Fitting Linear Models with Endogenous Regressors using Latent Instrumental Variables
Fitting Linear Models with one Endogenous Regressor using Latent Instr...
Confidence Intervals for Bootstrapped Model Parameters
Fitting Linear Models Endogenous Regressors using Gaussian Copula
Fitting Linear Models with Endogenous Regressors using Heteroskedastic...
Fitting Linear Models with Endogenous Regressors using Lewbel's Higher...
Fitting Multilevel GMM Estimation with Endogenous Regressors
Predict method for Models using the Gaussian Copula Approach
Predict method for fitted Regression Models with Internal Instrumental...
Predict method for Models using the Latent Instrumental Variables appr...
Predict method for Multilevel GMM Estimations
Fitting Linear Models with Endogenous Regressors using Latent Instrume...
Summarizing Bootstrapped copulaCorrection Model Fits
Summarizing latentIV Model Fits
Summarizing Multilevel GMM Estimation with Endogenous Regressors Model...
Calculate Variance-Covariance Matrix for Models Fitted with Bootstrapp...
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.