Tracking Greenspan: Systematic and Unsystematic Monetary Policy Revisited

This Paper proposes a new framework to analyse systematic and unsystematic monetary policy within the same econometric model. As in Bernanke and Boivin, 2001, the model aims at capturing the following facts: monetary authorities use information from a large number of data series to extract a signal on current economic activity, which is typically measured with error. Due to strong collinearity between macroeconomic time series, relevant information is obtained by regressing the observables on few aggregates. Collinearity implies that a large panel of time series, which constitutes the information available to policy makers, can be represented as a dynamic factor model {it a la} Forni and Reichlin, 1998, Stock and Watson, 1999 and Forni et al., 2000. Here we show how, in this framework, shocks can be identified structurally and the parameters of monetary policy rules, conditional on these shocks, can be estimated. Our results for the US economy between 1982 and 2001 show that: (i) Two shocks capture 80% of the variance of key variables such as output and inflation at all horizons; (ii) The monetary shock mainly affects the term structure of interest rates, but has virtually no effect on output and inflation so that monetary policy affects the economy through its systematic behavior rather than by surprising agents; (iii) Since demand and technology have been the main forces for the dynamics of cyclical output and inflation during the Greenspan era, while supply shocks have been negligible, monetary authorities did not face any tradeoff between inflation and output. By stabilizing inflation conditionally on demand shocks, they also achieved output stabilization; (iv) Conditionally on demand, Greenspan followed the Taylor principle while, conditionally on technology, monetary policy did not respond; (v) Systematic monetary policy had a substantial role in output and inflation stabilization.