IDEAS home Printed from https://ideas.repec.org/p/cen/wpaper/23-21.html
   My bibliography  Save this paper

Estimating the U.S. Citizen Voting-Age Population (CVAP) Using Blended Survey Data, Administrative Record Data, and Modeling: Technical Report

Author

Listed:
  • J. David Brown
  • Genevieve Denoeux
  • Misty L. Heggeness
  • Carl Lieberman
  • Lauren Medina
  • Marta Murray-Close
  • Danielle H. Sandler
  • Joseph L. Schafer
  • Matthew Spence
  • Lawrence Warren
  • Moises Yi

Abstract

This report develops a method using administrative records (AR) to fill in responses for nonresponding American Community Survey (ACS) housing units rather than adjusting survey weights to account for selection of a subset of nonresponding housing units for follow-up interviews and for nonresponse bias. The method also inserts AR and modeling in place of edits and imputations for ACS survey citizenship item nonresponses. We produce Citizen Voting-Age Population (CVAP) tabulations using this enhanced CVAP method and compare them to published estimates. The enhanced CVAP method produces a 0.74 percentage point lower citizen share, and it is 3.05 percentage points lower for voting-age Hispanics. The latter result can be partly explained by omissions of voting-age Hispanic noncitizens with unknown legal status from ACS household responses. Weight adjustments may be less effective at addressing nonresponse bias under those conditions.

Suggested Citation

  • J. David Brown & Genevieve Denoeux & Misty L. Heggeness & Carl Lieberman & Lauren Medina & Marta Murray-Close & Danielle H. Sandler & Joseph L. Schafer & Matthew Spence & Lawrence Warren & Moises Yi, 2023. "Estimating the U.S. Citizen Voting-Age Population (CVAP) Using Blended Survey Data, Administrative Record Data, and Modeling: Technical Report," Working Papers 23-21, Center for Economic Studies, U.S. Census Bureau.
  • Handle: RePEc:cen:wpaper:23-21
    as

    Download full text from publisher

    File URL: https://www2.census.gov/library/working-papers/2023/adrm/ces/CES-WP-23-21.pdf
    File Function: First version, 2023
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bruce D. Meyer & Nikolas Mittag, 2019. "Using Linked Survey and Administrative Data to Better Measure Income: Implications for Poverty, Program Effectiveness, and Holes in the Safety Net," American Economic Journal: Applied Economics, American Economic Association, vol. 11(2), pages 176-204, April.
    2. Jennifer Hook & Frank Bean & James Bachmeier & Catherine Tucker, 2014. "Recent Trends in Coverage of the Mexican-Born Population of the United States: Results From Applying Multiple Methods Across Time," Demography, Springer;Population Association of America (PAA), vol. 51(2), pages 699-726, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Meyer, Bruce D. & Mittag, Nikolas, 2019. "Combining Administrative and Survey Data to Improve Income Measurement," IZA Discussion Papers 12266, Institute of Labor Economics (IZA).
    2. Breen, Casey & Goldstein, Joshua R., 2022. "Berkeley Unified Numident Mortality Database: Public Administrative Records for Individual-Level Mortality Research," SocArXiv pc294, Center for Open Science.
    3. Colleen Heflin & Michah W. Rothbart & Mattie Mackenzie-Liu, 2022. "Below the Tip of the Iceberg: Examining Early Childhood Participation in SNAP and TANF from Birth to Age Six," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 41(2), pages 729-755, April.
    4. Davillas, Apostolos & Pudney, Stephen, 2020. "Using biomarkers to predict healthcare costs: Evidence from a UK household panel," Journal of Health Economics, Elsevier, vol. 73(C).
    5. Chloe N. East & Annie L. Hines & Philip Luck & Hani Mansour & Andrea Velásquez, 2023. "The Labor Market Effects of Immigration Enforcement," Journal of Labor Economics, University of Chicago Press, vol. 41(4), pages 957-996.
    6. Michele Lalla & Maddalena Cavicchioli, 2020. "Nonresponse and measurement errors in income: matching individual survey data with administrative tax data," Department of Economics 0170, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
    7. Lidia Ceriani & Vladimir Hlasny & Paolo Verme, 2021. "Bottom Incomes and the Measurement of Poverty: A Brief Assessment of the Literature," Working Papers 589, ECINEQ, Society for the Study of Economic Inequality.
    8. Kate W. Strully & Robert Bozick & Ying Huang & Lane F. Burgette, 2020. "Employer Verification Mandates and Infant Health," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 39(6), pages 1143-1184, December.
    9. Hicks, Jeffrey & Simard-Duplain, Gaëlle & Green, David A. & Warburton, William, 2022. "The effect of reducing welfare access on employment, health, and children's long-run outcomes," CLEF Working Paper Series 51, Canadian Labour Economics Forum (CLEF), University of Waterloo.
    10. Meyer, Bruce D. & Mittag, Nikolas, 2021. "An empirical total survey error decomposition using data combination," Journal of Econometrics, Elsevier, vol. 224(2), pages 286-305.
    11. Christoph Albert & Albrecht Glitz & Joan Llull, 2021. "Labor Market Competition and the Assimilation of Immigrants," Working Papers 1280, Barcelona School of Economics.
    12. Dillon, Andrew & Karlan, Dean & Udry, Christopher & Zinman, Jonathan, 2020. "Good identification, meet good data," World Development, Elsevier, vol. 127(C).
    13. Julia Heinzel & Rebecca Heller & Natalie Tawil, 2021. "Estimating the Legal Status of Foreign-Born People: Working Paper 2021-02," Working Papers 57022, Congressional Budget Office.
    14. Ha Trong Nguyen & Huong Thu Le & Luke Connelly & Francis Mitrou, 2023. "Accuracy of self‐reported private health insurance coverage," Health Economics, John Wiley & Sons, Ltd., vol. 32(12), pages 2709-2729, December.
    15. Jeff Larrimore & Jacob Mortenson & David Splinter, 2023. "Unemployment Insurance In Survey And Administrative Data," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 42(2), pages 571-579, March.
    16. Martin Rama, 2019. "Challenges in Measuring Poverty and Understanding its Dynamics: A South Asian Perspective," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 65(S1), pages 2-32, November.
    17. Watson, C. Luke, 2021. "the General Equilibrium Incidence of the Earned Income Tax Credit," SocArXiv 8n3ag, Center for Open Science.
    18. Joshua D. Gottlieb & Maria Polyakova & Kevin Rinz & Hugh Shiplett & Victoria Udalova, 2020. "Who Values Human Capitalists' Human Capital? Healthcare Spending and Physician Earnings," Working Papers 20-23, Center for Economic Studies, U.S. Census Bureau.
    19. Otto Lenhart, 2023. "The earned income tax credit and food insecurity," American Journal of Agricultural Economics, John Wiley & Sons, vol. 105(5), pages 1543-1570, October.
    20. James X. Sullivan, 2020. "A Cautionary Tale of Using Data From the Tail," Demography, Springer;Population Association of America (PAA), vol. 57(6), pages 2361-2368, December.

    More about this item

    Keywords

    citizenship; administrative records; voting-age population; nonresponse bias;
    All these keywords.

    JEL classification:

    • J1 - Labor and Demographic Economics - - Demographic Economics
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cen:wpaper:23-21. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Dawn Anderson (email available below). General contact details of provider: https://edirc.repec.org/data/cesgvus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.