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Cityscape: Volume 23 Number 1 | Regulatory Reform and Affordable Housing


The goal of Cityscape is to bring high-quality original research on housing and community development issues to scholars, government officials, and practitioners. Cityscape is open to all relevant disciplines, including architecture, consumer research, demography, economics, engineering, ethnography, finance, geography, law, planning, political science, public policy, regional science, sociology, statistics, and urban studies.

Cityscape is published three times a year by the Office of Policy Development and Research (PD&R) of the U.S. Department of Housing and Urban Development.

Regulatory Reform and Affordable Housing

Volume 23 Number 1

Mark D. Shroder

Michelle P. Matuga

Measuring Neighborhood Opportunity with Opportunity Atlas and Child Opportunity Index 2.0 Data

Brent D. Mast
Alexander Din
U. S. Department of Housing and Urban Development

The views expressed in this article are those of the author and do not represent the official positions or policies of the Office of Policy Development and Research, the U.S. Department of Housing and Urban Development, or the U.S. Government.

Researchers have recently introduced two datasets measuring neighborhood opportunity: the Harvard University Opportunity Atlas data (Chetty et al., 2018b) and the Brandeis University Child Opportunity Index (COI) 2.0 data (Noelke et al., 2020).

The Opportunity Atlas data measure neighborhood opportunity longitudinally on the basis of children’s outcomes in adulthood for the years 1989 to 2015. The COI 2.0 data measure neighborhood opportunity contemporaneously for the years 2010 and 2015 on the basis of 29 child welfare indicators categorized into three domains: (1) education, (2) health and environment, and (3) social and economic.

In this article we describe the two datasets and present a data analysis example estimating what the Part I crime distribution in Dallas would be if neighborhood opportunity distributions (based on both neighborhood opportunity data sources) in Dallas were more similar to those of Chicago. We adjust for neighborhood opportunity differences between the two cities using the nonparametric propensity score matching technique (Barskey et al., 2002). We conclude that neighborhood opportunity differences explain little of the crime differences between the two cities.

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