Suppose you have estimated hat$($Y$)=1+2**$X$\_(1)+3**$X$\_(2)+4**$X$\_(3).$ The sample consists of $60$

observations and the Durbin$-$Watson d statistic of $1\mathrm{.}55.$ what can you conclude?

a$.$ The model has heteroskedasticity and autocorrelation.

b$.$ The model does not have autocorrelation.

c$.$ The model does not have autocorrelation.

d$.$ It is indeterminate whether or not the model has autocorrelation.

e$.$ None of the above.

How does the Breusch$-$Godfrey $($BG$)$ test differ from the Durbin$-$Watson $($DW$)$ test?

a$.$ The BG test can test higher orders of autocorrelation, whereas DW can only test

first order.

b$.$ The BG test can test for autocorrelation in models that have a lagged dependent

variable, whereas the DW cannot.

c$.$ Both A and B$.$

d$.$ None of the above.