1. Towards Upgrading or Polarization
Towards Upgrading or Polarization? Changes in the Swedish Occupational Structure
What are the effects of a temporary employment on the labour market situation of the future?
Is it a stepping stone or a dead end?
Tomas Berglund Department of Sociology and Work Science University of Gothenburg

2. The Challenges of Polarization on the Swedish Labour Market
Research program for 6 years funded by FORTE
Purpose: To study trends of polarisation in the Swedish labour market, and analyse possible consequences for individuals, unions and employers, as well as more general societal consequences. Work Packages:
WP1: Job polarisation and social structuration. (Tomas Berglund; Olof Reichenberg)
WP 2: Flexibilisation and Polarisation. (Kristina Håkansson; Tommy Isidorsson)
WP3: Migration and Polarisation – patterns, mechanisms and experiences. (Denis Frank; Gabriella Elgenius; Vedran Omanovic)
WP4: Polarised work environment: trajectories and consequences for trends of health and sick leave. (Linda Corin; Lotta Dellve Gunnel Hensing; Lisa Björk; Chioma Nwaru)
WP 5. The “workers’ collective” and polarisation: trade unions and workers’ representation. (Bengt Larsson; Jesper Prytz)
WP6 – Perceptions of occupations and occupational prestige – mechanisms of the polarisation of the occupational structure. (Ylva Ulfsdotter Eriksson; Erica Nordlander)

3. Theoretical starting point
New technology (computerization, robotization, ICT, digitalization, AI) is believed to fundamentally change the occupational structure. Two theories:
Skill-Biased Technological Change (SBTC): Upgrading – Jobs demanding higher education and skills, and are better paid will increase in numbers. The new technology augment the productivity of the work conducted in these jobs. Low paid jobs are replaced by technology (robots, automatization etc).
Routine-Biased Technological Change (RBTC): Polarization – Specify that the new technology mainly replace jobs with a routine-component:
Routine jobs, for example in manufacturing and offices (clerical), are hit. Those jobs (according to theory) are often middle paid jobs.
Non-routine jobs are often found in the better paid regions of the occupational structure (e.g. developers, technicians, researchers)
However, non-routine jobs are also often found in the bottom of the wage structure and often involve personal services (e.g. hairdressers, waiters, childcare workers). These are less affected by the digital technology.

4. Other factors than technology have also been suggested:
Outsourzing abroad: manufacturing, services
Changing labour supply: Feminization, immigration (both RBTC), high supply of highly skilled (SBTC)
Deliberate policies to increase low wage jobs (Mini-jobs i Germany, the RUT-reform (Cleaning, Maintenance and Laundry) in Sweden), but, on the other hand, also educational reforms to meet the demand in the higher-end of the occupational structure.
Increased demand of personal services
Main actors:
Scientists and technicians supplying with new technology
Employers, use new technology to increase productivity and develop products
Governments, e.g. trying to reduce unemployment by facilitating the creation of low wage, initial jobs, or increase spendings on RTD.
Unions? Luddite responses? Solidaristic Wage Policies  Up-grading, but side-effect polarization?

5. Data and Methods Labour Force Studies (AKU) 1997-2015
Focus on occupations (SSYK-96, the Swedish version of ISCO-88) on 3-digit level (about 113 different occupations).
To each occupation is the mean full-time wage imputed. The wages of the latest year of the time-series are used as the basis.
Rationale: Wages are a function of qualifications and skills in demand (price), and productivity of work tasks (+ several other factors, in particular, institutional (e.g. in Sweden The Industrial Agreement)). However, this approach do not measure skills directly!
For the first year of the time series (e.g. year 2000), the occupations are ranked from the lowest to highest wages.
The number of employed within each occupation are then included, and quintiles calculated, reconstructing the occupational/wage structure into 5 more or less equal shares of number of employed, ranked from the fifth with the lowest wages to the fifth with the highest wages.
The cut-points for the quintiles of the first year (e.g. 2000) (and the included occupations) are used to recalculate the occupational/wage structure the last year of the time series (e.g. 2015).

6. Figure 1: Change in Total Number of Employed Persons (Wage Earners) in Occupational Wage Quintiles, in Sweden. LFS, years. Weighted data.

7. Figure 2: Relative Distribution of Employed Persons (Wage Earners) in Occupational Wage Quintiles, 2000 and 2015 in Sweden. LFS, years. Weighted data.

8. Figure 3: Change in Number of Private Sector Employed Persons (Wage Earners) in Occupational Wage Quintiles, in Sweden. LFS, years. Weighted data.

9. Figure 4: Change in Number of Private and Public Sector Employed Persons (Wage Earners) in Occupational Wage Quintiles, in Sweden. LFS, years. Weighted data.

15. Figure 5: Cumulative Change in Private Sector Employment (numbers) in Occupational Wage Quintiles, in Sweden. LFS, years. Weighted data.

16. 2006
2009
Figure 5: Cumulative Change in Private Sector Employment (numbers) in Occupational Wage Quintiles, in Sweden. LFS, years. Weighted data.

17. 2009
2006
2009
Figure 6: Cumulative Change in Public Sector Employment (numbers) in Occupational Wage Quintiles, in Sweden. LFS, years. Weighted data.

18. Paper together with Denis Frank, Gabriella Elgenius, Vedran Omanovic “The impact of Sweden’s changing occupational structure on the labor market opportunities of immigrants” Research questions: - How does the changing occupational structure and a changing labour supply – increasing share of immigrants – interact? - Are occupation in low-paid employment an entrance point for mobility upward in the occupational structure?

19. Unemployment ratio* (%)
Table 2. Percentage Swedish and foreign born, years.
Origin
Share (%)
Males (%)
Age
(mean)
Primary
educ. (%)
Tertiary
educ.(%)
In employ-
ment (%)
Unemployment ratio* (%)
Swedish
88.1
51.1
39.6
24.4
27.4
75.7
4.2
Nordic
3.4
43.6
47.2
34.6
20.3
69.9
4.5
EU-15
1.0
55.0
45.5
22.7
33.8
71.2
4.8
EU New Member States
1.1
37.6
42.8
18.2
34.3
62.2
8.4
Europe (Non-EU)
2.3
50.9
39.1
36.3
19.4
44.9
11.9
Non-Europe
4.1
52.5
35.0
32.6
28.8
49.2
12.3
Total
100
50.8
39.7
25.2
27.2
73.5
 Share (%)
80.7
51.4
14.5
40.4
78.3
3.6
2.4
44.1
49.3
19.7
35.9
75.0
3.8
1.4
57.7
42.5
13.4
58.0
78.2
2.0
41.0
10.7
46.4
72.9
7.0
3.5
48.7
40.5
23.4
33.6
66.3
7.9
10.1
49.7
28.0
39.0
56.3
10.8
39.8
16.2
40.2
75.5
Note. Swedish Labor Force Survey, years, all yearly observations per period. Weighted data. *Calculated on total population years.

20. Unemployment ratio* (%)
Table 2. Percentage Swedish and foreign born, years.
Origin
Share (%)
Males (%)
Age
(mean)
Primary
educ. (%)
Tertiary
educ.(%)
In employ-
ment (%)
Unemployment ratio* (%)
Swedish
88.1
51.1
39.6
24.4
27.4
75.7
4.2
Nordic
3.4
43.6
47.2
34.6
20.3
69.9
4.5
EU-15
1.0
55.0
45.5
22.7
33.8
71.2
4.8
EU New Member States
1.1
37.6
42.8
18.2
34.3
62.2
8.4
Europe (Non-EU)
2.3
50.9
39.1
36.3
19.4
44.9
11.9
Non-Europe
4.1
52.5
35.0
32.6
28.8
49.2
12.3
Total
100
50.8
39.7
25.2
27.2
73.5
 Share (%)
80.7
51.4
14.5
40.4
78.3
3.6
2.4
44.1
49.3
19.7
35.9
75.0
3.8
1.4
57.7
42.5
13.4
58.0
78.2
2.0
41.0
10.7
46.4
72.9
7.0
3.5
48.7
40.5
23.4
33.6
66.3
7.9
10.1
49.7
28.0
39.0
56.3
10.8
39.8
16.2
40.2
75.5
Note. Swedish Labor Force Survey, years, all yearly observations per period. Weighted data. *Calculated on total population years.

21. Unemployment ratio* (%)
Table 2. Percentage Swedish and foreign born, years.
Origin
Share (%)
Males (%)
Age
(mean)
Primary
educ. (%)
Tertiary
educ.(%)
In employ-
ment (%)
Unemployment ratio* (%)
Swedish
88.1
51.1
39.6
24.4
27.4
75.7
4.2
Nordic
3.4
43.6
47.2
34.6
20.3
69.9
4.5
EU-15
1.0
55.0
45.5
22.7
33.8
71.2
4.8
EU New Member States
1.1
37.6
42.8
18.2
34.3
62.2
8.4
Europe (Non-EU)
2.3
50.9
39.1
36.3
19.4
44.9
11.9
Non-Europe
4.1
52.5
35.0
32.6
28.8
49.2
12.3
Total
100
50.8
39.7
25.2
27.2
73.5
 Share (%)
80.7
51.4
14.5
40.4
78.3
3.6
2.4
44.1
49.3
19.7
35.9
75.0
3.8
1.4
57.7
42.5
13.4
58.0
78.2
2.0
41.0
10.7
46.4
72.9
7.0
3.5
48.7
40.5
23.4
33.6
66.3
7.9
10.1
49.7
28.0
39.0
56.3
10.8
39.8
16.2
40.2
75.5
Note. Swedish Labor Force Survey, years, all yearly observations per period. Weighted data. *Calculated on total population years.

22. Unemployment ratio* (%)
Table 2. Percentage Swedish and foreign born, years.
Origin
Share (%)
Males (%)
Age
(mean)
Primary
educ. (%)
Tertiary
educ.(%)
In employ-
ment (%)
Unemployment ratio* (%)
Swedish
88.1
51.1
39.6
24.4
27.4
75.7
4.2
Nordic
3.4
43.6
47.2
34.6
20.3
69.9
4.5
EU-15
1.0
55.0
45.5
22.7
33.8
71.2
4.8
EU New Member States
1.1
37.6
42.8
18.2
34.3
62.2
8.4
Europe (Non-EU)
2.3
50.9
39.1
36.3
19.4
44.9
11.9
Non-Europe
4.1
52.5
35.0
32.6
28.8
49.2
12.3
Total
100
50.8
39.7
25.2
27.2
73.5
 Share (%)
80.7
51.4
14.5
40.4
78.3
3.6
2.4
44.1
49.3
19.7
35.9
75.0
3.8
1.4
57.7
42.5
13.4
58.0
78.2
2.0
41.0
10.7
46.4
72.9
7.0
3.5
48.7
40.5
23.4
33.6
66.3
7.9
10.1
49.7
28.0
39.0
56.3
10.8
39.8
16.2
40.2
75.5
Note. Swedish Labor Force Survey, years, all yearly observations per period. Weighted data. *Calculated on total population years.

23. Figure 1. Changes in thousands of employed in different quintiles of
the Occupational-Wage distribution between the two periods to
Note. Swedish Labor Force Survey, years, all yearly observations per period. Weighted data.

24. 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5 Quintile Total
Total foreign born
within Quintile
1 Quintile
2 Quintile
3 Quintile
4 Quintile
5 Quintile
Total
12.2
9.9
9.8
6.8
7.7
9.3
25.5
17.8
14.0
12.0
13.4
16.2
Between
Quintiles
Swedish
21.1
18.3
20.1
21.7
18.8
100
17.7
14.5
19.4
23.6
24.9
New EU Members
25.1
18.2
19.5
18.6
28.5
14.2
16.8
21.0
19.6
European (non-EU)
30.9
24.1
26.0
8.8
10.2
31.2
20.4
14.4
Non-European
36.4
21.8
18.1
13.5
37.5
13.0
17.5
Note. Swedish Labor Force Survey, years, all yearly observations per period. Weighted data.

25. 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5 Quintile Total
Total foreign born
within Quintile
1 Quintile
2 Quintile
3 Quintile
4 Quintile
5 Quintile
Total
12.2
9.9
9.8
6.8
7.7
9.3
25.5
17.8
14.0
12.0
13.4
16.2
Between
Quintiles
Swedish
21.1
18.3
20.1
21.7
18.8
100
17.7
14.5
19.4
23.6
24.9
New EU Members
25.1
18.2
19.5
18.6
28.5
14.2
16.8
21.0
19.6
European (non-EU)
30.9
24.1
26.0
8.8
10.2
31.2
20.4
14.4
Non-European
36.4
21.8
18.1
13.5
37.5
13.0
17.5
Note. Swedish Labor Force Survey, years, all yearly observations per period. Weighted data.

26. 1 Quintile 2 Quintile 3 Quintile 4 Quintile 5 Quintile Total
Total foreign born
within Quintile
1 Quintile
2 Quintile
3 Quintile
4 Quintile
5 Quintile
Total
12.2
9.9
9.8
6.8
7.7
9.3
25.5
17.8
14.0
12.0
13.4
16.2
Between
Quintiles
Swedish
21.1
18.3
20.1
21.7
18.8
100
17.7
14.5
19.4
23.6
24.9
New EU Members
25.1
18.2
19.5
18.6
28.5
14.2
16.8
21.0
19.6
European (non-EU)
30.9
24.1
26.0
8.8
10.2
31.2
20.4
14.4
Non-European
36.4
21.8
18.1
13.5
37.5
13.0
17.5
Note. Swedish Labor Force Survey, years, all yearly observations per period. Weighted data.

27. ORGANISATIONSNAMN (ÄNDRA SIDHUVUD VIA FLIKEN INFOGA-SIDHUVUD/SIDFOT)
Table 5: Mobility after 1 year for individuals in quintile 1 of different origins in percentage.
Quintile 1
at t
Swedish
Nordic EU
European
(non-EU)
Non-European
Total
Stable
t+1 year
83.8
86.8
85.3
77.1
77.2
83.6
Upward
6.6
4.9
7.4
8.5
7.0
Out
9.6
8.3
14.4
15.9
9.9
100
(9,264)
(409)
(217)
(201)
(460)
(10,551)
81.7
88.6
82.9
82.5
79.7
8.7
5.5
6.4
5.8
6.5
8.2
9.7
5.9
10.7
11.8
13.9
10.1
(8,321)
(237)
(299)
(382)
(1,083)
(10,322)
Note. Swedish Labor Force Survey, years, rotation group 1-4. Unweighted data.

28. ORGANISATIONSNAMN (ÄNDRA SIDHUVUD VIA FLIKEN INFOGA-SIDHUVUD/SIDFOT)
Table 5: Mobility after 1 year for individuals in quintile 1 of different origins in percentage.
Quintile 1
at t
Swedish
Nordic EU
European
(non-EU)
Non-European
Total
Stable
t+1 year
83.8
86.8
85.3
77.1
77.2
83.6
Upward
6.6
4.9
7.4
8.5
7.0
Out
9.6
8.3
14.4
15.9
9.9
100
(9,264)
(409)
(217)
(201)
(460)
(10,551)
81.7
88.6
82.9
82.5
79.7
8.7
5.5
6.4
5.8
6.5
8.2
9.7
5.9
10.7
11.8
13.9
10.1
(8,321)
(237)
(299)
(382)
(1,083)
(10,322)
Note. Swedish Labor Force Survey, years, rotation group 1-4. Unweighted data.

29. ORGANISATIONSNAMN (ÄNDRA SIDHUVUD VIA FLIKEN INFOGA-SIDHUVUD/SIDFOT)
Table 5: Mobility after 1 year for individuals in quintile 1 of different origins in percentage.
Quintile 1
at t
Swedish
Nordic EU
European
(non-EU)
Non-European
Total
Stable
t+1 year
83.8
86.8
85.3
77.1
77.2
83.6
Upward
6.6
4.9
7.4
8.5
7.0
Out
9.6
8.3
14.4
15.9
9.9
100
(9,264)
(409)
(217)
(201)
(460)
(10,551)
81.7
88.6
82.9
82.5
79.7
8.7
5.5
6.4
5.8
6.5
8.2
9.7
5.9
10.7
11.8
13.9
10.1
(8,321)
(237)
(299)
(382)
(1,083)
(10,322)
Note. Swedish Labor Force Survey, years, rotation group 1-4. Unweighted data.

30. Paper with Kristina Håkansson and Tommy Isidorsson
“Dualisation and Polarisation of the Swedish Labour Market”
Figure 1: Mean changes between the periods 2000−2002 and 2013−2015 of employed persons with
permanent or temporary contracts and in different quintiles of the Occupational-Wage Structure.

31. Occupation/Wage Quintile 2000−2002 2013−2015
Table 1: Temporary employment in Occupational-Wage Quintile 2000−2002 and 2013−2015 (%).
Occupation/Wage Quintile
2000−2002
2013−2015
1 Quintile (Lowest wage)
25.2
30.1
2 Quintile
18.2
22.8
3 Quintile
12.5
14.1
4 Quintile
9.8
10.4
5 Quintile
8.2
Total
15.0
16.4
Note. Swedish Labor Force Survey, years. Weighted data.

32. Conclusions
The general pattern of occupational change in Sweden is towards upgrading. However, the tail of the lowest paid jobs are not decreasing.
The significance of the Swedish/Nordic model for the outcome: Low wage differences make high-paid jobs relatively cheap and low-paid jobs relatively expensive Upgrading!
Technological development is not the sole factor of occupational change  Privatizations, public procurement and ”New Public Management” in the public sector have important implications in the Swedish context
A changing labour supply (immigration) add to the development – the non-decreasing low-paid tail
Specific policies in Sweden to increase and subsidize employment in low- paid occupations (e.g. RUT, reduced VAT for restaurants) may have prevented job losses, but reinforced polarization tendencies.
Low paid employment has become more insecure (temporary contracts) and increasently consists of people with foreign background.
An important research area: The significance of changes in the occupational structure for inequality (i.e. from wages to incomes (earnings)).

33. Many thanks! Tomas.Berglund@socav.gu.se