Dustin White, PhD

Assistant Professor. Economics. University of Nebraska at Omaha.

Equilibrium Game

Moneyball Simulator

March Madness: NCAA Tournament Participation and College Alcohol Use

While athletic success may improve the visibility of a university to prospective students and thereby benefit the school, it may also increase risky behavior in the current student body. Using the Harvard School of Public Health College Alcohol Study, we find that a school's participation in the NCAA Basketball Tournament is associated with a 47% increase in binge drinking by male students at that school. Additionally, we find evidence that drunk driving increases by 5% among all students during the tournament. (JEL I12, I23, Z28)

Improved grade outcomes with an e-mailed “grade nudge”

Information provided at the moment a person makes a decision can influence behavior in predictable ways. The United Kingdom's Behavioural Insights Team have used this idea to help improve the insulation of lofts, collect taxes, and even reduce litter. The authors of this article developed software that appends a personalized message to each assignment in the class regarding the student's current grade. This “grade nudge” explains precisely how the assignment will impact the student's final grade given their current standing in the class. Through a randomized trial, the authors show that the nudge improves student homework performance by about four percentage points.

The effects of merit-based financial aid on drinking in college

We study the effect of state-level merit aid programs (such as Georgia's HOPE scholarship) on alcohol consumption among college students. Such programs have the potential to affect drinking through a combination of channels – such as raising students’ disposable income and increasing the incentive to maintain a high GPA – that could theoretically raise or lower alcohol use. We find that the presence of a merit-aid program in one's state generally leads to an overall increase in (heavy) drinking. This effect is concentrated among men, students with lower parental education, older students, and students with high college GPA's. Our findings are robust to several alternative empirical specifications including event-study analyses by year of program adoption. Furthermore, no difference in high-school drinking is observed for students attending college in states with merit-aid programs.

An In-Class Experiment to Teach Marginal Revenue Product Using the Baseball Labor Market and Moneyball

The baseball labor market captured the imagination of the public following the release of the film Moneyball in 2011, based on the Michael Lewis book of the same name (Lewis, 2003). Under strong assumptions, the marginal product of labor in the baseball labor market can be calculated as a function of observable statistics recorded during the course of each baseball game. It is rare for production statistics to be publicly observable in almost any market, making the baseball labor market an excellent way to introduce students to concepts that can be applied to labor markets at large.

In order to improve students’ understanding of the principles of labor markets, we developed the project presented below. Our objectives in creating this project were to:(1) teach marginal revenue product (MRP) through an exciting exercise;(2) use real data to teach practical analysis using spreadsheets and trend lines to demonstrate marginal effects; and (3) show the workings of a simplified labor market with a simulation.

Agency Theory and Work from Home

Wages for individuals working from home have converged toward, and even exceeded, those of office‐workers. I argue that these changes are driven by the ability of firms to monitor employees working from home. Using American Community Survey and Census data spanning 1980–2014, I find wage differentials have shifted from a 26 per cent penalty in 1980 to a 5 per cent premium in 2014. Furthermore, I find that higher wage variance (44 per cent greater in 1980) for home‐workers disappears by 2013. Changes in variance suggest that the falling cost of monitoring employee effort has made it less costly for firms to allow work from home. These findings support agency theory as a driver of the changes in wages and wage structure for individuals working from home.

Improving Student Performance through Loss Aversion

As shown by Tversky and Kahneman (1991), framing an outcome as a loss causes individuals to expend extra effort to avoid that outcome. Since classroom performance is a function of student effort in search of a higher grade, we seek to use loss aversion to encourage student effort. This field experiment endows students with all of the points in the course upfront, then deducts points for every error throughout the semester. Students perform three to four percentage points better when controlling for student ability and domain knowledge. This result is significant at the 1% level in our most robust specification.

Network Externalities and Friendly Neighbors: When Firms Choose to Invite Competition

Economic theory on the subject of barriers to entry focuses almost exclusively on firms seeking to preserve market power and economic profits. In this paper, we propose that, under certain circumstances, firms may instead choose to reduce barriers to entry as a profit-maximizing mechanism. We model this behavior and show that, under certain conditions, profit can increase for some existing firms as the number of firms in the industry increases. We provide evidence of this behavior from three distinct industries: personal computers, non-petroleum cars and professional American football.

On Guessing: An Alternative Adjusted Positive Learning Estimator and Comparing Probability Misspecification with Monte Carlo Simulations

Instructors and researchers have used the ‘flow’of knowledge (post-test score minus pre-test score) to measure learning in the classroom for the past fifty years. Walstad and Wagner (2016) and Smith and Wagner (2018) move this practice forward by disag-gregating the flow of knowledge and accounting for student guessing. These estimates are sensitive to misspecification of the probability of guessing correct. This work provides guidance to practitioners and researchers facing this problem. We introduce a transformed measure of true positive learning that under some knowable conditions performs better when students’ ability to guess correctly is misspecified. This measure converges to Hake’s (1998) under certain conditions. We then use simulations to compare the accuracy of two estimation techniques under various violations of the assumptions of those techniques. Using recursive partitioning trees fitted to our simulation results, we provide the practitioner concrete guidance based on a set of yes/no questions.

Courses I Teach

Links and info about my classes.

Business Forecasting

Covers time-series and predictive models relevant for forecasting in a business environment. Models implemented in Python.

Tools for Data Analysis

Learn the basics of programming with respect to data. Learn to collect and clean data in preparation for analysis using Python and open-sourse libraries.

Sports Economics

Economics is everywhere. We apply various economic models to problems encountered in sports and in the business of sports.

Business Intelligence and Reporting

Learn to communicate clearly with data. We emphasize creating clear communication that can be shared with both technical and non-technical audiences.

Business Analytics

Learn to understand the importance of data in modern business applications. We cover critical concepts being used in nearly all sectors, and ensure that future leaders have the ability to understand how careful data analysis leads to improved business outcomes.

Principles of Microeconomics

Learn about how people make choices. We will learn how people choose what to buy, what to sell, or even when to lie!

About Me

Hey there! I am Dusty White, and I love mixing data with economics! I did my PhD at Washington State University, and have been working at the University of Nebraska at Omaha since I graduated in 2016. My research is all over the place... I love asking interesting questions, and I like to ask them no matter which topics they relate to. Some of my more recent projects have to do with testing the responses of students to nudges (in both the short and long term), exploring the relationship between working from home and wages, and measuring alcohol consumption on college campuses around major sporting events. When I am not at work, I love spending time with my wife, Mindy, and our four kids (Lily, Charlie, Victoria, and Eleanor) going on bike rides, camping in the backyard, and answering crazy questions that kids ask.