Bias of s2 in Linear Regression Model with correlated errors

We derive bounds for the relative bias of the 0LS-based estimate s2 of the disturbance variance in the linear regression model when disturbances are stationary AR(1) and show that this bias vanishes as sample size increases (i.e. s2 is asymptotically unbiased irrespective of the particular form of the regressor sequence).