clusterIV: Clustered Jackknife Instrumental Variables Estimation

Tools for instrumental variables estimation and inference under clustered errors with many instruments. The current release provides the cluster-jackknife IV estimator (CJIVE) of Frandsen, Leslie and McIntyre (2025) <doi:10.1162/rest.a.263> for a single endogenous regressor in a just-identified design, with cluster-robust inference: each observation's first-stage value is fitted leaving out its entire cluster, which removes the many-instrument bias that survives clustering. The leave-cluster-out fits use an exact Woodbury block update – one factorisation of the instrument Gram matrix plus a small solve per cluster – so the estimator scales to large samples. A companion 'iv_compare()' reports ordinary least squares, two-stage least squares, the observation-level jackknife and CJIVE on a common cluster-robust standard error.

Version:	0.1.0
Imports:	stats
Published:	2026-06-30
DOI:	10.32614/CRAN.package.clusterIV
Author:	Atal Katawazi [aut, cre]
Maintainer:	Atal Katawazi <atalkatawazi at hotmail.com>
BugReports:	https://github.com/atal-kat/Clustered-Estimation-and-Inference/issues
License:	MIT + file LICENSE
URL:	https://github.com/atal-kat/Clustered-Estimation-and-Inference
NeedsCompilation:	no
Materials:	README
CRAN checks:	clusterIV results

Documentation:

Reference manual:

clusterIV.html , clusterIV.pdf

Downloads:

Package source:	clusterIV_0.1.0.tar.gz
Windows binaries:	r-devel: clusterIV_0.1.0.zip, r-release: clusterIV_0.1.0.zip, r-oldrel: clusterIV_0.1.0.zip
macOS binaries:	r-release (arm64): clusterIV_0.1.0.tgz, r-oldrel (arm64): clusterIV_0.1.0.tgz, r-release (x86_64): clusterIV_0.1.0.tgz, r-oldrel (x86_64): clusterIV_0.1.0.tgz

Linking:

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