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David Puelz

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A Bayesian Semiparametric Approach to Treatment Effect Variation with Noncompliance

Jared Fisher (BYU) joins us to discuss estimating varying treatment effects in randomized trials with noncompliance is inherently challenging since variation comes from two separate sources: variation in the impact itself and variation in the compliance rate. In this setting, existing Frequentist and ML-based methods are quite flexible but are highly sensitive to the so-called […]

Call for Research Assistants: Policy Research Laboratory Fall 2022

Call for Research Assistants: Policy Research Laboratory Fall 2022 The Salem Center for Policy at McCombs is looking for outstanding, curious, and driven students to participate in the Policy Research Laboratory (PRL) in Fall 2022. Students will take a semester-long course in statistics, econometrics, and data science to learn the tools necessary for policy and […]

A graph-theoretic approach for testing causal effects under interference.

David Puelz from UT Austin and the Salem Center presents an approach for randomization tests of causal effects under general forms of interference.  The key idea is to represent a null hypothesis of spillovers as a bipartite graph and condition the test on a biclique in this graph. The approach is completely algorithmic and is […]

David Puelz

David Puelz is the Director of Policy Analytics for the Salem Center and a Clinical Assistant Professor in the McCombs School of Business. His research develops computational methods for applied data analysis, especially in social and behavioral sciences.