The authors consider the relative bias of the OLS-based estimate s(squared) of the disturbance variance in the linear regression model when disturbances are stationary AR(1). They improve upon previous bounds for the bias and show that E(s[squared]/[sigma squared]) tends to zero as autocorrelation increases whenever there is an intercept in the regression.