Hunter Johnson

I am a Ph.D. candidate in economics at Claremont Graduate University.

Research Interests

I am interested in the criminal justice procedure and how discrimination and disparities affect public safety outcomes. My recent research pertains to how differences in the composition of law enforcement affect outcomes related to crime rates, arrests, and the use of force.




Estimating Effects of Affirmative Action in Policing: A Replication and Extension of Previous Research

International Review of Law and Economics, Forthcoming, (2019) (with M. Garner and A. Harvey)

This paper examines whether externally-imposed affirmative action plans in police departments have impacted the rates of reported offenses and/or offenses cleared by arrest. Using a series of modern econometric strategies, including difference-in-differences decomposition and generalized synthetic controls, we do not find a significant effect of court-imposed affirmative action plans on the rates of reported offenses or reported offenses cleared by arrest.

Using Machine Learning to Predict Earnings Per Share for Technology Companies

Working Paper

I use machine learning methods to predict earnings per share (EPS) for technology companies. The predictions from the machine learning methods are then compared to earnings forecasts from professional analysts. The goal is to outperform the predictions made by the analysts. Since I am interested primarily in prediction, the basis for comparison between analyst estimates and my machine learning estimates is root mean squared error (RMSE).