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DATE DUE DATE DUE DATE DUE 2/05 p:/C|RC/DateDue.indd-p.1 THE DETERMINANTS OF RURAL NON-FARM EMPLOYMENT AND INCOMES IN BOLIVIA By Valeria Sanchez A THESIS Submitted to Michigan State University In partial fulfillment of the requirements For the degree of MASTER OF SCIENCE Department of Agricultural Economics 2006 ABSTRACT THE DETERMINANTS OF RURAL NON-FARM EMPLOYMENT AND INCOMES IN BOLIVIA By Valeria Sanchez This thesis examines the factors influencing non-farm employment and income among rural households in Bolivia. Two econometric models are used to estimate the determinants of a) participation in nonagricultural employment, b) the determinants of the intensity of participation and c) the income level of rural households by sector. To estimate participation and intensity of participation, a double hurdle model is applied whereas to estimate income determinants, ordinary least squares (OLS) and tobit models are implemented. The results suggest that gender plays an important role in participation, intensity of participation and level of income. Women tend to focus on nonagricultural self employment activities. Education is also an important determinant in all three models especially nonagricultural wage employment and highly skilled employment. The ecoregion also influences whether a household engages in agricultural work or not. Finally, those individuals who reside in dispersed rural areas are less likely to find employment other than agricultural wage labor. Education must be an important component of any policy intervention, focused on training, and recognizing the heterogeneity of the ecoregions. Policy makers should also note the high share of nonagricultural wage employment in household activities. This thesis is dedicated to my beautiful children Anika and Joaquin and to my unconditional partner, Cristébal. ACKNOWLEDGEMENTS I would like to take the opportunity to thank all of the people who in one way or another made a difference during my stay at Michigan State for three years and whom I will always remember. To begin with I would like to thank the Department of Agricultural Economics for all of the support I received throughout my stay at Michigan State, and even before I arrived. I would like to especially thank Dr. Eric Crawford, Dr. Thomas Reardon, Dr. Scott Swinton, Dr. Laura Cheney, Sheryl Rich and Pat Neumann. One of the biggest strengths of the Department in my view is the comradeship between students. I would like to thank every one of my fellow students for being so supportive, unselfish and encouraging. My experience at MSU has been amazing thanks to all of you. I also want to thank Dr. Scott Swinton, Dr. Thomas Reardon and Dr. John Giles for their valuable support and guidance during the thesis writing process. I will carry many things with me which I have learned from you. Dr. Swinton and Dr. Reardon, I want to thank you both especially for your patience, advice and friendship. Last but not least, I thank my entire family for supporting me until the very last day of finishing my studies and writing this thesis. I really could not have made it without your continuous support, encouragement and belief in me. iv TABLE OF CONTENTS LIST OF FIGURES ....................................................................................................................................... vi LIST OF TABLES ........................................................................................................................................ vii ACRONYMS ................................................................................................................................................. ix 1 . INTRODUCTION ..................................................................................................................... I 2. INCOME DIVERSIFICATION AND NON-F ARM EMPLOYMENT .................................... 4 3. CONCEPTUAL FRAMEWORK: DERIVING LABOR SUPPLY .......................................... 7 4. THE EMPIRICAL ANALYSIS ................................................................................................ 9 4.1 Data ........................................... - .. ........................................................................ 9 4.2 Definitions and descriptions of the dependent and independent variables .............................. 11 4.2.1 Dependent variables .............................................................................................................. 12 4.2.2 Independent variables ............................................................................................................ 13 4.3 Econometric Models and Estimation Methods ......................................................................... 15 4.3.1 Determinants of participation and intensity of participation by sector .................................. 16 4.3.2 Determinants of household income ....................................................................................... 19 5.1 Conditioning household characteristics and sources of income in Bolivia .............................. 22 5.1.1 Zone and household characteristics ....................................................................................... 22 5.1.2 Sources of income by region and income strata .................................................................... 23 5.2 Regression results .................................................................................................................... 27 5.2.1 Determinants of participation in nonagricultural activities ................................................... 27 5.2.2 Determinants of the level of participation in nonagricultural activities ................................ 32 5.2.3 Determinants of household incomes ..................................................................................... 35 6, CONCLUSIONS AND RECOMMENDATIONS .................................................................. 40 BIBLIOGRAPHY ......................................................................................................................................... 45 APPENDICES .............................................................................................................................................. 49 TABLES .................................................................................................................................................... 50 QUESTIONNAIRE ................................................................................................................................... 55 LIST OF FIGURES Figure 1. Structural diagram of the general categories of income sources ......... 7 vi Table 1. Table 2. Table 3. Table 4. Table 5. Table 6. Table 7. Table 8. Table 9. LIST OF TABLES Classification of farm and non-farm activities in the rural areas ......................... 4 List of dependent variables for nonagricultural labor supply models ............... 13 List of independent variables for nonagricultural labor supply models ........... 145 Mean characteristics of individuals and households in rural Bolivia, by macro ecoregion: Agricultural Year 2001-2002 ........................................................... 23 Sources of rural income of rural households in Bolivia: Agricultural Year 2001-2002 ................................................................................. 26 Share of income source by income quartiles, by sector: Agricultural Year 2001- 2002 .......................................................................................................... 27 Determinants of individual participation in non-farm activities Results estimated using survey probit: Agricultural Year 2001 -2002 ........................... 28 Determinants of individual participation in low-skilled and high-skilled activities in agricultural and nonagricultural wage employment Results estimated using survey probit: Agricultural Year 2001-2002 ......................... .29 Determinants of level of individual participation: Results estimated using a truncated regression on days per year worked. Agricultural Year 2001 2002 ........................................................................................ 34 Table 10.Determinants of level of individual participation. Results estimated using a truncated regression on days per year worked: Agricultural Year 2001- 2002 ........................................................................................ 35 Table 1 1.Determinants of annual household income: Results estimated using OLS and tobit regressions Agricultural Year 2001-2002 ...................................... 39 Table 12.T-tests of significance to compare means: for Table 4 in document .............. 50 vii Table 13. Table 14. Table 15. Table 16. Table 17. Table 18. Table 19. Table 20. Table 21. Table 22. Coefficients of Variation for Income Strata, for Table 6 in the document ..... 50 Average level of income of those who obtain income from non-farm_activities, by income quartile. In US. Dollars* ............................................................ 51 Average level of income of those who obtain income from non-farm_activities, by ecoregion, in US Dollars“ .......................................................................... 51 Wage activities by ecoregion (percent of 10,548 individuals) ....................... 52 Employment by ecoregion (percentage of 10,548 individuals) ...................... 52 Households participating in nonagricultural self employment by ecoregion (percent of 3,299 households) ......................................................................... 53 Sources of unearned income for the households who received unearned income. (Based on 1901 households from a sample of 3,300 in all three regions) ........................................................................................................... 53 Wage labor activities (percent of 3,338 wage laborers among 10,548 individuals) ..................................................................................................... 53 Nonagricultural self employment activities for the household classified into two categories: food processing, and manufacturing and services ................ 54 Location of wage employment by ecoregion (10,548 individuals) ................ 54 viii CIES Internacional MAPA NAE OLS PRSP RNFE UDAPE USAID ACRONYMS Centro de Investigacién Econérnico y Social Market Access and Poverty Alleviation Nonagricultural Employment Ordinary Lest Squares Poverty Reduction Strategy Paper Rural Non-Farm Employment Unidad de Analisis y Politicas Econémicas United States Agency for International Development ix 1. INTRODUCTION Perceptions of how income diversification affects the rural economy have dramatically changed in recent years (Escobal 2001; de Janvry and Sadoulet 2001). In Latin America many studies have found that the share of rural non-farm employment (RNFE) in rural areas is high and ranges from 40-50 percent of the total income (Berdegue, et al., 2001, Elbers and Lanjouw, 2001, Escobal, 2001, da Silva, 2001; Reardon 2001). These findings have promoted a wave of policy interventions among countries dealing with structural problems in rural poverty and unemployment. In countries in Latin America, RNFE has increased significantly. Berdegué et al. (2000) state that by the 19905, the percentage of total household income derived from nonagricultural employment (NAE) ranged from 38% in El Salvador and Honduras, to 42% in Nicaragua and even up to 68% in Haiti. Moreover, the income derived from these activities has also increased and continues to have a positive trend. In Bolivia, recent government policies and strategies have been designed with the objective of reducing poverty. One of those strategies is focused in the development of the rural and agricultural sector and the generation of nonagricultural opportunities in the nrral areas (Castro, 2005). This strategy is particularly important since it acknowledges the elevated degree of diversification in the rural areas, which was not traditionally regarded as important. The creation of micro and small enterprises is envisioned as a way to create non-farm employment opportunities for the poor in the rural areas (Gennrich, 2002; PRSP, 2001; Paz, 1997), although this approach may diminish the significance of temporary or permanent wage employment (Comision Europea, 2000). In either case, it is expected that the reactivation of a local economy generates activities which are expected to absorb the rural labor surplus and thereby slow down migration to the urban areas (Lanjouw and Lanjouw, 2001). Following similar research efforts in other countries of Latin America, several studies in Bolivia have observed a high share of total rural income coming from nonagricultural activities, although agricultural production is still the most important source of income (Ormachea, 2002, Jimenez and Lizarraga 2003, Comisién Europea, 2000). Ormachea (2002), states that the rural employment composition has undergone important changes, evidencing an increase in employment from non-farm sources. These changes are due to several factors which include: low contributions from peasant agriculture compared to more modern sectors; low productivity of the peasant agriculture; and changes in the organization of the market for agricultural goods which promote more capital intensive activities. In an analysis of structural changes in Bolivia, Urioste (1989) explains that the difficult situation in the rural areas has forced peasants to look for alternate sources of income. The major issues discussed that affect peasants are small landholdings, a lack of access to credit and low repayment capacity, and increasing costs of agricultural production. Of course these are only a few salient factors, among a myriad of issues influencing these trends in rural employment and rural incomes in Bolivia. Despite these important findings, neither of the studies mentioned above empirically tested the determinants of participation and income related to rural non-farm activities. The studies have relied on limited data on rural incomes and therefore, have failed to provide detailed information about the dynamic of the rural non-farm sector. This thesis uses a new data set to analyze the determinants of non-farm employment choices and incomes in selected regions of rural households in Bolivia, addressing three specific questions: i) What are the determinants of an individual’s participation in non-farm employment? ii) What is the level of labor allocated to the different non-farm activities? iii) What are the determinants of household’s rural non-farm incomes? The remainder of this thesis is organized in five parts. Chapter 2 discusses the rural non- farm sector and its components. Chapter 3 describes the conceptual framework which serves as the base for this study, analyzing how the labor supply is affected by the incentives and capacities of households. Chapter 4 presents the empirical analysis describing the data, econometric models, methods and variables used. Finally, Chapters 5 and 6 present the results, conclusions and recommendations. 2. INCOME DIVERSIFICATION AND NON-F ARM EMPLOYMENT Income diversification activities in the rural areas have come to be recognized as rural non-farm employment or RNFE in the literature. The rural non-farm sector, as explained by Lanjouw and Lanjouw (2001), is a set of economic activities carried out in the rural areas that are not agricultural. Table 1 below, illustrates the types of activities that fall under each of the four main categories of employment carried out in the rural areas. Table 1. Classification of farm and non-farm activities in the rural areas Sector Activity Agricultural wage employment Hired farm worker in crop and livestock farming Agricultural self employment Own farm activity Nonagricultural wage Wage employment in manufacturing and/or employment services; food processing. Nonagricultural self employment Own enterprise in manufacturing and/or services. As Barrett et al. (2001) illustrate, diversification of activities in the rural areas can be classified into several categories. The major categories presented in Figure 1 below are: sectoral, functional and spatial. Sectoral refers to the agricultural and nonagricultural sectors; functional refers to wage and self employment categories; and spatial refers to the locality of employment. Here it is important to define the spatial component of RNFE and to indicate where employment takes place. In this study, any activity carried out in the community where the household resides or in another neighboring community or town is considered local. Presumably, local would also be considered rural, however it is difficult to discern this from the data set since the rural-urban classification has not been specified. The non local category is defined as any activity carried out in another place where a person spends the night. This may be in another community, town, city or country. Figure 1. Structural diagram of the general categories of income sources Income Diversification l I 1 Agricultural Nonagricultural l I l l l l Wage Self Wage Self employed employed Local Non Local Non Local Non Local Non Local Local Local Local Source: Author’s typology adapted fi'om Barrett et al. (2001) One can go into further detail, distinguishing between different skill requirement levels in each of the sectors. For example, Elbers and Lanjouw (2001) make the distinction between two categories of wage employment: “high-productivity” or “low productivity” jobs. Similarly, Dirven (2004) classifies jobs as “low productivity” and “higher productivity”, emphasizing the different entry requirements into the labor market. Escobal (2001) disaggregates each of the two major categories of non-farm employment, self employment and wage employment into “high skilled” and “low skilled”. In this study, we will follow the distinction between jobs that are “high skilled” and those that are “low skilled” in order to differentiate the high/low capital requirements and also higher/lower returns of some activities. Low skilled activities are characterized by having low entry barriers and low rates of return, making access and exit from the market easy (Dirven, 2004). 3. CONCEPTUAL FRAMEWORK: DERIVING LABOR SUPPLY In order to explore the topic of non-farm employment, this study uses a utility maximization framework under the agricultural household approach (de J anvry and Sadoulet, 1995). The household approach is justified when both production and consumption decisions are interrelated (Caillavet, 1994), and when household characteristics play an important role in determining household behavior, as is the case in imperfect markets (Lofgren and Robinson, 1999). From the constrained utility maximization problem, de J anvry and Sadoulet (1995) derive a labor supply function of the form: (1) L3=fm k, 2) Where: LS = Labor supply p = Vector of input and output prices k = Vector of capital available to the household 2 = Vector of household characteristics Under the same behavioral model, Corral and Reardon (2001) explain the variables in the labor supply function in terms of a household’s incentives and capacities. The incentives are expressed as the “returns and risks” in the forms of prices of inputs and outputs, wages, and production risks in the model above. The capacities are expressed as the vectors of capital and household characteristics of a household which make it able to [I respond to the incentives. These assets are described as the level of education, amount of cattle owned, and amount of land owned for example (Corral and Reardon, 2001). Reardon (1998) explains that incentives either “pull” or “push” individuals into the labor market. The potentially higher returns to labor that could be obtained from working off the farm would “pull” or lure households into diversifying. Lanjouw and Lanjouw (2001) similarly explain that households which are “pulled” into non-farm activities participate as a means of obtaining more income and improving their current living conditions. By contrast, factors such as risk to the farm production, lack of access to credit, for example will tend to “push” households into nonagricultural activities. Households that are “pushed” into nonagricultural activities resort to diversification as a safety net. The capacities are assets, at individual and household level which are vectors of capital including human capital, physical capital, social capital and organizational capital. These capacities will place households in relatively better positions to respond to incentives. A household may have the incentive to participate in non-farm employment, say because of higher wage rates offered, but if the capacities are not in place (such as skills to qualify for the job), then even though the incentives are in place, the household will not be able to take advantage of them. 1"" 4. THE EMPIRICAL ANALYSIS The following section includes a description of the data, variables and econometric models used to test empirically which household characteristics determine nonagricultural labor supply and income. Section 4.] covers the data, specifically the type of survey carried out and the sampling technique used to gather information. Section 4.2 describes the dependent and independent variables, following the specification of the theoretical labor supply function. Finally, Section 4.3 describes the econometric models and specifications implemented to test first, the determinants of participation and intensity of participation, and second, the determinants of household income by source. 4.1 Data The baseline survey entitled “Characteristics of the rural households in the Altiplano, Valles and Yungas — Agricultural Year 2001-2002”, was designed and carried out in Bolivia during the months of June-July 2002, by CIES Intemacional, a consulting firm based in La Paz, Bolivia. This activity was financed by the United States Agency for International Development (U SAID) through the Fundacion Valles and the Market Access and Poverty Alleviation (MAPA) project. The survey was designed to collect information specifically on household income in selected rural areas of Bolivia. Data were collected in three macro ecoregions, the Altiplano, Valles and the region of the Yungas, located in the department of La Paz. The Altiplano is located in the highlands at 9,800- 13,000 feet over sea level and is characterized for being arid and having low agricultural productivity. The Valles by contrast is located between the mountain chains of the Andes which form fertile valleys. This region is located between 5,900 and 9,500 feet above sea level. The region of the Yungas is formed by steep valleys with subtropical vegetation, located at 1,900 — 2,300 feet above sea level. After stratification by region, the sample was also stratified between populated centers and dispersed areas], both located in the rural areas. In this survey, a rural area is defined as an area with 2,000 inhabitants or less. The survey excluded towns with more than 25,000 inhabitants. The survey sample includes 3,300 households (3,299 usable household observations, covering 10,548 individual observations) selected at random from 121 municipalities in six departments of Bolivia, which are: Chuquisaca, Cochabamba, La Paz, Potosi, Tarija and Santa Cruzz, all distributed between the two macro ecoregions mentioned above, Valles and Altiplano. Chuquisaca, Santa Cruz, Tarija and a part of Cochabamba are located in the Valles and, La Paz, Potosi and another part of Cochabamba are located in the Altiplano. Of the 121 municipalities surveyed, 76 are located in the Valles, 37 in the Altiplano and 8 in the Yungas zone. Of the 3,300 rural households surveyed, approximately 30% or 735 households are located in rural populated centers and 70% or 2,565 households are located in rural dispersed areas. The framework for the baseline survey takes into account information developed for the Population and Housing Census 2001, which in turn is based upon the Cartographic Update for the 2001 Census” (CIES Intemacional, 2002). According to the last national ' Populated centers are defined as a group of 50 or more households that make up organized blocks. Dispersed areas are any populated area where the households have no particular organization, and where the inhabitants are dedicated primarily to agricultural activities 2 Six of the nine departments were considered; Beni, Pando and Oruro were left out of the study since they did not form part of the scope of activities by the MAPA project. 10 census carried out in 2001, a rural area is defined as a geographic area with a population of 2,000 inhabitants or less. A three-stage sampling technique was used to select the households. The technique reported by CIES Intemacional follows: “The selection of the census sectors [first stage selection] as the sampling unit in the populated and dispersed centers was done based on a weighted probability. Its selection is justified due to the fact that the data base of the Cartographic Update constructed census sectors of standard size; consequently, the populated center holds approximately 120 households on average, and the dispersed area holds 280 households on average”. “The second sampling stage, the census segment, corresponds to a smaller geographic region than the census sector. This area contains 20 households in the populated center and 45 households, on average, in the dispersed areas. For purposes of the sampling design, two contiguous segments in the populated center were added together so that both sum up to 40 households, and maintain the 45 households in the dispersed areas. These areas had equal probability of selection like the selected census sectors in the first level”. “The last and third sampling stage is the inhabited household. Its probability of selection is weighted. A total of 15 households were chosen per census segment. The selection of the households was performed at random; that is to say, starting with the first household surveyed, every third household was surveyed after that. In order to obtain an equally distributed sample throughout the country, non statistical representation was given to the existing municipalities within the sampling framework. In total, the selection corresponds to 220 sampling units (clusters) distributed in a total of 121 municipalities, with one or two points per municipality” (CIES Intemacional, p.10). It is noteworthy that the population includes households with and without agricultural production since the objective of the survey was to collect data on incomes in rural households, independent of their activities. 4.2 Definitions and descriptions of the dependent and independent variables The dependent variables measure participation, intensity of participation and incomes for each non-farm activity choice. These activities are agricultural wage employment, nonagricultural wage employment, and nonagricultural self employment. The 11 independent variables show individual characteristics, household characteristics and location characteristics. Each empirical variable is linked to the categories of variables described in the conceptual labor supply model described in Chapter 3. Below are descriptions of the dependent and independent variables. Tables 2 and 3 below provide a list of the dependent and independent variables used in the study. 4.2.] Dependent variables The dependent variables on participation are defined as: nonagricultural self employment, agricultural wage employment, nonagricultural wage employment, and, low skilled wage employment and high skilled wage employment (Escobal 2001). All of these activities measure the probability of an individual participating in primary employment activities in the rural areas. These dichotomous dependent variables are firnctions of a vector of individual characteristics, a vector of household assets, and location characteristics. The next dependent variable, days worked per year, measures how much time an individual dedicates to non-farm activities, given their participation on the non-farm labor market. A “jomal” or day of work is a common measure of labor in the rural areas of Bolivia. The variable in this study aggregates (or disaggregates) the number of hours, days, weeks and months of work declared by an individual; eight hours of work per day make up a day’s work. The dependent variable on the determinants of household income is a function of household characteristics which seeks to establish which characteristics are more important in determining a household’s level of income from different sources. 12 Table 2. List of dependent variables for nonagricultural labor supply models Dependent variable description Value Participation in nonagricultural self employment 1=Yes, 0=No Participation in agricultural wage employment 1=Yes, 0=No Participation in nonagricultural wage employment 1=Yes, 0=No Participation in nonagricultural wage employment — 1=Yes, 0=No Low skilled jobs Participation in nonagricultural wage employment — 1=Yes, 0=No High skilled jobs Days per year worked in wage activities of those Number of days who participate Incomes derived from nonagricultural activities Income in Bs.* ‘Exchange rate for 1.00 USS was 6.83 Bolivianos (85.) by December 2001 4.2.2 Independent variables The study considers a set of explanatory variables that corresponds to the theoretical variables expressed in the labor supply equation stated in Chapter 3. Each variable is listed in Table 3 below and is described next. In order to analyze the determinants of an individual’s participation in non-farm activities, a set of variables at the individual level are first considered including age, level of education, gender, and whether the individual is the head of household or the spouse. The variable on educational level is modeled quadratically to show the marginal rate of return of having additional years of education and how it impacts participation, intensity of participation and level of income. Two additional variables on education were considered: whether an individual can read and write and the average years of education of adults in the household. After performing a Pearson’s correlation test, it was observed that these variables were highly correlated amongst each other and therefore, were dropped from the model. 13 The household asset variables are expressed as the vectors of capital in the theoretical model. These predetermined variables include: landholding, value of livestock and adult members in the household. Landholding is measured as the total area of land owned by an individual, in hectares. Livestock is measured as the value of total livestock owned at the end of the previous agricultural period (June 2001) before income was registered for the period of June 2001-June 2002. Lastly, the number of adults in the household takes into account all individuals in the household over the age of 12 years who are considered to be part of the economically active population. It is prudent to note the potential correlation between the independent variables and other unobserved variables (in the error term) as well as the potential ambiguous causal relationship or simultaneity between the independent variable and the dependent variables in the model (Wooldridge, 2002). Having livestock could be a determinant of participation, but it could also be a result of additional incomes fiom non-farm activities. Having more adult members in the household may increase participation and level of incomes; but it may also be a choice variable as households may choose to have more children or live with extended family members as a way to obtain higher incomes. Under the presence of endogeneity, the potential effects are biased and inconsistent coefficient estimates, but an effort was made to minimize this risk by looking for appropriate predetermined variables. Other explanatory variables include distance to nearest market which serves as a proxy for input and output prices, theoretical variable described in the labor supply function. This variable is useful to understand which types of activities have an effect on 14 participation and income derived from each activity. Lastly the location variables describe two major macro ecoregions of the country, Valles and Altiplano and the zone of the Yungas, located in the department of La Paz. These variables represent two distinct agro ecological regions, and a sub tropical zone, the Yungas. Reardon and Taylor (1996) state that in places where there is contrasting agroclimatic variability, there will also be significant differences in income composition. Likewise, a location variable identifying dispersed areas is included due to the expected effect on household access to labor and product markets. Table 3. List of independent variables for nonagricultural labor supply models Independent Definition Value Individual Female Individual gender (female=l) 1=Female,0=Male hh_head Individual is household head 1=Yes, 0=No hh-spouse Individual is spouse of household head 1=Yes, 0=No Age Individual age Years Education Number of years of education completed by each Years household member education2 Number of years of education completed by each Years squared household member squared Household hh_female Gender of head of household (Female=l) 1=Female,0=Male hh_age Age of head of household Years hh_leved Completed level of education of household head Years hh_leved2 Completed level of education of household head Years squared adults in hh Adult workers in household over age 12 Number landholding Landholdings per household Hectares Livestock Value of livestock per household as of June 2001 In Bs.’ distance_hr Distance from household to nearest fair/market Hours Location Valles Valles macro eco-region 1=Yes, 0= No Altiplano Altiplano macro eco— region 1=Yes, 0= No Dispersed area Populated center or dispersed area l=dis, O=pop "Exchange rate for 1.00 USS was 6.83 Bolivianos (85.) by December 2001 4.3 Econometric Models and Estimation Methods In order to address the three research questions stated in Chapter 1, three different econometric models are used to analyze the determinants of participation in 15 nonagricultural employment, intensity of participation and resulting income. First the econometric models will be discussed. In a following section, the dependent and independent variables used to implement these models will be explained. 4.3.1 Determinants of participation and intensity of participation by sector The double-hurdle model was chosen for the initial analysis because it allows for the distinction between the determinants of participation and the level of participation in non- farm activities through two separate stages. This model was developed by Cragg (1971) and has been applied by Matshe and Young (2004) who model household labor allocation decisions in Zimbabwe and also by Serumaga-Zake and Naudé (2003) who apply the model to the rate of return of education in South Africa through the decision of participation and employment. In their study, Matshe and Young (2004) state that by separating the model into two stages, it is possible to establish that the two decisions are sequential. The first stage of this model examines participation in three main categories of employment: nonagricultural wage employment, agricultural wage employment and nonagricultural self employment. Two additional equations evaluate participation in high and low skilled wage employment. The distinction made between the latter two is based on “whether earnings respectively fall below, or exceed, the average earnings of someone with agricultural wage labor as a primary activity” (Elbers and Lanjow, 2001). The analysis of the decision to participate is estimated by means of the following probit regression: 16 (2) P()'=1|JC) =fio+fiiXi + u Where: P is the probability of participation by an individual in a non-farm activity; ,6,- is the vector of parameters, X, is the vector of exogenous explanatory variables and u is the error term. In order to estimate this model, the survey probit procedure under survey data analysis in the statistical package STATA 8 was used. The “census segment” was defined as the primary sampling unit (PSU). Accounting for PSU effects allows controlling for unobserved variables within clusters that share similar if not identical characteristics (Deaton, 1997). The sample stratification for the ecoregions made some of them to be over represented and others under represented, which is not consistent with the random sampling condition necessary to produce unbiased estimates (Wooldridge, 2002). Therefore, in order to compensate for the inequitable distribution of the sample size between the macro ecoregions, these were weighted. The weights were calculated by dividing the proportion of population of the survey by the proportion of the sample size for each region. This adjustment factor was included as part of the regressions in the survey procedure to avoid over representation of larger regions over smaller ones. The second stage of the model determines the level of participation, conditional on participation, and is implemented using a truncated regression. This regression examines l7 the determinants of how many days per year an individual allocated to non-farm activities. This stage involves a truncated regression that can be specified as: (3) L=L‘ ifL‘>0 and P‘ >0 L = 0 otherwise 14230 + flt/Yi'I' u Where: L* is the observed level of participation, ,8,- is the vector of parameters, and X.- is the set of exogenous explanatory variables. Five equations are estimated for determinants of nonagricultural self employment, agricultural wage employment, nonagricultural wage employment and for high and low skilled employment as well. The analysis uses a truncated regression with survey weights, and robust standard errors. 4.3.1.1 Hypotheses on employment determinants Based on the conceptual framework and the research questions, the model specified above is used to test the following hypotheses: 0 Residence in populated centers, where individuals have greater access to infrastructural capital assets, will have a positive and significant effect on participation in nonagricultural activities, especially nonagricultural wage employment, high skilled employment and nonagricultural self employment. 0 Individuals who come from wealthier households participate in nonagricultural activities more than those who do not. 18 4.3.2 Determinants of household income A set of models are specified for the analysis of the determinants of household income derived from activities in the following categories: agriculture, nonagricultural self employment, agricultural wages, nonagricultural wages and total income. The equations analyzing the determinants of total income, nonagricultural self enterprise and agricultural income are estimated following a standard ordinary least squares (OLS) model using a linear regression for survey data. As with the probit models under this procedure, PSU clusters and survey weights were incorporated. The equations estimating agricultural and nonagricultural wage incomes were regressed using tobit, a censored regression model. Because these two dependent variables have many observations at zero, estimating them using an OLS would yield biased and inconsistent results (Pindyck and Rubinfeld, 1991). Due to Tobin (1958), the tobit model allows for the analysis of censored data, originally applied to variables censored so that they could not fall below zero. In this study the presence of zeroes in the dependent variables of income derived from wage, are due to non participation in wage activities, not from zero income obtained from wage employment. Therefore, by using a tobit model, the zero observations are accounted for and the censored regression provides a more accurate estimation (Wooldridge, 2002). However, the presence of heteroskedasticity may cause inconsistent coefficient estimates by the standard tobit estimator (Wooldridge, 2002). In light of this potential problem, Kennedy (2003) suggests the use of robust estimators such as Powell’s censored least 19 absolute deviations (CLAD) to control for heteroskedasticity. This estimator was tested but for the purpose and scope of this study, the tobit proved to be an appropriate model. The OLS specification models for total income, nonagricultural self enterprise and agricultural income follows: :(4) Y: =flo +fl,-X,- + u Where: Y; is the dependent variable representing income earned from each of the non- farm activities, explained by ,Bi which represent a vector of parameters and X,- is a vector of exogenous explanatory variables (Pindyck and Rubinfeld, 1991). The two tobit equations take the following specification: (5) Y.‘ =flo +M— + u Y; = Y: iin. >0 Y; = 0 otherwise WherezYi' is the unobserved latent variable, Yi is the actual observed outcome, ,8,- is a vector of unknown parameters and Xi is a vector of exogenous explanatory variables (Wooldridge, 2002). 4.3.2.1 Hypothesis on income determinants Based on the conceptual framework and the research questions, the empirical models of income seek to test the following hypothesis: 20 o More capacities existing in the household in the form of physical assets and level of education will cause an increased likelihood of a household’s participation in non- farm activities and thereby, level of income obtained. 21 5. RESULTS The following section first describes the zones and households, in order to place the results in context. Next, the regression results are analyzed and discussed. 5.1 Conditioning household characteristics and sources of income in Bolivia 5.1.1 Zone and household characteristics The Valles, Altiplano and Yungas have unique geographical characteristics which also make their economies distinct. The Valles are characterized by warm tempered climate with very fertile soils. They are large producers of vegetables, cereals, legumes, and tree fruits. The Valles also have dairy cattle for milk production. By contrast, the Altiplano is characterized by high plateaus, and an arid climate, unfavorable for extensive agricultural production. Because of the characteristics of the Altiplano, and a considerable rural exodus, the population density is low (Enciclopedia de Bolivia, p.249). The main agricultural enterprises in this region are wheat, barley, and potatoes, and dairy cattle. In the subtropical zone of the Yungas, the warm and humid weather and fertile lands make it very apt for the production of coffee, sugar, tree fruit, bananas, and coca. Table 4 below summarizes survey results for the three regions. Households and landholdings are relatively small, averaging 0.91 hectares per household in the Valles, 1.08 hectares in the Altiplano and 1.77 hectares in the Yungas. Access to markets is difficult; data from the National Institute of Statistics affirm that 64% of the roads in Bolivia are mostly dirt roads. 22 Table 4. Mean characteristics of individuals and households in rural Bolivia, by macro ecoregion: Agricultural Year 2001-2002 Variables Macro eco-rmon Total Valles Altiplano Yungas_ Number of individuals (observations) 10548 6703 2698 1147 Number of households 3299 2010 915 374 Individual characteristics Individual gender (% male) 50.0 50.5 47.9 53.4 Individual age (years) 34.3 34.0 35.5 33.1 Individual can read and write (% Yes) 80.7 79.4 80.0 90.7 Years of education completed (number) 5.0 5.0 4.8 5.9 Household characteristics Gender of household head (% Female) 1 1.0 10.9 1 1.7 12.3 Age of household head (years) 47.5 47.7 47.6 45.8 Level of education of household head (years) 6.5 6.4 6.3 7.2 Number of adults in household (over age 12) 4.0 4.1 3.6 3.8 Access to electricity (%) 43.0 47.7 24.2 55.7 Access to potable water (%) 64.0 67.9 47.7 79.5 Distance from household to market (km.) 19.3 18.4 23.0 16.3 Total value of livestock per household (in ES.) 4751.2 5604.9 4169.3 1131.3 Household land size (in hectares) 1.5 .91 1.08 1.77 Dispersed area-(%) 78.0 76.7 84.7 70.9 Regarding household assets, the Altiplano seems to be the most disadvantaged region, with access to electricity and potable water at 24% and 48% respectively, is lower than the other two regions. The average years of education per person ranged from 4.8 in the Altiplano to 5.9 in the Yungas. Literacy is also highest in the Yungas at 90%. 5.1.2 Sources of income by region and income strata In the following section, five sources of household income are analyzed. These follow the income source classification discussed in Chapter 3, with the addition of unearned income. Although this source of income is not included in the models, since the relevance of the study lies on the earned sources of income, it is useful to recognize the contribution of pensions, remittances and rents to the household income. These sources 23 of unearned income are only included so as to provide a more complete picture of the income composition of rural households. Agricultural income is defined as including all income from crop and livestock production minus expenses, home consumption and production losses. Income earned through nonagricultural self employment activities includes agricultural processing and entrepreneurial activity in the areas of services and manufacturing. Agricultural wage income and nonagricultural wage income are gross incomes derived from those pursuits. Table 5 below shows income shares by source of income, per region. Approximately 42% of total income is derived from agricultural production and 11% from agricultural wages. All other earned income from non-farm activities sums up to 46% of total income. This study shows that approximately 49% of the working population is involved in nonagricultural activities. The most important categories of non-farm work are: construction, artisan work, commerce and services. Also, an important share of the working population is unskilled workers or laborers, especially in the Valles and Altiplano (see Table 16 in Appendix). Agricultural production income alone represents nearly half of all income in the Altiplano and the Yungas. However, in the Yungas, approximately 75% of the population participates in agricultural wage activities as agricultural peons. This figure contrasts with the share in the Altiplano (33%) which may be explained by the types of agricultural production particular to each region. The Altiplano is more oriented towards subsistence 24 agriculture, whereas the Yungas region has more intensive and commercial agriculture demanding more labor force. Interestingly, Table 5 shows that the Valles has a more balanced distribution of income shares than the other regions, however, the Altiplano seems to have a more diverse and balanced participation in the different activities in non- farm employment. This can be explained by the fact that households in the Altiplano will diversify more because of the higher risk involved in agricultural production in that ecoregion. Most of the activities that households in the Altiplano are involved in are in construction and artisanal work. In the Valles, by contrast, few participate in artisanal work; instead, the shares are highest in construction work and unskilled wage labor. Also important is nonagricultural wage employment, particularly in the Valles and Altiplano (22 and 21% respectively). In the Yungas, the share of nonagricultural wage employment reaches 9%, however, employment in this category is better remunerated than in the Altiplano. Also in the Yungas, the share of nonagricultural self employment is the highest and, the level of income, on average, of those who engage in this activity will be three times higher than the Valles and five times higher than the Altiplano (see Table 14 in Appendix). Possibly, these substantial differences may be explained by the fact that the Yungas has a more diverse agricultural production which is mostly destined towards commercial markets. In the Altiplano, agricultural wages represent only 5% of total income. The Yungas also has the highest share of self enterprise activities among the regions, whereas the Valles have the highest share of income from nonagricultural wage activities. 25 Table 5. Sources of rural income of rural households in Bolivia: Agricultural Year 2001-2002 Source of income Rggion Valles AltiLlano Yungas Total Agricultural Production Income 37% 48% 49% 42% Agricultural Wage Income 13% 5% 15% 1 1% Nonagricultural Wage Income 22% 21% 9% 20% Nonagricultural Self Employment 16% 12% 20% 15% Uneamed Income 12% 13% 6% 12% Total Income 100% 100% 100% 100% Table 6 below illustrates how income is distributed by income quartiles. For the highest quartile, 32% of income comes from nonagricultural wage employment. Not only is this share the highest, but also the level of income obtained, on average, from nonagricultural wage activities for the highest income quartile is nearly three times as much as the third quartile and 14 times greater than the lowest quartile. From Table 2 in the Appendix, one can observe that the highest and lowest income quartiles show larger variability compared to the 2nd and 3rd income quartiles. The income shares of the highest quartile are relatively well balanced across activities, demonstrating the capacity of the wealthier households to diversify. On the other hand, the share of income for the lowest quartile is heavily dependent upon agriculture which accounts for 55% of earnings followed by 15% of unearned sources, 13% from nonagricultural self employment and 8% from nonagricultural wage income. The income obtained from nonagricultural wage employment, steadily increases with higher income quartiles. By contrast, while agriculture represents a larger share of income, it is not the 26 highest provider of income for those who participate in this sector. Households in the lowest income quartile appear to diversify as much as households in the other quartiles, but likely do so as a result of being pushed into participation. The second and third income quartiles are more balanced among activities than the poorest, but they show a similar tendency toward reliance upon agriculture as the main source of income. Table 6. Share of income source by income quartiles, by sector: Agricultural Year 2001- 2002 Source of income Quartiles Low 2nd 3rd High # of households 3,329 Agricultural Income 55% 48% 38% 25% Agricultural Wage Income 9% 13% 14% 9% Nonagricultural Wage Income 8% 16% 25% 32% Nonagricultural Self Employment 13% l 1% 14% 23% Uneamed Income 1 5% 12% 9% 10% Total Income 100% 100% 100% 100% 5.2 Regression results 5.2.1 Determinants of participation in nonagricultural activities Tables 7 and 8 present the first stage of the double-hurdle estimation, namely, the probit model using a survey probit procedure with survey sampling weights and using census segments as primary sampling units (PSU) to control for fixed effects. The STATA 8.1 econometric software was used to estimate this model. Separate regressions were performed for nonagricultural self employment, agricultural wage employment and nonagricultural wage employment. Two additional equations were estimated for low- 27 skilled jobs and high-skilled jobs in wage employment. Regression results show the marginal effects on participation given a one unit change, or a discrete change, in the explanatory variables. Based on the results presented in Table 7, the role of individual and household factors will be discussed and how each influences the decision to take part in non-farm activities. Table 7. Determinants of individual participation in non-farm activities; results estimated using survey probit: Agricultural Year 2001-2002 Dependent variables: Nonagricultural self Nonagricultural wage Agricultural wage employment employment employment Marginal Marginal Marginal Variables Effect P-value effect P-value effect P-value Individual characteristics Female 0.02 1 (0.06) -0.052 (0-00) -0. 132 (0.00) hh_head -0.026 (0.07) 0.122 (0.00) 0.085 (0.00) hh_spouse -0.01 1 (0.40) 0.034 (0.03) 0.038 (0.01) Age 0.002 (0.00) -0.002 (0.00) -0.002 (0.00) education 0.020 (0.00) -0.005 (0.1 1) 0.000 (0.92) education2 -0.001 (0.10) 0.001 (0.00) -0.001 (0-00) Household characteristics hh_female -0.030 (0.27) 0.052 (0.00) 0.058 (0-00) hh_hage -0.001 (0.34) -0.002 (0.00) -0.001 (0.03) adults in hh 0.011 (0.06) 0.012 (0-00) 0.003 (0.26) tota1_land 0.000 (0.40) 0.000 (0.3 1) 0.000 (0.70) livestock 0.000 (0.83) 0.000 (0. 10) 0.000 (0.32) distance -0.009 (0.02) -0.001 (0.54) -0.001 (0.43) Location characteristics Valles 0.080 (0.02) 0. 124 «mm -0.077 (0.00) Atiplano 0.034 (0.43) 0. 169 (0-00) -0. 140 (0.00) dispersed areas -0.322 (0.00) -0.057 (0-00) 0.052 (0.00) Number of observations 10548 10548 10548 Number of PSUs 220 220 220 F( 15, 205) 14.82 45.58 27.07 Prob > F 0.000 0.000 0.000 28 Table 8. Determinants of individual participation in low-skilled and high-skilled activities in agricultural and nonagricultural wage employment; results estimated using survey probit: Agricultural Year 2001-2002 Dependent variables: Low- skilled wage High-skilled wage employment employment Marginal Marginal Variables effect P-value Effect P-value Individual characteristics female 0.012 (0.20) -0.222 (0.00) hh_head 0.072 (0.00) ' 0.130 (0.00) hh_spouse -0.014 (0.21) 0.127 (0.00) age -0.002 (0.00) -0.001 (0.02) Education -0.005 (0.16) -0.01 1 (0.00) education2 0.000 (0.81) 0.001 (0.00) Household characteristics hh_female 0.057 (0.00) 0.055 (0.00) hh_age 0.000 (0.6 1) -0.003 (0.00) adults in hh 0.007 (0.02) 0.009 (0.00) total_1and 0.000 (0.29) 0.000 (0.74) livestock 0.000 (0.34) 0.000 (0.42) distance 0.000 (0.74) -0.002 (0.04) Location characteristics Valles -0.041 (0.06) 0.061 (0.00) Altiplano -0.045 (0.03) -0.007 (0.72) dispersed area -0.014 (0.36) 0.001 (0.92) Number of observations 10548 10548 Number of PSUs ‘" 220 220 F(15, 205) 11.95 54.85 Prob > F 0.000 0.000 (1) PSU is census segment Among individual characteristics, the results suggest that females are more likely to participate in nonagricultural self employment. Agricultural wage employment, nonagricultural wage employment, and high-skilled jobs seem to be more accessible to men. This may be a reflection of the fact that 60% of women in fertile age have children and are dedicating themselves to domestic activities. Similar outcomes were found by Matshe and Young (2004) in Zimbabwe. Carafa (1993) highlights the participation of women in the rural areas in several activities ranging from domestic to agricultural 29 production and commercialization, recognizing the multiple roles that women play in regards to household welfare and economy. This, as Glick and Sahn (1997) acknowledge, may have a strong influence on the types of activities women will become involved in. Additional years of education increase the likelihood of participation in nonagricultural wage employment and high skilled employment. A large portion of the wage jobs are not local and appear to be acquired through temporary migration (see Table 22 in Appendix). It makes sense that individuals with more capital, financial and physical assets will have an increased possibility of migrating and working outside their community, especially if they reside in a populated center, with easier access to urban locations. The quadratic variable on level of education shows the marginal rate of return of education on the dependent variables. With the quadratic model it was possible to determine that the education has a U-shaped effect in nonagricultural wage employment and high skilled employment. This means that those with few years of education are less likely to participate in nonagricultural wage employment and highly skilled jobs. But, as the number of completed years of education increases, then education has a positive effect on participation in both activities. The minimum number of years of education completed before an individual begins to increase their likelihood of participation is four for nonagricultural wage employment, and five for highly skilled wage employment. Lizarraga (2001) explains that in the rural areas of Bolivia, most youths attend primary school, but few continue to secondary school. This is in part due to a lack of access to a 30 schooling system, but also because of the opportunity cost of obtaining an education versus the necessity of employment. An interesting result in the regressions is the positive and significant effect of education on participation in nonagricultural self employment. This is worth mentioning since studies in non-farm employment, in particular studies in Nicaragua, Guinea and Mali (Corral and Reardon, 2001; Glick and Sahn, 1997; and Abdulai and CroleRees, 2000) found the relationship between education and non-farm self employment to be unimportant or not significant. In this case however, education is important for increasing the likelihood of participation, but additional years of education will not contribute to the likelihood of participation in nonagricultural self employment. Households headed by women increase an individual’s likelihood of participation in agricultural and nonagricultural wage employment increases, as well as low and high skilled wage employment. Furthermore, for every additional member in the household, 12 years or older, participation in all forms of employment significantly increases. This is expected and logical since the household, especially if it is run by a female will rely on the members of the family to generate additional income. Being from a dispersed rural area as opposed to being from a populated center decreases the likelihood of participation in almost all forms of non-farm activities. As Barrett et a1. (2001) explain, “being in remote areas is costly and causes factor and product market failures”. By contrast, residing in a town or “populated center” makes the options of 31 participation in wage and self employment more accessible, generating more income opportunities for individuals (Elbers and Lanjouw, 2001, Barrett et al. 2001). Likewise, residing in a more favorable climatic and geographic environment, as is the region of the Valles, gives rise to more opportunities to diversify and participate in nonagricultural self employment, nonagricultural wage employment and high skilled employment. Reardon and Taylor (1996) found that in environments that are so favorable, the incentives are in place to diversify locally, whereas in places like the Altiplano, where the agroclimatic conditions are difficult, individuals are “pushed” into diversification in another zone or perhaps within a zone if the income source is not agriculture. 5.2.2 Determinants of the level of participation in nonagricultural activities The results of the probit estimation discussed in the previous section allowed us to understand which characteristics play an important role in determining the probability of participation in different kinds of employment. In this section, the analysis will focus on the second stage of the model which examines the time dedicated to employment, given participation. The results are presented in tables 9 and 10. Before proceeding to the analysis, it is necessary to mention that the result of the Wald statistic in the model for agricultural wage employment was not significant. Some of the coefficients in the model are significant but no interpretation can be made of those, since it may be only by coincidence that they explain, or not, the model for agricultural wage. Nonetheless, given the characteristics of agricultural wage labor and its seasonality, the intensity of participation is likely to be based more on a demand and supply basis rather than on Whether individuals possess certain skills or assets. 32 As was expected from the hypothesis on intensity of participation, the results and findings in this section regarding education are positive. The intensity of participation in nonagricultural wage employment and high skilled employment increases with higher education levels. On household size, an additional adult member in the household will contribute to an increased level of participation in agricultural wage activities and nonagricultural self employment. In Bolivia, for cultural reasons, the family ties are such that the younger members of the family provide for and take care of the elderly, and therefore, the elder members of the family probably do not participate intensively in nonagricultural activities, plus having additional members in the family is viewed as a potential of more opportunities for the generation of income. It is interesting to note that those individuals who reside in the Valles and Altiplano will participate significantly more in nonagricultural wage activities than those living in the Yungas, yet they have very opposite geographic and climatic conditions. This leads to assume that perhaps individuals in the Valles are pulled into nonagricultural wage employment, whereas individuals in the Altiplano are pushed into diversification. Conversely, individuals residing in the Yungas will participate more in agricultural wage activities than those who reside in the Valles, and at an even larger scale to those residing in the Altiplano. In the case of the Yungas and Valles, these results are consistent with the theory that Reardon and Taylor (1996) pose, that the favorable conditions of a region will tend to create more opportunities for diversification, especially in activities that 33 provide higher returns. Also from the results, it can be concluded that residing in a dispersed rural area definitely decreases the amount of days per year worked in all nonagricultural activities. By contrast, the shorter the distance from the household to a nearest market has a positive effect on the intensity of participation in all three forms of employment. This may be so because the transaction costs are lower for households who have relatively easier access to markets. Table 9. Determinants of level of individual participation: Results estimated using a truncated regression on days per year worked. Agricultural Year 2001-2002 Dependent variable: Days per year worked in: Nonagricultural self Nonagricultural wage Agricultural wage employment employment employment Marginal Marginal Marginal Variables Effect P-value effect P-value effect P-value Individual characteristics Female -10.346 (0.26) 6.029 , (0.36) -11.662 (0.04) hh_head 20.980 (0.27) 21.641 (0.07) 6.932 (0.47) hh_spouse -1 . 106 (0.96) -0.240 (0.99) -7.777 (0.50) Age -0.134 (0.83) 0.343 (0.3 8) -0.089 (0.78) Education 1 .282 (0.69) 7.505 (0.00) -2. l 84 (0.16) education2 0.210 (0.20) -0.148 (0.20) 0.182 (0.12) Household characteristics hh_gender 16.300 (0.18) 11.618 (0.14) 2.226 (0.70) hh_age -0.228 (0.66) -0.212 (0.52) -0.530 (0.06) Adults in hh 6.460 (0.01) 1.977 (0.20) 2.618 (0.02) total_1and -0.381 (0.00) -0. 195 (0. 12) 0.025 (0.00) livestock -0.008 (0.07) -0.002 (0.33) 0.000 (1.00) Distance 1.147 (0.33) -1.192 (0.04) 0.354 (0.38) Location characteristics Valles 14. 183 (0.26) 43.679 (0.00) -12.269 (0.00) Altiplano -9.238 (0.54) 23 .454 (0.10) -55.279 (0-00) Dispersed area -27.800 (0.00) -35.699 (0.00) -l6.823 (0-00) Number of observations 763 161 1 1750 Wald x2 (15) 116.68 329.89 13.67 _Prob > x2 0.000 0.000 0.550 34 Table 10. Determinants of level of individual participation. Results estimated using a truncated regression on days per year worked: Agricultural Year 2001-2002 Dependent variables: Low- skilled wage High-skilled wage employment employment Marginal Marginal Variables Effect P-value effect P-value Individual characteristics Female 7.729 (0.12) 1.215 (0.87) Hh_head 7.849 (0.44) 1 8.679 (0. 10) Hh_spouse -10.291 (0.35) -0.220 (0.99) Age 0.072 (0.83) 0.035 (0.92) education 0.759 (0.69) 6.484 (0.00) education2 0.108 (0.34) -0.065 (0.51) Household characteristics Hh_gender 13.793 (0.02) -7.574 (0.34) Hh_age -0.3 83 (0.14) -0.348 (0.29) adults in hh 2.841 (0.06) 3.100 (0.01) total_1and -0.108 (0.26) 0.024 (0.05) Livestock 0.000 (0.99) -0.001 (0.43) Distance 0.4 80 (0.46) -0.646 (0. 17) Location characteristics Valles 1 1.480 (0.10) 9.979 (0.22) Altiplano -6.598 (0.44) -3.704 (0.69) Dispersed area -33.200 (0.00) -35.517 (0.00) Number of observations 1395 1966 Wald x2 (15) 36.07 358.28 Prob > x2 0.001 0.000 5.2.3 Determinants of household incomes In this section, the focus of the analysis will be the household. This analysis is done primarily to understand which characteristics are important in determining whether a household will obtain income from one sector versus another. Five equations are estimated, these are: total income, agricultural income, self employment, agricultural wage income and nonagricultural wage income. Total income is defined as all earned income obtained from all four income sources. Agricultural 35 income is net income and it is the sum of crop and livestock net incomes. Self employment is also net income and it includes entrepreneurial activities in the agricultural processing sub sector, service provision and manufacturing. Agricultural wage income and nonagricultural wage income, which are incomes derived from remunerated activities, are all gross incomes. These dependent variables have censored data since many households do not participate in nonagricultural employment and therefore, did not obtain income derived from these activities. As described previously, the results are estimated using OLS for total income, agricultural income and nonagricultural self employment, since all income is observed. The incomes derived from wage activities are estimated irsing a tobit model. Estimation results for all equations are reported in Table 11. The importance of education is highlighted once again in this model, however, the results vary depending on the activity. For income earned from agricultural production activities, education has a positive effect, but then declines with additional years of education. Similarly for activities related to self employment (mostly services and manufacturing) having a basic level of education is an advantage, but additional years of education do not contribute to higher incomes. It is likely that basic literacy is important for carrying out activities that range from production to services and manufacturing. These findings are consistent with the literature, where it is found that higher levels of education will not contribute to increased earnings from agricultural wage employment (Escobal, 2001). On the other hand, for incomes obtained from wage activities, education 36 does play a more important role, especially for those activities in the nonagricultural wage sector. These activities are in construction, office employment, artisans, and technicians among others where additional years of education or specialized training may be required or is highly valued. For all of the sources of income, having additional adult members in the household is a highly significant determinant for obtaining higher incomes, especially for nonagricultural wage employment. This implies that having a larger household, thereby having a greater labor force gives the household the flexibility to distribute work between the own farm, agricultural activities and also nonagricultural employment, and therefore have a higher capacity of diversification. The distance variable measured by hours of distance to a nearest market shows that as distance increases, incomes from self employment activities decrease. This result is as expected and suggests that in less accessible rural areas, probably with a low population concentration, it is difficult to establish rural enterprises because of the lack of derived demand and the fact that productive linkages cannot be established. In terms of location, being from a dispersed area, as Opposed to being from a more accessible populated center, significantly reduces total income, self employment income, and nonagricultural wage incomes. Both of these variables, distance to market and whether an individual lives in a populated center or dispersed rural area, reinforce the fact that in areas where there is more access to markets and where linkages are created, self enterprise initiatives and wage activities in the nonagricultural sector seem to flourish. Households located in 37 dispersed rural towns have positive incomes derived from agricultural wage activities, which is expected since those areas are more dedicated to agricultural production and have a higher demand for agricultural wage labor as peons, and likely to be non skilled labor. The results show that households in the Altiplano and Valles regions, as compared to the Yungas, have significantly higher incomes obtained from nonagricultural wage activities. Also, the level of income obtained from agricultural wage activities is significantly lower than that obtained in the Yungas. 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Sets. 58 MES-m 9:8 8321 A28 83.8. 888 $32:- 58 Ensem- eaeelfi _a>rm “8058mm _m>-.n— Logo—5.2mm _a>rm 33:83A— _M>nm BEEN-am _w>rm BEEN-3m wotflLmEULS‘u ENQEu-aom Bee .55 So So So 0802.: 0:505 0:505 05005 836.2an own? _~._B_=otwa:oz owe? .83_:otw< “5:32an tom Bugger—ma, 2:85 .80... 263$me agar—3N 23> _a._5_=o_._w< 333-0qu ~33 can mac new»... 3:358 $.33— SEeaow-ae: aaflm .8.“ 083.: 22.92::— _a===a he 85383qu .2 «Ea-H 39 6. CONCLUSIONS AND RECOMMENDATIONS This study contributes to understanding the rural economy in three different regions of Bolivia by addressing three research questions: i) What are the determinants of an individual’s participation in non-farm employment? ii) What is the level of labor allocated to the different non-farm activities? iii) What are the determinants of household’s rural non-farm incomes? The findings highlight the importance of several factors. An individual’s gender will have a significant influence on whether participation in non-farm activities occurs. Women’s participation in non-farm employment is definitely limited, regardless of the region. These findings coincide with studies in other countries like Nicaragua (Corral and Reardon, 2001) who find that women mostly participate in self employment activities. As was mentioned previously, Carafa (1993) and Glick and Sahn (1997) recognize that this may be due to women’s many roles in the household. In terms of policy interventions, focus should be on analyzing the reasons for this tendency in the case of Bolivia and whether women in the rural areas do not participate in non-farm activities because of limitations or by choice, or a combination of both. In any case, programs encouraging education or training at some level for women are critical in order to provide women with the tools required to enter other labor markets. On this note, the importance of education is also highlighted from the findings. While it is undeniable that more education contributes positively to an individual’s capacities, it was determined that each activity has different education level requirements. 40 Participation in nonagricultural self employment requires some level of education but tends to decline after a certain level of education is attained. Similar results can be observed for agricultural production, where there is a significant negative effect on income beyond three years of education. More education on the other hand, proved to be a determinant for participation in high skilled wage employment. Also, education is a determinant for obtaining higher incomes, especially in nonagricultural wage activities. These findings are similar to those described by Taylor and Yunez-Naude (2000) in Mexico where education was found to increase the likelihood of participation in wage work. The opposite occurs for agricultural production and self employment activities where additional years of education will probably not contribute to higher earnings for a household. This thesis shows that education clearly contributes to higher earnings from nonagricultural wage income, although not so for agricultural wage income. Similarly, Yuflez-Naude and Taylor (2001) find that basic education has positive returns for income derived from maize production in rural Mexico and wage activities, although they do not disaggregate between agricultural wage employment and nonagricultural wage employment. But like this study, they conclude that education plays a very important role in the activity a household will be involved in. This study finds that a significant share of total income in the three regions of Bolivia is derived from agriculture, but it also proves that incomes derived from nonagricultural activities are very important components of total household income. Of these activities, 41 the one that has the highest share of total income is nonagricultural wage employment, followed by nonagricultural self employment. From a policy perspective, it is important to take into account the high level and share of nonagricultural wage employment of total income in rural areas by region. An example of how to strengthen this sector would be by strengthening the already existing but neglected network of rural training centers, which currently do not match training programs with the actual demand. But it is also necessary to look at the importance of agricultural production, which is socially and economically important for rural households in Bolivia. Greater economic development impacts could be achieved by identifying strategic agricultural crops which have the potential to generate a derived demand of manufacturing and services, thereby creating upstream and downstream productive linkages. Regarding the significance of non-farm activities, the policies designed to reactivate the rural economy and promote the generation of sources of non-farm employment and income should incorporate self enterprise initiatives but also, acknowledge the importance of wage employment and the close link that exists between the two sectors. The design of intervention strategies that focus on skills obtained through training for example will allow for a greater participation and level of income derived from these two activities. Likewise, interventions by the public or private sectors should acknowledge the heterogeneity of labor and income distribution in the three ecoregions. In the region of the Valles, for example, nonagricultural wage employment along with agricultural wage employment are important contributors to the household income. This region is diverse in terms of sources of income and the creation of small and medium enterprises could be 42 appropriate in order to promote and consolidate productive chains. Households in the Altiplano are also engaged in nonagricultural self employment, but given the harsh agroclimatic conditions which limit agricultural production, households have to look to other activities to control for the risk in order to guarantee a certain level of income. The focus in this region could be directed at providing training for individuals to obtain skills so they can access nonagricultural skilled jobs since agriculture is not a feasible alternative for many. Finally, the region of the Yungas shows the highest share of income obtained from agricultural wage employment and also agricultural and nonagricultural self employment. In this region households have alternatives to agricultural production and therefore have more opportunities to diversify. Interventions in this region supporting the creation of small enterprises and cooperatives or other forms of organization based on the agricultural potential of this region are appropriate, especially if they are aimed at creating linkages that will help create a sustainable local economic dynamic. For future research it would be valuable to follow up the baseline survey used for this study in order to compare changes between periods (agricultural year 2001-2002 to future years) and to see the patterns of rural employment and incomes in the three regions over time. Also, it would also be interesting to analyze non-farm activities in the context of the governmental policies to decentralize municipalities and what the impacts have been. These policies gave rise to the development of local economies by giving accountability to the municipalities. Studying the impacts of nonagricultural employment and incomes 43 in this context could provide a richer interpretation of the dynamic of agricultural production, self employment and nonagricultural wage incomes of the rural economy. 44 APPENDICES 45 TABLES Table 12. T-tests of significance to compare means: for Table 4 in document. Variables Macro eco-region Total Valles- Valles- Altiplano- Altiplano Yungas Ymas Number of households 3299 2010 915 374 Number of observations (household members) 10548 6703 2698 1147 Individual gender (% male) 50.0 0.02 0.07 0.00 Individual age (years) 34.3 0.00 0.13 0.00 Individual can read and write (% Yes) 80.7 0.49 0.00 0.00 Years of education completed (number) 5.0 0.17 0.00 0.00 Gender of household head (% Female) 10.0 0.24 0.15 0.61 Age of household head (years) 47.5 0.71 0.00 0.00 Household head can read and write (%) 0.8 0.00 0.00 0.02 Level of education of household head (years) 6.5 0.00 0.00 0.00 Number of members in household >12 4.0 0.00 0.00 0.00 Access to electricity (% ) 43.0 0.00 0.00 0.00 Access to potable water (%) 64.0 - 0.00 0.00 0.00 Distance from household to nearest market (km.) 19.3 0.00 0.02 0.00 Total value of livestock per household (in 83.) 4751.2 0.00 0.03 0.68 Household land size (in hectares) 1.5 0.11 0.01 0.69 Dispersed area (%) 78.0 0.00 0.00 0.00 Table 13. Coefficients of Variation for Income Strata, for Table 6 Source of income Quartiles Low 2nd 3rd High # of households 3,299 Agricultural Income (4.0) (1 .0) (0.9) (2.8) Agricultural Wage Income (1 .0) (0.8) ' (0.8) (1.1) Nonagricultural Wage Income (0.9) (0.7) (0.8) (1.0) Nonagricultural Self Employment (2.1) (1.7) (1.6) (1.9) Uneamed Income (1.0) (1.0) (1.2) (1.6) Total Income (1.3) (0.2) (0.2) (1.1) ‘ Coefficients of variation are in parenthesis (standard deviation/mean) 46 Table 14. Average level of income of those who obtain income from non-farm activities, by income quartile in US. Dollars* Source of income Quartiles Low 2nd 3rd High # of households 3,299 Agricultural Income 60 249 408 1,222 Agricultural Wage Income 92 191 385 873 Nonagricultural Wage Income 159 380 749 2,146 Nonagricultural Self Employment 73 126 187 602 Uneamed Income 37 76 192 1,156 Total Income 1 57 493 1,002 3,439 "' Exchange rate as of December 2001 1US$/6.83 Bs. Table 15. Average level of income of those who obtain income from non-farm activities by ecoregion, in US Dollars* Source of income Region Valles Altiplano Yungas Total Agricultural Income 5 l 3 292 613 461 Agricultural Wage Income 381 169 5 19 366 Nonagricultural Wage Income 1,247 871 950 1,125 Nonagricultural Self Employment 274 210 307 257 Uneamed Income 401 197 896 389 Total Income 1,443 8 13 1,483 l ,273 "' Exchange rate as of December 2001 lUS$/6.83 Bs. 47 Table 16. Wage activities by ecoregion (percent of 10,548 individuals) Macro region Total Valles Altiplano Yurgas Agriculture peon 50% 33% 75% 50% Livestock peon 1% 1% 0% 1% Wood extraction peon 0% 0% 1% 0% Construction worker 12% 18% 7% 12% Fishing peon 0% ~ 0% 0% 0% Driver 4% 2% 4% 3% Office employee 2% 2% 2% 2% Machine operator 1% 0% 0% 1% Artisan 5% 16% 2% 7% Armed F orces/Police 0% 0% 0% 0% Commerce/Sales 5% 6% 3% 5% Non skilled wage peon 13% 16% 3% 13% Technician or mid level 5% 4% 3% 5% professional Professional 1% 0% 0% 1% Director and Executive in 0% 0% 0% 0% Government or Private Sector Total 100% 100% 100% 100% Table 17. Employment by ecoregion (percentage of 10,548 individuals) Macro region Total Valles Altiplano Yungas Agriculture 52% 34% 78% 5 1% Livestock 1% 1% 0% 1% Mining 0% 11% 0% 2% Manufacture 3% 2% 1% 2% Construction 13% 21% 5% 14% Commerce 7% 7% 3% 6% Services 9% 9% 4% 9% Public Sector 6% 8% 6% 6% Housework 4% 3% 1% 3% Education 3% 3% 1% 3% Hotels and Restaurants 1% 1% 2% 1% Community Activities 0% 0% 0% 0% Transport, Storage 1% 0% 1% 1% Provision of gas and water 1% 0% 0% 0% Financial Intermediary 0% 0% 0% 0% Total 100% 100% 100% 100% 48 Table 18. Households participating in nonagricultural self employment by ecoregion (percent of 3,299 households) Valles 67,60% Altiplano 2 1,60% Yungas 10,80% Total 1 00,00% Table 19. Sources of unearned income for the households who received unearned income. (Based on 1901 households from a sample of 3,300 in all three regions) Unearned income Percent Rents 11% Pensions 31% Remittances 35% NGOs or State money 11% Other 12% Total 100% Table 20. Wage labor activities (percent of 3,338 wage laborers among 10,548 individuals) Agricultural wage Percent Crop and livestock wage worker 52% Nonagricultural wage Construction worker 13% Artisan wage worker 7% Commerce/sales wage worker 5% Driver 3% Technician 5% Non skilled wage worker 13% Other 2% Total 100% 49 Table 21. Nonagricultural self employment activities for the household classified into two categories: food processing, and manufacturing and services Food processing Out of 3,3 00 households elaboration of by products of primary production Nonagricultural self employment Percent Food processing* 73% Total 73% Manufacturing and services Out of 9 73 participating households; secondary and tertiary activities performed by households Nonagricultural self employment Percent Manufactured goods“r 26% Artisan 8% Alcoholic beverages 7% Carpentry 3% Bread making 3% Other 5% Services 74% Convenience store 26 Kiosk 24 Transport 6 Intermediary/Middlemen 5 Food pension 4 Others 9 Total 100% "Households may obtain income from food processing, as well as manufacturing and services. Table 22. Location of wage employment by ecoregion (10,548 individuals) Macro region Total Valles % Altiplano % Yungas % Non Local 5422 80 2383 88 867 76 8672 Local 1281 20 315 12 280 24 1876 Total 6703 100 2698 100 l 147 100 10548 50 QUESTIONNAIRE 51 I. IDENTIFICACION NUMERO DE BOLETA [ I MACRO-ECO-REGION ENCUESTA DE LIN EA DEP ART AMENTO BASE VALLES, ALTIPLANO Y PROVINCIA YUNGAS MUNICIPIO HOGARES RURALES CANTON Sistema Boliviano de COMUNIDAD Tecnologla Agropecuaria LOC ALlD AD SIBTA SECTOR CENSAL FILTRO MAN ZANO (En Centros Poblados‘l CENTRO POBLADO 1 AREA DISPERSA 2 MEDICION DEL GPS ALTI T UD (AL 1): POSICION LATITUD (S): LONGITUD (W): HORA A. © PRESENTACION: Buenos dlas, (Buenas tardes) soy ................ © (MENCIONAR NOMBRE Y PRESENTAR CREDENCIAL), encuestador de CIES Intemacional y estamos realizando una encuesta por encargo de la Fundacion de Desarrollo de T ecnologla Agropecuaria, que tiene como objettvo conocer las necesidades en cuanto al apoyo agropecuario, necesidades de capacitacion y mejora del nlvel de vida para reducir la pobreza, y para ello neceslto hablar con eljefe de hogar. © (ENCUESTADOR: SI ATIENDE UN NINO PEDIR HABLAR CON UNA PERSONA DE 18 ANOS O MAS PARA EXPLICAR EL OBJETIVO DEL ESTUDIO) © B. © EXPLIQUE: Toda la lnformacion que nos proporcione es ABSOL U TAMEN TE confldenclal. HORA DE INICIO DE LA ENTREVISTA: 52 PERSONAL DE ENCUESTA CARGO NOMBRE Y APELLIDO CODIGO FECI-IA FIRMA Encuestador: Supervisor de Campo: Editor de Campo: Critico-Codifrcador Gabinete: Transcriptor Gabinete: RESULTADO DE LA ENTREVISTA Entrevista Completa 1 Entrevista Incompleta 2 ENCUESTADOR (A): La boleta tiene la siguiente simbologia: 1. © significa una instruccién y seflala la forma de llenado, saltos o filtros 2. Todo lo que se encuentra en negrilla y cursiva se debe leer a1 entrevistado 3. Todo lo que se encuentra con letras MAYUSCULAS 0 EN MAYUSCULAS Y PARENTESIS son instrucciones 5610 para usted y que no debe leer a1 entrevistado. 4. DSignifica que debe encerrar en un clrculo a las personas que entran en cada seccién II. DATOS DEL HOGAR 1P. Nombre y apellldos del Jefe de Hogar 2P. Nombre de la persona tnformante 3P. Relacidn de parentesco del Informante con el Jefe de Hogar: I 0rd I 0rd OTR I 0rd en en 0 en 4P. gQué ldlomas hablan en el hogar? Castella Quechu © (TIQUEAR Y LUEGO ANOTAR “0 a ORDEN DE IMPORTANCIA DE USO) MULTIPLE Aymara Guam 1 © EXPLIQUE: Para propositos de la entrevista vamos a entender a an hogar como an grupo de personas que comparten las comidas (una olla comrin), techo y hayan vivido en el hogar por lo menos 3 meses desde laflesta de San Juan del ano pasado (Junto 2001) a Iafecha. 5P. {Cudntas personas viven o vivteron en su hogar, incluyendo nlnos recién nacidos, personas mayores y usted? 53 © ANOTE LOS NOMBRES, SEXO Y EDAD EN LA “PESTANA SUPERIOR” Y PROCEDA A FORMULAR LAS PREGUNTAS SUSTITUYENDO LOS ESPACIOS ( ) VERBALMENTE Y SIN ESCRIBIR NADA EN EL CUESTIONARIO POR EL NOMBRE DE CADA PERSONA. © 6P. {Me podrla dar el nombre de todas estas personas, cornenzando can eljefe de hogar, la esposa(o), hljos, entenados(as), otrosfarnlllares y otros no parientes en ese orden? 7P. 3 a varén o majer? 8P. (Cudntos alias curnplldos tiene .’ © (SI TIENE MENOS DE 1 ANO ANOTE EN LA FILA DE EDAD EN ANOS “00” Y LOS MESES EN LA F ILA MESES) NUMERO DE LA PERSONA 01 02 03 04 05 06 07 08 09 10 9P. (Cad! es la relacidn de parentesco de con el Jefe dc Hagar? l Jefe o Jefa de Hogar fl — # fl _ — — ~ — fl 2 COnyuge/Esposa(o) del Jefe de Hogar 3 Hijo/hija del hogar o entenado 4 Yemo/ nuera 5 Nieto(a) 6 Hermano(a) o cuflado(a) 7 Padre o madre 8 Suegro o suegra 9 Empleada(o) del hogar cama adentro \OOO\10\QIIAUJN \OOOQONMAWN NOOOQON'JIAUJN \OOOQO‘UIADJN \OOONO‘um-hwtx) \OflNO\UI&bJN \OOOQGUIAMN VOOOQGLh-hwh) \OOONGlltwa \OQQONMAWN 10 Otro pariente (especificar) ll Otro no pariente (especificar) @PARA PERSONAS DE SIETE (7) 0 MAS ANOS @ D NUMERO DE LA PERSONA 01 02 03 04 05 06 07 08 09 10 10F. (Danae vivla en San Juan del ano pasado (junio 2001) ? 1 Aqul (en esta provincia) 2 En otra provincia del mismo departamento (especificar provincia) 3 En otro departamento del pais (especificar provincia (especificar departamento 4 En el exterior (en otropais) S4 III. EDUCACION © PARA PERSONAS DE CUATRO (4) o MAS ANOS © C1 NU MERO DE LA PERSONA 01 02 03 04 05 06 07 08 09 10 11P. gSabe leer y escrlbir ? 1 Si 1 1 1 l 1 1 l l 1 1 2 No 2 2 2 2 2 2 2 2 2 2 12F. gActualmente asiste a algun centro educatlvo del Sistema regular ? 1 Si 1 l 1 1 1 1 1 1 1 1 2 No 2 2 2 2 2 2 2 2 2 2 13F. © POR Si, PREGUNTAR gCudl es el curso y nivel del sistema "W" ‘1'“ ‘3" “‘“d’“"""—7 © SOLO SE ACEPTA UNA RESPUESTA POR :2 :lOR No, PREGUNTAR gCudl W ultimo curso y nivel del Sistema rggular que aprobd ? © ESCRIBACURSOOANO — _ _ — _ _ — ‘— 1 Ninguno l 1 l 1 l 1 l l 1 1 2 Educacién pre escolar (kinder) 2 2 2 2 2 2 2 2 2 2 3 Curso de alfabetizacién 3 3 3 3 3 3 3 3 3 3 SISTEMA ANTIGUO 4 Primaria (l a 6 aflos) 4 4 4 4 4 4 4 4 4 4 S Secundaria (l a 6 afios) 5 5 5 5 5 5 5 5 5 5 SISTEMA ANTERIOR 6 Basico (1 a 5 aflos) 6 6 6 6 6 6 6 6 6 6 7 Intermedio (l a 3 afios) 7 7 7 7 7 7 7 7 7 7 8 Media (1 a 4 aflos) 8 8 8 8 8 8 8 8 8 8 SISTEMA ACTUAL 9 Primaria (1 a 8 aflos) 9 9 9 9 9 9 9 9 9 9 10 Secundaria (1 a4afios) 10 10 10 10 10 10 10 10 10 10 55 EDUCACION ALTERNATIVA 11 EducaciOn Basica de Adultos (EBA) 11 11 11 11 ll 11 11 11 11 11 12 Centro de Educacién Media de Adultos 12 12 12 12 12 12 12 12 12 12 (CEMA) 13 Instituto Boliv1anodeAprend1zaJe 13 13 13 13 13 13 13 13 13 13 (13A) EDUCACION SUPERIOR 14 Normal Superior 14 14 l4 14 14 14 14 14 14 14 15 Universidad 15 15 15 15 15 15 15 15 15 15 16 Post gradoomaestria 16 16 16 16 16 16 16 16 16 16 17 Técnico universitario 17 l7 l7 l7 17 17 17 17 17 17 18 'I‘écnico de instituto con 18 18 18 18 18 18 18 18 18 18 bachillerato 19.(?°'eg‘° m‘l‘tamacadem‘a 19 19 19 19 19 19 19 19 19 19 how! OTROS 2° .Técmw d" ‘nsnmmsm 20 20 20 20 20 20 20 20 20 20 bachillerato 21 Otros (especificar) 97. No sabe 97 97 97 97 97 97 97 97 97 97 IV. SALUD/F EC UNDIDAD © LEA LOS NOMBRES DE LA “PESTANA SUPERIOR” Y PROCEDA A FORMULAR LAS PREGUNTAS DEPENDIENDO DE LA EDAD, SUSTITUYENDO LOS ESPACIOS ( ) VERBALMENTE Y SIN ESCRIBIR NADA EN EL CUESTIONARIO POR EL NOMBRE DE CADA PERSONA. © a PARA N1NOS(AS) DE CINCO (5) ANOS o MENOS o C1 NUMERO DE LA PERSONA 01 02 03 04 05 06 07 08 09 10 14P. {En las ultimas 2 semanas tuvo diarrea? 1 Si 1 1 l 1 l 1 1 1 1 1 2 No 2 2 2 2 2 2 2 2 2 2 a PARA TODOS LOS MIEMBROS DEL HOGAR @ NUMERODELAPERSONA [ 01 L02] 03 [04 l 05 [06 | 07 I 08] 09 [10 15P.1Ha tenldo alguna enferrnedad, accldente, o Iesidn desde la fiesta de San Juan del ano pasado (lunlo 2001) a lafecha? 56 lSi 2 No 69 (PORNO SALTEA LA 17P O 24p SE GUN 2 2 2 2 2 2 2 2 2 2 CORRESPONDA) 1GP. {Que tlpa de enferrnedad /prablerna / lesian tuva a tiene ? l Diarrea o VOmitos u otra enferrnedad l 1 1 1 1 1 1 l 1 1 del estOmago 2 Enfermedad respiratoria (tos, gripe, 2 2 2 2 2 2 2 2 2 2 garganta, etc) 3 Enfermedad crOnica (diabetes, del 3 3 3 3 3 3 3 3 3 3 corazOn _______________ (especificar) 4 Accidente 4 4 4 4 4 4 4 4 4 4 5 Otras (especificar) © PARA MUJERES DE DOCE1121A CUARENTA Y NUEVE (49) ANOS © C] NUMERO DE LA PERSONA 01 02 I 03 04 05 06 07 08 09 10 17P. {En su vida ha tenida algun hija a Inga nacida viva ? 1 Si 1 l 1 1 1 1 1 1 1 1 2 No ©-)PASEA23P 2 2 2 2 2 2 2 2 2 2 18F. gEn total cudntas hijas e hijas nacldas vivas ha tenida incluyenda las que hayan muerta a estdn ausentes? _ _ _ _ _ _ _ _ _ _ 19F. we (as hijas e hijas nacidas vivas de , cudntas estdn vivas actualrnente? __ 20F. aDe las Iufias e hfias nacidas vivas de _, cudntas murieran antes de cumplir un afla? __ 21F. gEn que mes y ana nacid su ultimo hija a hlja naclda viva de 1’ _l\"‘ ‘ "7 _ME _ME _ME _ME _ME _ME _ME _ME 1 MES S S S S S S S S A1210 A121 A121 A121 A121 A121 A121 A121 A121 A121 A121 0 0 O O O O O O O O 22P.1£'n su ultimo hija(a) le hicieran a mm a nnis cantrales prenatales durante su embaraza? 1 Si 1 1 1 1 1 1 l 1 1 l 2 No 2 2 2 2 2 2 2 2 2 57 23F. Estuva a esta embarazada desde San Juan del alto pasada a la feclta? 1 Si 1 l l l 1 l l 1 1 l 2 No 2 2 2 2 2 2 2 2 2 v. OCUPACION PERSONA. © © LEA LOS NOMBRES DE LA “PESTANA SUPERIOR” Y PROCEDA A FORMULAR LAS PREGUNTAS DEPENDIENDO DE LA EDAD, SUSTITUYENDO LOS ESPACIOS ( ) VERBALMENTE Y SIN ESCRIBIR NADA EN EL CUESTIONARIO} POR EL NOMBRE DE CADA @ PARA PERSONAS DE SIETE (7) 0 MAS ANOS @ D NU MERO DE LA PERSONA 01 02 03 04 05 06 07 08 10 del hagar 0 en el hogar 7 24F. Durante la semana anterior, de lanes 11 dominga, g trabajd [uera ISI 1 1 l 1 l H 1 l l 1 2 No © -) PASE A 26P 2 2 2 2 2 2 2 2 2 Men.” 25F. {Que tipa de trabaja u acupacion realiza durante la semana anterior (uera del hagar 0 en Agricultor Cria de animales ExtracciOn de madera Albaflil Actividades de pesca Conductor, chofer Empleado de oficina Operario de maquinas Artesano \OWQQM-bUN—i ©00\l0\M-§WN~ \OOOQQMAUJN— \OOOQQ'Jt-th— \ONQQMADJN—A OWQQM45UJN— \OWQO‘MAuN—P fl OOOOQOKMAMN— Fuerzas armadas o policia ll Comercio o venta de productos “fl u—uoo u—n.‘ --O _— ~O u—Ip—a -'O :gxoooxicmmaww— :SOOOQONUt-AWN— u—ou—n —O _—a '—‘o u—o—n ho zscmanRwN— u—n N Otros empleos (especificar) 26F. {Durante la semana anterior, de lanes 11 dominga realizd alguna de las siguientes actividades [uera del hagar 0 en el hogar ? © LEER : I T rabajd en cultivos agrlcalas l 2 Trabajo en crianza de anirnales 2 3 Atendld o ayudo en un negacia familiar 4 Realiza alguna actividadpor dinera 58 5 Tenia trabaja pera no trabajo par que estaba enferrno, can 5 5 5 5 5 5 5 5 5 5 lieencia, o no tenla materiales 6 Busco trabajo habienda trabajada 6 6 6 6 6 6 6 6 6 6 antes 7 Busca trabajo pagoda par 7 7 7 7 7 7 7 7 7 7 prirnera vez 8 S610 se dedicd a estudiar 8 8 8 8 8 8 8 8 8 9 Realizd solo labores de 9 9 9 9 9 9 9 9 9 9 casa 1” Esjubuado" 1o 10 10 10 - 10 10 10 10 10 10 pensionado a rentista II Otro (especiflcar) VI. TRABAJO REMUNERADO INDIVIDUAL FUERA DEL HOGAR EN LOS ULTIMOS 12 MESES 06 07 © PARA PERSONAS DE SIETE (7‘ E] NUMERO DE LA I l PERSON A 01 02 03 04 05 O MAS ANOS © 08 09 10 27F. Desde laflesta de San Juan del ano pasado Ounio 2001) gqué actividades pagadas realizé [uera del hagar a de la gragkdad agrlcala? l Agricultor peOn 2 Cria de animales peOn 3 ExtracciOn de madera peOn 4 Albaflil 5 Actividades de pesca peOn MANNH 1 2 3 4 5 M-bU’Nn—s MANNI— Lit-bub)— M & urn—- MAMN" MbMN1—1 MAWN— MADON— 6 Conductor, chofer asalariado 7 Empleado de oficina 8 Operario de maquinas 9 Artesano asalariado 000% O5 \000Q 05 000‘.) O‘ \OOOxI O\ \OWQ O\ 000% 0\ \OOO\) O\ \OOOQ O\ VOOOQ O\ 000% O5 10 Fuerzas armadas o policia 12 Comercio o venta de productos asalariado 11 11 ll 11 11 11 11 11 11 ll 13 Otros empleos (especificar) 97 Ninguna © SI TODOS NINGUNA PASAR AL MODULO VII PAG 7 97 97 97 97 97 9‘7 97 97 97 97 ANOTE NUMERO DE LA ‘PERSONA ANOTE CODIGO DE LAQTIYIDADS 59 © PREGUNTAR POR CADA ACTIVIDAD DE CADA PERSONA© 28F. gA qué se dedica el lugar d ersana donde a para quién trabajd ? l Agricultura l l l 1 l 1 l l 1 l 2 Ganaderia 2 2 2 2 2 2 2 2 2 2 3 Mineria 3 3 3 3 3 3 3 3 3 3 4 Industria Manufacturera 4 4 4 4 4 4 4 4 4 4 5 Construccién 5 5 5 5 5 5 5 5 5 5 6 Comercio 6 6 6 6 6 6 6 6 6 6 7 Servicios 7 7 7 7 7 7 7 7 7 7 8 Sector pfiblico 8 8 8 8 8 8 8 8 8 8 9 Otros (especificar) 29F. gEn esta ocupacian trabajd coma: l Obrero u empleado(a)? l 1 1 1 1 1 l l 1 1 2 Oooperativista de 2 2 2 2 2 2 2 2 2 2 producerén? 3 .Trabajador famrllar o 3 3 3 3 3 3. 3 3 3 3 aprendlz? 4 Trabaj ador por cuenta 4 4 4 4 4 4 4 4 4 4 propia 5 PatrOn 50cm 6 5 5 5 5 5 5 5 5 5 5 empleador 6 Otra (especificar) 30F. Desde la fiesta de San Juan del aiia pasada 0unio 2001) a la fecha gCudnta tiempo trabajd [uera del hagar a de la ........... ro iedad amiliar/ unidad a rlcala? 1 Horas por dia 2 Dias por semana 3 Semanas por mes 4 Meses 5 Todo el aflo 1 l 1 1 1 1 1 1 1 l 6 Otro (especificar) 31F. Desde la fiesta de San Juan del alto pasado Ounio 2001) gCudnto le pagaran (a gand) a en Bs. ? © SI EXISTE A ALGUN PAGO EN ESPECIE ANOTAR EN CIRCULO EL TOTAL ESTIMADO EN 85. POR PERSONA POR ACTIVIDAD AL FINAL DE LA PAGINA. 1 Por hora 2 Por dia 3 Por semana 4 Por mes 5 Otro (especificar) 32F. g Y ddndefue esa ocupacldn? © LEER 1 en esta cornunldad 1 1 1 1 1 1 1 ll 1 I 1 2 en otra cornunidad a pueblo aledatta 2 2 2 2 2 2 2 2 2 2 3 en otra lugar donde va a dormir 3 3 3 3 3 3 3 3 3 lenatropats 4 4 4 4 4 4 4144 4 60 v11. PRODUCCION AGRICOLA / MAQUINARIA Y EQUIPO 33F. Desde laflesta de “San Juan ” del ana pasada, galgtin rnlembro de su hogar a peon trabajd la tierra © (ESTAS TIERRAS PUEDEN SER PROPIAS, ALQUILADAS 0 AL PARTIR) ? -) © POR NO PASAR A PRODUCCION PECUARIA PAGINA SI 1 NO 2 12 ENCUESTADOR DIBUJE CON EL PRODUCTOR LA TOTALIDAD DE PARCELAS TRABAJADAS PARA EL HOGAR QUE COMPONE SU UNIDAD AGROPECUARIA, INCLUYE TIERRAS ALQUILADAS AL HOGAR o QUE SON DE LA COMUNIDAD Y QUE LAS TRABAJA EL HOGAR. EN ESTE CROQUIS DETALLAR EL TAMANO DE LA EXTENSION DESAGREGADA POR CULTIVOS Y USO DE LA TIERRA. DIBUJE TODOS LOS OTROS ASPECTOS RELEVANTES DE UN CROQUIS COMO CARRETERAS, RIOS, ADEMAS DEL TIEMPO QUE TOMA IR DEL LOTE DONDE SE ENCUENTRA SU VIVIENDA A LOS OTROS LOTES CON UNA LINEA. LUEGO TRASPASAR LOS DATOS POR mm A LA PAGINAvs. WWW»?211.11.313.1117152;” 9‘“ PW . . . . . . . 1 1 . , . . . . ................ ............ . . Q 4 I . . . 1 . . , 1 1 . . . 1 NUMERODELOTE | 01 [ 02 l 03 I 04] 05 L06 | 07 | 081 09 [ 10 ”RA Cudlfue el usa del late durante este alto agrlcola? 1 Cultivado 1 1 1 l 1 1 1 l 1 1 2 Barbecho 2 2 2 2 2 2 2 2 2 2 3 Descanso 3 3 3 3 3 3 3 3 3 3 4 Pasto cultivado 4 4 4 4 4 4 4 4 4 4 5 Pastos naturales 5 5 5 5 5 5 5 5 5 5 6 Monte y / o bosque 6 6 6 6 6 6 6 6 6 6 7 Otto uso especificar 33P.B Cudl es la superflcle de este late? CANTIDAD UNIDAD 33P.C Este late es ....... l propio? l 1 1 l 1 1 1 1 1 1 2 alquilado? 2 2 2 2 2 2 2 2 2 2 61 3 a1 partido? 4 0110 especificar 33P.D Este late esta a..... 1 Riego 2 Secano 33P.E De ddnde se abtiene el agua ?. 1 Rio / quebrada 2 Lago / laguna 3 Represa 4 Vertiente AWN-— l 2 3 4 #UJN—t bWNr— AWN— AWN—- AWN-— AWN-— l 2 3 4 $9319— 5 Otro especificar 33P.F POR RIEGO Cudnta es el gasta par late de riega ? (SI NO GASTO NADA ANOTE “00”, ANOTE CADA CUANTO PAGA) BS NUMERO DE LOTE [ 11 [#12 1 13 [*14 ] 15 [716 J 17 l 18 I 19 l 20 33P.A Cudlfue el usa del late durante este aflo a rlcala? l Cultivado 2 Barbecho 3 Descanso 4 Pasto cultivado 5 Pastos naturales 6 Monte y / o bosque aka-kWN—i QMcBWNU-fi @M-bb-DN— @211.wa— $211th— aka-huts)— 0MRWN1— GUI-huh)— @MAMN— QMhUJN— 7 Otro uso especificar 33P.B Cutil es la superflcie de este late? CANTIDAD UNIDAD 3313.0 Este late es ....... 1 propio? ~ H H fl — _ 2 alquilado? N 3 al partido? 4 Otro especificar 33P.D Este late esta a..... l Riego — _ — ~ — .— —n —i _- 2 Secano N— 33P.E De donde se obtlene el agua ?. 1 Rio / quebrada 2 Lago / laguna 3 Represa 4 Vertiente Jib-DN— AWN— 42.9.119— AWN-— AWN— 503N— b9310— ADJN~ AWN— AWN—- 5 Otro especificar 33P.F POR RIEGO Cudnta es el gasta par late de rlega? (SI NO GASTO NADA ANOTE “00”, ANOTECADACUANTO PAGA) Bs NUMERO DE LOTE 21 |22f123 [24.I25 26]27[28I29L30 62 33m! Cudlffue el usa del late durante este alto ‘ agrlcola.’ 1 Cultivado 1 l 1 1 1 1 1 1 l l ZBarbecho 2222222222 3Descanso 3333333333 4Pasto cultivado 4 4 4 4 4 4 4 4 4 4 5Pastosnaturales 5 5 5 5 5 5 5 5 S 5 6Montey/obosque 6 6 6 6 6 6 6 6 6 6 7 Otro uso especificar 33P.B Cudl es la superflcie de este late? CANTIDAD UNIDAD 33P.C Este late es ....... lpropio? 1 l 1 1 l 1 1 1 1 l 2alquilado? 2 2 2 2 2 2 2 2 2 2 3alpartido? 3 3 3 3 3 3 3 3 3 3 4 Otro especificar 33P.D Este late estd a..... 1 Riego 1 l 1 1 1 1 l 1 l 1 2Secano 22222 2222 33P.E De ddnde se abtiene el agua?. 1 Rio / quebrada 1 l 1 1 l l 1 l 1 1 2Lago/laguna 2 2 2 2 2 2 2 2 2 2 3Represa 3333333333 4Vertiente 4444444444 5 Otro especificar 33P.F POR RIE GO Cudnta es el gasta par late de rlego? (SI NO GASTO NADA ANOTE “00”, ANOTE CADA CUANTO PAGA) Bs NUMERODELOTE 131 [ 32 l 33 L34 1 35 [36] 37 L38 l 39 [4o 33P.A Cudlfue el usa del late durante este afla agrlcala? 1 Cultivado l l l 1 1 l 1 1 1 1 2 Barbecho 2 2 2 2 .2 2 2 2 2 2 3 Descanso 3 3 3 3 3 3 3 3 3 3 4 Pasto cultivado 4 4 4 4 4 4 4 4 4 4 5 Pastos naturales 5 5 5 5 5 5 5 5 5 5 6 Monte y/ o bosque 6 6 6 6 6 6 6 6 6 6 7 Otro uso especificar 33P.B Cudl es la superficie de este late? CANTIDAD UNIDAD 63 3312c Este late es ....... 1 propio? 2 alquilado? 3 al partido? 4 Otro especificar 33P.D Este late estd a..... 1 Riego fl — 2 Secano 33P.E De donde se abtiene el agua ?. 1 Rio / quebrada 2 Lago / laguna 3 Represa 4 Vertiente AWN—- l 2 3 4 «59319-— hWN-d l 2 3 4 l 2 3 4 AWN—- AWN—- l 2 3 4 AWN-— 5 Otro especificar 33P.F POR RIEGO Cudnto es el gasta par late de riega? (SI NO GASTO NADA ANOTE “00”, ANOTE CADA CUANTO PAGA) Bs CULTIVOS EN EL ANO AGRICOLA © FORMULAR LAS PREGUNTAS SUSTITUYENDO LAS ESPACIOS( )VERBALMENTE Y SIN ESCRIBIR NADA EN EL CUESTIONARIO POR EL NOMBRE DE CULTIVOS DE CADA LOTE © ANOTE POR LOTE CULTIVADO-) PARA LOS CULTIVOS PREGUNTE SOBRE EL A1210 AGRiCOLA DE JUNIO 2001 A JUNIO DEL 2002 Nfimero del lote Nfimero del lote Nfimero del lote Cultivo Cultivo Cultivo CANT. UNID. CANT. CANT. UNID. 3411.3 Qué supetflele chums a casecha de 35F. gQué cantidad de praducto abtuvo u obtemlrd en este anaflrlcala de ? 36F. (Coma distribuyd (ird) o usa(ar1i) su praduccion? CANT. UNID. CANT. UNID. CANT. UNID. 1 Para e1 consumo del hogar? 2 Consumo animal? 3 Pérdidas? 4 Transformacién? 64 5 Trueques? 6 Regalos? 7 Para semilla? 8 Venta? 37F. 3,0141 fue el precio al que vendio vendera la mayor parte de ? BS. UNID. Bs. UNID. Bs. UNID. 38F. {Que cantidad de semillas y/a pldntulas utilizd de: © LEER CANT. UNID. CANT. UNID. CANT. UNID. 1 C rialla? 2 Mejorada a certificada.’ 39F. 3 Y cudnta gusto en este ana agricola en semillas: © (N O GASTO 00”) Bs. UNID. Bs. UNID. Bs. UNID. 1 Criolla? 2 Mejorada o certificada? 40F. gQué cantidad de abana o fertilizantes utilizd de: 69 LEER CANT. UNID. CANT. UNID. CANT. UNID. I Abono (huano, bosta, etc) 2 Abono quimico 411’. g Y cudnta gastd en este ana agrlcala en total en abana? © (NO GASTO “00”) Bs. UNID. Bs. UNID. Bs. UNID. 1 Abono (huano, bosta, etc) 2 Abono quimico 42F. gCudntos jarnales utilizd o utilizard para FA MI- PAGA DO AYNI (NO LI AR PAGA DO) FA MI- PAGA AYNI DO (NO LIA PAGA DO) FA MI PAGA DO AYNI (N0 LI AR PAGA 1 La siembra 2 Labores culturales 3 La cosecha 43F. gCudnto pogo a pagard par jarnal? BS. B5. B5. l VarOn 2 Mujer 44F. gA dermis deljornal le dieron alga mds? BS. BS. Bs. 1 Si Que? © ESTIMAR CUANTO SERIA EN Bs. 2N0 NOTACION: v= VARON / M=MUJER 65 45F. gCudnta gasta este alto agrlcala en. ....... © LEER ? Bs. I ..... Insecticidas? 2 ..... Herbicidas? 3 ..... F ungicldas? 4GP. gCudnto gasta a gastard en el alquiler de animales (yunta) para la produccidn de este alto agrlcola? © (ANOTE “00” SI NO GASTO NADA) Bs. 47F. {Cudnto gasta a gastard en alquiler de tractares, maquinarlas y equipo agrlcola utilizado en la produccion de este alto agrlcala? © (ANOTE “00” SI NO GASTO NADA) Bs. 48F. gHa realizado pagas en efectivo a otras personas por el alquiler de tierras en este alto agrlcala? © (ANOTE “00” SI NO GASTO NADA) Bs. 48.a.P {Me podrla decir si realizo atras gastos adicionales en las cultivos agrlcalas desde la fiesta de San Juan del alto pasada Gunia 2001), sin contar gastos de transporte a camercializaclon de sus cultivos? © (Especificar) © (ANOTE “00” SI NO GASTO NADA) BS. 49F. gEste alto agrlcalafue. ..... © LEER. ANOTAR CODIGO I Buena 1 2 Regular 2 3 Mala 3 50F. gLa produce-ion abtenida este alto agrlcolafue. ...... can relacidn al alto anterior? © LEER ANOTAR CODIGO 1 Mayor 1 2 Igual 2 3 Menor 3 51F. gCudles de las slguientes maquinarias e lntplernentas en usa que le voy a leer utiliza para trabajar sus cultivas? © POR 81 CIRCULE EL CODIGO, ANOTAR TOTAL Y PREGUNTAR P52 Y P53 © 52F. g Y qué cantidad de éstos © (VER TOTAL) son prapios? 53F. Y que cantidad de éstas © (VER TOTAL) son alqullados? CIRCULE EL CODIGO TOTAL '2 “" “ " ' ‘7 ‘ Arada 1 Tractor 2 Motosierra 3 Motacultor 4 Bamba de riego 5 Casechadara mecdnica 6 66 Otra (especificar) v111. PRODUCCION PECUARIA 52 54F. ; Deede laflesta de San Juan del alto pasado (iunia 2001), crld animales en el hogar? © SI 1 9gCudles N 2 -) © POR NO PASAR A ELABORACION DE SUB- ? O PRODUCTOS PAG 14 © DEBEN ANOTAR Y DIFERENCIAR DE LA SIGUIENTE FORMA: GANADO PORCINOS O V A CUN O OVEJAS POLLOS CERDOS . VACAS . MACHOS ' :gRRILLE . MACHOS . TOROS . HEMBRAS ' KONEDOR . HEMBRAS o BUEYES CABRAS / CHIVOS o BEBE LLAMAS/ o TERNEROS ALP AC AS CONEJOS © ANOTAR EN ESPACIOS VACIOS ESPECIE-) . CODIGOS 55F. (Que cantldad tiene altara (en CAN CAN CAN CAN CAN CAN CAN CAN CANT estafeclta) de ? T. T. T. T. T. T. T. T. ' 56P.gY a quéprecio venderia sus Bs. Bs. Bs. Bs. Bs. Bs. Bs. Bs. Bs. animales ahara par cabeza? 57F. gCudntos nacieron o campraron CAN CAN CAN CAN CAN CAN CAN CAN CANT desde la fiesta de San Juan del T. T. T. T. T. T. T. T. ' alto pasada ([unio 2001) a la fecha? Naclrnlentos Campras 58F. gCudntas las vendio vivas 0 en CAN CAN CAN CAN CAN CAN CAN CAN CANT ple desde la fiesta de San Juan T- T- T- T- T- T- T- T. ' del alto pasada (junio 2001)? 59B; Valor total de la venta de Bs. Bs. Bs. Bs. Bs. Bs. Bs. Bs. Bs. ? 60P.gA queprecio vendio por Bs. BS. Bs. BS. Bs. Bs. Bs. Bs. Bs. cabeza? 67 61P.3Cudntas las vendiofaenados/ CAN CAN CAN CAN CAN CAN CAN CAN CANT. desolladas /carneadas ? T- T- T- T- T- T- T- T- 62P-2A que precio vendio 88108 Bs. Bs. Bs. Bs. Bs. Bs. Bs. Bs. Bs. animales faenadas / desallados /carneadas_? Unidad 63F. gCudntas animales las destlnd CAN CAN CAN CAN CAN CAN CAN CAN CANT al cansumo del hogar ? T. T. T. T. T. T. T. T. ' 64F. gCudntas animales murieran y CAN CAN CAN CAN CAN CAN CAN CAN CANT no pudo recuperarlas? T. T. T. T. T. T. T. T. ' 65P. gCudntos animales las destind CAN CAN CAN CAN CAN CAN CAN CAN CANT al trueque? T. T. T. T. T. T. T. T. ' 66F. {Cudntas animales las destino CAN CAN CAN CAN CAN CAN CAN CAN CANT para regalo? T. T. T. T. 1 T. T. T. T. ' MP. 1 Cudntas animales tenla en CAN CAN CAN CAN CAN CAN CAN CAN CANT junta de12001 (San Juan del T. T. T. T. T. T. T. T. ' alto pasado)? “P- ”3103 animales We “5"!“ £5" Bs. Bs. Bs. BS. Bs. Bs. Bs. Bs. Bs. cudnto las hublera vendida en junlo del 2001? OBSERVACIONES© ANOTAR AQUI’ OTROS INGRESOS (EJEMPLO POR VISCERAS, CUERNOS, OTROS) 69F. gCudnta gusto en la alirnentacion de animales desde la flesta de San Juan del alto pasado 0unio 2001) a lafecha? Bs. 70F. g Utilizd mano de abra pagoda para la crianza o cuidado? lSi l 2 No '9 © PASAR A 72P 71F. g Y cudnto pogo par este trabaja desde la fiesta de San Juan del alto pasado (junta 2001) a lafecha? © (SI PAGO EN ESPECIE, ESTIMAR CUANTO SERIA EN Bs.) Bs. 72F. gCudnta gusto en servicios de veterinario desde Iaflesta de San Juan del alto pasada (iunio 2001) a la feclta? © (INCLUYA GASTOS POR VACUNAS, MEDICAMENTOS U OTROS RELACIONADOS A GASTOS DE VETERINARIO) © (ANOTE “00” SI NO GASTO NADA) 68 Bs. 73F. {Ha realizado pagos en efectivo a otras personas par el alquiler de tlerras para el pastarea? © (ANOTE “00” S1 NO GASTO NADA) Bs. 74F. {Me podrla decir si realizo otras gastas adicionales en la crianza de sus animales desde la fiesta de San Juan del alto pasada Ounlo 2001), sin cantar gastas de transparte a cornerciallzacldn de sus animales? © (Especificar) © (ANOTE “00” SI NO GASTO NADA) Bs. 1x. ELABORACION DE SUBPRODUCTOS 75F. g Desde la fiesta de San Juan del alto pasada Ounio 2001), obmva a elabard algun producta? SI 1 -)‘°Cudles N 2 © -) POR NO PASAR A MODULO DE 2 O COMERCIALIZACION PAG 15 E“ S 8 D H g 89 CIRCULE SUBPRODUCTOS {5' E o QUE OBTIENE O ELABORO Y ANOTE OTROS -) 1 2 3 7GP. gQué cantidad ha elaborada u abtenldo desde la fiesta de San Juan del alto pasado 0unlo 2001)? CANTIDAD UNIDAD Frecuencia 1 Diario l 1 1 1 l l l 1 l 2 Semanal 2 2 2 2 2 2 2 2 2 3 Mensual 3 3 3 3 3 3 3 3 3 4 Otro(especificar) ' NUMERO DE VECES AL A1210 TODO EL AN0 1 l l 1 1 l 1 1 l 77F. {Que cantidad destina para la venta? © ANOTAR I FRECUENCIA CANTIDAD UNIDAD 69 7GP. gCudnta es el preclo par ? UNIDAD 79F. gCudnto gastd en Bs. para abtener este producto desde la flesta de San Juan del alto pasado (Iunia 2001) a lafeella? 80F. gCudnto se echd a perder y no puda vender? CANTIDAD UNIDAD 81F. gCudnto destind al consuma del hagar? CANTIDAD UNIDAD 82F. zDestind parte de este sub- praducta para la elaboracidn de algtin otra? 1 Si Cudnto? CANTIDAD © (REALIZAR TODAS LAS PREGUNTAS POR EL NUEVO SUB- PRODUCTO) UNIDAD 2N0 83F. g Utilizd mano de abra pagoda para la elaboracldn de estas productos ? 181 ~ _ 2 No -) © PASAR A 84aP MP. 3 Y cudnta pagd par este trabajo dade lafiesta de San Juan del alto pasado Gunla 2001) a la feclta? ©SI PAGO EN ESPECIE, ESTIMAR CUANTO SERIA EN Bs. 70 84 a.P {Me padrla decir si reallzd otras gastas adicionales en la elaboracldn de sub-productos desde laflesta de San Juan del alto pasado 0unlo 2001), sln contar gastas de transporte a camercializacidn de éstas? © (Especificar) por tipo de sub- producto (ANOTE “00” SI NO GASTO NADA) Bs. X. COMERCIALIZACION / MERCADO ELABORACION DE SUB PRODUCTOS © © REALICE LAS SIGUIENTES PREGUNTAS SI AL MENOS EL HOGAR CUENTA CON ALGUNO DE LOS MODULOS DE PRODUCCION AGRICOLA, PRODUCCION PECUARIA O MODULOS CIRCULADOS 9 © CIRCULAR LOS MODULOS CON QUE CUENTA EL HOGAR Y FORMULAR LAS PREGUNTAS PARA LOS Crianza a Elaboracio faenada de n de sub- Ag ricultura animales productos | 1 2 3 85F. {De quién recibe la mayor cantidad de lnfarmaclon acerca de las precias de sus productos agrlcalas y/o animales y/a sub -praductas ? © (REFIERASE A LA PRINCIPAL FUENTE) Del mismo comprador Programas de capacitaciOn Radio TelevisiOn PeriOdicos O‘M5LQN—n Miembro de la comunidad 7 Organizacién de productores 8 En el mercado mxtambwm— ooqoquAwN— ”\IQMAUJN— 9 0110 (especificar) 86F. gDonde vende la mayarla de sus productos agrlcalas y/a animales y/o sub-productos ? I Feria local 1 l 2 F eria de otra comunidad 3 En la ciudad 4 Directo al rescatista 2 3 4 2 3 4 kWN—n 5 Otro (especificar) hasta © (MENCIONAR 86P) ? 87F. gCudnta tlempo tarda en llegar desde su prapledad CAN TIEM PO CA NT TIE MPO CA NT TIE MPO de su prapledad? 88P. 4A qué dlstancia le queda © (MENCIONAR 86P) CAN DIST ANC CA NT DIST AN CA NT DIST ANC 89F. gCudnta gasta a gusto en transporte de su praduccion Bs. Bs. Bs. 71 agrlcola y/o de sus animales y/a de sus subproductos al mercado desde la fiesta de San Juan del alto pasado (lunia 2001) a lafecha? © (ANOTE “00” S1 NO GASTO NADA) _PRODUCCION COMPARTEN GASTOS O INDAGAR SI LOS PRODUCTOS AGRICOLAS Y IO ANIMALES Y / O SUB-PRODUCTOS COMPARTIERON O COMPARTIRAN GASTOS DE TRANSPORTE, ANOTE QUE 89a.P gEn casa que comparta gastos de transporte, cuénto gasto' en total? O (Especificar) O (ANOTE “00” SI NO GASTO NADA) Bs. 90F. gMe podrla declr si realizd otras gastas adicianales para vender sus productos agricolas y/o animales y/o subproductos desde laflesta de San Juan del alto pasado (lunia 2001) a lafecha, sin contar gastos de transporte? (Ejemplo Sentaje, Manipuleo, T rancas, etc.) Bs. Bs. Bs. Bs. Bs. Especificar Especificar Especificar _PRODUCCION COMPARTEN GASTOS O INDAGAR SI LOS PRODUCTOS AGRICOLAS Y /O ANIMALES Y / O SUB-PRODUCTOS COMPARTIERON O COMPARTIRAN GASTOS ADICIONALES , ANOTE QUE 90a.P gEn casa que comparta otras gastas, cudnto gasto' en total? O (Especificar) O (ANOTE “00” SI NO GASTO NADA) x1. ASISTENCIA TECNICA / CAPACITACION ELABORACION DE SUB PRODUCTOS O REALICE LAS SIGUIENTES PREGUNTAS SI AL MENOS EL HOGAR CUENTA CON ALGUNO DE LOS MODULOS DE PRODUCCION AGRICOLA, PRODUCCION PECUARIA O Crlanza a Elaboraci 91F. ifeclblo aslstencia técnlca y capacitacldn Agricultura faena do de (in de sub- animales productos 1 Si . l l l 2 No 9 © SI TODOS NO PASAR A 96? 2 2 2 92p. gQué tipo de ayuda recibid? WLTIPLE) 1 En el uso de material genético o semilla certificada l 2 Agoyo en manejo cosecha 0 pos cosecha 2 3 Cursillos de capacitaciOn de agricultura en general 3 4 Crianza O faenado de animales 4 5 Cursillos de capacitaciOn de producciOn pecuaria en _general 6 Apoyo en la comercializaciOn 6 6 6 7 Cursillos de capacitacién de elaboracién de subproductos en 7 general 72 8 Otro (especificar) 92aP.g Esta asistenciafue en grupa a lndividual? 1 En grupo 1 l 1 2 Individual 2 2 2 93F. Pagd par la aslstencia a capacitacidn técnlca? Bs. Bs. Bs. 1 Si , POR Si gCudnta £986? 2 No 2 2 2 94F. Especiflcar lnstitucldn (es) que brindd a brindaron aslstencla 95F. Especificar prayecto (as) que brindd o brlndaron aslstencla 96F. {Que tipo de asistencia técnica qulslera reclbir en sus cultivos a praduccidn agricola en general? pecuaria en general? 97F. {Que tipo de asistencla técnica quisiera recibir para la crianza de sus animales a praduccion 98F. gQué tlpo de asistencla técnlca qulsiera recibir para la elaboracidn de subproductos en general? XII. ACT IVIDADES INDEPENDIENTES CUENT A PROPIA QUE RINDEN INGRESO O FORMULAR LAS PREGUNTAS SUSTITUYENDO LAS ESPACIOS 1 ) VERBALMENTE Y SIN ESCRIBIR NADA EN EL CUESTIONARIO POR EL NEGOCIO O ACTIVIDAD QUE TIENE EL HOGAR O 99F. gReallzd usted a alguien de su hagar alguna actividad econdmlca (micro-empresa) de manera lndependiente desde la fiesta de San Juan del alto pasado ([unio 2001) a la feclta? Cudl? O DE EJEMPLOS ANTES DE PASAR 73 SI 1 9gCudl? g 2 O LEER I T lene o tuvo una tiendita 2 Tiene a tuvo una pension de camida 3 Tlene o tuvo taller de carpinterla 4 Tiene o tuvo una metal mecdnlca 9 O POR NO PASAR A MODULO XIII PAG 18 O 5 Otro (especificar) ANOTAR ACTIVIDADES [1 map. {Cudnto reclbid par ventas su Bs. Bs. Bs. Bs. desde San Juan del alto pasado (iunia 2001) a lafecha? 101P. gCudnto destind para el Bs. Bs. Bs. Bs. consumo del hagar desde San Juan del alto pasado (junta 2001) a la fecha? O SI PAGO EN ALIMENTOS O ESPECIE ESTIMAR CUANTO SERIA EL VALOR EN BOLIVIANOS 102P. gCudnto destlno para el trueque Bs. Bs. Bs. Bs. desde San Juan del alto pasado Ounio 2001) a lafeclta? 69 SI DESTINO EN ALIMENTOS O ESPECIE ESTIMAR CUANTO SERIA EL VALOR EN BOLIVIANOS 103P. gCudnto gasto en su BS. Bs. Bs. BS. en salarios o jomales desde San Juan del alto pasado unia 2001) a lafeclta? O Si PAG EN ALIMENTOS O ESPECIE ESTIMAR CUANTO SERIA EN BOLIVIANOS 1MP. gCudnta gastd en su en Bs. Bs. BS. Bs. insumas o mercaderla desde San Juan del alto pasado aunia 2001) a lafecha? » O Si PAGO EN ALIMENTOS O ESPECIE ESTIMAR CUANTO SERIA EN BOLIVIANOS 105P. gTuva otras gastas en su BS. Bs. Bs. Bs. 74 dmde San Juan del alto pasado 0unla 2001) a la fecha? O Si PAGO EN ALIMENTOS O ESPECIE ESTIMAR CUANTO SERIA EN BOLIVIANOS 1 Si -> POR SI gCudnto? 2 No 106P. {Cudnta tiempo en el alto se dedicd a esta actlvidad desde San Juan del alto pasado Ounla 2001) a la fecha? CANTIDAD UNIDAD DE F RECUENCIA DE TIEMPO XIII. OTRAS ACTIVIDADES QUE RINDEN INGRESO O LEER: Todas las preguntas que le hare se refleren a todas las mlembras del hagar y tadas sus respuatas serdn mantenldas en confldencialidad. © S1 NO SABE EL TOTAL DEL A1210 PREGUNTAR 107R gRealizd usted o alguien de su 108R gCudnta 109P. {Cudnta recibid 110A Nit hogar alguna de las siguientes reclblo en par esa actividad? mera de actividades de manera independiente TOTAL en el veces al desde la fiesta de San Juan del alto ultimo alto? alto pasado (junio 2001) a lafeclta? g Usted o algun miembro se dedico a la Por dia Bs. caza o pesca? l 1 Si Por semana 2 19 For quincena 3 2 No Por mes 4 g Usted a algun miembro se dedlcd a la Por dia Bs. extraccldn o tala de drboles? l 1 Si Por semana 2 19 For quincena 3 2 No (especificar actividad) Por mes 4 {Dleran tierras en alquiler? Por dia Bs. 1 1 Si Por semana 2 19 For quincena 3 2 No Por mes 4 gDieron alguna casa o pleza en alquiler? Por dia Bs. 1 1 Si Por semana 2 19 P01 quincena 3 2 No Por mes 4 gDieran algun vehiculo en alquiler? Por dia Bs. 1 1 Si Por semana 2 19 For quincena 3 2 No Por mes 4 75 ngeran alguna otra casa en alquiler? Por’dia BS. 1 1 Si Por semana 2 19 For quincena 3 2 No Por mes 4 g, Tiene usted a su hogar algun ingresa Por dia Bs. par cancepto de Jubilacianes, Pension, l Bolivida y otras ? Por semana 2 1 Si Por quincena 3 19 For mes 4 2 No (especificar cual) Por afio 5 z, Tiene usted a su hogar algtin ingresa Por dia Bs. par cancepto de remesas defamiliares u 1c otras personas ? Por semana 2 1 Si Por quincena 3 19 For mes 4 2 No (especificar quien) Por aflo 5 gRecibieron alguna ayuda de ESTIMAR EN Bs. Por dia Bs. institucianes del Estada, 0N0 u otras A CUANTO 1 entldada en: alimentacldn, salud a ASCIENDE LA Por semana 2 educacidn? AYUDA Por quincena 3 1 Si Por mes 4 19 For afio 2 No 5 g Tuvieron alguna otra actividad que no Por dia Bs. se haya incluido? 1 1 Si Por semana 2 19 For quincena 3 2 No Por mes 4 Por afio 5 XIV. ACONTECIMIENTOS DURANTE LOS ULTIMOS 12 MESES O ( ENCUESTADOR(A): LEER TODAS LAS O POR CADA SI PREGUNT AR gQué OPCIONES DE ACONTECIMIENTOS Y CIRCULAR hicieron en el hogar para cubrir las gastas LAS QUE SE APLICAN de que tuvieran? 8 g E 1 0 A 5 .§ 3 e 35 5 E 5 «I i g 0 SE ACONTECIMIENTOS 1 Si No a a 5 5 _1 < 2, § 5 1:: 8 s a: 5 s a 8 :a < 7.. V § .2 P "" E ° 3: “g 8. g 11.1 8 "' o E ) 9" D > m < 111P. g Tuva algun heclto adverso lmportante en el hagar desde laflesta de San Juan del alto pasado Ounio 2001) a lafecha? gCudl? O LEER 76 I Disturbias saciales 1 2 Ha habida una muerte de algun mlembra de su hogar desde San Juan del alia 1 pasado a lo echo? 3 Ha tenido algun miembro de su hogar una enferrnedad o accidente grave que le Impidio l trabajar al menos I mes desde lafiesta de San Juan a Iojeclla? 4 Ha habida algdn divorcia a separacion desde 1 San Juan del alto pasado a la techa? 5 0tra(especif1car ) 1 112P. g Tuva una pérdlda en el valor de ma’s de la cuarta parte (25 %) de sus productos agrlcolas desde laflesta de 1 San Juan del alto pasado (junta 2001) a lafeclla? O (POR NO PASAR 115P) 113P. gCudlesfueran las causas de la pérdida? 1 Sequias 2 Inundaciones y/o riada 3 Helada 4 Plagas y enfermedades 5 Los precios bajaron 6 Otro (especificar) 114P. Esta pérdldo afecto a: 1 S610 e1 hogar 2 Mayoria de los agricultores de la comunidad 3 Otros (especificar) 115P. ‘- Tuva uno pérdida en el valor de mos de la cuarta parte (25 %) del ganada u otras animales desde laflesta 1 de San Juan del afio pasado Gunio 2001) a lafeclta? O (POR NO PASAR A 118P) 116P. gCudlesfueran las causas de la pérdida? Sequias 2 Inundaciones y/o riada 3 Helada 4 Plagas y enferrnedades 5 Los precios bajaron 6 Otro (especificar) 117P. Esta pérdida afecta a: 3 Otros (especificar) 1 S610 e1 hogar 2 Mayoria de los que comercializan con animales de la comunidad 77 XV. CREDITOS O LAS SIGUIENTES PREGUNTAS SE REFIEREN A CONOCIMIENTO Y ACCIONES DEL ENTREVISTADO Y TODOS LOS DEMAS MIEMBROS DEL HOGAR (LEER TODAS LAS OPCIONES POR CATEGORIA). 118P. g Algtin miembro ha solicitado 119P. {Rectal 120P. 3 En 121P. 1 En 122P. (Salicit crédita alguna vez en su vido de _? eran crédita que alto que alto d O (LEER DE LA OPCION l A LA 42. alguna vez recibld el recibio el préstomos POR SI SOLICITO PREGUNTAR 119P, de ? primer tiltima dejunia del 120P, EN CASO crédita? crédita? 2001 a 121P Y 122P) DE NO, junio del SALTE A 2002 LA 122P de_? SI SI No ANO ANO SI No NO FUENTES FORMALES (Bancos Comerciales) I Banca Economico 21 1 2 1 2 2 Banco Solidario (Bancosal) 1 2 1 2 ' l 2 3 Banco Ganadera 2l 1 2 1 2 4 Bonca Real 21 1 2 l 2 5 Banca de la Unidn l 1 2 1 2 (incluyendo Credidgil) 2 6 Banco Santa Cruz (Bancruz) l 2 l 2 1 2 7 Banca Hipatecorio 21 1 2 1 2 8 Banco Mercantil (incluyendo 1 l 2 I 2 supegfdcil) 2 9 Banco Nacionol 21 1 2 1 2 I0 Banca de Crédito 21 1 2 1 2 II Banco Biso 21 l 2 1 2 12 Banco extranjero 2l 1 2 1 2 I3 Otra banco 1 gCudl 2 1 2 1 2 _? FONDOS FINANCIEROS PRIVADOS (FFP) 14 F lnonciero Accesa 1 2 l 2 1 2 I 5 Ecafutura 21 1 2 l 2 l6 Fie 21 1 2 l 2 I 7 Caja Las Andes (incluyendo l l 2 l 2 Procrédito) 2 78 18 Fassil I9 Prodern 20 Otrofando financiero privado gCudI ? COOPERA TIVAS QUE PRESTAN DINERO 21 San Martin de Porres 22 F irranciacoop 23 Otra. gCudl ? 7 Otra. gCudl 7 M U TUALES 25 Mutual La Primera 26 Mutual La Paz 27 Otras gCudl ? FUENTES SEMIFORMALES 28 Bancos comunala de Crecer 29 Asoclaciones de Pro Mujer 30 Clare 3I Fonda de la comunidad (F oudeco) 32 Idepro 33 F rJf/Diaconia 34 Sartawl 35 Agrocapital 36 Fades 37 Arm! 79 g ' 38 Proa 21 l 2 1 2 39 Otros bancos comunales 21 l 2 1 2 40 F ondos Rotatorios 2l 1 2 1 2 41 Otra 0N G que da crédiio. 1 1 2 l 2 {Cual 7 2 42 Otrafuente semiformal l {Cudl 2 1 2 l 2 ? ”JP. 3 Algun mianbro ha solicitado 119R gRecibi 1201’. g En 121P. g En 122P. Solicito crédito alguna vez en su vida de _? eron crédito que ailo que ano préstamos © (LEER DE LA OPCION 43 A LA 62. alguna vez recibio el recibio el dejunio del POR SI SOLICITO PREGUNTAR 119P, de 7 primer ultimo 2001 a 120P, EN CASO crédito? crédito? junio del 121P Y 122P) DE NO, 2002 SALTE A tie—7 LA 122P SI SI NO ANO ANO SI N0 N0 FUENTES INFORMALES 43 Un preslamisla local 1 2 1 2 1 2 44 Algun familiar que le presto 1 2 1 2 1 2 dinero 45 Algun amigo que le puede 1 2 l 2 l 2 prestar dinero 46 Pasanaku en efectivo 1 2 l 2 l 2 47 La persona que le da trabajo l 2 l 2 l 2 48 El comprador de la cosecha 1 2 l 2 l 2 49 El que le alquila la tierra l 2 1 2 l 2 50 Alguna otra persona. C at z u 7 l 2 1 2 I 2 51 Otrafuenle informal gCudl 1 2 l 2 l 2 7 FUENTES COMERCIALES @ INCL UIR COMPRAS A CREDI T 0 52 Almacen comercial 1 2 l 2 1 2 53 Casa comercial 1 2 1 2 1 2 54 Tienda l 2 1 2 l 2 55 Pasanaku l 2 l 2 I 2 56 Vendedor o promotor ambulante l 2 1 2 l 2 5 7 Promotor de insumos/ l 2 1 2 l 2 agroservicios 58 Proveedor de mercaderia 1 2 1 2 l 2 59 Otrafuente 1 2 l 2 l 2 80 comercial 60 Comercianies de la feria l 2 1 2 l 2 61 Otrafuenie comercial 2 Cudl l 2 1 2 l 2 ? BANCO ESTATAL 62 Banco Agricola de Bolivia 1 2 l 2 [ ] 1 2 © POR NINGUNA F UENTE PASAR A NINGUNA FUENTE 97 AHORROS VOLUNTARIOS PAG 25 SI EN LA PREGUNTA 122P CONTESTO “NO” PARA TODAS LAS FUENTES (CODIGOS DEL 01 AL 62) PASAR A LA PREGUNTA AHORROS VOLUNTARIOS PAG 25 © INFORMACION SOBRE LOS ULTIMOS CREDITOS SOLICITADOS. 81 EN LA PREGUNTA 122P CONTESTO “NO” PARA TODAS LAS FUENTES (CODIGOS DEL 01 AL 62) PASAR A LA PREGUNTA AHORROS VOLUNTARIOS EN LA PAG 25. SI HA SOLICITADO MAS DE UN CREDITO PARA LA MISMA FUENTE ENTRE IUNIO 2001 Y JUNIO DEL 2002, LAS PREGUNTAS SIGUIENTES SON SOLAMENTE PARA SOLICITUDES DEL ULTIMO ANO. © ANOTAR EL NOMBRE Y EL CODIGO Fuente: F uente: Fucnte: Fuente: DE LAS FUENTES A Cédigo: Cédigo: Cédigo: Cédigo: LAS QUE SOLICITC) CREDITO LA ULTIMA VEZ -) NUMERO DE LA PERSONA Nfiméro: NI’Imero: NI'Imero: NI'Imero: SOLICITANTE (DE MODULO II) -) 123R {A qué distancia de su propiedad CAN DIST CAN DIS CAN DIST CA DIST queda 7 T T T T NT 124R {Cudnio tiempo le toma llegar desde CAN TIEM CAN TIE CAN TIEM CA TIEM su propiedad hasta la insiitucidn / lugar / T PO T MPO T PO NT PO persona? la I? la E [on I", I? (n 125P. {Cuanto soliciio inicialmente para fig este préstamo? 126P. {En quépensaba usar el dinero? l Gastos generales del hogar l l 2 Cuotas escolares, pensiones, miles y 2 2 2 2 otros gastos relacionados 3 Gastos médicos 3 4 Una boda, fiesta de 15 aflos, preste u otra celebracién 5 Para pagar otras deudas 5 6 Para que un miembro de la familia pudiera emigrar 7 Para prestarle a otra persona _ _ b) U) U) A A A A M M M O\ O\ O‘ O\ \J \l \l \) 81 8 Adquisicién de bienes durables para la 8 8 8 8 casa 9 Construccién de vivienda 9 9 9 9 10 Reparar o ampliar la vivienda IO 10 10 10 11 Comprar materiales necesarios para la 11 11 1 I 11 produccién 12 Comprar maquinaria, equipo o 12 12 12 12 herramienta para producir 13 Comprar animales 13 13 13 13 14 Comprar tierra 14 14 14 14 15 Para atender gastos inesperados 15 15 15 15 16 Para pagar mano de obra/ planilla 16 16 16 16 17 Compra de mercaderia para el negocio 17 17 17 17 18 Otro uso (especificar) 127P. gAlflnal, le oiorgaron elpréstamo? 1 Si 9 © PASE A 129P l l l l 2 No 2 2 2 2 128P. gPor quépiensa que no le oiorgaron el crédito? 1 No tenIa que dar en garantia 1 1 1 1 2 No tenIa fiador 2 2 2 2 3 No 10 aceptaron en el grupo de crédito 3 3 3 3 4 No tenIa los documentos de propiedad 4 4 4 4 necesanos 5 Estaba anasado en el pago de un préstamo 5 5 5 5 anterior 6 Dieron malas referencias de 61 6 6 6 6 7 Consideraron que sus ingresos eran 7 7 7 7 muy pocos 8 La institucién se quedé sin fondos 8 8 8 8 9 Otro (especificar) 9 © PASE A AHORROS VOLUNTARIOS PAG 25 © ANOTAR EL NOMBRE Y EL CODIGO F uente: Fuente: F uente: F uente: DE LAS FUENTES A Cédigo: Cédigo: Cédigo: Cédigo: LAS QUE SOLICITO CREDITO LA ULTIMA VEZ 9 NUMERO DE LA PERSONA NI'IInero: NI'Imero: NI'Imero: NI’Imero: SOLICITANTE (DE MODULO II) 9 129P. Alflnal, gqaé cantidad de dinero le 35 SUS Bs $US BS $US Bs. $US prestaron? 130P. {Cudntos dlas pasaron desde que presento la solicitud hasta que le desembolsaron el crédito? dIas dIas d1 as dias 131P. 11.1ng a iiempo el desembolso para el uso que usted lo tenla proyeciado? 82 1 Si © (PASE A LA PREGUNTA 1 . 1 l 1 133P) 2 No 2 2 2 2 132P. gQué hicieron? 1 Nada 1 1 l 1 2 Acudio a un prestamista 2 2 2 2 3 Acudio a un amigo o pariente 3 3 3 3 4 No pudo comprar mercaderia 4 4 4 4 5 No pudo sembrar / cosechar 5 5 5 5 6 Tuvo que cambiar de proyecto 6 6 6 6 7 Otra cosa (especificar) 133P. {Que ofrecio de garantia para este préstamo? © (LEER LAS OPCIONES - MULTIPLE) 1 La iierra 1 1 1 l 2 La cosecha 2 2 2 2 3 Animales 3 3 3 3 4 Un contrato de compra-venta 4 i 4 4 4 5 Otra propiedad 5 5 5 5 6 Lo que iba a comprar con el crédito 6 6 6 6 7 Un vehiculo 7 7 7 7 8 Maquinaria 8 8 8 8 9 Un flador/ codeudor /garante 9 9 9 9 personal I 0 La responsabilidad de un grupo 10 10 10 10 solidario I I Bienes de la casa /muebles / I l 1 1 1 l 1 l electrodomésticos [2 Un cheque 12 12 12 12 I3 Firmar letras de cambio 13 13 13 13 I 4 Deposito a plazofljo 14 14 14 14 I5 Documentos originates de propiedad 15 15 15 15 I6 Nada, solo su repuiacion l6 . 16 16 16 I 7 Dim (especificar) 134P. gQué tasa de inierés le aplicaron? © ANOTE LA TASA DE INTERES EN % % % % % l Diaria l l l l 2 Semanal 2 2 2 2 3 Quincenal 3 3 3 3 4 Mensual 4 4 4 4 5 Anna] 5 5 5 5 6 No sabe 6 6 6 6 7 Otra (especificar) © ANOTAR EL NOMBRE Y EL CODIGO Fuente: Fuente: Fuente: Fuente: DE LAS FUENTES A CédijOZ C6digo: C6digo: C6digo: 83 LAS QUE SOLICITO CREDITO LA ULTIMA VEZ -> NUMERO DE LA PERSONA (DE MODULO II) -) NI'Imero: NI’Imero: NI'Imero: NI'Imero: 135P. {Que plazo le dieron? l Dias 2 Semanas 3 Quincenas 4 Meses 5 Aflos 6 Cuando pudiera pagar GUIAUJND— QMQWN-fl O‘MAWNU‘ QMAth—I 7 Otra(especif1car) 136R gCudl era la forma de pago que le dieron para we préstamo? 1 Cada semana 2 Cada dos semanas 3 Dos veces a1 mes 4 Una vez a] mes 5 Cada tres meses 6 Una sola cuota al final OMAWN-fl @MAMN-fl O‘MAWN-fl QMAUJNH 7 Otra forma (especificar) 1371’. {De cudnto le salio cada caota? Bs $US Bs $US Bs $US Bs. SUS 138P. Para poder pagar las cuotas delprésiamo de © (LEER OPCIONES, MULTIPLE) I Han sido siempre suflcientes los ingresos de la actividad relacionada con el préstamo? 2 Algunas veces ie ha tocado trabajar mas para poder pagar 3 Alguna vez ha pagado con ahorros que tenia 4 Alguna vez Ira pagado con ingresos de otra actividad no relacionada con el présiamo 5 Ha tenido que vender alguna casa 0 animal para poder pagar 6 Ha tenido que pedirprestado 7 Ha pedido ayuda a familiares o amigos en Bolivia 8 Ha pedido ayuda a familiares o amigos fuera de Bolivia 84 1391’. {Ha pagado atrasado alguna vez? 1. SI 1 l 1 I 2. No ........ © PASE A LA PREGUNTA 2 2 2 2 I42P 3. Todavia no 1e ha tocado pagar 3 3 3 3 © PASE A LA PREGUNTA 142 “UP. La vez que pago mas tarde, gcudntos dias se atraso en pagar7 I. NI'Imero de dias que pago tarde I I I I dias dias dias dias 2. No ha pagado todavIa: Dias de retraso 2 2 2 2 en total estimando Ios dias dias dias dias dias que Ie faltan para pagar © ANOTAR EL NOMBRE Y EL CODIGO Fuente: Fuente: Fuente: Fuente: DE LAS FUENTES A codigo: C6digo: C6digo: C6digo: LAS QUE SOLICITO CREDITO LA ULTIMA VEZ 9 NUMERO DE LA PERSONA (DE NI’Imero: NI'Imero: Nfimero: NI'Imero: MODULO II) 9 141P. gQué hizo al respecto? © (NO LEER- MULTIPLE) I No pagué nada 1 1 I I 2 Pagué una parte 2 2 2 2 3 Refinancié 3 3 3 3 4 Pagué con otro préstamo 4 4 4 4 (,De d6nde? 5 Di lo que tenia en garantia 5 5 5 5 6 Vendi tierra, animales, carro, etc. 6 6 6 6 para pagar 7 Pagué atrasado 7 7 7 7 8 Me perdonaron 1a deuda 8 8 8 8 9 Voy a pagar en el futuro 9 9 9 9 10 Otro (Especificar) 142P. Ahora que usted y los miembros del © (LEA TODA LA PREGUNTA PARA CADA hogar ya iienen experiencia con _, OPCION) MARQUE UNA RESPUESTA PARA {Esta usted contento(a), indiferente o TODAS LAS OPCIONES DONDE desconienio(a) con 7 l = CONTENTO, 2 = INDIFERENTE , 3 = DESCONTENTO Co Ind De Co In De Co Ind De Co In De nt sc nt d sc nt sc nt d sc 1 El monto que le prestan l 2 3 I 2 3 1 2 3 I 2 3 2 Las plazas de los préstamos I 2 3 I 2 3 l 2 3 I 2 3 3 Las tasas de interés I 2 3 I 2 3 1 2 3 I 2 3 4 El sistema de pagos que le dieron I 2 3 l 2 3 l 2 3 1 2 3 5 La facilidad de los trdmites 1 2 3 1 2 3 I 2 3 1 2 3 85 I 6 La garantia que lepiden I 2 3 2 3 2 3 1 2 3 7 Eltratoquelebrindaelquele l 2 3 2 3 2 3 l 2 3 presto AHORROS VOLUNTARIOS. © LEER: Todas las respuestas que nos de serdn mantenidas en ABSOL UTA CONFIDENCIALIDAD 143P. g Tienen ustedes... 7 © (LEER CADA UNA DE LAS SIGUIENTES OPCIONES) SI NO gEn cudl7 (soLo FORMAL) I Cuentas en un banco, FFP a mutual 2 Ahorros voluntarios en una cooperativa 3 Ahorros voluntarios en una asociacion o banco comunal 1WLEERCM quépodria hacerfrente a una emergencia? © SI N0 I Animaies que puede vender 2 Terreno que puede vender 3 Bienes de la casa que puede vender 4 Una casa que puede vender 5 Tubérculos o granos almacenados 6 Material de construccion que pueda vender NNNNNN 7 Otro (especificar) XVI. VIVIENDA © ENCUESTADOR: PREGUNTAR Y CIRCULAR EL CODIGO QUE CORRESPONDE EN CADA CATEGORIA 1455- La vivienaa del [1080' 151P. gCual es la 158A gEl Sistema de eliminacién de es """ procedencia del agua basura es... 7 utilizada para beber y cocinar? 1 Casa Independiente 1 Cafleria de red 1 A1 110 2 Departamento 2 Pileta pI'Iblica 2 A an cenizal basural 3 Habitaci6n(es) 3 C art'd 3 C b suelta(as) arro rep 1 or arms asureros 4 Choza, Pahuichi 4 P020 0 noria con bomba 4 La entierran 5 Vivienda improvisada 5 P020 0 noria sin bomba 5 La queman 146P. La vivienda que ocupa 6 Rio /vertiente/ acequia 6 Otro (especificar) el hogar es ............. _— I Propia con papeles 7 Lago /laguna/ curiche 8 Otra (especificar)___ 159R gPrincipalmente qué tipo de 2 Propia sin papeles 86 I . 152P. ngmo se distribuye combustible a energia utiliza para 3 Alquilada el agua para beber y cacinar? cacinar? 4 En contrato anticrético 1 Por cafieria dentro de la 1 Leila Vivienda 5 Cedida por parentesco 2 Por caileria fuera de la Vivienda 2 Guano / bosta / taquia 6 Cedida por servicios 3 No se distribuye por cafleria 3 Kerosén 7 Cedida de otra manera 1531’. g Tiene bano, water a letrina? 4 Gas garrafa 0 per cafieria 8 Otro (especificar) lSi 5 Electricidad 2 No SALTE A 156P. 6 Otrflespecificar) 147P. gCudl es el material mtis utilizado en las paredes de la vivienda? 154P. {El baiio, miter o letrina es usatio ....... I Adobe 0 tapial 1 S610 para su hogar 2 Ladrillos / bloques de cemento / hormigon 2 Compartido con otras hogares 160R gCudntas cuartos a habitacianes ocupa su hogar, sin contar el batia ni la cacina7 155P. gEl baiio, miter o 1MP. gDe esos cu r SH .1 r para dormir? .- 3 Tabique / quinche letrina tiene desague a. ...... 4 Piedra 1 alcantarillado? 5 Madera 2 camara séptica? 162p. g Tiene un cuarto solo para 6 Cafia/Palma/troncos 3 pozo ciego? cacinar.’ 7 Otro 4 la superficie calle/ rio? 1 Si 7 es eCIficar) 148P. Ttenen revaque las paredes interiores de la 2 N o Vivienda? 5 Otro 1 Si (especificar) 163P. gCudnda algun miembro de su 2 No hogar se enferma 6 accidenta, donde acuden par la general7 149P. Cutil es el material . . . mas utilizado en el techa de 156Pé1écfrgza fizrzumminar l HOSPMI publico la vivienda7 , P su pudenda? 2 Centro de salad 1 Calamina o pIancha 1 Si 3 Puesto de salud 2 Tejas (cemento 4 Caja Nacional de Salud u otra larcilla / 2 No Caja (CNS) fibrocemento) 5 Clinica, hospital privado 3 Losa de hormigén 157P. gEn su hogar 6 Consultorio médico particular armado tienen ..... 4 Paja/cafla/palma . 7 . lbarro 1 radio. 7 FarmaCIa 5 Otro (especificar) 2 televisor? 150P. Cua'l es el material 8 Kallawaya, jampiri, yatiri, curandero o médico tradicional mas utilizado en las pisos 3 bicicleta? de la vivienda? 1 Tierra 4 motocicleta? 2 Tablén de madera 5 vehiculo automotor? 9 En su casa (medicina tradicional) 3 Parquet / machimbre 6 refrigerador? 1MP. gDel tiltimo itiia(a) nacida viva dande acurria elparto7 87 I 4 Alfombra / tapizén 7 teléfono fijo? 1 En un establecimiento de salud 5 Cemento 8 teléfono celular? 2 En un domicilio 6 Mosaico /baldosas/ 9 bomba electrica de agua? . 3 En otro lugar ceram1ca 7 Ladrillo 10 count; a gas 0 3 165A gQuién atendia elparto7 kerosene. II ropero 6 c6moda 6 catre? l Médico 2 Enfermera/ Auxiliar de enferrneria 8 Otro (especificar) 3 Partera —— 4 La misma mujer 5 Otra persona 166R A {ue distancia queda su Vivienda de 7 167P. Cuantas minutas tardarla en llegar en el KILO © LEER DE 1 A 4 METR CUADR ME- media tie transporte que OS AS TROS utiliza normalmente desde su vivienda a 7 1 La carretera, calle pavimentada o empedrada mas cercana 2 El carnino no pavimentado transitable todo e1 0230 3 El lugar mas cercana dontle pueden tamar an medio de transporte ptiblico 4 El mercado aferia mas cercana HHzMM HORA DE FINALIZACION AGRADECER Y ENTREGAR EL REGALO : 88 BIBLIOGRAPHY 89 Abdulai, A., A. CroleRees (2001). "Determinants of income diversification amongst rural households in Southern Mali." Food Policy 26: 437—452. Barrett, C. B., T. Reardon, P. Webb. (2001). "Nonfarm income diversification and household livelihood strategies in rural Africa: concepts, dynamics, and policy implications." Food Policy 26: 315—331. Berdegué, J., E. Ramirez, T. Reardon, G. Escobar (2001). "Rural Non-farm Employment and Incomes in Chile." World Development 29(3),: 411-425. Berdegué, J., T. Reardon, G. Escobar. (2000). Empleo e Ingreso Rurales No Agricolas en Américflana y el Caribe. Development of the Rural Economy and Poverty Reduction in Latin America and the Caribbean, New Orleans, Louisiana, Inter- American Development Bank (IDB). Caillavet, F ., H. Guyomard, R. Lifran, Eds. (1994). Agricultural Household Modelling and Famin Economics. Developments in Agricultural Economics, Elsevier. Carafa, Y., V. del Carpio, B. Pinto, A. Rochkovski, M. Udaeta, Eds. (1993). “Genero y Desarrollo: Las Mujeres del Campo y la Produccion Agricola”. RURALTER. Revista de Desarrollo Rural Altemativo, CICDA. Nro. Especial 11 & 12: 19-46. Castro, J. J. (2005). Bolivia Productiva y la ENDAR. Pro Campo 1(94): 16-18. CIES, I. (2002). Estudio de Linea Base: Caracteristicas de los Hogares Rurales en el Altiplano, Valles y Yungas, Afio Agricola 2001-2002. La Paz, Bolivia, CIES Intemacional: 1-91. Comision Europea (2000). La economia rural en Bolivia: Estructura de empelo, composicién de ingresos e integracion a1 mercado. Apuntes técnicos Unide de segu_ridad alimentaria. La Paz, Bolivia. Corral, L., T. Reardon (2001). "Rural Non-farm Incomes in Nicaragua." World Development 29(3): 427—442. da Silva, J. G., E. De] Grossi (2001). "Rural Non-farm Employment and Incomes In Brazil: Patterns and Evolution." World Development 29(3): 443-453. de Janvry, A., E. Sadoulet (1995). Quantthative Development Policy Analysis. Baltimore: Johns Hopkins University Press. de Janvry, A., E. Sadoulet (2001). "Income Strategies Among Rural Households in Mexico: The Role of Off-farm Activities." World Development 29(3): 467-480. 90 Deaton, A. (1997). The Analysis of Household Surveys: A Microeconometric Approach to Development Policy. Baltimore, MD, Published for the World Bank by Johns Hopkins University Press. Dirven, M. (2004). El empleo rural no agricola y la diversidad rural de América Latina. Revista deit CEPAL: 49-69. Elbers, C., P. Lanjouw (2001). "Intersectoral Transfer, Growth, and Inequality in Rural Ecuador." World Development 29(3): 481-496. Enciclopedia de Bolivifia (2002), Oceano Grupo Editorial S.A., Barcelona, Espafia. Escobal, J. (2001). "The Determinants of Non-farm Income Diversification in Rural F Peru." World Develgament 29(3): 497-508. ‘ Gennrich, N. (2002). The impact of microenterpnises on poverty reduction in rural areas: The case of El Quiché (Guatemala). Deutsche Tropentag, Germany. Glick, P., D. E. Sahn (1997). "Gender and Education Impacts on Employment and Earnings in West Afi'ica: Evidence from Guinea." Economic Development and c: Cultural Change: 794-823. Jimenez, W., S. Lizarraga (2003). Ingresos y Desigualdad en el Area Rural de Bolivia, Unidad de Analisis de Politicas Sociales y Economicas. Analisis Economico- UDAPE. Kennedy, P. (2003). A Guide to Econometrics. Cambridge, MA, MIT Press Lanjouw, J ., P. Lanjouw (2001). "The rural non-farm sector: issues and evidence from developing countries." Agg'cultural Economics 26: 1-23. Lanjouw, P. (2001). "Non-farm Employment and Poverty. in Rural El Salvador." World Development 29(3): 529-547. Lizarraga, K. (2001). Educacién técnica en Bolivia: efectos sobre los ingresos. Revista inflisis Economico. UDAPE, La Paz, Bolivia. Lofgren, H., S. Robinson (1999). To Trade or Not to Trade: Non-Separable Farm Household Models in Partial and General Equilibrium. IFPRI, TMD Discussion Paper #37. Washinton, D.C. Matshe, I., T. Young (2004). "Off-farm labour allocation decisions in small-scale rural households in Zimbabwe." Agricultural Economics 30(3): 175-186. Morales, R. (2000). Bolivifloliticfiiconémicgfieografia y Pobreza. La Paz, Bolivia. 91 Pacheco, P., E. Ormachea (2000). Campesinosmatrones y obreros agricolas: un_a aproxingcion a_la_s tendencias del empleo y los ingresos rurales en Bolivia. CEDLA. Santiago, Chile Paz, D. (1997). Cuestion Agram BolivianLPresente v Futuro. Secretaria Ejecutiva PL. 480 Titulo III. La Paz, Bolivia Pindyck, R. S., D. L. Rubinfeld (1991). Econometric Models and Economic Forecasts. New York, McGraw-Hill. PRSP (2001). Poverty Reduction Strategy Paper,. La Paz, Bolivia, Presidency of the Government of Bolivia: 1-224. Reardon, T. (1998). Rural Non-farm Income in Developing Countries. The State of Food and Agriculture, Rome. Reardon, T., J. Berdegue, G. Escobar (2001). "Rural Nonfarm Employment and Incomes in Latin America: Overview and Policy Implications." World Development 29(3): 395-409. Reardon, T., E. Taylor (1996). "Agroclimatic Shock, Income Inequality, and Poverty: Evidence from Burkina F aso." World Development 24(5): 901-914. Serumaga-Zake, A. E., W. Naude (2003). "Private Rates of Return of Education of Africans in South Africa for 1995: A Double Hurdle Model." Development Southern Africa 20(4): 515-527. Taylor, E., A. Yunez-Naude (2000). "The Returns from Schooling in a Diversified Rural Economy." American Jouflal of Agg'cultural Economics 82: 287-297. UDAPE (2000). Bolivia: PrcysgectivaEconomiga y Social 2000-2010. La Paz, Bolivia, Programa de las Naciones Unidas para el Desarrollo. Urioste, M. (1989). Efectos de lafiPolitica Economica Neoliberal del D.S. 21060. Resistencia Campesina, La Paz, CEDLA. Wooldridge, J. M. (2002). Econometric Aaalysis of Cross Section and_Panel Data. Cambridge, MA, MIT Press. Yuflez-Naude, A., E. Taylor (2001). "The Determinants of Non-farm Activities and Incomes of Rural Households in Mexico, with Emphasis on Education." World Development 29(3): 561-572. 92