Data and code from: The impact of light-rail stations on income sorting in US urban areas

The impact of public transit (PT) on income sorting in U.S. cities has long been debated. Theory suggests that richer households may cluster near PT stations to minimize commute time – or avoid them in favor of more convenient automobile commuting. The equilibrium depends on factors such as PT speed relative to cars and the income gap between rich and poor households. Empirical evidence supports both possibilities, but prior multi-city studies suffer from identification flaws. Using data from 21 U.S. light-rail (LR) systems built or expanded since 1991, this study estimates the effect of new LR stations on nearby neighborhood incomes. My event-study design improves upon earlier work by constructing controls that match pre-treatment conditions and trends in treated station areas and by correcting for the bias that staggered treatment timing can introduce to event study estimates. Across the pooled sample, there is little evidence that new LR stations make surrounding neighborhoods poorer..., , This README.txt file was generated on 2025-10-04 by Erik Nelson.

GENERAL INFORMATION

1. Title of Dataset: The impact of light-rail stations on income sorting in US urban areas.
2. Author Information
Name: Erik Nelson
Institution: Bowdoin College
Address: 9700 College Station
Brunswick, ME 04011-8497.
Email: [[e-mail]](mailto:[e-mail])

The Stata .do files in this depository generate the results that are plotted or presented in table format in the paper \"The impact of light-rail stations on income sorting in US urban areas.\" All .do files load the needed datasets. All datasets are .xlsx format. Each Excel file contains data for the urban area that is part of the file's name. The data in each Excel file is in panel form. Each observation in a dataset represents a treated or control area i in urban area u in year t. We observe each area i's average nominal per capita and median HH income in year t = 1990, 2000, 2010, 2017, 2019, 2021, and 2022 (thes...,