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Using Nonexperimental Methods to Address Noncompliance

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  • Daniel Litwok

    (Abt Associates)

Abstract

The analysis compares estimates of the incremental impact for those who receive HPOG with a program enhancement to the standard HPOG program. The experimental benchmark for the incremental impact comes from two-stage least squares with random assignment as an instrumental variable for enhancement take-up. Then, ignoring the randomly assigned conditions, the analysis estimates the counterfactual for those who “take up” the enhancement using ordinary least squares and inverse propensity weighting. The analysis also tests whether adding information that is only available due to the experiment—who complied with their randomization status and who did not—improves the nonexperimental estimates. The analysis compares these estimates using statistical tests recommended by the within-study comparison literature.

Suggested Citation

  • Daniel Litwok, 2020. "Using Nonexperimental Methods to Address Noncompliance," Upjohn Working Papers 20-324, W.E. Upjohn Institute for Employment Research.
  • Handle: RePEc:upj:weupjo:20-324
    as

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    References listed on IDEAS

    as
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    6. Charles Michalopoulos & Howard S. Bloom & Carolyn J. Hill, 2004. "Can Propensity-Score Methods Match the Findings from a Random Assignment Evaluation of Mandatory Welfare-to-Work Programs?," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 156-179, February.
    7. repec:mpr:mprres:3694 is not listed on IDEAS
    8. James Heckman & Hidehiko Ichimura & Jeffrey Smith & Petra Todd, 1998. "Characterizing Selection Bias Using Experimental Data," Econometrica, Econometric Society, vol. 66(5), pages 1017-1098, September.
    9. Atila Abdulkadiroğlu & Joshua D. Angrist & Susan M. Dynarski & Thomas J. Kane & Parag A. Pathak, 2011. "Accountability and Flexibility in Public Schools: Evidence from Boston's Charters And Pilots," The Quarterly Journal of Economics, Oxford University Press, vol. 126(2), pages 699-748.
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Treatment effects; Experimental methods; Nonexperimental methods; Within-study comparison;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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