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Multiple Choice Test Bank Questions No Feedback – Chapter 5
Correct answers denoted by an asterisk.
1. A researcher conducts a Breusch-Godfrey test for autocorrelation using 3 lags of the
residuals in the auxiliary regression. The original regression contained 5 regressors
including a constant term, and was estimated using 105 observations. What is the
critical value using a 5% significance level for the LM test based on T R2?
2. Which of the following would NOT be a potential remedy for the problem of
multicollinearity between regressors?
3. Which of the following conditions must be fulfilled for the Durbin Watson 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
4. If the residuals of a regression on a large sample are found to be heteroscedastic which
of the following might be a likely consequence?
(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
5. The value of the Durbin Watson test statistic in a regression with 4 regressors
(including the constant term) estimated on 100 observations is 3.6. What might we
suggest from this?
6. Which of the following is NOT a good reason for including lagged variables in a
regression?
7. What is the long run solution to the following dynamic econometric model?
yt =
1 +
2X2t +
3X3t + ut
8. Which of the following would you expect to be a problem associated with adding
lagged values of the dependent variable into a regression equation?
9. A normal distribution has coefficients of skewness and excess kurtosis which are
respectively
10. Which of the following would probably NOT be a potential “cure” for non-normal
residuals?
11. What would be the consequences for the OLS estimator if autocorrelation is present
in a regression model but ignored?
12. If OLS is used in the presence of heteroscedasticity, which of the following will be
likely consequences?
(i) Coefficient estimates may be misleading
(ii) Hypothesis tests could reach the wrong conclusions
(iii) Forecasts made from the model could be biased
(iv) Standard errors may inappropriate
13. If a residual series is negatively autocorrelated, which one of the following is the
most likely value of the Durbin Watson statistic?
14. If the residuals of a model containing lags of the dependent variable are
autocorrelated, which one of the following could this lead to?
15. Which one of the following is NOT a symptom of near multicollinearity?
16. Which one of the following would be the most appropriate auxiliary regression for a
Ramsey RESET test of functional form?
17. If a regression equation contains an irrelevant variable, the parameter estimates will
be
18. Put the following steps of the model-building process in the order in which it would
be statistically most appropriate to do them:
(i) Estimate model
(ii) Conduct hypothesis tests on coefficients
(iii) Remove irrelevant variables
(iv) Conduct diagnostic tests on the model residuals
19. Test statistics for the LM test and the Wald test are usually constructed to follow a
20. Which of these statements is true?
(I) The F-distribution has 2 degrees of freedom parameters
(II) Asymptotically, the LM test and the Wald test are equivalent
(III) The results from the LM and Wald tests may differ somewhat in small samples
(IV) The F-distribution is a special case of the t-distribution
21. The assumption of homoscedasticity can be written mathematically as
( )
22. Assuming you are interested in conducting a Goldfeld-Quandt test at a 5%
significance level and the regression model is estimated on each sub-sample with residual
variances
2
10.15s=
and
2
20.14s=
,
112T=
,
214T=
and
2k=
. What would your
conclusion be?
23. Which of these is a test for heteroscedasticity?
24. Which of these is not a viable ‘solution’ for heteroscedasticity?
(A) (B)
25. The graphs above are time series plots of residuals from two separate regressions.
Which of these combinations is true?
26. Assuming a researcher runs the following regression
1t t t
u u v
−
=+
where
t
u
is
residual from a regression. If the researcher conducts a hypothesis test with null
hypothesis of
0:0H
=
against an alternative hypothesis of
1:0H
, what type of test
is he/she conducting?
27. Assuming the researcher now runs the following regression
1 1 2 2 ...
t t t r t r t
u u u u v
− − −
= + + + +
where
t
u
is residual from a regression. If the
researcher conducts a test with a null hypothesis of
01
:0H
=
and
20
=
and ... and
0
r
=
against an alternative hypothesis of
11
:0H
or
20
or ... or
0
r
, what
type of test is he/she conducting?
28. Which of these is not a consequence of ignoring autocorrelation if it is present?
29. Which of these is a viable solution to the problem of multicollinearity?
(I) Ignore it
(II) Drop one of the collinear variables
(III) Transform the highly correlated variables into a ratio
(IV) Take the logs of the variables
30. Which of the following statements are true about parameter stability tests?
(I) Parameter stability tests test the assumption that the estimated parameters of a model
are constant for the entire sample
(II) Chow test and predictive failure tests are two types of parameter stability tests
(III) Backward and forward predictive failure tests are two types of parameter stability
tests
(IV) Parameter stability tests examine violations of the classical linear regression model
assumptions
31. Simultaneous equations bias is a situation where
