Employer-provided training and productivity: Evidence from a panel of Japanese Firms

Masayuki Morikawa

Journal of the Japanese and International Economies, 2021, vol. 61, issue C

Abstract: This study presents evidence on the relationship between employer-provided training and productivity. The important contributions of this study are its comparison of the relative contribution of training to productivity and wages and its distinction between manufacturing and service firms. The results indicate that training significantly contributes to the labor productivity, particularly for firms in the service sector. The elasticities of productivity and wages to training stock are similar in size, meaning that the returns to firms’ training investments are shared by their workers in proportion to the wage share of the value-added.

Keywords: Training; Labor productivity; Wage; service sector; Intangible assets (search for similar items in EconPapers)
JEL-codes: J24 J31 J53 L80 M53 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0889158321000290
Full text for ScienceDirect subscribers only

Related works:
Working Paper: Employer-Provided Training and Productivity: Evidence from a Panel of Japanese Firms (2019)
Working Paper: Employer-Provided Training and Productivity: Evidence from a Panel of Japanese Firms (2019)
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:eee:jjieco:v:61:y:2021:i:c:s0889158321000290

DOI: 10.1016/j.jjie.2021.101150

Access Statistics for this article

Journal of the Japanese and International Economies is currently edited by Takeo Hoshi

More articles in Journal of the Japanese and International Economies from Elsevier
Bibliographic data for series maintained by Catherine Liu ().