David Puelz 
CV | Google Scholar
Welcome to my website! I am a statistician and professor at 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 The University of Houston. His website can be found here.
Papers
Causal inference and randomizations
Heterogeneous Treatment Effect Estimation under Noncompliance with Bayesian Tree Ensembles, with J Fisher and S Deshpande, submitted (2025).
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).