Cookies?
Library Header Image
LSE Research Online LSE Library Services

Labor search and matching in macroeconomics

Yashiv, Eran (2007) Labor search and matching in macroeconomics. CEPDP, 803. Centre for Economic Performance, London School of Economics and Political Science, London, UK. ISBN 9780853281801

[img]
Preview
PDF
Download (461kB) | Preview
Identification Number: 803

Abstract

The labor search and matching model plays a growing role in macroeconomic analysis. This paper provides a critical, selective survey of the literature. Four fundamental questions are explored: how are unemployment, job vacancies, and employment determined as equilibrium phenomena? What determines worker flows and transition rates from one labor market state to another? How are wages determined? What role do labor market dynamics play in explaining business cycles and growth? The survey describes the basic model, reviews its theoretical extensions, and discusses its empirical applications in macroeconomics. The model has developed against the background of difficulties with the use of the neoclassical, frictionless model of the labor market in macroeconomics. Its success includes the modelling of labor market outcomes as equilibrium phenomena, the reasonable fit of the data, and — when inserted into business cycle models — improved performance of more general macroeconomic models. At the same time, there is evidence against the Nash solution used for wage setting and an active debate as to the ability of the model to account for some of the cyclical facts.

Item Type: Monograph (Discussion Paper)
Official URL: http://cep.lse.ac.uk
Additional Information: © 2007 Eran Yashiv
Subjects: H Social Sciences > HD Industries. Land use. Labor
Sets: Collections > Economists Online
Research centres and groups > Centre for Economic Performance (CEP)
Departments > Economics
Date Deposited: 21 Jul 2008 09:33
Last Modified: 01 Oct 2010 09:12
URI: http://eprints.lse.ac.uk/id/eprint/19707

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics