Text

theses

ETD doctoral

In Chapter 1, I investigate the migration response of college students to tuition differences between states, using variation introduced by tuition regional reciprocity agreements. Out-of-state students generally pay higher tuition than in-state students, but reciprocity agreements reduce the premium paid by students from other states in the agreement (sometimes to zero). I examine migration between directed pairs of states, with the tuition difference faced by a potential migrant as the covariate of interest. By instrumenting the tuition difference with a binary variable indicating the pair of states’ membership in a common regional reciprocity agreement, I find that a one percent decrease in the nonresident tuition of the destination state due to the regional reciprocity agreements would increase nonresident students’ inflow to the destination state by 0.4-0.5%. The reduced form shows that having a regional reciprocity agreement between states increases college migration between states by 29%.

In Chapter 2, I provide a new method to decompose discrimination by Chinese employers into customer and coworker discrimination. Using data from an online job board, I relate employer advertisements for beautiful and tall applicants to oc- cupational job requirements as measured by the American O*NET data. I find that employers hiring in occupations with more contact with customers are more likely to require beautiful applicants in their job ads and employers hiring in occupations with more contact with coworkers are more likely to require tall applicants in their job ads. Customer discrimination plays a more important role in terms of contributions to the R-squared for both beauty and height requirements than coworker discrimination. The determinants of requiring tall applicants are similar for ads requesting males and females. For beauty, on the other hand, the effect of customer contact is driven by jobs requesting females, while the effect of coworker contact is driven by jobs requesting males.

In Chapter 3, I compare how the gender wage gap evolves with age for occupations with different levels of contact with the public, coworkers, and customers. I use the O*NET data describing occupational job requirements to create indices of contact by occupation. I merge these indices with worker data from the Current Population Survey. I find suggestive evidence that the gender wage gap grows faster with age in occupations with greater overall contact; the evidence is stronger and statistically significant for occupations with high direct customer contact and with high public contact. This link is stronger for non-college graduates than more educated workers. I hypothesize that perceptions of how male and female beauty change with age could explain the results.

ETD_11256

Ph.D.

Includes bibliographical references

doi:10.7282/t3-5n9s-2x78

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