None* i 
 
 ho. 305 
 
 STACKS 
 
 3 1175 00503 OGOG 
 
 DIVISION OF AGRICULTURAL SCIENCES 
 UNIVERSITY OF CALIFORNIA 
 
 AN ECONOMIC ANALYSIS 
 OF THE FACTORS AFFECTING 
 THE CALIFORNIA DAIRY INDUSTRY 
 
 By 
 
 Robert A. Milligan 
 
 CALIFORNIA AGRICULTURAL EXPERIMENT STATION 
 GIANNINI FOUNDATION OF AGRICULTURAL ECONOMICS 
 
 Giannini Foundation Research Report No. 325 
 February, 1978 
 
 MAY 1 8 1978 
 
AN ECONOMIC ANALYSIS OF THE FACTORS AFFECTING 
 TI1E CALIFORNIA DAIRY INDUSTRY 
 
 Robert A. Milligan 
 
ACKNOWLEDGEMENTS 
 
 This research was undertaken while the author was a Post-Graduate 
 Research Economist at the University of California, Davis. The author 
 wishes to thank Drs. Harold 0. Carter and Ben C. French of the Depart- 
 ment of Agricultural Economics and Dr. Nathan E. Smith of the Animal 
 Science Department. 
 
 The author also wishes to thank the staff of the California Bureau 
 of Milk Stabilization for their assistance in providing data and for 
 offering insight into the California Dairy Industry. Particular thanks 
 is expressed to Dr. Jed Adams, Mr. Roy Walker, Mr. Robert Abbott, Mr. 
 Gene Carpenter, Mr. Mark Temme, and Mr. Duane Flaten. 
 
 Financial assistance for this study was provided by the California 
 Bureau of Milk Stabilization, the California Agricultural Experiment 
 Station, and by an NDEA fellowship. 
 
TABLE OF CONTENTS 
 
 Page 
 
 LIST OF TABLES iv 
 
 LIST OF FIGURES vi 
 
 INTRODUCTION AND OBJECTIVES 1 
 
 THE CALIFORNIA DAIRY INDUSTRY 3 
 
 Producer Subsector 3 
 
 Processor Subsector 10 
 
 Consumer Subsector 10 
 
 Milk Stabilization Program 14 
 
 The Federal Milk Program 18 
 
 The California Milk Stabilization Program 19 
 
 Evaluation of Milk Stabilization 23 
 
 THE STRUCTURE OF THE CALIFORNIA DAIRY INDUSTRY 24 
 
 Graphical Representation 24 
 
 The Structural Model 26 
 
 Milk Production 27 
 
 Market Milk 31 
 
 Manufacturing Milk 37 
 
 Percent Milkfat and Solids-not-Fat 37 
 
 Processor Prices and Allocation to Final Products 38 
 
 Prices Paid Producers 39 
 
 Allocation to Final Usage 39 
 
 Retail Prices 40 
 
 i 
 
Page 
 
 Demand for Dairy Products 42 
 
 Demand for Fluid Milkfat and Fluid Skim 44 
 
 Demand for Milkfat and Solids-not-Fat in Products .... 46 
 
 Summary of the Structural Model 47 
 
 EMPIRICAL ESTIMATES OF BEHAVIORAL RELATIONSHIPS 47 
 
 Milk Production 54 
 
 The Results 55 
 
 Discussion of the Market Milk Estimates 58 
 
 Southern California 60 
 
 Southern San Joaquin Valley 60 
 
 Northern San Joaquin and Sacramento Valleys 61 
 
 Central Coast 61 
 
 Mountain Areas and North Coast 62 
 
 Discussion of the Manufacturing Milk Estimates 62 
 
 Analysis of Supply Response 63 
 
 Supply Elasticities 63 
 
 Elasticities for Costs and Opportunity Costs .... 65 
 
 Percent Fat and Solids 66 
 
 Processor and Consumer Subsectors 66 
 
 Manufacturing Milk Price 68 
 
 Behavioral Equations for Retail Value of Fat and Solids 
 
 in Products and Consumption of Fluid Products 68 
 
 Retail Value of Fat in Products 69 
 
 Simultaneous Subsystem 70 
 
 Consumption of Fat and Solids in Products 73 
 
 Evaluation of the Model 74 
 
 ii 
 
Page 
 
 SIMULATION OF THE CALIFORNIA DAIRY INDUSTRY 78 
 
 Prediction of Future Exogenous Variables 78 
 
 Operation of the Simulation Model 83 
 
 The Base Model 87 
 
 Simulation Runs with Altered Control Variables 93 
 
 Effects of Changes in All Milk Prices 94 
 
 Effects of Changes in Product Prices 96 
 
 Effects of Changes in Fluid Milk Prices 98 
 
 Effects of Changes in Regional Price Differences 102 
 
 Discussion of the Effect of Price Changes 103 
 
 Simulation Runs with Altered Exogenous Variables 108 
 
 Effects of Changes in Variable Costs of Producers 108 
 
 Effects of Changes in Population Growth Rate 110 
 
 Effects of Changes in Consumer Tastes for Fluid Milk . . . 110 
 
 Discussion of Simulation Runs 112 
 
 SUMMARY AND CONCLUSIONS 115 
 
 APPENDIX A. DATA SOURCES 119 
 
 REFERENCES 131 
 
LIST OF TABLES 
 
 Table Page 
 
 1 Total Production on Farms, Average Production Per Cow, and 
 
 Average Herd Size in California, 1958-1975 5 
 
 2 Average Price Received by Manufacturing and Market Milk 
 
 Producers and Proportion of Production Produced by Market 
 Milk Firms, 1958-1975 7 
 
 3 Estimated Per Capita Consumption of Selected Dairy Products 
 
 in California, 1958-1975 15 
 
 4 Per Capita Consumption of Selected Manufactured Dairy 
 
 Products in the United States, 1958-1975 16 
 
 5 Summary of Selected Studies of U. S. Milk Production Response 28 
 
 6 Price and Income Elasticities for Dairy Products 43 
 
 7 A Reader's Guide to the Structural Model of the California 
 
 Dairy Industry 48 
 
 8 A Comparison of the Results for Selected Variables for the 
 
 Five Regional Market Milk Equations and the Statewide 
 Manufacturing Milk Equation 56 
 
 9 The Effect of Seasonality on Production by Regions with the 
 
 Coefficient on the Dummy Variables Expressed as a Percent- 
 age of Average Production in the Region 59 
 
 10 Margin and Price Elasticities for Milk Produced in California 64 
 
 11 Elasticities Indicating the Responses of Milk Production to 
 
 Costs and Opportunity Costs 67 
 
 12 Elasticities for the Consumption of Fluid Milkfat and Fluid 
 
 Skim Milk 73 
 
 13 Elasticities for the Consumption of Fats and Solids in 
 
 Manufactured Dairy Products 74 
 
 iv 
 
Table 
 
 14 Summary of Occurrence and Non-occurrence of Actual and 
 
 Predicted Turning Points 76 
 
 15 Evaluation Measures Comparing Actual Values with Values 
 
 Predicted by the Model for Selected Endogenous Variables 
 using 1961-1973 Bimonthly Observations 77 
 
 16 Actual Values for 1973 and Predicted Values for 1977, 1981, 
 
 and 1985 for the Endogenous Variables of the Base Model . 88 
 
 17 Comparison of Actual and Simulated Daily Market Milk Produc- 
 
 tion for 1974 and 1975 92 
 
 18 Summary of Results from Simulation Run 1: Changes in All Milk 
 
 Prices 95 
 
 19 Summary of Results from Simulation Run 2: Changes in All 
 
 QQ 
 
 Product Prices " 
 
 20 Summary of Results from Simulation Run 3: Changes in Fluid 
 
 Milk Prices 101 
 
 21 Summary of Results from Simulation Run 4: The Effects on 
 
 Regional Production of Changes in Regional Price Differ- 
 ences 104 
 
 22 A Comparison of the Effects of a General Price Change, a 
 
 Change in Product Prices, and a Change in Fluid Prices. . 105 
 
 23 Summary of Results from Simulation Run 5: Changes in 
 
 Variable Costs of Producers 109 
 
 24 Summary of Results from Simulation Run 6: Changes in Popula- 
 
 tion Growth Rate 111 
 
 25 Summary of Results from Simulation Run 7: Changes in Consumer 
 
 Tastes for Fluid Milk 113 
 
 26 Summary of the Effects of Changes in Selected Control and 
 
 Exogenous Variables 114 
 
 v 
 
LIST OF FIGURES 
 
 F1 Sure Page 
 
 1 A Diagram of the Relationships Among the Four Components of 
 
 the California Dairy Industry 4 
 
 2 Location of the Five Market Milk Production Regions in 
 
 California and Percentage of 1975 Production in Each 
 
 Region 8 
 
 3 Percentage of Total Market Milk Produced in the Five Primary 
 
 Producing Regions of California, 1958-1975 9 
 
 4 Feed Cost per Hundredweight and as a Percent of Fixed and 
 
 Variable Costs, Southern San Joaquin Valley, July 1972- 
 
 Dec. 1974 11 
 
 5 Total Commercial Production, Market Milk Production, and 
 
 Fluid Utilization, 1958-1975 12 
 
 6 Percentage of Commercial Milk Utilized for Fluid Products, 
 
 1958-1975 12 
 
 7 Estimated Utilization of Commercial Milkfat Produced in 
 
 California, 1958-1975 13 
 
 8 Illustration of the Procedure for Determining Quota, Base, 
 
 and Overbase Prices 22 
 
 9 A Graphical Representation of the California Dairy Industry. 25 
 
 10 Flow Chart of the Operation of the Simulation Model 84 
 
 11 Flow Chart of the Procedure Required to Generate Endogenous 
 
 Variables for a Given Time Period 86 
 
 12 Projections of Four Key Endogenous Variables in the Base 
 
 Model 89 
 
 13 Time Paths of Adjustment in Daily Market Milk Production and 
 
 in Market Milk Price Resulting from Increasing All Milk 
 Prices Five Percent 97 
 
 vi 
 
AN ECONOMIC ANALYSIS OF THE FACTORS AFFECTING 
 THE CALIFORNIA DAIRY INDUSTRY 
 
 by 
 
 Robert A. Milligan^ 
 
 INTRODUCTION AND OBJECTIVES 
 
 The dairy industry is an important sector of the California economy. 
 In 1975, cash receipts from farm marketings of dairy products were $997 
 million in California and $9,866 million in the U. S. (Calfornia Crop 
 and Livestock Reporting Service [1976], pp. 9-10). Approximately seven- 
 teen percent of the consumer's food budget is spent on dairy products 
 (George and King [1971]). Producer prices are the most critical component 
 of the retail price of dairy products and have significant ramifications 
 for producers and consumers alike, directly affecting producers and 
 indirectly affecting consumers. Milk prices also have nutritional 
 implications, especially for low income families. 
 
 Of all agricultural prices, producer prices for milk are perhaps the 
 farthest removed from the competitive market. In 1971, 95 percent of all 
 milk meeting the requirements for fluid use was priced under state laws 
 and/or Federal milk orders (Mathis, Friedly, and Levine [1972], p. 2). 
 In California, the prices processors pay most milk producers are estab- 
 lished by the California Bureau of Milk Stabilization. Although these 
 prices are usually adopted as effective prices, officially they are mini- 
 mum prices. 
 
 When the price level is established by a government agency rather 
 than by competitive market forces, some means must be available to obtain 
 and evaluate the information required by the decision-making body. The 
 economist must be careful in performing economic evaluations because many 
 conventional theories and techniques assume perfect competition. Finally, 
 
 — Assistant Professor of Agricultural Economics at Cornell University. 
 
and probably most important, the presence of government control means 
 that the institutional structure, often overlooked by economists assuming 
 perfect competition, becomes a crucial component of the problem. 
 
 The overall objective of this study is to develop economic informa- 
 tion concerning the factors that affect the day-to-day functioning of 
 the California dairy industry. The analysis is designed with the above- 
 mentioned restrictions in mind so that the results should be useful to 
 those individuals responsible for establishing the price paid California 
 milk producers. In meeting this objective, the following subobjectives 
 are established: 
 
 1. To develop a model that delineates those variables that affect 
 the California dairy industry. In developing this model, the 
 prices paid to producers are controlled variables established 
 administratively. The model then must center on determining 
 the effects of changes in these prices. 
 
 2. To package the model so that it can be used by decision-makers 
 in the dairy industry. Fulfilling this subobjective involves 
 designing the model to be used with a minimum knowledge of 
 computers and developing procedures to incorporate additional 
 data as it becomes available. 
 
 3. To utilize the model to investigate the projected effects of 
 important variables including milk price variables, production 
 cost variables, retail prices of dairy products, population, 
 and variables for changing technology and consumer tastes. 
 
 The presentation of the material generated to meet these objectives 
 is accomplished in four major sections. The first delineates some of the 
 important characteristics of the California dairy industry. The second 
 section describes the economic structure of the industry in terms of the 
 apparent relationships among price and other variables included in these 
 relationships. The third section develops the quantitative measurements 
 of the relationships developed in section two. In the final section these 
 measurements are used to investigate the possible effects of alternative 
 pricing policies and changes in other variables affecting the dairy 
 industry. 
 
 2 
 
THE CALIFORNIA DAIRY INDUSTRY 
 
 The California dairy industry is composed of four important 
 components: the three subsectors — producer, processor, and consumer — 
 and the milk stabilization program. Figure 1 illustrates the important 
 relationships among the four components. The producer subsector is 
 composed of market milk firms that meet the sanitary requirements to sell 
 milk for fluid consumption and manufacturing milk firms that do not meet 
 these requirements and sell milk for use only in manufactured dairy 
 products. Therefore, processors of fluid milk products obtain their 
 milk from market milk producers; manufactured dairy product processors 
 purchase the remaining production of market milk firms and the produc- 
 tion of manufacturing milk producers. Consumers purchase dairy products 
 processed by these firms plus additional manufactured dairy products 
 imported from other states. The Bureau of Milk Stabilization assigns 
 quota and base to producers, sets minimum prices processors must pay 
 market milk producers, and until recently had the authority to establish 
 minimum wholesale and retail prices for fluid milk products.— ^ The legal 
 aspects of milk stabilization are discussed after an examination of the 
 three subsectors. • 
 
 Producer Subsector 
 
 California milk production in 1975 was 10,853 million pounds, 
 accounting for 9.4 percent of the U. S. production; only Wisconsin had 
 greater total production (California Crop and Livestock Reporting Service 
 [1976], p. 11). Average production per cow was 13,566 pounds, the 
 highest of any state. Table 1 presents total California production, 
 average production per cow, and average herd size for 1958-1975. The 
 typical California dairy is larger and more specialized than dairies in 
 most other states. 
 
 As indicated above, milk producing firms are of two types. The 
 proportion of milk produced by market milk firms has increased from 35 
 percent in 1935 (Kuhrt [1965], p. 184) to 93 percent in 1974 (California 
 Crop and Livestock Reporting Service [1975], p. 14). A major factor in 
 
 — ^The State's authority to set minimum retail and wholesale prices 
 on fluid milk products was repealed, effective January 1, 1978. 
 
FIGURE 1 
 
 A Diagram of the Relationships Among the Four Components 
 of the California Dairy Industry 
 
 Manufacturing 
 Milk 
 Producers 
 
 Manufactured 
 Dairy Product 
 Processors 
 
 Consumers of 
 Manufactured 
 Dairy Products 
 
 Price Paid 
 
 for Market Milk 
 
 Market 
 Milk 
 Producers 
 
 Fluid 
 Milk 
 Processors 
 
 Consumers 
 of Fluid 
 Milk 
 
 Quota 
 ,Base 
 
 Price 
 
 Paid 
 Produc- 
 ers 
 
 Bureau of 
 Milk 
 Stabi lization 
 
 Retail 
 
 Price: 
 
 IT 
 
 Manufactured Dairy 
 Products from 
 Other States 
 
 —On January 6, 1977 all minimum price controls on retail prices were 
 suspended. Effective January 1, 1978 the authority to set minimum 
 retail prices was repealed. 
 
TABLE 1 
 
 Total Production on Farms, Average Production Per Cow, and 
 Average Herd Size in California, 1958-75 
 
 Total a j Average production j, 
 
 production— per cowi*/ Average herd size- 
 
 Year (million lbs.) (pounds) (cows) 
 
 1958 
 
 7,586 
 
 8,730 
 
 158 
 
 1959 
 
 7,947 
 
 8,950 
 
 163 
 
 1960 
 
 8,109 
 
 9,770 
 
 166 
 
 1961 
 
 8,236 
 
 10,130 
 
 169 
 
 1962 
 
 8,316 
 
 10,330 
 
 176 
 
 1963 
 
 8,307 
 
 10,410 
 
 180 
 
 1964 
 
 8,540 
 
 10,810 
 
 185 
 
 1965 
 
 8,488 
 
 10,840 
 
 190 
 
 1966 
 
 8,569 
 
 11,100 
 
 199 
 
 1967 
 
 8,724 
 
 11,170 
 
 215 
 
 1968 
 
 8,950 
 
 11,460 
 
 225 
 
 1969 
 
 8,940 
 
 11,521 
 
 233 
 
 1970 
 
 9,494 
 
 11,957 
 
 253 
 
 1971 
 
 9,706 
 
 11,985 
 
 270 
 
 1972 
 
 10,430 
 
 13,406 
 
 294 
 
 1973 
 
 10,348 
 
 13,066 
 
 312 
 
 1974 
 
 10,601 
 
 13,301 
 
 332 
 
 1975 
 
 10,853 
 
 13,566 
 
 352- 
 
 a/From California Crop and Livestock Reporting Service [1959-1976], 
 Table 3. 
 
 b/Calculated from California Bureau of Milk Stabilization [1st 
 " quarter 1958— 4th quarter 1973] . 
 
 c/Estimated. 
 
 5 
 
this shift has been the differential between market and manufacturing 
 prices. This difference is larger than the additional costs required to 
 produce market milk. Table 2 contains market and manufacturing milk 
 prices and the share of total milk produced by market milk firms. Milk 
 prices remained relatively constant until 1966 when a gradual increase 
 began and continued until the substantial increases in the 1973-1975 
 period. 
 
 Although milk is produced in all parts of California, production is 
 centered near large metropolitan areas and in the Central Valley. Manu- 
 facturing milk production is concentrated in the San Joaquin Valley, 
 especially Stanislaus and Merced Counties, with additional production in 
 the Sacramento Valley and North Coast Area. Market milk production is 
 centered in the San Joaquin Valley and Southern California,-^ particularly 
 San Bernardino and Riverside Counties. In this study market milk produc- 
 tion is separated into the five regions shown in Figure 2. The Southern 
 California region (1) produces fluid milk for the Los Angeles area and 
 is characterized by large, specialized dairies that purchase nearly all 
 feed inputs and replacements. Producers in the South San Joaquin Valley 
 (2) typically ship milk to Los Angeles from dairies that are larger and 
 more specialized than in other parts of the Central Valley, but not as 
 large or specialized as those in Southern California. Milk produced in 
 the North San Joaquin and Sacramento Valleys (3) is usually shipped to 
 the Bay Area or processed in Sacramento. In the Central Coast Area (4), 
 milk is produced on smaller dairies primarily for consumption in the Bay 
 Area. Production in Mountain Areas and the North Coast (5) is for local 
 markets and has limited significance to the dairy industry of the state. 
 
 These dairies are few and small. Figure 3 depicts the change in importance 
 
 2/ 
 
 of the four significant regions over the last 16 years. - 
 
 In 1972-74, producers were faced with rapidly escalating costs, 
 particularly for feed inputs. In two and one-half years feed costs almost 
 
 —In 1975 85.6 percent of the market milk production was in these two 
 areas (Calculated from California Crop and Livestock Reporting Service 
 [1976], Table 8). 
 
 2/ 
 
 — North Coast and Mountain Areas decreased slowly from 1.6 percent 
 in 1958 to 1.1 percent in 1975. 
 
 6 
 
 I 
 
TABLE 2 
 
 Average Price Received by Manufacturing and Market Milk Producers 
 and Proportion of Production Produced by Market Milk Firms, 1958-1975 
 
 Manufacturing Market milk a j Percentage of 
 
 milk priced' priced' Difference— production by 
 Year ($/cwt.) ($/cwt.) ($/cwt.) market milk firms*!' 
 
 1958 
 
 3.21 
 
 4.68 
 
 1. 47 
 
 79 . 7 
 
 1959 
 
 3.28 
 
 4. 74 
 
 1.46 
 
 81. y 
 
 1960 
 
 3 . 20 
 
 A "7 "7 
 
 1.3/ 
 
 on o 
 oU . Z 
 
 1961 
 
 3. 33 
 
 4 . 71 
 
 1.38 
 
 on *7 
 oU . / 
 
 1962 
 
 3.21 
 
 4 . 69 
 
 1.48 
 
 81.0 
 
 1963 
 
 3.21 
 
 4.63 
 
 1.42 
 
 Q *3 Q 
 
 oj.3 
 
 1964 
 
 3.39 
 
 4.60 
 
 1.21 
 
 88.2 
 
 1965 
 
 3.41 
 
 4.66 
 
 1.25 
 
 88.3 
 
 1966 
 
 3.88 
 
 4.81 
 
 0.93 
 
 89.8 
 
 1967 
 
 4.02 
 
 4.97 
 
 0.95 
 
 89.7 
 
 1968 
 
 4.12 
 
 5.11 
 
 0.99 
 
 90.8 
 
 1969 
 
 4.21 
 
 5.25 
 
 1.04 
 
 90.9 
 
 1970 
 
 4.47 
 
 5.45 
 
 0.98 
 
 90.7 
 
 1971 
 
 4.72 
 
 5.64 
 
 0.92 
 
 89.8 
 
 1972 
 
 4.83 
 
 5.70 
 
 0.87 
 
 89.0 
 
 1973 
 
 5.46 
 
 6.56 
 
 1.10 
 
 91.4 
 
 1974 
 
 6.65 
 
 8.32 
 
 1.67 
 
 93.1 
 
 1975 
 
 7.40 
 
 8.95 
 
 1.55 
 
 93.6 
 
 -California Crop and Livestock Reporting Service [1959-1974], Tables 
 22 and 23, 1958; Tables 21 and 22, 1959-1960; Tables 15 and 16, 
 1961-1972; Tables 14 and 15, 1973-1975. 
 
 -^Calculated from California Crop and Livestock Reporting Service 
 [1959-1974], Tables 25 and 27, 1958; Tables 24 and 26, 1959-1960; 
 Table 18, 1961-1972; Table 17, 1973-1975. 
 
 7 
 
 ■ 
 
FIGURE 2 
 
 Location of the Five Market Milk Production Regions in California 
 and Percentage of 1975 Production in Each Region 
 
 8 
 
FIGURE 3 
 
 50 
 
 40 
 
 30 
 
 Percent 
 
 20 
 
 10 
 
 Percentage of Total Market Milk Produced in each of Four Primary Producing Regions 
 
 of California, 1958-1975^ 
 
 SOUTHERN CALIFORNIA 
 
 NORTHERN SAN JOAQUIN AND SACRAMENTO 
 
 CENTRAL COAST 
 
 58 
 
 59 
 
 60 
 
 61 
 
 62 
 
 63 
 
 64 
 
 65 
 
 66 
 
 a/ 
 
 67 
 
 68 
 
 69 
 
 70 
 
 71 
 
 72 
 
 73 
 
 74 
 
 75 
 
 -Calculated from California Crop and Livestock Reporting Service [1959-1975], Table 7, 1958-59; Table 8, 1960-1975, 
 
doubled. This increase is illustrated for the Southern San Joaquin 
 region in Figure 4. These rapid increases have created considerable 
 adjustment problems for the dairy industry. 
 
 Processor Subsector 
 
 The processor subsector is composed of two segments: fluid and 
 manufacturing. Due to the perishability of fluid milk products, it 
 can be assumed that fluid products are produced and processed within 
 the state.— ^ Most manufactured dairy products, on the other hand, are 
 sold in a national market. The exceptions are frozen dairy products and 
 cottage cheese. Since fluid products have higher selling prices, produc- 
 ers are anxious to have a large proportion of their milk utilized for 
 fluid products. Figure 5 illustrates the changes in utilization in the 
 last eighteen years; Figure 6 reviews the percentage of production used 
 for fluid milk. As can be seen from these figures, the quantity and the 
 proportion of production devoted to fluid uses has declined, resulting 
 in increased use in manufactured dairy products. 
 
 First call on milk available for manufactured dairy products is for 
 frozen dairy products and cottage cheese because returns are somewhat 
 higher and the relevant market is more localized due to product perish- 
 ability. Milk which remains is then used for other manufactured dairy 
 products including hard cheese, butter, and evaporated and condensed 
 milk. Forker [1965] predicted that this residual would approach zero by 
 1975. Although this prediction has proven to be inaccurate, it does 
 indicate one possible direction for the industry. Figure 7 reviews the 
 estimated utilization of commercial milkfat produced in California. 
 
 Consumer Subsector 
 
 A downward trend in total consumption of dairy products and consump- 
 tion of fluid milk has persisted for many years. Per capita consumption 
 
 — In December 1975, less than 0.1 percent of the fluid milk processed 
 in California was sold out of the state (California Crop and Livestock 
 Reporting Service [1976a]). The assumption is realistic because of the 
 hauling distance due to the mountains surrounding California and would not 
 be tenable in most states. 
 
 10 
 
FIGURE 4 
 
 Feed Cost Per Hundredweight and as a Percent of Fixed and Variable Costs, 
 
 a/ 
 
 Southern San Joaquin Valley, July 1972-Dec. 1974- 
 
 dollars/cwt. percent 
 
 6.00 
 5.75 . 
 5.50 - 
 
 
 
 
 
 Percentage of 
 Variable Costs 
 
 / 
 
 / 
 
 / 
 
 
 
 
 
 78 
 76 
 74 
 
 5.25 - 
 5.00 - 
 4.75 - 
 
 
 
 
 / 
 
 s 
 
 / 
 
 
 Feed Cost . 
 
 y 
 
 
 
 
 72 
 70 
 68 
 
 4.50 - 
 
 
 
 
 
 
 
 
 
 
 
 66 
 
 4.25 " 
 4.00 ■ 
 3.75 - 
 3.50 - 
 
 
 
 
 
 r / 
 
 / — 
 
 v 
 
 
 Percentage of 
 
 Fixed 
 
 Costs 
 
 64 
 62 
 60 
 
 58 
 
 3.25 " 
 3.00 ' 
 
 
 
 / 
 
 ' 
 
 
 
 
 
 
 
 
 56 
 54 
 
 2.75 " 
 
 
 1 
 
 i 
 
 I I 
 
 1 1 
 
 1 1 
 
 i 
 
 i i i 
 
 
 1 
 
 52 
 
 July 
 Aug 
 
 Sept 
 Oct 
 
 1972 
 
 Nov 
 Dec 
 
 Jan Mar 
 Feb Apr 
 
 May Jul 
 June Aug 
 
 1973 
 
 Sept Nov 
 Oct Dec 
 
 Jan 
 Feb 
 
 Mar May Jul 
 Apr June Aug 
 
 1974 
 
 Sept 
 Oct 
 
 Nov 
 Dec 
 
 
 a/ 
 
 — Calculated from California Bureau of Milk Stabilization (3rd quarter 1972-November-December 
 1974] Southern San Joaquin Valley Production Area. The figures are averages of the 
 producers surveyed in the region. Eighty to one hundred thirty samples were typical in 
 this period. 
 
 11 
 
 11 
 
FIGURE 5 
 
 Total Commercial Production, Market Milk Production, 
 and Fluid Utilization, 1958-1975^ 
 
 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 
 
 a/ 
 
 California Crop and Livestock Reporting Service [1976] Table 17. 
 
 FIGURE 6 
 
 a/ 
 
 Percentage of Commercial Milk Utilized for Fluid Products, 1958-1975- 
 
 80 . 
 
 70 
 
 60 
 
 30 
 
 Percentage of Market Milk 
 
 _l I I i_ 
 
 Percentage of All Milk 
 
 _l I I l_ 
 
 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 
 
 a/ 
 
 -Calculated from California Crop and Livestock Reporting Service [1976], Table 17. 
 
 12 
 
FIGURE 7 
 
 Estimated Utilization of Commercial Milkfat Produced in California, 1958-1975- 
 
 — From California Crop and Livestock Reporting Service [1976], Table 16. Other manufactured dairy products 
 accounted for 4.2 to 6.5 percent of the milkfat. 
 
 13 
 
for California can be estimated accurately for the perishable products 
 that are processed for a local market: fluid products, cottage cheese, 
 buttermilk, and frozen dairy products. Table 3 shows the trend in 
 consumption of these products. Consumption of fluid milk and buttermilk 
 has steadily declined. Only U. S. consumption data are available for 
 the remaining manufactured dairy products and are presented in Table 4. 
 
 Consumers, as well as producers, have been adversely affected by 
 increased feed costs since these increased costs have been reflected in 
 increased retail prices. Consumer groups have responded by severely 
 criticizing the milk stabilization program. These groups have demanded 
 and received representation at the hearings called to consider price 
 increases.—'' As a result of consumer pressure on state legislators, the 
 Senate Committee on Agriculture and Water Resources has held lengthy 
 hearings on milk stabilization, numerous bills have been introduced in 
 the State Legislature, and the authority to establish minimum wholesale 
 and retail prices on fluid milk products has been repealed. 
 
 Milk Stabilization Program 
 
 Clarke [1961, 1968] has argued that due to special characteristics 
 of the dairy industry some form of price control is necessary to avoid 
 an unstable market. The characteristics mentioned are: 
 
 1. The nature of the product; there are no close substitutes. 
 
 2. The bargaining disparity created by the industry structure 
 of many producers and few distributors and retailers. 
 
 3. The continuous buyer-seller relationship along with the 
 perishability of milk can force the producer to take almost 
 any price that is offered. 
 
 Prior to the depression of the 1930 's, producer organizations 
 exerted sufficient price control to maintain reasonable stability in 
 
 — The mechanism for price increases is discussed in the following 
 section. 
 
 14 
 
TABLE 3 
 
 Estimated Per Capita Consumption of Selected Dairy Products 
 in California, 1958-1975^ 
 
 
 Fluid 
 
 Cottage 
 
 
 Frozen 
 
 
 products 
 
 cheese 
 
 Buttermilk 
 
 products 
 
 Year 
 
 (quarts) 
 
 (pounds) 
 
 
 
 1958 
 
 145.89 
 
 8.19 
 
 4.47 
 
 23.50 
 
 1959 
 
 144.72 
 
 8.27 
 
 4.23 
 
 23.67 
 
 1960 
 
 140.85 
 
 8.18 
 
 3.99 
 
 22.98 
 
 1961 
 
 136.85 
 
 7.77 
 
 3.75 
 
 22.99 
 
 1962 
 
 135.32 
 
 7.50 
 
 3.54 
 
 23.23 
 
 1963 
 
 136.02 
 
 7.47 
 
 3.49 
 
 23.43 
 
 1964 
 
 137.12 
 
 7.43 
 
 3.36 
 
 24.04 
 
 1965 
 
 133.99 
 
 7.34 
 
 3.25 
 
 24.52 
 
 1966 
 
 134.80 
 
 7.14 
 
 3.13 
 
 24.69 
 
 1967 
 
 131.88 
 
 7.14 
 
 2.97 
 
 24.23 
 
 1968 
 
 129.72 
 
 7.25 
 
 2.83 
 
 24.47 
 
 1969 
 
 126.87 
 
 7.55 
 
 2.86 
 
 24.07 
 
 1970 
 
 125.41 
 
 8.26 
 
 2.93 
 
 24.02 
 
 1971 
 
 123.81 
 
 8.34 
 
 2.96 
 
 23.34 
 
 1972 
 
 128.01 
 
 8.24 
 
 2.94 
 
 23.49 
 
 1973 
 
 128.34 
 
 7.88 
 
 2.78 
 
 22.73 
 
 1974 
 
 127.85 
 
 7.16 
 
 2.51 
 
 23.67 
 
 1975 
 
 128.60 
 
 6.84 
 
 2.42 
 
 23.96 
 
 a/ 
 
 — From California Crop and Livestock Reporting Service [1976] Table 64. 
 
 15 
 
TABLE 4 
 
 Per Capita Consumption of Selected Manufactured Dairy 
 
 a/ 
 
 Products in the United States, 1958-1975- 
 
 Data 
 
 Butter 
 (pounds) 
 
 Hard 
 cheese 
 (pounds) 
 
 Evaporated & 
 condensed milk 
 (pounds) 
 
 Dry milk 
 products 
 (pounds) 
 
 lotal milk 
 solids 
 (pounds) 
 
 1958 
 
 8.3 
 
 8.1 
 
 19.0 
 
 6.8 
 
 69.4 
 
 1959 
 
 7.9 
 
 8.0 
 
 19.0 
 
 7.3 
 
 68.8 
 
 1960 
 
 7.5 
 
 8.3 
 
 18.2 
 
 7.3 
 
 67 .9 
 
 1961 
 
 7.4 
 
 8.6 
 
 18.1 
 
 7.3 
 
 67 .0 
 
 1962 
 
 7.3 
 
 9.2 
 
 17.3 
 
 7.3 
 
 66.9 
 
 1963 
 
 6.9 
 
 9.2 
 
 16.1 
 
 7.0 
 
 65 . 7 
 
 1964 
 
 6.9 
 
 9.4 
 
 16. 1 
 
 7 . 1 
 
 66 . U 
 
 1965 
 
 6.4 
 
 9 .6 
 
 15.7 
 
 7.0 
 
 65 . 6 
 
 1966 
 
 5.7 
 
 9.8 
 
 15.1 
 
 "7 1 
 
 7 . 3 
 
 64 . 7 
 
 1967 
 
 5.5 
 
 10.1 
 
 14.0 
 
 7.1 
 
 63.0 
 
 1968 
 
 5.7 
 
 10.6 
 
 13.7 
 
 7.2 
 
 63.0 
 
 1969 
 
 5.4 
 
 11.0 
 
 12.8 
 
 7.2 
 
 62.6 
 
 1970 
 
 5.3 
 
 11.5 
 
 12.1 
 
 6.8 
 
 61.7 
 
 1971 
 
 5.1 
 
 12.2 
 
 11.9 
 
 6.8 
 
 62.2 
 
 1972 
 
 4.9 
 
 13.2 
 
 11.1 
 
 6.7 
 
 62.8 
 
 1973 
 
 4.8 
 
 13.7 
 
 10.3 
 
 7.4 
 
 62.6 
 
 1974 
 
 4.6 
 
 14.6 
 
 9.1 
 
 6.6 
 
 61.2 
 
 1975^ 
 
 4.8 
 
 14.5 
 
 8.9 
 
 5.7 
 
 61.1 
 
 - Data for 1958-1959 are from Hiemstra [1968], for 1960-1975 are from 
 U. S. Department of Agriculture [1976]. 
 
 b/ 
 
 — Preliminary. 
 
 16 
 
California milk markets.— With the diminished demand during the 
 depression, producer organizations lost almost all effectiveness. 
 By the early 1930 's the situation was chaotic. Price wars were 
 common with the store price of milk falling to as low as one cent 
 per quart. Most of the price decline was passed back to producers; 
 instances of producers not being paid at all were common. 
 
 By mid-1932 the situation had deteriorated to the point where 
 violence was feared, particularly in the Los Angeles milkshed. 
 After an urgent appeal to the Governor by producers, officials of 
 the Division of Markets were able to mediate an agreement which 
 brought reasonable although tenuous stability to the Los Angeles 
 area. After Congress passed the Agricultural Adjustment Act of 1933, 
 milk officials in Los Angeles and other California markets applied for 
 Federal orders; however, within a year the courts ruled the program 
 could not be enforced as milk production in California was local in 
 nature and not a part of interstate commerce. 
 
 In 1935, a bill to establish minimum producer prices, the Young 
 
 Act, easily passed the State Legislature and was signed by the Governor. 
 
 Under this program the Director of Agriculture could establish minimum 
 
 producer prices for market milk upon approval of market milk producers 
 
 representing 65 percent of their number and of the production in an 
 
 established marketing area. Pricing of manufacturing milk was not 
 
 included in the legislation. The basic legislation remains in effect 
 
 although amendments to update and modify the procedures have been 
 
 enacted in nearly every legislative session. All producing areas have 
 
 voted to be in the program. In 1937 passage of the Desmond Act extended 
 
 minimum price control to wholesale and retail prices of fluid milk 
 2/ 
 
 products .— 
 
 Although the Young and Desmond Acts and their amendments are 
 the basis of the California Milk Stabilization Program, action taken 
 
 — The history of milk stabilization in California is discussed 
 by Kuhrt [1965] and in great detail by Tinley [1938], especially 
 chapters one through three. The discussion in this section emanates 
 from these sources. 
 
 2/ 
 
 — See footnote 1, page 3. 
 
 17 
 
under Federal legislation also affects the California dairy industry. 
 Therefore, a brief review of the Federal milk stabilization program is 
 included prior to a more detailed discussion of the California milk 
 stabilization program. 
 
 The Federal Milk Program^ 
 
 Federal regulation related to the dairy industry is contained in 
 two programs. The first is known as the "Dairy Price Support Program". 
 This program was developed to carry out provisions of the Agricultural 
 Act of 1949 requiring that the price of manufacturing milk and certain 
 of its products be supported at between 75 and 90 percent of parity. 
 The second, the "Federal Milk Marketing Order Program", is designed to 
 implement the provisions of the Agricultural Marketing Agreement Act of 
 1937. Its purpose is to establish the minimum differential between the 
 producer price of manufacturing milk in Minnesota and Wisconsin and the 
 price paid for milk used in fluid products in any area of the country 
 which has voted to join this program (Federal order market). The minimum 
 price paid producers in these Federal order markets for milk used in 
 fluid products is then the Minnesota-Wisconsin manufacturing milk price 
 plus the differential established by the Secretary of Agriculture. This 
 program does not significantly affect the California dairy industry. 
 
 The price support program, on the other hand, has an important impact 
 on the California dairy industry since most manufactured dairy products 
 compete in a national market. Under this program, the Secretary of 
 Agriculture announces a support price for manufacturing milk, butterfat 
 (in farm-separated cream), butter, cheddar cheese, and nonfat dry milk. 
 The price for manufacturing milk and butterfat is the minimum that can 
 be paid producers; the support for the three products is maintained by 
 Commodity Credit Corporation purchases of all excess production. Because 
 of ease of diverting milk among products, these purchases effectively 
 establish a floor under the price of all manufactured dairy products. 
 
 — The discussion in this section is based on the material in 
 Vial [1972]. 
 
 18 
 
The California Milk Stabilization Program-' 
 
 The objectives of milk stabilization as recorded in the Agricul- 
 tural Code [1969, Division 21, Part 3, Chapter 2, Article 4] are: 
 
 1. To maintain an adequate supply of pure and wholesome milk. 
 
 2. To eliminate unfair and destructive trade practices which 
 tend to undermine the quality and availability of milk to 
 the inhabitants of the state. 
 
 3. To promote and maintain efficiency, stability, and reason- 
 able prosperity in the milk industry. 
 
 In meeting these objectives, the Bureau of Milk Stabilization and the 
 Director of Food and Agriculture have exercised four types of control: 
 
 1. Set minimum (usually adopted as effective) prices to be 
 paid by distributors to market milk producers. 
 
 2. Set minimum wholesale and retail prices for fluid milk 
 
 2/ 
 
 products .— 
 
 3. Determine the location differentials for quota milk. 
 
 4. Calculate the base and quota for each producer. 
 
 Minimum prices to be paid by distributors are established by 
 
 components for four classes of market milk. These four classes are 
 
 based upon utilization of the milk as specified in the Agricultural 
 
 3/ 
 
 Code [1969, Division 21, Part 3, Chapter 2, Article 3] :- 
 
 1. Class 1 comprises all fluid milk, fluid skim milk, or fluid 
 cream supplied to consumers as fluid milk, fluid low fat, 
 fluid skim, half-and-half, and yogurt. 
 
 — ^The legal basis for milk stabilization is contained in Division 
 21, Part 3, Chapters 2 and 3 of the Agricultural Code of California [1969]. 
 
 2/ 
 
 — See footnote 1, page 3. 
 3/ 
 
 — This interpretation of the lengthy legal description in the code 
 follows Kuhrt [1965]. Specific product references are from the California 
 Department of Food and Agriculture [1974]. A complete classification is 
 available in the California Department of Food and Agriculture [1974, p. 
 14]. 
 
 19 
 
2. Class 2 comprises any fluid milk, fluid skim milk, or fluid 
 cream which is used in the manufacture of any product not 
 included in class 1, class 3, or class 4. Commonly used products 
 are the heavy creams, cottage cheese, and sterilized milk 
 products. 
 
 3. Class 3 comprises all fluid milk, fluid skim milk, or fluid 
 cream which is used in frozen dairy products. 
 
 4. Class 4 comprises all fluid milk, fluid skim milk, or fluid 
 cream used in the manufacture of butter, hard cheese, and 
 nonfat dry milk po\<rder. 
 
 5. In addition, the condensed and evaporated milk products shall 
 be assigned to the classification of ultimate usage. 
 
 Class 1 and some class 2 products (the heavy creams and cottage cheese) 
 must be made from market milk.— ^ Processors of the remaining products 
 can use market or manufacturing milk. 
 
 The Bureau employs component pricing, whereby producers are paid for 
 
 the milk fat and solids-not-fat content of their milk. Only in class 1 
 
 is any value attributed to the residual liquid carrier. Because of 
 
 competition with manufacturing milk and the national market for most 
 
 manufactured dairy products, class 2, class 3, and class 4 prices must 
 
 be in line with prevailing prices throughout the country. At the present 
 
 time class 4 milk fat price is determined by a formula based on either 
 
 the butter price on the Chicago Mercantile Exchange or the Federal support 
 
 price for butter in California. Each price is adjusted for processing 
 
 and transportation costs, and the larger of the two prices is used. 
 
 Similarly, the solids-not-fat price is based on either a weighted average 
 
 price for nonfat dry milk f.o.b. California plants or the Federal support 
 
 2/ 
 
 price for nonfat dry milk.— Class 2 and class 3 prices are determined 
 by addition of a predetermined differential to the preceding month's 
 class 4 price. 
 
 — The requirement that certain class 2 products must be made from 
 market milk was implemented January 1, 1974. This requirement should 
 have little influence on this study because of the large volume of 
 market milk available for manufactured products. 
 
 2/ 
 
 — Further details including some history and an example are 
 contained in the California Department of Food and Agriculture [1974]. 
 
 20 
 
Minimum class 1 prices are announced by the Director of Food and 
 Agriculture after consideration of the testimony of interested parties 
 at one or more public hearings. Because almost all class 1 milk 
 products are produced and marketed within the state, California market 
 conditions are given primary consideration in this decision process. 
 Supply and demand factors, milk production costs, and price stability 
 considerations are evaluated, but no precise formula exists with 
 weights for these and other factors. 
 
 Once the above classified prices are established, actual producer 
 returns depend on the statewide proportion of market milkfat and solids 
 utilized in each product class. Producers were formerly paid according 
 to utilization in the milk processing plant to which they shipped. 
 However, the Gonsalves Milk Pooling Act passed in 1967 authorized state- 
 wide pooling to overcome inequities arising from the individual handler 
 pooling system.—^ 
 
 Under this system, each market milk producer was assigned a produc- 
 tion base for fat and solids equal to average daily production in 1966 
 or 1967 (the base years). The class 1 portion of the base year shipments, 
 increased by 10 percent, became the producer's quota. New quota is 
 allocated whenever there is an increase in class 1 sales, with 20 percent 
 going to new producers and the remainder to existing producers. The 
 largest allocations are given to dairymen with the lowest quotas relative 
 to their production base. 
 
 Each producer is paid a blend price determined by the relative 
 amounts of his production sold as quota, base (production base minus 
 
 2/ 
 
 quota), and overbase (shipments over production base) fat and solids.— 
 As illustrated in Figure 8, the value for quota payments is derived 
 from the highest valued uses of the milk. The value from milk utilized 
 in all class 1 and some class 2 products is usually required to meet 
 quota payments. After the value is allocated to quota, the value of 
 
 —^Discussion of the inequities of individual plant pools and develop- 
 ment of the statewide pool can be found in Kuhrt [1972], Ortego, Forker, 
 and Courtney [1967], and California Agricultural Experiment Station [1964], 
 
 2/ 
 
 — Details of the allocation of quota and production base are detailed 
 in California Department of Food and Agriculture [1974] and California 
 Department of Food and Agriculture [1973] . 
 
 21 
 
FIGURE 8 
 
 Illustration of the Procedure for Determining 
 Quota, Base, and Overbase Prices 
 
 Class 1 
 
 Class 2! 
 
 1 
 
 Class 3 
 
 1 
 
 1 
 
 Class 4 
 
 1 
 
 
 1 
 1 
 
 Quota 
 
 Base 
 
 Over- 
 Base 
 
 the highest valued classes remaining is allocated to the base price. 
 The allocation to quota and base have always required all utilization 
 in classes 1-3 and some of the utilization in class 4; consequently, the 
 overbase price has been the same as the class 4 price. These calcula- 
 tions are executed independently for milkfat and solids-not-fat. 
 
 The only adjustment to the above procedure is for location differ- 
 entials. These adjustments are applied to quota only and are based on 
 the location of the plant that first receives the milk. They are 
 designed to encourage producers to make milk available to plants in 
 areas with large fluid consumption, namely the Los Angeles and San 
 Francisco areas. 
 
 Until recently, the Milk Stabilization Program had the power to 
 establish minimum wholesale and retail prices for class 1 products. The 
 general procedure was to pass price increases at the farm level on to 
 consumers keeping the margin constant. Adjustments in margins were made 
 when other costs changed. In January 1977, all minimum wholesale and 
 retail prices were suspended. Effective January 1, 1978, the authority 
 to establish minimum prices was repealed. Minimum prices can be 
 reimposed for no more than 90 days under conditions of severe market 
 disruption. 
 
 22 
 
 I 
 
Evaluation of Milk Stabilization 
 
 On two occasions, in the mid-fifties and again in the mid-sixties, 
 extensive evaluations of the milk stabilization program have been 
 conducted. The results have been reported in California Agricultural 
 Experiment Station [1964], Clarke [1955], Hammerberg [1965], Ortego, 
 Forker, and Courtney [1967], Revzan [1965], and Warner [1965]. In 
 each case the results were generally favorable, finding that prices 
 were in line with those in other areas of the country. Ortego, Forker, 
 and Courtney [1967] using cross-sectional (analysis of covariance) 
 and comparative analysis found class 1 prices to be about the same 
 as in uncontrolled markets and markets under Federal milk orders. The 
 price level in California was found, however, to be somewhat lower than 
 in other state controlled markets. In both evaluations, actual and 
 potential areas of inefficiency were exposed. Many of these have been 
 corrected by subsequent legislation. 
 
 More recent comparisons are made in California Department of Food 
 and Agriculture [1974]. This report indicates that class 1 prices in 
 California have been below the average of all Federal Milk Marketing 
 Areas since 1966. In May 1974 the differential was 44 cents. Further- 
 more, the marketing margin is found to be less than the average of 19 
 other cities as of February 1974. 
 
 In spite of the information provided by comparative analyses of 
 this type, three inadequacies are present. First, the analysis concerns 
 past prices and may rapidly become dated. This problem is aggravated 
 by the current price instability. Second, due to the various forms of 
 price controls, few even approximately competitive milk markets remain 
 for comparison. Finally, such comparisons may be of limited value. 
 The prices should be based on supply-demand conditions which are not 
 necessarily equivalent in the regions compared. It is possible that a 
 lower California price is required to generate producer profits equal 
 to other regions due to the favorable climate and the institutional 
 structure that has resulted in large, efficient producing units. 
 
 One attempt at overcoming these problems was a simulation model 
 of fluid aspects of the California dairy industry. Desai [1968] 
 
 23 
 
simulated four institutional arrangements including the present arrange- 
 ment,—^ a similar arrangement with class 1 prices tied to Midwest prices, 
 a nationwide pooling scheme, and an unregulated industry. The author 
 concludes that the alternative systems can achieve lower producer and 
 retail prices. 
 
 THE STRUCTURE OF THE CALIFORNIA DAIRY INDUSTRY 
 
 The first step in delineating the effects of the key variables on 
 producers, processors, and consumers in the California dairy industry is 
 to develop a representation of the underlying economic structure of the 
 industry. Included in the "structure" are relationships between costs, 
 prices, and quantities produced or sold in the producer, processor, and 
 consumer subsectors of the industry. 
 
 This section commences with a graphical outline of the structure of 
 the industry. Following an overview of the relationships in the system, 
 each equation or set of equations is described and discussed. The result 
 of this section is a system of relationships that can be used to measure 
 the effects of the specified variables on producers, processors, and 
 consumers in California. 
 
 Graphical Representation 
 
 Figure 9 depicts the important relationships in the California dairy 
 industry. For simplicity, the regional specification of market milk 
 production and the utilization of milk as milkfat and solids-not-fat are 
 excluded. Those variables whose values are determined primarily within 
 the sector (endogenous variables) are indicated by rectangles, while 
 variables whose levels are important to the industry but are determined 
 in other sectors of the economy (exogenous variables) are represented by 
 ovals. The numbers in parentheses in the rectangles reference the appro- 
 priate equation(s) in the structural model (Table 7) outlined later. 
 The arrows indicate the expected direction of major influence. 
 
 — The arrangement at the time consisted of handler pooling rather 
 than statewide pooling. 
 
 24 
 
FIGURE 9 
 
 A Graphical Representation of the California Dairy Industry 
 
 
 \ 
 
 Class 1, 2, 3, \ 
 
 ^ and A 
 
 prices J 
 
 
 
 Market milk 
 
 price 
 
 (15 
 
 i 
 
 -16) 
 
 
 
 Manufacturing 
 milk price * 
 (17) 
 
 
 
 Federal 
 support 
 price 
 
 Retail value 
 of products 
 (22-23) 
 
 Federal 
 support 
 prices 
 
 Labor costs 
 for products J 
 
 Class 2, 3, 
 and 4 prices 
 
 Retail fluid 
 milk price 
 
 1 Population 
 
 Consumer 
 age distribution 
 and tastes 
 
 Population 
 
 / \ 
 
 / Consumer income, V 
 
 \ age distribution ! 
 
 \ and tastes 
 
 Products from 
 other states 
 
The lefthand section of the graph indicates those factors from 
 previous periods that affect the current production of market and manu- 
 facturing milk. These variables include the prices of market and 
 manufacturing milk, production costs, returns from alternative uses of 
 resources, and technological advances. In addition, current costs and 
 returns from alternative uses of resources affect production. Due to 
 the time-consuming procedure used to establish the price paid to the 
 market milk producer, the price currently received is not known prior 
 to the end of the bimonthly time period used in this study. 
 
 The available supply of market milk is first used to satisfy the 
 demand of fluid milk processors. The remaining market milk supply and 
 the manufacturing milk supply are used to satisfy the demands of manu- 
 facturers of dairy products other than fluid milk.— ^ Although the 
 manufacturing milk price is not a controlled price, its level is in 
 line with the class 2, 3, and 4 market milk price and the Federal support 
 price for manufacturing milk. The average market milk price is a weighted 
 average of the established class 1-4 prices with utilization in each class 
 as the weights. 
 
 The consumption of products depends upon the retail value (price) 
 of these products and exogenous factors. The consumption of fluid milk 
 is influenced by the retail price with its controlled minimum level, by 
 numerous exogenous factors, and by the retail value of milk products; 
 however, the dashed line for this last relationship is used to indicate 
 that the influence may be minor. 
 
 The Structural Model 
 
 To more precisely define the relationships described above, the 
 
 2/ 
 
 system outlined in Figure 9 must be given specific mathematical form.— 
 The model specified contains 27 equations; 13 of the equations are 
 specified to measure the economic behavior of different segments of the 
 
 — ^The exception to this simple scenario is that certain class 2 
 products (see previous section) must now be made from market milk. 
 2/ 
 
 — Readers interested in results but not the quantitative procedures 
 used to obtain these results should skip to the section on empirical 
 estimates beginning on page 47. 
 
 26 
 
industry. These 13 equations are referred to as behavioral relationships 
 and contain unknown parameters (coefficients) to be statistically esti- 
 mated. The remaining equations are identities required to complete the 
 system. 
 
 The discussion now turns to the development of the specific form 
 of the thirteen behavioral relationships. Following this discussion 
 and prior to the empirical estimation in the next section is a table 
 summarizing the structural model. This summary, Table 7 on pages 48-53, 
 includes the variables in all 27 equations, the exact form of all 
 identities, and the definition of all variables; the table should be a 
 useful reference to the reader. All equation numbers in this section 
 and the next are identical to the corresponding relationship in Table 7, 
 with the equations in this section preceded by "A" and the equations in 
 the estimation section preceded by "B". 
 
 Milk Production 
 
 Although considerable effort has been invested in the analysis of 
 aggregate milk supply response, little consensus has been reached on 
 either the factors which significantly affect milk production or the 
 magnitude of the price elasticity. Analyses of milk production have 
 typically used econometric analysis. Since the introduction of distri- 
 buted lag models in the late 1950' s,—^ the econometric analyses have 
 been of three types: (1) the simultaneous estimation of equations 
 for cow numbers and production per cow, (2) single equation estimation 
 of total production, and (3) recent attempts to estimate recursive 
 models of the milk production sector. Table 5 provides a summary of 
 the studies of the first two types. 
 
 Three studies employ two stage least squares to simultaneously 
 estimate cow numbers and production per cow. Zepp and McAlexander 
 [1969], using yearly changes for these two variables in a simplistic 
 model, obtained prediction results that proved to be better than a 
 
 — Prior to the introduction of distributed lag models, the analysis 
 of supply measured only short-run effects. Examples of such studies 
 include Cochrane [1958] and Halvorson [1955], 
 
 27 
 
TABLE 5 
 
 Summary of Selected Studies of U. S. Milk Production Response 
 
 Time Dependent 
 Author of Study Series Variables 
 
 Predetermined Variables 
 
 Elasticity 
 
 SR 
 
 LR 
 
 O 
 
 so 
 era 
 
 a 
 
 ri 
 
 r> 
 a> 
 
 c- 1 
 » 
 M 
 
 n> 
 o- 
 
 a. 
 
 ■3 
 
 3 
 
 n> 
 3 
 
 o 
 c 
 
 00 
 
 =r 
 
 00 
 
 n> 
 
 05 
 
 c 
 
 "3 
 
 i< 
 
 o 
 o 
 3 
 o 
 rt> 
 
 3 
 rt 
 
 0) 
 
 g 
 
 T3 
 
 o 
 
 O 
 3 
 
 r> 
 n> 
 3 
 rt 
 H 
 0) 
 
 o 
 
 03 
 
 It 
 
 X} 
 
 o 
 
 o 
 
 era 
 
 •3 
 H 
 
 H* 
 O 
 
 o 
 
 c 
 n 
 rt 
 H- 
 O 
 3 
 
 T) 
 fD 
 
 O 
 
 o 
 
 3 
 
 I 
 
 CD 
 
 n 
 
 8 
 
 cn 
 cr 
 
 a. 
 
 n 
 
 t- 1 
 CO 
 
 cr 
 o 
 i-( 
 
 o 
 o 
 
 CO 
 rt 
 
 Halvorson [1953] 1927-57 Milk Prod. 
 
 ,157 
 
 .403 
 
 Cromarty [1959] 1929-53 Milk Prod. 
 
 ,212 
 
 Wipf & Houck 
 [1967] 
 
 1945-64 Milk Prod. 
 
 ,027 to .041 to 
 .140 .192 
 
 Prato [1973] 
 
 1950-68 
 
 Cow Numbers 
 Prod. Per Cow 
 
 I 
 I 
 
 I 
 
 S 
 
 I 
 I 
 
 Hammond [1974] 
 
 1947-72 Milk Prod. 
 
 .039 
 
 .145 
 
 Wilson & 1947-63 
 Thompson [1967] 
 
 Cow Numbers 
 Prod. Per Cow 
 
 I 
 I 
 
 .003 
 
 ,521 
 
 I - Included but not significant at 5 percent level of significance. 
 S - Included and significant at 5 percent level of significance. 
 
recursive programming model. Wilson and Thompson [1967] and Prato 
 [1973] estimate these two equations as part of simultaneous equation 
 models of the dairy industry. The resulting inclusion of current 
 milk prices in the structural equation indicated that the use of lagged 
 prices may be more appropriate as this year's price never proved to 
 be statistically significant. 
 
 Halvorson [1958], Wipf and Houck [1967], and Hammond [1974] have 
 used the partial adjustment hypothesis on annual U. S. data to estimate 
 total milk production (see Table 5) . Wipf and Houck and Hammond found 
 the coefficient of adjustment to be about 0.6 while Halvorson's investi- 
 gation found it to be about 0.4. All three specifications included 
 milk price lagged one year and found it to be highly significant. Each 
 study found milk supply to be inelastic in the short and long run with 
 Halvorson obtaining a somewhat more inelastic response. Hammond was 
 unable to obtain significance on any cost of production variables while 
 the other two studies had some success, particularly Wipf and Houck 
 with significant coefficients on grain prices and roughage available. 
 Hammond found several measures of opportunity cost — beef price, land 
 value, the unemployment rate, and hog price — to have significant 
 coefficients while Wipf and Houck found the beef price to be very 
 
 important. As is common with time series analyses of this type, all 
 
 2 
 
 three studies recorded impressive R values. Graphic ex post verifica- 
 tion of the Hammond model provided impressive results. 
 
 Two additional single-equation analyses are of particular interest 
 for this study; Hammond [1974] estimates supply response for the Pacific 
 region (California, Oregon, and Washington), and Chen, Courtney, and 
 Schmitz [1972] estimate the response for California market milk using 
 quarterly data. Both studies found price elasticities larger than in 
 most other studies. Hammond calculated a long-run elasticity of 1.04; 
 he also found that the adjustment in production resulting from a price 
 change took longer in the Pacific region than in other regions. 
 
 Chen, Courtney, and Schmitz estimated quarterly supply of market 
 milk in California using a geometric and a second order polynomial 
 lag. Explanatory variables include a milk price/purchased feed ratio, 
 
 29 
 
a technology variable, and a seasonal dummy variable. The authors 
 conclude that the polynomial lag model produced superior results; 
 however, the price variables were only significant when the technology 
 variable was excluded. With this exclusion a seven period lag was 
 chosen. Prices lagged two through five periods had the greatest 
 effect; a long-run elasticity of 2.53 was obtained. The coefficient 
 on P was not significant and had a small value.— ^ 
 
 The third type of econometric estimation of milk production involve 
 estimating recursive models of the milk producing sector based on 
 biological as well as economic considerations. These models are based 
 on simple accounting equations first outlined by Frick and Henry [1956]. 
 Elterich and Johnson [1970] employ this approach to develop a recursive 
 model of the Connecticut dairy industry using annual data from 1939-1966 
 Hallberg [1973a] proposes a somewhat expanded model with structural 
 equations for cows on hand at the beginning of the year, deaths during 
 the year, the culling rate, calves produced this year, heifer calves 
 produced during this year, herd replacements during (t+2), heifer calf 
 culling rate, veal calves marketed during this year, and milk output per 
 cow. His proposal is to estimate this model for each of several regions 
 To illustrate the approach he estimates a model with fewer equations 
 (due to data limitations) for the entire U. S. 
 
 Jackson [1973] estimated a recursive model for the Pacific region 
 (California, Oregon, and Washington) . A polynomial lag model was used 
 to estimate structural equations for number of cows, yield per cow, 
 concentrate fed per cow, number of heifers, and cull cow numbers. The 
 estimated elasticities indicate an inelastic cow number response (0.57 
 in the short run [sum of years t and t-1] and 0.71 in the long run) and 
 an inelastic yield response (0.63); however, the total supply elasticity 
 is then slightly elastic (1.21 in the short run and 1.34 in the long run! 
 The response in the Pacific region was more elastic than that estimated 
 for the major milk producing areas (Lake States and the Northeast) but 
 less elastic than many other regions particularly in the long run. 
 
 — No reason was given for considering P as an independent variable 
 in the single-equation framework. fc 
 
 30 
 
Although recursive models have great potential, several significant 
 limitations appear: 
 
 1. The accuracy of some of the data is questionable. Elterich and 
 Johnson [1970, p. 12] comment: 'The authors are apprehensive 
 about the quality of data concerning capital stock and labor 
 used on dairy farms." 
 
 2. There is no method of specifying separate equations for Grade A 
 (market) and Grade B (manufacturing) producers. 
 
 3. In some areas, particularly large-scale dairy areas like 
 California, there are sales of dairy animals between states 
 which are not recorded. 
 
 Due to these limitations, the construction of such a model for California 
 is not feasible in this study. 
 
 Based upon the above material, analysis of the industry, and the 
 data and time available, the conclusion was reached to estimate several 
 total production equations. Each equation should contain variables to 
 reflect (1) the profitability of milk production, (2) the opportunity 
 cost of the owners' labor and capital, (3) the gradual improvement in 
 technology, management, and genetic ability and (4) the seasonality of 
 milk production. 
 
 Significant differences exist between dairies producing market milk 
 and those producing manufacturing milk, and among milk dairies in 
 different regions of California. Mindful of the likelihood that these 
 differences affect the supply response, six production response equations 
 are specified: one for manufacturing milk and five for market milk with 
 one for each of the regions outlined in Figure 2, page 8. Since the 
 availability of data dictated that different variables be specified for 
 market and manufacturing milk producers, they are discussed separately, 
 with the five market milk response equations discussed first. 
 
 Market Milk 
 
 Profitability of production is determined by the price received, the 
 cost of production, and the production per cow. The typical specification 
 
 31 
 
of profitability in the studies mentioned in the previous section was to 
 include the milk price and the cost of one or more inputs. For this 
 study, an alternative procedure was chosen; the procedure is to calculate 
 the short-run margin per cow or the price minus the variable costs per 
 hundredweight times production per cow. 
 
 This procedure was employed for two reasons. First, this value 
 represents the return to the dairyman; any substitution of inputs due 
 to input price changes has already occurred. For most of the previous 
 studies, this procedure was not a viable alternative because the cost 
 of production data were not available. The second reason is that the 
 separate specification of prices received and costs of production gave 
 inferior results including the frequent occurrence of incorrect signs. 
 Although this result is surprising from a theoretical viewpoint and 
 somewhat inconsistent with results reported in the literature (although 
 Hammond [1974] discarded all feed cost variables), the problem may 
 relate to State milk control procedures since these same cost of produc- 
 tion figures are employed as a basis for determining class 1 prices. 
 Consequently, a causation problem is created, and the ambiguous results 
 may be the consequence. 
 
 Very little guidance is available for selecting a lag structure on 
 margin per cow since the available literature deals predominantly with 
 annual data and the timing of producer responses is ambiguous. Chen, 
 Courtney and Schmitz [1972] specify a second degree polynomial lag 
 function using quarterly observations; however, their results contain 
 few variables and the lag is rather short (two years). Analysis of 
 actions of dairymen indicates that they often adopt a short-run and a 
 long-run response to alterations in the margin they are receiving. One 
 of two short-run courses of action is commonly taken. The first is to 
 increase (decrease) production by increased (decreased) feeding and 
 reduced (increased) culling when returns increase (decrease) . On the 
 other hand, producers, having large fixed costs, may determine that 
 they must generate an approximately constant income stream. Their short- 
 run reaction to a reduced margin, consequently, is often to generate 
 additional production by decreased culling or even adding cows to 
 maintain the income stream. Not only are the results of the alternative 
 
 32 
 
courses of action conflicting, the major impact of the actions may not 
 be felt for many months. 
 
 Although the direction of the long-run capacity decision is 
 unambiguous, the length of time before the impact of the decision is 
 reflected in total production varies dramatically among producers and 
 regions. Once a decision is made to increase capacity, plans must be 
 formulated for the expansion. Producers can spend many months choosing 
 among the numerous milking, feeding, and housing systems. Only after 
 additional delays for construction can expansion of the herd begin. 
 Once again alternatives are available including purchasing mature cows, 
 purchasing heifers, and raising replacements. 
 
 To specify the length of time required for decisions based on 
 margins to be reflected in total production, bimonthly observations 
 lagged up to three years were initially considered. Since these eigh- 
 teen observations cannot be specified as eighteen variables, three 
 combinations of the eighteen were investigated: (1) a second degree 
 polynomial;-^ (2) three averages (simple average of t-1 through t-6 
 denoted as m , simple average of t-7 through t-12 denoted as m L _ 1> and 
 simple average of t-13 through t-18 denoted as m L _ 2 ) '> and ( 3 ) f our 
 bimonthly observations (t-1, t-6, t-12, and t-18). Although all 
 three forms provided reasonable results, the six-period averages 
 are selected because the results are more rational. The results from 
 the polynomial lag apparently produced inferior results because the 
 polynomial function does not approximate the form of the lagged 
 responses of producers. The use of four bimonthly observations 
 completely disregards the information contained in the remaining 
 fourteen observations; consequently, inferior results are obtained. 
 To test whether all production adjustments have been completed within 
 three years, an additional average margin for periods t-19 through 
 t-24 (year 4) was introduced in the ensuing analysis ( m L _ 3 ) • In 
 regions where many producers raise their own replacements, production 
 adjustments may not be completed within three years due to the length 
 of the lags described above. 
 
 -^See Chen, Courtney, and Schmitz [1972] for details of the form 
 of the polynomial lag employed. 
 
 33 
 
The possibility of including several margin variables without 
 introducing overly restrictive multicolinearity is created by two factors 
 not usually present when analyzing supply response for milk. The first 
 is the large number of observations available with bimonthly observations. 
 The second is the relatively small correlation between margin variables 
 (n^f "Y.i* I \_2' "^-3^ be cause the margin is a combination of three 
 variables — price, costs, and production. The correlations among the 
 variables for the different periods of lag generally range from 0.6 to 
 0.8; for price variables alone the correlations are 0.95 and higher. 
 
 Although the use of several average margin variables is not a 
 sophisticated distributed lag scheme, its use more nearly represented 
 the lag structure of the dairyman than did the geometric or the polynomial 
 distributed lag. Other distributed lag schemes could have been tested; 
 however, since operational computer programs were unavailable, it was 
 decided that the additional time required would be better spent on other 
 aspects of the study. 
 
 Three variables were chosen to represent the opportunity cost of 
 the owners' labor and capital: (1) the beef price, (2) the index of 
 land prices in California, and (3) the interest rate lagged two years. 
 The beef price is included to reflect both the price at which marginal 
 cows can be culled and the cost of replacements since the beef price and 
 the price of replacements are highly correlated. 
 
 Because California agriculture is so diversified, the inclusion of 
 profitability variables for alternative enterprises was impractical. 
 Instead, the index of California land prices was specified since land 
 prices reflect the profitability of the best possible use of the land.-^ 
 Normally, land prices increase rapidly (slowly) when the price of 
 specialty crops are high (low) . When these prices are high, feed input 
 prices are high and roughage in particular may be difficult to obtain. 
 The effect on the cost of production is reflected in the margin variables, 
 but the increased uncertainty associated with obtaining an adequate 
 supply of roughage is not. The land price does, however, reflect this 
 change in the availability of roughage. 
 
 - Although many large dairies include little land, the purchase of 
 land is an alternative use of capital. 
 
 34 
 
To reflect the availability of capital and the return from invest- 
 ing capital in items other than dairy facilities, the interest rate is 
 specified as the third opportunity cost variable. Because the effect 
 of additional investment in dairy facilities is not totally reflected 
 in production for some time, the variable is lagged two years. 
 
 Any attempt to specify behavioral relationships using time series 
 data faces the problem of incorporating changes resulting from improve- 
 ments in technology, management, and genetic ability. The selection 
 of variables to reflect these changes is nearly impossible. In this 
 study, as in most studies, proxy variables are specified to approximate 
 these changes. The percentage of cows in California on DHI test is 
 used as a proxy for management while a time trend is specified as a 
 proxy for gradual change in technology and genetic ability. 
 
 The final set of variables is necessitated by the bimonthly time 
 period and the seasonality of milk production. Due to genetic factors, 
 climatic conditions, and traditional practices, more milk is produced 
 in the spring and summer than in the fall and winter, ceteris paribus . 
 In order to estimate the importance of seasonality the January- February 
 period is selected as a base period, and five dummy variables are 
 specified. The dummy variables then measure the difference between 
 production in January-February and each of the other five bimonthly 
 periods due to seasonality. 
 
 The five market milk equations are specified as follows. The 
 sources of all variables are delineated in Appendix A: 
 
 (A.1-A.5) q 
 
 j 
 
 = 1, 2, 
 
 5 
 
 where 
 
 t = The bimonthly observation t. 
 
 T = The observation is the simple average of bimonthly 
 observations t through t-5. 
 
 35 
 
T-2 = The observation is the simple average of bimonthly 
 observati ons t — 12 through t — 17 (two years ago) . 
 
 L = The observation is the simple average of bimonthly 
 observations t-1 through t-6. 
 
 L-i, i = 1, 2, 3 = The average value of the variable lagged 
 
 2, 3, and 4 years. Calculated by averaging bimonthly 
 observations t-1 -(6xi) through t-6 -(6xi) . 
 
 A1 
 
 q = Production (hundredweight per day) of market milk in 
 
 region j, 
 
 j = 1 
 2 
 3 
 4 
 5 
 
 Southern California, 
 
 South San Joaquin Valley, 
 
 North San Joaquin and Sacramento Valleys 
 
 Central Coast, and 
 
 Mountain areas and North Coast. 
 
 Ai 
 
 m J = Margin per cow (price minus variable costs times hundred- 
 weight production in the bimonthly period) for market milk 
 producers in region j (See Table 7, Equations 6-10 for 
 calculation) . 
 
 BF 
 
 P = Price per hundredweight received for beef in California. 
 
 p L = Index of land prices in California. 
 INT 
 
 p = Interest rate in percent, 
 dhi = Percent of all dairy cattle in California on DHI test. 
 TM = Time trend: January-February 1961 =1, ... 
 S* = Dummy variables to measure seasonal effects, 
 
 i = 1 
 2 
 3 
 4 
 5 
 
 March -April 
 May- June 
 July- August 
 September-October 
 November-December 
 
 Vj ■ Disturbance term for region j. 
 
 These five equations give the mathematical form of the first five 
 relationships of the model as outlined in Table 7, on pages 48-53. The 
 next six equations (relationships 6-11, Table 7) in the structural model 
 are identities required to link the producer subsector with the processor 
 and consumer subsectors. An equation is required for each region to 
 calculate the margin (m using the average price received for market 
 
 36 
 
milk (p t ) determined in the processor subsector and exogenous variables. 
 The sixth identity simply calculates total market milk production by 
 summing the regional productions. 
 
 Manufacturing Milk 
 
 Since less than ten percent of California milk production occurs 
 on manufacturing milk dairies and since manufacturing milk dairies are 
 more homogeneous than market milk dairies, one equation for California 
 manufacturing milk production is specified. Unfortunately, the margin 
 per cow variables cannot be used in this equation as cost of produc- 
 tion data are no longer collected for manufacturing milk dairies. The 
 alternative specification for profitability is to use lagged milk price 
 received and the price of corn. Corn is the major purchased feed input 
 on these dairies. The same variables are used for the other factors 
 affecting milk production. 
 
 The following equation is specified for manufacturing milk: 
 
 (A. 12) q* = b 6Q + b 6 ^ + b^p^ + b 63 p*_ 2 + b^ 0 ™ + b 65 P^ + 
 
 1 b 6,5 + i S t + V 6t 
 i=l 
 
 where P = Price received by manufacturing milk producers. 
 
 pCORN = Price per hundredweight for corn. 
 All other variables are defined in equations A.l - A. 5. 
 
 Percent Milkfat and Solids-not-Fat 
 
 In order to determine the quantities of milkfat and solids-not-fat 
 available to the processor subsector, total production and percent 
 milkfat and solids-not-fat are required. The percentage fat varies 
 seasonally and has been declining over time due to greater efforts to 
 genetically increase milk production potential. Using a time trend as 
 
 37 
 
a proxy variable captures this decline very well. The following equation 
 is specified to measure these factors: 
 
 (A.i3) pcf -b 70 + b« + t b s^ + v 7t 
 
 1=1 
 
 PCF t is the percent fat and the other variables have been previously 
 defined.. Since only very recent data are available on percent solids 
 and since percent fat and solids are very closely correlated, the 
 percent solids is related to percent milkfat by an identity. This 
 identity is included as the fourteenth equation in the model; see Table 
 7, pages 48-53. 
 
 Processor Prices and Allocation to Final Products 
 
 Numerous price and allocation functions are carried out in the 
 processor subsector. These functions are divided into the following 
 three types of decisions: (1) the prices processors pay market and 
 manufacturing milk producers (Table 7, relationships 15-17), (2) the 
 allocation of milkfat and solids-not-fat to fluid and manufacturing uses 
 (relationships 18 and 19) , and (3) the prices charged consumers for 
 dairy products (relationships 20-23) .— Because of the high degree of 
 governmental control exerted in the California dairy industry, many 
 of the market functions performed in this subsector are represented by 
 a control variable or by an identity. 
 
 Because the focus of the study is at the farm level and because 
 accurate data for individual manufactured dairy products are difficult 
 to obtain, the consumer and processor subsectors are specified for fat 
 and solids-not-fat used in fluid and manufactured products rather than 
 by individual dairy products. This specification is consistent with 
 recent models by Wilson and Thompson [1967] and Prato [1973]. 
 
 — As was noted in the section outlining the structure model, several 
 of these relationships are determined simultaneously with consumer 
 demand . 
 
 38 
 
Prices Paid Producers 
 
 The average price paid to market milk, producers is determined by 
 an identity. This equation (Table 7, equation 15) weights the price 
 paid for milkfat and solids-not-fat in fluid and manufactured products 
 by the quantities of fat and solids used for each purpose.—^ 
 
 The price paid manufacturing producers is not a control variable; 
 however, the price is closely related to the price paid market milk 
 producers for milk used in manufactured dairy products and to the 
 Federal support price for manufacturing milk. These relationships are 
 expressed as follows: 
 
 (A.17) P» = b + b SP + b 82 PMP t + b 83 TM + I b 8 sj + v 
 
 i=l 
 
 where SP = Federal support price for manufacturing milk. 
 
 PMP = Hundredweight equivalent of average price paid by manu- 
 facturing dairy product processors for market milk fat 
 (PFP) and market milk solids (PSP)-' 
 
 Again, the other variables have been defined previously and all data 
 sources are referenced in Appendix A. 
 
 Allocation to Final Usage 
 
 Since fluid usage returns the most income to the industry and 
 represents the most perishable products, all demands for fluid products 
 are filled first, with the residual available for manufactured dairy 
 products. Although this scenario might be somewhat simplistic, it is 
 an adequate representation of reality. Given production (from the 
 producer subsector of the model) and consumption of fluid products 
 (from the consumer subsector), the allocation equations in the model 
 
 -^The complications introduced by quota and base (see discussion 
 in the first section) can be overlooked since an average price is being 
 calculated. 
 
 2/ 
 
 -Assumes milk is 3.5 percent fat and 8.7 percent solids. Manu- 
 facturing milk is not component priced. 
 
 39 
 
are simply accounting identities. Relationships 18 and 19 in the struc- 
 tural model (see Table 7, pages 48-53) are identities to calculate the 
 amount of fat and solids produced in California that are available for 
 processing into manufactured dairy products. The identity for milkfat 
 (18) simply subtracts the fat used in fluid products (which is determined 
 in the consumer subsector) from the total fat produced in California. 
 The solids identity (19) is somewhat more complicated since the actual 
 amount of solids used in fluid products is unavailable. The quantity 
 is estimated by increasing the average solids content of all milk by ten 
 percent. The increase is required to include solids used to fortify 
 fluid milk. 
 
 Retail Prices 
 
 Three retail prices are required by the model: the retail price 
 for a half gallon of fluid milk, the retail value of milkfat sold in 
 manufactured dairy products, and the retail value of solids-not-fat 
 sold in manufactured dairy products. During the time period of the 
 observations for this study, the retail fluid milk price was established 
 by the Bureau of Milk Stabilization.—^ The calculation of the data 
 series for retail value of fats and solids is based on retail price of 
 manufactured dairy products and the composition of the products; the 
 details are in Appendix A. 
 
 Behavioral equations are specified for the retail value of fats and 
 solids that reflect the interactions between processors and consumers. 
 These marketing margin equations include the price paid for fats and 
 solids and variables that influence the magnitude of the marketing margin. 
 Since fats and solids for products come from both market and manufacturing 
 milk, the average price paid for fats and solids produced in California 
 and used for processing in manufactured dairy products must be calculated. 
 These identities (Table 7, relationships 20 and 21) weight the prices 
 paid market and manufacturing milk producers by the quantities used. 
 
 — Although the Bureau actually establishes minimum prices, the price 
 they set has almost always been the effective price. 
 
 40 
 
Several factors are hypothesized to affect the retail value of fat 
 (RFP™) in addition to the price paid for fat (APF) . The price paid for 
 solids (APS) is introduced to reflect the complementarity between fats 
 and solids. The hourly wage rate for manufacturing dairy products in 
 California (XMCH) is included to represent the cost of production since 
 labor is the largest processing cost. In recent times an increasing 
 proportion of the fat has been allocated to cheese production. Since 
 cheese production involves a larger marketing margin than most dairy 
 products, the proportion of fat used in manufactured dairy products 
 that is used in cheese (CHESF) is hypothesized to affect the retail 
 fat value. To reflect the imnact of CCC purchases on retail prices, 
 the support price for butter (SB) is included. A time trend is included 
 as a proxy for the ceteris paribus decline in margin due to technologi- 
 cal innovations and economies of size. 
 
 The resulting specification of the behavioral equation for retail 
 value of milkfat used in manufactured dairy products is: 
 
 (A.22) RFP™ = b 9Q + b 91 APF t + b^APS,. + b^SI^ + b^XMC^ + b^ CHESF ^ + 
 b 96™ + X b 9,6 + i S l + V 9t 
 
 A somewhat analogous equation is specified for the retail value of 
 solids sold in manufactured dairy products (RSP 1 ") . The wage rate, the 
 proportion of solids used in cheese (CHESS), and time trend are specified 
 for similar reasons. No variable is included to reflect CCC purchases 
 because surplus supplies of solids have been less frequent. 
 
 The resulting specification of the behavioral equation for retail 
 value of solids-not-fat used in manufactured dairy products is: 
 
 (A.23) RSP™ - b 1(Jf0 + b 10fl APS t + b 1Q>2 XMCH t + b^CHE^ + b^TM + 
 
 X b 10,4+i S t + V 10t 
 i=l 
 
 41 
 
These two relationships complete the specification of the processor 
 subsector of the structural model (see Table 7, relationships 15-23). 
 
 Demand for Dairy Products 
 
 Demand equations for three types of dairy products are specified: 
 per capita consumption of fluid milkfat, per capita consumption of fluid 
 skim milk, and per capita consumption of milkfat and solids-not-fat in 
 manufactured dairy products. The theory of the consumer behavior of 
 individuals is well developed and documented elsewhere (George and King 
 [1971], Henderson and Quandt [1971]). This theory is used to justify 
 inclusion in demand equations of price of the product (referred to as 
 own price), the price of substitutes, and income.-^ Other variables 
 representing demographic and other characteristics that change over time 
 must be specified for aggregate, time-series analysis. 
 
 Table 6 summarizes own price and income elasticities from several 
 of the more comprehensive studies of the demand for dairy products. 
 Most studies have concluded that the demand for dairy products, like 
 that for most food items, is both price and income inelastic. Most of 
 the research in this area has been with fluid products; the resulting 
 price elasticities have generally been in the range of -0.2 to -0.6, 
 with income elasticities in the range of 0.0 to 0.5. The recent work 
 by Boehm and Babb [1975] using data from the Market Research Corporation 
 of America National Consumer Panel found the demand for fluid products 
 to be very income inelastic but price elastic. Using cross section data 
 they obtained price elasticities that ranged from -0.833 for one percent 
 milk to -1.701 for regular whole milk. Using the same data they 
 estimated a time series model in which the price elasticities ranged 
 from -0.12 to -1.18 with total fluid milk -0.14. They argue that the 
 inelastic results from the time series model give the short-run response, 
 and the elastic response from the cross section is the long-run result. 
 
 — ^The basic assumption is that consumers maximize utility subject to 
 their budget constraint. The resulting Lagrangian function is then 
 solved to get: gj = gj (p r ... , p^ Y) , j=l, ... , n 
 
 where n is the number of commodities. The concept of want independence 
 (see Frisch [1959]) is used to eliminate equations for non-dairy products 
 and price variables with small cross-elasticities. 
 
 42 
 
TABLE 6 
 
 Price and Income Elasticities for Dairy Products 
 
 Elasticity—' 
 
 Author 
 
 Price 
 
 
 Income 
 
 Type of Study 
 
 
 
 A. 
 
 Fluid Milk 
 
 RranHno r 19611 
 
 -0. 285 + 
 
 
 0.16 + 
 
 All food elasticities 
 
 George & King [1971] 
 
 -0.346 + 
 
 
 0.204 + 
 
 All food elasticities 
 
 Prato [1971] 
 
 -5.765* 
 
 
 
 334 Florida households 
 
 Boehm & Babb [1975] 
 
 -1.628* 
 
 
 0.052 
 
 Market Research Corpo- 
 ration of America Data 
 - cross section 
 
 
 
 B. 
 
 Frozen Dairy Products 
 
 Brandow [1961] 
 
 -0.55 + 
 
 
 0.35 + 
 
 All food elasticities 
 
 George & King [1971] 
 
 -0.528 + 
 
 
 0.331 + 
 
 All food elasticities 
 
 Boehm & Babb [1975b] 
 
 -0.471* 
 
 
 0.07 
 
 MRCA - cross section 
 
 
 
 C. 
 
 Cottage 
 
 Cheese 
 
 Boehm & Babb [1975b] 
 
 -1.29* 
 
 D. 
 
 0.168* 
 Cheese 
 
 MRCA - cross section 
 
 Brandow [1961] 
 
 -0.7 + 
 
 
 0.45 
 
 All food elasticities 
 
 George & King [1971] 
 
 -0.46 
 
 
 -0.25 
 
 All food elasticities 
 
 Boehm & Babb [1975a] 
 
 -0.851* 
 
 E. 
 
 0.234* 
 Butter 
 
 MRCA - cross section 
 
 Brandow [1961] 
 
 -0.85 + 
 
 
 0.33 + 
 
 All food elasticities 
 
 George & King [1971] 
 
 -0.65 + 
 
 
 0.32 + 
 
 All food elasticities 
 
 Boehm & Babb [1975a] 
 
 -0.76* 
 
 
 0.17 
 
 MRCA - cross section 
 
 
 
 F. 
 
 Nonfat Dry Milk 
 
 Boehm & Babb [1975b] 
 
 -2.24 
 
 
 -0.03 
 
 MRCA - cross section 
 
 -An asterisk (*) indicates that the elasticities were found to be 
 significant at the 5 percent level of significance; a (+) indicates 
 no test of significance was possible or was performed. 
 
 43 
 
Most authors have concluded that the demand for most manufactured 
 dairy products is more price and income elastic than the demand for 
 fluid milk. The results reported by Coehm and Babb support the conclu- 
 sion that the products are more income elastic, but their results did 
 not support the conclusion that fluid products are more price inelastic.- 1 - 7 
 They obtained an inelastic price response for most perishable dairy 
 products including all types of frozen dairy products, dairy dips, and 
 yogurt. The demand for cottage cheese, half & half cream, and sour 
 cream, although price elastic, was less elastic than the demand for 
 fluid products. 
 
 As might be expected, there was considerable variation in price 
 elasticity of the storable dairy products; nonfat dry milk powder 
 exhibited an elastic response (-2.24), butter was inelastic, and the 
 cheese products investigated fluctuated around an elasticity of -1.0. 
 Boehm and Babb found the meat price index to have a significant effect 
 on cheese consumption. Similarly, butter and margarine produced a 
 significant positive cross-elasticity. 
 
 Demand for Fluid Milkfat and Fluid Ski m 
 
 Although it is expected that these two equations will contain the 
 same or similar variables, it is hypothesized that the coefficients 
 derived in the two separate equations will be useful in projecting 
 future changes in the composition of fluid purchases. The per capita 
 consumption of fluid milkfat has been declining more rapidly than per 
 capita consumption of fluid skim. The projection of a continuation or 
 alteration in this trend can be used to more accurately calculate the 
 fat and solids remaining for processing into products. 
 
 The variable specification is identical for the two equations. 
 Tito price variables are included— the retail price of fluid milk (RFLP) 
 and the retail value of solids sold in manufactured dairy products (RSP m ) M 
 
 --^These conclusions are reached from the results in Table 6 and from 
 further analysis of the three publications authored by Boehm and Babb 
 [1975, 1975a, 1975b]. 
 
 2/ 
 
 ~ The data sources and transformations for all variables are described 
 in Appendix A. 
 
 44 
 
The latter is included to reflect the substitutability among dairy 
 products particularly fluid milk and evaporated milk products. To 
 reflect the large milk consumption by children, an age distribution 
 variable, the proportion of the California population attending kinder- 
 garten through the eighth grade (AD), is included. A time trend is 
 specified as a proxy for the continuing change in consumer tastes from 
 milk to other beverages. The per capita consumption of imitation 
 dairy products in California (XTMIT) is specified to reflect (1) the 
 substitutability between fluid and imitation milk and (2) the reluctance 
 of consumers to purchase milk during periods of increased cholesterol 
 concern. Income was not specified in the equation due to low signifi- 
 cance and severe multicolinearity with milk price, value of solids, and 
 the time trend. 
 
 The resulting specification of the behavioral equations for fluid 
 milkfat and fluid skim demand is: 
 
 (A. 24) RFQF = b, , _ + b,, RFLP + b . 0 RSP m + b AD + b , XIMIT + 
 t 11,0 11,1 t 11,2 t 11,3 t 11,4 t 
 
 5 
 
 b in TM + I b,, .^.S 1 + v„ 
 11,5 ll,5+i t lit 
 
 where RFQF = Per capita consumption of milkfat in fluid (Class 1) 
 t products. 
 
 (A.25) RSQF t = b 12j() + b 12)1 RFLP t + b^RSP* + b^^ + b^XIMI^ + 
 
 b 12,5™ + j x b 12,5 + i S t i + V 12t 
 
 where RSQF^ = Per capita consumption of fluid skim milk. 
 
 An identity (Table 7, relationship 26) is then included to calcu- 
 late per capita consumption of fluid milk (RFLQ^) by summing RFQF^ 
 and RSQF . 
 
 45 
 
Demand for Milkfat and Solids-not-Fat in Products 
 
 The preferred specification of separate equations for milkfat and 
 solids-not-fat sold in manufactured dairy products proved to be impossible 
 because of the prevailing pricing policy of the Bureau of Milk Stabiliza- 
 tion to increase the value of solids relative to fat. Although this 
 policy has a sound economic basis, the procedure of making large adjust- 
 ments of the controlled prices every year or two with no relative change 
 in between did not adequately match the gradual but continuous economic 
 adjustment in uncontrolled prices. 
 
 The specified equation contains mostly economic variables; the 
 demand for each manufactured dairy product is affected by a different 
 set of demographic variables, but few demographic variables exert a large 
 impact on demand for all manufactured dairy products.— The economic 
 variables included are the two own price variables (retail value of fat 
 (RFP m ) and solids (RSP™) in products) , the retail price of fluid milk 
 (RFLP) , and per capita personal income (Y) . The fluid milk price reflects 
 the above-mentioned substitutability between fluid and evaporated milk. 
 In addition the dummy variables for seasonality and a time trend as a 
 proxy for taste changes are included. 
 
 The resulting behavioral equation for demand for fats and solids 
 sold in manufactured dairy products is: 
 
 (A.27) RMDQ t - b^ + b^RFP* + b^RSP™ + b^RFI^ + + 
 b 13,5™ + ^13,5+1^ + V 13t 
 
 — The specification of an equation for each of the manufactured 
 dairy products would be better for this section of the model; however, 
 since the emphasis in this study is on the California dairy industry and 
 fluid products, the use of one equation was deemed to be satisfactory. 
 The multiple equation specification would be difficult but useful and 
 should reflect a national demand since a national market exists for products 
 Rojko [1969] discusses such a specification. 
 
 46 
 
Summary of the Structural Model 
 
 As indicated in the previous sections, Table 7 (pages 48-53) 
 contains the 27 relationships and all variable definitions for the 
 structural model of the California dairy industry. Twenty-seven 
 endogenous variables (variables whose value is determined within the 
 system) and 42 exogenous variables (variables whose values are determined 
 outside of the system) are included in these relationships; six of the 
 42 exogenous variables are control variables whose values are established 
 by the Federal "Dairy Price Support Program" or by the California 
 Bureau of Milk Stabilization. 
 
 Equations 1-5, 12, 13, 17, 22-25, and 27 are behavioral equations 
 to be estimated. Equations 1-12 of Table 7 determine the supply of 
 milk available. These equations are considered independent of demand 
 because current price received is not included as an explanatory 
 variable. 
 
 In the processor and consumer subsectors relationships 18, 19, 20, 2 
 23, 24, 25, and 26 form a simultaneous subsystem for the consumption of 
 fluid milk products, the retail value of solids in products, and the 
 quantities available and average price paid for fat and solids produced 
 in California and used in manufactured dairy products. The simultaneity 
 of this system results from the substitutability of solids in dairy 
 products and fluid milk. 
 
 Equations 17, 22, and 27 are a part of the processor and consumer 
 subsectors but are not included in the simultaneous subsystem. The 
 next section contains the empirical estimates of the behavioral equa- 
 tions developed in this section. 
 
 EMPIRICAL ESTIMATES OF BEHAVIORAL RELATIONSHIPS 
 
 Estimates of the parameters of the behavioral equations described 
 in the previous section are derived from bimonthly (six per year) obser- 
 vations for the period 1958 through 1973. As indicated earlier, the 
 bimonthly time period is chosen to be consistent with the time frame 
 
 47 
 
TABLE 7 
 
 A Reader's Guide to the Structural Model of the California Dairy Industry 
 
 Relationship for^and Variables Included-^ 
 (exogenous variables in parentheses) 
 
 c/ 
 
 Producer Subsecto r— 
 
 1-5. Daily market milk production in region i: q A i m Aj m A i m A 3 m A i 
 
 J q fc , m L , m L _ 1 , ra L _ 2 , m^, 
 
 CP™), (Pf), (Pj). (dhi T ), (bo, (sj), (s*), ( s t 3 ), (sj). (s 5 t ) t 
 
 V 
 
 6-10. where: nA 1 = [p A - ( L J) - (vcj j )] x (PPcj) 
 
 11. Market milk production: q A = q A1 + q A2 + q A3 + q M + a A5 
 
 t t ^t l t M t 4 t 
 
 12. Daily manufacturing milk production: q B , p B , p B _ , p B , (p C0RN ) , 
 
 t L L X L 2 X 
 
 (p£>. (sj), (S*), (S 3 ), (sj), (s*) f (v fit ) 
 
 13. Percent milkf at: PCF^, (TM) , (S^) , (S*) , (S 3 ) , (sj) , (S^) , ( v ) 
 
 14. Percent solids: PCS = 7.07 + .444 x PCF 
 
 t t 
 
 15. Average price per cwt. of market milk paid by processors: pp A = 
 
 t 
 
 {RFQF x (C1FP ) + .01 x RSQF x (C1SP ) + [ (PFQ™ - . 01 x PCF x 
 
 t t t t 
 
 q B /(P0P t )] x (PFP t ) + [(PSQ° - .01 x PCS t x q B /(P0P t >] x 
 (PSP t )}/{[q A /(POP t )]/100} 
 
 16. Average price per cwt. of market milk received by producers: 
 
 48 
 
TABLE 7 (continued) 
 
 P rocessor Subsector— 
 Manufacturing milk price: p*. (SP fc ) , (PMP^) , (TM) , (S^) , (S fc ) , (S fc ) , 
 
 (S 4 t ), (S 5 t ), (v gt ) 
 Fat produced in California and available for products: PFQ™ = 
 [(PCF t /100) x (q^ + qj*)] - (RFQF^ x (POP^) 
 
 m 
 
 Solids produced in California and available for products: PSQ^ - 
 [(PCS t /100) x (q A + q®)] - [ (PCS t x .011) x (RFLQ^ x (POP^)] 
 
 Average price paid for fat produced in California for products: 
 
 APF = {(PFP ) x PCF x [q A - (RFQF x (POP ) ) ] + {[ (PFP ) x 
 
 t t t t t L L 
 
 B B 
 
 PCF /((PFP ) x PCF + (PSP ) x PCS )] /PCF }x p x q x 
 t t t t t ttt 
 
 (PCS t /100)}/PFQ™ 
 
 Average price paid for solids produced in California for products: 
 
 APS = {(PSP ) x [(q A - (RFLQ x 1.1 x (POP ))) x (PCS /100) ] + 
 t t t t t t 
 
 {[(PSP t ) x PCS t /((PFP t ) + PCF fc + (PSP t ) x PCS t )]/PCS t > x P t x 
 q® x (PCS t /100)}/PSQ™ 
 Retail value of fat in products: RFP™, APF fc , APS t , (SB t ) , (XMCH fc ) , 
 (CHESF t ), (TM), (S*), (S^), (sj*), (sj) , (S^) , (v^) 
 
 49 
 
TABLE 7 (continued) 
 
 23. Retail value of solids in products: RSP t , APS^ (XMCH^ , (CHESS^ , 
 (T), (sj), (S 2 t ), (S 3 t ), (S*), (S*), (v^) 
 
 Consumer Subsector 
 
 24. Per capita consumption of fluid milkfat: RFQF^ , (RFLP^) , RSP™, (AD ), 
 
 (XIMIT.), (TM),(sJ), (S*), (S*), (S*), (S*), ( V ) 
 
 25. Per capita consumption of fluid skim milk: RSQF . (RFLP ), RSP m 
 
 t' t t 
 
 (AD t ), (XIMIT t ), (TM),(S*) S (S*) , ( S *) , ( S *) , (S*) , (v^) 
 
 26. Per capita consumption of fluid milk: RFLQ^ = RFQF^ + RSQF 
 
 27. Per capita consumption of fat and solids in products: RMDQ fc , RFP™, 
 
 RSP™, (RFLP t ), (Y t ), CBO.(SJ), (gj), (S 3 t ), (sj), <S*) , (v^) 
 
 e/ 
 
 Variable Identification- 
 Control Variables :—^ 
 
 C1FP = Class 1 price for fat (pound) 
 
 C1SP = Class 1 price for skim milk (cwt.) 
 
 PFP = Average price paid by manufactured dairy product processors for 
 market milk fat 
 
 PSP = Average price paid by manufactured dairy product processors for 
 market milk solids 
 
 PMP = Hundredweight equivalent of PFP and PSP 
 
 RFLP = Retail price for fluid milkF 
 
 50 
 
TABLE 7 (continued) 
 
 Endogenous Variables : 
 Ai 
 
 q = Production (hundredweight per day) of market milk in region j, 
 
 j = 1 
 2 
 
 3 
 4 
 5 
 
 Southern California 
 
 South San Joaquin Valley 
 
 North San Joaquin and Sacramento Valleys 
 
 Central Coast 
 
 Mountain Areas and North Coast 
 
 q = Total production of market milk 
 B 
 
 q = Total production of manufacturing milk 
 PCF = Percent fat in milk produced in California 
 PCS = Percent solids in milk produced in California 
 
 P = Manufacturing milk price 
 
 RFP m = Retail value of fat in manufactured dairy products (referred to 
 as "products") 
 
 RSP m = Retail value of solids in manufactured dairy products 
 
 PFQ m = Quantity of fat produced in California and used in products 
 
 PSQ m = Quantity of solids produced in California and used in products 
 
 APF = Average price paid for fat produced in California and used in 
 products 
 
 APS = Average price paid for solids produced in California and used 
 in products 
 
 pp = Average price per hundredweight of market milk paid by processors 
 
 p = Average price per hundredweight of market milk received by 
 producers 
 
 Ai 
 
 m = Margin per cow for market milk producers in region j 
 RFQF = Per capita consumption of milkfat in fluid (Class 1) products 
 RSQF = Per capita consumption of fluid skim milk 
 RFLQ = Per capita consumption of fluid milk 
 
 RMDQ = Per capita consumption of fat and solids in manufactured dairy 
 products 
 
 Exogenous Variables : 
 
 p L = Index of land prices in California 
 BF 
 
 p = Price per hundredweight received for beef in California 
 TM = Time trend: January-February 1961 =1, ... 
 
 51 
 
 ■ 
 
TABLE 7 (continued) 
 
 Exogenous Variables : continued 
 
 S 1 = Dummy variables to measure seasonal effects, 
 
 INT 
 
 P 
 
 dhi 
 CORN 
 
 p 
 
 SP 
 SB 
 XMCH 
 CHESF 
 CHESS 
 POP 
 H 
 
 Aj 
 
 i = 1 
 2 
 3 
 A 
 5 
 
 March - April 
 May - June 
 July - August 
 September - October 
 November - December 
 
 Interest rate in percent 
 
 Percent of all cattle in California on DHI test 
 Price received for corn in California 
 Federal support price for manufacturing milk 
 Support price for butter 
 
 Hourly wage rate for manufacturing dairy products in California 
 Proportion of fat consumed as cheese 
 Proportion of solids consumed as cheese 
 Population of California 
 
 Differential between price processor pays and producer receives 
 
 Differential between average market milk price and market milk 
 price in region j 
 
 vc J = Variable costs per hundredweight in region j: 
 
 set 1 -' + set 2 "' + set 3 '' 
 
 PPC J = Hundredweight production per cow in the period in region j 
 
 AD = Proportion of the population attending kindergarten through the 
 eighth grade 
 
 XIMIT = Per capita consumption of imitation dairy products in California 
 Y = Personal income per capita (U.S.) 
 
 52 
 
TABLE 7 (continued) 
 
 F ootnotes : 
 
 -^The equation numbers in this table correspond with the equation 
 numbers used in the text. 
 
 -^The subscripts have the following meaning: 
 t-i = the t-i th bimonthly period 
 
 X-i = the six bimonthly periods starting with the period I years 
 ago and going back five more periods: simple average 
 
 L-I = the six bimonthly periods starting with the period I years 
 ago last period: simple average. 
 
 ^See Figure 2 for the location of the regions. 
 
 -^The quantities produced per day as determined from the equations in 
 the producer subsector must be multiplied by the days in the period 
 and by 100 to convert hundredweights to pounds prior to performing 
 the calculations required in the processor subsector. 
 
 -''a more complete description of the data including sources and trans- 
 formations is contained in Appendix A. 
 
 -^The control variables are in parentheses with the exogenous variables 
 in the equations. 
 
 ^As indicated previously, the State's authority to set minimum 
 wholesale and retail prices on fluid milk products was repealed, 
 effective January 1, 1978. The retail price of fluid milk was 
 controlled during the period from which observations were drawn 
 and, hence, is appropriately treated as an exogenous (control) 
 variable . 
 
 53 
 
normally considered by the Bureau of Milk Stabilization. The observa- 
 tions for 1958 through 1960 are used only for lagged variables. As 
 described in the previous section, the system to be estimated has 
 equations containing variables that are determined simultaneously and other 
 equations with no simultaneously determined variables. The simultaneous 
 equations are estimated with two stage least squares, and the remaining 
 estimates are obtained from ordinary and generalized least squares. 
 
 Milk Production 
 
 Because the initial regression results indicated that the data are 
 characterized by autocorrelated residuals, the six production response 
 equations are estimated by generalized least squares.-'' In the following 
 three sections the results are presented, discussed, and elasticities 
 are calculated and compared to other studies. 
 
 - The presence of autocorrelation as indicated by Durbin-Watson 
 statistics in the range of 0.6 to 0.8 is not unexpected with bimonthly 
 data. Both first order and second order transformations were tested 
 with the first order transformation recording superior results. 
 
 Accordingly, the two-step generalized least squares procedure 
 suggested by Theil [1971, p. 254] is used for all results reported in 
 this section. The first step consists of running ordinary least squares 
 and employing the residuals to generate an estimate of the first-order 
 autoregressive coefficient (p) using 
 
 n-1 
 
 P = 
 
 E e - x e 
 f 1 * t+1 
 
 (n-1) s 
 
 The second stage then consists of obtaining ordinary least squares 
 estimates from the transformed model: 
 
 k 
 
 y t " p> t-i = h= \ B h (x th - >Vr h) + (e t " P e t-i> 
 
 for t=2,...,n. Because of the use of p, only large-scale statistical 
 properties have been derived for the resulting estimates (see Theil [1971], 
 pp. 405-415). The results have the desirable statistical properties (e.g.] 
 consistency, efficiency, etc.) only when no lagged dependent variables 
 are specified. Since only large-sample properties apply, a standard 
 normal table is used for all tests of statistical significance. For more 
 details see Theil [1971], Goldberger [1964], or Milligan [1975a]. 
 
 54 
 
The Results 
 
 The estimated effects of the variables specified in relationships 
 1-5 and 12 (Table 7) are presented below. In some regions one or more 
 of the variables were not found to be significant and the corresponding 
 
 b is assumed to be zero. The t-statistic for each coefficient is in 
 
 kj 
 
 parentheses, the asterisks indicate the level of significance (one is 
 
 -2 
 
 ten percent, two is five percent and three is one percent), R is the 
 adjusted coefficient of determination, and D-W is the Durbin-Watson 
 statistic. For ease of comparison, the coefficients of each equation 
 for all variables except the seasonal dummy variables are summarized in 
 Table 8. 
 
 Southern California 
 
 (B.l) q A1 = 101076.38- 45.18 mf 1 , + 226.69 m A1 „ - 115.20 p* F " 356,95 P T 
 t L-l L-z 1 
 
 (8.82)*** (-0.64) (3.74)*** (-0.93) (-2.50)** 
 
 + 386.97 TM+ 2693.68 S* + 3372.01 + 616.84 S 3 + 388.78 S* 
 (4.57)*** (7.41)*** (7.61)*** (1.33)* (0.87) 
 
 - 743.76 S 5 
 
 t 
 
 (-1.99)** 
 
 R 2 = .820, D-W = 1.31- , 0 = .53 
 2/ 
 
 Southern San Joaquin Valley— 
 
 (B.2) q M = 53687.4 + 75.17 m^ + 103.37 m£\, + 126.66 m^ 3 - 640.65 p™* 
 (3.33)*** (1.08) (1.64)* (1.92)** (-1.34) 
 
 - 578.53 p£ + 532.59 dhi T + 634.45 TM+ 2722.81 S^ + 5152.50 S fc 
 (-4.05)*** (1.74)** (5.26)*** (8.16)*** (12.82)*** 
 
 + 5380.47 S 3 + 3439.86 S^ + 267.29 S 5 
 (12.83)*** (8.55)*** (0.80) 
 
 -2 3/ ~ 
 
 R = .966, D-W = 1.29- , P = .50 
 
 — ^At the 1 percent level of significance, this value is in the indeter- 
 minancy region. 
 
 -''observations from January-February 1962 through November-December 
 1973 (n=72) are used in the Southern San Joaquin Valley, Northern San 
 Joaquin and Sacramento Valleys, and the Mountain Areas and North Coast 
 regions where nAi_ significantly affected production. 
 
 3/ 
 
 — At the 1 percent level of significance, this value is in the 
 indeterminancy region. 
 
 55 
 
TABLE 8 
 
 A Comparison of the Results for Selected Variables for the Five Regional Market Milk Equations 
 
 and the Statewide Manufacturing Milk Equation 3 -' 
 
 Dependent 
 
 Variable Constant 
 
 (B.l) 
 Al 
 1- 
 
 101076 
 (8.82) 
 
 nv 
 
 Aj 
 
 A.i 
 
 V-l 
 
 m 
 
 L-2 
 
 L-3 
 
 -45.18 
 (-0.64) 
 
 226.69 
 (3.74) 
 
 INT 
 T— 2 
 
 BF 
 
 -115.20 -356.95 
 (-0.93) (-2.50) 
 
 dhi 
 
 TM 
 
 386.97 
 (4.57) 
 
 (B.2) 
 
 A2 
 
 53687 
 (3.33) 
 
 75.17 
 (1.08) 
 
 103.37 
 (1.64) 
 
 126.66 
 (1.92) 
 
 -640.65 
 (-1.34) 
 
 -578.53 
 (-4.05) 
 
 532.59 
 (1.74) 
 
 634.45 
 (5.26) 
 
 (B.3) 
 A3 
 
 7651 -64.41 -121.78 295.46 238.58 
 (0.59) (-0.68) (-1.18) (2.66) (2.17) 
 
 759.35 
 (1.95) 
 
 142.00 
 (1.22) 
 
 (B.4) 
 A4 
 9- 
 
 28603 
 (5.98) 
 
 -54.12 
 (-1.91) 
 
 -222.66 
 (-5.04) 
 
 73.38 
 (0.54) 
 
 65.81 
 (2.07) 
 
 (B.5) 
 A5 
 
 2530 
 (6.77) 
 
 18.98 
 (2.25) 
 
 12.10 18.81 -100.86 -50.90 
 (1.47) (2.21) (-1.95) (-4.04) 
 
 23.84 
 (2.07) 
 
 (B.12) 
 B 
 q t 
 
 73020 
 (16.68) 
 
 B 
 
 9416 
 (3.20) 
 
 L-l 
 
 10581 
 (3.43) 
 
 L-2 
 
 6533 
 (2.24) 
 
 CORN 
 
 -2598 
 (-1.86) 
 
 -1465 
 (-14.06) 
 
 The dummy variables for seasonality are not included in this table. 
 
Northern San Joaquin and Sacramento Valleys 
 
 (B.3) q A3 = 7650.59 - 64.41 mf 3 - 121.78 mf 3 , + 295.46 m A \ + 238.58 m A3 
 
 t L L-l L-2 L-3 
 
 (0.59) (-0.68) (-1.18) (2.66)*** (2.17)** 
 
 + 759.35 dhi + 142.00 TM+ 3684.80 S 1 + 6595.36 S 2 
 T t t 
 
 (1.95)** (1.22) (8.88)*** (13.17)*** 
 
 + 6081.70 S + 3088.82 S 4 - 159.18 S 5 
 t t t 
 
 (11.63)*** (6.16)*** (-0.38) 
 
 R 2 = .930, D-W = 1.10^, p = .51 
 
 Central Coast 
 
 A4 A 4 RF 
 
 (B.4) q t = 28603.2 - 54.12 - 222.66 p* + 73.38 dh± T + 65.81 TM 
 (5.98)*** (-1.91)** (-5.04)*** (0.54) (2.07)** 
 
 + 1519.32 + 1618.61 S 2 + 1091.56 S 3 + 410.15 S 4 - 149.68 S 5 
 t t t t t 
 
 (12.11)*** (10.41)*** (6.65)*** (2.62)*** (-1.16) 
 
 -2 2/ - 
 
 R = .765, D-W = 1.21- , p = .62 
 
 Mountain Areas and North Coast 
 
 (B.5) q A5 = 2530.39 + 18.98 m^ 5 + 12.10 + 18.81 - 100.86 p™* 
 
 (6.77)*** (2.25)** (1.47)* (2.21)** (-1.95)** 
 
 - 50.90 P J F + 23.84 dhi + 515.73 S 1 + 875.23 S 2 + 641.78 S 3 
 T t t t t 
 
 (-4.04)*** (2.07)** (15.32)*** (21.40)*** (15.00)*** 
 
 + 303.47 S 4 + 53.96 S 5 
 t t 
 
 (7.41)*** (1.59)* 
 
 R 2 = .882, D-W = 1.20^ , p = .54 
 
 — The hypothesis of positive autocorrelation is accepted at the 
 1 percent level of significance. 
 
 2/ 
 
 — At the 1 percent level of significance, this value is in the 
 indeterminancy region. 
 
 57 
 
Manufacturing Milk 
 
 (B.12) q B = 73020.2 + 9415.54 p£ + 10581.1 p x + 6533.04 p£_ 2 
 (16.68)*** (3.20)*** (3.43)*** (2.24)** 
 
 - 2598.06 p^ 0RN - 1464.72 p£ + 6809.24 sj + 10781.4 S 2 
 (-1.86)** (-14.06)*** (11.59)*** (15.20)*** 
 
 + 9544.07 + 4104.83 + 596.63 
 (12.89)*** (5.76)*** (0.99) 
 
 R 2 = .891, D-W = Q.91-^ (5 = .49 
 
 Discussion of the Market Milk Estimates 
 
 Given the discussion of the short-run constant income stream objec- 
 tive (pages 32-33) , relatively small and/or insignificant coefficients 
 Ai Ai 
 
 on m^ J and m L _-^ would not be surprising. Negative coefficients even with 
 questionable significance are, however, rather surprising. In order to 
 be certain that the negative signs are not a function of the particular 
 specification used, a series of alternative specifications, particularly 
 on the lag structure, were investigated. The negative short-run coeffi- 
 cients appeared consistently in these specifications. Since most price 
 changes in the time period considered (1958-1973) were small, it may be 
 that the short-run constant income stream objective prevails for small 
 price changes. It is unlikely this response would hold for large price 
 changes . 
 
 The unambiguous direction and importance of the capacity decision 
 is indicated by the response to the third and fourth lagged margin variable. 
 These coefficients are much more significant than the short-run variable; 
 consequently, the long-run response to an increased (decreased) margin 
 is positive (negative) as expected. 
 
 — The hypothesis of positive autocorrelation is accepted. An analysis 
 of the residuals indicates there is one or more factor(s) affecting manu- 
 facturing milk producers that has not been delineated. All attempts to 
 isolate such factor(s) were unsuccessful. 
 
 58 
 
The seasonality of milk production is manifested in the significance 
 of the dummy variables. Production is significantly greater than in 
 January-February in all periods except November-December . As Table 9 
 illustrates, differences among the regions do exist. Seasonal adjust- 
 ments in production are less pronounced in the Southern California and 
 the Central Coast regions. 
 
 TABLE 9 
 
 The Effect of Seasonality on Production by Regions 
 with the Coefficient on the Dummy Variables Expressed as a Percentage 
 of Average Production in the Region 
 
 
 March- 
 
 May- 
 
 July- 
 
 Sept.- 
 
 November- 
 
 Region 
 
 April 
 
 June 
 
 August 
 
 October 
 
 December 
 
 Southern California 
 
 3.25 
 
 4.07 
 
 0.74 
 
 0.47 
 
 -0.90 
 
 Southern San Joaquin 
 
 4.84 
 
 11.04 
 
 11.54 
 
 7.38 
 
 0.57 
 
 Northern San Joaquin 
 
 7.00 
 
 12.52 
 
 11.55 
 
 5.86 
 
 -0.29 
 
 Coast 
 
 5.33 
 
 5.68 
 
 3.83 
 
 1.44 
 
 -0.53 
 
 Mountains 
 
 18.33 
 
 31.10 
 
 22.81 
 
 10.79 
 
 1.92 
 
 California 
 
 5.17 
 
 8.23 
 
 6.48 
 
 3.53 
 
 -0.37 
 
 When a regression was run with California market milk as the 
 
 _2 
 
 dependent variable, the R wa s high but the significance of most coeffi- 
 cients was less than in the regional equations. This situation illustrates 
 
 that a factor of importance in one region may be diluted when total market 
 
 -2 
 
 milk production is considered. Although the R cannot strictly be 
 compared among regions since the p's are different, the results suggest 
 that relatively larger unexplained variation exists in Southern Cali- 
 fornia and the Central Coast where urban pressure is great and in the 
 Mountain Areas and North Coast where only a little over one percent of 
 market milk is produced. The importance of the urban pressure may 
 introduce forces that are not specified in the equations. 
 
 All regions except the Mountain Areas exhibit a significant trend 
 toward increased production. This trend is a proxy for increased prod- 
 uction per cow and increased herd size due to improvements in technology, 
 genetics, and management. A part of the improvement in management is 
 
 59 
 
separately included in most regions by the proxy dhi^ variable. The 
 largest time trend is in the Southern San Joaquin region; a region that 
 has been increasing production rapidly with dairies relocating from 
 other regions, primarily Southern California. The individual regional 
 equations are discussed further in the subsections that follow. 
 
 Southern California 
 
 Southern California dairies are typically very large, industry- 
 type operations that purchase nearly all feed inputs and operate with 
 large quotas. Due to the large quotas and the lack of alternatives 
 resulting from the high degree of specialization, there is little aggre- 
 gate short-run reaction to changes in margin per cow. Short-run reactions 
 of the two types presented above seem to cancel out in the first year 
 while a little of the "income stream" adjustment carries over to the 
 second year. Capacity adjustments (long-run) occur more rapidly in this 
 region, probably because management is better and because production has 
 been increasing less rapidly indicating fewer large capacity adjustments. 
 The latter factor is also reflected in the importance of beef prices. 
 With fewer capacity adjustments producers have more latitude to cull cows 
 when beef prices are high. On the other hand, the price of beef is less 
 significant than one might expect. This may be due to the dairies being 
 specialized and production per cow so high that the beef price only 
 marginally affects culling decisions. The significance of the land price 
 eminates from the general competition of feed inputs with other crops and 
 the increased difficulties, apart from price, encountered in obtaining 
 feed supplies when competitive crops and thus land prices are high. 
 
 Southern San Joaquin Valley 
 
 The Southern San Joaquin region has been characterized by rapid 
 increases in production and by an accelerated movement toward larger, 
 more specialized dairies similar to those found in Southern California. 
 The aggregate short-run response is again almost insignificant. Because 
 much of the production increase is created by new dairies or by large 
 
 60 
 
capacity increases, the capacity adjustments are not as rapid as in 
 Southern California, and the costliness of borrowing money (the interest 
 rate) shows some significance. As in the Southern California region, 
 the index of land prices has a strong negative effect on production. 
 Production is unaffected by beef prices probably because of the large 
 capacity increases requiring all available quality cows and the high 
 degree of specialization present in the region. 
 
 Northern San Joaquin and Sacramento Valleys 
 
 The results from this region with dairies that raise much more of 
 their feed inputs but still are firmly entrenched in milk production are 
 perplexing. Although still minor, the aggregate short-run response to 
 marpin is larger than in the previous regions. The capacity adjustment 
 again continues into the fourth year. 
 
 The perplexing aspect of this equation is that none of the oppor- 
 tunity cost variables that should negatively affect production — 
 
 BF L INT , . ... Tfc . 
 
 > Pj» Pj 2 — appears in the fxnal equation. It is not surprising 
 
 when one or two of the variables are excluded since all three may not 
 
 be important in a particular region and since there is colinearity 
 
 between the three and with dhi^ and TM; however, the absence of all three 
 
 is unexpected. It may be that the interest rate is less important 
 
 because capacity adjustments are smaller, beef price is insignificant 
 
 because it affects the culling rate only marginally, and land price is 
 
 reflected in the margins since many more producers grow their own feed 
 
 inputs. 
 
 Central Coast 
 
 The results for the Central Coast region are also unexpected with 
 no capacity adjustment to margin. Since production has remained constant 
 in this region, with smaller dairies possessing high quotas and facing 
 pressures from urban expansion, further analysis indicates the results 
 may not be unreasonable. Many producers are primarily interested in a 
 
 61 
 
constant income stream which they acquire by increasing production when 
 margins shrink and by culling cows when beef prices are high. In general, 
 dairymen in this area have not purchased larger dairies elsewhere in the 
 region when urban expansion has forced them to move or sell out, as has 
 been the case in Southern California. 
 
 Mountain Areas and North Coast 
 
 The typical dairy in this region is much smaller, much less special- 
 ized, and more marginal than market milk firms in the other regions. 
 This situation is reflected in the large positive short-run reaction to 
 margin. When the margin increases, production is increased; when profit- 
 ability declines, cows are culled and herds are liquidated. The coefficients 
 A5 A5 
 
 on m and m indicate that capacity adjustments occur less rapidly than 
 L~ "2 L~~3 
 
 in other regions primarily because many producers raise their own replace- 
 ments. The reactions to interest charges and beef prices reflect the 
 more marginal nature of production in this region. The land price variable 
 is not included since this region is so different from the state as a 
 whole. This is the only region failing to exhibit a ceteris paribus 
 trend of increased production. 
 
 Discussion of the Manufacturing Milk Estimates 
 
 When compared to market milk dairies, typical manufacturing milk 
 dairies are much smaller, have lower production per cow, and are much 
 more diversified. Although the three price variables possess severe 
 multicolinearity , each is significant at the five percent level. In 
 addition, the price of corn has an important negative effect on produc- 
 tion. The corn price had a more significant effect than did the price 
 of 16 percent dairy feed. Hay price did not show a significant effect 
 probably because most producers raise their own roughage and apparently 
 fail to recognize the opportunity cost of feeding the roughages to their 
 cows. The extreme significance of the land price reflects the diversifi- 
 cation typical of these firms with the land price serving as a proxy for 
 the profitability of raising cash crops that compete with feed inputs. 
 
 62 
 
The unexpected deletion of beef price can probably be attributed to the 
 presence of multicolinearity. 
 
 Analysis of Supply Respons e 
 
 A meaningful comparison of the results of this study with other 
 studies is limited because: (1) the dairies in California are typically 
 much larger and more specialized than dairies in other states, (2) 
 production in this study is separated into market and manufacturing 
 milk, (3) the bimonthly observations, and (4) the lag structure 
 employed. The reader should remain cognizant of these dissimilarities 
 throughout the following discussion. 
 
 Supply Elasticities 
 
 Table 10 contains the margin and price elasticities for the 
 estimated equations presented above. The margin elasticities are 
 small since a one percent change in margin is created by a much smaller 
 change in price or costs. To obtain a margin elasticity value compar- 
 able to price elasticity, the percentage change in margin created by 
 a one percent change in price is determined (all calculation using mean 
 values and the most recent values) .— This percentage is then multiplied 
 by the margin elasticity to derive a value that can be compared (with 
 the appropriate qualifications) with price elasticities. Limited analysis 
 with equations containing price indicated that these values are slightly 
 higher than price elasticities for the market milk regions; however, the 
 indicated differences are small enough that the calculated values can 
 be compared with price elasticities for manufacturing milk and all milk, 
 and with price elasticities in other studies. 
 
 — The value is calculated by multiplying one percent of the price 
 by the production per cow. The number is then divided by the margin 
 per cow and converted to a percent. 
 
 63 
 
TABLE 10 
 
 Margin and Price Elasticities for Milk Produced in California 
 
 Area of Production, 
 Time Period, and 
 Equation 
 
 Southern California 
 (Equation B.l) 
 
 L-l 
 
 L-2 
 
 Total 
 
 South San Joaquin 
 (Equation B.2) 
 
 L-l 
 
 L-2 
 
 L-3 
 
 Total 
 
 North San Joaquin 
 (Equation B.3) 
 L 
 
 L-l 
 L-2 
 L-3 
 Total 
 
 Central Coast 
 (Equation B.4) 
 L 
 
 Mountains 
 (Equation B.5) 
 L 
 
 L-2 
 L-3 
 Total 
 
 Manufacturing Milk 
 (Equation B.12) 
 L 
 
 L-l 
 L-2 
 Total 
 
 All Milk 
 L 
 
 L-l 
 
 L-2 
 L-3 
 Total 
 
 Margin 
 Elasticity 
 
 ■ rice 
 Elasticity 
 
 Comparable 
 Value 
 
 Nov-Dec Nov-Dec Nov-Dec 
 
 Mean 1973 Mean 1973 Mean 1973 
 Values Values Values Values Values Values 
 
 ,011 
 
 ,050 
 ,040 
 
 ,016 
 ,018 
 ,017 
 .051 
 
 .019 
 ,033 
 .068 
 .046 
 .062 
 
 ,015 
 ,067 
 ,052 
 
 ,031 
 .042 
 ,046 
 ,119 
 
 -.020 
 -.060 
 .136 
 .094 
 .140 
 
 -.031 -.032 
 
 .124 
 .068 
 .093 
 ,285 
 
 ,291 
 184 
 
 ,289 
 764 
 
 1.315 
 1.424 
 .852 
 3.591 
 
 .425 
 -.460 
 .252 
 .706 
 .924 
 
 3.242 
 3.219 
 1.941 
 8.402 
 
 .522 
 -.511 
 .283 
 .781 
 1.075 
 
 ,066 
 ,323 
 ,257 
 
 ,141 
 ,186 
 ,217 
 ,543 
 
 .119 
 ,214 
 ,496 
 ,390 
 ,552 
 
 .086 
 .370 
 .284 
 
 160 
 ,201 
 ,218 
 ,579 
 
 -.154 
 -.260 
 .587 
 .423 
 .596 
 
 -.200 -.306 
 
 .630 
 .377 
 .566 
 1.573 
 
 1.334 
 .740 
 1.054 
 3.128 
 
 64 
 
The elasticities labeled "total"— , which are the sum of the yearly 
 
 elasticities, are reasonable when compared to the long-run elasticities 
 
 2/ 
 
 derived in other studies and summarized in Table 5.— Most researchers 
 have found long-run elasticities in the range of 0.4 to 1.0. Since the 
 price elasticities are at least approximately comparable to the "compar- 
 able value", the major production areas for market milk — Southern California, 
 South and North San Joaquin — fall at the lower end of this range. The 
 elasticity for all milk production of .924 is very close to the elasticity 
 of 1.04 recently derived for California, Washington, and Oregon by 
 Hammond [1974]. 
 
 The difference in elasticities among the regions and the types 
 of production is revealing. The market milk regions of Southern Cali- 
 fornia and Central Coast regions, both with significant urban pressures 
 and high quotas, have a very inelastic market milk supply response. The 
 Central Valley market milk production regions maintain a somewhat less 
 inelastic response. These areas of large, specialized dairies have a 
 more inelastic response presumably because even in the long run they 
 are firmly entrenched in the dairy industry. The smaller, less special- 
 ized dairies in the Mountains and those producing manufacturing milk 
 possess an elastic supply response. The very elastic supply response 
 obtained when manufacturing milk firms are isolated reflects the 
 diversification and ease of transfer from the industry typical of 
 these producers. 
 
 Elasticities for Costs and Opportunity Costs 
 
 In the results presented in the preceding section, dairymen in all 
 regions except North San Joaquin and Sacramento Valleys exhibit a 
 
 — The total or the sum of the elasticities for individual years is 
 an approximation of the long-run elasticity. Since the individual elas- 
 ticities are the percentage change in production for a one percent change 
 in margin L-i years ago, the sum gives the total percentage change in 
 production resulting from a one percent change in margin. This procedure 
 is consistent with Wilson and Thompson [1967] for a finite series and 
 with the procedure used to derive the long-run elasticity in the partial 
 adjustment hypothesis. In this case the sum is a geometric series. 
 
 2/ 
 
 — No equivalent elasticities are available for comparison with the 
 elasticities for individual years. 
 
 65 
 
significant response to one or more variables representing the costs and 
 opportunity costs of producing milk. The elasticities for these responses 
 are summarized in Table 11. As was the case with the response to producer 
 returns, the smaller and more diversified market milk producers in the 
 Mountain region and manufacturing milk producers are much more responsive 
 than the large, specialized market milk producers. 
 
 Percent Fat and Solids 
 
 Wilson and Thompson [1967] found production per cow and the proportion 
 of cows bred artificially to exert a significant effect on the fat percent- 
 age. No similar relationship is found to characterize the fat percentage 
 in California production. In fact, the following equation, containing 
 only dummy variables for seasonality and a time trend, captures the down- 
 ward trend in fat percentage characteristic of this period. 
 
 (B.13) PCF = 3.845 - 0.176 S 1 - 0.306 - 0.314 
 
 t t t t 
 
 (422.78)*** (-16.51)*** (-28.69)*** (-29.40)*** 
 
 - 0.174 S 4 + 0.004 S 5 - 0.00125 TM 
 t t 
 
 (-16.29)*** (0.39) (-9.07)*** 
 
 -2 1/ 
 R = .959, D-W = 1.26- 
 
 Processor and Consumer Subsectors 
 
 Because the simultaneous subsystem contains elements of both the 
 processor and consumer subsectors, the results from the remaining behavioral 
 equations are discussed in this section. The results for the manufacturing 
 milk price (relationship 17 in Table 7) are discussed first. Results for 
 the retail value of fat and solids in products (relationships 22 and 23) 
 and the per capita consumption of fluid milkfat and fluid skim milk 
 (relationships 24 and 25) are then presented. The simultaneous subsystem 
 is included in these equations. Finally, the estimates of the demand for 
 fats and solids in products (relationship 27) is detailed. 
 
 — This value is in the indeterminant region at the one percent 
 significance level. 
 
 66 
 
TABLE 11 
 
 Elasticities Indicating the Responses of Milk. Production to Costs and Opportunity Costs 
 
 Area of Production 
 
 Interest 
 Elate 
 (T-2) 
 
 Beef 
 Price 
 (T) 
 
 Index of 
 Land Prices 
 (T) 
 
 Price 
 of Corn 
 (T) 
 
 Mean 
 Values 
 
 Nov-Dec 
 
 1973 
 Values 
 
 Mean 
 Values 
 
 Nov-Dec 
 
 1973 
 Values 
 
 Mean 
 Values 
 
 Nov-Dec 
 
 1973 
 Values 
 
 Mean 
 Values 
 
 Nov-Dec 
 
 1973 
 Values 
 
 Southern California 
 (Equation A. 2) 
 
 South San Joaquin 
 (Equation A. 3) 
 
 Central Coast 
 (Equation A. A) 
 
 Mountains 
 (Equation A. 5) 
 
 Manufacturing Milk 
 (Equation A. 12) 
 
 -.079 
 
 -.273 
 
 -.063 
 
 -.318 
 
 -.037 
 
 .058 
 
 ,207 -.386 
 
 -.480 -1.185 
 
 -.424 
 
 .506 
 
 -1.203 -1.164 
 
 -5.041 -11.334 
 
 -.250 
 
 -.778 
 
 All Milk 
 
 .565 -.670 
 
 -.122 
 
 -.204 
 
Manufacturing Milk Price 
 
 The following estimates are attained using the generalized least 
 squares procedure discussed in the previous section: 
 
 (B.17) p B = 0.242 + 0.0986 SP + 0.893 PMP - 0.00345 TM- 0.0716 S 1 
 t t t t 
 
 (2.31)** (1.63)* (15.79)*** (-2.53)*** (-2.23)** 
 
 - 0.0629 S 2 - 0.0475 S 3 - 0.0206 S 4 + 0.0498 S 5 
 t t t t 
 
 (-1.83)** (1.37)* (-0.66) (1.60)* 
 
 R 2 = .990, D-W = 0.97- , P = .37 
 
 The results indicate that the principal explanatory variable for 
 
 manufacturing milk price is the hundredweight equivalent of market milk 
 
 21 
 
 prices for classes 2 through 4 fats and solids (PMP) .— Additional 
 explanatory power emanates from the Federal support price for manufac- 
 turing milk, a time trend, and seasonality. The negative time trend 
 indicates that the manufacturing milk price is losing about two cents 
 per year in comparison with the controlled prices. Manufacturing milk 
 prices are highest in November-December and lowest in March-April, every- 
 thing else equal; however, the range is only about twelve cents. These 
 results appear to be reasonable in light of the extreme price control in 
 the dairy industry. Prato [1973] estimated a similar relationship for 
 the price nationally and found the Federal support price to be the prime 
 explanatory variable. 
 
 Behavioral Equations for Retail Value of Fat and Solids in Products and 
 Consumption of Fluid Products 
 
 Four behavioral relationships are discussed in this section: (1) 
 the retail value of fat in products (relationship 22 in Table 7); (2) the 
 
 — The hypothesis of positive autocorrelation is accepted. Although 
 undesirable, given the purpose of the study, the presence of autocorrelation 
 even after the autoregressive transformation is not too worrisome with an 
 
 R 2 of .990. 
 
 2/ 
 
 — The fat and solids prices are converted to a hundredweight because 
 manufacturing milk is still priced on a hundredweight basis with a butter- 
 fat differential. 
 
 68 
 
retail value of solids in products (relationship 23) ; (3) per capita 
 consumption of fluid milkfat (relationship 24) ; and (4) per capita 
 consumption of fluid skim milk (relationship 25). The first relation- 
 ship, which is not part of the simultaneous subsystem, is estimated by 
 ordinary least squares (OLS) ; the other three relationships are part 
 of this system and are estimated by two stage least squares (TSLS) 
 
 Retail Value of Fat in Products 
 
 The equation for the retail value of fat in products is not a part 
 of the simultaneous subsystem since the endogenous variables included 
 in the right hand side are determined recursively because the hypothesis 
 that fluid skim and/or fluid milkfat are substitutes for fat in products 
 is rejected. The behavioral equation estimated by ordinary least 
 squares is: 
 
 (B.22) RFP m = -0.881 + 1.241 APF + 0.373 APS + 0.0238 XMCH 
 
 t t t t 
 
 (-5.41)*** (7.82)*** (1.76)** (0.63) 
 
 + 0.0013 SB + 0.0460 CHESF - 0.0093 TM+ 0.0353 S 1 
 t t t 
 
 (0.68) (5.92)*** (-6.77)*** (2.43)*** 
 
 + 0.0715 S 2 - 0.0107 S 3 + 0.0089 S 4 + 0.0475 S 5 
 t t t t 
 
 (3.36)*** (-0.89) (0.61) (2.64)*** 
 
 -2 2/ 
 R = .974, D-W = .79- 
 
 — The complete simultaneous subsystem is relationships 18-21 and 
 23-26 of Table 7. As the results indicate the simultaneity is tenuous. 
 Ordinary least squares estimates of equations very similar to these were 
 deemed less desirable. 
 
 Although most of the estimated equations possess positive auto- 
 correlation, no corrective measures are attempted for two reasons. First, 
 since no means of correcting for autocorrelation in simultaneous systems 
 of equations is known to the author, the comparison of the results would 
 be hindered. Further, the high R^ i n most equations indicates that 
 although the residuals are correlated, they are so small the importance 
 of the correlation is questionable. _^ 
 
 It is recognized that both the R statistic and the Durbin-Watson 
 statistic are invalid for simultaneous equations. They are presented as 
 they provide indication of the properties of the estimated equation. In 
 the analysis of almost identical equations estimated by ordinary least 
 squares and two stage least squares, the statistics from the two are 
 almost identical. 
 
 2/ 
 
 — The hypothesis of positive autocorrelation is accepted. 
 
 69 
 
The variables included, the signs, and the magnitudes of the coeffi- 
 cients are consistent with expectations based on economic theory and 
 knowledge of the industry. The marketing margin for fat in products 
 appears to be primarily a percentage markup with ceteris paribus price 
 increases larger at the retail than the farm level. The coefficient and 
 the significance of the labor cost variables (XMCH) is less than might 
 be expected, possibly due to multicolinearity. Also the support price 
 for butter is less significant than might be expected probably because 
 of close correlation with the support price for manufacturing milk which 
 is a partial determinant of the average price paid for solids. The 
 positive, highly significant coefficient on the proportion of fat used 
 in cheese production (CHESF) reflects the high degree of marketing 
 services associated with cheese production. The negative coefficient on 
 the time trend indicates that ceteris paribus the marketing margin has 
 been shrinking about one cent per bimonthly period. 
 
 Simultaneous Subsystem 
 
 Two stage least squares are used to estimate the three behavioral 
 equations in the simultaneous subsystem — the retail value of solids in 
 products, per capita consumption of fluid milkfat, and the per capita 
 consumption of fluid skim milk (relationships 23-25 in Table 7) . The 
 results are: 
 
 (B.23) RSP™ = - 0.274 + 1.686 APS fc + 0.0809 XMCH^ + 0.00404 CHESS t 
 
 (-8.99)*** (15.48)*** (3.37)*** (1.45)* 
 
 - 0.00300 TM+ 0.00019 S* + 0.00138 - 0.000073 S^ 
 (-10.17)*** (0.03) (0.18) (-0.01) 
 
 4 5 
 
 - 0.0122 - 0.00236 S fc 
 
 (-1.47)* (-0.36) 
 R 2 = .992, D-W = 1.57 
 
 70 
 
(B.24) RFQF = 1.47 - 0.00155 RFLP + 0.0755 RSP m + 0.0247 AD 
 
 t t t t 
 
 (4.58)*** (-0.33) (0.52) (1.60)* 
 
 - 0.144 XIMIT - 0.0039 TM+ 0.043 S 1 - 0.0014 S 2 
 
 t t t 
 
 (-6.44)*** (-7.46)*** (3.88)*** (-0.12) 
 
 - 0.030 S 3 + 0.072 S + 0.076 S 5 
 
 t t t 
 
 (-2.50)*** (6.41)*** (6.68)*** 
 R 2 = .956, D-W - 0.94 
 
 (B.25) RSQF = 48.45 - 0.0458 RFLP + 1.893 RSP m + 0.0145 AD 
 t t t t 
 
 (5.76)*** (-0.38) (0.50) (0.04) 
 
 - 3.156 XIMIT - 0.0338 TM+ 1.05 S 1 - 0.321 S 2 
 
 t t t 
 
 (-5.88)*** (-2.45)*** (3.58)*** (-1.04) 
 
 - 0.947 S 3 + 2.133 S 4 + 1.109 S 5 
 
 t t t 
 
 (-3.05)*** (7.28)*** (2.98)*** 
 
 R 2 - .841, D-W = 0.93 
 
 The equation for retail value of solids in products is similar to 
 the equation for fat presented above. The marketing margin again 
 appears to be a percentage markup where farm-level price changes are 
 nearly doubled by the time they reach the consumer. As expected, 
 increases (decreases) in labor costs increase (decrease) the marketing 
 margin. The response to the proportion of solids used in cheese 
 production again is positive, and ceteris paribus the marketing margin 
 is shrinking. 
 
 When Equations B.24 and B.25 are adjusted for the differences 
 between a pound of fat and a pound of skim milk, most of the coefficient 
 in the two equations are almost identical. The two differences are 
 (1) the age distribution variable appears to have some effect on the 
 demand for fat only and (2) the coefficients on the time trend reflect 
 the expected result that the demand for fat is declining more rapidly 
 than the demand for skim milk. Because of these differences, the 
 separate specification of fat and skim milk is retained in the model; 
 however, the equations are analyzed together in the following paragraphs 
 
 71 
 
A general conclusion that can be drawn from Equations B.24 and B.25 
 is that the demand for fluid milk products is explained primarily by 
 exogenous variables: concern over cholesterol, downward trend in consump- 
 tion, and seasonality. The per capita consumption of imitation milk 
 products (XIMIT) has a greater impact than simply substitution. The 
 author hypothesizes that this large impact results from the variable 
 serving as a proxy for the level of consumer concern over cholesterol. 
 Per capita consumption is indicated to be declining about 0.2 pound of 
 fluid milk per year, ceteris paribus . Consumption is relatively high 
 in September through December and relatively low in May through August. 
 The seasonality problem in the dairy industry is illustrated by comparison 
 with seasonality in production (Table 9, page 59) which is highest in 
 May-August and lowest in November-February. 
 
 The elasticities in Table 12 indicate that the demand for fluid milk 
 products is inelastic; however, the significance of the coefficients (see 
 Equations B.24 and B.25) is very low. This inelasticity is further 
 indicated by constructing a confidence interval on the demand coefficients. 
 When a 95 percent one-sided confidence interval is constructed on the 
 coefficient for retail milk price in the demand equations for fluid 
 milkfat (B.24) and fluid skim milk (B.25) and an elasticity is computed 
 from the limit using mean values, it is determined that with 95 percent 
 probability the demand for milk is more price inelastic than -0.28. 
 
 Although the inelasticity is consistent with a food that has few food 
 substitutes and is considered to be a basic element in every diet, the 
 elasticities in Table 12 are more inelastic than is generally accepted for 
 fluid milk. Wilson and Thompson [1967] found a price elasticity of -0.31. 
 Prato [1973] found a price elasticity of -0.105 with a t-ratio of 0.563. 
 
 There is some indication that California consumers may be more price 
 inelastic than the national average. Forker [1965] was unable to obtain 
 a negative coefficient on price, and Johnson [1967] completely excluded 
 the price variable in an extensive analysis of demand for milk in Cali- 
 fornia. A possible explanation is that consumers lost their consciousness 
 of price when the controlled price remained constant for months at a time. 
 
 72 
 
TABLE 12 
 
 Elasticities for 
 
 the Consumption of 
 
 Fluid Milkfat 
 
 and Fluid Skim Milk 
 
 
 Milk Price 
 Elasticity 
 
 
 Cross- 
 with 
 Solids 
 
 -Elasticity 
 Value of 
 in Products 
 
 Product 
 and 
 Equation 
 
 Mean 
 Values 
 
 Nov-Dec 
 
 1973 
 Values 
 
 Mean 
 Values 
 
 Nov-Dec 
 
 1973 
 Values 
 
 Milkfat (B.24) 
 
 -0.048 
 
 -0.068 
 
 0.017 
 
 0.043 
 
 Skim Milk (B.25) 
 
 -0.051 
 
 -0.067 
 
 0.015 
 
 0.036 
 
 Consumption of Fat and Solids in Products 
 
 The ordinary least squares estimates of the final relationship in 
 the model — per capita consumption of fat and solids in products — are 
 as follows: 
 
 (B.27) RMDQ = 2.94 - 0.477 APF - 0.577 APS + 0.0109 RFLP 
 
 t t t t 
 
 (7.94)*** (-5.18)*** (-1.83)** (1.58)* 
 
 + 0.00059 Y - 0.0221 TM+ 0.172 S 1 + 0.343 S 2 
 t t t 
 
 (5.44)*** (-9.58)*** (10.60)*** (20.01)*** 
 
 + 0.437 S 3 + 0.570 S + 0.699 S 5 
 t t t 
 
 (24.83)*** (35.74)*** (43.85)*** 
 R 2 = .968, D-W = 0.83^ 
 
 Table 13 indicates that the demand for manufactured dairy products 
 is more elastic than the demand for fluid products. The income 
 elasticities are particularly significant, and they compare favorably 
 with those of Wilson and Thompson [1967] , who found an income 
 elasticity of 0.60 for fat and 0.71 for solids. The price elasti- 
 cities are similar to those determined by Wilson and Thompson [1967] 
 
 — ^The hypothesis of positive autocorrelation is accepted. 
 
 73 
 
and Prato [1973]. Exact comparison with other studies is not possible 
 since each study has a different scheme for deriving the value of fats 
 and solids. As with fluid milk products, consumption is declining 
 ceteris paribus . 
 
 TABLE 13 
 
 Elasticities 
 
 for the Consumption of Fats and 
 Manufactured Dairy Products 
 
 Solids in 
 
 Elasticity with 
 
 Mean 
 Values 
 
 Nov. -Dec. 
 1973 Values 
 
 Retail Value of Fat 
 
 -0.192 
 
 -0.236 
 
 Retail Value of Solids 
 
 -0.035 
 
 -0.119 
 
 Fluid Milk Price 
 
 0.139 
 
 0.169 
 
 Income 
 
 0.495 
 
 0.734 
 
 Evaluation of the Model 
 
 Before proceeding to simulate future values of the endogenous variables, 
 it must be determined whether, in fact, the model will generate meaningful 
 values of the endogenous variables. Three kinds of tests are applied. 
 First, through the development of the model and the derivation of the 
 evaluation measures to be discussed below, it was concluded that the model 
 is superior to naive models such as "the same as last year" or "the same 
 change as last year". A look at actual versus predicted values provides 
 graphic proof that this conclusion is correct. 
 
 The second aspect of the evaluation procedure was to investigate the 
 stability of the model. Since nonlinearities appeared in the identities, 
 the dynamic properties could not readily be derived. Instead the following 
 procedure was employed. Using the exogenous and control variables for the 
 final year of the data series, 1973, the model was allowed to generate 
 new endogenous variables until it stabilized or exploded. All lagged and 
 recursive endogenous variables are composed of predicted values. When 
 this procedure was performed, there was a minimal amount of adjustment 
 
 74 
 
among the endogenous variables; however, within six to eight years 
 all values had stabilized at reasonable levels. 
 
 The third and most important part of the evaluation procedure was 
 to allow the model to generate a new time path for all endogenous 
 variables. This is accomplished by using the actual values of all 
 exogenous variables and the predicted values for all lagged endogenous 
 variables and for all endogenous variables entered in recursive 
 relationships. This procedure is designed to test whether the model 
 has any inadequacies that would allow one or more variables to drift 
 away from the actual time series. It should be noted that as French 
 and Matsumoto [1970] point out, this procedure is sensitive to the 
 starting point of the analysis. If the lagged endogenous variables 
 for the initial period are out of equilibrium the predicted values 
 from the model may deviate from actual values for some time. 
 
 In order to evaluate the results of the above procedure, the 
 following two measures are calculated for levels of the key endogenous 
 variables over the seventy-eight period (1961-1973, bimonthly observa- 
 tions) . Comparisons of levels utilize the values of the actual and 
 predicted endogenous variable in each time period. 
 
 1. Percent Mean Forecast Error is of Mean Value. 
 
 Mean forecast error is simply the average difference between 
 
 the actual and predicted level 
 N 
 
 [I (A - P )/N] where A is actual level, P is 
 t =l t t t t 
 
 predicted level, and N is the number of time periods. This 
 value is then divided by the average level of the variable. 
 
 2. Percent Mean Absolute Forecast Error is of Mean Value. 
 
 Mean absolute forecast error is the average error disregarding 
 the sign. 
 N 
 
 ( r |a - p. | / n) 
 t=i 
 
 This value is again divided by the average level of the 
 variable. 
 
 75 
 
In addition to these single-valued measures, tracking measures are 
 presented to evaluate the ability of the model to correctly foresee the 
 occurence of turning points. Table 14 provides a convenient method of 
 summarizing the incidence of the four possible combinations of actual and 
 predicted turning points.—^ In this table, a and d give the number of 
 each of the two types of correct forecasts; b and c provide the number 
 
 of periods in which each of the two types of errors occur. From this 
 
 b c 
 
 table the proportion of false turns (- — - — ) and missed turns ( ; — 7) c 
 
 b + a c + d 
 
 be calculated with ratios close to zero indicating accurate forecasts. 
 
 TABLE 14 
 
 Summary of Occurence and Non-occurence of 
 Actual and Predicted Turning Points 
 
 \ 
 
 \ Predicted 
 
 Actual \ No Turning Point Turning Point 
 
 No Turning Point a b 
 
 Turning Points c d 
 
 These measures are summarized in Table 15 for the important endogenous 
 
 2/ 
 
 variables in the model.— The magnitude of the figures indicates satis- 
 factory performance of the model. Only four of the variables had more 
 than two percent error in the mean absolute forecast error. Most of the 
 variables had predominantly correct (a + d) prediction of turning points. 
 
 —See Theil [1961] and Zarnowitz [1967] for examples of the use of 
 this summary table. 
 
 2/ 
 
 — A much more detailed presentation of these measures is contained 
 in Milligan [1975a] . 
 
 76 
 
TABLE 15 
 
 Evaluation Measures Comparing Actual Values with Values Predicted by 
 the Model for Selected Endogenous Variables 
 using 1961-1973 Bimonthly Observations 
 
 Percent Mean Percent Mean Tracking Measures 
 Relation Forecast Error Absolute Forecast (See Table 14 
 
 (Relation number in 
 
 is of Mean 
 
 Error is of 
 
 
 for a 
 
 - d) 
 
 
 parentheses) 
 
 
 Value 
 
 Mean Value 
 
 a 
 
 b 
 
 c 
 
 d 
 
 Daily Market Milk Production 
 
 
 
 
 
 
 
 Southern California 
 
 (1) 
 
 0.03 
 
 1.31 
 
 27 
 
 14 
 
 14 
 
 21 
 
 South San Joaquin 
 
 (2) 
 
 -0.02 
 
 1.83 
 
 45 
 
 6 
 
 6 
 
 19 
 
 North San Joaquin & 
 Sacramento 
 
 (3) 
 
 -0.02 
 
 2.08 
 
 40 
 
 9 
 
 11 
 
 16 
 
 Central Coast 
 
 (A) 
 
 0.12 
 
 1.58 
 
 36 
 
 11 
 
 15 
 
 14 
 
 Mountain & North Coast 
 
 (5) 
 
 -0.10 
 
 3.05 
 
 50 
 
 1 
 
 1 
 
 24 
 
 All Market Milk 
 
 (6) 
 
 0.02 
 
 1.44 
 
 46 
 
 5 
 
 5 
 
 20 
 
 Daily Manufacturing 
 Production 
 
 (7) 
 
 -1.42 
 
 5.80 
 
 49 
 
 2 
 
 2 
 
 23 
 
 Percent Milkfat 
 
 (8) 
 
 0.00 
 
 0.58 
 
 42 
 
 9 
 
 9 
 
 16 
 
 Percent Solids-not-fat 
 
 (9) 
 
 -0.00 
 
 0.11 
 
 42 
 
 10 
 
 9 
 
 15 
 
 Manufacturing Milk Price (10) 
 
 -0.06 
 
 1.36 
 
 42 
 
 5 
 
 7 
 
 22 
 
 Ave. Price Paid for Fat 
 
 (13) 
 
 -0.04 
 
 0.45 
 
 40 
 
 9 
 
 6 
 
 21 
 
 Ave. Price Paid for 
 Solids 
 
 (14) 
 
 -0.01 
 
 0.48 
 
 48 
 
 8 
 
 4 
 
 16 
 
 Consumption of Fluid 
 Milkfat 
 
 (15) 
 
 -0.36 
 
 1.26 
 
 18 
 
 9 
 
 7 
 
 42 
 
 Consumption of Fluid 
 Skim 
 
 (16) 
 
 -0.33 
 
 1.19 
 
 21 
 
 4 
 
 4 
 
 47 
 
 Consumption of Fluid 
 Milk 
 
 (17) 
 
 -0.33 
 
 1.19 
 
 21 
 
 4 
 
 4 
 
 47 
 
 Retail Value of Solids 
 
 (18) 
 
 -0.18 
 
 2.87 
 
 31 
 
 13 
 
 9 
 
 23 
 
 Retail Value of Fat 
 
 (19) 
 
 -0.02 
 
 1.53 
 
 21 
 
 20 
 
 11 
 
 24 
 
 Market Milk Price 
 
 (21) 
 
 -0.07 
 
 0.50 
 
 45 
 
 4 
 
 4 
 
 23 
 
 Consumption of Fat & 
 Solids in Products 
 
 (27) 
 
 0.01 
 
 0.86 
 
 52 
 
 0 
 
 0 
 
 24 
 
 77 
 
SIMULATION OF THE CALIFORNIA DAIRY INDUSTRY 
 
 In this section the development of and the results from the model 
 utilized to simulate future values of the endogenous variables of the 
 California dairy industry are discussed. This model employs (1) the 
 coefficients from the model just presented and (2) predicted time paths 
 for the exogenous and control variables to estimate the effects on the 
 California dairy industry of selected alterations in the time paths of 
 control and exogenous variables. 
 
 To avoid the problem of uncountable combinations of alternative time 
 paths for control and exogenous variables, the simulation procedure is to 
 initially specify a base model. This base model contains predicted time 
 paths for all exogenous and control variables for 1974-1985 and simulated 
 time paths for all endogenous variables. 1985 is chosen as the termination 
 date because it allows sufficient time to measure the effects of lagged 
 variables and because projecting to 1985 is somewhat standard. Simulations 
 are then executed by altering the time paths of exogenous and control 
 variables and comparing the results with the base model. 
 
 Prediction of Future Exogenous Variables 
 
 The inclusion of a sophisticated econometric model to predict the 
 future values of exogenous variables is beyond the scope of this study. 
 Various alternatives are available, however. Two very simple predictive 
 devices are (1) to assume that there is no change since the previous 
 bimonthly period or since the same bimonthly period a year ago and (2) 
 to assume that the change is occurring at the same rate as the last 
 period or year for which observations are available. Two techniques 
 that should produce more accurate predictions are to project each exogenous 
 variable based on the trend anticipated by the researcher and to estimate 
 an integrated autoregressive-moving-average (ARIMA) process for each 
 exogenous variable. An application of incorporating expected trends is 
 provided by French and Matsumoto [1970]. The ARIMA process was devised 
 
 78 
 
by Box and Jenkins [1970]. Further explanation including examples is 
 provided by Nelson [1973]. 
 
 For many of the key exogenous variables in the processor and 
 consumer subsectors — population, income, etc. — projections are published 
 by governmental agencies. In addition, employees of the Bureau of Milk 
 Stabilization are extremely knowledgeable concerning anticipated changes 
 in the levels of the exogenous variables affecting the producer sub- 
 sector. Consequently, the future values of the exogenous variables are 
 predicted based on anticipated trends for each variable. 
 
 There are forty-two exogenous and control variables (see Table 7, 
 pages 48-53) that require future time paths. Although not all data 
 series for 1974 were available when the simulations were executed, 
 enough information was available to recognize that many of these 
 variables registered abnormal values during 1974. Consequently, many 
 predicted values for 1974 are based on actual observations for all or 
 part of the year. 
 
 For 1975 and beyond, linear trends are specified based on past 
 trends, published projections, and expectations of the author. The 
 unusually high price level for feed inputs and consequently milk 
 prices in 1974 is reflected in the predicted values. No consensus has 
 emerged concerning the future direction of feed prices. Few expect the 
 prices to return to the levels of 1972 and before; however, the prices 
 could decline somewhat or continue upward depending upon world produc- 
 tion and demand conditions. In the absence of any consensus, it is 
 assumed that feed prices and milk prices will remain at the current 
 high levels, but no additional increases will occur until 1978. At 
 that time feed and milk prices are projected to return to a "normal" 
 gradual increase. 
 
 In arriving at the following projected trends the following 
 procedure was employed. All exogenous variables were considered first, 
 followed by the control variables for class 2-4 prices. These prices, 
 although control variables, must be closely aligned with Federal milk 
 market order prices. Finally, the class 1 prices and the fluid milk 
 
 79 
 
price were established at levels which approximately maintained producer 
 returns at past levels and retained stable supply and demand conditions 
 in the California dairy industry. 
 
 The reader should remain cognizant of the fact that any prediction 
 of future trends contains some degree of arbitrariness. The level of 
 this arbitrariness is increased by the unstable trends currently exhibited 
 by many variables. As a result, the analysis of this section emphasizes 
 the relative changes in endogenous variables resulting from alterations 
 in control and exogenous variables rather than the absolute levels of 
 the variables. 
 
 The trends employed for the exogenous and control variables are: 
 
 vc^ Variable cost per hundredweight in region j , j= 
 
 1: Southern California. Linear increase from Nov. -Dec. 1973 
 value ($6.85) to $8.00 in Nov. -Dec. 1974. Constant for 
 3 years. Then vc^ = vc^ + .03. 
 
 2: Southern San Joaquin. Linear increase from Nov. -Dec. 1973 
 value ($6.08) to $7.50 in Nov. -Dec. 1974. Constant for 3 
 years. Then vc ^ = vc ^i + *03« 
 
 3: Northern San Joaquin. Linear increase from Nov. -Dec. 1973 
 value ($6.66) to $7.55 in Nov. -Dec. 1974. Constant for 3 
 years. Then vc^ = VC A ' + .03. 
 
 4: Coast. Linear increase from Nov. -Dec. 1973 value ($6.85) 
 
 to $8.05 in Nov. -Dec. 1974. Constant for 3 years. Then 
 
 A4 A4 „- 
 vc = vc . + .03. 
 t t-1 
 
 5: Mountains. Linear increase from Nov. -Dec. 1973 value 
 
 ($6.01) to $7.55 in Nov. -Dec. 1974. Constant for 3 years. 
 Then vc^ 5 = vc^ + .03. 
 
 PPC"' Hundredweight production per cow in the period in region j , j = 
 
 1: Southern California. No change in 1974. Then yearly 
 increases equal to 1.5 percent of 1973 production. 
 2-5: No change in 1974. Then yearly increases equal to 2.0 
 percent of production in 1973. 
 
 80 
 
t,CORN CORN 
 
 P Price received for corn. For 1974-1977 ^ ^ = 6.00. There- 
 
 ..CORN CORN , _._ t 
 after P = P , + .025. 
 t t-1 
 
 I? Differential between average market milk price and market 
 
 milk price in region j , j = — » 
 
 1: Southern California. = L^_ 1 - .003 where = 0.30.-^ 
 
 2 2 2 
 
 2: Southern San Joaquin. = L fc _ 1 + .003 where L Q = -0.30. 
 
 3 3 3 
 
 3: Northern San Joaquin. L fc = ^ + .002 where - -0.20. 
 
 4 4 L 
 4: Coast. L fc ■ L t _ 1 - .0015 where = .15. 
 
 5: Mountains. - L fc _ 1 - .005 where = .50. 
 
 INT INT 
 P Interest rate, p =10.00. 
 
 BF 
 
 p Price received for beef in California. Decrease by 4 percent 
 
 of Nov. -Dec. 1973 level ($42.78) for six periods. Increase 
 
 by 2 percent of Nov. -Dec. 1973 level for twelve periods. Then 
 
 BF BF 
 P t " P t-1 + ' 25 ' 
 
 p^ Index of land prices in California. For 1974 and 1975 p^ = 
 
 L L L T ' 
 
 p t . +1.0 where p„ = 121. Thereafter p = p , + 0.6. 
 t-1 r 0 t t-1 
 
 dhi Percent of all cattle in California on DHI test, dhi ■ 
 
 t 
 
 dhi t _ 6 +1.0 where 1973 values are 51.652, 51.783, 51.915, 
 52.047, 52.178, and 52.310. 
 
 H Differential between price processor pays and producer 
 
 receives. H =0. 
 
 t 
 
 POP Population of California. Linearization to 1985 of the 
 
 baseline (Series D-100) population projections in California 
 Department of Finance [1974a, page 9]. P0P t = POP fc ^ + 
 50,964 where P0P Q - 20,281,000. 
 
 — The initial regional price differential is based on past values. 
 Since regional differences are shrinking as producer quotas reach 
 equalization, the differentials are moving toward zero. 
 
 2/ 
 
 — The observation for t = 0 is the Nov. -Dec. 1973 observation. 
 
 81 
 
SP Support price for manufacturing milk. Price raised to $6.75 in 
 
 March-April 1974. Starting in Jan. -Feb. 1975. SP - SP^ + .03. 
 
 Y Personal income per capita. Y = Y . + 30 where Y Q - 5229.35. 
 
 AD Proportion of the population attending kindergarten through 
 
 eighth grade. Based on age distribution reports in United 
 
 States Department of Commerce [1972b], the proportion in this 
 
 age group will decrease about .15 percent per year. AD^ - 
 
 AD , - 0.15 where AD 10 _. = 14.68. 
 t-1 1973 
 
 XIMIT Per capita consumption of imitation dairy products in California. 
 
 XMCH 
 SB 
 
 CHESF 
 CHESS 
 
 XIMIT = 0.413. 
 t 
 
 Hourly wage rate for manufacturing dairy products in California. 
 XMCH t = XMCH t 1 + .03 where XMCH Q = 5.755. 
 
 Federal support price for butter. SB fc = 66.00. 
 
 Proportion of fat consumed as cheese. CHESF^ - CHESF fi +1.0 
 where 1973 values are 48.1, 46.9, 46.2, 49.4, 48.2, and 47.9. 
 
 Proportion of solids consumed as cheese. CHESS t = CHESS t _g + 
 1.0 where 1973 values are 35.9, 37.5, 38.5, 40.4, 39.2, and 
 38.2. 
 
 TM 
 
 s 1 
 
 PFP 
 
 PSP 
 
 PMP 
 
 Time trend. TM = TM^ + 1 where TM Q = 78. 
 
 Seasonal dummy variable. No change from sector model. 
 
 Average price paid by manufactured dairy product processors 
 
 for market milk fat. For 1974-1976, PFP fc - .70. Thereafter 
 
 PFP = PFP + .001. 
 t t-1 
 
 Average price paid by manufactured dairy product processors 
 
 for market milk solids. Increased to .46 in Jan. -Feb. 1974 
 
 and to .52 in Mar. -Apr. 1974. Constant until Jan. -Feb. 1977 
 
 after which PSP = PSP , + .003. 
 
 t t-1 
 
 Hundredweight equivalent of PFP and PSP. PMP t = 3.50 x PFP t + 
 
 8.70 x PSP . 
 
 t 
 
 82 
 
C1FP 
 
 C1SP 
 
 Class 1 price for fat (pound). For 1974-1977 ClFP t - .749. 
 Thereafter ClFP t - C1FP + .001. 
 
 Class 1 price for skim milk (cwt.). After remaining constant 
 at 6.08 for two periods, increases to 7.25 and remains constant 
 
 RFLP 
 
 until Jan. -Feb. 1974. Thereafter ClSP t = CISP^ + .03. 
 
 Retail price for fluid milk. Increases in Mar. -Apr. 1974 by 
 5 cents (to 70.33) and remains constant through 1977. 
 
 Thereafter RFLP = RFLP 
 t 
 
 t-1 
 
 + .20. 
 
 Operation of the Simulation Model 
 
 The simulations are performed by computing values of endogenous 
 variables from the coefficients of the model presented in the previous 
 section and the predicted exogenous variables. All disturbance terms 
 are set equal to zero to generate deterministic predictions, which are 
 then expected values — i.e., trend or average levels of the endogenous 
 variables. 
 
 An alternative simulation approach is to include stochastic elements 
 based on the variance of the equations estimated in the preceding 
 section. Although this procedure would provide insight into the 
 sensitivity of the model to random exogenous shocks, the number of 
 computations is increased manyfold since repeated simulation runs are 
 required. Since the expected benefits do not appear to justify the 
 additional cost in time and money, expected values are used. 
 
 The operation of the simulation model is illustrated in Figure 10. 
 Using the data required to specify lagged endogenous and exogenous 
 variables and to compute predicted exogenous variables, the time paths 
 for the exogenous variables are computed. The structural model described 
 in the previous section is then used to compute the predicted values of 
 the endogenous variables for bimonthly periods in 1974-1985 (72 periods) . 
 
 In order to facilitate the presentation of the results of the 
 simulations, the bimonthly observations are converted to yearly values 
 
 83 
 
FIGURE 10 
 
 Flow Chart of the Operation of the Simulation Model 
 
 Start 
 T=0 
 
 
 
 f 
 
 
 
 Read lagged 
 variables 
 
 
 
 
 
 
 Calculate time paths 
 for 
 
 exogenous variables 
 
 
 ■ 
 
 Read coefficients 
 for sector model 
 
 
 
 Change control or 
 exogenous variables 
 
 
 
 T=0 
 
 Print output 
 desired 
 
 yes 
 
 no / Last 
 
 \ Simulation 
 
 
 
 Compute 
 
 yearly 
 
 values 
 
 yes 
 
 Generate endogenous 
 variables for T— 
 
 > 
 
 
 a/ 
 
 — See Figure 11. 
 
 84 
 
by summation or by averaging with the appropriate weights. The execu- 
 tion of these computations completes the first simulation run. Additional 
 simulation runs are then executed with changes in exogenous and/or 
 control variables. 
 
 The output for each endogenous variable^ includes bimonthly and 
 yearly values for each simulation run and the actual and percentage 
 deviation from the base simulation run for each additional run. These 
 deviations illustrate the impact of the specified changes in exogenous 
 and control variables. 
 
 The procedure executed to generate the endogenous variables for 
 each bimonthly period is outlined in Figure 11. After the lagged margin 
 and manufacturing price variables are computed, the production of market 
 milk (by regions), manufacturing milk, percent fat and solids, and 
 manufacturing milk price are predicted from the margin and exogenous 
 variables. 
 
 After per capita consumption of class 1 products is determined, 
 the quantities of fats and solids available for processing into manu- 
 factured dairy products is calculated. Further, the market and 
 manufacturing milk prices are weighted by the respective quantities to 
 calculate the average price paid for fats and solids processed into 
 products. Given these prices, the margin equations are used to determine 
 the retail value of fats and solids in products. These values are 
 then used to compute the per capita consumption of fats and solids in 
 products. 
 
 The average price paid market milk producers is determined by 
 weighting the controlled prices by the utilization of market milk. 
 This price, along with exogenous variables for variable costs, produc- 
 tion per cow, and regional price differences, is used to calculate the 
 margin per cow in each region which is utilized in determining production 
 in the following time period. 
 
 ~ ^Only 26 of the 27 endogenous variables in the sector model are 
 printed out because the average price per cwt. of market milk paid by 
 processors (pp^) and the average price per cwt . of market milk received 
 
 by producers (p^) are equal in the simulation model. 
 
 85 
 
FIGURE 11 
 
 Flow Chart of the Procedure Required to Generate Endogenous Variables 
 
 for a Given Time Period 
 
 Start 
 
 End 
 
 Generate lagged 
 margin variables 
 
 
 Compute market milk price and 
 
 margins 
 
 A A Aj 
 PP t » P t » n» t , .1 = 1. • • .5 
 
 Table 7, Relationships 6-10 
 and 15 
 
 + 
 
 Compute market milk production 
 
 A l i c A 
 q t > 3=1. • • .5, q t 
 
 Equations B.1-B.6 and Table 7, 
 Relationship 11 
 
 
 A 
 
 
 Compute per capita consump- 
 tion of fat and solids, 
 RMDQ , Equation B.27 
 
 I 
 
 Generate lagged manufacturing 
 price variable 
 
 
 
 
 Compute margin equations for 
 products, RFP m , RSP m 
 Equations B.22 and B.23 
 
 i 
 
 Compute manufacturing milk 
 production, q^, Equation B.12 
 
 
 
 
 Compute quantities and prices 
 of fat and solids going to 
 
 products, PFQ™, PSQ m , APF fc , 
 
 APS , Table 7, Relationships 
 18-21 
 
 1 
 
 Compute percent fat and solids 
 
 PCF and PCS , Equation B.13 
 t t 
 
 and Table 7, Relationship 14 
 
 
 I 
 
 
 Compute consumption of class 
 1 products, RFQF t> RSQF^ , 
 
 RFLQ^, Equations B.25 and 
 
 B.26 and Table 7, Relation- 
 ship 26 
 
 I 
 
 Compute manufacturing milk 
 price, p , Equation B.17 
 
 
 
 
 86 
 
The Base Model 
 
 One adjustment is required in the model before generating simulation 
 results. In 1974, the first simulated year, the base model predicted 
 negative manufacturing milk production. Three factors contributed to 
 this result: (1) 1974 was a very bad year for manufacturing milk firms 
 as milk price increases lagged behind feed input increases, (2) the 
 model (see Equation B.12) puts major weight on current feed costs and 
 lagged milk price, and (3) the predicted value for the price of corn 
 increased more rapidly than the actual price. Since manufacturing milk 
 is now a very small part of California milk production and since manu- 
 facturing milk production did decrease substantially in 1974 (actual 
 production decreased 17.43 percent from 1973 [calculated from California 
 Crop and Livestock Reporting Service [1974a] ]), this occurrence is not 
 considered to indicate a major flaw in the model. This result did not 
 occur in any other years in the base run. The negative values are set 
 equal to zero in the simulation runs. 
 
 Table 16 presents the actual values for 1973 and the predicted 
 
 values for 1977, 1981 and 1985 for the endogenous variables of the 
 
 base model.—''' In addition, Figure 12 illustrates the time paths of 
 
 four key endogenous variables: daily market milk production, per capita 
 
 consumption of class 1 products, percentage of market milk utilized as 
 2/ 
 
 class 1 products,— and average market milk price. This information is 
 presented to illustrate the general direction projected for the endogenous 
 variables and to serve as a basis for comparison during the discussion 
 of the remaining simulation results. 
 
 — The values are computed for the bimonthly observations but are 
 converted to yearly values by summation or weighted averages for presen- 
 tation purposes. 
 
 2/ 
 
 — Percentage of market milk utilized as class 1 products is not an 
 endogenous variable in the sector model; however, it is a good indicator 
 of supply-demand conditions within the industry. Producers and consumers 
 both benefit when this percentage is high: producer because a higher 
 price results from increased utilization in high value products; consumers 
 because a lower class 1 price is required to sustain production. 
 
 87 
 
TABLE 16 
 
 Actual Values for 1973 and 
 
 Predicted 
 
 Values for 
 
 1977 , 
 
 1981, and 
 
 1985 
 
 for the Endogenous Variables of the 
 
 Base Model 
 
 
 Variable 
 
 units 
 
 1 O 7 0 
 
 1 fi 7 7 
 19 / / 
 
 1981 
 
 1085 
 
 Daily market milk production 
 
 cwt . 
 
 256281 
 
 264746 
 
 282992 
 
 302407 
 
 Percent of market milk 
 
 
 
 
 
 
 production in: 
 
 
 
 
 
 
 Southern California 
 
 percent 
 
 34 . 83 
 
 O O Q O 
 
 32.78 
 
 31.63 
 
 Southern San Joaquin 
 
 percent 
 
 25.91 
 
 25.97 
 
 27.30 
 
 28.68 
 
 Northern San Joaquin 
 
 percent 
 
 27.24 
 
 27.98 
 
 28.49 
 
 28.89 
 
 Coast 
 
 percent 
 
 10.90 
 
 11.23 
 
 10.69 
 
 10.22 
 
 Mountains 
 
 percent 
 
 1.1/ 
 
 u . y4 
 
 U . /4 
 
 0. 5o 
 
 Daily manufacturing milk 
 
 
 
 
 
 
 pruuucLi. on 
 
 cwt • 
 
 9AOP.Q 
 
 1.1 1 A 9 
 
 ? i ni 7 
 
 14095 
 
 Percent fat 
 
 percent 
 
 3.60 
 
 3.56 
 
 3.53 
 
 3.50 
 
 Percent solids 
 
 percent 
 
 8.67 
 
 8.65 
 
 8.64 
 
 8.62 
 
 Manufacturing milk price 
 
 $/cwt. 
 
 5.46 
 
 6.55 
 
 7.14 
 
 7.73 
 
 Per capita consumption of 
 
 
 
 
 
 
 class 1 fat 
 
 lb. 
 
 8.94 
 
 8.25 
 
 7.63 
 
 7.01 
 
 Per capita consumption of 
 
 
 
 
 
 
 class 1 skim milk 
 
 lb. 
 
 265.90 
 
 260.93 
 
 256.84 
 
 252.63 
 
 Per capita consumption of 
 
 
 
 
 
 
 class 1 fluid 
 
 lb. 
 
 274.84 
 
 269.18 
 
 264.48 
 
 259.64 
 
 Percent of market milk 
 
 
 
 
 
 
 utilized in class 1 
 
 percent 
 
 61.15 
 
 61.05 
 
 59.24 
 
 57.31 
 
 Fat available for products 
 
 thousand 
 
 1833 
 
 2032 
 
 2163 
 
 2329 
 
 
 cwt . 
 
 
 
 
 
 Solids available for products 
 
 thousand 
 
 3415 
 
 3727 
 
 3765 
 
 3958 
 
 
 cwt . 
 
 
 
 
 
 Average fat price for products 
 
 $/lb. 
 
 0.73 
 
 0.69 
 
 0.72 
 
 0.75 
 
 Average solid price for 
 
 
 
 
 
 
 products 
 
 $/lb. 
 
 0.37 
 
 0.52 
 
 0.59 
 
 0.67 
 
 Retail value of fat in 
 
 
 
 
 
 
 products 
 
 $/lb. 
 
 1.91 
 
 1.89 
 
 1.93 
 
 1.97 
 
 Retail value of solids in 
 
 
 
 
 
 
 products 
 
 $/lb. 
 
 0.75 
 
 1.00 
 
 1.12 
 
 1.24 
 
 Per capita consumption of 
 
 
 
 
 
 
 fats and solids in products 
 
 lb. 
 
 23.39 
 
 23.30 
 
 22.42 
 
 21.57 
 
 Market milk price 
 
 $/cwt. 
 
 6.50 
 
 8.38 
 
 8.99 
 
 9.65 
 
 88 
 
FIGURE 12 
 
 Projections of Four Key Endogenous Variables in the Base Model 
 310, 
 
 2591 I I I I I I I l l i i i 
 
 1973 1977 1981 1985 
 
FIGURE 12 (continued) 
 
 Percent 
 
 O 
 
 1973 
 
 1977 
 
 1981 
 
 1985 
 
 Dollars 
 per cwt . 
 
 10.00 
 
 9.00 - 
 
 8.00 - 
 
 7.00 - 
 
 1973 
 
 1977 
 
 1981 
 
 1985 
 
As Figure 12 illustrates, the gradual increase that has characterized 
 market milk production (see Figure 5) is expected to continue until 1985 
 except for the 1976-1977 period when production declines. This decline 
 is a result of the reduced short-run margin in 1973-1975 when feed costs 
 spiraled upwards. The increasing proportion of production in the 
 Central Valley (Southern San Joaquin and Northern San Joaquin and Sacra- 
 mento Valleys) illustrated in Figure 3 is expected to continue until 
 1985. 
 
 Actual production for 1974 and 1975 is compared to that predicted 
 by the base model in Table 17. The simulated production is reasonably 
 close to the actual with the largest deviations occurring toward the 
 end of the period compared. 
 
 Since population increases do not offset the increased production 
 and decreased per capita consumption, the percentage of market milk 
 utilized in class 1 products declines except for the 1976-1978 period. 
 This decline is a continuation of the past trend illustrated in Figure 
 6. As a result of this trend and the increased production, the quantity 
 of fat and solids available for products is projected to increase 
 dramatically. These production increases raise numerous questions 
 including availability of processing capacity, competition with other 
 farm enterprises, and relevance of the law of comparative advantage. 
 These questions can be more adequately addressed after all simulation 
 results have been presented. The results of the base model indicate 
 that the price increases granted to cover the increased production 
 costs in 1973-74 have been more than sufficient to ensure an adequate 
 supply of milk. 
 
 The continuing shift in value from the fat component to the solids 
 component of the milk is evidenced by the average price paid for and 
 the retail value of fat and solids in products. The fat prices are 
 projected to be relatively constant while solids prices increase 
 dramatically. Both market and manufacturing milk prices increase 
 initially as a result of the cost spiral in 1973 and 1974, level off 
 for several years, and then increase gradually. 
 
 91 
 
TABLE 17 
 
 Comparison of Actual and Simulated Daily Market Milk Production 
 
 for 1974 and 1975 
 
 a/ 
 
 Period Actual- Simulated Percentage 
 
 (cwt.) (cwt.) Deviation 
 
 197A 
 
 Jan. -Feb. 251,911 251,614 -0.12 
 
 Mar. -Apr. 266,563 264,966 -0.60 
 
 May-June 282,167 273,581 -3.04 
 
 July-Aug. 282,117 271,555 -3.74 
 
 Sept. -Oct. 267,914 266,894 -0.38 
 
 Nov. -Dec. 255,617 259,826 +1.65 
 
 Annual 267,841 264,830 -1.13 
 
 1975 
 
 Jan. -Feb. 257,521 261,146 +1.40 
 
 Mar. -Apr. 271,730 272,001 +0.10 
 
 May- June 288,309 278,598 -3.37 
 
 July-Aug. 288,795 272,541 -5.63 
 
 Sept. -Oct. 277,114 265,495 -4.19 
 
 Nov. -Dec. 269,484 256,092 -4.97 
 
 Annual 275,627 267,695 -2.88 
 
 a/ 
 
 — Calculated from California Crop and Livestock Reporting Service [1974a 
 1975a], Table 2. 
 
 92 
 
In the following sections the base model is used as the basis for 
 two types of simulations. First, the effects of price changes are 
 investigated by various alterations in the control variables. Second, 
 the effects of changes in key exogenous variables — population, producer 
 costs, consumer tastes — are simulated. 
 
 Simulation Runs with Altered Control Variables 
 
 Simulation runs one through four concern changes in variables that 
 are controlled within the dairy industry. The changes are: 
 
 1. All milk price variables are (a) increased by five percent and 
 (b) decreased by five percent;—''' 
 
 2. All milk price variables directly or indirectly related to the 
 Federal milk marketing program are (a) increased by ten 
 percent and (b) decreased by ten percent; 
 
 3. The milk price variables related to fluid milk and consequently 
 under the effective control of the California Bureau of Milk 
 Stabilization are (a) increased the equivalent of five cents 
 per half gallon of fluid milk and (b) decreased the equivalent 
 of five cents per half gallon of fluid milk;— ^ 
 
 h. The regional price differentials are (a) eliminated immediately 
 and (b) eliminated gradually over a four year period. 
 
 Any presentation of the time paths of the endogenous variables would 
 require many pages and would probably inundate the reader with so many 
 graphs that little would be retained. The alternative procedure employed 
 is to present a summary table for each simulation run. For each 
 endogenous variable that is significantly affected by the simulated 
 change, the following six values are presented: 
 
 1. The actual 1973 value; 
 
 2. The projected 1985 value when the first alteration of control 
 variables (usually a decrease) is simulated; 
 
 — ^See footnote f, p. 53. Although retail price is no longer a 
 control variable, farm level price changes still affect retail prices. 
 The simulation results retain validity as indicators of the effect of 
 price changes. 
 
 93 
 
3. The projected 1985 value from the base model; 
 
 4. The projected 1985 value when the second alteration of control 
 variables (usually an increase) is simulated; 
 
 5. Percent deviation of the value under the first alteration from 
 the base model; 
 
 6. Percent deviation of the value under the second alteration from 
 the base model . 
 
 Interesting trends or additional items of note are presented in tables, 
 figures, and/or the text. 
 
 Effects of Changes in All Milk Prices 
 
 The first simulation run considers the effects of a five percent 
 increase and decrease in all milk prices whether controlled by the 
 Bureau (control variables) or by Federal policy (exogenous variables) . 
 Eight control and exogenous variables are affected: the class 1 price 
 for fat (C1FP), the class 1 price for skim milk (C1SP) , the average 
 price paid by manufactured dairy product processors for market milk (PFP) , 
 the average price paid by manufactured dairy product processors for market 
 milk solids (PSP) , the hundredweight equivalent of PFP and PSP (PMP) , the 
 retail price of fluid milk (RFLP) , the support price for manufacturing 
 milk (SP), and the support price for butter (SB). This simulation run 
 is designed to measure the effect of a general increase and decrease in 
 price and consequently profits on the California dairy industry. All 
 other exogenous variables have the same time series as in the base model. 
 
 The results are summarized in Table 18. The five percent price 
 changes precipitate a slight change in market milk production and a 
 major change in manufacturing milk production. The magnitude of the 
 changes reflect the size of the price elasticities in the sector model 
 (see Table 10). When prices are decreased, the percentage used in fluid 
 products decreases significantly. The opposite effects occur for price 
 increases. Due to the inelastic demand for dairy products (see Tables 
 12 and 13), per capita consumption is affected only slightly. 
 
 94 
 
TABLE 18 
 
 Summary of Results from Simulation Run 1: Changes in All Milk Prices 
 
 
 
 Actual 
 
 1973 
 amount 
 
 Projected 1985 
 
 Value 
 
 Percent 
 
 Change 
 
 Endogenous Variable 
 
 Units 
 
 5 percent 
 decrease 
 
 Base 
 model 
 
 5 percent 
 increase 
 
 5 percent 
 decrease 
 
 5 percent 
 increase 
 
 Daily market milk production 
 
 cwt. 
 
 256281 
 
 293009 
 
 302407 
 
 311770 
 
 - 3.11 
 
 3 .10 
 
 Percentage of production in 
 Southern California 
 Southern San Joaquin 
 Northern San Joaquin 
 Coast 
 Mountains 
 
 percent 
 percent 
 percent 
 percent 
 percent 
 
 34.83 
 25.91 
 27.24 
 10.90 
 1.12 
 
 31.91 
 28.39 
 28.49 
 10.77 
 0.43 
 
 31.63 
 28.68 
 28.89 
 10.22 
 0.58 
 
 31.36 
 28.94 
 29.27 
 9.70 
 0.72 
 
 0.88 
 
 - 1.01 
 
 - 1.38 
 5.38 
 
 -25 .86 
 
 -0.85 
 0.92 
 1.31 
 -5.07 
 24 . 14 
 
 Daily manufacturing milk production 
 
 cwt. 
 
 24089 
 
 4285 
 
 14095 
 
 24281 
 
 -69.60 
 
 72.26 
 
 Manufacturing milk price 
 
 $ /cwt . 
 
 5.46 
 
 7.30 
 
 7.73 
 
 8.13 
 
 - 5.48 
 
 5.21 
 
 Per capita consumption of class 
 1 fluid 
 
 lb. 
 
 274.84 
 
 260.23 
 
 259.64 
 
 259.05 
 
 0.23 
 
 -0.23 
 
 Percent of market milk utilized 
 as class 1 
 
 percent 
 
 ai i k 
 
 01 . 1 J 
 
 59.28 
 
 57.31 
 
 JJ.HD 
 
 -J mHH 
 
 — j . l j 
 
 Fat available for products 
 
 thousand 
 cwt. 
 
 1 Q O 1 
 
 lo 33 
 
 2080 
 
 2329 
 
 / JO J 
 
 — J.U . Oj 
 
 in qi 
 
 J.U . J 1 
 
 Solids available for products 
 
 thousand 
 cwt. 
 
 3415 
 
 3341 
 
 3958 
 
 4588 
 
 -15.59 
 
 15.92 
 
 Average fat price for products 
 
 $/lb. 
 
 0.73 
 
 0.71 
 
 0.75 
 
 0.78 
 
 - 4.58 
 
 4.64 
 
 Average solids price for products 
 
 $/lb. 
 
 0.37 
 
 0.64 
 
 0.67 
 
 0.70 
 
 - 4.41 
 
 4.51 
 
 Retail value of fat in products 
 
 $/lb. 
 
 1.91 
 
 1.92 
 
 1.97 
 
 2.03 
 
 - 2.93 
 
 2.96 
 
 Retail value of solids in products 
 
 $/lb. 
 
 0.75 
 
 1.18 
 
 1.24 
 
 1.30 
 
 - 4.57 
 
 4.58 
 
 Per capita consumption of fats 
 and solids in products 
 
 lb. 
 
 23.39 
 
 21.68 
 
 21.57 
 
 21.47 
 
 0.47 
 
 -0.48 
 
 Market milk price 
 
 $/cwt. 
 
 6.50 
 
 9.20 
 
 9.65 
 
 10.09 
 
 - 4.59 
 
 4.58 
 
After all adjustments are completed, the average market milk price 
 changes by slightly less than five percent. The change is slightly less 
 because the price change affects the margin and production adjustments. 
 This production adjustment and the slight adjustment in consumption reduce 
 the effective change in price. 
 
 Figure 13 illustrates the time paths of production and market milk 
 price adjustments in percentage terms for the five percent price increase. 
 Similar changes occur for price decreases. As indicated above, the 
 greatest price change is registered almost immediately. Significant 
 production adjustments, however, are not registered until the third year. 
 The percent change remains relatively constant after the fifth year. In 
 the fourth year the percent change in price declines as the increased 
 production affects utilization adversely. The shape of these time paths 
 also typifies the reaction to price changes in the simulation runs that 
 follow. 
 
 Effects of Changes in Product Prices 
 
 In the previous simulation run the effects of changes in all milk 
 prices were illustrated. The prices can be separated into two sets of 
 prices: (1) class 1 or fluid product prices and (2) all prices related 
 to products. The first set of prices is the effective means of price 
 control of the Bureau. Since products are generally transportable over 
 long distances, these prices are directly or indirectly tied to Federal 
 support prices. In simulation run 2 the product related prices — the 
 average price paid by manufactured dairy product processors for market 
 milk fat (PFP) , the average price paid by manufactured dairy product 
 processors for market milk solids (PSP) , the hundredweight equivalent of 
 PFP and PSP (PMP) , the support price for manufacturing milk (SP) , and 
 the support price for butter (SB) — are decreased and increased by ten 
 percent. All class 1 prices and retail fluid milk prices are held 
 constant. The first three variables are controlled by the Bureau, but 
 the price levels are tied to Federal support prices or national price 
 levels. The final two variables are Federal support prices. This 
 
 96 
 
FIGURE 13 
 
 Time Paths of Adjustment in Daily Market Milk Production and in Market Milk Price 
 Resulting from Increasing All Milk Prices Five Percent 
 
 Percent 
 increase 
 over base 
 model 
 
 1974 
 
 1977 
 
 Change in market milk price 
 
 Change in production 
 
 "2 
 
 1981 
 
 1985 
 
simulation run illustrates the influence on the California dairy industry 
 of the prevailing U. S. prices for products. 
 
 The results from this simulation are summarized in Table 19. As 
 can be seen by these results, the California dairy industry is definitely 
 affected by events occurring in the national market for manufactured 
 dairy products. The ten percent change results in a three to four 
 percent change in market milk price. Although this change is not extremely 
 large, the effect on profitability would be significant. This fact is 
 illustrated by the adjustment in market milk production. The effect on 
 manufacturing milk, which is used in products exclusively, is dramatic; 
 the price changes by more than ten percent and production adjustments in 
 excess of fifty percent are typical throughout the time period. 
 
 These results underscore the relatively high degree of diversification 
 and the marginal nature of manufacturing milk dairies. These producers 
 generally operate on a very thin margin and frequently switch to other 
 enterprises or leave farming when that margin is reduced. Most of the 
 production increases would probably come from increased production within 
 existing herds; however, production decreases would come largely from 
 liquidations of existing herds. Because individual producers may have 
 elasticities significantly different (lower) than the aggregate, their 
 production would not fall to zero with the price decrease, but the 
 decrease would be very significant. 
 
 The effects recorded in the processor and consumer subsectors are 
 limited to the products component. The quantity of fat and solids 
 available for products is altered dramatically, especially for price 
 increases. Some change results from market milk production adjustments, 
 but the majority of the change comes from manufacturing milk production. 
 Farm- level and retail prices are affected significantly, and some changes 
 in consumption of products is projected. 
 
 Effects of Changes in Fluid Milk Prices 
 
 The more interesting control variables, because the Bureau of Milk 
 Stabilization maintains effective control of their levels, are those 
 
 98 
 
TABLE 19 
 
 Summary of Results from Simulation Run 2: Changes in All Product Prices 
 
 - 
 
 
 A t_ l_ LI d JL 
 
 1973 
 amount 
 
 Projected 1985 
 
 Value 
 
 Percent 
 
 Change 
 
 Endogenous Variable 
 
 Units 
 
 10 percent 
 decrease 
 
 Base 
 model 
 
 10 percent 
 increase 
 
 10 percent 
 decrease 
 
 10 percent 
 increase 
 
 Daily market milk production 
 
 cwt . 
 
 256281 
 
 /.yj /oo 
 
 3U24U 7 
 
 309328 
 
 -2.19 
 
 2.29 
 
 Daily manufacturing milk production 
 
 cwt. 
 
 24089 
 
 n 
 U 
 
 
 34467 
 
 -100.00 
 
 144.53 
 
 Manufacturing milk price 
 
 $/cwt. 
 
 5.46 
 
 
 "7 "7 1 
 / . 73 
 
 8.53 
 
 — 
 
 10.37 
 
 Percent of market milk utilized 
 
 
 
 
 
 
 
 
 in class 1 
 
 percent 
 
 61.15 
 
 JO . J / 
 
 ->/ . 31 
 
 56.24 
 
 1.85 
 
 -1.87 
 
 Fat available for products 
 
 thousand 
 cwt . 
 
 1833 
 
 2076 
 
 2329 
 
 2669 
 
 -10.88 
 
 14.60 
 
 Solids available for products 
 
 thousand 
 cwt . 
 
 3415 
 
 3330 
 
 3958 
 
 4844 
 
 -15.87 
 
 22.39 
 
 Average fat price for products 
 
 $/lb. 
 
 0.73 
 
 0.68 
 
 0.75 
 
 0.82 
 
 -9.44 
 
 9.21 
 
 Average solids price for products 
 
 $/lb. 
 
 0.37 
 
 0.61 
 
 0.67 
 
 0.73 
 
 -9.18 
 
 8.96 
 
 Retail value of fat in products 
 
 $/lb. 
 
 1.91 
 
 1.85 
 
 1.97 
 
 2.09 
 
 -6.02 
 
 5.89 
 
 Retail value of solids in products 
 
 $/lb. 
 
 0.75 
 
 1.13 
 
 1.24 
 
 1.35 
 
 -9.03 
 
 9.03 
 
 Per capita consumption of fats 
 and solids in products 
 
 lb. 
 
 23.39 
 
 22.30 
 
 21.57 
 
 20.86 
 
 3.37 
 
 -3.33 
 
 Market milk price 
 
 $/cwt. 
 
 6.50 
 
 9.32 
 
 9.65 
 
 9.99 
 
 -3.42 
 
 3.60 
 
pertaining to class 1 or fluid products. The three variables are the 
 
 class 1 price for fat (C1FP) , the class 1 price for skim milk (C1SP) , and 
 
 1/ 
 
 the retail price of fluid milk (RFLP) . When class 1 price changes are 
 
 granted under the procedure described in the introductory section, the 
 
 equivalent hundredweight price is changed in increments of 23 cents, 
 
 which corresponds to a one cent change in the retail price of a half 
 
 gallon of whole milk. To be consistent with this procedure the changes 
 
 simulated are (a) a five cent decrease in the minimum retail price of a 
 
 half gallon of milk, a six cent decrease in class 1 fat price, and a 94 
 
 2/ 
 
 cent decrease in the class 1 skim milk price— and (b) increases of the 
 same magnitude. Price changes of more or less than the equivalent of 
 five cents per half gallon would have approximately proportionate effects. 
 
 The results of the changes in fluid prices are summarized in Table 
 20. Based on the 1985 base model values, the changes in the control 
 variables amount to a 7.53 percent change in class 1 fat price, a 10.82 
 percent change in class 1 skim milk price, a 10.01 percent change in the 
 equivalent hundredweight price for class 1 milk, and a 6.26 percent change 
 in retail fluid milk price. These changes trigger significant changes 
 throughout the industry. The price decrease results in a slightly larger 
 percentage change because the lower prices result in a higher class 1 
 utilization; therefore, the class 1 changes affect a larger proportion 
 of the production. 
 
 The 1985 market milk price is altered by about forty cents per 
 hundredweight or six percent. The percent change declines gradually 
 from slightly over eight percent. The decline emanates from production 
 adjustments and an increasing base value with a constant change in class 
 1 prices. These price changes introduce a change in market milk produc- 
 tion in excess of four percent. Production adjustments are minor in the 
 first two years, increase quickly to almost five percent in the third and 
 fourth year, and are almost constant in absolute terms thereafter. 
 
 — See footnote 1, p. 93. 
 2/ 
 
 — Six cents per pound of fat times 3.5 is 21 cents which added to the 
 94 cents makes $1.15 which is the same as a five cent retail change 
 
 (5 times the 23 cent increment) . 
 
 100 
 
TABLE 20 
 
 Summary of Results from Simulation Run 3: Changes in Fluid Milk Prices 
 
 
 
 i\.C U lid. J- 
 
 Projected 1985 
 
 Value 
 
 Percent 
 
 Change 
 
 
 
 
 
 
 
 
 
 
 1973 
 
 Price 
 
 Base 
 
 Price 
 
 Price 
 
 Price 
 
 Endogenous variable 
 
 Units 
 
 amount 
 
 decrease 
 
 Model 
 
 increase 
 
 decrease 
 
 increase 
 
 Daily market milk production 
 
 cwt . 
 
 256281 
 
 288708 
 
 302407 
 
 314904 
 
 -4.53 
 
 4.13 
 
 Per capita consumption of class 
 1 fluid 
 
 lb. 
 
 274.84 
 
 261.00 
 
 259.64 
 
 258.28 
 
 0.52 
 
 -0.52 
 
 Percent of market milk utilized 
 in class 1 
 
 percent 
 
 61.15 
 
 60.34 
 
 57.31 
 
 54.75 
 
 5.29 
 
 -4.47 
 
 Fat available for products 
 
 thousand 
 cwt. 
 
 1833 
 
 2144 
 
 2329 
 
 2500 
 
 -7.94 
 
 7.34 
 
 Solids available for products 
 
 thousand 
 cwt . 
 
 3415 
 
 3496 
 
 3958 
 
 4384 
 
 -11.67 
 
 10.76 
 
 Per capita consumption of fats 
 and solids in products 
 
 lb. 
 
 23.39 
 
 21.25 
 
 21.57 
 
 21.90 
 
 -1.49 
 
 1.49 
 
 Market milk price 
 
 $/cwt. 
 
 6.50 
 
 9.06 
 
 9.65 
 
 10.18 
 
 -6.08 
 
 5.55 
 
The five percent change in utilization of market milk in class 1 
 products is particularly significant. This change and the opposite change 
 in production are reflected in an even larger adjustment in fat and solids 
 available for manufactured dairy products. This adjustment emanates 
 entirely from market milk production since manufacturing milk production 
 is unaffected. 
 
 Farm-level and retail product prices and values are virtually 
 unchanged; however, a slight adjustment in per capita consumption of fats 
 and solids in products occurs. The direction of the consumption adjust- 
 ment is the same as the price change since the adjustment emanates from 
 the substitutability of fluid milk and manufactured dairy products (see 
 Table 13). 
 
 As can be seen by the results in Table 20, changes in fluid milk 
 prices produce significant adjustments throughout the industry. In 
 addition, it should be noted that a less inelastic price elasticity for 
 fluid milk would increase the magnitude of these adjustments. Since the 
 true elasticity is at least as large as the almost insignificant value 
 in the sector model (see Table 12), the actual adjustments to changes in 
 class 1 prices should be at least as large as those in Table 20. 
 
 Effects of Changes in Regional Price Differences 
 
 Although the regional price differences in market milk price are 
 not under the direct control of the Bureau of Milk Stabilization, the 
 California Legislature is currently considering alternatives to the 
 current procedure for allocation of quota. Since the regional differences 
 stem largely from the unequal regional distribution of quota (see the 
 introductory section or Milligan [1975] for details of the current alloca- 
 tion procedure), the regional differences would be affected by any changes. 
 
 Recall that the regional differences are projected to decline 
 gradually throughout the simulated period (1 percent of initial value 
 each period in the base model) . The two alternatives simulated are (a) 
 an immediate elimination of the regional differences and (b) a linear 
 
 102 
 
decrease in the differences to attain elimination after four years.— 
 Since the only variables significantly affected are regional produc- 
 tion, the usual summary table is discarded in favor of Table 21, which 
 illustrates the regional adjustments over time. As would be expected, 
 the movement of production into the Central Valley (Southern San Joaquin 
 and Northern San Joaquin) is accelerated as the regional price differ- 
 ences are eliminated. 
 
 The elimination of the price differences also stimulates market 
 milk production slightly as margins increase in the Valley areas and 
 decrease in Southern California and the Coast region where production 
 is more price inelastic. This adjustment never reaches one percent 
 of production and falls to about a third of a percent by 1985. Subsequent 
 minor adjustments in utilization and fats and solids available for 
 products are also registered. Essentially no changes are registered 
 in statewide prices and per capita consumption. 
 
 Since the aggregate effect of the regional differences is not great, 
 the impact on the industry of changes in quota might appear to be minimal. 
 This is probably not true because the alternative proposals have a tremen- 
 dous impact on individual producers. Drastic changes, such as the first 
 alternative, would almost certainly result in transitional adjustments 
 not measured by the simulation model and could result in long run adjust- 
 ments in addition to those predicted by the model. In addition the 
 equity questions for individual producers must be carefully considered. 
 
 Discussion of the Effect of Price Changes 
 
 To facilitate the comparison of simulation runs 1-3, Table 22 
 summarizes the percentage changes resulting from general price changes, 
 product price changes, and fluid milk price changes. The price increases 
 are roughly similar: (1) a 5 percent general increase; (2) a 10 percent 
 
 - These alternatives are designed to approximate the effect of 
 (1) immediately allocating additional quota to bring all producers to 
 equalization and (2) achieving this goal over a four year period. The 
 achieving of quota equalization would not eliminate all regional price 
 differences. 
 
 103 
 
TABLE 21 
 
 Summary of Results from Simulation Run 4: The Effects on Regional Production of Changes 
 
 in the Regional Price Differences 
 
 Region and 
 Alternative 
 
 Actual 
 1973 
 
 Projected 
 1976 
 
 Projected 
 1979 
 
 Projected 
 1982 
 
 Projected 
 1985 
 
 Southern California 
 Base model 
 4 years 
 Immediate 
 
 34.83 
 
 (percent of total market milk production) 
 
 34.01 
 34.02 
 33.85 
 
 33.52 
 33.13 
 32.86 
 
 32.46 
 31.95 
 31.96 
 
 31.63 
 31.27 
 31.27 
 
 o 
 
 Southern San Joaquin 
 
 Base model 25.91 
 
 4 years 
 
 Immediate 
 
 Northern San Joaquin 
 
 Base model 27.24 
 
 4 years 
 
 Immediate 
 
 25.49 
 25.54 
 25.77 
 
 28.23 
 28.16 
 28.13 
 
 26.57 
 26.91 
 27.04 
 
 28.06 
 28.19 
 28.42 
 
 27.67 
 28.03 
 28.03 
 
 28.61 
 28.89 
 28.87 
 
 28.68 
 28.93 
 28.93 
 
 28.89 
 29.09 
 29.09 
 
 Coast 
 
 Base model 
 4 years 
 Immediate 
 
 10.90 
 
 11.31 
 11.34 
 11.37 
 
 11.05 
 11.07 
 11.04 
 
 10.56 
 10.56 
 10.56 
 
 10.22 
 10.22 
 10.22 
 
 Mountains 
 
 Base model 
 4 years 
 Immediate 
 
 1.12 
 
 0.96 
 0.94 
 0.88 
 
 0.81 
 0.70 
 0.65 
 
 0.70 
 0.58 
 0.58 
 
 0.58 
 0.49 
 0.49 
 
TABLE 22 
 
 A Comparison of the Effects of a General Price Change, a Change in Product Prices, 
 
 and a Change in Fluid Prices 
 
 
 
 
 
 Projected Chang 
 
 e in Percent from 1985 Base Amount 
 
 
 
 Actual 
 1973 
 
 Projected 
 1985 
 
 General 
 Price Change 
 
 Product 
 Price Change 
 
 Fluid 
 Price Change 
 
 Endogenous variable 
 
 Units 
 
 amount 
 
 amount 
 
 Decrease 
 
 increase 
 
 Decrease 
 
 Increase 
 
 Decrease 
 
 Increase 
 
 Daily market milk 
 production 
 
 cwt . 
 
 256281 
 
 302407 
 
 - 3.11 
 
 3.10 
 
 - 2.19 
 
 2.29 
 
 - 4.53 
 
 4.13 
 
 Daily manufacturing 
 milk production 
 
 cwt . 
 
 24089 
 
 14095 
 
 -69.60 
 
 72.26 
 
 -100.00 
 
 144.53 
 
 0 
 
 0 
 
 Manufacturing milk 
 price 
 
 $/cwt. 
 
 5.46 
 
 7.73 
 
 - 5.48 
 
 5.21 
 
 
 
 10.37 
 
 0 
 
 0 
 
 Per capita consumption 
 of class 1 fluid 
 
 lb. 
 
 274.84 
 
 259.64 
 
 0.23 
 
 - 0.23 
 
 0 
 
 0 
 
 0.52 
 
 - 0.52 
 
 Percent of market milk 
 utilized as class 1 
 
 % 
 
 61.15 
 
 57.31 
 
 3.44 
 
 - 3.23 
 
 1.85 
 
 - 1.87 
 
 5.29 
 
 - 4.47 
 
 Fat available for 
 products 
 
 thousand 
 cwt. 
 
 1833 
 
 2329 
 
 -10.69 
 
 10.91 
 
 - 10.88 
 
 14.60 
 
 - 7.94 
 
 7.34 
 
 Solids available for 
 products 
 
 thousand 
 cwt . 
 
 3415 
 
 3958 
 
 -15.59 
 
 15.92 
 
 - 15.87 
 
 22.39 
 
 -11.67 
 
 10.76 
 
 Average fat price 
 for products 
 
 $/lb. 
 
 0.73 
 
 0.75 
 
 - 4.58 
 
 4.64 
 
 - 9.44 
 
 9.21 
 
 0 
 
 0 
 
 Average solids price 
 for products 
 
 $/lb. 
 
 0.37 
 
 0.67 
 
 - 4.41 
 
 4.51 
 
 - 9.18 
 
 8.96 
 
 0 
 
 0 
 
 Retail value of fat 
 in products 
 
 $/lb. 
 
 1.91 
 
 1.97 
 
 - 2.93 
 
 2.96 
 
 - 6.02 
 
 5.89 
 
 0 
 
 0 
 
 Retail value of 
 solids in products 
 
 $/lb. 
 
 0.75 
 
 1.24 
 
 - 4.57 
 
 4.58 
 
 - 9.03 
 
 9.03 
 
 0 
 
 0 
 
 Per capita consumption 
 of fats and solids 
 in products 
 
 lb. 
 
 23.39 
 
 21.57 
 
 0.47 
 
 - 0.48 
 
 3.37 
 
 - 3.33 
 
 - 1.49 
 
 1.49 
 
 Market milk price 
 
 $/cwt. 
 
 6.50 
 
 9.65 
 
 - 4.59 
 
 4.58 
 
 - 3.42 
 
 3.60 
 
 - 6.08 
 
 5.55 
 
increase for 45 percent of the 1985 base model production (manufacturing 
 production and market production diverted to products) ; and (3) approx- 
 imately a 10 percent increase on 55 percent of the 1985 base model produc- 
 tion (market milk for fluid use) . 
 
 Since, in general, the prices for manufacturing milk and manufactured 
 dairy products are affected by Federal policies and national markets for 
 products while market milk prices, particularly fluid milk prices, are 
 affected by decisions made by the Bureau of Milk Stabilization, the 
 discussion focuses on market milk and fluid milk prices. Three items 
 are particularly noteworthy: (1) the importance of pricing decisions; 
 (2) the impact on producers and consumers of price changes; and (3) the 
 relevance of the law of comparative disadvantage. 
 
 Because of the extremely inelastic short run response in supply and 
 demand, price adjustments must be made with extreme caution. If an 
 adjustment over- or undershoots the mark, subsequent readjustments to 
 correct the original error may take years. Although one of the stated 
 criteria for setting milk prices is to maintain an adequate future supply 
 of milk, little consideration is given to long run implications during 
 the price-setting process. The correction of this deficiency could 
 significantly improve the pricing decisions made by the Bureau of Milk 
 Stabilization. 
 
 During debate over some issues concerning agriculture, producers 
 and consumers have aligned themselves using the argument that a healthy 
 producing sector is in the long run best interest of consumers. Such 
 harmony has not existed in the hearings for producer price adjustments; 
 in fact consumer groups have vigorously opposed recent producer proposals. 
 The results of the simulations suggest that this confrontation is to be 
 expected since producer and consumer interests appear to be in conflict 
 in both the short and long run. Because the market milk that is not 
 needed for fluid needs goes into manufactured dairy products where quantity 
 changes in California have little price impact, price increases result 
 in increased producer profits in both the short and long run. In no 
 simulation did the fluid demand come close to utilizing the available 
 supply of market milk. Since added production has little if any affect 
 
 106 
 
on retail prices for manufactured dairy products, the consumer has 
 virtually nothing to gain in the short or long run from price increases. 
 The confrontation between producers and consumers will undoubtedly 
 continue. 
 
 The final point for discussion concerns the advisability of 
 large scale production of milk for manufactured dairy products and 
 the relevance of the law of comparative advantage.—^ In the absence 
 of controls this economic relationship would determine the quantities 
 of milk produced in California for fluid and product uses. There is 
 little question that production to meet fluid and perishable product 
 needs — both actual and excess to meet daily and seasonal fluctuations — 
 should remain in California. The question of whether fertile, irrigated 
 land capable of growing specialty crops, cotton, tomatoes, etc., should 
 be used to grow roughage to be used to produce milk for butter, cheese, 
 etc. should be answered by the law of comparative advantage. 
 
 Unfortunately, the law of comparative advantage cannot operate 
 effectively under the present procedure for setting prices: prices 
 for products are administratively aligned with those prevailing 
 throughout the country and class 1 or fluid prices are then established 
 at a level that will result in the desired average market milk price. 
 Since all simulations provide adequate supplies of milk to meet fluid 
 demands, the decisions made regarding fluid milk prices will actually 
 determine the quantity of milk available for processing into products. 
 Consequently, explicit consideration of California's relative advantage 
 in production of milk for the storable products should be carefully 
 considered and the conclusions used in setting class 1 prices. 
 
 Policy-makers should consider the possibility of adopting a 
 pricing policy that would attempt to maintain production at a level 
 consistent with a pre-established target level for percent of market 
 milk utilized in class 1 products. The target level would be established 
 after considering comparative advantage, producer interests, and consumer 
 
 — ^The law of comparative advantage states that an enterprise will 
 be located in the region that has the largest relative economic advantage 
 or the least relative economic disadvantage in its production. 
 
 107 
 
interests. These simulation runs raise serious questions about a continua- 
 tion of the present pricing policy which encourages production of milk for 
 manufactured dairy products that probably should remain in the Great Lakes 
 and Northeast and which appears to favor producers at the expense of 
 consumers . 
 
 Simulation Runs with Altered Exogenous Variables 
 
 Three simulation runs (numbers 5-7) are executed to illustrate the 
 effects of exogenous variables on the California dairy industry. The 
 three runs trace the effects of changes in variable costs incurred by 
 producers, the population growth rate, and consumer tastes for fluid 
 milk. The format for the presentation of results is the same as in the 
 previous section. 
 
 Effects of Changes in Variable Costs of Producers 
 
 Simulation run 5 is devised to measure the effects on the California 
 dairy industry of exogenous changes in variable costs, most likely in 
 the form of altered feed costs. The effects are measured by simulating 
 (a) a five percent decrease in each of the regional variable cost and 
 corn price variable and (b) a five percent increase in the same variables. 
 Table 23 summarizes the effect of changes in production costs. 
 
 A comparison of the cost changes with the five percent price changes 
 (Table 22) indicates that market milk production adjustments are similar 
 but that manufacturing milk production adjustments to cost change are 
 significantly less than to price changes. The production adjustments 
 affected utilization of market milk and the quantity of fat and solids 
 available for products; however, consumption remained constant and prices 
 were unchanged with the exception of a very minor change in market milk 
 price due to the change in utilization. 
 
 108 
 
TABLE 23 
 
 Summary of Results from Simulation Run 5: Changes in Variable Costs of Producers 
 
 Endogenous variable 
 
 Units 
 
 A c t*na 1 
 
 t\ l_ LUaJ. 
 
 1973 
 amount 
 
 Projected 1985 
 
 values 
 
 Percent 
 
 change 
 
 Cost 
 decrease 
 
 Base 
 model 
 
 Cost 
 increase 
 
 Cost 
 decrease 
 
 Cost 
 increase 
 
 Daily market milk production 
 
 cwt. 
 
 256281 
 
 311097 
 
 302407 
 
 293749 
 
 2.87 
 
 -2.86 
 
 Percentage of production in 
 
 
 
 
 
 
 
 
 Southern California 
 
 % 
 
 34.83 
 
 31.42 
 
 31.63 
 
 31.85 
 
 -0.66 
 
 0.71 
 
 Q i f- V» q T*n Can Tr\an 1 1 ^ n 
 
 JUU Hit— L LI iJall kJ Uclv^UXll 
 
 7 
 
 /o 
 
 25 91 
 
 28.92 
 
 28.68 
 
 
 0 8ii 
 
 
 Northern San Joaquin 
 
 % 
 
 27.24 
 
 29.23 
 
 28.89 
 
 28.53 
 
 1.18 
 
 -1.24 
 
 Coast 
 
 % 
 
 10.90 
 
 9.73 
 
 10.22 
 
 10.74 
 
 -4.79 
 
 5.10 
 
 Mountains 
 
 % 
 
 1.12 
 
 0.71 
 
 0.58 
 
 0.45 
 
 22.41 
 
 -23.18 
 
 Dailymanuf acturing milk production 
 
 cwt. 
 
 24089 
 
 15023 
 
 14095 
 
 13168 
 
 6.58 
 
 -6.58 
 
 Percent of market milk utilized 
 
 % 
 
 61.15 
 
 55.71 
 
 57.31 
 
 59.00 
 
 -2.79 
 
 2.94 
 
 in class 1 
 
 
 
 
 
 
 
 
 Fat available for products 
 
 thousand 
 
 1833 
 
 2454 
 
 2329 
 
 2207 
 
 5.27 
 
 -5.26 
 
 
 cwt . 
 
 
 
 
 
 
 
 Solids available for products 
 
 thousand 
 
 3415 
 
 4262 
 
 3958 
 
 3657 
 
 7.65 
 
 -7.62 
 
 
 cwt . 
 
 
 
 
 
 
 
 Market milk price 
 
 $/cwt. 
 
 6.50 
 
 9.61 
 
 9.65 
 
 9.68 
 
 -0.35 
 
 0.37 
 
Effects of Changes in Population Growth Rate 
 
 The California Department of Finance [1974a] has released four 
 alternative population projections for California. The baseline projec- 
 tion is specified in the base model. In simulation run 6 (a) the low 
 alternative (series E-0, population of 22,575,000 on July 1, 1985) and 
 (b) the high alternative (series C-150, population of 25,159,000 on 
 July 1, 1985) are linearized and the effects compared to the baseline 
 population projections (24,363,000 on July 1, 1985). Table 24 summarizes 
 the results. 
 
 The primary impact of population growth is on the utilization of the 
 market milk production. The greater the increase in population growth, 
 the larger the consumption of fluid products, and the smaller the quantity 
 of fats and solids available for products. Since this improved utiliza- 
 tion of market milk increases market milk price slightly, production is 
 also increased by a very small amount. 
 
 The impact of population change is felt gradually because the 
 population time paths deviate only slightly at first. The percent 
 changes of the variables in Table 24, gradually increase through the 
 time period, and reach a maximum in 1985. This gradual change is not 
 exhibited by any of the previously considered changes. 
 
 Effects of Changes in Consumer Tastes for Fluid Milk 
 
 As evidenced by the strong negative time trend in the equations 
 for fluid fat and skim milk (see Equations B.24 and B.25, page 71), 
 consumer tastes have been turning from milk to other beverages. The 
 future course of this trend has important implications for the California 
 dairy industry. In the base model the downward trend in consumer tastes 
 for fluid milk is projected to continue. In simulation run 7 the effects 
 of (a) a gradual reduction in downward trend of tastes-'' and (b) a 
 
 — The gradual reduction is simulated by taking the square root of 
 the portion of the time trend occurring during the simulation period. 
 
 110 
 
TABLE 24 
 
 Summary of Results from Simulation Run 6: Changes in Population Growth Rate 
 
 
 
 Actual 
 
 Projected 1985 
 
 values 
 
 Percent 
 
 change 
 
 Endogenous variable 
 
 Units 
 
 amount 
 
 Slower 
 growth 
 
 Base 
 model 
 
 r datcl 
 
 growth 
 
 jiower 
 growth 
 
 Faster 
 growth 
 
 Daily market milk production 
 
 cwt. 
 
 256281 
 
 301142 
 
 302407 
 
 303031 
 
 -0.42 
 
 0.21 
 
 Percent of market milk utilized 
 in class 1 
 
 percent 
 
 61.15 
 
 53.76 
 
 57.31 
 
 59.06 
 
 -6.19 
 
 3.05 
 
 Fat available for products 
 
 thousand 
 cwt. 
 
 1833 
 
 2426 
 
 2329 
 
 2282 
 
 4.16 
 
 -2.03 
 
 Solids available for products 
 
 thousand 
 cwt. 
 
 3415 
 
 4315 
 
 3958 
 
 3782 
 
 9.02 
 
 -4.44 
 
 Market milk price 
 
 $/cwt. 
 
 6.50 
 
 9.57 
 
 9.65 
 
 9.69 
 
 -0.77 
 
 0.38 
 
leveling off of tastes at 1973 levels are simulated. The results are 
 summarized in Table 25. 
 
 As with the population changes simulation, the effects of changing 
 consumer tastes are manifested primarily in the utilization of market 
 milk. The change in utilization is caused by increased per capita 
 consumption rather than by population growth. Again, changes occur 
 gradually over time. 
 
 Discussion of Simulation Runs 
 
 The increase in market milk production and decrease in fluid utiliza- 
 tion characterize all simulation runs. Table 26 summarizes the results 
 of all simulation runs except regional differences for the alternative that 
 is most favorable to dairymen. The other alternative would produce the 
 opposite result in all instances, except changes in consumer tastes. As 
 can be seen from this table, market milk price has the greatest impact on 
 production while market milk price and the exogenous factors affecting 
 demand have large impacts on the percent of market milk utilized as class 1. 
 The implications for pricing policy were discussed following the price 
 changes (simulation runs 1-4); in this section other impacts of the increased 
 production are discussed. 
 
 The most important question is how will the additional capacity at 
 all levels be acquired. At the producer level the additional capacity 
 will come primarily from continued expansion of presently operating herds. 
 
 The more interesting question concerns processing the increased 
 quantities of fats and solids available for manufactured dairy products 
 for which new processing plants will probably be required. Since cheese 
 production is presently minor in California and since cheese producers 
 are interested in building in California because of relatively high levels 
 of solids, the potential for increased production of cheese is good. 
 
 112 
 
TABLE 25 
 
 Summary of Results from 
 
 Simulation 
 
 Run 7: 
 
 Changes 
 
 in Consumer Tastes 
 
 for Fluid 
 
 Milk 
 
 
 
 Actual 
 
 1973 
 amount 
 
 Projected 1985 
 
 values 
 
 Percent 
 
 change 
 
 Endogenous variable 
 
 Units 
 
 Base 
 model 
 
 Gradual 
 decrease 
 
 Constant 
 tastes 
 
 Gradual 
 decrease 
 
 Constant 
 tastes 
 
 Daily market milk production 
 
 cwt . 
 
 256281 
 
 3L)2407 
 
 303217 
 
 303350 
 
 0.27 
 
 0.31 
 
 Per capita consumption of 
 class 1 fluid 
 
 lb. 
 
 274.84 
 
 259.64 
 
 273.50 
 
 275.39 
 
 5.34 
 
 6.07 
 
 Percent of market milk utilized % 
 in class 1 
 
 61.15 
 
 57.31 
 
 60.21 
 
 60.60 
 
 5.06 
 
 5.73 
 
 Fat available for products 
 
 thousand 
 cwt . 
 
 1833 
 
 2329 
 
 1988 
 
 1942 
 
 -14.66 
 
 -16.65 
 
 Solids available for products 
 
 thousand 
 cwt . 
 
 3415 
 
 3958 
 
 3664 
 
 3625 
 
 -7.45 
 
 -8.44 
 
 Market milk price 
 
 $/cwt. 
 
 6.50 
 
 9.65 
 
 9.70 
 
 9.70 
 
 0.52 
 
 0.59 
 
TABLE 26 
 
 Summary of the Effects of Changes in Selected Control and Exogenous Variables 
 
 Endogenous variables 
 
 Percent change from the 1985 base value resulting from a 
 
 5 percent 
 increase 
 in milk 
 prices 
 
 10 percent 
 
 increase 
 in product 
 prices 
 
 5 cent 
 per half 
 
 gallon 
 increase 
 in fluid 
 
 prices 
 
 5 percent 
 decrease 
 in 
 
 variable 
 costs 
 
 Increased 
 population 
 growth 
 rate 
 
 Leveling 
 
 off of 
 downward 
 trend in 
 fluid milk 
 consumption 
 
 Daily market milk 3.10 
 production 
 
 Per capita consumption -0.23 
 of fluid milk 
 
 Percent of market milk -3.23 
 utilized as class 1 
 
 Market milk price 4.58 
 
 2.29 
 _jj 
 
 -1.87 
 3.60 
 
 4.13 
 
 -0.52 
 
 -4.47 
 
 5.55 
 
 2.87 
 
 0.21 
 
 -2.79 
 
 -0.35 
 
 3.05 
 
 0.38 
 
 0.31 
 
 6.07 
 
 5.73 
 
 0.59 
 
 a/ 
 
 — Value is close to zero. 
 
SUMMARY AND CONCLUSIONS 
 
 Milk price increases necessitated by increases in recent years in 
 feed and other costs incurred by dairymen have focused the attention of 
 producers and consumers in California on the important role of the State 
 of California in establishing milk prices. To provide additional economic 
 input into the procedure employed to establish producer prices, an 
 econometric model of the California dairy industry using bimonthly 
 observations for 1958-1973 was developed. This model was used to 
 simulate the effects of changes in price and other key variables. 
 
 Six supply response functions were estimated in the producer 
 subsector: five regional equations for market milk and one statewide 
 equation for manufacturing milk. Returns to producers were introduced 
 by separate variables for average short-run margin per cow for each of 
 the last four years. The results exhibited minimal short-run response 
 to margin per cow. The overall price response was inelastic in the four 
 regions where most dairies are large and specialized; in the remaining 
 two equations, where most producers are smaller and more diversified, 
 an elastic response was indicated. Significant responses were also 
 found for variables reflecting the opportunity cost of the dairyman's 
 capital and labor, for dummy variables for seasonality of production, 
 and for proxy variables for improvements in management, technology, 
 and genetic ability. 
 
 In the consumer subsector demand equations were estimated for 
 fluid and manufactured dairy products. All equations were characterized 
 by inelastic responses to price and income; the demand for fluid products 
 was more inelastic with little significance in the coefficients. Fluid 
 consumption is affected significantly by other factors including 
 seasonality, a downward trend in consumption, and a proxy variable for 
 consumers' concern over the cholesterol content of milk. The demand 
 for fats and solids in products was also characterized by seasonality 
 and by a downward trend in consumption. 
 
 115 
 
Due to the control exerted by the State of California, most of the 
 relationships in the processor subsector are identities; behavioral 
 equations were estimated for manufacturing milk price in California and 
 marketing margin equations for milkfat and solids-not-fat in manufactured 
 dairy products. The manufactured milk price was found to be very closely 
 aligned with the controlled price for market milk used in manufactured 
 dairy products. The margin equations exhibited a combination of absolute 
 and percentage markups, a significant response to increased labor costs, 
 and a ceteris paribus decrease in margin over time . 
 
 Simulation runs indicate that increases in the supply of milk will 
 exceed any increases in fluid demand for the foreseeable future. All 
 simulation runs predicted rather large increases in market milk production, 
 decreases in the percentage of market milk utilized as class 1, and 
 increases in fats and solids available for products. Changes in key 
 variables including prices paid producers for milk, variable costs incurred 
 by producers, population growth rates, and consumer tastes for fluid milk 
 indicated that the proportion of market milk used for fluid products and 
 the quantity of milkfat and solids-not-fat available for manufactured 
 dairy products are particularly sensitive to all changes. The simulation 
 results indicate that recent price increases are sufficient to maintain 
 adequate supplies of fluid milk and that requests for additional increases 
 should be thoroughly investigated. 
 
 Although little problem is anticipated in expanding capacity to 
 handle the increased production, two issues should be addressed by policy- 
 makers who set the prices that could result in the increase. The first 
 issue is whether milk production for use in storable (and transportable) 
 dairy products should be expanded in California where the land required 
 for roughage could be used for specialty crops, etc. The second issue 
 is that with the adequate supply of milk and inelastic demand, price 
 increases are almost totally passed on to consumers. 
 
 Future research related to this model could be centered in three 
 areas. The first is to refine the estimates in the structural model 
 particularly the short-run supply response to price and the demand for 
 
 116 
 
dairy products. The simulation model itself could be altered so 
 that a policy maker could specify the desired producer margin or 
 production, and the model would determine the price levels required 
 to meet the desired goal. A third and less directly related issue 
 would be an analysis of the comparative advantage question relative 
 to storable products. 
 
 117 
 
APPENDIX A. DATA SOURCES 
 
 In this appendix the sources of all data utilized are indicated 
 and any transformations performed on the original data are outlined. 
 Unless noted otherwise, the data are for 1958-1973. The data required 
 for the producer subsector are discussed first. Most bimonthly prices 
 are simple or weighted averages of monthly prices. 
 
 Data for the Producer Subsector 
 
 Since supply functions for market milk, are estimated for five 
 regions of the state, a j subscript indicates the data are collected 
 for each of the five regions. The five regions are: 
 
 1. Southern California 
 
 2 . Southern San Joaquin Valley 
 
 3. Northern San Joaquin and Sacramento Valleys 
 
 4. Central Coast 
 
 5. Mountain Areas and North Coast 
 
 The map in Figure 2, page 8, shows the location of the five regions. 
 
 Quantity Produced 
 
 q : Designation - Production of market milk. 
 
 Source - California Crop and Livestock Reporting Service [1959 
 
 1974], Table 7, 1958-1960; Table 8, 1961-1973. 
 Transformations - Summation of monthly production. 
 
 q : Designation - Production of market milk in region j. 
 
 J A 
 Source - Same as q . 
 
 Transformation - Summation of monthly production in counties 
 in region j . 
 
 q : Designation - Production of manufacturing milk. 
 
 Source - California Crop and Livestock Reporting Service [1959 
 1974], Table 8, 1958-1960; Table 9, 1961-1973. 
 
 119 
 
Prices Received by Producers 
 
 p : Designation - Average price paid for market milk in California. 
 
 Source - California Crop and Livestock Reporting Service [1959- 
 
 1974], Table 15, 1961; Table 14, 1973. 
 Transformations - Weight monthly prices by market milk production. 
 
 p. : Designation - Average price paid for market milk in region j. 
 J a 
 
 Source - Same as p and Agricultural Commissioner Annual Report 
 
 [1958-1974] . 
 
 Transformations - The prices received by market milk producers 
 
 in the counties in the regions are weighted 
 by county production to give a regional yearly 
 price. The bimonthly prices are arrived at by 
 incorporating the yearly trend of the state 
 price into the regional annual price. These 
 prices are then refined so that the regional 
 prices are consistent with the state average 
 price. 
 
 p : Designation - Average price paid for manufacturing milk. 
 
 Source - California Crop and Livestock Reporting Service [1959- 
 
 1974], Table 16, 1961; Table 15, 1973. 
 Transformations - Weight monthly prices by manufacturing milk 
 
 production. 
 
 Standard Cost of Production Data^ 
 
 set : Designation - Average feed cost per hundredweight in region j . 
 
 Source - California Bureau of Milk Stabilization [First quarter 
 
 1958— Nov. -Dec. 1974]. 
 Transformations - Average of cost regions in region j weighted 
 
 by production in each cost region. 
 
 — ^The standard cost of production data are taken from surveys conducted 
 by the Bureau of Milk Stabilization. Although the surveys are not conducted 
 on a random basis, they are considered to be representative. The aggrega- 
 tion of these regions into the five used in this study is detailed in 
 Milligan [1975a]. 
 
 120 
 
set"'" : Designation - Average feed cost per hundredweight for market 
 
 milk producers. 
 
 Source - Same as sct\ 
 
 J 
 
 Transformations - Average of five regions weighted by produc- 
 tion in each region. 
 
 Note: For the remainder of this subsection the source and transforma- 
 tions are the same as above. 
 
 2 
 
 sctj : Designation - Average labor cost per hundredweight in region j 
 
 2 
 
 set : Designation - Average labor cost per hundredweight for market 
 
 milk producers. 
 
 3 1/ 
 sct^ : Designation - Average miscellaneous cost per hundredweight— 
 
 in region j . 
 
 3 1/ 
 set : Designation - Average miscellaneous cost per hundredweight— 
 
 for market milk producers. 
 PPC^ : Designation - Average production per cow in region j . 
 
 Other Data 
 BF 
 
 p : Designation - Average price received by California beef producers 
 
 (dollars per cwt.) 
 Source - California Crop and Livestock Reporting Service [1960b], 
 Table 41, 1958; California Crop and Livestock Reporting 
 Service [1970b], 1959-1969; and California Crop and 
 Livestock Reporting Service [ 1970c-1975c] , 1970-1975. 
 Transformations - Simple average of the two months in the 
 
 bimonthly period. 
 
 p>C0RN : Designation - Average price received per hundredweight by 
 
 California corn growers. 
 
 — This miscellaneous cost is not the miscellaneous cost in the 
 survey. It is taxes and insurance + operating costs + marketing costs - 
 miscellaneous income. 
 
 121 
 
Source - California Crop and Livestock Reporting Service [1960b], 
 Table 2, 1958; California Crop and Livestock Reporting 
 Service [1970b], 1959-1969; and California Crop and 
 Livestock Reporting Service [ 1970c-1975c] , 1970-1975. 
 
 Transformations - Simple averages. 
 
 Designation - Index of average farm real estate value per acre, 
 
 California (1967=100). 
 Source - United States Department of Agriculture [1973b], page 11, 
 1958-1972; and United States Department of Agriculture 
 [1974b], Table 1, 1973. 
 Transformations - March index is used for first three bimonthly 
 periods and November index for the last three 
 of each year. 
 
 Designation - Bank interest rates on short-term business loans. 
 
 Source - An item titled "Finance-Banking, Money and Interest 
 
 Rates, Bank Rates on Short-Term Business Loans, (a) in 
 19 cities (1958-1966), (b) in 35 centers (1967-1973)" 
 in United States Department of Commerce [1959-1973, 
 biennial], 1958-1972; and United States Department of 
 Commerce [1973a-1975a] , 1973-1975. 
 
 Transformations - Quarterly data converted to bimonthly with 
 
 bimonthly observations 1, 3, 4, 6 corresponding to the 
 quarters, observation 2 is the average of quarters 1 
 and 2, observation 5 of quarters 3 and 4. 
 
 Designation - Percentage of cows on DHI test. 
 
 Source - California Crop and Livestock Reporting Service [1959- 
 1974], Table 1 and University of California [1974]. 
 
 Transformations - Divide average number of cows on test by 
 
 estimated number of cows in the state. Percent- 
 age serves for the six bimonthly observations 
 for the year. 
 
 122 
 
Data for the Processor and Consumer Subsectors 
 
 In this section the sources of the data used in the specification 
 of the processor and consumer subsectors are indicated. The data 
 
 series are statewide and begin in 1958. The variable production per 
 
 1 B 
 cow (PPC ) and price received for manufacturing milk (p ) are not 
 
 described below since they appear in the previous section. 
 Control Variables 
 
 C1FP : Designation - Average price per pound processors paid producers 
 
 for fat used in class 1 products. 
 Source - California Crop and Livestock Reporting Service [1959- 
 1974], Table 26, 1958; Table 25, 1959-60; Table 21, 
 1961-72; Table 20, 1973; California Crop and Livestock 
 Reporting Service [ 1958a- 1969a] , Table (inside back 
 
 cover) titled: "Minimum Class 1 Prices as of ", 
 
 California Crop and Livestock Reporting Service [1969a- 
 1974a], table titled, "Monthly Statistical Summary of 
 California Milk Pool Data", and California Bureau of 
 Milk Pooling [1974a]. 
 Transformations - To obtain bimonthly observations prior to 
 
 July 1969, the price paid for fat in each 
 marketing region (California Crop and Livestock 
 Reporting Service [1958a-1969a]) is weighted 
 by the class 1 sales of fat in each marketing 
 region (California Crop and Livestock Reporting 
 Service [1959-1970]). To calculate the series 
 after July' 1969, the monthly class 1 pool 
 price for fat (California Bureau of Milk Pooling 
 [1974a]) is weighted by the utilization in the 
 two months (California Crop and Livestock 
 Reporting Service [19693-19743]).-^ 
 
 — ^Due to the changes instituted in July 1969 with the implementation 
 of statewide milk pooling, each procedure correctly calculates the price. 
 
 123 
 
C1SP : Designation - Average price per hundredweight processors paid 
 
 producers for skim milk used in class 1 products. 
 Source - All of the sources listed for C1FP plus California Crop 
 and Livestock Reporting Service [1959-1974], Table 36, 
 1958-1960; Table 24, 1961-72; Table 23, 1973 and Cali- 
 fornia Bureau of Milk Pooling [1971-1974]. 
 Transformations - To obtain bimonthly observations prior to 
 
 July 1969, the price paid for skim milk in 
 each marketing region (California Crop and 
 Livestock Reporting Service [1958a-1974a] ) is 
 weighted by the class 1 sales of fluid milk 
 minus class 1 sales of fat in each region 
 (California Crop and Livestock Reporting 
 Service [1959-1974]). To complete the data 
 series, the price of skim milk in each month 
 is derived from the price of class 1 solids 
 (California Bureau of Milk Pooling [1974a]) 
 using the percentage solids in skim milk 
 (California Bureau of Milk Pooling [1971-1974]).- 
 The monthly price is then weighted by the 
 quantity of solids sold as class 1 (California 
 Crop and Livestock Reporting Service [1969a- 
 1974a]). 
 
 RFLP : Designation - Average minimum retail price for a half gallon of 
 
 milk. 
 
 Source - California Crop and Livestock Reporting Service [1959- 
 1974], Table 36, 1958-60; Table 24, 1961-72; Table 23, 
 1973 and California Crop and Livestock Reporting Service 
 [1969a-1974a] , Table (inside back cover) titled: "Minimum 
 Class 1 Prices as of ". 
 
 ~~ The formula pet. solids = .444 x pet. fat + 7.07 was used for 
 July 1969-December 1970 observations. 
 
 124 
 
Transformations - Retail price of a half gallon of milk in 
 
 each marketing region weighted by the class 1 
 sales in that region.—^ 
 
 PFP : Designation - Average price paid by processors for market milk 
 
 fat used in manufactured dairy products (classes 
 
 2, 3, and 4) . 
 
 Source - California Bureau of Milk Stabilization [ 1958a-1969a] , 
 California Crop and Livestock Reporting Service [1969a- 
 1974a], and California Bureau of Milk Pooling [1974a]. 
 Transformations - To obtain observations since 1969, the average 
 
 price of fat in each class (California Bureau 
 of Milk Pooling [1974a] is weighted by the 
 utilization in each class (California Crop 
 and Livestock Reporting Service [1969a-1974a] ) 
 For observations prior to July 1969 neither 
 an average statewide price for class 2 and 3 
 fat (class 4 was not created until July 1969) 
 nor the utilization in each class was compiled 
 In this absence the price for class 2 and 
 class 3 fat sold in the Central Valley was 
 combined in a manner consistent with utiliza- 
 tion after July 1969. 
 
 PSP : Designation - Average price paid by processors for market solids 
 
 used in manufactured dairy products (classes 2, 
 
 3, and 4) . 
 Source - Same as PFP. 
 
 Transformations - Same as PFP using solids. Prior to July 1969 
 
 skim milk price was converted to a price for 
 solids . 
 
 — This price series is not precise price measure since not all 
 fluid milk is sold as half gallons of milk nor is all milk sold at the 
 minimum price; however, the series is representative of retail class 
 1 prices. 
 
 125 
 
Endogenous Variables 
 
 PCF : Designation - Percentage fat in milk produced in California. 
 
 Source - California Crop and Livestock Reporting Service [1959- 
 1974], Table 6 and 9, 1958-61; Tables 7 and 10, 1962- 
 1973. 
 
 Transformations - Division of total fat production by total 
 milk production. 
 
 PCS : Designation - Percentage solids-not-fat in milk produced in 
 
 California. 
 
 Source - California Bureau of Milk Pooling [1974b]. 
 
 Transformations - The percentage solids is derived from the 
 
 percentage fat by a formula, referred to by 
 Bureau personnel as "Dr. Jack's Formula", 
 
 PCS = 7.07 + .444 x PCF 
 
 Note: The sources and transformations for the following four variables 
 are included in one description following the designation of the 
 four variables. 
 
 RFP : Designation - Retail price of the milkfat purchased in manufac- 
 tured dairy products. 
 RSP : Designation - Retail price of the solids-not-fat purchased in 
 
 manufactured dairy products. 
 RFQM : Designation - Per capita quantity of fat purchased in manufac- 
 tured dairy products. 
 RSQM : Designation - Per capita quantity of solids purchased in manufac- 
 tured dairy products. 
 Source - United States Department of Labor [1958-1974], California 
 Crop and Livestock Reporting Service [1974], Table 66, 
 Hiemstra [1968], Table 11, United States Department of 
 Agriculture [1974], Table 11, United States Department 
 of Agriculture [1973c], Table 4 and 5, pages 10-13, 
 Fallert [1973a], and United States Department of Agricul- 
 ture [1959d-1974d] . 
 
 126 
 
Transformations - Since manufactured dairy products are not 
 
 purchased as fats and solids, the retail 
 
 value of the fats and solids must be derived 
 
 from the retail prices and quantities of the 
 
 various manufactured dairy products, the 
 
 proportions of fats and solids in these 
 
 products, and the price paid (to the producer) 
 
 for fat and solids by the processor. Estimated 
 
 monthly prices for evaporated milk, ice cream, 
 
 American Processed cheese, and butter in San 
 
 Francisco and Los Angeles are available (U. S. 
 
 Department of Labor [1958-1974]). The yearly 
 
 per capita consumption of buttermilk, ice 
 
 cream, and cottage cheese is calculated for 
 
 California (California Crop and Livestock 
 
 Reporting Service [1974]) and national averages 
 
 are obtainable for the remaining manufactured 
 
 dairy products (Hiemstra [1968] and United 
 
 States Department of Agriculture [1974]). The 
 
 yearly per capita consumption is separated 
 
 into the six bimonthly periods according to 
 
 seasonal consumption in the Western U. S. 
 
 (U. S. Department of Agriculture [1973c]).— ^ 
 
 The total quantity of fats and solids purchased 
 
 in manufactured dairy products is calculated by 
 
 multiplying the proportion of fat and solids 
 
 2/ 
 
 (Fallert [1973a]),- the per capita yearly 
 consumption, and the proportion consumed in 
 the appropriate bimonthly period. The retail 
 
 — The data in the survey are reported by quarters. These quarters 
 are converted to bimonthly periods as follows: bimonthly periods 1, 3, 
 4, and 6 come directly from the quarters, bimonthly period 2 is the 
 average of quarters 1 and 2, and bimonthly period 5 is the average of 
 quarters 3 and 4. The consumption in these periods is then converted 
 to the proportion of the yearly consumption in each period. 
 
 2/ 
 
 — In addition to the information in Fallert [1973a], the ratio of 
 ice cream mix to ice cream was required (U. S. Department of Agriculture 
 [1959d-1974d]) . 
 
 127 
 
prices of fat and solids in the four products 
 for which prices are available are derived by 
 dividing the retail price per pound of the 
 product (the simple average of the price in San 
 Francisco and Los Angeles in each of the two 
 months adjusted to one pound) by the value of 
 the fats and solids included in the product 
 (proportion fatxAPF + proportion solids x APS). 
 This markup constant is then multiplied by APF 
 and APS to obtain a retail value of fat and solids 
 in each of the four products. These four prices 
 are then weighted by the quantity of fats and 
 solids consumed in products similar to the four 
 possessing retail prices.— 
 
 RFQF : Designation - Per capita quantity of fat processed and sold in 
 
 fluid (class 1) products. 
 Source - California Crop and Livestock Reporting Service [1959- 
 1974], Table 26, 1958; Table 25, 1959-60; Table 21, 
 1961-72; Table 20, 1973. 
 Transformations - The total quantity of fat sold in class 1 products 
 
 in the two month period is divided by the estimated 
 population (POP) . 
 
 SD : Designation - Support price, cents per pound, for nonfat dairy 
 
 milk, extra grade, spray. 
 Source - United States Department of Agriculture [1968f ] , Table 
 84, p. 102, and United States Department of Agriculture 
 [1974h], Table 5, p. 11. 
 Transformations - Use price prevailing during bimonthly period. 
 
 When the support level changes during the period, 
 the prices were weighted by the days each price 
 prevailed. 
 
 — ^The price of fats and solids in evaporated milk is weighted by the 
 quantity of fats and solids in evaporated whole milk, evaporated and condensed 
 skim milk, condensed whole milk — sweetened, condensed whole milk — unsweetened, 
 nonfat dry milk, dry whole milk, dry buttermilk, dry whey and malted milk; 
 ice cream is weighted by buttermilk, ice cream, ice milk, sherbert, imitation 
 ice cream, and imitation ice milk; American processed cheese is weighted by 
 
 cottage cheese, low fat cottage cheese, American cheese, and other cheese; 
 and butter is weighted by butter. 
 
 128 
 
XMCH : Designation - Average hourly earnings of production and related 
 
 workers in manufacturing, dairy products. 
 Source - California Department of Industrial Relations [1959- 
 1971], California Department of Human Resources 
 Development [1972], and California Employment Develop- 
 ment Department, [1973-74]. 
 Transformations - Simple average of the earnings in the two 
 
 months . 
 
 Y : Designation - Per capita personal income in the U. S. at a 
 
 seasonally adjusted annual rate. 
 Source - United States Department of Commerce [1973], "Personal 
 Income, Total", p. 206, and "Population, U. S. Total", 
 p. 240, and United States Department of Commerce 
 [ 1973a-1974a] , items titled "General Business Indicators 
 Monthly Series, Seasonally Adjusted, at Annual Rate, 
 Total Personal Income" and "Labor Force, Employment 
 and Earnings, Population of the United States, Total, 
 Including Armed Forces Overseas". 
 Transformations - Average total personal income for the two 
 
 months divided by the average population. 
 POP : Designation - Estimated total population of California. 
 
 Source - California Department of Finance [1959-1974], Table 
 titled: "Estimated Total and Civilian Population 
 of California, Total Population (July 1)". 
 Transformations - The bimonthly populations are derived by 
 
 assuming the change from July 1 to the 
 following July 1 is linear. 
 AD : Designation - Proportion of the California population enrolled 
 
 in kindergarten through grade eight. 
 Source - California Department of Finance [1959-1974], Table 
 titled: "Estimated and Projected Enrollment in 
 Kindergarten and Grades 1-12, California Public Schools, 
 Kindergarten through Grade Eight". 
 
 129 
 
Transformations - Enrollment divided by population serves for 
 
 six bimonthly periods. 
 XIMIT: Designation - Per capita consumption of imitation dairy products. 
 
 Source - California Crop and Livestock Reporting Service [1959- 
 1974] . 
 
 Transformations - Percentage of class 1 sales from California 
 
 Crop and Livestock Reporting Service [1959- 
 1974] times per capita consumption of class 1 
 products . 
 
 130 
 
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