Making sense of the 2016 Census


This article was originally published by The Lawyer’s Daily, published by LexisNexis Canada Inc.

The litigation and insurance communities frequently rely on census data in the determination of income losses. In 2017 and 2018, Statistics Canada released the 2016 census, the seventh quinquennial census. The 2016 census is the most recent collection of social, geographic and economic characteristics of the Canadian populace and households since the preceding Census in 2011. In this article, we highlight common issues in determining income losses and introduce you to the 2016 census, its key characteristics and how it can be of assistance in determining the quantum of damages.

Income losses in personal injury claims are based on the difference between projections of the plaintiff’s earnings, absent and after a tortious act. The expert witness’ role in determining income losses, thus, depends on estimating applicable earning capacities before and after an accident. For a mature adult, the most accurate predictor of an individual’s earnings trajectory, absent an incident, is their historical income and earnings trajectory.

In many cases, however, client-specific information is unavailable. For instance, it is common for individuals working in the restaurant and food service industry to not document or report cash tip income for tax purposes. In other cases, where historical earnings are available, such historical earnings data may be unreliable, as in the case of a self-employed individual who took advantage of significant write-offs for tax planning purposes. Census data is also very helpful in the case of minors and young adults who have not yet established their careers and can be used as a statistical benchmark to compare with an individual’s historical earnings. 

Sent to Canadian residents on May 10, 2016, the response rate for the 2016 census was the highest in national census history at 98.4 per cent. For comparison, the preceding 2011 census had a response rate of only 68.6 per cent. The high response rate for the 2016 census is not only impressive but also important in reinforcing confidence in the statistics. A high response rate indicates more accurate survey results and ensures that the statistics are representative of the target population.

The difference between the response rates of the two surveys can be explained, in part, by the structure of the surveys themselves. For the 2016 census, Statistics Canada reinstated the mandatory long-form survey, previously discontinued in 2010 in favour of a voluntary survey for the 2011 census.  Thus, the 2016 census questionnaire was comprised of two mandatory components - a short and a long-form version. The short-form survey included 10 questions regarding basic household composition, whereas the long-form survey, sent to randomly selected households representing 25 per cent of the Canadian population, included 53 supplementary questions on social, demographic and economic subjects, such as education, income and labour market activities. Due to its breadth, the mandatory long-form census offered more robust, detailed data on the Canadian population.

In light of the new census data, calculations of income capacity relying on the previous survey may need to be revisited. However, differences between the survey structures and variances in response rates contribute to the complexity of this task. For these reasons, the 2011 and 2016 censuses are not directly comparable, and updating of income statistics from one to the other should be attempted with caution and on a case-by-case basis.

Statistics Canada offers a variety of data tables that summarize the results of the 2016 census. The publicly accessible data tables are available online for different topics of which the labour category, comprised of wages, salaries and other earnings, is most relevant for statistical benchmarking earnings.   When relying on population statistics in determining income losses, it is appropriate to apply data most representative of the individual’s characteristics. The publicly available data tables, although useful for a general overview, are not detailed and are therefore only offering statistics with limited alternative parameters.

Custom data tables are available from Statistics Canada, allowing for tailored refinements of the 2016 census. For example, income statistics can be segmented by gender, geography, education, age, occupation, activity level and other parameters. In addition to the 2016 census, other customized tools are available from private research firms, which can also be used in projecting income and may be considered depending on the case facts.

The 2016 census considers different types of income and the data can be used for claims in personal injury, business valuation, expropriation, commercial disputes and other litigation. In personal injury claims, income losses are defined by a reduction in earned income. That is, passive income, derived from endeavours in which the individual is not actively involved and not impacted by the tortious act, is generally excluded. Furthermore, in Ontario, in the case of motor vehicle accidents, the Statutory Accident Benefits Schedule under the Insurance Act requires the calculation of pre-trial income losses at 70 per cent of gross income. Thus, only two definitions of income are of interest in determining the quantum of damages for tort purposes – wages and salaries and employment income. The former refers to active pre-tax earnings from employment and includes overtime pay, commissions, tip income and some compensatory income payments, such short-term disability benefits. The latter combines wages and salaries with self-employment income.

In summary, the 2016 census data is a valuable resource for litigation and insurance professionals, which can be used as a statistical benchmark for comparative purposes or as a basis for income projections. Given the high response rate combined with the reinstatement of the long-form survey, we can be more confident in these statistics when relying on them to calculate income losses.


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