What the Consequence of
Autocorrelation?
When the disturbance term exhibits
serial correlation, the values as well as the standard errors of the parameters
estimates are affected. In particular
- When the residuals are serially correlated the parameters estimates of OLS are statistically unbiased.
- With auto correlated values of the disturbance term, the OLS variances of the parameter estimates are likely to be larger than those of other econometrics method.
- The variance of the random term u may be seriously underestimated if the u’s are auto correlated.
- Finally, if the values of u are auto correlated the prediction based on ordinary least squares estimates will be inefficient.
As per consequence no 2, if the variance of parameter estimate is larger in the presence of autocorrelation, then how t score could be larger?
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