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Aggregate and disaggregate sector forecasting using consumer confidence measures
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DOI：10.1016/0169-2070(95)00594-2.png)
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The usefulness of the combination of Katona's ''ability and willingness to buy'' framework and Bayesian vector autoregression for business forecasting was examined. Models were estimated with and without a measure of consumer confidence and with either a vector autoregression model with lag structure determined by a stepwise (VAR) or a Bayesian (BVAR) approach. Additionally, Katona's framework was tested at different levels of aggregation of consumer expenditures. Unlike in past research, monthly data were used in the operationalization of the framework. It was found that the BVAR, along with the consumer confidence measure, performed the best across three forecasting horizons and three performance measures. Any degradation of model performance at lower levels of aggregation across expenditure categories was only modest. The findings suggest that the use of BVAR, with consumer confidence index as a predictor should be considered in business forecasting.
Keyword:
Katona's framework
business forecasting
VAR
BVAR
index of consumer sentiment
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