1. Workshop on Standardisation Brussels, 14-15 October 2010 Comparative review of SDC and SA standards Jean Marc MUSEUX – Eurostat

2. Workshop on Standardisation Brussels, 14-15 October 2010 Seasonal Adjustment and Statistical Disclosure Control Why SA and SDC ? State of the art of standards Process leading to standard Learnings and conclusions

3. Workshop on Standardisation Brussels, 14-15 October 2010 Why SA and SDC ? Statistical Disclosure Control X-sectional tabular output and micro data files Seasonal Adjustment Time-series and Infra-annual statistics “Historical” domains where Eurostat central methodological unit developed some expertise in the 90’s Important steps for Eurostat business process 5. Process - 6. Analyse Specific expertise independent of statistical domains

4. Workshop on Standardisation Brussels, 14-15 October 2010 Why SA and SDC ? Statistical Disclosure Control Committee on Statistical Confidentiality since 1997 Working group on Statistical Confidentiality since 2009 Seasonal Adjustment Informal Working Group on Seasonal Adjustment 1999- 2002 SA Steering Group since 2007 Dedicated working group for ESS coordination

5. Workshop on Standardisation Brussels, 14-15 October 2010 Why SA and SDC Statistical Disclosure Control Coherence required because secondary confidentiality in tables Disclosure risk increases if uncoordinated release at EU and MS level Strong impact on EU data utility Sensitivity of breach of confidentiality in the ESS Seasonal Adjustment Seasonally adjusted data: reference key indicators for analysis and forecasting exercises Reliability and comparability EU aggregate derived from MS series – need for coherence Non linear process with propagation of error Striking need for harmonisation

6. Workshop on Standardisation Brussels, 14-15 October 2010 SA standards – state of the art (1/3) ESS Guidelines on Seasonal Adjustment –Endorsed by CMFB and SPC in 2008 –SA process decomposed in substeps (pre-treatment, signal extraction, revision, release, metadata, …) –For each elementary steps, the guidelines lists three alternatives A, the best approach to be aimed at; B, acceptable and viable if A proved to be too costly C, practice to be avoided. –Provide a open framework to design SA process (guidance), Improve SA process (clear preference) benchmark several processes

7. Workshop on Standardisation Brussels, 14-15 October 2010 SA standards – state of the art (2/3) ESS Guidelines Implementation –Seasonal Adjustment Steering Group (SASG) in charge of overseeing the implementation of the guidelines –SASG is high level group bringing together Eurostat, ECB and SA experts in MS and CB –Main barriers for implementation 1) Lack of institutional recognition 2) Organisational issues 3) Cost of option A (human resources) 4) Methodological issues 5) Knowledge, skills 6) IT infrastructure

8. Workshop on Standardisation Brussels, 14-15 October 2010 SA standards – state of the art (3/3) ESS Guidelines Implementation –Three main strands for fostering implementation decided by SASG Information in sectoral WG, Scientific conferences Cooperative (re)development of a software tool (Demetra+) in line with the guidelines (A and B options can be implemented) Training, workshops (with experts) for spreading knowledge and exchange of experience –Further difficulties No global review and impact assessment Need to continuously refine, going beyond guidelines (crisis, …)

9. Workshop on Standardisation Brussels, 14-15 October 2010 input output Implementation Knowledge Generation (R&D/innovation) Good-practice Generation (ESSnets) & Tools Knowledge Formalisation Competence Building Operational Governance Production Strategy Quality Methodology resources products Framework for analysing process leading to standard

10. Workshop on Standardisation Brussels, 14-15 October 2010 Good-practice Generation (ESSnets) 3 2 4 Quality Production Strategy Knowledge Formalisation Methodology Implementation & Tools Knowledge Generation (R&D/innovation) 4 Competence & Capacity Building 3 3 3 1 2 Tracking back Seasonal Adjustment works 1 1 input RESOURCES Operational gouvernance PRODUCTS output Tracking back SA standardisation process 2 2 2 1:Eurostat initial studies on SA: 1995-1999 2: Eurostat development of Demetra 1999-2005 3: SASG and guidelines 2006-2009 3 4: Demetra + cooperative development 2009-2010

11. Workshop on Standardisation Brussels, 14-15 October 2010 SA standards process – key elements Early expertise development First Demetra tool –Did not achieve harmonisation –Distanciation from expertise SASG breakthrough –Technical expertise –Governance –Methodology Demetra+ –After methodology –Cooperative and open source

12. Workshop on Standardisation Brussels, 14-15 October 2010 SDC standards – state of the art (1/4) Tabular data –Standard tool for protecting tables Tau-Argus developed by Statistics Netherlands Financial support from Commission since 2001 Difficulty to integrate in standard production processes –Handbook on SDC (last edition 2010) – glossary and review of options –No standard (SDC depends on national perception and rules) –EU table protection at the border of feasibility –Lack of standardisation hampers release of EU figures (suboptimal solution)

13. Workshop on Standardisation Brussels, 14-15 October 2010 SDC standards – state of the art (2/4) Tabular data –First step towards standardisation Confidentiality Charter (SBS, Prodcom, Animal production) –Objective rules for protection of cells –Practical rules at domain level ensuring consistency between Eurostat and MS processing –Flexibility in primary confidentiality documented (flags) –Methodology for SDC of EU aggregate

14. Workshop on Standardisation Brussels, 14-15 October 2010 SDC standards – state of the art (3/4) Micro data protection –Baseline methodology and corresponding software (Mu-Argus – Statistics Netherlands) – suitable for one off application –Domain in constant development (computer science, Web,..) –Anonymisation of EU micro data –Output harmonisation through input harmonisation Same global recoding for all MS datasets Micro aggregation for all records Little flexibility Least common denominator effect Low information content (almost public use files)

15. Workshop on Standardisation Brussels, 14-15 October 2010 SDC standards – state of the art (4/4) Micro data protection – way forward –ISTAT model Q2008 – Community Innovation Survey PSD2010 – Harmonisation of SDC Bounded flexibility Core common disclosure scenario and risk assesment methodology Flexibility among a common set of methodologies for protecting records –adapting to country specificities –transparent parametrisation –good balance between global methods (recoding, top coding) and local methods (perturbation) –Data utility target (threshold) using common measures and constraint on comparability (benchmarking using key research statistics)

16. Workshop on Standardisation Brussels, 14-15 October 2010 Quality Production Strategy (CVD) Knowledge Formalisation (LDF) Methodology Implementatio n & Tools (IT) Good-practice Generation (ESSnets) Knowledge Generation (R&D/innovation) 4 4 4 Competence & Capacity Building 2 3 3 3 3 3 1 2 2 Tracking back Seasonal Adjustment works 1 1 input RESOURCES Operational gouvernance PRODUCTS output Tracking back SDC developments 2 2 2 4 1:CASC FP5 research project 1997-2004 2: CENEX project 2004-2006 3: ESSnet SDC II 2007-2009 4 Next steps

17. Workshop on Standardisation Brussels, 14-15 October 2010 SDC standards – key elements of the process Importance of research – early steps towards tool development – centric development – difficulty of integration Importance of ESSnet for sharing good practices Lack of technical governance –To identify best practices –To set up priorities Next steps –Technical governance (TF) –Open source development –More flexibility – stronger metadata

18. Workshop on Standardisation Brussels, 14-15 October 2010 * Not yet active Conclusions Review of two cases studies with difference outcomes Main differences political context technical governance type of guidelines Main communalities Need for harmonisation Need for expertise – research Process steps relatively independent of the statistical domain Need for flexibility Need for appropriate – sustainable software tools Living standard – need for maintenance