Projections of the Indigenous populations and households in Canada, 2016 to 2041: Overview of data sources, methods, assumptions and scenarios

Acknowledgments

This report is the work of the Demosim team. The following are or were members of the Demosim team during the development of the versions of the model based on the 2016 Census: Arnaud Bouchard-Santerre, Patrice Dion, Stéphanie Langlois, Anne Milan, Jean-Dominique Morency, David Pelletier, Elham Sirag, Stéphanie Tudorovsky, Gabriel Vesco and Samuel Vézina of the Centre for Demography; Dominic Grenier, Chantal Grondin and Amélie Lévesque of the Statistical Integration Methods Division.

For the development of this version of Demosim, funding was received from Statistics Canada and two external partners: Indigenous Services Canada (ISC) and Immigration, Refugees and Citizenship Canada (IRCC). Representatives of these departments were consulted at different stages, through an interdepartmental working group and an interdepartmental steering committee.

The Demosim team would like to thank especially the authors of the two previous versions of the Demosim technical report: Éric Caron-Malenfant, Simon Coulombe and Dominic Grenier. Large sections of these two previous versions of the technical report were directly incorporated into this updated version.

Thanks to Carol D’Aoust, for his technical support in preparing this report. Thanks also to Laurent Martel who reviewed a preliminary version of this document.

Introduction

For a third consecutive cycle, Indigenous Services Canada (ISC) has mandated Statistics Canada’s microsimulation population projection team to update projections of the Indigenous^Note populations and households in Canada. For this new projection cycle, the objective is to produce prospective data for the period from 2016 to 2041, taking into account the most recent data sources, chief among which is the 2016 Census.

This new cycle of Indigenous populations projections differs from previous ones in several respects. First, much effort was put into improving parameter specification, integrating information from new data sources, and further validating the models’ functioning and the results. It also differs in that more attention was given to uncertainty in the early years of the projection, because it has been shown that many users of Indigenous projections used them for data needs over a very short horizon. In previous cycles, the choice of assumptions was essentially guided by long-term considerations. It did not explicitly aim to take into account the possible—sometimes significant—fluctuations that could occur in the short term for some components.

It further differs in the choice of dissemination products. In the previous cycle, two reports related to the projections of the Indigenous populations and households were made public: (1) an analytical report (Statistics Canada 2015-1) that described the projection assumptions and scenarios, as well as the main projection results, and (2) a technical report (Statistics Canada 2015-2) that provided an overview of how Demosim, the projection model used to produce these projections, generally works, its base population, and the data sources and methods related to each of its components. For this projection cycle, it will now be possible to extract, free of charge, the results of the projections of the Indigenous populations and households from the data tables available on the Statistics Canada website. In addition, an interactive data visualization tool and infographics will be made available to users. These various products (see Box 1) will replace the analytical report that was disseminated in the past.

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Box 1. Dissemination products for results of Indigenous projections

Analysts and researchers interested in obtaining results from the current projections of the Indigenous populations and households are invited to consult the following products available to the public free of charge:

The Daily

The Daily is Statistics Canada’s official release bulletin. A special article in The Daily was published the day the projections of the Indigenous populations and households were disseminated. This article provides a brief description of the main projection results (Statistics Canada 2021-1).

Infographics

Five infographics were developed, one for each of the following population groups:

• Total Indigenous population;
• First Nations people;
• Métis;
• Inuit;
• Registered or Treaty Indians.

Each infographic presents results based on a selection of indicators at the 2041 horizon. These infographics are available on the Statistics Canada website (Statistics Canada 2021-2; 2021-3; 2021-4; 2021-5; 2021-6).

Projected data tables

Two data tables present the projected size of the Indigenous populations. The first table (table 17-10-0144-01: Statistics Canada 2021-9) is broken down using an Indigenous identity classification that gives precedence to Indigenous groups, while the second table (table 17-10-0145-01: Statistics Canada 2021-10) is broken down using an Indigenous identity classification that gives precedence to Registered or Treaty Indian status (see the “Key concepts related to Indigenous populations” section for more details regarding these classifications). In both cases, the projected population figures are broken down by age group, sex, region of residence, provinces and territories, and projection scenario for years 2016 to 2041. These tables are available on the Statistics Canada website and can be consulted using the following links: table 17-10-0144-01 and table 17-10-0145-01.

Interactive data visualization tool (dashboard)

An interactive data visualization tool, also available on the Statistics Canada website, can also be used to explore projection results regarding Indigenous populations in a dynamic manner. The base data for this tool are those from the two CODR tables (Statistics Canada 2021-11).

Data produced on demand

For users of data from the projections of the Indigenous populations and households who are unable to find the data that would be useful to them in the products presented above, it is possible to request custom data by contacting customer service at the Centre for Demography (statcan.demography-demographie.statcan@statcan.gc.ca). Custom tables are prepared using a cost recovery approach.

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Lastly, it is appropriate to mention that at the time of making these projections, the COVID-19 pandemic has occurred and is likely to have impacts on the demographic evolution of Indigenous populations in the coming years, impacts that are hard to predict at the time of writing given the recent nature of the pandemic. Readers are invited to see Box 4 in the “Cautionary notes” section for more information about this matter.

Base population

Projected characteristics

The base population for the version of Demosim used to prepare projections of the Indigenous populations and households is essentially derived from the 25% sample microdata file from the 2016 Canadian Census of Population,^Note a database comprising 8.6 million records representative of the Canadian population living in private households on May 10, 2016. The main variables of the base population are as follows:^Note

• Age;
• Sex;
• Indigenous group;
• Registered or Treaty Indian status;
• Registration category on the Indian Register (6[1] or 6[2]);
• Marital status;
• Place of birth (province/territory or country/world region);
• Immigrant status and time elapsed since immigration;
• Generation status;
• Immigrant admission category;
• Canadian citizenship;
• Visible minority group;
• Mother tongue;
• Language spoken most often at home;
• Knowledge of official languages;
• Education level (secondary [high] school diploma or equivalency certificate).^Note

Registration category on the Indian Register is a variable that was added through file linkages, as it was not included in the 2016 Census database. Registration category, which defines the conditions for children to inherit Registered or Treaty Indian status from their parents, was obtained from pre-existing linkages between the Indian Register and the 2016 Census, to identify, among census respondents who reported being Registered or Treaty Indians, those who had status under subsection 6(1) of the Indian Act and those who had status under subsection 6(2).^Note In 85% of cases, registration category was determined through file linkages. For the remaining 15%, categories 6(1) and 6(2) were either deterministically imputed using information on the registration of other census family members, or else were imputed using a probabilistic model (logistic regression).^Note

Geographic infrastructure in Demosim

In addition to the characteristics listed above, Demosim also has a geographical infrastructure made up of 85 geographic regions. Among these 85 regions, there are 52 main regions. The main regions include all 35 Canadian census metropolitan areas (CMA) identified in the 2016 Census, the non-CMA part of each province, and the three territories. Some of these regions are further divided into sub-regions that are also part of the main regions: the Montréal CMA is divided into Montréal Island and the rest of the CMA; the Ottawa–Gatineau CMA is divided into its Ontario part and its Quebec part; and the non-CMA parts of New Brunswick and of Ontario are each divided into a part with a concentration of Francophones and a non-francophone part (see Caron-Malenfant [2015] for a map of these regions in New Brunswick and Ontario).

Of the main regions, 31 include at least one reserve. For these 31 regions, we distinguish an on-reserve and an off-reserve part. These 31 regions are non-CMA Newfoundland and Labrador, Prince Edward Island, Halifax, non-CMA Nova Scotia, Moncton, non-CMA francophone New Brunswick, non-CMA anglophone New Brunswick, Québec, Trois-Rivières, the part of the Montréal CMA outside the island of Montréal, non-CMA Quebec, Peterborough, Toronto, Brantford, Greater Sudbury, Thunder Bay, non-CMA francophone Ontario, non-CMA anglophone Ontario, Winnipeg, non-CMA Manitoba, Saskatoon, non-CMA Saskatchewan, Calgary, Edmonton, non-CMA Alberta, Kelowna, Vancouver, Victoria, Abbotsford–Mission, non-CMA British Columbia, and the Northwest Territories.

Likewise, three main regions (excluding Nunavut, all of which is included inside Inuit Nunangat) include portion of the Inuit homelands. For these three regions, we distinguish one part inside and one part outside Inuit Nunangat. The four regions of Inuit Nunangat are (1) Nunatsiavut (located in the non-CMA region of Newfoundland and Labrador), (2) Nunavik (located in the non-CMA region of Quebec), (3) Nunavut territory, and (4) the Inuvialuit region (located in the Northwest Territories).

Adjustments made to the 2016 Census microdata file

Some adjustments were made to the 2016 Census microdata file so that the Demosim base population reflects the entire Canadian population as closely as possible.

The population living on the 14 Indian reserves or Indian settlements that were incompletely enumerated in the 2016 Census were added to the Demosim base population. It was assumed that the population was consistent with estimates produced by the Statistical Integration Methods Division (SIMD) of Statistics Canada. Records were then imputed with characteristics that were representative of similarly sized reserves enumerated in the same province.

Adjustments were then made to obtain a population that was representative of the population estimates of May 10, 2016, which includes people living in institutions and in collective dwellings and accounts for the net undercoverage in the census. The adjustment for institutions and collective dwellings involved multiplying the sampling weights of individuals by the ratio of the 2016 short-form Census estimated population (which includes institutions and collective dwellings) to the 2016 long-form Census estimated population by age, sex and place of residence.^Note

Lastly, correction factors were applied to sampling weights to take into account census net undercoverage of the population. An adjustment was first made by age, sex, and place of residence for the population living off Indian reserves for both Indigenous and non-Indigenous people. The approach assumes that Indigenous and non-Indigenous people are equally undercovered in the regions in question, an assumption that cannot be disproved because the data on undercoverage are not broken down by Indigenous identity.

Moreover, an additional adjustment was also applied to the weights of males with Registered or Treaty Indian status aged 15 to 54 years living off reserve. This adjustment was warranted given that the sex ratios of Registered or Treaty Indians decline when they are in their twenties, according to 2016 Census data (long-form questionnaire), a decline that can hardly be attributed to purely demographic processes. In fact, this decline instead appears to be because of the overrepresentation of men among the institutionalized population, outside of the long-form census questionnaire universe, and among the population with no fixed address, who are difficult to enumerate (see Akee and Feir, 2018). The adjustments made to the 2016 Census weights to account for the institutionalized population and for the net census undercoverage described above do very little to reduce the decline in sex ratios because they do not specifically take Indigenous identity into account. To remedy this situation, weights of males with Registered or Treaty Indian status have been adjusted to reflect the estimated sex ratios of Indian Register data, under the assumption that they are more realistic. In fact, despite some shortcomings, such as the occasional late registration of births and deaths, and incomplete updating of information on individuals’ place of residence, the Indian Register has the advantage of being little affected by undercoverage. Furthermore, it must be noted that similar declines in sex ratios are also observable among First Nations people without Registered or Treaty Indian status and Métis without Registered or Treaty Indian status, but no additional adjustments could be made because of a lack of reliable alternative data.

For the on-reserve population, adjustments for net undercoverage are made differently for the Registered or Treaty Indian population and the population without Registered or Treaty Indian status. For the population without Registered or Treaty Indian status, the same net census undercoverage rates are applied by age, sex and place of residence as they are for the off-reserve population. For the Registered or Treaty Indian population, the net census undercoverage rate for reserves in Canada is applied. The distribution of the net census undercoverage of Registered or Treaty Indians by age, sex and place of residence is assumed to be proportional to the gaps in the observed population (by age, sex and place of residence) between the Indian Register and the census for the on-reserve population.^Note

All of these adjustments increased the total population by about 1.6 million people. These adjustments had a greater impact on some population groups—notably young adults, who had higher net undercoverage rates, and Registered or Treaty Indians, because of the adjustment for incompletely enumerated reserves.^Note

Demosim’s general functions and features

These new projections of the Indigenous populations were produced using Demosim, Statistics Canada’s microsimulation population projection model.

Demosim projects individuals in the population one by one, rather than projecting the population on the basis of aggregate data, as is done with cohort-component and multistate models.^Note Demosim simulates the life of each person in its base population, as well as that of the newborns and immigrants who are added to the population during the simulation.^Note Individuals advance through time and are subject to the likelihood of “experiencing” various events simulated by the model (for example, the birth of a child, death, a change in education level) until they die, emigrate or reach the end of the simulation.

The probabilities (or risks) of “experiencing” each event depend on the individual’s characteristics. The probabilities are used to derive waiting times, which—being a function of the probabilities associated with the events, individual characteristics and a random process—correspond to the time that will elapse between the present and the occurrence of each event (see Box 2). The event with the shortest waiting time occurs first. After an event occurs, a new set of waiting times are calculated for the events that depend on the characteristic that has changed; the individual then advances through time to the next event (again, the one with the shortest waiting time), and so on. Since Demosim is a continuous-time model, the various simulated events may occur at any time of the year, although some of them occur on a fixed date (for example, birthdays). As well, some characteristics are imputed annually to the individuals. Events and waiting times are managed using the computer language Modgen,^Note in which Demosim is programmed.

This approach is used to yield projections at a level of detail that is not possible using standard models because of their matrix nature. The simultaneous and consistent projection of a large number of variables made possible through microsimulation permits the use of more characteristics, both as determinants of simulated events and for tabulating results. Demosim has also shown flexibility in formulating assumptions and projection scenarios, as well as an ability to reproduce the results of cohort-component models at an aggregate level.^Note

The use of this method assumes that the probabilities (or risks) associated with simulated events have been calculated in advance. Calculations are done using existing data sources (censuses, surveys, administrative data and database linkages) to which various methods are applied. The next section describes these methods in more detail.

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Box 2. On calculating waiting times, as well as the concepts of transition rate (risk) and probability

In a continuous-time model like Demosim, events can occur at any time. Their occurrence depends on waiting times, which are associated with each individual based on his or her present characteristics. The individual-level waiting times required to run a microsimulation model like Demosim cannot be obtained from observation data; they must be derived.

Waiting times are derived from the transition rate (which quantifies the risk) denoted by λ. The transition rate is defined by the number of events observed divided by the number of person-years lived. An example of a transition rate in demography is the mortality rate (m_x), found in mortality tables alongside the death probability (q_x), which represents the probability that a person will die during the year.

The waiting time before an event occurs follows an exponential distribution of parameter λ. Under this exponential law, it is assumed that the risk of experiencing an event (e.g., death) remains constant during a given period of time. The risks in Demosim are thus assumed to be constant, as long as the characteristics that determine the modelled event remain unchanged for the individual. Since most events in Demosim are age-dependent, this period for these events is a maximum of one year.

The probability of an event occurring before or exactly at time t is given by the exponential distribution function: P(T ≤ t) = F(t) = 1- e^-λt

The inverse exponential distribution function, t = -ln(1- F(t)) / λ, indicates the time t at which a proportion F(t) of the population will have experienced the event, knowing that the transition rate is λ.

Demosim uses a random process in conjunction with the inverse exponential distribution function to generate individual-level waiting times for each simulated event. First, a random value is obtained from the uniform distribution U[0,1]. This value is inserted into the inverse exponential distribution function in place of F(t). For example, if an event has a transition rate of λ = 0.15 and the random number generated is 0.5, then the waiting time generated for this event will be t = -ln(1- F(t)) / λ = -ln(1- 0.5) / 0.15 = 4.62 years. Any lower random value will give a waiting time below 4.62 years, and any higher value will give a longer waiting time.

The projection parameters often consist of probabilities rather than transition rates. When this is the case, they need to be converted to transition rates by isolating λ in the exponential distribution function to obtain λ = -ln(1- F(t)) / t , and then replacing F(t) with the annual probability and t with 1 year. Therefore, an annual probability of dying of 0.10 has a transition rate of 0.1053 because λ = -ln(1- 0.10) / 1 = 0.1053.

Although the concept of probability is frequently used in this document, it should be noted that the Demosim model actually uses risks to derive waiting times. Furthermore, the term “risk” is used in reference to the more precise concept of transition rate only for the sake of simplicity.

To learn more about calculating waiting times, please consult Willekens (2011).

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Key concepts related to Indigenous populations

Definition and classifications of the Indigenous identity population

The 2016 Census includes four questions related to Indigenous populations, i.e., questions 17, 18, 20 and 21. Question 17 deals with the ethnic or cultural origin of the respondent’s ancestors, and the information collected from this question is not projected in the current projections. Question 18 gives respondents the opportunity to self-identify with one or more Indigenous group(s): First Nations (North American Indian), Métis or Inuk (Inuit). Question 20 asks if the person is a Registered Indian or a Treaty Indian (Status Indian) and Question 21 whether the respondent is a member of a First Nation or an Indian band. The responses to these questions can be combined in various ways to define the Indigenous population (Guimond et al. 2009).

To clarify the language, it is important to distinguish between the categories of Question 18—First Nations (North American Indian), Métis or Inuk (Inuit) —each constituting what will be called here the Indigenous groups, and the Indigenous identity that results from the combination of responses given to Questions 18, 20 and 21 of the 2016 Census. ^Note , ^Note To meet the needs of various users, two separate Indigenous identity classifications are used to present the results of the Indigenous population projections, one focusing on Indigenous groups (Question 18) and the other giving precedence to Registered or Treaty Indian status (Question 20).

Indigenous identity, classification that gives precedence to Indigenous groups

• First Nations^Note —single identity (respondents self-identifying only with the First Nations group [North American Indians] in response to Question 18);
• Métis—single identity (respondents self-identifying only with the Métis group in response to Question 18);
• Inuit^Note —single identity (respondents self-identifying only with the Inuit [Inuk] group in response to Question 18);
• other Indigenous people (respondents self-identifying with more than one Indigenous group in response to Question 18, or not self-identifying with any Indigenous group in response to Question 18 but reporting being a Registered or Treaty Indian in response to Question 20 or a member of a First Nation/Indian band in response to Question 21);
• non-Indigenous people (respondents not self-identifying with an Indigenous group in response to Question 18, and not reporting being a Registered or Treaty Indian in response to Question 20 or being a member of a First Nation/Indian band in response to Question 21).

Indigenous identity, classification that gives precedence to Registered or Treaty Indian status

• Registered or Treaty Indians (respondents reporting being a Registered or Treaty Indian [Status Indian] in response to Question 20 of the 2016 Census);
• First Nations—single identity—without Registered or Treaty Indian status (respondents self-identifying only with the First Nations [North American Indian] group in response to Question 18 and not reporting Registered or Treaty Indian status in response to Question 20);
• Métis—single identity—without Registered or Treaty Indian status (respondents self-identifying only with the Métis group in response to Question 18 and not reporting being a Registered or Treaty Indian in response to Question 20);
• Inuit—single identity—without Registered or Treaty Indian status (respondents self-identifying only with the Inuit [Inuk] group in response to Question 18 and not reporting being a Registered or Treaty Indian in response to Question 20);
• other Indigenous people without Registered or Treaty Indian status (respondents: 1) self-identifying with more than one Indigenous group in response to Question 18, or 2) reporting being a member of a First Nation/Indian band in response to Question 21 without reporting being a Registered or Treaty Indian in response to Question 20 or self-identifying with an Indigenous group in response to Question 18);
• non-Indigenous people (respondents not self-identifying with an Indigenous group in response to Question 18, and not reporting being a Registered or Treaty Indian in response to Question 20 or being a member of a First Nation/Indian band in response to Question 21).

These two classifications include exactly the same total number of people with an Indigenous identity. However, the second classification includes the “Registered or Treaty Indian” category, which leads to a corresponding reduction in population for all other Indigenous identities. Table 1 shows the distribution of the Indigenous identity population by the two Indigenous identity classifications.



Registration category on the Indian Register

In this document, a few references will be made, in speaking of Registered or Treaty Indians, to the registration category on the Indian Register, in other words, to category 6(1) and category 6(2) Registered or Treaty Indians. Registration categories 6(1) and 6(2) are designated as such because they correspond to the rules set out in subsections 6(1) and 6(2) of the 1985 Indian Act, which establish the criteria that individuals must meet in order to be entitled to have their names included on the Indian Register. Within the meaning of the Act, people registered under subsection 6(1) differ from those registered under subsection 6(2) with regard to their ability to transmit their status to their children. All children with at least one Indian parent under category 6(1) are entitled to be registered: they are in category 6(1) if the other parent is also registered, and in category 6(2) if not. Children of a category 6(2) registered parent are entitled to be registered only if the other parent is also a Registered or Treaty Indian; children of such unions are in category 6(1).^Note It should be added that some people may see their registration category change during the course of their lives. This would represent a case in which the registration category was “amended.”



Main projected components in Demosim

This section, which aims to document the main components projected by Demosim, is divided into three main parts. The first is concerned with events that are modelled using waiting times, the second discusses characteristics that are imputed annually, and the third gives an overview of how individuals are created during the simulation.

Each of the components projected in Demosim corresponds to a “module,” which includes the computer code specifying the dimensions and functioning of the modelled event, including its relation to other parts of the model and its associated parameters. Table 3 presents the different components of the projection model and summarizes the methods and data sources used in modelling these components.^Note



Events with waiting times

The first category of events contains those events that are modelled using waiting times (see Box 2). These events make it possible to create a dynamic and distinct life course for each simulated individual. Events in this category are fertility, mortality, internal migration, emigration, registration on the Indian Register and registration category amendment over an individual’s lifetime, intragenerational ethnic mobility of Indigenous people and changes in education level.

Fertility

The fertility module was designed to obtain a projection of births that reflects fertility differences between the various groups projected such as Indigenous people or immigrants. On the one hand, it includes “base probabilities” of giving birth by age, number of children at home, and having or not having an Indigenous identity. Calculated using the own-children method^Note applied to the 2016 Census data, they represent the probability of having given birth to at least one child during the year preceding census day.^Note Base probabilities are adjusted to take into account children not living with their mother and deaths that may have occurred during the year, and calibrated to correspond to the estimated number of births according to data from the Canadian Vital Statistics - Birth database.

The base probabilities are then combined with the results of complementary log-log regressions (see Box 3) computed using the same 2016 Census data to which the own-children method was applied. The regressions aim to estimate the probability—for various combinations of age group, number of children in the home and Indigenous identity^Note —of having given birth to one or more children during the same period according to other variables. These variables are marital status, education level, Indigenous group, Registered or Treaty Indian status and registration category on the Indian Register, immigrant status, time elapsed since immigration, generation status, immigrant admission category, place of birth, visible minority group, mother tongue and detailed place of residence (on or off Indian reserves, inside or outside Inuit Nunangat, in or outside a CMA, and province and territory in regression models for the Indigenous identity population and CMA of residence only in regression models for the non-Indigenous population).^Note For the sake of consistency between base probabilities and regressions results, both estimate the number of women having given birth to one or more children, and not the total number of births (since multiple births are possible). To obtain the total number of births, an adjustment consisting of ratios between the number of births during the period and the number of women who have given birth, by Indigenous identity or visible minority group, is applied.

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Box 3. Combining base rates or probabilities with regression results

In a number of Demosim modules, the likelihood of certain events is estimated using base rates combined with relative factors derived from results of regressions. Combining base rates and regression results increases the flexibility for developing projection assumptions and makes it possible to incorporate information from various data sources for event modelling. However, some difficulties are associated with it.

First, the reference category of regression models is normally not the entire population, but only one or more subgroups. A conversion or adjustment is therefore required if the results of such regressions are to be combined with one or more rates that refer to the entire population.

A second difficulty lies in differences between the composition of the population used to calculate the regression models and the composition of the population to which these regression results are applied, that is the base population for the projection. When a data source other than the Demosim base population is required to calculate parameters, the weighted sum of probabilities from the regression will not necessarily be equal to the sum that would be obtained by weighting these same probabilities using the population from another data source.

To address these difficulties, a calibration method is used to adjust the y-coordinate at the origin of the regression models without changing the model’s other coefficients. This adjustment is made in such a way as to reproduce target rates (base rates) within a population whose composition is the same as the composition of the Demosim base population.

To illustrate the method, let us suppose that we performed a logistic regression estimating the probability than an event Y will occur according to a set of characteristics X. This regression was carried out on a survey that we will call source A. This data source A has a population whose composition according to the X characteristics differs from the composition of the Demosim base population, to which, however, the probabilities from source A will be applied. We will call the Demosim base population data source B. Let us suppose that we also want to assume that the probability that the event in question will occur reaches a pre-established target, as is often the case when making projections.

Keep in mind that with a logistic regression, the probability P_A (with A referring here to data source A) that event Y will occur given the set of characteristics X ($P_A\left(Y=1\text{|}X\right)$ ) is calculated using the following formula:

$P_A\left(Y=1\text{|}X\right)=\text{exp}\left({\alpha }_A+{\beta }^{\prime }X\right)$

If we weight the probabilities using weights derived from data source A ($w_A$ ), the overall probability (or the mean probability in the population) that event Y will occur is

$\sum w_A\text{*}{P}_A\left(Y=1\text{|}X\right)=P_A\left(Y=1\right)$

If we apply the probabilities resulting from this regression to another data source—say, source B—andwe weight it based on the composition of this source (with weights $w_B$ ), we will produce an overall probability of event Y occurring that will not be equal to either the one that we would obtain using only source A, or the one that that we could have obtained using only source B.

$\sum w_B\text{*}{P}_A\left(Y=1\text{|}X\right)\ne \{\begin{array}{c}{P}_A\left(Y=1\right)\\ or\\ P_B\left(Y=1\right)\end{array}$

Let us now suppose that we want to find an adjustment to reproduce the overall probability for source A or source B. Since the result of the above equation gives the overall probability neither for source A nor for source B, it would not be sufficient to multiply it by the quotient of the two ($P_B/P_A$ or the inverse).

The adjustment that we use for this purpose consists in using an iterative method to find an ${\alpha }_{target}$  that we add to the ordinate at the origin ${\alpha }_A$  so that

$\sum w_B\text{*}\widetilde{P_A}\left(Y=1\text{|}X\right)=Target$

where $\widetilde{P_A}\left(Y=1\text{|}X\right)=\text{exp}\left({\alpha }_{Target}+{\alpha }_A+{\beta }^{\prime }X\right)$ .

This method, while used in the above example to reach a target such as the overall probability for source A or source B, can also be generalized to any target. In Demosim, to modify the assumption by changing the base rates (the target to be reached), a new adjustment specific to the desired target can simply be calculated. This type of adjustment can also be adapted to other types of regressions.

This method of calibrating the model makes it possible to preserve the odds ratios of the regression model while accurately reaching the target, assuming a population whose composition does not change from the start of the projection. Therefore, this method makes it possible to maintain compositional effects that may arise during the projection. As well, since the target set by the base rates is reached by adjusting the y-coordinate at the origin of the regressions, it limits the probabilities to no more than 100%, regardless of target. That also means that relative differences are maintained during the projection in terms of odds ratios (for logistic regression) or risk ratios (for proportional risk regression).

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Mortality

The mortality module has a similar structure to the fertility module, as it also uses base rates combined with relative mortality risks obtained through regressions models (see Box 3). The mortality module aims to simulate the future number of deaths, taking into account the differences between the projected groups. Owing to the lack of a single, comprehensive source of data, in Demosim’s previous projections of the Indigenous populations (Statistics Canada, 2015-1), relative mortality risks for the Indigenous groups (First Nations people, Métis, and Inuit) were modeled using a combination of both different data sources and methodology. The methods used this cycle, however, are consistent across all demographic groups. This is attributable to the use of the 2006 and 2011 Canadian Census Health and Environment Cohorts (CanCHECs)^Note as the sole data source in the computation of relative risks. These CanCHECs were used to follow-up on a five-year period following the census date.

The CanCHECs are probabilistically-linked datasets that combine information from the long-form censuses or the National Household Survey (NHS) with death data from the Canadian Vital Statistics Death Database (CVSD). Beginning with the 2006 CanCHEC, the age criteria for inclusion in the cohort was extended from only those aged 19 or older to all individuals aged 0 or older on census day, allowing the computation of mortality parameters for all relevant ages within Demosim.^Note

The base rates consist of projected age- and sex-specific mortality rates obtained from the most recent national population projections (Statistics Canada, 2019-2). For individuals aged 0 to 90, the base rates are combined with the results of proportional hazards regressions (Cox models) calculated from the CanCHEC data, stratified by sex. These regressions estimate the relative risk of death by various characteristics: Indigenous group, Registered or Treaty Indian status, residence on or off reserve, residence in an Inuit region, visible minority group, time elapsed since immigration, education level, region of residence, ^Note and age group.

The models were not stratified by age group, and instead included interactions between certain variables and age in order to account for potential differences in their impact on mortality outcomes. For individuals aged 91 and above, no relative risks were applied to the base rates. Results of regression models fit to these ages demonstrated little to no relationship between selected variables and mortality risks.

Internal migration

The purpose of the internal migration module is to simulate migratory movements among the 85 geographic regions in Demosim, taking into account the main characteristics included in the projection.

Two types of migrations are modelled:

1. Interregional migration refers to migration between the 52 main regions of the model;
2. Intraregional migration pertains to migration between on- and off-reserve parts^Note , or between parts inside and outside Inuit Nunangat within each of the main regions where these distinctions exist.

Modelling internal migration includes several steps. The first steps aim to estimate interregional and intraregional migration based on the relationship between place of residence one year earlier and current place of residence (also known as one-year mobility in the census) contained in a database consisting of the 2001, 2006, and 2016 censuses, and the 2011 NHS, to which a constant geography, based on the geographical limits defined in the 2016 Census, has been applied.^Note

Interregional migration modelling is broken down into nine distinct flows that take into account both the place of origin and the destination of migrants. This approach, which involves breaking migration flows into different paths, has the advantage of increasing flexibility when implementing assumptions. For example, it becomes easy to set specific migration levels to and from Indian reserves.

Here is a summary of these nine flows:

1. migration from an off-reserve region outside Inuit Nunangat (ORROIN) to another ORROIN;
2. migration from an ORROIN to a reserve region (RR);
3. migration from an ORROIN to an Inuit Nunangat region (INR);^Note
4. migration from a RR to an ORROIN;
5. migration from a RR to another RR;
6. migration from a RR to an INR;
7. migration from an INR to an ORROIN;
8. migration from an INR to a RR;
9. migration from an INR to another INR.

With respect to interregional migration between two ORROINs (by far the most frequent), the probabilities of leaving each of the regions are estimated using complementary log-log regression models based on a large number of individual characteristics: age group, education level, Indigenous group, Registered or Treaty Indian status, immigrant status, time elapsed since immigration, marital status, place of birth, generation status, visible minority group, number of children at home, age of the youngest child at home, mother tongue, language spoken most often at home, and knowledge of official languages.^Note

Migrants who leave an ORROIN for another ORROIN are assigned a destination region based on probabilities estimated using a series of logistic regression models and transition matrices. Regression models first determine whether the migrants will settle in a francophone region and, if so, whether they will settle in a predominantly francophone region.^Note The models are stratified by immigrant status and by whether the place of residence is in or outside a francophone region, and take into account the same variables used to estimate the probability of leaving a region. The specific destination region is ultimately determined from among the 50 available regions^Note using matrices that take into account the region of origin, place of birth, mother tongue, Indigenous group, Registered or Treaty Indian status, visible minority group and age.

For the other types of interregional migration flows, the probability of leaving a region is calculated from migration rates detailed by Indigenous identity and, when the data allowed it, by age group and education level. Matrices classified by region of origin and, when the data allowed it, by Registered or Treaty Indian status or Indigenous group are then used to determine the specific region of destination among all possible destinations.

Intraregional migration is simulated using migration rates specific to each combination of origin, destination, Indigenous identity, and, when the data allowed it, age group and education level.

Up until now, the calculation of migration parameters used census one-year-mobility data. The next steps involve applying a series of adjustments to the regression model results, migration rates and origin-destination matrices in order to have the migration parameters reflect the net migration observed using the census five-year-mobility variable. The idea is that if the one-year-mobility variable accurately captures the characteristics of migrants that are unlikely to change in the space of a single year, the calibration to the five-year-mobility variable anchors the intensity of migratory movements and their directions on greater numbers and longer periods, which reduces the weight of short-term and singular phenomena that are unlikely to reoccur in the future. The calibration ensures that the contribution of net internal migration to regional population growth reflects the average trends observed over the selected reference periods. Most of the adjustments were calculated using the same database used for the previous steps, based on the relationship observed between the census one-year-mobility and five-year-mobility information.

A recent study that explored the possibility of using linkages between censuses to analyze migration to and from Indian reserves showed that the retrospective information on place of residence five years before the census/NHS had several limitations that could affect the quality of migration flow estimates (Morency et al. 2021). The study also showed that estimates of the size of these flows seemed more adequate when measured from information about the place of residence obtained from two consecutive censuses. For this reason, the calibration of migration rates and origin-destination matrices related to migration to and from reserves based on the five-year-mobility data was carried out using linkages between the 2006 and 2011 short-form censuses and between the 2011 and 2016 short-form censuses.

Emigration

The purpose of the emigration module^Note is to project net emigration, which is defined according to the components of Statistics Canada’s Demographic Estimates Program (DEP) as the sum of emigration and net temporary emigration, minus return emigration. The emigration module has a similar structure to the fertility and mortality modules, as it combines base rates and regression results (see Box 3) for the population aged 18 and older, making it possible to take into account several characteristics, in particular immigrant status, which is known to be a predisposing factor for emigration.^Note For the population aged 18 and older, the base emigration rates were calculated by age and sex at the national level by dividing the net number of emigrants, as estimated by Statistics Canada’s DEP from 2002/2003 to 2011/2012, by the population (excluding non-permanent residents^Note ) from the same source for the same period.^Note They are combined with the results of a proportional hazards regression model (Cox model) that uses a linkage between the Longitudinal Administrative Databank and the Longitudinal Immigration Database from 1995 to 2010 to estimate the propensity of the adult population to emigrate, by country/region of birth, period of immigration, province or territory of residence, age and sex.

For the population aged 17 and younger, net emigration rates were calculated by age, sex, and province or territory using population estimates for 2002/2003 to 2011/2012.

Registration on the Indian Register and registration category amendment over an individual’s lifetime

The modules involving registration on the Indian Register have three separate purposes: 1) to model registrations that may occur during an individual’s lifetime^Note as a result of legislative amendments; 2) to model the registration category amendments from 6(2) to 6(1) that may occur during an individual’s lifetime;^Note and 3) to model the late registration of individuals who were entitled to registration at birth.

1. The legislative amendments that could cause individuals to register during their lifetime are the 1985 amendments of the Indian Act (Bill C-31), the Gender Equity in Indian Registration Act (Bill C-3) which came into effect as of January 2011, as well as S-3: An Act to amend the Indian Act in response to the Superior Court of Quebec decision in Descheneaux c. Canada (Procureur général) (Bill S-3). The latter came into force in two phases, the first of which started in December 2017 and the second in August 2019. For these legislative amendments, target numbers of registrations by year of registration were estimated. From May 2016 to January 2021, target numbers were calculated from the actual registrations recorded on the Indian Register.^Note For subsequent years, when very little data are available, the target numbers are derived from projection assumptions, which are described in the “Assumptions” section of this document. Once the targets had been determined, the individuals in the base population who were likely to register under these legislative amendments were identified from among those who did not have Registered or Treaty Indian status (according to distributions specific to each bill), and then their time of registration was determined in advance.^Note The majority of individuals selected in this way were initially First Nations people without Registered or Treaty Indian status.
2. Amendments from registration category 6(2) to category 6(1) may result from the application of Bill C-3, Bill S-3 or for various other reasons.^Note Category amendments from 6(2) to 6(1) arising under C-3 or S-3 were modelled using a method similar to the one just described for registration under legislative amendments, except the target numbers by year of the change and other characteristics specific to each of these two bills were determined only from the category amendments that occurred from May 2016 to January 2021 based on the Indian Register. Thus, for the following years, the assumption was made that there would be no further category amendments under C-3 or S-3. For other registration category amendments from 6(2) to 6(1), annual category amendment numbers by sex and place of residence were calculated based on the average of the data from 2007 to 2017 from the Indian Register. These are assumed to be constant throughout the projection.
3. The late registration of individuals entitled to registration on the Indian Register at birth is modelled separately for children and adults. For children born during the simulation, the modelling is done in two steps. First, in order to identify individuals potentially subject to this type of registration, we determine which of the simulated births will be entitled to registration on the register.^Note Entitlement depends on the mother’s registration category, whether or not she was in a mixed union at the time the child was born, and the rules of transmitting Registered or Treaty Indian status. Those entitled to registration but not having a Registered or Treaty Indian status at birth are assigned a probability of registering on the Indian Register that depends on their age and whether or not they live on an Indian reserve. The probabilities were derived so that they can reproduce the progression by age observed in the 2016 Census of the proportion of children with a Registered or Treaty Indian status among children who are in principle entitled to register—namely the children with two parents who are Registered or Treaty Indians, or with one parent who is in registration category 6(1).^Note Late registration rates derived from the same data are also applied to some children aged 0 to 2 years in the base population. Among adults aged 19 or older, a number of late registrations occur during the projection process among the at-risk population by age group and sex. The annual number of late registrations modelled is the average annual number of registrations of this type from 2007 to 2017, based on the Indian Register.

Intragenerational ethnic mobility of Indigenous people

The purpose of the Indigenous intragenerational ethnic mobility module^Note is to simulate changes in the reporting of Indigenous group from one census to the next, a phenomenon that is behind a significant share of the increase in the number of Métis and First Nations people observed at least since 1986 in Canada.^Note The parameters of the intragenerational ethnic mobility of Indigenous people were calculated using a residual method applied to data from the 1996, 2001, 2006, and 2016 censuses, and the 2011 NHS, adjusted for net undercoverage. It involves calculating the share of the residual growth of a given Indigenous group after the share that can be obtained through fertility, mortality and net migration have been taken into account, for each five-year period. This residual growth is interpreted as resulting from changes in the Indigenous group reported in the censuses (or the NHS). The net gains in Métis and First Nations people obtained this way were divided by the population that was non-Indigenous, non-immigrant and that did not belong to a visible minority group at the start of the period to obtain probabilities of an individual joining the First Nations or Métis group over five years, taking into account age and region of residence. Sets of probabilities were computed for four periods (1996 to 2001, 2001 to 2006, 2006 to 2011 and 2011 to 2016)^Note and it is possible to combine them to prepare various projection assumptions.

Change in education level

The last event projected using waiting times is change in education level. Probabilities associated with this event were derived by combining 2001 General Social Survey (GSS) and 2016 Census data adjusted for net undercoverage which, together, include the information required for the projection. First, probabilities of change in education level by year of birth, age, sex, and immigrant status were obtained by fitting logistic regression models to retrospective data from the 2001 GSS. Alignment factors were then calculated to ensure that the previously calculated probabilities make it possible to accurately reproduce the distributions obtained from the 2016 Census for a number of key characteristics. These alignment factors help calibrate the education level of cohorts on the data from the 2016 Census by sex and immigrant status, and take into account the differences in terms of education that exist with respect to individuals’ province or territory of birth, visible minority group, Indigenous group, Registered or Treaty Indian status, and the registration category on the Indian Register.

Characteristics imputed annually

Some components of Demosim are not meant to project events but rather to impute certain characteristics to individuals, including marital status, head-of-family and head-of-household status as well as labour force participation. These characteristics are assigned once a year on a fixed date.

Marital status

Marital status is projected mainly for its use in determining other events during the simulation, particularly fertility, to which it is closely related.

The marital status module is derived from logistic regression models that are estimated using data from the adjusted 2016 Census for the population aged 15 and older. The initial models determine whether or not the individual is in a union. If the individual is in a union, other models determine the type of union (married or common law). Models are stratified by sex and by having or not having an Indigenous identity. They take into account age, education level, number of children at home and the age of the youngest child, immigration status, citizenship status, place of birth, mother tongue, language spoken most often at home, visible minority group, Indigenous group, Registered or Treaty Indian status and the registration category on the Indian Register, as well as place of residence (province or territory, in or outside a census metropolitan area, on or off reserve, or inside or outside Inuit Nunangat).

The probabilities derived from these models evolve during the projection based on trends observed in the 2011 NHS and 2016 Census (adjusted), which showed an increasing propensity for couples to live in a common-law union. The marital status module finds its complement in the mixed union parameters that are used to assign characteristics such as Registered or Treaty Indian status to newborns (see the “Creation of individuals during the simulation” section).^Note

Head of household

A head-of-household status^Note is assigned to individuals annually to obtain a projection of the number of private households by certain characteristics, including Indigenous composition.^Note The headship rate method^Note is used to establish a relationship between the number of heads of household and the population, by certain characteristics of the projected population. This rate is then multiplied by the projected population to obtain a future number of private households.

For the purposes of these projections, different types of households were identified in the data from the 2016 Census according to a combination of household characteristics (Indigenous composition, household size and the presence of individuals younger than 19 years of age, etc.^Note ). The number of heads of household for each type by age group, Indigenous group, Registered or Treaty Indian status, marital status and place of residence was determined and then divided by the total population with the same characteristics to obtain headship rates for use in the annual imputation of head-of-household status during the simulation.^Note

Head-of-household status is used strictly to derive a number of households. It is not used as a determinant of other events during simulation. The same holds true for labour force participation.

Labour force participation

The purpose of the labour force participation module is to impute a status to individuals aged 15 and older regarding their labour force participation. The module has been designed to take into account differences in labour force participation among the various groups projected (for example, Indigenous people, visible minority groups, and immigrants). It includes two sets of parameters.

The first is composed of labour force participation rates by sex and age group taken from Labour Force Survey (LFS) data. The parameters are then adjusted to take into account populations excluded from the survey, in particular Indian reserves.

The second is composed of the results of logistic regressions that estimate (separately by sex and age group) the probability of being in the labour force by the following variables: Indigenous group, Registered or Treaty Indian status and registration category on the Indian Register, visible minority group, immigrant status, time elapsed since immigration, immigrant admission category, generation status, marital status, presence of children and age of youngest child, education level, knowledge of official languages, citizenship status and place of residence. The logistic regressions use data from a file that combines data from the 2016 Census and the 2011 NHS (adjusted). Each January 1 in the simulation, these two sets of parameters are combined to determine the labour force participation (in the labour force or not in the labour force) for the upcoming year.

Creation of individuals during the simulation

Aside from individuals in the Demosim base population, individuals may be added to the population during the simulation as a result of births, immigration, and the arrival of non-permanent residents. New individuals are added by creating complete records, that is, records having all the characteristics required for them to be projected by Demosim. The process for assigning characteristics to new individuals is described below.

Creation of newborns

The creation of newborns from births occurring after the start of the simulation requires the use of methods that differ according to the characteristic to be assigned to new individuals. First, a number of characteristics can be assigned deterministically to newborns, such as marital status (not in a union), education level (less than high school), immigrant status (non-immigrant), Canadian citizenship (Canadian citizenship at birth), etc.

Other characteristics are instead assigned probabilistically. The sex of the child is determined by applying a sex ratio of 105 boys born for every 100 girls, as has been observed in Canada and in many other populations around the world for several decades.

For the visible minority group and the Indigenous group, assignment is based on parameters derived by applying the own-children method to the adjusted data from the 2016 Census. Once the youngest children are linked to the woman in the census or NHS most likely to be their mother, it becomes possible to calculate the probability that the child has certain characteristics based on those of their mother (see the characteristics considered in Table 4). Transition matrices and vectors were created for assigning visible minority group and Indigenous group.



The methods for assigning Registered or Treaty Indian status, registration category on the Indian Register and generation status differ from the methods above by indirectly taking into account information about the child’s father. Births in Demosim are generated by women, and women are not associated with a spouse. Therefore, it is not possible to directly know the father’s characteristics at the time of birth. However, spousal characteristics may be associated with mothers through mixed unions. This is done in Demosim when a child is born.

A first mixed-union module determines whether the mother is in a union with a category 6(1) Registered or Treaty Indian, a category 6(2) Registered or Treaty Indian or an individual not having Registered or Treaty Indian status. The probability that the mother is in one of these types of unions is estimated using a file derived from adjusted 2016 Census microdata that—by using information on the relationship among members of the same census family—links women in a union who gave birth during the previous year to their spouse and their children. The probabilities are calculated based on the mother’s marital status, Registered or Treaty Indian status combined with registration category on the Indian Register, region of residence (on or off reserve) and province or territory of residence, and the child’s Indigenous group and visible minority status.

Probabilities were also calculated using the 2011 NHS to establish trends related to mixed unions by Registered or Treaty Indian status combined with the registration category on the Indian Register and the fact of living on or off reserve. Registered or Treaty Indian status (including the registration category) is then assigned to newborns probabilistically, using transition matrices that take into account the mother’s type of mixed union, as well as other characteristics of the mother and the child (Table 4).^Note

An additional adjustment factor is applied to the probabilities of women being in a union with a Registered or Treaty Indian to take into account new registrations and registration category amendments from 6(2) to 6(1) (see the section “Registration on the Indian Register and registration category amendment over an individual’s lifetime”) that occurred during simulation and that cannot be accounted for in the 2016 Census data. This adjustment factor is necessary to increase the likelihood of having Registered or Treaty Indian status transmitted to children born during the simulation. The magnitude of this adjustment factor depends on the number of new registrations and category amendments that occurred during the simulation.

A second mixed-union module uses the same data source to calculate the probability that the woman is in a union with a spouse whose immigrant status is identical or different to her own at the time the child is born in order to determine the child’s generation status. The module includes a series of logistic regression models that take into account age, education level, visible minority group, Indigenous group, time elapsed since immigration, age at immigration, immigrant category, generation status, citizenship status, mother tongue and language spoken most often at home, knowledge of official languages, number of children at home and age of the youngest child and place of residence (province or territory, in or outside a census metropolitan area and on or off reserve).^Note

Generation status is then assigned to the newborn as follows: the newborn is considered second generation if the mother is an immigrant not in a mixed union, 2.5 generation if the mother is in a mixed union, and third generation or higher if the mother is not an immigrant and not in a mixed union.

Immigration

Immigration also involves the creation of individuals possessing all the characteristics required for their simulation following their arrival in Canada. This module includes two main dimensions.

First, a predetermined number of newcomers is added annually to the projected population.

Second, the characteristics of new immigrants are determined using a donor imputation method, with donors being selected from among the immigrants in the Demosim base population. The result is a projected immigrant population whose composition is representative of the immigrant population of the donor pool (which itself may be a subset of the immigrant population, for example recently admitted immigrants). Adjustments are also made to some of the characteristics that are likely to have changed between the time of immigration and the time of the 2016 Census—the survey on which Demosim is based—so that they will be as close as possible to what they were at the time of arrival. For instance, when a new immigrant is created, the age assigned to the new immigrant is the donor’s age at immigration (and not the donor’s age in the 2016 Census); the marital status is imputed on arrival using Demosim’s annual marital status imputation parameters; and education on arrival is imputed by Demosim’s education module.

Non-permanent residents

The final Demosim component that requires the creation of individuals is the arrival of new non-permanent residents. This component functions similarly to immigration. Like immigrants, non-permanent residents are projected in two steps: (1) determining an annual net gain in non-permanent residents; and (2) imputing the characteristics of the new non-permanent residents using donors who are selected from among non-permanent residents in the Demosim base population.

Because of its special characteristics, the non-permanent resident population is processed separately in Demosim. Individuals are non-permanent residents for only a short time and there is almost no information available on the propensity of non-permanent residents to experience the events simulated. Therefore, and to maintain consistency with Statistics Canada’s population estimates data on non-permanent residents (annual net change), it is assumed that composition of the non-permanent resident population is perfectly stable. To achieve this, members of this population do not experience any of the events simulated except for fertility, since children born in Canada of non-permanent residents become Canadian citizens at birth. Thus, the assumption is made that each departing non-permanent resident is immediately replaced by the arrival of a new non-permanent resident with the same characteristics as the one who just left. The resulting stability is echoed by the data, at least regarding the composition of this population by age, sex and place of residence, in spite of slight variations from one period to the next.

Assumptions

As is true in any prospective exercise, these population projections were made on the basis of assumptions on the components of population growth. Assumptions were developed not only for Indigenous populations, but also for non-Indigenous populations, which are part of the projections. They were selected to meet the following objective: to create scenarios comprising a plausible range of possibilities for Indigenous populations until 2041.

The assumptions were developed by Statistics Canada in consultation with Indigenous Services Canada (ISC) and based on an analysis of the latest data, existing literature and consultations conducted by Statistics Canada.

The objective of this section is to provide a description and rationale for the main assumptions selected for this projection exercise. Particular attention is given to the description and rationale for the assumptions having the greatest impact on the evolution of Indigenous populations and households in Canada.

Table 5 offers a short description of the assumptions related to Indigenous populations for each of the main components of the projection model. Because they exert a strong influence on the growth of Indigenous populations, three distinct assumptions were developed for the components of fertility, mortality, intragenerational ethnic mobility, and registration on the Indian Register.



Fertility

The fertility of Indigenous women decreased over the second half of the 20th century, in both the population with Indigenous ancestry and the population with Registered or Treaty Indian status (Ram 2004; Guimond and Robitaille 2009; Maynard and Kerr 2007; Loh and George 2003). However, the last 15 years were marked by a relative stability of Indigenous fertility (Morency et al. 2018; Morency and Caron-Malenfant 2014; Statistics Canada 2011; Amorevieta-Gentil et al. 2013). Morency et al. (2018) showed that the fertility rate of the various Indigenous groups followed the same trends as those observed for the Canadian population as a whole, such that the gaps between groups remained relatively constant, with the exception of the Métis without Registered or Treaty Indian status and Registered or Treaty Indians living off Indian reserves, for which a rapid convergence of fertility to that of non-Indigenous people was observed between 2011 and 2016.

In 2016, the fertility of Indigenous populations remained higher than that of non-Indigenous populations, although the situation varies from one Indigenous identity group to another. The total fertility rate (TFR) of the Indigenous identity population as a whole in 2016 was 1.9 children per woman compared with 1.6 for the non-Indigenous population. Among the categories of the Indigenous identity classification that gives precedence to the Registered or Treaty Indian status, the Inuit without Registered or Treaty Indian status and Registered or Treaty Indians had the highest fertility at 2.8 and 2.2 children per woman, respectively. The total fertility rate of the Métis without Registered or Treaty Indian status was similar to that of the non-Indigenous population at 1.6 children per woman, while it remained lower for First Nations people without Registered or Treaty Indian status at 1.5 children per woman.

It is difficult to determine with certainty whether the above-noted recent convergence of the fertility of Métis without Registered or Treaty Indian status and Registered or Treaty Indians living off reserve with that of the non-Indigenous population is due to a real trend change or to a change in the composition of these two groups. For example, we know that between 2011 and 2016, intragenerational ethnic mobility had a significant impact on the composition of the Métis population and that the people who newly self-reported as Métis in the 2016 Census self-identified, for the most part, as non-Indigenous people in the previous census (O’Donnell and LaPointe 2019). As, in general, non-Indigenous women have a lower fertility than Métis women (Morency et al. 2018), this may have greatly contributed to the decrease observed in the fertility of Métis women between 2011 and 2016.

As for the population of Registered or Treaty Indians living off reserve, their number has also increased rapidly over this period because of a number of legislative changes that allowed many people (the vast majority living off reserve) to obtain Registered or Treaty Indian status (C-3, recognition of the Qalipu Mi’kmaq First Nation, etc.). These new registrants in the 2016 Census were, for the most part, either First Nations people without Registered or Treaty Indian status or non-Indigenous people in the previous census (O’Donnell and LaPointe 2019). As for the Métis, it is very likely that the fertility of these new registrants was lower than that of their new group, which could have significantly contributed to the decrease of the TFR for Registered or Treaty Indians living off reserve between 2011 and 2016.

In light of the above, it was assumed that the future evolution of the fertility of the various Indigenous populations will follow the same trajectory as that of the general population and that any convergence would be the result of a change in the composition of these populations. It was also assumed that the people who will change Indigenous identity (through intragenerational ethnic mobility) or who will obtain Registered or Treaty Indian status (following a legislative amendment) during the projection, will keep the fertility rate of their original group.

In the end, three distinct fertility assumptions were developed. This seemed justified given the magnitude of past fluctuations, as well as the importance of this component as a source of growth of the Indigenous population. These three assumptions are similar to those proposed in Statistics Canada’s most recent national projections (Statistics Canada 2019-2; Galbraith et al. 2019), to the extent that they propose a similar evolution of fertility rates by age (and TFR) over time.^Note That said, the observed rates were used for the projection from 2016 to 2019, which means that there is no difference between the three hypotheses over this period.^Note

These three assumptions have the advantage of taking into account both short- and long-term trends in the future evolution of fertility. Thus, in the early years of the projection, a very significant weight is given to the recent evolution of fertility in Canada, then fairly quickly, fertility rates converge with the various fertility targets (low, medium and high) that correspond to the values obtained from a survey conducted among demography and population study experts (Dion et al. 2019). Chart 1 shows the three fertility assumptions for the main Indigenous populations using the TFR as the indicator.

Data table for Chart 1



Table for Chart 1
Evolution of the total fertility rate by Indigenous identity (variant prioritizing the Registered or Treaty Indian status) and projection assumption, Canada, 2016 to 2041
Table summary
This table displays the results of Evolution of the total fertility rate by Indigenous identity (variant prioritizing the Registered or Treaty Indian status) and projection assumption. The information is grouped by Year (appearing as row headers), Low assumption, Medium assumption, High assumption, Registered or Treaty Indians, Without Registered or Treaty Indian status, First Nations people, Métis, Inuit and First Nations people , calculated using children per woman units of measure (appearing as column headers).

Year	Low assumption				Medium assumption				High assumption
	Registered or Treaty Indians	Without Registered or Treaty Indian status			Registered or Treaty Indians	Without Registered or Treaty Indian status			Registered or Treaty Indians	Without Registered or Treaty Indian status
		First Nations people	Métis	Inuit		First Nations people	Métis	Inuit		First Nations people	Métis	Inuit
	children per woman
2016	2.21	1.50	1.58	2.82	2.21	1.50	1.58	2.82	2.21	1.50	1.58	2.82
2017	2.15	1.46	1.54	2.73	2.15	1.46	1.54	2.73	2.15	1.46	1.54	2.73
2018	2.10	1.42	1.50	2.67	2.10	1.42	1.50	2.67	2.10	1.42	1.50	2.67
2019	2.05	1.39	1.47	2.61	2.05	1.39	1.47	2.61	2.05	1.39	1.47	2.61
2020	1.97	1.34	1.41	2.51	2.03	1.37	1.45	2.58	2.08	1.41	1.49	2.65
2021	1.93	1.31	1.38	2.46	2.01	1.36	1.44	2.56	2.10	1.42	1.50	2.67
2022	1.90	1.29	1.36	2.42	2.01	1.36	1.44	2.55	2.11	1.43	1.51	2.69
2023	1.88	1.28	1.35	2.39	2.00	1.36	1.43	2.55	2.13	1.44	1.52	2.71
2024	1.87	1.27	1.34	2.37	2.00	1.36	1.43	2.54	2.14	1.45	1.53	2.72
2025	1.86	1.26	1.33	2.36	2.00	1.36	1.43	2.55	2.15	1.46	1.54	2.74
2026	1.85	1.25	1.32	2.35	2.00	1.36	1.43	2.55	2.17	1.47	1.55	2.76
2027	1.85	1.25	1.32	2.35	2.01	1.36	1.44	2.56	2.18	1.48	1.56	2.77
2028	1.84	1.25	1.32	2.34	2.02	1.37	1.44	2.56	2.20	1.49	1.57	2.79
2029	1.84	1.25	1.32	2.34	2.02	1.37	1.45	2.57	2.21	1.50	1.58	2.81
2030	1.84	1.25	1.32	2.35	2.03	1.38	1.45	2.58	2.23	1.51	1.60	2.83
2031	1.85	1.25	1.32	2.35	2.04	1.38	1.46	2.60	2.25	1.52	1.61	2.86
2032	1.85	1.25	1.32	2.35	2.05	1.39	1.47	2.61	2.26	1.53	1.62	2.88
2033	1.86	1.26	1.33	2.36	2.06	1.40	1.48	2.62	2.28	1.55	1.63	2.90
2034	1.86	1.26	1.33	2.37	2.08	1.41	1.49	2.64	2.30	1.56	1.65	2.93
2035	1.87	1.27	1.34	2.38	2.09	1.42	1.50	2.66	2.32	1.57	1.66	2.95
2036	1.88	1.27	1.34	2.39	2.10	1.43	1.51	2.67	2.34	1.59	1.68	2.98
2037	1.89	1.28	1.35	2.40	2.12	1.44	1.52	2.69	2.36	1.60	1.69	3.00
2038	1.90	1.29	1.36	2.41	2.13	1.45	1.53	2.71	2.38	1.62	1.71	3.03
2039	1.91	1.29	1.36	2.42	2.15	1.46	1.54	2.73	2.40	1.63	1.72	3.06
2040	1.92	1.30	1.37	2.44	2.17	1.47	1.55	2.75	2.43	1.65	1.74	3.09
2041	1.93	1.31	1.38	2.45	2.18	1.48	1.56	2.78	2.45	1.66	1.75	3.12
Note: The total fertility rates shown in this figure are theoretical targets. In practice, changes in the composition of the population could cause the projected values to diverge. Source: Statistics Canada, Centre for Demography.

Transmission of the Indigenous group from mother to child

Strongly linked to mixed unions (Boucher et al. 2009; Robitaille and Guimond 2003), the likelihood of parents reporting for their children an Indigenous group different from their own (also known as intergenerational ethnic mobility) varies from one Indigenous group to another. According to adjusted 2016 Census data, 91% of children aged under one whose mother is an Inuk are also Inuk. The proportions were 88% among the First Nations people and 67% among the Métis. Compared with estimates obtained for previous projections (Statistics Canada 2015-1), this phenomenon has remained highly stable in recent years. Therefore, a single assumption was used for this component, namely that the rates of intergenerational ethnic mobility remain at their 2016 levels until 2041.

Transmission of Registered or Treaty Indian status and registration category from mother to child

The intergenerational transmission of Registered or Treaty Indian status and of the registration category is governed by rules set out in the 1985 Indian Act (see the “Key concepts related to Indigenous populations” section). However, children entitled to registration are not registered automatically at birth; rather, the parents must complete a process with the department in charge of the Indian Register.

According to adjusted 2016 Census data, about 66% of children aged under one with at least one Registered or Treaty Indian parent are themselves Registered or Treaty Indians. This proportion varies according to the Registered or Treaty Indian status of each parent and whether or not the child belongs to an Indigenous group (Table 6). The proportion is highest when both parents are Registered or Treaty Indians, whether or not the child belongs to an Indigenous group, while it is virtually nil when neither parent is a Registered or Treaty Indian. In cases where only one parent is registered (mixed unions), the proportion falls in between and is little affected by the sex of the registered parent. For each type of union and Registered or Treaty Indian status of the mother, the proportion of registered children is higher when the child belongs to an Indigenous group—which, of course, depends on the mother’s Indigenous group.



The analyses carried out as part of these projections also revealed that the propensity to be in a mixed union among women in a union who gave birth to a child between 2015 and 2016 was higher, off Indian reserves, among registered women (the propensity being greater among category 6[2] than among category 6[1] women), and, on Indian reserves, among non-registered women, in particular. This propensity varied slightly from 2011 to 2016, increasing among women registered under category 6(2) or non-registered women living off reserve, decreasing among women registered under category 6(1) living off reserve, and decreasing among non-registered women living on Indian reserves.

While the objective and legal nature of the rules of transmitting Registered or Treaty Indian status might suggest a certain stability in the propensity of transmitting Registered or Treaty Indian status across generations, the future evolution of this propensity will depend mainly on changes in the prevalence of women entering into unions with spouses of different status. For this reason, it is assumed that the transmission rates of Registered or Treaty Indian status from mother to child will remain at their 2016 level until 2041, and that trends with respect to mixed unions will gradually slow down over the next 25 years.

Mortality

Estimation of the life expectancy of the Indigenous population, and mortality more generally, is often challenging from a methodological standpoint. Measuring trends and estimating mortality rates most often requires the use of multiple data sources and numerous adjustments, which makes comparisons over time within and between groups quite difficult. Despite these obstacles, studies on the topic converge on the existence of large disparities in the mortality outcomes of the Indigenous and non-Indigenous populations. Tjepkema et al. (2019-2), for example, show that life expectancy at age 1 of the First Nations, Métis, and Inuit household populations was significantly lower than that of the non-Indigenous household population in 2011. For First Nations people, the gap was 9 years for males and 10 years for females; for Métis, it was 5 years, and for Inuit 11 years, for both males and females. As for infant mortality, Sheppard et al. (2017), using a data linkage between vital statistics and 2006 Census data to track the 2004-2006 birth cohorts, find that infant mortality rates were more than twice as high for each of these groups when compared to the non-Indigenous population.

In fact, the differences in mortality between these groups is often as large, if not larger, than differences observed when comparing to the non-Indigenous population, reflecting the diversity of these populations. Differences also exist between the provinces and territories. Katz et al. (2019) find notable differences in life expectancy at birth in 2012-2016 between First Nations people with Registered or Treaty Indian status living on reserves and those living off reserves, as well as between these two groups and the rest of the population in certain Regional Health Authorities in Manitoba, for example. At the national level, Feir and Akee (2019) demonstrate that the general reduction in male mortality observed in Canada between 1974 and 2013 was less pronounced among First Nations people with Registered or Treaty Indian status living on reserve than among those living off reserve.

While life expectancy at birth for both the total Canadian population and the Indigenous population (in groups for which these data are available)^Note has increased in recent decades, there is little in the literature to suggest convergence in the mortality rates of the Indigenous and non-Indigenous populations.^Note Theories surrounding the origin of this mortality gap center on potential differences in both access to health care services and quality of care, disparities in socioeconomic conditions, and differences in the geographical location of these populations (Katz et al., 2019; PHAC, 2018; Gilbert et al., 2015). The latter of these three has been shown to contribute significantly to widening gaps in post-neonatal mortality between the Indigenous and non-Indigenous populations in Quebec (Gilbert et al., 2015). Although the factors contributing to mortality differentials are not immutable, recent historical trends and the limited support found in the literature tend to invalidate the assumption of a possible convergence of mortality of the Indigenous population and the non-Indigenous population. For this reason, no assumption of convergence was made for these projections.

Three assumptions based on the low, medium, and high mortality assumptions presented in Statistics Canada’s latest national population projections (Statistics Canada, 2019-2) were developed for the Indigenous population. Each of these assumptions see gradual declines in age- and sex-specific mortality rates between 2016 and 2041, with the key difference being a less pronounced decline in the high mortality assumption than in the medium, and a more pronounced decline in the low assumption. Under all assumptions, the relative gap between the mortality rates of the Indigenous and non-Indigenous populations remains unchanged up to 2041. Estimates produced as part of these projections show that the life expectancy of Indigenous males and females appears to be shortest among the Inuit population, followed by Registered or Treaty Indians and First Nations people without Registered or Treaty Indian status, and then the Métis, whose life expectancy tends to be closest to that of the non-Indigenous population.

Internal migration

Relatively few studies have analyzed the internal migration of Indigenous populations. Among the few recent studies are those of Cooke and Penney (2019) and Clatworthy and Norris (2014) that used retrospective information on the place of residence one year or five years before the census or NHS to paint a picture of the migration of Indigenous populations. The two studies highlight the generally marginal nature of the contribution of migrations to changes in the proportion of Indigenous people living in certain types of regions, in particular, CMAs and the Inuit Nunangat regions. For example, in the CMAs, it is mainly intragenerational ethnic mobility and natural increase that influence the proportion of Indigenous people, whereas internal migration has a minor impact (Cooke and Penney 2019).

The two studies also show that Indigenous people have a greater propensity to migrate than non-Indigenous people, although differences observed between the two populations tend to decrease over time. Furthermore, Indigenous people are more likely to undertake an interprovincial migration than are non-Indigenous people. In terms of characteristics, the age composition of migration is fairly similar for Indigenous and non-Indigenous people and remains rather stable over time. Thus, migration rates are generally lower below age 20 and highest among the 20 to 34 age group. After age 35, migration rates decrease constantly with age. Overall, Indigenous women have higher migration rates than Indigenous men.

Among the various Indigenous identity populations, Registered or Treaty Indians and Inuit are the two least mobile groups, whereas Métis and First Nations people without Registered or Treaty Indian status have significantly higher migration rates. These observations remain true to a large extent from one census to another (Cooke and Penney 2019).

Indigenous identity populations often have specific migration patterns. For example, among Registered or Treaty Indians, there are relatively significant migration flows between reserves and off-reserve regions (especially toward CMAs). In this regard, many analyses based on retrospective information about the place of residence five years prior to the census or the NHS have shown that more Registered or Treaty Indians moved onto reserves than left them, a trend that has been observed for several decades (Cooke and Penney 2019; Cooke and O’Sullivan 2015; Clatworthy and Norris 2014; Norris and Clatworthy 2011).

However, a new study based on linkage files between the 2011 and 2016 censuses and the 2006 and 2011 censuses has shown that reserves very likely experienced migration losses in favor of urban and rural areas between 2006 and 2011 and between 2011 and 2016, in terms of both the total population and the Registered or Treaty Indian population alone (Morency et al. 2021).^Note

The Inuit population also has its own specific migration patterns. There are specific migration flows for the Inuit between Inuit Nunangat regions and outside Inuit Nunangat. However, Cooke and Penney’s (2019) analysis showed that these flows were relatively small and that the net result of these migrations has a marginal impact on the growth of populations in Inuit regions.

A single internal migration assumption was selected for these projections. It assumes an internal migration contribution to the growth of regions similar to that observed during the 1996 to 2016 period in the off-reserve regions, and similar to that observed during the 2006 to 2016 period on reserves. As for the composition of migrants, particularly with respect to Indigenous identity, this is modelled after the migration flows observed during the 2000 to 2001, 2005 to 2006, 2010 to 2011, and 2015 to 2016 periods (i.e. the observation periods of the census one-year-mobility variable).

International migration

According to data from the 2016 Census, among immigrants living in Canada, 7,500 declared an Indigenous identity, which represented less than half a percent of the total Indigenous population in Canada. In addition, two thirds of these immigrants were First Nations people born in the United States. As for emigrants with an Indigenous identity, although no estimate is available, it seems reasonable to assume that they are few. Given the low numbers involved and the absence of emigration data, it is assumed that no international migration, in or out, will occur among the Indigenous population during the projection, which is equivalent to assuming a zero international migration balance (at any age).

Intragenerational ethnic mobility

Changes in the reporting of an individual’s Indigenous group over their lifetime—i.e. intragenerational ethnic mobility—were responsible for a large part of the growth of Indigenous populations in Canada in recent decades (O’Donnell and LaPointe 2019; Statistics Canada 2015-1; Caron-Malenfant et al. 2014; Guimond et al. 2007; Guimond 1999). It is mainly the Métis, but also the First Nations people, who saw their populations grow through changes in the self-reporting of Indigenous group^Note (see Table 7). Over the quinquennial period from 2011 to 2016, this component made a very significant contribution to the population growth observed for these two groups (74% for the Métis and 58% for First Nations people). However, the same phenomenon appears almost non-existent among the Inuit and Indigenous populations living on Indian reserves and the territories.



Variations observed in the ethnic mobility rates from one intercensal period to another are considerable and highlight the unpredictability of the magnitude of this phenomenon. That said, it is plausible that all non-Indigenous people do not have the same probability of transferring to one Indigenous group or another over their lifetime. Thus, the future evolution of the ethnic mobility component could be linked not only to variations in transfer rates but also to changes in the size of the pool of people most likely to make these transfers.

One of the populations that seems particularly likely of making an ethnic transfer is the population reporting Indigenous ancestry^Note without, however, self-identifying to an Indigenous group on the census. The analysis of past censuses shows that the size of this population is maintained over time mainly because new people report having Indigenous ancestry from one census to another. Thus, according to census and NHS data, the number of people reporting Indigenous ancestry without reporting an Indigenous identity went from 503,000 in 2006 to 435,000 in 2011, and then to 457,000 in 2016. In other words, it does not appear that this potential pool of ethnic migrants is about to run out.

In light of the above, three distinct ethnic mobility assumptions are proposed. Each one assumes zero ethnic mobility among the Inuit throughout the projection period, as well as on reserves and in the territories.

According to the medium assumption, for each Demosim main region, net ethnic mobility rates (among Métis and First Nations people) correspond at the start of the projection (2016) to those observed during the intercensal period 2011 to 2016 and converge following a logarithmic curve to the average net rates of the past four intercensal periods, reaching this target in 2041.

The low and high assumptions are similar to the medium assumption, except that the initial net mobility rates correspond, respectively, to the lowest and highest ethnic mobility rates observed during the four most recent intercensal periods. In both assumptions, the rates then converge, linearly this time, to the average net rates for the four most recent periods. As with the medium assumption, the average net rates are attained in 2041.

Registration on the Indian Register and registration category amendment over an individual’s lifetime

The legislative framework that defines the population entitled to registration on the Indian Register has undergone a number of amendments since the Indian Act was passed in 1876.^Note Special agreements recognizing the right to registration of specific groups have also been made over time, such as the 2008 Agreement for the Recognition of the Qalipu Mi'kmaq Band. These changes have had and will continue to have an impact on the number of registrations on the Indian Register and the number of registration category amendments from 6(2) to 6(1). As part of the current projections of the Indigenous populations, three bills (C-31, C-3 and S-3) that amended the Indian Act were considered, as well as late registrations and other category amendments from 6(2) to 6(1) that are not the result of legislative amendments or special agreements.

The various amendments to the Indian Act passed in recent decades have had a considerable impact on the size of the Registered Indian population. Clatworthy (2001) estimates that, from 1985 to 1999, nearly 107,000 individuals were registered on the Indian Register under Bill C-31, which came into effect on April 17, 1985. According to Crown-Indigenous Relations and Northern Affairs Canada (CIRNAC) (2018), the adoption of the Gender Equity in Indian Registration Act (Bill C-3) in January 2011 resulted in 37,000 registrations from 2011 to 2017. Although most of C-31 and C-3 registrations occurred in the years immediately following the coming into force of those two bills, a small number of C-31 and C-3 registrations continues to take place each year. Using Indian Register data, it was estimated that 1,300 individuals residing in Canada were registered under Bill C-31 and 3,900 individuals under Bill C-3 during the period from the 2016 Census reference date (May 10, 2016) to December 31, 2020. In addition, just over 2,200 category amendments from 6(2) to 6(1) under Bill C-3 were made during that same period.

More recently, Bill S-3^Note came into force to eliminate the sex-based inequities in registration that had not been resolved by bills C-31 and C-3. The adoption of An Act to amend the Indian Act in response to the Superior Court of Quebec decision in Descheneaux c. Canada (Procureur général) occurred in two phases: on December 22, 2017, and August 15, 2019. The first phase of Bill S-3 implemented amendments to resolve sex-based inequities for certain issues specific to the period after September 4, 1951. Following consultations with First Nations, the second phase of Bill S-3 came into force and eliminated the 1951 cut-off, thus resolving inequities that had occurred since 1869, the year in which Indian women began to lose their right to registration if they married a non-Indian man under the Gradual Enfranchisement Act. A report on the review of Bill S-3 (ISC, 2020) describes the new provisions enacted under this bill as follows:

Given that the amendments made under S-3 broaden entitlement to registration to a potentially large number of individuals, this new bill could have a considerable impact on the growth of the Registered Indian population over the coming years. However, as indicated by ISC (2020), there is a great deal of uncertainty about that impact, especially for 1869 to 1951 because there are no data sources that make it possible to estimate the number of new individuals entitled to registration as a result of Bill S-3, since the Indian Register was created in 1951. Furthermore, many of those individuals may be unaware, for various reasons, that they have become entitled to registration under Bill S-3 or may have difficulty obtaining the necessary documents to prove their entitlement to registration. According to estimates by Clatworthy (2017) and the Office of the Parliamentary Budget Officer (2017), ISC (2020) estimated that the number of new registrations under S-3 could be 35,000 over five years for the first phase of the bill, and between 270,000 and 450,000 over 10 years for the second phase. However, it is also possible these new S-3 registrations could take place over a longer period than expected.

While previous bills had widespread impacts across the country, an agreement made in 2008 had a considerable impact on one province in particular. The Qalipu Mi’kmaq First Nation was established by order on September 22, 2011, and nearly 24,000 individuals were registered on the Indian Register between 2011 and 2013 as founding members, most residing in Newfoundland and Labrador. In June 2013, a supplemental agreement was made, intended to resolve challenges with the Founding Members List. From 2018 to 2021, the Founding Members List was amended with the addition of registered individuals, but these increases were offset by a slightly larger number of de-registrations.^Note In addition, some changes to registration categories occurred during this period, mostly changes from 6(1) to 6(2) resulting in fewer subsequent registrations.

Lastly, in addition to the legislative amendments and special agreements, individuals submit late registrations to the Indian Register every year (children in the first years after their birth represent a large portion) or have their registration category changed from 6(2) to 6(1) for various reasons.

In light of the above, it was decided to make only one assumption concerning registrations under bills C-31 and C-3, category amendments from 6(2) to 6(1) under bills C-3 and S-3, and late registrations and category amendments from 6(2) to 6(1) for various reasons. However, given the considerable uncertainty surrounding these registrations, three assumptions were made about the number of future registrations under Bill S-3. Lastly, no change associated with the establishment of the Qalipu Mi’kmaq First Nation was modelled in the projection.

Each assumption has two components. The first corresponds to a target number of registrations or registration category amendments. The second, which is based on the fact that the Demosim model projects the entire Canadian population, is intended to determine the composition of the population that will register or change registration category during the projection.

It is assumed that, from May 2016 to January 2021, the number of registrations under Bill C-31 (1,300) and under Bill C-3 (3,900) occurring during the projection corresponds to the number estimated directly from the Indian Register. A similar assumption is used for category amendments from 6(2) to 6(1) under Bill C-3 (2,200) and under Bill S-3 (20,200 and 24,600 for phases 1 and 2, respectively). Although some registrations are still likely to occur in the coming years under bills C-31 and C-3, as well as registration category amendments under bills C-3 and S-3, it is expected that the number will be low. Furthermore, amendments made to subsection 6(1) of the Indian Act in August 2019 make it more difficult to identify those registrations in the Indian Register data. For these reasons, these different types of registrations and category amendments are not modelled after January 2021.

Lastly, for the period from 2016 to 2041, constant rates of late registrations of children aged 0 to 2 years, an average number of 400 late registrations per year among adults aged 19 or older, and an average of 700 category amendments from 6(2) to 6(1) for various reasons per year are assumed. These annual figures are based on the average of Indian Register data from 2007 to 2017.

These new registrations on the Indian Register will have an impact on the Registered Indian population, but also on the population of First Nations people without Registered or Treaty Indian status, because it is assumed that First Nations individuals without Registered or Treaty Indian status will be the most likely to register on the Indian Register during their lifetimes. However, an exception is made for children aged 0 to 2 years simulated during the projection. Children at risk of late registration are non-registered children who are considered entitled to registration at birth, regardless of their Indigenous identity.

Given the considerable uncertainty surrounding future registrations resulting from Bill S-3, especially for phase 2, three assumptions were developed. From 2018 to 2041, the number of registrations under S-3 for phases 1 and 2 combined is assumed to be 34,000 for the low assumption, 66,000 for the medium assumption and 251,000 for the high assumption (for an illustration of the calculation used to arrive at these target numbers, refer to Table 8).

The low and medium assumptions are based on estimates of the number of individuals entitled to registration calculated from Indian Register data as of July 2016, which were 28,970 for phase 1 (Clatworthy, 2016-1; 2016-2; 2016-3) and 86,917 for the two phases of S-3 combined (Clatworthy, 2017). Since it is unlikely that the entire entitled population will actually register, an assumption is made of the effective registration rates. The low assumption consists of registration rates of 57% for phase 1 and 40% for phase 2, while the medium assumption consists of registration rates of 90% for both phase 1 and phase 2.

As for the high assumption, it is based on the estimate of 747,045 individuals who are not registered but who reported First Nations Indigenous ancestry (North American Indian) as a single or multiple response on the 2016 Census (Clatworthy, 2017). For phase 1, the assumption is the same as the medium assumption. For phase 2, a registration rate of 40% is applied to the residual entitled population (i.e., excluding those from phase 1).

Subsequently, since approximately 2% of the population registered on the Indian Register reside outside Canada, it is assumed that the same percentage applies to S-3 registrations, and the number of registrations is reduced accordingly in the three assumptions.

Lastly, it was assumed that all phase 1 S-3 registrations would occur during the projection, but only 80% of phase 2 S-3 registrations will have been completed by 2041. A registration timeline that is relatively similar to C-3 (for phase 1 of S-3) and C-31 (for phase 2 of S-3) was assumed, but with a slower and more gradual progression. For the period from 2018 to 2020, the number of registrations under S-3 corresponds to the number estimated directly from the Indian Register for the three assumptions (5,600 for phase 1 and 5,700 for phase 2).



For phase 1 of S-3 registrations, it was assumed that only individuals who reported that they are First Nations people without Registered or Treaty Indian status could register in their lifetimes. For phase 2, which covers the period since 1869 and consists of higher target numbers of registrations, it was assumed that the population likely to register is larger and more diverse. For the low and medium assumptions, it was assumed that new registrations will be distributed as follows: First Nations people without Registered or Treaty Indian status (85%), other Indigenous people with First Nations ancestry (5%) and non-Indigenous people with First Nations ancestry (10%). However, for the high assumption, the distribution of registrations among these three populations is set at 40%, 20% and 40%, respectively. This distribution was necessary in order to have a pool of individuals who are likely to register that is sufficiently large to obtain the selected target number of registrations.

Household headship rates

In Canada, studies revealed that headship rates for the Indigenous population are lower than those for the population as a whole, an expected consequence of the fact that the average size of Indigenous households is greater than that of non-Indigenous households (Statistics Canada 2015-1; Clatworthy 2012 and 2006; Ng and Perreault 1998; Kerr and Kopustas 1995). These analyses have also underscored the difficulty of establishing trends in this regard. As stated by Clatworthy (2012), it is difficult to determine whether changes in headship rates over time among the various Indigenous populations (especially Registered or Treaty Indians, First Nations people without Registered or Treaty Indian status and Métis without Registered or Treaty Indian status) are the result of actual changes in behaviour or simply changes in the composition of the population (for example, ethnic mobility, legislative amendments and specific agreements that impact registrations).

As part of these projections, trends affecting the evolution of headship rates from 2011 to 2016 were analyzed, revealing a slight increase in the headship rate over time. However, when these rates are standardized to account for the age of the household head, place of residence, Indigenous identity, marital status and household size, the trends recorded between 2011 and 2016^Note disappear almost completely. This means that the trends are largely the result of compositional effects related to the variables used in these projections. For this reason, headship rates are kept constant at the level observed in 2016 throughout the projection.

Other assumptions

The other assumptions developed for these projections deal with either components that contribute indirectly to the growth of Indigenous populations (for example, education and marital status) or components that more specifically affect non-Indigenous populations (for example, international migration). Each of these components was the subject of only one assumption, generally developed to reflect the most recent situation and trends and with the concern to be as consistent as possible with two other sets of Statistics Canada projections: (1) Population Projections for Canada (2018 to 2068), Provinces and Territories (2018 to 2043) (Statistics Canada 2019-2), whose assumptions underwent extensive consultation,^Note and (2) Immigration and Diversity: Population Projections for Canada and its Regions, 2011 to 2036 (Statistics Canada 2017-2), whose assumptions were also the subject of consultations. These assumptions stick as closely as possible to those selected for the M1 medium growth scenario of Population Projections for Canada (2018 to 2068), Provinces and Territories (2018 to 2043) for international migration, fertility and mortality for the population as a whole, and to the assumptions contained in the reference scenario of the publication entitled Immigration and Diversity: Population Projections for Canada and its Regions, 2011 to 2036 for the other components, in a version updated in light of the recent demographic context.

The main assumptions are as follows:

• The annual immigration rate fluctuates around 7.5 per thousand at the start of the projection and then climbs to more than 10.0 per thousand starting in 2022 before slowly converging to 8.3 per thousand at the end of the projection period;
• The net emigration is kept constant at the level recorded from 2002/2003 to 2011/2012 and emigration differences observed from 1995 to 2010 remain the same;
• Net non-permanent residents decline to zero over the projection horizon and the population composition of new non-permanent residents is representative of that observed in the 2016 Census;
• The fertility of the non-Indigenous population gradually decreases to 1.43 children per woman in 2023 then gradually reaches 1.56 children per woman in 2041;
• A moderate increase in life expectancy of the non-Indigenous population following trends observed from 1981 to 2016;
• The upward trend in population education gradually levels off and differences between Indigenous and non-Indigenous populations are maintained;
• Trends in marital status for both Indigenous and non-Indigenous populations gradually slow down;
• The visible minority group intergenerational transmission rates estimated from the 2016 Census.

Scenarios

For this set of projections, three scenarios were selected: a low-growth scenario, a medium-growth scenario, and a high-growth scenario (Table 9). These scenarios were chosen to obtain a plausible range of growth for the Indigenous populations over the period from 2016 to 2041.



Scenario 1 (low growth of the Indigenous populations) combines the assumptions of low fertility, low intragenerational ethnic mobility at the start of the projection, slow increase in life expectancy, and a low number of new registrations on the Indian Register as a result of Bill S-3.

Scenario 2 (medium growth of the Indigenous populations) combines the assumptions of medium fertility over the projected period, intragenerational ethnic mobility starting from the most recently observed levels (2011 to 2016), moderate increase in life expectancy, and a medium number of new registrations on the Indian Register as a result of Bill S-3.

Scenario 3 (high growth of the Indigenous populations) combines the assumptions of high fertility, high intragenerational ethnic mobility at the start of the projection, rapid increase in life expectancy at birth, and a high number of new registrations on the Indian Register as a result of Bill S-3.

It is important to note that a projection scenario is constructed for a specific purpose. Scenario 2 is the one that most accurately reproduces recently observed population trends while taking the most recent developments into account. As for scenarios 1 and 3, they, respectively, aim to generate the lowest and highest population growth for the Indigenous populations. These three scenarios provide a plausible range of Indigenous population growth and reflect the uncertainty surrounding the future evolution of fertility, intragenerational ethnic mobility, life expectancy at birth and the number of new registrations on the Indian Register as a result of the new Bill S-3.^Note Projection users are advised to consider this range rather than a single scenario.

In addition, using only one assumption for each of the components that affects the non-Indigenous population does not mean that the future evolution of non-Indigenous populations is not uncertain. This choice was made to estimate the percentage of the total population represented by Indigenous people under the three adopted scenarios, the growth of the rest of the population being equal. Future publications from this new version of Demosim will be more specific as to the potential growth of other groups within the rest of the population and will use scenarios different from the ones presented here.

Other scenarios can of course be developed, depending on the users’ needs. Statistics Canada can be contacted on this regard.

Cautionary notes

As in any forward-looking exercise, many sources of uncertainty can affect these projections. First there are those that are linked to the future evolution of the components. For instance, the intragenerational ethnic mobility and the number of future registrations on the Indian Register that will result from the adoption of the new Bill S-3 are two components for which the evolution is especially difficult to predict.

The potential impacts of the COVID-19 pandemic on the future demographic evolution of Indigenous populations are also difficult to predict (see Box 4 for more details on this topic). They could have affected and continue to affect fertility and mortality levels and hinder the migration movements of Indigenous populations over an undetermined period of time.

Start of text box 4

Box 4. Impact of COVID-19 on population projections

The COVID-19 pandemic has had an impact on the composition of the Canadian population and on the evolution of its growth, and will continue to do so in the future. Chief among these impacts are the deaths attributed to COVID-19, reflected in episodes of excess mortality in 2020 and 2021 (Statistics Canada 2021-7). The negative impact of these deaths on life expectancy, estimated at approximately five months in Canada, is non-negligible in light of the annual variations, most often positive, in life expectancy observed over the last decade (Dion, 2021). That said, since the spring of 2021, the trend in the number of deaths has been generally similar to the situation that prevailed before the pandemic, and life expectancy is expected to resume its upward course in the near future, as the population is vaccinated.

The pandemic could also impact fertility. A number of countries, such as Italy and France, saw the number of births decline a few months after the start of the pandemic (Wall Street Journal 2021). Studies have shown that, in the past, epidemics, disasters or wars have often been followed by a short-term decrease in fertility and recovery in the long term (Aassve et al. 2020). However, this trend was not noticeable in Canada at the time of writing this document.

In fact, to date, it has been immigration changes that have had the most impact on the evolution of the Canadian population. Border and travel restrictions put in place to stop the spread of COVID-19 caused the share of population growth due to international migration to drop from 85.7% in 2019 to 58.0% in 2020 (Statistics Canada 2021-8). That said, this component has a marginal influence on the size and composition of the Indigenous population and may therefore only affect the proportions of Indigenous people in Canada, through the effect of declining immigration on the size and growth of the non-Indigenous population.

Lastly, the pandemic could have impacted movements inside the country. However, current data does not allow this to be measured, especially with regard to Indigenous populations.

Clearly, the COVID-19 pandemic will leave a mark on the evolution of the Canadian population. However, at the time these projections were produced, this impact, depending on the component, was either quite uncertain, barely perceptible or fairly negligible, specifically with respect to Indigenous populations in Canada. For these reasons, the projection assumptions do not propose any special adjustment to account for the impact of COVID-19.

End of text box 4

Also, various data sources were used to prepare these projections, each with their own limitations. While data sources were selected and used with a view to obtaining the most reliable and robust parameters possible, it goes without saying that coverage of the target populations can vary from one source to another, and that parameters estimated on the basis of a sample surveys can show variability due to sampling error. Samples from Indigenous populations often being limited in size, estimates for these populations are subject to even greater variability. In other words, the population projections described here include several sources of uncertainty related to data sources.

Some variance is also associated with the Monte Carlo process used to calculate waiting times in the simulation model. The impact of this variance on the results, although relatively small compared with other sources of uncertainty present in the model, tends to increase as the projection moves through time and is more significant among highly modelled populations (for example, children born during the simulation).

For all the reasons raised above and to avoid giving a false impression of accuracy, all the projection results presented publicly are rounded to the nearest thousand.

Finally, the choice of assumptions and scenarios is not intended to predict the future, but rather to provide data users with a portrait of the Indigenous populations if certain conditions were met. The plurality of scenarios is intended to paint a plausible picture of what the future growth of the Indigenous population in Canada could be, given past data and trends as well as the most recent developments. For this reason, users of these projections are advised to consider a range of results from several scenarios rather than the results of a single scenario.

Projection users who want to know more about the Demosim model or obtain customized data can contact Statistics Canada’s Centre for Demography at the following email address: statcan.demography-demographie.statcan@statcan.gc.ca.

Bibliography

AMOREVIETA-GENTIL, Marilyn, David DAIGNAULT, Norbert ROBITAILLE, Eric GUIMOND and Sacha SENÉCAL. 2013. La fécondité des Indiennes inscrites du Canada entre 1986 et 2008. Report from the Groupe d’études sur la dynamique démographique des Indiens inscrits (GEDDII), University of Montréal, Demography Department.

AASSVE, Arnstein, Nicolo CAVALLI, Letizia MENCARINI, Samuel PLACH and Massimo LIVI BACCI. 2020. “The COVID-19 pandemic and human fertility”. Science. Volume 369. Issue 6502. Pages 370 to 371.

AKEE, Randall and Donna FEIR. 2018. Estimating institutionalization and homelessness for status First Nations in Canada: A method and implication. University of Victoria. Department Discussion Paper DDP1801. ISSN 1914-2838.

AYDEMIR, Abdurrahman and Chris ROBINSON. 2006. Return and Onward Migration Among Working Age Men. Statistics Canada catalogue number 11F0019.

BÉLANGER, Alain and Patrick SABOURIN. 2017. Microsimulation and Population Dynamics, an Introduction to Modgen 12. The Springer Series on Demographic Methods and Population Analysis. 192 pages.

BÉLANGER, Alain and Stéphane GILBERT. 2003. “The Fertility of Immigrant Women and their Canadian-Born Daughters”. Report on the Demographic Situation in Canada, 2002. Statistics Canada Catalogue number 91-209.

BOHNERT, Nora, Patrice DION and Jonathan CHAGNON. 2014. “Projection of Emigration”, in BOHNERT, Nora, Jonathan CHAGNON, Simon COULOMBE, Patrice DION and Laurent MARTEL (editors). Population Projections for Canada (2013 to 2063), Provinces and Territories (2013 to 2038): Technical Report on Methodology and Assumptions. Statistics Canada catalogue number 91-620.

BOUCHER, Alexandre, Norbert ROBITAILLE and Eric GUIMOND. 2009. “La mobilité ethnique intergénérationnelle des enfants de moins de 5 ans chez les populations autochtones, Canada, 1996 et 2001”. Cahiers québécois de démographie. Volume 38, number 2.

BRITISH COLUMBIA OFFICE OF THE PROVINCIAL HEALTH OFFICER AND FIRST NATIONS HEALTH AUTHORITY. 2018. Indigenous health and well-being.

CARON-MALENFANT, Éric. 2015. “Demosim’s Population Projection Model: Updates and New Developments”. Proceedings of Statistics Canada International Methodology Symposium 2014: Beyond traditional survey taking: adapting to a changing world.

CARON-MALENFANT, Éric and Alain BÉLANGER. 2006. “The Fertility of Visible Minority Women in Canada”. Report on the Demographic Situation in Canada, 2003 and 2004. Statistics Canada catalogue number 91-209.

CARON-MALENFANT, Éric, Patrice DION, André LEBEL and Dominic GRENIER. 2011. “Immigration et structure par âge de la population canadienne : quelles relations?”. Cahiers québécois de démographie. Volume 40, number 2.

CARON-MALENFANT, Éric, Simon COULOMBE, Eric GUIMOND, Chantal GRONDIN and André LEBEL. 2014. “Ethnic Mobility of Aboriginal Peoples in Canada between the 2001 and 2006 Censuses”. Population. Volume 69, number 1.

Clatworthy, Stewart J. 2001. Re-assessing the Population Impacts of Bill C-31. Ottawa, Indian and Northern Affairs Canada, Research and Analysis Directorate.

CLATWORTHY, Stewart J. 2006. “Projections of Aboriginal Households and Families for Canada, Provinces and Regions, 2001-2026”. Study produced by the Research and Analysis Directorate, Indian and Northern Affairs Canada, Ottawa.

CLATWORTHY, Stewart J. 2012. “Projections of Aboriginal Households and Families for Canada, Provinces and Regions, 2006-2031”. Study produced by the Directorate of Strategic Analysis, AANDC, Ottawa.

CLATWORTHY, Stewart J. and Mary Jane NORRIS. 2014. “Aboriginal mobility and migration in Canada: Trends, patterns and implications, 1971 to 2006”. In TROVATO, Frank and Anatole ROMANIUK (editors). Aboriginal Populations: Social, Demographic and Epidemiological Perspectives. The University of Alberta Press.

Clatworthy, Stewart J. 2016-1. Estimating the Population Impacts of a Proposed Legislative Remedy Concerning the “Cousins” Issue. Ottawa, Indigenous Affairs and Northern Development Canada.

Clatworthy, Stewart J. 2016-2. Estimating the Population Impacts of a Proposed Legislative Remedy Concerning the “Siblings” Issue. Ottawa, Indigenous Affairs and Northern Development Canada.

Clatworthy, Stewart J. 2016-3. Estimating the Population Impacts of a Proposed Legislative Remedy Concerning the “Enfranchised Children” Issue. Ottawa, Indigenous Affairs and Northern Development Canada.

Clatworthy, Stewart J. 2017. An Assessment of the Population Impacts of Select Hypothetical Amendments to Section 6 of the Indian Act. Ottawa, Indigenous and Northern Affairs Canada.

COOKE, Martin and Christopher PENNEY. 2019. “Indigenous Migration in Canada, 2006-2011”. Canadian Studies in Population. Volume 43, number 2.

COOKE, Martin and Erin O’SULLIVAN. 2015. “The Impact of Migration on the First Nations Community Well-Being Index”. Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-life Measurement. Springer. Volume 122, number 2. Pages 371 to 389.

CROWN-indigenous relations and northern affairs canada. 2018. Background on Indian registration. https://www.rcaanc-cirnac.gc.ca/eng/1540405608208/1568898474141 (accessed September 16, 2021).

CYR, André, Julien BÉRARD-CHAGNON, Patrice DION, Dominic GRENIER and Éric CARON-MALENFANT. 2010. From Traditional Demographic Calculations to Projections by Microsimulations. Workshop presented at the 2010 Statistics Canada International Methodology Symposium.

DESPLANQUES, Guy. 1993. “Mesurer les disparités de fécondité à l’aide du seul recensement”. Population. Volume 48, number 6.

DION, Patrice. 2021. “Reductions in life expectancy directly associated with COVID-19 in 2020”. Demographic Documents. Statistics Canada catalogue number 91F0015M.

DION, Patrice, Nora GALBRAITH and Elham SIRAG. 2019. “2018 Survey of Experts on Future Demographic Trends”. In CHAGNON, Jonathan, Patrice DION, Nora GALBRAITH, Elham SIRAG and Yu ZHANG (editors). Population Projections for Canada (2018 to 2068), Provinces and Territories (2018 to 2043): Technical Report on Methodology and Assumptions. Statistics Canada catalogue number 91-620.

DURAND, Claire, Yves-Emmanuel MASSÉ-FRANÇOIS, Michael SMITH and Luis Patricio PENA IBARRA. 2016. “Who is Aboriginal? Variability in Aboriginal Identification between the Census and the APS in 2006 and 2012”. Aboriginal Policy Studies. Volume 6, number 1.

FEIR, Donna and Randall AKEE. 2019. “First Peoples lost: Determining the state of status First Nations mortality in Canada using administrative data”. Canadian Journal of Economics. Volume52, number 2.

GALBRAITH, Nora. 2019. “Projection of Immigration”. In CHAGNON, Jonathan, Patrice DION, Nora GALBRAITH, Elham SIRAG and Yu ZHANG (editors). Population Projections for Canada (2018 to 2068), Provinces and Territories (2018 to 2043): Technical Report on Methodology and Assumptions. Statistics Canada catalogue number 91-620.

GALBRAITH, Nora, Patrice DION and Elham SIRAG. 2019. “Projection of fertility”. In CHAGNON, Jonathan, Patrice DION, Nora GALBRAITH, Elham SIRAG and Yu ZHANG (editors). Population Projections for Canada (2018 to 2068), Provinces and Territories (2018 to 2043): Technical Report on Methodology and Assumptions. Statistics Canada catalogue number 91-620.

GILBERT, Nicolas L., Nathalie AUGER and Michael TJEPKEMA. 2015. “Stillbirth and infant mortality in Aboriginal communities in Quebec”. Health Reports. Volume 26, number 2. Statistics Canada catalogue number 82-003-X.

GRABILL, Wilson R. and Lee Jay CHO. 1965. “Methodology for the Measurement of Current Fertility from Population Data on Young Children”. Demography. Volume 2, number 1.

GUIMOND, Eric. 1999. “Ethnic Mobility and the Demographic Growth of Canada’s Aboriginal Populations from 1986 to 1996”. Report on the Demographic Situation in Canada, 1998 and 1999. Statistics Canada catalogue number 91-209.

GUIMOND, Eric and Norbert ROBITAILLE. 2009. “Mère à l’adolescence : analyse de la fécondité des indiennes inscrites âgées de 15 à 19 ans, 1986 à 2004”. Cahiers québécois de démographie. Volume 38, number 2.

GUIMOND, Eric, Norbert ROBITAILLE and Sacha SENÉCAL. 2007. “Définitions floues et explosion démographique chez les populations autochtones du Canada de 1986 à 2001”. Paper presented at the Statistiques sociales et diversité ethniqueconference, organized jointly by the Quebec Inter-university Centre for Social Statistics (QICSS) and the Institut national d’études démographiques (INED).

GUIMOND, Eric, Norbert ROBITAILLE and Sacha SENÉCAL. 2009. “Les Autochtones du Canada: une population aux multiples définitions”. Cahiers québécois de démographie. Volume 38, number 2.

KATZ, Alan, Kathi Avery KINEW, Leona STAR, Carole TAYLOR, Ina KOSEVA, Josée LAVOIE, Charles BURCHILL, Marcelo L. URQUIA, Andrew BASHAM, Leanne RAJOTTE, Venkata RAMAYANAM, Jessica JARMASZ and Susan BURCHILL. 2019. The Health Status of and Access to Healthcare by Registered First Nation Peoples in Manitoba.

KERR, Don and Nelson KOPUSTAS. 1995. Projections of Households and Families for Canada, Provinces and Territories, 1994-2016. Statistics Canada catalogue number 91-522.

INDIGENOUS SERVICES CANADA. 2020. The Final Report to Parliament on the Review of S-3: December 2020.

INDIGENOUS SERVICES CANADA. 2021-1. Bill S-3: Eliminating known sex-based inequities in registration. https://www.sac-isc.gc.ca/eng/1467214955663/1572460311596 (accessed September 16, 2021).

INDIGENOUS SERVICES CANADA. 2021-2. Qalipu enrolment process update. https://www.sac-isc.gc.ca/eng/1319805325971/1572459825339 (accessed September 16, 2021).

LI, Nan and Ronald LEE. 2005. “Coherent Mortality Forecast for a Group of Populations: An Extension of the Lee-Carter Method”. Demography. Volume 42, number 3.

LOH, Shirley and M.V. GEORGE. 2003. “Estimating Fertility Level of Registered Indians in Canada: A Challenging Endeavour”. Canadian Studies in Population. Volume 30, number 1.

MAYNARD, Donna and Don KERR. 2007. “From Pre-Contact to the Present: The Demography of the Aboriginal Peoples of Canada”. In BEAUJOT, Roderic and Don KERR (editors). The Changing Face of Canada: Essential Readings in Population. Canadian Scholar’s Press Inc.

MORENCY, Jean-Dominique. 2015. “Projections of Aboriginal Families and Households in Canada.” Proceedings of Statistics Canada International Methodology Symposium 2014: Beyond traditional survey taking: adapting to a changing world.

MORENCY, Jean-Dominique and Éric CARON-MALENFANT. 2014. “Variations de la fécondité selon diverses caractéristiques au recensement”. Presented at the seminar of the Association des démographes du Québec, Congrès de l’ACFAS 2014 (Montréal).

MORENCY, Jean-Dominique, Éric CARON-MALENFANT and David DAIGNAULT. 2018. “Fertility of Aboriginal People in Canada: An Overview of Trends at the Turn of the 21st Century”. Aboriginal Policy Studies. Volume 7, number 1.

MORENCY, Jean-Dominique, Patrice DION and Chantal GRONDIN. 2021. “Migration between Indian reserves and off-reserve areas: An exploratory analysis using census data linkage”. Canadian Studies in Population. Volume 48, number 1.

NG, Edward and Jeanine PERREAULT. 1998. Projections of Households and Families of Registered Indians: 1996-2021. Indian and Northern Affairs Canada. Ottawa.

NORRIS, Mary Jane and Stewart CLATWORTHY. 2011. “Urbanization and migration patterns of Aboriginal populations in Canada: A half century in review (1951 to 2006)”. Aboriginal Policy Studies. Volume 1, number 1.

O’DONNELL, Vivian and Russell LAPOINTE. 2019. Response mobility and the growth of the Aboriginal identity population, 2006-2011 and 2011-2016. Statistics Canada catalogue number 99-011-X.

OFFICE OF THE PARLIAMENTARY BUDGET OFFICER. 2017. Bill S-3: Addressing sex based inequities in Indian registration.

PUBLIC HEALTH AGENCY OF CANADA. 2018. Key health inequalities in Canada: A national portrait. HP35-109/1-2018E-1.

RAM, Bali. 2004. “New Estimates of Aboriginal Fertility 1966-1971 to 1996-2001”. Canadian Studies in Population. Volume 31, number 4.

ROBITAILLE, Norbert and Eric GUIMOND. 2003. “La reproduction des populations autochtones du Canada : exogamie, fécondité et mobilité ethnique”. Cahiers québécois de démographie. Volume 32, number 2.

SHEPPARD, Amanda J., Gabriel SHAPIRO, Tracey BUSHNIK, Russell WILKINS, Serenity PERRY, Jay S. KAUFMAN, Micheal S. KRAMER and Seungmi YANG. 2017. “Birth outcomes among First Nations, Inuit and Métis populations”. Health Reports. Volume 28, number 11. Statistics Canada catalogue number 82-003-X.

STATISTICS CANADA. 2005. Population Projections of Visible Minority Groups, Canada, Provinces and Regions 2001 to 2017. Statistics Canada catalogue number 91-541.

STATISTICS CANADA. 2010. Projections of the Diversity of the Canadian Population, 2006 to 2031. Statistics Canada catalogue number 91-551.

STATISTICS CANADA. 2011. Population Projections by Aboriginal Identity in Canada, 2006 to 2031. Statistics Canada catalogue number 91-552.

STATISTICS CANADA. 2014. Population Projections for Canada (2013 to 2063), Provinces and Territories (2013 to 2038). Statistics Canada catalogue number 91-520.

STATISTICS CANADA. 2015-1. Projections of the Aboriginal Population and Households in Canada, 2011 to 2036. Statistics Canada catalogue number 91-552.

STATISTICS CANADA. 2015-2. Demosim: An Overview of Methods and Data Sources: Demosim 2015. Statistics Canada catalogue number 91-621.

STATISTICS CANADA. 2017-1. Demosim: An Overview of Methods and Data Sources: Demosim 2017. Statistics Canada catalogue number 91-621.

STATISTICS CANADA. 2017-2. Immigration and Diversity: Population Projections for Canada and Its Regions, 2011 to 2036. Statistics Canada catalogue number 91-551.

STATISTICS CANADA. 2018-1. Table 13-10-0403-01. Life expectancy, at birth and at age 65, by sex, five-year average, Canada and Inuit regions.

STATISTICS CANADA. 2018-2. Dictionary, Census of Population, 2016. Statistics Canada catalogue number 98-301-X2016001.

STATISTICS CANADA. 2019-1. Coverage Technical Report, Census of Population, 2016. Statistics Canada catalogue number 98-303.

STATISTICS CANADA. 2019-2. Population Projections for Canada (2018 to 2068), Provinces and Territories (2018 to 2043). Statistics Canada catalogue number 91-520.

STATISTICS CANADA. 2021-1. “Projections of the Indigenous populations and households in Canada, 2016 to 2041”. The Daily. October 6.

STATISTICS CANADA. 2021-2. “Indigenous population in Canada: Projections to 2041”. Statistics Canada – Infographics. Statistics Canada catalogue number 11-627.

STATISTICS CANADA. 2021-3. “First Nations people in Canada: Projections to 2041”. Statistics Canada – Infographics. Statistics Canada catalogue number 11-627.

STATISTICS CANADA. 2021-4. “Métis in Canada: Projections to 2041”. Statistics Canada – Infographics. Statistics Canada catalogue number 11-627.

STATISTICS CANADA. 2021-5. “Inuit in Canada: Projections to 2041”. Statistics Canada – Infographics. Statistics Canada catalogue number 11-627.

STATISTICS CANADA. 2021-6. “Registered or Treaty Indians in Canada: Projections to 2041”. Statistics Canada – Infographics. Statistics Canada catalogue number 11-627.

STATISTICS CANADA. 2021-7. “Provisional death counts and excess mortality, January 2020 to March 2021”. The Daily. June 7.

STATISTICS CANADA. 2021-8. “Canada’s population estimates, fourth quarter 2020”. The Daily. March 18.

STATISTICS CANADA. 2021-9. Table 17-10-0144. Projected population by Indigenous identity, age group, sex, area of residence, provinces and territories, and projection scenario, Canada.

STATISTICS CANADA. 2021-10. Table 17-10-0145. Projected population by Indigenous identity (variant prioritizing the Registered or Treaty Indian status), age group, sex, area of residence, provinces and territories, and projection scenario, Canada.

STATISTICS CANADA. 2021-11. Projections of the Indigenous Populations: Interactive Dashboard. Catalogue number 71-607.

TJEPKEMA, Michael, Tanya CHRISTIDIS, Tracey BUSHNIK and Lauren PINAULT. 2019-1. “Cohort profile: The Canadian Census Health and Environment Cohorts (CanCHECs)”. Health Reports. Volume 30, number 12. Statistics Canada catalogue number 82-003-X.

TJEPKEMA, Michael, Tracey BUSHNIK and Evelyne BOUGIE. 2019-2. “Life expectancy of First Nations, Métis and Inuit household populations in Canada”. Health Reports. Volume 30, number 12. Statistics Canada catalogue number 82-003-X.

UNITED NATIONS. 1973. Manual VII. Methods of Projecting Households and Families. Demographic Studies. Number 54. ST/OA/SERA. New York.

VAN IMHOFF, Evert and Wendy POST. 1998. “Microsimulation methods for population projection”. Population: An English Selection. Volume 10, number 1.

WALL STREET JOURNAL. 2021. The Covid-19 Baby Bust Is Here. March 4.

WILLEKENS, Frans. 2011. “La microsimulation dans les projections de population”. Cahiers québécois de démographie. Volume 40, number 2.

ZHANG, Yu, Nora GALBRAITH and Patrice DION. 2019. “Projection of Mortality”. In CHAGNON, Jonathan, Patrice DION, Nora GALBRAITH, Elham SIRAG and Yu ZHANG (editors). Population Projections for Canada (2018 to 2068), Provinces and Territories (2018 to 2043): Technical Report on Methodology and Assumptions. Statistics Canada catalogue number 91-620.

Glossary^Note

Base population

Population used as the starting point for population projections.

Canadian citizenship

A person’s legal status as a Canadian citizen, whether by birth or by naturalization.

Census metropolitan area (CMA)

Area consisting of one or more adjacent municipalities centered on a population core. It has a population of at least 100,000, of which 50,000 or more live in the core.

Cohort-component method

Method used for population estimates or projections that is based on the components of demographic change and a base population as input. The phrase “cohort-component method” is usually restricted to methods projecting the future evolution of cohorts by age and sex, as opposed to other methods, such as microsimulation, that also use components of population growth but that project the demographic destiny of individuals.

Collective dwelling

Dwelling used for commercial, institutional or communal purposes, such as a hotel, a hospital or a work camp.

Components of population growth

Any class of event that generates population changes. For example, births, deaths and migration are components that modify either the size of the total population or its composition by age and sex.

Education level (secondary [high] school diploma or equivalency certificate)

In Demosim, it is the education variable “secondary (high) school diploma or equivalency certificate” from the 2016 Census that is used. This variable is defined in two parts: 1) a person has a high school diploma or equivalency certificate or not, and 2) among people with a high school diploma or equivalency certificate, the education level shows a person’s most advanced certificate, diploma or degree.

Ethnic mobility

Refers to “the phenomenon of individuals and families changing the ethnic affiliation that they report” (Guimond et al. 2007). Ethnic mobility has two components: intragenerational (over one individual’s lifetime) and intergenerational (from parents to their children) (Boucher et al. 2009).

Fertility

A demographic phenomenon related to live births that can be considered from the point of view of women, the couple and, very occasionally, men.

Generation status

The respondent’s generation rank since the settlement of his/her family (meaning direct ascendants) in Canada. In the context of Demosim, immigrants are the first generation; the second generation refers to non-immigrants born in Canada to at least one foreign-born parent; the generations that follow (third or more) comprise non-immigrants born in Canada to two Canadian-born parents. A more detailed version of this variable split the first and second generations into two distinct groups: generations 1 and 1.5; and generations 2 and 2.5. According to this version of the variable, generation 1 refers to immigrants admitted at age 15 or more, while generation 1.5 refers to immigrants admitted at age 14 or less. Generation 2 refers to non-immigrants born in Canada to two foreign-born parents, while generation 2.5 refers to non-immigrants born in Canada to one foreign-born parent and to one parent born in Canada. This definition of generation status differs slightly from the one used in the census, which is based only on the place of birth (without regard to immigrant status).

Headship rate

Proportion of household heads in a given population.

Household head

In the context of Demosim projections, a person is considered a household head if they are 15 years or older at the time of the census. If a household has more than one head, each head’s weight corresponds to the weight of the household divided by the number of household heads such that the sum of the heads’ weights corresponds to the household weight.

Immigrant

Person who has been granted the right to live in Canada permanently by immigration authorities.

Immigrant category of admission

An administrative category under which a person is admitted to Canada as a permanent resident under the Immigration and Refugee Protection Act. At the aggregate level, classes are composed of economic immigrants, immigrants admitted as members of a family, immigrants admitted as protected people (refugees) and other immigrants.

Immigration

The sum of all immigrants from other countries landing in Canada, involving a change in usual place of residence.

Indian reserve

In the context of the 2016 Census, “residence on or off reserve” refers to whether the person’s usual place of residence is in a census subdivision (CSD) that is defined as “on reserve” or “off reserve.” “On reserve” includes six census subdivision (CSD) types legally affiliated with First Nations or Indian bands, i.e., Indian reserve (IRI), Indian settlement (S-É) (except for the four Indian settlements of Champagne Landing 10, Klukshu, Two Mile and Two and One-Half Mile Village, and Kloo Lake located in Yukon), Indian government district (IGD), terres réservées aux Cris (TC), terres réservées aux Naskapis (TK)and Nisga’a land. “Off reserve” includes all CSDs in Canada not defined as “on reserve.”

Indigenous ancestry

People who reported an ancestry associated with the Indigenous peoples of Canada in response to the ethnic origin question in the 2016 Census. “Indigenous ancestry” refers to whether a person has ancestry associated with the Indigenous peoples of Canada, that is, First Nations (North American Indian), Métis, and Inuit. Indigenous peoples of Canada are defined in the Constitution Act, 1982, Section 35(2) as including the Indian, Inuit and Métis peoples of Canada. Ancestry refers to the ethnic or cultural origins of the person’s ancestors, an ancestor being usually more distant than a grandparent. A person can have more than one ethnic or cultural origin. This does not mean that the person identifies with his or her ancestors’ Indigenous group or groups.

Indigenous group

People who reported being an Indigenous person—First Nations (North American Indian), Métis or Inuk (Inuit)—in response to Question 18 of the 2016 Census. These are the three groups defined as the Indigenous peoples of Canada in the Constitution Act, 1982, Section 35(2). A person may identify with more than one of these three specific groups.

Indigenous household

Private household composed of at least one person of Indigenous identity.

Indigenous identity

Refers to people identifying with the Indigenous peoples in Canada. This includes those who reported being First Nations (North American Indian), Métis or Inuk (Inuit) and/or those who reported being Registered or Treaty Indians (that is, registered under the Indian Act of Canada), and/or those who reported having membership in a First Nation or Indian band on the 2016 Census. Indigenous peoples of Canada are defined in the Constitution Act, 1982, Section 35(2) as including the Indian, Inuit and Métis peoples of Canada.

Indigenous people

See “Indigenous identity.”

Internal migration

The sum of all population movements between the geographical units within Canada’s geographical boundaries, involving a change in usual place of residence.

International migration

The sum of all movements between Canada and other countries, involving a change in the usual place of residence.

Interregional migration

The sum of all movements among the 52 main geographic entities defined in Demosim, namely the 37 regions derived from the census metropolitan areas and the 15 regions derived from elsewhere in the provinces and territories.

Intraregional migration

The sum of all movements within one of the 52 main geographic entities defined in Demosim, namely one of the 37 regions derived from the census metropolitan areas or one of the 15 regions derived from elsewhere in the provinces and territories.

Inuit Nunangat

“Residence inside or outside Inuit Nunangat” refers to whether the person’s usual place of residence is in a census subdivision (CSD) that is inside or outside Inuit Nunangat. Inuit Nunangat is the homeland of Inuit of Canada. It includes the communities located in the four Inuit regions: Nunatsiavut (Northern coastal Labrador), Nunavik (Northern Quebec), the territory of Nunavut and the Inuvialuit region of the Northwest Territories. These regions collectively encompass the area traditionally occupied by the Inuit in Canada. “Outside Inuit Nunangat” includes all CSDs in Canada not located in the four Inuit regions of Inuit Nunangat.

Knowledge of official languages

Sufficient knowledge of English or French (or both) to conduct a conversation in any of those languages.

Labour force

The population that is employed or unemployed.

Language spoken most often at home

The language spoken most often by the respondent at home.

Life expectancy

A statistical measure derived from the life table indicating the average number of years of life remaining for a population at a specific age “x”, calculated on the basis of the mortality rates observed in a given year.

Mother tongue

The first language learned at home in childhood and still understood.

Member of a First Nation or an Indian band

The people who reported being a member of a First Nation or an Indian band in the 2016 Census. In the 2016 Census, an Indian band is defined as a body of Indians for whose collective use and benefit lands have been set apart or money is held by the Crown, or who have been declared to be a band for the purpose of the Indian Act. Many Indian bands have elected to call themselves a First Nation and have changed their band name to reflect this. With the 1985 amendment to the Indian Act (Bill C-31), many Indian bands exercised the right to establish their own membership code, whereby it was not always necessary for a band member to be a Registered or Treaty Indian according to the Indian Act (Statistics Canada 2018-2).

Microsimulation

Unlike population estimates and projections produced using the cohort-component method, microsimulation simulates the demographic destiny of each individual. The method is based on multiple random drawing at the individual level rather than on aggregated data applied at the population group level.

Net undercoverage

Difference between the number of people who were targeted by the census but who were not enumerated (undercoverage), and the number of people who were enumerated when they should not have been, or who were enumerated more than once (overcoverage).

Non-permanent resident

People who have a work or study permit or who are refugee claimants, and the family members living in Canada with them.

Own-children method

A method that indirectly estimates fertility by using a census or an equivalent data source (Grabill and Cho 1965; Desplanques 1993). This method links the youngest children—here children aged less than one year—to the woman aged 15 to 49 years living in the same family who is most likely to be the mother. The women identified in this way are considered to have given birth recently to a child (here during the last year). Using this link, as well as some adjustments, it is possible to compute fertility rates according to various characteristics.

Population projection

The future population size resulting from a set of assumptions regarding the demographic and non-demographic components of growth.

Private dwelling

A set of living quarters designed for or converted for human habitation in which a person or group of people reside or could reside. In addition, a private dwelling must have a source of heat or power and must be an enclosed space that provides shelter from the elements, as evidenced by complete and enclosed walls and roof and by doors and windows that provide protection from wind, rain and snow.

Private household

A person or group of people (other than foreign residents) who occupy a private dwelling and who do not have a usual place of residence elsewhere in Canada. The number of private households is equal to the number of occupied dwellings.

Projection scenario

A set of assumptions related to the components, demographic or otherwise, used to make a population projection.

Registered or Treaty Indian (Status Indian)

People who reported that they were Status Indians (Registered or Treaty Indians) in the 2016 Census. Registered Indians are people who are registered under the Indian Act of Canada. Treaty Indians are people who belong to a First Nation or Indian band that signed a treaty with the Crown. Registered or Treaty Indians are sometimes also called Status Indians.

Registration categories 6(1) and 6(2) on the Indian Register

The registration category 6(1) or 6(2) is assigned to Registered or Treaty Indians when they register on the Indian Register. Registration categories 6(1) and 6(2) correspond to the rules set out in subsections 6(1) and 6(2) of article 6 in the Indian Act, which establish the criteria that people must meet to register on the Indian Register. Within the meaning of the act, people registered under subsection 6(1) differ from those registered under subsection 6(2) with regard to their ability to transmit their status to their children. A parent registered under category 6(1) can always pass on his/her Registered or Treaty Indian status to the child, but a parent registered under category 6(2) can pass on the status only if the other parent is also registered.

Registration category amendment from 6(2) to 6(1)

Refers to Registered or Treaty Indians with a registration category of 6(2) that is amended to a registration category of 6(1) during their lifetime. In this report, registration category amendment from 6(2) to 6(1) may result from the application of bills C-3 and S-3 or from various other reasons.

Sex ratio

The ratio of the number of men to the number of women. This ratio is usually expressed as an index, with the number of female taken to be a base of 100.

Total emigration

The number of emigrants minus the number of returning emigrants plus net temporary emigration.

Total fertility rate

The sum of age-specific fertility rates during a given year. It indicates the average number of children that a generation of women would have if, over the course of their reproductive life, they experienced the age-specific fertility rates observed during the year considered.

Visible minority groups

The Employment Equity Act defines visible minorities as “persons, other than Indigenous peoples, who are non-Caucasian in race or non-white in colour.”