Disclosing pollution: causal impacts of key emission unit listings on Shanghai's housing market

Abstract We provide causal estimates of the effect of Shanghai's key emission unit listings on nearby housing prices. Implemented in 2016, the disclosure policy requires annual public disclosure of designated polluting firms and their pollution information. Using repeated cross-sectional data on Shanghai housing transactions from 2015 to 2022, we apply a heterogeneity-robust staggered difference-in-differences estimator to identify dynamic capitalization effects while addressing treatment heterogeneity, treatment reversibility and time-invariant omitted variables. We find that each additional disclosed key emission unit within 1,000 m reduces nearby housing prices by 1.31 per cent, with larger declines for suburban properties than for properties in the urban core. By examining ongoing industrial pollution under a unified disclosure framework, our findings extend prior U.S. and Chinese studies that focus on legacy contamination or specific pollutants. The results highlight the policy relevance of pollution transparency and inform China's nationwide implementation.

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Publication Details

Journal
Environment and Development Economics
Published
2026-10-06
DOI
https://doi.org/10.1017/s1355770x26100771
Primary Topic
Housing Market and Economics
Type
article
Field-Weighted Citation Impact
0.00
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article

Disclosing pollution: causal impacts of key emission unit listings on Shanghai's housing market

H. Allen Klaiber, Jingke Wu
Environment and Development Economics
Housing Market and Economics
article

Disclosing pollution: causal impacts of key emission unit listings on Shanghai's housing market

H. Allen Klaiber, Jingke Wu
article en

Abstract

Abstract We provide causal estimates of the effect of Shanghai's key emission unit listings on nearby housing prices. Implemented in 2016, the disclosure policy requires annual public disclosure of designated polluting firms and their pollution information. Using repeated cross-sectional data on Shanghai housing transactions from 2015 to 2022, we apply a heterogeneity-robust staggered difference-in-differences estimator to identify dynamic capitalization effects while addressing treatment heterogeneity, treatment reversibility and time-invariant omitted variables. We find that each additional disclosed key emission unit within 1,000 m reduces nearby housing prices by 1.31 per cent, with larger declines for suburban properties than for properties in the urban core. By examining ongoing industrial pollution under a unified disclosure framework, our findings extend prior U.S. and Chinese studies that focus on legacy contamination or specific pollutants. The results highlight the policy relevance of pollution transparency and inform China's nationwide implementation.

Environment and Development Economics
The Ohio State University (US)
Openalex Percentile: Top 7%
Housing Market and Economics
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