Quantifying Heterogeneous Returns to Genetic Selection: Evidence from Wisconsin Dairies
Estimates of productivity growth in the dairy sector attribute as much as half of observed growth to genetic improvement. Unobserved match quality is an important determinate of genetic selection by dairy farmers that confounds attribution to genetic improvement alone. Using data from a large sample of Wisconsin dairy farms, and national-level data on sire rankings, we develop and estimate a model that accounts for selection behavior, and decompose total productivity change into separate effects for genetic improvement and endogenous selection. We find that selection accounts for as much as 75 percent of the total productivity improvement in our sample. Our results provide evidence for positive assortative matching, whereby farmers who adopt above-average yield genetics also perform better than average for their chosen genetics. Further, we find that management behavior accounts for a significant portion of within-herd cow-level heterogeneity, suggesting that dairy farmers manage their herds at the level of individual cows. Overall, our results indicate that a large portion of productivity growth in dairy farming can be explained by farmers’ ability to identify and select genetics well suited to their production environment.
We are grateful for the feedback on preliminary versions of this research provided by researchers at the Animal Genetics Improvement Laboratory (AGIL) in the USDA and the Council on Dairy Cattle Breeding (CDCB). We also are grateful to the participants in the NBER Economics of Research and Innovation in Agriculture meeting in Washington DC on May 17, 2019, especially the insightful feedback and comments from our discussant Paul Scott. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.
Forthcoming: Quantifying Heterogeneous Returns to Genetic Selection: Evidence from Wisconsin Dairies, Jared Hutchins, Brent Hueth, Guilherme Rosa. in Economics of Research and Innovation in Agriculture, Moser. 2020