Explanation

Positive serial correlation in time-series analysis leads to:

1. Underestimated standard errors: When residuals are positively correlated, the OLS estimator underestimates the true standard errors of the regression coefficients.

2. More Type I errors: Since standard errors are underestimated, t-statistics appear larger than they actually are, leading to more frequent rejection of true null hypotheses.

3. Inefficient parameter estimates: The OLS estimates are no longer BLUE (Best Linear Unbiased Estimators).

Option B is correct because positive serial correlation causes standard errors to be underestimated, making the regression appear more precise than it actually is.