Reading 12: Multiple Regression and Issues in Regression A

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Q1. During the course of a multiple regression analysis, an analyst has observed several items that she believes may render incorrect conclusions. For example, the coefficient standard errors are too small, although the estimated coefficients are accurate. She believes that these small standard error terms will result in the computed t-statistics being too big, resulting in too many Type I errors. The analyst has most likely observed which of the following assumption violations in her regression analysis?

A) Positive serial correlation.

B) Multicollinearity.

C) Homoskedasticity.

Q2. Alex Wade, CFA, is analyzing the result of a regression analysis comparing the performance of gold stocks versus a broad equity market index. Wade believes that serial correlation may be present, and in order to prove his theory, should use which of the following methods to detect its presence?

A) The Breusch-Pagan test.

B) The Hansen method.

C) The Durbin-Watson statistic.

Q3. Which of the following statements regarding serial correlation that might be encountered in regression analysis is least accurate?

A) Serial correlation occurs least often with time series data.

B) Negative serial correlation causes a failure to reject the null hypothesis when it is actually false.

C) Positive serial correlation typically has the same effect as heteroskedasticity.

Q4. An analyst is estimating whether company sales is related to three economic variables. The regression exhibits conditional heteroskedasticity, serial correlation, and multicollinearity. The analyst uses Hansen’s procedure to adjust for the standard errors. Which of the following is most accurate? The:

A) regression will still exhibit multicollinearity, but the heteroskedasticity and serial correlation problems will be solved.

B) regression will still exhibit heteroskedasticity and multicollinearity, but the serial correlation problem will be solved.

C) regression will still exhibit serial correlation and multicollinearity, but the heteroskedasticity problem will be solved.

Q5. Which of the following is least likely a method of detecting serial correlations?

A) The Durbin-Watson test.

B) The Breusch-Pagan test.

C) A scatter plot of the residuals over time.

Q6. Which of the following is least accurate regarding the Durbin-Watson (DW) test statistic?

A) If the residuals have negative serial correlation, the DW statistic will be greater than 2.

B) In tests of serial correlation using the DW statistic, there is a rejection region, a region over which the test can fail to reject the null, and an inconclusive region.

C) If the residuals have positive serial correlation, the DW statistic will be greater than 2.