Sufficient statistics for climate change counterfactuals

Pierre Mérel, Emmanuel Paroissien and Matthew Gammans

Journal of Environmental Economics and Management, 2024, vol. 124, issue C

Abstract: Recent years have seen a growing interest among empiricists in exploiting random weather fluctuations to identify climate change impacts, yet a clear understanding of the conditions under which short-run weather effects can reveal long-run climatic impacts is lacking. We derive necessary and sufficient conditions for weather fluctuations to systematically identify the marginal effect of climate on an economic outcome. Under these conditions, empirical estimates of local marginal weather effects flexibly trace out a common long-run response function to climate that can be used for non-marginal climate change counterfactuals. Our application considers the effect of weather on county-level agricultural GDP in the United States. Depending on model specification, agricultural GDP is predicted to decrease by 6%–10% under a 2 °C warming scenario.

Keywords: Climate change; Climate adaptation; Sufficient statistic; Weather (search for similar items in EconPapers)
JEL-codes: C23 Q16 Q54 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jeeman:v:124:y:2024:i:c:s0095069624000147

DOI: 10.1016/j.jeem.2024.102940

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