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REndo

R Package implementing state of the art methods to controll for endogeneity when no instrumental variables are available.

The second version of the pacakge, REndo 1.1, implements four instrument-free methods. These are: the latent instrumental variables method proposed by Ebbes et al. (2005), the higher moments approach proposed by Lewbel (1997) , the joint estimation method using Gaussian copula (Park and Gupta, 2012) and the mixed generalized method of moments proposed by Kim and Frees (2007). The later method can be used to treat endogeneity in multilevel models.

The names of the two functions implemented in the first version of the package have been changed to the following:

liv() -> latentIV() hmlewbel() -> higherMomentsIV()

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Version

Install

install.packages('REndo')

Monthly Downloads

1,461

Version

1.1

License

GPL-3

Maintainer

Raluca Gui

Last Published

November 16th, 2016

Functions in REndo (1.1)

coef,copulaREndo-method

coefficients for the copulaCorrection method
boots

Bootstrapping Standard Errors
latentIV

Fitting Linear Models with one Endogenous Regressor using Latent Instrumental Variables
internalIV

Constructs Internal Instrumental Variables From Data
checkAssumptions

Checks Assumptions for Constructing Internal Instruments
copulaPStar

Inverse-Normal Distribution of the Empirical Distribution Function
dataCopC1

Simulated Dataset
coef,heterogenREndo-method

methods for the heterogenIV function
copulaCont1

Fitting Linear Models with One Enedogenous Regressor using Gaussian Copula
copulaCorrection

Fitting Linear Models Endogeneous Regressors using Gaussian Copula
logL

Likelihood Estimation for latentIV
logLL

Log-likelihood
multilevelGMM

Multilevel GMM estimation
multilevelIV

Multilevel GMM Estimation
summary,livREndo-method

latentIV methods
summary,mixedREndo-method

methods for the multilevelIV function
coef,livREndo-method

latentIV methods
coef,mixedREndo-method

methods for the multilevelIV function
summary,copulaREndo-method

summary for the copulaCorrection method
summary,heterogenREndo-method

methods for the heterogenIV function
heterogenIV

Fitting Linear Models with Endogenous Regressors using Heteroskedastic Covariance Restictions
higherMomentsIV

Fitting Linear Models with Endogenous Regressors using Lewbel's Higher Moments Approach
tScores

Test scores of 3054 test scores of 1174 students in 60 schools
dataCopDis

Simulated Dataset
dataCopC2

Simulated Dataset
copulaDiscrete

Fitting Linear Models with Endogeneous Discrete Regressors using Internal Instrumental Variables
copulaMethod2

Fitting Linear Models with Endogeneous Regressors using Gaussian Copula - Method 2