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...

This paper describes the existing research (as of February 2008) on real-time data analysis, divided into five areas: (1) data revisions; (2) forecasting; (3) monetary policy analysis; (4) macroeconomic research; and (5) current analysis of business and financial conditions. In each area,...