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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.

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 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).

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.

Farmers are the largest group of financially excluded persons in Nigeria, thereby highlighting the supply shortfall in finance to agriculture in Nigeria. Availability of finance would go a long way in improving output and productivity in agriculture, and consequently help in reducing poverty. This study conducts an empirical investigation of the effects of financial inclusion on agricultural productivity in Nigeria.

This study makes use of the Living Standards Measurement Study–Integrated Surveys on Agriculture (LSMS-ISA). This is a new data set on agricultural households which contains information on agricultural activities and various household activities, including banking, savings and insurance behaviour. Considering the data are such that there are observations for households over three time periods, the study exploits the time series and cross-section dimension of the data by using panel data estimation.

The empirical results of the study show that financial inclusion, irrespective of how it is measured, has exerted positive and statistically significant effects on agricultural productivity in Nigeria.

While considerable research has been conducted to examine how finance affects broad macroeconomic aggregates, little is known about the effects of finance at the household and individual level. It is important to explicitly account for financial inclusion when examining the effects of finance on individuals and households. This study improves on existing research and offers new insights into the effects of financial inclusion on the economic activities of agricultural households in Nigeria.

The Million Farmers School (MFS) program—also known as Kisan Pathshala was launched to impart training to the farmers by the government of the state of Uttar Pradesh (India) in December 2017. This study estimates the impact of training on agricultural knowledge of the farmers.

The study is based on household survey conducted in Uttar Pradesh (UP), India, during March–May 2019. The authors employed matching methods, the two-stage least square (2SLS)-residual and endogenous switching regression approaches to control for selection bias and endogeneity.

The results suggest that knowledge outcomes are significantly better among participants vis-à-vis non-participants. The results are robust to different model specifications. Further, the benefits are observed across different regions and social groups.

The MFS program can go a long way in enhancing agricultural know-how and the farmers' economic well-being, bringing a transformative change in the agricultural landscape of UP.

This study is based on a field survey data and analyzes various aspects of the program's impact, design and implementation, and offers implementation advice for greater efficacy in future.

Based on the brief historical review, the purpose of this paper is to expound the target and bottom line for the farmland institutional reform of in China, analyze the “Chinese scenes” and historical heritage of farmland institutional arrangement, evaluate the policies and their effects over the last four decades and outline the keynotes and possible direction of the future reform.

The paper builds the analytical clue of “institutional target – institutional heritage – policy effort – realistic dilemma – future direction” and review and forecast the Chinese farmland institutional reform.

The farmland institution is an important issue with Chinese characteristics. Over the last four decades, the farmland institutional reform in China has focused on “stabilizing the land property rights” and “promote the farmland transfer.” As the study indicates, the promotion of farmland transfer has not effectively improved the scale economy of agriculture and stabilizing land property rights by titling may restrain the development of farmland transfer market because farmland transfer is of special market logic.

It depends on the revitalization of farmland management rights to resolve the transaction constraint of personal property and its endowment effect in farmland transfer. And, classifying the land management property to involve farmers into the economy of division can be reference for the reform of traditional agriculture worldwide.

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.

Natural calamities impair agricultural households' ability to invest in their farms. Facilitating access to agricultural credit may assist farmers in the face of negative revenue shocks. The aim of this study is to investigate the impact of agricultural credit on the agricultural input expenditure of disaster-affected farmers in Bangladesh.

The study utilizes data on 2,519 disaster-affected farming households from Bangladesh's Household Income and Expenditure Study (HIES) 2016–2017, which employs a nationwide representative five-year interval survey. Further, propensity score matching (PSM) identification strategy is used to estimate the average treatment effect on the treated (ATET), and Mahalanobis distance matching (MDM) is used for the robustness test. In addition, heterogeneous analysis has been conducted to explore the impact of agricultural credit on different types of farming households.

The findings reveal that access to agricultural credit has a favorable and significant effect on farm input expenditure for disaster-affected farmers. Therefore, agricultural credit accessibility could be utilized as a policy tool to assist disaster-affected farmers in improving their investment capacity, and hence, agricultural output.

This study, using a quasi-experimental design of access to agricultural credit on agricultural input expenditures of the disaster-affected farming households in coastal areas of Bangladesh to estimate the causal effect.

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.