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The results of this study have significant policy implications for charting a new course toward enhancing agricultural productivity among Chinese farmers.

By establishing a rural household decision-making model based on the transfer market of farmland operation rights, this paper systematically analyzes the effects of land transfer-in and land transfer-out on the productivity (per labor income) of rural households. The authors conducted basic regression analysis and robustness tests using propensity score-matching and proxy variable approaches based on the micro survey data from rural households in 30 counties in 21 provinces/municipalities/autonomous regions in 2013.

After the completion of land transfer, the total productivity of rural households transferring in lands will increase with an increase in the agricultural productivity; the total productivity of rural households transferring out land will increase due to a rise in non-agricultural productivity and the absolute total productivity of rural households not involved in land transfer will remain unchanged.

Unlike previous literature, this paper discusses the impacts of land transfer-in and transfer-out on total productivity, agricultural productivity and non-agricultural productivity among various rural households (i.e. those transferring in land, transferring out land or which are self-sufficient).

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 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.

In the early stage of the COVID-19 pandemic, Vietnam imposed many drastic restrictions to curb the outbreak of this virus. Such restrictions interrupted the normal functioning of various economic sectors, including agriculture. This research examined disruptions to agricultural activities, income loss and perceived food insecurity among farm households during the pandemic, and then explored the relationships among these economic factors.

Household data from Vietnam and Generalized Structural Equation Model (GSEM) were used for empirical analysis.

Descriptive analyses found that only a small proportion of farm households suffered from the COVID-19 disruptions to their agricultural activities, a large percentage experienced income loss, and a medium number were worried about their food insecurity. GSEM results also revealed that the COVID-19 disruptions to agricultural activities significantly increased the likelihood of worrying about food insecurity, mediated by income loss.

Due to data limitations, the authors could not use better indicators to define and measure the variables of interest (e.g. COVID-19 disruptions to agricultural activities, income loss and food insecurity). Another similar concern was that our models did not account for unobservables, causing some estimation biases.

This research is among the first attempts that examined the direct and indirect (mediated by income loss) effects of the COVID-19 disruptions to agricultural activities on food insecurity.

The lack of theoretical and pragmatic way of measuring agricultural commercialization has been responsible for the inconsistent results for the impact of agricultural commercialization on household welfare. This study makes use of an input-based market participation approach that utilizes household preplanting production decision to stratify farming households according to production orientation.

The study estimates a system of input and consumer demand equations. It augments traditional input and consumer demand equations with an additional variable based on an endogenous switch, which measures the probability of being a commercial farming household. Empirical evidence suggests that market orientation is an important determinant of the level of traded input and hence, market participation. Predicted probabilities obtained from the endogenous switch are used to stratify households into subsistence and commercial agricultural households.

Results of the relative effect of commercial agriculture on the level of household food security support the claim that production orientation does affect the relationship between the relative share of food expenditure to the household total expenditures and the logarithm of household expenditure for this part of sub-Saharan Africa.

As in the case of all generalized method of moments studies, the results depend on the robustness of the instruments. However, search for better instruments may run afoul of Leamer's ad hoc specification search with nonexperimental data.

This paper is original in its formulation of an endogenous switch between subsistence and commercial agriculture. This switch is estimated as a latent variable following a logit form.

The aim of this paper is to address a local separability character partly identified by non‐farm participation behaviors in the context of multiple market imperfections.

The paper develops a model to analyze agricultural household's non‐farm participation based on heterogeneous asset endowments. The model is applied to recent data from Zhouzhi, a mountainous county in rural western China.

The paper shows that human capital, social capital and other capital assets have significant but different effects on the agricultural household's participation in non‐farm activities, and they help to break down non‐farm labor constraints. Nonseparability holds only for those households unable to participate in non‐farm activities due to poor asset endowments.

The agricultural household model developed in this paper and its application in China provide insights into theory and empirical analysis of agricultural households' behavior and rural development.

Ghana's economy is largely agrarian, and the business of agriculture is dominated by smallholder farmers who are predominantly rural dwellers. As a result, efforts to lift rural farming households from poverty have been narrowed to the promotion of agricultural development to the neglect of the rural non-farm sector. However, this is fast changing in the advent of a burgeoning rural nonfarm economy and must engage the attention of policy actors. This study thus assesses the effect of non-farm participation on households' level of commercialization of agricultural crops in Ghana.

The study applies a generalized structural equation model (GSEM) to the Ghana Living Standards Survey round 6 dataset, a stratified and nationally representative random sample of 16,772 households in 1,200 enumeration areas.

This study finds that non-farm participation increases the produce sold to output ratio. It is concluded that non-farm engagement by farmers boosts commercialization in Ghana. Thus, for the Ghanaian and similar contexts, agricultural development interventions that incorporate non-farm activities are more likely to be successful in improving livelihoods.

The study uses only the ratio of sales value to output value definition for commercialization and acknowledges use of multiple definitions could be superior.

Various empirical studies have examined the link between the farm and nonfarm sectors. This paper is original in its approach as it tackles an aspect of the subject that has been understudied, namely, an exploration of nonfarm and farm linkages from the perspective of agricultural commercialization.

This paper aims to test the impact of remittances receipt on agricultural productivity. The paper empirically assesses whether heterogeneity in economic activity of farming households affects the effects of remittances on productivity of tradable and nontradable crop farming households in Ghana.

The authors employ propensity score matching (PSM) methods to address potential endogeneity issues that could arise from the estimation due to selection bias. This paper uses the seventh round of Ghana living standard survey dataset for Ghana.

The authors find that, the involvement of farming households in other economic activities alters the impact of remittances on crop yield. This differential impact also varies according whether the crop is tradeable or not.

Policy can reduce the cost of sending remittances and include financial literacy modules in the farmer training modules to increase farmers' knowledge on investment of remittance in agricultural production.

The authors distinguish the paper from others by controlling for crop types (particularly tradeable or otherwise and gestation period), farming of a second or more crops and engagement of smallholder farmers in nonfarm economic activities.

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 evaluate the effects of price and income changes on food and nutrient demand of rural households by including own-produced food and production-side effects in the demand estimation to correct potential measurement bias in the income and price elasticities for rural households in underdeveloped areas. Simulation results of income and grain price changes on food and nutrition security are provided for economic nutrition security policy applications.

This study analyzes survey data of 1,555 households from underdeveloped rural areas of China to find out how price and income changes affect food and nutrition insecurity of rural households. The authors employ the quadratic almost ideal demand system (QUAIDS) in a two-stage budgeting framework, using quality adjusted prices that were retrieved with regressions of the difference between the unit value surveyed at household level and its village average on household characteristics. The bias correction is implemented by using an augmented IV (instrumental variable) method, in which each market price is instrumented with farm-specific variables. Important macro- and micronutrient elasticities are computed for (a) households with agriculture as main income and (b) other households (of which still many have agriculture as a side business). Finally, the authors use these elasticities to simulate how changes in income or grain prices affect the food and nutrition security in the studied areas.

In general, food income elasticities of agricultural households are at a higher level than those for other households, and so are the food price elasticities. Income changes also have a greater nutritional effect on agricultural households than on other households. Nutrient income elasticities ranged from 0.22 (energy) to 0.27 (Vitamin A) for agricultural households and from 0.19 (energy) to 0.23 (Vitamin A) for other households. Grain price increases have greater effect on nutritional status of non-agricultural households, while a grain price reduction is not clearly favoring the nutritional situation of a particular household group.

This demand study contributes to the literature by taking into account differences in consumption of own production between households and the potential endogeneity of prices resulting thereof. The authors also demonstrate that merely reporting nutrient elasticities might not be sufficient for policy recommendations, and simulations should be reported as a valuable addition.