Chapter 8
1. Which of the following is true of heteroskedasticity?
a. Heteroskedasticty causes inconsistency in the Ordinary Least Squares estimators.
b. Population R2 is affected by the presence of heteroskedasticty.
c. The Ordinary Least Square estimators are not the best linear unbiased estimators if heteroskedasticity
is present.
d. It is not possible to obtain F statistics that are robust to heteroskedasticity of an unknown form.
2. Consider the following regression model: yi=β0+β1 xi+ui. If the first four Gauss-Markov assumptions
hold true, and the error term contains heteroskedasticity, then _____.
a. Var(ui|xi) =0
b. Var(ui|xi) =1
c. Var(ui|xi) = σi2
d. Var(ui|xi) =σ
3. The general form of the t statistic is _____.
a. 𝑡 = estimate−hypothesized value
standard error
b. 𝑡 = hypothesized value−estimate
standard error
c. 𝑡 = standard error
estimate−hypothesized value
d. 𝑡 = estimate − hypothesized value
4. Which of the following is true of the OLS t statistics?
a. The heteroskedasticity-robust t statistics are justified only if the sample size is large.
b. The heteroskedasticty-robust t statistics are justified only if the sample size is small.
c. The usual t statistics do not have exact t distributions if the sample size is large.
d. In the presence of homoscedasticity, the usual t statistics do not have exact t distributions if the
sample size is small.
5. The heteroskedasticity-robust _____ is also called the heteroskedastcity-robust Wald statistic.
a. t statistic
b. F statistic
c. LM statistic
d. z statistic
6. Which of the following tests helps in the detection of heteroskedasticity?
a. The Breusch-Pagan test
b. The Breusch-Godfrey test
c. The Durbin-Watson test
d. The Chow test
7. What will you conclude about a regression model if the Breusch-Pagan test results in a small p-value?
a. The model contains homoskedasticty.
b. The model contains heteroskedasticty.
c. The model contains dummy variables.
d. The model omits some important explanatory factors.
8. A test for heteroskedasticty can be significant if _____.
a. the Breusch-Pagan test results in a large p-value
b. the White test results in a large p-value
c. the functional form of the regression model is misspecified
d. the regression model includes too many independent variables
9. Which of the following is a difference between the White test and the Breusch-Pagan test?
a. The White test is used for detecting heteroskedasticty in a linear regression model while the Breusch-
Pagan test is used for detecting autocorrelation.
b. The White test is used for detecting autocorrelation in a linear regression model while the Breusch-
Pagan test is used for detecting heteroskedasticity. .
c. The number of regressors used in the White test is larger than the number of regressors used in the
Breusch-Pagan test.
d. The number of regressors used in the Breusch-Pagan test is larger than the number of regressors used
in the White test.
10. Which of the following is true of the White test?
a. The White test is used to detect the presence of multicollinearity in a linear regression model.
b. The White test cannot detect forms of heteroskedasticity that invalidate the usual Ordinary Least
Squares standard errors.
c. The White test can detect the presence of heteroskedasticty in a linear regression model even if the
functional form is misspecified.
d. The White test assumes that the square of the error term in a regression model is uncorrelated with
all the independent variables, their squares and cross products.
11. Which of the following is true?
a. In ordinary least squares estimation, each observation is given a different weight.
b. In weighted least squares estimation, each observation is given an identical weight.
c. In weighted least squares estimation, less weight is given to observations with a higher error variance.
d. In ordinary least squares estimation, less weight is given to observations with a lower error variance.
12. Weighted least squares estimation is used only when _____.
a. the dependent variable in a regression model is binary
b. the independent variables in a regression model are correlated
c. the error term in a regression model has a constant variance
d. the functional form of the error variances is known
13. Consider the following regression equation: y = β0+ β1x1+ u. Which of the following indicates a
functional form misspecification in E(y|x)?
a. Ordinary Least Squares estimates equal Weighted Least Squares estimates.
b. Ordinary Least Squares estimates exceed Weighted Least Squares estimates by a small magnitude.
c. Weighted Least Squares estimates exceed Ordinary Least Squares estimates by a small magnitude.
d. Ordinary Least Square estimates are positive while Weighted Least Squares estimates are negative.
14. Which of the following tests is used to compare the Ordinary Least Squares (OLS) estimates and the
Weighted Least Squares (WLS) estimates?
a. The White test
b. The Hausman test
c. The Durbin-Watson test
d. The Breusch-Godfrey test
15. The linear probability model contains heteroskedasticity unless _____.
a. the intercept parameter is zero
b. all the slope parameters are positive
c. all the slope parameters are zero
d. the independent variables are binary
16. The interpretation of goodness-of-fit measures changes in the presence of heteroskedasticity.
17. Multicollinearity among the independent variables in a linear regression model causes the
heteroskedasticity-robust standard errors to be large.
18. If the Breusch-Pagan Test for heteroskedasticity results in a large p-value, the null hypothesis of
homoskedasticty is rejected.
19. The generalized least square estimators for correcting heteroskedasticity are called weighed least
squares estimators.
20. The linear probability model always contains heteroskedasticity when the dependent variable is a
binary variable unless all of the slope parameters are zero.