American Journal of Agricultural Economics最新文献

In the context of rural Bangladesh, we assess whether agriculture training alone, nutrition behavior communication change (BCC) alone, combined agriculture training and nutrition BCC, or agriculture training and nutrition BCC combined with gender sensitization improve: (a) production diversity, either on household fields or through crop, livestock, or aquaculture activities carried out near the family homestead; and (b) diet diversity and the quality of household diets. All treatment arms were implemented by government employees. Implementation quality was high. No treatment increased production diversification of crops grown on fields. Treatment arms with agricultural training did increase the number of different crops grown in homestead gardens and the likelihood of any egg, dairy, or fish production but the magnitudes of these effect sizes were small. All agricultural treatment arms had, in percentage terms, large effects on measures of levels of homestead production. However, because baseline levels of production were low, the magnitude of these changes in absolute terms was modest. Nearly all treatment arms improved measures of food consumption and diet with the largest effects found when nutrition and agriculture training were combined. Relative to treatments combining agriculture and nutrition training, we find no significant impact of adding the gender sensitization on our measures of production diversity or diet quality. Interventions that combine agricultural training and nutrition BCC can improve both production diversity and diet quality, but they are not a panacea. They can, however, contribute toward better diets of rural households.

Conducting experiments can be time consuming and expensive, and may not always be reasonable. Therefore, empirical research often derives structural parameters based on observational data and reduced-form econometric models. The state-contingent approach presents a consistent conceptual framework for analyzing producer decisions under uncertainty. However, application of this structural modeling approach has been hampered by data constraints, particularly the lack of information for mapping producers' stochastic outputs onto a set of the states of nature representing different uncertain events. Consistent mapping of uncertainty is particularly critical in the context of multiple output production where weather shocks often have different effects across crops and in microeconometric analyses when unobserved farm heterogeneity may confound the effect of uncertainty. Our study demonstrates how the application of reduced-form approaches can overcome constraints of structural econometric modeling associated with the lack of relevant data and presents an approach for identifying states of nature in the context of multiple output production using reduced-form econometric models of crop yield. In an empirical application based on Hungarian farm accountancy data, we demonstrate that the proposed approach allows a consistent mapping of production uncertainty in crop farming, utilizes panel data structure, and controls for potential endogeneity due to unobserved farm heterogeneity. We anticipate the presented approach to be useful for developing further the state-contingent approach and to stimulate further studies combining the strengths of structural approaches and reduced-form models.

Due to the nature of nitrogen cycling, policies designed to address water quality concerns have the potential to provide benefits beyond the targeted water quality improvements. For example, actions to protect water quality by reducing nitrate leaching from agriculture also reduce emissions of nitrous oxide, a potent greenhouse gas. These positive effects, which are incidental to the regulation's intended target, are termed “co-benefits.” To quantify the co-benefits associated with reduced nitrate leaching, we integrate an economic model of farmer decision making with a model of terrestrial nitrogen cycling for the watershed surrounding Lake Mendota, Wisconsin, USA. Our modeling approach provides a framework that links air and water pollutants in an agri-environmental system and offers a direction for future studies. Our model results highlight the finding that the co-benefits from nitrous oxide abatement are substantial, and their inclusion increases the benefit–cost ratio of water quality policies. Consideration of these co-benefits has the potential to reverse the conclusions of benefit–cost analysis in the assessment of current water quality policies.

Past experiences influence choices, and people's preferences for more similar (habit-forming) or different (variety-seeking) experiences are reflected in these choices. We develop a structural estimation framework to capture whether people are habit forming or variety seeking and apply it to the choice of recreation site. This research contributes to the revealed preference literature by demonstrating how to account for habit or variety-seeking behavior in recreation site choice models in a two-stage framework. Using this framework, we estimate similarity weights that reflect the birders habit formation and variety seeking preferences. Predicted probabilities from the first stage model are then incorporated into the second stage, a mixed logit recreation site choice model of bird watching trips from eBird, by their members. We find that including the dynamic elements of choice, specifically variety-seeking behavior, can double the estimated willingness to pay (WTP) for individual sites relative to the static model. Although our sample of bird watching trips taken by eBird members is a sample of convenience, these results suggest that static models of recreation site choice are a lower bound on our recreation demand WTP estimates. We find variety-seeking preferences are related to land cover and the site's fixed attributes, whereas habit formation appears for seasonality in the bird watching context.

The Conservation Reserve Program is the largest agricultural land retirement program in the United States, with more enrolled acreage entering the program through a competitive auction called the General Signup than any other component. In this study, we assess the land use impacts of the Conservation Reserve Program by observing the land use decisions of parcels following the 2016 General Signup. We estimate land use impacts using a regression discontinuity design based on the Environmental Benefits Index, the program's selection and ranking mechanism. Our estimates largely rely on the auction design of the General Signup, such that we observe the land use decisions of rejected offers. We also use information on the rental rates of these offers to understand what the program pays to retire land in different uses. We estimate that a marginal acre of land enrolled in the Conservation Reserve Program replaces 0.30 acres in cropland, 0.25 acres in mixed forage, 0.32 acres in grassland, 0.12 acres in idle or fallow land, and 0.01 acres in timberland. We also find that enrollments from newly offered fields are more likely to displace cropland and less likely to displace grassland than returning fields. Consequently, we estimate that new enrollments lead to 47% greater reductions in water-driven erosion and 12% greater reductions in wind-driven erosion, compared to fields with prior enrollment.

Assessing the effects of weather and climate on agricultural production is crucial for designing policies related to climate change adaptation and mitigation. A large body of literature has identified the detrimental effects of climate change on crop yields worldwide, and farm-level adaptation has been shown to mitigate the adverse effects on agricultural production. In this study, we employ a structural model to examine farm production responses to ongoing weather trends. We investigate how farmers adjust output and input decisions by estimating a system of output supply and input demand functions, controlling for nonrandom crop selection. Using panel data with 14,796 observations reflecting 1638 German crop farms (1996–2019), we find that both the expected and realized weather determine farmers' production decisions. In the event of a drought, the supply of most considered crops and the demand for fertilizer decrease. The drought shock has also lasting effects on farmers' production decisions, with a reduced supply of protein crops and an increased level of root crops production in subsequent years. These findings highlight the need to account for farm-level production responses when assessing weather and climate impacts.

Monitoring smallholder agricultural productivity growth, one of the targets of the Sustainable Development Goals, rests on accurate measures of crop production and land area. Existing methods and protocols for measuring smallholder production and plot size are prone to various sources and forms of mismeasurement. Inaccuracies in production and land area measurement are likely to distort descriptive and predictive inferences. We examine the sensitivity of empirical assessments of the relationship between agricultural productivity and land area to alternative measurement protocols. We implement six production and six land area measurement protocols, and show that most of these protocols differ systematically in their accuracy. We find that an apparent inverse size–productivity relationship in our data is fully explained by measurement error in both production and plot size. Moreover, we show that some of the previously used “gold standard” measures are themselves prone to nonclassical measurement error, and hence can generate spurious inverse size–productivity findings. Our results also show that slight improvements in the precision of objective measures significantly reduce the inferential bias associated with the size–productivity relationship.

A large literature has assessed the impacts of climate change on agricultural production by estimating reduced-form models of crop yields conditionally on weather and individual fixed effects. The estimates obtained are usually interpreted as the weather impacts on yields once farmers have adapted. Yet, few attempts have documented that farmers do adapt to weather, and none have verified that these adjustments actually impact crop yields. Our objective here is to unpack how weather affects agricultural production by developing a structural model that explicitly accounts for both the plants' biophysical and farmers' behavioral responses to weather. Considering adaptation during the growing season through fertilizer and pesticide applications, our approach allows us to distinguish the “direct” weather effects (i.e., the agronomic impacts of weather changes on plant growth per se) from the “indirect” weather effects via farmers' input choices (i.e., the adaptation impacts). We estimate the underlying structural model using farm-level data from the Meuse French department, which provides details of fertilizer and pesticide uses by crop. We show that the reduced-form and structural estimates indicate similar weather impacts on crop yields, for a large range of sensitivity analyses. Our structural estimates indicate that the adaptation effects are sizable and that farmers' adjustments reduce projected damage from climate change. In our illustrative case, farmers' adaptation offsets between one-quarter to two-thirds of the negative agronomic impacts of future warming on crop yields. Our analyses exhibit that commonly used reduced-form models of crop yields inherently capture these within-season behavioral responses to weather.

Inadequate information on the benefits of and knowledge about innovative agricultural technologies continue to be a major constraint to technology adoption among smallholder farmers in developing countries. The low adoption of new technologies is one of the causes of low productivity and high poverty incidence among smallholder farmers, particularly in Africa. In this paper, I briefly review the literature on social networks and technology diffusion, and argue that the diffusion potential of social networks is underexplored. I then present results from two empirical studies on the impact of social networks on the adoption of improved crop varieties in Ghana and Ethiopia. The results reveal that farmers' peer adoption decisions and experiences, as well as information from trained development agents positively and statistically influence their adoption decisions. I also find that network structural characteristics such as lower segmentation within networks, high credibility of the information, and high effectiveness and efficiency of the amount of information flow tend to improve information acquisition and speed up diffusion of improved crop varieties.

Preference heterogeneity in food demand has important health and equity implications for targeted and broad-based taxes and subsidies intended to enhance diet quality and reduce obesity. We study the role of obesity in the purchases of food at home and food away from home using data from the nationally representative National Household Food Acquisition and Purchase Survey. We develop a method for incorporating the complex survey design and retail scanner data into the estimation of a 21-good Exact Affine Stone Index demand system with endogenous prices and truncated purchases. We find significant preference heterogeneity associated with the obesity status of household members. Counterfactual simulations find that (1) a sweetened beverage tax is effective in increasing the healthfulness of purchases by lower income obese consumers; (2) the nutritional benefits of a fruit and vegetable subsidy are concentrated on nonobese consumers with little improvement in obese consumers' Healthy Eating Index and an increase in their total calories purchased; and (3) a fiscally neutral healthy food subsidy fully funded by an unhealthy food tax benefits nonobese consumers both financially and nutritionally more than it does obese consumers. These findings show that lowering healthy food prices without raising the cost of unhealthy foods is unlikely to reduce obesity. Policymakers in favor of a systems approach of simultaneously taxing unhealthy foods and subsidizing healthy foods should be mindful of the distributional effects of this policy on obese consumers and the lower income population.