American Journal of Agricultural Economics最新文献

Agricultural production is the largest contributor of nitrogen and phosphorus pollution in lakes, rivers, and streams in the United States. The effectiveness of agricultural conservation programs that encourage farmers to adopt certain practices to reduce this water pollution, once implemented, is an open question. We develop a unique data set combining the spatial structure of the watershed river system, the timing of federal conservation contracts, water quality measurements, land use, land cover, and weather data to study the effect of conservation contracts on nitrogen and phosphorus levels in the Wabash River watershed, which drains Indiana and Illinois. We develop econometric models that generate a causal understanding of the effectiveness of these conservation contracts for reducing nitrogen and phosphorus levels in the surface water system. We find that at current treatment levels, these programs reduce surface water pollution only during relatively dry periods. The efficacy of these programs in the study area is highly sensitive to precipitation to the extent that average precipitation can eliminate the nutrient loss reduction benefits of conservation program installations at current treatment levels. Therefore, we find weak evidence to support ambient downstream water quality improvements resulting from program investment levels to date. We anticipate this work will motivate further inquiry into the manner in which these conservation programs have or have not been effective.

Balancing conflicting policy goals is a key challenge in the transition to sustainable agricultural systems. An important example is herbicide use reduction potentially conflicting with conservation tillage—which often strongly relies on herbicide use. We investigate the joint uptake of two agri-environmental schemes, conservation tillage and herbicide-free agriculture systems. To this end, we use a combination of detailed survey data on farmer behavior, environmental and agronomic data, and census data on the complete population of all farmers from Switzerland. Findings based on a multinomial logit and fixed effects multinomial logit indicate that, conditional on observable factors, the systems are not complementary, but joint adoption occurs for 35% of farmers. Behavioral factors explain 26% of joint adoption behavior, emphasizing the role of risk taking, openness to innovation, and biodiversity valuations in farmers' decisions. Our analysis provides broader implications for assessing and navigating conflicting sustainability goals in agriculture globally.

Climate change is amplifying the threat of drought to food security. Despite a growing literature examining how drought affects crop yield, previous studies have mostly overlooked the impacts of drought on production through planting and harvesting decisions, which are crucial climate adaptation strategies for farmers. To address this gap, we study corn and soybean production in U.S. counties from 2001 to 2023, examining drought impacts on acreage decisions—planned acres, prevented planting, crop abandonment—and yield within a unified framework. Decomposition analysis shows that, together, acreage decisions account for up to 25% and 20% of drought impacts on corn and soybean production, respectively. Moreover, drought affects production throughout the crop year, not solely during the growing season. Specifications that omit preplanting- and planting-season drought underestimate the adverse impacts of growing-season drought on the harvested ratio, yield, and production of corn and soybeans. Our findings highlight the importance of considering adaptive behavioral responses when quantifying climate-related damage in agriculture.

Nonclassical measurement error threatens the validity of empirical economic models. We examine the extent to which land value measures that are commonly used in studies of the US farmland market are subject to nonclassical measurement error. We consider differences in county-level land values from two popular data sources: (1) self-reported land value assessments from the 2017 US Census of Agriculture and (2) observed sales prices from agricultural land transactions (2013–2017). We find that the difference between these data sources, which we interpret as measurement error, is correlated with multiple determinants of land value. Farmland market characteristics, including market size, are negatively related to this difference, implying that more information in a market allows respondents to better update their priors about their land's value. Survey respondents are also slow to update their assessments in areas of rapid recent price changes. Surprisingly, we find measurement error in farmland value to be correlated with climate. To illustrate the empirical implications, we conduct a Ricardian analysis of agricultural climate change impacts and find that temperature, in particular, is differentially capitalized into self-reported land value estimates and sales prices. Under certain climate specifications, using self-reported land values generates climate damage estimates that are more pessimistic but ultimately not significantly different from those using sales prices. However, regional heterogeneity highlights where this difference is significant, namely the northern half of the eastern United States. More generally, our findings highlight important considerations for researchers relying on farmland values from alternative data sources.

We study the role of incentives in inducing sabotage in political contents, vis-à-vis natural resource windfalls. The latter induce plausibly exogenous increases in contests' stakes by extending opportunities for policy implementation or private gain upon winning and enhancing incumbent advantage. A model of political contests with endogenous sabotage indicates that higher stakes increase sabotage in political campaigns. We validate these predictions using over 5 million TV ads from United States gubernatorial elections (2010–2020), leveraging plausibly exogenous variations in states' natural resource endowments. Results show that resource windfalls significantly escalate negative campaigning: A standard deviation increase in resource windfalls leads to a 10% rise in campaign negativity. We show that this effect is primarily fueled by corruption and observed most strongly in symmetric, more competitive environments.

Farm delinquency is linked to many negative indicators of farm survival, including increased risk of bankruptcy and farm failure. Minority farmers and ranchers (MFR) have been found to exhibit higher rates of delinquency on U.S. Department of Agriculture (USDA) Farm Service Agency (FSA) loans compared to their non-Hispanic White male counterparts. These findings persist even after accounting for economic/financial factors expected to predict loan repayment performance. In this study, to further explore the existing discrepancy between loan default rates for MFR and White, non-Hispanic borrowers, we look more broadly than financial indicators and introduce MFR representation on the FSA County Office Committee (COC) as a proxy for the local cultural climate in an agricultural community. Using changes in COC membership demographics over time and across counties, this study suggests that MFR representation on the COC is associated with a lower probability of MFR delinquency by roughly 10 percentage points. With the probability of delinquency also being about 10 percentage points higher among MFR, the effect represents a significant improvement in loan repayment outcomes for the group. The FSA COCs represent an important linkage between the USDA and the local agricultural community. Moreover, elected minority representation on COCs can be considered as indicative of supportive cultural climates for minorities in agriculture. Given that COC membership composition may represent a proxy for local cultural climate in agriculture, this research raises interesting questions about the potential relationship of MFR representation and community engagement, to FSA program performance.

Understanding the impacts of environmental conditions is critical for shaping policies aimed at improving human capital outcomes in developing contexts. This study utilizes individual-level data on children from Pakistan to investigate the impact of rainfall shocks, from the in-utero stage to age 16, on human capital development. The results reveal that positive rainfall shocks reduce cognitive performance in older children (ages 11–16), as their school attendance declines and their participation in labor increases. In contrast, younger children (ages 5–10) are mostly unaffected. Positive rainfall shocks during school transition and early teenage years (ages 11–16) reduce the overall educational attainment among young adults (ages 16–30) and increase the likelihood of marriage between ages 18 and 24. Conversely, children born during years of positive rainfall shocks exhibit improved physical and cognitive development, and are less likely to engage in child marriage or child labor. These long-term effects are especially pronounced among girls.

Smallholder farmers in low- and middle-income countries face several constraints to technology adoption. We test the relative efficacy of interventions designed to incentivize the production and consumption of a biofortified orange-fleshed sweet potato crop by female farmers in Uganda. Through a clustered randomized controlled trial involving more than 8000 female farmers across 210 communities, we track the impact of the interventions on adoption, consumption, and health outcomes, both in the short term and long term. Our findings suggest that the provision of inputs and agricultural extension is an effective approach to adoption, leading over 60% of households to cultivate and 50% to consume the crop. Nutrition training emphasizing the crop's health benefits has limited impact on cultivation, but it leads 20% of households to consume the biofortified crop. Combining the two approaches with supplementary credit and insurance products has limited marginal effects on adoption. We also observe improvements in dietary diversity resulting from the tested interventions, along with spillover effects through social networks in neighboring communities. We find little evidence of treatment effects on higher-order outcomes such as visual acuity, child health and nutrition, or income.

Many fish consumers reveal a preference for sustainably sourced seafood in their purchasing decisions. We propose a bioeconomic modeling approach and an empirical strategy, based on a discrete choice experiment, to quantify the resulting effects on fishery dynamics and to derive implications for efficient fishery management. We show that a “consumer stock effect” arises, which stabilizes a fishery under open access and which decreases catches under economically efficient management. We quantify these effects for the Western Baltic cod fishery.

Most studies on gender gaps in agricultural productivity leverage within-household differences between plots managed by women and men. Such a gender-based division of plot management simplifies empirical tests for productivity differences, but it is not a common arrangement outside some locations in sub-Saharan Africa. In most rural households, women and men jointly participate in production, complicating the identification of gender-based productivity differences. This study proposes a broader empirical test of productivity gaps that applies to such systems and is rooted in gender-based inequities rather than gender per se. We explore productivity gaps in rice-cultivating Indian households, where women and men perform distinct cultivation tasks. We measure productivity gaps based on the differential use of family and hired female labor across households and then compare them with gaps based on the differential use of family and hired male labor. Using plot-level data, we identify significant gender-based productivity gaps after controlling for input use and plot- and household-level characteristics, along with using village fixed effects and machine learning estimators to address selection and model misspecification concerns. We find that households using family female labor have lower agricultural productivity than those also hiring female workers, such that forgone production value is greater than the cost of hiring women. We find suggestive evidence that this gap stems from skill differences between hired and family female workers. In contrast, we find no similar gap regarding male labor use. Overall, household welfare is lower because of gender-based inequities, and highlights the potential productivity implications of expanding women's labor choices in both on- and off-farm roles.