Journal of Agricultural Economics最新文献

Introducing and lifting COVID-19 restrictions caused significant disruptions throughout the world economy, including in international trade. This study employs a panel gravity model to examine the impact of the pandemic on the agri-food trade of EU countries. Specifically, we estimate the direct effects of the intensity of lockdown-type policies on bilateral trade across country, product, and time dimensions, and the indirect effects of those policies as they work through domestic market impacts. We also decompose the indirect effects of COVID-19 between the domestic demand side and supply side impacts. We provide insights into the sources of pandemic disruptions by comparing a ‘no-COVID’ counterfactual scenario from March 2020 to February 2022 to the COVID-19 reality. Our data analysis reveals a loss of 162 billion EUR in agri-food trade due to direct and indirect effects of COVID-19, equivalent to 11.3% of imports over the period. Approximately half of this total is comprised of intra-EU bilateral trade. The COVID-19 effects were proportionally greatest in the trade of fats and oils, and animal-origin products, while vegetable-origin and processed food products were affected only about half as much. Reduced intra-industry demand was a dominant source of indirect effects in the trade of non-processed food. In turn, the weakening of consumer demand was the main factor behind trade losses in processed food imports. The proportional trade impacts differ greatly across EU countries.

Despite the many studies providing evidence of the benefits of cooperatives, most small farms and farm households, particularly in transition economies, do not participate in them. This study analyses the effect of cooperative activity on farm performance using a large-scale farm survey conducted in Armenia. In addition, it addresses the issue of heterogeneity, which is often overlooked in the literature. It looks at heterogeneity in terms of observed effect modifiers, which are measured covariates that can modify the causal effect of cooperation on a specific farm performance indicator. This is the first study that pays special attention to heterogeneity and uses the causal forest approach in the context of cooperative membership to characterise the drivers of treatment heterogeneity (i.e., variation in the causal impact of cooperative membership across farmers with different observable characteristics). Participation in cooperatives is associated with greater perceived farm performance among farmers with limited access to market information and low financial literacy. Similarly, higher benefits are observed for less experienced and older farmers, suggesting that cooperatives play a particularly important role in supporting more vulnerable subgroups.

This study investigates farmer preferences for publicly and privately financed agri-environmental contracts. Using a labelled Discrete Choice Experiment with 366 German grassland farmers, we examine trade-offs between payment schemes (public/private), payment criteria (practice-based/result-based), collaboration options, and advisory services. Our results show that farmers require higher compensation for privately financed contracts compared to public ones. On average, respondents prefer practice-based over result-based payments and value free advisory services, particularly in private schemes. Preferences for collaborative implementation indicate a strong desire for autonomy. A key contribution of this study lies in integrating farmer identity into the analysis. Drawing on a psychometric scale of ‘good farmer’ attributes, we identify three latent identities—productivist, environmentalist and civic-minded—and show that these significantly explain heterogeneity in preferences and land enrolment decisions. Productivist farmers demand higher compensation and commit less land, while environmentalist and civic-minded farmers are more inclined to participate and enrol larger areas, even at lower compensation levels. These findings highlight the importance of tailoring agri-environmental contracts to farmers' identities through for example framing of agri-environmental contracts accordingly. Privately financed schemes, such as those based on crowdfunding platforms, must address perceived risks, offer advisory support and develop communication strategies that resonate with different identity profiles. Recognising farmer identity as a behavioural driver can enhance participation in both public and private agri-environmental schemes and inform more effective contract design.

Gene editing (GE), a revolutionary genetic engineering technology that makes targeted modifications to plant and animal genomes, offers the potential to address key challenges in food security, nutrition, safety, health, agricultural productivity, and sustainability, yet consumer demand for GE foods remains uncertain and complex. This study reviews (1) the factors affecting consumer preferences for GE foods and (2) studies on consumer acceptance of GE foods that feature comparisons to genetically modified (GM) foods. The present manuscript also discusses implications for industry and policymakers and identifies areas where additional research would further promote the acceptance of GE technology. A total of 74 consumer studies were identified, reviewed, and discussed. The results indicate that many factors drive consumer preferences for GE foods, mainly sensory attributes, nutritional content, price, risk perception, trust in institutions, consumer socio-demographics, and available knowledge and information about GE technology. Furthermore, we found that consumers generally prefer GE foods over GM foods, but this preference varies depending on specific products and contexts. These findings provide useful insights for science, industry, and policymakers aiming to develop, commercialise, and regulate GE foods. Finally, several future research avenues are outlined and discussed.

We examine farm management decisions of smallholder farmers during the first wave of COVID-19 infections in India between June 2020 and March 2021. We use panel data from 256 farm households in the rural–urban interface of Bangalore from a pre-COVID-19 face-to-face survey and a phone survey at the end of the first COVID-19 wave. We combine this survey data with sub-district and village level data on the number of COVID-19 infections as well as rainfall data. Results of fixed effects panel data models show that higher COVID-19 exposure, measured by numbers of sub-district and village level COVID-19 infections, positively affects the number of sustainable agricultural practices adopted. Conversely, higher COVID-19 exposure is related to a reduction in the share of crops treated with external inputs such as fertilisers and pesticides. The results suggest that disruptions related to COVID-19 exposure levels restricted farmers' access to agricultural inputs, prompting a shift towards sustainable agricultural practices.