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Implementation of the categorical instrumental variable (CIV) estimator proposed by Wiemann (2023) <doi:10.48550/arXiv.2311.17021>. CIV allows for optimal instrumental variable estimation in settings with relatively few observations per category. To obtain valid inference in these challenging settings, CIV leverages a regularization assumption that implies existence of a latent categorical variable with fixed finite support achieving the same first stage fit as the observed instrument.
Version: | 0.1.0 |
Depends: | R (≥ 3.6) |
Imports: | stats, AER, kcmeans |
Suggests: | testthat (≥ 3.0.0), covr, knitr, rmarkdown |
Published: | 2023-12-08 |
DOI: | 10.32614/CRAN.package.civ |
Author: | Thomas Wiemann [aut, cre] |
Maintainer: | Thomas Wiemann <wiemann at uchicago.edu> |
BugReports: | https://github.com/thomaswiemann/civ/issues |
License: | GPL (≥ 3) |
URL: | https://github.com/thomaswiemann/civ |
NeedsCompilation: | no |
Materials: | README NEWS |
CRAN checks: | civ results |
Reference manual: | civ.pdf |
Vignettes: |
Get Started |
Package source: | civ_0.1.0.tar.gz |
Windows binaries: | r-devel: civ_0.1.0.zip, r-release: civ_0.1.0.zip, r-oldrel: civ_0.1.0.zip |
macOS binaries: | r-release (arm64): civ_0.1.0.tgz, r-oldrel (arm64): civ_0.1.0.tgz, r-release (x86_64): civ_0.1.0.tgz, r-oldrel (x86_64): civ_0.1.0.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.