Matthew Gammans, University of California, Davis
Pierre Mérel, University of California, Davis
Long-run Impacts of Climate Change on Crop Yields: Estimation Framework and Evidence from France
Date and Location
Thursday, October 5, 2017, 4:10 PM - 5:30 PM
ARE Conference Room, 2102 Social Sciences and Humanities
The panel data approach with fixed effects has emerged as the preferred method to uncover the effects of climate change on economically relevant outcomes using historical weather data. While the panel method has been criticized for its purported inability to account for long-run adaptation, it has been argued that including nonlinearities in explanatory weather variables makes cross-sectional variation enter coefficient identification, suggesting that the estimates obtained from a nonlinear, fixed effects panel model at least partially reflect long-run adaptation.
We formalize this argument in the context of the popular quadratic specification and show that (i) skewness in the historical weather data conditional on location is an essential driver of the bias in the panel estimates relative to the underlying long-run values, and can result in bias in either direction, (ii) in the absence of such skewness, the panel estimates are a convex combination of the short-run and long-run coefficients, and (iii) the panel estimates reflect the long-run values whenever the cross-sectional variation in climate “dominates” the location-specific weather fluctuations, in a sense that we make explicit. We then illustrate how the panel approach can be leveraged to simultaneously estimate short-run and long-run effects using data on French cereal yields. We extend the existing framework by allowing unobserved heterogeneity to affect both yield levels and the marginal response of yields to weather. In contrast to recent results for US crops, our results suggest significant adaptation to temperature and precipitation changes in the long run.
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