Can off farm employment affect the privatization of social safety net? The case of self-employed farm households

This study uses a two-stage econometric framework with farm household level data to investigate whether off-farm work of operators and spouses influences healthcare expenditures and retirement savings. Results indicate that agricultural policy discourages off-farm work by farm operators and spouses. However, off-farm work decisions of farm couples significantly decrease healthcare expenditures and increase retirement savings of farm households in the US. The effect of farm spouse’s off-farm employment on household retirement saving is more pronounced. These conclusions can extend to middle-income countries where off-farm work may enable farmers to afford better healthcare and retirement pension plans.     

Impact of off-farm income on food security and nutrition in Nigeria

While the poverty implications of off-farm income have been analyzed in different developing countries, much less is known about the impact of off-farm income on household food security and nutrition. Here, this research gap is addressed by using farm survey data from Nigeria. Econometric analyses are employed to examine the mechanisms through which off-farm income affects household calorie and micronutrient supply, dietary quality, and child anthropometry. We find that off-farm income has a positive net effect on food security and nutrition. The prevalence of child stunting, underweight, and wasting is lower in households with off-farm income than in households without. Using a structural model, we also show that off-farm income contributes to higher food production and farm income by easing capital constraints, thus improving household welfare in multiple ways.     

Labor market participation of Chinese agricultural households: Empirical evidence from Zhejiang province

This work is devoted to the analysis of the different labor market participation regimes of Chinese farm households over the reform process in the 1980s and 1990s. Using household data over the period 1986–2002 from the province Zhejiang, we apply a multinomial logit model to empirically examine household, farm, and regional characteristics affecting the probability that farmers participate in one of four alternative labor market regimes. As generally accepted, off-farm participation is the dominant form of farm households’ labor market participation. But rural households show additionally a significant impact on rural employment mainly linked with non-agricultural household business. Results suggest that labor market decisions are significantly related to several family, farm, and village characteristics. In particular, we find education to be a key determinant of participation. Furthermore, results point to a higher probability of female household members to take up off-farm work.     

The effect of household wealth on the adoption of improved maize varieties in Zambia

Production and price risks that could render input use unprofitable sometimes prevent rural households from benefiting from input technological change. The household’s ability to cope with such risks and hence benefit from input technological change is often positively related to its wealth or stock of productive assets. Empirical evidence, however, suggests a non-linear relationship between wealth and adoption of new agricultural technologies so that within a rural community, households on the lower wealth continuum behave differently from those on the higher level. Using farm level data collected from 300 randomly selected households in three districts of Zambia in 2004/2005 crop season, this paper first stratifies households into poorly- and well-endowed households based on their access to productive assets and estimates separate double-hurdle models for the adoption of improved, high yielding maize (IHYM) varieties for each group. The results show that factors influencing the adoption and use intensity of IHYM varieties differ between the two groups. This draws attention to the need for recommending wealth group-specific interventions to increase the adoption and use intensity of such varieties and their subsequent impacts on food security and general livelihoods of the households. The explicit testing for the possibility that differences in household wealth affect the way in which other variables influence adoption decisions is the paper’s unique contribution to the adoption literature.     

The effect of prime age adult mortality on household composition and consumption in rural Ethiopia

Using panel data from Ethiopia covering 1994–1997, we estimate the impact of prime age adult mortality on household composition, household expenditures and dietary diversity. We employed propensity score matching with a difference-in-difference estimator to control for endogeneity of mortality to the outcomes of interest. Households losing a productive adult did not replenish the lost labor, regardless of economic status, sex or status of the deceased adult. With the exception of non-poor households, adult mortality resulted in increased dependency ratios, but did not adversely affect households’ expenditure patterns (total, food and non-food expenditures) regardless of the sex and position of the deceased and the economic status of the households. Although food expenditures were protected, a decline in dietary diversity, especially among the poorest households, reflected increased nutrition insecurity associated with adult mortality.     

Breakfast,lunch, and dinner expenditures away from home in the United States

This study investigates the differentiated effects of economic and socio-demographic variables on food away from home (FAFH) expenditures by type of meal among different types of households in the United States. Using data from the 2008 and 2009 Consumer Expenditure Surveys, the systems of expenditures on breakfast, lunch, and dinner are estimated with a multivariate sample selection procedure. Statistical significance of error correlations among equations justifies estimation of the sample selection systems. Income, work hours, race, education, geographic region, and household composition are important determinants of FAFH expenditures. Income contributes to FAFH expenditures of all meal types implying that the future of FAFH industry is tied to macroeconomic conditions. More education is associated with increased expenditures for FAFH lunch and dinner. Effects of the Supplemental Nutrition Assistance Program (SNAP) are negligible.     

How does population density influence agricultural intensification and productivity? Evidence from Malawi

This article uses nationally representative household-level panel data from Malawi to estimate how rural population density impacts agricultural intensification and household well-being. We find that areas of higher population density are associated with smaller farm sizes, lower real agricultural wage rates, and higher real maize prices. Any input intensification that occurs seems to be going to increasing maize yields, as we find no evidence that increases in population density enable farmers to increase gross value of crop output per hectare. We also find evidence that households in more densely populated areas increasingly rely on off-farm income to earn a living, but there appears to be a rural population density threshold beyond which households can no longer increase off-farm income per capita.     

Income diversification and entry barriers: evidence from the Tigray region of northern Ethiopia

Farm households diversify their income sources into off-farm wage employment motivated by low farm income and availability of surplus family labor, whereas they enter into off-farm self employment to earn an attractive return. Farm households have upward-sloping, although inelastic, off-farm labor supply curves. Therefore, increasing the availability of off-farm activities and improving the wage rate received by farm households can expand the economic activity of the Tigray Regional State. Due to entry barriers, relatively wealthy farm households may dominate the most lucrative rural non-farm activities such as masonry, carpentry and petty trade. Hence the underlying factors that hinder participation in non-farm activities such as credit constraints and lack of skill may have to be addressed through the provision of credit and technical training for the poor.     

Farm production diversity is associated with greater household dietary diversity in Malawi: Findings from nationally representative data

Farm production diversity has the potential to influence the diversity of household diets, an important nutrition outcome associated with the nutrient adequacy of diets and the nutritional status of individuals. Yet, little empirical research has assessed the relationship between farm diversity and diet diversity or the plausible causal mechanisms that may operate between these two constructs. This research examines cross-sectional data from the Malawi Third Integrated Household Survey (IHS3), a nationally representative sample of farming households in Malawi, implemented from March 2010–March 2011 as part of the World Bank Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA). These data were used to determine the relationship between farm production diversity and household dietary diversity, and to identify determinants of this relationship. Two indicators of dietary diversity, a modified Household Dietary Diversity Score (HDDS), and the Food Consumption Score (FCS), were calculated along with three indicators of farm production diversity including the Simpson’s Index, a metric accounting for both species richness and evenness. In multiple regression analyses, adjusting standard errors for the complex survey design of the IHS3 and controlling for the effects of several covariates on household dietary diversity, farm production diversity was consistently positively associated with dietary diversity (P < 0.0001). The association of increased farm diversity as measured by a combined crop and livestock measure on dietary diversity was significantly greater in woman-headed households compared to those headed by men (HDDS: P = 0.008; FCS: P = 0.076). The positive association of farm diversity with dietary diversity was also greater in wealthier households (P < 0.05). Consumption of legumes, vegetables and fruits was especially strongly associated with greater farm diversity. More diverse production systems may contribute to more diverse household diets. However, this relationship is complex; it may be influenced by gender, wealth, control of household decisions, the relative market-orientation of a household’s agricultural production, and the specific nature of farm diversity.     

Non-farm work and food security among farm households in Northern Ghana

This paper examines the impact of non-farm work on household income and food security among farm households in the Northern Region of Ghana. We analyze the impact by employing propensity score matching method that accounts for self-selection bias. The matching results show that participation in non-farm work exerts a positive and statistically significant effect on household income and food security status, supporting the widely held view that income from non-farm work is crucial to food security and poverty alleviation in rural areas of developing countries.     

Measuring Neighborhood Investments: An Examination of Community Choice

Community choice is a very important household decision, since it represents an investment in community attributes that can have a significant effect on the quality of life of all household members, particularly by influencing the future prospects of children. In this paper, we examine the housing and community choices of migrants to and within Los Angeles County identified in the 1990 5% public-use sample of the Census. Controlling for income, we find that expenditures on housing structure are quite similar across races. However, controlling for income, black and Hispanic households consume significantly less in community attributes than white households.     

First of the month effect: Does it apply across food retail channels?

In this study we use detailed daily scanner data on household food purchases to examine monthly food expenditure patterns across food retail channels. We compare food expenditure patterns in high and low-income households comparing those where Supplementary Nutrition Assistance (SNAP) is received in the first 10 days of the month versus households which receive SNAP over the first 15 days of the month. We find that food expenditure patterns vary systematically across the month within different retail channels by income and SNAP payment schedules. Low-income households in early SNAP distribution areas decrease their grocery and mass/club/superstore expenditures at the end of the calendar month and supplement this decrease with increased food expenditures in convenience stores and food away from home. Households in staggered SNAP payment areas show far fewer systematic patterns given the more distributed payment system.     

Food aid targeting in Ethiopia: A study of who needs it and who gets it

The need for systematic, empirical analysis of food aid targeting and impacts is overwhelming, especially given the large numbers of people concerned and volume of funds allocated to the problem of feeding Ethiopia's food insecure. This research examines the efficiency of food aid targeting in rural Ethiopia based on empirical evidence from a nationally representative survey of 4166 farm households.A key finding of the study is that there is no significant association between household food insecurity (vulnerability) and food aid receipts—a result of high errors of exclusion and inclusion at both the wereda and household levels. Four factors are identified as causes of the high level of targeting error: (1) the primary beneficiaries of food aid programs are found to be households at the extremes in terms of food availability: those with the least and those with the most food available; (2) a disproportionate number of female and aged heads of households received food aid, irrespective of their food needs; (3) an inability of the food aid system to reach households outside of the historically deficit areas; and (4) a disproportionate concentration of food aid in the region of Tigray.     

Household-level determinants of adoption of improved natural resources management practices among smallholder farmers in western Kenya

Integrated natural resources management (INRM), of which integrated soil fertility management (ISFM) is a component, offers considerable promise for increasing food production in Kenya. It nonetheless remains unclear whether ISFM/INRM techniques lend themselves easily to adoption by smallholder farmers. Using panel data collected in western Kenya in 1989 and 2002, this study finds that resource constraints limit many farmers’ adoption of ISFM/INRM techniques. The size of the farm owned by a household, the value of its livestock, off-farm income, family labor supply, and the educational attainment and gender of the household head all had a significant positive effect on the likelihood of adoption. Similar factors were found to be statistically significant in discouraging abandonment of the practices under study. There thus seem to exist reinforcing feedback between investments in soil fertility management and household wealth, as measured by asset endowments. Our findings raise important questions as to whether ISFM and related techniques are really affordable to poorer smallholder farmers.     

Impact of tissue culture banana technology on farm household income and food security in Kenya

While tissue culture (TC) technology for vegetative plant propagation is gradually gaining in importance in Africa, rigorous assessment of broader welfare effects for adopting smallholder farm households is lacking. Using survey data and accounting for selection bias in technology adoption, we analyze the impact of TC banana technology on household income and food security in Kenya. To assess food security outcomes, we employ the Household Food Insecurity Access Scale (HFIAS) – a tool that has not been used for impact assessment before. Estimates of treatment-effects models show that TC banana adoption, combined with improved crop management, causes considerable increases in farm and household income. Technology adoption also reduces relative food insecurity in a significant way. These results indicate that TC technology can be welfare enhancing for adopting farm households. Adoption should be further promoted through upscaling appropriate technology delivery systems.     

Spatial patterns of rural poverty and their relationship with welfare-influencing factors in Bangladesh

This study determines the spatial variation of rural poverty in Bangladesh and its relation to people’s livelihood assets affecting their ability to procure food. We estimated household income for over 1 million census households using a predictor model based on a nationally representative sample survey data set. We computed and mapped poverty indices for 415 rural subdistricts revealing distinct areas with high poverty incidence that correspond with ecologically depressed areas. However, other livelihood-influencing factors such as education, accessibility and services are significantly correlated with poverty. This indicates the need for continued focus on providing education and access to income-generating opportunities so that the poor can better meet their food needs. Geographically weighted regression analysis indicated spatial differences in the relative importance of various poverty-influencing factors. Multivariate clustering of the local parameter (β) estimates of the determinant factors revealed distinct spatial relationships, which have implications on poverty alleviation interventions specific to the different regions.     

Does farm structure affect rural household incomes? Evidence from Tanzania

Many African countries have recently experienced rapid growth in the numbers of medium- and large-scale farms. These developments have generated considerable speculation about the impacts of farmland concentration and inequality on smallholder households and communities. This study exploits inter-district variation in farm landholding patterns in Tanzania to determine how differences in localized farmland structure affect rural household incomes using nationally representative household panel survey data. Because farm structure is a multifaceted concept, five alternative indicators of farmland structure are defined for 142 districts in Tanzania: (i) the Gini coefficient; (ii) skewness; (iii) coefficient of variation; (iv) share of controlled farmland under medium-scale farms; and (v) share of controlled farmland under large farms. These alternative farm structure variables are included in models of rural household income to test their effects after controlling for available household and community covariates. The study highlights four main findings. First, most indicators of farmland concentration are positively associated with rural household incomes. Second, household incomes from farm and non-farm sources are positively and significantly associated with the share of land in the district controlled by farms in the 5–10 and 5–20 ha category. Third, these positive spillover benefits are smaller and less statistically significant in districts with a relatively high share of farmland controlled by farms over 20 ha in size. Fourth, poor rural households are least able to capture the positive spillovers generated by medium-scale farms and by concentrated farmland patterns.     

Household Behavior with Imperfect Labor Markets

A household model with differential asset endowments and idiosyncratic transactions costs in accessing labor markets is developed to (1) explain membership of farm households to alternative labor regimes (sellers, employers, or self-sufficient in labor), (2) test for recursivity between production and consumption decisions selectively by labor regime, and (3) identify the determinants of differential labor productivity across labor regimes. The model is applied to a 1994 household survey of the Mexican land reform sector.     

Are SNAP benefits adequate? A geographical and food expenditure decomposition

The Supplemental Nutrition Assistance Program (SNAP) provides resources to supplement household food expenditures in order to achieve a nutritious diet. Determining the amount of support required - or extent of food expenditure poverty -- entails comparing available resources for food to a nutrition-determined threshold. Clearly the value of the threshold will affect the degree of food expenditure poverty. If the threshold value is inaccurate, the calculated degree of poverty will be inaccurate. USDA uses a threshold for setting SNAP benefits that does not vary geographically or temporally, so consequently (food expenditure) poverty may be understated or overstated in different regions and time periods. This article compares food expenditure poverty estimates for SNAP participants when geographical differences in the threshold are ignored versus not ignored. In addition, the article decomposes household food expenditures into Food-Away-From-Home (FAFH), Food-at-Home (FAH), personal funded FAH, and SNAP funded FAH in order to assess the degree to which each of these contribute to reducing food expenditure poverty. The general findings are that all food expenditure poverty measures are worse when geographical differences are taken into account. In addition, the analysis shows that FAH expenditures, and in particular SNAP FAH expenditures, contribute the most to reducing food expenditure poverty in SNAP households. The policy implications are that food expenditure poverty is currently underestimated in the US by ignoring geographical differences in thresholds, but the food expenditure poverty would be even worse without SNAP benefits. Geographical adjustments to the national threshold could help reduce food expenditure poverty across regions.     

Compounding food and income insecurity in Yemen: Challenges from climate change

This paper provides a model-based assessment of local and global climate change impacts for the case of Yemen, focusing on agricultural production, household incomes and food security. Global climate change is mainly transmitted through rising world food prices. Our simulation results suggest that climate change induced price increases for food will raise agricultural GDP while decreasing real household incomes and food security. Rural non-farm households are hit hardest as they tend to be net food consumers with high food budget shares, but farm households also experience real income losses given that many of them are net buyers of food. The impacts of local climate change are less clear given the ambiguous predictions of global climate models (GCMs) with respect to future rainfall patterns in Yemen. Local climate change impacts manifest itself in long term yield changes, which differ between two alternative climate scenarios considered. Under the MIR scenario, agricultural GDP is somewhat higher than with perfect mitigation and rural incomes rise due to higher yields and lower prices for sorghum and millet. Under the CSI scenario, positive and negative yield changes cancel each other out. As a result, agricultural GDP and household incomes hardly change compared to perfect mitigation.