Population projections on immigration and diversity for Canada and its regions

Detailed information for 2016 to 2041





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

Data release - September 8, 2022


This statistical program develops population projections by certain ethnocultural variables (racialized group, generation status, place of birth) for Canada, provinces and territories as well as census metropolitan areas from 2016 to 2041. These projections are based on various assumptions and scenarios regarding the components of population growth and differential demographic behaviours.

The results of these projections are useful to decision-makers responsible for planning programs in the areas of social cohesion, labor market integration, anti-racism and anti-discrimination, multiculturalism, immigration and urban development. The projections are also intended for any organization or individual interested in the evolution of ethnocultural diversity in Canada, including researchers, academics and students.

Reference period: The reference period is 25 years from the start of the projections (2016).


  • 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 entire Canadian population.

Instrument design

This methodology does not apply.


This methodology does not apply.

Data sources

The base population for the projections is drawn from the 2016 Census database, which was adjusted for census net undercoverage.

The assumptions and parameters underpinning the population projections were developed from various data sources: the 2001, 2006 and 2016 censuses, the 2011 National Household Survey, survey data (General Social Survey) and administrative data (population estimates, vital statistics, Immigration, Refugees and Citizenship Canada files, Longitudinal Administrative Databank linked to the Longitudinal Immigration Database, 2006 and 2011 Canadian Census Health and Environment Cohorts [CanCHEC]).

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 which differs from the traditional cohort-component model in that it uses microdata rather than aggregated data, allowing for the projection of a large number of individual characteristics.

The starting point for the projections is the 2016 Census micro-database, adjusted for census net undercoverage. This database includes more than 8.6 million respondents, each with their own characteristics: age, sex, marital status, place of residence, generation status and time elapsed since immigration, place of birth, racialized group, etc.

As is the case in a cohort-component model, the population at time T+1 in a microsimulation model results from changes to the population during 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 the country 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 racialized 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 into account the new characteristics of the individual. 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 2041, unless they die or leave Canada in the meantime.

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

The projection model also requires assumptions on each component of population growth (including differential behaviours). As a result, this projection exercise is based on three fertility assumptions, three immigration levels, two provincial and territorial distributions of immigrants upon arrival, two compositions of immigrants by country of birth, five internal migration assumptions and three assumptions each for mortality, emigration and net non-permanent residents. Eleven combinations of assumptions were then chosen to develop scenarios of population change that are plausible in light of 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. The choice of assumptions and scenarios is examined through consultations with federal departments or the Advisory Committee on Demographic Statistics and Studies. Lastly, the projection results undergo detailed validation, including an analysis of the fit between estimated and projected transitions, a comparison with other sets of population projections and a comparative analysis of past and projected trends for the populations of interest.

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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