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Nonresponse and Focal Point Answers to Subjective Probability Questions

Author

Listed:
  • Kleinjans, Kristin J.

    (California State University, Fullerton)

  • van Soest, Arthur

    (Tilburg University)

Abstract

We develop and estimate a panel data model explaining the answers to questions about subjective probabilities, using data from the US Health and Retirement Study. We explicitly account for nonresponse, rounding, and focal point “50 percent” answers. Our results indicate that for three of the four questions considered, almost all 50 percent answers can be explained by rounding. We also find observed and unobserved heterogeneity in the tendencies to report rounded values or a focal answer, explaining persistency in 50 percent-answers over time. Incorporating rounding and focal answers changes some of the conclusions about the socio-economic factors that determine expectations.

Suggested Citation

  • Kleinjans, Kristin J. & van Soest, Arthur, 2010. "Nonresponse and Focal Point Answers to Subjective Probability Questions," IZA Discussion Papers 5272, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp5272
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    References listed on IDEAS

    as
    1. van Soest, Arthur & Hurd, Michael, 2008. "A Test for Anchoring and Yea-Saying in Experimental Consumption Data," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 126-136, March.
    2. van Soest, Arthur & Hurd, Michael, 2008. "A Test for Anchoring and Yea-Saying in Experimental Consumption Data," Journal of the American Statistical Association, American Statistical Association, pages 126-136.
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    Cited by:

    1. Gutierrez, Italo A., 2016. "Job insecurity, unemployment insurance and on-the-job search. Evidence from older American workers," Labour Economics, Elsevier, vol. 41(C), pages 228-245.
    2. Alexander Zimper, 2012. "The emergence of "fifty-fifty" probability judgements in a conditional Savage world," Working Papers 201221, University of Pretoria, Department of Economics.
    3. Olivier Coibion & Yuriy Gorodnichenko & Saten Kumar & Jane Ryngaert, 2018. "Do You Know That I Know That You Know...? Higher-Order Beliefs in Survey Data," NBER Working Papers 24987, National Bureau of Economic Research, Inc.
    4. Aylit Tina Romm, 2014. "An interpretation of focal point responses as non-additive beliefs," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 9(5), pages 387-402, September.
    5. repec:cup:judgdm:v:9:y:2014:i:5:p:387-402 is not listed on IDEAS
    6. Coibion, Olivier & Gorodnichenko, Yuriy & Kumar, Saten & Pedemonte, Mathieu, 2020. "Inflation expectations as a policy tool?," Journal of International Economics, Elsevier, vol. 124(C).
    7. Italo A. Gutierrez & Pierre-Carl Michaud, 2017. "Whistle While You Work: Job Insecurity and Older Workers’ Mental Health in the United States," CIRANO Working Papers 2017s-21, CIRANO.
    8. van Santen, Peter & Alessie, Rob & Kalwij, Adriaan, 2012. "Probabilistic survey questions and incorrect answers: Retirement income replacement rates," Journal of Economic Behavior & Organization, Elsevier, vol. 82(1), pages 267-280.
    9. Gabrielle Penrose & Gianni La Cava, 2021. "Job Loss, Subjective Expectations and Household Spending," RBA Research Discussion Papers rdp2021-08, Reserve Bank of Australia.
    10. Robin L. Lumsdaine & Rogier J.D. Potter van Loon, 2013. "Wall Street vs. Main Street: An Evaluation of Probabilities," NBER Working Papers 19103, National Bureau of Economic Research, Inc.

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    More about this item

    Keywords

    rounding; item nonresponse; expectations;
    All these keywords.

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations

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