Economic Damages: Work-life Expectancy v. Retirement Age
Adding years onto the end of earnings loss calculations

The only supporting rationale from the forensic for this assumption was the fact that the plaintiff had older siblings who continued to be active in the labor force into their 70s. The statistical work-life tables detailed an additional six years of active work for the man. The result from the economist’s assumption was the 100% continuous employment from the age of 60 to 75 in “Medium to Heavy” categories. The economist would have you believe that the plaintiff would never be injured, his health would never deteriorate, and he would never transition between jobs or projects. The impact is an overestimate of future earnings with nine years added to the end of the calculation.

 

The disagreement can be further supported with the point that the majority of the work-life sample (labor data) consists of sedentary and light category workers. While the plaintiff would continue working in construction in the medium and heavy categories, I would argue that the statistical work-life expectancy presented is a best-case scenario for the plaintiff considering his job’s physical category, his age, and his level of education. (Note: There are no published statistical work-life tables for construction workers.)

 

These are some examples of the persuasive case against the use of the crystal ball by the economist when attempting to guess plaintiff’s retirement age. In the end, you can be certain that the foundation for this speculation is the resulting additional years of annual earnings for the plaintiff.

 

A work-life expectancy is a conceptual contradiction from the idea of guessing the plaintiff’s future retirement age at 65 or 67. Selecting a retirement age of 65 and subtracting the plaintiff’s age does not garner a work life expectancy. In truth, my 16-year-old son could throw darts at future retirement ages and then perform a back-of-the-envelope calculation and call it a “work-life expectancy”. Not only does this methodology invite speculation, but it also assumes 100% full-time employment for the remainder of the plaintiff’s work-life duration. This approach does not consider any of the factors (voluntary and involuntary) that lead one to leave the labor force.

 

The work-life expectancy is the average number of years that a person will spend either working or actively looking for work during the remainder of his or her life. Work-life tables were developed over time to allow for the probability of traditional factors that might cause someone to leave the labor market temporarily (i.e. change in job locations or being injured) or permanently (i.e. death, early retirement).

The Department of Labor’s Bureau of Labor Statistics (BLS) had published a work-life expectancy table that was normally relied on by economists for the purpose of ascertaining the expected future work life expectancy of an individual.  The BLS tables were constructed from information collected in the Current Population Survey (CPS) of the U.S. Census. Three distinguished economists now share the responsibility of producing these tables every few years. The recently updated table[1], published in 2019, presents estimates using 2012-2017 labor force data for persons ages 18+ by sex and level of education. Failure to take into consider the standard statistical probabilities through the use of this table results in an inappropriate estimate of future work life expectancy (in actuality, failure to use this table results in ignoring the whole concept of a work-life expectancy estimate). The work-life tables are peer-reviewed and are the preeminent source used by both plaintiff and defense experts for projecting future work life[2].

 

In addition, there are many alternative methodologies utilized by experts to determine a future retirement age. For example, the use of recent Gallup polls, Social Security retirement eligibility age, and the plaintiff’s own subjective testimony (“I planned to retire at 75”) are effective alternatives. However, these methodologies are flawed for the same fundamental reason of assuming 100% continuous employment for the entirety of the plaintiff’s remaining work duration.

 

Over the past few years, several economic experts have taken the strategy to present multiple work-life scenarios. Their first scenario presents the plaintiff’s statistical work-life expectancy from the work-life tables and considers the statistical probability of all factors limiting the plaintiff’s active participation in the labor force. Their second work-life scenario will assume that the plaintiff will retire at age 67 (example). These two scenarios are in direct conflict with one another. The expert’s first scenario accepts the process of census labor data combined with transition probabilities, resulting in median active work years. The second work-life scenario essentially suggests that the previous statistical work-life expectancy is nonsense and the plaintiff will work continuously (without transition) and longer than the median, amongst his peers. A counter question for this expert would be why a third scenario is not presented with the plaintiff estimated to work for a shorter period of time when compared to the average amongst his peers.

 

An additional concept introduced to eschew the statistical work-life expectancy is the idea that workers are retiring at a later age today when compared to previous decades. To be clear, the work-life tables do not delineate a future retirement age for the individual. The tables simply provide the number of active years in the labor force from the date of the incident to the plaintiff’s future retirement age. Furthermore, the work-life tables published in 2019 include labor data from 2012 through 2017, which would capture this theory of workers retiring at a later age more recently.

 

Although throwing darts and peering into a crystal ball to determine retirement ages are fun pass times, they are of no value in the determination of a platintiff's loss of earnings.  An older sibling's work longevity may make for good conversation at family gatherings, but it hardly represents a viable forecast for any other family member's work-life expectancy.  Objective data and peer-reviewed work-life tables (albeit less exciting than darts and crystal balls) are the only viable choices for the economist when determining work-life expectancy.  

 


[1] Gary Skoog, James Ciecka, Kurt Krueger, “The Markov Model of Labor Force Activity 2012-2017: Extended Tables of Central Tendency, Shape, Percentile Points, and Bootstrap Standard Errors,” Journal of Forensic Economics 28, (2019).

 

[2] Michael Luthy, “A 2015 Survey of Forensic Economists: Their Methods, Estimates, and Perspectives,” Journal of Forensic Economics 26, (2015): 53-83.

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