logL

- a vector of initial values for the parameters of the model to be supplied to the optimization algorithm.

theta

- a vector or matrix containing the dependent variable.

- a vector with the endogeneous variable or a matrix of dimention n X 2, where each column contains an endogeneous variable

Computes the log-likelihood function. Only two groups are considered, since as presented in Ebbes et al (2005) this gives good, unbiased results.

internal

instruments

latent

endogenous

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.

logL: Likelihood Estimation for latentIV

Description

Usage

Arguments

Value

References