Immigration Impact Matrix
20 Countries × 7 Themes at a Glance
Official data organised as a cross-country matrix. Red = negative impact documented, green = positive, grey = no public data. Consult each country page for individual figures.
| Theme |  DK |  SE |  NO |  FI |  DE |  AT |  CH |  FR |  BE |  NL |  UK |  IE |  IT |  ES |  PT |  CZ |  US |  CA |  AU |  NZ |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Population share Definition varies by country | 12.6% | 21% | 17.5% | 11.7% | 25.6% | 20.5% | 27.7% | 11.3% | 13.8%* | 24.6% | 19% | 12% | 9.1% | 14% | 14% | 10.4% | 14.3% | 23% | 32% | 28.8% |
| Fiscal impact Net fiscal effect | −DKK 16bn | +SEK 6bn* | −4.1m NOK | ongoing study | −€2.1bn/yr | N/A | N/A | N/A | N/A | by motive − | OBR mixed | N/A | INPS + | GDP + | N/A | N/A | NAS mixed | N/A | skilled + | N/A |
| Employment gap Natives vs immigrants | −10 pt | −10.5 pt | −12 pt | N/A | women −35 pt | large gap | medium gap | −5 pt unempl. | large gap | large gap | medium gap | medium gap | medium gap | medium gap | medium gap | small gap | medium gap | medium gap | regional var. | N/A |
| PISA gap PISA 2022 maths | +28 pts gap | large gap | large gap | large gap | large gap | large gap | medium gap | −51 pts | large gap | large gap | medium gap | small sample | medium gap | medium gap | medium gap | N/A | medium gap | medium gap | +26 pts over | outperform |
| Crime data Origin-disaggregated | ×2.6 (adj.) | ×2.5 (raw) | over-repr. ↓ | N/A | foreign over-repr. | N/A | by nationality | nationality only | N/A | N/A | N/A | N/A | N/A | N/A | N/A | N/A | N/A | N/A | no national data | N/A |
| Housing impact Documented housing effects | 5 parallel soc. | 65 vuln. areas | overcrowd. 26% | N/A | gap exists | gap exists | N/A | QPV cluster | large reg. var. | gap exists | demand pressure | demand surge | gap exists | gap exists | gap exists | N/A | gap exists | housing pressure | +0.5% rents | gap exists |
| Asylum claims Recent claim level | medium | medium | low (↓) | medium | high | high (↓) | 25,781 | 153,600 | 39,615 ↑ | medium | high | surge → ↓ | high | high | 2,677 | low | medium | medium | low | low |
Note: Colour coding for population share is informational only and does not imply a value judgement. For fiscal, gap, housing and asylum rows: red = negative impact documented in official data; green = positive impact or low level; yellow = mixed or partial data; grey = no publicly available official data found.
Population share definitions vary by country — hover each cell for the definition used. Belgium (*) = 13.8% non-Belgian nationals; 36.6% if foreign-origin including naturalised citizens is counted. Germany uses migration background (broad definition). Switzerland and France use foreign nationals. Denmark, Sweden, Norway use foreign-born. Direct cross-country comparison of population shares requires caution.
Fiscal row (Norway): Figure shown is −4.1m NOK net present value per person for group R3 (asylum seekers and non-European family migration), 2015 cohort, measured 2015–2100 (SSB 2017). This is not a per-year national total. Sweden fiscal (*): +SEK 6bn applies to labour migrants only; total balance for all immigrant categories is not officially published.
Country profiles identified
Nordic restrictive model (DK / SE / NO)
Immigrant share 17–21%. Non-Western immigrants show consistently negative fiscal balances (Denmark: −DKK 16bn/yr for all immigrants and descendants, Finansministeriet 2023; Norway: −4.1m NOK net present value per person for group R3, SSB 2017). Employment and PISA gaps are large and well-documented. Data transparency is Europe's highest. Policy has shifted towards selection since the late 2010s.
Signal: Fiscal, employment and education dimensions all document negative net impacts for non-EU immigrants.
Anglosphere points-based model (AU / NZ / CA)
Immigrant share 23–32%. Australia and New Zealand show PISA reversal — immigrants outperform native-born students. Skilled migrants produce positive fiscal contributions; humanitarian and family streams show mixed results. Per-category breakdown is central to the policy design.
Signal: Skills-selection visibly shapes integration outcomes.
Southern European transition model (IT / ES / PT)
Immigrant share 9–14%. Fiscal data are limited, but Banco de España documents a positive GDP contribution. PISA gaps are moderate. Asylum claims are high (Italy is the Mediterranean entry point). Statistical transparency is lower than in Nordic countries.
Signal: Labour immigration increasingly filling demographic gaps from very low birth rates.
Central European emerging model (CZ / AT)
Austria: 20.5% immigrant share, asylum claims peaked at Europe's highest per-capita levels in 2022–23. Czechia: 10.4%, with Ukrainian refugees making up 54% of all foreign nationals. Fiscal and PISA data are not yet officially published for these countries. Integration infrastructure is still developing.
Signal: Rapid inflows after decades of low immigration — data systems lagging behind reality.
Methodological note
Each cell is a summary of data found in the country pages and involves simplification. Measurement methods, reference years and definitions of "immigrant" vary across countries. Always consult individual country pages for precise figures, sources and methodological caveats. A grey cell means "no publicly available primary source confirmed" — not "no impact exists".