The Long Run Consequences of Neighborhood Revitalization Efforts

About This Grant

This award funds a research project that uses existing administrative records to understand the long-term impacts of neighborhood revitalization policies on individual and family economic outcomes. Government interventions that reshape neighborhoods may have profound and lasting effects on residents' economic mobility and well-being. While prior research has studied the effects of these projects on local economies and property values, very little is known about what happened to the families displaced by neighborhood revitalization over decades. By linking historical Census records with modern administrative data, the researchers employ Large Language Models (Artificial Intelligence) to systematically analyze and classify thousands of original source documents, including newspaper articles, project reports, and archival records, enabling systematic extraction of information. The researchers analyze how government policies affected multiple aspects of family well-being including health, labor market outcomes, housing quality, and geographic mobility. Understanding the long- run consequences of economic development policies serves the national interest by providing evidence to guide place-based policies at federal, state, and local levels that affect millions of urban and rural American families. Ultimately, the research findings could help the United States develop infrastructure investment designs and improve citizens’ wellbeing. This award funds a research project providing new evidence on the long-run economic consequences of large-scale displacement and makes three primary contributions to economic science. First, the project develops a comprehensive new database of federal government project boundaries and timing through systematic collection and digitization of archival records, addressing critical measurement gaps in existing data sources. Second, it generates unique longitudinal data by linking public and restricted Census microdata across multiple decades, enabling rigorous analysis of how residential displacement shapes long-term economic trajectories. Third, it leverages historical variation in project implementation and local policy contexts to provide a robust empirical setting for analyzing long-run outcomes. The empirical analysis is divided into three interconnected sub-projects: (1) database construction using federal archives, municipal records, and historical newspapers with Large Language Models used to automate summarizing and classifying diverse textual sources, including newspaper coverage, government project reports, documents from national, state, and local archives; (2) analysis of long-run migration and mortality outcomes for those who lived in or near affected areas, using publicly available data; and (3) examination of long-run outcomes using restricted Census data. This research advances several areas of economic science. In regional economics, it provides the first comprehensive analysis of how federal initiatives transformed neighborhoods and affected families over multiple decades, contributing to debates about neighborhood effects and place-based policies. In labor economics, it demonstrates how housing and neighborhood disruption affect individual economic mobility over the long term. The validated database becomes a public resource enabling future research across multiple disciplines. The findings have potential to inform discussions about urban development, infrastructure investment, and displacement mitigation strategies by providing evidence on whether the effects of neighborhood-level interventions persist across decades. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.