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Quality indicators for statistics based on multiple sources

Quality indicators for statistics based on multiple sources. Mihaela Agafiţei , Fabrice Gras, Wim Kloek , Sorina Vâju Eurostat, European Commission. Content. Introduction Quality of statistics – general discussion Output quality assessment – input and process

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Quality indicators for statistics based on multiple sources

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  1. Quality indicators for statistics based on multiple sources Mihaela Agafiţei, Fabrice Gras, WimKloek, Sorina Vâju Eurostat, European Commission

  2. Content Introduction Quality of statistics – general discussion Output quality assessment – input and process Direct output quality assessment Conclusions Quality indicators for statistics based on multiple sources Mihaela Agafiţei, Fabrice Gras, WimKloek, Sorina Vâju (Eurostat, European Commission) Q2014 – Vienna – 5th of June, 2014 Session No 32 - Statistics beyond survey and administrative data 2/11

  3. 1. Introduction Quality indicators for statistics based on multiple sources Mihaela Agafiţei, Fabrice Gras, WimKloek, Sorina Vâju (Eurostat, European Commission) Q2014 – Vienna – 5th of June, 2014 Session No 32 - Statistics beyond survey and administrative data 3/11

  4. 2. Quality of statistics – general discussion Quality indicators for statistics based on multiple sources Mihaela Agafiţei, Fabrice Gras, WimKloek, Sorina Vâju (Eurostat, European Commission) Q2014 – Vienna – 5th of June, 2014 Session No 32 - Statistics beyond survey and administrative data 4/11

  5. 2. Quality of statistics – general discussion Quality indicators for statistics based on multiple sources Mihaela Agafiţei, Fabrice Gras, WimKloek, Sorina Vâju (Eurostat, European Commission) Q2014 – Vienna – 5th of June, 2014 Session No 32 - Statistics beyond survey and administrative data 5/11

  6. 3. Output quality assessment: input and process • Not feasible: • multiple sources • multiple uses • large and complex processes • certainly at the European level Quality indicators for statistics based on multiple sources Mihaela Agafiţei, Fabrice Gras, WimKloek, Sorina Vâju (Eurostat, European Commission) Q2014 – Vienna – 5th of June, 2014 Session No 32 - Statistics beyond survey and administrative data 6/11

  7. 3. Output quality assessment: input and process Quality indicators for statistics based on multiple sources Mihaela Agafiţei, Fabrice Gras, WimKloek, Sorina Vâju (Eurostat, European Commission) Q2014 – Vienna – 5th of June, 2014 Session No 32 - Statistics beyond survey and administrative data 7/11

  8. 4. Direct output quality assessment • Direct assessment of output quality from the output itself • Assessment of output quality with a common reference data source • Bootstrapping • Not replacing the input + process approach Quality indicators for statistics based on multiple sources Mihaela Agafiţei, Fabrice Gras, WimKloek, Sorina Vâju (Eurostat, European Commission) Q2014 – Vienna – 5th of June, 2014 Session No 32 - Statistics beyond survey and administrative data 8/11

  9. 4. Direct output quality assessment • Direct assessment of output quality from the output itself • time series or cross-sectional data • breaks in series are a direct indication of bias • revisions • outliers • Assessment of output quality with a common reference data source • quality survey • additional statistics or administrative sources with considerable conceptual harmonisation Quality indicators for statistics based on multiple sources Mihaela Agafiţei, Fabrice Gras, WimKloek, Sorina Vâju (Eurostat, European Commission) Q2014 – Vienna – 5th of June, 2014 Session No 32 - Statistics beyond survey and administrative data 9/11

  10. 4. Direct output quality assessment Methods derived from bootstrapping Quality indicators for statistics based on multiple sources Mihaela Agafiţei, Fabrice Gras, WimKloek, Sorina Vâju (Eurostat, European Commission) Q2014 – Vienna – 5th of June, 2014 Session No 32 - Statistics beyond survey and administrative data 10/11

  11. 5. Conclusions • Output quality assessment through input and process quality gets too complex in processes combining several sources, especially at the European level • Alternative solutions should be found: • direct output assessment • a common reference source • bootstrapping • Output quality assessment: • internal use: to monitor and improve statistical production process • external use: a coherent summary of information on quality output • Assessing quality is not for free Quality indicators for statistics based on multiple sources Mihaela Agafiţei, Fabrice Gras, WimKloek, Sorina Vâju (Eurostat, European Commission) Q2014 – Vienna – 5th of June, 2014 Session No 32 - Statistics beyond survey and administrative data 11/11

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