From City Proxies to Legal Entities: How Measurement Choices Change Climate-risk Inference in Chinese Corporate Bonds

Abstract

Empirical climate-finance results often travel from geographic proxies to firm-level claims without a direct audit of what changes during that transport. This paper conducts such an audit for Chinese corporate bonds. Its starting point is a deliberately constructed twelve-city diagnostic, not a bondpricing estimate: 2024 weather indicators and assigned credit categories generate a positive association with a rating-implied three-year coupon. The design is then transported to a frozen universe of 1,468 Chinese interbank medium-term notes issued by 165 listed legal entities during 2010–2025. Four bridges are examined separately: geographic support and aggregation, constructed versus observed outcomes, benchmark-yield decomposition, and weather-source completeness. Under harmonized outcomes and exposures, city-year, issuer-year, and bond-level estimates are all negative and statistically indistinguishable from zero. In the five-city common-support sample, the observed-coupon coefficient is statistically detectable under restricted wild-cluster inference (p=0.0225), whereas the corresponding issue-premium estimate is only marginal (p=0.0710). Complete ERA5 temperature data preserve a positive association inside the prototype. Separately, a literal city-specific all-day precipitation-percentile count has no cross-city variation under complete daily coverage. The evidence shows that the prototype and full-sample results are not contradictory: they answer different estimands. City proxies are useful diagnostic devices, but their coefficients should not be transported as legal-entity bond-pricing estimates without explicit outcome, support, and data-source bridges.

Author abstract from the research manuscript. Typography and line breaks have been normalized; the linked source may show a different manuscript version.