Several efforts have been made to solve the multicollinearity problem, which arises from correlated regressors in linear regression model. This is because Ordinary Least Squares (OLS) Estimator becomes inefficient presence of multicollinearity.

In this paper we obtain a consistent estimator when there exist some measurement errors and multicollinearity in the instrumental variables in a two stage least square estimation of parameters. We investigate the asymptotic distribution of the proposed estimator and discuss its properties using some theoretical proofs and a simulation study. A real numerical application is also provided for mor...

For modeling count data, the Poisson regression model is widely used in which response variable takes non-negative integer values. However, presence of strong correlation between explanatory variables causes problem multicollinearity. Due to multicollinearity, variance maximum likelihood estimator (MLE) will be inflated causing parameters estimation become unstable. Multicollinearity can tackle...