Assessing direct and indirect seasonal adjustment in state space - a comparison between ordinary and optimal approaches
2013 (English)Report (Other academic)
The problem of whether seasonal adjustment should be used prior to or after aggregation of time series is quite old. We tackle the problem using the state space representation and the variance/covariance structure. The variances of the estimated components are compared for direct and indirect adjustment and also to the optimal adjustment method. The covariance structure between the time series is important for the relative efficiency. Indirect adjustment is always best when the series are independent, but when the series or the measurement errors are negatively correlated, direct estimation may be much better in the above sense. Some covariance structures indicate that direct adjustment should be used while others indicate that indirect approaches are more efficient. Signal to noise ratios and relative variances are used for inference.
Place, publisher, year, edition, pages
Stockholm, 2013. , 24 p.
Research Report / Department of Statistics, Stockholm University, ISSN 0280-7564 ; 2013:1
covariance, signal to noise, efficiency, indirect seasonal adjustment
Probability Theory and Statistics
Research subject Statistics
IdentifiersURN: urn:nbn:se:su:diva-89235OAI: oai:DiVA.org:su-89235DiVA: diva2:616537