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Do Climate Risks Predict US Housing Returns and Volatility? Evidence from a Quantiles-Based Approach

Author

Listed:
  • Elie Bouri

    (School of Business, Lebanese American University, Byblos, Lebanon)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa)

  • Hardik A. Marfatia

    (Department of Economics, Northeastern Illinois University, BBH 344G, 5500 N. St. Louis Avenue, Chicago, IL 60625, USA)

  • Jacobus Nel

    (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa)

Abstract

This paper analyzes the ability of textual-analysis-based daily proxies of physical (natural disasters and global warming) and transition (US climate policy and international summits) climate risks to predict daily movements in the US housing market in the entire conditional distribution of housing returns and volatility. Using data for the period 2 August 2007 to 29 November 2019, a nonparametric causality-in-quantiles test is used, accounting for nonlinearity and structural breaks between housing returns and climate risk factors. The Granger causality analysis shows that climate risk factors (and the associated uncertainty) predict housing returns and volatility across the entire conditional distribution. These results are robust to alternative daily data of aggregate housing prices for the US and 10 major metropolitan statistical areas. Insights from our findings are beneficial for the decision-making of investors, policymakers and the academic research community.

Suggested Citation

  • Elie Bouri & Rangan Gupta & Hardik A. Marfatia & Jacobus Nel, 2025. "Do Climate Risks Predict US Housing Returns and Volatility? Evidence from a Quantiles-Based Approach," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 20(01), pages 1-21, March.
    • Handle: RePEc:wsi:afexxx:v:20:y:2025:i:01:n:s2010495225500046
    DOI: 10.1142/S2010495225500046
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    Keywords

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    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • R30 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - General

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