BEEF PRODUCHON AND PROCESSING: - _ _ e RELATIONSHIPS FOR THE, SLAUGHTER 00w MARKET : I ~ Thesis for the Degree of M. S. ' MICHIGAN STATE UNIVERSITY PAUL L. KRAM, 'Jr. 1975 . ..... ..... - c ..... ~ o . 12! 5.5!8 , H..-‘ . -. «in! /' .4-8. Pu“. I x. ,. \ .‘. .. .. h‘: 1 "r; T‘ {5" {7.1" ‘ L. -: .r' “‘1 L53- ‘I VAL”) .r g . . ‘.-' ’- r' ‘q A: AU $ film-11*? mw— .- "L NA If“! A IAN/NAN JAN 1 3 2007, JAN” 1‘: 4" 2002 ABSTRACT BEEF PRODUCTION AND PROCESSING: RELATIONSHIPS FOR THE SLAUGHTER COW MARKET By Paul L. Kram, Jr. Erratic price movements of beef over the last few years have caused highly volatile earnings to cattle producers while injecting considerable uncertainty into the beef production and marketing system. Two groups of participants whose interest in how various changes will affect their respective activities are the meat processing industry and the food service industry. This study investigated the relation- ship of cow slaughter to beef production and to the beef processing industry which serves the needs of the food-away-from-home market. If beef supplies for meat processors and purveyors is partially de- rived from cow slaughter, predicting the available cow slaughter would benefit those firms utilizing cow beef as an important primary supply source. A growing beef supply over time has been the result of increasing cattle numbers and increasing productivity of the cattle herd. How- ever, the importance of productivity gains relative to increases in the size of the cattle herd has decreased over time. Therefore, future increases in the supply of beef are much more dependent on increases Paul L. Kram, Jr. in the size of the cattle herd. Beef production can be divided into two major operations: (1) cowbcalf operations and (2) cattle feeding operations. Cow-calf fi—fla Operations are characterized as relatively small sized production 1 units, maintaining traditional production methods. These producers have increased their productivity to some degree by increasing calving percentages, decreasing death losses, and introducing larger-sized breeds. Forage production per acre has also increased. However in a general sense, the cow-calf enterprise is conducted today in a fashion quite similar to that of 25 years past. In contrast with cow-calf operations, the cattle feeding industry has undergone a great deal of change. There has been a large decrease in the number of feedlots accompanied by a corresponding increase in the number of cattle fed per lot. However, changing grain-slaughter relationships suggest the need for continual adjustments by this seg- ment of the beef production industry. To examine relationships of beef processors to the beef produc— tion and marketing system, the functions of beef processors to purvey- ors were investigated. Information gleaned from a questionnaire re- ceived from 103 member firms of the National Association of Meat Pur— veyors was the major data source. The analysis concentrated on three areas: production aspects, supply logistics and disposition of finished products to the food service industry. The major findings with respect to production aspects was that hamburger was the most important component of average total weekly beef production followed in descending order by chucks, boneless strips, Paul L. Kram, Jr. rib-eyes, short loins, butt, rib roasts, and bone-in strips. Processed pork, lamb, fish products and specialized meat items not listed in the questionnaire was the largest single category of the respondents weekly production composition. This category is an important portion of the purveyor business. The range of meat volume processed weekly by these firms was from 2,000 pounds to 7,500,000 pounds. The average amount processed weekly was 210,591 pounds, with a standard deviation of 813,659 pounds. It was estimated that approximately 32 per cent of the respond- ing firms raw product supply source came from cow beef sources. Ninety- three (93) per cent of the firms reported that their beef supply came from domestic sources. Order buying via telephone was the most common method of securing raw products. The average number of accounts serviced by responding firms was 568 accounts, although 79 per cent of the firms serve an average of 100 to 500 accounts. The most important outlet for the processing firms' finished products was "in-service waitress restaurants," by institutions, other, hotels, and self-serve steak houses.* A.model of three equations was specified to forecast the number of: (1) beef cows on U. S. farms, (2) milk cows on U. S. farms, and (3) the estimated total cow slaughter. The equations were estimated by the ordinary least squares method utilizing time series data from 1954-1974. The model predicted 46,899,000 head *The various sizes of responding processor and purveyor firms served a variety of food service outlets; no conclusive pattern of product disposition existed. Paul L. Kram, Jr. of beef cows on farms for January 1, 1976 and 48,281,000 head for January 1, 1977. The number of milk cows on farms January 1, 1976 was estimated at 11,138,000 head and 11,042,000 head for January 1, 1977. The model estimated the annual cow slaughter for 1975 at 7,999,000 head and 8,447,000 head for the year 1976. The findings of this study suggest the increasing interdependence of the participants of the vast and complex beef production and market- ing system. The meat purveyors are a specialized and important link in the meat industry in terms of volume of meat processed and handled. The system participants should be aware of the factors determining beef supply. The understanding of trends and forces behind change can pro- vide firm management with a basis for anticipatingand/or projecting future change. BEEF PRODUCTION AND PROCESSING: RELATIONSHIPS FOR THE SLAUGHTER COW MARKET Paul L. Kram, Jr. A THESIS Submitted to Michigan State University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE Department of Agricultural Economics 1975 ACKNOWLEDGMENTS I would like to express my sincere thanks to the numerous peOple who assisted, advised, and encouraged me throughout the duration of my graduate program. Acknowledgment is due to: Dr. Harold Riley, Dr. Lester Manderscheid and the Department of Agricultural Economics in appreciation for their financial as— sistance, academic guidance, and the use of departmental facilities. Dr. Gerald Schwab, my major professor, who provided valuable guidance and counseling throughout this study. Dr. John Ferris and Pam Marvel who provided advice and counsel throughout the course of this study. Dr. Estes Reynolds and Dr. John Allen for their assistance in the research project. Ms. Margaret Huston, Margaret White, Ms. Betty Peasgood for their valuable assistance in preparing the manuscript. My family and Jane Lynch, whose patience, understanding, and encouragement I am deeply grateful. ii TABLE OF CONTENTS LIST OF TABLES AND FIGURES . . Chapter I. INTRODUCTION . . . . . . . . . A. B. C. Problem Setting . . . . . . . . . . Thesis Objectives . . . . Plan of Study . . . . . . . . . . . . . . II. DESCRIPTION OF THE BEEF PRODUCTION INDUS TRY . O O O O O O O O O O O O O O O O O A. B. Introduction . . . . . . . . . . . . . . Physical Determinants of Beef Production . Trends in Beef and Milk Cow Numbers . Structure and Changes in Beef PrOduction . 1. Beef Cow—Calf Operations . 2. Feeder Calf Supply . . . . . . . . . 3. Cattle Feeding . . . a. Uncertainties in Cattle Feeding b. Relationship of Margins to Net Returns . . . . . . . . . . . Economic Relationships of the Beef Sector 1. Demand for Beef 2. Supply of Beef . 'The Cobweb Model . . . . . . . . . . . . Economic Activities of the Beef Production Process . . . . . . . . . . . . . iii Page viii 10 14 16 18 18 19 20 21 23 24 Chapter, H. III. BEEF A. F. Page 1. Beef Breeders: Relationship of Activities to Total Beef Supply . . . . . 25 2. Feedlot Operators: Relationship of Activities to Total Supply . . . . . . . 30 3. Cattle Slaughter and Total Beef Supply . . . . . . . . . . . . . . . . . 31 a. Steer and Heifer Slaughter . . . . 31 b. Beef Cow Slaughter . . . . . . . . 33 c. Dairy Cow Slaughter . . . . . . . . 33 d. Bull Slaughter . . . . . . . . . . 34 e. Imports . . . . . . . . . . . . . . 34 Summary . . .j. . . . . . .4. . . . . . . . . . 34 PROCESSORS AND PURVEYORS AND THEIR FUNCTIONS . . 36 Introduction . . . . . . . . .4. . . . . . . . 36 Review of Literature . . . . . . . . . . . . . 37 An Overview of the Meat Packing and Processing Industry . . . . . . . . . . . . . . 38 Food Service Establishments . . . . . . . . . . 41 1. Franchising in the Food Service Industry . . . . . . . . . . . . . . . . 43 Background in Describing Meat Purveyors . . . . 44 1. National Association of Meat Purveyors . 46 2. Organization of the Study . . . . . . . . 46 3. Collection of Data . . . . . . . . . . . 48 4. Breakdown of Responses . . . . . . . . . 48 Analysis of Information . . . . . . . . . . . . 51 1. Production Aspects . . . . . . . . . . . 51 iv Chapter Page a. Operation Type . . . . . . . . . . 51 b. Raw Product Form . . . . . . . . . 51 c. Production Line Activity . . . . . 52 d. Average Weekly Production Composition . . . . . . . . . . . 53 e. Total Pounds Processed Per Week .‘ 57 2. Supply Logistics . . . . . . . . . . . . 57 a. Raw Product Supply Origins . . . . 57 b. Geographic Supply Source .-. . . . 61 1. Domestic Geographic Origins of Beef Supply . . . . . . 62 c. Raw Product Purchasing . . . . . . 65 d. Purchasing on Contract . . . . . . 66 e. Storage Arrangements . . . . . . . . 66 f. Method of Securing Raw Product . . 66 g. Firm Size Relative to Competitors 67 3. Product Disposition . . . . .-. . . . . 67 a. Accounts Normally Serviced . . . . 67 b. Disposition of Product: Accounts semi-cad O O O O I O I O O O O O O 68 4. Cross Tabulations . . . . . . . . . . . 72 a. Raw Product Types Used by the Various Operations . . . . . . . . 72 b. Average Total Pounds Per Week by Operation Types . . . . . . . . . 74 c. Use of Physical Tenderizers and Vegetable Enzymes by Operation Types 0 O O O 0 O O O O I O O O O 77 Chapter d. Grade of Cattle Bought by Operator Types from Packers or Cattle Sellers . . . . . . . . . e. Use of Cow Beef As a Supply Source for Operation Types . . . f. Disposition of Finished Products by Size of Firm and Typical Product Grades . . . . . . . G O smry O O O O O O O O O O O O O O O O C IV. DEVELOPMENT OF A PREDICTION MODEL FOR FORECASTING ANNUAL COW SUPPLY AND SLAUGHTER . . . . . . . . A. IntrOduction O O O I O O O O O I O O O O O B. Relationship of Cow Supply and Slaughter to Meat Purveyors and the Food Service Industry 0 O O O I O O I O O 0 O O 0 O O O C. Definition of Variables . . . . . . . . . . D. Development of the Supply Functions: Equations to be tested . . . . . . . . . . 1. Number of Beef Cows on Farms . . . . . 2. Number of Milk.Cows on Farms . . . . . 3. Estimated Total Number of Cows Slaughtered . . . . . . . . . . . . . . 4. Forecast of Beef and Milk Cow Supplies 5. Forecast of Total Cow Slaughter . . . . 6. Comments on the Model . . . . . . . . . a. Consideration in Projecting Long Range Supplies . . . . . . . 7.' Conclusion . . . . . . . . . . . . . . 'v. SUMMARY, CONCLUSIONS, AND IMPLICATIONS . . . . . . A. smry O O O O 0 O O O O O O O O O O O O O 1. Objectives of the Study . . . . . . . . vi Page 78 79 8O 84 89 89 89 9O 91 91 97 103 107 111 112 113 113 115 115 115 Chapter B. C. BIBLIOGRAPHY APPENDIX A APPENDIX B APPENDIX C The Beef Production Industry . . . Cow Calf Operations . . . . . . . . Cattle Feeding Operations . . . . . Beef Processor and Purveyors and Their Functions . . . . . . . . . . a. Relationship of Meat Purveyors and Processors to the Meat Pack- ing Industry 0 O O O O O O O 0 0 Production Aspects . . . . . . . Supply Logistics . . . . . . Disposition of Finished Products to the Food Service Industry . . Development of a Prediction Model for Forecasting Annual Cow Supply and Slaughter . . . . . . . . . . . Conclusions and Implications . . . . . . Possible Future Studies . . . . . . . vii Page 116 117 117 118 118 119 120 121 122 123 125 126 130 137 142 Table 11.1 o II-2 . II-3 . III-1 o III-2 . III-3 . III-4 . III-5 . III-6 . III-7 . III-8 . III-9 o III-13. III-15. LIST OF TABLES AND FIGURES Beef cowhcalf operations in the United States: inventories and average herd sizes for 15 leading states . . . . . . . . . Farms with beef cows, by size of herd and regions, 1964 and 1969 . . . . . . . . . Number of cattle marketed and percentage by two feedlot capacity groups by regions, 1962,1967,1972 . . . . . . . . . . . Structure of meat packing and processing industries, by type and size . . . . . . Structure of meat packing and processing industry, by states, November 1973 . . . . Breakdown of responses to the questionnaire . Beef processed . . . ... . . . . . . . . . . Summary of raw product supply sources . . . . Geographic supply origins . . . . . . . . . . Domestic beef supply origin . . . . . . . . . Disposition of finished product . . . . . .4. Raw product types used by the various operations . . . . . . . . . . . . . . . Average weekly production by processor firms Use of tenderizees and enzymes by operation type 0 O C O O O O O O O O O O O O O O O O Cattle grade bought by various operations-. . Use of cow beef as raw product source . . . . Disposition of finished products by size Of firm 0 O 0 O O O O O O O O O O O O O O O O Disposition of finished product by typical product grade bought by purveyors and proces- sors from cattle sellers or packers . . . . . viii Page 11 12, 13 17 39 4O 49 54 58 61 62 69 73 75, 76 78 79 8O 81 82 Table IV-1 IV-2 IV-3 Figure II-l II-Z III-1 III-2 Number of beef cows in farms, January 1 . Number of milk cows on farms, January 1 . Estimated total of cows slaughtered . . . Flow chart of beef producing industry . . Beef production process relationships: conceptual framework . . . . . . . . . Distribution of total response to the questionnaire . . . . . . . . . . . . . Domestic geographic origins of beef supply ix Page 108 108 108 26 50 63 CHAPTER I INTRODUCTION Problem Setting Livestock enterprises are of substantial importance to the domestic farm economy and meat is central in the American diet. Tight feed grain supplies, increasing demand for beef over time, and government price controls during 1973 are but a few of the acknowledged ingredients to the problems of erratic price move— ments of beef over the last few years. The consequences of these movements have included significant losses to cattle producers while injecting considerable price and cost uncertainty into the beef production and marketing system. The U.S. cattle population has been increasing and changing in mix over the past twenty years. Dairy cow numbers have experi— enced a continuous decline since the early 1950's. Possible ex— planatory factors are increased per animal productivity, substitute non-dairy products, and a resultant reduced demand for dairy prod— ucts. On the other hand, beef cattle numbers have been increasing rapidly and consistently since 1950. USDA data indicates that on January 1, 1975 there were 11,217,000 milk cows on U.S. farms while beef cows numbered 45,421,000 compared to 1955 when milk cows numbered approximately 22,000,000 and beef cows 24,966,000 head. Livestock convert many kinds of feeds into palatable materials for absorption and assimilation by humans. In this Country, livestock consume corn and other grains that are often of a quality suitable for human consumption. Still, about 60 per cent of the feed consumed by livestock, mainly grasses and other roughages, is inedible by humans [1,p.1].1 The term "livestock-feed relationships" refers to both physical and economic interrelationships between livestock and feed. The quantity of livestock production is closely associated with quantity of available feed. Thus, when supplies of feed are large, feed costs decrease, ceteris_paribus, and livestock production may also increase. In 1973 and 1974, weather conditions contributed primarily to the decreased production of agricultural feedstuffs. At the same time, increasing domestic and world demand for feed grains were impacting on the feed grain situation. Consequently, feed costs for livestock producers soared. The American National Cat- tleman's Association statement for the Agriculture and Food Eco- nomic Summit Conference in September, 1974, indicated that the cattle industry incurred substantial losses in 1973-1974 due to the cost-price squeeze [24,p.6]. The U.S. average corn price for August, 1972 was $1.65 per bushel. In August, 1974, the U.S. average corn price was $3.45 per bushel, 51 per cent higher than in 1972. Interest expense in 1974 increased 40 per cent since 1972. By September of 1974, the cost of adding a pound of grain to a steer in a feedlot averaged 60 cents, compared with 30 cents 1Bracketed number refers to items listed in bibliography. The second number indicates the page location within that reference. in late 1972 [24,p.6]. The other side of the price-cost squeeze was the cattle price of choice steers at market. In September, 1972, the price of choice steers at Omaha was $34.28 per hundredweight, and $43.35 per hundred- weight for September, 1974. The ratio of market beef prices to corn prices is known as the beef-corn ratio. This represents the rela— tive profitability of feeding corn to cattle. Thus, the beef-corn ratio, which is calculated by dividing the market beef price by the price of corn per bushel, declined from 20.7 in September, 1972 to 12.5 in September, 1974. Thus, the beef industry is faced with a complex set of emerg- ing issues which include the world food situation, higher and more volatile grain prices, volatile beef prices, and changing consumer demand in reaction to these beef prices and to their own income goal. The fed-beef industry cannot survive in the long run if production losses continue as witnessed in recent time. In short, these types of relationships suggest significant changes ahead for the cattle feeding industry. The food service industry consists of hotel, restaurant, and institutional food sales. This industry accounts for about 35 per cent of all wholesale meat packer sales [22,p.189]. "By mid-1972, the food-away-from—home industry was described as a $40 billion industry. It has been estimated that in 1969 it required 'more than 34 billion pounds of feed to satisfy the American public's eating-out appetite ... (or) almost 20% of all the food produced in the U.S.'" Since the food-away-fromrhome market historically "has been viewed as a part of or an adjunct of the broad grocery market, it is virtually impossible to verify either size estimates or growth rates. Suffice to say that this industry is huge, important, and growing rapidly." [30,p.l] The food service industry and consumers are also adjusting to cost-price squeeze conditions. Although per capita consumption of beef rose from 85 pounds in 1960 to 114 pounds in 1970, per capita consumption declined approximately 6 pounds per capita in 1973 as a result of consumer adjustments to higher meat prices. However, beef consumption in 1974 rebounded to a record high of 116 pounds per capita. The USDA projects per capita beef consumption for 1980 to be 127 pounds [27,p.l]. With prices for restaurant meals and snacks rising nearly as much as groceries, the all-food retail average for 1974 is expected to be up 15 per cent from 1973 [26,p.3]. Because of these many changes and interactions occurring in the beef industry, various types of steak house and beef restaurant Chains are trying to assess these implications for their future business success. Within this context, the future supply and demand for beef is a current topic of importance for all participants of the Beef Pro- duction and Marketing System. Two groups of participants whose in- terest in how various changes will affect their respective activities are the meat purveyors and the food service industry. The essence of the problem to be investigated in this study is: Who are the meat purveyors and the food service industry? What are the relationships between meat purveyors and food service estab- lishments? How do the implications for intermediate future beef B. supply and demand forecasts affect these participants? Thesis Objectives Investigation of the research problem involves the following research objectives: 1. To describe the beef producing industry with respect to: a) The changes taking place in the last twenty years. b) The implications for future supply of beef. 2. To describe and analyze the functions performed by repre- sentative firms serving the beef needs of the food-away- from—home market. 3. To formulate a model for cow beef numbers and slaughter supply which would help predict one of the important supply sources for meat purveyors and food service outlets. ‘ Plan of Study The study is divided into four major parts. Chapter 11 describes the structural framework of the beef production chain and corresponding fundamental changes taking place. Chapter II describes and analyzes the functions performed by representative firms serving the needs of the food-away-fromrhome market. In- formation gathered is based on previous research and the results of this project's questionnaire. Chapter IV conceptualizes and formulates a simple econometric model for cow beef supply and slaughter. Empirical data will be used to test the apprOpriate- ness of a particular functional form of the supply equation. The final chapter summarizes the findings of this study and their impli— cations. A. CHAPTER II DESCRIPTION OF THE BEEF PRODUCTION INDUSTRY Introduction As McCoy [22] points out, it is important to know the current situation at any given time, but of greater importance is an under- standing of trends and forces behind Change. Knowledge of this sort provides a basis for anticipating or projecting future changes. Market outlook, a subject of substantial interest among producers, basically is an attempt to evaluate the impact of ever Changing market supply and demand factors on livestock prices. The beef producing industry has been characterized by various changes throughout the production stages. The ultimate result of these changes has been an increased beef supply over the last twenty years. The objectives of this chapter are: 1. To describe the basic structure of the beef producing industry. 4 2. To discuss recent production changes. 3. To set forth the economic relationships between feeder cattle, fed cattle and cow numbers which will serve as a partial basis for the beef cow supply analysis pref sented in Chapter IV. B. Physical Determinants of Beef Production Trimble [32,p.7] analyzes the physical determinants of total beef production. Basically, the quantity of beef supplied for any particular year is related to the number of animals held in farm inventories for production purposes and the number of pounds of beef each animal produces. Between 1930-1971, the increased beef supply over time has been the result of increasing cattle numbers and increasing productivity of the cattle herd. Trimble [32,p.8] presents the functional relationship between quantity of beef sup- plied, cattle numbers and the herd productivity in a production function relationship: Quantity supplied 8 F (cattle numbers and productivity). Productivity includes farm slaughter and the change in liveweight of the existing cattle inventories. The most important factors which have contributed to increased productivity in the past have been: 1. Increased calf drop percentage. 2. Decreased death losses. 3. Increased number of animals held to mature size. 4. Increased number of beef cattle in the total herd. 5. Increased average dressed weights. 6. Increased number of cattle fed. The productivity measures reflect technical efficiency in beef production. Major areas for further improvements will likely come from areas such as performance testing, hybrid vigor, reproduction, animal health, and forage production. Thus, to enlarge the future supply of beef may require much greater cow inventory to produce feeder calves which are fed to produce the type of beef customarily demanded by consumers. Trends in Beef and Milk Cow Numbers Before 1950, there were more milk cows than beef cows in the United States. Beef cow numbers first exceeded milk cow numbers in 1954 and the difference has been increasing ever since. The number of beef cows has more than doubled in the last twenty years, increasing from 16.7 million in 1950 to 45.4 million in 1975 [14,p.6]. The Southeastern states are rapidly assuming a major position among cattle producers, with a twenty year increase of 6.0 million cows and a fourth of the present national total. In 1950, milk cows numbered approximately 23 million head whereas by 1975, milk cows declined to 11.2 million head. The decline in the number of milk cows can be related to decreased per capita consumption of dairy products and to increased pro- duction per cow. Per capita consumption of milk in all dairy products fell from 653 pounds in 1960 to 564 pounds in 1970 [27,p.5]. Milk production per cow averaged 7,002 and 9,388 pounds in 1960 and 1970, respectively. Structure and Changes in Beef Production It is relatively difficult to generalize the entire U.S. cattle producing industry. But the important economic relation- ships may be clarified through the use of Figure II—l. Rectangles represent variables. Arrows show the direction of influence among variables (one-way or two~way), with heavy lines representing the critical flow of beef through the production system and the dashed Figure II-l L TOTAL SUPPLY I OF BEEF _ R \ \ DOMESTIC IMPORT SUPPLY SUPPLY K ' \ \ \ \ \ \ \ FED BEEF NONFED SUPPLY BEEF SUPPLY IK N \ \v CULL STOCK VEAL CALVES T u ‘\ I - BEEF cow \ HERD \ \ ' ‘ \ \ BEEF ‘p$_ FEEDER DAIRY EEDLOT CALVES é' - - - - HERD Figure II-l: Flow chart of beef producing industry. 10 lines indicating the less predominant or occasional paths of in- fluence of beef through the production system. 1. Beef Cowaalf Operations The cowbcalf Operations supply the feeder calves for the cattle feeding industry. These operations have maintained, for the most part, traditional production methods. The beef cow herd has been typically characterized as a relatively small sized production unit which is of a supplementary income nature. 7”” "””“”';gb1e II-l shows that on February 1, 1974, 15 states ac- counted for almost 70 percent of the total U.S. beef cow herd. On December 31, 1969, the average herd size in the U.S. was 26 cows, and average herd size exceeded 100 cows in only three of the 15 leading states. Thus, cowbcalf operations are char- acterized as relatively small and widely dispersed. Beef cow systems include cow-calf, cowhyearlings and various combinations of the two, with a finishing program some- times integrated onto the same farm or ranch. In the cow-calf enterprises, calves are usually sold at a weight of less than 550 pounds. In the cow-yearling enterprise, the calves are held longer and grown further on pasture or other crap roughages to weights as high as 800 pounds. Table II-2 shows the number of farms with beef cows by size of herd. There seems to be some trend toward farms with larger beef herds, especially for the Corn Belt and Lake State regions. Yet, the trend toward larger production units in the beef cow- calf industry has not been as pronounced as it has been in beef Table II-l. Beef cow-calf operations in the United States: and average herd sizes for 15 leading states. Inventories December 31, February 1, 1974 1969 Percentage of Beef cow total U.S. Cumulative Average inventory inventory percentage herd size Texas 6,470,000 15.1 15.1 82.5 Okalahoma 2,594,000 6.1 21.2 57.8 Missouri 2,379,000 5.6 26.8 37.2 Nebraska 2,248,000 5.2 32.0 73.0 Kansas 2,058,000 4.8 36.8 59.3 South Dakota 2,050,000 4.8 41.6 76.6 Iowa 1,790,000 4.2 45.8 36.6 Montana 1,746,000 4.1 49.9 153.0 Mississippi 1,285,000 3.0 52.9 67.0 Kentucky 1,282,000 3.0 55.9 34.4 Florida 1,247,000 2.9 58.8 199.0 Tennessee 1,178,000 2.8 61.6 33.5 North Dakota 1,125,000 2.6 64.2 74.6 Colorado 1,125,000 2.6 66.8 106.1 Arkansas 1,096,000 I 2.6 69.4 54.0 Total U.S. 42,874,000 100.0 100.0 26.0 Source: United States Department of Agriculture, Statistical Reporting Service, Crop Reporting Board, Cattle, Washington, D.C., February 1, 1974. U.S. Bureau of Census, Census onggriculture, 1969, Volume V, Special Reports, Part 9, Cattle, Hogs, Sheep, Goats, U.S. Govt. 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Numerous studies indicate that beef cow operations are low profit in nature and can be a viable undertaking only where there are large amounts of under-utilized roughages which can be used by beef cows at a very low cost.l! Trimble [32,p.72] suggests that the unprofitability of an investment in a beef cow, when both fixed and variable costs are included suggests that the most important investment decision does not involve the land and other fixed factors that are used to sup- port the cow. The relevant investment decision concerns the addition of a cow to an existing herd, or the substitution of a beef cow herd for an enterprise that uses the same fixed resources. Trimble's data pointed out that investment in a beef cow will generate revenue sufficient to cover all fixed and variable costs and provide a return on invested capital equal to the firm's cost of capital only if relatively high calf prices and low costs of capital exist. 2. Feeder Calf Supply The potential supply of feeder calves in any given year is equal to the total production of calves from all beef and milk cows, plus imports, less calves needed for other purposes which includes calf veal slaughter and replacement stock. All of the steer calves and a majority of the heifer calves produced by the beef and dairy cow herds are available lJNumerous studies are listed in the bibliography that have reached this type of general conclusion. See (3, ll, 19). 15 for placement in feedlots. The relationship between feedstuff and beef prices affect the degree of culling and the change in beef cow numbers. Beef heifers are needed for herd replacements and expansion. Dairy heifers are used for herd replacements, expansion, and veal. The impact of dairy-beef is limited due to declining dairy cow numbers, slaughter of veal male dairy calves, and reluctance to feed out due to relatively low quality grading of dairy beef. Some male animals are needed for breed- ing purposes in beef and dairy operations, but this number is small. The inventory of bulls amounts to about 5 per cent of cow numbers [14,p.13]. Estimating the number of calves that will become available as feeder cattle is a difficult task. One method that could be used as a trend indicator would be to assume a proxy set of production efficiency measures and utilize the January beef cow inventory figures published by the USDA. For example, if one takes the number of beef cows on hand January 1, assumes a 93 per cent calf drOp, a 4 per cent death loss, a 20 per cent replacement rate, and a l per cent death loss in replacements, the number of calves available as feeder cattle can be esti- mated as 68 per cent of the number of beef cows on hand. Many factors affect the number of cattle actually moving into the final feeder calf supply. Among these factors are: the number of beef and dairy calves slaughtered as nonfed beef; difference between estimated and actual rates of calvings; the extent of cow cullings; the need for breeding herd replacements; l6 and death losses. Cattle Feediqg The beef cattle feeding industry has grown rapidly since World War II as the number of fed cattle marketings has more than doubled [14,p.3]. This growth has been based upon a readily available supply of feed grains especially abundant in the Corn Belt. More than half Of the nation's cattle feeding is in six plains states - Texas, Oklahoma, Kansas, Nebraska, Colorado, New Mexico [23,p.l]. The notable trend in the past ten to fifteen years has been increased beef feeding conducted by decreasing numbers of producing units. The number of small feedlots (capacity of less than 1,000 head) has decreased during the 1962-1972 period while the number of large feedlots (capacity of 1,000 head or more) has increased [32,p.27]. As pointed out by Trimble [32,p.27], the Change in number of cattle marketed by feedlot size has been more dramatic than the change in feedlot numbers, as illustrated in Table II-3. The proportion Of cattle marketed by large feedlots has in~ creased from 37 per cent in 1962 to 62 per cent in 1972. This 62 per cent fed by only 2,089 producing units while the re- maining 38 per cent was fed by 151,347 producing units [32,p.27]. The Northern Plains, Southwest and Mountain regions have in- creased their proportion of cattle fed at the expense of other regions. Research findings have attributed the trend towards w.ao c.m¢ o.cm ~.wm q.qm ¢.mo moumum Nu o.mm m.qm m.om o.m n.n n.m oamaomm n.am m.wn ~.so m.» ~.HN m.~m damuoaoz m.nm N.aa o.¢w m.~ w.w o.oH umosnusom «.mo a.¢¢ m.m~ w.om H.mm H.¢n moamHm ononuuoz N.HH o.w w.¢ w.ww o.~a ~.nm uHOm oaou 5.x m.n N.m m.H¢ “.mm w.¢a mwumum mama unmuuom macs no case ooo.a same ooo.a mo muaommmo sues muoaommm Home: huwumnmo nuwa muoaommm ha vmumxamz mauumo mo uaooamm an wouoxamz OHuumo mo oomoaom mmm.sa mos.s ms~.m ma~.oa mam.aa msa.m museum ma ~om.~ mmm.~ smo.u mm oea mam oamaomm oas.~ mms.a ass was sea was manages: mmo.o Non.N msm.a «ma New New ummsnuoom wmm.¢ m¢N.N ems wmm.~ omm.m wm~.N maaoam duosuuoz ANN wmm 0mm an.m 00¢.o mnm.e uamm ouoo mma moa mm ssm.a mmm.a moo.a saunas mama swam ooo.a aa aopasz Numa noma mama Nnaa mama Noma who: no comm ooo.a comm ooo.a soawmm mo buaommmo anus muoavoom ha monoxunz OHuumo mo awaanz Home: huwummmo no“? muoavoom ma umuoaamz_maunwo as usaauz .Nnma .nwmn .NomH .meHwou hm mason» huaumamo uoawoom oku mp ammunooumm can ouumxama mauumo mo nonauz .MIHH manna 17 18 much larger feedlots to the economies of size characteristics of beef feeding operations which have resulted in lower average costs of productionrz/ a. Uncertainties in Cattle Feedigg The many uncertainties in cattle feeding, its highly specialized nature, and the large required investment in fixed facilities and feeder cattle make it an unusually high-risk enterprise. Basically, there are three broad groups of uncertainties: technical, price, and others. Technical undertainties are those related to physical aspects of production and in general, affect costs of pro- duction. Price uncertainties are those resulting from changes in prices of inputs and outputs. Substantial change in the price of slaughtered cattle is one of the most impor- tant factors affecting net returns of cattle feeders. Other uncertainties include monetary policy as it affects interest rates, fiscal policy as it affects real disposable income, and management and behavioral variables. b.. Relationship of Margins to Net Returns ' Net returns from cattle feeding are largely dependent upon achieving two favorable margins. The first, a feeding margin, is the difference between the feed cost per pound gained and the price received from the gain put on cattle. .glNumerous studies are listed in the bibliography that have reached this general conclusion. In particular, see (7, 13, 15, 18). 19 This margin can be adversely affected by an increase in price of feeds or a decrease in price of slaughter cattle. The second, a price margin, is the difference between pur- chase and selling prices per hundredweight. A drop in market price for slaughter cattle can be disastrous for operators who buy heavy feeder cattle and then must bear the burden of a negative price margin on 75 to 80 per cent of the livestock weight sold. A negative price margin does not necessarily indicate a loss, as it may be more than compensated if liveweight gains are a high proportion of final sale weight and the feeding margin is favorable. Conversely, positive price margins may not reflect a profit if they are offset by a poor feeding margin.* E. Economic Relationships of the Beef Sector Up to this point, the discussion has dealt with the structure of the beef cattle sector and the fundamental structural changes oc- curing at the various levels. One of the Objectives of this study is to develOp a simplified econometric model for cow beef supply ——__..-a__, and slaughter,nwhichgwould help-tonprediCt one of the important I. if...“ M-"—1-‘- 1 “.a supply sources for meat purveyors and their market, the Food Service Industfy;’/,,flc A quantitative approach to either price analysis or forecasting M is to consider the relationships among variables. Tomek and *However, neither of these margins reflect investment costs which also affect net returns of cattle feeding. 20 Robinson [31,p.3ll] state the following about model building: "Model building may be viewed as having two parts. One involves the specification of the economic model, that is, the general economic relationships. Economic theory can be thought of in terms of functions and certain variables within these functions. The second part of model building involves the explicit defini— tion of equations which are to be estimated. For example, what variables appear in a particular equation, and how are these explicitly defined... Out of the answers to these and other similar questions, explicit equations are defined." A model should be consistent with the logic and theory under- lying the commodity sector being analyzed. A model of a particular economic sector may be thought of as one or more equations that describe the important relationships among the variables. Demand and supply functions are examples of particular economic relationships. 1. Demand for Beef From consumer demand theory, retail (consumer) demand for beef is postulated as a function of the price of beef, prices of close substitutes, prices of all other goods, con- sumer's real income, the number of consumers, and exports. The quantity of beef consumed and the average retail price of beef could be specified as being jointly dependent (endogenous) variables, as Unger suggests [33,p.60]. While a complete analysis of cattle demand might involve looking at each of the major end products — steak, roast, ribs, briskets, stew, ground beef, etc., aggregating beef products into beef per §g_will facilitate explaining the initial demand- supply relationships. 21 Thus, the first part of a static equilibrium situation, which simultaneously determines price and quantity, can be defined by two equations with the third equation specifying that in equilibrium quantity demanded must equal quantity supplied. Equation II-l. Demand for Beef is represented as: d QBEEFt I f(PBEEFt, POMEATRt, DI/CPI, PPLN, BEXP) where: QBEEF: = Quantity of beef demanded in time period t PBEEFt = Retail price of beef in time period t t is a time parameter in years. t - one year. POMEATRt - Price of other meat at retail (weighted average of pork, lamb and mutton, veal and poultry meat) deflated by Consumer Price Index. Disposable personal income per capital DI/CPI = ($) deflated by the Consumer Price Index (1967 - 100) PPLNt - Population in time period t BEXPt = Beef exports in time period t Sgpply of Beef The number of beef cattle which beef producers plan to keep on farms is partially determined by the expected price to be received for feeder calves or slaughter animals. A realistic first step towards a supply model for beef consistent with the peculiar nature of the product is the disaggregation of total beef slaughter into several components - steers, heifers, cows and bulls. 22 If we abstract from uncertainty, assume that firms maxi- mize profits in a competitive industry, and assume given fixed technological conditions of production; output is related to variable input product prices, to substitute product prices, and to investment cost of capital items necessary for pro- duction. The major factors thought to influence beef supply are incorporated in the following relationship: Equation II-2. Supply of Beef s QBEEF‘t = f(NBCt_1, PSt_1, PFCt_1, PFGt_L, RFt) where: s QBEEFt - Quantity of beef supplied in time period t NBCt_1 = Number of beef cows on farms January 1, 2 years old and older PSt_1 = Average price of choice steers at Omaha ($1/cwt) in time period t-l PFCt_1 = Price of good-choice feeder calves at Kansas City in August to December ($l/cwt) divided by Index of Prices paid by farmers (1967 - 100) (IPP) in year t-l PFGt_1 - Annual Average feed grain price paid by Y farmers in time period t-l RFC - Range feed condition in year t (USDA 1 index) t - During time period t. t = one year. Lagged prices are used because many production decisions are made prior to the marketing year and lagged price is a reasonable proxy for expected price. While equation specifi- cation must emphasize the major factor thought to influence 23 supply, it is impossible to include an exhaustive set of vari- ables. Then according to economic theory, for equilibrium to occur, quantity demanded must equal quantity supplied as pre- sented by the following equation: Equation II-3. QBEEF: - QBEEF: The Cobweb Model The cyclical pattern in numbers of cattle kept on farms, amount of beef produced, and the beef price level are explained in terms of "inventory cycles, production cycles,' and "price cycles." The factors which generate these cycles have been regarded as closely related to each other. "The cobweb model provides a theoretical explanation of the cyclical components of certain price-quantity paths through time. Prices and quantities are viewed as being linked recursively in a causal chain. A high price leads to large production; the large supply results in.low prices, which in turn result in smaller production and so forth." [31,p.176] The cobweb model exemplifies a recursive system of equations where the endogenous variables are determined sequentially as a chain through time rather than simultaneously. Moreover, it ex- plains under specified conditions the movement of price and of quantities demanded and supplied around the hypothesized equili- brium price-quantity combination. This equilibrium point is determined by the intersection of supply and demand functions as producers and consumers react to price changes. Cycles are generated by lagged responses to changes in prices 24 or other external events. Lagged responses are called lagged endo- genous variables. Exogenous and lagged endogenous variables are grouped under the general heading of predetermined variables. Formal models incorporating such variables, especially lagged prices, have been developed which help to explain cyclical behavior [33,p.60]. Kim [16,p.25] notes that "the explanation of any cyclical phenomena in the strategic variables Characterizing the cattle industry should be based on a systematically developed set of hypotheses from the fundamental activities of economic agents rather than a blind application of any existing economic theorems to a set of time series data of these strategic variables." Economic Activities of the Beef Production Process Kim's [l6] dissertation provides a set of hypotheses to explain the fundamental economic activities of the economic agents Of the beef production system. The economic agents of the beef production system are the beef breeders (cow-calf Operators), feedlot operators, and slaughter- house operators. According to the vertical chain of the beef pro- duction process, the economic activities as stated by Kim [16,p.18] are as follows: v25<1a) The economic activities of beef breeders depend on the 'v .-.m'fi~-.... aggregate demand for feeder cattle and for slaughter cattle on one hand and the aggregate breeding herd supply maintained on the other. «;¥é’b) The economic activities of feedlot operators depend on 25 the aggregate demand for fed cattle (by slaughter-house operators) and the aggregate supply of feeder cattle (of various classes and grades). c) The economic activities of slaughter-house Operators depend on the aggregate demand for red meat (of various classes and grades) and the aggregate supply of slaughter cattle (of various Classes and grades). The vertical chain of the beef production process as stated by Kim may best be illustrated by Figure II-2. 1. Beef Breeders: Relationship of Activities to Total Beef Supply The number of beef cows on hand is the key variable in the M U.S. beef supply relationships [9,p.ll]. The number of beef — "ll—”w" -‘F' "H mm,uI-v:”r’» cattle which beef producers plan to keep on farms is partially determined by the prices expected to be received for feeder —-———- calves or slaughter animals. Changes in cow numbers are also W v—v related to random weather elements which affect range and pasture conditions and roughage supplies. Kim [l6,p.l7] describes the causal mechanism for beef breeder behavior: "There can be no doubt that a beef breeder (or beef breeders as a whole) maintain a herd of breeding animals over time in order to produce a series Of calf crops which in turn, yield a series of "econo- mic returns." "Nor is it difficult to recognize the multiple role of breeding females in the herd: at any given point in time a female can be viewed as (a) a finished good, (b) a good in process or (c) a piece of fixed capital (or durable input). This is perhaps most dramatically apparent for a young heifer. If she has been well fed, Figure II-2 BEEF PRODUCTION PROCESS RELATIONSHIPS Conceptual Framework Production Level DEMAND SUPPLY MARKET SYSTEM Demand for Supply of Red Meat Slaughter Cattle (Various Classes (Various Classes and Grades) and Grades) K. r :3 \ SLAUGHTER // IT \ HOUSE " \ ACTIVITIES / ‘ / I __T__I II Demand for Supply of Fed Cattle Feeder Cattle (BY Slaughter ./”(Various Classes House Operators) \ ._.__u__. / and Grades) , \ \ FEEDLOT / U l \ OPERATOR / l I \ ACTIVITIES . I II Demand for Feeder Cattle and Demand for K Slaughter Cattle \ 2 Aggregate / Breeding Herd ” Maintained BEEF BREEDER / ACTIVITIES " -' "‘ - "" "' ‘9 Dependency Relationships Derived Demands ‘ a~. Linkages in Production Chains Supply Determinant Relationship 26 27 she may be immediately marketable as medium or possibly better grade beef. Alternatively, she may profitably be fed intensively for a short period with a consequent increase in weight and possibly in grade. A third alternative is to retain her in the breeding herd to produce calves." Figure II—l demonstrates that factors which affect the beef — cow herd have effects on the whole system and ultimately change the total beef supply in subsequent time periods. If the number of cows in the breeding herd is increased during the current period, this will result in more feeder calves being born within the next year. This increased supply of feeder calves will move through the feeding system in the following year to be slaughtered as fed beef. Thus, a change in the size of the beef herd may take two or three years before it is reflected through final slaughter; but it may influence total supply for sometime thereafter. The same can be said for a reduction in the size of the beef breeding herd. Ferris points out that because the biological cycle in \ cattle stretches over several years, cowbcalf operators must ‘ anticipate selling prices wellgingadvagce. Changing feeder .xj cattle price is not likely to induce quick production adjust- ments by these operators in the short run. Theory would tell us that the number of livestock units can be changed in the short run and the long run. The tendency for supply curves is to become more responsive (flatter) as more time is allowed for adjustments. Hence, the time dimension is important in defining supply relationships, but it is dif- ficult to precisely define in terms of time units the meaning 28 of the very short run, the short run, the intermediate, and the long run as applied to supply. Since the form of the price response relationship is not known.it might be presumed to approximate a distributed lag with more recent prices having greater influence on their expectations than price in the more distant past. To get some measurement of this distribution, Ferris used the fol- lowing equation estimated by least squares using data for the period 1950-1972: NBCt a -9308 + 1.045 NBCt_ + 109.7 PFCt_2 + 25.41 1 (6080) (4.38) (.89) PFCt_3 + 52.16 FPCt_4 + 40.54 RFt_1 (2.29) (1.48) 2 R - .995 S.E.E. - 452 ( ) Numbers in parenthesis indicate the calculated value of the t statistic for each beta coefficient. If absolute value is greater than or equal to 2.11, the coefficient is significant at the 5 per cent level of significance. NBC - Number of beef cows on farms on January 1 in t year t (1000 head) PFC 8 Price of good choice feeder calves at Kansas City in August to December ($/th.) divided by the Index of Prices Paid by Farmers (IPP) (in year t) (1967 - 100) ' RFt - Range feed conditions in year t (U.S.D.A. index) According to Ferris [9,p.12]: "The long biological cycle and momentum effect is re- flected in the highly significant coefficient on NBC . Of particular interest is the pattern on the valfiég of the coefficients (and their significance) on PFCt_2, PFCt_3 and PFCt_4. As anticipated the value and 29 significance of the coefficient on PFC were the great- est. However, the coefficient in PFC - was larger and more significant than PFCt_3. A plauSISle explanation is that feeder prices may be more influential at the time a cowbcalf Operator is deciding on how many heifers to hold back. Normally, these operators would keep more heifers than they actually need for replacement purposes just to have some flexibility. But usually, most of the heifers to be sold as feeders are sold as calves rather than yearlings." In conclusion, the economic relationships between cow numbers and the other components of the total beef supply can be summarized as follows: 1. Number of cows on hand is the key variable in supply relationships as the increases or decreases in cow 32%;, herd numbers ultimately affect total beef supply in subsequent time periods. Number of beef cattle kept on farms is due largely to the price the cow-calf Operator expects to receive .J*_l for feeder cattle and slaughter cattle in present and subsequent time periods. Expected price is based on prices received in past time periods. The rate of change in cow numbers is indicative of the build-up or liquidation of breeding stock. Decisions to breed more cows are usually made about July 1. If feeder cattle and slaughter prices in ,:3// year t-3 are favorable, more cows are bred during .5 the summer of year t-2. This results in a larger calf crop in year t-l which is slaughtered in year "t". The economic relationship of cow numbers is specified 2. 30 in the equation: NBCt - a + NBCt_1 + PFCt-2 + PFCt_3 + PFCt_4 + RFt_1. (see previous page for variable definitions.) Feedlot Operators: Relationship of Activities to Total Supply The economic activities of feedlot Operators depend on the aggregate demand for fed cattle (by slaughter-house Operators), and the aggregate supply of feeder cattle (of various classes and grades). In recent years, fed cattle have represented about two thirds of total slaughter [lO,p.4]. The aggregate consumer demand for fed beef and beef by-products is translated through the retailer, wholesaler, and packer to the cattle feeder hime self. The feeder, in turn, transmits this demand back to the producer of feeder cattle. As Ferris suggests, [lO,p.l4], the cattle feeders must predict slaughter prices to determine what he can pay for feeders. For this reason, the demand for feed- ers is based on expected slaughter prices. The level of feed grain prices and the availability and price of hay and other roughages will also influence the demand for feeder cattle. The higher the feed costs.ceter18 paribus, the lower the demand for feeder cattle. Nonfed costs such as facility costs and outside investor behavior in the feeding business have a mixed effect on the feedlot operators. Large capital requirements for feeding cattle imply that interest rates might affect the demand for 31 feeder cattle [lO,p.l4]. An increase or decrease in cattle on Feed January 1 is as- sociated with a change in demand for feeder cattle. The annual feeder price of the preceding year is an important determinant of several January inventory variables: cattle on feed, number of cows and heifers on farms, and others. Cattle Slaughter and Total Beef Supply The economic activities of slaughter-house Operators depend on the aggregate demand for red meat (of various classes and grades), and the aggregate supply of slaughtered cattle (of various classes and grades). Ferris [lO,p.lZ] explains the relationship between the com? ponents of cattle slaughter and the total beef supply available to slaughter-house operators. Total U.S. cattle slaughter may be divided into two categories: 1) steer and heifer beef, and 2) domestic cow and bull beef plus imports. a. Steer and Heifer Slaughter The potential supply of steers and heifers for slaugh- ter originates primarily from the number of beef calves produced domestically, and to a minor extent, from the number Of dairy veal calves (mostly steers) dropped, and the number of feeder imports. The proportion of these steers and heifers actually carried to maturity will depend on such factors as the price of cattle, the price of feed, and range feed conditions. Nearly all male type calves are eventually sold for 32 slaughter as mature animals, except for those "fat calves" or "baby beef calves" sold at weaning weights of 500-600 pounds. About 30-40 per cent of the heifer calves are gen— erally retained as replacements for the beef herd, while most of the balance are fed out. Year to year changes in the proportion of heifer calves placed on feed lots depend on the relationship between the current demand for feeder cattle and expected future cattle prices. The rancher's decision to sell the heifer calf as a feeder or hold for- herd replacement or expansion purposes is influenced by expected cattle prices, available range and pasture feed, and availability and cost of other resources used by cow- calf enterprises. From the total supply of feeder cattle, total steer and heifer beef production is affected by the proportion of these feeders which go into feed lots and are classified as "fed cattle." Most steers and heifers move to slaugh- ter as "fed cattle," the nonfed component has been of minor importance [lO,p.lZ]. However, nonfed beef from steer and heifer sources may become more predominant at the retail level. This type of beef has been commonly called "economy beef" or "lean beef." Since cattle fed on grain tend to be marketed at heavier weights than nonfed steers and heifers, a change in the proportion of cattle fed would tend to change total pounds of beef supply. Also, the average slaughter 33 weights of fed cattle and nonfed cattle do vary yearly and quarterly. Slaughter weights tend to be heaviest in the winter, and lightest in the summer [lO,p.lS]. Weight vari- ations by cattle feeders is based on changing price expecta— tion response of beef and of feed costs. The other supply source of cattle is domestic cow and bull beef plus imports. In the 1960's, nearly all of this category went into boneless products, hamburger, and other processed beef products. However, this is changing in that meat technology is now capable of "fabricating" table cuts from cow beef. Beef Cow Slaughter As Ferris indicates [lO,p.l3], the size of the beef cow inventory becomes the base for establishing how many beef cows will be slaughtered. The length of time that a beef cow is held in a herd varies considerably. Cul- ling rate is highly dependent on the outlook for feeder prices and to some extent on range and pasture conditions and feed prices. Dairy Cow Slaughter Chapter I illustrated the nature of the U.S. dairy herd composition for the last twenty years. Year to year varia- tion in slaughter of dairy cows is usually small, especially in comparison to variations in beef cow slaughter. Culling rates for dairy cows are affected by milk prices, quality and price of feed grain and roughages, government regu- lations, and investment costs. Similarly, pasture conditions H. Summapy E. 34 also affect culling rate. Bull Slaughter Bull beef contributes a very small portion to total beef supplies. Bull beef has been running over 2% in total cattle slaughter and would be even higher in terms of beef pounds. Imports "U.S. imports of beef and veal have been affected primarily by 1) supply and price of domestic cow and bull beef 2) foreign trade of our own and other countries 3) range conditions and stage of build up of our liquidation in exporting countries 4) beef prices in other major importing countries." [lO,p.13] Factor two above refers to import quotas set by the U.S. government of foreign beef imports, exchange rates, trade policies of importing countries affecting the U.S. beef export situation. The tendency over time for imports is to increase when domestic production of cow and bull beef drOps off and decrease when domestic production increases. The combined total has not changed much from year to year [9,p.16]. This chapter provided a descriptive explanation of the beef pro— duction industry and accompanying structural changes over the last two decades. A growing cattle herd and increasing productivity of the beef industry have both contributed to the general increase in the supply of beef over time. As Trimble points out, various factors have 35 contributed to the beef industry's ability to increase productivity in the past. Many of these factors have been fully exploited (calving per- centage and death losses contributing to increased productivity). But, the importance of productivity gains relative to increases in the size of the cattle herd has decreased over time. As a result, future in- creases in the supply of beef are much more dependent on increases in the size of the cattle herd than in the past [32,p.137]. This chapter attempted to explain the economic relationships for the demand and supply of beef. The aggregate economic activities of the beef production system participants (the beef breeders, feedlot operators, and slaughter-house operators) underline the increasing interdependence of all participants of a vast and complex industry. Now that beef production process has been explained, what services are performed by those firms involved in preparing and supplying meat to various food service outlets of the hotel, restaurant, and insti- tutional trade? And what is their significance as a link in the total beef production and marketing system? To this topic we now turn. CHAPTER III BEEF PROCESSORS AND PURVEYORS AND THEIR FUNCTIONS Introduction The meat packing and processing industry is an integral link in the beef system which transforms a raw product, meat animals, into a marketable retail product. The firms responsible for supply beef needs to the food service industry are commonly referred to as purveyors or meat processors. Stafford [30,p.2] collectively refers to this group as "handlers." For clarification, the following terms are functionally defined: Meat packing companies — Firms that slaughter livestock and may or may not process meat animals. Meat Processing firms - Firms that do not slaughter livestock but may purchase carcass, primals, or sub- primals; and manufacture table cuts, sau- sage and other meat products for various outlets. Meat Purveyors - Firms that purchase carcass, primal or sub- primals and prepare and supply retail cuts for hotel, restaurant and institutional outlets. Boners - Firms that typically buy cow carcasses and break them down into lean, retail cuts for various outlets. The approach taken in this study utilizes the aggregate U.S. available information that describes those firms of the meat in- dustry who primarily cater to the food service industry, while 36 37 focusing on those U.S. firms where primary data could be gathered. The information gathered is based upon a questionnaire forwarded to various beef slaughter, processing and purveying firms which supply the needs of various food service establishments. Review of Literature While studies have been made concerning the commercial slaughter plants and the economics of meat packing [2,18], in- formation on firms in the meat purveying and processing business is generally lacking. According to Brasington [4,p.l], practi- cally all beef processing firms in Operation today, which he re- ' are less than 25 years old. fers to as "custom service houses,‘ This relatively young age suggests why our knowledge of this industry is quite limited. The Agricultural Research Service of the USDA has published two reports related to this area: Hotel and Restaurant Meat Purveyors-Improved Methods and Facilities for Custom Service Houses (1966) [5] Hotel and Restaurant Meat Purveyors-Improved Methods and Facilities for Supplying Frozen Portion Con- trolled Meat (1971) [4] Both reports are engineering studies that provide custom service houses with cost and efficiency guides for selection of work practices, and suggest methods and equipment that will reduce the cost or time to perform specific operations. In the area of frozen meat research, a Kansas State Univ- ersity Meat Research Team has studied frozen meat distribution, costs, acceptance, cooking and eating qualities [29]. Ezzell [8] found that about a 50 per cent saving in total meat retailing 38 costs could be made by shifting completely to frozen meat retail- ing. Stafford [30] examined methods and costs of distributing beef to the food service industry. An Overview of the Meat Packing and Processing Industry Before describing and anlyzing the questionnaire responses of those firms participating in this study, an overview of the structure of the meat packing and processing industry is in order. Industrial organization theory tells us that the structure of a relative market embraces such features as the number and size of buyers and sellers, the degree of product differentiation, the presence or absence of barriers to the entry of new firms, cost structure, and degree of vertical integration. The meat packing and processing industry is composed of many different types and sizes of plants. Wissman [9,p.l] stated that: "The Standard Industrial Classification (SIC) 2011 includes packing houses and slaughter plants of which the USDA reports a total of 1,420 plants in 1972 that achieve a liveweight kill of greater than 2,000,000 pounds per year. In addition, the meat processing industry (SIC) 2013 includes 1,297 plants of all sizes as reported in 1972. These plants are located throughout the U.S. with numer- ous plants located in each state." Given this classification system, the structure of the present industry summarized by Wissman is shown in Table III-l. The structure of the tap ten states by number of plants slaughtering, processing, and boning is shown in Table 111-2. These figures are derived from USDA Animal and Plant Health Inspection Service Directory figures. A further explanation may be found in 39 o.ooa o.ooH asm.a A huumoonH mmmmoamam mo madman mo mwwm mom mama HmuoH mo N umnaoz .Noumm4 umnanz .Noamq< mmwuumooaH mnammmooum w wowxomm mom: «0 muouoouum .HIHHH manna 40 Table III-2 Structure of Meat Packing & Processing Industry By States - November 1973 Top 10 States in Number of Plants: Slaughtering, Processing, Boning Approx. # of Plants Z of U.S. That: Total SLAUGHTER 1) Pennsylvania 112 15.3 2) Missouri 70 9.6 3) Nebraska 54 7.4 4) Texas 53 7.2 5) Minnesota 40 5.4 6) Oregon 34 4.6 7) Montana 28 3.8 8) North Dakota 28 3.8 9) New York 25 3.4 10) Washington 25 3.4 Total 469 63.9% PROCESS 1) Pennsylvania 212 9.6 2) California 205 6.7 3) New York 179 5.9 4) Missouri 155 5.1 5) Texas 114 3.7 6) Minnesota 96 3.1 7) Illinois 95 3.1 8) Nebraska 90 2.9 9) Washington 85 2.8 10) Ogegon 65 2.1 Total 1376 45.0% BONE 1) California 155 13.9 2) Illinois 75 6.7 3) Minnesota 69 6.1 4) Missouri 67 6.0 5) Nebraska 61 5.4 6) Oregon 60 5.3 7) Washington 56 5.0 8) Montana 44 3.9 9) New York 44 3.9 10) Texas 41 3.6 Total 672 59.8% Appendix A.1. 41 Food Service Establishments The Food Service Industry is a vast and complicated industry. The economic activities of the meat purveyors depend primarily upon the aggregate demand for red meat (of various classes and grades) by the Food Service Industry. This industry is a heterogeneous group of enterprises that can be classified into numerous segments. Kotschevar and Terrell [17,p.21] include the following types of food service facilities: 1. College food units a. Cafeteria service b. Coffee shop or snack bar c. Catering service d. Union buildings e. Faculty clubs f. Residence Halls Commercial Restaurants a. Service Restaurants b. Cafeterias c. Coffee shops d. Drive-ins e. Take-out—food Hospital Food Service Hotel and Club food service a. Essential Meals b. Food for or with entertainment c. Catering for special needs Employee food service Industrial lunchrooms a. Executive dining rooms b. Seated service c. Cafeteria d. Mobile and vending service 7. 8. 42 School food service Miscellaneous There are many other types of classification schemes for describing the functioning food service operations. Van Dress and Freund [36] classify them as: 1. 10. 11. 12. 13. 14. Separate eating places Separate drinking places Drug or proprietary stores Retail stores Hotels, motels or tourist courts Recreation or amusement places Civic, social or fraternal associations Other public eating places Factories, plants or mills Hospitals Sanatoria, convalescent or rest homes Homes for children, aged, handicapped or mentally ill Colleges, universities, professional or normal schools Other institutions Other food service outlets to consider would be those that function in elementary and secondary schools, the military services, federal hospitals, federal and state correctional institutions, in- transit feeding operations (e.g., planes, trains, ships) and board- ing houses. 43 Franchising;in the Food Service Industry While the United States Department of Commerce does not collect information on the number of beef restaurant Chains in the U.S. and the sales generated by their units, information is collected on fast food firms Operated as franchisers. The franchise method of distribution is a significant part of the current marketing system, creating more and more new business opportunities, new jobs and new services as well as eXport Opportunities. The fast food franchise restaurants posted sales of $9.8 billion in 1974, up from $8.5 billion the year before. And regardless of economic uncertainties in 1975, the leaders of this business expect an annual improvement in sales volume of nearly 18 per cent, compared with the restaurant industry's annual average of 9 per cent. This thriving trade, numbering 40,084 establishments on January 1, 1974, predicts further expansion of about 4,600 more units during 1975 [35,p.4]. Designed to serve good food at relatively low cost and provide uniformity in menu and service, the fast food operation is a technological innovation. It has become a computerized, standardized, and premeasured production machine. The structure of franchises in relation to all types of fast food restaurants is depicted in Appendix Table A.2. Further background information on fast food restaurants by activities in terms of numbers and sales dollar are found in Appendix Tables A.3 and A.4. 44 Background in DescribipgyMeat Purvgyors A primary objective of this research is to describe and analyze the functions performed by representative firms serving the needs of the food-away-from-home market. Those firms responsible for supplying the beef needs of the food service industry are commonly referred to as hotel-supply houses, purveyors or specialized meat wholesalers. This collective group of firms also includes inde- pendent purveyors, beef breakers, central commissaries and the specialized sales outlets of packing companies. Aggregation problems associated with defining the structure and functions of beef purveyors include: 1) Heterogeneous group of activities performed by meat pur- veyors serving numerous types of food service facilities. 2) Definition of "meat purveyor." Inconsistent definitions are employed in categorizing firm numbers and changes in number of these firms. As a starting point, Stafford [30,p.3] sheds light on the nature of beef: "Beef differs markedly from most manufactured products. Instead of starting with many new raw products, combining them into a finished good, and then distributing it, the beef distribution industry starts with a single complex product and produces many end products. Because of the nature of these products, much "manufacturing" or fabri- cating takes place throughout the system, thus the industry cannot be classified into the typical institutional frame- work of manufacturers, wholesalers and retailers ... each firm performs particular specialized marketing and "manu- facturing" functions and the interrelationships of the firms can be viewed as a channel of distribution ..." 45 Further, a typical channel of distribution as described by Stafford might be: "A packer located in the midwest sells quarters to a breaker in Boston. The breaker cuts the quarters into primal cuts, selling some - for instance, the chuck and a few rounds - to retailers; others, such as ribs, loins and remaining rounds to purveyors; and the items left, such as flank, briskets and trimmings to processors and renderers. The purveyors, loca- ted nearby, fabricate the ribs, loins and rounds into steaks, roasts and hamburgers and sell them to restaurants in Boston or other cities. The restaurants may do some extra trimming on the product received and then cook and serve it to custom- ers." While this is not a study in distribution channels, the previous section suggests the complexities and interactions of moving beef from slaughter to the customer's plate in food service establish- ments. A factor that has prompted this research effort is the growing importance of the meat purveying business. Brasington captures the industry's emergence saying: "The meat purveying business, already an important part of the meat industry, together with custom service houses, account for more than two thirds of the total volume of meat and meat products sold to the food service industry in 1966. The meat purveyors have had a spectacular growth within the past several decades, both in number of houses and volume of meat handled. The number of houses in 1964 was estimated as 1,000 - an increase of about 70 per cent since WOrld War 11." Another factor which has enhanced the competitive position of meat purveyors is the trend toward specialization and resultant in- creased efficiencies. Meat procurement for hotel, restaurant and institutional firms is an important function. The trade magazines of the various segments of the food service industry have discussed 46 the merits of buying precut meats for many years. Wanderstock [37,p.60] states: 2. "Changes in hotel and restaurant meat purchasing practices have been dramatic. There has been a decided shift from carcasses to quarters, to primal cuts, to prefabricated cuts, to portion control cuts, and even to precooked (rare, medium, well done) meat . "The only justification for buying carcass meat is when all parts of the carcass can be utilized in the food service operations. High labor costs and the relative unavailability of trained butchers in hotels and restaurants has led to the shift away from onepremise fabrication to purchasing ready to use meat from purveyors. These purveyors are able to utilize their expertise as well as the volume of meat processed to create a market for by-products which are of no use to hotels but can be sold through the appropriate channels." National Association of Meat Purvgyors The National Association of Meat Purveyors is a non-profit organization of Hotel, Restaurant and Institutional supply houses who purvey (supply) meats and other food items to food service establishments. This organization was founded in 1942 in an effort to cope with problems that would arise under the Emer- gency Price Control Act of 1942 and the Office of Price Admin- istration. The Association was successful in establishing the fact that the business of the hotel supply house was a distinct branch of the meat industry and performed essential services and functions, entitling it to a markrup higher than to a packer or wholesaler. The 1974 Directory listed some 400 members of the organization, located throughout the United States and Canada. nganization of the Study Data for this portion of the study were gathered by survey- ing meat purveyor firms throughout the United States by the 47 questionnaire method. No existing secondary data was available. The author felt that industry information was needed to answer some questions on this portion of the beef industry supplying the food service industry. Thus the problem was to secure industry participation. Time and money did not permit personally visiting and inter- viewing a large sample of meat purveyors throughout the country. SO with the cooperation and support of the National Association of Meat Purveyors, a list of all 1974 member firms was acquired with the understanding that all information forwarded by the respective firms would be considered private information, and not available for public scrutiny. The identity of each firm would remain confidential. Of special interest to the author were production aspects, supply logistics, and product disposition. Or essentially, from what sources was the raw meat product coming from and in what forms. How much processing and by whom was being ac- complished; and finally, who bought the finished product? Although only limited data was available on the cow-beef component of the total red meat beef supply, the author Shared the belief that cow slaughter was one of the principal beef raw product supply sources for meat purveyors. And, if this was true, predicting the available cow slaughter for a given time period would benefit the purveyors relying on cow-beef as an important component of their raw product supply source. In addition, the author was interested in the general operational arrangements of meat purveyors such as the types 48 of accounts serviced, (self-serve steak houses, hotels, restau— rants with waitresses, and insititutions) the method of trans- acting their purchases, etc. Collection Of Data Considerable time was taken in the beginning of the study to formulate an effective but brief questionnaire that would help to answer some questions about the meat purveying business and its interaction with the Food Service Industry. A pilot questionnaire was sent to a typical meat purveying firm for review of format, terminology, and length. The final question- naire, the accompanying explanatory letter, and a self-addressed stamped return envelope was then forwarded. Breakdown Of Responses Table 111-3 presents the number of respondents and the per cents. Figure III-l indicates the geographic distribution of the respondents. The accompanying letter and the questionnaire used in this study are found in Appendix B. The Statistical Package for the Social Sciences computer program was employed in analyzing the raw data from the questionnaire received. Specific procedures for editing, processing, and coding the data are found in Appendix B. 49 Table III-3 Breakdown of Responses to the Questionnaire Questionnaires Sent Out First mailing to purveyors in Michigan and North Central Region (January 3, 1975) Second mailing to members of National Association of Meat Purveyors (January 31, 1975) Total Questionnaires Sent Out Questionnaires Received Usable (having sufficient data to process) Non-Usable (not having sufficient informa— tion) Total Received Per cents % Total Return 112_ a 28% .424 % Total Usable 104 -*' = 24.5% 54 50 .h--. ..b. .— to. al.0 «I ......E. .oouaoa-ou luau one swan ouol muons huao q so am sequouba canon-mu manna. a A. nomads nuns-sumo: a madam h$~U1P‘P‘P‘P‘P‘O\OJPJNJF4£~ DJUIO‘NHHNHNJ-‘NJ-‘Hkfi HQQOOOQONQMNOW N M 100.00% H O b TOTAL 60 2) The response was coded by weight ranges and the results were as follows: Absolute Per Cent of Frequencies Respondents 400-500 pounds 3 2.9 501-600 pounds 12 11.5 601-700 pounds 16 15.4 701-800 pounds 25 24.0 801-900 pounds 7 6.7 Over 1000 pounds 1 1.0 All weights 5 4.8 Missing observations _35_ 33.7 Total 104 100.00% 3) "The typical product that you buy from packers or cattle sellers is: Class: Steer Heifers Cow Bull ." Some respondents marked more than one categroy, accounting for a combined total of more than 104. The response was coded such that if any of the categories were marked with an x or check, this was interpreted as "yes" while blank meant "no." Totally unanswered were included in the "missing observations." The results were as follows: Absolute Per Cent of Frequency Respondents Steer Yes 75 72.1 No 20 19.2 Missing Observations 9 8.7 Total 104 100.00% 61 Absolute Per Cent of Frequency Respondents Heifer Yes 37 35.6 No 59 56.7 Missing Observations 8 7.7 Total 104 100.00% Cow Yes 44 42.3 No 52 50.0 Missing Observations 8 7.7 Total 104 100.00% Bull Yes 7 6.7 No 89 85.6 Missing Observations 8 7.7 Total 104 100.00% b. Geographic Supply Source In an effort to determine the geographic origin of beef supply source, the following question was asked: "An estimate of where your beef supply is obtained Domestic % Foreign % Table III-6 below summarize the results of the responses. Table 111-6. Geographic Supply Origins Beef Supply Standard Range Obtained From Mean Deviation Minimum Maximum Source: % % % % Domestic 93.1 13.91 40.0 100 Foreign 6.9 13.91 0. 60.0 100.0 62 a. Domestic Geogrgphic Origins of Beef Sppply The following analysis represents the responses to the second part of the question which asked: "Of your domestic supply, what % comes from the Southeast % Far West % Central % Plains % Northwest % Other %" Figure III—2 on the following page indicates the regional breakdown by states of the above categories. However, since the areas were not defined specifically by states in the questionnaire, the individual firms were at their own discretion to mark the area they considered southeast, far west, etc. Table 111—7 summarizes the regional breakdown statistics pertaining to this question. Table 111-7. Domestic Beef Supply Origin Standard Ran e Percent of Domestic Mean Deviation Minimum Maximum Supply Coming From: l_%__ % % % Southeast 1.2 6.64 0 60 Far West 20.0 33.35 0 100 Central 54.5 38.26 0 100 Plains 18.8 29.48 0 100 Northwest 1.0 2.75 0 25 Other 4.5 14.31 0 100 100.0% 63 Hm<.m .\ H mwhchw mutt: H 23mm.— ‘ s 1-. ‘ is... man... so: ... O. 0‘. 5.33 an”: no .TEEOE «528 SE 3.528 . a... 1‘ 64 Southeast Eighty-one (81) respondents (85.6%) said they received pp 2.0f their beef supply from the southeastern states, whole the average amount of domestic supply derived from this area was 1.2%. Hence, this appearsrunzto be a major meat secure- ment area for the beef purveyors and processors surveyed. Far West There was a wide range of distribution here, from O to 100% of the firms supply coming from this area. Still, 62 respondents or 59.6% indicated they received pqu_of their supply from this area. The average amount of supply coming from the far west states was 20.0%, suggesting it was the second largest supply area next to the central states. Central Twenty-four respondents (or 23.1%) said they received 100% of their beef supply from the Central states. The average amount of beef supply coming from this area for all the 104 respondents was 54.5%, making it the most important domestic beef supply region for these responding beef purvey- ors and processors. Plains Fifty per cent of the respondents noted that they received none of their beef supply from the Plains states, while the average total amount supplied by this area was 18.8%. Hence, this was the third most important beef supply region for these beef purveyors and processors. 65 Northwest As shown, a negligible portion of beef supply for the re— sponding firms comes from the Northwest. However, there is a slight problem of ambiguity in that many firms probably in- cluded Northwest into the Far West category. 91112.: In retrospect, the question should have been formulated not to include an "other," but probably the category "eastern" or "southwest." Each category should then have been non- ambiguously defined by state components. Seventy-five per cent of the respondents did not mark "other" as a supply source. The average supply from this area was 4.5. c. Raw Product Purchasing The author attempted to determine the timing of raw product meat purchase by purveyor and processor firms. In the questionnaire, the wording of the question was: "Up to how many months are raw products purchased?" In retrospect, as indicated by the results of the return, this question was poorly worded and ambiguous. The question should have been worded as, "How many weeks ahead do you forward purchase raw product supply?" Thirty-six (36) of 103 respondents (35.0%)did pqp_answer this question. Those firms responding to this question indicated a time period of seven weeks for purchasing ahead their raw meat products. However, 16% of the 66 respondents indicated they purchased weekly. In light of the high number of missing observations, further diagnosis would be misleading. d. Purchasing on Contract The following was the response to the question: "Are individual purchases of your product made on a contract (forward purchase) basis? yes no Absolute Per Cent of Frequencies Respondents Yes 18 17.3 No 79 76.0 Some 5 4.8 Missing Observations 2 1.9 Total 104 100.00% e. Storage Arrangements The following question was posed: "With respect to storage arrangements: tons of meat storage available length of storage before quality deteriorates This question received no response from almost half the respondents. For this reason, no anlaysis was conducted for this response. f. Method of Securing Raw Product The response to the question "Method of securing raw product: Order buying via telephone Broker at supply source Other (specify) 67 was as follows: Absolute Per Cent of Frequency, Reepondents Order buying via telephone 58 55.8 Other 2 1.9 Order buying plus broker 23 22.1 Order buying plus broker plus other 8 7.7 Order buying plus other 11 10.6 MissingObservations .__2 1.9 Total 104 100.00% g. Firm Size Relative to Cogpetitors The participants were asked the following question: "Firm size in terms of meat processed relative to your competitors Small Medium Large The results were as follows: Absolute Per Cent of Frequencies Reepondents Small 17 16.3 Medium 20 57.7 Large 26 25.0 Missing Observations l 1.0 Total 104 100.00% 3. Product Disposition a. Accounts Normally Serviced The question was asked: "Approximately how many accounts do you normally service? #." 68 The responses were rounded off to the nearest hundred. The results were as follows: Absolute Achounts Normally Frequency Per Cent of Total Serviced per Firm of Responses Response 100 8 7.8 200 24 23.3 300 18 17.5 400 13 12.6 500 12 11.7 600 5 4.9 700 l 1.0 800 1 1.0 900 l 1.0 1,000 3 2.9 1,200 2 1.9 1,500 2 1.9 2,000 l 1.0 3,000 2 1.9 5,000 2 1.9 Missing Observations __31 7.8 Total 103 100.00% The firms serving on the average from 100 to 500 accounts represented 78.9% of the total response to this question, while the two firms serving on the average of 5,000 accounts were an exception to the average, accounting for only 1.9% of the total response. The average number of accounts serviced by the 103 responding purveyor and processor firms was 568 accounts. Summary statistics for 'number of accounts servicedpper firm'. 5 Mean 568 Standard Deviation 819 Minimum 100 Maximum 5,000 Range 4,900 Disposition of Product: Accounts Serviced In an effort to determine where the final product of beef purveyor and processor firms were going, the author 1) 2) 3) 4) 5) 69 followed the "number of accounts normally serviced" question by the following: "Of your accounts serviced: Self-serve Steak Houses Hotels Institutions (hospitals, schools) In-service (waitress/steak house) Other Table III-8 summarizes the responses. Disposition of Finished Product Table 111-8 % of Business Mean Standard Range Food Service % of Deviation Minimum Maximum Outlet Business % % % Self-Serve Steak Houses 8.5 19.71 0 100 Hotels 13.00 13.03 0 7O Institutions 24.50 20.28 0 100 In-Service (waitress/Steak House) 32.0 25.13 0 95 Other 22.0 26.30 0 95 100.0% Self-Serve Steak Houses The self-serve steak houses are commonly referred to as the "economy steak houses" or the "family style self-serve restaurants." Of the 103 respondents, 45 (43.7%) said that none of their business dealt with this type of food service outlet. And, 35 (92.4%) of the respondents said they did less than 20% of their total business (including those who did Q_business) with self-serve steak houses. The average amount of business generated from self—serve steak houses 70 to the 103 responding purveyor and processor firms was only 8.5%, indicating that this type of outlet does not represent a signifi- cant portion of purveyor and processor firm sales for the majority of these firms. Hotels Seventy-three respondents (70.9%) do from 0 to 20% of their business to hotels, while only 17.4% do more than 20% with hotels. Missing Observations accounted for 11.7% of the total response to this question. The average amount of business to hotels by pur- veyors and processor firms was only 13.0%, making it the second smallest outlet for these firms' products. Institutions Among the types of outlets included under institutions were hospitals, school lunch programs, sanatoriums, rest homes, state correctional institutions, elementary and secondary schools, and universitities. This category represented the second most important distribution outlet for these responding purveyor and processor firms' products. The average amount of business to institutions for this group was 24.5% of their business. The range was from O to 100% of total business going to institutions. In—Service (Waitress) Steak Houses The in-service waitress steak houses are the most important portion of the responding purveyor and processor firm's business, with an average of 32.0% of total business going to this outlet. Sixty-nine respondents (66.9%) said they did from 0 to 50% of their total business with in—service waitress restaurants. 71 Other While not many of the respondents who indicated "other" as a component of their total business explained their outlets, those who did indicated that the types of outlets as other included: 1) fast food chains 2) taverns 3) retail grocery stores 4) drive-in restaurants 5) U.S. government bids 6) full line restaurants 7) airlines 8) distributors 9) wholesalers 10) coffee shops ll) dinner house clubs 12) clubs 13) vending outlets The average amount of total business going to "other" sources than those listed in the question (self-serve steak houses, hotels, institutions, and in-service waitress steak houses) was 22.0% for the responding firms. Additional Comments by Responding Firms The author designed the last question of the survey as an open ended question in an effort to secure any salient production information or comments not covered by the previous questions. The question was posed: "What factors or variables influence future production practices of technologies for the future of your Operations?" The feedback could be categorized as follows: OperatipgTCosts increasing fuel costs increased packaging costs and machinery costs rising labor costs which necessitate the purchasing of labor saving equipment so as to maintain lower production costs 72 Market Conditions changing customer demands use of more "ready to serve items" competition's prices and aggressiveness beef supply and availability seasonal usages general condition of the economy (inflation rate, unemployment rates, etc.) Institutional Influences Government policies Government purchasing programs monetary policies interest rates and finance costs respondent's answer to this question was: "I am firmly convinced that all segments of the meat industry face a crisis in the next 10 years as a result of the in- creasing use of 'red meat substitutes' (some of which are nutritionally equal to meat in protein, etc.). For example, in 1973 and 1974, ground beef average price was $1.00 plus. Today, 1/31/75, a local chain advertised ground beef soya added for 39¢/lb.!!" Crosstabulations As previously mentioned, the author was interested in determining the source of raw meat products, raw meat break- out form, and how much product was being processed weekly, and finally, who purchased the finished product? The previous analysis based on the participating firms' responses began to answer these types of questions. The use of crosstabulations in this section enables one to view the relationships between variables. a. Raw Product Types Used by the Various Operations The objective of this crosstabulation was to determine the forms of raw product supply received by the various operation types. Results presented in Table 111-9 indicate NOOH o o o o 5.00 o o m.mm o nmsuo NOOH o o o o o.o~ o o o.ow o mmmooum w Hmuowomaw Nooa N.N ~.~ m.mm N.NN ¢.q m.na n.o N.HH o achm>hom w Hommmooam NOOH o o n.m~ H.HN w.m H.HN m.oa o w.mH HOhm>aom NQOH o m.w m.w n.0H o.mN m.w 0 «.mm o aommmooum mmmm Hmuoe umsuo mamaaamnom mHmBaHQOOm mamawum mamaaum Mano .JNHoo mane .mno make w mmmoamo I w mamaaam loam w w mHmEaam mamaaum mmmowmo momma“: cowumammo w mmmoamo mamaaum mmmoamu loom ANV msaom uooooum 3mm hamasam mooaumammo maoaum> mnu ho omwa Omaha mooooum 3mm .aIHHH mHQmH 74 that for beef processor operations, carcasses and primals are the most important forms of raw product. For purveyors and for processors and purveyors; carcass, primals, and subprimals are the most important. For slaughter and process operations, carcass is the most important form of raw product supply. However, this suggests nothing about which form is the most economical form for firm types. Average Total Pounds_per Week Processed by Operation Types The intent of this crosstabulation was to view the range of average total pounds of product processed weekly by the various types of Operations conducted by the respond- ing firms. [See Table 111-10] The 12 beefyprocessors in this study are a large volume type firm: 49.8% of the beef processors process on the average from over 100,000 pounds weekly up to 500,000 pounds weekly. Those 38 firms who responded as solely purveyors tended to process a weekly average volume lower than the other categories, with 63.8% of the respondents (excluding mis- sing observations) processing a weekly average of less than 100,000 pounds per week. Of the 45 operations categorized as processor and pur- veyor, 70.5% processed a weekly average of less than 100,000 pounds per week, with the remaining 21.0% of these types of firms processing a weekly average of products ranging from 105,000 pounds to 2,055,000 and the remaining 8.5% were coded as "missing observations." 75 Table III-10 Average Weekly Production by Processor Firms Type of Operation Summary Average Total Pounds Processed Beef Processor Slaughter per Week Processor Purveyor & Purveyor & Process Other Percent 0 8.3 16.3 8.5 0.0 33.4 (Missing Observations) 2,000 8.3 5,000 5.3 6,000 2.2 7,000 2.2 8,000 2.6 10,000 2.2 12,000 5.3 13,000 2.6 15,000 5.3 18,000 2.6 2.2 19,000 4.4 20,000 2.6 33.3 21,000 8.3 2.6 2.2 22,000 2.2 23,000 2.2 24,000 20.0 28,000 17.0 29,000 2.6 2.2 30,000 2.6 2.2 31,000 2.6 32,000 5.3 33,000 2.6 35,000 2.2 37,000 5.3 38,000 4.4 40,000 2.6 4.4 45,000 8.3 2.2 47,000 2.6 48,000 2.6 . 50,000 11.1 51,000 4.4 52,000 2.6 2.2 57,000 2.6 58,000 2.6 2.2 76 Table III-10 (Continued) Type of Operation Summary Average Total Pounds Processed Beef Processor Slaughter Per Week Processor Purveyor & Purveyor & Process Other Per Cent 64,000 20.0 70,000 33.3 76,000 2.2 78,000 2.2 79,000 2.6 80,000 4.4 88,000 2.2 100,000 2.2 105,000 2.2 114,000 2.6 120,000 8.3 127,000 2.6 142,000 2.2 150,000 8.3 2.6 165,000 2.2 185,000 8.3 195,000 8.3 198,000 2.6 200,000 2.6 4.4 301,000 2.6 303,000 8.3 350,000 2.2 498,000 2.2 500,000 8.3 505,000 2.2 600,000 2.6 610,000 20-0 1,500,000 20.0 2,055,000 2.2 7,500,000 20.0 100.00% 100.00% 100.00% 100.00% 100.00% 77 Five firms indicated their operations were slaughtering and processing. Three of these 5 (60%) firms processed a 'weekly average of greater than 610,000 pounds per week. Use of Physical Tenderizers and Vegetable Enzymes_by Operation Types The intent of this crosstable was to determine to what extent physical tenderizers and vegetable enzymes were being utilized by the responding Operation types. The actual process of'physically tenderizing" meat is per- formed by a mechanical tenderizer machine which consists of a large number of needle-like knives which penetrate the meat physically to sever the tissues within the meat to increase its tenderness. A vegetable enzyme is a chemical additive injected mechanically for taste, pre- servative, and tenderizing purposes. Generally, the lower grades of meat would tend to need this type of "fabri- cation" more than the higher grades of meat. The results are.indicated on Table III—ll. 78 Table III-ll Use of Tenderizers and Enzymes by Operation Type (Number of Firms) Use Physical Tenderizer Total # Operation Type M.O Yes No Some Firms Beef Processor 0 4 6 2 12 Purveyor 0 15 18 5 38 Processor & Purveyor 3 l6 l9 7 45 Slaughter & Process 0 2 3 O 5 Other 0 l 2 0 3 Totals 3 38 48 14 103 Use Vegetable Enzyme Beef Processor 0 3 8 l 12 Purveyor 2 '8 25 3 38 Processor & Purveyor 0 8 32 5 45 Slaughter & Process 0 l 4 0 5 Other 0 O 3 0 3 Totals 2 20 72 9 103 M.O. - Missing Observations By including the "some" and "yes" category from Table III-ll, about one-half of the responding firms in- dicated use of physical tenderizers on their production lines. However, use of vegetable enzymes was less comon. d. Grade of Cattle Bought by Operator Types from Packers or Cattle Sellers The purpose of this crosstable is to relate and dif- ferentiate the typical product grade of cattle purchased by the various operation types. Missing observations (M.O.) accounted for 23 of 103 responding firms' returns. 79 Choice grade cattle was the most typical grade of cattle supply source for these respondents with 34 of the 103 firms indicating this category The summary results are below: Table III—12 Cattle Grade Bought by Various Operations By Operation Type (# of Firms) Typical Product Operation Type E eef roces- Pur- Processor Slaughter Grade Bought or veyor & Purveyor & Process Other Total M.O. 2 10 8 l 2 23 Prime & Choice 0 l 4 0 O 5 Prime & Cutter 0 0 0 0 l 1 Choice only 4 15 14 l O 34 Choice & Good 0 6 5 1 0 12 Choice & Commercial 0 2 2 O 0 4 Choice 8 Utility 2 2 3 0 0 7 Good only 1 O 0 0 O 1 Good & Commercial 0 O 2 0 0 2 Good & Utility 0 O l O O 1 Commercial only 1 0 0 0 O 1 Commercial & Utility 0 O l l 0 2 Utility only 1 2 3 0 O 6 All Grades 1 O 2 l O' 4 Totals 12 38 45 5 3 105 e. Use of Cow Beef As a Sppply Source for Qperepion Types The objective of this crosstable was to determine the use of cow beef as a typical supply source for the various responding operation types. Table III—l3 merely indicates the firm's acknowledgment of cow beef as a typical supply 80 source of raw product for their operations. Table III-13 Use of Cow Beef as Raw Product Source Operation Type M.O. Yes No Total Beef Processor 1 6 5 12 Purveyor 3 14 21 38 Processor & Purveyor 3 19 23 45 Slaughter & Process 1 3 l 5 Other 0 2 l 3 Totals 8 44 51 103 M.0. - Missing Observations As noted earlier in this chapter's analysis, the average amount of raw product coming from commercial and utility grade cow beef was 19.2% for the responding firms; canner and cutter grade beef which would generally be cow beef was an average of lgygz_of the responding firms raw product supply source; while standard or ggod grade bull, heifer, steer and cow beef made up 12412 of the responding firms raw product supply source. Hence, it could be estimated by adding the two categories of commercial and utility grade cow beef plus cutter and canner grade beef categories accounted for approximately 32.1% of the responding firms raw product supply source for their Operations. This roughly represents the average amount of cow beef usage by these responding firms. Disposition of Finished Product: by size of firm and typical product grade The objective of these crosstables was to determine the 81 relationships (1) between purveyor and processor firm size based on numbers of accounts normally serviced epq_the dis- position of their product to types of fOod service outlets, and (2) between the typical product grade bought by pur- veyor and processor firms from cattle sellers and packers epg the disposition of the firms' finished product to types of food service outlets. The conclusions of the findings follow Table 111-14 and Table III—15. Table III—l4 Disposition of Finished Products By Size of Firm # of Firms Types of Food Service Outlets # Accounts Responding In- Normally in this Self- Institu- Service Serviced Category Serve Hotels tions Waitress Other Total 100 6 7 7 34 28 24 100% 200 23 3 10 27 31 29 100 300 18 15 ll 27 34 13 100 400 12 7 17 24 35 17 100 500 10 4 . 21 15 38 22 100 600 5 22 10 14 30 24 100 700 l 5 15 35 25 20 100 800 l 20 10 10 50 10 100 900 l 0 4O 8 48 4 100 1000 3 7 8 8 27 50 100 1200 2 5 5 4O 10 40 100 1500 l 10 10 40 20 20 100 2000 l 100 O O 0 0 100 3000 2 3 3 10 55 29 100 5000 2 0 15 50 15 20 100 Total 88 208 182 342 446 322 1500 Average % of Business 14 12 23 30 21 100 82 Table III-15 Disposition of Finished Product By Typical Product Grade Bought By Purveyors and Processors From Cattle Sellers or Packers Types of Food Service Outlets Typical Product Grade Bought from Packers or Cattle # of Firms Sellers By Respond- Responding ing Purveyor and in this Self- Average Per Cent Insti- of Business In- Ser- Processor Firms Category Serve Hotel tution vice Other Total Prime and Choice 5 4 17 8 63 8 100% Choice - 28 7 15 25 36 17 100 Choice and Good 10 4 13 32 23 28 100 Choice and Commercial 4 2 26 23 16 33 100 Choice and Utility 7 10 11 29 36 14 100 Good 1 0 0 30 20 50 100 Good and Commercial 2 3 5 12 70 10 100 Good and Utility 1 5 20 25 50 0 100 Commercial 1 70 5 5 10 10 100 Commercial and Utility 2 4 0 13 47 36 100 Utility 6 35 8 19 12 26 100 All Grades 4 6 9 20 29 36 100 The following conclusions may be drawn from these re- turns 3 1) On the basis of these responses, the finest grades of beef, prime and choice, most frequently went to the "in-service waitress" restaurant outlets, suggesting this to be a higher quality restaurant based on the higher quality of meat purchased. 2) Choiceggrade beef is the most typical grade of raw product bought by the responding purveyor and processor 83 firms from packers and cattle sellers. The largest amount of choice grade beef goes to "in-service wait- ress" restaurants who generally carry a full line menu. The 1ga§£_amount of choice grade beef goes to the "self- serve steak houses" which are commonly cafeteria style or family style dining facilities. 3) The one respondent who indicated "commercial” as the typical supply source was channeling 70% of his business to the "self-serve steak house” outlets. Those 6 firms responding to "utilit " as the typical supply source "self-serve were averaging 35% of their business to steak houses.” 4) For those 3 firms who responded that the typical product grade was "good and commercial" and "good and utility," the per cent of finished product going to "in—service waitress" restaurants was 70% and 50%, respectively. This suggests that the "in—service waitress" restaurants do receive some lower quality meat in addition to the higher qualities of meat as indicated in paragraphs (1) and (2), above. The sample size is not large enough to conclusively determine a fixed relationship between types of food service outlets and the quality of purveyor and pro— cessors finished product based on typical cattle grades bought from cattle sellers or packers. 84 (l Summary The meat purveyor and processor firms serving the food-away-from— home market are a very specialized and important segment of the meat industry. The meat purveyors have enjoyed spectacular growth within the past several decades, both in number of houses and volume of meat hand- led. [See page 45, Chapter III]. The economic activities of meat -purveyors and processors depend primarily upon the aggregate demand for red meat of various classes and grades by the Food Service Industry which serves this food-away-fromrhome market. The Food Service Industry is a vast and complicated industry whose size is difficult to measure since the components are so diverse. The importance of the Food Service Industry to beef retailing was reflected in the A. T. Kearney & Company study in 1969 which estimated nearly 45% of all beef moved through the food—away from-home market. Our society will continue to rely on the food—away-from—home market as an important link in food marketing system. Consumers will continue to demand quality food at a reasonable cost coupled with uniform products and services from a variety of food service outlets. Consequently, this competition for a reasonably-priced quality beef product will necessitate even further specialization and increased efficiencies from the purveyor and processing segment of the meat industry. The bulk of questionnaire responses came from midwestern or central states, although the total usable responses (104) were scattered through- out the country. Nearly 80% of the responses were from firms that con— sidered their operations as either "Purveyor" or "Purveyor and Processor" operations. Purveyors tend to fabricate more products from primals and 85 subprimals for hotels, restaurants, and institutional trade, while processors generally break down and process meat cuts from carcasses vis-a-vis primals or subprimals. The most common types of raw product purchased by these respondents were, in descending order, primals, subprimals, and carcass. Forty-six per cent of the firms indicated that a physical tender- izer was ngE_used on the production lines as opposed to 50% who did. Also, 69% of the respondents indicated that a vegetable enzyme was not_ used on the production lines as Opposed to 31% who do use a vegetable tenderizer. The most important component of average total weekly beef production was hamburger, followed by chucks, boneless strips, rib eyes, short loins, butts, rib roasts, and bone-in strips. While the category "other" was the largest of all_components of weekly production, this included . items other than beef such as pork, lamb, and fish products which make up an important portion of the purveyor business. The range of meat volume processed weekly by these firms was from 2,000 pounds to 7,500,000 pounds. The average amount processed weekly was 210,591 pounds, with a standard deviation of 813,659. Thus,the large range suggests the heterogeneous nature of purveyor firms in terms of size and operation. In regard to supply logistics, the raw product supply source summary 86 by the firms was as follows: Average Per Cent of Total Raw Raw Product Supply Source Product Supply a) Commercial & Utility Cow Beef 19.2 b) Canner & Cutter Grade Beef 12.9 c) Standard or Good Grade Heifer, Bull, Steer, or Cow Beef 12.7 d) Choice Grade Heifer, Steer Beef 54.9 99.7% Forty-four of the 103 respondents acknowledged the use of cow beef as a typical raw product supply source for their Operations. It could be estimated by adding the two categories Of commercial and utility grade cow beef plus cutter and canner grade beef accounted for approximately 32% of the firms'raw product supply. This roughly repre- sents the average amount of cow beef usage for these firms' operations. 0n the average, 93.1% Of the respondent's beef supply comes from domestic sources as Opposed to foreign sources, with the central states being the most important domestic beef supply region. The most common method of securing raw product was order buying via telephone, with order buying plus the use Of a broker being the second most important method. Such a system not utilizing written contracts necessitates a great deal of confidence and familiarity among cattle sellers and meat processors-purveyors in negotiating transactions. Only 17.3% of individual purchases of processor and purveyor firms products are made on a contract basis, while 76.0% do not engage in this practice. The remainder do use this practice occasionally. The most typical product grades bought by the responding firms 87 were choice, and choice and good, with the typical cattle class being steers and cows followed by heifers and bulls. While 57.7% of the firms considered themselves "medium" size relative to their competitors, further analysis showed that there was no positive correlation between the size of firm relative to their competitors and the average total pounds per week processed or number of accounts normally serviced. Although the average number of accounts serviced by responding firms was 568 accounts, the firms serving an average of 100 to 500 ac— counts represented 78.9% of the total response to this question. The following conclusions can be drawn in regard to the disposition of processor and purveyors' finished products: 1) The Food Service Industry is a heterogeneous group of enterprises that serve a variety of types of food service outlets. While the author felt that the categories of "self-serve steak house," "hotels," ' were the more "institutions," "in-service waitress restaurants,’ important types, the average per cent of business to the category "other" was 22.1%, which represented numerous types of outlets other than the four specified. 2) The "in-service waitress restaurants" were the most important outlet for the firm's finished products, followed in descending order by institutions, other, hotels, and self-serve steak houses. 3) There is insufficient data to suggest a correlation between the size of processor and purveyor firms (based either on total pounds of beef processed weekly or accounts normally serviced) and the disposition of product going to any one specific type Of 88 food service outlet. Various sizes of processor and purveyor firms tended to serve various types of food service outlets. 4) Similarly, there is insufficient evidence to conclude that any one type Of food service outlet receives finished products from firms who typically buy a certain grade Of meat (prime, choice, utility, etc.) for their production. CHAPTER IV DEVELOPMENT OF A PREDICTION MODEL FOR FORECASTING ANNUAL COW SUPPLY AND SLAUGHTER Introduction The purpose of this chapter is to develop and interrelate beef and dairy cows supply equations with a cow slaughter equation that can be used for forecasting short run cow beef production in the United States. An illustration is presented on how the equations can be used to predict the quantity of beef and dairy cows on farms for 1976 and 1977 and cow slaughter for 1975 and 1976. The ordinary least squares method using time series data from 1954-1974 was em- ployed to develop the short run supply equations. Longer range projections will require use of considerable subjective judgment concerning structural changes and level of exogenous variables. Relationship of Cow Supply and Slaughter to Meat Purveyors and the Food Service Industry Chapter II provided a descriptive explanation of the beef pro- duction industry and related structural changes. It also demonstra- ted the economic inter-dependencies among the participants of the total beef production and marketing system. Data from this project's 103 responding purveyor and processor firms indicated that approximately 32 per cent of their raw product supply was coming from cow beef sources. Cow beef does represent an important raw product supply source for meat purveyors and their 89 90 market (i.e., the various types of food service outlets). Meat Pro- cessing technology utilizing physical tenderizing machines and/or vegetable enzyme applicators is capable of manufacturing retail table cuts from cow beef. Definition of Variables Estimation of the economic model requires the measurement of factors that are specified as influencing the cow beef numbers and slaughter. The following variables, as herein defined, will be func- tionally related in the form of the three equations to explain number of beef and milk cows on farms and cow slaughter during the 20 year period under analysis. The variables used in the anlaysis are now listed and defined. DEFINITIONS OF VARIABLES NCSLt Estimated total number of cows slaughtered in year t, United States, (1000 head)* NBC - Number of beef cows on farms on January 1 in year t, t (1000 head) NDCt a Number of dairy cows on farms on January 1 in year t, (1000 head) PFC - Price of Good-Choice—Feeder calves at Kansas City in August to December ($/cwt) divided by the index of prices paid by farmers (1967-100) in year t RF - Range Feed and pasture conditions in year t (USDA Index) GMM - Gross Margin ($) Per hour of labor in milk production -[average price received by farmers per cwt - total con- centrate costs per cwt of milk] + hours 0f labor required to produce 100 pounds of milk (LM)] + [Index Of prices paid by farmers (IPP) (1967-100)] DUM - Dummy variable on milk production assuming the value of 0 for 1954-1964 and 1 thereafter, recognizing the struct- ural change in the dairy industry 91 PRIHAXt - Annual average price in dollars per ton ($/ton) received by farmers for all hay baled RWR - Real Wage Rates ($/hour) of workers in non-agricultural sector deflated by the Consumer Price Index *NCSL - (Federally Inspected Cattle Slaughter number, U.S. + Per t cent of total slaughter that is Federally Inspected) x per cent Federally Inspected Cow Slaughter). Development Of the Supply Functions: Equations to be Estimated The develOpment of this cow supply and slaughter model involves three equations: (1) the number of beef cows on farms, (2) the number of dairy cows on farms, and (3) estimated total cow slaughter. Prediction of total U.S. cow slaughter creates the need for predic- tion of the two separate components of cow slaughter; i.e., beef and dairy cow inventory levels. 1. Number of Beef Cows on Farms The number of beef cows on farms is the key variable in the U.S. beef supply relationships. The preliminary work of Ferris [9] was utilized in deriving a supply equation for beef cows on farms. The specification of his model and results can be found in Chapter II. a. The model specified and estimated is: NBC I a * b NBC * b PFC + b PFC + b t t- t- t- 1 1 2 2 3 3 4 PFC + b RF . t-4 5 t-l Using this equation it is possible to investigate the in- fluence of each independent variable (those on the right hand side) upon the dependent variable (NBCt). b. 92 Testingpof 'Accounted-For' Variation To test if a significant amount of variation Of the en- dogenous variable, NBCt, was accounted for by the exogenous variables in the equation, a null hypothesis was tested with the 'F' test. with the alternate hypothesis being: HA : B i 0; i.e., the total variation of the exogenous variable does account for significant amount of variation in the endogenous variable. Testing Hypothesis about Single Coefficients In order to test the significance of the individual co- efficients in the equation, 't' tests were employed. The general hypothesis being tested is: HD : B1 - 0 with the alternate hypothesis being: HA : B1 {.0 depending on sign or expected directional effect of the ith coefficient. Specified Alternative Hypothesis: 1) HA : b1 7 0 The number of beef cows on farms, NBGt_1, in any particular year is expected to have a positive effect on numbers in the follow— ing year, NBC . Expanding numbers of beef cows on farms in (t-l) would tend to increase the number of beef cows on farms in year t. 93 0 The number of beef cows on farms is believed to be positively related to the expected net returns over variable costs for that enterprise. As the feeder calf price is a principal ingredient of the profitability 3) H : b *yO measure, and as calf prices expected to A 3 be received by farmers are believed to be influenced by past prices; a positive re- lationship is hypothesised for the lagged calf price with the number of beef cows 4) H : b 310' on farms. A 4 5) HA : b5, 0 The range conditions that prevail during the period for decision to expand or liqui- date beef cow numbers constrains the numbers of animals that can be grazed. Hence, we would expect NBCt to be positively associa- ted with RF(t-l)° Estimated Equation Presented The relationship fitted to the years 1954 to 1974 was estimated and resulted in: Equation IV-l NBCt - -4922 + 1.051 NBCt_1 + 117.6 PFCt_2 (standard (48.25) (3.14) error t ) + 18.35 PFC + 51.31 PFC - 3.03 RF (3'3 (.L‘ t-l ( .42) (1.77) ( .09) E2 - .995; S.E.E. - 506 ( ) Numbers in parenthesis are t-values. Testing Results (l) Rejection Criteria The null hypothesis is rejected if the calculated F ‘ - O 2 statistic 7 Fvl, v2, or F5,l4, .05 2 958 where V1 = 5 degrees of freedom in SSR calculation, v2 = 14 degrees Of freedom in SSE calculation, and the test is conducted at the 5% level of significance. (2) (3) 94 .Regult Of 'F' Tegp: As the calculated F statistic is 555.49, H0 is rejected, HA is accepted; and the variation accounted for by the predetermined variables is significantly different from zero at the 5% level Of significance. Rejection Criterion for 'T' Test: Reject Ho if calculated T > Td.f,°( = 2.145 for l-tailed test at the 5% level of significance. The calculated 't' values are presented below their re— spective coefficients in equation IV—l and suggest the following: Results of 'T' Tests: 1) Reject Ho : b1 - 0 Accept HA : b1 3 0 Since the t value of B1 is 48.25 and thus greater than 2.145, we reject the hypothesis that NBCt_1 is not significantly different from zero. We accept the alternative hypothesis that NBCt_1 does contribute significantly to the deter— mination of NBCt_1. The highly significant coef- ficient on NBCt-l reflects the long biological cycle and the rapid upward trend in beef cow numbers. 95 2) Reject Ho : b2 = 0 Accept HA : b2‘7 O The 't' value, 3.14, for the PFCt_2 coefficient indicates that we accept the alternative hypothesis that the feeder calf price in any particular year significantly influences beef cow numbers two years hence. 3) Accept Ho : b3 = 0 The 't' value for the PFCt_3 coefficient was .42. Thus, we accept the null hypothesis that the t value of the coefficient for the variable PFCt_3 does not differ significantly from zero. The determination of NBCt does not depend significantly on PFCt_3_ 4) Accept Ho : b4 - 0 The 't' value for the PFCt_4 coefficient was 1.77. Therefore, we accept the null hypothesis that the 't' value of the coefficient for variable PFCt_4 does not differ significantly from zero. The determination of NBCt does not depend significantly on PFCt_4. The coefficient on PFCt_4 was larger than PFCt_3. Ferris suggests that a plausible explanation is that feeder prices may be more influential at the time a cow calf Operator is deciding how many heifers to hold back. Normally, these operators would keep more heifers than they actually need for replacement purposes just to have some flexibility. But usually, most of the heifers 5) 96 to be sold as feeders are sold as calves rather than yearlings. Accept HO : b5 = 0 The 't' value for the RFt_1 was .09. Thus, we accept the null hypothesis that the 't' value of the coefficient for variable RFt_1 does not differ signifi- cantly from zero. As indicated bth'2 99.5 per cent of the quantity variation in beef cow supply was 'explained' by the variation of the specified independent variables. The equation missed direction changes once in year to year changes from 1954 to 1974. In this case, the error meant that the model indicated an increase in the esti- mated number from the previous year, whereas the actual number from the previous year declined. For the period used in this analysis, the "fit" of the equation was not as close as in the period 1950- 1972 analyzed by Ferris. The above equation suggests the following relation— ships: 1) A strong upward trend is present in beef cow numbers. 2) A dollar increase in the deflated price of good-choice feeder calves at Kansas City in August - December in year t-2 will tend to increase the number of beef cows on farms in year t by about 117,600 head. Similarly, a 97 dollar increase for feeder calves for this period in years t-3 and t-4 will tend to in- crease number Of beef cows on farms about 18,350 and 51,310 head respectively in year t. The actual effects, of course, cannot be measured this precisely. Other relevant statistical data are found in Appendix Table C—2. Number of Milk Cows on Farms The number of dairy cows in the U.S. has experienced a continued decrease since the early 1950's. The decline in the number of milk cows is related to the decrease in per capita consumption Of dairy products and to increased production per cow. Per capita consumption of milk in all dairy products fell from 653 pounds in 1960 to 564 pounds in 1970 [l,p.5]. Milk pro- duction per cow averaged 7,002 and 9,388 pounds in 1960 and 1970 respectively. While the number of milk cows has been declining consistently from year to year, the rate of decline has varied. Therefore, it seemed necessary to produce a model that would explain this variation. Conceptually, many economic forces impinge upon dairy farmers. To account for these influences in a supply equation, a number of variables would normally be required. To alleviate possible multicollinearity problems between a number of these supply-determining, cost-related variables, it was decided to use gross margin to simplify the supply equation. a. The model specified and estimated is: NDCt ' a ‘1' b1 NDCt_1 + bzGMMt_1 -b3 DUMt - b4 RWRt_1. b. 98 Testing of 'Accounted-for' Variation To test if a significant amount of variation of the endogenous variable, NDCt, was accounted for by the predetermined variables in the equation, a null hypothe- sis was tested with the 'F' test. Ho : B = 0 with the alternate hypothesis being: HA : B i 0 : i.e., the total variation of the exogenous variable does account for significant amount of varia- tion in the endogenous variable. Testingpfiypothesis about Single Coefficients In order to test the significance Of the individual coefficients in the equation, 't' tests were employed. The general hypothesis being tested is: Ho : bi - 0 with the alternate hypothesis being: HA : b110 depending On sign or expected directional effect Of the 1th coefficient. Specified Alternative Hypothesis: 1) HA : b1>0 The number of milk cows on farms in any particular year is expected to have a positive effect on numbers in the following year. The relationship between NDCt_1 and NDCt is expected to be positive. 2) 3) 4) 99 HA : b2 > 0 One Of the main problems in using a gross margin analysis is determining what costs to include in the computations and the relative weight of each cost as a part of total costs. The availability of a data source for making computations is also a constraint. Essentially, the GMM measure used gave a gross return over variable costs per hour of labor. This variable was then deflated by the Index Of Price Paid by Farmers (IPP) (1967=-100) to keep quantities in constant dollars. These data series are found in the Appendices B-6, B-7, B-8. We would expect the relationship between GMMt_1 and NDCt to be positive. As the net above variable costs for milk production increases, the number of milk cows is expected to increase. HA : b3 < 0 To recognize a marked downward trend in the dairy cow numbers that occurred in the mid 1960's, a dummy variable is introduced. This dummy variable carries the value "zero" for 1954-1964, and the value "one" for 1965-1974. The relationship is expected to be negative. HA : b4 < 0 The relationship between lagged real wage rates, RWRt_1’ and NDCt is expected to be negative. As the real wage rate in dollars per hour for workers in the 100 nonagricultural sector increases, the Opportunity cost incurred by these remaining on teh farm in- creases and provides incentive for movement off the farm. d. Estimated Equation Presented The estimated supply model is as follows: Equation IV—Z NDCt=6438 + .767 NDCt_1 + 34.33 GMMt—l -603.0 DUMt (1.23) (8.60) (.26) (-2.99) ”1232.6RWRt_1 (-.74) E2 = .996 S.E.E. =221 ( ) Numbers in parenthesis are t-values. Testing;Results l) Rejection Criteria The null hypothesis is rejected if the calcu- lated F statistic y Fv1,v2, cc or F5,14, .05 a 2.9582 where v1 = 5 degrees of freedom in SSR calculation, v2 - 14 degrees of freedom in SSE calculation, and the test is conducted at the 5% level of significance. 1) Result of 'F' test: As the calculated F statistic is 1094.22, H0 is rejected, HA is accepted; and the variation accounted for by the exogenous variables is significantly different from zero at the 5% level Of significance. 101 2) Rejection Criterion for 'T' Test: The rejection criteria is the same as for the testing Of the beef cow numbers on farm equations previously stated. Results of 'T' Tests 1) 2) 3) Reject Ho : b1 - I 0 Accept HA : b1 Since the 't' value of Bl is 8.60 and thus greater than 2.145, we reject the hypothesis that NDCt_1 is not significantly different from zero. We accept the alterna— tive hypothesis that NDCt_1 does contribute significantly to the determination of NDCt. Accept Ho : b2 = 0 The 't' value of B2 is .26 and hence is less than 2.145. Thus, we accept the hypo— thesis that GMMt_1 is not significantly different from zero. Reject Ho : b = 0 3 Accept HA : b3 7 0 Since the 't' value Of b3 is 2.99 and greater than 2.145, we reject the hypothesis that DUMt is not significantly different from zero. We accept the alternative hypo- thesis that DUMt does contribute signifi- cantly to the determination of NDCt. 4) 102 Accept Ho : b4 = 0 The 't' value of b4 is .74 and hence is less than 2.145. Thus, we accept the hypothesis that RWRt_1 is not significantly different from zero, and is not an important determinant Of NDCt. Although usage of the aggregated varia- bles in this supply equation was intended to reduce multicollinearity problems, dif— ficulties remained as shown in Appendix Table C-3. This simply is a case where two or more independent variables are so highly correlated that their separate effects upon the dependent variable cannot be distinguish- ed. Acknowledging this structural weakness Of the model, it is important to note that this will not jeOpardize the prediction Of the dependent variable, NDCt. The‘R-2 value at .996 indicated a high percentage of the variation in NDC is ex- plained" by the independent variables. Equation IV—2 suggests that there is a strong downward trend effect on NDC which accounts for the major variation in supply of dairy cows. 103 Estimated Total Number of Cows Slaughtered The need for a prediction equation for total cow slaughter stems from the reliance of meat purveyors and the food service industry's usage of cow beef as an important raw product supply source. The first step in predicting cow slaughter was to predict the two separate components: beef cow numbers and dairy cow numbers. Since beef cows currently outnumber dairy cows almost 4 to 1, it was expected that the level Of beef cow inventory would strongly influence the number of cows slaughtered. a. The model specified and estimated is: NCSLt = a + b1 NBCt + bZNDCt - b3(NBDt+1—NBDt) - b4(NDCt+1 — NDCt) b. Testing Of 'Accounted-For' Variation The same criteria as explained for the beef and dairy cow models are employed here. (1) Rejection Criteria Similarly, the rejection criteria for the beef and dairy cow models is applicable here. c. Testing Hypothesis about Single Coefficients The same testing criteria for the beef and dairy cow models is used again for the cow slaughter equation. Specified Alternative Hypothesis: 1) HA : b1 7 0 The relationship between NBCt and NCSLt is expected to be positive. An 104 increase in the number of beef cows between years suggests that the heifer replacements entering the cow herd during the year would permit an increase in the culling of Older beef cows; hence, an increase in cow numbers slaughtered. 2 2) HA : b2~.0 The relationships between NDCtand NCSLt is also expected to be positive for the same reasoning as stated for NBCt. 3) HA : b3 ‘0 The relationship between (NBCt+1-NBCt) and NCSLt is expected to be negative. As the growth in beef cow inventory increases from year to year, slaughter would be expected to decrease and vice versa. As the rate of growth in beef cow numbers increases; more heifers are retained, mature cows are main- tained for a longer period of time and thus, the number Of cows slaughtered may tend to decrease during this growth phase. 4) HA : 64,.0 The relationship between (NDCt+1—NDCt) is also expected to be negative for the same reasoning as the beef cow inventory changes. d. Estimated Equation Presented The estimated supply model is as follows: 105 Equation IV-3 NCSLt a -6195 + .2594 NBCt + .3617 NDCt - 1.148 (NBCt+1-NBCt) (-2.69) (6.63) (4.67) (—11.47) -.4960 (NDCt+1-NDCt) (-1. 60) E? a .995 S.E.E. = 304 ( ) Numbers in parenthesis are t-values. Testinijesults 1) 2) Result of 'F' Test: As the calculated F statistic is 304.11, H0 is rejected; HA is accepted; and the variation accounted for by the pre- determined variables are significantly different from zero at the 5% level of significance. Rejection Criteria for 'T' Tests: The rejection criteria is the same as for the beef and milk cow supply equations. Results of 'T' Tests: 1) Reject Ho : b1 - 0 Accept HA : b1 7 0 The 't' value of b1 is 6.63 and hence greater than 2.145. Thus, we reject the hypothesis that b of NBCt is not significantly different from zero and accept the alternative hypothesis that NBC: does contribute signifi- cantly to the determination of NCSLt. 2) Reject Ho : b2 - 0 Accept HA : b2 7 0 3) 4) The 106 Since the 't' value Of b2 is 4.67 and thus greater than 2.145, we reject the null hypothesis and accept the alternative hypothesis. The variation in the number of dairy cows explains a significant amount of variation of the total number of cows slaughtered. Reject Ho : b3 = 0 Accept HA : b3 3 O The 't' value 0f b3 is 11.47 and hence greater than 2.145. We reject the null hypothesis and accept the alternative hypothesis for the same reasoning as b1 and b2. As growth rate increases, the number of cows slaughtered decreases and vice versa. 3 Accept Ho " b4 8 0 The 't' value 0f ha is 1.60 and hence is less than 2.145. Thus, we accept the hypothesis that the change in dairy cow numbers, (NDCt+1- NDCt), is not significantly different from zero and is not a signifi- cant determinant Of NCSLt. above equation suggests the following relationships: A 1000 head increase in the number of beef cows on farms January 1 in year t will increase number of cows slaughtered (NCSL) during year t by 259 head. A 1000 head increase in the number of milk cows on farms January 1 in year t will increase NCSL during year t by 361 head. A positive inventory change of 1000 in beef cow num- bers on farms will decrease number of cows slaughtered 107 by 1,148 head during year t. 4. A positive inventory level change of 1000 in dairy cows on farms will decrease number of dairy cows slaughtered by 496 head during year t. Over 95 per cent of the quantity variation in cow slaughter supply is accounted for by Equation IV-3. The equation missed direction changes four times in twenty years. The highly coef- ficient on (NBCt+1-NBCt) reflects the relative importance Of beef cow inventory lev e1 changes. Other relevant statistical data can be found in the Appendix Tables C-4 and C-5. Forecast of Beef and Milk Cow Supplies Using the derived equations and assumptions about endogenous variables, estimates of beef and dairy cow numbers were made for 1976 and 1977. These results are presented in Tables IV—l and Iv-2 0 Number of Beef Cows on Farms,jJanuary l,_1976 and 1977 Based on published USDA figures for number of beef cows on farms, January 1 of 1975 and utilizing the derived equation, the model predicts 46,889,000 head of beef cows for 1976 compared with 45,421,000 head in 1975. This assumes normal weather yield- ing normal range and pasture conditions. This increase demon— strates the powerful momentum of the cattle numbers cycle. It is not likely that the cattle production cycle will turn down during 1975. Further, USDA estimates that heifers over 500 pounds for cow replacements numbered 13 million head on January 1, 1975, an increase of 7 per cent from January 1, 1974. This would wml 000: l NOMH waH.Hl m a . . ms- .u . m H HH sawm mam mmm. mmawn ems; wees sea a- eem.ee seam. 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