House of Microdata (HoM) and Research Data and Service Centre
(RDSC) at the Deutsche Bundesbank – a Draft Concept
Workshop on Integrated Management of Micro-Databases,
hosted by the Banco de Portugal, Porto, June 20-22, 2013
Ulf von Kalckreuth, Deutsche Bundesbank
A mandate
Mandate for Statistics Dept in medium term strategic planning:
Enhance availability of micro data both for scientific research
and for analytical tasks
Background:
❙ New focus on financial stability – need for granular information by Banking
Supervision, the new Financial Stability Dept and the ECB in its new role
❙ Bundesbank Research Centre asking for support
Ulf von Kalckreuth, Deutsche Bundesbank
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Problems to solve
❙ Data management in Stat Dept and elsewhere not conceived to support
micro level analysis – micro data are intermediate products in a process of
creating statistical aggregates.
❙ No well structured data sets ready for analysis
❙ Documentation for the use of externals incomplete or missing
❙ Use of microdata subject to complicated sets of confidentiality rules.
Purpose of data use important. Level of confidentiality must be
systematically assigned to groups of users
❙ Data are created in different processes which are not integrated – cannot
be analysed simultaneously
Ulf von Kalckreuth, Deutsche Bundesbank
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Problems to solve
Working with new micro data extremely time intensive:
→ Data sets underused
→ Certain questions not adressed at all
→ Users liable to misinterprete data – analysis misleading
Ulf von Kalckreuth, Deutsche Bundesbank
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Suggestion
Set up a House of Microdata with the following tasks:
❙ Compilating, documenting and archiving micro data collections that are
informative for external research and analysis
❙ Providing a platform for rapid compilation of microdata for varying purposes
- analytical (extrnal) and cross-validation (internal)
❙ Enhancing existing data by record linkage – also based on external data
❙ Providing the micro data collections to internal and external users, within
the legal bounds relevant for each case
❙ Methodological and substantial (data content and interrelations) support
❙ Analytical work on behalf of internal clients in those cases, where clients
either do not have legal access or where the evaluation by client himself is
impossible due to time constraints or insufficient data expertise
❙ Limited amount of own research -- descriptive in nature and focussed on
the data provided by the unit
Ulf von Kalckreuth, Deutsche Bundesbank
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Suggestion
Create a potential for
❙ Receiving and disseminating data from other Depts and external sources
❙ Exchange of research data within the ESCB
Ulf von Kalckreuth, Deutsche Bundesbank
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Suggestion
❙ Statistics Dept cannot answer all possible questions. The production and
dissemination of micro data collections fit for analysis of externals is a new
statistical product sui generis: The result of the statistical process is not a
set of indicators but an information basis for users to work out their own
results, answering their own questions following their own criteria.
❙ Evaluations on the behalf of externals is a classical product: Moments and
quantiles of distributions are derived from the available granular information
❙ Own research needed to enhance methodological competence and
knowledge on data, to communicate to researchers, understand the
research agenda and being motivated to create highly relevant data
Ulf von Kalckreuth, Deutsche Bundesbank
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1) A Research Data and Service Centre (RCDS)
❙ Changing statistical processes takes time and consumes human resources.
Data recording and formats may have to be adapted. Legal constraints have
to be overcome
❙ A first (limited) stage leaves statistical processes as they are
❙ Start providing data where there is experience with scientific usage
❙ Would be constituted as scientific use files, periodically saved (data freeze),
archived and documented.
❙ User rights and limitations, setting up an application procedure
❙ Manual record linkage on the basis of available characteristics
❙ Progressively develop new data collections
❙ Long time lags and limited linkage – in terms of flexibility, timeliness and
simultaneous analysis, this is still very much the old world
Ulf von Kalckreuth, Deutsche Bundesbank
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Process data
bases
Analytical
data bases
Record
linkages
1) A Research Data and Service Centre (RCDS)
Sub-Unit 1: Experts for the relevant data sets, with the task of setting up and
developing the research data collections, the documentation and the interaction
with users in matters of data content. They would also do evaluations on demand
and a certain amount of own research
Sub Unit 2: Staff for the technical side of the dissemination, process, supporting
❙ Evaluation from a distance
❙ Safe computers „on site“
❙ Provision of de facto or fully anonymised scientific use files
❙ Possibly exchange with other research centers in „safe rooms“
Ulf von Kalckreuth, Deutsche Bundesbank
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1) A Research Data and Service Centre (RCDS)
Sub Unit 3: Record linkage and validation, including the enhancement by
additional characteristics, such as sector information
Substantive areas eg:
❙ Company level information from balance sheets and BoP statistics
❙ Financial institutes
❙ Securities
❙ Survey data (household wealth survey, travel survey, payment survey)
Ulf von Kalckreuth, Deutsche Bundesbank
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1) A Research Data and Service Centre (RCDS)
❙ The RCDS on its own will address some of the urgent needs, while leaving
other problems on the wayside
❙ Will put a new focus on the use and the information content of granular
information
❙ Manual record linking is a crutch – slow and limited
❙ Legal problems for matching data on companies (no access to NSI‘s
company register) and banks (dual purpose of bank data – supervision and
statistics).
Ulf von Kalckreuth, Deutsche Bundesbank
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2) Integrated micro data management
❙ In the longer run, statistical processes can be adapted to make possible an
integrated processing of micro data.
❙ The information availably on any observational unit can be addressed
simultaneously and without delay
❙ Data repositories could be centralised or kept decentral
❙ The potential of an RDCD would increase exponentially and record linkage
does not create additional work, as far as internal informaton is concerned
❙ Evaluation and quality control – increasing informational content by crosschecking – reduction of inconsistencies
Ulf von Kalckreuth, Deutsche Bundesbank
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Important ideas from a visit to the Banco de Portugal
❙ Common reference data bases
❙ Introducing a distinct exploration level into the various stat. processes
❙ read-only
❙ Validated
❙ Subset relevant for analysis
❙ Intermediate step may be to make available common identifyers: record
linkage could then be done in a satellite environment (data repositories
within the RCDS)
Ulf von Kalckreuth, Deutsche Bundesbank
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Four level concept within one business area
File reception
Processing
Generic business unit
New: Analysis
Example
bank
balance
sheets
Micro data from
reporting
BMI
reports
Data to be validated
and recombined,
visible only for the
business unit
BASWeb
operative system
Finalisised data
used for cross
chacking in Stat
Dept and as data
warehouse for
external analysis
„House of micro
data “
Publication
Dissemination
ZIS
time series
Ulf von Kalckreuth, Deutsche Bundesbank
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Four level concept between various business areas
Ulf von Kalckreuth, Deutsche Bundesbank
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Key features of integrated micro data management
❙ Shared reference information
❙ Eg by using an SDMX framework
❙ Overarching four level framework
❙ Common model instead of a common platform
❙ Implemented by each business unit locally, respecting specific restrictions
Success factors as seen from the experience in Portugal
❙ „Step By Step“ instead of „Big Bang“
❙ Unit by unit, beginning with the most important and the easiest cases
❙ Sequential implementation -- on the basis of existing infrastructure
❙ Integrating only where there is value added
❙ Cost benefit analysis
❙ New areas need to follow a common blueprint
❙ Overall, a disciplining effect
Ulf von Kalckreuth, Deutsche Bundesbank
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Summary
A vision for the House of Microdata:
1. The RDCS, a separate business unit, specialised on the interchange with
external analytics
2. Integrated microdata management as a joint feature of all business
units
❙ Common reference data
❙ Harmonised level for data analysis in all business units for information crossing
Many thanks for listening and for discussing!
Ulf von Kalckreuth, Deutsche Bundesbank
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