Package: civ 0.1.0.9000

civ: Categorical Instrumental Variables

Implementation of the categorical instrumental variable (CIV) estimator proposed by Wiemann (2023) <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.

Authors:Thomas Wiemann [aut, cre]

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Bug tracker:https://github.com/thomaswiemann/civ/issues

On CRAN:

1 exports 1 stars 1.18 score 68 dependencies 5 scripts 204 downloads

Last updated 7 months agofrom:e37be8d1d7. Checks:OK: 7. Indexed: yes.

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Dependencies:abindAERbackportsbootbroomcarcarDataCkmeans.1d.dpclicolorspacecowplotcpp11DerivdoBydplyrfansifarverFormulagenericsggplot2gluegtableisobandkcmeanslabelinglatticelifecyclelme4lmtestmagrittrMASSMatrixMatrixModelsmgcvmicrobenchmarkminqamodelrmunsellnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigpurrrquantregR6rbibutilsRColorBrewerRcppRcppEigenRdpackrlangsandwichscalesSparseMstringistringrsurvivaltibbletidyrtidyselectutf8vctrsviridisLitewithrzoo