Monetary policy rules based on real-time data

In recent years, simple policy rules have received attention as a means to a more transparent and effective monetary policy. Often, however, the analysis is based on unrealistic assumptions about the timeliness of data availability. This permits rule specifications that are not operational and ignore difficulties associated with data revisions. This paper examines the magnitude of these informational problems using Taylor's rule as an example. I demonstrate that the real-time policy recommendations differ considerably from those obtained with the ex post revised data and are revised substantially even a year after the relevant quarter. Further, I show that estimated policy reaction functions obtained using the ex post revised data can yield misleading descriptions of historical policy. Using Federal Reserve staff forecasts I show that in the 1987-1992 period simple forward-looking specifications describe policy better than comparable Taylor-type specifications, a fact that is largely obscured when the analysis is based on the ex post revised data.