logLL

initial values for the parameters to be optimized over.

theta

a vector containing the dependent variable.

a matrix containing the regressors, with the endogeneous variable being on the last column.

a vector containing the discrete endogeneous regressor.

Computes the log-likelihood function

internal

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.

logLL: Log-likelihood

Description

Usage

Arguments

Value