logL: Likelihood Estimation for liv

In Rgui/REndo_1.0: Fitting Linear Models with Endogenous Regressors when No External Instruments Are Available

Description

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

Usage

logL(theta, y, P)

Arguments

theta	- a vector of initial values for the parameters of the model to be supplied to the optimization algorithm.
y	- a vector or matrix containing the dependent variable.
P	- a vector with the endogeneous variable or a matrix of dimention n X 2, where each column contains an endogeneous variable

Value

returns the value of the negative log-likelihood.

Author(s)

adapted by Raluca Gui from the code provided by Professor Ebbes during a workshop at Univ. of Zurich in April 2015.

References

Ebbes, P., Wedel,M., Boeckenholt, U., and Steerneman, A. G. M. (2005). 'Solving and testing for regressor-error (in)dependence when no instruments

Rgui/REndo_1.0 documentation built on May 9, 2019, 10:03 a.m.