DBnomics, the world's economic database

[62111L4012] Structure of earnings survey, Gross hourly earnings, Gender pay gap, Länder, Influence of the public authorities, Year

Updated by provider on December 8, 2020 (8:03 AM).

Search filters
Länder [DLAND] (16)
Influence of the public authorities [OEFHD1] (2)
Indicator [ind] (2)

This dataset has 64 series:

[01.EINFLUSS-01.VST007] Schleswig-Holstein – Dominant influence – Gross hourly earnings

from
2014=20.5
to
2018=22.31
min:
20.5
max:
22.31
avg:
21.405
σ:
0.905

[01.EINFLUSS-01.VST100] Schleswig-Holstein – Dominant influence – Gender pay gap

from
2014=14
to
2018=8
min:
8
max:
14
avg:
11
σ:
3

[01.EINFLUSS-02.VST007] Schleswig-Holstein – No or limited influence – Gross hourly earnings

from
2014=15.6
to
2018=17.37
min:
15.6
max:
17.37
avg:
16.485
σ:
0.885

[01.EINFLUSS-02.VST100] Schleswig-Holstein – No or limited influence – Gender pay gap

from
2014=20
to
2018=16
min:
16
max:
20
avg:
18
σ:
2

[02.EINFLUSS-01.VST007] Hamburg – Dominant influence – Gross hourly earnings

from
2014=20.62
to
2018=23.38
min:
20.62
max:
23.38
avg:
22
σ:
1.38

[02.EINFLUSS-01.VST100] Hamburg – Dominant influence – Gender pay gap

from
2014=5
to
2018=11
min:
5
max:
11
avg:
8
σ:
3

[02.EINFLUSS-02.VST007] Hamburg – No or limited influence – Gross hourly earnings

from
2014=20.18
to
2018=21.95
min:
20.18
max:
21.95
avg:
21.065
σ:
0.885

[02.EINFLUSS-02.VST100] Hamburg – No or limited influence – Gender pay gap

from
2014=24
to
2018=22
min:
22
max:
24
avg:
23
σ:
1

[03.EINFLUSS-01.VST007] Niedersachsen – Dominant influence – Gross hourly earnings

from
2014=19.66
to
2018=21.71
min:
19.66
max:
21.71
avg:
20.685
σ:
1.025

[03.EINFLUSS-01.VST100] Niedersachsen – Dominant influence – Gender pay gap

from
2014=14
to
2018=12
min:
12
max:
14
avg:
13
σ:
1