Work

Rethinking Nonlinear Instrumental Variable Models through Prediction Validity.

Year: 2022

Type: article

Abstract: . Prediction validity checks that error terms - which should be independent from the instrument - cannot be modeled with machine learning any better than a model that is identically zero. We use prediction validity to develop both one-stage and two-stage approaches for IV, and demonstrate their performance on an example relevant to climate change policy.

Source: PubMed

Authors: Chunxiao Li, Cynthia Rudin, Tyler H McCormick

Institutions: Duke University, University of Washington

Language: English

Topic: Advanced Causal Inference Techniques

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

Open Access status: green

Funder: National Institute of Mental Health

Award: Big Data, Big Models, and Big Bias?: A decision making framework for vital rate estimates based on extrapolation

OpenAlex ID: W4404162872

FWCI: 0.354

Cites: 8

Cited by: 2

Related to: 10