The Regression Kink (RK) design is an increasingly popular empirical method, with more than 20 studies circulated using RK in the last 5 years since the initial circulation of Card, Lee, Pei and Weber (2012). We document empirically that these estimates, which typically use local linear regression, are highly sensitive to curvature in the underlying relationship between the outcome and the assignment variable. As an alternative inference procedure, motivated by randomization inference, we propose that researchers construct a distribution of placebo estimates in regions without a policy kink.
We apply our procedure to three empirical RK applications – two administrative UI datasets with true policy kinks and the 1980 Census, which has no policy kinks – and we find that statistical significance based on conventional p-values may be spurious. In contrast, our permutation test reinforces the asymptotic inference results of a recent Regression Discontinuity study and a Difference-in-Difference study. Finally, we propose estimating RK models with a modified cubic splines framework and test the performance of different estimators in a simulation exercise. Cubic specifications – in particular recently proposed robust estimators (Calonico, Cattaneo and Titiunik 2014) – yield short interval lengths with good coverage rates.
We use cookies to provide you with an optimal website experience. This includes cookies that are necessary for the operation of the site as well as cookies that are only used for anonymous statistical purposes, for comfort settings or to display personalized content. You can decide for yourself which categories you want to allow. Please note that based on your settings, you may not be able to use all of the site's functions.
Cookie settings
These necessary cookies are required to activate the core functionality of the website. An opt-out from these technologies is not available.
In order to further improve our offer and our website, we collect anonymous data for statistics and analyses. With the help of these cookies we can, for example, determine the number of visitors and the effect of certain pages on our website and optimize our content.