1

Value Indicators in Feeder Cattle:

An Analysis of Multi-State Auction Data

Final Report prepared for the 

Agricultural Marketing Service, USDA

Derrell S. Peel, Ethan McGill, Kellie Curry Raper and Eric A. DeVuyst1

Oklahoma State University

September 2023

1 Breedlove Professor of Agribusiness and Extension Livestock Marketing Specialist; former Extension Assistant; 

Professor and Livestock Marketing Specialist; and Professor and Rainbolt Chair; Department of Agricultural 

Economics, Oklahoma State University 
2

Value Indicators in Feeder Cattle:

An Analysis of Multi-State Auction Data

Derrell S. Peel, Ethan McGill, Kellie Curry Raper and Eric A. DeVuyst2

Introduction

Feeder cattle, collectively and at any one point in time, represent a diverse set of animals that 

vary widely in size, age, gender, quality, genetics, condition, and management. Moreover, regional 

variation in cattle production systems, cattle types and cattle industry culture add to the national 

diversity across feeder cattle markets. The Agricultural Marketing Service faces numerous challenges to 

capturing feeder cattle market price levels and trends across a vast array of public auctions around the 

country. Increasingly, there is demand for additional information regarding the range of factors that 

affect the value of feeder cattle. This project was initiated to help address these growing needs.

Project background

Oklahoma Cooperative Extension Service (OCES) has collaborated with the Oklahoma 

Cattlemen’s Association since 2001 to offer and support a value-added preconditioning program called 

the Oklahoma Quality Beef Network (OQBN) for cattle producers. The program consists of 

preconditioning calf management protocols that producers adopt which are then certified by OCES 

personnel for cattle to qualify to sell in special OQBN sales at participating public livestock auctions. 

In 2008, OCES personnel began collecting detailed auction data to verify the differences in value 

for cattle marketed as part of the OQBN program compared to other cattle. This data collection effort 

was led by Derrell Peel and Kellie Raper and was supported by OCES personnel, OSU graduate students,

and other faculty. A programmed spreadsheet was developed by Eric DeVuyst to facilitate the real-time 

capture of auction data and a broad array of sale lot characteristics beyond what is typically captured in

publicly available data. This spreadsheet makes it possible to capture many sale and lot characteristics 

during auctions that can be analyzed to determine the impact of physical and management factors on 

2 Breedlove Professor of Agribusiness and Extension Livestock Marketing Specialist; former Extension Assistant; 

Professor and Livestock Marketing Specialist; and Professor and Rainbolt Chair; Department of Agricultural 

Economics, Oklahoma State University 
3

the value of cattle and to compare OQBN program cattle to non-OQBN cattle. This has resulted in a 

growing database of over 18,000 lots and over 178,000 head of OQBN program and non-OQBN cattle 

from 2010-2022. 

In the fall of 2021, the Agricultural Marketing Service (USDA-AMS) approached Derrell Peel and 

Kellie Raper about collecting similar data on a broader set of markets in multiple states with the 

objective of a more comprehensive analysis to analyze factors that impact feeder cattle value and 

provide additional evidence to support AMS efforts to expand market information in AMS market 

reports. Moving rapidly, efforts were initiated to identify collaborators in various states to utilize the 

OSU data collection tool (with some modifications) to collect feeder cattle auction data in several states 

and sale locations. 

Project Objectives

The project had two primary objectives:

1) To collect feeder cattle auction data in multiple states/sales including as many cattle 

characteristics as possible to permit analysis that would identify factors affecting the value of 

different lots of cattle.

2) To quantify the individual impact of various factors that affect the value of feeder cattle using 

multi-variate econometric analysis.

Data Collection

The basic data collection protocol consisted of capturing the details of the sale for a particular 

lot of animals. Information on lot characteristics, physical cattle characteristics, and calf management 

practices were recorded for each lot. Table 1 includes the range of sale characteristics included in the 

data collection spreadsheet. Lot characteristics include number of head in the lot, average weight, sex, 

and uniformity. Calf management characteristics include weaning status, days weaned, vaccination 

status, health status and program certifications. Physical cattle characteristics include hide color/breed, 

muscling, frame, fill, flesh, Brahman influence, and horns. Additional data collected include sale time, 

date, age and source verification, seller-announced, and any announced or written management 

comments. In general, the project attempted to capture the full range of information that buyers have 

available to them during the sale. This includes visual characteristics of the sale lot, announcements and 

verbal descriptions provided and, sometimes, written sale information. This set of information, 
4

combined with the details of the sale transaction, represents the data that can be analyzed to assess the 

impact of various factors on the value of a given lot of cattle.

Data was collected from October 2021-April 2022 across seven states in a total of 92 individual 

sales at 21 locations (Tables 2 and 3). States included Kansas, Kentucky, Nebraska, Missouri, Oklahoma, 

South Dakota, and Wyoming. In total, the data includes 275,335 head of feeder cattle in 18,038 sale lots. 

The value of cattle included in the data was over $291 million. Data was collected by extension 

personnel and contractors in each of the states. Locations in Oklahoma and South Dakota account for 

60% of the lots, but 75% of the cattle.

Data Summary

Lot Size Differences Across States

Average lot size is one indicator of regional differences, both across states and within states. Table 3 

indicates that average lot size was highest in South Dakota at 25.6 head, followed by Nebraska (20.6), 

Wyoming (15.5) and Oklahoma (13.1). Kansas (8.8), Missouri (6.2) and Kentucky (4.3) all have average 

lots sizes under 10 head, with Kentucky reporting the smallest lot sizes, overall and across individual 

sales within the state. Lots sizes were relatively consistent across in-state sales for Kentucky, Nebraska, 

and South Dakota. The Joplin sale in Missouri had the largest lot size (15.4 head) by far for the state 

while, in Oklahoma, the average lot size for McAlester (2.5) was substantially lower than for the other 3 

sale sites.

Physical Characteristics 

Nearly 48% of steer lots and 47% of heifer lots were sold at average weights between 500 and 700 

pounds (Table 4). Table 4 also indicates that mixed #1-2 muscled lots represented approximately 63% of 

total lots as did medium/large-framed lots. Interestingly, lot sizes were significantly higher for lots 

scored as #1 muscling than for those with lower muscling scores. This holds true to a lesser extent for 

large-framed lots relative to lots with other frame scores.

The distribution of hide color and/or breed designation is reported in Table 5. Not surprisingly, black 

hided cattle dominate the data, with 60% of cattle recorded as black hided and another 15% recorded as 

predominantly black. This is followed by nearly 9% designated at mixed high quality lots. These are 

typically lots with no predominant hide color, but cattle of good quality. Red or predominantly red lots 
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make up 7.8% of lots, followed by white/gray-hided lots of cattle at 6.3%. Herefords were represented 

in less than 1% of lots. Approximately 9% of lots showed Brahman influence with another 1% of lots 

showing minimal Brahman influence.

Management Characteristics

Management characteristics are those attributes of the cattle directly influenced by producers through 

how cattle are managed between birth and sale. Nearly 64% of cattle were marketed as weaned cattle, 

implying they had been separated from the dams for a minimum of 30 days before marketing (Table 6). 

Vaccination information was collected in two forms: (1) vaccinated cattle were reported as having more 

than one dose of respiratory complex vaccinations and (2) limited vaccination cattle were reported as 

having had one dose of respiratory complex vaccinations. Cattle considered fully vaccinated comprise 

54.1% of the lots collected and limited vaccination cattle comprise another 8.4%, for a total of 62.5% of 

lots having received at least one round of respiratory vaccinations prior to sale. Approximately 46% of 

lots were both weaned and vaccinated prior to marketing. Nearly 6% of lots were marketed as Natural 

(5.4%) or Non-Hormone Treated Cattle (NHTC) (0.5%). Interestingly, the lot size for NHTC cattle was 

nearly double that of other characteristics. Two certification programs with sizable data were the 

Oklahoma Quality Beef Network (OQBN) with 1.1 percent of the lots and the Integrity Beef program

with 0.5 percent of total lots. A very small number of sale specific certification programs were noted in 

the data as well. Finally, horns or minimal horns were documented in 3.3% of lots. 

Value Characteristics of Feeder Cattle Auction Data

Modeling

The economic concept of the “law of one price” holds that price differences for a particular product are 

explained by adjusting for time, place, and form. In the case of feeder cattle, observed price differences 

for a particular lot of cattle are therefore due to time differences impacting the supply and demand that 

determine overall market values, location differences, and individual characteristics of the animals. A 

hedonic pricing model was used to analyze the contribution of lot attributes, physical attributes, and 

management attributes to overall lot price. The basic assumption of hedonic models is that buyers 

choose among goods with varying attributes and place values on the individual characteristics of a good 

based on the perceived utility or benefit that they gain from each (Lancaster, 1966; Rosen, 1974). The 

overall price of a good then is the sum of values that the buyer places on each of the good’s individual 

characteristics. 
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Hedonic models are commonly used to model pricing differences in markets where the product can be 

viewed as differentiated in that buyers have choices related to specific characteristics. Examples include 

real estate, rental housing, and cars. Hedonic modeling has been used often to analyze the marginal 

price impact of varying lot characteristics, physical characteristics, and calf management practices on lot 

prices for feeder cattle. Selected examples include Bulut and Lawrence (2007), Coatney, Menkhaus, and 

Schmitz (1996), Schroeder et al. (1988), Williams et al. (2014), Williams et al. (2012), and Zimmerman et 

al. (2012). 

Conceptually, the hedonic model used for this analysis is: 

1) Pit = f(Mt, Cji),

where Pit is the price of the lot i of cattle in time t; Mt is the cattle market level in time t; and Cji is the set 

of j characteristics that differentiate each lot of cattle, i, including sale locations. 

Because the data for this project was collected over several months, adjusting prices for changes in 

general market conditions is necessary. The CME Feeder Cattle Index was used as a reference market 

for underlying market values each week. Thus, the price of a lot of cattle in a given week (equation 1) 

would reflect the underlying market level Mt (as indicated by the CME Feeder Cattle Index) along with 

the set of sale characteristics and the sale location.

However, cattle price and the CME Index value will be highly correlated, resulting in a regression model 

with a high degree of multicollinearity when the CME Index is included as a separate independent 

variable. The usual solution for this is to use a first-difference specification, where the dependent 

variable is the difference between the lot price and the CME Index value. The resulting value is called a 

basis, as it is the difference between two prices, and is specified as:

2) Basisit = Pit − CME Indext.

By subtracting out the underlying market value, the regression model focuses on the remaining 

differences in value due to the lot characteristics. Using this basis specification, changes in cattle market 

conditions at different times are removed from the model, while retaining the focus on the impact of 

individual sale characteristics and location differences. 
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The hedonic model to be estimated is:

3) Basisi = β0 + β1Ln(headi) + β2(

avgwt

100 )i + β3 (

avgwt

100 )

i

2

+ ∑β3+j

3

j=1

Genderij + β7Weani

+ β8Vaxxi + β9Health i + ∑β9+jHidecolorij

10

j=1

+ ∑β19+j

2

j=1

Horni

+ ∑β21+j

3

j=1

Conditionij +∑β24+j

5

j=1

Musclingij + ∑β29+j

4

j=1

Frameij

+ ∑β33+j

3

j=1

Fillij + β37Uniformi + ∑β37+j

7

j=1

Certificationij

+∑β44+j

2

j=1

Brahmani + β47Naturali + β48Cripplei + β49Badeyei

+∑β49+j

21

j=1

Locationij + ∑β70+j

5

j=1

Monthij + μ i + ei

where i = 1,...,18038 denotes each sale lot; head is the number of animals in lot i; avgwt is the average 

weight of the animals in lot i; genderi1 equals 1 if heifers; genderi2 equals 1 if the lot is bulls or mixed 

gender; genderi3 equals 1 if the lot is replacement heifers; wean equals 1 if the lot is weaned; vac

equals 1 if the lot is vaccinated; health equals 1 if there are unhealthy animals in the lot; hidecolorij are 

dummy variables for hide colors (black is base color); horn equals 1 if horns are present in the lot; 

conditonij are condition (fleshiness) scores (average flesh is base); musclingij are dummy variables 

for muscle score (1&2 is base); frameij are dummy variables for frame size (medium framed is base); 

fillij are dummy variables for amount of fill (average fill is base); uniform equals 1 if the lot is not 

uniform; certification equals 1 if third-party verification of vaccination and weaning; Brahman equals 1 if 

Brahman influence is visible in the lot; locationij is composed of dummy variables for sale location (OKC 

is Base); monthij is comprised of dummy variables for the month the sale occurred (October is Base); 

and ei are error terms for each observation.

Note that the vaxx variable combines vaccinated cattle and limited vaccinated cattle into one category 

for estimation. The gender variable splits heifers designated as replacement heifers into a separate 
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gender variable. The horns variable splits lots with horns present into horned lots (20% or more have 

horns) and minimal horns (some horns but less than 20% of animals).

Lot size was modeled as a natural logarithm, and average weight was divided by 100. Basis was 

calculated using the weekly CME Feeder Cattle Index retrieved from the LMIC. The regression was 

estimated using the Mixed procedure in STATA 15 with the variance for each sale and each lot being 

held as a random effect.

Results

Results from the hedonic model analysis are presented in Tables 7, 8, 9, 10, 11, and 12. Table 7 reports 

estimates for general sale characteristics, including lot size and average weight. Figure 1 illustrates 

market premiums for lot size as depicted in the data set, based on a logarithmic function. Lot size 

premiums for feeder cattle are routinely observed to be nonlinear with larger marginal premiums as lots 

move from 1 up to 10 head and decreasing marginal premiums thereafter3. 

Table 8 shows the impact of lot size on price premiums. Price premiums are quite pronounced for lots 

less than 10 head. For example, a lot of 5 head has a premium of $11.58/cwt compared to a single 

animal lot. For larger lots the marginal increase in price for larger lots decreases significantly. For 

example, a 40 head lot receives an average premium of $4.99/cwt. compared to a 20 head lot and a lot 

of 60 animals receives a premium of $2.91/cwt. over a 40 head lot.

3 The pattern of lot size premiums will depend on the nonlinear functional form utilized in the analysis. Lot size is 

sometimes estimated as a quadratic function, which implies a peak lot size premium with declining premiums 

beyond the peak. The logarithmic function is chosen here because it captures the initial increases in premiums 

faster and is asymptotic, with no maximum value.
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Feeder cattle price per hundredweight ($/cwt.) decreases as animal weight increases. This price 

decrease is not linear but decreases at a decreasing rate as weight increases. In fact, heavy weight 

feeder cattle may show little price decrease as weight increases. This price decrease, frequently 

referred to as the price slide or price rollback, varies seasonally and with different market conditions, 

including feed costs (Peel and Riley, 2018). The model estimates show that price decreases in a nearly 

linear fashion by $14.62/cwt for each one hundred pounds of weight. The quadratic term is small but 

will slow the decrease in price by weight by 0.416 times weight squared. This quadratic term would 

offset the linear decrease at a weight well above the feeder cattle weight range. 

Value of Animal Characteristics

Table 9 includes model estimates for the value of various animal characteristics. Compared to steers, 

heifer price is lower by an average of 18.70/cwt. Bulls/mixed lots are lower in price by 7.39/cwt. 

Although producers cannot generally control the production of steers versus heifers (sexed semen being 

an exception), marketing bulls rather than steers is a management choice. At the average weight of 596 

pounds, this analysis indicates that bulls bring an average of $44.06/head less than steers. Some heifers 

are specifically identified as replacement heifers in sales. The price of replacement heifers is 

$20.09/cwt. less than steers and is a bigger discount than the heifer average. However, a check of the 

data confirmed that replacement heifers are all among the heaviest heifers by weight and the price 

reflects the heavier weight. All of the gender variables are highly significant statistically.

All lots were identified by hide color or breed characteristics if possible. The majority of lots were blackhided (60%) with another 15 percent predominantly black-hided. All of the estimated differences due to 

hide-color/breed were statistically significant. Compared to black-hided lots, the predominantly blackhided lots had the smallest discount of $1.93/cwt. (Table 9). Red-hided, white/gray hided, and mixed 

high quality lots all had discounts between $5-$6/cwt relative to black-hided lots. Animals with 

distinctive Hereford breeding received a discount of $9.93/cwt. compared to black-hided animals. Lots 

identified as dairy or longhorn breeding, mixed low quality or beef-dairy crossbred animals received 

discounts ranging from $28.62 - $32.52/cwt. Regardless of hide color, animals exhibiting brahman 

breeding were identified and received an additional discount of $8.94/cwt. While lots with a few 

animals showing Brahman breeding (Minimal Brahman) received an additional discount of $6.17/cwt. 
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compared to cattle exhibiting no Brahman influence. These discounts are in addition to any discount 

related to the lot’s specific hide color or breed notation.

Using lots with mixed #1-#2 muscling as a base, lots that were all #1 muscling received a premium of 

$2.91/cwt. In comparison. Lots of #2 muscling received a slight discount of $0.63/cwt. While lots of #2-

#3 muscling were discounted $6.06/cwt. However, the estimates for #2 and #2-#3 muscling were not 

statistically different from #1-#2 muscled lots. Lots with #3 muscling received a statistically significant 

discount of $24.31/cwt.

 

Compared to medium-framed animals, lots of large-framed animals received a statistically significant 

discount of $2.67/cwt. Mixed medium/large frame and small framed animals received similar discounts 

of $1.41-$1.51/cwt. However, these discounts were not statistically different from the medium-framed 

animals.

Value of Management Characteristics

Management decisions have a significant impact on the value of feeder cattle. The decision to market 

feeder cattle as bulls rather than steers was discussed in the previous section (see Table 9). Table 10

presents the value of a variety of other management decisions affecting feeder cattle. Weaned calves 

(30 days or more) bring a premium of $4.48/cwt compared to unweaned calves. Vaccinated calves 

receive a premium of $1.97/cwt. over unvaccinated calves. Removing horns or using polled genetics 

increases feeder cattle value over horned cattle. Cattle with horns receive a discount of $8.47/cwt. 

compared to no horns. Lots that included only a few horned animals (less than 20 %) received a slightly 

smaller discount of $6.20/cwt. 

Animals marketed with excessive flesh were discounted $4.02/cwt. compared to animals of average 

flesh. Animals described as thin flesh received a slight but statistically insignificant premium compared 

to average fleshed animals. Animals described as full (tanked) received a discount of $15.15/cwt. 

compared to animals with average fill. Likewise, animals described as gaunt received a similar discount 

of $16.30/cwt. Animal fill is sometimes under control of the producer but may also be the result of 

auction facility management.
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Producers may participate in a wide variety of certification programs. In this analysis, enough data for 

three programs permitted evaluation of program certification value, including the Oklahoma Quality 

Beef Network (OQBN), the Integrity Beef program, and Non-Hormone Treated Cattle (NHTC). A small 

number of other program cattle were included in the data, but numbers were insufficient to analyze 

individually. The value of OQBN certification was $4.52/cwt. while the Integrity Beef certification had a 

premium of $10.39/cwt. NHTC had a positive value of $1.20/cwt., but the estimated parameter is not 

statistically significant. Note that numbers of NHTC cattle were minimal in the data but the estimated 

parameter is included here because of the national scope of the program. Programs such as OQBN and 

Integrity Beef encompass preconditioning protocols such as weaning and vaccination, along with 

castration and dehorning. Integrity Beef includes additional requirements for genetics, likely influencing 

the magnitude of the premium. The total value of these programs is the sum of these management 

practices and the certification. For example, the value of OQBN would be a total of certification, 

weaning and vaccination implying that the total value-added for a 550-pound steer would be 

$10.97/cwt. ($4.52+$1.97+$4.48). This is consistent with observed premiums for OQBN cattle in 

Oklahoma, where the 5-year average OQBN premium over nonpreconditioned cattle for 5 weight steers

was $12.59/cwt for 2018-2022 (Raper and Peel, 2023). A significant number of cattle were marketed as 

natural (977 lots with 24,233 head). Natural definitions vary widely and are not consistent. The 

estimated parameter on natural cattle is slightly negative at -$0.88/cwt. but is not statistically different 

from zero.

Cattle identified visually as obviously unhealthy received discount of $38.25/cwt. Cattle specifically 

identified as crippled received a discount of $49.90/cwt. while cattle with bad eyes were discounted 

$20.46/cwt.

Location

Feeder cattle prices at any point time vary considerably in different regions of the country (Highfill and 

Peel, 2015). The hedonic model used in this analysis included binary variables to account for different 

sale locations. Table 11 presents the estimated parameters for each sale location compared to the base 

market at OKC National. The signs and significance of the location variables generally confirm previously 

identified regional differences in feeder cattle prices. Variables that are statistically insignificant cannot 

be said to have prices different from OKC National. 
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Consistent with previous research, the highest average prices and largest premiums to the base market 

are noted in Nebraska/Wyoming with statistically significant premiums of $11.07/cwt. for Valentine, a 

premium of $9.47/cwt. for Ogallala and $10.24/cwt. in Torrington. By contrast, Kentucky auctions 

showed statistically significant discounts to the base market of OKC National. Estimates for the four 

Kentucky markets are -$19.09/cwt. for Springfield; -$12.75/cwt. in Campbellsville; -$9.22/cwt. in 

Stanford; and -$7.56/cwt. for Richmond.

South Dakota auctions showed a mixed set of discounts and premiums, generally not significantly 

different from the base market. This includes premiums of $4.01/cwt. in Faith; $3.62/cwt. in Philip and 

discounts of -$1.80 for Mitchell and -$0.57 for Pierre. The discount of $5.16/cwt for Hub City was 

statistically different from the base market at OKC National.

Within Oklahoma, OKC West (El Reno) has a premium of $2.05/cwt while Woodward posts a slight 

premium of $0.58/cwt. However, neither of these estimates are statistically significant. Prices at 

McAlester, OK are significantly less than OKC National by $5.58/cwt. The auction at Salina, KS posted a 

$4.02/cwt. premium to the base market that was marginally significant. 

 

Regional Observations and Comments

Significant regional differences became apparent in this project that impacts both market reporting and 

data collection. In some cases, these differences reflect regional culture relative to how cattle are 

marketed as well as regionally unique terminology and practices including the amount of information 

provided and the manner in which information is provided to buyers. Individual sale barns vary widely 

in sale management and information availability/communication, which affect the feasibility and 

amount of market information that can be reported/collected4. Individual auction and regional 

differences will impact the feasibility of collecting additional value data on a broader scale.

Summary

This project analyzes factors affecting the value of feeder cattle with what is likely the most 

comprehensive feeder cattle auction data set available. The data includes information on numerous 

4 An example is the attempt to collect data at the auction in Okeechobee, FL. While this auction is currently 

reported with the current market information, the management and pace of the auction made it infeasible to 

collect the augmented data needed for this project. No usable data was obtained to include in this analysis. This 

highlights the challenges of expanding market information for some markets.
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additional factors beyond current market reporting. The analysis provides estimates of the 

contributions of a variety of sale, animal and management characteristics that contribute to the value of 

a lot of feeder cattle. Additionally, the analysis confirms regional differences in feeder cattle value 

based on geographic location.
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References

Bulut, H., & Lawrence, J. D. (2007). The value of third-party certification of preconditioning claims at 

Iowa feeder cattle auctions. Journal of Agricultural and Applied Economics, 39(1379-2016-112663), 625-

640. https://doi.org/10.1017/S1074070800023312

Coatney, K. T., Menkhaus, D. J., & Schmitz, J. D. (1996). Feeder cattle price determinants: an hedonic 

system of equations approach. Review of Agricultural Economics, 193-211. 

https://doi.org/10.2307/1349432

Highfill, Brian and Derrell S. Peel. “A Model of Spatial Feeder Cattle Prices.” Selected Poster, 

Southern Agricultural Economics Association Annual Meeting, Atlanta, Georgia, February, 2015.

Lancaster, Kelvin J. “A New Approach to Consumer Theory.” Journal of Political Economy, 74(2):132-157. 

https://www.jstor.org/stable/1828835

Peel, Derrell S. and John Michael Riley. “Feeder Cattle Price Fundamentals” Western Economic Forum, 

December 2018, Volume 16, Issue 2:6-19.

Raper, K.C. and Derrell S. Peel. “Oklahoma Quality Beef Network History By the Numbers”. Unpublished 

Powerpoint Presentation, April 2023.

Rosen, Sherwin. “Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition.” 

Journal of Political Economy, 82(1):34-55, 1974. https://www.jstor.org/stable/1830899. 

Schroeder, T., Mintert, J., Brazle, F., & Grunewald, O. (1988). Factors affecting feeder cattle price 

differentials. Western Journal of Agricultural Economics, 71-81. https://www.jstor.org/stable/40987944

Williams, B. R., DeVuyst, E. A., Peel, D. S., & Raper, K. C. (2014). The likelihood of positive returns from 

value-added calf management practices. Journal of Agricultural and Applied Economics, 46(1379-2016-

113914), 125-138. https://doi.org/10.1017/S1074070800000675

Williams, G. S., Raper, K. C., DeVuyst, E. A., Peel, D., & McKinney, D. (2012). Determinants of price 

differentials in Oklahoma value-added feeder cattle auctions. Journal of Agricultural and Resource 

Economics, 114-127. https://www.jstor.org/stable/23243052

Zimmerman, L. C., Schroeder, T. C., Dhuyvetter, K. C., Olson, K., Stokka, G. L., Seeger, J. T., & 

Grotelueschen, D. M. (2012). The effect of value-added management on calf prices at superior 

livestock auction video markets. Journal of Agricultural and Resource Economics, 128-143. 

https://www.jstor.org/stable/23243053
15

Table 1. Data Collection Details and Protocol.

Characteristic Description/Details Protocol

Lot Size Number of Head in sale group

Sale price $/cwt. Cattle sold by the head not 

included.

Average Weight Average weight per head (lbs.) General 

weight range for data is animals from 300-

1000 pounds.

Gender Steers, Heifers, Bulls/Mixed lots

Vaccinations Vaccinated, limited vaccinations, 

unknown/not vaccinated 

Animals with a single round of 

respiratory vaccination are 

designated limited vaccination

Weaned Weaned, not weaned/unknown weaning Must be 30 days or more to be 

designated as weaned.

Days Weaned Days weaned are noted if announced or 

documented.

Comments may include “long 

weaned” or “yearling”, etc.

Certified Animals certified in a specific program are 

designated. Common programs are 

indicated (OQBN, Noble Beef, NHTC, 

NeverEver, MacVac and Breed) 

Other program names are noted 

in comments if not part of 

program list.

Hide Color Lots are identified by color description 

including black, black mixed, red, red 

mixed, Hereford, white/grey, 

dairy/longhorn, mixed color, and other

Predominantly black-hided lots 

with minority other colors noted 

as black mixed. Same for red.

Brahman Brahman influenced breeding is noted. If roughly 20% or more of the lot 

shows Brahman influence. Less 

than 20% but obvious Brahman 

influence is designated minimal 

Brahman.

Flesh Thin, average, and fleshy cattle noted. 

Muscling #1, 1-2, 2, 2-3, light

Frame Large, medium-large, medium, and small

Horns Horned cattle noted If roughly 20% or more of the lot 

have horns

Uniformity Non-uniform lots are noted

Health Unhealthy cattle are noted

Additional 

characteristics 

either stated or 

observed

Includes age/source; owner identified; BQA 

certified; natural; genetic information; 

crippled; rugged; wormy; bad eye; cough; 

lice; ringworm; muddy/tags; dewormed

Additional characteristics or 

information can be noted in 

comments

Sale location Sale and state

Sale Date

Time Each sale lot is time stamped when entered
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Table 2. General Data Summary

Total Average Range (Min-Max)

Sales 92

Head 275,335

Sale Lots 18,038 15.3 head 1 – 453

Weight (lbs.) 596 149 – 1422

Price ($/cwt.) $156.82 $5.00 - $308.18

Value of Sales $291,710,731.01 Lot: $16,172

Head: $919

Table 3. State and Sale Locations 

State Sale Location (Number of Sales) Total Lots Total Head Ave. Lot Size 

(Head)

Kansas Salina (1) 230 2,019 8.8

Kentucky

Campbellsville (1)

Richmond (1)

Springfield (1)

Stanford (4)

1891

206

145

178

1362

8,090

477

409

439

6765

4.3

2.3

2.8

2.5

5.0

Nebraska

Ogallala (5)

Valentine (1)

997

828

169

20,529

17,867

2,662

20.6

21.6

15.8

Missouri

EMCC (Bowling Green) (4)

F&T (Palmyra) (4) 

Joplin (2)

Kingsville (1)

2,751

1,151

938

415

247

16,948

5,301

3,506

6,390

1,751

6.2

4.6

3.7

15.4

7.1

Oklahoma

OKC West (El Reno) (12)

McAlester (3)

OKC Natl (Oklahoma City) (7)

Woodward (9)

5,411

2,110

917

894

1490

70,957

30,661

19,418

18,552

2,326

13.1

14.5

2.5

21.7

12.5

South Dakota

Faith (4)

Ft. Pierre (7)

Hub City (Aberdeen) (4)

Mitchell (4)

Philip (9)

5,426

988

1,106

896

1,063

1,373

136,150

16,407

40,545

20,869

21,562

36,767

25.6

16.6

36.7

23.3

20.3

26.8

Wyoming Torrington (8) 1,332 20,642 15.5
17

Table 4. Feeder Cattle Weight, Muscling and Frame Characteristics

Weight (lbs.) Steers Heifers

Lots Head Avg Lot 

Size

Lots Head Avg Lot 

Size

<300 95 224 2.4 121 305 2.5

300-400 572 3215 5.6 718 3774 5.3

400-500 1428 15972 11.2 1744 16988 9.7

500-600 2207 37681 17.1 2157 31851 14.8

600-700 1949 35533 18.2 1672 27712 16.6

700-800 1321 29757 22.5 1059 24179 22.8

800-900 706 19548 27.7 487 10164 20.9

900-1000 284 7793 27.4 141 2231 15.8

>1000 135 2567 19.0 65 407 6.3

Total 8697 152290 17.5 8164 117611 14.4

Muscling All Animals

#1 2,207 62,594 28.4

#1-2 11,347 151,815 13.4

#2 3,334 39,144 11.7

#2-3/light 399 2,221 5.6

Frame All Animals

Large 2,338 43,586 18.6

Medium/Large 11,693 172,933 14.8

Medium 3.091 38,705 12.5

Small 164 508 3.1

Table 5. Hide Color/Breed

Color/Breed Head % of Total

Black 165,845 60.0

Predominantly Black 41,310 15.0

Red 10,499 3.8

Predominantly Red 11,030 4.0

Hereford 2,658 0.1

White/Gray 17,429 6.3

Dairy/Longhorn 546 0.2

Mixed High Quality 24,131 8.8

Brahman Influence 2,559 9.3

Minimal Brahman Influence 2,765 1.0
18

Table 6. Management Characteristics

Lots Total Head Avg Lot 

Size

% of Lots

Weaned 11,451 177,942 15.5 63.5

Vaccinated 9,763 192,799 19.7 45.1

Limited Vaccination 1,514 20,355 13.4 8.4

Vacc/Limited Vacc 11,277 213,154 18.9 62.5

Weaned/Vacc 8,349 141,311 16.9 46.3

Natural 977 24,233 24.8 5.4

OQBN 192 1524 7.9 1.1

Integrity 91 1179 13.0 0.5

NHTC 97 4,270 44.0 0.5

Horns 384 3,204 8.3 2.1

Minimal Horns 221 6,089 27.6 1.2

Table 7. Model Estimates: General Sale Characteristics

Variable Estimate Std. Error t-value

Log lot size (head) 7.196*** .312 23.03

Ave.weight (cwt.) -14.62*** 1.086 -13.46

Ave. weight2(cwt.) .416*** .086 4.86

Table 8. Lot Size Premium

Lot Size 

(Head)

Premium ($/cwt)

(Relative to 1 head)

Marginal Premium 

($/cwt)

2 $4.99

3 $7.91 $2.92

4 $9.98 $2.07

5 $11.58 $1.60

10 $16.57 $4.99

20 $21.56 $4.99

30 $24.48 $2.92

40 $26.55 $2.07

50 $28.15 $1.60

60 $29.46 $1.31

70 $30.57 $1.11

80 $31.53 $0.96

90 $32.38 $0.85

100 $33.14 $0.76
19

Table 9. Model Estimates: Animal Characteristics

Comparison Base Variable Estimate Std. Error t-value

Steers

Heifers -18.698*** .487 -38.43

Bulls -7.392*** .862 -8.58

Rep. Heifers -20.094*** 2.096 -9.59

Black-hided

Black mixed -1.93*** .502 -3.84

Red -5.252*** .817 -6.43

Hereford -9.932*** 1.304 -7.62

White/Gray -5.152*** .789 -6.53

Dairy/Longhorn -32.521*** 4.628 -7.03

Mixed Low Quality -28.057*** 4.468 -6.28

Mixed High Quality -5.597*** .722 -7.75

Beef-Dairy Cross -29.618*** 6.688 -4.43

Brahman Influence -8.935*** 2.315 -3.86

Minimal Brahman -6.165*** .966 -6.38

#1-2 Muscling

# 1 2.91** 1.48 1.97

#2 -.631 1.039 -0.61

#2-3 -6.061 3.719 0.103

#3 -24.31*** 2.555 -9.51

Medium Frame

Large -2.669*** 1.033 -2.58

Medium/Large -1.406 .946 -1.49

Small -1.514 6.006 -0.25
20

Table 10. Model Results: Management Characteristics

Comparison Base Variable Estimate Std. Error t-value

Unweaned

Weaned 4.475*** .649 6.89

Unvaccinated

Vaccinated 1.966*** .578 3.40

No Horns

Horns -8.465*** 1.563 -5.42

Minimal Horns -6.198*** 1.324 -4.68

Average Flesh

Thin .466 1.566 0.30

Fleshy -4.024*** 1.37 -2.94

Average Fill

Full -15.153*** 3.035 -4.99

Gaunt -16.295** 7.173 -2.27

Not Certified

OQBN 4.524*** 1.539 2.94

Integrity Beef 10.39*** 1.61 6.45

NHTC 1.204 1.418 0.85

Conventional

Natural -.884 .97 -0.91

Table 11. Model Results: Animal Health

Comparison Base Variable Estimate Std. Error t-value

Healthy

Unhealthy -38.248*** 6.182 -6.19

Crippled -43.903*** 7.381 -5.95

Bad Eye -20.458*** 3.228 -6.34
21

Table 12. Model Results: Location Impacts 

Comparison 

Base

State Sale Estimate Std. Error t-value

OKC National

Oklahoma OKC West 2.045 2.495 0.82

McAlester -5.581** 2.23 -2.47

Woodward .581 1.884 0.31

Kansas Salina 4.016* 2.355 1.71

Kentucky Springfield -19.088*** .973 -19.62

Campbellsville -12.745*** 2.263 -5.63

Stanford -9.218*** 3.253 -2.83

Richmond -7.562** 3.282 -2.30

Missouri F&T Livestock -1.583 2.845 -0.56

Joplin 0.66 2.824 0.23

EMCC 1.371 2.169 0.63

Kingsville 4.546** 2.234 2.03

Nebraska Ogallala 9.474*** 2.285 4.15

Valentine 11.071*** 2.378 4.66

South Dakota Faith 4.012 2.639 1.52

Ft. Pierre -0.569 2.362 -0.24

Hub City -5.157** 2.149 -2.40

Mitchell -1.799 1.922 -0.94

Philip 3.616 3.039 1.19

Wyoming Torrington 10.236*** 2.024 5.06
22

Appendix: Complete Model Regression Results

Mixed-effects regression 

Basis Coef. St.Err. t-value p-value [95% Conf Interval] Sig

Lnhead 7.196 .312 23.03 0 6.584 7.809 ***

avgwthun -14.62 1.086 -13.46 0 -16.749 -12.491 ***

avgwt2hun .416 .086 4.86 0 .248 .583 ***

Heifer -18.698 .487 -38.43 0 -19.652 -17.744 ***

bullsmixed -7.392 .862 -8.58 0 -9.081 -5.704 ***

repheifer -20.094 2.096 -9.59 0 -24.202 -15.985 ***

weaned 4.475 .649 6.89 0 3.203 5.747 ***

Vaxx 1.966 .578 3.40 .001 .834 3.098 ***

nothealthy -38.248 6.182 -6.19 0 -50.364 -26.132 ***

blckmix -1.93 .502 -3.84 0 -2.913 -.946 ***

red -5.252 .817 -6.43 0 -6.854 -3.65 ***

redmix -2.945 .678 -4.34 0 -4.273 -1.616 ***

heref -9.932 1.304 -7.62 0 -12.487 -7.377 ***

whgr -5.152 .789 -6.53 0 -6.698 -3.606 ***

daiLong -32.521 4.628 -7.03 0 -41.592 -23.45 ***

mixlowqual -28.057 4.468 -6.28 0 -36.815 -19.299 ***

other -19.237 2.666 -7.22 0 -24.462 -14.012 ***

mixhighqual -5.597 .722 -7.75 0 -7.013 -4.182 ***

BDB -29.618 6.688 -4.43 0 -42.726 -16.511 ***

horned -8.465 1.563 -5.42 0 -11.529 -5.402 ***

minhorn -6.198 1.324 -4.68 0 -8.794 -3.602 ***

thin .466 1.566 0.30 .766 -2.603 3.534

fleshy -4.024 1.37 -2.94 .003 -6.709 -1.338 ***

thick1 2.91 1.48 1.97 .049 .009 5.81 **

med2 -.631 1.039 -0.61 .544 -2.667 1.405

twoand3 -6.061 3.719 -1.63 .103 -13.349 1.227

light3 -24.31 2.555 -9.51 0 -29.318 -19.301 ***

large -2.669 1.033 -2.58 .01 -4.693 -.644 ***

medlarg -1.406 .946 -1.49 .137 -3.26 .447

small -1.514 6.006 -0.25 .801 -13.285 10.257

Full -15.153 3.035 -4.99 0 -21.101 -9.205 ***

gaunt -16.295 7.173 -2.27 .023 -30.354 -2.236 **

OQBN 4.524 1.539 2.94 .003 1.509 7.54 ***

othercert 1.793 1.163 1.54 .123 -.487 4.073

NobleBeef 10.39 1.61 6.45 0 7.235 13.545 ***

NHTC 1.204 1.418 0.85 .396 -1.575 3.984

MacVac .373 2.34 0.16 .873 -4.213 4.958

Breed .693 3.23 0.21 .83 -5.638 7.025

BQACert -1.348 1.274 -1.06 .29 -3.845 1.148

brahman -8.935 2.315 -3.86 0 -13.473 -4.398 ***

minbrahman -6.165 .966 -6.38 0 -8.058 -4.273 ***

Natural -.884 .97 -0.91 .362 -2.785 1.016

Cripple -43.903 7.381 -5.95 0 -58.369 -29.437 ***

BadEye -20.458 3.228 -6.34 0 -26.785 -14.13 ***

Elreno 2.045 2.495 0.82 .412 -2.845 6.934

McAlister -5.581 2.263 -2.47 .014 -10.017 -1.146 **

Woodward .581 1.884 0.31 .758 -3.112 4.274

Salinakansas 4.016 2.355 1.71 .088 -.6 8.632 *

Torrington 10.236 2.024 5.06 0 6.268 14.204 ***

Ogallala 9.474 2.285 4.15 0 4.995 13.953 ***

Valentine 11.071 2.378 4.66 0 6.41 15.731 ***
23

springfield -19.088 .973 -19.62 0 -20.994 -17.181 ***

Campbellsville -12.745 2.263 -5.63 0 -17.181 -8.31 ***

Stanford -9.218 3.253 -2.83 .005 -15.594 -2.843 ***

Richmond -7.562 3.282 -2.30 .021 -13.995 -1.13 **

FTL -1.583 2.845 -0.56 .578 -7.159 3.993

Joplin .66 2.824 0.23 .815 -4.875 6.195

EMCC 1.371 2.169 0.63 .527 -2.88 5.623

Kingsville 4.546 2.234 2.03 .042 .167 8.924 **

Faith 4.012 2.639 1.52 .128 -1.161 9.186

FTpierre -.569 2.362 -0.24 .81 -5.199 4.061

Hubcity -5.157 2.149 -2.40 .016 -9.369 -.945 **

Mitchell -1.799 1.922 -0.94 .349 -5.566 1.967

Philip 3.616 3.039 1.19 .234 -2.34 9.571

Nov 1.225 2.858 0.43 .668 -4.376 6.827

Dec -.803 2.654 -0.30 .762 -6.004 4.398

Jan 2.467 2.668 0.92 .355 -2.763 7.696

Feb 11.13 2.149 5.18 0 6.917 15.342 ***

Mar 14.029 2.217 6.33 0 9.683 18.375 ***

April 22.031 3.472 6.34 0 15.225 28.837 ***

Constant 59.442 3.907 15.21 0 51.784 67.099 ***

Constant 1.196 .153 .b .b .932 1.536

Constant 2.836 .021 .b .b 2.796 2.877

Constant 1.861 .122 .b .b 1.637 2.116

Mean dependent var -0.397 SD dependent var 28.056

Number of obs 18038 Chi-square .

Prob > chi2 . Akaike crit. (AIC) 156225.527

*** p<.01, ** p<.05, * p<.1