Quantifying Heterogeneous Returns to Genetic Selection: Evidence from Wisconsin Dairies

Jared P. Hutchins, Brent Hueth, Guilherme Rosa

NBER Working Paper No. 26417
Issued in November 2019
NBER Program(s):Development of the American Economy, Productivity, Innovation, and Entrepreneurship

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.

Acknowledgments

Machine-readable bibliographic record - MARC, RIS, BibTeX

Document Object Identifier (DOI): 10.3386/w26417

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