OVERQUALIFICATION AMONG SALARIED WORKERS OF IMMIGRANT ORIGIN IN MONTREAL, TORONTO AND VANCOUVER: A COMPARATIVE ANALYSIS

Jacques LEDENT Institut national de la recherche scientifiqueCentre Urbanisation, Culture et Société

Prepared for presentation in the Speakers Series of the Social Statistics Program, McGill University, November 23, 2011

1

Background

Immigration represents an increasing proportion of the Canadian labour force, especially in the three metropolises (Montreal, Toronto and Vancouver)

… and it is more and more diversified in terms of • geographical origin• ethnic origin / visible minority • language etc…

The economic integration of the recent immigrants is more difficult Lower activity Higher unemployment Lower income

… and more segmented owing to greater difficulties encountered by some groups (such as Arabic vismin, women coming from Africa etc…) 2

Motivation for comparing overqualification in Montreal, Toronto and Vancouver

But the immigrant population is highly educated, especially the more recent cohorts, and thus it is more prone to overqualification than the non-immigrant population

Starting point : Statistical analysis carried out for Emploi-Québec (with Alain Bélanger and Guillaume Marois) on the influence of birthplace and vismin membership on overqualification of salaried workers residing on the Island of Montreal

This analysis = offshoot of the above that was carried out in the context of a summer internship awarded to Alina-Nicoleta Dinescu, a master’s student in demography at the Université de Strasbourg

Analysis more meaningful if for a true labour market => CMA level Increasing interest of the Metropolis Project for the pan-canadian

dimension => MTV focus Employed rather than active salaried workers (to be able to

distinguish full/part-time workers)3

OVERQUALIFICATION:GENERAL REMARKS

4

Literature review (1) Initial impetus : Freeman (1976)

Theoretical model : a qualified workforce larger than is necessary will settle for less => Returns to education should plummet => Reduced investment in education => Return to equilibrium

But an increase in the demand for jobs with high skills has led to an even larger increase in educational level of workers. Hence, overqualification is a persistent issue

Measurement is a major problem. Three approaches: Skills requirements determined by analyst (like in this presentation) Worker’s self assessment Comparison with a predefined educational distribution by

occupation Most of the literature is on prevalence and

determinants of the phenomenon and its impact on wages

5

Literature review (2)Burgeoning literature on factors of overqualification in a

high immigration context Focus on ethnic differences

US : Duncan / Hoffman (1991) UK : Sloan / Battu (2004)

Focus on differences according birthplace/period of immigration Australia: Kler (2006) Canada: Galarneau / Morissette (2004, 2008) Quebec: Renaud / Cayn (2008), Bégin (2009) – See also

Girard / Smith / Renaud (2008) OECD (2007) where main factors are

Immigrant status Socio-demographic factors (gender, age) Human capital characteristics (origin of diploma, literacy

proficiency, mother tongue)6

Overqualification: Definition

Overqualified worker = worker having a job that is not commensurate with his/her skills

Level of education of the worker > Level of skills required by the job

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Skills level

Education level D C B A

D        

C        

B        

A       Overqualified workers

Jobs’ skills levels

5 levels defined by Human Resources and Skills Development Canada from the 2006 National Occupation Classification Level D: Requires on-the-job training Level C: Usually requires secondary school and/or

occupation-specific training Level B: Usually requires college education or

apprenticeship training Level A: Usually requires university education Level 0: Management occupations

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Workers’ education level

4 levels defined in agreement with Emploi-Québec on the basis of the highest certificate, degree or diploma (hcdd) completed: Level D: None Level C: High school diploma or equivalent Level B: Trade cdd; college, CEGEP and other non-

university ccd; university cdd less than a baccalaureate Level A: University cdd at least equal to a baccalaureate

9

Raw index = 100 * (# of workers in green cells) / Total # of workers = 29.4% But D-level workers cannot be overqualified => Corrected index = 100 * (# of workers in green cells) / Total # of workers in last

three rows = 33.4 %

Note : No standardised skills and jobs levels => Comparison impossible between studies

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Skills level

Education level D C B A 0

D 59855 84590 41651 2001 8318 196415

C 64065 163416 89884 14727 27496 359588

B 56491 220353 258731 71934 51098 658607

A 9837 58635 67550 210126 62828 408976

190248 526994 457815 298788 149740 1623585

Overqualification: Measure for the Montreal CMA

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Canada Outside Canada No YesAll Birthplace Vismin membership

0

5

10

15

20

25

30

35

40

45

50

33.431.4

41.2

31.3

46

Overqualification index: Salaried workers, Montreal CMA, 2006

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Variable Value Montreal Toronto Vancouver

All 33.4 34.4 34.4

Overqualification index

13

Variable Value Montreal Toronto Vancouver

All 33.4 34.4 34.4

Birthplace Canada 31.4 27.6 29.0Outside Canada 41.2 40.9 41.9

Overqualification index

Birthplace appears to influence overqualification a bit less than membership in a visible minority group

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Variable Value Montreal Toronto Vancouver

All 33.4 34.4 34.4

Birthplace Canada 31.4 27.6 29.0Outside Canada 41.2 40.9 41.9

Vismin membership No 31.3 28.0 28.5

Yes 46.0 43.5 44.1

Overqualification index according to birthplace or vismin membership

THE STATISTICAL ANALYSIS

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Objectives and research questions Q1 : What are the net effects of

Being born outside (rather than in) Canada Belonging (rather than not belonging) to a visible minority after controlling for differences in other individual

characteristics? How do these net effects compare between Montreal, Toronto and Vancouver?

Q2 : What are the main risk factors of overqualification for salaried workers with an immigrant origin? How do they compare with the corresponding factors for the remaining salaried workers? What are the similarities and differences in those factors between Montreal, Toronto and Vancouver ?

16

Practical considerations

Recourse to the 2006 census microdata (20% sample) accessible at QICSS

Utilization of a logistic regression model where Being overqualified or not = f (birthplace, visible minority membership, other individual characteristics)

17

Other individual characteristics

• Socio-demographic characteristics Gender Age Family status

• Human capital characteristics Highest certificate, degree or diploma completed Place of study Number of hours worked per week Proficiency in the official languages

18

Note regarding interpretation of the results

For each risk factor, the parameter corresponding to a given category is an odds ratio (OR) which expresses the relative change in the propensity to be overqualified if one belongs to that category rather than to a fixed category considered as the reference category, everything else being equal

Example : Influence of the genre : If OR = 1.20 for women (versus 1 for men) => Women are 20% more often overqualified than men, all other characteristics being the same

Significance levels : *** 0.0001 ; ** 0.01 ; * 0.1 19

RESEARCH QUESTION 1 :Influence of birthplace and visible minority status

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Equation Variables / values Montreal Toronto Vancouver

1 Birthplace(Canada) Outside Canada 1.53 *** 1.81*** 1.76***

21

Equation Variables / values Montreal Toronto Vancouver

1 Birthplace(Canada) Outside Canada 1.53 *** 1.81*** 1.76***

2Vismin membership (No) Yes 1.87*** 1.99*** 1.98***

22

Equation Variables / values Montreal Toronto Vancouver

1 Birthplace(Canada) Outside Canada 1.53 *** 1.81*** 1.76***

2Vismin membership (No) Yes 1.87*** 1.99*** 1.98***

3 Birthplace(Canada) Outside Canada 1.16*** 1.34*** 1.29***Vismin membership (No) Yes 1.67*** 1.67*** 1.69***

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In the end, only vismin membership really counts, for birthplace outside Canada has little influence

Equation Variables / values Montreal Toronto Vancouver

1 Birthplace(Canada) Outside Canada 1.53 *** 1.81*** 1.76***

2Vismin membership (No) Yes 1.87*** 1.99*** 1.98***

3 Birthplace(Canada) Outside Canada 1.16*** 1.34*** 1.29***Vismin membership (No) Yes 1.67*** 1.67*** 1.69***

4 (w. control variables)

Birthplace(Canada) Outside Canada 1.01ns 1.06*** 0.96*

Vismin membership (No) Yes

1.29*** 1.32*** 1.22***24

However, recent immigrant workers are more often overqualified than workers belonging to the 3rd generation, but less so in Vancouver …..

25On the contrary, immigrant workers who immigrated before 1981 are less often overqualified than workers belonging to the 3rd generation

Montreal Toronto Vancouver0.600000000000001

0.700000000000001

0.800000000000001

0.900000000000001

1

1.1

1.2

1.3

1.4

1.5

1.6

Influence of the status/period of immigration

Gen 2/ 1 parent born outside CanadaGen 2 / 2 parents born outside Canadaimmigrated before1971Immigrated in 1971-1980Immigrated in1981-1990Immigrated in 1991-1995Immigrated in 1996-2000Immigrated in 2001-2006Non permanent resident

Ref. cat: Gen 3+

3 vismin groups (Filipinos, Blacks and Latino-Americans) are much more overqualified in the 3 metropolises, 2 other groups (South Asians and Southeast Asians) are more overqualified in Toronto and Vancouver and a last group is slightly more overqualified in Toronto (Arabs)

- Blacks and especially Filipinos (who include many educated women accepted as NPRs in CIC’s Living-in caretaker program) are somewhat more overqualified than Whites

- On the contrary, Chinese and West Asians are less overqualified than Whites26

Montreal Toronto Vancouver0.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2

Influence of the visible minority group

ChineseSouth AsianBlackFilipinoLatin AmericanSoutheast AsianArabicWest AsianOther

Ref. cat.: White

A birthplace outside Canada reinforces the vismin effect

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Montreal

Toronto

Vancouver

Montreal

Toronto

Vancouver

Montreal

Toronto

Vancouver

Vism

in m

embe

rshi

p

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6

Net effects with interaction between birthplace and vismin

RESEARCH QUESTION 2The risk factors of overqualificationin the target and comparison groups

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Schematic representation of the population of immigrant origin

  Vismin membership

Birthplace No Yes

Canada

   

Outside Canada    

  Population of immigrant origin  (target group)                Remaining population (comparison group)

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Being a female, being young or not having a spouse results in more overqualification

Socio-demographic characteristics

Both groups

Target group

Comparison group

Gender (Males)- Females

1.15***

Age (25-44 yrs)- 15-24 yrs- 45 yrs and over

1.68*** 1.01ns

Family status (Spouse)- Not in economic family- Lone parent- Child / Grandchild

1.40*** 1.20** 1.91***

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Montreal CMA

The influence of socio-demographic factors appears to be similar in both groups with one exception (child)

Socio-demographic characteristics

Both groups

Target group

Comparison group

Gender (Males)- Females

1.15***

1.24***

1.13***

Age (25-44 yrs)- 15-24 yrs- 45 yrs and over

1.68***1.01ns

1.80***1.02ns

1.63***1.01ns

Family status (Spouse)- Not in economic family- Lone parent- Child / Grandchild

1.40***1.20**

1.91***

1.32***1.11**

1.58***

1.43*** 1.23*** 2.02***

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Montreal CMA

The influence of socio-demographic factors appears to be similar across cities with one exception (45 yrs and over)

Socio-demographic characteristics Montreal Toronto Vancouver

Gender (Males)- Females 1.24*** 1.40*** 1.49***

Age (25-44 yrs)- 15-24 yrs- 45 yrs and over

1.80***1.02ns

1.75***1.13***

1.61***1.09***

Family status (Spouse)- Not in economic family- Lone parent- Child / Grandchild

1.32***1.11**

1.58***

1.16***1.18***1.36***

1.26***1.31***1.42***

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Target group

Having a Level B education, having studied elsewhere than in a Western country or working between 10 and 30 hours weekly results in more overqualification

Human capital characteristics

Both groups

Target group

Comparison group

Education level (Level A)- Level C- Level B

0.32***1.39***

Place of study (Canada)- Western country- Elsewhere

0.86***1.39***

Hours worked (30 hours or more)- Less than 10 hours- Between 10 and 30 hours

1.30***1.79***

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Montreal CMA

Again, the influence of human capital characteristics appears to be similar in both groups (except place of study)

Human capital characteristics

Both groups

Target group

Comparison group

Education level (Level A)- Level C- Level B

0.32***1.39***

0.25*** 1.21***

0.34*** 1.46***

Place of study (Canada)- Western country- Elsewhere

0.86***1.39***

0.91*** 1.89***

0.69***1.05ns

Hours worked (30 hours or more)-Less than 10 hours-Between 10 and 30 hours

1.30***1.79***

1.27*** 1.60***

1.31*** 1.85***

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Montreal CMA

The influence of the human capital characteristics appears to be similar across cities with two exceptions (Level B education, study in Western country)

Human capital characteristics Montreal Toronto Vancouve

r

Education level (Level A)- Level C- Level B

0.25*** 1.21***

0.20***

1.05***

0.22*** 0.96**

Place of study (Canada)- Western country- Elsewhere

0.91*** 1.89***

0.86***

1.73***

0.98ns

1.81***

Hours worked (30 hours or more)- Less than 10 hours- Between 10 and 30 hours

1.27*** 1.60***

1.27***

1.80***

1.35*** 1.72***

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Target group

Target group (Levels A and B) : The higher the (specific) diploma, the lower is overqualification

Level B ( other < Bacc) Level A (>= Bacc)hcdd Montrea

l Toronto Vancouver hccd Montrea

l Toronto Vancouver

Trades cdd 2.00***

2.08***

1.83***

Bachelor’s degree 1 1 1

Non-university studies: less than 1 year

1.97***

1.37***

1.52***

University certificate above bachelor level

0.80**

*

0.79***

0.70***

Non-university studies: 1 to 2 yrs

1.55***

1.53***

1.22***Degree in medecineetc ..

0.25**

*

0.51***

0.51***

Non-university studies: more than 2 yrs

1.16***

1.05*

0.93*

Master’s degree

0.43**

*

0.49***

0.46***

University certificate below bachelor level

1 1 1 Earned doctorate

0.14***

0.25*** 0.18*** 36

Proficiency in the official languages None of the language variables in the census

has a discriminating capacity Proficiency in either official language (English

or French) is better for those who speak it at home and, a fortiori, for those who have it as a mother tongue

As a result, our variable of language proficiency is obtained by cross-classifying the three language variables (Mother tongue, home language and Knowledge of the official languages) => 7 categories reflecting a continuous variation in language proficiency 37

For the target group, overqualification increases with diminishing proficiency in the official languages, in the 3 metropolises, not just in Montreal !

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MT=Official, HL=Official, KOL=Fr and En (ref)

MT=Official, HL=Official, KOL=Fr or En

MT=Non official, HL=Official, KOL=Fr and En

MT=Non official, HL=Official, KOL=Fr or En

HL=Non official, KOL=Fr and En

HL=Non official, KOL=Fr or En

HL=Non official, KOL=Neither Fr nor En

0 0.5 1 1.5 2 2.5

Target group:Influence of proficiency in the official languages

VancouverTorontoMontreal

SUMMARY AND CONCLUSIONS

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Main findings Influence of birthplace and vismin

Strong influence of vismin membership 3 groups in all three cities: Filipino, Black and Latino -

American South Asian and Southeast Asian in Toronto and Vancouver Arab in Toronto

Reinforcing role of birthplace outside Canada Nevertheless strong influence among recent (2001-2006)

immigrants Influence of other individual characteristics

Similar influence in both target and comparison groups (with a few exceptions including the linguistic variable)

Similar influence across the 3 cities Clear gradient in the impact of the proficiency in the

official languages (target group only)40

Policy implications and future research Policy implications

Target salaried workers belonging to the vismin and especially the Filipino, Black and Latin American groups

“No size fits all” programs intended for those born outside Canada but rather promote programs

Targeting recent immigrants Aiming to attenuate the negative effects of risk factors such as being a

female, young, having obtained a diploma in a non Western country, lacking proficiency in the official languages)

Research development Pursue the analysis by level of education (already in

progress) Refine the dependent and independent variables

41