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Category Archives: K42

Patrolling the Future: Unintended Consequences of Predictive Policing in Chicago

By Jenny Jiao   

In the past decade, police departments have increasingly adopted predictive policing programs in an effort to identify where crimes will occur and who will commit them. Yet, there have been few empirical analyses to date examining the efficacy of such initiatives in preventing crime. Using police and court data from the second-largest police department in the country, this paper seeks to evaluate the pilot version of Chicago’s Strategic Subject List, a person-based predictive policing program. Using a boundary discontinuity design, I find that individuals eligible for the Strategic Subject List were 2.07 times more likely to be found not guilty of all charges in court than similarly situated individuals in the control group. Taking into account crime category heterogeneity, I find evidence that individuals previously arrested for drug crimes drive this result. This research sheds light on the potential unintended consequences of person-based predictive policing.

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Advisors: Professor Patrick Bayer, Professor Bocar Ba | JEL Codes: K4, K42, O33

Does Media Coverage of Sexual Assault Cases Cause Victims to Go to the Police? Evidence from FBI Data and Google Trends

By Harry Elworthy

This paper investigates the effect that national news coverage of prominent sexual assaults has on the reporting decisions of sexual assault victims. Estimates are based on time series data of reports made to police stations in the US from 2008 to 2016 and Google Trends data of search volume, along with an identification strategy that uses a number of individual high profile sexual assault allegations and related events as instruments. By removing assaults that occurred on the day that they were reported, I estimate the effect of coverage only on the reporting of assaults, and not on assaults themselves. A significant positive effect of news coverage on sexual assault reporting is found using several specifications. Back-of-the-envelope calculations suggest that there were between 31 and 121 additional reports of sexual assault for each of the 38 high profile events captured. No evidence is found to suggest that these additional reports of sexual assault have different arrest rates to other reports, indicating that there are not a significant number of false reports. This paper adds to current literature on the sexual assault reporting decision by considering the effect of news coverage and by using different methods of inference to previous papers.

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Advisor: Professor Patrick Bayer | JEL Codes: D91, J16, K42, L86, Z13

Security Without Equity? The Effect of Secure Communities on Racial Profiling by Police

By Jack Willoughby

Anecdotal and circumstantial evidence suggest that the implementation of Secure Communities, a federal program that allows police officers to more easily identify illegal immigrants, has increased racial bias by police. The goal of this analysis is to empirically evaluate the effect of Secure Communities on racial bias by police using motor vehicle stop and search data from the North Carolina State Bureau of Investigation. This objective differs from most previous research, which has largely attempted to quantify racial profiling for a moment in time rather than looking at how an event influences racial profiling. I examine the effects of Secure Communities on police treatment of Hispanics vs. whites with an expanded difference-in-difference approach that looks at outcomes in
motor vehicle search success rate, search rate conditional on a police stop, stop rate, and police action conditional on stop. Statistical analyses yield no evidence that the ratification of Secure Communities increased racial profiling against Hispanics by police. This finding is at odds with the anecdotal and circumstantial evidence that has led many to believe that the ratification of Secure Communities led to a widespread increase in racial profiling by police, a discrepancy that should caution policy makers about making decisions driven by stories and summary statistics.

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Advisor: Frank Sloan | JEL Codes: J15, K14, K37, K42 | Tagged: Racial Policing, Bias, Immigration Law, Secure Communities

Marijuana Pricing Structure and State-Level Price Determinants

By Rebecca Li

This study uses the PriceofWeed.com data set first examined in Thies (2012) to analyze the price-quantity relationship for marijuana transactions and to determine the effect of various state-level factors on marijuana prices. By applying the cost-based full fixed cost recovery pricing model developed by Britney, Kuzdrall, and Fartuch (1983), this paper finds support for an inverse price-quantity relationship for marijuana rather than a logarithmic or linear relationship. User-rated quality is robust and significant across all models, and price-quantity discount elasticity of -0.220 is observed empirically. An analysis of state-level legal, demand-side, and supply-side determinants of marijuana price demonstrates that medical marijuana has a negative relationship with price, perhaps due to the reduction in risk faced by suppliers when medical marijuana is legalized.

Honor’s Thesis

Data Set

Advisor: Michael Munger, Phil Cook | JEL Codes: D04, I18, K42 | Tagged: Marijuana, Price, Quality, Transaction Size

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