Skip to main content

Table 1 Key variables of the data set

From: Occupation-specific wage returns: shedding light on differentials between employees with a VET degree either with or without an Abitur

Categorical variables

Full Sample (%)

VET1 (%)

VET2 (%)

Educational attainment

   

 No degree

9.24

  

 VET1 degree

50.28

  

 VET2 degree

9.70

  

 Advanced VET degree

7.56

  

 HE degree

23.22

  

Gender (Male)

53.38

53.94

42.10

Region (West)

80.05

78.08

83.84

Erikson-Goldthorpe-Portocarero-Schema (EGP)

  

 I Higher managerial and professional workers

14.50

8.00

18.04

 II Lower managerial and professional workers

13.25

8.85

17.65

 IIIa/b Routine clerical and service and sales work

8.11

8.40

10.43

 IVa Small self-employed with employees

3.66

3.18

3.73

 IVb Small self-employed without employees

1.82

1.86

1.98

 V Manual supervisors

3.41

3.25

2.10

 VI Skilled manual workers

20.67

25.29

17.53

 VIIa Semi- and unskilled manual workers

17.42

21.70

12.70

 VIIb Agricultural labour

2.36

3.21

1.72

 IVc Self-employed farmers

3.10

3.68

3.58

Migration status

  

 No

80.21

85.98

78.94

 Yes

8.38

8.06

9.07

 Foreigner

11.30

5.87

11.73

Married (yes)

54.02

55.21

51.02

Children under 18 (yes)

33.28

31.73

36.81

School-leaving grade

   

 Very good

9.61

5.02

7.20

 Good

48.60

45.82

50.56

 Satisfying

32.09

37.58

37.57

 Sufficient

2.68

3.29

2.13

Grade training degree

   

 Very good

15.53

9.72

23.95

 Good

46.84

51.03

53.68

 Satisfying

22.01

31.40

16.09

 Sufficient

2.38

3.76

2.19

Pursuit the goal of a career

   

 Very strong

7.27

5.28

8.14

 Strong

28.66

24.20

29.66

 No much

40.34

42.50

42.58

 Not at all

21.75

25.94

18.49

 Part/Part

0.87

1.09

0.65

Firm size

  

 Under 9

12.47

14.41

12.92

 9 to 49

26.51

27.62

26.94

 50 to 250

24.78

24.87

24.02

 Over 250

32.66

29.29

33.41

Sector

  

 Agricultural/Mining

2.31

2.48

1.78

 Manufacturing

11.04

12.46

8.02

 Metal and electrical industry

17.35

19.06

11.99

 Construction industry

6.02

8.54

3.43

 Trade

9.61

11.62

9.18

 Private services

15.04

14.53

13.93

 Banks/insurance companies

2.92

1.78

6.14

 Business-related services

7.76

5.80

8.03

 Public service

12.44

8.34

14.44

 Health and social services

15.20

15.02

22.94

Works council (yes)

56.49

53.14

54.98

Metric variables

Mean (standard deviation)

Tenure

11.29 (10.73)

12.63 (11.15)

10.50 (9.80)

Working hours

37.79 (10.94)

37.52 (10.62)

37.00 (10.22)

Age

43.24 (11.73)

44.79 (11.44)

40.55 (11.28)

Share of analytic and interactive tasks

0.58 (0.24)

0.50 (0.23)

0.64 (0.20)

Share of routine tasks

0.23 (0.17)

0.27 (0.17)

0.19 (0.13)

N

15,640

6349

2084

  1. Source: BIBB/BAuA Employment Survey 2018, all values are weighted
  2. Population: German employees
  3. Percentages missing up to 100% are due to missing values