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Testing Stability of Regression Discontinuity Models

In: Regression Discontinuity Designs


  • Giovanni Cerulli
  • Yingying Dong
  • Arthur Lewbel
  • Alexander Poulsen


Regression discontinuity (RD) models are commonly used to nonparametrically identify and estimate a local average treatment effect. Dong and Lewbel (2015) show how a derivative of this effect, called treatment effect derivative (TED) can be estimated. We argue here that TED should be employed in most RD applications, as a way to assess the stability and hence external validity of RD estimates. Closely related to TED, we define the complier probability derivative (CPD). Just as TED measures stability of the treatment effect, the CPD measures stability of the complier population in fuzzy designs. TED and CPD are numerically trivial to estimate. We provide relevant Stata code, and apply it to some real datasets.

Suggested Citation

  • Giovanni Cerulli & Yingying Dong & Arthur Lewbel & Alexander Poulsen, 2017. "Testing Stability of Regression Discontinuity Models," Advances in Econometrics, in: Matias D. Cattaneo & Juan Carlos Escanciano (ed.), Regression Discontinuity Designs, volume 38, pages 317-339, Emerald Publishing Ltd.
  • Handle: RePEc:eme:aecozz:s0731-905320170000038013

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    Cited by:

    1. Gaggero, Alessio, 2020. "The effect of type 2 diabetes diagnosis in the elderly," Economics & Human Biology, Elsevier, vol. 37(C).
    2. Alessio Gaggero & Getinet Haile, 2020. "Does class size matter in postgraduate education?," Manchester School, University of Manchester, vol. 88(3), pages 489-505, June.
    3. Sebastian Calonico & Matias D. Cattaneo & Max H. Farrell, 2018. "Optimal Bandwidth Choice for Robust Bias Corrected Inference in Regression Discontinuity Designs," Papers 1809.00236,, revised Jan 2020.
    4. Arthur Lewbel, 2019. "The Identification Zoo: Meanings of Identification in Econometrics," Journal of Economic Literature, American Economic Association, vol. 57(4), pages 835-903, December.

    More about this item


    Regression discontinuity; external validity; threshold changes; marginal effects; treatment effect heterogeneity; program evaluation; C21; C25;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities


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