test

Question 1

A biased estimator always has higher mean-square error than an unbiased estimator.

Answer 1

false

Question 2

The OLS residuals are, by construction, uncorrelated with the exogenous variables of the regression equation.

Answer 2

true

Question 3

The reason why the OLS coefficient estimates are usually considered to follow a t-distribution rather than the normal is that the error variance is usually unknown.

Answer 3

true

Question 4

f we wish to test the hypothesis that a coefficient is positive then we would use a two-tailed test

Answer 4

false

Question 5

The standard error of the regression always lies in the range zero to one and the closer it is to one then the better the fit of the model.

Answer 5

false

Question 6

The F test for the joint significance of the right hand side variables is distributed as F with degrees of freedom equal to T-k-1, k (where T is the number of observations and kis the number of slope coefficients)

Answer 6

true

Question 7

Serial correlation of the errors in a regression model would not, in itself, lead us to expect the OLS coefficient estimates to be biased.

Answer 7

true

Question 8

f the Durbin-Watson statistic lies between the upper and lower critical bounds then we should reject the null that there is no serial correlation.

Answer 8

false

Question 9

Heteroscedasticity is most often found in time series regression model

Answer 9

false

Question 10

Heteroscedasticity can often be dealt with by scaling the data appropriat

Answer 10

true