The use of price risk management tools by cattle producers

As with any commodity, United States (US) beef cattle production is not immune to price risk, which can cause major economic losses (Hart et al., 2001; Hall et al., 2003; Belasco et al., 2009). Price risk refers to the uncertainty of the expected price of a commodity at its time of sale (Kay et al., 2024). To manage price risk, cattle producers have various tools at their disposal, such as futures contracts, options contracts and livestock risk protection (LRP) insurance. However, few agricultural producers, especially cattle producers, utilize these tools (Shapiro and Brorsen, 1988; Hill, 2015; McKendree et al., 2021). According to Hill (2015), only 7% of surveyed beef producers utilized LRP to manage price risk, 37% used futures contracts and 27% used options contracts. Similarly, McKendree et al. (2021) reported that only 1% of the cattle producers surveyed used LRP, 20% used options contracts and 41% used futures contracts.

Studies have found that price risk management tools are effective if properly implemented (Belasco et al., 2009; Burdine and Halich, 2014; Merritt et al., 2017; Wei, 2019; Boyer and Griffith, 2023a, b; Boyer et al., 2023). However, several reasons exist as to why cattle producers do not frequently use these tools. One of the noted obstacles to using futures and options contracts is that the contracts are not suitable for most cattle operations due to their size. For example, feeder cattle contracts are 50,000 pounds, which requires more cattle than what the average US feeder cattle producer typically sells at a given time in the year (United States Department of Agriculture [USDA] National Agricultural Statistics Service [NASS] 2024). If a producer with less than 50,000 pounds of feeder cattle were to use a futures or options contract to hedge, this would result in an over-hedge, which reduces the effectiveness of this risk management tool (Griffith, 2014).

LRP is an insurance program for cattle producers to manage financial losses from price declines. These insurance policies allow producers to guarantee a minimum price for a specified time. Producers pay a subsidized premium to guarantee a minimum price (i.e. coverage price) during the endorsement period. Policyholders receive an indemnity payment at the end of the insurance (i.e. endorsement) period if the expected ending price (either the Chicago Mercantile Exchange (CME) Feeder Cattle Index or the CME live cattle futures price) is less than the coverage price or minimum price set with the LRP contract (USDA Risk Management Agency [RMA] 2021). LRP policies are tailored by the number of head (between one and 25,000 head annually), the insurance periods (13, 17, 21, 26, 30, 34, 39, 43, 47 or 52 weeks) and coverage levels (70–100%) of an expected ending price, which are adjusted daily based on breed (cattle, predominately dairy, predominantly Brahman) composition, sex (steer or heifer) and weight (cattle less than 600 pounds and cattle between 600 and 1,000 pounds).

Like futures and options contracts, LRP has had limited usage, which has been attributed to its cost. Studies have shown that the premium for LRP is frequently higher than the indemnities paid if a payment is even triggered (Burdine and Halich, 2014; Merritt et al., 2017). Additionally, Merritt et al. (2017) showed that not all LRP contract lengths and coverage levels are equally effective across months due to the seasonality of cattle prices. In response to low participation in LRP, the premium subsidy increased from 13% to 20% of the total premium in 2019 (USDA RMA, 2024). In 2020, the premium subsidy was further increased and shifted to a tiered structure ranging from 35% to 55% based on coverage level (USDA RMA, 2024) ^[1].

Another explanation for the low adoption of price risk management tools by cattle producers, which has received little attention, is how individual risk preferences impact cattle producers’ use of price risk management tools. Fields and Gillespie (2008) included risk preferences in their survey of producers' willingness to purchase a hypothetical livestock insurance product and found that more risk-averse producers were likely to purchase insurance. Similarly, McKendree et al. (2021) showed that more risk-averse producers were more likely to use price risk strategies, but did not differentiate between the various tools such as futures, options and LRP. On the other hand, Boyer et al. (2024a) reported that cattle producers who identified as more willing to take risks were more likely to buy LRP.

Building from previous studies, the objective of this study is to determine factors associated with the use of options contracts, futures contracts, and LRP insurance for managing cattle price risk. We conducted a national survey of US cattle producers and estimated multivariate probit models to understand what drives the likelihood of producers using these risk management tools. The findings create a basis for educational programs for producers in handling price uncertainty and may have consequences for future policy modifications. The article also broadens the body of knowledge on the acceptance of price risk management among cattle producers.

Data came from a 2022 email survey of US beef cattle producers through Qualtrics (UTK IRB-21-06647-XM). We acquired the national list of cattle producers from DTN, and the list includes cattle operations of diverse sizes for the 48 contiguous states. A total of 87,419 valid email addresses were utilized. The survey was administered following Dillman’s (2007) method using Qualtrics. This method is a tailored approach for maximizing response rates and data quality. The Dillman (2007) method follows a pretesting and multi-contact strategy to motivate participation by reducing perceived costs and increasing perceived rewards for participants. Thus, a pretest consisting of 15 livestock producers and extension agents received the survey prior to the launch. The survey questions and format were revised using feedback from the pretest. The survey was then emailed to the cattle producer email list on June 1, 2022. A reminder email was sent one week following the initial delivery and another reminder was sent a week following the first follow-up email. A total of 699 responses were received. Of the responses, 591 were complete, which means the respondents answered all the questions. This results in a response rate of slightly less than 1%. While this is a low response rate, it is consistent with other emailed cattle producer surveys, which had a similar response rate of 1.9% (McKendree et al., 2016).

The survey instrument was divided into multiple sections. These sections are generally classified as producer characteristics, farm and herd characteristics and producers’ attitudes toward price risk management. The producer characteristics questions asked about the producer’s age, education and income from cattle production. The farm or herd characteristic questions asked about the number of head of cattle and the marketing of cattle. The following section asked producers about their attitudes toward the price risk management tools. The first question asked about the producer’s use of LRP as well as futures and options contracts. The question specifically asked if the producers have ever used these price risk management tools, if they are currently using them, and if they have used them in the past. We asked cattle producers to state their perceived effectiveness of the tools at managing price risk and their barriers to using these tools. Additionally, we also elicited producers’ risk preferences using the Dohmen et al. (2011) stated preference approach. Specifically, producers were asked to rate their willingness to take risks in financial matters related to the cattle business from one (not at all willing) to eleven (very willing). This procedure has been used in previous studies (DeLong et al., 2023; Ingram et al., 2023; Smith et al., 2022; Boyer et al., 2024a, b) and has been found to be an effective alternative to measuring risk preferences without playing a lottery game, which can be complex in a survey (Dohmen et al., 2011) ^[2].

The dependent variables were binary and equal to one if the respondent had used, or currently uses, the given price risk management tool and zero otherwise. A multivariate probit model was estimated to determine the factors affecting a cattle producer’s likelihood of using LRP, futures contracts or options contracts while controlling for any potential correlations among the unexplained factors (i.e. use of LRP, future contracts or option contracts) (Greene, 2012). The model is defined as:

Where $Yij$ represents the jth price risk management tool (j = LRP, futures contracts, options contracts) by the ith producer; $xij′$ denotes a matrix of explanatory variables that impact the use of risk management tools; $βj$ is the vector of coefficients to be estimated and $εij$ is the unobserved error term that is assumed to be multivariate normal distributed (Greene, 2012). The model was estimated using cmp with the Huber–White Sandwich estimator in StataCorp (2023). This estimator is useful to obtain robust standard errors when there is a concern that errors are heteroskedastic. Variance inflation factors were estimated for covariates to test for multicollinearity in StataCorp (2023). We found no indication of multicollinearity.

While the estimated multivariate probit coefficients indicate the direction of the relationship between the predictors and the dependent variables, they do not directly provide the magnitude or give a practical interpretation often required for decision-making and policy formulation (Wooldridge, 2010). Therefore, marginal effects were estimated for the multivariate probit coefficients. The delta method, following Greene (2012), was used to calculate the marginal effects StataCorp (2023).

Table 1 defines the independent variables included in the analysis and provides their hypothesized signs. The literature indicates that the use of risk management tools could be affected by producers’ characteristics (including risk preferences), herd and farm characteristics, the cost of using the tools, the perceived effectiveness and understanding of the tools, and their method of selling cattle.

Producers' characteristics included in the analysis are age, level of education and percentage of household income from their cattle operation. We expect that an increase in age will decrease the likelihood of using risk management tools. Studies have reported that cattle producers are less likely to adopt new practices as they get older (Gillespie et al., 2007; Ward et al., 2008; Lambert et al., 2020; Greig et al., 2023). A college education has been shown to increase the likelihood of cattle producers adopting various management practices (e.g. rotational grazing, pasture mixtures and nutritional management) (Pruitt et al., 2012; Lambert et al., 2020; Ren et al., 2022; Boyer et al., 2024b); thus, we hypothesize that the estimated parameter for college education will be positive. Mixed results are often reported for how the percentage of income originating from beef cattle operations impacts the adoption of various risk management and grazing practices (Gillespie et al., 2007; Lambert et al., 2020; Ren et al., 2022). Therefore, we are unsure how these variables will impact the use of risk management tools and signs are not predetermined.

We included the variables of the total number of calves (home-raised and purchased) and the total number of cattle in feedlots to control for herd size. We are unclear if the sign of this estimated parameter will be positive or negative, but expect it to differ across the risk management tools. For example, LRP was developed for smaller livestock producers; thus, the sign could be negative. However, futures and options are more appropriate for larger producers; thus, the sign could be positive. McKendree et al. (2021) found that larger feedlot operations were more likely to use price risk management strategies; therefore, we hypothesize producers with more cattle in a feedlot will be more likely to use these tools. Also, if the producer marketed cattle in an auction market, we expect those producers to be more likely to use LRP. The market uncertainty of this marketing method might encourage producers to insure against price risk. However, McKendree et al. (2021) reported that most producers in their survey primarily sold cattle in the spot market without using price risk management.

Regarding risk, Fields and Gillespie (2008) and McKendree et al. (2021) included risk preferences in their surveys of producers’ willingness to manage price risk using various tools. Both of these studies found that more risk-averse producers were more likely to use price risk strategies. Similarly, Davidson and Goodrich (2023) included a risk preference measurement when trying to understand cattle producers’ use of pasture, rangeland and forage insurance (i.e. production risk and not price risk) and also found that the more risk-averse producers had resulted in a higher likelihood of them purchasing the pasture, rangeland and forage insurance. However, Boyer et al. (2024a) found cattle producers who identified as more willing to take risks were more likely to buy LRP. We hypothesized that producers who are more risk averse would be more willing to purchase the price risk tools used in this study based on the evidence of previous studies (Fields and Gillespie, 2008; McKendree et al., 2021; Davidson and Goodrich, 2023) and that these tools are intended to reduce risk; thus, a risk averse producer might be more likely to purchase them. We anticipate that the sign of the risk preferences parameter estimate was expected to be negative.

We hypothesize that producers' perceived understanding and perceived effectiveness of the price risk management tools could impact their use. Higher degrees of perceived effectiveness and understanding are anticipated to increase the likelihood of using the tools. Studies have shown that small operations are better off using LRP than futures and options contracts (Wei, 2019); thus, we assume that if respondents believe they are too small to benefit from using price risk tools, they will be less likely to use them. We also hypothesize that those who check prices daily might be more likely to use price risk tools since they are actively watching the market.

Table 2 provides summary statistics for the analyzed variables. Few producers have used any of these price risk management tools. Only 12% have used LRP, 6% have used futures and 5% have used options. Of these tools, more of our respondents used LRP than futures and options contracts. This is different than what Hill (2015) and McKendree et al. (2021) reported in their studies, but Hill (2015)’s study focused primarily on stocker producers and McKendree et al. (2021)’s analysis was focused on feedlots. These operational differences between our sample and the samples in these studies, as well as the timing of the survey, are likely to explain these differences. For example, the subsidy rate change in 2020 occurred after these samples were collected and studies have shown large increases in LRP use after the subsidy increase (Boyer et al., 2023). Overall, the use of these price risk management tools aligned with what we report, which is that most producers are not using price risk management tools.

On average, the cattle producers surveyed were 59 years old. Approximately 50.3% of respondents held at least a bachelor's degree. Regarding herd composition, respondents had an average of 106 calves and 23 head owned in the feedlot, indicating that most of the surveyed producers are cow-calf producers. Relative to the average US cattle producer, the sample represents larger (average US herd size is 47 head) and slightly older (average age is 58 years old) (USDA NASS, 2024). Notably, 80% of the respondents used traditional auction markets for cattle marketing.

The average risk preference score was 5.6 out of 11, which suggests respondents were generally risk neutral. When asked if their operation was too small to benefit from price risk management tools, producers’ average score was 4.6 out of 7, agreeing that their operation is too small to benefit from price risk management. The majority of the respondents stated that the income from their cattle operation accounted for less than 39.99% of their income with the majority indicating that income from their cattle operation accounted between 20% and 39.99% of their income. Approximately 18% of respondents indicated that they check cattle prices daily.

As for their understanding of price risk management tools, most respondents stated that they have “no idea” about these tools (Figure 1). Specifically, 65 and 69% of respondents have “no idea” of futures and options, respectively, compared to 59% for LRP. Few respondents indicated they understand these tools “extremely well,” with only 2%–3% stating elevated levels of understanding (Figure 1). These findings suggest a significant lack of knowledge about price risk management tools among cattle producers in our sample.

Regarding the perceived effectiveness of these tools, respondents indicated increased levels of “no idea” in their effectiveness. Respondents indicated a lack of awareness of the effectiveness of futures hedges (74%), options hedges (76%) and LRP (67%) (Figure 2). Conversely, 13%–20% of respondents believe these tools are moderately too extremely effective for managing price risk (Figure 2). Specifically, 20% of respondents perceive LRP as moderately to extremely effective, compared to 16% for futures and 13% for options. This suggests that LRP is perceived to be the most effective tool among the three.

The regression results are presented in Table 3, and the marginal effects of the significant factors are shown in Table 4. The coefficients for the unexplained factors (i.e. rho estimates) for the use of LRP and futures contracts were correlated (p < 0.05); for LRP and options contracts were also correlated (p < 0.01), and for futures and options contracts (p < 0.01). All these correlation coefficients were positive, indicating that the unobserved factors influencing the use of one risk management strategy are positively correlated with the unobserved factors influencing the use of another price risk management strategy. The results indicate the multivariate model is appropriate over individual probit regressions.

For LRP, a one head increase in cattle in the feedlot was associated with a 0.011% decrease in the likelihood of using LRP (p < 0.05). Respondents with a higher perceived understanding of LRP were significantly more likely to use LRP (p < 0.01). Higher reliance on income from cattle operations is associated with a higher likelihood of using LRP (p < 0.01). Income from cattle sales is volatile and managing this risk would be logical if it were a larger percentage of household income. Relative to the producers that rely on their cattle income for less than 19.99% of their household income, a higher percentage of households’ income from cattle production results in an increase in the likelihood of using LRP. Additionally, producers who check cattle prices daily are 4.14% more likely to use LRP (p < 0.10). We did not find risk preference to impact the use of LRP, which differs from Boyer et al. (2024a).

For futures contracts, older producers were more likely to use futures contracts to manage price risk (p < 0.05), which is different from what most studies find for cattle producers’ adoption of management practices (Gillespie et al., 2007; Ward et al., 2008; Lambert et al., 2020; Greig et al., 2023). We expected this estimated parameter to be negative. There could be several explanations for this result, such as younger producers not having a large enough operation or capital to justify the use of futures contracts, which might be an area for future research. A one-head increase in cattle in the feedlot increased the likelihood of using futures contracts by 0.014% (p < 0.10). A one-unit increase in a producer’s risk preference scores resulted in an increase in the probability of using futures contracts (p < 0.05). This finding diverges from the literature (Field and Gillespie, 2008; McKendree et al., 2021; Davidson and Goodrich, 2023) and our hypothesis that more risk-averse producers would be inclined to use risk management tools. Instead, it suggests that producers who are more open to taking risks are more likely to use futures as a price risk management strategy. This does, however, align with Boyer et al. (2024a), who found that the more risk-tolerant producers were the more likely they were to adopt LRP. An increase in perceived understanding of futures contracts increases the likelihood of usage (p < 0.01). Similarly, an increase in producers' perceived effectiveness of futures contracts at managing price risk increased the likelihood of usage (p < 0.01). Furthermore, believing that the operation is too small to benefit from price risk management decreases the likelihood of using futures contracts (p < 0.05). Like LRP, producers who check cattle prices daily are 5.19% more likely to use futures contracts (p < 0.01).

The estimated parameters for factors explaining the use of options contracts were similar to those for the use of futures contracts. Older producers were more likely to use options contracts (p < 0.10), which was counter to what we expected. A one-unit increase in the head of cattle in the feedlot increased the likelihood of using options contracts (p < 0.10). McKendree et al. (2021)’s sample was feedlot producers, and they found higher use of options and futures; thus, our results are supportive of these earlier findings. Conversely, a one-unit increase in the number of calves reduced the likelihood of using options contracts (p < 0.10). Using a traditional auction to market cattle increased the probability of using options by 2.88% (p < 0.10). Like LRP and futures contracts, producers who check cattle prices daily are 6.07% more likely to use options contracts (p < 0.01). An increase in producers’ understanding of options contracts increased the likelihood of usage (p < 0.01). Additionally, believing that the operation was too small to benefit from price risk management decreased the likelihood of using options contracts (p < 0.01).

The analysis indicates that understanding and frequent monitoring of cattle prices are crucial factors for the adoption of price risk management tools. Additionally, perceptions regarding the size of the operation significantly influence the use of futures and options contracts but not LRP, suggesting that LRP could be more accessible for smaller operations. These insights are valuable for educators and those in the agricultural insurance industry aiming to increase the adoption of risk management tools among cattle producers.

Cattle producers have various price risk management tools available to use to help manage price risk, but historically, adoption has been low. The purpose of this research is to determine factors associated with the use of LRP insurance, futures contracts and options contracts. To do this, we conducted a survey of US cattle producers asking them about their use of these tools and estimated a multivariate probit model to understand what drives the likelihood of use. The contribution of this work is to help identify barriers to use, as well as to find ways to encourage the use of price risk management tools among producers.

The findings of this research indicate that beef cattle producers, at least for our sample, have limited usage, understanding and perceived effectiveness of price risk management tools. The survey data reveal that most respondents have never utilized LRP, futures contracts or options contracts for price risk management. Results from the multivariate probit indicate factors such as age, education, daily activities, cow percentage and understanding play significant roles in influencing the utilization and perception of price risk management tools among producers.

A limitation of these findings is the small sample size. The results, while important implications for both policymakers and industry stakeholders, are not generalizable to the US cattle producer population due to the low response rate and small number of observations. However, the results from our sample do provide useful insights. Efforts could be made to raise awareness among beef cattle producers regarding the benefits and usage of price risk management tools. Enhancing understanding in this area can contribute to the implementation of risk management practices and potentially better financial outcomes for producers. For example, Extension educators could create a decision tool to help producers select the optimal coverage level and coverage length based on their marketing periods.

We want to thank the anonymous reviews and editors for the helpful comments.