Title

Beyond Treatment Effects: Estimating the Relationship Between Neighborhood Poverty and Individual Outcomes in the MTO Experiment

Author(s)

Jeffrey B. Liebman Jeffrey Liebman (Harvard University and NBER)

Lawrence F. Katz Lawrence Katz (Harvard University and NBER)

Jeffrey R. Kling Jeffrey Kling (Princeton University and NBER)

Abstract

Several important social science literatures hinge on the functional relationship between neighborhood characteristics and individual outcomes. Although there have been numerous non-experimental estimates of these relationships, there are serious concerns about their reliability because individuals self-select into neighborhoods. This paper uses data from HUD's Moving to Opportunity (MTO) randomized housing voucher experiment to estimate the relationship between neighborhood poverty and individual outcomes using experimental variation. In addition, it assesses the reliability of non-experimental estimates by comparing them to experimental estimates. We find that our method for using experimental variation to estimate the relationship between neighborhood poverty and individual outcomes - instrumenting for neighborhood poverty with site-by-treatment group interactions - produces precise estimates in models in which poverty enters linearly. Our estimates of nonlinear and threshold models are not precise enough to be conclusive, though many of our point estimates suggest little, if any, deviation from linearity. Our non-experimental estimates are inconsistent with our experimental estimates, suggesting that non-experimental estimates are not reliable. Moreover, the selection pattern that reconciles the experimental and non-experimental results is complex, suggesting that common assumptions about the direction of bias in non-experimental estimates may be incorrect.

Creation Date

2004-08

Section URL ID

IRS

Paper Number

493

URL

https://dataspace.princeton.edu/bitstream/88435/dsp01g158bh29k/1/493.pdf

File Function

Jel

N32, N33, N34

Keyword(s)

neighborhood effects, social experiments

Suppress

false

Series

1