Reading 12- LOS g(Part 1): Q11-14 class, 施工, statements, following, regarding

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11．Which of the following statements regarding heteroskedasticity is FALSE?
A)    Multicollinearity is a potential problem only in multiple regressions, not simple regressions.
B)    Heteroskedasticity only occurs in cross-sectional regressions.
C)    Autocorrelated error terms can be detected using a Durbin-Watson (DW) test or visual inspection of a plot of the residuals.
D)    The presence of heteroskedastic error terms results in a variance of the residuals that is too large.


13．Which of the following is least likely a method used to detect heteroskedasticity?
A)    Plot of the residual in the sample.
B)    Test of the variances.
C)    Durbin-Watson test.
D)    Breusch-Pagan test.

14．An analyst is trying to estimate the beta for a fund. The analyst estimates a regression equation in which the fund returns are the dependent variable and the Wilshire 5000 is the independent variable, using monthly data over the past five years. The analyst finds that the correlation between the square of the residuals of the regression and the Wilshire 5000 is 0.2. Which of the following is most accurate, assuming a 0.05 level of significance? There is:
A)    evidence of conditional heteroskedasticity and serial correlation in the regression equation.
B)    evidence of conditional heteroskedasticity but not serial correlation in the regression equation.
C)    no evidence that there is conditional heteroskedasticity or serial correlation in the regression equation.
D)    evidence of serial correlation but not conditional heteroskedasticity in the regression equation.

[此贴子已经被作者于2008-4-12 16:35:05编辑过]

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11．Which of the following statements regarding heteroskedasticity is FALSE?
A)    Multicollinearity is a potential problem only in multiple regressions, not simple regressions.
B)    Heteroskedasticity only occurs in cross-sectional regressions.
C)    Autocorrelated error terms can be detected using a Durbin-Watson (DW) test or visual inspection of a plot of the residuals.
D)    The presence of heteroskedastic error terms results in a variance of the residuals that is too large.
The correct answer was B)
If there are shifting regimes in a time-series (e.g., change in regulation, economic environment), it is possible to have heteroskedasticity in a time-series.

13．Which of the following is least likely a method used to detect heteroskedasticity?
A)    Plot of the residual in the sample.
B)    Test of the variances.
C)    Durbin-Watson test.
D)    Breusch-Pagan test.
The correct answer was C)
The Durbin-Watson test is used to detect serial correlation. The Breusch-Pagan test is used to detect heteroskedasticity.

14．An analyst is trying to estimate the beta for a fund. The analyst estimates a regression equation in which the fund returns are the dependent variable and the Wilshire 5000 is the independent variable, using monthly data over the past five years. The analyst finds that the correlation between the square of the residuals of the regression and the Wilshire 5000 is 0.2. Which of the following is most accurate, assuming a 0.05 level of significance? There is:
A)    evidence of conditional heteroskedasticity and serial correlation in the regression equation.
B)    evidence of conditional heteroskedasticity but not serial correlation in the regression equation.
C)    no evidence that there is conditional heteroskedasticity or serial correlation in the regression equation.
D)    evidence of serial correlation but not conditional heteroskedasticity in the regression equation.
The correct answer was C)     
The test for conditional heteroskedasticity involves regressing the square of the residuals on the independent variables of the regression and creating a test statistic that is n × R², where n is the number of observations and R² is from the squared-residual regression. The test statistic is distributed with a chi-squared distribution with the number of degrees of freedom equal to the number of independent variables. For a single variable, the R² will be equal to the square of the correlation; so in this case, the test statistic is 60 × 0.2² = 2.4, which is less than the chi-squared value (with one degree of freedom) of 3.84 for a p-value of 0.05. There is no indication about serial correlation.