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University Micrcxilrrts International 300 N. Zeeb Road Ann Arbor, Ml 48106 8424432 H lubik, J o s e p h G. THE PROFITABILITY OF PURCHASING VS. GROWING FEEDS ON DAIRY FARMS IN SOUTHERN MICHIGAN M ichigan State University University Microfilms International 300 N. Zeeb Road, Ann Arbor, Ml 48106 Ph.D. 1984 PLEASE NOTE: In all c a s e s this material has been filmed in the best possible way from the available copy. Problems encountered with this docum ent have been identified here with a check mark V . 1. Glossy photographs or p a g e s ______ 2. Colored illustrations, paper or print______ 3. Photographs with dark backgrou n d______ 4. Illustrations a re poor c o p y ______ 5. P ages with black marks, not original 6. Print shows through as there is text on both sid es of pag e______ 7. Indistinct, broken or small print on several p a g e s 8. Print exceeds margin requirem ents______ 9. Tightly bound copy with print lost in spine______ 10. Computer printout pages with indistinct print______ 11. P ag e(s)____________ lacking when material received, and not available from school or author. 12. P ag e(s)____________ seem to be missing in numbering only a s text follows. 13. Two pages nu m b ered _____________. Text follows. 14. Curling and wrinkled p a g e s ______ 15. Other_____________________________________ copy_ ■ y /' University Microfilms International THE PROFITABILITY OF PURCHASING VS. GROWING FEEDS ON DAIRY FARMS IN SOUTHERN MICHIGAN By Joseph G. Hlubik A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Department of Animal Science 1984 ABSTRACT THE PROFITABILITY OF PURCHASING VS. GROWING FEEDS ON DAIRY FARMS IN SOUTHERN MICHIGAN By Joseph G. Hlubik The profitability of three strategies of securing feeds on dairy farms in Southern Michigan was investigated considering equal investment levels. These include: 1) growing forages and grain forages only (GF) and purchasing all feed (PR). (GFG), 2) growing Alfalfa and corn silage ware the forages and corn the grain. The electronic spreadsheet program: Microsoft Multiplan (1982) was employed to synthetically model farms of herd sizes ranging from 40 to 500 cows (plus replacements). Budgeted analyses of profitability across various herd sizes (representing different investment levels) provided a basis to regress profit on dollars invested for each strategy. Stra­ tegies were then compared on the basis of profitability considering equal investment levels ranging from $.5 to 2.5 million. The model employs a static budgeting approach and assumes crop yields, level of milk, and prices specified (by the user) are constant over the investment period. The profitability and ranking of strategies was examined considering: levels of milk production ranging from 13 to 19 thousand lb, milk prices ranging from 511.40 to 12.60/cwt and corn prices ranging from $2.55 to Joseph G. Hlubik 3.30/bu. These analyses revealed: 1) the ranking of strategies according to profit changes with the level of milk production and investment 2) GFG is profitable at levels of milk production >15 thousand lb 3) GF always ranks either 1st or 2nd and is profitable at levels of production >15 thousand lb 4) PR was a profitable strategy at levels of production >17 thousand lb Land prices ranging from $500 to 1300/acre were examined assuming a soil classified in soil management group 3 and a level of milk pro­ duction of 15 thousand lb. It was found that GFG and GF were much more profitable than PR until the price of land was >_$1100/acre. It was also discovered that when different levels of soil productivity (i.e. different soil management groups) were considered profitability was not affected if the price of land was changed accordingly. These analyses are a few examples of situations which can be examined using the dairy investment model developed in this dissertation. ACKNOWLEDGEMENTS I would like to express appreciation to John Speicher, J. Roy Black, Clyde Anderson and Sherill Nott for being on my dissertation committee. I am also grateful to my comrades in the Animal Science and Agricultural Economics Departments and sincerely appreciate the help and friendships I have known here; Special thanks to John Walter for his help in dealing with the computer and to Elaine Kibbey for typing this dissertation. I dedicate this dissertation to the Sacred Heart of Jesus Christ. TABLE OF CONTENTS CHAPTER PAGE 1. INTRODUCTION 2. REVIEW OF THE LITERATURE 7 Review of the Literature-......................... 7 2.1.1 2.1.2 2.1.3 Growing vs. B u y i n g ........................ What Combinations of Feeds to Grow . . . . Size Relationships in D a i r y i n g .......... 7 10 16 ........ 23 M a n a g e m e n t ................................ What to Produce and How M u c h ............ Comparative Advantage .................... How to Produce Capital Budgeting Determining the Annual Costs of Durable Assets ................... ; ............ Risk 23 24 29 32 33 P R O T O C O L ................................................ 39 2.2 Basic Economic and Management Theory . 2.2.1 2.2.2 2.2.3 2.2.4 2.2.5 2.2.6 2.2.7 4. 1 AND BASIC THEORY ............... 2.1 3. ........................................... 34 36 3.1 O b j e c t i v e ........................................ 39 3.2 Protocol 39 ........................................ ASSUMPTIONS AND SPECIFICATIONS 4.1 Feed Costs 4.1.1 4.1.2 4.1.3 4.1.4 4.1.5 4.1.6 4.1.7 OFTHE INVESTMENT MODEL 44 ...................................... 44 R a t i o n .................................... Feed Storage F a c i l i t i e s ................... Land ..................................... A. Purchase Price of L a n d ............... B. Annual Use Cost of L a n d ............... C. Land Productivity ................... Cash Crop E x p e n s e s ....................... Crop M a c h i n e r y ........................... Crop Labor R e q u i r e m e n t s ................... Purchased Feed C o s t s ..................... 44 52 58 59 60 61 63 65 66 67 iii CHAPTER 4.2 PAGE Dairy E x p e n s e s ........................... 4.2.1 4.2.2 4.3 4.3.4 4.3.5 4.3.6 4.4 4.4.3 4.4.4 68 70 70 .................. Milk Income Cull Cows I n c o m e ................ 73 Income From Deacon Calves, Replacements Sold, and Cull H e i f e r s .......... 73 Estimated Fertilizer Cost Savings and the Value of Manure ................. Estimated Soybean Meal Savings for Farms Growing Forages . . . •.. 76 Savings in Dairy Equipment and Crop Machinery ............................. Price Expectations 4.4.1 4.4.2 5. Dairy Buildings and Facilities, Land For Facilities and Dairy Equipment . . . Livestock Expenses, Labor and Invest­ ments .................................... Incomes and Adjustments to C o s t s ...... 4.3.1 4.3.2 4.3.3 68 ............................. Setting Prices in the M o d e l ..... 77 Level of Milk Production and Milk/Feed Price Ratios . . ..................... Prices Related to the Price of Milk . . . Feed Prices and R e l a t i o n s h i p s ... 80 A. Price of C o r n .............. 80 B. Price of Hay and Soybean Meal . . . . C. Purchase Price of Corn Silage . . . . RESULTS AMD D I S C U S S I O N ...........: .................. 5.1 5.2 75 76 77 78 78 80 81 85 The Effect of Level of Milk Production on Pro­ fitability Across Strategies ................... 86 The Effect of Changing the Milk/Feed Price Ratio on Profitability by Changing the Price of Milk . 96 5.3 The Effect of Changing the Milk/Feed Price Ratio by Changing the Price of C o r n .......... 97 5.4 The Impact of Changing the Price of Land on Profitability .................................. 5.5 70 The Impact of Changing the Soil Management Group and Price of Land on P r o f i t a b i l i t y...... 110 iv 103 PAGE CHAPTER 6. SUMMARY AND C O N C L U S I O N S ................................ 121 APPENDIX A. MICHIGAN LAND VALUES AND AVERAGE CASH RENTS . . . . B. LOGIC OF FEED PURCHASING D E C I S I O N S ....... C. CROP MACHINERY C O M P L E M E N T S ........................ 137 D. CROP LABOR E S T I M A T E S ............................... 146 E. DAIRY BUILDINGS AND FACILITIES ESTIMATES ......... 160 ........................ 166 F. THE FI F2 F3 F4 F5 DAIRY INVESTMENT MODEL 131 Orientation ................................. I n t r o d u c t i o n .................................. Outline of theInvestment M o d e l ................ Example of the Model As It Appears to the User. Formulas, Values and Their Explanation. 172 B I B L I O G R A P H Y ........................... v 128 166 168 170 172 215 LIST OF TABLES TABLE 1.1 PAGE Time Trends in Business of Michigan Telfarm Special­ ized Dairy F a r m s ....................................... 3 Hours of Labor Used in Producing Milk and Corn in the Lake States and Corn Belt (Hypothetical) . 1............. 32 4.1 Characteristics of Rations for Lactating Cows ........ 47 4.2 Nutrient Content of Michigan Feeds Analyzed at Ohio . . 48 2.1 4.3 4.4 4.5 4.6 4.7 4.8 4.9 Nutrient Content of Feeds Used in Estimating Feed ............................................... Budgets 49 Quantities of Feed Needed/Cow and Replacement/Year by Production L e v e l .............................. . . . 51 Telfarm Estimates of Feed Disappearance by Level of Milk P r o d u c t i o n ......................................... 52 (Cement Stave).......... 56 Estimated Vertical Silo Costs (Cement Stave, Including Top Unloader) v s . Costs Predicted by Linear Equations for Corn Grain, Silage and H a y l a g e ................... 57 Estimated Horizontal Silo Costs (Cement Sides, Floor and Back Wall) vs. Costs Predicted by Linear Equa­ tions, for Corn S i l a g e ................................ 58 1982 Property Taxes and Insurance Paid and Farm Capital Owned by Michigan Telfarm Specialized Dairy Farms According to Herd S i z e .......................... 61 Vertical Silo Sizes and Costs 4.10 Expected Crop Yields/Acre by Soil Management Group 4.11 Cash Crop Budgets: E x p e n s e s / A c r e ..................... 64 4.12 Summary of Machinery Investments by Herd Size and Feeding Strategy ....................................... 65 vi . . 63 TABLE PAGE 4.13 Crop Labor Requirements ................................... 67 4.14 Summary of Dairy Buildings and Investments by Herd Size ........................................................ 70 Dairy Livestock Budgets: Selected Cash Expense by Pro­ duction Level .............................................. 71 Estimated Annual Dairy Labor Requirements by Herd Size 72 4.15 4.16 4.17 4.18 4.19 4.20 5.1 5.2 5.3 5.4 5.5 __ Savings in Machinery Investments for Farms Growing ................................................. Crops Milk/Feed Price Ratios Over Time 77 ........................ 79 Time Trends and Relationships of Relevant Commodity Prices ...................................................... 82 Estimate of Prices to Use in the Model ................... 84 Changes in Profitability by Lefel of Investment According to Strategy (Milk Production(lb)= 13,000)...... 89 Changes in Profitability by Level of Investment According to Strategy (Milk Production(lb)= 15,000)...... 90 Changes in Profitability by Level of Investment According to Strategy (Milk Production(lb)= 17,000)...... 91 Changes in Profitability by Level of Investment According to Strategy (Milk Production(lb)= 19,000)...... 92 Profitability by Level of Investment According to Level of Production and Strategy (Milk/Feed Ratio = 1.55) ............................... 98 5.6 Profitability by Level of Investment According to Level of Production and Strategy (Milk/Feed Ratio = 1.45) ......................................................190 5.7 Changes in Profitability by Level of Investment According to Strategy Considering Different Prices of Corn (Level of Production = 13,000 l b ) .................. 105 5.8 Changes in Profitability by Level of Investment According to Strategy Considering Different Prices of Corn (Level of Production = 15,000 lb).................. 106 vii PAGE TABLE 5.9 5.10 Changes in Profitability by Level of Investment According to Strategy Considering Different Prices of Corn (Level of Production = 17,000 l b ) ............. 107 Changes in Profitability by Level of Investment According to Strategy Considering Different Prices of Corn (Level of Production = 19,000 l b ) ............. 108 5.11 Changes in Profitability by Level of Investment According to Strategy (Price of Land ($/Acre) =500). . 112 5.12 Changes in Profitability by Level of Investment According to Strategy (Price of Land ($/Acre) = 700). . 113 5.13 Changes in Profitability by Level of Investment According to Strategy (Price of Land ($/Acre) = 900). . 114 5.14 Changes in Profitability by Level of Investment According to Strategy (Price of Land ($/Acre) = 1100) . 115 5.15 Changes in Profitability by Level of Investment According to Strategy (Price of Land ($/Acre) = 1300) . 116 5.16 Changes in Profitability by Level of Investment According to Strategy (Soil Management Group = 2 . 5 ) . . 118 . . . 119 5.17 Changes in Profitability by Level of Investment According to Strategy (Soil Management Group = 3 ) 5.18 Changes in Profitability by Level of Investment According to Strategy (SoilManagement Group = 4) A 1 A 2 B 1 B 2 C 1 C 2 120 Average Michigan Farmland Values and Indexes During the Last 5 Y e a r s ....................................... 130 Average Per Acre Cash Rents and Farmland Values in Michigan from 1960 to 1980 130 Nominal Prices of Corn and Hay Received by Michigan Farmers from 1972 to 1982 135 Adjusted (1983 Dollars) Prices of Corn and Hay Received by Michigan Farmers from 1972 to 1982 . . . . 136 Crop Machinery and Equipment (Grow All Feed): Herd Size = 40 C o w s ......................................... 138 Crop Machinery and Equipment (Grow Forages Only): Herd Size = 40 C o w s ..................................... 139 viii TABLE C 3 C 4 C 5 C 6 C 7 C 8 D 1 PAGE Crop Machinery and Equipment (Grow All Feeds): Herd Size = 75 C o w s .......................................... 140 Crop Machinery and Equipment (Grow Forages Only): Herd Size = 75 C o w s ........ ........................... 141 Crop Machinery and Equipment (Grow All Feeds): Herd Size = 150 Cows . .'................................... 142 Crop Machinery and Equipment (Grow Forages Only): Herd Size = 150 C o w s .................. '................ 143 Crop Machinery and Equipment (Grow All Feeds): Herd Size = 300C o w s .......................................... 144 Crop Machinery and Equipment (Grow Forages Only): Herd Size =300 C o w s ...................................... 145 Machine Capacities, Acres/Hour for Selected Farming O p e r a t i o n ................................................ 147 D 2 Corn Grain Labor: 40 Cows, 42 Acres C o r n .............. 148 D 3 Corn Grain Labor: 75 Cows, 79 Acres C o r n .............. 148 D 4 Corn Grain Labor: 150 Cows, 158 Acres C o r n ............ 149 D 5 Corn Grain Labor: 300 Cows, 149 D 6 Corn Silage Labor: 40 Cows, 24 Acres Corn Silage . . . 150 D 7 Corn Silage Labor: 75 Cows, 45 Acres Corn Silage . . . 150 D 8 Corn Silage Labor: 150 Cows, 90 Acres Corn Silage . . 151 D 9 Corn Silage Labor: 300 Cows, 180 Acres Corn Silage . . 151 D10 Dll D12 D13 315 Acres C o r n ............ Haylage Labor: 75 Cows, 71.1 Acres Haylage (11.9 Acres New Crop, 59.2 E s t a b l i s h e d ) ................... 152 Haylage Labor: 150 Cows, 142.2 Acres Haylage (23.7 Acres New Crop, 113.5 Acres Established) . . . . 153 Haylage Labor: 300 Cows, 284.4 Acres Haylage (47.5 Acres New Crop, 236.9 Established) ................... 154 Hay Labor: 40 Cows, 63 Acres Hay (10.5 Acres New Crop, 52.5 E s t a b l i s h e d ) .............................. 155 ix TABLE D14 D15 D16 D17 D18 E 1 E 2 E 3 E 4 E 5 PAGE Hay Labor: 150 Cows, 95 Acres Hay (15.8 Acres New Crop, 79.2 Acres Established)............................ 156 Hay Labor: 300 Cows, 190 Acres Hay (31.6 Acres New Crop, 158.4 Established) ................................ 157 Summary of Crop Labor Requirements by Acres and Equations to Predict Crop Labor Requirements ........... 158 Telfarm Equations Estimating Enterprise Labor Requirements ............................................. 158 Calculated and Predicted Labor Requirements by A c r e s .................................................... 159 Dairy Buildings and Facilities, Equipment; Herd Size = 40 Cows, Confinement-Stall B a r n ................. 161 Dairy Buildings and Facilities, Equipment; Herd Size = 75 Cows, Free-Stall Barn 162 Dairy Buildings and Facilities, Equipment; Herd Size = 150 Cows, Free-Stall B a r n ...................... 163 Dairy Buildings and Facilities, Equipment; Herd Size = 300 Cows, Free-Stall B a r n ...................... 164 Dairy Buildings and Facilities, Equipment; Herd Size = 500 Cows, Free-Stall B a r n ...................... 165 x LIST OF FIGURES FIGURE PAGE 2.1 Production Possibilities .......................... 25 2.2 Production Possibilities (Increasing Returns to Size) ............................................. 31 2.3 How to P r o d u c e ..................................... 32 3.1 Flow Chart of the Dairy Investment M o d e l ......... 43 5.1 Profitability by Level of Investment According to Strategy and Level of P r o d u c t i o n ............... 93 Profitability by Level of Production According to Strategy and Level of P r o d u c t i o n ............... 94 Rate of Return on Investment (RROI) by Level of Production According to Level of Investment and S t r a t e g y ............. . . ..................... 95 Profitability by Level of Investment According to Strategy and Level of Production (Increasing the Milk P r i c e ) ....................... 99 5.2 5.3 5.4 5.5 5.6 5.7 5.8 5.9 Profitability by Level of Investment According to Strategy and Level of Production (Decreasing the Milk P r i c e ) .................................... 101 The Impact of Changing the Price of Milk on Pr o f i t a b i l i t y .................................. 102 The Impact of Changing the Price of Corn on Pr o f i t a b i l i t y....................... 104 Contrasting the Effect of Changing the Milk/Feed Price Ratio by Changing the Price of Milk v s . Changing the Price of C o r n ....................... 109 The Impact of Changing the Price of Land on P r o f i t a b i l i t y ...................................... 117 xi CHAPTER 1 INTRODUCTION This research investigates the economies of different dairy farm organization alternatives relative to securing feed. These include: 1) farms with ownership of sufficient capital assets to grow forages and grain (GFG), 2) those with assets to grow forages only (GF) and, 3) those organized to purchase protein and minerals. The forages considered are alfalfa and corn silage and the grain is corn. Comparing the profitability of these alternative strategies and investigating the risks involved will indicate the preferred investment and shed light on the direction of expansion. The more common Michigan dairy farm organization is a crop farm which markets its harvest through milk sales. Growing crops requires investments in or rental of land as well as a substantial investment in crop machinery in addition to investment requirements for the dairy enterprise. Also, additional labor is required to handle cropping operations which creates seasonal labor problems. Growing feeds can usually act to buffer against the effects of sudden changes in feed prices but also leaves the farmer the risk of crop failure due to drought or other adverse weather conditions; in such instances the farmer actually pays doubly for feed due to the incurred crop expense as well as higher purchased feed costs. 2 Crop land is also available for manure disposal when crops are not being raised which results in savings in fertilizer costs. The essential question to ask becomes: Is it financially pre­ ferable for dairy farmers to grow their feeds or would they be just as well off or better purchasing feeds? Table 1.1 shows the time trend of returns to Michigan dairymen from 1971 to 1982. This table reveals that over the past 12 years dairymen have experienced a positive management income five of those years. Eleven out of 12 years dairymen have experienced positive management returns from the dairy enterprise whereas only in two of the past 12 years have they experienced positive management income from the cropping enterprise. This indicates that dairymen would have been better off if they had purchased feed instead of growing it. Brown and Nott (1982), explained the negative returns to the cropping enterprise of Michigan Telfarm farms (mail-in farm account­ ing system at Michigan State University) in 1981 in the following manner: " .... lower yields and lower prices of crops produced .... Crop costs were up .... Mechanical technology used in crop pro­ duction requires a very high investment and few dairy farms work a large enough acreage to make economical use of the investment they have m a d e ." Buying all feed, or at least the concentrate, reduces the initial capital investments in land and machinery and allows for a larger investment in cows (increasing herd size) and dairy facili­ ties and equipment for a given amount of capital invested. Table 1.1. Time Trends in Business of Michigan Telfarm Specialized Dairy Farms3 Year (lumber of farms Number of cows Number of people Met cost/cwt milk 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 397 71.17 2.40 5.75 37 3 70.89 2.32 5.62 365 72.20 2.46 6.75 436 76.48 2.63 9.60 470 77.32 2.66 10.09 474 80.12 2.72 9.29 457 01.84 2.75 9.50 379 83.25 2.82 9.54 423 85.02 2.89 10.55 432 85.05 2.74 10.94 419 84.29 2.73 12.29 438 84.08 2.73 12.17 70,414 93,294 93,846 92,522 110,622 113,013 152,465 176,405 189,289 177,026 181.303 67,242 81,446 97,240 106,371 118,378 128,363 142,132 169,085 188,073 209,098 212,010 3,172 11,848 -3,394 -13,849 -7,756 -15,350 59,527 Total value of production Total cost 63,663 Manaqement income*1 -4,136 S Total farm 10,333 7,320 1,216 -32,072 -30,707 662 629 1,022 696 1,178 823 1,194 912 1,180 990 1,209 1,021 80 33 326 355 282 190 188 163 170 147 184 144 188 169 211 185 241 213 268 181 293 191 301 14 -7 -37 -44 -42 -56 -55 -112 -110 2.52 2.85 2.35 2.04 1.95 2.22 2.46 3.05 2.39 2.20 29.50 31.00 37.50 44.00 43.00 58.00 45.50 36.00 36.50 56.50 61.50 6.75 14.21 10.56 9.24 10.92 13.20 11.85 13.28 14.00 15.40 13.30 6.17 7.20 8.22 8.55 9.85 9.65 10.50 12.00 13.20 13.80 13.60 Dairy Enterprise: Total value ofc production/cow $ Total cost/cow $ Management income/ cow $ 456 412 4 58 4 50 541 506 560 547 416 565 664 504 44 B 35 .13 -149 Crop Enterpri se: Total value of production/cow S Total cost/acre $ Management income/ acre $ 78 100 95 105 158 135 170 156 -22 -10 23 Corn-avg price/bu received by Michigan farmers $ 1.03 1.49 llay-nvg price/ton received by Michigan farmers $ 28.50 Soybean meal avg price paid/cwt by 5.94 Michigan farmers $ Price of milk/cwt S 5.96 ■ ’Sources: Drown and Nott, 1982, 1978 and 1974. Michiqan Dept, of Agric. 1973-1983. ^lanaqement income is defined as: the value of production less total costs. Total costs include an 8% return to owner's equity as well as the value of paid and unpaid labor. cThe value of feed (purchased and qrown) is deducted from qross income to estimate total value of production. 4 As herd size increases, farmers should be able to achieve any existing economies of size relative to the dairy operation. Increased herd size results in reducing the average fixed cost/cow of dairy facilities and may result in the ability to shift to technologies which may reduce some of the average variable costs of producing milk. For example, the least cost milking parlor for a herd size of 150 cows is a double-four herringbone parlor (no mechanization) with a throughput of approximately 37 cows/hour (Armstrong, 1980) and an annual cost/hour of daily milking time of approximately $3900 (Wetzel et al.,- 1979). is estimated as: The annual milking expense/cow/year (1 cow/37 cows/hour) * 2 milkings per day * $3900 annual charge/hour of daily milking = $210.00. parlor for a herd size of 300 cows is a parlor A low-cost milking double-eight herringbone (with detachers and a power gate) with a throughput of 70 cows/hour and an annual cost/hour of daily milking of $4170 (Wetzel et a l ., 1979). The annual milking expense/cow/year for this parlor considering a herd size of 300 cows was approximately $120.00. Thus, moving from a herd size of 150 to 300 cows and switching from a double-four to a double-eight herringbone parlor results in a savings of $90/cow/year. The initial investment in a double-four herringbone parlor (without mechanization) was $124,560 Armstrong, 1980). (1980 prices obtained from Considering a herd size of 150 cows this is estimated as an investment of $124,500/150 cows equals $830/cow. The initial investment in a double-eight herringbone parlor (with 5 detachers and a crowd gate) is $147,970 or $493/cow. This results in an investment savings/cow of $337 in moving from a double-four to a double-eight herringbone parlor and moving from a 150 to a 300 cow herd size. Similarly, as crop acreages increase farmers should be able to achieve economies of size relative to crop pro­ duction. Expanding both the dairy and crop enterprise requires an ex­ tensive capital outlay as well as a manager who is able to effec­ tively handle both or two managers. Given a limited supply of capital, logical alternatives to obtain economies of size for those who are already established in dairying include: 1) expanding the dairy herd and keeping the crop acreage the same or reducing it, thus purchasing more feed, 2) cutting back or eliminating the dairy operation and expanding crop production, or 3) slightly expanding both dairy and cropping enterprise as capital becomes available. Investigating the profitability of alternatives of growing versus buying feeds should shed light on the direction of expansion farmers should consider. When analyzing the profitability of growing versus purchasing feeds, the cost of producing feeds (including land cost, crop machinery cost, crop expenses, labor and.feed storage costs) and the cost of purchasing supplements to complete the nutritional needs of cows must be compared to the cost of purchased feed and feed storage costs for those farms purchasing all or at least concentrates and supplements. 6 Advantages and Disadvantages Problems associated with purchasing all or much of the feed supples include: 1) finding a reliable source of quality feed, especially forages, 2) obtaining credit to purchase large quantities of feeds, 3) unpredictable price fluctuations of feeds, 4) the management ability to secure good feed buys, 5) an increase in the number of cows/man, 6) disposing of manure produced on the farm; Advantages include: 1) a farm with a smaller land base is needed, 2) less machinery is required; combined with savings in land purchases, this will result in a substantial savings in capital required to start or expand an operation, 3) farmers can take advantage of contracting feed supplies (e.g. hedging on the future's market and contracting with local farmers), 4). milking machinery and equipment and barns as well as other fixed costs can be lowered on a per cow unit basis (.assuming herd size increases), 5) farmers purchasing most feeds will reduce irregular labor patterns in the spring and fall, 6) farmers purchasing feeds do not have to assume short term loans for crop supplies including fertilizer and seed in the spring, 7 7) farmers do not have to be crop managers as well as dairy managers, 8) there may be substantial savings in feed storage facilities. Purchasing most or all feeds may be a viable alternative especially in an economy.characterized by expensive land, high interest rates, low commodity prices and high fuel costs. Although purchasing all or most feeds is atypical of Midwestern dairymen, it is a common practice of many dairymen in California and the Southwest. dairymen. Purchasing grain is common practice among Northeast CHAPTER 2 REVIEW OF THE LITERATURE AND BASIC THEORY 2.1 Review of the Literature 2.1.1 Growing v s . Buying Feed The question of profitability of buying vs. purchasing feeds on dairy farms in the Midwest and East is not new. Several authors including Hoglund (1967), Speicher (1969) and Wysong have addressed this question. (1967) Hoglund and Wysong approached the problem by analyzing synthetic farm situations in which herd size and milk yield levels varied. They also looked at levels of crop productivity for those farms growing all feeds. Hoglund (.1967) in­ vestigated the economics of growing v s . buying feed for dairy herds of 40 to 240 cows. The major reasons cited for increased interest in buying more of the feed needs were: 1) increased size and specialization in dairy farming, 2) recent low prices for feed grains, 3) increasing land prices and taxes and, 4) difficulties in buying land near the farmstead. An analysis was made of: 1) growing all the feed, 2) growing only the forage and buying the grain, and 3) buying both forage and grain. These alternatives were budgeted for 40, 80, 160 and 240 cow farms on which all of the replacements were grown. Crop yields were estimated under levels of good and average management. Yields under average management 8 conditions were ~80% of those under good management. The analysis involved two levels of milk production, 12,000 lb/cow/year and 14,000 lb/cow/year. The average acres/cow of tillable land that he estimated were needed to grow all feed under good management and at 14,000 lb of milk production was estimated to be approximately 3.3 acres/cow. Under average yield conditions it was 4 acres/cow. Hoglund estimated that buying the grain rather than producing it reduced acreage needed by about one third. As herd size increased investments in a dry-lot operation became a smaller percentage of total investments compared to farms where all feed was grown. For the 80 cow operation buying all feed, the investment was about 53 percent as high as when all feed was grown. For the 240 cow herd, investments in a dry-lot operation were about 47 percent as much as when all feed was produced. that farmers should continue to grow feeds. Hoglund concluded Purchasing all feeds was not a very profitable enterprise unless herd size exceeded 240 cows. He did, however, state that/dollar invested, purchasing was more profitable than growing feed. He estimated that increasing the cost of land from $300/acre to $600/acre made all three alternatives equally profitable. One of the problems Hoglund foresaw for Michigan dairymen wishing to purchase all feeds was that of contracting for delivery of high quality corn silage or hay in quantities needed. He also states, "The large scale dairyman usually has some price advantage in buying feeds. 9 He also may gain by his ability to bargain for lower costs of hauling milk. Some large scale dairymen in Michigan are saving at least IOC/ cwt in their hauling bill." Wysong (1967) examined the feasibility of specialized dairying in Maryland for herd sizes ranging from 50 to 400 cows at a level of milk of 7,000 to 14,000 lb/cow. He essentially examined three types of operations: 1) specialized dry-lot dairy farms which purchased all forages and concentrate feeds and all dairy cow replacements; 2) stan­ dard specialized dairy farms with average crop yields which produced all of their forage requirements; and 3) intensive standard specialized dairy farms with 33% above average crop yields and 25% less crop and pasture land/cow and replacement. The intensive dairy farms also raised all replacements and all forages required. Land was valued at $200/acre with an average of 3.6 acres of land/cow on standard specialized farms. He used a constant man-cow ratio of 50 cows and 33 replacement heifers to each worker. His objec­ tives were: 1) to determine the comparative costs, net returns and investments of several types of dairy operations; and 2) to provide planning guidelines for farm managers who are making adjustments to stay competitive. He found that dry-lot dairy farms had the highest costs/cwt of milk at all herd sizes when cows were producing at a level of 10,000 lb/cow. Costs/cwt milk on the dry-lot farms were lower at a level of production of 14,000 lb of milk. He also found that costs/ cwt declined at a decreasing rate from 50 to 250 cows across all 10 types of farms. The average costs of producing milk showed little decline between 250 and 400 cows. The most rapid declines in pro­ duction costs occurred between the 50 and 100 cow herd sizes for each of the levels of milk output studied from 7,000 to 14,000 lb/cow. "These economies resulted from fuller utilization of fixed buildings and equipment on the larger farms as well as the use of larger buildings and items of equipment." Wysong concluded that even under the extreme minimum cost assumptions, the labor manage­ ment incomes on dry-lot type dairy operations were lower than on the standard specialized dairy operations operated under average or above average crop yield assumptions. Both Hoglund and Wysong found profitability of the dry-lot type of dairy sensitive to the level of milk production. Speicher approached the problem by examining returns to dairy farmers enrolled on Michigan State University's computerized farm accounting records. Partial enterprise accounting allows costs and returns to be attributed to either crops or livestock units. Exam­ ining these records, he concluded that the dairy herd carried the cropping program on Michigan farms based on conditions which existed in 1967-1969. He budgeted synthetic farms which either grew or purchased feed across herd sizes ranging from 35 to 300 cows. His conclusion was that/dollar invested, farmers who purchased feeds were most profitable. 2.1.2 What Combinations of Feeds to Grow The authors discussed above realized that the question of 11 profitability of growing versus buying feeds relied heavily upon the costs and returns to the cropping program. They essentially were concerned with categorizing the cropping program based on different levels of soil productivity which greatly influences the crop costs/acre and thus feed costs. Both Hoglund and Wysong assumed specific ratios of corn silage to hay in their models based on their conception of an economical cropping program and a speci­ fied amount of corn to achieve a given level of milk production. Other studies such as Knoblauch (1977), Schwab (1969), Hoglund et al. (1972), Parsch (1982) and Knoblauch and Milligan (1979) and Nott (1974) were concerned with each crop (e.g. corn silage, corn grain, hay) which should be raised to supply feed needs. Work by Schwab (1969) and Hoglund, Schwab and Tesar (1972) looked specifi­ cally at the economics of growing and feeding various combinations of corn silage and alfalfa in Southern Michigan considering three major soil groups and their level of productivity, and two levels of management (good and excellent) for a 120 cow dairy herd. level of milk production was assumed to be 13,000 lb/cow. sons were done using partial budgeting. The farm size The Compari­ (acreage) was based on crop yield/acre and total feedstuff requirements. Although all rations would supply adequate nutrition, the corn silage ration was the lowest cost for soil groups I and II which were highly productive soils. With group III soils (i.e. least productive), cost and yield relationships were such that the 50% corn silage ration was the least-cost. It would have required 12 a yield of 5.2 tons/acre of alfalfa production in soil groups I and II for alfalfa to be competitive. Parsch (1982) and Savoie (1982) developed a dairy forage model simulating growth, harvest, storage, handling and feeding to dairy cows. Parsch examined the impact of various ratios of corn silage and alfalfa production whereas Savoie was concerned primarily with machinery and storage alternatives and with management of the alfalfa crop. Using the model (jointly developed by both authors), Parsch simulated six alternative rations ranging between 0 and 100% corn silage size 120 or (in increments of 20%), specified for milking herds of 80 cows. For each ration, alternative dairy forage systems were designed and simulated over a 26 year period. suggested that systems low in corn silage Results (i.e. 20% corn silage) are preferred to those containing high levels of corn silage or no corn silage at all. Parsch also simulated the possibility of purchasing all corn grain for a farm with 120 cows vs. growing it. In that case, the 20% corn silage and the 40% corn silage systems were the most economical. He found that net feed costs were approximately $16,800 higher for the 120 cow systems that purchased corn grain than for 120 cow high-moisture homegrown corn systems. The trade-off was that the same 120 cow herd is fed with only 251 acres of home­ grown crops as compared with the 382 acres required of the highmoisture corn systems. He implied that on the average, a farmer purchasing corn could afford to spend a total of $128/acre to grow corn (including land charge). . 13 In a comparison of hay versus haylage systems for dairy farms in Michigan, Savoie (1982) estimated that a 100% hay system is generally less expensive than a 100% haylage system for farms growing less than 100 acres of alfalfa. Between 100 acres and 300 acres, haylage may become less expensive than hay. Although the hay system was more expensive, it offered less variability in amounts of haycrop harvested. He also found that a haylage system can produce the same quantity of feed on about 16% less land. Nott (1974) examined crop strategies for New England dairy farmers during a period of time when nitrogen and phosphorus costs were high and influenced the comparative profitability between corn silage and alfalfa. By analyzing alternative ration costs utilizing market prices instead of production costs, he identified the more profitable and less profitable feeding systems. Partial budgets computed with a least-cost ration generator indicated that the most profitable alternative was to feed all roughage as corn silage for­ tified with nonprotein nitrogen (NPN) to attain 13% crude protein (CP) on a 100% dry matter basis. He found that feeding alfalfa hay with 18.4% crude protein was better than all c o m silage with no NPN added for dairies producing 13,500 lb milk/cow/year. Whole farm budgeting was then utilized to indicate the pro­ fitability of alternative cropping systems. Farm budgets were com­ puted for small and large farms which were either extensively or intensively operated (2.5 acres/cow vs. 1 acre/cow) for 45, 50 and 100 cow farms. On the smaller farms (45, 50 cows), hay (16% crude 14 protein) was competitive only on the extensively operated farms. On the large farm (100 cows) 21% crude protein hay crop silage was the most profitable and high moisture ear corn was second. When land was scarce, the large farm would secure the most profit using NPN-fortified corn silage. However, there was little difference in profit between NPN-fortified corn silage and high quality hay crop silage. Knoblauch et al. (1981) examined capital investments, crop production costs and feed purchases relative to economical forage systems in the production of milk and beef in the Northeast United States. Their objectives were to determine the most economical systems of forage production for: milk production, finishing steers to slaughter weight, and finishing steers of a traditional beef breed to slaughter weight on a productive vs. a marginal land resource base. They also compared profitability of the various enterprises. Forage systems consisting of different proportions of hay crop sil­ age and corn silage were included. On the productive land resource, the three forage combinations were: 1) hay crop silage only, 2) equal parts hay crop silage and corn silage and 3) 70% corn silage and 30% hay crop silage. Acreage, productivity and ration constraints were specified for two soil resource situations representative of the Northeast. The most economical forage system was determined by calculating the total production, storage and feeding costs for each forage combination. This calculation was comprised of three components: 1) formulation of rations for each forage composition, 2) determination of storage 15 facilities and equipment required and the associated costs and 3) calculations of crop production costs and feed purchases or sales. On the marginal land resource system, all hay and equal parts hay and corn silage were considered. Investments and annual costs increased as the level of corn silage in the ration increased up to a level of 50% of the forage and, then, decreased with increasing levels of corn silage greater than 50% of the forage. They found the most economical forage system for the production of milk contained 50% of the forage dry matter from hay-crop silage and 50% from corn silage for the productive land resource. The sys­ tem of mostly corn silage proved less economical because of large purchases of soybean meal. the smaller herd The most economical forage system for (35 cows) marginal land resource unit was that of 100% of the forage as hay. Bratton (1982) in a management study of growing corn on New York dairy farms, analyzed dairy farm business summaries and found that the ratio of hay to corn silage in dairy rations has increased from an average, of 5.3 to 1 (1956-1960) to 2.2 to 1 (1976-1980), and that corn silage comprises almost 26% of total crop acreages. It appears that dairy farmers are supplying about 30-40% of the forage in the ration in the form of corn silage. Using Telfarm business analysis summary (1981) for 413 specialized dairy farms in Michigan, it is estimated that approximately 15% of the acres devoted to crop production for the dairy enterprises are in corn for silage. 16 One of the critical considerations in the analyses discussed above is the nutrient content of the feeds considered as well as amounts of nutrients produced/acre. NPN-treated corn silage is a viable alternative to hay or hay-crop silage for production levels considered by Nott (1974) (e.g. 13,000-15,000 lb milk). However, as farmers move to higher levels of milk production it is question­ able that there is a linear positive relationship when substituting NPN for more slowly degraded protein sources such as alfalfa hay (Hlubik, 1980). This becomes an important consideration in ration formulation especially when NPN-treated corn silage makes such a difference in the cropping strategy. Another important nutritional constraint which most of the models recognize is the differences in the net energy content of the feeds. In his analysis, Nott (1974) gives hay a net energy value of .44 Mcal/lb as compared to corn silage with a value of .72. Based on N.R.C. (1978) this seems to be an unrealistically low energy value of hay. 2.1.3 5i2e Relationships in Dairying When average total costs/unit of output decreases as the level of output increases economies of size exist. When average total costs/unit of output increase as output increases, diseconomies of size exist. Economies of size may be attributed to technical or pecuniary economies. Technical economies result from either fuller utilization of fixed assets, such as equipment, machinery and other durables, or from firm size adjustments. Pecuniary economies refer to prices paid by farmers for inputs and received for products. 17 For example, large farms may purchase fertilizer in bulk and secure price advantages compared to smaller farmers. Diseconomies of size may exist as farms become larger and include items such as costs associated with timeliness of crop and livestock operations, mana­ gerial ability, labor inefficiency, overhead costs, etc. (Harsh et al., 1981, pg. 57-58). According to Hall and LeVean (1978), "overall economic effi­ ciency is a function of both price (pecuniary) and technical effi- cience and a firm is only completely efficient economically if it minimizes cost/unit of output .... the relevant criterion is whether economic efficiency increases with farm size (i.e. whether the long run average cost curve declines as size increases)." Raup (.1969) states that as farm size increases management becomes a critical cost item. "Management skills must be learned and producing a superior manager is expensive. To discuss the effi­ ciency of farms of alternative sizes without allowing for the dif­ ferential costs of management error feedback and growth in skill, is to ignore one of the most important aspects of transition in size of farm." Stanton (1978) discovered that, "it is difficult to recognize explicitly and specifically the nature of diseconomies in a budget­ ing or economic engineering model. The technical data and cost func­ tions are simply not available to describe the rates at which either yields decline or costs increase when important diseconomies do exist. In the Lake States and Northeast where more than half of the nation's 18 dairy cows are found, 1,000 cow producing units are almost non­ existent and the number of farms with 500 or more cows is small. The logic of survivorship is rather clear. Some combination of technical relations and constraints limit the ability of most young entrepreneurs to expand much beyond 300 milking cows given current knowledge, technology and institutions." According to Lund and Hill (1979), "an indirect method of analy­ zing the existence or otherwise of economies and diseconomies of size, and of any optimum farm size, lies in the examination of farm size distribution. The underlying theory is that if there exists some optimum farm size the force of competitive pressures will grad­ ually lead to an increase in the proportion of farms of that size and the proportion of total industry output produced by them." They caution care in interpreting increases in farm size over time and relate two causes to it: profit and efficiency. Efficiency is defined as outputs/inputs and is an averaging concept. Profit maxi­ mization* is a marginal concept (i.e. the increase or decrease in total profit, given a unit increase/decrease in production). Under the assumptions of pure competition, firms maximize profit up to a level of production where marginal costs equal price of the product. This level of output will be above that at which its average costs are lowest and its efficiency highest. may be technically less Thus, a more profitable farm efficient than a less profitable one. Lund and Hill (1979) and Stanton (1978) recognize that factors other than profitability influence farm firm decisions. According to *Profit is defined as gross returns-case and certain non-cash expenses. 19 Stanton, "Over the past 75 years that agricultural economists have been studying and observing farmers and their families both in Western societies and others, some generalizations begin to emerge. It is not returns to any single scarce resource that motivates farm decisions. A farm family tries to get the most it can out of the bundle of resources it controls. that matters to a family. It is not net income by itself Rather it is some larger combination of things including survival, net income over time, enlarging the bundle of resources that the family controls and increased pres­ tige within the local social system.11 Madden (1967) reviewed economies of size studies in crop pro­ duction, specialized beef feedlots and dairy farms. studies was that of Fellows, Frich and Weeks Among the dairy (1952) which examined New England dairies using a synthetic farm budgeting technique. In this study farms with more than 35 cows were considered the larger units. Farms with 35 or more milk cows were found to have signifi­ cantly lower average total cost/unit of output than the smaller dairy farms. The average cost curve was relatively flat from the 35 cow farm to a 105 cow farm. Madden found the study consistent with broad changes in size distribution of New England dairy farms during the 1950's . Another study reviewed by Madden was that of Barker and Heady (1960) of Iowa dairy-cash-grain farms. Linear programming was used to select optimum crop rotations for herd sizes up to 64 cows. These authors found most economies were achieved by a herd size of 32 cows. 20 Only a slight reduction in costs/cow was experienced as farm size expanded to 58 cows. Madden also reviewed a study by Martin and Hill (1962) consid­ ering Arizona dairies. They found that the average cost curve de­ clined sharply up to a herd size of approximately 150 head, grad­ ually declining to 250 to 350 head and then gradually rising as herd size approached 600 head. The analysis did not consider al­ ternative milking-barn technologies for each size group. The last study reviewed by Madden was that of Buxton and Jensen (1964) who conducted a completely synthetic analysis of Minnesota dairy farms using linear programming. Alternative farm enterprises considered were: hogs, corn, soybeans, and herd sizes up to 90 cows. Buxton and Jensen estimated that all the economies of size were achieved by a 1-man, 48-cow dairy, using a double-6 herringbone milking parlor. Madden found these studies difficult to compare for the following reasons: 1) assumptions and procedures varied from one study to the next; 2) there is no common measure of average total cost among the studies; 3) they differed in the degree to which the synthetic-firm economic engineering approach was used. The Iowa and Minnesota studies considered modern milking parlor arrangements for all dairy sizes, not limiting the resource combinations to those found on existing farms. The Arizona study considered only the typical barn technologies for each size group as they were observed in the sample dairies. The New England study considered only those technologies in use at the time. Madden commented that the coordination and supervision problems 21 increased with the size of herd and the labor force in the Arizona study. He also noted that management experienced increased diffi­ culty in coping with feed price uncertainty as there was not enough time for "shopping around" in buying feed. Wysong (1965) examined the economies of large size in the pro­ duction of fluid milk on specialized dairy farms in Maryland. His objectives were: 1) to obtain data on physical input-output relation­ ships for the whole farm business, and 2) to determine cost economies and diseconomies on commercial dairy farms of different sizes. Survey data was obtained by personally interviewing dairymen in the Piedmont area of Maryland. In examining herd sizes up to 400 cows/farm, labor efficiency showed little tendency to increase beyond the average level of about 30 cows/man. He found that farms between 50 to 100 cows can attain relatively high levels of labor and capital efficiency/worker. The major economies in the utilization of buildings and equipment were obtained at the 100 cow level, although additional economies did occur as size increased to 400 cows/farm. Therefore, the major advantage of moving to larger size farms beyond the 100-cow level lies in the in­ creased net return/operator. The larger number of cows increased net returns primarily from greater milk sales, and only slightly from re­ duced average total costs/unit of output. Matulich (1978) studied efficiencies in large scale dairying in the Chino Valley of California where dairying is intense. size herd there is 600 cows confined to 10 to 60 acres. The average Several herds 22 are in excess of 2,000 cows. His analysis investigated herd sizes ranging from 375 to 3,600 cows. The dairy was dis-aggregated into: milking, housing and feeding components. Detailed input-output rela­ tionships were specified for each component and combined to model dairies of various sizes. Required quantities of fixed and variable inputs were combined with their market price to synthesize both shortrun and long-run cost functions. This allowed analysis of typical and new, but not widely adopted dairy production technologies. Alternative milking parlors and varying degrees of mechanization were of primary importance in determining the annual cost of the milking component. Herringbone, side-opening and polygon parlors were selected as relevant to large scale dairying. The feeding component was analyzed in two parts. First, three alternative feeding programs were modeled with a linear program that maximizes income over feed costs. The typical feeding program was modeled as a single "commercial-mixed" ration fed in equivalent quan­ tities to all lactating cows. Second, feed delivery and storage systems corresponding to the three feed programs were examined. Dry-lot corrals and covered free-stalls with adjacent loafing pens were the housing systems considered. Significant economies over much of the 375 to 1,200 cow herd size range were found. Unit costs declined $64/cow from $1,056/cow to $992/cow in going from the 375 cow herd to the 750 cow herd. Costs/cow were approximately the same for the 900 and 1,200 cow dairies. Milking parlor automation and better capacity utilization were the principal origins of efficiencies. 23 Over 60% of available unit cost reductions were realized between the 375 cow herd (the only non-automated dairy) and the 450 cow herd. Further unit cost reductions to the 750 cow herd size resulted from better utilization of the milking parlor in conjunction with changes in particular parlor configurations. Matulich emphasizes three major characteristics which distinguish industrialized dairying from that of small multi-enterprise dairying: 1) a well developed feed market and distribution center, 2) yearround availability of quality labor is essential, 3) the level of managerial and operational expertise required of industrialized dairy­ ing differs from small multi-enterprise operations. He states, "The long-run average cost curve derived in this study is representative of similar industrialized production regions (e.g.. California, Arizona, Florida and Texas), but the analysis offers potentially broad implica­ tions regarding future structural change throughout the dairy industry. The reported efficiencies are not limited to the exclusive domain of specialized dairies. of size is mobile. Much of this technology contributing to economies However, specialized management over each of the enterprises is essential to achieve comparable efficiencies. Moreover, the technological advances may be transferable to dairies smaller than examined in this study." 2.2 Basic Economic and Management Theory 2.2.1 Management Management is concerned with decision making. In an economic sense it is concerned with maximizing the rate of return to 24 a given amount of capital invested, considering various possibilities of resource employment and the risks involved. The rate of return is that interest rate which equates the present value of cash receipts expected to flow from an investment over its lifetime, with the present value of all expenditures relating to the investment (Spencer et a l ., 1975). Managers deal with three basic interdependent questions: 1) what to produce? 2) how to produce it? and 3) how much to produce? (Harsh et a l . , 1981). 2.2.2 What to Produce and How Much? Consider an investor (or group of investors) with a given amount of capital to invest in a dairy farm. An important considera­ tion is whether to invest all capital in cows and dairy facilities or invest in cows and enough crop land and machinery to raise crops to feed the herd. Although crops are necessary complements to produce milk, the enterprises are competitive because the ability to trade allows for the purchase of crops. Thus, the dairy and cropping enter­ prises are in competition for the limited capital available for invest­ ment. Model 1 First consider the cropping and dairy enterprises as selling their products in the market. Figure 2.1A is a hypothetical production possibility curve, and assumes constant returns to size. the various combinations of dairy It shows (milk) and crops which could be produced for a given number of dollars to invest in a dairy or in a cropping enterprise. 25 B . Labor A. $ Invested Dairy Yi Dairy Crops Y2 Crops C. $ Invested and Labor *2 D. $ Invested, Labor and Profi isorevenue Dairy Y Dairy Y 1 a Crops Y E. $ Invested and Profit Dairy and Buv Feed y 1 • iscrevenue Dairy and Grow Feed Figure 2.1. Production possibilities (heterogeneous inputs). 26 A maximum quantity of crops Y^ could be grown if there is no dairy (.Y^) . By giving up some crop production, investments can be made in a dairy operation. This process substitutes dairy cattle for crop production in the product mix. The basic problem is to select (within the constraints imposed) the "optimum" product mix. The production possibility curve in Figure 2.1A is concave to the origin indicating a diminishing rate of marginal substitution of Y ^ for Y . As movement is made from point to point to the right, the absolute value of the slope of the curve (AY^/AY^ is increasing. To obtain one more unit of Y 2 , more and more Y^ must be foregone as Y 2 increases. Each point on the curve in Figure 2.1A represents a feasible product mix that will utilize all of the available investment money. Each point in the shaded area represents a feasible product mix that will leave some of the investment unused. A production possibility curve could be drawn for each of the limiting resources. Figure 2.IB shows the various combinations of crops and dairy assuming a fixed supply of labor. The curve would be linear if each unit of labor were homogenous. Figure 2.1C shows the two production curves superimposed. shaded region is a set of points common to both curves. The Only those points within the shaded region of Figure 2.1C are feasible, given the limitations of labor and capital. Once the set of feasible product mixes has been delineated the optimum product mix can be derived. tribution of the two products. This depends on the relative con­ Contributions are determined by the 27 prices of the products and by prices and amounts of the inputs required to produce them (i.e. by some measure of net profit/unit of product). An isorevenue (isoprofit) line shows the various combina­ tions of two enterprises that will produce the same amount of income. There is an infinite number of isorevenue lines. The one which is just tangent to the production possibilities curve determines the . . optimum combination by its point of tangency. This is the point where: ay1/ ay2 = py2/py In Figure 2.ID the optimal product mix occurs at point z where "a" units of Y^ are produced and "b" units of Y^. The slope of the isorevenue line depends upon the relative contribution of Y^ and Y 2 , considering both product prices and input costs. The slope is cri­ tical in determining the product mix. Using a straight line for an isorevenue line implies: 1) that product prices do not change with the amount of products produced, implying a horizontal demand curve, 2) costs/unit of input is con­ stant. duction. Constant unit costs is not typically observed in actual pro­ Diminishing marginal factor costs and diminishing marginal returns to production as output increases is more commonly the case in agriculture. Diminishing marginal factor costs would make the isorevenue line concave to the origin, diminishing marginal returns would make the isorevenue line convex to the origin (Haynes and Henry, 1974, pg. 265). Model 2 Instead of selling the crops produced, assume they are used by 28 the dairy enterprise as the feed input. The possibility exists to either grow or buy crops needed for the dairy. Since grown or purchased crops are perfect substitutes, the question becomes: Is it more profitable to grow or buy crops? This question cannot be answered using Figure 2.ID because there is no direct measure of profitability of growing crops used in the dairy enterprise to establish an isoprofit line. As an alternative illustration, consider two enterprises: 1) "dairy and grow feeds" and 2) "dairy and buy feeds" as in Figure 2.IE. Now the question can be addressed by examining the profit­ ability of each alternative "strategy" of dairying. Model 3 From an investment standpoint the question of growing vs. pur­ chasing crops is a critical consideration. Money invested in .crop machinery and land could be used to establish a larger dairy. Es­ tablishing a larger dairy may achieve economies of size due to de­ creased average fixed costs of buildings and facilities/unit of out­ put. A larger investment in the dairy enterprise also allows switching to a different level of technology, resulting in a more efficient level of production. Farms organized to dairy and crop farm have the potential to achieve economies of size in regard to both dairying and cropping if_ the investment is large enough. If the investment isn't substantial enough to achieve significant economies of size, it may well be that specialization in dairying is the more profitable alternative. It is a matter of discerning whether the economies of 29 size achieved by specialization in dairying offsets a possible price advantage of reducing feed costs by growing feeds. Figure 2.2A-D demonstrates how the production possibilities curve changes as the level of investment changes when economies of size exist. As the level of investment increases, economies of size rela­ tive to the "dairy and buy feed" are indicated in Figure 2.2A-C. At a level of investment indicated in Figure 2.2D, economies of size are experienced relative to the "dairy and grow feeds" enterprise. these curves become concave to the origin As (with increasing levels of investments), it is apparent that there will be a tendency to special­ ize in one strategy of dairying vs. the other. This will depend on the slope of the isorevenue line (determined by price ratios) as well as the level of investment. 2.2.3 Comparative Advantage Another way of approaching the question, as to which is the most profitable strategy of investment, is through the concept of comparative advantage. This states that a product will tend to be produced by a firm when its relative advantage in producing one pro­ duct compared with another product is greatest (Dolan, 1977). An example of comparative advantage would be the tendency of corn to be produced in the Midwest Lake States. (Corn Belt) and milk to be produced in the The crucial element in comparative advantage is com­ paring the marginal rate of product substitution. Consider the following hypothetical situation in the Corn Belt and the Lake States in the production of corn and milk (Harsh et al., 30 1981). Notice in Table 2.1 that both milk and corn require less labor/ton of output in the Corn Belt than in the Lake States. Thus, the Corn Belt has an absolute advantage in producing both goods with respect to labor. There are differences in the opportunity costs of producing these commodities between the two regions. For example, consider the cost of each good in each region not in terms of labor, but in terms of the other good. In the Corn Belt producing a ton of milk means foregoing the use of 4 hrs of labor for corn production. The opportunity cost of labor in producing milk is: (4 hrs of labor used for milk production/1.5 hrs of labor used for corn). This results in the loss of the opportunity to produce 2.67 tons of corn for every ton of milk produced. for milk = 2.67. The rate of substitution of corn In the Lake States, producing a ton of milk means giving up 5 hrs of labor which would produce 2.5 tons of corn. Thus the rate of substitution of corn for milk is 2.5 in the Lake States which is different from the opportunity cost in the Corn Belt. In terms of relative opportunity cost, milk is cheaper in the Lake States than in the Corn Belt. The region in which the cost of pro­ ducing a good is lower is said to have a comparative advantage in pro­ ducing that good. Although the Lake States have an absolute disadvantage in the production of both goods, they can maximize their position by spec­ ialization in the production of milk as opposed to producing corn. Corn Belt can maximize its position by producing more corn, and trading the corn for milk from the Lake States. Comparative advan­ tage explains why there is a tendency for specialized regions of The 31 Level 3 Level 1 Dairy and Suv Feed Dairy and Grow Feed Dairy ar.d Level 2 Dairy and Buy Feed Level 4 Dairy and Buy Feed Dairy and Grow Feed Figure 2.2. Production possibilities to size). (increasing returns 32 production for certain agricultural commodities. Table 2.1. Hours of Labor Used in Producing Milk and Corn in the Lake States and Corn Belt (Hypothetical) Hrs of Labor/Ton Output Lake States Corn Belt Milk 5 4 Corn 2 1.5 2.2.4 How to Produce The firm seeks to produce a given amount of product at the cheapest cost considering the inputs and processes involved. For example, consider the amount of forage and grain needed to produce the level of milk shown in Figure 2.3. Any combination of X^ and X^ that will produce the same quan­ isoproduct line forage(X ) tity of milk are located along the isoproduct line. For example, the same quan­ tity of milk can be produced using a^ amount of X^ and b^ isocost line amount of X^ or a^ amount of X^ and b 2 amount of X 2 * X^ and X 2 are said to be comple­ ments in that some grain Figure 2.3. *> How to produce. and some forage (X^) (X^) are re­ quired to produce the amount 33 of milk represented by the isoproduct line. X-j^ and X2 are said to be substitutes in that we can exchange grain for forage in the pro­ portions indicated on the isoproduct line and still produce the same amount of milk. The relative costs of inputs determine the least-cost combina­ tion of inputs to use to produce a given amount of output. The isocost line indicates the amount of X^ and X w h i c h can be purchased for a given amount of money. The solution for the least-cost combina­ tion of inputs (considering these 2 inputs only) is determined at the point where the isoproduct line is tangent to be isocost line closest to the origin. That is, the marginal rate of substitution for the inputs is equal to the inverse price' ratio 2.2.5 (Harsh et al., 1981). Capital Budgeting Economic theory is useful in understanding behavior of the firm but is difficult to apply directly to any business. Managers do not have a complete set of information from which to make choices, and the alternatives available are limited. Also, there are varying degrees of risk involved which cannot be completely evaluated. None­ theless, business managers do have methods of analyzing the profita­ bility of business ventures. The process of allocating capital among alternative investment opportunities is called capital budgeting. The firm selects a product mix that appears to offer the best prospects for achieving its objectives by projecting the consequences of investing in plausible alternatives. Capital buigeting involves defining the revenues and costs over the horizon of the investment period for each 34 alternative considered and involves several steps. 1. A search of profitable investment opportunities 2. Determining the amount of capital required by each alterna­ tive 3. A forecast of the cash flows which will likely result from each investment 4. A method for computing the cost of capital which takes into account the availability of funds 5. A method for computing future cash flows and the time value of money 6. Determining the criteria or methods to select the most profitable investment(s) (Harsh et al., 1981) Annual revenues and costs over the investment period can be projected using forecasts of prices of inputs and products for each investment. The value of future costs and returns can be discounted to the present enabling a common point in time as a basis for com­ parison. The average revenue/unit of time is then calculated since the profit objective involves maximizing average net revenue/unit of time. This is comparable to an annuity (Paris and Reed, 1960). Investments with a positive present value are profitable. Ranking investments by the rate of return on investment enables comparisons of projects involving different amounts of dollars in­ vested or different lengths of time. 2.2.6 Determining Annual Costs of Durable Assets Total annual costs include a charge against all inputs used in the production of goods. Inputs which are used and whose life is less than 1 year are referred to as non-durable or current 35 goods. Those which have a life greater than 1 year are referred to as durable goods. The firm expresses annual output as a function of current inputs and the stocks of durable equipment and inven­ tories of inputs, and goods-in-process employed in production (Smith, 1961). Consider a production function with only two inputs, one current (X^) and one durable (X^). Assume that the durable good has an infinite life and requires neither repairs or maintenance. The production function can be written as: Y = F (X , X 2 ) Assuming an infintely long planning horizon, the annual outlay for current inputs is * X^, where W 1 is the price of X^. If W 2 is the price of X2 then W 2 * X^ is the investment in durable goods. As X2 has an infinite life, a method must be employed to assess an annual charge for the use of this durable good. This charge should be the opportunity cost of capital invested in X2 . The opportunity cost is the amount of money which the investor has foregone by em­ ploying capital in X^ instead of the next most profitable alterna­ tive. The opportunity cost is reflected in the discount rate (r) which represents the required rate of return on investment by the investor. The annual cost on an initial investment is: r * W 2 * X^. Therefore, total annual cost is: W 1 * X 1 + r * w 2 * X2 The second term is the depreciation on the investment W * X^. Next, assume that the durable good requires replacement every L years but has zero salvage value. If the planning horizon is 36 infinite, the annual cost of current inputs is W * x . W 2 * X2 dollars must be invested initially and every L years' thereafter. The opportunity cost of capital invested in X b e c o m e s : r * W2 * X2 / (1 - l/ll+r)L ) This formula is essentially that developed by Smith (.1961) . Smith's present value formula is based on continuous compounding using the expression (1 - e ) to explain the value of the geometric series of investments in W 2 * X^. The substitution of (1 - l/(l+r)L ) is basecl on compounding at yearly intervals. If either the discount rate or the life of the durable is short, the depreciation charge becomes / L which is the ordinary straight-line method of depreciation. Next, consider durable goods which have a salvage value at the end of every L years, when they are replaced. Using P to represent the initial investment in X 2 (formerly represented by W 2 * X 2 ) and S to represent the salvage value, the annual use charge for capital invested in durable goods with a fixed life and a salvage value can be approximated by the following formula: r * P/(l - 1 / (1+r)L ) - (r * S/(l - l/(l+r)L ) + r * S (Black and Fox, 1977) This formula does not account for maintenance and repair costs of durable assets which must be included in the total cost estimate. Maintenance and repair of durables are typically estimated by engin­ eering equations considering the rate of use and age and are depen­ dent upon the particular investment in question. It is also necessary to include estimates of annual insurance and taxes if applicable. 37 2.2.7 Risk Risks are also a major investment concern. Lacking per­ fect knowledge we can at best predict the future using probability distributions based on previous observations, correlations and know­ ledge. This is classified as statistical risk by Knight (1921). The confidence with which we can define the future, the ability to adapt to changes (flexibility) and the personal consequences of success or failure are three factors which influence willingness to engage in risky situations. Each investment has different risks and degrees of risk involved. The traditional Midwest dairy farm includes a land base to grow feeds and has been viewed as a relatively safe investment. Land is a secure investment in that the value of land increases with time and land is a flexible asset which can produce a wide variety of pro­ ducts. Farms with both dairy and cropping enterprises depend upon this diversification to stabilize their income. This will be true: 1) as long as income from the two enterprises varies in opposite directions (i.e. they are negatively correlated) or 2) there are com­ plementary relationships which makes this combination more profitable than either one considered separately, or 3) the combination allows the flexibility to shift emphasis from one enterprise to the other to take advantage of short term comparative advantages or opportuni­ ties which arise. Specialization is a consequence of trying to become more effi­ cient and reduce costs. Specialization usually involves devoting 38 one's resources to the one most profitable enterprise and-becoming as large as possible in regard to that enterprise for a given number of dollars to invest. ialized dairy farms From the traditional viewpoint of risk, spec­ (i.e. those with a limited land base which purchase feeds) increase risk in that they are less flexible and there is no supplemental income from other enterprises to rely on when dairying is unprofitable. On the other hand, as an enterprise becomes more specialized and size increases (for a given number of dollars invested) and feed costs are lowered/unit of output pro­ duced, the impact of changing input and product prices will have less affect on total profitability due to these decreased costs and also due to increased output from a larger sized operation. In this sense then, specialization is actually a form of risk reduction. The question of which strategy (specialization vs. diversifica­ tion) is most profitable should consider these factors (i.e. the complementary relationships of diversification and the economies of size that exists with specialization). The sensitivity of the pro­ fitability of these strategies to change in milk prices, feed prices, and other inputs should reveal which strategies are most risky. CHAPTER 3 PROTOCOL 3.1 Objective The objective of this research is to examine the profitability of different strategies for securing feeds on dairy farms in Southern Michigan and similar areas. These strategies include: 1) farms with ownership of sufficient capital assets to grow forages and grain (GFG), 2) those with assets to grow forages only (GF) and, 3) those organ­ ized to purchase all feeds protein and minerals. (PR). All strategies purchase supplemental The forages considered are alfalfa and corn silage and corn is the grain crop. The impact of various levels of milk production, categories of soil productivity (as estimated by soil management groups), feed prices, milk prices and land prices on profitability is analyzed for different levels of investment. 3.2 Protocol The electronic spreadsheet template: Microsoft Multiplan (Zenith Data Systems, 1982) is employed to model the three strategies: GFG, GF and PR. Synthetic farms of various herd sizes are first assembled to generate estimates of investments, costs, incomes and profits for each herd size within each strategy. These budgets are assembled based on assumptions and specifications outlined in Chapter 4. 39 40 Estimates of profit according to herd size (representing dif­ ferent investment levels) provides a basis to regress profit on dollars invested for each strategy. Strategies can then be compared on the basis of profit, given equal levels of investments across all strategies, to determine the most profitable strategy (see Figure 3.1). This is a static model which is useful in projecting long-term profit expectations. It does not consider within year or across years price and yield variations, income taxes, method or details of financing or yearly cash-flow requirements necessary to keep the business solvent. Real interest rates are used and the model assumes that income and expenses inflate at the same rate. Total investments for each farm include investments in feed stor­ age facilities, dairy housing and facilities and equipment, and dairy cows. Investments in crop land and machinery are included for the strategies which include crop production (i.e. GFG, G F ) . Annual costs are divided into two categories: feed costs and other dairy costs. Annualized costs of feed storage facilities and purchased feed costs (including interest) comprise the feed cost for farms PR. Annualized costs charged for crop land, crop machinery, crop labor, crop expenses (including interest), feed storage facili­ ties and purchased feed costs are summed to compute total feed costs for farms GFG and GF. Annualized costs charged to dairy cows, housing and facilities and dairy equipment and livestock labor are added to feed costs to estimate total annual costs for each herd size within each strategy. 41 The annual cost of capital (C) invested in durable assets (e.g. feed storage facilities, crop machinery, housing and facilities and equipment) is based on the opportunity cost of capital approximated by the real interest rate (r), the purchase price of the asset the useful life of the asset (L) and its salvage value (S). (P), The capitalization formula below is used to estimate this charge. C = r * P/(l - 1/ (1+r)L - (r * S/(l - l/(l+r)L ) + r * S (see Black and Fox, 1977) Land and cows are considered durable assets with an infinite life. The annual cost of these capital items is estimated by multiplying the interest rate by the purchase price. Annual income is derived from the sale of milk, cull cows, and heifers, deacon calves and excess replacement heifers. Consid­ eration of the fertilizer value of manure, savings in soybean meal purchases for farms GF and GFG, and savings in machinery and equip­ ment costs due to complementary relationships are accounted for when appropriate. Profit is defined as annual income - total annual costs. Profit is actually returns to management as labor and capital are accounted for in the estimate of total annual costs. Farms of herd sizes of: 40, 75, 150 and 300 cows ments) are synthesized for strategies GFG and GF. (plus replace­ Herd sizes of 40, 75, 150, 300 and 500 cows are budgeted for farms PR. Spanning these herd sizes within each strategy includes changing investments, costs and returns as herd sizes and crop acreages expand and considers the 42 technical economies which exist for the specific set of resources and technology modeled. Linear estimates of profit, rate of return on investment (RROI), number of cows and number of laborers are summarized across all strategies for levels of investment of: $.5, 1.0, 1.5, 2.0 and 2.5 million. The budgeting model developed permits the user to consider milk production levels thousand lb. (rolling herd averages) of: 13, 15, 17 or 19 Soils in management groups: 2.5, 3 or 4 can be specified as well as the prices of milk, corn, and land. Other prices (e.g. labor, fuel, fertilizer and the interest rate) can also be changed by the user. The prices of hay, corn silage and soybean meal are en­ dogenous and depend upon the price of corn. The prices of cull cows and heifers, deacon calves, and excess replacement heifers are endog­ enous and depend upon the price of milk. This model is employed to estimate profitability and relative ranking of strategies based on the most likely economic conditions facing the dairy industry for the 1980's considering: 1) various levels of milk production 2) changes in the milk/feed price ratio caused by changing the price of milk or by changing the price of the feeds 3) various land prices 4) various soil management groups 43 The user specifies: soil management group = 2.5, 3 or 4 milk production (thousand lb) = 13, 15, 17 or 19 price of land ($/acre) Price of milk ($/cwt) price of corn ($/bu) and can also specify: price of nitrogen, phosphorus and potassium ($/lb) prices of dicalcium phosphate, salt and limestone ($/lb) property tax charge, insurance, real growth rate in land values and real interest rate price of labor ($/hr) and price of fuel ($/gal) __________________________________ j/_____________________________ The model estimates the appropriate investments and costs and incomes for each herd size (40, 75, 150 and 300 cows for the strategies GFG or GF and additionally 500 cows for the strategy PR). Total profit, rate of returns on investment (RROI), total investments, total man equivalents and costs/cwt milk are pro­ jected. ± ____________________________________ Estimates of profit across herd sizes are regressed on total dollars invested for each strategy to enable a comparison of strategies based , equal dollars invested in farms of all three strategies. j Projections are summarized for levels of investments of: $.5, 1.0, 1.5, 2.0 and ! 2.5 million. ! Using this model the user can: 1) compare profits within each strategy across herd sizes for a given set of specifications. 2) compare strategies across herd sizes on the basis of profit/dollar invested. 3) examine the sensitivity of the analysis to changes in the inputs. Figure 3.1. Flow Chart of the Dairy Investment Model CHAPTER 4 ASSUMPTIONS AND SPECIFICATIONS OF THE INVESTMENT MODEL This chapter discusses the formulation of the model. The components of the model are discussed in four categories. 4.1 4.1 Items dealing with feed costs 4.2 Dairy expenses 4.3 Incomes and adjustments to costs 4.4 Setting prices in the model (other than feed costs) Feed Costs Investments for all strategies include feed storage facilities. Land and crop machinery are also included for farms growing grain and/or forages. Annual feed costs include annual expenses incurred from the investments above plus cash crop expenses, interest charged to cash crop expenses, crop labor and purchased feed costs. For those farms purchasing all feed, interest on purchased feed costs is also included. 4.1.1 Ration Specifying the ration sets the stage for the analysis as it determines the feeds and quantities of feeds that are to be purchased and grown. This dictates the number of acres of crops needed to grow 44 45 feeds (based on expected crop yields), which defines the crop mach­ inery complement needed, which defines the crop labor needed and so forth. The model includes rations for levels of milk production of 13, 15, 17 and 19 (thousand lb) rolling herd average production. The ration composition is critical in achieving a particular level of milk output given the genetic potential to produce at that level. There are many combinations of feeds that will meet the nutrient requirements. Typical dairy rations in Michigan include corn grain, corn silage, alfalfa and soybean meal. These feeds form the basis for the rations formulated for the model which are presented in Table 4.1. They are based on the following assumptions: 1) The forage dry matter for the lactating herd is 60% alfalfa and 40% corn silage. This is significant in that it dictates the cropping program and machinery complement for farms growing forages. It also implies that farmers purchasing feeds live near sources of corn available as silage. This combination of forages was one of the low cost systems found by Parsch (1982). This cropping combina­ tion also permits a more even distribution of labor over the cropping season than an all hay or all corn silage forage system. Including corn silage helps ensure an energy dense ration which is important for herds at high levels of performance. Alfalfa is important for its contribution as a source of fiber and protein and helps to offset soybean meal purchases. 2) Alfalfa is fed in the form of hay to all herds; haylage is included in the rations for all but the smallest herd size (i.e. 40 cows) for the strategies which grow forages. Including haylages 46 permits harvesting alfalfa under unfavorable weather conditions for hay. It is a common practice to harvest much of the first cutting hay crop as haylage due to rainy weather conditions in Michigan in late May and early June. Haylage is not included for the 40 cow herd as it is not deemed to be cost effective due to the added machinery and feed-storage investment incurred. Harvesting alfalfa as haylage results in a higher harvested yeild/acre and an increase in the nutrient content losses. (particularly protein) due to decreased leaf It is assumed that haylage supplies 60% of the total alfalfa dry matter when it is included in the ration. 3) Corn is considered as in drying expenses and allows high moisture shelled corn. This saves corn to be ensiled. 4) The nutrient content of feeds are based on the sample means of Michigan feeds analyzed at Ohio, adjusted by a safety factor (fraction of a standard deviation) to ensure feeds satisfy nutrient specifications a given percent of the time. are located in Tables 4.2 and 4.3. Feed nutrient densities The protein and energy content of alfalfa are very important determinants of feed cost and production level. It is not uncommon for the protein content of haylage to exceed 20% for an alfalfa crop that is well managed. For the purpose of this analysis however, the adjusted mean value of alfalfa and alfalfa mixed with grass is used (see Table 4.3). 5) The dry matter content of feeds are: shelled corn, 70%; corn silage, 35%; hay, 87%; haylage, 50%; soybean meal, 87% and dicalcium phosphate, limestone and salt, 100%. 47 Table 4.1 Characteristics of Rations for Lactating Cows Characteristic Forage:Concentrate (DM basis)3 Energy conc.(NE,Mcal/lb DM) Crude protein conc.(% DM) Average daily milk production Level of production balanced for (lb milk/day) (lead factor - 1.15) Estimated dry matter intake (lb/day) Net energy required (Meal) Crude protein required (lb). Net energy required(Mcal/lb DM) Crude protein required($ DM) Crude protein (% grain DM) Grain(% of grain as soybean meal) Calcium (% in ration DM before minerals added) Phosphorus (% in ration DM before minerals added) Dicalcium phosphate (lb/day) Limestone added (lb/day) Salt added (lb/day) Calcium (% in ration after minerals added) Phosphorus (% in ration after minerals added) Corn (shelled) (lb DM/day) Soybean meal (lb DM/day) Corn silage (lb DM/day) Hay crop (lb DM/day) 305 Day Milk Yield 13,000 15,000 17,000 19,000 70:30 .68 13.0 42.6 60:40 .70 14.0 49.2 50:50 .73 15.0 55.7 43:57 .74 15.5 62.3 49.0 56.0 64.0 71.0 39.5 26.0 5.1 .67 13.0 14.0 41.5 28.0 5.7 .68 14.0 16.3 43.5 31.0 6.3 .72 14.5 17.5 45.5 33.0 6.9 .73 15.3 18.0 10.0 15.0 18.0 20.0 .6 .52 .45 .41 .26 .22 .27 .22 .28 .24 .15 .2 .2 .2 .28 .24 .10 .2 .72 .63 .67 .64 .36 I Q .5 1.2 10.9 16.4 .37 13.9 2.5 9.8 14.8 .38 17.6 3.9 8.6 12.9 .38 20.0 5.2 8.0 11.8 0 0 aAssumes the NE content of the grain mix ^ .87 Mcal/lb and the NE content of the forage mix = .6 Mcal/lb. Table 4.2. Nutrient Content of Michigan Feeds Analyzed at Ohio3 (Dry Matter Basis) Feed no. X % DM SD % CV X % CP SD % CV X % TDM SD %CV no. X % ADF SD % CV % P SD % Ca SD % CV X .113C .07 66.1 .22 .07 31.4 X % CV 76 77 5 6.5 10.8 1.7 15.7 90.5 3.1 3.4 1 2.8 -- --- Corn silage 270 37 11 29.7 9.2 2.2 23.9 70.1 5.9 8.4 6 27.2 1.9 7.0 •33d .18 54.5 .27 .07 25.9 Alfalfa hay 175 87 4 17.0 3.2 18.8 57.8 4.9 8.5 9 36.1 6.2 17.2 1.34 .32 23.9 .28 .08 28.6 Alfalfa-grass hay 102 89 3 3.3 14.5 3.8 26.2 55.1 3.5 6.4 2 42.1 2.1 5.0 1.17 .44 37.6 .27 .08 29.6 Alfalfa-alfalfagrass hay*3 277 87 3.6 --- 16.1 3.4 -- 56.8 4.4 -- - 38.4 4.7 1.28 .36 28.1 .276 .08 29.0 Shelled corn 4.5 -- cl Source: Thomas, 1979. ^Tliis is the composition of the weighted average of samples of alfalfa and alfalfa-grass hay. cShelled corn calcium content is quite different than that listed in 1978 N.R.C. dThe calcium content reported ranged from .11 to 1.07%; 1.67 is either aldulterated corn silage or a printing mistake. 49 6) (1978). Nutrient Content of Feeds Used in Estimating Feed Budgets (Dry Matter Basis) for the Model 10.3 .89° Corn silage 35 8.5C 89 15.0d 89 Dicalcium phosphate Limestone Alfalfa hay crop b Soybean meal a a\ 00 o 85 % Ca • Shelled corn (dry) % ADF CM Meal NE/lbc O % CPC o CO % DM • CM Feed % P to o Table 4.3. • N.R.C. Nutrient requirements for protein and energy are based on 26.8C .29 .26 .55 37.6C 1.21 .26 50.0 .85 10.0 .36 .75 — --- -- --- 22 18 ”““ —— —— — — 38 aThe weighted average of nutrient values of alfalfa and alfalfagrass hay was used as an estimate of the nutrient content of hay used in the analysis in regard to protein, energy and fiber. ^The nutrient content of soybean meal was estimated using N.R.C. (1978). cThe nutrient content o f 'feeds is based on the average content of Michigan feeds analyzed at Ohio weighed by a fraction of the standard deviation of that nutrient, e.g. shelled corn protein = 10.8 - .3 * (1.7) = 10.3. Using .3 * SD estimates the nutrient value which should be surpassed by 62% of the population (using Z table distribution; Zar, 1974, pg. 412). <^As hay is of the most important protein sources the average value for alfalfa protein is estimated as 16.1 - .3 * (3.4) = 15.0. This value should be surpassed by 62% of the hay population. Using these safety factors, approximately only 5% of the time will hay and corn silage and shelled corn nutrients be less than the table values for all three feeds (assuming feed nutrient contents are not correlated among feeds). Only 14% of the time will 2 of the 3 feeds have values lower than the mean and 38% of the time at least one feed will have a protein value lower than the mean. 50 7) Dry matter intakes for lactating cows are based on the aver­ age daily milk produced over the entire lactation using the equations Dry matter intake (DMI) = (2 + .022 * lb of 3.5% fat milk) * (cwt body weight) (Hlubik and Thomas, 1980). It is assumed that cows weigh 1350 lb. 8) Rations for lactating cows are balanced using a lead factor of 1.15 x average daily milk production. This is approximately the same as dividing the herd into a high and low group, balancing the high group based on requirements and intake 60 days into lactation and the low group balanced at 150 days into lactation. 9) Quantities of feeds needed are based on amounts to meet nutrient requirements of lactating cows according to their level of milk production as well as feed needs of heifers and dry cows. Ex­ pected feed intake, nutrient content of feeds and losses in feeding and storage are considered. Quantities of feeds needed/cow and replacement are located in Table 4.4. Quantities of feeds needed are similar to those summarized for Telfarm farmers as reported in Table 4.5. 51 Table 4.4. Quantities of Feed Needed/Cow and Replacement/Tear by Production Level Feed Lactating® cow Dry° cows Youngstockc Total Storage Total and feed needed lossd Production level of 13,i000 lb, 3 .S% milk Shelled c o m (87% DM) Soybean meal(87% CM) Hay crop(87% DM) C o m silage (35% DM) Dicalcium phosphate (100% DM) Salt(100% DM) 66 410 2.9 4.8 Shelled c o m (87.% DM) Soybean meal (87% DM) Hay crop(87% DM) C o m silage (35% DM) Dicalcium phosphate (100% DM) Salt(100% DM) 88 863 2.6 4.3 Shelled c o m (87% DM) Soybean meal (87% 1X4) Hay crop(87% DM) C o m silage (3S% DM) Dicalcium phosphate (100% DM) Limestone(100% DM) Salt(100% DM) • 110 1357 2.3 4.3 bu lb ton ton 2 — .5 .8 bu ■— ton ton 12 100 2.2 3 bu lb ton ton 82 510 5.6 8.6 bu lb ton ton 8% 5% 16% 18% 87 535 6.5 10.1 bu lb ton ton -----70 lb 25 lb 100 lb . 95 lb 5% 60 lb 5 lb 25 lb 5% 95 lb 90 lb ‘ Production level of 15,1300 lb, 3 .5% milk bu lb lb .' ton 2 bu --.5 ton .8 ton 12 100 2.2 3 bu lb ton ton 102 963 5.3 8.1 bu lb ton ton 8% 5% 16% 18% 110 1011 6.2 9.6 bu lb ton ton 70 ton 5 lb 25 .lb 95 lb 100 lb 5% 90 lb 95 lb 60 lb 5 lb 25 lb 5% Production level of 17,1300 lb, 3..5% milk bu lb ton ton 2 bu --.5 ton .8 ton — — 70 lb 30 lb 60 lb 5 lb Production level 12 100 2.2 3 bu 124 bu lb 1457 lb ton 5.3 ton ton 8.1 ton 8% 5% 16% 18% 25 lb 95 lb -30 lb 25 lb 90 lb of 19,000 lb, 3..5% 134 1529 6.2 9.6 bu lb ton ton 100 lb 5% 32 lb 5% S% 95 lb milk 157 bu 8% 131 bu 12 bu 144 bu Shelled c o m (87% DM) 2 bu --5% 2020 lb 100 lb 1920 lb 1820 lbSoybean meal(87% DM) 16% 5.6 ton Hay crop(87% DM) 2.0 ton .5 ton 2.2 ton 4.7 ton 8.6 ton 18% 3.5 ton .8 ton 3.0 ton 7.3 ton Corn silage(35% DM) . Dicalcium phosphate ---100 lb 95 lb 5% 70 lb 25 lb (100% DM) . ---30 lb 5% 32 lb Limestone(100% DM) 30 lb 5% 95 lb 25 lb 90 lb 5 lb Salt(100% DM) 60 lb Quantities or feed for lactating covs are based upon a 305 day lactation. b.CQuantities of feeds for dry covs and youngstock are estimated from: Thomas, Emery, Hlubik (1980). It is assumed that dry cows will be brought onto grain approximately 2 weeks before freshening. •^According to Telfara summary data (1981) there is approximately one re­ placement heifer/cow/year. It is assumed that 1/2 of replacements are be­ tween 0 and 1 yr of age and 1/2 between 1 and 2 years of age. Therefore, for every heifer the amount of feed needed is the amount needed between birth and freshening/2. _ ___ ^Storage and feeding losses are based on: 'Knoblauch(1977),eg. 17 and Parseh (1932), pg. 134. Losses include feeding and storage losses. Losses for c o m are those for high moisture corn stored in an up­ right silo. Losses for c o m silage are losses based on bunker s-ilo storage. Losses of hay crop are estimated as 40% dry hay and 60% of the losses of haylage stored in an upright silo (i.e. .4 * 12 + .6 * 19 * 16). 52 Table 4.5. Telfarm Estimates of Feed Disappearance by Level of Milk Production3 (1980 and 1981 Summary Data)*3 No. Observations^ (farms) Avg. Milk Sold/Cow Corn Eq.d Hay Eq. (bu) (ton) Corn Silage (ton) Purchased Feed $ 263 14,950 115 6.6 8.9 340 157 17,041 118 6.1 9.2 370 27 18,871 136 6.8 6.5 402 Source: Mulvaney, 1982. aTelfarm accounts for total milk sold and not all milk produced. ^These estimates are weighted average amounts estimated from Telfarm production sorts. In addition to including dairy heifers these esti­ mates include feed disappearance for bulls and steers. cAs these observations include 1980 and 1981 data many observations are of the same farms over 2 years time. <3corn equivalent includes estimates of barley and oats fed, converted to a corn equivalent basis by weight. 4.1.2 Feed Storage Facilities A. Assumptions There is a wide variety of possible feed storage in­ vestment alternatives. For example, silages can be stored in bunker silos, upright cement stave silos, oxygen limiting upright silos and more recently in vacuum-sealed plastic silage bags. The choice of storage systems depends on such factors as: purchase price, annual use costs/unit of feed stored, compatibility with the harvesting and feeding systems, feed storage losses, feed quality, labor requirements, ease of handling and rate of feedcut. 1) Shelled corn is stored as high moisture corn in upright cement stave silos. All but the smallest herd size are assumed to 53 have a top unloader for the silo. All strategies are assumed to ensile a year's supply of corn during the fall harvest season (see Appendix B ) . This allows farmers to take advantage of reduced harvest season prices and also eliminate the cost of drying corn which is estimated as approximately $.30/bu (Schwab et al., 1983). It is assumed that farmers purchasing corn (i.e. PR and GF) can contract with neighboring crop farmers to supply their needs. 2) Corn silage is stored in bunker silos for farms of herd sizes of 75, 150, 300 and 500 cows. Corn silage is stored in an upright cement stave silo for herd sizes of 40 cows. Bunker silos are a low investment silo compared to oxygen limiting or cement stave silos. They are well suited to mixer wagon feeding but require careful management. Storing silage in bunker silos typically results in greater feed storage losses compared to upright silos 1977) . (Knoblauch, Storing silage in a bunker for a herd size of 40 cows is considered impractical because the small size needed would not provide adequate room to maneuver tractors for packing during ensiling which would result in excessive feed spoilage and storage losses. 3) Haylage is stored in upright cement stave silos with top unloaders for herd sizes j>75 cows for farms GF and GFG. As the crop is harvested throughout the growing season (late May to early October), storage facilities are sized to accomodate 70% of the total annual hay crop harvested as haylage. 4) Hay is stored in pole barns for all strategies and herd sizes. Storage facilities are sized to accomodate 70% of the total annual hay 54 crop harvested as hay for farms GFG and GF. Farms PR.have facilities adequate to store 40% of their annual needs (see Appendix B ) . The model estimates total investments in feed storage facilities by summing the investments for facilities to store shelled corn, corn silage, hay and haylage (when included) for each herd size within each strategy. The annual use cost of capital invested in feed storage facili­ ties is based on the opportunity cost of capital for durable assets as outlined in section 3.2 considering an expected life of 20 years, a salvage value of zero, and the real interest rate at 4%. B. Estimating Feed Storage Costs Table 4.6 presents some recent estimates of costs of cement stave upright silos with top unloaders. From this table, equations estimating feed storage costs for silage, haylage and high moisture corn are derived. Predicted costs of silos are compared to actual costs in Tables 4.7 and 4.8. Costs to build bunker silos were ob­ tained from a Michigan builder Vertical silo costs and are presented below: (cement stave, top unloading, including unloader) Y = $12,918 + 66.8 * (X) where Y X Y = cost of silo = tons of silage or haylage dry matter = $11,542 + .902 * (X) where Y = cost of silo X = bushels of c o m at 70% dry matter 55 Horizontal silo costs: (12 ft high walls, concrete) $100 per foot of wall $1.40 per square ft concrete floor 20' apron in front of silo site work estimated at $300 Y = $12,560 + 55 * (X) where Y = cost of silo X = tons of 32% DM silage Hay storage costs: Assuming $3.50/square ft to build a pole barn for hay and straw storage, the barns are 14 foot high to the eaves, and that hay occupies 250 square feet/ton, hay storage investment = $62.50/ton. (250 sq ft/14 ft) * $ 3 .50/sq ft = $62.50/ton Table 4.6. Vertical Silo Sizes and Costs (Cement Stave) Silo Size diameter & height Volume ft3 Silage storage + (DM) Corn storage bu Silo cost $ Unloader cost $ Total cost $ 12' X 30' 3,390 21 2,354 5,000 16' X 50' 10,050 78 6,980 11,000 5,300 16,300 20' X 50' 15,560 122 10,900 14,300 5,500 20,600 20' X 6 0 ’ 18,840 159 13,080 17,100 5,500 22,600 20' X 70' 21,980 198 15,260 19,900 5,500 25,400 20' X 80' 25,120 214 17,800 22,700 6,300 29,000 24' X 60* 27,120 228 18,830 21,700 8,500 30,200 24' X 80* 36,160 341 25,640 28,300 8,500 36,800 30' X 60' 42,360 357 30,030 28,800 9,300 38,100 30' X 80' 56,480 529 40,040 36,700 9,300 46,000 aSavoie, P. 1982. 5,000 Source MSR Silo Co. (1983) Tri State (1983) Tri State3 (1983) Central Dairy(1983) Central Dairy(1983) Tri State3 (1982) Tri State3 (1982) Tri State3 (1982) Tri State3 (1982) Tri State3 (1982) Corn/Ton silage $ Cost/Bu corn § 112.00 2.12 208.00 2.33 169.00 1.89 142.00 1.73 128.00 1.66 135.50 1.63 132.50 1.60 108.00 1.44 107.00 1.26 107.00 .91 57 Table 4.7. Silo size3 Estimated Vertical Silo Costs (Cement Stave, Including Top Unloader) vs. Costs Predicted by Linear Equations for Corn Grain, Silage and Haylage Silage*3 capacity ton DM Corn capacity bu Estimated0 cost,$ Predicted^ cost, $ Predicted® cost, $ 16' X 50' 78 6,800 16,300 18,128 17,676 20' X 50' 122 10,900 20,600 21,067 21,374 20' X 60' 159 13,083 22,600 23,539 23,343 20' X 70' 198 15,263 25,400 26,144 25,309 20' X 80' 214 17,800 29,000 27,213 27,598 24' X 60' 228 18,833 30,200 28,148 28,529 24' X 80' 341 25,635 36,800 35,697 34,665 30' X 60' 357 30,030 38,100 36,766 38,629 30' X 80' 529 40,040 46,000 48,255 47,658 aVertical silo sizes are diameter * height in feet. fc*DM refers to dry matter. cCosts are estimated from Table 4.8. ^Predicted as: $12,918 + 66.8 * (tons of silage or haylage DM). ePredicted as: $11,542 + .902 * (bushels of shelled corn). 58 Table 4.8. Estimated Horzontal Silo Costs (Cement Sides, Floor and Back Wall) vs. Costs Predicted by Linear Equations, for Corn Silage (32% DM) Silage Silage Estimated^5 Predicted^ tons 32% DM ton DM cost cost ______________________ capacity_____ capacity_________ $____________ $_____ 328 105 16,540 18,335 30' X 80' x 10' 631 202 23,500 23,670 30' X 100' x 10' 790 253 28,340 26,475 50' X 120' x 10' 1521 487 39,100 39,345 x 10' 1903 609 47,200 46,055 60' X 180' x 10' 2715 869 59,100 60,355 O x 10' o in to Silo size® X 60' X 150' aHorizontal silos are expressed as width * length * height; it is assumed that the average height of silage will be 2. ft higher than the walls when figuring capacity. ^Estimated costs are based on; $100/sq ft wall (concrete); $1.40/ sq ft floor (concrete); $300 for site preparation. The cost includes 3 sides plus an apron (20') extension on the open end; these costs were estimated using cost information from a Michigan builder, W. Steer from Vassar, Michigan. cCost is predicted as: $12,560 + 55 * (tons of silage DM), 4 .1.3 Land The model estimates the number of acres of cropland needed by dividing the quantities of each feed needed by the expec­ ted yield/acre for each crop grown. An additional 5% above required acreages is included to account for headlands. Expected yield/acre for each crop is determined in the model by the soil management group. There are three soil management groups which can be specified by the user. These are discussed below. 59 A. Purchase Price of Land The investment value of land is estimated by multiplying the purchase price/acre by the number of acres. In the model, the pur­ chase price/acre is specified by the user it should be consistent with the market value and productivity of the land. Average values/ acre and the index values of land prices in Michigan over the last 5 years are listed in Appendix Table Al. Note that the value of cropland has decreased since 1981. The investment cost/acre can be approximated from cash crop rents. Table A2 presents cash crop rents and average land values of Michigan farmland from 1960 to 1979. tension Bulletin E-683 Ex­ (Schwab, 1983b) provides estimates of cash rents for Michigan by crop production districts considering the crop grown. Michigan soils are divided into eight productivity groups to assess their value for property tax purposes mission, 1972). (Michigan State Tax Com­ A soil of productivity group 1 is given a value of 100%; 2, 95%; 3, 90%, 4, 80%; 5, 75%; 6, 65%; 7, 55%, and 8, 45%. Thus, when properties in a township are sold and their productivity is known, values of other properties can be adjusted using this scale. Soils are placed in productivity groups based on their crop production potential under average management conditions; this is determined by classifying them into soil management groups and is based on productivity according to Extension Bulletin E-550 (Warncke and Christenson, 1981). Broadly speaking, soils in soil management group 2.5 include productivity groups 1 and 2, soils in management group 3 include productivity groups 60 3 and 4 and soils in management group 4 include productivity groups 5 and 6. Valuing soil management group 2.5 at 100%, soils in manage­ ment groups 3 and 4 should have approximately 87% and 72% of the value of soils in management group 2.5. This can be used as a guideline to estimate relative value of crop land. B. Annual Use Cost of Land In estimating the annual cost/acre to charge against land, consideration is given to the opportunity cost of capital. This re­ flects what the investor could earn on the next best alternative. The real interest rate is used to approximate the opportunity cost of capital invested in land. The MSU Agricultural Model (Ross et al., 1983) predicts the real interest rate to average 4.1% over the period from 1983 to 1990. The long-run real interest rate is generally assumed to be about 3%. change in the real This cost should be adjusted by the expected (deflated) value of the investment which is re­ ferred to as the growth rate. The average real growth rate of land has been approximately 5%/ year from the period 1960-1980 values have declined 9%/year (Barry, 1983); recently (1981-1982) land (see Appendix A ) . price outlook for farm commodities Based on the pessimistic (Christenson and Sorenson, 1983), it is estimated that the real growth in land value will be similar to that experienced in the 1960's 1.45%/year. (Barry, 1983, pg. 129) which was approximately The real growth rate in land value is approximated as 1%/year in the model. Property taxes are another expense item to account for when estimating the annual cost of land. In the model, the value of property 61 multiplied by .02 is used to estimate the annual property tax charge. This estimate was derived by regressing property taxes on the value of the taxable assets and is reported in Table 4.9. This charge is comparable to the estimate of .017 used by (Knoblauch> 1977) in his study analyzing hay crop production, storage and feeding on New York dairy farms. Table 4.9. 1982 Property Taxes and Insurance Paid and Farm Capital Owned by Michigan Telfarm Specialized Dairy Farms3 Ac­ cording to Herd Size Herd size (no. cows) No. of farms Avg. value of taxable property13 Avg. property taxes paid Avg. value of insured property Avg. insurance paid <50 119 $139,975 50-75 113 $234,854 75-100 80 $277,321 >100 126 $474,807 $ $ $ 5,973 $ 10,613 3,243 5,422 $ 88,475 $147,368 $194,468 $312,543 $ $ $ $ 1,103 1,678 1,967 3,426 ^Source: Brown and Nott, 1983. Includes land (agric value), buildings and improvements. cIncludes the value of buildings and improvements and machinery. Property taxes can be approximated as: $125 + .022 * (avg. value of property) r = .99 for the 4 estimates. Insurance can be approximated as: 123 + .010 * (avg. value of insured property) r = .99 for the 4 estimates. C. Land Productivity Land productivity depends upon the soil characteristics relative to crop recruirements. yield potentials form Soils with similar properties and soil management groups. This combines soils with similar profiles, management requirements and responses to like management practices. 62 Mineral soils are given a number based on the dominant profile texture as follows: 0 - fine clay, more than 60% clay; 1 - clay, 40 to 60% clay; 1.5 - clay loam and silty clay loam; 2.5 - loam and silt loam; 3 - sandy loam; 4 - loamy sand and 5 - sand. Soils are further subclassified according to natural drainage conditions, slope and degree of erosion which has occurred (Mokma and Robertson, 1976). With over 275 soils series mapped in Michigan, the concept of classi­ fying soils according to management groups greatly aids the ability to communicate soils information. The model can investigate the growing strategies considering soils broadly classified into management groups 2.5, 3 or 4. Soils in management group 2.5 are loams considered to be very productive. Capec, Conover, Celina, Dunbridge, Isabella, Miami, Tuscola, Brookston and Kokomo soils are among those in group 2.5. Group 3 soils are sandy loams and considered moderately productive. Osktemo soils are among those in this group. Hillsdale, Lapeer, Soils in management group 4 are considered to be loamy sands and not very productive. Gilchrist, Gladwin, Leelanau, Montcalm and Spinks soils are examples of group 4 soils. Expected harvest yields/acre for corn, c o m silage and alfalfa for soils in Southern Michigan with a growing season of over 140 consecutive frost free days are reported in Table 4.10. It is assumed that alfalfa harvested as haylage yields more dry matter/ acre than that harvested as hay due to reduced leaf losses during har­ vest (McGuffey and Hillman, 1976; Savoie, 1982) . In the model this is estimated as 10% more dry matter/acre of haylage vs. hay. 63 The model also assumes that alfalfa lasts 5 years and is re­ seeded during the end of the fifth year; therefore, 16.7% of the hay crop is replaced each year and the reduction in yield due to re­ seeding is accounted for. Table 4.10. Expected Crop Yields/Acre by Soil Management Group3 Soil Management Corn bu Corn Silagec tons @ 35%DM Crop Yields Alfalfa-Grass Hayd tons @ 87% DM Alfalfa-Grass Haylagee tons @ 50% DM 2.5 120 16.8 4.6 9.0 3 105 15.3 4.0 7.9 4 86 13.2 3.5 6.9 ^Source: Warncke and Christenson, 1981. ^Crop yields are derived as the average harvested yields for soils classified in management groups 2.5, 3 or 4 as reported in E-550 by Warncke and Christenson, 1981. cIt is assumed that corn silage yields in E-550 are expressed in tons of 32% DM c o m silage; this table expresses vields at 35% DM. dAlfalfa-grass hay and haylage yields are adjusted to reflect a re­ seeding of 16.7% of the crop/year with a yield on the re-seeded acreage of 2 tons/year. eKaylage is assumed tc yield 10% more crop than hay due to reduced leaf losses. 4.1.4 Cash Crop Expenses Estimated cash crop expenses for cropping enterprises are presented in Table 4.11 and are expenses/acre for each crop grown. Some expenses such as fertilizer, seeds and fuel vary depending on the crop yield. These items are linearly approximated considering expenses across the various yield categories presented by Schwab et al. (1983) considering non-irrigated crops. Amounts of phosphorus and Table 4.11. Cash Crop Budgets3 : Expenses/Acre Item Crop Acronym Corn Seeds and plants SOS Weedspray WS Insecticides IHSCT Corn Silage Alfalfa Hayb $ 5.00 $ 5.00 $11.20 $11.20 $ 1.75 $ 1.75 $ 2.00 $ 2.00 $ 5.00 $ 5.00 0.00 0.00 (8.16+.06* Bud/A)«$l.25/lb (6.5+.534*Te/A)*$1.25/lb Nitrogen (17.2+1.1* Bu/A)• ($/lb N) (6.3+9.3* T/A)*($/lb N) Phosphorus1 (10.45+.409* Bu/A)« ($/lb P) (4.35*T/A)* ($/lb P) Potassium9 75 * ($/lb K) 8-64 * ($/lb K) 45 « T/A « ($/lb K) 5.94«T/A*(S/lb LMSTH/.38) 59*T/A«($/lb LHSTN/.32) Limestone11 LMSTN 95 « ($/lb LHSTN/.38) Utilities UTLTS $.041 + .021 « Bu/A Trucking TRCK $.105 » Bu/A $-1.6 + 1.08 * T/A FL 11.3 * ($/gal FL) (6.92+.336*T/A)« ($/qal FL) RPRS $13.60 Fuel Repairs Alfalfa Haylagefc (10.7*T/A)*($/lb P) 5.9*T/A)» ($/lb P) 25 » T/A « ($/lb K) >2.8*T/A*($/lb LMSTN/.38) $.339 * T/A $18.20 $1.47 * T/A (6.02+.44+T/A)* ($/gal FL) $12.94 +1.91 * T/A $.45 * T/A 19.9 * ($/gal FL) $18.9 + .725 * T/A 2.35 • T/A 3.00 * T/A OTHR Crop Supplies aSource: Schwab et al., 1983. Approximations of expenses for SDS, N, P,K, LMSTN, UfTLTS, TRCK,FL,RPRS,OTHRarebasedonyields/acre, considering expenses/acre for the various yield categories for crops as reported by Schwab et al. b>cBudgets for alfalfa are based on the assumption that alfalfa will be re-seeded every 6th year. d »eYield is expressed as bushels/acre or tons/acre. f•9<^The amount of P, K, LMSTN for alfalfa and corn silage are estimated by multiplying the nutrientcontent of these forages by the quantities of dry matter harvested/acre. 65 potassium needed for corn silage and alfalfa are estimated by multi­ plying the nutrient content of these forages presented in Table 4.3 by the quantities of dry matter harvested/acre. The model estimates cash crop expenses/acre by multiplying the number of acres of each crop by the total cash crop expenses/acre. 4.1.5 Crop Machinery Appendix Tables Cl through C8 contain machinery comple­ ments for farms of sizes 40, 75, 150 and 300 cows which grow forages and grains (GFG) or grow forages only (GF). Machinery is assembled based on the size of machinery needed to complete cropping programs in a timely manner relative to the size of the farm and the costs of the machinery. These machinery complements are summarized in Table 4.12. Table 4.12. Summary of Machinery Investments by Herd Size and Feeding Strategy Strategy: Grow Forages & Grain Total Per Cow Grow Forages Only Total Per Cow 40 $ 145,700 3,643 129,700 3,243 Herd Size 75 150 $ $ 300 $ 161,400 2,152 207,900 1,386 323,520 1,078 143,000 1,907 176,400 1,176 240,400 801 aBased on Appendix C. The annual cost of capital invested in machinery is approximated considering an expected life of 8 years, a salvage value of 25% and a 66 real interest rate of 4%. value of crop machinery list price Salvage value is estimated as the remaining (at the (John Deere and Co., Other costs comprising the insurance and shelter. end of 8 years) as a percent of the 1981, pg. 62). annual use cost of machinery includes Insurance is estimated as 1% of the average investment in machinery. This cost is based on Table 4.12. The annual cost of shelter is estimated to be 1 to 2% of the value of machinery (John Deere and Co., 1981, pg. 63). The estimate used in this analysis is 1.5% of the average investment in machinery. and maintenance costs are estimated in the cash crop budgets Repairs (see Table 4.11). 4.1.6 Crop Labor Requirements Crop labor requirements are derived by estimating the hours of labor needed for each crop based on the tasks to be accom­ plished, crop machinery sizes and rates of work, and acres of each crop grown. grown. Machinery sizes change with changes in the acres of crops Labor requirements for various acres of each crop are bud­ geted in Appendix D. These estimates are used to derive the following linear approximations of hours of labor needed/acre for corn, corn silage, haylage and hay based on the acres of each crop grown. 67 Table 4.13. Crop Labor Requirements Corn grain Y = 2.2 + 125/X Com Y = 3.7 + silage 90/X Hay Y = 5.4 + 250/X Haylage Y = 4.6 + 284/X Where X = no. acres of each crop; Y = hrs of labor/ acre 4.1.7 Purchased Feed Costs Purchased feed costs are estimated by multiplying the feed purchase prices by the quantity of each feed needed which is determined by the level of milk production size. (see Table 4.4) and herd Costs of soybean meal, dicalcium phosphate, limestone and salt are calculated in this manner for all herd sizes and strategies. Costs of corn grain are estimated for farms purchasing corn (GF,PR), and costs of alfalfa hay and corn silage are estimated for farms purchasing forages. These costs are estimated considering the quan­ tities of these feeds needed (based on the level of milk production and the price of the feeds specified). It is assumed that corn is purchased in the fall as high moisture shelled corn, and silage is purchased in the fall as well; hay is purchased throughout the year and there is a 4 month inventory on the farm (see Appendix B for the logic of these assumptions). 68 4.2 Dairy Expenses 4.2.1 Dairy Buildings and Facilities, Land for Facilities and Dairy Equipment Investments for dairy buildings and facilities, land for facilities, equipment and dairy cattle are included. Annual costs include annual expenses incurred from the investments above plus live­ stock and labor expenses. These are considered to be the same across strategies depending on the herd size. The annual use cost of capital invested in dairy buildings and facilities is estimated based on an e j e c t e d life of 20 years, a salvage value of zero and a real interest rate of 4%. The annual use cost of capital invested in dairy equipment is estimated based on an expected life of 8 years, a salvage value of 25% and a real interest rate of 4%. ' The total costs of investments in dairy buildings and facilities and equipment include property taxes and insurance. Maintenance and repairs of buildings and equipment are estimated in the livestock budgets. The total annual use cost of capital invested in land for dairy buildings is estimated based on an opportunity cost of capital at 4%, property taxes and an annual rate of growth in value of land of 1%. Investments in dairy cattle are estimated by multiplying the purchase price of cows by the number of cows. The annual use cost of capital invested in cows is approximated by multiplying the value of the dairy cattle by the interest rate. able asset with an infinite life. Cows are considered a dur­ Investments in buildings and 69 facilities and equipment are based on the following assumptions. 1) Farms of herd size of 40 cows are housed in confinement-stall barns with a pipeline milking system. 2) Farms of herd sizes of: 75, 150, 300 and 500 cows are housed in free stall b a m s and milked in a herringbone parlor. 3) Farms of herd sizes 75 or 150 cows are milked in a double-4herringbone parlor with no mechanization. 4) Farms of herd sizes 300 or 500 cows are milked in double-8herringbone parlor with detachers and power gates. 5) All farms have 6 months manure storage. 6) Manure is stored as a solid for 40 cow herds, on a concrete slab with 3 side walls using a gutter cleaner and a manure stacker. 7) Manure and parlor wastes are stored in an uncovered earthen pit for herd sizes >75 cows. 8) All farms feed total mixed rations. 9) All farms have youngstock facilities; hutches fornewborn calves, Virginia style barns for calves weaned through freshening. 10) Approximately 85% of the cows are milking, 15% are dry at any given time. 11). The number of (number heifers on the farm at any time i.s: of cows in the herd) (see 1.05 * section 4.3.3). 12) The layout of physical facilities requires 1 acre of land for every 20 cows. Appendix Tables El through E5 contain dairy buildings and facili­ ties and equipment for farms ranging in herd size from 40 to 500 cows. These are summarized in Table 4.14. Table 4.14. Summary of Dairy Buildings and Equipment Investments by Herd Sizea • Herd Size___________________ _ 40______ 75________150______ 300 500 $ Dairy buildings Equipment 71,350 $ 119,800 $ $ $ 202,850 368,700 590,300 66,250 101,100 136,950 205,450 221,400 ^Based on Appendix Table El through E8. 4.2.2 Livestock Expenses, Labor and Investments Livestock expenses/cow (including replacements) are pre­ sented in Table 4.15 and vary according to the production level. Total livestock expenses are calculated by multiplying total expenses/cow (based on the level of production) by the herd size. Labor require­ ments for each herd size are calculated in Table 4.16 based on the technology employed (i.e. the buildings, facilities and equipment). From these estimates a linear relationship was formulated to estimate labor requirements/cow/year for a given number of cows. Livestock labor (hrs/cow/year) = 36 + (1480/herd size). 4.3 Incomes and Adjustments to Costs Income is derived from the sale of milk, deacon calves, cull cows and heifers and excess replacement heifers. 4.3.1 Milk Income Milk sold is estimated as 95% of that produced. The dif­ ference between the amount of milk produced and the amount sold can be 71 Table 4.15. Dairy Livestock Budgets: Selected Cash Expense9 by Pro­ duction Level Item 11,000 $ Level of Production 13,000 14,000 15,000 16,000 $ $ $ $ 18,000 $ Building repairs 11.10 10.40 12.00 12.70 13.00 13.30 Equipment repairs 50.70 49.40 56.20 57.00 58.00 58.10 Livestock supplies 30.20 58.40 58.50 58.90 61.80 68.30 9.60 20.30 20.60 33.80 35.00 43.50 28.40 38.00 39.00 47.80 55.50 69.40 8.70 10.00 10.30 10.80 11.40 11.50 Insurance 10.20 12.40 14.40 14.60 15.00 15.70 Utilities 43.00 50.40 53.30 53.50 53.90 57.20 Marketing 71.30 84.80 88.50 96.80 105.00 118.20 6.60 11.90 12.70 12.70 12.70 19.10 269.80 346.00 365.50 398.60 421.30 474.30 Breeding fees Vet and medicine Gasoline,fuel,oil Other cash expense Total selected cash expense aSource: Schwab et a l ., 1983. These cash expenses are approximated using the linear expression: livestock cash expense = -36.2 + .0286 * (lb of milk production), r2 = .99 for the equation developed using the 6 estimates above. Table 4.16. Estimated Annual Dairy Labor Requirements by Herd Size (Hours/Year) Item Milking3 Manure handling*3 Feeding0 Bedding*^ Other:^ Heat detection Breeding Youngstock Dry cow care Records Turn in and out of stall Miscellaneous Total hours/year Total hours/cow/year 40 75 1113 230 511 117 1879 346 620 141 94 24 340 30 40 161 178 2838 71 Herd Size 150 300 500 3149 526 1022 208 3927 886 1716 343 6099 1366 2592 523 133 45 533 60 75 215 90 945 112 150 380 180 1170 225 300 600 300 2870 375 500 -- -- -- -- 290 530 1010 1650 4122 55 6947 46 10737 36 16875 34 aMilking time for a 40 cow herd is based o n : Bath et a l ., 1978, Appendix Table V-I, pg. 531. Milking time for other herd sizes is based on: Wetzel, 1979, Table 3. Hours/milking is estimated assuming that 85% of the herd is milking, hrs/milking = .833 + .0273 * (herd size * .85) for a double-4-herringbone parlor with no mechanization. This is used to estimate labor for herd sizes of 75 and 150 c o w s . hrs/milking = .917 + .0175 * (herd size * .85) for a double-8herringbone parlor with detachers and power gates. This is used to estimate labor for herd size of 300 and 500 cows. ^Manure handling labor is based on: Bath et al., 1978, Appendix Table V-I, pg. 531. cFeeding labor for corn, corn silage and haylage is based on: Norell et al., 1978, Table 4, pg. 15. Feeding labor for hay is based on: Bath et al., 1978, Appendix Table V-I, pg. 531. ^Bedding and other labor costs with the exception of records and dry cow care are based on: Bath et a l ., 1978, Appendix Table V-I, pg. 531. 73 attributed to abnormal milk during the first week of lactation, mastitic milk from udders treated with antibiotics and other milk consumed by the farm family, and calves. Rundell and Speicher (1967) estimated the average difference in the amount produced vs. that sold as approximately 700 lb/cow. Milk hauling and marketing charges are accounted for in the livestock budgets (see Table 4.15). Milk income is estimated as: 95% * (cwt of milk produced) * (price of milk/cwt). 4.3.2 Cull Cows Income The income from cull cows is calculated by multiplying the cwt of cull cows sold by the price of cull cows. that cull cows average 1350 lb. It is assumed The cwt of cull cows depends on the number of cows culled and their body weight. Since death losses contribute to the number of cows culled, this must also be taken into account. Assuming a culling rate of 25% (Etgen and Reaves, 1978, pg. 330) and a death loss of 1% (Salisbury et al., 1978, pg. 582) income from cull cow sales is approximated as: cwt/cow) (24%) * (.13.5 * price/cwt cull cows * (herd size) = 3.24 * price/cwt cull cows * herd size. 4.3.3 Income From Deacon Calves, Replacements Sold and Cull Heifers Income from deacon calves, cull heifers, and the sale of replacement heifers depends on the culling rate and calf and heifer mortality. The following logic was used to determine income from these sources. Given: 100 cows, a 12 month calving interval (Cl) and a replace- 74 ment rate of 25%/year, there are a possible 125 calves born/year. Assuming 1/2 of the cull cows calve before they are removed from the herd, there remain a possible 112 births. Assuming good manage­ ment, approximately 6% of the calf crop potential is lost due to abortions and stillbirths (Salisbury et al., 1978, pg. 688) resulting in 105 live calves born for every 100 cows. Based on an average calf mortality rate of 12% (Salisbury et al., 1978, pg. 688) there are 92 calves that survive, 1/2 of which are males. possible replacements added/year. are unable to conceive Thus, there are 46 Assuming that 3% of these heifers (Fogwell et al., 1981) and that 2% will die from weaning to freshening (Etgen and Reaves, 1978, pg. 330) there remain approximately 44 heifers added/year. birth to freshening is 27 months If the interval from (D.H.I.A., 1982), then 44 heifers * (24 months/27 months) = 39 heifers available/year to replace heifers in the herd. With a calving interval of 13 months instead of 12, the number of replacements would be reduced by 8%. This results in approximately 36 heifers available to replace cows in the herd each year. Based on a replacement rate of 25% there are 11 heifers available for sale as dairy replacements for every 100 cows in the herd. The total number of female youngstock on the farm at any given point in time is 46 possible replacements/year * (27 months to freshen/24 months in 2 years) = 103. The number of deacon calves for sale assuming a 13 month calving interval is: (105(calves) * .5 (males) * .9 (10% death loss) * .923 (13 mo. calving interval)) = .44. Assuming that deacon calves weigh 75 100 lb, income from the sale of deacon calves/cow is estimated as: .44 * 1 cwt * (price/cwt of deacon calves) * (herd size) Estimating the weight of cull heifers to be 1,000 lb and the number of cull heifers sold/cow as .014 (i.e. 3% of 46), the income from the sale of cull heifers = .014 * (10 cwt) * (price of'cull heifers) * (herd size). Assuming there are 36 heifers/100 cows avail­ able for replacement and the culling rate is 25%, the income from the sale of replacement heifers/year can be estimated as: (36-25% cows culled/yr) 4.3.4 * (price of replacements) * (herd size) Estimated Fertilizer Cost Savings and the Value of Manure The fertilizer value of manure saves cash crop expenses for fertilizer as well as the interest charge on fertilizer purchases for farms growing crops. This savings can be estimated assuming that each cow and replacement produces 164 lb lb nitrogen (N), .146 lb phosphorus of manure/day containing .82 (P) and .54 lb potassium (K) . This amounts to 300 lb N, 54 lb P and 200 lb K/cow and replacement/year. Fifty percent cf the N is assumed to be available considering handling and storage losses (Midwest Plan Services, 1979, pg. 4,5,82,83). Thus, the amount of savings/cow is estimated as: (150 lb N * price of N) + (54 lb P * price of P) + price of K) It is assumed that farms growing forages only (200lb K * (GF) use approxi­ mately 1/2 of the manure produced to fertilize corn silage and 1/2 to fertilize the hay crop. Because the alfalfa hay crop does not need the nitrogen the value of nitrogen is excluded from the estimated 76 value of 1/2 of the manure. Thus, for farms growing forages (GF), the value of manure is estimated as: (75 lb N * price of N) + (54 lb P * price of K) Farms PR are assumed to contract pose manure on their property and net * price of P) -(200 lb K with nearby crop farms todis­ .25 * the value of the manure produced. 4.3.5 Estimated Soybean Meal Savings for Farms Growing Forages Those farms harvesting forage as haylage (farms growing forages with herd sizes greater than 40 cows) are assumed to save soybean meal costs due to the increased protein content of the haylage vs. hay resulting from reduced field leaf losses 1976). (McGuffey and Hillman, The difference in protein/lb of dry matter is estimated to be 1.5% greater for haylage than hay for this analysis. The amount of soybean meal saved/cow/year is estimated as: 42 lb DMI * 60% DM as forage * 60% forage as hay * 60% hay crop as haylage * (1.5% crude protein difference/lb D M ) / (44% crude protein/lb soybean meal) * 305 days/lactation = 94 lb soybean meal/cow/year. This is rounded to 100 lb/cow in the model. 4.3.6 Savings in Dairy Equipment and Crop Machinery The cropping and dairy enterprises complement each other in that some of the equipment can be shared by both. ifies the value of this equipment. Table 4.17 spec­ Since equipment is specified sep­ arately for the dairy and cropping programs, the value of this "savings" in investment costs is subtracted from the total investment in equip­ ment and machinery. The annual savings on capital invested, property taxes and 77 shelter is approximated in the same way annual ccrsts were estimated for machinery in section 4.1.5. Table 4.17. Savings in Machinery Investments for Farms Growing Crops Item Herd Size 75b $ 40 $ Investment savings Annual savings (NO. COWS) 150c $ 300d $ : 20,200 45,200 50,200 50,200 2,680 6,057 6,727 6,727 aThis is based on the cost of a 40 hp tractor at $14,000 and a pickup truck valued at $6,200. ^This is based on the cost of a 40 hp tractor at$14,000,a pick­ up truck at $6,200 and an 80 hp tractor at $25,000. cThis is based on the cost of a 40 hp tractor at$14,000,a pick­ up truck at $6,200 and a 90 hp tractor at $90,000. %.B. These cost estimates can be traced- in the dhiry equipment costs in Appendix Tables El through E 8 . 4.4 Price Expectations 4.4.1 Setting Prices in the Model Expected prices of relevant variables are needed to project incomes and expenses to determine profit. Since this is an investment analysis involving strategic planning (i.e. longrange planning), forecast prices (1983 dollars) should include the average long-run outlook of prices considered. Many prices are highly correlated and if one price changes it will likely affect the others. Prices forecast by the MSU Agricultural Model (Ross et al., 1983; Christenson and Sorenson, 1983) and other sources of information are 78 used to establish the expected economic conditions for the forecast period 1983-199JL contained in Table 4.20. Absolute values as well as price ratios determine the ranking of strategies according to profitability. Two of the most important prices in this regard are the price of milk compared to the price of corn. 4.4.2 Level of Milk Production and Milk/Feed Price Ratios There has been a recent trend of overproduction of milk in the U.S. as a result of excessive milk prices compared to the cost of feed. Current government policy is to adjust milk prices to bring supply in line with consumption. According to Ross (1983) it will be necessary to close the gap on the milk price/feed cost ratio from 1.75 to below 1.55 to accomplish this. This will result in an average milk price below $12.10/cwt (1983 dollars) for the period 1983-1991 based on price forecasts of the MSU Agricultural Model (Ross, 1983). The milk price/feed cost ratio is based on the average price received by farmers for milk and the cost/cwt of a 16% protein dairy concentrate mix. It is estimated that a ratio of approximately 1.5 will equilibrate the quantity of milk supplied with that demanded. The relationship of the milk/feed price ratio as it is reported by the U.S.D.A. is related to a milk/corn, hay and soybean meal price ratio (see Table 4.18). This provides a means to approximate the milk/feed price ratio, given the milk price and corn, soybean meal and hay prices specified in the model. 4.4.3 Prices Related to the Price of Milk Important prices related to the price of milk include cull cows, cull heifers, dairy cows, and deacon calves. Table 4.19 contains 79 Table 4.18. Milk/Feed Price Ratios Over Time3 Year M/F*3 M/HSCc 1973 1974 1975 1976 1977 1978 1979 1980 1981 1.39 1.24 1.26 1.34 1.38 1.47 1.54 1.51 1.46 1.89 2.04 2.18 2.26 2.41 2.61 2.71 2.62 2.69 ' Mpd • 10189 10206 10327 10627 11050 11225 11366 11689 12018 AM/Fe AM/HSCf 1.42 1.26 1.30 1.42 1.53 1.64 1.75 1.77 1.76 1.92 2.08 2.25 2.40 2.66 2.92 3.08 3.06 3.23 aSource of prices: USDA, 1982. ^Milk:feed price ratio (2 yr avg). cMilk:hay, soybean meal, shelled corn price ratio (2 yr avg): price/lb of hay * .55 + price/lb.of soybean meal * -.15 + price/lb of shelled corn * .30. These prices are weighted to approximate the feed composition of dairy rations. dMP is the level of milk production/cow/yr (lb). e ,fAM/F is the adjusted milk:feed price ratio (adjusted by the time trend of efficiency of production and is estimated by multi­ plying AM/F by MP/10000. Regression: AM/F (1973-1981) = .522 + .388 * (AM/HSC), r = .928. the average yearly prices for these commodities for the U.S. for the years 1965 to 1981. The relationship of these prices to each other and the price of milk is defined by the regression outlined there. Ultimately all of these prices are tied to the price of milk. The price of dairy cows (as well as the price of heifers) is influenced by the level of milk production as well as the price of milk. The regression estimate of the price of cows is adjusted to reflect this difference by multiplying the difference in milk pro­ duction from the national herd average of 13,000 lb by $85, for every 1,000 lb difference (Hillman, .1983) (see Table 4.20). Since 80 heifers are not expected to produce as much milk as more mature cows in the herd, the price of heifers reflects this lower milk production level. 4.4.4 Feed Prices and Relationships A. Price of Corn The Agricultural and Food Act of 1985 is expected to reduce the loan rate on corn to $2.35/bu which would be approx­ imately 30 to 50 cents lower than the expected market price according to Ferris (1983). This results in an expected corn price of $2.70/ bushel. The price of corn specified is the expected purchase price. Since all corn is assumed to be purchased as high moisture shelled corn, the drying cost is subtracted from the cost entered in the model to estimate the cost to farms purchasing corn. This drying cost is estimated as: $.025/pt to dry * 12 pts = $.30/bu (Schwab, 1983) . B. price of Hey end Scybeen Mesl The price of hay is highly correlated to the price of corn as revealed in Table 4.19. Since the price in this table is a price farmers received for hay, a transportation and handling charge of $18.50/ton is.added to the intercept of the regression esti­ mated in Table 4.19 to estimate the hay purchase price in the model (see Koszarek, 1983). The price of soybean meal is highly correlated to the price of hay and is approximated based on the regression esti­ mated from Table 4.19. 81 C. Purchase Price of C o m Silagte There are different ways of estimating the value of corn silage. One approach is to consider corn silage as a sub­ stitute for hay, and using the purchase price of hay, adjust the • hay price considering the difference in the dry matter content be­ tween hay and silage. This typically results in overestimating the value of corn silage relative to its protein content and under­ estimating its value as ah energy source. Also, in the Midwest c o m silage would more than likely be purchased "in the field", and harvested and transported to the buyer during the fall harvest season. The seller (theoretically) would have two choices: 1) sell the corn for silage, or 2) sell it as corn grain. If the option is to sell c o m for silage then silage must -return more profit than grain. The following procedure outlines how corn harvested as silage vs. grain is valued. The purchase price of c o m silage is based on the value of the corn grain plus the nutrient value of the stalk; The value of the corn grain takes into account the savings in corn drying expense as the crop is harvested as silage. The value of the stalk takes into account the difference in quantities of nutrients harvested which present a cost to the grower. This difference is calculated for phosphorus and potassium and calcium; the nitrogen is assumed lost regardless of the method of harvest. Based on an expected yield of 100 bu of shelled corn/acre or 15 tons of 35% dry matter c o m silage, the additional quantity of 82 Table 4.19. Year 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 Time Trends and Relationships of Relevant Commodity Pricesa Milk Price $/cwt Cows Dairy $/head Cows Utility $/cwt 4.23 4.81 5.02 5.24 5.49 5.71 5.87 6.07 7.14 8.33 8.75 9.66 9.72 10.60 12.00 13.00 13.80 212 246 260 274 300 332 358 397 496 500 412 477 504 675 1040 1190 1200 14.44 17.83 17.22 17.92 20.29 21.32 21.62 25.21 32.82 25.56 21.09 25.31 25.32 36.78 50.10 45.72 41.93 Calves Deacon $/cwt Heifers Cull $/cwt 21.74 22.00 26.00 22.85 26.30 • 22.80 27.60 23.89 31.60 26.13 26.42 34.50 28.52 36.40 32.24 44.70 56.60 40.43 35.20 38.00 27.20 37.60 34.10 34.10 36.90 35.20 59.10 46.11 61.47 88.70 76.80 61.22 64.80 59.46 Corn $/bu 1.16 ' 1.24 1.03 1.08 1.16 1.33 1.08 1.57 2.55 3.02 2.54 2.15 2.02 2.25 2.52 3.11 2.45 Soybean Hay Meal $/cwt $/ton 81.46 78.83 76.93 74.12 .78.45 78.51 90.20 228.99 146.35 130.86 147.78 199.80 163.56 190.06 181.91 218.18 216.00 23.20 25.00 24.50 23.60 24.70 26.10 28.10 31.30 41.60 50.90 52.10 60.20 53.70 49.80 59.50 71.00 67.10 aSource: U.S.D.A., 1982. Agricultural Statistics. Regression: Cows (dairy) with milk price = $-260.77 + 98.26 * (milk price), r = .937. Utility cow price with milk price = $2.63 + 3.07 * (milk price), r = .882. Deacon calves with utility cow prices = $-5.99 + 1. 8 0 * (utility cow price), r = .984. Cull heifers prices with utility cow prices = $2.91 + 1.23 * (utility cow prices), r = .972. Hay price with c o m price = $2.44 + 20.80 * (corn price), r = .891. Soybean meal price with hay price = $ 2 3 . 5 0 + 2.78 * (hay price), r = .816. nutrients removed from the soil when corn is harvested as silage is estimated to b e : 80.5 lb of potassium 18.6 lb of phosphorus 29.5 lb of calcium Because different machinery is used to harvest corn as silage, 83 the difference in the cost of thrashing v s . ensiling is important in determining the value of silage for sale. The custom rate to harvest and ensile corn silage is reported as $31.30/acre for horizontal silos and the custom rate to harvest shelled corn was reported as $20.85/ acre for 1982 (Schwab, 1983a). = $10.45/acre. The difference in these harvest costs With these considerations in mind, the purchase price of corn silage/acre is estimated as: ((price of corn/bu - drying expense) * (potential grain yield/acre) + difference in custom rate to ensile vs. harvest as grain + (price of potassium) * (additional lb of potassium removed by harvesting c o m as silage as com­ pared to grain) + (price of phosphorus) * (additional lb of phosphorus removed by harvesting c o m as silage) + (price of limestone (38% Ca)) * (additional lb of calcium removed by harvesting c o m as silage/. 38)) . Dividing the cost/acre of corn silage by the number of tons harvested/acre estimates the cost/ton of corn silage. for estimating this cost is presented in Table 4.20. The formula 84 Table 4.20. Estimates of Prices to use in the Model Item Acronym Value Com Corn silage PSCORN PCS LG $2.70/bu exogenous ((PSCORN-.3)* yield of shelled corn/ acre) + 10.45 + 18.6 * PP + 80.5 * PK + 77.6 * PLMSTN/yield/acre of corn silage) Alfalfa hay Soybean meal PALFHY PSYML /ton /lb 21 + 20 * PSCORN 24.72 + 2.74 * PALFHY/2000 Salt Dicalcium phosphate Limestone PSLT PDCL PLMSTN $.07/lb $.19/lb $.05/lb exogenous exogenous exogenous Milk PMLK PCWS $12.00/cwt exogenous (milk production 13000) * 85 260.77 + 98.26 * (PMLK) Replacements PHFRS (.9 * milk production - 13000) * 85 260.77 + 98.26 * PMLK Cull cows PCLLCW 2.63 + 3.07 * PMLK Cull heifers Deacon calves PCLLHFR PDCNCLVS 2.91 + 1.23 * PCLLCW -5.99 + 3.07 * PMLK Land PLND S1100/acre exogenous Nitrogen Phosphorus Potassium PN PP PK $.16/lb $.20/lb $.12/lb exogenous exogenous exogenous Schwab et al . , 1983 Interest rate INTRT .05 exogenous Ross et a l . , 1983 Labor PLBR $6.00/hr exogenous Schwab et a l ., 1983 Fuel PFL $1.10/gal exogenous How Estimated Source Ferris, 1983 Schwab et al., 1983 Ross 1983 Robinson and Espel 1981 CHAPTER 5 RESULTS AND DISCUSSION This chapter contains examples of the effects of various price scenarios, levels of production and soil management groups on the profitability of the strategies of growing forages and grain growing forages only (GF) and purchasing all feeds (PR). (GFG), Levels of investments in each strategy of $.5, 1.0, 1.5, 2.0 and 2.5 million are projected to examine how profitability, rate of return on in­ vestment, number of cows in the herd and number of laborers changes by level of investment, according to strategy. The first analysis considers the returns to each strategy for each level of investment, based on an expected milk/feed price ratio of 1.50 and a price of corn of $2.70/bu. $12.00/cwt for milk. This results in a price of These prices reflect the average of those anti­ cipated to be encountered by dairymen over the next 8-10 years (Christenson and Sorenson, 1983; Ross, Black and Sorenson, 1983). Returns to each strategy are compared across levels of milk production of: 13, 15, 17 and 19 thousand lb milk. The ranking of strategies on the basis of profitability depends on absolute prices as well as price ratios. This is especially true in regard to milk and feed prices. 85 86 The second analysis examines the consequences of changing the milk/feed ratio to either 1.45 or 1.55. The price of corn is main­ tained at $2.70/bu and the price of milk is set to either $11.40 or $12.60/cwt respectively. The third analysis examines the consequences of different corn prices of: $2.55, 2.70, 2.85, 3.10 and 3.30/bu on the profitability of each strategy. The milk price is maintained at $12.00/cwt. This results in milk/feed price ratios of: 1.55, 1.50, 1.46, 1.39 and 1.35. The effect of these prices across levels of production of 13,000, 15,000, 17,000 and 19,000 lb are examined. Section 5.4 examines the effect of changing the price of land on the profitability of each strategy, assuming a level of milk produc­ tion of 15,000 lb, soil management group of 3, a price of milk at $12.00/cwt and a c o m price at $2.70/bu. The effect of soil management group on profitability of the strategies is discussed in section 5.5, considering soil management groups 2.5, 3 or 4, and respective land prices of $1300, 1100 and $900/acre. 5.1 The Effect of Level of Milk Production on Profitability Across Strategies Tables 5.1 through 5.4 and Figures 5.1 pact that levels of milk production ranging and 5.2 illustrate the im­ from 13,000 to 19,000 lb milk have upon profitability. At a level of production of 13,000 lb milk, the strategies rank in order of profitability as: GF>GFG>PR, across all levels of invest­ ment. PR is clearly not desirable when the level of production is >13,000 lb of milk. Figure 5.1 reveals that the breakeven point ($0 87 profit point) is not reached until levels of investment exceed $1,000,000 for the strategics GFG or GF, and not until a level of investment >$1,500,000 for the strategy of PR. This illustrates that there is a critical size of investment in dairying for any of the strategies to be profitable and this changes according to strategy. At a level of production of 15,000 lb, the strategies PR and GF are the two most profitable. However, there are minimal dif­ ferences among all three strategies at this level of production. As the level of milk production increases, PR emerges as a more profitable alternative; at a level of production of either 17,000 or 19,000 lb, it is the most profitable strategy across all levels of investment. Table 5.1 reveals that the labor requirement is greatest for the strategy PR. For example, it requires 175% more labor for PR than for GFG considering a level of investment of $1,000,000. The number of cows on farms PR is substantially greater than for those GFG or GF. For example, Table 5.2 shows that the number of cows on farms PR is over 3.1 times the number on farms GFG (at a level of investment of $500,000). This tapers off to approximately 2.6 to 2.7 at levels of investment >_$1,500,000. The strategy of GF ranks either first or second across all levels of investment, considering all levels of production. Notice that the number of cows for a given level of investment •and strategy changes as the level of production changes. The model assumes that the price of dairy cows is dependent upon the level of production. The investment in cows is determined by the price of dairy 88 cows, and thus for a given level of investment, the number of cows * changes as the production level changes. Figure 5.3 reveals that most economies of size (as indicated by the slope of the plot of rate of return on investment (RROI) vs. level of investment) are realized between a level of investment of $500,000 and $1,000,000 for all strategies. The strategies GFG and GF continue to experience substantial economies of size at all levels of investment examined. An investment of $1,000,000 repre­ sents herd sizes of ~104, 132 and 290 cows for the strategies GFG, GF and PR, respectively. 89 TABLE 5-1 CHANGES IN PROFITABILITY BY LEVEL OF INVESTMENT ACCORDING TO STRATEGY fMilk production (lb) = Corn Price ($/bu) = Milk Price ($/cwt) = 130001 2.70 12.00 Milk/feed ratio® LEVEL OF INVESTMENT ($ million) 2 1 1 -5 0.5 2.5 STRATEGY s GFG SPROFIT RR0I(£) cows(#) LBR(#) 1.50 -24784 -0.96 40.25 1 .29 -5675 5.43 107.86 2.36 13433 4.90 175-48 3.43 32542 5.63 243.09 4.50 51651 6.07 310.70 5.57 -21967 -0.39 49.21 1 .36 -1122 5.89 131.87 2.62 19724 5.31 214.53 3.88 40569 6.03 297.20 5.13 61414 6.4 6 379.86 6.39 -18695 0.26 129.51 2.05 -11573 2.84 303-53 4.14 -4450 3.70 477.54 6.22 2672 4.13 651-56 8.31 9794 4.39 825.57 10.40 regression: profit by Sinvested a= -43895 b= 0.038 R2= 0.999 GF SPROFIT RROI(^) C0WS(#) LBR(#) a= b= R2= -42812 0.042 0.996 a= b= R2= -25817 0.014 0.804 PR SPROFIT RROl(jg) cows(#) LBR(#j Returns to levels of investment extrapolated for the strategy Returns to levels of investment extrapolated for the strategy Returns to levels of investment extrapolated for the strategy Soil management group = Price of land ($/acre) = Price of hay ($/ton) = Price of corn silage ($/ton)= Price of soybean meal ($/lb)= beyond $ 2416296 GFG beyond $ 2008516 GF beyond $ 1540477 PR 3 1100 75-00 18.31 0.115 Price Price Price Price Price are are are of dairy cows ($/cow)=918.35 of cull cows ($/cwt)= 39.47 of hfrs ($/heifer)= 307.85 of cull hfrs ($/cwt)= 51*46 of cull civs ($/cwt)= 65.06 90 TABLE 5.2 CHANGES IN PROFITABILITY BY LEVEL OF INVESTMENT ACCORDING TO STRATEGY iMilk production (.lbj = Corn Price ($/bu) = Milk Price ($/cwt) = 0.5 150001 2.70 12.00 Milk/feed ratio= LEVEL OF INVESTMENT ($ million) 1 2 1 .5 2.5 STRATEGY: GFG SPROFIT RROl(jo) C0WS(#) LBR(#) 1.50 -21229 -0.25 38.64 1 .26 3955 4.40 103-66 2.29 29140 5.94 168.67 3.32 54325 6.72 233.69 4.35 79509 7.18 298.71 5-38 -17864 0.43 48.74 1 .34 9984 5.00 130.75 2.53 37833 6.52 212.75 3-82 65681 7.28 294.76 5.05 93530 7.74 376.77 6.29 -7048 2.59 122.01 1 .96 15835 5.58 286.2i 3.93 38718 6.58 450.40 5.90 61601 7.08 614.60 7.87 84484 7.38 778.79 9.84 regression: profit by Sinvested a= -46414 0.050 b= ■ R2= 0.999 GF SPROFIT RROI(^) cows(#) LBR(#) a= b= R2= -45712 0.056 0.997 ab« R2= -29931 0.046 0.970 PR SPROFIT RROI(^) C0W3(#) LBR(#) Returns to levels of investment extrapolated for the strategy Returns to levels of investment extrapolated for the strategy Returns to levels of investment extrapolated for the strategy Soil management group = Price of land ($/acre) = Price of hay ($/ton) = Price of corn silage ($/ton)= Price of soybean meal ($/lb)= beyond $ 2505532 GFG beyond $ 2023625 GF beyond $ 1627287 PR 3 1100 75.00 18.31 0.115 Price of Price of Price of Price of Price of are are are dairy cows ($/cow)=1088.35 cull cows ($/cwt)= 39*47 hfrs ($/heifer)= 960.85 cull hfrs ($/cwt)= 51*46 cull civs ($/cwt)= 65.06 91 TABLE 5-5 CHANGES IN PROFITABILITY BY LEVEL OF INVESTMENT ACCORDING TO STRATEGY Milk -production (lb) = Corn Price ($/bu) = Milk Price ($/cwt) = 1700QJ 2.70 12.00 Milk/feed ratio® LEVEL OF INVESTMENT ($ million) 2 1 1 .5 0.5 2.5 STRATEGY • GFG SPROFIT RR0I($) cows(#) LBR(#) 13090 5.31 100.27 2.23 44042 6.94 163.20 3-23 74993 7.75 226.12 4.22 105944 8.24 289.05 5-22 -13718 1 .26 43.67 1 .33 21213 6.12 130.69 2.55 56144 7.74 212.70 3.77 91075 8.55 294.72 4.99 126007 9.04 376.73 6.21 3678 4.74 115.51 1 .88 41127 8.11 271 .19 3-75 78577 9.24 426.88 5.62 116027 9.80 582.57 7.48 153476 10.14 738.25 9.35 -17861 0.45 57.34 1 .24 1.50 regression: profit by Sinvested a-48813 0.062 b= 1 .000 R2= GF a= SPROFIT RROI(^) cows(#) LBR(#) b= R2= -48650 0.070 0.998 PR a® SPROFIT RR0l(j6) cowsu) LBR(#) Returns to levels of investment extrapolated for the strategy Returns to levels of investment extrapolated for the strategy Returns to levels of investment extrapolated for the strategy Soil management group = Price of land ($/acre ) = Price of hay (S/ton) = Price of corn silage ($/ton)® Price of soybean meal ($/lb)= beyond $ 2582724 GFG beyond $ 2024019 GF beyond $ 1711374 PR 3 1100 75i.CO 1£i.31 0 . 115 Price Price Price Price Price of of of of of b= R2= -33772 0.075 0.987 are are are < dairy cows ($/ c o w )=1258.35 cull cows ($/cwt)= 39. 47 !hfrs ($/heifer)= 1113.85 cull hfrs (S/cwt)= 51• 46 ' cull civs ($/cwt)= 65. 06 92 TABLE 5.4 CHANGES IN PROFITABILITY BY LEVEL OF INVESTMENT ACCORDING TO STRATEGY Milk production (lb) = Corn Price ($/bu) = Milk Price ($/cwt) = 0.5 190001 2.70 12.00 Milk/feed ratio= LEVEL OF INVESTMENT ($ million) 1 1.5 2 2.5 STRATEGY: GFG SPROFIT RROI($) C0WS(#) LBR(#) 1.50 -15068 0.99 35.85 1.22 20726 6.07 96.55 2.18 56519 7.77 156.86 3.13 92512 8.62 217.56 4.09 128106 9.12 277.87 5.05 -10074 1 .99 43.04 1.52 31 145 7.11 129.13 2.51 72364 8.82 210.21 3-71 113585 9.68 291.50 4.90 154802 10.19 372.59 6.10 12110 6.42 109-45 1 .81 61070 10.11 257.20 3.58 110029 11.34 404.95 5-35 158988 11 .95 552.70 ~7.15 207948 12.52 700.45 8.90 regression: profit by Sinvested a= -50861 b= 0.072 R2= 1.000 GF SPROFIT RR0I($) cows(#) LBR(#) a= b= R2= -51295 0.082 0.998 a= b= R2= -56849 0.098 0.991 PR SPROFIT RROI(%) cows(?SO LBR(#) Returns to levels of investment extrapolated for the strategy Returns to levels of investment extrapolated for the strategy Returns to levels of investment extrapolated for the strategy Soil management group = Price of land (S/acre) = Price of hay (S/ton) = Price of corn silage ($/ton)= Price of soybean meal ($/lb)= beyond $ 2678708 GFG beyond $ 2045586 GF beyond $ 1798472 PR 5 1100 75.00 18.51 0.115 Price Price Price Price Price are are are of dairy cows ($/cow)=1428.55 of cull cows ($/cwt)= 59-47 of hfrs ($/heifer)= 1266.85 of cull hfrs ($/cwt)= 51.46 of cull civs ($/cwt)= 65.06 93 Profit GF ($000) 90 ■■ 80-- Profit ($000 ) .60 -- Level of Production 13,000 lb // GF 60" GFG 50 -• PR ■'GFG Level of Production 15,000 lb 50" 40 -■ 30 -- 30” 20 -- 20” PR 10 10 TTo -10 ■■ -20 + 10” -20” $ Investment $ Investment (000 ,000 ) (000,000) Profit ($000 ) PR 200 Profit Level of Production 19,000 lb ($000) PR 160 140 Level of Production 17,000 lb 160-140-- GF 120 -- 120 T GFG 100” 80-- 80-- 60-- 40-- 40” 20-- 20-- -20-- Figure 5.1. -20 Profitability by level of investment according to strategy and level of production. Milk price ($/cwt) Corn price ($/bu) Milk/feed price ratio = = = 12.00 2.70 1.5 Dashed line indicates extrapolated values. GF GFG 94 Profit (5000) Level of Investment (5500,000) 20 FR GF GFG Profit (5000) 160 Level of Investment (52,000,000) PR 140 GF 120 13 15 17 100 19 GFG 80 Milk Production (000 lb) 60 40 20 Profit (5000) 50 Level of Investment (51,000,000) PR 13 15 17 19 Milk Production (000 lb) GF 30 GFG 20 10 Profit (5000) 200 Level of Investment (52,500,000) 180 ■ 10 19 15 160 ■ Milk Production (000 lb) GF 140 ■ f GFG 120 Profit (5000) 100 Level of Investment / PR (51,500,000) / 100 60 SO 40 70 GF eo ✓/ 80 90 20 GFG 17 50 Milk Production (000 lb) 40 30 20 10 0 17 19 Milk Production (000 lb) F igure 5.2. PR P r o f i t a b i l i t y b y level of p r o d u c t i o n a c c o r d i n g to st r a t e g y a n d level of investment. M i l k p r i c e ($/cwt) = 12.00 C o m p r i c e ($/bu) =2.70 Milk/feed price ratio = 1.5 Dashed line indicates extrapolated values. 19 95 RROI % RROI % GF PR GFG Level of Production (15,000 lb) ^ Level of Production (13,000 lb) GF GFG 6 PR -1 -2 -1 -2 1.0 RROI % RROI % Level of Production (17,000 1b) 10 1.5 2.0 2.5 Level of Investment (5000,000) Level of Investment (5000,000) PR 9 GF 8 GFG -PR Level of Production (19,000 lb) 11 10 -- GF GFG 7 6 6 -■ 5 4 3 2 1 0 -1 -2 5 1.0 1.5 2.0 2.5 Level of Investment (5000 ,000 ) Figure 5.3. -1 -2 5 1.0 1.5 2.0 Level of Investment (5000,000) Rate o f r e t u r n o n i n v e s t m e n t (RROI) b y level of p r o d u c ­ tion a c c o r d i n g to level o f i n v e s t m e n t a n d strategy. M i l k p r i c e ($/cwt) = 12.00 Corn p r i c e ($/bu) 2.70 Milk/feed price ration = 1.5 Dashed line indicates extrapolated values. 2.5 96 5.2 The Effect of Changing the Milk/Feed Price Ratio on Profita­ bility by Changing the Price of Milk The ranking of strategies depends upon prices relative to each other and the absolute value of these prices. The milk/feed price ratio can be changed by changing either the price in the numerator or the denominator or both. Table 5.5 analyzes the impact of changing the milk/feed price ratio to 1.55 by changing the milk price to $12.60/cwt keeping the corn price at $2.70/bu. Increasing the milk price has the impact of making all strategies more profitable. This impact is greatest for farms PR as the number of cows is greatest for a given number of dollars invested. The strategy of PR becomes a profitable alternative even at levels of production of 13,000 lb milk. The strategy of GF is the most profit­ able at a level of production of 13,000 lb milk (see Table 5.5) . At levels of production >15,000 lb, the strategy of PR is the most pro­ fitable, followed by GF and lastly GFG (see Figure 5.4). Table 5.6 analyzes the impact of changing the milk/feed price ratio to 1.45 by changing the milk price to $11.40/cwt, keeping the corn price at $2.70/bu. This has the inpact of making the strategy of PR the least favorable option until levels of production >17,000 (see Table 5.6). The strategy of GF ranks as the most profitable at levels of production of 13,000 and 15,000 lb milk. Regardless of whether milk price is $11.40, $12.00 or $12.60, the strategy of PR is the most profitable for levels of production of 19,000 lb. The strategy of GF ranks either first or second across all levels of 97 production at milk prices $11.40, 12.00 or 12.60/cwt. When the price of milk is $11.40/cwt there is little difference in profita­ bility between the strategies of GF or GFG. Figure 5.6 demonstrates the sensitivity of all three strategies to the price of milk for a given level of production and level of investment. The strategy of PR is, of course, the most sensitive. The strategies of GF and GFG diverge as the price of milk increases (due to the greater number of cows) for a given level of investment for farms GF. Although profitability of the strategy of PR is the most sensitive to the price of milk, it is always the most profitable at level of production at 19000 lb, even at a milk price of $11.40/ cwt. 5.3 The Effect of Changing the Milk/Feed Ratio on Profitability by Changing the Price of Corn Figure 5.7 and Tables 5.7 through 5.10 illustrate that the stra­ tegy of PR is most sensitive to changing the price of corn. At a level of production of 13,000 lb (given a level of investment of $1,000,000), PR becomes unprofitable once the corn price >$2.55/bu. When the price of corn >_$3.10/bu, the strategy GFG is the most pro­ fitable. At a level of production of 15,000 lb, PR is a profitable stra­ tegy until the price of corn >$2.85/bu; at 19,000 lb, PR is still a profitable alternative with a corn price at $3.30/bu. The strategy GF ranks as either 1st or 2nd across all levels of production and all levels of investment. 98 Table 5.5. Profitability by Level of Investment According to Level of Production and Strategy Corn Price ($/bu) = Milk Price ($/cwt)_______ = |Milk/feed ratio = .5 Level of milk production(lb) and strategy 13'000 15,000 17,000 19,000 2.70 12.60 1.55 j Level of Investment 1 1.5 $ $ ' $ ($ million) 2 2.5 $ $ GFG GF PR -21,300 -17,800 - 7,500 3,600 10,200 14,600 28,500 38,100 36,800 53,500 66,100 58,900 78,400 94,000 81,000 GFG GF PR -17,500 -13,200 4,600 14,000 22,600 43,200 45,500 77,000 58,300 94,100 81,900 120,500 108,400 129,800 159,100 GFG GF PR -13,900 - 8,500 15,900 23,800 61,600 99,300 35,200 78,900 122,600 69,700 123,600 177,400 137,000 166,300 231,300 GFG GF PR -10,900 - 4,500 24,700 32,100 75,100 118,000 46,300 97,000 147,800 90,700 156,800 222,800 161,000 198,500 288,800 Return to levels of investment beyond -$2,000,000 are extrapolated for the strategy GF. Returns to levels of investment beyond ~$1,500,000 are extrapolated for the strategy PR. 99 Profit ($000) PR Level of Production (15,000 lb) 160 140 ■■ Profit ($000) 100" 120 " 100 Level of Production 80 60 ” 40 20 -20 .5 Investment ($000,000) 1.0 1.5 2.0 2.5 Investment ($000 ,000 ) Profit ($000) 260 -jProfit ($000) PR 240 220 •• Level of Production 220 ■■ 200 200 ■■ - <1 7 '000 l b ) 180 180 ■■ 160 ■■ 160 140 140 GFG 120 100 -■ GF GFG 120 100 80 80 60 60 -- 40 40 20 20 -20 -40 Level of Production (19,000 lb) -20 .5 1.0 l.E 2.0 2.5 40 Investment ($ 000 ,000) Figure 5.4. ■■ Investment ($ 000 ,000 ) Profitability by level of investment according to strategy and level of production (increasing the milk price). Milk price ($/cwt) Corn price ($/bu) Milk/feed price ratio = 12.60 = 2.70 = 1.55 Dashed line indicates extrapolated values. 100 Table 5.6. Profitability by Level of Investment Accroding to Level of Production and Strategy C o m Price ($/bu) Milk Price ($/cwt) Milk/feed ratio = 2.70 = • 11.40 =____1 .45 .5 $ Level of Investment ($ million) 1 1.5 2 2.5 $ $ $ $ Level of Milk Production(lb) and Strategy 1j,uuu 24,600 GFG -28,300 -15,100 - 1,800 11,400 -26,300 -12,600 28,400 GF 1,100 14,700 PR -30,300 -38,800 -47,300 -55,800 - 64,300 15,000 -25,000 - 6,200 12,600 31,500 50,300 GFG 56,800 -22,600 -28,000 17,100 36,900 GF 7,100 PR -19,200 -12,600 - 6,100 500 17,000 74,600 -21,900 2,200 26,300 50,500 GFG 7,000 33,100 59,200 GF -19,000 85,200 32,000 52,400 72,900 PR - 8,900 11,500 19,000 94,900 -19,400 9,200 37,800 66,400 GFG -15,800 15,800 47,300 78,900 110,500 GF PR 900 30,400 61,700 93,100 124,000 Returns for the Returns for the to levels of investment beyond ~$2,000,000 are extrapolated strategy GF. to levels of investment beyond -$1,500,000 are extrapolated strategy PR. 101 Profit ($000 ) 40 30 Profi t ($000) 50-- GF Level of Production (15,000 lb) GFG 40-Level of Production (13,000 lb) GF GFG 20 10 30" 20" 10" -10 -10 -20 -20 -30 PR Investment ($000,000) -40 50 -60 PR -80 Investment ($000,000) Profit ($000) 110 .PR Level of Production (19,000 lb) 100 Profit ($000) Level of Production 0(>_ (17,000 lb) GF GFG 90 80 A PR 70" 70 60 60r 50" 50 40-- 40 30" 30 2 0 -- 20 10 0 2.0 -10 -10 -20 -20 Investment ($000 ,000 ) Investment ($000 ,000 ) Figure 5.5. Profitability by level of investment according to strategy and level of production (decreasing the milk price). Milk price ($/cwt) Corn price ($/bu) Milk/feed price ratio GF = 11.40 = 2.70 =1.45 Dashed line indicates extrapolated values. 102 Profit ($000) Level of Production (15,000 lb) Profit ($000) Level of Production (19,000 lb) 90 60 ” GF 50 11.40 12.00 12.60 40 GFG -30 30 Milk Price ($/cwt) 20 10 -10 Profit 12.00 12.60 Milk Price ($/cwt) Level of Production (17,000 lb) ($000) h 11.40 PR GF 30 '■ GFG 10" 60 -10 Milk Price ($/cwt) Figure 5.6. The impact of changing the price of milk on profitability. Price of corn ($/bu) Level of investment = 2.70 = $1,500,000 103 Profitability changes slightly for the strategy of GFG as the price of corn changes. This is a result of the price of soybean meal being correlated to the price of c o m in the model. Figure 5.8 reveals that the impact on profitability of changing the milk/feed price ratio by changing the numerator (i.e. the price of milk) is different than the impact of changing the denominator (i.e. the price of corn). Changing the price of milk has the most dramatic effect on profitability across all strategies. Changing the milk/feed price ratio by changing the price of corn has little effect upon the strategy of GFG and a moderate affect on the strategy of GF. 5.4 The Impact of Changing the Price of Land on Profitability Figure 5.9 and Tables 5.11 through 5.15 illustrate the impact of changing the price of land without changing the soil management group (SMG), considering: SMG = 3, level of production at 15,000 lb, price of milk at $12.00/cwt and c o m at $2.70/bu. At a land price of $500/acre, both GFG and GF are equally profitable and returns to these strategies are almost double those received under the stra­ tegy of PR. At a land price of $700/acre the strategy of GF is slightly more profitable than that of GFG and again, both yield sub­ stantially greater returns than the strategy of PR. At a land price of $900/acre the strategy of GF is the most profitable. The strategy of PR yields greater returns than GFG until an investment level of $1,500,000. At this level GFG is a more profitable strategy than PR. At a land price of $1100/acre the strategy of PR yields the greatest returns until investment levels approach $1,500,000. Beyond this 104 Profit 50 ' Profit ($000 ) 40 Level of Production (13,000 lb) 30 20 10 ■■ 20 10 GFG GF -10 -20- Level of Production (15,000 lb) 2.55 -10 20 ■■ 2.70 2.55 2.70 -30 30 •40 + 40” PR -50 ' Corn Price ($/bu) PP. -70" Corn Price ($/bu) Profit ($000 ) 100 Level of Production (17,000 lb) 90 Profit ($000 ) 80 80" 70 70" 60 60" 50 50" Level of Production (19,000 lb) 40 30 20 10 GFG GF 10 GFG GF .PR -10 FR -20 -30 20” 10" 2.55 -20” -30Corn Price ($/bu) Corn Price ($/bu) Figure 5.7. The impact of changing the price of corn on profitability. Price of milk ($/cwt) = Level of investment = 12.00 $1,000,000 105 Table 5.7. Changes in Profitability by Level of Investment According to Strategy Considering Different Prices of Corn (Level of Production = 13,000 lb) GFG N o . cows No. laborers Corn 2.55 2.70 2.85 3.10 3.30 -24,700 -24,800 -24,900 -25,000 -25,100 GF N o . cows No. laborers Corn 2.55 2.70 2.85 3.10 3.30 - 5,500 5,700 5,900 6,200 6,500 132 2.6 - 900 1,100 3,100 6,400 9,100 130 2.1 304 -12,700 -18,700 -24,700 -34,600 -42,500 2,400 -11,600 -25,500 -48,800 -67,500 i—1 Returns for the Returns for the Returns for the 108 2.4 49 1.4 -21,200 -22,000 -22,700 -24,000 -25,000 PR N o . COWS No. laborers Corn 2.55 2.70 2.85 3.10 3.30 40 1.3 176 3.4 13,800 13,400 13,100 12,600 12,200 215 3.9 23,000 19,700 16,500 11,100 6,800 478 6.2 243 4.5 33,000 32,500' 32,200 31,400 30,800 297 5.1 45,100 40,600 36,100 28,600 22,600 652 8.3 311 5.6 52,300 51,600 51,200 50,200 49,500 380 6.4 67,300 61,400 55,800 46,200 38,500 826 10.4 17,600 32,700 47,900 - 4,500 9,800 2,700 -26,400 -27,300 -28,200 -63,100 -77,300 -91,600 -92,400 -117,300 -142,300 to levels of investment beyond $2,415,596 are extrapolated strategy GFG. to levels of investment beyond $2,007,816 are extrapolated strategy GF. to levels of investment beyond $1,540,477 are extrapolated strategy PR. 106 Table 5.8. Changes in Profitability by Level of Investment According to Strategy Considering Different Prices of Corn (Level of Production = 15,000 lb) .5 GFG N o . cows N o . laborers Com 2.55 2.70 2.85 3.10 3. 30 Corn 2.55 2.70 2.85 3.10 3. 30 PR N o . cows No. laborers Returns for the Returns for the Returns for the 39 1.3 -21,100 -21,200 -21,400 -21,600 -21,800 GF N o . cows No. laborers Corn 2.55 2.70 2.85 3.10 3. 30 Level of Investment ($ million) 2.0 1.0 1.5 104 2.3 4,400 4,000 3,600 2,900 2,400 2.5 169 3.3 234 4.3 299 5.4 29,800 29,100 28,500 27,500 26,600 55,300 54,300 53,500 52,000 50,800 80,700 79,500 78,500 76,500 75,000 49 1.3 131 2.6 213 3.8 295 5.1 377 6.3 -16,900 -17,900 -18,900 -20,600 -21,900 12,700 10,000 7,300 2,800 800 42,300 37,800 33,500 26,200 20,300 71,900 65,700 59,700 49,500 41,400 101,400 93,500 85,900 72,900 62,500 122 2.0 900 - 7,000 -13,200 -23,300 -31,500 286 3.9 450 5.9 30,200 61,300 15,800 38,700 1,500 16,200 -22,400 -21,500 -41,500 -51,600 615 7.9 779 9.8 92,500 61,600 30,800 -20,500 -61,600 123,600 84,500 45,500 -19,600 -71,600 to levels of investment beyond $2,504,832 are extrapolated strategy GFG. to levels of investment beyond $2,022,925 are extrapolated strategy GF. to levels of investment beyond $1,627,287 are extrapolated strategy PR. 107 Table 5.9. Changes in Profitability by Level of Investment According to Strategy Considering Different Prices of Corn (Level of Production = 17,000 lb). .5 GFG N o . cows N o . laborers Corn 2.55 2.70 2.85 3.10 3. 30 GF N o . cows N o . laborers Corn 2.55 2.70 2.85 3.10 3.30 PR N o . cows N o . laborers Corn 2.55 2.70 2.85 3.10 3.30 Returns for the Returns for the Returns for the Level of Investment 1.0 1.5 37 1.2 -17,700 -17,900 -18,100 -18,500 -18,800 49 1.5 -12,400 -13,700 -15,000 -17,200 -18,900 100 2.2 13,700 13,100 12,500 11,500 10,700 131 6.5 24,700 21,200 17,800 12,000 7,400 163 3.2 45,100 44,000 43,100 41,500 40,200 213 8.1 61,800 56,100 50,600 41,200 33,700 ($ million) 2.0 226 4.2 76,400 75,000 73,700 71,400 69,600 295 9.0 99,000 91,100 83,400 70,300 60,000 2.5 289 5.2 107,800 105,900 104,300 101,400 99,100 377 9.4 136,100 126,000 116,200 99,500 86,200 116 1.9 271 3.8 427 5.6 583 7.5 738 9.4 9,900 3,700 - 2,500 -12,900 -21,300 55,800 41,100 26,500 2,100 -17,400 101,700 78,600 55,600 17,100 -13,600 147,500 116,000 84,600 32,200 - 9,800 193,400 154,500 113,700 47,200 - 6,000 to levels of investment beyond $2,582,024 are extrapolated strategy GFG. to levels of investment beyond $2,023,319 are extrapolated strategy GF. to levels of investment beyond $1,711,374 are extrapolated strategy PR. 108 Table 5.10. Changes in Profitability by Level of Investment According to Strategy Considering Different Prices of Corn (Level of Production = 19,000 lb). .5 GFG N o . cows N o . laborers Corn 2.55 2.70 2.85 3.10 3. 30 GF N o . cows N o . laborers Corn 2.55 2.70 2.85 3.10 3.30 Corn 2.55 2.70 2.85 3.10 3.30 Returns for the Returns for the Returns for the ($ million) 2.0 36 1.2 96 2.2 157 3.1 217 4.1 -14,800 -15,100 -15,400 -15,900 -16,200 21,500 20,700 20,000 18,700 17,600 57,800 56,500 55,300 53,200 51,500 94,100 92,300 90,600 87,700 85,400 48 1.3 - 8,500 -10,100 -11,600 -14,200 -16,200 PR N o . cows No. laborers Level of Investment 1.0 1.5 129 2.5 35,300 31,100 27,000 20,100 14,600 210 3.7 291 4.9 79,200 72,400 65,700 54,400 45,500 123,000 113,600 104,300 88,800 76,300 109 1.8 257 3.6 405 5.4 18,500 12,100 5,700 - 4,900 -13,400 76,100 61,100 46,100 21,100 1,100 133,700 110,000 86,400 47,100 15,600 553 7.1 191,300 159,000 126,800 73,048 30,000 2.5 278 5.1 ■ 130,400 128,100 126,000 122,200 119', 200 373 6.1 166,900 154,800 143,000 123,100 107,200 701 8.9 248,900 207,900 167,200 99,032 44,500 to levels of investment beyond $2 ,678,008 are extrapolated strategy GFG. to levels of investment beyond $2 ,044,886 are extrapolated strategy GF. to levels of investment beyond $1 ,798,472 are extrapolated strategy PR. 109 Profit ($000 ) Profit ($000 ) PR 40 PR 30GF 20- 20" GFG GF 10- 10" GFG -10 -10 11.40 12.00 2.85 Price of Corn ($/bu) Milk/Feed Price Ratio Milk/Feed Price Ratio Figure 5.8. 1.50 2.55 12.60 Price of Milk ($/cwt) 1.55 2.70 1.55 1.45 1.50 1.45 The impact of changing the milk/feed' price ratio by changing the price of milk vs. changing the prige of corn. Level of investment Level of production = = $1,000,000 15,000 lb 110 level of investment, GF is the most profitable strategy followed by the strategy of PR. At a land price of 51300/acre, the strategy of PR is the most profitable across all levels of investment. Notice that profitability for the strategy PR changes slightly as the land price changes. This is because the model assumes that land is purchased for facilities for the dairy at the same price/ acre as is charged for land for crops. 5.5 The Impact of Changing the Soil Management Group and Price of Land on Productivity Tables 5.16 through 5.18 indicates that there is little change in profit when the soil management group (SMG) is changed to either 2.5 or 4 if the price of land is adjusted to reflect the difference in soil productivity. Assuming a price of 51100/acre for land in SMG 3, the price of land in SMG 2.5 is approximated as: .87 = 1260, or ~1300/acre. as: (51100/acre)/ The price of land in SMG 4 is approximated (51100/acre)/I.20 * 5900/acre (see thesis section 4.1.3A). The fact that there is little difference in profitability across SMG of 2.5, 3 or 4 when the price of land is adjusted, indicates that the method of assessing land values defined in the Tax Assessor's Manual (1972) adequately estimates the difference in land value in regard to hay and corn production. Notice that the profitability of PR changes slightly as SMG changes in Tables 5.16 through 5.18. This is due to the fact that the price of corn silage, as estimated in the model, is dependent on the pro­ ductivity of the soil on which it is produced. The model assumes that Ill farms PR will be buying corn silage from farms with the same SMG as farms organized to GFG or GF. 112 TABLE 5.11 CHANGES IN PROFITABILITY BY LEVEL OF INVESTMENT ACCORDING TO STRATEGY Milk production (rb)= Corn Price ($/bu) = Milk Price ($/cwt) = 15000 2.70 12.00 Milk/feed ratio® LEVEL OF INVESTMENT ($ million) 1 2 1.5 0.5 2.5 STRATEGY ; GFG SPROFIT RR0I(£) COWS(#) LBR(#) 10160 1.97 52.98 1 .49 33264 7.33 141.63 2.89 -8917 2.22 62.62 1 .55 33596 7.36 167.39 3-13 -6701 2.66 123-20 1.97 16661 5.67 289.04 3.96 1.50 76687 9.11 230.27 4.30 120110 10.01 318.92 5.70 76109 9.07 272.16 4.71 118622 9-93 376.92 6.29 161135 10.45 481.69 7.87 63385 7.17 620.72 7.94 86747 7.47 786.57 9.93 163534 10.54 407-56 7.10 regression: profit by Sinvested a= -53583 b= 0.087 R2= 0.999 GF SPROFIT RROl(g) COWS(#) LBR(§) a= b= R2= -51429 0.085 0.997 a= b= R2= -30063 0.047 0.971 PR SPROFIT RROI (.?) COWS(#) LBR(#) 40023 6.67 454.88 5.95 Returns to levels of investment extrapolated for the strategy Returns to levels of investment extrapolated for the strategy Returns to levels of investment extrapolated for the strategy Soil management group = Price of land (S/acre n . Price of hay (S/ton) = Price of corn silage ($/ton)= Price of soybean meal ($/lb)= beyond S! 1888377 GFG beyond $; 1624001 GF beyond $; 1612287 PR 3 "5GF>PR'across all levels of investment. At a level of produc­ tion of 15,000 lb, the strategies PR and GF are the two most profitable. However, there are minimal differences among all three strategies. At levels of production of 17,000 or 19,000 lb, the strategies rank in order of profitability as: PR>GF>GFG. 2) The amount of labor required for a given level of investment and production is 1.5 to 1.9 times greater for the strategy PR com­ pared to GFG. 3) The numbers of cows for a given level of investment and pro­ duction level is 2.5 to 3;2 times greater for the strategy PR com­ pared to GFG. 4) The strategy GF ranks either first or second across all levels of investment and milk production. 5) Most economies of size are realized between a level of in­ 123 vestment of $500,000 and $1,000,000 for all strategies. The strate­ gies GFG and GF continue to experience economies of size at all levels of investment examined. The second analysis examined the consequence of changing the milk/feed price ratio to 1.45 and 1,55 by changing the price of milk to $11.40 or $12.60/cwt, respectively. This analysis revealed that the ranking of strategies depends upon relative prices price ratios) in addition to absolute values. (i.e. Increasing the milk price to $12.60/cwt had the obvious effect of making all strategies more profitable. At this price, PR was a profitable strategy with the level of milk production as low as 13,000 lb, at a level of investment >$1.0 million. Decreasing the milk price had a dramatic negative impact across all strategies, but PR was the most sensitive. When the milk price was dropped to $11.40/cwt, the strategy PR was the least profitable until a level of milk production >17,000 lb. The strategy of GF ranked either 1st or 2nd across all levels of invest­ ment and production. The third analysis examined the consequences of changing the milk/feed price ratio by changing the price of corn. Corn prices of: $2.55, 2.70, 2.85, 3.10 and 3.30/bu were budgeted across levels of production of: 13, 15, 17 and 19 thousand lb of milk. The analysis revealed .1) At a level of milk production of 13,000 lb and a level of investment of $1,000,000, the strategy PR becomes unprofitable once corn price >$2.55/bu. When the price of corn >$3.10/bu, the strategy GFG is the most profitable. 124 2) At a level of production of 15,000 lb, the strategy of PR is profitable until the price of corn >$2.85/bu; at 19,000 lb PR is still a profitable alternative with a corn price at $3.3Q/bu. 3) The strategy GF ranks either 1st or 2nd across all levels of production. Analyses 2 and 3 reveal that the consequences of changing the milk/feed ratio by changing the price of milk (the numerator) is different than changing the price of feed (the denominator). The fourth analysis examined the effect of the price of land on the profitability of each strategy, assuming a level of milk produc­ tion of 15,000 lb, soil management group 3, a price of milk of $12.00/ cwt, and a c o m price at $2.70/bu. This analysis revealed: 1) At a price of $500/acre, both GFG and GF are equally profit­ able and returns to these strategies are almost double those received under the strategy PR. 2) At a price of $700/acre, the strategy of GF is slightly more profitable than that of GFG and both yield substantially greater returns than PR. 3) At a price of $900/acre the strategy GF is most profitable. The strategy PR yields greater returns than GFG, until an investment level of $1,500,000. At this level, GFG is a more profitable strate­ gy than PR. 4) At a land price of $1100/acre, the strategy of PR yields the greatest returns until investment levels approach $1,500,000. Beyond this level of investment, GF is the most profitable strategy followed 125 by the strategy of PR. 5) At a land price of $1300/acre, the strategy of PR is the most profitable across all levels of investment. The fifth analysis examined the effect on profitability of changing the soil management group (SMG) to either 2.5, 3 or 4, and consequently changing the price of land. There were no differences in profitability for the strategies as the SMG was changed, when the price of land was adjusted accordingly. All of the analyses showed minimal to negative returns for levels of investment of $500,000. These results show: 1) The strategy of PR is a viable strategy of dairying in Michigan, given an expected milk price of $12.00/cwt, a corn price of $2.70/bu, a level of production >17,000 lb milk and an investment level >_$1,000,000. 2) the strategy of GF is a profitable strategy of dairying for all levels of production provided the level of investment >_$1,000,000. 3) The strategy of GFG is a profitable strategy of dairying across all levels of production, provided the level of investment >$1,500,000. 4) The impact of changing the price of milk or corn on profita­ bility is greatest for the strategy of PR. 5) High levels of production (>17,000) are most important to make PR a profitable enterprise. 6 ) The strategy of GF usually ranks 1st or 2nd in terms of profit 126 for a given level of investment or production. The tremendous varia­ bility in profit and potential for lower profit for given levels of investment and production considering corn prices ranging from $2.55 to $3.10/bu indicate that PR is not the strategy of choice for risk averse investors. Although the variability in profit is greater for the strategy of GF compared to GFG, the potential 'for lower profit is not substantially less than GFG but the potential for greater income makes this option the strategy of choice. Further research should focus on the consequences of shifting from the strategy of GFG to GF or PR, considering cash flow implications in addition to total profit. The results presented here are a few examples of the possible situations that can be analyzed using the dairy investment model. The impact on profitability of different interest rates, fertilizer prices, fuel prices, labor costs, etc. can be examined. These results should not encourage farmers to switch from their current strategy of securing feeds on dairy farms to either grow for­ ages only or to purchase all feeds. specific set of resources These results are based on a (i.e. complements of machinery, buildings, etc.) and conditions simulated in the model. It does not examine the consequences of shifting from one strategy to another or the specific circumstances of any particular farm. It does indicate, however, that as more resources are invested in dairying, many farmers would be better to concentrate on increasing herd size and milk pro­ duction level, and purchase c o m grain from neighboring crop farmers as high moisture shelled corn to meet additional grain needs. 127 Another important factor which is not taken into account is management ability. Someone who is a good dairy farmer is not nec­ essarily a good crop farmer. One who is a good manager of an 80 cow herd may not have the ability or desire to manage 300 cows. These factors must all be accounted for in making an initial investment or expansion decision. This is a static model which does not consider cash-flow com­ mitments over time, method of debt financing or the ability to project the impact of different prices or price variability over different time periods of the investment. add to the value of the m o del. These components would substantially APPENDIX A MICHIGAN LAND VALUES AND AVERAGE CASH RENTS Prom the early 1970*s to 1981 farm real estate values increased annually and unrealized capital gains were a major component in the total returns to agricultural production assets (Burghardt, 1982). Depressed farm income, high interest rates and higher returns to money markets since that time have resulted in a negative growth rate in the value of farm real estate. After adjusting for inflation, the average value of U.S. farmland slipped equal amounts in 1981-82 and 1982-83. During this first period the value of land decreased 1%; coupled with an 8% increase in the Consumer Price Index (CPI), this resulted in the real value of land declining by 9%. At 6% decline in price plus a 3% gain in the CPI during 1982-83 again resulted in a decline of 9% in the real value of land (Doane's Agric. Report, 1983). Because of the low number of farm real estate transactions over the past few years as well as the fact that many of these have resulted from forced sales for estates or liquidations, caution is urged when interpreting these numbers. According to several observers, land prices seem to have leveled off or improved somewhat since the beginning of 1983 (Doane's Agric. Report, 1983). Henderson (1983) states that improved crop prices and higher farm incomes should spark increased interest in buying farmland by farmers with reasonable debt loads for expansion purposes. He notes that a number of factors such as: relatively high interest rates, modest 128 129 inflation, increased distress sales of those who fell into financial difficulties in 1981 and 1982 and a hesitancy of farm lending agencies to make farm real estate loans limit land price increases in 1983. 130 Table Al. Average Michigan Farmland Values and Indexes During the Last 5 Yearsa Year 1979 1980 Value ($/acre) 975 1082 124 138 Index (.1977=100) aSource: Doane's Agric. Report, 1983. Table A2. Year 1982 1192 152 1983 1109 141 Average Per Acre Cash Rents and Farmland Values in Michigan from 1960 to 1980a A v g . Rent $ 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1232 157 14.08 14.00 14.58 14.81 15.42 16.12 17.24 20.49 18.48 19.15 18.00 20.21 19.85 22.77 26.23 28.50 31.17 37.51 38.00 40.00 46.40 A v g . Land Value (as of Feb.) $ 228 239 248 241 258 271 301 328 350 359 341 328 393 448 563 564 631 786 811 885 1039 Predicted*} Land Rent Predicted Land Value0 $ $ 16.45 16.94 17.33 17.02 17.77 18.34 19.66 20.85 21.82 22.22 21.42 20.85 23.71 26.13 31.19 31.24 27.76 41.00 42.10 45.36 52.14 240 237 252 257 272 239 316 395 346 362 334 388 380 448 534 539 ■ 653 807 819 867 1022 aSource: Robison and Espel, 1981. DThe predicted land rental rate is calculated as: 6.42 + .044 * avg. land value (r = .987, 20 observations). If a property tax of 1.6% of the value of land is assumed, then the real after tax rate of return expected by those who rent land is approximately .044 - .016 = .028 or 2 .8 %. cThe predicted land value is calculated as: -100.9 + 2 4 . 2 * average cash rental rate, r = .99 for observations from 72 to 80. APPENDIX B LOGIC OF FEED PURCHASING DECISIONS A. Purchasing Corn Once the decision is made to purchase all feeds or at least the grain, the next decision is to determine how much should be purchased and stored at any given time. It seems reasonable to assume that feeds purchased at harvest time would cost less than they would if purchased month by month. As a matter of fact, for the past 7 out of 10 years it would have cost those purchasing corn more if they purchased through­ out the year than if they purchased all of their corn at harvest time as shown in Table Bl. However, this does not take into account the costs of: storage, interest paid on the corn purchased, or the phy­ sical cost to store corn. for is drying costs. Another important consideration to account Corn purchased at harvest time can be ensiled as high moisture shelled corn. This would eliminate the drying cost which is assumed to be passed to the feed purchaser. harvest price of corn over the past 10 years Adjusting the average (expressed in 1983 dollars; see Table B2) by these costs and comparing them with the average season price adjusted by a margin paid to the grain elevator reveals, that based on the expected price of corn and today's costs, farmers would be as well off if they purchased corn at harvest season from nearby grain farmers and ensile as high moisture corn. Savings in drying cost is estimated a s : $.025/point to dry * 12 points/bushel = $.30/bushel (Schwab et al., (1983) Corn storage cost is calculated based on the cost of a 20'x60' silo 131 132 with a top unloader using a 20 year expected life and a 4% interest rate. In 1983 the initial investment amounts to over $22,600 (see Table 4.6). The annual use cost of the silo is estimated using the formula: r * purchase price 1 1 - (1+rL) where: r = interest rate = 4% L = years of life= 20 years .04 * $22,600 1 1 - (1.0420) = .074 * 22,600 = 1672/year 1672 f 13000 bu = .13/bu/year Interest cost of corn is based on: 4% interest rate * average harvest season price * 1/2 .04 * 3.56 * .5 = $.07/bu interest Cost to fill the silo is estimated based on the labor and fuel estimated to be needed. Assuming a farm with a 20'x60' silo holding 455 tons of high moisture corn at 30% moisture and a filling rate of 10 tons/hr (the slow rate of filling due to the harvest capacity limi­ tation of the combining process) it should take (455 tons)/l0 tons/hr = 45.5 hr to fill the silo. Assuming that ensiling requires one person to transport wagons and ensile, it would require 45.5 hr of labor. At $5.00/hr this would amount to 45.5 hr * $5.00/hr = $228 for labor. Assuming that the blower requires a 40 hp tractor (requiring 3 gal diesel fuel/hr) and that the blower is operating about 1/2 of the time = 1 . 5 gal/hr. Assuming that tractors transporting corn are 40 hp also, then total fuel consumed/hr = 4.5 gal/hr. 205 gal of diesel fuel. Thus, 45.5 hr * 4.5 gal/hr = Using a price of $1.20/gal of fuel required, results in a fuel cost of 205 gal * $1.20/gal = $246 fuel cost to fill the silo. 133 The total cost to ensile would be: $246 + $228 = $474. Since the capacity of a 20'x60' silo is 13,000 bu of high moisture corn, then the cost/bushel to ensile is estimated to be $474 ? 13,000 = $.036 or ~$.04/bushel to ensile c o m . The margin paid to the elevator is estimated as the difference in price that the elevator will pay to buy c o m and the price they charge when they sell it to the farmers. This is estimated as $.15 per bushel (JEcker, 1983) . The cost to buy c o m at harvest and ensile as high moisture corn = Corn avg. harvest price + Storage + Interest - Savings in + Cost to = Adjusted cost charge drying fill silo harvest price (1983 dollars) $3.56 + .13 + .07 - .30 + .04 = $3.50/bu Cost to buy corn through the year as needed: Corn avg. yearly price (1983 dollars) $3.61 B. + Margin paid = Adjusted yearly price to elevator + .15 = $3.76 Purchasing Hay Table B1 shows the harvest season price and the yearly price of hay received by Michigan farmers over the past 10 year's. This table reveals that in 8 out of 10 years, farmers purchasing hay would have paid less if they purchased all hay during the harvest season. However, this does not consider the cost to store hay or the interest cost to purchase hay at harvest time. Once these costs are included it is calculated that it cost approximately $2.15 more/ton to purchase hay at harvest time 134 than purchasing it evenly throughout the year, assuming hay is purchased directly from other fanners. Hay storage cost is estimated based on the cost to construct a pole barn with an expected life of 20 years and a real interest rate of 4%. Assuming a b a m cubic feet/ton then: 14' to the eaves and that hay occupies 250 (.250 cu ft/ton)/14 ft = 17.85 square ft needed/ton. Assuming a cost of $3.50/square ft to construct a pole b a m then 17.85 ft * $3.50 = $62.50/ton to store hay. Since storage would be needed for about 70% of the hay at any one time then: $62.50 * .7 = $43.70/ton investment cost/ton of hay. The annual use cost of the hay barn is estimated using the formula: r * purchase price 1 1 - (l+rL ) where: r = interest rate L = years of life = .074 * 43.70 = $3.23/ton/year storage cost Interest charge for hay is based on 4% interest * 1/2 * average season price 4 % * .5 * $61/ton = $L22/year interest cost for hay Cost to purchase hay at harvest time and store it: Hay harvest price (1983 dollars) $61/ton + Hay storage + Interest = Adjusted harvest price cost charge + 3.23 + 1.22 Cost to purchase hay throughout the year Average season price (1983 dollars) $67.60/ton = $65.45/ton 135 Based on the estimates above, it is assumed, in this analysis, that farmers purchasing corn purchase their annual corn needs at harvest time and ensile it as high moisture corn. It is also assumed that farmers purchasing hay purchase hay throughout the year as needed and when the price is right. To allow flexibility in hay purchasing and to guard against dramatic seasonal price changes there is a 4 month inventory of hay on the farm. Table Bl. Nominal Prices of Corn and Hay Received by Michigan Farmers from 1972 to 1982a Year Corn Harvest Season13 Price ($/bu) 1972-73 1973-74 1974-75 1975-76 1976-77 1977-78 1978-79 1979-80 1980-81 1981-82 1.22 2.16 3.29 2.28 2.10 1.73 1.98 2.28 3.05 2.30 Avg. Yearlyc Price ($/bu) 1.59 2.51 2.82 2.42 2,02 1.99 2.28 2.43 3.05 2.35 Hay Harvest Seasond Price ($/ton) Avg. Yearlye Price ($/ton) 27.50 30.10 31.00 43.50 38.40 53.00 43.10 36.00 30.00 40.60 29.40 31.20 40.90 42.00 44.90 60.00 45.40 36.40 37.70 58.90 aSource: Michigan Dept. Agric. 1973-1983. bcorn harvest season price is estimated as the average of the average monthly prices received in October, November and December. cCorn average yearly price is estimated as the average of the average monthly prices received from October to October. *%ay harvest season price is estimated as the average of the average monthly prices received in June, July, August and September. eHay average yearly price is estimated as the average of the average monthly price received from June to June. 136 Table B2. Adjusted (1983 Dollars)a Prices of C o m and Hay Received by Michigan Fanners from 1972 to 198213 Year '. , Corn Harvest Seasonc Price (,$/bu) 1972-73 1973-74 1974-75 1975-76 1976-77 1977-78 1978-79 1979-80 1980-81 1981-82 X SD CV Avg. Yearly01 Price ($/bu) Hay Harvest Seasone Avg. Yearlyf Price ($/ton) Price ($/ton) 2.81 4.59 6.23 4.02 3.53 2.73 2.87 2.93 3.47 2.40 3.54 5.07 5.18 4.18 3.29 3.02 3.13 2.94 3.33 2.41 64.10 65.70 60.90 78.20 65.50 84.80 63.90 47.90 35.30 43.20 67.40 65.90 77.60 74.30 75.10 94.00 65.30 46.30 42.90 61.60 3.56 1.15 .32 3.61 .92 .25 60.95 15.17 .25 67.04 14.92 .22 a1983 adjusted prices are estimated using the Consumer Price Index of: purchasing power of the dollar, obtained from: Bureau of Economic Analy­ sis, 1983,1980,1978,1976. Index values of the appropriate months are used. For example, the appropriate CPI's to use for corn harvest season for 1972-73 for October, November and December are: .790, .788 and .786. The average of these values is .788. The CPI value used to convert to 1983 dollars is .341. Thus, to convert corn harvest season price for 1972-73 to 1983 dollars multiply the c o m price ($1.22) * (.788/.341) = $2.81. ^Source: Michigan Dept, of Agric. 1973-1983. cCorn harvest season price is estimated as the average of the average monthly prices received in October, November and December. ^Corn average yearly price is estimated as the average of the average monthly prices received from October to October. eHay harvest season prices is estimated as the average of the average monthly prices received in June, July, August and September. % a y average yearly price is estimated as the average of the average monthly prices received from June to June. APPENDIX C CROP MACHINERY COMPLEMENTS 137 Machinery complements were assembled using information from the following: Maddex and White John Deere and Co., 1969 White, 1978 White, 1977 White, 1972 Sources of prices used to estimate costs in Table Cl through C8 are listed below: Abbreviation Source OG National Farm Power and Equipment Dealers Assoc., 1982 PPFI Crop Reporting Board, 1982a,b T Dealer: Thesier's John Deere Farm Equipment, N. Cedar St., Mason, MI, 1983 - via phone conversation CAP Shaudys, 1980 EST Estimated price based on similar equipment: Crop Reporting Board, 1983a,b AC Dealer: William's Farm Equipment, 1983 1115 Lansing St., Charlotte, MI, 1983 via phone conversation SN Nott, 1980 Make: JH = John Deere IH = International Harvester NI = New Idea 138 Table Cl. Crop Machinery and Equipment = 40 Cows Equipment No. Price each($) 40 hp tractor 1 14,000 60 hp tractor 2 18,600 Plow (3 bottom) 1 Disk (10 ft) (Grow All Feed); Herd Size Yr Make OG 82 JD 2040 OG 82 JD 2440 2,300 PPFI 82 1 3,500 EST Corn planter (.4 row) 1 6,900 PPFI 82 Grain drill 1 5,000 PPFI 82 Sprayer 1 1,600 PPFI 82 1 2,200 PPFI 82 Picker sheller (2 row) 1 10,600 OG 82 Gravity box 2 1,600 PPFI Forage harvester - with attachments 1 10,700 PPFI 82 Mower conditioner 1 8,100 OG 82 Rake 1 2,200 SN 80 82 Cultivator (4 row) (9 ft) Source Baler (med. duty) 1 6,800 PPFI Wagon (hay) 3 1,400 EST Forage wagons 3 6,000 T 83 Forage blower 1 3,000 T 83 Pickup 1 6,200 CAP 80 Total Per Cow (3/4 ton) 145,700 3,643 IH 234 139 Table C2, Crop Machinery and Equipment (Grow Forages Only); Herd Size = 40 Cows Equipment Yr Make OG 82 JD 2040 OG 82 JD 2440 2,300 PPFI 82 1 3,500 EST Sprayer 1 1,600 PPFI 82 Grain drill 1 5,000 PPFI 82 Corn planter 1 6,900 PPFI 82 Forage harvester - with attachments 1 10,700 PPFI 82 Mower-conditioner 1 8,100 OG 82 Rake (9 ft) 1 2,200 SN 80 Baler (med. duty) 1 6,800 PPFI 82 Wagons 3 1,400 EST Forage wagons 3 6,000 T 83 Forage blower 1 3,000 T 83 Pickup (3/4 ton) 1 6,200 CAP 80 No. Price e ach($) 40 hp tractor 1 14,000 60 hp tractor 2 18,600 Plow (3 bottom) 1 Disk (8 ft) Total Per Cow (hay) 129,700 3,243 'Source 140 Table C3. Crop Machinery and Equipment = 75 Cows Equipment No. Price each($) (Grow All Feeds); Herd Size Source Yr Make V 40 hp tractor 1 14,000 OG 82 JD 2040 80 hp tractor 2 25,000 OG 82 JD 2440 Plow (3 bottom) 1 2,300 PPFI 82 Disk 1 4,000 EST Sprayer 1 1,600 PPFI 82 Grain drill 1 5,000 PPFI 82 Corn planter (4 row) 1 6,900 PPFI 82 Cultivator (4 row) 1 2,200 PPFI 82 Picker shelled 1 11,400 PPFI 82 Gravity box 3 1,600 PPFI 82 Forage harvester - with attachments 1 10,700 PPFI 82 Mower-conditioner (9 ft) 1 8,100 OG 82 Rake 1 2,200 SN 82 1 6,800 PPFI 82 Wagon (hay) 3 1,400 EST Forage wagons 3 6,000 T 83 Forage blower 1 3,000 T 83 Pickup truck 1 6,200 CAP 80 Baler (10 ft) (9 ft) (med. duty) Total Per Cow 161,400 2,152 JD 1209 141 Table C4. Crop Machinery and Equipment (Grow Forages Only); Herd Size = 7 5 Cows Equipment No. Price .each($) 40 hp tractor 1 14,000 80 hp tractor 2 25,000 Plow (3 bottom) 1 Disk (10 ft) Yr Make OG 82 JD 2040 OG 82 2,300 PPFI 82 1 4,000 EST Sprayer 1 1,600 PPFI 82 Grain drill 1 5,000 PPFI 82 Corn planter 1 6,900 PPFI 82 Forage harvester - with attachments 1 10,700 PPFI 82 Mower-conditioner(9 ft) 1 8,100 OG 82 Rake (9 ft) 1 2,200 SN 82 Baler (med. duty) 1 6,800 PPFI 82 Wagon (hay) 3 1,400 EST Forage wagons 3 6,000 T 83 Forage blower 1 3,000 T 83 Pickup truck 1 6,200 CAP 80 Total Per Cow 143,000 1,907 Source JD 1209 142 Table C5. Crop Machinery and Equipment (Grow All Feeds); Herd Size = 150 Cows Equipment No. Price each($) 40 hp tractor 1 14,000 80 hp tractor 1 110 hp tractor Source Yr Make OG 82 JD 1250 25,000 OG 82 JD 2940 1 34,400 OG 82 JD 4240 Plow (5 bottom) 1 6,700 PPFI 82 Disk (12 ft) 1 5,100 PPFI 82 Sprayer 1 1,600 PPFI 82 Grain drill 1 5,000 PPFI 82 6,900 PPFI 82 2,200 PPFI 82 49,000 PPFI 82 1,600 PPFI 82 1 12,000 PPFI 82 (set) 1 5,000 PPFI 82 Baler (heavy duty) 1 8,500 T 83 Automatic (55 balePTO wagon) 1 11,000 AC 83 Forage wagon 3 6,000 T 83 1 14,000 T 83 Forage blower 1 3,000 T 83 Pickup truck(3/4 ton) 1 6,200 CAP 80 Corn planter (4 row) Cultivator (4 row) Combine (SP) 1 1/2 Gravity box Windrower Tandem rakes Forage harvester duty) Total Per Cow (med. 207,900 1,386 143 Table C6. Crop Machinery and Equipment Size = 150 Cows Equipment (Grow Forages Only); Herd Yr Make OG 82 JD 1250 25,000 OG 82 JD 2940 1 34,400 OG 82 JD 4240 Plow (5 bottom) 1 . 6,700 PPFI 82 Disk 1 5,100 PPFI 82 Sprayer 1 1,600 PPFI 82 Grain drill 1 5,000 PPFI 82 Corn planter 1 6,900 PPFI 82 Windrower 1 12,000 PPFI 82 (set) 1 5,000 PPFI 82 (heavy duty) 1 8,500 T 83 Automatic (55 balePTO wagon) 1 11,000 AC 83 Forage wagon 3 6,000 T 83 Forage harvester (med. duty) 1 14,000 T 83 Forage blower 1 3,000 T 83 Pickup truck (3/4 ton) 1 6,200 CAP 80 No. Price e a c h ($) 40 hp tractor 1 14,000 80 hp tractor 1 110 hp tractor (13 ft) Randem rakes Baler Total Per Cow 176,400 1,176 Source 144 Table C7. Crop Machinery and Equipment (Grow All Feeds); Herd Size = 300 Cows Equipment No. Price e a c h ($) Source Yr Make 60 hp tractor 1 18,600 0G 82 JD 2440 130 hp tractor 1 38,400 OG 82 JD 4440 150 hp tractor 1 46,300 OG 82 JD 4640 Plow 1 9,480 PPFI 82 1 7,560 PPFI 82 Sprayer 1 1,600 PPFI 82 Grain drill 1 5,000 PPFI 82 Planter (.8 row) 1 13,000 Cultivator 1 4,480 PPFI 82 Gravity box 4 1,600 PPFI 82 Combine 1 49,000 PPFI 82 1 19,000 OG 82 Tandem rakes (set 18 ft) 1 5,000 T 83 Baler 1 8,500 T 83 Automatic (104 bale PTO wagon) 1 18,000 AC 83 Forage blower 1 3,000 T 83 Forage wagon 4 6,000 T 83 1 40,000 OG 82 1 6,200 PPFI 82 (7 bottom) Disk harrow Windrower (16 ft) (8 row) (14 ft SP) (heavy duty) Forage harvester (SP) Pickup truck (3/4 ton) Total Per Cow 323,520 1,078 EST JD 2320 NI 767 Uni 145 Table C8. Crop Machinery and Equipment = 300 Cows Equipment No. Price e a c h ($) 60 hp tractor 1 18,600 130 hp tractor 1 110 hp tractor (Grow Forages Only); Herd Size Source Yr Make OG 82 JD 2440 38,400 OG 82 JD 4440 1 34,400 OG 82 JD 4240 Plow (5 bottom) 1 6,700 •PPFI 82 Disk harrow (.13 ft) 1 5,100 PPFI 82 Sprayer 1 1,600 PPFI 82 Grain drill 1 5,000 PPFI 82 Corn planter 1 6,900 PPFI 82 Windrower 1 19,000 OG 82 1 5,000 T 83 1 8,500 T 83 Automatic (104 bale PTO wagon) 1 18,000 AC 83 Forage wagon 4 6,000 T 83 Blower 1 3,000 T 83 Forage harvester 1 40,000 OG 82 Pickup truck 1 6,200 PPFI 82 (14 ft, SP) Tandem rakes Baler (set 18 ft) (heavy duty) Total Per Cow 240,400 801 JD 2320 NI 767 Uni APPENDIX D CROP LABOR ESTIMATES Table D2 through D15 contain estimated hours of labor for corn, corn silage, hay and haylage for various herd sizes specified in the model and corresponding crop acreages. Specific tasks to be performed and the labor requirements to perform them are enumerated based on estimates from Table D1 considering the machinery complements estimated in Table Cl through C8. Some labor requirements were approximated when estimates were unavailable (e.g. transporting and ensiling labor). These estimates were used to derive linear approximations for crop labor based on the number of acres grown and the specific crop in question. They are summarized in Table D16 and can be compared with Telfarm labor requirements in Table D17 and D18. Labor estimates differ most markedly from Telfarm estimates relative to hay and di­ verge substantially as crop acreages increase for all crops. 146 147 Table Dl. Machinery Capacities, Acres/Hour for Selected Farming Operations9 Machine Field 1 efficiency % Width inches Speed mi/hr Acres/ hr Tillage Moldboard Plow: 3 bottom 5 bottom 7 bottom 80 80 80 42 80 112 4.5 4.5 4.5 1.51 2.88 4.03 Tandem Disk Harrow: 8 ft 12 ft 85 85 96 144 4.5 4.5 1.49 2.24 Row Crop Cultivator:4 row,40 in 8 row,30 in 80 80 160 240 3.5 3.5 4.48 6.72 60 55 55 160 180 240 3.5 4.5 4.5 3.36 4.46 5.94 70 70 119 184 4.0 4.0 3.33 5.15 70 65 30 90 3.0 2.5 .63 1.46 Combine:self-propelled 4 row,30 in 6 row,30 in 65 65 120 180 2.5 2.5 1.95 2.93 Mower-conditioner: 9 ft,pull type 12 ft,self-propelled 75 75 108 144 4.5 4.5 3.65 4.86 80 80 84 216 4.5 4.5 3.02 7.78 Baler,bales dropped:7 ft windrow 9 ft windrow 75 75 84 108 3.5 3.5 2.21 2.84 Baler,bale thrower: 7 ft windrow 9 ft windrow 65 65 84 108 3.5 3.5 1.91 2.46 65 65 60 84 108 144 2.0 2.0 2.0 1.09 1.40 1.73 60 55 60 120 2.5 2.5 .90 1.65 65 252 6.5 10.65 Planting Conventional Tillage: 4 row,40 in 6 row,30 in 8 row,30 in Grain Drill: 17 hole,7 in 23 hole,8 in Harvesting Corn picker:1 row,30 in 3 row,30 in Side Delivery Rake: 7 ft 18 ft Forage harvester - Haylage: 7 ft windrow 9 ft windrow 12 ft windrow - Corn Silage 2 row, 30 in 4 row, 30 in Miscellaneous Boom type sprayer: 21 ft aSource: White, 1978. 148 Table D2. Corn Grain Labor: 40 Cows, 42 Acres Corn Field efficiencv Item Calculation Hours 27.8 Plow, 3 bottom 80 42 acres •? 1.51 acres/hr Disk, 8 ft, 2 times 85 (42 acres t 3.67 acres/hr)*2 22.9 Plant, 4 row conventional 60 42 acres r 3.0 acres/hr Spray, 21 ft boom 65 42 acres ? 10.65 acres/hr Cultivate, 4 row 80 42 acres -r 3.36 acres/hr 12.5 Picker, 2 row, 30 in 65 42 acres ? 1.0 acres/hr 42.0 Transport and ensile — 42 acres ? 1.0 acres/hr 42.0 Total hr Hr/acre Table D3. 14.0 3.9 165.1 3.9 Corn Grain Labor: 75 Cows, 79 Acres Corn Item Field efficiency Calculation Hours 36.0 Plow, 4 bottom 80 79 acres ■? 2.19 acres/hr Disk, 10 ft,2 times 85 (79 acres ? 4.59 acres/hr)*2 34.4 Plant, 4 row conventional 60 79 acres * 3.0 acres/hr Spray, 21 ft boom 65 79 acres -r 10.65 acres/hr Cultivate, 4 row 80 79 acres * 3.36 acres/hr 23.5 Picker, 2 row, 30 in 65 79 acres ? 1.0 acres/hr 79.0 Transport and ensile — 79 acres ■? 1.0 acres/hr 79.0 Total hr Hr/acre 26.3 7.4 285.7 3.6 149 Table D4. Corn Grain Labor: 150 Cows, 158 Acres Corn Item Field efficiency Calculation Hours Plow, 5 bottom 80 158 acres Disk, 12 ft 85 (.158 acres ? 5.51 acres/hr)*2 57.4 Plant, 4 row conventional 60 158 acres * 3.0 acres/hr 52.7 Spray, 21 ft boom 65 158 acres Cultivate, 4 row 80 158 acres * 3.36 acres/hr 47.0 Combine 4 row, 30 in 65 158 acres f 1.95 acres/hr 81.0 Transport and ensile — 158 acres * 1.95 acres/hr 81.0 2.88 acres/hr 10.65 acres/hr Total hr Hr/acre Table D5. 54.9 14.8 38.8.8 2.5 C o m Grain Labor: 300 Cows , 315 Acresi Corn Field efficiency Item Hours Calculation 4.03 acres/hr 78.2 7.30 acres/hr)*2 86.3 Plow, 7 bottom 80 315 acres Disk, 16 ft 85 (315 acres Plant, 8 row conventional 60 315 acres - 5.94 acres/hr 53.0 21 ft boom 65 315 acres r 10.65 acres/hr 29.6 Cultivate, 8 row 80 315 acres A • 6.72 acres/hr 46.9 Combine 4 row, 30 in 65 315 acres T 1.95 acres/hr 161.5 315 acres 4b 1.95 acres/hr 161.5 Spray. Transport and ensile a • Total hr Hr/acre 617.0 1.9€ 150 Table D6, Corn Silage Labor: 40 Cows, 24 Acres C o m Silage Item Field efficiency Hours Calculation Plow, 3 bottom 80 24 acres • Disk, 8 ft, 2 times 85 (24 acres <* • Plant, 4 row conventional 60 24 acres * 3.0 acres/hr 8.0 Spray, 21 ft boom 65 24 acres - 10.65 acres/hr 2.3 Cultivate, 4 row 80 24 acres 7.1 Forage harvester, 1 row,30 in 60 24 acres • .59 acres/hr 40.7 24 acres- A .59 acres/hr 40.7 Transport and ensile 1.51 acres/hr 15.9 1.49 acres/hr)*2 32.2 3.36 acres/hr Total hr Hr/acre Table D7. 146.9 6.1 Corn Silage Labor: 75 Cows , 45 Acres Corn Silage Item Field efficiency Calculation Plow, 4 bottom 80 Disk,10 ft, 2 times 85 Plant, 4 row conventional 60 45 acres * 3.0 acres/hr Spray, 21 ft boom 65 45 acres * 10.65 acres/hr Cultivate, 4 row 80 45 acres ■? 3.36 acres/hr 13.4 Forage harvester,2 row, 30 in 60 45 acres t .9 acres/hr 50.0 Transport and ensile,2 men 45 acres Hours 2.19 acres/hr (45 acres * 1.86 acres/hr)*2 (45 acres r .9 acres/hr)*2 men Total hr Hr/acre 20.5 48.4 15.0 4.2 100.0 251.5 5.6 151 Table D8. Corn Silage Labor: 150 Cows, 90 Acres Corn Silage S., V ______________________________________________________ Item Field efficiency Calculation Hours Plow, 5 bottom 80 90 acres Disk, 12 ft, 2 times 85 (90 acres Plant, 4 row conventional 60 90 acres - 3.0 acres/hr Spray, 21 ft boom 65 90 acres Cultivate, 4 row 80 90 acres A • 3.36 acres/hr 26.8 Forage harvester,med. duty 65 90 acres • 1.25 acres/hr 72.0 Transport and ensile,2 men — (90 acres men ♦ 2.88 acres/hr 31.3 5.51 acres/hr)*2 65.3 10.65 acres/hr 1.25 acres/hr)*2 At Total hr Hr/acre Table D9. 30.0 8.5 144.0 449.9 5.0 Corn Silage Labor: 300 Cows, 180 Acres Corn Silage Item _____________________ Field Calculation Hours efficiency_______________________________ 4.03 acres/hr 80 Disk, 16 ft, 2 times 85 Plant, 8 row conventional 60 180 acres - 5.94 acres/hr 30.3 Spray, 21 ft boom 65 180 acres - 10.65 acres/hr 16.9 Cultivate, 8 row 80 180 acres Forage harvester, selfpropelled Transport and ensile,3 men 65 — 180 acres 44.6 Plow, 7 bottom (180 acres r 7.30 acres/hr)*2 a 49.3 6.72 acres/hr 26.8 180 acres * 1.65 acres/hr 109.1 (180 acres t 1.65 acres/hr)* 3 men Total hr Hr/acre 327.3 604.2 3.4 152 Table DIO. Haylage Labor: 75 Cows, 71.1 Acres Haylage Crop, 59.2 Established)a Item Field efficiency (11.9 Acres New Calculations Hours Plow,4 bottom,new crop 80 Disk,10 ft,new crop,2 times 85 Grain drilled, new crop 60 11.9 acres ■? 3.33 acres/hr 3.6 Spray,21 ft boom,weeds,new crop 65 11.9 acres t 10.65 acres/hr 1.1 Spray,21 ft boom,insects, all acreage 65 71.1 acres -r 10.65 acres/hr 6.7 Mower conditioner,9 ft, 1 time, new crop 75 11.9 acres * 3.65 acres/hr 3.3 Mower conditioner,9 ft,3 times,established 75- Rake,18 ft,2 times,new crop 80 Rake,18 ft, 6 times,estab. 80 Forage harvester,9 ft,new crop 65 Forage harvester,9 ft,estab. 3 times 65 Transport and ensile,new crop, 2 men Transport and ensile, estab.,3 times,2 men — — 11.9 acres 2.19 acres/hr 5.4 (11.9 acres ? 4.59 acres/hr)*2 5.2 (59.2 acres *■ 3.65 acres/hr)*3 48.7 11.9 acres ♦ 3.88 acres/hr 3.1 (59.2 acres ? 3.88 acres/hr)*6 91.5 11.9 acres t 1.75 acres/hr (59.2 — 1.75 acres/hr)*3 (11.9 acres * 1.75 acres/hr) *2 (59.2 ■? 1.75 acres/hr) *6 Total hr Hr/acre 6.8 101.5 13.6 203.0 493.5 6.9 aAssumes aflalfa is re-seeded at the end of every 5th year and the new crop is 16.7% the total acres. 153 Haylage Labor: 150 Cows, 142.2 Acres Haylage Crop, 118.5 Acres Established)a Item Field efficiency (23.7 Acres New Hours Calculations 23.7 acres 2.88 acres/hr Plow, 5 bottom,new crop 80 Disk,12 ft, 2 times 85 Grain drill, new crop 60 23.7 acres Spray, 21 ft boom,weeds, new crop 65 23.7 acres •? 10.65 acres/hr Spray,21 ft boom,insects, all hay 65 142.2 acres ■? 10.65 acres/hr Mower conditioner^ ft,new crop 75 23.7 acres * 3.88 acres/hr t CD • to Table Dll. (.23.7 acres * 5.51 acres/hr) *2 8.6 7.2 3.31 acres/hr 2.2 13.4 6.1 Mower conditioner,9 ft,estab • 3 times 75 (118.5 acres t 3.88 acres/hr) *3- Rake,18 ft,2 times,new crop 80 (23.7 acres t 7.78 acres/hr)*2 Rake,18 ft,6 times,estab. 80 (118.5 acres * 7.78 acres/hr) *6 Forage harvester,9 ft,new crop 65 Forage harvester,9 ft,estab. 3 times 23.7 acres r 2.5 acres/hr (118.5 acres ■? 2.5 acres/hr) *3 Transport and ensile,new crop, 3 men — (23.7 acres * 2.5 acres/hr)*3 Transport and ensile,estab. 3 times, 3 men — (118.5 acres ? 2.5 acres/hr) *9 Total hr Hr/acre 91.6 6.1 91.4 9.5 142.2 28.4 426.6 841.5 5.9 aAssumes alfalfa is re-seeded at the end of every 5th year and the new crop is 16.7% of the total acres. 154 Table D12. Haylage Labor: 300 Cows, 284.4 Acres Haylage Crop, 236.9 Established)3 Item Field efficiency (47.5 Acres New Calculations Hours Plow, 7 bottom,new crop 80 47.5 acres t 4.03 acres/hr 11.8 Disk,16 ft new crop,2 times 85 (47.5 acres ? 7.30 acres/hr) *2 13.0 60 Spray,21 ft boom,weeds, new crop 65 Spray,21 ft boom,insects, all acreage 65 284.4 acres t 10.65 acres/hr Windrower,14 ft,self-pro­ pelled, new crop 75 47.5 acres t 5.67 acres/hr Windrower,14 ft,self-pro­ pelled, estab. ,3 times 75 (236.9 acres ? 5.67 acres/hr) *3 125.3 Rake,18 ft,new crop,2 times 80 (47.5 acres ? 7.78 acres/hr) *2 Rake,18 ft,estab.,6 times 80 (236.9 acres ? 7.78 acres/hr) *6 182.7 Forage harvester,14 ft,selfpropelled, new crop 65 Forage harvester,14 ft,selfpropelled, estab .,3 times 65 Transport and ensile,new crop, 3 men Transport and ensile,estab. 3 times, 3 men — — 47.5 acres t 3.3 acres/hr 14.4 Grain drill,new crop 47.5 acres ? 10.65 acres/hr 47.5 acres *■ 3.5 acres/hr (236.9 acres * 3.5 acres/hr) *3 (47.5 acres * 3.5 acres/hr) *3 (236.9 acres r 3.5 acres/hr) *9 Total hr Hr/acre 4.5 26.7 8.4 12.2 13.6 203.0 40.7 609.2 1265.5 4.4 aAssumes alfalfa is re-seeded at the end of every 5th year and the new crop is 16.7% of the total acres. 155 Table D13. Hay Labor: 40 Cows, 63 Acres Hay (10-5 Acres New Crop, 52.5 Established)3 Item Field efficiency Hours Calculations Plow, 3 bottom,new crop 80 Disk,8 ft, 2 times,new crop 85 Grain drill,new crop 60 10.5 acres • 3.33 acres/hr 3.2 Spray,21 ft boom,weeds,new crop 65 10.5 acres 1.0 Spray,21 ft boom,insects, all acreage 65 63 acres «■ 10.65 acres/hr 5.9 Mower conditioner^ ft,l time,new crop 75 10.5 acres «••» 3.65 acres/hr 2.9 Mower conditioner,3 times estab. 75 (52.5 acres ? 3.65 acres/hr) *3 Rake,9 ft,2 times,new crop 80 (10.5 acres *2 Rake,9 ft, 6 times, estab. 80 (52.5 acres *r 3.88 acres/hr) *6 Baler thrower,1 time, new crop 65 10.5 acres • 1.91 acres/hr Baler thrower,3 times,new crop 65 (52.5 acres * 1.91 acres/hr) *3 82.5 Transported and stored,1 time,new crop,3 men — (10.5 acres *3 16.5 Transported and stored,3 times,estab.,3 men — (52.5 acres r 1.91 acres/hr) *9 10.5 acres ■ 1.51 acres/hr (10.5 acres 3.67 acres/hr ) * 2 10.65 acres/hr 6.9 5.8 43.1 3.88 acres/hr) 81.2 5.5 1.91 acres/hr) Total hr Hr/acre 247.4 507.3 8.1 ^Assumes alfalfa is re-seeded at the end of every 5th year and the new crop is 16.7% of the total acres. 156 Table D14. Hay Labor: 150 Cows, 95 Acres Hay (.15.8 Acres New Crop, 79.2 Acres Established)a Item Field efficiency Hours Calculations Plow,5 bottom,new crop 80 15.8 acres * 2.88 acres/hr 5.5 Disk,12 ft, 2 times 85 (15.8 acres * 5.51 acres/hr) *2 5.7 Grain drill,new crop 60 15.8 acres t- 3.33 acres/hr 4.7 Spray,21 ft boom,weeds, new crop 65 15.8 acres i.5 Spray, 21 ft boom,insects all hay 65 95 acres •? 10.65 acres/hr Mower conditioner,9 ft,new crop 75 15.8 acres Mower conditioner,9 ft, estab.,3 times 75 (79.2 acres *3 Rake,18 ft,2 times, new crop 80 (15.8 acres r 7.78 acres/hr) *2 4.1 Rake,18 ft,6 times, estab. 80 (79.2 acres r 7.78 acres/hr) *6 61.1 Baler,bales dropped, 1 time,new crop 75 15.8 acres 2.21 acres/hr Baler,bales dropped, 3 times, estab. (79.2 acres *3 2.21 acres/hr) 75 (15.8 acres *3 2.21 acres/hr) (79.2 acres *9 2.21 acres/hr) Transport and store,1 time new crop, 3 men Transport and store,3 times estab., 3 men — a 10.65 acres/hr • 3.88 acres/hr • 3.88 acres/hr) 8.9 4.1 61.2 7.1 107.5 21.4 322.5 Total hr Hr/acre 615.3 6.5 aAssumes alfalfa is re-seeded at the end of every 5th year and the new crop is 16.7% of the total acres. 157 Table D15. Hay Labor: 300 Cows, 190 Acres Hay C31.6 Acres New Crop, 158.4 Established)a Item Field efficiency Hours Calculations Plow,7 bottom,new crop 80 31.6 acres ■? 4.03 acres/hr 7.8 Disk,16 ft, new crop,2 times 85 (31.6 acres ? 7.30 acres/hr) *2 8.7 Grain drill, new crop 60 31.6 acres Spray,21 ft boom,weeds, new crop 65 31.6 acres t 10.65 acres/hr Spray,21 ft boom,insects, all acreage 65 190 acres <• 10.65 acres/hr 17.8 Windrower,14 ft,self-pro­ pelled,! time,new crop 75 31.6 acres * 5.67 acres/hr 5.6 Windrower,14 ft,self-pro­ pelled, 3 times,estab. 75 (158.4 acres * 5.67 acres/hr) *3 83.3 Rake,18 ft,2 times,new crop 80 (31.6 acres t 7.78 acres/hr) *2 81.2 Rake,18 ft,6 times,estab. 80 (158.4 acres * 7.78 acres/hr) 122.2 *6 Baler,bales dropped,9 ft windrow,1 time,new crop 65 Baler,bales dropped,9 ft windrow,3 times,new crop 65 (158.4 acres *■ 2.84 acres/hr) 167.3 *3 Transport and store,l time, new crop, 2 men — (31.6 acres * 2.84 acres/hr) *3 Transport and store, 3 times — estab.,2 men 3.33 acres/hr 31.6 acres t 2.84 acres/hr 9.5 3.0 11.1 33.3 (158.4 acres ? 2.84 acres/hr) 502.0 *9 Total hr Hr/acre 1053.3 5.5 aAssumes alfalfa is re-seeded at the end of every 5th year and that the new crop is 16.7% of the total acres. 158 Table D16. Summary of Crop Labor Requirements by Acres and Equations to Predict Crop Labor Requirements3 Acres Hours/Acre^ Haylage 71 142 284 8.6 7.4 5.5 Hay 63 95 190 10.1 8.1 6.9 42 79 158 315 4.9 4.5 3.1 2.5 24 45 90 180 7.6 7.0 6.3 4.3 Crop Corn Grain Corn Silage Equation0 Y = 4.6 + 284/X Y = 5.4 + 250/X Y = 2.2 + 125/X Y = 3.7 + 90/X aBased on Tables D2 through D15. ^Estimated by multiplying hours of labor/acre estimated in Tables D2 through D15 by 1.25 to allow for breaks, breakdown, etc. CY = hr of labor acre; X = number of acres Table D17. Telfarm Equation Estimating Enterprise Labor Requirements3 Crop Equation Haylage Y = 8.47 + 47.88/X Hay Y = 11.29 + 47.89/X Corn Grain Y = 5.39 + 57.41/X Corn Silage Y = 7.39 + 57.41/X aSource: Schwab et al., 1983. 159 Table D18. Crop Calculated and Predicted Labor Requirements by Acres Acres Calculated hr (Tables D2-D15) Predicted (Table D16) Predicted by Telfarm (Table D17) Haylage 71 142 284 8.6 7.4 5.5 8.6 6.6 5.6 9.1 8.8 8.6 Hay 63 95 190 10.1 8.1 6.9 9.4 8.0 6.7 12.0 11.8 11.5 Corn Grain 42 79 158 315 4.9 4.5 3.1 2.5 5.2 3.8 3.0 2.6 6.8 6.1 5.8 5.6 Corn Silage 24 45 90 180 7.6 7.0 6.3 4.3 7.5 5.7 4.7 4.2 9.8 8.7 8.0 7.7 APPENDIX E DAIRY BUILDINGS AND FACILITIES ESTIMATES Buildings and facilities and equipment were assembled for herd sizes of 40, 75, 150, 300 and 500 cow herds. The principle source of informa­ tion used to assemble building costs is: Bath et al., Appendix Table V-J. Cost estimates published there are outdated and therefore inflated by a factor of 1.44 for buildings 1.65 for other equipment (Bureau of Industrial Economics, 1983) and (Economic Research Service, 1983). Sources of prices used to estimate costs in Tables El through E8 are listed below: Abbreviation Source H Bath et al., 1978,Appendix Table V-J CD Central Dairy Supply, 2810 Canal St., Lansing, Michigan - via phoen conversa­ tion, 1982 PPFI Crop Reporting Board, 1982a,b CAP Shaudys, 1980 OG National Farm Power and Equipment Dealers Association, 1982 AE Prices obtained from exhibitors at Ag Expo, East Lansing, Michigan via conversation, 1983 D DeLaval, Alfa-Laval, Inc., 1983 via mail correspndence 160 161 Table El. Dairy Buildings and Facilities, Equipment; Herd Size = 40 Cows, Confinement-Stall B a m Item Buildings and facilities; Confined-stall barn (.including gutter and other cement work, ventillation, insulation, milkroom, and hospital area Investment cost ($) Source Years life Inflation factor 71,350 1.44 58,450 H 20 Youngstock housing(Virginia style barn,hutches for newborn calves 6,000 B 20 Manure storage,6 months 6,900 H 20 1.44 Equipment: Pipeline milking system (including bulk tank,sinks etc.) 66,250 20,500 CD 8 --- Gutter cleaner + manure stacker 11,150 H 8 1.65 Manure spreader (150 bu) 2,500 CAP 8 --- Front end loader 3,000 PPFI 8 --- OG 8 --- Tractor, 40 hp tractor 14,000 Pickup truck 6,200 PPFI 8 --- Roller mill 1,300 AE 8 --- Feed cart (59 bu Uebler cart) 4,400 AE 8 --- Miscellaneous equipment3 3,200 8 Miscellaneous is estimated as 10% of the total equipment cost. 162 Table E2. Dairy Buildings and Facilities, Equipment; Herd Size = 75 Cows Free-stall Barn Item Investment cost (.$) Source Years life Inflation factor 119,800 94,400 H 20 1.44 Youngstock housing(Virginia style barn,hutches for newborn calves) 15,000 B 20 ---- Manure storage(earthen pit, 6 months) 10,400 H 20 1.44 101,100 23,700 D 8 ---- 13,000 CE 8 Manure agitator pump(trailer) 5,000 PS 8 Manure spreader 6,800 OG 8 Front end loader 2,900 PPFI 8 Buildings and facilities: Free-stall barn(including barn structure and con­ crete ,free-stall,water, wiring and plumbing,milkroom and parlor and hospital area Equipment: Herringbone parlor milking system(double-4,no mechani­ zation,std. stalls)bulk tank and cooling Tractor (40 hp) 14,000 OG 8 Tractor (75 hp) 19,000 OG 8 Pickup truck 6,200 PPFI 8 Roller mill 1,300 AE 8 Feeding c art(50 bu,Uebler cart) 4,400 AE 8 Miscellaneous 4,800 — 8 163 Table E3, Dairy Buildings and Facilities, Equipment; Herd Size = 150 Cows, Free-Stall Barn Item Investment cost ($) Source Years life Inflation factor 202,850 154,350 H 20 Youngstock housing(Virginia style barn,hutches for new­ born calves 30,000 B 20 Manure storage (earthen pit, 6 months) 18,500 H 20 Equipment: Herringbone parlor milking system(double-4,including HD stalls,no mechanization) 136,950 26,300 D 8 --- 18,650 H 8 1.65 PS 8 --- H 8 1.44 PPFI rt O --- Buildings and Facilities: Free-stall b a m (including barn structure and con­ crete, free stalls,water wiring and plumbing,milkroom and parlor and hospital area) Bulk tank and cooling Manure agitator pump(trailer) Manure spreader, liquid Front end loader 5,000 10,100 2,900 1.44 1.44 Tractor (40 hp) 14,000 OG 8 --- Tractor (90 hp) 30,000 OG 8 --- Pickup truck 6,200 PPFI 8 --- Roller mill 1,300 AE 8 --- Mixer wagon 16,000 H 8 1.44 - 8 --- Miscellaneous 6,500 164 Table E4. Dairy Buildings and Facilities, Equipment; Herd Size = 300 Cows, Free-Stall Barn Item Investment cost ($) Buildings and facilities: Free-stall barn(including barn structure and con­ crete, free stalls,water wiring and plumbing,milkroom and parlor and hospital area) Youngstock housing(Virginia style barn,hutches for newborn calves) Manure storage 6 months) Bulk tank and cooling Manure agitator pump(trailer) Manure spreader, liquid Front end loader (40 hp) Tractor (90 hp) Years life Inflation factor 368,700 274,000 H 20 60,000 B 20 34,700 H 20 1.44 205,450 60,250 D 8 --- 30,000 H 8 1.65 PS 8 --- H 8 1.44 PPFI 8 --- 28,000 OG 8 --- 30,000 OG 8 --- 1.44 (earthen pit, Equipment: Herringbone parlor milking system(double-8, with detachers,power gates) 2 tractors Source 5,000 12,000 2,900 Pickup truck 6,200 PPFI 8 --- Roller mill 1,300 AE 8 --- Mixer wagon 20,000 H 8 1.44 - 8 --- Miscellaneous 9,800 165 Table E5. Dairy Buildings and Facilities, Equipment; Herd Size = 500 Cows, Free-Stall Barn Item Investment cost (.$) Source Years life Inflation factor Buildings and facilities: Free-stall barn(including barn structure and concrete free stalls,water,wiring and plumbing,milkroom and parlor and hospital area) 590,300 434,000 H 20 1.44 Youngstock housing(Virginia style barn,hutches for newborn calvesi 100,000 B 20 1.44 56,300 H 20 1.44 221,400 60,250 D 8 --- 45,200 H 8 1.65 - 8 --- 12,000 - 8 --- 2,900 - 8 --- 28,000 OG 8 --- 30,000 OG 8 --- Manure storage(earthen pit, 6 months) Equipment: Herringbone parlor milking system(double-8,with detachers,power gate) Bulk tank and cooling Manure agitator pump(trailer) Manure spreader, liquid Front end loader 2 tractors Tractor (.40 hp) (90 hp) 5,000 Pickup truck 6,200 PPFI 8 --- Roller mill 1,300 AE 8 --- Mixer wagon 20,000 H 8 1.44 Miscellaneous 10,550 - 8 --- APPENDIX F THE DAIRY INVESTMENT MODEL THE DAIRY INVESTMENT MODEL FI. Orientation This contains the template of the investment program for use with the MICROSOFT MULTIPLAN elec­ tronic worksheet and was developed to evaluate the three strategies described in this thesis. The program name is DRYINV.MP and can be accessed by this name. A brief description of each component of the model and the formulas comprising each component are presented in the following pages. The user should be familiar with MULTIPLAN to operate the program. All cells containing text and formulas are locked except those containing the values for rows 13:17 column 3. These are values for the following variables: Location Description Acronym Value R13C3 soil management group SMG enter either R14C3 milk production level of the herd(thousand lb) MP enter either 19 R15C3 price of land ($/acre) PLND enter price R16C3 price of milk ($/cwt) PMLK enter price R17C3 price of shelled corn($/bu) PSCORN enter price Values of other variables are default values; they can be changed by simply unlocking the cell containing the value to change, and then making the change. Variables described as endogenous var­ iables should be changed with caution as their values are estimated by formulas. Section IA is typically the only section where users will enter values. Every time the value of a cell (e.g. variable) is changed the entire worksheet is re-estimated based on the new value entered. It is a good idea to define: Options recalc as "no" (see users manual for Microsoft:Multiplan) which will allow the user to change all the values he/she desires without having to wait for the program to re-estimate for each individual change. When all values have been changed to those desired, simply press the exclamation character (!) and the worksheet will be re-estimated based on all the new values entered. F2. INTRODUCTION DAIRY INVESTMENT ANALYSIS PROGRAM This program is designed to allow the user to investigate the profitability of three alternative strategies of securing feeds on dairy farms in Southern Michigan and other similar areas. The strate­ gies include: 1) growing forages and grain (GFG); 2) growing forages (GF) or 3) purchasing all feed (PR). The strategies are examined across herd sizes of 40, 75, 150 and 300 cows for farms GFG and GF and 40, 75, 150, 300 and 500 cows for farms PR. The model assumes: 1) farms GFG or GF just have enough land to grow the appropriate amounts of alfalfa and c o m silage; 2) farms GFG have additional land to grow corn needed; 3) 60% of the forage dry matter is alfalfa and 40% is corn silage, across all feeding strategies. Component I (A-D) sets the stage in terms of economic conditions and prices and production factors. This includes selecting the soil management group (2.5, 3 or 4) which selects which crop yields/acre to use to estimate the amount of land needed and the crop budget expenses for farms which GF or GFG. The level of milk production: (13,15,17 or 19)000 lb specified, selects which ration (quantities of each feed needed/cow and replacement/year) to use to estimate quantities of feeds n e e d e d / h e r d / y e a r . Components II through IX estimate the various inputs and expenses incurred by herd sizes, noting differences across strategies where they exist. Component X estimates incomes across herd sizes and possible adjustments to income taking into account: 1) the value of manure produced; 2) soybean meal savings on farms GFG or GF which grow haylage and 3) savings in the annual use charge on machinery which is common to the dairy and cropping enter­ prises for farms GFG or GF. Components XI and XII estimate the total feed cost and total annual costs across herd sizes by 168 The user specifies the economic conditions and prices and production factors within the bounds of the program by setting the values of the exogenous variables in component IA. This allows the user to examine profitability across all three strategies and each herd size within each strategy for any given set of conditions. feeding strategy b y summing up r e l e v a n t c o m p o n e n t costs in III thro u g h IX. C omponent XIII (A-C) es t i mates p r o f i t (in terms o f total profit/farm) b y summ i n g rel e v a n t incomes - total costs, for ea c h he r d size w i t h i n ea c h strategy. Total i n vestments are e s t i m a t e d b y summing the appropriate investment c o m p o n e n t costs w i t h i n ea c h herd size and strategy. C omponent XIV estimates the intercepts, slopes a n d c o e f f icients o f d e t e r m i n a t i o n r e g r e s s i n g profit, number o f cows and number of laborers o n total inves t m e n t a c ross he r d sizes for ea c h strategy. Component XV summarizes profits, rates o f r e t u r n o n investment, numbers o f laborers and n umber of cows for levels of invest m e n t of: $.5, 1.0, 1.5, 2.0 a nd 2.5 m i l l i o n for ea c h strategy. This m o d e l is useful in p r o j e c t i n g l o n g - t e r m p r o f i t expectations. It does not c onsider w i t h i n year or across years p r i c e or y i e l d variations, income taxes, m e t h o d or detail o f f i n a ncing o r y e a r l y cash flows necessary to keep the b u s i n e s s solvent. Real i n terest rates are u s e d a nd the m o d e l assumes that incomes and expenses inflate at the same rate. P rofit is d e fined as total income-total expense. The m o d e l charges in t e r e s t agai n s t a ll capital investments. All labor (including that w h i c h m a y b e family or operator/owner) is c o n s i d e r e d as an expense. Since returns to capital a n d l abor are a l r e a d y a c c o u n t e d for in expenses, p r o f i t is e s s e n ­ tially m anagement income. F3. OUTLINE OF THE INVESTMENT MODEL I. IA. INPUTS: The value of the variables described here are used to estimate the costs and returns and total investment budgeted in sections II-XIII. The user can specify values for the following exogenous (EX) variables: Variable Value t Variable Name __________________________________________________ (acronym)_____________ (default)____ Soil management group (2.5,3 or 4) Milk production (thousand lb) (13,15,17 or 19) Price of land ($/acre) Price of milk ($/cwt) Purchase price of shelled corn($/bu) Interest rate (decimal) Property tax charge(decimal) Property insurance charge(decimal) Land value growth rate (decimal) Price of nitrogen ($/lb) Price of phosphorus ($/lb) Price of potassium ($/lb) SMG MP PLND PMLK PSCORN 3 15 1100 12 2.70 INTRT PTXRT INSRT LNDGRWTHRT .04 .02 .01 .01 PN PP PK .16 .20 .12 Price of dicalcium phosphate($/lb) Price of limestone ($/lb) Price of salt ($/lb) PDCL PLMSTN PSLT Price of labor ($/hr) Price of fuel ($/gal) PLBR PFL .19 .05 .07 6.00 1.10 Values of the following exogenous variables should not be changed: Herd Herd Herd Herd Herd size size size size size Investment Investment Investment Investment Investment 1 2 3 4 5 (# (# (# (# (# size size size size size cows) cows) cows) cows) cows) 1 2 3 4 5 ($) ($) ($) (?) (?) HS2 HSZ HSZ HSZ HSZ 1 2 3 4 5 INV INV INV INV INV 1 2 3 4 5 40 75 150 300 500 500,000 1,000,000 1,500,000 2,000,000 2,500,000 Values of the following endogenous (EN) variables are estimated by formulas: Variable Price Price Price Price Price of of of of of Variable Name (acronym) milking cows ($/cow) cull cows ($/cwt) cull heifers ($/cwt) heifers ($/heifer) deacon calves($/cwt) Contingent upon PCWS PCLLCW PCLLHFR PHFRS PDCNCLVS M P ,PMLK PMLK PCLLCW M P ,PMLK PCLLCWS Price of alfalfa hay ($/ton) Price of corn silage($/ton) Price of soybean meal ($/lb) PALFHY PCSLG PSYML PSCORN PSCORN,PP,PK PALFHY Capital charge for machinery(decimal) Capital charge for buildings and facilities (decimal) CPTMCH INTRT CPTBLDG INTRT IB:CROP BUDGETS: Estimates costs/acre for corn, corn silage, alfalfa hay, alfalfa haylage are based on crop yields/acre which are determined based on the soil management group specified in IA. These yields by management group are contained in ID. IC:RATIONS: This is a table containing the amount of shelled corn (bu), corn silage (tons), alfalfa hay (tons), soybean meal (lb), dicalcium phosphate (lb), salt (lb) and limestone (lb) needed/cow and replacement for levels of production of 13, 15, 17 or 19,000 lb of milk and considers amounts of feeds wasted. ID:CROP YIELDS: This is a table containing the yields/acre of: corn, alfalfa haylage for land in soil management groups 2.5, 3 or 4. II. corn silage, alfalfa hay and F E E D QUANTITIES: This co m p o n e n t e s t i mates the total amou n t o f feed n e e d e d for he r d sizes o f This is e s t i m a t e d using the amounts of feed n eeded/c o w a nd r e p l a c e m e n t a c c o r d i n g to level o f m i l k p r o d u c e d (IC) and the number of cows. 40, 75, 150, 300 and 500 cows a n d includes amou n t s n e e d e d b y replacements. III. FEED STORAGE FACILITIES: Estimates the investments in feed storage facilities for corn, corn silage, alfalfa hay and haylage and the annual costs associated with these facilities for each herd size within each strategy. IV. PURCHASED FEED: Estima t e s the v a l u e of p u r c h a s e d feeds for ea c h he r d size w i t h i n each category. CROPLAND: Estimates the total acres of crops needed to supply feed needs for each herd size for the strategy of GFG and GF. The total investment in land for crop production and annualized costs/acre for land are estimated. Annual costs include an interest charge and considers the rate of growth of land values. V. VI. CROP MACHINERY: Estimates the total i n v e s t m e n t a n d a n n u a l i z e d costs for cr o p m a c h i n e r y for ea c h herd size for farms G F G o r GF. VII. CROP EXPENSES: A) Estimates the annual crop e x penses for ea c h h e r d size for the G F G and GF. Estimated b y m u l t i p l y i n g the n u m b e r o f acres of ea c h crop b y the b u d g e t e d ses/acre from IB. B) Labor re q u i r e d for each c r o p is e s t i m a t e d b a s e d o n t he n u m b e r o f C) T h e cost of labor is esti m a t e d b y m u l t i p l y i n g n u m b e r of h ours o f labor b y th e p r i c e strategies crop expen­ a c r e s grown. paid/hr. VIII. DAIRY FACILITIES: Es t i mates the investments and a n n u a l i z e d costs o f i n v estments in bu i l d i n g s and facilities, equipment an d land for facilities for each he r d size w i t h i n each strategy. IX. LIVESTOCK EXPENSES: A) Estimates the l i v e stock care e xpenses (building repairs, e q u i p m e n t repairs, livestock supplies, b r e e d i n g fees, v et and medicine, fuel, insurance, utilities, m a r k e t i n g and o ther cash expenses) ass o c i a t e d w i t h the d airy for each h e r d size w i t h i n ea c h strategy. B) E s ­ timates the labor requirements a n d c osts c o n s i d e r i n g the e f fect of h e r d size a nd t e c h n o l o g y o n hours of labor/cow. C) Estimates the investment in d a i r y cows a n d the a n n u a l i z e d charge o f capital in­ vested in dairy cows c onsid e r i n g cows as assets w i t h an infinite life. X. I N C O M E : A) Estimates income from the sale o f milk, d e a c o n calves, cull cows, cull heifers, a nd excess replacement heifers for ea c h he r d size w i t h i n e a c h strategy. B) T he v a l u e o f m a n u r e as a savings in fertilizer cost is e s t i m a t e d for the s trategies o f G F G a n d GF. The savings in soybean meal costs due to h i gher q u a l i t y forages is e s t i m a t e d for the strategies of G FG a nd GF. C) E s t i mates the investment savings in m a c h i n e r y due to the c o m p l e m e n t a r i t y o f some o f the crop m a c h i n e r y a nd d a i r y equipment. The savings in a n n u a l i z e d costs o f this m a c h i n e r y is estimated. XI. TOTAL F E E D COST: Estimates total feed costs c o n s i d e r i n g p u r c h a s e d feed c osts (IV) a n d a n nual feed storage costs (III) for e a c h h e r d size w i t h i n ea c h strategy. Soyb e a n m e a l savings (X) a nd annu a l crop expenses and labor (VII), land (V) a n d m a c h i n e r y (VI) are c o n s i d e r e d for G F G and GF. Savings in annualized crop m a c h i n e r y ex p e n s e s (X) are a c c o u n t e d for. I n terest is char g e d a g a i n s t p u r c h a s e d feed and crop expenses. XII. TOTAL ANNUAL COST: Estimates total annual expenses for each herd size within each strategy considering total feed cost (XI), and all livestock ejqpenses including livestock and expenses, livestock labor, annual use cost of capital invested in livestock (IX). It also accounts for annualized costs attributed to dairy buildings and facilities, equipment and land for dairy facili­ ties (VIII). XIII. PROFIT: 1) Estimates total profit for each herd size within each strategy. Profit is esti­ mated considering: Income (X) total annual costs (XII) and the savings in fertilizer expense including interest (X) for farms GF and GFG. Farms PR are assumed to recover 25% of the value of manure pro­ duced, by selling it. 2) Estimates total investments for each herd size within each strategy con­ sidering investments in: feed storage facilities (III), dairy buildings and facilities (VIII), land for dairy facilities (VIII), dairy equipment (VIII) and livestock (VIII). For farms GFG and GF in­ vestments in: crop land (V), crop machinery (VI), savings in investments in machinery due to the com­ plementarity of the cropping and dairy enterprises (X) are accounted for. 3) Estimates the rate of return on investment (RROI). 4) Estimates the number of laborers and 5) Estimates the adjusted cost/cwt of milk produced. 6) Calculates the linear regression estimate of profit based on the total investment, for each herd size within each strategy. This value can be compared to the profit esti­ mated above to examine how well the regression estimate tracks the budgeted value of profit. XIV. REGRESSION: Estimates the intercepts, slopes and coefficients of determination by regressing profit, number of cows and number of laborers on total investment across herd sizes for each strategy as summarized in XIII. XV. SUMMARY. Summarizes in tabular form the profit, rate of return on investment (RROI), number of cows and numbers of laborers for each strategy, considering levelsof investment of: $.5, 1.0, 2.0, and 2.5 million. The slopes (b), intercepts (a) and coefficients of determination (R2) for the re­ gression estimating profit/dollar invested are listed for each strategy. The footnotes contain the maximum numbers of dollars actually budgeted in the analysis. Investment sizes greater than these are extrapolations. 1 1 2 2 3 4 DAIRY INVESTMENT ANALYSIS PROGRAM 6 3 BY a 7 9 J. HLUBIK VALUE 0 .1 2 1 0.074 0.16 0 .2 0 0 .1 2 VARIABLE NAME VALUE INV1 INV2 INV3 INV4 INV5 5 0 0 0 0 0 .0 0 1 0 0 0 0 0 0 .0 0 1 5 0 0 0 0 0 .0 0 2 0 0 0 0 0 0 .0 0 2 5 0 0 0 0 0 .0 0 40 75 150 3 00 500 25.00 175 3 4 5 6 7 IA INPUTS: SET PRODUCTION FACTORS AND ECONOMIC CONDITIONS AND PRICES TO PROPOSED VALUES e a VARIABLE VARIABLE 10 VARIABLE VALUE NAME VALUE NAME n NAME i1£ o 75.00 CPTNCH SMC PALFHY 3 13 CPTBLDG PCSLG MP 18.31 14 15 PLND PSYML 0 .1 2 1100 15 PN 16 PMLK 1 2 .0 0 PLMSTN 0.05 PP PDCL PSCORN 2.70 0.19 17 18 PK PSLT 0.07 INTRT 0.040 19 0 .0 2 0 PCVS 20 PTXRT HSZ1 1088.35 HSZ2 1NSRT 0 .0 1 0 PCLLCW 21 39.47 51-46 PCLLHFR 22 LNDGRVfTHRT 0 .0 1 0 HSZ3 PFL 1 .1 0 PHFRS 960.85 IISZ4 23 65.06 6 .0 0 FDCNCLVS PLBR HSZ5 24 CLLS 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 40 49 50 51 52 53 54 IB CHOP BUDGETS: — SDS VS INSCT N P K LMSTN UTLTS TRCK FL RPHS OTHR TTL IC RATIONS: — MILKPHOD 13 15 17 19 BSCORN 18.08 BCSLC 18.34 1 1 .2 0 2 .0 0 1 1 .2 0 2 .0 0 21.33 23.77 13.31 1 0 .6 8 9 .0 0 4.75 2.56 11.03 12.43 1 3 -6 0 0 .0 0 1 5 .8 6 4.54 5.19 14.92 12.57 18.20 0 .0 0 BSCORNT 116.65 BCSLGT 139.92 NO SCORN 87.0 1 2 3 4 BALFHY 5.00 1.75 5.00 BALFHYLG 5 .0 0 1.75 0 .0 0 5 .0 0 0 .0 0 8.56 21.60 11.80 9-32 23.70 12.96 0 .0 0 5 .8 8 0 .0 0 2 0 .5 8 3.56 21.89 24.63 9-40 3 .0 0 7.96 BALFHYT 97.53 BALFHYLGT 110.80 CSLC ALFUY 6.5 10.1 SYML 535.0 1 1 0 .0 9-6 6 .2 1 0 1 1 .0 134.0 157.0 8 .9 5-8 5.6 2 0 2 0 .0 8.3 1529-0 SLT 95.0 95.0 95.0 95.0 DCL 1 0 0 .0 1 0 0 .0 1 0 0 .0 1 0 0 .0 6 1 2 4 5 3 55 ID CROP YIELDS: YCSLG SMCRNO YSCORN 56 — 1 114.0 15-5 57 1 2 0 .0 1 6 .8 58 2.5 105.0 3 15-3 59 8 6 .0 60 4 13.2 61 6 2 -----------------------------------------63 7 YALFHYLC 8.7 9.0 7.9 6.9 YALFHY 5.0 4.6 4.0 3-5 --------------------------------- 64 II FEED QUANTITIES : 65 — HERD SIZE DO 40 67 75 150 OtlilWITY VUAniiJ1 68 QSCORN 4400 8250 16500 69 QCSLG 720 1440 70 384 QALFHYC F 248 186 372 71 QALFHYIGGF 0 485.46 72 970.92 248 QALFHYPR 465 930 73 151650 40440 QSYHL 75825 74 4000 7500 15000 QDCL 75 3800 14250 76 QSLT 7125 0 0 QLHSTN 0 77 78 7 9 -------------------------------80 -------------------------------81 III FEED STORAGE FACILITIES: 82 -HERD SIZE 40 150 75 STOSCOHN STOCSLO STOALFHYGF STOALFHYPR STOALFHYLG STOTINVGF STOANNGF ST0T1NVPR STOTANNPR 300 500 33000 2880 744 1941.84 1860 303300 55000 4800 0 0 3100 28500 505500 50000 47500 0 0 300 500 104960.00 30000 2 1 9 0 5 -6 0 1 0 8 5 0 .0 0 18983-50 26420.00 8137.50 26425-00 40280.00 16275-00 41308.00 68000.00 6200.00 1 1 6 2 5 .0 0 2 3 2 5 0 .0 0 46500.00 0 .0 0 24268.05 35618.11 5 8 3 1 8 .2 2 42083.60 3727.84 37433-60 3315-93 77809.05 6892.46 57028.50 5051.6 8 118598.11 10505.63 89955.00 7968.37 200176.22 17731.96 13801.75 21579.58 40 HERD SIZE 75 150 300 5 00 5681.05 16681.05 42310.76 10651.97 31276.97 79332.67 21303.93 62553-93 158665-34 42607.86 125107.86 317330.69 71013.11 208513.11 528884.48 9328.00 6 1 1 5 2 .0 0 3 2 5 5 0 .0 0 1 5 5 8 0 6 .0 0 77500.00 2 4 3 6 1 2 .0 0 . IV PURCHASED FEED: — PRFDGFG PRFDGF PRFDPh 1 2 4 3 6 5 7 V CHOP LAND; HERD SIZE 40 75 150 300 ASCOKtl ACSLG AALFIU 41.90 25.10 62.00 78.57 47.06 107-95 157.14 94.12 215.90 431.80 ACM AGPCT 91.45 140.03 162.76 253.40 325.52 506.80 651.04 1013.59 154028.15 7701.41 100598.24 5029.91 278737.72 13936.89 179035.92 IKDIHVCKG LNDAUNGPC LMD1HVGP LUDANRGP 8 9 5 1 .8 0 314.29 188.24 557475.44 1114950.87 55747.54 27873.77 358071.84 716143.69 35807.18 17903.59 VI CHOP BACHINKHV; HERD SIZE 75 150 300 323400.00 18220.79 229800.00 31343.77 198300.00 25262.60 40 HEKD SIZE 75 ISO 300 9558.23 14446.53 17914.74 27080.32 35829.49 54160.64 71658.98 108321.29 LBBSCOR* LBRCSLC LBBALPIII LBHALPHIUS 217.19 182.86 584-80 0 .0 0 297.86 264.12 366.49 367.14 470.71 438.24 622.98 645.22 816.43 786.47 1135.96 1201.39 LBRTCP IBRTCPG 767.66 984.85 997.75 1295.61 1706.44 2177.16 3123.82 3940.25 4605.98 5909.12 5986.51 7773-65 10238.64 13062.93 18-/42.91 23641.49 40 HCHCRPINVGPC 145720.00 MCllCltPAHRGFG 19875-61 MCHCRP1RVCP 129720.00 HCHCRPANNGK 16525.79 161400.00 22014.29 143025.00 44110.43 240300.00 'sj 30613.23 VII CHOP BXPERSESi CHPBXPCF CRPEXPUFC LBRC3TUP LBBCSrCKC VIII UAIBt FACILITIES: 40 DBLDCINV UbLDGANH DLNUINV ULMUANN liRQINV deqann HERD SIZE 75 150 300 500 368700.00 32660:09 1 01100.00 202800.00 17964.38 8250 412.5 136950.00 14092.92 19090.26 590500.00 52307-52 27500 1375 221500.00 30876.19 71360.00 6321.19 119775.00 2200 110 6 6 2 4 0 .0 0 3575 178.75 9253.58 10609.88 16500 825 205500.00 28645.85 170 171 IX LIVESTOCK EXPENSES: 172 HERD SIZE 173 40 75 174 175 176 15712.00 29460.00 LVSTCKEXP 2 9 2 0 .0 0 4180.00 LBRLVSTCK 177 178 17520.00 2 5 0 8 0 .0 0 LBRCSTLVSTCK 150 300 500 58920.00 6880.00 41280.00 1 1 7 8 4 0 .0 0 1 9 6 4 0 0 .0 0 12280.00 7 3 6 8 0 .0 0 19480.00 116880.00 163252.50 6530.10 3 2 6 5 0 5 .0 0 1 3 0 6 0 .2 0 544175.00 21767.00 150 300 500 306636.34 8820.00 7020.00 1726.65 50200.00 7449.47 6 1 3 2 7 2 .6 8 1022121.14 17640.00 14040.00 3453.30 2 9 4 0 0 .0 0 150 300 500 154274-05 158775.64 169807.02 287932-05 296350.36 337479.05 561041.74 150 300 500 294746.56 299248.14 314004.27 550918.45 559336.77 604190.19 980647.45 179 211 212 213 214 215 216 TTLANHCSTSGP TTLANNCSTSGF TTLANNCSTPR 104944.68 103854.15 97111.04 164202.74 165325.62 168657.61 5 0 2 0 0 .0 0 7449.47 178 1iJO LVSTCKINV 43534.00 81626.25 LVSTCKANN 1741-36 181 3265.05 1132 1'33 184 185 X INCOME: 186 HERD SIZE 40 187 75 188 189 INCH 81769.69 153318.17 4410.00 2 3 5 2 .0 0 190 HNKSVNG3 3510.00 1872.00 MNKSVNGSCP 191 SYMLSVNGS 460.44 863.33 192 4 5 2 0 0 .0 0 2 0 0 0 0 .0 0 HCIISVNCSINV 193 HCIISVNGSANN 2967-92 6707.49 194 195 136 197 198 XI TOTAL PEED COST: HERD SIZE 199 40 230 75 231 PDC3TTCPG 232 55790.50 84869.89 FDCSTTGP 203 85992.77 54699.97 85971.01 FDCSTTPN 204 46472.91 205 206 207 208 XII TOTAL ANNUAL COST: HERD SIZE 209 210 40 75 1 2 3 4 5 6 7 B 9 10 11 12 13 14 217----------------------------------------------------------------------------------------------------------------------------------21B XIII PROFIT: XIV REGRESSION ESTIMATION 219 --HERD SIZE 220 40 75 150 300 500 SUP. (SUMX2) AVG SUKXI SLOPE INTERCEPT R2 221 '5 ---------------------------------------------------------------- 179 222 X1IIA GROW FORAGES AND GRAIN 223 PRFTGFG -20775-95 -6386.37 20666.19 80347.03 74070.899 7364303926 18517.725 1.189E+11 0.0503694 -46414-12 0-9994337 PBOFIT 2 24 INVGFG 505165-75 776823-02 1366926.05 2505532-09 5156446-9 9-0O794EM2 1289111.7 INVESTMENT 225 RR01GPC -0.113 3-1B0 5-528 7.207 226 LBRGFC 1.30 1.83 3-02 5-41 11.552622 43-37318472 2.6881554 4860026.9 2.059E-06 0.2342311 0-9998034 LABOR 227 CSTCVTKUC 16.14 13-06 11.50 10-59 565 119725 141-25 3069687650.00013-26-37703 0-9999326 HERD SIZE 228 LNRAPPRXGFC -20969.20 -7185-23 22437-19 79788.14 229 -------------------------------- ---------------------------------------------------------------------------------------------- ■ 230 XIIIB GROW FORAGES 231 PRFTGF -20175.02 -8427.25 1 4 5 4 8 .6 0 68256.71 54203-041 5348690734 13550.76 8.262EM0 0.0556968 -45712.46 0-9972909 PROFIT 232 INVGF 435735-84 660746.23 1136022.45 2023624-91 4256129-4 6.01206E«12 1064032.4 INVESTMENT 233 RROIGF -0.630 2-725 5-261 7.373 234 LBRCF 1.23 1.73 2.66 5-13 10.951891 39-04584184 2.7379729 3664822.6 2.471E-06 0.1092155 0.9993718 LABOR 235 CSTCWTMLKGF 15-95 13-18 11.71 10.79 565 119725 141-25 243297960 0.000164 -33-2663 0.9996379 HERD SIZE 236 LHRAPPRXCF -21443-36 -8 9 1 1 .0 0 1 7 5 6 0 -3 8 66997-01 237 ------------------------------------------------------------------------------------------------------------------------------238 XIIIC PURCHASE ALL FEEDS 239 PRFTFR -14753-35 -14236-94 -5162.92 13492-49 48823-69 28162-965 3012807378 5632-5929 6.051E*10 0.0457659 -29930-95 0-9702988 PROFIT 240 INVPR 220767.60 363104.75 601207.50 1073013.00 1627287.00 3885379-9 4-34145EM2 777075-97 INVESTMENT 241 RROIPB -2.683 0.079 3-141 5-257 7-000 242 LBRPH 0-97 1-39 2-29 4-09 6.49 15-246667 67.06688889 3-0493333 5210474.1 3-941E-06 -0.012895 0.9979697 LABOR 243 CSTCVTHUCPR 14.76 13-50 12.40 11.84 11-47 1065 369725 213 434206177 0.0003284-42-18567 0-9979697 HERD SIZE 244 LNRAPPRXFR -19827-34 -13313-15 -2416.18 19176.40 44543-23 11 12 13 14 15 16 17 ia 19 1 XV 2 — 3 TABLE 5-2 CHANGES IN PROFITABILITY BY LEVEL OF INVESTMENT ACCORDING 4 TO STHATEGY 5 6 Milk production (lb)* 15000 7 Corn Price ({/bu) 2.70 Milk/feed ratio* 1.50 b Milk Price ({/cat) - 12.00 9 10 LEVEL OF INVESTMENT ({ million) 11 1 2 0.5 1.5 2.5 12 13 STRATEGY! CFG 14 15 16 {PROFIT 17 rhoi (£) 16 COWS(#) 19 lbh (#) 20 21 22 -21229 -0.25 38.64 1.26 3955 4.40 1 0 3 .6 6 2.29 29140 5.94 168.67 3-32 54325 6.72 233.69 4.35 79509 7.18 298.71 5.38 regression: profit by {invested a-46414 b0.050 R20.999 GF a-45712 65681 93530 b* 0 .0 5 6 -17864 9984 37835 23 {PROFIT 5 .0 0 7.28 24 RROI(^) 0.43 6.52 B2 0.997 7.74 294.76 25 COWS(#) 48.74 130.75 212.75 376.77 26 LBR(l) 2 .5 8 3.82 1.34 5.05 6.29 27 28 PR 29 a- -29931 30 {PROFIT -7048 38718 61601 b0.046 15835 84484 5.58 6.58 7.08 7.38 31 RROI(J) H20.970 2.59 122.01 286.21 450.40 614.60 778.79 32 C0N3(#) LBk(#) 1.96 5-90 33 7.87 3.93 9.84 34 35 36 Returns ' to levels of investment beyond J■ 2505532 are 37 extrapolated For the strategy GFG 38 Returns < to levels of investment beyond { 2023625 are 39 extrapolated for the strategy CF 40 Returns to levels of investment beyond {; 1627287 are extrapolated for the strategy PR 41 42 Price of i 43 Soil management group 3 dairy c o m b ( { / c o w ) * 1 0 8 8 . 3 5 44 Price of land ({/acre ) 1100 Pries of cull cows ((/cat)- 39.47 75.00 45 Price of hay ({/ton) ■* Price of 1 hfrs ({/heifer)* 960.85 46 Price of corn silage ({/ton)* 18.31 Price of • culi hfrs ({/cut)* 51.46 47 Price of soybean meal ({/lb)~ 0.115 Price of < cull civs ({/cut)* 6 5 .0 6 F5. FORMULAS, VALUES AND THEIR EXPLANATION IA: INPUTS: Set Production Factors and Economic Conditions And Prices to Proposed Values. This component allows the user to select which soil management group (2.5, 3 or 4) and level of milk production (13,15,17 or 19 thousand lb) to consider. In addition, the user can set values for the price of land, milk and corn. Other exogenous (EX) variables can be changed as well. En­ dogenous (EN) variables are estimated by formulas. They should be changed with caution. Variable Name Refers to Row:Col R13C3 MP R14C3 PLND R15C3 See Thesis Section Contingent Model Components Soil management group (2.5,3,or 4); determines which set of crop yields in (ID) to use to estimate the no. of acres of each crop required to supply feed on farms GFG or GF Rolling herd average milk production/cow (13,15,17 or 19 thousand lb); determines which set of ration quantities to use to estimate annual feed quantities needed for cows and replacements Used to estimate:PCWS and PHFRS livestock expenses milk income EX 4.1.3.C ID EX 4.1.1 Purchase price of land ($/acre) should reflect the value of land for crop pro­ duction and be different for each SMG Used to estimate: cropland land for dairy facilities EX 4.4.3 4.2.2 4.3.1 181 SMG Type Variable (units); notes II IA IX X XV 4.1.3A Appendix A 4.1.3 4.2.1 V IX XV Variable Name PMLK PSCORN XNTRT PTXRT INSRT LNDGRWTHRT Refers to Row:Col R16C3 R17C3 R19C3 R20C3 R21C3 R22C3 Variable (units); notes Type Price received at the farm($/cwt) sold Used to estimate; PCWS,PHFRS milk income milk/feed price ratio Purchase price of shelled corn ($/bu); should reflect market value Used to estimate; PCSLG,PALFHY purchased feed costs milk/feed price ratio Real interest rate(decimal);applied against investments and operating expenses such as feed purchases and crop expenses Used to estimate; CPTMCH CPTBLDG annual land charge total feed cost total annual cost profit annual livestock expenses Property tax charge(decimal);charged against; Value of crop land Feed storage facilities (avg. value) Dairy facilities(avg. value) Property insurance charge(decimal);charged against: Value of crop machinery(avg,value) Value of feed storage facilities(avg. value) Daily facilities(avg. value) Land value growth rate(decimal);credited to the annual land expense For crop land For land for dairy facilities EX See Thesis Section 4.3.1 4.4.3 4.3.1 4.4.2 4.4.4 EX 4.4.4 4.1.7 4.4.2 4.4.5 EX Contingent Model Components IA X XV IA IV XV IA IA V XI XII XIII IX EX 4.1.3B V III VIII EX 4.1.5 Table 4. 12 VI III VIII EX 4.1.3B 4.1.3B 4.2.1 VIII Variable Name Refers to Row:Col PFL R23C3 PLBR R24C3 PALFHY PCSLG PLMSTN PCWS R14C5 R15C5 R17C5 R20C5 Purchase price for fuel and lubrication used to estimate fuel expenses for crop budgets Purchase price of labor($/hr) used to estimate: labor for cropping livestock labor Purchase price of alfalfa hay ($/ton);cal­ culated based on the price of corn Used to estimate:purchase price of soybean meal purchased feed costs milk/feed price ratio Purchase price of 35% dry matter corn sil­ age ($/ton);calculated based on the prices of PSCORN,PP,PK,PLMSTN Used to estimate:purchased feed costs Purchase price of soybean meal ($/lb); Calculated based on the price of ALFHY Used to estimate: purchased feed costs soybean meal savings milk/feed price ratio Purchase prices of limestone,dicalcium phosphate, and salt ($/lb) Used to estimate: purchased feed costs PDCL used to estimate PCSLG PLMSTN used to estimate crop budgets Purchase price of dairy cows ($/cow);this is calculated based on MP and PMLK Used to estimate: livestock expenses Type See Thesis _______ Section EX 4.4 Contingent Model Components EN 4.1.4 4.4 4.1.6 4.2.2 4.4.4B IA IV XV EN 4.4.4B 4.1.7 4.4.2 4.4.4C 4.1.7 IV XV EX IB VII IX 183 PSYML R13C5 Variable (units); notes EN 4.4.4B EX 4.1.7 4.3.5 4.4.2 4.1.7 4.4.4C IV X XV IV IA IB EN 4.2.2 IX XV Variable Refers to Variable (units); notes Type Name Row:Col __________________________________________________________________________________ R21C5 PCLLCW Sale price of cull cows($/cwt); this is EN calculated based on PMLK Used to estimate: income cost/cwt milk PCLLHFR PHFRS PDCNCLVS CPTMCH CPTBLDG R22C5 R23C5 R24C5 R13C7 R14C7 Sale price of cull heifers($/cwt);this is calculated based on PCLLCW Used to estimate: income cost/cwt milk Sale price of excess replacement heifers ($/heifer); this is calculated based on MP,PMLK and CLLS Used to estimate: income cost/cwt milk EN Sale price of deacon calves($/cwt);this is calculated based on PCLLCW Used to estimate: income cost/cwt milk EN Capitalization formula to use to estimate the interest and depreciation charge on durable assets with a fixed life(decimal); based on INTRT. CPTMCH is calculated based on assets with a life of 8 yrs and a salvage value of 25%. CPTMCH is used to estimate the annual use cost of capital for investments in crop machinery and dairy equipment and savings in equipment CPTBLDG is calculated based on assets with a life of 20 yrs and a salvage value of 0. It is used to estimate the annual use cost of capital for investments in feed storage facilities and dairy buildings and facilities EN See Thesis Section 4.4.3 4.3.2 X XIII XV 4.3.3 4.3.3 EN Contingent Model Components X XIII XV 4.3.3 4.3.3 X XIII XV 4.3.3 4.3.3 X XIII XV 4.1.5 4.1.2 VI,VIII,X 4.2.1 III,VIII Variable Name R16C7 PN HSZ HSZ HSZ HSZ HSZ 1 2 3 4 5 R20C7 R21C7 R22C7 R23C7 R24C7 R25C5 1 2 3 4 5 R13C9 R14C9 R15C9 R16C9 R17C9 Variable (units); notes Prices of nitrogen,phosphorus,and potassium ($/lb); Used to estimate:cash crop budgets PCSLG fertilizer value of manure Herd sizes(no. cows); the model assumes replacements are raised Used to estimate and summarize by herd sizes model components il-xill Type See Thesis _______ Section 4.4 EX 4.1.4 4.4.4C 4.3.4 Contingent Model Components IB IA X EX II-XV Used in section XIV to estimate a regression to estimate the number of cows for a given level of investment for the summary table in XV DO NOT CHANGE THESE CELLS Percent of the herd culled annually(20 to 35%) Investment levels;used to summarize profitability by levels of investment for each strategy;used in section XV of the model DO NOT CHANGE THESE CELLS 185 CLLS INV INV INV INV INV Refers to Row:Col EX 4.3.2 4.3.3 EX X XV 186 > !oo ~ *.-»f8 if* *.c* c * m *• •« L*' II S fmV w W» I — • IW o I l * wi i I H ©*•H >* lH^BS (B» I 9 to eg N K «N*■ iMfi K *J to to to to -a £ © x x x 4 X t/7 b. H xu O o c\ j v^»a./-S S. X SC K | o-£x s E x *-< 4 _a • KSft.^.< 5' XJ I K/-. 4 K U X J (\J tO 4 O >• f- s—i2 X< i >CU E • rs^SB< « cK\‘©©••SO XO* •l 44 ©I• ^ f — “ r 4 N L‘ • !S2 I» !8 o S S c rsi tO • i •m w • •X • K 4T I . . . 'OCCOwOOO © H X 9 55 to Sc >h 5 3 Sc to * iJJd. £ «r rg 8 — •3 ffi <-4•U2 t C Cx X X £» X II I I SSE* ' B o b: rv o » £ fc rg eg X o • t- • » © © H fX X t- X 3£ — ■O © O • • • o o •- . &C HC KoOfiI(9 t x x S. © — IB:CROP BUDGETS: This subcomponent estimates selected crop cash expenses (crop budgets)/acre for corn, corn silage, alfalfa hay and haylage. The following is a list of abbrevia­ tions of expenses and the item each represents; SDS = seeds, WS = weed spray, INSCT = insecticides, N = nitrogen, P = phosphorus, K = potassium, LMSTN = limestone, UTLTS = utilities, TRCK = trucking, FL = fuel, RPRS = repairs, OTHR = other and TTL refers to the total esqpense. BSCORN, BCSLG, BALFHY and BALFHYLG and alfalfa haylage are abbreviations for shelled corn budget, corn silage budget, alfalfa hay budget and alfalfa haylage budget, respectively. The variables BSCORNT, BCSLGT, BALFHYT and BALFHYLGT contain the total cash expense for each crop which is contained in the cell immediately below the variable name. Many of the crop expenses are linear approximations based on the yield/acre for that particular crop which is determined by the soil management group selected in (IA) and e j e c t e d crop yields in (ID) . The formulas or constant values for each particular expense item are listed below. These were estimated in Table 4.11. Here is an example how part of one of the formulas works: INDEX is a multiplan command used to locate a particular value in an array or table. The array is indicated by the first value in the parenthesis and the ordinal position of the particular value by the second number in the parenthesis. In this instance the instruction is to look up the value of the array YSCORN corresponding to the number indicated by SMG. If SMG were set to 3 in (IA) then the 3rd value of the array YSCORN (i.e. 105) would have been selected (see section ID of the model). Another example indicates how the SUM command operates: SUM (R(-14)C;R(-3)C directs the summation of values 14 rows above the present cell (in the same column) down to and including values 3 rows above the present cell. 187 INDEX (YSCORN, SMG) 188 C5 to R s s ►« E in rg X 6M W • c -a r* a a O C5 a r ►- i S Ji^ wcc •<*"“N O' w CO n3 • : rg * * si i A A < < H IE3 B c •-a E h 3 «5 s A i-a § W »a t-»as sc M * o K> < h w ?r cn u r gJ O A + B M * * * * •* -» • © o • x m I *Jw I ■< X r g #-■* < n C3 m • cnmE - A K * £a - to • c rg to • s o t o •»•■ r g * I A I * p to s a s a to u to I 3 ? ^ 5 m * - * rg > •o ♦ ■*rt->k> E ©• rn* cn to m so s <*ra, • wso © w* ft ® !im• SO «- O OS © • • X CD O 10 ••- t ** i eI C 5u~i J i <-a os i t o - —' I U X I A I t P to m i A rg i n cs rg o ^ x © e ♦ * o M •x » * r - to c — x in 1COw ~ ro-^ x * -- > « r O (\J • to A u I fe I 5 — u in O o Xw - A E R IC:RATIONS: This table contains amounts of feeds consumed/cow and replacement/year by level of milk production considering feeding and storage losses of feeds (see Table 4.4). The forage component on a dry matter basis is assumed to be 60% alfalfa (as either hay or hay and haylage) and 40% corn silage. See thesis section 4.1.1 for details. The appropriate ration (quantities of each feed) is selected based on the level of milk production (MP) specified in (IA) and is used when estimating quantities of feeds needed/herd/year for the various sizes of herds in component II. Beware that changing values in this table will change the number of acres of crops for farms GFG or GF and thus may make the crop machinery component (VI) inaccurate. The array variables: SCORN, CSLG, ALFHY, SYML, DCL, SLT and LMSTN refer to the bushels of shelled corn, tons of 35% dry matter corn silage, tons of air dry alfalfa hay equivalent, lb of soybean meal, lb of dicalcium phosphate, lb salt and lb of limestone that are needed for each level of milk production. The array variables NO contains the ordinal numbers (subscripts) for indexing (re­ trieving) appropriate values from the array variables above based on the level of milk production specified in IA. 1 48 — 49 50 51 52 2 MILKPROD 13 15 17 19 3 NO 1 2 3 4 4 SCORN 87.0 1 1 0 .0 134.0 157.0 5 CSLC 10.1 9-6 a.9 8.3 6 ALFHY 6.5 6 .2 5.8 5.6 7 SYML 535.0 1 0 1 1 .0 1 5 2 9 .0 2 0 2 0 .0 8 SLT 95-0 95.0 95-0 95.0 9 DCL 1 0 0 .0 1 0 0 .0 1 0 0 .0 1 0 0 .0 189 The array variable MILKPROD contains the values corresponding to the possible milk production levels. ID:CROP YIELDS: This table contains the expected crop yields/acre for corn, corn silage and alfalfa hay and haylage by soil management group. Yields for haylage are assumed to be 10% greater on a dry matter basis than the same crop harvested as hay. See thesis section 4.1.3C and Table 4.10 for details. The appropriate yields/acre for each crop are selected based on the soil management group number specified in (IA) and is used in (V) where acres of crops needed are estimated for farms GF and GFG. Beware that changing values in this table will change the number of acres of crops for farms GFG or GF and may make the crop machinery component (VI) inaccurate. The array variables YSCORN, YCSLG, YALFHY and YALFHYLG refer to the bushesl/acre of shelled corn, tons of 35% dry matter corn silage, tons of air dry alfalfa hay and tons of 50% dry matter alfalfa haylage produced. 1 56 — 57 58 59 60 2 5 OMQRHO 1 2.5 5 4 4 YSCORN 114.0 1 2 0 .0 105.0 8 6 .0 5 YCSLG 15-5 16.8 15.5 13.2 6 Y4LFHY 5.0 4.6 4.0 3.5 7 YALFHYLG 6.7 9-0 7.9 6.9 190 The array variable SMGNO contains the value corresponding to the possible soil management group numbers. These same values can be used as the ordinal numbers (subscripts) for indexing (retrieving) appropriate values from the array variables above based on the soil management group specified in IA. II;FEED QUANTITIES: The amounts of feeds needed/herd/year for the various herd sizes are determined by multiplying the quantity of each feed needed/cow and replacement from (IB) by the herd sizes. Feed quantities which differ according to strategy are suffixed by: GF for the strategies GF or GFG, or PR for the strategy PR. Farms which GF or GFG feed alfalfa haylage and hay for herd sizes 75, 150, and 300. Farms PR, feed hay and no haylage. Haylage is estimated as: 50% alfalfa hay dry matter * (87% dry matter/lb hay)/(50% dry matter/lb of haylage) = 1.044 * quantity of alfalfa hay. See thesis section 4.1.1. 0 SCORN, QCSLG, QSYML, QDCL, QSLT and QLMSTN are array variables referring to the quantities of shelled corn, corn silage, soybean meal, dicalcium phosphate, salt and limestone needed for each herd size. QALFHYGF and QALFHYLGGF are array variables which refer to quantities of alfalfa hay and haylage needed for each herd size for the strategies GFG or G F . QALFHYPR is an array variable which refers to quantities of alfalfa hay for each herd size for the strategy PR. INDEX (SCORN, LOOKUP (MP,MILKPROD:NO)) IXDOKUP (N, table) is a multiplan command which directs a search in the first col. (or row) of a table for a value equal to the value of N. The search then returns the value from the last col. (or row) which corresponds to the position in the col. (or row) held by N. In this instance LOOKUP (MP, MILKPROD:NO) directs MILKPR0D:N0 for a value = MP, it then returns the NO (see IB). Thus, if MP were set to 15 in (IA), searched for a value in MILKPR0D = 15 and returned from NO. a search in component IC in table: corresponding value of the array then the computer would have the corresponding value of 2 The purpose of the LOOKUP was to provide a subscript to indicate the ordinal position of the value of the array SCORN that was being searched for by the INDEX command. 191 The formulas or constants used to calculate these quantities are located below. Here is an example of how part of the one of the formulas works: 192 IM O IOXiJO I o ir\x O (ft O (Oy N * SB(ft IIOOU X W OS X X 9B X H H H J O ISO OV UWX ZO I CftQO U O W X X gG s s sefts1-9a* O (ft X X * .^-se-. o /- E < O X O X I CftA X O MX (ft X 1-9 A K A ^« o KO Xa OUOUB. O.UOSU WAPO KO K p M X X X H H J H a* x a £ X M x »-* x ^N o eft Cft x x o W X u x x pa U O U O U ft X 0. ^ S m s * O (ft 55 e s o X o c ! ^Si I Z IX O Q « * ( O X J ( I O •• Cft S I Cft Q O Iw O w ( X X X I U0.U i a^axa: IX X X x x . X •-*. 8§ X S £ N-p* X m 3r ix :x o -EH o •• a 'W Q ;SSI : QXt ix x S IM m § M f r « C f t* X O 9C • • >*- x l w X i M Sx m*- ©O xCft 8 x "^2- I X x C wftX••wi-9o (K A * « IU O U X ;A X X X .Z X X X :M X M M Ill: FEED STORAGE FACILITIES: This component estimates the dollars invested and annual use charge for feed storage facilities. The storage investment for each of the feeds is esti­ mated across herd sizes and then the appropriate components are assembled according to the storage needs for each particular strategy. It is assumed that shelled corn is stored as high moisture shelled corn in upright cement stave silos for all herd sizes. All but the smallest herd size are equipped with unloaders. C o m silage is stored in bunkers except for the smallest herd size where it is stored in an upright cement stave silo with a top unloader. Hay is stored in a pole barn. Haylage is stored in upright cement stave silos. Linear equations are used to estimate the costs of feed storage facilities depending on the quantity of each feed to be stored. It is assumed that 70% of the total hay equivalent required will be stored on farms GF or GFG and that 40% will be stored on farms PR. For details see thesis section 4.1.2. Annual use charges are derived by multiplying the total investment in feed storage facilities by the annual use charge on capital (CPTBLDG) + (multiplying the average investment by the charge for property taxes and insurance). STOINVGF, STOANNGF refer to the total feed storage investments and annual use costs for farms GF or GFG. STOINVPR, STOANNPR refer to the total feed storage investments and annual use costs for farms PR. 193 STOSCORN, STOCSLG, STOALFHYGF, STOALFHYPR, STOALFHYLG are array variables refer­ ring to feed storage facilities investments for shelled corn, c o m silage, al­ falfa for GF and GFG, alfalfa hay for PR and alfalfa haylage for GF or GFG. 194 o * u x o o M * to 2 I Q r CO I * O t cm or IO i ch* i • m io m i + ♦ i cm o in i m-vo i m m m W x« I N — X ♦ o K O h M- H O * . •X O OOOh i * u u m *9 I CM o r : T e-i« t e- co 3 * * «J i cr co P**ce < C9 OB ♦ © X U 0 * r - i -a 9 CO 03 H r - a i I •*> * c r < z r CM © * * CO x h Sg+H i_i< ^a* fr** » eh • x sc -«r X pu » i «in tJr> i O in < < (O I UOSCBOIS * CO i «t in in — tq i in m • • CO I 33 * ^ CM CM CMCM e - »- *- VOv© «- . i iso r- v ?p * • ♦Sb I .. ► 4Zi »*JX « H t- « H I -■>->* I p w * 33 ^ I Ch* f k ,X f* 2u . iinm * I 6* ♦ a. e * o X x x+ *o K x I •m u »J tn i K '+ t o♦ m♦<9< or I N O * * CD m i«r vo in m ~ N 1X ♦ e* x ♦ e-« « x ♦o x o CO u p (O O W O O fc. CO m3 * + 1-3 t A CB < I • O U Q .9 * f^ £ rH r H , e > • ■ N - 'O “ I» I I* • •o' CO I « - CM CM CMCM C rc * - vo*o «— OJOf'fl-Si O* “ U U — OO Ow h w. T v • u-r qco :Xy t ucc qw CO a * r• + • O (fl6u I 3 . « UOfcOr t (M O S i> < * 9X n J x S *fc-i—Ii EXh 6+n I O w i m *X au 33^« a N i .m iJ x m i O in< ^ tn I -f♦ Oror ♦ A I CM O • * CD mdi n i n ~ X CM i i n in • •oi U N • • CM CM CM CMC K CO I g O P—•^ • CO • U k I * OS i cro o> IbX:* >M i j x >4 iu I CO CM < < 1 O' t 9 9 t* o • • i cm cm m m i— < j\ • • • CM CM CM x * CM « - SO lO O (4 CO ‘ b Z t as o X X C3 « a * -4 X >H >* = s s O J k k k U (Q r J CO o < < ifi lO r- • * l h « x ♦* X •X X o * o ca r—« car—> T in T i —i X x •*• ca ♦ U — I«'~' 6i x t co u + eu OS r— i ,j a n 0o Xt o in ® n r- X n I I g-» ♦ »F* * q ii — i cue * * —i x 6 » » x ca x x o x I ♦* K c♦ •K i ca ca a ca t I t — i r —i X r —i—1 6 , i i o c a ^ »— (D w I 1m | • | |« 11 — >cm i— i m > I X i x • x t x >m • IV:PURCHASED FEED: This component estimates the cost of purchased feed for each herd size within each strategy. It is estimated by multiplying the quantities of each feed pur­ chased by the approximate price from component (IA). The feeds purchased depend on the feeding strategy. See thesis section 4.1.7. PRFDGFG, PRFDGF and PRFDFR refer to the array variables containing the cost of purchased feeds on farms which GFG, GF or PR respectively. 3 99 100 10) 102 "PRFDGFC" HSZ1 HSZ3 6 HSZ4 - 7 HSZ5 QSm»PSm*Q:;LT*PSLT*Q QSYHR*PSY!a+QSLT»PSLT+l5 QSm»PSm*QSLT*PSLT*Q QSm»PSYML*QSLT*PSLT*C) QSYML'PSYML*QSLT*PSLT*Q DCL*PDCL+QIjHS"M*PLWSTN DCL*PDCL-QLMSTH*PLMSTN DCL*PDCL4(JU(ST»»PL«STH DCL*PDCL4QLMSTH»PLMSTH DCL«PDCL4QLHSTN*PLMSTN H[-llC4 QSC0 RN»(PSC0 RM- 0 b[-i]c«QSCORH*(PSCORM- 0 b[—1]c-*QSCORN*(PSCORN-0 h[-1 ]OQSCORN*(PSCORN-O R[ - 1 JOQSCORH*(PSCORN-O .2) 104 “PRFDPR” 5 > .2) -2) , •?) , •?> , R[-l]c»QCSLG*PCSl.G+t)ALF r[-i]C4 QCSLG»PCSLG4 QALF r[-1 ]C4 QCSLG«PCSLG4 QAU r[-1 ]C4 QCSLG*PCSLG4 QALF R[-|JC4 QCSLG»PCSLG4 QALF HYPR*PALFHY HYPR*PALFHY HYPR*PALFHY HYPR*PALFHY HYFR»PALFHY 195 103 "PRFBGF" 4 "HERB SIZE" HSZ2 V:CROP LAND: This component estimates the acres of land required to supply alfalfa and corn silage on farms GF as well as corn on farms GFG. Acres of each crop needed are calculated by dividing the quantity needed for a particular herd size (from component II) by the expected yield/acre (ID) for each crop; this is then multiplied by 1.05 toaccount for headlands and wasted acreage. The total acres necessary to GF or GFG is estimated by summing the acreages of the crops needed according to the strategy. The total investment in land is estimated by multiplying the number of acres needed by the price of land (PLND, component IA). The annual use cost is established by multiplying the investment value by the interest rate - growth rate in land value + property tax charge. See thesis section 4.1.3 for details. ASCORN, ACSLG, AALFHY are array variables referring to the acres of corn, corn silage and alfalfa (both for hay and haylage) required to supply the quantities of these feeds needed for each herd size. needed forcropping LNDINVGFG, LNDANNGFG, LNDINVGF and LNDANNGF are array variables which refer to the total investment and annual use cost for farms GFG and GF respectively. 196 AGFT and AGFGT are array variables referring to the total acres for each herd size for the strategies GF and GFG. 197 6 * w01 >h as -Xa M H SC: 5iS! $s S3-! 3£i i o c a -3 X X • Bm C/3 J h3 w v I CM ■< 6-.j ex x c 6-» CO 3 'h Cm Bn < *a u : < C9I >H J ' M CO l-H I I I CO I 5 W It o C/1 X * * X t I O U sssats aO* , B uN 6 -* 0« (M X :E U I * O X • _ O I* < « r— OI—CJ■«< » as >5 i!h3 X NgglTiOU IO X t uX Jj^ CS M»JuiO IK 0 -I X CM-PN-i •-aa : 3 £ ♦ 53^ k e* x t- x : Gd B a ,j n i >*u a • xx* ei = J h S : x I O X X • »cm co : ia B, CM « U u < f * ip q X t< » x u IX 1 X 0 • t- I 6XX- O w ^ X* H J t-i X i t4B * :a o o< hx ?3~£i c » so Cm Cm O U «h ££ CJ O •< VI:CROP MACHINERY: This component estimates the total crop machinery investment and annual use charge for farms GFG or GF. Investments are derived by multiplying the crop machinery investments/cow (Table 4.12) by the appropriate herd size. See thesis section 4.1.5. The annual use charae for machinery is calculated by multiplying the Machinery investment by the annual use charge for capital (CPTMCH) for machinery estimated in (IA) + the average value of the investment (.6 * investment cost) multiplied by (insurance + machinery storage charge). MCHCRPINVGFG, MCHCRPANN, MCHCRPINVGF and MCHCRPANNGF are array variables referring to the machinery investment and annual cost for farms GFG and GF respectively. 128 129 130 131 "MCHCRPINVCFG" 132 "MCHCRPANNGFG" 133 "MCHCRPINVGF" 134 "MCHCRPANNGF" HSZ1 "HERD SIZE’ HSZ2 HSZ3 HSZ4 3643*HSZ1 2152»HSZ2 1532*HSZ3 1078»HSZ4 r [—1]c *cpthcii+r [-i ]c *o . r [-i ]c »cptmch -*r [-i ]c »o . r [-1 ]c *cptnch *r [-i ]c »o . r [-i ]c*cptmch *h [-i ]c»o . 6«(INSRT*0.015) 6*(INSRT*0.015) 6«(INSRT*0.013) 6«(INSRT«0.015) 3243*HSZ1 V 1907*HSZ2 1322*HSZ3 801»HSZ4 h [“1]c *cptmch +r [-i ]c*o . r [-i ]c *cptmch *r [-i ]c ,o . r [-1]c *cptmch +r [-i ]c *o . r [-i ]c »cptmch «r [-i Jc *o . 6*INSRT 6*INSRT 6*INSRT 6»INSRT o CO V I I :CROP EXPENSES A N D LABOR: This c o m p o n e n t e s t imates the cash crop expenses for farms w h i c h GFG or GF, by multiplying acres of each feed by the crop budget expense estimated in (IB). Total hours of labor for each crop are estimated across herd sizes using linear relationships dependent upon the number of acres of each crop grown. See thesis section 4.1.4 and 4.1.6. The total hours of labor are then estimated for each strategy of GFG or GF by summing the appropriate labor hours for each crop. The cost of labor is estimated by multiplying the total hours of labor by the cost of labor (PLBR) from component (IA). CRPEXPGF and CRPEXPGFG are array variables referring to the cash crop expenses for farmers GF or GFG across herd sizes. Since alfalfa haylage is assumed to yield 10% greater yield than hay, and 60% of the hay crop is harvested as hay­ lage, .6 * 1.03 = .56 of the total acres of hay crop is harvested as haylage and .44 is harvested as hay. LBRTGF and LBRTGFG are array variables which refer to the total hours of labor required to GF or GFG for each herd size. LBRCSTGF a n d LB R C S T G F G are a r r a y v a r i ables re f e r r i n g to the total labor cost to G F or G FG for ea c h h e r d size. 199 LBRSCORN, LBRCSLG, L B RALFHY a n d LBRHYLG are a r r a y va r i a b l e s r e f e r r i n g to the hours o f labor r e q u i r e d for each p a r t i c u l a r crop (i.e. corn, corn silage, alfa l f a hay and h a y l a g e ) . 200 < ca OS co ca -s CO £ < OS a n A A o a (N O tA ~ 0*1CM r> r» CO « cv ca tn o u O iJ CO h3 ■< < CO < • C4* A A << 3.24*PC LVS-0.4*PCLLHFR*3.24*PC IVS*1.4*PCLLHFR*3.24*PC LLCH+(36-CLLS)i£*PHFRS)» LLCW+(36-CLLS)f*PHFRS)* LLCH*(36-CLLS)$*PHFRS)* LLCW*(36-CLLS)<*FHFRS)» HSZ2 HSZ3 HSZ4 HSZ5 (150«PN-*54*PP*200»PK)*II (150»PN«54*PP«200*PK)*H (150»PH*54*PP*200»PK)*II (150*PM+54*PP*200*PK)*H SZ2 SZ4 SZ5 SZ3 (75*PM«54*PP*200*PK)*HS (75*PN'*54*PPt200*PK )*HS (75*PH+54*PP+200*PK)*HS Z2 Z4 Z3 100*PSYKL*HSZ4 100*PSYKL*HSZ2 100*PSYML*HSZ3 50200 45200 50200 20000 K[-1]c»CPTMCH*Kf-1]C*0. r [-i]c*cpthch «r [-i ]c*o . r [-i]g»cptmch »r [-i]c*o . R[-1]c #cptmch «r [-i ]c«o . 6*(PTXRT+INSRT*0.015) 6*(PTXRT+IHSRTtO.015) 6*(PTXRT+INSRT+0.015) 6*(mRT*ISSRT<0.015) (KP*9.5*PMLK«0.44*PDCNC LVS*1.4*PCLLHFR«3.2^*PC LLCWt (36-CLLS)!f»PHFHS)* HSZ1 (150*PH+54*PP+200*PK)*H SZ1 (75*PN«54*PP*2C>0»PK)*HS Z1 100*PSYML*HSZ1 204 192 "SmSVNGS" 193 "MCHSVNCSINV" 194 "MCHSVNGSANN" HSZ1 XI:TOTAL FEED COST: This component estimates total feed costs for farms of all three feeding strategies across all herd sizes. The feed cost for farms GFG or GF are denoted by the variable names FDCSTTGFG and FDCSTGF and are estimated as: (Purchase feed cost - soybean meal savings + cash crop expenses) * (1 + interest rate * .5) + feed storage annual cost + crop labor cost + annual land use cost + (crop machinery annual cost - machinery savings annual use cost * .5)). Only 1/2 of the machinery savings annual use cost is applied to the cropping program. The other 1/2 is attributed to the dairy. FDCSTPR refers to the as: feed cost for farms purchasing all feeds and is estimated Purchased feed cost * (1 + interest rate * .5) + feed storage cost 205 199 "HERD SIZE HSZ2 200 201 HS21 202 "FDCSTTGFG" ((PRFDCFC-SYKLSVNGS*CRP ((PRFDCFG-SIHLSVHGS’CRP ((PRFDGFC-SIHLSYNGS*CRP EXPGFG)*(1«(IHT«T*0.5)) EXPCFC )*(1•»(INTRT»0.5) ) EXPCFG)*(l«(lNTRT*0.5)) ♦STOANNGF+LBRCSTCFGVUID *ST0ANNGF*lBHCSTGFG«L>n> ♦STOANNGF*LBRCSTGFG♦LMD ANNGFG«I!CHCRPANKCFG-HCH ANNGFU«HCHCRFANNGFG-MCII ANNGFG*HCHCRPANNOFC-NCH SVNGSANN*0.5) SVNCSANN*0.5) SVHGSAHH*0.5) ((PRFDGF-SIHLSVNCS«CRPE ((PRFDCF-SIHLSVHGS+CRPE ((FRFDGF-SYMLSVNGS*CRPE xPGF)*(t*(iiM,RT*o.5))*s XPGF)*(t♦(IRTRT*0.5))4S XPGF)*(1♦(INTRT»0.5))»S T0ANNCP-*LBRCSTC1,*LHDAN!I T0ANNGF-*LBHCSTGF'»LNDANN T0ANNGF+LBRCSTGF♦LKDANN GF*MCHCRPANHGF-MCHSVHCS GF*MCHCRFANNGF-MCHSVNCS GF*MCHCRPANNGF-MCHSVNCS ANN*0.5) ANM*0.5) AN1I*0.5) PRFDPR* (I♦(INTRV*0.5 ))♦ PRFDPR* (1■•(INTRT*0.5))♦ PRFI)PR*( H(lNTRT*0.5))* STOTANNPR STOTANNPR STOTANNPR 203 "FUCSTTGF” 204 "FDCSTTPH" HSZ3 HSZ4 n n HSZ5 n ((PRFDGFG-SYHLSVNCS«CRP EXPGFG)»(I♦(IHTRT»0.5)) ♦STOANNGF*LBRCSTGFG»IiND ANNGFG+NCHCRPANNGFG-MCH SYNCSANN*0.5) ((PRFDCF-SYMLSVHCS*CRPE XPGF)*(1♦(INTRT*0.5))*S TOANNGF’LBRCSTGF+I.NDANH GF»HCHCRPANNGF-HC11SVNGS ANN*0-5) PHFDPR*(l*(lNTRT*0.5)V PRPDPR*(l+(lNTRT*0-5))+ STOTANNPR STOTANNPR XIT:t o t a l ANNUAL COST: This comjxment estimates the total annual cost for farms of all three feeding strategies across all herd sizes. TTLANNCSTSGFG, TTLANNCSTSGF and TTLANNCSTPR refer to the array variables estimating total annual costs for farms GFG, GF and PR. Total annual costs include: total feed cost estimated in (XI) + dairy building and facilities annual use cost + dairy equipment annual use cost + livestock cash expense + livestock labor cost + livestock annual use cost - (machinery savings annual use cost * .5) -1 209 210 211 HSZ1 212 "TTLANNCSTSGFG" r [-10]c +DBLDGANN«DEQANN 214 "TTLANNCSTPH” •t ♦DLHDANN+LVSTCKEXP+LBRC STLVSTCK+LVSTCKANN-JICHS VNCSANN*0.5 ' fi[-10)C ♦DBLDGAH1H DESANN ♦DLNDAHN♦LVSTCKEXP+LBRC STLVSTCK+LVSTCKANN-MCHS VNGSANH*0.5 r [-io ]c +dbldgann +deqann ♦DLNDANN+LVSTCKEXP+LBHC STLVSTCK+LVSTCKANN H R[-1o]c+DBLDCANN+DEQANN ♦DLNDANN+LVSTCKEXP+LBHC STLVSTCK+LVSTCKANN-MCHS VNGSANN*0.5 r [-io ]c +dbldgann +deqann +DLNDANN*LVSTCKEXP+LBRC STLVSTCK*LVSTCKANN-MCHS VNGSANN*0.5 R[- 1 0]c+ D B L D G A N N *D E Q A N N ♦DLNDANN+LVSTCKEXP+LBRC STLVSTCK‘ LVSTCKANN HSZ3 HSZ4 HSZ5 R(-1o]c+DBLDCANN+DEQANR h [-io ]c +dbldgann +deqann ♦DLNDANN+LVSTCKEXP+LBRC *DLNDANN*LVSTCKEXP*LBRC STLVSTCK+LVSTCKANN-MCHS STLVSTCK+LVSTCKANN-MCHS VNGSANN#0.5 VHGSAHN*0.5 R[-10]c+DBLDGANN+DEQANN R[-10]C*DBLDCAHN*DEQAHN +DLNDANN+LVSTCKEXP* LBRC ♦DLHDAHN *LVSTCKEXP*LBRC STLVSTCK* LVSTCKANN -MCHS STLVSTCK+LVSTCKANN-MCHS VNGSANN*0.5 VNCSAKR#0.5 k [-io ]c +dbldgann +deqann h [-io ]c *dbldgasn *deqahn R[-10]C*DBLDGANN*DE()ANN +DLNDANN♦LVSTCKEXP*LBRC *DLNDANN+LVSTCKEXP+LBRC *DLNDANN*LVSTCKEXP*LBRC STLVSTCK+LVSTCKANN STLVSTCK+LVSTCKANN STLVSTCK+LVSTCKANN ^This is a reduction in annual costs to be applied to farms GF or GFG and is b&sed on the machinery cost common to both the dairy and cropping enterprise. Since half of this savings was included in estimating feed costs for farms GF or GFG, the other half (attributable to the dairy enterprise), is included here. 20G 213 “TTLANNCSTSGF" "HERD SIZE HSZ2 Total farm profit for each herd size within each strategy is estimated in this compon­ ent. Profit is actually dollar returns to management as labor and capital have already been accounted for. The array variables PRFTGFG and PRFTGF refer to total annual farm profit for farms GFG or GF. It is estimated as; income - total annual costs + savings in fertilizer cost due to use of manure,including interest on the fertilizer savings. The value of manure for farms growing forages (GF) is based on the value of all of the P and K produced but only half of the value of N as over 1/2 of the manure will be spread on hay crops. PRFTPR is an array variable referring to total annual farm profit for farms PR. It is estimated as: income - total annual cost + .25 * savings in fertilizer cost due to the value of manure. Thus the model assumes that .25 * the value of the manure produced will be retrieved by farms PR through sales to neighboring farmers. See thesis section 4.3.4. Profit is denoted by the variables: PRFTGFG, PRFTGF and PRFTPR for the strategies GFG, GF or PR. The array variables:INVGFG, INVGF and INVPR refer to total investments in the farms. Total investments include: land + feed storage facilities + crop machinery investments savings in machinery investments + dairy building and facility investments + dairy equipment + livestock investments for the strategies GFG and GF. Total investments for farms PR include: feed storage + dairy buildings and facilities + dairy equipment + livestock investments. The array variables: RROIGFG, RROIGF and RROIPR refer to the ratio of: + INTRT) for the strategies of GFG, GF, PR. (profit/investment) The array variables:LBRGFG, LBRGF and LBRPR refer to the total man equivalents (hrs/2300) for the strategies GFG, GF and PR. The array variables:CSTCWTMLKGFG, CSTCWTMLKGF and CSTCWTPR refer to the adjusted cost/ cwt of milk sold. It is estimated as: (total annual costs - income from the sale of deacon calves, cull heifers, cull cows and excess replacement heifers) * herd size)/ (total lb of milk sold/cow * herd size). The array variables:LNRAPPRXGFG, LNRAPPRXGF and LNRAPPRXPR refer to the estimated profit for each herd size within each strategy. This is based on the regression estimates calcu­ lated in XIV and are predictions of profit based on dollars invested. - LOZ XIII;PROFIT; 208 CO u a A A > I s .H Jg ©»- > *f r< a a A P» HO H t3 £ ♦ A M O A 9*«—1 Eh f CO O a A A — A ♦ l A A A a A O. A 'N . a ♦ > i—j S 3 £ 3^ I a co * >a * ' U I I co x u H H o cj a co^otf 8 SS-9 s s A O « :A ♦ £ C3 S a rj> t* J’TT «I i ♦ a H ;> * « a a ♦ iT* © « Sa £ o >■£9 0 a a ♦ &» saga 1 A CJ « a►-IA oH a cm cj i _ S'"* 8 «— m co 4t> 1A a r & ■^a SgE A ON k( 35 M t CO C4 «r^o x S • B H I co a s 33 M • A E CM« VO a a* cj o co Q u CO co o MOM > A CO a a a Of u o « Z O fH t O • CO • aM A vO lO O t Cl) O a A 0* CM fc» CM C9 I • S N Oh V * • X p. • A %t • O tk> A CO VO A N • tn u CO I 4 if\ A 4 ♦ C9 O A A ON 5* ^gVlg a&ia — s? > o • Ob O C9 • (/] H z ^ COK CO C4 v X lfl t * U 'J > NH(™H s r > > a a cm — • vO X ft, i co a a a ej i _ i h t ir» w o a (9 w h o e^i— i O i » ■ ' - ' ■ S Eo a co « o A as * 5 & H CO A CJ A A w 4 d o w ♦ a cm h* M O M C9 a a ♦ J M 9n *4 A S O O • C9 CM SU A 8 >u—• a a © £-• O CO H A GO CO9V A CM CO A w O CO u C9 > z On / h a O * CO Hi hr a * ~ > m m O O l o c9 : fe. (a, » J at 12 *" O O > • > > a : I CO a o A hh C9 o a a > § ^ 3 A > cm • > « -_ i ►w ♦ » |CNW os a ^ CO O VO 1*%ft*CO © i *e t n w C9 C9 A Ob Ch ^ CO 6-* U COO M *- * ?? a >*a ^o 6- A JOW tb o a CO w> i a a a H * I a a J3 » « Q a a co a w o <—l • ' - v . e-« a N- h .*-* a * a ♦ H MN On m c o U C9 • a a co e» «-• a h eg nr w 6* o s cj a Eh o a § a ? s H O *-JJ • 03*-N# £ 3 On « C9 S M O n & kA "*■♦ wj -«a a-a gC9 > > g £ a s ZX .H H S?au I g gi SA Oaco CaaO “'SS a a ? T 5 > **-» a M O N CO V H__________ S oX♦ S>B♦A!: f* ♦ ^ *• « C9 _ O o • co e a x 2 CO A i >E ih iw o « CJ ♦^N» co^ co A A CM A CO Ob A co a > o. CJ CO frN aa Oh co a KN CO g CO ♦ C9 (h tj w* . W V . fiH CJ A M vfl in i n CO h ea ga A A •KN CM CM K> CM cj A O a t Eh On. a cj cj CS E* a co 03 4 u t > « r < v n r KN N> KT \v CM 4 C Q rS I, | _ • I lO I I ♦ t'* * u u j y u c» s o *— IA i | I (Mr-«O OS t X«—* I (Mr— * | u ^ U , • OSI— i I CM i—» _ r —* I ♦ Xr~» i—>« XI— * I !A x {A«_J— A OQi—<« Xi—* I a I CJ A I grr-i m as (At— *O I lA CM O i — I I lA CM CO • I CJi— » vBBUUuu I iI ^ sfgt-rAio wNam i CM I t— i CJ X g + CM CJ « Ki-' ♦ CM CM I x<— > CO A X N ♦ CO ♦ IA CM I r- s w ' CM IA CJ CM CM CM | A O CM CM CM CM t ♦A CJ — M N CO CO X fA ^ (A (A CM CM — CM y* CM CM XV:SUMMARY: This component summarizes in tabular form the profit, rate of return on investment (RROI), number of cows and number of laborers for each strategy, considering levels of investment of: $.5, 1.0, 1.5, 2.0 and 2.5 million. The slope (b), intercept (a) and coefficient of determination (R2) for the regression estimating profit/ dollar invested are listed for each strategy. The footnotes contain the maximum number of dollars actually budgeted in the analysis. Investment sizes greater than these are extrapolations. In addition many of the factors describing the specifics of a particular analysis such as level of milk production, price of corn, price of milk, etc. are printed. The approximate milk price/feed cost ratio is printed using a regression equation which relates a weighted average of the price of corn, soybean meal and hay with 16% concentrate (see thesis section 4.4.3). as o • fc. o o Jw * < f t. J CM ft. ♦ X eg m >*ir\ w t- w • 213 m CM ft. O 0 * * O © 'ft co OOtOffl s o g ft* CJ ft. , £ & ft.— * ^ O J 1 a; ir\ ►H CO ■>—' >« OS — 2 Pi CJ CJ I ft.m S I u u xi i £ w ir." es^.2 i ; co x . _l X M J M p . n . *i i—o f:- * £.• >U u ' ^ « f t. CJ f t. CJ KT uCoi/^UkOb. H (9< w > ^ H o i I i I I H o i c f t. &- f t. -a 60 H- 8 2 a ft.> *J X ft. _ S5. o * ce•MCJ w f t. cj I ej CJ s x M ♦ . i — h z e* : . M ft.» S acMu—I o* •ec/a~ .oft cj* f ft t. ft* *•> CJ ft. > < ft e-. X * 6s .E ft. a *4> S> a s &. x ft, M ft. M o • oft H O H U I .. X E-« I o * ft.> 1—X >o O — -t O X O X MX 1-4 f f t. f t. cj o N CO = ft. H flu »ft ♦ J _ S 2 . O f t IX — O H C A^ f t. c o «■ ® ^ « Oft -a * ft *ft M ft H ft O ft H O H C3 ! * > I O ^ 1^1 f •K >»— ft*.^ > ► X X i O— Oft-SX» I— Ot X 4 M w * ft I—I I c s § •j CO ♦ CJ ft. 5 ♦ M X CM o g r— i > «> eo m CO CM CQ CM X > > 9 -w ft H 53 H O l £ e« o CO Ift X -3 ; E-> CM 6-> (\i 5J.8B5ES X — CJ ft O f t 2 * e M | O fto *I £ a. S2^8S2££ 6* • ■-L8ESES X — O X OX ft iBI : i-a : : ( I < 33 «ft K I fr.M I ssi m: * - cm r \ _ _ HH t i 12 13 14 15 16 ICPTPFTPR+SLPPFTPR* INV1 (r [-1 Jc/IKV!♦INTR1') •100 ICPTHSZPR+SLPHSZPR* INV1 ICPTLBRPR+SLPLBRPR* INV1 ICPTPFTPR+SLPPFTPR* INV2 (r [-1]C/INV2*INTRT) •100 ICPTHSZPR+SLPHSZPR* INV2 ICPTLBRPR+SLPLBRPR* INV2 ICPTPFTPR+SLPPFTPR* INV3 (r [-1]c /INV5*IWTRT) •100 ICPTHSZPR+SLPHSZPR* INV3 ICPTLBRPR+SLPLBRPR* INV3 ICPTPFTPR+SLPPFTPR* INV4 (r [-1JC/INV4^I»TRT) *100 ICPTHSZPR+SLPHSZPR* INV4 ICPTLBRPR+SLPLBRPR* INV4 ICPTPFTPR+SLPPFTP R*IHV5 (r [-1JC/IHV5+JNTB T)*100 ICPTHSZPR+SLPHSZP R*1HV5 1CPTLBRPR+SLPLBRP R*INV5 •t .. „ 11 28 "Hi" 29 50 "SPKOFIT" 31 "RKGlCC)" 32 "COWS(#V 33 "lbr (#)“ 34 ' IC y> „ „ H •f « „ f* „ INDEX(lNVGFGv4) "are " INDEX(IHVGF,4) “are" IHDEX(INVPH,5) "are" "a-" "b-“ ICPTPFTPR SLPPFTPH "S2*" RPFTPR „ _________________ 214 36 "Returns to levels of investment beyon A o « 37 M extrapolated for the strategy GFG" 38 "Returns to levels of investment beyon A a ta" 39 " extrapolated for the strategy GF" 40 "Returns to levels of investment beyon ,4 « " □ a 41 " extrapolated for the strategy PR" 18 17 A O■ •1 > 43 "Soil management gr oup *" 44 "Price of land ($/a ere) ■" 45 "Price of hay (S/t on) »" 46 "Price of corn sila ge (S/ton)*" 47 "Price of soybean m eal ($/lb)«" SHC PLOD PALFHY PCSLO PSYML "Price of dairy cow a ($/cow}-" "Price of cull cows ($/Cwt)“" "Price of hfra (*/h eirer)-" "Price of cull hfrs (*/cwt)-" “Price of cull civs (S/cwt)-" PCW3 PCLLCW PHFRS PCLLHPR PDCNCLVS BIBLIOGRAPHY BIBLIOGRAPHY Armstrong, D. 1980. 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