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The Role of Time Preferences and Exponential-Growth Bias in Retirement Savings

Author

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  • Gopi Shah Goda
  • Matthew R. Levy
  • Colleen Flaherty Manchester
  • Aaron Sojourner
  • Joshua Tasoff
Abstract
There is considerable variation in retirement savings within income, age, and educational categories. Using a broad sample of the U.S. population, we elicit time preference parameters from a quasi-hyperbolic discounting model, and perceptions of exponential growth. We find that present bias (PB), the tendency to value utility in the present over the future in a dynamically inconsistent way, and exponential-growth bias (EGB), the tendency to neglect compounding, are prevalent and distinct latent variables. PB, EGB, and the long-run discount factor are all highly significant in predicting retirement savings, even while controlling for measures of IQ and general financial literacy as well as a rich set of demographic controls. We find that lack of self-awareness of these biases has an additional independent negative impact on retirement savings. We assess potential threats to a causal interpretation of our results with a hypothetical choice experiment and several robustness exercises. Finally, we explore potential mechanisms for our findings. If the relationship we estimate is causal, our estimates suggest that eliminating PB and EGB would be associated with an increase in retirement savings of 12%, or as high as 70% using estimates that account for classical measurement error.

Suggested Citation

  • Gopi Shah Goda & Matthew R. Levy & Colleen Flaherty Manchester & Aaron Sojourner & Joshua Tasoff, 2015. "The Role of Time Preferences and Exponential-Growth Bias in Retirement Savings," NBER Working Papers 21482, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:21482
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    2. Ross Hikida & Jason Perry, 2020. "FinTech Trends in the United States: Implications for Household Finance," Public Policy Review, Policy Research Institute, Ministry of Finance Japan, vol. 16(4), pages 1-32, August.
    3. Jason S. Scott & John B. Shoven & Sita N. Slavov & John G. Watson, 2020. "Can Low Retirement Savings Be Rationalized?," NBER Working Papers 26784, National Bureau of Economic Research, Inc.
    4. Benjamin Enke & Thomas Graeber & Ryan Oprea & Thomas W. Graeber, 2023. "Complexity and Hyperbolic Discounting," CESifo Working Paper Series 10861, CESifo.
    5. Börsch-Supan, Axel & Bucher-Koenen, Tabea & Hurd, Michael D. & Rohwedder, Susann, 2023. "Saving regret and procrastination," Journal of Economic Psychology, Elsevier, vol. 94(C).
    6. Levy, Matthew R. & Tasoff, Joshua, 2017. "Exponential-growth bias and overconfidence," LSE Research Online Documents on Economics 68881, London School of Economics and Political Science, LSE Library.
    7. Callen, Michael & Blumenstock, Joshua & Ghani, Tarek, 2016. "Mobile-izing Savings with Automatic Contributions: Experimental Evidence on Present Bias and Default Effects in Afghanistan," CEPR Discussion Papers 11400, C.E.P.R. Discussion Papers.
    8. McGowan, Féidhlim & Lunn, Pete & Robertson, Deirdre, 2019. "Underestimation of money growth and pensions: Experimental investigations," Papers WP611, Economic and Social Research Institute (ESRI).
    9. Robert L. Clark & Robert G. Hammond & Christelle Khalaf, 2019. "Planning for Retirement? The Importance of Time Preferences," Journal of Labor Research, Springer, vol. 40(2), pages 127-150, June.
    10. Joshua Blumenstock & Michael Callen & Tarek Ghani, 2018. "Why Do Defaults Affect Behavior? Experimental Evidence from Afghanistan," American Economic Review, American Economic Association, vol. 108(10), pages 2868-2901, October.
    11. David Huffman & Raimond Maurer & Olivia S. Mitchell, 2016. "Time Discounting and Economic Decision-making among the Elderly," Working Papers wp347, University of Michigan, Michigan Retirement Research Center.
    12. Levy, Matthew R. & Tasoff, Joshua, 2017. "Exponential-growth bias and overconfidence," Journal of Economic Psychology, Elsevier, vol. 58(C), pages 1-14.
    13. Victor Stango & Joanne Yoong & Jonathan Zinman, 2017. "The Quest for Parsimony in Behavioral Economics: New Methods and Evidence on Three Fronts," NBER Working Papers 23057, National Bureau of Economic Research, Inc.
    14. Ritwik Banerjee & Priyama Majumdar, 2023. "Exponential growth bias in the prediction of COVID‐19 spread and economic expectation," Economica, London School of Economics and Political Science, vol. 90(358), pages 653-689, April.
    15. Königsheim, C. & Lukas, M. & Nöth, M., 2018. "Individual preferences and the exponential growth bias," Journal of Economic Behavior & Organization, Elsevier, vol. 145(C), pages 352-369.

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