Quantifying Heterogeneous Returns to Genetic Selection: Evidence from Wisconsin Dairies, ,This chapter is a preliminary draft unless otherwise noted. It may not have been subjected to the formal review process of the NBER. This page will be updated as the chapter is revised.
Chapter in forthcoming NBER book Economics of Research and Innovation in Agriculture, Petra Moser, editor Estimates of productivity growth in the dairy sector attribute as much as half of observedgrowth to genetic improvement. However, productivity can be over-attributed to the quality ofthe genetics instead of the skill of the farmer in selecting them when models ignore selectionbias in the dairy cow production function. Our work decomposes total productivity changeon Wisconsin dairy farms due to genetics into separate effects for genetic improvement andendogenous selection. Using data from a large sample of Wisconsin dairy farms and national-level data on dairy sire rankings, we develop and estimate a model that accounts for selectionbehavior in the animal’s production function. We find that selection accounts for as much as 75percent of the total productivity improvement in our sample. Our results provide evidence forpositive assortative matching, whereby farmers who adopt above-average yield genetics alsoperform better than average for their chosen genetics. Overall, our results indicate that a largeportion of productivity growth in dairy farming can be explained by farmers’ ability to identifyand select genetics well suited to their production environment, and not solely the quality ofthe genetics they choose. This paper is available as PDF (419 K) or via email
Supplementary materials for this chapter: Machine-readable bibliographic record - MARC, RIS, BibTeX This chapter first appeared as NBER working paper w26417, Quantifying Heterogeneous Returns to Genetic Selection: Evidence from Wisconsin Dairies, Jared P. Hutchins, Brent Hueth, Guilherme Rosa |
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