Hedonic pricing models for red angus bulls

Abstract

The process of introducing genetics into a cow-herd is arguably the most important strategic decision a producer can make. Each producer has unique objectives for their herd, and unique ways of making the bull buying decision. Expected progeny differences have been created to highlight the genetic merits of bulls and to aid producers in valuing the bull for sale. Furthermore, indexes take multiple EPD’s and combine them into one score to make wading through genetic information simpler for the bull buyer. The objective of this thesis is to highlight the genetic factors, regional factors, and sire code factors that affect auction bull sale prices within the Red Angus Breed. Auction sale data has been collected from the Red Angus Association of America for all bulls sold during the Spring 2017 and Spring 2018 auction sales which include over 10,000 observations. A hedonic pricing method and regression analysis was used to quantify the impact of various independent variables on the dependent variable, price. Three separate models were used in this analysis to look at the expected progeny difference variables in three unique ways. Running the EPD's as single variables in the first model allowed the researcher to see which individual genetic variables have the greatest impact on price. Running a composite trait package model allowed the researcher to see which categories have the greatest impact on price. And finally, running the Red Angus Index model provides valuable feedback to the Red Angus Association of America and their members on the importance of their indexes. Results showed that the Great Plains Region represented the vast majority of bulls sold at auction with 75% of the total population, and Montana showed the largest percentile ranking among states with 23%. Bulls that were sired by embryo transfer and artificial insemination sold for an average premium of $906 and $574 over bulls that were sired by natural service. The composite trait group model in this study showed that bull buyers paid the most for calving traits followed by maternal traits, growth traits, and finally carcass traits. The two indexes developed by the Red Angus Association of America both had strong marginal effects on the sale price of a bull, with buyers paying a premium of 244% for one unit change in GridMaster over HerdBuilder in 2017, and a 12% premium for GridMaster over HerdBuilder in 2018 on an equitable impact scale. The EPD isolation model showed that twelve out of thirteen variables were at least 90% statistically significant in at least one out of the two years. On average for the spring of 2017 and 2018, for every unit increase in score of the following variables, the sale price of the bull changed as follows: Lot number – decrease in sale price by $5.88, calving ease direct – increase in sale price by $184.91, milk – increase in sale price of $30.40, maternal energy – decrease in sale price by $84.50, heifer pregnancy – increase in sale price by $11.31, calving ease maternal – increase in sale price by $14.67, stayability – increase in sale price by $39.13, calving/weaning/yearling weight composite variable – increase sale price by $23.96. A more appropriate one-tenth of a unit increase in marbling, ribeye area, and back fat lead to increases in the sale price by $6.11, $10.92, and $64.26, respectively. The 2017 data-set predicted bulls between the ages of 2.5 – 3.5 years of age sold for the highest prices, while the 2018 data-set did not follow the same predicted parabolic arch.