I would like to share with you some of my thoughts about economic forecasts and monetary policy. I will begin with some comments about the economy's recent performance and the outlook for 2006. Next, I will explain why making sound policy decisions requires me to think about both the demand and...

President Pianalto spoke of her perspective on the economy and inflation. She explained how some critical assumptions affect her economic projections and talked about the role that inflation expectations play in the current environment.

President Pianalto spoke about the Federal Reserve's economic projections and shared her current views on the state of the economy.

Economic forecasts are essential tools for monetary policymakers. But behind the numbers of any given forecast, demand- or supply-side factors could be at play, each requiring very different policy responses. For this reason, explains Sandra Pianalto, the president and chief executive officer of...

President Pianalto spoke of her perspective on the economy and inflation. She explained how some critical assumptions affect her economic projections and talked about the role that inflation expectations play in the current environment.

I would like to share with you some of my thoughts about economic forecasts and monetary policy. I will begin with some comments about the economy's recent performance and the outlook for 2006. Next, I will explain why making sound policy decisions requires me to think about both the demand and...

President Pianalto spoke about the Federal Reserve's economic projections and shared her current views on the state of the economy.

In this paper, we present a forecasting technique that uses contemporaneous correlations for forecasting in a time series model when only a subset of the variables are available for the current period. This method potentially provides more accurate forecasts than the standard time series...

The purposes of this study are two: 1) to compare the forecasting abilities of the three methods: univariate autoregressive integrated moving average (ARIMA), multivariate autoregressive integrated moving average (MARIMA), and vector autoregression (both unconstrained — VAR — and Bayesian...

The estimation of large vector autoregressions with stochastic volatility using standard methods is computationally very demanding. In this paper we propose to model conditional volatilities as driven by a single common unobserved factor. This is justified by the observation that the pattern of...