Search, Matching and Training

Christopher Flinn, Ahu Gemici and Steven Laufer ()

No 2016-075, Finance and Economics Discussion Series from Board of Governors of the Federal Reserve System (U.S.)

Abstract: We estimate a partial and general equilibrium search model in which firms and workers choose how much time to invest in both general and match-specific human capital. To help identify the model parameters, we use NLSY data on worker training and we match moments that relate the incidence and timing of observed training episodes to outcomes such as wage growth and job-to-job transitions. We use our model to offer a novel interpretation of standard Mincer wage regressions in terms of search frictions and returns to training. Finally, we show how a minimum wage can reduce training opportunities and decrease the amount of human capital in the economy.

Keywords: Minimum Wage; On-the-job training; Wage growth (search for similar items in EconPapers)
JEL-codes: J24 J64 (search for similar items in EconPapers)
Pages: 73 pages
Date: 2016-07-13
New Economics Papers: this item is included in nep-dge and nep-ltv
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
http://www.federalreserve.gov/econresdata/feds/2016/files/2016075pap.pdf (application/pdf)

Related works:
Journal Article: Search, Matching, and Training (2017)
Working Paper: Search, Matching and Training (2016)
Working Paper: Search, Matching and Training (2014)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:fip:fedgfe:2016-75

DOI: 10.17016/FEDS.2016.075

Access Statistics for this paper

More papers in Finance and Economics Discussion Series from Board of Governors of the Federal Reserve System (U.S.) Contact information at EDIRC.
Bibliographic data for series maintained by Ryan Wolfslayer ; Keisha Fournillier ().