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

Elie Bouri (), Rangan Gupta, Hardik Marfatia () and Jacobus Nel ()
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Elie Bouri: School of Business, Lebanese American University, Beirut, Lebanon
Hardik 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

No 202240, Working Papers from University of Pretoria, Department of Economics

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.

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 (search for similar items in EconPapers)
JEL-codes: C22 C32 Q54 R30 (search for similar items in EconPapers)
Pages: 22 pages
Date: 2022-09
New Economics Papers: this item is included in nep-ene, nep-env, nep-fmk, nep-rmg and nep-ure
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