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In Equations We Trust? Formula Knowledge Effects on the Exponential Growth Bias in Household Finance Decisions

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  • Bryan Foltice

    (College of Business, Butler University, Indianapolis, Indiana 46208)

  • Thomas Langer

    (Finance Center Muenster, University of Muenster, 48143 Muenster, Germany)

Abstract

Exponential growth effects play a major role in many household finance decisions. A systematic bias in dealing with exponential growth can lead to poor savings and debt decisions. In this paper, we extend previous research on the exponential growth bias in the savings and debt domains and provide a first experimental link between these two important fields of consumer financial decision making. We develop a measure for the exponential growth bias that naturally extends over different domains and parameter settings, and we explore the ramifications of being acquainted with the basic formula of exponential savings growth. Specifically, we analyze whether such formula knowledge helps only in calculating simple compound interest scenarios with a pocket calculator or if it provides benefits that go beyond this narrow field of application. We observe that—even without a pocket calculator—individuals who know the compound interest formula provide less biased estimates for problems from the savings domain and also for slightly more complicated debt amortization problems that also build on exponential growth effects. We conclude that being acquainted with the compound interest formula provides some intuitive grasp of exponential effects that can be helpful in a broader range of household finance decisions. At the same time, we observe that too much dependence on a calculator can have adverse effects: when equipped with a pocket calculator, a number of participants, both aware and unaware of the compound savings formula, provided persistently insensible answers greater than the initial loan balance in the debt domain.

Suggested Citation

  • Bryan Foltice & Thomas Langer, 2017. "In Equations We Trust? Formula Knowledge Effects on the Exponential Growth Bias in Household Finance Decisions," Decision Analysis, INFORMS, vol. 14(3), pages 170-186, September.
    • Handle: RePEc:inm:ordeca:v:14:y:2017:i:3:p:170-186
    DOI: 10.1287/deca.2017.0351
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    References listed on IDEAS

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    1. Gopi Shah Goda & Colleen Flaherty Manchester & Aaron Sojourner, 2012. "What Will My Account Really Be Worth? An Experiment on Exponential Growth Bias and Retirement Saving," NBER Working Papers 17927, National Bureau of Economic Research, Inc.
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    3. Goda, Gopi Shah & Manchester, Colleen Flaherty & Sojourner, Aaron J., 2014. "What will my account really be worth? Experimental evidence on how retirement income projections affect saving," Journal of Public Economics, Elsevier, vol. 119(C), pages 80-92.
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    5. Victor Stango & Jonathan Zinman, 2009. "Exponential Growth Bias and Household Finance," Journal of Finance, American Finance Association, vol. 64(6), pages 2807-2849, December.
    6. Johan Almenberg & Christer Gerdes, 2012. "Exponential growth bias and financial literacy," Applied Economics Letters, Taylor & Francis Journals, vol. 19(17), pages 1693-1696.
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    Cited by:

    1. Henning Cordes & Bryan Foltice & Thomas Langer, 2019. "Misperception of Exponential Growth: Are People Aware of Their Errors?," Decision Analysis, INFORMS, vol. 16(4), pages 261-280, December.
    2. Foltice, Bryan & Langer, Thomas, 2018. "Exponential growth bias matters: Evidence and implications for financial decision making of college students in the U.S.A," Journal of Behavioral and Experimental Finance, Elsevier, vol. 19(C), pages 56-63.
    3. Nikolov, Plamen & Pape, Andreas & Tonguc, Ozlem & Williams, Charlotte, 2020. "Predictors of Social Distancing and Mask-Wearing Behavior: Panel Survey in Seven U.S. States," IZA Discussion Papers 13745, Institute of Labor Economics (IZA).

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