1. 13-Jul-07 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. ESS guidelines on seasonal adjustment 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.

3. ESS guidelines on seasonal adjustment 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

4. ESS guidelines on seasonal adjustment 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

5. ESS guidelines on seasonal adjustment 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

6. ESS guidelines on seasonal adjustment 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

7. ESS guidelines on seasonal adjustment 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

8. ESS guidelines on seasonal adjustment 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

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

10. ESS guidelines on seasonal adjustment 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

11. ESS guidelines on seasonal adjustment 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

12. ESS guidelines on seasonal adjustment 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

13. ESS guidelines on seasonal adjustment Example: 2.1

14. ESS guidelines on seasonal adjustment 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

15. ESS guidelines on seasonal adjustment 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

16. ESS guidelines on seasonal adjustment 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

17. ESS guidelines on seasonal adjustment 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

18. ESS guidelines on seasonal adjustment 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

19. ESS guidelines on seasonal adjustment 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

20. ESS guidelines on seasonal adjustment 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

21. ESS guidelines on seasonal adjustment 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

22. ESS guidelines on seasonal adjustment 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

23. ESS guidelines on seasonal adjustment 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

24. ESS guidelines on seasonal adjustment 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

25. ESS guidelines on seasonal adjustment 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

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