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Integrated Data Sources and methodological Issues. A Case Study from the German AFiD Project Hans - Peter Hafner NTTS 2009, Brussels February 20, 2009.

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Presentation on theme: "Integrated Data Sources and methodological Issues. A Case Study from the German AFiD Project Hans - Peter Hafner NTTS 2009, Brussels February 20, 2009."— Presentation transcript:

1 Integrated Data Sources and methodological Issues. A Case Study from the German AFiD Project Hans - Peter Hafner NTTS 2009, Brussels February 20, 2009

2 © Statistische Ämter der Länder, ForschungsdatenzentrumFolie 2 Overview The AFiD Project Data Products Methodological Issues Case Study: Longitudinal Weighting Factors for the AFiD – Panel Services

3 © Statistische Ämter der Länder, ForschungsdatenzentrumFolie 3 AFiD AFiD = Amtliche Firmendaten für Deutschland (Official Business Data for Germany) Project of the Research Data Centre of the statistical offices of the Länder of Germany (since 2007) Goal: Generation of integrated data sources Method: Matching of business and environmental surveys Legal basis: §13a BStatG (German Federal Statistics Law)  Added in 2005

4 © Statistische Ämter der Länder, ForschungsdatenzentrumFolie 4 AFiD Data access for universities and similar scientific institutions  Safe scientific work stations in the statistical offices   Controlled Remote Data

5 © Statistische Ämter der Länder, ForschungsdatenzentrumFolie 5 AFiD – Products AFiD - Panel Industrial Plants All essential information about local units with focus of economic activity in the manufacturing sector  sector of economic activity, number of employees, turnover, investment, working hours and earnings. Combination of full surveys with a cut-off of 20 employees. Additional until 2002: Small Firm Survey with data on local units having less than 20 employees. From 1995 to Actual data will be added.

6 © Statistische Ämter der Länder, ForschungsdatenzentrumFolie 6 AFiD – Products AFiD - Panel Industrial Enterprises Information about enterprises with focus of economic activity in the manufacturing sector  sector of economic activity, number of employees, turnover, investment, working hours and earnings, cost structure. Combination of full surveys with a cut-off of 20 employees and a sample survey (cost structure survey, contains around 45% of the enterprises). Complements the Plants panel. All fields of activity of the enterprise are included, not only those in the manufacturing sector. No back- calculation of values for the local units possible.

7 © Statistische Ämter der Länder, ForschungsdatenzentrumFolie 7 AFiD – Products AFiD - Panel Agriculture Farm level data of the agricultural census 1999 and the agricultural structure services 2003 and 2007  Agricultural production, land use and livestock, legal form, property and tenure situation and manpower Germany 1999: About half a million farms cultivate 17,1 millions hectares of cropland with 1,4 million full- or part-time farmers 2007: Number of farms had reduced to about Scientific interest: Analyzing the determinants of this development Political interest due to high subsidy payments

8 © Statistische Ämter der Länder, ForschungsdatenzentrumFolie 8 AFiD – Products AFiD - Panel Services Recently many enterprise foundations in the services sector  Sector become more and more important for the national economics Panel consists of the structure survey for the services sector for 2003 to 2005 (sample of around 15% of the enterprises) Information about the number of employees, the earnings, the turnover, the taxes, the subsidies of the enterprise Longitudinal dataset permits for example the analysis of growth processes

9 © Statistische Ämter der Länder, ForschungsdatenzentrumFolie 9 AFiD – Products AFiD – Module Earnings Structure of Earnings Survey (SES) for the years 2001 and 2006 SES is a linked employer employee dataset Employees: Socio-demographic attributes (sex, year of birth), working hours and earnings, specification which collective or enterprise agreement is applied Local unit or enterprise to which it belongs: information about the economic sector, the influence of the public sector, number of employees Analysis of gender-specific earnings differences and differences between local units tied to labor contracts and units that remunerate by individual agreement Can be merged with the AFiD - Panel Industrial Plants

10 © Statistische Ämter der Länder, ForschungsdatenzentrumFolie 10 AFiD – Products AFiD – Module Environment Module combines surveys about water supply and waste water disposal, investment for environment protection and good for environment protection Can be merged with the AFiD - Panel Industrial Plants  simultaneous analysis of economic and environmental relevant factors

11 © Statistische Ämter der Länder, ForschungsdatenzentrumFolie 11 Methodological Issues Inconsistencies concerning the Identifiers Identifiers: Numbers of the plant respective the enterprise (business register) Problems:  Merger of enterprises: New enterprise receives one of the numbers of the old companies.  Splitting up of an enterprise: One part retains the old number.  Change of form of organization or headquarter moves to another federal state: Enterprise gets new number.  No or no proper matching possible

12 © Statistische Ämter der Länder, ForschungsdatenzentrumFolie 12 Methodological Issues Implausibilities when matching Data from different Surveys Several attributes are contained in different surveys, for example number of employees and turnover, but the definitions or the date of report can differ  Check of definitions and reporting dates may help to clear implausibilities

13 © Statistische Ämter der Länder, ForschungsdatenzentrumFolie 13 Methodological Issues Diverse Sampling Frames and Sampling Units AFiD combines complete surveys with a cut-off and sample surveys Compare results of analyses including all units with results obtained by using the units of the sample (check whether there is a selectivity problem)

14 © Statistische Ämter der Länder, ForschungsdatenzentrumFolie 14 Methodological Issues Missing Values Unit does not answer a question: Rare in official statistics since for the most surveys there is an obligation to give information Unit does not participate in the survey: Values can be imputed. Until now no imputations are planned by the research data centre.

15 © Statistische Ämter der Länder, ForschungsdatenzentrumFolie 15 Methodological Issues Panel Attrition and longitudinal Weighting Factors See the following detailed example.

16 © Statistische Ämter der Länder, ForschungsdatenzentrumFolie 16 Case Study: Construction of longitudinal Weighting Factors for the AFiD – Panel Services Motivation Surveys that are conducted in regular intervals allow for analyses of every cross – section and – as far as some units participate in more than one wave – the longitudinal section. Units for which we have valid data for a wave and which belong to the population of interest at the reference date of the wave, represent the population and they build the basis for the cross – sectional weighting. In the case of longitudinal sections it is not always clear, what the population is. This depends on the specific scientific question.

17 © Statistische Ämter der Länder, ForschungsdatenzentrumFolie 17 Case Study: Construction of longitudinal Weighting Factors for the AFiD – Panel Services Kinds of Attrition False attrition: The unit exists no longer or it belongs no longer to the population of the survey, for example because of a change of the focus of the economic activity. True attrition: The unit does not answer (refusal or moved to a new address which is unknown). The true attriters have to be compensated by increasing the weighting factors of the units with valid data.  Additional factor ni / (ni - ai,e) ni number of sample units in strata i ai,e number of true attriters in strata i

18 © Statistische Ämter der Länder, ForschungsdatenzentrumFolie 18 Case Study: Construction of longitudinal Weighting Factors for the AFiD – Panel Services Methodology of the Structure Survey for the Services Sector Twofold stratified sample survey: 68 strata of economic activity and 12 strata of turnover classes. Sample unchanging for some years, at most 15% of all enterprises. To compensate for attrition: Additional new entrant sample every year (layered by 22 groups of economic activity and 8 classes of turnover).

19 © Statistische Ämter der Länder, ForschungsdatenzentrumFolie 19 Case Study: Construction of longitudinal Weighting Factors for the AFiD – Panel Services Panel attrition from 2003 to

20 © Statistische Ämter der Länder, ForschungsdatenzentrumFolie 20 Case Study: Construction of longitudinal Weighting Factors for the AFiD – Panel Services Problems:  Number of stratum not included in original dataset (additional reference file had to be ordered by all statistical offices of the federal states -> delay of the project)  Strata of the original sample and the new entrant sample had to be harmonized

21 © Statistische Ämter der Länder, ForschungsdatenzentrumFolie 21 Case Study: Construction of longitudinal Weighting Factors for the AFiD – Panel Services Plan for the construction of the weighting factors : Basis weight:  Number N of all enterprises that have existed in at least one of the years 2003 to 2005 for every stratum  Basis weight = N divided by the number of enterprises of the stratum contained in the sample for at least one year Additional factor:  Calculate separate factors for 2003 to 2005 to compensate the true attriters  Compute the average of the factors

22 © Statistische Ämter der Länder, ForschungsdatenzentrumFolie 22 Case Study: Construction of longitudinal Weighting Factors for the AFiD – Panel Services Outlook Test and modification of the concept Enhancement of the panel for the year 2006

23 © Statistische Ämter der Länder, ForschungsdatenzentrumFolie 23 Contact Statistical Offices of the Länder Research Data Centre Wiesbaden Hans-Peter Hafner Phone Thank you for your attention!


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