Bovine trichomoniasis is a venereal disease that causes significant losses in the US beef industry. The USDA Animal and Plant Health Inspection Service views bovine trichomoniasis as endemic and delegates control to state agencies and producers. Disease management’s positive externalities are not reflected in a producer’s profit maximization problem, leading to potentially suboptimal levels of control. Our objective was to assess the economic impacts of 50% and 100% reductions of herd-level bovine trichomoniasis prevalence. The cumulative present value of net welfare increased by $388.856 and $193.222 million under the 100% and 50% scenarios, respectively. Feeder cattle producers and retail beef consumers benefit most from enhanced control.

This study analyzes empirically and graphically the effects of the relative market price level on the premiums and discounts received associated with alfalfa hay quality. Findings indicate that at times when alfalfa prices are elevated relative to the average, there is no significant impact on the average premiums and discounts received. Conversely, at times when alfalfa prices are depressed relative to the average, there are statistically significant variations in the premiums and discounts across quality grades compared with a market characterized by average prices. Understanding these dynamics can aid producers in optimizing production decisions and assist consumers in managing input costs.

Relationships between broiler cut prices are evolving as production and consumer preferences change. Stronger price relationships are observed within white and dark meats categories than between them. This can be attributed to the unique substitutability of cuts within categories, while weaker relationships between categories arising from their roles, white meats are predominantly consumed domestically, while dark meats are more oriented towards export. The analysis also shows that own price is the main driver of price variation, suggesting that treating chicken as a single category may be misleading. Considering different cuts may offer valuable insights into economic/market analysis for other meats.

Past research shows that farm animal welfare (FAW) policies can reduce consumer and retailer welfare, but producer welfare implications are less certain. This study uses equilibrium displacement modeling of the U.S. wholesale shell egg market to determine how the transition to cage-free egg sales could affect short- and long-run producer welfare. Under varying assumptions and retailer demand shifts, the results consistently demonstrate that producer profits are expected to decline as retailers pivot toward cage-free purchasing, holding all else constant. These findings help explain the tension surrounding FAW policies across the supply chain and can be used to inform industry and policymaker discussions on the topic.

Since early 2021, food prices in Britain have increased by 30%. Using monthly microdata, researchers have found that frictions in the UK’s new trade relationship with the European Union (EU) play an important part in this inflation. The trade relationship is evolving, with further changes expected in 2024. This article establishes a framework for identifying trade-related inflation in close to real time. Using programming techniques, we collect daily prices of over 100,000 supermarket items, covering 80% of the UK grocery market. We identify 1,200 products from 12 countries with a protected designation of origin (PDO). This allows us to link price changes to individual EU economies. Addressing the predominance of EU PDOs, we employ a large language model to discern product origins from additional web-scraped data, thus broadening our analysis to cover over 67,000 products. Since August 2023, we find that prices for EU-originating food products have increased at a rate of 50% higher than domestically sourced products. This study presents a unique methodological approach to dissecting food sector inflation, which is well-positioned to be used in a policy setting, allowing us to assess the possible impact of impending nontariff barriers at the GB-EU border in 2024.

This study explores several alternative specifications of futures-based forecasting models to improve existing approaches constrained by restrictive assumptions and limited information sets. In lieu of historical averages, our approaches use rolling regressions and include current market information reflected in the deviation of the current basis from its historical average. To mitigate potential challenges arising from nonstationarity and structural changes in the relationship between farm and futures prices, we employ a 5-year rolling estimation window. We find that a rolling regression approach offers significant improvements (as evidenced by our Modified Diebold–Mariano test) in the accuracy and information content of forecasts of cotton season-average prices (SAPs) mostly at short forecast horizons.

Cannabis regulatory reform has opened areas for product innovation and entrepreneurship. One dimension that has so far been understudied is the potential for cannabidiol (CBD) and tetrahydrocannabinol (THC) beverages. This study uses double-bounded contingent valuation techniques and parametric and nonparametric estimation procedures to assess consumer demand and willingness to pay (WTP) for various cannabis-infused beverages. By targeting a nationally representative sample of U.S. adults, the study finds that roughly half of consumers are willing to try cannabis-infused beverages. Among these respondents, cannabis-infused juices and sweetened iced tea elicit the highest mean WTP, though the WTP for other beverage options varies across demographics and consumer preferences. On average, the mean WTP for THC-infused beverages is 12.5% higher per 12 oz can than its CBD-infused counterpart, and younger consumers are willing to pay more for each of these products. These results have important implications for entrepreneurial decision-making, product development, and marketing strategies.

The goal of this paper is to systematically review the literature on United States Department of Agriculture (USDA) forecast evaluation and critically assess their methods and findings. The fundamental characteristics of optimal forecasts are bias, accuracy and efficiency as well as encompassing and informativeness. This review revealed that the findings of these studies can be very different based on the forecasts examined, commodity, sample period, and methodology. Some forecasts performed very well, while others were not very reliable, resulting in forecast specific optimality record. We discuss methodological and empirical contributions of these studies as well as their shortcomings and potential opportunities for future work.

The beef industry is facing increasing pressure to adopt sustainable practices, driven by environmental, economic, and social concerns. Designing effective policies that satisfy industry demands while aligning with public interests is a complex challenge. Using a nationally representative survey of 3,001 U.S. residents, we employ a best–worst scaling approach to assess preferences for nine beef sustainability policies. Results reveal consumers prioritize affordability of beef products and welfare of cattle as most important sustainability policies. Conversely, policies addressing greenhouse gas emissions from cattle production are least important, with less than 6% of respondents preferring them.

This study explores the economics of culling decisions in cow-calf operations in the Southern U.S. with a novel application of a dynamic mathematical programing model. The results provide an optimal culling strategy under the base model and a range of optimal strategies that vary with respect to different components such as fertility probabilities, prices, replacement costs, and pregnancy checking. The results suggest that producers should cull all cows that are older than age 10 and cows that fail to calve once they reach the age of 7. The sensitivity analysis underlines the impact of market conditions, replacement costs, and pregnancy check use on the optimal culling decisions.

Consumers often struggle to make their choice in the highly diversified wine market. With wine being an experience good, consumers must rely on extrinsic characteristics, e.g., information on the label. Thus, easily available quality signals like consumer ratings have become an increasingly useful and widespread tool. Vivino is one of the largest online wine communities with over 60 million users, which have more than doubled since 2018. Hence, users have easy access to peer ratings, while established wine expert ratings are being challenged. This study analyzes data from Vivino to explore factors affecting consumer ratings at different price points, considering several wine attributes like geographical indications, brand, and the so-called “community effect.” We show that there is a small but significant community effect on wine's perceived quality related to its popularity among users of the Vivino community, as well as effects from specific wine attributes. Moreover, we estimate a hedonic quantile model on similar price ranges to compare the effect of the same regressors on wine prices. Results contribute to a better understanding of how different factors affect consumers’ wine evaluations, allowing to compare their effect on the “pure” consumer preference (i.e., consumer ratings) and market value.

Causal flow analyses combined with time series analyses are used to examine price relationships among fresh broiler retail markets (Northeast, South, Midwest, and West). Results indicate structural changes have occurred in this industry. Reasons for changes in price relationships include the perishable nature of fresh broilers, along with vertical integration and increases in production and concentration in the industry. The four markets are integrated, but the level of integration has decreased over time. With the markets becoming more exogenous, there may be a decrease in society’s welfare. The South market is the most important market for price discovery.

We develop a theoretical framework and present a corresponding empirical analysis of the Food and Drug Administration’s irrigation water quality regulatory standard under the Food Safety Modernization Act using lettuce as a case study. We develop a stochastic price endogenous partial equilibrium model with recourse to examine the standard’s efficacy under various scenarios of foodborne illness severity, standard implementation, demand response to foodborne outbreaks, and irrigation costs. The stringency of regulation is evaluated with endogenous producer response to regulatory requirements and corresponding implications for economic surplus. The baseline results show that in the case of the lettuce market, the proposed microbial irrigation water quality regulation in the Food Safety Modernization Act (FSMA) is not cost effective relative to the existing Leafy-Greens Marketing Agreements relying on water treatment for mitigation of microbial contamination. However, FSMA can be cost effective if water treatment is sufficiently expensive.

We use a dynamic model of the U.S. apple industry separated into organic and conventional production to better measure the impacts of pest or disease outbreaks on producers and consumers, along with an equilibrium displacement model to simulate welfare effects from various shocks compared to a baseline. Our results show that the impacts of the outbreaks differ between organic and conventional production methods. Growers’ and consumers’ responses to shocks differ widely across the industry. Farmers and policy makers should use these findings to appropriately respond to different shocks and production methods.

This study investigates the effects of genetic improvement policies on dairy production, with a particular emphasis on Artificial Insemination projects. Furthermore, we evaluate the major barriers and challenges of Artificial Insemination projects including water scarcity. Using the data-driven synthetic control method, we found evidence that the Artificial Insemination projects caused milk production to increase by 59 thousand tons on average from 2008 to 2018. This could be correlated with food security (i.e., synergies), but increased dairy production may also place strain on Senegal’s water resources (i.e. trade-offs). To achieve a more efficient outcome, Senegalese dairy policies should consider the negative externalities of these projects on water resources.

This paper proposes an approach to determine efficient release prices on the Bordeaux en primeur (primary) market. The model exploits information from the secondary market to estimate efficient release prices. We apply the model to a representative sample of wines from the 2021 vintage. The results show that most chateaux released their wines at prices that were too high. The median overpricing is 5.2% but exceeds 30% for some wines. This situation may be partially attributed to excessively uniform pricing caused by the tendency of chateaux with similar status to release their wines at similar price levels.

This study builds upon the existing literature on the Working curve and backwardation to explore the impact of storage regimes on the volatility measures of substitute agricultural commodity markets. We investigate the impact of commodity fundamentals (storage regime and stocks-to-use ratio), commodity-specific financial variables (options hedging pressure-long and -short), world economic activity, market-wide volatility index, seasonality, and time-to-maturity on nearby and deferred implied volatility (IV) series of selected commodity pairs of corn-soybean and winter wheat-spring wheat. Our work confirms that, in some cases, grain and oilseed IV derived from options premia respond to shocks in commodity (and substitute commodity) fundamentals which are in line with the behaviour of volatility in futures markets. Own-storage regime effects on price variability are stronger in the selected markets, while spillover effects from substitute commodity storage regimes show a modest impact on volatilities. We also find some evidence for the stocks-to-use ratio of both corn and soybean to impact both their own and each other’s IV, while options hedging pressure has some impact only on wheat IVs.

As the market for fine-wine investing matures, basic questions of portfolio strategy remain unexplored. I evaluate how adding fine wine from the superstar châteaux of Bordeaux's Right Bank might complement the traditional focus on the five first-growths of Bordeaux's Left Bank. Fundamentals for the Right Bank's superstars are attractive: they produce roughly an order of magnitude less, face different production conditions, and receive equally impressive critical reviews. However, they receive far less attention than their Left Bank counterparts. To examine returns over the long run, I hand-collected 10,885 prices for eight wines from an archive of 391 Sherry-Lehmann catalogs, a New York City retailer, which began at the end of Prohibition. Using these historical price records, I compare the real returns from investing in the five Premier Cru to a portfolio that adds three superstar châteaux from the Right Bank: Ausone, Cheval Blanc, and Petrus. I find the geometric-average annual return was 6.78% in real terms from 1938 to 2017 for the joint portfolio, less than 0.01% different, but with better risk-reward as measured by the Sharpe ratio. Additionally, I find the life cycle of aging is substantially different across the two Banks, which could provide further diversification benefits for the strategic investor.

This paper investigates the relative importance of various attributes, including varietal, brands, and geographic origin, in explaining retail wine prices for the United States market. We use a metric based on the Shapely value, from cooperative game theory, in the context of an empirical hedonic price equation estimated using a large sample of retail wine sales for home consumption over the period 2007–2019. We find that brands alone explain more than 70% of the variation in wine prices, but geographic origin and varietals retain additional explanatory power. Furthermore, information about the geographic origin appears to be a considerably more important attribute than varietals.

Wine investment returns can come from overall market trends or price increases with age. Because of the short wine price histories available, market and maturation effects are difficult to separate. Consequently, researchers often obtain dramatically different estimates of investment returns. We find that data sample bias may be the hidden cause of the disparate estimates. In wine auction data, the sample bias refers to a shift in the distribution of which wines are traded as a function of their age. Such sample bias in panel data sampled across many different wine labels can distort the estimation of price increases versus age and consequently impact the estimation of market trends. This analysis shows that segmenting the analysis such that the data panels contain wine labels with similar trading characteristics can lead to a more stable estimation.

The analysis here looks at data from Bordeaux, Italy, Australia, and California. An Age-Period-Cohort (APC) analysis is applied to data panels from each region. Then the data in each region is segmented by a measure of popularity in order to reduce sampling bias. Data thus segmented is then re-analyzed to demonstrate the difference in estimating price appreciation lifecycles and market trends.