David Puelz 
CV | Google Scholar
Welcome to my website! I am a statistician and professor at UT Austin and The University of Austin (UATX). My research develops computational methods for applied data analysis, especially in economics + social + behavioral sciences.
My identical twin is an Assistant Professor at Baylor College of Medicine. His website can be found here.
Papers
Causal inference and randomizations
A Bayesian Classification Trees Approach to Treatment Effect Variation with Noncompliance, with J Fisher and S Deshpande, submitted (2024).
A Graph-Theoretic Approach to Randomization Tests of Causal Effects Under General Interference, with G Basse, A Feller, and P Toulis, Journal of the Royal Statistical Society, Series B (2022).
* R package under development.
* Chicago Booth Review video (below) and article.
Financial Literacy and Financial Well-being, with M Doh and R Puelz, submitted (2024).
Financial Literacy and Perceived Economic Outcomes, with R Puelz, Statistics and Public Policy (2022).
Regularization and Confounding in Linear Regression for Treatment Effect Estimation, with J He, PR Hahn, and C Carvalho, Bayesian Analysis (2018).
Bayesian methods
A Symmetric Prior for Multinomial Probit Models, with LH Burgette and PR Hahn, Bayesian Analysis (2021).
Monotonic Effects of Characteristics on Returns, with J Fisher and C Carvalho, Annals of Applied Statistics (2020).
Portfolio Selection for Individual Passive Investing, with PR Hahn and C Carvalho, Applied Stochastic Models in Business and Industry (2019).
Variable Selection in Seemingly Unrelated Regressions with Random Predictors, with PR Hahn and C Carvalho, Bayesian Analysis (2017).
Regularization in Econometrics and Finance, dissertation (2018).
Social science topics
The Disutility of Compartmental Model Forecasts during the COVID-19 Pandemic, with T Sudhakar, A Bhansali, and J Walkington, Frontiers in Epidemiology (2024).
Review of: “Firearm Purchasing and Firearm Violence in the First Months of the Coronavirus Pandemic in the United States”, with J Fisher, Rapid Reviews: COVID-19 (2020).
Medicine
Identification of High-risk Variables for Pediatric Patients with Anomalous Aortic Origin of the Right Coronary using Statistical Modeling, with C Puelz, D Reaves-O’Neal, and S Molossi, Journal of the American College of Cardiology (2024).
Talks
Randomization, Machine Learning, and Everything in Between. The University of Austin (2024) - New College of Florida (2024).
Randomization Tests of Causal Effects Under General Interference (slides + video). Salem Center Causal Inference Seminar - UT Austin (2022) / Society for Political Methodology Annual Meeting - NYU (2021) / International Indian Statistical Association (2021) / Arizona State University (2020) / The University of Chicago Booth School of Business - Econometrics and Statistics Seminar (2019) / Atlantic Causal Inference Conference - McGill University (2019) / International Conference on the Design of Experiments - University of Memphis (2019) / Society for Political Methodology Annual Meeting - MIT (2019) / Design and Analysis of Experiments - UT Knoxville (2019) / Advances with Field Experiments - Chicago Economics (2019).
A Flexible Model for Returns. Statistical Methods in Finance (2021) / Seminar on Bayesian Inference in Econometrics and Statistics - Brown University (2019) / Eastern Asia ISBA Conference - Kobe University (Japan, 2019) / The University of Chicago Booth School of Business - Research Workshop (2018).
Posterior Summarization in Finance. International Society for Bayesian Analysis World Meeting - University of Edinburgh (2018).
Regret-based Selection. Seminar on Bayesian Inference in Econometrics and Statistics - Washington University in St. Louis (2017).
Decoupling Shrinkage and Selection. Goldman Sachs. New York, NY (2016).
The ETF Tangency Portfolio. Seminar on Bayesian Inference in Econometrics and Statistics - Washington University in St. Louis (2015).
Betting Against β: A State-space Approach. UT McCombs. Austin, TX (2014).