Journal of Agricultural Economics最新文献

We investigate the effects of diet diversity on health outcomes indicated by the body-mass index (BMI) of Kenyan women in their reproductive age (15–49 years). We estimate the demand for diet diversity (which is a proxy for diet quality) and analyse its relationship with BMI by allowing the effect of diet diversity to vary along the conditional BMI distribution. Results show that diet diversity is associated with a beneficial effect on the lower and upper tails of the BMI distribution, that is, dietary diversity improves BMI for underweight individuals while, at the same time, it reduces BMI for overweight/obese individuals. Specifically, doubling the diet diversity is associated with a 14.7% increase in BMI for underweight women and a 7.0% reduction in BMI of obese women. These results support the hypothesis that diet diversity is associated with optimal BMI and, thus, better health, contributing to the policy discourse concerning the double burden of malnutrition in developing countries.

We use a detailed dataset to examine the impact of social networks, conditional on contextual and individual confounders, on farmers' adoption of competing improved soybean varieties in Ghana. Based on the contagion conceptual framework, we employ a spatial autoregressive multinomial probit model to examine how neighbours' varietal and cross-varietal adoption of improved varieties affect a farmer's adoption decision in the social network. Our results show that adoption decisions in a network tend to converge on one variety, such that beyond a threshold of adopting neighbours of that improved variety, the cross-varietal effects tend to lose significance in the network. If the shares of adopting neighbours of the improved varieties are equal, we find evidence that farmers are not more likely to adopt either improved variety compared to farmers with no neighbours who have adopted the improved varieties. The findings demonstrate the significance of neighbourhood effects in the adoption of competing technologies.

COVID-19 has caused major disruptions to agricultural supply chains around the world. Researchers and policy-makers are interested in identifying means to reduce the disruptive effects caused by the pandemic. We investigate the impacts of COVID-19 on the operation of e-commerce stores (in short, e-stores) specialising in agricultural inputs. The difference-in-differences method (DID) is employed to estimate the causal relationship between COVID-19 and online sales of agricultural inputs using data from 54,244 agricultural input e-stores registered in 118 prefecture-level cities across 15 provinces and hosted on two major Chinese e-commerce platforms. The results show that COVID-19 led to a substantial growth in monthly sales of agricultural input e-stores, and this growth of online sales varied across store scales and by types of agricultural inputs. In particular, e-stores selling seeds and seedlings experienced a larger growth in sales than stores selling agricultural machinery and implements, and the mid- and larger-scaled e-stores experienced more growth of sales than micro- and small-scaled e-stores. Further analysis reveals that the growth of online sales of agricultural inputs was driven mainly by an increase in the quantity of customer orders (QCO). The findings of this paper underscore the importance of e-commerce in ensuring the resilience of the agricultural supply chain during the pandemic period.

Taxes on fats and sugar-sweetened beverages are deployed in the developed world to encourage healthier diets. How effective might such fiscal instruments be in emerging economies? We evaluate the impacts of a subsidy for palm oil, introduced as part of the public distribution system in three Indian states. Using variants of the difference-in-differences approach, we find that palm oil consumption increased, particularly in rural areas, as a result of the subsidy, and traditional oils were displaced by cheaper palm oil. However, the intervention did not significantly alter overall edible oil consumption. These results are robust to different specifications, alternative estimation samples, and the exclusion of households who may have been potential beneficiaries of other interventions. Impacts were higher in Tamil Nadu than in other states, and were higher for vegetarian households in rural areas. There was only weak evidence of spillover income effects on other food groups. Given India's dual burden of malnutrition, our analysis suggests that fiscal policy interventions have the potential to effectively nudge consumer choices towards healthier edible oil consumption.

The agricultural sector is currently confronted with the challenge to reduce greenhouse gas (GHG) emissions, whilst maintaining or increasing production. Energy-saving technologies are often proposed as a partial solution, but the evidence on their ability to reduce GHG emissions remains mixed. Production economics provides methodological tools to analyse the nexus of agricultural production, energy use and GHG emissions. Convexity is predominantly maintained in agricultural production economics, despite various theoretical and empirical reasons to question it. Employing non-convex and convex frontier frameworks, this contribution evaluates energy productivity change (the ratio of aggregate output change to energy use change) and GHG emission intensity change (the ratio of GHG emission change to polluting input change) using Hicks-Moorsteen productivity formulations. We consider GHG emissions as by-products of the production process by using a multi-equation model. Given our empirical specification, non-convex and convex Hicks-Moorsteen indices can coincide under certain circumstances, which leads to a series of theoretical equivalence results. The empirical application focuses on 1,510 observations of Dutch dairy farms for the period of 2010–2019. The results show a positive association between energy productivity change and GHG emission intensity change, which calls into question the potential of on-farm, energy-efficiency-increasing measures to reduce GHG emission intensity.

New plant engineering techniques (NPETs) may significantly improve both production and quality of foods. Some consumers and regulators around the world might be reluctant to accept such products and the global market penetration of these products may remain low. We develop a parsimonious economic model for R&D investment in food innovations to identify conditions under which NPET technology emerges in the context of international trade. The framework integrates consumers' willingness to pay (WTP) for the new food, the uncertainty of R&D processes, the associated regulatory cost of approval, and the competition between domestic and foreign products. With generic applicability, the model enables the quantitative analysis of new foods that could be introduced in markets and then traded across borders. We apply the framework to a hypothetical case of apples improved with NPETs. Simulation results suggest that import bans and high values of sunk cost can reduce R&D investment in NPETs to suboptimal levels.

We explore the effects of different farmer organisations on smallholder farmers' economic performance. The average treatment effect of switching between different farmer organisations is examined. In addition, based on the premise that a higher level of social capital is accumulated through participation in multiple farmer organisations, we also investigate how the economic consequences of farmer organisation membership vary with the intensity of participation. Our conceptual model explicitly includes social capital to provide a micro-foundation and a theoretical justification for the linkage between farmer organisation participation and the economic outcome. This indicates that participating in different types of farmer organisations is beneficial for farm households only when the returns from social capital investment outweigh the time cost of participation. Our empirical results suggest that membership of farmer organisations that are more homogeneous in terms of member specialty and similarity in production and marketing activities results in a significant increase in farm sales revenue and net returns. This result supports the view that technological proximity accentuates knowledge spillovers within the farmer organisations, and thus leads to better economic outcomes. In line with the prediction of the theoretical model, the average treatment effect of participation is found to increase with the number of organisations that farmers belong to. Moreover, results from the quantile regression provide empirical evidence supporting increasing returns to social capital accumulated through participation in several farmer organisations.

This study evaluates the impact of conventional cage bans for laying hens in the EU on exports of poultry-keeping equipment. Using detailed data on international trade in poultry-keeping equipment combined with an event study regression approach yields several new findings. The results suggest that the cage bans were associated with an increase in intra-EU trade, and also an increase in exports of poultry equipment from EU member states to non-EU countries where conventional cages are still permitted. The results suggest that some banned cages were likely exported to countries outside the EU to be used in egg production.

Smallholder agriculture in sub-Saharan Africa is commonly characterised by high levels of technical inefficiency. However, much of this characterisation relies on self-reported input and production data, which are prone to systematic measurement error. We show theoretically that non-classical measurement error introduces multiple identification challenges and sources of bias in estimating smallholders' technical inefficiency. We then empirically examine the implications of measurement error for the estimation of technical inefficiency using smallholder farm survey data from Ethiopia, Malawi, Nigeria and Tanzania. We find that measurement error in agricultural input and production data leads to a substantial upward bias in technical inefficiency estimates (by up to 85% for some farmers). Our results suggest that existing estimates of technical efficiency in sub-Saharan Africa may be severe underestimates of smallholders' actual efficiency and what is commonly attributed to farmer inefficiency may be an artefact of mismeasurement in agricultural data. Our results raise questions about the received wisdom on African smallholders' production efficiency and prior estimates of the productivity of agricultural inputs. Improving the measurement of agricultural data can improve our understanding of smallholders' production efficiencies and improve the targeting of productivity-enhancing technologies.