Population Projections for Canada (2025 to 2075), Provinces and Territories (2025 to 2050): Technical Report on Methodology and Assumptions

1 Introduction

This edition of population projections for Canada, the provinces and territories comes at a time of rapid demographic change, including historically low fertility rates and several recent changes in immigration and temporary resident policies. The medium- and long-term consequences of the COVID-19 pandemic remain uncertain, despite a return to increases in life expectancy in 2023 and 2024. The methods selected and assumptions made aim to produce results that are both plausible and indicative of the uncertainty associated with developing population projections in a changing context. This document briefly describes the methods, assumptions and various scenarios proposed.

Part of the content in this report was created using a generative artificial intelligence (AI) tool and then verified and adjusted by Statistics Canada specialists. To learn more about how we use AI responsibly, please visit Statistics Canada's Trust Centre.

2 Caveat

The population projections produced by Statistics Canada’s Centre for Demography should in no way be interpreted as predictions of what the future holds. Rather, they should be understood as an exercise of what the Canadian population could look like in the coming years based on certain scenarios of evolution that seemed plausible when these projections were completed.

Users of projection results are encouraged to communicate the uncertainty inherent in projections, particularly by considering multiple scenarios. Furthermore, some events, such as economic crises, wars, pandemics or natural disasters, are difficult—and even impossible—to predict and may affect the growth and composition of the Canadian population. For this reason, Statistics Canada makes sure to revise its population projections regularly, so that the context in which they are developed is taken into account.

3 Brief overview of the methodology

These projections are produced using a cohort-component model, into which assumptions about changes to each component of population growth (births, deaths and international migration [immigration and emigration]) can be incorporated. These assumptions are developed in order to achieve three general objectives:

1. To take into consideration both short-term and long-term future outcomes in building projection assumptions.
2. Determine distinct trajectories for each province and territory in order to take into account historical trends prevailing in each region.
3. To ensure that the provinces and territories follow a convergent pattern in the long term (reflecting patterns usually observed over a long period of time).

For each of these components, long-term objectives were set first at the national level for selected demographic indicators (total fertility rate, immigration rate, etc.) following consultations involving many experts. To this end, members of the country’s two demography associations, the Canadian Population Society and the Association des démographes du Québec, were invited to answer the 2025 Survey on Future Demographic Trends, a structured expert elicitation protocol designed to collect probabilistic assessments using best practices in the field (Dion, Galbraith, & Sirag, 2020). Individual responses are encoded as probability distributions using Metalog distributions (Keelin, 2016). Experts can view the resulting distribution through a graphical interface and adjust their responses if desired while they answer the survey. Expert’s distributions are combined to form one single Metalog distribution (Keelin & Howard, 2021) using quantile aggregation (Genest, 1992; Lichtendahl Jr, Grushka-Cockayne, & Winkler, 2013). The median of the aggregate probability distribution serves as the target for medium assumptions, while the 10th and 90th percentiles are used for low and high assumption targets.

Next, time series forecasting methods were used to extrapolate current trends in each province and territory. More specifically, targets were set for a five-year horizon (for the period 2029/2030) using double exponential smoothing models with damped trends (Holt method) in the case of fertility (total fertility rate) and non-permanent residents (proportion of the total population), and single exponential smoothing models in the case of emigration (gross migraproduction rate). A distinctive feature of these models is that the weight given to observations decreases geometrically over time, allowing greater importance to be given to recent observations. In addition, a damping parameter ensures that trends are attenuated, even in regions where they are pronounced.

In each region and for each sex, long-term targets are determined in such a way as to replicate the gap (proportionally) between the projected short-term value and the long-term target at the national level. They are therefore dependent on both their specific historical trends and anticipated developments on a larger scale in the long term. Long-term national targets and regional projections are combined to develop comprehensive pathways for each region. The projections are therefore made for provinces and territories, and the results for Canada are obtained through aggregation (a method known as ‘bottom-up’). The age and sex parameters used as inputs for the projections (e.g., emigration rates by age and sex) are calculated based on the projected values of the demographic indicator (e.g., the gross migraproduction rate of emigration). However, different methods are used for the mortality and interprovincial migration components (see sections 6 and 10).

Furthermore, the projections include a multiregional perspective in which regions are linked by migration flows (interprovincial migration). In particular, matrix operations combine all demographic events, including interprovincial migration, the parameters of which are presented as migration rates from each region to each of the other regions. Various scenarios were produced, each reflecting distinct historical periods. An adjustment was made to the projected migration rates so that internal migration flows were adjusted based on the size and characteristics not only of the source populations, but also on the destination regions. One advantage of this approach is that it stabilizes projected net migration rates close to the values observed during the selected reference periods, thereby increasing transparency of the internal migration assumptions (Dion, 2017).

Although projections are available by age and gender, they are modelled based on results produced first by sex using ratios calculated based on 2021 Census data.

As a final note, projection assumptions have been designed with plausibility in mind. For example, the use of time series models with damped trends, which consists in reducing the magnitude of forecast trends to maintain forecast values closer to historical averages, and the combination of independent expert’s views follow a conservative approach known to improve accuracy in forecasting (Armstrong, Green, & Graefe, 2015). However, the overwhelming fact is that there is no comprehensive causal system that demographers can rely on to accurately predict future changes in vital rates accuracy (Keyfitz, 1972). Moreover, demographers have few opportunities to evaluate their projections and adjust their methods because their projection horizons span decades, unlike weather forecasters, for example, who have a large number of daily forecasts to work with (United Nations Economic Commission for Europe, 2018). These factors explain in large part the mixed results of past demographic projections in terms of “accuracy” (Dion & Galbraith, 2015). In addition, Canada's population dynamics in recent years have demonstrated what Francesco Billari refers to as "fast demography," which is highly responsive to social, economic, and policy shifts (Billari, 2022). This is in contrast to a “slow demography” perspective, where population moves inertially, is mainly exogenous to other factors, and thus easier to "predict”. The central role of international migration in Canada makes population size and age structure particularly sensitive to policy decisions, and markedly hard to predict (Bijak & Wiśniowski, 2020). There is also considerable uncertainty about future fertility trends in low-fertility countries such as Canada (Goujon, 2025; Icardi, Galley, & Goujon, 2023). In view of this, users should take great care to present the results in a way that reflects their uncertainty, including those using Statistics Canada's projections as predictions in the absence of a viable alternative. This involves labeling the results as projections, describing their uncertain nature and using more than one scenario when possible. While demographers cannot be held responsible for inaccuracy in their projections, they are responsible for warning the public about their uncertainty (Keyfitz, 1981).

4 Assumptions and choice of scenarios

The purpose of having multiple projection scenarios is to reflect the uncertainty associated with the future. The projection scenarios are constructed by combining a number of assumptions about the future evolution of each component of population growth.

Six scenarios (M1, M2, M3, M4, M5 and M6) are designed to illustrate a medium level of growth, essentially reflecting a continuation of current trends in the short term and a trajectory considered plausible in the long term. Each of these scenarios includes a distinct interprovincial migration assumption, to reflect the volatility of this component.

The low-growth (LG) and high-growth (HG) scenarios include assumptions that are consistent with either lower or higher population growth than in the medium-growth scenarios at the national level. For example, assumptions that entail high fertility, low mortality, high immigration, low emigration and high numbers of non-permanent residents are the foundation of the high-growth scenario.

The fast-aging (FA) and slow-aging (SA) scenarios include assumptions that are consistent with either faster or slower population aging than in the medium-growth scenarios. For example, assumptions that entail high fertility, high mortality, high immigration and high numbers of non-permanent residents are the foundation of the slow-aging scenario.

The 10 scenarios are intended to provide a plausible and sufficiently broad range of projected numbers to take account of the uncertainties inherent in any projection exercise. Note that in the low-growth (LG), high-growth (HG), slow-aging (SA) and fast-aging (FA) scenarios, the interprovincial migration assumption is the same as the one used in the M1 medium-growth scenario. The projection assumptions and scenarios are summarized in Tables 4.1 and 4.2.

5 Projection of fertility

5.1 Background

In 2024, Canada’s total fertility rate (TFR) was 1.25 children per woman, its lowest level to date (Statistics Canada, 2025a). This continues the general downward trend observed since 2008 (Provencher & Galbraith, 2024; Teng & Margolis, 2024). The historic low in the TFR was observed in nine provinces and territories. Meanwhile, the average age of childbearing continued to rise across the country, reaching 31.8 years in 2024 (Statistics Canada, 2025a).

The decline in fertility can be seen in most countries around the world, generally occurring at a faster rate than experts predicted (Peeples, 2025). The number of countries with a TFR below 1.30 has been on the rise in recent years (Statistics Canada, 2025a). It is difficult to explain this decline, given so many potential determinants of fertility. However, certain emerging trends could be responsible for this decrease, such as diversification of the types of unions, changing ways of meeting people—particularly with the advent of social media—and a growing preference to not have children (Bloom, Kuhn, & Prettner, 2024). In addition, the housing affordability crisis affecting many high-income countries including Canada (Igan, 2024) could have a negative impact on fertility, according to studies from the Netherlands and the United States (van Wijk & Feijten, 2025; Japaridze & Sayour, 2024). Van Wijk (2024) generally observes a positive and growing association between income and parenthood, suggesting that the cost of living poses difficulties.

In terms of future trends, most of the experts consulted agree that without significant intervention, fertility in Canada will remain low or even decline over the next 25 years. The reasons for this revolve around economic constraints, cultural changes, and structural societal factors that delay or reduce the desire and ability to have children. These include the cost of living (housing, food, education, debt), delaying parenthood (extended studies, career), the rise of individualism and urban lifestyles, and the psychological and practical impact of crises — especially climate and geopolitical crises — on the desire to have children. Many experts also point out that weakened or insufficient institutional mechanisms (family policies, government assistance, access to childcare services) amplify these trends. Some have noted that the low fertility observed in recent years may become a norm that future generations adopt, thus creating a self-reinforcing cycle. Other factors mentioned include the impact of transformations (e.g., automation, artificial intelligence) on youth employment, fewer social interactions and relationships, and access to contraception.

Experts believe an increase in fertility is nonetheless possible, particularly if the material constraints that delay parenthood are reduced or if changes in couples’ preferences encourage them to have more children. Robust family policies (daycare, parental leave, financial assistance, support for work–life balance) and tangible improvements in housing accessibility are potential levers to boost fertility. Cultural changes, such as a partial return to more family-oriented or conservative values or a decline in individualism, could also contribute to increasing fertility in Canada. Lastly, some experts mentioned factors that, while not triggering a shift in trends, could still encourage higher fertility, such as immigration, a rebound in births caused by a stagnant or lower average age of childbearing, and better access to fertility treatments for infertile couples.

5.2 Projection assumptions

Separate assumptions are developed for the non-permanent resident (NPR) population and the permanent population (PP).^Note  This can make a difference because fertility tends to be significantly lower among NPRs, which is expected given their status. In addition, after more than doubling from 2021 to 2024, the number of NPRs in Canada fell in 2025 and is expected to continue to significantly decline over the coming years, according to the targets in the 2026–2028 Immigration Levels Plan (see section 7). Age-specific fertility rates for the female NPR population were produced by applying the own-children method (Grabill & Cho, 1965) to 2011, 2016 and 2021 census data.^Note  Since these values vary little over time, a single assumption for NPRs is proposed, consisting of a weighted average of the 2011, 2016 and 2021 values. To mitigate the impact of small numbers, the Atlantic provinces were combined into a single region, as were the territories.

For the PP, three projection assumptions (medium, low and high) were proposed and formulated for the TFR at the national level. The long-term TFR targets (for 2050) were derived from the aggregate distribution representing the opinion of 19 experts (Chart 5.2.1). Since these targets apply to the entire population, they were modified to correspond to targets applicable only to the PP. To do this, the difference between the TFR values of the PP and NPRs calculated for 2024 in each region was assumed to be the same in 2050. The medium assumption produces a TFR of 1.32 children per woman in 2050, based on the median of the aggregate distribution representing the opinion of experts (Chart 5.2.1). The low and high fertility assumptions for the PP produce TFRs of 1.09 and 1.55 children per woman, respectively, based on the 10th and 90th percentiles of the experts’ distribution.

Chart 5.2.1 start

Description for Chart 5.2.1

This line graph shows the probability distribution of the values that the period total fertility rate could take in Canada in 2050 provided by each expert (grey lines) as well as the aggregate probability distribution representing all the experts (red line). The horizontal axis shows the number of children per woman. The vertical axis shows the probability density. In the aggregate distribution, there is an 80% probability that the value lies between 1.05 and 1.49. The median of the distribution is 1.27.

Chart 5.2.1 end

The projected trajectories for the medium assumption in each province and territory combine extrapolations from the historical TFR series with the long-term targets determined from the national target (see section 3). The historical series specific to the PP needed to calculate TFR trajectories in each province were produced by subtracting the contribution of NPRs from the age-specific fertility rates of the total population.^Note  A trajectory for the low assumption is established by interpolating the difference between the low and medium assumption targets in 2050 using a logarithmic function to obtain a quick divergence and better reflect the uncertainty early in the projection. The same method was used to produce a trajectory for the high assumption (Chart 5.2.2). The projected TFRs for the provinces and territories are presented in Table 5.2.1 for 2029/2030 (reflecting the results of time series forecasting models applied to each region) and for 2049/2050 (reflecting long-term targets).^Note 

Chart 5.2.2 start

Data table for Chart 5.2.2

Data table for Chart 5.2.2
Table summary
The information is grouped by Year (appearing as row headers), Permanent population, Projected non permanent residents, Total population - Historic, Historic, Low assumption, Medium assumption and High asumption, calculated using children per woman units of measure (appearing as column headers).

Year	Permanent population				Projected non permanent residents	Total population - Historic
	Historic	Low assumption	Medium assumption	High asumption
	children per woman
Note ... not applicable Sources: Statistics Canada, Canadian Vital Statistics - Birth database (CVSB), Annual Demographic Estimates, population censuses (2016 and 2021), 2011 National Household Survey and Centre for Demography.
2000	... not applicable	... not applicable	... not applicable	... not applicable	... not applicable	1.51
2001	... not applicable	... not applicable	... not applicable	... not applicable	... not applicable	1.54
2002	... not applicable	... not applicable	... not applicable	... not applicable	... not applicable	1.52
2003	... not applicable	... not applicable	... not applicable	... not applicable	... not applicable	1.55
2004	... not applicable	... not applicable	... not applicable	... not applicable	... not applicable	1.56
2005	... not applicable	... not applicable	... not applicable	... not applicable	... not applicable	1.58
2006	... not applicable	... not applicable	... not applicable	... not applicable	... not applicable	1.63
2007	... not applicable	... not applicable	... not applicable	... not applicable	... not applicable	1.67
2008	... not applicable	... not applicable	... not applicable	... not applicable	... not applicable	1.70
2009	... not applicable	... not applicable	... not applicable	... not applicable	... not applicable	1.69
2010	... not applicable	... not applicable	... not applicable	... not applicable	... not applicable	1.64
2011	1.66	... not applicable	... not applicable	... not applicable	... not applicable	1.63
2012	1.66	... not applicable	... not applicable	... not applicable	... not applicable	1.63
2013	1.64	... not applicable	... not applicable	... not applicable	... not applicable	1.61
2014	1.65	... not applicable	... not applicable	... not applicable	... not applicable	1.61
2015	1.64	... not applicable	... not applicable	... not applicable	... not applicable	1.60
2016	1.63	... not applicable	... not applicable	... not applicable	... not applicable	1.59
2017	1.59	... not applicable	... not applicable	... not applicable	... not applicable	1.55
2018	1.55	... not applicable	... not applicable	... not applicable	... not applicable	1.51
2019	1.52	... not applicable	... not applicable	... not applicable	... not applicable	1.47
2020	1.45	... not applicable	... not applicable	... not applicable	... not applicable	1.41
2021	1.48	... not applicable	... not applicable	... not applicable	... not applicable	1.44
2022	1.37	... not applicable	... not applicable	... not applicable	... not applicable	1.34
2023	1.31	... not applicable	... not applicable	... not applicable	... not applicable	1.27
2024	1.30	... not applicable	... not applicable	... not applicable	... not applicable	1.25
2025	... not applicable	1.23	1.27	1.32	1.06	... not applicable
2026	... not applicable	1.19	1.26	1.34	1.06	... not applicable
2027	... not applicable	1.16	1.25	1.34	1.06	... not applicable
2028	... not applicable	1.14	1.24	1.35	1.06	... not applicable
2029	... not applicable	1.12	1.24	1.36	1.06	... not applicable
2030	... not applicable	1.10	1.23	1.36	1.06	... not applicable
2031	... not applicable	1.09	1.23	1.37	1.06	... not applicable
2032	... not applicable	1.09	1.23	1.38	1.06	... not applicable
2033	... not applicable	1.08	1.23	1.39	1.06	... not applicable
2034	... not applicable	1.08	1.24	1.40	1.06	... not applicable
2035	... not applicable	1.08	1.24	1.41	1.06	... not applicable
2036	... not applicable	1.07	1.24	1.42	1.06	... not applicable
2037	... not applicable	1.07	1.25	1.43	1.06	... not applicable
2038	... not applicable	1.08	1.26	1.44	1.06	... not applicable
2039	... not applicable	1.08	1.26	1.46	1.06	... not applicable
2040	... not applicable	1.08	1.27	1.47	1.06	... not applicable
2041	... not applicable	1.08	1.28	1.48	1.06	... not applicable
2042	... not applicable	1.08	1.29	1.49	1.06	... not applicable
2043	... not applicable	1.09	1.29	1.51	1.06	... not applicable
2044	... not applicable	1.09	1.30	1.52	1.06	... not applicable
2045	... not applicable	1.09	1.31	1.53	1.06	... not applicable
2046	... not applicable	1.09	1.31	1.54	1.06	... not applicable
2047	... not applicable	1.09	1.31	1.54	1.06	... not applicable
2048	... not applicable	1.09	1.32	1.55	1.06	... not applicable
2049	... not applicable	1.09	1.32	1.55	1.06	... not applicable

Chart 5.2.2 end

6 Projection of mortality

6.1 Background

Uncertainty with respect to the evolution of future mortality in Canada remains larger than it did prior to the COVID-19 pandemic. While life expectancy at birth in Canada increased between 2022 and 2023 (from 81.13 years to 81.68 years), it has yet to return to the value observed in 2019 (82.22 years). Preliminary data for 2024 suggest that life expectancy has continued to increase across Canada, in some regions attaining or surpassing pre-pandemic levels. Whether current rates of mortality improvement will be sustained, return to those observed pre-pandemic, or decrease depends in part on the unknown effect of the pandemic on long-term mortality.

Most recent data also suggest that the number of deaths related to opioid intoxication, which negatively impacted life expectancy during this same period, has begun to decrease. The Public Health Agency of Canada reported a 17% decrease in opioid-related deaths between 2023 and 2024 (Public Health Agency of Canada, 2025).

6.2 Projection assumptions

As in previous editions, a variant of the common Lee-Carter model (Lee & Carter, 1992) elaborated by Li and Lee (Li & Lee., 2005) was used to obtain coherent projections of mortality by age, sex, and province or territory. The Lee-Carter model decomposes historical age‑specific mortality rates for a single population into age and time components, then projects future mortality by applying a univariate time series model to the time trend.^Note  The Li-Lee extension provides a framework for applying the Lee-Carter method coherently to multiple populations groups or subgroups. The model features shared age and time components, which characterize overall mortality trends, in addition to population‑specific deviations that diminish over time. This approach is used to derive mortality projections by sex and by province and territory that don’t diverge unrealistically over time.^Note 

Assumptions related to mortality have been formed so as to reflect: (1) the diminishing immediate impact of the COVID-19 pandemic on life expectancy in Canada; (2) the likelihood of larger, short-term gains in life expectancy as it catches up (partially or in whole) to pre-pandemic levels; and (3) greater uncertainty surrounding the long-term evolution of mortality, given that long-term primary and secondary effects of the pandemic on overall health and longevity remain unknown.   

Disruptive shocks to mortality (such as a pandemic) that may in fact be temporary in nature may induce permanent level shifts in the projections of mortality. In an effort to allow for more uncertainty regarding the permanence of the impact of the pandemic on both long-and short-term mortality, two sets of projections were produced, reflecting hypothetical pre- and post-COVID developments. In the case of the first, only data up to 2019 were used in the model-fitting process so that projections begin in 2020 – thus representing a counterfactual trajectory for mortality in the absence of the pandemic. In the case of the second scenario, projections were produced using all available data at the time of production (i.e., up to 2023). The two pre- and post-COVID projections were combined so that the final low, medium, and high mortality assumptions each represent varying levels of optimism about the evolution of mortality in the current post-pandemic setting.

The medium assumption was derived by computing a dynamic weighted average of median mortality of the two projections up to 2074. At the start of the projection, more weight is given to post-COVID mortality rates; as the projection continues, a logarithmic interpolation scheme was used to assign increasing weight to the pre-COVID mortality rates in each subsequent year until 2074, where this weight reaches 1. A logarithmic weighting scheme was selected in order to depict a rapid catch-up toward pre-COVID mortality at the beginning of the projection that slows in pace as it eventually approaches these levels.

The low and high mortality assumption were derived by applying the same approach to the lower and upper bounds of the 97% confidence interval surrounding median mortality in both the pre- and post-COVID scenarios. However, in the low mortality assumption, rather than achieving convergence toward pre-COVID levels in 2074, convergence is achieved in 2049. From 2049 onward, the pre-COVID projections are used directly. The low assumption thus reflects both a quicker catch-up towards pre-COVID mortality and reduced long-term impacts of the pandemic compared to the medium assumption.

Projected life expectancy at birth by sex and province/territory for selected years according to the low, medium and high mortality assumptions are shown in tables 6.2.1, 6.2.2 and 6.2.3.

7 Projection of immigration

7.1 Background

In the short term, the number of immigrants admitted to Canada each year is largely determined by the Immigration Levels Plan presented annually to Parliament by Immigration, Refugees and Citizenship Canada (IRCC) and required by the Immigration and Refugee Protection Act. The plan provides targets for the next three years, although those for the second and third years are theoretical in scope, in that they may be revised over the coming years. Furthermore, in the 2026-2028 plan, IRCC intends to implement two “one-time” initiatives to “recalibrate the immigration system” (Immigration, Refugees and Citizenship Canada, 2025a). Admissions under these one-time initiatives do not count toward the targets in the Immigration Levels Plan (Immigration, Refugees and Citizenship Canada, 2025b).

The targets proposed in the Immigration Levels Plans rose steadily from 2015 to 2024, mostly to address the pressures caused by labour shortages in some economic sectors and by an aging population. The increases were quite considerable from 2021 to 2023 to offset the drop in arrivals during the pandemic and to support economic recovery. The consequences of rising immigration (and more non-permanent residents), along with the resulting strong population growth, have been significant. For example, Marion and Ducharme (2024) and Young and Lalonde (2024) described the pressure on infrastructure caused by sustained immigration levels in recent years, leading to inflationary pressures and a lack of affordable housing. With respect to the labour shortage, Fortin (2024) showed that the additional demand for goods and services generated by recent increases in immigration has helped redistribute, and even exacerbate, it across the economy. Furthermore, polls have shown that Canadians’ support for immigration declined sharply in 2023 and 2024 (Environics Institute, 2024; Immigration, Refugees and Citizenship Canada, 2025c) and remained stable in 2025 (Coletto, David; Sheppard, Eddie, 2025; Environics Institute, 2025). A similar finding emerged from the public consultation process recently conducted by IRCC: more than 75% of respondents not representing an organization felt that the targets for 2026 and 2027 (in the 2025-2027 Immigration Plan) were too high, and 75% advocated for a reduction in the number of new permanent residents beyond 2027 (Immigration, Refugees and Citizenship Canada, 2025d).^Note  Many respondents raised the need to adapt immigration levels to structural issues (housing, infrastructure, health care) and regional realities. Lastly, the very objectives of immigration policies have recently been discussed (Doyle, Skuterud, & Worswick, 2025; Drummond & Mahboubi, 2024; Hiebert, 2025; C.D. Howe Institute, 2025).

Concerns about the immigration system and Canada’s capacity to receive immigrants — particularly regarding affordable housing, health care access, and infrastructure — prompted the government to stabilize targets in the 2024–2026 plan, then reduce them in the 2025–2027 plan (Immigration, Refugees and Citizenship Canada, 2023, 2024). The most recent Immigration Levels Plan maintains the targets for the 2026–2028 period at levels very close to the previous plan and indicates that it intends to keep the number of admissions at less than 1% of the Canadian population (Immigration, Refugees and Citizenship Canada, 2025e).

In the longer term, the vast majority of experts who participated in the consultation process established to support the development of projection assumptions agree that increasingly unfavorable public opinion, fueled by the perception that immigration places excessive pressure on public services, the health care system, education, and infrastructure, could contribute to pushing immigration levels downward. The rising cost of living and housing, along with the growing influence of populist or xenophobic political discourse, could exacerbate the negative perceptions of immigration. Economic and structural factors such as an economic slowdown, rising unemployment, declining GDP per capita, and transformation of the labour market due to automation and artificial intelligence could also contribute to lower immigration thresholds. Some experts also point to international competition for talent, the shrinking pool of migrants in countries of origin, and the impact of global crises.

Experts also believe that immigration levels could rise, including to support employment, growth and essential services in the context of an aging population, declining fertility, and shortages in health care, construction and services. Pressure from the business community and the private sector to fill positions and expand the consumer base, as well as Canada’s ongoing reputation as a safe and prosperous country, could also contribute to an increase in the number of admissions. External and cyclical factors such as geopolitical instability, wars, increased refugee flows and climate migration are likely to increase asylum claims and humanitarian needs, which could also lead to an increase in immigration to the country. Lastly, experts mentioned that determining immigration targets largely depends on the direction taken by the governments in power.

7.2 Projection assumptions

Three projection assumptions were made — medium, low and high — and expressed as annual immigration rates (number of admissions relative to the Canadian population). In the medium immigration assumption, the immigration rate matches the national targets set out by the 2026–2028 Immigration Levels Plan (Table 7.2.1).^Note  For 2026 and 2027, the rates are calculated to also include a number of new permanent residents from the one-time initiatives announced by the government. As a result, the plan anticipates that 148,000 people, in addition to the targets, will obtain resident status in 2026 or 2027. When calculating the rates, this number was divided equally between these two years.

From 2028/2029 to 2049/2050, immigration rates are linearly interpolated to reach 9.2 per thousand, representing the median of the aggregate distribution summarizing the experts’ responses (Chart 7.2.1).

The low and high immigration assumptions are developed to produce a difference corresponding to an 80% prediction interval drawn from the aggregate distribution of expert opinions. Therefore, the targets in 2049/2050 are 5.4 per thousand for the low immigration assumption and 11.3 per thousand for the high immigration assumption. The trajectories from 2025 to 2050 are designed to produce a relatively large difference with the medium assumption early in the projection and a decreasing divergence rate over time, resulting in a plausible representation of the uncertainty propagation process. A logarithmic function is used to model these gaps (Chart 7.2.2).

Chart 7.2.1 start

Description for Chart 7.2.1

This line graph shows the probability distribution of the values that the immigration rate could take in Canada in 2050 provided by each expert (grey lines) as well as the aggregate probability distribution representing all the experts (red line). The horizontal axis shows the immigration rate. The vertical axis shows the probability density. In the aggregate distribution, there is an 80% probability that the value lies between 6.9 and 11.3. The median of the distribution is 9.2.

Chart 7.2.1 end

Chart 7.2.2 start

Data table for Chart 7.2.2

Data table for Chart 7.2.2
Table summary
The information is grouped by Period (appearing as row headers), Historic, Low assumption, Medium assumption and High assumption, calculated using per thousand units of measure (appearing as column headers).

Period	Historic	Low assumption	Medium assumption	High assumption
	per thousand
Note ... not applicable Sources: Immigration, Refugees and Citizenship Canada and Statistics Canada, Centre for Demography.
2000/2001	8.2	... not applicable	... not applicable	... not applicable
2001/2002	8.3	... not applicable	... not applicable	... not applicable
2002/2003	6.4	... not applicable	... not applicable	... not applicable
2003/2004	7.6	... not applicable	... not applicable	... not applicable
2004/2005	7.7	... not applicable	... not applicable	... not applicable
2005/2006	7.9	... not applicable	... not applicable	... not applicable
2006/2007	7.3	... not applicable	... not applicable	... not applicable
2007/2008	7.6	... not applicable	... not applicable	... not applicable
2008/2009	7.4	... not applicable	... not applicable	... not applicable
2009/2010	8.0	... not applicable	... not applicable	... not applicable
2010/2011	7.6	... not applicable	... not applicable	... not applicable
2011/2012	7.6	... not applicable	... not applicable	... not applicable
2012/2013	7.6	... not applicable	... not applicable	... not applicable
2013/2014	7.6	... not applicable	... not applicable	... not applicable
2014/2015	6.8	... not applicable	... not applicable	... not applicable
2015/2016	9.1	... not applicable	... not applicable	... not applicable
2016/2017	7.6	... not applicable	... not applicable	... not applicable
2017/2018	8.3	... not applicable	... not applicable	... not applicable
2018/2019	8.5	... not applicable	... not applicable	... not applicable
2019/2020	7.6	... not applicable	... not applicable	... not applicable
2020/2021	6.0	... not applicable	... not applicable	... not applicable
2021/2022	12.9	... not applicable	... not applicable	... not applicable
2022/2023	12.0	... not applicable	... not applicable	... not applicable
2023/2024	11.6	... not applicable	... not applicable	... not applicable
2024/2025	10.6	... not applicable	... not applicable	... not applicable
2025/2026	... not applicable	9.4	9.9	10.4
2026/2027	... not applicable	10.1	11.0	11.9
2027/2028	... not applicable	9.0	10.1	11.1
2028/2029	... not applicable	8.0	9.1	10.2
2029/2030	... not applicable	7.9	9.1	10.3
2030/2031	... not applicable	7.8	9.1	10.4
2031/2032	... not applicable	7.7	9.1	10.5
2032/2033	... not applicable	7.6	9.1	10.6
2033/2034	... not applicable	7.6	9.1	10.6
2034/2035	... not applicable	7.5	9.1	10.7
2035/2036	... not applicable	7.4	9.1	10.8
2036/2037	... not applicable	7.4	9.1	10.8
2037/2038	... not applicable	7.3	9.1	10.9
2038/2039	... not applicable	7.3	9.1	10.9
2039/2040	... not applicable	7.3	9.1	11.0
2040/2041	... not applicable	7.2	9.1	11.0
2041/2042	... not applicable	7.2	9.1	11.1
2042/2043	... not applicable	7.1	9.1	11.1
2043/2044	... not applicable	7.1	9.1	11.1
2044/2045	... not applicable	7.1	9.1	11.2
2045/2046	... not applicable	7.0	9.1	11.2
2046/2047	... not applicable	7.0	9.1	11.2
2047/2048	... not applicable	7.0	9.1	11.3
2048/2049	... not applicable	7.0	9.2	11.3
2049/2050	... not applicable	6.9	9.2	11.3

Chart 7.2.2 end

The projected proportions of immigrants admitted in each province and territory, as well as their distribution by age and gender in each region, were determined using an average of the distributions observed in IRCC data for the period from 2021 to 2024, as well as the targets set by the Government of Quebec for 2026 with regard to economic immigration (Ministère de l’Immigration, de la Francisation et de l’Intégration, 2025). It should be noted that under the Canada-Quebec Accord, Quebec has full responsibility for selecting economic immigrants destined to that province.

The projected proportion of immigrants for Quebec is based on the number of economic immigrants planned for in Quebec's annual immigration plan and the average distributions observed between 2021 and 2024 for the other major immigration categories. In other provinces and territories, the projected distribution of immigrants reflects that observed between 2021 and 2024 for all major immigration categories. However, it underwent two successive adjustments. An initial adjustment was made to correct differences between the province or territory of destination originally reported by the immigrant to IRCC before arriving in Canada and the province or territory they were actually living in once in Canada. This was carried out by applying correction factors calculated using the Longitudinal Immigration Database (Statistics Canada 2025b). A second adjustment was made based on the distribution of admissions by immigration category, as specified in the 2026–2028 Immigration Levels Plan. More specifically, this adjustment reflects how variations in the proportion of each category can influence the location and composition of new immigrants compared with previous years. The proportions remain the same after 2027/2028 (Table 7.2.2).

8 Projection of the number of non permanent residents

8.1 Background

A non-permanent resident (NPR) is a person from another country with a usual place of residence in Canada and who (1) has claimed refugee status (asylum claimants, protected persons and related groups) or (2) holds a work permit, a study permit, or a temporary resident permit. Family members living with permit holders are also included, unless these family members are already Canadian citizens, landed immigrants (or permanent residents), or NPRs themselves (Statistics Canada, 2025c).

In 2024, the federal government included new targets for the proportion of temporary residents in the country in the 2025-2027 Immigration Levels Plan for the first time. In this plan, the government committed to reducing the number of temporary residents to aim for a proportion of 5% of the total population by 2026 (Immigration, Refugees and Citizenship Canada, 2024). The most recent (2026-2028) Immigration Levels Plan focuses on continuity by aiming to bring the temporary resident population to “sustainable levels,” or “to less than 5% of our total population by the end of 2027” (Immigration, Refugees and Citizenship Canada, 2025e). The plan states that IRCC wants to collaborate with the provinces and territories to prioritize individuals who wish to study or work in areas affected by tariffs, labor shortages, and rural and remote community needs. IRCC will also prioritize granting permanent residence to people with sought-after skills and experience.^Note 

The objectives contained in the 2026–2028 Immigration Levels Plan provide essential benchmarks for formulating short-term assumptions given that NPRs, as defined by Statistics Canada, are for the most part also temporary residents, as per IRCC’s definition. But the correspondence is not exact. For example, in addition to study or work permit holders, the NPR population includes their family members, protected persons and related groups, work and study permit holders in the process of renewal, and persons who arrived under the Canada-Ukraine Emergency Travel Authorisation (CUETA). Conversely, individuals who only have a visitor permit in Canada and who are not family members of a work or study permit holder are not included in the NPR population but are included in the statistics published by IRCC. (Figure 8.1.1). Furthermore, while the plan specifies that the objectives will be achieved by taking departures into account, limiting admissions and reducing immigration levels, only targets in terms of new arrivals are provided, and these are limited to the categories of foreign students and temporary foreign workers (Table 8.1.1). The targets represent a decrease compared to the figures observed in 2024 but continuity with the volumes observed more recently (i.e. between October 2024 and September 2025, the most recent period for which figures were available at the time the assumptions were prepared). But it is also necessary to consider temporary residents who will leave the country, renewal applications, transitions to permanent resident status, and the future number of asylum seekers, events over which IRCC does not necessarily exercise strict control, and which are therefore more difficult to anticipate.^Note  There is therefore uncertainty about how the reduction in the number of temporary residents will be achieved in the short term and what the impact will be on the population of the NPRs.  

Figure 8.1.1 start

Description for Figure 8.1.1

This figure illustrates how Statistics Canada defines non-permanent residents (NPRs) and how IRCC defines temporary residents and asylum claimants. It provides context on the differences and similarities between the two definitions and on how each organization uses these data.

The visual layout is a stylized Venn diagram that highlights which sub-groups are included in either definition or in both.

Groups included in both definitions are shown in the overlapping area of the diagram, split into two halves to represent distinct sub-groups:

• Asylum claimants
• Work or study permit holders

Groups included only in Statistics Canada’s definition of NPRs are shown in the left outer part of the diagram:

• Protected persons and related groups
• Family members of permit holders living with them
• Work or study permit holders awaiting extension
• Persons who arrived under CUAET

Group included only in IRCC’s definition of temporary residents appears in the right outer part of the diagram:

• Visitor visas and supervisas

Figure 8.1.1 end

That being said, the measures taken by the government to reduce the number of temporary residents in the country have had a significant impact on the number of NPRs. While they represented 7.6% of the Canadian population on October 1, 2024, a historic peak, this proportion has since declined to 6.8% on October 1, 2025 (Statistics Canada, 2025d). These changes generated a significant slowdown in Canada’s population growth in recent months. According to preliminary demographic estimates, Canada's population declined by more than 76,000 people (-0.2%) during the third quarter of 2025, reaching 41,575,585 as of October 1, 2025. By comparison, Canada posted quarterly population growth rates of 1.0% and 0.6% in the third quarters of 2023 and 2024, respectively, driven mainly by an important increase in the number of NPRs.^Note  Caranci & Ercolao (2025) note that the slowed growth has already helped ease pressure on the housing market (mainly the rental market) and curb rising unemployment. However, researchers are concerned that the decline in the number of work permit and study permit holders may increase financial pressure on postsecondary institutions and industries that rely heavily on temporary foreign workers (Valencia & Bartlett, 2025).

Overall, the government's policy directions are consistent with the results of the recent public consultation process conducted by IRCC, which showed that a large proportion of individuals considered the temporary resident targets for 2026 and 2027 contained in the previous Immigration Levels Plan to be too high (80 per cent) and wanted to see a reduction in the number of temporary residents beyond 2027 (83 per cent) (Immigration, Refugees and Citizenship Canada, 2025b). That said, the results also show a significant divide between individuals and organisations, with the latter generally favouring stabilisation or an increase after 2027.

As for longer-term trends, the vast majority of the experts who participated in the consultation process established to support the development of projection assumptions stressed that in the longer term, the number of NPRs in the country will depend on political decisions, public opinion and Canada’s attractiveness (quality of life, reputation for welcoming immigrants). According to these experts, some factors that could contribute to a decline in the number of NPRs include a government desire to limit population growth, particularly to reduce pressure on housing demand, public services and infrastructure (health, education, transportation), as well as negative perceptions surrounding the rapid increases in recent years. Similarly, other factors likely to reduce the need for temporary workers in the medium and long terms include a prolonged recession, a sustained increase in unemployment, and technological and structural changes in the labour market driven by automation and artificial intelligence.

In contrast, the number of NPRs could increase to address sectoral labour shortages and pressure from the business community to fill positions and support economic growth. Expanding international student programs, which generate revenue for postsecondary institutions and enable individuals with sought-after profiles to transition to permanent residence, could also contribute to this increase. Lastly, international crises and climate-related migration may lead to additional influxes of refugees and asylum seekers.

8.2 Projection assumptions

In the short-term, assumptions for the NPR component have been developed to reflect the government's desire to reduce the temporary resident population to less than 5% of the total population by the end of 2027. They also assume that these proportions apply to the NPR population, even though, as specified above, the concordance with the population of temporary residents is not perfect. In the longer term, the assumptions reflect the responses provided by experts during the consultation exercise (Chart 8.2.1).

Chart 8.2.1 start

Description for Chart 8.2.1

This line graph shows the probability distribution of the values that the proportion of non-permanent residents could take in Canada in 2050 provided by each expert (grey lines) as well as the aggregate probability distribution representing all the experts (red line). The horizontal axis shows the proportion of non-permanent residents. The vertical axis shows the probability density. In the aggregate distribution, there is an 80% probability that the value lies between 3.2 and 6.2. The median of the distribution is 4.6.

Chart 8.2.1 end

Three distinct assumptions are proposed: medium, low and high. In the medium assumption, the proportion of NPRs in 2026 and 2027 is established using linear interpolation between the value of 7.3% observed in July 2025 and the value of 5% hypothetically reached at the end of 2027. Even though the government is aiming for a proportion of less than 5% by that date, there are many factors that could prevent the NPR population from declining as quickly as expected, such as an increase in the number of asylum seekers for example. The target for 2050 represents the median of the aggregate distribution synthesising the responses of the experts consulted (see section 3 for more details on the method). Simple interpolation is used to complete the trajectory from 2027 to 2050 (Chart 8.2.2). The targets for the low and high projection assumptions in 2050 correspond to the 10th and 90th percentiles of the aggregate distribution of experts. The low and high assumptions were established by interpolating the difference with the average assumption in 2050 to previous years using a logarithmic function allowing for trajectories that diverge rapidly in the short term.

Chart 8.2.2 start

Data table for Chart 8.2.2

Data table for Chart 8.2.2
Table summary
The information is grouped by Year (appearing as row headers), Historic, Low assumption, Medium assumption and High assumption, calculated using percent units of measure (appearing as column headers).

Year	Historic	Low assumption	Medium assumption	High assumption
	percent
Note ... not applicable Sources: Statistics Canada. Table 17-10-0121-01 Estimates of the number of non-permanent residents by type, quarterly (DOI: https://doi.org/10.25318/1710012101-eng) and Centre for Demography.
2021	3.56	... not applicable	... not applicable	... not applicable
2022	4.07	... not applicable	... not applicable	... not applicable
2023	5.64	... not applicable	... not applicable	... not applicable
2024	7.37	... not applicable	... not applicable	... not applicable
2025	7.26	... not applicable	... not applicable	... not applicable
2026	... not applicable	5.96	6.36	6.83
2027	... not applicable	4.92	5.45	6.10
2028	... not applicable	4.38	5.00	5.75
2029	... not applicable	4.28	5.00	5.86
2030	... not applicable	4.20	4.99	5.95
2031	... not applicable	4.12	4.98	6.02
2032	... not applicable	4.05	4.96	6.08
2033	... not applicable	3.98	4.95	6.12
2034	... not applicable	3.92	4.93	6.15
2035	... not applicable	3.86	4.90	6.17
2036	... not applicable	3.80	4.88	6.18
2037	... not applicable	3.74	4.85	6.19
2038	... not applicable	3.69	4.82	6.19
2039	... not applicable	3.64	4.79	6.19
2040	... not applicable	3.59	4.77	6.19
2041	... not applicable	3.54	4.74	6.18
2042	... not applicable	3.50	4.71	6.18
2043	... not applicable	3.46	4.68	6.17
2044	... not applicable	3.42	4.66	6.16
2045	... not applicable	3.38	4.64	6.16
2046	... not applicable	3.35	4.62	6.15
2047	... not applicable	3.32	4.60	6.15
2048	... not applicable	3.29	4.59	6.16
2049	... not applicable	3.27	4.58	6.17
2050	... not applicable	3.25	4.57	6.18

Chart 8.2.2 end

The regional distribution and composition by age and gender of NPRs are based on proportions observed in the past. From 2026 to 2030, the proportion of the total number of NPRs that a region receives is a linear interpolation of the proportion observed in 2025 and the average proportion observed from 2021 to 2025 (Table 8.2.1). The distribution remains fixed after 2030. Furthermore, the proportions are adjusted during the projection period based on changes in the relative size of the regions within the provinces and territories. For example, a region whose demographic weight increases will receive an increasing proportion of NPRs. The assumption is that regions that are developing more rapidly offer a growing number of opportunities for NPRs compared to regions with slower growth. This adjustment has no impact on the distribution by age and gender within a region.

9 Projection of emigration

9.1 Background

The emigration component is the net amount of two elements: people leaving the country (emigration) and Canadians returning to the country (return emigration). Permanent emigrants, referred to simply as emigrants, are defined as Canadian citizens or permanent residents who left Canada to settle in another country. Return emigrants are defined as Canadian citizens or immigrants who have returned to Canada to re-establish permanent residence after having previously emigrated.

Historical series of emigration rates are short and highly volatile.^Note  It is therefore hazardous to extract trends for each province and territory. With regard to the long-term evolution of emigration and return emigration, experts^Note  believe that it will depend mainly on the country's economic conditions. For example, good living conditions and integration (affordable housing, quality jobs, policies promoting access to the labour market) and an attractive economic environment (increased GDP per capita, productivity, employment, incentives for innovation and favourable taxation) could increase Canada's retention and attraction, which would reduce emigration and increase return migration. Added to this are external factors such as global instability, climate changes, reduced migration flows and less favourable economic conditions abroad, which could encourage more people to stay or return to Canada. Experts also note that a decrease in immigration would automatically reduce the number of departures, since immigrants are more likely to emigrate. Conversely, a deterioration in living or economic conditions in Canada and more favourable economic conditions abroad would be likely to encourage an increase in emigration and a decrease in return emigration.

9.2 Projection assumptions

Three projection assumptions (medium, low and high) for emigration were established, formulated in terms of the gross migraproduction rate (GMPR)^Note  and distributions by age, gender, province and territory. As with most other components, assumptions are made taking into account recent trends in each region and potential future developments envisaged at national level by experts.

The medium assumption was developed to reflect the historical levels in each province and territory and the possible long-term developments. A short-term GMPR forecast (for period 2029-2030) was produced for each region using simple exponential smoothing (SES) models applied to time series from 2016/2017 to 2024/2025. Given that they show atypical trends related to COVID-19 travel and migration restrictions, values for the 2020/2021 period have been imputed to the median value for the historical period. The SES model was chosen for its capacity to provide higher weight to more recent data and work with a relatively short time series of historical data. The long-term targets (2049/2050) are determined based on values taken from the aggregate distribution of the nine experts consulted. For the medium assumption, the national target corresponds to the median of the distribution (Chart 9.2.1). The trajectories of the medium assumption are developed by interpolation using a cubic spline where the nodes are the most recent observed values of the GMPR, the short-term projected values and the long-term targets (Chart 9.2.2).^Note Note  In each region, the long-term GMPR targets are set so that the ratio between the 2030 and 2050 GMPR targets projected at the national level remains the same in each region. After 2050, the assumptions are kept constant for the remainder of the projection (until 2075).

Chart 9.2.1 start

Description for Chart 9.2.1

This line graph shows the probability distribution of the values that the gross migraproduction rate of emigration could take in Canada in 2050 provided by each expert (grey lines) as well as the aggregate probability distribution representing all the experts (red line). The horizontal axis shows the gross migraproduction rate of emigration. The vertical axis shows the probability density. In the aggregate distribution, there is an 80% probability that the value lies between 191 and 306. The median of the distribution is 257.

Chart 9.2.1 end

The targets for the low and high assumptions in 2050 correspond to the 10th and 90th percentiles of the aggregate distribution of experts. The low and high assumptions were established by interpolating the difference with the average assumption in 2050 to previous years using a hyperbolic function (Table 9.2.1 and Chart 9.2.2). This method was employed to obtain trajectories that diverge rapidly from the medium assumption, thereby better reflecting the initial uncertainty of the projection. Lastly, composition by age and gender of projected emigrants is established based on the proportions and trends observed in each province and territory in the period from 2021/2022 to 2024/2025.

Chart 9.2.2 start

Data table for Chart 9.2.2

Data table for Chart 9.2.2
Table summary
The information is grouped by Period (appearing as row headers), Historic, Low assumption, Medium assumption and High assumption, calculated using per thousand units of measure (appearing as column headers).

Period	Historic	Low assumption	Medium assumption	High assumption
	per thousand
Note ... not applicable Source: Statistics Canada, Centre for Demography.
2016/2017	289	... not applicable	... not applicable	... not applicable
2017/2018	235	... not applicable	... not applicable	... not applicable
2018/2019	217	... not applicable	... not applicable	... not applicable
2019/2020	180	... not applicable	... not applicable	... not applicable
2020/2021	155	... not applicable	... not applicable	... not applicable
2021/2022	233	... not applicable	... not applicable	... not applicable
2022/2023	262	... not applicable	... not applicable	... not applicable
2023/2024	267	... not applicable	... not applicable	... not applicable
2024/2025	272	... not applicable	... not applicable	... not applicable
2025/2026	... not applicable	224	259	285
2026/2027	... not applicable	208	253	287
2027/2028	... not applicable	199	248	285
2028/2029	... not applicable	193	245	284
2029/2030	... not applicable	189	243	284
2030/2031	... not applicable	188	243	285
2031/2032	... not applicable	187	244	286
2032/2033	... not applicable	186	244	287
2033/2034	... not applicable	186	245	289
2034/2035	... not applicable	186	246	290
2035/2036	... not applicable	186	247	291
2036/2037	... not applicable	187	247	293
2037/2038	... not applicable	187	248	294
2038/2039	... not applicable	187	249	296
2039/2040	... not applicable	188	250	297
2040/2041	... not applicable	188	251	298
2041/2042	... not applicable	189	252	299
2042/2043	... not applicable	189	253	301
2043/2044	... not applicable	189	254	302
2044/2045	... not applicable	190	255	303
2045/2046	... not applicable	190	255	304
2046/2047	... not applicable	190	256	304
2047/2048	... not applicable	191	256	305
2048/2049	... not applicable	191	256	305
2049/2050	... not applicable	191	257	306

Chart 9.2.2 end

The assumptions regarding return emigration were derived directly from those regarding emigration. More specifically, the projected long-term target for the average return migration assumption is a ratio of the target for the medium emigration assumption, i.e. the average ratio of return migrants to permanent migrants observed during the periods 2016/2017 to 2024/2025 (55.3%). The same ratio is used for both the low and high assumptions (Table 9.2.1). This assumption of a fixed ratio of return migration to permanent migration appears plausible because it tends to remain relatively stable over time, having fluctuated, for example, between 46% and 63% during the reference period. The short-term assumptions were obtained in the same way as for emigration, based on the extrapolation of trends in return emigration rates during the period 2016/2017 to 2024/2025. As with emigration, the age and gender composition of projected return emigrants is based on the proportions and trends observed in each province and territory during the period 2021/2022 to 2024/2025.

10 Projection of interprovincial migration

10.1 Background

Interprovincial migration is the movement of people between the provinces and territories in Canada. The COVID-19 pandemic and the changes in the world of work that followed upset interprovincial migration trends in the country. Record numbers of interprovincial migrants have been recorded in 2021/2022 and 2022/2023, following the start of the pandemic. However, the most recent data show a decline in the number of interprovincial migrants and a return to trends observed before the COVID-19 pandemic (Statistics Canada, 2025d).

10.2 Projection assumptions

Internal migration parameters consist of interprovincial migration rates by origin and destination. Rates are calculated based on historical data, with the various scenarios reflecting distinct historical periods. An adjustment is made to the projected migration rates to account for the fact that migration flows change only according to the sizes and characteristics of the populations of origin, regardless of the populations of the regions of destination, and to keep the projected net migration rates close to the values observed during the selected reference periods (Dion, 2017).

In order to account for the magnitude of the uncertainty associated with the projection of internal migration, six assumptions are proposed, constituting as many scenarios. Scenario M1, which can be considered a sort of average scenario, covers a period of 25 years, from 2000/2001 to 2024/2025. In the short term, however, it takes into account the recent trends. Thus, for hypothesis M1, migration rates during the first ten years are a linear interpolation between the average rates observed from 2022/2023 to 2024/2025 and those observed from 2000/2001 to 2024/2025. The rates remain constant thereafter (after 2034/2035).

Assumptions M2 to M5 reflect situations observed over shorter periods, chosen so that each province and territory has at least one assumption representative of a relatively favourable period (in terms of population growth) and another reflecting a relatively unfavourable period. Averages of net migration rates observed during the period 2000/2001 to 2024/2025, excluding the five years with the least favourable balances (in terms of population growth) and those with the most favourable balances, respectively, were used as approximate references for the choice of periods (table 10.2.1). Scenario M6 reflects the situation observed during the very recent period 2022/2023 to 2024/2025.

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