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Within the framework of potential efforts and strategies to employment generation for young people in Africa in general and Ethiopia in particular, the agricultural sector is increasingly considered as an important sector and a valuable means for poverty reduction, the promotion of economic development, and youth's economic independence. Renewed hope is placed on the sector to offer sustainable livelihood prospects for the rural youth. Yet, the success and sustainability of the sector require a proper understanding of how households allocate youth labor time in the sector and whether agricultural labor supply is responsive to economic incentives such as shadow wages. Using gender- and age-specific plot-level panel data, we systematically analyze the impacts of shadow wages of each household member on youth agricultural labor supply across types of farms. The results indicate that agricultural shadow wages matter for the youth's labor supply in the sector, but the impact differs for male and female youth. We also show that trends and patterns of youth labor supply vary across gender and whether they work on their own farm, and so do their labor returns. The results are consistent after controlling for individual heterogeneity and instrumenting for possible endogeneity. Taking into account the intensity of youth's actual involvement in the family farm, own farm or off-farm work instead of their stated intentions, the results challenge the presumption that youth are abandoning agriculture, at least in agricultural potential areas of Ethiopia. Instead, the frequent narrative of youth disengaging from agriculture may be a result of methodological flaws or data limitations. The findings suggest that it is necessary to invest in agricultural development to enhance labor productivity and employability of young people in agriculture.

The objective of this study is to investigate the simultaneity between farm couples’ decisions on labor allocation and production efficiency. Using an unbalanced panel data set of Norwegian farm households (1989–2008), we estimate off-farm labor supply of married farm couples and farm efficiency in a three-equation system of jointly determined endogenous variables. We address the issue of latent heterogeneity between households. We solve the problem by two-stage OLS and GLS estimation where state dependence is accounted for in the reduced form equations. We compare the results against simpler model specifications where we suppress censoring of off-farm labor hours and endogeneity of regressors, respectively. In the reduced form specification, a considerably large number of parameters are statistically significant. Davidson–McKinnon test of exogeneity confirms that both operator and spouse's off-farm labor supply should be treated as endogenous in estimating farming efficiency. The parameter estimates seem robust across model specifications. Off-farm labor supply of farm operators and spouses is jointly determined. Off-farm work by farm operator and spouses positively affects farming efficiency. Farming efficiency increases with operator's age, farm size, agricultural subsidises, and share of current investment to total farm capital stock.

The aim of this study was to evaluate determinants of four diversification practises by cocoa smallholders in West Sulawesi, Indonesia: (1) growing other crops, (2) keeping livestock, (3) off-farm work for wages (4) off-farm self-employment, and the impact of diversification on welfare of community members.

Household interviews (n = 116) conducted in two subdistricts (Anreapi and Mapilli) of Polewali-Mandar District, West Sulawesi, provided quantitative data on household characteristics, crop and livestock production, income sources, expenditure and credit access. Two villages per subdistrict were included in the study, each producing cocoa as the main crop but differing in their proximity to a market town. Logistic regression was applied to identify determinants of diversification by households. Multiple linear regression (MLR) models evaluated the impact of diversification practices and other explanatory variables on two proxies of welfare (or household wealth): per capita value of durable assets (household assets other than land or livestock) and per capita expenditure for each household.

Mean per capita cocoa production in the sample was low (51 kg dry beans/annum). The mean dependency ratio (proportion of household occupants age <18 and >64) was 35%, with an average of five occupants per household. Household heads were predominantly male (95%), averaging 46 yo and 7 years of formal education. Most households (72%) depended on loans, but only 24% accessed formal loans. Significant determinants of diversification practices were access to formal credit for self-employment and subdistrict for livestock, with Mapilli subdistrict households more likely to keep livestock. Household predictors in the MLR accounted for 28% variation of the dependent, per capita value of durable goods. Off-farm self-employment and raising livestock significantly improved welfare, but growing other crops or off-farm work for wages had little effect. Other household variables demonstrated to have significant positive effects on welfare were education of the household head, proximity to a market town and land area per household.

The study was restricted to a relatively small sample size (n = 116). Studies including panel data or larger numbers of households could enable the identification of further determinants of diversification.

The study demonstrates that diversification has the potential to improve rural livelihoods, but that obstacles, especially formal credit access, may deter poorer households from diversifying their income sources.

Programs and policies that facilitate access to formal finance by smallholders could encourage diversification into small business and improve livelihoods in cocoa-dependent communities.

In the light of the decline in cocoa farm productivity in West Sulawesi, the study demonstrates the potential benefits, as well as limitations, of income diversification by smallholders.

Off-farm employment is an important factor associated with fertility transition in many developing countries. The purpose of this paper is to investigate the impact of female off-farm employment on their fertility desire in rural China.

Based on the data from the China Labor-force Dynamics Survey, the authors adopt an instrumental variable approach to address the endogeneity issue. Desired number of children and desire for a second child are used to measure fertility desire.

The results show that off-farm employment participation significantly reduces women's desired number of children and the likelihood of their desire for a second child. Moreover, off-farm employment reduces women's fertility desire mainly through pathways including the weakening of son preference and a decrease in job autonomy, rather than the changes in leisure hours. Further evidence suggests that social health insurance plays an important role in moderating the adverse relationship between off-farm employment and the desire for a second child. The fertility-reducing effects are more pronounced among younger women, among those participating in off-farm wage employment and among families with only wives' participation in the off-farm labor market.

This paper contributes to the existing research by investigating the causal impact of off-farm employment on fertility desire in a rural developing context and the possible underlying mechanisms responsible for this relationship. This study provides important insights on this topic in developing countries and may have important implications for theory and practice.

For many farm families and operators across the OECD countries, off‐farm income has become a major determinant of their well‐being. The purpose of this paper is to investigate the potential role of off‐farm employment as a risk management tool among farm operators.

A two‐part model is applied to a longitudinal farm‐level data set for about 20,000 Canadian farms, from 2001 to 2006, in order to estimate the relationship between farm income risk and the decision to participate in the off‐farm labor market and the level of off‐farm employment income.

The variability of farm market revenue is found to be positively related to the likelihood of off‐farm work and the level of off‐farm employment income, in particular for operators of relatively large farms. Hence, farm operators' production decisions appear to be conditioned on an income portfolio that includes a substantial amount of off‐farm income for all sizes of farms.

These results reinforce the need to consider the portfolio effect induced by the integration of farm resources within the non‐farm sector. This is particularly relevant to risk management farm policies that have typically considered decisions made in the agricultural sector in isolation.

This paper uses a true farm‐level panel data set to investigate the relationship between farm income risk and off‐farm work. The size of the data set also allows the robustness of the results across farm typologies and size to be tested. This study contributes to the understanding of structural changes in the farm sector, and their potential implications for both rural and agricultural policies.

The purpose of this paper is to estimate the returns to rural schooling in China, addressing both endogeneity in rural individuals’ schooling and self-selection into off-farm work.

This paper exploits geographical proximity to rural secondary schools to create instrumental variables (IV) for individuals’ years of schooling. It addresses both endogenous schooling and self-selection using the two-step procedure developed in Wooldridge (2002, p. 586).

The preferred IV estimate of schooling returns, 7.6 percent, is considerably higher than most previous estimates found in rural China.

This paper is among the few papers that examine returns to rural schooling in China while simultaneously addressing both endogeneity in individuals’ schooling and self-selection into off-farm work. Its findings suggest that rural education in China is potentially able to generate a respectable level of economic returns if policies are designed to provide greater school accessibility to rural individuals.

The purpose of this paper is to identify the potential relationship between farm income variability and off-farm employment decisions in the short and medium term for the case of Irish farm operators.

Panel probit models of off-farm labour supply are estimated using Teagasc National Farm Survey data for Irish farms. The framework is based largely on standard expected utility but includes a constraint for recent employment history.

The analyses identifies some evidence of a positive association between farm income variability and off-farm employment in the medium term but no significant relationship in the short term. This suggests that off-farm employment is part of a wider portfolio decision but is not a strong solution to short-term farm income shocks.

European farmers increasingly face high income variability but financial risk management tools are not sufficiently developed or widely accessible to assist farmers in managing the associated risk. This deficiency can have negative implications for household economic welfare and future farm investments and hence the future farm income. Off-farm employment can form part of a wider medium-term portfolio strategy but more effective tools are also required for risk management particularly in dealing with short-term volatility and where off-farm employment is not a realistic endeavour given time constraints and/or demographics.

The estimation of farm income variability includes a detrending method thus reducing the likelihood of overestimating farm income variability for farms in deliberate expansion or decline. While previous research has typically focused on the short-term response of farmers to historical farm income variability, this research has distinguished between the short and medium term.

The purpose of this paper is to examine the effect of falling commodity prices on farm debt usage of corn and soybean farms, and how this debt usage differs based on the financial leverage of the farm.

Using panel data on farms surveyed at least twice in the Agricultural Resource Management Survey (ARMS) from 1996 to 2015, this paper uses a difference-in-differences approach to measure the effect of low commodity price shocks on financially vulnerable farms. To account for the correlation in the error structure between the three dependent variables (real estate debt, non-real estate debt, and interest payments) we use a seemingly unrelated regression approach.

Following a commodity price shock, financially vulnerable farms (debt-to-asset ratio greater than 40 percent) were found to increase their non-real estate debt when compared with non-financially vulnerable farms. Off-farm business income was found to help farms reduce real estate debt and interest payments in the face of these shocks.

Data consist of corn and soybean farms surveyed more than once in the ARMS from 1996 to 2015 and are not representative of all US farms, but have similar characteristics to US commercial farms.

The results indicate that financially vulnerable commercial crop farms respond to lower prices by taking on non-real estate debt, increasing financial stress. Well-targeted federal programs could prevent further financial stress for this group.

This is the first paper to use unbalanced panel data from ARMS to examine how farm debt use responds to commodity prices. This paper can inform policymakers about the financial risks to farms resulting from the current low-price environment.

The determinants of income of rural and urban farm households, with emphasis on the role of off-farm employment by farm household members and of farm size, are examined using data from the 2016 Agricultural Resource Management Survey (ARMS) and quantile regression procedure. The implemented quantile regression technique is extended to allow for the decomposition of the income gap between the two groups of farm households. Findings indicate, regardless of the location of the farm, a positive and significant impact of a previous year's participation in off-farm work by household members on the distribution of current household income. Having operated a larger-sized farm in the previous year is shown with a similar effect in the upper range of the income distribution for urban households and with a comparable impact but across the whole income distribution for rural farm households.

Data from the 2016 ARMS are used in conjunction with quantile regression in order for decomposition of the income gap between the two groups of farm households.

Findings show that urban farm households who in a previous year have participated in off-farm work and operated larger-sized farms tend to earn higher incomes. Results further indicate higher rates of return to education for “urban” farm households in comparison to “rural” farm households, particularly for those with a college education and beyond who are at the lower portion of the income distribution.

To the extent that the ARMS is an annual cross-sectional data, the temporal impacts of factors that potentially may influence the incomes of farm households in urban and rural areas cannot be measured.

Findings from this research indirectly support previous published research where higher earnings by urban US population were documented in comparison to rural population and where earnings tend to rise as a result of participation in off-farm work and in expanding the size of the farming operation; this is in addition to the procurement of higher education.

The results of a higher rate of return to education for “urban” farm households in comparison to “rural” farm households have important policy implications for policymakers.

This is the first paper in the agricultural economic literature that implements a method of assessing the rural–urban divide across all of the quantiles of income distribution.

Since the implementation of the New Cooperative Medical Scheme (NCMS) in 2003, this program has experienced rapid growth. Even so, little is known about the association between NCMS expansion and labor force supply among rural residents in China. The purpose of this paper is to examine the effects of the NCMS on labor force supply for rural Chinese populations.

Using data from the China Health and Nutrition Survey (CHNS), a difference-in-differences (DD) approach is employed to estimate the impact of NCMS expansion on labor supply outcomes, including hours of worked in agriculture, off-farm labor force participation, not working, and weeks off due to illness. A number of falsification tests are conducted to identify whether the assumption of common trends of DD analyses is satisfied. The robustness of results is checked through additional estimation, including panel fixed effects and instrumental variable approach.

Results show that the NCMS expansion has a positive effect on the hours of worked in agriculture and off-farm labor force participation, and reduces the likelihood of not working and weeks off due to illness. The effect on hours of agricultural production is larger for male adults, those aged 50 or more, and individuals in low-income families. This study demonstrates the importance of potential health improvements from public health insurance in promoting rural residents’ labor productivity.

Studies concerning the effects of public health insurance on labor supply in developing countries remain limited. The findings of this study provide important insights into how public health insurance programs, like the NCMS, may affect patterns of labor supply among rural residents, and can help policymakers improve health policies aimed to reduce the number of uninsured farmers while maintaining high levels of labor supply, productivity, and health status among the most vulnerable of populations.