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Dynamic Flows on Unequal Labour Markets: Immigrant Careers in Swedish Metropolitan Regions. Charlotta Hedberg, Department of Human Geography Stockholm University Liverpool 19-21 June 2006. Starting points. ”Spatial pockets of entrenched joblessness” (Martin and Morrison 2003: 6) - PowerPoint PPT Presentation
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Dynamic Flows on Unequal Labour Markets:
Immigrant Careers in Swedish Metropolitan Regions
Charlotta Hedberg,Department of Human Geography
Stockholm UniversityLiverpool 19-21 June 2006
Starting points
• ”Spatial pockets of entrenched joblessness” (Martin and Morrison 2003: 6)
• Economic integration in Sweden– Foreign born: employment rate 61,5 % (2004)– Area based policy: distressed
neighbourhoods• Static picture of immigrant employment
Objectives• How is immigrant employent actually shaped?
– What patterns of entrance, continuity and exit on the labour can be found?
• To study immigrant labour markets from a dynamic perspective– How is the labour market constituted?
• How to think about labour mobility and population geography?
• How to use longitudinal datasets?– Findlay (2003: 185): ”New data sources have provided excellent
opportunities for innovative modelling work and theorisations of populations in space and time”.
Preliminary aim and research questions
• The project aims to describe and explain patterns of labour mobility for individuals with immigrant background: – What is the “speed” of finding a (first) job?– What is the stability of jobs?– From which livelihood positions (unemployment, education,
social allowance, etc.) do individuals enter the labour market?– How is the labour market constructed for various social
categories?• Groups of focus: immigrant background, young cohort, gender• Group of reference: county region (Stockholm/Malmö)
– Why..?
Conceptualising the labour market• Population mobility as a constituent of the labour market
”Local labour markets are not exogenous, pre-given entities […] within which various labour processes take place. Rather, they are highly endogeneous in nature, being actively and continously constructed through the very processes that take place within them” (Martin and Morrison 2003:8).
• Dynamic space (Massey 1999) - dynamic labour markets (Peck 1989; Hanson and Pratt 1992) – Social actors and spatially situated– Embedded networks (Granovetter 1985; Peck 2005)
• Segmented labour markets (Peck 1989; Morrison 1990)– Discrimination
• Time geography (Hägerstrand 1975) – Individual life biograhpies within ”fields of prevailing distributional forces” – Livelihood positions and budget restrictions in space-time
Some operationalisations
• Hägerstrand (1975) – Livelihood positions: employment, unemployment,
study, pension, social allowance, etc.– Budget restrictions: travel-to-work-area, ”rigid
structure of options”• Labour markets as socially constructed and
spatially situated (Hanson and Pratt 1992, etc)– Structures of gender and ethnicity
• Travel-to-work-area (restrictions)• Labour market entry (discrimination)
Research design• Case study design
– Three ”distressed neighbourhoods” (Rinkeby, Flemingsberg, Rosengård)
• Population with immigrant background (PIB)• Young finishing school in 1993• Young not finishing upper secondary school
– Reference groups:• Greater Stockholm and Malmö regions
• Time analysis– 1993-2002– Sequences of livelihood positions (employment, unemployment,
pension, etc.)• Mixed methods apporach
– Quantitative, mainly descriptive analysis– Qualitative interview study
Data material
• Longitudinal, geocoded data base (PLACE)– All individuals– Neigbourhood level– Place of work– Income tax return
• 30 interviews– Immigrants who reside and have reisded in the case
study areas– Biographical approach
Definition
• ”Immigrant”– Quantitative study: Immigrant background
• Foreign born or both parents born in a foreign country
– Interview study: Self definition
Population in the case study areas
Flemingsberg• Pop. 7811• PIB: 4541 (58,1 %)
• PIB 16-64: 2923• Place of birth
– W. Europe (28,1 %)• Finland
– W. Asia (23 %)• Turkey
• Young leaving school 1993 (IB): 25
• Young not finishing school (at all) (IB): 43 (44,3 % of cohort)
Rosengård• Pop. 13 776• PIB: 11 321 (82,2 %)
• PIB 16-64: 6174• Place of birth
– E. Europe (35,9 %)• Yugoslavia• Poland
– W. Asia (29,5 %)• Libanon• Iraq
– Sweden (11,5 %)
• Young leaving school 1993 (IB): 67
• Young not finishing school (at all) (IB): (51,4 % of cohort)
Rinkeby 1993• Pop.: 13 091• PIB: 11 375 (86,9 %)
• PIB 16-64: 7412• Place of birth
– W. Asia (35,4 %)• Turkey• Iran
– W. Europe (22,1 %)• Greece • Finland
– Africa (12,6 %)• Ethiopia• Somalia
• Young leaving school 1993 (IB): 82
• Young not finishing school (at all) (IB): 163 (49,8 % of cohort)
Livelihood positions Stockholm region
Livelihood positions among immigrants, Flemingsberg (longitudinal 1993)
01020304050607080
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
Valid
per
cent
EmployedUnemployedStudentSocial allowancePensionOthersNo data
Livelihood positions, Greater Stockholm region (longitudinal 1993)
01020304050607080
Valid
per
cent
EmployedUnemployedStudentSocial allowancePensionOthersNo data
Livelihood positions among immigrants, Rinkeby (longitudinal 1993)
0
10
20
30
40
50
60
70
80
1993
1995
1997
1999
2001
Valid
per
cent
Employed
Unemployed
Student
Social allowance
Pension
Others
No data
Livelihood positionsMalmö region
Livelihood positions, greater Malmö region (longitudinal 1993)
01020304050607080
Valid
per
cent
EmployedUnemployedStudentSocial allowancePensionOthersNo data
Livelihood positions among immigrants, Rosengård (longitudinal 1993)
01020304050607080
1993
1995
1997
1999
2001
Valid
per
cent
EmployedUnemployedStudentSocial allowancePensionOthersNo data
Livelihood positions Young leaving school, Stockholm
Livelihood positions among young leaving school 1993, Rinkeby
0102030405060708090
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
Valid
per
cent
EmployedUnemployedStudentSocial allowancePensionOthersNo data
Livelihood positions among young leaving school 1993 in Greater Stockholm region
0
10
20
30
40
50
60
70
80
90
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002
Val
id p
erce
nt
Employed
Unemployed
Student
Social allowance
Pension
Others
No dataLivelihood positions among young leaving school 1993,
Flemingsberg
0102030405060708090
100
1993
1995
1997
1999
2001
Valid
per
cent
EmployedUnemployedStudentSocial allowancePensionOthersNo data
Livelihood positions Young leaving school, Malmö
Livelihood positions among young leaving school 1993 in great Malmö
0
10
20
30
40
50
60
70
80
90
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
Valid
per
cent
EmployedUnemployedStudentSocial allowancePensionOthersNo data
Livelihood positions among young leaving school 1993, Rosengård
01020304050607080
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
Valid
per
cent
EmployedUnemployedStudentSocial allowancePensionOthersNo data
Livelihood positions among young leaving school 1993 in great Malmö
0,01
0,1
1
10
100
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
Valid
per
cent
Employed
Unemployed
Student
Social allowance
Pension
Others
No data
Livelihood positions among young leaving school 1993, Rosengård
1
10
100
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
Valid
per
cent
EmployedUnemployedStudentSocial allowancePensionOthersNo data
Livelihood pos. among young not finishing school, Stockholm
Livelihood positions among young not finishing upper secondary school, Rinkeby
0
10
20
30
40
50
60
70
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
Valid
per
cent
EmployedUnemployedStudentSocial allowancePensionOthersNo data
Livelihood positions among young not finishing upper secondary school, Flemingsberg
0
10
20
30
40
50
60
70
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
Valid
per
cent
EmployedUnemployedStudentSocial allowancePensionOthersNo data
Livelihood pos. among young not finishing upper secondary school in Greater Stockholm region
0
10
20
30
40
50
60
70
80
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
Val
id p
erce
nt
EmployedUnemployedStudentSocial allowancePensionOthersNo data
Livelihood pos. among young not finishing school, Malmö
Livelihood positions among young not finishing upper secondary school, Rosengård
01020
30405060
7080
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
Valid
per
cent
EmployedUnemployedStudentSocial allowancePensionOthersNo data
Livelihood pos. among young not finishing upper secondary school in Greater Malmö region
0
10
20
30
40
50
60
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
Val
id p
erce
nt
EmployedUnemployedStudentSocial allowancePensionOthersNo data
Employment among categoriesEmployment among total population
0
10
20
30
40
50
60
70
80
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002
Valid
per
cent
Total pop. Sthlm
Total pop. Malmö
All imm. Rinkeby
All imm. Flemingsberg
All imm. Rosengård
Employment career 1: Fast
0102030405060708090
100
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002
Total pop. Sthlm
Fin. school, Sthlm
Fin. school, Malmö
Fin. school, Rinkeby
Fin. school, Flemingsberg
Employment career 2: Middle
0
10
20
30
40
50
60
70
80
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002
Total pop. Sthlm
All imm. Rosengård
Fin. school, Rosengård
Not fin. school, Sthlm
Not fin. school,Flemingsberg
Employment career 3: Slow
0
10
20
30
40
50
60
70
80
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
Total pop. Sthlm
All imm. Rosengård
Not fin. school, Malmö
Not fin. school, Rinkeby
Not fin. school, Rosengård
But – where did they live in 2002?!
Immigrant population residing in the same area 1993 - 2002
0102030405060
Totalpopulation
Youngleaving
school 1993
Young notfinishingschool
Valid
per
cent
Rinkeby
Flemingsberg
Rosengård
Work and out-migration
Share of working population 2002 residing in the same area 1993 - 2002
05
101520253035404550
Totalimmigrant
pop.
Youngleaving
School 1993
Young notfinishingschool
%
RinkebyFlemingsbergRosengård
Next step• How much of this difference does gender
explain?• How does this pattern look for newly arrived
immigrants in middle age?• In what sectors did they work?
• From what positions did they enter the labour market?– Follow typical individual life histories– Aggregation of categories
Individual life paths 1993-2002Young leaving school in Rinkeby 1993
• Aggregation of life paths – individual combinations
• How to generalise these in order to follow the individual as close as possible?
ink_karriär
5 6,1 6,1 6,14 4,9 4,9 11,03 3,7 3,7 14,62 2,4 2,4 17,11 1,2 1,2 18,31 1,2 1,2 19,51 1,2 1,2 20,71 1,2 1,2 22,01 1,2 1,2 23,21 1,2 1,2 24,41 1,2 1,2 25,61 1,2 1,2 26,81 1,2 1,2 28,01 1,2 1,2 29,31 1,2 1,2 30,51 1,2 1,2 31,71 1,2 1,2 32,91 1,2 1,2 34,11 1,2 1,2 35,41 1,2 1,2 36,61 1,2 1,2 37,81 1,2 1,2 39,01 1,2 1,2 40,21 1,2 1,2 41,51 1,2 1,2 42,71 1,2 1,2 43,91 1,2 1,2 45,11 1,2 1,2 46,31 1,2 1,2 47,61 1,2 1,2 48,81 1,2 1,2 50,01 1,2 1,2 51,21 1,2 1,2 52,41 1,2 1,2 53,71 1,2 1,2 54,91 1,2 1,2 56,11 1,2 1,2 57,31 1,2 1,2 58,51 1,2 1,2 59,81 1,2 1,2 61,01 1,2 1,2 62,21 1,2 1,2 63,41 1,2 1,2 64,61 1,2 1,2 65,91 1,2 1,2 67,11 1,2 1,2 68,31 1,2 1,2 69,51 1,2 1,2 70,71 1,2 1,2 72,01 1,2 1,2 73,21 1,2 1,2 74,41 1,2 1,2 75,61 1,2 1,2 76,81 1,2 1,2 78,01 1,2 1,2 79,31 1,2 1,2 80,51 1,2 1,2 81,71 1,2 1,2 82,91 1,2 1,2 84,11 1,2 1,2 85,41 1,2 1,2 86,61 1,2 1,2 87,81 1,2 1,2 89,01 1,2 1,2 90,21 1,2 1,2 91,51 1,2 1,2 92,71 1,2 1,2 93,91 1,2 1,2 95,11 1,2 1,2 96,31 1,2 1,2 97,61 1,2 1,2 98,81 1,2 1,2 100,0
82 100,0 100,0
1111111111311111111116111111114111111111112211111146111111111164......166111111113644444416644444111112111111133311311116661062216361111111611124400101261113111163314111114612261113344611131366211111136161133323113311311366111010036440111113441113311464111111133311111116333331111661161111233112441116611111111446411333431211111113333316111361113...1330000100033112411116111111111361111111136141111113661444111351441211166611161116616111111311116131116661111464411106111161111331136644444043163341..31613331111336110111031441111661133111111111111111263333111003644444111133333113211114111113611231511662111611144411111116621111111464461111113111113331131111116361311111136661111113333333311663313136046414441114111133311Total
ValidFrequency Percent Valid Percent
CumulativePercent
Preliminary conclusions• When using longitudinal data it is possible to see
dynamic tendencies of immigrant employment
• Finish upper secondary school is important for all young people to enter the labour market, but it is most important for immigrant youth– Young immigrants who finish school in Flemingsberg enter the
labour market to a higher degree than all other groups– Young immigrants in Rinkeby have fast or ”middle position” –
which is better than perhaps expected– Immigrants from Rosengård experience particular difficulties on
the labour market• Immigrants who are employed seldom remain as
residents in the case study area– Rosengård and young cohorts in particular