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The purpose of this paper is to examine the impact of off-farm employment on agricultural fixed assets among households in rural China.

The authors drew on panel data from two rounds of household-level surveys of more than 2,000 households in rural China. The two surveys were conducted in 2008 and 2012 in five provinces. The authors used instrumental-variable Tobit model to test whether the current value of agricultural fixed assets differ between households with different levels off-farm employment.

The authors observe that off-farm employment has a negative effect on the current value of agricultural fixed assets at the household level in rural China.

The authors believe that the results will contribute positively to the assessment of the effect of off-farm employment on the investment in agricultural fixed assets at the household level in the context of China.

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.

This paper explores the rural labor market impact of migration in China using cross-sectional data on rural households for the year 2007. A switching probit model is used to estimate the impact of belonging to a migrant-sending household on the individual occupational choice categorized in four binary decisions: farm work, wage work, self-employment, and housework. The paper then goes on to estimate how the impact of migration differs across different types of migrant households identified along two additional lines: remittances and migration history. Results show that individual occupational choice in rural China is responsive to migration, at both the individual and the family levels, but the impacts differ: individual migration experience favors subsequent local off-farm work, whereas at the family level, migration drives the left-behinds to farming rather than to off-farm activities. Our results also point to the interplay of various channels through which migration influences rural employment patterns.

This paper examines household and community characteristics that influence the entry of rural households into non-farm entrepreneurship and investigates the various factors that influence the market exit of non-farm enterprises (NFEs).

The authors use data from three rounds (2011/12, 2013/14 and 2015/16) of the World Bank’s Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA). The authors employ panel logit and multilevel logit models to examine the probability of opening one or more enterprises and the enterprise exit rates.

Results indicate that the likelihood of starting a NFE is positively associated with primary education attainment, access to credit, experiencing idiosyncratic shocks and availability of formal financial institutions. Age, higher education attainment and rising farm input prices constrain entry into non-farm entrepreneurship. The enterprise exit rate is negatively associated with small-town residence, wealth, access to tar/gravel roads and cellphone communication.

Policymakers and administrators should strive to address the challenges that communities face in transportation, communication and financial services. Policies aimed at stabilizing prices and increasing access to mobile communication, primary education and road infrastructure could help expand the rural non-farm sector.

Previous studies primarily examined the determinants of participation in NFEs at a given time using cross-sectional data. The current study uses panel data to study the dynamics of NFE ownership by investigating households’ decisions to enter into or exit from the sector.

The peer review history for this article is available at https://publons.com/publon/10.1108/IJSE-09-2022-0611

This study aims to analyse the consumption inequality between farm and non-farm households in rural Vietnam, using the data from the 2016 Vietnam household living standards survey.

The present paper applies the “recentered influence functions (RIF)” in “Oaxaca-Blinder (OB)” type decomposition as proposed by Firpo et al. (2018) to allow for the flexible distribution of the outcome variables and the non-randomness of non-farm employment that violates the classical linearity assumption.

Non-farm households have significantly higher per capita consumption expenditure than farm households for the entire distribution. The gap in expenditure is large at low percentiles and narrowing with higher percentiles. At 10th percentile, the gap is estimated at 27.1%, but it is decreasing to 11.1% at 90th percentile. Most of the gaps are explained by the differences in the observed characteristics between farm and non-farm households such as ethnicity, education, income, internal transmittances and household composition. Non-farm households are endowed with more productive factors that result in higher per capita consumption expenditure.

Gaps in ethnicity and education are found to be key predictors of the inequality in consumption expenditures between farm and non-farm households, then, government policies that are aimed at increasing access to non-farm employment and education for ethnic minorities and for rural poor households are pathways to improve rural household welfare and hence reduce inequality.

In the past decade, there has been a dramatic decline in agricultural employment in Bulgaria and several reports have pointed at supply chain modernisation and poor milk quality as the main reasons for the dramatic decline in the number of farms. However, to date the policy debate is been based on ad hoc claims, while there is relatively little micro-level evidence. The purpose of this paper is to analyse the determinants of structural change in the Bulgarian dairy sector in the period 2003-2009.

This paper analyses the determinants of structural change in the Bulgarian dairy sector in the period 2003-2009, using a unique panel survey of 296 farm households in the North and South Central Region of Bulgaria. In order to control for sample attrition bias, the authors use a two-step Heckman model of farm survival and growth model.

The data confirms the rapid outflow of agricultural labour from dairy farming activities: 55 per cent of the farm households supplying milk to a dairy company in 2003 stopped supplying in 2009. The main reasons for quitting are ageing of the household, health problems and an increase in off-farm employment alternatives and not supply chain modernisation and milk quality standards. The institutional innovations which are associated with integration in modern supply chains, such as the provision of farm assistance programmes, have a positive impact on small farms’ growth.

The study is one of the first to use panel data to analyse the impact of standards on the survival and growth of small farms in value chains. The authors analyse the determinants of farm survival and growth in the Bulgarian dairy sector in the period 2003-2009, using panel surveys of 296 dairy farm households in the North and South Central Region of Bulgaria and panel data from interviews with dairy companies. The findings are relevant beyond the Bulgarian dairy sector as supply chain modernisation and changes in quality regulations are taken place in many other transition and developing countries.

The purpose of this paper is to investigate the impact of internet usage on financial performance of small farm business households in the USA. In particular, the authors want to assess the impact of internet usage on small farm businesses, where the owner’s main occupation is farming. Using a nationwide farm-level data in the USA and a non-parametric matching estimator, the study finds a significant positive impact of internet usage on gross cash income, total household income, off-farm income. The study further suggests that small farm businesses receive benefits from internet usage as it facilitates reduction in income risk through off-farm income sources, as well as a reduction in marketing and storage costs; households’ non-farm transportation and vehicle leasing expenses.

In this study, the authors use the “nearest neighbors” matching method in treatment evaluation, developed by Abadie and Imbens (2002). In this method, a weighting index is applied to all observations and “nearest neighbors” are identified (Abadie et al., 2004). Although matching estimation through the nearest neighbor method does not require probit or logit model estimation per se, the authors have estimated a probit model because it allows the authors to check the balancing property and to analyze the association of included variables with the likelihood of internet use.

The study suggests that small farm business households using the internet are better off in terms of total household income and off-farm income. As compared to the control group (which is counterfactual, representation of small farm businesses not using the internet), small farm businesses using the internet earn about $24,000-$26,000 more in total household income and about $27,000-$28,000 more in off-farm income. Also, small farm businesses using the internet earn about $4,100-$4,900 more in gross cash farm income compared to their counterpart. The estimate of ATT for NFI is not different from zero. However, gross cash farm revenue increased significantly.

To this end internet can provide an important role in information gathering. Internet is one of the convenient means to access and exchange information. Information and communication facilitation through internet have opened up new areas of commerce, social networking, information gathering, and recreational activities beyond a geographical bound. Producers and consumers can take advantages of internet in both collaborative and competitive aspects in economic activities as it can reduce the information asymmetries among economic agents.

Farmers will seek assistance in interpreting data and applying information to their farming operations, via the internet. Therefore, it is essential that land grant universities continue to improve the delivery of electronic extension and provide information in a clear and concise manner.

Studies in farm households have mainly investigated factors influencing internet adoption, purchasing patterns through internet, internet use, and applications. In most cases, impact analyses of communication and information technologies such as internet in agricultural businesses are discussed with references to large scale farm businesses. Thus, the authors know very little about access to the internet when it comes to small farm businesses and small farm households and about how it impacts well-being of small farm households.

The purpose of this paper is to examine how households’ engagement in concurrent business (CB), which is measured by the contribution of off-farm income to household income, affects the farm size–technical efficiency (TE) relationship in Northern China.

This paper applies a stochastic frontier analysis method to analyze data on 1,006 rural households collected from four major wheat-producing provinces in Northern China, adopting a translog specification for the underlying production function.

The analysis yields three findings. First, the farm size–TE relationship is inverted U-shaped for all CB engagement levels higher than 5 percent, and the most technically efficient farm size increases with the level of household CB engagement. Second, how TE varies with the level of CB engagement depends on farm size: an inverted-U relationship for relatively small farms (<10μ), a positive relationship for middle-size farms (10–20μ), and a negative relationship for large farms (>20μ). Finally, the overall TE score, 0.88, suggests that wheat output can be increased by 12 percent in Northern China if technical inefficiency were eliminated.

Unlike most previous studies that examine the impacts of farm size and households’ off-farm business involvement separately, this paper examines how these two factors interact with each other.

Building on the risk balancing theory and on recent discussions the appropriateness of using farm income maximization as behavioural assumption, this paper extends the risk balancing framework by accounting for business-household interactions. The purpose of this paper is to theoretically introduce the concept of farm household risk balancing, a theoretical framework in which the farm household sets a constraint on the total household-level risk and balances farm-level and off-farm-level risk.

The paper argues that the risk behaviour of farmers is better understood by considering risk at the household level. Using an analytical framework, equations are derived linking the farm activities, off-farm activities, consumption and business and private liquidity.

The framework shows that a farm household that wants to minimize the risk that total household cash flow falls below consumption needs, may exhibit a wide variety of behavioural responses to changes in the policy and economic environment.

The framework suggests multiple ways for policy makers and individual farmers to support risk management.

Risk management is at the core of the agricultural policy and it is of paramount importance to be able to understand behavioural responses to market and policy instruments. This paper contributes to that by suggesting that the focus of current risk analysis and management studies may be too narrowly focused at the farm level.

The purpose of this paper is to examine the differences in the rural household agricultural income by farmers’ education while exploiting a nationally representative household survey data set, i.e. the India Human Development Survey-2005, in the rural Indian context. The author seeks to answer the question: how much variation in the household net agricultural income per acre of land cultivated can farmers’ education explain?

The author has employed the ordinary least squares regression model with village fixed effects. The author also analysed the data using some exploratory statistics.

The author finds that farmers’ education significantly increases the net household farm income per acre of land cultivated last year. The results are robust to the inclusion of the five educational degree categories (dummies) in lieu of the years of schooling variable. The results are also robust to its decomposition into that for men and for women separately. Women farmers’ education has an amplified impact on farm incomes. The author also confirms the inverse relationship between the household agricultural income and land area cultivated, which is consistent with the huge literature on the negative relationship between land size-class and farm productivity.

In a developing country with a not-so-modernized agriculture sector and low adoption of newer farming technologies, this validated importance of education in explaining the differences in rural farm earnings has guiding policy implications in that a positive return to farmer schooling signals the need for increased investments in the farmers’ education and awareness so as to enhance farm incomes and productivity. The special policy thrust on education of women and women farmers is critical to ensuring higher farm incomes and outcomes.

The literature on the impact of farmers’ education on rural household agricultural income is very sparse. To the best of the author’s knowledge, this issue has not been addressed before in the Indian context. The author explains the contribution of farmer education to farm income in rural Indian households. The author also revisits the negative relationship between farm income and land size holdings in the Indian agriculture.