Edited by Ariel Dinar and Robert Mendelsohn
Chapter 7: Using Panel Data Models to Estimate the Economic Impacts of Climate Change on Agriculture
Olivier Deschenes and Michael Greenstone INTRODUCTION Agriculture is one of the economic sectors most sensitive to weather fluctuations and extreme events since temperature and precipitation are direct inputs in agricultural production. As a result, there have been long-standing concerns and debates about the likely effects of global climate change on the agricultural sector in the USA and elsewhere.1 Despite this massive research effort, there remains considerable uncertainty about the sign and magnitude of the likely effect of climate change on the US agricultural sector. In this chapter, we review the emerging literature that has used panel data methods to estimate the economic impacts of climate change on agriculture. The focus is on methods relying on interannual variation in weather as the primary source of identification for the statistical models, as in Deschenes and Greenstone (2007), Kelly et al. (2005), Guiteras (2009) and Schelenker and Roberts (2009).2 In the third section we present a simple conceptual framework that emphasizes the strengths and weaknesses of approaches that rely on interannual variation in temperature and precipitation distributions to identify their effects on farm productivity, as well as guiding its interpretation. The key point is that the approach’s primary limitation is that farmers cannot implement the full range of adaptations in response to a single year’s weather realization whereas they could do so in response to a more permanent change. As such, relying on short-term variation to infer long-run responses may overstate the damage associated with climate change. We make use of detailed...
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