Answer: Underestimated standard errors

## 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.

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