Generally, when there is autocorrelation
of any kind, this will lead to the conclusion
that the parameter estimates in an OLS are
more precise than they actually are. There
will be a tendency to reject or accept the
null hypothesis when infact, they should
not be rejected or accepted. A test of autocorrelation
therefore is necessary in an OLS
analysis so as to obtain the best linear and
unbiased estimates.