Efforts to accurately measure and define poverty in Canada have been hindered by inconsistent and poor quality data, resulting in a confusing picture that is often further distorted by politicians and activists, according to a new study, What is Poverty? Providing Clarity for Canada , written by noted poverty researcher and Fraser Institute senior fellow Professor Chris Sarlo of Nipissing University.

In What is Poverty? Providing Clarity for Canada Sarlo finds that poverty, whether measured by income or consumption, has remained in the four to six per cent range since 1996. Sarlo points out that most descriptions of poverty deal with 'relative poverty,' which is really an estimate of the proportion of Canadians who are less well off than average. This is a measure of inequality that tells nothing about the state of deprivation in Canada.

Sarlo has long argued that the most realistic and credible measurement of poverty is one based on the necessities of life. He defines poverty as the cost of a list of basic needs required for long-term physical well-being, including nutritious food purchased at grocery stores fulfilling all Canada Food Guide requirements, rental accommodation, clothing purchased new at major department stores, household furnishings, supplies, personal hygiene items, laundry, insurance, and out-of-pocket health costs such as medications, dental, and vision care.

In What is Poverty? Providing Clarity for Canada , Sarlo tracks the latest information about the incidence of basic needs poverty in Canada, utilizing two different sets of data (one focused on family spending and the other on labour market information), and two different equivalence scales in the estimation of poverty in Canada. In addition, Sarlo's latest research again reveals concerns about data quality related to the issue of underreporting and hidden income, particularly in regards to income data, which is often used to indicate economic well-being in studies of poverty and he calls for Statistics Canada to improve the quality and reliability of its data collection.