Man vs. Machine: An Investigation of Speeding Ticket Disparities Based on Gender and Race

This paper analyzes the extent to which police behavior in giving speeding tickets differs from the ticketing pattern of automated cameras. The automated tickets provide an estimate of the population of speeders at a given location, time, and even severity of the violation. The data, obtained from Lafayette, Louisiana, provides a wide range of details concerning characteristics of the violation such as location, date, time of day, legal speed, speed over the limit, day of the week, and also specific details about the ticketed driver. The probability of a ticketed driver being African-American or female is significantly higher when the ticket was given by a police officer in contrast to an automated source, implying that police use gender and race as a determining factor in issuing a speeding ticket. Potential behavioral reasons of this outcome have been discussed.

The Economics of Discrimination in the Court System: Police, Technology, and Their Interaction

This dissertation consists of three essays which utilize automated traffic enforcement data to investigate the existence of police discrimination in issuing speeding tickets and potential crime reduction as a secondary effect of using such programs. In the first chapter, I use tickets issued by automated traffic enforcement cameras as a measure of the population of speeders to compare with police-issued tickets. The novel dataset has an advantage over previous literature because data collection was not a result of suspected police bias. I find that a ticketed individual is more likely to be African-American and more likely to be female when ticketed by police as opposed to an automated camera. Though this implies some form of discrimination based on gender and race, it cannot be determined whether police are engaging in statistical or preference-based discrimination. Next, I extend the research question to determine whether the differential treatment of women and African-Americans by police should be characterized as preference-based or statistical discrimination. I use a detailed individual level dataset which follows individuals through the court process from receipt of a speeding ticket to trial. It seems that police are not engaging in statistical discrimination, because women and African-Americans are no more likely to immediately pay a speeding ticket. In fact, since African-Americans are actually more likely to attend a trial, police are targeting individuals who will utilize more court resources: contradictory to one motive of statistical discrimination. Individuals behave differently based on which judge they are assigned, but judges do not seem to be issuing fines discriminatorily. The final chapter aims to answer a different question regarding automated traffic enforcement: do automated traffic programs reduce crime? Many cities and companies which implement the automated systems cite crime reduction as a byproduct of adoption. They claim that these programs actually reduce crime rates by enabling police to focus on more serious offenders, increasing the marginal productivity of police. This is the first research to rigorously investigate these claims, and I find some supportive evidence, however, it seems that these companies may be exaggerating the extent of this effect

Do Driver Decisions in Traffic Court Motivate Police Discrimination in Issuing Speeding Tickets?

This research provides new insights into police discrimination by following individuals’ decisions in the court process from the time a speeding ticket is issued to trial. Quintanar (2011) finds that African-Americans and women are more likely to receive a speeding ticket from a police officer as opposed to an automated source, but is unable to determine whether this is evidence of statistical or preference-based discrimination. This paper expands upon those results by using a unique dataset which contains detailed information about the court procedural choices of individuals ticketed by police. African-Americans are more likely to fight their speeding ticket, while there is no significant behavioral difference by gender. This contradicts a motive of statistical discrimination by police; targeting individuals who are likely to pay immediately rather than use court resources to fight the ticket. Potential discrimination in prosecutor and judge behavior is also investigated.

Separately measuring home-field advantage for offenses and defenses: A panel-data study of constituent channels within collegiate American football

We improve constituent-channel estimates of home-field and neutral-site advantage for collegiate American football\u27s top division by utilizing a richer, 12-season data set and by exploiting the COVID-19 pandemic as a random shock. Novel to the literature, we separately examine points scored by each team, allowing us to identify impacts on each team\u27s offense and defense individually. The information set provided by our model is a strict superset of that provided by the previous standard in the literature, making ours a strictly dominant modeling choice. We demonstrate this improvement theoretically and empirically. Physiologically, away-team travel distance does not impact their own score, but it increases home-team scores, consistent with the notion that defenses tire faster than offenses. There is also similar but limited evidence of this effect for neutral-site teams. Time zones may play a minor role, too. Psychologically, crowd size and density hurt away-team scores but do not impact home or neutral-site teams. The away-team effect disappears in 2020, however, indicating that the pre-2020 effect is caused by the crowd\u27s noise, not their mere presence. We also find that increasing stadium capacity while holding crowd size constant hurts home-team scores, highlighting the importance of considering ticket demand when considering stadium expansion. Tactically, stadium familiarity helps offenses, not defenses, while team-opponent familiarity has the opposite effect. Weather also plays a role. At median values for key variables, we find an overall home-field advantage of 4.1 points

You are Close to Your Rival and Everyone Hates a Winner: A Study of Rivalry in College Football

We use a recent survey of college (American) football fans to study rivalry, where we find the most intense rivalries occur between in-state teams. Relatedly, within a conference fans are more likely to target rivalrous feelings toward the winningest teams and, in Bowl Championship Series conferences, teams who have been conference members for a longer proportion of time. While the stakes are different from other settings, such as warring nations, college football teams compete for resources and often have loyal followings with strong emotional ties. Thus, examining rivalrous feeling in this setting provides insights into rivalry more generally besides being of interest in its own right as college football is a multi-billion dollar industry