Economic and Social Reports
Economic outcomes of Provincial Nominees: Differences between Express Entry and non-Express Entry
DOI: https://doi.org/10.25318/362800012026000200005-eng
This study was jointly conducted by Immigration, Refugees and Citizenship Canada and Statistics Canada.
Canada’s immigration system plays an important role in addressing the country’s short- and long-term labour market needs, admitting many immigrants with high levels of education, official language proficiency and work experience. Across provinces and territories, distinct regional population dynamics and economic conditions create varying demands for immigration to address specific workforce gaps, demographic challenges and community development priorities. From
The expansion of the PNP has played a primary role in bringing economic immigrants to the Atlantic and Prairie provinces (Picot et al., 2023a). Provincial Nominees used to earn more in the initial years after immigration than immigrants in the Federal Skilled Worker Program (FSWP), but this pattern was reversed in recent years, likely because of changes in the selection criteria for FSWP immigrants (Picot et al., 2023b). In 2015, IRCC introduced the Express Entry (EE) system to manage applications for federal economic immigration streams (IRCC, 2024). Compared with the earlier points system, this approach is more efficient in selecting applicants with a high likelihood of economic success through the Comprehensive Ranking System (CRS). EE principal applicants (PAs) had higher entry earnings than non-EE PAs (IRCC, 2020).
Through the PNP, provinces and territories can select and nominate applicants from the EE candidate pool to partially meet their annual PNP allocation (IRCC, 2017; 2024). Understanding the differences in human capital characteristics and labour market outcomes between EE Provincial Nominees (enhanced PNs) and regular (base) PNs can inform policy discussions regarding potential ways of improving the PNP and the coordination between federal and provincial immigration programs (Business Council of Alberta, 2024; Office of the Auditor General of Ontario, 2024).
Several factors may affect the differences between enhanced PNs and base PNs. The EE system, to which EE PNs are invited to apply, focuses on higher-skilled and higher-educated candidates, while some base PNP streams seek medium and lower-skilled workers to fill chronic labour market needs at different skill levels. This can result in differences in skill and education levels between enhanced EE and base PNs.Note Furthermore, the additional language and education assessments imbedded in the CRS may improve the level and quality of human capital for enhanced PNs relative to base PNs. These screens are not necessarily required for base PNs. However, under the CRS, EE applicants with a provincial nomination are generally guaranteed admission (IRCC, 2017; 2024). Consequently, EE candidates with lower CRS scores or lower levels of human capital are more likely to be admitted through the PNP than through federal programs (Picot et al., 2023b). Whether going through the EE pool makes a difference in the characteristics and labour market outcomes of PNs remains to be seen.
The objective of this study is to examine whether enhanced PNs have better labour market outcomes than base PNs. This study uses the Longitudinal Immigration Database, which combines the admission records and annual tax information (
The share of Provincial Nominee Program principal applicants screened through the Express Entry system has increased
Enhanced PNP PAs accounted for 21% of all PNP PAs in 2016, when a sizable number of immigrants were admitted under the newly implemented EE system (Chart 1). Nova Scotia, Ontario and British Columbia had the largest shares, at about 35% or higher. Manitoba, Newfoundland and Labrador, and Alberta had the lowest shares, at about 1% or lower.
From
Ontario had the highest share (57%) of enhanced PNs among its PNP PAs in 2024, followed by British Columbia (56%) and New Brunswick (41%). Saskatchewan (11%) and Newfoundland and Labrador (8%) had the lowest share of PNP PAs screened through the EE system.

Data table for Chart 1
| 2024 | 2016 | |
|---|---|---|
| NL | 8.3 | 0.5 |
| PE | 18.2 | 29.1 |
| NS | 22.8 | 56.7 |
| NB | 41.0 | 18.0 |
| ON | 57.4 | 49.1 |
| MB | 27.5 | 1.1 |
| SK | 11.1 | 16.3 |
| AB | 34.8 | 0.0 |
| BC | 56.4 | 34.8 |
| YT | 8.5 | 8.2 |
| All of Canada | 37.6 | 20.5 |
| Sources: Statistics Canada, Longitudinal Immigration Database. | ||
Enhanced Provincial Nominee Program principal applicants had higher levels of education and earnings than base Provincial Nominee Program streams
While enhanced and base PNP PAs had similar demographic profiles in terms of sex, age at admission and knowledge of official languages, there was greater disparity in educational attainment (Table 1, left panel). Enhanced PNs were more likely to have a university degree (78%) than base PNs (65%).
There was also a disparity in intended occupations. Nearly all the intended occupations of enhanced PNP PAs were at the managerial, professional, and skilled and technical levels, compared with about two-thirds of base PNP PAs. These differences in education and intended occupation would tend to result in higher earnings among enhanced PNs, compared with base PNs. However, enhanced PNP PAs were 20 percentage points less likely to have Canadian work or study experience than base PNP PAs. This would tend to reduce initial earnings among enhanced PNs, compared with base PNs.
There was little difference in employment incidenceNote between enhanced and base PNP PAs at one year and three years after admission.
Based on annual earnings, enhanced PNP PAs outearned base PNP PAs by about 19% (
Spouses and dependants of enhanced Provincial Nominee Program principal applicants have greater employment earnings than spouses and dependants of base Provincial Nominee Program principal applicants
There were only modest differences between the demographic profiles of spouses and dependants of enhanced PNP PAs and those of spouses and dependants of base PNP PAs (Table 1, right panel).Note Of note, spouses and dependants of enhanced PNP PAs were about 5 percentage points less likely to have no official language proficiency than the non-EE group. Spouses and dependants of enhanced PNP PAs were also about 12 percentage points less likely to have previous Canadian work or study experience than their base counterparts.
Spouses and dependants of enhanced PNP PAs had lower employment incidence than their base PNP counterparts by about 5 percentage points one year after admission and 1 percentage point three years after admission (
Among those who were employed, the enhanced group had higher annual earnings than the base group by about 21% (
In summary, the results from this article show that enhanced screening through the EE selection matters for the labour market outcomes of PNP PAs. One year and three years after arrival, PNP PAs who were screened through EE had higher average employment earnings than those admitted through the base streams. This result held, although somewhat reduced, after accounting for differences in sociodemographic characteristics. Furthermore, spouses and dependants of enhanced PNP PAs had higher employment earnings than spouses and dependants of base PNP PAs. The enhanced PNP category is designed to attract higher-skilled individuals, while base PNP streams are used to address labour market shortages across varying skill levels.
| Principal applicants | Spouses or dependants | ||||||
|---|---|---|---|---|---|---|---|
| Enhanced provincial nominees | Base provincial nominees | Total | Enhanced provincial nominees | Base provincial nominees | Total | ||
| percent | |||||||
Source: Statistics Canada, Longitudinal Immigration Database. |
|||||||
| Sex | |||||||
| Male | 62.8 | 63.5 | 63.3 | 39.3 | 34.8 | 36.3 | |
| Female | 37.3 | 36.5 | 36.7 | 60.8 | 65.2 | 63.7 | |
| Age at landing | |||||||
| 29 years or younger | 40.3 | 42.5 | 41.7 | 22.0 | 26.0 | 24.6 | |
| 30 to 39 years | 46.2 | 34.4 | 38.4 | 56.1 | 41.9 | 46.8 | |
| 40 years or older | 13.5 | 23.1 | 19.9 | 21.8 | 32.1 | 28.6 | |
| Official languages | |||||||
| Unable to speak English or French | 0.0 | 1.0 | 0.6 | 1.8 | 6.3 | 4.8 | |
| Other mother tongue, able to speak English or French | 90.1 | 92.7 | 91.9 | 88.9 | 87.6 | 88.1 | |
| Mother tongue English or French | 9.9 | 6.3 | 7.5 | 9.3 | 6.1 | 7.2 | |
| Education | |||||||
| Secondary or less | 5.4 | 8.6 | 7.5 | ... not applicable | ... not applicable | ... not applicable | |
| Some postsecondary | 16.4 | 24.3 | 21.6 | ... not applicable | ... not applicable | ... not applicable | |
| Bachelor's degree | 46.3 | 41.7 | 43.3 | ... not applicable | ... not applicable | ... not applicable | |
| Graduate degree | 31.8 | 23.0 | 26.0 | ... not applicable | ... not applicable | ... not applicable | |
| Education missing | 0.1 | 2.4 | 1.6 | ... not applicable | ... not applicable | ... not applicable | |
| Intended occupation | |||||||
| Managerial | 13.6 | 7.9 | 9.8 | ... not applicable | ... not applicable | ... not applicable | |
| Professional | 38.7 | 11.9 | 21.0 | ... not applicable | ... not applicable | ... not applicable | |
| Skilled and technical | 46.1 | 44.3 | 44.9 | ... not applicable | ... not applicable | ... not applicable | |
| Intermediate and clerical | 0.6 | 17.9 | 12.0 | ... not applicable | ... not applicable | ... not applicable | |
| Elemental and labourers | 0.0 | 7.8 | 5.2 | ... not applicable | ... not applicable | ... not applicable | |
| Others | 1.0 | 10.2 | 7.0 | ... not applicable | ... not applicable | ... not applicable | |
| Canadian work or study experience | |||||||
| No prior Canadian work or study experience | 34.2 | 14.4 | 21.1 | 54.0 | 42.2 | 46.2 | |
| Work or study permits before immigration | 65.8 | 85.6 | 78.9 | 46.0 | 57.8 | 53.8 | |
| Source region | |||||||
| United States | 0.9 | 0.5 | 0.6 | 0.9 | 0.6 | 0.7 | |
| Caribbean and Central and South America | 5.4 | 5.2 | 5.3 | 7.4 | 7.8 | 7.6 | |
| Europe | 6.8 | 8.5 | 7.9 | 7.2 | 10.9 | 9.6 | |
| Africa | 13.8 | 6.2 | 8.8 | 18.2 | 7.3 | 11.0 | |
| Southern Asia | 49.7 | 38.4 | 42.2 | 45.1 | 28.5 | 34.2 | |
| Southeast Asia | 5.0 | 16.1 | 12.3 | 5.6 | 20.3 | 15.3 | |
| Eastern Asia | 12.6 | 21.2 | 18.3 | 9.4 | 19.8 | 16.2 | |
| Western Asia | 4.6 | 3.1 | 3.6 | 5.3 | 4.3 | 4.6 | |
| Other regions | 1.4 | 0.8 | 1.0 | 0.9 | 0.6 | 0.7 | |
| Employment incidence, observed | |||||||
| One year after immigration, 2016 to 2019 arrivals | 92.8 | 92.4 | 92.5 | 72.4 | 76.9 | 75.8 | |
| One year after immigration, 2020 to 2022 arrivals | 94.0 | 92.9 | 93.4 | 80.2 | 78.9 | 79.4 | |
| Three years after immigration, 2016 to 2019 arrivals | 93.2 | 91.3 | 91.8 | 77.9 | 79.0 | 78.8 | |
| Employment incidence, adjusted | |||||||
| One year after immigration, 2016 to 2019 arrivals | 92.7 | 92.5 | 92.5 | 74.7 | 76.2 | 75.8 | |
| One year after immigration, 2020 to 2022 arrivals | 93.8 | 93.1 | 93.4 | 79.6 | 79.3 | 79.4 | |
| Three years after immigration, 2016 to 2019 arrivals | 92.4 | 91.5 | 91.8 | 79.2 | 78.6 | 78.8 | |
| Average annual earnings among the employed, observed | 2023 constant dollars | ||||||
| One year after immigration, 2016 to 2019 arrivals | 62,100 | 52,300 | 54,800 | 37,400 | 30,900 | 32,400 | |
| One year after immigration, 2016 to 2019 arrivals | 62,100 | 52,300 | 54,800 | 37,400 | 30,900 | 32,400 | |
| One year after immigration, 2020 to 2022 arrivals | 71,300 | 53,400 | 59,200 | 46,000 | 35,000 | 38,500 | |
| Three years after immigration, 2016 to 2019 arrivals | 76,700 | 59,400 | 64,000 | 47,800 | 36,000 | 39,000 | |
| Average annual earnings among the employed, adjusted | |||||||
| One year after immigration, 2016 to 2019 arrivals | 57,500 | 53,900 | 54,800 | 35,500 | 31,500 | 32,400 | |
| One year after immigration, 2020 to 2022 arrivals | 65,200 | 56,300 | 59,200 | 44,400 | 35,700 | 38,500 | |
| Three years after immigration, 2016 to 2019 arrivals | 69,500 | 62,000 | 64,000 | 44,700 | 37,000 | 38,900 | |
Acknowledgments
The authors would like to thank Sarah Evershed, Chantal Goyette, Maciej Karpinski and Zackary Van-Daele for their advice and comments on an earlier version of this article.
Authors
Max Stick and Feng Hou are with the Economic and Social Analysis and Modelling Division, Analytical Studies and Modelling Branch, at Statistics Canada. Garnett Picot is with the Research and Knowledge Mobilization Division at Immigration, Refugees and Citizenship Canada.
References
Business Council of Alberta. (2024). Watered Down: The Case for Strengthening, Rather than Diluting, the Provinces’ Role in Immigration.
IRCC (Immigration, Refugees and Citizenship Canada). (2017). Evaluation of the Provincial Nominee Program.
IRCC (Immigration, Refugees and Citizenship Canada). (2020). Evaluation of Express Entry: Early impacts on economic outcomes and system management. Evaluation Division, Reference number: E3-2019.
IRCC (Immigration, Refugees and Citizenship Canada). (2024). Express Entry Year-End Report 2023.
Office of the Auditor General of Ontario. (2024). Ontario Immigrant Nominee Program (OINP).
Picot, G., Hou, F., & Crossman, E. (2023a). The Provincial Nominee Program: Its expansion in Canada.Economic and Social Reports, 3(7), 1-14.
Picot, G., Crossman, E., & Hou, F. (2023b). Provincial Nominee Program: Recent trends and provincial differences in earnings outcomes. Economic and Social Reports, 3(12), 1-21.
Picot, G., Hou, F., & Crossman, E. (2024). The Provincial Nominee Program: Provincial differences. Economic and Social Reports, 4(3), 1-23.
Picot, G., Stick, M., & Hou, F. (2025). The occupational outcomes of provincial nominees. Economic and Social Reports, 5(8), 1-6.
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