American Journal of Agricultural Economics最新文献

Choices by farmers—notably what crop to grow, where—are not only influenced by spatially sensitive environmental attributes but also economic factors that respond to changes in government policies. In South Africa, the policy stance toward agriculture swung toward an extended period of support spanning the middle of the 20th century. Subsequently, the agricultural support policies were eliminated in the post-Apartheid period beginning in the 1990s. Using a purpose-built, spatially explicit data set for South African agriculture spanning the period 1918–2015, we show these structural shifts in agricultural policy regimes concord with major shifts in national corn price trends and variability, and the area planted to corn (accounting for half the country's cropped area). More subtly, and much less studied, we reveal that these switching policy regimes also aligned with changes in the location of crop production, with pronounced consequences for crop output and climate risk. At its peak, policy-aligned crop movement in South Africa reduced corn output by between 7.9% and 15.3%, and placed production in areas with reduced and riskier rainfall patterns. Upon removal of the policy distortions, the decline in total corn area continued, and the crop largely reverted to its predistorted, less climate-risky geographical locations. The geographical sensitivities of the agricultural policy–production–climate risk nexus we reveal suggest these locational aspects deserve more concerted analytical and policy design attention, especially in light of the longer run, spatially sensitive production and food security risk implications of the changing climate realities facing agriculture the world over.

In their in situ habitat, renewable resource populations are subject to stochastic growth caused by environmental variability such as fluctuations in upwelling conditions or temperature. In this paper, we examine the effects of this type of uncertainty on the noncooperative harvest decisions made by harvesters exploiting a common-pool renewable resource. To do this, we extend the related literature on dynamic resource extraction games based on Markov strategies to allow for asymmetric extraction costs and general economic, biological, and environmental conditions. We find equilibrium behaviors that can reverse conventional wisdom. For example, in response to increasing risk caused by anticipated higher variability in biological growth, a harvester may choose to enhance conservation efforts, whereas another harvester diminishes his escapement. Increasing risk can lead to conflicts as it may increase a harvester's payoff while causing a loss to another harvester. In response to an increase in the discount rate, we find that strategic interactions can give rise to greater conservation efforts. Overall, this paper highlights the importance of adequately accounting for uncertainty and strategic behaviors in renewable resource management.

Electronic commodity trading witnesses a massive volume of order messages every trading day, but little is known about their informativeness. We examine limit order dynamics and their role in price discovery in the Chicago Mercantile Exchange (CME) corn, soybean, and wheat futures markets from January 2019 to June 2020, using order-level data. Between 75% and 79% of the large number of limit orders submitted are then deleted, which contrasts with the much smaller proportion getting executed or revised. Aggressive trades and limit orders substantially contribute to price discovery, whereas nonaggressive trades and limit orders, representing most market events, play a minor role. Following public information releases, there is a shift in trading strategies, with trades contributing more to price discovery and aggressive limit orders contributing less, compared to nonrelease days. Our findings suggest that most limit orders in agricultural futures markets continue to play the traditional role of uninformed liquidity provision.

Economic sanctions are more popular than ever. But do they affect agricultural trade? Combining two new datasets and capitalizing on the latest developments in the empirical structural gravity literature, we investigate the effects of sanctions on international trade of agricultural products. We find that trade sanctions impede agricultural trade, whereas other sanctions do not show any significant impact. Complete trade sanctions have led to about a 67% decrease in the agricultural trade between the sanctioned and sanctioning countries, or a corresponding tariff equivalent of 25%, and we also obtain significant estimates for partial sanctions. At the industry level, we find substantial heterogeneity depending on the sanctioning and sanctioned countries, the type of sanctions used, and the direction of trade flows. The 2014 sanctions on Russia substantially decreased Russia's agricultural trade, mainly due to reduced trade with the EU but also due to reduced trade with other countries. Although no definitive evidence exists that sanctions alter the actions of governments of receiving countries, this paper provides broad evidence that sanctions hamper agrifood trade and hurt producers, consumers, and real output.

We examine intra- and intergenerational food security dynamics in the United States using longitudinal data from the Panel Study of Income Dynamics (PSID) while accounting for measurement error. We apply recently developed methods on the partial identification of transition matrices and show that accounting for measurement error is crucial as even modest errors can dwarf the information contained in the data. Nonetheless, we find that much can be learned under fairly weak assumptions; the strongest and most informative assumption being that measurement errors are serially uncorrelated. In particular, although the evidence—both intragenerational and intergenerational—is consistent with significant mobility, we also find food security status to be persistent for at least some households in the tails of the distribution. We further document some heterogeneities in dynamics across households differentiated by race and education. Finally, the impact of measurement error in the context of underlying dynamics is widely applicable to other areas of applied microeconomics generally as well as to food security dynamics in less developed countries specifically.

Organic food production growth has remained relatively slow compared to organic retail sales growth in the United States. This paper questions whether the conduct of downstream agents plays any role in explaining the difference. Mainly, we shed light on structural differences between organic and conventional fresh fruit and vegetable markets by examining differential price pass-through rates. We estimate a rolling-window retail pricing model using retail and wholesale price data from five metropolitan statistical areas with terminal markets in the United States. We find that pass-through rates are 10 to 15 percentage points lower in the organic market, and the differences are statistically significant. We also find that the gap between pass-through rates narrows as the organic market share increases. Our results suggest the organic market is significantly less competitive than the conventional market. The implication is that farmers may have less incentive to convert to organic farming as they may not capture the full retail price premium consumers pay.

In many markets, consumers believe things about products that are not true. We study how incorrect beliefs about product quality can persist even after a consumer has used a product many times. We explore the example of fertilizer in East Africa. Farmers believe much local fertilizer is counterfeit or adulterated; however, multiple studies have established that nearly all fertilizer in the area is good quality. We develop a learning model to explain how these incorrect beliefs persist. We show that when the distributions of outcomes using good and bad quality products overlap, agents can misattribute bad luck or bad management to bad quality. Our learning model and its simulations show that the presence of misattribution inhibits learning about quality and that goods like fertilizer with unobservable quality that are inputs into production processes characterized by stochasticity should be thought of as credence goods, not experience goods. Our results suggest that policy makers should pursue quality assurance programs for products that are vulnerable to misattribution.

We examine the effects of income uncertainty on mental health in Vietnam. We assess this issue using volatility in the price of coffee, a key export commodity, that exposes small coffee farmers to income uncertainty. Using household panel data collected over 2016–2020, we find an increase in volatility of the international coffee price to be positively associated with psychological distress among coffee farmers. The magnitude is greater for men, and the findings are robust to several checks. These results are further substantiated by corresponding estimates for related health measures and self-reported happiness. Channels include an increase in mental stress due to pessimistic expectations of future economic well-being, increased cognitive load and alcohol consumption, and reduced social capital. The results highlight the psychological toll of living with income uncertainty and provide support for the provision of social safety nets that protect farmers from frequent commodity price fluctuations.