American Journal of Agricultural Economics最新文献

We examine the relationship between investments in animal breeding and productivity growth on Wisconsin dairy farms using a control function approach. We incorporate farm-level annual investment in breeding and genetics into the law of motion of productivity as in De Loecker (2013) to test the relationship between these investments and realized productivity. Our unique dataset also allows us to look at the effect of choosing bulls with high milk yield potential on productivity. Our results indicate that breeding investments made 3 years prior are associated with higher productivity of the current cohort. However, the farms with the highest level of productivity reap the lowest benefits from breeding investments, suggesting that there are diminishing returns to investing in genetics. When milk output is not quality adjusted, the contribution of breeding to productivity is undetectable, suggesting that breeding and investments in milk quality are related. We conclude that investments in breeding and genetics significantly contribute to dairy farm productivity, especially in terms of milk quality.

Recent extreme events and the disruptions they caused have made food supply chain resilience a key topic for researchers and policymakers. This paper provides input into these discussions by evaluating the efficiency and resilience properties of the leading policy proposals. We develop a conceptual model of a prototype agricultural supply chain, parameterize the model based on the empirical literature, and conduct simulations to assess the impacts on resilience and economic welfare of four key policy proposals: (i) intensified antitrust enforcement to improve market competition, (ii) subsidization of entry of additional processing capacity, (iii) prevention of price spikes through anti-price-gouging laws, and (iv) diversification of production and processing across multiple regions. Results show that some of the policies have potential to improve supply-chain resilience, but their impacts depend on the existing market structure, and resilience gains often come at the cost of reduced efficiency.

We develop a gravity trade model based on a theoretical analysis of heterogeneous firms that engage in horizontal Foreign Direct Investment (FDI) or exporting. The model allows firms' endogenous choice between exporting or FDI to impact the proportion of exporting firms and subsequently bilateral trade. Based on the theoretical results, we propose a three-stage estimation procedure: First, estimate firm selection into horizontal FDI; second, use predicted probabilities from the first stage in the estimation of firm selection into exporting; and third, use predicted probabilities from the previous two stages in the gravity estimation of bilateral trade. We apply this procedure to the European Union (EU) processed food industry, which engages in worldwide FDI and trade. We estimate a baseline model of a standard gravity equation, a two-stage model without FDI selection, and our proposed three-stage model and quantify bias corrections in the coefficient estimates of the trade friction variables in the baseline and two-stage gravity models. The bias corrections can be large. For instance, the inclusion of the proportion of Multinational Enterprises (MNEs) in the trade-selection equation leads to a sign reversal of the distance coefficient estimate and results in an upward bias correction of $��173�\%�$. The three-stage gravity corrects a downward bias of $��31�\%�$ in the coefficient estimate of distance in the baseline but an upward bias of $��77�\%�$ in the two-stage method, which indicates that the two-stage method overcorrects the downward bias in the baseline gravity.

Cover cropping has the potential to improve resilience of agriculture to climate-change-induced extreme weather events. However, rigorous quantitative evidence on the resilience effect of cover crops is still lacking. Using a novel data set that combines satellite-based cover crop information and county-level crop insurance data, we examine the impact of planting cover crops on prevented-planting-related losses that are typically caused by heavy rainfall events. The US federal crop insurance program offers “prevented planting” coverage, which pays indemnities if insured growers are unable to plant their crop due to adverse weather. Linear fixed effects models, instrument-based estimation methods, long-difference models, and a number of other robustness checks are utilized in the empirical analysis to achieve the study objective. Our findings suggest that counties with higher cover crop adoption rates tend to have lower levels of crop insurance losses due to prevented planting. The resulting reduction in prevented planting risk also becomes larger with longer term, multiyear cover crop use. These results support the notion that cover crops improve soil conditions such that the likelihood and magnitude of prevented planting losses decrease. We posit that the ability of cover crops to handle excess moisture (i.e., through better water absorption and improved water infiltration in the soil) is the main factor in its ability to reduce prevented planting losses in the US Midwest.

USDA invests significant public resources into developing its crop projection reports. These publications inform decisions across the supply chain. Several previous studies find that revisions to the department's production and yield forecasts for major agricultural commodities are positively correlated and conclude that they deviate from what would be observed under rational expectations, possibly due to smoothing on the part of forecasters. Yet correlated revisions may also be explained by information rigidities that cause forecasts to be infrequently or only partially updated. We apply a recently developed test to these USDA revisions for corn, soybeans, and wheat, and find no significant evidence that the forecasts are smoothed strategically. Rather, we show that information rigidities are the more likely culprit, due to production and yield information that is either too costly to obtain or too noisy. Our results demonstrate that data challenges are the main source of inefficiency in USDA projections, and that the department can improve the efficiency of its forecasts by making investments that improve its access to crop data, perhaps through crop-monitoring satellite and remote sensing technology.

Using a survey of 430 farmer respondents in the Boone and North Raccoon River watersheds in Iowa, we examine the impacts of three program innovations—reverse auctions, spatially targeted payments, and higher offered payments—on agricultural conservation program cost effectiveness and participation by farmers. We combine farmer responses to a discrete choice experiment offering voluntary conservation contracts with township-level estimates of per-acre nitrogen reductions from each practice derived from the process-based ecohydrological Soil and Water Assessment Tool model. Using a random-parameters logit model, we show that both cost-reducing and benefit-boosting interventions reduce budgetary costs per projected pound of nitrogen removed from the watershed for each practice and thus are more cost effective than the prevailing current cost-share programs. However, we find that these interventions can reduce participation by 30%–70%. Our policy simulations show that even with large budgets, the watershed-level nitrogen reduction from all policy interventions remains far below the policy targets set by the Iowa Nutrient Reduction Strategy. Furthermore, we find cover crop contracts are far more cost effective than no-till/strip-till split nitrogen application contracts.

This presidential address calls the membership to explore ways of doing justice work in their research, teaching, extension, and outreach activities. By sharing my story and developing a content analysis of presidential addresses and invited papers published in the Agricultural and Applied Economics Association journals, I demonstrate how race has shaped my work and the need for additional work in this area. Through this example, I hope that members of the profession will find new inspiration to do justice work.

Seasonal commodity price fluctuations can potentially offer farmers arbitrage opportunities to increase their income. However, smallholder farmers in most of sub-Saharan Africa often do not exploit these opportunities to the fullest extent possible. To inform this issue, we conducted a randomized controlled trial among 1739 smallholder farmers in Malawi to estimate the impact of two key post-harvest constraints, lack of appropriate storage technology and commitment issues, on farmers' legume storage and sales decisions. The treated groups received (i) an improved storage technology in the form of two hermetic (airtight) bags, (ii) the same improved storage technology under the condition that farmers store collectively with members of their farmer club in their village, and/or (iii) the improved storage technology under the condition that farmers store collectively at a centralized association warehouse. We analyzed the impacts of these treatments on storage behavior and revenue from sales. Results indicated that addressing the technological and commitment constraints simultaneously had the largest average impacts. One year after the intervention, farmers offered hermetic bags and the village storage program (Treatment 2) stored 24% more legumes at harvest, stored 27% longer, received a 3% higher price for their legumes and ultimately made 12% more on average than farmers in the control group. Farmers in that treatment also improved some (but not all) outcomes compared to farmers in other treatment groups. These findings suggest that combining technology with collective action that is localized and flexible can lead to better post-harvest outcomes for smallholder farmers.

The Supplemental Nutrition Assistance Program (SNAP) has grown rapidly over the past 2 decades. A large literature relies on state-level panel data on SNAP enrollment and implements traditional two-way fixed effects estimators to identify the impact of economic conditions on SNAP enrollment. This empirical strategy implicitly assumes slope parameter homogeneity and ignores the possibility of cross-sectional dependence in the regression error terms. The latter could feasibly arise in state-level panel data if the time-varying unobserved common shocks, such as national financial crises, have differential effects on SNAP participation across states in the United States. This study empirically evaluates the appropriateness of these two assumptions by adopting a more general common factor model, allowing for slope parameter heterogeneity and error term cross-sectional dependence both separately and jointly. We find that although assuming a common slope parameter across states does not seem problematic for identification, allowing for the error term cross-sectional dependence leads to a roughly 40% reduction in the estimated long-run impact of the unemployment rate on SNAP enrollment. This finding has important implications for policymaking decisions—even small biases could lead to suboptimal policy responses considering the program's size. Our counterfactual simulations support our main results, implying the importance of carefully accounting for time-varying unobserved heterogeneity when studying the cyclicality of SNAP enrollment using state-level panel data.

This paper examines empirically the importance of equity preferences for the formation of international environmental agreements (IEA) for transboundary pollution control. Although it has been shown theoretically that the existence of equity preferences among countries considering an IEA increases the chances for formation and stability of a coalition, empirical assessments of such preferences have been limited to climate change mitigation and single-country studies. We consider the case of marine plastic pollution, of which a large share consists of food and beverage containers, representing a transboundary pollution control problem of increasing policy concern, with properties that lead to distinct considerations for equity and the sharing of abatement costs. We employ a coordinated choice experiment in the United Kingdom and United States to assess preferences for abatement-cost allocations in a marine plastics IEA. Pairs of cooperating countries and the relative allocation of abatement costs are varied experimentally. Results show systematic aversion to both advantageous and disadvantageous inequality with respect to abatement costs but also that the relative strength of advantageous and disadvantageous inequality aversion differs across countries. Across both countries, there is evidence that left-leaning voters generally favor more equal international sharing of abatement costs. Differences of these results from the case of greenhouse gas emission reduction, and implications for current efforts to establish a legally binding global treaty on marine plastic pollution, are discussed.