IDEAS home Printed from https://ideas.repec.org/p/cir/cirwor/2018s-22.html
   My bibliography  Save this paper

Decision Rules for Precautionary and Retirement Savings

Author

Listed:
  • Dina Tasneem
  • Jim Engle-Warnick

Abstract

We report results from an experiment that compares precautionary savings behavior with retirement savings behavior. We ?nd that more than 30% of precautionary savings behavior can be categorized as optimal or near optimal, while virtually all of this behavior disappears in favor of simple decision rules that specify constant consumption in each period when retirement savings is added as a motive. We discuss the the costs and bene?ts of these rules, which make a complex decision-making environment manageable. Our experiment is the ?rst to identify how decision-making changes when agents are required to save for retirement.

Suggested Citation

  • Dina Tasneem & Jim Engle-Warnick, 2018. "Decision Rules for Precautionary and Retirement Savings," CIRANO Working Papers 2018s-22, CIRANO.
    • Handle: RePEc:cir:cirwor:2018s-22
    as

    Download full text from publisher

    File URL: https://cirano.qc.ca/files/publications/2018s-22.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. T. Ballinger & Eric Hudson & Leonie Karkoviata & Nathaniel Wilcox, 2011. "Saving behavior and cognitive abilities," Experimental Economics, Springer;Economic Science Association, vol. 14(3), pages 349-374, September.
    2. Houser, Daniel & Winter, Joachim, 2004. "How Do Behavioral Assumptions Affect Structural Inference? Evidence from a Laboratory Experiment," Journal of Business & Economic Statistics, American Statistical Association, vol. 22(1), pages 64-79, January.
    3. John Y. Campbell, 2016. "Restoring Rational Choice: The Challenge of Consumer Financial Regulation," American Economic Review, American Economic Association, vol. 106(5), pages 1-30, May.
    4. Daniel Houser & Michael Keane & Kevin McCabe, 2004. "Behavior in a Dynamic Decision Problem: An Analysis of Experimental Evidence Using a Bayesian Type Classification Algorithm," Econometrica, Econometric Society, vol. 72(3), pages 781-822, May.
    5. Joachim K. Winter & Kathrin Schlafmann & Ralf Rodepeter, 2012. "Rules of Thumb in Life‐cycle Saving Decisions," Economic Journal, Royal Economic Society, vol. 122(560), pages 479-501, May.
    6. David B. Gross & Nicholas S. Souleles, 2002. "Do Liquidity Constraints and Interest Rates Matter for Consumer Behavior? Evidence from Credit Card Data," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 117(1), pages 149-185.
    7. James J. Choi & David Laibson & Brigitte C. Madrian, 2011. "$100 Bills on the Sidewalk: Suboptimal Investment in 401(k) Plans," The Review of Economics and Statistics, MIT Press, vol. 93(3), pages 748-763, August.
    8. Lusardi, Annamaria & Mitchell, Olivia S., 2007. "Baby Boomer retirement security: The roles of planning, financial literacy, and housing wealth," Journal of Monetary Economics, Elsevier, vol. 54(1), pages 205-224, January.
    9. Enrica Carbone & John D. Hey, 2004. "The effect of unemployment on consumption: an experimental analysis," Economic Journal, Royal Economic Society, vol. 114(497), pages 660-683, July.
    10. Kenneth Matheny & Charles Noussair, 2000. "An experimental study of decisions in dynamic optimization problems," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 15(2), pages 389-419.
    11. Enrica Carbone, 2006. "Understanding intertemporal choices," Applied Economics, Taylor & Francis Journals, vol. 38(8), pages 889-898.
    12. John Y. Campbell & N. Gregory Mankiw, 1989. "Consumption, Income, and Interest Rates: Reinterpreting the Time Series Evidence," NBER Chapters, in: NBER Macroeconomics Annual 1989, Volume 4, pages 185-246, National Bureau of Economic Research, Inc.
    13. Carbone, Enrica & Duffy, John, 2014. "Lifecycle consumption plans, social learning and external habits: Experimental evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 106(C), pages 413-427.
    14. Enrica Carbone, 2005. "Demographics and Behaviour," Experimental Economics, Springer;Economic Science Association, vol. 8(3), pages 217-232, September.
    15. T. Parker Ballinger & Michael G. Palumbo & Nathaniel T. Wilcox, 2003. "Precautionary saving and social learning across generations: an experiment," Economic Journal, Royal Economic Society, vol. 113(490), pages 920-947, October.
    16. Feltovich, Nick & Ejebu, Ourega-Zoé, 2014. "Do positional goods inhibit saving? Evidence from a life-cycle experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PB), pages 440-454.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Duffy, John & Li, Yue, 2019. "Lifecycle consumption under different income profiles: Evidence and theory," Journal of Economic Dynamics and Control, Elsevier, vol. 104(C), pages 74-94.
    2. Dina Tasneem & Marine de Montaignac & Jim Engle-Warnick & Audrey Azerot, 2018. "A Laboratory Study of Nudge with Retirement Savings," CIRANO Working Papers 2018s-23, CIRANO.
    3. Miller, Logan & Rholes, Ryan, 2023. "Joint vs. Individual performance in a dynamic choice problem," Journal of Economic Behavior & Organization, Elsevier, vol. 212(C), pages 897-934.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dina Tasneem & Audrey Azerot & Marine de Montaignac & Jim Engle-Warnick, 2018. "A Laboratory Study of the E?ect of Financial Literacy Training on Retirement Savings," CIRANO Working Papers 2018s-24, CIRANO.
    2. Bachmann, Kremena & Lot, Andre & Xu, Xiaogeng & Hens, Thorsten, 2023. "Experimental Research on Retirement Decision-Making: Evidence from Replications," Journal of Banking & Finance, Elsevier, vol. 152(C).
    3. Duffy, John & Li, Yue, 2019. "Lifecycle consumption under different income profiles: Evidence and theory," Journal of Economic Dynamics and Control, Elsevier, vol. 104(C), pages 74-94.
    4. Miller, Logan & Rholes, Ryan, 2023. "Joint vs. Individual performance in a dynamic choice problem," Journal of Economic Behavior & Organization, Elsevier, vol. 212(C), pages 897-934.
    5. Thomas Meissner, 2016. "Intertemporal consumption and debt aversion: an experimental study," Experimental Economics, Springer;Economic Science Association, vol. 19(2), pages 281-298, June.
    6. John Duffy, 2022. "Why macroeconomics needs experimental evidence," The Japanese Economic Review, Springer, vol. 73(1), pages 5-29, January.
    7. Enrica Carbone & Konstantinos Georgalos & Gerardo Infante, 2019. "Individual vs. group decision-making: an experiment on dynamic choice under risk and ambiguity," Theory and Decision, Springer, vol. 87(1), pages 87-122, July.
    8. Carbone, Enrica & Duffy, John, 2014. "Lifecycle consumption plans, social learning and external habits: Experimental evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 106(C), pages 413-427.
    9. John Duffy & Enrica Carbone, 2013. "Lifecycle Consumption Plans, Social Learning and External Habits: Experimental Evidence," Working Paper 513, Department of Economics, University of Pittsburgh, revised Sep 2013.
    10. Dina Tasneem & Marine de Montaignac & Jim Engle-Warnick & Audrey Azerot, 2018. "A Laboratory Study of Nudge with Retirement Savings," CIRANO Working Papers 2018s-23, CIRANO.
    11. Lu, Kelin, 2022. "Overreaction to capital taxation in saving decisions," Journal of Economic Dynamics and Control, Elsevier, vol. 144(C).
    12. John Duffy & Yue Li, 2016. "Lifecycle Consumption Under Different Income Profiles: Experimental Evidence," Working Papers 161702, University of California-Irvine, Department of Economics.
    13. Carbone, Enrica & Infante, Gerardo, 2015. "Are groups better planners than individuals? An experimental analysis," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 57(C), pages 112-119.
    14. Koehler, Derek J. & Langstaff, Jesse & Liu, Wu-Qi, 2015. "A simulated financial savings task for studying consumption and retirement decision making," Journal of Economic Psychology, Elsevier, vol. 46(C), pages 89-97.
    15. Alexander L. Brown & Zhikang Eric Chua & Colin F. Camerer, 2009. "Learning and Visceral Temptation in Dynamic Saving Experiments," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 124(1), pages 197-231.
    16. Geiger, Martin & Luhan, Wolfgang J. & Scharler, Johann, 2016. "When do fiscal consolidations lead to consumption booms? Lessons from a laboratory experiment," Journal of Economic Dynamics and Control, Elsevier, vol. 69(C), pages 1-20.
    17. Luhan, Wolfgang J. & Scharler, Johann, 2013. "Monetary Policy, Inflation Illusion and the Taylor Principle – An Experimental Study," Ruhr Economic Papers 402, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    18. Keys, Benjamin J. & Wang, Jialan, 2019. "Minimum payments and debt paydown in consumer credit cards," Journal of Financial Economics, Elsevier, vol. 131(3), pages 528-548.
    19. Enrica Carbone, 2006. "Understanding intertemporal choices," Applied Economics, Taylor & Francis Journals, vol. 38(8), pages 889-898.
    20. Halim, Edward & Riyanto, Yohanes E. & Roy, Nilanjan, 2022. "Sharing idiosyncratic risk even though prices are “wrong”," Journal of Economic Theory, Elsevier, vol. 200(C).

    More about this item

    Keywords

    Precautionary Savings; Retirement Savings; Dynamic Optimization; Decision Heuristics;
    All these keywords.

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cir:cirwor:2018s-22. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Webmaster (email available below). General contact details of provider: https://edirc.repec.org/data/ciranca.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.