A Comparison of Seasonal Adjustment Methods: Dynamic Linear Models versus TRAMO/SEATS
2013 (English)Report (Other academic)
Seasonal adjustment can be done in the state space framework by Dynamic Linear Models. This approach is compared with seasonal adjustment by TRAMO/SEATS. The comparison uses simulated time series and real Swedish foreign trade data, the latter allowing a discussion on the consistency issue in aggregation, i.e. direct versus indirect seasonal adjustment. We start by a simple dynamic model and then increase the model structure using Gibbs sampling to identify coefficients for the state evolution matrix. Our empirical study shows that the simpler state spate approach exaggerates seasonal adjustment while the extended model with sampled coefficients may offer a tool for seasonal adjustment. For simulated data, we find that TRAMO/SEATS is better than the state space approach.
Place, publisher, year, edition, pages
2013. , 22 p.
Research Report / Department of Statistics, Stockholm University, ISSN 0280-7564 ; 2013:2
Dynamic Linear Models, DLM, seasonal adjustment, consistency, foreign trade
Probability Theory and Statistics
IdentifiersURN: urn:nbn:se:su:diva-89141OAI: oai:DiVA.org:su-89141DiVA: diva2:616519