Comparison of 2010 Census Nonresponse Follow-Up Proxy Responses with Administrative Records Using Census Coverage Measurement Results

Open access

Abstract

The U.S. Census Bureau is currently conducting research on ways to use administrative records to reduce the cost and improve the quality of the 2020 Census Nonresponse Followup (NRFU) at addresses that do not self-respond electronically or by mail. Previously, when a NRFU enumerator was unable to contact residents at an address, he/she found a knowledgeable person, such as a neighbor or apartment manager, who could provide the census information for the residents. This was called a proxy response. The Census Bureau’s recent advances in merging federal and third-party databases raise the question: Are proxy responses for NRFU addresses more accurate than the administrative records available for the housing unit? Our study attempts to answer this question by comparing the quality of proxy responses and the administrative records for those housing units in the same timeframe using the results of 2010 Census Coverage Measurement (CCM) Program. The assessment of the quality of the proxy responses and the administrative records in the CCM sample of block clusters takes advantage of the extensive fieldwork, processing, and clerical matching conducted for the CCM.

If the inline PDF is not rendering correctly, you can download the PDF file here.

  • Cantwell P.J. M. Ramos and D. Kostanich. 2009. “Measuring Coverage in the 2010 U.S. Census.” In JSM Proceedings Social Statistics Section American Statistical Association Washington DC August 1–6 2009. Alexandria VA: American Statistical Association. 43–54. Available at: https://ww2.amstat.org/sections/srms/proceedings/y2009/Files/302739.pdf (accessed January 2017).

  • Chesnut J. 2005. “Item Nonresponse Error for the 100 Percent Data Items on the Census 2000 Long Form Questionnaire.” In JSM Proceedings Section on Survey Research Methods American Statistical Association Minneapolis MN August 7–11 2005. Alexandria VA: American Statistical Association. 2857–2864. Available at: http://ww2.amstat.org/sections/srms/Proceedings/y2005/Files/JSM2005-000341.pdf (accessed January 2017).

  • Keller A. and T. Fox. 2012. “2010 Census Coverage Measurement Estimation Report: Components of Census Coverage for the Household Population in the United States.” DSSD 2010 CENSUS COVERAGE MEASUREMENT MEMORANDUM SERIES #2010-G-04. Washington DC: U.S. Census Bureau. Available at: http://www.census.gov/coverage_measurement/pdfs/g04.pdf (accessed January 2017).

  • King T. S. Cook and J. Hunter Childs. 2012. “Interviewing Proxy Versus Self-Reporting Respondents to Obtain Information Regarding Living Situations.” In JSM Proceedings Survey Research Methods Section American Statistical Association San Diego CA July 28–August 2 2012. Alexandria VA: American Statistical Association. 5667–5677. Available at: https://ww2.amstat.org/sections/srms/proceedings/y2012/files/400243_500698.pdf (accessed January 2017).

  • Layne M. D. Wagner and C. Rothhaas. 2014. “Estimating Record Linkage False Match Rate for the Person Identification Validation System.” CARRA Working Paper Series. Working Paper #2014-02. Washington DC: Census Bureau. Available at: https://www.census.gov/library/working-papers/2014/adrm/carra-wp-2014-02.html (accessed March 2017).

  • Lohr S. 1999. Sampling: Design and Analysis. Cengage Learning. Boston MA.

  • Martin E. 1999. “Who Knows Who Lives Here? Within-household Disagreements as a Source of Survey Coverage Error.” Public Opinion Quarterly 63: 220–236. Doi: http://dx.doi.org/10.1086/297712.

  • Morris D. A. Keller and B. Clark. 2016. “An Approach for Using Administrative Records to Reduce Contacts in the 2020 Census.” Statistical Journal of the IAOS 32: 177–188. Doi: http://dx.doi.org/10.3233/SJI-161002.

  • Mule T. 2012. “Census Coverage Measurement Estimation Report: Summary of Estimates of Coverage for Persons in the United States.” DSSD 2010 CENSUS COVERAGE MEASUREMENTMEMORANDUMSERIES #2010-G-01. Washington DC: U.S. Census Bureau. Available at: http://www.census.gov/coverage_measurement/pdfs/g01.pdf (accessed January 2017).

  • Mulrow E. A. Mushta S. Pramanik and A. Fontes. 2011. Assessment of the U.S. Census Bureau’s Person Identification Validation System. Report for the U.S. Census Bureau. Chicago IL: NORC. Available at: http://www.norc.org/PDFs/May%202011%20Personal%20Validation%20and%20Entity%20Resolution%20Conference/PVS%20Assessment%20Report%20FINAL%20JULY%202011.pdf (accessed January 2017).

  • Mulry M.H. and B.D. Spencer. 2012. “A Framework for Cost Models Relating Cost and Data Quality.” Presentation at the 2012 International Total Survey Error Workshop. Sanpoort The Netherlands September 2–4 2012. Research Triangle Park NC: National Institute of Statistical Science. Available at: http://www.niss.org/sites/default/files/Mulry_september2012.pdf (accessed January 2017).

  • Olson D. and R. Griffin. 2012. “2010 Census Coverage Measurement Estimation Report: Aspects of Modeling.” DSSD 2010 CENSUS COVERAGE MEASUREMENT MEMORANDUM SERIES #2010-G-10. U.S. Washington DC: Census Bureau. Available at: http://www.census.gov/coverage_measurement/pdfs/g10.pdf (accessed January 2017).

  • U.S. Census Bureau. 2015. Planning Database. Washington DC: Census Bureau. Available at: http://www.census.gov/research/data/planning_database/ (accessed January 2017).

  • Wagner D. and M. Layne. 2014. “The Person Identification Validation System (PVS): Applying the Center for Administrative Records Research and Applications.” CARRA Working Paper Series. Working Paper #2014-01. Washington DC: Census Bureau. Available at: https://www.census.gov/library/working-papers/2014/adrm/carra-wp-2014-01.html (accessed March 2017).

  • Wolfgang G. R. Byrne and S. Spratt. 2003. Analysis of Proxy Data in the Accuracy and Coverage Evaluation Census 2000 Evaluation O.5. Washington DC: U.S. Census Bureau. https://www.census.gov/pred/www/rpts/O.5.PDF (accessed March 2017).

Search
Journal information
Impact Factor

IMPACT FACTOR 2018: 0.837
5-year IMPACT FACTOR: 0.934

CiteScore 2018: 1.04

SCImago Journal Rank (SJR) 2018: 0.963
Source Normalized Impact per Paper (SNIP) 2018: 1.020

Metrics
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 426 235 54
PDF Downloads 177 107 5