Verknüpfung von Befragungs- und Prozessdaten : Selektivität durch fehlende Zustimmung der Befragten?
Abstract"Linking data from different sources can be used to compensate for the weaknesses characteristic for the single sources and therefore significantly increase the potential for analyses. This requires that linking data implies no consequences that cancel out the advantages. Considering this background the contribution analyses to which extent we face such consequences when linking administrative data of the 'Bundesagentur für Arbeit' (BA) to survey data on the level of individuals. Due to reasons of data protection the respondents have to be asked to allow linking their survey data to their administrative data. This necessity may result in a kind of 'linkage bias', as it may be, that their willingness to admit correlates with other characteristics relevant for the research question. This may bias results. Using data of a study, in which persons were asked, whether they allow linking the survey data to administrative data, we analyse whether there is selectivity in admission regarding a number of characteristics that are known to influence respondent behaviour. Using multilevel analysis we show that only some characteristics are correlated with allowing data linking: Women, foreign persons, persons with low income and persons interested in protecting private information as for example on income or social benefits tend to be underrepresented in the restricted sample using the linked data set. In order to investigate the consequences of this selection for specific research questions we propose a simple test based on a 'seemingly unrelated estimation' and present two examples." (Author's abstract, IAB-Doku) ((en))
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany] in its series IAB Discussion Paper with number 200713.
Length: 43 pages
Date of creation: 23 Mar 2007
Date of revision:
Publication status: published as: Zeitschrift für ArbeitsmarktForschung, Jg. 42, H. 2 (2009), p. 121-139
prozessproduzierte Daten; Befragung; Datenanalyse; Datenqualität; Stichprobenfehler;
Find related papers by JEL classification:
- C - Mathematical and Quantitative Methods
- J - Labor and Demographic Economics
- Z - Other Special Topics
This paper has been announced in the following NEP Reports:
- NEP-ALL-2007-03-31 (All new papers)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Heckman, James J, 1979.
"Sample Selection Bias as a Specification Error,"
Econometric Society, vol. 47(1), pages 153-61, January.
- Stephen P. Jenkins & Peter Lynn & Annette Jäckle & Emanuela Sala, 2005.
"Linking Household Survey and Administrative Record Data: What Should the Matching Variables Be?,"
Discussion Papers of DIW Berlin
489, DIW Berlin, German Institute for Economic Research.
- Achatz, Juliane & Gartner, Hermann & Glück, Timea, 2004. "Bonus oder Bias? Mechanismen geschlechtsspezifischer Entlohnung," IAB Discussion Paper 200402, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (IAB, Geschäftsbereich Dokumentation und Bibliothek).
If references are entirely missing, you can add them using this form.