The Extended Least Squares Assumptions in the Multiple Regression Model

Multiple Choice

The extended least squares assumptions in the multiple regression model include four assumptions from Chapter 6 (u_i has conditional mean zero; (X_i,Y_i) , i = 1,…, n are i.i.d. draws from their joint distribution; X_i and u_i have nonzero finite fourth moments; there is no perfect multicollinearity) . In addition, there are two further assumptions, one of which is

A) heteroskedasticity of the error term.
B) serial correlation of the error term.
C) the conditional distribution of u_i given X_i is normal.
D) invertibility of the matrix of regressors.