Download or read book Measuring Value Added Characteristics in Feeder Cattle written by Crystal Dawn Mathews and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: According to the USDA, there were 52.7 million marketings of cattle through live and internet auction markets and other venues in 2005. With the national average herd size at 43 head, most producers have limited bargaining power when it comes to marketing and auctioning their cattle. This has led to the birth of numerous value added cattle programs in the U.S. Value added programs are named as such, because they add additional value to the cattle before they are sold, but this value is difficult to quantify. The objective of this research was to measure the value of characteristics of feeder cattle sold through auction markets and special source verified feeder cattle sales, specifically the value of participating in these value added programs. Data over seven years from regular and special feeder cattle sales at Joplin Regional Stockyards were used. The effects of explanatory variables on sale price were analyzed using ordinary least squares regression hedonic model. Type of sale, seasonality, cyclical effects, lot size, weight, breed type, sex, commingling, fed cattle futures price, and corn price were all found to have an impact on the sale price of feeder cattle. Feeder calves sold through MFA Health Track Beef Alliance and other value added programs received a premium over those calves that sold through regular sales and the premiums for MFA and other value added programs were statistically different. Commingled lots of feeder cattle received a discount in comparison with non-commingled lots, but a lot size of 17 head would offset the negative effect of commingling. The predictive power of the hedonic model was tested using out of sample forecasting. The mean absolute percent error and root mean square error are indicators of the ability of the model to forecast sale price based on the measured impact of the explanatory variables. When the hedonic model was used for forecasting the out of sample data, the MAPE was 7.84 and the RMSE was 10.48.