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Farmers' decisions about how much crop insurance to buy are not generally consistent with expected utility maximization. Taking into account both marginal risk benefits and marginal subsidy effects suggests that most farmers have chosen lower coverage levels than would be predicted by standard models. By modeling financial outcomes as gains and losses, cumulative prospect theory offers an alternative framework to perhaps better understand farmers' purchase decisions. The role of the reference point that defines outcomes as either a gain or a loss, the degree of loss aversion, curvature of the value function, and the probability weighting function in determining optimal crop insurance coverage levels are explored for three representative farms calibrated to 2009 conditions. Loss aversion and how crop insurance is framed through choice of the reference point are shown to be the key factors that determine whether predictions from prospect theory are consistent with observed crop insurance coverage choices. When crop insurance is framed as a tool to manage farm risk then optimal choices under prospect theory are not consistent with observed choices. If crop insurance is framed as a stand-alone investment where a loss is felt if the indemnity received is less than the premium paid, then prospect theory can generate optimal coverage level choices that are largely consistent with observed decisions. This result is shown to be robust to changes in parameterizations as long as loss aversion is maintained and if curvature of the value function is accompanied by decision weights that overweight low probability outcomes.

Contracts between farmers and intermediaries and crop insurers are important means for farmers to mitigate risks in modern U.S. agriculture. In this paper, we investigate the effect of crop insurance enrollment on contract terms and farmers' participation in marketing contracts. Following Ligon (2003), we set up a mechanism design framework to demonstrate an intermediary's contract design problem, where farmers are assumed to be utility maximizing agents. We depict farmers' optimal choices of insurance coverage using the specification developed by Babcock (2012). Our model shows that improved terms of crop insurance (lower premiums, higher subsidies) make contracts less appealing to farmers as mechanisms for mitigating risk. Therefore, intermediaries may revise their contract offers so that they are more attractive. However, improvements in contract terms are limited by their cost to the intermediaries and will not lead to expanded participation in contracts.

This article assesses the political economy of the 2014 U.S. farm bill, with a focus on the farm support safety net. The farm bill secured substantial bipartisan majorities in a politically contentious Congress. Planned outlays are predominately for nutrition assistance programs directed toward a traditional nonfarm constituency in the farm bill coalition, while annual fixed direct payments to farmers are eliminated but replaced with enhanced downside risk protection against low prices or revenue. The new support programs may prove more or less costly than the foregone fixed payments, with farmers offered a choice between a price countercyclical program with increased reference prices and a revised moving-average revenue guarantee program. The role of insurance is enhanced, notably by replacing past support programs with a new upland cotton revenue insurance program and dairy milk-to-feed margin protection program. Open policy issues that are highlighted include the costs and distortionary effects of moving-average revenue benchmarks versus fixed reference prices, the overall level of insurance premium subsidies, the potential for overlap between commodity and insurance programs, and lastly, food, environmental, and biofuels concerns that reflect the diverse portfolio of products demanded from agriculture. In an international context, we conclude that the 2014 farm safety net likely would not have been enacted had multilateral agreement been reached on the 2008 Doha Round World Trade Organization negotiating documents. Conversely, the 2014 farm bill makes achieving those limits more difficult. Research is discussed that can elucidate the ongoing political economy of U.S. farm policy and help shape future program design.

In economic models of behavior, consumers are assumed to value the goods and services they purchase based on stable preferences over externally identifiable attributes such as quality. These models predict that consumers will respond to changes in price in a way that is independent of the source of the price change. Yet research in the behavioral sciences indicates that consumers that are emotionally attached to a consumption good or other behavior might respond with resistance when policies threaten their consumption or behavior. Moreover, policies that in fact validate some emotional attachments can stir a stronger preference for the good or behavior. Reviewing both survey and experimental data from the literature, we demonstrate how such emotional responses can create hidden costs to policy implementation that could not be detected using standard welfare economic techniques. Building upon Rabin's work on fairness in games, we propose a partial equilibrium model of emotional response to policy whereby preferences are endogenous to policy choices. In accordance with evidence both from our own analysis and the field, we propose that confrontational policies (such as a sin tax) increase the marginal utility for a good, and that validating policies (such as a subsidy) also increases the marginal utility for a good. A social planner that ignores potential emotional responses to policy changes may unwittingly induce significant dead weight loss. Using our model, we propose a feasible method to determine if emotional deadweight costs exist, and to place a lower bound on the size of these costs.

Domestically funded (and performed) research and development (R&D) has historically been a major source of productivity gains in U.S. agriculture, and a principal source of R&D spillovers to the rest of the world. In the waning decades of the 20th century, U.S. policymakers opted to ratchet down the rate of growth in public support for food and agricultural R&D. As the 21st century unfolds, slowing growth has given way to real cutbacks, reversing the accumulation of U.S.-sourced public R&D capital over most of the previous century and more. The 2014 Farm Bill did little to reverse these long-run research funding trajectories—politicians failed to heed the economic evidence about the still substantial social payoffs of that research and the consequent slowdown in U.S. agricultural productivity growth associated with the spending slowdown. Meanwhile, R&D spending by other countries has been moving in different directions. We present new evidence that today's middle-income countries—notably China, Brazil, and India— are not only growing in relative importance as producers of agricultural innovations through investments in public R&D, they are also gaining considerable ground in terms of their share of privately performed research of relevance for agriculture. The already substantive changes in global public and private R&D investment trajectories are accelerating. If history is any guide to the future, these changing R&D trajectories could have profound consequences for the competitiveness of U.S. agriculture in the decades ahead.

The 2014 farm bill reduced expected budgetary costs of US farm programs, according to estimates prepared by the Congressional Budget Office. Cost projections are very sensitive to market conditions and program participation assumptions, and stochastic analysis indicates that farm program costs could easily differ from expected values by $5 billion or more in any given year. By replacing direct payments with new policies that make payments tied to market prices and yields, the bill could have important World Trade Organization (WTO) implications. If the new policies are classified as non-commodity specific amber box support, projections indicate that existing WTO limits on the current Aggregate Measure of Support would not be exceeded on average, but could be under some market conditions. Furthermore, the new policies are very likely to exceed some WTO rules proposed by various parties in the Doha Round negotiations.

Limited access to healthy food is commonly regarded as a contributing factor to poor dietary choices. The objective of this article is to test this hypothesis in a French context given France's increasing obesity rates and incidence of poor dietary habits. We use data on fruit and vegetable consumption frequency and different food retail availability measures, for example the number of food stores, food surface area, and a dispersion measure based on store numbers, store types, and food area surface, from several data sources in France. We also employ different types of geographic units when measuring the food retail environment and instrumental variable model specifications to test the robustness of our results, which indicate that fewer but larger retail outlets increase the odds of consuming the recommended level of fruit and vegetables. We also find that an increase in food supply dispersion will improve fruit and vegetable consumption in Paris, but not in its suburbs.

This article examines bilateral trade patterns in the Asia-Pacific using a new model in which comparative advantage within the agricultural sector is linked to agro-ecological characteristics, and trade costs are product-specific. Bilateral market share is a function of productivity and trade costs. However, countries with similar land and climate characteristics systematically have high productivity in similar products making them disproportionately sensitive to changes in each other's trade costs. We use a random coefficients logit model to estimate a parametric distribution of comparative advantage and trade costs across products and calculate regional trade liberalization elasticities for each exporter in each import market. Unlike most existing models, the value of the elasticity depends on the degree to which liberalization includes competitors with similar comparative advantage within the agricultural sector. We find disproportionately larger trade elasticities under China-led liberalization relative to U.S.-led liberalization among close U.S. competitors compared to countries whose agricultural products are unlikely to compete head-to-head with U.S. exports. For the United States, we find that the \"lost opportunity\" cost of exclusion from regional liberalization is increasing in the extent to which its close competitors gain new access.

Community Supported Agriculture (CSA) contracts allow consumers to buy claims on a farm's future production. In turn, the consumer provides working capital to the farm during the growing season. CSA contracts also provide risk management for farmers with limited access to Federal crop insurance by transferring part of the farm's risk to the consumer. We derive a theory of CSA contract pricing for the two most prevalent types of CSA contracts: yield contracts, in which consumers receive a percentage of the farm's production, and weight contracts, in which consumers receive fixed quantities. We develop a two-period model in which expected utility maximizing producers and consumers engage in CSA contracting in the first period based on anticipation of yields and spot prices in the second period. Using the model, we generate several testable hypotheses to be explored in future research. Additionally, we present an overview of the data necessary to test the propositions and potential challenges that might arise in related empirical work.

Harvest by means of hunting is a commonly used tool in large carnivore management. To evaluate the effects of harvest on populations, managers usually focus on numerical or immediate direct demographic effects of harvest mortality on a population's size and growth. However, we suggest that managers should also give consideration to indirect and potential evolutionary effects of hunting (e.g., the consequences of a change in the age, sex, and social structure), and their effects on population growth rate. We define “indirect effects” as hunting-induced changes in a population, including human-induced selection, that result in an additive change to the population growth rate “lambda” beyond that due to the initial offtake from direct mortality. We considered 4 major sources of possible indirect effects from hunting of bears: (1) changes to a population's age and sex structure, (2) changes to a population's social structure, (3) changes in individual behavior, and (4) human-induced selection. We identified empirically supported, as well as expected, indirect effects of hunting based primarily on >30 years of research on the Scandinavian brown bear (Ursus arctos) population. We stress that some indirect effects have been documented (e.g., habitat use and daily activity patterns of bears change when hunting seasons start, and changes in male social structure induce sexually selected infanticide and reduce population growth). Other effects may be more difficult to document and quantify in wild bear populations (e.g., how a younger age structure in males may lead to decreased offspring survival). We suggest that managers of bear and other large carnivore populations adopt a precautionary approach and assume that indirect effects do exist, have a potential impact on population structure, and, ultimately, may have an effect on population growth that differs from that predicted by harvest models based on direct effects alone.