Booth’s Panos Toulis suggests a statistical method that can help officials arrive at more accurate infection counts.What Percentage of the Population Has Contracted COVID-19?
Academic Areas Econometrics and Statistics Faculty and Research
Chicago Booth is a community that is full of analytical thinkers who believe data leads to discoveries.
In our econometrics and statistics academic area, Booth faculty teach students how to analyze business and economic problems by leveraging vast amounts of data using economic, mathematical, and computer techniques.
Our faculty members’ groundbreaking research in this area covers a broad spectrum—from the uses of high-dimensional data and methods in economics applications to the development of robust forecast evaluation methodologies. Some of this research has led to our faculty winning prestigious awards: Dacheng Xiu was awarded the 2018 AQR Insight Award; Ruey S. Tsay won John Wiley and Sons Author of the Year for his book Analysis of Financial Time Series; Tengyuan Liang and Veronika Rockova are recipients of NSF CAREER awards; Max Farrell was the winner of Political Methodology’s Best Statistical Software Award; and Panagiotis Toulis was the recipient of the LinkedIn Economic Graph Challenge award.
Econometrics and statistics professors at Booth are regularly published in top journals, including American Economic Review; Annals of Statistics; Biometrika; Econometrica; Journal of the American Statistical Association; Journal of Machine Learning Research; Journal of Political Economy; Journal of the Royal Statistical Society: Series B; and Review of Economic Studies.
Some faculty in this area are also active at a number of top machine learning conferences, including COLT, NeurIPS, AISTATS, and ICML. Many are active in organizations and initiatives, including in the American Statistical Association and the Becker Friedman Institute for Economics’ Big Data Initiative.
Econometrics and Statistics Faculty
Booth is home to preeminent scholars of econometrics and statistics, who regularly incorporate their research into the classroom.
Courses such as Big Data teach students how to model and interpret complicated datasets by leveraging a number of techniques, including linear and logistic regression, model choice and false discovery rates, and multinomial and binary regression, among others. In other courses such as Machine Learning, students learn how machine learning can be used to create value and provide insights from data. In this course, students learn about decision trees, nearest neighbor classifiers, boosting, random forests, deep neural networks, naive Bayes, and support-vector machines.
Other courses such as Analysis of Financial Time Series leverage real-world examples to teach students to analyze financial and macroeconomic data, while Statistical Insight into Marketing, Consulting, and Entrepreneurship leverages econometrics to give future consultants and entrepreneurs important tools and methodologies they can leverage in their careers.
Discover more about our econometrics and statistics faculty, including the classes they teach, below.
Awards and Honors
“We’re not saying those 300 factors are fake. It may be true that some deliver significant risk premia for investors. But they could also be simply duplicating a few other important factors.”
Dacheng Xiu, commenting on his paper, “Taming the Factor Zoo,” for which he and his two coauthors won the 2018 AQR Insight Award. Booth’s Brent Neiman was also a recipient of the same award in 2018 for a separate paper.Awards and Honors
Research with Impact
Recent research from Max Farrell, along with two Booth colleagues, Tengyuan Liang and Sanjog Misra, quantifies the uncertainty that arises when a business leader uses machine learning to analyze data and make a decision on the basis of that analysis. One particular aspect of machine learning, deep learning, has become common in business. What Professor Farrell and his Booth colleagues uncovered could have broad applications—potentially in hospitals, where doctors need to make life-and-death decisions.Research with Impact
Partnering across the University of Chicago and Beyond
Our econometrics and statistics faculty members are active in and outside of the University of Chicago.
Max Farrell, Christian B. Hansen, Tetsuya Kaji, Mladen Kolar, Tengyuan Liang, Veronika Rockova, and Panos Toulis are each UChicago Scholars at the Becker Friedman Institute’s Big Data Initiative, which uses consumer and business data to improve decision-making. Jeffrey R. Russell is an associate editor of the Journal of Business and Economic Statistics. Ruey S. Tsay is a fellow of the American Statistical Association, the Institute of Mathematical Statistics, the Royal Statistical Society, and Academia Sinica.
Discover some of the latest working papers and published papers from our econometrics and statistics faculty.
“Pre-Event Trends in the Panel Event-Study Design”
Christian B. Hansen, with coauthors Simon Freyaldenhoven (Federal Reserve Bank of Philadelphia) and Jesse M. Shapiro (Brown University)
“Lasso Meets Horseshoe: A Survey”
Nicholas Polson, with coauthors Anindya Bhadra (Purdue University), Jyotishka Datta (University of Arkansas at Fayetteville), and Brandon Willard (University of Chicago)
“The Art of BART: On Flexibility of Bayesian Forests”
Veronika Rockova, with coauthor Seonghyun Jeong (University of Chicago, Principal Researcher, Chicago Booth)
This center supports researchers from across Booth and UChicago in making revolutionary advances in the applications of A.I. Their work touches fields as diverse as finance, health care, public policy, education, and behavioral science.Center for Applied Artificial Intelligence