Degrees of Separation: An Alternate Cause of Discrimination
Abstract/Contents
- Abstract
- This paper builds a social network employment model that divides the labor force into two groups of different relative size: a majority and minority group is introduced. Average workers from each group are otherwise completely identical, possessing an equal level of ability. However, due to social network effects, minority workers not only receive a disproportionately low fraction of job offers through referral, but also expect lower average wages. Thus, the model suggests that simply the introduction of a majority and minority group in the labor force (when workers are more likely to know others who share similar attributes) breeds inequality. Discrimination (measurable differences in expected welfare between groups, given equal ability) can persist independently of psychological prejudices like racism or sexism—discrimination may be an inherent consequence of the interaction of more- and less- “advantageous” social networks.
Description
Type of resource | text |
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Date created | May 2007 |
Creators/Contributors
Author | Okafor, Chika | |
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Primary advisor | Arrow, Kenneth | |
Degree granting institution | Stanford University, Department of Economics |
Subjects
Subject | Stanford Department of Economics |
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Subject | labor force |
Subject | discrimination |
Subject | inequality |
Subject | social network |
Genre | Thesis |
Bibliographic information
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- Use and reproduction
- User agrees that, where applicable, content will not be used to identify or to otherwise infringe the privacy or confidentiality rights of individuals. Content distributed via the Stanford Digital Repository may be subject to additional license and use restrictions applied by the depositor.
Preferred citation
- Preferred Citation
- Okafor, Chika. (2007). Degrees of Separation: An Alternate Cause of Discrimination. Stanford Digital Repository. Available at: https://purl.stanford.edu/fh520js1265
Collection
Stanford University, Department of Economics, Honors Theses
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