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Statistics Netherlands

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II Dutch Taxonomy project (XBRL) Case I:The Social Statistical Database ... Backbone: Dutch population register ... Case II: The Dutch Taxonomy project ... – PowerPoint PPT presentation

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Title: Statistics Netherlands


1
Statistics Netherlands modernization programme
the use of administrative data, lessons learned
and the way ahead.
  • Geert Bruinooge
  • Assistant Director General
  • gbne_at_cbs.nl

2
Contents
  • Characteristics The Netherlands official
    statistics
  • Driving forces for change
  • The use of administrative data preconditions for
    efficient use.
  • Two cases
  • Lessons learned
  • The way ahead

3
Characteristics The Netherlands official
statistics
  • Highly centralised Statistics Netherlands
    produces 95 of official statistics
  • No regional offices
  • Professional independence guaranteed by law and
    highly respected
  • Strong tradition for statistical integration
    system of national accounts and modules

4
Driving forces for change
  • Ongoing budget cuts (- 30 since 1999)
  • Need for new statistical information
  • Programme renewal
  • Faster and more flexible outputs
  • Strong emphasis on European demands
  • Quality improvement
  • Cutting back the administrative burden
  • Increased availability of external
    administrations and registers
  • Competition from third parties (ICT developments,
    availability registerdata)

5
The use of administrative data
  • Preconditions for use
  • Legal obligation (2004) first external available
    data must be used, and surveys on second place.
  • Free access to administrations
  • Legal possibilities matching data files
  • Unique identification numbers both for businesses
    and persons

6
The use of administrative data (2)
  • External political support
  • Imposed reduction of response burden by 25 for
    businesses
  • At National and EU level
  • Wider existance of administrations and
    registrations in the country
  • Enabling provisions in national legislation

7
Examples of administrative data sources
  • Some examples
  • The Dutch population register
  • The social security administration
  • Corporate tax administation
  • Land ownership registration
  • Comprehensive business register

8
Two show cases
  • I Social Statistical Data base
  • II Dutch Taxonomy project (XBRL)

9
Case IThe Social Statistical Database
  • The SSD all relevant information on persons,
    families, households, jobs, benefits and living
    quarters
  • Product consistent statistical output
  • Advantages regional detail, more information on
    smaller groups, on demand outputs.

10
Case I The Social Statistical Database
  • Primary base register information
  • Additionally survey data from business and
    households
  • Backbone Dutch population register
  • All other files linked demographic data, income
    tax, labour market participation, social security
    benefits, educational attainment, housing.

11
Case I Social Statistical Database
  • Methodology
  • Micro-integration linking records from different
    sources (link identification number)
  • Check for consistency and corrected
  • Consistent and repeated weighting
  • Started in 1997
  • Sampling frame for special social surveys
  • Basis for output in social area and input for
    Statline database
  • Virtual census in 2001, to be repeated in 2011.

12
Case II The Dutch Taxonomy project
  • Objective standardisation of the reporting
    requirements for business to different parts of
    government (tax, annual reporting, statistics)
  • How using single technical standard (XBRL) and
    common vocabulary of government administrations.
  • Build in functionality in software programmes

13
Case II the Dutch Taxonomy project
  • So far no single report for business to all
    administrations, but a modular more tailor made
    report.
  • For SN from 189 to 6 reports
  • Still limited success in so far (contrary to
    Portugal)
  • Reasons not build in business software
  • Voluntary
  • Lack of political support
  • But a clear way forward in future.

14
Lessons learned
  • Legal basis is precondition (but not enough)
  • Strong political support indispensable
  • Innovation from the own organisation is
    prerequisite
  • Contacts at all levels NSI administrations
  • NSI involvement in setting up and changing
    administrations standards/concepts
  • Variations in quality of administrative data
  • NSIs not in control
  • Risk of abolishment of basic administrations

15
Our future environment
  • Our environment the coming years
  • Integrated Architecture Framework to be
    implemented in 2011
  • Future budget reductions?
  • Further reduction administrative burden high
    political issue
  • Enrichment of outputs by more and higher quality

16
The way ahead
  • Future directions
  • Stronger co-operation statistics/administrations
    (one counter)
  • Joint research and programmes
  • Stronger profile for NSI as bureau of standard
  • Create value added for statistics
  • More service oriented attitude NSIs
  • Political support

17
Thank you for your attention
  • www.cbs.nl
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