Research Statement

While I am interested in a wide variety of topics, my research agenda primarily consists of applied microeconomics, specifically behavioral economics and health economics. Most of my behavioral interests center on examining the extent to which we can identify cognitive biases in decision-making in available data. My health research is joint with my colleague Joey Smith and, at a basic level, examines the extent to which alcohol affects crime using disaggregated data on different types of alcohol consumption (public vs. home) and a large panel data set on crime and consumption patterns. Finally, I occasionally explore other fields in economics and other disciplines, primarily because I have found that working with others in their fields has familiarized me with many strands of literature and research techniques that I would otherwise know nothing about. This increased awareness has helped me with my primary agenda.

Published/Accepted Work

Does the Hot Hand Drive the Market? Evidence from College Football Betting Markets (with Trevon Logan, accepted at Eastern Economic Journal)

Structuring a Bona-Fide Sale of Excess or Slow-Moving Inventory for Tax Purposes, (with Mark Wills and Bruce Bird, accepted at CPA Journal)

Working Papers

Identifying Confirmatory Bias in the Field: Evidence from a Poll of Experts (with Rodney Andrews and Trevon Logan, under review)
NBER Working Paper no. 18064

Laboratory experiments have established the existence of cognitive biases, but their explanatory power in real-world economic settings has been difficult to measure. We estimate the extent of a cognitive bias, confirmatory bias, among experts in a real-world environment. In the Associated Press Top 25 College Football Poll expert pollsters are tasked with assessing team quality, and their beliefs are treated week-to-week with game results that serve as signals about an individual team's quality. We exploit the variation provided by actual game results relative to market expectations to develop a novel regression-discontinuity approach to identify confirmatory bias in this real-world setting. We construct a unique personally-assembled dataset that matches more than twenty years of individual game characteristics to poll results and betting market information, and show that teams that slightly exceed and barely miss market expectations are exchangeable. The likelihood of winning the game, the average number of points scored by teams and their opponents, and even the average week of the season are no different between teams that slightly exceed and barely miss market expectations. Pollsters, however, significantly upgrade their beliefs about a team's quality when a team slightly exceeds market expectations. The effects are sizeable-- nearly half of the voters in the poll rank a team one slot higher when they slightly exceed market expectations; one-fifth of the standard deviation in poll points in a given week can be attributed to confirmatory bias. This type of updating suggests that even when informed agents make repeated decisions they may act in a manner which is consistent with confirmatory bias.

How Do Experts Use Bayes' Rule? Lessons from a Non-Market Environment (revisions requested at Journal of Socio-Economics)

Experts are regularly relied upon to provide their professional assessments in a wide array of markets (e.g., asset pricing, stock and bond ratings, expert witnesses, forecasting), which frequently have characteristics that may generate incentives for experts to provide biased analyses. I ask how consistent experts' assessments are to Bayes' rule in a relatively simple environment devoid of market incentives. Using data from the Associated Press (AP) Top 25 Poll for college football I find that many standard sets of Bayesian beliefs are rejected by the data, and that experts, while using Bayes' rule may still be subject to similar psychological biases as non-experts, namely Bayesian reassessment and confirmatory bias. In more complex environments, experts may have strong incentives to substantially deviate from Bayes' rule, biasing expert predictions in unknown directions.

Like Mike or Like LeBron? Do the Most Able Need College to Signal? (with Benjamin C. Anderson)

Do individuals with demonstrably high ability need to attend college to further signal their ability to potential employers? We examine the labor market entry decision for basketball players deciding to enter or return to college versus entering the labor market for professional basketball, specifically the National Basketball Association (NBA). Individuals in this market have significant financial incentive to forgo further schooling in order to pursue their careers immediately and therefore face a trade-off between possible immediate financial rewards and the acquisition of additional skill-related human capital or improving the signals regarding own productivity. We exploit the variation generated from three exogenous ability rankings of college prospects, the Scout 100, Rivals 150, and ESPN 100, in order to document three key findings related to signaling and human capital accumulation. First, we find that players who were ranked as being of high ability before entering college systematically pursue fewer years of schooling than those who were not. Next, among those signaled to be most able, individuals who are ranked more highly - indicating the highest ability levels - are less likely to accumulate significant amounts of skill-specific human capital, as they opt to be professionals more quickly than those ranked less highly. Finally, we find that exogenous signals of ability are highly informative to potential employers. After controlling for other possible determinants of player quality, whether a player was identified as being of high ability in high school is both an economically and statistically significant determinant of draft position.

Do Social Settings Affect Sexual Assault Prevalence? Evidence from Texas Alcohol Consumption (with Joey Smith, e-mail for a copy)

A large psychology and health literature suggests a relationship between alcohol and sexual assaults, but little is known about the exact relationship. We expand on this literature by decomposing alcohol into both measures of consumption and availability in order to better understand which components of alcohol are important determinants of sexual assaults. To estimate this relationship, we match a unique panel data set which contains the total amount of alcohol sales and total number of package outlets and bars from the Texas Alcoholic Beverage Commission to individual-level crime incident reports from the NIBRS. We find that private settings are substantially more risky; in particular, we find a positive and statistically significant impact of alcohol sales from liquor stores on the number of sexual assaults, but do not find any relationship between alcohol sales from mixed-drink establishments. We interpret our estimates as a lower bound of the relationship, since sexual assaults are substantially underreported.