Transcript Slide 1

Developments of the Data Infrastructure in
Germany since the end of the 90‘s
PD Dr. Hilmar Schneider, IZA Bonn
ODaF Europe 2009,
IZA, Bonn, April 2nd-3rd, 2009
Who are the key players in official micro data production
in Germany?
• Independent Statistical Offices at the Länder level are collecting
data on household and firm level (Micro census, census, income
and expenditure survey, cost structure survey, etc.)
• Federal Statistical Office, Wiesbaden (co-ordinates statistical offices
at the Länder level, but has no directives; however, many official
surveys are based on federal law)
• Federal Labor Agency, Nürnberg (main source: individual data that
are relevant for pension claims; individual data related to job search
and active labor market policy)
• Federal Reserve Bank of Germany (firm level data and data related
to the monetary market)
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Philosophy of the Federal Statistical Offices
• Providing aggregate figures for relevant issues of the economy and
the society
• Data collection according to legal duties
Consequences
• Relevant information is collected independently in different surveys
(Example: Hourly wages can only be computed on the aggregate
level)
• Huge waste of information
• Heterogeneity on the micro level cannot be exploited for the
identification of causal structures
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The situation in the middle of the 90‘s
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Access to micro data from official statistics was almost impossible
No interaction between official statistics and the research community
Researchers had to address directly to the administration
Prohibitive cost for access to micro data
Little documentation of available data
Huge concern about the potential of de-anonymization of official
micro data
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What caused the tipping point at the end of the 90‘s?
• Large-scale research project on anonymization of micro data
(Hauser/Müller)
• As a result, the concept of factual anonymization became accepted
• Memorandum by Hauser, Wagner, Zimmermann:
Erfolgsbedingungen empirischer Wirtschaftsforschung und
empirisch gestützter wirtschafts- und sozialpolitischer Beratung
(IZA DP No. 14)
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The process triggered by the memorandum
• In late 1999, the Federal Minister for Education and Research called
a „Commission for the improvement of informational infrastructure
between science and statistics“
• In early 2001, the commission published its report („Ways to an
improved informational infrastructure“)
• The report contained 35 recommendations, among them
 Creation of research data centres and data service centres
 Creation of public use files from official micro data
 Creation of a Council for Social and Economic Data (RatSWD)
• In late 2001, the Constituing Council for Social and Economic Data
was formed
• In 2002, the first research data centres were founded
• In late 2004, the Council for Social and Economic Data was
constituted
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About the RatSWD
• 12 members, 6 of them elected every two years by a scientist
community (researchers with a doctoral degree), the other 6 are
mandated by research data centres and data service centres
• Funded by the Federal Ministry of Education and Research
• Main objectives:
 Advising federal governments with regard to further improvement of
data infrastructure
 Recommendations regarding the establishment and evaluation of
research data centres and data service centres
 Stimulating and supporting projects that might contribute to the
improvement of data infrastructure
 Promotion of scientific offspring
 Improving the interrelations between science and official statistics
• The RatSWD has been called for six years and is currently
undergoing an evaluation of its work
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About the RatSWD
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The research data centres
• Data Research Centre of the Federal Statistical Office
• Data Research Centre of the Statistical Offices of the Länder
• Data Research Centre of the Federal Labor Agency at the Institute
for Employment Research
• Data Research Centre of the German Pension Insurance
• Data Research Centre at the Institute for Educational Progress
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What are the objectives of Research Data Centres?
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Provision of available data for scientific research
Compliance with data protection rules
Equal treatment of data users
Creation of user friendly data
Independent research
Avoiding privileged access to micro data
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Structural Problems of Research Data Centres
• Dependent part of a public authority instead of independent
institution
• Fuzzy frontier between routine task of authority and special task of
RDC
• Declarative disposal with regard to external funds needed
• After initial funding by the Federal Ministry of Education and
Research has run out, internal legitimization is becoming dominant
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Synergy Effects
• KombiFid (establishment data based on surveys carried out by the
Federal Statistical Office, and the Deutsche Bundesbank with
establishment data of the Federal Labor Agency)
• Merged Biographies (employment status records of the Federal
Labor Agency merged with pension records of the German Pension
Insurance)
• McTax Panel (tax payer panel merged with data from micro census)
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The Data Service Centres
• IDSC at IZA
• German Micro Data Lab at GESIS
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What are the objectives of Data Service Centres?
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Provision of comparative data documentation (meta data)
Training and advising data users
Development of adequate concepts of anonymization
Development of prototypical scientific use files
Extension of analytical potential of available data sets
Service for data analysis (remote access)
Support for data users
Agency to international micro data sets
Preparation of virtual data library
Development of links across different data sources
Development of indicators
Independent research with focus on methodology
Many more ...
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Conflicts between Research Data Centres and
Data Service Centres
• Competition between RDCs and DSCs in the field of user service,
especially with regard to data documentation and remote data
access
• RDSs are under external pressure by service offered through DSCs
• RDCs are trying to make DSCs obsolete by adapting services that
were originally provided by DSCs
• Danger of losing comprehensive value added (e.g. comparative
documentation of data)
• RDCs may lose internal power of legitimation, if competitive
pressure vanishes
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Concluding remarks
• The creation of RDCs and DSCs has been a success story
• Competition between RDCs and DSCs should rather be understood
as a driving force for progress than a redundancy, which absorbes
ressources
• Unused potential for the creation of DSCs
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