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  • Krueger_Nolte2015-full

    Rights statement: This is the author’s version of a work that was accepted for publication in Journal of Banking & Finance. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Banking & Finance, 72 2016 DOI: 10.1016/j.jbankfin.2015.05.007

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Disagreement versus uncertainty: evidence from distribution forecasts

Research output: Contribution to journalJournal article

Published
<mark>Journal publication date</mark>11/2016
<mark>Journal</mark>Journal of Banking and Finance
Issue numberSuppl.
Volume72
Number of pages15
Pages (from-to)172-186
Publication statusPublished
Early online date20/06/15
Original languageEnglish

Abstract

We use a cross-section of economic survey forecasts to predict the distribution of US macro variables in real time. This generalizes the existing literature, which uses disagreement (i.e., the cross-sectional variance of survey forecasts) to predict uncertainty (i.e., the conditional variance of future macroeconomic quantities). Our results show that cross-sectional information can be helpful for distribution forecasting, but this information needs to be modeled in a statistically efficient way in order to avoid overfitting. A simple one-parameter model which exploits time
variation in the cross-section of survey point forecasts is found to perform well in practice.

Bibliographic note

This is the author’s version of a work that was accepted for publication in Journal of Banking & Finance. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Banking & Finance, 72 2016 DOI: 10.1016/j.jbankfin.2015.05.007