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We analyze the food security implications of off-farm labor reallocation decisions of rural farm households in transitional Albania. We accomplish this by examining local and nonlocal off-farm incomes for at-home food consumption expenditures.

An instrumental variable approach is employed to correct for endogeneity and censorship biases of off-farm income variables in a two-stage estimation of the food consumption expenditures.

We find that local off-farm income exerts a positive and significant effect on per capita food consumption expenditures of farm households, while private remittances from nonlocal off-farm income has the opposite effect on food consumption expenditures. In terms of regional heterogeneity, we discover that the mountain region spends significantly less on annual per capita food consumption compared to the central region. This confirms anecdotal evidence that food and nutrition insecurity in rural Albania is predominant in the mountain region.

Our findings suggest the need for policy makers to promote a development agenda that enables farm households to exploit the synergies among the various income-generating activities in the rural economy. This spectrum of income-generating activities forms complex livelihood strategies adopted by rural farm households to improve and maintain their food security.

We distinguish between local and nonlocal sources of off-farm income. Knowing which off-farm income source(s) has the largest impact on household welfare through improved food security status should be of interest to policy makers.

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 factors affecting the relative variability in farm and off‐farm income for Canadian farm operators.

Variability of farm and off‐farm income is analyzed using a dataset of 17,000 farm operators from 2001 to 2006. Relative ranking of the coefficients of variation (CV) for farm and off‐farm income are compared across farm types and are regressed against factors conditioning the variations.

Greater reliance on farm income results in lower (greater) relative variability in farm (off‐farm) income. Larger commercial operations experience larger farm income volatility because they are less risk averse or they can manage more risk. Diversification and off‐farm employment appear to be risk management strategies for commercial operations.

Government payments have a small, positive effect on farm and off‐farm income variability, indicating this support leads farmers to take on more risky activities and/or reduce the use of self‐insurance activities. Results could also be due to the lag between the time of the income reduction and the time in which the aid is received. Further research is necessary to decipher the effects of government support on farm decisions.

The results on relative variation in the farm and off‐farm income across farm type raises questions about whether government programs should target specific operations.

While income variation remains a focus of public policy, factors affecting its variability are not well‐understood. Studies have examined the level of farm income and the decision to participate in off‐farm employment but none has examined the variance in both income sources.

The purpose of this paper is to examine the impact of off-farm income on food expenditure, using survey data of 493 rural households from Gansu, Henan and Shandong provinces in China.

A two-stage least squares estimator is used to jointly estimate the determinants of off-farm income and the direct impact of off-farm income on food expenditure while controlling for the endogeneity issue associated with off-farm income variable.

The empirical results show that gender, education of household head, household size, farm size, the presence of children, smartphone use and asset ownership mainly determine off-farm income, and the off-farm income affects food expenditure of rural households significantly. In particular, the results show that a 1,000 yuan increase in per capita off-farm income increases per capita food expenditure by 61 yuan. Further estimations reveal that off-farm income has a larger effect on food expenditure of high-income rural households relative to their low-income counterparts.

Although poverty implications of off-farm income have been well documented, few studies have analysed the effects of off-farm income on food expenditure of rural households. To the best of the authors’ knowledge, there are no studies on this issue that focus on rural China. Therefore, the present study attempts to provide a first insight into the association between off-farm income and food expenditure of rural households in China, with the aim of providing useful evidence for policymakers in their efforts to reduce rural and urban food consumption gap and further increase social welfare.

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 study is to examine the effects of agricultural policy reform – specifically the change from market to direct payment support – on income variability of Swiss farming households. In addition, the observed heterogeneity in income risks across farms and time is explained in terms of farm and regional characteristics.

Unbalanced farm‐level panel data of the Swiss farm accountancy network (FADN) are used to construct coefficients of variation of five‐year overlapping time intervals for total household income and gross farm revenues over the period 1992 to 2009. Linear fixed effect models are applied to measure the effect of specialization, off‐farm income, direct payments, farm size, and liquidity on the variability of gross farm revenues and household income in the valley, hill, and mountain regions.

The switch from market‐based support to direct payments has decreased the variability of farm revenues and household income. The strong reliance on direct payments serves as insurance for most farmers and reduces both household income and revenue risk. Off‐farm income can be used by farmers to reduce household income risk but it increases revenue risk in the valley regions. In all of the regions considered, farm size has a positive effect on household income risk and a negative effect on revenue risk. A high degree of specialization increases both gross revenue and household income risk. Potential revenue insurance contracts should specify farmers' off‐farm employment, the degree of specialization, farm size, and regional specific risk profiles.

This paper assesses the complementary effects of specific farm characteristics and risk management strategies with regard to both farm revenue and household income risk. Influences of agricultural policy changes on income risks are also empirically assessed at different spatial scales.

The purpose of this paper is to examine the factors (including conservation payments) that influence household decisions to participate in off-farm work and estimate the impact of participation on household welfare under the auspices of the Grain for Green (GfG) program.

The authors used survey data from 225 farm households on the Loess Plateau and addressed the possible sample selection and endogeneity problems by employing a jointly estimated endogenous switching regression (ESR) model.

The findings of this paper are as follows: off-farm participation is positively related to households’ educational attainment and negatively related to their land resource endowment and the presence of children; participation in off-farm work exerts positive effects on household income and per capita household income, but negative effects on farm productivity; and conservation payments show no significant impact on off-farm participation, no significant impact on any of the three household welfare indicators for off-farm non-participant households, but a significantly negative impact for off-farm participant households.

This paper makes two contributions. First, the authors address the selection bias and endogeneity problem of GfG participating households by employing the ESR method and explicitly estimating the treatment effects of off-farm participation on their household welfare. Neglecting these problems leads to biased estimates and misleading policy implications. Second, this analysis stresses the important role of government in reducing market or institutional failure and other barriers that impede farmers’ efficient allocation choices instead of compensating households for conserving sloping land, shedding new light on the most effective policy options to achieve the program’s goals.

Off‐farm investment decisions of farm households are analyzed. Farm‐level data for a sample of Kansas farms observed from 1994 through 2000 are utilized. A system of censored dependent variable models is estimated to investigate the factors that influence the composition of farm households’ portfolios. The central question underlying the analysis is whether farm income variability influences off‐farm investment decisions. Previous analyses on the determinants of non‐farm investments have failed to consider the role of income variability. Results of this study indicate that higher farm income fluctuations increase the relevance of non‐farm assets in the farm household portfolio, thus suggesting these assets are used as farm household income risk management tools.

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.

This paper aims to examine the role of off-farm work in the rural residential energy transition in China.

To guide this empirical work, the authors present a simple farm-household model to explain rural energy consumption. The authors then empirically assess three main mechanisms through which off-farm work can speed up energy transition in rural China using panel data methods.

The study shows that income growth from off-farm work can reduce the consumption of traditional biomass energy and facilitate a shift to commercial energy. The losses of labor available for on-farm production raise the shadow price of non-tradable biomass energy and further dampen the demand for traditional biomass energy. More importantly, the authors find that working in service sectors can significantly promote the consumption of commercial energy by rural households. The sectoral exposure effect indicates that a new working environment may influence rural households' energy preferences and thus accelerate the transition away from traditional biomass energy.

Previous studies focus mainly on the income effect of off-farm work on rural energy consumption. The authors first identify three related but essentially different effects of off-farm work on rural energy transition in China. This study provides new insights into the process of energy consumption transition in rural China.