REndo: Fitting Linear Models with Endogenous Regressors using Latent Instrumental Variables

Fits linear models with endogenous regressor using latent instrumental variable approaches. The methods included in the package are Lewbel's (1997) <doi:10.2307/2171884> higher moments approach as well as Lewbel's (2012) <doi:10.1080/07350015.2012.643126> heteroskedasticity approach, Park and Gupta's (2012) <doi:10.1287/mksc.1120.0718> joint estimation method that uses Gaussian copula and Kim and Frees's (2007) <doi:10.1007/s11336-007-9008-1> multilevel generalized method of moment approach that deals with endogeneity in a multilevel setting. These are statistical techniques to address the endogeneity problem where no external instrumental variables are needed. Note that with version 2.0.0 sweeping changes were introduced which greatly improve functionality and usability but break backwards compatibility.

Version: 2.0.0
Depends: R (≥ 3.5)
Imports: methods (≥ 3.5), stats (≥ 3.5), utils (≥ 3.5), Formula (≥ 1.2), optimx (≥ 2013.8.7), mvtnorm (≥ 1.0-8), AER (≥ 1.2-5), corpcor (≥ 1.6.9)
Suggests: testthat, covr, knitr, rmarkdown
Published: 2018-11-10
Author: Raluca Gui [cre, aut], Markus Meierer [aut], Rene Algesheimer [aut], Patrik Schilter [aut]
Maintainer: Raluca Gui <raluca.gui at>
License: GPL-3
NeedsCompilation: no
Materials: README NEWS
In views: Econometrics
CRAN checks: REndo results


Reference manual: REndo.pdf
Package source: REndo_2.0.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X binaries: r-release: REndo_2.0.0.tgz, r-oldrel: REndo_1.3.tgz
Old sources: REndo archive


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