Real-Time Model Uncertainty is Real

Brian Ironside and Robert Tetlow find a surprisngly large degree of model uncertainty in the principal macro model used by the Federal Reserve Board:

Real-Time Model Uncertainty in the United States: The Fed from 1996-2003, by Brian Ironside and Robert Tetlow, CEPR Discussion Paper No. 5305: Abstract We study 30 vintages of FRB/US, the principal macro model used by the Federal Reserve Board staff for forecasting and policy analysis. To do this, we exploit archives of the model code, coefficients, baseline databases and stochastic shock sets stored after each FOMC meeting from the model's inception in July 1996 until November 2003. The period of study was one of important changes in the US economy with a productivity boom, a stock market boom and bust, a recession, the Asia crisis, the Russian debt default, and an abrupt change in fiscal policy. We document the surprisingly large and consequential changes in model properties that occurred during this period and compute optimal Taylor-type rules for each vintage. We compare these optimal rules against plausible alternatives. Model uncertainty is shown to be a substantial problem; the efficacy of purportedly optimal policy rules should not be taken on faith. We also find that previous findings that simple rules are robust to model uncertainty may be an overly sanguine conclusion. [open link, outline of Lucrezia Reichlin discussion]