Journal of Agricultural Economics最新文献

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.

By fully accounting for the distinct tariff regimes levied on imported meat, we estimate substitution elasticities of Japan's two-stage import aggregation functions for beef, chicken and pork. Although the regression analysis crucially depends on the price that consumers face, the post-tariff price of imported meat depends not only on ad valorem duties but also on tariff rate quotas and gate price system regimes. The effective tariff rate is consequently evaluated by utilising monthly transaction data. To address potential endogeneity problems, we apply exchange rates that we believe to be independent of the demand shocks for imported meat. The panel nature of the data allows us to retrieve the first-stage aggregates via time dummy variables, free of demand shocks, to be used as part of the explanatory variable and as an instrument in the second-stage regression.

Natural disasters affect economic activities and welfare of small-scale producers in developing countries, but may also offer opportunities to reinvest in productive asset, economic capital, and new technologies for future economic prospects. This paper investigates the impacts of a livelihood recovery project that provided access to finance and rehabilitated communal infrastructures in the coastal communities of Tamil Nadu, India which were severely affected by the 2004 tsunami. We replicate the project's eligibility criteria to build the counterfactual to identify control households based on the validation of secondary data and administrative records. Using data from a carefully designed primary survey, we estimate the impacts of providing access to finance and rehabilitating communal infrastructures on economic and livelihood outcomes. Results indicate positive and significant impacts on income, asset and food security. These impacts are mainly driven by improved access to finance provided and participation in groups. Findings highlight the importance of ensuring access to finance for sustainable economic recovery among small-scale producers, particularly in the aftermath of natural disasters.

Intermediaries play a crucial role in the functioning of agricultural and food markets in developing countries through linking production, imports and storage with consumption. We analyse how competition in the intermediary sector and alternative forms of intermediaries determine the incentives for storage and market outcomes more generally. We apply this framework to the Egyptian wheat sector as an illustrative case study, a country where food security is a priority, where both forms of intermediaries co-exist and undertake storage but where issues of reforms to the role of intermediaries have been raised. Through stochastic simulation, we analyse two changes in government policy: first, the effects of changing the policy instruments with both types of intermediaries undertaking storage; second, relating to market reforms where the private sector replaces the storage function of the parastatal. These issues have wider significance for addressing the interaction between food security and a wide range of policy reforms including de-regulation of parastatals in developing countries.

The return of wolves to Swiss mountains and the damage they cause to sheep and goat herds in the region have raised concerns about a consequent wave of farm closures. In this paper, we examine the relationship between wolf attacks and the decline of Alpine summer farms, a specific high-altitude farm type. We collected farm structure data and monitoring data on wolf attacks between 2004 and 2021 and analysed them using a causal random forest method, enabling a detailed analysis of the relation between wolf attacks and the number of different types of Alpine summer farms at a regional level. The results show that the farming systems are unaffected by incidental and infrequent wolf attacks, but that a high number of wolf attacks in a region is related to faster decrease in number of grazing systems where sheep are most vulnerable to such attacks. In contrast, systems that allow for better herd protection tend to show an increase in areas with frequent wolf attacks.