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Forecasting Australian Macroeconomic Variables Using a Large Dataset

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  • Sarantis Tsiaplias

    (Melbourne Institute of Applied Economic and Social Research, The University of Melbourne)

  • Chew Lian Chua

    ()

Abstract

This paper investigates the forecasting performance of the diffusion index approach for the Australian economy, and considers the forecasting performance of the diffusion index approach relative to composite forecasts. Weighted and unweighted factor forecasts are benchmarked against composite forecasts, and forecasts derived from individual forecasting models. The results suggest that diffusion index forecasts tend to improve on the benchmark AR forecasts. We also observe that weighted factors tend to produce better forecasts than their unweighted counterparts. We find, however, that the size of the forecasting improvement is less marked than previous research, with the diffusion index forecasts typically producing mean square errors of a similar magnitude to the VAR and BVAR approaches. JEL Classification: C22; C53; E17

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Bibliographic Info

Paper provided by Melbourne Institute of Applied Economic and Social Research, The University of Melbourne in its series Melbourne Institute Working Paper Series with number wp2008n04.

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Length: 25 pages
Date of creation: Feb 2008
Date of revision:
Handle: RePEc:iae:iaewps:wp2008n04

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Keywords: PDiffusion indexes; Forecasting; Australia.;

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Cited by:
  1. de Silva, Ashton J, 2010. "Forecasting Australian Macroeconomic variables, evaluating innovations state space approaches," MPRA Paper 27411, University Library of Munich, Germany.

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