andreas berg federal statistical office of germany c 1 - mathematical-statistical methods
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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 - PowerPoint PPT PresentationTRANSCRIPT
© FSO, Unit C 1, Division Mathematical Statistical Methods, Research Data Center
Federal Statistical Office of Germany
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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 in
North Rhine-Westphalia
Andreas BergFederal Statistical Office of GermanyC 1 - Mathematical-statistical [email protected]
1st of September 2013Bangkok
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Federal Statistical Office of Germany
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NRW
Germany
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Federal Statistical Office of Germany
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Outline:I. Problem descriptionII. The Data
Microcensus data Data from the German Federal Employment
AgencyIII. Matching processIV. ModelV. ResultsVI. Outlook
Problem specific In General
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Federal Statistical Office of Germany
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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
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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
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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)
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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
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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
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Data from Microcensus and German Federal Employment Agency differ markedly even on high-aggregated levels, but they are highly correlated
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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
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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
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Model:
MSE estimation according to Ghosh and Rao
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Software:
Tools developed for the ESSNET Project on SAE 2010-2012.
Public deliverables available on CROS webportal at EU
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Results:
Estimation carried out in SAS
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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
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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
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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
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Microcensus Labour force survey European Union statistics on
Income and Living Conditions Information and communication
technology surveys
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I would like to thank the Statistical office of the Land of North Rhine Westphalia (“Information und Technik Nordrhein-Westfalen”) for their cooperation
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Reference: Körner, T. and Puch,K: “Coherence of German Labour Market Statistics”, in Statistics and Science, Vol. 19.
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Federal Statistical Office of Germany
Thank You for your Great Deal of Attention
Khorb khun khrab
Andreas Berg, Unit C 1Federal Statistical Office of Germany,WiesbadenPhone: +49 (0)611 / 75-4362Mail: [email protected]