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This study aims to determine whether consumers are willing to pay a premium for locally produced hard apple cider and examine the factors influencing this premium. This study examines the influence of hard apple cider attributes and consumer characteristics on consumer preferences for local hard apple cider.

Data from a 2019 survey of 875 Tennessee consumers regarding their preferences for a local hard apple cider were obtained. Probit estimates were used to calculate the premium consumers were willing to pay for a locally made hard apple cider and factors influencing this premium. A multivariate probit was used to ascertain factors influencing the importance of attributes (e.g. heirloom apples, sweetness/dryness, sparking/still and no preservatives added) on local hard apple cider preference.

Consumers would pay a $3.22 premium for local hard apple cider compared with a $6.99 reference product. Local foods preferences, urbanization, weekly purchases of other alcoholic beverages and shopping venues influenced premium amounts. Other important attributes were sweetness/dryness and no preservatives. Influence of consumer demographics suggests targeted marketing of local ciders could be successful.

Few studies examine consumer preferences for hard apple ciders. This study represents a cross-sectional analysis of the premium consumers would pay for local hard apple ciders and the importance of other hard apple cider attributes.

The United States (US) sugar program protects domestic sugar farmers from unrestricted imports of heavily-subsidized global sugar. Sugar-using firms (SUFs) criticize that program for causing US sugar prices to be higher than world sugar prices. This study examines the financial performance of publicly traded SUFs to determine if they are performing at an economic disadvantage in terms of accounting profitability, risk and economic profitability compared to other industries.

Firm-level financial accounting and market data from 2010 to 2019 were utilized to construct financial metrics for publicly traded SUFs, agribusinesses and general US firms. These financial metrics were analyzed to determine how SUFs compare to their agribusiness peer group and general US companies. The comprehensive financial analysis in this study covers: (1) accounting profit rates, (2) drivers of profitability, (3) economic profit rates, (4) trend analysis and (5) peer comparisons. Quantile regression analysis and Wilcoxon–Mann–Whitney statistics are employed for statistical comparisons.

Regarding various profitability and risk measures, SUFs outperform their agribusiness peers and the general benchmark of all US firms in terms of accounting profit rates, risk levels and economic profit rates. Furthermore, compared to other US industries using the 17 French and Fama classifications, SUFs have the highest return on investment and economic profit rate―measured by the Economic Value Added® margin―and the second-lowest opportunity cost of capital, measured by the weighted average cost of capital.

This study finds nothing to suggest that the US sugar program hinders the financial success of SUFs, contrary to recent claims by sugar-using firms. Notably in this analysis is the evaluation of economic profit rates and a series of robustness techniques.

Premium subsidy rates were increased in 2019 and 2020 for livestock risk protection (LRP) insurance, which is price insurance for cattle producers. The authors examined if the LRP subsidy rate changes affected the LRP coverage levels purchased by feeder and fed cattle producers.

The authors collected the United States Department of Agriculture Risk Management Agency summary of business sales data for daily LRP purchases from 2015 to 2023. The authors estimated a multinomial logit model to determine if subsidy rate changes were associated with the likelihood of LRP policies being purchased at different coverage levels.

After the 2019 and 2020 subsidy rate changes, the likelihood of producers buying LRP-feeder cattle policies with coverage over 95% increased relative to the policies with coverage less than 89.99% but did not influence the likelihood of producers buying LRP-feeder cattle policies with coverage between 90 and 94.99% relative to policies with coverage less than 89.99%. Marginal effects show these subsidy rate changes increased the likelihood of buyers purchasing LRP-feeder cattle policies with greater than 95% coverage. The subsidy change did not affect the purchase of LRP-fed cattle policies.

The results demonstrate the influence of the recent LRP policy adjustments on insurance purchases, which could be important for agency officials and policy makers. This is the first study to explore the LRP policy purchases which provides the United States cattle industry insight into the LRP price insurance take-up, which can guide producer extension education on managing price risk.

The objective of this research was to determine the optimal age and pregnancy status for buying and selling replacement of beef females for risk-neutral and risk-averse producers.

A hedonic pricing model was estimated to measure how age, pregnancy status, breed and cull cow prices impact the sale price of these cattle. Data came from an annual heifer and cow sale in Tennessee between 2009 and 2018. A financial simulation model was developed to generate distributions of net present value (NPV) for buying replacement females at various ages and pregnancy status and then selling that female at various ages and pregnancy status.

The hedonic pricing model indicates sale prices were highest for five-year-old cows that were between four to five months pregnant. NPV was higher for buying heifers versus buying cows and for buying an open female versus a pregnant female. Regardless of age and pregnancy status when purchased, NPV was higher when the female was sold as pregnant prior to the end of her productive life. The risk analysis showed that risk aversion, buying older open cows and selling them as pregnant earlier in their productive life was preferred

This research offers unique insight into how pregnancy status and age at sale impacts the animal's NPV while considering risk. These results have implications for educating producers on purchasing and selling decisions of heifers and cows as well as for lenders who finance these purchases.