Migration and Social Capital Factors in the School-to-Work Transitions of Immigrant Youth

1. Migration and Social Capital Factors in the School-to-Work Transitions of Immigrant Youth Lori Wilkinson, Ph.D. Associate Professor University of Manitoba 29 September 2009 Presented at the Prairie Metropolis Centre Winnipeg Research Symposium

2. Youth Employment in Canada • Finding good employment a marker of integration • 352,500 youth are looking for work • Youth between the ages of 15 & 24 make up 31.1% of all unemployed persons • Among youth, immigrants are most likely to be unemployed • Over half of all migrants to developed nations are under age 29 years UN, 2007; Statistics Canada, 2007 & 2003; Anisef et al., 2006; Wilkinson, 2008

3. Only 25% of immigrant youth have job experience by the time they are 18 years, compared with 60% of Canadian-born youth • Factors that influence job history among immigrants: • Age at immigration • Level of education • Visible minority status • Obtaining “Canadian” work experience • Many immigrant youth do not find work that is equivalent to their previous work experience or level of education Shields & Rahi, 2003; Perreira et al., 2007; Kunz, 2003; Omidvar & Richmond, 2003; Anisef, et al., 2007; Beaujot and Kerr, 2007

4. Labour Force Participation Indicators, 2005- Employed Data from Statistics Canada (2008) 2006 Census of Canada, based on calculations of the researcher.

5. Labour Force Participation Indicators, 2005- Unemployment Data from Statistics Canada (2008) 2006 Census of Canada, based on calculations of the researcher.

6. Social Capital, Family Influences on Job Search Strategies • Few studies on the influence of social capital on full-time employment for immigrants • More than 70% of American-born workers find their current jobs through networks • Research suggests that finding full-time employment may be affected by: • English language proficiency or accent • Age at immigration • Perceived standing in host culture • Immigrant status: 1.5/2.0 generation are most neglected in research Yan, 2000; Manni, 1994; Kilbride et.al, 2004; Anisef et. Al, 2003; Nesdale and Pinter 2000; Leu, 2009

7. Phase One • Quantitative analysis of the Longitudinal Survey of Immigrants to Canada (LSIC) • Consists of 20,300 immigrants who arrived in Canada during autumn 2001 • Randomly selected by Citizenship & Immigration Canada • Representative of major immigrant-sending countries • Representative of the major entrance classes (including government/private sponsored refugees) • Not representative of refugee claimants • Wave 1 (6 months after arrival), Wave 2 (2 years after arrival), and Wave 3 (four years after arrival)

8. Phase Two • Qualitative, semi-structured interviews with 100 youth in Toronto, Hamilton, Winnipeg & Vancouver • Similar characteristics to those in LSIC • Special interest in comparing the trajectories for those with high school education, trade/technical school education or university education • Extensive questions about educational and work history prior to arrival, at arrival & post-arrival

9. LSIC Sample Characteristics & Methodology • Respondents are aged 15 to 29 years at time of arrival • Must have immigrated to Canada between October 2000 and September 2001 • Excludes those coming from the US and Australia • Used logistic regression models for each of the three time periods: six months after arrival, 2 years after arrival and four years after arrival

10. Dependent variable • Full-time employment status: are you working full-time or not? • 1=working full-time (using Statistics Canada definition of 30 hours per week) • 0=not working full-time • Measured at Waves 1, 2 and 3 • Log [P(Y)/P(NoY)]= Statistics Canada, 2007a; 2007b

11. Pre-migration/SWT characteristics Gender (1=female) Marital status (1=relationship) Presence of dependents in household (1=yes) Highest education prior to arrival (dummy) Canadian degree (1=yes) Age (continuous) Integration variables: Immigration category (dummy) Visible minority status (1=yes) Language proficiency (index) Social capital variables Family in Canada prior to arrival (1=yes) Friends in Canada prior to arrival (1=yes) Sponsorship status (1=yes) Determinants of Full-time Employment

12. Logistic Models of SWT Wave 1 Table 1 Logistic Models of SWT, Integration and Social Capital by Wave 1 Models. Model 1 Model 2 Model 3 Logged Odds SE Logged Odds SE Logged Odds SE School-to-work Gender .674** .144 .660** .145 .668** .145 Age 1.009 .025 1.009 .026 1.006 .026 Marital status 1.222 .173 1.261 .181 1.262 .182 Children .956 .169 .932 .183 .952 .183 Education level Some university .944 .215 .971 .218 .988 .219 Doctorate 1.033 .253 1.282 .262 1.329 .263 Canadian Degree .970 .388 1.087 .393 1.099 .395 Integration Immigration category Skilled workers .457** .244 .706 .312 Business immigrants .861 .317 1.222 .353 Family Class .605* .250 .559* .258 Visible minority .645** .166 .644** .168 Language proficiency 1.749 .299 1.813* .300 Social Capital Family 1.068 .170 Friends 1.293 .147 Sponsor 1.878* .252 Constant ..095*** .516 .206** .607 .108** .658 • Note: *p<0.05; **p<0.01; ***p<0.001; Model 1 R2 = .009; Model 2 R2 = .026; Model 3 R2 = .034

13. Factors influencing full-time employment 6 months after arrival Sponsor- ship Status* Language Proficient* Doctoral degree Friend SK Marital Status Business class Degree in Canada Family SK Age Some tertiary education Children present Visible Minority** Skilled worker class Gender*** Family Class* *p<0.05 **p<001 ***p<0.001

14. Logistic Models of SWT Wave 2 Table 2 Logistic Models of SWT, Integration and Social Capital by Wave 2 Models. Model 1 Model 2 Model 3 Logged Odds SE Logged Odds SE Logged Odds SE School-to-work Gender .779* .125 .770* .126 .780 .127 Age .987 .021 .983 .022 .977 .023 Marital status 1.091 .149 1.098 .156 1.096 .157 Children .779 .150 .770 .162 .783 .163 Education level Some university 1.321 .189 1.372 .191 1.400 .193 Doctorate 1.258 .226 1.451 .233 1.519 .235 Canadian Degree 1.042 .327 1.102 .331 1.092 .333 Integration Immigration category Skilled workers .628* .221 .906 .283 Business immigrants .762 .300 1.028 .333 Family Class .725 .228 .652 .235 Visible minority .697* .147 .696* .149 Language proficiency 1.752* .268 1.840* .271 Social Capital Family 1.184 .149 Friends 1.636*** .129 Sponsor 1.820** .224 Constant ..197*** .450 .368 .534 .184** .583 Note: *p<0.05; **p<0.01; ***p<0.001; Model 1 R2 = .008; Model 2 R2 = .018; Model 3 R2 = .034

15. Factors influencing full-time employment 2 years after arrival Sponsor- ship status** Language Proficient* Friend SK*** Doctoral degree Some tertiary education Family SK Marital Status Degree in Canada Business class Age Skilled worker *p<0.05 **p<001 ***p<0.001 Children present Gender Visible Minority* Family class

16. Logistic Models of SWT Wave 3 Table 3 Logistic Models of SWT, Integration and Social Capital by Wave 3 Models. Model 1 Model 2 Model 3 Logged Odds SE Logged Odds SE Logged Odds SE School-to-work Gender .396*** .094 .381*** .095 .380*** .095 Age 1.106*** .015 1.132*** .016 1.135*** .016 Marital status .765* .112 .632*** .118 .639*** .119 Children .576*** .102 .711** .111 .706** .112 Education level Some university 1.597*** .130 1.544** .134 1.543** .134 Doctorate 1.971*** .156 1.946*** .163 1.963*** .164 Canadian Degree 1.165 .260 1.268 .264 1.317 .264 Integration Immigration category Skilled workers 1.205 .173 1.517 .225 Business immigrants .830 .232 1.010 .263 Family Class 1.965*** .179 1.780** .183 Visible minority .759* .115 .729** .116 Language proficiency .544* .237 .558* .237 Social Capital Family 1.245* .109 Friends .884 .095 Sponsor 1.226 .180 Constant .161*** .318 .092*** .392 .068*** .430 • Note: *p<0.05; **p<0.01; ***p<0.001; Model 1 R2 = .199; Model 2 R2 = .219; Model 3 R2 = .223

17. Factors influencing full-time employment 4 years after arrival Doctoral Degree*** Family Class** Some tertiary education** Skilled worker Sponsor- ship status Family SK* Age*** Business class Degree In Canada Friend SK Children Present*** Visible Minority** Marital Status*** *p<0.05 **p<001 ***p<0.001 Language Proficient* Gender***

18. Model interpretation • Gender plays a role at arrival and 4 years later • It takes time for educational credentials to be recognized with full-time work • Mixed results with immigrant class • Language proficiency key to finding full-time work in short and medium-term • Visible minority status has a negative effect on access to full-time work at all time points • Social capital factors play a role, particularly sponsorship status; Family and friendship social capital more important in the early stages of integration

19. Policy Questions to Consider • Why are visible minority migrant youth having significant difficulties in the labour market? Is it time to reconsider challenges to Employment Equity legislation? • How can we ensure youth requiring language training have access to it? • How can we facilitate friendship & family social capital networks among newcomers? • What can be done to convince employers of the value of the credentials and languages brought to the labour market by migrant youth?

20. A Note from Statistics Canada • The UBC and Manitoba Research Data Centres of Statistics Canada provided invaluable advice relating to the statistical analysis and access to the confidential data from the Longitudinal Survey of Immigrants to Canada. All errors and omissions are the responsibility of the author. • The analysis is based on confidential micro-data received from Statistics Canada and the opinions expressed do not represent the views of Statistics Canada.

21. Acknowledgements • Research assistants • Colleagues: • Dr. Rick Sin McMaster University • Dr. K.T. Tsang University of Toronto • Dr. M.C. Yan UBC • Advisory panel members • Statistics Canada Research Data Centres • SSHRC/Metropolis Strategic Joint Initiative & our Metropolis Centres for funding this study and the pilot projects.