This paper analyses the forecasting performance of monetary policy reaction functions using U.S. Federal Reserve's Greenbook real-time data. The results indicate that artificial neural networks are able to predict the nominal interest rate better than linear and nonlinearTaylor rule models as...

In this paper, we derive a modification of a forward-looking Taylor rule, which integrates two variables measuring the uncertainty of inflation and GDP growth forecasts into an otherwise standard New Keynesian model. We show that certainty-equivalence in New Keynesian models is a consequence of...

We combine questions from the Michigan Survey about the future path of prices, interest rates, and unemployment to investigate whether households are aware of the basic features of U.S. monetary policy. Our ndings support the view that at least some groups of households form their expectations...

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...