IDEAS home Printed from https://ideas.repec.org/a/taf/jnlasa/v110y2015i511p935-945.html
   My bibliography  Save this article

The Role of CPS Nonresponse in the Measurement of Poverty

Author

Listed:
  • Charles Hokayem
  • Christopher Bollinger
  • James P. Ziliak

Abstract

The Current Population Survey Annual Social and Economic Supplement (CPS ASEC) serves as the data source for official income, poverty, and inequality statistics in the United States. There is a concern that the rise in nonresponse to earnings questions could deteriorate data quality and distort estimates of these important metrics. We use a dataset of internal ASEC records matched to Social Security Detailed Earnings Records (DER) to study the impact of earnings nonresponse on estimates of poverty from 1997-2008. Our analysis does not treat the administrative data as the "truth"; instead, we rely on information from both administrative and survey data. We compare a "full response" poverty rate that assumes all ASEC respondents provided earnings data to the official poverty rate to gauge the nonresponse bias. On average, we find the nonresponse bias is about 1.0 percentage point.

Suggested Citation

  • Charles Hokayem & Christopher Bollinger & James P. Ziliak, 2015. "The Role of CPS Nonresponse in the Measurement of Poverty," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(511), pages 935-945, September.
    • Handle: RePEc:taf:jnlasa:v:110:y:2015:i:511:p:935-945
    DOI: 10.1080/01621459.2015.1029576
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/01621459.2015.1029576
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/01621459.2015.1029576?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Marc Roemer, 2002. "Using Administrative Earnings Records to Assess Wage Data Quality in the March Current Population Survey and the Survey of Income and Program Participation," Longitudinal Employer-Household Dynamics Technical Papers 2002-22, Center for Economic Studies, U.S. Census Bureau.
    2. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gopi Shah Goda & Emilie Jackson & Lauren Hersch Nicholas & Sarah See Stith, 2023. "The impact of Covid-19 on older workers’ employment and Social Security spillovers," Journal of Population Economics, Springer;European Society for Population Economics, vol. 36(2), pages 813-846, April.
    2. Meyer, Bruce D. & Mittag, Nikolas, 2017. "Using Linked Survey and Administrative Data to Better Measure Income: Implications for Poverty, Program Effectiveness and Holes in the Safety Net," IZA Discussion Papers 10943, Institute of Labor Economics (IZA).
    3. Borgschulte, Mark & Cho, Heepyung & Lubotsky, Darren, 2022. "Partisanship and survey refusal," Journal of Economic Behavior & Organization, Elsevier, vol. 200(C), pages 332-357.
    4. George L. Wehby & Dhaval M. Dave & Robert Kaestner, 2020. "Effects of the Minimum Wage on Infant Health," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 39(2), pages 411-443, March.
    5. Bruce Meyer & Nikolas Mittag, 2017. "Using Linked Survey and Administrative Data to Better Measure Income: Implications for Poverty, Program Effectiveness and Holes in the Safety Net," Working Papers 2017-075, Human Capital and Economic Opportunity Working Group.
    6. 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.
    7. 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.
    8. Adam Bee & Joshua Mitchell & Nikolas Mittag & Jonathan Rothbaum & Carl Sanders & Lawrence Schmidt & Matthew Unrath, 2023. "National Experimental Wellbeing Statistics - Version 1," Working Papers 23-04, Center for Economic Studies, U.S. Census Bureau.
    9. Carlos A. Piccioni & Saulo B. Bastos & Daniel O. Cajueiro, 2024. "Measuring Inequality Using Electronic Payment Data," Working Papers Series 608, Central Bank of Brazil, Research Department.
    10. David Brady & Zachary Parolin, 2020. "The Levels and Trends in Deep and Extreme Poverty in the United States, 1993–2016," Demography, Springer;Population Association of America (PAA), vol. 57(6), pages 2337-2360, December.
    11. Klee, Mark A. & Chenevert, Rebecca L. & Wilkin, Kelly R., 2019. "Revisiting the shape of earnings nonresponse," Economics Letters, Elsevier, vol. 184(C).
    12. Ethan Krohn, 2024. "Earnings Through the Stages: Using Tax Data to Test for Sources of Error in CPS ASEC Earnings and Inequality Measures," Working Papers 24-52, Center for Economic Studies, U.S. Census Bureau.
    13. Bhashkar Mazumder, 2018. "Intergenerational Mobility in the United States: What We Have Learned from the PSID," The ANNALS of the American Academy of Political and Social Science, , vol. 680(1), pages 213-234, November.
    14. Margaret E. Brehm & Olga Malkova, 2023. "The Child Tax Credit over Time by Family Type: Benefit Eligibility and Poverty," National Tax Journal, University of Chicago Press, vol. 76(3), pages 707-741.
    15. Peter Valet & Jule Adriaans & Stefan Liebig, 2019. "Comparing survey data and administrative records on gross earnings: nonreporting, misreporting, interviewer presence and earnings inequality," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(1), pages 471-491, January.
    16. Robert Bernhardt & David Munro & Erin L. Wolcott, 2024. "How does the dramatic rise of nonresponse in the Current Population Survey impact labor market indicators?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(3), pages 498-512, April.

    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. James P. Ziliak & Charles Hokayem & Christopher R. Bollinger, 2022. "Trends in Earnings Volatility Using Linked Administrative and Survey Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(1), pages 12-19, December.
    2. Mengyuan Zhou, 2022. "Does the Source of Inheritance Matter in Bequest Attitudes? Evidence from Japan," Journal of Family and Economic Issues, Springer, vol. 43(4), pages 867-887, December.
    3. Campbell, Randall C. & Nagel, Gregory L., 2016. "Private information and limitations of Heckman's estimator in banking and corporate finance research," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 186-195.
    4. Giuliani, Elisa & Martinelli, Arianna & Rabellotti, Roberta, 2016. "Is Co-Invention Expediting Technological Catch Up? A Study of Collaboration between Emerging Country Firms and EU Inventors," World Development, Elsevier, vol. 77(C), pages 192-205.
    5. Ilona Babenko & Benjamin Bennett & John M Bizjak & Jeffrey L Coles & Jason J Sandvik, 2023. "Clawback Provisions and Firm Risk," The Review of Corporate Finance Studies, Society for Financial Studies, vol. 12(2), pages 191-239.
    6. Şahan, Duygu & Tuna, Okan, 2018. "Environmental innovation of transportation sector in OECD countries," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Kersten, Wolfgang & Blecker, Thorsten & Ringle, Christian M. (ed.), The Road to a Digitalized Supply Chain Management: Smart and Digital Solutions for Supply Chain Management. Proceedings of the Hamburg International C, volume 25, pages 157-170, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    7. Eric Fesselmeyer & Kiat Ying Seah, 2018. "Individual Payoffs and the Effect of Homeownership on Social Capital Investment," Journal of Housing Research, Taylor & Francis Journals, vol. 27(1), pages 59-78, January.
    8. Ruomeng Cui & Dennis J. Zhang & Achal Bassamboo, 2019. "Learning from Inventory Availability Information: Evidence from Field Experiments on Amazon," Management Science, INFORMS, vol. 65(3), pages 1216-1235, March.
    9. Luiz Paulo Fávero & Joseph F. Hair & Rafael de Freitas Souza & Matheus Albergaria & Talles V. Brugni, 2021. "Zero-Inflated Generalized Linear Mixed Models: A Better Way to Understand Data Relationships," Mathematics, MDPI, vol. 9(10), pages 1-28, May.
    10. Shaikh M. S. U. Eskander & Sam Fankhauser, 2022. "Income Diversification and Income Inequality: Household Responses to the 2013 Floods in Pakistan," Sustainability, MDPI, vol. 14(1), pages 1-12, January.
    11. Iván Fernández-Val & Martin Weidner, 2018. "Fixed Effects Estimation of Large-TPanel Data Models," Annual Review of Economics, Annual Reviews, vol. 10(1), pages 109-138, August.
    12. Peter Harasztosi & Attila Lindner, 2019. "Who Pays for the Minimum Wage?," American Economic Review, American Economic Association, vol. 109(8), pages 2693-2727, August.
    13. Jinwon Kim & Jucheol Moon & Dongyun Yang, 2024. "Pigouvian Congestion Tolls and the Welfare Gain: Estimates for California Freeways," Working Papers 2402, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
    14. Cho, Seong-Hoon & Kim, Heeho & Roberts, Roland K. & Kim, Taeyoung & Lee, Daegoon, 2014. "Effects of changes in forestland ownership on deforestation and urbanization and the resulting effects on greenhouse gas emissions," Journal of Forest Economics, Elsevier, vol. 20(1), pages 93-109.
    15. Kazuki Onji & John P. Tang, 2015. "A nation without a corporate income tax: Evidence from nineteenth century Japan," Discussion Papers in Economics and Business 15-12, Osaka University, Graduate School of Economics.
    16. Brown, Sarah & Greene, William H. & Harris, Mark N. & Taylor, Karl, 2015. "An inverse hyperbolic sine heteroskedastic latent class panel tobit model: An application to modelling charitable donations," Economic Modelling, Elsevier, vol. 50(C), pages 228-236.
    17. Roberto Martino & Phu Nguyen-Van, 2014. "Labour market regulation and fiscal parameters: A structural model for European regions," Working Papers of BETA 2014-19, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    18. Etienne Redor & Magnus Blomkvist, 2021. "Do all inside and affiliated directors hold the same value for shareholders?," Economics Bulletin, AccessEcon, vol. 41(3), pages 882-895.
    19. Upasak Das & Rupayan Pal & Udayan Rathore & Bibhas Saha, 2023. "Rein in pandemic by pricing vaccine: Does social trust matter?," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2023-008, Indira Gandhi Institute of Development Research, Mumbai, India.
    20. Andreas Fagereng & Luigi Guiso & Davide Malacrino & Luigi Pistaferri, 2020. "Heterogeneity and Persistence in Returns to Wealth," Econometrica, Econometric Society, vol. 88(1), pages 115-170, January.

    More about this item

    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:taf:jnlasa:v:110:y:2015:i:511:p:935-945. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/UASA20 .

    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.