Several recent papers employ the regression discontinuity design (RDD) to estimate the causal effect of a diploma (or similar credentials) on wages. Using a simple model of asymmetric information, I show that RDD estimates the information value of a diploma. A positive information value arises if employers, unable to observe the test score that determines diploma receipt, infer that workers with a diploma have higher average productivity than those without.
Crucially, a diploma can have information value regardless of whether workers' productivity is solely determined by acquisition of knowledge and skills through studying (the pure human capital model) or whether studying has no effect on productivity (the pure signaling model). Thus, while RDD estimates of diploma effects are evidence for information frictions and statistical discrimination, they do not help to distinguish between human capital and signaling. However, with longitudinal data, RDD can be used to estimate the speed of employer learning, since RDD coefficients are direct estimates of (differences in) expectation errors.
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.