Evaluation of the Federal Skilled Worker program
Appendix A: Profile of Federal Skilled Workers surveyed
Out of 30,000 FSWs who arrived to Canada between 2002 and 2008 and were invited to participate in the study, 2,053 consented and 1,499 were surveyed. The information on the number of years of school completed, landing province, their gender, country of birth, level of education, age at time of landing, marital status, mother tongue, and the knowledge of official languages, allows the profile comparison of FSW surveyed to that of the sample (30,000) and the population (66,612). Appendix A presents the various distributions.
Years of School | Respondents surveyed | Total Sample | Population |
---|---|---|---|
n/a | 5.0% | 3.9% | 3.9% |
1-14 | 7.9% | 5.6% | 5.8% |
15 | 10.5% | 8.4% | 8.6% |
16 | 15.4% | 15.9% | 15.8% |
17 | 16.8% | 16.5% | 16.5% |
18 | 14.3% | 18.5% | 18.6% |
19 | 10.2% | 10.5% | 10.3% |
20 | 6.7% | 7.7% | 7.6% |
21 | 5.1% | 4.7% | 4.7% |
22 | 2.4% | 3.3% | 3.4% |
23 | 2.4% | 2.0% | 2.0% |
24 | 1.4% | 1.2% | 1.2% |
25 | 2.0% | 1.6% | 1.6% |
Province | Respondents surveyed | Total Sample | Population |
---|---|---|---|
Unknown | 0.0% | 0.0% | 0.0% |
Newfoundland | 0.4% | 0.2% | 0.3% |
Prince Edward Island | 0.5% | 0.1% | 0.1% |
Nova Scotia | 2.5% | 1.5% | 1.4% |
New Brunswick | 0.5% | 0.5% | 0.4% |
Quebec | 2.0% | 2.5% | 2.5% |
Ontario | 56.7% | 63.6% | 61.8% |
Manitoba | 1.3% | 0.9% | 0.9% |
Saskatchewan | 1.0% | 1.1% | 1.0% |
Alberta | 14.8% | 10.7% | 10.1% |
Northwest Territories | 0.0% | 0.0% | 0.1% |
British Columbia | 20.1% | 19.0% | 21.3% |
Yukon | 0.2% | 0.0% | 0.1% |
Nunavut | 0.0% | 0.0% | 0.0% |
Gender | Respondents surveyed | Total Sample | Population |
---|---|---|---|
Male | 64.2% | 69.4% | 69.3% |
Female | 35.8% | 30.6% | 30.7% |
Rank Surveyed | Citizenship country | Respondents surveyed | Rank - CIC file |
Total Sample |
Population |
---|---|---|---|---|---|
1 | British | 11.2% | 3 | 6.6% | 6.7% |
2 | India | 8.3% | 1 | 16.8% | 16.8% |
3 | China | 6.9% | 2 | 15.8% | 16.2% |
4 | U.S.A. | 6.7% | 4 | 4.3% | 4.4% |
5 | Philippines | 5.2% | 7 | 3.1% | 3.1% |
6 | Russia | 2.7% | 10 | 1.9% | 1.8% |
7 | Nigeria | 2.7% | 14 | 1.4% | 1.3% |
8 | Netherlands | 2.3% | 34 | 0.6% | 0.6% |
9 | Iran | 2.3% | 9 | 2.1% | 2.0% |
10 | Mexico | 2.1% | 17 | 1.0% | 1.1% |
Education | Respondents surveyed | Total Sample | Population |
---|---|---|---|
None | 5.0% | 3.9% | 3.7% |
Secondary or less | 1.0% | 0.7% | 0.8% |
Formal Trade Cert. or Apprenticeship | 4.2% | 2.2% | 2.3% |
Non-University Certificate or Diploma | 8.5% | 7.8% | 7.9% |
Some University- No Degree | 2.7% | 1.4% | 1.4% |
Bachelor's Degree | 41.0% | 37.3% | 36.9% |
Some Post-Grad Education - No Degree | 1.0% | 1.7% | 1.6% |
Master's Degree | 26.7% | 37.1% | 37.5% |
Doctorate | 9.8% | 7.9% | 8.1% |
Age | Respondents surveyed | Total Sample | Population |
---|---|---|---|
20-24 years old | 1.1% | 1.2% | 1.1% |
25-29 years old | 14.8% | 19.6% | 19.6% |
30-34 years old | 21.1% | 28.5% | 28.7% |
35-39 years old | 22.3% | 21.1% | 20.9% |
40-44 years old | 18.3% | 15.1% | 15.1% |
45-49 years old | 13.9% | 9.3% | 9.3% |
50-54 years old | 6.1% | 4.0% | 4.1% |
55-59 years old | 1.2% | 0.7% | 0.7% |
60-64 years old | 0.4% | 0.3% | 0.3% |
65-69 years old | 0.2% | 0.1% | 0.1% |
70-74 years old | 0.2% | 0.0% | 0.0% |
75-79 years old | 0.1% | 0.0% | 0.0% |
80-84 years old | 0.1% | 0.0% | 0.0% |
85-89 years old | 0.0% | 0.0% | 0.0% |
Age | Respondents surveyed | Total Sample | Population |
---|---|---|---|
Maximum | 82 years old | 89 years old | 89 years old |
Minimum | 22 years old | 4 years old | 4 years old* |
Average | 38 years old | 36 years old | 36 years old |
65 years old and over | 8 | 43 | 78 |
70 years old and over | 5 | 14 | 26 |
75 years old and over | 2 | 8 | 13 |
80 years old and over | 1 | 4 | 6 |
* This is likely due to a coding error. |
Marital status | Respondents surveyed | Total Sample | Population |
---|---|---|---|
Unknown | 0.0% | 0.0% | 0.0% |
Single | 32.1% | 34.3% | 34.2% |
Married | 60.2% | 60.5% | 60.4% |
Widowed | 0.2% | 0.2% | 0.2% |
Divorced | 3.1% | 2.1% | 2.2% |
Separated | 0.5% | 0.3% | 0.4% |
Common-law partner | 3.8% | 2.6% | 2.6% |
Rank Surveyed |
Mother tongue | Respondents surveyed | Rank - CIC file |
Total Sample |
Population |
---|---|---|---|---|---|
1 | English | 28.9% | 1 | 19.3% | 19.2% |
2 | Spanish | 8.5% | 5 | 4.6% | 4.4% |
3 | Arabic | 4.9% | 4 | 5.6% | 5.5% |
4 | Russian | 4.8% | 8 | 3.6% | 3.5% |
5 | Mandarin | 4.4% | 3 | 8.6% | 8.8% |
6 | Chinese | 4.1% | 2 | 9.4% | 9.9% |
7 | Tagalog | 3.9% | 11 | 2.5% | 2.6% |
8 | German | 2.5% | 19 | 1.2% | 1.2% |
9 | Dutch | 2.1% | 31 | 0.6% | 0.6% |
10 | Hindi | 2.0% | 6 | 4.6% | 4.7% |
Official languages | Respondents surveyed | Total Sample | Population |
---|---|---|---|
English | 82.0% | 84.7% | 85.0% |
French | 1.1% | 1.0% | 1.0% |
Both French and English | 14.5% | 11.2% | 11.0% |
Neither | 2.3% | 3.1% | 3.1% |
Appendix B: Logic model for FSWP
Appendix C: Comparison of Canada’s federal skilled workers program selection system with other similar programs in 2009
Country/ |
Description |
|
---|---|---|
|
Eligibility requirements |
|
Canada |
|
|
Quebec |
|
|
Australia |
|
|
New Zealand |
|
|
|
Work Experience |
Max. points |
Canada |
Maximum of 21 points are awarded for experience:
|
21 |
Quebec |
Up to 8 points awarded for experience:
|
8 |
Australia |
Additional points are awarded for years of experience
|
10 |
New Zealand |
Maximum of 30 points can be claimed for number of years worked in the relevant occupation
Additional points (max. 30) can be claimed if:
|
60 |
|
Offer of employment |
Max. points |
Canada |
Permanent job offer from a Canadian employer, approved by the Canadian Government Department of Human Resources and Skills Development Canada (HRSDC) – 10 points
|
10 |
Quebec |
Maximum 10 points are awarded under the Quebec Immigration Assured Job program for job offers outside the metropolitan area of Montreal.
|
10 |
Australia |
Points are awarded for the occupations that are in demand in Australia and are on the Migration Occupations in Demand List (MODL). Extra points are awarded if an applicant has a job offer for the occupation in demand. |
20 |
New Zealand |
|
60 |
|
Age |
Max. points |
Canada |
|
10 |
Quebec |
|
16 |
Australia |
|
30 |
New Zealand |
|
30 |
|
Language |
Max. points |
Canada |
1st language (max 16 points):
2nd language (max 8 points):
|
24 |
Quebec |
|
22 |
Australia |
IELTS test results are required. Points are awarded as:
Test results are not required for those who hold a passport from UK, USA, Canada, New Zealand, and Republic of Ireland. |
25 |
New Zealand |
NO points are awarded for language. It is a minimum requirement. |
n/a |
|
Education |
Max. points |
Canada |
|
n/a |
Quebec |
Maximum of 28 points are awarded for education:
Additional points are awarded for Field Training: Item in part I / (Foreign certificate) or in part II (Certificate from Quebec or equivalent) from the list. - 0, 2, 6, 12,or 16 pts |
25 |
Australia |
Education is assessed as part of skill level:
|
60 |
New Zealand |
If qualification(s) are not in the List of Qualifications Exempt from Assessment, or the List of Qualifications Recognized as an Exception, applicants must have their qualifications recognized by the New Zealand Qualifications Authority (NZQA). The points are awarded as follows:
|
65 |
|
Other criteria (adaptability) |
Max. points |
Canada |
Up to 10 points are awarded for:
|
10 |
Quebec |
|
39 |
Australia |
|
55 |
New Zealand |
|
50 |
Appendix D: IMDB regression results—Impact of the selection regime and selection factors on FSWS employment earnings
Assessing the impact of IRPA
Given the unique circumstances of having immigrants selected under both policy regimes entering Canada at the same time, the impacts of the IRPA selection system relative to the pre-IRPA points system was estimated by taking the mean differences in outcomes experienced by IRPA and pre-IRPA arrival cohorts. For example, in the case of employment earnings – the key outcome measure available in the IMDB data – for the 2002 arrival cohort we took differences in mean earnings in 2003 to 2006. The arrival year 2002 was omitted as immigrants arrived at various points in time during the year so the annual earnings reported for income tax purposes constitute earnings over part of the year. The portion of the year worked is not available from tax data. Similarly, for the 2003 arrival cohort we took differences in mean earnings in 2004 to 2006. Regressions were also ran taking differences in log earnings as this gives a measure of the percentage difference in earnings between immigrants selected under the IRPA and pre-IRPA selection systems.
Note that in comparing earnings of these two groups we did not control for observed characteristics such as age, education, work experience and language proficiency. The reason is that a central objective of the new IRPA policy was to select immigrants with different observable characteristics than those who would be selected under the previous policy regime. If we would have controlled for these observed characteristics, we would have eliminated this potential source of difference in immigrant outcomes. Indeed, if the only difference between the pre-IRPA and IRPA selection systems consists of choosing immigrants with different observed characteristics, controlling for these characteristics would completely eliminate the impact of the policy change.50 Note also that it was not appropriate to control for observed characteristics that may influence immigrant outcomes but that are not taken into account in the points system -- such as country of origin. To the extent that the source country composition of immigrants admitted under IRPA differs from that associated with pre-IRPA, this difference is part of the IRPA “treatment.” Controlling for this feature would have eliminated this potential source of differences in immigrant outcomes.
Based on that design, linear regressions were estimated to assess the impact of the IRPA selection regimes on FSWs outcomes. To do so, FSWs who were assessed under both regimes simultaneously (dual assessed cases) were excluded, as it was impossible to know under which of the two selection systems they were selected. Therefore, regressions were made only on pre-IRPA and IRPA cases.
The dependent variable for this first step of the analysis is employment earnings. Pooled data was used, so one individual can contribute as many times to the analysis as they have filed a tax form reporting employment earnings of $1,000 and above between 2002 and 2006. All the observations on the landing year were excluded from the regression, as this year might not represent a full year for everyone depending on when they landed during the year (i.e.: FSWs who landed in 2002 for the 2002 tax year, who landed in 2003 for the 2003 tax year were excluded, etc.).
Model 1 | Model 2 | |||
---|---|---|---|---|
Coefficient | Sig. | Coefficient | Sig. | |
Intercept | 34,665 | *** | 34,665 | *** |
Cohort 2002, tax year 2003 | -8,933 | *** | -8,933 | *** |
Cohort 2002, tax year 2004 | -3,185 | *** | -3,185 | *** |
Cohort 2002, tax year 2005 | 1,597 | *** | 1,597 | *** |
Cohort 2002, tax year 2006 | 6,946 | *** | 6,967 | *** |
Cohort 2003, tax year 2004 | -10,365 | *** | -10,365 | *** |
Cohort 2003, tax year 2005 | -4,069 | *** | -4,069 | *** |
Cohort 2003, tax year 2006 | 1,841 | *** | 1,841 | *** |
Cohort 2004, tax year 2005 | -10,380 | *** | -10,380 | *** |
Cohort 2004, tax year 2006 | -3,331 | *** | -3,331 | *** |
(reference: Cohort 2005, tax year 2006) | ||||
Cohort 2002, tax year 2003 * IRPA | 14,877 | *** | -3,001 | |
Cohort 2002, tax year 2004 * IRPA | 17,301 | *** | -1,991 | |
Cohort 2002, tax year 2005 * IRPA | 17,058 | *** | -4,011 | |
Cohort 2002, tax year 2006 * IRPA | 17,182 | *** | -6,904 | |
Cohort 2003, tax year 2004 * IRPA | 9,739 | *** | 4,335 | *** |
Cohort 2003, tax year 2005 * IRPA | 10,005 | *** | 1,298 | |
Cohort 2003, tax year 2006 * IRPA | 9,654 | *** | 340 | *** |
Cohort 2004, tax year 2005 * IRPA | 15,783 | *** | 7,387 | *** |
Cohort 2004, tax year 2006 * IRPA | 16,162 | *** | 6,384 | *** |
Cohort 2002, tax year 2003 * Gender | 22,701 | *** | ||
Cohort 2002, tax year 2004 * Gender | 24,903 | *** | ||
Cohort 2002, tax year 2005 * Gender | 27,127 | *** | ||
Cohort 2002, tax year 2006 * Gender | 31,297 | *** | ||
Cohort 2003, tax year 2004 * Gender | 7,680 | *** | ||
Cohort 2003, tax year 2005 * Gender | 12,726 | *** | ||
Cohort 2003, tax year 2006 * Gender | 14,538 | *** | ||
Cohort 2004, tax year 2005 * Gender | 11,918 | *** | ||
Cohort 2004, tax year 2006 * Gender | 14,003 | *** | ||
n | 199,190 | 199,190 | ||
df | 18 | 27 | ||
F | 612.91 | *** | 446.57 | *** |
r2 | 0.052 | 0.057 | ||
*p<0.05 | ||||
**p<0.01 | ||||
***p<0.001 |
Model 1 | Model 2 | |||
---|---|---|---|---|
Coefficient | Sig. | Coefficient | Sig. | |
Intercept | 10.013 | *** | 10.013 | *** |
Cohort 2002, tax year 2003 | -0.224 | *** | -0.224 | *** |
Cohort 2002, tax year 2004 | -0.013 | -0.013 | ||
Cohort 2002, tax year 2005 | 0.143 | *** | 0.014 | *** |
Cohort 2002, tax year 2006 | 0.304 | *** | 0.304 | *** |
Cohort 2003, tax year 2004 | -0.293 | *** | -0.293 | *** |
Cohort 2003, tax year 2005 | -0.058 | *** | -0.058 | *** |
Cohort 2003, tax year 2006 | 0.144 | *** | 0.144 | *** |
Cohort 2004, tax year 2005 | -0.299 | *** | -0.299 | *** |
Cohort 2004, tax year 2006 | -0.047 | *** | -0.047 | *** |
(reference: Cohort 2005, tax year 2006) | ||||
Cohort 2002, tax year 2003 * IRPA | 0.036 | *** | -0.189 | |
Cohort 2002, tax year 2004 * IRPA | 0.398 | *** | -0.072 | |
Cohort 2002, tax year 2005 * IRPA | 0.347 | *** | -0.092 | |
Cohort 2002, tax year 2006 * IRPA | 0.393 | *** | -0.162 | |
Cohort 2003, tax year 2004 * IRPA | 0.267 | *** | 0.119 | ** |
Cohort 2003, tax year 2005 * IRPA | 0.249 | *** | 0.025 | |
Cohort 2003, tax year 2006 * IRPA | 0.212 | *** | -0.011 | *** |
Cohort 2004, tax year 2005 * IRPA | 0.462 | *** | 0.237 | *** |
Cohort 2004, tax year 2006 * IRPA | 0.435 | *** | 0.196 | *** |
Cohort 2002, tax year 2003 * Gender | 0.697 | *** | ||
Cohort 2002, tax year 2004 * Gender | 0.608 | *** | ||
Cohort 2002, tax year 2005 * Gender | 0.566 | *** | ||
Cohort 2002, tax year 2006 * Gender | 0.722 | *** | ||
Cohort 2003, tax year 2004 * Gender | 0.210 | *** | ||
Cohort 2003, tax year 2005 * Gender | 0.328 | *** | ||
Cohort 2003, tax year 2006 * Gender | 0.324 | *** | ||
Cohort 2004, tax year 2005 * Gender | 0.319 | *** | ||
Cohort 2004, tax year 2006 * Gender | 0.342 | *** | ||
n | 199,190 | 199,190 | ||
df | 18 | 27 | ||
F | 507.41 | *** | 357.26 | *** |
r2 | 0.043 | 0.046 | ||
*p<0.05 | ||||
**p<0.01 | ||||
***p<0.001 |
Assessing the impact of selection factors
The IMDB data was also used to investigate the factors that account for successful integration into the Canadian labour market. This was done by estimating the relationship between individual earnings and individual and demographic characteristics that influence earnings. The following regression models focus on how the different factors from the selection grid impact on the employment earnings of FSWs. Again, dual assessed cases were excluded from the analysis as it was impossible to determine under which selection grid they qualified for immigration.
As the factors included in the selection grid and the weight assigned to them changed with the introduction of IRPA, equations will be estimated separately using data from the two regimes. The dependent variable for the analysis is the log of employment earnings in 2006. For the purpose of this analysis, the 2006 arrival cohort was excluded as these observations might not have contributed for a full year. In addition, in order to cover the same observation period for both selection regimes, pre-IRPA cases were considered only if they landed in 2002 or after (2002-2005 cohorts). However, it is important to note that not many IRPA cases arrived in 2002, as most of the cohort for that year was composed of pre-IRPA FSWs. Therefore, for 2002, the repartition of the sample between the two regimes was not balanced.
Model 1 | Model 2 | Model 3 | ||||
---|---|---|---|---|---|---|
Coefficient | Sig. | Coefficient | Sig. | Coefficient | Sig. | |
Intercept | 8.681 | *** | 9.634 | *** | 9.372 | *** |
Years since landing | 0.395 | *** | 0.397 | *** | 0.310 | *** |
Years since landing - squared | -0.050 | * | -0.057 | ** | -0.040 | |
Gender (Ref. Women) | 0.295 | *** | 0.272 | *** | 0.227 | *** |
Age at landing (Ref. 50 years and older) | ||||||
Less than 30 years old | 0.210 | *** | 0.313 | *** | 0.279 | *** |
30 to 34 years old | 0.179 | *** | 0.264 | *** | 0.234 | *** |
35 to 39 years old | 0.148 | ** | 0.220 | *** | 0.214 | *** |
40 to 44 years old | 0.122 | * | 0.713 | *** | 0.150 | ** |
45 to 49 years old | 0.097 | 0.139 | ** | 0.144 | ** | |
Education points (Ref. 0 to 15 points) | ||||||
20 points | 0.131 | ** | 0.183 | *** | 0.142 | *** |
22 points | 0.091 | * | 0.115 | ** | 0.094 | * |
25 points | 0.107 | ** | 0.195 | *** | 0.174 | *** |
Language points (Ref. 0 to 7 points) | ||||||
8 points | 0.052 | 0.090 | 0.065 | |||
9 to 11 points | 0.100 | 0.123 | * | 0.120 | * | |
12 points | 0.227 | *** | 0.203 | *** | 0.195 | *** |
13 to 15 points | 0.324 | *** | 0.265 | *** | 0.279 | *** |
16 points | 0.501 | *** | 0.375 | *** | 0.385 | *** |
17 to 19 points | 0.553 | *** | 0.367 | *** | 0.381 | *** |
20 points | 0.554 | *** | 0.351 | *** | 0.391 | *** |
21 to 23 points | 0.508 | *** | 0.308 | *** | 0.329 | *** |
24 points | 0.484 | *** | 0.304 | *** | 0.339 | *** |
Experience points (Ref. 15 points) | ||||||
17 points | 0.010 | 0.017 | 0.008 | |||
19 points | 0.080 | 0.064 | 0.053 | |||
21 points | 0.171 | *** | 0.152 | *** | 0.141 | *** |
Arranged employment points (Ref. 0 points) | ||||||
10 points | 0.917 | *** | 0.789 | *** | 0.743 | *** |
Arranged employment points * years since landing | -0.117 | *** | 0.100 | ** | 0.092 | ** |
Adaptability points | ||||||
Partner's education points (Ref. 0 points) | ||||||
3 points | 0.021 | 0.016 | 0.011 | |||
4 points | -0.021 | 0.032 | 0.014 | |||
5 points | 0.092 | *** | 0.135 | *** | 0.121 | *** |
Work in Canada points (Ref. 0 points) | ||||||
5 points | 0.320 | *** | 0.294 | *** | 0.274 | *** |
Study in Canada points (Ref. 0 points) | ||||||
5 points | -0.162 | *** | 0.061 | * | 0.061 | * |
Relatives in Canada points (Ref. 0 points) | ||||||
5 points | -0.081 | *** | 0.099 | *** | 0.080 | *** |
Province of residence in 2006 (Ref. Ontario) | ||||||
Atlantic | -0.002 | -0.056 | -0.084 | |||
Quebec | -0.431 | *** | -0.370 | *** | -0.380 | *** |
Manitoba and Saskatchewan | -0.040 | -0.026 | -0.036 | |||
Alberta | 0.155 | *** | 0.131 | *** | 0.145 | *** |
British Columbia | -0.053 | ** | -0.068 | *** | 0.047 | * |
Country/region of last permanent residence (Ref. United Kingdom) | ||||||
North America | -0.041 | 0.023 | ||||
Central America, South America, Caribbean and Bermuda | -0.234 | *** | -0.237 | *** | ||
Other Western and Northern Europe | -0.123 | ** | -0.108 | ** | ||
Eastern and Southern Europe | -0.399 | *** | -0.396 | *** | ||
Western, Eastern, Central and Southern Africa | -0.276 | *** | -0.241 | *** | ||
Northern Africa and West Central Asia and Middle East | -0.438 | *** | -0.414 | *** | ||
China | -0.726 | *** | -0.749 | *** | ||
Other Eastern and South-east Asia | -0.412 | *** | -0.401 | *** | ||
India | -0.310 | *** | -0.314 | *** | ||
Pakistan | -0.510 | *** | -0.556 | *** | ||
Other South Asia | -0.680 | *** | -0.678 | *** | ||
Oceania | -0.115 | * | -0.101 | |||
NOC - skill type (Ref. Professional occupations in natural science and applied sciences (21)) | ||||||
Business, finance and administration occupations, and senior management occupations (00, 01, 11, 12, 14) | 0.091 | *** | ||||
Other natural and applied sciences and related occupations (02, 22) | -0.038 | |||||
Health occupations (03, 31, 32, 34) | -0.198 | *** | ||||
Occupations in social science, education, government service and religion (04, 41, 42) | -0.250 | *** | ||||
Occupations in art, culture, recreation and sport (05, 51, 52) | -0.426 | *** | ||||
Sales and service occupations (06, 62, 64, 66) | -0.238 | *** | ||||
Trades, transport and equipment operators and related occupations (07, 72, 72, 74, 76), | -0.130 | *** | ||||
Occupations unique to primary industry (08, 82, 84, 86), | ||||||
Occupations unique to processing, manufacturing and utilities (09, 92, 94, 96) | ||||||
n | 13,490 | 13,490 | 12,205 | |||
df | 36 | 48 | 55 | |||
F | 89.54 | *** | 82.48 | *** | 73.97 | *** |
r2 | 0.1993 | 0.2276 | 0.2509 | |||
*p<0.05 | ||||||
**p<0.01 | ||||||
***p<0.001 |
Model 1 | Model 2 | Model 3 | ||||
---|---|---|---|---|---|---|
Coefficient | Sig. | Coefficient | Sig. | Coefficient | Sig. | |
Intercept | 8.745 | *** | 9.129 | *** | 9.225 | *** |
Years since landing | 0.452 | *** | 0.376 | *** | 0.361 | *** |
Years since landing - squared | -0.046 | *** | -0.036 | *** | -0.037 | *** |
Gender (Ref. Women) | 0.246 | *** | 0.238 | *** | 0.222 | *** |
Age at landing (Ref. 50 years and older) | ||||||
Less than 30 years old | 0.134 | *** | 0.233 | *** | 0.229 | *** |
30 to 34 years old | 0.155 | *** | 0.236 | *** | 0.236 | *** |
35 to 39 years old | 0.132 | *** | 0.201 | *** | 0.198 | *** |
40 to 44 years old | 0.079 | * | 0.109 | ** | 0.104 | ** |
45 to 49 years old | 0.014 | 0.032 | 0.020 | |||
Education points (Ref. 0 to 13 points) | ||||||
15 points | 0.064 | *** | 0.045 | *** | 0.065 | *** |
16 points | 0.104 | *** | 0.099 | *** | 0.121 | *** |
Language points (Ref. 0 to 5 points) | ||||||
6 points | -0.103 | *** | -0.031 | -0.036 | ||
7 to 8 points | -0.074 | ** | 0.037 | 0.035 | ||
9 points | 0.209 | *** | 0.209 | *** | 0.213 | *** |
10 to 14 points | 0.223 | *** | 0.130 | *** | 0.149 | *** |
15 points | 0.295 | *** | 0.154 | *** | 0.167 | *** |
Specific vocational preparation (Ref. 0 to 13 points) | ||||||
15 points | 0.110 | *** | 0.151 | *** | 0.111 | *** |
17 points | 0.034 | 0.095 | *** | 0.071 | * | |
18 points | 0.048 | 0.050 | 0.106 | ** | ||
Occupation (Ref. 0 to 1 point) | ||||||
2 to 4 points | 0.007 | 0.020 | 0.034 | |||
5 to 8 points | 0.125 | *** | 0.143 | *** | 0.121 | *** |
10 points | 0.057 | *** | 0.100 | *** | 0.099 | *** |
Experience points (Ref. 0 to 2 points) | ||||||
4 points | -0.044 | * | -0.024 | -0.022 | ||
6 points | -0.019 | 0.011 | 0.008 | |||
8 points | -0.083 | *** | 0.004 | -0.008 | ||
Arranged employment points (Ref. 0 points) | ||||||
10 points | 0.848 | *** | 0.684 | *** | 0.633 | *** |
Arranged employment points * years since landing | -0.154 | ** | 0.147 | ** | -0.128 | ** |
Personal suitability (Ref. 0 points) | ||||||
1 to 4 points | -0.276 | *** | -0.253 | *** | -0.234 | *** |
5 points | -0.181 | *** | -0.198 | *** | -0.188 | *** |
6 points | -0.095 | *** | -0.125 | *** | -0.116 | *** |
7 points | -0.041 | ** | -0.113 | *** | -0.103 | *** |
8 points and more | 0.014 | -0.076 | *** | -0.067 | *** | |
Relatives in Canada points (Ref. less than 5 points) | ||||||
5 points and more | -0.039 | *** | -0.048 | *** | -0.051 | *** |
Province of residence in 2006 (Ref. Ontario) | ||||||
Atlantic | 0.110 | * | 0.077 | 0.074 | ||
Quebec | -0.484 | *** | -0.402 | *** | -0.420 | *** |
Manitoba and Saskatchewan | -0.033 | -0.042 | -0.050 | |||
Alberta | 0.268 | *** | 0.266 | *** | 0.261 | *** |
British Columbia | -0.119 | *** | -0.092 | *** | -0.087 | *** |
Country/region of last permanent residence (Ref. United Kingdom) | ||||||
North America | 0.072 | 0.086 | ||||
Central America, South America, Caribbean and Bermuda | -0.063 | -0.056 | ||||
Other Western and Northern Europe | -0.085 | * | -0.066 | |||
Eastern and Southern Europe | -0.175 | *** | -0.174 | *** | ||
Western, Eastern, Central and Southern Africa | -0.119 | *** | -0.104 | ** | ||
Northern Africa and West Central Asia and Middle East | -0.435 | *** | -0.415 | *** | ||
China | -0.672 | *** | -0.657 | *** | ||
Other Eastern and South-east Asia | -0.347 | *** | -0.353 | *** | ||
India | -0.318 | *** | -0.313 | *** | ||
Pakistan | -0.645 | *** | -0.637 | *** | ||
Other South Asia | -0.482 | *** | -0.477 | *** | ||
Oceania | -0.051 | -0.047 | ||||
NOC - skill type (Ref. Professional occupations in natural science and applied sciences (21)) | ||||||
Business, finance and administration occupations, and senior management occupations (00, 01, 11, 12, 14) | -0.012 | |||||
Other natural and applied sciences and related occupations (02, 22) | 0.089 | *** | ||||
Health occupations (03, 31, 32, 34) | -0.062 | ** | ||||
Occupations in social science, education, government service and religion (04, 41, 42) | -0.082 | *** | ||||
Occupations in art, culture, recreation and sport (05, 51, 52) | -0.234 | *** | ||||
Sales and service occupations (06, 62, 64, 66) | -0.099 | *** | ||||
Trades, transport and equipment operators and related occupations (07, 72, 72, 74, 76), | 0.085 | ** | ||||
Occupations unique to primary industry (08, 82, 84, 86), | ||||||
Occupations unique to processing, manufacturing and utilities (09, 92, 94, 96) | ||||||
n | 55,215 | 55,200 | 54,005 | |||
df | 37 | 49 | 56 | |||
F | 182.80 | *** | 196.31 | *** | 170.83 | *** |
r2 | 0.1092 | 0.1485 | 0.1506 | |||
*p<0.05 | ||||||
**p<0.01 | ||||||
***p<0.001 |
Glossary of acronyms
AEO – Arranged Employment Offer
CAIPS – Computer Assisted Immigration Processing System
CADGEDC – China Academic Degrees and Graduate Education Development Center
CBA – Canadian Bar Association
CEC – Canadian Experience Class
CIC – Citizenship and Immigration Canada
CSIC – Canadian Society of Immigration Consultants
CVOA – Canadian Visa Office Abroad
CVOS – Canadian Visa Office Staff
FSW(s) – Federal Skilled Workers
FSWP – Federal Skilled Worker Program
FOSS – Field Operations Support System
GCMS – Global Case Management System
HQ – Headquarters
HRSDC – Human Resources and Skills Development Canada
IA – Immigration Act
IELTS – International English Language Testing System
IMDB – Immigration Database
IRPA – Immigration and Refugee Protection Act
NARIC – National Recognition Information Centre for the United Kingdom
NOC – National Occupation Classification
PA- Principal Applicant
PNs – Provincial Nominees
PNP – Provincial Nominee Program
PR – Provincial Representatives
RPP – Report on Plans and Priorities
PRTD –Permanent Resident Temporary Document
QSW – Quebec Skilled Worker
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