Question

Specify a multiple regression model in matrix form. Explain how GLS estimator can be used to take care of both autocorrelation and heteroscedasticity.

18 Feb 2026
Answer :
Word Count : 877
The general form of a multiple regression model can be specified as: [ \mathbf{Y} = \mathbf{X}\beta + \mathbf{u} ] Where: * (\mathbf{Y}) is an (n \times 1) vector of the dependent variable observations, * (\mathbf{X}) is an (n \times k) matrix of the independent variables (with (k) being the number of explanatory variables, including the constant term), * (\beta) is a (k \times 1) vector of the regression coefficients, * (\mathbf{u}) is an (n \times 1) vector of the error terms. To estimate the parameters (\beta), we use Ordinary Least Squares (OLS) estimation, where the estimator is: [ \hat{\beta}_{OLS} = (\mathbf{X}^T \mathbf{X})^{-1} \mathbf{X}^T \mathbf{Y} ] However, OLS estimators assume that the error terms (\mathbf{u}) have certain properties: they must have zero mean, constant variance (homoscedasticity), and no autocorrelation. When these assumptions are violated—specifically when there is autocorrelation (the error terms are correlated over time) or heteroscedasticity _________ ______ _____ _________ ______ ____ ___.
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