OVERDUE FINES ARE 25¢ PER DAY PER ITEM Return to book drop to remove this checkout from your record. THE ALLOCATION OF FAMILY RESOURCES TO FARM AND NON-FARM ACTIVITIES IN A VILLAGE IN NORTHERN THAILAND By Rapeepun Sektheera A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY 1979 ABSTRACT THE ALLOCATION OF FAMILY RESOURCES TO FARM AND NON-FARM ACTIVITIES IN A VILLAGE IN NORTHERN THAILAND By Rapeepun Sektheera The Multiple Cropping Project (MCP) at Chiang Mai University has attempted to develop cropping systems which are biologically stable and economically viable for the Chiang Mai Valley. The ultimate goal of the MCP is the adoption of these systems by farmers in order that these might be a substantial increase in the farm income and living standard of the farmers. The project is now in the period of measuring its impacts on farmer with references to changes in cropping systems and income. There is evidence of resistance on the part of farm families to adopt systems that, on the basis of analysis to date, would significantly increase income. This study was designed to provide some insights as to the basis for this resistance. The objectives of the study are as follows: 1) To describe in detail Ban Pa Mark village and the individual households of a 30 family sample of its inhabitants for the two—fold purpose of (a) identifying and measuring critical constraints surrounding the management of typical cropping patterns and (b) specifying representa- tive farms and individual household cases fOr more detailed analysis. Rapeepun Sektheera 2) To develop a LP model to incorporate the constraints and to involve the representative farms and household cases from objective 1 in such a way as to determine possible reasons for dry season cropping being less than its full potential. 3) To use the model developed in objective 2 to specify appro- priate dry season cropping patterns consistent with the resource endowments and assumed constraints for the various representative farms and case households. 4) To interpret the linear programming solution for their implications for further research and extension program implementation in the MCP at Chiang Mai University. Ban Pa Mark, a village twenty kilometers south from Chiang Mai ' was chosen to provide daily record data from July l, l973 to June 30, 1974 from the 30 households on labor utilization, employment, cash and non-cash income and expenditure. These data are explored and analyzed in a descriptive fashion to determine the nature of family household constraints. The case households and representative farms were selected on the basis of resource constraints for the subsequent analysis using a poly- period linear programming model. The main findings and implications are as follows: 1) Each household represents a unique case with regard to resource endowment and other constraints thus each situation will have its own best cropping system. Rapeepun Sektheera 2) Even with the crop well established in the community there is room for possible resource reallocation to improve the farming system and the level of farm income. 3) The existence of a farmer who is doing better than the LP solution for his farm suggests a need to continually monitor on the part of the MCP of what farmers are doing and to introduce change only as it can be demonstrated consistent with the resource situation for individual farm families. 4) Any multiple cropping system in the area must be rice based. 5) The domination of women in production of dry season crops may be very significant for the extensiOn and outreach personnel of the MCP. 6) The dominant role of exchange labor implies that it is difficult for a cropping system regarded as an innovation to be accepted by one farmer if it is not generally acceptable to the entire community. 7) The cultural inflexibility of time allocated to non-farm community commitment implies that crops specified should not compete for capital and labor in the high priority non-farming period and the cash flow management problem is found in the non—farm employment and the management of crop inventories rather than in producing crops that can be harvested in time of primary need. To Kanya ii ACKNOWLEDGEMENTS I wish to express my sincere appreciation and thanks to all who provided advice and encouragement during my graduate studies. For their guidance and assistance, I wish to thank the members of my guidance committee: Drs. John N. Ferris, Carl Liedholm, Peter J. Matlon, and Warren H. Vincent for the insights, suggestions and con- structive criticisms. I am especially grateful to Dr. Warren H. Vincent, my major professor and thesis advisor, for providing his valuable time, his continuing interest and his kindly, patient advice throughout the graduate program and the preparation of the thesis. Appreciation is also expressed to Dr. Lester V. Manderscheid for his constructive comments, Dr. Stephen Harsh for model construction. I wish to thank the Thai government for the permission to continue my graduate school and the Agricultural Development Council for financial support. Thanks go to the farmers at Ban Pa Mark who were so cooperative during the field surveys and to Dr. Alan R. Thodey and Peter La Ramee for their work on the survey. I am grateful to Aree Wiboonpongse for responding quickly and effectively to my requests for data while I was beginning my research work at Michigan State University. I am indebted to Drs. Warren H. Vincent and Alan R. Thodey who encouraged me to continue my graduate study, to my fellow graduate students for their intellectual stimulation, to Cathy Cooke for her I good nature, support and typing this manuscript and to Kanha Urasyanandana for the graphic preparations. Finally, without the love, encouragement and support provided by my parents and my family, this endeavor would have remained undone. iv TABLE OF CONTENTS Dedication ......................... Acknowledgements ...................... List of Tables ....................... List of Figures ...................... List of Maps ........................ Chapter I. INTRODUCTION ..................... 1.1 Background .................... 1.2 Need for the Study ................ 1.3 Related Research ................. 1.3.1 Farming Systems/Multiple Cropping Research ................. 1.3.2 Research on Distribution of Farm Labor Between Male and Female Family Member . . . l.3.3 Linear Programming in Farm Planning . . . . Objectives of the Study ............. Methodology ................... 1.5.1 Data ................... 1.5.2 Procedures ................ 1.6 Organization of the Study ............ _.a._a 01th II. DESCRIPTION OF THE STUDY AREA ............. 2.1 The Village of Ban Pa Mark ............ 2.1.1 Demographic Features ........... 2.1.2 Physical ................. a. Soil Type ............... b. Rainfall ............... c. Irrigation .............. 2.1.3 Institutions and Ban Pa Mark Development ................ a. Infrastructure ............ b. Administrative Structure ....... c. Conclusion .............. Chapter III. HOUSEHOLD CONSTRAINTS 0N AGRICULTURAL PRODUCTION . 3.1 Introduction ................... 3.2 Land and Land Use ................ 3.2.1 Land Holdings ............... 3.2.2 Land Fragmentation ............ 3.2.3 Land Tenure ................ 3.2.3.1 Land Use ............. 3.2.3.2 Existing Cropping Systems . 3.3 Family Composition and Labor Force ........ 3.4 Land-Labor Relationships ............. 3.5 Selection of Case and Representative Households .................... IV. FARM LABOR UTILIZATION PATTERNS ........... 4.1 Crop Production Labor .............. 4.1.1 Labor Requirement for Individual Crops . 4.1.2 Nursery for Rice Production ........ 4.1.3 Land Preparation for Crops ........ 4.1.4 Transplanting Rice and Planting Other Crops . . .‘ ............. 4.1.5 Care of Crops ............... 4.1.6 Harvesting ................ 4.1.7 Relative Male and Female Participation in Crop Labor Activities ......... 4.1.8 Crop Labor by Source ........... 4.1.9 Seasonal Distribution of Crop Labor . . . . 4.1.9.1 Seasonal Crop Labor Distribution in the Total Sample ....... 4.1.9.2 Seasonal Crop Labor Distribution for Representative and Case Farms .............. 4.2 Other Farm Labor ................. 4.2.1 Seasonal Distribution of Other Farm Labor ................ 4.2.2 Seasonal Distribution Comparison of Other Farm Labor Between the Farm Size Groups and the Case Households . . . . V. OFF-FARM LABOR PATTERNS ................ 5.1 Exchange Labor .................. 5.2 Unpaid Special Activities ............ 5.3 Paid Labor .................... 5.4 Seasonal Distribution of Off-Farm Labor ..... 5.5 Seasonal Profile of Total Labor ......... 5.5.1 Seasonal Profile of the Total Sample ............... 5.6 Seasonal Distribution of Labor by Farm Size Group and Case Households .......... 5.7 Interpreting the Findings ............ vi Chapter Page VI. FAMILY INCOME AND ASSETS ............... 100 6.1 Sources and Definition of Income ......... 100 6.1.1 Crop Income ................ 101 6.1.2 Farm Non-Crop Income ........... 103 6.1.3 Family Non—Farm Income .......... 104 6.1.4 Total Income ............... 108 6.1.5 Distribution of Income .......... 111 6.2 Family Assets .................. 115 6.2.1 Real Estate ................ 115 6.2.1.1 Land and Land Distribution . . . . 115 6.2.1.2 Buildings ............ 116 6. 2. 2 Livestock ................. 120 6. 2. 3 Farm Implements .............. 122 6. 2. 4 Total Farm Assets ............. 122 6.3 Non- Farm and Total Assets ............ 123 6.3.1 Selected Durable Goods .......... 123 6.3.2 Cash Holdings ............... 124 6 3. 3 Total Assets ............... 125 VII. HOUSEHOLD EXPENDITURE PATTERNS ............ 130 7.1 Field Crop Production Expenses .......... 130 7.1.1 Hired Labor ................ 130 7.1.2 Land Rent ................. 131 7.1.3 Farm Supplies and Equipment ........ 133 7.1.4 Power Cost ................ 138 7.1.5 Water Charge ............... 138 7.1.6 Summary of Crop Expenditures by Crop . . . 139 7.2 Livestock Expenses ................ 139 7.3 Non- Farm Business Expenditures .......... 140 7.3.1 Expenses for Handicrafts Activities . . . . 140 7. 3. 2 Expenses for Trading Activities ...... 140 7. 3. 3 Total Business Expenses .......... 141 7.4 Family Consumption Pattern ............ 141 7.4.1 Rice Consumption Requirement ....... 141 7. 4. 2 Other Food Expenditure .......... 142 7. 4. 3 Non-Food Expenditure ........... 143 7. 4. 4 Seasonal Variation in Household Expenditures ............... 146 7.5 Income Distribution: Another Measurement . . . . 150 7.6 Summary ..................... 152 VIII. THE ANALYTICAL MODEL ................. 154 8.1 Introduction ................... 154 8.2 General Feature of the Model ........... 154 8.3 The Objective Function .............. 158 8.3.1 Crop Yields ................ 158 8.3.2 Crop Prices ................ 162 8.3.3 Crop Production Expenses ......... 162 vii Chapter 8.4 Crop Production Activities ............ 8.5 Capital Activities ................ 8.5.1 Capital Borrowing Activities ....... 8.5.2 Capital Payback Activities ........ 8.5.3 Capital Transfer Activities ........ 8.6 Labor Activities ................. 8.6.1 Labor Hiring Activities .......... 8.6.2 Selling Labor Activities ......... 8.7 Household Expenditure Activities ......... 8.8 Resource Constraints ............... 8.8.1 Land Constraint .............. 8.8.2 Labor Constraints ............. 8.8.2.1 Family Labor Constraints ..... 8.8.2.2 Hired Labor ........... 8.8.3 Financial Constraints ........... 8. 6 3.1 Initial Available Capital Constraints ........... 8.8.3.2 Borrowed Capital Constraints . . . 8.8.3.3 Borrowed Money Payback Constraints ........... 8.8.4 Coons umption and Behavioral Constraints . . 8.8.4.1 Consumption Constraints ..... 8.8.4.2 Behavioral Constraints ...... IX. RESULTS OF THE ANALYSIS ................ 9.1 Farm Organization and Income Measures ...... 9.1.1 Case Farm Comparisons ........... 9.1.1.1 Small Farm: Household 65 with Actual and Programmed Results ............. 9.1.1.2 Lower Middle Size Farm: Household 63 With Actual versus Programmed Solution . . . . 9.1.1.3 Upper Middle Size Farm: Household 50 With Actual versus Programmed Solution . . . . 9.1.1.4 Large Size Farm: Household 3 With Actual versus Programmed Solution ............. 9.2 Representative Farm Comparison: Actual versus Programmed Results ......... 9.3 Representative Farm Comparisons by Farm Size . . . 9.4 Representative Farm: Labor Constraint Effective and Relaxed . . . .- .......... 9.5 Marginal Value Products of Resources ....... 9.5.1 Marginal Value Product of Family Labor ............... 9.5.1.1 Marginal Value Product of Male Labor .......... 9.5.1.2 Marginal Value Product for Female Labor ...... ". . . viii 186 187 190 193 194 195 199 200 202 203 Chapter Page 9.5.2 Marginal Value Product of Hired Labor . . . 203 -9.5.3 Marginal Value Product of Capital ..... 204 9.5.4 Marginal Value Product of Land ...... 205 9.6 Summary ..................... 205 X. SUMMARY AND CONCLUSIONS ................ 208 10.1 Summary ..................... 208 10.1.1 Restatement of the Problem and Research Approach ........... 208 10.1.2 Summary of Production Constraints ..... 212 10.1.2.1 Land Holdings .......... 212 10.1.2.2 Family Composition and Labor Force ......... 213 10.1.2.3 Capital ............. 218 10.1.3 Household Income and Assets ........ 218 10.1.4 Summary of the Linear Programming Results .................. 220 10.1.4.1 Results from Case Household Analysis ............. 220 10.1.4.2 Results from Representative Farm Analysis .......... 222 10.1.4.3 Results from Relaxed Labor Constraint ......... 222 10.2 Implications of the Study ............ 223 10.2.1 Implications of the Findings for the Multiple Cropping Project ....... 223 10.2.2 Need for Further Research ......... 228 APPENDIX .......................... 230 BIBLIOGRAPHY ........................ 255 ix LIST OF TABLES Distribution of Land Area Operated per Household Non-Contiguous Fields and Plots within Fields by Farm Size Groups Land Ownership, Land Rented and Rental Rates Area per Farm and Dry Season Crop and Cropping Intensity Index by Farm Size Group Composition of Household by Relationship to Household Head Age Distribution by Family Size Family Size, Adult Consumer Equivalents and Labor Force by Farm Size Land and Labor Resource Level for Representative Farms and Selected Case Households Labor Use Per Household by Farm Size Crop Labor Requirement by Crop Percentage Crop Labor Uses by Sex for Activities by Crop Percentage Crop Labor Uses by Source and Activities Crops Grown, Case and Representative Farms Livestock and Poultry, Numbers and Average, Representative and Case Farms Average Annual Non-Farm Activities by Sex Seasonal Distribution of Non-Farm and Off-Farm Labor for the 30 Households Average of Annual Total Labor Uses by Farm Size Groups, Hours per Household and Percent of Total 38 44 46 50 54 56 58 64 67 78 82 86 88 95 Crap Value per Household by Crop and Percent of All Crops for Representative Farms Average Value of Food Self-Supplied by Household, Ban Pa Mark, 1973-74 Cash Receipts from Hired and Self-Employed Labor Receipts Per Household from Hired and Self-Employed Labor by Farm Size Group Total Family Income and Net Income per Household Farm and Non-Farm Assets for Representative Farms Total Non-Consumption Family Expenditure, Average per Household by Farm Size Use of Fertilizer and Chemical by Crop Production Expenses for Crops by Farm with Crop and Per Rai Average Household Consumption Expenditures Value of Farm Supplied Food for Case Households and Representative Farm Seasonal Index of Food - Non-Rice and Non-Food Expenditure Non-Food Expenditure by Items by Periods Gross Margins on Net Returns per Rai for Crop Activities Price Information for Chiang Mai Area Labor Requirements per Rai (Aij) by Sex and Period by Crop and Farm Size Capital Requirements for Crop Activities by Period Wage Rate of Hired Labor and Family Wage Rate Used in the Model (Baht) Household Expenditure by Period for Case and Representative Farms (Baht) xi 105 107 109 110 126 132 135 136 144 145 148 149 160 163 168 169 172 174 .7a .7b Land and Labor Constraints (RHS) for Case Farms Land and Labor Constraints (RHS) for Representative Farms by Size Classes Cropping Program, Case and Representative Farms, Actual and Programmed Farm and Family Income, Other Factors Small and Lower Middle Farms Farm and Family Income, Other Factors, Upper Middle and Large Farms Farm Organization, Farm and Family Income, Programmed Solutions with Non-Crop and Community Service Constraint, Representative Farms Farm Organization, Farm and Family Income, Representative Farms, With and Without Committed Labor Constraint, LP Solutions Marginal Value Product of Family Labor, Case and Representative Farms Marginal Value Product for Land/Rai xii Page 176 177 185 188 189 191 197 201 205 45000000 —-I NVO‘O‘O‘O‘ 0'14th LIST OF FIGURES Existing Cropping Systems in Ban Pa Mark Activities Profile by Period for Household 37 Activities Profile by Period for Household 45 Farm Labor Profile, Average Hour per Period on 30 Farms Farm Labor Profile, Average Hours per Period for Small Representative Farm and Household 65 Farm Labor Profile, Average Hour per Period for Lower Middle Representative Farm and Household 63 Farm Labor Profile, Average Hour per Period for Upper Middle Representative Farm and Household 50 Farm Labor Profile, Average Hour per Period for Large Farm and Household 3 Seasonal Profile of Exchange, Paid and Unpaid Special Labor Seasonal Profile of Farm and Non-Farm Labor, Average of the 30 Households Lorenz Curve of Per Capita and Per Consumer Income Distribution Lorenz Curve for Net Income per Household Lorenz Curve of Distribution of Owned Land Lorenz Curve of Distribution of Land Operated Lorenz Curve of Distribution of Assets Seasonal Distribution of Household Expenditures Lorenz Curve for Income Distribution Measured by Total Expenditure per Household Structure of the Linear Programming Model xiii 71 74 75 76 77 92 94 112 113 117 118 128 147 151 159 LIST OF MAPS Page Map of Chiang Mai Area 21 xiv CHAPTER 1 INTRODUCTION 1.1 Background Thailand, like any other developing country, relies to a great extent on the agricultural sector. It is therefore expected to per- form all the roles often cited by development economists, i.e., supply of food, capital formation and supply of labor to the development of economy at large. In 1976, 70 percent of the country's total working population was engaged in agricultural employment. Agriculture con- tributes about 30 percent of Gross Domestic Product and the bulk of Thailand's exports are agricultural products. Traditionally, the agricultural economy of Thailand has been dominated by a single crop . . . rice. Since 1950 more crops have been introduced and the area under nonrice crops has expanded greatly. During the 10 year period ending in 1976, the area planted in rice rose by 18 percent while the area in all other cash crops quadrupled. This corresponds to the 1972-76 Third National Development Plan which stated that for one of the highest priorities in agricultural development, a policy guideline is "to accelerate the diversification and improvement of agricultural production" (Royal Thai Government, 1973; p. 12). The 1976-79 Fourth National Development Plan states the same important position of agriculture. The policy guidelines emphasized diversification and the growth of agricultural production through 2 intensification and increased productivity to ensure adequate food supplies for the growing population and to increase the farm income and the standard of living in the farming community (Royal Thai Government, 1976; p. 167). Multiple cropping is a means to serve these policy purposes since multiple cropping is the practice of planting in a given field a crop or crops two or more times in one year. Land and labor will be used more intensively. New technology and the introduction of new farming practices may need to be used. Multiple cropping also is a means of organizing production to better utilize water and energy resources. The environment of Northern Thailand is particularly favorable for multiple cropping. It is concentrated in the valley basin and it is supplied with water by a large number of streams, many of which flow year round. The Chiang Mai Valley is one of the largest and is the most important river valley in Northern Thailand. The two main towns are Chiang Mai and Lumpoon. It has an area of 1,500 square kilometers which supports a population of one million people. It is one of the chief sources of the country's food supplies as well as being a primary center for political and economic activities. Although crop yields in Northern Thailand are higher than other parts of Thailand, they are still low in comparison with their poten— tial. Compared to elsewhere in Thailand, the Valley is relatively well endowed with roads and irrigation facilities. The potential for inten¥ sified crop production in this area is very substantial: the soil, climate and water resources of the low land area are favorable and the technology for increasing both yield and land use intensity is being continually developed. So it is possible to substantially increase the intensity of land use through multiple cropping. 3 Research on the development and adoption of improved cropping systems in Thailand has been conducted as part of the Great Chao Praya Basin Development Project to develop high yielding crop varieties, and combinations of crops and cropping patterns suitable for the Central Region of Thailand (ADC, 1974; pp. 126-132). The most comprehensive program of research in multiple cropping systems in Thailand has been carried out by the Multiple Cropping Pro- ject (MCP) located at Chiang Mai University. Initiated in 1969, financed jointly by the Ford Foundation and the Thai government, it has the following objectives: a) C) to develop, on a pilot basis, ecologically sound systems of multiple cropping with soil and water management designed to substantially increase farm income to get all agencies of government and private business con- cerned with agriculture to develop a "package of services" for farmers that will enable them to make the best possible use in both economics and production terms, of the improved production technology and other resources to monitor the adoption process in order to continuously evaluate the project and improve its impacts on the village farm community To achieve the above objectives, work plans were set into 5 stages: 1) 2) 3) 4) 5) inventory of farm systems synthesis of prototypical farming systems technology design and farm system validation evaluation of impact of the farms implementation of multiple cropping process in village development 4 At the beginning of the project, 1969-70, most of the time was spent in developing, building facilities, equipment and an experimental farm of 35 rai1 area. The inventory of farming systems was conducted during 1970-74 by a socioeconomic team to study the resource base and the behavior of farmers (Chiang Mai University, 1975), assess the market potential for various crops and evaluate the capacity and behavior of the marketing system (Wiboonpongse and Thodey, 1974). Analyses of the optimum multiple cropping systems (Thodey and Sektheera, 1974) were developed and at the same time, the synthesis of prototypical farming systems was also conducted at the experimental farm (Chiang Mai University, 1974). During 1975-76 the technology and farm system validation was carried out at the Village of Ban Harn Keow and Ban Mai Kuang about 20 kilometers south of the University. The evaluation of impact on the farms was scheduled for the period 1977-78 and the implementation of multiple cropping process in village development will follow. The agronomy program includes observations on agroclimatic conditions at the experimental plots, variety trials and cultivation methods for cereal, oil and vegetable crops. The work also includes production trials on six alternative cropping systems at the experi- mental farm. The socioeconomic program deals with production economic and farm management, socioeconomic surveys and marketing studies (Chiang Mai University, 1974). 1One rai (the unit of land measurement in Thailand) is equal to 1600 square meters, .16 hectares or .395 acres. 1.2 Need for the Study The ultimate goal of the Multiple Cropping Project, apart from developing multiple cropping systems adapted to Northern Thailand, is the adoption of these systems by farmers in order that there might be a substantial increase in the farm income and the living standard of the farmers. Two studies have been done in the socioeconomic program to gain a better understanding of the process by which farmers make their farm-related decisions. One focused on physical factors affecting crops choice (see Multiple Cropping Project Annual Report 1975), another focused on social factors (Ireson, 1976). Neither of these studies attempted to study a farm household as an integral unit of production, consumption and exchange. To do so requires a careful assessment of the resource endowments of individual families and to study how these resources are allocated toward the fulfillment of family goals. Lack of understanding of these facets of the Multiple Cropping Project handi- caps the project management in its direction of future research and extension needs. The project is now in its scheduled period of measuring its impacts on farmers with reference to changes in cropping systems and changes in family income. There is evidence that there has been resistance on the part of farm families to adopt systems that, on the basis of analysis to date, would significantly increase income. There is need for further research which will provide insights as to why this resistance exists. It is in response to the need that this thesis is undertaken. 1.3 Related Research 1.3.1 Farming Systems/Multiple Cropping Research There is a vast literature dealing with cropping systems and cropping patterns research.2 The increasing number of books, journal articles and unpublished papers is an indication of the vast resources that are being channeled into this kind of research (especially in the international research institutes) in recent years. The motivation for this is the realization that, with the increasing ratio of population to arable land, more intensive use of land must be undertaken to pro- vide food for a growing world population. A further motivation is that on most of the continents the agricultural production system is repre- sented by growers working small farms with little hope of working a larger farm. Their household income is low and intensification in land use provides one hope of increasing farm income. The increases in the literature on cropping systems/patterns research is due not only to the increase in the research investment in this area but also to its interdisciplinary nature making it difficult to decide what is a part and what should be excluded from the literature of relevant research. 2"Cropping systems" is defined as the cropping_patterns utilized on a given farm and their interactions with farm resources, other farm enterprises and the available technology which determine their makeup. "Cropping patterns" specifically refers to the Yearly sequence and special arrangement of crops or of crop and fallow on a given year. (From R. R. Harwood, farmer-oriented research aimed at crop intensifi- cation, in Proceedings, Cropping Systems Workshops, IRRI 1975, appendix, Los Banos, Laguna: International Rice Research Institute, 1975). 7 In response to the growing interest in cropping systems research worldwide and the lack of a comprehensive listing of literature dealing with the subject and problem concerning it, the Library and Documenta- tion Center of the International Rice Research Institute (IRRI) was commissioned to prepare an international bibliography on cropping sys- tems. The product of that effort was published in August 1976 and claims to "embrace all published and unpublished technical works dealing with all aspects of cropping system produced in 1973 and 1974" (Ramos, 1976). It is unquestionably the most comprehensive listing of literature available dealing with cropping systems. It contains 1416 references on cropping system research arranged according to the following classifications: general works, followed by studies con- centrated on physiology and biochemistry, crop ecology and meteorology, crop varieties and breedings, agronomy, irrigation/drainage/water management and crop water requirements, mechanization, plant protection, economic and sociological aspects of multiple cropping research. According to the listings less than 10 percent of the literature is devoted to economic aspects including works in statistics and statis- tical methods. This section does include the published works from MCP in Chiang Mai published during 1973-74 period. Only 6 citations in total referred to the relationship between labor utilization and cropping systems according to the title. The conclusion to be reached is that research in farming/cropping systems has received a renewed interest in recent years but that the economic analysis constitutes a minor share. 8 1.3.2 Research on Distribution of Farm Labor Between Male and Female Family Member Throughout the present study, there is a thread of interest pertaining to the female level of participation in farm and nonfarm income producing activities of the rural household. This area of interest has also received renewed attention as people have become more concerned about women's role in development. The primary interest in this thesis is to identify the contributing roles that various family members play in supplying their labor services to the economic activities of the household. Research on the division of labor in agriculture between sexes has taken many forms and has been conducted in many parts of the world. Baumann (1928) conducted an extensive survey of the division of labor by sex in Africa. He concluded that men's labor input on farms consisted of clearing bush before the land was tilled. It was confined to a short period whereas work done by women continued throughout the agricultural year. Women were in charge of growing root crops, kitchen vegetables and spices. Meek (1931) studies the Jukun-speaking people of Nigeria and his findings concerning the division of labor between men and women agreed with Baumann's. Edel's study of the Chiga of Western Uganda (1957) appears to agree with Baumann's observations. The division of labor among the Chiga suggested that the entire responsibility of agricultural produc- tion rested mostly with women who turn soil, sowed, weeded and harvested. Men clear the land and that was all. Women were also responsible for domestic work. 9 Spencer's work on Sierra Leone, using mostly cross-sectional data, concentrated on a detailed microeconomic evaluation of the effects of female participation and household decision making on income generation. His study shows that women in the Integrated Agricultural Development Project of Sierra Leone play a substantial role in the cultivation of a "development crop" (swamp rice) using improved technology which proved incorrect the hypothesis that women do not use the improved technology introduced by agricultural development project. Esther Boserup (1970) discussed the division of work within African agriculture according to two systems; one in which food produc- tion is cared for by women with little help from men, and one where food is produced by men with relatively little help from women. These two are the female and male farming systems. In her view, most tradi- tional African agricultural systems are female farming systems where women do most of the routine work related to food crop production. She presented quantitative evidence of different work inputs in terms of hours per week according to sex in eight African countries. She found that men spend an average of 15 hours per week on agricultural work, while women spend between 15 and 20 hours per week. In some areas of Gambia and Uganda, men work less than 10 hours a week in agriculture while in some areas in Kenya, Uganda and Congo (Brazzaville) women do agricultural work for as many as 25 hours a week. In per- centage terms, it was found that women account for between 70-90 per- cent of agricultural work. This high participation of women in agricul- tural work can be partly explained by a number of factors: women tend to marry older men so that they continue to work in the field long 10 after their husbands are too old; there are more men away from home with wage employment; and more boys than girls go to school and there is a higher drop out rate for girls. While Boserup's statistics may not be entirely representative for Africa as a whole, they do point to the large contribution of women in African agrarian systems. Simmon's (1976) research on women in Zaria involved several surveys, i.e., consumption survey, survey of food grain marketing system and several small studies of the adoption of innovations. The extent of women's economic participation in village commerce was sig- nificant in the consumption survey while men function largely as pro- ducers and traders of agricultural raw materials. These initial findings on the divisions of labor led her to explore systematically and quan- titatively the economics of women's money-earning enterprises in three villages in Zaria provinces in Northern Nigeria. The findings from research in Asia are not unlike those of Africa. Kahn (1976) reports that in a Pakistan village a typical woman works for 14 hours in a normal day, i.e., a day outside the hectic harvesting or sowing seasons. Activities include animal care, collecting, carrying and preparing fodder, milking, churning, cooking and carrying food to the fields. Planting, harvesting and processing seasons intensify the physical chores of the village women. During the wheat harvest, for example, women spend about 10 hours a day in the fields. They also take part in husking, winnowing and storing of wheat. They help their husbands in rice transplanting and sowing. Picking cotton and chilies are also major annual activities. A rural woman performs all the duties of a wife, a mother and a daughter-in-law and simultaneously shares the burden of field work with her husband. ,‘ I'- U I A. "- 6,. L-‘ .J.‘ Fr 'a _‘. 11’ fl ll Castillo (1977) reports that for the Philippines in addition to being farm laborer, the housewife "participates in the management not only of matters concerning household and family but also of farming _ and livelihood. In the Philippines, the decision making pattern in the Filipino household is more egalitarian and joint-with-husband rather than patriarchal. The Filipino wife is the keeper of family finances." This indicates the degree of authority and influence which a woman exercise in farm and family matters and also the quality of her input into the decision making process and what might be done to enhance the content of what she contributes. The above studies are of interest and are related to the present study. However, the focus of the present investigation will be more on the cooperative and integrative aspects of family member labor utilization than on the unique roles for the adult female. 1.3.3 Linear Programming in Farm Planning Prantilla and Heady (1972) state the multiple cropping problem concisely by claiming that the goal is to "minimize the number of days that land is made idle." They see the problem as best handled by employing linear programming techniques which for given resource con- straints and cropping opportunities, the solution will provide an optimum use of limited land (with a minimum period idle) as well as an optimum use of labor, the most abundant resource in the small farm household. The focus of cropping systems research in irrigated areas is on the choice of dry season crops, the combination of those crops and the sequencing of them through time. If the concept involved in programming are suitable for crapping system analysis, then modifica- tion of linear programming to incorporate the time dimension make this 12 methodology even more suitable. Polyperiod linear programming (PLP) can handle the time dimension quite adequately because of the timing of inflow and outflow and maintenance of reserves between periods are critical in present agricultural production systems. Realistic analy- sis of the situation requires careful attention to the linkage between periods and to intertemporal resource allocation. PLP is designed precisely to incorporate such an interperiod relationship (Crawford, et. a1., 1977). The mathematical framework of a LP matrix requires a number of important assumptions to be made about the nature of the process being represented. These assumptions include additivity of resources and activities, linearity of objective function, non-negativity of the decision variables, divisibility of activities and resources, finiteness of the activities and resources restrictions, proportionality of activity levels to resources and single value expectations (Agrawal and Heady, 1972; 31-33). Although for many purposes, these assumptions may provide a useful simplification of reality, risk considerations are also important in small holder decision making and some method of incorporating risk factor into a LP framework is desirable (Kenedy Francisco, 1974; Upton and Casey, 1974). There have been several studies designed to test the hypothesis that small farm operators behave rationally (Yotopoulos, 1968; Hopper, 1965 and Schultz, 1964). Such studies generally conclude that pro- ducers, even in the most backward areas, act as profit maximizers within their technological and institutional constraints. Other 13 findings conclude that peasant farmers seek status (Wolf, 1966) and security (De Wilde, 1967) as objectives. Norman (1973, 43) found that farmers in Zaria, Northern Nigeria have both security and profit maximization in their goal set, since he learned that farmers in this area used inputs in a manner consistent with a profit maximizing objective but also adopted intercropping as an insurance against risk. Heyer (1971) has stressed the "difficulty of deciding what it is that the subsistence farmer aims for," and suggests that ensuring an adequate food supply in drought years, producing a suitably varied diet, maximizing the number of people fed and maximizing the market value of output can be alternative objectives. Connor (1954) discusses various hypotheses concerning the motives of decision makers. He enumerates them as follows: 1. maximizing profits 2. producing at a level below the profit maximizing output 3. producing at a level above the profit maximizing output 4. preserving status quo 5. maximizing some preference function 6. survival of the firm 7. maximizing sales after obtaining some minimum profit level 8. selecting a course of action consistent with a satisficing principle I The complexity of behavior and decisions of small scale farmers, especially when the household is viewed as an integrated group, makes it difficult to accurately model the rural household. Any choice of analytic methodology is bound to be a gross oversimplification of reality. 14 There are critics of the use of linear programming for farm planning in peasant agriculture (Upton, 1974). Criticism usually relates to the assumptions pertaining to its basically static nature, the perfect knowledge assumption regarding prices, technology, etc., and the need to specify a single objective function. Nevertheless, for a relatively low cost analytical device, it does provide the most adequate analytical procedure for planning whole farm situations than any of the commonly used techniques available to us. 1.4 Objectives of the Study The general purpose of the study is to determine the effect that certain heretofore ignored constraints on farm planning have on the intensity of dry season cropping in an area known for its dependable year round irrigation. Some of the constraints to be studied include labor needed to maintain the traditional noncropping farm activities (such as supplementary livestock enterprises, vegetables grown in the "kitchen plot" and the harvesting of native fruits) and labor committed to off-farm non-income generating activities (such as community service, religious functions, weddings, funerals, etc.). Also attention will be given to the extent to which the specialized functions of males and females in crop production both by activity and by season of the year may serve to constrain choice of dry season crops. In addition, the need for the family to supply basic foodstuffs (especially rice) as well as to meet certain family cash consumption needs on a seasonal basis (particularly religious commitments) will be examined for their influence on decisions regarding cropping patterns. Other constraints customary in farm management analysis such as farm credit and the 15 availability of family and hired labor during critical crop production periods will also be considered. 1. 5 Specific objectives of the study may be stated as follows: 1) 4) to describe in detail Ban Pa Mark village and the individual households of a 30 family sample of its inhabitants for the two-fold purpose of (a) identifying and measuring critical constraints surrounding the management of typical cropping patterns, and (b) specifying representative farms and individual household cases for more detailed analysis to develop a linear programming model to incorporate the constraints and to involve the representative farms and household cases from objective 1 in such a way as to determine possible reasons for dry season cropping being less than its apparent full potential to use the model developed in objective 2 to specify the most appropriate dry season cropping patterns consistent with the resource endowments and assumed constraints for the various representative farms and case households to interpret the linear programming solutions for their implications for further research and extension program implementation in the Multiple Cropping Project at Chiang Mai University. Methodology 1.5.1 Data Data for this thesis came mainly from agro-socioeconomic studies of Multiple Cropping Project (MCP) with which the researcher has been 16 working closely in designing, collecting and supervising the acquisition of data. In 1971 the MCP began a longitudinal study in two lowland villages in the Hang Dong District including Ban Pa Mark. This study aimed to collect a wide range of agro-socioeconomic data on a semi- annual basis, i.e., at the end of rainy and dry seasons. It was found that the six month interval was too long for farmers to recall accurate information on crops, employment, income and expenditures. As a result, an intensive study of Ban Pa Mark was conducted involving a sample of 30 households2 including some of those contained in the original sample. Detailed information was collected daily from the 30 households from July 1, 1973 to June 30, 1974. The main items of information collected were: all labor (male, female, children, hired and exchange), as well as power and supplies used in the production of each crop.. Specifically: - the employment of each household member in economic activities - the cash and non-cash expenditure on food and other items - all cash and non-cash income In addition, time and motion observations were made of all labor operations. Each plot was surveyed to enable these observations to be . . 3 . converted to a common unit (man hours per rai or tang per rai). 2The 30 households constituted a sample from a total of 44 house- holds in the village of Ban Pa Mark. 3"Tang" is a local unit of yield measurement approximately equal to 10.0 kilograms of paddy rice. l7 Residents of Ban Pa Mark were employed as enumerators to collect information from each household and also to observe family members in their work. Each day the enumerators had to spend at least ten minutes for an entire year with the farmer to get information of each day's cropping activities, utilization of labor, income and expenditure apart from observing them working in the field. The survey data were aggregated into 13 periods of 28 days each and some were published in report form by the project. These reports provided some of the needed information for this study. However, for this study detailed information on each household was required. This was obtained from original field schedules and summary sheets obtained by the researcher during a one month visit to Chiang Mai University in July, 1978. 1.5.2 Procedures The first step taken to fulfill the thesis objectives will be to analyze in a descriptive fashion the data referred to above for the purpose of determining the nature of the family household constraints. This activity will also guide in the selection of case households and representative farms for the subsequent analysis using a polyperiod linear programming model. The effects of household resource endowments and other types of constraints on farm organization and family income will be analyzed using a polyperiod linear programming model wherein the following comparisons will be made: 1) case households within farm size strata will be compared on the basis of 1973-74 existing conditions with programmed 18 solutions utilizing the resource conditions found in the actual cases. This will include a labor constraint in which the actual reported amount of family labor allocated to non- crop farm production and to off-farm community services will be maintained. 2) The programmed results from the previous step involving the described labor constraint will be compared with programmed results obtained by relaxing the labor constraint. This is to suppose that the above constraints are basically unchangeable. This comparison will give an indication of the importance of taking this type of constraint into account while doing farm planning. LThe experiment will be referred to as a comparison between "the constrained system" with the "unconstrained system" with regard to specialized family labor activities. 3) The final comparison will be directed toward analyzing the effect of farm size on the allocation of family resources with regard to farm reorganization and family income. For this phase, the LP solution from the constrained system for the representative farms for the four farm size groups will be compared. 1.6 Organization of the Study The physical and institutional features of the Village of Ban Pa Mark for their possible influences on household behavior will first be undertaken. The findings will be presented in Chapter 2. Three chapters will deal with issues of farm family labor alloca- tion and utilization. The first (Chapter 3) will examine the l9 relationships between labor and the use of land. Out of this discussion, the case households will be selected. The second chapter on labor utilization (Chapter 4) will concentrate on how family labor is used in the farm business with attention given to crop labor by enterprise requirement, by sex, by source, and by annual seasonal distribution. Chapter 5 will follow a similar format but will concern itself with both the off-farm labor activities as well as a summary of the utiliza- tion in both farm and nonfarm work. From the discussion on the use of farm inputs, the attention will then be diverted (in Chapter 6) to the rewards accruing to farm family resources in the form of income and asset ownership. This will be followed in Chapter 7 with an examination of how rural households spent their money for business and other purposes. The previous chapters will have identified the resource levels and decision rules that will be incorporated in the model to be explained in Chapter 8. Then in Chapter 9 the model will be utilized to conduct the experiments described above. The results of using the model will be presented in Chapter 9 with the findings and implications presented in the final chapter. CHAPTER 2 DESCRIPTION OF THE STUDY AREA 2.1 The Village of Ban Pa Mark Ban Pa Mark is located three kilometers from amphur Hang Dong (district center) and twenty kilometers south of Chiang Mai city (see Map l). The road to Hang Dong is a two lane paved highway that is quite busy since it is part of the main highway that leads into other districts such as San Pa Tong, Chom Tong and other provinces, i.e. Mae Hong Son. To reach Ban Pa Mark, travel south along this road toward Hang Dong, pass an open market before the district office, turn left on a well graded laterite road, go for about three kilo- meters, and the destination will be reached by crossing the bridge to the left. The village itself has three subvillages, Ban Pa Mark, Ban Don Ka and Ban Muang Nga. The subvillages are surrounded on all sides by open rice fields and are connected by an old narrow winding road. As in most of the northern villages, the houses are clustered on the highest land, along both sides of the road. Each compound has up to five houses with no fence between the home lots. Many trees grow around the edge of the compound, giving a nice cooling shade. Each household is composed of a house, a rice barn, a pig pen, a buffalo shade and perhaps a small kitchen plot. The houses are generally uniform in construction, made of wood floor, raised about six feet off the ground 20 21 Paddy Land Upland Land our 400 Mn -....-- Main Road ------ Mina: Road H+O++ Railroad """/o new m.n_ m.mm F.¢~ wo.m< mm.oF o.om 0.0, m me.nplo.mp m.mm o.o~ mm.mo mm.m~ o.ow u.o— m mm.¢~-m.m_ m.m¢ o.mm F¢.om m¢._F m.mm m.m~ x m¢.~Puo.o— m.- ¢.- mm.oo .ox.m o.o¢ m.m~ N mm.m . m.m e.m e.m mm.FF om.m n.op m.m N me.n . o.m o.~ m. vo.m eo.m o.o_ m.m _ mm.e . m.~ F.F P.F mm.m um.F ~.m 5.0 N m.~ cozu mmob o>wumF=Ezoo< Page» 6o Pom uFocmmaoz N m>wumpsszoo< pcmoema consaz awmev pcmuemm emu Pom mmmpu m~wm ome< magma uFogmmao: emu umumemao mme< can; we :o_u:apeumwo —.m mpnmh 33 calls for the division of land equally among children, male or female. This means, when they are married both man and woman can bring land into the household. Further, the matter of land fragmentation is related to the availability and size of parcels for sale when a farmer attempts to buy land to expand his business. If land becomes available to a potential buyer, it is quite likely that it will not border the land he already owns. The number of noncontiguous fields, the plots per field and their respective areas are shown for each household in Appendix Table 3.1. When summarized on the basis of farm size we note, as might be expected, that the largest farms have the most noncontiguous fields (Table 3.2). The 8 farms in the smallest quartile by farm size average 1.4 fields whereas those in the large farm size quartile average 2.9 fields. Interestingly also, the size of field in the large farms is about 64 percent larger than found on the smallest farms. The size of plot within field is the area considered by the farmer to be appropriate for good water and crop management. The average size plot within fields for households ranges from .22 to .49 rai but a safe generalization is that there will be about 3 plots to make a rai regardless of the size of farm overall. How important is the matter of land fragmentation for the purposes of this study? It is granted that the number of separate parcels, their individual land areas and their respective distances from the family dwelling can be a factor in choice of the amount and kind of crops to be grown. However, in the analysis to follow, the matter will be ignored for the following reasons: (1) seventy percent of the 34 mmmpu mNNm Egon em. w mm. m em. Nm. Nm. eope\_em N.m m e.e w e.N e.e m.m e_oed\eem o.N. m N.N_ m N._N m.ee e.N_ e_oe6\mooee m.em M N.Nm m m.Nm ” _._m m _.N_ e_oeom=oz w w “ emu moo—m o.N m.N M N._ _.N _ e._ e_oeom=o: M “ emu mGmem . 6. _ - e cop om _ oo_ N _ oo. N " cox ” N _ oo_ N _eeoe m_ e mm m e_ _ W o ” o m o o e N_ m mN N ex e W NN e N M o o m om m mN N o w Ne w e mm N N oe N, M N, _ PN m . ep m F No m P ucmuema A.ozv W pcmuema A.ozv ucmuema A.ozv ucmuema A.ozv pcmuemo A.ozv cowuanwepmwo menu; 6 meson magma were; magma vpmwm « mated __< w emcee drone: Logos, abbey: eozoo __e5m sope ._ manage mNPm Esme x5 mn—owm cwgpwz muopa use mupwwe mzozmwpcoulcoz N.m anmh 35 households have only 1 or 2 fields, (2) all fields are within walking distance from the dwelling, (3) all fields in the village are very similar with regard to fertility, water availability, drainage and other such management considerations and, finally, the matter of incorporating the problem of fragmentation into a household-firm linear programming model is highly intractable. 3.2.3 Land Tenure The effect of land tenure on income distribution, economic incen- tives and political power are quite apparent among the countries of the world with a dominant agricultural production sub-sector. It affects the level of production, technology and determines the interpersonal distribution of production and income. The level of tenancy is low in this village. Only 3, or 10 per- cent, of the sample households operated as full tenants and one of these families was renting from parents without having to pay rent (Table 3.3). A third of the sample households own all of the land1 they farm and the remaining 57 percent have been able to expand their farm land base by renting additional land. About a fifth of all land cultivated is rented in one season or both under some kind of rental arrangement. Many of the rental agreements are between relatives and the amount of rent paid in cash or kind varies according to individual 1Most households have either "Bai Chang" (reserve license) or "Nor Sor" title (exploitation testimonial) which provides permission to occupy land temporarily without the right to transfer until the land is under a full title deed (Chanode Tidin). 36 Table 3.3 Land Ownership, Land Rented and Rental Rates Tenure No. of Land Area/Farm (rai) Average Rent Pattern Farms Owned Rented Total Per Rai (8) Ownership only 10 10.54 0 10.54 ---- Tenants only1 2 o 9.53 9.53 2l7 Own plus rent Rent Wet Season Only 10 9.21 3.50 12.71 642 Rent Dry Season Only 4 8.74 .69 9.43 564 Rent All Year 3 14.75 3.33 18.08 1094 Average All Farms1 30 9.22 2.42 11.64 539 1 One household renting from parents rent-free not included. circumstances. One tenant pays 30 percent of crops produced. Others pay up to 50 percent of the rice crop. In dry season some farmers will grow crops on rented land but the rent paid is tied to the rainy season crop. Because of these situations, it is difficult to generalize as to the true market condition for rented land and the amount of rent paid per rai varies widely from farm to farm (see Appendix Table 3.1). Nevertheless, from Table 3.3 it appears safe to say that dry season rental rates are lower than rainy season rates even though some dry season crops may have higher profit potential than rainy season rice. In the analysis of case farms to follow some will be cases involving rented land. However, there is no evidence that rented land is managed differently than owned land. Therefore, it will not be considered a constraint to cropping decisions. The cost of land rent will be deducted from projected net income in cases where appropriate. 37 3.2.3.1 Land Use Cultivated land in the Chiang Mai Valley can be distinguished into three utilization categories; paddy land, upland and orchards. Land where flooded rice could be grown is paddy, while the cultivated area that is too elevated for inundation is considered upland. With respect to the orchards, this is mostly used in the growing of lumygj_ (a tropical tree fruit). Land in the studied area is utilized mostly as paddy. Each household compound contains an area used for vegetables, native fruit and care of livestock. This compound area is excluded from the discussion of cultivated area and from Table 3.3. The paddy land is usually inundated in the rainy season but with the irrigation and a suitable drainage system, it can be used for dry season crops. During the 1973 rainy season, all thirty households under study planted on the average of 11.64 rai, almost all in glutinous rice. Apart from climatological suitability, rice growing is traditionally regarded as the basic staff of life for the Thai farmers. It is necessary for then to grow enough rice for their families for the year and it is a disgrace to have to buy rice. Thus, growing one's own rice is preferred even if to means to forego some income earning from other crop activities. Some farms may use the nursery area to plant soybeans which are intended to provide some seed for the dry season soybean production. During the following dry season they planted on the average 10.25 rai per farm or 88 percent of the average farm size of 11.64 rai. The dry season land area was utilized on the average as follows: 4.12 rai (40 percent of dry season land) in dry season rice, 5.34 rai (52 percent) in soybeans, .69 rai (7 percent) in peanuts and .10 (1 percent) in garlic (see Table 3.4). 38 Table 3.4 Area per Farm and Dry Season Crop and Cropping Intensity Index by Farm Size Group Farm Size Group Small L. Middle U. Middle Large Total Dry Season Crop Area Rice 3.64 2.39 3.63 6.55 4.12 Soybeans 1.80 5.23 6.04 8.37 5.34 Peanuts .22 .23 1.55 .81 .69 Garlic .14 .19 .05 .Ol .10 Total 5.80 8.04 11.28 15.74 10.25 Total Land 5.43 9.88 12.68 18.48 11.64 Intensity Index 207 180. 189 185 188 From Table 3.4 in which land use has been organized by farm size group it can be observed that the amount of soybean increases absolutely and relatively as farm size increases whereas garlic decreases absolutely and relatively as farm size increases. The crop intensity index2 averaged 22 points higher on farms in the small farm quartile by farm size than for the farms in the large size quartile. averaged 188 for the samples (see Appendix Table 3.2). The cropping intensity index ranged from 147 to 270 and When household heads interviewed in July 1978 were asked why they chose one dry season . crop over another, they responded with the following: 2 Dry Season Crop Area * 100 Total Land Area higher expected because 100 percent of land is used in the rainy season. + 100 = Cropping Intensity Index 39 yield, expected price, easy to grow, land suitability, water avail- ability, capital availability for seed and fertilizer (peanuts and garlic) and labor availability. 3.2.3.2 Existing Cropping Systems Rice is the staff of life in Thailand and glutinous rice (126 day traditional varieties, not high yielding varieties) is the preferred form for consumption in the Chiang Mai area. One can safely generalize that all available land on individual farms will be prepared as paddy for this crop in the rainy season. The nursery for rice may be prepared as early as June and as late as the end of July. Of course, the planting date for rainy season rice will determine the harvesting period and thus effect the starting date for potential dry season crops. Figure 3.1 identifies ten crop sequencing patterns found in the thirty households. They are summarized below: System No. Rainy Season followed by -- 1 Dry season rice 2 Dry season rice with soybeans 3 Dry season rice with peanuts 4 Dry season rice with soybeans and peanuts 5 Dry season rice with soybeans and garlic 6 Dry season rice with soybeans and peanuts 7 Soybeans only Soybeans and peanuts Soybeans and garlic ONOCD Soybeans, peanuts, and garlic 40 Figure 3.1 was prepared to reflect usual periods on which crops are grown and should not be interpreted as showing the only periods that they can be grown. With irrigation water available in the dry season, many possibilities are open according to the unique circumstances of individual families. The depicted simplification was done to accommo- date the modeling to follow. After examination of individual house- hold data, it became evident that any modeling effort employing the linear programming method that functions within the time and financial constraints of the typical graduate student would fall short of simulating the true management behavior of the Thai household. The primary reason for this is that farmers manage their labor and other resources on a day to day (if not hour to hour) basis rather than weekly, monthly or other uniform time block through the year. Their actions also impinge upon such other things as weather conditions of the day or general state of health or energy. Even describing activities on a period basis delineates sharp differences among farms as can be seen by comparing Figures 3.1.1 and 3.1.2. Household number 37 has the highest cropping intensity index in the sample and has some of each of the 5 crops grown in the area. In period seven we observe participation in 10 different activities involving work on all five crops. Whereas household number 45 following the simplest system never has more than three activities reported in a single period. The latter system can be easily modeled. The former one can be modeled but at great expense. 3.3 Family Composition and Labor Force The primary unit in Thai society is the family. Unlike many traditional societies where the household is characterized as extended 41 . Season Rainy Season Cool Dry Season Hot Dry Season ‘ Month July 1August1$eptj Oct. Nov.#I Dec.jJan. lFeb. March IApril IMay ]June Period 1 j z 3 I 4 T 5 I 6 I 7 J 8 1 9.119) 11 |_l_2m[_l__3'_-l‘ 1 System ' j . l. 1 Rice (126) 1 l Rice (115) _..__...I 1 Rice (115) 1 2. Rice (126) Soybeans (117) *__ 3 f Rice m5) ‘ Rice (126) Peanuts (112) 1 1 Rice (115) _J 4. 3 Rice (126) Soybeans L117) 1 Peanuts (112) [ Rice (115) ] 5. Ri (126) 17' Soybeans (1171 “3 _.__9ar.l_ic_e§_>_.,-__ I Rice (115) J 6. Rice (126) Soybeans (117) Peanuts (112) L Garlic (98) I 7' 1 ._--_F{59<:-I1292_- 1 Soybeans (H7) 1 Soybeans (117); 8' Rice (126) Peanuts (112) 1—— Soybeans (117) I 9. Rlce (126) Garlic (98) _] Soybeans (117) .1 . Peanuts (112) . R1 126 — 10 ce ( ) Garlic (98) Note: Numbers in parentheses represent number of days in the field within the designated periods. Figure 3.1 Existing Cropping Systems in Ban Pa Mark 42 Activities by Crop and Period Crop 1 2 . 3 4 5 6 7 8 9 10 ll 12 1? (Nurs. ’ 1 Rainy lLand Prep. ' Season LT, fi Crop Care Rlce 1 Plant Harwest i 1 e _ : Pfifirs. 1 Dry 5 Land Prep. Crop C re Season ? Rice f Plait Harvest 1 Land Prep. Soybeans i i —819Q3 Care (Harvest 5 ””“"' green) i .__Haryg§§_u_ I Land re . Soybeans 5 Plant (Harvest ; figrop Care dry) : Harvest E l 1 Seed Efiep. l ‘" i Peanuts 1 EEEE*E:EE:W--EEOP.-FPEF-1 E Plant [ larvest ‘ _e__u. - L 1 1 etc ,1... l E 5 (Seed _rgp. ‘ . i i Garlic 5 ELand Prep.4.— Crb Car 1 , l ; 1 Plant 1 Haerst b l j J 1 . Figure 3.1.1 Activities Profile by Period for Household 37 43 me e_oeom=oz Lee eoeeoa xe oeeeoea moeee>eoo< N._.m wczmwu - 4 M .--es- , W m m w memuw m goeu m M m e W n H n _ m .1..1...I-iil-l..:.i .-_ . ;:-.; . i -11.-.. ii p . u, pmm>emz . Hem_¢ m m M w mcmmnxom M -zzi..~ m W W H use; 2 m M m i l V « .M: i . l.l.lli... 1.4... 1 .. 111-111. - i . w: 4 L .. i i i i . m .1 1r W m 1m ppm 3 W mu E W W weep noeuw m comomm w n .9: ;;:r iii: w cowpmxmamegvcmo xcwmm illll . . mm> m m . 2:2 _ W p N I 4.64.52 N, N_ _P o_ e W N N e m 4 w _ P e . e eoeeoe xe aoeu xe moepe>moo< 44 family, a typical Northern Thai household includes the immediate family and occasionally grandparents and grandchildren. The 30 households in this study totalled 163 members with the household size ranging from 3 to 10. On the average, there were 5.4 members per household. Most households are composed of a husband, wife and one or more children.' Some households have in terms of relationship to household head children- in-law (5 percent), grandchildren (5 percent), parents (3 percent), brothers (3 percent), and aunts (1 percent). The distribution of all members in the households in terms of their relationship to the household head and his or her spouse is shown in Table 3.5. Table 3.5 Composition of Household by Relationship to Household Head Relationship to Total Household Head Male Female Number Percent (number of people) (percent) Head and spouse1 3o 24 54 33 Children 35 47 82 50 Children-in-law 8 5 Grandchildren 8 5 Parents 1 5 3 Brothers 4 -- 4 3 Aunts -- 2 2 1 . Total 81 82 163 100 Source: Terminal Survey, July 1974. 1Where applicable. Six households with head without spouse. 45 The age of male heads of the household ranged from 26 to 78 with an arithmetic mean of 48 years. The average age of female heads of the household was 44 years and the average age of all household members is 28 years. A distribution of family members by age and sex for each household is given in Appendix Tables 3.3 and 3.4 and are summarized by family size in Table 3.6. In the total sample, 30 percent of the family members are under 15 years old and 8 percent are over 60 years old. This means that 62 percent are in the active economic working group (that is, in the range of 15 to 60 years of age). Each member of these families was reported to be in good health except 4 persons of old age in households 6, l7 and 18 and which were too old for full-time farm work. In general, family members under 45 years of age have four years of education whereas nearly all of the women and men over 45 have less than four years of formal education. This is due to the compulsory primary education decree in 1921 which required the children to attend school at least through the fourth grade. Of the 30 male household heads, one had 11 years of schooling, 16 had 4 years, 6 had one to 3 years and 7 had no formal education at all. All children are attending schools in the adjacent villages if they are at or under fourth grade. Higher grade schooling has to be obtained from the district center or in Chiang Mai. Since schooling is taken seriously, labor contributions from children are very limited except in some periods which coincide with school vacation and in periods of peak labor demand. 46 0.0N 0.N 02 0.02 NN 0.02 NN 0.0N N4 2.00 04 00_ 002 00 04404 N.NN 0 0 0.0N N 0.02 2 0.04 4 0.00 0 02 0.0 2 02 0.NN 0.NN N 0.N2 N 0.N_ N 0.N2 N 0.00 0 02 N.0 N 0 N.0N 0 0 N.0N 0 N.0_ N 0.N4 02 N.0N 0 00 N.0_ 0 N 0.00 N.NN 4 0 0 0.00 0 2.22 N 0.00 0 02 0.02 0 0 0.NN 0.0 0 0.02 0 0.0_ 0 0.0N 02 0.N0 02 00 0.00 02 0 0.0N N.02 0 N.02 0 4._N 0 _.N0 0 0.0N N 0N 0.0N N 4 0.00 N.02 2 0.00 N N.0_ _ 0.00 N 0 0 0 N.0 N 0 N000N 00 N .02 N .02 N .02 N .02 N .02 0000002 220 00 .02 0400 002 00000>< 0020 0 00 00-04 44-00 0N-0_ 02 00000 20004 0000000 020000 memnemz Page» mo cowuzneepmwo mmq .004000030: 0000 020000 00 000000000000 004 9m 3an 47 Farming is the household's major occupation. Adult males of the household also engage in other activities such as trading, handicrafts, carpentry, and working as hired men for others. The female adults of the household may engage in handicrafts, trading and dress-making for additional income besides performing the customary household duties. The amount of time spent and the contribution of non-farm activities to family income will be examined in a later chapter. Also the contri- bution of women's labor to farming activities will be investigated in some detail. For the moment, our interest is in viewing the family as a composite of members varying in age who contribute to the family labor supply and participate as consumers. Because of the variations in family size and in sex and age com- position a common denominator is needed for comparing families and. groups of households. Two approaches will be employed here. The first will be to compute adult male labor equivalents for households. The idea of converting family labor to adult male equivalents has been with us for many years in farm management analysis. However, the factors for converting the labor of men, women and children to a common unit are not universal. The lack of standardized conversion factors may be explained by perceived differences in labor productivity by age and sex but they may also be explained by the different ways one may look at the problem. Some would approach it by weighting labor by the amount of wages the respective age and sex classes might earn in the farm labor market. Others may approach it by using judgement as to the varying capacities of individuals to do farm work. Still others may view it as a matter of estimating the proportion of time the various classes of family labor are available for farm work. 48 This latter approach is the one preferred for this study. Unfortunately, there are no data from the survey which would reveal the amount of time available for work. All that is known is the amount of time spent by individual in various activities. Hence, to develop conversion factor on the basis of time available will be based on the researcher judgement and first hand observation of family behavior in the study area. For this study, the following conversion factors are used to compute what will be called a "full time labor force equivalent." Age Group in Years Sex <8 8-14 15-60 >60 Female 0 .20 .72 .20 Male ' O .30 1.00 .30 It is proposed that these factors represent the proportion of an average working day that respective family members are available for farm and non-farm work and for non-income generating community commitments in addition to performing domestic chores (and/or attending school in the case of children). For example, if men can work an average 7 hour day, then the availability of female children in the 8 to 14 age category, women in the 15 to 60 age category and women over 60 years will be 1.4, 5.04 and 1.4 hours respectively. Full time labor force equivalents have been computed for each household and reported in Appendix Table 3.3. Later in the study these will be used to define labor constraints on farm work when case farms and representative farms are analyzed. 49 The number of consumers in a family exceeds those actively engaged in farm work. A method for converting families of different composi- tions to a common denominator is needed. The method used here is that adopted by Hart3 from the work of Epstein. It differentiates by age and sex as follows: Age Class d 1-3 4-5 6-9 lO-15 16+ Children .10 .30 .50 .65 --- --- Females --- --- --- --- _75 .30 Males --- --- --- --- .80 1.00 Adult male consumer equivalents for each household were computed and reported in Appendix Table 3.4. The relationships between family size, full time labor force and adult male consumer equivalents are summarized in Table 3.7. The average size family of 5.4 members has 4.4 adult consumer equivalents and 3.3 adult full time labor equivalents. The total population is about 51 percent female but with the lower weights placed on female for both consumption and farm work they represent only 42 percent of the total in these conversions. Using information in Appendix Table 3.3 and Table 3.7 it can be shown that children under 15 constitute only 6 percent of the adult equivalent labor force but make up more than 11 percent of the adult equivalent consumers. 3Hart, Gillian, "Labor Allocation Strategies in Rural Javanese Households," unpublished Ph.D. thesis. Cornell University, 1978. 5() Table 3.7 Family Size, Adult Consumer Equivalents and Labor Force by Farm Size Farm Size Item Small Lower Middle Upper Middle 1 Large All Farms Number of Hshlds 8 7 7 j 8 30 Sex M F T M F 1 M F T f M F T M F T Family Nam. 21 15 36 15 26 41 18 20 38 125 23 48 79 84 163 Hem/Family 2.62 1.88 4.50 2.14 3.72 5.86 2.57 2.86 5.43§ 3.12 2.88 6.00 2.63 2.80 5.43 Percent 58.3 41.7 100 36.6 63.4 100 r7.4 52.6 100 352.1 47.9 100 48.5 51.5 100 Adult Male 5 Consumer 1 Equivalent Per Hshld % Per Hshld % Per Hshld % f Per Hshld 1 Per Hshld 1 Children .39 10.4 .89 19.9 .41 9.3; .37 7.3 .50 11.4 Women 1.18 31.6 2.01 45.0 2.16 49.1; 2.07 40.9 1.84 41.7 Men 2.17 58.0 1.57 35.1 1.83 41.6: 2.62 51.8 2.07 46.9 Total 3.74 100 4.47 100 4.40 100 1 5.06 100 4.41 100 Adult Full 2 Time Labor 2; Equivalent Per Hshld % Per Hshld % Per Hshld % ; Per Hshld % Per Hshld Z I Female 1.00 35.9 1.43 44.9' 1.53 45.9; 1.49 38.9 1.35 41.7 Male 2.79 64.1 1.76 55.1 1.80 54.11 2.30 61.1 1.92 58.3 Total 3.79 100 3.19 100 f 3.33 100 l 3.79 100 3.27 100 1 Land Area (rai) 1 Per Household 5.43 9.58 ' 12.68 18.48 11.64 Per Family Mem. 1.21 1.69 2.33 2.84 2.14 Per Consumer Equ. 1.45 2.14 ' 2.88 3,55 2.64 Per Labor Equiv. 1.95 3.10 3.81 4.88 3.59 51 3.4 Land-Labor Relationships Land worked primarily by family labor is the chief source of food and income to the farm family. For a given area of farm land available the amount and kind of crops grown may be related to both the number of family members to be fed and cared for as well as the available family labor to work in the fields. The relationships among these variables are summarized in Table 3.7 according to size of farm. We observe that larger farms have more family members and consequently a larger labor force. The land farmed per adult labor equivalent is 1.95, 3.10, 3.81 and 4.88 rai for farms in the small, lower middle, upper middle and large sized farms respec- tively. This indicates that the farms in the large size group have more than twice as much land per adult labor equivalent than the farms in the small size group. 3.5 Selection of Case and Representative Households Before explaining the method for selecting them, it is in order to comment on the need for having both case households and representative farms in the analysis. Ideally, because each household represents a unique situation, a farm plan using linear programming procedures would be prepared for each farm in the sample. However, this is not a practical approach from either a research or extension point of view. Therefore, it is desirable to select a household or households representative of all farms in the sample or of some sub-sets of the total sample. 52 Availability of land, labor and operating capital constitute the resource constraints which largely determine the volume and kind of farm business for a particular household. Levels of land and labor resources of individual households have been described above. The amount of capital for each family will be discussed in a later chapter. Realizing that cash on hand for any family may vary widely from week to week, it is felt that the most appropriate criterion for selecting case households and/or representative farms on the basis of resource levels is one which takes account of land and labor only. The selection process entailed first stratifying the 30 households into four strata on the basis of total land farmed and letting the com- posite of the farms within these strata to become the "representative" farms by farm size class. Selection of a case household within each stratum took into account the amount of male and female labor in the families expressed as adult labor equivalents. The attempt was to identify the household most like the stratum average when land area, available female labor and available male labor were taken into account. Since land and labor amounts are expressed in different units, the stratum average for each variable was expressed as a base=lOO and an index using this base was computed for each variable for each household. The ultimate selection was made by choosing the household within strata which had the minimum value for the following expression .5 (Li-100)2 + .25 (FLi-100)2 + .25 (mi-100)2 where identifying household number do 11 r ll land area as an index of strata average 53 FL = adult female labor equivalent as an index of strata average ML = adult male labor equivalent as an index of strata average The land area for the representative farms is the average of the farms within the four strata obtained by classifying the samples according to farm size (Table 3.8). The amount of labor available for the representative farms was obtained by average female and male adult labor equivalent obtained from the farms in these strata. Following the selection criterion described above household numbers 65, 63, 50 and 3 were chosen for farm size categories small, lower middle, upper middle and large respectively. These are the households that have the least weighted deviations from the representa- tive farms using the procedures outlined above. The amount of land and the amount of labor available expressed in adult labor equivalents for these selected farms may be compared with the land and labor resources available in the corresponding representa- tive farms by farm size in Table 3.8. This selection process suggests now the pattern for comparative analysis to follow. Linear programming solutions for eight examples (including 4 cases and their corresponding strata representative farms) will be obtained for comparisons based on the effect of farm size in relation to available labor on cropping patterns. In addition, the 4 case household LP solutions will be compared with their respective actual cropping programs. Having defined a representative farm and corresponding case house- - holds, attention will be given to how they utilize family labor in the production of crops. 54 Table 3.8 Land and Labor Resource Level for Representative Farms and Selected Case Households Farm Size Group Small L. Middle U. Middle Representative Farms Land Area (rai) 5.43 9.88 12.68 Adult Labor Equivalent Female 1.00 1.43 1.53 Male 1.79 1.76 1.80 Selected Case Household Household Number 65 63 50 Land Area (rai) 5.67 10.76 12.21 Adult Labor Equivalent Female .72 1. Male 1.60 2.00 2.00 CHAPTER 4 FARM LABOR UTILIZATION PATTERNS Farm labor use in the family varies according to farm size, the kinds of crops and livestock grown and to a certain extent the family composition. Crop labor needs take precedence over other outlets for labor such as livestock, fruit and vegetables on the farm or trading and handicraft as nonfarm activities and hired labor as an off-farm activity. So our attention to labor use in this chapter will be directed first to crop production labor. 4.1 Crop Production Labor To examine the relationship between farm size and labor use the sample of 30 farms was divided into two groups of 15 farms each according to size with comparisons made between them (Table 4.1).1 The farms in the upper half averaged more than twice as much farm land per household and about 75 percent more land per man equivalent. Why a larger labor force is associated with the larger farms is not explained with data available. It is likely that larger families seek additional land to utilize the larger labor supply. Care must be exercised in interpreting the labor efficiency ratios reported in Table 4.1. Reported hours in crop production includes labor 1Four size groups were not used in this table because atypical farms seemed to negate the relationship. 55 56 00.0 N4.4 N0.N 000003000 00500 N40— 040 4.0000 0000 N04 0.0000 040_ NNN 0.0000 00000 F000» 0000 4mm 4.oomm 000 00— 0.Noom 0000 0N4 F.mmmm 00000 5000 -660 0:0 002 000 mom 0.0000 MNOF 04m 0.NNmm moN mom N.0N~m 00000 5000 F000» 4N0 04 4.000 00_ 00 0.000 000 0N 0.N00 00000 2000 00000 mmN m_~ 0.N04m 4_m Now m.m0mm NNm NNN _.moN_ 00000 0000 .0.E\00: 000N001 .00: .0.E\00I 000N001 .00: .0.E\00: 000N001 .00: NN.0 N00 00.N 300003000 0050 00000 00000 40.4_ NN.0_ 00.N 50000 002000 0000 0000 05000 __< 600: 0000: 000: 00300 04000000: 000 5000 000m 5000 0~0m 5000 00 00000000: 000 00: 00000 _.0 0—000 57 from all sources including family, exchange and hired. Large farms hire more labor resulting in crop hours per family man equivalent averaging nearly 60 percent higher than found on the smaller farms. On larger farms, the cropping program is more demanding for labor and relatively less time (per unit of land or labor) is spent on livestock, and off-farm activities. It is particularly interesting to note that on the smaller farms there are enough additional hours spent in live- stock production and off-farm work to compensate for the less time spent in crop production. 4.1.1 Labor Requirement for Individual Crops Attention will now be given to the requirements for labor for the commonly grown crops in the study area; namely, rice in both the rainy and dry seasons and soybeans, peanuts, and garlic in the dry season. Each crop has a different level of labor requirement depending on the activities performed. Table 4.2 summarizes the time spent on the various cropping activities for the several crops with averages computed using only the farms growing the respective crops. 4.1.2 Nursery for Rice Production On the average, a household requires 5.18 hours and 3.29 hours for .05 rai of nursery, the amount needed to provide seedlings for one rai of rainy season and dry season rice respectively. Labor is required to soak rice. The time required for soaking rice is minimal but before planting the seeds the grower must wait a few days before they are ready to be sown. Meanwhile, the family members may cut grass Crop Labor Requirement by Crop 58 Table 4.2 ————0._. ...... ~— Labor Hours Per Rai by Crop Activity Rainy S. Rice Dry S. Rice Soybean Peanut Garlic Farms Growing Crop 3O 25 28 ll 6 Nursery1 5.18 3.29 -- -- -- 2. Land Prepara- tion Plow & Harrow 19.88 17.99 -- 3.57 46.76 Other (Bed) 4.83 1.61 21.21 32.83 150.85 Sub-total, 24.71 19.60 21.21 36.40 197.61 3. Transplant/ PIant 2 Pull Seedlings 9.94 13.58 -- 17.15 90.51 Transplant/ Plant 11.06 17.22 35.28 38.85 194.60 Other 3.64 1.96 4.83 2.80 -- Sub-total 24.64 32.76 40.11 58.80 285.11 4. Care of Crop3 14.70 17.36 15.83 21.91 205.30 5. Harvest 4 Cut (Pull) 5 19.46 20.65 23.94 66.50 67.83 Bundle (Clean) 6.37 9.52 10.64 -- 123.90 Thresh 6.93 8.12 14.84 76.65 -- Move Grain 4.90 7.49 13.09 31.50 -- Otherf 3.99 .21 3.64 7.42 -- Sub-total 41.65 45.99 66.15 182.07 191.73 6. Total Labor 110.88 119.00 142.80 299.18 879.48 1Nursery labor is for .05 rai of land, the amount needed to establish 1 rai of rice crop. 2Also include seed preparation for peanut and garlic. 3Includes irrigation, insect and weed control, fertilization, fence building, etc. 4"Pull" applies to soybeans, peanut and garlic. 5Clean refers to soybean and garlic. fIncludes straw handling, cleaning, cutting ties, etc. Source: Computed from recorded hours on farms growing the crop. 1973-74 survey. 59 or irrigate the field so that they can plow and harrow. A seed bed must be prepared which is the major task in the nursery. Sowing is done after the seed bed is prepared. The difference in time required for nursery in the rainy season and dry season is due to more time spent on grass cutting in the rainy season and some farmers bought seedlings in the dry season rather than taking time to grow them in their own nursery. 4.1.3 Land Preparation for Crops The labor requirement for land preparation varies according to crop grown. Soil condition requirements for planting as well as planting methods vary. Land preparation for rice involves cutting grass, irri- gating the land, plowing and harrowing and the repair of bunds. On the average, farmers spent about 25 and 20 hours respectively for rainy and dry season rice land preparation. The difference is again due to the amount of time needed to cut grass in the wet rainy season, an activity not needed in the dry season. Rice is planted in fields that have been both plowed and harrowed. On the average, 67 percent of the farmers puddled (the harrowing of very wet soil) their fields twice. Puddling once was done by 23 per- cent in the rainy season and by 27 percent in the dry season. Two passes are made of the field in each puddling. The puddled soil is usually at a depth of from 8 to 12 centimeters. Land preparation for soybeans involves first cutting the rice straw since soybeans will use the same land. The straw or rice stubble is then burned. Most farmers just make a shallow hole in the rice 60 stubble in which the soybean seeds are put and covered. Periodically thereafter, the field will be irrigated. On only 9 of 25 farms were soybeans planted on land that had been plowed and bedded. Time to dig drainage channels in the field is also part of the land preparation activity for soybeans. Land preparation for peanut involves plowing after clearing the rice field then the making of beds (33 hours out of total 36 hours). Other activities are to cut grass, irrigate, plow and dig drainage channels in the field. Land preparation for garlic involves cutting grass, plowing and bedding up. On the average a household spent 151 hours making garlic beds. Peanuts and garlic are grown on beds of about 10 to 20 centi— meters in height. The beds were prepared by hand. 4.1.4 Transplanting Rice and Planting Other Crops Rice will be transplanted after being in the nursery for 20 to 30 days. The activities involved are pulling seedlings in the nursery, bundling them and then cutting the leaves. Seedlings are moved from the nursery to the prepared fields and then transplanted. The most common transplanting time was August for rainy season rice and March for dry season rice. Most households planted 3 to 4 plants per stand and used 30x30 centimeters spacing for rice. Replanting may be needed a week after transplanting. On the average, a household requires 25 and 33 hours to transplant a rai of rainy and dry season rice respectively. Soybeans and peanuts are commonly planted in January. They need 3 to 4 seeds per hill with 30x30 centimeters spacing for soybeans and 20x20 centimeters spacing for peanuts. 0n the average, soybeans require 61 35 hours for planting and 5 hours per rai for replanting while peanuts require 39 hours for planting and 3 hours for replanting. The replanting requirement for peanuts is less than soybeans due to the bedding tech- nique but about 17 additional hours are needed for shelling peanut seed before planting. Garlic needs cool weather, so it is usually planted in November or December. One plant is grown per stand with a 10x10 centimeter spacing. Garlic planting is very labor intensive since it is closely spaced and requires careful planting, fertilizing, and irrigating. In addition, each bed has to be covered with rice straw to preserve soil moisture. On the average, garlic requires about 195 hours for planting alone and 285 hours per rai for all that is needed from the time the bed is prepared to the time the sprouted clove is in the ground. 4.1.5 Care of Crops Activities in crop care are similar for all crops. They include such activities as irrigation (watering), weeding, insect control and post-planting fertilization. The time spent on these activities varied according to crops. Fertilizers are used mostly in the dry season crops such as dry season rice (which is a high yielding variety) and garlic. Manures are commonly used in rainy season rice, soybeans and peanuts. Fertilizers are usually applied 15 to 30 days after planting. Some farmers used a chemical for killing crabs in the rice field. Irrigation water is usually maintained at 5 to 10 centimeters in the rice field and usually during the dry season the field is flooded once every two weeks. Most households weeded their rice but did not weed soybeans and peanuts. Garlic is weeded heavily. Most weeding is 62 done by hand and with hoe. For rice, most farmers waited until the weeds were 10 to 15 centimeters high before weeding. 0n the average, the time requirement for care of crop ranged from 15 hours for rainy season rice to 205 hours for garlic. 4.1.6 Harvesting The time requirement for harvesting also varied widely among crops for the various activities involved. For rice, harvesting activities begin with cutting rice stalks, bundling them and then moving the unthreshed rice to a central place. Some farmers might make bamboo ties from their own bamboo trees. Threshing is mostly done by hitting the rice bundle against a huge basket (called a "Ku") so that the grains drop into the basket. The rice grains are then cleaned and moved to be stored in the barn. Rice is usually stored in paddy form to be milled a week or as little as a day before consumption. Straw and other crop residues are used for livestock feed or as a mulch for garlic and mushrooms. If straw is sold, additional time may be required to build and stake a straw stack. 0n the average, a household requires 42 and 46 hours per rai for harvesting rainy season and dry season rice respectively. Soybeans are generally cut or pulled, bundled for drying one to three weeks before threshing. Cutting, threshing and cleaning are major activities for soybean harvesting and require about 66 hours per rai on the average. Peanuts are generally dug and dried for 3 days before threshing. Threshing is done by hand and requires about 77 out of the total 182 hours for harvesting activity, the time needed for harvesting one rai. 63 Garlic requires about 68 hours on average per rai for digging and 124 hours for bundling, cleaning and drying. Typically, farmers will either sell their garlic green in the field or sell them soon after harvest. Garlic is the most labor intensive crop, not only requiring the most per rai but also requiring it for a relatively short period from planting to harvest. 4.1.7 Relative Male and Female Participation in Crop Labor Activities Table 4.3 shows the relative contribution of men and women and children in the various crop production activities for the several crops in the study area. In general, we can say that men do the activities which need physical strength like plowing, harrowing for rice, bedding for peanuts and garlic, pulling rice seedlings and threshing rice and soybeans. Women are generally more skillful in transplanting and cutting at harvest time. They also do bundling and moving rice. Women spend more time than men in planting dry season crops such as soybeans, peanuts and garlic. Bundling and cleaning soy- beans and peanuts were done more by women than by men. Women represented 38 percent of the average family labor force on a man equivalent basis and contributed 47 percent of the total labor utilized in crop production. Children play a minor role in farming operations due to schooling. Their contribution will be used primarily in the critical periods for planting/transplanting or post harvesting activities in the dry season. On the basis of adult man equivalent, children constitute 8 percent of the labor force but contribute only 3 percent of the labor spent on crop production (Appendix Table 4.1). 64 .ucmucma cop apuumxm can» «cos :0 ems» mmwF m—muou cw p.3mmc 3mg acwucaomF m.~ F.5m m.ovmm.n m.ee 3.33. ~.m m.me ~.me a. m.mm ~.mm F.F p.~m m.om page» 0.3 m.~m m.wmm~.mp m.om m.~mw m.n m.m¢ N.me 0.. m.nv m.Pm m._ m._¢ m.nm Papohigam o o o W o N.eo m.mm3 m.m v.mm m.mm 1 o o.oo~ m.F o.Fm n.mm cmcuo o o o Mm.PP m.m~ m.mmm _.o o.mv m.m¢ . m.mm m.o¢ ¢._ P.3m ¢._¢ m>oz o o o Mm.mF m.mo m.mpm m.¢ m.- m.- o N.F m.mm o o.o m.em smuggh o ¢.mm o.Fvw o o o mm.m m.- P.m_ ¢._ u.om m.uv m.m «.me e.w¢ Acmmpov mpuczm P.F_ N.mm P.mmmm.P_ 0.3m n.3mw F.p o.om m.mm m._ o.Fm m.~m m. n.m¢ m.m¢ AF~=av psu M pmm>gm3 m.~ “.mm m.mmw 0 _.mm m.on m. m.mm m.om o ¢.m~ 0.33 m. N.mp ~.vm maogu we menu 0 m.um «.mmmm.~ “.mm _._¢ m.m m.~o N.mm o m._o m.wm _.N o.mm m.mm quohunzm o o o n o o.m_ o.mw m.¢ m.om P.mm o c.mm ¢.o¢ m._ _.—u m.om . gmguo o o.mm o._mm¢.m o.wm m.mm m.m m.mm m.mm o e.m~ m.m~ ~.p «.mm m.mm “cmpa\u=mpamcmcp o 3.0m m.m _ o «.08 e.mm o o c o m.me 3.0m m.~ “.mm e.mm Aumam .aweav 3 chFuomm Fan m “cm_a\pcmpgmcmgh 3 o N.m~ m.en o m.m m.om m.~ m.F¢ P.om o N.m m.o~ m. ¢.m m.mm Pmuohinam o m.FF v.wm o _.¢ m.mm c o o o N.—N m.wn o m.mp o.¢m Aumnv gmgpo o o o o o o.oo_ m.~ m.P¢ ~.mm o m.— ¢.mm v. a. m.mm 3ocgw: a zepm .amgm use; 0 o.m_ o.mw ¢.F m.m_ F.mm 3gmmg=z u 3 z u 3 z o 3 3 u 3 z u 3 z owpgmw “scam; cmmoxom muwm commmm ago muwm commmm xcwom P m.v mpnmh aocu 3n mm_uw>wuu< so» xmm 33 wow: conwA aogo mmmucmugma 65 One may wonder whether the relative contribution of women to the production of crops varies according to farm size. Obviously, the reported time spent by women will vary according to farm size class if the proportion of women in the labor force varies from class to class. On the basis of adult labor equivalent, the proportion of women in the total labor force per household varied from 32 percent in the small farm class to 43 percent in the upper middle farm size class. Therefore, to examine the relationship between women's contribution according to farm size adjustment was required which assumes the same sex composition in the labor force for all farm size classes. This was done and is reported in Appendix Table 4.1. With the adjustment for constant sex composition, we observe that the women's contribution to crop production work varied from 45 percent in the small farm class down slightly to 40 percent in the upper middle farm size class and 42 percent in the large farm size class. We need not conclude from these findings that women are incapable of doing those activities which are dominated by men nor that men are incapable of doing those activities usually done by women. Nevertheless the figures strongly suggest that the kinds of labor by sex and age are not perfectly substitutable. Whether the apparent differentiation is due to local tradition and/or differences in physical stamina and functional skills cannot be documented from data available from the study. In any case, it appears that this facet of family labor utiliza- tion appears sufficiently important not to be ignored in the implementa- tion of proposed cropping systems. Later in the thesis labor require- ments for both male and female will be specified separately for the 66 various crop activities. 'These requirements will follow the relation- ship shown in Table 4.3 in which it can be noted that the woman labor contribution to individual crop production varied from 32 percent for rainy season rice to 57 percent for garlic. The assumption that male and female labor are used in fixed proportions as differentiated inputs may not be fully defensible. Nevertheless, on the basis of the results in Table 4.3 this assumption seems more reasonable than an alternative one which would assert that all family labor is perfeCtly substitutable regardless of age or sex. Further observation on the contributions of women to the farm labor effort will be made in subsequent sections of this chapter. 4.1.8 Crop Labor by Source Labor for cropping is available from three main sources: the family, exchange labor from other households and hired labor. Table 4.4 shows the percentage of the various crop labor that were provided from these activities by sources. In general, labor for crop production is drawn from family more than from other sources (above 50 percent). The family supplies 77, 65 and 73 percent of the total in the production of soybeans, peanuts and garlic respectively, while for both rainy and dry season rice the share is about 56 percent. Exchange labor is used extensively for the threshing of rainy season rice (66 percent) and for transplanting it (43 percent). It is also high for rice threshing (73 percent) and rice cutting (42 percent) in the dry season. Exchange labor is also used in other dry season crops for activities such as threshing soybean (44 percent), plowing .acoucwa cop xpuuuxm cagu ages so cog» mmoF upmuou c. uFamac Ame merucaozp m.mm m.v m.- m.- m.~ o.~m ~.mm ¢.m o.op o.u~ o.o. m.w~ ~.- m.F~ m.mm 4oz o m.¢e o.mm ~.- m.m~ m.m P.o o.mo m.w~ guess» 0 o 9.2: a; is 3.3 3.. 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FLMG pacmwa :mmnxom may: comamm 3pc muwm :omomm acvum — mm_uw>_uu< new oucaom an mom: Lonm4 coco oompcmugoa e.¢ wpnap 68 and harrowing (84 percent) and cleaning peanut (54 percent) and making bed for garlic (68 percent). A household will keep record of the exchanged labor days which have been received and given for the purpose of having the days given be equal to days received. The decision of whom to send in the family for exchange work depends on the activities. A woman would represent a family in transplanting while a man would be sent for making bed. Exchanging labor is traditional and considered a social function. It improves community morale as each household shares in the social obliga- tion to finish some rice crop operation within a short period of time. The host will usually provide food and drinks to the helpers. The fact that received exchange labor is paid back in like effort means that there is very little indebtedness of duty carried over from one period to another. The general community concern for successful crop production in general and the exchange labor phenomenon in particular is an important aspect of agricultural production in Ban Pa Mark. However, in the linear programming model to follow, the exchange labor procedures will be omitted for the following reasons: (a) it is unusual for a family to engage more exchange labor than can be repaid by the family members, and (b) the repayment of the exchange labor usually is done within a period of less than 28 days. These reasons combined make the linear programming model behave essentially the same whether account is made of exchange labor or not. Hired labor is used to supplement family labor in the critical periods of both the rainy and dry seasons. It accounted for 22 and 16 percent of all labor in the production of rainy season and dry season 69 rice respectively (Table 4.4). It is particularly important for the pulling of rainy season rice seedlings where it accounted for 64 percent of the total on the average. It accounted for 26 percent of the labor in rainy season rice transplanting but increased to 40 percent of the transplanting labor to dry season rice. At the opposite extreme, labor use for the production of soybeans, peanuts and garlic involved only 3, 3, and 5 percent hired, respectively. A family may prefer to hire men to women or vice versa depending on the kind of work. For example, women are preferred to men for transplanting rice and for undertaking dry season post-harvesting activities. Of course, the wage rate and the productivity of hired labor are important in determining the demand for it by farmers. Wages paid for hired labor seasonally and for specific task will be discussed in a later chapter when crop production and expenses are analyzed. 4.1.9 Seasonal Distribution of Crop Labor Growing period and the labor required for production activities govern the seasonal pattern of crop labor. To analyze the annual labor profile for crop production, the year was divided into 13 periods of 28 days each (except for the first period which was assigned 29 days). The periods are as follows: Period No. Starting Date Ending Date 1 July 1, 1973 July 29, 1973 2 July 30 August 26 3 August 27 September 23 4 September 24 October 21 5 October 22 November 18 6 November 19 December 16 7 December 17 January 13, 1974 8 January 14, 1974 February 10 70 Period No. Starting Date Ending Date 9 February 11 March 10 10 March 11 April 7 11 April 8 May 5 12 May 6 June 2 13 June 3 June 30 The seasonal distribution of labor will be presented and analyzed by these periods. However, in the LP model, periods 2, 6 and 10 will be divided into two and periods 3, 4 and 5 will be combined to more accurately represent the actual timing of crop production activities. 4.1.9.1 Seasonal Crop Labor Distribution in the Total Sample Figure 4.1 shows the profile of farm labor used in crop and other farm production. It is clearly seen that crop labor uses are highly seasonal. In general, time in period 1 is used for nursery and land preparation, period 2 is primarily for land preparation and transplanting and period 3 is for transplanting. On the average, a household used 122, 253 and 219 hours for crop production in periods 1, 2 and 3 respectively. The transplanting period for individual farms can be either periods 2 or 3 depending on whether the family harvested dry season crops in period 1. Periods 4 and 5 are slack periods when the crop labor use dropped to only 48 hours in period 4 and 39 hours in period 5. After rice is in the field these two periods become the waiting periods. During this time some farmers will fertilize, weed, and irrigate the crops. Period 6 is the rice harVesting period. Period 7 is a combination of rice harvesting and dry season land preparation and planting. It is the most critical one requiring 476 hours of labor. Rice harvesting 71 n. N. __ o. magma om co nowgma Lma Lao: mmmcm>< .mfiwmoga conm3 Egan _.q mczmwd m o c. m n n ~ _ 8.22 Loam; aogu MHHH .833 Eco... .350 E 31 m an 00. 1 nxum” 1 00¢ H .. con 4 Com 72 can occur in either period 6 or 7 depending on whether it was planted in period 2 or 3. Period 8 is primarily for dry season planting. Periods 9, 10 and 11 are the dry season slack period using 115, 54 and 93 hours for crop labor respectively. Periods 12 and 13 comprise another peak period in the dry season when dry season crops are harvested. They averaged 207 and 228 hours of crop labor per household respectively. The share of the work load in farm work borne by men, women and children is shown in tabular form for each period in Figure 4.1. The distribution of work according to sex varies through the season as they perform their respective specific tasks. Men carry the heaviest share of the crop work load (88 percent) in period 1 when rice nursery and land preparation activities take place. The women's role is shown in periods 2 and 3 (31 percent and 53 percent of the crop work respec- tively) when rainy season rice transplanting takes place. In periods 6 and 7 women share almost equally with men in harvesting rice and planting dry season crops while in period 12 women worked more than men (48 percent compared with 41). It can be noticed that the labor contribution from children in relative terms is most in the dry season (highest in period 12 with 11 percent of total). During the school break from March 15 to May 17 (periods 10 to 12) children are called upon to contribute more heavily at the time when dry season rice is harvested. Though minor in relative terms, the contribution of child labor is evident in other peak labor periods of the year. 73 4.1.9.2 Seasonal Crop Labor Distribution for Representative and Case Farms Labor profiles for crop production and other farm work are pre- sented as bar graphs in Figures 4.2, 4.3, 4.4, and 4.5 for comparing the selected case farms with their corresponding group average (representative farm). In each figure for each period, the case farm appears on the right with the representative farm on the left. In making these comparisons it is appropriate to begin by comparing the kinds and amounts of crops grown which in turn determine the seasonal labor requirements for crop production (Table 4.5). Obviously, for a given farm, a larger area for the production of dry season crops will result in a higher labor requirement especially if they include labor intensive crops such as garlic. Considering the representative farms, they will contain all crops grown even though, for a particular farm, only one dry season crop may be grown. In Table 4.5 we see that all four representative farms show at least a little of each possible crop being grown when in fact for the 30 household sample, there was but one farm where all possible crops were grown. This is one difficulty with using the representative farm approach. Nevertheless, as the labor profiles indicate, the peaks and troughs of the seasonal distribution of crop production labor follow similar patterns whether we speak of an individual farm or a representative farm defined as a composite of farms of a similar farm size. Another point worth noting is that the composite representative farm tends to depict a much more uniform labor requirement over the year than that actually required for an individual farm. This is because the critical periods for all farms do not coincide. Different 74 n. mo upocmmao: new sewn m>_umucmmmgamm Pmem Low vowgma emu mczoz mamgm>< .mpw$og¢ Loam; Eco; N.q mesmwm N. : O. m m h . w 0 ¢ n Loam; aogu Loam; Econ cmguo D E uo_ema com com 75 mm upocmmzc: new Econ m>wumucmmmcamz m_unwz Logo; L03 cowcmq cm; Lao: mmmcm>< .m__moc¢ Loam; Egan m.v mczcwm m. N. __ o. m m - m 0 ¢ n N _ cote; CON con 00¢ .593 no.5 D Loam... ES .550 g 000 com 76 n. N. om v_o;mm:oz ucm mFuv.: emqa: eom nowemm emu e303 momem>< .. o. m m h m eono. goeu eonc. gem. emcee Eeme m>wumucmmmeomm .m_weoea eonm. sewn v.3 mezmwu n v m N woweae OO. OON con 00¢ com com 77 m u~ozmmzox can send mcem. eoe uo_eme ewe ego: momem>< .m_wmoe3 eoam. seam m.v we:m_e n_~_:o_moeon¢n~.§§ e83 aoeu D :53 sec. emfioa ooe. 78 .mmmpu m~wm gene eoe gene m>wpopcmmmeqme u.nm¢ F omen pmmm mmmm mwem .eow _ mmep W noe~ NPNN mesa: aoeu Pouch _. o e. o m.. W o w m.~ m.m ucmueme Fo. -11 mo. -- mp. -- 3.. mm. Pam . uppemw e. o ~.~_ m.~_ m.~ o F.e o ucmueme .m. -1- mm.~ m..~ mm. -1- mm. -- pea . muzcmme m.me m.eo m.ee m.mm a.~m w 0 _.mm e.em bemaewe um.m em.o_ eo.c mm.¢ mm.m M 1-- om._ o~.m Pom w mcmmnaom «.mm m.~o o.m~ N.m ~.¢~ W ¢.mm o.~o P.mm pcmoema mm.o -.o_ mm.m oo.. mm.~ M mo.m vo.m mm.m Fem ; muvm .m zen co. co. co. co. oo. oo— co. co. ucmueme me.m~ e~.o_ mm.N— .~.~_ mm.m m~.o— m¢.m mo.m Pom «gem .m eeeam Pwamm m upogmmaoz _.Qmm om upogmmso: _.am¢ ”mo opogmmsoz _.amm mo upogmmaoz noeu 35 mFuuwz eman: mpucwz emzo. FFmEm cam—goeu mo mmm.u m~vm seam ucmoeme new wax m.¢ wpnmh mseme m>wumucmmmeam3 new ammo .czoec mqoeu 79 crops grown in different proportions and with different planting and harvesting periods among the several households make this true. It is possible to make some simple observations at this time to explain why the case farm profiles differ particularly in some periods from the corresponding representative farms. For example, Farm 65 has a relatively high labor requirement in period 1. This is due to the need to harvest soybeans and dry season rice in this period which postpones the transplanting of rainy season rice to period 3, another period with labor use higher than average. (Detailed crop production activities for each crop on each case farm are shown in Appendix Tables 4.2 to 4.5.) Comparing household 63 with its corresponding representative farm in the lower middle farm size class (Figure 4.3) we observe that the seasonal peaks are similar for each period except period 7 where the representative farm was ten times more than household 63. This differ- ence is explained by the fact that household 63 grew only rice in the dry season whereas the representative farm had over 50 percent of its land to soybeans requiring land preparation and planting labor in period 7. Comparing household 50 with its corresponding representative farm in the upper middle farm size class (Figure 4.4) we observe that the peak periods occur for both in periods 2, 6, 7 and 12. Their cropping systems are similar except that the representative farm has a much higher proportion of land in dry season rice. Household 50 required more labor in period 2, 7 and 12 than the group average. This is explained by the fact that rainy season rice land preparation and . . 80 transplanting were concentrated in period 2 resulting in the harvesting being spread to periods 6 and 7. Period 7 was also the period for planting soybeans and land preparation for peanuts. Comparing household 3 with its corresponding representative farm in the large farm size class (Figure 4.5) we observe that the seasonal profile is similar to that of other farms discussed except that as the farm size increases the total crop labor increases accordingly. The critical periods are more pronounced on farm 3 because of the larger area of dry season land being used for rice and soybean than was the situation for the representative farm in this size class. The annual crop hours by crop and activities for the four case households are summarized in Appendix Table 4.6. 4.2 Other Farm Labor Labor spent on other farm work is primarily for the care of live- stock and poultry including buffalo and cattle, pigs, hens and ducks. Time spent (mainly by men) in taking care of buffaloes and cattle is for cutting grass or taking them to and from pasture which are not fenced. In the care of swine, time is spent collecting pig weeds and banana stems which are cut up and cooked before adding bran, household waste, broken rice, etc., for feed. This work is mainly done by women. Fruit production is not a significant activity. Generally no time is spent taking care of these trees until harvesting for either the local market or home consumption. Vegetable gardens are mainly for home consumption. Time require- ments for the vegetable gardens are chiefly for watering and picking the crop. Women and children are generally engaged in these operations. 81 All of these non-crop labor activities on the average represented 19 per- cent of farm work and 9 percent of total family labor. 4.2.1 Seasonal Distribution of Other Farm Labor Figure 4.1 shows that these other farm labor activities are dis- tributed throughout the year but the hours spent do not fluctuate as widely as for the crop labor. 0n the average, the least time spent (24 hours) was in period 1 while the peak (79 hours) was in period 4. The slack periods for crop production appear to coincide with the periods when the other farm work activities are the highest. For example, periods 4 and 5 are generally slack for crops but peak for other farm work (79, 71 hours). Table 4.1 shows that on the average a farm spent 568 hours of their labor in the other farm activities. In general the figures show that this time spent in these other farm activities per household per year was independent of the farm size. 4.2.2 Seasonal Distribution Comparison of Other Farm Labor Between the Farm Size Groups and the Case Households The other farm labor distribution of the representative farms and the cases in general followed the same pattern, i.e., the other farm peak labor occurred at the slack crop labor periods, mostly period 4 and 5 (Figure 4.1). The difference in labor used in each period and annual total labor used between case and representative farms depended chiefly on the kinds and number of livestock raised (Table 4.6). The small representative farm averaged 576 hours annually in the other farm work compared to 291 hours for household 65. The difference was in the time needed to take care of cattle in the small representative 82 .opaeezn ecu m0~em>m as» 0. umc=_u:H_ m om. Na omem 0.N .0 e m. N.. NN . .auoe 0 0 me me 0.. F P F 1-1 0 m 0903mm=oz e on N0 000 0.. m_ N F._ N seam .003 omen. 0 0 00 00 0.. P P N -- 0 om upozmmzox N. 0N. pm. 00.. 0.— 0. m 5.. N seen .003 0.00.: e000: 0 0 00N 00N 0.0 . 0 p 0 0.N N 00 uponmmzoz 0 0 pm. 0.0 «.0 0N m 0.. a seam .nmm mpoupz emzo. 0 0 me me 0.N N F 0 1-1 0 00 0903mm=o= 0 0 mm 00N P.. 0 m 0. 0 seem .0mm .FmEm mmoem>< em0502 womeo>< emnssz m0~em>< em0202 mmmem>< ewnE=z mmmem>< ewnsaz 10m~m3u00 100. mew: 00.30 mzoo opmeeam mmmu 3eu~=oe 0:0 xuoumm>w3 \azoew «~00 maemu ammo use m>vumucmmmeamm .mmmem>< new memasaz .xeyFsoe 0:0 xuoumm>w4 0.0 «pack 83 farm while household 65 did not have any. The lower middle representa- tive farm averaged 557 hours annually compared to household 63 which spent 766 hours for its other farm works. From Table 4.6, household 63 had 2 buffaloes, 9 pigs, 200 baht worth of poultry which is a larger livestock inventory for the representative farm for the size group. The upper middle representative farm averaged 505 hours compared with house- hold 50 which spent 645 hours. The difference can be seen from the number of pigs. The large farm group averaged 626 hours which was less than the 758 hours spent by household 3. Since the number of cattle were comparable in the two groups, the difference can be due to time spent by the family on the kitchen plot. In the linear programming analysis to follow, the livestock, vegetable and native fruit activities will be excluded from the set of productive activities in the model. However, this section has demonstrated that these farming activities are an integral part of every household. It will be assumed that these activities should be maintained at the reported levels regardless of what the cropping program might be. CHAPTER 5 OFF-FARM LABOR PATTERNS The pattern of labor availability and use over the season is a key to understanding the village agricultural system. Chapter 4 described the crop labor use pattern. This chapter described the off- farm labor uses and commitments. From this description, we will hope to determine the extent to which the off—farm labor activities comple— ments and to what extent they compete with the all-important family function of crop production. For purposes of this description the off-farm labor activities are classified into exchange labor, paid labor and other income generating activities and unpaid special activities. 5.1 Exchange Labor Exchange labor has been practiced in Thai rice production for centuries. It usually occurs in transplanting and harvesting periods when the work must be done quickly. Farmers have experienced that if the seedlings are transplanted too young, they will be weak and damaged. If transplanted too old, the tillering phase is shortened and yield is consequently reduced (Janlekha 1955: 108; Grist 1959: 120). It also reduces yields if unrooted seedlings are transplanted in a dried out condition (Thailand 1947: 67). In order to minimize these dangers, farmers usually transplant in large work groups so as to accomplish 84 85 the task quickly. Similar arguments apply to harvesting. Farmers fear that "if the harvesting is delayed for even a short period of three or four days, the paddy will be over-ripe, resulting in a higher propor- tion of breakage and hence in a lower price" (Janlekha 1955, p. 109, Kaufman 1960: 41). These reasons explain why exchange labor is a major community concern and why all families engage in it. The whole village must plan and schedule transplanting and harvesting dates in such a way as to permit everyone to have a chance to receive the labor of others and to give of their labor. Exchange labor practices have also extended to the planting and harvesting of some dry season crops. The notion of exchange labor carries with it the obligation to provide meals and drinks to others when you receive it. Meal expendi- ture for exchange labor is reflected in the consumption expenditure pattern presented in the next chapter. The host tries to make the atmosphere relaxed and pleasant so that work can be done smoothly and quickly and to see that everyone is happy. The commitment that exchange labor received must be paid back equally and timely is a constraint to labor availability for the care of crops on one's own farm. But if it can be assumed that laborers are of equal productivity, the result is to make debts equal credits and by staggering crop production events the community is able to accomplish more than if each household functioned independently. On the average, men provide 62 hours per person and women provide 61 hours per person of exchange labor (Table 5.1). Thus, for the entire year the role of women in exchange labor activities is essentially equal to that of men. However, the share of exchange labor provided 86 Table 5.1 Average Annual Non-Farm Activities by Sex Activity Men Women Exchange Labor Paid Labor Activity_ Laborer Service Activity Handicraft Trading Fishing and Cooking1 Sub-Total Unpaid Special Activity Ceremony Community Activity Other Sub-Total Total (Average Hours per Person) 62 61 269 92 4 6 101 648 44 - 169 15 27 433 942 53 43 34 8 127 55 214 106 709 1109 Source: Survey. 1 Cooking or preparing food for sale. 87 by women varied widely from season to season (Table 5.2). The most exchange labor activity takes place in period 2 (land preparation and transplanting), period 6 (rice harvesting), and period 8 (planting dry season crops). Except for period 4, 9 and 10 exchange labor may take place at other times of the year but not at a very significant level. As might be expected, the differentiation of crop production activity in exchange labor by sex followed closely that found in home crop production activity. During the transplanting period, men are engaged mostly in pulling, cutting, bundling and carrying seedlings while women do the actual transplanting. This is explained by saying that the strength of men is suited for the more demanding physical tasks while women have more nimble fingers and thus excel in the delicate work of transplanting. The division of labor is also a matter of culture and propriety. For example, it is considered improper for women to raise their legs in order to knock the soil from the root of seedlings. Nevertheless, when practical circumstances require it, women do the work of men and men do the work of women. 5.2 Unpaid Special Activities Special activities are classified into three types: ceremonial, community activity and others. Ceremonial activities include weddings, funerals, anniversary celebrations, house dedications, and monkhood ceremonies for sons, all of which are traditional and important to a host family. These sometimes involve the whole community since in Ban Pa Mark it appears that nearly everyone holds some kinship relationship to all others. Thus, it has been common practice for every household 88 Table 5.2 Seasonal Distribution of Non-Farm and Off-Farm Labor for the 30 Households 2 Percentage b Period1 Period Class Exchange Off-Farm Labor ,Special Totali 1% P% T%' P%’ % 7P1 ’1% M 59 1.4 20 1.4 61 3.8 28 1.9 l W 41 1.0 79 5.6 39 2.4 72 4.8 T 100 2.4 100+ 7.1 100 6.3 100 6.7 M 46 7.3 23 2.2 73 2.8 28_ 2.6 2 W 54 8.6 77 7.5 27 1.0 71 7.2 T 100 15.9 100 9.7 100 3.8 100+ 9.0 M 57 6.7 31 3.5 81 5.8 39 4.1 3 W 41 4.8 68 7.5 19 1.4 60 6.3 T 100+ 11.6 100+ 11.1 100 7.2 100+ 10.5 M - - 34 4.2 68 4.4 38 4.0 4 N - - 65 7.8 32 2.1 61 6.4 T - - 100+ 12.0 100 6.5 100+ 10.4 M 6 * 36 3.9 64 5.4 40 4.0 5 W 94 1.0 63 6.9 36 3.0 59 5.9 T 100 1.0 100+ 10.8 100 8.4 100+ 9.9 M 66 25.7 36 1.8 55 3.3 48 3.3 6 W 34 13.1 64 3.2 45 2.7 52 3.7 T 100 38.8 100 5.0 100 6.1 100 7.0 M 23 .3 26 1.0 60 2.0 31 1.2 7 W 77 1.4 73 2.9 40 1.3 68 2.6 T 100 1.7 100+ 4.0 100 3.4 100+ 3.8 M 25 4.4 29 2.0 53 1.9 31 2.1 8 W 74 12.5 70 4.8 47 1.7 68 4.6 T 100+ 17.5 100+ 6.8 100 3.5 100+ 6.8 M - -3 28 2.9 61 6.6 34 3.4 9 W 100 * 72 7.5 39 4.2 66 6.6 T 100 * 100 10.5 100 10.8 100 10.0 M - - 33 3.0 55 6.4 38 3.5 10 W - - 66 6.0 45 5.1 61 5.6 T - - 100+ 9.2 100 11.5 100+ 9.1 M 32 * 32 1.7 60 6.5 40 2.5 11 W 68 .2 68 3.7 40 4.3 59 3.6 T 100 .2 100 5.4 100 10.9 100+ 6.1 M 65 2.9 32 1.4 73 6.3 46 2.3 12 N 35 1.6 64 2.7 27 2.3 52 2.6 T 100 4.5 100+ 4.3 100 8.6 100+ 5.0 M 55 3.4 15 .6 61 8.0 36 2.0 13 W 45 2.8 83 3.3 39 5.0 64 3.6 T 100 6.3 100+ 3.9 100 13.0 100+ 5.6 Total Hours XX 174 XX 2584 XX 586 XX 3344 1P% 8 Percentage of Period; T% = Percentage of Annual Total. 2If men plus women < 100%, the difference is child labor indicated by +. 3* = less than 1%. 89 to offer some help and participation. These activities in general take priority over crop production or activities for the earning of cash. The economic implications are that the more ceremonial activities there are that occur in the village the less time there is available for farming. Actually these ceremonies (except for funerals) generally occur in the dry season (periods 9 through 13) when farm work is not labor demanding (Table 5.2). It is forbidden to have a wedding during the three rainy season months of Phansa, the so called Buddhist Lent (July through September). All marriages customarily take place either just before plowing or just before harvesting. As a young bachelor explained, the "old people won't permit marriage at any other time. They say that the son-in-law would then be coming just in order to eat their cooked rice" (Moerman, 130). In the central plain, funerals are held in the dry season. Corpses are often held in the morgue of the temple until after harvest when public ceremonies begin. But in Ban Pa Mark, funerals may occur any time during the year. The ceremony involves religious functions and decorating the cremation platform which may take more than 8 hours a day for 3 to 7 days. House dedication and anniversaries are held mostly in the dry season. The monkhood ceremony is preferred before the Phansa. In the North, parents usually get their boys aged 12-15 to a monkhood rather than wait until the son has reached 20 years or more since labor is so important in farm production. Even though it is the son that has been given up for a religious purpose, the ceremony involves the entire family for a few days. Referring again to Table 5.1 we see that men 9O spent 53 hours and women spent 43 hours annually for ceremonial activities. Community activities are usually social events as well as an obligation to all households. Examples for Ban Pa Mark included irrigation canal cleaning and repairing, repairing a road to the village and building a new road to the temple. The village has its own tradi- tional irrigation which is administered and maintained locally. Each farmer is obliged to be a member of the association and must agree to provide material and labor to maintain the canal in exchange for the right to use water. Cleaning and repairing usually takes place in period 1. Each household must prepare materials such as bamboo baskets, rocks and/or wood in an amount proportional to their farming area and to bring them to repair the weir. This is usually done in period 3. Repairing the road to the village and building the road to the new temple were done in periods 12 and 13. Table 5.1 shows that men pro- vided more of their labor than women (34 hours compared with 8) per person on the above community activities. Other non-regular activities included: unspecified trips away from home, government type business, farmer group or cooperative ~ meetings, visiting friends and relatives, trips to the hospital, special shopping trips, getting haircuts, repairing vehicles, repairing the bridge to the household compound, hunting, finding ant eggs, baby sitting, chopping wood and some other pleasure and business excursions. 0n the average, these activities took 127 hours for men and 55 hours for women annually. 91 5.3 Paid Labor The off-farm income generating activities in the rainy season reflect how farm family members use their time while waiting for the crops to be ready for harvest. Working in handicraft or as a laborer may be a good way to occupy one's time. Table 5.1 shows that women spent more time than men in handicraft and trading. Men concentrated more on the wage laboring activities such as house building and furni- ture construction which are usually done in the dry season. These activities take men away from farming, leaving women to be responsible for dry season crops. The implication of this finding to the Multiple Cropping Project is that if new crops are to be introduced, their planting requirements must be suitable to women or their expected return must be high enough to attract men away from their current non-farm income generating activities in the dry season. Some men engaged in trading but to a lesser degree than women. Performing services such as hair dressing and dress making and preparing food for sale accounted for some of the women's time but not a significant amount. 5.4 Seasonal Distribution of Off-Farm Labor Figure 5.1 and Table 5.2 show the seasonal distribution of non- farm and off-farm labor for the 30 households under study. Exchange labor that a family must give corresponds to the special crop activity periods and especially in period 6. None of the exchange labor given occurs in the crop slack times of periods 4 and 10. Off-farm income generating activities of the family members occur in every period of the year but are concentrated in the slack periods such as periods 4, 5, 9 and 10. Special activities also occurred in every period but were e000. .mwumam 0.000: use 0.00 .mmcmguxu mo mpwwoee Pacemmmm m - 92 oo. CON v I O O O O " 0.. O... O. O... 0. VV 0 I. O O. con 't'. O. C. .0 O O. e000. .mwumam 0.00:0 HHHHH .803 0.50 a 1 000 e000. mmcmzoxm 1 00m 93 concentrated in periods 9, 10, 11 and 13. This demonstrates that the non-farm labor complements the farm labor efforts and serves to smooth out the total family labor seasonal profile. In periods where there was a high demand for crop labor, less time was allocated to non-farm and other activities. In the period where less labor was required, farm family members supplement their income by working off the farm, trading and by engaging in handicraft activities. 5.5 Seasonal Profile of Total Labor 5.5.1 Seasonal Profile of the Total Sample The seasonal labor profile of the 30 households and the percentage breakdown between farm and non-farm work is shown in Figure 5.2. It shows that farming activities dominated in periods 6, 7 and 8 as well as periods 12 and 13. We learn from this that in the sample households, the families are able to allocate their labor in such a way as to remove most of the peaks and troughs observed earlier in the annual labor profile of farm labor distribution alone. This is an important observation because it indicates how inappropriate it would be for a farm advisor to recommend farm reorganization on the basis of only the crop labor requirements. 5.6 Seasonal Distribution of Labor by Farm Size Group and Case Households Table 5.3 is a summary of average annual total labor uses by farm size groups. It reports hours per household and percent of total hours spent on the various kinds of labor activities. It shows that on the average a family used 48 percent of its labor for farm and work and 52 percent of its labor in off-farm paid and unpaid activities. Of the mnpozmmzoz om 030 No momem>< .eonm. Eemm-coz new Eeme mo m_weoe0 Pacemmmm N.m mez0wu 02.83 m. N. .. O. m m h m n v n N . 94 L can 1 00¢ .. 00m 1 00m .803 FEE-:02 D e003 sea... a .- CON. 95 .ucmuema . can» 000. . 0.00. 0N00 0.0001 .0001 ouppbi 00N0 0.00. 0000 0.00.- 0000 10 ..N 00. ..N 00. 0.. 00 N.. .. 0.N 0m. 0 0.N0 0000 N.00 0000 ..00 0N.0 N.00 .000 N..0 ...0 3 0.00 000N ...m 0000 ..00 N000 0.00 000N 0.00 0NNN z 0000. ..N0 0000 0.00 .000 0.00 00.N 0..0 0000 0.00 0.00 . 0. .N .. N0 .. m N. .. .. . 0 sec. 0.00 000N ..0N 00.. 0.0N 000. N.00 000N N.N0 000N 3 -:oz N.0. 0NN. ..0N 000. N.0. .0.. 0.0. .00. 0.NN .NN. z .000. ..0 000 0.0 000 N.0 N00 0.. .00 0.0. 000 . 1 . a 0 1 1 - 1 1 1 0 0.0 0.N .0.N 00. ..0 00N 0.N 0.. ..0 00N 3 0.0 0.0 0.0 000 0.0 00N 0.0 00N 0.0 0.0 : rm.omam 0.00 000N ..N0 .00N ...0 N00. 0..0 .00N 0..0 000N . 0. 0. 0. 00 .. 0 N. .. - 1 0 0.0N .0.. 0.0N .00. 0.0. 0... 0.00 .0.N ...0 000N 3 e000. 0.N. 00. 0... 0.0 0.N. 000 N... 000 0.0. .0. z seam-0.0 ..N 0.0111 0.0 00w. 0.N 00.1 0.N 00. 0.N- 00. . 1 . - - 1 1 - - .. . 0 0.. N0 0.. 0. 0.N 0N. 0.. 00 0. .0 3 0.. .0 0.N N..1 0. 00 0. 00 -0.r 0.- z 00:0:uxu 0..0 0.00 0400 00.0 N.0m 0000 0.N0 000N ..00 000.11 . 0.. 0.. 0.N 00. 0.. 00 0.. 00 ..N N0. 0 e000. 0.0N 000. ..NN 000. N.0N 0N0. 0.0N .NN. 0.0. N00 3 Sec. 0.0N 000. 0..0 0.0N 0.00 0.0. 0..N ..0. 0.0. 000 z .mwmh 0.0 ..0 0.0 0N0 oum, 0001 ..0 .00 0.00 0.0 -h 0. .0 N. m. 0. 0N - 1 0.. 00. 0 0.0 NON 0.N 0.N 0.N 00. ..0 00N 0.0 00N 3 sec. 0.0 NON 0.0 000 ..0 00N 0.0 00N ..0 .0N z emguo 0.00 .00N ..00 0000 10000 .N00 .m.00 .00N 0.0N .00. . N.. .. 0.. .0. ... 00 0.. 00 0. 00 0 0.0. 000. N.0. 000. 0..N 000. 0.0. N00 N.0. .00 3 e000. 0..N .00. ..0N 0.0. ..0N 0.0. N... 000. 0.0. N0. 2 noeu a mesa: a mesa: -0 meaoz a meaoz 1n meaom, ween. .ouo. sec. 0 e0. Sea. «.00.: e000: Sec. 0.00.2 e030. sec. ..020 .000. 00 acoueme 0:0 0.030m003 eon meao: .mnaoeo w~.m.seo. 30 0000 e000. .uuo. .m:==< mo m0uem>< 0.0 0.00. 96 farm work, 81 percent was for crop production with the remainder spent on livestock and other farm work. Exchange labor accounted for only 3 percent of total labor but paid hired labor off the farm constituted about 40 percent of the total labor. The special unpaid activities involving ceremony, community services and other activities accounted for 9 percent. Comparing labor allocation by farm size groups we noted that crop labor requirement as a share of total labor increases with farm size. Farms in the upper half by land area expend nearly twice as much labor in crop production as that used on the smallest farm when expressed as a percent of total. Consequently non-cropping activities diminished as a percent of total with increases in farm size. Off-farm work was 52 percent of all labor in the small farm size and only 32 percent for the large farm size. This indicates again how the labor requirements for crop production is largely determined the residual amount of labor that is available for off-farm work. Non-cropping farm works ranged from 8 to 10 percent in the four farm size classes and roughly inversely by farm size. Exchange labor as a percent of total was approximately 2 to 3 percent for all size groups. In the four farm size groups, periods 4 and 5 as well as 9 and 10 was when the most family labor was expended off farm. The periods of least off-farm activities were 6 and 7 when rice was being harvested and periods 12 and 13 when dry season crops were being harvested. Nevertheless, it can be noted that, even in a critical crop production period such as period 6, farmers spent on the average 21 percent of their time in off-farm income generating activities. We are led to 97 believe that for many farms the labor bottleneck is not serious and that on these farms there is surplus labor that can be hired by farming households in greater need and/or can be marketed in the form of income generating activities such as trading. The evidence that non-farm work occurred in some degree the year around probably indicates the need for most households to seek off-farm employment to meet the. normal cash flow requirement of the family. The seasonal distribution of non-farm activities by case households within farm size classes are shown in Appendix TablesELl to 5.4. The seasonal unpaid special labor activities shown in these tables will be used later in the analysis where it will be assumed that time spent in these activities is of sufficient priority as to effectively constrain the family labor available in the case households for crop production. 5.7 Interpreting the Findings Average hours per household and per activity as well as by sex have been reported. A close examination of the many tables showing detailed characteristics of individual households in the appendices could demonstrate that statistics describing labor utilization may vary widely among families. One may be quick to conclude that labor measure- ments in agriculture are inherently subject to error and that the reported findings are totally unreliable. Difficulty in labor measure- ment is not denied and no claims are made to error free data especially since different enumerators were involved in the measurement process. On the other hand, the average number of man hours utilized per activity or per rai of a given crop may vary widely among households as a con- sequence of differing levels of productivity per worker. Such differing 98 levels of productivity may be expected from a variety of causes: differences in age, differences in nutritional intakes and differing states of health, differences in the environmental conditions of works such as temperature and/or humidity and presence of a breeze during time of work or differing conditions facing workers in the accomplish- ment of a given task. Examples of the latter include differing soil conditions and differing work capacity of the draft buffalo in the plowing operation or differing size and number of weeds in weeding operation. Since the specification of labor as a required input in farm pro- duction is imprecise at best, one is faced with the problem of deciding what coefficients to use in the preparation of farm budgets or for setting up a linear programming tableaux. For this study in the linear programming analyses to follow, labor requirements by period for individual crops will be based on average reported hours utilized on farms less than 10 rai for one set of coefficients and the average reported on farms with 10 or more rai as another set. The reason for not developing coefficients around the quartile size grouping is that the number of observations was too small for reliable estimates. The reason for not developing coefficients around equal numbers (the lower half and the upper half) on the size groupings is that the farm size distribution is skewed to the right. Thus, it was concluded that farms with less than 10 rai would be considered small farms and farms with 10 or more rai would be considered large. Another implication of the description of labor utilization phenomena in the previous chapters is the manner in which peasant families manage 99 their labor to cope with the seasonal peaks and troughs in the labor requirements in crop production. All sub-classes of labor (exchange, family labor hired out, handicraft activities, off-farm activities) have their own seasonal profiles. Exchange labor and hired farm labor correspond to peak seasons in crop labor requirements. Other activities contribute to smoothing the year long labor profile. Recognition of the importance of maintaining the subsistence level livestock enter- prises, the cultivation of a household kitchen plot, the harvesting and the need for a family to uphold its community responsibilities are considered to understanding the economics of multiple cropping systems. It is for this reason in the analysis to follow that comparisons will be made between linear programming solutions that have been obtained with and without these labor utilization considerations as effective resource constraints. Before turning to how the above constraints fit into a linear pro- gramming model, it seems appropriate to first give attention to the rewards to the labor effort; namely, to the family income and to the accumulation of family assets. CHAPTER 6 FAMILY INCOME AND ASSETS 6.1 Sources and Definition of Income The components of the household income include (1) income from fann sources, and (2) income from non-fann sources. For present pur- poses, farm gross income is classified into (1) incane fran field crops computed as the gross value of field crop production, and (2) receipts fran the sale of other fann produce including vegetables from the garden plot, fruits sometimes found in the family compound and livestock (excluding the sale of capital assets). This second cate- gory is referred to as "fann non-crap income." The non-fanm income is unambiguous if we regard it as the incone to family labor for income producing activities conducted in the home (handicraft activities), on another farm (hired fanned labor) or in the cannunity (activities for payment as non-agricultural laborer or ser- vices). No attempt, however, has been made to compute a value for the production services rendered by the family within the home as a form of expense saving even though they do constitute a significant (but unknown) portion of the time spent particularly by the female labor force. Reference is made here to activities such as child care, food preparation, other services for the family and maintenance of the hone. In the discussion to follow, attention will first be given to gross value or gross receipts fran the productive enterprises. This 100 101 is taken as a measure of business volume. In subsequent sections a conversion to net incane will be made by taking account of the respec- tive enterprise expenses. 6.1.1 Crop Income The level of crop income in the rainy season (expressed as the value of rice produced) in each household depends on rice price, the area of rice harvested and the yield of rice per unit of land. The dry season crop incune depends on area planted, and the gross value per rai for the various dry season crops grown. Rainy season rice is the major crop accounting on the average for 57 percent of the value of all crops grown (Table 6.1). Dry season crops represent, on the average, the remaining 43 percent for which the major crops are dry season rice and soybeans. On the average, the households generate in crop value B8250 for rainy season rice, B2596 for dry season rice, B2714 for soybeans, B449 for peanut and B458 for garlic. Consistent with the earlier finding that snaller fanns have a higher cr0pping intensity index than large fanns, the percent of crop value provided by dry season crops is highest on the snallest fanns. This implies a sanewhat heavier dependence on dry season cropping for the smaller fanns than is true for the larger fanns. Larger fanns will grow some dry season rice either to insure food supplies or as a cash crop. In general, soybeans (basically a woman's crop) contri- bute the most to dry season crop incane in the dry season. See Appendix Table 6.1 for the distribution of crop incane by enterprise and by household. 102 0.00. 0.00 N.0 ..0 0.0. 0... 0..0 .000. .0 ucmuema .000. ..N0 000 000 0..N 000N 00N0 0.000000: e00 n 00:0“. ..0 0.00. 0.00 0.. N.N .... 0.0N 0.00 .0.0. .0 0000e00 0000N 00.0 0.0 000 0000 0000 000.. 0.000.362 e00 0 00e0._ 0.00. 0.00 0.. 0.. N... ..0. 0.00 .000. .0 0000300 .000. 0000 .0N 00.. 000N 000. 0000 0.0000003 e00 n 0.00.2.e000: 0.00. 0.00 0.0 0. . ..00 0... N.0. .006. .6 .c0ue0a 0.0.. NNNO 00N 00 0000 ..0. .000 0.000000: e00 n 0.00.: e030. 0.00. N.00 0.0 0.. 0.N. 0.0N 0..0 .0po. .0 ucmuema .000 0N00 N.0 00. 00.. 000N .000 0.000000: e00 n ..000 - 00.0 00.0 Ee0. maoeu .0uo. 0:0 u..e00 000000 0000000 000000 zen 000000 0>.u000000e00m ..0 000e0 000000 0e0 00.00 .0 00.. ..0 0.00. mse0. 0>.00u0000e000 e0. mqoeu ..0 .0 0000e00 000 00e0 .0 0.0000003 e00 0:.0> 00e0 103 6.1.2 Fann Non-Crop Income The fann non-crop incane is derived from the sales of fruits and vegetables grown in the household canpounds and kitchen plots, the sale of swine, the sale of poultry and eggs and also (in rare situa- tions) the sale of fish. Appendix Table 6.2 shows that 16 households have receipts from fruits and vegetables and 24 households sold swine. Only eight fanilies raised enough poultry for a surplus to sell and only one had egg sales. Nine households have livestock as the only source of non-crop incone. 0n the average, the household earned £806 in fann non-crop sales in which swine provided B722 (90 percent) and fruits and vegetables provided £57 (7 percent). Poultry, eggs and fish are mainly for home consumption. It should be noted that, for this summary, the money received fran the sale of cattle and water buffalo owned for more than one year have been excluded. The reason for this exclusion is that from an accrual accounting point of view, the cost of such animals was offset by their end of year inventory value and the sale of then is offset by their beginning of year inven- tory value. From the 30 household study, there were a total of six cows and buffaloes sold from five fanns with an average of £2283 bahts per animal sold. It should be apparent that on no fann are any of the non-field crop enterprises of sufficient size to be called a con- mercial venture. They are best regarded as supplementary enterprises that utilize a limited amount of land around the household conpound and/or some family labor primarily to provide additional substance and variety to the family diet. if there is more than the fanily will eat, it can be sold. There is the exception of pork production where 104 the hogs are fed prflnarily on grain byproducts and kitchen waste and are sold at a time to meet critical cash contingencies such as when school fees must be paid. The amount of food supplied by these supplementary enterprises is shown in Table 6.2. As a share of the total value of hone produced conswnption, the enterprises contribute only 8 percent because rice is the staple food. 0f the non-rice portion, meats constitute about two- thirds with about three-fourths of the meat being consumed in the fonm of poultry or fish. The value of the conswned fruits and vegetables is about the same as the amount sold on the average. The value of meat consumed is only about 16 percent (3176 conpared with 31099) of the value of meat sold because of the practice of selling the swine. In the linear programming analyses to follow, it will be assumed that these fann non-crop incone aetivities be maintained at the re- ported levels. This means that the fmnily labor used to maintain them will not be available for allocation to alternative uses. Furthennore, when the LP results are obtained, it will be reasonable to add the appropriate amounts of home consumed fann production and sales from these supplemental enterprises to the value of the objective function in the LP solution. 6.1.3 Family Non-Faun Income The return to family labor used in the productive activities apart fran the care of livestock, maintaining the vegetable plot, har- vesting native fruits and cultivating their own land are discussed in this section. Fanily incone is supplemented by household fanily labor being hired to work in someone else's land in agricultural production 105 Table 6.2 Average Value of Food Self-Supplied by Household, Ban Pa Mark, l973-74 % of % of % of F°°d Type Baht Class Non-rice All Heat Poultry 67.10 38.1 26.2 3.2 Fish 67.26 38.2 26.2 3.2 Eggs 12.60 7.2 4.9 6 Other 29.01 16.5 11.3 1.3 Sub-total 175.97 100 68.6 8.3 Vegetables Leafy Vegs. 37.26 48.6 14.6 1.8 Pepper .58 .8 .2 — Other 38.81 50.6 15.1 1.8 Sub-total 76.65 100 29.9 3.6 Fruit 3.95 100 1.5 .2 Total Non-Rice 256.57 -- 100 12.1 Rice 1865.96 100 -- 87.9 Total 2122.53 -- -- 100 Source: Thodey, A. R. and Peter LaRmnee. Ban Pa Mark, Northern Thailand. Results of a Daily Record Keeping Study, 1973-74. Agricultural Economics Report No. 4 Chiang Mai University. 1974. 106 and post-harvesting work or to work in the non-fann work such as carpentry, house building and repairing. Handicraft activities within the household and trading outside the home are also common non-fann income producing activities. On the average, the household earned 82715 from non-fann sources including 8419 from farm labor hired out, 81144 from non-fann hired labor, 831 from services, 8286 from handi- craft and B835 net from trading (Table 6.3). Expenses for trading were deducted from gross receipts yielding the net return. About a third of the family non-fann income is re- ceived from trading. On this basis approximately 42 percent of the non-fann receipts come fron self-employed receipts. Handicraft activities utilized 80 percent of the labor expended on non-farming activities but represented only 10 percent of the total receipts. Most of the handicraft activities are in the fonn of braiding hats from material prepared by the family from bamboo. Sane house- holds made winnowing trays, sieves, water dippers and baskets. Handi- craft work, especially hat braiding, has the lowest return of all non—fann incane activities but it takes little skill and it is a means of using slack time. Appendix Table 6.3 shows the hours spent, annual returns and return per hour for non-fann income by household and by source. From this we can see that paid labor receipts ranged from nil to more than 83000 per household. There were four households which earned income from carpentry work including sawing and building with receipts aver- aging 82675 per household. Three households did some carving with an average of 82632 per household. One household reported incone from lO7 Table 6.3 Cash Receipts from Hired and Self-Employed Labor1 Hours Baht/ Percent Percent Source Baht H.H. Hour of Class of Total Labor Hired In fanning 419 * * 26.8 15.5 Other 1144 * * 73.2 42.1 Sub-total 1563 777 2.01 100.0 57.6 Self-Employed Services 31 13 2.38 2.7 1.1 Handicraft 286 1370 .21 24.8 10.5 Trading 835 328 . 2.54 72.5 30.8 Sub-total 1152 1711 .67 100.0 42.4 Total 2715 2488 1.09 -- 100.0 Sources: Appendix Table 6.2. lTrading receipt adjusted for trading expenses. Household data seemed unreliable in relationship between reported hour and reported earning have been anitted. *Data available do not provide division of hours between fann and non-fann hired labor. l08 sewing and in another occasional printing was done with earnings totalling 32743 and B7654 respectively. Other paid non-fann work was for works such as assisting a carpenter in sawing, wood planing, carving wood or other like tasks. Labor hiring for non-fann work pro- vided annual receipts per household of an average of 31144. This is approximately three times the receipts fran hired labor in farming activity. Annual non-fanh receipts are reported in Table 6.4 summarized per household and per hour for the four representative fanns. Receipts from labor hired were highest for the upperlniddle sized representa- tive fann, and lowest for the snall representative fann. With regard to receipts from self-employed activity, the large representative fann received the most even though the hours spent were less than either the snall or lower middle sized representative fann size. In general we observe that the rate of return per hour received in non-fann employment increases steadily with fanm size. 6.1.4 Total Income The value of crop production plus the receipts from labor hired out and fron self employed activities yielded an average of 818,536 (Appendix Table 6.4). The farm component of this income (crop and non—crop) represented 82 percent of the total leaving 18 percent for receipts to the fmnily labor in off-fann activities. When summarized on the basis of representative fanns, we observe that the non-fann income is substantially higher as a percent of total for the small representative fann than is true for the rest of the sample (Table 6.5). It amounted to 25 percent for this representative 109 Table 6.4 Receipts Per Household from Hired and Self-Employed Labor by Farm Size Group Fann Size Group (Representative Fanns) Source Shall Lower Middle Upper Middle Large Baht Bht/ Baht Bht/ Baht Bht/ Baht Bht/ hr. hr. hr. hr. Labor Hired 1227 1.83 1557 1.93 1876 2.50 1632 1.86 Self-Bnployed Services 59 2.47 67 2.47 -- -- -- -- Handicraft1 334 .18 424 .22 271 .24 132 .19 Trading 173 2.64 416 2.28 175 2.79 2443 2.57 Sub-total 566 .29 907 .43 446 .38 2575 1.55 Total 1792 .70 2464 .85 2322 1.21 4207 1.66 Source: Appendix Table 6.3. 1The returns per hour to handicraft activities are extremely low and may not be canparable to returns to handicraft activities reported in studies in other parts of the world. The bamboo braiding skills are expected to be learned by all younger familylnenbers even if the re- turns to family income from doing it are minimal. It is the type of activity one might see in a social setting just as wonen in Western culture may be seen knitting at any time or place. It is possible that hours for handicraft work are over-reported because of the training, recreational and joint-product nature of these activities. llO ' Table 6.5 Total Family Income and Net Income per Household Fann Size Group (Representative Farms) Itan Snall Lower Middle Upper Middle Large Baht Pct.of Baht Pct.of Baht Pct.of Baht Pct.of Gross Gross Gross G ross Fann Income Crop Incone 9587 67 11,919 81 15,641 81 20,549 81 Other Fanm Income 1198 8 358 2 1,115 6 536 2 Total Fann NL784 75 12,277 83 16,756 87 21,084 83 Non-Farm Incone 3,534 25 2,444 17 2,574 13 4,289 17 Gross Income 14,330 100 14,722 100 19,331 100 25,373 100 Expenses 3,271 23 3,382 23 4,860 25 5,120 20 Net Income IU4071 77 11,340 77 14,472 75 20,253 80 Source: Appendix Table 6.4. lll farm and approximately 17 percent for the large representative fann. We see the attanpt on the part of the snall fanners to compensate fann income with incane from other sources. Nevertheless, the gross in- come for the snall representative fann is only about 66 percent of that found on the large representative fann. When gross incane is adjusted for all expenses, the net family incune was 311,071, 311,340, 314,422, and 320,253 per household for the snall, lower middle, upper middle, and large representative fanns, respectively. 6.1.5 Distribution of Incane The matter of incane distribution has becone an important con- sideration in economic developnent. Economic planners have long con- cerned thenselves with increased productivity in agriculture and increased fann income absolutely and on the average. Such an objec— tive could belnet by concentrating development effort on the largest and most advanced fanners. However, this approach to developnent has increased the income gap between the poorest of the poor and those best off. To examine the incane distribution in Ban Pa Mark, Lorenz curves were constructed on the basis of net income per capita, per adult consumer equivalent and per household. These are shown in Fig- ures 6.1 and 6.2. The Gini coefficients are .233, .192, and .232 for incane per capita, per conswner equivalent and per household respec- tively. These coefficients are very low for a developing country and the per capita income coefficient is considerably lower than Sundrum's1 (1973) estimated figure of .44 for rural Thailand. This 1Sundrum (1973:91) cites Gini coefficients on incane for rural areas in India, Sri Lanka, the Philippines and Thailand of 0.34, 0.45, 0.43, and .44 respectively. coPaanPLum_o meoucn gmszmcou gm; vcm upwamu gm; we m>g=u ~cmeo4 _.o mgzmwm Amumucmugma m>wumF:E=uv gonzo: waEmu 00.0mom0homOmowomON O. Amamgcmucmm m>wump353uv mu< 00.0mooONOwono¢On ON 0. 112 N2. u 286.580 .25 0. m8. " “66:38 .25 o. om m om 0» Wu... on ow m o... on w on 8 m... 8 .2. m. 2. 8 w om om W om oo. _ oo. (afiequaouad aAtaelnwng) awoouI 13M Net Income (Cumulative Percentage) l00‘ 40 20 IO 0 113 Gini Coefficient = .232 J l l l l l I l 1 IO 203040 5060708090 Households (Cumulative Percentage) Figure 6.2 Lorenz Curve for Net Income per Household |00 ll4 suggests that the income distribution wdthin a village is more equal than income distribution between or among villages. The following are offered as possible reasons for the relatively equal income distribu- tion in Ban Pa Mark (1) there is a high degree of kinship among house- holds and an overt concern for one another among all families; (2) there is evidence that fanns with a high labor-to-land ratio provided hired labor to those fanns with a low labor-to-land ratio. This has an equilibriating effect in that the income received by one fann is an expense for another farm; (3) it was observed above that snall fanns have" a lower family income than large farms but with the larger family size on large fanns, the per capita and per conswner income measures become more alike when comparisons are made among families; (4) fortun- ately, the Ban Pa Mark area appears to have off-fann enploynent opportunities to utilize at least some of the surplus labor where it exists so that labor under-utilized on the farm may belnarketed off the farm to augment fann incone. The distribution of income among households on the basis of household net income, per capita and per consumer equivalent is shown in Appendix Table 6.5. The annual per capita income average of 82,648 is equivalent to $132 and the per con- suner income average of 83,260 is equal to $163. The average incone per consumer is higher than per capita because there are fewer adult consumer equivalents in a household than there are familylnanbers. The estimated per capita incone for Ban Pa Mark is only 43 percent of the national average reported in the 1977 statisticalyearbookfor1974.2 21977 Statistical Yearbook shows the 1974 per capita incone to be India=$136, Pakistan=$154, Indonesia=$175, Sri Lanka=$228, Philippines= $326, Thailand=$304, Korea=$436, Malaysia=$715. ll5 This is not surprising since~much of the wealth of the kingdon is concentrated in the large cities, especially Bangkok. 6.2 Fanily Assets Assets possessed by the sanple households will be discussed under the following classifications: real estate including land and build- ings, other fann assets including livestock and farm implements and non-fann assets including conswner durables and cash holdings. 6.2.1 Real Estate 6.2.1.1 Land and Land Distribution Land is the major valuable asset held by the farm family. It is usually used as collateral for long tenn loans. The value of fanner land holdings detennines the ability to borrow. Thus, fanners try to expand the area of land ownership. Land is kept in the fanily and it is usually passed fron one generation to the next. Land sale trans- actions occur but are rare. As part of the July 1974 household survey, the fanners were asked to estimate the value of their land. Estimates ranged from 85,000 to 310,000 per rai with the following distribution: seven operators valued their land at 55,000 per rai, one at 85,500, 16 at 36,000, 2 at 37,000, 1 at £8,000 and 3 operators valued their land at 810,000 per rai. This distribution resulted in an average of 86,283 per rai for the village. Given the wide range in farmers' estimates, it was decided to use the village average in the analysis to follow. 0f the 30 households, three own no land (Appendix Table 6.6). The renaining 27 average 9.2 rai with a total average valuation of ll6 37,936. Land is the major fann investment constituting about three- fourths of the total fann invesunent of 876,272. Since land is the primary producer of fanily incone, it was felt appropriate to make note of the distribution of land ownership. The Lorenz curve for relationship between land ownership and household population is shown in Figure 6.3. The Gini coefficient is .418. This coefficient is higher than the Gini coefficient for family incone largely because 10 percent of the population own no land at all. Access to the services of land is as important as land ownership in detennining the level of farm income sincelnost of the fanners are tenants as well as land owners, the distribution of land operated is much more evenly distributed than the amount of land owned. The Lorenz curve showing the relationship between land operated and household population is shown in Figure 6.4. The Gini coefficient is .256, a figure quite comparable to the Gini coefficient for the distribution of fanily incone. 6.2.1.2 Buildings All farmers own their houses. Houses are built and improved over thne in stages and each stage is paid for in cash which has been saved with this specific purpose in mind. The value of the house varies with the building material used, its age and size. Wood is the most common material used for walls and flooring and canent tile or clay tile is the material used for roofing on the more expensive house. The expensive house would have brick walls instead of wood. The least expensive one would be built with bmnboo flooring and walls and the roof will be covered with tree leaves. This type of roofing is Owned Land (Cumulative Percentage) I00 117 80 70 8 8 4o 30 20 I0 Gini Coefficient = .4l8 0 1 l l l l l I 1 IO 2030405060 70809 Households (Cumulative Percentage) Figure 6.3 Lorenz Curve of Distribution of Owned Land l00 Land Operated (Cumulative Percentage) 118 I00 90 r- 80 - 70 - 60 - 50 *- 40 ' 30 - 20(- Gini Coefficient = .256 l0 l l l l l l 1 l J 0 l0 203040 5060708090 Households (Cumulative Percentage) Figure 6.4 Lorenz Curve of Distribution of Land Operated |00 ll9 inexpensive because tree leaves are abundant, but it requires annual repair and maintenance. The value of housing as reported in 1973-74 survey for individual household is shown in Appendix Table 6.6. It ranges fron 8400 to 830,000 reflecting the differences in material use, the size and the age of the houses. The house has an average value of 810,970. It is an indicator of household wealth because surpluses from fanming and labor income may have been saved for many years and then invested in the building. The capacity to save depends in part on the size of fann and we note in Appendix Table 6.6 that the snall repre- sentative fanm has an average house value less than 84,000 conpared with an average value of more than 816,000 for the large representative fann. A house is not the only building to be found on the typical Ban Pa Mark compound. Fanners store their grains in a separate building called the rice barn. Twenty-three households have their own barn, the remaining seven stored their grains with parents, brothers or neighbors. As with the house, the value of the barn varies according to material used, age and size of the building. In general, the material and the size of the barn correspond with the house. Appendix Table 6.6 shows that the barn value ranged fron 8300 to 810,000 with the lowest valu- ation occurring with the least expensive house and the highest valu~ ation in general occurring with the highest value house. Hence the snall representative fann has a rice barn value less than half of the average valuation of the rice barn for the large representative fann. 120 6.2.2 Livestock Since there are no connercial livestock enterprises in Ban Pa Mark it is very difficult to make an accurate accounting of the amount of livestock maintained in the sample households. The amount of livestock on hand is a function of both essential family need (for example, draft animal requirement for specific period, cash requirements from the sale of swine in other periods and the need for poultry to meet special food requirements for group in critical labor periods or the time of reli- gious events) and the amount of feed in the fonn of byproducts avail- able. Appendix Table 6.7 presents the June 30, 1974 inventory of livestock on hand. It shows an average per household of .73 buffalo, .43 oxen, and 1.77 swine. Inventory for chickens and ducks expressed in monetary tenns averaged 92 and 5 baht respectively. Hater buffalo and oxen provide animal power for plowing, harrow- ing threshing and pulling carts. Water buffalo like wet land and thus are nonmally used for land preparation in the rainy season. Either oxen or buffalo can be used for plowing in the dry season. Carts are nonmally drawn by oxen. Because of their relatively high unit value, ownership of buffalo and/or oxen is an indication of wealth. In most parts of Thailand, they are used as collateral for short tenm loans but in Ban Pa Mark, farmers resist borrowing money regardless of their level of collateral. Short tenm credit requirements are met with personal loans on the basis of verbal agreement. In the Chiang-Mai area both buffalo and cowsunay provide a sort of liquidity. Fannerslmay sell their animal at a cattle market such as the one located about 10 kilometers south of Kan Dong District 121 Center if they need cash. This open market is especially active in the dry season after dry season crops have been planted when fanmers sell their buffalo and may transact for a bicycle which will be used for transportation until the rainy season begins. Buffalo are con- sidered costly to keep, income is forgone from time that could be spent on alternative activities and all fanners fear the risk of having their buffalo stolen. Even though they buy at the beginning of the rainy season at a relatively high price and sell in the dry season at a relatively low price, this behavior is considered rational for the above reasons. Some fanners prefer not to own buffalo at all. They wnll either have plowing done by custom work or will rent buffalo fron a neighbor. Even though the inventory shows only'23households with swfine, hog production is a universal phenomenon. One can expect that the 7 households without the swine would have one orlmore sometmne during the year. The number of hogs kept is detenmined by a sensitive bal— ance between the amount of byproduct feed available and the amount of cash needed to buy protein supplement. The small hog enterprise is raised in confinement using low cost homemade pens constructed in the compound area. A small family flock of chickens is maintained in each household. They are raised for both meat and egg consumption and run freely uncon- fined in the home lot. Three households at the time of inventory were raising ducks. The average value of livestock per household totalled 84836. It is of interest to note that there were eight households where the livestock valuation at tune of inventory was greater than the value of the family residence. 122 6.2.3 Farm Implements From Appendix Table 6.6 it can be seen that farm implements repre- sent an almost negligible part of the total value of fanm assets (averaging only 8138 out of a total of 876,272). This points out very clearly that the traditional cultural practices are rather prflmitive. The usual complement of implements includes one or two plows, one or two harrows, two to four hoes and/or spades and about four sickles. One family (HH34) without a male adult had all land preparation work hired therefore owned only a few sickles for crop harvest. In 1974, at the tmne of the closing survey, no fanmers in this village owned a tractor. Some tractor services were hired in the dry season but not in the rainy season because of the high cash requirement and because of the waiting tflme. Fanmers in the 1973-74 crop year did not consider a tractor suitable since individual land parcels are small. Nevertheless, when the village was revisited in July 1978, about one family in six now owns a small tractor. However, without repeating the type of study done in 1973-74 it is not possible to eval- uate the mnpact of mechanization in Ban Pa Mark. 6.2.4 Total Fanm Assets In summary, real estate in the form of land and housing represents almost 94 percent of the value of fanm assets. Most of the remainder (6 percent) comes from the value of the small livestock and poultry enterprises. In the context of fanning practices carried out by families in this study, fann mmplements are not conSidered long tenm capital assets because annual replacement is commonplace. Consequently l23 in the preparation of the budget for LP analysis, a charge was made for the annual cost of replacement of fanm tools. 6.3 Non-Fanm and Total Assets 6.3.1 Selected Durable Goods At the time of the survey, it was decided to enumerate and evalu- ate selected consumer goods and to ignore those parts of the household inventory (bed, chairs, cooking utensils, etc.) that would be common to all families. Hence the value of the total household inventory is deficient by the amount of these omissions. Selection of the consumer durables wasumade on the basis of the extent to which they would pro- vide insight regarding differential levels of living among households. The selected items included bicycles, motorcycles, watches, clocks, radios, and sewing machines. The distribution of ownership of these items by household is shown in Appendix Table 6.8. Of the itemsumen- tioned, bicycles are the most common among families. This reflects the role of the bicycle as a means of transportation for both people and goods. A radio was the second most frequent item found in the selected list. All families but five have one orlmore radios with an average value of 8178. Radios are locally produced and relatively inexpensive but nevertheless, the value of the radio still exceeds that of the total value of the fanm flnplements inventory. Motorcycles when new are the most expensive items in the inventory of personal property (costing as much as 89,000 and averaging 83,313 in value for the 12 vehicle inventory). This item probably best repre- sents financial well-being since it appears that most families are l24 anxious to replace the bicycle with a motorcycle. In general, motor- cycles are to be found in the families with the highest income. Likelmotorcycles, sewing machines are individually costly, Sewing machines were found in only 6 households wfith an average value per machine or almost 82,600. The motivation for owning a sewing machine is more closely tied to the potential for expense saving or income earning than it is to status. In summary, the availability of consumer goods in the stores in the district center can be an incentive for fanmers to work harder so that they can earnlmore income and save for such items. Ownership of a radio and a bicycle are an incentive for a family of moderatelmeans. Motorcycles being more expensive can serve to raise the aspiration. level particularly of young fanmers. 6.3.2 Cash Holdings An inventory of cash on hand was taken July 1, 1973 and again on June 30, 1974. The reported results are shown by household under non- fanm assets in Appendix Table 6.7. The average of the beginning and ending of year amounts give us some indication of how much cash is kept on hand by families at the beginning of the rainy season, The level of cash holdings and the wide variation that we observe in Appendix Table 6.7 is probably explained by such things as the following: (1) the amount of dry season crop sold at tmme of harvest; (2) the amount of indebtedness to friends and neighbors that must be repaid at this tmme; (3) the amount of cash considered essential to enter the rainy season cropping program; (4) the amount expended during the dry season for home improvement or other abnormal purchases; and (5) differences in general saving habits among individual families. 125 We observe that families in the small fanm size class appear to be always at a fairly low level of cash reserve. But we can also note that many families in larger farm size categories were holding little cash at this time of the year. With regard to the reliability of this figure we recognize that it is difficult to get truly accurate re- sponses in an interview situation and, for obvious reasons, it is considered confidential infonmation. The amount of cash assumed to be on hand for the linear program- ming model was guided by the reported inventory of cash on hand. When individual case households were being analyzed, the July 1, 1973 figures were used. When the representative fanms according to fanm size were analyzed, 8500, 81,000, 81,500 and 81,500 were assumed for the small, lowerlmiddle, upper middle and large representative fanms respectively. In addition to this, assumptions werelmade with regard to a cash value for the beginning of year rice inventory necessary t0Imeet family con- sumption requirements from the beginning of the year to the tmme of rice harvest. This assumption will be explained inlmore detail in Chapter 8. 6.3.3 Total Assets Total assets per family for individual households ranged from 86,655 to 8166,248 with an average of 880,992. The averages for re- presentative fanms ranged from $27,169 for the small to $129,622 for the large (Table 6.6). Since most of the value of family assets comes from real estate, it is to be expected that total asset increases wfith fanm size. The percentage of total assets in the fonm of livestock .o.m mpnmh chcmna< "mucaom o.ooH ~mm.ow o.ooH www.mNH o.ooH mm¢.¢oH o.ooH mw¢.mw o.oo~ moH.uN muwmm< xpwsmm.~muo» m.m omn.v m.e wnw.m ~.m mmo.m o.¢ mum.~ N.m mno.a =cmmucoz peach m.H amN.H H.H mH¢.H H.N mmH.N m.~ mum w.H use nmmu mmogm>< mé mw¢.m in awe; 0.0 mmmd m.~ Sm; eé momJ 359:5 umuumpmm mummm< =nmmicoz 126 N.¢m NNN.NN m.mm NNN.NNN m.Nm Nom.mm o.mm Nmm.oo N.mm Hm¢.mN scam Peach N. NNN N. omN N. NNN N. CNN N. am mocaemNQEN 0.N NNN.N m.m mce.a N.m NNN.N 0.N NNN.m N.NN omo.m NUONmN>Ns m.oN mom.NN m.mN mNN.0N 0.NN NNN.NN N.NN NNN.NN N.0N mNm.m mucNuNwzm m.NN mmm.Nm N.0N Noo.mm N.ao NNN.NN N.No NNN.NN N.Nm NNN.NN new; mummm< Em... N n N n .N n N N N N WEE E 8.5.. 28:2. .58: 22.; 823 :25 Amccmm m>wueucmmmgammv macaw aNPm scum magma m>wumacammgamm com mpwmm< Eamm-=oz can scan o.w mpnmh l27 decreases with fanm size (from 11 percent in the small representative fanm to less than 4 percent in the large representative fanm. One farm in the upper middle farm size group is of particular interest because of the unusually high value of selected durable 900ds. Household 33 possessed at the time of the end of year inventory, bicycles valued at 81,000, two motorcycles values at 818,000, a watch and a radio each valued at 8200 and a sewing machine valued at 85,600 for a total of 825,000. This fanm alone had valuation of these sel- ected durables over seven times the average of all households. In such a small sample overall, this situation distorts the assets distri- bution for this household's fanm size group as well as the distribution on the average for the entire sample. Nevertheless, it is reasonably safe to say that approximately 3 percent of the family total assets are comprised of these selected durable items. Earlier, attention was given to the distribution of assets in the fonm of owned and operated land. One may wonder what the distribution of assets would look like if the value of assets are considered except for land. The Lorenz curve for this distribution is illustrated in Figure 6.5, which has for it an associated Gini coefficient of .378. Assets ownership defined in this fashion has a more unequal distribu- tion among households than is true for family income (.232), income per capita (.288), income per adult consumer equivalent (.192) and the area of land operated per household (.256). The reason for this is that the twolmajor components of the non-land assets, namely house and durable consumer goods, are highly correlated and rather wddely distri- buted in value. Assets (Cumulative Percentage) 128 l00 i3 70- 50'- Gini Coefficient = .378 l L i 1 l l l l J 0 l0 203040506070809 Households (Cumulative Percentage) Figure 6.5 Lorenz Curve of Distribution of Assets |00 129 Having summarized the income and assets for families on the gross value basis, it is appropriate now to give attention to the relation- ship between income and assets to the fanm business and conswmption expenditure patterns. CHAPTER 7 HOUSEHOLD EXPENDITURE PATTERNS The purpose of this chapter is to describe the household expendi- ture patterns with particular attention given those features which will be useful in the linear programming model. Discussion of household expenditures is organized in the following order: (l) field-crop pro- duction expenses, (2) non-crop farm production expenses, and (3) ex- penses in family consumption. 7.l Field Crop Production Expenses The crop expenditure for each household depends on the kind and amount of crops grown and the level of technology employed. It was found, except for two cases using hired tractor for plowing land in the dry season, farmers have what can be called a "traditional" technology, characterized by a high labor to capital ratio. All household expenditures for individual households are classified and recorded in Appendix Table 7.1. They will be discussed in the order of their importance to the family budget. 7.l.l Hired Labor All families had some hired labor expenses and regardless of farm size it constituted the highest percent of crop production cash cost. On the average of all households, hired labor expenditures represented 43 percent of total farm expenses and 40 percent of total household 130 131 expenses (Table 7.l). For individual farms, hired labor expenses ranged from 880 to 84882 averaging 8659 per household (Appendix Table 7.l). For the representative farms in the study, hired labor expense per family increased substantially by farm size but there was no pattern in the relationship between farm size and hired labor expenditure per rai. One might expect hired labor to increase with farm size but it has already been noted that the large farms tended to grow a smaller proportion of labor intensive crops. With regard to the LP model, neither hired labor per family nor per rai as reported by farmers will be used. This is because the model calls for a labor hiring activity to be employed when the family labor force is inadequate for crop requirement. It will be necessary, however, to have hired labor rates corresponding to each period. How these were obtained will be discussed in the next chapter. 7.l.2 Land Rent Two-thirds of the households rented some land (Appendix Table 7.l)- The rental arrangement in the village was discussed in Chapter 3. It was noted that the rate for land rent was not institutionalized at a fixed level but varied by season, quality of land and personal arrange- ments that may have been worked out between leasee and leasor (frequently among relatives). For the sample as a whole, the value of rent paid represents a third of total production cost. However, for the reasons given in Chapter 3, rent as a production cost will be excluded from the LP models. When interpretations of the solutions are made, rental payments will be subtracted from the value of the objective function where appropriate. 1132 NP can» mmmp u « AN mmmcmaxm ELNN-:oz a Econ Nauoh No N u on mmmcquu Egon No N n N4 mm mm omen em om mmmv No mm wmee cm om NNNm NN Nm ONMN Nona» Nm mm emNN co «e eNNN m— ON NNm om Nm aNoN mN Nm on ucom « a NP .1 a. N.. a a 3. a. a Z. a a m Laue: MN «N mmm NN NN mam NN NN mNm mp mN mpm op mp Nmm mowpaazm N N cm a N NN m m Pop N N cm a a m ucoeawaau m m NN— a a o_ m m NNN N N QMN m a ma Nazca oe me mmcp mm mm mooN om Nm «NeN oe Ne mmmp on an Nmm Lona; coNuuauosa nogu NN Numucmmmcqmmv aaogw mNNm Egan oNNm Esau an upogmmaoz can ommcm>< .mgauwucuaxu NNNEuN gorgesSNcooucoz pouch N.N mpnmh l33 7.l.3 Farm Supplies and Equipment Farm supplies including seed, fertilizer and chemicals are third in importance for crop production expenses. Since equipment purchases are typically minor outlays for replacement of small tools or maintenance for the plow and harrow. they can be discussed along with farm supplies. Seed Seeds for rainy season rice are usually provided by farmers them- selves.1 All households planted the same variety of glutinous rice (Keow Daw) which is a local variety having been selected by farmers over the years. For dry season rice, the newly released "high yielding varieties" were used which are a cross between 1R8 and some local varieties selected for high yield, disease resistance and short-growing season. Farmers plant them in the dry season as "selling rice." Almost all planted RDl, a non-glutinous rice while only 13 percent planted R02, a glutinous rice. The non-glutinous rice is for the market but the families planting glutinous rice keep it for home consumption. RDl and R02 seeds were purchased from the Rice Experimental Station. The cost of dry season rice seed was 8l30.8 per household, averaging 86 per rai. Some farmers grow their own soybean seed in the small parcel of land which was used for rice nursery. This is done to avoid purchase of seed but are of relatively low yield. Most of the farmers purchased their seed from the Mae Jo Crop Experimental Station where SJl and SJ2 1However, in developing the budgets for the LP model, the cost of seed at l baht per rai was included whether supplied by farmer or pur- chased. This is based on a seeding rate of .77 kilograms forl..05 rai of nursery and l.3 baht per kilogram of rice. 134 were developed. The cost of purchased soybean seed was 8292.10 per household averaging 843.70 per rai. Peanut seeds were usually purchased from the merchant. The cost was 82l6.l per household averaging 873 per rai. Garlic seeds were mostly purchased at the beginning of the planting season when the price is very high. This is due to the farmer not wanting to take risk of seed spoilage coming from early purchase. The cost of garlic seed is very high compared to the seed for other crops. A household spent an average of 8332 for garlic seed averaging 8673 per rai.2 With regard to fertilizer use, some farmers put buffalo or ox manure on their fields, some used chicken or duck droppings and some used pig manure. Manure was used for all crops but the amount per crop varied somewhat. For rainy season rice, 30 percent of the house- holds did not use any kind of fertilizer, 60 percent used manure and only 10 percent used chemical fertilizer (Table 7.2). The average cost for fertilizer for rainy season rice is only 81.l0 per rai (Table 7.3). This includes a value for the home produced manure. Of the farmers growing dry season rice, 46 percent used chemical fertilizer and 27 percent used manure making the average cost of fer- tilizer equal to 8ll.30 per rai which is about l0 times the cost of fertilizer for rainy season rice. Soybeans use the residual fertilizer from rice supplemented with the addition of more manure. Ninety-two percent used fertilizer for 28300 per rai was used for garlic in the model. On the basis of the researcher's experience, the reported average was unreasonably high. The 8300 per rai assumption has also been used previously in research at Chiang Mai University. 135 Tab1e 7.2 Use of Fertilizer and Chemical by Crop l’ Rice J Rainy S. Dry S. 1 Soybean Peanut Garlic Type of Fertilizer %(Percent) Manure 1-2 kwien] 23 9 z 23 30 -- 3 kwien & ' over 37 E 23 3o -- Not known -- 14 ; 31 3o -- Chemical 1-2 bags lO 4l 4 -- 50 3 bags & over -- 5 -- -- 17 Not known 3 -- 9 -- -- 33 None Used i 30 ‘18 4 3 10 -- No Response 1 -- -- -- 3 -- -- Total 5100 100 ; 100 ' 100 100 n § 30 22 1 26 1o 6 Type of Chemical 2 Crab Killer f 5 Parawin : 44 26 1 ' l9 -- g -- Folidon ; -- 5 § -- -- 1 -- Insecticide , z 1 Not known 5 3 5 i -- E 5 1 7 Home Used ? 50 59 j 77 5 95 1 93 No Response 3 3 5 -.1 4 a -- g _- Total 1100 100 ( 100 1 100 3 100 1 3r *1 i n 3 3o 22 f 26 ' 1o 1 6 l l kwien = 100 tangs = 2,000 litres = 5283.4 gallons 136 .uNNcem eoN Naauxm maogo NNN Low Notes a; :N tam: N aoeu co eeex N o.NNmN m o¢.N¢N oN.mN 0.NNN _ om.om mmcwaxm coco Nmuok oo.NNNN m ON.NNN om.Ne oo.N_ om.eN NeNON-e=m o—.NN " om. oN. oN. ON. NmNmuNsmsu om.mmm w oo.mN oN.¢ om._N oN.N NemNNNNNLmN co.MNm W oN.mN 0N.m¢ om.o om. ummm --- m ON.m --- oN. o_.o Faces Nzcu --- oN.mN --- ON. oo.m Luzon . mmcqum .Nuzuoga cacao m.m¢m " om.a_N om.oN oo.oNN ON.mN Loam; vase: N we; Nag mmmcmgxm Ne. W om.N e_.m m mm.m Ne.NN aeeo co eoe< oN.mmm W oo.mmm om.Noe W oN.Nmo o_.mNNN mmcmaxm nose Nmuoh ON.Nmm . oN.NmN oN.mmN " om.mm o.mmN Nmuohunam ON.¢ . om.N ow. W cm. ON.N mNmuNEmsu o¢.¢¢N W om.N¢ ow.mN m om.oc om.N_ cmNNNNNLmN om.¢NN m o_.moN oo.moN m oN.em oN.oN ummm --- m N.NN om. _ om. oo.0N acmsawzam 1.. m N.Nm --- ow. om.mm Nazca 2 mmcmaxm .uuzuoga gospo o¢.oqp om.NmN ON.moN o~.mmm om.NNm cone; umeNz aogu saw: IINNmmcmaxN N m oN mN om coco saw: msgmu uwpcmu mpscmma mammnxom muwm commmm Nee mama commmm Acmmm Nam can can aogo gum: scum an maocu Low mmmcmaxm comuuawoca m.N mpnwh 137 soybean in the form of manure, only 4 percent used chemical fertilizer and 4 percent did not use any at all. The cost of fertilizer averaged 84.70 per rai for soybeans. For the farmers growing peanuts, 90 percent used manure and 10 per- cent used none. All growers of garlic used chemical fertilizer. The cost of fertilizer for peanuts averaged 818.60 per rai while chemical fertilizer for garlic cost 8590 per rai. This difference is due to the high price of imported fertilizer compared to that of local manures which are available on the farm or are purchased from other farmers at very low cost. Not many farmers used chemicals. Table 7.2 shows the percentage of households not using any were: 50 percent for rainy season rice, 59 percent for dry season rice, 77 percent for soybean, 95 percent for peanut and 93 percent for garlic. The most commonly used chemical, parawin, was for killing crabs (44 percent for rainy season rice, 26 per- cent for dry season rice and 19 percent for soybean). Table 7.3 shows that the cost per rai for chemicals was 8.20 for rainy season rice, 8.10 for dry season rice and soybean, 8.60 for peanut and 811.10 for garlic. The expenses for equipment are very small compared to other items since they are usually made by the farmer himself. Plow and harrows may last 5 to 10 years with some maintenance and repair. Hoes, spades and sickles usually last for 2 to 5 years but need to be sharpened. No major equipment expenditures were reported. The indicated cost of equipment was only for the buying of the blades for plow, spade, hoes and sickles. The most expensive piece of equipment is the threshing 138 basket (Ku) which would last more than 5 years. On the average, a household spent only 860 for equipment (Table 7.1). 7.1.4 Power Cost Power is the cost of renting oxen or buffalo using the farmer's own labor to plow and harrow the land. Households 53 and 45 are exceptions in that power cost included 8200 and 8100 respectively for the cost of hired tractor service in the dry season in addition to some renting of buffalo. Seven households reported renting buffalo, mainly used for rainy season rice. The cost varied depending on the hours used. Expenditures varied from 860 to 81500. Because of this wide range accounted for by many farmers owning their own animals, it was decided in the preparation of the LP budgets to assume that each farmer would hire animal power services at the going rate ranging from 820 to 825 per rai. 7.1.5 Water Charge Even though every farmer is subjected to some water charge, it is minor in total cost of production, averaging only 812 per household. It represents the fee that farmers pay as member of an irrigation association providing for the right to use water. In addition to this small cash outlay farmers are expected to provide material and labor for cleaning and repairing the canal. In the LP budgets, no accounting was made of the material supplied in the cost of production and the labor contribution was included in community services rather than as a labor requirement for crop production. Water charge along with land rent was deducted from the value of the objective function where applicable. 139 7.1.6 Summary of Crop Expenditures by Crop For the purpose of the linear programming to follow, it became necessary to summarize the expenditure for each crop on a per rai basis. Since the representative farms were defined on the basis of land area, the question arose as to whether crop expenses should be estimated according to farm size. Since hired labor, rent of animal power, land rent and water charge will be excluded from the budget, this leaves only expenses for equipment and supplies for consideration. Table 7.] indicates little relationship between farm size and the expenses for equipment and supplies on a per rai basis as an average per farm. The relevant consideration, however, is the expenditure for these items per rai on the individual crop basis. It was felt that the limited number of farms and limited area devoted to individual crops did not justify the estimation of these expenses stratified according to farm size. It seemed more reasonable to make these estimates on the basis of the total sample and to use the results for each of the representative and case farms. This decision is further justified by the fact mentioned above that the primary crop production expenses are for hired labor and land rent which are handled outside the crop budget in the LP model. The expenses per rai by crop are summarized in Table 7.3. 7.2 Livestock Expenses Buffalo, oxen and cows are kept and fed with straw, grass and some grazing along the rice field bund. Pigs are kept mainly on the household waste, rice bran, weeds and banana stems. Chicken and ducks fed themselves but occasionally were fed with paddy rice. Thus, the expenditure for livestock was mainly for some additional bran, banana 140 stems, supplemental diet and veterinarian. Pigs share more of the livestock expenditure than others due to the number and the amount each consumes. 0n the average, a household spent 8197 for livestock which is only 5 percent of the total farm expenditure (Table 7.1). To interpret the LP solutions, these expenditures were deducted from the gross value of non-crop farm income yielding a net return which was added to the total value of the objective function. 7.3 Non-Farm Business Expenditures 7.3.1 Expenses for Handicrafts Activities The handicrafts in which the families engaged are mostly for hat braiding and the making of winnowing trays, sieves, water dippers and baskets. They utilize local materials such as the bamboo which is grown on the household compound. Farmers did not purchase them so there is no cost to it. Only one household reported spending 8138 for the handicraft expenses but the details of this expenditure are not known. 7.3.2 Expenses for Trading Activities Trading activity expenses are considered to be the cost of produce that a household buys from off the farm and resells in the market, the cost of transportation and market fee. However, from the data avail- able it is difficult to draw clear conclusion about what the expenses represent and the nature of the profit function for these activities. Only six households reported having incurred trading expenses including the household identified in Chapter 2 as running a small store in the village. However, as was noted in Chapter 6, there were 23 households reporting income from trading activities. It appears that trading income must be interpreted as the sale of farm produce and cannot be 141 related to expenses reported in Table 7.1. This finding will not affect the subsequent analysis because the LP model does not contain a trading activity. 7.3.3 Total Business Expenses On the average, a household spent 84161 annually for its farm and non-farm business. Farming constituted 93 percent of total business leaving 7 percent for the non-farming business expense. As would be expected, total expenses increase as farm size increases (primarily hired labor and land rent) as indicated by the fact that the small representative farm shows an average annual expenditure approximately three-fourths of the large representative farm. 7.4 Family Consumption Pattern Household family consumption expenditures vary by family size, income level and household composition. Three components of the family consumption expenditures will be presented as follows: 1) value of rice consumption requirement, 2) other food expenditure and, 3) non-food expenditure. 7.4.1 Rice Consumption Requirement Rice is the major component in the three meals consumed a day by families in the Thai household. Each household grows its own rice and to sell it only if there is a surplus beyond consumption requirements. In the previous chapter, income was ascertained by taking the value of crops including rice as crop income to a family. Some rice purchases were indicated in the expenditure survey and expenses were shown for the cost of milling the family's own rice. However, there were 142 insufficient data for estimating rice consumption in a family. The value of rice consumed by the family was estimated using information obtained from a survey of the households in which the question was asked as to how much rice was cooked in the household per day. From this it was determined that the average consumption of milled rice per meal per adult consumer equivalent was a little less than one-quarter liter. The quantity of milled rice was converted to paddy equivalent, valued at paddy price to which was added the cost of milling using the average cost per liter reported by the family in the expenditure survey. The resulting value of rice consumed per adult consumer equivalent was 8297.54 per year. The value of rice thus computed plus other household expenditures will be used in the linear programming model as one of the constraints. The value instead of quantity of rice consumed was used in the LP model as a matter of simplification. With money as a common unit, all financial requirements for periods were combined into a single con- straint. 7.4.2 Other Food Expenditure Meat, eggs, vegetables, fruits, fat and oil, condiments and food away from home are major categories in the other food expenditure. Meats consumed are usually pork, beef, chicken, and fish both prepared and fresh. Eggs include chicken, duck, bird and ants. Vegetables were leafy vegetables, garlics, onions, and peppers. Fruits were mainly bananas, mangoes, and oranges. Fat and oil were for cooking including land and vegetable oils. Condiments were mainly spices for cooking, fish sauce and coconut or cane sugar. Food away from home included soft drinks, prepared meals and snacks. 143 Food expenditure by class (as well as non-food expenditure) have been summarized for representative farms in farm size classes and for the total sample in Table 7.4. In this table, rice has been computed following the procedure outlined above and other expenditures were those actually reported in the field study. From this we can see that the value of rice and meat constituted about three-fourths the total value of the food budget and about a half of total family non-business expenditure. The amount purchased by individual families may depend on the amount consumed from farm produce sources. The value of the food supplied to households directly from farm production is summarized by case household and representative farms in Table 7.5. This value averaged 8257 per household of which, it was found, 61 percent was in the form of meat and 39 percent from fruits and vegetables. The food away from home on average is about one-tenth of the total food outlay. 7.4.3 Non-Food Expenditure The main elements of non-food expenditure are expenditures for improving or repairing house and barn, purchasing furniture and house- hold items, expenditure for tobacco, whiskey and fermented tea, for clothing, personal expenses, transport, gifts, and taxes. Seven households incurred maintenance and repair costs for housing. This can range from the minimum repairs to the change of the roof, the floor and some cases the addition of a bath and/or sanitation facilities. 0n the average, a household spent 8319 (13 percent of non-food and 4 per- cent of total consumption expenditures), for such needs. Three house- holds incurred expenses for barn improvement and spent 8197 on the average. Every family purchased something for the household in the 144 up. case NNwNN uwsONOON mu_m No NONN> NOONN>< umuageoup Om _ N N N, N NONOOOOOON NO NOOeOz O.OO__ONON 1“ O.OONNOONO 0.00N ONNN 0.00N ONNN 0.00_ ONNN ONOONOOOONN NOOON N.ON ONNN M N.NO M NOOO111,O.ON ONNN O.NN NNNN N N.ON OONN NONOONOOONNN OOON OOz NOOON O. NN m O. OO N N. ON . N. N M1 N. N NON N.N N NON . N.N NON _ N.ON .NN . N.N NON N N.N ONO ONNN N.N w NON . 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NN N.N NON O.N ON O.N NN NONONN N.N .NO 0.0 NNO O.N NNO O.N ONO N.N NON NONNOOOOO> N.ON NOON N.NN NNNN N.NN NNNN N.ON NNNN O.NN NNNN ONO: N.ON OONN N.NN ONNN N.NN NNNN N.NN ONNN N.NN ONNN NOONN Neauwvcmaxu vooN N N N N N N N N N N NWOON OONON ONOONN NOOOO ONOONN eOzON NNOeN NNENON m>NNOucNNmemmmv ONNNu NNNm ELNN NNNONNOcNOxN coNNOEONcou upocmmaoz omogm>< O.N mpamh 145 Table 7.5 Value of Farm Supplied Food for Case Households and Representative Farm Case Households Representative Farms Farm Size HH No. ' Baht Baht Small 65 242 334 Lower Middle 63 366 120 Upper Middle 50 426 348 Large 3 46 151 All Households xxx xxx 257 in the form of furniture and household items. These items ranged from mirror, picture frame to bed, table and chairs, which cost in total 8309 on the average. Farmers in the North usually smoke local tobacco and chew fermented tea (instead of beetle-nut which is chewed by farmers in the Central Plain). These two items are also for receiving guests. Some men drink local whiskey especially during the off-farm ceremony season. The household spent 8458, on the average for these items. Clothing expenditures depend on household size and composition by sex and age. The younger families or families with teenagers tend to spend more than others. The clothing expenditure was 8273 on the average. Personal expenditures were for haircuts, beauty salon, cos- metics, medicines, and unspecified personal items. These expenditures averaged 8155 per family. Expenditure for transportation such as bus, bicycle, and jitney are primarily for non-business trips such as visiting friends and relatives, shopping, cinema and a relaxing excur- sion. Transportation expenditures per household were 8236 on the 146 average. Gifts were mainly for "merit making" such as offering clothing to the monks and giving money or other necessities for the temple. They also included gifts given at house dedications, weddings and money given at the funeral. The household expenditure on gifts amounted to an average of 8552 and constituted the highest non-farm expenditure. Not all households paid a tax on property. Compound land area less than an amount indicated by law is exempt. Twelve households paid the tax averaging only 827 for the entire sample. 7.4.4 Seasonal Variation in Household Expenditures The seasonal distribution in baht for non-rice food expenditure, the seasonal distribution of non-food expenditure and total expendi- ture per household are shown in Figure 7.1. On the average, periods 4, 5 and 11 were the peaks for food expenditure while periods 4 and 11 were the peaks for non-food expenditures. Period expenditures as a percent of the period average are shown in Table 7.6. From Figure 7.1 and Table 7.6 we can see that food expenditures fluctuate less from average than for the case of the non-food expenditure. It can be seen that the food expenditure peaks correspond with the non-food expenditure peaks and these periods corresponded in turn to the ceremonial periods. Period 4 was the end of Buddhist lent when there were usually "merit making" events (Pa Par and Katin) and weddings. Period 11 corresponds to the Thai New Year (Songkran). Table 7.7 shows the non-food expendi- ture by item and their seasonal indices. It is clear that expenditures for tobacco, whiskey, fermented tea, clothing and gifts were particularly high in these periods. Merit making in periods 4 and 11 involved offering 147 NNNONNuchxN cNocmmzo: No coNNONNNNNNo NNNONNmm N.N mesmNN NONOONOOOONN NOOON xunuuxnluux Nmesfiuzmaxm vooNéoz 0.1101116 mmcaficcmnxu 3.57.52 woo... 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ON..N. o=.O> no.9 ON . .Nauu< ON _ .N:.0< O4 .Nzuu< ON .Nzuo< m>mumacmngmmm m m>NumuchmNama om Egan mace; Egan «.NN.: swam: NELNN NNLON use N.OONz Lona: .Neouumu ewcuo .msou:~ N.NENN new Econ N.N m—nmh 190 and decrease the amount paid for hired labor and apparently could increase total net crop income by some 34 percent. This reorganization will reduce off-farm income slightly, but overall, the result would be an increase in income per worker of about 8600 per year. In addition to the number of dry season crops that could be grown, the choice of crops is important. The programmed solution would recommend the entire farm be devoted to rice in the dry season with two planting dates. That is to say, in the cool dry season about one-half of the farm should go to rice with about one-fourth of the farm planted to peanut and garlic at this time. Then a half of the farm would be planted again to rice in the hot dry season. This recommendation seems particularly suitable for this family because his rice yield per rai of 622 kilograms per rai is about 12 percent higher than the village average. It would have also the effect of placing greater reliance on the farm for the family's income because 70 percent rather than 59 percent of total household income would come from farm sources. It is worth noting that for the two previous farms described it was possible for the families' income to be improved by diverting family labor resourtes from off-farm employment to the intensification of the farming system. 9.1.1.4 Large Size Farm: Household 3 With Actual versus Programmed Solution Household number 3 is composed of 3.4 adult members in the labor force operating a farm of 16.24 completely owned rai (Table 9.3). This is slightly smaller in land area and labor force than the corresponding representative farm for this size group. It is an interesting case because the cropping intensity index at 228 is larger by 14 points than 191 Table 9.4 Farm Organization, Farm and Family Income, Programmed Solutions with Non-Crop and Community Service Constraints, Representative Farms Representative Farm by Size Items Small Lower Middle Upper Middle Large Crops , Rice 1 5.43 9.88 12.68 16.09 Rice 2.1 2.54 .40 1.80 .54 Soybean 1 -------------------- Peanut l 1.55 2.10 2.07 2.08 Garlic 1 .25 .74 .81 .81 Rice 2.2 ----- .45 ----- 4.17 Rice 2.3 2.89 9.03 10.85 6.90 Peanut 2 -------------------- Soybean 3 --------------- 6.86 Peanut 3 2.26 .35 .09 ----- Intensity Index 275 232 223 203 Crop Value 10,439 16,571 20,394 26,742 (-) Hired Labor 478 1,553 1,822 2,294 (-) Rent 926 1,029 917 2,224 (-) Water 7 11 14 17 Net Crop Value 9,028 13,978 17,641 22,207 (+) Other Farm Income 1,198 358 1,115 535 ‘Total Farm Income 10,226 14,336 18,756 22,742 (+) Off Farm Income 4,544 5,301 5,785 6,130 Total Household Income 14,770 19,637 24,541 28,872 (-) Consumption Expense 5,427 6,219 8,630 9,461 (-) Rice Value 711 854 838 966 E-) Cash 500 1,000 1,500 1,500 +) Value of Home Food 334 120 348 151 Net for Saving 8,466 11,684 13,921 17,096 Labor Force 2.79 3.19 3.33 3.79 Household Income/Worker 5,294 6,156 7,370 7,618 Percent Farm Income 69 73 72 77 Farm Size 5.43 9.88 12.68 18.48 Household Income/rai 2,720 1,987 1,935 1,562 Net Crop Income/rai 1,663 1,415 1,391 1,202 Land Area/Worker 1.95 rai 3.10 rai 3.81 rai 4.86 rai 192 the programmed solutions proposed for this farm. Yet the total crop value for the farm was 88438 less than the programmed solution would generate. The existing cropping program is dominated by rice at a time when the rice yield per rai was only 416 kilograms per rai or 75 per- cent of the village average. It appears that in this case more atten- tion is needed in improving yield of the primary crop than to the diversification of the dry season cropping program. The linear pro- gramming solution calls for six different dry season crops compared with the two currently grown by the farm operator. Without question the more complex the dry season cropping program becomes, the more skilled the management must be. This seems especially true for this situation because substantially more labor must be hired to accomplish the requirements of the more complex dry season cropping program. On the other hand, the programmed solution does suggest the opportunity for marketing more of the family labor in off-farm employment. Whether these additional opportunities actually exist or not is unknown but if it is quite likely that the rather ingeneous way the program distri- buted the seasonal crop labor among a variety of crop would make avail- able more family labor for off-farm employment. ‘ Even without the necessity to pay rent, the low value of crops in combination with the rather modest level of off-farm income resulted in household earnings too small to meet the reported level of consump- tion, to replace the beginning of year Cash on hand and to cover the estimated value of rice placed on inventory at the beginning of the year. The reported family consumption expenditure for the year of 817,773 included 87,682 spent on house and farm building investment. 193 In keeping with our understanding of household behavior in Ban Pa Mark, it can be presumed that the building investments were paid from long- term personal savings rather than from current income. Therefore, the figure in Table 9.3 representing the residual for savings includes this building investment since it was not deducted from the reported consumer expenditure figure in the table. 9.2 Representative Farm Comparison: Actual versus Programmed Results All of the representative farms show in the actual situation some of each possible crop in the land use pattern. This is because the representative farms are defined as the average of all units in their respective farm size classes. Because of this it is impossible to identify crops according to planting and harvesting periods. The total area of each crop is shown in Table 9.1 in parentheses. The LP solution showed for each representative farm areas of improvement in all aspects of the farm and home business. The cropping programs were intensified and also simplified. The cropping intensity index was increased from 207 to 275, 180 to 232, 189 to 223 and 185 to 203 for the small, lower middle, upper middle, and large representative farms respectively. For the small representative farm, hired labor expense was cut in half but for the other representative farms the LP solution and the actual expenditure for hired labor was within B400 of each other. The off-farm income was increased for each representative farm except for the one in the upper middle farm size class. From a reallocation of available family resources the LP solutions show an increase in total household income of 19, 59, 54 and 36 percent for small, lower middle, upper middle and large farms respectively. In 194 terms of household income per worker, this means an increase of 8937, 32291, 82573, and 81930 for small, lower middle, upper middle and large representative farms respectively. These are significant income increases which could come from increased resource allocative efficiency given the assumptions of the analysis. This conclusion need not be in conflict with the"efficient but poor"proposition regarding small farms in the developing world (Schutz, 1964). In the first place, the Ban Pa Mark farmers are not at a subsistence level and secondly they may be in a period of transition from a time when dry season irrigation was not possible to one which more completely exploits dry season irrigation potential. 9.3 Representative Farm Comparisons by Farm Size The purpose of this section is to compare programmed solutions that were obtained for the four farm size classes and to determine whether the optimal solutions differ by farm size for the several variables selected for interpretation. Looking first to the resources employed, as farm size increases, so does the size of the labor force and the amount of cash that the family has available for productive purposes at the beginning of the year (Table 9.4). A part of the increase in farm size had come about by an increasing amount of land being rented. Hence, the share of crop or cash outlays for rent increase in absolute terms as farm size increases. Assuming that farms were to function as the LP solutions would indicate the effect that this differential resource bundle would have on farm organization and family income appears to be as follows: 195 1) the smaller the farm, the higher the crop intensity index ranging from 275, 232, 223 to 203 as one moves up the size classes from small, lower middle, upper middle to large farms; 2) even as the crop intensity diminishes as result of less possible land being planted in the dry season, the amount of hired labor required increases with size of farm. Also the higher hired labor and higher rental charge notwith- standing, as the farm size increases, the increase in net crop value increases at an increasing rate because of the larger area of land being farmed. In absolute terms, the value of off-farm income changes inversely with the farm size as a consequence of higher proportion of family labor being involved in cropping activities as the farm size increases. :3)Using net for savings as an indicator of living standards, larger farms would be considered better off. The large representative farm had a programmed net for saving per household slightly more than twice that for the small representative farm. Total household income per adult worker would increase steadily with increases in farm size according to the programmed results. The clue to this relationship is that taking the sample households as we find them, even as labor force increases with the increases with farm size, the land area per worker also increases. The land area per adult labor force member is 1.95, 3.10, 3.81 and 4.86 for small, lower middle, upper middle and ' large sized farm groups respectively. As farms become larger, the employment opportunity set for individual family members expands. 9.4 Representative Farm: Labor Constraint Effective and Relaxed The first programming solutions were obtained by assuming that the time spent by the family caring for their livestock and vegetable 196 plots and participation in non-paid community activities should be maintained at the customary level. The second set of solutions were obtained by assuming that the time spent in these activities could be made available for on-farm or off-farm income producing works. The purpose of the experiment is to observe the consequences of relaxing this constraint. Behind this experiment is the contention that peasant families would be reluctant to forego these activities and that to ignore them is to overstate the amount of labor that is available for productive work. In the case of the small representative farm, the amount of time devoted to these activities amounted to 438.87 hours of male time and 281.02 hours of female time for a total of 719.87 hours (Table 9.5). This represents 13 percent of the total annual farm labor force time available for farm and non-farm work. Relaxing this constraint had the following effects on the pro- gramming solution: it increased the area planted to dry season crops resulting in an intensity index of 291 compared with 275 for the result in the constrained system. Of course, this increase intensity resulted in a higher crop value in total and per rai. Making more time avail- able for the farm family made it possible to hire less labor which resulted in an increase in the total net crop value of 8708 or 8 per— cent. In addition, more family labon-was made available for off-farm employment resulting in an increase in total household income of 8913 or an increase of 6 percent. In case of lower middle representative farm, we note a difference of only 416 hours of labor available in the two situations. This less than 60 percent of the time spent on these activities as was the Farm Organization, Farm and Family Income, Representative Farms, 1597 Table 9.5 With and Without Committed Labor Constraint, LP Solutions Small Lower Middle Upper Middle Lar e With Without With ; Without With Without With without Constr. Constr. Constr.; Constr. Constr. Constr. Constr. Constr. T Crops 1 ; Rice 1 5.43 5.43 9.88 1 9.88 12.68 12.68 16.09 18.34 Rice 2.1 2.54 3.19 .40 l 1.34 1.80 5.00 .54 2.36 Rice 2.2 ---------- .45 . --------------- 4.17 2.94 Rice 2.3 2.89 2.24 9.03 f 8.54 10.85 7.64 6.90 14.81 T Soybeans 1 -------------------- ' --------------- | ----- Soybeans 2 -------------------- 1 ---------- | ----- 1 ----- Soybeans 3 ---------------- i --------------- l 6.86 i .72 i i Peanuts 1 1.55 1.81 2.10 2.27 2.07 2.34 1 2.08 i ----- Peanuts 2 ------------------------------ 1 ----- l ----- Peanuts 3 2.26 2.91 .35 P .84 .09 1.30 g ----- f ----- Garlic 1 .25 .23 .74 3 .74 . .81 .72 1 .81 l .92 Garlic 2 1 --------------- ‘ ----- i ---------- l ----- 1 ----- Garlic 3 g --------------- . ----- l ---------- J ----- 3 ----- i .- i a Intensity Index 1 275 291 232 ' 239 : 223 234 l 203 . 217 fi r + *2 *5 Crop Value 3 10.439 . 10,996 16,571 16.997 20.394 21.174 3 26.742 1 28,679 (-) Hired Labor : 478 i 329 1,553 1,379 ‘ 1.822 1.786 2,294 i 1.914 (-) Rent i 926 1 926 1.029 g 1,029 917 917 2.224 1 2,224 (-1 Water 1 7 1 7 11 f 11 14 14 17 e 17 Net Crop Value 1 9,028 i 9.736 13,978 1 14.578 117.641 18,457 ’ 22.207 ‘ 24.524 . _ __- 4________ N 1 I (+) Other Farm Income 1 1,198 l o 358 i ------ 1.115 0 1 535 I 0 Total Farm Income = 10,226 1 9,736 14,336 .1 14.578 .18.756 18,457 1 22,742 1 24,524 (+) Off Farm Income ‘ 4,544 i, 5.947 5,301 A) 6.334 5,785 6,773 i 6,130 i 7.817 Total Household Income ; 14.770 f 15,683 19,637 1 20.912 24,541 25,230 j 28,872 2 32.341 (-) Consumption Exp. 5 5.427 5,427 6,219 1 6,219 8,630 8,630 1 9,461 9.461 (-) Rice Value . 711 711 854 3 854 838 838 i 966 966 (-) Cash 1 500 ; 500 1,000 g 1.000 1.500 1.500 . 1.500 1.500 (+) Value of Home Food 1 334 i O 120 I O 348 O f 151 O 1 1 4 Y L Net for Saving 1 8.466 1 9.045 .11.684 F 12.839 13.921 14.262 { 17.096 20,414 Labor Force Q 2.79 2.79 3.19 ‘ 3.19 3.33 3.33 3.79 3.79 Household Income/Worker. 5.294 5.621 6.156 6,555 7.370 7,576 7.618 8,533 Percent Farm Income ' 69 ' 62 73 70 72 73 77 76 Farm Size 5.43 5.43 9.88 9.88 12.68 12.68 18.48 18.48 Household Income/rai 2.720 2.888 1,987 2.117 1.935 1.990 1.562 1.750 Net Crop Income/rai 1.663 1.793 1.415 1,476 , 1.391 1,456 1,202 , 1.327 Additiona! Male 438.87 216.62 260.54 398.25 ”°“"S Ava“ab‘e Female 281.02 200.07 219.15 123.11 198 situation for the representative farm in the small farm group. The reason for this is that for farms of this intermediate size group, work in the care of livestock is of relatively small importance. The main effect coming from the relaxation of the labor constraint for this representative farm was to reduce the cost of hired labor and increase the amount of income from off-farm sources. The percent of total income coming from farm sources decreased and the total income from all sources increased about 6 percent (the same percentage increase as was true for the small representative farm). The average amount of family labor for upper middle sized repre- sentative farm spent about 260 hours of male time and 219 hours of female time for a total of 480 h0urs per year to non-cropping farm activities and non-income earning activities of the family. This is about 70 percent of the farm labor supply. For the upper middle sized representative farm, the effect from relaxing the Specialized labor constraint was to maintain the level of dry season rice production but to change the proportion of cool dry season and hot dry season rice to accommodate more peanuts in the hot dry season. This increased the intensity index from 223 to 234 resulting in higher total cr0p value of B780. Slightly less hired labor was required because, as noted before, more family labor is presumed.available for farm work. Like- wise, there is more opportunity for off-farm employment resulting overall in an increase in household income per worker of about B206 per year and an increase of B689 for the total family. In this case a 6 percent increase in the available family labor supply resulted in only a 3 percent increase in total household income. 199 One might have guessed that because of the larger farm area to be farmed the available family labor supply would already be utilized in the farm cropping program. However, the programmed solutions indicate a surplus of labor for farm work even with the imposed labor constraint. Consequently, the programmed results appear similar to those previously discussed in that as the constraint is relaxed, the cropping program becomes more intense, less labor is hired and more family labor becomes available for off-farm employment. The overall effect is to increase net crop income about 10 percent and to increase the total household income by 12 percent. From this it may be concluded that the omission of these constraints in planning the large farm is a more serious matter than for the other farm Size claSses. Even though the percent of income being pr0vided by the farm remained essentially unchanged, the apparent potential earnings for a household in the large farm sized category is grossly overestimated by ignoring this class of Specialized labor activity. 9.5 Marginal Value Products of Resources When the amount of an available resource has been fully used up in an LP program, the addition of one more unit of such a resource at the margin would increase the net revenue by a certain amount. This amount at the margin is called the Marginal Value Product (MVP) or "shadow price" for the resource in question. This section will report the MVPS of family male labor, of family female labor, of hired labor and of borrowed money as determined by the model. 200 9.5.1 Marginal Value Product of Family Labor The MVP of family labor for male and female will be discussed separately by giving attention to the four possible outcomes that may be produced by a linear programming solution as described below and as presented in Table 9.6. l) The MVP of family labor is equal to a wage rate which the family can receive from working in non-farm activities. The LP solution shows the MVP of family labor at all times to be at least equal to this rate since it was assumed that family labor not used in the farm business could earn additional income by performing non-farm activities and thus pick up some earnings according to the wage schedule by periods. This situation where the MVP is equal to the off-farm working opportunity is represented in Table 9.6 by the word "OUT" in periods where it occurs. 2) The MVP of family labor is greater than the rate that could be obtained from being hired out but less than the rate that would be paid if labor would be hired in by the family. This means that an additional hour of family labor is worth more working in the farm business than in the non-farm activity but that the on-farm work earns too little at the margin to justify hiring additional labor. 3) The MVP of family labor is equal to a wage rate that the family would pay if hiring in. This implies that if an additional unit of family labor is available, cost savings can be achieved from not having to hire labor. The saving would be equal to the MVP for the unit not hired. Whenever this situation occurs, it is represented in Table 9.6 by the word "IN." =3:— 20l mum. use NON.N; cu .OOON N. O>z Ncowgma umuuwso .0N use ONNN; A O>z A c. NN.N; muoowucw Newman: mappgmucaicoz NNN: c. NN.N: A N>z NNNUNNON Newcasc NNNNLNNON N.N. pao NN.N; o. .Nacm Ncmms NNN mum; c. NN.N; ow .Nacm NONNE z. ”muoz N20 N20 Ono NNN 2. N20 2. N20 NN. 00.. .. NNN N20 N20 2. N20 N20 NNN z. NN. NN.N N.N. NN.N NN.N .N.N NN.N N..N NN.N NN.N ON.N NN. oo.. o. om.. .N.. 0N.. 0N.. om.. .m.. NN.N NN.N oo.. NN.N N NNN NNN NNN NNN 2. N20 N20 N20 NN.N NN.N N.N z. z. z. z. z. 2. 2H 2. NN.N NN.N N z. 2. 2H N30 2. z. z. z. No.. NN.. N.N 2. N20 2. z. 2. N20 2. z. oo.. NN.N . Lone; N.NENN N.NENN NN.O NN.. z. z. ON.O z. NNN z. NN. oo.. N.N. NN.N z. z. z. NN.N z. NNN z. NN. oo.. o. NNN NNN N20 N20 NNN N20 2. z. NN.N NN.N N.N NO.N. z. 2. N20 NO.N. z. 2. N30 NN.N NN.N N z. z. z. 2. 2H 2. z. z. NN.N NN.O N .N.N NN.N NN.N NO.N z. ON.N NN.N NN.N NN.N NN.N . NOON; N.NEON NNN: NN.N; m.Nu_z N.NNNZ ..OEN N am NN NN .30 c. NO.NNO .NOOO .OOOO I: I: I: I: OOO.N NELON m>NprcmNommmm NN.ONNNOo: ONNN NOON NNN: NENNN m>NuNucmchamm NON «NNN .NONON N.NENN No .OONONO m:.N> .Ncwmeez N.N N.NNN 202 4) The last situation possible in an LP solution is where the MVP of family labor is greater than the rate that would be paid by the family for hiring in additional labor. To have the MVP greater than the wage rate means that the resource is very constraining and that if we were able to use an additional unit of family labor, it would yield a return greater than the rate necessary to hire an addi- tional unit. This situation is represented in Table 9.6 by underlined numbers. 9.5.1.1 Marginal Value Product of Male Labor In all periods except 1, 2, 6, 6.5, 10 and 10.5 the MVP for male labor was equal to the wage rate that male family members could have received if hired outside the farming business. These periods are omitted from the table. In the exceptional periods the MVP for male family labor is at least equal to the off-farm opportunity wage rate. In period 1, the MVP fell between the hiring in rate and the off-farm opportunity rate. Male labor is constrained in this period by the necessity to harvest dry season cr0ps and at the same time to prepare the nursery for the rainy season rice crop. The only occurrences in which the MVP for male family labor was higher than the hiring in rate was in certain critical periods for the large representative and the same farm, periods on the large case farm. This situation held in periods 6, 10 and 10.5. It occurred because the large farms have a large area to be harvested for both rainy season rice (period 6) and cool dry season crops (period 10) as well as planting hot dry season crops (period 10.5). 203 9.5.1.2 Marginal Value Product for Female Labor In all periods except 1, 2, 5, 6, 6.5, 7, 10, 10.5 and 11, the MVP for female labor was equal to the wage rate which female family members could receive if hired outside the farm business. These periods are omitted from the table. In the exceptional periods, the MVP of female family labor is at least equal to the off-farm opportunity wage rate. In period 7 the MVP falls between the hiring in rate and the off-farm opportunity cost. Female labor is constrained in this period when planting of dry season cr0ps takes place. As noted earlier, women play a major role in dry season cropping. The MVP for female labor is particularly high in period 10 when it exceeds the hiring in rate. This is the period for harvesting dry season crops. In periods 10.5 and 11, the MVP is equal either to the hiring in rate or to the hiring out rate. 9.5.2 Marginal Value Product of Hired Labor The amount of male and female labor which a household could hire and the corresponding wage rate that would be paid by period was imposed upon the model at the level of two man equivalents per period for male and female in the rainy season, one and one-half man equivalents each for male and female in the cool dry season and one man equivalent per period each for male and female in the hot dry season. One must con- clude that this was not a serious constraint because in most periods and for most case farms and representative farms, the MVP for hired labor was zero. An exception was for the large representative farm and the case household within this size class which used all available hired labor in period 6 with a resulting MVP of B19 which is more than 204 four times the hired labor rate for this period of B3.50. There was also an effective hired labor constraint for large farms needing to employ labor in period 10 and 10.5 where the MVP ranged from 1.4 to 3.8 times the hired wage for those periods. The MVP for female labor was from 1.2 to 2.5 times the hired wage rate in period 10 for farms in the lower middle size class or larger. The labor constraint was effective on small farms only for female hired labor in period 10.5. 9.5.3 Marginal Value Product of Capital The linear programming result shows that no capital was borrowed for any representative farm or case farm regardless of size. This shows, given the assumptions of the model, that capital was not a limiting resource. Thus, the MVP of borrowed capital was equal to zero. In interpreting the MVP for capital, it is well to recall that the LP model was not designed to provide for the substitution of . capital for labor. This is to say that labor requirements were specified absolutely with the constraint imposed on the basis of family labor force and assumed hired labor availability. Capital requirements were specified to meet farm and home expenses and constrained by assumed capital on hand with opportunities to increase capital through produc- tive activities. There was no opportunity to reduce capital expenditure by increasing labor input nor to reduce labor input requirement by increasing capital expenditure. The borrowing activities were included in the design of the model to ensure feasible solutions knowing in advance that is not customary for Ban Pa Mark village people to borrow money to any appreciable extent. 205 9.5.4 Marginal Value Product of Land The linear programming model was designed to force all available land to be planted to rainy season rice if other constraints would permit it. Only the large farm (case household number 3 and the large representative farm) were unable to meet this condition resulting in an MVP for land equal to zero for these situations (Table 9.7). Table 9.7 Marginal Value Product for Land/Rai Case Constrained Unconstrained Farm Size Farm Farm Farm Small 8391 B342 B406 Lower Middle 333 310 391 Upper Middle 339 332 332 Large 0 O 268 With these levels of the MVP, an additional return from having one unit land if rented will be less than its cost. It is appropriate to compare this MVP with the rent for one rai of land but as was discussed in Chapter 3, it may be difficult to find an appropriate value for comparison. There was considered variability in land rental rates reported as a probable consequence of the various provision in the rental agreement. The average rent per rai for household reporting land rent was B696 and the average per rai computed over all rented land was B539. 9.6 Summary This chapter has presented the findings of the LP analysis. Specific findings will be summarized in the final chapter. General 206 conclusions point to the following: 1) Without adding to the resource base of small farmers, there is opportunity to increase family income by improved resource alloca- tion to involve, in most cases, a more intensive use of land for cropping in the dry season and an improved allocation of family labor berween farm work and non-farm employment. 2) An increase in the cropping intensity index is not necessarily a means to increase income. Good crop husbandry with better than average crop yield can, with a low cropping intensity index. produce more net crop value than a high crop intensity index with low crop yield. 3) Increasing the crop intensity index usually required the introduction of additional crops. For some farmers the more difficult management problems associated with the care of a larger number of crops could be sufficient to justify a simpler cropping system even if it. resulted in a lower total crop value. 4) For the conditions found in Ban Pa Mark, and with the assump- tions employed in the analysis, it would appear that neither capital nor labor constitute serious constraints on the improvement of family income. This is not to conclude that the computed income level are necessarily adequate to meet the goals of Ban Pa Mark families. Per- haps the introduction of more advanced technology could make a more significant change in income than was found in this study. But the answer to this question is found outside the scope of this thesis. 5) The consequences of omitting certain type of family labor commitment were evaluated in this chapter. Time customarily used by 207 families in the care of non-crop farming activities and for non-income producing community activities approaches of one-fifth of all time accounted for. Farm management analysts are prone to ignore this type of constraint in their planning efforts, not because it is considered unimportant, but because the necessary data are seldom available. Fortunately for this study, the available data did provide an opportunity to measure the extent to which farm and family income may be overestimated by ignoring this constraint. The implication of these and other findings will be discussed in the next and final chapter. CHAPTER 10 SUMMARY AND CONCLUSIONS 10.1 Summary - 10.1.1 Restatement of the Problem and Research Approach The 1976-79 Fourth National Development Plan of Thailand emphasized diversification and the growth of agricultural production through inten- sification and increased productivity to ensure an adequate food supply for the growing population and to increase the farm income and the standard living of the community. Multiple cropping has been offered as a means to serve this policy purposes since it is the practice of planting in a given field, a crop or crops two or more times in one. year. Land is limited and the size of farm is generally small in Thailand. This condition is generally true throughout the developing world and multiple cropping is receiving increasing attention as a means to improve the agricultural production system on small farms especially in areas of tropical agriculture. This thesis is a modest contribution to the vast and ever-growing literature on the problem and issues surrounding farming systems and multiple cropping research. The locational setting for this study is the village of Ban Pa Mark, located in the Chiang Mai Valley of Northern Thailand. This is a location particularly favorable for multiple cropping with a reasonably well developed infrastructure and reliable year-round water supply made 208 209 available as part of the Mea Taeng Irrigation Project, the largest of the three irrigation projects serving the Chiang Mai Valley. The village of Ban Pa Mark first came under study during 1972-73 as part of a socio-economics baseline survey of 22 villages conducted as an early activity of Multiple Cr0pping Project (MCP) at Chiang Mai University. During the same period it was one of a subsample of 3 selected from the original villages to provide specialized economic and production data at the end of both rainy season and dry season crop harvests. Because more accurate measurement on labor utilization, income sources and expenditure patterns than was possible from the six month interval study, Ban Pa Mark was designated as the single village which would be subject to a full year intensive study with data collected daily throughout the crop year of 1973-74. The primary data needed for this thesis came from the above mentioned studies but mostly from the intensive study of 1973-74. The Multiple Cropping Project at Chiang Mai University was initiated in 1969 with the following objectives: a) to develop,on a pilot basis, ecologically sound systems of multiple cropping with silo and water management designed to substantially increase farm income b) to get all agencies of government and private business concerned with agriculture to develop a "package of services" for farmers that will enable them to make the best possible use in both economics and production terms, of the improved production technology and other resources 210 c) to monitor the adoption process in order to continuously evaluate the project and improve its impacts on the village farm community To achieve the above objectives, the work plan called for five sequential stages: 1) inventory of farming system 2) synthesis of prototypical farming systems 3) technology design and farm system validation 4) evaluation of impacts on the farms 5) implementation of multiple cropping process in village development At the time the current research was undertaken, the project was entering the phase having to do with evaluation of impacts on farms, however, during the validation phase there was evidence to suggest strong reluctance on the part of the farmers to make the kind of changes in their traditional farm organization and practices which would be needed if the research results of the university were to be incorporated into the everyday life of the Ban Pa Mark farmers. The underlying principle for the conduct of this present research is that it is extremely important to introduce change starting from where the farmer is. In support of this principle little attention was given to the research at Chiang Mai University which concentrates on new production systems. Rather, the attention was given to the systems and practices being followed by the farmers at the time of the inten- sive study. 211 With this focus in mind, the following objectives were set forth: 1) to describe in detail Ban Pa Mark village and the individual households of a 30 family sample of its inhabitants for the two-fold purpose of (a) identifying and measuring critical constraints surrounding the management of typical cropping patterns, and (b) Specifying representative farms and individual household cases for more detailed analysis 2) to develop a linear programming model to inCorporate the con- straints and to involve the representative farms and house- hold cases from objective 1 in such a way as to determine possible reasons for dry season cropping being less than its apparent potential 3) to use the model developed in objective 2 to specify the most appropriate dry season cropping patterns consistent with the resource endowments and assumed constraints for the various representative farms and case households 4) to interpret the linear programming solutions for their implications for further research and extension program implementation in the Multiple Cropping Project at Chiang Mai University The first step taken to fulfill the thesis objective was to describe in detail the land, labor and capital constraints of individual households which would have bearing on the kind and the amount of crops that would be grown in the dry season periods. The analysis of the effect of resource endowment and specialized constraints of farm organization and family income entailed the use of a poly-period 212 programming model to specify optimal solutions for representative farms derived from four farm sized strata and for one case household selected from each Stratum. It was felt, given the objectives of the study, that both case households and representative farms would be useful. There is no individual farm like a representative farm as it was defined because no farm is likely to have exactly the average amount of every kind of crop and the thought that the planting and harvesting dates for an individual farm will include all of the dates found in the sample is somewhat incomprehensible. The individual farm analysis is appropriate if one is attempting to examine what is possible for a particular set of family circumstances and is looking for recommendations to improve the income position of such a family situation. The representative farm is more appropriate if one is attempting to examine certain rela- tionships such as the relationship between the level of earnings and farm size. The reason for this is that some of the determinants for the variation in level of earnings are being controlled in the averaging process from which the representative farm is derived. This study has elements of both types of problem and hence it was decided to use both the case household and the representative farms. 10.1.2 Summary of Production Constraints 10.1.2.1 Land Holdings The range in farm size for the 30 household sample was from 1.79 to 24.25 rai operated with a mean of 11.64 rai. 0n the average 9.22 of the 11.64 rai were owned with the rental land operated under a variety of leasing arrangements but with the average computed value of 213 rent per rai of B539. Regardless of farm size, farm operators tend to subdivide their parcels into fairly uniform units of about .34 rai per field plot. The dry season land area was utilized on the average as follows:. 4.12 rai (38.6 percent of dry season land) in dry season rice, 5.77 rai (54 percent) in soybeans, .69 rai (6.5 percent) in peanuts, and .10 (.9 percent) in garlic. This pattern of land utilization resulted in a cropping intensity index of 192 which means that 92 percent of the total land area was utilized during the dry season period. All avail- able land was planted to rice in the rainy season because for reasons of tradition, food security, and the suitable rice growing conditions, no Thai farmer would produce any Other crop at this time of the year. 10.1.2.2 Family Composition and Labor Force Household size ranged from 3 to 10 members with an average of . 5.4 per household and an average age of 28 years. The model household size was 5 members with an average age of 27.6 years. For comparability among families, the diverse age and sex distributions were converted to two common denominators. The first was to an adult male work equivalent with consideration given to age and availability of family members for farm work. The average family size of 5.4 members converted to 3.2. adult full time equivalents of which 42 percent was composed of female and 6 percent children with the remaining 52 percent being male adult. This conversion was used to establish the labor availability coefficients (RHS) for each period by sex in the linear programming model. The family composition was also converted to the common denominator of adult equivalent consumer. On the basis of an estimated share that 214 members have of total consumption, adult consumer equivalents were computed on the basis of age and sex. This computation revealed an average of 4.4 adult consumer equivalents with 42 percent female, 11 percent children and 47 percent adult male. The computed adult con- sumer equivalents for each family were used in the analysis of income distribution and compared with income distribution based on all family members. When the households were stratified by farm Size, it was observed that family Size (hence adult labor equivalents and adult consumer equivalents) increase in direct proportion to land area operated. It was found that farms in the upper half by farm size average more than twice as much farm land per household but about 75 percent more land per man equivalent. From the recorded hours of time spent by family members on farming activities, the following statistics were computed for use in the linear programming model: 1) labor requirement by activities by crop and by sex. The labor requirement by crop activity were aggregated to period for use in the model. Requirements for crops were computed using the average of farms with less than 10 rai and from farms with 10 rai or more. Had there been sufficient number of grower for each crop it probably would have been desirable to develop labor coefficients for every representative farm. This was not the case. Given the distri- bution of farm by land area operated, dividing the total sample into those less than 10 rai and those with more than 10 rai seem quite reasonable. The coefficients obtained from the farm with less than 10 rai would be suitable for the case household found in the small and lower middle farm size classes. The coefficients obtained from the 215 averages of farms with 10 rai or more would be suitable for analyzing the case household and representative farms in the upper middle and large farm Size classes. Particular attention was given to specialized roles that family members play in crop production. Men carry out the activities which need physical strength like plowing, harrowing for rice, bedding for peanuts and garlic, pulling rice seedlings and threshing rice and soy- beans. Women do most of the rice transplanting and participate very heavily in the cutting, bundling and moving of rice at harvest time. They spent more time in planting dry season crops than did men. They also spent more time than men in bundling and cleaning soybeans and peanuts. Children may be regarded as standby labor to be called into service during critical periods and to work on occasion when they are not in school. Exchange labor is an interesting phenomenon in the Ban Pa Mark. agricultural system. Two-fifths of the labor used in rice transplanting and two-thirds of the labor used in rainy season rice harvesting is provided by exchange labor. It is also high for rice threshing (73 per- cent) and for rice cutting (42 percent) in the dry season. Exchange labor is also used in other dry season crops for activities such as threshing soybeans (44 percent), plowing and harrowing (84 percent) and cleaning peanuts (54 percent), and making bed for garlic (68 percent). Despite its importance to farm production, exchange labor was not included in the design of the linear programming model in view of its fast turn- around requirement resulting in the usual completion of exchange tran- sactions within a single period. 216 Farming is more than growing crops in the Thai farm family. Approximately 18 percent of the total farm labor is devoted to the care of livestock, maintenance of the family garden and the harvesting of native fruit. These activities contribute only 8 percent of total value of home produce consumed but are a very Significant part of farm life. Some enterprises such as swine and poultry are found at some 1 time of the year on all farms. They are sustained mainly from kitchen and field by-products and by using labor that is not urgently needed in other parts of the farm business. Most of the labor for non~crop farm enterprises is supplied by women and children. Since these activities have been maintained primarily for home consumption rather than for commercial purpoSes, livestock enterprises were not introduced as viable alternatives in the linear programming model. However, because they are so fixed in the system, the labor required to maintain them was regarded unavailable (in one part of the analysis) for crop production or other income generating activities. To measure the effect of this concept, linear programming solutions were obtained for both the case where this labor was assumed available to the program and in another case where it was assumed unavailable. The seasonal pattern of this labor requirement was also imposed on the model. Non-farm activities were examined both for their contribution to family income and their share of total labor utilization. In addition, the amount of time spent in non-farm income producing and off-farm income producing activities were analyzed. In accounting for all labor activities of the farm families (except for in-home activities such as preparing meals, sewing, resting, care 217 of children, etc.), 52 percent of the time was spent away from home with 48 percent in farm production. 0f the time spent away from home 5 percent was involved in exchange labor activities, 77 percent was in non-farm income earning work and the remaining 18 percent was involved in community activities or other types of non-income producing effort. Looking at the total labor utilization, off-farm labor represented 40 percent and the non-paying community work activities constituted 9 percent of the total. In terms of gross income, farming is by far the most important because 42 percent of the total time expended produced 82 percent of the family gross income; whereas off- farm labor activities representing 40 percent of the time contributed only 18 percent of the family gross income. Family members hiring themselves out to others contributed 58 percent of the total earnings from non-farm employment. Four-fifths of this was in the form of non-farm employment (for example, carpentry, wood carving, or building construction). Self-employed non-farm activities included paid services (such as barber or beautician),handicraft and trading. The latter represented three-quarters of the income from self-employed works. Taking into account time spent and the corresponding earnings, a seasonal distribution of wage rates per period was derived for use in the LP model. All families had some hired labor expenses and regardless of farm size, it constituted the highest percent of total crop production cost. The outlay for hired labor ranged from B80 to B4882 per farm, averaged B1659 and represented 43 percent of total farm expenses. Labor was hired primarily for harvesting but was also important for plowing 218 (especially when both man and buffalo were hired together). Taking into account time hired and amount spent plus considerable judgement on the part of the researchers, seasonal labor rates paid by the family were estimated for use in the LP model. 10.1.2.3 Capital Unlike most studies dealing with peasant agriculture, capital availability was not found to be a major limiting resource in Ban Pa Mark for the production technology currently employed. From the data, it was found that the production cost for crops (except garlic) are relatively low aside from the outlays for the hired labor mentioned above. Ignoring rent and considering only rental of buffalo and farm supplies, including seed, fertilizer and chemicals, the average cash expenditures per rai used in the LP model per crop are as follows: B32 for rainy season rice, B38 for dry season rice, B49 for soybeans, B127 for peanuts and B660 for garlic. The relatively low capital requirement for crop production and the apparent traditionally high propensity for Thai farmers to save, one finds that the borrowing of money for short term use takes place chiefly among friends and relatives. In designing the LP model, the initial capital on hand for representative farms was estimated from the actual inventory of households within the respective farm size strata. This estimate came to about B500, B1000, B1500 and B1500 for the small, lower middle, upper middle and large representative farms respectively. 10.1.3 Household Income and Assets The value of crop production plus the receipts from labor hired out and from self-employed activities yielded an average of B18,536 per 219 household. As noted above, the farm component of this income (crops and non-crop) represented 82 percent of the total leaving 18 percent for receipts to the family labor from off—farm activities. When summarized on the basis of farm sized group, it was found that the non-farm income component of family income was substantially higher in the small farm quartile than was true for the rest of the sample. To examine income distribution in Ban Pa Mark, it was found that the Gini coefficients were .233, .192, and .232 for income per capita, per consumer equivalent and per household respectively. The coefficients, reflecting a relatively equal distribution, are low for developing countries and the per capita income coefficient is considerably lower than the .44 coefficient estimated for rural Thailand in an earlier study. The annual per capita income average was B2,648 (or $132 and approximately 43 percent of the per capita income average for the nation reported in the 1977 Statistical Yearbook). With regard to asset ownership, real estate in the form of land and housing, represents about 94 percent of the total value of farm assets. Most of the remainder (6 percent) comes from the value of livestock and poultry enterprises. The value of farm implements and farm supplies on hand are negligible in value in relation to other assets. In the initial survey on which this study was based, no attempt was made to enumerate or evaluate personal property in total. Atten- tion was given only to certain selected durable goods which might give some indications as to differential levels of living among the house- holds. These goods included bicycles, motorcycles, watches, clocks, 220 radios and sewing machines. Of these items, bicycles, closely followed by radios, were the most common. Motorcycles and sewing machines being the most expensive were the least common and were found chiefly in the homes of the most well-to-do families. 10.1.4 Summary of the Linear Programming Results 10.1.4.1 Results from Case Household Analysis Four households were selected which were most like the average of the farms in their corresponding farm size classes (households 65, 63, 50, and 3 in order of size). In discussing the organization of any farm, what may be regarded optimum from one point of view is not necessarily optimum for another. It is quite possible that the individual farm operators in the present analysis may regard their existing farming systems more satisfactory than the reorganizations that might be recommended from the LP solutions. For example, the linear programming solutions in general call for more crops and in many cases much smaller area per crop than was found on the existing farms. The increased complexity of the system may be in itself sufficient reason to be rejected by the farmer. Nevertheless, the results are presented here as an indication of how farms might be reorganized (if necessary) to demonstrate a more complete utilization of available resources. Highlights of the linear programming solutions in relation to existing conditions are as follows: 1) For the small farm, the LP solution yielded a lower intensity index with a lower total crop value than that found in the actual case. 221 Primarily because of a higher crop yield, even with nearly twice the amount of hired labor expenditure, this case farmer had a net crop value 20 percent higher than the LP solution generated. More family labor marketed in off-farm labor activities resulted in a lower percent of total income coming from farm sources. 2) In a reverse situation, the LP solution for household 63 specified a stronger emphasis on the cropping program and a decrease in the allocation of family labor to off-farm activities than holds for the existing situation. The program solution would nearly double crop value because of an expanding dry season cropping program and because of an existing crop yield for rice on farm 63 being less than average. To handle the expanded cropping program, almost 10 times the existing level of hired labor would be needed. 3) Farm 50 was distinguished by high total crop value despite a low cropping intensity index. The dry season cropping program was marked by variety but the total amount of dry season crops utilized only 66 percent of the farm land available. The LP solution would call for dry season cropping using 134 percent of the land available. Less family resources would be utilized in off-farm employment. The net effect would be an increase in income per worker by about B600 per year. 4) The farm number 3 in the large farm category had a 14 point higher crop intensity index than would be specified in the LP solutions. The existing organization concentrated on rice and soybeans whereas the LP solution would propose growing some of all of the commonly grown crops. It is quite possible that the farmers present organization is satisfactory if crop yields could be increased. His rice yield was only 222 75 percent of the village average. Given the rather relatively large supply of family labor on this farm, a substantial amount of off-farm earning could be obtained even with maintenance of an intensive cropping system in the dry season. 10.1.4.2 Results from Representative Farm Analysis The purpose of the comparison of linear programming results for the various representative farms was to determine how the optimum solution obtained differed by farm size for the several variables selected for interpretation. The results indicated marked differences in the solutions according to farm size with the following generaliza- tions forthcoming: 1) As farm size increases, the cropping intensity index decreases. 2) Even as the crop intensity diminishes as the result of less possible land being planted in the dry season, the amount of hired labor required increases with the size of the farm. Also, the larger hired labor expenditure and higher rental charges notwithstanding, net crop value increases with farm size because of the larger amount of land area being farmed. 3) As farm size increases, the proportion of total family income generated from non-farm sources decreases. 4) Total household income per worker increases steadily with farm size. 10.1.4.3 Results from Relaxed Labor Constraint In recognition of the fact that, on the average, 18 percent of the total labor accounted for in this study was expended for the maintenance of traditional non-field cropping enterprises and for non-income 223 producing community activities, it was decided to measure the effect of these constraints on the volume and organization of the cropping system. Obviously freeing more resources should call for either an expansion of a cropping system or an increased amount of non-farm work or some combination of the two. For all representative farms, the cropping intensity index increased from 3 to 7 percent depending on farm size and off-farm income increased from 11 to 27 percent depending on farm size. In monetary terms, relaxation of this constraint increased the total household income B913 (6 percent), B1275 (6 percent), B689 (3 percent) and B3469 (12 percent) for the small, lower middle, upper middle and large sized representative farms respectively. Overall, to ignore this type of labor constraint is to overstate the availability of farm labor supply for cropping or non-farm work by some 13 percent and the income by approximately 6 percent. 10.2 Implications of the Study 10.2.1 Implications of the Findings for the Multiple Cropping Project The Multiple Cropping Project at Chiang Mai University has been an example of one approach to research and education for the intensifi- cation of dry season cropping programs. This approach is to start at the experiment station with the evaluation of potentially biologically stable and economically viable cropping systems. The emphasis is on the evaluation of new crops (such as wheat, sorghum, sunflower, caster bean, cabbage, tomatoes, chickpeas, sweet corn, etc.) with special attention being paid to developing new genetic material and engineering new 224 cultural practices in the field. After a development stage, the new system components are tested in the farmer's field. Implicit in this approach is the expectation that some new cropping system will evolve which will have general suitability for a large population of farmers. An alternative approach to the problem of farming systems develop- ment is one viewing it as a need to apply basic principles of farm and home management to the individual farm situation. In this approach recognition is given to the fact that each household represents a unique case with regards to resource endowments and other constraints such as attitudes, age, health, experience, etc. Each Situation will have its own best cropping system. The cropping pattern is a part of the cropping system which, in turn, is a part of the complete farming system. In this approach consideration will also be given to off-farm employment, off-farm community service obligations and opportunities for individual self fulfillment. This study has demonstrated that even with crops well established in the community, there is room for possible resource reallocations to improve the farming system and the level of family income. On the other hand, it was found in certain individual cases that researchers themselves can learn from farmers. This was indicated by the case where the farm organization appears to be as good or superior to the LP solution. In the opinion of this researcher, the Multiple Cropping Project Should return to the field and to continually monitor what farmers are doing and to introduce change only as it can be demonstrated consistent with the resource situation for individual farm families. 225 Obviously, any multiple cropping system in the area must be rice-based. The role that dry season rice plays both as an insurance for adequate food as well as for a cash crop needs to be recognized. The findings from this study indicate that women dominate farm production activities in the dry season. This finding may be very significant for the extension and out-reach personnel of the Multiple Cropping Project. It may have implications to the types of crops that may be acceptable in the area and it may have bearing on how extension programs are conducted. In the Thai setting, it is the man alone who attends public meetings. The man according to his mood will decide how much and in what form his findings at educational meetings will be passed on to family members. The policy implication of this finding that women dominate the dry season cropping scene is not clear but it does seem worthy of evaluation by those responsible for extension pro- gramming in the MCP. The dominant role that exchange labor plays in critical production periods is also worthy of careful attention. Though non-conclusive, there is evidence indicating that the planting dates for rainy season rice are staggered through the village. Exchange labor is an old and well-established practice in Thai farming communities carrying with it both economic and social implications. From the economic side, a different planting date implies a different harvesting period as well as different ecological stress in the life of the plant. Hence, the community decision as to whose crop will be planted first and whose will be planted last raises some interesting welfare economic questions such as who benefits and who loses in this process and how are the 226 decisions made? On the social side, to assume in the multiple cropping research that the family function independently can lead to invalid analysis. To assume independence may discount unduly the true oppor- tunities for the introduction of more crops to the farming systems. At the same time, since so much of the farm work is characterized by group participation, it will be difficult for a cropping system regarded as an innovation to be accepted by one farmer if it is not generally acceptable to the entire community. Reference has been made to the amount of family labor time expended in community services and self-fulfillment religious activities for their impact on the amount of total labor that may be available for income generation. There is another dimension of this which may have implications for the adoption of a dry season cropping program. It has to do with the seasonal distribution of this commitment which has a "peak" in period 4 and another in period 11.. One might conclude that this is good timing for non-farm work in the sense that these periods are not typically critical in terms of labor requirements for crop production. However, it was observed that these periods correspond to the time for heaviest consumption expenditures because of the expenses related to Par Pa, Katin and Songkarn seasons. The implication is that the greatest drain on the family's cash flow occurs in the periods prior to the harvest of both rainy season rice and dry season crops. It is felt that for cultural reasons, the typical allocation of family labor for these activities is highly inflexible. Therefore, crops shouldnot be specified which compete for labor in this high priority non-farming period. It appears that the solution to the cash flow management pro- blem is found in the non-farm employment effort and in the management 227 (of crop inventories, rather than in producing crops that can be har- vested in time of primary need. The above conclusions have been based on both the descriptive and the linear programming aspects of the study. Both aspects have helped to provide improved insight regarding how rural village farmers utilized their resources. Before turning to the need for further research, it may be appropriate to review the role that the poly-period programming methodology can aid in this type of analysis. The second objective of the study shows interest in comparing what farmers actually do to what is potentially possible without knowing in advance what the potentialities are under traditional farming methods. The linear programming model helped answer that question. For the resource condition analyzed and the assumption employed including the assumption that family would maintain their current level of labor utilization in non-crop farming activities and off-farm community services, the highest cropping intensity index obtained was 275 on a large representative farm. This can be compared with one household in the village having the highest cr0pping intensity index equal to 270. The income potential per adult worker equivalent was found to be about B7600. This programmed result is nearly B2200 per worker higher than what realized by the farm family at the time of the survey. The matter of income potential is more pertinent than is the matter of cropping intensity potential. The former is concerned with maximizing net income in total and from all sources whereas the latter is concerned only with the proportion of available land being cultivated in the dry season. The linear programming method is particularly useful in a 228 problem of maximization of income for a given resource when all relevant alternatives are considered. All the reasons which might explain why farmers are not achieving thier full potential are not found in this study. Nevertheless, many clues were provided in the LP analysis. It helps to diagnose the effect of lower than average crop yield, the relation between farm and non-farm income, the importance of crop choice, and the contribution of women on total family income. Never- theless, the well known shortcoming of the LP analysis are conceded. As indicated earlier, the so called optimal solution may only provide possible direction for change and should not be regarded as sacred. 10.2.2 Need for Further Research Discussion on the need for further research will be based on perceived weaknesses in the current study. The data on which the research was based were abundant and carefully collected. Nevertheless, making estimates of certain parameters (particularly inputs and outputs of dry season crops) was difficult for lack of sufficient observations. If this type of analysis is to continue at Chiang Mai University, it will be necessary to monitor local production conditions more carefully and to isolate the primary variables affecting crop yield and in general to improve the estimates of these parameters. On the methodological side, more research is needed on how the Thai farmer deals with risk and uncertainty. Risk considerations were introduced primarily as a safety first consideration. The probabilistic aspects of risk were not incorporated. As more work is done in this area, perhaps the linear programming approach would be replaced by one more capable of dealing with stochastic processes. With adequate 229 resources, this linear programming model could be improved to more closely simulate farmer behavior and hence improve the LP solutions. Every attempt was made to bring reality into the design of this model but some of the simplifications of reality are troublesome. For example, it would have been more realistic but too complex to introduce labor requirements in terms of specific sex and specific activities as well as by period. Dividing periods6 and 10 improved the performance but a more realistic (but larger and more cumbersome) design would have recognized that some critical farming operations are performed in a matter of a very few days and failure to perform them on time may have consequences for the output. Over-aggregation of these events is a common shortcoming in farm planning by LP, but to cope with this pro- blem completely would require a very major investment. For whatever shortcoming there may be in this study, it is hoped that the result will have some usefulness to the on-going effort in multiple cropping research at Chiang Mai University. APPENDIX 230 ' Appendix Table 3.1 LAND AND LAND TENURE FACTORS BY HOUSEHOLD Land Rented Rent/rai (B) Number Rai Hshld Land Total No. Owned R.S. D.S Both Total Land R.S. D.S 80th Total Fields Plots Pl/Fld Per/Field Per/Plot 34 1.79 - - - 1.79 - - - - 1 6 6 1.79 .30 49 1.96 - - - - 1.96 - - - - 1 9 9 1.96 .22 61 1.54 - 1.50 - 1.50 3.04 - 455 - 455 1 12 12 3.04 .25 65 - - - 5.67 5.67 5.67 - - * * 2 18 9 2.84 .32 39 6.25 - - - - 6.25 - - - - 2 20 10 3.12 .31 54 4.56 3.50 - 3.50 3.50 8.06 506 - - 506 2 26 13 4.03 .31 30 - - - 8.30 8.30 8.30 - - 402 402 1 22 22 8.30 .38 37 5.37 3.00 - - 3.00 8.37 540 - - 540 1 21 21 8.37 .40 sub Total 21.47 6.50 1.50 13.97 21.97 43.44 1046 455 402 1903 11 137 xx xx xx Ave 3.57 3.25 1.50 6.98 4.39 5.43 523 455 402 476 1.4 17.1 12.4 3.95 .32 1 4.94 15.0 3.4 32.2 50.6 100 - - - - - - - - - 6 7.00 1.49 - - 1.49 8.49 1268 - - 1268 l 28 28 8.49 .30 19 4.31 4.30 - - 4.30 8.61 512 - - 512 2 25 12.5 4.30 .34 10 8.99 - .25 - .25 9.24 - 1712 - 1712 2 29 14.5 4.62 .32 53 5.82 4.00 - - 4.00 9.82 472 - - 472 2 36 18 4.91 .27 63 - - - 10.76 10.76 10.76 - - 74 74 3 37 12.3 3.52 .29 4 11.05 - - - - 11.05 - — - - 2 24 12 5.52 .46 59 11.20 - - - - 11.20 - - - - 3 39 13 3.73 .29 sub Total 48.37 9.79 .25 10.76 20.8 69.17 2252 1712 74 4038 15 218 xx xx xx Ave 8.06 3.26 .25 10.76 4.16 9.88 751 1712 74 808 2.1 31.1 14.5 4.61 .32 % 69.9 14.2 .4 15.5 30.1 100 - - - - - - - - - 20 10.80 - .50 - .50 11.30 - 440 - 440 3 29 9.7 3.77 .39 33 10.31 1.50 - - 1.50 11.81 1180 - - 1180 l 41 41 11.81 .29 32 12.08 - - - - 12.08 - - - - 1 3O 30 12.08 .40 50 8.71 3.50 - - 3.50 12.21 989 - - 989 4 48 12 3.0 .25 45 13.34 - - - - 13.34 - - - - 1 42 42 13.34 .32 25 11.87 2.00 - - 2.00 13.87 375 - - 375 1 37 37 13.87 .37 18 13.62 — .50 - .50 14.12 - 440 - 440 l 34 34 14.12 .42 sub Total 80.73 7 00 1.00 - 8.00 88.73 2544 880 - 3424 12 261 xx xx xx Ave 11.53 2 33 .50 - 1.60 12.68 848 440 - 685 1.7 37.3 21.8 7.4 .34 1 91.0 8 O 1.0 9.0 100 - - - - - - - - - 17 14.29 - - - - 14.29 - - - - l 29 29 14.29 .49 36 11.34 - - 3.00 3.00 14.34 - - 1467 1467 2 46 23 7.17 .31 11 14.16 - - 1.50 1.50 15.66 - - 1880 1880 4 43 10.8 3.91 .36 3 16.24 — - — - 16.24 - - - - 4 47 11.8 4.06 .34 16 17.14 - - - - 17.14 - - - - 2 50 25 8.57 .34 58 16.92 5.75 - - 5.75 22.67 652 - - 652 4 75 21.7 5.67 .30 31 17.22 6.00 - - 6.00 23.22 567 - - 567 3 60 20 7.74 .39 23 18.75 - - 5.50 5.50 24.25 - - 676 676 3 68 22.7 8.08 .36 sub Totl 126.06 11.75 - 10.00 21.75 147.81 1219 - 4023 5242 23 418 xx xx xx Ave 15.83 5.88 - 5.00 4.35 18.48 110 - 1341 1048 2.9 52.2 18.2 6.4 .35 1 85.3 7.9 - 6.8 14.7 100 - - - - - - - - - Totl 276.63 35.04 2.75 34.73 72.52 349.15 7061. 3047 449914607 61 1034 xx xx xx Ave 10.24 3.50 .69 5.79 3.63 11.64 706 762 643 696 2.0 34.5 17.0 5.72 .34 % *Rented free from parents. Omitted from all averages. **Averages computed on basis of farms reporting. Land use percentages based on all farms. Appendix Table 3.2 231 CROPS GROWN IN DRY SEASON AND CROPPING INTENSITY INDEX. HOUSEHOLDS STRATIFIED BY FARM SIZE Rice Soybean Peanut Garlic Total Intensity System HH Land ND Area Rai % Rai % Rai 1 Rai % Rai Index Number 34 1.79 1.59“ 89 - 1.59“ 189 1 49 1.96 1.96“ 100 1.96“ 200 1 61 3.04 1.40“ 46 - 1.28 42 2.68“ 188 3 65 5.67 3.69“ 65 5.20 92 .22 4 9.11“ 260 5 39 6.25 1.50“ 24 1.45 23 2.95“ 147 4 54 8.06 3.33“ 41 2.29 29 5.62“ 170 2 30 8.30 7.38“ 89 .53 6 .39 5 8.30“ 200 5 37 8.37 8.29“ 99 4.91 59 .47 6 .53 6 14.20“ 270 6 sub Total 43.44 29.14 67 14.38 33 1.75 4 .14 2 46.41 207 x Ave 5.43 3.64 xx 1.80 xx .22 xx .14 xx 5.80 xx xx 6 8.49 4.87“ 57 1.56 18 6.43“ 175 2 19 8.61 - - 4.79 56 .63 7 5.42“ 163 9 10 9.24 2.39“ 26 7.03 76 1.62 17 11.04“ 219 4 53 9.82 - - 8.42 86 8.42“ 186 7 63 10.76 3.06“ 28 - 3.06“ 128 1 4 11.05 3.41“ 31 6.62 60 .70 6 10.73“ 197 S 59 11.20 3.03“ 27 8.18 73 11.21“ 200 2 sub Total 69.17 16.76 24 36.6 53 1.62 2 .33 2 56.31 180 x Ave 9.88 2.39 xx 5.23 xx .23 xx .19 xx 8.04 xx xx 20 11.30 10.00“ 88 5.94 53 .37 3 16.31“ 244 5 33 11.81 3.16“ 27 5.94 50 9.10“ 177 2 32 12.08 9.45 78 2.63 22 12.08“ 200 8 50 12.21 1.06“ 9 4.82 39 2.18 18 8.06“ 166 4 45 13.34 - - 2.84 21 2.84“ 121 7 25 13.87 7.11“ 51 3.22 23 3.27 24 13.60“ 198 4 18 14.12 4.10“ 29 10.11 72 2.75 19 16.96“ 220 4 sub Total 88.73 25.43 29 42.32 48 10.83 12 .37 * 78.95 189 x Ave 12.68 3.63 xx 6.04 xx 1.55 xx .05 xx 11.28 xx xx 17 14.29 10.2 71 3.99 28 .12 1 14.31“ 200 10 36 14.34 5.96“ 42 4.60 32 10.56“ 174 2 11 15.66 - - 8.10 52 8.10“ 152 7 3 16.24 10.22 63 10.54 65 20.76“ 228 2 16 17.14 7.30 43 6.49 38 13.79“ 181 2 58 22.67 6.71 30 6.64 29 2.50 11 15.85“ 170 4 31 23.22 22.23 96 4.68 20 26.91“ 216 2 23 24.25 - - 15.69 65 15.69“ 165 7 sub Total 147.81 52.42 35 66.94 45 6.49 4 .12 * 125.97 185 x Ave 18.48 6.55 xx 8.37 xx .81 xx .01 xx 15.74 xx xx Total 349.15 123.75 35 160.24 46 20.69 6 .96 1 307.64 188 x Ave 11.64 4.12 xx 5.34 xx .69 xx .10 xx 10.25 xx xx *Less than .5 percent. 232 Appendix Table 3.3 FULL TIME LABOR FORCE EQUIVALENTS BY HOUSEHOLD Female Members of Age Male Members by Age Labor Force Conversion Factor Conversion Factor R / a. 0 .2 .72 .2 0 .3 1.0 .5 Total HH Family Labor NO Size <8 8-14 15-60 >60 Total <8 8-14 15-60 >60 Total Female Male Total Force 34 4 1 2 3 1 1 1.64 1.0 2.64 .68 49 5 2 1 3 1 1 2 1.12 1.0 2.12 .92 61 5 1 1 1 3 4 .72 3.3 4.02 .76 65 4 1 l 2 1 3 .72 1.6 2.32 2.44 39 3 1 l 1 1 2 .72 1.5 2.22 2.82 54 5 1 1 2 2 4 .72 2.6 3.32 2.43 30 7 1 1 2 4 l l 1 3 1.64 1.30 2.94 2.82 37 3 1 1 2 2 .72 2.0 2.72 3.08 sub Total 36 1 4 10 0 15 2 6 12 l 21 8.00 14.3 22.30 xx Ave 4.50 .12 .50 1.25 0 1.87 .25 .75 1.50 .12 2.62 1.00 1.79 2.79 l 95 1 100 2.8 11.1 27.8 0 41.7 5.6 16.7 33.3 2.8 58.3 35.9 64.1 100 xx 6 4 l 1 1* .3 1 l .72 1.0 1.72 4.94 19 4 1 1 l 1 1 3 .72 1.3 2.02 4.26 10 10 2 4 6 1 3 4 2.88 3.0 5.88 1.57 53 7 1 1 2 4 3 3 1.64 3.0 4.64 2.12 63 5 2 1 3 2 2 1.12 2.0 3.12 3.45 4 6 l 2 l l 5 l 1 1.32 1.0 2.32 4.76 59 5 1 1 2 4 1 l 1.64 1.0 2.64 4 24 sub Total 41 6 6 12 1*.1 26 2 1 12 0 15 10 04 12.3 22 34 xx Ave 5.86 .86 .86 1.71 .29 3.71 .28 .14 1.72 o 2.14 l 43 1.76 3 19 3 10 1 100 14.6 14.6 29.3 4.9 63.4 4.9 2.4 29.3 36.6 44 9 55.1 100 xx 20 5 2 2 1 2 3 1.44 2.3 3.74 3.02 33 5 l 2 3 2 2 1.44 2.0 3.44 3.44 32 8 2 2 4 1 1 2 4 1.84 2.3 4.14 2.92 50 4 2 2 2 2 1.44 2.0 3 44 3.55 45 5 2 2 l 2 3 1.44 2.0 3 44 3.88 25 5 1 l 2 1 2 3 .92 1.0 1.92 7.22 18 6 3 2* 5 1 1 2.16 1.0 3.16 4.47 sub Total 38 l 3 l4 2* 20 3 2 11 2 18 10.68 12.6 23.28 xx Ave 5.43 .14 .43 2.0 .29 2.86 .43 .29 1.57 .29 2.57 1.53 1.80 3.33 3.81 z 100 2.6 7.9 36.8 5.3 52.6 7.9 5.3 28.9 5.3 47.4 45.9 54.1 100 xx 17 6 1 1 1‘ 3 2 l 3 .72 1.6 2.32 6.16 36 5 3 3 l 1 2 2.16 .5 2.66 5.39 11 4 l 1 2 2 2 .4 2.0 2.4 6.52 3 4 2 2 2 2 1.44 2.0 3.44 4.72 16 7 1 3 4 3 3 2.36 3.0 5.36 3.20 58 7 4 4 3 3 2.88 3.0 5.88 3.86 31 7 1 1 2 2 3 5 .92 3.6 4.52 5.14 23 8 l 1 l 3 1 l 2 l 5 .92 2.8 3.72 6.52 sub Total 48 2 3 15 1*.2 23 2 5 l6 2 25 11.8 18.5 30.3 xx Ave 6.00 .25 .38 1.87 .38 2.88 .25 .62 2.00 .25 3.12 1.49 2.30 3.79 4.94 S 100 4.2 6.2 31.3 6.2 41.9 4.2 10.4 33.3 4.2 52.1 38.9 61.1 100 xx Total 163 10 16 51 7 84 9 14 51 5 79 40.32 57.7 98.22 xx Ave 5.43 .33 .53 1.70 .23 2.80 .30 .47 1.70 .17 2.63 1.35 1.92 3.27 3.55 “ 100 6.1 9.8 31.3 4.3 51.5 5.5 8.6 31.3 3.1 48.5 41.3 58.7 100 xx *Too old to work on the farm. excluded from labor force. 233 Appendix Table 3.4 Adult Hale ConSumer Equivalents by Household Family Members with Conversion Factor by Age Adult Male --- Consumer Equiv. Children Female Male HH Family .10 .30 .50 .65 xx .75 .80 xx .80 1.00 xx No. Size <1 1-3 4-5 6-9 Total 10-15 16+ Total 10-15 16+ Total C F H T 34 4 l 1 2 2 1 1 .65 1.60 1 00 3.25 49 5 1 1 2 1 3 l 1 .65 2.30 l 00 3.95 61 5 0 1 1 2 2 4 .80 3.60 4.40 65 4 0 1 1 2 1 3 .80 2.60 3.40 39 3 0 1 1 1 1 2 .80 1 80 2.60 54 5 1 1 1 1 2 1 3 .65 .80 2.60 4.05 30 7 1 1 2 1 1 2 1 2 3 1.15 1.55 2.80 5.50 37 3 0 1 1 2 2 .80 2 00 2.80 sub Total 36 O 0 1 4 5 3 12 11 19 3.10 9.45 17.40 29.95 Ave 4.50 O O 12 50 .62 .38 1 12 1.50 1.0 1.38 2.38 .39 1.18 2.18 3.74 7 100 0 0 2 8 11 1 13.9 8.3 25.0 33.3 22.2 30.6 52.8 10.3 31.6 58.1 100 6 4 l 1 2 2 1 1 .10 1.60 1.00 2.70 19 4 2 2 1 1 1 1 1.30 .80 1.00 3.10 10 10 l 1 2 4 1 3 4 2 2 1.70 3.15 2.00 6.85 53 7 1 1 1 2 3 3 3 .65 2.35 3.00 6.00 63 5 1 l 1 1 2 2 2 .65 1.55 2.00 4.20 4 6 1 1 2 1 2 3 1 1 1.15 2.35 1.00 4.50 59 1 1 2 1 3 1 1 .65 2.30 1.00 3.95 sub Total 41 2 1 1 8 1 6 12 18 11 11 6.20 14.10 11.00 31.30 Ave 5.86 .28 14 .14 1.14 1.71 .86 1.71 2.57 0 1.57 1.57 .89 2.01 1.57 4.47 1 100 4.9 2 2.4 19.5 29.3 14.6 29.3 43.9 0 26.8 26.8 1913 45.0 35.2 100 20 5 1 l 2 2 2 2 .65 1.60 2.00 4.25 33 5 1 1 2 2 2 2 .30 1.60 2.00 3.90 32 8 1 1 2 2 4 1 2 3 .65 3.10 2.80 6.55 50 4 O 2 2 2 2 1.60 2.00 3.60 45 5 1 l 2 2 2 2 .30 1.60 2.00 3.90 25 5 l 1 2 2 2 1 1 .95 1.60 1.00 3.55 18 6 0 5 5 l 1 4.00 1.00 5.00 sub Total 38 0 3 O 3 6 2 17 19 1 12 13 2.85 15.10 12.80 30.75 Ave 5.43 O .43 O .43 .86 .28 2.43 2.71 .14 1.71 1.85 .41 2.16 1.83 4.39 ” 100 0 7.9 0 7.9 15.8 5.3 44.7 50.0 2.6 31.6 34.2 9.3 49.1 41.6 100 17 6 l 1 2 2 2 1 1 2 1.15 1.60 1.80 4.55 36 5 1 1 3 3 1 1 .50 2.40 1.00 3.90 11 4 ' 0 1 1 2 2 2 1.55 2.00 3.55 3 4 0 1 1 2 2 2 1.55 2.00 3.55 16 7 0 2 2 4 3 3 3.10 3.00 6.10 58 7 0 4 4 3 3 3.20 3.00 6.20 31 7 0 1 1 2 2 3 5 1.55 4.60 6.15 23 8 2 2 2 2 2 2 4 1.30 1.60 3.60 6.50 Sub Total 48 0 O 2 3 5 5 16 21 5 17 22 2.95 16.55 21.00 40.50 Ave 6.00 0 0 .25 .37 .62 .62 2.0 2.62 .62 2.13 2.75 .37 2.07 2.62 5.06 100 0 0 4.2 6.2 10.4 10.4 33.3 43.8 10.4 35.4 45.8 7.3 40.9 51.8 100 Total 163 2 4 4 18 28 16 54 70 14 51 65 15.1 55.2 62.2 132.5 Ave 5.43 .07 .13 .13 .60 .93 .53 1.80 2.33 .47 1.70 237 .5 1.84 2.07 4.41 11.1 100 100 1.2 2.4 2.4 17.2 9.8 33.1 42.9 8.6 31.3 39911.4 41.7 46.9 12394 Appendix Table 4.1 Distribution of Labor by Men, Women. and Children to Crop Production and other Farm Work by Size of Farm; Both Unadjusted and Adjusted for Family Composition Unadjusted for Composition Adjusted for Compositiona iAdjusted All Item Per Farm Size Class Farm Size Class Farms Heusehold Small L. Mid. U. Mid. Large Small L. Mid. U. Mid. Large Labor Forceb Amt. % Amt. : Amt. z Amt. 7. Amt. z Amt. 2. Amt. a; Amt. 2'. Amt. 1 Men 1.56 56 1.71 54 1.71 52 2.13 56 1.52 54 1.74 54 1.81 54 2.06 54 1.78 54 women .90 32 1.26 39 1.44 43 1.40 37 1.06 38 1.21 38 1.26 38 1.44 38 1.24 38 Children .33 12 .22 7 .17 5 .26 7 .21 8 .24 8 .25 8 .29 8 .25 8 Total 2.79 100 3.19 100 3.32 100 3.79 100 2.79 100 3.19 100 3.32 100 3.79 100 3.27 100 Haurs on Crops Men 792 56 1049 51 1591 53 1919 55 772 53 1067 53 1684 57 1856 54 1339 54 Women 567 40 932 46 1329 45 1430 41 668 45 895 44 1163 40 1471 42 1060 43 Children 48 4 60 3 68 2 131 4 30 2 65 3 100 3 146 4 78 3 Total 1407 100 2041 100 2988 100 3480 100 1470 100 2027 100 2947 100 3473 100 2477 100 Hours Other Farm Men 207 36 268 48 296 58 396 63 202 35 273 50 313 61 383 62 292 51 women 265 46 289 52 185 37 215 34 312 54 278 50 162 32 221 35 238 42 Children 104 18 0 0 25 5 15 3 66 11 0 0 37 7 17 3 38 7’ Total 576 100 557 100 506 100 626 100 580 100 551 100 512 100 621 100 568 100 Heurs Total Farm Men 999 50 1317 51 1887 54 2315 56 973 47 1340 52 1997 58 2239 55 1631 53 Women 832 42 1221 47 1514 43 1645 40 980 48 1172 45 1325 38 1692 41 1290 43 Children 152 8 60 2 93 3 146 4 97 5 65 3 137 4 163 4 116 4 Total Farm 1983 100 2598 100 3494 100 4106 100 2050 100 2577 100 3459 100 4094 100 3045 100 Hours/Rai Crop 259 71 206 79 236 86 188 85 271 72 205 79 232 85 188 85 213 81 Other Farm 106 29 56 21 40 14 34 15 107 28 56 21 40 15 34 15 49 19 Total Farm 365 100 262 100 276 100 222 100 378 100 261 100 272 100 222 100 262 100 Rai/Farm 5.43 9.88 12.68 18.48 5.43 9.88 12.68 18.48 11.64 aAdjustment procedure: (a) total labor force distributed by percentage of all farms, (b) unadjusted hours/man equivalent computed for men, women and children. 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NN Na NN MA “N Raw NN an RN an N 3N3 NOOLO N 3N3 NOONN N 3N3 NOONN N 3N3 NOONO NNNON NNNumqm LoONN umNN: mm333uxm \MNNNNQ uoNgmN 33OLu ELNN mm334 uca m3 uNocmmao: NON Nona; ELNNINNO No :oNuanNNNNNo Nacommmm .INHNQNN an ammo new Q3030 Now coNNmN an mauucmugmq v. m mpnaN x_u=waa< .2114 1 APPENDIX TABLE 6.1 CROP GROSS VALUE BY HOUSEHOLD AND SEASON Rainy Séason Drx, Season Crops Hagggggld fi1ce % of a11 Gross Va1ue (Bahtf' % of a11 T3§1Le Va1ue B crops Rice qubeans Peanut Gar1ic Tota1 crops 34 1560 51.3 1480 1480 48.7 3040 49 1390 51.8 1296 1296 48.2 2686 51 6020 58.5 3654 624 4278 41.5 10298 55 3450 26.9 3036 3598 2760 9394 73.1 12844 39 3816 65.0 1540 518 2058 35.0 5874 54 10840 35.2 2540 1025 3565 24.8 14405 30 5460 56.3 3640 105 500 4245 43.7 9705 37 7200 4034 1560 4320 729 4032 10641 59.6 17841 SUb‘tOtETii 39736 51.8 18746 9566 1353 7292 36957 48.27 6693’ AVE ("=81 4967 xxx 2343 1196 169 912 4620 xxx 9587 6 6000 65.5 2400 762 3162 34.5 49162 19 4590 59.6 1809 1300 3109 40.4 7699 10 4500 44.4 1909 3283 450 5642 55.6 10142 53 8310 57.8 6078 6078 42.2 13288 63 6920 74.5 2373 2373 25.5 9293 4 7950 52.4 2960 3900 350 7210 47.6 15160 59 8610 48.9 8983 8983 51.1 17593 Sub-tota1 46880 56.2 9642 24815 450 1650 36557 43.8 83437 Ave (n=7), 6697 xxx 1377 3545 64 236 5222 xxx 11919 20 12100 70.0 3445 1800 5245 30.2 17345 33 10800 74.5 3160 540 3700 25.5 14500 32 9180 61.1 4130 1708 5838 38.9 15018 50 10650 62.3 760 3548 2146 6454 37.7 17104 as 9495 96.4 358 353 3.6 9853 25 9780 60.5 3980 900 1512 6392 39.5 16172 18 7630 39.9 3180 5940 2744 11864 60.1 19494 Sub-tota1 69635 63.6 1080 18861 8110 1800 39851 36.3 09486 Ave (n =7), 9948 xxx 1583 2694 1159 257 5693 xxx 15641 17 12000 52.6 6890 910 3000 10800 47.4 22800 36 10320 69.6 3460 1045 4505 30.4 14825 11 8850 64.8 4800 4800 35.2 13650 3 7230 44.3 4000 5100 9100 55.7 16330 16 12610 66.1 4440 2015 6455 33.9 19065 58 16740 55.8 5290 5335 2632 13257 44.2 29997 31 17135 52.4 13200 2352 15552 47.6 32687 23 6360 42.3 1140 7534 8674 57.7 15034 5hb-tota1 91245 55.5 38420 28181 3542 3000 73143 44.5 64388 Ave ("=81_, 11406 xxx 4802 3523 443 375 9143 xxx 20549 T0ta1 47496 87 0 77888 81472 11485 12747 888n8 4338 aanna Ave (n=30) 8250 xxx 2596 2714 449 458 6217 xxx 14467 1 Averages of sub-c1asses equa1 the representative farms. APPENDIX TABLE 6.2 245 FARM NON-CROP INCOME Source of Other Income (Baht and % of househo1d) H/H # 4Fruits ’POUTtry Veg. z Swine % 5 Eggs 1 Fish % Tota1 34 35 1 2560 97 35 1 13 1 2643 49 1980 100 1980 61 35 19 145 81 180 65 611 60 400 40 1011 32 49 9 475 91 524 5 ' -- 30 2645+ 100 2645 37 420 70 177 30 597 Sub-Tota1 730 8625 212 13 9580 87:1n38) 91 1078” 90 27 2 2 * 1198 Av/ H H reprtng 183 xx 1232 xx 106 xx 13 xx xxx 6 8 1 650 97 12 2 670 19 21 100 + 21 10 600 90 68 10 668 53 400 100 400 63 200 100 200 4 27 5 500 95 527 59 19 100 19 Sub-tota1 75 2300 80 2505 Av. (n=7) 11 3 336 94 11 3 358 Av. / H H reprtng 19 xx 470 xx 40 xx xx xx 20 525 100 525 33 12 + 2662 100 2674 32 4 1 392 58 282 41 678 50 637 97 18 3 655 45 40 4 975 89 77 7 1092 25 135 9 1300+ 91 1435 18 9 1 740 99 734 Sub-tota1 837 6594 377 7804 Av. (n=71 119 11 942 84 54 5 1115 Av./H H reprtnq 140 xx 1099 xx 126 xx xx xx 17 36 40 3 1205+ 97 1245 11 3 730 100 830 16 1705 100 1705 58 19 100 19 31 + 136 100 136 23 450 100 450 Sub-tota1 59 4090 136 4285 Av. (n=81’ 7 1 511 96 17 3 535 fly./H H reprtng 30 xx 1023 xx 136 xx x xx ‘Totai ' 1701 21.659 805 13 24,174 Av. ("330) ’57 7 722 90 27 3 x xx 806 Av/ H.H reprtngr 106 xx 985 xx 101 xx 13 xx xx * = less than 1% + = exc1uding the sa1e of Yater buffa1o and oxen Appendix Table 6.3 Hours Spent 246 Returns and Returns Per Hour For Hon-Farm Income by Sourcea Hause- Laborer Service Handicraft Trading Total hold Number Hours Baht 8/ hr Haurs Baht B/hr Hours Baht 8/ hr 11H0urs Baht / hr Hours Baht 8/ hr 34 701.5 2119 3.02 4021 660 .16 238 795 3.34 4960.5 3574 .72 49 1142.4 1339 1.17 1124 158 .14 (71.2) 20 ( .28) 3266.4 1497 .66 61 729.6 1589 2.18 3499 530 .15 201 261 1.30 4429.6 2380 .54 65 -- -- -- 522 114 .22 (230) 1763 (7.66) 522.0 114 .22 39 728.6b 884 1.21 917.7 370 ..40 -- -- b -- 1646.3 1254 .76 54 159.7 321 (2.01) b 2343 160 .07 ( 61) 171 2.81) 2502.7 481 .19 30 956.0 1232 1.29 72.5 179 (2.47) 1496.7 432 .29 (1154) 3243b 2.81) 2525.2 1843 .73- 37 938.0 2334 2.49 118 292 2.47 630.7 245 .39 84 324 3.86 1770.7 3195 1.80 Total 5355.8 9818 xx 190.5 471 xx 14554.1 2669 xx 523.0 1380 xx 20623.4 14338 xx Ave. 669.5 1227 ..83 23.8 59 2.47 1819.3 334 .18 65.4 172.5 2.64 2577.9 1792 .70 6 -- -- -- -- -- b -- -- -- -- -- -- -- 19 61.0 142 2.33 327 69 (.21) 90 331 3.68 478.0 542 1.13 10 253.7 616 2.43 3592 632 .18 160 301 1.88 4005.7 1549 .39 53 3161.8 4165 1.32 b 2920 556 .19 290 442 1.52 6371.8 5163 .81 63 1693.9 5120 3.02 190.4 470 (2.47) 3677 1143 .31 247 899 3.64 3808.3 7632 2.00 4 225.7b 331 1.47 569 109 .19 --- -- -- 794.7 440 .55 59 261.0 524 (2.01) 2083.3 459 .22 489.5 938 1.92 2833.8 1921 .68 Total 5657.1 10898 xx 190.4 470 xx 13168.3 2968 xx 1276.5 2911 xx 20292.3 17247 xx Ave. 808.2 1556.8 1.93 23.8 67 2.47 1881.2 424 .22 182.3 415.9 2.28 2898.9 2464 .85 20 650 682 1.05 -- -- -- (21 )b (230”) 650 682.0 1.05 33 2461.6 7871 3.20 504 164 .32 (160 ) (450) 2965.6 8035.0 2.70 32 1145.2 3012 2.63 1927.6 587 .30 186 813 4.37 3258.8 4412.0 1.35 50 706.8 1115 1.58 1951.2 437 .22 267 410 1.54 2925.0 1962.0 .67 45 197.0 280 1.42 1766 339 .19 -- -- -- 1963.0 619.0 .32 25 16.0 52 3.25 641.2 207 .32 -- -- -- 657.2 259.0 .39 18 79.0 118 1.49 917 160 .17 -- -- -- 996.0 278.0 .28 Total 5255.6 13130 xx ~- -- -- 7707 1894 xx 453 1223 xx 13415.6 16247.0 xx Ave. 750.8 1875.7 2.50 -- -- -- 1101 270.6 .24 64.7 174.7 2.69 1916.5 2321.0 1.21 17 -- -- -- 161.3 34 (.21) 1 425.2 417 .98 586.5 451 .77 36 104.9 110 1.05 767.6 206b .27 131.0 216 1.65 1003.5 532 .53 11 390.0 680 1.74 17 4b (.21) -- -- -- 407.0 684 1.68 3 3.0 10 3.33 32.3 7 (.21) 943.8 3401 3.60 979.1 3418 3.49 16 3346.5 5400 1.61 1 829.6 292 .35 1058 13446 3.26 5234.1 9138 1.74 58 1385.4 3969 2.86 1 3443.9 451 .13 11561.3 5047 3.23 6390.6 9467 1.48 31 547.0 600 1.10 1 -- -- -- 39 124 3.18 586.0 1 724 1.24 23 1260.9 2287 1.81 1 419.9 65 .15 13435.2 16890 2.00 5116.0 9242 1.81 Total 7037.7 13056 xx -- -- -- 5671.6 1059 xx 7593.5 19541 xx 20302.8 33656 xx Ave. 879.7 1632 1.86 -- -- —- 709.0 132 .19 949.2 2443.6 2.57 2537.8 4207 1.66 A11 1 1 Farms 23306.2 46902 xx 380.9 941 xx 41101 8590 xx 9846.0 125055 xx 74634.1 81488 xx Ave 776.9 1563.4 2.01 12.7 31 2.47 1370 286 .21 328.2 835 2.54 2487.8 2962 1.09 aAverages computed on basis of all households in corresponding grOup. 0 this income source. Reported data considered unreliable. This figure adjusted using average baht/hour for remaining households for Results of this adjustment shown in parentheses. 247 .wcaumucmaxw ..0uwu Lo» 0 cwuaozu ~00 002:0.u:oaxo 5:001co: .xuoumm>.. .:o..u:uocq nocu 00v:.0:. 02:..ccoaxuo .IIIIIII-IoIIYoaaIOAIIu’IIO 00000000 fails.1040:448447141I801:1’|1409:4440.01841481001- lllllll Issai‘latoolaoalot 111111 (1.111110. 020.0. . .0..0 . 000.. _ 000.0. 0 200.0 . ” 020.0. 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A. 000.. 000.0 020.0 000.0 000.0 000.0 00 .111 1 -111111 - - 1. m .0000 aocu . .00 oeou:. a 00.000x mo 0 .muop 0 :oz 0 00:0 «Eouc. _ “ \mEouc. wmoLo . Li - 2mn532 umz . 000:0000. 0020 .0000 0200:. 5:00-:02 0500:. 5:00 . v.0:00so: 1a!‘l-nlaa'..'411|.-.l|'41l 144 -1 O'III 44:11154E‘iil- .0:00. 0500:. 062 0:0 .mm\mEou:. nocu .msouc. A..Eou .muop II. l.l“: -‘1’1411 -1.‘ I 11.01 411-4’14-‘ 11.1- .«.0 0.00. 0.000000 APPENDIX TABLE 6.5 248 HOUSEHOLD NET INCOME. PER CAPITA INCOME AND INCOME PER CONSUMER EQUIVALENleBaht), H/H Househo1d Per Capita Per Consumer # Net Income EIEcome ’1ncome 34 7,845 1.961 2.414 49 4,921 984 1.246 61 11,969 2,394 2,720 65 14.557 3.639 4.282 39 6,958 2.319 2.676 54 10.012 2.002 2.472 30 14.491 2.070 2.635 37 17,818 5,939 6,364 Sub-tota1 88,571 xxxx xxxx Av (n=81, 11,071 2,460 2,960 6 6,706 1.676 2.484 19 3,195 799 1.030 10 10.674 1,067 1.558 53 15,703 2.243 2,617 63 15,557 3.111 3.704 4 13.780 2.297 3.062 59 13,763 2,753 2,484 Sub-tota1 79,378 xxxx xxxx Av (n:1),, 11,340 1,935 2,537 20 15,683 3,137 2,690 33 18.542 3.708 4.754 32 17.002 2,125 2.596 50 13.015 3.254 3.615 45 9.962 1,992 2.554 25 11.246 2.249 3,168 18 15,851 2,642 3,170 Sub-tota1 101,301 xxxx xxxx Av (n=7) 14,472 2,665 3,297 17 20,490 3.415 4.503 36 11,226 2,245 2.878 11 10,150 2,538 2,859 3 18,200 4.550 5.127 16 27.589 3,941 4,523 58 30,846 4,407 4,975 31 25.270 3.610 4.109 23 18,250 2,281 2,808 Sub-tote] 162,021 xxxx xxxx Av,jn=81, 20,253 3.376 4.003 Total 431,271 xxxx ‘ xxxx Average 14,376 2,648 3,260 1‘ 719 132 163 1 Baht converted to d011ars using 20:1 exchange rate. 249 .2... ..un names as .53; — -~.o~ an. onm.c oa~._~ mam.~ ofio.o. oaa.Nm -.o .omucv ,< mo_.mw~.~ an... 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ON OOO OOO OOO OOO.N -- OO OOO.N N -- -- -- -- OO -- -- -- OO... -- -- OO... . -- -- -- -- .O OOO OON OON ONO.N -- ON -- -- -- -- OOO.N . OO -- -- -- OOO.. -- OO OOO.. . -- -- -- -- ON OOOLoOO ONNONNO NNN.NN OOOO N.N.OON OO... .02 «O.., .02 OO..) .02 Lungs: zmou .uuo» .wo u:.o> m.m :mxo o.amO:m v.0:mmao: .OOOO O. OO.~>O O.OOOOOOO NO ONO. .ON OOOO .OOO: co zOou ma~go>< use xuoumo>wg we Agouco>c. .N.O O.OO. N.OOOOOO 25] OOO.N N.O ON. ON ON ON..N OOO .ON.=O OO OO0.00. OO0.0. O OON.O ON OOO O OOO.. N OOO.NO N. OON.O. ON .N.O. OOO.O .N ON. ON .N N.N.N OOO .Ouc. OO ON0.0N OOO.N . OO... N ONO N ON. . OO0.0N O OON.O O. .OOO. OOO OO0.0 -- -- OO. . -- -- -- -- OOO.O . OOO.. . NN OON.N -- -- OO. . OON . -- -- OOO.O . OOO . .N OO0.0. OOO.N . -- -- ON . -- -- OOO.O . ONO . OO OON.. -- -- OO. . OON . -- -- -- -- OOO N O. OON.O -- -- OON . -- -- -- -- OO0.0 . OOO N N ONN -- -- OON . -- -- ON. . -- -- -- -- .. OO. -- -- OO. . -- -- -- -- -- -- -- -- ON OON.. -- -- OON . -- -- -- -- -- -- OOO.. N N. ON0.0 O.N.. OO. NN OO ON0.0 OOO .Nucv >< OOO.OO OON.O N OO... O ONN . OOO N OOO..N O OON.O O .OOO. OOO OO..N -- -- OON . -- -- -- -- -- -- OOO.. N O. OON.. -- -- OO. . -- -- -- -- -- -- OOO.. . ON -- -- -- -- -- -- -- -- -- -- -- -- -- OO OO0.0 OOO.N . OON . -- -- OON . OO0.0 . OOO . OO OOO.N OOO . OON . ONN . -- -- OOO.O . OOO.. N NN OO0.0N OO0.0 . OON . -- -- OON . OO0.0. N OOO.. . NN OON.N -- -- OO. . -- -- OON . OOO.N . -- -- ON .OO.. OO. OON O .N ONO OON .Nucv >4 OO0.0. OON.. . OOO.. O OO . ONN N OOO.O N OO..N O .NOO. OOO OOO.O OON.. . -- -- -- -- OON . OOO.O . OO. . OO OOO.. -- -- -- -- -- -- -- -- -- -- OOO.. . O OOO -- -- OOO . -- -- -- -- -- -- -- -- NO -- -- -- -- -- -- -- -- -- -- -- -- -- NO OON.. -- -- OOO N OO . -- -- -- -- OOO . O. ONO.. -- -- OO. . -- -- ON . OOO.. . -- -- O. OON -- -- OO. . -- -- -- -- -- -- OOO . O OON.. ONN N.N O ON ONO .OuOO >< OO0.0 OOO.N . OON.. N -- -- OO . OON . OO0.0 N .N.O. OOO OOO.. -- -- OOO . -- -- -- -- -- -- OO... . NN OON.N -- -- OO. . -- -- -- -- -- -- OO..N N ON OON -- -- OO . -- -- -- -- -- -- OON . OO OOO -- -- OON . -- -- -- -- -- -- OO. . ON OO0.0 OOO.N . OON . -- -- -- -- -- -- OOO . OO OOO -- -- OO . -- -- OO -- OON . -- -- .O OON -- -- OOO . -- -- -- -- -- -- OO. . OO II I- II II I- II II II II II II I- I. a OO..) .oz OO..) .OO «O.., .oz OO.O> .Oz OO.O> .oz OO.O> oz 332.5 *0 0552.. 395: 2:2. .38. 9:33 33.. .608 :32. 033 No.8: 033.8 29.33: 3.2.3 2...; v... «23. ..0..-5:3 039:5 .0.0 O.OO. N.OOOOOO 252 I\ppendix Table 6.9. Tota1 Farm Assets, Non-Farm Assets and Total Family Assets Household Tota1 Farm Non-Farm Assets Total Fam11y Number Assets wr-Assets Selected Average Tota1 Durables Cash 34 13,800 -- -- -- 13.800 49 17,183 750 500 1.250 18.433 61 35.859 400 -- 400 36.259 65 3,115 4.000 550 4.550 7,665 39 47,849 450 1,025 1,475 49,324 54 38.616 350 300 650 39.266 30 6,550 2,200 400 2,600 9,150 37 40,959 1,500 1,000 2,500 43,459 Sub Total 203,931 9,650 3,775 13,425 217,356 Av (n=8) 25,491 1,206 472 1,678 27,169 6 48,940 700 900 16,000 50,540 19 33,484 1,920 3,750 5,670 39,154 10 90,463 1,240 400 1,640 92,103 53 40,965 --- 1 800 800 41,765 63 18,678 400 200 600 19,278 4 88,187 1,000 190 1.190 89.377 59 105,990 5,600 600 6,200 112,190 Sub Tota1 426,707 10,860 6,840 17,700 444,407 Av (n=7) 60,958 1,551 977 2,528 63,486 20 107,738 3,300 6,150 7,450 117,188 33 91,896 25,000 2,000 27,000 118,896 32 102,008 7,480 2,125 9,605 111,613 50 74,067 8,900 1,100 10,000 84,067 45 97,171 -- 350 350 97,521 25 93,010 1,700 400 2,100 95,110 18 101,687 2,100 2,850 4,950 106,637 Sub Tota1 667,577 48,480 14,975 63,455 731,032 Av (n=7) 95,368 6,926 2,139 9,065 104,433 17 107,223 1,200 550 1,750 107,973 36 79,199 150 450 600 79,799 11 107,249 370 1,000 1.370 108.619 3 141,462 8,700 3,900 12,600. 154,062 16 133,341 1,300 -- 1,300 134,641 58 153,093 10,655 2,500 13,155 166,248 31 139,286 7,300 2,750 10,050 149,336 23 130,100 6,000 200 6,200 136,300 Sub Total 989,953 35,675 11,350 47,025 1,036,978 Av (n=8) 123,744 4,459 1,419 5,878 129,622 Tota1 2,288,168 104,665 36,940 141,605 2,429,773 Av (n=30) 76,272 3,489 1,231 4,720 80,992 Percent 95.5 3.4 1.1 4.5 100 Appendix Table 7.1 Househo1d Expenditures: 253 Crop Production lnc1uding Land Rent, Livestock and Nonfarm Per Household by Farm Size HH Crop Production Non-Fara Total No. -“ Labor Power Equip Supp1ies Hater Sub Rent Tota1 Livestock H/Craft Trading Sub Total Total 34 465 100 34 215 6 820 -- 820 591 -- -- -- 1411 49 1093 -- -- -- 2 1095 -- 1095 167 -- 180 180 1442 61 80 -- -- 115 2 197 682 879 110 -- -- -- 989 65 966 ; -- -- 170 7 1143 9 1143 37 -- 460 460 1640 39 575 -- -- 103 8 686 -- 686 12 -- -— -- 698 54 1930 —- -- 237 7 2174 1770 3944 137 138 5249 5387 9468 30 1846 609 734 17 3211 3340 6551 155 -- -- -- 6706 37 655 -- -- 1076 7 1738 1620 3358 457 -- .4 -- -- 3815 - .--_......11_ __ Sub Total 7610 709 39 2650 56 11064 7412 18476 1666 138 5889 6027 26169 Ave. n=8 951 89 5 331 7 1383 926 2310 208 17 736 753 3271 —-— d --.. .-0.-—....--”— 6 684 -- 35 498 10 1227 1890 3117 9 -- -- -- 3126 19 1126 -- 199 1312 15 2652 2200 4852 146 -- -- -- 4998 10 - 963 -- 62 99 6 1130 428 1558 127 -- 400 400 2085 53 421 1500 -- 322 11 2254 1890 4144 104 -- -- -- 4248 63 186 -- 66 -- 6 258 792 1050 49 -- -- -- 1099 4 1307 112 60 723 18 2220 -- 2220 129 -- -- -- 2349 59 4784 -- 25 548 11 5368 -- 5368 402 -- -- -- 5779 N..—.... 0*--kaflp- -—._—Jr.-_-._._T.-- .. ..-.l--......+.--.....-_... Sub Tota1 9471 1612 447 3502 77 15109 7200 22309 966 -- 400 400 23675 Ave. n=7 1353 230 64 515 11 2158 1029 3187 138 +-- 57 57 3382 ~m~ A -------- 1-“ u-nw-Ouwv-~u-n-- 20 1312 -- -- 1510 20 2842 220 3062 37 -- -- -- 3099 33 3602 -- 468 308 8 4386 1770 6156 961 -- -- -- 7117 32 1614 -- 162 1028 12 2816 -- 2816 290 -- -- -- 3106 50 2924 -- 20 148 11 3103 3461 6565 142 -- 1096 1096 7802 45 487 900 -- 127 13 1527 -- 1527 75 -- -- -- 1602 25 4882 -- 350 495 13 5740 750 6490 130 -- -- -- 6620 18 2149 -- 123 2077 20 4369 220 4589 81 -- -- -- 4670 -—-~-*- ---—-°--'-- -+-r----‘ir- '—--lr- ------- r—------ ----- "11 ------- 4 --------- '41- ----- 1 ---------- - Sub 1 Total 16970 900 1123 5693 97 24783 6421 31204 1716 l-- 1096 1096 34016 Ave. n=7 2424 128 161 813 14 3540 917 4458 245 -- 157 157 4860 ------- 3L.....-.-.------3---1--..,.--....---Or.._..4L--.... --—-~ »~ ~1--.-~---~---------1------11-------- - - 17 1653 70 -- 459 13 2195 -- 2195 532 -- 700 700 3427 36 603 -- 5 182 12 802 4400 5202 174 -- -- -- 5376 11 633 -- 6 660 12 1311 2820 4131 49 -- -- -- 4180 3 1707 60 7 454 25 2253 -- 2253 18 -- 2 -- -- 2271 16 1377 -- -- 554 13 1944 -- 1944 375 -- i -- -- 2319 58 4168 -- 114 412 22 4716 3750 8466 170 -- -- -- 8636 31 3588 -- 25 1493 20 5126 3100 8226 51 -- 1 -- -- 8277 23 1989 -- 23 545 18 2575 3720 6295 181 .-- 1 -- -- 6476 ------- 4----------L---..__----..--L---..-----L-..- --———O»—---N- O-------«o--~-1----—---4---- - --«------11--»--- - - Sub ' 1 . Total 15718 130 180 4759 135 20922 17790 38712 1550 l-- 1 700 5 700 40962 AVE. 7 : n=8 1 1965 16 F 22 41 595 17 2615 2224 4839 194 g-- i 88 E 88 1 5120 -------- -------------- - ----—o— ---—---—-->-‘-- r’----.-rr------ ----- -----~------1--------- --°-°----v-------o----—-------- Total 1 49768 3351 : 1789 i 16604 365 71878 3882 f110701 5898 1138 i 8085 2 8223 1124822 Ave. ; . I . : : . n=30 1 1659 1 112 i 60 1 553 12 2376 1294 E 3690 197 3 5 I 269 3 274 1 4161 ------- 1-~-~-—+-~--+-~-~-4 -u-~-~O~-.ur~-u~-»Nu~4o-u-- -~-~-u-~-+o~—~-4-~-~-+--~-¢-~-n-~-» : 39.9 :2 7 : 1.4 513.3 .3 57.6 31.1 3 88.7 : 4.7 1.1 16.5 56.6 g 100 ------.-- --- ----'r--- -'r -----r----------r ------ r-------1.r------T—-'-“HT-0°". "T --- .----- T ------ v- ------------ Ave/ : : . . | I i 4 3 4 I HH Rep 5 1659 L 479 L 94 L 593 L12 i 2396 [1941 [ 3690i 197 5138 I 1348 E 1371 i 4161 aRent free from parents. Exc1uded from farms reporting. ' BIBLIOGRAPHY 10. BIBLIOGRAPHY AGRANAL, R. C. and E. 0. Heady. 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