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For Whom are Permanent Jobs off Limits? A Markov-Chain-Based Analysis of Individual Labor Market Dynamics

Magali Beffy, Elise Coudin and Roland Rathelot
Annals of Economics and Statistics
No. 115/116, SPECIAL ISSUE ON KNOWLEDGE CAPITAL IN NANOTECHNOLOGY AND OTHER HIGH TECHNOLOGY INDUSTRIES (December 2014), pp. 315-342
Published by: GENES on behalf of ADRES
DOI: 10.15609/annaeconstat2009.115-116.315
Stable URL: http://www.jstor.org/stable/10.15609/annaeconstat2009.115-116.315
Page Count: 30
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For Whom are Permanent Jobs off Limits? A Markov-Chain-Based Analysis of Individual Labor Market Dynamics
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Abstract

How many workers are confined indefinitely in a labor cycle, moving back and forth from temporary jobs to nonemployment periods without the potential to secure a steady job? To answer this question, we develop a mixture of four Markov chains, each of them modeling a specific type of labor market dynamics: stayers in steady jobs, stayers out of the labor market, unconfined movers who move between states and eventually enter a permanent job, and confined movers who do not. This model is estimated using data from the French Labor Force Surveys from 2005 to 2009 for eight groups defined by gender and age to account for age-related life cycle periods. Education is included as an explanatory variable for the dynamics type. Confined movers represent 5% of the 20- to 59-year-old individuals who have finished their studies but 12% of 20- to 29-year-olds, and more than 25% of 20- to 29-year-olds with less education – up to junior high school completion. Confined movers experience far more frequent periods of unemployment than movers who can access stable jobs. Furthermore, confined movers are more likely to have less favored social backgrounds, have immigrant parents, and live in deprived areas (“Zones Urbaines Sensibles”). These empirical findings may be related to the economic mechanisms responsible for the duality of the French labor market. JEL: J21, J60, C33 / KEY WORDS: Labor Market Transitions, Labor Market Mobility, Duality, Mover-Stayer Models, Markov Chains, Mixture

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