 0 Low : 1 ,4 0 0 00 88 YEAR Actual - o - Exponential Trend Figure 1 1 2 P ears A c re s H a rv ested , 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 Avg. Anl. Chg: -1 1 .4 4 % 151 PEARS; NUMBER OF TREES 21 Y R T R E N D NUMBER OF TREES 1970 TO 1990 1,200 (/> LU 21 - YEAR 960 A verage: 4 2 4 ,8 1 0 720 LU T3 m£ t□ os High: 2 E LU m , 480 - 1 0 0 0 ,0 0 0 240 - Low : 1 4 0 ,0 0 0 A v g. Anl. Chg: -1 1 .2 6 % YEAR ■^— Actual F ig u re 1 1 3 - o - Exponential Trend P e a r s N u m b e r o f T r e e s , 2 1 -Y ear T re n d , 1 9 7 0 - 1 9 9 0 PEARS; PRODUCTION 21 YR TREN D PRODUCTION 1970 TO 1990 21 - YEAR 40 A verage: 2 0 ,1 9 0 ,4 7 6 3 0 -■ High: 4 5 .0 0 0 .0 0 0 0 5 20 - 10 - Low: 5 .0 0 0 .0 0 0 Avg. Anl. Chg: -6.11 % 80 YEAR Actual - o - Exponential Trend Figure 1 1 4 Pears P roduction, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 88 90 152 PEARS; YIELD 21 YR TREN D YIELD 1970 TO 1990 21 - YEAR a 5.B - A verage: 3 .1 4 a 4 .2 - High: 6 .2 5 9 2.BLow : 0 .9 4 0.0 A v g . Anl. C h g: 5 .2 7 % 72 70 74 76 78 80 82 04 06 08 90 YEAR Actual F ig u re 1 1 5 -© - Linear T tend P e a r s Yields, 2 1 -Y ear T r e n d , 1 9 7 0 - 1 9 9 0 PEARS; PRICE 21 YR TREN D PRICE 1970 TO 1990 31.50 21 - YEAR A verage: $ 0 ,9 6 9 $ 1.20 - High: $ 1 ,3 3 5 5 0 60 -• Low : $ 0 ,4 0 5 o o $0.30 - Avg. Anl. Chg: 3 .8 6 % 70 72 74 80 70 82 84 YEAR Actual Figure 1 1 6 -® - Linear Trend P ears Price, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 86 88 90 153 P r u n e s an d Plums: The pro du ction of p r u n e s and plums fell th r o u g h o u t th e 7 0 ' s an d 8 0 ' s . The pr un e and plum declines w e r e not a s significant a s pears, b u t th e y w e r e e n o u g h to place t h e m in s e c o n d to last place in a n u m b e r of c a te g o r i e s . Acr es h a r v e s te d declined an a v e r a g e annual rate of 4 . 9 6 % , s e e Figure 1 1 8 . Prunes and plum s s h o w e d a small re covery in a c r e s h a r v e s t e d bo uncing b ack from a low of 2 . 8 t h o u s a n d a c r e s in 1 9 8 3 to r ea ch 3 . 7 t h o u s a n d a c r e s in 1 9 9 0 . The trend for th e n u m b e r of fruit bearing t re e s m o v e d in close t a n d e m with th e a c r e s h a r v e s t e d t re nd, falling an a v e r a g e an nual rate of 4 . 3 3 % . Production also tr e n d e d lower declining an a v e r a g e annual rate of 2 . 7 0 % . For th e 21 year period, Mich igan 's prune and plum s e c t o r a v e r a g e d 2 8 . 2 million p o u n d s a year. The cr op yields in cr ea se d slightly, up an a v e r a g e annual rate of 2 . 0 4 % , s e e Figure 121. Price per pou nd fluc tu a te d from a low of $ 0 . 3 6 in 1971 to a high of $ 1 . 5 0 in 1 9 8 5 . The long run price tre nd is an a v e r a g e annual increase of 3 . 8 6 % , th e s e c o n d highest g r o w t h rate for fruit, s e e Table IV. The incr ea se in p rune an d plum prices w a s e n o u g h to offs et th e declining trend for production an d g e n e r a t e a small positive tre nd for th e value of production. Michigan's prune and plum crop w a s valued a t an a v e r a g e of $ 2 . 4 million a yea r for t h e 21 yea r period of analysis. T he w e s t side of th e s t a t e p r o duced m o s t of th e p r u n e s an d plums in t h e 7 0 ' s an d 8 0 ' s . The co u n tie s of Leelanau, O c e a n a , an d Van Buren p r oduce m o s t of th e fruit. The Stan ley variety a c c o u n t e d for 8 5 % of th e total s t a t e a c r e a g e . In 1 9 9 0 Michigan ranked 5th in the c o u n tr y in pro du ction , producing 2 . 2 % of th e total U.S. to n n a g e , California is th e leading pro du ce r. 154 PRUNES & PLUMS; VALUE OF PRODUCTION 21 YR TREND VALUE OF PRODUCTION 1970 TO 1990 $3,600 21 - YEAR $2,860 -• A verage: $ 2 ,3 5 4 ,9 0 5 High: $ 3 ,3 1 2 ,0 0 0 L ow : $ 1 ,4 4 0 ,0 0 0 $720 -• A v g . Aril. C hg: 0 .8 7 % 88 YEAR Actual - o - Linear Trend F ig ure 1 1 7 P r u n e s & P lu m s V a lu e o f P r o d u c tio n , 2 1 -Y ear T r e n d , 1 9 7 0 1990 PRUNES & PLUMS; ACRES HARVESTED 21 YR TREND 1970 TO 1990 A CRES HARVESTED 90 21 - YEAR cn K-B5.4 -• Q£ A verage: 4 ,7 2 4 High: 7 ,4 0 0 L ow : 2 ,8 0 0 00 86 88 90 YEAR Actual - o - Exponential Trend Figure 1 1 8 P ru n e s & P lum s A c res H arv ested , 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 Avg. Anl. Chg: -4 .9 6 % 155 PRUNES & PLUMS; NUMBER OF TREES 21 YR TREND 1970 TO 1990 NUMBER OF TREES 800 640 -■ 21 - YEAR A verage: 4 5 9 ,2 8 6 High: 7 0 0 .0 0 0 LU CD 160 - L ow : 2 7 5 .0 0 0 06 80 80 90 YEAR ■Actual F ig u re 1 1 9 A v g . Anl. C h g: -4 .3 3 % Exponential Trend P r u n e s & P lu m s N u m b e r o f T r e e s , 2 1 -Y ear T r e n d , 1 9 7 0 - 1 9 9 0 PRUNES & PLUMS; PRODUCTION 21 YR T R E N D PROD U CTIO N 1970 TO 1990 21 - YEAR 40 - Q z3 =§£ A verage: 2 8 ,1 9 0 ,4 7 6 30 - High: 4 8 .0 0 0 .0 0 0 20 - L ow : 10 1 2 .0 0 0 .0 0 0 - 00 82 00 Avg. Anl. Chg: -2 . 7 0 % 90 YEAR — Actual -e>- Linear T rend Figure 1 2 0 P runes & P lum s P ro d u ctio n , 21 -Year Trend, 1 9 7 0 - 1 9 9 0 156 PRUNES & PLUMS; YIELD 21 YR TRE N D 1970 TO 1990 YIELD BO 21 - YEAR a. 4.8 - A verage: 3 .2 2 Q- 3 6 - High: 5 .1 6 Low : 1 .6 2 A v g . Anl. Chg: 2 .0 4 % 00 YEAR — F ig u re 1 2 1 Actual -© - Linear Trend P r u n e s & P lu m s Yield, 21 -Y ear T r e n d , 1 9 7 0 - 1 9 9 0 PRUNES & PLUMS; PRICE 21 YR TREND 1970 TO 1990 PRICE $1 60 21 - YEAR $1 28 - A verage: $ 0 ,9 0 4 High: $ 1 ,4 9 5 O o $0.64 - Low: $ 0 ,3 6 0 $0 32 - $0 00 86 YEAR ■Actual Linear Trend Figure 1 2 2 P run es & Plums Price, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 80 Avg. Anl. Chg: 3 .8 6 % 90 157 S w e e t Cherries: Michigan s w e e t cherries a c r e s h a r v e s t e d h av e tre n d e d lower during th e d e c a d e s of th e 7 0 ' s an d 8 0 ' s , falling at an a v e r a g e annual rate of 1 . 7 4 % , s e e Figure 132 . Th e path of th e actual ac r e s h a r v e s t e d h o w e v e r , can be broken into t w o different s e g m e n t s . The first s e g m e n t declined from th e level ar ound 12 t h o u s a n d a c r e s in th e early 7 0 ' s , to a low of 7 , 5 0 0 a c r e s in 1 9 8 2 , a drop of over 3 3 % . Th e s e c o n d s e g m e n t is an increasing tre nd in a c r e s h a r v e s t e d , a c r e s h a r v e s te d e x p a n d e d ev e r y yea r from 1 9 8 2 to 1 9 9 0 , up from 7 , 5 0 0 t o 9 , 9 0 0 a c r e s . The nu m b er of fruit bearing t r e e s followed a similar trend prog re ssion a s a c r e s h ar v este d , first declining an d th e n recovering at t h e end of t h e 1 9 8 0 ' s . Th e 21 yea r trend for s w e e t cherry pr od uct io n w a s fairly flat,91 increasing an a v e r a g e an nual rate of 0 . 3 0 % . The s t a t e a v e r a g e d a crop of 51 million p o u n d s a yea r for t h e t w o d e c a d e s . Cherry yields per a c r e s improved en o u g h to o f fs e t th e declines in a c r e a g e h a r v e s t e d to n e t t h e positive pro duc tion tre nd . Th e yields in c r e a se d an a v e r a g e annual a m o u n t of 1 . 9 5 % , s e e Figure 127. Prices rose steadily from a low of $ 0 . 1 0 in 1971 to a high of $ 0 . 3 3 in 1 9 8 8 , and t h e n m o d e r a t e d . Th e price tre nd per si ste d a t an a v e r a g e annual rate of 4 . 6 0 % , this w a s th e highes t calc ulated price tre nd for t h e fruit cr op s, s e e Table IV. T he value of production tre nd w a s also highly positive, s e c o n d in rank for p e r c e n t a g e c h a n g e . Value of production w a s ex tremely variable, ranging from a low of $ 4 . 2 million in 1 9 7 0 to a high of $ 1 8 . 4 in 1 9 8 7 , t h e 21 y ear a v e r a g e w a s 91 E v e n t h o u g h t h e p r o d u c t i o n t r e n d w a s a m o d e s t i n c r e a s e , s w e e t c h e r r i e s w e r e o n e o f on ly fo u r fru it c r o p s p o s tin g p o s itiv e g a in s ( a p p le s , g r a p e s , a n d t a r t c h e r r ie s w e r e t h e o t h e r s ) , s e e T a b l e IV. 158 $ 1 0 million, s e e Figure 123. More t h a n 8 0 % of Mich igan 's s w e e t cherry cr op is g r o w n in the n o r t h w e s t region of th e s t a t e . T w o co u n t ie s alone, Leelanau and Grand T raverse , p r o d u c e m o s t of th e cherry crops. In 1 9 9 0 Michigan ranked 4th in t h e c o u n t r y in s w e e t cherries produced, W a s h i n g to n w a s first. Total Michigan p o u n d s p r o d u c e d eq ualed an 8 . 6 % s h a r e of th e U.S. produc tion. SWEET CHERRIES; VALUE OF PRODUCTION 21 YR TREND 1970 TO 1990 VALUE OF PRO DU CTIO N $20 $ 1 6 -• 21 - YEAR A verage: $ 1 0 ,0 7 6 ,4 2 9 $8 High: $ 1 8 ,4 3 6 ,0 0 0 -■ $4 - Low: $ 4 ,2 4 2 ,0 0 0 80 YEAR Actual 88 90 -© - Linear Trend Figure 1 2 3 S w e e t Cherries Value of Production, 2 1 -Year Trend, 1 9 7 0 1990 Avg. Anl. Chg: 4 .5 7 % 159 SWEET CHERRIES; ACRES HARVESTED 21 YR TREND 1970 TO 1990 ACRES HARVESTED 14 0 21 - YEAR & -8 Q£ Average: 9,843 84 - High: 12 ,1 00 Low: 7,500 00 BO YEAR — Fi gure 1 2 4 Actual 82 86 88 90 Avg . Anl. Chg: -1.74% - o - Exponential Trend S w e e t C h e r r i e s A c r e s H a r v e s t e d , 2 1 -Year T r e n d , 1 9 7 0 - 1 9 9 0 SWEET CHERRIES; NUMBER OF TREES 21 YR TREND 1970 TO 1990 NUMBER OF TREES 1 .1 0 0 UJ I/. UJ T3 880 -■ 21 - YEAR 660 - Average: 825.000 m Is t *5 L L i High: 980.000 220 Low: 625.000 -■ 8G 90 YEAR — Actual -e>- Exponential Trend Figure 1 2 5 S w e e t Cherries N u m b e r of Trees, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 Avg. Anl. Chg: -1.48% 160 SWEET CHERRIES; PRODUCTION 21 YR T RE ND 1970 T O 1990 PRODUCTION BO 21 - YEAR 48 Average: 5 1,190,476 32 High: 7 5.000.000 16 Low: 2 7.000.000 0 00 90 A v g. Anl. Chg: 0.30% YEAR — Fi gure 1 2 6 Actual - o - Exponential T rend S w e e t C h e r r i e s P r o d u c t i o n , 2 1 -Year T r e n d , 1 9 7 0 - 1 9 9 0 SW EET CHERRIES; YIELD 21 YR TREND 1970 TO 1990 YIELD 21 - YEAR 4 - Average: 2.69 111 „ CL 3 - V) 3 High: 4.13 _ O l . . . n * Low: 1.16 Avg. Anl. Chg: 1.95% 00 YEAR — Actual - o - Linear T rend Figure 1 2 7 S w e e t Cherries Yield, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 90 161 SW EET CHERRIES; PRICE 21 YR TREND 1970 TO 1990 PRICE $0 40 21 - YEAR $ 0.32 - Average: $0,200 High: $0,329 $ O O 0.16 -■ Low: $0,096 $ 0.00 - A v g . Anl. Chg: 4.60% $0 00 YEAR ■Actual F igur e 1 2 8 - o - Linear Trend S w e e t C h e rr i es Price, 2 1 -Year T r e n d , 1 9 7 0 - 1 9 9 0 Tart Cherries: Tart cherries are o n e of th e s t a t e ' s m o s t significant fruit cr o p s in t e r m s of value of p rodu ction and national m arket s h are. T he n o r t h w e s t s e c t o r of t h e s t a t e w a s th e leading p r o ducer of tart cherries in t h e d e c a d e s of t h e 7 0 ' s an d 8 0 ' s . The primary producing c o u n t ie s in this ar ea w e r e Grand T r av er se, Leelanau, and O c e a n a . In 1 9 9 0 Michigan ranked 1st in th e c o untry in ta r t cherries produced, a c c o u n ti n g for 7 6 . 6 % of th e U.S. total. Acr es h a r v e s te d of tart cherries tr e n d e d gradually d o w n w a r d in th e d e c a d e s of th e 7 0 ' an d 8 0 ' s , falling a t an a v e r a g e annual rate of 0 . 8 3 % , this w a s t h e s e c o n d smallest a c r e a g e decline for fruit, s e e Table IV. Th e high for a c r e s h a r v e s t e d w a s 3 9 . 5 t h o u s a n d in 1 9 7 0 an d th e low w a s 2 7 . 0 t h o u s a n d in 1 9 8 2 . Since 1 9 8 2 a c r e s h a r v e ste d hav e r e covere d s o m e of t h e lost ground by ex p a n d in g a b o v e 3 2 t h o u s a n d acr es , s e e Figure 13 0. The tre nd for the 162 n u m b e r of fruit bearing c herry tr e e s w a s a positive a v e r a g e an nu al rate of 0 . 3 6 % . 92 For th e t w o d e c a d e s t h e tart cherry tr e e s a v e r a g e d 3.1 million annually, in 1 9 9 0 th e r e w e r e 3 . 4 5 million tr ees , just b e lo w t h e high of 3 . 6 million in 1 9 8 7 . Cherry yields improved gradually, increasing an a v e r a g e an nual rate of 1 . 6 5 % , last for all fruit cr ops , s e e Table IV. A typical har v ested a c r e p r o duced an a v e r a g e of 2 . 6 million p o u n d s of tart ch erries over th e 21 y e a r period. Total pro du ction tr e n d e d higher while having quite a bit of variability, s e e Figure 13 2. Tart cherry production incr ea se d an a v e r a g e an nual a m o u n t of 1 . 4 2 million p o u n d s a year. Price per p o u n d of tart cherries e x p a n d e d an a v e r a g e annual a m o u n t of only 2 . 0 0 % , ranking 7th for t h e fruit c r o p s , s e e Table IV. The in c r e a s e s in both produ ction and price t re n d s g e n e r a t e d a positive tre nd for th e value of production. Tart cherries crop value of pro ductio n in cr eased an a v e r a g e annual rate of 1 . 9 2 % , and a v e r a g e d in dollar t e r m s $ 3 2 million a y e a r during th e 7 0 ' s and 8 0 ' s . 92 The only other positive growth trend was calculated for apples. 163 TART CHERRIES; VALUE OF PRODUCTION VALUE OF PRODUCTION 21 YRTREND 1970 TO1990 $60 21 - YEAR $40 - Average: $32,169,714 High: $56,832,000 Low: $1 1 , 2 9 7 , 0 0 0 A vg . Anl. Chg: 1.92% YEAR ■Actual Linear T rend Fi gure 1 2 9 T a r t C h e r r i e s V al u e o f P r o d u c t i o n , 2 1 -Year T r e n d , 1 9 7 0 - 1 9 9 0 T A R T C H E R R IE S ; A C R E S H A R V E S T E D 2 1 YR TREND 1970 TO 1990 A CRE S HARVESTED 21 - YEAR 36 - Average: 32,486 High: 39,500 Low: 27,000 908 YEAR ■Actual Exponential Trend Figure 1 3 0 Tart Cherries A c r e s Ha r ve st ed , 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 Avg. Anl. Chg: -0.83% 164 TART CHERRIES, NUMBER OF TREES 21 YR TREND NUMBER OF TREES 1970 TO 1990 4.200 cn UJ UJ 21 - YEAR 3.360 £ 2.620 -- Average: 3,092,857 £ .1 .6 0 0 - High: 3.600.000 lu Low: 2.600.000 840 - 86 90 A v g. Anl. Chg: 0.36% YEAR Actual Fi gure 1 3 1 - o - Exponential Trend T a r t C h e r r i e s N u m b e r of T r e e s , 2 1 -Year T r e n d , 1 9 7 0 - 1 9 9 0 TART CHERRIES; PRODUCTION 21 YR TREND PRODUCTI ON 1970 TO 1990 275 21 - YEAR Average: 168,761,905 co — 165 O£ High: 265.000.000 A §1 PS Low: 87.000.000 55 - Avg. Anl. Chg: 0.84% 82 86 00 YEAR Actual - o - Linear Trend Figure 13 2 Tart Cherries Production, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 98 165 TART CHERRIES; YIELD 21 YR T R E ND 1970 T O 1990 YIELD 55 21 - YEAR Average: 2.60 cl 3.3 - High: 4.81 in □ z £>2 .2 - Low: 1.46 A v g. Anl. Chg: 1.65% 00 YEAR Actual Fi gure 1 3 3 - o - Linear T rend T a r t C he r r i e s Yield, 2 1 -Year T r e n d , 1 9 7 0 - 1 9 9 0 TART CHERRIES; PRICE 21 YR TREND 1970 TO 1990 PRICE $ 0 60 21 - YEAR $0 40 - Average: $0,226 f t $ 0 36 -■ High: $0,491 a m $ 0 24 - Low: $0,072 $ 0 12 - A v g . Anl. Chg: 2 .00% $0 00 YEAR Actual - o - Exponential Trend Figure 1 3 4 Tart Cherries Price, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 166 General V egetable Overview This s ection reviews th e im portant cr op t r e n d s of price, yield, a c r e s h a r v e s t e d , quan tity p r o d u c e d , and value of production, for e a c h of Michigan's to p thirteen v e g e ta b l e c r o p s . 93 Table V is a tre nd s u m m a r y of ve g e ta b l e crop s ranked by th e a v e r a g e annual p e r c e n t c h a n g e s for e a c h c a t e g o r y (yields, price, etc. ). Figures 13 5 and 1 3 6 are the ag g r e g a tio n of all v e g e ta b le cr o p s for the ca te g o r ie s of value of pro du ction and a c r e s h a r v e s te d . Total Michigan v e g e ta b le crop a c r e s h a r v e ste d h av e tre nded higher during t h e last t w o d e c a d e s , increasing at an a v e r a g e annual rate of 0 . 8 3 % , s e e Figure 138. Ac res h a r v e s te d of v e g e t a b l e s s to o d at 88.1 t h o u s a n d in 1 9 7 0 , and inc rea se d to 1 1 6 . 4 t h o u s a n d a c r e s in 1 9 9 0 , up 3 2 % . Th e value of ve g e ta b l e production rose t h r o u g h o u t m o st of t h e 7 0 ' s and 8 0 ' s . Total crop value incre ased an a v e r a g e annual a m o u n t of $ 4 . 6 million or 4 . 2 9 % . A high of $ 1 5 5 million w a s record in 1 9 8 3 and th e low occ urre d in 1 9 7 0 at $ 4 8 million. 93 The selection of the top seven Michigan vegetable crops for the analysis is predicated on the value of production for each crop. 167 T a b l e V T r e n d S u m m a r y for V e g e t a b l e C r o p s , C o m m o d i t y R a n k b y A v e r a g e A n n u a l % C h a n g e f or 2 1 - Ye ar s, 1 9 7 0 - 1 9 9 0 TREND S U M M A R Y FOR V e g e t a b l e C R O P S C OM MO DI T Y RANK BY AVERAGE ANNUAL % CHANGE FOR 2 1 - Ye ar S FROM 1 9 7 0 - 9 0 Production rAMc ri ce ds H n dairvveeas it e ud Rank 1 2 3 4 5 6 7 8 9 10 11 12 13 Commodity % Ch g. Rank S n a p Beans Tomatoes, process Asparagus Ce le ry C a u li f lo w er Carrots Onions S w e e t Corn Cucumbers Lettuce T o m a t o e s , f r e sh Strawberries Mushrooms 2.83% 2.49% 2.41 % 1.84% 1.35% 1.18% 0.78% -0.33% -0.58% - 2 . 31 % -2.53% -3.48% -5.04% 1 2 3 4 5 6 7 8 9 10 11 12 13 Average -0.1 1 % 1 2 3 4 5 6 7 8 9 10 11 12 13 % Chg. Tomatoes, process Snap Beans Ca ul i f l o w e r Cucumbers Carrots Celery M ushrooms Asparagus Onions S w e e t Co r n Lettuce T o m a to e s, fresh Strawberries 5.62% 3.61 % 2.14% 1.98% 1.98% 1.79% 1.17% 0.92% 0.53% -0.68% -1.24% -2.35% -2.62% Average 0.99% Price Yield Rank Commodity Commodity % Chg. Rank M ushrooms Tomatoes, process Cucumbers Lettuce Carrots C a u l if l ow e r Sn a p Beans Strawberries T o m a t o e s , f r e sh Ce le ry Onions S w e e t Corn Asparagus 5.99% 3.53% 2.43% 1.00% 0.82% 0.80% 0.80% 0.71% 0.04% 0.02% -0.23% -0.35% -1.58% 1 2 3 4 5 6 7 8 9 10 11 12 13 Ave rag e 1.01% % Ch g . Commodity S w e e t Co r n Ca ul i f l o we r Lettuce Asparagus T o m a to es , fresh Onions Strawberries Celery Cucumbers Tomatoes, process Mushrooms Sn a p Beans Carrots 6.18% 5.77% 5.33% 4.41 % 3.65% 3.53% 3.51 % 3.23% 2.87% 2.79% 2.77% 2.59% 1.80% Average 3.73% 168 T a b l e V ( C o nt i n u ed ) T r e n d S u m m a r y for V e g e t a b l e C r o p s , C o m m o d i t y R a n k b y A v e r a g e A n n u a l % C h a n g e f o r 2 1 -Years, 1 9 7 0 - 1 9 9 0 TREND S U MM A RY FOR V e g e t a b l e C R O P S CO MM O D IT Y RANK BY AVERAGE ANNUAL % CHANGE FOR 2 1 - YearS FROM 1 9 7 0 - 9 0 Va lue of P r o d u c t i o n Ra nk 1 2 3 4 5 6 7 8 9 10 11 12 13 Commodity % Chg. Ca ul i f l o we r Tomatoes, process Snap Beans S w e e t Cor n Asparagus Cucumbers Celery Lettuce Mushrooms Carrots Onions T o m a t o e s , f re sh Strawberries 7.35% 7.35% 6.52% 6.22% 5.13% 5.05% 4.57% 3.99% 3.97% 3.53% 3.31% 1.29% 1.15% Average 4.57% 169 TOTAL VEGETABLES VALUE O F PR O DU CT I ON T RE ND VALUE OF PRODUCTION 1970-90 21 - YEAR Average: $106,685,954 oz $72 -• High: $155,125,372 $36 - Low: $48,089,995 A vg . Anl. Chg: 4.29% YEAR Actual - o - L in e a r Trend Fi gure 1 3 5 Tot al V e g e t a b l e s V a l u e of P r o d u c t i o n , 2 1 - Y e a r T r en d , 1970-1990 TOTAL VEGETABLES ACRES HARVESTED A C RE S HARVESTED 21 YR TREND 1970-90 140 21 - YEAR Average: 101,941 C/5^ 84" *<* si/> 3 n 56 - High: 116,400 Low: 20 - 8 8,1 00 82 ^ — Actual 86 90 - o - L in e a r T rend Figure 136 Total V eget ab les A c r e s Ha rv es ted , 21 -Year Trend, 1 9 7 0 - 1 9 9 0 Avg. Anl. Chg: 0.83% 170 A s p a r a g u s (Dual Purpose): A s p a ra g u s s h o w e d noticeable in c r e a s e s in a c r e s h a r v e s t e d and production during the 7 0 ' s and 8 0 ' s . Acres h a r v e s te d incr ea sed an a v e r a g e annual rate of 2 . 4 1 % , third hi ghes t for all ve g e ta b le s , s e e Table V. In 1 9 7 0 1 2 . 4 t h o u s a n d a c r e s w er e h a r v e s t e d in Michigan, by 1 9 9 0 , a c r e s h a r v e s t e d had risen to a s t a t e record of 2 3 . 5 t h o u s a n d acr es, s e e Figure 138. Production tre nd ed higher with an a v e r a g e an nu al g r o w th rate of 0.96% . In 1 9 9 0 t h e s t a t e p r o duced a record h a r v e s t of 2 5 9 , 0 0 0 Cwt. A s p a r a g u s yields t re nded d o w n in the 7 0 ' s an d improved in th e 8 0 ' s . Yields per ac re in h u n d r e d w e ig h t declined an a v e r a g e annual rate of 1 . 5 8 % , last for all v eg etab le crops. The price of a s p a r a g u s m ove d from th e low $ 2 0 ' s Cw t. to th e high $ 5 0 ' s per Cwt. in the 8 0 ' s . per Given t h e incr ea se in both th e tre nd for price and production, th e trend for the value of pro duction also incr ea se d. The value of production rose at an a v e r a g e an nual rate of 5 . 1 3 % . Michigan p r o d u c e s more process ing a s p a r a g u s t h a n fresh market a s p a r a g u s . In 1 9 9 0 , 1 0 . 4 t o n s of p r o c e s s e d a s p a r a g u s w e r e h a r v e s t e d c o m p a r e d to 5 1 , 0 0 0 h u n d r e d w e ig h t of fresh m ark et a s p a r a g u s . In 1 9 9 0 Michigan ranked 3rd in the c o un tr y in a s p a r a g u s o u t p u t b a s e d on p o u n d a g e , with a s hare 1 0 . 6 % , California is the leading producer. 171 ASPARAGUS; DUAL PURPOSE VALUE OF PRODUCTION TREND VALUE OF PRODUCTION 1970-90 21 - YEAR $16 - Average: $11,025,496 .<7: $8 High: $1 5 , 5 4 4 , 8 0 0 - Low: $4,158,000 $4 - A v g. Anl. Chg: 5.13% YEAR N ote e s tim a te s we *0 a < ro V) v_v 3 3! O High: 23,500 Low: 12,400 86 88 90 YEAR N ote e s tim a te s w ere not m ad e in 1982 an d 1963 • Actual -© - Linear T rend Figure 1 3 8 A s p a r a g u s (Dual P urpos e) Ac res H a rv es t ed , 2 1 -Year Trend, 1970-1990 Avg. Anl. Chg: 2. 41 % 172 ASPARAGUS;DUAL PURPOSE PR OD U CT I ON 21 YR T REND 1970-90 PRODUCTION 300 21 - YEAR 240 -■ Average: 227 f 180 - “ 120 High: 259 - Low: 171 60 - Avg . Anl. Chg: 0.96% YEAR N ote e s tim a te s w e ie not m a d e in 1962 and 1963 Fi gure 1 3 9 1990 Actual ~ o - Exponential Trend A s p a r a g u s (Dual P u r p o s e ) P r o d u c t i o n , 2 1 -Year T r e n d , 1 9 7 0 - ASPARAGUS; DUAL PURPOSE YIELD 21 YR TREND 1970-90 18 0 YIELD 21 - YEAR Average: 144 1 2. 2 UJ o: o< 0 8 aU J High: 16.0 C L ot 7 2 Low: 9.0 36 Avg. Anl. Chg: -1.58% 00 YEAR N ote e s tim a te s w ere not m a d e in 1962 and 1963 ■Actual Exponential T rend Figure 1 4 0 A s p a r a g u s (Dual Purpose) Yield, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 173 ASPARAGUS; DUAL PURPOSE PRICE 21 YR T REND PRICE 1970-90 $75 21 - YEAR $60 - Average: $47.9 a. $45 --- L U CL (r High: $67.4 3 $30 --- Low: $21.0 $15 - Avg . Anl. Chg: 4.41% 80 YEAR N ote e s tim a te s w ere not m a d e in 1962 and 1903 Fi gur e 1 4 1 Actual 86 - o - Linear T rend A s p a r a g u s (Dual P u r p o s e ) Price, 2 1 -Year T r e n d , 1 9 7 0 - 1 9 9 0 Ca rrots (Dual Purpose): Carrot a c r e a g e h a r v e ste d tr e n d e d higher during th e 7 0 ' an d 8 0 ' s . Acr es e x p a n d e d at an a v e r a g e annual rate of 1 . 1 8 % , s e e Figure 143. In 1 9 8 4 t w o s t a t e r eco rd s w e r e se t, (1) 7 , 5 0 0 a c r e s h a r v e s te d and (2) pro duct io n of 2 . 0 3 million C w t. Following th e record yea r of production, t w o y e a r s of significant declines occ urre d d u e to a d v e r s e w e a t h e r conditions. From 1 9 8 6 to 1 9 9 0 , h o w e v e r , ac r e s h a r v e s te d r e s u m e d th e earlier u pw ard tre nd . Pro du ction in h u n d r e d w e i g h t e x p a n d e d at an a v e r a g e annual rate of 1 . 9 8 % , or 2 9 , 6 0 0 Cwt. a year, th e 5th f a s t e s t v e g e ta b l e pro ductio n trend, s e e Table V. Yield per a cr e m ov ed co nsis tently higher, increasing a t an a v e r a g e an nual rate of 0 . 8 2 % . The 21 year yield high w a s s e t in 1 9 9 0 at 2 8 0 Cw t. per acre. Carrot price per Cw t. tre n d e d higher at an a v e r a g e annual rate 174 of 1 . 8 0 % . 94 The com bination of expan ding car rot o u tp u t and higher carrot prices g e n e r a t e d incre ased value of production. The value of production tr e n d e d higher at an a v e r a g e annual rate of 3 . 5 3 % , ranked 10 th for the v e g e ta b le cr o p s analyzed. Michigan ranked 3rd in the c o u n tr y in total carrot o u t p u t in 1 9 9 0 , producing 6 . 5 % of th e U.S. total har ve st, California w a s the leading producer. CARROTS; DUAL PURPOSE VALUE OF PRODUCTION TREND 1970-90 VALUE OF PRODUCTION $25 $20 21 - YEAR - A ve r ag e : $13,350,640 x> High: $21,362,500 o $5 - Low: $5,332,320 GO Y EA R — —Actual 00 - o - Linear T rend Fi gur e 1 4 2 C a r r o t s (Dual P u r p o s e ) Va lu e o f P r o d u c t i o n , 2 1 - Year T r e nd , 1970-1990 94 T h e s m a l l e s t t r e n d g r o w t h f o r v e g e t a b l e p r i c e s , s e e T a b l e V. A vg . Anl. Ch g : 3.53% 175 CARROTS; DUAL PURPOSE ACRE S HARVESTED A C R E S HARVESTED 21 YR T RE ND 1970-90 21 - YEAR 7 2 -■ Average: 6,043 LU r A Ct -o 0.4 High: 7,500 Low: 3,700 A v g. Anl. Chg: YEAR Actual - o - Linear Trend Fi gure 1 4 3 C a r r o t s (Dual P u r p o s e ) A c r e s H a r v e s t e d , 2 1 -Year T r e nd , 1970-1990 CARROTS; DUAL PURPOSE P R OD U CT I ON 21 YR TREND 1970-90 P RODUCTI ON 21 - YEAR 1,760 - Average: 1,495 % 1,320 -■ o 980 - High: 2,025 440 - Low: 925 CD CD ° 86 03 90 YEAR ■Actual -O - Linear Trend Figure 1 4 4 C ar r o t s (Dual P ur pos e) Production, 2 1 -Year Trend, 1 9 7 0 1990 Avg. Anl. Chg: 1.98% 176 CARROTS; DUAL PURPOSE YIELD 21 YR TREND 1970-90 YIELD 375 21 - YEAR 260 -■ Average: 246 Jo- LU O 195 - High: 280 Ui i 130 -■ Low: 195 65 - A v g. Anl. Chg: 0.82% YEAR — Fi gur e 1 4 5 Actual -O - Linear Trend C a r r o t s (Dual P u r p o s e ) Yield, 2 1 -Year T r e nd , 1 9 7 0 - 1 9 9 0 CARROTS; DUAL PURPOSE PRI CE 21 YR T REND 1970-90 PRICE $13 0 21 - YEAR $104 - Qt UJ Average: $8.85 $7 8 - - High: $12.50 Q. cr> $5 2 Low: $4.83 O Q $2 6 - Avg. Anl. Chg: 1.80% $0 0 80 YEAR ----- Actual - o - L inearT rend V. Figure 1 4 6 Carr ots (Dual P urpos e) Price, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 177 Cauliflower (Dual Purpose): For th e d e c a d e s of th e 7 0 ' s an d 8 0 ' s th e s ta t e a v e r a g e d 1 , 0 9 7 a c r e s h a r v e s t e d of dual p u r p o s e cauliflower. Th e 21 -year tre nd for a c r e s h a r v e s t e d w a s gradually higher with an a v e r a g e an nu al in c r e a se of 1 . 3 5 % , 5th for all v eg e t a b l e s . Cauliflower yields also improved steadily, climbing from a low of 41 Cw t. per ac re in 1 9 7 3 to a high of 7 0 C w t. per a cr e in 1 9 9 0 . 95 Th e higher yields coup led with e x p a n d e d a c r e s h a r v e s t e d led to an i ncrease in total production. Cauliflower production tr e n d e d higher, e x p anding at an annual a v e r a g e rate of 2 . 1 4 % , s e e Figure 1 4 9 . Total o u t p u t a v e r a g e d 6 3 , 3 0 0 Cwt. a year. Figure 151 s h o w s th e significant rise in t h e price of cauliflower per h u n d r e d w e i g h t in th e last 21 y ear s. Th e price of cauliflower incre ased at an a v e r a g e annual rate of 5 . 7 7 % , s e c o n d h ig h est rate for all v eg e t a b l e s , and tra ded in a rang e b e t w e e n $ 6 . 7 0 a n d $ 3 9 . 5 0 per Cwt. Th e trend of rising prices an d inc rea se d production yielded higher cauliflower value of production. The value of pro du ction trend e x p a n d e d a t an a v e r a g e an nual rate of 7 . 3 5 % , tied for 1st for all ve getable c r o p s , s e e Table V. In th e 8 0 ' s , th e value of cauliflower pro du ction av e r a g e d over $ 2 . 5 million a year. Michigan w a s ranked 5th in th e c o u n tr y in cauliflower o u t p u t in 1 9 9 0 , producing 0 . 9 % of th e U.S. total, California and it's multiple growing s e a s o n s w a s th e leading s ta te . 95 T h e s t a t e r e c o r d y i e l d w a s 1 4 1 C w t . p e r a c r e s e t in 1 9 4 9 . 178 CAULIFLOWER; DUAL PURPOSE VALUE OF PRODUCTION TREND VALUE OF PRODUCTION 1970-90 $4 non 21 - YEAR $ 3 ,2 0 0 -■ Average: $1,761,106 High: $3,439,800 Low: $517,000 $800 - 90 A vg . Anl. Chg: 7.35% YEAR Actual - o - Linear Trend Fi gur e 1 4 7 C a u l i f l o w e r (Dual P u r p o s e ) Va lu e of P r o d u c t i o n , 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 CAULIFLOWER; DUAL PURPOSE ACRES HARVESTED 21 YR TREND 1970-90 A CR E S HARVESTED 1.700 21 - YEAR 1,360 - o if) £ o< Average: 1,097 1 ,0 2 0 -- High: 1,500 600 - Low: 700 340 - 70 06 90 YEAR — Actual - o - Linear Trend Figure 1 4 8 Cauliflower (Dual Purpose) Ac r es H ar ves t ed, 2 1 -Year Trend, 1970-1990 Avg. Anl. Chg: 1.35% 179 CAULIFLOWER; DUAL PURPOSE PR OD U CT I ON 21 YR T RE ND 1970-90 PRODUCTION 1 21 - YEAR 88 £ u o Average: 63.3 66 - High: 98.0 CD 44 - Low: 38.0 22 - A v g. Anl. Chg: 2.14% YEAR ■^—Actual Fi gure 1 4 9 1990 - o - Linear T rend C a u li f l ow e r (Dual P u r p o s e ) P r o d u c t i o n , 2 1 -Year T r e nd , 1 9 7 0 - CAULIFLOWER; DUAL PURPOSE YIELD 21 YR TREND 1970-90 YIELD 21 - YEAR 64 - - Average: 57.2 LU O 48 -■ High: 70.0 iu 32 - Low: 40.9 Avg. Anl. Chg: 0.88% 66 YEAR — Actual -o -E x p o n e n tia l Trend Figure 1 5 0 Cauliflower (Dual P urpos e) Yield, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 180 CAULIFLOWER; DUAL PURPOSE PRI CE 21 YR T R EN D PRICE 1970-90 $50 21 - YEAR Average: $26.7 a $30 - LU CL High: $39.5 cn 3 $20 - - Low: $6.7 $10 - Av g. Anl. Chg: 5.77% YEAR — Fi gure 1 5 1 Actual -c»- Linear T rend Ca ul if l ow er (Dual P u r p o s e ) Price, 2 1 -Year T r e n d , 1 9 7 0 - 1 9 9 0 Celery (Dual Purpose): The nu m b er of celery a c r e s h a r v e s t e d s h o w e d m o d e s t gains in t h e d e c a d e s of th e 7 0 ' s and 8 0 ' s , ranging from a low 2 , 3 0 0 a c r e s to a high of 3 , 9 0 0 a cr es. Th e a c r e s h ar v ested tre nd w a s an increase of an a v e r a g e annual rate of 1 . 8 4 % , s e e Figure 1 5 3. This g r o w th rate w a s th e 4th f a s t e s t for all v eg etab le crops, s e e Table V. The yield per acr e remained flat, with an a v e r a g e annual rate of 0 . 0 0 % . From 1 9 7 0 to 1 9 9 0 , celery o u t p u t per acr e a v e r a g e d 4 1 0 Cw t. per y e a r .90 Production tre n d e d higher, increasing at an a v e r a g e an nu al rate of 1 . 7 9 % . Based on th e trend analysis, t h e rise in prod uc tion is primarily a function of the increase in a c r e s h a r v e s t e d , given th e flat yield trend. Celery price per Cwt. tr e n d e d persiste ntly higher, increasing at an a v e r a g e annual rate of 3 . 2 3 % , s e e Figure 156. For th e 21 yea r period 96 In 1 9 8 2 a s t a t e r e c o r d a v e r a g e yi el d o f 4 7 0 C w t . p e r a c r e w a s s e t . 181 t h e price of celery ranged from a low of $ 5 . 9 8 to a high of $ 1 4 . 1 0 , and a v e r a g e d $ 9 . 9 7 per Cw t. The value of p rodu ction t re n d e d higher, increasing a t an a v e r a g e an nu al rate of 4 . 5 7 % , 7th for all v e g e t a b l e s . In t h e 8 0 ' s celery value of produ ction a v e r a g e d app ro xima tely $ 1 5 million a year . Michigan ranked 3rd in th e c o u n t r y in h u n d r e d w e i g h t production, producing 6 . 3 % of t h e U.S. total in 1 9 9 0 , California w a s t h e leading pro du ce r. CELERY; DUAL PURPOSE VALUE OF PRODUCTION TREND 1970-90 VALUE OF PRODUCTI ON $20 21 - YEAR $1 6 - Average: $1 1 , 5 7 3 , 7 6 4 £ —$12 -■ O5 $0 - High: $16,446,500 $4 - Low: $5,226,520 80 88 90 Y EAR — Actual -© - Linear T rend Figure 1 5 2 Celery (Dual P urpos e) Value of Production, 2 1 -Year Trend, 1970-1990 Avg. Anl. Chg: 4.57% 182 CELERY; DUAL PURPOSE ACRES HARVESTED A C R E S HARVESTED 21 YR TRE ND 1970-90 4,200 21 - YEAR 3,360 -■ Average: 2,790 O 72 -• Low: 83 36 - A v g. Anl. Chg: 1.98% YEAR N ote e s tim a te s w ere not m a d e in 1982 an d 1903 Fi gur e 1 5 9 1990 •Actual E>cponential Trend C u c u m b e r s ( P r o c e s s i n g ) P r o d u c t i o n , 2 1 -Year T r e n d , 1 9 7 0 - CUCUMBERS; PROCESSING YIELD 21 YR TREND 1970-90 YIELD 7.0 21 - YEAR Average: 5.06 56 '-O ' LU <42-CL High: 6.70 c LU O. £ 20 - - Low: 3.38 Avg. Anl. Chg: 2.43% 0.0 86 YEAR Note: e s tim a te s w e ie not m ade in 1962 an d 1903 ■A c tu a l - © - L in e a r T r e n d Figure 1 6 0 C u c u m b e r s (Processi ng) Yield, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 187 CUCUMBERS; PROCESSING PRICE 21 YR T REND PRICE 1970-90 21 - YEAR $160 -■ Average: $129 a. $120 - LU CL High: $168 tr> 3 $ 8 0 -- Low: $86 $40 - A v g. Anl. Chg: 2.87% YEAR N ote e s tim a te s w ere not m ad e in 1982 and 1903 Fi gur e 1 6 1 Actual Linear Trend C u c u m b e r s ( P r o c e s s i n g ) Price, 2 1 - Year T r e nd , 1 9 7 0 - 1 9 9 0 Le ttuce (Fresh Market): Fresh lettuce production in t h e 7 0 ' s and 8 0 ' s tre nde d significantly d o w n w a r d . Acres h a r v e s te d fell an a v e r a g e an nua l rate of 2 . 3 1 % , or 2 9 a c r e s a year. In 1 9 7 0 t h e s ta t e h a r v e s te d 1 , 5 0 0 a c r e s of lettuce, by 1 9 8 8 total a c r e a g e had dropped to 8 0 0 an all time record low, s e e Figure 163. Production also declined but a t a slo w er rate, falling an a v e r a g e of 1 . 2 4 % a year. The ne gati v e production trend for lettuce ranked it 1 1th o u t of 13 v e g e ta b le cr ops , s e e Figure 1 64. For t h e 21 year period, th e s t a t e a v e r a g e d 2 5 4 , 0 0 0 Cwt. a yea r in production. Lettuce yields per acr e s h o w e d s t e a d y im pro ve m en t, increasing annually an a v e r a g e of 1 . 0 0 % . 100 In 1 9 8 2 and 1 9 8 5 all time record yields w e r e s e t of 2 5 0 Cw t. per acre. The price of lettuce per h u n d r e d w e ig h t t re n d e d rapidly higher. Increasing at an annual 100 This was the 4th fastest yield growth rate, see Table V. 188 a v e r a g e rate of 5 . 3 3 % , t h e 3rd f a s t e s t g r o w t h tre nd, s e e Table V. The 21 ye ar high price w a s s e t in 1 9 9 0 at $ 2 2 . 3 0 per Cw t. Prices rose at a fast e n o u g h rate to o f fs e t t h e declines in o u t p u t an d e x p a n d lettu ce cr op values. Th e valu e of crop pro duct io n tr e n d e d u p w a r d at an a v e r a g e an nu al rate of 3 . 9 9 % , 8 t h for v e g e ta b le crops. Michigan ranked 9th in th e c o u n t r y in th e pro duct io n of fresh lettuce, producing only 0 . 3 % of t h e total U.S. o u t p u t in 1 9 9 0 , California lead production. LETTUCE; FRESH MARKET VALUE OF PRODUCTION TREND 1970-90 VALUE OF PRODUCTI ON $7 0 21 - YEAR $5 6 - Average: $3,550,584 o —'$ 2 8 - High: $6,160,000 $1 4 - L o w: $1,468,800 $0 0 Avg. Anl. Chg: 3.99% o is YEAR ■Actual Linear T rend Figure 162 L et t uc e (Fresh Market) Value of Product ion, 2 1 -Year Trend, 1970-1990 189 LETTUCE; FRESH MARKET ACRES HARVESTED PRODUCTION 21 YRTREND 1970-90 21 - YEAR 320 -■ ^ 240 - A verage: 1 ,2 6 7 - - 160 -■ High: 1 ,6 0 0 Low: 800 80 - 90 Avg. Anl. Chg. -2.31 % YEAR Actual - o - Linear Trend Figure 1 6 3 L ettuce (Fresh Market) A cres H arv ested , 2 1 -Year Trend, 1 9 70-1990 LETTUCE; FRESH MARKET ACRES HARVESTED 21 YRTREND 1970-90 PRODUCTION 1,800 21 - YEAR 1,440 - A verage: 254 if) ^ 1.080 - O < o I- 720 - High: 375 360 - Low: 140 80 90 YEAR —— Actual - o - Linear Trend Figure 1 6 4 Le tt u ce (Fresh Market) Product ion, 2 1 -Year Trend, 1 9 7 0 1990 Avg. Anl. Chg: -1.24% 190 LETTUCE; FRESH MARKET YIELD 21 YRTREND 1970-90 YIELD 275 21 - YEAR 220 A verage: -• 201 uj O 165 - High: 250 Low: 150 55 - Avg. Anl. Chg: 1.0 0 % YEAR Actual - o - Linear T rend Figure 1 6 5 L ettuce (Fresh Market) Yield, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 LETTUCE; FRESH MARKET PRICE 21 YRTREND 1970-90 $25 $20 O. PRICE 21 - YEAR Average: $ 1 4 .3 - $15 -- High: $ 2 2 .3 aUJ cn 3$10 - Low: $ 5 .8 $5 - Avg. Anl. Chg: 5.33% B2 YEAR ■Actual Linear T rend Figure 1 6 6 Let t uce (Fresh Market) Price, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 191 M u sh r o o m s:101 M u s h r o o m s and their ar ea of pr oduction, declined significantly from 7 , 3 6 3 , 0 0 0 s q u a r e ft. in 1981 to 4 , 0 1 0 , 0 0 0 s q u a r e ft. in 1 9 9 0 , a decline of 4 5 . 5 % , s e e Figure 168. Production in p o u n d s h o w e v e r , tr e n d e d slightly higher, increasing a t an a v e r a g e annual rate of 1 . 1 7 % . For th e d e c a d e of th e 8 0 ' s th e s t a t e a v e r a g e d over 2 0 , 0 0 0 p o u n d s of m u s h r o o m s a year . In 1 9 9 0 Michigan p r o d u c e d 1 9 , 9 0 0 pou nds , e n o u g h to rank 3rd in t h e co u n tr y , a c c o u n t i n g for 2 . 7 % of total U.S. o u tp u t, Pennsylvania w a s th e leading s ta te. The s t a t e ' s production is predominantly th e Button m u s h r o o m an d th e Shiitake varieties. Improved yields helped p us h o u t p u t higher in th e eighties. Yields per s q u a r e ft. tre n d e d higher at an a v e r a g e an nual rate of 5 . 9 9 % , s e e Figure 1 7 0 an d Table V. The yield gr ow th rate w a s clearly th e largest for an y of the v e g e ta b le crops. A s q u a r e foot of m u s h r o o m pro du ctio n ar ea e x p a n d e d its yield an an nu al a v e r a g e of 0 . 2 6 p o u n d s a year. Th e price of m u s h r o o m s per p oun d also i n c r e a s e d . 102 Th e ten-y ea r low w a s $0.7 1 a p ound in 1981 and th e high w a s $ 1 . 0 2 pou nd in 1 9 9 0 . The trend to w a r d higher prices an d o u t p u t , led to an e x p a n s io n of th e value of cr op produ ction. Total crop value r e a c h e d ov er $ 2 0 million tw ic e in the 8 0 ' s , in 1 9 8 8 and 89 . 101 Note: The Michigan Agricultural S tatistics Service started data collection in 1981. 102 The average annual trend rate for mushroom prices was 2 .7 7 % , ranking it 1 1th for all vegetables. 192 MUSHROOMS VALUE O F P R O D U C T IO N TREN D 1 9 8 1 -9 0 VALUE OF PRODUCTION 1 0 - YEAR $2 0 - A verage: $ 1 7 ,3 7 4 ,4 2 6 High: $ 2 0 ,7 1 9 ,4 3 3 $5 No1e: The M ichigan Agricultural S ta tis tic s Service s ta rte d d ata collection in 1981 Figure 1 6 7 Low: $ 1 3 ,4 4 5 ,0 6 4 -■ Avg. Anl. Chg: 3 .9 7 % YEAR - o - Exponential Trend Actual M u sh ro o m s Value of Production, 10 Year Trend, 1 9 8 1 - 1 9 9 0 MUSHROOMS; AREA IN PRODUCTION 10 YRTREND 1981-90 ACRES HARVESTED 80 10 - YEAR 64 - uj ~ 4 I I 1/1 uj A verage: 4 ,9 0 2 ,6 0 0 8 - S High: 7 .3 6 3 .0 0 0 Low: 4 .0 1 0 .0 0 0 Avg. Anl. Chg: -5.04% 00 Note: The M ichigan A gricultural S ta tis tic s S ervice sta rte d d a ta co llectio n in 1981 YEAR -A ctual E xponential T ren d Figure 1 6 8 M u s h r o o m s A c re s H ar ves t ed , 10 Year Trend, 1 9 8 1 - 1 9 9 0 193 MUSHROOMS; PRODUCTION 10 YRTREND 1981-90 PRODUCTION 1 0 - YEAR 20 - in -S A verage: 2 0 ,1 8 9 § S S pI O Q- §i High: 2 3 ,3 5 9 Low: 1 7 ,5 0 6 N ote. The M ichigan A gricultural S ta tis tic s Service s ta rte d d a ta collection in 1901. Avg. Anl. Chg: 1 .1 7 % YEAR ■Actual E xponential T rend Figure 1 6 9 M u s h ro o m s P roduction, 10 Year Trend, 1 9 8 1 - 1 9 9 0 MUSHROOMS; YIELD 10 YRTREND 1981-90 YIELD 6 5 10 - YEAR 5 2 LL A verage: 4 .2 6 A verage: 7 ,3 7 1 7 5.7 - u j •JT c K High: 8 ,5 0 0 Low: 5 ,7 0 0 86 Avg. Anl. Chg: 0 .7 8 % YEAR — Actual - o - L in e a r Trend Figure 1 7 3 O nions (Fresh Market) A cres H a rvested , 2 1 -Year Trend, 1970-1990 ONIONS; FRESH MARKET PRODUCTION 21 YRTREND 1970-90 PRODUCTION 3.200 21 - YEAR 2,560 - A verage: 2 ,2 4 1 5 1,920 -■ High: 2 ,933 1,280 - Low: 1 ,6 5 3 Avg. Anl. Chg: 0.53% A ctual - o - Linear Trend Figure 1 7 4 Oni ons (Fresh Market) Production, 21-Ye ar Trend, 1 9 7 0 1990 197 ONIONS; FRESH MARKET YIELD YIELD 21 YRTREND 1970-90 4DD 21 - YEAR 320 -■ Average: 303 LU O 240 - High: 345 UJ i 160 - Low: 250 80 - Avg. Anl. Chg: -0 .2 3 % YEAR Actual -© - Linear T rend Figure 1 7 5 O nions (Fresh Market) Yield, 2 1-Y ear Trend, 1 9 7 0 - 1 9 9 0 ONIONS; FRESH MARKET PRICE PRICE 21 YRTREND 1970-90 $160 21 - YEAR $12 0 A verage: $ 8 .4 2 - o£ 0~ $9 6 - High: $ 1 4 .3 0 UJ a (/) $6 4 - Low: $ 2 .8 4 O O $3 2 - Avg. Anl. Chg: 3.53% $ 00 8B 90 YEAR ■Actual -o Linear T rend Figure 1 7 6 Oni ons (Fresh Market) Price, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 198 S n a p Beans (Processing): S n a p bean pro duc tion incre ased su bstan tially in th e 7 0 ' s an d 8 0 ' s . All time s t a t e re co rd s w e r e s e t in 1 9 9 0 for th e a m o u n t of a c r e s h a r v e s te d , highes t o n e year yield, an d th e largest o n e y e a r quantity of s n a p b e a n s p r o d u c e d . T h e incr ease in o u t p u t w a s a function of both higher yields an d an e x p a n s i o n in a c r e s h ar v ested . Acres h a r v e ste d in crease d at an a v e r a g e annual rate of 2 . 8 3 % , the highest for all ve g e ta b l e crops, s e e Table V a nd Figure 17 8. From 1 9 7 0 to 1 9 9 0 s n a p b e a n s ac r e s in cr ea se d from 1 0 , 1 0 0 a c r e s to a s ta t e record of 2 7 , 0 0 0 acr es , a rise of 1 6 7 % . Yields also rose but not an d significantly a s a c r e s h a r v e s t e d . The tre nd for yields w a s an a v e r a g e an nual rate of 0 . 8 0 % , 7th for all v eg etab le crops. In 1 9 9 0 an all time record w a s s e t of 2 . 9 5 t o n s of s n a p b e a n s per acre. Production t re n d e d higher, ex p a n d in g at an a v e r a g e an nu al rate of 3.61 %, 2nd for all v e g e t a b le crops. In 1 9 7 0 t h e s t a t e p r o duced 2 0 , 0 0 0 Cwt. of s n a p b eans , by th e record yea r of 1 9 9 0 , 7 9 , 7 0 0 C w t. had b e e n pro d u ced , an incr ea se of a lm o st 3 0 0 % . Th e price pe r of s n a p b e a n s flu ctua ted within a ra nge of $ 1 3 6 per ton to $ 1 7 5 per ton. Price tr e n d e d u pw ard but more slowly th an th e ot her crops, increasing at an a v e r a g e annual rate of 2 . 5 9 % . The value of production increased c o m m e n s u r a t e l y with th e significant rise in production. Value of production e x p a n d e d a t an a v e r a g e an nu al rate of 6 . 5 2 % , 3rd for ve g e ta b le c r o p s. In 1 9 7 0 total crop value equ aled $ 1 . 8 9 million. By 1 9 9 0 th e value of s n a p bea n pro duct io n had risen 6 1 5 % to $ 1 3 . 5 4 million. Michigan ranked 3rd in the nation in p r o c e ss i n g s n a p b e a n s and a c c o u n t e d for 9 . 7 % of U.S. pro du ction in 1 9 9 0 , Wisc onsin w a s first. 199 SNAP BEANS; PRO CESSING VALUE OF PRODUCTION TREND 1970-90 VALUE OF PRODUCTION $15 21 - YEAR $12 in _ O2 - $9 - A verage: $ 5 ,7 5 2 ,2 3 3 $6 High: $ 1 3 ,5 4 0 ,5 0 0 -■ Low: $ 1 ,8 9 4 ,0 0 0 $3 - Avg. Anl. Chg: 6 .5 2 % YEAR Actual -© - Exponential Trend Figure 1 7 7 S n a p B eans (Processing) Value of P roduction, 2 1 -Year Trend, 1970-1990 SNAP BEANS; PROCESSING ACRES HARVESTED 21 YRTREND 1970-90 ACRES HARVESTED 20 0 - r 21 - YEAR 22 4 - A verage: 1 6 ,4 9 5 m or -o u £ High: 2 7 ,0 0 0 Low: 56 - 1 0 ,1 0 0 YEAR -^ A c tu a l -© - Exponential Trend Figure 1 7 8 S n a p Beans (Processing) Ac r es H ar ves t ed, 2 1 -Year Trend, 1970-1990 Avg. Anl. Chg: 2.83% 200 SNAP BEANS; PROCESSING PRODUCTION 21 YRTREND 1970-90 PRODUCTION 90 21 - YEAR 72 -■ A verage: 4 0 .5 High: 7 9 .7 “ 36 - ■- Low: 20.0 18 - Avg. Anl. Chg: 3 .6 1 % YEAR —— Actual -o -E x p o n e n tia l Trend Figure 1 7 9 S n a p B eans (Processing) Production, 21-Y ear T rend, 1 97 0 1990 SNAP BEANS; PROCESSING YIELD 21 YRTREND 1970-90 YIELD 35 21 - YEAR 2.9 -■ A verage: 2 .4 3 UJ CL o< cr UJ CL High: 2 .9 5 (/> z o h- Low: 1 .8 0 0.7 - YEAR I Actual - o - Linear T rend Figure 1 8 0 S n a p Beans (Processing) Yield, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 Avg. Anl. Chg: 0.80% 201 SNAP BEANS; PROCESSING PRICE 21 YR TREND PRICE 1970-90 $200 21 - YEAR $160 -■ A verage: $ 1 3 7 .9 to z o $120 - High: $ 1 7 5 .0 LU Q_ $80 - ..................... Low: $ 9 0 .8 O o $40 $0 Avg. Anl. Chg: 2 .5 9 % 70 72 ‘ 74 76 "" T i 80 82 ^~84 '~ 8 6 88 90 YEAR -A ctual Figure 181 Linear T rend S n a p B eans (Processing) Price, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 S tr a w b e r r i e s (Dual Purpose): Acres h a r v e ste d of dual p u r p o s e s tr aw b er rie s s h o w e d significant declines in d e c a d e s of th e 7 0 ' and 8 0 ' s , s e e Figure 183. S t r a w b e r r y a c r e a g e tre nded lower, falling an a v e r a g e an nu al rate of 3 . 4 8 % , placing it 12th for all ve g e t a b le cr op s. In 1 9 7 0 the s t a t e h a r v e s te d 5 , 8 0 0 a c r e s , by 1 9 9 0 , a c r e a g e had d r o pped to an all time record low of 2 , 2 0 0 , down 62%. S tra w berr y yields s h o w e d a slight im pro ve m en t, tending u pw ard at an a v e r a g e annual rate of 0 . 7 1 % . For t w o yea rs, 1 9 7 6 an d 1 9 8 2 , all time record high yields w er e s e t of 8 0 Cw t. per acre . Th e m o d e s t im p ro v e m e n t in yields w a s not e n o u g h to of fset th e large declines in acr e h ar v ested . S tr a w b e r r y production fell more precipitously th an an y o th e r v e g e ta b le crop. T he tre nd for production w a s an a v e r a g e an nual decline of 2 . 6 2 % , s e e Figure 202 18 4. By 1 9 9 0 th e s t a t e pr o d u c e d almost half the production level of 1 970. Th e tre nd for price w a s an a v e r a g e annual incr ea se of 3.51 %, slightly belo w t h e v e g e ta b le crop group a v e r a g e , s e e Table V. The value of production s h o w e d t h e sm allest of gains. The trend w a s an a v e r a g e annual incr ea se of only 1 . 1 5 % , last for all v e g e ta b l e cr ops , s e e Table V. In 1 9 9 0 Michigan's s tr a w b e r r y cr op w a s valued at $ 7 . 2 million. Michigan ranked 5th in t h e c o u n tr y in s tr a w b e r r y pro du ction in 1 9 9 0 , producing 1 . 1 % of t h e sh are, California w a s n u m b e r one. STRAWBERRIES; DUAL PURPOSE V A LU E O F P R O D U C T IO N $12 ir> _ TREN D 1 9 7 0 -9 0 VALUE OF PRODUCTION 21 - YEAR -■ A verage: $ 6 ,9 6 4 ,8 0 0 $g - High: $ 1 1 ,4 6 9 ,6 0 0 O 2 Low: $3 - $ 4 ,7 2 5 ,0 0 0 YEAR Actual - o - Linear T rend Figure 182 S t r a w b e r r i e s (Dual P ur po se) Value of Product ion, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 Avg. Anl. Chg: 1.15% 203 STRAWBERRIES; DUAL PURPOSE ACRES HARVESTED 21 YR TREND 1970-90 ACRES HARVESTED 21 - YEAR 4.8 -■ A verage: 3 ,0 1 4 High: 5 ,8 0 0 Low: 2,200 Avg. Anl. Chg: - 3 .4 8 % YEAR Actual -© - Exponential Trend Figure 1 8 3 S tra w b e rrie s (Dual Purpose) A cres H arv ested , 2 1 -Year Trend, 1970-1990 STRAWBERRIES; DUAL PURPOSE PRODUCTION 21 YRTREND 1970-90 300 PRODUCTION 240 -■ 21 - YEAR A verage: 182 o .- 120- High: 255 60 - Low: 117 YEAR Actual -© - Linear T rend Figure 1 8 4 S t r aw be r ri es (Dual Purpose) Production, 2 1 -Year Trend, 1970-1990 Avg. Anl. Chg: -2 .62% 204 STRAWBERRIES; DUAL PURPOSE YIELD 21 YR TREND 1970-90 YIELD 21 - YEAR 72 -■ A verage: 6 2 .2 LU U 54 - High: 8 0 .0 CL * 3 B -- Low: 4 4 .0 Avg. Anl. Chg: 0.71 % 86 YEAR — Actual - o - Linear Trend Figure 1 8 5 S tr a w b e rrie s (Dual P urpose) Yield, 2 1-Y ear Trend, 1 9 7 0 1990 STRAWBERRIES; DUAL PURPOSE PRICE 21 YRTREND 1970-90 $60 PRICE $4 0 -• 21 - YEAR oc $36 LU □. A verage: $ 3 9 .5 3 $24 -■ High: $53 .1 $12 Low: $20.1 cn - YEAR Actual -© - Linear Trend Figure 1 8 6 S t r a w b e r r i e s (Dual P urpos e) Price, 2 1 -Year Trend, 1 9 7 0 1990 Avg. Anl. Chg: 3.51% 205 S w e e t Corn (Fresh Market): The n u m ber of a c r e s h a r v e s t e d t re n d e d d o w n w a r d during th e d e c a d e s of th e 7 0 ' s and 8 0 ' s , falling an a v e r a g e annual rate of 0 . 3 3 % . w as 11,948. Th e 21 y e a r annual a v e r a g e of s w e e t corn a c r e s h a r v e s te d Production followed a similar trend p atter n as a c r e s h a r v e s t e d , declining m o d e s tly a t an a v e r a g e annual rate of 0 . 6 8 % , s e e Figure 1 8 9 . 103 Yield per a c r e tre n d e d nominally d o w n w a r d , falling at an a v e r a g e an nua l rate of 0 . 3 5 % . S w e e t corn w a s o n e of thre e v e g e ta b le c r o p s to h av e a neg ativ e yield t r e n d , 104 s e e Table V. Prices incr eased t h r o u g h o u t m o s t of th e 7 0 ' s and 8 0 ' s , ex p a n d in g a t an a v e r a g e annual rate of 6 . 1 8 % , hi ghest for all v e g e t a b le s , s e e Figure 1 9 1 . The price of s w e e t corn h a s risen from $ 3 . 1 3 per C w t. in 1 9 7 0 to a b o v e $ 1 6 . 0 0 per Cwt. in th e late 8 0 ' s . Value of production br ok e th e $ 1 0 million barrier for the first time in 1 9 8 9 , with a level of $ 1 4 million. For th e 21 yea r period, value of production t re n d e d higher a t an a v e r a g e an nu al rate of 6 . 2 2 % , 4th for all ve g e ta b le c r o p s, s e e Figure 187. 1 9 9 0 Michigan ranked 6th in th e country in pr oduction, pr oducing 4 . 9 % of th e total, Florida w a s th e n a ti o n 's leader. 103 N o t e : 1 9 7 0 w a s t h e all t i m e r e c o r d h ig h for s w e e t c o r n p r o d u c t i o n , o f 1 .0 1 m illion C w t . 104 N o t e : a r e c o r d h ig h y ield fo r s w e e t c o r n w a s e s t a b l i s h e d in 1 9 7 0 o f 8 0 C w t . per acre. In 206 SWEET CORN; FRESH MARKET VALUE OF PRODUCTION TREND 19 7 0 -9 0 VALUE OF PRODUCTION $15 $12 -■ 21 - YEAR A verage: $ 6 ,9 3 1 ,6 9 9 OS $6 High: $ 1 4 ,0 3 5 ,0 0 0 - $3 - Low: $ 3 ,1 8 0 ,0 8 0 Avg. Anl. Chg: YEAR Actual 6 .2 2 % - o - Exponential Trend Figure 1 8 7 S w e e t Corn (Fresh Market) Value of Production, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 SWEET CORN; FRESH MARKET ACRES HARVESTED 21 YRTREND 1970-90 ACRES HARVESTED 15 12 21 - YEAR C O U ^3 CJt X y IA s 3 A verage: 1 1 ,9 4 8 9 High: 1 3 .0 0 0 3 Low: 9 .0 0 0 0 YEAR — Actual - o - Linear T rend : igure 1 8 8 S w e e t Corn (Fresh Market) Ac r es H ar ves t ed , 2 1 -Year Trend, 1970-1990 Avg. Anl. Chg: -0.33% 207 SWEET CORN; FRESH MARKET PRODUCTION 21 YRTREND 1970-90 PRODUCTION 1.200 21 - YEAR 960 - 5 o Average: 767 720 - - High: 1 ,016 CD CD CD Low: 540 240 - Avg. Anl. Chg: -0 .6 8 % YEAR •^ A c tu a l - o - Linear Trend Figure 1 8 9 S w e e t Corn (Fresh Market) Production, 2 1 -Year Trend, 1 9 7 0 1990 SWEET CORN; FRESH MARKET YIELD 21 YRTREND 1970-90 YIELD 21 - YEAR 72 A verage: 6 4 .0 LU LU High: 8 0 .0 i 36 - Low: 5 1 .4 YEAR Actual - o - Linear T rend Figure 1 9 0 S w e e t Corn (Fresh Market) Yield, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 Avg. Anl. Chg: -0.35% 208 SWEET CORN; FRESH MARKET PRICE 21 YR TREND 1970-90 PRICE $20 21 - YEAR $16 -■ A verage: $ 9 .2 4 a $12 - $6 High: $ 1 7 .5 0 -■ Low: $ 3 .1 3 Avg. Anl. Chg: 6 .1 8 % YEAR Actual Figure 191 - o - L in e a r Trend S w e e t Corn (Fresh Market) Price, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 T o m a t o e s (Fresh Market): Fresh t o m a t o pro du ctio n declined t h r o u g h o u t the d e c a d e s of t h e 7 0 ' s and 8 0 ' s . Acres h a r v e s te d declined at an a v e r a g e annual rate of 2 . 5 3 , 105 s e e Figure 193. In 1 9 8 8 a c r e a g e d r o pped to an all time record low of 2 , 4 0 0 a c r e s , from a 21 y ea r high of 4 , 4 0 0 a c r e s in 1 9 7 4 . Production also tr e n d e d d o w n w a r d , falling an a v e r a g e annual rate of 2 . 3 5 % , and ranked 12 th o u t of th e 13 ve g e ta b l e cr op s. Yields remained flat for the t w o d e c a d e s , increasing at an a v e r a g e an nu al rate of only 0 . 0 4 % , s e e Figure 195. Howe ver , all time record yields of 1 2 0 Cw t. per ac re w e r e reco rd ed four times in 1 9 7 9 , 1 9 8 3 , 1 9 8 4 , and 1 9 9 0 . Price per h u n d r e d w e ig h t fluctuated b e t w e e n a high of $ 3 4 in 1 9 8 8 to a low of $ 9 . 3 0 in 1 9 7 0 an d tre n d e d higher. 105 T h e t r e n d fo r f r e s h t o m a t o e s w a s t h e 1 1 t h l a r g e s t a n n u a l d e c l i n e fo r all v e g e t a b l e c r o p s , s e e T a b l e V. 209 The tre nd w a s an a v e r a g e annual incr ease of 3 . 6 5 % , 5th highest for all v e g e ta b le c r o p s. Crop value of pr oduction t re n d e d higher at an a v e r a g e an nu al rate of 1 . 2 9 % , this s e c o n d to last for v e g e ta b le c r o p s, s e e Table V. For th e 21 yea r time period, fresh market t o m a t o e s a v e r a g e d a value of prod uc tion of $ 7 . 2 million a year. Michigan ranked 1 5 th in th e c o u n tr y in pro du ction , a c c o u n t in g for 0 . 9 % of th e total U.S. production in 1 9 9 0 , Florida lead all s t a t e s . TOMATOES; FRESH MARKET VALUE O F P R O D U C T IO N TREN D 1 9 7 0 -9 0 VALUE OF PRODUCTION $15 21 - YEAR $12 - A verage: $ 7 ,1 9 6 ,1 8 6 $9 _v c . —1 — a — $6 $ 3 High: $ 1 2 ,0 9 6 ,0 0 0 Low: $ 3 ,8 1 3 ,0 0 0 -■ Avg. Anl. Chg: 1 .2 9 % YEAR Actual -© - Linear T rend Figure 1 9 2 T o m a t o e s (Fresh Market) Value of Product ion, 2 1 -Year Trend, 1970-1990 210 TOMATOES; FRESH MARKET ACRES HARVESTED 21 YRTREND 1970-90 ACRES HARVESTED 21 - YEAR A verage: 3 ,4 9 5 o^ £t '9 High: 4 .4 0 0 - Low: 2 .4 0 0 Avg. Anl. Chg: -2 .5 3 % YEAR ■^— Actual - o - Linear Trend Figure 1 9 3 T o m a t o e s (Fresh Market) A cres H arv ested , 2 1 -Year Trend, 1970-1990 TOMATOES; FRESH MARKET PRODUCTION 21 YRTREND 1970-90 PRODUCTION 520 21 - YEAR 416 - A verage: 365 § 312 200 High: 483 -• Low: 204 104 - YEAR ----- Actual -© - Linear T rend Figure 194 T o m a t o e s (Fresh Market) Production, 21-Ye ar Trend, 1 9 7 0 1990 Avg. Anl. Chg: -2.35% TOMATOES; FRESH MARKET YIELD 21 YRTREND 1970-90 YIELD 140 21 - YEAR 112 -• A verage: 105 LU 04 - High: 120 LU Q_ 56 -• Low: 85 29 - Avg. Anl. Chg: 0 .0 4 % YEAR Actual -Q - E>ponential Trend Figure 1 9 5 T o m a t o e s (Fresh Market) Yield, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 TOMATOES; FRESH MARKET PRICE 21 YRTREND 1970-90 PRICE 21 - YEAR $32 - a: $24 - A verage: $ 2 0 .3 3 $ 1 6 -• High: $ 3 4 .0 U J Q_ $0 Low: $ 9 .3 - YEAR — Actual -Q - Linear Trend Figure 196 T o m a t o e s (Fresh Market) Price, 21-Year Trend, 1 9 7 0 - 1 9 9 0 Avg. Anl. Chg: 3 .6 5 % 212 T o m a t o e s (Processing): P rocess in g t o m a t o e s s h o w e d s o m e of th e m o s t significant gains for e a c h of th e c ategorie s analyzed. Acres h a r v e s t e d tre nded higher at an a v e r a g e an n ual rate of 2 . 4 9 % , th e s e c o n d f a s t e s t for all v e g e t a b l e s . T he s t a t e a v e r a g e d an an nual t o m a t o h a r v e s t of 5 , 4 7 1 a c r e s for th e 21 ye a r period. In 1 9 8 2 an all time s t a t e record of 9 , 7 0 0 a c r e s h a r v e ste d w a s e s ta bli s hed, s e e Figure 1 9 8. Production incr ea se d substantially, tending u p w a r d at an a v e r a g e an nual rate of 5 . 6 2 % , 106 this tr a n s la te s into an a v e r a g e yearly in c r e a se of 6 , 0 4 0 to n s. Yields also ro se at c o n s is te n tly higher rate. T he calcu lated yield tre nd w a s an a v e r a g e annual rate of 3 . 5 3 % , 107 s e e Figure 200. A record yield w a s s e t in 1 9 9 0 of 2 9 . 8 to n s per acr e. Prices ranged from a 21 ye a r high of $ 9 2 . 6 0 per ton in 1 9 8 2 to a low of $ 3 6 . 9 0 per to n in 1970. T he tr e n d for prices w a s an a v e r a g e annual i ncrease of 2 . 7 9 % , 5th in rank, s e e Table V. Th e com binat ion of higher prices an d produc tion led to an increase in th e value of crops. Value of pro du ctio n e x p a n d e d at an a v e r a g e an nual rate of 7 . 3 5 % , tied for first for v eg etab le crops. In t h e 7 0 ' s value of product io n e x p a n d e d from th e $2 million level to a b o v e th e $ 1 0 million mark a n d higher for m o s t of t h e 8 0 ' s . Michigan ranked 4 t h in t h e c o u n t r y in t o m a t o e s for process ing, produ cing 1 . 6 % of U.S. total production in 1 9 9 0 , t h e n u m b e r o n e s t a t e w a s California. 106 N o t e : t h e p r o d u c t i o n t r e n d r a t e w a s t h e s w i f t e s t fo r all c r o p s , s e e T a b l e V. 107 N o t e : t h e yield t r e n d r a t e w a s t h e s e c o n d h i g h e s t fo r all v e g e t a b l e c r o p s . 213 TOMATOES; PROCESSING VA LU E O F P R O D U C T IO N TREN D 1 9 7 0 -9 0 VALUE OF PRODUCTION 21 - YEAR $20 - A verage: $ 7 ,8 4 3 ,0 6 0 l/> c o $10 High: $ 1 8 ,9 4 5 ,9 6 0 -■ Low: $2 ,0 1 0 ,0 0 0 $5 - Avg. Anl. Chg: 7 .3 5 % YEAR Actual - o - Linear Trend Figure 1 9 7 T o m a t o e s (P rocessing) Value of P roduction, 2 1 -Year Trend, 1970-1990 TOMATOES; PROCESSING ACRES HARVESTED 21 YRTREND 1970-90 ACRES HARVESTED 8 .8 -■ 21 - YEAR (f) ^ a-S 6.6-** A verage: 5 ,4 7 1 IA s' 8 o £ 4.422 High: 9 ,7 0 0 - Low: 3 ,3 0 0 00 YEAR ^ — Actual - o - Linear Trend Figure 1 9 8 T o m a t o e s (Processi ng) Ac r es H ar ves t ed, 2 1 -Year Trend, 1970-1990 Avg. Anl. Chg: 2.49% 214 TOMATOES; PROCESSING PRODUCTION 21 YRTREND 1970-90 PRODUCTION 220 21 - YEAR 176 -- A verage: 1 0 7 .5 z 132 - High: 2 0 4 .5 98 - Low: 5 3 .4 Avg. Anl. Chg: 5.6 2 % YEAR Actual - o - Linear T rend Figure 199 T o m a to e s (Processing) P roduction, 2 1-Year T rend, 1 9 7 0 1990 TOMATOES; PROCESSING YIELD 21 YRTREND 1970-90 YIELD 32.0 21 - YEAR 25.6 -• A verage: 19.1 LU a: L > < CL LU □. High: 2 9 .8 (zr> O t— Low: 6.4 - 11.4 00 YEAR — A ctual - o - Exponential Trend Figure 2 0 0 T o m a t o e s (Processi ng) Yield, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 Avg. Anl. Chg: 3.53% 215 TOMATOES; PROCESSING PRICE 21 YRTREND 1970-90 PRICE $100 21 - YEAR DOLLARS PER TON $00 - Average: $ 6 7 .4 $60 - High: $92.6 $ 4 0 -■ Low: $ 3 6 .9 $20 - Avg. Anl. Chg: 2 .7 9 % YEAR -A ctual Figure 201 - o - Linear T rend T o m a t o e s (Processing) Price, 2 1 -Year Trend, 1 9 7 0 - 1 9 9 0 AN ANALYSIS OF BASELINE DATA TO ASSESS STRUCTURAL SHIFTS, TRENDS AND LINKAGES OF MICHIGAN'S PRODUCTION AGRICULTURE ECONOMY DURING THE 1 9 7 0 ' s AND 1 9 8 0 ' s VOLUME II By J o h n Frederick W hims A DISSERTATION S ubm itted to Michigan S t a t e University in partial fulfillment of the req u i re m e n ts for th e d e g r e e of DOCTOR OF PHILOSOPHY D e p a r t m e n t of Agricultural Ec on om ics 1995 V. THE APPLICATION OF SHIFT-SHARE ANALYSIS TO FARM CASH RECEIPTS, TO ASSESS THE SHIFTS IN MICHIGAN'S COMPETITIVE POSITION IN PRODUCTION AGRICULTURE RELATIVE TO THE UNITED STATES Introduction The following disc us sion is an interpretation of the results of t h e shifts h a r e m e t h o d of analysis a s applied to Michigan's production agricultural industry. Th e p u r p o s e for using th e shift-share tech n iq u e in t h e th e sis is to inves tigat e th e position of Michigan' s production agriculture v e r s u s th e general (United S tate s) production agricultural e c o n o m y during t h e d e c a d e s of th e 7 0 ' s and 8 0 ' s . Th e United S t a t e s is called th e b a s e region and Michigan is called th e local region of analysis. Three time periods are analyzed to c a p t u r e the shifts in Michigan production agriculture. The first s e g m e n t ana lyze d is the d e c a d e of t h e 7 0 ' s , th e s e c o n d time period is the d e c a d e of th e 8 0 ' s and th e third s e g m e n t is th e 7 0 ' s an d 8 0 ' s co m bined to yield a longer-run ( tw en ty -o n e year) focus. Farm c a s h r e c e i p t s 108 are used a s th e basis of c o m par is o n b e t w e e n t h e United S t a t e s and Michigan. The s tu d y is co nfined to only th o s e agricultural c o m m odit ie s t h a t are p r oduced in th e s ta t e of Michigan. Regional c o m m o d it ie s s u c h a s t o b a c c o , citrus fruits, c otton, and tre e n u t s ar e excluded from th e analysis. The c a s h receipts d a t a 109 us ed in the analysis is from various United S t a t e s D ep a r t m e n t of Agriculture, Economic R es e a r c h Service, publications called th e "Economic Indicators of th e Farm S e c t o r ." A potential 108 N o t e : f o r p u r p o s e s o f t h i s s t u d y c a s h r e c e i p t s a r e in n o m i n a l t e r m s . 108 Note: the data used in the analysis is found in the data appendix for chapter V. 216 217 p ro b le m arises w h e n usin g cash re c e ip ts as a basis fo r a n a ly tic a l c o m p a ris o n . Farm c o m m o d ity cash re c e ip ts can be h ig h ly v a ria b le fro m ye a r to ye a r and d iffe r g re a tly b e tw e e n re g io n s. The v a ria n c e can u s u a lly be a ttrib u ta b le to th e d iffe re n tia l e ffe c ts o f w e a th e r, e s p e c ia lly fo r fie ld c ro p s , v e g e ta b le s , and fru its . T o a d dre ss th e issue o f v a ria n c e o f fa rm c o m m o d ity cash re c e ip ts (C ), w e ig h te d a ve ra g e s have been c a lc u la te d fo r each o f th e U .S. and M ic h ig a n c o m m o d itie s . T he fo llo w in g is a d e s c rip tio n o f th e w e ig h tin g p ro c e d u re : ( ^ 1 9 6 9 * ^ 1 8 7 0 4 ^1 9 7 1 ) 3 ( ^ 1 9 7 0 * Q flS O * ^1 9 8 1 ) 3 ( ^1989 * ^1990 * ^1 9 9 1 ) 3 = 1 9 7 0 W eighted A verage for each U S -M ic h Com m odity = 1 9 8 0 W eighted A verage for each U S -M ic h Com modity = 1 9 9 0 W eighted A verage for each U S -M ic h Com m odity W h e n th e cash re c e ip ts are w e ig h te d , th e y are th e n a p plied to th e s h ift-s h a re m e th o d o f a n a ly s is , w h ic h is d e scrib e d in d e ta il b e lo w . In c h a p te r V th e s h ift-s h a re re s u lts are d is p la y e d in a ta b u la r fo rm a t. T he ta b le s are se p a ra te d b y a g ric u ltu ra l p ro d u c tio n s e c to rs and by tim e d iv is io n s . T he a g ric u ltu ra l s e c to rs are (1) liv e s to c k and p ro d u c ts , (2) fie ld c ro p s , (3) fr u it and o th e r, and (4) v e g e ta b le s and m e lo n s. T he tim e d iv is io n s are fro m 1 9 7 0 to 1 9 8 0 , 1 9 8 0 to 1 9 9 0 , and 1 9 7 0 to 1 9 9 0 . In o rd e r to a ssist th e reader w ith th e in te rp re ta tio n o f th e re s u lts , th e s h ift-s h a re m odel is d e ve lo p e d in d e ta il b e lo w . It is su g g e ste d th a t th e reader re v ie w th e s h ift- 218 sh a re d e fin itio n s and te rm s b e fo re p ro c e e d in g to th e ta b le s . T h e fir s t s e ctio n re v ie w s th e b a s ic 110 s h ift-s h a re m e th o d o f a n a lysis. The basic m odel is th e n e x te n d e d to a m ore ro b u s t d e riv a tio n called th e A rc e lu s (I)111 s h ift-s h a re m o d e l. A fte r d e s c rib in g in d e ta il th e A rc e lu s m o d el, th e A rc e lu s m odel is a p p lie d to a c o m m o d ity (M ic h ig a n d ry beans cash re ce ip ts) to illu s tra te th e m e c h a n ic s o f th e m e th o d . The s te p -b y -s te p a n a lysis o f d ry beans sh o uld fa c ilita te th e in te rp re tiv e p ro ce ss o f th e s h ift-s h a re ta b le s . T he ta b le s a t th e end o f th e c h a p te r h ig h lig h t th e A rc e lu s (I) s h ift-s h a re re su lts fo r m o s t m ajor M ic h ig a n c o m m o d itie s . T he S tru c tu re o f the Basic S h ift-S h a re m odel T h e goal o f th e s h ift-s h a re m e th o d o f a n alysis is to s ta tis tic a lly separate (d e co m p o se ) th e m ain n a tio n a l and re g ional fo rc e s a ffe c tin g th e in c re m e n ta l ch a n g e in cash re c e ip ts fo r th e v a rio u s a g ric u ltu ra l c o m m o d itie s in M ic h ig a n . In its s im p le s t fo rm , s h ift-s h a re an alysis is d e scrib e d by th e fo llo w in g e q u a tio n : *0,1 = Njj + Nljj + CE|j 110 Note: the literature calls it the "classic" shift-share model. 111 The technique is named after the researcher Francisco J. Arcelus. 219 w h e re : i = T he n u m b e r o f s e c to rs o r in d u s trie s in a re g io n o r n a tio n ( i = 1, 2, ... s). In th is a n a lysis th e " i's " re p re s e n t an a g ric u ltu ra l s u b ­ s e c to r su ch as d a iry , h o gs, and o a ts. j = T he n u m b e r o f re g io n s in a g e o g ra p h ic a l area ( j = 1, 2, ... r ). In th is a n a lysis w e are o n ly c o n c e rn e d w ith th e U n ite d S ta te s as th e base re g io n and M ic h ig a n as th e local re g io n .112 ^Cij = The ch a ng e in cash re c e ip ts fro m a base ye a r to a te rm in a l ye a r. For e xa m p le , w h e n a n a lyzin g th e 7 0 's , th e base ye a r is 1 9 7 0 and th e te rm in a l y e a r is 1 9 8 0 . If a M ic h ig a n c o m m o d ity has $1 m illio n in ca sh re c e ip ts in th e base y e a r and $3 m illio n in cash re c e ip ts in th e te rm in a l ye a r, th e n th e a C is $2 m illio n . Njj = The n a tio n a l g ro w th e ffe c t, th a t p a rt o f th e aC^ a ttrib u ta b le to th e g ro w th rate o f th e n a tio n . NSjj = The s e c to ra l113 m ix e ffe c t, th a t p a rt o f aC^ a ttrib u ta b le to d iffe re n c e s b e tw e e n th e s e c to ra l c o m p o s itio n o f re g io n j and th a t o f th e n a tio n . CE|j = T he c o m p e titiv e e ffe c t, th a t p a rt o f aC^ a ttrib u ta b le to d iffe re n c e s in th e g ro w th ra te o f s e c to r i a t re g io n a l and n a tio n a l levels. T h e th re e s h ift-s h a re e ffe c ts ; N^, NSjj( and CE(j are d e te rm in e d by c a lc u la tin g p e rc e n t c h a n g e s (g ro w th rates) o f th e d iffe re n t levels o f n a tio n a l and s ta te c o m m o d ity cash re c e ip ts o v e r s p e c ifie d tim e p e rio d s. The fo llo w in g lis t o f ke y d e fin itio n s are p a rt o f th e basic s h ift-s h a re m odel and also th e e x te n d e d s h ift-s h a re m odel A rc e lu s (I) w h ic h w ill be d e scrib e d a fte r th e basic m odel. 112 Note: under typical circum stances shift-share analysis is used to analyze em ploym ent data th a t considers regional differences, e.g., a m etropolitan area versus a rural area. 113 Note: the literature refers to this as the industrial component. For this study the term has been changed to sectoral for consistency in term inology reflected in other chapters. 220 Cjj = The p e rc e n t c h a n g e ( % * ) in cash re c e ip ts in a g ric u ltu ra l s u b ­ s e c to r i (c o m m o d ity ), re g io n j (M ic h ig a n ), re la tiv e to a base year and a te rm in a l ye a r, e .g ., 1 9 7 0 to 1 9 9 0 . c io = The % * in n a tio n a l cash re c e ip ts fo r a g ric u ltu ra l s u b -s e c to r i (c o m m o d ity ). c oj = T he % a in to ta l c o m m o d ity cash re c e ip ts fo r M ic h ig a n . c DO = T he % a in to ta l n a tio n a l c o m m o d ity cash re c e ip ts , th e n a tio n a l g ro w th e ffe c t. C = C a p ita l "C " is th e a c tu a l level o f ca sh re c e ip ts in a base ye a r. Cu = C ash re c e ip ts fo r th e ith c o m m o d ity in th e jth re g io n (M ic h ig a n ). C oj = T o ta l M ic h ig a n c o m m o d ity cash Cjo = T o ta l n a tio n a l c o m m o d ity cash re c e ip ts fo r th e ith c o m m o d ity , Zj re c e ip ts , I ; E^. ElCon = T o ta l n a tio n a l a g ric u ltu ra l cash re c e ip ts , I , Z; E^. T h e th re e e ffe c ts o f th e b a sic s h ift-s h a re m odel are c a lc u la te d as fo llo w s : Njj = C^ ( C 00 ) NSjj = Cjj ( c io - CEjj = Cjj ( Cjj - c jo ) c do ) T h ese th re e c o m p o n e n ts fo rm th e fo u n d a tio n fo r th e e x p a n d e d A rc e lu s (I) m o d el w h ic h is used in th e a n a ly s is o f M ic h ig a n 's c o m m o d ity cash re c e ip ts . 221 T he S tru c tu re o f th e A rc e lu s (I), S h ift-S h a re M o d e l T he A rc e lu s (I)114 s h ift-s h a re m odel ta ke s th e b asic sh ift-s h a re m odel and d e c o m p o s e s th e th re e (n a tio n a l, s e c to ra l, and c o m p e titiv e e ffe c ts ) c o m p o n e n ts in to fu rth e r d e ta il. Each o f th e c o m p o n e n ts is b ro ke n d o w n in to tw o n e w te rm s ; an "e x p e c te d " g ro w th e ffe c t, and a " d iffe r e n tia l" e ffe c t. The A rc e lu s 115 s h ift-s h a re te c h n iq u e also u tilize s w h a t is ca lle d a h o m o th e tic c o m p o n e n t to se p arate th e basic sh ift-sh are c o m p o n e n ts in to a p ro p o rtio n a l p e rs p e c tiv e o f th e level o f e c o n o m ic a c tiv ity in th e loca l re g io n fo r each s u b ­ s e c to r " i. " The h o m o th e tic c o m p o n e n t is d e fin e d as fo llo w s : T he h o m o th e tic c o m p o n e n t is th e level o f e c o n o m ic a c tiv ity (a g ric u ltu ra l cash re ce ip ts) th a t a s u b -s e c to r " i" (c o m m o d ity ) in M ic h ig a n w o u ld have if it w e re id e n tic a l to th e n a tio n a l s u b -s e c to r " i's " (c o m m o d ity ) level o f e c o n o m ic a c tiv ity and s tru c tu re . The fo llo w in g is th e fo rm u la tio n o f th e h o m o th e tic c o m p o n e n t: c f ' C i (C jl For e xa m p le , if n a tio n a l cash re ce ip ts fo r th e d a iry s e c to r is $ 1 6 b illio n , th e to ta l n a tio n a l a g ric u ltu ra l cash re c e ip ts are $ 1 1 8 b illio n and to ta l M ic h ig a n cash re c e ip ts is $ 2 .5 b illio n , th e n th e h o m o th e tic cash re c e ip ts C ’ ^ w o u ld be: 114 Note: the Arcelus (I) model is distinguished from another shift-share model he developed called Arcelus (II). 115 Note: Esteban-Marquillas first applied the hom othetic com ponent concept to the competitive effect, Clj( variable to lessen the problem of data interdependence. Arcelus was the first researcher to extend the hom othetic com ponent to all parts of the shift-share model. c; ( $ 2 . 5 billion) ( $ 1 6 billion) ( $ 1 1 8 billion) - $ 3 3 9 million The h o m o th e tic c o m p o n e n t m eans th a t if M ic h ig a n w e re to m irro r th e n a tio n in te rm s o f th e p ro p o rtio n o f d a iry cash re c e ip ts , th e n th e s ta te w o u ld g e ne ra te $ 3 3 9 m illio n . The h o m o th e tic c o m p o n e n t fo rm s a basis to m easure th e degree o f sp e c ia liz a tio n and level o f c o m p a ra tiv e a d v a n ta g e fo r each c o m m o d ity in M ic h ig a n . T h e basic sh ift-s h a re e ffe c ts (va ria b les) are m o d ifie d in th e A rc e lu s (I) m odel b y in tro d u c in g th e h o m o th e tic c o m p o n e n t and th e e x p e c te d and d iffe re n tia l e ffe c ts . The basic s h ift-sh are e ffe c ts (id e n tifie d in b old and ita lic) are n o w d e c o m p o s e d in to th e fo llo w in g v a ria b le s w h e re : N;j = ENjj + DNjj = B oth va ria b le s c o m b in e d is called th e n e t n a tio n a l g ro w th e ffe c t. N S ff = EMij + Djj = B oth va ria b le s c o m b in e d is called th e n e t s e c to ra l m ix e ffe c t. CE, = Ejj + A (j = B oth va ria b le s c o m b in e d is called th e n e t c o m p e titiv e e ffe c t. T h e c o m p le te A rc e lu s (I) m odel is d e scrib e d as fo llo w s : 223 T he six v a ria b le s o f th e A rc e lu s (I) m odel a b o ve are d e fin e d m a th e m a tic a lly as fo llo w s : ENjj = T he "e x p e c te d n a tio n a l g ro w th e ffe c t" is th e in flu e n c e o f th e ch a ng e in to ta l n a tio n a l in ca sh re c e ip ts (cDO) on th e ch a ng e in re g io n j cash re c e ip ts fo r c o m m o d ity i, had C^" (th e h o m o th e tic c o m p o n e n t) been eq ua l to C (j. EN„ = c ; ( c j (C ^ (C J (CJ *(c j DNjj = T he "d iffe re n tia l n a tio n a l g r o w th e f fe c t." The in flu e n c e o f th e n a tio n a l g ro w th e ffe c t (co0) on cash re c e ip ts fo r c o m m o d ity i based on th e d e gre e o f s p e c ia liz a tio n 116 o f c o m m o d ity i in re gion j. DA/, = (C, - c;) x (c j = (C J (C J (C J * (C j EMy = T he "e x p e c te d s e c to ra l g ro w th e f fe c t." Is th e e x p e c te d c h a n g e in loca l ca sh re c e ip ts based on th e d iffe re n c e b e tw e e n th e n a tio n a l g ro w th rate o f c o m m o d ity " i" (cio) v e rs u s th e g ro w th rate fo r all n a tio n a l c o m m o d itie s (c00) a p plied to th e h o m o th e tic c o m p o n e n t. T his s h o w s e x p e c te d e ffe c t o f th e n a tio n a l s u b -s e c to rs ' ” i" p a tte rn o f c h a n g e on th e local s u b -s e c to r " i. " £Af, = (clo c j - (C J (C J (C J * (Cm, - c j 116 Specialization is the degree of importance for a com m odity i (based on cash receipts) in the state relative to it's share of the national total for com m odity i. 224 D,j = T h e ’’d iffe re n tia ! s e c to ra l m ix e f fe c t." The n a tio n a l g ro w th rate d iffe re n tia ls a p plied to th e d iffe re n c e b e tw e e n th e local level o f ca sh re c e ip ts fo r c o m m o d ity " i" m inus th e h o m o th e tic c o m p o n e n t. dm, ( C J (CJ (C J = (c , - c ;) (clo - c j " Ey = T he " e x p e c te d c o m p e titiv e e f fe c t" m easures th e c o m p e titiv e a d v a n ta g e o r d is a d v a n ta g e o f th e loca l re gion and c o m m o d ity " i" w ith re s p e c t to th e n a tio n and c o m m o d ity " i. " EC, - C, (c, cj - (C J (C J (C J A ;j = T h e "allo catio n e ffe c t" ta ke s in to a c c o u n t re gion j's d e gree o f sp e c ia liz a tio n in th e v a rio u s c o m m o d itie s i th a t it p ro d u c e s . AE, - [C, ) (c, c/o) - ^ (C0) (C J x (c, cj T o b e tte r u n d e rs ta n d th e d e c o m p o s itio n a l p ro ce ss o f th e A rc e lu s s h iftshare te c h n iq u e , a s te p -b y -s te p e xa m ple has been in c lu d e d o f M ic h ig a n d ry beans cash re c e ip ts fro m 1 9 7 0 to 1 9 8 0 . A lso in c lu d e d in th e e xa m p le is a s e c tio n th a t in te rp re ts th e re s u lts o f th e m odel. T h e in te rp re tiv e p ro ce ss o f th e d ry beans sh o u ld aid th e reader w h e n re v ie w in g th e ta b le s and ta b le s u m m a ry s e c tio n s . 225 An Example o f Shift-Share A nalysis Applied to Michigan Dry B ean s Dry B ean s C ash R eceipts from M arketings ($ 0 0 0 ' s ) 17 U n ite d S ta te s : 1970 1980 %a D ry Beans $ 1 5 5 ,0 5 6 $ 5 8 7 ,6 6 2 2 7 9 .0 T o ta l R eceipts $ 4 3 ,6 7 0 ,6 1 6 $ 1 1 8 ,3 7 4 ,0 3 9 17 1.1 D ry Beans $ 5 6 ,2 3 3 $ 1 5 3 ,9 0 8 1 7 3 .7 T o ta l R eceipts $ 8 8 1 ,2 9 5 $ 2 ,6 1 3 ,3 7 3 1 8 7 .2 M ic h ig a n : Identification o f Variables for Shift-Share A n aly sis C a lcu la te d G ro w th R ates, 1 9 7 0 base ye a r and 1 9 8 0 te rm in a l ye a r: c io c OD Cjj c oj = = = = 2 7 9 .0 % 1 7 1 .1 % 1 7 3 .7 % 1 8 7 .2 % ( % a ( % a ( % a ( % a in in in in n a tio n a l d ry beans ca sh re ce ip ts) to ta l n a tio n a l c o m m o d ity ca sh re ce ip ts) M ic h ig a n d ry beans ca sh re ce ip ts) to ta l M ic h ig a n c o m m o d ity cash re ce ip ts) C ash R ece ip ts {$ 0 0 0 's ) : Ci0 = $ 1 5 5 ,0 5 6 C00 = $ 4 3 ,6 7 0 ,6 1 6 C, = $ 5 6 ,2 3 3 Coi - $ 8 8 1 ,2 9 5 (n a tio n a l cash re c e ip ts base ye a r 1 9 7 0 ) (n a tio n a l cash re c e ip ts in base ye a r 1 9 7 0 ) (n a tio n a l cash re c e ip ts base ye a r 1 9 7 0 ) (n a tio n a l cash re c e ip ts in base ye a r 1 9 7 0 ) fo r d ry beans in th e fo r all c o m m o d itie s fo r d ry beans in the fo r all c o m m o d itie s 117 Note: the cash receipts are a w eighted average of three years centered around 1970 and 1980. This is to reduce the variance of the value of production, w hich is often associated w ith agricultural com m odities. This technique is applied to all com m odities and all base and term inal years in the analysis. 226 H o m o th e tic C o m p o n e n t ($ 0 0 0 's ): c; = ($881,295) ($155,056) ($43,670,616) - $3,129 R em e m b e rin g th e s h ift-s h a re c o m p o n e n ts fo r th e A rc e lu s m o d el are: a 0^ = ENjj + DNjj -f E M (j + D (J + Ei3 4- Ajj Calculation o f the A rcelus Model C o m p o n en ts for Dry B ean s ($ 0 0 0 ' s ) 118 II UJ (3 ,1 2 9 ) x (1 .7 1 1 ) II Q [(5 6 ,2 3 3 ) - (3 ,1 2 9 )] x (1 .7 1 1 ) EMy = (3 ,1 2 9 ) x (2 .7 9 0 - 1 .7 1 1 ) D. = [( 5 6 ,2 3 3 ) - (3 ,1 2 9 )] x (2 .7 9 0 - 1 .7 1 1 ) Eii = A, -c , = (3 ,1 2 9 ) x (1 .7 3 7 - 2 .7 9 0 ) = 5 ,3 5 3 > = 9 6 ,1 9 3 > = 6 0 ,6 9 8 = 9 0 ,8 3 9 = 3 ,3 7 8 = 5 7 ,3 2 0 = -3 ,2 9 5 > [(5 6 ,2 3 3 ) - (3,129)1 x (1 .7 3 7 - 2 .7 9 0 ) = 1 5 3 ,9 0 8 - 5 6 ,2 3 3 = = - 5 9 ,2 1 4 = -5 5 ,9 1 9 $ 9 7 ,6 7 5 = $ 9 7 ,6 7 5 Where: EN^ + DN jj = IMjj = 9 6 ,1 9 3 th e net g ro w th e ffe c t. 118 N o t e : m a n y o f t h e n u m b e r s ( e s p . t h e g r o w t h r a t e s ) h a v e b e e n r o u n d e d f o r s im p lic ity of d is p la y a n d t h e r e s u l t s m a y differ slightly. 227 EMy + Djj Ey + Ajj = NS^ = = CES = 6 0 ,6 9 8 th e n e t s e c to ra l m ix e ffe c t. -5 9 ,2 1 4 th e n e t c o m p e titiv e e ffe c t. In te rp re ta tio n o f the S h ift-S h a re R esults fo r D ry Beans T h e fir s t va ria b le o f n o te is th e h o m o th e tic c o m p o n e n t119 fo r d ry beans o f $ 3 ,1 2 9 ,0 0 0 . T his s tip u la te s th a t if M ic h ig a n w e re to have th e sam e p ro p o rtio n as th e n a tio n in te rm s o f d ry beans cash re c e ip ts to to ta l cash re c e ip ts , M ic h ig a n 's re c e ip ts w o u ld have been $3.1 m illio n in 1 9 7 0 . The a c tu a l level o f M ic h ig a n d ry bean re ce ip ts in 1 9 7 0 w e re $ 5 6 .2 m illio n . S uch a large to ta l o f d ry bean cash re ce ip ts (18 tim e s g re a te r th a n th e n a tio n a l p ro p o rtio n ) h ig h lig h ts th e s ig n ific a n c e 120 o f d ry beans to M ic h ig a n 's a g ric u ltu ra l e c o n o m y . T he a b s o lu te cha ng e in ca sh re c e ip ts fo r d ry beans fro m 1 9 7 0 to 1 9 8 0 w e re $ 9 7 .7 m illio n , e xp a n d in g fro m $ 5 6 .2 m illio n to $ 1 5 3 .9 m illio n . T his ch a ng e in d ry beans cash re c e ip ts w a s th e n d e c o m p o s e d in to th e d iffe re n t g ro w th e ffe c ts . A n e x p la n a tio n o f c a lc u la te d g ro w th e ffe c ts is se g m e n te d in to th e th re e n e t g ro w th e ffe c t c o m p o n e n ts : th e n a tio n a l, s e c to ra l, and c o m p e titiv e . The net e ffe c ts are as fo llo w s : 119 R e m e m b e r t h e h o m o t h e t i c c o m p o n e n t is t h e i n t e g r a l v a r i a b l e w h i c h h e l p s t o s e p a r a t e t h e e x p e c t e d e f f e c t s f r o m t h e d i f f e r e n t i a l e f f e c t s in t h e m o d e l . 120 S i g n i f i c a n c e is m e a n t in t e r m s o f r e l a t i v e s i z e o f t o t a l M i c h i g a n a n d n a t i o n a l c a s h receipts. 228 T h e N et G ro w th E ffe c t: T he c a lc u la te d n e t n a tio n a l g ro w th e ffe c t121 is $ 9 6 .2 m illio n . The e x p e c te d n a tio n a l g ro w th e ffe c t is $ 5 .4 m illio n and th e d iffe re n tia l n a tio n a l g ro w th e ffe c t is $ 9 0 .8 m illio n , th e se tw o c o m p o n e n ts c o m b in e to yie ld th e net e ffe c t. The e x p e c te d n a tio n a l e ffe c t s h o w s th e in flu e n c e o f th e g ro w th in to ta l n a tio n a l ca sh re c e ip ts m u ltip lie d b y th e h o m o th e tic c o m p o n e n t. T h is p ro d u ce s th e e x p e c te d n a tio n a l c o n trib u tio n to th e a b s o lu te ch a ng e in M ic h ig a n d ry bean re c e ip ts . T he d iffe re n tia l n a tio n a l g ro w th e ffe c t122 is th e d iffe re n c e b e tw e e n th e h o m o th e tic c o m p o n e n t and th e a c tu a l level o f M ic h ig a n ca sh re c e ip ts . In th is e xa m p le , th e d iffe re n tia l g ro w th e ffe c t is so m u ch larg e r th a n th e e x p e cte d g ro w th e ffe c t because o f th e h o m o th e tic c o m p o n e n t is s ig n ific a n tly sm a lle r th a n a c tu a l d ry bean cash re ce ip ts . T h e N et S e c to ria l G ro w th E ffe c t: T he n e t se c to ra l g ro w th e ffe c t lo o k s a t th e d iffe re n c e b e tw e e n th e n a tio n a l g ro w th rate fo r d ry beans c io (2 7 9 .0 % ) ve rsu s th e g ro w th rate fo r all n a tio n a l c o m m o d itie s c eo (1 7 1 .1 % ). In th is e xa m ple c io > c 00, w h e re bean cash re c e ip ts are g ro w in g fa s te r th a n o ve ra ll cash re c e ip ts . T h is in d ic a te s th a t 121 N o t e : t h e n e t g r o w t h e f f e c t (in t h i s c a s e p o s i t i v e ) in t o t a l n a t i o n a l c a s h r e c e i p t s i s a n a l o g o u s t o t h e r i s i n g t i d e c o n c e p t . If t o t a l n a t i o n a l c a s h r e c e i p t s a r e g r o w i n g t h e n t h e r e is a n a s s u m e d i n c r e a s e d in t h e c h a n g e o f e a c h c o m m o d i t y ' s c a s h r e c e i p t s b e c a u s e of t h e i n f l u e n c e of t h e n a tio n a l a g r ic u ltu ra l e c o n o m y . 122 N o t e : t h e t e r m ( CN - C*,,) x c O0 t h e p r o v i d e s a r o u g h m e a s u r e o f t h e e f f e c t o f n a t i o n a l m a r k e t c o n d i t i o n s o n a C,,. 229 d ry beans are in a fa s t g ro w th s e c to r o f p ro d u c tio n a g ric u ltu re . T h e re fo re , the n e t e x p e c te d s e c to ra l e ffe c t on M ic h ig a n d ry beans cash re c e ip ts is an increase o f $ 6 0 .7 m illio n . The e x p e c te d s e c to ra l g ro w th e ffe c t is $ 3 .4 m illio n and th e d iffe re n tia l s e c to ra l m ix e ffe c t is $ 5 7 .3 m illio n . T he N et C o m p e titiv e G ro w th E ffe c t: For p u rpo se s o f th is s tu d y th e n e t c o m p e titiv e e ffe c t is p ro b a b ly th e m o st im p o rta n t s h ift-s h a re c o m p o n e n t c a lc u la te d . T his s h o w s th e re la tiv e g ro w th in re c e ip ts b e tw e e n th e local c o m m o d ity and th e n a tio n a l c o m m o d ity . In th is e xa m p le , th e g ro w th in n a tio n a l cash re c e ip ts is g re a te r th a n th e g ro w th in M ic h ig a n re c e ip ts , c io (2 7 9 .0 % ) > c^ (1 7 3 .3 % ). D u rin g th e 7 0 's M ic h ig a n e n jo ye d n a tio n a l p ro m in e n c e fo r d ry beans p ro d u ce d in th e c o u n try , b u t in 8 0 's th e ch a n g e in cash re c e ip ts co m p a re d th e U.S. s h o w s an e ro s io n in its c o m p e titiv e p o s itio n . T he c a lc u la te d n e t c o m p e titiv e e ffe c t is a loss o f $ 5 9 .2 m illio n . T h is m eans th a t if th e s ta te had k e p t pace w ith th e n a tio n a l g ro w th in d ry beans cash re c e ip ts th e a c tu a l level o f M ic h ig a n re c e ip ts in 1 9 8 0 sh o uld have been $ 2 1 3 .1 m illio n inste ad o f $ 1 5 6 .9 m illio n . The e x p e c te d c o m p e titiv e e ffe c t is d e clin e o f $ 3 .3 m illio n and th e a llo c a tio n e ffe c t is a d e c lin e o f $ 5 5 .9 m illio n . F u rth e r C o n s id e ra tio n s fo r In te rp re tin g th e S h ift-S h a re R esults 230 T h e N e t G ro w th E ffe c t (Nfi): ■ In p e rio d s o f n a tio n a l e x p a n s io n 123 (or c o n tra c tio n ) w h e n c DO > 0 (cDO< 0 ), th e re w ill te n d to be a p o s itiv e (n e g a tive ) e ffe c t on *.Cir T he size o f th e n a tio n a l (p o s itiv e , n e g a tiv e , or no ch a ng e ) e ffe c t w ill be d e te rm in e d by th e d e gree o f s p e c ia liz a tio n o f region j in in d u s try i, th e g re a te r th e va lu e o f (Cjj - th e g re a te r th e e ffe c t on th e re g io n . T h e N et S e c to ra l M ix G ro w th E ffe c t (NS}j): ■ If (cjo - c OD) > 0 , th e n th e n a tio n a l c o m m o d ity " i's " cash re c e ip ts are g ro w in g fa s te r th a n to ta l n a tio n a l ca sh re c e ip ts . T he lo ca l c o m m o d ity i is th e re fo re , in a p o s itiv e ly g ro w in g s e c to r and has a s e c to ra l a d v a n ta g e o v e r o th e r loca l c o m m o d itie s . ■ If (cio - c DO) > 0 , has been p o s itiv e fo r long p e rio d s o f tim e fo r n a tio n a l c o m m o d ity i and (CSj - C *^) > 0 , th e n a p o s itiv e in flu e n c e is p ro d u c e d on aC^. T h is m eans th a t local re g io n j is specializin g in a n a tio n a lly g ro w in g c o m m o d ity i. ■ If th e re are n e g a tiv e sign s fo r b o th te rm s o f th e n e t s e c to ra l g ro w th e ffe c t, th e n b o th te rm s have a p o s itiv e e ffe c t on a C^. The tw o n e g a tiv e sign s 123 N o t e : in t h e t i m e p e r i o d s a n a l y z e d , e v e r y c a l c u l a t e d c o m m o d i t y c 00 w a s p o s i t i v e i n d i c a t i n g t h e e x p a n s i o n o f c a s h r e c e i p t s ( c a s h r e c e i p t s a r e in n o m i n a l t e r m s ) . It is p o s s i b l e h o w e v e r , t h a t if all c a s h r e c e i p t s w e r e a n a l y z e d in r e a l t e r m s ( d e f l a t e d ) c e r t a i n c o m m o d i t y c DO w o u l d i n d i c a t e c o n t r a c t i o n a r y e c o n o m i c a c t i v i t y . 231 s h o w th a t loca l re g io n j is n o t sp e c ia liz in g in a la g g in g c o m m o d ity i, w h ic h is b e n e fic ia l to th e lo ca l re gion. ■ If th e re are o p p o s ite sign s fo r th e te rm s , th e n a n e g a tiv e va lu e is c a lc u la te d fo r NS^ and has a n e g a tiv e e ffe c t on a C^. T h e n e g a tiv e e ffe c t is b e cause re g io n j is e ith e r s p e c ia liz in g , (C^ - C*^) > 0 , in a la g g in g c o m m o d ity , (cjo - c OD) < 0 ,o r n o t s p e c ia liz in g , (C;, - C *^) < 0 , in a fa s t g ro w th c o m m o d ity , (c,D - c QO) > 0. ■ By s u m m in g NS^ fo r all c o m m o d itie s i (s e c to rs ), N loj = X6j = 1 Nl^, fo r each o f th e fo u r m a jo r c o m m o d ity g ro u p s (liv e s to c k and p ro d u c ts , fie ld cro p s, fru it & o th e r, and v e g e ta b le s ), p ro d u ce s an in d ic a to r o f w h e th e r region j is sp e c ia liz in g (or n o t sp e c ia liz in g ) in c o m m o d itie s in w h ic h th e y have a c o m p e titiv e p o s itio n . T h e N et C o m p e titiv e G ro w th E ffe c t (CE;j ): ■ If (C|j - c jo) > 0, th e n th e local c o m m o d ity " i's " cash re c e ip ts are g ro w in g fa s te r th a n th e n a tio n a l c o m m o d ity " i's " cash re c e ip ts , and th e loca l c o m m o d ity have a c o m p e titiv e a d v a n ta g e o v e r th e n a tio n a l c o m m o d ity . ■ If (Cjj - c io) > 0 , has been p o s itiv e fo r long p e rio d s o f tim e fo r local c o m m o d ity i and (C^ - C *^) > 0 , th e n a p o s itiv e a llo c a tio n e ffe c t is 232 p ro d u c e d on a C^. T h is m eans th a t region j is sp e cia lizin g in a local c o m m o d ity i th a t is fa s t g ro w in g . ■ A p o s itiv e a llo c a tio n e ffe c t can also re s u lt if th e e x p e c te d ca sh re c e ip ts and th e d iffe re n tia l ca sh re ce ip ts are b o th n e g a tive . T his m eans th a t th e re g io n j is n o t sp e cia lizin g in a c o m m o d ity i th a t is g ro w in g s lo w e r a t th e re g io n a l level th a n a t th e n a tion a l level. The tw o n e g a tiv e sign s c re a te a p o s itiv e e ffe c t on a C^. ■ If th e re are o p p o s ite sig n s fo r th e te rm s , th e n a n e g a tiv e va lu e is c a lc u la te d fo r CE^ and has a n e ga tive e ffe c t on a C;,. The n e g a tiv e e ffe c t is b ecause region j is e ith e r s p e cia lizin g , (C^ - C*^) > 0 , in a lagging c o m m o d ity , 0. ■ By s u m m in g CE^ fo r all c o m m o d itie s , CEoj = I 8i = 1 CEij( fo r each o f th e fo u r m a jo r c o m m o d ity g ro u p s (liv e s to c k and p ro d u c ts , fie ld c ro p s , fr u it & o th e r, and ve g e ta b le s ), pro du ce s an in d ic a to r o f w h e th e r re gion j is sp e cia lizin g (or n o t sp e cia lizin g ) in c o m m o d itie s th a t th e y have a c o m p e titiv e p o s itio n in. H ig h lig h ts o f th e A rc e lu s S h ift-S h a re M o d e l R e s u lts 124 124 N o t e : all d o l l a r s a r e in n o m i n a l t e r m s . 233 L iv e s to c k and P ro d u c ts 1 9 7 0 -1 9 8 0 : ■ D a iry P ro d u c ts : D airy ca sh re ce ip ts e xp an d e d fro m $ 2 6 2 .3 m illo n in 1 9 7 0 to $ 6 3 7 .8 m illio n in 1 9 8 0 . A t th e n a tio n a l level d a iry cash re c e ip ts lagged th e g ro w th rate o f to ta l n a tio n a l cash re c e ip ts . T h is is id e n tifie d b y th e n e g a tiv e e x p e c te d s e c to ra l g ro w th e ffe c t o f $ 2 4 .5 m illio n on M ic h ig a n d a iry re c e ip ts . The n e g a tiv e $ 2 4 .3 m illio n d iffe re n tia l s e c to ra l m ix e ffe c t s h o w s th a t th e s ta te w a s sp e cia lizin g in a la g g in g s e c to r in te rm s o f cash re c e ip t g ro w th . From a c o m p e titiv e p o s itio n n a tio n a lly M ic h ig a n fe ll s lig h tly b ehind as th e e x p e c te d c o m p e titiv e e ffe c t w a s a n e g a tiv e $ 1 2 .2 m illo n , m e a nin g th a t n a tio n a l d a iry re c e ip ts g re w a t a fa s te r rate th a n M ic h ig a n re c e ip ts . ■ H og s: In 1 9 7 0 , M ic h ig a n hog re c e ip ts o f $ 5 3 .0 m illo n w e re s u b s ta n tia lly b e lo w th e c a lc u la te d h o m o th e tic c o m p o n e n t o f $ 8 9 .6 m illio n . e xp a n d e d fro m th e $ 5 3 in 1 9 7 0 to $ 1 2 9 .7 m illio n in 1 9 8 0 . th e ho g s e c to r w a s s lo w g ro w in g in th e 7 0 's . R eceipts N a tio n a lly T h is m eans th a t a t th e n a tio n a l level th e g ro w th rate o f hog cash re c e ip ts w a s less th a n to ta l n a tio n a l cash re c e ip ts . The lag g ing n a tio n a l hog re c e ip ts are in d ic a te d by th e n e g a tiv e c a lc u la te d e x p e c te d s e c to ra l e ffe c t o f $ 5 6 .3 m illio n . M ic h ig a n gained g ro u n d in its share o f n a tio n a l hog re c e ip ts . The e x p e c te d c o m p e titiv e e ffe c t w as a p o s itiv e e ffe c t o f $ 3 6 .8 m illio n , s h o w in g th a t th e s ta te 's c o m p e titiv e a d v a n ta g e . From an a llo c a tio n e ffe c t 234 p e rs p e c tiv e h o w e v e r, th e s ta te did n o t specialize e n o u g h , g ive n th e c a lc u la te d a llo c a tio n n e g a tiv e e ffe c t o f $ 1 5 .4 m illio n . The n e t c o m p e titiv e e ffe c t w a s a p o s itiv e $ 2 1 .4 m illio n . Since th e s ta te w a s n o t sp e cia lizin g in h o gs, th e d iffe re n tia l s e c to ra l m ix e ffe c t w a s a p o s itiv e $ 2 3 .6 m illio n . ■ T o ta l L iv e s to c k & P ro d u c ts : From 1 9 7 0 to 1 9 8 0 to ta l liv e s to c k & p ro d u c ts cash re c e ip ts g re w fro m $ 4 8 4 .9 m illio n to $1.1 b illio n . The h o m o th e tic c o m p o n e n t o f $ 5 9 0 .0 m illio n in 1 9 7 0 s h o w s th a t M ic h ig a n sh o u ld have a p p ro x im a te ly 2 2 % m ore cash re c e ip ts c o m in g fro m th e liv e s to c k s e c to r in o rd e r to m a tc h th e n a tio n a l s tru c tu re . L iv e s to c k had n e g a tiv e n u m b e rs fo r b o th th e net c o m p e titiv e ($ 6 1 .0 m illio n ) and net s e c to ra l m ix e ffe c ts ($ 1 7 9 .6 m illio n ). T his in d ic a te s th a t th e M ic h ig a n liv e s to c k s e c to r u n de r p e rfo rm e d th e n a tio n w ith re g ard s to s p e c ia liz a tio n in fa s t g ro w th n a tio n a l c o m m o d itie s and also did n o t keep pace w ith th e n a tio n a l g ro w th rate fo r all liv e s to c k c o m m o d ity cash re c e ip ts . L iv e s to c k and P ro d u c ts 1 9 8 0 -1 9 9 0 : ■ T u rk e y s : g ro u p . T u rk e y s s h o w e d som e o f th e m o s t p o s itiv e ga in s in th e liv e s to c k From 1 9 8 0 to 1 9 9 0 tu rk e y cash re c e ip ts increased fro m $ 1 5 .7 m illio n to $ 4 7 .7 m illio n . The c a lc u la te d n e g a tiv e d iffe re n tia l e ffe c ts (n a tio n a l, s e c to ra l, and c o m p e titiv e ) re su lted because th e s ta te w a s under sp e cia lize d in a fa s t g ro w th in d u s try . The h o m o th e tic c o m p o n e n t s h o w e d th a t th e s ta te sh o uld have had a t least $ 2 7 .1 m illio n in cash re c e ip ts in 1 9 8 0 to m irro r th e n a tio n a l p ro p o rtio n . A ll o f th e e x p e c te d e ffe c ts (n a tio n a l, s e c to ra l, and c o m p e titiv e ) are p ro m in e n tly p o s itiv e . O f p a rtic u la r n o te is th e fa c t th a t M ic h ig a n tu rk e y re c e ip ts o u t p e rfo rm e d th e g ro w th rate o f n a tio n a l tu rk e y cash re ce ip ts. B o th c a ttle and ca lve s and b ro ile rs s h o w e d q u ite large d is p a ritie s b e tw e e n th e ir a c tu a l level o f 1 9 8 0 cash re c e ip ts and th e ir re s p e c tiv e h o m o th e tic c o m p o n e n ts . C a ttle and ca lve s a ctu a l cash re c e ip ts in 1 9 8 0 w e re $ 2 1 6 .1 m illo n and th e h o m o th e tic c o m p o n e n t w a s $ 6 8 7 .5 m illio n . B ro ile rs a ctu a l ca sh re c e ip ts in 1 9 8 0 w e re $2.1 m illio n and th e h o m o th e tic c o m p o n e n t w a s $ 9 4 .0 m illion . T he d a iry p ro d u c t s e c to r c o n tin u e d to s h o w n e g a tiv e re s u lts in th e n e t c o m p e titiv e e ffe c t. The e x p e c te d c o m p e titiv e e ffe c t w a s a n e g a tiv e $ 3 1 .9 m illio n and th e a llo c a tio n e ffe c t w as a n e g a tiv e $ 2 4 .9 m illio n . F rom 1 9 8 0 to 1 9 9 0 to ta l liv e s to c k & p ro d u c ts cash re c e ip ts g re w fro m $1.1 b illio n to $ 1 .3 b illio n . T h e h o m o th e tic c o m p o n e n t o f $ 1 .5 b illio n in 1 9 8 0 s h o w s th a t M ic h ig a n sh o u ld have a p p ro x im a te ly 3 6 % m ore cash re c e ip ts c o m in g fro m th e liv e s to c k s e c to r in o rd e r to m a tc h th e n a tio n a l s tru c tu re . D urin g th e decad e o f th e 7 0 's liv e s to c k p o ste d n e g a tiv e re su lts 236 fo r th e n e t c o m p e titiv e c o m p o n e n t. In th e 8 0 's h o w e v e r, th e n e g a tive e ffe c ts w e re re v e rs e d , la rg e ly in p a rt to th e gains m ade in hog re c e ip ts . A c tu a l ho g re c e ip ts e x p a n d e d fro m $ 1 2 9 .7 m illio n in 1 9 8 0 to $ 2 2 1 .3 m illio n in 1 9 9 0 . L iv e s to c k and P ro d u c ts 1 9 7 0 -1 9 9 0 : ■ T o ta l M ic h ig a n liv e s to c k cash re ce ip ts g re w fro m $ 4 8 4 .9 m illio n in 1 9 7 0 to $ 1 .3 b illio n in 1 9 9 0 . Both th e net s e c to ra l m ix e ffe c t ($ 2 2 4 .9 m illio n ) and th e n e t c o m p e titiv e e ffe c t ($ 3 5 .7 m illio n ) are n e g a tiv e . ■ H ogs p o ste d th e la rg e s t n e t c o m p e titiv e e ffe c t gain o f $ 9 6 .0 m illio n . ■ T h e la rg e s t n e g a tiv e n e t c o m p e titiv e e ffe c t w a s fo r d a iry a t $ 8 5 .3 m illio n . ■ B roilers and T u rk e y s are th e o n ly tw o c o m m o d itie s p o s itio n e d in fa s t g ro w th s e c to rs . T h is is e v id e n c e d by th e c a lc u la te d p o s itiv e e x p e c te d se c to ra l g ro w th e ffe c ts . H o w e v e r, th e s p e c ia liz a tio n in b o th c o m m o d itie s w a s b e lo w th e h o m o th e tic c o m p o n e n t and th e y re g iste re d n e g a tiv e d iffe re n tia l s e c to ra l m ix e ffe c ts . 237 Field Crops 1 9 7 0 - 1 9 8 0 : 125 ■ D u rin g th e 7 0 's fie ld c ro p s p o ste d m ore fa v o ra b le gains in cash re ce ip ts co m p a re d to th e liv e s to c k s e c to r. T o ta l cash re c e ip ts e x p a n d e d fro m $ 2 4 1 .0 m illo n in 1 9 7 0 to $ 1 .0 8 b illio n in 1 9 8 0 , up a p p ro x im a te ly 3 4 8 % . A ll n e t e ffe c t c o m p o n e n ts are p o s itiv e : th e net c o m p e titiv e e ffe c t w as $ 2 1 1 .2 m illio n , th e n e t s e c to ra l m ix e ffe c t w a s $ 2 1 4 .6 m illio n , and th e n e t g ro w th e ffe c t w a s $ 2 4 0 .5 m illio n . ■ Four c ro p s s h o w e d large v a ria tio n s fro m th e ir 1 9 7 0 levels o f cash re ce ip ts and th e ir re s p e c tiv e h o m o th e tic c o m p o n e n ts . P o ta to e s, su g a r b e ets, and d ry beans all had cash re c e ip ts levels in 1 9 7 0 th a t w e re s u b s ta n tia lly h ig h e r th a n th e ir h o m o th e tic c o m p o n e n ts . B arley w a s th e one fie ld cro p th a t w a s s u b s ta n tia lly lo w e r th a n it's h o m o th e tic c o m p o n e n t. A c tu a l b a rle y cash re c e ip ts w e re $ 3 9 0 th o u s a n d in 1 9 7 0 co m p a re d to a h o m o th e tic c o m p o n e n t o f $6.1 m illio n . ■ T h e la rg e s t n e t c o m p e titiv e e ffe c t w as c o rn a t $ 1 9 8 .1 m illio n . M o s t o f th e p o s itiv e n e t e ffe c t w a s because o f th e e x tre m e ly large e x p e c te d c o m p e titiv e e ffe c t o f $ 2 1 0 .9 m illio n . 125 N o t e : d r y b e a n s f r o m 1 9 7 0 t o 1 9 8 0 h a v e b e e n c o v e r e d q u i t e e x t e n s i v e l y in a n exam ple above. 238 ■ S o yb e a n s also s h o w e d a large p o s itiv e net c o m p e titiv e e ffe c t, $5 4.1 m illio n . The e x p e c te d c o m p e titiv e e ffe c t o f $ 1 0 1 .7 m illio n w a s th e second la rg e s t fo r fie ld c ro p s . The n e g a tiv e a llo c a tio n e ffe c t o f $ 4 7 .7 m illio n in d ic a te s th a t th e s ta te w a s un de r specialized in th e c o m m o d ity . Field Crops 1 9 8 0 - 1 9 9 0 : ■ T o ta l M ic h ig a n fie ld c ro p cash re ce ip ts d e clin ed s lig h tly fro m $ 1 .0 9 b illio n in 1 9 8 0 to $ 1 .0 7 b illio n in 1 9 9 0 . O n ly six cro p s (so yb ea n s, hay, p o ta to e s , su g a r b e ets, b a rle y, and m u sh ro o m s) s h o w e d p o s itiv e g ro w th in a c tu a l cash re c e ip ts . ■ From a n e t c o m p e titiv e e ffe c t p e rs p e c tiv e th e big g a in e rs w e re so yb ea n s, h ay, and su g a r b e ets. For b o th so yb ea n s and ha y th e e x p e c te d c o m p e titiv e e ffe c t w a s h ig h ly p o s itiv e , m e aning th e g ro w th rate o f th e loca l c o m m o d itie s o u t paced th e n a tio n a l c o m m o d itie s g ro w th ra te . T h e ir a llo c a tio n e ffe c t h o w e v e r, w as n e g a tiv e im p ly in g th a t M ic h ig a n w a s under sp e cia lize d in s o yb e a n s and hay. S ugar beets on th e o th e r hand had b o th a p o s itiv e e x p e c te d e ffe c t and a llo c a tio n e ffe c t. ■ M ic h ig a n d ry beans c o n tin u e d to s h o w a ste a d y e ro sio n in its c o m p e titiv e p o s itio n . The net c o m p e titiv e e ffe c t w a s a n e g a tiv e $ 7 0 .8 m illio n . 239 ■ A t th e n a tio n a l level p o ta to e s , hay, m in t, and m u sh ro o m s w e re fa s t g ro w th s e c to rs fo r th e fie ld cro p s , (n o tice th e p o s itiv e e x p e c te d se cto ra l g ro w th e ffe c ts ). ■ Field c ro p to ta ls fo r b o th th e n e t se c to ra l m ix e ffe c t and th e n e t c o m p e titiv e e ffe c t are n e g a tiv e . The to ta l n e g a tiv e e x p e c te d s e c to ra l e ffe c t o f $ 2 2 0 .4 m illio n s h o w s th a t at th e n a tio n a l level m a n y fie ld cro p s e c to rs lagged to ta l n a tio n a l cash re c e ip t g ro w th in th e 8 0 's . T he p o s itiv e d iffe re n tia l s e c to ra l m ix e ffe c t o f $ 2 2 .5 m illio n m eans th a t th e s ta te w as n o t o v e r sp e cia lizin g in lagging n a tio n a l s e c to rs . e ffe c t w a s a n e g a tiv e $ 4 4 .1 m illio n . The n e t c o m p e titiv e The s ta te o u t p e rfo rm e d m a n y o f the n a tio n a l c o m m o d itie s g ive n th e p o s itiv e e x p e c te d c o m p e titiv e e ffe c t o f $ 1 3 1 .4 m illio n . H o w e v e r, th e a llo c a tio n e ffe c t w a s a n e g a tiv e $ 1 7 5 .5 m illio n , s h o w in g th e o v e r s p e c ia liz a tio n o f som e th e c o m m o d itie s in la g g in g s e c to rs . Field C rop s 1 9 7 0 -1 9 9 0 : ■ O ve r th e tw o d ecades, to ta l cash re c e ip ts increased fro m $ 2 4 1 .0 m illio n in 1 9 7 0 to $ 1 .0 5 b illio n in 1 9 9 0 . A ll th re e s h ift-s h a re to ta l n e t e ffe c t c o m p o n e n ts are p o s itiv e , and all to ta l e x p e c te d and d iffe re n tia l e ffe c ts are p o s itiv e e x c e p t fo r th e a llo c a tio n e ffe c t. n e g a tiv e $ 2 4 2 .9 m illio n . The to ta l a llo c a tio n e ffe c t is a 240 ■ T he n e g a tiv e to ta l a llo c a tio n e ffe c t is p rim a rily a re s u lt o f tw o cro p s , s o yb e a n s and d ry beans. The n e g a tive s o yb e a n a llo c a tio n e ffe c t o f $ 1 0 6 ,9 4 8 m illio n m eans th a t th e s ta te un de r sp e cialized in a fa s t g ro w th c o m m o d ity (s e c to r). The e x p e c te d c o m p e titiv e e ffe c t fo r M ic h ig a n so yb e a n cash re c e ip ts h o w e v e r, g re w fa s te r th a n n a tio n a l so y b e a n cash re c e ip ts and th e n e t c o m p e titiv e e ffe c t w a s $ 1 2 1 .3 m illio n . M ic h ig a n d ry beans on th e o th e r hand re co rd e d a n e g a tiv e a llo c a tio n e ffe c t because g ro w th in cash re c e ip ts is w e ll b e lo w th e n a tio n a l g ro w th ra te . D ry beans like s o yb e a n s w e re co n s id e re d a fa s t g ro w th c o m m o d ity 126 d u rin g th e 7 0 's and 8 0 's . ■ M ic h ig a n c o rn cash re ce ip ts im p ro ve d in th e 7 0 's and 8 0 's w ith m o s t o f th e g ro w th o c c u rrin g in th e 7 0 's . A c tu a l cash re c e ip ts e xp an d e d fro m $ 6 1 .0 m illio n in 1 9 7 0 to $ 3 3 8 .7 m illio n in 1 9 9 0 . N a tio n a lly co rn cash re c e ip ts g re w fa s te r th a n to ta l cash re c e ip ts and are c o n s id e re d a g ro w th c o m m o d ity . M ic h ig a n 's c o rn re c e ip ts a c tu a lly g re w a t a fa s te r ra te th a n th e n a tio n a l c o rn re c e ip t rate. T his re su lte d in a h ig h ly p o s itiv e e x p e cte d c o m p e titiv e e ffe c t o f $ 9 4 .7 m illio n . ■ From a p e rc e n ta g e g ro w th p e rs p e c tiv e hay w a s one o f th e la rg e s t fie ld 126 N o t e : t h e f a s t g r o w t h c o m m o d i t y is i d e n t i f i e d b y t h e p o s i t i v e e x p e c t e d s e c t o r a l g r o w t h e f f e c t , in t h i s c a s e $ 2 , 5 6 5 mi ll i o n. 241 c ro p g a in e rs. A c tu a l ca sh re ce ip ts increased fro m $ 1 0 .7 m illio n in 1 9 7 0 to $ 8 6 .8 m illio n in 1 9 9 0 , up 7 1 1 % . The g ro w th in ca sh re c e ip ts o f $ 7 6 .0 m illio n is d e c o m p o s e d in to th e p o s itiv e n e t e ffe c ts o f $ 2 4 .2 m illio n fro m th e n a tio n a l g ro w th e ffe c t, $ 1 9 .7 m illio n fro m th e n e t s e c to ra l m ix e ffe c t, and $ 3 2 .1 m illio n fro m th e net c o m p e titiv e e ffe c t. Each o f th e m o d e st n e g a tiv e d iffe re n tia l and a llo c a tio n e ffe c ts s h o w th a t th e s ta te w a s s lig h tly u n d e r sp e cia lize d in hay. F ru it and O th e r 1 9 7 0 -1 9 8 0 : ■ Based on th e c a lc u la te d h o m o th e tic c o m p o n e n t o f $ 2 2 .4 m illio n co m p a re d to th e to ta l a c tu a l 1 9 7 0 cash re c e ip ts o f $ 6 8 .4 , M ic h ig a n is co n s id e re d a fru it o rie n te d s ta te . O f th e seven fru it cro p s a n alyze d , fiv e o f th e cro p s had 1 9 7 0 cash re c e ip ts th a t are a b ove th e ir re s p e c tiv e h o m o th e tic c o m p o n e n ts . ■ D u rin g th e 7 0 's M ic h ig a n 's c o m p e titiv e p o s itio n in th e fru it s e c to r e ro de d . E very c o m m o d ity e x c e p t ch e rrie s, had n e g a tiv e re s u lts fo r th e ir e x p e cte d c o m p e titiv e e ffe c t. $ 2 0 .8 m illio n . T h e to ta l e x p e c te d c o m p e titiv e e ffe c t w a s a n e g a tive T his m eans th a t M ic h ig a n fr u it cash re c e ip ts g re w a t a m u ch s lo w e r ra te th a n th e n a tio n a l fr u it cash re c e ip ts . ■ C he rrie s s h o w e d th e m o s t s ig n ific a n t gains fro m a c o m p e titiv e p o s itio n 242 (g ro w in g fa s te r th a n th e n a tio n a l c h e rry re c e ip ts ). The n e t c o m p e titiv e e ffe c t w a s $4.1 m illio n , w ith th e e x p e c te d c o m p e titiv e e ffe c t $ 2 8 2 th o u s a n d and th e a llo c a tio n e ffe c t $ 3 .8 m illio n . The n u m b e rs are n o t as fa v o ra b le h o w e v e r, fo r th e n e t s e c to ra l m ix e ffe c t, w ith a n e g a tiv e $ 5 .7 m illio n , s h o w in g th a t c h e rrie s w e re in a s lo w g ro w th s e c to r in a g ric u ltu re . ■ A p p le s , an im p o rta n t fr u it c ro p in th e s ta te , did n o t p e rfo rm w e ll c o m p e titiv e ly . The net c o m p e titiv e e ffe c t w a s a n e g a tiv e $ 9 .7 m illio n . T h is happened d e s p ite apples being a fa s t g ro w th s e c to r127 a t th e n a tio n a l level. ■ M ic h ig a n grape cash re c e ip ts fell c o n s id e ra b ly b ehind th e g ro w th in n a tio n a l grape re c e ip ts . G rapes p o ste d a n e g a tiv e n e t c o m p e titiv e e ffe c t o f $ 1 4 .8 m illio n . ■ G re e n ho u se & n u rs e ry p ro d u c ts cash re c e ip ts increased fro m $ 3 0 .5 m illio n in 1 9 7 0 to $ 1 0 8 .4 m illio n in 1 9 9 0 , up 2 5 6 % . are p o s itiv e . A ll net e ffe c t c o m p o n e n ts O f p a rtic u la r n o te is th e fa c t th a t g re e n h o u se and n u rse ry p ro d u c ts is c o n sid e re d a fa s t g ro w th s e c to r, (the p o s itiv e e x p e c te d s e c to ra l g ro w th e ffe c t o f $ 1 5 .4 m illio n ). The s ta te also sp e cia lize d in th e c o m m o d ity , w h ic h yie ld e d a p o s itiv e d iffe re n tia l s e c to ra l m ix e ffe c t o f $ 9 .8 127 Note: the net sectoral mix e ffe ct was $8.2 million. 243 m illio n . Fruit and Other 1 9 8 0 - 1 9 9 0 : ■ D u rin g th e d e cad e o f th e 8 0 's to ta l M ic h ig a n fr u it cash re c e ip ts increased o n ly a s lig h t a m o u n t, fro m $ 1 8 0 .6 m illio n in 1 9 8 0 to $ 1 9 3 .5 m illio n in 1990. N a tio n a lly th e to ta l fr u it s e c to r w a s c o n s id e re d a fa s t g ro w th in d u s try , (the to ta l e x p e c te d s e c to ra l g ro w th e ffe c t w a s $ 1 7 .0 m illio n ). D e s p ite th e n a tio n a l g ro w th fo r fru it cash re c e ip ts , M ic h ig a n c o n tin u e d to lose c o m p e titiv e g ro u n d . The e x p e c te d c o m p e titiv e e ffe c t fo r M ic h ig a n w a s a n e g a tiv e $ 3 1 .2 m illio n and th e a llo c a tio n e ffe c t w a s a n e g a tive $ 1 9 .8 m illio n , fo r a c o m b in e d n e g a tiv e net e ffe c t o f $ 5 1 .0 m illio n . ■ In a b s o lu te te rm s apples had th e la rg e st n e g a tiv e net c o m p e titiv e e ffe c t o f $ 2 3 .0 m illio n .128 A t th e n a tio n a l level apples are a fa s t g ro w th c o m m o d ity . T he e x p e c te d s e c to ra l g ro w th e ffe c t w a s a p o s itiv e $5.1 m illio n . ■ A c tu a l s tra w b e rry cash re c e ip ts fell fro m $ 8 .5 m illio n in 1 9 8 0 to $ 6 .5 m illio n in 1 9 9 0 , d o w n 2 3 .5 % . T his o c c u rre d w h ile n a tio n a l s tra w b e rry ca sh re c e ip ts w e re a c tu a lly g ro w in g fa s te r th a n to ta l c o m m o d ity cash re c e ip ts . In p e rc e n ta g e te rm s s tra w b e rrie s s h o w e d th e la rg e s t n e g a tive 128 Note: this was 45 % of the negative net com petitive e ffe c t for all fru it. 244 c o m p e titiv e e ffe c ts . The e x p e c te d c o m p e titiv e e ffe c t w a s a n e g a tiv e $ 8 .3 m illio n and th e a llo c a tio n e ffe c t w a s a n e g a tiv e $ 3 .7 m illio n . ■ B lu e b e rrie s 129 w e re one o f M ic h ig a n 's fru its th a t rem ained c o m p e titiv e in th e 8 0 ’ s. A c tu a l cash re ce ip ts increased fro m $ 1 9 .7 m illio n in 1 9 8 0 to $ 2 7 .0 m illio n in 1 9 9 0 . The e x p e c te d c o m p e titiv e e ffe c t w a s $ 2 2 3 th o u s a n d and th e a llo c a tio n e ffe c t w a s $ 3 .6 m illio n . Fruit and Other 1 9 7 0 - 1 9 9 0 : ■ T h e d ecades o f th e 7 0 's and 8 0 's w e re p e rio d s o f s lo w g ro w th fo r M ic h ig a n fr u it cash re c e ip ts co m p a re d w ith n a tio n a l fru it re c e ip ts . M ic h ig a n fru it p ro d u c e d a n e g a tive n e t c o m p e titiv e e ffe c t. E very The to ta l net c o m p e titiv e e ffe c t w a s a n e g a tiv e $ 1 0 1 .5 m illio n , w h ile th e n e t s e c to ra l m ix e ffe c t w a s $ 4 6 .0 m illio n . ■ From a n a tio n a l p e rs p e c tiv e grapes w e re one o f th e fa s t g ro w th c o m m o d itie s . The e x p e c te d s e c to ra l g ro w th e ffe c t fo r M ic h ig a n w a s a h ig h ly p o s itiv e $ 1 4 .0 m illio n . H o w e v e r, M ic h ig a n grape re c e ip ts d id n o t keep pace w ith n a tio n a l grape re c e ip ts . T h is is re fle c te d by th e n e g a tive e x p e c te d c o m p e titiv e e ffe c t o f $ 2 3 .5 m illio n . 129 Note: blueberries were not analyzed in the 7 0 's because the Michigan A gricultural Statistical Service did not then collect data on blueberries. 245 ■ M ic h ig a n has been a n a tio n a l p a c e s e tte r in th e p ro d u c tio n o f ch e rrie s fo r ye a rs . T his lea d e rsh ip is re fle c te d by th e large d iffe re n c e b e tw e e n th e h o m o th e tic c o m p o n e n t o f $ 1 .3 m illio n and th e a c tu a l cash re c e ip ts o f $ 1 9 .4 m illio n in 1 9 7 0 . For th e 7 0 's and 8 0 's M ic h ig a n c h e rrie s e xp e rie n c e d s lig h t e ro s io n in th e s e c to r. N e g a tive e ffe c ts w e re c a lc u la te d fo r b o th th e n e t s e c to ra l m ix e ffe c t and th e n e t c o m p e titiv e e ffe c t. M ost o f th e n e g a tiv e e ffe c ts are a re s u lt o f n a tio n a l c h e rry re c e ip ts la g g in g to ta l c o m m o d ity re c e ip ts .130 ■ M ic h ig a n 's g re en h o use and n u rs e ry re ce ip ts g re w s u b s ta n tia lly d u rin g th e 7 0 's and 8 0 's b u t so did n a tio n a l re c e ip ts . M ic h ig a n cash re c e ip ts incre a se d fro m $ 3 0 .5 m illio n in 1 9 7 0 to $ 2 5 9 .7 m illio n in 1 9 9 0 , up 7 5 1 .5 % . T he e x te n t o f th e fa s t g ro w th in n a tio n a l re c e ip ts is h ig h lig h te d b y th e e x p e c te d s e c to ra l g ro w th e ffe c t o f $ 1 0 2 .8 m illio n . From a c o m p e titiv e p e rs p e c tiv e th e g ro w th o f M ic h ig a n re c e ip ts w a s s lig h tly b e hin d th e U .S ., th is is em phasized by th e n e g a tiv e e x p e c te d c o m p e titiv e e ffe c t o f $ 4 .6 m illio n . V e g e ta b le s and M e lo n s 1 9 7 0 -1 9 8 0 : ■ In 1 9 7 0 th e s ta te had to ta l v e g e ta b le s and m e lo n s cash re c e ip ts o f $ 5 6 .5 130 In other w ords Michigan was specializing in a lagging sector. 246 m illio n c o m p a re d to a h o m o th e tic c o m p o n e n t o f $ 3 2 .5 m illio n .131 This stre sse s th e re la tiv e im p o rta n c e o f th is s e c to r to M ic h ig a n 's a g ric u ltu ra l econom y. ■ From 1 9 7 0 to 1 9 8 0 to ta l M ic h ig a n v e g e ta b le and m elon ca sh re c e ip ts incre a se d fro m $ 5 6 .5 m illio n to $ 1 1 9 .1 m illio n . T h is s e c to r h o w e v e r, w a s co n s id e re d a s lo w g ro w th s e c to r n a tio n a lly . T he e x p e c te d s e c to ra l g ro w th e ffe c t w a s a n e g a tiv e $ 1 6 .0 m illio n and th e d iffe re n tia l s e c to ra l m ix e ffe c t w a s a n e g a tiv e $ 1 1 .7 m illio n . The n e g a tiv e d iffe re n tia l e ffe c t s h o w s th a t th e s ta te w a s s p e c ia liz in g in a s lo w g ro w th g ro u p (ve g e ta b le s and m elons). ■ T h re e v e g e ta b le s (snap beans, c e le ry , and asp ara g u s) d is p la y e d th e g re a te s t c o m p e titiv e e ffe c ts . The la rg e s t n e t c o m p e titiv e e ffe c t belonged to a sp ara g u s o f $ 6 .3 m illio n , seco nd c e le ry w ith $ 3 .0 m illio n and th ird snap beans w ith $ 2 .5 m illio n . ■ O n io ns and c a rro ts s h o w e d the la rg e s t n e g a tiv e n e t c o m p e titiv e e ffe c ts . T h e n e g a tiv e e ffe c t fo r o n io n s w a s $ 9 .9 m illio n and th e n e g a tiv e e ffe c t fo r c a rro ts w a s $ 5 .7 m illio n . M ic h ig a n o n io n s had th e n e g a tiv e c o m p e titiv e e ffe c t d e s p ite being in a fa s t g ro w th n a tio n a l s e c to r and p o s itiv e se cto ra l 131 Note: of the 1 3 com m odities analyzed in this sector, 10 had actual 1 970 cash receipts th a t are greater than their respective hom othetic com ponents. 247 mix ef fe cts . V e g e ta b le s and M elon s 1 9 8 0 - 1 9 9 0 : ■ In t h e 8 0 ' s Michigan v e g e t a b l e an d melon rec ei pts in c r e a se d from $ 1 1 9 . 1 million in 1 9 8 0 to $ 1 5 1 . 1 million in 1 9 9 0 , up $ 3 2 . 0 million. Michigan c o n tin u ed th e s a m e p a tte r n a s in the 7 0 ' s with an e v e n larger negative net com petitive ef fe c t of $ 2 4 . 5 million. As a gr oup at t h e national level v e g e t a b l e s and m elon s m oved into a g r o w th s e c t o r in th e 8 0 ' s . 132 ■ Th e positive co m petitive ef fect trend of a s p a r a g u s in t h e 7 0 ' s shifted during t h e 8 0 ' s . In the 8 0 ' s Michigan a s p a r a g u s had a nega tive ne t co m pe titive ef fe c t of $ 6 . 3 million, despite a positive e x p e c t e d sectoral g r o w t h effect. ■ T o m a t o e s are o n e of th e v e g e ta b le s to s h o w t h e sm alles t g r o w th in receipts. In 1 9 8 0 Michigan t o m a t o rece ip ts w e r e $ 1 7 . 2 million an d in 1 9 9 0 th e y had only incre ased to $ 1 8 . 4 million, up app ro ximately 7 . 0 % . Th e flat Michigan rece ipts oc c u r re d while national c a s h rece ipts for t o m a t o e s had e x p a n d e d alm ost 8 3 % . The large d i v e r g e n c e in receipt g r o w th r a t e s p r o d u c e d a negative e x p e c t e d co m pet itive ef fe c t of $ 1 5 . 8 132 Note: the total expected sectoral gro w th e ffe c t was $25.5 million, highlighting vegetables and melons as a fast grow th group. 248 million for Michigan t o m a t o e s . ■ S w e e t cor n, c u c u m b e r s an d s n a p b e a n s all yielded positive co m pe ti ti ve e f fe c t s . S n a p b e a n s had th e largest ne t com pe titive ef fe c t of $ 3 . 4 million, followed by c u c u m b e r s with a co m pe titive effe ct of $ 3 . 0 million, an d s w e e t co rn had a c o m petitive effe ct of $ 2 . 4 million. V e g e t a b l e s and Melons 1 9 7 0 - 1 9 9 0 : ■ During t h e d e c a d e s of t h e 7 0 ' s and 8 0 ' s total Michigan v e g e t a b l e s and m elo n s c a s h receipts i n creased $ 9 4 . 6 million. Nationally t h e g r o u p 's c a s h rece ip ts g r e w at a slightly f aster p a c e th a n total c o m m o d it y c a s h receipts. ■ M ic higan's co mpetitive position for v e g e t a b l e s an d m elons er o d e d in during t h e 7 0 ' s and 8 0 ' s . The e x p e c t e d co mpetitive e f f e c t w a s a negative $ 2 2 . 3 million and the allocation effe ct w a s a n egative $ 1 1 . 0 million.133 ■ Four v e g e t a b l e crop s with large positive e x p e c t e d c o m petitive e f fe c t s w e r e : s w e e t corn, s n a p b e a n s , a s p a r a g u s , and p e p p e r s . M ost of th e gains for t h e s e com m odities h a p p e n e d in t h e 8 0 ' s . S w e e t co rn a n d p e p p e r s 133 The negative allocation e ffe c t shows that the state was over specialized in vegetables and melons that grew at a slower rate than national vegetables and melons cash receipts. 249 improved their co m pet itive positions in fast g r o w t h s e c t o r s . 134 S n a p b e a n s an d a s p a r a g u s h o w e v e r , improved their co mpetitive positions d e s p ite being in s lo w g r o w th s e c t o r s . 135 ■ T hree c o m m o d it ie s with th e largest ne gative e x p e c t e d co m peti ti ve e f fe c t s w e r e : t o m a t o e s , lettuce, and onions. T o m a t o e s an d lettuce had negative e x p e c t e d co m petit iv e ef fe c ts of $ 1 4 . 3 million an d $ 7 . 4 million. Each of t h e s e c o m m o d it ie s h o w e v e r had positive allocation e f f e c t s 136 t h a t offset t h e a d v e r s e e x p e c t e d com petitive ef fe cts. Onions had th e largest negative n e t c o m petitive ef fe c t for all v e g e ta b le s of $ 1 4 . 7 million. 134 Note: the positive expected sectoral grow th e ffe cts for each com m odity. 135 Note: the negative expected sectoral grow th e ffe cts for each com m odity. 136 The positive allocation e ffe cts for tom atoes and lettuce show th a t the state w as not specialized in these com m odities. 250 C h a p te r V S h ift-S h a re T ab les Table VI S h ift-S h a re Analysis of Livestock & P ro d u c ts C ash R eceipts, 1 9 7 0 - 1 9 8 0 SHIFT-SHARE ANALYSIS OF AGRICULTURAL CASH RECEIPTS, MICHIGAN VERSUS THE UNITED STATES SECTOR: LIVESTOCK & PRODUCTS, PERIOD OF EVALUATION 1970 & 1980, ($ 000's) Cattle & Calves 1 9 70 Cash Receipts 119,231 Homothetic Component Expected National G row th Effect Differential National G row th Effect Dairy Products Sheep Farm & Lambs Chickens Total Livestock Hogs Eggs 2 6 2 ,2 7 7 5 2 ,0 3 8 3 8 ,9 7 5 92 2 4 ,7 9 6 3 ,6 4 3 1 ,5 4 7 1 ,4 3 7 4 8 4 ,8 6 6 2 7 7 ,3 6 6 1 3 1 ,5 4 0 8 9 ,631 4 2 ,1 0 8 3 0 ,2 4 3 9 ,7 5 5 6 ,5 5 2 1 ,9 8 2 899 5 9 0 ,0 7 6 4 7 4 ,4 6 6 2 2 5 ,0 1 3 1 5 3 ,3 2 3 72 ,031 5 1 ,7 3 3 1 6 ,6 8 8 1 1 ,2 0 8 3 ,3 9 0 1,5 3 7 1 ,0 0 9 ,3 9 0 (2 7 0 ,5 0 8 ) 2 2 3 ,6 4 1 (6 4 ,3 0 6 ) (5 ,3 5 9 ) (5 0 ,1 5 7 ) (8 ,4 8 4 ) (4 ,9 7 7 ) (744) 921 (1 7 9 ,9 7 2 ) Net G row th Effect: 2 0 3 ,9 5 8 4 4 8 ,6 5 4 8 9 ,0 1 7 6 6 ,6 7 2 1 ,5 7 7 8 ,2 0 4 6,2 3 1 2 ,6 4 6 2 ,4 5 8 8 2 9 ,4 1 8 Expected Sectoral G row th Effect (1 1 4 ,1 2 7 ) (2 4 ,4 5 7 ) (5 6 ,3 0 4 ) (4 5 ,4 3 0 ) 5 ,1 8 4 (1 ,3 3 5 ) (8 ,6 4 7 ) (2 ,5 2 3 ) 142 (2 4 7 ,4 9 8 ) Differential Sectoral 6 5 ,0 6 7 (2 4 ,3 0 8 ) 2 3 ,6 1 5 3 ,3 8 0 (5 ,0 2 6 ) 679 3 ,8 3 9 554 85 6 7 ,8 8 5 M ix Effect Net Sectoral Mix (4 9 ,0 6 0 ) (4 8 ,7 6 6 ) (3 2 ,6 8 9 ) (4 2 ,0 5 0 ) 158 (656) (4 ,8 0 7 ) (1 ,9 7 0 ) 227 (1 7 9 ,6 1 3 ) Expected Competitive Effect Allocation Effect (1 3 4 ,9 4 1 ) (1 2 ,2 2 0 ) 3 6 ,7 9 5 (1 ,0 9 0 ) (1 7 ,7 8 2 ) 6,8 61 (1 .3 8 7 ) (244) (521) (1 2 4 ,5 2 7 ) 7 6 ,9 3 4 (1 2 ,1 4 6 ) 1 7 ,2 4 0 (3 ,4 8 8 ) 1312) 6 3 ,5 4 6 (2 4 ,3 6 6 ) (1 ,0 0 9 ) (542) 3 ,3 7 3 616 (771) 53 (5 8 ,0 0 7 ) (1 5 ,4 3 3 ) 2 1 ,3 6 3 81 Net Competitive (190) (833) (6 0 ,9 8 1 ) 1 9 80 Cash Receipts 2 1 6 ,1 2 3 6 3 7 ,8 0 0 1 2 9 .7 2 9 6 2 ,5 8 9 2 ,1 1 4 1 5 ,7 1 7 4 ,2 9 6 2 ,0 3 4 3 ,2 8 9 1 ,0 7 3 ,6 9 0 Change in Cash 9 6 ,8 9 2 3 7 5 ,5 2 3 7 7 ,6 9 1 2 3 ,6 1 3 1,1 9 3 10,921 653 487 1,8 5 2 5 8 8 ,8 2 4 Broilers Turkeys Honey Effect: Effect: Receipts 251 Commodities: Table Vli S h ift-S hare Analysis of L ivestock & P ro d u c ts C ash R eceipts, 1 9 8 0 - 1 9 9 0 SHIFT-SHARE ANALYSIS OF AGRICULTURAL CASH RECEIPTS, MICHIGAN VERSUS THE UNITED STATES SECTOR: LIVESTOCK & PRODUCTS, PERIOD OF EVALUATION 1980 & 1990, ($ 000's) Commodities: Cattle & Calves Dairy Products Hogs Eggs Broilers Turkeys Sheep & Lambs Farm Chickens Honey Total Livestock 1 9 8 0 Cash Receipts 2 1 6 ,1 2 3 6 3 7 ,8 0 0 1 2 9 ,7 2 9 6 2 ,5 8 9 2 ,1 1 4 1 5 ,7 1 7 4 ,2 9 6 2 ,0 3 4 3 ,2 8 9 1 ,0 7 3 ,6 9 0 Homothetic 6 8 7 ,5 4 0 3 5 8 ,0 4 7 2 0 1 ,2 3 6 7 4 ,0 7 9 9 3 ,9 7 1 2 7 ,071 9 ,8 2 5 3 ,0 7 2 2 ,7 7 9 1 ,4 5 7 ,6 2 0 1 3 4 ,9 9 8 7 0 ,3 0 2 3 9 ,5 1 3 1 4 ,5 4 5 18 ,451 5 ,3 1 5 1 ,9 2 9 60 3 546 2 8 6 ,2 0 2 (9 2 ,5 6 2 ) 5 4 ,9 2 9 (1 4 ,0 4 0 ) (2 ,2 5 6 ) (1 8 ,0 3 6 ) (2 ,2 2 9 ) (1 ,0 8 6 ) (204) 100 (7 5 ,3 8 4 ) Net Growth Effect: 4 2 ,4 3 6 12 5,23 1 2 5 ,4 7 2 1 2 ,2 8 9 415 3 ,0 8 6 84 3 399 646 2 1 0 ,8 1 8 Expected Sectoral G row th Effect 2 2 ,171 (9 ,7 3 6 ) (8 ,0 2 7 ) (3 ,5 2 8 ) 7 2 ,7 2 4 1 8 ,0 7 0 (2 ,3 2 0 ) (1 ,5 2 7 ) (993) 8 6 ,8 3 3 Differential Sectoral M ix Effect Net Sectoral Mix Effect: (1 5 ,2 0 2 ) (7 ,6 0 7 ) 2 ,8 5 2 547 (7 1 ,0 8 7 ) (7 ,5 7 9 ) 1 ,3 0 6 516 (182) (9 6 ,4 3 6 ) 6 ,9 6 9 (1 7 ,3 4 4 ) (5 ,1 7 5 ) (2 ,9 8 1 ) 1 ,6 3 6 10,491 (1 ,0 1 4 ) (1 ,0 1 1 ) (1 ,1 7 6 ) (9 .6 0 3 ) Expected Competitive Effect 3 4 ,5 9 9 (3 1 ,9 0 4 ) 1 1 0 ,5 9 3 (6 ,5 8 6 ) (1 3 9 ,2 9 3 ) 3 1 ,7 0 6 376 133 1 ,2 8 7 910 Allocation Effect Net Competitive Effect: (2 3 ,7 2 3 ) 1 0 ,8 7 6 (2 4 ,9 2 8 ) (5 6 ,8 3 2 ) (3 9 ,2 9 8 ) 7 1 ,2 9 5 1,021 (5 ,5 6 4 ) 1 3 6 ,1 5 9 (3 ,1 3 4 ) (1 3 ,2 9 8 ) 1 8 ,4 0 8 (211) 164 (45) 88 236 1 ,5 2 4 3 5 ,9 1 5 3 6 ,8 2 5 1 9 9 0 Cash Receipts 2 7 6 ,4 0 4 6 8 8 ,8 5 5 2 2 1 ,3 2 2 6 6 ,3 3 3 1,0 3 2 4 7 ,7 0 2 4 ,2 8 9 1 ,5 1 0 4 ,2 8 2 1 ,3 1 1 ,7 3 0 Change in Cash 6 0 ,2 8 1 5 1 ,0 5 6 9 1 ,5 9 3 3 ,7 4 4 (1 ,0 8 3 ) 3 1 ,9 8 5 (7) (523) 99 4 2 3 8 ,0 4 0 Component Expected National G rowth Effect Differential National G rowth Effect 252 Receipts Table VIII Shift-Share A nalysis of L ivestock & P ro d u c ts C ash R eceipts, 1 9 7 0 - 1 9 9 0 SHIFT-SHARE ANALYSIS OF AGRICULTURAL CASH RECEIPTS, MICHIGAN VERSUS THE UNITED STATES SECTOR: LIVESTOCK & PRODUCTS, PERIOD OF EVALUATION 1970 & 1990, ($ 000's) Commodities: Cattle Dairy & Calves Products Hogs Eggs Broilers Turkeys Sheep Farm & Lambs Chickens Honey Total Livestock 1 1 9 ,2 3 1 2 6 2 ,2 7 7 5 2 ,0 3 8 3 8 ,9 7 5 922 4 ,7 9 6 3 ,6 4 3 1,5 4 7 1 ,4 3 7 4 8 4 ,8 6 6 Homothetic Component 2 7 7 ,3 6 6 1 3 1 ,5 4 0 8 9 ,6 3 1 4 2 ,1 0 8 3 0 ,2 4 3 9 ,7 5 5 6 ,5 5 2 1,9 8 2 899 5 9 0 ,0 7 6 Expected National G rowth Effect 6 2 2 ,0 8 8 2 9 5 ,0 2 2 2 0 1 ,0 2 7 9 4 ,4 4 2 6 7 ,8 2 9 2 1 ,8 8 0 1 4 ,6 9 5 4 ,4 4 5 2 ,0 1 5 1 ,3 2 3 ,4 4 3 Differential National Growth Effect Net G rowth Effect: (3 5 4 ,6 7 1 ) 2 9 3 ,2 2 3 (8 4 ,3 1 3 ) (7 ,0 2 7 ) (6 5 ,7 6 2 ) (1 1 ,1 2 3 ) (6 ,5 2 5 ) (976) 1,2 0 7 (2 3 5 ,9 6 7 ) 2 6 7 ,4 1 6 5 8 8 ,2 4 5 1 1 6 ,7 1 3 8 7 ,4 1 5 2 ,0 6 7 1 0 ,7 5 7 8 ,1 7 0 3 ,4 7 0 3 ,2 2 3 1 ,0 8 7 ,4 7 6 Expected Sectoral G row th Effect (1 1 5 ,9 7 2 ) (3 8 ,2 9 0 ) (7 4 ,8 0 4 ) (5 7 ,6 2 2 ) 7 3 ,6 5 4 1 5 ,1 6 3 (1 2 ,4 9 6 ) (4 ,4 3 5 ) (752) (2 1 5 ,5 5 5 ) Differential Sectoral 6 6 ,1 1 9 (3 8 ,0 5 7 ) 3 1 ,3 7 4 4 ,2 8 7 (7 1 ,4 0 9 ) (7 ,7 0 9 ) 5 ,5 4 9 973 (450) (9 ,3 2 2 ) M ix Effect Net Sectoral Mix (4 9 ,8 5 3 ) (7 6 ,3 4 7 ) (4 3 ,4 3 0 ) (5 3 ,3 3 5 ) 2 ,2 4 5 7 ,4 5 5 (6 ,9 4 8 ) 13,461) (1 ,2 0 2 ) (2 2 4 ,8 7 7 ) Expected Competitive (1 4 0 ,4 8 8 ) (4 2 ,7 9 0 ) 1 6 5,35 1 (7 .2 6 3 ) (1 3 7 ,8 7 4 ) 5 0 ,2 3 2 (1 ,0 3 6 ) (57) 516 (1 1 3 ,4 1 0 ) Effect Allocation Effect Net Competitive 8 0 ,0 9 6 (4 2 ,5 2 9 ) (6 ,7 2 3 ) 1 3 3 ,6 7 2 (4 ,2 0 2 ) (2 5 ,5 3 7 ) (8 5 ,3 1 9 ) (6 9 ,3 5 0 ) 9 6 ,0 0 0 540 (6 0 ,3 9 1 ) 2 4 ,6 9 5 460 (57 6) 13 (45) 309 825 7 7 ,6 7 4 (3 5 ,7 3 6 ) 1 9 9 0 Cash Receipts 2 7 6 ,4 0 4 6 8 8 ,8 5 5 2 2 1 ,3 2 2 6 6 ,3 3 3 1,0 32 4 7 ,7 0 2 4 ,2 8 9 1 ,5 1 0 4 ,2 8 2 1 ,3 1 1 ,7 3 0 Change in Cash 1 5 7 ,1 7 2 4 2 6 ,5 7 8 1 6 9 ,2 8 4 2 7 ,3 5 8 110 4 2 ,9 0 6 646 (37) 2 ,8 4 5 8 2 6 ,8 6 3 Effect: Effect: Receipts 253 1 9 7 0 Cash Receipts Table IX S hift-S hare Analysis of Field C ro ps C a s h R ece ip ts, 1 9 7 0 - 1 9 8 0 SHIFT-SHARE ANALYSIS OF AGRICULTURAL CASH RECEIPTS, MICHIGAN VERSUS THE UNITED STATES SECTOR: FIELD CROPS, PERIOD OF EVALUATION 1970 & 1980, ($ 000's) Commodities: Corn Soybeans W heat Hay Potatoes Sugar Beets Barley 1 9 7 0 Cash Receipts 6 1 ,0 1 2 3 3 ,3 8 9 2 6 ,5 7 5 1 0 ,7 7 0 2 1 ,0 6 0 2 2 ,5 8 7 390 Homothetic 6 4 ,9 4 6 6 2 ,8 2 9 3 9 ,7 2 8 1 2 ,8 8 7 1 2 ,5 5 3 7 ,8 0 4 6,0 91 Expected National G rowth Effect 1 1 1 ,0 9 7 1 0 7 ,4 7 6 6 7 ,9 5 9 2 2 ,0 4 5 2 1 ,4 7 4 1 3 ,3 5 0 1 0 ,4 2 0 Differential National (6 ,7 2 9 ) (5 0 ,3 6 1 ) (2 2 ,5 0 0 ) (3 ,6 2 2 ) 1 4 ,5 5 2 2 5 ,2 8 8 (9 ,7 5 3 ) Net G rowth Effect: 1 0 4 ,3 6 8 5 7 ,1 1 6 4 5 ,4 5 9 1 8 ,4 2 3 3 6 ,0 2 6 3 8 ,6 3 8 667 Expected Sectoral G row th Effect 7 8 ,5 7 3 9 6 ,3 5 2 7 4 ,8 6 6 2 ,0 9 9 (6 ,1 3 7 ) (777) (1 ,2 5 6 ) Differential Sectoral (4 ,7 5 9 ) (4 5 ,1 4 8 ) (2 4 ,7 8 6 ) (345) (4 ,1 5 9 ) (1 ,4 7 2 ) 1 ,1 7 6 M ix Effect Net Sectoral Mix Effect: 7 3 ,8 1 4 5 1 ,2 0 4 5 0 ,0 8 0 1 ,7 5 4 (1 0 ,2 9 6 ) (2 ,2 4 9 ) (80) Expected Competitive 2 1 0 ,8 7 0 1 0 1 ,7 1 2 (1 ,9 0 1 ) (8 ,8 9 0 ) 1 ,9 3 8 4 ,6 2 3 8,0 01 (1 2 ,7 7 2 ) 1 9 8 ,0 9 8 (4 7 ,6 6 0 ) 5 4 ,0 5 2 62 9 (1 ,2 7 1 ) 1,461 (7 ,4 3 0 ) 1 ,3 1 3 3 ,2 5 2 8 ,7 5 7 13,381 (7 ,4 8 9 ) 512 1 9 8 0 Cash Receipts 4 3 7 ,2 9 3 1 9 5,76 1 1 2 0 ,8 4 3 2 3 ,5 1 8 5 0 ,0 4 2 7 2 ,3 5 7 1 ,4 8 9 Change in Cash 3 7 6 ,2 8 1 1 6 2 ,3 7 2 9 4 ,2 6 8 1 2 ,7 4 8 2 8 ,9 8 2 4 9 ,7 7 0 1,099 Component G rowth Effect Net Competitive Effect: Receipts 254 Effect Allocation Effect Table IX (C ontinued), Shift-Share Analysis of Field C rops C ash R eceipts, 1 9 7 0 - 1 9 8 0 SHIFT-SHARE ANALYSIS OF AGRICULTURAL CASH RECEIPTS, MICHIGAN VERSUS THE UNITED STATES SECTOR: FIELD CROPS, PERIOD OF EVALUATION 1970 & 1980, ($ 000's) Total Field Commodities: Dry Beans Oats Mushrooms Rye Crops Mint 1 9 7 0 Cash Receipts 7 ,0 6 6 5 6 ,2 3 3 n.a. 648 1.2 83 2 4 1 ,0 1 4 Homothetic 4 ,3 6 6 3 ,1 2 9 n.a. 610 545 2 1 5 ,4 9 0 7 ,4 6 9 5 ,3 5 3 n.a. 1 ,0 4 3 9 33 3 6 8 ,6 2 0 4 ,6 1 8 9 0 ,8 4 1 n.a. 66 1,261 4 3 ,6 6 2 1 2 ,0 8 7 9 6 ,1 9 3 n.a. 1 ,1 0 9 2 ,1 9 4 4 1 2 ,2 8 1 Expected Sectoral G rowth Effect (5 ,4 6 2 ) 3 ,3 7 8 n.a. ( 9 5 2) (196) 2 4 0 ,4 8 8 Differential Sectoral M ix Effect Net Sectoral Mix Effect: (3 ,3 7 7 ) 5 7 ,3 2 0 n.a. (60) (265) (2 5 ,8 7 6 ) ( 8 ,8 3 9 ) 6 0 ,6 9 8 n.a. (1 ,0 1 2 ) (462) 2 1 4 ,6 1 2 6 ,8 4 2 (3 ,2 9 5 ) n.a. 151 (601) 3 1 9 ,4 5 1 4 ,2 3 0 1 1 ,0 7 2 ( 5 5 ,9 2 2 ) ( 5 9 ,2 1 7 ) n.a. n.a. 10 161 (813) (1 ,4 1 4 ) (1 0 8 ,2 5 5 ) 2 1 1 ,1 9 6 1 9 8 0 Cash Receipts 2 1 ,3 8 6 1 5 3 ,9 0 8 n.a. 906 1,501 1 ,0 7 9 ,1 0 4 Change in Cash 1 4 ,3 2 0 9 7 ,6 7 5 n.a. 258 318 8 3 8 .0 9 0 Component Expected National G row th Effect Expected Competitive Effect Allocation Effect Net Competitive Effect: Receipts 255 Differential National Growth Effect Net G rowth Effect: Table X S hift-S h are Analysis of Field C rops C a s h R eceip ts, 1 9 8 0 - 1 9 9 0 SHIFT-SHARE ANALYSIS OF AGRICULTURAL CASH RECEIPTS, MICHIGAN VERSUS THE UNITED STATES SECTOR: FIELD CROPS, PERIOD OF EVALUATION 1980 & 1990, ($ 000's) Commodities: Corn Soybeans W heat Hay Potatoes Sugar Beets Barley 1 9 8 0 Cash Receipts 4 3 7 ,2 9 3 1 9 5 ,7 6 1 1 2 0 ,8 4 3 2 3 ,5 1 8 5 0 ,0 4 2 7 2 ,3 5 7 1 ,4 8 9 Homothetic 2 7 4 ,5 1 4 2 8 7 ,4 9 6 1 9 6 ,8 2 0 3 9 ,9 2 6 3 0 ,0 7 0 2 1 ,9 7 0 1 6 ,4 4 7 Expected National G rowth Effect Differential National G rowth Effect 53 ,901 5 6 ,4 5 0 3 8 ,6 4 5 7 ,8 3 9 5 ,9 0 4 4 ,3 1 4 3 ,2 2 9 3 1 ,9 6 2 (1 8 ,0 1 2 ) (1 4 ,9 1 8 ) (3 ,2 2 2 ) 3 ,9 2 2 9 ,8 9 4 (2 ,9 3 7 ) Net Growth Effect: 8 5 ,8 6 2 3 8 ,4 3 8 2 3 ,7 2 7 4 ,6 1 8 9 ,8 2 6 1 4 ,2 0 7 292 Expected Sectoral G rowth Effect (48,4661 (1 1 1 ,1 9 8 ) (9 4 ,6 0 4 ) 2 2 ,711 14,191 (1 ,2 5 1 ) (2 ,3 5 5 ) Differential Sectoral (28,7391 3 5 ,4 8 1 3 6 ,5 1 9 (9 ,3 3 3 ) 9 ,4 2 6 (2 ,8 7 0 ) 2,141 Mix Effect Net Sectoral Mix (7 7 ,2 0 5 ) (7 5 ,7 1 7 ) (5 8 ,0 8 5 ) 1 3 ,3 7 8 2 3 ,6 1 7 (4 ,1 2 1 ) (213) (6 7 ,3 4 9 ) 1 1 3 ,8 6 8 1 0 ,8 8 4 7 6 ,8 2 5 (7 ,0 3 6 ) 8 ,4 7 9 7 ,8 3 8 (3 9 ,9 3 6 ) (1 0 7 ,2 8 5 ) (3 6 ,3 3 3 ) 7 7 ,5 3 5 (4 ,2 0 1 ) 6 ,6 8 2 (3 1 ,5 7 2 ) 4 5 ,2 5 3 (4 ,6 7 3 ) (1 1 ,7 0 9 ) 1 9 ,4 4 7 2 7 ,9 2 6 (7 .1 7 4 ) 714 1 9 9 0 Cash Receipts 3 3 8 ,6 6 5 2 3 6 ,0 1 7 9 3 ,1 6 8 8 6 ,7 6 7 7 1 ,7 7 7 1 1 0 ,3 6 9 2 ,2 8 2 Change in Cash (9 8 ,6 2 3 ) 4 0 ,2 5 6 (2 7 ,6 7 5 ) 6 3 ,2 4 9 2 1 ,7 3 4 3 8 ,0 1 2 79 3 Component Expected Competitive Effect Allocation Effect Net Competitive Effect: Receipts 256 Effect: Table X (C ontinued) Shift-Share A nalysis of Field C rops C ash R eceipts, 1 9 8 0 - 1 9 9 0 SHIFT-SHARE ANALYSIS OF AGRICULTURAL CASH RECEIPTS, MICHIGAN VERSUS THE UNITED STATES SECTOR: FIELD CROPS, PERIOD OF EVALUATION 1980 & 1990, ($ 000's) Commodities: Oats Dry Beans Mushrooms Rye Total Field Crops Mint 2 1 ,3 8 6 1 5 3 ,9 0 8 1 4 ,6 8 4 906 1,601 1 ,0 9 3 ,7 8 8 Homothetic Component 6 ,8 7 1 1 2 ,7 8 6 7 ,5 7 4 756 1 ,3 8 2 8 9 6 ,6 1 2 Expected National G row th Effect 1 ,3 4 9 2,511 1 ,4 8 7 148 271 1 7 6 ,0 4 9 Differential National G rowth Effect 2 ,8 5 0 2 7 ,7 0 9 1,3 9 6 29 43 3 8 ,7 1 5 Net G row th Effect: 4 ,1 9 9 3 0 ,2 2 0 2 ,8 8 3 178 314 2 1 4 ,7 6 4 Expected Sectoral (3 ,5 4 6 ) (1 ,5 9 1 ) 5,191 (541) 1 ,0 7 9 (2 2 0 ,3 7 8 ) G row th Effect Differential Sectoral (7 ,4 9 0 ) (1 7 ,5 5 5 ) 4 ,8 7 3 (10 7) 170 2 2 ,5 1 6 M ix Effect Net Sectoral Mix (1 1 ,0 3 6 ) (1 9 ,1 4 6 ) 1 0 ,0 6 5 (648) 1 ,2 4 9 (1 9 7 ,8 6 1 ) (1 ,1 7 2 ) (5 ,8 8 4 ) (3 ,6 2 4 ) 129 (1 ,6 1 3 ) 1 3 1 ,3 9 6 (2 ,4 7 5 ) (3 ,6 4 7 ) (6 4 ,9 4 3 ) (3 ,4 0 2 ) (1 7 5 ,4 9 2 ) (7 ,0 2 6 ) 26 155 (25 5) (7 0 ,8 2 7 ) (1 ,8 6 8 ) (4 4 ,0 9 6 ) 1 9 9 0 Cash Receipts 1 0 ,9 0 2 9 4 ,1 5 5 2 0 ,6 0 6 591 1 ,2 9 6 1 ,0 6 6 ,5 9 5 Change in Cash (1 0 ,4 8 4 ) (5 9 ,7 5 3 ) 5 ,9 2 2 (315) (305) (2 7 ,1 9 3 ) Effect: Expected Competitive Effect Allocation Effect Net Competitive Effect: Receipts 257 1 9 8 0 Cash Receipts Table XI S h ift-S h are Analysis of Field C ro p s C a s h R eceipts, 1 9 7 0 - 1 9 9 0 SHIFT-SHARE ANALYSIS OF AGRICULTURAL CASH RECEIPTS, MICHIGAN VERSUS THE UNITED STATES SECTOR: FIELD CROPS, PERIOD OF EVALUATION 1970 & 1990, ($ 000's) Commodities: Corn Soybeans W heat Hay Potatoes Sugar Beets Barley 1 9 7 0 Cash Receipts 6 1 ,0 1 2 3 3 ,3 8 9 2 6 ,5 7 5 1 0 ,7 7 0 2 1 ,0 6 0 2 2 ,5 8 7 390 Homothetic Component 6 4 ,9 4 6 6 2 ,8 2 9 3 9 ,7 2 8 1 2 ,8 8 7 1 2 ,5 5 3 7 ,8 0 4 6,0 91 Expected National 1 4 5 ,6 6 3 1 4 0 ,9 1 5 8 9 ,1 0 3 2 8 ,9 0 4 2 8 ,1 5 5 1 7 ,5 0 4 1 3 ,6 6 2 Differential National G rowth Effect (8 ,8 2 3 ) (6 6 ,0 2 9 ) (2 9 ,5 0 0 ) (4 ,7 4 9 ) 1 9 ,0 8 0 3 3 ,1 5 6 (1 2 ,7 8 7 ) Net Growth Effect: 13 6,84 1 7 4 ,8 8 6 5 9 ,6 0 3 2 4 ,1 5 5 4 7 ,2 3 5 5 0 ,6 6 0 875 Expected Sectoral G row th Effect 4 9 ,0 4 8 1 2 ,1 3 3 1 ,8 2 0 2 3 ,5 7 7 5,8 21 (2 ,0 9 0 ) (3 ,6 8 7 ) Differential Sectoral (2 ,9 7 1 ) (5 ,6 8 5 ) (603) (3 ,8 7 4 ) 3 ,9 4 4 (3,95 9) 3 ,4 5 1 M ix Effect Net Sectoral Mix 4 6 ,0 7 7 6 ,4 4 8 1,2 1 7 1 9 ,7 0 3 9 ,7 6 5 (6,05 0) (23 6) Expected Competitive Effect Allocation Effect 1 0 0 ,8 4 3 2 2 8 ,2 4 2 8 ,6 3 0 3 8 ,4 5 7 (3 ,7 4 6 ) 1 4 ,9 1 7 19 ,581 (6 ,1 0 8 ) (6 ,3 1 8 ) (2 ,5 3 8 ) 2 8 ,2 5 5 (1 8 ,3 2 7 ) 9 4 ,7 3 5 (1 0 6 ,9 4 8 ) 1 2 1 ,2 9 4 (2 ,8 5 7 ) Net Competitive 5 ,7 7 3 3 2 ,1 3 8 (6 ,2 8 4 ) 4 3 ,1 7 2 1 ,2 5 4 1 9 9 0 Cash Receipts 3 3 8 ,6 6 5 2 3 6 ,0 1 7 9 3 ,1 6 8 8 6 ,7 6 7 7 1 ,7 7 7 1 1 0 ,3 6 9 2 ,2 8 2 Change in Cash 2 7 7 ,6 5 3 2 0 2 ,6 2 8 6 6 ,5 9 3 7 5 ,9 9 7 5 0 ,7 1 6 8 7 ,7 8 2 1 ,8 9 2 G rowth Effect Effect: Receipts 258 Effect: Table XI (C ontinued ) S h ift-S hare Analysis of Field Crops C a sh R eceipts, 1 9 7 0 - 1 9 9 0 SHIFT-SHARE ANALYSIS OF AGRICULTURAL CASH RECEIPTS, MICHIGAN VERSUS THE UNITED STATES SECTOR: FIELD CROPS, PERIOD OF EVALUATION 1970 & 1990, ($ 000's) Total Field Commodities: Dry Beans Oats Mushrooms Rye Mint Crops 7 ,0 6 6 5 6 ,2 3 3 n.a. 64 8 1 ,2 8 3 2 4 1 ,0 1 4 Homothetic Component 4 ,3 6 6 3 ,1 2 9 n.a. 610 54 5 2 1 5 ,4 9 0 Expected National G rowth Effect 9 ,7 9 3 7 ,0 1 8 n.a. 1,3 6 8 1 ,2 2 3 4 8 3 ,3 0 9 Differential National 6 ,0 5 5 1 1 9 ,1 0 4 n.a. 86 1 ,6 5 4 5 7 ,2 4 6 Net Growth Effect: 1 5 ,8 4 7 1 2 6 ,1 2 2 n.a. 1,4 5 4 2 ,8 7 7 5 4 0 ,5 5 5 Expected Sectoral Growth Effect (9 ,8 2 3 ) 2 ,5 6 5 n.a. (1 ,6 4 1 ) 766 7 8 ,4 8 8 Differential Sectoral M ix Effect Net Sectoral Mix (6 ,0 7 3 ) 4 3 ,5 3 9 n.a. (103) 1,0 3 5 2 8 ,7 0 0 (1 5 ,8 9 7 ) 4 6 ,1 0 4 n.a. (1 ,7 4 4 ) 1 ,8 0 0 1 0 7 ,1 8 8 2,401 (7 ,4 7 3 ) n.a. 218 (1 ,9 8 3 ) 4 0 0 ,0 8 6 1 ,4 8 4 (1 2 6 ,8 3 1 ) (1 3 4 ,3 0 5 ) n.a. 14 n.a. 23 2 (2 ,6 8 1 ) (4 ,6 6 4 ) (2 4 2 ,8 5 5 ) 3 ,8 8 5 1 9 9 0 Cash Receipts 1 0 ,9 0 2 9 4 ,1 5 5 n.a. 591 1 ,2 9 6 1 ,0 4 5 ,9 8 9 Change in Cash 3 ,8 3 6 3 7 ,9 2 2 n.a. (58) 13 8 0 4 ,9 7 5 G rowth Effect Effect: Expected Competitive Effect Allocation Effect Net Competitive 157,231 Effect: Receipts 259 1 9 7 0 Cash Receipts Table XII S hift-S hare Analysis o f Fruit & O th er C a s h R eceipts, 1 9 7 0 - 1 9 8 0 SHIFT-SHARE ANALYSIS OF AGRICULTURAL CASH RECEIPTS, MICHIGAN VERSUS THE UNITED STATES SECTOR: FRUIT & OTHER, PERIOD OF EVALUATION 1970 & 1980, ($ 000's) Straw ­ Commodities: Grapes Apples Peaches berries Cherries Plums & Prunes Total Pears Blueberries Fruit Greenhouse & Nursery 7 ,1 5 9 28 ,571 4 ,9 4 3 5 ,7 2 2 1 9 ,3 9 2 1 ,2 3 3 1 ,4 0 0 n.a. 6 8 ,4 2 1 3 0 ,4 7 9 Homothetic Component 6 ,3 9 5 6 ,0 5 8 3 ,5 7 1 2 ,2 8 3 1,3 4 3 1 ,3 6 9 1 ,4 0 2 n.a. 2 2 ,4 2 1 1 8 ,6 0 4 Expected National Growth Effect Differential National Growth Effect 1 0 ,9 4 0 1 0 ,3 6 3 6 ,1 0 8 3 ,9 0 5 2 ,2 9 8 2 ,3 4 2 2 ,3 9 8 n.a. 3 8 ,3 5 4 3 1 ,8 2 3 1 ,3 0 7 3 8 ,5 1 1 2 ,3 4 8 5 ,8 8 4 3 0 ,8 7 5 (233) (3) n.a. 7 8 ,6 8 8 2 0 ,3 1 4 Net G rowth Effect: 1 2 ,2 4 7 4 8 ,8 7 4 8 ,4 5 6 9 ,7 8 8 3 3 ,1 7 2 2 ,1 0 9 2 ,3 9 5 n.a. 1 1 7 .0 4 2 5 2 ,1 3 8 Expected Sectoral G row th Effect 7 ,7 8 8 1,7 4 3 (2 ,5 4 5 ) (766) (395) 21 (350) n.a. 5 ,4 9 5 1 5 ,3 5 4 Differential Sectoral Mix Effect Net Sectoral Mix Effect: 930 6 ,4 7 6 (97 8) (1 ,1 5 4 ) (5 ,3 1 3 ) (2) 0 n.a. (40) 9,801 8 ,7 1 8 8 ,2 1 8 (3 .5 2 4 ) (1 ,9 1 9 ) (5 ,7 0 8 ) 19 (35 0) n.a. 5 ,4 5 5 2 5 ,1 5 5 Expected Competitive Effect Allocation Effect (1 3 ,2 3 2 ) (2 ,0 6 2 ) (1 ,8 9 4 ) (2 ,0 3 2 ) 282 (354) (1 ,5 2 5 ) n.a. (2 0 ,8 1 7 ) 350 (1 ,5 8 1 ) (7 ,6 6 3 ) (72 8) n.a. (2 ,6 2 2 ) 4 ,0 6 6 (1 ,5 2 3 ) n.a. (9 ,2 1 3 ) (3 0 ,0 2 9 ) 223 (9 ,7 2 5 ) 35 (318) 2 (1 4 ,8 1 3 ) (3 ,0 6 2 ) (5 ,0 9 4 ) 3 ,7 8 4 Net Competitive 1 9 8 0 Cash Receipts 13 ,311 7 5 ,9 3 9 7 ,2 5 4 8 ,4 9 7 5 0 ,9 2 2 3 ,0 4 3 1,9 2 2 n.a. 1 6 0 ,8 8 8 1 0 8 ,3 4 5 Change in Cash 6 ,1 5 2 4 7 ,3 6 7 2,3 1 1 2 ,7 7 5 3 1 ,5 3 0 1 ,8 1 0 522 n.a. 9 2 ,4 6 7 7 7 ,8 6 6 573 Effect: Receipts 260 1 9 7 0 Cash Receipts Table XIII S h ift-S h a re Analysis of Fruit & O th e r C a s h R eceipts, 1 9 8 0 - 1 9 9 0 SHIFT-SHARE ANALYSIS OF AGRICULTURAL CASH RECEIPTS, MICHIGAN VERSUS THE UNITED STATES SECTOR: FRUIT & OTHER, PERIOD OF EVALUATION 1980 & 1990, ($ 000's) StrawCommodities: Grapes Apples Peaches berries Plums & Cherries Prunes Total Pears Blueberries Fruit Greenhouse & Nursery 1 9 8 0 Cash Receipts 13,311 7 5 ,9 3 9 7 ,2 5 4 8 ,4 9 7 5 0 ,9 2 2 3 ,0 4 3 1,9 2 2 1 9 ,7 1 2 1 8 0 ,6 0 0 1 0 8 ,3 4 5 Hom othetic 2 7 ,0 8 6 1 9 ,5 8 4 7,6 91 5 ,8 4 5 3 ,4 9 9 4 ,0 2 4 3 ,7 1 9 1 ,1 4 9 7 2 ,5 9 8 7 0 ,921 5 ,3 1 8 3 ,8 4 5 1 ,5 1 0 1,1 4 8 687 790 730 226 1 4 ,2 5 5 1 3 ,9 2 5 Differential National G row th Effect Net G rowth Effect: (2 ,7 0 5 ) 1 1 ,0 6 5 (86) 521 9,311 (193) (353) 3 ,6 4 5 2 1 ,2 0 6 7 ,3 4 8 2 ,6 1 4 1 4 ,9 1 0 1 ,4 2 4 1,6 6 8 9 ,9 9 8 59 7 37 7 3 ,8 7 0 3 5 ,4 6 1 2 1 ,2 7 3 Expected Sectoral 5 ,0 3 2 5 ,1 1 7 (1 ,0 1 8 ) 5 ,7 1 3 (159) 1 ,0 2 6 1 ,2 9 6 (23) 1 6 ,9 8 3 9 1 ,0 1 5 Differential Sectoral M ix Effect Net Sectoral Mix Effect: (2 ,5 5 9 ) 1 4 ,7 2 5 58 2,591 (2 ,1 5 8 ) (250) (626) (378) 1 1 ,4 0 4 4 8 ,0 2 7 2 ,4 7 3 1 9 ,8 4 2 (96 0) 8 ,3 0 4 (2 ,3 1 7 ) 776 670 (401) 2 8 ,3 8 7 1 3 9 ,0 4 2 Expected Competitive (1 1 ,8 5 6 ) (5 ,9 4 1 ) 1 ,3 2 9 (8 ,2 6 1 ) (786) (2 ,8 2 3 ) (3 ,1 1 5 ) 223 (3 1 ,2 3 2 ) (5 ,8 5 8 ) 6 ,0 3 0 (5 ,8 2 7 ) (1 7 ,0 9 7 ) (76) 1 ,2 5 3 (3 ,7 4 8 ) (1 2 ,0 0 9 ) (1 0 ,6 5 6 ) (1 1 ,4 4 2 ) '6 8 3 (2 ,1 3 5 ) 1 ,5 0 5 (1 ,6 1 0 ) 3 ,5 9 6 3 ,8 1 9 (1 9 ,7 5 7 ) (2 3 ,0 3 8 ) (5 0 ,9 8 9 ) (3 ,0 9 1 ) (8 ,9 4 9 ) 1 9 9 0 Cash Receipts 12,571 8 7 ,6 5 3 8 ,9 7 2 6 ,4 6 0 4 7 ,1 6 1 2 ,2 8 2 1 ,3 5 9 2 7 ,0 0 0 1 9 3 ,4 5 9 2 5 9 ,7 1 1 Change in Cash (740) 1 1 ,7 1 5 1 ,7 1 7 (2 ,0 3 6 ) (3 ,7 6 1 ) (761) (563) 7 ,2 8 8 1 2 ,8 5 9 1 5 1 ,3 6 6 Component Expected National G row th Effect Effect Allocation Effect Net Competitive Effect: Receipts 261 G row th Effect Table XIV S hift-S h a re Analysis of Fruit & O th e r C a s h R eceipts, 1 9 7 0 - 1 9 9 0 SHIFT-SHARE ANALYSIS OF AGRICULTURAL CASH RECEIPTS, MICHIGAN VERSUS THE UNITED STATES SECTOR: FRUIT & OTHER, PERIOD OF EVALUATION 1970 & 1990, ($ 000's) S traw ­ Commodities: Grapes Apples Peaches berries herries Plums & Prunes Total Pears Blueberries Fruit Greenhouse & Nursery 1 9 7 0 Cash Receipts 7 ,1 5 9 2 8 ,5 7 1 4 ,9 4 3 5 ,7 2 2 1 9 ,3 9 2 1,2 3 3 1 ,4 0 0 n.a. 6 8 ,421 3 0 ,4 7 9 Homothetic 6 ,3 9 5 6 ,0 5 8 3 ,5 7 1 2 ,2 8 3 1 ,3 4 3 1 ,3 6 9 1 ,4 0 2 n.a. 2 2 ,421 1 8 ,6 0 4 1 4 ,3 4 4 1 3 ,5 8 8 8 ,0 0 9 5 ,1 1 9 3 ,0 1 3 3,071 3 ,1 4 4 n.a. 5 0 ,2 8 7 4 1 ,7 2 5 Differential National G row th Effect 1 ,7 1 3 5 0 ,4 9 3 3 ,0 7 8 7 ,7 1 4 4 0 ,4 8 1 (3061 (4) n.a. 1 0 3 ,1 7 0 2 6 ,6 3 5 Net G rowth Effect: 1 6 ,0 5 7 6 4 ,0 8 1 1 1 ,0 8 7 1 2 ,8 3 4 4 3 ,4 9 3 2 ,7 6 5 3 ,1 4 0 n.a. 1 5 3 ,4 5 7 6 8 ,3 5 9 Expected Sectoral G row th Effect 1 3 ,9 8 4 6,8 31 (3 ,9 8 9 ) 4 ,3 8 3 (621) 977 78 3 n.a. 2 2 ,3 4 8 1 0 2 ,7 8 7 Differential Sectoral M ix Effect Net Sectoral Mix Effect: 1,6 7 0 2 5 ,3 8 5 (1 ,5 3 3 ) 6 ,6 0 4 (8 ,3 4 0 ) (97) (1) n.a. 2 3 ,6 8 8 6 5 ,6 1 3 1 5 ,6 5 5 3 2 ,2 1 5 (5 ,5 2 3 ) 1 0 ,9 8 7 (8 ,9 6 1 ) 880 782 n.a. 4 6 ,0 3 6 1 6 8 ,4 0 0 (2 3 ,4 9 4 ) (7 ,8 9 1 ) (1 ,1 1 0 ) (9 ,2 0 8 ) (468) (2 ,8 8 4 ) (3 ,9 6 7 ) n.a. (4 9 ,0 2 1 ) (4 ,5 9 5 ) (2 ,8 0 6 ) (2 6 ,3 0 0 ) (2 9 ,3 2 3 ) (3 7 ,2 1 4 ) (4 2 6 ) (1,5361 (1 3 ,8 7 5 ) (2 3 ,0 8 2 ) (6 ,2 9 5 ) (6,7631 287 (2 ,5 9 7 ) 5 (3 ,9 6 3 ) n.a. n.a. (5 2 ,4 3 4 ) (2 ,9 3 3 ) (1 0 1 ,4 5 5 ) (7 ,5 2 8 ) 1 9 9 0 Cash Receipts 12,571 8 7 ,6 5 3 8 ,9 7 2 6 ,4 6 0 4 7 ,1 6 1 2 ,2 8 2 1 ,3 5 9 n.a. 1 6 6 ,4 5 9 2 5 9 ,7 1 1 Change in Cash 5 ,4 1 2 5 9 ,0 8 2 4 ,0 2 8 738 2 7 ,7 6 9 1 ,0 4 9 (41) n.a. 9 8 ,0 3 8 2 2 9 ,2 3 2 Component Expected National G row th Effect Effect: Receipts 262 Expected Competitive Effect Allocation Effect N et Competitive Table XV S hift-S h are Analysis of V e g e ta b le s & M elons C ash R eceipts, 1 9 7 0 - 1 9 8 0 SHIFT-SHARE ANALYSIS OF AGRICULTURAL CASH RECEIPTS, MICHIGAN VERSUS THE UNITED STATES SECTOR: VEGETABLES AND MELONS, PERIOD OF EVALUATION 1970 & 1980, ($ 000's) Commodities: Tomatoes Lettuce Sw eet Corn Snap Beans Onions Carrots Cantaloupes 7.5 61 2 ,2 5 9 2 ,9 2 4 3 ,0 4 0 6,691 9 ,0 1 2 1,241 Homothetic Component 8 ,7 0 5 5 ,3 1 4 2 ,6 1 4 2 ,1 0 9 2 ,0 8 3 1 ,7 7 8 1,8 49 Expected National 1 4 ,8 9 0 9 ,0 9 0 4,471 3 ,6 0 8 3 ,5 6 3 3,041 3 ,1 6 2 (1 ,9 5 6 ) (5 ,2 2 5 ) 531 1,5 9 2 7 ,8 8 3 1 2 ,3 7 5 (1 ,0 3 9 ) 1 2 ,9 3 4 3 ,8 6 5 5 ,0 0 2 5 ,2 0 0 1 1 ,4 4 6 1 5 ,4 1 6 2 ,1 2 3 (4,2211 (2 ,6 2 6 ) (1 ,4 5 2 ) (1 ,7 5 9 ) 2 ,2 6 0 (1 ,6 1 5 ) (1,68 3) 55 5 1 ,5 1 0 (172) (777) 5 ,0 0 0 (6 ,5 7 4 ) 553 (3 ,6 6 6 ) (1 ,1 1 7 ) (1 .6 2 4 ) (2 ,5 3 6 ) 7 ,2 6 0 (8 ,1 9 0 ) (1 ,1 3 0 ) Expected Competitive 372 2 ,5 2 9 120 1,721 (3 ,0 8 5 ) (1 ,1 2 3 ) 1,429 Effect Allocation Effect G rowth Effect Differential National G rowth Effect Net Growth Effect: Expected Sectoral G row th Effect Differential Sectoral Mix Effect Net Sectoral Mix Effect: (49) (1 ,4 5 3 ) 14 323 1 ,0 7 5 134 75 9 2 ,4 8 0 (6 ,8 2 5 ) Net Competitive Effect: (9 ,9 1 1 ) (4 ,5 7 0 ) (5 ,6 9 3 ) (470) 960 19S0 Cash Receipts 1 7 ,1 5 2 6 ,0 8 3 6 ,4 3 6 8 ,1 8 4 1 5 ,4 8 7 1 0 ,5 4 6 3 ,1 9 4 Change in Cash Receipts 9,5 91 3 ,8 2 3 3 ,5 1 2 5 ,1 4 4 8 ,7 9 6 1,5 3 4 1 ,9 5 3 263 1 9 7 0 Cash Receipts Table XV (Continued) S h ift-S hare Analysis of V e g e ta b le s & Melons C ash R eceipts, 1 9 7 0 - 1 9 8 0 SHIFT-SHARE ANALYSIS OF AGRICULTURAL CASH RECEIPTS, MICHIGAN VERSUS THE UNITED STATES SECTOR: VEGETABLES AND MELONS, FERIOD OF EVALUATION 1970 & 1980, ($ 000's) Commodities: Cucumbers Celery Cabbage Asparagus Total Vegetables Cauliflower Peppers 1 9 7 0 Cash Receipts 9 ,7 3 3 5 ,0 8 0 2 ,8 4 3 4 ,3 1 2 1 ,2 2 0 597 5 6 ,5 1 5 Homothetic 1,781 1 ,7 9 0 1 ,5 6 2 1 ,2 2 9 1,1 8 5 53 7 3 2 ,5 3 4 Expected National Growth Effect 3 ,0 4 6 3,0 61 2 ,6 7 2 2 ,1 0 2 2 ,0 2 6 91 9 5 5 ,6 5 2 Differential National 1 3 ,6 0 4 5 ,6 2 9 2,191 5 ,2 7 5 61 102 4 1 ,0 2 2 G rowth Effect Net Growth Effect: 1 6 ,6 5 0 8 ,6 9 0 4 ,8 6 3 7 ,3 7 7 2 ,0 8 7 1,021 9 6 ,6 7 5 Expected Sectoral (1 ,0 9 8 ) (1 ,2 7 0 ) (1 ,0 0 9 ) 11,481) (62 3) 532 (1 6 ,0 4 5 ) Differential Sectoral (4 ,9 0 2 ) (2 ,3 3 5 ) (827) (3 ,7 1 5 ) (19) 59 (1 1 ,6 4 5 ) Mix Effect Net Sectoral Mix Effect: (6 ,0 0 0 ) (3 ,6 0 4 ) (1 ,8 3 7 ) (5 ,1 9 6 ) (641) 592 (2 7 ,6 9 0 ) Expected Competitive (60 8) 1,0 6 2 (1 ,2 5 9 ) 1,7 8 2 671 (96) 3 ,5 1 5 Effect Allocation Effect (2 ,7 1 7 ) 1 ,9 5 4 3 ,0 1 6 4 ,4 7 2 6 ,2 5 4 691 (11) (107) (9 ,9 0 8 ) (3 ,3 2 5 ) (1 ,0 3 2 ) (2 ,2 9 1 ) 20 Net Competitive 1 9 8 0 Cash Receipts 1 7 ,0 5 8 1 3 ,1 8 2 3 ,5 7 9 1 2 ,7 4 7 3 ,3 5 7 2 ,1 0 2 1 1 9 ,1 0 7 Change in Cash 7 ,3 2 5 8 ,1 0 2 736 8 ,4 3 5 2 ,1 3 7 1,5 0 5 6 2 ,5 9 2 Component (6,3931 Effect: Receipts 264 Growth Effect Table XVI S hift-S hare Analysis of V e g e ta b le s & M elon s C ash R eceipts, 1 9 8 0 - 1 9 9 0 SHIFT-SHARE ANALYSIS OF AGRICULTURAL CASH RECEIPTS, MICHIGAN VERSUS THE UNITED STATES SECTOR: VEGETABLES AND MELONS, PERIOD OF EVALUATION 1980 & 1990, ($ 000's) Commodities: Tomatoes Lettuce S w eet Corn Snap Beans Onions Cantaloupes Carrots 1 9 8 0 Cash Receipts 1 7 ,1 5 2 6 ,0 8 3 6 ,4 3 6 8 ,1 8 4 1 5 ,4 8 7 1 0 ,5 4 6 3 ,1 9 4 Homothetic 2 0 ,8 8 8 1 2 ,6 9 8 6 ,0 7 3 4 ,2 6 7 8 ,5 2 4 3 ,4 5 3 3 ,5 8 8 Expected National G rowth Effect 4,1 01 2 ,4 9 3 1 ,1 9 2 838 1 ,6 7 4 67 8 704 Differential National G row th Effect (734) (1 ,2 9 9 ) 71 769 1,3 6 7 1 ,3 9 3 (77) Net G rowth Effect: 3 ,3 6 8 1 ,1 9 4 1 ,2 6 4 1,6 0 7 3,041 2,071 62 7 Expected Sectoral 1 3 ,2 0 0 3 ,7 5 3 3 ,1 0 7 (46 1) 2 ,0 1 3 2 ,2 4 0 (641) Differential Sectoral (2 ,3 6 1 ) (1 ,9 5 5 ) 186 (42 3) 1,6 4 5 4,6 01 70 M ix Effect Net Sectoral Mix Effect: 1 0 ,8 3 9 1 ,7 9 8 3 ,2 9 3 (88 4) 3 ,6 5 8 6,841 (571) Expected Competitive (1 5 ,8 3 9 ) (9 ,9 4 0 ) 2 ,2 3 8 1,7 4 9 (278) (1 .0 5 1 ) (1 ,5 7 5 ) Effect Allocation Effect Net Competitive 2 ,8 3 3 (1 3 ,0 0 6 ) 5 ,1 7 8 (4 ,7 6 2 ) 134 2,3 71 1 ,6 0 6 (228) 3 ,3 5 5 (506) (2 ,1 5 9 ) (3 ,2 1 0 ) 173 (1 ,4 0 2 ) 1 9 9 0 Cash Receipts 1 8 ,3 5 3 4 ,3 1 3 1 3 ,3 6 4 1 2 ,2 6 3 2 1 ,6 8 0 1 6 ,2 4 7 1 ,8 4 8 Change in Cash Receipts 1,201 (1 ,7 6 9 ) 6 ,9 2 8 4 ,0 7 9 6 ,1 9 3 5,701 (1 ,3 4 6 ) Component Effect: 265 G row th Effect Table XVI (Continued) S hift-Share Analysis of V e g e ta b le s & M elons C ash R eceip ts, 1 9 8 0 - 1 9 9 0 SHIFT-SHARE ANALYSIS OF AGRICULTURAL CASH RECEIPTS, MICHIGAN VERSUS THE UNITED STATES SECTOR: VEGETABLES AND MELONS, PERIOD OF EVALUATION 1980 & 1990, ($ 000's) Commodities: Celery Cucumbers Cabbage Asparagus Total Vegetables Cauliflower Peppers 1 7 ,0 5 8 1 3 ,1 8 2 3 ,5 7 9 1 2 ,7 4 7 3 ,3 5 7 2 ,1 0 2 1 1 9 ,1 0 7 Homothetic Component 4,0 21 3,8 6 1 3 ,4 7 7 1,9 9 5 2 ,7 9 0 2 ,1 4 3 7 7 ,7 7 9 Expected National G row th Effect 790 758 68 3 39 2 54 8 421 1 5 ,272 Differential National 2 ,5 6 0 1 ,8 3 0 20 2,111 111 (8) 8 ,1 1 5 Net Growth Effect: 3 ,3 4 9 2 ,5 8 8 70 3 2 ,5 0 3 659 413 2 3 ,3 8 7 Expected Sectoral G row th Effect (01 376 (2 ,0 1 4 ) 868 1 ,4 3 6 1 ,6 6 8 2 5 ,5 4 6 Differential Sectoral Mix Effect Net Sectoral Mix (11 907 (59) 4,6 81 292 (32) 7 ,5 4 9 (1) 1,2 8 2 (2 ,0 7 3 ) 5 ,5 4 9 1 ,7 2 8 1 ,6 3 6 3 3 ,0 9 6 708 (1 ,1 3 7 ) 761 (981) 62 8 (1 ,7 3 5 ) (2 6 ,4 5 3 ) 2 ,2 9 6 3 ,0 0 4 (2 .7 4 6 ) (3 ,8 8 3 ) 22 78 4 (5 ,2 8 7 ) 128 756 34 1,9 8 4 (6 ,2 6 8 ) (1 ,7 0 1 ) (2 4 ,4 6 9 ) 1 9 9 0 Cash Receipts 2 3 ,4 1 0 1 3 ,1 7 0 2 ,9 9 2 1 4 ,5 3 2 6 ,5 0 0 2 ,4 4 9 1 5 1 ,1 2 0 Change in Cash 6 ,3 5 2 (13) (587) 1 ,7 8 4 3 ,1 4 3 347 3 2 ,0 1 3 G rowth Effect Effect: Expected Competitive Effect Allocation Effect Net Competitive Effect: Receipts 266 1 9 8 0 Cash Receipts Table XVII S h ift-S h a re Analysis of V e g e ta b le s & M elons C ash R eceipts, 1 9 7 0 - 1 9 9 0 SHIFT-SHARE ANALYSIS OF AGRICULTURAL CASH RECEIPTS, MICHIGAN VERSUS THE UNITED STATES SECTOR: VEGETABLES AND MELONS, PERIOD OF EVALUATION 1970 & 1990, ($ 000's) Commodities: Tomatoes Lettuce Sweet Corn Snap Beans Onions Cantaloupes Carrots 1 9 7 0 Cash Receipts 7,561 2 ,2 5 9 2 ,9 2 4 3 ,0 4 0 6,691 9 ,0 1 2 1,241 Homothetic 8 ,7 0 5 5 ,3 1 4 2 ,6 1 4 2 ,1 0 9 2 ,0 8 3 1 ,7 7 8 1 ,8 4 9 Expected National G rowth Effect 1 9 ,5 2 3 1 1 ,9 1 8 5 ,8 6 2 4 ,7 3 0 4 ,6 7 2 3 ,9 8 7 4 ,1 4 6 Differential National Growth Effect (2,5651 (6 ,8 5 1 ) 696 2 ,0 8 8 1 0 ,3 3 6 1 6 ,2 2 5 (1 ,3 6 2 ) Net G rowth Effect: 1 6 ,9 5 8 5 ,0 6 7 6 ,5 5 8 6 ,8 1 8 1 5 ,0 0 8 2 0 ,2 1 2 2 ,7 8 4 Expected Sectoral G row th Effect 7 ,1 9 4 339 1 ,1 4 5 (2 ,5 3 2 ) 4,5 71 145 (2 ,6 0 8 ) Differential Sectoral (945) (1 9 5 ) 136 (1 ,1 1 8 ) 1 0 ,1 1 3 591 857 6 ,2 4 9 144 1,281 (3 ,6 5 0 ) 1 4 ,6 8 4 736 (1 ,7 5 1 ) (1 4 ,2 9 3 ) (7 ,4 2 7 ) 2 ,3 2 5 4,201 (4 ,5 7 7 ) (2 ,7 0 5 ) (634) 1,8 7 8 (1 2 ,4 1 5 ) 4 ,2 6 9 (3 ,1 5 8 ) 27 6 2,601 1 ,8 5 4 6 ,0 5 5 (1 0 ,1 2 6 ) (1 4 ,7 0 3 ) (1 1 ,0 0 9 ) (1 3 ,7 1 4 ) 208 (426) 1 9 9 0 Cash Receipts 1 8 ,3 5 3 4 ,3 1 3 13 ,364 1 2 ,2 6 3 2 1 ,6 8 0 1 6 ,2 4 7 1 ,8 4 8 Change in Cash Receipts 1 0 ,7 9 2 2 ,0 5 4 1 0 ,4 4 0 9 ,2 2 3 1 4 ,9 8 9 7 ,2 3 5 607 Component Net Sectoral Mix Effect: Expected Competitive Effect Allocation Effect Net Competitive Effect: 267 M ix Effect Table XVII (Continued) S hift-Share Analysis of V e g e ta b le s & M elons C ash R eceipts, 1 9 7 0 - 1 9 9 0 SHIFT-SHARE ANALYSIS OF AGRICULTURAL CASH RECEIPTS, MICHIGAN VERSUS THE UNITED STATES SECTOR: VEGETABLES AND MELONS, PERIOD OF EVALUATION 1970 & 1990, ($ 000's) Total Commodities: Cucumbers Celery Asparagus Cabbage Cauliflower Peppers Vegetables 1 9 7 0 Cash Receipts 9 .7 3 3 5 ,0 8 0 2 ,8 4 3 4 ,3 1 2 1 ,2 2 0 597 5 6 .5 1 5 Homothetic 1,781 1 ,7 9 0 1 ,5 6 2 1 ,2 2 9 1,1 8 5 53 7 3 2 ,5 3 4 Expected National G rowth Effect 3 ,9 9 4 4 ,0 1 4 3 ,5 0 4 2 ,7 5 6 2 ,6 5 7 1 ,2 0 4 7 2 ,9 6 8 Differential National G rowth Effect 1 7 ,8 3 6 7,381 2 ,8 7 3 6 ,9 1 6 79 134 5 3 ,7 8 6 Net G rowth Effect: 2 1 ,8 3 0 1 1 ,3 9 4 6 ,3 7 6 9 ,6 7 2 2 ,7 3 6 1 ,3 3 8 1 2 6 ,7 5 3 Expected Sectoral G row th Effect (1 ,3 1 4 ) (1 .1 7 1 ) (3 ,0 7 6 ) (966) 58 7 2 ,1 8 4 4 ,5 0 0 Differential Sectoral (5 ,8 6 6 ) (2 .1 5 3 ) (2 ,5 2 2 ) (2 ,4 2 3 ) 18 243 (3 ,2 6 4 ) M ix Effect Net Sectoral Mix (7 ,1 7 9 ) (3 ,3 2 3 ) (5 ,5 9 7 ) (3 ,3 8 9 ) 60 5 2 ,4 2 7 1 ,2 3 5 (17 8) 6 (346) 1,1 2 2 1 ,8 8 3 (1 ,7 2 1 ) (2 2 ,3 4 6 ) (79 6) (9 7 4 ) 12 (284) 2 ,8 1 5 56 (630) 3 ,9 3 7 1 ,9 3 9 (191) (1 ,9 1 2 ) (1 1 ,0 3 7 ) 18 1 9 9 0 Cash Receipts 2 3 ,4 1 0 1 3 ,1 7 0 2 ,9 9 2 1 4 ,5 3 2 6 ,5 0 0 2 ,4 4 9 1 5 1 ,1 2 0 Change in Cash Receipts 1 3 ,6 7 7 8 ,0 8 9 149 1 0 ,2 1 9 5 ,2 8 0 1,8 5 3 9 4 ,6 0 6 Component Expected Competitive Effect Allocation Effect Net Competitive Effect: (3 3 ,3 8 3 ) 268 Effect: VI. THE APPLICATION OF INPUT-OUTPUT MODELING TO A S S E S S THE LINKAGES AND IMPACT OF PRODUCTION AGRICULTURE ON THE STATE OF MICHIGAN'S ECONOMY Introduction T he following c h a p t e r interprets th e r e s e a r c h findings137 of t h e 1-0 (Iinput, O-output) model, micro IMPLAN,138 pertaining to Michigan p roductio n agriculture. The IMPLAN model provides an u n d e r s t a n d in g of th e linkages an d im pac ts of M ichigan 's pro duction agriculture on t h e s t a t e ' s e c o n o m y . Th e 1-0 model also provides information regarding t h e s t a t e ' s supply an d d e m a n d relationships for g o o d s and se rvices , tr a d e flow a c c o u n t s , a n d e c o n o m ic multipliers. Economic multipliers are useful m e a s u r e m e n t s in t h e es tim at ion of e c o n o m i c im pacts in t h e s t a t e ' s e c o n o m y resulting from a c h a n g e in th e final d e m a n d of g o o d s or s e rv i c e s from a particular s e c t o r 139 (this will be des cr ibe d b e lo w in greater detail). The t ra d e flow a c c o u n t s p r o d u c e d s h o w th e supply, d e m a n d , e x p o r t an d import levels (in dollars) for e a c h of IMPLAN's 5 2 8 s e c t o r s of M ichig an's e c o n o m y . In this c h a p t e r th e es ti m a te d multipliers and tra d e a c c o u n t s ar e displayed 137 Note: each micro IMPLAN model utilizes large quantities of Michigan specific data and generates numerous econom etric results. Of particular im portance to the quality of the analysis is the use of production agriculture data th a t is based on the 1992 United States Census of Agriculture for Michigan. 138 See the "M ethods" chapter III for a more comprehensive discussion of the method of 1-0 analysis and an overview of m icro IMPLAN. 139 IM PLAN's data base consists of 528 different industrial sectors. 269 270 in a tabular format. Each table is a r ra nged by t h e major Michigan production agriculture s u b - s e c t o r s : crop, livestock, and miscellaneous, (e.g., dairy farm p r o d u c ts , fruits, and feed grains) plus a g g r e g a t e d nonagricultural s e c t o r s s u c h a s m anufacturi ng, trade , an d services . The inclusion of th e nonagricultural s u b s e c t o r s in t h e 1-0 analysis provides a b e n c h m a r k to c o m p a r e Michigan pro du ction agriculture ag a in s t th e o th e r s e c t o r s of th e economy. In order to a s s i s t the re ad er with th e interpretation of th e multiplier and t r a d e a c c o u n t results, key t e r m s and definitions are p r e s e n t e d . It is s u g g e s t e d t h a t th e re ader review the definitions for th e different 1-0 variables befo re p r o c e e d i n g . 140 For p u r p o s e s of this s tu d y thre e different multiplier classifications w e r e ca lculated, th e y ar e a s follows: (1) e m ploym ent, (2) o u tput, and (3) total incom e. Each multiplier classification is further s e p a r a t e d into t w o different " T y p es ," of impac ts. The different multiplier im pacts are d e s i g n a te d as a "Type I" or a "Type III" coefficient. The f o u ndations of th e multipliers are th e e c o n o m ic i m pacts k n o w n a s the direct effect, indirect ef fect an d induced ef fe ct . Th e "Type I" multiplier is a compos itio n of t h e direct, an d indirect e f f e c t s and t h e "Type III" multiplier is d es cr ibe d in t e r m s of th e direct, indirect, and induced e f fects . The following is a list of th e definitions of t h e 140 Note: IMPLAN calculates a Type III m ultiplier instead of the typical Type II found in m ost other 1-0 models, this is discussed in the methods Chapter III. 271 th r e e different effects: Direct Effect: Is a c h a n g e in production a s so c ia te d with th e immediate ef fect of a c h a n g e in final d e m a n d for a good or service. Indirect Effect: Is th e c h a n g e in production in backward-linked industries (sectors) c a u s e d by a c h a n g e in input needs of th e directly effe cted industry. In duce d Effect: Is th e c h a n g e in regional hou seho ld s p en d in g p a t te r n s c a u s e d by c h a n g e s in hou seh old income, g e n e r a te d from t h e direct and indirect ef fects. Total Effect: The total effect is the combination of both th e indirect and induced ef fe cts. An ex a m p le will help clarify th e p r o c e s s of h o w a c h a n g e in th e final d e m a n d for a good or service in a specific sector, influences th e rest of the economy. For ex ample, a s s u m e th at th ere is a significant i n c r e a s e 141 in th e d e m a n d (consumption) for low fat fluid milk in Michigan, and f o c u s on th e dairy p r o d u c e r a s th e pivotal link in t h e econo m y. The initial r e s p o n s e in th e e c o n o m y would be a direct effect by th e produ cer (farmer) to increase o u t p u t (more fluid milk) to m e e t th e rise in d e m a n d . In th e long-run the p r o d u c e r will d e m a n d more production inputs (livestock, labor, fe ed , capital, etc.), c aus in g an inc re as e in o u t p u t from all the back ward- linked industries t h a t supply th e farmer their inputs, this is called t h e indirect effect. The last s t a g e of t h e r e s p o n s e to an increase in final d em and is called t h e induced 141 Note: a reduction (instead of an increase) in final demand can also be used to model negative economic im pacts, for example, a m anufacturing plant closing and the repercussions (loss of jobs, income, etc.). 272 effect. The indu ced ef fect c a p t u r e s th e c h a n g e s in income an d e m p lo y m e n t p a t t e r n s b e y o n d th e farm level a s t r a n s a c tio n s an d s p e n d in g sp read t h r o u g h o u t th e e c o n o m y at large. Employmen t, Out put, and Per sonal Income Multipliers Explained Em ploym en t Multipliers Th e Type I an d Type III e m p lo y m en t multipliers142 ar e e s t i m a t e s of th e direct, indirect, an d induced effe ct s on a reg ion's e m p l o y m e n t given an in c r e a se or d e c r e a s e in d e m a n d for a good or service in th e local e c o n o m y . 1-0 e m p l o y m e n t multiplier calculations are a valuable statistical results th at s h o w th e forward an d b a c k w a r d impact of th e n u m b e r of jobs c r e a te d (or re duced ) b e y o n d a cor e e m p l o y m e n t c h a n g e in th e regio n's e c o n o m y . The e m p l o y m e n t multiplier is of te n th e m o s t d i s c u s s e d multiplier in th e inputo u t p u t literature, policy d e b a te s , and s trateg ic planning a n a ly s e s b e c a u s e of t h e critical topic of "jobs." Many a n a ly s ts and politicians s e e k a n s w e r s to s u c h q u e s ti o n s as, " h o w man y jobs will be c r eated in a local e c o n o m y if a n e w p r o c e ss in g plant (e.g., a s o y b e a n milling facility) is a t t r a c t e d to th e a r e a ? " T he s u c c e s s or failure of attra cting t h e plant to th e region will often hinge on th e " b o t to m line" estim ation of th e n u m b e r of n e w jobs t h a t might be g e n e r a t e d . Positive e m p lo y m e n t esti m ations c a n also lead to tax 142 Note: M icro IMPLAN uses the measure of full tim e equivalent units or w h a t's known as FTE's for all employment calculations. 273 a b a t e m e n t s for corpora tions, reelection for politicians, an d an increase in c o n s u m e r c o n f id e n c e in t h e local e c o n o m y . Example: Th e Type I e m p lo y m e n t multiplier for Michigan' s dairy farm s e c t o r is 1.3 4 , meaning t h a t for e a c h job c r e a t e d directly by the s e c to r , 0 . 3 4 jobs are c r e a t e d 143 indirectly, in th e b a c k w a r d linked s e c t o r s , s e e Table XVII. Th e Type III em p lo y m e n t multiplier of 2 . 2 5 for th e dairy industry is larger t h a n t h e Type I multiplier. The Type III multiplier is larger b e c a u s e it c a p t u r e s both th e indirect and induced ef fe cts, or w h a t is called th e total ef fect. Th e total ef fe ct for dairy is th e combinatio n of the indirect effect coefficient 0 . 3 4 plus th e induced effect coefficient of 0 . 9 0 , or 1.2 5 , s e e Table XVIII. Th e Type III multiplier s h o w s t h a t for e a c h n e w job c r e a te d in t h e dairy s e c t o r, t h er e will be 1.25 n e w jobs g e n e r a t e d in the e c o n o m y at large. O u t p u t Multipliers T he T y p e I o u t p u t multiplier r e p r e s e n t s th e value of production (from the indirect an d direct effects) required from all s e c t o r s in t h e e c o n o m y by a particular s e c t o r to deliver o n e dollar's w or th of o u tput. Th e T ype III o u t p u t multiplier a d d s th e induced effect. It is important to k n o w t h a t th e relative size of t h e o u t p u t multiplier is not a m e a s u r e of the i m p o rtan ce of a given 143 Note: the m ultiplier can be used to address either the creation of jobs or the negative im pacts of a decline in final demand and the reduction of jobs. 274 industry in th e e c o n o m y . Th e o u t p u t multiplier is an estim ation of w h a t h a p p e n s if a specific i n d u str y 's sale s to final d e m a n d is increase d or d e c r e a s e d . One of t h e useful pr op erties of an o u t p u t multiplier is th e identification of a s e c t o r ' s interdependence with t h e rest of t h e e c o n o m y . T he larger (smaller) t h e calcu lated multiplier for a s ecto r, t h e g r e a te r (lesser) is t h e i n te r d e p e n d e n c y or linkage a s ecto r. Example: T he calcu lated T yp e I o u tp u t multiplier for M ich ig an's dairy farm p r o d u c t s s e c t o r is 1 .2 9 , s e e Table XIX. This m e a n s t h a t for e a c h dollar of in creased o u t p u t p r o d u c e d by th e s e c t o r (to m e e t an increase in final d e m a n d ) , 0 . 2 9 dollars w o r th of indirect o u tp u t (backward-linked s ectors ) is g e n e r a t e d in ot her Michigan industries, s e e Table XX.144 The multiplier c a n also be us ed to a n s w e r th e que stion, " w h a t if final d e m a n d dr o p s by o n e dollar in t h e dairy s ecto r, w h a t is t h e indirect ef fect?" Th e a n s w e r is an e c o n o m ic impac t with an indirect ef fe ct t h a t c a u s e s a decline of o u t p u t of 0 . 2 9 dollars in t h e back ward -linked s e c to rs . T h e calcu lated T ype III dairy multiplier is 1 . 8 4 , s e e Table XIX. From the definition a b o v e r e m e m b e r t h a t th e Type III multiplier builds on t h e Type I multiplier. Th e T yp e III c a p t u r e s both th e direct and indirect e f f e c ts the s a m e a s th e T ype I multiplier, b u t it also includes t h e induced ef fe ct . To c a p t u r e th e induced ef fe ct , t h e Type III multiplier of 1 . 8 4 is s u b tr a c t e d by 144 Note: All of the indirect e ffe cts are easily determined by subtracting 1.00 from the Type I m ultiplier, in this example, 1.29- 1.00 yields the indirect e ffe c t of 0 .2 9 . 275 t h e T ype I multiplier of 1 . 2 9 , and equals th e induced effe ct of 0 . 5 4 , s e e Table XX. T he induced o u t p u t ef fect of 0 . 5 4 dollars o c c u r s for ev ery dollar of o u t p u t p r o d u c e d by th e dairy farm s e c to r. To ca lculate t h e total o u t p u t e f f e c t of th e incr ea se in final d e m a n d , th e Type I multiplier of 1 . 0 0 is s u b tr a c t e d from t h e T ype III multiplier of 1.84 , yielding 0 . 8 4 dollars, s e e Table XX. Th e total effe ct of 0 . 8 4 is th e com binat ion of th e indirect ef fe c t 0 . 2 9 plus t h e induced ef fe c t of 0 . 5 4 . 145 Total Income Multipliers Th e T ype I total income multiplier is th e direct an d indirect em p lo y e e c o m p e n s a t io n , proprietary inco m e and o th e r income divided by t h e direct e m p l o y e e c o m p e n s a t io n , proprietary inco me and o t h e r in co m e t h a t is g e n e r a t e d by t h e c h a n g e in o n e dollar of final o u t p u t for a specific s ecto r. "Employee c o m p e n s a t io n " is defined as th e w a g e s an d salaries paid to e m p l o y e e s by industries plus th e value of benefits, an d th e contrib utions to social s ec urity and pension fu n d s by th e e m p lo y e e an d employer. "Proprietary in com e" is t h e income from self e m p lo y m e n t, w hich is th e major s o u r c e of farm en ter pri se inco m e in Michigan. "Other incom e" includes c o r p o r a te income, rental income, interest, and c o r p o r a te t ra n s f e r p a y m e n t s . The T y p e III multiplier a d d s to the Type I multiplier t h e ind uc ed effect. The 146 Note: the indirect and induced effects do not equal the total e ffe ct. This is because of rounding the calculated m ultipliers from the four digit level to the tw o digit level. 276 a d v a n t a g e of th e total inco me multiplier (versus a perso na l income multiplier) is t h e inclusion of t h o s e individuals t h a t ar e self em plo yed. The self em p l o y e d c o m p o n e n t in this multiplier is especially importa nt to th e farming s e c t o r b e c a u s e of t h e high n u m b e r of e n te rpri s es having a self em p lo y ed tax s tr u c tu r e . Example: Continuing with Mich igan 's dairy farm s e c to r , th e calcu lated T ype I total in come multiplier is 1.63, and the Type III multiplier is 2 . 9 3 , s e e Table XXI. For e a c h dollar of direct e m p lo y ee c o m p e n s a t i o n g e n e r a t e d by o n e dollar of final o u t p u t in th e dairy s ecto r, 0 . 6 3 dollars of indirect e m p l o y m e n t c o m p e n s a tio n , and 1 . 0 0 dollar of induced em p lo y e e c o m p e n s a t io n is g e n e r a t e d . Review of 1-0 Model Results: the Multipliers Em ploym en t Multiplier R e v ie w 146 Th e a v e r a g e Type I multiplier for th e agricultural production s e c t o r 147 is 1.3 8 , s e e Table XVII. The agricultural livestock s e c t o r has a lower T ype I multiplier of 1 . 2 6 t h a n th e T ype I multiplier of 1 . 4 9 for th e cr op s e c t o r . The higher crop multiplier c o m p a r e d to th e lower livestock multiplier is c o n s i s t e n t with o th e r studies . Typically, cr op e n te r p ris e s ar e m or e labor 140 For an explanation of the em ploym ent m ultiplier definitions see the definition section above. 147 The agricultural production sector includes the livestock and crop sectors. 277 i n t e n s iv e , 148 and livestock en te r p ris e s are more capital in te n s iv e . 149 A n u m b e r of c r o p multipliers exhibited th e labor intensive properties. Th e Type I multiplier for fruit cr o p s w a s 2 . 0 4 and v e g e t a b l e s p o s te d a 2 . 2 6 , th e h i g h e s t for all prod uction agriculture. The o th e r Type I multipliers for th e p roductio n c r o p s ran ged from 1 . 0 4 to 1.59. The largest Type I multipliers in th e livestock s e c t o r w e r e for t h e hog and s w i n e s u b s e c t o r a t 1.3 8 , and th e dairy s u b s e c t o r a t 1.3 4 . C o m p a r e d to th e nonagricultural s e c t o r , 150 th e agricultural prod uction s e c t o r Type I multiplier a v e r a g e is marginally higher 1 . 3 8 v e r s u s 1 . 3 5 . Th e largest Type I nonagricultural multiplier calculated w a s 1 . 8 6 in t h e m a n ufacturi ng se cto r. The T yp e III agricultural multipliers ar e all c o m m e n s u r a t e l y higher th a n th e Type I multipliers by approximate ly 6 6 % . Th e larger Type III multiplier reflects t h e addition of th e ind uced effe ct in th e e c o n o m y . It is e s ti m a t e d th a t for e a c h job th a t is c r e a te d in th e pro duct io n agriculture s e c t o r t h a t a n o th e r 1.31 jobs would be c r e a t e d in o t h e r s e c t o r s of th e e c o n o m y , given th e Type III multiplier of 2 . 3 1 . The e s ti m a t e d T ype III multiplier a v e r a g e for th e non-agricultural e c o n o m y is slightly lower a t 2 . 2 1 , s e e Table XVII. 148 R e q u i r i n g m o r e l a b o r in p r o d u c t i o n p r o c e s s e s a n d t h e r e f o r e a h i g h e r e m p l o y m e n t m u l t i p l i e r s is e x p e c t e d . F o r e x a m p l e , c a s h c r o p s s u c h a s v e g e t a b l e s h a v e h e a v y labor n e e d s especially during h a rv e s ts . 149 N o t e : t h e l i v e s t o c k s e c t o r u s u a l l y r e q u i r e s m o r e c a p i t a l i n v e s t m e n t s s u c h a s s h e l t e r for l a y e r s , milking p a r l o r s for dairy, a n d h o g c o n f i n e m e n t s t r u c t u r e s . 150 N o t e : t h e n o n a g r i c u l t u r a l s e c t o r is t h e r e s t o f t h e s t a t e ' s e c o n o m y a g g r e g a t e d i n t o e i g h t m a j o r c a t e g o r i e s , s e e T a b l e XVII. 278 O u tp u t Multiplier R e v ie w 151 Th e T ype I o u t p u t multiplier for Michigan production agriculture w a s 1 . 2 4 , c o n s i s t e n t with th e no n agricultural a v e r a g e of 1 . 2 4 , s e e Table XIX. A Type I multiplier of 1 . 2 4 for pr oduction agriculture m e a n s t h a t a $1 million i ncr ea se in final d e m a n d for th e a v e r a g e agricultural production s u b s e c t o r would i ncrease total s t a t e o u t p u t of g o o d s and s er vice s an additional $ 0 . 2 4 million. Within pro ductio n agriculture, the livestock s e c t o r had a Type I multiplier a v e r a g e of 1.2 6 , slightly higher th a n th e crop s e c t o r Typ e I multiplier a v e r a g e of 1.2 2 . The Type I livestock production s u b s e c t o r multipliers ranged from a low of 1 . 0 9 to a high of 1.39. Th e s u b s e c t o r s of h o g s , pigs and s w in e and "o ther m e a t animals p r o d u c t s" had t h e largest T ype I multipliers with a coefficient of 1.3 9 . S heep, lambs, an d g o a t s had t h e l o w e s t livestock coefficient of 1.0 9 . The crop s e c to r Type I multiplier also r a n g e d quite widely. Crop multipliers varied from a low of 1 . 0 7 for g r e e n h o u s e an d nu rsery p r o d u c t s to a high of 1 . 3 4 for fru its.152 The g r e a t e r th a n a v e r a g e fruit s e c t o r multiplier of 1 . 3 4 highlights th e im port an ce of t h e industry in th e s t a t e from t h e backward-linked (integrated) p e r sp e c tiv e . Th e fruit s u b s e c t o r Type III multiplier of 1 . 8 2 also highlights t h e significant d e g r e e of i n t e r d e p e n d e n c e from th e induced effect, or 151 F o r a n e x p l a n a t i o n o f t h e o u t p u t m u l t i p l i e r d e f i n i t i o n s s e e t h e d e f i n i t i o n s e c t i o n above. 152 N o t e : t h e f r u i t s u b s e c t o r h a d t h e s e c o n d h i g h e s t T y p e I e m p l o y m e n t m u l t i p l i e r of 2 . 0 4 . 279 forward-linked pe rspecti ve. The calculated Type III multipliers reveal t h a t m a n y pro duct io n agriculture s u b s e c t o r s in Michigan 's e c o n o m y are very im port ant b e c a u s e of their forward-linkages. Of special n o te is th e g r e e n h o u s e an d nu rsery p r o d u c t s s u b s e c t o r . G r e e n h o u s e and nursery p r o d u c t s had t h e largest T y p e III o u t p u t multiplier of 4 . 5 7 for all agricultural pr od uct io n s u b s e c t o r s , s e e Table XIX. Michigan is a national leader in th e pr od uct io n of m any of th e com m odities pr o d u c e d in this s u b s e c t o r . The s h e e p , lambs an d g o a t s s u b s e c t o r also registered a larger t h a n a v e r a g e Type III multiplier of 3 . 7 2 . Production agriculture in general yielded higher Type III multipliers th a n th e rest of t h e e c o n o m y . Th e a v e r a g e Typ e III o u tp u t multiplier for the cr op and livestock s e c to rs of 2 . 0 6 , is 11 % higher t h a n th e non-agricultural a v e r a g e of 1.8 5 , s e e Table XIX. The large production agriculture o u t p u t multipliers signifies th e im port ance of th e in d u str y 's contribution to total e c o n o m ic activity in th e s ta te . Total Income Multiplier R e v i e w 153 Michigan production agriculture total inc om e multipliers on a v e r a g e are higher t h a n t h e non-agriculture s e c t o rs . T he a v e r a g e T y p e I total income multiplier for Michigan prod uction agriculture is 1 . 2 9 a n d th e T ype III is 2 . 2 2 , c o m p a r e d to t h e non-agricultural sectoral T y p e I a v e r a g e of 1 . 2 5 an d a Type 153 F o r a n e x p l a n a t i o n o f t h e p e r s o n a l i n c o m e m u l t i p l i e r d e f i n i t i o n s s e e t h e definition s e c tio n a b o v e . 280 III a v e r a g e of 1.8 4 . The livestock s e c t o r in general has larger total income multipliers t h a n t h e crop s e c to r. The a v e r a g e livestock Type I multiplier is 1 . 3 4 an d th e T ype III is 2 . 4 6 c o m p a r e d to th e a v e r a g e crop Type I multiplier of 1 . 2 5 and a T yp e III of 1.9 9 . Several of th e agricultural s u b s e c t o r s are c h ar acte r iz e d as having sizable total inco me multipliers, s u c h a s fruits and g r e e n h o u s e an d nurse ry p ro d u c t s . Th e Type I an d Type III total inc om e multipliers for t h e s e t w o s u b s e c t o r s are quite large b e c a u s e of th e significant n u m b e r of indirect jobs and t h e level of value a d d e d activity linked to the s t a t e ' s e c o n o m y . Th e T ype I total income multiplier for fruits is 1 . 7 0 and t h e T y p e III multiplier is 3 . 1 9 . The fruits Type I multiplier is 3 6 % gr e a te r th a n t h e non-agricultural a v e r a g e and t h e Type III is 7 3 % higher t h a n th e non-agricultural a v e r a g e . Th e g r e e n h o u s e an d nur se ry s u b s e c t o r T yp e I multiplier is 1 . 0 7 an d th e T yp e III i n cr eases notably to 3 . 2 1 . T w o other s u b s e c t o r s with large induced effe ct s are s h e e p , lambs and g o a t s with an indu ced ef fe ct of 2.01 and dairy farm p r o d u c ts at 1.30 . 281 T a b le XVII 1 9 9 2 M ic hi gan T y p e I a n d T y p e III E m p l o y m e n t Multipliers for P r o d u c t i o n A gr ic ul tu re a n d R es t of t h e E c o n o m y TYPE I a n d TYPE III EMPLOYMENT MULTIPLIERS fo r P RO D UC T I O N AGRICULTURE a n d DIFFERENT S E C T O R S ESTI MATED for MI CHIGAN, 1 9 9 2 Type I T y p e III 1.34 1.24 1.23 1.24 1.24 1.03 1.38 1.29 1. 31 1.26 2.25 2.08 2.07 2.07 2.08 1.73 2.30 2.18 Crops F o o d G r a i ns Feed Grains Hay And Pasture Grass Seeds Fruits Vegetables Sugar Crops Miscellaneous Crops Oil Beari ng C r o p s G re e n h o u se And NurseryProducts Average 1.50 1. 31 1.45 1.09 2.04 2.26 1.34 1.25 1.59 1.04 1.49 2.50 2.18 2.42 1.82 3.42 3.79 2.25 2.10 2.65 1.76 2.49 M i s c . Agr icult ur al R e l a t ed Agr icul tur al , F o r e s t r y , Fi sh er y S e r v i c e s L a n d s c a p e a n d Hor ti cult ur al S e r v i c e s Forest Products C o m m e r c i a l Fishing Average 1.27 1.48 2.74 1.02 1.63 2.14 2.50 4.58 1.72 2.74 Non -Ag ri c ul tu ra l Mining (14) C o n s t r u c t i o n (9) Manufacturing (349) T r a n s p o r t a t i o n , C o m m . , Utilities ( 14) T r a d e (9) F i na n ce , I n s u r a n c e , Real E s t a t e (7) S e r v i c e s (47) G o v e r n m e n t (9) Average 1.59 1.36 1.86 1.47 1.14 1.53 1.17 1.02 1.35 2.59 2.23 3.04 2.40 1.86 2.50 1.93 1.68 2.21 Sector L i v e st o c k Dairy Fa rm P r o d u c t s Po u l tr y A n d E g g s R a n c h Fe d Ca t t le R a n g e Fe d Ca t tl e Cattle Feedlots Sheep, Lambs And Goats H o g s , Pigs A n d S w i n e O t h e r M e a t An ima l P r o d u c t s M i s c e l l a n e o u s Li ve s to c k Average Note: t h e ( ) t h a t follow t h e nonagricultural industry h e a d in gs in t h e table a b o v e identify t h e n u m b e r of s e c t o r s in e a c h a g g r e g a t e d industry. 2.20 2.11 282 T a b le XVIII A n a ly si s o f M ic hi gan E m p l o y m e n t Multiplier E f fe c ts for P r o d u c t i o n A g ri c u lt u re a n d R e s t o f t h e E c o n o m y ANALYSI S Of E MPLOYMENT MULTIPLIER EFFECTS f o r P R OD U CT IO N AGRICULTURE a n d DIFFERENT S E C T O R S ESTI MATED f or MI CHIGAN, 1 9 9 2 Sector Indi rect Ef fe ct Induced Ef f ec t To ta l Ef fe ct Livestock Dairy F a r m P r o d u c t s P ou l tr y A n d E g g s R a n c h Fed C a t t l e R a n g e Fe d Ca t tl e Cattle Feedlots Sheep, Lambs And Goats H o g s , Pigs A n d S w i n e O th e r M e a t Animal P r o d u c ts M i s c e l l a n e o u s L i v e s to c k Average 0.34 0.24 0.23 0.24 0.24 0.03 0.38 0.29 0.31 0.26 Crops F o o d Gr a in s F e e d Gr ai ns Hay And Pasture Grass Seeds Fruits Vegetables S u g a r Crops Miscellaneous Crops Oil Bearing C r o p s G re e n h o u se And Nursery Products Average 0.50 0.31 0.45 0.09 1.04 1.26 0.34 0.25 0.59 0.04 0.49 1 . 01 0.88 0.98 0.73 1.37 1.52 0.90 0.84 1.07 0.72 1.00 1.50 1.18 1.42 0.82 2.42 2.79 1.25 1.10 1.65 0.76 1.49 M i sc . Agr i cu l tu ra l R e l a t ed Agr icult ur al , F o r e s t r y , F i sh e ry S e r v i c e s L a n d s c a p e a n d Hor ti cul tur al S e r v i c e s Forest Products C o m m e r c i a l Fishing Average 0.27 0.48 1.74 0.02 0.63 0.87 1.02 1.84 0.77 1.11 1.14 1.50 3.58 0.72 1.74 Non - Ag ri cu lt ur al Mining (14) C o n s t r u c t i o n (9) Manufacturing (349) T r a n s p o r t a t i o n , C o m m . , Utilities (14) T r a d e (9) F i na n ce , I n s u r a n c e , Real E s t a t e (7) S e r v i c e s (47) G o v e r n m e n t (9) Average 0.59 0.36 0.86 0.47 0.14 0.53 0.17 0.02 0.35 1.00 0.86 1.18 0.93 0.73 0.97 0.75 0.65 0.86 1.59 1.23 2.04 1.40 0.86 1.50 0.93 0.68 1. 21 0.90 0.84 0.84 0.83 0.84 0.71 0.93 0.89 1.25 1.08 1.07 1.07 1.08 0.73 1.30 1.18 0.88 1.20 0.85 1. 11 Note: (1) T h e ( ) t h a t follow t h e nonagricultural i ndust ry h e a d in gs in t h e t abl e a b o v e identify t h e n u m b e r of s e c t o r s in e a c h a g g r e g a t e d i ndustry. (2) N u m b e r s m a y n o t a dd correctl y b e c a u s e of rounding. 283 T a b le XIX 1 9 9 2 M ic hi ga n T y p e I a n d T y p e III O u t p u t Multipliers for P r o d u c t i o n A gric ul tu re a n d R e s t of t h e E c o n o m y TYPE I a n d TYPE III O U T P U T MULTIPLIERS f or P R OD U CT IO N AGRICULTURE a n d DIFFERENT S E C T O R S E STI MATED f or MICHIGAN, 1 9 9 2 Sector Livestock Dairy F a r m P r o d u c t s P ou l tr y A n d E g g s R a n c h Fed C a t t l e R a n g e Fed Ca t tl e Cattle Feedlots Sheep, Lambs And Goats H o g s , P i gs A n d S w i n e O t h e r M e a t Ani ma l P r o d u c t s M i s c e l l a n e o u s L i v e st o c k Average Type I T y p e III 1.29 1.18 1.30 1.23 1.29 1.09 1.39 1.39 1.20 1.26 1.84 1.75 2.10 1.77 2.00 3.72 2.03 2.38 1.52 2.12 Crops F o o d G r a in s Feed Grains Hay And Pasture Grass Seeds Fruit s Vegetables S u gar Crops Miscellaneous Crops Oil Be ar in g C r o p s G re e n h o u s e And Nursery Products Average 1.29 1.18 1.23 1.08 1.34 1.25 1.29 1.21 1.29 1.07 1.22 1.69 1.54 1.59 1.52 2.00 1.64 1.87 1.87 1.67 4.57 2.00 M i sc . Agr i cul t u r al Re l a t e d Agri cul tural, F o r e s t r y , F i sh e ry S e r v i c e s L a n d s c a p e a n d Hor ticul tur al S e r v i c e s Forest Products C o m m e r c i a l Fishing Average 1.30 1.30 1.28 1.04 1.23 3.00 3.46 1.73 2.13 2.58 Non - Ag r i cu lt ur al Mining (14) C o n s t r u c t i o n (9) Manufacturing (349) T r a n s p o r t a t i o n , C o m m . , Utilities (14) T r a d e (9) F in a n c e , I n s u r a n c e , Real E s t a t e (7) S e r v i c e s (47) G o v e r n m e n t (9) Average 1.34 1.27 1.40 1.28 1.25 1.28 1.27 1.05 1.24 1.72 1.88 1.74 1.69 2.41 1.67 2.28 2.23 1.85 Note: t h e ( ) t h a t follow t he nonagricultural i ndus try h e a d i n g s in t h e table a b o v e identify t h e n u m b e r of s e c t o r s in e a c h a g g r e g a t e d industry. 284 Ta b le XX A n a ly si s of M ic h i g an O u t p u t Multiplier E f fe c ts for P r o d u c t i o n A gr ic ul tu re a n d R e s t of t h e E c o n o m y ANALYSI S of O U T PU T MULTIPLIER EFFECTS f or PR O DU C T I ON AGRICULTURE a n d DIFFERENT S E C T O R S E STI MATED for MICHIGAN, 1 9 9 2 Sector Livestock Dairy F a rm P r o d u c t s P ou l tr y A n d E g g s R a n c h Fe d C a t t le R a n g e Fed C a ttl e Cattle Feedlots Sheep, Lambs And Goats H o g s , Pigs A n d S w i n e O t h e r M e a t An i ma l P r o d u c t s M i s c e l l a n e o u s L iv e s t o c k Average I ndi r ect Effect Induced Ef fect To t al Ef fect 0.84 0.75 0.20 0.54 0.57 0.80 0.54 0.71 2.63 0.65 0.98 0.32 0.26 0.86 1.12 Crops F o o d G r a in s Feed Grains Hay A nd Pasture Grass Seeds Fruits Vegetables Sugar Crops Miscellaneous Crops Oil Be ar in g C r o p s G re e n h o u se A nd Nursery Products Average 0.29 0.18 0.23 0.08 0.34 0.25 0.29 0.21 0.29 0.07 0.22 0.40 0.36 0.36 0.44 0.66 0.40 0.58 0.67 0.37 3.50 0.77 0.69 0.54 0.59 0.52 1.00 0.64 0.87 0.87 0.67 3.57 1.00 M i s c . Agr i c ul tu ra l R e l a t e d Agr icul tur al , F o r e st r y , F i sh e ry S e r v i c e s L a n d s c a p e a n d Hor ticul tur al S e r v i c e s Forest Products C o m m e r c i a l Fishing Average 0.30 0.30 0.28 0.04 0.23 1.70 2.16 0.44 1.09 1.35 2.00 2.46 0.73 1.13 1.58 N on- Ag ri cul t ur al Mi ning (14) C o n s t r u c t i o n (9) Manufacturing (349) T r a n s p o r t a t i o n , C o m m . , Utilities (14) T r a d e (9) F i na n ce , I n s u r a n c e , Real E s t a t e (7) S e r v i c e s (47) G o v e r n m e n t (9) Average 0.34 0.27 0.40 0.28 0.25 0.28 0.27 0.05 0.24 0.38 0.61 0.34 0.40 1.16 0.39 1.01 1.18 0.61 0.72 0.88 0.74 0.69 1. 41 0.67 1.28 1.23 0.85 0.29 0.18 0.30 0.23 0.29 0.09 0.39 0.39 1.10 0.77 1.00 2.72 1.03 1.38 0.52 Note: (1) Th e ( ) t h a t follow t h e nonagricultural i ndust ry h e a d i n g s in t h e t able ab ov e identify t h e n u m b e r of s e c t o r s in e a c h a g g r e g a t e d i ndustry. (2) N u m b e r s m ay n ot ad d cor rectl y b e c a u s e of rounding. 285 T a b l e XXI 1 9 9 2 M ic hi ga n T y p e I a n d T y p e III Tot al I n c o m e Multipliers for P r o d u c t i o n A gr ic ul tu re a n d R es t of t h e E c o n o m y TYPE I a n d TYPE III TOT AL INCOME MULTIPLIERS f o r PR O DU C T I ON AGRICULTURE a n d DIFFERENT S E C T O R S ESTI MATED f o r MICHIGAN, 1 9 9 2 Type I T y p e III 1.63 1.15 1.40 1.26 1.38 1.07 1.49 1.49 1.19 1.34 2.93 1.90 2.67 1.98 2.51 3.07 2.52 3.04 1.55 2.46 Crops Food Grains Feed Grains Hay A nd Pasture Grass Seeds Fr uit s Vegetables Sugar Crops Miscellaneous Crops Oil Be ar ing C r o p s G re e n h o u se And NurseryProducts Average 1.30 1.14 1.23 1.07 1.70 1.26 1.29 1.17 1.27 1.06 1.25 1.80 1.48 1.64 1.48 3.19 1. 71 1.98 1.77 1.69 3.21 1.99 Mis c. A gr i cu l tu ra l R e l a t e d Agr icul tur al , F o r e s t r y , Fi sh er y S e r v i c e s L a n d s c a p e a n d Ho r tic ul tur al S e r v i c e s Forest Products C o m m e r c i a l Fi shi ng Average 1.43 1.36 1 . 31 1.02 1.28 3.68 3.26 1.80 1.70 2.61 N on- Ag ri cul t u r al Mining (14) C o n s t r u c t i o n (9) Manufacturing (349) T r a n s p o r t a t i o n , C o m m . , Utilities (14) T r a d e (9) F i na n ce , I n s u r a n c e , Real E s t a t e (7) S e r v i c e s (47) G o v e r n m e n t (9) Average 1.38 1.29 1.53 1.28 1.23 1.31 1.22 1.03 1.25 1.84 1.98 2.11 1.71 2.34 1.75 2.08 1.71 1.84 Sector Livestock , Dairy F a r m P r o d u c t s Po u l t r y A n d E g g s R a n c h F e d Ca t tl e R a n g e Fe d Ca t tl e Cattle Feedlots Sheep, Lambs And Goats H o g s , Pi gs A n d S w i n e O t h e r M e a t An i ma l P r o d u c t s M i s c e l l a n e o u s L i v e s to c k Average Note: t h e ( ) t h a t follow t he nonagricultural i nd us try h e a d i n g s in t h e table a b o v e identify t h e n u m b e r of s e c t o r s in e a c h a g g r e g a t e d industry. 286 T a b le XXII A n a ly si s of M ic hig an Tot al I n c o m e Multiplier E f fe ct s for P r o d u c t i o n A gr ic ult ure a n d R es t of t h e E c o n o m y A NAL YSI S o f TOT AL INCOME MULTIPLIER EFFECTS f o r P R O D U C TI O N AGRICULTURE a n d DIFFERENT S E C T O R S ESTI MATED for MI CHIGAN. 1 9 9 2 Sector I ndi rect E ff ec t L iv e s t o c k Dairy F a rm P r o d u c t s P ou l t r y A n d E g gs R a n c h Fe d Ca t tl e R a n g e Fe d C a t t l e Cattle Feedlots Sheep, Lambs And Goats H o g s , Pigs A n d S w i n e O t h e r M e a t A ni ma l P r o d u c t s Miscellaneous Livestock Average 0.63 0.15 0.40 0.26 0.38 0.07 0.49 0.49 0.19 0.34 Crops Food Grains F e e d G r a in s Hay A nd Pasture Grass Seeds Frui ts Vegetables S u g a r Crops Miscellaneous Crops Oil Bear ing C r o p s G re e n h o u se And Nursery Products Average Induced Ef f ec t Tot al Ef fe ct 1.12 1.93 0.90 1.67 0.98 1. 51 2.07 1.52 2.04 0.55 1.46 0.30 0.14 0.23 0.07 0.70 0.26 0.29 0.17 0.27 0.06 0.25 0.50 0.34 0.41 0.42 1.49 0.46 0.68 0.60 0.42 2.15 0.75 0.80 0.48 0.64 0.48 2.19 0.71 0.98 0.77 0.69 2.21 0.99 M i sc . Agr i cu l tu ra l Re l a t ed A gr ic ul tur al , F or e st r y, F i s h e r y S e r v i c e s L a n d s c a p e a n d Ho r ti cult ur al S e r v i c e s Forest Products C o m m e r c i a l Fishing Average 0.43 0.36 0.31 0.02 0.28 2.25 1.90 0.49 0.68 1.33 2.68 2.26 0.80 0.70 1.61 Non - Ag ri cu lt ur al Mi ni ng ( 14) C o n s t r u c t i o n (9) Manufacturing (349) T r a n s p o r t a t i o n , C o m m . , Utilities (14) T r a d e (9) F i na n ce , I n s u r a n c e , Real E s t a t e (7) S e r v i c e s (47) G o v e r n m e n t (9) Average 0.38 0.29 0.53 0.28 0.23 0.31 0.22 0.03 0.25 0.46 0.69 0.58 0.43 1.10 0.44 0.86 0.69 0.58 0.84 0.98 1.11 0.71 1.34 0.75 1.08 0.71 0.84 1.30 0.72 1.28 0.72 1.13 2.01 1.03 1.55 0.37 Note: (1) The ( ) t h a t follow t h e nonagricultural i ndus try h e a d i n g s in t he t abl e a b o v e identify t h e n u m b e r of s e c t o r s in e a c h a g g r e g a t e d i ndustry. (2) N u m b e r s m a y no t add cor rectl y b e c a u s e of rounding. 287 Supply, D e m a n d , an d Trade A c c o u n t s Explained Three statistical ta b le s are included in this c h a p t e r b e c a u s e of their potential im p o rtan ce in as sis ting policy and str a te g ic planning p r o c e s s e s . IMPLAN t e r m s t h e s e descriptive ta bles a s th e "social a c c o u n t s . " Th e social a c c o u n t s are t h e result of t h e tra nsf orm ati on of regional (in this c a s e Michigan) and national d a t a s e t s into the social a c c o u n t s . The IMPLAN social a c c o u n t s feature th e following four c a te g o r i e s : (1) th e values of th e c o m m odities supplied (produced) regionally, (2) t h e value s of regional c o m m odit ie s d e m a n d e d , (3) regional (Michigan) t r a d e flow coefficients, and (4) tr a d e flow coefficients applied to gross regional c o m m o d itie s (Michigan) d e m a n d e d . 154 For p u r p o s e s of this r e se a r c h report, th e social a c c o u n ti n g information has b een re str u c tu re d to appropriately c a p t u r e an d e m p h a s iz e th e e c o n o m ic activities of Michigan production agriculture. Th e th re e res tr u ctu red statistical ta bles are th e de m a n d - si d e , supply-side, an d tra d e b a l a n c e a c c o u n t s for th e s t a t e . 155 T h e s e tables ren der a solid fo undat io n (baseline) for further r e s e a r c h and discu ssion co n c e r n in g th e flow of goo d s an d serv ices of s t a t e ' s pro du ction agriculture s ecto r. 154 N o t e : t h i s is a h i g h l y s i m p l i f i e d e x p l a n a t i o n o f t h e c a l c u l a t i o n o f t h e s o c i a l accounts. 155 N o t e : e v e n t h o u g h t h e s t a t i s t i c s a r e d i s c r e t e ( 1 9 9 2 ) , o n e y e a r is still u s e f u l b e c a u s e l it t l e i n f o r m a t i o n is a v a i l a b l e c o n c e r n i n g t r a d e p a t t e r n s f o r M i c h i g a n pro d u ctio n agriculture. 288 Preceding all of th e ta bles ar e definitions t h a t explain e a c h tables variables. The definitions also de scri be the com posi tion of th e d e m a n d , supply an d b al an ce of tr a d e eq uat ions. Supplv-Side A c c o u n t Definitions: Table VII The supply-side a c c o u n t is t h e calculation of th e net c o m m o d it y supplied by an industry s e c t o r. The net supply is calculated by adding th e value of product io n for e a c h c o m m o d it y and the nonindustrial (e.g., inventory sales) supplies of e a c h c o m m o d it y and s ubtr acting th e foreign e x p o r ts of th e c o m m o d it y . The definitions below de scr ibe e a c h column 1-6 moving from left t o right in t h e table. Column 1 Sector: the industry s e c to r nam e. Column 2 Gross C om modity Production (GCP): t h e total value of a c o m m o d i ty p r o d u c e d by an industry s e c t o r in Michigan. Column 3 S ta te , Local, an d Federal Sales (SLGS): Sales of g o o d s and se rv ic e s t h a t h a v e bee n p r o d u c e d or stockpiled by th e different g o v e r n m e n t ag e n c i e s . Column 4 Inventory Reduction (IR): Michigan g o o d s t h a t w e r e pr o d u c e d in an earlier time period (a year) and w e r e not immediately c o n s u m e d . N o w th e stor ed g o o d s are tak en o u t of inventory for direct c o n s u m p t i o n or utilized as a pr oduct iv e input. Note: a go od t h a t c o m e s o u t of inventory h a s non per ish ab le c h a r acte r is tics (an item t h a t will last longer th a n a year). For exam ple, a farmer m ay hold grain in s to r a g e for a s e a s o n hoping to receive higher prices at a latter d a t e in st ea d of selling th e grain upon immediate harvesting. 289 Column 5 Foreign Exports (FE): this is th e value of g o o d s an d serv ices t h a t are pr o d u c e d or g e n e r a t e d in Michigan and ar e s hip ped o u tsid e of th e United S tates. Column 6 Net C om mod ity Supply (NCS): Th e ne t c o m m o d i ty supplied for e a c h s e c t o r is calculated by th e following arithmetic equation: GCP + SLGS + IR - FE = NCS D em and-S ide A c c o u n t Definitions: Table VIII The d e m a n d - s i d e a c c o u n t is the calculation of gross regional (Michigan) c o m m o d i ty d e m a n d . Gr oss co m m o d ity d e m a n d is calcu lated by adding th e local d e m a n d s for locally p r oduced com m odities with th e local d e m a n d s for imported com m odities . The definitions be low descri be e a c h colu mn 1-6 moving from left to right in th e table. Column 1 Sector: th e industry s e c to r name. Column 2 Gross Michigan C o m m o d ity 150 D e m a n d (GMCD): r e p r e s e n t s M ichigan 's d e m a n d for various g o o d s and s er vice s. T h e s e g o o d s an d serv ices are either imported or p r o d u c e d in t h e s t a t e in order to m e e t d e m a n d . The arithmetic calculation of gr os s c o m m o d i ty d e m a n d is: GMCD Column 3 = TMFD + CCI A ver ag e Regional P u r c h a s e Coefficient (RPC): t h e RPC r e p r e s e n t s th e proportion of locally (in Michigan) p r o d u c e d g o o d s or s er vices (net com m od it y sup ply NCS) t h a t are used to m e e t local d e m a n d (total Michigan final d e m a n d TMFD). The RPC for e a c h c o m m o d i ty is unique to t h e s tu d y region (in this c a s e Michigan) an d is b a s e d on prediction e q u atio n in IMPLAN. 156 N o t e : t h e t e r m c o m m o d i t y d e n o t e s e i t h e r a g o o d or a s e r v i c e . 290 Column 4 Total Michigan Final De man d (TMFD): Th e value of Michigan pr o d u c e d c o m m odities p u r c h a s e d for local final u s e is calculated by multiplying th e RPC for e a c h c o m m o d ity by the c o r re s p o n d in g level of g r o s s Michigan c o m m o d it y d e m a n d . For ex am ple, co nsid e r th e Dairy farm p r o d u c ts s e c t o r in 1 9 9 2 : GMCD x RPC 456.7 = TMFD x 0.65 = 296.7 Th e equation a b o v e s h o w s t h a t 6 5 % of th e final d e m a n d for dairy p r o d u c ts in the s t a t e is m e t by g o o d s t h a t ar e pr o d u c e d in th e s ta t e , th e rest are imported. Column 5 A verage Import Propensity Coefficient (IPC): th e import prop en sity r e p r e s e n t s the portion of th e g r o s s c o m m o d i ty d e m a n d e d not p u r c h a s e d locally (Michigan), or one minus th e regional prope ns ity to c o n s u m e (1-RPC). Column 6 Competitive C om modity Imports (CCI): is t h e value of c o m m o d it y imports p u r c h a s e d for local final use . CCI is calcu lated by multiplying (1- RPC) for e a c h c o m m o d it y by th e c o r re s p o n d in g level of gross Michigan c o m m o d it y d e m a n d . For e xam ple, c o ns id e r the Dairy farm p r o d u c t s s e c t o r in 1 9 9 0 : GMCD x (1-RPC) 456.7 = CCI x (1 - 0 . 6 5 ) = 160.0 Balance of Trad e A c c o u n t Definitions: Table IX T he tra de-f lo w a c c o u n t f o c u s e s on t w o im port an t tra d e statistics: (1) the value of d o m e s t i c c o m m o d it y ex ports and (2) th e net tra d e surplus or deficit for e a c h c o m m odity. The definitions below d e s cri be e a c h colu mn 1-6 moving from left to right in th e Table. Column 1 Sector: th e industry s e c t o r nam e. 291 Column 2 Foreign Exports (FE): s e e variable definition a b o v e in th e supply-side table definitions. Column 3 Domestic "Michigan" Comm od ity Exports (DCE): d o m estic c o m m o d it y e x p o r t is t h e value of t h o s e c o m m o d itie s t h a t are pr o d u c e d in Michigan and ar e ex p o r te d ou tsid e th e s t a t e to th e rest of th e U.S. This is differentiated from th e "Foreign Exports" c a t e g o r y in th e supply-side a c c o u n t table t h a t f o c u s e s on Michigan p r o d u c e d p r o d u cts t h a t are ship ped outsi d e th e U.S. Dom es tic co m m o d ity e x p o r ts are calcu lated by s u b tr actin g t h e value of net c o m m o d i ty supplied from t h e total Michigan final d e m a n d . The arithmetic calculation of d o m estic c o m m o d ity e x p o r te d is: NCS - TMFD = DCE Column 4 Competitive Comm od ity Imports (CCI): s e e variable definition a b o v e in th e d e m a n d - s id e classification. Colum n 5 Th e Net Trade Surplus or Net T rad e Deficit (NTS or NTD): is t h e calculation t h a t a d d r e s s e s th e b alan ce of tr a d e for e a c h of t h e c o m m o d it ie s in th e s ta t e . NTS or NTD is calcu lated by s u b tr actin g t h e value of "foreign e x p o r ts" and " dom esti c co m m o d ity e x p o r t s " for e a c h c o m m o d ity from th e value of it's "co m pe titive c o m m o d i ty imports." A ne t tr a d e surplus m e a n s t h a t m or e (the $ value) of a good or service is being ex porte d from t h e s t a t e t h a n t h e value of t h e good or se rvice t h a t is com ing into t h e s ta t e . A ne t tr a d e deficit is just th e opposite as th e tra d e surplus. The tr a d e deficit m e a n s t h a t th e s t a t e is importing m or e of a good or service t h a n exporting th e good or service. The arithmetic calculation of a n e t co m m o d ity tr ade surplus, net tr a d e com m odity surplus or b alan ce is a s follows: if (FE if (FE if (FE -f DCE) + DCE) + DCE) > < = CCI t h e r e is a Net Trad e Surplus CCI th er e is a Net Trade Deficit CCI t h e r e is a b alan ce of tr ade 292 Review of 1-0 Model Results: Supply, D em an d, an d Trad e Flow A c c o u n t s Supplv-Side A c c o u n t R e v ie w 157 Th e IMPLAN model e s ti m a t e s t h a t th e total value of Michigan 's g ross c o m m o d i ty production for pro du ction agriculture (livestock an d crops) w a s $ 3 . 7 6 billion in 1 9 9 2 . This w a s approximately 0 . 9 0 % of t h e total g r o s s product io n for all g o o d s and s er vice s in th e s t a t e . 158 Th e value of product io n for all livestock s u b s e c t o r s w a s $ 9 8 5 . 7 million. Within th e livestock s ecto r, dairy farm p r o d u c ts a c c o u n t e d for 4 7 % of th e value of pro du ction, or $ 4 6 0 . 6 million, s e e Table XXIII. Hogs, pigs and s w in e w er e ne x t in t h e valu e of livestock c o m m o d it y production, with 1 5 % of th e sh are, of $ 1 4 7 . 4 million. Th e value of pro ductio n for all c r o p s w a s $ 2 . 7 7 billion. Th e g r e e n h o u s e and nu rsery p r o d u c ts s u b s e c t o r in t e r m s of value of prod uc tion w a s th e largest for all c rops at $ 6 7 4 . 8 million, or 2 4 % of th e total. Th e nex t largest cr op s u b s e c t o r s w e r e the feed grains and fruits. Both of t h e s e s u b s e c t o r s co m bin ed a c c o u n t e d for $ 8 9 8 . 6 million in value of produc tion. T he value of ex p o r t e d agricultural g o o d s to foreign m a r k e t s w a s calcu lated to be $ 4 9 2 . 3 million. The majority of the g o o d s e x p o r te d w e r e 157 N o t e : t h e s u b s e c t o r s o f c o t t o n , t o b a c c o , a n d t r e e n u t s a r e i n c l u d e d in t h e s u p p l y - s i d e a c c o u n t . T a b l e XXIII, t h o u g h t h e s t a t e d o e s n o t p r o d u c e t h e c o m m o d i t i e s . T h e t h r e e c o m m o d i t i e s will h o w e v e r , e n t e r t h e d e m a n d - s i d e a c c o u n t , T a b l e X X IV . 158 N o t e : t o t a l M i c h i g a n g r o s s c o m m o d i t y p r o d u c t i o n w a s $ 4 1 9 . 1 billion f o r all g o o d s and services. 293 from t h e crop s ecto r, $ 4 8 4 . 6 million, v e r s u s th e livestock s e c t o r of $ 7 . 7 million. Leading all agricultural s u b s e c t o r s w a s feed grain, w hich $ 1 8 2 . 3 million w o r t h of p r o d u c t w a s expo rted. The largest proportion of foreign e x p o r t s a s a p e r c e n t s h a re of gro ss co m m o d ity p r oduct w a s in t h e s u b s e c t o r of food grains. Over 5 7 % or a total $ 4 5 . 8 million of the food grain value of product io n w a s s hippe d a b road. The m iscellaneous livestock s u b s e c t o r w a s th e larg es t foreign ex p o r te r in the livestock industry, exporting $3.1 million of p r o d u c t in 1 9 9 2 . A point of significance in th e supply a c c o u n t is th e relative im p o rt a n c e of foreign ex p o r ts to production agriculture. As m e n t io n e d a b o v e pro du ctio n agriculture's s h a re of th e s t a t e ' s total value of g r o s s c o m m o d it y produ ction w a s 0 . 9 0 % . On t h e other hand, production ag r icu ltu r e's s h a r e of total Michigan foreign e x p o r ts is a lm o st double, 1 . 6 % , th e proportion of g r o s s co m m o d ity production. This highlights th e im p o rta n c e of foreign e x p o r ts to production agriculture. D em an d- S id e A c c o u n t R e v ie w 159 In 1 9 9 2 Michigan d e m a n d e d $ 4 4 0 . 1 billion w o r th of g o o d s and services, s e e tab le XXIV. As a portion of th e s t a t e total, $ 3 . 7 5 billion160 in 159 N o t e : t h e r e is s o m e r e d u n d a n c y b e t w e e n t h e d e m a n d - s i d e a n d t h e t r a d e - f l o w ta b le s . T h e d e m a n d - s id e ta b le looks a t th e regional p u r c h a s e c o e ffic ie n ts (RPC's) an d i m p o r t p r o p e n s i t y c o e f f i c i e n t s ( I P C ' s ) a s it r e l a t e s t o g r o s s M i c h i g a n c o m m o d i t y d e m a n d . T h e t r a d e - f l o w t a b l e a l s o e x a m i n e s t h e R P C ' s a n d I P C ' s b u t in t h e c o n t e x t of t h e n e t flow of c o m m o d iti e s . 160 T h i s r e p r e s e n t s 0 . 8 5 % o f t h e s t a t e t o t a l . 294 livestock an d crop p r o d u c t s w er e d e m a n d e d for final c o n s u m p t io n or to be u s e d as an input. Of t h e $ 3 . 7 5 billion agricultural com m odities d e m a n d e d 61 % of th e total value is for th e cr op s e c to r an d 3 9 % for th e livestock s e c t o r. Th e agriculture production s u b s e c t o r with th e largest value of d e m a n d w a s dairy farm p r o d u c ts at $ 5 0 0 . 6 million. The v e g e ta b le s u b s e c t o r is t h e n ex t largest for g r o s s com m odity d e m a n d e d th e and largest value for crops, with a total of $ 3 9 4 . 4 million. The considera ble c o m m o d it y d e m a n d for v e g e t a b l e s e m p h a s i z e s th e significance of th e s t a t e ' s ve g e t a b le in d u str y .161 As m entioned a b o v e th e t o b a c c o , c o tt o n , and tree nut s u b s e c t o r s ar e not p r o d u c e d in th e s ta t e , h o w e v e r , th er e is d e m a n d for the ra w com m odities . In 1 9 9 2 Michigan imported $ 1 . 0 million from the c o tto n s u b s e c t o r an d $ 1 7 1 . 3 from the tree nut s u b s e c t o r . Since Michigan imports everything for both of t h e s e com mod ities, th e a v e r a g e import propensity coefficient (IPC) is 1 . 0 0 an d t h e regional (Michigan) p u r c h a s e coefficient (RPC) is 0 . 0 0 . In s o m e s u b s e c t o r s th e coefficients are just th e op posit e, w h e r e t h e a v e r a g e import prop en sity is con sid erably smaller and th e regional p u r c h a s e is considerably larger. T h e se s u b s e c t o r s reflect t h e f a c t th a t m o st of th e local d e m a n d (gross Michigan c om m odity de m and) is m e t by local productio n (total Michigan final dem and). Three s u b s e c t o r s h a v e noticeably large agricultural pro du ction RPC's, t h e y are s u g a r cr op s, "h o g s, pigs and 161 M i c h i g a n h a s s u c h f i r m ' s a s V l a s i c a n d G e r b e r ' s t h a t r e q u i r e l a r g e q u a n t i t i e s o f v e g e t a b l e s f o r t h e i r p r o c e s s i n g a c t i v i t i e s . M i c h i g a n is a l s o a n a t i o n a l l e a d e r in t h e p r o d u c t i o n o f v e g e t a b l e c r o p s like: c u c u m b e r s , c e l e r y , c a r r o t s , c a u l i f l o w e r , s n a p b e a n s and asparagus. 295 s w in e ," an d g r e e n h o u s e an d nur sery p r o d u c ts. Each of t h e s e s u b s e c t o r s h av e RPC's t h a t are a b o v e 9 2 % or higher. The a v e r a g e RPC for all livestock w a s 5 8 . 6 % and th e IPC w a s 4 1 . 4 % , c o m p a r e d to the a v e r a g e RPC for all c r o p s of 4 6 . 9 % and an IPC of 5 3 . 1 % . Balance of T rade A c c o u n t 162 The b al an ce of tr a d e a c c o u n t a d d r e s s e s th e net flow of t h e value of g o o d s an d s erv ices a s th e y c r o s s the s t a t e line. In 1 9 9 2 Michigan p rod uction agriculture ex p o r t e d $ 1 . 4 0 billion w o r t h of c o m m o d i tie s to the res t of th e United S t a t e s (domestically). The $ 1 . 4 0 billion is app ro ximately 0 . 8 0 % of th e s t a t e ' s total g o o d s and services t h a t w e r e ex p o r te d domestically t h a t year. Th e crop s e c t o r e x p o r te d the major s h a re , 9 0 % of th e total co m m oditi es, valued at $ 1 . 3 8 billion c o m p a r e d to th e livestock s ecto r, w hich e x p o r te d $ 1 3 3 . 3 million. Over 5 7 % of t h e valu e of d o m e s tic c o m m o d ity e x p o r t s for pro du ction agriculture w e r e attributable to thre e c om m odities . Th e largest e x p o r t s w er e g r e e n h o u s e a n d nu rsery p r o d u c ts, w hich c o n s tit u t e d 2 0 . 6 % of th e value of total d o m e s tic agricultural ex ports or $ 2 8 7 . 3 million. Th e s e c o n d largest d o m e s ti c e x p o r ts w e r e feed grains with 2 0 . 2 % of th e s h are, a t $ 2 8 1 . 2 million. And th e third largest d o m e s t ic e x p o r t w a s hay and p a s tu r e with a 1 6 . 6 % s h a re valued at $ 2 3 1 . 1 million. 162 N o t e : r e f e r t o t h e d e f i n i t i o n s e c t i o n a b o v e f o r a n e x p l a n a t i o n o f t h e b a l a n c e o f tra d e calculation. 296 The 1-0 model e s ti m a te d t h at in 1 9 9 2 the s t a t e of Michigan had a total tr a d e deficit of $ 1 2 . 3 billion.163 Production agriculture h o w e v e r , had a m o d e r a t e t r a d e su rplus of $ 6 7 . 5 million. Most of Michigan's production agriculture tra d e s u rp l u s e s oc cu rred in th e cr op s u b s e c t o r s . C r o p 's trade surplu s w a s $ 5 2 5 . 1 millon c o m p a r e d a tra de deficit for livestock of $ 4 5 7 . 7 million. The largest tr ade s u rp lu s es in th e crop s e c t o r be lo ng ed to the s u b s e c t o r s of feed grains and g r e e n h o u s e and nursery p r o d u c ts of $ 3 2 9 . 2 million an d $ 2 7 7 . 8 million. The other m e a t animal p r o d u c ts s u b s e c t o r yielded th e largest tra d e surplus for livestock, at a level of $ 5 . 9 million. The hog, pigs an d s w in e s u b s e c t o r also p r o duced a small tra de surplus of $3.9 . The major crop tra d e deficits occ urre d in th e food grains an d tree nut subsectors. Food grains a $ 3 0 8 . 5 million tr ade deficit an d tree n uts p o s te d a $ 1 7 1 . 1 million tra d e deficit.164 The largest livestock tra de deficits are in th e cattle feed lots an d ra nc h fed cattle s u b s e c t o r s at levels of $ 1 1 4 . 5 million and $ 1 1 1 . 9 million respectively. 163 N o t e : a d e f i c i t o c c u r s w h e n (FE -l- D CE ) < C CI . 164 N o t e : t h e t r a d e d e f i c i t f o r t r e e n u t s is e x p e c t e d s i n c e t h e s t a t e d o e s n o t produce tree nut crops. Table X X III 1 9 9 2 Supply-Side Account for Michigan Production Agriculture and Aggregated Industries Supply-Side Account for Michigan Production Agriculture and Aggregated Industries, 1 9 9 2 , ($ M M ) Gross Commodity Production Sector Livestock Dairy Farm Products Hogs, Pigs And Swine Other M eat Animal Products 1. 2 0.0 1.4 4 5 9 .4 9 3 .8 0.0 0 .7 0 .5 93.1 0.1 0.2 1 4 4 .4 0.0 0.0 1.4 0 .7 13 .8 145.1 2.8 0.0 0.0 0 .3 2.6 1 4 7 .4 1.3 0 .3 1 4 8 .5 0.1 0.0 10.1 18.4 0.0 0.0 0.0 0.0 3.1 Total 15.3 $ 9 8 5 .7 $ 0.0 $ 3 .6 $ 7 .7 $ 9 8 1 .7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 4 .3 2 7 .6 1 4 .4 4 5 .8 18 2.3 9 .9 3 8 .9 318.1 2 6 0 .6 0.0 0.0 0.0 0.8 0.0 0.0 4 2 5 .9 0.0 0.0 0.0 8 7 .2 3 3 8 .7 0.2 0.0 0.0 0.0 0.2 3 4 3 .8 126.1 0.0 0.0 2 7 .9 3 1 5 .9 0.2 68.8 0 .3 0.0 0.0 0.0 1 2 5 .8 69.1 3 2 3 .2 0.0 0.0 4 .6 1 0 7 .9 0.0 22.6 2 1 9 .9 6 5 2 .3 $0 .3 $ 5 0 .9 $ 4 8 4 .6 $ 2 ,3 4 1 .5 Crops Cotton Food Grains Feed Grains Hay And Pasture 8 0 .3 4 7 2 .7 256.1 2.7 Grass Seeds Tobacco 0.0 Fruits Tree Nuts Vegetables Sugar Crops Miscellaneous Crops Oil Bearing Crops Greenhouse And Nursery Products Total 6 7 4 .8 $ 2 ,7 7 4 .6 0.0 2.0 297 0.0 10.1 Miscellaneous Livestock Net Commodity Supply Foreign Exports 0.0 13.8 Range Fed Cattle Cattle Feedlots Sheep, Lambs And Goats Sales Inventory Reduction 0.0 4 6 0 .6 9 5 .3 9 2 .9 Poultry And Eggs Ranch Fed Cattle State, Local, and Federal Table X X III (Continued) 1 9 9 2 Supply-Side Account for Michigan Production Agriculture and Aggregated Industries Supply-Side Account for Michigan Production Agriculture and Aggregated Industries, 1 9 9 2 . ($ M M ) Sector Gross Commodity Production c. Agricultural Related Agricultural, Forestry, Fishery 1 5 7 .9 State. Local, and Federal Sales Net Inventory Reduction Foreign Exports Commodity Supply 2 0 .6 0 .0 0 .0 17 8 .5 Services Landscape and Horticultural Services 5 2 6 .3 12 .8 0 .0 0 .0 539.1 Forest Products Commercial Fishing 1 8 6 .0 10.1 2 0 .8 0 .0 9 .7 $ 8 8 0 .3 0 .0 $ 5 4 .2 0 .0 $ 0 .0 8 .2 $ 1 7 .9 2 0 3 .3 1.9 $ 9 2 2 .8 1 ,2 0 0 .4 2 1 ,9 5 0 .4 8 0 .6 0 .0 7.1 8 9 .2 0 .0 0 .0 1 ,1 9 9 .0 2 1 ,9 5 0 .4 1 9 6 ,4 9 2 .2 3 9 .5 2 4 ,1 7 2 .8 1 ,0 5 2 .5 1 7 2 ,4 3 5 .8 2 2 ,3 7 7 .9 1,4 13.1 1 ,2 1 5 .6 3 0 9 .9 1 ,8 5 4 .6 4 0 ,7 4 4 .2 4 2 ,9 5 5 .5 6 7 ,4 2 5 .2 2 3 ,6 7 1 .5 Total i-Agricultural Construction (9) Manufacturing (349) Transportation, Comm., Utilities (14) 2 3 ,3 3 5 .3 Trade (9) Finance, Insurance, Real Estate (7) Services (47) Governm ent (9) 4 1 ,7 7 5 .9 4 4 ,1 7 0 .5 6 3 ,5 6 8 .7 2 2 ,0 6 6 .1 7 6 .8 95.1 3 8 1 .3 0 .6 4 ,1 6 6 .4 4 3 .2 $ 4 1 0 ,6 0 1 .9 $ 4 ,8 4 4 .2 $3 21 .1 $ 3 0 ,1 0 7 .7 $ 3 9 2 ,9 5 6 .5 $ 4 1 9 ,1 2 2 .8 $ 4 ,9 0 4 .7 $ 3 7 5 .7 $ 3 0 ,6 1 7 .7 $ 3 9 7 ,2 0 2 .3 Total State Total 0 .0 0 .0 0 .0 0 .0 0 .0 Note: the ( ) that follow the nonagricultural industry headings in the table above identify the number of sectors in each aggregated industry. Note: the "State Total" summation for each category above reflects a number of special adjustments by the l-O model and does not equal the sum of the individual sectoral totals. 298 Mining |14) Table X X IV 1 9 9 2 Demand-Side Account for Michigan Production Agriculture and Aggregated Industries Demand-Side Account for Michigan Production Agriculture and Aggregated Industries, 1 9 9 2 , ($ M M ) Sector Gross Michigan Commodity Average Regional Purchase Total Michigan Final Demand Coefficient Demand Average Import Propensity Coefficient Competitive Commodity Imports Livestock Dairy Farm Products Poultry And Eggs Ranch Fed Cattle Range Fed Cattle Cattle Feedlots Total Crops Cotton Food Grains Feed Grains Hay And Pasture Grass Seeds Tobacco Fruits Tree Nuts Vegetables Sugar Crops Miscellaneous Crops Oil Bearing Crops Greenhouse And Nursery Products Total 0 .6 8 8 0 .4 7 7 3 4 4 .6 0 .3 1 2 1 5 6 .0 9 3 .8 1 0 3 .0 0 .4 5 3 93.1 0 .5 2 3 0 .5 4 7 5 8 .9 2 6 0 .3 8 .2 14 4 .9 0 .2 3 3 0 .5 5 7 13 .8 145.1 0 .7 6 7 0 .4 4 3 4 5 .2 1 1 5 .3 4 .3 6 7 .5 $ 1 ,4 4 7 .0 0 .3 1 5 0 .9 3 9 0 .9 5 3 0 .2 2 7 0 .5 8 6 2 .6 1 3 6 .0 4.1 0 .6 8 5 0 .0 6 1 0 .0 4 7 15.3 $ 4 8 .4 0 .7 7 3 0 .4 1 4 1 .0 3 9 3 .2 0 .0 0 0 0 .0 9 9 0 .0 3 8 .9 171.1 1 5 8 .2 3 6 .9 0 .0 2 9 6 .6 1 7 1 .3 3 9 4 .4 0 .2 1 6 0 .1 8 6 0 .0 5 4 0 .0 0 0 0 .5 7 6 0 .0 0 0 0 .5 4 7 3 6 .9 2 9 .5 2 .0 0 .0 1 .0 0 0 0 .9 0 1 0 .7 8 4 0 .8 1 4 1 0 0 .8 41.1 0 .9 8 3 0 .8 4 1 1 7 0 .9 0 .0 2 1 5 .6 99.1 3 4 .6 1 4 0 .2 0 .6 2 3 0 .9 1 9 8 7 .3 3 6 5 .0 0 .4 6 9 $ 1 ,0 7 9 .7 3 9 7 .0 $ 2 ,3 0 1 .9 0 .9 4 6 1 .0 0 0 0 .4 2 4 1 .0 0 0 0 .4 5 3 0 .0 1 7 11 2 .3 5 .6 8 .8 0 .2 5 2 .2 $ 9 8 .6 1.0 3 5 4 .3 13 4 .2 12 8 .7 3 4 .9 0 .0 1 2 5 .7 1 7 1 .3 1 7 8 .8 0 .1 5 9 0 .3 7 7 1.8 6 .5 5 2 .9 0 .0 8 1 0 .5 3 1 32.1 $1 ,2 2 2 .1 299 Sheep, Lambs And Goats Hogs, Pigs And Swine Other M eat Animal Products Miscellaneous Livestock 5 0 0 .6 1 9 6 .8 2 0 5 .5 Table X X IV (Continued) 1 9 9 2 Demand-Side Account for Michigan Production Agriculture and Aggregated Industries Demand-Side Account for Michigan Production Agriculture and Aggregated Industries, 1 9 9 2 ($ M M ) Gross Michigan Sector Comm odity Demand Misc. Agricultural Related Average Commodity Purchase Coefficient Total Michigan Average Import Competitive Final Demand Propensity Coefficient Commodity Imports Agricultural, Forestry, Fishery 6 2 2 .1 0 .2 8 7 1 7 8 .5 0 .7 1 3 Services Landscape and Horticultural Services 5 1 0 .2 0 .6 2 0 3 1 6 .2 0 .3 8 0 19 4 .0 2 2 2 .8 1 3 4 .7 0 .0 1 9 4 .2 0 .9 8 1 2 1 8 .6 0 .0 1 4 0 .3 3 6 1.9 $ 5 0 0 .8 0 .9 8 6 0 .6 6 4 13 2 .8 $ 9 8 9 .0 0 .0 3 8 0 .8 9 7 0 .3 4 9 1 2 3 .2 2 1 ,8 1 3 .9 6 1 ,4 0 2 .4 0 .9 6 2 0 .1 0 3 3 ,0 7 8 .6 2 ,5 1 3 .8 0 .5 0 3 0 .7 1 7 0 .5 6 7 0 .4 7 4 1 5 ,6 7 3 .3 3 4 ,3 7 9 .9 2 9 ,0 1 3 .6 3 4 ,9 9 4 .0 2 3 ,2 4 3 .2 0.6 5 1 0 .4 9 7 1 1 4 ,4 5 5 .1 1 5 ,4 6 0 .4 0 .2 8 3 0 .4 3 3 0 .5 2 6 0 .1 4 5 0 .4 9 3 1 3 ,5 6 7 .7 2 2 ,1 1 2 .0 3 8 ,7 6 3 .1 3 ,9 5 1 .2 $ 2 1 4 0 6 5 .2 Forest Products Commercial Fishing Total $ 1 ,4 8 9 .8 4 4 3 .6 Non-Agricultural 3 ,2 0 1 .8 2 4 ,3 2 7 .7 Manufacturing (34 9) Transportation, Comm ., Utilities (14) Trade (9) Finance, Insurance, Real Estate (7) Services (47) Government (9) 1 7 5 ,8 5 7 .4 3 1 ,1 3 3 .6 4 7 ,9 4 7 .6 5 1 .1 2 5 .6 7 3 ,7 5 7 .2 2 7 ,1 9 4 .5 Total State Total $ 4 3 4 ,9 0 5 .8 $ 4 4 0 ,1 4 4 .5 0 .8 5 5 0 .5 0 7 $ 2 2 0 ,6 4 3 .5 $ 2 2 3 ,2 6 9 .5 $ 2 1 6 ,8 7 5 .0 Note: the ( ) that follow the nonagricultural industry headings in the table above identify the number of sectors in each aggregated industry. Note: the "State Total" summation for each category above reflects a number of special adjustments by the l-O model and does not equal the sum of the individual sectoral totals. 300 Mining (14) Construction (9) Table X X V 1 9 9 2 Balance of Trade Account for Michigan Production Agriculture and Aggregated Industries Balance of Trade Account for Michigan Production Agriculture and Aggregated Industries. 1 9 9 2 . ($M M ) Domestic Commodity Exports Foreign Sector Exports Competitive Commodity Imports Net Trade Surplus + or Deficit (-) ivestock Dairy Farm Products Poultry And Eggs 1.2 1 1 4 .8 0 .0 1 5 6 .0 (40.01 1.4 1 0 3 .0 (1 0 1 .6 ) Ranch Fed Cattle 0 .5 0 .0 1 1 2 .3 (1 1 1 .9 ) Range Fed Cattle Cattle Feedlots Sheep, Lambs And Goats Hogs, Pigs And Swine 0 .2 0 .7 4 5 .2 0 .3 0 .3 0 .0 0 .0 0 .0 12 .4 (45 .0 ) (1 1 4 .5 ) (5.4) Other M eat Animal Products 0 .0 6.1 1 1 5 .3 5 .6 8 .8 0 .2 Miscellaneous Livestock 3.1 0 .0 5 2 .2 5.9 (49 .1 ) S7.7 $ 1 3 3 .3 $ 5 9 8 .6 ($ 4 5 7 .7 ) 0 .0 0 .0 0 .0 1.0 (1.0) 4 5 .8 3 5 4 .3 (3 0 8 .5 ) 18 2.3 9.9 0 .8 2 8 1 .2 231.1 0 .0 1 3 4 .2 1 2 8 .7 3 4 .9 3 2 9 .2 11 2 .3 (34 .2 ) 0 .0 0 .0 1 2 5 .7 Total 3 .9 :rops Cotton Food Grains Feed Grains Hay And Pasture Grass Seeds Tobacco Fruits Tree Nuts Vegetables Sugar Crops Miscellaneous Crops Oil Bearing Crops Greenhouse And Nursery Products Total 0 .0 8 7 .2 0 .0 2 7 .9 0 .2 0 .0 1 6 7 .8 0.1 1 0 0 .3 2 6 .7 3 4 .6 1 7 1 .3 1 7 8 .8 1.8 6 .5 0 .0 12 9 .3 (1 7 1 .1 ) (5 0 .6 ) 2 5 .2 2 8 .0 10 7 .9 1 3 2 .6 5 2 .9 1 8 7 .6 2 2 .6 $ 4 8 4 .6 2 8 7 .3 $ 1 ,2 6 1 .7 32.1 $ 1 ,2 2 1 .1 2 7 7 .8 $ 5 2 5 .2 Table X X V (Cont.) 1 9 9 2 Balance of Trade Account for Mich. Production Agriculture and Aggregated Industries Balance of Trade Account for Michigan Production Agriculture and Aggregated Industries, 1 9 9 2 , ($ M M ) Sector Domestic Commodity Exports Foreign Exports ;c. Agricultural Related Competitive Commodity Imports Agricultural, Forestry, Fishery 0 .0 0 .0 Services Landscape and Horticultural Services 0 .0 2 2 2 .9 1 9 4 .0 2 8 .9 9.7 1 9 8 .9 8.2 $ 1 7 .9 0 .0 2 1 8 .6 1 3 2 .7 $ 4 2 1 .8 $ 9 8 9 .0 (1 2 4 .5 ) (10 .0 ) (5 4 9 .3 ) 8 9 .2 0 .0 1 ,0 7 5 .8 1 3 6 .5 2 4 ,1 7 2 .8 1 ,0 5 2 .5 1,413.1 1 ,2 1 5 .6 3 0 9 .9 1 ,8 5 4 .6 1 1 1 ,0 3 3 .5 6 ,7 0 4 .7 3 ,0 7 8 .6 2 ,5 1 3 .8 1 1 4 ,4 5 5 .1 1 5 ,4 6 0 .4 6 ,3 6 4 .2 1 3 ,9 4 1 .9 1 3 ,5 6 7 .7 2 2 ,1 1 2 .0 3 2 ,4 3 1 .1 4 2 8 .2 3 8 ,7 6 3 .1 3 ,9 5 1 .2 Total $ 3 0 ,1 0 7 .7 $ 1 7 2 ,1 1 5 .9 $ 2 1 4 ,0 6 5 .2 (1 ,6 6 8 .3 ) ($ 1 1 ,8 4 1 .6 ) State Total $ 3 0 ,6 1 7 .7 $ 1 7 3 ,9 3 2 .8 $ 2 1 6 ,8 7 5 .0 ($ 1 2 ,3 2 4 .5 ) Forest Products Commercial Fishing Total 4 4 3 .6 Net Trade Surplus + or Deficit (-) (4 4 3 .5 ) vAgricultural Trade (9) Finance, Insurance, Real Estate (7) Services (47) Government 19) (1 ,9 1 3 .6 ) (2 ,3 7 7 .2 ) 2 0 ,7 5 1 .3 17,703.3) (5 ,7 9 0 .4 ) (6 ,9 5 4 ,5 ) (6 ,0 2 2 .1 ) Note: the ( ) that follow the non-agricultural industry headings in the table above identify the number of sectors in each aggregated industry. Note: the "State Total" summation for each category above reflects a number of special adjustments by the l-O model and does not equal the sum of the individual sectoral totals. 302 Mining (14) Construction (9) Manufacturing (349) Transportation, Comm., Utilities (14) VII. MAJOR FINDINGS AND SYNTHESIS Introduction The s t a t e d intent of this diss ertation a s defined in c h a p t e r I w a s to a c c o m p lish th e following purpose: " a s s e m b l e a c o m p r e h e n s i v e collection of Michigan pr oduct io n agriculture bas eline d a t a and to apply th e statistical m e t h o d s of ordinary leas t s q u a r e s regre s sion, shift-share analysis, and in put-o utput modeling to d e te r m in e the tr e n d s , shifts, an d linkages of th e s e c to r during th e d e c a d e s of th e 7 0 ' s and 80 's. This r e s e a r c h effort is on e of th e m o s t e x te n s iv e historical re view s of Michigan pro duct io n agriculture g e n e r a te d to d a te . The s t u d y w a s d e s ig ne d to a s s i s t decis ion m ak er s in Michigan farm organizations, farm ente rpri s es, ag r i b u s in e s s e s , food p ro c e s s i n g c o m p a n ie s , g o v e r n m e n ta l ag e n c ie s , universities, env ironmental gro ups, an d input suppliers." This c h a p t e r s y n t h e s i z e s t h e major r e se a r c h findings resulting from th e application of various statistical m e t h o d s to agricultural bas eline d a t a to a c h ie v e th e s ta t e d p u r p o s e a b o v e . The findings in this c h a p t e r are not e x h a u s t i v e but rather are m e a n t to be illustrative. Th e c h a p t e r is s e g m e n t e d into five primary classifications (1) general farming, (2) field c r o p s, (3) livestock a n d p ro d u c t s , (4) fruit, and (5) v e g e ta b le s . S e lected c o m m o d it ie s h a v e b e e n identified within e a c h classification to d i s c u s s th e statistical results of t h e tre nd r e g re s sio n s , shifts-share, an d in p ut-o utput an a ly s e s . A brief o v e r v ie w of a n u m b e r of the unique c h a r a c t e r is t ic s of th e 303 304 diss erta tion is provided her e for t h o s e re aders t h a t are not interested in w a d in g t h r o u g h th e larger body of text. This s t u d y is th e first to review in s u c h g r e a t detail th e d e c a d e s of the 7 0 ' s an d 8 0 ' s , for Michigan production agriculture. Th e c o m p r e h e n s i v e natur e of th e diss ertation is char ac teriz ed by t h e n u m b e r of c o m m odities reviewed. In th e tre nd c h a p t e r IV, 38 c o m m o d it ie s are analyzed and in th e shift-share c h a p t e r V, 4 3 co mm od ities are analyze d over th e t w o - d e c a d e period. Secondly, t h e diss ertation m er g es n u m e r o u s powerful personal c o m p u t e r (PC) applications. T h e s e PC applications w e r e us ed to g e n e r a t e all figures, tables, statistical regressio ns, s p r e a d s h e e t s , input-ou tp ut analysis and word p r ocess ing a s p e c t s of the d isser tation. Thirdly, a n u m b e r of statistical m e t h o d s and models hav e bee n applied to Michigan pro ductio n agriculture d a ta for th e first time. This is t h e first k n o w n r e s e a r c h application of th e shift-share m e th o d of analysis, us ed to d e c o m p o s e t h e co mpetitive shifts and tr e n d s in Michigan production agr iculture b a s e d on c o m m o d i ty c a s h receipts. The s tu d y is also th e first to apply t h e inp ut-output model, Micro-IMPLAN, to exam ine th e e conom ic s tr u c t u r e an d linkages of produ ction agriculture with Michigan's general economy. Major Findings General Farming Trend Analysis Highlights: 305 ■ From 1 9 7 0 to 1 9 9 0 th e n u m b e r of Michigan fa rm s declined by 3 6 % , falling from 8 4 . 0 0 0 to 5 4 , 0 0 0 , an annual decline of 2 . 0 7 % . ■ Land in farms declined from a high of 1 2 . 7 million a c r e s in 1 9 7 0 to a low of 1 0 . 8 million a c r e s in 1 9 9 0 , an an nu al decline of 0 . 7 0 % . ■ Th e size of Michigan farm s e x p a n d e d from an a v e r a g e of 151 a c r e s in 1 9 7 0 to 2 0 0 a c r e s in 1 9 9 0 , up 3 2 . 5 % . Field C rops Tren d Analysis Highlights for Field C r o p s : 170 The 2 1 -year field c r o p tre nd analysis f o c u s e d on th e c a t e g o r i e s of a c r e s h a r v e s te d , value of production, quantity pro d u ced , yield, and price for th e com m odities. ■ Every field crop p o s t e d positive tre n d s for price, value of production, and yield. ■ Total field cr o p s valu e of production t re n d e d higher at an a v e r a g e an nual rate of 4 . 4 0 % . This w a s the largest c o m p u t e d a v e r a g e annual g r o w t h rate for th e four major co m m odity g r o u p s analyz ed . Field cr o p s value of produ ction e x p a n d e d from ju st be lo w $ 4 0 0 million in t h e early 7 0 ' s to a b o v e $ 1 . 5 0 billion in th e late 8 0 ' s . 170 Note: ten field crops were analyzed in the field crop trend section of chapter IV; barley, corn for grain, corn silage, dry beans, hay, oats, potatoes, soybeans, sugarbeets, and wheat. Total a c r e s h a r v e s t e d in cr ea se d gradually for the t w o d e c a d e s . A c r e a g e ro se m ore rapidly in th e 7 0 ' s th a n th e 8 0 ' s . For t h e 2 1 -year period th e s t a t e a v e r a g e d 6 . 5 4 million a c r e s of field crops. S o y b e a n s s h o w e d th e m o s t significant trend in c r e a s e s in production. S o y b e a n pr od uct io n quad ru pled , ex p a n d in g from 10 million bush els per yea r in the early 7 0 ' s to ov er 4 0 million bus hels in 1 9 9 0 . The yield (per acre) tre nd w a s also the m o s t prominent, increasing at an a v e r a g e an nual rate of 2 . 3 0 % . Althou gh t h e s ta t e d o e s not pr o d u c e large quantities of barley from a national p e r sp e c ti v e , barley w a s a fa st g r o w th crop, doubling in th e a m o u n t of a c r e s h a r v e s t e d . Acres h a r v e s t e d e x p a n d e d from the low 2 0 t h o u s a n d a c r e s ra n ge in t h e 7 0 ' s to a b o v e 4 0 t h o u s a n d a c r e s in t h e late 8 0 ' s . The s t a t e had a significant decline in the prod uction of dry b e a n s in t h e 7 0 ' s and 8 0 ' s . The nu m b er of a c r e s h a r v e s te d fell from a level of 6 0 0 , 0 0 0 a c r e s in th e 7 0 ' s to a level of 3 0 0 , 0 0 0 a c r e s in th e 8 0 ' s (an a v e r a g e annual tre nd decline of 3 . 3 8 % ) . The qu an tity of b e a n s p r o d u c e d declined c o m m e n s u r a t e l y , falling an a v e r a g e an nual rate of 1 . 9 9 % , from a ra n g e of 7 . 0 million Cw t. to 4 . 5 million Cw t. S u g a r b e e t s , an d hay s h o w e d th e g r e a t e s t incr ea se in th e value of pr odu ction. Value of pr oduction for t h e s e c r o p s g r e w at an a v e r a g e an nu al rate a b o v e 7 . 0 0 % . 307 S h i f t - S h a r e A na ly si s Highlights for Field C r o p s : 171 Shift-share analysis has specific terminology th a t is us ed to de scr ibe th e statistical results. In c h a p t e r V t h er e are t w o s e c t i o n s entitled "The S tr u c tu r e of t h e Arcelus (I), Shift-Share Model" and "An Example of Shift-Share Analysis Applied to Michigan Dry Beans" t h e reader is e n c o u r a g e d to review t h e s e s e c tio n s to facilitate a b e tte r un d e r sta n d in g of t h e results d i s c u s s e d below. The highlights are s e g m e n t e d into thre e time per iods 1 9 7 0 - 1 9 8 0 , 1 9 8 0 - 1 9 9 0 , and 1 9 7 0 - 1 9 9 0 . 1 9 7 0 - 1 9 8 0 H ighlights: ■ Total field cr op c a s h receipts re cord ed un usua l gains in th e 7 0 ' s . C a s h rec ei pt s e x p a n d e d from $241 million in 1 9 7 0 to $ 1 . 0 8 billion in 1 9 8 0 , up 3 4 8 % . T he calculated net " e x p e c t e d co m pe tit iv e effe ct " of $ 3 1 9 . 5 million m e a n s th a t Michigan field crop c a s h rec ei pts g r e w at a significantly fas ter rate th an national field cr o p c a s h receipts. ■ S o y b e a n s w e r e on e of Michigan's c rops t h a t exhibited notable receipt g r o w th , increasing from $ 3 3 million in 1 9 7 0 to $ 1 9 5 million in 1 9 8 0 , up 4 8 6 % . Nationally, s o y b e a n s w e r e c o n s id e re d a "fa st g r o w th " 171 N o t e : t w e l v e f i e ld c r o p s w e r e a n a l y z e d in s h i f t - s h a r e c h a p t e r V; b a r l e y , c o r n dry b e a n s , h ay , m int, m u s h r o o m s , o a ts , p o ta to e s , rye, s o y b e a n s , s u g a r b e e t s , an d w h e a t . A l s o n o t e t h a t m u s h r o o m s a r e i n c l u d e d in t h e f i el d c r o p a n a l y s i s , t h i s t h e w a y th a t th e c a s h receip t d a ta w a s divided by th e U .S.D .A . E c o n o m ic R e s e a r c h Service. 308 c o m m o d i t y 172 in t e r m s of c a s h receipts. G r o w th of Michigan s o y b e a n c a s h rec ei pts w a s e v e n faster t h a n t h e national s o y b e a n rate. The s t a t e w a s actually under allocated in s o y b e a n s given the negatively ca lcula ted differential g r o w t h ef fect, differential se ctora l mix ef fect, and allocation effect. ■ Michigan corn receip ts ro se significantly in th e 7 0 ' s , increasing by more t h a n s e v e n tim es , to $ 4 3 7 million. Michigan co rn rec ei pts also g r e w at a f a s t e r rate th a n national corn receipts. 1 9 8 0 - 1 9 9 0 H ig h lig h ts: ■ During th e 8 0 ' s g r o w t h in field cr op c a s h rec ei pts s lo w e d significantly. In fact, total field cr op rece ipts declined slightly from $ 1 . 0 9 billion in 1 9 8 0 to $ 1 . 0 7 billion in 1 9 9 0 . ■ Three c r o p s s h o w e d s tr o n g positive gains in their c o m petitive position nationally. Hay, s o y b e a n s , and s u g a r b e e t s all p o s t e d net co m petitive ef fe c ts (meaning th a t th e g r o w th rate of t h e rece ip ts out p a c e d th e national c o m m o d ity g r o w t h rate). Hay and s o y b e a n s h o w e v e r , had n eg ativ e allocation e f f e c ts implying t h a t th e s t a t e w a s u n d e r specialized in t h e t w o com m odities. S ugar b e e t s on t h e o th e r h a n d had a positive allocation ef fe c t highlighting t h e s t a t e ' s 172 F a s t g r o w t h m e a n i n g t h a t t h e c a s h r e c e i p t s f o r t h e s p e c i f i c c o m m o d i t y i n c r e a s e d a t a f a s t e r r a t e t h a n t o t a l c a s h r e c e i p t s f o r all n a t i o n a l c o m m o d i t i e s . 309 p r o m i n e n c e in the ir p r o d u c t i o n . ■ Dry b e a n s c o n tin u e d to s h o w s t e a d y er osion in its co mpetitive position. Actual c a s h receipts fell from $151 million in 1 9 8 0 to $ 9 4 million in 1 9 9 0 , a decline of app ro xima tely 3 8 % . 1 9 7 0 - 1 9 9 0 H ighlig hts: ■ Over t h e long-run, total field crop c a s h receipts more t h a n qu adrupled to a level of $ 1 . 0 5 billion in 1 9 9 0 . During this time period Michigan's s h a r e of national field cr op r eceipts i n creased substantially, this is indicated by th e calculated e x p e c t e d co m pe titiv e ef fect of $ 4 0 0 million. ■ Both corn and s o y b e a n s s h o w e d positive c a s h receipt a d v a n c e m e n t s for th e t w o d e c a d e s . Michigan corn receipts in crease d by more th an five times to $ 3 3 9 million in 1 9 9 0 an d s o y b e a n s in crease d by more th a n s e v e n times to $ 2 3 6 million in 1 9 9 0 . C a s h receipts for e a c h of t h e s e cr o p s g r e w substantially fa st er th a n th e r esp ectiv e national c o m m o d i ty rate. ■ Hay w a s o n e of th e bigge st gainers from a p e r c e n t g r o w th p er sp ecti v e. Actual c a s h receipts incr ea se d fn m $ 1 0 . 7 million in 1 9 7 0 to $ 8 6 . 8 million in 1 9 9 0 , up 7 1 1 % . Michigan hay receipts e x p a n d e d at a m u c h fas te r rate th a n th e national rate, th e calculated e x p e c t e d c o m petitive ef fe ct w a s a highly positive $ 3 8 . 5 million. 310 I n p u t - O u t p u t A na ly si s Highlights for Field C r o p s : 173 ■ Field crop employment multipliers (both Type I an d T ype III) w e r e both c o m p a r a b le to the s t a t e non-agricultural a v e r a g e s . The Type I field cr op multiplier w a s 1 . 3 2 and t h e Type III field cr op multiplier w a s 2.21 c o m p a r e d to th e s t a t e non-agricultural a v e r a g e s of 1.3 5 and 2 . 2 1 . ■ The T yp e I output multiplier for field cr o p s w a s slightly lower th an the s t a t e non-agricultural a v e r a g e and th e crop Type III multiplier w a s slightly larger th a n th e s ta t e non-agricultural a v e r a g e . ■ In 1 9 9 2 Mich igan 's field crop e x p o r t s (both d o m e s t i c and foreign) totaled $ 1 . 7 5 billion. L iv esto ck a n d Poultry Tren d Analysis Highlights for Livestock and Poultry:174 The 2 1 -year livestock an d poultry tre nd analysis f o c u s e d on the ca te g o r ie s of qu an tity pro d u ced , n u m b e r of head, valu e of production, yield, and price for th e r esp ecti v e com m odities . 173 N o t e : s e v e n f i el d c r o p t y p e c a t e g o r i e s w e r e a n a l y z e d in t h e i n p u t - o u t p u t c h a p t e r VI; f o o d g r a i n s , f e e d g r a i n s , g r a s s s e e d , h a y a n d p a s t u r e , s u g a r c r o p s , oil b e a rin g c r o p s , a n d m i s c e l l a n e o u s c r o p s . T h e s h if t- s h a r e a n a ly s is w a s c o n d u c t e d for th re e tim e periods, 1 9 7 0 to 1 9 8 0 , 1 9 8 0 to 1 9 9 0 , a n d 1 9 7 0 to 1 9 9 0 . 174 N o t e : n i n e c o m m o d i t i e s w e r e a n a l y z e d in t h e l i v e s t o c k a n d p o u l t r y t r e n d s e c t i o n o f c h a p t e r IV; b e e f , b r o i l e r s , c a t t l e - c a l v e s , c h i c k e n s , d a i r y , h o g s - p i g s , l a y e r hen s, sh e e p -la m b s, a n d turkeys. Only th re e of th e nine livestock c o m m odities had positive tr e n d s for t h e n u m b e r of hea d (or birds) for th e t w o d e c a d e s . The thre e c o m m odities with positive tre n d s w e r e tu rk eys, ho gs-p igs and broilers. All livestock c o m m odit ie s had positive t r e n d s for their value of pr oduction, ( ex cep t for chick en s, which declined at an a v e r a g e annual rate of 1 . 0 8 % ) . As c o m m o d it y group, livestock value of pr oduction in crease d a t an a v e r a g e annual rate of 3 . 7 2 % (3rd a m o n g th e major c o m m o d i ty gr o u p s analyzed). The f a s t e s t value of produc tion g r ow th tre nd w a s tu rk e y s increasing at an exceptionally fa st annual rate of 12.57% . Tu rke ys w e r e th e fast g r ow th c o m m o d i ty in th e livestock s ecto r. The n u m b e r of birds e x p a n d e d by an a v e r a g e an nu al rate of 9 . 4 3 % , rising from approxim ate ly 1. 0 million birds in th e early 7 0 ' s to 4 . 3 million in 1 9 9 0 . Total pro du ction in millions of p o u n d s quintupled from th e low 2 0 ' s (20 million p ounds) to a b o v e 1 2 0 (million po und s). Hogs and pigs also s h o w e d positive t r e n d s for all ca t e g o r ie s analyzed. For all com m odities, hogs an d pigs ranked 2nd (behind turkeys) in th e a v e r a g e annual in c r e a s e s (see Table II in c h a p t e r IV) in t h e n u m b e r of head, quantity pr o d u ced , an d value of pr oduction. For t h e t w o d e c a d e s , s t a t e production has doub led from appr ox im ately 2 4 0 million p o u n d s per year to 4 8 0 million p o u n d s per year. 312 ■ The n u m b e r of dairy c o w s in t h e s t a t e declined a lm o st ev ery year from 1 9 7 0 to 1 9 9 0 , falling from 4 3 3 , 0 0 0 hea d to 3 4 4 , 0 0 0 head . Despite th e decline in the nu m ber of c o w s , pro duction has actually tr e n d e d higher b e c a u s e of higher yields per c o w . Milk per c o w yield rose at an a v e r a g e annual rate of 1 . 9 7 % , increasing from 1 0 , 5 0 0 p o u n d s to a b o v e 1 5 , 0 0 0 p o u n d s per c o w in 1 9 9 0 , up over 4 2 % . ■ There w e r e significant declines in s h e e p an d lamb n u m b e r s for the t w o d e c a d e s . The largest declines occu r re d in th e 1 9 7 0 ' s and m o d e r a te d in th e 8 0 ' s . In total, th e s t a t e has had red uction of 55 to 6 0 % of s h e e p and lamb n u m b e r s over th e 2 1 -year period. Shift-Share Analysis Highlights for Livestock and Poultry:17b Th e highlights are s e g m e n t e d into th re e time periods 1 9 7 0 - 1 9 8 0 , 1 9 8 0 - 1 9 9 0 , and 1 9 7 0 - 1 9 9 0 . 1 9 7 0 - 1 9 8 0 H ighlig hts: ■ At t h e national level livestock and p r oducts , w e r e c o n s id e re d to be a s lo w g r o w t h s e c t o r relative to the c h a n g e in total c o m m o d ity c a s h receipts. 175 N o t e : n i n e l i v e s t o c k a n d p r o d u c t s c o m m o d i t i e s w e r e a n a l y z e d in s h i f t - s h a r e c h a p t e r V; b r o i l e r s , c a t t l e - c a l v e s , c h i c k e n s , d a i r y , e g g s , h o g s , h o n e y , s h e e p - l a m b s , and turkeys. From 1 9 7 0 to 1 9 9 0 total Michigan livestock an d p r o d u c t s c a s h re ce ipts in crease d from $ 4 8 4 . 9 million to $1.1 billion, up 1 2 7 % . Of t h e nine c o m m o d it ie s analyzed only t w o c o m m o d it ie s (turkeys and hogs) p o s te d positive n et co mpetitive e f f e c ts (by gro win g a t a fa ste r rate t h a n their national c o u n ter p art) . Tu rk ey s an d h o g s h o w e v e r , had n eg ativ e allocation ef fe c ts . Th e negative allocation ef fe c ts m e a n t h a t t h e s t a t e w a s und er specialized in both c o m m o d it ie s relative to th e U.S. From a compe titive position nationally Michigan dairy fell slightly behind, given th e nega tive n e t co mpetitive e f f e c t of $ 2 4 . 4 million. H o wev er , at t h e national level dairy w a s a s lo w g r o w th s e c t o r w h e r e dairy receipts lagged total co m m o d it y receipts. 1 9 8 0 - 1 9 9 0 H ighlig hts: From 1 9 8 0 to 1 9 9 0 total livestock and livestock p r o d u c t s c a s h rece ip ts incre ased from $1.1 billion to $ 1 . 3 billion. The hom o th e t ic c o m p o n e n t of $ 1 . 5 billion in 1 9 8 0 s h o w s th a t if th e s t a t e w e r e to m a t c h th e national s tr u c t u r e Michigan livestock rec ei pts should be 3 6 % higher. T he dairy p r oduct s e c t o r c ontinued to lose its c o m peti ti ve s h a r e in t h e 8 0 ' s . The e x p e c t e d co mpe titive effect w a s n eg ativ e $ 3 1 . 9 million an d th e allocation ef fe ct w a s neg ative $ 2 4 . 9 million. 314 ■ Turkey s an d h o g s again m a d e significant gains in rec ei pts in th e 8 0 ' s . Turkey rece ip ts increase d from $ 1 5 . 7 million in 1 9 8 0 to $ 4 7 . 7 million in 1 9 9 0 , up 2 0 4 % . The e x p e c t e d com pe titive e f f e c t for t u rk e y s w a s $ 3 1 . 7 million. Hog rece ipts incr ea se d from $ 1 2 9 . 7 million in 1 9 8 0 to $ 2 2 1 . 3 million in 1 9 9 0 , up 7 1 % . The e x p e c t e d c o m petitive ef fe c t for h o g s w a s $ 1 1 0 . 6 million. 1 9 7 0 - 1 9 9 0 H ig h lig h ts : ■ From 1 9 7 0 to 1 9 9 0 Michigan livestock rece ipts in creased from $ 4 8 4 . 9 million to $ 1 . 3 billion. The rece ipts lagged slightly behind the nation in th e rate of g r o w th . The total n e t c o m petit iv e ef fe c t w a s a n eg ativ e $ 1 1 3 . 4 million for Michigan. Nationally th e livestock s e c to r w a s a s lo w g r o w t h s e c t o r . The s ta t e w a s actually u n d e r specialized in this s e c t o r t h a t w a s a d v a n t a g e o u s . ■ Of t h e nine c o m m o d ities analyzed only three: ho ney , t u rk e y s and h ogs o u tp e r fo r m e d their re sp ective national c o m m o d i ty g r o w th rate an d ha d a positive n et co mpetitive effect. ■ T w o c o m m o d itie s p o s te d large ne gati ve net co m petitive e f fects , dairy p r o d u c t s and cattle an d calves. Dairy had th e larg est n eg ativ e net com pet itive ef fect for all livestock com m odities, of $ 8 5 . 3 million. Cattle and calves neg ative net co mpetitive ef fe c t w a s $ 6 0 . 4 million. 315 I n p u t - O u t p u t A na ly si s Highlights for L iv es to c k a n d P o u l t r y : 176 ■ Th e a v e r a g e employment multiplier (both Type I an d Type III) for the livestock s e c t o r w a s slightly lower t h a n for t h e crop s e c to r. ■ T h e s u b s e c t o r s of hogs, pigs and s w in e an d dairy farm p r o d u c t s have t h e largest Type III employment multipliers at 2 . 3 0 an d 2 . 2 5 . ■ Th e Type I an d III output multipliers for th e livestock s e c t o r w e r e moderate ly higher th a n th e crop s e c t o r o u t p u t multipliers. ■ In 1 9 9 2 Michigan livestock e x p o r t s (both d o m e s t i c and foreign) totaled $ 1 4 1 . 0 million. Total s ta te livestock imports w e r e valued at $ 5 9 8 . 6 million. ■ T he s t a t e had a n et tr a d e deficit177 of $ 4 5 7 . 7 million for livestock an d p r oducts. Fruit an d Other Trend Analysis Highlights for Fruit and O t h e r : 178 Th e 2 1 -year fruit c r o p trend analysis f o c u s e d on t h e c a t e g o r i e s of 176 N o t e : n i n e l i v e s t o c k c a t e g o r i e s w e r e a n a l y z e d in t h e i n p u t - o u t p u t c h a p t e r VI; dairy farm p r o d u c ts , poultry a n d e g g s , ra n c h fed c a ttle , ra n g e fed c a ttle , c a ttle feedlots, sh eep -lam b s-g o ats, hogs-pigs-sw ine, other m e a t anim als, m iscellaneous livestock. 177 N o t e : a n e t t r a d e s u r p l u s / d e f i c i t is d e f i n e d a s t h e d i f f e r e n c e b e t w e e n M i c h i g a n d o m e s tic c o m m o d ity e x p o rts a n d M ichigan foreign e x p o rts m in u s M ichigan c o m p e titiv e c o m m o d ity im ports. 178 N o t e : s e v e n c o m m o d i t i e s w e r e a n a l y z e d in t h e f r u i t t r e n d s e c t i o n o f c h a p t e r IV; apples, g ra p e s, p e a c h e s , pears, p ru n e s a n d plum s, s w e e t cherries, and tart cherries. 316 a c r e s h a r v e s t e d , value of production, quan tity p r o d u c e d , yield, price, and n u m b e r of fruit bearing t r e e s for each of t h e co m m odities . ■ All fruit cr o p s had positive tre n d s for yields, prices, an d value of pr od uct io n (except pears). ■ Total fruit crop value of production increase d at an a v e r a g e annual rate of 3 . 6 1 % , from $ 5 8 million in 1 9 7 0 to c o ns is tently a b o v e $ 1 4 0 million in th e late 8 0 ' s . Fruit c r o p s ' value of pr od uct io n tre nd of 3 . 6 1 % placed th e group last for the major c o m m o d it y groups an alyzed, (field cr o p s w e r e first with a rate of 4 . 4 % ) . ■ Only apples and s w e e t cherries po s te d positive tre n d s for t h e nu m b er of fruit bearing t re es. ■ Every fruit crop had a neg ativ e 2 1 -year trend for a c r e s h a r v e s te d . Th e 2 1 -year total s t a t e trend for a c r e s h a r v e s te d w a s a decline by an a v e r a g e of 1 . 7 5 % per year. When investigating th e historical d ata further h o w e v e r , (see Figure 92) t w o distinct tre nd p a tte r n s e m e r g e . The first trend patt ern is from 1 9 7 0 to 1 9 8 2 , w h e r e total a c r e s h a r v e s te d fell ever y ye a r from 1 5 6 , 3 0 0 a c r e s to 1 0 0 , 9 0 0 a c r e s . 1 9 8 2 th e neg ativ e tre nd re v e rs e s as a c r e a g e in c r e a s e s e a c h year from 1 0 0 , 9 0 0 a c r e s to 1 1 9 , 0 0 0 in 1 9 9 0 . ■ A p p l e s , d e s p i t e a declin ing t r e n d in a c r e s h a r v e s t e d , d i s p l a y e d an In 317 a v e r a g e an nua l increase of 1 . 9 9 % for the qu an tity p r o d u c e d . The re a s o n for th e u p w a r d trend in production w a s th e increasing trend in yields per acre. Th e rise in apple yields w a s a function of the significant ex p a n s i o n of trees. The n u m ber of fruit bearing t r e e s in th e s t a t e g r e w from 2. 9 million in 1 9 7 0 to 5.5 million in 1 9 9 0 , rising at an a v e r a g e an nu al rate of 3 . 2 8 % (highest for all fruit crops). The com binat ion of greate r production, an d higher prices, lead to a value of pro duct io n t h a t tripled from $2 5 million to $ 7 5 million. ■ Pear s s h o w e d th e largest declines and w e r e last in a c r e s h ar v ested , qu an tity p r o d u c e d , value of production, an d n u m b e r of fruit bearing t r e e s for all fruit cr ops . For e a c h of th e preceding c ateg o r ies, pear s p o s te d negative t re n d s. The nu m b er of fruit bearing tr e e s in th e s t a t e fell from a level of 1 . 0 million tre e s in 1 9 7 0 to 1 4 0 , 0 0 0 tr e e s in 1 9 9 0 , a decline of 8 6 . 0 % . Shift-Share Analysis Highlights for Fruit an d O t h e r : 179 Th e highlights are s e g m e n t e d into th r e e time periods 1 9 7 0 - 1 9 8 0 , 1 9 8 0 - 1 9 9 0 , an d 1 9 7 0 - 1 9 9 0 . 179 N o t e : e i g h t f r u i t c r o p s w e r e a n a l y z e d in s h i f t - s h a r e c h a p t e r V; a p p l e s , blueberries, cherries, p e a c h e s , pears, plum s a n d prunes, stra w b e rrie s. Also note: the c o m m o d ity of g r e e n h o u s e an d nursery p ro d u c ts w a s analyzed se p a ra te ly but included in t h e r e s u l t t a b l e s f o r f r u i t a n d o t h e r , t h e " o t h e r " b e i n g g r e e n h o u s e a n d n u r s e r y products.. 318 1 9 7 0 - 1 9 8 0 H ig h lig h ts : ■ Total fruit c a s h rece ipts incr ea se d from $ 6 8 million in 1 9 7 0 to 161 million in 1 9 8 0 , up approximately 1 3 7 % . T he co m peti tive position of Michigan fruit er o d e d h o w e v e r , d es pit e t h e increase in c a s h receipts. If Michigan had k ep t p a c e with th e national g r o w t h rate for fruit cr op s rec eipts should h a v e bee n $ 3 0 million higher (this is reflected in the ne gative e x p e c t e d com pe titive effe ct of $ 2 0 . 8 an d th e negative allocation effe ct of $ 9 . 2 million). ■ Every co m m odity, e x c e p t for cherries, had n eg ati v e results for their e x p e c t e d co m pe titive effect. Cherry receipts e x p a n d e d from $ 1 9 . 4 million in 1 9 7 0 to $ 5 0 . 9 million in 1 9 9 0 , up 1 6 2 % . T h e e x p e c t e d co m petitive ef fect for cherries w a s $ 2 8 2 t h o u s a n d an d t h e allocation ef fe c t w a s $ 3 . 8 million for a net competitive ef fe c t of $4.1 million. ■ Apples an impo rta nt fruit crop in the s ta te, p o s te d c a s h rec ei p ts t h a t w e r e slightly behind th e national gr ow th rate. T he net co mpetitive effe ct w a s a negative $ 9 . 7 million. Nationally apple s w e r e a fast g r o w t h com m od ity. 1 9 8 0 - 1 9 9 0 H ighlig hts: ■ Total s t a t e fruit cr op receipts incr eased only marginally in t h e 8 0 ' s . From 1 9 8 0 to 1 9 9 0 , receipts rose from $ 1 8 0 . 6 million to $ 1 9 3 . 5 million. Despite fruit crop s being a fast g r o w t h s e c t o r nationally, 319 Michigan continued to lose ground competitively. If Michigan had kep t p a c e with th e national g r o w th rate for fruit crops, 1 9 9 0 receipts would be larger by $51 million. ■ Apples w e r e th e major contribu tor to t h e d o w n w a r d tre nd in th e s t a t e ' s co m pe titive fruit crop position. Apples p o s te d a ne gati ve net co m pe titive ef fe ct of $ 2 3 million. ■ Blueberries w e r e o n e of the important fruit cr op gainers in th e s t a t e in 80's. Rec eipts e x p a n d e d from $ 1 9 . 7 million in 1 9 8 0 to $ 2 7 . 0 million in 1 9 9 0 , up 3 7 % . Th e relative s t r e n g t h of blueberries nationally is identified by th e calculated net co mpetitive ef fe ct of $ 3 . 8 million. 1 9 7 0 - 1 9 9 0 H ighlig hts: ■ Total Michigan fruit cr op receipts lagged significantly behind the nation in th e rate of gr ow th. A negative net com pe titive ef fe ct w a s calcu lated for ever y Michigan fruit c r o p . 180 In total, th e ne t co m petitive ef fect w a s a negative $ 1 0 1 . 5 million for Michigan. This m e a n s t h a t if Michigan fruit c a s h receipts had g r o w n at th e national rate, total receipts would be $ 2 6 7 million, instead of $ 1 6 6 . 5 million in 1 9 9 0 . ■ For th e t w o d e c a d e s str a w b e r rie s w e r e a f ast g r o w t h c o m m o d it y at t h e national level. In Michigan receipts in crease d from $ 5 . 7 million in 180 N o t e : b l u e b e r r i e s w e r e a n a l y z e d o n l y f o r t h e d e c a d e o f t h e 8 0 ' s . 320 1 9 7 0 to $ 6 . 5 million in 1 9 90. Michigan h o w e v e r , did not k e e p pac e with th e national g r o w th rate, s t a t e s tr a w b e r r y rece ipts sh ould hav e b e e n $23. 1 million181 higher in 1 9 9 0 , s h o w in g h o w significantly rece ip ts lagged. ■ Michigan g r e e n h o u s e and nur sery p r o d u c ts receipts e x p a n d e d from $ 3 0 . 5 million in 1 9 7 0 to $ 2 5 9 . 7 in 1 9 9 0 , up ap proxima te ly 7 5 2 % . Michigan c a s h rece ipts incr ea se d substantially during t h e 7 0 ' s and 8 0 ' s , but so did national g r e e n h o u s e and nur se ry receipts. From a com pet itive position, s ta t e receipts w e r e actually just behind t h e U.S. in t e r m s of t h e rate of gr o w th , this is illustrated by t h e n e g a tiv e net co m petitive ef fe ct of $ 7 . 5 million. Input-O utput Analysis Highlights for Fruit and O t h e r : 182 ■ Fruit employment multipliers (both Type I and Type III) w e r e both conside ra bly higher t h a n t h e s ta t e non-agricultural a v e r a g e s . The Type I fruit multiplier w a s 2 . 0 4 and th e Type III fruit multiplier w a s 3 . 4 2 c o m p a r e d to th e s t a t e non-agricultural a v e r a g e of 1 . 3 5 and 2 .21. 181 M i c h i g a n s t r a w b e r r i e s h a d a n e g a t i v e n e t c o m p e t i t i v e e f f e c t o f $ 2 3 . 1 m il l i on . 182 N o t e : a g e n e r a l f r u i t c a t e g o r y a n d a g r e e n h o u s e a n d n u r s e r y p r o d u c t s c a t e g o r y w a s a n a l y z e d in t h e i n p u t - o u t p u t c h a p t e r VI. 321 ■ Th e Type I output multiplier for fruit w a s slightly higher th a n th e s ta t e crop a v e r a g e and th e T ype III multiplier w a s app ro xima tely th e s a m e a s th e s t a t e cr op ave r a g e . ■ In 1 9 9 2 Michigan's fruit ex p o r ts (both d o m e s t ic an d foreign) totaled $ 2 5 5 . 0 million. Total s t a t e fruit imports w e r e valued at $ 1 2 5 . 7 million. ■ Th e s ta t e had a ne t fruit tra de s u rp lu s 1”3 valued at $ 1 2 9 . 3 million. V e g etab les Tren d Analysis Highlights for V e g e ta b l e s :184 The 2 1 -year ve g e ta b le cr op trend analysis f o c u s e d on t h e ca te g o r ie s of a c r e s h a r v e s te d , value of production, quantity pr o du ce d, yield, and price for e a c h of th e com m od ities. ■ Total v e g e ta b le cr o p s a c r e s har ve st ed e x p a n d e d gradually t h r o u g h o u t t h e 7 0 ' s and 8 0 ' s . A c r e a g e in creased from 8 8 , 0 0 0 t h o u s a n d in 1 9 7 0 to 11 6 t h o u s a n d in 1 9 9 0 , rising at an a v e r a g e annual rate of 183 N o t e : a n e t t r a d e s u r p l u s / d e f i c i t is d e f i n e d a s t h e d i f f e r e n c e b e t w e e n M i c h i g a n d o m e s t i c c o m m o d i t y e x p o r ts a n d M ichigan foreign e x p o r ts m in u s M ichigan c o m p e titiv e c o m m o d ity im ports. 184 N o t e : t h i r t e e n c o m m o d i t i e s w e r e a n a l y z e d in t h e v e g e t a b l e t r e n d s e c t i o n o f c h a p t e r IV; a s p a r a g u s , c a u l i f l o w e r , c a r r o t s , c e l e r y , c u c u m b e r s , l e t t u c e , m u s h r o o m s , onions, s n a p b e a n s, straw b erries, s w e e t corn, fresh to m a to e s , an d p ro c e ss to m a to e s . A lso n o t e t h a t s tr a w b e r r ie s are included w ith th e v e g e ta b le s , th e M ichigan Agricultural S t a t i s t i c a l S e r v i c e c a t e g o r i z e s t h e d a t a in t h i s m a n n e r . 322 0 .83% . ■ Total v e g e t a b le cr o p s value of production tr e n d e d higher at an a v e r a g e annual rate of 4 . 2 9 % (ranking 2nd of th e major c o m m o d ity g r o u p s analyzed, field crop s w e r e first with a rate of 4 . 4 % ) . Value of a lm o st tripled from t h e $ 4 8 million level in th e early 7 0 ' s to a b o v e $ 1 4 0 million in th e late 8 0 's . ■ Every v e g e ta b le cr op p o s te d positive tre n d s for price an d value of produc tion. The com m odities with t h e largest positive price tre n d s w ere: s w e e t corn 6 . 1 8 % , cauliflower 5 . 7 7 % , and let tuce 5 . 3 3 % . T he c om m odities with th e largest positive value of production tre nds w e r e cauliflower 7 . 3 5 % , process ing t o m a t o e s 7 . 3 5 % , an d s n a p beans 6.52% . ■ Ten of th e thirteen v eg etab le c rops exhibited positive yield trends. Th e top thre e c o m m odit ie s w e r e m u s h r o o m s 185 5 . 9 9 % , pr oce ss ing t o m a t o e s 3 . 5 3 % , and c u c u m b e r s 2 . 4 3 % . ■ T o m a t o e s for p r o c e ss in g s h o w e d significant pro du ction gains. The positive trend w a s an a v e r a g e annual incr ea se of 5 . 6 2 % , th e largest for all v eg etab le crops. Production tripled from 5 5 , 0 0 0 t o n s in the early 7 0 ' s to th e 1 7 0 , 0 0 0 - t o n level in the late 8 0 ' s . Acr es h a r v e ste d also tre n d e d higher, rising from th e 3 , 5 0 0 - a c r e ra n g e to th e 185 Note: the mushroom yield is calculated on a square foot basis. Also, the data used in the mushroom analysis (from 1981 to 1990) is not as complete as other Michigan Agricultural Statistical Service time series. 323 5 , 5 0 0 - a c r e level. The value of pro ductio n also in crease d cons iderably rising over six times, from app ro ximately $2 million a y ear to $ 1 2 million annually. ■ S n a p b e a n s w e r e a n o t h e r crop that e x p a n d e d significantly in th e d e c a d e s of th e 7 0 ' s and 8 0 ' s . Acres h a r v e s t e d tre n d e d higher doubling from 1 1 , 0 0 0 to 2 2 , 0 0 0 acr es. A ver ag e annual production incr ea se d at a rate of 3.61 %, from a range of 2 6 , 0 0 0 t o n s per yea r in th e 7 0 ' s to the 5 4 , 0 0 0 ton s per year in the late 8 0 ' s . ■ Fresh m arket s tr a w b e r rie s g e n e r a te d t h e largest negative tre nd for the v e g e t a b le crop c a t e g o r y of production. The s t a t e ' s pro ductio n of fresh m ar ket str a w b e r ri e s fell an a v e r a g e annual rate of 2 . 6 2 % , from 2 5 5 , 0 0 0 Cw t. in 1 9 7 0 to th e 1 4 0 , 0 0 0 Cw t. level in th e late 8 0 ' s . Acres h a r v e s te d d r o pped nearly 5 0 % in the early 7 0 ' s and th e negative tre nd b e g a n to slow in th e 8 0 ' s ranging from 2 , 7 0 0 a c r e s to 2 , 2 0 0 acr es . ■ A n other crop t h a t displayed nega tive pr oduction t re n d s w a s fresh m ar ket t o m a t o e s . Fresh m ar ket t o m a t o production fell an a v e r a g e annu al rate of 2 . 3 5 % . The n u m b e r of a c r e s h a r v e s te d fell from th e 4 , 0 0 0 - a c r e level in t h e early 7 0 ' s to th e 2 , 5 0 0 - a c r e level in th e late 80's. 324 S h i f t - S h a r e A na ly si s Highlights for V e g e t a b l e s : 186 Th e highlights are s e g m e n t e d into thre e time periods 1 9 7 0 - 1 9 8 0 , 1 9 8 0 - 1 9 9 0 , an d 1 9 7 0 - 1 9 9 0 . 1 9 7 0 - 1 9 8 0 H ighlig hts: ■ Total v e g e ta b le c a s h receipts increase d from $ 5 6 . 5 million in 1 9 7 0 to 119.1 million in 1 9 8 0 , up 1 1 1 % . ■ From a co mpetitive s ta n d p o in t Michigan v e g e t a b l e s ou tp e r fo r m e d national ve g e ta b l e receipts, given th e positive e x p e c t e d co mpetitive ef fe c t of $ 3 . 5 million. However , th e allocation ef fe c t w a s a negative $ 9 . 9 million, m eanin g t h a t th e s t a t e over specialized in m a n y s lo w g r o w t h (at th e national level) v e g e ta b le s . ■ Three v e g e t a b le s : s n a p b e a n s , celery, an d a s p a r a g u s p o s te d positive com petit iv e gains. Each of t h e s e c o m m o d it ie s had positive e x p e c t e d com petit iv e e f fe c ts and allocation ef fe cts . The large net co mpetitive e f fe c t pertain to a s p a r a g u s of $ 6 . 3 million, s e c o n d w a s celery with $ 3 . 0 million, an d third w a s s n a p b e a n s with $ 2 . 5 million. 1 9 8 0 - 1 9 9 0 H ighlig hts: ■ In t h e 8 0 ' s c a s h rec ei pts e x p a n d e d from $ 1 1 9 . 1 million in 1 9 8 0 to 186 N o t e : t h i r t e e n v e g e t a b l e c r o p s w e r e a n a l y z e d in s h i f t - s h a r e c h a p t e r V; a s p a r a g u s , c a b b a g e , c a n ta lo u p e s , cauliflower, carro ts, celery, c u c u m b e r s , lettuce, onions, p ep p ers, sn a p b ean s, s w e e t corn, and to m a to e s . $ 1 5 1 .1 million in 1 9 9 0 . Michigan c ontinued a similar p atter n a s in t h e 7 0 ' s with a neg ative e x p e c t e d co m pe titive effect, o n e of $ 2 4 . 5 million. Nationally t h e v e g e ta b le s e c to r m oved into a fast g r o w t h m o d e. This is highlighted by th e net sectoral mix effe ct of $33.1 million t h a t w a s e s tim a t e d for all Michigan ve getables. S n a p b e a n s c o nti n ued to gain s tr e n g th competitively a s in t h e 7 0 ' s . The ne t co m pe ti ti ve ef fe ct of $ 3 . 4 million w a s t h e largest for all v eg e ta b l e s . Four c o m m o d ities actually had declines in their c a s h receipts from 1 9 8 0 to 1 9 9 0 : c a n t a l o u p e s d o w n 4 2 % , let tuce d o w n 2 9 % , c a b b a g e d o w n 1 6 % , and celery d o w n 0 . 0 9 % . Each of t h e s e c o m m o d it ie s had e s t i m a t e s of nega tive net co mpetitive ef fe c t s e x c e p t for c a b b a g e . Even t h o u g h Michigan c a b b a g e receipts declined, th e y declined eve n further at t h e national level. 1 9 7 0 - 1 9 9 0 H ighlig hts: Total Michigan v eg etab le and melons c a s h rece ip ts in crease d from $ 5 6 . 5 million in 1 9 7 0 to $ 1 51.1 million, up 1 6 7 % . The net co mpetitive effect for total v e g e t a b le s w a s a ne gative $ 3 3 . 4 million. This m e a n s t h a t if Michigan receipts had kept p a c e with th e national g r o w th rate for v e getable s , th an total Michigan receipts 326 should h av e been $ 1 8 4 . 5 million in 1 9 90. ■ T he c o m m odities with th e largest e s ti m a t e d net co m p etitive e ffe cts w e r e : s w e e t corn, s n a p b e a n s , a s p a r a g u s , and p e p p e r s . ■ The c o m m odities with th e largest e s tim a te d neg ativ e n e t co m pe titive e f f e c t s were: onions, carro ts , t o m a t o e s , and lettuce. I n p u t- O utp ut Analysis Highlights for V e g e t a b l e s : 187 ■ Both T ype I and III v e g e ta b le employment multipliers w e r e s o m e of th e h ig h e s t for all s e c t o r s an alyze d. The Typ e I multiplier w a s 2 . 2 6 an d t h e T yp e III w a s 3 . 7 9 c o m p a r e d to th e s t a t e non-agricultural a v e r a g e s of 1 . 3 5 and 2 . 2 1 . T he larger multipliers reflect th e labor intensive na ture of v e g e t a b le cr ops. ■ Th e T y p e I and III output multipliers for v e g e t a b l e s w e r e slightly higher for the Type I an d slightly lower for th e Type III t h a n th e s t a t e non-agricultural a v e r a g e s . ■ In 1 9 9 2 Michigan's v e g e t a b le e x p o r t s (domestic and foreign) totaled $ 1 2 8 . 2 million. Total s t a t e v e g e ta b le imports w e r e val ued at $ 1 7 8 . 8 million. ■ Th e s t a t e had a v e g e t a b l e n e t t r a d e deficit188 valued at $ 5 0 . 6 million. 187 N o t e : a g e n e r a l v e g e t a b l e c a t e g o r y w a s a n a l y z e d in t h e i n p u t - o u t p u t c h a p t e r VI. 188 N o t e : a n e t t r a d e s u r p l u s / d e f i c i t is d e f i n e d a s t h e d i f f e r e n c e b e t w e e n M i c h i g a n d o m e s tic c o m m o d ity e x p o rts a n d M ichigan foreign e x p o rts m in u s M ichigan c o m p e titiv e c o m m o d ity im ports. 327 Sy n th esis T he v a s t a m o u n t of re se arch information p r e s e n te d in this dissertation could be c o n s id e re d overw helm ing and invoke a r e s p o n s e by th e reader(s) t h a t s a y s , "all this is very nice but w h a t difference d o e s it m ake to me." The p u r p o s e of this dissertation w a s to c r e a te an analysis of key baseline d a t a for Michigan pro ductio n agriculture during t h e d e c a d e s of t h e 7 0 ' s and 8 0 ' s . Th e diss er ta ti on is d e s ig ne d to be a f oun dation t h a t will a s s is t s ta t e policy m ak ers affiliated with production agriculture. This applied r esear ch e n d e a v o r provides a r eso u r ce th at will help to minimize th e s e a r c h and tr a n s a c t i o n c o s t s th a t are a s s o c i a te d with t h e gen er ation of production agriculture policies, specifically to th e S ta te of Michigan. During th e dev elo p m en ta l s t a g e s of m o s t policies, it is critical to have a r e f e r e n c e point in order to identify realistic goals an d objectives. This diss erta tion is a road map th at provides an a n c h o r point and a des cription of t h e p a t h t h a t Michigan h a s taken, regarding th e production of m any and varied agricultural commodities, over th e last 2 0 yea rs. It should be noted, h o w e v e r , t h a t th e analysis d o e s not furnish a prescription for th e policy m aker of w h a t should or should not be do ne . H o w t h e n might the policy maker b e s t utilize this diss er ta ti on? The d iss erta ti on h a s th r e e primary s ectio ns . Each se ction u s e s th r e e different t y p e s of analytical m e t h o d s to d es crib e the s t a t e ' s agricultural tre n d s, shifts an d linkages during th e d e c a d e s of th e 7 0 ' s and 8 0 ' s . Th e following is a 328 sampling of possible w a y s t h a t th e re se arch results may be utilized by th e policy maker: 1) H o w might t h e results of th e trend c h a p t e r IV be utilized, and w h a t t y p e s of policy q u e s ti o n s are relevant to th e trend analysis?. ■ Recognize th e trend analysis is a historical b e n c h m a r k or proxy for being able to quantify specific objectives, during t h e cr eation p r o c e s s of a policy. ■ In th e formative p r o c e s s of the policy recognize t h a t m any of t h e s e t r e n d s are well e n t r e n c h e d and may not c h a n g e rapidly. The following policy questio n might be a s k e d , is it r e a s o n a b le to a s s u m e , hypothetically, for th e s t a t e to try and ex p a n d th e pro ductio n of p e a r s? Given p e a r 's historical pro du ction trend of an a v e r a g e annual decline of 6.11 from 1 9 7 0 to 1 9 9 0 (see Figure 114), increasing pear pr od uct io n in th e s h o rt run is probably not a realistic goal and e x p e c t a t i o n s would n eed to be adjusted. ■ Recognize t h a t o n c e a policy is implemented, it's e f f e c t iv e n e s s can be tra ck ed an d m e a s u r e d ag a i n s t th e s t a t e d objective. ■ R e m e m b e r t h e benefit of t h e trend analysis is t h e identification of w hat h a s h a p p e n e d . The next s te p (and b eyond th e s c o p e of this res ea rch ) is to ask t h e questi on an d identify why certain tr e n d s e m e r g e d ? The final s t e p in th e p r o c e s s is to ask w hat will it t a k e in 329 o rd er to m a k e c h a n g e s in certain tre nds, if des ired? 2) H o w might t h e results of the shift-share c h a p t e r V be utilized, a n d w h a t t y p e s of policy q u e s tio n s are relevant to th e shift-sh are analysis?. ■ Recognize t h a t shift-shar e analysis is an important analytical te c h n i q u e t h a t identifies t h e p a tte r n s of g r o w th and th e c hanging s tr u c t u r e of Michigan production agriculture over time. ■ Recognize t h a t th e results of t h e shift-shar e analysis is for t h e policy m aker in u n d e r st a n d i n g Michigan' s co mpetitive position (from a United S t a t e s perspective) for m o s t of it's agricultural com m odities . 3) H o w might th e results of th e i np ut -o utput c h a p t e r VI be utilized, and w h a t t y p e s of policy q u e s tio n s are relevant to th e inpu t-output analysis? ■ Recognize t h a t th e inp ut-o utput analysis is useful in un d e r sta n d in g th e influential linkage of Michigan production agricultural with the S tate's economy. ■ Recognize t h a t t h e inpu t-o utpu t results a d d r e s s e s specific issues c o n c e r n i n g t h e p a t t e r n s of Michigan production agriculture; e m p lo y m e n t, tra de, supply, d e m a n d , in co m es , value a d d e d and o u t p u t levels. 330 R es earch Co ns ideratio ns 1) Future Trend R es earch Considerations : ■ The fitted t r e n d s (linear an d exponential functions) could be e x p a n d e d to include o th e r t y p e s of fitted functions. ■ Th e time series d a t a ( 1 9 7 0 - 1 9 9 0 ) s e t could be enlarg ed to include more r ecen t d a t a as well as older ob s erv atio n s , t h u s enriching th e results. 2) Future Shift-Share R es earch Considerations: ■ T he shift-shar e te c h n iq u e could be modified to inco rp orate time series coefficien ts (instead of th e c r o s s sectional rates of c h a n g e coefficients) g e n e r a t e d by ordinary least s q u a r e s regression. ■ N e w d a t a s e t s could be g ath er ed and th e shift-sh are analysis could be e x p a n d e d to included s t a t e s s u c h a s Texa s, California and Florida. ■ Co ntinue to explore the utilization of agricultural c a s h receipts a s th e basis for co m pa ring different t y p e s of com m od ities. 3) Future Inpu t-O utput R es earch Considerations: ■ T h e in put-o utput results could be a d a p t e d to a d a t a b a s e s tr u c tu r e t h a t would a s sis t th e policy maker in th e querying an d investigation of th e model results. 331 ■ Th e inpu t- outp ut model could be easily ad ap ted to an alyze specific pr o d u ctio n agriculture ec o n o m ic dev elo p m en t q u e s ti o n s . For e x am p le, w h a t are t h e e c o n o m ic implications (i.e., e m p lo y m e n t , o u t p u t an d incom es) of a p r o p o s e d soybea n milling facility in th e state? APPENDICES Appendix A Data S e t for Chapter IV Trend A nalysis A ppendix A , Data S e t for Chapter IV, Trend A nalysis General Farming Year Number of Farms L an d in Farms (Acres) Average F a rm Size ( Acres) 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 84,000 82,000 81,000 78,000 76,000 70,000 70,000 68,000 66,000 66,000 65,000 65,000 64,000 63,000 63,000 61,000 59,000 57,000 56,000 55,000 54,000 12,700,000 12,500,000 12,400,000 12,300,000 12,300,000 1 1,500,000 11,400,000 11,200,000 1 1,400,000 11,400,000 11,400,000 1 1,400,000 1 1,400,000 11,400,000 11,300,000 1 1,300,000 11,100,000 11,000,000 10,900,000 10,800,000 10,800,000 151 152 153 158 162 164 163 165 173 173 175 175 178 181 179 185 188 193 195 196 200 332 o o o o o o O O o O O o o O o o o o CD CN LO in o 03 O CN o o m CN CO LO o o o o 03 cn n O fv 03 cn o 00 in CO o CN O o CD o o 0) d rv 05 00 CO CO CO 00 o' CN o CD rv T— in in CO CO 0) 00 05 r^ 00 rv o o 05 05 in r™ o CO T"” CN r — 03 o: CO o> CO in ^5* 1— 00 CD ^y *. «. CN CN n CN CN CN *y 'S ' lO *}• in in in O o o o o o 00 o ^y CN co f— CN CO co o CD v> Q. * O' CO 03 CD ID CN co co • 0 v> < j> 0 0 0 V> 0 0 in in 0 00 5i n o i n o o o o CO CD q q 0 0i n O CD 0 0 CO 0 5CO o o d r “ CN CN CO CN CN CN CO CN CN CN CN CN CO CN 0 0 ■o W • o 0 «/> CN CO CD CN Tq 9 CN i n 9 T“ CN CN »—■ 5 CO r“ 0 CD CN CO ^ y 0 5 0 5 o 0 00 5 LO CN 0 0o i n * y LO CO i n *y O CD O CN i n CO CO 0 3 i n CN CN 0 0 r-i J CO CN CN CN CN CN 0 0 v> O rv CO n r - > c o — 'D o o D f— "O 0 cl re CO CO CO O o o rv 03 U) Gi W a > w < r- in CO CO 1 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 CQ m CO CO m CO CO CO CO CO CO CO CO CO m CD CO CD CD CD 6 3 3 3 cn CD cn m O o o O O 0 O O 0 O O 0 ffl o o o o o o CN T“ CM CN CN o o o o o o o o o O O O CN o ' 05' ,-T CN CN T— CN O O O CN CN O r CN CN CN CN O O O O O O O O O O O O O O O O O O O O O 0 0 0 O O 0 O O O O O O O O O O O O co' co' co 00 LO o ' co o ' co' IN C*5 cn co co LO LO co <* re CM 05 LO CO IN co 05 O ,_ CN o rv rv IN rv fN |V IN rN IN 00 00 00 m 05 05 05 05 05 05 05 05 O) O) 05 05 »— *— <— i— 1— r~ *— r— »— 1— T- CO LO CO 00 00 00 00 05 05 05 05 «— w— •— IN 00 05 O 00 co 00 05 05 05 05 05 f— i— 1— 0 0 0 o' 0 0 O 0 0 O 0 0 O o' o' o' 1— 0 CO ID 0 0 0 0 0 r-' r - CN h03 03 03 «“ O > •5 o c o u r-* CN CN CN CN CN CN CN CN 0 O O CN TO TO r- ' CN CO ^y i n CD 00 03 0 t— CN n 1^ r^* Is * 03 CO CO CO 0 3 C3 03 03 03 0 3 0 3 03 03 o> 03 *- r“ *— r - »— T— »— t— r - r - 0 O 0 O O 0 O 0 O O 0 O 0 O O o' o' o' o' o' ID ID LD 0 cCO CN CN 0 CO co' P-' LD' CN CN CD ID 00 .—CN CN CN * “ •— CN 3 3 3 m 3 3 O O O o' LD O CD cn CN 3 ffl ffl ffl ffl ffl O 0 O 0 O 0 O 0 O 0 O 0 O O O O O O o' o' o' o' o' o' cn ID ID 0 IV r>» IV <3" m TO 05 0 CN CN r— r-' r“ Cs| ^y in CD CO 03 O 0 0 GO 00 00 00 GO 03 0 3 03 0 3 03 03 03 0 3 *— r— r “ »— T— Dry Beans —ft —ft —ft —ft —A — ft CO CO CD CO CO CO CO CO CO CO CO CO CO CO CO CO CO CD CD CD CD CD CD CD 0 0 0 0 CD v j v l v l v J v l CO CD 0 5 CD A C J N J — O CO 0 0 v l 0 5 c d o * 1970 1971 1972 1973 1974 — ft 1 1 —t _F _ _ 1 _ _F _F _F mmt CO CO CO CO CO CO CO CO CO CO CO CO CO CO CO CO CO CO CO CO CO V j Nl CO 00 00 00 00 03 00 00 00 00 00 vj •vl •vl vj vj ^1 o CO co vj 03 cn A CJ NJ o CO oo vj 03 cn A CJ NJ o < 0D > X o o o o o o o o o o o o o o o o o o o o o o o o o o O o cn NO O O o O O O n nnn n no no n nnn n nn < < < < < << << << < << «r< <<: < < < r<-* < < < << ff Ff F* fF r4 ^4 < F* u 03 o Oo o 'o 6,153,000 5,643,000 7,319,000 5,320,000 6,902,000 cn A cn NO CD A O O cn O b O 575,000 Cwt. 570,000 Cwt. 615,000 Cwt. 560,000 Cwt. 575,000 Cwt. CJ CJ a co A CO CO cn cn cn A CJ o vj nj A — . to cn cn CO Vl 03 o op O O O o o O O O O o o o o o o o o o O o o _A u NJ A cn o 'o A CJ CJ CJ CJ CJ A A A A A CJ CJ A NJ o CB co •Vl 03 vj NJ A CJ NJ cn 00 CJ CO oo o o o o o o o cn o o p o o NJ p p oo NJ o b o o o 'o o o o o o o b o o b o o CJ CJ CJ CJ NJ A o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o —i H H H H H H H H H H H — t H H H H H H H H o o o o o 0 o o o o o o o o o o o o o o o 3 3 3 3 3 3 3 CJ CJ vj p A A A A NJ CJ cn A CO NJ CO p 3 3 3 3 3 3 3 3 3 3 3 3 3 3 2< O > (D ^D (/> C *+ C ft (t) a c 3 GO CJ “U cn a NO p NO Ol A a vj vj vj p cn cn ~ -f '•vl A NO cn co V 'cn •vl a 'co b , CD cn •vl CO cn A oo 03 a o A NO NO — p o NO * O NO O O cn 00 NO O O a p V cn O a '•vl co NO b o 'o 'o o c b 'o 'o 'o o o 'o 'o o 'o o o o o o o o o o o o o o o o O o o o o o o o o o o o o o o o o O o o 05 NO O O O O _» 'co co A NO o o cn o o o o NO NO O 'co A —A 'o CD cno cn C Oo o o o o o o ■o v> •o> •o NJCJ * ro ro kNJfS5 NJ 00 05 A CJOl C OCJCJOl 05 00 A P 05 P NJCJC DC O05 o b N5 b b b CJ C O o OOo o o o Oo o Oo o o o o — — —a —N $9.70 $11.50 $8.70 $27.30 $14.80 —A —ft o p o o o o o o o vj 05 CD v> v> » in—* NJ — . •CA — , in —» $59,684,100 $64,894,500 $63,675,300 $145,236,000 $102,149,600 ■o cn A cn vj WNJ o A — * cn CD r o CD o o P CD ro O o o o b 00 'oo 'o 'o NO 'o 'oo o o O o o o o O o o o o o o o o o o o o o O o o o o o o CO — » 05 CD CJ b CO U1 CO 'o co 03 o o o o o o o o 'o 'o 'o 'o 'o 'o 'o o o o o o o o o o o o o o o o o o —ft cn A cn Ol A p 'co NJ cn CO NJ CO 01 03 A cn o cn o p p o A A A A NJ 03 A CO oo CO NJ vj O A o o 'o 'o o o b o o 'o o o o o o o o o o o o o o o o o o o o —ft A CJ vj C J w w — ft C J A A A CO ro b o cn o CD CD o o b o o CD (J1 w A 03 CO o o 'o o o o o o o o o o o o —ft N5 NJ p CD Cl bi NJ CJ O NJ ° _l £ ° o' 3 Y ie ld cn _F 'cn NO NO 00 1,070 990 1,190 950 1,200 _F b A Ol p CO A "If A 03 00 cn o o o b "a C DO ^ o if CD r+ OT —k —* -a —i, si —A —k CO CO CO CO CO CO CO CO CO CO CO CO CO CO CO 00 00 00 oo oo 00 00 00 00 00 v l v l v i o CO 00 v l o cn A CO N J —* o CO 00 v j B_k CO CO CO CO CD CO CO v l vj v l v l v i v i v l O ) cn A CO N J - * o C D C 0C 0C 0C O C O C O C O C 0C O 1J ' v J > s j ' s J ' s J ' s J -< o Qi ocooovJOJcnACONj-^ocooovjojcnAGJro-^o I NJ NJ p b o o CO NJ o o o o o o o o o o CO NJ o vl o o o o o o o o CO CO CO A CO cn o cn o o p o o o b b o o o o o o o o CO CO CO A A CO o p o p o b o o o o o o o o o o CJ CJ •p> 00 o cn o o o o o o CJ CJ v j cn o o o o o o o o CJ CJ o o o o CJ ro o o o o ■c* 05 p •v l o o o o o o 03 CD CD 03 CD CD 03 03 CO 03 CD CD 03 03 03 DO CD 03 CD CD CD c c c c c c c c c c c c c c c c c c c c c —» CJ o cn o o o o ro o —I o o o o o —» —» 0) o o o o o o vj o o o o o ro ro —1 vj p p cn vj b o —* CJ o o o o o o o b o o o o o o o o o o cn o 03 v l CO vj O NJ A —* 03 if* if* P CJ p p to CJ V j b —» vj O C J o O o p o o o o o o o o o o o o ro o CO OJ Vi Vj In ro cn o o O o o o o o o o o o o vj b o o o o o p cn o p b o o NJ vl o 03 p o o o cn 0) cn 0) cn O J 03 03 03 cn cn cn cn cn cn cn cn CO v j ro ro CO to o - * Vj cn - » O ) cn o cn Vj 03 v > if* if* if* N J —* N J N J ■ o 4 ^k —» —* — Lk b b vi CO CO if* if* •o> if* if* if* •o -* —» —1 —* mmk •A —» b b v j cn cn ro NJ cn v j b b b b 03 CO cn cn if* if* o o O b vl vl —* O if* if* if* if* if* if* if* if* if* if* if* if* if* if* if* CO CO N J U CJ N J N J N J CO N J CO N J _k -A cn CO cn vl o O vl U) CO -* N J cn CO vl o 00 o 0 3 o CO * N J b o o o CO o o o o o o o o o o o o CO 00 N J CO cn N J cn NJ A NJ CO CO —4 vl o o b b o o o o o o o o vl vi CO CO o 00 N J vj 03 00 CO O CO —k cn CO N J CO o O o b b o b 00 o o o o o o o o o o o o NJ vl N J 0) vi NJ cn b O o o o o v> _k A CO CO vj 00 CD CO A 03 A CO O o b NJ o cn O o O o ACnCOAvJvlvlACONJCOCOACONJCONJCOGJCOGJ a i ^ o O N ic n c n O s J - v J - * w w o < o o ^ O ) - * - u a i o o O p p p o p p p o o o o O O O p O O p o o o o b o b o b b b o b b b b o o o b o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o ;< o> CD -i CO CD ^ CD co a. 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CD 1 o 05' 0) 00' 05 CO q " o ' 05' 05 o ' o ' CN CN in ' in' r-' o ' 0 ) ' 05' CN 1— 1“ T*” ’ «— CO i v CN CO CN CO CO r v CN 05 0 CO CO f v 0 5 q q CN CO CO O’ O q Td d d CN CN CN CN CN CN CN CO CN CO CO CO CO CO CN CO CO CO CN CO CO 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 o' o' o' o' o' «— 0 0 cn CN cn <33 1— CN 1— in cn CN cn cn cn cn cn 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 o' o' o' o' o' o' co 0 in O ) CO CN in •cT 1— 0 co cn o' cc LO 00 cn cn cn cn cn cn co co ro c D ■ao> CO 0) (A o 0>) < > > o 4-1 «-• *-« ♦-» *-< > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > u O u U O CJ O ( J U u O O O u u O O u u u O 0 0 O 0 0 0 0 0 0 O O 0 0 O O O O O 0 0 O 0 O O O 0 0 O O O O O O O to CO CO CO q 00 q CO 00 0 0 O CO O *- CO 0 in in o ' o ' CN co' ai CN 0 co' 0 5 CN d r v CN co' co' ■n’ ' J 'J- cn CO ^3* ^3* i n i n i n 0 0 0 0 0 0 0 0 3 3 3 3 3 3 3 0 0 0 0 0 0 D1* o ' o ' * t' c n o' o' i n 0 0 CN 03 cn 1— co i n i n i n c o CO co i n CD 3 3 3 3 O O O 0 O O 0 O O 0 0 O 0 0 O 0 0 O O O O 0 O O O O O 0 0 0 03 0 05 05 r— * — 05 r- 05 r- 05 05 »— 05 05 05 1— r * m CO rv 0 5 O r ~ CN CO IV 0 0 0 0 CO CO CO CO CO 0 5 0 5 O) 0 5 0 5 0 5 0 5 0 5 0 5 r" r— CO 05 co CO CO 05 r“ 05 r— O 05 05 O r- 05 05 CN rv rv rv (0 c CD 0) .o > o CO 05 cn (V rv 05 05 r— If) CO rv CO 0 5 0 rv rv rv rv rv CO 05 05 0 0 0 O O O 03 0 I— CN co in CO rv CO rv rv rv rv rv rv rv rv rv 3 3 3 3 3 3 3 3 0 0 0 O O q O O O O O O 0 0 O O O O o' o' o' o' o' o' o' o' o' o' o' o' — ■n- 03 co i n 03 1— 0 1 I O 3 3 CQGQCQCQCQCQCOCOCOCOCQCQCQCDCQCQCOCDCQCQCQ CT) 0 5 T“ 05 05 w— r - T“ t—' O 0 T-' r - ' r~ 03 O r“ CN O O O O O O O CO o' •'T O r“ r-~ r - ' 1—* r - CN cn IO CO rv CO 0 5 O CO CO CO CO CO CO CO CO CO 0 5 05 05 05 05 1— r— 05 05 05 05 05 05 v— 337 A c re s H a r v e s te d Total P ro d u c tio n Value of P ro d u c tio n Year S u g arb eets 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 8 9 ,9 0 0 8 2 ,6 0 0 8 6 ,6 0 0 8 6 ,7 0 0 8 0 ,4 0 0 9 1 ,4 0 0 9 1 ,4 0 0 8 5 ,5 0 0 9 1 ,5 0 0 8 8 ,0 0 0 9 8 ,0 0 0 9 9 ,0 0 0 9 6 ,5 0 0 1 0 4 ,0 0 0 1 0 8 ,0 0 0 1 1 8 ,0 0 0 1 0 9 ,6 0 0 1 4 2 ,0 0 0 1 4 5 ,0 0 0 1 5 0 ,0 0 0 1 5 7 ,0 0 0 Ton Ton Ton Ton Ton Ton T on T on Ton Ton Ton Ton Ton Ton Ton Ton T on Ton Ton Ton Ton 1 ,9 1 3 ,0 0 0 1 ,4 1 5 ,0 0 0 1 ,6 3 8 ,0 0 0 1 ,5 2 4 ,0 0 0 1 ,3 6 4 ,0 0 0 1 ,7 5 5 ,0 0 0 1 ,5 4 0 ,0 0 0 1 ,7 9 6 ,0 0 0 1 ,7 7 0 ,0 0 0 1 ,5 5 0 ,0 0 0 1 ,8 9 2 ,0 0 0 2 ,0 3 0 ,0 0 0 1 ,8 5 3 ,0 0 0 1 ,9 7 6 ,0 0 0 2 ,1 1 7 ,0 0 0 2 ,3 2 5 ,0 0 0 2 ,2 8 0 ,0 0 0 2 ,9 1 1 ,0 0 0 2 ,3 9 3 ,0 0 0 2 ,5 6 5 ,0 0 0 3 ,2 6 6 ,0 0 0 2 1 .3 17.1 1 8 .9 1 7 .6 1 7 .0 1 9 .2 1 6 .8 2 1 .0 1 9 .3 1 7 .6 1 9 .3 2 0 .5 1 9 .2 1 9 .0 1 9 .6 1 9 .7 2 0 .8 2 0 .5 1 6 .5 17.1 2 0 .8 $ 1 2 .2 0 $ 1 3 .4 0 $ 1 2 .4 0 $ 3 0 .5 0 $ 4 7 .5 0 $ 2 4 .8 0 $ 2 2 .4 0 $ 2 0 .1 0 $ 2 3 .5 0 $ 3 8 .9 0 $ 4 0 .7 0 $ 2 6 .5 0 $ 3 5 .8 0 $ 3 6 .2 0 $ 3 4 .4 0 $ 2 9 .6 0 $ 3 0 .0 0 $ 3 1 .0 0 $ 3 6 .0 0 $ 4 1 .9 0 $ 3 8 .3 0 $ 2 3 ,3 3 8 ,6 0 0 $ 1 8 ,9 6 1 ,0 0 0 $ 2 0 ,3 1 1 ,2 0 0 $ 4 6 ,4 8 2 ,0 0 0 $ 6 4 ,7 9 0 ,0 0 0 $ 4 3 ,5 2 4 ,0 0 0 $ 3 4 ,4 9 6 ,0 0 0 $ 3 6 ,0 9 9 ,6 0 0 $ 4 1 ,5 9 5 ,0 0 0 $ 6 0 ,2 9 5 ,0 0 0 $ 7 7 ,0 0 4 ,4 0 0 $ 5 3 ,7 9 5 ,0 0 0 $ 6 6 ,3 3 7 ,4 0 0 $ 7 1 ,5 3 1 ,2 0 0 $ 7 2 ,8 2 4 ,8 0 0 $ 6 8 ,8 2 0 ,0 0 0 $ 6 8 ,4 0 0 ,0 0 0 $ 9 0 ,2 4 1 ,0 0 0 $ 8 6 ,1 4 8 ,0 0 0 $ 1 0 7 ,4 7 3 ,5 0 0 $ 1 2 5 ,0 8 7 ,8 0 0 W heat 1970 1 97 1 1972 1973 1974 1975 1976 1977 1978 1979 1980 19 81 1982 1983 1984 1985 1986 1987 1988 1989 1990 4 8 0 ,0 0 0 4 9 5 ,0 0 0 5 3 5 ,0 0 0 5 6 8 ,0 0 0 9 4 0 ,0 0 0 9 0 0 ,0 0 0 8 7 0 ,0 0 0 8 2 5 ,0 0 0 4 1 0 ,0 0 0 7 3 5 ,0 0 0 8 0 0 ,0 0 0 8 3 0 ,0 0 0 5 6 0 ,0 0 0 7 3 0 ,0 0 0 8 0 0 ,0 0 0 7 5 0 ,0 0 0 6 8 0 ,0 0 0 4 0 0 ,0 0 0 6 2 0 ,0 0 0 6 4 0 ,0 0 0 7 5 0 ,0 0 0 Bu. Bu. Bu. Bu. Bu. Bu. Bu. Bu. Bu. Bu. Bu. Bu. Bu. Bu. Bu. Bu. Bu. Bu. Bu. Bu. Bu. 1 8 ,7 2 0 ,0 0 0 17 ,8 2 0 ,0 0 0 2 1 ,4 0 0 ,0 0 0 1 9 ,8 8 0 ,0 0 0 3 7 ,6 0 0 ,0 0 0 3 4 ,2 0 0 ,0 0 0 3 3 ,0 6 0 ,0 0 0 3 3 ,0 0 0 ,0 0 0 1 6 ,4 0 0 ,0 0 0 3 1 ,6 0 5 ,0 0 0 3 5 ,2 0 0 ,0 0 0 4 1 ,5 0 0 ,0 0 0 2 2 ,9 6 0 ,0 0 0 3 5 ,7 7 0 ,0 0 0 4 5 ,6 0 0 ,0 0 0 4 5 ,0 0 0 ,0 0 0 3 0 ,6 0 0 ,0 0 0 1 9 ,2 0 0 ,0 0 0 2 6 ,0 4 0 ,0 0 0 3 3 ,9 2 0 ,0 0 0 4 1 ,2 5 0 ,0 0 0 39 36 40 35 40 38 38 40 40 43 44 50 41 49 57 60 45 48 42 53 55 $ 1 .4 0 $ 1 .3 4 $ 1 .6 5 $ 4 .3 0 $ 3 .6 4 $ 3 .2 2 $ 2 .5 3 $ 2 .0 2 $ 3 .3 0 $ 3 .8 2 $ 3 .6 0 $ 3 .4 7 $ 3 .3 3 $ 3 .4 0 $ 3 .1 8 $ 2 .8 4 $ 2 .3 8 $ 2 .6 3 $ 3 .5 9 $ 3 .6 3 $ 2 .4 0 $ 2 6 ,2 0 8 ,0 0 0 $ 2 3 ,8 7 8 ,8 0 0 $ 3 5 ,3 1 0 ,0 0 0 $ 8 5 ,4 8 4 ,0 0 0 $ 1 3 6 ,8 6 4 ,0 0 0 $ 1 1 0 ,1 2 4 ,0 0 0 $ 8 3 ,6 4 1 ,8 0 0 $ 6 6 ,6 6 0 ,0 0 0 $ 5 4 ,1 2 0 ,0 0 0 $ 1 2 0 ,7 3 1 ,1 0 0 $ 1 2 6 ,7 2 0 ,0 0 0 $ 1 4 4 ,0 0 5 ,0 0 0 $ 7 6 ,4 5 6 ,8 0 0 $ 1 2 1 ,6 1 8 ,0 0 0 $ 1 4 5 ,0 0 8 ,0 0 0 $ 1 2 7 ,8 0 0 ,0 0 0 $ 7 2 ,8 2 8 ,0 0 0 $ 5 0 ,4 9 6 ,0 0 0 $ 9 3 ,4 8 3 ,6 0 0 $ 1 2 3 ,1 2 9 ,6 0 0 $ 9 9 ,0 0 0 ,0 0 0 Unit Yield Dollars Per Unit Commodity 338 TOTAL Year A c re s H a rv e s te d 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 5 ,2 4 1 ,9 0 0 5 ,6 9 7 ,7 0 0 5 ,5 1 2 ,9 0 0 5 ,7 3 4 ,7 0 0 6 ,1 3 9 ,8 0 0 6 ,4 6 6 ,8 0 0 6 ,5 7 9 ,0 0 0 6 ,7 9 7 ,3 0 0 6 ,6 4 5 ,8 0 0 6 ,8 6 3 ,6 0 0 7 ,0 7 2 ,3 0 0 7 ,4 0 9 ,8 0 0 7 ,3 8 1 ,8 0 0 6 ,1 8 9 ,8 0 0 7 ,6 9 8 ,8 0 0 7 ,6 6 3 ,8 0 0 6 ,9 8 6 ,6 0 0 6 ,1 2 5 ,3 0 0 6 ,3 7 6 ,0 0 0 6 ,3 7 0 ,0 0 0 6 ,4 8 9 ,0 0 0 Value of Pro duction $ 4 2 2 ,0 9 5 ,0 4 0 $ 3 7 6 ,4 4 8 ,5 0 0 $ 4 8 9 ,3 5 4 ,5 1 0 $ 8 9 1 ,0 6 0 ,2 1 0 $ 8 9 7 ,0 2 0 ,5 0 0 $ 9 8 6 ,5 1 8 ,8 5 0 $ 8 2 4 ,3 6 4 ,3 0 0 $ 9 8 1 ,0 8 5 ,4 4 0 $ 1 ,0 1 5 ,7 6 2 ,6 1 0 $ 1 ,2 8 0 ,4 4 6 ,7 2 0 $ 1 ,6 4 4 ,9 9 5 ,6 5 0 $ 1 ,5 5 5 ,7 1 7 ,8 2 0 $ 1 ,5 3 6 ,3 4 7 ,8 6 0 $ 1 ,4 6 2 ,4 7 8 ,4 5 0 $ 1 ,5 0 5 ,5 5 2 ,0 0 0 $ 1 ,4 6 6 ,4 4 4 ,5 0 0 $ 1 ,1 0 6 ,4 6 5 ,4 0 0 $ 1 ,1 3 1 ,4 4 8 ,7 0 0 $ 1 ,2 7 2 ,2 8 1 ,4 0 0 $ 1 ,5 3 0 ,7 7 2 ,1 0 0 $ 1 ,5 2 9 ,3 5 7 ,8 0 0 339 o m m o d ity All C attle & C alves Y ear Number of H ead 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1 ,5 0 0 ,0 0 0 1 ,5 6 0 ,0 0 0 1 ,5 7 6 ,0 0 0 1 ,5 7 6 ,0 0 0 1 ,5 5 0 ,0 0 0 1 ,5 8 0 ,0 0 0 1 ,5 5 0 ,0 0 0 1 ,5 7 0 ,0 0 0 1 ,4 7 0 ,0 0 0 1 ,2 5 0 ,0 0 0 1 ,3 1 0 ,0 0 0 1 ,3 4 0 ,0 0 0 1 ,4 5 0 ,0 0 0 1 ,5 0 0 ,0 0 0 1 ,4 5 0 ,0 0 0 1 ,4 1 0 ,0 0 0 1 ,3 2 5 ,0 0 0 1 ,2 2 5 ,0 0 0 1 ,2 2 5 ,0 0 0 1 ,2 2 5 ,0 0 0 1 ,2 0 0 ,0 0 0 Unit lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. Total P ro d u c tio n 4 9 1 ,1 4 0 ,0 0 0 4 4 9 ,3 8 0 ,0 0 0 4 7 6 ,3 8 5 ,0 0 0 4 8 9 ,9 7 0 ,0 0 0 5 1 3 ,7 1 5 ,0 0 0 5 0 2 ,1 9 5 ,0 0 0 3 5 6 ,8 6 5 ,0 0 0 3 9 3 ,4 2 0 ,0 0 0 4 3 1 ,5 4 0 ,0 0 0 4 6 1 ,7 8 0 ,0 0 0 4 6 1 ,0 0 0 ,0 0 0 4 5 4 ,1 3 0 ,0 0 0 4 6 3 ,4 8 5 ,0 0 0 4 6 6 ,0 8 5 ,0 0 0 4 6 2 ,1 3 0 ,0 0 0 4 4 0 ,6 3 5 ,0 0 0 4 3 6 ,5 5 5 ,0 0 0 3 8 9 ,3 0 5 ,0 0 0 Yield Dollars Per C w t. C alv es $ 3 7 .6 0 $ 4 0 .3 0 $ 4 9 .7 0 $ 6 2 .4 0 $ 4 5 .0 0 $ 3 0 .4 0 $ 3 5 .4 0 $ 3 8 .8 0 $ 6 1 .6 0 $ 8 6 .6 0 $ 8 2 .5 0 $ 6 5 .2 0 $ 5 7 .2 0 $ 5 7 .0 0 $ 5 4 .1 0 $ 5 3 .3 0 $ 5 5 .0 0 $ 7 1 .9 0 $ 8 5 .4 0 $ 9 3 .7 0 $ 9 9 .0 0 Cattle Beef 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1 7 0 ,0 0 0 1 8 7 ,0 0 0 1 9 4 ,0 0 0 1 9 6 ,0 0 0 1 9 9 ,0 0 0 2 0 5 ,0 0 0 2 0 8 ,0 0 0 2 3 9 ,0 0 0 1 9 6 ,0 0 0 1 3 8 ,0 0 0 1 4 0 ,0 0 0 1 6 0 ,0 0 0 1 9 4 ,0 0 0 1 9 5 ,0 0 0 1 5 8 ,0 0 0 1 6 0 ,0 0 0 1 5 3 ,0 0 0 1 5 0 ,0 0 0 1 3 0 ,0 0 0 1 2 5 ,0 0 0 1 3 1 ,0 0 0 lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. $ 2 5 .8 0 $ 2 6 .4 0 $ 3 0 .5 0 $ 4 0 .2 0 $ 3 6 .3 0 $ 3 3 .5 0 $ 3 3 .0 0 $ 3 2 .8 0 $ 4 4 .2 0 $ 5 8 .2 0 $ 5 5 .9 0 $ 4 9 .5 0 $ 4 8 .0 0 $ 4 7 .2 0 $ 4 8 .2 0 $ 4 6 .3 0 $ 4 4 .5 0 $ 5 2 .5 0 $ 5 6 .1 0 $ 5 8 .5 0 $ 6 3 .2 0 Value of Production $ 1 9 7 ,7 6 0 ,0 0 0 $ 1 6 4 ,4 3 3 ,0 0 0 $ 1 5 9 ,5 6 9 ,0 0 0 $ 1 6 2 ,1 0 5 ,0 0 0 $ 1 6 8 ,1 9 7 ,0 0 0 $ 2 2 1 ,9 9 7 ,0 0 0 $ 2 1 5 ,7 5 4 ,0 0 0 $ 2 2 7 ,4 7 1 ,0 0 0 $ 2 1 6 ,3 4 8 ,0 0 0 $ 2 2 3 ,5 5 8 ,0 0 0 $ 2 1 8 ,6 6 1 ,0 0 0 $ 2 1 9 ,9 9 6 ,0 0 0 $ 2 1 5 ,3 7 3 ,0 0 0 $ 2 0 8 ,7 3 0 ,0 0 0 $ 2 4 7 ,2 4 5 ,0 0 0 $ 2 5 2 ,1 5 5 ,0 0 0 $ 2 6 2 ,0 9 0 ,0 0 0 $ 2 4 9 ,2 5 7 ,0 0 0 0 0 0 0 0 0 0 0 0 r o co " IN 0 0 1— i n , — in 00 in cn O O O 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 co' c o ' o ' o ' CO CO o ' i n ' c o ’ c o ' r v 0 3 T“ CO <0 r v r v IX) i n r “ CO r v CO CM t - CO CM CO 0 0 CO p * CO P-' c o ' i n cm' c n ' i n r v t -T | v 0 c n ' i n ' 03' MP 'C P v ' c n r > CO i n i n CD CO i n CO i n CO CO CD r v i n CD i n v > <0 v> <0 « > < 1 IV 0 0 0 3 r v c/3 cc O O O O O O 0 0 0 CO CO CO CO CD < - CO 0 3 CD 0 3 0 0 CO « - CM O CM |V O CO CD CO in in V 'S ' ■ < 0 b 0 Q 0 0 0 0 O O O co ' 00' 0 00 CD in •CO $ 0 ,0 8 5 0 0 0 $ 0 ,1 1 8 O O O in 03 rv T— r v 0 3 rv > r 03 $ 0 ,0 8 0 O O O $ 0 ,0 8 1 0 0 0 0 0 0 O O O cm ' cn' rv rv rv 0 0 0 0 0 O CM 0 T“ 0 0 0 0 0 0 ' t ' cn c n O )' 1— O cn O ) cn n - in 00 O ) r v 00 CN CN CM cn in CO ' S 0 •- 0 O O O r“ 0 0 O O 0 cm' 0 0 0 O O O rv O) CN 0 0 O 0 0 0 0 cn in T“ CO r v CN « v cn <0 O O IT) l0 tr> IT) O »— i n CN CJ) CO CO 0 T“ 0 rO 0 O 0 0 6 w 6 O 0 0 0 O O O O O O O 0 0 0 0 0 pm ' CN CD CM 0 0 CD 0 0 0 O O O 03' c n CN 00 00 cn ,-T CN cm' cd O O O CN 'S m r— O O CN o > r- O in 0 0 0 n T- CO O O O 0 O O O 0 O O O O CL T3 V ■Q h- CO O ■M- CO O CN CO CO CD 0 3 CO in CO 0 3 r v 0 0 in r - CO O CD CN CO CM CO CM O CO CO CO CM 'S ' <3- CO CN co in CO CD in CM CM CN CN CN CN CN CM CM CM CM CN CN CN CM CN CN CN CN CM CM ■C m > 0 0 0 in ' 03 'S co' 0 rv O) O O 0 0 O O 0 0 O O 0 0 o ' cm' co' CN in r — O m in 00 CD CM 10' co' co' co' c 0 0 o 0 0 0 'o 0 0 0 'o' 'J 0 't ' J co 3 1— , — r - ' 1- ' 1- ' r - ' r - ' r “ T—' 0 0 O 0 0 O 0 0 O o'o'o' in in 0 co CM »s co' co' co' O O O o' 0 co cd ' O O O O O O O O O O O O o'o'o'o' 0 0 0 0 co CN r v « co' co' co' r v 0 0 O o' 0 rv co' O O O o' 0 CD cd ' 0 0 0 o' 0 00 in ' O 0 O O O O o ' 0 O co' cn o ' 00 0 in rv in cn i n ' T c n CO c n co' 0 'S r-' o ' c n CN o ' T“ CM CN CN 0 O 0 O O O o 'o' 0 O CD in in ' in ' 0 ,_ CN co M- m CD r v co O ) 0 00 00 00 00 00 00 00 00 00 00 03 O) 03 03 03 03 03 03 03 03 03 O) 03 O) 03 03 03 03 03 03 03 CM co ' S in CD IV 00 03 r v r v r v IV r v IV r v r v r v r— r— »— f- ' *— r— T- i — r— r ~ »— ,— ,— 1— r™ 1— f— 5 ,2 2 6 ,0 0 0 o ' o ' o ' o ' o ' o ' o ' o ' o ' 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 in ' c o ' o s ' in ' co ' o ' o ' p»' d i n 0 CM CO |V 0 CM c o 0 3 '3 - LO i n i n c o c o m i n 'S r - r - T— T— 1— I - <— r~- «— >■ 08 S'1 o o 0 0 0 0 0 O O O O O 0 O 0 0 0 0 0 O 0 0 0 O O 0 cm' cn 0 0 0 O O O n -' cn rv 00 c n 00 CM c n r v o ' r - ' CN CN CN CN 0 0 0 0 0 0 O O O O O O 0 0 O 0 0 O 0 0 0 co' rv CN n i n T- CN 0 CM o ' O ' T— CN CN CN O 0 O o' o' o' o' o' o' o' o' o' 0 0 03 0 in ' 0 0 CD fN 0 r— 0 0 CD 0 co' in' in' in ' O ' LO CO 1973 l_ fT\ C W 03 0 0 0 4 ,5 5 2 ,0 0 0 0 W 0 u03 .O 03 E X 0 z 0 0 0 1972 O 0 0 c 4 ,3 4 6 ,0 0 0 0. O O O 4 ,3 4 0 ,0 0 0 lo co O O O 1 9 7 1 O O O O 1970 CO a 0 3 w O O O C h ic k e n s n .9 O O O fN fN fN cn O) 0) 1— 0 0 0 O O O O O O o ' o ' o ' o ' o ' o ' in in 00 c n CN r v CD CN c n c n r v n -' c n o ' n - ' cd ' c n CN CM CN CN T— <— O O O O O O O O o' o' o' o ' o ' o ' O O O 0 0 0 0 LD Lf> CO CO O) «— in in 0 O CN CD r — *“ O O O O O O i n ' in ' in ' LO Lf) Lf) LD If) O O O 0 0 0 0 0 0 O O O Lf)' co' O'" CO O) O T— CN CO O 1 Lf) c o fN CO O) O 1-N fN CO CO CO CO CO CO CO CO CO CO c n 0 O cn 0 ) 0) 0 0 c n 0 ) 0 ) O) c n c n r — r— r— «— r- T— »— r - r— r - n o in f— D " fU © —* — » —a «"A _ A . A _A _ 4 _A _A CD CO CO CO CO CO CO CO CO CO CO CO CO CO CO CO CO CO CO CO (O CD 0 3 CD CO CO v j V l v l v l v l v l v l v l v l v l CO CO v ] CO CO CO vj CO CO N J 03 03 O • J —A _A 00 00 00 00 ho —* o __ k 00 _A 03 cn -_ k —* o _* ro ro ro ro cn 0 3 ro cn OP o (T O CO CO N j Vl Vl -n| o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o w o o o o o CJ CJ cr cr cr cr O’ O’ O’ O’ O’ O’ O’ O’ O’ O’ O’ O’ O’ o* O’ C/3 c/3 c/> CO CO CO C ft C/3 Vi W {/> V) w vt w CO CO CO CO CO (0 ow* O’ V) (0 ro o o o —* c n C l 03 CD o —k —A o o I O CO 0 1 • u fo ro 0 3 —* CD o o o o o o 0 0 CO o P o o CD CD b vl b ro u cn CO cn v l cn p o o o o o o o o o o o o 03 03 cn o o o —k —A o P CD vl 03 b 03 p o vl p o b cn o o o o o o o o o CD ro b P b cn O O cn b o o o o c o o o CD vl o p A CO 03 00 S3 vl o v l v l 03 o o b vl vl o cn o cn o b o o o o o o o o CD o cn vl b b 0 3 cn cn cn o o o o o o o P o o o o CD b b —A CD O CO o b o o o o •CO- ■CO •CO < o ■CO •oo •oo •CO •CO CO CO •CO CO CO CO CO CO CO CO co cn 03 03 v l 03 03 cn cn cn cn 03 03 o> 03 03 ro ro ro cn ro p cn v l v l CD 03 NJ • i v l 03 0 0 03 CO —1 03 vl cn o O o o o Oo o b O p o o o b b ro b ’_k b b b b b o o o o o o o o o o o o o b O CO CO CO CO CO CO CO CO CO CO CO CO CO CO CO CO CO CO cn cn cn cn cn * 03 03 03 cn •c* •O 03 03 03 03 03 O ro o b v l Vl b b o o b b b ro CD V l 03 CD cn 03 v l ro —* CD cn cn o cn v l ro v l ro vj ro ro 03 03 *ro P ro 03 — P o o o o o o o o o o o o b o o o ro b ro co — * o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o P ro o o b _* _A _A _A _A CD CD CD CD CD CD CD CD CD CD CD CD CD CD CD CO 0 0 CD CO CO 0 0 0 0 v l v l v j v j v l v j vj vl vl v j cn A 0 3 ro O CO 0 0 v l a > cn A 0 3 ro • 4 o CO O) sJ OOO CJ V> - - - 03 03 O o o o CD O o o o ro P b b 03 cn v j CD o ro o O o o O O o o o O o o o O - O o o o C J c? C J Vi CO CO <0 CJ V CJ NO o o o CJ CJ NJ NJ 'c j CO cj —» O co ■v> <0O O O CO v l —A o o o o cn 03 O o o cn cn cn cn - A v l v l 03 o v l —A P o O cn o o O o o o O o o o o o O o o a ? cn CJ cn cn o o o CJ CJ NJ N) CO 03 b CO — > cn o -C* CJ p -* p o o o o o o o o o o o o *n iff iff •CA b NJ b b b b b N) b b NJ NJ NJ NJ M NJ NJ !_• cn N l CO CO cn CJ o vj NJ 00 CO c n 0J vl CO CJ CO 00 vl b j ^ » — iff k00 CO 0) cn CJ NJ *NJ — n ■uo o CO cn CO vl O c 00 ■fe. CO CO NJ NJ p p o o o c o o o o o o o o o o o o o o o o 00 o vl N> OJ OJ NJ cno o cn .—* o o o o o o o o o s 03 3ik C D V o a. —1 c O o 2L o 3 J-> o□ C 3 ST TJ s < iff in iff CJ < CD as 2-f Cn CO NJ cn A a •t* p o cn V '•vl b Vi cn 'o Vi NJ cn ■u CJ N) NJ cn CO o p CO O O p O o o o o o o o o o o o o o o o o o o o o o o o o v> O o a o cn co CO C T CT CT U" CT uex CO CO CO Vi CO CO CO CO CO M (n iff 3 3 in in vj 00 o —> p p NJ cn o o o o o o o o o o o o o o o o o o o o o o o o c c O 1 Year Apples Fruit Bearing Trees Acres Harvested Unit Total Production ( 0 0 0 's) Tons Per Acre Dollars Per Unit N n o o in o o »— •T rv in c o T— •s ■m o o in rv m o co 05 i— CD m 00 (V o o o o o o o o « • in in in CO r-“ o 05 00 r v ,_ CO CM CO CO (V 05 o o o o o o o CO o CO IV o i n 05 o o i n i n CO ■m • o o o o 10 1_ O in o rv - 05 o o i n 0 5 •S q rv o co co - O o O o o o o o o o o o o 05 CN r— f— co CO CN c o 05 r v CO O o O o o o o O o o o 6 it O 00 O *— T - in 05 o o 10 O o CN o CD CO i n r - i n CO 05 CO o 05 o CN i n O ' CO LD CO r v CD f v i n CM CD CO o O CO CN 05 r v CM i n ^3* CO CN ^3* in •co­ ■CO­ •co- 00 00 ’S i n LO 05 CM CN o m in in tj * LO 00 o CD CN O 6 6 o o r> •co­ •co■co- < 00 00 o o o o o o CN O O O 00 00 O o o o o o CN CD co CM o CN CD o o o CM 05 CD CN o L0 r— CM CM O O o o o o o o o o o o o o o o o o o o o o o o 00 00 o o o o o o o rv CD CO CN o o o in in in in in in in £ £ £ £ £ £ £ 1/5 £ in in £ .a c/> w £ £ £ o O O a o o O O o o i n CO CD CM CO CO CO CO CM co O ’ o o O c o r v O ’ O' o O ’ o O’ O’ o o • t ’t O o O o in o 05 r— • s in o o o o 05 «— r — CN l0 i n O o o O o o o o O o i n *— T— CO o 05 0 5 05 co co CO CO CO cn cn O o O O o o O o o O o o 05 05 CO f v CN o o o O o o o o o o o o o o o O O o o o o o CM T“ o o o o o o o o o O o o o i n o LD o i n O i n o 05 r v CD CD (V CD CD r v o £ O O O O O O O o o O i n i n i n LO |V CD i n • s co CM i— in in in in in m O o O o 05 o o o o o o o O o o o CM o 05 o o o o o o o o o in m O O o o o o o o O O O o o o o O O o o o o in in in in in in in in £ £ £ £ £ £ £ £ O O O O O O CO i n o o o o o o o o o o o o o o o o o o o o o o o 05 CO 0 5 <— c o CM co CO CO CO co CO CM CM CM CO CO <— r— CM c o o O | v r - ' |V r v r v 05 05 05 05 05 r— *“ 00 05 |V LA CO IV r v r v IV r v 05 05 05 05 r— *“ o o o o o o o o o o o o i n r*^ 00 O o o o o o o o o o o o o o o o o o o o LO o o i n IV 05 CM • t c o C/5 co w £ n o o o o o in o co i n 00 o 05 05 *“ o o o O o o o o o in o o N1 CO CO CO •S • s • t i n i n i n o CM CO o LO CO r v 05 oo oo 00 00 oo c o oo c o 0 0 CO 05 0 5 05 0 5 05 05 05 05 0 5 0 5 05 r— r*~ *“ T“* *“ •“ r — f " 00 o o o o o d o o o •c^ •co- o o o o o o i n co i n i n IV o 05 00 CN CD CN in ' 05 CO CN CN CO J> ■o -CO- < rv i n CO 05 i n 05 CO 05 i n 05 rv CO CN r— T“ CN CN o o o o o o o o o o o o o o o o o 05 o CO r v r v o CO r v CM m rv o o CO CO rv rv • s CO r v •S i n 05 CO 05 CO 05 r v IV 00 o 05 i n o i n 05 i n CO CN r v CO CO CO i n r v i n CO CO CO c o c o CD i n o CO i n o o o CO i n co »— ■n r v CO rv i n i n CO i n i n ^3- LD 05 r v fv ^3* CN CN T“ CN r~ r - CO CO CN CO CN CN CN CN CN CN r— CM c n O o 00 O O o 00 6■0> o < 6r> o •S LD o • - T— CN 05 r v o o o CN r* o o CN CN CN o o CO CN cn CM rv CN r v CO t— r - CN c n in ■o> CN 0 5 r v 05 5 o q o 00 o o o o o o d o ■in in o o o o o in rv rv U) o o o in in £ £ CO c/i £ < h n l/j o o o O o o O O o O O o O o o O o o o o o o o o O O O o o O O o o o d in o o d T“* CN r v CD CD CO CD CN CN CN CO i/i t/5 CO C/S ui w 5 n n n X ) 5 x> -Q o o o o CD o O 05 r v CO 05 r v rv. cn CO CN CN CN CN CN CN O O o o o o o o o o O o o o o CD CO O CO X) O o O o o O CO CO 05 CO o CO ^3*' CO CO CN CN CO CO CO CO CO CO CO o o o o o o o o o o o o o o o o o o o o o o in o o o CN i n CO m O o o o O O o o o in in CO CO CO c n CO cn CN CN CN CN CN CN CN CN co' CO CO co' co' co' co' *0) Q) X. o rTO o rv r v 05 •" 2 CN c n r * IV r * 05 05 05 T~ 00 05 i n CO r v rv rv rv fv 05 0 5 05 05 T— •“ T_ in o T— CN CO r v CO 00 CO CO CO CD 05 05 05 0 5 05 05 05 T— *— r “ T - *— *“ 00 05 o CO t v CO CO CO 05 05 05 05 05 05 *“ r— * - «— 00 345 rries Year Fruit Bearing T rees A cres H a r v e s te d Unit Total P ro d u c tio n ( 0 0 0 's ) Tons Per A cre Dollars Per Unit 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 9 2 0 ,0 0 0 9 5 0 ,0 0 0 9 7 0 ,0 0 0 9 8 0 ,0 0 0 9 8 0 ,0 0 0 9 8 0 ,0 0 0 9 8 0 ,0 0 0 9 0 0 ,0 0 0 8 5 0 ,0 0 0 7 7 5 ,0 0 0 7 0 0 ,0 0 0 6 7 5 ,0 0 0 6 2 5 ,0 0 0 6 4 0 ,0 0 0 6 7 0 ,0 0 0 7 0 0 ,0 0 0 7 4 0 ,0 0 0 7 8 0 ,0 0 0 8 1 0 ,0 0 0 8 4 0 ,0 0 0 8 6 0 ,0 0 0 1 1 ,4 0 0 1 1 ,6 0 0 1 1 ,7 0 0 1 1 ,5 0 0 1 1 ,8 0 0 1 2 ,1 0 0 1 1 ,6 0 0 1 0 ,9 0 0 1 0 ,2 0 0 9 ,3 0 0 8 ,4 0 0 8 ,1 0 0 7 ,5 0 0 7 ,7 0 0 8 ,0 0 0 8 ,2 0 0 8 ,6 0 0 9 ,1 0 0 9 ,4 0 0 9 ,7 0 0 9 ,9 0 0 lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. 4 2 ,0 0 0 4 7 ,0 0 0 5 6 ,0 0 0 3 4 ,0 0 0 5 6 ,0 0 0 6 2 ,0 0 0 2 7 ,0 0 0 5 0 ,0 0 0 7 5 ,0 0 0 5 4 ,0 0 0 5 8 ,0 0 0 4 6 ,0 0 0 6 2 ,0 0 0 3 6 ,0 0 0 6 6 ,0 0 0 6 2 ,0 0 0 4 0 ,0 0 0 6 4 ,0 0 0 5 6 ,0 0 0 5 0 ,0 0 0 3 2 ,0 0 0 1.8 4 2 .0 3 2 .3 9 1.4 8 2 .3 7 2 .5 6 1.1 6 2 .2 9 3 .6 8 2 .9 0 3 .4 5 2 .8 4 4 .1 3 2 .3 4 4 .1 3 3 .7 8 2 .3 3 3 .5 2 2 .9 8 2 .5 8 1 .6 2 $ 0 ,1 0 1 $ 0 ,0 9 6 $ 0 ,0 9 8 $ 0 ,1 4 0 $ 0 ,1 8 0 $ 0 .1 1 8 $ 0 ,1 8 6 $ 0 ,2 0 5 $ 0 ,2 2 9 $ 0 ,2 0 4 $ 0 ,1 7 7 $ 0 ,1 8 8 $ 0 ,1 9 9 $ 0 ,2 3 0 $ 0 ,2 1 2 $ 0 ,2 5 0 $ 0 ,2 8 8 $ 0 ,2 8 8 $ 0 ,3 2 9 $ 0 ,2 3 4 $ 0 ,2 5 6 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1 ,5 5 0 ,0 0 0 1 ,6 0 0 ,0 0 0 1 ,5 3 0 ,0 0 0 1 ,4 3 0 ,0 0 0 1 ,3 5 0 ,0 0 0 1 ,2 6 0 ,0 0 0 1 ,2 0 0 ,0 0 0 1 ,0 0 0 ,0 0 0 7 0 0 ,0 0 0 5 0 0 ,0 0 0 4 5 0 ,0 0 0 4 2 5 ,0 0 0 5 0 0 ,0 0 0 5 7 0 ,0 0 0 6 6 0 ,0 0 0 7 2 0 ,0 0 0 7 9 0 ,0 0 0 8 7 5 ,0 0 0 9 2 5 ,0 0 0 9 5 0 ,0 0 0 9 7 5 ,0 0 0 1 6 ,1 0 0 1 6 ,5 0 0 1 5 ,6 0 0 1 4 ,3 0 0 1 3 ,5 0 0 1 2 ,7 0 0 1 1 ,9 0 0 9 ,9 0 0 6 ,9 0 0 4 ,9 0 0 4 ,4 0 0 4 ,1 0 0 4 ,7 0 0 5 ,3 0 0 5 ,9 0 0 6 ,3 0 0 6 ,6 0 0 7 ,3 0 0 7 ,7 0 0 7 ,9 0 0 8 ,0 0 0 lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. 7 5 ,0 0 0 8 2 ,0 0 0 1 0 ,0 0 0 5 0 ,0 0 0 7 0 ,0 0 0 6 5 ,0 0 0 4 0 ,0 0 0 5 5 ,0 0 0 6 0 ,0 0 0 3 5 ,0 0 0 4 0 ,0 0 0 3 5 ,0 0 0 5 0 ,0 0 0 3 5 ,0 0 0 4 5 ,0 0 0 5 5 ,0 0 0 5 0 ,0 0 0 6 0 ,0 0 0 4 5 ,0 0 0 5 5 ,0 0 0 4 5 ,0 0 0 2 .3 3 2 .4 8 0 .3 2 1 .7 5 2 .5 9 2 .5 6 1 .6 8 2 .7 8 4 .3 5 3 .5 7 4 .5 5 4 .2 7 5 .3 2 3 .3 0 3 .8 1 4 .3 7 3 .7 9 4 .11 2 .9 2 3 .4 8 2.81 $ 0 ,0 7 2 $ 0 ,0 5 8 $ 0 ,1 0 7 $ 0 ,1 1 5 $ 0 .1 1 7 $ 0 ,1 3 4 $ 0 ,1 4 1 $ 0 ,1 5 6 $ 0 ,1 6 0 $ 0 ,1 9 4 $ 0 ,1 9 2 $ 0 ,1 9 2 $ 0 ,2 0 9 $ 0 ,2 1 5 $ 0 ,1 7 1 $ 0 ,2 0 9 $ 0 ,1 7 7 $ 0 ,1 6 1 $ 0 ,1 7 8 $ 0 ,1 9 1 $ 0 ,1 7 8 *CDT3 0) O Q> ■CDo CO CO _ , - a _ , —i _ , _ k —, _ _ h CO CO CO CO CO CO CO CO CO 0 0 0 0 0 0 0 0 0 0 0 0 0 0 oo v l v l 03 m C J ro —* o CO —* A ■c* a —* —* _, _1 _, _, CO CO CO CO CO vl vl vj vl vl 00 v l O ) O l 1970 1971 1972 1973 I _* _i CO CO CO CO CO 0 3 o CO 03 —I •_>A —* a t mA _A CD CD CD CD CD CD CD CD CD CD CD CD CD CD CD CD CD CD CD 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 CD 0 0 v j v j v l v l v j v l v l O CD 0 0 v l O ) c n A C J N J O CD CD v l 0 ) c n A CO cn cn cn cn p - vl 00 U1 Ol 03 03 vl 00 O NJ Ol CO Ol O Ol CJ o CJl 0 ) o Ol o Ol p o O Ol p o o O o o o o o o o b o o o o o o o b o o o o o o o o O o o o o o o o o o o o o o o o o O o o o o o o o o o o o a NJ t o NJ NJ •o 03 1,000,000 1,000,000 970,000 940,000 —A —* o p b o o o o o o o o _ «v4 b o o o o o vl vl vl vl vl vl vj vi cn cn cn cn P 03 03 vl b C J o> O c n o o o o o o o o o o o o o o cn b o o O o b o O b O o CO c o 0 3 o o o o o o o o o o o o o o o o o o o o o o o N J CD A c n b o o o o c n o o o o o o o _» _k _1 CO CO c o vl vl vl NJ 1 o o o o o o o o o o o o o o o o b o o o o o o o o o o o o o o -< CD 0) . < 03 CD TI 3 =2 S CO= ~ X GJ CJ* cn r* 03 'v j v j -* NJ 00 b NJ NJ CO •o p v l b 00 b b vl 00 co vl o o o o o O o O o o o O o o o o o o o o o o O o O o o o o o o o o o O ' O ' CT a c c r O' O ' c C C C C C O ' O' C cn cn cn cn cn cn cn cn cn cn cn cn cn cn cn cn cn -* —1 r o Nj -* o o O o o o O O lbs. lbs. lbs. lbs. r* 10,600 10,500 10,200 9,900 cn «jk c (n c r CJ 5 w w w N J N J CO CO w c n o o O N J c n v J O c n o o o o o o o o o o o o o o o o o o o o o o o o P b o o wA c n c n CJl U 1 p CD b o o o o Ol 0 0 0 0 CO CO o o o o o o o o Crt Cft w Co c/> Co w 5 V) CT E tfl in a CT CO cn CO 0 0 O N J 0 3 O CD r o NJ 03 03 o NJ 00 o O CD —» CO 0 3 N J CD O 0 3 N3 v i 0 3 CD v l c n 0 3 CD N J c n v l 0 3 0 0 o o o O O O O O O o o o o o o o o o b o o o o o o O O O o o O o o O o o O O o o o o b o o o o o o o o o o o O o o o o o o o o 3 CJ A o 1^ ' 2 cd Cfl c f. ~ o — 3 TJ •n CD CJ p o L. o o o b NJ ro c o CO CD CO —* c n 0 0 c n o c n c n c n cn O cn o if* if* b —» CD cn o NJ r o 00 CO 00 o ro CD o 03 CJ O —4 00 03 O o o o L» L> b o O O o cn cn O 00 o o o «/> V > — 1 NJ NJ —» NJ r o vl Co ro o v l cn — * 03 03 o o00 o o CD o o p —* —* —* - * NJ b ro b ro o o N J 0 0 o CO O cn o o if* if* —» —* —* —» —» —* —* —1 —* - * —A —* A $0,470 $0,405 $0,445 $0,770 03 O l C J p •O •O p C J - * o - * b NJ b NJ b Nj NJ !_> b b b b b C J O l C J CO C J 03 CO v l CO CO v l ■O O CD 1.60 1.76 2.21 1.16 -» O l .o v l CO o CD C J o < n .a —A —a CJ CD c n v l CJ c n CJ3 CD vl al o f o c n 0 0 CD 0 3 if* —J O ,° ° CD 03 cn CJ 03 N J —* N J b vl b vl b o b b b 00 NJ 00 ro 00 v l NJ o . CO CO b b b b b CO N J 0 3 v l o p A 03 A w 03 b (O O l o if* if* if* if* —* o o o o « > —± —» —* C J —» CO c n v l 0 0 C J 0 0 0 0 O L_k v l cn 03 cn NJ c n O 0 0 c n CO CD if* if* if* NO v l 0 0 NO NO v j —A o CD c n O v > v> 00 03 v l CJ co O 00 ® CD N3 0 0 03 o o > n S’ o v o C 5T 2 -3 lq |£ |« 6-a 3 347 ’lu m s Year 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 Fruit Bearing T rees 6 5 0 ,0 0 0 6 6 5 ,0 0 0 6 7 5 ,0 0 0 6 8 0 ,0 0 0 6 9 5 ,0 0 0 7 0 0 ,0 0 0 6 0 0 ,0 0 0 5 0 0 ,0 0 0 4 5 0 ,0 0 0 4 0 0 ,0 0 0 3 5 0 ,0 0 0 3 0 0 ,0 0 0 2 7 5 ,0 0 0 2 8 0 ,0 0 0 3 0 0 ,0 0 0 3 1 5 ,0 0 0 3 3 5 ,0 0 0 3 4 5 ,0 0 0 3 6 5 ,0 0 0 3 7 5 ,0 0 0 3 9 0 ,0 0 0 A c re s H a r v e s te d 6 ,8 0 0 7 ,0 0 0 7 ,1 0 0 7 ,2 0 0 7 ,3 0 0 7 ,4 0 0 6 ,4 0 0 5 ,4 0 0 4 ,8 0 0 4 ,2 0 0 3 ,7 0 0 3 ,1 0 0 2 ,8 0 0 2 ,8 0 0 2 ,9 0 0 3 ,0 0 0 3 ,2 0 0 3 ,3 0 0 3 ,5 0 0 3 ,6 0 0 3 ,7 0 0 Unit lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. Total Production ( 0 0 0 's ) 2 3 ,0 0 0 4 0 ,0 0 0 2 8 ,0 0 0 3 6 ,0 0 0 3 2 ,0 0 0 4 0 ,0 0 0 3 2 ,0 0 0 2 8 ,0 0 0 4 8 ,0 0 0 2 8 ,0 0 0 2 5 ,0 0 0 3 2 ,0 0 0 2 0 ,0 0 0 2 4 ,0 0 0 2 4 ,0 0 0 2 2 ,0 0 0 2 2 ,0 0 0 2 8 ,0 0 0 2 2 ,0 0 0 2 6 ,0 0 0 1 2 ,0 0 0 T o ns P e r Acre 1 .6 9 2 .8 6 1 .9 7 2 .5 0 2 .1 9 2 .7 0 2 .5 0 2 .5 9 5 .0 0 3 .3 3 3 .3 8 5 .1 6 3 .5 7 4 .2 9 4 .1 4 3 .6 7 3 .4 4 4 .2 4 3 .1 4 3.61 1 .6 2 Dollars Per Unit $ 0 ,6 4 0 $ 0 ,3 6 0 $ 0 ,6 9 5 $ 0 ,6 1 5 $ 0 ,8 7 5 $ 0 ,5 9 5 $ 0 ,6 6 5 $ 0 ,7 0 5 $ 0 ,6 9 0 $ 1 .0 3 5 $ 1 .0 4 0 $ 0 ,7 0 0 $ 1 ,2 8 0 $ 0 ,9 8 5 $ 1 ,3 8 0 $ 1 ,4 9 5 $ 1 .2 1 5 $ 0 ,6 7 5 $ 0 ,9 9 0 $ 0 ,8 7 5 $ 1 .4 8 0 Value of Pro duction ( 0 0 0 's ) $ 1 ,4 7 2 $ 1 ,4 4 0 $ 1 ,9 4 6 $ 2 ,2 1 4 $ 2 ,8 0 0 $ 2 ,3 8 0 $ 2 ,1 2 8 $ 1 ,9 7 4 $ 3 ,3 1 2 $ 2 ,8 9 8 $ 2 ,6 0 2 $ 2 ,2 3 7 $ 2 ,5 6 5 $ 2 ,3 6 6 $ 3 ,3 1 0 $ 3 ,2 8 5 $ 2 ,6 6 8 $ 1 ,6 2 4 $ 2 ,1 7 3 $ 2 ,2 8 1 $ 1 ,7 7 8 TOTAL 1970 19 71 1972 1973 1974 1975 1976 1977 1978 1979 1980 19 81 1982 1983 1984 1985 1986 1987 1988 1989 1990 1 5 6 ,3 0 0 1 5 6 ,1 0 0 1 5 4 ,0 0 0 1 4 9 ,0 0 0 1 4 5 ,6 0 0 1 4 2 ,5 0 0 1 3 1 ,1 0 0 1 2 0 ,4 0 0 1 0 9 ,9 0 0 1 0 5 ,3 0 0 1 0 4 ,3 0 0 1 0 1 ,9 0 0 1 0 0 ,9 0 0 1 0 2 ,5 0 0 1 0 5 ,3 0 0 1 0 8 ,8 0 0 1 1 2 ,1 0 0 1 1 6 ,0 0 0 1 1 7 ,5 0 0 1 1 8 ,9 0 0 1 1 9 ,0 0 0 $ 5 8 ,5 6 5 $ 6 4 ,1 4 5 $ 6 7 ,8 9 1 $ 8 4 ,8 6 7 $ 1 1 1 ,2 3 1 $ 7 9 ,2 5 1 $ 8 1 ,6 7 7 $ 1 2 2 ,6 9 2 $ 1 7 1 ,6 2 2 $ 1 3 7 ,8 6 4 $ 1 2 0 ,6 3 2 $ 1 3 3 ,5 4 0 $ 1 3 1 ,6 7 2 $ 1 3 1 ,3 8 8 $ 1 4 5 ,6 6 6 $ 1 6 9 ,5 3 2 $ 1 3 1 ,0 6 4 $ 1 4 3 ,0 2 8 $ 1 4 9 ,4 0 8 $ 1 4 1 ,4 0 3 $ 1 3 9 ,1 9 8 348 Total Commodity Year A c re s H a r v e s te d Unit P ro d u c tio n ( 0 0 0 's ) Yield Dollars Per Unit V alue of P rod uc tio n A sparagus 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1 2 ,4 0 0 1 3 ,5 0 0 1 4 ,5 0 0 1 5 ,4 0 0 1 7 ,0 0 0 1 7 ,8 0 0 1 8 ,0 0 0 1 9 ,0 0 0 1 9 ,5 0 0 1 9 ,5 0 0 1 9 ,5 0 0 1 9 ,0 0 0 2 1 ,3 7 1 2 2 ,0 3 0 1 9 ,2 0 0 1 9 ,2 0 0 2 0 ,5 0 0 2 2 ,0 0 0 2 2 ,5 0 0 2 3 ,0 0 0 2 3 ,5 0 0 C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. 198 189 218 246 255 196 180 209 254 254 234 171 223 223 230 230 246 242 248 253 259 1 6 .0 1 4 .0 1 5 .0 1 6 .0 1 5 .0 1 1 .0 1 0 .0 1 1 .0 1 3 .0 1 3 .0 1 2 .0 9 .0 1 0 .4 10.1 1 2 .0 1 2 .0 1 2 .0 1 1 .0 1 1 .0 1 1 .0 1 1 .0 $ 2 1 .0 0 $ 2 4 .2 0 $ 2 7 .0 0 $ 2 8 .9 0 $ 3 3 .7 0 $ 2 4 .3 0 $ 3 3 .0 0 $ 4 4 .6 0 $ 5 6 .7 0 $ 6 1 .2 0 $ 5 1 .3 0 $ 6 2 .5 0 $ 6 3 .5 8 $ 6 7 .3 9 $ 5 7 .9 0 $ 5 8 .4 0 $ 5 8 .2 0 $ 5 8 .6 0 $ 5 9 .0 0 $ 5 8 .4 0 $ 5 6 .7 0 $ 4 ,1 5 8 ,0 0 0 $ 4 ,5 7 3 ,8 0 0 $ 5 ,8 8 6 ,0 0 0 $ 7 ,1 0 9 ,4 0 0 $ 8 ,5 9 3 ,5 0 0 $ 4 ,7 6 2 ,8 0 0 $ 5 ,9 4 0 ,0 0 0 $ 9 ,3 2 1 ,4 0 0 $ 1 4 ,4 0 1 ,8 0 0 $ 1 5 ,5 4 4 ,8 0 0 $ 1 2 ,0 0 4 ,2 0 0 $ 1 0 ,6 8 7 ,5 0 0 $ 1 4 ,1 5 2 ,9 3 7 $ 1 5 ,0 5 9 ,3 8 2 $ 1 3 ,3 1 7 ,0 0 0 $ 1 3 ,4 3 2 ,0 0 0 $ 1 4 ,3 1 7 , 2 0 0 $ 1 4 ,1 8 1 ,2 0 0 $ 1 4 ,6 3 2 ,0 0 0 $ 1 4 ,7 7 5 ,2 0 0 $ 1 4 ,6 8 5 ,3 0 0 C a rro ts 1 9 7 0 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 4 ,8 0 0 5 ,2 0 0 4 ,8 0 0 6 ,1 0 0 6 ,0 0 0 5 ,8 0 0 6 ,0 0 0 5 ,6 0 0 6 ,1 0 0 6 ,6 0 0 5 ,6 0 0 5 ,6 0 0 6 ,7 0 0 7 ,2 0 0 7 ,5 0 0 6 ,4 0 0 3 ,7 0 0 7 ,0 0 0 6 ,7 0 0 6 ,8 0 0 6 ,7 0 0 C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. 1 ,1 0 4 1 ,2 2 2 1 ,0 0 8 1 ,5 2 4 1 ,3 2 7 1 ,1 3 3 1 ,6 4 1 1 ,3 0 1 1 ,6 1 4 1 ,7 1 3 1 ,3 4 0 1 ,3 1 6 1 ,7 0 9 1 ,6 5 6 2 ,0 2 5 1 ,6 6 4 925 1 ,9 2 5 1 ,7 0 9 1 ,6 6 6 1 ,8 7 6 230 235 210 250 2 21 195 274 232 265 260 239 235 255 230 270 260 250 275 255 245 280 $ 4 .8 3 $ 6 .9 0 $ 7 .5 3 $ 7 .1 2 $ 9 .0 5 $ 8 .2 7 $ 7 .7 0 $ 9 .8 3 $ 9 .6 9 $ 7 .8 8 $ 1 1 .7 0 $ 9 .4 3 $ 7 .5 3 $ 1 1 .2 0 $ 1 0 .1 0 $ 9 .7 6 $ 9 .9 3 $ 7 .3 6 $ 1 2 .5 0 $ 8 .4 3 $ 9 .2 0 $ 5 ,3 3 2 ,3 2 0 $ 8 ,4 3 1 ,8 0 0 $ 7 ,5 9 0 ,2 4 0 $ 1 0 ,8 5 0 ,8 8 0 $ 1 2 ,0 0 9 ,3 5 0 $ 9 ,3 6 9 ,9 1 0 $ 1 2 ,6 3 5 ,7 0 0 $ 1 2 ,7 8 8 ,8 3 0 $ 1 5 ,6 3 9 ,6 6 0 $ 1 3 ,4 9 8 ,4 4 0 $ 1 5 ,6 7 8 ,0 0 0 $ 1 2 ,4 0 9 ,8 8 0 $ 1 2 ,8 6 8 ,7 7 0 $ 1 8 ,5 4 7 ,2 0 0 $ 2 0 ,4 5 2 ,5 0 0 $ 1 6 ,2 4 0 ,6 4 0 $ 9 ,1 8 5 ,2 5 0 $ 1 4 ,1 6 8 ,0 0 0 $ 2 1 ,3 6 2 ,5 0 0 $ 1 4 ,0 4 4 ,3 8 0 $ 1 7 ,2 5 9 ,2 0 0 349 Total A c res H a rv e s te d P ro d u c tio n ( 0 0 0 's ) Dollars Per Unit V alue of P ro d u c tio n Commodity Year Cauliflow er 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1 ,2 0 0 800 800 930 1 ,0 0 0 1 ,1 0 0 700 1 ,0 0 0 1 ,1 0 0 1 ,1 0 0 1 ,0 0 0 1 ,2 0 0 1 ,5 0 0 1 ,4 0 0 1 ,5 0 0 1 ,5 0 0 700 1 ,2 0 0 1 ,1 0 0 1 ,2 0 0 1 ,0 0 0 C wt. C w t. Cw t. C w t. C w t. C w t. Cwt. C w t. C w t. C w t. C w t. C w t. Cw t. Cw t. Cw t. C w t. C w t. Cw t. Cw t. C w t. C w t. 79 49 44 38 51 49 39 50 55 77 50 74 87 77 98 98 39 72 61 72 70 66 61 55 41 51 45 56 50 50 70 50 62 58 55 65 65 56 60 55 60 70 $ 6 .7 0 $ 1 3 .0 0 $ 1 1 .7 5 $1 5 .6 9 $ 1 4 .7 0 $ 1 4 .5 0 $ 2 2 .0 0 $ 1 6 .6 0 $ 2 8 .5 0 $ 2 7 .7 0 $ 3 6 .5 0 $ 3 8 .6 0 $ 2 9 .5 0 $ 3 5 .3 0 $ 3 5 .1 0 $ 3 3 .9 0 $ 3 9 .5 0 $ 2 8 .8 0 $ 3 9 .0 0 $ 3 3 .0 0 $ 3 9 .4 0 $ 5 2 9 ,3 0 0 $ 6 3 7 ,0 0 0 $ 5 1 7 ,0 0 0 $ 5 9 6 ,2 2 0 $ 7 4 9 ,7 0 0 $ 7 1 0 ,5 0 0 $ 8 5 8 ,0 0 0 $ 8 3 0 ,0 0 0 $ 1 ,5 6 7 ,5 0 0 $ 2 ,1 3 2 ,9 0 0 $ 1 ,8 2 5 ,0 0 0 $ 2 ,8 5 6 ,4 0 0 $ 2 ,5 6 6 ,5 0 0 $ 2 ,7 1 8 ,1 0 0 $ 3 ,4 3 9 ,8 0 0 $ 3 ,3 2 2 ,2 0 0 $ 1 ,5 4 0 ,5 0 0 $ 2 ,0 7 3 ,6 0 0 $ 2 ,3 7 9 ,0 0 0 $ 2 ,3 7 6 ,0 0 0 $ 2 ,7 5 8 ,0 0 0 Celery 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 2 ,3 0 0 2 ,4 0 0 2 ,3 0 0 2 ,3 0 0 2 ,5 0 0 2 ,4 0 0 2 ,3 0 0 2 ,4 0 0 2 ,3 0 0 2 ,6 0 0 3 ,1 0 0 3 ,2 0 0 3 ,3 0 0 3 ,5 0 0 3 ,9 0 0 3 ,2 0 0 2 ,6 0 0 3 ,1 0 0 3 ,1 0 0 2 ,8 0 0 3 ,0 0 0 C w t. Cw t. Cw t. C w t. C w t. Cw t. C wt. C w t. C w t. C w t. Cw t. Cw t. C w t. C w t. Cwt. Cw t. C w t. C w t. Cw t. Cw t. C w t. 874 888 794 1 ,0 4 1 1 ,0 7 4 905 1 ,0 1 6 1 ,0 7 4 936 1 ,1 5 3 1 ,3 8 7 1 ,4 4 0 1 ,5 5 1 1 ,2 9 5 1 ,5 6 0 1 ,3 1 2 1 ,0 4 0 1 ,1 4 7 1 ,1 7 8 1 ,0 6 4 1 ,2 9 0 380 370 345 453 430 377 442 448 407 443 447 450 470 370 400 410 400 370 380 380 430 $ 5 .9 8 $ 6 .6 5 $ 7 .0 1 $ 7 .8 8 $ 7 .0 1 $ 7 .8 4 $ 8 .5 2 $ 8 .2 4 $ 1 4 .1 0 $ 9 .5 2 $ 9 .2 9 $ 1 1 .0 0 $ 1 0 .6 0 $ 1 2 .7 0 $ 9 .8 7 $ 1 0 .6 0 $ 1 4 .0 0 $ 1 1 .5 0 $ 1 3 .7 0 $ 1 3 .3 0 $ 9 .9 9 $ 5 ,2 2 6 ,5 2 0 $ 5 ,9 0 5 ,2 0 0 $ 5 ,5 6 5 ,9 4 0 $ 8 ,2 0 3 ,0 8 0 $ 7 ,5 2 8 ,7 4 0 $ 7 ,0 9 5 ,2 0 0 $ 8 ,6 5 6 ,3 2 0 $ 8 ,8 4 9 ,7 6 0 $ 1 3 ,1 9 7 ,6 0 0 $ 1 0 ,9 7 6 ,5 6 0 $ 1 2 ,8 8 5 ,2 3 0 $ 1 5 ,8 4 0 ,0 0 0 $ 1 6 ,4 4 0 ,6 0 0 $ 1 6 ,4 4 6 ,5 0 0 $ 1 5 ,3 9 7 ,2 0 0 $ 1 3 ,9 0 7 ,2 0 0 $ 1 4 ,5 6 0 ,0 0 0 $ 1 3 ,1 9 0 ,5 0 0 $ 1 6 ,1 3 8 ,6 0 0 $ 1 4 ,1 5 1 , 2 0 0 $ 1 2 ,8 8 7 ,1 0 0 Unit Yield 350 Total Commodity Year A c re s H a r v e s te d Unit P rod uc tio n ( 0 0 0 's ) Yield Dollars Per Unit Value of P ro d u c tio n S tr a w b e r r ie s 1970 197 1 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 5 ,8 0 0 5 ,2 0 0 4 ,0 0 0 3 ,4 0 0 3 ,1 0 0 3 ,0 0 0 2 ,9 0 0 2 ,8 0 0 2 ,8 0 0 2 ,8 0 0 2 ,7 0 0 2 ,7 0 0 2 ,7 0 0 2 ,7 0 0 2 ,7 0 0 2 ,5 0 0 2 ,4 0 0 2 ,4 0 0 2 ,3 0 0 2 ,2 0 0 2 ,2 0 0 C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. 255 250 212 150 177 195 232 196 210 196 176 176 216 162 189 163 144 144 127 117 143 44 48 53 44 57 65 80 70 75 70 65 65 80 60 70 65 60 60 55 53 65 $ 2 0 .1 0 $ 2 0 .2 0 $ 2 4 .6 0 $ 3 1 .5 0 $ 3 1 .1 0 $ 3 2 .7 0 $ 3 4 .0 0 $ 3 2 .0 0 $ 3 8 .0 0 $ 5 1 .2 0 $ 4 7 .5 0 $ 4 7 .1 0 $ 5 3 .1 0 $ 5 1 .9 0 $ 3 7 .4 0 $ 3 8 .7 0 $ 4 4 .2 0 $ 4 7 .1 0 $ 4 7 .9 0 $ 4 9 .0 0 $ 5 0 .5 0 $ 5 ,1 2 5 ,5 0 0 $ 5 ,0 5 0 ,0 0 0 $ 5 ,2 1 5 ,2 0 0 $ 4 ,7 2 5 ,0 0 0 $ 5 ,5 0 4 ,7 0 0 $ 6 ,3 7 6 ,5 0 0 $ 7 ,8 8 8 ,0 0 0 $ 6 ,2 7 2 ,0 0 0 $ 7 ,9 8 0 ,0 0 0 $ 1 0 ,0 3 5 ,2 0 0 $ 8 ,3 6 0 ,0 0 0 $ 8 ,2 8 9 ,6 0 0 $ 1 1 ,4 6 9 ,6 0 0 $ 8 ,4 0 7 ,8 0 0 $ 7 ,0 6 8 ,6 0 0 $ 6 ,3 0 8 ,1 0 0 $ 6 ,3 6 4 ,8 0 0 $ 6 ,7 8 2 ,4 0 0 $ 6 ,0 8 3 ,3 0 0 $ 5 ,7 3 3 ,0 0 0 $ 7 ,2 2 1 ,5 0 0 S nap Beans P ro c e s s in g 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1 98 1 1982 1983 1984 1985 1986 1987 1988 1989 1990 1 0 ,1 0 0 1 2 ,4 0 0 1 4 ,4 0 0 1 8 ,3 0 0 1 3 ,8 0 0 1 3 ,1 0 0 1 4 ,0 0 0 1 6 ,8 0 0 1 6 ,4 0 0 1 7 ,3 0 0 1 3 ,7 0 0 1 4 ,3 0 0 1 4 ,2 0 0 1 4 ,8 0 0 1 7 ,5 0 0 1 8 ,7 0 0 1 7 ,6 0 0 1 9 ,5 0 0 2 1 ,0 0 0 2 1 ,5 0 0 2 7 ,0 0 0 Tons Tons Tons Tons Tons Tons Tons Tons Tons Tons Tons Tons Tons Tons Tons Tons Tons Tons Tons Tons Tons 20 25 36 47 36 30 30 41 34 36 38 36 37 41 49 49 42 43 38 62 80 1 .9 8 2 .0 2 2 .5 0 2 .5 5 2 .5 8 2 .2 9 2 .1 7 2 .4 6 2 .1 0 2 .0 8 2 .8 0 2 .5 3 2 .5 8 2 .8 0 2 .8 0 2 .6 0 2 .4 0 2 .2 0 1 .8 0 2 .9 0 2 .9 5 $95 $91 $97 $102 $124 $129 $122 $125 $148 $162 $156 $160 $145 $144 $136 $158 $143 $149 $175 $166 $170 $ 1 ,8 9 4 ,0 0 0 $ 2 ,2 7 4 ,5 4 0 $ 3 ,4 8 4 ,8 0 0 $ 4 ,7 5 8 ,3 0 0 $ 4 ,4 1 4 ,4 0 0 $ 3 ,8 7 0 ,0 0 0 $ 3 ,7 0 8 ,8 0 0 $ 5 ,1 6 2 ,5 0 0 $ 5 ,0 9 8 ,6 0 0 $ 5 ,8 2 8 ,7 6 0 $ 5 ,9 7 4 ,8 0 0 $ 5 ,7 9 2 ,0 0 0 $ 5 ,3 0 7 ,0 0 0 $ 5 ,9 6 1 ,6 0 0 $ 6 ,6 6 4 ,0 0 0 $ 7 ,6 7 8 ,8 0 0 $ 6 ,0 3 4 ,6 0 0 $ 6 ,3 9 2 ,1 0 0 $ 6 ,6 1 5 ,0 0 0 $ 1 0 ,3 4 1 ,8 0 0 $ 1 3 ,5 4 0 ,5 0 0 351 Total A cres H a r v e s te d Unit P r o d u c tio n ( 0 0 0 ’s) Yield Dollars Per Unit V alue of P ro d u c tio n Com modity Year C ucum bers P r o c e s s in g 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 2 3 ,2 0 0 2 4 ,5 0 0 2 6 ,0 0 0 2 6 ,4 0 0 2 7 ,4 0 0 2 7 ,6 0 0 2 5 ,5 0 0 2 4 ,5 0 0 2 6 ,5 0 0 2 5 ,5 0 0 1 8 ,9 0 0 1 5 ,5 0 0 2 3 ,7 1 0 2 3 ,5 1 3 2 1 ,3 0 0 2 4 ,0 0 0 2 4 ,0 0 0 2 4 ,0 0 0 2 3 ,0 0 0 2 4 ,5 0 0 2 4 ,0 0 0 Tons Tons Tons Tons Tons Tons Tons Tons Tons Tons Tons Tons Tons Tons Tons Tons Tons Tons Tons Tons Tons 104 83 98 107 116 129 103 114 126 118 105 101 124 126 118 134 139 161 127 147 142 4 .4 8 3 .3 8 3 .7 6 4 .0 7 4 .2 3 4 .6 8 4 .0 5 4 .6 5 4 .7 5 4 .6 2 5 .5 6 6 .5 0 5 .2 3 5 .3 7 5 .5 2 5 .6 0 5 .8 0 6 .7 0 5 .5 0 6 .0 0 5 .9 0 $100 $92 $86 $88 $125 $124 $112 $109 $120 $132 $125 $135 $137 $141 $147 $158 $146 $139 $156 $168 $167 $ 1 0 ,3 5 3 ,4 2 0 $ 7 ,6 1 7 ,6 0 0 $ 8 ,3 9 1 ,2 4 0 $ 9 ,4 7 7 ,0 9 0 $ 1 4 ,4 8 7 ,5 0 0 $ 1 6 ,0 2 0 ,8 0 0 $ 1 1 ,5 6 9 ,6 0 0 $ 1 2 ,4 2 6 ,0 0 0 $ 1 5 ,1 2 0 ,0 0 0 $ 1 5 ,5 5 0 ,9 2 0 $ 1 3 ,1 3 5 ,0 0 0 $ 1 3 ,6 0 1 ,2 5 0 $ 1 6 ,9 7 9 ,7 7 5 $ 1 7 ,7 4 6 ,5 9 0 $ 1 7 ,2 7 2 ,5 0 0 $ 2 1 ,2 3 5 ,2 0 0 $ 2 0 ,3 2 3 ,2 0 0 $ 2 2 ,3 5 1 ,2 0 0 $ 1 9 ,7 3 4 ,0 0 0 $ 2 4 ,6 9 6 ,0 0 0 $ 2 3 ,6 4 7 ,2 0 0 T om atoes P r o c e s s in g 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 3 ,3 0 0 4 ,3 0 0 4 ,0 0 0 3 ,6 0 0 5 ,3 0 0 4 ,4 0 0 4 ,0 0 0 4 ,1 0 0 4 ,5 0 0 5 ,6 0 0 6 ,0 0 0 6 ,2 0 0 9 ,7 0 0 9 ,2 0 0 7 ,4 0 0 6 ,6 0 0 5 ,4 0 0 5 ,0 0 0 5 ,2 0 0 5 ,4 0 0 5 ,7 0 0 Tons Tons Tons Tons Tons Tons Tons Tons Tons Tons Tons Tons Tons Tons Tons Tons Tons Tons Tons Tons Tons 55 65 54 53 60 63 75 64 81 101 74 118 205 183 174 166 133 119 112 133 170 1 6 .7 15.1 1 3 .4 1 4 .8 1 1 .4 1 4 .4 1 8 .6 1 5 .5 1 8 .0 18.1 1 2 .3 19.1 2 1 .1 1 9 .9 2 3 .5 2 5 .2 2 4 .7 2 3 .7 2 1 .6 2 4 .6 2 9 .8 $ 3 6 .9 0 $ 3 7 .3 0 $ 3 7 .5 0 $ 4 3 .4 0 $ 6 9 .3 0 $ 6 4 .0 0 $ 6 5 .2 0 $ 6 5 .8 0 $ 6 7 .3 0 $ 6 8 .3 0 $ 7 2 .9 0 $ 8 6 .0 0 $ 9 2 .6 0 $ 8 4 .0 0 $ 8 4 .0 0 $ 8 0 .0 0 $ 7 6 .0 0 $ 6 9 .2 0 $ 6 8 .2 0 $ 7 2 .8 0 $ 7 5 .5 0 $ 2 ,0 3 5 ,0 3 5 $ 2 ,4 2 6 ,3 6 5 $ 2 ,0 1 0 ,0 0 0 $ 2 ,3 1 7 ,5 6 0 $ 4 ,1 8 5 ,7 2 0 $ 4 ,0 5 1 ,2 0 0 $ 4 ,8 5 7 ,4 0 0 $ 4 ,1 7 8 ,3 0 0 $ 5 ,4 6 4 ,7 6 0 $ 6 ,9 2 6 ,9 8 6 $ 5 ,3 6 5 ,4 4 0 $ 1 0 ,1 7 3 ,8 0 0 $ 1 8 ,9 4 5 ,9 6 0 $ 1 5 ,3 7 2 ,0 0 0 $ 1 4 ,6 0 7 ,6 0 0 $ 1 3 ,3 0 4 ,0 0 0 $ 1 0 ,1 3 0 ,8 0 0 $ 8 ,2 0 0 ,2 0 0 $ 7 ,6 5 8 ,8 6 0 $ 9 ,6 6 7 ,8 4 0 $ 1 2 ,8 2 4 ,4 3 0 352 Total A c re s H a r v e s te d Unit P r o d u c tio n ( 0 0 0 ’s) Yield Dollars Per Unit Value of P ro d u c tio n C o m m o d ity Y ear S w e e t Corn 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1 2 ,7 0 0 1 2 ,0 0 0 1 2 ,2 0 0 1 2 ,1 0 0 1 2 ,0 0 0 1 2 ,0 0 0 1 2 ,3 0 0 1 2 ,3 0 0 1 1 ,7 0 0 1 1 ,5 0 0 1 1 ,5 0 0 1 2 ,0 0 0 1 3 ,0 0 0 1 2 ,8 0 0 1 2 ,3 0 0 12 ,0 0 0 11 ,7 0 0 1 1 ,5 0 0 9 ,0 0 0 1 1 ,8 0 0 1 2 ,5 0 0 C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. 1 ,0 1 6 876 854 781 617 728 701 775 702 667 771 732 858 896 800 780 702 713 540 802 788 80 73 70 65 51 61 57 63 60 58 67 61 66 70 65 65 60 62 60 68 63 $ 3 .1 3 $ 4 .6 0 $ 4 .1 6 $ 5 .3 5 $ 7 .8 5 $5 .7 1 $ 7 .3 3 $ 7 .0 7 $ 9 .2 8 $ 8 .2 8 $ 8 .9 2 $ 9 .8 4 $ 8.8 1 $ 1 1 .1 0 $ 1 0 .8 0 $ 1 2 .4 0 $ 1 0 .5 0 $ 1 0 .2 0 $ 1 6 .9 0 $ 1 7 .5 0 $ 1 4 .3 0 $ 3 ,1 8 0 ,0 8 0 $ 4 ,0 2 9 ,6 0 0 $ 3 ,5 5 2 ,6 4 0 $ 4 ,1 7 8 ,3 5 0 $ 4 ,8 4 3 ,4 5 0 $ 4 ,1 5 6 ,8 8 0 $ 5 ,1 3 8 ,3 3 0 $ 5 ,4 7 9 ,2 5 0 $ 6 ,5 1 4 ,5 6 0 $ 5 ,5 2 2 ,7 6 0 $ 6 ,8 7 7 ,3 2 0 $ 7 ,2 0 2 ,8 8 0 $ 7 ,5 5 8 ,9 8 0 $ 9 ,9 4 5 ,6 0 0 $ 8 ,6 4 0 ,0 0 0 $ 9 ,6 7 2 ,0 0 0 $ 7 ,3 7 1 ,0 0 0 $ 7 ,2 7 2 ,6 0 0 $ 9 ,1 2 6 ,0 0 0 $ 1 4 ,0 3 5 ,0 0 0 $ 1 1 ,2 6 8 ,4 0 0 L e ttu c e 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1 ,5 0 0 1 ,6 0 0 1 ,5 0 0 1 ,4 0 0 1 ,5 0 0 1 ,3 0 0 1 ,4 0 0 1 ,3 0 0 1 ,3 0 0 1 ,4 0 0 1 ,2 0 0 1 ,2 0 0 1 ,5 0 0 1 ,2 0 0 1 ,1 0 0 1 ,2 0 0 1 ,2 0 0 1 ,0 0 0 800 1 ,1 0 0 900 C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. C w t. 263 328 255 273 263 19 5 238 260 286 280 252 258 375 228 259 300 240 215 140 209 207 175 205 170 195 175 150 170 200 220 200 210 215 250 190 235 250 200 215 175 190 230 $ 6 .1 4 $ 6 .2 7 $ 5 .7 6 $ 7 .6 8 $ 8 .6 0 $ 9 .6 7 $ 1 3 .9 0 $ 9 .6 0 $ 1 3 .7 0 $2 2 .0 0 $ 1 9 .3 0 $ 1 8 .0 0 $ 1 3 .8 0 $ 1 5 .0 0 $ 1 5 .7 0 $ 1 7 .5 0 $ 1 6 .7 0 $ 2 0 .2 0 $ 1 8 .9 0 $ 2 0 .4 0 $ 2 2 .3 0 $ 1 ,6 1 4 ,8 2 0 $ 2 ,0 5 6 ,5 6 0 $ 1 ,4 6 8 ,8 0 0 $ 2 ,0 9 6 ,6 4 0 $ 2 ,2 6 1 ,8 0 0 $ 1 ,8 8 5 ,6 5 0 $ 3 ,3 0 8 ,2 0 0 $ 2 ,4 9 6 ,0 0 0 $ 3 ,9 1 8 ,2 0 0 $ 6 ,1 6 0 ,0 0 0 $ 4 ,8 6 3 ,6 0 0 $ 4 ,6 4 4 ,0 0 0 $ 5,1 7 5 , 0 0 0 $ 3 ,4 2 0 ,0 0 0 $ 4 ,0 6 6 ,3 0 0 $ 5 ,2 5 0 ,0 0 0 $ 4 ,0 0 8 ,0 0 0 $ 4 ,3 4 3 ,0 0 0 $ 2 ,6 4 6 ,0 0 0 $ 4 ,2 6 3 ,6 0 0 $ 4 ,6 1 6 ,1 0 0 no o 3 5' 1— 1 _1 o _» CO CO CO 03 00 00 00 v j 03 NO NJ N cn ** _k _k _t _A •A _A CO CO CO CD CO CD CD CD CD CD CD CD CD CD CD CD * sj v l 0 0 0 0 CO 0 0 0 0 CD v l V j v j vj vl vl vl GJ NJ — CO CO r o CD 0 0 v l 0 5 A N J CO CO P *o cn o CO CO CO CO CO CO CO A A _A A A CO CO CCCO CO CDCOCOCOCOCOCOCOCOCOCOCOCOCOCOCOCOCO c o o o o o o o o o c o c o o o o o c o o o v i v i v i v i v i v i v i v i v i v i -< (S CD OlD00Nl0)Ul^UtO-‘ O r * ^4 r-+ a u> bo 'o N J cd 'co 01 A A A b CO 'co CO A 'ro 03 'co Oo o o o Oo o o o o o o o o o OOOOo o o o o o o o o o o o o o o o o Oo o o o lr o 3 r in — . CO CO CO 0 0 CO 3 3 CO 'o b o o o o O O v l CO CD O O O O O O o o o o O O o O O O O O vj O o A O O o o o o O O o o o o o o I ;“ V > % °-I C D (/) CO C/i CO a. c 3 TJ CD cn CD ro N J N J N J rororo ro ro roro • a ro V ro o CO b > cn CD cncncn 0 3 b b ro'rovj 'o b > N J o o cn CD CD vj O J 0 3 o o o o o v l CD 0 3 CO A A O N J N J o o CD c n CD CD o o o 0 3 0 3 ro v l CO CO 0 3 a CD NJ NJ NJ CO M IO ro ro CO A CO A CO CO A CO CO A CO CO A A CO A O CD O 01 03 ro ro CO o CO v l O v i CO O 03 CO CD — iCO — * o o A ro 01 o o 0 3 CO —* A 03 00 o CD v i 03 CO O CO o o o o ro —* CD CO CO o ro ro ro o o CO CO CD O o O Ol O U1 o O O CD CD o o CD o CD O O CD O CD CD in in in < />< />< />in < />in < />■ />iff— oo < />< />< /► />< i ‘< — 1 t roro N roroCO roro — Jro ro JN j P 00< OCD Ao -* N D-t*Acn00N Jcn p CO CO o C O »vj CD cn00in b b b vi roo b C Orobo b) cjl cnL o o o Oo OOo o OOOo o o o o o Oo o a i ch 03 03 CD 03 CD ro CO CO » ro CD * O CO —* A O o o 03 CD — » A — — o o o O O O O O O 03 O O CD O O O O —I __ _A in in i n i n i n i n i n i n co- i n i n CO O •v l 03 03 CD 03 03 CD A CO CD — * ro O CO CO v l CD CO 03 CO CO k A > ■O 03 A 03 CO CO ro CO ro CO CO O 00 » CO v l A v l V i co CO in _i vj CO ro 00 o co ro co 03 v j 00 O 03 oo o o o o o o o — CD O O o 03 03 O o O O o o O O o — CD 03 O CO O O O O o O O O O o o — o O o O o NJ ro ro ro •a ro CD NJ o cn o o o o o o cno O CO CO CO CO CO CD CD N J N J NO N J CD CD CD CD CD CD 0 0 CD N J N J CD CD A A CO 0 3 —1 CD CD CD O O O O cn cn oo o cncn i f f if f iff ■o iff if f i f f iff CD —» N J CD i n i n a i 03 _» 03 O ro if f cn v l cn o if f i f f i f f •v> in i n __ * — A —k «■ ro -» 03 ro CO 03 P A b Ol A A CD A 'oo 00 v j A v l CD 03 03 ro v j CO M A ro IO CO 03 —* ro 03 03 03 A ro CD 00 p ro •A to 05 IN "U I£ c c n re CD 354 Commodity Year M ushroom s 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 Area H a rv e s te d 1 , 0 0 0 Sq. Ft. 7 ,3 6 3 ,0 0 0 5 ,2 9 2 ,0 0 0 5 ,9 1 1 ,0 0 0 4 ,7 0 9 ,0 0 0 4 ,5 0 4 ,0 0 0 4 ,0 6 0 ,0 0 0 4 ,4 0 0 ,0 0 0 4 ,2 7 9 ,0 0 0 4 ,4 9 8 ,0 0 0 4 ,0 1 0 ,0 0 0 Unit lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. lbs. Total P ro d u c tio n ( 0 0 0 's ) 2 1 ,2 2 1 1 9 ,0 4 4 1 8 ,8 6 5 1 7 ,5 0 6 1 9 ,5 0 1 2 0 ,1 7 1 2 0 ,3 0 6 2 3 ,3 5 9 2 2 ,5 1 2 1 9 ,4 0 8 Yield 2 .8 8 3 .6 0 3 .1 9 3 .7 2 4 .3 3 4 .9 7 4 .6 2 5 .4 6 5 .0 0 4 .8 4 Dollars Per Unit $ 0 .7 7 $ 0 .7 1 $ 0 .8 3 $ 0 .9 4 $ 0 .8 4 $ 0 .8 3 $ 0 .8 7 $ 0 .8 9 $ 0 .9 2 $ 1 .0 2 Value of Production $ 1 6 ,3 1 8 ,9 4 9 $ 1 3 ,4 4 5 ,0 6 4 $ 1 5 ,6 5 7 ,9 5 0 $ 1 6 ,3 6 8 ,1 1 0 $ 1 6 ,2 8 3 ,3 3 5 $ 1 6 ,7 6 2 ,1 0 1 $ 1 7 ,7 2 7 ,1 3 8 $ 2 0 ,7 1 9 ,4 3 3 $ 2 0 ,6 6 6 ,0 1 6 $ 1 9 ,7 9 6 ,1 6 0 A c re s TOTAL 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 88,100 9 1 ,9 0 0 9 5 .0 0 0 1 0 0 ,7 3 0 1 0 0 ,9 0 0 9 9 ,6 0 0 9 8 .8 0 0 1 0 1 .4 0 0 1 0 3 .7 0 0 1 0 5 ,2 0 0 9 3 .8 0 0 9 2 .0 0 0 6 4 ,1 0 0 6 4 ,4 0 0 1 0 6 .4 0 0 1 0 6 ,3 0 0 9 8 ,5 0 0 1 0 7 .1 0 0 1 0 5 .1 0 0 1 1 0 .7 0 0 1 1 6 .4 0 0 $ 4 8 ,0 8 9 ,9 9 5 $ 5 3 ,7 7 1 ,5 6 5 $ 6 2 ,6 4 0 ,8 6 0 $ 7 3 ,9 5 9 ,8 2 0 $ 8 0 ,6 9 7 ,8 6 0 $ 7 6 ,3 9 9 ,0 4 0 $ 8 9 ,3 2 3 ,8 5 0 $ 8 8 ,2 0 1 ,0 4 0 $ 1 0 8 ,9 5 4 ,2 8 0 $ 1 1 2 ,9 2 4 ,1 2 6 $ 1 1 5 ,1 2 6 ,5 9 0 $ 1 2 4 ,0 4 9 ,8 1 0 $ 1 0 1 ,1 7 2 ,2 1 0 $ 1 2 2 ,3 1 9 ,4 0 0 $ 1 4 0 ,0 1 0 ,5 0 0 $ 1 3 0 ,0 1 8 ,1 4 0 $ 1 1 5 ,0 6 5 ,8 5 0 $ 1 2 2 ,9 6 8 ,4 0 0 $ 1 3 0 ,2 7 3 ,2 6 0 $ 1 3 8 ,1 5 7 ,0 2 0 $ 1 4 2 ,3 4 2 ,7 3 0 Appendix B Regression Results for C h a p te r IV Trend Analysis A ppendix B R egression R esults for Chapter IV Estimated Trends: Linear (L) and Exponential (E)189 General O v e rv iew T r e n d F u n c ti o n R£ N u m b e r o f F a r m s : (L) N u m b e r o f F a r m s : (E) NF, = 8 2 , 3 1 0 - 1 , 4 0 9 T NF, = 8 3 , 3 7 8 x 0 . 9 7 9 3 T .9 4 6 5 .9 6 0 6 * L a n d in F a r m s : AH, = 5 , 9 1 7 , 7 2 8 + 5 7 , 0 1 5 T AH, = 5 , 8 8 9 , 0 8 0 x 1 . 0 0 9 2 T .2 6 7 6 * .2 4 7 9 V a lu e o f P r o d u c tio n : (L) V a lu e of P r o d u c tio n : (E) VP, = 9 1 0 , 0 2 1 + 2 3 8 . 7 6 5 T VP, = 1 , 1 8 8 , 9 2 6 x 1 . 0 8 9 8 T .8 0 7 3 * .6 0 6 6 A c r e s H a r v e s t e d : (L) A c r e s H a r v e s t e d : (E) AH, = 1 4 , 0 2 9 + 1 . 4 3 9 T AH, = 1 6 , 9 4 7 x 1 . 0 4 7 4 T .6 7 7 1 .7 0 4 5 ' Q u a n t ity P r o d u c e d : (L) Q u a n tit y P r o d u c e d : (E) QP, = 5 7 4 , 3 6 7 + 9 1 , T QP, = 7 8 2 , 3 9 4 x 1 , 0 5 6 8 T .5 8 7 4 .5 9 2 6 * Yield: (L) Yield: (E) Y, = 4 5 . 5 + 0 . 5 4 0 3 T Y, = 4 5 . 9 x 1 . 0 0 9 4 T .1 7 3 0 * .1 6 3 6 Price: (L) Price: (E) P, = 1 .8 1 + 0 . 0 4 5 5 T P, = 1 . 5 2 x 1 .0 3 1 2 T .1 1 9 5 * .0115 B arley 189 Note: the linear or exponential equations with the (*) designation, represent the calculated "best fit" correlation coefficient R2 for each commodity category, and the "best fit" trend utilized in the graphical analysis chapter four. 355 356 C o m for Grain Trend Function Value of P roduction: (L) Value of P roduction: (E) VP, = 2 7 3 , 7 4 5 , 6 8 8 + 1 4 , 7 2 1 , 3 3 8 T VP, = 2 3 6 , 0 7 3 , 7 7 7 x 1 . 0 4 7 8 T .2 6 2 7 ' A c r e s H a r v e s t e d : (L) A c r e s H a r v e s t e d : (E) AH, = 1 , 9 4 3 , 8 4 8 + 2 0 . 6 9 4 T AH, = 1 , 8 9 9 , 1 1 9 x 1 . 0 1 0 5 T .0 9 0 9 ' .0 6 8 9 Q u a n t i t y P r o d u c e d : (L) Q u a n t i t y P r o d u c e d : (E) QP, = 1 3 7 , 5 1 0 , 4 0 0 + 5 , 2 2 9 , 1 1 9 T QP, = 1 3 5 , 6 1 1 , 0 6 4 x 1 . 0 2 9 1 T .3008* .2 4 6 2 Yield: (L) Yield: (E) Y, = Y, = 7 0 .5 + 1 .6 4 5 5 T 7 1 .4 x 1 .0 1 8 5 T .4 5 5 1 ' .4 5 1 5 Price: (L> Price: (E) P, = P, = 1 .8 8 + 0 .0 2 9 0 T 1 .7 4 x 1 .0 1 8 1 T .0 9 8 1 ' .0 5 1 1 .1 1 1 9 C o rn S ila g e A c r e s H a r v e s t e d : (L) A c r e s H a r v e s t e d : (E) AH, = 4 2 0 , 2 7 6 - 3 , 7 2 2 T AH, = 4 1 7 , 1 4 9 x 0 . 9 9 0 3 T .1 5 1 8 ' .1 4 0 0 Q u a n t i t y P r o d u c e d : (L) Q u a n tit y P r o d u c e d : (E) QP, = 4 , 9 3 7 , 6 6 7 - 2 7 . 2 3 4 T QP, = 2 4 6 3 . 1 x 2 6 . 7 0 T .0 7 5 9 ' .0 6 5 0 Yield: (L) Yield: (E) Y, = 1 1 . 7 7 + 0 . 0 5 7 1 T Y, = 1 1 . 7 7 x 1 . 0 0 3 7 T .0 4 3 1 * .0 3 4 7 V alu e of P r o d u c tio n : (L) V a lu e o f P r o d u c tio n : (E) VP, = 1 0 1 , 1 9 6 , 2 0 7 + 1 1 6 , 5 6 8 T VP, = 9 3 , 4 8 9 , 6 1 8 x 1 . 0 0 3 1 T .0 0 0 4 .0 2 5 9 ' A c r e s H a r v e s t e d : (L) A c r e s H a r v e s t e d : (E) AH, = 6 4 2 , 8 5 7 - 1 5 , 8 4 4 T AH, = 6 8 9 , 9 8 0 x 0 . 9 6 1 9 T .6 7 8 1 ' .6137 Q u a n t i t y P r o d u c e d : (L) Q u a n t i t y P r o d u c e d : (E) QP, = 6 , 7 7 3 , 1 1 0 - 1 1 0 , 4 9 5 T QP, = 7 , 0 0 7 , 9 2 2 x 0 . 9 7 5 4 ' .2 1 3 6 ' .1 6 8 9 Yield: (L) Yield: (E) Y, = 1 , 0 0 5 . 7 + 1 7 . 7 5 T Y, = 2 4 6 3 . 1 x 1.01 4 0 t .2 7 9 0 ' .2 7 5 4 Price: (L) Price: (E) P, = 1 4 . 2 6 + 0 . 4 5 2 2 T P, = 1 3 . 3 4 x 1 . 0 2 8 4 T .1 9 0 1 ' .1 5 5 6 Dry B e a n s 357 Hay Trend Function Value of Production: (L) Value of P roduction: (E) VP, = 3 9 , 4 0 6 , 5 4 8 + 1 5 , 2 7 4 , 3 7 0 T VP, = 7 5 , 3 6 3 , 1 6 4 x 1 . 0 8 4 3 T .8 9 6 3 * .8 7 0 9 A c r e s H a r v e s t e d : (L) A c r e s H a r v e s te d : (E> AH, = 1 , 2 1 8 . 3 8 1 + 1 9 , 8 4 4 T AH, = 1 , 2 3 3 , 4 4 6 x 1 . 0 1 3 2 T .4 1 3 2 .4 1 6 7 ' Q u a n t ity P r o d u c e d : (LI Q u a n tit y P r o d u c e d : (E) QP, = 2 , 5 8 6 , 7 0 0 + 1 3 1 , 7 8 1 T QP, = 2 , 7 3 4 , 0 3 9 x 1 . 0 3 3 5 T .7 1 6 6 ' .7 0 8 3 Yield: (L) Yield: (E) Y, = 2 . 1 8 + 0 . 0 5 5 4 T Y, = 2 . 2 2 x 1 . 0 2 0 0 T .5 4 0 4 ' .5 2 7 6 Price: (L) Price: (E) P, = 2 4 . 3 5 + 2 . 2 9 2 9 T P, = 2 7 . 4 1 x 1 , 0 5 0 0 T .6 9 9 9 ' .6 8 2 1 V alu e of P r o d u c tio n : (L) V a lu e o f P ro d u c tio n : (E) VP, = 2 4 , 5 3 0 , 2 2 6 + 2 3 7 . 1 3 2 T VP, = 2 3 , 2 1 5 , 5 2 2 x 1 . 0 0 9 5 T .0 2 9 0 .0 5 5 9 ' A c r e s H a r v e s t e d : (L) A c r e s H a r v e s te d : (E) AH, = 4 1 4 , 4 5 2 - 6 . 6 9 5 T AH, = 4 2 2 , 6 1 2 x , 9 7 8 9 T .3 9 0 8 ' .3 7 0 7 Q u a n t i t y P r o d u c e d : (L) Q u a n t i t y P r o d u c e d : (E) QP, = 2 2 , 2 4 6 , 0 7 1 - 2 5 8 , 3 1 8T QP, = 2 2 , 9 8 1 , 6 7 6 x , 9 8 1 2 T .1 0 9 6 ' .0 6 3 7 Yield: (L) Yield: (E) V, Y. 5 3 .9 + 0 .2 3 3 8 T 5 4 .4 x 1 .0 0 2 3 T .0 3 2 5 ' .0 1 8 5 Price: (L) Price: (E) P, = 1 . 0 5 + 0 . 0 3 6 2 T P, = 1 .01 x 1 , 0 2 8 8 T .2 5 2 9 ' .2 0 4 8 V a lu e o f P r o d u c tio n : (L) V a lu e of P r o d u c tio n : (E) VP, = 2 8 , 4 8 7 , 7 8 9 + 2 , 4 8 6 , 0 7 6 T VP, = 3 0 , 7 9 4 , 4 9 9 x 1 , 0 5 0 2 T .7 3 1 0 ' .6 8 1 1 A c r e s H a r v e s te d : (L) A c r e s H a r v e s te d : (E) AH, = 4 1 , 2 9 4 + 2 7 5 T AH, = 4 1 , 2 6 0 x 1 . 0 0 5 9 T .0 9 5 1 ' .0 9 0 5 Q u a n t i t y P r o d u c e d : (L) Q u a n t i t y P r o d u c e d : (E) QP, = 9 , 1 4 9 , 2 1 9 + 1 4 0 . 8 8 1 T QP, = 9 , 1 8 6 , 4 5 8 x 1 . 0 1 2 8 T .2 2 4 0 ' .2 1 4 7 Yield: (L) Yield: (E) Y, = 2 2 3 . 3 + 1 . 4 8 7 0 T Y, = 2 2 3 . 5 x 1 . 0 0 6 1 T .3 2 0 0 * .3 1 5 9 Price: (L| Price: (E) P, = 3 .3 1 + 0 . 1 7 2 9 T P, = 3 . 3 5 x 1 . 0 3 7 0 T .5 2 6 3 ' .5 0 8 6 O ats All P o t a t o e s 358 Soybeans Trend Function R2 Value of P roduction: (L) Value of Production: (E) VP, = 4 0 , 1 3 6 , 7 1 9 + 10 , 3 3 7 , 9 5 4 T VP, = 4 9 , 3 4 6 , 3 5 2 x 1 , 0 9 2 9 T .7 4 4 0 * .5 2 5 8 A c r e s H a r v e s t e d : (L) A c r e s H a r v e s t e d : (E) AH, = 4 8 7 , 5 6 7 + 3 6 , 3 3 4 T AH, = 5 1 7 , 2 8 1 x 1 . 0 4 6 2 T .8 1 8 5 * .7 4 1 2 Q u a n tit y P r o d u c e d : (L) Q u a n t i t y P r o d u c e d : (E) QP, = 9 , 0 3 8 , 0 1 9 + 1 , 5 8 1 , 3 0 1 T QP, = 1 1 , 4 3 8 , 9 9 7 x 1 , 0 7 0 2 T .8 7 4 7 * .8 0 0 3 Yield: (L) Yield: (E> Y, = 2 1 . 7 + 0 . 6 4 4 2 T Y, = 2 2 .1 x 1 , 0 2 3 0 T .6 2 8 6 .6 3 1 4 * Price: (L) Price: (E) P, = 4 . 6 3 + 0 . 0 8 9 6 T P, = 4 . 3 2 x 0 . 1 1 6 0 T .1 7 1 2 * .1160 V a lu e o f P r o d u c tio n : (L) V a lu e of P r o d u c tio n : (E) VP, = 1 6 , 5 8 1 , 0 2 3 + 4 , 0 2 3 , 1 7 8 T VP, = 2 3 , 9 7 8 , 8 3 9 x 1 , 0 7 6 8 T .8 0 2 6 .8 2 4 2 * A c r e s H a r v e s t e d : (L) A c r e s H a r v e s t e d : (E) AH, = 6 7 , 9 1 4 + 3 . 3 5 5 T AH, = 7 3 , 6 9 3 x 1 . 0 3 0 5 1 .7 6 7 8 .8 1 5 4 * Q u a n t i t y P r o d u c e d : (L) Q u a n t i t y P r o d u c e d : (E) QP, = 1 , 2 5 8 , 6 8 1 + 6 6 . 8 4 3 T QP, = 1 , 3 6 5 , 0 9 4 x 1 , 0 3 2 6 T .7140 .7 5 7 5 * Yield: (L) Yield: (E) Y, = 1 8 . 6 + 0 . 0 3 8 1 T Y, = 1 8 . 5 x 1 , 0 0 2 0 T .0 2 3 4 * .0 2 1 8 Price: (L) Price: (E) P, = 1 9 . 2 8 + 0 . 9 5 7 5 T P, = 1 7 . 5 7 x 1 . 0 4 3 0 T .3 5 6 9 * .2 8 3 3 V a lu e o f P ro d u c tio n : (L) V a lu e o f P r o d u c tio n : (E) VP, = 6 2 , 6 8 2 , 6 9 6 + 2 , 6 2 8 , 7 0 2 T VP, = 5 0 , 1 5 9 , 9 5 0 x 1 . 0 4 5 1 T .1 7 8 8 * .0 4 8 8 A c r e s H a r v e s t e d : (L) A c r e s H a r v e s t e d : (E) AH, = 6 6 7 , 1 1 0 + 1 , 3 3 6 T AH, = 6 3 7 , 2 6 6 x 1 . 0 0 3 5 T .0 0 2 7 .0 2 3 3 * Q u a n t i t y P r o d u c e d : (L) Q u a n tit y P r o d u c e d : (E) QP, = 2 3 , 4 2 4 , 3 5 7 + 6 4 4 . 2 1 4 T QP, = 2 2 , 6 0 5 , 5 9 6 x 1 , 0 2 3 2 T .1 8 6 6 * .1 5 3 4 Yield: (L) Yield: (E) Y, = 3 4 . 8 + 0 . 8 7 2 7 T Y, = 3 5 . 5 x 1 . 0 1 9 6 T .5 7 4 3 * .5 7 0 5 Price: (L) Price: VP, = 4 7 , 5 2 1 , 2 1 9 + 9 7 4 , 5 4 3 T VP, = 4 6 , 2 6 8 , 6 5 4 x 1 , 0 1 9 3 T .3 1 0 6 ’ .2 6 9 6 N u m b e r o f H e a d : (L) N u m b e r o f H e a d : (E) NH, = 6 , 6 5 1 , 8 6 7 - 2 5 . 9 4 0 T NH, = 6 , 6 6 8 , 2 5 3 x 0 . 9 9 5 6 T .1 8 1 1 ’ .1 7 6 5 Q u a n t i t y P r o d u c e d : (L) Q u a n t i t y P r o d u c e d : (E) QP, = 1 , 4 5 5 , 4 0 0 , 0 0 0 + 4 , 8 0 7 , 7 9 2 T QP, = 1 , 4 5 4 , 6 4 4 , 8 5 7 x 1 . 0 0 3 1 T .1112’ Yield: (L) Yield: (E| Y, = 2 1 7 . 7 + 1 . 7 9 0 5 T Y, = 2 1 8 . 1 x 1 . 0 0 7 5 T .5 7 0 2 .5 7 5 5 ’ Price: (L) Price: (E) P, = 0 . 3 9 2 6 + 0 . 0 0 6 5 T P, = 0 . 3 8 1 7 x 1 .01 6 1 T .2 0 6 7 ’ .1 7 9 2 S h eep and Lam bs Layers .1 0 9 7 361 C hick ens Trend Function Value of P roduction: (L) Value of Production: (E) VP, = 2 , 5 0 5 , 9 4 9 - 2 4 , 7 3 3 T VP, = 2 , 4 2 7 , 2 9 9 x 0 . 9 8 9 5 T .0 3 5 3 ' .0233 N u m b e r o f H e a d : (L) N u m b e r o f H e a d : (E) NH, = 5 , 2 9 7 , 7 4 3 - 1 8 . 1 3 2 T NH, = 5 , 2 7 8 , 5 0 7 x 0 . 9 9 6 2 T .0 3 5 3 ' .0 2 8 8 Q u a n t i t y P r o d u c e d : (L) Q u a n t i t y P r o d u c e d : (E) OP, = 2 1 , 7 4 4 , 7 0 6 - 2 2 , 8 8 2 T QP, = 2 1 , 7 4 3 , 5 0 7 x 0 . 9 9 8 6 T .0 0 3 9 ' .0 0 1 7 Price: (L) Price: (E) P, = 0 . 0 9 8 6 + 0 . 0 0 0 4 T P, = 0 . 0 9 7 0 x 1 , 0 0 3 7 T .0 1 3 3 ' .0 0 2 6 V a lu e o f P r o d u c tio n : (L) V a lu e o f P r o d u c tio n : (E) VP, = 1 , 3 5 0 , 2 8 7 - 2 , 0 3 2 T VP, = 1 , 1 8 6 , 7 3 6 x 1 , 0 0 5 6 t .0 0 0 4 .0 2 8 9 ' N u m b e r o f H e a d : (L) N u m b e r o f H e a d : (E) NH, = 9 0 1 , 6 1 2 + 6 , 5 2 7 T NH, = 7 9 9 , 6 9 1 x 1 , 0 1 0 2 T .0075 .0 4 3 5 ' Q u a n t i t y P r o d u c e d : (L) Q u a n t i t y P r o d u c e d : (E) QP, = 5 , 0 6 5 , 9 5 6 - 7 2 , 5 0 5 T QP, = 4 , 6 0 8 , 0 0 9 x 0 . 9 8 7 6 T .0 3 5 2 ' .0 0 5 3 P rice: (L) Price: (E) P, = 0 . 1 9 7 8 + 0 . 0 0 7 5 T P, = 0 . 1 9 9 6 x 1 . 0 2 9 5 T .7 3 3 7 ' .6 8 6 9 V a lu e of P r o d u c tio n : (L) V a lu e o f P r o d u c tio n : (E) VP, = - 3 5 3 , 5 4 2 + 2 , 3 1 5 , 9 2 9 T VP, = 5 , 8 0 8 , 1 9 0 x 1 , 1 2 5 7 t .8 9 2 6 .9 3 9 2 ' N u m b e r o f H e a d : (L) N u m b e r o f H e a d : (E) NH, = 2 8 8 , 9 0 8 + 1 7 5 , 1 3 8 T NH, = 7 3 7 , 5 4 2 x 1 , 0 9 4 3 T .8 8 4 5 .9 6 3 2 ' Q u a n t i t y P r o d u c e d : (L) Q u a n t i t y P r o d u c e d : (E> QP, = 2 , 0 1 4 , 4 5 1 + 5 , 2 0 5 , 7 6 0 T QP, = 1 6 , 8 1 8 , 0 9 8 x 1 . 1 0 7 4 T .8 6 4 2 .9 6 1 2 ' Price: (L) Price: (E) P, = 0 . 3 5 1 2 + 0 . 0 0 6 2 T P, = 0 . 3 4 5 4 x 1 .0 1 6 6 T .2 0 1 8 .2 2 5 6 ' Broilers T urkeys 362 Fruit Overv iew T o ta l T rend Function V a lu e of P ro d u c tio n : (L) V a lu e o f P ro d u c tio n : (E) VP, = VP, = A c r e s H a r v e s te d : (L) A c r e s H a r v e s te d : (E) AH, AH, 7 2 ,2 6 6 ,4 1 0 + 4 ,3 2 3 ,556T 7 1 ,9 9 1 ,0 7 2 x 1,0 4 3 1 t = 1 4 8 , 1 4 2 - 2 ,3 1 0 T = 1 4 7 ,2 6 7 x 0 .9 8 2 5 T Rz .6 2 7 3 ' .5 2 6 6 .5 3 1 0 .5 6 4 9 ' A p p les V a lu e o f P ro d u c tio n : (L) V a lu e o f P r o d u c tio n : (E) VP, = VP, = A c r e s H a r v e s te d : (L) A c r e s H a r v e s te d : (E) AH, = 5 1 , 6 3 5 - 2 6 4 T AH, = 5 1 , 3 5 8 x 0 . 9 9 4 9 T .1 3 5 9 .1 4 2 3 ' N u m b e r o f T r e e s : (L) N u m b e r o f T r e e s : (E) NT, = NT, = 2 ,2 6 7 ,6 1 9 + 1 2 5 ,9 7 4 T 2 ,4 9 6 ,8 3 6 x 1 ,0 3 2 8 T .7 7 6 2 .8 2 9 6 ' Q u a n t i t y P r o d u c e d : (L) Q u a n t i t y P r o d u c e d : (E) QP, = QP, = 5 9 7 ,2 8 5 ,7 1 4 + 1 5 ,1 8 1 ,8 1 8 T 5 9 7 ,4 0 2 ,4 1 7 x 1 ,0 2 0 4 T .3 0 9 2 ' .3 0 1 2 Yield: (L) Yield: (E) Y, = 5 . 8 8 + 0 . 1 8 7 6 T Y, = 5 . 8 2 x 1 . 0 2 5 7 T .3 1 8 6 ' .2 8 3 3 P rice: (L) Price: (E) P, = P, = .4 6 3 6 ' .4 1 3 4 2 6 ,1 2 2 ,9 3 8 + 2 ,6 7 8 ,0 1 4 T 2 9 ,1 8 1 ,8 0 7 x 1 .0 5 4 9 T 0 .0 5 0 7 + 0 .0 0 2 1 T 0 .0 4 8 8 x 1 .0 3 4 1 T .8 7 1 8 ' .8 1 2 1 G rapes V a lu e o f P r o d u c tio n : (L) V a lu e o f P ro d u c tio n : (E) VP, = VP, = 6 ,8 8 2 ,1 2 4 + 3 0 2 .3 6 1 T 6 ,4 5 7 ,0 8 6 x 1 ,0 3 5 3 T .2 9 4 0 ' .2 5 6 3 A c r e s H a r v e s t e d : (L) A c r e s H a r v e s t e d : (E) AH, = AH, = 1 6 ,6 8 4 - 2 9 8 T 1 6 ,9 6 7 x 0 .9 7 8 0 T .9 5 9 8 .9 6 1 8 ' N u m b e r o f V ines: (L) N u m b e r o f V ines: (E) NV, = NV, = 8 ,4 1 6 ,9 0 5 - 1 7 3 .1 8 2 T 8 ,6 2 4 ,9 0 3 x 0 .9 7 3 6 T .9 5 2 9 ' .9 5 1 0 Q u a n t i t y P r o d u c e d : (L) Q u a n t i t y P r o d u c e d : (E) QP, = QP, = 1 0 0 ,7 4 2 ,8 5 7 - 1 5 8 ,442T 9 0 ,1 6 0 ,4 7 9 x 1 ,0 0 3 6 T .0 0 1 3 .0 4 2 2 ' Yield: (L) Yield: IE) Y, = Y, = 2 .9 2 + 0 .0 7 7 0 T 2 .6 6 x 1 ,0 2 6 2 T .1 8 3 6 ' .1 4 6 3 Price: (L) P rice: IE) P, = P, = 0 .7 2 2 3 + 0 .0 2 8 0 T 0 .7 3 0 7 x 1 .0 2 9 3 7 .5 8 7 1 ' .5 6 6 2 363 Peaches Trend Function Bl Value of P roduction: (L) Value of Production: (E) VP, = 4 , 7 3 6 , 7 0 0 + 2 6 6 . 9 2 3 T VP, = 4 , 2 3 5 , 8 9 3 x 1 , 0 4 7 9 T .4 9 7 8 * .3 8 6 2 A c r e s H a r v e s t e d : (L) A c r e s H a r v e s t e d : (E) AH, = 1 4 , 6 0 0 - 5 0 3 T AH, = 1 4 , 0 0 7 x 0 . 9 5 2 6 T .5 5 6 7 .6 0 6 0 ' N u m b e r o f T r e e s : (L) N u m b e r o f T r e e s : (E) NT, = 1 , 3 8 3 , 4 7 6 - 3 9 , 3 6 4 T NT, = 1 , 2 9 8 , 9 6 9 x 0 . 9 6 4 9 T .4 0 0 7 .4 2 7 9 ' Q u a n t i t y P r o d u c e d : (L) Q u a n t i t y P r o d u c e d : (E) QP, = 5 6 , 3 7 6 , 1 9 0 - 5 4 9 , 3 5 1 T QP, = 4 6 , 6 7 9 , 6 0 1 x 1 , 0 0 0 7 T .0 4 5 6 ' .0 4 5 5 Yield: (L) Yield: (E) Y, = 2 . 0 5 + 0 . 1 0 4 0 T Y, = 1 . 6 7 x 1 . 0 5 0 5 T .3 0 7 9 ' .1 1 3 8 Price: P, = 0 . 0 9 7 4 + 0 . 0 0 5 5 T P, = 0 . 0 9 4 0 x 1 , 0 4 4 0 T .6 1 0 4 ' .4 5 8 2 V a lu e of P r o d u c tio n : (L) V a lu e o f P r o d u c tio n : (E) VP, = 2 , 0 0 9 , 2 0 0 - 2 2 , 4 3 4 T VP, = 2 , 0 6 4 , 5 9 0 x 0 . 9 8 2 1 1 .0 8 8 9 ' .0 4 1 4 A c r e s H a r v e s t e d : (L) A c r e s H a r v e s t e d : (E) AH, = 1 0 , 2 6 1 - 5 2 7 T AH, = 1 2 , 5 1 8 x 0 . 8 8 5 6 T .8 2 7 6 .9 1 8 5 ' N u m b e r o f T r e e s : (L) N u m b e r o f T r e e s : (E) NT, = 9 7 1 , 2 6 7 - 4 9 . 6 7 8 T NT, = 1 , 1 7 1 , 5 6 6 x 0 . 8 8 7 4 T .8 2 2 6 .9 1 3 5 ’ Q u a n t i t y P r o d u c e d : Y, = Y, = P ric e: (L) P, = 0 . 5 2 0 0 + 0 . 0 3 4 9 T P, = 0 . 5 4 5 2 x 1 . 0 4 1 4 T .4 6 4 8 ' .4 3 0 7 VP, = VP, = 5 ,0 0 6 ,1 4 3 + 4 6 0 ,9 3 5 T 5 ,1 6 6 ,2 1 4 x 1 .0 5 3 1 T .3 3 5 8 P ric e : (E) x 0 .9 7 1 2 T 2 .5 0 + 0 .0 6 5 7 T 2 .4 2 x 1 .0 2 1 8 T .1 6 7 1 ' .1 2 0 6 S w e e t C h erries V a l u e o f P r o d u c t i o n : (L) V a l u e o f P r o d u c t i o n : (E) A c r e s H a r v e s t e d : (L) A c r e s H a r v e s t e d : (E) AH, = .4 0 8 4 ’ 1 1 ,7 9 4 - 17 7T .4 9 5 9 ' AH, = 1 1 ,7 9 8 x 0 .9 8 2 6 T .51 91 N u m b e r o f T r e e s : (L) NT, = 9 6 3 ,2 8 6 - 1 2 .5 7 1 T .3 8 8 2 N u m b e r o f T r e e s : (E) NT, = 9 6 1 ,1 8 5 x 0 .9 8 5 2 T .4 0 7 1 ' Q u a n t i t y P r o d u c e d : (L) QP, = 4 9 , 4 6 1 , 9 0 5 Q u a n t i t y P r o d u c e d : (E) Q P, = 4 7 , 9 7 7 , 1 5 7 x 1 , 0 0 3 0 T + Y i e l d : (L) Y, = 2 .1 1 Y i e l d : (E) Y, = 2 .0 3 x 1 .0 2 0 8 T Price: (L) Price: (E) P, = 0 . 0 9 8 9 1 5 7 ,1 4 3 T + 0 .0 5 2 3 T + 0 .0 0 9 2 T P, = 0 . 1 0 8 0 x 1 . 0 5 2 2 T .0 0 6 0 .0 2 2 5 ' .1 4 5 8 ' .1 0 4 9 .7 8 1 8 ' .7 2 8 5 365 Tart C herries V alue o f P roduction: (L) V alue o f Production: (E) A c r e s H a r v e s t e d : (L) Trend Function E! VP, = 2 5 ,3 8 0 ,0 7 1 VP, = 2 1 ,8 4 3 ,8 3 7 x 1 ,0 2 7 6 T + 6 1 7 ,2 4 0 T .0 8 5 6 * .0 0 9 3 AH, = 3 5 ,7 1 3 - 29 3 T AH, = 3 5 ,3 3 7 x 0 .9 9 1 7 T .2 1 8 0 * N u m b e r o f T r e e s : (L) NT, = 2 ,9 7 0 ,7 1 4 .0 3 7 1 * N u m b e r o f T r e e s : (E) NT, = A c r e s H a r v e s t e d : (E> + 1 1 ,1 0 4 T .2 0 7 3 2 ,9 6 1 ,6 7 9 x 1 .0 0 3 4 T .0 3 6 7 .0 2 6 7 * Q u a n t i t y P r o d u c e d : (L) QP, = 1 5 3 ,1 9 0 ,4 7 6 Q u a n t i t y P r o d u c e d : (E) QP, = 1 4 6 ,2 9 8 ,9 9 9 x 1 .0 0 8 1 T Y i e l d : (L) Y i e l d : (E) Y, = Y, = P ric e : (L) P, = 0 . 1 9 7 2 P ric e : (E) P, = 0 . 1 5 3 2 x 1 . 0 2 0 0 T .0 9 5 5 ' V a l u e o f P r o d u c t i o n : (L) V a l u e o f P r o d u c t i o n : (E) VP, = .8 1 7 3 ' VP, = 5 9 , 4 2 0 , 5 3 7 x 1 , 0 4 9 9 T .7 1 0 3 A c r e s H a r v e s t e d : (L) AH, A c r e s H a r v e s t e d : IE) AH, = .5 3 5 0 ' .5 3 4 0 + 1 ,4 1 5 ,5 8 4 T 2 .1 3 + 0 .0 4 3 0 T 2 .0 7 x 1 .0 1 6 5 T + 0 .0 0 2 6 T .0 0 0 9 .0 9 8 9 ' .0 7 8 2 .0 1 4 2 V e g e ta b le O verview T otal 5 6 ,3 7 5 ,0 1 5 = 9 2 ,6 4 8 + + 4 ,5 7 3 ,7 2 2 T 8 4 4 .8T 9 2 ,8 3 0 x 1,0 0 8 3 T A sparagus V a l u e o f P r o d u c t i o n : (L) VP, = 4 , 8 0 2 , 4 7 7 V a l u e o f P r o d u c t i o n : (E) VP, = 5 , 1 1 0 , 4 1 8 x 1 . 0 6 4 0 T .5 9 7 1 A c r e s H a r v e s t e d : (L) AH, = 1 3 ,9 4 5 + 4 5 6 .9T A c r e s H a r v e s t e d : (E) AH, = 1 4 ,1 5 1 x 1,0 2 5 7 T .8 5 1 4 * .8 1 9 2 Q u a n t i t y P r o d u c e d : (L) QP, = 2 0 3 . 6 Q u a n t i t y P r o d u c e d : (E) QP, = 2 0 2 . 6 x 1 . 0 0 9 6 T .2 3 4 6 * Y i e l d : (L) Y, = 1 4 .4 6 - 0 .2 0 8 4 T .4 1 7 5 Y i e l d : (E) Y, = 1 4 .3 2 x 0 .9 8 4 2 T .4 3 2 6 * P ric e: (L) P, = 2 4 .6 6 .7 0 0 5 * P ric e: (E) P, = 2 5 . 2 3 x 1 . 0 5 4 0 T + + + 5 6 5 ,7 2 9 T 2 .0 9 2 9 T 2 .1 1 5 9 T .7 3 4 1 * .2 3 3 9 .5 5 2 2 366 C arrots (Dual P u rp ose) Trend F unction V a l u e o f P r o d u c t i o n : (L) VP, = 8 , 1 7 2 , 0 5 5 + V a l u e o f P r o d u c t i o n : (E) VP, = x 1.0 4 0 0 T A c r e s H a r v e s t e d : (L) AH, = 5 ,2 5 6 A c r e s H a r v e s t e d : (E) AH, = 5 , 2 7 7 x 1 .0 1 1 3 T .2 2 6 9 Q u a n t i t y P r o d u c e d : (L) Q u a n t i t y P r o d u c e d : (E) QP, = 1 ,1 7 0 .3 5 2 0 ’ QP, = 1 ,1 7 9 x 1 .0 1 9 8 T Y i e l d : (L) Y, Y i e l d : (E) Y, = P ric e: (L) P ric e: (E) 8 ,2 4 1 ,2 9 2 = 2 2 3 .7 + + + 4 7 0 .7 8 0 T 7 1 .6T 2 9 .6T 2 .0 2 4 0 T .4 9 9 1 ‘ .4 4 0 9 .2 3 7 1 * .3 3 8 7 .3 2 4 7 ' 2 2 3 .4 x 1 .0 0 8 5 T .3 2 3 0 P, = 7 .1 0 P, = 6 .9 9 x 1 .0 1 9 8 T .3 0 4 3 ' .2 7 1 9 + 0 .1 5 9 2 T C a u liflo w e r V a l u e o f P r o d u c t i o n : (L) VP, = 3 3 6 ,9 3 5 V a l u e o f P r o d u c t i o n : (E) VP, = 5 2 3 ,2 0 6 x 1,0 9 7 6 T .4 5 7 9 .1 4 2 9 ' .1 2 6 6 + 12 9 ,4 7 0 T A c r e s H a r v e s t e d : (L) AH, = 934 A c r e s H a r v e s t e d : (E) AH, = 9 2 4 x 1 .0 1 3 5 T + 1 4 .8T .6 5 8 7 ' Q u a n t i t y P r o d u c e d : (L) QP, = 4 8 . 4 Q u a n t i t y P r o d u c e d : (E) QP, = 4 7 . 5 x 1 , 0 2 2 4 T Y i e l d : (L) Y, Y i e l d : (E) Y, = 5 1 .5 x 1 ,0 9 7 6 T . 13 9 4 ‘ P ric e : (L) P, = 9 .7 4 .7 8 6 1 • P ric e : (E) P, = 1 1.0 1 = 5 2 .0 + 1 .3 5 3 2 T + 0 .4 6 9 3 T + 1 .5 3 7 6 T x 1.0 7 3 6 T .1 9 9 0 ’ .1 8 0 3 .1 3 8 4 .6 1 5 2 C e le ry (D u al P urpose) V a lu e o f P ro d u c tio n : (L) V a l u e o f P r o d u c t i o n : (E) A c re s H a rv este d : (L) VP, = 5 ,7 4 9 ,9 9 6 VP, = 6 ,0 4 0 ,0 2 4 x 1 .0 5 4 7 T + 5 2 9 ,4 3 3 T .7 1 1 4 ’ .57 51 AH, = 2 ,2 2 6 + 5 1 .3T .4 5 2 5 ’ A c r e s H a r v e s t e d : (E) AH, = 2 ,2 4 3 x 1 .0 1 8 8 T .4 3 0 9 Q u a n t i t y P r o d u c e d : (L ) Q u a n t i t y P r o d u c e d : (E) QP, QP, = 9 1 8 .8 + 2 0 .4 5 T = 9 1 3 .3 x 1 .0 1 9 0 T .3 3 0 5 " .2 9 7 9 Y ield : (L) Y i e l d : (E) Price: (L) Price: (E) Y, = 4 0 9 . 5 + 0 .0 1 32 T Y, = 4 0 7 . 2 x 1 , 0 0 0 2 T P, = 6 . 4 3 + 0 .3 2 1 8T P, - x 1 .0 3 5 0 T 6 .6 1 .0 0 0 0 .0 0 2 1 ' .6 1 7 8 ' .5 7 5 5 367 C u cu m b ers (P r o c e ssin g ) a! Trend F unction V a l u e o f P r o d u c t i o n : (L) VP, = 7 ,6 6 6 ,4 7 5 V a l u e o f P r o d u c t i o n : (E) VP, = 8 ,7 3 6 ,6 2 9 x 1 .0 5 0 5 1 A c r e s H a r v e s t e d : (L) A c r e s H a r v e s t e d : (E) AH, = 2 5 ,4 9 9 - 1 3 8 .4 T + 7 3 9 ,1 3 5 T .8 5 6 0 .8 6 1 9 ’ AH, = 2 5 ,3 3 3 x 0 .9 9 4 3 T .0 9 6 2 ' .0 9 4 4 Q u a n t i t y P r o d u c e d : (L) QP, = 9 4 .4 .6 0 8 5 Q u a n t i t y P r o d u c e d : (E) QP, = 9 5 .7 x 1 .0 1 9 8 T + 2 .3 3 1 9T .6 1 2 1 ’ Y i e l d : (L) Y, = 3 . 7 1 Y i e l d : (E) Y, = 3 .7 8 x 1 ,0 2 5 6 T .7 0 8 2 P ric e: (L) P, = 8 8 .3 .8688’ P ric e : (E) P, = 9 1 . 3 x 1 , 0 3 0 1 T + 0 .1 2 3 3 T + 3 .6 9 2 0 T .7 2 7 4 ’ .8 5 8 6 L e ttu c e (Fresh M a r k e t) V a l u e o f P r o d u c t i o n : (L) VP, = 1 ,9 9 1 ,7 3 8 V a l u e o f P r o d u c t i o n : (E) VP, = 1 ,9 1 9 ,3 0 5 x 1 .0 4 9 9 T .3 0 3 3 A c r e s H a r v e s t e d : (L) AH, = 1 ,5 9 9 - 2 9 .2T A c r e s H a r v e s t e d : (E) AH, = 1 ,6 3 0 x 0 .9 6 0 T .7 4 1 5 ’ .7 2 3 5 Q u a n t i t y P r o d u c e d : (L) Q u a n t i t y P r o d u c e d : (E) QP, = 2 8 8 .2 - 3 .1 5 0 6 T .1 5 9 6 ’ QP, = 2 9 0 .8 x 0 .9 8 5 9 T .1 4 1 0 Y i e l d : (L) Y, = 1 7 8 .9 Y i e l d : (E) Y, = 1 7 8 .4 x 1 .0 1 0 1 T .2 0 5 6 P r ic e : (L) P, = 5 .9 3 .7 5 2 9 ’ P ric e : (E) P, = 6 .6 0 x 1 ,0 6 4 8 T + + 14 1 ,7 1 3T 2 .0 0 8 4 T + 0 .7 6 4 8 T .4 1 7 9 ’ .2 1 4 5 ’ .6 5 6 5 M u sh ro om s V a l u e o f P r o d u c t i o n : (L) V a l u e o f P r o d u c t i o n : (E) VP, = VP, = 1 3 ,6 5 0 ,9 3 1 + 6 7 6 ,9 9 9 T 1 3 ,9 1 2 ,5 1 3 x 1 .0 3 9 7 T S q u a r e F e e t H a r v e s t e d : (L) SFH, = S q u a r e F e e t H a r v e s t e d : (E) SFH, = 6 ,4 0 2 ,0 3 1 6 ,4 1 1 ,4 6 7 - 2 7 4 , 3 3 9 T Q u a n t i t y P r o d u c e d : (L) QP, = 1 8 ,8 7 2 Q u a n t i t y P r o d u c e d : (E) QP, = 1 8 ,8 7 8 x 1 .0 1 1 7 T Y i e l d : (L) Y, = Y i e l d :