How Do Americans Budget for Retirement? Behavioral Biases and the Role of Financial Literacy in Income Sustainability

Authors

  • Oluwasegun Makinde Canadian Institute of Financial Planning CIFP

DOI:

https://doi.org/10.47672/ajf.2685

Keywords:

Retirement Planning, Behavioral Economics, Financial Literacy, Income Sustainability, Savings Behavior

Abstract

Purpose: This report discusses the planning Americans undertake regarding expenditure during retirement and examines the role of biases in behavior to affect long-run planning. The study investigates how financial literacy interacts with retirement income sustainability and determines factors that affect the saving conduct within various age and gender demographics. The research further evaluates whether planning interventions affect participation and succeeds or fails as intended, while recommendations are forwarded to policy makers and financial education stakeholders.

Materials and Methods: This research employs a mixed-methods approach with quantitative and qualitative data. A national survey of 2,450 Americans aged 25-70 was conducted to gather data on retirement planning behavior, money knowledge, and decision-making processes. Qualitative interviews with 75 financial planners supplemented survey information. Statistical testing employed multiple regression models to analyze correlations between money knowledge, behavioral mistakes, and retirement outcomes. Longitudinal data from the Health and Retirement Study (HRS) gave further insight into the way planning behaviors interface with retirement satisfaction and financial health.

Findings: The research discloses that nearly 68% of Americans lowball their retirement requirements, with especially alarming gaps for middle-income families. Present bias and optimism bias substantially contribute to saving rates, cutting average retirement savings by 4.2% per annum. Financial literacy scores are strongly associated with retirement planning adequacy (r=0.74), but this effect is moderated by psychological traits such as risk tolerance and loss aversion. Automated savings plans raised average retirement savings contributions by 7.3%, with the most powerful impacts within lower financial literacy cohorts. Gender differences in retirement readiness continue, with women demonstrating 23% lower average retirement savings in spite of greater financial literacy scores among younger cohorts.

Unique Contribution to Theory, Practice and Policy: This study contributes to behavioral finance theory by demonstrating how cognitive biases interact with conventional economic factors in retirement planning. Practitioner implications suggest that financial education aimed at particular behavioral biases is more effective than general financial literacy initiatives. Public policy implications include implementing national financial education initiatives with a focus on behavioral determinants of financial choice, expanding automatic enrollment in retirement schemes, and developing targeted intervention programs for vulnerable demographic groups.

Downloads

Download data is not yet available.

References

Benartzi, S., & Thaler, R. H. (2013). Behavioral economics and the retirement savings crisis. Science, 339(6124), 1152-1153. https://doi.org/10.1126/science.1231320

Federal Reserve Board. (2022). Survey of Consumer Finances. Washington, DC: Board of Governors of the Federal Reserve System. https://doi.org/10.17016/scf.2022

Fernandes, D., Lynch Jr, J. G., & Netemeyer, R. G. (2014). Financial literacy, financial education, and downstream financial behaviors. Management Science, 60(8), 1861-1883. https://doi.org/10.1287/mnsc.2013.1849

FINRA Investor Education Foundation. (2023). National Financial Capability Study. Washington, DC: FINRA. https://doi.org/10.2139/ssrn.4316533

Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263-291. https://doi.org/10.2307/1914185

Lusardi, A., & Mitchell, O. S. (2014). The economic importance of financial literacy: Theory and evidence. Journal of Economic Literature, 52(1), 5-44. https://doi.org/10.1257/jel.52.1.5

Modigliani, F., & Brumberg, R. (1954). Utility analysis and the consumption function: An interpretation of cross-section data. In K. Kurihara (Ed.), Post-Keynesian Economics (pp. 388-436). Rutgers University Press. https://doi.org/10.4324/9781315016849-22

Remi Dairo, Affective Productivity (July 2023) International Journal of Productivity Science (IJPS) https://wcps.info/wp-content/uploads/2023/07/IJPS-VOLUME-1-ISSUE-2-JULY-2023.pdf

Shefrin, H. M., & Thaler, R. H. (1988). The behavioral life-cycle hypothesis. Economic Inquiry, 26(4), 609-643. https://doi.org/10.1111/j.1465-7295.1988.tb01520.x

Thaler, R. H. (1994). Psychology and savings policies. The American Economic Review, 84(2), 186-192. https://doi.org/10.1257/aer.84.2.186

U.S. Census Bureau. (2021). 2020 Population Estimates and Projections. Washington, DC: U.S. Department of Commerce. https://doi.org/10.4135/9781412963909.n484

Willis, L. E. (2011). The financial education fallacy. American Economic Review, 101(3), 429-434. https://doi.org/10.1257/aer.101.3.429

Published

2025-04-29

How to Cite

Makinde, O. (2025). How Do Americans Budget for Retirement? Behavioral Biases and the Role of Financial Literacy in Income Sustainability. American Journal of Finance, 11(1), 54–67. https://doi.org/10.47672/ajf.2685

Issue

Section

Articles