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Andreas Berg Federal Statistical Office of Germany C 1 - Mathematical-statistical methods

First steps of the Federal Statistical Office of Germany working with small area methods : An attempt to provide more reliable results for publishing data in smaller subgroups with application to labor force data in North Rhine-Westphalia. 1st of September 2013 Bangkok. Andreas Berg

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Andreas Berg Federal Statistical Office of Germany C 1 - Mathematical-statistical methods

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  1. First steps of the Federal Statistical Office of Germany working with small area methods:An attempt to provide more reliable results for publishing data in smaller subgroupswith application to labor force data inNorth Rhine-Westphalia 1st of September 2013 Bangkok Andreas Berg Federal Statistical Office of Germany C 1 - Mathematical-statisticalmethods andreas.berg@destatis.de

  2. Germany NRW

  3. Outline: • Problem description • The Data • Microcensus data • Data from the German Federal Employment Agency • Matching process • Model • Results • Outlook • Problem specific • In General

  4. Description of the problem: • Exemplary for the largest German Land with 18 Mio inhabitants we would like to analyze via small area methods NUTS3-level estimates for labor force data • Starting point is estimation of number of unemployed persons • Estimates for NUTS3-level based on classical methods exist but have not been published

  5. Description of the problem: • Due to restriction to the use of aggregated data only area level models can be analyzed • Comparison of the estimates will be done (and therefore the politically-induced decision of publishing) mainly on the base of a hopefully smaller MSE which should also not touch a certain barrier

  6. Microcensus: • Annual survey of 1% of the German private households • Sampling units are clusters of about 8 to 10 households • Includes the German Labour Force Survey • MSE of estimated results acceptable only for regions with at least inhabitants (here: only NUTS2-level Data will be published => Bezirke)

  7. Microcensus: • Here: data from 5 NUTS2-areas comprising 53 NUT3-areas (Kreise) available for 2009 • Variable of interest: number of unemployed persons according the ILO definition

  8. Data from the German Federal Employment Agency: • Number of people registered of being unemployed as auxiliary variable • Data from 395 labor office areas averaged over several time points during the year 2009 • Problem: this variable differs from the ILO definition, • Not all jobless persons are recorded by the German Federal Employment Agency, there are additional community based institutions recording jobless people

  9. Data from Microcensus and German Federal Employment Agency differ markedly even on high-aggregated levels, but they are highly correlated

  10. Matching process: Regional administrative structures are different between microcensus and labor office data collection First attempt: splitting overlapping labor office areas proportional to number of inhabitants involved Cooperation with microcensus and labour office experts highly recommended

  11. Model: • Area level model according to Fay/Herriot as a combination of a synthetic and a HT estimator • Covariates: • As unemployed registered persons according to Federal Employment Agency • NUTS2 data • NUTS1 data

  12. Model: MSE estimation according to Ghosh and Rao

  13. Software: Tools developed for the ESSNET Project on SAE 2010-2012. Public deliverables available on CROS webportal at EU

  14. Results: Estimation carried out in SAS

  15. Outlook 1: • Extend analyses to all Länder and additional variables of interest • Further refinements, for instance regarding sex/age groups • Cooperation matching • Different/Refined small area models especially with hindsight towards survey design • MSE of MSE: how to explain to users and deal with this “unknown” concept

  16. Outlook 1: • Balance between “easy” calculation and loss of accuracy • long way to go until production of results based on small area techniques can be established

  17. Outlook 2 – in general: Small area estimation is on the agenda at the federal Statistical office of Germany. At the methodological unit we are currently trying to anticipate future demands regarding the development of a new system of household statistics which might start off with issues in the field of

  18. Microcensus • Labour force survey • European Union statistics on Income and Living Conditions • Information and communication technology surveys

  19. I would like to thankthe Statistical office of the Land of North Rhine Westphalia (“Information und Technik Nordrhein-Westfalen”) for their cooperation

  20. Reference: Körner, T. and Puch,K: “Coherence of German Labour Market Statistics”, in Statistics and Science, Vol. 19.

  21. ThankYouforyour Great Deal of AttentionKhorbkhunkhrab Andreas Berg, Unit C 1 Federal Statistical Office of Germany, Wiesbaden Phone: +49 (0)611 / 75-4362 Mail: andreas.berg@destatis.de

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