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...

Evaluation methodologies for rare events from meteorology, psychology and medical diagnosis are used to examine the value of probabilistic forecasts of real GDP declines during the current quarter (Q0) and each of the next four quarters (Q1–Q4) using data from the Survey of Professional...

We study the role of the well-known monthly diffusion indices produced by the Institute for Supply Management (ISM) in nowcasting current quarter US GDP growth. In contrast to the existing literature on ISM surveys, we investigate their marginal impact on these nowcasts when large unbalanced...

This paper provides a critical review of the popular Carlson–Parkin (CP) quantification method using household-level data from the University of Michigan’s Survey of Consumers. We find strong evidence against the threshold constancy, symmetry, homogeneity, and overall unbiasedness...

We combine the probability forecasts of a real GDP decline from the US Survey of Professional Forecasters, after trimming the forecasts that do not have “value”, as measured by the Kuiper Skill Score and in the sense of Merton (1981). For this purpose, we use a simple test to evaluate the...