The extended least squares assumptions in the multiple regression model include four assumptions from Chapter 6 (ui has conditional mean zero; (Xi,Yi),i = 1,…,n are i.i.d.draws from their joint distribution;Xi and ui 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 ui given Xi is normal.
D)invertibility of the matrix of regressors.

Question

Quizplus · Accepted Answer

The additional assumption is that the conditional distribution of the error term (ui) given Xi is normal. This is important for inference and hypothesis testing in multiple regression models.

The Extended Least Squares Assumptions in the Multiple Regression Model