Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/209947 
Year of Publication: 
2010
Series/Report no.: 
Working Paper No. 2010/02
Publisher: 
Norges Bank, Oslo
Abstract: 
We propose a methodology for producing forecast densities for economic aggregates based on disaggregate evidence. Our ensemble predictive methodology utilizes a linear mixture of experts framework to combine the forecast densities from potentially many component models. Each component represents the univariate dynamic process followed by a single disaggregate variable. The ensemble produced from these components approximates the many unknown relationships between the disaggregates and the aggregate by using time-varying weights on the component forecast densities. In our application, we use the disaggregate ensemble approach to forecast US Personal Consumption Expenditure inflation from 1997Q2 to 2008Q1. Our ensemble combining the evidence from 11 disaggregate series outperforms an aggregate autoregressive benchmark, and an aggregate time-varying parameter specification in density forecasting.
Subjects: 
ensemble forecasting
disaggregates
JEL: 
C11
C32
C53
E37
E52
Persistent Identifier of the first edition: 
ISBN: 
978-82-7553-540-3
Creative Commons License: 
cc-by-nc-nd Logo
Document Type: 
Working Paper
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