A Social Network Analysis of Occupational Segregation

Leij, Marco van der; Buhai, Sebastian

doi:10.2139/ssrn.1117949

Cited by 7 publications

(4 citation statements)

References 51 publications

(55 reference statements)

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“…In our study, ethnic inbreeding homophily captures the tendency of individuals to have more friendships with members of their own ethnic or racial group, relative to the proportion of the same racial or ethnicity friendships one would expect to observe if friends were chosen randomly. Theoretical network models suggest that inbreeding homophily is a crucial factor causing labor market inequality (Montgomery 1991;Calvó-Armengol & Jackson 2004;Van der Leij & Buhai 2008). We examine this claim empirically.…”

Section: Introductionmentioning

confidence: 93%

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Social networks and labor market inequality between ethnicities and races

2013

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Social networks and labor market inequality between ethnicities and racesToomet, O.; van der Leij, M.J.; Rolfe, M. Link to publication General rightsIt is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons). Disclaimer/Complaints regulationsIf you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library: http://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible. Abstract This paper analyzes the relationship between unexplained racial/ethnic wage differentials on the one hand and social network segregation, as measured by inbreeding homophily, on the other hand. Our analysis is based on both U.S. and Estonian surveys, supplemented with Estonian telephone communication data. In case of Estonia we consider the regional variation in economic performance of the Russian minority, and in the U.S. case we consider the regional variation in black-white differentials. Our analysis finds a strong relationship between the size of the differential and network segregation: regions with more segregated social networks exhibit larger unexplained wage gaps.JEL codes: J71, J31, Z13

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Section: Introductionmentioning

confidence: 93%

“…Van der Leij and Buhai (2008) have an explicit model in which inbreeding homophily creates persistent unemployment and wage gaps through occupational segregation. A key factor in this model is the education decision that individuals make before entering the labor market.…”

Section: Structural Network Theoriesmentioning

confidence: 99%

Social networks and labor market inequality between ethnicities and races

2013

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“…This complex web of relationships exposes us to different types of people, whilst segregating us from others. Computational social science can help to better understand this complexity and network analysis has become a pervasive methodology for understanding complex social systems and group dynamics [1,2,3,4,5].…”

Section: Mainmentioning

confidence: 99%

“…In accordance with the law which governs Statistics Netherlands conduct 2 and the General Data Protection Regulation 3 , the data are protected by extensive rules and regulations with respect to privacy to ensure that no information about individual persons is disclosed in any output from these data sets, and individuals can never be recognized in the output. This applies to all analyses presented here 4 .…”

Section: Mainmentioning

confidence: 99%

Using a network of the whole population of the Netherlands to measure exposure to differing educational backgrounds

Laan¹,

Das²,

Riele³

et al. 2021

Preprint

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In this analysis we present a whole population network which uses administrative data to construct a network incorporating 1.4 billion relationships between the 17 million inhabitants of the Netherlands. Relationships are identified between individuals who live in the same household, live close to each other, work for the same company, attend the same educational institution, or belong to the same extended family. This network has properties that are rare in observed social networks, which opens up new applications for network science in the social sciences. To demonstrate the applications of such a network, we use a random walk approach to estimate segregation of individuals from differing educational backgrounds and whether specific types of relationships increase or decrease this segregation. The results suggest that relationships between people in the same household greatly increase segregation whilst work, school and neighborhood networks relationships increase exposure to individuals with different backgrounds. The size of these effects is context dependent. Further applications of a whole population network are also discussed

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Knowledge sharing and the dynamics of social capital

Araújo¹,

Minetti²

2011

European Economic Review

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A Social Network Analysis of Occupational Segregation

Cited by 7 publications

References 51 publications

Social networks and labor market inequality between ethnicities and races

Social networks and labor market inequality between ethnicities and races

Using a network of the whole population of the Netherlands to measure exposure to differing educational backgrounds

Knowledge sharing and the dynamics of social capital

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