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Neighborhood effects and job search behaviors

Florence Goffette-Nagot () and Marie Aurélie Lapierre ()
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Florence Goffette-Nagot: CERGIC - Center for Economic Research on Governance, Inequality and Conflict - ENS de Lyon - École normale supérieure de Lyon - Université de Lyon
Marie Aurélie Lapierre: GATE Lyon Saint-Étienne - Groupe d'Analyse et de Théorie Economique Lyon - Saint-Etienne - UL2 - Université Lumière - Lyon 2 - UJM - Université Jean Monnet - Saint-Étienne - EM - EMLyon Business School - CNRS - Centre National de la Recherche Scientifique

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Abstract: This paper aims to test for the influence of interactions with neighbors on job search behaviors of unemployed individuals. Using data from the 2014-2019 French Labor Force Survey, we implement a model of endogenous, contextual and group effects inspired from Manski (1993) and applied to job search intensity for different channels. We control for location endogeneity in a similar way as in Bayer et al. (2008) and tackle the reflection issue by using the approach proposed by Lee (2007) and developed by Boucher et al. (2014). We find evidence of endogenous peer effects for all the job search channels, which indicates the existence of imitation or spread of information effects, particularly for job search through personal and professional networks. We also find some contextual and group effects with regards to neighbors' occupations. Such results underline the importance for job search of being surrounded by neighbors with strong labor market connections, and suggest that local social interaction effects in job search could amplify labor market inequalities across neighborhoods.

Keywords: Job search behavior; Neighborhood effects; Reflection issue; Location endogeneity; Unemployment (search for similar items in EconPapers)
Date: 2024-08-26
Note: View the original document on HAL open archive server: https://hal.science/hal-04868773v1
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Published in 39th meeting of the European Economic Association, European Economic Association, Aug 2024, Rotterdam (NL), Netherlands

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