The U.S. economy performed well across the board in 1997, with low unemployment, robust economic growth, and the lowest sustained inflation in decades. Nevertheless, the current framework for monetary policymaking does not ensure that inflation is down for the count, says Federal Reserve Bank of...

The authors report the results of the estimation of a rich dynamic stochastic general equilibrium model of the U.S. economy with both stochastic volatility and parameter drifting in the Taylor rule. They use the results of this estimation to examine the recent monetary history of the U.S. and to...

Remarks before the Greater Houston Partnership, Houston, Texas, September 1, 2010 ; "If the fiscal and regulatory authorities are able to dispel the angst that they are reportedly causing, further accommodation may not be needed because the liquidity that has been built up on corporate balance...

We start from the assertion that a useful monetary policy design should be founded on more realistic assumptions about what policymakers can know at the time when policy decisions have to be made. Since the Taylor rule - if used as an operational device - implies a forward looking behaviour, we...

This study presents an extension of the Gaussian process regression model for multiple-input multiple-output forecasting. This approach allows modelling the cross-dependencies between a given set of input variables and generating a vectorial prediction. Making use of the existing correlations in...

In this paper, we document the forecasting performance of estimated basic dynamic stochastic general equilibrium (DSGE) models and compare this to extended versions which consider alternative expectation formation assumptions and financial frictions. We also show how standard model features,...

A structural break is viewed as a permanent change in the parameter vector of a model. Using taxonomies of all sources of forecast errors for both conditional mean and conditional variance processes, we consider the impacts of breaks and their relevance in forecasting models: (a) where the...