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Climate policy uncertainty and its impact on real estate market dynamics: A sectoral and regional analysis

Author

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  • Chulyoung Cho
  • Jinseok Yang
  • Beakcheol Jang

Abstract

This study explores the impact of Climate Policy Uncertainty (CPU) on real estate market volatility, utilizing the CPU index to assess how climate policy affects various real estate segments. It highlights the significant impact of CPU on sectors with high energy demand and emissions, such as industrial and residential. A multi-horizon analysis reveals the long-term sensitivity of CPU’s influence, with significant sensitivity noted in coastal regions prone to climate risks. The findings provide crucial insights for investors and policymakers, emphasizing the importance of integrating CPU considerations into strategic decision-making for real estate investment.

Suggested Citation

  • Chulyoung Cho & Jinseok Yang & Beakcheol Jang, 2024. "Climate policy uncertainty and its impact on real estate market dynamics: A sectoral and regional analysis," PLOS ONE, Public Library of Science, vol. 19(10), pages 1-15, October.
    • Handle: RePEc:plo:pone00:0311688
    DOI: 10.1371/journal.pone.0311688
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    References listed on IDEAS

    as
    1. Barrage, Lint & Furst, Jacob, 2019. "Housing investment, sea level rise, and climate change beliefs," Economics Letters, Elsevier, vol. 177(C), pages 105-108.
    2. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    3. Tashman, Leonard J., 2000. "Out-of-sample tests of forecasting accuracy: an analysis and review," International Journal of Forecasting, Elsevier, vol. 16(4), pages 437-450.
    4. Emanuele Campiglio & Yannis Dafermos & Pierre Monnin & Josh Ryan-Collins & Guido Schotten & Misa Tanaka, 2018. "Climate change challenges for central banks and financial regulators," Nature Climate Change, Nature, vol. 8(6), pages 462-468, June.
    5. Vinod Thomas & Ramón López, 2015. "Global Increase in Climated-Related Disasters," ADB Economics Working Paper Series 466, Asian Development Bank.
    6. Lv, Wendai & Li, Bin, 2023. "Climate policy uncertainty and stock market volatility: Evidence from different sectors," Finance Research Letters, Elsevier, vol. 51(C).
    7. Cheung, Yin-Wong & Lai, Kon S, 1995. "Lag Order and Critical Values of the Augmented Dickey-Fuller Test," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 277-280, July.
    8. Bouri, Elie & Iqbal, Najaf & Klein, Tony, 2022. "Climate policy uncertainty and the price dynamics of green and brown energy stocks," Finance Research Letters, Elsevier, vol. 47(PB).
    9. Stephen Roulac, 1996. "Real Estate Market Cycles, Transformation Forces and Structural Change," Journal of Real Estate Portfolio Management, Taylor & Francis Journals, vol. 2(1), pages 1-17, January.
    10. He, Mengxi & Zhang, Yaojie, 2022. "Climate policy uncertainty and the stock return predictability of the oil industry," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    11. Markus Baldauf & Lorenzo Garlappi & Constantine Yannelis & José Scheinkman, 2020. "Does Climate Change Affect Real Estate Prices? Only If You Believe In It," The Review of Financial Studies, Society for Financial Studies, vol. 33(3), pages 1256-1295.
    12. Joshua J. Thompson & Robert L. Wilby & John K. Hillier & Richenda Connell & Geoffrey R. Saville, 2023. "Climate Gentrification: Valuing Perceived Climate Risks in Property Prices," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 113(5), pages 1092-1111, May.
    13. John Y. Campbell & Samuel B. Thompson, 2008. "Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1509-1531, July.
    14. Justin Tyndall, 2023. "Sea Level Rise and Home Prices: Evidence from Long Island," The Journal of Real Estate Finance and Economics, Springer, vol. 67(4), pages 579-605, November.
    15. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
    16. Raza, Syed Ali & Khan, Komal Akram, 2024. "Climate policy uncertainty and its relationship with precious metals price volatility: Comparative analysis pre and during COVID-19," Resources Policy, Elsevier, vol. 88(C).
    17. Harvey, David & Leybourne, Stephen & Newbold, Paul, 1997. "Testing the equality of prediction mean squared errors," International Journal of Forecasting, Elsevier, vol. 13(2), pages 281-291, June.
    18. Liang, Chao & Umar, Muhammad & Ma, Feng & Huynh, Toan L.D., 2022. "Climate policy uncertainty and world renewable energy index volatility forecasting," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    19. Ren, Xiaohang & Zhang, Xiao & Yan, Cheng & Gozgor, Giray, 2022. "Climate policy uncertainty and firm-level total factor productivity: Evidence from China," Energy Economics, Elsevier, vol. 113(C).
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    1. Donia Besher & Anirban Sengupta & Tanujit Chakraborty, 2025. "Probabilistic Forecasting of Climate Policy Uncertainty: The Role of Macro-financial Variables and Google Search Data," Papers 2507.12276, arXiv.org, revised Jan 2026.

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