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Regression discontinuity design with multivalued treatments

Author

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  • Carolina Caetano
  • Gregorio Caetano
  • Juan Carlos Escanciano

Abstract

We study identification and estimation in the regression discontinuity design with a multivalued treatment. We show that heterogeneity in the first stage discontinuities can be used for the identification of the marginal treatment effects under an alternative assumption, namely, the homogeneity of the LATEs along some covariates. This assumption can often be tested and relaxed. Our estimator can be programmed as a simple two‐stage least squares regression, and packaged standard errors and tests can also be used. We apply our method to estimate the effect of Medicare insurance coverage on health care utilization.

Suggested Citation

  • Carolina Caetano & Gregorio Caetano & Juan Carlos Escanciano, 2023. "Regression discontinuity design with multivalued treatments," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(6), pages 840-856, September.
    • Handle: RePEc:wly:japmet:v:38:y:2023:i:6:p:840-856
    DOI: 10.1002/jae.2982
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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. Xie, Haitian, 2024. "Nonlinear and nonseparable structural functions in regression discontinuity designs with a continuous treatment," Journal of Econometrics, Elsevier, vol. 242(1).

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