Using a Bayesian learning model with heterogeneity across agents, our study aims to identify the relative importance of alternative pathways through which professional forecasters disagree and reach consensus on the term structure of inflation and real GDP forecasts, resulting in different...

Using a standard decomposition of forecast errors into common and idiosyncratic shocks, we show that aggregate forecast uncertainty can be expressed as the disagreement among the forecasters plus the perceived variability of future aggregate shocks. Thus the reliability of disagreement as a...

Transportation Indicators and Business Cycles recognises the important role the transportation sector plays in business cycle propagation and develops indicators for this sector to identify its current state, and predict its future. The reference cycle is defined, including business and growth...

This paper provides a detailed analysis of the forecasts of real GDP, inflation and unemployment made by individual members of the Federal Open Market Committee (FOMC) for the period 1992–2003. Despite a general tendency for the committee members to underpredict real GDP over the sample...

Relying on the well-established theoretical result that uncertainty has a common and an idiosyncratic component, we propose a new measure of earnings forecast uncertainty as the sum of dispersion among analysts and the variance of mean forecast errors estimated by a GARCH model. The new measure...

We propose an adaptive truncated product method that facilitates the selection of the truncation point among a set of candidates. To efficiently estimate the distribution of the proposed method when the p-values are correlated, we develop a single-layer bootstrap procedure.