2020
DOI: 10.1162/rest_a_00933
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Evidence of Neighborhood Effects from Moving to Opportunity: LATEs of Neighborhood Quality

Abstract: This paper estimates neighborhood effects on adult labor market outcomes using the Moving to Opportunity (MTO) housing mobility experiment. We propose and implement a new strategy for identifying transition-specific effects that exploits identification of the unobserved component of a neighborhood choice model. Estimated Local Average Treatment Effects (LATEs) are large, result from moves between the first and second deciles of the national distribution of neighborhood quality, and pertain to a subpopulation o… Show more

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Cited by 35 publications
(34 citation statements)
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“…One set of policies along these lines would aim to equalize opportunity within public education, since pre-market factors influenced by education are strong predictors of wages and employment (Neal and Johnson (1996), Keane and Wolpin (1997)). Additional policies likely to improve the relative labor market outcomes of African Americans would address incarceration (Neal and Rick (2014)), discrimination in the labor market (Bertrand and Mullainathan (2004), Nunley et al 2015), labor market attachment (Ritter and Taylor (2011), Daly et al (2019)), and persistent residential segregation (Aliprantis and Richter (2019), Chetty et al (2016), Bayer et al (2008)).…”
Section: Resultsmentioning
confidence: 99%
“…One set of policies along these lines would aim to equalize opportunity within public education, since pre-market factors influenced by education are strong predictors of wages and employment (Neal and Johnson (1996), Keane and Wolpin (1997)). Additional policies likely to improve the relative labor market outcomes of African Americans would address incarceration (Neal and Rick (2014)), discrimination in the labor market (Bertrand and Mullainathan (2004), Nunley et al 2015), labor market attachment (Ritter and Taylor (2011), Daly et al (2019)), and persistent residential segregation (Aliprantis and Richter (2019), Chetty et al (2016), Bayer et al (2008)).…”
Section: Resultsmentioning
confidence: 99%
“…Following Aliprantis and Richter (2019), we define neighborhood quality in terms of a neighborhood's poverty rate, employment to population ratio, unemployment rate, high school attainment rate, BA attainment rate, and the share of households with children under 18 that are singleheaded. We measure these variables in terms of the percentiles of their national distributions, and then define neighborhood quality as the percentile of the first principal component of these variables.…”
Section: Datamentioning
confidence: 99%
“…To characterize neighborhoods, we use tract-level data from the 2012-2016 American Community Survey (ACS). We follow Aliprantis and Richter (2018) and measure neighborhood quality as the first principal component of the poverty rate, the unemployment rate, the employed to population ratio, the share with a HS diploma, the share with a BA, and the share of families with children under 18 that are single-headed. Each of these variables is first put into percentiles of the national distribution (in terms of population living in census tracts with these characteristics).…”
Section: Hud and Census Datamentioning
confidence: 99%