Forecast Densities for Economic Aggregates from Disaggregate Ensembles
Shaun P. Vahey
Australian National University (ANU) - Centre for Applied Macroeconomic Analysis (CAMA)
March 12, 2010
CAMA Working Paper No. 10/2010
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.
Keywords: Ensemble forecasting, disaggregates
JEL Classification: C11, C32, C53, E37, E52working papers series
Date posted: August 31, 2010
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