Possibilistic Instrumental Variable Regression
Methodology
2026-01-22 v2 Econometrics
Statistics Theory
Statistics Theory
Abstract
Instrumental variable regression is a common approach for causal inference in the presence of unobserved confounding. However, identifying valid instruments is often difficult in practice. In this paper, we propose a novel method based on possibility theory that performs posterior inference on the treatment effect, conditional on a user-specified set of potential violations of the exogeneity assumption. Our method can provide informative results even when only a single, potentially invalid, instrument is available, offering a natural and principled framework for sensitivity analysis. Simulation experiments and a real-data application indicate strong performance of the proposed approach.
Cite
@article{arxiv.2511.16029,
title = {Possibilistic Instrumental Variable Regression},
author = {Gregor Steiner and Jeremie Houssineau and Mark F. J. Steel},
journal= {arXiv preprint arXiv:2511.16029},
year = {2026}
}