Skip to main content

Consumer sentiment and consumer spending: decomposing the Granger causal relationship in the time domain

Buy Article:

$55.00 plus tax (Refund Policy)

Abstract:

It is often believed that the consumer sentiment index has predictive power for future consumption levels. While Granger causality tests have already been used to test for this, no attempt has been made yet to quantify the predictive power of the consumer sentiment index over different time horizons. In this article, we decompose the Granger causality at different time lags, by looking at a sequence of nested prediction models. Since the consumer sentiment index turns out to be cointegrated with real consumption, we resort to error correcting models. Four consumption series are studied, namely total real consumption, real consumption of durables, non-durables and services. Among other findings, we show that the consumer sentiment index Granger causes future consumption with an average time lag of 4-5 months. Furthermore, it is found that the consumer sentiment index has more incremental predictive power for consumption of services than for consumption of durables or non-durables, and that the index is not only useful as a predictor at the very short term, but keeps predictive power at larger time horizons.

Document Type: Research Article

DOI: https://doi.org/10.1080/00036840500427791

Affiliations: 1: Faculty of Economics and Applied Economics, Katholieke Universiteit Leuven, 3000 Leuven, Belgium 2: Faculty of Economics and Applied Economics, Katholieke Universiteit Leuven, 3000 Leuven, Belgium,Erasmus Research Institute of Management, Erasmus Universiteit Rotterdam, The Netherlands

Publication date: 2007-01-01

More about this publication?
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more