1) If the residuals of a regression on a large sample are found to be heteroscedastic which of the following might be a likely consequence? (10 points)

(i) The coefficient estimates are biased

(ii) The standard error estimates for the slope coefficients may be too small

(iii) Statistical inferences may be wrong.

2) What would be the consequences for the OLS estimator if autocorrelation is present in a regression model but ignored? (10 points)

(a) It will be biased

(b) It will be inconsistent

(c) It will be inefficient

All of (a), (b), and (c) will be true

3) Which of the following conditions must be fulfilled for the DurbinWatson test to be valid?

(i) The regression includes a constant term

(ii) The regressors are non-stochastic

(iii) There are no lags of the dependent variable in the regression

(iv) There are no lags of the independent variables in the regression.

(10 points)

4) A normal distribution has coefficients of skewness and excess kurtosis which are, respectively,

(a) 0 and 0

(b) 0 and 3

(c) 3 and 0

(d) Will vary from one normal distribution to another.

(10 points)