The role of nonfarm income in coping with the effects of drought in southern Mozambique

To reduce their dependence on subsistence agriculture, farm households in rural Africa may diversify their income sources by participating in the nonfarm sector. In years of drought, nonfarm income can also be part of the coping strategies. A multivariate sample selection model was used to analyze three years of data from a nationally representative household survey in Mozambique. The analysis was guided by the following three questions. During a drought year: (1) Do households increase their participation in nonfarm activities? (2) Are poorer households as likely as others to participate in and benefit from nonfarm activities? and (3) Which factors are associated with higher nonfarm incomes? The results suggest that households are more likely to engage in at least one nonfarm income‐generating activity during a drought year. Although poorer households are more likely to engage in nonfarm activities, they are less likely to participate in nonfarm activities of high return. The results suggest that policies reducing entry barriers (e.g., improved road infrastructure, micro‐credit schemes, and livestock promotion programs) and increasing education levels can facilitate income diversification, thus allowing rural households to better cope with the effects of drought. When designing polices, care must be taken to avoid exacerbating income inequality by targeting measures toward poorer and female‐headed households.     

Income Diversification of Rural Households in China

This article examines how different patterns of farm‐level diversification affect the income levels of rural households in China. Using quantile regression analysis of data from a rural household survey, the empirical results exhibit significant differences in diversification effects across rural income strata and various structural characteristics. Diversification, especially involving nonfarm employment and migration, brings a monetary premium to low‐income rural families and an income discount to high‐income families. The policy implications suggest the encouragement of labor‐intensive enterprises in rural areas and improvement of labor quality through rural education and training programs.     

How has microcredit supported agriculture? Evidence using panel data from Bangladesh

Improving agricultural productivity has received a greater attention in recent years amid concerns about rising food insecurity, population pressures, and climate change. Many believe that better access to institutional credit, spanning microcredit as well as commercial and agricultural banks, can help rural households smooth risks, and access inputs and other technology to modernize agriculture and improve farm/nonfarm linkages. We use recently augmented household panel data spanning over 20 years in Bangladesh to examine the effects of rural credit expansion (both microcredit and formal bank channels) on outcomes for agricultural households. We find that microcredit has benefited households with lower landownings, raising agricultural income from activities such as livestock rearing that require less land, as well as nonfarm income diversification for all households, but with the strongest effect for landless or near‐landless households. We do not find effects of microcredit on crop income, but do, however, find that reported supply‐side credit constraints significantly lower crop income. Borrowing by both men and women has contributed to nonfarm income growth for marginal farmers, but only men's borrowing has contributed to nonfarm income growth among higher landowning groups.     

Income distribution in rice–growing villages during the post-Green Revolution periods: the Philippine case, 1985 and 1998

This paper aims to examine changes in household income sources and its impact on household income distribution in the post‐Green Revolution periods in 1985 and 1998 in the rural Philippines. We found that there has been a structural shift of household income away from farm in favor of nonfarm labor income sources. This finding indicates that rural development is being led by nonfarm sectors. Such a shift has resulted in an increase in household income inequality as the distribution of nonfarm income has become less equal over time and was markedly more unequal than that of farm income in 1998.     

Rural nonfarm activities and agricultural crop production in Nigeria

Although most rural households are involved in the farm sector, the nonfarm sector has grown significantly in recent decades, and its role in rural development has become increasingly important. This article examines the effect of participation in nonfarm activities on crop expenses of farm households in Nigeria. The relationship is modeled using a nonseparable agricultural household model that suggests that participating in nonfarm activities can relax the credit constraints facing farm households and reduce risk thereby helping households improve farm production and smooth consumption over time. The results show that participation in nonfarm activities by Nigerian farmers has a positive and significant effect on crop expenses and in particular on payments for hired labor and inorganic fertilizers. Separate analysis of the six geopolitical zones in Nigeria indicates that it is in the South-South and South-East zones where nonfarm participation appears to induce more hiring of labor. The results support the hypothesis that nonfarm participation helps relax liquidity constraints but suggests how that liquidity is used is zone-specific. In general, the results also indicate that liquidity is used more to pay for inputs into staple production as opposed to cash crops.     

Consumption inequality between farm and nonfarm households in Taiwan: a decomposition analysis of differences in distribution

Consumption has been recognized as a more reliable indicator of household well‐being than income. Although a considerable body of literature has examined income inequality between farm and nonfarm households, little is known about inequality in consumption. This research aims to fill this knowledge gap by investigating consumption disparity between farm and nonfarm households. Using a nationally representative household survey from Taiwan, we apply an unconditional quantile regression‐based decomposition method to decompose the differences in the distribution of household expenditure between these farm and nonfarm households. The results indicate that differences in the observed characteristics between these two types of households explain most of the consumption inequality. Moreover, the difference in the education level of the farm operator, household income, and the degree of urbanization are particularly important.     

Contract farming: opportunity cost and trade‐offs

An important literature has established that participation in contract farming leads to higher incomes and has a number of other beneficial effects on the welfare of participating households. Yet no one has looked at the opportunity cost of and the various trade‐offs involved in participating in contract farming. I look at the relationship between participation in contract farming and income from (i) livestock, (ii) labor markets, (iii) nonfarm businesses, and (iv) agricultural sources other than livestock and contract farming and (v) unearned income. Using data from Madagascar, I find that participation in contract farming is associated with a 79% decrease in how much income per capita the average household derives from labor markets and a 47% decrease in how much income per capita it derives from nonfarm businesses, but also with a 51% increase in how much income per capita the average household derives from agricultural sources other than livestock and contract farming, possibly due to technological spillovers. Thus, even though contract farming has been shown to improve welfare in multiple ways in this context, it looks as though those gains come at the cost of an “agricultural involution” on the part of participating households, who seem to turn away from non‐agricultural activities. This has important implications for structural transformation narratives.     

Cash crop liberalization and poverty alleviation in Africa: evidence from Malawi

This article uses the case of burley tobacco liberalization in Malawi to investigate the efficacy of cash crop liberalization as an instrument for poverty alleviation in sub‐Saharan Africa. The principal justification for cash crop liberalization is that markets allow farm households to increase their incomes by producing that which provides the highest return to their productive resources and use the cash to buy consumption goods. Using a latent welfare model, we find that households that selected to grow cash crops had higher incomes than those that did not grow cash crops. However, we also find that due to the lumpiness and seasonality of cash crop incomes, higher household incomes, while increasing food purchases did not significantly affect per capita food intake. Irrespective of participation in cash crops, for much of the cropping season rural households seem to rely more on nonfarm income for expenditure and consumption smoothing.     

Cash crop choice and income dynamics in rural areas: evidence for post‐crisis Indonesia

In this article we investigate the factors affecting levels and growth of incomes in rural Indonesia following the crisis of 1997–1998. In particular, we investigate the relative roles of nonfarm incomes and productivity improvements achieved via changes in crops versus improvements on the same crops on income dynamics. Framing the article in the context of an optimal labor allocation model, relying on unique household panel data from Central Sulawesi, and using advanced panel econometric methods, we find that local innovations related to the adoption and intensification of new cash crop varieties, more specifically the shift from coffee to cocoa production, can explain a substantial part of the observed post‐crisis developments. Causal estimates of the effect of growing cocoa suggest that households were on average able to achieve about 14% higher income levels during the post‐crisis period compared to the planting of other crops, most notably coffee. Also, our results demonstrate the importance of engagement in nonfarm activities for household income growth. Comparative analyses using a nationally representative survey suggest that similar processes are at play in other parts of Indonesia.     

Land rental markets and labor productivity: Evidence from rural China

This study investigates the impact of the land rental market on labor productivity in rural China. Particular attention is given to farm and nonfarm labor productivity. Using 2012 household‐level data and a multinomial endogenous switching treatment regression technique, we find that rural households renting in farmland increased labor productivity in the farm sector by about 55%, whereas labor productivity in the nonfarm sector decreased by about 6%. We also find that rural households renting out farmland had lower labor productivity in both the farm and nonfarm sectors by 13% and 9%, respectively. More family labor transferred from the farm to the nonfarm sector after renting out land.     

Rural nonfarm income and its impact on agriculture: evidence from Albania

Using data from the 2005 Albania Living Standards Measurement Study (ALSMS05) survey, this article analyzes the overall impact of household nonfarm income-generating activities (RIGA) on agricultural expenditures as well as technical efficiency of rural farm households. We also differentiate the impact for subsistence and commercial farmers, who are in the top 25% of the distribution of value of annual agricultural sales. Our results show that on the whole, Albanian rural households utilize their nonfarm earnings not to invest in time-saving, efficiency-increasing technologies, but to move out of crop production. We derive similar findings when we try to estimate the same relation separately for commercial and subsistence farmers. However, for commercial farmers, we find a positive impact of household nonfarm earnings on livestock expenditures.     

Poverty decline, agricultural wages, and nonfarm employment in rural India: 1983–2004

We analyze five rounds of National Sample Survey data covering 1983, 1987/1988, 1993/1994, 1999/2000, and 2004/2005 to explore the relationship between rural diversification and poverty. Poverty in rural India has declined at a modest rate during this time period. We provide region-level estimates that illustrate considerable geographic heterogeneity in this progress. Poverty estimates correlate well with region-level NSS data on changes in agricultural wage rates. Agricultural labor remains the preserve of the uneducated and also to a large extent of the scheduled castes and scheduled tribes. We show that while agricultural labor grew as a share of total economic activity over the first four rounds, it had fallen back to the levels observed at the beginning of our survey period by 2004. This all-India trajectory also masks widely varying trends across states. During this period, the rural nonfarm sector has grown modestly, mainly between the last two survey rounds. Regular nonfarm employment remains largely associated with education levels and social status that are rare among the poor. However, casual labor and self-employment in the nonfarm sector reveals greater involvement by disadvantaged groups in 2004 than in the preceding rounds. The implication of this for poverty is not immediately clear—the poor may be pushed into low-return casual nonfarm activities due to lack of opportunities in the agricultural sector rather than being pulled by high returns offered by the nonfarm sector. Econometric estimates reveal that expansion of the nonfarm sector is associated with falling poverty via two routes: a direct impact on poverty that is likely due to a pro-poor marginal incidence of nonfarm employment expansion; and an indirect impact attributable to the positive effect of nonfarm employment growth on agricultural wages. The analysis also confirms the important contribution to rural poverty reduction from agricultural productivity, availability of land, and consumption levels in proximate urban areas.     

Farm households and nonfarm activities in Ethiopia: does clustering influence entry and exit?

This article examines how clustering affects the entry and exit decisions of farm households into and from nonfarm enterprises in rural Ethiopia. We find that the existence of clusters of microenterprises in the same district increases the likelihood of a rural household to start a nonfarm enterprise. Similarly, clustering of big manufacturing firms in the same zone is found to increase the likelihood of farm households to start a nonfarm enterprise. Nonfarm enterprises operating in clusters are also found to have a lower probability of exit than those operating outside of clusters. The study further investigates the impact of entry and exit into and from nonfarm enterprises on farm household's well‐being using as indicators total household income, the food security status of a household, and the household's ability to raise enough money in case of emergency. Using propensity score matching to account for selection bias, we find that entry into nonfarm enterprises significantly increases household's income and food security status. Exit from nonfarm enterprises, on the other hand, is found to significantly reduce household's income.     

集体林区农户收入不平等状况分析——基于辽宁省林改农户调查数据

根据辽宁省5个县3年农户数据的洛伦兹曲线、基尼系数的结果,判断出调查区农户收入差距在加大。文章运用Shapley值计算调查区农户收入结构对收入不平等状况的影响,结果显示,造成农户收入差距的主要因素是非农工作以及农民的教育水平,林改对农户收入的影响主要是通过对农户造林或是转出行为起作用的结果,林改为农户创造了较为公平的多样的收入渠道。     

Is off-farm income reforming the farm? Evidence from Mexico

Does access to off-farm income complement or compete with agricultural production? This article explores the effect of off-farm income on agricultural production activities, using data from the 2003 Mexico National Rural Household Survey. We first discuss the theoretical conditions under which access to off-farm income may influence production in an agricultural household model. Instrumental-variable (IV) estimation methods are then used to test whether agricultural production activities, technologies, and input use differ between households with and without access to off-farm income. We find that off-farm income has a negative effect on agricultural output and the use of family labor on the farm, but a positive impact on the demand for purchased inputs. There is also a slight efficiency gain in households with access to off-farm income. Findings offer insights into how household production evolves as rural households increasingly engage in off-farm income activities.     

Does human capital raise farm or nonfarm earning more? New insight from a rural Pakistan household panel

This study explores how human capital affects farm household earnings using two tools to refine measurement of human capital effects. First, it employs a two‐sector model to allow the allocation of family labor between farm and nonfarm activities. Second, it accounts for village fixed effects to evaluate whether results from panel data differ meaningfully from a cross‐sectional data analysis with local binary variables. The results show that education has a negligible effect on farm earnings; instead, experience appears to be the principal channel by which human capital affects agricultural performance in a traditional rural setting. Our results also suggest that prior models that fail to separate nonfarm activities spuriously exaggerated the effect of education to the farm sector. In addition, typical cross‐sectional analyses that ignore fixed effects may cause the effects of education on rural household earnings to be significantly overstated. The fact that panel data regressions accounting for village‐level fixed effects found only one instance of education raising earnings—the effect of literacy on nonfarm income—suggests that considerable heterogeneity may have been ignored in cross‐sectional data analyses, especially ones that omitted village‐level effects.     

The effects of China's Sloping Land Conversion Program on agricultural households

In the late 1990s, China aimed to mitigate environmental degradation from agricultural production activities by introducing the world's largest “Payments for Environmental Services? program: the Sloping Land Conversion Program (SLCP). We develop a microeconomic Agricultural Household Model, which can model the production, consumption, and nonfarm labor supply decisions of agricultural households in rural China in a theoretically consistent fashion. Based on this theoretical model, we derive an empirical specification, which we econometrically estimate using the Hausman–Taylor method and a large longitudinal farm household data set. The empirical results significantly differ between regions, but are generally consistent with the results of our theoretical comparative static analysis, for example, that the SLCP significantly decreases agricultural production. While the SLCP only increases nonfarm labor supply and total consumption in some regions, these effects could not be observed in others. The recent reduction of the SLCP compensation payment rates generally had negligible effects on agricultural production and off‐farm work and only very small effects on household consumption.     

Participation and returns in rural nonfarm activities: evidence from the Kyrgyz Republic

This article uses two representative household budget surveys from the Kyrgyz Republic to analyze factors influencing participation and returns from different types of nonfarm activities in 2005 and 2006. We use the double hurdle and Heckman models, which allow us to demonstrate that a number of variables has different effects on participation and income from nonfarm activities. For example, residing in remote areas and lack of capital are found to stimulate participation in nonfarm activities, but decrease nonfarm income. Results are robust, but using the Heckman model seems to produce more accurate results for returns to education and gender under the presence of selection bias. Overall, nonfarm activities are found to be most important for the poor, who are pushed out of agriculture due to limited and poor land resources. This indicates that equipping poor households to enable them to move towards better remunerative nonfarm activities should be a priority for Kyrgyz rural policy makers.     

Pathways out of poverty in lagging regions: evidence from rural western China

How to reduce poverty in lagging regions remains much debated and underserved with solid empirical evidence. This study illustrates an empirical methodology to analyze the pathways households followed out of poverty and to explore their potential in the future using 2000–2004 rural household panel data from two lagging provinces of China, Inner Mongolia and Gansu. It finds that rising labor productivity in agriculture has been key in understanding poverty reduction in rural lagging areas of these provinces and that it still holds much promise. Circular migration has also been important in Gansu, though less so in Inner Mongolia. On average, rural diversification has not proven to contribute much to poverty reduction and income transfers and agricultural tax abolishment have only helped at the margin. The findings from these two case studies highlight that the scope for reducing poverty in rural lagging regions can still be substantial in agriculture, also when nonagriculture drives national growth.     

Livelihood diversification strategies in the Himalayas*

This article examines livelihood diversification strategies of rural households using survey data from the Himalayas. We present and explore an analytical framework that yields different activity choices as optimal solutions to a simple utility maximization problem. By classifying the range of activities of rural households into a few distinct categories based on their profitability and by considering portfolios of farm and non‐farm activities, we provide novel insights into diversification behaviour of rural households. The evidence shows that while the poor are mainly agricultural labourers and work in the low‐return non‐farm sector, the better‐off diversify in high‐return non‐farm activities. As expected, we find strong evidence that education plays a major role in accessing more remunerative non‐farm employment. A somewhat less intuitive finding is that larger household size is associated with higher probability of diversification into the high‐return non‐farm sector. The finding that the farm size is not a constraint to diversification in lucrative non‐farm employment is also surprising. Geographical location plays a role in diversification behaviour of rural households indicating the importance of local context.