Human Capital, Signaling, and Employer Learning: What Insights Do We Gain from Regression Discontinuity Designs?
Georg Graetz
No 11125, IZA Discussion Papers from Institute of Labor Economics (IZA)
Abstract:
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.
Keywords: regression discontinuity design; human capital; signaling; employer learning; statistical discrimination (search for similar items in EconPapers)
JEL-codes: C2 D8 J2 (search for similar items in EconPapers)
Pages: 19 pages
Date: 2017-11
New Economics Papers: this item is included in nep-hrm
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Citations: View citations in EconPapers (2)
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Working Paper: Human Capital, Signaling, and Employer Learning. What Ingsights Do We Gain from Regression Discontinuity Designs (2017) 
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