Applied Economic Perspectives and Policy最新文献

In this paper, we discuss the reasons why agricultural and applied economics and similar departments are often stand-alone academic units. The factors that affect and shape the relationship of agricultural and applied economics faculty and departments with those from general economics departments are discussed. We present case studies of three universities having different relationships with general economics faculty at their respective universities: a merged unit, an unmerged unit, and a never-merged unit. We conclude with rationale for the existence and future trajectory of agricultural economics and related academic units at Land Grant Universities.

This study uses statistical learning methods to identify robust coverage alternatives for the Pasture, Rangeland, Forage (PRF) insurance program. Shrinkage and ensemble learning techniques are adapted to the context of the PRF coverage selection process. The out-of-sample performance of the proposed methods is evaluated on 116 representative grids throughout Texas during 2018–2022. Ensemble learning methods generated more stable coverage choices compared with the other selection strategies considered. Depending on the target return, a reduction in the prediction error between 5% and 14% was observed. Furthermore, the proposed coverages can provide a broader protection than current coverage choices made by farmers.

Forecasts are common in agricultural settings where they are routinely used for decision-making. The advent of the computer age has allowed for rapid generation of individual forecasts that can be updated in real time. It is well known that the selection and use of a single forecast can expose the forecaster to serious error as a result of model mis-specification. Forecast combination avoids this problem by combining information from different forecasts. Although forecast combination can be as simple as averaging across forecasts, advances in machine learning have made it possible to combine forecasts according to more complicated weighting schemes and criteria. We provide an overview of forecast combination techniques, including those at the frontier of current practice and involving machine learning. We also provide a retrospective on the use of forecast combination in agricultural economics and prospects for the future. Several of the techniques are illustrated in an application to forecasting nationwide corn and soybean planted acreage and we demonstrate how forecast combination can improve expert USDA projections.

National food security data have been vital in raising public awareness and motivating policy. This paper uses cross-survey multiple imputation as a flexible way to assess within-state food security patterns that cannot be measured well with the Current Population Survey. Using a CPS-based model, we impute food security status to households in the much larger American Community Survey. We illustrate the value of this approach by showing how grouping households by demographic or geographic attributes can provide insight into disparities within states by race and ethnicity, as well as variation in food security across substate geographies.

The aim of this paper is to discuss the challenges in attracting and securing adequate budgets for departments of agricultural and applied economics, while recognizing that the institutional and political contexts matter. Agricultural and applied economics departments that operate with an entrepreneurial mindset, that maintain and grow their student numbers, and that have a vibrant demand for their extension and research activities will thrive. The good news is we often have considerable control over the factors that contribute to our longer-term success.

This paper analyzed farmers' willingness to accept (WTA) payment and uncertainties toward carbon market through a 2021 U.S. Midwest farmer survey. The findings showed that farmer carbon supply was elastic at intermediate prices ($20–50/Mg), but inelastic at low ($10–20/Mg) and high ($50–70/Mg) price levels. While perceived co-benefits play significant roles in promoting participation at low-price levels, variables such as age, education, farm size, and soil quality are more likely to influence producers' choices at intermediate- and high-price levels. To enhance farmers' support for carbon programs, measures should be taken to improve benefit, while reducing cost and uncertainty.

Using National Agricultural Workers Survey (NAWS) data, we examine which farmworkers are unionized and whether their status differs systematically from non-unionized farmworkers. Logit results indicate farmworkers are less likely to be unionized if they are Black, unauthorized to work in the U.S., less educated, have English proficiency, work for farm labor contractors (versus growers), and cultivate field (vs. horticulture) crops. Blinder-Oaxaca decomposition reveals that union members earn $0.87 more in hourly wages, are 4.8% points more likely to receive a bonus, and are 15.6% points more likely to have employer-provided health insurance than comparable non-unionized farmworkers.

Blacks have been systematically under-represented in the Agricultural Economics profession, representing only 7% of agricultural economists in academia and between 5% and 10% in the private and public sectors, respectively. Although different policies and funding strategies have been implemented to increase the representation of minorities in the profession, these numbers have not shown significant improvements over time. This paper provides an overview of the history, role, and struggles of 1890 Land-Grant Historically Black Colleges and Universities in general, and in particular, their agricultural economics and business (AEB) Programs. Recommendations and thoughts on how to increase diversity in AEB programs are also discussed.

There is an international consensus that Africans consume less fruits and vegetables (FV), and animal products (AP) than they need for adequate nutrition, and that production and supply chains of these products are constrained. Yet, in this paper, we show that despite these problems, there is a lot of dynamism in demand and supply of these nutrient-dense products in Africa: (1) macro evidence of “domestic supply booms"—with supply growing as fast as or faster than in Asia and Latin America; (2) only 2–4% of FV, and 10% of AP consumption in Africa is imported, and only about 1–2% of the output of FV and AP is exported: the supply booms have thus been overwhelming domestically sourced, not imported; (3) micro evidence of substantial shares of consumption of FV and AP in total food consumption, similar to Asia's; (4) evidence of rapid development of spontaneous clusters of farms and off-farm SMEs (output wholesalers, logistics, processors, and agro-dealers supporting farmers). These clusters are important in fueling the supply booms. Illustrative cases from Ethiopia, Nigeria, Tanzania, and Zambia are presented. We recommend that African governments and international partners: (1) internalize the fact that these spontaneous clusters are forming and already fueling supply booms; (2) note that important drivers of the booms have been government investments in wholesale markets, roads, and other infrastructure like electrification, and agricultural research/extension; (3) leverage and support existing spontaneous clusters and help new ones to form by greatly increasing those three types of public investments.

We investigate the distinct associations between Supplemental Nutrition Assistance Program (SNAP) participation and different experiences of food-related hardship. Using a generalization of the Rasch model with USDA Economic Research Service 2022 data for 10 adult-referenced food security survey items, we find evidence of uniform differential item function. The gap in odds of response between the first item (food-related worry) and the third item (difficulty acquiring balanced meals) was larger for SNAP households than for non-SNAP households. Similar differences were observed for other survey items. We consider whether SNAP policy or program changes could increase beneficial impacts differentially for particular food-related hardships.