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Studies in Nonlinear Dynamics & Econometrics

Ed. by Mizrach, Bruce

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Volume 18, Issue 4 (Sep 2014)

Issues

Forecast densities for economic aggregates from disaggregate ensembles

Francesco Ravazzolo
  • Research Department, Norges Bank and Economic Department, BI Norwegian Business School, Oslo, Norway
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Shaun P. Vahey
Published Online: 2013-08-13 | DOI: https://doi.org/10.1515/snde-2012-0088

Abstract

We extend the “bottom up” approach for forecasting economic aggregates with disaggregates to probability forecasting. Our methodology utilises a linear opinion pool to combine the forecast densities from many disaggregate forecasting specifications, using weights based on the continuous ranked probability score. We also adopt a post-processing step prior to forecast combination. These methods are adapted from the meteorology literature. In our application, we use our approach to forecast US Personal Consumption Expenditure inflation from 1990q1 to 2009q4. Our ensemble combining the evidence from 16 disaggregate PCE series outperforms an integrated moving average specification for aggregate inflation in terms of density forecasting.

This article offers supplementary material which is provided at the end of the article.

Keywords: density combinations; disaggregates; ensemble forecasting

JEL codes: C11; C32; C53; E37; E52

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About the article

Corresponding author: Shaun P. Vahey, Warwick Business School, University of Warwick, Coventry, UK, e-mail:


Published Online: 2013-08-13

Published in Print: 2014-09-01


Citation Information: Studies in Nonlinear Dynamics & Econometrics, ISSN (Online) 1558-3708, ISSN (Print) 1081-1826, DOI: https://doi.org/10.1515/snde-2012-0088.

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