The number of non-reported county yields by the United States Department of Agriculture (USDA) National Agricultural Statistics Service (NASS) is increasing. This article explores factors that impact county corn and soybean yields that are not reported by USDA NASS. Factors such as county, land coverage, and average farm size are used to explain the likelihood of a yield being reported. We find that counties that have a high number of acres concentrated in a few farms may not have a NASS yield reported due to NASS reporting requirements.

PurposeUnited States (US) cattle producers have tools to manage price risk, such as options contracts, futures contracts and livestock risk protection (LRP) insurance. However, there has been limited use of price risk management tools among beef cattle producers. The purpose of this research is to determine factors associated with the use of options contracts, futures contracts and LRP insurance.Design/methodology/approachWe conducted a survey of US cattle producers about their use of LRP insurance, futures contracts and options to manage price risk. A multivariate probit model was estimated to understand what drives the likelihood of these price risk management tools.FindingsWe find most producers have never used any price risk management tools, but LRP was the most used (12.5%), followed by futures contracts (6%) and option contracts (5.5%). Producer age, herd size, risk preferences, perceived effectiveness at managing price risk and other factors affected the use of these tools. Interestingly, high risk tolerance results in an increased likelihood of using futures contracts, which is opposite to what was anticipated.Originality/valueFindings inform industry stakeholders, educators and policymakers in developing effective educational programs for producers regarding price risk management. This article also broadens the body of knowledge on the acceptance of various price risk management among cattle producers.

PurposeThis study investigates the impact of ad hoc government payments-specifically the Market Facilitation Program (MFP) and Coronavirus Food Assistance Program (CFAP)-and Farm Bill safety net payments-Agricultural Risk Coverage (ARC) and Price Loss Coverage (PLC)-on non-real estate agricultural loan delinquencies in the United States. The goal is to evaluate the relative effectiveness of these payments in alleviating financial stress in the agricultural sector.Design/methodology/approachWe use a state-level panel dataset covering the years 2015-2022 and apply linear fixed effects models to estimate the marginal effect of each payment type on total non-real estate farm debt and delinquency rates. Robustness is assessed using dynamic panel models and Lewbel's IV estimator to address potential endogeneity.FindingsARC and CFAP payments are significantly associated with reductions in short-term loan delinquencies (30-89 days past due). ARC payments also increase total operating debt, suggesting improved liquidity. PLC payments reduce longer-term delinquencies (90+ days past due), while MFP payments increase total debt but do not reduce delinquencies, indicating weaker effectiveness.Originality/valueThis is the first study to jointly evaluate the effects of ARC, PLC, MFP, and CFAP payments on non-real estate farm debt outcomes using actual payment timing and amounts. It offers novel empirical insights into the financial efficacy of government support programs in agriculture.

We examine the dynamic relationships between formula and negotiated cash prices using new fed cattle price distribution data. We estimate vector autoregressive models to determine the relationship between weighted average prices and weighted variances for negotiated and formula prices of fed cattle. Formula prices respond to negotiated cash prices, but not vice versa. We also find that formula price variances are impacted by the previous week's weighted variance of negotiated cash prices. This study is the first to explore how negotiated cash and formula prices' weighted variances (live and dressed) can influence the weighted variance of both price series.

This paper develops a stochastic dynamic programming model to investigate optimal cover crop adoption policies, accounting for cumulative effects on soil fertility, uncertain future fertilizer and output prices, irreversibility of sunk machinery costs and flexibility in the timing of adoption over time. Based on data from a 35-year cotton field experiment in West Tennessee (1984–2018), we first estimate the static and dynamic yield effects of cover crop adoption and then use these estimates to evaluate the decision of a representative cotton farmer to adopt three cover cropping practices—hairy vetch, winter wheat and crimson clover—under conventional till and no-till production systems. Econometric estimates imply significant cumulative effects of cover crops on yields, as well as static and dynamic substitution effects between cover crops and nitrogen fertilizer inputs. With these substitution effects implying increasing marginal profit from soil fertility, our analysis suggests a threshold level of soil fertility level, above which it is optimal to adopt cover crops and below which it is not. Adoption of cover crops is more favored if no-till practices have been implemented. Moreover, in the presence of sunk costs that have not yet been incurred, the optimal strategy is to postpone the adoption of cover crops in both conventional till and no-till fields until crop prices improve, the cost of adoption decreases, or fertilizer prices increase. Our results also indicate that when fertilizer prices are higher, cover crop adoption in no-till systems can lead to substantial fertilizer cost savings, with the amount of those fertilizer cost savings increasing over time as soil health further improves.

In 2004, beef briskets were the lowest valued primal cut on a carcass, but in recent years, briskets have been ranked as high as the 3rd most valuable cut on a carcass. In this study, we determined factors associated with wholesale graded brisket prices with a novel estimated national graded brisket supply. We used a multivariate price determination model for Prime, Choice, Select, and Ungraded brisket using monthly data from 2004 to 2019. We found that all graded brisket prices increased after Arby's introduced their brisket sandwich nationwide. Additionally, we used Google Trends data for brisket searches and found that consumer interest is also increasing brisket prices over time (P < 0.01). Own- and cross-price flexibilities were estimated using the quantity grade data. Choice briskets were found to have a significant own- price flexibility (P < 0.01) and cross-product flexibility (P < 0.01), which indicates that as the supply of Choice briskets changes, the price of Choice and other graded briskets changes. Cross-quantity flexibilities showed substitutes across brisket quality grades and pork shoulders (P < 0.05). Our results expand the BBQ literature and provide insights that are useful for market participants.

Feeder cattle genomic tests assess the potential of economically important traits to feedlots, such as residual feed intake and marbling. A survey was utilized to determine feedlot willingness to pay for genomictested feeder cattle. Depending on test results, feedlots were willing to pay as much as 4.60% more for genomictested cattle compared to untested cattle. Feedlots prioritize using genomic tests for marketing decisions and future purchases, despite reporting "poor" knowledge and perceived high costs associated with the tests. Findings can assist Extension personnel with advising cattle producers about the potential uses and benefits of this technology.

The 2018 Farm Bill established the Feral Swine Eradication and Control Pilot Program (FSCP), which was focused on removing feral hogs and restoring damaged property. We conduct a quasi-experimental analysis of FSCP on crop damage using crop insurance data and a staggered difference-in-difference model. We found that the FSCP reduced insurance losses for corn, but we did not find an effect on soybeans, cotton, wheat, or peanuts. There are ongoing policy discussions to continue, expand, or make FSCP permanent, and this analysis provides policymakers with a timely analysis of the FSCP impact on crop damage.

Precision livestock farming (PLF), which utilizes digital technologies for real-time data collection to improve various farming operations, is an emerging interdisciplinary field of study that could aid US and global livestock production. Currently, dairy, hog, and poultry producers are utilizing PLF technologies for real-time decision making, however, use by beef cattle producers has been less widespread. Using data collected from an online survey of beef cattle producers in Tennessee, we examined factors associated with the use of various PLF technologies. Logistic regression models revealed beef cattle producers' decisions regarding technology use were influenced by their individual risk preferences and attitudes towards farm data privacy. Producers with greater trust in farm data privacy were more likely to use software management systems and drones while those more willing to take risks were more likely to use drones. Overall, results suggest widespread use of these technologies will require that they be affordable, relevant to production, and capable of improving on-farm profits. Findings from this study can inform the development, deployment, and marketing of PLF technologies related to beef cattle production.

The rising prices of N fertilizer led to exploring cost-saving efforts, such as intercropping cool- or warm-season legumes serving as alternative sources of N for managing fall-stockpiled tall fescue [Schedonorus arundinaceus (Schreb.) Dumort.; TF]. We aimed to evaluate red clover (Trifolium pratense L.; RC) and sunn hemp (Crotalaria juncea L.; SH) mixed with TF as alternative sources of N for stockpiling TF to increase productivity and animal performance. The experiment was conducted in Crossville, TN, in 2020 and 2021 and consisted of TF pastures mixed with RC (TRC) or SH (TSH), and TF fertilized with urea (TU). The experiment was divided into two periods: the pre-grazing period (stockpiling) (April-October) and the grazing period (October-December). After the stockpiling period, Black Angus beef (Bos taurus) steers were used for the grazing period. The study evaluated the botanical composition, herbage mass (HM), nutritive value, steer average daily gain (ADG), and net returns (NR). The TRC pastures had a greater proportion of legumes compared to TSH plots in May, October, November, and December of both years. There were no differences among treatments for the total HM and nutritive value in 2020; however, in 2021, TU had greater HM at the beginning of the grazing period and greater average crude protein values compared to the other treatments. In both years, there were no differences among treatments for ADG or NR. Therefore, producers can make the same profit considering the beef steer price and the cost of conventional and alternative N sources. Legumes have the potential to suppress weeds when mixed with grasses. Nitrogen is the most important nutrient that contributes to forage production. Stockpiling forages contributes to the extension of grazing season. Grass and legume mixtures can increase the nutritive value and, consequently, improve animal performance.

Pasture systems that include cool- and warm-season species have the potential to enhance tall fescue (TF) [Schedonorus arundinaceus (Schreb.) Dumort.] forage systems beyond their typical season. The objectives of this study were to incorporate crabgrass (Digitaria ciliaris Retz.) into TF swards and compare the production of monoculture TF to a binary mixture of crabgrass and TF as well as its effect with different sources of nitrogen (such as red clover [Trifolium pratense L.] or sunn hemp [Crotalaria juncea L.]). The experiment was conducted in Crossville, TN, in 2020 and 2021. The treatments were as follows: (1) TF + 0 N (T), (2) TF + ammonium nitrate (TA), (3) TF + red clover (TR), (4) TF + sunn hemp (TS), (5) TF + crabgrass + 0 N (TFC), (6) TF + crabgrass + ammonium nitrate (TCA), (7) TF + crabgrass + red clover (TCR), and (8) TF + crabgrass + sunn hemp (TCS). The plots containing red clover indicated a greater herbage mass (HM) and crude protein (CP) along with lesser neutral detergent fiber compared to the other treatments. Sunn hemp performed best during the mid-summer, contributing to the increase of HM. Tall fescue swards that were mixed with crabgrass and a source of N (legumes or N fertilizer) had greater HM during the warm season, having the potential to decrease the stationarity of production. Thus, including crabgrass, red clover, and sunn hemp (grass and legumes, respectively) in TF pasture can be a great strategy to increase HM and improve nutritive value. Inclusion of cool- and warm-season grasses increases the seasonality of production. Crabgrass is a warm-season grass that improves nutritive value in mixed pasture. Nitrogen fertilizer increases forage mass and nutritive value. Increasing the use of legumes in pastures may decrease the use of synthetic N fertilizer.

While wildlife damages are a relatively small part of crop insurance claims in the United States, reported damages from wildlife are growing and producers are concerned this issue is getting worse. Wildlife agencies advocate for hunting as a control to wildlife damages to crops but to our knowledge, no study has econometrically explored if hunting could reduce crop damage. Therefore, we analyze if county-level white-tailed deer (Odocoileus virginianus) harvest and other factors like habitat and field fragmentation are associated with corn and soybean acres being indemnified due to wildlife damages in Tennessee. We estimate a fractional probit model using crop insurance data to measure crop damages and a county-level white-tailed deer harvest dataset. We find a higher coverage level of a policy increases the likelihood of both corn and soybean acres being indemnified due to wildlife damage. We also find white-tailed deer harvest during the period post-harvest in the previous crop year (November through January) slightly decreases the likelihood of a claim being made due to wildlife damage for corn but was not found to mitigate losses to soybeans. The whitetail hunting season appears to align better with corn production to reduce crop losses than with soybeans. This study will be useful for wildlife and crop agencies in state and federal governments to develop policies to more effectively utilize hunting to reduce crop insurance claims from wildlife damages.

Prevented planting payments reimburse crop producers for losses from not being able to plant. These payments provide critical protection to producers; however, these payments, which are determined using a nationwide, crop-specific coverage factor, have been questioned to induce moral hazard. Depending on the region and crop insurance coverage, payments from this provision exceed producers’ losses. This paper estimates the prevented planting coverage factor by coverage level and region that would equitably reimburse corn and soybean producers for their losses. We find the prevented planting coverage factor has significant variation across coverage levels and location within our study region. The prevented planting coverage factor was found to decline as the policy coverage level increases. The further north in the study region the higher the coverage factor, likely due to increased land rent expenses. The results provide a unique perspective of how these coverage factors would vary to equitably compensate producers for losses, which addresses the moral hazard concerns with prevented planting.

United States cattle producers have various government-sponsored programs to protect against weather and disease related risks, but livestock risk protection (LRP) insurance is the only program that protects against price risk. However, adoption of LRP insurance is low even though cattle price declines are the primary cause of economic loss, and LRP premium subsidies have recently been increased. Therefore, the objective of this study is to explore how informational nudges about receiving an indemnity payment, LRP contract characteristics, and individual risk preferences affect the use of LRP. Producer survey results were estimated using a Cragg model to determine the factors affecting producers' likelihood of purchasing LRP and the number of head they would insure. Producers were more likely to purchase 100% LRP coverage and would also insure more head at 100% coverage when compared to lower coverage levels. We found providing information on the probability of receiving an indemnity did not impact LRP purchasing decisions. However, counter to expectations, producers were more likely to buy LRP when the randomly provided cattle prices in the survey were successively increasing each month, and if participants considered themselves more willing to take risks in their cattle operation. Results provide insights into behavioral factors affecting LRP participation which could help inform future insurance policies.

This research introduces a new method for event studies in time-series analysis named the Markov regime-switching event response model (MS-ERM). The MS-ERM is a comprehensive approach that integrates two different event study approaches: 1) measuring the impact of an event through structural shift and 2) measuring the impact via additional distributional components. As an empirical application, the study measures the impact of beef-packing plant closures on the weekly live-to-cutout beef price spread. The results indicate that the MS-ERM is a promising tool for event studies, particularly when an empirical dataset has both groups of events that cause and do not cause structural changes.

We investigate the relationships of the often-publicized live cattle to box beef price spread and weekly and Saturday slaughter capacity utilization (CU). We find that an increase in the price spread in the previous period does positively impact national Saturday slaughter CU under a low price spread regime, but not in the identified middle and high regimes. Also, changes in weekly or Saturday slaughter CU does not impact the price spread except for the high regime. Our results do not support the notion that weekly, or Saturday slaughter CU is used by the beef packers to control the price spread.

Federal and state legislators recently enacted policies to fund new and renovated small and local meat processors expansion with the aim of increasing the meat-processing sector's resiliency. Wages must be competitive to attract employees for these new and renovated plants to be competitive. No previous studies have examined what has happened to employee labor costs at United States (US) meat-processing plants since the early 2000s. This study estimates how meat-processing firm size affects employee wages in the US. We use average employee wages for beef and pork processing plants from 2007 to 2019. We find larger plants pay higher wages than smaller ones, which is likely attributable to lower fixed costs resulting from economies of scale. Findings suggest that facilities with more than 500+ employees will most likely offer wage that are high enough to recruit workers in for this industry. Small plants will need to increase real wages that are higher than historical averages. Thus, if smaller facilities increase the sector's resiliency, then it will likely come at a cost in terms of higher wage bills. [EconLit Citations: Q12, Q18].

Genomic tests (GTs) provide information about the expected performance of cattle. Cattle producer survey results indicated that 56% of producers were interested in using GTs for marketing cattle and 74% would use GTs to select replacement heifers. If interested in using GTs to market cattle, on average, producers indicated they were willing to pay $21/head and test 55% of their animals. For replacement heifers, on average, they were willing to pay $23/head and test 77% of their heifers. A conditional mixed process regression framework found producer characteristics and risk preferences were associated with the decisions involved in using GTs.

Purpose 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. Design/methodology/approach 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. Findings 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. Originality/value 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.

Objective: The objective of this analysis was to deter-mine whether an online bidding format affects the price of female beef cattle along with several factors such age, months bred, and her sire's EPD. Materials and Methods: This analysis uses annual sales data from 2017 to 2022 from a registered Angus cow and heifer sale in Crossville, Tennessee, that occurs in No-vember at the University of Tennessee Plateau Research and Education Center. A hedonic pricing model was used to determine the value of these factors on sale price.Results and Discussion: The results indicate heifer lots were sold for less than cows lots. The sale price of bred females increases until they are approximately 5 and 6 mo bred, and then the prices start declining. These re-sults were expected based on the literature. The primary finding of this analysis is that having a sale to have online bidding increased the sale price by approximately $379 per head. Implications and Applications: This research ex-tends the literature by considering the effects of an online bidding presence on female sale prices. This article also builds on the growing literature examining how various factors affect female sale prices in the southeastern United States. These results are useful for producers with small-and medium-sized herds who market cattle in their farm; they might consider implementing an online bidding com-ponent when marketing their cattle.