Question #1
Reading: Reading 1 Multiple Regression
PDF File: Reading 1 Multiple Regression.pdf
Page: 1
Status: Unattempted
Correct Answer: A
Question
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?
Answer Choices:
A. Positive serial correlation
B. Homoskedasticity
C. Multicollinearity
Explanation
Positive serial correlation is the condition where a positive regression error in one time
period increases the likelihood of having a positive regression error in the next time
period. The residual terms are correlated with one another, leading to coefficient error
terms that are too small.