VAR Priors: Success or lack of a decent macroeconomic theory?

The purpose of this paper is to demonstrate that the success of the Litterman prior in VAR forecasting is not due to the realism of the prior, but rather because the prior conveniently reduces forecast error variance in common cases of misspecification. Specifically, it is shown that the imposition of a random walk prior reduces forecast error variance in misspecifications involving (1) time-varying coefficients misspecified as constant coefficients, (2) serially correlated residuals misspecified as white noise, and (3) the inclusion of an irrelevant unit root process in VAR.