C. Calizzani – G.L. Mazzi – R. Ruggeri Cannata Eurostat Quality 2008 , Rome 8 -11 July 2008

1. European Statistical System guidelines on seasonal adjustment: a major step towards PEEIs harmonisation C. Calizzani – G.L. Mazzi – R. Ruggeri Cannata Eurostat Quality 2008 , Rome 8 -11 July 2008

2. Introduction (1) • Crucial role in the production process of infra-annual statistics • Reliability • Comparability • Seasonally adjusted data: reference key indicators for analysis and forecasting exercises • Several aspects: • Treatment of calendar effects • Outliers • Temporal and sectoral reconciliation • Revisions policy • Etc. ESS guidelines on seasonal adjustment

3. Introduction (2) • Well known tools: • TRAMO-SEATS • Census II X-12 ARIMA • Unobserved components based decomposition • Same seasonal adjustment tool can produce quite different seasonally adjusted results Need for harmonisation ESS guidelines on seasonal adjustment

4. ESS specificities (1) • More than 27 members plus Eurostat • Different characteristics of national statistical systems • Different level of expertise • Different internal organisations • Legal acts as the major instrument for harmonisation of statistical production • Rarely giving clear rules for seasonal adjustment • Seasonal adjustment performed on the basis of sectoral and national practices • Lack of comparability ESS guidelines on seasonal adjustment

5. ESS specificities (2) • European aggregates derived from national data • Aggregation • Estimation • Aggregation/estimation • Crucial role of harmonisation for the quality of European aggregates • Harmonisation of seasonal adjustment needed • Relevant discrepancies in: • calendar adjustment • seasonal adjustment • Revisions policies ESS guidelines on seasonal adjustment

6. ESS specificities (3) • Several recommendations for the harmonisation of seasonal adjustment practices • ECOFIN Council • Economic and Financial Committee (EFC) • Committee for Monetary, Finance and Balance of payments statistics (CMFB) • Key points: • High degree of harmonisation of seasonal and calendar adjustment practices for Principal European Economic Indicators (PEEIs) needed • Convergence of revisions policy for seasonal adjusted data • Improvements on the communication on seasonally and calendar adjusted data ESS guidelines on seasonal adjustment

7. ESS specificities (4) • Some already existing guidelines on seasonal adjustment • U. S. Census Bureau • Statcan • ONS • Synthetic versus detailed guidelines • Complexity of the harmonisation problem • Sectoral level • Geographical level • Privileging detailed guidelines • Eurostat guidelines 2006 starting point ESS guidelines on seasonal adjustment

8. ESS specificities (5) • European Statistics Code of Practice: definition of good practices covering the institutional environment, the statistical processes and its outputs • Principle 7: Sound methodology must underpin quality statistics. This requires adequate tools, procedures and expertise • Principle 14: European statistics should be consistent internally, over time and comparable between regions and countries… • Principle 15: European statistics should be presented in a clear and understandable form, disseminated in a suitable and convenient manner, available and accessible on an impartial basis with supporting metadata and guidance ESS guidelines on seasonal adjustment

9. Main characteristics • Sound methodology • Completeness • Flexibility • Pragmatism • Clarity • User-oriented • Transparency of seasonal adjustment practices • Expertise development and capacity building ESS guidelines on seasonal adjustment

10. Guidelines Table of Contents (1) • 0 – SEASONAL ADJUSTMENT BENEFITS AND COSTS • 1 - PRE-TREATMENT • 1.1: Objectives of the pre-treatment of the series • 1.2: Graphical analysis of the series • 1.3: Calendar adjustment • 1.3.1: Methods for trading/working day adjustment • 1.3.2: Correction for moving holidays • 1.3.3: National and EU/euro area calendars • 1.4: Outlier detection and correction • 1.5: Model selection • 1.6: Decomposition scheme • 2 - SEASONAL ADJUSTMENT • 2.1: Choice of seasonal adjustment approach • 2.2: Consistency between raw and seasonally adjusted data • 2.3: Direct versus indirect approach • 2.3.1: Direct versus indirect approach: dealing with data from different agencies ESS guidelines on seasonal adjustment

11. Guidelines Table of Contents (2) • 3 - REVISIONS POLICIES • 3.1: General revisions policy • 3.2: Concurrent versus current adjustment • 3.3: Horizon for published revisions • 4 - QUALITY OF SEASONAL ADJUSTMENT • 4.1: Validation of seasonal adjustment • 4.2: Quality measures for seasonal adjustment • 4.4: Comparing alternative approaches and strategies • 4.5: Metadata template for seasonal adjustment • 5 - SPECIFIC ISSUES ON SEASONAL ADJUSTMENT • 5.1: Seasonal adjustment of short time series • 5.2: Treatment of problematic series • 6 - DATA PRESENTATION ISSUES • 6.1: Data availability in databases • 6.2: Press releases ESS guidelines on seasonal adjustment

12. Chapters’ structure • Chapters subdivided into specific items describing different steps of the seasonal adjustment process • Items presented in a standard structure providing: • Description of the issue • List of options which could be followed to perform the concerned step • Prioritized list of three alternatives from the most recommended one to the one to be avoided (A,B, and C) • A synthetic list of main references • Added value: • Conceptual framework and practical implementation steps • Both for experienced users and beginners ESS guidelines on seasonal adjustment

13. Example: 2.1 ESS guidelines on seasonal adjustment

14. Pre-treatment - Key topics • Removal of non-linearity and deterministic effects affecting a proper identification of the seasonal component • Detailed graphical analysis as essential starting point for the detection of all effects • Linearization of the series • Calendar effects • Outliers • Modelling and extrapolating time-series • Identification of ARIMA models ESS guidelines on seasonal adjustment

15. Pre-treatment – Main implications • Use of national calendars to improve and better tune calendar adjustment • Estimation of proper calendar effects represented by the deviation of the number of working or trading days from their long-term monthly/quarterly average • Part of calendar effects are seasonal and do not have to be removed • Statistical and economic validation of size and sign of regression coefficients • Accurate identification and correction of outliers by type • More conservative approach recommended at the end of the series ESS guidelines on seasonal adjustment

16. Seasonal adjustment – Key topics • Identification of recommended filters to remove seasonality • TRAMO-SEATS • Census II X-12 ARIMA • Structural time series models • Relationship between non seasonally adjusted data, calendar adjusted data and seasonally adjusted data • Time consistency • How to impose to a set of seasonally adjusted data the same aggregation constraints corresponding to raw data • Direct versus indirect ESS guidelines on seasonal adjustment

17. Seasonal adjustment – Main implications • Focus on TRAMO-SEATS and X-12 ARIMA: widely used and most developed methods • Structural models also acceptable if well-defined pre-treatment module available • Other approaches discarded • No guidance on which method to prefer and why • applying the same method to a given set of related series • No methodological rational in imposing time consistency between raw, calendar and seasonally adjusted data • Strong users’ request for time consistency, especially in some areas • Direct approach to be preferred when component series show similar seasonal patterns, indirect otherwise • Check of residual seasonality • Considering users’ preferences for sectoral and geographical consistency ESS guidelines on seasonal adjustment

18. Revisions policy – Key topics • Causes of seasonally adjusted data revisions • Raw data revisions • Revisions specific to seasonal and calendar adjustment methods • Need for a general policy for seasonal adjustment • Transparent • Coherent • Publicly available • Timing of revisions based on trade-off between precision and accuracy • Current versus concurrent adjustment • Depth of revisions ESS guidelines on seasonal adjustment

19. Revisions policy – Main implications • Seasonal adjusted data published according to the scheduling of raw data • Release calendar • Most appropriate strategy for re-identification and re-estimation of parameters and filters based on: • Number of periods revised in raw data • Stability of the seasonal component • Presence of benchmarking constraints • Depth of revisions should take into account: • Depth of raw data revisions • Number of periods needed to stabilise the seasonal filters results ESS guidelines on seasonal adjustment

20. Quality of seasonal adjustment – Key topics • Validation of seasonal adjusted data before their dissemination • Check for absence of residual seasonal and calendar effects • Stability and reliability of estimates • Definition of appropriate quality measures to assess the quality of seasonal adjustment • Defining a common set of quality measures • Comparing alternative seasonal adjustment methods • Comparing alternative seasonal adjustment strategies • Documenting all seasonal adjustment steps ESS guidelines on seasonal adjustment

21. Quality of seasonal adjustment – Main implications • Validation of results by using a large set of quality measures • Specific measures to each method • Additional measures • Detailed graphical analysis • Identification of a common set of quality measures • Helping users in comparative analysis • TRAMO-SEATS versus X-12 ARIMA • Direct versus indirect • Definition of an harmonised metadata template for seasonal and calendar adjustment ESS guidelines on seasonal adjustment

22. Specific issues on seasonal adjustment – Key topics • Overall quality of seasonal adjustment affected by: • Length of time-series • Presence of strange features • Non-linearity • Outliers • Volatility • Special treatment needed • Particular attention to key indicators ESS guidelines on seasonal adjustment

23. Specific issues on seasonal adjustment – Main implications • No seasonal adjustment for series shorter than 3 years • Awareness of the instability of seasonally adjusted data for series of 3 - 7 years length • Assessing a specific strategy for re-identification and re-estimation of filters and parameters • Users information • Case by case approach for series with high degree of irregularity • Use of standard tools ESS guidelines on seasonal adjustment

24. Conclusions (1) • Major step towards the harmonisation of PEEIs production • Enhancing Quality • Improvement of comparability • Robustness and reliability of European aggregates • Transparency • Promoting best practices • Great contribution to the international methodological and empirical debate • Largely supported inside and outside European Union ESS guidelines on seasonal adjustment

25. Conclusions (2) • Efforts required to Eurostat production units and Members States to become compliant with the guidelines • Based on voluntary commitment • Implementation plan to be developed • Monitoring strategy • Regular reporting to institutional bodies • Collecting information inside and outside Eurostat on seasonal adjustment practices • Metadata template ESS guidelines on seasonal adjustment

26. Thank you for your attention! ESS guidelines on seasonal adjustment