Department of Land, Air and Water Resources, University of California, Davis, One Shields Ave, Davis, CA 95616, USA.
Department of Civil and Environmental Engineering, University of Maryland, 1173 Glenn Martin Hall, College Park, MD 20742, USA.
Int J Environ Res Public Health. 2021 Nov 20;18(22):12195. doi: 10.3390/ijerph182212195.
In this paper we examine the effects of localized air pollution measurements on the housing prices in Oakland, CA. With high-resolution air pollution measurements for NO, NO, and BC, we can assess the ambient air quality on a parcel-by-parcel basis within the study domain. We combine a spatial lag model with an instrumental variable method to consider both the spatial autocorrelation and endogeneity effects between housing prices and air pollution concentrations. To the best of our knowledge, this is the first work in this field that combines both spatial autocorrelation and endogeneity effects in one model with accurate air pollution concentration measurements for each individual parcel. We found a positive spatial autocorrelation with housing prices using Moral's I (value of 0.276) with the total sample number of 26,386. Somewhat surprisingly, we found a positive relationship between air pollution and housing prices. There are several possible explanations for this finding. Homeowners in high demand, low-stock housing areas, such as our study, may be insensitive to air pollution when the overall ambient air quality is relatively good. It is also possible that under clean air conditions, low variability in pollutant concentrations has little effect on property values. These hypotheses could be verified with more high-resolution air pollution measurements with a diversity of regions.
本文研究了加利福尼亚州奥克兰市局部空气污染测量对房价的影响。我们利用高分辨率的 NO、NO 和 BC 空气污染测量数据，可以在研究区域内逐块评估环境空气质量。我们结合空间滞后模型和工具变量方法，考虑了房价和空气污染浓度之间的空间自相关和内生性效应。据我们所知，这是第一个在一个模型中同时考虑空间自相关和内生性效应，并对每个单独的地块进行精确空气污染浓度测量的相关研究。我们使用莫尔尔 I （I 值为 0.276）对 26386 个总样本数量进行分析，发现房价存在正的空间自相关。有些令人惊讶的是，我们发现空气污染与房价之间存在正相关关系。对于这一发现，有几种可能的解释。在像我们这样的研究中，高需求、低库存住房地区的房主可能对整体环境空气质量相对较好时的空气污染不敏感。也有可能在清洁空气条件下，污染物浓度的低可变性对房地产价值影响不大。这些假设可以通过在更多不同地区进行更高分辨率的空气污染测量来验证。
