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Program Monitoring and Research Division Working Paper Series


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Posted Date:   
August 26, 2009



Measuring Neighborhood Quality with AHS and CSS Data: A Bayesian Approach by Brent D. Mast.

While neighborhood quality is important for public policy, it is also difficult to quantify. This study measures neighborhood quality using data from two sources: the 2002 American Housing Survey (AHS), and HUD’s Customer Satisfaction Survey (CSS) of Section 8 Housing Choice Voucher Program (HCVP) households. Survey responses are analyzed regarding neighborhood quality, home quality, and crime perceptions. Tract level Bayesian estimates are computed using AHS metro level data and CSS census tract data.

Compared to estimates solely based on CSS data, the Bayesian estimates have fewer outliers. Bayesian analysis also allows for estimation for tracts with lower sample sizes than would be practical using only CSS data. The Bayesian estimates tend to correlate more strongly with these auxiliary variables, and the differences are more apparent for tracts with larger differences between the CSS and Bayesian estimates.

Program Monitoring and Research Division Working Papers



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