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Linking Household Survey and Administrative Record Data: What Should the Matching Variables Be?

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Author Info
Stephen P. Jenkins
Peter Lynn
Annette Jäckle
Emanuela Sala

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Abstract

Linkages of household survey responses with administrative data may be based on unique individual identifiers or on survey respondent characteristics. The benefits gained from using unique identifiers need to be assessed in the light of potential problems such as non-response and measurement error. We report on a study that linked survey responses to UK government agency records on benefits and tax credits in five different ways. One matched on a respondent-supplied National Insurance Number and the other four used different combinations of sex, name, address, and date of birth. As many linkages were made using matches on sex, date of birth, and post-code, or on sex, date of birth, first name and family name, as were made using matches on self-reported National Insurance Number, and the former were also relatively accurate when assessed in terms of false positive and false negative rates. The five independent matching exercises also shed light on the potential returns from hierarchical and pooled matching.

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File URL: http://www.diw.de/documents/publikationen/73/diw_01.c.43285.de/dp489.pdf
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Publisher Info
Paper provided by DIW Berlin, German Institute for Economic Research in its series Discussion Papers of DIW Berlin with number 489.

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Length: II, 22 p.
Date of creation: 2005
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Handle: RePEc:diw:diwwpp:dp489

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Related research
Keywords: Record linkage; Matching; National Insurance number; Measurement error;

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References listed on IDEAS
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.:
  1. Haider, S. & Solon, G., 2000. "Nonrandom Selection in the HRS Social Security Earnings Sample," Papers 00-01, RAND - Labor and Population Program.
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  2. Lorenzo Cappellari & Stephen P. Jenkins, 2003. "Multivariate probit regression using simulated maximum likelihood," United Kingdom Stata Users' Group Meetings 2003 10, Stata Users Group. [Downloadable!]
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  3. Simon Burgess & Deborah Wilson, 2004. "Ethnic Segretation in Englands Schools," CASE Papers 079, Centre for Analysis of Social Exclusion, LSE. [Downloadable!]
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Cited by:
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  1. Hartmann, Josef & Krug, Gerhard, 2007. "Verknüpfung von Befragungs- und Prozessdaten : Selektivität durch fehlende Zustimmung der Befragten?," IAB Discussion Paper 200713, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany]. [Downloadable!]
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