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Panel Conditioning in Longitudinal Studies: Evidence From Labor Force Items in the Current Population Survey

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  • Andrew Halpern-Manners
  • John Warren

Abstract

Does participating in a longitudinal survey affect respondents’ answers to subsequent questions about their labor force characteristics? In this article, we investigate the magnitude of panel conditioning or time-in-survey biases for key labor force questions in the monthly Current Population Survey (CPS). Using linked CPS records for household heads first interviewed between January 2007 and June 2010, our analyses are based on strategic within-person comparisons across survey months and between-person comparisons across CPS rotation groups. We find considerable evidence for panel conditioning effects in the CPS. Panel conditioning downwardly biases the CPS-based unemployment rate, mainly by leading people to remove themselves from its denominator. Across surveys, CPS respondents (claim to) leave the labor force in greater numbers than otherwise equivalent respondents who are participating in the CPS for the first time. The results cannot be attributed to panel attrition or mode effects. We discuss implications for CPS-based research and policy as well as for survey methodology more broadly. Copyright Population Association of America 2012

Suggested Citation

  • Andrew Halpern-Manners & John Warren, 2012. "Panel Conditioning in Longitudinal Studies: Evidence From Labor Force Items in the Current Population Survey," Demography, Springer;Population Association of America (PAA), vol. 49(4), pages 1499-1519, November.
    • Handle: RePEc:spr:demogr:v:49:y:2012:i:4:p:1499-1519
    DOI: 10.1007/s13524-012-0124-x
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Ward, Jason M. & Anne Edwards, Kathryn, 2021. "CPS Nonresponse During the COVID-19 Pandemic: Explanations, Extent, and Effects," Labour Economics, Elsevier, vol. 72(C).
    2. Chadi, Adrian, 2021. "Identification of attrition bias using different types of panel refreshments," Economics Letters, Elsevier, vol. 201(C).
    3. Beatty, Timothy K.M. & Ritter, Joseph A., 2018. "Measuring the Health Cost of Prolonged Unemployment: Evidence from the Great Recession," Miscellaneous Publications 280435, University of Minnesota, Department of Applied Economics.
    4. Jed Friedman & Kathleen Beegle & Joachim De Weerdt & John Gibson, 2016. "Decomposing response error in food consumption measurement: implications for survey design from a survey experiment in Tanzania," Working Papers of LICOS - Centre for Institutions and Economic Performance 537166, KU Leuven, Faculty of Economics and Business (FEB), LICOS - Centre for Institutions and Economic Performance.
    5. Hie Joo Ahn & James Hamilton, 2022. "Measuring Labor-Force Participation and the Incidence and Duration of Unemployment," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 44, pages 1-32, April.
    6. Ryan D. Edwards, 2018. "If My Blood Pressure Is High, Do I Take It to Heart? Behavioral Effects of Biomarker Collection in the Health and Retirement Study," Demography, Springer;Population Association of America (PAA), vol. 55(2), pages 403-434, April.
    7. Beatty, Timothy K.M. & Ritter, Joseph A., 2018. "Measuring the Health Cost of Prolonged Unemployment: Evidence from the Great Recession," Staff Papers 280435, University of Minnesota, Department of Applied Economics.
    8. repec:lic:licosd:37516 is not listed on IDEAS
    9. Hie Joo Ahn & James Hamilton, 2022. "Measuring Labor-Force Participation and the Incidence and Duration of Unemployment," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 44, pages 1-32, April.
    10. Bernhardt, Robert & Munro, David & Wolcott, Erin, 2021. "How Does the Dramatic Rise of CPS Non-Response Impact Labor Market Indicators?," GLO Discussion Paper Series 781, Global Labor Organization (GLO).
    11. Bach, Ruben L. & Eckman, Stephanie, 2020. "Rotation group bias in reporting of household purchases in the U.S. Consumer Expenditure Survey," Economics Letters, Elsevier, vol. 187(C).
    12. Hannah Schwarz & Melanie Revilla & Bella Struminskaya, 2022. "Do previous survey experience and participating due to an incentive affect response quality? Evidence from the CRONOS panel," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(3), pages 981-1003, July.
    13. Georgarakos, Dimitris & Kenny, Geoff, 2022. "Household spending and fiscal support during the COVID-19 pandemic: Insights from a new consumer survey," Journal of Monetary Economics, Elsevier, vol. 129(S), pages 1-14.
    14. Friedman, Jed & Beegle, Kathleen & De Weerdt, Joachim & Gibson, John, 2017. "Decomposing response error in food consumption measurement: Implications for survey design from a randomized survey experiment in Tanzania," Food Policy, Elsevier, vol. 72(C), pages 94-111.
    15. Bach, Ruben L. & Eckman, Stephanie, 2017. "Does participating in a panel survey change respondents' labor market behavior?," IAB-Discussion Paper 201715, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    16. Bailey, Keith A. & Spletzer, James R., 2021. "A new measure of multiple jobholding in the U.S. economy," Labour Economics, Elsevier, vol. 71(C).
    17. Ryan D. Edwards, 2013. "If My Blood Pressure Is High, Do I Take It To Heart? Behavioral Impacts of Biomarker Collection in the Health and Retirement Study," NBER Working Papers 19311, National Bureau of Economic Research, Inc.
    18. 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.

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