Immigration and Diversity: Population Projections for Canada and its Regions

Detailed information for 2011 to 2036





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This statistical program develops projections of the ethnocultural composition of population for Canada, provinces and census metropolitan areas, based on various assumptions and scenarios on population growth components.

Data release - January 25, 2017


This statistical program develops population projections by certain ethnocultural variables (visible minority group, generation status, place of birth, religion and mother tongue) for Canada, provinces and census metropolitan areas from 2011 to 2036, based on various assumptions and scenarios on population growth components and differential demographic behaviours.

These projections are useful to decision makers in planning programs related to social cohesion, labor market integration, fight against racism and discrimination, multiculturalism, immigration and urban development. The projections are also intended for others organizations, researchers, academics, students as well as others interested in the evolution of ethnocultural diversity in Canada.

Reference period: The reference period is 25 years from the start of the projections (2011).


  • Immigration and ethnocultural diversity (formerly Ethnic diversity and immigration)
  • Population and demography
  • Population estimates and projections
  • Visible minorities

Data sources and methodology

Target population

The target population for these projections is the complete Canadian population.

Instrument design

This methodology does not apply.


This methodology does not apply.

Data sources

Data are extracted from administrative files and derived from other Statistics Canada surveys and/or other sources.

The data were prepared using Demosim, a microsimulation projection model.

The base population for the projections is drawn from the 2011 National Household Survey database, which was adjusted for census net undercoverage.

The assumptions and parameters behind the population projections were developed from various data sources: the 2001 and 2006 censuses (20% samples), the 2011 National Household Survey, survey data (General Social Survey) and administrative data (population estimates, vital statistics, Citizenship and Immigration Canada files, Longitudinal Administrative Database, 1991 Canadian census mortality follow-up database).

Error detection

This methodology type does not apply to this statistical program.


This methodology type does not apply to this statistical program.


The projections were produced using a microsimulation model that differs from the traditional cohort-component model, in that it uses microdata rather than aggregated data, which makes it possible to project a many individual characteristics.

The starting point for the projections is the 2011 National Household Survey microdatabase, adjusted for census net undercoverage. This database includes more than seven million respondents, each with individual characteristics: age, sex, marital status, place of residence, generation status and year of immigration, place of birth, visible minority group, religion and mother tongue.

As is also the case for the cohort-component model, the population at time T+1 results from changes to the population in the previous year. However, the changes occur at the individual level rather than at the aggregate level. In the model, an individual may change marital status, have a child, change place of residence, leave Canada or die, among other possibilities. Also, new individuals are added over time, either through birth or immigration.

For each person, the model calculates the probability that these events will occur based on the person's own characteristics. For example, the probability that a woman will have a child differs depending on whether she is married or single, belongs to a visible minority group, etc. Using a Monte Carlo process and based on the probabilities associated with each event, the model determines which event will occur first for each individual and calculates the amount of time that will elapse before it occurs. Each time an event occurs, the probabilities are recalculated to take account of the individual's new characteristics. For example, the probability of changing place of residence declines after the birth of a child. The model moves individuals forward in this manner until 2036, unless they die or leave Canada in the meantime.

To operationalize this model, it was necessary to use various data sources and methods (multivariate analysis, rates, transition matrices, etc.).

The projection model also requires assumptions on each component of population growth (including differential behaviours) to be developed in advance. As a result, this projection exercise is based on three fertility assumptions, three immigration levels, three provincial and territorial distributions of immigrants upon arrival, two compositions of immigrants by country of birth, four internal migration assumptions, three assumptions each for mortality, emigration and net non-permanent residents, and two assumptions for intragenerational religious mobility. Twelve combinations of assumptions were then chosen to develop plausible scenarios of the evolution of the population, based on past trends.

Quality evaluation

Various mechanisms are used to ensure the quality of these population projections. First, at the beginning of each cycle, the data sources and methods used to produce the projections are reviewed in depth; an independent scientific committee is consulted in this regard. The choice of assumptions and scenarios is also examined through consultations with federal departments or the Advisory Committee on Demographic Statistics and Studies. Lastly, the projection results undergo detailed validation, including comparative analyses of the estimated and projected transitions and of past and projected trends for the populations of interest, as well as a comparison with other series of population projections.

Disclosure control

Statistics Canada is prohibited by law from releasing any information it collects that could identify any person, business, or organization, unless consent has been given by the respondent or as permitted by the Statistics Act. Various confidentiality rules are applied to all data that are released or published to prevent the publication or disclosure of any information deemed confidential. If necessary, data are suppressed to prevent direct or residual disclosure of identifiable data.

Revisions and seasonal adjustment

The model may be subject to revisions to be carried out on a cost recovery basis.

Data accuracy

The accuracy of any projection depends on the quality of the data relating to the base population and the components of population growth, as well as the accuracy of the assumptions with regard to future trends. Projections are not predictions; rather, they represent an effort to establish plausible scenarios based on assumptions of population growth, which themselves are uncertain. As a result, it cannot be claimed that the values observed in the coming years will always remain within the range suggested by the low and high growth scenarios.

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