State whether the following statements are true or false. Briefly justify your answer.

a. When autocorrelation is present, OLS estimators are biased as well as inefficient.

b. The Durbin–Watson d test assumes that the variance of the error term u_t is homoscedastic.

c. The first-difference transformation to eliminate autocorrelation assumes that the coefficient of autocorrelation ρ is −1.

d. The R² values of two models, one involving regression in the first-difference form and another in the level form, are not directly comparable.

e. A significant Durbin–Watson d does not necessarily mean there is autocorrelation of the first order.

f. In the presence of autocorrelation, the conventionally computed variances and standard errors of forecast values are inefficient.

g. The exclusion of an important variable(s) from a regression model may give a significant d value.

h. In the AR(1) scheme, a test of the hypothesis that ρ = 1 can be made by the Berenblutt–Webb g statistic as well as the Durbin–Watson d statistic.

i. In the regression of the first difference of Y on the first differences of X, if there is a constant term and a linear trend term, it means in the original model there is a linear as well as a quadratic trend term.