Agglomerative hierarchical clustering for selecting valid instrumental variables (replication data)

DOI

Description: This reproduction package includes: 1. A text-file describing how to access the data used in the application. 2. R-Code necessary for the replication of results.

Abstract: We propose a procedure which combines hierarchical clustering with a test of overidentifying restrictions for selecting valid instrumental variables (IV) from a large set of IVs. Some of these IVs may be invalid in that they fail the exclusion restriction. We show that if the largest group of IVs is valid, our method achieves oracle properties. Unlike existing techniques, our work deals with multiple endogenous regressors. Simulation results suggest an advantageous performance of the method in various settings. The method is applied to estimating the effect of immigration on wages.

Identifier
DOI https://doi.org/10.15456/jae.2024142.1250902445
Metadata Access https://www.da-ra.de/oaip/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai:oai.da-ra.de:780140
Provenance
Creator Apfel, Nicolas; Liang, Xiaoran
Publisher ZBW - Leibniz Informationszentrum Wirtschaft
Publication Year 2024
Rights Creative Commons Attribution 4.0 (CC-BY); Download
OpenAccess true
Contact ZBW - Leibniz Informationszentrum Wirtschaft
Representation
Language English
Resource Type Collection
Discipline Economics