Question #88 - Reading 1 Multiple Regression

Reading: Reading 1 Multiple Regression

PDF File: Reading 1 Multiple Regression.pdf

Page: 41

Status: Unattempted

Shared Context

- Based on a R2 calculated from the information in Table 2, the analyst should conclude that the number of analysts and ln(market value) of the firm explain: A) 18.4% of the variation in returns. B) 84.4% of the variation in returns. C) 15.6% of the variation in returns.

Question

Upon further analysis, Turner concludes that multicollinearity is a problem. What might have prompted this further analysis and what is intuition behind the conclusion?

Answer Choices:

A. At least one of the t-statistics was not significant, the F-statistic was significant, and a positive relationship between the number of analysts and the size of the firm would be expected

B. At least one of the t-statistics was not significant, the F-statistic was not significant, and a positive relationship between the number of analysts and the size of the firm would be expected

C. At least one of the t-statistics was not significant, the F-statistic was significant, and an intercept not significantly different from zero would be expected

Explanation

Multicollinearity occurs when there is a high correlation among independent variables and may exist if there is a significant F-statistic for the fit of the regression model, but at least one insignificant independent variable when we expect all of them to be significant. In this case the coefficient on ln(market value) was not significant at the 1% level, but the F- statistic was significant. It would make sense that the size of the firm, i.e., the market value, and the number of analysts would be positively correlated.

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