This paper has elaborated upon the deleterious effects of outliers and corruption of dataset on estimation of linear regression coefficients by the Ordinary Least Squares method. Motivated to ameliorate the estimation procedure, we have introduced the robust regression estimators based on...

Multicollinearity in empirical data violates the assumption of independence among the explanatory variables in a linear regression model and by inflating the standard error of estimates of the estimated regression coefficients leads to failure in rejecting a false null hypothesis of...

The Two-Stage Least squares method for obtaining the estimated structural coefficients of a simultaneous linear equations model is a celebrated method that uses OLS at the first stage for estimating the reduced form coefficients and obtaining the expected values in the arrays of current...