Random Sampling of Beef Cattle for Genetic Testing: Optimal Sample Size Determination

Nathanael Thompson, B Brorsen, Eric DeVuyst and Jayson Lusk

No 229195, 2016 Annual Meeting, February 6-9, 2016, San Antonio, Texas from Southern Agricultural Economics Association

Abstract: Sample size is often dictated by budget and acceptable error bounds. However, there are many economic problems where sample size directly affects a benefit or loss function, and in these cases, sample size is an endogenous variable. We introduce an economic approach to sample size determination utilizing a Bayesian decision theoretic framework that balances the expected costs and benefits of sampling using a Bayesian prior distribution for the unknown parameters. To demonstrate the method for a relevant applied economics problem, we turn to randomly sampling beef cattle for genetic testing. A theoretical model is developed, and several simplifying assumptions are made to solve the problem analytically. Data from 101 pens (2,796 animals) of commercially-fed cattle are then used to evaluate this solution empirically. Results indicate that at the baseline parameter values an optimal sample size of n^*=10 out of 100 animals generate returns from sampling of nearly $10/head, or a return-on-investment of 250%. Therefore, a large portion of the additional value for higher-quality cattle can be captured by testing a relatively small percentage of the lot. These results vary depending on the actual quality (or profitability) of a particular pen of cattle, the homogeneity within the pen, the variance of the buyer’s subjective prior distribution of expected profit, and the per-head cost of genetic testing. Nonetheless, results suggest that random sampling has the potential to provide a context in which the benefits of genetic testing outweigh the costs, which has not generally been the case in previous research.

Keywords: Farm Management; Livestock Production/Industries; Production Economics (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:ags:saea16:229195

DOI: 10.22004/ag.econ.229195

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