In this article, the author discusses the use in policy analysis of models that incorporate uncertainty. He believes that all models should consider incorporating uncertainty, but that at the same time it is important to understand that sampling variability is not usually the dominant driver of uncertainty in policy analyses. He also argues that…

Rectifies the unsatisfactory textbook treatment of the finite-sample proprieties of estimators of regression models with a lagged dependent variable and autocorrelated disturbances. Maintains that the bias of the ordinary least squares estimator is determined by the dynamic and correlation effects. (MJP)