Innovative Rental Market and Neighborhood Data

Session Submission Type: Panel

Abstract

This panel brings together three innovative projects that leverage high-frequency, spatially granular data to advance research and policy understanding of rental markets and neighborhood change. Christina Stacy and colleagues introduce the Neighborhood Rental Database (NeRD), a novel data infrastructure that uses real-time web scraping of rental listings to construct timely, neighborhood-level measures of rents, availability, and unit characteristics. By moving beyond traditional data sources that are often lagged or aggregated, NeRD enables researchers and policymakers to track rental market dynamics as they unfold and to better understand how supply, pricing, and affordability vary across neighborhoods and over time.Complementing this work, Schuylar and colleagues provide new evidence on the role of rent stabilization as a key housing policy in high-cost markets, focusing on New York City. Drawing on longitudinal data from the Poverty Tracker, they examine the extent to which rent-stabilized housing supports tenants facing overlapping forms of disadvantage, including poverty, material hardship, and health challenges. Their analysis finds that rent stabilization functions as a meaningful anti-poverty tool—reducing the Supplemental Poverty Measure rate by approximately 9 percentage points annually—while also documenting that many rent-stabilized tenants continue to experience significant financial strain. By highlighting both the benefits and limitations of rent stabilization, this work underscores the importance of pairing tenant protections with additional supports to improve housing stability and well-being.

Finally, Yung Chun and Xueying Mei demonstrate how high-resolution data can be applied to rigorously evaluate place-based policies, focusing on the St. Louis Choice Neighborhoods Initiative. Utilizing a novel "TWDeConv" framework to recover annual tract-level signals from 5-year ACS aggregates, they implement a Synthetic Control Method to isolate the year-over-year impacts of federal housing interventions on neighborhood racial composition and economic resilience. This methodological innovation transforms the ACS into a dynamic signal recovery system, allowing for the detection of rapid neighborhood shifts and "gentrification spikes" that are typically masked by standard data products.
Together, these papers illustrate the growing potential of combining novel data infrastructure, rigorous policy analysis, and tenant-centered evidence to deepen our understanding of housing markets and neighborhood change. By integrating real-time rental data, longitudinal survey insights on housing stability, and innovative methods to extract dynamic signals from traditionally lagged datasets, the panel highlights how different data sources and approaches can complement one another. Collectively, this work provides a more complete picture of how housing policies shape affordability, opportunity, and well-being, and points toward more responsive, evidence-based policymaking in rapidly evolving housing markets.

Policy Area

• Housing, Community Development, and Urban Policy

Chair

• Daniel C Teles, Urban Institute

Discussants

• Warren Robert Lowell, Vanderbilt University

• Stephanie Casey Pierce, University of Tennessee (Knoxville)

Organizer

• Christina Plerhoples Stacy, Urban Institute

Individual Presentations

• Real-Time Rental Data Scraping and Analysis for Policy and Research: The Neighborhood Rental Database (NeRD) - Presenting Author: Christina Plerhoples Stacy, Urban Institute

• Unmasking Inequality in Real-Time: Examining the St. Louis Choice Neighborhoods Initiative using High Resolution Data - Presenting Author: Yung Chun, Washington University in St. Louis

• A Portrait of Rent Stabilization in New York City using Data from the Poverty Tracker - Presenting Author: Schuyler Ross, Columbia University; Non-Presenting Co-Author: Daniel Salgado, Columbia University

• Measuring Renters in Credit Data: Evidence from Linked Survey and Administrative Data - Presenting Author: Erin Troland, Federal Reserve Board