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A Distance Metric for Modeling the Quality of Administrative Records for Use in the 2020 U.S. Census

Author

Listed:
  • Keller Andrew
  • Mule Vincent T.
  • Morris Darcy Steeg
  • Konicki Scott

    (U.S. Census Bureau, Washington, DC20233, U.S.A.)

Abstract

The U.S. Census Bureau is conducting research on using administrative records to reduce the cost while maintaining the quality of the 2020 Census Nonresponse Followup (NRFU). Previous census tests have implemented approaches that use predictive models and optimization procedures to identify vacant and occupied housing units using administrative records. This article details a modification to previous approaches, introducing a simple distance metric to define a quality ranking of housing units to enumerate using administrative records. The distance approach is illustrated, assessed, and compared to a previous approach via a retrospective study of the 2010 U.S. Census.

Suggested Citation

  • Keller Andrew & Mule Vincent T. & Morris Darcy Steeg & Konicki Scott, 2018. "A Distance Metric for Modeling the Quality of Administrative Records for Use in the 2020 U.S. Census," Journal of Official Statistics, Sciendo, vol. 34(3), pages 599-624, September.
    • Handle: RePEc:vrs:offsta:v:34:y:2018:i:3:p:599-624:n:2
    DOI: 10.2478/jos-2018-0029
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    References listed on IDEAS

    as
    1. Mary Layne & Deborah Wagner & Cynthia Rothhaas, 2014. "Estimating Record Linkage False Match Rate for the Person Identification Validation System," CARRA Working Papers 2014-02, Center for Economic Studies, U.S. Census Bureau.
    2. Melissa C. Chow & Hubert P. Janicki & Mark J. Kutzbach & Lawrence F. Warren & Moises Yi, 2017. "A Comparison of Training Modules for Administrative Records Use in Nonresponse Followup Operations: The 2010 Census and the American Community Survey," Working Papers 17-47, Center for Economic Studies, U.S. Census Bureau.
    3. Task Force Members Include: Lilli Japec & Frauke Kreuter & Marcus Berg & Paul Biemer & Paul Decker & Cliff Lampe & Julia Lane & Cathy O'Neil & Abe Usher, "undated". "AAPOR Report on Big Data," Mathematica Policy Research Reports 4eb9b798fd5b42a8b53a9249c, Mathematica Policy Research.
    4. Sharon R. Ennis & Sonya R. Porter & James M. Noon & Ellen Zapata, 2015. "When Race and Hispanic Origin Reporting are Discrepant Across Administrative Records and Third Party Sources: Exploring Methods to Assign Responses," CARRA Working Papers 2015-08, Center for Economic Studies, U.S. Census Bureau.
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