[2603.25509] Conformal Prediction for Nonparametric Instrumental Regression

Economics > Econometrics arXiv:2603.25509 (econ) [Submitted on 26 Mar 2026] Title:Conformal Prediction for Nonparametric Instrumental Regression Authors:Masahiro Kato View a PDF of the paper titled Conformal Prediction for Nonparametric Instrumental Regression, by Masahiro Kato View PDF HTML (experimental) Abstract:We propose a method for constructing distribution-free prediction intervals in nonparametric instrumental variable regression (NPIV), with finite-sample coverage guarantees. Building on the conditional guarantee framework in conformal inference, we reformulate conditional coverage as marginal coverage over a class of IV shifts $\mathcal{F}$. Our method can be combined with any NPIV estimator, including sieve 2SLS and other machine-learning-based NPIV methods such as neural networks minimax approaches. Our theoretical analysis establishes distribution-free, finite-sample coverage over a practitioner-chosen class of IV shifts. Subjects: Econometrics (econ.EM); Machine Learning (cs.LG); Applications (stat.AP); Methodology (stat.ME); Machine Learning (stat.ML) Cite as: arXiv:2603.25509 [econ.EM]   (or arXiv:2603.25509v1 [econ.EM] for this version)   https://doi.org/10.48550/arXiv.2603.25509 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Masahiro Kato [view email] [v1] Thu, 26 Mar 2026 14:45:30 UTC (302 KB) Full-text links: Access Paper: View a PDF of the paper titled Conformal Prediction for Nonparametric Instrument...