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Doubling farming households’ income through occupational diversification to the non-farm sector has been advocated to be of paramount importance in an agrarian economy such as India. The purpose of this paper is to analyse the effects of non-farm activities on rural household incomes in four different Indian states by using a propensity score matching technique and developing an endogenous switching model.

The research is based on secondary data taken from four quinquennial rounds of employment and unemployment surveys conducted by the National Sample Survey Organization.

The matching results indicate a maximum monthly rise in per capita income of Rs. 60 in Gujarat and a minimum increase of Rs. 18 in Rajasthan among rural households employed in the non-farm sector as compared to the farm sector. The findings confirm that rural non-farm structural diversification cannot be viewed as a blueprint for increasing rural household incomes in different states. Further, it suggests the need to segmenting the different states on the basis of agricultural development for increasing rural incomes.

The study argues that Indian states with a strongly developed farm sector i.e. Gujarat and Punjab are not ideally suited to undergo structural changes in their economic pursuit. The estimates suggest that the transition of rural households from farm to non-farm-sector activities is a very weak strategy in agriculturally developed states of Gujarat and Punjab, whereas non-farm diversification becomes a pivotal strategy for increasing rural household incomes in less agriculturally developed states such as Rajasthan and Uttar Pradesh. A contrasting point that arises from these evidence is that although diversification to the non-farm sector leads to higher income, but the resultant figures are very scanty.

The present study contributes to the existing literature by providing evidence and policy implications on rural non-farm diversification in India and its impact on the rural household income. The study can help the policymakers in framing policies aiming at increasing the income of the rural household through the structural transition of the rural economy.

The purpose of this paper is to identify the determinants of China’s rural households’ non-farm participation. The authors pay special attention to the effect of potential income differential on this participation.

The data used in this study come from a household survey conducted in Hubei Province. The authors estimate participation equation and income equation, respectively, then introduce potential income differential simulated in participation equation to examine its effect on non-farm participation.

Potential income differential serves as the major pull factor that favors non-farm participation. Education, proximity to a city and specialized commercial farming are crucial in helping rural households to participate in non-farm production; while the land shortage or the labor surplus act as the push factor in non-farm participation. Better quality of land reduces the household’s propensity to participate in non-farm activities. Moreover, the income gap between households that participate in non-farm activities and pure farmers is mainly determined by the differences in household characteristics.

The authors use the method of “switching regression and structural probit” to examine the impact of potential income differential on non-farm participation, and simulate the response of the participation probability to the change of potential income differential. The authors also analyze the sources of income gap between non-farm and farm households using Oaxaca decomposition.

The purpose of this paper is to examine the income strategies adopted by rural households in Ghana and analyzes the determinants of households’ choice of income portfolio.

A multinomial logit approach is employed by the paper to investigate the determinants of various income strategies adopted by households in rural Ghana.

Results indicate that household characteristics, location and infrastructure all play a role in explaining the adoption of income strategies other than a purely on-farm strategy by households. Education is a key determinant of income strategies involving non-farm wage employment, while access to credit and electricity play important roles in non-farm self-employment income strategies.

The findings of the paper call for a promotion of off-farm income opportunities to complement farm incomes and to enhance access of rural households to these sources of income.

The paper models rural household income portfolios into mutually exclusive categories which enables the application of the multinomial logit approach. The paper deviates from mainstream rural income diversification literature that has focussed on assessing the determinants of income shares.

This study aims to analyze the factors that determine non-farm enterprise diversification among farm households in Ethiopia. It extends the analysis by examining enterprises and using pooled data, which has the capacity to generate more accurate outcomes. The existing empirical evidence has focused on all non-farm activities, based on single period, single region data. Much of the existing empirical evidence is based on small-scale and location-specific sample surveys that do not demonstrate the characteristics of aggregate populations.

The empirical analysis was conducted using a quantitative method. To cater to the censoring nature of participating in non-farm enterprise activities, a panel data double-hurdle model is used to a representative sample of 3,594 Ethiopian rural households.

The study finds that the age of household head, household size, distance to the market, social capital and access to credit, are determinants for owning one or more non-farm enterprises. The level of income from these enterprises is then determined by the age and education level of the household head, household size, agricultural equipment, distance to markets and access to credit.

This study brings to light factors that influence households to participate in non-farm enterprises and the determining factors for the income level.

Non-farm activities are an important source of household income and a driver of development. This paper provides empirical evidence on factors that determine enterprise ownership using panel data.

This paper examines the determinants of participation in non-farm activities in rural Sudan. It also investigates whether the factors that influence participation in non-farm activities vary across agriculture sub-sectors.

The study adopts the multinomial logit and probit methods on labour supply participation theory using the Sudanese National Baseline Household Survey (2009). The analysis was applied across job types and agriculture sub-sectors.

The results indicated that educational level, means of transportation, lack of land and access to formal agricultural credit are the most significant factors that push rural farmers to participate in non-farm activities. Surprisingly, the effect of household income was positive and significant, implying that individuals from rich households have higher opportunity to engage in non-farm activities compared to their poor counterparts. The results also revealed some variations in the factors that influence participation in non-farm activities according to the agricultural sub-sectors.

The originality of this article lies in investigating the factors that influence participation in non-farm activities across irrigated and rainfed systems. To the best of our knowledge, this is the first study identifying the determinants of participation in non-farm activities across agriculture sub-sectors. Therefore, the paper fills an important gap in the literature and helps in designing appropriate pro-poor policies to allocate infrastructures across irrigated and rainfed areas in Sudan.

The peer review history for this article is available at https://publons.com/publon/10.1108/IJSE-02-2022-0092.

Education plays an important role in improving Chinese rural laborers’ non-farm incomes. However, in Chinese western rural area, the level of return to education is very low due to the underdeveloped economy and the condition of the education system. For improving the schooling returns level, Chinese central government is paying great attention to the condition of education in the rural western area. To date, no research has examined what educational style is more favorable for improving western rural laborers’ non-farm incomes. To answer this question, the purpose of this paper is to compare the treatment effect of high school education and secondary vocational education on their non-farm incomes. That will provide significant evidence for the government to carry out educational policy.

Base on the Mincer model, several methods is used to estimate the average return to a year education on western rural labors’ non-farm income, including OLS, IV and Heckman tow-steps method, to accounting for the ability endogenous and self-selection bias. And the propensity score matching method is used in estimate the treatment effects of high school education and secondary vocational education.

The results from Mincer model showed that the schooling returns in Chinese western rural area were estimated to range from 2.7 to 3.9 percent, that were lower than the average levels in Chinese whole rural area that are estimated in the other recent studies. By using propensity score matching to roll out the heterogeneous bias, show that the treatment effect from high school education was higher than that from secondary vocational education, indicating that the secondary vocational education is better.

Studies concerning the causal relationship between schooling (high school education and secondary vocational education) and non-farm earnings in the western region of China remain very limited, even empty. This paper will make an update contribution to the literature in the area of education earnings in China.

This study investigates how income from non-farm activities affects households' consumption in two land holders' groups: households with insecure land holding and households with secure land holding.

Following an instrumental variable approach, this study analyzes data collected on a nationwide sample of 1,800 households in rural Burkina Faso.

For insecure land holders' group, this study finds that income from non-farm activities has a positive effect on household consumption per capita. Moreover, the share of household food consumption is negatively associated with non-farm income in this group. For secure land holders' group, the results show that non-farm income has only a negative effect on the share of their food consumption.

The study highlights the livelihood sustaining role of non-farm activities for rural households. Unlike previous studies, the results show that non-farm income is particularly important for land tenure insecure households facing risk of losing agricultural income.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-05-2023-0423

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.

This chapter uses the Ghana Living Standards Survey (GLSS) 7 datasets to investigate and examine the effect of rural non-farm diversification and its implications on agricultural (tree-crop) farming sector inequalities and sustainable development in Ghana. Applying a Gini-decomposition method and/or technique within a quantitative approach, the study outcome indicates the average non-farm income thus, increased income inequality among tree-crop smallholder rural livelihoods and households. Income diversification by farm households has gained the attention of governments, policy makers, and researchers because of its commonness and contribution to socio-economic development especially in developing countries. Aggregationally, non-farm self-employment reduced income inequality, and non-farm wage employment income led to an increase in income inequality. Increased rate of educational enrollment and achievement is the most important variable of non-farm income inequality. Government effort at expanding tree-crop acreages and improve yields have to degree achieved its intended policy implementation, increased rate of educational achievement could undermine the socio-economic policy cohesion and sustainable development of rural livelihood, communities, and national economy. Tree crop policies should take account of the spatial distribution of tree-crop commodity production and in particular, the implication and effect of rural non-farm diversification on agricultural sector inequalities.

The purposes of this paper are to analyze the path and speed of rural transformation (RT) and explore the relationship between farmer's income and RT as well as structural transformation (ST) and typology of RT in the past four decades in China.

Based on the major indicators of RT and ST, graphic illustration is used to analyze the relationships between these indicators and farmer's income using the time-series and cross-provincial data in 1978–2017.

While China has experienced significant RT and ST, the levels and speeds of these transformations differed largely among provinces. Higher and faster RT and ST are often positively associated with the higher and faster growth of rural income. Based on this study, a general typology of rural and structural transformations and rural income is developed. The likely impacts of institutions, policies and investments (IPIs) on RT are discussed.

The authors believe that the findings of this study provide the insights on regional RT and ST and policy implications to increase farmer's income through facilitating and speeding up RT and ST with appropriate IPIs during the rural transformation.