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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 |
| 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.
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