Why do we value immediate rewards more than long-term rewards?

Hyperbolic Discounting

, explained.

Bias

What is Hyperbolic Discounting?

Hyperbolic discounting is our inclination to choose immediate rewards over rewards that come later in the future, even when these immediate rewards are smaller.

Where this bias occurs

Consider the following hypothetical: John buys a lottery ticket every week. He hopes to someday win big. One fortunate day, against all odds, he does. John is now worth just over $5 million.

After a frenzy of celebrations and hugs, John drives to the lottery offices to claim his prize. When he arrives, the lottery director gives him a choice: he could either claim the $5 million now, or he could choose to receive $250,000 every year for the rest of his life instead. John is only 35. Quick mental math points to the second option generating more revenue for John if he lives past the age of 55—which he plans on doing. But, John imagines having a seven figure total in his bank account and relishes the idea of all the things he could buy today.

John decides to take the first option, even though he will likely receive less money from it in the long-run. His preference towards immediate benefits over future gain can be attributed to hyperbolic discounting.

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Sources

Samson, A. (2017). The Behavioral Economics Guide 2017. Behavioral Science Solutions.
Bickel, W. K., Odum, A. L., & Madden, G. J. (1999). Impulsivity and cigarette smoking: Delay discounting in current, never, and ex-smokers. Psychopharmacology, 146(4), 447-454. doi:10.1007/pl00005490
Samson, A. (2017). The Behavioral Economics Guide 2017. Behavioral Science Solutions.
Prospect Theory and Loss Aversion: How Users Make Decisions. (n.d.). Retrieved July 11, 2020, from https://www.nngroup.com/articles/prospect-theory/
Temporal Myopia: Making Bad Long-term Decisions. (2012, September 23). Retrieved July 11, 2020, from https://www.psychologytoday.com/ca/blog/brain-bugs/201209/temporal-myopia-making-bad-long-term-decisions
Holyoak, K. J., & Morrison, R. G. (2013). Decisions Regarding the Future: Temporal Discounting. In The Oxford handbook of thinking and reasoning (pp. 312-313). Oxford: Oxford University Press.
YEŞİLKAYALI, D. (n.d.). PROCRASTINATION AND FUTURE DISCOUNTING. The Journal of International Social Research, 7(30).
Sheffer, C. E., Mackillop, J., Fernandez, A., Christensen, D., Bickel, W. K., Johnson, M. W.,Mathew, M. (2016). Initial examination of priming tasks to decrease delay discounting. Behavioural Processes, 128, 144-152. doi:10.1016/j.beproc.2016.05.002
Hershfield, H. E., Goldstein, D. G., Sharpe, W. F., Fox, J., Yeykelis, L., Carstensen, L. L., & Bailenson, J. N. (2011). Increasing Saving Behavior Through Age-Progressed Renderings of the Future Self. Journal of Marketing Research, 48(SPL). doi:10.1509/jmkr.48.spl.s23
Ainslie, G. (2012). Pure Hyperbolic Discount Curves Predict “Eyes Open” Self-Control. Theory and Decision. doi:10.1007/s1123801192725
Loewenstein, G., & Thaler, R. (1989). Anomalies: Intertemporal Choice. The Journal of Economic Perspectives, 3(4), 181-193. Retrieved July 11, 2020, from www.jstor.org/stable/1942918
Frederick, S., Loewenstein, G., & O’Donoghue, T. (2002). Time Discounting and Time Preference: A Critical Review. Journal of Economic Literature, 40(2), 351–401. http://www.jstor.org/stable/2698382
Chung, H., & Herrnstein, R. J. (1967). CHOICE AND DELAY OF REINFORCEMENT1. Journal of the Experimental Analysis of Behavior, 10(1), 67-74. https://doi.org/10.1901/jeab.1967.10-67
Solá, A. T. (2024, November 4). Gen Z, millennials are using AI for personal finance advice, report finds. CNBC. https://www.cnbc.com/2024/11/04/how-to-use-artificial-intelligence-for-personal-finance.html
Brocas, I., Carrillo, J. D., & Dewatripont, M. (2004). Commitment devices under self-control problems: An overview. The Psychology of economic decisions, 2, 49-67.

About the Authors

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Dan Pilat

Dan is a Co-Founder and Managing Director at The Decision Lab. He is a bestselling author of Intention - a book he wrote with Wiley on the mindful application of behavioral science in organizations. Dan has a background in organizational decision making, with a BComm in Decision & Information Systems from McGill University. He has worked on enterprise-level behavioral architecture at TD Securities and BMO Capital Markets, where he advised management on the implementation of systems processing billions of dollars per week. Driven by an appetite for the latest in technology, Dan created a course on business intelligence and lectured at McGill University, and has applied behavioral science to topics such as augmented and virtual reality.

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Dr. Sekoul Krastev

Sekoul is a Co-Founder and Managing Director at The Decision Lab. He is a bestselling author of Intention - a book he wrote with Wiley on the mindful application of behavioral science in organizations. A decision scientist with a PhD in Decision Neuroscience from McGill University, Sekoul's work has been featured in peer-reviewed journals and has been presented at conferences around the world. Sekoul previously advised management on innovation and engagement strategy at The Boston Consulting Group as well as on online media strategy at Google. He has a deep interest in the applications of behavioral science to new technology and has published on these topics in places such as the Huffington Post and Strategy & Business.

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