Interpreting the Beveridge curve. An agent-based approach
Gabriele Cardullo and
Eric Guerci
Journal of Economic Behavior & Organization, 2019, vol. 157, issue C, 84-100
Abstract:
We construct an agent based computational model of the labour market with heterogeneous workers and firms to study the behaviour of the Beveridge curve along the business cycle. In this framework, search frictions arise because filling a vacancy is a costly activity that takes time, whereas productivity mismatch comes from firms’ imperfect information about the value of the workers before the job interview takes place. The model offers an interpretation for the outward movement exhibited by the U.S. Beveridge curve since the last months of 2009. Sectoral misallocation plays a role. Moreover, when the speed of recovery from a recession is not uniform across sectors, unemployed workers are less selective in their application strategy and firms must spend more time in choosing the best match. Unemployment remains high in spite of an increase in the number of vacancies.
Keywords: Beveridge curve; Mismatch; Unemployment; Agent-based modelling (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167268117303451
Full text for ScienceDirect subscribers only
Related works:
Working Paper: Interpreting the Beveridge curve: an agent-based approach (2018) 
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:jeborg:v:157:y:2019:i:c:p:84-100
DOI: 10.1016/j.jebo.2017.12.003
Access Statistics for this article
Journal of Economic Behavior & Organization is currently edited by Houser, D. and Puzzello, D.
More articles in Journal of Economic Behavior & Organization from Elsevier
Bibliographic data for series maintained by Catherine Liu ().