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Forecast Densities for Economic Aggregates from Disaggregate Ensembles

Listed author(s):
  • Francesco Ravazzolo
  • Shaun P. Vahey

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.

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File URL: https://cama.crawford.anu.edu.au/sites/default/files/publication/cama_crawford_anu_edu_au/2017-03/10_ravazzolo_vahey_2010.pdf
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Paper provided by Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University in its series CAMA Working Papers with number 2010-10.

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Length: 31 pages
Date of creation: Apr 2010
Handle: RePEc:een:camaaa:2010-10
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Web page: http://cama.crawford.anu.edu.au
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  28. repec:nsr:niesrd:337 is not listed on IDEAS
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