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Long-term Effects of Temperature Variations on Economic Growth: A Machine Learning Approach

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  • Eugene Kharitonov
  • Oksana Zakharchuk
  • Lin Mei

Abstract

This study investigates the long-term effects of temperature variations on economic growth using a data-driven approach. Leveraging machine learning techniques, we analyze global land surface temperature data from Berkeley Earth and economic indicators, including GDP and population data, from the World Bank. Our analysis reveals a significant relationship between average temperature and GDP growth, suggesting that climate variations can substantially impact economic performance. This research underscores the importance of incorporating climate factors into economic planning and policymaking, and it demonstrates the utility of machine learning in uncovering complex relationships in climate-economy studies.

Suggested Citation

  • Eugene Kharitonov & Oksana Zakharchuk & Lin Mei, 2023. "Long-term Effects of Temperature Variations on Economic Growth: A Machine Learning Approach," Papers 2308.06265, arXiv.org.
  • Handle: RePEc:arx:papers:2308.06265
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    1. Nordhaus, William D, 1991. "To Slow or Not to Slow: The Economics of the Greenhouse Effect," Economic Journal, Royal Economic Society, vol. 101(407), pages 920-937, July.
    2. Marshall Burke & Solomon M. Hsiang & Edward Miguel, 2015. "Global non-linear effect of temperature on economic production," Nature, Nature, vol. 527(7577), pages 235-239, November.
    3. Melissa Dell & Benjamin F. Jones & Benjamin A. Olken, 2012. "Temperature Shocks and Economic Growth: Evidence from the Last Half Century," American Economic Journal: Macroeconomics, American Economic Association, vol. 4(3), pages 66-95, July.
    4. Stern, David I., 2004. "The Rise and Fall of the Environmental Kuznets Curve," World Development, Elsevier, vol. 32(8), pages 1419-1439, August.
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