State whether the following statements are true or false. Briefly justify your answers.
a. When autocorrelation is present, OLS estimators are biased as well as inefficient.
b. The Durbin-Watson d is useless in autoregressive models like the regression (10.7) where one of the explanatory variables is a lagged value(s) of the dependent variable.
c. The Durbin-Watson d test assumes that the variance of the error term ut is homoscedastic.
d. The first difference transformation to eliminate autocorrelation assumes that the coefficient of autocorrelation p must be -1.
e. The R2 values of two models, one involving regression in the first difference form and another in the level form, are not directly comparable.