UC Santa Barbara

This dissertation consists of three works which consider how frictional labor market models align with data, as well as how labor market data should be combined and used in applications of theoretical models. What unifies these essays is the underlying goal to further the consolidation of theoretical labor market models with empirical observations of worker and firm behavior in order to better understand and influence policy.

The first essay asks the question: How do changes in the minimum wage affect criminal activity? I answer this question by describing a frictional world in which a worker's criminal actions are linked to his labor market outcomes. The model is calibrated to match labor market outcomes and crime decisions of workers from the National Longitudinal Survey of Youth 1997, and shows that the relationship between the aggregate crime rate and the minimum wage is U-shaped. The results from the calibrated model as well as empirical evidence from county level crime data and state level minimum wage changes from 1995 to 2014 suggest that the crime minimizing minimum to median wage ratio for 16-19 year olds is 0.91. However, the welfare maximizing minimum to median wage ratio is 0.87, not equal to the crime minimizing value.

The second essay, joint with Ben Griffy, Bryan Engelhardt and Peter Rupert, asks the question: Is the arrival rate of a job independent of the wage that it pays? We answer this question by testing how, and to what extent, unemployment insurance changes the hazard rate of leaving unemployment across the wage distribution using a Mixed Proportional Hazard Competing Risk Model and data from the 1997 National Longitudinal Survey of Youth. Controlling for worker characteristics we reject that job arrival rates are independent of the wages offered. We apply the results to several prominent job-search models and interpret how our findings are key to determining the efficacy of unemployment insurance.

Finally, the third essay, joint with Finn Kydland and Peter Rupert argues that not all hours are created equally. In this paper we present a method for adjusting aggregate hours to account for changes in the quality of hours worked. Average human capital has rapidly increased since 1980 as better educated cohorts enter the workforce and the baby boomers continue to work and gather experience. We construct an aggregate labor input series from 1979 to adjust for changes in the experience and education levels of the workforce using the Current Population Survey's Outgoing Rotation Groups. We show that a decrease in labor productivity beginning in 2004, the "productivity slowdown," is understated by 23 percentage points when using aggregate hours instead of labor input to calculate productivity, and that 80% of the average quarterly growth rate of labor productivity can be attributed to increases in education and experience since 2004.