Investigating Causal Inference of Policies: Ban the Box on Employment, Wage Transparency on Wage Gap, and DNA Databases on Serious Crimes
This dissertation is a collection of three chapters that investigate selected policy issues and their broader implications, specifically focusing on the causal inference of policies. Ban the Box on employment, Wage Transparency on wage gaps, and DNA databases on serious crimes. Chapter 1 - Ban the Box (BTB) policies move the inquiry about the candidate’s criminal record to later in the hiring process. The intention of this policy is to have employers evaluate the candidates based on their performance on the interview and qualifications instead of their criminal history. In this paper, we will study the effect of Ban the Box policy on employment for young men with no college degree in United States. We find that in the metropolitan areas where the policy was implemented, there is a negative effect on employment for unskilled young men; however, we are unable to conclude that these policies negatively impacted employment of unskilled young Black and Hispanic men with strong confidence. Chapter 2 - Gender-based wage disparities persist in the United States, despite significant strides toward workplace equality. This study investigates the wage gap, emphasizing the urgency of addressing this issue. Drawing on research by Blau and Khan (2017), we examine the extent of gender pay inequality and its implications for full-time private sector employees. In response to these disparities, legislative changes have been implemented at both the state and city levels. In particular, Ohio has proactively mandated wage transparency for firms in two of its metropolitan areas. This paper examines the impact of such legislation in two major cities in Ohio: Cincinnati (implemented in March 2020) and Toledo (implemented in June 2020). We find that the wage transparency policy in Ohio has a significant positive effect on female employees, resulting in a 4.8% increase in their income levels, while it has a significant negative effect on male employees, with a 6% decrease in their incomes. Furthermore, among female employees, white women are the only group positively impacted by the policy, while racial minority women experience no statistically significant change in their incomes. Among the male population, the incomes of non-white male employees are reduced by a higher percentage than those of their white counterparts. This suggests that, although the policy has reduced the gender wage gap, it has not addressed the gap between racial minority groups. Chapter 3 - In 2007, Orange County, California, implemented a DNA collection system that expanded its scope to include minor crimes, setting it apart from the statewide approach. Using the Synthetic Difference in Differences methodology, our study investigates the long-term causal effects of this policy on serious crime rates. Our analysis utilizes data from the Uniform Crime Reporting (UCR) system and the American Community Survey (ACS) spanning 2000 to 2018. The results reveal sustained reductions in violent crime, robbery, and burglary rates. Specifically, we observed decreases of approximately 122 violent crimes, 23 robberies, and 103 burglaries per 10,000 people due to the implementation of the DNA system. In contrast, the rates of assault, theft, and rape consistently showed increases, highlighting the policy’s complex and varied impacts. The results for other serious crime types were inconsistent or too small to indicate any significant effect. Despite these mixed findings, our study demonstrates the potential efficacy of DNA databases in reducing certain serious crimes. These findings provide valuable insights into the broader implications of such policies and contribute to the existing literature by emphasizing the local impact of DNA systems on crime rates. While the policy primarily focused on lower-level offenses, our hypothesis that the presence of DNA data may deter individuals from committing more serious crimes over time (rather than in the short term) is supported by our results.
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