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TED: Stata Module for Testing Stability of Regression Discontinuity Models

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  • Giovanni Cerulli

    () (CNR - IRCrES)

Abstract

Regression discontinuity (RD) models are commonly used to nonparametrically identify and estimate a local average treatment effect (LATE). Dong and Lewbel (2015) show how a derivative of this LATE can be estimated. They use their Treatment Effect Derivative (TED) to estimate how the LATE would change if the RD threshold changed. We argue that their estimator 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, Cerulli et al. (2016) 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. In this article, we provide the Stata module “ted†that can be used to easily implement TED and CPD estimation, and we apply it to some real data sets.

Suggested Citation

  • Giovanni Cerulli, 2016. "TED: Stata Module for Testing Stability of Regression Discontinuity Models," 2016 Stata Conference 12, Stata Users Group.
  • Handle: RePEc:boc:scon16:12
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    File URL: http://fmwww.bc.edu/repec/chic2016/chicago16_cerulli.pdf
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