Cara Brown's article on the HALS/PALS wage gaps has been published in the Journal of Legal Economics April 2010.     if you want to receive a copy of the journal article.

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HALS/PALS Methodology: Using Statistics Canada's databases on the disabled to project loss of income or "loss of opportunity"

The Participation and Activity Limitation Survey (PALS) is Canada’s national survey that gathers information about adults and children whose daily activities are limited by a physical, mental, or other health-related condition or problem1.  The official definition of disability from the PALS is "persons with disabilities... who reported difficulties with daily living activities, or who indicated that a physical or mental condition or health problem reduced the kind or amount of activities they could do."  (PALS uses the World Health Organization’s (WHO) framework of disability provided by the International Classification of Functioning (ICF).2)  The sample of disabled persons is drawn from those who answer "YES" to the Census disability filter question.  (The Census3 is conducted every 5 years and is a mandatory survey that Canadians complete and yields information about population, housing, income, expenditures, etc.)  The precursors to the 2006 PALS were the 2001 PALS and the 1991 HALS4.

From the 2001 PALS, 12.4% of the total population reported being disabled in Canada (11.5% males, 13.3% females). In the 2006 PALS, these rates changed to 14.3% overall (13.4% males, 15.2% females).5

The usefulness of the HALS and PALS surveys is that they provide a statistical basis to formulate a future "loss of earning capacity" or "loss of opportunity" award.   When there exists medical and/or vocational evidence indicating that the claimant will suffer impediments in the future but the precise nature of such impairments is unknown (or difficult to quantify) at the time of settlement or trial, the data from the HALS and PALS surveys allow us to estimate a future loss of income by applying wage deficits in percentage terms.

For instance, if the court finds the plaintiff will suffer an ongoing disability in the future of, say 25%, then the HALS/PALS data can be used to substantiate that the plaintiff has a disability that is affecting his or her earning capacity to this degree. There are three steps in this process:

  1. Medical and/or vocational evidence is adduced to attest to the claimant’s impairments and that these impairments will affect his or her earning capacity in the future;
  2. Research shows that people with disabilities, depending on severity or type of disability, experience wage gaps compared to non-disabled people; and
  3. The plaintiff completes the same questionnaire as filled out by HALS and PALS respondents to determine his/her level of severity of disability.
Counsel for the plaintiff is responsible for assembling the documentation in (1), if it exists. Brown Economic has already done the research on wage gaps with the HALS and PALS data ((2) above) so we know what percentage wage deficits to apply to the plaintiff’s earning capacity in the future (see publications below). The plaintiff subsequently completes the HALS/PALS questionnaires to provide a determination of his/her severity of disability under (3) above. To complete the HALS and PALS questionnaires, please click here.

Brown Economic's HALS/PALS research

Brown Economic has purchased the micro-data files for all three surveys; the most recent, of course, is the 2006 PALS, which was conducted between Oct. 30, 2006 and February 28, 2007.  From the 2001 PALS and 1991 HALS, Ms. Brown published a working paper (Working Paper 2008-26) with Dr. Herb Emery at the University of Calgary entitled "The Impact of Disability on Earnings and Labour Force Participation in Canada: Evidence from the 2001 PALS".

Brown Economic will be publishing regression results from the 2006 PALS in a future Brown's Economic Damages Newsletter.  

Brown Economic has also published several articles summarizing the results from the 1991 HALS and 2001 PALS surveys, using the actual micro-data (by purchasing the raw data from Statistics Canada).  These results have been printed in various issues of the firm's newsletter, as follows:

Brown Economic has derived specific wage deficits, as a percentage of income,6 to apply based on gender and SEVERITY OF DISABILITY.7   We have also derived wage deficits based on TYPE OF DISABILITY, 8 using percentages.   These percentages have been calculated using sophisticated regression analysis, namely Heckman's two-stage process and correction for sample selection bias, as described in Berndt and Greene. 9   The usefulness of regression analysis to derive the percentage losses cannot be underestimated and are more accurate than simply calculating the "residual" income of disabled people.  The latter will grossly overestimate the loss arising from disability because other human capital factors are not controlled for, as they are in regression analysis.  Moreover, using an average income for disabled people for a claimant's "residual earning capacity" is not specific enough to the plaintiff since it does not represent the plaintiff's education level, whereas applying wage deficits from regression analysis will be specific to the plaintiff's human capital characteristics.

The most common concern mentioned by judges when assessing the usefulness of HALS/PALS data is that it be tied as closely as possible to the plaintiff (see Justice Veit's comments in Dabrowski v. Robertson (2007), in which Ms. Brown's testimony on the HALS/PALS data was accepted as an approach to use for calculating loss of income).  Ms. Brown has now testified in several cases in which the HALS/PALS wage gaps derived from the original micro-data "PUMF" (Public Use Micro-data) files has been accepted by judges: Robinson v. Williams (2005); Dabrowski v. Robertson (2007); Mahe v. Boulianne (2008); Russell v. Turcott (2009).  Justice Benzler ruminated on the usefulness of the HALS/PALS approach in Gerlitz v. Lee (2007), because Mr. Gerlitz was self-employed, but we have since determined that the PALS 2001 survey included self-employed persons, and we have modified the HALS/PALS approach for self-employed persons by excluding the component of business income generated by non-physical or indirect methods.

[1] As per Statistics Canada’s Participation and Activity Limitation Survey 2006: Tables 2006, catalogue no. 89-628-XIE - No. 003 (Ottawa, Ontario: Minister of Industry), December 2007, p.2.
[2] As per Statistics Canada’s Participation and Activity Limitation Survey 2006: Technical and Methodological Report, cataqlogue no. 89-0628-XIE - No. 001 (Ottawa, Ontario: Minister of Industry), December 2007.
[3] Census information is combined with data from the HALS and PALS respondents to provide socio-economic details on the respondents. This allows us to compare income levels, education levels, employment characteristics, labour force attachment, etc.
[4] The precursor to the 1991 HALS was the 1986 HALS, but the 1991 survey improved on the 1986 one considerably. Given the 1986 survey is now more than 20 years old, was the first in this cycle of surveys, and we have three since then, we do not display the 1986 results.
[5] As per Statistics Canada’s Participation and Activity Limitation Survey 2006: Tables. Catalogue no. 89-628-XIE – No. 003. (Ottawa: Minister of Industry, 2007). Tables 3.1 and 3.1-1, pp. 31-32. These rates exclude the Yukon, Northwest Territories and Nunavut. The total size of the 2001 PALS sample was 43,276; the total size of the 2006 PALS sample was 47,793. In 2001, the Aboriginal community was excluded as it was covered in the Aboriginal Peoples Survey (APS); in 2006, the aboriginal communities were included. (Source: Statistics Canada’s Participation and Activity Limitation Survey 2006: Technical and Methodological Report, catalogue no. 89-0628-XIE – No. 001 (Ottawa, Ontario: Minister of Industry), December 2007, pp. 10 and 12).
[6] For the results showing percentage of wage deficits, see The Economics Editor, "Proving economic loss when injury isn't obviously manifest & magnitude of impact unknown at settlement", November/December 2007, Vol. 4, Issue 8; Tables 1 and 2 on p. 2.
[7] The percentages by severity of disability (mild, moderate, severe and very severe) are for average educational levels. When sample sizes are divided up by gender and education level and severity of disability, many of the samples are too small to derive results for specific education levels.
[8] The "type" of disability include: agility; hearing; mobility; pain; seeing; speech; and other. The "other" category consists of disabilities related to learning, memory, developmental, psychological, and unknown.
[9] Ernst R. Berndt, The Practice of Econometrics Classic and Contemporary (Massachusetts: Addison-Wesley Publishing Company), 1991; and William H. Greene, Econometric Analysis 2nd edition (Englewood Cliffs, New Jersey: Prentice-Hall), 1993.