Forecast Densities for Economic Aggregates from Disaggregate Ensembles

Francesco Ravazzolo and Shaun Vahey

CAMA Working Papers from Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University

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.

JEL-codes: C11 C32 C53 E37 E52 (search for similar items in EconPapers)
Pages: 31 pages
Date: 2010-04
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Citations: View citations in EconPapers (2)

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Related works:
Journal Article: Forecast densities for economic aggregates from disaggregate ensembles (2014)
Working Paper: Forecast densities for economic aggregates from disaggregate ensembles (2010)
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Persistent link: https://EconPapers.repec.org/RePEc:een:camaaa:2010-10

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