4 papers
Inference for Fixed Effects Estimators when Panels are Unbalanced
Daniel Czarnowske, Amrei Stammann
We develop the asymptotic theory for two-way fixed effects M-estimators in unbalanced panels, within a framework where both panel dimensions grow large at proportional rates. The s…
Inference in Unbalanced Panel Data Models with Interactive Fixed Effects
Daniel Czarnowske, Amrei Stammann
We derive the asymptotic theory of Bai (2009)'s interactive fixed effects estimator for unbalanced panels in which the source of attrition is conditionally random. For inference, w…
(Debiased) Inference for Fixed Effects Estimators with Three-Dimensional Panel and Network Data
Daniel Czarnowske, Amrei Stammann
Inference for fixed effects estimators is often unreliable due to Nickell- and incidental parameter biases. While these issues are well understood for classical two-dimensional pan…
The Effects of Flipped Classrooms in Higher Education: A Causal Machine Learning Analysis
Daniel Czarnowske, Florian Heiss, Theresa M. A. Schmitz +1
This study uses double/debiased machine learning (DML) to evaluate the impact of transitioning from lecture-based blended teaching to a flipped classroom concept. Our findings indi…