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Item III.2 Frame population EGR frame methodology Barry Coenen, Statistics Netherlands

MEETS Conference 25-26 June 2014. Item III.2 Frame population EGR frame methodology Barry Coenen, Statistics Netherlands. EGR 2.0. Towards an user oriented approach: providing frame populations when needed Introduction EGR Introduction of frame population methodology

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Item III.2 Frame population EGR frame methodology Barry Coenen, Statistics Netherlands

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  1. MEETS Conference 25-26 June 2014 Item III.2 Frame populationEGR frame methodologyBarry Coenen, Statistics Netherlands

  2. EGR 2.0 Towards an user oriented approach: providing frame populations when needed • Introduction EGR • Introduction of frame population methodology • EGR design: a network of statistical business registers • National SBR: authentic store for national entities (enterprises, legal units, relationships) • EGR: authentic store for supra national entities (global enterprise group, UCI, relationships)

  3. EGR The EGR is foreseen to become the platform that supports the production of micro based statistics on globalisation in Europe, both on country and European level by offering compilers access to integrated and up-to-date register data on those enterprise groups which have statistically relevant transnational operations (financial and non-financial) in at least 1 of the European countries. The EGR is foreseen to become the platform that supports the production of micro based statistics on globalisation in Europe, both on country and European level by offering compilers access to integrated and up-to-date register data on those enterprise groups which have statistically relevant transnational operations (financial and non-financial) in at least 1 of the European countries.

  4. EGR (2) The EGR willbe a central business register kept at Eurostat where • Data from different sources canbeprocessed • Users will have access to the data andwillbeabletoassessand update the data • Users canassesswhatoccuredtotheir population • Users canretrieve the data neededfortheirnationalprocess

  5. EGR (3) Provide data Commercial Data Provider Process data andcreateprelimenary population Create frame population EGR NSI Provide data Statistical Activity Data Quality Management

  6. Frame population methodology • set of rules and procedures • for maintenance and common use of populations of statistical units by statistical activities • Rules and procedures apply for NSI, NSA and Eurostat • Maintenance is aimed at achieving a good quality of the frame population • Common use is aimed at using one population frame for all national statistics on globalization in all 31 member states

  7. Some main concepts • Master frame population reference period T = data set on population referring to period T to be used by statistical activities • Initial and intermediate frame population reference period T = data set on population referring to period T to be used for data quality management and data validation • Frame population error procedure = rules and procedures dealing with mistakes in the master frame population

  8. Objectives for coming years • Master Outward FATS frame population of reporting units (UCI’s) referring to year T produced and disseminated in April T+1 (or T+4 months) • Master FATS frame population of enterprises referring to year T produced and disseminated in March T+2 (or T+14 months)

  9. Outward FATS population of reporting units Initial frame population Intermediate frame population Master frame population Validation Frame error correction procedure Data quality management Sept year T Feb year T+1 Apr year T+1 Reference year T Reference year T+1 Reference year T+2 Data quality management Validation Frame error correction procedure March year T+2 Apr year T Nov year T+1 Master frame population Initial frame population Intermediate frame population FATS population of enterprises

  10. EGR 2.0 process reference Year T (1) September year T – Februaryyear T+1 • EGR defines a starting list of UCI’s • NSA’svalidate list of resident UCI’s(cooperation BR and OFATS) • NSI’s select on basis of this list • nationalenterprisegroupswhich are in the OFATS population • nationalenterprisegroupswhich are foreignowned • Legal units andrelationships • Enterprises (SBS) • EGR processes data sets • NSA’sresolves issues on UCI’s in EGR

  11. EGR 2.0 process reference Year T (2) Februaryyear T+1 – April yearT+1 • ESTAT andNSI’svalidateUCI’s in EGR • ESTAT createsfinal population frame OFATS andintitial frame IFATS • NSI’sdefine the national survey populationsfor OFATS April year T+1 – Marchyear T+2 NSA’scanuse ‘frame error correction procedure’ forcorrectingreporting units (UCI’s) referring to year T

  12. EGR 2.0 process reference Year T (3) April year T – November year T+1 • EGR data quality management on legal unit structure • NSI’sprovide update of population of intra EU enterprises (SBS) • NSA’suse ‘frame error procedure’ correcting UCI mistakes November year T+1 – Marchyear T+2 • ESTAT andNSI’svalidatestructure of globalenterprisegroups • ESTAT createsfinal population frame IFATS • NSA’sadd the ‘country of UCI’ to the SBS frame population year T November year T+1 – Marchyear T+2 November NSA’suse ‘frame error correction procedure’ forcorrecting country of UCI mistakes IFATS

  13. EGR 2.0 process reference Year T (4) General • NSA’scanprovide ‘live’ updates (EGR offers features tomaintain 2 legal unit structures: topicalandpreviousreferenceyear) • EGR DQM of NSI’sfocuses on: direct cross-border relationshipsandrelationshipswith UCI • Intermediate releases possible but shouldbelimitedduetovalidation procedures needed • Maintenance of intra EU enterprises serving intra EU OFATS

  14. ESTAT and NSA challenges • ESTAT: getting commitment of NSA’s on the frame population methodology (ESS and ESSnet on Consistency) • NSA’s: organising the synchronisation of the different nationalstatisticalactivitiescollectingandproducing data on globalisation • NSA’s: organising the maintenance of the datastores of the nationalstatisticalactivitieswith the values of the ‘coordinatedcharacteristics’ • NSI’s: DQM on direct cross-border relationshipsandrelationshipswith UCI • EGR: Realisation of a by FATS accepted quality

  15. EGR designa network of statistical business registers • Resident legal unit • Resident relationships • Enterprises CDP NBR EGR Authentic data NBR Non authentic data NBR • Ent. GroupCountry of UCI • Link Enterprise to country of UCI National statisticalprocesses National statisticalprocesses National statisticalprocesses

  16. Thank you • Additional information: • Harrie van der Ven, HVEN@CBS.NL • Barry Coenen, BCNN@CBS.NL

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