SDS Seminar Series – Rafael Campello de Alcantara, University of Texas at Austin
Oct
3
2025
Oct
3
2025
Description
The Fall 2025 SDS Seminar Series continues on October 3rd from 2:00 p.m. to 3:00 p.m. with Dr. Rafael Campello de Alcantara (Postdoctoral Fellow, Department of Statistics and Data Sciences, University of Texas at Austin). This event is in-person in the Avaya Room (POB 2.302).
Title: Searching for Parallel Trends: A Decision Tree Algorithm for Discovering Conditional Diff-in-Diff Estimators
Abstract: Difference-in-differences (DiD) designs represent one of the most common empirical strategies for learning treatment effects in the social sciences. The most basic DiD design consists of two periods and two groups. In the first period, both groups are not treated, while only one of the groups receive treatment in the second period. Identification in that setting relies crucially on the parallel trends assumptio: on average, the outcomes of the treated and untreated groups evolve following the same trend. Typically, two versions of PTA are considered in the literature. On one extreme, PTA is invoked unconditionally. On the other extreme, much of the literature invokes PTA for every possible covariate value. We discuss identification in the intermediate ( and potentially more realistic) case where PTA holds only for some subsets of the covariate space. Importantly, in that scenario, it is likely that none of the commonly targeted causal estimands are identified. Then, we draw on placebo tests for DiD to design an algorithm that uses auxiliary data to search for regions of the covariate space where PTA can be assumed to hold. The regions flagged by our algorithm can then be used to learn about conditional effects on the data set we are interested in.
Other Events in This Series
Oct
4
2024
SDS Seminar Series – Huiyan Sang, Texas A&M University
GS-BART: Graph Split Additive Decision Trees for Spatial and Network Data
2:00 pm – 3:00 pm • In Person
Speaker(s): Huiyan Sang
Oct
11
2024
SDS Seminar Series – Mingyuan Zhou, University of Texas at Austin
Building Faster, Better, and Safer Deep Generative Models via Score Identity Distillation
2:00 pm – 3:00 pm • In Person
Speaker(s): Mingyuan Zhou
Oct
18
2024
SDS Seminar Series – Sherry Zhang, University of Texas at Austin
Pivoting between Space and Time: Spatio-Temporal Analysis with Cubble
2:00 pm – 3:00 pm • In Person
Speaker(s): Sherry Zhang
Oct
25
2024
SDS Seminar Series – Matt Koslovsky, Colorado State University
Sparse Dirichlet-Multinomial Models
2:00 pm – 3:00 pm • In Person
Speaker(s): Matt Koslovsky
Nov
1
2024
SDS Seminar Series – Aaditya Ramdas, Carnegie Mellon University
A Game-Theoretic Theory of Statistical Evidence
2:00 pm – 3:00 pm • In Person
Speaker(s): Aaditya Ramdas
Nov
8
2024
SDS Seminar Series – Myungsoo Yoo, University of Texas at Austin
Dynamic Spatio-Temporal Model Integrating Physics for Fire Front Propagation
2:00 pm – 3:00 pm • In Person
Speaker(s): Myungsoo Yoo
Nov
15
2024
SDS Seminar Series – Rafael Irizarry, Harvard University
Twenty-Five Years of Data Science: Music, Genomics, and Public Health Surveillance
2:00 pm – 3:00 pm • In Person
Speaker(s): Rafael Irizarry
Mar
7
2025
SDS Seminar Series - Arun Kuchibhotla, Carnegie Mellon University
Adaptive Inference Techniques for Some Irregular Problems
2:00 pm – 3:00 pm • In Person
Speaker(s): Arun Kuchibhotla
Mar
28
2025
SDS Seminar Series – Po-Ling Loh, University of Cambridge
Differentially Private M-estimation via Noisy Optimization
2:00 pm – 3:00 pm • In Person
Speaker(s): Po-Ling Loh
Apr
18
2025
SDS Seminar Series – Richard Samworth, University of Cambridge
How Should We Do Linear Regression?
2:00 pm – 3:00 pm • In Person
Speaker(s): Richard Samworth