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dc.contributor.advisorStantcheva, Stefanie
dc.contributor.advisorFryer, Roland G.
dc.contributor.advisorKatz, Lawrence F.
dc.contributor.advisorLaibson, David I.
dc.contributor.authorCraig, Ashley C.
dc.date.accessioned2019-12-12T08:41:35Z
dc.date.created2019-05
dc.date.issued2019-04-12
dc.date.submitted2019
dc.identifier.citationCraig, Ashley C. 2019. Essays on Incentives and Human Capital Formation. Doctoral dissertation, Harvard University, Graduate School of Arts & Sciences.
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:42029622*
dc.description.abstractI study policies designed to affect the production of human capital, either to improve efficiency or reduce inequality. Each chapter provides insights into how human capital accumulation is affected by the structure of the labor market, information, and policy interventions themselves. In Chapter 1, I study optimal income taxation when workers' human capital investment is imperfectly observable by employers. Bayesian employer inference about worker productivity drives a wedge between the private and social returns to human capital investment. The resulting positive externality from worker investment implies lower optimal marginal tax rates. I calibrate my model to match empirical moments from the United States. Taking into account the spillover from human capital investment introduced by employer inference reduces optimal marginal tax rates by 13 percentage points at around 100,000 dollars of income, with little change in the tails of the income distribution. In Chapter 2 (joint with Roland Fryer), I develop a model of two-sided statistical discrimination, in which firms try to infer whether workers have made investments required for them to be productive, and simultaneously, workers try to deduce whether firms have made investments necessary for them to thrive. Complementarity between worker and firm beliefs complicates both empirical analysis designed to detect discrimination and policy meant to alleviate it. We propose "two-sided investment insurance" as an alternative tool that is weakly more effective than any alternative. The chapter concludes by proposing a way to identify statistical discrimination when beliefs are complementary. In Chapter 3 (joint with David Martin), I study the causal effect of student suspension on test scores. Our identification comes from quasi-experimental variation in the impact of a policy change in 2012 in New York City, which eliminated suspensions for minor offenses such as smoking or using obscene language. For the majority of schools, in which suspensions for minor infractions were used extremely rarely, the new suspension policy necessarily had no impact. However, it led to a sharp reduction in the total suspension rate in schools that had previously used them. Our estimates indicate that more relaxed student discipline can be beneficial for students.
dc.description.sponsorshipEconomics
dc.format.mimetypeapplication/pdf
dc.language.isoen
dash.licenseLAA
dc.subjectoptimal taxation
dc.subjectincome taxation
dc.subjecthuman capital
dc.subjectimperfect information
dc.subjectexternalities
dc.subjectdiscrimination
dc.subjectstatistical discrimination
dc.subjectsignaling
dc.subjectsuspensions
dc.subjecteducation
dc.subjectpunishment
dc.subjectstudent discipline
dc.subjectaffirmative action
dc.subjectpublic economics
dc.titleEssays on Incentives and Human Capital Formation
dc.typeThesis or Dissertation
dash.depositing.authorCraig, Ashley C.
dc.date.available2019-12-12T08:41:35Z
thesis.degree.date2019
thesis.degree.grantorGraduate School of Arts & Sciences
thesis.degree.grantorGraduate School of Arts & Sciences
thesis.degree.levelDoctoral
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy
thesis.degree.nameDoctor of Philosophy
dc.type.materialtext
thesis.degree.departmentEconomics
thesis.degree.departmentEconomics
dash.identifier.vireo
dc.identifier.orcid0000-0001-8717-3980
dash.author.emailash@ashleycraig.com


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