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)homoskedasticity of the error term.
D)invertibility of the matrix of regressors.

Question

Quizplus · Accepted Answer

The extended least squares assumptions include the assumption of homoskedasticity, which means that the error term has constant variance across observations.

The Extended Least Squares Assumptions in the Multiple Regression Model