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

Keller Andrew (), Mule Vincent T. (), Morris Darcy Steeg () and Konicki Scott ()
Additional contact information
Keller Andrew: U.S. Census Bureau, Washington, DC20233, U.S.A.
Mule Vincent T.: U.S. Census Bureau, Washington, DC20233, U.S.A.
Morris Darcy Steeg: U.S. Census Bureau, Washington, DC20233, U.S.A.
Konicki Scott: U.S. Census Bureau, Washington, DC20233, U.S.A.

Journal of Official Statistics, 2018, vol. 34, issue 3, 599-624

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.

Keywords: 2020 Census; administrative records; nonresponse followup (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://doi.org/10.2478/jos-2018-0029 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:vrs:offsta:v:34:y:2018:i:3:p:599-624:n:2

DOI: 10.2478/jos-2018-0029

Access Statistics for this article

Journal of Official Statistics is currently edited by Annica Isaksson and Ingegerd Jansson

More articles in Journal of Official Statistics from Sciendo
Bibliographic data for series maintained by Peter Golla ().