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> heteroscedasticity 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.

Package details

AuthorRaluca Gui [cre, aut], Markus Meierer [aut], Rene Algesheimer [aut], Patrik Schilter [aut]
MaintainerRaluca Gui <[email protected]>
LicenseGPL-3
Version2.1.0
URL https://github.com/mmeierer/REndo
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("REndo")

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REndo documentation built on Jan. 16, 2019, 5:05 p.m.