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Federal Reserve Bank of Cleveland
Working Papers (Old Series)
Frequency Dependence in a Real-Time Monetary Policy Rule
Richard Ashley
Kwok Ping Tsang
Randal Verbrugge

We estimate a monetary policy rule for the US allowing for possible frequency dependence—i.e., allowing the central bank to respond differently to more persistent innovations than to more transitory innovations, in both the unemployment rate and the inflation rate. Our estimation method uses real-time data in these rates—as did the FOMC—and requires no a priori assumptions on the pattern of frequency dependence or on the nature of the processes generating either the data or the natural rate of unemployment. Unlike other approaches, our estimation method allows for possible feedback in the relationship. Our results convincingly reject linearity in the monetary policy rule, in the sense that we find strong evidence for frequency dependence in the key coefficients of the central bank's policy rule: i.e., the central bank's federal funds rate response to a fluctuation in either the unemployment or the inflation rate depended strongly on the persistence of this fluctuation in the recently observed (real-time) data. These results also provide useful insights into how the central bank's monetary policy rule has varied between the Martin-Burns-Miller and the Volcker-Greenspan time periods.

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Richard Ashley & Kwok Ping Tsang & Randal Verbrugge, Frequency Dependence in a Real-Time Monetary Policy Rule, Federal Reserve Bank of Cleveland, Working Papers (Old Series) 1430, 19 Nov 2014.
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Keywords: Taylor rule; frequency dependence; spectral regression; real-time data
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