This dissertation is comprised of three distinct papers covering topics in applied
microeconomics and applied econometrics. The first paper addresses a common problem faced by empirical researchers wishing to estimate Markov regime-switching models. For these models, testing for the possible presence of more than one regime requires the use of a non-standard test statistic. The analytic steps needed to implement the test of Markov regime-switching proposed by Cho & White (2007) are derived in detail in Carter & Steigerwald (2013). We summarize those implementation steps and address the computational issues that arise. A new Stata command to compute the regime-switching critical values, rscv, is introduced and presented in the context of empirical economic research. This paper is joint work with Douglas Steigerwald, and has previously appeared in the Stata Journal (Bostwick and Steigerwald, 2014).
In the second paper, I address a question in the field of economics of education: that is,
whether college students use their choice of major as a signal of unobserved productivity
in the labor market. I propose a model of postsecondary education in which major field
of study can be used by individuals to signal productivity to employers. Under this
signaling model, I show that geographic areas with high access to elite universities result
in fewer science, technology, engineering, and mathematics (STEM) majors among lower ability students at non-elite colleges. Using data from the National Center for Education Statistics' Baccalaureate and Beyond survey, I find evidence that is consistent with the signaling model prediction, specifically a 2.3-3.7 percentage point (or 16-25%) decrease in the probability of choosing a STEM major among lower ability students in areas with greater access to elite colleges. This paper has previously appeared in Economic Inquiry (Bostwick, 2016).
In the third paper, I analyze an unexpected consequence of a highly debated education
policy. Many school districts are now considering delaying high school start times to
accommodate the sleep schedules of teens. This paper explores whether such policy
changes can have an impact on teen car accident rates. This impact could function
both through a direct effect on teen sleep deprivation and indirectly through changes to
the driving environment, i.e. shifting teen commute times into the high volume, "rush
hour" of the morning. I find that, during the morning commute hours, any potential
effect stemming from avoided sleep deprivation is offset by the effect of shifting teen
driving into rush hour, so that a 15 minute delay in high school start times leads to a
21% increase in morning teen accidents. However, by focusing on late-night accidents, I
also find evidence of a persistent sleep effect. By decreasing teen sleep deprivation, a 15 minute delay in school start times leads to a 26% decrease in late-night teen accidents.