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Farmers and farm workers are critical to the secure supply of food, yet this population is potentially at high risk to acquire COVID-19. This study estimates the prevalence of COVID-19 among farmers and farmworkers in the United States by coupling county-level data on the number of farm workers relative to the general population with data on confirmed COVID-19 cases and deaths. In the 13 month period since the start of the pandemic (from March 1, 2020 to March 31, 2021), the estimated cumulative number of COVID-19 cases (deaths) was 329,031 (6,166) among agricultural producers, 170,137 (2,969) among hired agricultural workers, 202,902 (3,812) among unpaid agricultural workers, and 27,223 (459) among migrant agricultural workers. The cases amount to 9.55%, 9.31%, 9.39%, and 9.01% of all U.S. agricultural producers, hired workers, unpaid workers, and migrant workers, respectively. The COVID-19 incidence rate is significantly higher in counties with more agricultural workers; a 1% increase in the number of hired agricultural workers in a county is associated with a 0.04% increase in the number of COVID-19 cases per person and 0.07% increase in deaths per person. Although estimated new cases among farm workers exhibit similar trends to that of the general population, the correlation between the two is sometimes negative, highlighting the need to monitor this particular population that tends to live in more rural areas. Reduction in labor availability from COVID-19 is estimated to reduce U.S. agricultural output by about $309 million.

The U.S. Food and Drug Administration has begun a public process to redefine how companies are allowed to use the term \"healthy\" on food packages. Although the definition is formulated based on the latest consensus in nutrition and epidemiological research, it is also important to understand how consumers define and understand the term if it is to be behaviorally relevant. This research is an exploratory study designed to provide a descriptive account of consumers' perceptions of and beliefs about the meaning of \"healthy\" food. A nationwide U.S. sample of 1,290 food consumers was surveyed in December 2018. Respondents answered 15 questions designed to gauge perceptions of healthy food and to elicit preference for policies surrounding healthy food definitions. Responses are weighted to demographically match the population. Categorical variables have a sampling error of ±2.7%. Exploratory factor analysis is used to determine latent dimensions of health perceptions related to food type. Consumers were about evenly split on whether a food can be deemed healthy based solely on the foods' nutritional content (52.1% believing as such) or whether there were other factors that affect whether a food is healthy (47.9% believing as such). Consumers were also about evenly split on whether an individual food can be considered healthy (believed by 47.9%) or whether this healthiness is instead a characteristic of one's overall diet (believed by 52.1%). Ratings of individual food products revealed that \"healthy\" perceptions are comprised of at least three underlying latent dimensions related to animal origin, preservation, and freshness/processing. Focusing on individual macronutrients, perceived healthiness was generally decreasing in a food's fat, sodium, and carbohydrate content and increasing in protein content. About 40% of consumers thought a healthy label implied they should increase consumption of the type of food bearing the label and about 15% thought the label meant they could eat all they wanted. Results suggest consumer's perceptions of \"healthy,\" which is primarily based on fat content, partially aligns with the FDA definition but also suggest consumers perceive the word as a broader and more nuanced concept that defies easy, uniform definition. Results highlight areas where nutrition education may be needed and suggest disclosures may need to accompany health claims so that consumers know what, precisely, is being communicated.

The promise of novel plant-based meat alternatives (PBMAs) to lessen the health and environmental impacts of meat consumption ultimately depend on market acceptance and the extent to which they displace meat in consumers’ diets. We use household scanner data to provide an in-depth analysis of consumers’ PBMA buying behaviors. PBMAs buyers tend to be young, single, female, college educated, employed, higher income, and non-white. About 20% of consumers purchased a PBMA at least once, and 12% purchased a PBMA on multiple occasions. About 2.79% of households only purchased PBMAs. About 86% of PBMA buyers also bought ground meat; however, PBMA buyers spent about 13% less on ground meat. Interestingly, after a household’s first PBMA purchase, ground meat consumption did not fall. The number of households buying a PBMA for the first time fell over the two year period studied, despite the increase in market share in the ground meat market.

New plant-based meat alternatives that aim to mimic the taste and texture of beef could have significant economic, environmental, and animal welfare impacts if they replace animal-based meats and reduce livestock production. Whether plant-based meat alternatives can achieve these ends depends on the extent to which consumers are willing to substitute for plant-based meat alternatives, the structure of the meat industry, and the inter-linkages of the livestock industry with the other parts of the economy. We construct and calibrate an economic model to estimate how a reduction in plant-based meat prices, or increases in demand for plant-based meat, in the United States affect cattle production. For every 10% reduction in price or increase in demand for plant-based meat alternatives, we estimate U.S. cattle production falls approximately 0.15%, U.S. cattle producers’ economic welfare falls by$300 million/year, and U.S. consumer welfare rises by $ 513 million/year. Increases in U.S. demand for plant-based meat alter trade patterns, leading to a reduction of beef imports and an increase in beef exports, a phenomenon that further reduces global greenhouse gas emissions and land use given the relative efficiency of U.S. beef production. For every 10% reduction in the price of plant-based meat alternatives, we estimate that the global reduction in emissions is equivalent to 0.41% of U.S. emissions from beef production and 1.4 % when including carbon sequestration from reforestation of abandoned cropland and pasture and reduced land-use change emissions.1 Even substantial reductions in prices of plant-based meat alternatives are unlikely to have substantive impacts on the U.S. cattle population and emissions, suggesting the need to also pursue alternative mitigation strategies, such as innovations to reduce the methane emissions per head.

New animal welfare policies on the horizon in many U.S. states have prompted debates about the cost of achieving happier hens and hogs. A recent policy change in California offers a unique opportunity to measure the economic repercussions of minimum space requirements for egg-laying hens. Using forecasting methods and structural break tests as applied to sixteen years of monthly data on egg production and input prices, we find that by July 2016, both egg production and the number of egg-laying hens were about 35% lower than they would have been in the absence of the new regulations. Out-of-state eggs were able to compensate for falling California production until around the time the new rules were implemented, at which point imports of eggs into California fell. For consumers, we estimate price impacts using panel structural break tests and difference-in-differences models as applied to five years of scanner data from the retail market for shell eggs in three California markets and three control markets. We find that the average price paid per dozen eggs was about 22% higher from December 2014 through September 2016 than it would have been in the absence of the hen housing restrictions. The price impact fell over time, from an initial impact of about 33% per dozen to about 9% over the last six months of the observed time horizon. These price increases correspond to welfare losses of at least $117 million for the three California markets over the observed time horizon. Our results suggest that because of the policy change, California consumers can expect to experience annual welfare losses of at least $25 million in future years from higher retail egg prices alone.

Because of the potential malleability of stated and revealed preferences for new food technologies and attributes, this research sought to determine consumers' food value systems by utilizing recent advances in best-worst scaling. Based on previous literature related to human values and food preferences, a list of eleven food values was compiled. Results reveal that on average the values of safety, nutrition, taste, and price were among the most important to consumers, whereas the values of fairness, tradition, and origin were among the least important; however, there was significant heterogeneity in the relative importance placed on food values. Results indicate that food values are significantly related to consumers' stated and revealed preferences for organic food.

This article investigates the distributional effects of the subsidized crop insurance program in the United States. An equilibnum displacement model is constructed, linking the supply of disaggregate farm commodities with final consumer food demands. Using state-specific data on farm commodity production, crop insurance payments, food expenditures, and federal tax payments, the welfare effects of the removal of the premium subsidies for crop insurance are calculated for each state in the United States. Results indicate that the removal of the premium subsidy for crop insurance would have resulted in aggregate net economic benefits of $622, $932, and $522 million in 2012, 2013, and 2014, respectively. The deadweight loss amounts to about 9.6%, 14.4%, and 8.0% of the total crop insurance subsides paid to agricultural producers in 2012, 2013, and 2014, respectively. In aggregate, removal of the premium subsidy for crop insurance reduces farm producer surplus and consumer surplus, with taxpayers being the only aggregate beneficiary. The findings reveal that the costs of such farm policies are often hidden from food consumers in the form of a higher tax burden. On a disaggregate level, there is significant variation in effects of removal of the premium subsidy for crop insurance across states. Agricultural producers in several Western states, such as California, Oregon, and Washington, are projected to benefit from the removal of the premium subsides for crop insurance, whereas producers in the Plains States, such as North Dakota, South Dakota, and Kansas, are projected to be the biggest losers.

A large body of literature suggests willingness-to-pay is overstated in hypothetical valuation questions as compared to when actual payment is required. Recently, \"cheap talk\" has been proposed to eliminate the potential bias in hypothetical valuation questions. Cheap talk refers to process of explaining hypothetical bias to individuals prior to asking a valuation question. This study explores the effect of cheap talk in a mass mail survey using a conventional value elicitation technique. Results indicate that cheap talk was effective at reducing willingness-to-pay for most survey participants; however, consistent with previous research, cheap talk did not reduce willingness-to-pay for knowledgeable consumers.

Although previous research has identified that consumers are willing to pay for traceability, it remains unknown which types of traceability information might have the highest value, and whether consumers have an intrinsic value for blockchain technology above and beyond the instrumental value of providing traceability. A choice experiment was conducted with over 1500 consumers in Hong Kong, South Korea, and the U.S. In all three countries, consumers were willing to pay premiums for beef with traceability related to all parts of the supply chain, country of origin, and temperature history; however, the preference ordering of beef from different countries varied across Hong Kong, South Korea, and the U.S. The intrinsic value of using blockchain to deliver traceability information differed by country and by attribute, and consumers in the U.S. were most sensitive to the information describing blockchain technology. Even when traceability conveys negative information, such as temperature rising above safe levels for a short period, we find that consumers prefer knowing to not knowing, suggesting uncertainty and ambiguity aversion.

We compare the ability of three preference elicitation methods (hypothetical choices, nonhypothetical choices, and nonhypothetical rankings) and three discrete-choice econometric models (the multinomial logit [MNL], the independent availability logit [IAL], and the random parameter logit [RPL]) to predict actual retail shopping behavior in three different product categories (ground beef, wheat flour, and dishwashing liquid). Overall, we find a high level of external validity. Our specific results suggest that the nonhypothetical elicitation approaches, especially the nonhypothetical ranking method, outperformed the hypothetical choice experiment in predicting retail sales. We also find that the RPL can have superior predictive performance, but that the MNL predicts equally well in some circumstances.