Abstract
Ensuring retirement income security is a priority for individuals, employers, and policymakers. To achieve this, employers and policymakers sponsor and subsidize retirement saving plans and provide educational interventions. The effectiveness of these tools will depend on individuals’ interest and willingness to engage in planning and preparing for retirement. Using merged administrative and survey data for public sector workers in North Carolina, we find that individuals who more heavily discount the future are less likely to plan and save for retirement. Further, retirement planning behavior is measured both subjectively and objectively, and time preferences have an association with subjectively measured retirement planning but not with objectively measured retirement planning. Finally, individuals’ retirement timing is associated with time preferences but only among individuals with a retirement plan. In total, our results highlight the important role of time preferences in determining retirement planning and preparedness.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Notes
See Bureau of Labor Statistics, Current Employment Statistics, http://www.bls.gov/web/empsit/ceseeb1b.htm, [accessed October 2, 2014].
We present a comparison of our sample of public workers and private sector workers in the Health and Retirement Study (HRS) in Online Appendix C. We confirm that the public sector workers we study are more risk averse and more patient than the private sector workers in the HRS.
As described in more detail in the Online Appendix, these data were gathered as part of a larger project titled “Challenges to Retirement Readiness in the North Carolina Public Sector Workforce.” More details on the full data and project can be found at: https://sites.google.com/a/ncsu.edu/retirementstudy/
Subjective measures have several disadvantages (e.g., social desirability bias and recollection errors), while objective measures have their own disadvantages (e.g., administrative data do not typically provide measures of all relevant outcomes). See the discussion in Section III.
The major exception to automatic inclusion in TSERS is that university faculty have the option of enrolling in TSERS or participating in a defined contribution plan managed by the University of North Carolina system. Faculty electing to be in TSERS are included in our sample; however, faculty who selected the Optional Retirement Plan (ORP) are not included in the survey sample.
Other details of the two plans can be found at the systems websites:
https://www.nctreasurer.com/ret/Benefits%20Handbooks/TSERShandbook.pdf
https://www.nctreasurer.com/ret/Benefits%20Handbooks/LGERShandbook.pdf.
Table A.2 explains in detail how years until eligible for retirement benefits is calculated.
Online Appendix A describes the data and sample in more detail. As described there, we conducted both an email and postal mail survey. All respondents were given the option to enter a drawing for two iPad tablets ($500 value) as an incentive for survey completion. Our response rate was approximately 18%.
Public school employees are also eligible to contribute to locally managed 403(b) and 457 plans. We do not have data on contributions to these plans. The extent of these plans and the participant rates by school employees in the locally managed plans compared to the state managed 401(k) and 457 plans is discussed in Clark et al. (2016) and Clark et al. (2018).
We describe sensitivity tests using alternative parameterizations further below and in the Online Appendix. Our preferred definition of subjective planning (have a retirement plan) has a stronger association with preferences than a more inclusive definition.
Among our married sample with an already retired spouse, 16% plan to retire within one year.
In fact, staff at RSD indicate that the member services staff at RSD and the employers’ human resources staff regularly refer workers to the ORBIT Self-Service Estimator to obtain estimated benefit information rather than conducting the calculation on behalf of the employee (personal correspondence with RSD staff).
Our 12 month window covers the period from August 19, 2013 to August 18, 2014.
Results using alternative timeframes are described in footnote 21 and Online Appendix Table D2.
Online Appendix B provides the wording of the question, which asks about any “retirement savings plan with my current public employer (e.g., 401(k), 403(b), 457(b) plan).” We find that about 13% of the population incorrectly self-reports participating but are not participating according to the administrative records. Thus, we believe our survey measure may be overstating participation for all our workers.
See Online Appendix C for a detailed description of the questions and responses. Lönnqvist et al. (2015) find that unincentivized survey questions outperform incentivized tasks in the measurement of preference parameters, because unincentivized survey questions are more highly correlated with actual decisions. This supports our categorization of individuals’ time preferences using unincentivized survey questions.
In results not shown, 19.6% chose the risky job (less risk averse) and 12.9% reported that they did not know which job they would choose. Online Appendix Table C3 compares responses to the HRS for those that choose either the first or second job and did not select “don’t know.”
We classify the employees in six agency categories (city, county, public school, general government, Department of Transportation, and other) and nine job categories (safety/rescue officers, executives/management, education professionals, educational support, health care professionals, professionals, trades and technical, social service professionals, and university). None of the estimated coefficients on agency categories are statistically significant. Of the job categories, only the coefficient for social service professionals is significant, where social service professionals are more likely to plan.
Similarly, Anderson and Mellor (2009) find that risk preferences elicited from a question involving windfall gains has more predictive power than those from a question involving anticipated gains.
The first email survey response was April 1st, 2014 and the last email survey response was June 17th, 2014. Therefore, we observe retirements approximately two years after completion of the survey.
See Table 2 for summary statistics of planned retirement age. Only 6% of respondents did not report a planned retirement age. The sample also excludes eleven deceased individuals.
The survey asked respondents their anticipated retirement age, not date. This is commonly done in surveys (e.g., Van Schieet al. 2015). Using the administrative data, we calculate the age of respondents at time of survey. We calculate the difference between self-reported planned retirement age and their imputed age at the time of the survey.
References
Ameriks J, Caplin A, Leahy J (2003) Wealth accumulation and the propensity to plan. Q J Econ 118(3):1007–1047
Anderson LR, Mellor JM (2009) Are risk preferences stable? comparing an experimental measure with a validated survey-based measure. J Risk Uncertain 39(2):137–160
Ashraf N, Camerer CF, Loewenstein G (2005) Adam Smith, Behavioral Economist. J Econ Perspect 19(3):131–145
Banks J, Blundell R, Casanova Rivas M (2010) The dynamics of retirement behavior in couples: Reduced-form evidence from England and the US. Working Paper, UCLA
Barsky R, Juster F (1997) Preference parameters and behavioral heterogeneity: An experimental approach in the health and retirement study. Q J Econ 112(2):537–579
Bellante DON, Link AN (1981) Are Public Sector Workers More Risk Averse Than Private Sector Workers ? Ind Labor Relat Rev 34(3):408–412
Binswanger J, Carman KG (2012) How real people make long-term decisions: The case of retirement preparation. J Econ Behav Organ 81(1):39–60
Bradford D, Courtemanche C, Heutel G, McAlvanah P, Ruhm C (2017) Time preferences and consumer behavior. J Risk Uncertain 55(2–3):119–145
Brown J, Previtero A (2014) Procrastination, present-biased preferences, and financial behaviors. Working Paper
Brown JR, Farrell AM, Weisbenner SJ (2015) Decision-making approaches and the propensity to default: evidence and implications. Journal of Financial Economics, Forthcoming
Clark RL, Hanson E, Morrill MS, Pathak A (2016) Supplemental Plan Offerings and Retirement Saving Choices: an Analysis of North Carolina School Districts. Journal of Pension Economics and Finance 15(3):333–355
Clark R, Pathak A, Pelletier D (December 2018) Supplemental Retirement Savings Plans in the Public Sector: Participation and Contribution Decisions by School Personnel. J Lab Res 39(4):383–404
Collins JM, Urban C (2016) The Role of Information on Retirement Planning: Evidence from a Field Study. Econ Inq 54(4):1860–1872
Finke MS, Huston SJ (2013) Time preference and the importance of saving for retirement. J Econ Behav Organ 89:23–34
Gustman AL, Steinmeier TL (2000) Retirement in Dual-Career Families: A Structural Model. J Labor Econ 18(3):503–545
Lönnqvist JE, Verkasalo M, Walkowitz G, Wichardt PC (2015) Measuring individual risk attitudes in the lab: Task or ask? An empirical comparison. J Econ Behav Organ 119:254–266
Lusardi A, Mitchell OS (2007) Baby Boomer retirement security: The roles of planning, financial literacy, and housing wealth. J Monet Econ 54(1):205–224
Lusardi A, Mitchell OS (2014) The Economic Importance of Financial Literacy : Theory and Evidence. J Econ Lit 52(1):5–44
Michaud P (2003) Joint labour supply dynamics of older couples. IZA Discussion Paper 832
Petkoska J, Earl JK (2009) Understanding the influence of demographic and psychological variables on retirement planning. Psychol Aging 24(1):245
Rosnick D, Baker D (2014) The Wealth of Households: An Analysis of the 2013 Survey of Consumer Finances
Thaler RH (1990) Anomalies: Saving, Fungibility, and Mental Accounts. J Econ Perspect 4(1):193–205
TIAA-CREF (1994) Looking ahead to retirement. Library Series No.3, New York
Van Rooij MC, Lusardi A, Alessie RJ (2011) Financial literacy and retirement planning in the Netherlands. J Econ Psychol 32(4):593–608
Van Schie RJ, Dellaert BG, Donkers B (2015) Promoting later planned retirement: Construal level intervention impact reverses with age. J Econ Psychol 50:124–131
Acknowledgements
The authors thank Melinda Sandler Morrill, whose contributions at an earlier stage of this project are greatly appreciated. The authors gratefully acknowledge funding from the Sloan Foundation, Grant Number 2013-10-20. The authors would like to thank Bryan Allard, Emma Hanson, and Aditi Pathak for research assistance. The research reported herein is part of an on-going project that is being conducted in partnership with the North Carolina Retirement Systems Division. The authors thank Janet Cowell, former North Carolina State Treasurer, Steven C. Toole, Director of the Retirement Systems Division, Mary Buonfiglio, Deputy Director of Supplemental Retirement Plans, and Sam Watts, Policy Director of the Retirement Systems Division for their help and support. An earlier draft of this paper was prepared for the 2014 SIEPR Conference on Working Longer and Retirement; the authors thank seminar participants for helpful comments. The authors also thank the editor, three referees, Olivia Mitchell, and John Pencavel for helpful suggestions. The opinions and conclusions expressed herein are solely those of the authors and do not represent the opinions or policies of the North Carolina Retirement System or any other institution with which the authors are affiliated.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of Interest
The authors declare that they have no conflict of interest.
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Electronic supplementary material
ESM 1
(DOCX 69 kb)
Rights and permissions
About this article
Cite this article
Clark, R.L., Hammond, R.G. & Khalaf, C. Planning for Retirement? The Importance of Time Preferences. J Labor Res 40, 127–150 (2019). https://doi.org/10.1007/s12122-019-09287-y
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12122-019-09287-y