End Game

Determining when a head of damage should cease can make a significant impact on the amount of compensation that needs to be paid out in a claim. Establishing when a person will likely die could make a significant impact on when compensation should terminate and the quantum of damages.

Over the past 30 years, Canadian life expectancy at birth has been steadily increasing. The longevity of those born in 2009 is 8% higher than those born in 1979, according to data from Employment and Social Development Canada. This improvement is accompanied with an increase in the number of years spent working and doing housework.

The aim of this article is to introduce the most prevalent methodologies and provide a general overview without delving into the mathematical and statistical details of the concepts of three types of expectancies – life, worklife and household.

These three types of expectancies play an important role when assessing damages and preparing reports on claims. That is, if Accident Benefit or Bodily Injury Adjusters determine that compensation payments are appropriate, the expectancies provide the endpoints of such payments. This article can serve as a reference for members of the legal and bodily injury insurance community on how the endpoints for services outlined in a life care plan and future valuations report are determined.

The calculations of damages in personal injury and wrongful death cases rely heavily on the duration of payments. A longer time period means a larger lump-sum present value of damages to be paid-out. The calculated expectancies determine the points at which certain services either need to continue or cease. These points may have a notable impact on the settlement or quantification of the pecuniary damages.

Life Expectancy

The life expectancy of the individual provides the endpoint of the future cost valuations and, thus, is an important variable when quantifying damages. Life expectancy influences the time period in which the cost of care as a result of the injury is accumulated and is retrieved from statistical models modelling the mortality experience of a population summarized in life tables.

There are two types of life tables. The cohort life table follows an actual specific cohort population from birth to death. The efforts and resources required for the construction of such a table are immense. This type of table demands a mass volume of data and estimation techniques for projecting mortality experiences in the future. For example, if we follow the cohort of individuals born in 1990, we will need to extrapolate data to predict the changes in population. The common obstacles of deficiency and incompleteness of data often renders the creation of the cohort table unattainable.

The second kind of life table, the period life table, is the widely accepted primary method used for mortality experiences modelling. The period life table overcomes the problems presented in the cohort life table by following a hypothetical cohort and applying the age-specific mortality rates of the actual population at each period in time.

An age, gender specific statistic for life expectancy in Canada can be retrieved from The Life Tables published by StatsCan. Observing Canada, the provinces and territories, the table tracks the population changes in an original hypothetical population of 100,000 followed from birth to 110 years of age. The life expectancy calculated from this approach tells us the average remaining number of years the individual is expected to live.

Using the most recent published 2007-2009 life table, a 60-year-old female, for example, has a life expectancy of 22.29 years. This is determined by considering the 2,017,686 combined years of life left for the 90,509 females left from the initial population.

Life expectancy, however, does not necessarily need to be based on gross normative population data, but could be based on health characteristics unique to the individual. This is especially relevant when the injury experienced impacts the individual’s life span.

Worklife Expectancy

Worklife expectancy is another expectancy that is often disputed in civil litigation cases. It tells us the individual’s average number of active years remaining in the labour force from a specified age. This statistic can be used to determine the age at which the individual ceases to work, which may not be equivalent to retirement age. This, in turn may impact the calculations regarding the damages accrued during income earning years such as loss of future earnings, loss of future earning capacity and loss of competitive advantage.

The determined retirement age has substantial effect on the estimate of damages and, thus, the worklife expectancy is of interest to both the plaintiff and defendant. Suppose a simplified situation not considering taxes or fringe benefits where 100% of future earnings constitute the loss and damages will be paid out at the beginning of each year. A base salary of $50,000 with a growth rate of 3%, discount rate of 5% will yield a present value of damages of $695,272 over 16 years. Over an 18-year period, the present value will amount to $768,052. Thus, evidently, an increase of worklife by only two years results in an increased loss of $72,813.

Similar to finding life expectancy endpoints, the method of projecting the duration of the income-earning period is to consult the worklife tables, which tell us the average remaining length of time in the labour force for an individual. These tables are derived by applying a labour force participation rate to the population numbers extracted from life tables effectively separating the population into two groups – those that are participating and those that are inactive in the labour force. The Canadian tables are multi-state tables that, instead of assuming full participation commencing from the specified age to age of retirement, these age, gender specific tables allow for unemployment periods at various times during the worklife reflecting inconsistencies, risk in the labour market.

Household Maintenance Expectancy

Household expectancy, the age at which housekeeping capacity declines, is rarely taken into any meaningful consideration in economists’ reports and rarer still in life care plans. However, this expectancy can play an important role in quantifying the damages and, thus, should be a factor of interest in the reports.

Household maintenance expectancy can be defined as the individual’s average outstanding years of declining capacity for household activities. The complexity of measuring this type of expectancy is shown through the suggested (and the authors would hesitate to suggest arbitrary framework) featured by StatsCanada in their household surveys.

This framework separates household activities into three types – heavy-duty tasks, intermediate-duty tasks and low-duty tasks. Each kind of activity requires a different amount of strength and ability and can contribute to different household expectancies. The logical assumption being that as humans age a person’s ability to complete heavier tasks naturally declines and occurs with a person losing the ability to do “heavy-duty” tasks first and then lighter tasks last.

Some loss may be attributed to other areas such as cognitive losses, such as Alzheimer’s, that would prevent a person to lose the ability to complete more complex tasks first, and then easier tasks last. This is notwithstanding the over learning of an activity, that becomes automatic. Regardless of the varying expectancies associated with the type of tasks involved, it is generally accepted in Canada that the individual’s ability for all household activities will generally cease at age 80.

It is the opinion of the authors that damages quantification can be more precisely and empirically utilized in life care plans and future valuations than is currently being completed in the insurance industry. This is especially true as Canadians continu
e to experience increased longevity in all areas of their lives, which means it is becoming increasingly important to apply a more thorough examination to these expectancies. _

Mathew Rose, OT (Reg). ON, CCLCP, is a Canadian Certified Life Care Planner, Occupational Therapist and Principal of Mathew Rose and Associates Inc. He is also an Adjunct Lecturer at University of Toronto’s Department of Occupational Therapy. Kateryna Shpir is the Economist at MRA Medlegal Consulting and provides economic/statistical assessments of damages used in settlement negotiations and litigation.