Bias of some commonly-used time series estimates

We study the bias of Yule-Walker and least squares estimates for univariate and multivariate autoregressive processes. We obtain explicit formulae for the large-sample bias of YuleWalker estimates in the scalar first- and second-order cases and for least squares estimates in the general case. Both simulations and theory indicate that Yule-Walker estimates are inferior to least squares estimates. For strongly autocorrelated processes, Yule-Walker estimates can be severely biased even for comparatively large-sample sizes.