On temporal aggregation and seasonal adjustment. Does the order matter?

• Activity Number: 523
• Type: Topic Contributed
• Date/Time: Wednesday, August 7, 2013 : 10:30 AM to 12:20 PM
• Sponsor: Business and Economic Statistics Section
• Author(s): Anna Ciammola*+ and Claudia Cicconi and Francesca Di Palma
• Companies: ISTAT and ISTAT and ISTAT
• Keywords: seasonal adjustment ; temporal aggregation ; ARIMA models ; revisions

Abstract

Many National Statistical Institutes apply temporal disaggregation techniques based on related indicators to estimate quarterly National accounts in unadjusted and seasonally adjusted form. In particular seasonally adjusted data are estimated through temporal disaggregation using seasonally adjusted related indicators. Since some of these indicators are available at monthly frequency, seasonal adjustment (SA) can be performed before or after temporal aggregation (TA). In general, using the information content of monthly data is expected to provide more accurate estimates. However, when SA is performed through ARIMA model-based procedures, using quarterly aggregated data can result in better properties in terms of revisions. The issue of TA of seasonal ARIMA models is largely documented in the econometric literature. Based on this literature, our work investigates if the order in which TA and SA are performed has an impact on the revision process of the quarterly adjusted data. Our conclusions are drawn by looking at the size of revisions and the speed of convergence of the concurrent estimates to the final estimates. Results are presented based on both simulated and observed data.