住房市场如何利用环境信息?来自中国国家环境空气质量标准的证据

IF 5.2 1区 经济学 Q1 ECONOMICS 中国经济评论 Pub Date : 2024-08-22 DOI:10.1016/j.chieco.2024.102264
Kunlun Wang , Hongjiang Yao
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引用次数: 0

摘要

以往的研究探讨了环境信息对人们在市场中避免污染行为的影响。然而,这些研究得到的实证结果相互矛盾,而且许多研究未能清楚地考察和验证所披露的信息在住房市场中的潜在作用机制。为了弥补这些不足,本研究采用自然实验设计来确定环境信息在住房价格中的作用。利用逐步公开空气质量信息的计划和全面的住房市场数据集,我们发现信息公开使住房价格降低了约 1.7%。这意味着,在项目实施前,人们低估了样本城市当地的空气污染状况。通过对人们对污染的主观感受进行代表性调查,我们的机制分析表明,信息更新是信息影响房价的一个渠道。在进行了多次稳健性检验并排除了其他一些竞争性解释之后,这些结果没有发生变化。
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How environmental information is capitalized into the housing market? Evidence from China's National Ambient Air Quality Standards
Previous studies examined the effects of environmental information on people's pollution avoidance behaviors in the market. However, they obtained contradictory empirical findings and many of them failed to clearly examine and verify the potential mechanisms of how the disclosed information works in the housing market. To address these gaps, this study used a natural experiment design to identify the role of environmental information in housing prices. Exploiting a step-by-step air quality information disclosure program and a comprehensive dataset for housing markets, we found that information disclosure decreased housing prices by around 1.7%. This implies that people underestimated local air pollution in our sample cities before the program. By employing a representative survey of people's subjective perceptions of pollution, our mechanism analyses suggest that information updating serves as a channel through which information influences housing prices. These results are unchanged after conducting several robustness checks and excluding some other competing explanations.
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来源期刊
中国经济评论
中国经济评论 ECONOMICS-
CiteScore
10.60
自引率
4.40%
发文量
380
期刊介绍: The China Economic Review publishes original works of scholarship which add to the knowledge of the economy of China and to economies as a discipline. We seek, in particular, papers dealing with policy, performance and institutional change. Empirical papers normally use a formal model, a data set, and standard statistical techniques. Submissions are subjected to double-blind peer review.
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