使用显示偏好衡量住房质量：一种地理 PageRank 方法
Measuring Housing Quality Using Revealed Preference: A Geographic PageRank Approach
NBER Working Papers · 2026 · [{"name": "Alex Bell", "affiliation": []}, {"name": "Sophie Calder-Wang", "affiliation": []}, {"name": "Shusheng Zhong", "affiliation": []}]
中文摘要
本文提出地理 PageRank（Geographic PageRank, GPR），这是一种基于迁移决策的创新性地方质量衡量指标，采用递归算法，充分利用迁移流的完整网络。利用多种公共数据来源，我们构建了美国各县及都市区的 GPR 排名。我们还将该排名扩展，以捕捉其随时间的变化以及不同人口子群体间的差异，提供了一种用途广泛的数据产品。作为一项应用，我们表明，在为环境舒适度定价时，GPR 可作为未观测住房质量的“反工具变量”，从而恢复出符号正确、且与准实验基准相符的空气污染隐含价格。
Abstract
This paper introduces Geographic PageRank (GPR), an innovative measure of place quality that is based on migration decisions, employing a recursive algorithm that leverages the full network of migration flows. Using various public data sources, we construct GPR rankings for U.S. counties and metropolitan areas. We also extend the rankings to capture changes over time and differences for population subgroups, providing a versatile data product. As an application, we show that GPR can serve as an "anti-instrument'' for unobserved housing quality when pricing environmental amenities, recovering a correctly signed implicit price of air pollution that is in line with quasi-experimental benchmarks.