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Testing Stability of Regression Discontinuity Models

In: Regression Discontinuity Designs

Author

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

Abstract

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: Regression Discontinuity Designs, volume 38, pages 317-339, Emerald Group Publishing Limited.
    • Handle: RePEc:eme:aecozz:s0731-905320170000038013
    DOI: 10.1108/S0731-905320170000038013
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    Citations

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    Cited by:

    1. Matias D. Cattaneo & Rocío Titiunik, 2022. "Regression Discontinuity Designs," Annual Review of Economics, Annual Reviews, vol. 14(1), pages 821-851, August.
    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, 2020. "Optimal bandwidth choice for robust bias-corrected inference in regression discontinuity designs [Econometric methods for program evaluation]," The Econometrics Journal, Royal Economic Society, vol. 23(2), pages 192-210.
    4. Christopher Erwin, 2019. "Low-performing student responses to state merit scholarships," Working Papers 2019-02, Auckland University of Technology, Department of Economics.
    5. Hung‐Hao Chang & Chad D. Meyerhoefer, 2023. "Do elections make you sick? Evidence from first‐time voters," Health Economics, John Wiley & Sons, Ltd., vol. 32(5), pages 1064-1083, May.
    6. 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.
    7. Powdthavee, Nattavudh, 2021. "Education and pro-environmental attitudes and behaviours: A nonparametric regression discontinuity analysis of a major schooling reform in England and Wales," Ecological Economics, Elsevier, vol. 181(C).
    8. Gaggero, Alessio, 2020. "The effect of type 2 diabetes diagnosis in the elderly," Economics & Human Biology, Elsevier, vol. 37(C).
    9. Pietro Santoleri & Andrea Mina & Alberto Di Minin & Irene Martelli, 2020. "The causal effects of R&D grants: evidence from a regression discontinuity," LEM Papers Series 2020/18, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.

    More about this item

    Keywords

    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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