Premium
Can consumer sentiment and its components forecast Australian GDP and consumption?
Author(s) -
Chua Chew Lian,
Tsiaplias Sarantis
Publication year - 2009
Publication title -
journal of forecasting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.543
H-Index - 59
eISSN - 1099-131X
pISSN - 0277-6693
DOI - 10.1002/for.1120
Subject(s) - consumer confidence index , consumption (sociology) , econometrics , index (typography) , economics , bayesian probability , aggregate (composite) , consumer spending , bayesian vector autoregression , sentiment analysis , computer science , macroeconomics , artificial intelligence , recession , social science , materials science , sociology , world wide web , composite material
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.