Work

Simple Tests for Selection: Learning More from Instrumental Variables

Year: 2022

Type: report

Abstract: We provide simple tests for selection on unobserved variables in the Vytlacil-Imbens-Angrist framework for Local Average Treatment Effects (LATEs).Our setup allows researchers not only to test for selection on either or both of the treated and untreated outcomes, but also to assess the magnitude of the selection effect.We show that it applies to the standard binary instrument case, as well as to experiments with imperfect compliance and fuzzy regression discontinuity designs, and we link it to broader discussions regarding instrumental variables.We illustrate the substantive value added by our framework with three empirical applications drawn from the literature.

Source: National Bureau of Economic Research

DOI: 10.3386/w30291

Authors: Dan Black, Joonhwi Joo, Robert LaLonde, Jeffrey Smith, Evan Taylor

Institutions: University of California, Riverside, Hitotsubashi University, National Bureau of Economic Research, University of Wisconsin–Madison, University of Arizona, The University of Texas at Dallas, University of Chicago

Language: English

Topic: Advanced Causal Inference Techniques

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W4287845257

Cites: 74

Cited by:

Related to: 10