An examination of whether one should seasonally adjust data before developing multivariate time series models to provide forecasts.

An argument that variations of extant general-equilibrium monetary models can generate real-time economic forecasts comparable in accuracy to those contained in the Federal Reserve Board's "Greenbook" briefing documents.

A presentation of multivariate time series forecasting in which the data consist of a mixture of quarterly and monthly series. In particular, a monthly series of M1 is used to forecast quarterly GNP.

The premise of this study is that the regional economist can better understand the Ohio economy by studying the properties of important Ohio time series that can be identified and quantified through simple regression methods.

A comparison of the forecasting abilities of univariate ARIMA, multivariate ARIMA, and VAR, and examination of whether series should be differenced before estimating models for forecasting purposes.

This paper explores the hypothesis that the sources of economic and financial crises differ from noncrisis business cycle fluctuations. We employ Markov-switching Bayesian vector autoregressions (MS-BVARs) to gather evidence about the hypothesis on a long annual U.S. sample running from 1890 to...

This paper shows entropic tilting to be a flexible and powerful tool for combining medium-term forecasts from BVARs with short-term forecasts from other sources (nowcasts from either surveys or other models). Tilting systematically improves the accuracy of both point and density forecasts, and...

Small or medium-scale VARs are commonly used in applied macroeconomics for forecasting and evaluating the shock transmission mechanism. This requires the VAR parameters to be stable over the evaluation and forecast sample, or to explicitly consider parameter time variation. The earlier...

In this paper we investigate the forecasting performance of the median CPI in a variety of Bayesian VARs (BVARs) that are often used for monetary policy. Until now, the use of trimmed-mean price statistics in forecasting inflation has often been relegated to simple univariate or...

In a speech to the Economic Club of Pittsburgh, Federal Reserve Bank of Cleveland President and CEO Sandra Pianalto discussed why and how the Bank develops its economic forecasts and why the role of judgment becomes paramount for forecasting during uncertain times such as these. She concluded...