Search and Rest Unemployment

Fernando Alvarez and Robert Shimer
Additional contact information
Fernando Alvarez: University of Chicago

No 809, EIEF Working Papers Series from Einaudi Institute for Economics and Finance (EIEF)

Abstract: This paper extends Lucas and Prescott’s (1974) search model to develop a notion of rest unemployment. The economy consists of a continuum of labor markets, each of which produces a heterogeneous good. There is a constant returns to scale production technology in each labor market, but labor productivity is continually hit by idiosyncratic shocks, inducing the costly reallocation of workers across labor markets. Under some conditions, some workers may be rest-unemployed, waiting for local labor market conditions to improve, rather than engaged in time consuming search. The model has distinct notions of unemployment (moving to a new labor market or waiting for labor market conditions to improve) and inactivity (enjoying leisure while disconnected from the labor market). We obtain closed-form expressions for key aggregate variables and use them to evaluate the model. Quantitatively, we find that in the U.S. economy many more people may be in rest unemployment than in search unemployment.

Pages: 52 pages
Date: 2008, Revised 2008-01
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

Downloads: (external link)
http://www.eief.it/files/2012/09/wp-09-search-and-rest-unemployment.pdf (application/pdf)

Related works:
Journal Article: Search and Rest Unemployment (2011)
Working Paper: Search and Rest Unemployment (2008)
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:eie:wpaper:0809

Access Statistics for this paper

More papers in EIEF Working Papers Series from Einaudi Institute for Economics and Finance (EIEF) Contact information at EDIRC.
Bibliographic data for series maintained by Facundo Piguillem ().