Research

Abstract: This paper studies the implications of mismatch in the college labor market, where mismatch is defined as the gap between the skills firms demand and the specific skills different college majors graduate with. In this paper, we construct a novel measure of skills associated with different college degrees and how those differ from skills demanded in different occupations. In our baseline regression, we estimate the correlation between earnings based on the initial skill mismatch in the first job out of college, before we estimate the effect of college major skill mismatch on lifetime earnings. We then use a search model to understand the decline of relevance of initial college skills over the life cycle of earnings and the importance of each skill and the level of skill a student in each major graduates with. By combining Lightcast data with restricted use U.S. Census Bureau data (NSCG (National Survey of College Graduates) and ACS (American Community Service)), we can track college graduates throughout their early career stages. With this data and our model, we are able to contribute to the literature by adding which relevant college skills and major-specific skills allow students to succeed in the labor market, in terms of earnings as well as determine the impact of these skills over the early life cycle. 

Abstract: In this paper, I construct a search model framework incorporating ``skill shocks" to illustrate how changes to occupational skill demand can influence displacement probabilities. I then empirically show how much jobs changed through the 1980s and 1990s. From the 1980s and 1990s, in the Atalay et al. (2020) data, I find that occupations on average had .28 words per 10,000 words in a job ad that corresponded to skills; additionally, on average, occupations change by about .14 words per 10,000 words per year. Using a difference-in-difference framework, I empirically estimate the impact of occupational skill shock, leveraging innovative data from Atalay et al. (2020), the Current Population Survey, and the Displaced Worker Supplement. If an occupation changes by the average amount, displacement probabilities increase by .14-.42%, occupational switching increases by nearly 1% for displaced workers, and real earnings growth for displaced workers is positive for occupational stayers but not significant from zero for occupational switchers. Overall, the analysis demonstrates that occupations' skill bundles are dynamic, and changes to occupational skill bundles impact short-run labor market outcomes. 

Full draft available upon request

Abstract:  Using innovative genetic data in the GSEOP, we examine correlations between inherited health and unemployment risk. We use predicted self-reported health status based on genetic data–a polygenic index (PGI)–and examine the correlation with unemployment risk; we note that PGIs are not subjected to justification bias like self-reported health measures since they are fixed at birth. A person with a self-report health PGI one standard deviation above the mean is about 1-1.9 percentage points less likely to experience unemployment. When we use observed self-reported health, a higher score is associated with a four percentage point decrease in unemployment probabilities, much larger than the estimated effect on the PGI. We note these are correlational and not causal statements.