Regression Kink Design: Theory and Practice

40 Pages Posted: 31 Oct 2016

See all articles by David Card

David Card

University of California, Berkeley - Department of Economics; Institute for the Study of Labor (IZA); National Bureau of Economic Research (NBER)

David Lee

Princeton University

Zhuan Pei

W.E. Upjohn Institute for Employment Research

Andrea Weber

Vienna University of Economics and Business; Austrian Institute of Economic Research (WIFO); Institute for the Study of Labor (IZA); CESifo (Center for Economic Studies and Ifo Institute)

Date Written: October 2016

Abstract

A regression kink design (RKD or RK design) can be used to identify casual effects in settings where the regressor of interest is a kinked function of an assignment variable. In this paper, we apply an RKD approach to study the effect of unemployment benefits on the duration of joblessness in Austria, and discuss implementation issues that may arise in similar settings, including the use of bandwidth selection algorithms and bias-correction procedures. Although recent developments in nonparametric estimation (e.g. Imbens et al. (2012) and Calonico et al. (2014)) are sometimes interpreted by practitioners as pointing to a default estimation procedure, we show that in any given application different procedures may perform better or worse. In particular, Monte Carlo simulations based on data generating processes that closely resemble the data from our application show that some asymptotically dominant procedures may actually perform worse than “sub-optimal” alternatives in a given empirical application.

Suggested Citation

Card, David E. and Lee, David and Pei, Zhuan and Weber, Andrea Michaela, Regression Kink Design: Theory and Practice (October 2016). NBER Working Paper No. w22781. Available at SSRN: https://ssrn.com/abstract=2861713

David E. Card (Contact Author)

University of California, Berkeley - Department of Economics ( email )

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David Lee

Princeton University ( email )

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Zhuan Pei

W.E. Upjohn Institute for Employment Research ( email )

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Andrea Michaela Weber

Vienna University of Economics and Business ( email )

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