7 papers
Safe and Sharp Honest Inference for Nonparametric Estimation via Empirical Bernstein Calibration
Zihao Yuan, Sven Klaassen, Holger Dette
Honest confidence intervals for nonparametric estimators usually need to balance two competing goals: uniformly small undercoverage over a prescribed smoothness class and interval…
Adventures in Demand Analysis Using AI
Philipp Bach, Victor Chernozhukov, Sven Klaassen +3
This paper advances empirical demand analysis by integrating multimodal product representations derived from artificial intelligence (AI). Using a detailed dataset of toy cars on t…
Causal explanations of outliers in systems with lagged time-dependencies
Philipp Alexander Schwarz, Johannes Oberpriller, Sven Klaassen
Root-cause analysis in controlled time dependent systems poses a major challenge in applications. Especially energy systems are difficult to handle as they exhibit instantaneous as…
Effect Identification and Unit Categorization in the Multi-Score Regression Discontinuity Design with Application to LED Manufacturing
Philipp Alexander Schwarz, Oliver Schacht, Sven Klaassen +2
RDD (Regression discontinuity design) is a widely used framework for identifying and estimating causal effects at the cutoff of a single running variable. In practice, however, dec…
Sensitivity Analysis for Causal ML: A Use Case at Booking.com
Philipp Bach, Victor Chernozhukov, Carlos Cinelli +4
Causal Machine Learning has emerged as a powerful tool for flexibly estimating causal effects from observational data in both industry and academia. However, causal inference from…
Sensitivity Analysis for Treatment Effects in Difference-in-Differences Models using Riesz Representation
Philipp Bach, Sven Klaassen, Jannis Kueck +2
Difference-in-differences (DiD) is one of the most popular approaches for empirical research in economics, political science, and beyond. Identification in these models is based on…