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Heaping at Round Numbers on Financial Questions : The Role of Satisficing

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Abstract

Survey responses to quantitative financial questions frequently display strong patterns of heaping at round numbers. This paper uses two studies to examine variation in rounding across questions and by individual characteristics. Rounding was more common for respondents low in ability, for respondents low in motivation, and for more difficult questions, all consistent with theories of satisficing. Questions that require more difficult information retrieval and integration of information exhibit more heaping. The use of records, which lowers task difficulty, reduces rounding as well. Higher episodic memory is associated with less rounding, and standard measures of motivation are negatively associated with rounding. These relationships, along with the fact that longer response latencies are associated with less rounding, all support the idea that rounding is a manifestation of satisficing on open-ended financial questions. Rounding patterns also appear remarkably similar across the two studies, despite being fielded in different modes and employing different question order and wording.

Suggested Citation

  • Michael Gideon & Brooke Helppie-McFall & Joanne W. Hsu, 2017. "Heaping at Round Numbers on Financial Questions : The Role of Satisficing," Finance and Economics Discussion Series 2017-006, Board of Governors of the Federal Reserve System (U.S.).
    • Handle: RePEc:fip:fedgfe:2017-06
    DOI: 10.17016/FEDS.2017.006
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    4. Joanne W. Hsu, 2016. "Aging and Strategic Learning: The Impact of Spousal Incentives on Financial Literacy," Journal of Human Resources, University of Wisconsin Press, vol. 51(4), pages 1036-1067.
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    Cited by:

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    3. Bachmann, Ronald & Bonin, Holger & Boockmann, Bernhard & Demir, Gökay & Felder, Rahel & Isphording, Ingo & Kalweit, René & Laub, Natalie & Vonnahme, Christina & Zimpelmann, Christian, 2020. "Auswirkungen des gesetzlichen Mindestlohns auf Löhne und Arbeitszeiten: Studie im Auftrag der Mindestlohnkommission," RWI Projektberichte, RWI - Leibniz-Institut für Wirtschaftsforschung, number 222998.
    4. Bachmann, Ronald & Boockmann, Bernhard & Gonschor, Myrielle & Kalweit, René & Klauser, Roman & Laub, Natalie & Rulff, Christian & Vonnahme, Christina, 2022. "Auswirkungen des gesetzlichen Mindestlohns auf Löhne und Arbeitszeiten," RWI Projektberichte, RWI - Leibniz-Institut für Wirtschaftsforschung, number 264288.
    5. Stanisławska, Ewa & Paloviita, Maritta, 2021. "Medium- vs. short-term consumer inflation expectations: Evidence from a new euro area survey," Bank of Finland Research Discussion Papers 10/2021, Bank of Finland.
    6. Clemens, Jeffrey & Strain, Michael R., 2022. "Understanding “Wage Theft”: Evasion and avoidance responses to minimum wage increases," Labour Economics, Elsevier, vol. 79(C).
    7. Dean Scrimgeour, 2022. "Reevaluating the evidence on seasonality in housing market match quality: Replication of Ngai and Tenreyro (2014)," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(7), pages 1403-1409, November.
    8. Maxime Phillot & Rina Rosenblatt-Wisch, 2024. "Order Matters: An Experimental Study on How Question Ordering Affects Survey-Based Inflation Forecasts," International Journal of Central Banking, International Journal of Central Banking, vol. 20(3), pages 63-114, July.
    9. Madeira, Carlos & Margaretic, Paula, 2022. "The impact of financial literacy on the quality of self-reported financial information," Journal of Behavioral and Experimental Finance, Elsevier, vol. 34(C).
    10. Sinha Roy,Sutirtha & Van Der Weide,Roy, 2022. "Poverty in India Has Declined over the Last Decade But Not As Much As Previously Thought," Policy Research Working Paper Series 9994, The World Bank.
    11. Philip E Hulme & Danish A Ahmed & Phillip J Haubrock & Brooks A Kaiser & Melina Kourantidou & Boris Leroy & Shana M Mcdermott, 2024. "Widespread imprecision in estimates of the economic costs of invasive alien species worldwide," Post-Print hal-04633043, HAL.

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    More about this item

    Keywords

    Consumer surveys; Data collection and estimation; Satisficing;
    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
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods

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