September 28, 2025Open Access

A statistician's guide to weak-instrument-robust inference in instrumental variables regression with illustrations in Python

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Weak-instrument-robust inference enhances estimation reliability in regression models, minimizing biases.
Key results highlight the efficacy of using the ivmodels package in Python for robust analyses.
Implementation of these methods supports accurate inference in settings with weak instruments, improving research outcomes.
Practical illustrations in Python serve as a user-friendly guide for applying these statistical techniques.

Implication

The study demonstrates weak-instrument-robust inference in instrumental variables regression, indicating practical implementations in Python.

Abstract

We provide an overview of results relating to estimation and weak-instrument-robust inference in instrumental variables regression. Methods are implemented in the ivmodels software package for Python, which we use to illustrate results.

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Cite This Study

Malte Londschien (2025) studied this question.

synapsesocial.com/papers/68d913a34ddcf71ba560b845 https://doi.org/10.48550/arxiv.2508.12474

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Implication

The study demonstrates weak-instrument-robust inference in instrumental variables regression, indicating practical implementations in Python.

A statistician's guide to weak-instrument-robust inference in instrumental variables regression with illustrations in Python

Key Points

Implication

Abstract

Discussion

Cite This Study

A statistician's guide to weak-instrument-robust inference in instrumental variables regression with illustrations in Python

Key Points

Implication

Abstract

Discussion

Cite This Study

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