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Assessing the evidence on neighborhood effects from Moving to Opportunity

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  • Dionissi Aliprantis

    () (Federal Reserve Bank of Cleveland)

Abstract

The Moving to Opportunity (MTO) experiment randomly assigned housing vouchers that could be used in low-poverty neighborhoods. Consistent with the literature, I find that receiving an MTO voucher had no effect on outcomes like earnings, employment, and test scores. However, after studying the assumptions identifying neighborhood effects with MTO data, this paper reaches a very different interpretation of these results than found in the literature. I first specify a model in which the absence of effects from the MTO program implies an absence of neighborhood effects. I present theory and evidence against two key assumptions of this model: that poverty is the only determinant of neighborhood quality and that outcomes only change across one threshold of neighborhood quality. I then show that in a more realistic model of neighborhood effects that relaxes these assumptions, the absence of effects from the MTO program is perfectly compatible with the presence of neighborhood effects. This analysis illustrates why the implicit identification strategies used in the literature on MTO can be misleading.

Suggested Citation

  • Dionissi Aliprantis, 2017. "Assessing the evidence on neighborhood effects from Moving to Opportunity," Empirical Economics, Springer, vol. 52(3), pages 925-954, May.
  • Handle: RePEc:spr:empeco:v:52:y:2017:i:3:d:10.1007_s00181-016-1186-1
    DOI: 10.1007/s00181-016-1186-1
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    References listed on IDEAS

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    Cited by:

    1. Dionissi Aliprantis & Daniel R. Carroll & Eric R. Young, 2019. "What Explains Neighborhood Sorting by Income and Race?," Working Papers 201808R, Federal Reserve Bank of Cleveland.
    2. Koki Fusejima, 2020. "Identification of multi-valued treatment effects with unobserved heterogeneity," Papers 2010.04385, arXiv.org, revised Jan 2021.
    3. Dionissi Aliprantis & Hal Martin, 2020. "Neighborhood Sorting Obscures Neighborhood Effects in the Opportunity Atlas," Working Papers 202037, Federal Reserve Bank of Cleveland.

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    More about this item

    Keywords

    Moving to Opportunity; Neighborhood effect; Program effect;
    All these keywords.

    JEL classification:

    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • H50 - Public Economics - - National Government Expenditures and Related Policies - - - General
    • I38 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Government Programs; Provision and Effects of Welfare Programs
    • J10 - Labor and Demographic Economics - - Demographic Economics - - - General
    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General

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