Retirement Spending and Biological Age

34 Pages Posted: 16 Feb 2017

See all articles by Huang Huaxiong

Huang Huaxiong

York University; York University - Department of Mathematics and Statistics

Moshe A. Milevsky

York University - Schulich School of Business

T. S. Salisbury

York University

Date Written: February 15, 2017

Abstract

We solve a retirement lifecycle model in which the consumer's age does not move in lockstep with calendar time. Instead, biological age increases at a stochastic non-linear rate in chronological age, which one can think of as working with a clock that occasionally moves backwards in time. Our paper is inspired by the growing body of medical literature that has identified biomarkers of aging which -- practically speaking -- offer better estimates of expected remaining lifetime and future mortality rates. It isn't farfetched to argue that in the not-too-distant future of wearable technology, personal age will be more closely associated with biological time vs. calendar age or time. Thus, after introducing our stochastic mortality model we derive optimal consumption rates in a classic Yaari (1965) framework adjusted to our proper clock and time. In addition to the normative implications of having access to biological age, our positive objective is to partially explain the cross-sectional heterogeneity in retirement spending rates at any given chronological age. In sum, we argue that biological age is not a sufficient statistic for making economic decisions and you need information about both your ages to behave rationally.

Keywords: Wealth Management, Retirement Planning, Insurance, Annuities, Pensions, Longevity, Aging and Demographics

JEL Classification: G11, B16, H31

Suggested Citation

Huaxiong, Huang and Huaxiong, Huang and Milevsky, Moshe Arye and Salisbury, Thomas S., Retirement Spending and Biological Age (February 15, 2017). Available at SSRN: https://ssrn.com/abstract=2918055 or http://dx.doi.org/10.2139/ssrn.2918055

Huang Huaxiong

York University - Department of Mathematics and Statistics ( email )

4700 Keele Street
Toronto, Ontario M3J 1P3
United States

York University ( email )

4700 Keele Street
Toronto, Ontario M3J 1P3
Canada

Moshe Arye Milevsky (Contact Author)

York University - Schulich School of Business ( email )

4700 Keele Street
Toronto, Ontario M3J 1P3
Canada

Thomas S. Salisbury

York University ( email )

4700 Keele Street
Toronto, Ontario M3J 1P3
Canada

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