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Assessing Coverage and Quality of the 2007 Prototype Census Kidlink Database

Author

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  • Adela Luque
  • Deborah Wagner

Abstract

The Census Bureau is conducting research to expand the use of administrative records data in censuses and surveys to decrease respondent burden and reduce costs while improving data quality. Much of this research (e.g., Rastogi and O’™Hara (2012), Luque and Bhaskar (2014)) hinges on the ability to integrate multiple data sources by linking individuals across files. One of the Census Bureau’s record linkage methodologies for data integration is the Person Identification Validation System or PVS. PVS assigns anonymous and unique IDs (Protected Identification Keys or PIKs) that serve as linkage keys across files. Prior research showed that integrating “known associates” information into PVS’s reference files could potentially enhance PVS’s PIK assignment rates. The term “known associates” refers to people that are likely to be associated with each other because of a known common link (such as family relationships or people sharing a common address), and thus, to be observed together in different files. One of the results from this prior research was the creation of the 2007 Census Kidlink file, a child-level file linking a child’s Social Security Number (SSN) record to the SSN of those identified as the child’s parents. In this paper, we examine to what extent the 2007 Census Kidlink methodology was able to link parents SSNs to children SSN records, and also evaluate the quality of those links. We find that in approximately 80 percent of cases, at least one parent was linked to the child’s record. Younger children and noncitizens have a higher percentage of cases where neither parent could be linked to the child. Using 2007 tax data as a benchmark, our quality evaluation results indicate that in at least 90 percent of the cases, the parent-child link agreed with those found in the tax data. Based on our findings, we propose improvements to the 2007 Kidlink methodology to increase child-parent links, and discuss how the creation of the file could be operationalized moving forward.

Suggested Citation

  • Adela Luque & Deborah Wagner, 2015. "Assessing Coverage and Quality of the 2007 Prototype Census Kidlink Database," CARRA Working Papers 2015-07, Center for Economic Studies, U.S. Census Bureau.
  • Handle: RePEc:cen:cpaper:2015-07
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    File URL: https://www.census.gov/content/dam/Census/library/working-papers/2015/adrm/carra-wp-2015-07.pdf
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    References listed on IDEAS

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    1. James Farber & Charlene Leggieri, 2002. "Building and validating an administrative records database for the United States," New Zealand Economic Papers, Taylor & Francis Journals, vol. 36(1), pages 65-67.
    2. Raj Chetty & Nathaniel Hendren & Patrick Kline & Emmanuel Saez, 2014. "Where is the land of Opportunity? The Geography of Intergenerational Mobility in the United States," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 129(4), pages 1553-1623.
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    Cited by:

    1. Amy O’Hara & Rachel M. Shattuck & Robert M. Goerge, 2017. "Linking Federal Surveys with Administrative Data to Improve Research on Families," The ANNALS of the American Academy of Political and Social Science, , vol. 669(1), pages 63-74, January.
    2. Katie Genadek & Joshua Sanders & Amanda Stevenson, 2022. "Measuring US fertility using administrative data from the Census Bureau," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 47(2), pages 37-58.
    3. Cuccaro-Alamin, Stephanie & Eastman, Andrea Lane & Foust, Regan & McCroskey, Jacquelyn & Nghiem, Huy Tran & Putnam-Hornstein, Emily, 2021. "Strategies for constructing household and family units with linked administrative records," Children and Youth Services Review, Elsevier, vol. 120(C).
    4. Gloria G. Aldana, 2022. "Comparison of California Birth Records and Census Household Composition Key," CES Technical Notes Series 22-13, Center for Economic Studies, U.S. Census Bureau.

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    Keywords

    children; kidlink; parents; ssn;
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