Local adaptation and maladaptation to climate change in US agriculture

• Agricultural Economics Workshop

Date and Location

Thursday, March 17, 2022, 4:10 PM - 5:30 PM
Online Meeting, Zoom

Abstract

Understanding agricultural adaptation to the changing climate is critical to evaluating the impact of climate change on agriculture. Variation in natural resource endowments, farming practices, and many other factors across counties in the United States suggests large heterogeneity in agricultural adaptation. By using a semi-parametric approach that allows county-specific coefficients for climate variables, this paper examines the spatial heterogeneity in the responsiveness and adaptation of U.S. agriculture to climate change. We also i) construct county-specific adaptation indices of corn, soybeans, and cotton to four climate variables (namely, normal growing degree days (GDD), overheating GDD, normal precipitation, and low precipitation); and ii) associate these four adaptation indices to crop insurance prevalence, genetically engineered (GE) crop adoption, cover crop adoption, and land quality. We find that large heterogeneity exists in agricultural adaptation across U.S. counties, with the Corn Belt showing adaptation to overheating GDD but maladaptation (i.e., ``negative adaptation'') to normal GDD. Results for Southeastern counties are largely opposite to those of the Midwest. We also find that the negative impact of future climate change on crop yields projected by models without considering spatial heterogeneity in adaptation ranges from 1.5 to 7.5 times higher than that predicted by our preferred models that explicitly consider the spatial heterogeneity in adaptation. Finally, we find that, in general, crop insurance prevalence is negatively associated to agricultural adaptation whereas GE crop adoption, cover crops, and land quality are positively associated to adaptation.