The regression problem that will most likely increase the chances of making Type II errors is:

A. multicollinearity
B. conditional heteroskedasticity
C. positive serial correlation

Correct Answer: A

Multicollinearity makes the standard errors of the slope coefficients to be artificially inflated. This increases the likelihood of incorrectly concluding that a variable is not statistically significant (Type II error).

B is incorrect. Conditional heteroskedasticity underestimates standard errors, while the coefficient estimates remain unaffected. This inflates the t-statistics, leading to the frequent rejection of the null hypothesis of no statistical significance (Type I error).

C is incorrect. Positive serial correlation makes the ordinary least squares standard errors for the regression coefficients to underestimate the true standard errors. This inflates the estimated t-statistics, making them appear to be more significant than they really are. This increases Type I error.