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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, Beirut, 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

We analyse 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 over the period 2nd August, 2007 to 29th November, 2019. To this end, we apply a nonparametric causality-in-quantiles test not only to uncover potential predictability in the entire conditional distribution of housing returns and volatility but also to account for nonlinearity and structural breaks which exist between housing returns and climate risk factors. We find that climate risk factors (and the associated uncertainty) do predict housing returns and volatility across the conditional distribution. These results are robust to alternative daily data of aggregate housing prices for the US and ten major metropolitan statistical areas (MSAs). Insights from our findings can benefit academics, investors, and policymakers in their decision-making.

Suggested Citation

  • Elie Bouri & Rangan Gupta & Hardik A. Marfatia & Jacobus Nel, 2022. "Do Climate Risks Predict US Housing Returns and Volatility? Evidence from a Quantiles-Based Approach," Working Papers 202240, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:202240
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Physical and transitional climate risks; US housing returns and volatility; higher-order nonparametric causality-in-quantiles test; natural disasters and global warming; US climate policy and international summits;
    All these keywords.

    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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