A search model with a quasi network

João Miguel Ejarque

No 597, 2010 Meeting Papers from Society for Economic Dynamics

Abstract: In a standard search model the expected duration of unemployment is independent of the duration of previous employment, as well as of the current length of the unemployment spell. This paper offers a network mechanism to generate these correlations. Here, employed workers invest in social contacts with other employed workers, which will help them find jobs in the event of unemployment. These social contacts "depreciate" because they can also become unemployed and unemployed contacts are assumed to be useless. In this model the longer you have been working, the more contacts you are likely to have, and the more contacts you have the shorter your expected unemployment duration will be. The model is a simple and tractable way of introducing network ideas in one of the workhorses of labour and macroeconomics. In the model the network is eroded during periods of high unemployment, and is therefore less productive in an absolute sense. Nevertheless, the number of job finders per contact in the unemployment pool increases during periods of high unemployment. Finally, the model provides guidance for indirect inference of network effects from the data.

Date: 2010
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://red-files-public.s3.amazonaws.com/meetpapers/2010/paper_597.pdf (application/pdf)

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:red:sed010:597

Access Statistics for this paper

More papers in 2010 Meeting Papers from Society for Economic Dynamics Society for Economic Dynamics Marina Azzimonti Department of Economics Stonybrook University 10 Nicolls Road Stonybrook NY 11790 USA. Contact information at EDIRC.
Bibliographic data for series maintained by Christian Zimmermann ().