Addressing the challenge of producing European comparable data using administrative data Mihaela AGAFIŢEI Sorina VÂJU UNECE Seminar on Statistical Data Collection Geneva, Switzerland, September 2013

Content Introduction Problem statement Possible Ways for Improvement Access to data & inter-institutional relations Statistical methods Quality Conclusions 25 September 2013UNECE Seminar on Statistical Data Collection (Geneva, Switzerland, September 2013) 2

Introduction ESS.VIP on Administrative Data sources Better aware about benefits Common approaches to tackle shortcomings 25 September 2013UNECE Seminar on Statistical Data Collection (Geneva, Switzerland, September 2013) 3 Multi sources Integration approach Statistical production process Statistical output

Problem statement International level Cope with large diversity Cope with different integration approaches National level Integration can leads to conflict Changes can leads to breaks in statistical series 25 September 2013UNECE Seminar on Statistical Data Collection (Geneva, Switzerland, September 2013) 4 Produce international comparable data by integrating data coming from different national administrative systems

Problem statement 25 September 2013UNECE Seminar on Statistical Data Collection (Geneva, Switzerland, September 2013) 5 Integrated system where statistics come from surveys and administrative sources Identify additional factors that affect comparability How and extent to which they affect comparability Way to improve comparability Coordinated efforts in the ESS

Access & inter-institutional relations Very diverse situation among EU Member States Stronger EU legal framework build/ modify / discontinue  right to be involved metadata – structure & content metadata – availability and clarity European Commission  coordination role of Eurostat 25 September 2013UNECE Seminar on Statistical Data Collection (Geneva, Switzerland, September 2013) 6

Statistical Methods 25 September 2013UNECE Seminar on Statistical Data Collection (Geneva, Switzerland, September 2013) 7 Make administrative data usable for statistical purposes improving input data quality directly at source in statistical system coping with their deficiencies as they are Integrate into statistical process Use for producing official statistics

Statistical Methods: ways to improve  Identify synergies among national administrative systems  Addressing common problems in the same manner  General decisional tree to convert administrative information into a coherent system of registers  Develop a methodology to assess quality of statistics based on a combination of sources (e.g. mixed sources) 25 September 2013UNECE Seminar on Statistical Data Collection (Geneva, Switzerland, September 2013) 8

Statistical Methods: ways to improve  Inventory of possible usages of administrative data + minimum quality requirements for input data  Identify common tools and a way to make them available for everybody  Terminology 25 September 2013UNECE Seminar on Statistical Data Collection (Geneva, Switzerland, September 2013) 9

Quality  How to measure the accuracy of statistics based on a combination of administrative data and survey?  Does the diversity of national integration approaches affect the quality of European statistics?  Which information do we need to assess quality of European statistics and the degree of comparability? 25 September 2013UNECE Seminar on Statistical Data Collection (Geneva, Switzerland, September 2013) 10

Quality: ways to improve 25 September 2013UNECE Seminar on Statistical Data Collection (Geneva, Switzerland, September 2013) 11  Input Group countries and propose tailored means to improve input data quality directly at source  Process Guidelines on quality assessment of statistical process where multiple sources are integrated  Output Quality indicators for statistical output and minimum quality standards

Conclusions 25 September 2013UNECE Seminar on Statistical Data Collection (Geneva, Switzerland, September 2013) 12 Preparatory Group Previous and on-going work Document and explain possible lack of comparability Agreeing on common standards & actions to: reconcile administrative and statistical purposes define and ensure a reasonable level of comparability over time and space