Hostname: page-component-cd9895bd7-gbm5v Total loading time: 0 Render date: 2024-12-23T23:12:01.307Z Has data issue: false hasContentIssue false
  • English
  • Français

How good are default investment policies in defined contribution pension plans?

Published online by Cambridge University Press:  13 July 2020

Daniel Duque ,
David P. Morton  and
Bernardo K. Pagnoncelli
Daniel Duque
Affiliation:
Department of Industrial Engineering & Management Sciences, Northwestern University, Evanston, IL, USA
David P. Morton
Affiliation:
Department of Industrial Engineering & Management Sciences, Northwestern University, Evanston, IL, USA
Bernardo K. Pagnoncelli*
Affiliation:
Department of Industrial Engineering & Management Sciences, Northwestern University, Evanston, IL, USA School of Business, Universidad Adolfo Ibáñez, Santiago, Chile
*
*Corresponding author. Email: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Defined contribution (DC) pension plans have been gaining ground in the last 10–20 years as the preferred system for many countries and other agencies, both private and public. The central question for a DC plan is how to invest in order to reach the participant's retirement goals. Given the financial illiteracy of the general population, it is common to offer a default policy for members who do not actively make investment choices. Using data from the Chilean system, we discuss an investment model with fixed contribution rates and compare the results with the existing default policy under multiple objectives. Our results indicate that the Chilean default policy has good overall performance, but specific closed-loop policies have a higher probability of achieving desired retirement goals and can reduce the expected shortfall at retirement.

Keywords

Closed-loop policiesdefined contributiondynamic programmingstochastic dominanceutility functions

JEL classification

H55: Social Security and Public Pensions D81: Criteria for Decision-Making under Risk and Uncertainty C61: Optimization Techniques • Programming Models • Dynamic Analysis
Type
Article
Information
Journal of Pension Economics & Finance , Volume 20 , Issue 2 , April 2021 , pp. 252 - 272
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Ang, A (2014) Asset Management: A Systematic Approach to Factor Investing. Oxford, England: Oxford University Press.CrossRefGoogle Scholar
Avallone, M (2018) Why target date funds dominate the 401(k) market. Available at https://www.forbes.com/sites/markavallone/2018/06/30/why-target-date-funds-dominate-the-401k-market/##3ced32b75868 (Accessed 29 May 2019).Google Scholar
Basu, A, Byrne, A and Drew, M (2011) Dynamic lifecycle strategies for target date retirement funds. The Journal of Portfolio Management 37, 83–96.CrossRefGoogle Scholar
Berstein, S, Fuentes, O and Torrealba, N (2011) La importancia de la opción por omisión en los sistemas de pensiones de cuentas individuales. Technical Report 44, Superintendencia de Pensiones.Google Scholar
Bick, B, Kraft, H and Munk, C (2013) Solving constrained consumption–investment problems by simulation of artificial market strategies. Management Science 59, 485–503.CrossRefGoogle Scholar
Biller, B and Nelson, BL (2003) Modeling and generating multivariate time-series input processes using a vector autoregressive technique. ACM Transactions on Modeling and Computer Simulation 13, 221–237.CrossRefGoogle Scholar
Blomvall, J and Shapiro, A (2006) Solving multistage asset investment problems by the sample average approximation method. Mathematical Programming 108, 571–595.CrossRefGoogle Scholar
Cario, MC and Nelson, BL (1996) Autoregressive to anything: time series input processes for simulation. Operations Research Letters 19, 51–58.CrossRefGoogle Scholar
Cario, MC and Nelson, BL (1997) Modeling and Generating Random Vectors with Arbitrary Marginal Distributions and Correlation Matrix. Technical report, Northwestern University.Google Scholar
Cvitanic, J and Karatzas, I (1992) Convex duality in constrained portfolio optimization. The Annals of Applied Probability 2, 767–818.CrossRefGoogle Scholar
Dentecheva, D and Ruszczyński, A (2006) Portfolio optimization with stochastic dominance constraints. Journal of Banking & Finance 30, 433–451.CrossRefGoogle Scholar
Estrada, J (2014) The glidepath illusion: an international perspective. The Journal of Portfolio Management 40, 52–64.CrossRefGoogle Scholar
Horneff, V, Maurer, R and Mitchel, OS (2020) Putting the pension back in 401(k) retirement plans: Optimal versus default deferred longevity income annuities. Journal of Banking & Finance. https://doi.org/10.1016/j.jbankfin.2020.105783CrossRefGoogle Scholar
Kahneman, D and Tversky, A (2013) Prospect theory: an analysis of decision under risk. In MacLean, LC and Ziemba, WT (eds), Handbook of the Fundamentals of Financial Decision Making, chapter 6. World Scientific, pp. 99–127. doi: 10.1142/9789814417358_0006.CrossRefGoogle Scholar
Laster, D, Vrdoljak, N and Suri, A (2016) Strategies for managing retirement risks. The Journal of Retirement 4, 11–18.CrossRefGoogle Scholar
Mehra, R and Prescott, EC (1988) The equity risk premium: a solution? Journal of Monetary Economics 22, 133–136.CrossRefGoogle Scholar
Merton, RC (1969) Lifetime portfolio selection under uncertainty: the continuous-time case. The Review of Economics and Statistics 51, 247–257.CrossRefGoogle Scholar
Merton, RC (1975) Stochastic Optimization Models in Finance. Journal of Economic Theory 3, 373–413. https://doi.org/10.1016/0022-0531(71)90038-XCrossRefGoogle Scholar
Michaelides, AG and Gomes, FJ (2005) Optimal life cycle asset allocation: understanding the empirical evidence. The Journal of Finance 60, 869–904.Google Scholar
Mladina, P (2016) Optimal lifetime asset allocation with goals-based, lifecycle glide paths. The Journal of Wealth Management 19, 10–22.CrossRefGoogle Scholar
OECD (2019) Pension spending (indicator). doi:10.1787/a041f4ef-en (Accessed 28 January 2019).CrossRefGoogle Scholar
Rabin, M (2013) Risk aversion and expected-utility theory: a calibration theorem. In MacLean LC and Ziemba WT (eds), Handbook of the Fundamentals of Financial Decision Making: Part I. New Jersey, United States: World Scientific, pp. 241–252.CrossRefGoogle Scholar
Rodríguez-Vives, M and Kezbere, L (2019) Social spending, a euro area cross-country comparison. Economic Bulletin Articles 5.Google Scholar
Rupert, J (2016) Workers need to put 15% of income into pension, report says. Available at https://www.theguardian.com/money/2016/mar/02/pensions-retirement-savings-15-per-cent-workers-income-needed-review-finds (Accessed 29 January 2019).Google Scholar
Samuelson, PA (1975) Lifetime portfolio selection by dynamic stochastic programming. In Stochastic Optimization Models in Finance. Cambridge, United States: Academic Press, pp. 517–524.CrossRefGoogle Scholar
Schechter, L (2007) Risk aversion and expected-utility theory: a calibration exercise. Journal of Risk and Uncertainty 35, 67–76.CrossRefGoogle Scholar
Smith, G (2011) Considering investment risk in a DC pension plan. Pensions: An International Journal 16, 33–38.CrossRefGoogle Scholar
Viceira, LM (2001) Optimal portfolio choice for long-horizon investors with nontradable labor income. The Journal of Finance 56, 433–470.CrossRefGoogle Scholar
Viceira, LM (2009) Life-cycle funds. In Lusardi, A (ed.), Overcoming the Saving Slump: How to Increase the Effectiveness of Financial Education and Saving Programs. Chicago, United States: The University of Chicago Press, pp. 140–177.CrossRefGoogle Scholar
von Neumann, J and Morgenstern, O (1953) Theory of Games and Economic Behavior. Princeton, United States: Princeton University Press.Google Scholar
Wasik, J (2015) Power boost your 401(k). Available at https://www.forbes.com/sites/johnwasik/2015/01/12/power-boost-your-401k/\#4f9a702fb49f (Accessed 32 January 2019).Google Scholar
Yoon, Y (2010) Glide path and dynamic asset allocation of target date funds. Journal of Asset Management 11, 346–360.CrossRefGoogle Scholar