Journal of Agricultural Economics最新文献

Choice models are used by applied economists for many purposes, such as non-market valuation or estimating willingness to pay for novel food and product attributes. Mixed-logit models allow researchers to account for preference heterogeneity and complex decision-making processes when modelling choices. In mixed-logit models, parameters of monetary attributes such as prices typically are assumed to follow a negative lognormal random distribution to ensure that the marginal utility of a price increase is strictly negative. However, this practice can cause means and standard deviations of welfare estimates to ‘explode’ to unfeasibly large levels, as the model assumes there are some marginal utilities of cost approaching zero. This paper examines whether cost non-attendance, which occurs when respondents ignore costs in stated-preference studies, could be a cause of inflated welfare estimates when a lognormal cost parameter is used. A two-class equality-constrained latent-class model is proposed, in which the cost parameter is fixed at zero for a cost non-attender class and is specified as a random lognormal parameter for cost attenders. This proposed model produces mean welfare estimates that are 17 times lower than a mixed-logit model with a lognormal cost parameter, and 10% lower than a model with a non-random cost parameter. These results suggest that cost non-attendance can result in inflated welfare estimates when employing a lognormal cost parameter, and that accounting for cost non-attendance could be a simple, parsimonious solution to this problem.

Understanding how subsidies affect the selection of farms with different risk exposure into insurance products is key to evaluating the efficiency of government-supported insurance programs. We study the US crop insurance program, which is a major federally supported insurance program, to assess the impact of premium subsidies on the riskiness of the insured. By exploiting two waves of policy changes, we find that the average loss per insured liability falls as premium subsidies increase, which implies that crop producers with lower risk are more responsive to the price of insurance.

Fifty years have passed since the Journal of Agricultural Economics published an article by Ruth Gasson on the goals and values of farmers in England. Gasson's research demonstrated the complexity of motives and, in particular, the importance farmers attached to the activities of farming (their intrinsic orientation), even among the operators of larger farms. Gasson's article has been widely cited as seminal by subsequent researchers on farmer behaviour. Governments have acknowledged the importance of understanding the motives of farm decision-makers when explaining their responses to economic and policy signals and designing schemes to shape farmers' behaviour. Brexit and the creation of national agricultural policies for each constituent UK country have highlighted the need for this better understanding, though precisely how this information can be used remains difficult. The continued dominance of an intrinsic orientation is particularly important for policies encouraging retirement and for the agri-environment. Gasson's legacy is also important in the quantification of goals and values to segment, and hence model, the heterogeneity of likely farmer responses to market and policy signals.

In this research, we use econometric analysis to estimate the impacts of the Black Sea Grain Initiative on international wheat and corn prices. Using these results, we assess the economic value of the treaty to the global food system, as well as the regional distribution of the associated welfare savings. We find that the Russian Invasion created economic costs of approximately $116.05 billion in the global wheat and corn markets. In the international wheat market, the Black Sea Grain Initiative reduced prices by 7.9%, offsetting approximately $21.48 billion of these costs. The largest winners from the Initiative outside Ukraine are primarily in the developing world, particularly in the Middle East and North Africa. We do not observe any economically meaningful impacts of the Initiative in the international corn market.

Seaborne shipping is the dominant mode of transport in international trade in agricultural products, and an increasing part of seaborne agricultural trade is carried in containers. Furthermore, the majority of world containers are moved through liner shipping services, that is, regular transport services provided by global shipping companies which comprise a dense network connecting ports and countries around the world. Using a theoretically consistent gravity equation and a novel identification strategy based on the use of intra-national trade flows, this paper investigates the effect of liner shipping connectivity on international trade in agricultural products. The results show that liner shipping connectivity has a positive and statistically significative effect on agricultural trade. Moreover, this positive effect can be observed for the majority of the agricultural products analysed and is also identified for countries at different stages of development. These findings appear especially relevant in terms of the objective of increasing less developed countries' participation in global agricultural trade.

Seasonal price variability for cereals is two to three times higher in Africa than on the international reference market. Seasonality is even more pronounced when access to appropriate storage and opportunities for price arbitrage are limited. As smallholder farmers typically sell their production after harvest, when prices are low, this leads to lower incomes as well as higher food insecurity during the lean season, when prices are high. One solution to reduce seasonal stress is the use of improved storage technologies. Using data from a randomised controlled trial, in a major maize-growing region of Western Ethiopia, we study the impact of hermetic bags, a technology that protects stored grain against insect pests, so that the grain can be stored longer. Despite considerable price seasonality—maize prices in the lean season are 36% higher than after harvesting—we find no evidence that hermetic bags improve welfare, except that access to these bags allowed for a marginally longer storage period of maize intended for sale by 2 weeks. But this did not translate into measurable welfare gains as we found no changes in any of our welfare outcome indicators. This ‘near-null’ effect is due to the fact that maize storage losses in our study region are relatively lower than previous studies suggested—around 10% of the quantity stored—likely because of the widespread use of an alternative to protect maize during storage, for example a cheap but highly toxic fumigant. These findings are important for policies that seek to promote improved storage technologies in these settings.

Most previous studies evaluating agricultural technology adoption focus on estimating homogeneous average treatment effects across technology adopters. Understanding the heterogeneous effects and drivers of impact heterogeneity should enable interventions to be better targeted to maximise benefits. We apply machine learning using data from a randomised controlled trial to estimate the heterogeneous treatment effect of fruit fly IPM practices (i.e., parasitoids, orchard sanitation, use of food bait, biopesticides, male annihilation technique, and their combinations) in Central Kenya. Results suggest significant heterogeneity in the effect of IPM practices conditioned on household characteristics. The most important covariates explaining differences in treatment effects are wealth, distance to the mango fruit market, age of the household head, labour and experience in mango farming. Results further indicate that those with fewer mango trees benefit more from most IPM practices. Additional analysis across other covariates shows mixed results but generally suggests significant differences between households benefiting the most and those benefiting the least from IPM practices.

Submissions to the Journal have stabilised since the Covid-related surge in 2020, and continue their strong international pattern. Our response times continue to meet or exceed our targets, with a few regrettable exceptions, for which our sincere apologies. The JAE's citation impact factor increased again in 2021 to 4.16, a modest increase from the 2020 score. Our total 2-year citations, however, show a worrying decline since last year. Our sincere thanks are due to our authors and our many reviewers for their contributions. Wiley continue to provide a strong publishing platform with our full archive, generating continuing growth in downloads.

Technological change co-determines agri-environmental performance and farm structural transformation. Meaningful impact assessment of related policies can be derived from farm-level models that are rich in technology details and environmental indicators, integrated with agent-based models capturing dynamic farm interaction. However, such integration faces considerable challenges affecting model development, debugging and computational demands in application. Surrogate modelling using deep learning techniques can facilitate such integration for simulations with broad regional coverage. We develop surrogates of the farm model FarmDyn using different architectures of neural networks. Our specifically designed evaluation metrics allow practitioners to assess trade-offs among model fit, inference time and data requirements. All tested neural networks achieve a high fit but differ substantially in inference time. The Multilayer Perceptron shows almost top performance in all criteria but saves strongly on inference time compared to a Bi-directional Long Short Term Memory.

The recent rise in global food prices threatens many countries worldwide, especially the vulnerable populations. Viable coping strategies can only be designed based on the important policy lessons learned from the experiences of these countries in confronting the similar shocks of 2007–2011. However, the disproportionate effects of these events and the impacts of policy responses remain largely unexplored. We examine the impact of a food price surge and the effectiveness of various mitigating policies in Bangladesh, one of the most populous, densely populated countries in the world that is plagued by poverty. Specifically, we combine individual-level expenditure survey data with recent advances in consumer theory to examine the welfare consequences across income groups and geographic areas of the country over 2000–2016. Our empirical findings lend support to the hypothesis that the brunt of the price surge was borne by relatively less affluent and rural households, and government poverty alleviation programmes were largely ineffective.