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Sufficient statistics for climate change counterfactuals

Author

Listed:
  • Pierre Mérel

    (University of California, Department of Agricultural and Resource Economics - UC Davis - University of California [Davis] - UC - University of California)

  • Emmanuel Paroissien

    (UMR PSAE - Paris-Saclay Applied Economics - AgroParisTech - Université Paris-Saclay - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

  • Matthew Gammans

    (Agricultural, Food, and Resource Economics - Michigan State University)

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.

Suggested Citation

  • Pierre Mérel & Emmanuel Paroissien & Matthew Gammans, 2024. "Sufficient statistics for climate change counterfactuals," Post-Print hal-04498651, HAL.
    • Handle: RePEc:hal:journl:hal-04498651
    DOI: 10.1016/j.jeem.2024.102940
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    Cited by:

    1. François Bareille & Raja Chakir & Derya Keles, 2024. "Weather shocks and pesticide purchases," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 51(2), pages 309-353.

    More about this item

    Keywords

    Climate adaptation; Sufficient statistic;

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