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Advances in Info-MetricsInformation and Information Processing across Disciplines$
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Min Chen, J. Michael Dunn, Amos Golan, and Aman Ullah

Print publication date: 2020

Print ISBN-13: 9780190636685

Published to Oxford Scholarship Online: December 2020

DOI: 10.1093/oso/9780190636685.001.0001

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PRINTED FROM OXFORD SCHOLARSHIP ONLINE (oxford.universitypressscholarship.com). (c) Copyright Oxford University Press, 2021. All Rights Reserved. An individual user may print out a PDF of a single chapter of a monograph in OSO for personal use. date: 13 June 2021

Estimating Macroeconomic Uncertainty and Discord

Estimating Macroeconomic Uncertainty and Discord

Using Info-Metrics

Chapter:
(p.290) 11 Estimating Macroeconomic Uncertainty and Discord
Source:
Advances in Info-Metrics
Author(s):

Kajal Lahiri

Wuwei Wang

Publisher:
Oxford University Press
DOI:10.1093/oso/9780190636685.003.0011

We apply generalized beta and triangular distributions to histograms from the Survey of Professional Forecasters (SPF) to estimate forecast uncertainty, shocks. and discord using an information framework, and we compare these with moment-based estimates. We find that these two approaches produce analogous results, except in cases where the underlying densities deviate significantly from normality. Even though the Shannon entropy is more inclusive of different facets of a forecast density, we find that with SPF forecasts it is largely driven by the variance of the densities. We use Jenson–Shannon Information to measure ex ante “news” or “uncertainty shocks” in real time, and we find that this “news” is closely related to revisions in forecast means, is countercyclical, and raises uncertainty. Using standard vector autoregression analysis, we confirm that uncertainty affects the real sector of the economy negatively.

Keywords:   density forecasts, uncertainty, disagreement, entropy measures, Jensen–Shannon Information, Survey of Professional Forecasters

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