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 objective was to estimate the difference in cost, revenue, and profit between unassisted and assisted calvings on western Canadian cow-calf operations. Historical records of individual animal production measures from 2015 to 2020 and industry-described inputs were used in a modified decision tree model. The incidence of assisted calvings in heifers and cows was 4.6 and 2%, respectively. Assisted heifers and cows had an expected profit of −$227.43 and −$67.06 CAD per calving, respectively, while unassisted heifers and cows had an expected profit of −$76.11 and $120.12 CAD per calving, respectively. Calving assistance can impact the profitability of western Canadian cow-calf operations.

Past research has only studied genetic panel scores and feedlot performance. This research combines impacts of genetic panel scores on a cow-calf operation with previously estimated feedlot impacts to evaluate the potential for misaligned economic incentives in the beef industry. Calves that were higher genetic scores for two carcass traits, marbling and tenderness, had lower weaning weights and lower net returns. Correlations between genetic traits and cow size were small and mostly insignificant. The sum of the effects on feedlot and cow-calf sectors of a one-unit higher panel score totaled $-2.83 per cow year for marbling and $-4.93 per cow year for tenderness.

Is it possible to exploit cognitive biases so that a non-professional taster prefers one wine to several other absolutely identical wines? To address this question, three complementary experiments were carried out. Each time, five wines were tasted blind in a tasting laboratory by 24 to 34 tasters. Converging evidence from the experiments shows that participants were not capable of identifying that some of the wines they were tasting were absolutely identical. Moreover, the results show that by providing information about the wines’ ratings, prices, or reputation, tasters’ expectations can be modified, and, as a result, their evaluations of the wines can be altered. Specifically, we show that it is possible to modify the ranking between different wines and to get tasters to prefer a wine over other absolutely identical wines. Finally, a surprising finding was that experienced tasters express stronger opinions and adapt their evaluations more strongly after being given manipulative information on the wines they taste.

Agritourism and direct-to-consumer sales are increasingly used as diversification strategies to generate additional farm revenue streams. Yet despite their growing importance, the impacts, interactions, and adoption of these strategies remain poorly understood. Here we use univariate and bivariate local Moran’s I statistics to identify agritourism and direct-to-consumer sales hotspots in the United States and a Seemingly-Unrelated-Regression Spatial Durbin Model to examine the association between agritourism and direct farm sales to consumers. We find that agritourism and direct sales reinforce each other within the same county but not consistently across neighboring counties.

Cattle feed yards routinely track and collect data for individual calves throughout the feeding period. Using such operational data from nine U.S. feed yards for the years 2016–2019, we evaluated the scalability and economic viability of using machine learning classifier predicted mortality as a culling decision aid. The expected change in net return per head when using the classifier predictions as a culling aid as compared to the status quo culling protocol for calves having been pulled at least once for bovine respiratory disease was simulated. This simulated change in net return ranged from −$1.61 to $19.46/head. Average change in net return and standard deviation for the nine feed yards in this study was $6.31/head and $7.75/head, respectively.

Question effects are important when designing and interpreting surveys. Question responses are influenced by preceding questions through ordering effects. Identity Theory is employed to explain why some ordering effects exist. A conceptual model predicts respondents will display identity inertia, where the identity cued in one question will be expressed in subsequent questions regardless of whether those questions cue that identity. Lower amounts of identity inertia are found compared to habitual inertia, where respondents tend to give similar answers to previous questions. The magnitude of both inertias is small, suggesting they are only minor obstacles to survey design.

This study explores how higher temperatures influence corn yield response to planting density. Using 1990–2010 field trial data from Wisconsin and econometric models with a variety of specifications, we find that higher temperatures reduce the yield benefits of increasing planting density. However, these adverse high-temperature effects are smaller for genetically modified corn varieties, especially those with rootworm-resistant traits. Consistent with previous studies, these results support the notion that varietal improvements through genetic modification may have paved the way for higher planting densities in US corn production. Moreover, our results imply that expected in-season temperatures are important considerations when making planting density decisions.

Drought events have critical impacts on agricultural production yet there is little consensus on how these should be measured and defined, with implications for drought research and policy. We develop a flexible rainfall-temperature drought index that captures all dry events and we classify these as Type 1 (above-average cooling degree days) and Type 2 droughts (below-average cooling degree days). Applied to a panel dataset of Indian districts over 1966–2009, Type 2 droughts are found to have negative marginal impacts comparable to those of Type 1 droughts. Irrigation more effectively reduces Type 2 drought-induced yield losses than Type 1 yield losses. Over time, Type 1 drought losses have declined while Type 2 losses have risen. Estimates of average yield losses due to Type 1 droughts are reduced by up to 27 per cent when Type 2 droughts are omitted. The associated ex-post economic costs in terms of rice production are underestimated by up to 124 per cent.

This paper examines the prioritization of management factors by farmers that lead to the success of their farm business. The research also examines the heterogeneity of producer prioritization of different success strategies. Using a hierarchical clustering approach, we found that each farmer group prioritizes either managing costs, managing output prices, managing people, managing production, or managing assets. The results indicate that the farmer groups are heterogeneous in their prioritization of five strategic management factors. These results provide useful insights for farmers, farm input providers, and farm service providers.

Adverse weather-related risk is a main source of crop production loss and a big concern for agricultural insurers and reinsurers. In response, weather risk hedging may be valuable, however, due to basis risk it has been largely unsuccessful to date. This research proposes the Lévy subordinated hierarchical Archimedean copula model in modelling the spatial dependence of weather risk to reduce basis risk. The analysis shows that the Lévy subordinated hierarchical Archimedean copula model can improve the hedging performance through more accurate modelling of the dependence structure of weather risks and is more efficient in hedging extreme downside weather risk, compared to the benchmark copula models. Further, the results reveal that more effective hedging may be achieved as the spatial aggregation level increases. This research demonstrates that hedging weather risk is an important risk management method, and the approach outlined in this paper may be useful to insurers and reinsurers in the case of agriculture, as well as for other related risks in the property and casualty sector.

In developing countries, problems such as malnutrition and food insecurity are shifting from rural to urban areas because of rapid urbanization. However, regional variations in alimental food consumption within urban settings have often been ignored. Using survey data, our study examines regional patterns of expenditure on fresh vegetables, fruits, and peanut products in urban households of Ghana. After accounting for socioeconomic and demographic factors, food expenditure on fresh vegetables and peanut products and income elasticity vary significantly across major cities. Food distributors may adjust their marketing strategies, while policy makers should pay attention to possible disparities in urban areas.

Using nationwide survey data, we investigate U.S. meat goat producer preferences and willingness to pay for meat goat breeding stock attributes. Discrete choice experiments were employed, and mixed logit and latent class models were used for analysis. Results showed that producers preferred animals that were highly masculine/feminine, had good structure and soundness, and were of the Boer breed, whereas they preferred fewer animals that were older, of Kiko and Spanish breeds, and priced higher. Significant preference heterogeneity was found among the respondents. Larger-scale producers had greater preference for high masculinity/femininity, good structure and soundness, and Boer bucks.

This research employs an agricultural sector model that links seasonal crop production with disaggregated livestock production sectors, in tandem with observed quarterly data on U.S. drought conditions to assess the long term economic implications of drought for U.S beef cattle producers. Short term impacts show increases in feed costs as well as increases in cattle slaughter resulting from drought-induced culling. The price of live cattle decreases in the short run; however, feed prices remain above baseline levels, and beef cattle breeding inventories decline in the long run, leading to fewer calves moving through the supply chain.

Rice, may be of a high- or low-quality type, based on the size and shape of the rice grain and variety. Thus, perhaps with an increase in income, consumers might not only switch from rice to other high-value-added foods, but also shift away from short-and-bold-grain to long-and-slender-grain rice. Using the case of Bangladesh, this article examines the drivers of change in rice grain-type preferences by households. We econometrically demonstrate that educated, rich, and urban households in Bangladesh are increasingly consuming fine-grain (i.e., long-and-slender-grain) rice, by replacing ordinary-grain (i.e., short-and-bold-grain) rice.

This study investigates the long-term adjustments to drought by crop and livestock sectors using a dynamic partial equilibrium quarterly model of the U.S. agricultural economy. Results show that short-term drought effects including increases in crop and forage prices are in tandem with decreased live cattle prices resulting from drought-induced beef cattle herd liquidation. Crop price increases in the long run cause livestock inventory reductions, leading to fewer animals moving through the U.S. meat supply chain and increased livestock prices. Longer-term market adjustments cause a significant decrease in consumer surplus, and prolonged drought amplifies and extends the model-predicted results.

This paper provides an overview of the development of the Management Analysis and Strategic Thinking (MAST) program conducted by Kansas State University. This intensive management training course for progressive farm and agribusiness operators is being delivered successfully using a combination of face-to-face and distance extension delivery techniques. We find that some parts of the program are best delivered face to face and other parts are best delivered via distance. Of participants surveyed, 94% would recommend the MAST program to their peers, and 100% believe the program will have a positive impact on their businesses' bottom line.

This article analyzes anomalous patterns of agent, adjuster, and producer claim outcomes and determines the most likely pattern of collusion that is suggestive of fraud, waste, and abuse in the federal crop insurance program. Log–linear analysis of Poisson-distributed counts of anomalous entities is used to examine potential patterns of collusion. The most likely pattern of collusion present in the crop insurance program is where agents, adjusters, and producers nonrecursively interact with each other to coordinate their behavior. However, if a priori an intermediary is known to initiate and coordinate the collusion, a pattern where the producer acts as the intermediary is the most likely pattern of collusion evidenced in the data. These results have important implications for insurance program design and compliance.

This study investigates a number of factors influencing technical efficiency of Greek farms participating in the 1994 European Union (EU) farm credit program. Technical efficiency measures are obtained within the framework of a parametric stochastic frontier. Factors showing a positive effect on technical efficiency are value of liabilities, number of hours of mechanical operation, large land size, and rental land, whereas those showing a negative effect are value of EU product subsidies, value of off-farm family income, and hired labor. The value of investments incurred by farms because of their participation in the 1994 farm credit program does not show any significant effect on technical efficiency. The predicted levels of technical efficiency indicate that the average technical efficiency of farms 3 years after participating in the 1994 farm credit program is lower than the average technical efficiency of the same farms the year before participating in the program. Thus, the program has failed to increase the efficiency of farms.

Human resource management in agriculture and associated risks are under-researched topics. To identify the sources of human resource management risks confronting dairy farms, gain insights into how dairy farmers perceive the impacts of these risks, and identify control strategies, four focus group discussions were held with dairy farm managers. Managers' perceptions served to develop a framework for the analysis of human resource management risks in agriculture and derive recommendations for reducing these risks. Results of this study have been used to tailor educational programs for farmers and suggest strategies for future research.