``Taylored'' Rules. Does One Fit All?

Modern monetary policymakers consider a huge amount of information in their evaluation of events and contingencies. However, most research on monetary policy relies on simple rules, and one relevant underpinning for this choice is the good empirical fit of the Taylor rule. This paper challenges the solidness of this foundation. We model the Federal Reserve reaction function during the Greenspan tenure as a Logistic Smoothing Transition Regime model in which a series of economically meaningful transition variables drive the transition across monetary regimes and allow the coefficients of the rule to change over time. We argue that estimated linear rules are weighted averages of the actual rules working in the diverse monetary regimes, where the weights merely reflect the length and not necessarily the relevance of the regimes. Thus, the actual presence of finer monetary policy regimes corrupts the general predictive and descriptive power of linear Taylor-type rules.