JEFMS Journal

ABSTRACT:

There exists a semi-hidden and little researched connection between planning and software programming that supports that planning, as well as little research into the connection to planning and programming related to the paradigm that exists underlying those connections. This paper discusses the paradigms of retirement income planning from past, to present, and observations to advance the planning profession and research into the future. The profession, researchers, and software programmers have transitioned from the first to the second paradigm and has yet to visualize the third paradigm to make that paradigm shift. Retirees continue to age year by year, but each cohort has a different distribution period due to the ever-decreasing time remaining in longevity tables as they age. There is not a universal retiree (as implied by current research using a single distribution time period with a single allocation; or at best two or three time periods and allocations). Instead, there exist many retirees with many different allocations and many remaining distributions time periods. Thus, one rule of thumb approach e.g., the 4% rule (or any drawdown rate) with inflation applied thereafter, or one Monte Carlo simulation, can't apply to all allocations plus all time periods at the same time because of those different ages with correlating shorter or longer remaining longevity for income drawdown. Therefore, research to date has been narrowly focused, which unintentionally leads to a narrowly applied approach for practitioners as well. Frank 2022a introduced how to model retiree drawdowns through a method that applies to any retiree at any age and subsequently over each retiree's remaining lifetime by cohort ages.

Therefore, researchers need to evaluate all the different time frames as well as many different efficient allocations, optimized along an efficient frontier range (Statman, Clark, 2013) to derive conclusions that can apply to any retiree at any age, not just an early-stage retiree (long term drawdown periods), i.e., a narrow set of early-stage cohorts while ignoring a large majority of others in many later stages of retirement (shorter term drawdown periods). The current paradigm ignores research and modeling later-stage retiree spending as well as the transition from any earlier stage into any later stage while aging. The author is a practitioner nearing nearly three decades specializing in research and application of drawdown of portfolios for supplemental retirement income, clinically with many different retirees of many different ages all at the same moment in time. Time, the transition between time periods, and control variables are key elements coming from the author's physics background. The author also has numerous research papers published in the Journal of Financial Planning (Frank, et. al., 2011, 2012a, 2012b, 2016, and numerous other published papers leading to the thoughts in these referenced papers leading to thoughts below). The author suggests integrating many different disciplines is important to advancing retirement income planning into more focused modeling, rather than today’s single simulation approach within a narrowly applied functional or career-based discipline approach.

KEYWORDS:

Financial Markets, Probabilities, Statistical Methods, Financial Services, Personal Economics, Retirement Income, Longevity, Age Based Modeling, Fintech, Cross-Disciplinary Business Management, Multi-Disciplinary Organization Management, Interdisciplinary Organization Management, Organizational Management
JEL Classification: C1, C29, C39, C5, C6, G4, G29, G40, M10, M15, 033, Y80

REFERENCES:

1) Bengen, William P. 1994. “Determining Withdrawal Rates Using Historical Data.” Journal of Financial Planning October 1994. (Reprinted March 2004)

2) Frank, Larry R. “Wealth Odyssey: The Essential Road Map For Your Financial Journey Where Is It You Are Really Trying To Go With Money?” Bloomington, IN. iUniverse. 2005

3) Bengen, William P. “Conserving Client Portfolios During Retirement.” Denver, CO. FPA Press (Financial Planning Association). 2006

4) Frank, Larry R., John B. Mitchell, and David M. Blanchett, 2011. “Probability-of-Failure-Based Decision Rules to Manage Sequence Risk in Retirement.” Journal of Financial Planning 24 (11): 44–53. Working paper: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1849868

5) Frank, Larry R., John B. Mitchell, and David M. Blanchett. 2012. (2012a). “An Age-Based, Three-Dimensional Distribution Model Incorporating Sequence and Longevity Risks.” Journal of Financial Planning 25 (3): 52–60. Working paper: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1849983

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