Search results

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.

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.

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 purpose of this paper is to examine the connections of agricultural productivity, access to credit and farm size in Africa using Ghana as a case study.

The paper employs mixed methods – quantitative and qualitative strategies for data collection and analyses. The hierarchical competitive model was used for the quantitative analyses supplemented with qualitative analyses using key informant interviews, focus group discussions and household case studies.

The results show that there is significant relationship between credit from formal and informal sources and agricultural productivity. Thus access to formal and informal credit increases farm household agricultural productivity by about 0.10 (p=0.05) and 0.45 (p < 0.01), respectively. The quadratic terms of formal and informal credit as well as farm size were found to significantly influence agricultural productivity. The implication of this is that the relationships between formal credit, informal credit and farm size on one hand and agricultural productivity on the other are non-linear in nature. The interactions of formal credit with informal credit; informal credit with farm size; and formal and informal credit with farm size have significant relationships with agricultural productivity. The amount of remittance received by farm households has negative and insignificant influence on agricultural productivity. Market access is also an insignificant determinant of agricultural productivity in Ghana.

This paper provides new insights on whether the scale of production (farm size as proxy) and access to financial services (credit as a proxy) matter in promoting agricultural productivity in Africa using Ghana as a case study. Thus the paper is of relevance to policy-makers and practitioners in Africa and Ghana in particular who are seeking to make informed policy decisions on effectively incorporating credit provision into the agricultural transformation agenda of the continent.

Climate change has become one of the most important development challenges worldwide. It affects various sectors, with agriculture the most vulnerable. In Ethiopia, climate change impacts are exacerbated due to the economy’s heavy dependence on agriculture. The Ethiopian Government has started to implement its climate-resilient green economy (CRGE) strategy and reduce CO₂ emissions. Therefore, the purpose of this study is to examine the impact of CO₂ emission on agricultural productivity and household welfare.

This study aims to fill these significant research and knowledge gaps using a recursive dynamic computable general equilibrium model to investigate CO₂ emissions’ impact on agricultural performance and household welfare.

The results indicate that CO₂ emissions negatively affect agricultural productivity and household welfare. Compared to the baseline, real agricultural gross domestic product is projected to be 4.5% lower in the 2020s under a no-CRGE scenario. Specifically, CO₂ emissions lead to a decrease in the production of traded and non-traded crops, but not livestock. Emissions also worsen the welfare of all segments of households, where the most vulnerable groups are the rural-poor households.

The debate in the area is not derived from a rigorous analysis and holistic economy-wide approach. Therefore, the paper fills this gap and is original by value and examines these issues methodically.

Agriculture in Ghana is dominated by smallholder farmers in rural areas. Majority of these farmers are resource-poor and faced with serious challenges in accessing formal financial services towards farming needs attributed to the stringent requirements. To bridge this gap, village savings and loan associations (VSLA) have been promoted in rural areas as an alternative to meeting the credit needs of smallholder farmers. Credit plays a vital role in input acquisition among farmers for improved agricultural value productivity. This study assesses the contribution of VSLA to agricultural value productivity in the Northern Region of Ghana.

The methodology is a primary cross-sectional data collected with the help of a semi-structured questionnaire. This study, therefore, applied a propensity score matching (PSM) to assess the effects of VSLA on agricultural value productivity.

Results from the PSM revealed that extension contact, contract farming, television set ownership, participating in “Planting for Food and Jobs” and nature of roads, including receiving VSLA information from members' increases participation decision of farmers in VSLA. Conversely, age of a farmer, household size, distance to output market and farmers in the Sagnarigu Municipality have negatively influenced VSLA participation. The propensity score matching estimates showed that members of VSLA obtained 38.2% higher agricultural value productivity than non-members.

Village savings and loans associations can be promoted among smallholder farmers as an effective alternative to formal financial service for inclusive development.

This paper assesses the effect of land ownership on household food security through its productivity enhancement effect in rural Burkina Faso.

As the link between land tenure security and productivity is indirect, the study relies on a complex mixed process regression model with robustness to assess the effect of land ownership on household productivity. Then, an instrumental variable (IV) approach is followed to investigate the association between household productivity and food security. The rural development program survey data collected from 1,892 households in 2017 are used.

The complex mixed process estimation results are robust and show that land ownership has a positive effect on household productivity. From the IV results, it is found that productive households spend more on food, have a low share of expenditures on food and are less likely to experience severe food shortages, implying an improvement in their food security status. This highlights a positive association between land ownership and food security.

Unlike previous studies that only focused on the effect of land ownership on land-related investments and agricultural productivity, this study deepens the analysis and sheds light on how land ownership, agricultural production and food security are related. It gives empirical evidence on the importance of land policies in the struggle against food insecurity in agrarian economies.

The peer review history for this article is available at https://publons.com/publon/10.1108/IJSE-11-2021-0658.

The purpose of this paper is to analyze the extent of aging in the agricultural labor force and its effect on farm production in a province of China.

The analysis uses panel data for the years 2004 through 2008 from a representative sample of farm households in Liaoning province. Descriptive statistics reveal the age structure of the agricultural labor force and correlations between labor force age and production characteristics. A translog stochastic frontier production function and technical inefficiency model is employed to analyze the effect of aging of the labor force on the technical efficiency of crop production.

The paper finds an accelerating trend towards aging of the agricultural labor force in the data. Results from the stochastic frontier production function and efficiency analysis reveal that household‐level technical efficiency increases until maximum efficiency is reached when the average age of the household labor force is 45, after which efficiency declines.

Aging of China's rural labor force may affect efficiency and productivity in crop production. Agricultural policies may need to pay more attention to the aging of the agricultural labor force. Some measures should be taken to address the pattern of migration, and policies to improve the social and economic environment in rural areas for younger workers should be developed. Also, extension programs could help older farmers to maintain efficient farming methods.

This is one of very few analyses of the effects of aging on production efficiency for a developing country, as well as for China. The analysis uses a unique panel dataset that covers 24 counties, 1,890 rural households, and more than 6,000 individuals, with each household tracked for five years. Most of the literature estimating technical efficiency carries out the analysis at the individual level; in China and other developing countries, farming is carried out at the household level. We have adapted the methodology to apply to situations where the unit of analysis is the household.

Digital finance has the transformative power to realise financial inclusion. However, evidence on the relationship between digital finance and poverty reduction remains limited. This study examines the mitigating effects of digital financial inclusion (DFI) on vulnerability to poverty in rural China, explores potential mechanisms at the micro-level, and investigates the external conditions for DFI to validate these effects.

Rural household data from the China Labour Force Dynamics Survey and the regional DFI index compiled by Peking University are used. The probit and mediation effect models are employed to assess the impacts of the DFI on vulnerability to poverty and explore its mechanisms, with an appropriate instrumental variable to mitigate potential endogeneity.

DFI can mitigate vulnerability to poverty in Chinese rural households. Specifically, both sub-indices – coverage breadth and depth of use – have a significant effect. Further analyses based on the mediation model show that improving agricultural productivity, stimulating entrepreneurial activities and promoting non-agricultural employment are the core mechanisms for alleviating poverty vulnerability. Heterogeneity analysis shows that DFI is pro-poor and benefits those who lack economic opportunities. Moreover, adequate endowment in rural households, such as production and human capital, is an external condition for digital finance to mitigate vulnerability to poverty.

This study is among the first to examine the vulnerability-mitigation effects from the perspective of digital finance development, relying on data from a large-scale, nationwide household survey and the regional DFI index. It also checks for the mechanisms and heterogeneity of the effects, which prove the effects can help balance efficiency and equity.