Low Income in Canada - A Multi-line and Multi-index Perspective

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By Brian Murphy, Xuelin Zhang and Claude Dionne

There is sustained interest in finding out in broad terms how many poor people are in Canada, how poor they are, what their characteristics are, where they live, and how long they stay poor. Statistics Canada does not define 'poor' nor does it estimate the number of poor families and individuals in Canada. However in recognition of the need for a statistical portrait, Statistics Canada has for 40 years been publishing statistics on Canadians with low-incomes, which is a key dimension of poverty. The primary purpose of Statistics Canada's low income lines are to provide some indication of the extent, nature, and evolution of persons with low-income who may be said to be at-risk of poverty.1
International practice has shown that using a number of different low-income thresholds can facilitate a more complete picture of the low-income population and this report examines three such lines: Statistics Canada's after-tax low income measure (LIM) and after-tax low income cut-off (LICO), and the Market Basket Measure (MBM) of Human Resources and Skills Development Canada (HRSDC). None of these lines is considered definitive and all have their strengths and limitations. Together they allow a more complete examination of the low income population in Canada.

This report uses these three thresholds applied to the Survey of Consumer Finances (SCF) and the Survey of Labour and Income Dynamics (SLID) to present and examine broad trends in the low-income population over a 34 year period from 1976 to 2009, with particular attention given to the changes between 2007 and 2009. The report examines the incidence (rate), gap ratio (depth), severity and persistence of low income for Canada as a whole and across different provinces, cities, family types, as well as for specific groups with a high risk of persistent low income.  


1. The imprecise and to some degree arbitrary operationalization of poverty concepts coupled with the statistical variability of surveys and the essentially political nature of such estimates render it inappropriate for a Statistical Agency to make such judgements (Fellegi, 1997). The low-income statistics are not intended to provide an indication of the success or failure of specific programs designed to assist the poor.

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