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    Question

    Non-spherical errors are related to

    A heteroskedasticity Correct Answer Incorrect Answer
    B autocorrelated errors Correct Answer Incorrect Answer
    C expected value of the error not equal to zero Correct Answer Incorrect Answer
    D both a) and b) Correct Answer Incorrect Answer

    Solution

    If the spherical errors assumption fails to hold, there are two problems with OLS. There is a better estimator available—one that is still unbiased, but is less sensitive to sampling variation (i.e., has lower standard errors). The formula we use to estimate the standard errors of OLS is invalid. Our confidence intervals and hypothesis tests will (usually) be overconfident, overstating the precision of our results. Spherical errors fails when we have either or both of: Heteroskedasticity and Autocorrelation

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