Linking Household Survey and Administrative Record Data: What Should the Matching Variables Be?
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.
|Length:||II, 22 p.|
|Date of creation:||2005|
|Date of revision:|
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- Steven Haider & Gary Solon, 2000.
"Non Random Selection in the HRS Social Security Earnings Sample,"
00-01, RAND Corporation.
- Haider, S. & Solon, G., 2000. "Nonrandom Selection in the HRS Social Security Earnings Sample," Papers 00-01, RAND - Labor and Population Program.
- JÃ¤ckle, Annette & Sala, Emanuela & Jenkins, Stephen P. & Lynn, Peter, 2004.
"Validation of survey data on income and employment: the ISMIE experience,"
ISER Working Paper Series
2004-14, Institute for Social and Economic Research.
- Annette Jäckle & Emanuela Sala & Stephen P. Jenkins & Peter Lynn, 2005. "Validation of Survey Data on Income and Employment: The ISMIE Experience," Discussion Papers of DIW Berlin 488, DIW Berlin, German Institute for Economic Research.
- Simon Burgess & Deborah Wilson, 2004.
"Ethnic Segretation in England's Schools,"
079, Centre for Analysis of Social Exclusion, LSE.
- BÃ¶heim, RenÃ© & Taylor, Mark P., 2000. "From the dark end of the street to the bright side of the road? investigating the returns to residential mobility in Britain," ISER Working Paper Series 2000-38, Institute for Social and Economic Research.
- Lorenzo Cappellari & Stephen P. Jenkins, 2003.
"Multivariate probit regression using simulated maximum likelihood,"
StataCorp LP, vol. 3(3), pages 278-294, September.
- Lorenzo Cappellari & Stephen P. Jenkins, 2003. "Multivariate probit regression using simulated maximum likelihood," United Kingdom Stata Users' Group Meetings 2003 10, Stata Users Group.
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