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

Workshop on Standardisation Brussels, 14-15 October 2010

Comparative review of SDC and SA

standardsJean Marc MUSEUX – Eurostat

Workshop on StandardisationBrussels, 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


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


Why SA and SDC ?


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


Why SA and SDC


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


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



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



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, …)


inp

ut

ou

tpu

t

Implementation

Knowledge Generation

(R&D/innovation)

Good-practiceGeneration

(ESSnets)

& Tools

Knowledge Formalisation

CompetenceBuilding

OperationalGovernance

Production Strategy

Quality

Methodology

resources

products

Framework for analysing process leading to standard


Good-practiceGeneration(ESSnets)

32

4 QualityProduction

Strategy


Methodology

Implementation& Tools


(R&D/innovation)

4

Competence & Capacity

Building3

3

31

2

1

1

input

RE

SO

UR

CE

S

Operational gouvernance

PR

OD

UC

TS

output

Tracking back SA standardisation process

2

2

2

1:Eurostat initial studies on SA:

1995-1999

2: Eurostat development of Demetra1999-2005

3: SASG and guidelines2006-2009

3

4: Demetra + cooperative development2009-2010


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


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)



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



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)



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)


QualityProduction

Strategy (CVD)


(LDF)

Methodology

Implementation

& Tools (IT)

Good-practiceGeneration(ESSnets)


(R&D/innovation)

4

4

4

Competence & Capacity

Building

2

3

3

33

31

2

21

1

input

RE

SO

UR

CE

S

Operational gouvernance

PR

OD

UC

TS

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

2007-20094 Next steps


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


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