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Can Propensity Score Analysis Replicate Estimates Based on Random Assignment in Evaluations of School Choice? A Within-Study Comparison



The ability of propensity score analysis (PSA) to match impact estimates derived from random assignment (RA) is examined using data from the evaluation of two interdistrict magnet schools. As in previous within study comparisons, the estimates provided by PSA and RA differ substantially when PSA is implemented using comparison groups that are not similar to the treatment group and without pretreatment measures of academic performance. Adding pretreatment measures of the performance to the PSA, however, substantially improves the match between PSA and RA estimates. Although the results should not be generalized too readily, they suggest that nonexperimental estimators can, in some circumstances, provide valid estimates of the causal impact of school choice programs.

Suggested Citation

  • Robert Bifulco, 2010. "Can Propensity Score Analysis Replicate Estimates Based on Random Assignment in Evaluations of School Choice? A Within-Study Comparison," Center for Policy Research Working Papers 124, Center for Policy Research, Maxwell School, Syracuse University.
  • Handle: RePEc:max:cprwps:124

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    References listed on IDEAS

    1. Elizabeth Ty Wilde & Robinson Hollister, 2007. "How close is close enough? Evaluating propensity score matching using data from a class size reduction experiment," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 26(3), pages 455-477.
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    Cited by:

    1. Ron Zimmer & Brian Gill & Jonathon Attridge & Kaitlin Obenauf, 2014. "Charter School Authorizers and Student Achievement," Education Finance and Policy, MIT Press, vol. 9(1), pages 59-85, January.
    2. Ron Zimmer & Brian Gill & Jonathon Attridge & Kaitlin Obenauf, 2013. "Charter School Authorizers and Student Achievement (Journal Article)," Mathematica Policy Research Reports 6e4664294f7341868c9a78142, Mathematica Policy Research.

    More about this item


    Nonexperimental; quasi-experimental; propensity score analysis; design replication; school choice.;

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • C90 - Mathematical and Quantitative Methods - - Design of Experiments - - - General
    • I28 - Health, Education, and Welfare - - Education - - - Government Policy

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