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Can consumer sentiment and its components forecast Australian GDP and consumption?

Listed author(s):
  • Chew Lian Chua

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

  • Sarantis Tsiaplias

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

This paper examines whether the disaggregation of consumer sentiment data into its sub-components improves the real-time capacity to forecast GDP and consumption. A Bayesian error correction approach augmented with the consumer sentiment index and permutations of the consumer sentiment sub-indices is used to evaluate forecasting power. The forecasts are benchmarked against both composite forecasts and forecasts from standard error correction models. Using Australian data, we find that consumer sentiment data increase the accuracy of GDP and consumption forecasts, with certain components of consumer sentiment consistently providing better forecasts than aggregate consumer sentiment data. Copyright © 2009 John Wiley & Sons, Ltd.

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File URL: http://hdl.handle.net/10.1002/for.1120
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Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

Volume (Year): 28 (2009)
Issue (Month): 8 ()
Pages: 698-711

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Handle: RePEc:jof:jforec:v:28:y:2009:i:8:p:698-711
DOI: 10.1002/for.1120
Contact details of provider: Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966

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