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Including Risk in a Case Study of When to Start Social Security Benefits

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Conference

2021 ASEE Virtual Annual Conference Content Access

Location

Virtual Conference

Publication Date

July 26, 2021

Start Date

July 26, 2021

End Date

July 19, 2022

Conference Session

Engineering Economy Division Technical Session

Tagged Division

Engineering Economy

Page Count

11

Permanent URL

https://peer.asee.org/37314

Download Count

16

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Paper Authors

biography

Neal Lewis University of Nebraska, Lincoln

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NEAL A. LEWIS, CPEM, received his Ph.D. in engineering management in 2004 and B.S. in chemical engineering in 1974 from the University of Missouri–Rolla and his MBA in 2000 from the University of New Haven. He has over 25 years of industrial experience at Procter and Gamble, and Bayer. He is a full time faculty member of the online Master of Engineering Management program at the University of Nebraska - Lincoln. Previously, he taught at UMR, Marshall University, University of Bridgeport, University of New Haven, Fairfield University, and Oregon State University. He has over 100 publications and presentations, including 3 books, 2 best paper awards at conferences, the 2009 Grant award (TEE), and the 2005 Eschenbach award (EMJ). Neal is a Fellow of ASEM.

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biography

Ted Eschenbach University of Alaska Anchorage

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Dr, Ted Eschenbach, PE, is the principal of TGE Consulting, an emeritus professor at the University of Alaska Anchorage, and EMJ’s founding editor emeritus. He is a Fellow of ASEE, ASEM, and IISE. He has over 300 publications and presentations, including 21 editions of 4 engineering economy titles, 6 best paper awards at conferences, and the 2009 Grant award. In 2016 he received ASEE’s biannual National Engineering Economy Teaching Excellence Award. He earned his B.S. from Purdue in 1971, his M.S. in operations research in 1973 and his Ph.D. in IE in 1975 from Stanford University, and his MCE from UAA in 1999.

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Abstract

Case studies introduce students to real world analysis but searching out the data usually requires only reading the case. In contrast, choosing when to start collecting social security is real world—thus students can be required to search out data on social security and/or real people with financial, health, motivation, etc. details. The case statement can be as simple as: “Your grandparents or parents need advice.” The many details and possible situations allow flexibility to match assignments to student maturity and course time constraints.

Engineering economy and the time value of money are part of choosing when to start Social Security. Though benefits may begin in any given month, the exemplar choices are collecting reduced benefits as early as age 62, receiving a primary insurance amount (PIA) by waiting until full retirement age (currently 66, with increases beginning with those who born in 1955 or later), or delaying up to age 70 for enhanced payments.

In an introductory course, a possible case statement would be: “Obviously the interest rate and the predicted age at death are both uncertain. Analyze choices for a variety of interest rates and expected lives. Present results so they make sense to someone who understands the meaning of present worth and/or rate of return, but who cannot calculate them.”

Many recipients of social security do not understand probability nor the time value of money. Yet risk can still be part of their decision-making. While this may be qualitative rather than quantitative, identifying specific situations and conflicting objectives is part of real-world applications of engineering economy. This paper summarizes viewpoints of risk that may drive the choice of when to start benefits.

In advanced or demanding engineering economy courses mortality distributions can become part of the analysis. Mortality distributions can be supplied in the needed format of conditional probabilities, for example the P(dying at 83|alive at 66). Or students can be expected to convert mortality distributions to conditional distributions. Note that mortality distributions vary by gender and other differences. Or if students search out sources of mortality data, then credibility of different sources and consistency of results can be explored. Student searches for data may subdivide the population differently offering potential new viewpoints.

Mortality distribution data supports the paired metric of expected value and standard deviation of benefits. Like investments higher returns and lower risks are preferred. Results for a single individual shows that differences in expected NPVs between starting ages are small, but delaying benefits significantly increases risk. This contradicts the conventional wisdom that delaying benefits is better.

This case can be extended in masters or doctoral research into other defined benefit programs. It can also be extended to couples where there are two additional benefit types (spousal and survivor’s) and many different combinations of ages and earning histories.

Lewis, N., & Eschenbach, T. (2021, July), Including Risk in a Case Study of When to Start Social Security Benefits Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. https://peer.asee.org/37314

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