Estimating consumer confidence using time series models
Estimating monthly consumer confidence indicators using structural time series models.
The Dutch Consumer Survey measures consumer confidence in the Netherlands with a monthly frequency. In this paper a model-based inference procedure based on a multivariate structural time series model is developed for the production of monthly figures about consumer confidence. The input for the model consists of five series of direct estimates for the indices, that are used to construct the consumer confidence index. The model improves the accuracy of the estimates for consumer confidence, since it provides a better separation of measurement error and sampling error from estimated target parameters. A second problem addressed in this paper is related to the transition to a new survey process in 2017. Structural time series models in combination with a parallel run are applied to estimate discontinuities induced by the redesign. A backcasting algorithm designed for the consumer confidence variables is developed to construct uninterrupted series about consumer confidence that date back to 1986.