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The purpose of this study is to assess the impact of credit constraints on agricultural labour productivity as well as the impact of credit constraints and agricultural labour productivity on rural households' consumption in Ghana.

This study uses the Ghana Living Standard Survey round six (GLSS 6) as the main source of data, which happens to be one of the most comprehensive household datasets in Ghana. Quantitative estimation techniques (namely: Endogenous Switching Regression and Two Stage Least Squares) are used to address possible endogeneity and selection into credit markets.

First, large households are prone to credit constraints while age (experience) and compliance with extension advice reduce credit constraints. Second, the determinants of agricultural labour productivity for both constrained and unconstrained households are age, sex, farm equipment, herbicide and farm size. Third, household size, education and livestock rearing influence agricultural labour productivity of constrained households. Fourth, credit constraints, irrespective of how they are measured, impede agricultural labour productivity while access to credit fosters labour productivity. Lastly, credit constraints robustly reduce consumption while agricultural labour productivity strongly enhances rural households' consumption.

The first contribution is that, unlike most previous studies, we do not focus on the widely used measure of productivity – output per unit land, but on agriculture labour productivity in particular. Secondly, unlike most previous studies which examine the effect of credit constraints either on productivity alone or consumption alone, our study examines the impact of credit constraints on both. Thirdly, unlike the existing literature which uses one or two measures of credit constraints, we use a wide range of measures of credit constraints – seven different measures of credit constraints. Lastly, our empirical strategy solves at least two critical econometric problems – sample selection bias and endogeneity.

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.

The purpose of this paper is to explore the impact of using computers to obtain information on the farm household’s production and consumption based on a field survey of farm households in the northern China.

The most important methods applied are instrumental variable (IV) method and propensity score matching (PSM) method. Estimators of IV, PSM and nearest neighborhood matching approaches are considered together to check the robustness of empirical results.

This paper careful impact evaluation results suggest that the use of computer not only improves the size of arable land rented in but also reduces family labor input intensity and the probability of selling agricultural outputs at farm-gate markets. Moreover, it also stimulates transportation, garment, housing and insurance expenditures per capita.

The database of this research comprises cross-section data, which does not support a cross-time comparison.

These results imply that it is vital to expand the coverage of computer use in rural areas. This may suggest that the importance of improving computer access is crucial for stimulating rural consumption increase. Furthermore, the need for the expansion of internet network coverage in western areas is also of importance.

First, the authors directly estimate computer usage impacts on a broader range of production and consumption indicators by including land-relative investments, variable investments, labor input and household’s expenditure and provide rigorous impact evaluations on the impact of access to computer. Second, the authors use IV and PSM methods to correct self-selection bias, going beyond the single equation approach in other studies. This enables us to identify the causal relationship between computer usage and farmer’s production and consumption decisions.

This study aims to verify the impact of the supply shock (fall in harvested output) and demand shock (fall in household income) due to the pandemic on the consumption of necessities and household savings of tilapia's smallholder farmer.

The researchers randomly chose 144 households as research samples using the proportional random sampling technique in Padang Jaya District, North Bengkulu Regency. Researchers collected data on household income, farm losses, household consumption for basic needs, labor demand, use of production inputs, the amount of output sold and saving both during and before the pandemic. The data were collected from the sample using a questionnaire prepared by the researchers. This study used a simultaneous equations system for arranging tilapia's smallholder farmer household economic model.

This study verified that the demand shock phenomenon makes households more severe than the supply shock phenomenon. The demand shock phenomenon made worse-off tilapia smallholder farmers because it caused their household savings to drop during the pandemic. The fall in savings will disrupt the stability of consumption of household necessities (health, food, education and clothing) in the future.

The main contribution of this study was providing empirical evidence about the impact of the demand and supply shock of COVID-19 on the most vulnerable entities in the Indonesian freshwater aquaculture industry, namely, smallholder farmer households of freshwater aquaculture fish.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-08-2022-0554.

The purpose of this paper is to empirically investigate the effects of farm income variability, farm size, and other socio‐demographic characteristics on the precautionary saving behavior of farm households and to estimate the influences of the identified factors on the amount of savings by self‐employed farm households.

Using 2003 Agricultural Resource Management Survey (ARMS) data and a Double‐Hurdle procedure, the likelihood and the amount of savings by farm households are estimated.

An important empirical finding of this study is that variability in income plays an important role in explaining precautionary savings of US farm households. Findings suggest that farm households facing higher income risk save more and accumulate more wealth. It is indicated that several farm, operator, household, and demographic attributes contribute to the precautionary savings of farm households. In particular, results show that educational attainment by operator and spouses have positive impact on the decision to save. In addition, results from this study show that farms that specialize in cash grain are likely to have precautionary savings.

Farm households today are virtually indistinguishable from non‐farm households in their levels of income and diversity of employment. As a result, government policies that influence general economic conditions have much more profound impacts on farm families. Federal support of farm income warrants continued scrutiny. This paper shows that greater income uncertainty increases savings and wealth of farm households. Therefore, farm policies that reduce income variability or uncertainty will have an impact on precautionary savings and wealth of farm households.

Several studies have investigated savings of households; however, these studies are limited to entire US population, older Americans, or non‐self‐employed individuals in the USA. Little is known about the savings behavior of self‐employed US farm households owing to a lack of household survey data and because of the complex relationship between the farm household and farm business in terms of resource allocation (both capital and labor).

A farm household consumption model based on the life‐cycle permanent income hypothesis (LPIH) has been specified and the Euler equations derived in this analysis. Estimation of the of the Euler equations using farm household consumption data provided estimates for the intertemporal elasticity of substitution and the coefficient of relative risk aversion. These parameters differ among the farm enterprises in which the households were engaged. Estimates for the intertemporal elasticity of substitution and the coefficient of relative risk aversion ranged from 0.158 to 0.351 and from 2.849 to 6.329, respectively. Results also provide further evidence that the LPIH is valid for modeling farm household consumption.

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.

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.

A major policy issue facing leaders in the developing world is whether international migration, through remittances, contributes to the development process in migrant-sending communities or impedes the efficient allocation of labor and human capital at the origin countries. This study examines the impact of remittance inflows on out-farm migration of farm labor toward the nonfarm sector. Specifically, this study shows how international migrant remittances may alter the predictions of out-farm migration models by Harris–Todaro.

The authors use unbalanced panel time-series data on 77 developing countries between 1991 and 2010 within a dynamic panel time-series framework to estimate the impact of remittances on the out-farm migration rate.

The authors find two competing effects of remittances on out-farm migration of labor in developing countries. First, remittances decelerate the out-farm migration rates by supplementing farm income and consumption expenditures. Second, remittances provide a source of investment in nonfarm activities that increase the rate of migration out of agriculture over time. Combining these effects, on average, our elasticity estimates indicate that a 10% increase in remittances reduces the migration out of agriculture, on average, by 0.5% in developing countries over time.

The authors findings align with the “developmentalist” or “optimistic” views of international migration. International migration, through remittances, help make the inevitable transition out of the farm sector smoother for developing countries.

To the authors’ knowledge, this is the first study to extend the empirical literature on macro-level determinants of out-farm migration within the Harris–Todaro framework to explicitly account for the impacts of remittances inflows into developing countries that the new economics of labor migration (NELM) theory hypothesizes.

Cassava production surged noticeably in Southeastern Africa beginning in the 1990s. The purpose of this paper is to examine the commercial responses and food security consequences of cassava production growth in the region.

The paper incorporates a mix of quantitative analysis, based primarily on original analysis of national farm household survey data, together with key informant interviews with value chain participants in the three neighboring countries of Malawi, Mozambique and Zambia.

In the cassava production zones, cassava's high productivity translates into per kilogram carbohydrate costs 60 per cent to 70 per cent of the cost of cereals such as maize and wheat, thereby opening up a range of profitable opportunities for commercialization of cassava‐based foods, feeds and industrial products. Despite this potential, cassava commercialization in Southeastern Africa remains in its formative stages, with only 10 per cent to 30 per cent of production currently marketed. Unlike West Africa, where cassava commercialization has centered on marketing prepared cassava‐based convenience foods, the emerging cassava markets in Southeastern Africa have centered on fresh cassava, low value‐added cassava flour, and experiments in industrial processing of cassava‐based starches, biofuels and feeds. Strategic investment in a set of key public goods (breeding, training in food sciences and food safety, and research on in‐ground cassava storage) can help to shape this transition in ways that benefit both commercial interests and the food security of vulnerable households.

The paper compares cassava commercialization across differing agro‐climatic zones, policy environments and food staple zones.