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V . ....|.l\$Lr. . \ V x I?! .5 I .Ilvllvbt,Ev.L...: III. . . . ii... z , . k: Mir... . .iK. - “FEE lufiialyr ll.‘ .2 nth. .\ $45-- :.........5.F..«Pinwgmrimflmm‘wfifi . 3 1293 10067 3825 T// n‘: «‘1‘ 1’. . ‘2 T/Ai - .V 4___"/ .mflls LI ‘33 I ~‘3 "' w 3"" 43 4'2. (i ‘ _ V5. P515 1' ‘ A “ ‘3‘ 11‘1”) 3‘ ‘. Vt-ysfi‘ 1 .nb.i‘alfu 11,-}; Q’I-f__".'~*) V-) ‘ W’ U nivcm fay ' I -.’ m. . ‘w‘~'v.r‘ This is to certify that the thesis entitled AN ECONOMETRIC ANALYSIS OF THE BEEF-CATTLE INDUSTRY OF URUGUAY presented by Luis O. Coirolo has been accepted towards fulfillment of the requirements for Ph.D. degree in Agricultural Economics WWK/%EZ¢Z/ Major professor Date January 4, 1979 0-7 639 OVERDUE FINES: 25¢ per day per it. RETURNIIG LIBRARY MATERIALS: Place in book return to renov 2 charge fro. circulation records . -v __4 T‘M"'fifi“ii.fi.mm v-rr-w-v-WV‘w—j AN ECONOMETRIC ANALYSIS OF THE BEEF-CATTLE INDUSTRY OF URUGUAY By Luis O. Coirolo A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Department of Agricultural Economics 1979 ABSTRACT AN ECONOMETRIC ANALYSIS OF THE BEEF-CATTLE INDUSTRY OF URUGUAY By Luis O. Coirolo Beef production has always been and still is a keystone in the Uruguayan economy. During the last thirty years, Uruguay has experienced a slowdown in the growth rate of the cattle sector. Research is needed to find means of accelerating growth in the cattle industry in order to continue economic growth at the national level. Substantial government intervention in the beef-cattle industry of Uruguay exists. This study provides descriptive and quantitative information which might help in the improvement of public policy decisions, particularly in the area of beef-cattle supply. However, domestic beef consumption and beef exports were also analyzed. The objectives of the study were: l. To obtain descriptive knowledge of the dynamics of the beef- cattle economy 2. To identify and quantify the effect of the most important factors affecting the beef-cattle economy 3. To model econometrically the structure of the Uruguayan beef— cattle industry, in particular, to investigate the critical relation- ships affecting (a) the number of cattle supplied, (b) the meat yield per animal slaughtered, (c) the amount of beef internally consumed, Luis 0. Coirolo (d) the amount of beef available for exports, and (e) the investments required to increase beef production The study was based on annual time-series data, and ordinary least squares was the statistical procedure used. For the estimation of the supply of cattle for slaughter, a polynomial distributed lag model was developed. The main conclusions of the study were as follows: 1. The most important variables affecting the number of cattle supplied for slaughter were the farmers' beef price, particularly when lagged one year, the number of hectares of improved pasture in produc- tion, and the weather. The effect of beef prices on beef-cattle supply for slaughter is negative for two years and positive for the next four years. The number of hectares of improved pasture is positively related to the supply of cattle; and the weather, expressed in terms of an index of pasture conditions, has a negative influence on the number of cattle supplied in the short run, since better weather conditions allow for the finishing of cattle that could otherwise have been sold before fattening. 2. The meat yield per animal slaughtered is positively related to weather conditions as they affect pasture conditions and negatively related to the slaughter extraction rate. Both variables are related to the availability of roughage. In Uruguay, raising and fattening cattle is done by direct grazing, and it appears that, in Uruguay, the extraction rate more than a productivity index has been an indication of lack of sufficient roughage to get all the supplied animals to the finished stage. Luis O. Coirolo 3. The only exogenous variable with a statistically significant parameter affecting domestic beef consumption was found to be the retail price of beef, which is controlled by the government. The price of beef substitutes and the income level parameters were not statistically different from zero. The level of beef consumption is very high in Uruguay; in addition, practically no beef substitutes exist in the country. 4. The demand for exports is affected by the total quantity of beef supplied and by the level of internal consumption. The export price does not play the role that would be expected in the case of an uncontrolled market. This finding suggests that the quantity of beef exported is the surplus above the level of domestic consumption. 5. Pasture improvement has been practically the only investment in cattle production during the period of the study. Phosphate fer— tilizer subsidies and a negative real rate of interest on government loans were the most important variables affecting the annual gross investment in hectares of improved pasture. This study also estimated the total beef supply that would result under different assumptions of government policies in relation to beef prices and subsidies on investment inputs. From this analysis and from the conclusions of the study, policy implications are drawn. Dedicated to My Family 11 ACKNOWLEDGEMENTS During the time of my graduate studies at Michigan State Univer- sity, I have been helped by several individuals and institutions. It is difficult for me to express my appreciation adequately to all of them. Nevertheless, I want to express my deepest gratitude to my Major Professor, Dr. Warren Vincent, for his deep human involvement in the creative guidance, intellectual stimulation, and encouragement given to me throughout all my graduate program. I want also to express my sincere appreciation and gratitude to Dr. Darrell Fienup, who was instrumental in getting the financial assistance needed for my graduate study, who provided important guidance at the earlier stages of my program, who gave me encouragement, and who served on my Guidance and Thesis Committees. It was Dr. Fienup who gave the initial impetus to my work. I also want to thank Dr. Stanley Thompson, who served as my Thesis Advisor. Dr. Thompson's dedicated help made possible the formu- lation and the conclusion of this thesis. Thanks are also extended to Dr. Anthony Koo, Dr. Vernon Sorenson, and Dr. Derek Byerlee, who served on my Guidance Committee, and to Dr. Harold Riley, who served on my Thesis Committee. To my fellow graduate students, in particular to those in Chittenden Hall, with whom I shared all these years at MSU, a special thanks. My gratitude also goes to the Comision Honoraria del Plan Agro- pecuario in Uruguay, the Ford Foundation, and the Agency for International Development for the financial support they provided during my studies at Michigan State University. I also want to give special thanks to Mrs. Ann Carroll for her committed and careful editing of my thesis and to Mrs. Cathy Cooke for her dedicated and expert typing job. They both worked without time limit to make possible finishing this thesis. To all these people-~Muchas gracias! iv TABLE OF CONTENTS List of Tables . List of Figures Chapter I II III INTRODUCTION Introduction The Problem . . Purpose of the Study . . . Objectives of the Study . Procedures . . . Relevance of the Study Chapter Organization THE AGRICULTURAL SECTOR . Background Conditions of the Country General Characteristics of the Agricultural Sector. Economic Importance Agricultural Land . Farm Size and Land Tenure . Summary . THE BEEF-CATTLE INDUSTRY The Cattle Stock Cattle Breeds . Production Internal Consumption Exports . Summary . oowmth—I l2 l2 l5 I6 20 21 21 22 23 32 36 38 Chapter IV METHODOLOGICAL APPROACH . . . . .......... The Economic Model Supply Beef Supply Equations . . . . . . Derived Demand for Roughage . . . Demand . . ..... Review of Beef Demand Studies I I I Beef Demand Equations . . The Statistical Model . . . . I I I I I Equations and Variable Definitions Equations . . . Variable Definitions Estimation Procedure Distributed Lag Model . . . . . . . Test of Statistical Estimates . . Summary ..... . . . . . . . V STATISTICAL ANALYSIS AND RESULTS The Estimated Supply Equations . . . Number of Beef Cattle Slaughtered . Meat Yield per Animal Slaughtered . The Derived Demand for Roughage . . Testing the Supply Equations . . Beef Supply Forecasting ........ The Estimated Demand Equations . . Beef Demand for Internal Consumption Beef Demand for Exports . . VI SUMMARY AND CONCLUSIONS Supply Analysis . . . ..... Review of Beef Supply Studies . . . 00000 Number of Beef Cattle Slaughtered I I I Meat Yield per Animal Slaughtered . Demand Analysis . . . . Policy Implications . . Recommendations for Further Research APPENDIX . BIBLIOGRAPHY . ..... vi Page 39 39 41 43 48 50 51 52 56 57 59 59 6O 62 65 67 68 7O 7O 71 79 81 83 91 95 95 100 102 102 103 105 107 108 112 114 123 Table 2.1 LIST OF TABLES Gross Domestic Product at 196l Prices (In thousands of Uruguayan Pesos) . Total Exports of Uruguay (In millions of U.S. dollars) . Percentage Distribution of Land Use . Percentage Distribution of Total Number of Holdings and Total Land Area by Various-Sized Holdings . Some Productivity Indicators by Size of Farm Ratio of Cattle Stock, Population, and Cattle to Inhabitants . . . . . . . . Percentage Distribution of Cattle by Size of Holdings Improved Pasture Production of Beef at the Farm Level Number of Producers Assisted by the Plan Agropecuario (1961—74) . Beef Production, Consumption and Exports (Carcass Weight Equivalent) . Quality of Steers, Cows and Total Animals Slaughtered (September 1970) . . . . . . . . . . . . . . Average Slaughter per Month . Breakdown of the Export Price of Beef (USS/Ton) . Beef Exports by Type of Product (Percent of Total Exports) Page 14 15 17 18 19 22 24 27 28 29 3O 31 35 37 Table 5.1 Page Parameter Estimates for Unconstrained and Constrained Second and Third Degree Polynomial Lag Models (Five- Year Lag) . . . . . . . . . . . . . . 73 Parameter Estimates for Unconstrained and Constrained Second and Third Degree Polynomial Lag Models (Six— Year Lag) . . . . ...... . . . . 74 Simple and Cumulative Price Elasticities of Total Slaughter . . . . . . . . . . . . . ..... . . . . 76 Short and Long-Run Price Elasticities of Slaughter Estimated in Previous Studies . . . . . . . . . . . . 78 Ability to Forecast Turning Points Supply Equations (Quantitative Measure of Graphical Analysis for Supply Equations) . . . . . . . . . . . . . . . . . . 85 Theil' s U Coefficient of Inequality for the Supply Equations . . . . . 90 Forecast of Beef Supplied Under Different Assumptions of Beef Price Increases and of Interest Rate (000 M.T.) . . . . . . . . . . . . . . . . . . . . . 92 Domestic Beef Demand Equations . . . . . . . . . . . 97 Price and Income Elasticities of Demand from Different Studies . . . . . . . . . . . . . . . . . 99 Cattle Stock, Slaughter, Average Weight, and Total Beef Supply . . . . . . . . . . . . . . . . . . . 115 Internal Beef Consumption . . . . . . . . . . . . . . 116 Export Price of Beef, Exchange Rate, Farmers' Beef Price, Price of Wool, Price of Phosphate Fertilizer, and Interest Rate on Loans for Improvement of Pastures 117 Retail Prices of Beef, Pork, Chicken, and Fish and Consumer Price Index . . . . . . . . . . . . . . . . 118 Number of Hectares of Improved Pasture: Created, Existing, and in Production 1956-75 (000 Hectares) . . . . . . . . . . . . . . . . . . . 119 viii Table Page F Data Used in Figures 5.1, 5.2, and 5.3 . . . . . . . 120 G Data Used in Figure 5.4 . . . . . . . . . . . . . . 121 H Forecast of Total Beef Supply Under Different Price Assumptions for Prices of Beef, Fertilizers, and Interest Rate (MT 000) . . . . . . . . . . . . . . . . . . . . . . 122 ix LIST OF FIGURES me m: 4.1 Diagram of Economic Interrelations in the Beef-Cattle Industry . . . . . . . . . . . . . . . . . . . . . . 40 5.1 Number of Beef Cattle Slaughtered . . . . . . . . . . 86 5.2 Meat Yield Per Animal Slaughtered , , , , , , , , , , 87 5.3 Total Beef Supplied . . . . . . . . . . . . . . . . . 88 5.4 Annual Gross Investment in Improved Pastures , , , , 89 5.5 Actual and Forecast Total Beef Supply (In thousand metric tons) . . . . . . . . . . . . . 94 CHAPTER I INTRODUCTION Introduction Uruguay relies heavily on the agricultural sector and particularly on beef production as a source of food for its population, as inputs for its industry, and as the basis of the foreign exchange needed for essential imports. Due to the fertile land endowment, excellent climate, and good water supply, beef production has always been and still is a major element in the Uruguayan agricultural economy. During the first fifty years of this century, Uruguay enjoyed a high level of income from her agricultural exports, mainly as a con- sequence of a high international demand for beef and wool.1 An increase in world beef supply and a slowdown in the growth rate of the cattle sector started a process that showed, particularly after the end of the Korean War, the intricate economic link between the cattle sector and the Uruguayan economy as a whole. It appears that it is necessary to regenerate the original growth rate of the cattle sector and to increase beef exports in order to continue economic growth at the national level. 1Ministerio de Ganaderia y Agricultura, Oficina de Programacion y Politica Agropecuaria, CIDE-—Sector Agropecuario, Estudio Economico y Social de la Agricultura en el Uruguay (Montevideo, 1967). 2 The intent of this study is to contribute to the growing stock of knowledge concerning the dynamics of the Uruguayan cattle sector. In particular, the study attempts to provide needed descriptive and quantitative information about some of the important relationships among the variables affecting this sector. The Problem The economic depression of the 19305 and the disruption of inter- national trade greatly reduced Uruguay's earnings derived from the export of livestock products (beef and wool). For the period on which this study focuses (1956-75), the livestock sector contributed, on the average, more than 80 percent of the country's annual total exports.2 During this difficult period, Uruguay began a pronounced policy of industrialization via import substitution. At the same time, it further emphasized policies promoting income redistribution and social welfare. These policies, as well as most other policy measures directed toward achieving economic development, were largely financed by the livestock sector;nminly through export taxes. This tendency was particularly accelerated at the beginning of the 19505. The role played by the livestock sector, and the beef—cattle industry in particular, in support of the rest of the economy has been guided by strong government intervention. This intervention has been substantial at all stages of the industry: in production, processing, internal consumption, and exports. However, in general, government intervention has not contributed to the solution of the problems of 2Ministerio de Ganaderia y Agricultura, Oficina de Programacion y Politica Agropecuaria, Objectivos y Metas del Sector Agropecuario (Montevideo, 1972). 3 the industry3 which occur at various levels. The main problems at the production level are 1) low beef-cattle productivity level based on extensive grazing of native pastures, 2) existence of foot-and-mouth disease, and 3) lack of adequate supply of pasture throughout the year with the subsequent seasonality of beef production.4 The most important shortcomings at the level of the meat packing industry are 1) low sanitation standards, which are not acceptable to some of the major importing countries, 2) lack of adequate cold storage capacity to compensate for the seasonal fluctuations in production, and 3) low value added of processed meat. Internal consumption of beef in Uruguay has been traditionally very high. In addition, the lack of beef substitutes for consumption and the important political power of the urban population determined that the price of beef has always been a political issue in which the consumer has been the winner. During the period 1956-75, prices to beef producers and consumers were maintained at artificially low levels. Beef exports accounted for almost 40 percent of total export earnings in the last five years of the study.5 Beef export performance greatly affects the country's balance of payments, has important implica- tions for monetary and fiscal policies, and in general affects the 3Brannon, Russell H., “The Role of the State in the Agricultural Staggation of Uruguay" (Ph.D. dissertation, University of Wisconsin, 1967 . 4Ministerio de Ganaderia y Agricultura, Cuarto Proyecto de Desarrollo Ganadero del Uruguay (Montevideo, 1971). 5Hunting Technical Services and Oficina de Programacion y Politica Agropecuaria, Agricultural Diversification Study (Montevideo, 1976). 4 country's economic growth and development possibilities. Purpose of the Stugy Given the importance that beef production has for the Uruguayan economy and its role in the country's development, it is necessary to determine the factors that have been affecting the possibilities of growth of the beef-cattle sector and the extent of their importance. From among the various problems that the beef industry faces, this study focuses particularly in the analysis of beef supply. However, analyses of demand of beef for internal consumption and of the avail- ability of beef for exports are also included. In addition to the artificially low prices of beef, producers face uncertainty in terms of other government policies regarding export taxes, exchange rates, production subsidies, price of inputs, credit, etc. These uncertainties have complicated the producers' decision making and created unfavorable conditions for investment in the sector. In light of these problems, this thesis studies past characteristics and trends of the beef-cattle sector which could be relevant to achieving the goal of increasing beef production and exports. Objectives of the Study The overall objective of the study is to investigate the struc— ture of the Uruguayan beef-cattle industry in order to suggest means of accelerating growth in this sector through improved public policy decisions in the areas of beef production, domestic beef consumption, and beef exporting. To accomplish this major objective, the following more specific objectives are set: 5 1. To obtain a descriptive knowledge of the dynamics of the beef- cattle economy, hence a better understanding of the determinants of the demand for inputs, beef supply schedules, internal consumption, and availability for exports 2. To identify and quantify the effect of the most important factors affecting the beef-cattle economy. Emphasis is placed on estimating the effect of relevant factors affecting the production, consumption, and beef-export subsystems, rather than on evaluating the whole beef-cattle economic system simultaneously 3. To model econometrically the structure of the Uruguayan beef- cattle industry, in particular, to investigate the critical relationships affecting a) the number of cattle supplied, b) the meat yield per animal slaughtered, c) the amount of beef internally consumed, d) the amount of beef available for exports, and e) the investment required to increase beef production and the price of needed inputs Procedures The study is based on annual time—series data. Heavy reliance is placed on the use of aggregate data that were obtained from secondary sources. Nevertheless, some nonnumeric, primary information is also used. Secondary data were obtained from the Ministry of Agriculture and Fisheries (the Direction of Agricultural Economics, the Livestock Development Plan, the National Research Center, and other agencies), the Central Bank, the Bank of the Republic, the Ministry of Industries, the National Meat Board, and the Association of Owners of Meat Packing 6 Plants. Data were also obtained from publications, both in Spanish and English, from the Foreign Agriculture Organization, International Bank of Reconstruction and Development, European Economic Community, and Organization for Economic Cooperation and Development. Some first- hand information was obtained by visiting farmers, processors, and decision makers in the government when the author was working in Uruguay and during the period of data collection in the field at the beginning of 1978. More specific information about the data collected will be presented in the Appendix. The econometric model consists of the following relationships: four behavioral equations (number of beef cattle slaughtered, meat yield per animal slaughtered, domestic demand for beef, and export demand for beef) and two identities (total beef supply=number of beef cattle slaughtered times meat yield and total beef demand=beef demand for internal consumption plus beef demand for exports). During the period of the study, severe and largely unpredictable government controls were operative, mostly with respect to prices. Con- sidering the extent to which beef prices may be regarded as predetermined and due to the recursive estimation of beef supply, a single equation approach for the statistical estimation of the equation parameters was selected. Ordinary least squares is the statistical procedure used. For the estimation of the supply of cattle for slaughter, a polynomial distributed lag model is developed. 7 Relevance of the Study It is expected that the results and policy implications of this study will be of use at least for the following policy-making bodies of Uruguay: 1. The Ministry of Agriculture and Fisheries. This Ministry is responsible for agricultural production and agricultural policy formu- lation. It determines the areas and level of government intervention in the sector 2. The Bank of the Republic. This agency is in charge of pro- viding financial assistance to the farmers contributing to the imple- mentation of the agricultural policy decided by the government 3. The Livestock Development Project, which provides technical assistance to beef producers and is in charge of the introduction of new technology into the sector 4. The Central Planning Office, which is responsible for the overall planning of the economy and the allocation of resources between the different sectors 5. The Ministry of Industry and Trade which is responsible for the agencies in charge of domestic supply and promotion of foreign markets 6. The Central Bank, which, in coordination with the Ministry of Finance, decides on matters of monetary policy, influences the low price of beef when trying to maintain a low inflation rate, and manipu- lates the exchange rate 7. The Uruguayan beef producers themselves, who are instrumental in investing in new technologies to increase productivity 8 Chapter Organization This introductory chapter explained the motivation for this research, the purpose and objectives of the study, as well as its relevance in policy making. Chapter II discusses the agricultural sector of Uruguay and some of the problems that it has faced during the period of the study and at the present. Chapter III is devoted to a description of the Uruguayan beef- cattle industry. Chapter IV discusses the methodological approach of the study. The economic and statistical model is presented. Chapter V explains the statistical analysis and provides the empirical results. The estimated supply and demand equations are reported and discussed. Chapter VI contains the summary and conclusions, the policy implica- tions of the study, and recommendations for further research. CHAPTER II THE AGRICULTURAL SECTOR General Background of the Country Uruguay, situated between southern latitudes 30 and 35, bordered by Argentina and Brazil, occupies an area of 187,000 square kilometers or 72,172 square miles, qualifying as one of the smallest countries in South America. Almost 90 percent of this area can be used for agricul- tural production, for it has good climate, soil, and water supply. Thus Uruguay must be considered as one of the world's most favored nations agriculturally. During the first part of the twentieth century, Uruguay was regarded as a model of democracy, stability, and social justice. With its fer— tile soils and small population, the country was able to build an economic system based on the agricultural sector, most specifically the livestock sector, exporting beef and wool. These exports provided high income levels and extensive social benefits for the population, which is literate, culturally homogenous, and largely urban. The population of Uruguay is about 2.8 million, with half living in the capital, Montevideo, about 300,000 living in rural areas, and the rest living in cities in the interior of the country. The rate of growth of the population is 1.2 percent per annum. It can be said that all the Uruguayan population is of European origin, since at the time of the conquest, the native population was very small, estimated at 10 about 5,0001 and was exterminated or absorbed by the European immigrants. The level of education is high-~the adult literacy rate is 91 per— cent; primary school enrollment was 94.5 percent as of 1970. The national per capita income was U.S. $890 in 1974.2 As mentioned earlier, until the mid-19505 Uruguay was regarded as a model of democracy, stability, and social justice in clear contrast with other Latin American countries. In terms of health services, Educa- tion, social security,and level of food consumption,Uruguay could be compared favorably with many developed countries. Until the 19305, the economic growth was primarily based on the extensive production of livestock products for export. In 1930 meat accounted for 46 percent of the total exports, wool 26 percent, and hides 11 percent, the rest being crops 11 percent and other exports 6 percent.3 The economic depression of the 19305 represented a collapse of the world market for Uruguay's traditional exports. Another develop- ment phase started then, with a process of productive structure diver- sification through industrialization via import substitution. This process was further emphasized due to the disruption of world trade during World War II. These policies were largely financed with taxes on agricultural exports; trade barriers were created to protect the 1Oddone, Juan Antonio, Economia y Sociedad en el Uruguay Liberal (Monte— video: Ediciones de la Banda Oriental, 1967). 2International Bank for Reconstruction and Development, Economic Memorandum on Uruguay (Washington, D.C., 1975). 3Universidad de la Republica, Instituto de Economia, E1 Proceso Economico del Uruguay (Montevideo, 1969). 11 local industry. The production of import substitutes that Uruguay could produce at a competitive level was rapidly reached. The result, as in other Latin American countries, was the development of high-cost industrial production that could compete only in the protected domestic market. The end of the Korean War brought about severe declines in the prices of Uruguay's principal exports, and this decline reinforced the previous government proclivity to develop industry at the expense of agriculture. Without maintaining its agricultural production and ex- ports, particularly the ones from the livestock subsector, Uruguay was not able to sustain either the industrial sector which had been created nor to support the welfare policies which had been implemented. Con— sequently, Uruguay, which had grown at over 5 percent per year during the period 1944-56, has grown at less than 1 percent during the 20 years (1956-75) considered in this study.4 Per capita income has declined over this period by a total of roughly 10 percent in real terms. The economic deterioration process led to a spread of social con- flicts over economic claims and even to the appearance of one of the most sohpisticated guerrilla movements in Latin America. This movement was destroyed in 1972-73 when military forces seized power. This was the end of almost 100 years of continuous multiparty democracy in which the armed forces played no political role. 4Universidad de la Republica, Facultad de Ciencias Economicas, Uruguay Estadisticas Basicas (Montevideo, 1976). 12 General Characteristics of the Agricultural Sector Uruguay's temperatures place it in the temperate zone, there being only slight variations within its territory. The average temperature for the warmest month, January, is about 23° Centrigrade (73 degrees Fahrenheit), and the average temperature for the coldest month, July, is about 10° Centigrade (50 degrees Fahrenheit). Frost occurs 10 to 20 times during winter. The average rainfall for the last 50 years was 1,070 millimeters, occuring uniformly throughout the year.5 The topog— raphy generally is slightly undulating with very few hills and no moun- tains. The highest elevation in the country is less than 600 meters (2,000 feet) above sea level. The vegetation originally was low grasses directly usable in livestock production. Water is plentiful from numerous rivers and small water courses. The soils, in general, are of medium to high fertility, but about 20 percent are superficial rocky soils.6 According to the last census of 1970, 90 percent of the soil is used for livestock production, 8 percent is utilized principally in extensive agriculture, 1 percent is forested, and 1 percent is used for more intensive crops such as horticultural crops, orchards, and vineyards. In the last general agricultural census of 1970, Uruguay had 8.5 million beef cattle, mainly Hereford; there were about 500,000 dairy cattle, mainly Holstein. Uruguay also has 19.8 million sheep, 5Comision Honoraria del Plan Agropecuario, E1 Plan Agropecuario (Montevideo, 1972). 6Ministerio de Ganaderia y Agricultura, Oficina de Programacion y Politica Agropecuaria, CIDE--Sector Agropecuario, Estudio Economico y Social de la Agricultura en el Uruguay, (Montevideo, 1967). 13 principally Corriedale. There were 460,000 horses and 383,000 pigs.7 Economic Importance During the period of the study, as is shown in Table 2.1, the contribution of the agricultural sector to the Gross National Product has been around 15 percent, with the contribution of the industrial sector being 23 percent, and the service sector 57 percent. The Uru— guayan population was around 2.8 million in 1975, 40 percent of it being the working population (1,100,000). The national census of 1966 indicated that only 190,000 (17 percent of the working population) were working in agriculture. The industrial sector employed 27 percent of that population and the service sector 56 percent of it.8 The census of 1970 showed a further decrease to 132,200 in the population working in the agricultural sector. The contribution of the agricultural sector to the national economic output and to employment has been low. These two economic indicators appear to follow similar patterns to those of developed countries, but this is only apparent since Uruguay, like other Latin American countries, has not been able to finance and absorb in a productive way the urbanization process. This has led to a hyper- trophy of the service sector, in particular the public one. When other indicators are analyzed, such as the participation of agriculture in the external trade sector and as a source of raw material for the local industry, the importance of the agricultural sector for 7Ministerio de Ganaderia y Agricultura, Departamento de Estadistica Division Censos y Encuestas, Censo General Agropecuario 1970 (Montevideo, 1973). 8Ministerio de Ganaderia y Agricultura, Oficina de Programacion y Politica Agropecuaria, Objectivos y Metas del Sector Agropecuario (Montevideo, 1972). 14 TABLE 2.1 Gross Domestic Product at 1961 Prices (In thousands of Uruguayan Pesos) 1956 1961 1966 1971 1975 Agriculture 2,482 2,193 2,429 2,839 2,715 Industrya 3,527 3,423 3,683 3,956 4,350 Construction 1,004 850 703 800 854 ServicesP 8,497 9,200 9,375 9,732 9,907 Total G.D.P. 15,510 15,666 16,190 17,327 17,826 Source: Banco de la Republica and Banco Central. aIncludes mining. bIncludes commerce, transportation, utilities, housing, financial, government, and other services. the Uruguayan economy appears clearly. For most of the twenty years of the study (1956-73), more than 90 percent of the total Uruguayan exports have been from the agricultural sector. In 1956, 99 percent of the country's exports were livestock or other agricultural products. Only in two years (1974 and 1975), as can be seen in Table 2.2, the relative contribution of the agricultural sector to exports declined. This was due to a reduction in the international price of beef and to an impor- tant increase in the exports of leather manufacture. The livestock subsector has been the most important contributor during the period of the study, contributing more than 80 percent of the country's total exports. These figures show that the external sector of Uruguay is heavily dependent upon agriculture and particularly on beef and wool production. The performance of the livestock sector determines what 15 will be the volume of foreign exchange available for development. Additionally 40 percent of the gross industrial product comes from industries that use agricultural inputs.9 Total Exports of Uruguay TABLE 2.2 (In millions of U.S. dollars) Total Agri. Livestock Total Agri. Contribution of Exports Products Products Sector Agri. Sector Exports (%) 1956 215.7 31.9 180.0 212.9 99 1961 174.7 12.4 157.1 169.5 97 1966 185.8 14.9 161.6 176.5 95 1971 196.6 25.5 154.9 180.4 92 1973 327.6 31.8 268.3 300.1 92 1974 381.3 52.6 269.5 322.1 85 1975 384.9 71.3 216.2 287.5 75 Source: Oficina de Programacion y Politica Agropecuaria with data from Banco de la Republica and Banco Central del Uruguay. Agricultural Land Uruguay's land area is about 18.7 million hectares (46.2 million acres) of which about 16.6 million hectares (41.0 million acres) could be used for livestock or agricultural production. basis, this represents roughly 6 hectares per person. On a per capita A more favorable 9Ministerio de Ganaderia y Agricultura, Oficina de Programacion y Politica Agropecuaria, Objectivos y Metas del Sector Agropecuario (Montevideo, 1972) 16 man/land ratio is found only in Australia and Argentina. Nevertheless, very little productive investment has been made in the Uruguayan agri- cultural sector. Most of Uruguay's agricultural land (around 80 percent) is in native pasture. Improved natural pasture, although increasing since the 1956 census, was still a very small percentage of the total area 10 (9.3 percent) in 1970 and about 10 percent in 1975. Only 8 percent of the agricultural land is devoted to cultivated crops. (See Table 2.3.) Farm Size and Land Tenure More than 55 percent of the land (60.9 percent in 1970) consists of farms with more than 1,000 hectares (2,471 acres) owned by only 5 percent of the producers. On the other extreme, 73 percent of the far- mers own only 6 percent of the land. The National Agricultural censuses of 1956, 1961, 1966, and 1970 show no important changes in the pattern of land distribution; however, there is slightly more concentration of land ownership as indicated by the decrease in the number of holdings and decrease in the land area of small farmers. (See Table 2.4.). Some authors have indicated that the concentration of the land in big farms constitutes a structural barrier to investment and to the ability to respond to price incentives. This indicates that an inverse 10International Bank for Reconstruction and Development. Uruguay Third and Fourth Livestock Development Projects (Washington, D.C., 1976). 17 TABLE 2.3 Percentage Distribution of Land Use 1956 1961 1966 1970 Pasture Natural Pasture 81.1 81.5 79.6 77.5 Artificial Pasture- annual 2.7 2.1 3.0 2.5 permanent ---— 0.9 1.9 2.2 Improved Natural Pasture 1 6 2.3 3.1 4 6 Scrub 2.6 2.7 2.5 2.9 88 0 89.5 90 1 89 7 Crop Land Cereals 7.3 5.7 5.0 5.6 Oilseeds 1.8 1.6 1.4 1.6 Other 0.7 0.6 0.7 0.8 9.8 7 9 7.1 8 0 Forestry Plantations 0.7 0.8 0.9 0.9 Other Use and Unproductive Land 1.5 1.8 1.9 1.4 TOTAL 100.0 100.0 100.0 100.0 Sources: General Agricultural Censuses—-1956, 1961, 1966, and 1970. 18 TABLE 2.4 Percentage Distribution of Total Number of Holdings and Total Land Area by Various-Sized Holdings ._—__— Size a Total Number of Holdings % Total Land Area % (hectares) 1956 1961 1966 1970 1956 1961 1966 1970 1-99 75.1 74.8 73.4 72.9 9.5 8.8 6.0 5.9 100-499 16.9 16.5 17.3 17.3 19.9 18.9 17.7 17.6 500-999 4.0 4.3 4.4 4.7 14.8 15.4 15.1 15.6 1000-2500 2.7 3.0 3.4 3.6 22.6 23.5 26.0 26.9 2500 & more 1.3 1.4 1.5 1.5 33.2 33.4 35.2 34.0 TOTAL 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Sources: General Agricultural Censuses 1956, 1961, 1966, and 1970. a1 hectare = 2.47 acres. relationship exists between size of holdings and productivity.”’12 But practically no research has been conducted in this important area even though such knowledge is very important for policy makers when a restructuring of the landholding pattern is considered. When some productivity indicators,such as birth, mortality, and stocking rates of cattle and sheep, crop yields, and use of fertilizer, are analyzed, there is no evidence that large holdings are less pro- ductive than small ones. The information of Table 2.5 has been obtained HUniversidad de la Republica, Instituto de Economia, E1 Proceso Economico del Uruguay (Montevideo, 1969). 12Ministerio de Ganaderia y Agricultura, Oficina de Programacion y Politica Agropecuaria, CIDE--Sector Agropecuario, Estudio Economico y Social de la Agricultura en el Uruguay (Montevideo, 1967). 19 .onmp .mamcmu Fmgzppzuwgm< ”moczom N.emw F.Nmm o.o F.0e m.F o.m o.~e 8.0 m.mm _eeoe m.~oo m.mmo.~ m.m N.oe N.P m.~ m._e o.o o.mm egos ace oom.N o.Fem w.moo._ m.m m.mo e._ e.N e.FN o.o ©._e oom.~-ooo._ m.mee e.omm N.o N.oe m._ _.m ~.me o.o m.em amm-oom P.N~m o.emm m.o m.oe m._ o.m m.ee w.o G.Nm mme-oo_ m.emm m.~mm _.m a.mm m._ w.m N.me m.o _.mm mm -_ eeou bees: aeewwmmoz cwwmm emuemwuuuz sewwwmmoz emwmm LeMLMWMHuz mnwmm_wwuwu Ammeeeumxv mgmuumz can upmw> nogo mumcm mpppmu em unwogwm wnmm Egon yo m~_m x5 mgogm0wvcH zuw>wuuacoea meow m.N m4m

aov mczwrzovem< x wwgmumcmm we o_cmumw:wz use mmccwu mu chowumz opauwumcH ”mugaom mm _om Fe _Fe em ooe em Fem me __N 255355;; ea waste eez - - ANV AFNV Amy A_¢v on Aoev Aev Am_v Ameoemmweeouv Smog wepem - 1 ANV Am_v Ao_v ANNV Aoev Aaev ARV Ammv _e>au gmusvoga mmxm» uuwcwvcm _ m 5 mm as m__ 8_ mo, PP om eoeee~w_eeeeeeeou co emou mm aow em owe me mpm ox owe em _eN 25535525 5e 55525 macaw mN “we em mmm __ ee m. aw mm No, cemeez mucosa museums pee: mucmpa mcmxuma 1 1 1 1 m Pm m cm N o_ yam: Eogu mm_wm co mmxoh 5 55 Amy Aomv ANV Aemv ANV Ae_v ANV Ae_v Aev “Nev wees: co Ae_v Aemmv Aav Ammv A__v Amev AN_V Aomv Ae_v “mov pee: :0 m_ 0mm N_ m__ mp Na 4_ Na m. mm mexe» eeeaxm cop mmm._ cop eoo.P oo_ coo.F oo_ ewe oo_ owe ee_ea “coax“ a a e w a a a w a a mmap .>oz N~m_ .>oz Fem, so: cum. .eeo amm_ an: Acop\wmav $mmm we move; ucoaxu any we czovxmmgm m.m m4mou ms x mumz H mm# mz 1 apaasm 111111. mcowuwucou mummz Legeo yo oowcm _weuem chgmucH xmauag :_ osouwH 1mv mmww we mucoqu gmszmcou powwa wmmm .pnmmoqmw. F. a co_uaszmcou A11111¢v mumz 1 Amli mgzummm mumew_u x_aa=m wmwm _cu0h :o_ucm>couc o_u:w>couc ucoE:Lm>oo acme:Lm>oo mmeeucsou . nguo An Comm 9 mo »_aa:m mpmou mc_umxng new cowumNPpm_gum=ucH mucmpa asexuaa Ham: momeucsou // mowguczou 1111111111111 mcwugoaefi measuTGmnam , mcwugoaem :owucm>cmgca :_ msoucH wmom cw pcmaccm>oo emanmcou we «owe; \ :owp:w>gwucu m_nmmoamwo unmEcgm>ou 41 to the consumers. During some months of the year, in some years, the government also determines the quantity offered for local consumption establishing ”vedas,“ or periods "without meat.” In the external market, the National Meat Board must approve all foreign sales made by meat-packing plants. The National Meat Board also determines weekly minimum prices at which contracts may be accepted. The quantity of beef exported is affected indirectly through fixed beef prices and directly when ”vedas” are imposed to increase the amount of beef available for exports. In the following section, the theory of supply and demand is reviewed to see its application to the particular conditions of the Uruguayan economy. Supply Supply response, or quantities of output, and its relationship to resource inputs and product prices appear to be one of the basic problems in Uruguay's agriculture. Supply research is necessary to provide additional information to policy makers, enabling them to make improved policy formulation. This supply response research should indicate the direction and the magnitude by which the relevant variables influence supply. Traditional economic theory suggests that the market supply of beef or any other product is a ceteris paribus relationship. That is, the quantity supplied will vary as the price of the product changes, other factors affecting supply holding constant. The other factors that can affect supply are substitution in production, price of inputs, technology, weather, price of other products, etc. 42 Up to this point, theory is used to assist in identifying the relevant variables that enter the behavioral relationship and in identi- fying the direction of their influence. The magnitude of their influence will be considered later in this study. (See Chapter V.) The market supply relationship can be expressed in functional form as follows: 05 = f (Pp,PI,PSP,T,W, . . . ) where: Q5 = quantity supplied Pp = price of product supplied PI = price of inputs PSP = price of substitutes in production T = technology W = weather Economic theory suggests that the price of the product at hand will have a positive effect on quantity supply. The price of inputs and the price of substitutes in production are expected to have a nega— tive effect on quantity supplied. In the case of technology, a posi- tive effect on quantity produced is also expected. The weather or climatic conditions could have positive or negative effects on produc- tion. Nevertheless, if a climatic or weather index is developed, it could be determined which index values would affect quantity supply positively and which values would affect it in a negative way. The properties or assumptions underlying the supply of output functions are based on comparative static economics and included in 43 theory of profit maximization in a competitive market. These proper— ties are presented in many books, and they are not repeated here.]’2’3 Review of Beef Supply Studies Before using the previous concepts for the analysis of the supply of beef in Uruguay, a short review of beef supply analyses performed in Uruguay or in countries with similar production conditions is pre- sented. Unfortunately, practically no interest was displayed in Uruguay in the analysis of beef-cattle production trends or the causes of stagnation of the sector until the whole economy became affected in the middle of the 19505. Since then, few studies have been carried out; most of them are of a descriptive nature. Some quantitative analyses have been conducted which have attempted to explain the effect of single variables on quantity of beef supply. The most relevant of those studies are reviewed. Probably the first of the descriptive studies was conducted in 1950 by a mission at the Food and Agriculture Organization and the International Bank for Reconstruction and Development.4 This study group was invited by the government of Uruguay to analyze the livestock sector and to suggest policies and programs that might help to increase 1Nicholson, Walter, Microeconomic Theory (Hinsdale, Ill.: The Dryden Press, 1972). 2Cohen, Kalman and Cyert, Richard, Theory of the Firm: Resource Alloca- tion in a Market Economy (Newark: Prentice Hall, Inc., 1975). 3Lloyd, Cliff, Microeconomic Analysis (Homewood, Ill.: Richard D. Irwin, Inc., 1967). 4International Bank for Reconstruction and Development and the Food and Agriculture Organization, Agricultural Development of Uruguay (Rome: The United Nations, 1951). 44 beef production. As mentioned in Chapter III, this study recognizes the lack of adequate roughage supply as the most important factor affecting livestock, particularly beef-cattle production. Between 1960 and 1970, the government of Uruguay with the finan— cial support of the IBRD regarded the same variable as the most impor- tant. It directed the first two livestock development projects of Uruguay for the improvement of grazing and arable land resources through phosphate fertilization and for practices of pasture improve- ment. (See Chapter III.) In 1970, the appraisal of the third Livestock Project of Uruguay by the IBRD5 shifted the perspective followed from the beginning of the 19505. Policy issues, such as the price of beef to producers and consumers, were seen at this stage as more important than technological issues in affecting the development of beef-cattle production. A major descriptive study was published by the Ministry of Agricul— ture in 1967.6 In this analysis the following variables were mentioned as affecting the production of Uruguayan beef cattle: (1) the technology (namely roughage production); (2) farmer beef prices; (3) climatic con- ditions; (4) price of substitutes in production (sheep wool was identi- fied as the main production alternative to beef cattle); (5) price of inputs (namely the price of phosphate fertilizers); (6) technical assistance to the farmers, and (7) agricultural credit. 5International Bank for Reconstruction and Development, Appraisal of Third Livestock Project of Uruguay_(Washington, D.C., 1970). 6Ministerio de Ganaderia y Agricultura, Oficina de Programacion y Politica Agropecuaria, CIDE--Sector Agropecuario, Estudio Economico y Social de la Agricultura en el Uruguay (Montevideo, 1967). 45 Other studies conducted later by Brannon,7 Fletcher and Merrill,8 and Coirolo9 generally concurred that the variables previously men— tioned are the most important factors affecting beef production in Uruguay. Virtually no quantitative analysis of the Uruguayan beef industry has been conducted to date. 10 11 The Planning Office of the Ministry of Agriculture, 12 Coirolo, and the Livestock Development Project studied the return on invest- ment in improved pastures in the livestock sector of Uruguay. The three studies concluded that the number of hectares of improved pastures in production has an important effect on beef supply at the farm level. Using regression analysis to study the effect of pasture improve- ment on beef supply, von Oven13 concluded that the introduction of this new technology had a positive effect on beef—cattle production. 7Brannon, Russell H., ”The Role of the State in the Agricultural Stag- nation of Uruguay'I (Ph D. dissertation, University of Wisconsin, 1967). 8Fletcher, L. and Merrill, H., The Uruguayan Agricultural Sector: Priorities for Government Policies, Investment Programs and Projects (Washington, 1970). 9Coirolo, Luis, ”Factors Affecting the Uruguayan Trade of Livestock Products” (M.S. Plan 8 paper, Michigan State University, 1976). 10Ministerio de Ganaderia y Agricultura, Oficina de Programacion y Politica Agropecuaria, Cuarto Proyecto de Desarrollo Ganadero (Montevideo, 1971). HCoirolo, Luis, ”Rentabilidad Marginal de los Mejoramientos de Campo en 23 Predios Seleccionados” (Tesis de Ingeniero Agronomo, Montevideo, 1972). 12Comision Honoraria del Plan Agropecuario, El Plan Agropecuario (Montevideo, 1972). 13von Oven, Roderick, ”Impacto de los Pasturas Mejoradas Sobre 1a Produccion Ganadera en el Uruguay,“ Comision Honoraria del Plan Agropecuario, Anuario 1975 (Montevideo, 1975). 46 According to his results the improved pastures accounted for 64 percent of the variation in beef production between 1961 and 1974. Pimentel,14 in his study "Mathematical Models for the Agricul- tural Sector of Uruguay," analyzed the factors affecting cattle stock and the supply of animals for slaughter. He concluded that the most important factor affecting both cattle stock and slaughter supply is the expected beef price. The price expectations, he stated, are based mainly on past prices. Jarvis,'5 using annual data for the period 1960-76, through regression analysis estimated two equations to explain aggregate cattle slaughter. One equation estimated tons of beef produced, and the other estimated gross number of animals slaughtered. In both cases he found that the most important variables affecting beef supply were cattle stock in the previous year and the farmer beef price in the same year. Different Argentinian time-series studies on beef supply16’17’18’19 found that the "expected" price of beef based on past beef prices, 14Pimentel, R., et al., Modelos Matematicos Para el Sector Agropecuario Uruguayo (Montevideo: Banco de la Republica, 1976). 15Jarvis, Lowell, "The Economic Determinants of Uruguayan Beef-Cattle Herd and Slaughter Levels 1960-1976“ (Unpublished paper, Montevideo, 1977). 16Iver, Raul E., ”The Investment Behavior and the Supply Response of the Cattle Industry in Argentina” (Ph.D. dissertation, University of Chicago, 1971). 17Jarvis, Lowell 3., “Supply Response in the Cattle Industry, The Argen— tine Case, l937/38--1966/67” (Ph.D. dissertation, Massachusetts Institute of Technology, August 1969). 18Reca, Lucio G., ''The Price and Production Quality Within Argentine Agriculture 1923—1965“ (Ph.D. dissertation, University of Chicago, 1967). 47 particularly in the previous year, is one of the most important variables affecting the supply of beef. According to these studies, farmers expect the prices of the last period of production to prevail in the current period. In their supply equations, other variables such as price of grains (substitute in production), weather conditions (proxy for pasture conditions), cattle stock, and time (as proxy for technological improvements) were also included. Most of these studies concluded that only a few variables can explain most of the variation in beef supply. Other studiesZO’ZI’22 have divided the supply of beef into two components: (1) number of cattle slaughtered and (2) average weight per animal slaughtered. Otrera analyzed the number of cattle slaughtered as a function of the farmer price of beef in current and previous years, the price of grains, and time. The average weight per animal was con- sidered to be a function of the farmer beef prices, rainfall conditions in the previous year, and time. The equations containing the mentioned variables were selected largely because of their ”high” explanatory DOWEY‘ . 19Nores, Gustavo A., ”Structure of the Argentine Beef Cattle Economy: A Short Run Model, 1930-1970” (Ph.D. dissertation, Purdue University, 1972). 20Otrera, Wylian R., ”An Econometric Model for Analyzing Argentine Beef Export Potentials” (Ph.D. dissertation, Texas A&M University, 1966). 2INores, Gustavo A., “An Econometric Model of the Argentine Beef-Cattle Economy'I (Master's thesis, Purdue University, 1969). 22Kulshreshtha, S.N., Wilson, A.G., Brown, D.N., An Econometric Analysis of the Canadian Cattle-Calves Economy (Saskatoon, Canada: Department of Agricultural Economics, University of Saskatchewan, 1971). 48 Beef Supply Equations Economic theory of supply, previous descriptive and quantitative studies particularly in Uruguay and Argentina, and the author's know- ledge of the Uruguayan beef industry provides the basis for specifying the supply functions in this empirical analysis. The supply model will consist of two behavioral relationships and one identity. This approach consists of dividing the supply of beef into two components: (1) number of beef cattle slaughtered and (2) meat yield per animal slaughtered. The identity determines total beef supply which is the product of the two components. Beef cattle supplied is postulated in the following,equations: (l) NBCS = f(FBC, CS, IP, IPC, PW) (2) MYPAS = f(FBP, IPC, IP, SERA) (3) TBS = (NBCS) x (MYPAS) where: NBCS = number of beef cattle slaughtered FBP = farmer beef prices CS = cattle stock IP = number of hectares of improved pastures in production IPC = index of pasture conditions PW = price of wool SERA = slaughter extraction rate Beef production is then postulated to be a function of several factors: (1) farmer beef prices; (2) cattle stocks, which previous studies indicate affect the number of cattle slaughtered; (3) improved pastures, which have been the only technological change that was governmentally promoted during the period of the study; (4) index of 49 pasture condition. For all practical purposes, livestock production in Uruguay is based exclusively on direct grazing. As a consequence, weather conditions affect the grazing capacity of the pastures, in- fluencing beef production. This index, constructed with climatic indicators (rainfall and temperature) is a proxy for the availability of pastures or grazing capacity. (5) Price of wool. In Uruguay, beef and sheep are produced together. At the country level, wool is the only substitute in production. In studies of the Argentinian beef industry, the price of grains, particularly wheat, was included as a substitute in production. From this point of view, the Argentinian situation is different from that in Uruguay. In most of the Argentinian beef producing areas, grains (mostly wheat) are real substitutes in production for beef. However, of the 16.6 million hectares used in livestock production in Uruguay, only 1.0 to 1.5 million are used in extensive agriculture. The total area potentially usable for grain 23 In production in Uruguay does not exceed 3.0 million hectares. addition, livestock producers do not have machinery or the ability to assume the risk involved in grain production. Great price fluctuations have determined that the area traditionally used with annual crops has not exceeded 1.5 million hectares. (6) Slaughter extraction rate. The extraction rate is defined as the total number of animals slaughtered divided by the total number of animals in stock. This variable is not included in any of the studies reviewed. In the case of Uruguay, stocks are reduced before the winter, due to reduction in pasture supply. The relationship between animals sold and total stock does 23Ministerio de Ganaderia y Agricultura, Los Suelos del Uruguay, Su Uso y Manejo (Montevideo, 1967). 50 (in the author's opinion) affect beef production. In particular, it is proposed that the slaughter extraction rate is related to the meat yield per animal slaughtered. Additionally, an identity (the product of the number of beef cattle slaughtered times meat yield per animal slaughtered) is needed for determining total beef supply. Derived Demand for Roughage The most important and practically only input used in cattle pro- duction is roughage. The agricultural frontier has long been reached in Uruguay, and the increase in pasture productivity is the way to increase this input availability. Grains are not generally an economic alternative in Uruguay. The following derived demand for additional roughage will be estimated: AGIIP = f(FBP, IR, PFF) where: AGIIP = annual gross investment in improved pastures expressed in number of hectares FBP = farmer beef prices IR = interest rates on credit PFF = price of phosphate fertilizer Farmer beef prices are believed to be an important variable affecting the decision to invest in improved pastures. At the farm and country level, cattle and sheep graze together, but the improved pastures have been and still are managed only with cattle.‘24’25’26 24Comision Honoraria del Plan Agropecuario, E1 Plan Agropecuario (Montevideo, 1972). 25Comision Honoraria del Plan Agropecuario, Anuario 1975 (Montevideo, 1975). 26Comision Honoraria del Plan Agropecuario, Anuario 1976 (Montevideo, 1976). 51 As mentioned in Chapter III, 98 percent of the beef producers who made investments in improved pastures received credit assistance. It is hypothesized that the interest rate of those credits affects farmers' investment decisions. In value terms, phosphate fertilizers represent more than 70 percent of the inputs to be used in improving pastures. Accordingly, fertilizer price is believed to have an important effect on the number of hectares of pastures improved. Demand The market demand relation describes the market behavior of con- sumers when buying a product. It indicates the amount of a product that consumers in a particular market will be willing and able to buy at different prices. This behavioral relationship between quantity demanded and prices holds under a certain set of assumptions. As in the case of supply, demand relationships are formulated, in general, under the ceteris paribus condition. This implies that the demand relationship explains changes in quantity demanded as the price of the product changes, all other factors that affect the demand of the product holding constant. Some of the major factors affecting product demand are price of substitutes in consumption, income level, population, tastes and preferences, inflation, etc. The demand relationship can be expressed in functional form as follows: d- Q - f(Pp1PS,I.P0P,TP, . . . .) where: 0d = quantity demand P = price of product demanded 52 .0 1| price of substitutes in consumption 5 I = income level POP = population TP = tastes and preferences As in the case of the supply relationship, the properties or assumptions underlying the demand function are those of comparative static economics based on the theory of profit maximization for a firm in a competitive market. Studies listing these properties have already been cited. Economic theory indicates a negative relationship between the quantity demanded of one particular product and its price. The prices of the products that are substitutes in consumption are directly related to the quantity demanded of the product that is being studied. A similar direct relationship holds for population and income. Review of Beef Demand Studies It is unfortunate that no quantitative analysis of beef demand has been performed for Uruguay. There are, however, descriptive studies indicating some of the factors affecting the demand for Uruguayan 27-35 beef. There is general agreement in these descriptive studies 27Brannon, Russell H., ”Uruguay: A Focus on Agriculture“ (Unpublished paper, 1966). 28Ministerio de Ganaderia y Agricultura, Oficina de Programacion y Politica Agropecuaria, CIDE--Sector Agropecuario, Estudio Economico y Social de la Agricultura en el Uruguay (Montevideo, 1967). 29Brannon, Russell H., ”The Role of the State in the Agricultural Stag- nation of Uruguay“ (Ph D. dissertation, University of Wisconsin, 1967). 53 that the high level of beef consumption in Uruguay is the result of the government setting the farm level price of beef at artificially low levels. The price of beef in Uruguay is substantially lower than the international price (see Chapter III). These studies single out the low farm price levels, even though no quantification is presented as the most important determinant of internal demand. It is also mentioned that the lack of beef substitutes in consumption is another reason for the perpetuation of the high levels of beef consumption. Prices of beef substitutes such as chicken and pork are higher in Uruguay than in the international market. Income and population are mentioned as affecting positively the level of beef demand. Most studies state, however, that both population and consumer income are not very important in affecting demand. 3OFletcher, L. and Merrill, W., The Uruguayan Agricultural Sector: Priorities for Government Policies, Investment Programs and Projects (Washington, D.C., 1970). 3IMinisterio de Ganaderia y Agricultura, Oficina de Programacion y Politica Agropecuaria, Cuarto Proyecto de Desarrollo Ganadero de Uruguay (Montevideo, 1971). 32Comision Honoraria del Plan Agropecuario, Quinto Proyecto de Desarrollo Ganadero del Uruguay (Montevideo, 1974). 33International Bank for Reconstruction and Development, Appraisal of the Fifth Livestock Development Project Uruguay (Washington, D.C , 1976). 34Hunting Technical Services Limited, and Oficina de Programacion y Politica Agropecuaria, Agricultural Diversification Study--Uruguay (Montevideo, 1976). 35International Bank for Reconstruction and Development, Appraisal of Agricultural Diversification Project--Uruguay (Washington, D.C., 1976). 54 Quantitative studies of demands have been conducted in Argentina. Beef production and consumption patterns in Argentina are similar to those of Uruguay. Guadagni36 in 1964 estimated a demand relation for beef with per capita beef consumption as a dependent variable. He used price of beef, price of pork, price of lamb, per capita income, and per capita consumptiop lagged QHEH¥SE:MEE.IPIEEEEQED¢ variables. He found that the most significant variable affecting consumption was the price of beef. Income was less important, and the price of beef sub- stitutes was found to be even less significant. He concluded that “the high consumption of beef in Argentina makes it inelastic to changes in per capita income.“ He further concluded that in Argentina there is a lack of true substitutes for beef. Otrera37 estimated the domestic demand for beef where price of beef was a function of total beef supply, total domestic consumption of beef, time, per capita national income, and population. His findings were similar to those of Guadagni. The price of beef was the most important variable affecting domestic consumption. Otrera included an export demand for beef in his model. He used quantity of beef exported as the dependent variable and total beef supply, internal price of beef, and the Argentinian population as explanatory variables. Use of the internal beef price in the export demand equation instead of the international or export price of beef 36Guadagni, A.A., ”Estudio Econometrico del Consumo de Carne Vacuna en Argentina en el periodo 1914—1959" Desarrollo Economico 3 (1964). 37Otrera,Wylian R., "An Econometric Model for Analyzing Argentine Beef Export Potentials” (Ph D. dissertation, Texas A&M University, 1966). 55 implies that the quantity of beef exported is the residual after satisfying domestic consumption. No role is given to the international price in determining the quantity of beef to be exported. A contrasting point of view in the treatment of the export demand for beef was presented by Nores.38 His study considered exports as playing an active role in the mechanism of beef price formation at the farm level. He proposed an export demand equation in which the inter— national demand for Argentinian beef is a function of the price of Argen- tinian beef, the price of beef offered by supply—competing countries, the aggregate disposable income of beef-importing countries, and the farmers' beef price in importing countries. In the case of Uruguay there are no quantitative evaluations of the international demand for Uruguayan meat. However, almost all descriptive analyses recognize explicitly or implicitly that the amount of beef available for exports will be the surplus above the traditional level of domestic per capita consumption. The fourth and fifth Live- stock Development Projects prepared by the government of Uruguay state as their main objectives: ”To provide technical and credit assistance to cattle producers to increase beef production. Increased beef pro- duction will make available more beef for exports.” In an evaluation report of the Livestock Development Project of Uruguay conducted by the World Bank, a similar conclusionwasreached.39 38Nores, Gustavo A., ”An Econometric Model of the Argentine Beef-Cattle Economy“ (Master's thesis, Purdue University, 1969). 39International Bank for Reconstruction and Development, Uruguay Third and Fourth Livestock Development Projects (Washington, D.C., 1976). 56 It concluded that due to the fact that the level of beef consumption in Uruguay has always been a political issue in which the consumer has been the winner, exports of beef will not increase unless beef produc- tion is increased. This point of view, considering Uruguayan beef exports a surplus over and above domestic consumption, is shared in 40’41 These studies appear to suggest for the Uruguayan other studies. beef export demand a similar model to the one used by Otrera in Argentina. Beef Demand Equations Considering traditional economic theory and the findings of previous studies conducted in Uruguay and Argentina, the following specifications for the Uruguayan domestic and export beef demand are proposed: (1) BDIC = f(RPB, PC, PP, GNI, POP) where: BDIC = beef demand for internal consumption RPB = retail price of beef PC = price of chicken PP = price of pork GNI = gross national income POP = population (2) BDE = f(PCBC, TBS, POP) 4OComision Honoraria del Plan Agropecuario, E1 Plan Agropecuario (1972). 4IMinisterio de Ganaderia y Agricultura, Oficina de Programacion y Politica Agropecuaria, Lineamientos de Politica Agropecuaria (Montevideo, 1972). 57 where: BDE = beef demand for exports PCBC = per capita beef consumption TBS = total beef supply POP = population The total quantity of beef demanded is equal to the sum of the demand for domestic consumption plus the demand for exports, or (3) TBD = BDIC + BDE The complete system consists of the following seven relationships: four behavioral equations (number of beef cattle slaughtered, meat yield per animal slaughtered, domestic demand for beef, and export demand for beef); two identities (total beef supply=number of beef cattle slaughtered times meat yield, and TBD = BDIC + BDE), and a market clearing condition (total beef supply=tota1 beef demanded). The Statistical Model Economic theory suggests the directional effect that some variables have upon others. Those effects were presented before when an economic model with its behavioral relationships was postulated. A statistical model to quantify the economic behavior of the variables affecting the beef—cattle sector is presented here. From a mathematical point of view, a linear functional relationship between the variables is postulated. In general terms the linear model can be considered as followsz4‘2’43 42Kelejan, H., Oates, W., Introduction to Econometrics, Principles and Applications (New York: Harper & Row Publishers, 1974). 43Neter, J. and Wasserman, W., Applied Linear Statistical Models (Homewood, Ill.: Richard 0. Irwin, Inc., 1974). 58 Yt =12] Bixit+Ut t = l n where: Yt = dependent or endogenous variable it = independent or exogenous variables Bi = coefficient or parameters of the independent variables, indicating the effect of the independent variables on the dependent variable Ut = the random terms. They represent the effect of the independent variable left out of the equation or the measurement errors of the dependent variable. For the purposes of this analysis, some assumptions related to the variables and the error terms of the equations in the model are made. All values of the independent variable should not be the same. This enables us to observe the changes in the dependent variable when Xt changes and therefore to estimate the parameters. Also, no exact linear relationship is expected to exist among X Otherwise, t' a problem of multicollinearity will arise. The expected value of the error term is assumed to be zero. The error terms are assumed to be normally distributed. The variance of the error term is constant (homoscedasticity). The previous assumption characterized the error term as an unobservable random variable with mean zero and constant variance and with the property that its value in some instances is independent of its value in another instance and then uncorrelated. Additionally, it is assumed that the error term is independent of all the values of the regressor, which implies a zero covariance with them (nonautoregression). 59 The specification of the relationship between the dependent and independent variables plus the previous assumptions constitutes the basic general statistical model. The equations that will be estimated are particular cases of this model. Equations and Variable Definitions Due to the lack of statistical models for the Uruguayan beef cattle economy, a very general and exploratory model is presented. All variables that are believed to have some effect in each equation (based on previous knowledge and studies in other countries) are in- cluded and will be tried in the empirical analysis. At that time only the equations including variables with greater explanatory power will be included. Eguations Beef Supply Number of beef cattle slaughtered. l) NBCSt = f1(FBPt,FBPt1,PWt,PWt_],IPt,Pt_],IPCt,IPCt_1,CSt,CSt_1) i=1. . . 5 i=l,3,4 Meat yield per animal slaughtered. 2) MYPASt = f2(IPCt,IPCt_],IP,IPt_],FBPt,SERAt) Total beef supply identity. 3) TBSt = NBCSt x MYPASt 60 Beef Demand Beef demand for international consumption. 4) BDICt = f3(FBPt,PCt,PPt,GNIt,POPt) Beef demand for exports. 5) BDEt = f4(FBPt,TBSt,POPt) Total beef demand identity. 6) TBDt = BDICt + BDE Market clearing condition. 7) TBSt = TBDt The variables used in the equations are defined below. The sym- bols used were previously defined in this chapter. Variable Definitions Endogenous Variables NBCSt = number of beef cattle slaughtered measured in thousand head per year MYPASt = average meat yield per animal slaughtered measured in kilograms/animal of carcass weight equivalent BDICt = quantity of beef demanded for internal consumption in thousand tons of carcass weight equivalent BDEt = quantity of beef demanded for exports in thousand tons of carcass weight equivalent Exogenous FBPt Pwt-l IP IPt-l IPC Ipct_1 SERAt PC PP GNI POP 61 Variables farmers' beef prices in new Uruguayan pesos per ton divided by the consumer price index farmers' beef prices as previously defined, lagged different numbers of years farmers' wool prices in new Uruguayan pesos per 10 kilo- grams, divided by the consumer price index farmers' wool prices as previously defined, lagged one year improved natural pastures in thousands of hectares in production, each year improved natural pastures, as previously defined, lagged one year index of pasture conditions, presented as an annual coefficient of availability of roughage index of pasture conditions, as previously defined, lagged one year slaughter extraction rate, percentage of total beef cattle stock slaughtered each year. price of chicken in new Uruguayan pesos per kilograms divided by the consumer price index price of pork in new Uruguayan pesos per ton divided by the consumer price index gross national income in millions of Uruguayan new pesos divided by the consumer price index Uruguayan population at June 20, in thousand inhabitants 62 An a priori specified sign for the coefficients of the variables in the equations is proposed. The sign refers to the parameters of the variables that are listed: NBCS Equation FBPt FBP >O, PWtO, IP >0, IPC <0, t-5 1 t-1 t IPC <0, CS >0, CS 0 t—l t t-1> MYPAS Equation IPCt>O, IPCt_]>O, IPt>O, IPt_]>O, FBPt>O, SERAtO, PPt>O, GNI>O, POP>O BDE Equation FBPt>O, TBSt>O, POPt 000000000 0000 000>-0>00V 00000: 000 0005000000 000000 00000 000 00oo0m 00000000000 000 0000000000002 000 000050000 000050000 _.m m0m<0 74 00.0 00.0 00.0 00.0 30 00. 00. 00. 00. 0a 00.0 0.0000 00.0 c.0o0 . 00.0 0.0000 00.0 0.0000 00000000 00.0 0000. 00.0 00mm. 00.0 0000. 00.0 000m. 00 00.0 0000.1 00.0 0000.- 00.0 0000.1 00.0 0000.1 x000 0000.1 0000. 0000.1 0000.1 50m 00. 0000. 00.0 0000. 00. 0000. 00. 0000. 001000000 00. 0000. 00.0 0000. 0m. 0000. 00.0 0000. 001000000 00.0 0000. 00.0 0000. 00.0 0000. 00.0 0000. 001000000 00.0 0000. 00.0 0000. 00.0 0000. 00.0 0000. 001000000 00.0 0000.1 00. 0000.1 m0. 00_o.1 00.0 0000.1 001000000 00.0 0000.1 00.m 0000.1 00.0 0m00.1 00.0 0000.1 001000000 00000 .0 .00000 00000 .0 .00000 00000 .0 .00000 00000 .0 .00000 0000000> 000000 000 000000 000 000000 000 000000 000 00000000000 00000000000 000000000000: 0000000000m 000000 000m 00 000502 ”0000000> 000000000 0000 000>1x0mv 00000: 000 0005000000 000000 00000 000 00oo0m 00000000000 000 0000000000000 000 000050000 000050000 0.m m0m<0 75 These values indicate inconclusive tests for autocorrelation; in other words,the hypothesis of no autocorrelation has to be rejected. The value and high statistical significance of the parameters not included in the lag structure are another reason for the selection of this equation. The estimated equation for the number of beef cattle slaughtered follows. Below the estimated parameters, their respective standard errors appear in parentheses. Parameters which are more than twice their standard error are indicated with a double asterisk. One asterisk indicates parameters which are larger than their error terms. The Durbin—Watson statistic test for autocorrelation is represented by the letter d. The computed d value has an a attached if the hypothesis of no autocorrelation has to be rejected in favor of the alternative hypothesis of autocorrelated disturbance terms. The letter i indicates an inconclusive test, and the letter n indicates the nonrejection of the hypothesis of no autocorrelated disturbance terms at the 5 percent level of significance. (1) most = 805.97l-0.2577**FBPR( —0.0398 FBPR( +O.l08l*FBPR( t—l) t—2) (368.7ll) (0.0756) (0.0583) (0.0594) t-3) ** ** *‘k * + 0.l86l FBPR( +O.l940 FBPR( +0.1320 FBPR( -0.5802 IPCXt t-4) t-5) t-6) (0.0609) (0.0533) (0.0334) (0.3089) ** + 0.3338 IPt (0.0937) 'fi2 = 0.77 d = 2.33(n) where: FBPR farmers' beef price deflated by the consumer price index IPCX ll first difference for the index of pasture conditions IP total number of hectares of improved pasture in production 76 The effect of beef prices on the number of beef cattle supplied for slaughter is negative for two years and positive thereafter. The total magnitude of the effect of price on number of cattle slaughtered is expressed in terms of the price-slaughter supply elasticities. The short—run price elasticity of slaughter is -0.26, and the long-run elasticity is 0.32 (see Table 5.3). The results presented in the table indicate that if the price of beef increases (decreases) by l0 percent, beef cattle slaughtered will decrease (increase) by 2.6 percent in the following year. It will take, with the production conditions prevailing in Uruguay, four years to regain the level of slaughter supply existing at the moment of the price increase. After six years, the total number of beef cattle slaughtered will be in— creased (decreased) by 3.2 percent. TABLE 5.3 Simple and Cumulative Price Elasticities of Total Slaughter Time Dependent Variable FBPR FBPR Period Simple Elasticity Cumulative Elasticity t-l -O.26 —O.26 t-2 -0.04 -O.3O t-3 0.ll -O.l9 t-4 0.l9 0.00 t-5 0.l9 0.l9 t-6 0.l3 0.32 77 Capital investment in any industry is generally a positively sloped function of the market price of the product that the industry produces. The cattle industry presents a unique characteristic when compared with most other industries. Its product is both a consumption and an investment good. When the price of beef increases, we would expect the capital stock to increase. The farmers make the capital stock investment withholding animals from slaughter in order to increase future production, which implies a short-run supply of animals for slaughter with a negative price elasticity. In the long run, however, as production increases, supply of cattle for slaughter also becomes higher than previous levels. The long-run supply of cattle will then present, in contrast with the short-run supply, a positive price elas- ticity. However, most previous studies have found both short and long- run negative price supply elasticities of cattle for slaughter. Jarvis1 estimated an equation to explain the number of beef cattle slaughtered in Uruguay each year between l960 and l977. He lagged the price of beef one year, but other lag periods were not included. The estimated short-run price elasticity of slaughter (year t-l) was —O.30l. Table 5.4 shows that the short-run price elas- ticity of slaughter estimated by Jarvis in Uruguay is very similar to the one estimated in this study. No other similar studies have been done in Uruguay; nevertheless, there are various Argentinian studies on cattle-supply response to beef prices. 1Jarvis, Lowell S., "The Economic Determinants of Uruguayan Beef-Cattle Herd and Slaughter Levels, l960—l976” (Unpublished paper, Montevideo, l977). 78 TABLE 5.4 Short and Long-Run Price Elasticities of Slaughter Estimated in Previous Studies Elasticity Author Country Study Period Short-Run Long-Run Jarvis Uruguay l960-76 — 0.30 n.e.a Reca Argentina l923-47 n.e. - 0.36 Nores Argentina l935-66 0.003 - 0.3l4 Iver Argentina l937-67 - 0.l6 l.l4 Otrera Argentina l945-64 - 2.48 - 2.66 Reca Argentina l948-65 n.e. - 0.2l This Study Uruguay l956-75 - 0.26 0.32 an.e. = not estimated. The main discrepancy between this study and those done by Reca,2 Nores,3 and Otrera4 in Argentina lies in their findings of a negative long-run price elasticity of slaughter. These Argentinian studies imply a behavior of the cattle industry which is inconsistent with the observed Uruguayan situation. In Uruguay,5 Argentina,6 and other 2Reca, Lucio G., "The Price and Production Duality Within Argentine Agriculture l923-l965” (Ph.D. dissertation, University of Chicago, l967). 3Nores, Gustavo A., "An Econometric Model of the Argentine Beef-Cattle Economy” (Master's thesis, Purdue University, l969). 4Otrera, Wylian R., "An Econometric Model for Analyzing Argentine Beef Export Potentials” (Ph.D. dissertation, Texas A&M University, l966). 5Secco, Garcia J. and Perez, Arrarte C., ”El Ciclo Ganadero," Revista de la Asociacion de Ingenieros Agronomos (Montevideo, l975). 6Iver, Raul E., "The Investment Behavior and the Supply Response of the Cattle Industry in Argentina" (Ph.D. dissertation, University of Chicago, l97l). 79 countries,7 it has been indicated that cattle firms actually behave following economic investment theory. When the price of beef increases, the farmers increase their capital stock (reducing the number of cattle supplied for slaughter). Once the investment in capital stock results in increased production (a process that can take between 3 to 6 years depending on the production technology), the number of cattle supplied for slaughter exceeds the level of supply existing before the price increase. This result implies a positive long-run supply elasticity of slaughter. Iver used a polynomial distributed lag model in which the farmers' beef price was lagged for five years. The positive long—run supply elasticity of slaughter is much greater than the elasticity estimated for this study (Table 5.4). Some of the factors which can account for the discrepancy include the fact that Argentina's cattle production is similar to Uruguay's cattle production, but still some differences remain. Second, length of run of the distributed lag structures is different. Third, a single equation technique is used in this study to estimate the number of beef cattle slaughtered,whereas Iver used a simultaneous equation approach to estimate the system of equationsin which he disaggregated beef-cattle slaughter. Meat Yield Per Animal Slaughtered Several variables were postulated as affecting the meat yield per animal slaughtered. The farmers' price of beef, the number of hectares 7Kalaitzis, Vassilios C., "An Econometric Analysis of the Feed-Grain Livestock Economy of Greece” (Ph.D. dissertation, Michigan State University, l978). 80 of improved pastures in production, the cattle stock, the index of pas- ture conditions,and the slaughter extraction rate were among the explana- tory variables that were tried in different combinations and forms of expression. The resulting equation for meat yield per animal slaughtered is: * 'k (2) MYPASt = 230.530+O.4507 *IPCXt-O.l845 *SERAt (5.799) (0.0745) (0.035l) where: IPCX = index of pasture conditions SERA = slaughter extraction rate R2 = 0.86 d = l.68(n) Higher values of the index of pasture conditions indicate more availability of roughage. As more roughage is available, the average meat yield per animal slaughtered increases. This is explained by the fact that in Uruguay, raising and fattening of cattle is done by direct grazing. No practice of forage reserves is followed, and all the potential livestock areas are already in use. The introduction of improved pastures has helped to reduce seasonal fluctuations, but they still represent a small percentage of the total grazing area (ll percent). Given this situation, the climatic conditions play an important role in determining forage supply and therefore in the yield that fattening animals can reach. The slaughter extraction rate (SERA) is defined as the total num- ber of animals slaughtered divided by the total number of animals in stock. This variable is also related to the problem of lack of adequate quantity of roughage. In the case of Uruguay in most years, the extrac- tion rate is an indication of the percentage of animals that had to 8] be sold before being finished due to a lack of forage rather than to an index of high productivity. This explains the negative relation- ship between SERA and the meat yield per animal slaughtered. In Argentina, Otrera and Nores found that the climatic conditions significantly affect the yield per animal slaughtered. The slaughter extraction rate was not included in their equations. The Derived Demand for Roughage Since practically no silage or hay is produced in Uruguay, the derived demand for additional roughage is referred to as the demand for inputs to improve the country's natural pasture. This demand is measured in terms of the annual gross investment in improved pastures expressed in hectares. The farmers' beef price, the price of phosphate fertilizer (the fertilizer used for improving pastures), and the interest rate were used for this equation. The chosen estimated equation is: AGIIPt = l48.000+0.2664**FBPRFt—l8.52l3**IRRt (40.736) (0.l094) (3.3470) where: FBPRF= farmers' beef price/price of phosphate fertilizer IRR = real rate of interest R2 = 0.80 d = 1.92(”) The annual gross investment in improved pastures as measured in number of hectares improved(AGIIPt)is significantly affected by the price of beef, the price of phosphate fertilizer, and the real rate of interest. 82 When the relationship farmer beef prices/price of phosphate fer- tilizer, both deflated GBPRF),increases, so does the investment in pasture improvement. No Uruguayan study has quantified this relationship, but different documents indicate this positive relationship. The relation— ship farmer beef prices/price of phosphate fertilizer has varied since l96l between l.6 and 3.6. Higher values of this relationship coincide with a higher number of hectares of pastures improved.8’9’]0 The parameter estimate for the real rate of interest has an impor- tant and highly significant effect statistically on the explained variable AGIIP. Between l96l and l968, the nominal rate of interest on loans for pasture improvements varied between ll and 26 percent. In the same period, Uruguay had a high annual rate of inflation. With only the exception of l968, the inflation rate has been higher than 50 percent. This resulted in a negative interest rate, especially when it is considered that the loans had two years'grace period for the principal and five years to be repaid. In 1969 an indexing system was introduced, but the way in which it was applied and the indicators that it had as a base determined that the interest rate still continued to be negative for most of the years. According to a World Bank study, the imperfect indexing system applied since I969 has still resulted in 8Ministerio de Ganaderia y Agricultura, Oficina de Programacion y Politica Agropecuaria, Cuarto Proyecto de Desarrollo Ganadero (Montevideo, l97l). 9Comision Honoraria del Plan Agropecuario, Quinto Proyecto de Desarrollo Ganadero del Uruguay (Montevideo, l974). 10Ministerio de Agricultura y Pesca, Conclave l977 (Montevideo, l977). 83 an average negative interest rate of approximately l0 percent.H Since the controlled price of beef has not been an incentive for investment in the livestock sector, it appears that the negative rate of interest on loans offered by the government for improved pastures technology has taken that investment incentive role. The effect of these loans has been important in the introduction of this technology if it is considered that,first, 98 percent of the producers who invested in improved pastures received government loans, and, second, that practically no other source of credit either from the government or from the private sector existed for investment in the livestock sector. Subsidies for phosphate fertilizer have also existed in most years. The role of the fertilizer subsidy for investment has been similar to that of the credit subsidy. That is, when the subsidy for phosphate fertilizer was reduced, it had an effect that was similar to that of reducing the price of beef. When the interest rate due to varying inflation became less negative, it had a similar effect to that of reduced beef prices. Testing the Supply Equations One of the important uses of the estimated equations is to fore- cast what change can be expected to occur in the dependent variable in terms of direction and magnitude, when the value of one or more of the independent variables varies. This is particularly important in the case of Uruguay where some of these variables are government HInternational Bank for Reconstruction and Development, Uru uay Third and Fourth Livestock Development Projects (Washington, D.C., l976). 84 controlled. 0n the other hand, the traditional view of government policies in Uruguay toward the fact that beef exports are the residual, after internal consumption has been satisfied, puts the emphasis on increasing beef production if a higher level of exports is to be achieved. The evaluation of the forecasting ability of the supply model is achieved using a graphical technique and Theil's U-coefficient of inequality.12 A desirable feature of the model is its ability to predict turning points in the event or variable that is under study. Four possibilities can be identified with respect to prediction of turning points: (i) correct prediction of a turning point, i.e., a predicted turning point actually occurring; (ii) incorrect prediction of a turning point, i.e., a turning point is predicted when there is no actual turning point; (iii) a turning point is not predicted, but an actual turning point does exist; and (iv) correct no prediction of a turning point, i.e., a turning point is not predicted when a turning point does not exist. Cases (ii) and (iii) represent failure in prediction of turning points, and they are described as Type I failure (Q1) and Type II failure (02) respectively. Q1 (ii) 02 - (iii) W (1 +(iii 12Theil, H., Economic Forecast and Policy (Amsterdam: North Holland Publishing Company, l965). 85 01 represents the set of predicted turning points that contains no actual turning points. 02 represents the set of actual turning points that contain no predicted ones. These are quantitative measures of the failure to forecast a turning point with the following value range 05010251. If any of the predicted turning points coincide with the actual points 01 and 02=l, then small values of Q1 and 02 indicate the presence of a successful turning point. The values of Q1 and 02 are small for the estimated supply equa- tions. In particular,a perfect turning point forecasting is achieved in the identity equation explaining total beef supply (see Table 5.5). The graphical analysis is based on the actual and predicted values of the supply equation as presented in Figure55.l, 5.2, 5.3, and 5.4. TABLE 5.5 Ability to Forecast Turning Points Supply Equations (Quantitative Measure of Graphical Analysis for Supply Equations) Variables Actual Predicted Turning Point N0 Turning Point 01 02 NBCS Turning Point (i)=5 (iii)=l No Turning Point (ii)=l (iu)=5 0.l7 0.l7 MYPAS Turning Point (i)=8 (iii)=l No Turning Point (ii)=l (iu)=4 0.ll 0.ll TBS Turning Point (i)=7 (iii)=0 No Turning Point (ii)=0 (iu)=5 0.00 0.00 AGIIP Turning Point (i)=2 (iii)=l N0 Turning Point (ii)=l (iu)=8 0.33 0.33 86 .uwgwpcmszm mFPHmu comm mo LwaE:z on P as: me we mw=_m> cmumewumm mw:_m> Fmapu< ._.m aczaca o—_ cONF oom_ 8: 9; _ some ooNF comp .82 SDSN 87 :8? ma_ 2a, _»m_ .eacau;m=a_m _mec:< 28a e_aw> paw: Ofia_ ama_ mace mam— Ama_ owm_ momp .N.m aczmca vom— mom— Nom— mw:_m> vmpmswumm mm:_m> _m=po< owr wa Lb on ,_ v OFN mrm SVdAW (qualeAInbg $523423 sweafioltx) 88 TBS (000 MT) 370‘ ._______.———.Actual Values ----— - -- Estimated Values 360, 350_ 340_ 330. A I I \ 320. 1’ \i I \ / \ / \ 310, / ‘ I ‘ I I ‘ I h I ‘ I 300, I “~. I ‘ I / '1 I ‘ I ’ \ I ‘ ' X \ I ‘ ’ 290‘ / \ I i l/ \ I \ \ ' ‘ l ’ ‘ 280 I ‘ 4 l ‘ ‘ I \ I \ \ I \\ 270 \ I ‘ i \ I \ \ I ‘v \ I 260 l ’ -4 ‘ I] \ I 250i ‘ I, K\ I \ \ \ 240. 230 . ‘ .T , , , . . . 1963 64 65 66 67 68 69 70 7l 72 73 74 75 Time Figure 5.3. Total Beef Supplied. 89 .moczpmmm vw>ocaEH cw “cospmm>cH mmocw Fmscc< .v.m mgzmwu 2.: mm «m mu mm —m om mm mm mo:_m> umumswumm IIIIIII mw:_m> —m:uo< om ron: vom— com ‘omm com .fi mmm dIIBV ) (saaeqoaH 000 90 The Theil's coefficient of inequality or U coefficient is used here to measure the ability of the model to forecast the course of the future supply of beef in the cattle industry. The Theil's U coefficient is calculated as follows: u l/n 22:] (Pt - At)2 l/n 22:] PE + l/n 22:] A: where: Pt = predicted value of the th observation for t=(l . . . .n) At = actual value of the th observation for t=(l . . . .n) When all predicted values of P are equal to all actual values of t A U=0, we have total equality or a perfect forecast. The opposite t’ case occurs when we have maximum of inequality; then U=l. In this latter case no worthwhile forecast can be made since the model is not able to accurately predict the past. Between 0 and l, the closer the U coefficient is to zero the better the forecasting ability of the model. In our case the U coefficients are very close to zero, which supports the contention that the model's forecasting accuracy should not be suspect (Table 5.6). TABLE 5.6 Theil's U Coefficient of Inequality for the Supply Equations Variable Variable Name Coefficient NBCS Number of Beef Cattle Slaughtered 0.0323 MYPAS Meat Yield Per Animal Slaughtered 0.007l TBS Total Beef Supply 0.0373 AGIIP Annual Gross Investment Improved 0.ll92 Pastures 91 Beef Supply Forecasting Most of the factors affecting the supply of beef are controlled by the government. Of these variables, the most important factor is the farmers' beef price. This price has been traditionally low (according to the international price level) to protect urban consumers. Different assumptions are made with respect to alternative government beef price policies. Each alternative is evaluated in terms of the supply of beef that would result: Alternative l: increase of 25 percent in the price of beef; Alternative 2: increase of 50 percent; and Alternative 3: increase of the price of beef to the export or international beef price. (Once the price is increased it is assumed to remain at that level throughout the forecast period.) Alternative 3, which represents the highest price increase, is equivalent to letting the market set the price. It is also assumed that an infinite quantity of Uruguayan beef could be sold in the international market. The increase of the price of beef will directly affect the supply of cattle for slaughter first through the herd buildup (reduction of supply), later through an increase in the supply (after the third year), and indirectly through the effect on investment in improved pastures. The number of improved pastures in production affects the total cattle supply for slaughter. Assuming all other factors constant, the direct and indirect effects of an increase in the price of beef will result in a net increase in the total quantity of beef supplied after a four-year period. If Alternative l is followed, the quantity of beef supplied will increase in a period of six years by 7.0 percent, 25,800 tons of carcass weight equivalent. If Alternative 2 is chosen, the increase 92 will amount to l4.l percent or 51,800 tons. Alternative 3 will yield an increase of 104,000 tons of beef supplied. The importance of this increase in supply is that all of the increased quantities would be exported. Actually, when the price of beef increases, local consump- tion will decrease making even larger the amount of beef available for exports. It is important to notice, though, that higher production increases require higher investment in capital stock. This would further imply a greater reduction in beef supply during the first two or three years (see Table 5.7). The forecast was made for a six-year period starting in l976 since no actual data were yet available for beef supply in l977 and l978. Nevertheless, the direction and magnitude of the forecast change is not affected from a practical point of view if those two years had been available and the forecast were extended to 1984. TABLE 5.7 Forecast of Beef Supplied Under Different Assumptions of Beef Price Increases and of Interest Rate (000 M.T.)a Increases in Beef Prices To Export Price and Years 25%b 50%b To Export Priceb % Real Interest Rate l976 367.0 367.0 367.0 367.0 l977 345.8 324.4 28l.8 27l.8 l978 34l.7 3l5.4 266.2 255.3 l979 353.9 340.6 3l4.6 304.4 l980 372.9 378.5 396.2 380.l l98l 386.4 405.5 444.2 434.2 l982 392.8 4l8.8 47l.0 46l.0 aThousandsof metric tons. bSubsidized interest rate of loans for improved pastures. 93 Other factors such as the price of phosphate fertilizer and the interest rate on loans for establishing improved pastures, also con- trolled by the government, affect the total supply of beef. Both factors have been traditionally highly subsidized. In the previous estimation of the yield of different courses of action in relation to the beef price, the market price (without subsidy) of phosphate fer— tilizers was used. The interest rate used was the subsidized one. If the price of beef is allowed to reach the level of the inter- national market (at FOB Montevideo prices), the price of phosphate fertilizer is the ongoing market price,and the interest rate reaching real terms is assumed to be 8 percent. The beef supply will then increase 26 percent over a period of six years (see Table 5.7 and Figure 5.5). The previous assumptions are very close to those that the free market mechanism will set for prices of product and inputs that affect the supply of beef in Uruguay. The magnitude in the change of the value of the exogenous variables that these assumptions imply is significant, for the farmers' beef price represents doubling its l975 level. A similar change will result from the interest rate, which would increase by almost two and a half times its l975 level. Price of fertilizer would remain at the market price of l975. The market mechanism would allow the increase in exports by some 94,000 tons of beef per year during a six-year period. At l975 prices this increase would represent an additional income for the country of l06 million U.S. dollars. The total dollar figure for all Uruguayan exports was 385 million for l975 and was estimated to be around 600 million for l977. Nm — .Amcou o_prE Ucmm305p :wv argazm wmwm quOH ammowLOm ucm Fmauo< .m.m wL:m_d meme Fm ow mm mm mm ox mm «A MR Nu FR Om me me No we me we moor s . . > . . . . . ooa 0mm .oov omv N3 IIIIIIII 90m l ..... 1|.II omv mo_cm “Loaxm 0H mcowuoazmm< mmmmcocfi mowca comm (IN 000) $81 95 The Estimated Demand Equations Two demand equations and one identity determine total demand in this study. The two estimated equations are: (l) beef demand for internal consumption, and (2) beef demand for exports. The identity that determines total demand is the product of both equations. Beef Demand for Internal Consumption Several factors are implied in economic theory and in previous studies for other countries as affecting the demand for beef. In par— ticular, the retail price of beef, the price of beef substitutes in consumption, and the level of income per capita are considered deter- minants of the demand for beef. Previous descriptive studies and the author's knowledge of the beef—cattle industry of Uruguay indicate that from a practical point of view no beef substitutes in consumption exist in Uruguay. At the same time, many have contended that the income level has not significantly affected beef consumption. This argument is based on the fact that the government, for political reasons, has always made beef readily avail— able to the Uruguayan population, which enjoys one of the highest levels of beef consumption in the world. Despite the fact that the previous statement appears in all the literature on the subject, a quantification has not been established. For this reason, different equations were tried including all variables that, at least from a theoretical point of view, affect the consumption of beef. Beef demand for internal consumption is expressed in terms of the per capita beef consumption in kilograms. The prices of beef, pork, chicken, and fish in Uruguayan pesos are deflated by the consumer price 96 index. The level of income is in per capita terms and is also deflated by the consumer price index. The quantity of beef exported is also investigated as an explanatory variable. The only parameter found to have a statistically significant effect on beef consumption is the parameter for the retail price of beef. The price of beef substitutes, per capita income, and the quan- tity of beef exported were not statistically significant in any of the equations, and some of them appear with the wrong expected sign (see Table 5.8). This result appears to confirm the arguments presented in various descriptive studies of the Uruguayan beef sector. All the equations have a very low R2. This is probably due to the failure to represent all the forms of government intervention taken to protect the urban consumer. Implicitly or explicitly, the govern- ment's target has always been to assure a high level of domestic beef 13 the consumption. In the national development plan for 1973-77, government set as an explicit target to reduce domestic consumption from the historical average of around 75 kilograms (l65.4 pounds) to 65 kilograms (143.3 pounds) per capita per annum. The reason was to increase the amount of beef exported. The target was not achieved.14 Since 1974, the beef consumption has been over 80 kilograms (176.4 pounds) per capita per year. No government appears to have been able 13Ministerio de Ganaderia y Agricultura, Oficina de Programacion y Politica Agropecuaria, Lineamientos de Politica Agropecuaria (Montevideo, 1973). 14Ministerio de Agricultura y Pesca, Conclave l977 (Montevideo, 1977). 97 xcoa mo mowga n ma; :mx8wco no mo_ga n mum uwugoqxw wmmn we zuwucmzc u xmmo gm.c co aocca n ma; mEoucw muvgmo Log n Hum memo we wowga _wmpoc u mmam .xmucr woven Lossmcou An cops—wow wEoucw ccc mmowcu —_< Acvmo.m e¢.o u Amoao.ov AmN.av a mmamxtkmn_.o - waa._a ” Qmua Amv A5m: _e.o p Aammo.ov p Ammem.ov a Ammmo.ov Aam.wv a xmmo mm_o.o - mHoa NA8_.O + «mamawmke_.o - .aem.om u umua Aev Aevmm.fi 44.0 a AFNN_.QV a Amom.ov a A_mmo.ov Amq.mv a mag mm~_.o + mfiua wpm.o - «mamwkmaw_.o - waaa.om n umua Amy Acvmw._ m¢.o u Amemm.ov p ANFm.ov a Acma.ov a flammo.ov Aom.mv 8 «am m8m_.o + «ca amo.o + «Hum aom.o - mmax.4NmAF.o - 44mm.am u umua Amy B Ammm.mv u Akmmo.ov a Aemkm.ov a Aomam.ov p Amom._v p Aommo.ov Amm.mv a Avaw.F 8¢.o muaumom.o + xumo Ao_o.o - mam FNoN.o + maa_kmo.o + mHua mmm.o - mmamtamem_.o - stow.ow u umua A_v a_aacta> v mm mmpnmwcm> ucmwcmamvcH pcmEaawo mcowpmzcm ucmsma wmmm owpmwsoo m.m m4mw:cm Hgmwmz mmmocmum .oxmsmzcs meowpuEmgmz mo—mvoz ..Fm pm _mp:mswa ”mcowawucoo mczammm we xmvcH owcmzuw o; < Louuwm pm new .ovgmzowaoem< :MFQ use mmpcmm>oswm we Fm:o_omz cowuumcmo n>_aa:m wwmm ucm cmunmzm—m .ommF vcm .oom_ .FomF .omm_ mowcmzomgocmoswm ww _m:owomz :ovoomgwo nm—upmu mo xuoum ”mocaom nnw._ om_.F m.mcm m.wom m.o— o.mmm._ o.mom.__ mum” Ame.” Noo.F m.nom o._om m.¢_ o.mmm.~ o._mm.o_ «NmF NmN._ noo._ n.~c~ o.mON m.m_ o.oom._ N.oom.m mum” man._ oFo._ m.o- o.mom o.<_ o.~om._ m.mm~.m N~o_ mom.p mvo.— _.mmm m.Nm_ o.w— o.om¢.F o.mNN.m _Nm_ mem._ mFo._ 0.0mm m.mm_ m._~ o._~w._ “.moo.w onF Amo.— mko._ _.m_m m.mom N.w_ o.wmm._ o.Foo.m mom— mmm.F Nma.o o.m~m o.mm_ m.w_ o.omm._ o.~mo.w moa— mom.~ owm.o m.omm m.mom ¢.m_ o._m_._ 0.0Nm.w Nom— eoo.— Nmo._ o.wm~ o.m_m m.m_ o.~o_._ N.nw_.w mmm_ m_v.— mma.o N.Nam m.~w_ m.m_ o.< cmucmszm «emu; :m_m mxoOpm mpupmu x_aazm wmmm _mp0H use .pgmwmz mmmcw>< .gmugmsmfim .xooum mFQumu < m4mwscm ucmwmz mmmocmum .mow_nsamm m_ on cauwmcm>wcs .mwowmmm meowum_umpmm Amsmscz umEoocH chovpmz mmocu Ucm cowpm_=aom cmxmamscz .mwcmzowgoem< mowpw_om A cowomEmLmoca mu acwowwo ”cowpaazmcoo chcwucH ”mwogzom 116 N.NNN.N m.mw o.qmm.m m.omm mNmF m.om¢.¢ m.om m.m¢m.m m.o—N amm— m.nmm.m m.mm _.mmm.N o.wn_ mmm_ N.mmm._ m.mo w.o~m.m w.NNF Nmm_ “.mmm N.mm m.oom.~ _.mm_ _mm_ N.Npo o.w~ m.mmm.~ o.F_N enm— _.oom m.Nw w.w~o.~ o._mm mmm_ m.vnm o.mw ¢.¢mm.m m.oww w©m_ w.mo_ m.ok m.0mo.N m.ow_ mom— m.mm m.mm o.mmc.m o.vw_ mom_ m.mm o.—w m.NNo.N ¢.N_N mom_ m.mm o.mo _.mom.w v.on_ amm— ¢.mm w.v~ m.mmm.m F.vm_ mom— w.w_ w.o~ m.mmm.m N.Pw_ Nmm_ m.m_ w.ow N.Nmm.m m.mom _mm— m.m_ m.mm N.¢wv.m m.mm_ oom— m.w m.m~ o.m¢v.m N.¢m~ amm— o.© m.wm m.q_¢.m m.om— mmm_ _.m m._n v._mm.m m.ox— “mm— m.m N.mw ©.wvm.m m.om_ 0mm— AWL: mo mcow__wz mo_P¥ Hz coo mEoocH v :owua%smcouvwmmm :oAchMMangcw mmov mcwwua23mwou me> chowumz mmocu muwamu cm; wp _ a co w :L: Facewch cowpassmcou wmwm chgwch m MJmeceaw use Lew snow :e “mecmecu Am .ewxmeeeeecm< :e—m wee aweccece: :ewmwsee Av . wecwEez we mews; .meescmm .mLeELen emcwzexm ugeexm meczpmma we pcese>eeaEH Lew memee :e mama pmecwucH use .LerwwuLwd mumsemega we mowce .Poez we mowca .wewca wmem .mLeELmd .wuea «meagexm .wewm we mewce ucequ u m4m meewm> meewe> meawm> meewe> mezpe> capeswpme Pazpo< empegwpmm ~8366< empaawpmm _a=pa< 88 :3 3:23.53 2363 3828 £285: 98: 88 8...; .233 weem F38 eegepgmemwm Egg Len. 2e; pee: 8.829.um e—pueuweem Leesez m.m 6:8 .N.m ._.m maezawa cw cam: 886D n_ HES. 121 TABLE G Data Used in Figure 5.4 Annual Gross Investment in Improved Pastures Year Actual ' Estimated Values Values 1961 18.0 10.2 1962 24.0 33.7 1963 32.0 14.5 1964 68.0 68.9 1965 91.0 164.4 1966 130.0 160.4 1967 145.0 176.2 1968 225.0 186.2 1969 200.0 186.2 1970 160.0 217.9 1971 270.0 265.2 1972 320.0 271.7 1973 308.0 280.7 1974 282.0 195.2 1975 110.0 180.6 122 “sesame>sw sew msmew se pmesepsw we ewes wees pseesee m sw pseseme>sw sew msme— se mums umesepsw eerewmeem esp .ewmw op meew>ese meme» esp see .m.m esemws sew use serwwpsew mpesemese sew mewse uexsez .mesepmme ee>eseew sw use serwwpsew epesemese sew mewse pexsezo .meszpmee se>esesw e .eem: ewe: < e—eew we meme weepem same we sew: esez mssewee.eessp pmsww eswm o._ee o.wse e.w_e w.Nmm Nem_ N.eme N.eee m.moe 4.8em _mm_ _.omm N.mmm m.wsm m.~sm oea. 4.40m e.e_m e.eam m.mmm awm_ m.mm~ N.eem e.mpm A._em ewe, m.FAN e._mN 8.6Nm m.mam snm_ o.~em c.58m o.~em o.wem osm— awWWM mmommw oe aawsa psoaxm Op see we nemm we .5 .. imam... a was. seamen... sw emeesesH . . . 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