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The determinants of Job Access Channels: Evidence from the Youth Labor Market in France

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  • Jihan Ghrairi

    (ERMES - Equipe de recherche sur les marches, l'emploi et la simulation - UP2 - Université Panthéon-Assas - CNRS - Centre National de la Recherche Scientifique, TEPP - Travail, Emploi et Politiques Publiques - UPEM - Université Paris-Est Marne-la-Vallée - CNRS - Centre National de la Recherche Scientifique)

Abstract

This article aims to study youth employability on the job access channel that provided their entry into the labor market. We examine the determinants of the formal and informal job access channels. For this purpose, we estimate a Multinomial Logit model of access channels controlling for selection bias. We use the youth sample of the French National Labor Force Survey (Enquête "Emploi") conducted by the INSEE. Our data provide a set of relevant variables required to identify the model which allows us to study different characteristics of young individuals that affect their access to the current job through a particular channel. First, we notice that young graduates access to their current jobs more often through direct applications and social networks. We find that, in 2010, referred young workers are more likely to be less educated man immigrants, living in rural areas and hired by large firms. However, immigrants were less likely to obtain a job through public employment agencies while the origin effect was not significant in 2007. Moreover, we find that the probability of finding a job through professional contacts increases significantly with the education level for both years (stronger effects for university graduates).

Suggested Citation

  • Jihan Ghrairi, 2013. "The determinants of Job Access Channels: Evidence from the Youth Labor Market in France," Working Papers halshs-00870042, HAL.
  • Handle: RePEc:hal:wpaper:halshs-00870042
    Note: View the original document on HAL open archive server: https://halshs.archives-ouvertes.fr/halshs-00870042
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    Keywords

    job access channels; social networks; multinomial logit; selection bias;

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