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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. See the publication related to this package in the Journal of Statistical Software for more details: <doi:10.18637/jss.v107.i03>. Note that with version 2.0.0 sweeping changes were introduced which greatly improve functionality and usability but break backwards compatibility.
Getting started
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Package details |
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| Author | Raluca Gui [cre, aut], Markus Meierer [aut], Rene Algesheimer [aut], Patrik Schilter [aut] |
| Maintainer | Raluca Gui <raluca.gui@gmail.com> |
| License | GPL-3 |
| Version | 2.4.10 |
| URL | https://github.com/mmeierer/REndo |
| Package repository | View on CRAN |
| Installation |
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