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. This version: - includes an omitted variable test in the multilevel estimation. It is reported in the summary() function of the multilevelIV() function. - resolves the error "Error in listIDs[, 1] : incorrect number of dimensions" when using the multilevelIV() function. - a new simulated dataset is provided, dataMultilevelIV, on which to exemplify the multilevelIV() function.

Version: 1.3
Depends: methods
Imports: optimx, mvtnorm, AER, e1071, stats, corpcor, lme4, gmm, lmtest, plyr, sandwich, compiler, data.table, Matrix
Published: 2017-11-08
Author: Raluca Gui, Markus Meierer, Rene Algesheimer
Maintainer: Raluca Gui <raluca.gui at>
License: GPL-3
NeedsCompilation: no
In views: Econometrics
CRAN checks: REndo results


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


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