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FRM Part I · FRM Exam Part I · Regression Diagnostics

A risk manager estimates a time-series regression by OLS and finds the residuals are positively autocorrelated, while the regressors are not lagged dependent variables. Which statement about the consequences for inference is correct?

OLS coefficients stay unbiased when residuals are positively autocorrelated and regressors are exogenous, but the conventional standard errors are usually too small. That inflates t-statistics and makes variables look more significant than they are, so Newey-West or similar corrections are needed.

  1. AOLS coefficient estimates remain unbiased, but the usual standard errors are typically understated, inflating t-statisticsCorrect
  2. BOLS coefficient estimates become biased upward, but the standard errors remain valid
  3. COLS coefficient estimates remain unbiased and the usual standard errors remain valid
  4. DOLS coefficient estimates become biased, and the standard errors are typically overstated

Explanation

With positive residual autocorrelation and strictly exogenous regressors, OLS remains unbiased and consistent, but the usual standard error formulas are wrong, typically too small. This inflates t-statistics and leads to over-rejection of true nulls. Options B and D wrongly claim bias, and C ignores the standard error problem.

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