Estimating the Probability of Leaving Unemployment Using Uncompleted Spells from Repeated Cross-Section Data

46 Pages Posted: 22 Aug 2003

See all articles by Maia Güell

Maia Güell

Universitat Pompeu Fabra - Faculty of Economic and Business Sciences; Centre for Economic Policy Research (CEPR); IZA Institute of Labor Economics

Luojia Hu

Federal Reserve Bank of Chicago

Multiple version iconThere are 2 versions of this paper

Date Written: July 2003

Abstract

We propose a new econometric estimation method for analysing the probability of leaving unemployment using uncompleted spells from repeated cross-section data, which can be especially useful when panel data are not available. The proposed method-of-moments-based estimator has two important features: (1) it estimates the exit probability at the individual level and (2) it does not rely on the stationarity assumption of the inflow composition. We illustrate and gauge the performance of the proposed estimator using the Spanish Labor Force Survey data, and analyse the changes in distribution of unemployment between the 1980s and 1990s during a period of labour market reform. We find that the relative probability of leaving unemployment of the short-term unemployed versus the long-term unemployed becomes significantly higher in the 1990s.

Keywords: Repeated cross-section data, GMM, duration analysis, unemployment

JEL Classification: C41, J64

Suggested Citation

Guell, Maia and Hu, Luojia, Estimating the Probability of Leaving Unemployment Using Uncompleted Spells from Repeated Cross-Section Data (July 2003). CEPR Discussion Paper No. 3957. Available at SSRN: https://ssrn.com/abstract=436993

Maia Guell (Contact Author)

Universitat Pompeu Fabra - Faculty of Economic and Business Sciences ( email )

Ramon Trias Fargas 25-27
Barcelona, 08005
Spain
+34 93 542 2717 (Phone)
+34 94 816 9721 (Fax)

HOME PAGE: http://www.econ.upf.es/~mguell/

Centre for Economic Policy Research (CEPR)

London
United Kingdom

IZA Institute of Labor Economics

P.O. Box 7240
Bonn, D-53072
Germany

Luojia Hu

Federal Reserve Bank of Chicago ( email )

230 South LaSalle Street
Chicago, IL 60604
United States

Register to save articles to
your library

Register

Paper statistics

Downloads
21
Abstract Views
696
PlumX Metrics