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

Chew Lian Chua, Sarantis Tsiaplias

Research output: Journal PublicationArticlepeer-review

12 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)698-711
Number of pages14
JournalJournal of Forecasting
Issue number8
Publication statusPublished - Dec 2009
Externally publishedYes


  • Bayesian
  • Cointegration
  • Composite forecast
  • Consumer sentiment

ASJC Scopus subject areas

  • Modelling and Simulation
  • Computer Science Applications
  • Strategy and Management
  • Statistics, Probability and Uncertainty
  • Management Science and Operations Research


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