Climate Policy Uncertainty and Housing Prices: Analyzing Bidirectional Transmission Across U.S. Metropolitan Areas
気候政策の不確実性と住宅価格：米国大都市圏における双方向伝播の分析 (AI 翻訳)
Sourav Batabyal, Alper Gormus
🤖 gxceed AI 要約
日本語
本研究は、米国の気候政策不確実性（CPU）指数と主要都市圏の住宅価格指数を用い、フーリエ拡張Toda-Yamamoto因果性検定によりCPUと住宅価格の双方向伝播を分析。沿岸部の高曝露市場でCPU感応性が強く、内陸成長市場では住宅価格からCPUへのフィードバックが確認された。CPUは系統的リスク要因として住宅金融監督やマクロプルーデンス政策に統合すべきと示唆する。
English
This study analyzes the bidirectional transmission between climate policy uncertainty (CPU) and housing prices across U.S. metropolitan areas using a Fourier-augmented Toda-Yamamoto causality framework. Findings reveal significant CPU-to-housing price transmission in coastal high-exposure markets, with feedback effects in inland growth markets. The authors argue CPU is a priced systematic risk factor requiring integration into housing finance oversight and macroprudential frameworks.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本では、気候変動リスクが不動産価格に与える影響はSSBJ開示や不動産投資判断で注目が高まっている。本研究成果は、日本の都市部における気候政策不確実性と不動産市場の関係を考察する上で参考になる。ただし、米国特有の市場構造や政策環境を考慮する必要がある。
In the global GX context
This paper contributes to the global literature on climate risk and asset pricing, particularly for real estate. It provides empirical evidence that climate policy uncertainty is a systematic risk factor, relevant for financial stability monitoring and macroprudential policy. The findings are useful for international investors and policymakers assessing climate-related financial risks in housing markets.
👥 読者別の含意
🔬研究者:Provides empirical evidence on climate policy uncertainty as a priced risk factor in housing markets, useful for further research on climate risk and asset pricing.
🏢実務担当者:Highlights the need for real estate investors and lenders to incorporate climate policy uncertainty into risk assessment and portfolio management.
🏛政策担当者:Suggests integrating climate policy uncertainty into macroprudential frameworks and housing finance oversight to enhance financial stability.
📄 Abstract（原文）
This study examines the relationship between climate policy uncertainty (CPU) and residential housing prices across U.S. metropolitan areas using the U.S. CPU index developed by Gavriilidis in 2021 and monthly S&P CoreLogic Case-Shiller Home Price Indices, covering January 1991 to May 2024. Employing a Fourier-augmented Toda–Yamamoto causality framework that accounts for both abrupt and gradual structural breaks, we document significant CPU → housing prices transmission in multiple metropolitan markets, with bidirectional transmission dynamics emerging in Los Angeles, New York, San Diego, and San Francisco, as well as at the U.S. national level. The results reveal substantial spatial heterogeneity across various market types. Coastal high-exposure markets exhibit strong CPU sensitivity, which may reflect the influence of physical climate risks and regulatory uncertainty; inland growth markets display housing prices → CPU feedback, likely operating through political economy channels; Midwest extreme-weather markets show persistent transmission despite their non-coastal locations; recession-sensitive markets become CPU-responsive following the Great Recession; and insulated markets show no significant transmission. The findings indicate that CPU operates as a priced systematic risk factor requiring integration into housing finance oversight, macroprudential frameworks, and investment strategies. These results have important implications for financial stability monitoring, mortgage credit risk assessment, and climate policy design as markets navigate transition risks in a low-carbon economy.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.3390/risks14050114first seen 2026-06-29 08:50:33 · last seen 2026-08-02 06:30:06
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