Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/228904
Authors: 
Melly, Blaise
Lalive, Rafael
Year of Publication: 
2020
Series/Report no.: 
Discussion Papers No. 20-16
Abstract: 
The Regression Discontinuity Design (RDD) has proven to be a compelling and transparent research design to estimate treatment effects. We provide a review of the main assumptions and key challenges faced when adopting an RDD. We cover the most recent developments and advanced methods, and provide the key intuitions that underlie the statistical arguments. Among others, we summarize new insights that we consider to be highly relevant about the choice of bandwidth, optimal inference, discrete running variables, distributional effects, estimation in the presence of covariates, and the regression kink design. We also show how structural parameters can be estimated by combining an RDD identification strategy with theoretical models. We illustrate the procedures by applying them to data and we provide codes to replicate the results.
Document Type: 
Working Paper

Files in This Item:
File
Size
489.83 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.