HOW THE IFR DEMOGRAPHY DASHBOARD WORKS

The IFR Demography Dashboard shows how the balance between native and migrant populations could develop across 15 European countries. It presents two demographic paths for the 14 countries modelled by the IFR; France is shown separately as an external reference.

The status-quo projection continues the selected demographic trends and identifies the tipping point: the first year in which the migrant population exceeds 50% of the total population. The remigration scenario models an alternative migration path and identifies the reverse tipping point: the first year in which the migrant share falls below 5%.

These results are projections, not predictions. They show what follows from the selected starting data and assumptions about births, deaths, immigration, emigration and remigration. The precise definition of the native and migrant populations differs between countries and is stated in each country view, with further details provided in the linked Country Methodology.

Population is not merely an aggregate number. Its composition shapes the social and political environment in which elections, representation, public institutions and cultural transmission develop. Research indicates that demographic concentration and anticipated majority change can influence political incentives, group perceptions and institutional behaviour, although the precise effects vary between countries and contexts (see the literature overview in the full methodology).

The Institute uses the term population replacement for the cumulative process through which sustained replacement migration and subsequent generational change transform a country’s population composition and can turn its native majority into a minority.

From the Institute’s perspective, a stable native majority provides the demographic foundation for ethnocultural continuity, the rule of law, democracy and demographic sovereignty. Ethnocultural continuity refers to the transmission of a historically developed culture and collective identity across generations. Demographic sovereignty refers to the ability of a historically formed people to influence the long-term composition and demographic future of its own country.

The dashboard makes this development measurable. The status-quo projection shows the direction produced by the selected demographic conditions, while the remigration scenario examines how an alternative migration policy could reverse that trajectory and create the conditions for demographic normalisation.

The dashboard divides each national population into two model groups: a native population and a migrant population. Together, these groups represent the modelled total population.

For each country, the starting migrant population is defined using the broadest available national definition that can be supported by sufficiently detailed, documented and reproducible age- and sex-specific data. “Broadest” refers to the definitional and generational reach of the population category, not simply to the largest available estimate. Where several viable constructions exist, the selected model and the principal alternatives are documented in the corresponding Country Methodology. Depending on the country, the definition may be based on a person’s own birthplace, parental birthplace, citizenship at birth, an official origin classification or census ethnicity. It may therefore cover only immigrants themselves or also include identifiable groups of their descendants.

The terms native and migrant provide common labels across the dashboard, but their precise statistical meaning is country-specific. The definition used for each country is stated in its dashboard box and documented in detail in the linked Country Methodology.

The dashboard uses an age-structured Leslie-matrix model, a standard method for projecting populations over time. For each country, the starting population is divided by single year of age, sex and population group.

The model then advances the population one year at a time. In each annual step:

1. Starting population
2. →Ageing and survival
3. →Births and group assignment
4. →Immigration and emigration
5. →Population in the next year

1. surviving cohorts move into the next age;
2. births are calculated from the number and age distribution of women;
3. newborns are assigned to the model group of their mother;
4. immigration is added and emigration is subtracted;
5. the resulting population becomes the starting point for the following year.

The status-quo projection provides the dashboard’s reference path. It asks how the population would develop if the selected demographic conditions continued over time.

Its principal assumptions are:

• each country begins with the most recent population data that support the required breakdown;
• fertility and mortality rates remain constant at their documented starting levels;
• immigration and emigration are treated as separate gross flows;
• these flows are normally based on the annual average observed from 2015 to 2024;
• from the common 2026 model state onward, immigration and emigration continue as constant annual numbers;
• no additional remigration is applied.

The standard migration input applies the same ten-year arithmetic-mean rule across countries, normally using the complete 2015–2024 observation window. It does not retrospectively exclude individual years and therefore includes periods of elevated migration as well as the temporary restrictions on mobility during the COVID-19 pandemic. The resulting average represents the migration regime actually observed during the decade, not a constructed crisis-free “normal” level. Excluding selected years or applying different smoothing rules by country would require additional judgements about which realised migration should count and would weaken comparability. Keeping immigration and emigration as separate fixed gross flows then preserves this observed regime instead of allowing the migration balance to change automatically with population size.

The baseline likewise does not assume that group-specific fertility rates will necessarily remain unchanged in reality. If these rates converge, fertility differences would contribute less to the long-term divergence between the two model populations. The size of this effect cannot be determined without additional assumptions about the timing, speed and endpoint of convergence. Modelling such a path would therefore not remove assumptions, but replace the constant-rate rule with a different set of transition assumptions.

For its first version, the dashboard deliberately retains the simpler rules as a transparent and comparable baseline. The status-quo projection does not predict that the selected conditions will persist unchanged; it shows their long-term implications if they do.

The tipping point is the first model year in which the migrant population becomes larger than the native population. It marks a clear numerical majority reversal within the selected country definition.

The 50% threshold does not imply that a society changes abruptly in a single year. Demographic transformation develops over time, and research has identified threshold and anticipatory effects in areas such as residential change, intergroup perceptions and political representation before a national majority reversal occurs (see the literature overview in the full methodology). The dashboard therefore presents the tipping point as the culmination of a longer development rather than its beginning.

For the Institute, the loss of a native majority is politically significant because it affects the conditions for ethnocultural continuity, the rule of law, democracy and demographic sovereignty. This is the Institute’s interpretation of the modelled transition; the year itself is a statistical result produced by the stated assumptions.

The remigration scenario begins from the same population, fertility and mortality assumptions as the status-quo projection. After the common 2026 model state, it changes the migration path in four ways:

• native immigration remains at its status-quo level;
• migrant immigration is reduced to 10% of its status-quo level;
• regular emigration changes proportionally with the remaining population of each model group;
• an additional annual remigration flow is applied to the migrant population. The annual number remains fixed at 1% of the country’s migrant population recorded in the underlying national starting data.

The fixed 1% rate is a demographic scenario parameter, not a single policy measure or a prescribed mix of instruments. In practice, the modelled reduction could result from a combination of enforced returns of persons without a legal right to remain, voluntary return, financial and structural incentives for return, and a reversal of existing push and pull factors. Although assimilation is not part of the calculation, a natural rate of assimilation could also contribute to an equivalent reduction in the migrant population and could increase as the native demographic majority becomes more dominant and stable.

Regular emigration is treated proportionally in this scenario because keeping it fixed as the migrant population declines would make it an ever-increasing share of the remaining population and mechanically accelerate the decline. The additional remigration flow remains fixed because it represents the explicitly defined scenario component rather than ordinary emigration.

The reverse tipping point is the first model year in which the migrant share falls below 5%. The Institute uses this threshold as a theoretical endpoint and a possible orientation point for demographic normalisation and harmonisation. The restoration of a stable native majority and the establishment of a demographic balance in which continued immigration and assimilation no longer place the continuity of that majority in question could occur before this theoretical endpoint is reached.

The 5% threshold is an institutional scenario target, not a universal scientific threshold. It also provides a broad historical orientation, as migrant or foreign-national shares in several Western European countries were around or below this level before large-scale post-war immigration. The underlying historical figures and their differing definitions are documented in the full methodology.

Like every long-term demographic projection, the dashboard uses simplifying rules to apply a consistent model across countries.

• The model does not simulate partnership formation, intermarriage or a separate mixed-background population. Newborns are assigned to their mother’s model group, while the father’s background is not modelled separately.
• This assignment remains in place throughout the projection and may therefore extend beyond the generational reach of the national definition used for the starting population. It is a transparent modelling rule, not a claim about individual identity or social affiliation.
• This simplification is deliberate. The first version of the dashboard is designed as a transparent and comparable baseline model with a limited number of assumptions. Modelling mixed-parent families, assimilation or later transitions between groups would require additional rules about when, how quickly and under which conditions such transitions occur. These rules would not remove uncertainty, but replace the current classification rule with a more complex set of assumptions that would themselves require empirical validation. The baseline therefore does not attempt to predict these social processes. It keeps them outside the model so that its assumptions and their effects remain understandable and consistently applicable across countries.
• The starting population includes only those migrant generations that can be identified in the available national statistics. Statistically unobserved later generations are not added through estimates.
• Fertility differences are based on the closest available official categories. In some countries, these categories are narrower than the population definition used by the model.
• The same age- and sex-specific mortality pattern is generally applied to both model populations because sufficiently detailed group-specific mortality data are not consistently available.

The country-specific implications of these assumptions are documented in the linked Country Methodologies.

The IFR projection model is applied consistently across the 14 modelled countries, but their underlying population definitions are not fully harmonised. Some countries identify only foreign-born people, while others also include their children, later descendants or ethnicity-based groups.

These differences affect the starting migrant share and must be considered when comparing countries. Portugal, for example, covers only the foreign-born population, while Ireland and the United Kingdom use census ethnicity.

France is presented separately using the OID’s high scenario as an external reference. Its definition and methodology differ from those of the IFR projections, so the displayed year around 2050 is not directly comparable with IFR tipping-point years. The France country methodology explains the source and meaning of this figure.

The precise definition is displayed in each country box. Sources, coverage and country-specific methodological decisions are available through “View country methodology”.

Not necessarily. The dashboard can model only those population groups that remain identifiable in the available national statistics. Most official definitions include immigrants and parts of the second generation but no longer classify later descendants as part of the migrant population.

This loss of statistical visibility does not necessarily mean that a family’s migration history, ethnic identification or identification with an ancestral country has disappeared. Countries in which large-scale immigration began earlier can therefore have more third, fourth and later-generation descendants outside the statistically observable migrant population.

Germany illustrates this limitation particularly clearly. Its model uses the official migration-background definition, which generally covers immigrants and their children. Because large-scale post-war immigration began in the 1960s and 1970s, however, substantial parts of the third and later generations are no longer separately identifiable.

The dashboard does not add these statistically unobserved later generations through speculative estimates. Their absence is documented as a limitation of the available data.

The dashboard presents conditional demographic projections, not exact predictions of the future. Results that lie closer to the present are more directly connected to the observed starting conditions, while distant tipping points primarily show the long-term implications of holding the selected assumptions constant.

The year shown is the first model year in which the relevant threshold is crossed. It is an annual-resolution model result, not a prediction of a precise calendar date.

Differences in definitions and gaps in official statistics determine what can be calculated, but they are not a reason to leave long-term demographic change unexamined. The dashboard uses the best available official data, discloses the assumptions required to make them usable and provides country-specific documentation wherever the statistical basis differs.

The Institute regards transparent definitions, reproducible calculations and more complete demographic statistics as prerequisites for an honest public debate. Where official data cannot fully describe the development of migrant populations across generations, this absence should be made visible and should strengthen the case for better data collection.

This page provides a concise explanation of how the dashboard works. The complete downloadable methodology contains the full model specification, formulas, assumptions, remigration parameters, literature context and individual country chapters with their principal sources.

Country-specific definitions, data construction and methodological considerations can also be accessed directly through “View country methodology” in the corresponding country box.

Download the full methodology (PDF)