Class Schemas and Employment RelationsComparisons between the ESeC and the EGP class schemas using European data

By Erik Bihagen, Magnus Nermo, & Robert EriksonSwedish Institute for Social Research, SOFI, Stockholm University

Bled 29-30 June, 2006

The purpose of this paper

To compare the ESeC schema with the EGP schema.

To what extent are respondents allocated to equivalent classes with the two class schemas?

Compare empirical outcomes related to employment relationships: (1) requirements of specific human capital (SHC)

(2) monitoring problems (MP)(3) age gradients in wage

Theoretical assumptions (for employees)

Both class schemas aims at grouping occupations with similarities in: requirements of specific human capital (SHC) levels of monitoring problems (MP)

Employees are offered long-term benefits by the employer in: Occupations with high requirements of SHC in order to keep

replacements costs low. Occupations characterized by a high level of MP as a way to keep

work incentives high.

Types of employment relationships; Service relationship; high SHC + high MP Labour contract; low SHC + low MP Mixed contract; (low SHC + high MP) or (high SHC + low MP)

Data: The European Social Survey (ESS)ESS round 2 (edition 2) 22 European countries Sample size for employees age 20-60 with valid ISCO

codes 15.772 Class is based on 3 digit ISCO and additional

information on supervisory tasks ESeC is coded using ESeC version 4.0 EGP is coded using a widely used algorithm (based on

ISCO-88) developed by Ganzeboom & Treiman (1996 in Social Science Research)

Relevant measures of employment relations

Table 1. Seven classes of employees in EGP and ESeC

ESeC EGP Employment relationships

1 Higher salariat occupations

I Higher grade Professional etc. Service

relationship2 Lower salariat occupations

II Lower grade Professional etc.

3 Intermediate occupations

IIIa Higher grade routine non-manual

Mixed Contract

6 Lower supervisory and lower technician occupations

V Lower technical, and manual supervisory

7 Lower services, sales and clerical occupations

IIIb Lower grade routine non-manual

Labour contract8 Lower technical

occupationsVI Skilled manual

9 Routine occupations VII Non-skilled manualNote: IIIb is here characterized by a labour contract in accordance with Goldthorpe (2000).

Figure 2. The relative class distributions for Europe (for the 22 countries included in the ESS data)

0

5

10

15

20

25

0

5

10

15

20

25

30

ESEC1/EGP I ESEC2/EGP II ESeC3/EGP IIIa ESeC6/EGP V ESeC7/EGP IIIb ESeC8/EGP VI ESeC9/EGP VII

%

ESeCEGP

Table 2 Cross-tabulation between EGP and ESeC. All 22 countries included in the ESS data. (percent)

EGPESeC I II IIIa V IIIb VI VII1 high serv 58 9

2 low serv 37 67 16

3 mixed-clerical 8 61 11

6 mixed-supervis 5 15 100 2 14

7 labour-service 17 65 5 7

8 labour-lo tech 86 6

9 labour-routine 6 23 7 74

100 100 100 100 100 100 100

Two dimensions of employment relations in ESS Specific human capital

If somebody with the right education and qualifications replaced you in your job, how long would it take for them to learn to do the job reasonably well?

Monitoring problems index … how much the management at your work allows

you to decide how your own daily work is organised? About the work organization… My work is closely

supervised

Figure 1. Expected location of ESeC classes according to theoretical assumptions regarding specific human capital and monitoring problems.

ESeC8ESeC7

ESeC6

ESeC3ESeC2

ESeC1

ESeC9

-1

-0,5

0

0,5

1

-1 -0,8 -0,6 -0,4 -0,2 0 0,2 0,4 0,6 0,8 1

Monitoring problems

Spec

ific h

uman

capi

tal

EGP VII

EGP VI

EGP IIIb

EGP V

EGP IIIa

EGP II

EGP I

ESeC9

ESeC1

ESeC2

ESeC3

ESeC6

ESeC7

ESeC8

-1

-0,5

0

0,5

1

-1 -0,5 0 0,5 1

Figure 3. Location of ESeC and EGP classes according to estimated levels of specific human capital and ‘monitoring problems’ (based on estimates from OLS regressions for a person in the age of 40) for all countries in ESS

ESeC8

ESeC7

ESeC6

ESeC3

ESeC2ESeC1

ESeC9

-1

-0,5

0

0,5

1

-1 -0,8 -0,6 -0,4 -0,2 0 0,2 0,4 0,6 0,8 1

Monitoring problems

Spec

ific h

uman

capi

tal

EGP VII

EGP VI

EGP IIIb

EGP V

EGP IIIa

EGP II

EGP I

ESeC9

ESeC1

ESeC2

ESeC3

ESeC6

ESeC7

ESeC8

-1

-0,5

0

0,5

1

-1 -0,5 0 0,5 1

Figure 3. Location of ESeC and EGP classes according to estimated levels of specific human capital and ‘monitoring problems’ (based on estimates from OLS regressions for a person in the age of 40) for all countries in ESS

EGP VII

EGP VI

EGP IIIb

EGP V

EGP IIIa

EGP II

EGP I

ESeC9

ESeC1ESeC2

ESeC3

ESeC6

ESeC7

ESeC8

-1

-0,5

0

0,5

1

-1 -0,8 -0,6 -0,4 -0,2 0 0,2 0,4 0,6 0,8 1

Monitoring problems

Spec

ific h

uman

capi

tal

EGP VII

EGP VI

EGP IIIb

EGP V

EGP IIIa

EGP II

EGP I

ESeC9

ESeC1

ESeC2

ESeC3

ESeC6

ESeC7

ESeC8

-1

-0,5

0

0,5

1

-1 -0,5 0 0,5

Figure 4. Location of ESeC and EGP classes according to SHC and MP for Central Europe (Austria, Belgium, Switzerland, Germany, Luxembourg, Netherlands)

EGP VII

EGP VI

EGP IIIb

EGP V

EGP IIIa

EGP II

EGP I

ESeC9

ESeC1

ESeC2

ESeC3

ESeC6

ESeC7

ESeC8

-1

-0,5

0

0,5

1

-1 -0,8 -0,6 -0,4 -0,2 0 0,2 0,4 0,6 0,8 1

Monitoring problems

Spec

ific h

uman

capi

tal

EGP VII

EGP VI

EGP IIIb

EGP IIIa

EGP IIESeC2

ESeC3

ESeC6

ESeC7

ESeC8

Figure 5. Location of ESeC and EGP classes according to estimated levels of SHC and MP for Northern Europe (Denmark, Finland, Iceland, Norway, Sweden)

ESeC8

ESeC7

ESeC6ESeC3

ESeC2

ESeC1

ESeC9

EGP IEGP II

EGP IIIa

EGP V

EGP IIIb

EGP VI

EGP VII

-1

-0,5

0

0,5

1

-1 -0,8 -0,6 -0,4 -0,2 0 0,2 0,4 0,6 0,8 1

Monitoring problems

Spec

ific h

uman

capi

tal

EGP VII

EGP VI

EGP IIIb

EGP IIIa

EGP IIESeC2

ESeC3

ESeC6

ESeC7

ESeC8

Figure 6. Location of ESeC and EGP classes according to estimated levels of SHC and MP for Eastern Europe (Czech Republic, Estonia, Poland, Slovenia, Slovakia, Ukraine)

EGP VII

EGP VI

EGP IIIb

EGP V

EGP IIIa

EGP II

EGP I

ESeC9

ESeC1ESeC2

ESeC3

ESeC6

ESeC7

ESeC8

-1

-0,5

0

0,5

1

-1 -0,8 -0,6 -0,4 -0,2 0 0,2 0,4 0,6 0,8 1

Monitoring problems

Spec

ific h

uman

capi

tal

EGP VII

EGP VI

EGP IIIb

EGP IIIa

EGP IIESeC2

ESeC3

ESeC6

ESeC7

ESeC8

Figure 7. Location of ESeC and EGP classes according to estimated levels of SHC and MP for United Kingdom and Ireland

EGP VII

EGP VI

EGP IIIb

EGP V

EGP IIIa

EGP II

EGP I

ESeC9

ESeC1ESeC2

ESeC3

ESeC6

ESeC7

ESeC8

-1

-0,5

0

0,5

1

-1 -0,8 -0,6 -0,4 -0,2 0 0,2 0,4 0,6 0,8 1

Monitoring problems

Spec

ific h

uman

capi

tal

EGP VII

EGP VI

EGP IIIb

EGP IIIa

EGP IIESeC2

ESeC3

ESeC6

ESeC7

ESeC8

Figure 8. Location of ESeC and EGP classes according to estimated levels of SHC and MP for Southern Europe (Spain, Greece, Portugal)

EGP VII

EGP VI

EGP IIIb

EGP V

EGP IIIa

EGP IIEGP I

ESeC9

ESeC1ESeC2

ESeC3

ESeC6

ESeC7

ESeC8

-1

-0,5

0

0,5

1

-1 -0,8 -0,6 -0,4 -0,2 0 0,2 0,4 0,6 0,8 1

Monitoring problems

Spec

ific h

uman

capi

tal

The proportion in ESeC 6 and the explanatory power of the ESeC class schema with six different ways of using information on supervisory status

02468

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no su

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inctio

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one s

ubordi

nate

two su

bordi

nates

three su

bordina

tes

four sub

ordina

tes

five s

ubord

inates

percent in ESeC 6R2 * 100; MPR2 * 100; SHC

The location of ESeC 6 depending on the number of subordinates (All 22 Countries)

5 4321

0

-1

-0.5

0

0.5

1

-1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1

monitoring problems

spec

ific h

uman

capi

tal

Figure 9. Estimated age gradients in hourly wages, Central Europe (Belgium, Switzerland, Germany (ref cat), Luxembourg, Netherlands)

0

5

10

15

20

25

25 30 35 40 45 50 55

age

Euro

ESeC 1

ESeC 2

ESeC 3

ESeC 6

ESeC 7

ESeC 8

ESeC 9

Figure 9. Estimated age gradients in hourly wages, Central Europe(Belgium, Switzerland, Germany (ref cat), Luxembourg, Netherlands)

0

5

10

15

20

25

25 30 35 40 45 50 55

age

Euro

EGP I

EGP II

EGP IIIa

EGP V

EGP IIIb

EGP VI

EGP VII

Figure 10. Estimated age gradients in hourly wages, Northern Europe (Denmark, Finland, Norway, Sweden (ref cat))

0

5

10

15

20

25

25 30 35 40 45 50 55

age

Euro

ESeC 1

ESeC 2

ESeC 3

ESeC 6

ESeC 7

ESeC 8

ESeC 9

Figure 10. Estimated age gradients in hourly wages, Northern Europe (Denmark, Finland, Norway, Sweden (ref cat))

0

5

10

15

20

25

25 30 35 40 45 50 55

age

Euro

EGP I

EGP II

EGP IIIa

EGP V

EGP IIIb

EGP VI

EGP VII

Figure 11. Estimated age gradients in hourly wages, Eastern Europe (Estonia, Poland (ref cat), Slovakia, Ukraine)

0

0,5

1

1,5

2

2,5

3

3,5

4

25 30 35 40 45 50

age

Euro

ESeC 1

ESeC 2

ESeC 3

ESeC 6

ESeC 7

ESeC 8

ESeC 9

Figure 11. Estimated age gradients in hourly wages, Eastern Europe (Estonia, Poland (ref cat), Slovakia, Ukraine)

0

0,5

1

1,5

2

2,5

3

3,5

4

25 30 35 40 45 50

age

Euro

EGP I

EGP II

EGP IIIa

EGP V

EGP IIIb

EGP VI

EGP VII

Figure 12. Estimated age gradients in hourly wages, United Kingdom and Ireland (ref cat)

0

5

10

15

20

25

30

35

25 30 35 40 45 50 55

age

Euro

ESeC 1

ESeC 2

ESeC 3

ESeC 6

ESeC 7

ESeC 8

ESeC 9

Figure 12. Estimated age gradients in hourly wages, United Kingdom and Ireland (ref cat)

0

5

10

15

20

25

30

35

25 30 35 40 45 50 55

age

Euro

EGP I

EGP II

EGP IIIa

EGP V

EGP IIIb

EGP VI

EGP VII

Figure 13. Estimated age gradients in hourly wages, Southern Europe(only Spain)

0

5

10

15

20

25 30 35 40 45 50 55

age

Euro

ESeC 1

ESeC 2

ESeC 3

ESeC 6

ESeC 7

ESeC 8

ESeC 9

Figure 13. Estimated age gradients in hourly wages, Southern Europe (only Spain)

0

5

10

15

20

25 30 35 40 45 50 55

age

Euro

EGP I

EGP II

EGP IIIa

EGP V

EGP IIIb

EGP VI

EGP VII

Main Findings

Striking similarities between EGP and ESeC; a vast majority allocated in the same basic contracts similarly associated with dimensions of employment

relations have a similar relation to ‘wage dynamics’.

But; EGP V is troublesome in the EGP schema. ESeC 6 is more in

line with our expectations throughout most of our analyses.

The most advantaged class, the higher salariat, in ESeC is smaller, and more distinct when it comes to empirical outcomes.

The explained variation of SHC, MP and wage are somewhat stronger when class is measured by ESeC than EGP.