In this paper, we suggest improved estimation strategies based on preliminarily test and shrinkage principles in a seemingly unrelated regression model when explanatory variables are affected by multicollinearity. To that end, we split the vector regression coefficient of each equation into two...

The asymptotic distribution of the linear instrumental variables (IV) estimator with empirically selected ridge regression penalty is characterized. The regularization tuning parameter is selected by splitting the observed data into training and test samples and becomes an estimated parameter...

It is known that, when in the linear regression model there is a high degree of multicollinearity, the results obtained by using the Ordinary Least Squares (OLS) method are unstable. As a solution to this situation, in this paper we present the raised method, the ridge method and the orthogonal...