Canada’s immigrant advantage is real, and it is not selection into rich provinces

Second-generation immigrant students outperform native-born Canadians, and the advantage grows rather than shrinks when socio-economic status and province are held constant. The same analysis run on Germany produces the opposite sign.

Dr Milos Kankaras | ORCID 0000-0002-3190-7751 | Center for Psychology, Podgorica | PISA 2022 country notes, North America | August 2026

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Summary

In most high-income countries, immigrant students score below native-born students, and the argument is about how much of the gap is socio-economic. Canada is the standing counter-example, and the counter-example is usually asserted rather than decomposed. This note decomposes it.

The comparison is deliberately the same one applied to Germany elsewhere in this series, with the same code, the same adjustments and the same standard errors, so the contrast between the two systems is a finding rather than an artefact of two different analyses.

What the data shows.

• Second-generation immigrant students scored 20.2 points above native-born students (3.6). First-generation students scored 1.9 points from parity (4.0).
• Adjustment does not remove the advantage, it enlarges it. Net of socio-economic status the second-generation advantage is 22.5 points, and net of socio-economic status and province it is 21.8 points (3.3).
• First-generation students, at parity on the raw comparison, are 8.4 points ahead once socio-economic status and province are held constant (3.5).
• Speaking a language other than the language of assessment at home carries no penalty in Canada: 2.5 points unadjusted, 10.4 net of socio-economic status, for 24.0% of the cohort.

The advantage is therefore not explained away by immigrants concentrating in wealthy households or in high-performing provinces. Whatever produces it survives both controls. That is a strong result, and it is also a warning: it means Canada’s immigrant outcomes cannot be transplanted by copying a school policy, because the most likely explanation lies substantially upstream of schooling, in who Canada’s immigration system selects.

Why this is the question for Canada

Canada is the system most often cited when other countries discuss immigrant education, and it is cited for a single stylised fact: that its immigrant students do not underperform. The fact is true. The inference usually drawn from it, that Canadian schools have solved something other systems have not, does not follow from it.

Two alternative explanations are testable in the public microdata and are tested here. The first is composition: immigrant families in Canada are on average more educated and more affluent than in most receiving countries, so the raw comparison may simply reflect that. The second is geography: immigrants concentrate in Ontario and British Columbia, and if those provinces perform well the national comparison inherits their advantage.

Both explanations predict that the advantage should shrink under adjustment. It does the opposite, which is the interesting part.

The data, and how it was handled

23,073 students in 863 schools, representing a weighted population of 357,911 15-year-olds, from the OECD’s PISA 2022 student and school Public Use Files. National mean in mathematics: 496.9 points (SE 1.6).

Achievement is imputed rather than measured, so estimates are pooled by Rubin’s rules over all ten plausible values. The sample is clustered in schools, so standard errors come from the 80 Fay-adjusted replicate weights the OECD ships for the purpose. Omitting either understates the uncertainty, usually by a factor of two or more.

Source: OECD, PISA 2022 Results (Volume I and II) Country Note: Canada, published 5 December 2023, https://www.oecd.org/en/publications/pisa-2022-results-volume-i-and-ii-country-notes_ed6fbcc5-en/canada_901942bb-en.html (read 6 August 2026)

The immigrant advantage, and what adjustment does to it

15,053 native-born students, 2,565 second-generation and 2,845 first-generation, together 16.3% and 14.4% of the cohort respectively. Canada’s immigrant students are not, in these data, socio-economically advantaged relative to the native-born.

That is the composition explanation failing. Immigrant students in Canada sit at or below the native-born on the socio-economic index, so composition cannot be what produces their advantage, and adjusting for it makes the advantage larger.

The geographic explanation fails in the same way. Holding province constant alongside socio-economic status, the second-generation advantage is 21.8 points and the first-generation advantage is 8.4 points. Comparing an immigrant and a native-born student of the same socio-economic background in the same province, the immigrant student is ahead.

The mechanism this note cannot see is immigration selection. Canada admits a large share of its immigrants through a points system weighted towards education, and the children of selected migrants carry advantages that the PISA socio-economic index, built from parental occupation, education and household possessions, captures only in part. That is the leading candidate explanation, and it is a hypothesis this analysis is consistent with rather than a finding it establishes.

Provincial variation, for context

Canada is one of the few systems where PISA adjudicates sub-national estimates, so provincial figures are properly supported by the sampling design rather than being an analyst’s slice of a national sample.

The provincial spread is substantial and is a reminder that Canada’s national mean is an average across ten education systems with separate ministries and separate curricula. A country note that stopped at the national number would be describing an entity that does not administer any school.

Can this comparison be trusted? A measurement audit

Test scores are placed on a common scale by design. Questionnaire indices are not. Comparing an index across groups assumes the items mean the same thing in every group being compared, and that assumption is testable. It is usually not tested.

Sense of belonging at school is the index most often reached for in discussions of immigrant integration, and it is the one most vulnerable to the objection that different groups interpret the items differently. Before comparing belonging across immigrant background, the measurement model is tested across exactly those groups.

Measurement invariance of the sense of belonging at school block across immigrant background. N = 19,320. Estimator MLR. Decision rule after Chen (2007).

The comparison can then be read as intended, and it is the second half of Canada’s story: whatever advantage immigrant students carry into achievement, it is not accompanied by a belonging deficit of the kind reported in many European systems.

What follows

Three statements are supported and narrow enough to defend.

• Canada’s immigrant advantage is not composition and not geography. It survives, and grows under, adjustment for socio-economic status and province.
• Home language is not a disadvantage marker in Canada. Students speaking another language at home perform at parity or better, in contrast with most European systems where the same indicator identifies a substantial gap.
• The national mean conceals a provincial spread wide enough that provincial figures, not the national one, are the relevant unit for any policy discussion.

The obvious next step for anyone wanting to learn from Canada is to separate immigration selection from schooling, which PISA alone cannot do. Linking to admission-category data, or comparing outcomes for immigrant children by parental admission stream, would answer the question that other countries actually want answered.

What this note does not claim

• No trend statement. Comparing 2022 with an earlier cycle requires the published link error for that cycle pair to be carried in the variance. No such comparison is made here.
• No causal claim. Every difference is an association measured at one point in time. “Net of ESCS” means one measured index is held constant, not that other things are equal.
• The invariance cascade is fitted without the replicate-weight design, which is standard practice and is stated rather than left implicit.
• Immigration selection is not observed in these data. The note reports what survives adjustment and names selection as the leading unobserved explanation; it does not measure it.
• Province is reported as adjudicated regions in the public file. Territorial jurisdictions are not separately represented, so this is a ten-province picture rather than a complete national one.

Method and reproducibility

Data: OECD PISA 2022 Public Use Files, downloaded from webfs.oecd.org on 6 August 2026. Point estimates pooled over ten plausible values by Rubin’s rules; sampling variance from 80 Fay-adjusted replicate weights with a Fay factor of 0.5, computed per plausible value and averaged; imputation variance inflated by (1 + 1/M). Invariance tested as a staged configural, metric, scalar and strict cascade in lavaan with full-information estimation for the rotated questionnaire design, plus a categorical sensitivity re-run on pairwise-present data.

Subgroups are derived from variables the OECD codes identically in every participating system, so this note was produced without country-specific recoding. Where a country’s own sampling strata carry a more policy-relevant structure, that structure is used instead and the note says so.

Enquiries about reproducing the analysis are welcome at milos@centerforpsychology.me. Commissioning the equivalent for another country is consulting work, handled by AdriaMont Consulting DOO at milos@adriamont.me.

All country notes in this series