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Can Consumer Sentiment and Its Components Forecast Australian GDP and Consumption?

  • Chew Lian Chua
  • Sarantis Tsiaplias

    ()

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

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-indexes 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 increases the accuracy of GDP and consumption forecasts, with certain components of consumer sentiment consistently providing better forecasts than aggregate consumer sentiment data.

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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 wp2008n03.

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Length: 20 pages
Date of creation: Feb 2008
Date of revision:
Handle: RePEc:iae:iaewps:wp2008n03
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