Abstract
This article focuses on the interrelationship between educational mismatch and earnings, taking three new approaches. First, we examine decompositions of the mismatch wage gap, finding that characteristics explain less than half of the mismatch penalty. Second, we use unconditional quantile regression to examine the mismatch penalty across the earnings distribution, showing that the penalty shrinks as the position in the earnings distribution increases. Third, we decompose the differentials using quantile decompositions. Different reasons for mismatch show heterogeneity in our results, with larger penalties for being mismatched due to working conditions, location, family, and no available job.
| Original language | English |
|---|---|
| Pages (from-to) | 441-456 |
| Number of pages | 16 |
| Journal | Southern Economic Journal |
| Volume | 85 |
| Issue number | 2 |
| Early online date | 3 Sep 2018 |
| DOIs | |
| Publication status | Published - Oct 2018 |
Keywords
- educational mismatch
- earnings
- decomposition
- quantile regression
Access to Document
- Accepted Manuscript
This is the peer reviewed version of the following article: Bender, K. A. and Roche, K. (2018), Educational mismatch and the earnings distribution. Southern Economic Journal, 85: 441-456 which has been published in final form at https://doi.org/10.1002/soej.12282. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.
