3 papers
stat.ME2026
Machine-Learning-Powered Specification Testing in Linear Instrumental Variable Models
Cyrill Scheidegger, Malte Londschien, Peter Bühlmann
The linear instrumental variable (IV) model is widely used in observational studies, yet its validity hinges on strong assumptions. Classical specification tests such as the Sargan…
math.ST2026
Weak-instrument-robust subvector inference in instrumental variables regression: A subvector Lagrange multiplier test and properties of subvector Anderson-Rubin confidence sets
Malte Londschien, Peter Bühlmann
We propose a weak-instrument-robust subvector Lagrange multiplier test for instrumental variables regression. We show that it is asymptotically size-correct under a technical condi…
stat.ME2026
Inference for Heterogeneous Treatment Effects with Efficient Instruments and Machine Learning
Cyrill Scheidegger, Zijian Guo, Peter Bühlmann
We introduce a new instrumental variable (IV) estimator for heterogeneous treatment effects in the presence of endogeneity. Our estimator is based on double/debiased machine learni…