Inequality and discrimination in historical and modern labor markets
Abstract/Contents
- Abstract
- This dissertation uses two disparate settings to investigate sources of racial and ethnic inequality in labor markets. In the first setting we study the effect of race on economic outcomes using unique data from the first half of the twentieth century, a period in which skin color was explicitly coded in population censuses as "White, " "Black, " or "Mulatto." We construct a panel of siblings by digitizing and matching records across the 1910 and 1940 censuses and identifying all 12,000 African-American families in which enumerators classified some children as light-skinned ("Mulatto") and others as dark-skinned ("Black"). Siblings coded "Mulatto" when they were children (in 1910) earned similar wages as adults (in 1940) relative to their Black siblings. This within-family earnings difference is substantially lower than the Black-Mulatto earnings difference in the general population, suggesting that skin color in itself played only a small role in the racial earnings gap. To explore the role of the more social aspect that might be associated with being Black, we then focus on individuals who "passed for White, " an important social phenomenon at the time. To do so, we identify individuals coded "Mulatto" as children but "White" as adults. Passing for White meant that individuals changed their racial affiliation by changing their social ties, while skin color remained unchanged. We compare passers to their siblings who did not pass. Passing was associated with substantially higher earnings, suggesting that race in its social form could have significant consequences for economic outcomes. The second setting is an online employer-freelancer matching platform freelancer.com. I study the effect of a freelancer's country-of-origin on the employer's decision of whether to hire them. Having to rely on a relatively small number of characteristics, employers use the freelancer's country of origin and reputation scores to infer the expected service quality. I find that freelancers from developing countries are less likely to be hired when they have no individual reputation, and as individual reputation becomes better this country effect disappears. This setting also allows me to study how employers' experience in past hires affects their behavior in current hires. I show that following a good match with a freelancer, employers are more likely to hire freelancers from the good match's country. I discuss how these findings contributes to our understanding of matching, learning, and discrimination in online settings.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Publication date | 2013 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Mill, Roy |
|---|---|
| Associated with | Stanford University, Department of Economics. |
| Primary advisor | Abramitzky, Ran |
| Thesis advisor | Abramitzky, Ran |
| Thesis advisor | Einav, Liran |
| Thesis advisor | Greif, Avner, 1955- |
| Thesis advisor | Wright, Gavin, 1943- |
| Advisor | Einav, Liran |
| Advisor | Greif, Avner, 1955- |
| Advisor | Wright, Gavin, 1943- |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Roy Mill. |
|---|---|
| Note | Submitted to the Department of Economics. |
| Thesis | Thesis (Ph.D.)--Stanford University, 2013. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2013 by Roy Mill
- License
- This work is licensed under a Creative Commons Attribution No Derivatives 3.0 Unported license (CC BY-ND).
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