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External Validity in Fuzzy Regression Discontinuity Designs

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  • BERTANHA, Marinho
  • IMBENS, Guido W.

Abstract

Many empirical studies use Fuzzy Regression Discontinuity (FRD) designs to identify treatment effects when the receipt of treatment is potentially correlated to outcomes. Existing FRD methods identify the local average treatment effect (LATE) on the subpopulation of compliers with values of the forcing variable that are equal to the threshold. We develop methods that assess the plausibility of generalizing LATE to subpopulations other than compliers, and to subpopulations other than those with forcing variable equal to the threshold. Specifically, we focus on testing the equality of the distributions of potential outcomes for treated compliers and always-takers, and for untreated compliers and never-takers. We show that equality of these pairs of distributions implies that the expected outcome conditional on the forcing variable and the treatment status is continuous in the forcing variable at the threshold, for each of the two treatment regimes. Our main recommendation is that researchers, as a matter of routine, present graphs with estimates of these two conditional expectations in addition to graphs with estimates of the expected outcome conditional on the forcing variable alone. We illustrate our methods using data on the academic performance of students attending the summer school program in two large school districts in the US.

Suggested Citation

  • BERTANHA, Marinho & IMBENS, Guido W., 2016. "External Validity in Fuzzy Regression Discontinuity Designs," CORE Discussion Papers 2016025, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  • Handle: RePEc:cor:louvco:2016025
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    References listed on IDEAS

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    More about this item

    Keywords

    Fuzzy Regression Discontinuity Designs; Treatment Effects; Potential Outcomes; Exogeneity; External Validity;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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