Productivity spillovers through labor mobility in search equilibrium
Tom-Reiel Heggedal,
Espen Moen () and
Edgar Preugschat
Journal of Economic Theory, 2017, vol. 169, issue C, 551-602
Abstract:
This paper proposes an explicit model of spillovers through labor flows in a framework with search frictions. Firms can choose to innovate or to imitate by hiring a worker from a firm that has already innovated. We show that if innovating firms can commit to long-term wage contracts with their workers, productivity spillovers are fully internalized. If firms cannot commit to long-term wage contracts, there is too little innovation and too much imitation in equilibrium. Our model is tractable and allows us to analyze welfare effects of various policies in the limited commitment case. We find that subsidizing innovation and taxing imitation improves welfare. Moreover, allowing innovating firms to charge different forms of fees or rent out workers to imitating firms may also improve welfare. By contrast, non-pecuniary measures that reduce the efficiency of the search process, always reduce welfare.
Keywords: Efficiency; Innovation; Imitation; Productivity; Search frictions; Spillovers; Worker flows (search for similar items in EconPapers)
JEL-codes: J63 J68 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0022053117300339
Full text for ScienceDirect subscribers only
Related works:
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:jetheo:v:169:y:2017:i:c:p:551-602
DOI: 10.1016/j.jet.2017.03.003
Access Statistics for this article
Journal of Economic Theory is currently edited by A. Lizzeri and K. Shell
More articles in Journal of Economic Theory from Elsevier
Bibliographic data for series maintained by Catherine Liu ().