American Journal of Agricultural Economics最新文献

This article examines how trade policies can mitigate the impact of trade frictions that worsen food price spikes when supply shocks are correlated across trading partners. El Niño Southern Oscillation (ENSO) offers a natural experiment of a global climate phenomenon that induces weather correlation across continents. Gravity-derived maize prices in southern and eastern Africa increase significantly in response to El Niño extremes. Eliminating border friction reduces self-sufficiency and the magnitude of El Niño-driven price increases. Either border elimination or diversification of import sources result in lower and less volatile prices regardless of El Niño occurrences. The results highlight that the ability of trade to alleviate price spikes in the focus regions depends much more on the volume of imports than on the location of trading partners.

Extreme weather events have nuanced implications for crop producers. While they can reduce local yields, widespread production losses often drive price increases. This study presents a panel approach that accounts for the price–yield correlation to assess the impact of such events on crop revenues, focusing on U.S. corn and soybeans. It conducts two key analyses: (1) quantifying the revenue impacts of the historic 1988 and 2012 U.S. heatwaves and (2) examining the implications of climate change on crop revenue variability. The results show that compensatory price increases often substantially offset yield losses, especially when price responsiveness to supply shocks is strong. In particular, U.S. corn in 2012 and soybeans in 1988 saw crop revenues rise by more than 8% compared to normal weather conditions, whereas U.S. corn in 1988 and soybeans in 2012 experienced decreases of no more than 4%. The study highlights the importance of crop-specific and time-varying price responsiveness to supply shocks. Furthermore, it demonstrates that if growing season weather during 1997–2019 had exhibited the volatility projected for 2036–2065 under a moderate emissions scenario, revenue variability for corn and soybeans in median U.S. counties would have increased by more than 60%, with more pronounced impacts in regions outside the major Corn Belt. These findings underscore the significant economic risks posed by climate change–induced variability in agricultural revenues.

Improving and maintaining agricultural productivity, which is pivotal to deliver private and public goods, is challenged by increasingly uncertain market and environmental conditions. Understanding differences in productivity among farms and its persistence over time helps assess the vulnerability of agricultural production to these external shocks. In this paper, we study productivity dispersion for European agriculture, assess the importance of different productivity components such as technical efficiency and environmental components, and investigate the persistence of productivity and its components over time. We measure total factor productivity based on a stochastic production frontier model applied to accountancy data from more than 100,000 farms and 26 European countries over the period 2004–2018 (N = 740,256). The results reveal a substantial dispersion in total factor productivity, even within the individual countries and farm types. Environmental factors play important roles in explaining these differences. Productivity persistence is high overall, but varies across farm types; for example, it is lowest for granivore farms and higher for mixed farms. We find that productivity persistence is slightly increasing over time, pointing toward improvements in the resilience of European farming systems during the considered period.

We compare the impact of two extension modalities on knowledge accumulation and willingness to pay for a weather index insurance product among smallholder farmers in Kenya. One approach to extension is based on experiential learning and involves participation in an incentivized framed experiment (or game). The other is based on conventional “narrative-based” learning. While both modalities increase farmer knowledge, incentivized gamification causes more learning. We also find that experiential learning affects follow-up demand for the insurance product, which is not true for narrative-based learning. Interestingly, demand for insurance shifts inward after playing the insurance game. This reduction in demand is mainly caused by increased knowledge about the insurance product, but we also present suggestive evidence that experiencing basis risk during the game was more salient than theory-based learning about basis risk. Game-based learning is an effective approach to promote knowledge accumulation and may accentuate or attenuate adoption of innovations by updating ex-ante, possibly biased, expectations.

Conservation investments must balance risk and return as the benefits and costs of conservation are becoming increasingly difficult to predict. This article investigates whether a more uncertain world will strengthen the case for conservation investments strategies that diversify risk. We consider two ways the world could be more uncertain: (1) a more uncertain future climate that increases uncertainty in conservation benefits and (2) broader market uncertainties affecting conservation costs. We use concepts from expected utility theory to highlight that, as there is more risk to diversify, the incentive and ability to diversify risk depend on relative changes in expected payoffs at each site and covariances across sites as uncertainty increases. We then illustrate our findings using an application to land protection investments in southern Appalachia. In this biodiversity hotspot, we find risk diversification is most cost-effective when conservation agencies face multiple uncertainties, and market uncertainty creates greater incentives to diversify risk than climate uncertainty.

Economic analyses of environmental policy projects typically use pre-existing estimates of welfare measures that are then transferred over time to the policy relevant periods. Understanding how stable and predictable these welfare estimates are over time is important for applying them in policy. Yet, revealed preference models of recreation demand have received few temporal stability assessments compared to other nonmarket valuation methods. We use a large administrative panel dataset on campground reservations covering 10 years to study temporal stability and predictability of environmental quality welfare estimates. Welfare estimates are statistically different across years in 62% of the comparisons, and this ranges from 47%–71% depending on modeling assumptions. Using an event study design, we find evidence that week-specific welfare estimates are stable after an initial adjustment week in response to a change in environmental quality. Our findings further reveal that using 2 years of data in the modeling compared to a single year improves the prediction of future welfare measure estimates substantially, but further prediction improvements are modest when including more than 2 years of data. Predictions of welfare estimates are more consistent when using data closer in time to the prediction year. We discuss the implications of our results for using revealed preference studies in policy analysis.

We estimate the effects of result-based agri-environmental payments on biodiversity using a unique dataset containing information about plant vegetation. The data include information on surveyed plant species for a large number of randomly selected plots followed over a period of 20 years in Switzerland. In our estimation, we utilize a difference-in-discontinuities approach based on exogenous variation in payments triggered by (i) a policy reform in Switzerland that led to a considerable increase in payments that was uncertain prior to the implementation and (ii) an administrative threshold of reform that defines eligibility for payment depending on the botanical quality. We find that the increase in result-based payments led to an increase in the biodiversity of plots that were almost eligible for the payments before the reform but not for plots that already satisfied the eligibility criteria. Our findings have important implications for the design of result-based payments.

Climate change will undoubtedly affect many aspects of the agricultural sector as a driver of impacts, as a force stimulating adaptation to limit or exploit climate change impacts, and as a focal point for mitigation opportunities to reduce its extent. Sectoral participants will react by undertaking a variety of adaptation and mitigation actions. Adaptation is largely inevitable but may require public action to either provide public goods or support private adaptation. Agriculture will also play an important role in mitigating climate change, as in cases it can provide low-cost net greenhouse gas reductions. This paper will discuss the economic and physical characteristics of adaptation and mitigation actions that can be taken in the agricultural sector plus introduce some analysis results and possible directions. Clearly, across these areas, economists will find rich areas for economic inquiry.

We compile a unique satellite-derived panel dataset to investigate the impacts of cropland coverage on the outbreak of Harmful Algal Blooms (HABs) in China between 2003 and 2019. Our results indicate that a 1% increase in cropland leads to a 0.5% increase in the size of HABs in lakes larger than 20 km². The increase in cropland not only affects the size of HABs but also significantly prolongs their duration on average. Furthermore, we provide evidence of a diminishing legacy effect of cropland on HAB area over time and a nonlinear relationship between cropland area and HABs. Fertilizer leakage from cropland shapes the entire pollution mechanism, with farming practices that require elevated fertilizer posing significantly greater impacts on water quality. While the nationwide fertilizer reduction policy implemented in 2015 successfully dampens HABs in nonreservoir lakes during the initial three years, its long-term effects remain uncertain. This study highlights the potential of satellite imagery data for economic analyses of nutrient pollution in China.

Informational barriers are often considered to be a major constraint to the adoption of improved farming practices, inputs, and technologies by smallholder farmers. In the Indian context, it is widely believed that farmers misapply chemical fertilizers because they lack scientific information on soil conditions and corresponding fertilizer recommendations, thus resulting in imbalanced and potentially detrimental fertilizer application. Policymakers are frequently interested in providing farmers with various streams of information to overcome these informational barriers to optimize farming activities. However, such informational interventions frequently fail either because generic recommendations may be ill-suited for decision makers in highly heterogeneous agricultural environments or because farmers' beliefs may be so entrenched as to make them unresponsive to new information. We implemented a field experiment in Bihar, India to test whether plot-specific fertilizer recommendations affect farmers' fertilizer use. We find little evidence for sizable impacts on fertilizer use in general, though impacts are more apparent for low cost or costless recommendations such as increasing the use of highly subsidized fertilizers or shifting the timing of application. Despite modest evidence of such effects, even those fall short of their potential magnitude. We show that treated farmers who are less confident in their subjective beliefs about optimal fertilizer application rates (i.e., with more disperse priors) are more responsive to the recommendations and have a higher ex ante willingness to pay for soil testing. These results suggest that heterogeneity in beliefs may constrain the overall effectiveness of information provision, even when the information is tailored to individual farms.