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Sufficient statistics for climate change counterfactuals

Author

Listed:
  • Mérel, Pierre
  • Paroissien, Emmanuel
  • Gammans, Matthew

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

  • Mérel, Pierre & Paroissien, Emmanuel & Gammans, Matthew, 2024. "Sufficient statistics for climate change counterfactuals," Journal of Environmental Economics and Management, Elsevier, vol. 124(C).
    • Handle: RePEc:eee:jeeman:v:124:y:2024:i:c:s0095069624000147
    DOI: 10.1016/j.jeem.2024.102940
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    More about this item

    Keywords

    Climate change; Climate adaptation; Sufficient statistic; Weather;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • Q16 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - R&D; Agricultural Technology; Biofuels; Agricultural Extension Services
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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