czech statistical office prague, czech republic

CZECH STATISTICAL OFFICENa padesátém 81, CZ - 100 82 Praha 10, Czech Republic

www.czso.cz

Bled, 29 – 30 June 2006

Czech Statistical OfficePrague, Czech Republic

ESeC and Gender

by

Dalibor Holy


www.czso.cz

Bled, 29 – 30 June 2006

The first attempt

1st quarter 2006 Labour Force Survey (LFS) data have been used as the most appropriate source. The ESeC 1-digit code has been derived using following variables:

- ISCO 3-digit code

- Status in employment

- Supervision or managerial position

- Number of persons on the workplace


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Bled, 29 – 30 June 2006

The ESeC

ESeC1

ESeC2

ESeC3

ESeC4

ESeC5

ESeC6

ESeC7

ESeC8ESeC9

Large employers, higher grade professional, administrative & managerial occupations

Low er grade professional, administrative and managerial occupations and higher grade technician

Intermediate occupations

Small employer and self employed occupations (exc agriculture etc)

Routine occupations

Self employed occupations (agriculture etc)

Low er supervisory and low er technician occupations

Low er services, sales & clerical occupations

Low er technical occupations


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Bled, 29 – 30 June 2006

Basic description of the database

27845 of employed persons 3125 were self-employed without employees; 1045

self-employed (employers) with employees; the rest was supposed to be employees

15446 men and 12399 women 4563 had position of supervisor or manager and

23153 had not, the rest unknown 21460 persons with timely unlimited labour

contract; 2013 limited, the rest unknown - n.a.


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Bled, 29 – 30 June 2006

Analysis I

Variables for the analysis: Sex (dummy: 0-man; 1-woman) Scale of Education (ISCED-97) Age groups (5-year intervals) Family status (single; married; widowed; divorced) - dummy: 0-not married; 1-married

(The ESeC was supposed to be a kind of scale for the correlation analysis)


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Bled, 29 – 30 June 2006

Analysis II

0

1000

2000

3000

4000

5000

6000

ES

eC1

ES

eC2

ES

eC3

ES

eC4

ES

eC5

ES

eC6

ES

eC7

ES

eC8

ES

eC9

nu

mb

er o

f p

erso

ns

Women

Men


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Bled, 29 – 30 June 2006

Analysis III – gender split

Men’s dominance is extreme in the ESeC 8 and also big is in the ESeC 1 and 4

Women are accumulated in the ESeC 3 and 7, i.e. in the middle of the scale

-3500-3000

-2500-2000-1500

-1000-500

0500

10001500

ES

eC

1

ES

eC

2

ES

eC

3

ES

eC

4

ES

eC

5

ES

eC

6

ES

eC

7

ES

eC

8

ES

eC

9

WOMEN

MEN


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Bled, 29 – 30 June 2006

Correlation matrixSPSS Correlations esec isced agegroup supervision isco family sex

esec Pearson Correlation 1 -0,5826967 -0,0507177 0,4471127 0,8620288 -0,0707871 -0,0687431

Sig. (2-tailed) . 0 2,491E-17 0 0 2,85E-32 1,586E-30

N 27845 27845 27845 27716 27845 27845 27845

isced Pearson Correlation-0,5826967 1 0,0265377 -0,2912148 -0,580784 0,0286063 0,0107712

Sig. (2-tailed) 0 . 9,473E-06 0 0 1,804E-06 0,0722807

N 27845 27845 27845 27716 27845 27845 27845

agegroup Pearson Correlation-0,0507177 0,0265377 1 -0,0814077 -0,01413 0,383759 0,0013205

Sig. (2-tailed) 2,491E-17 9,473E-06 . 5,651E-42 0,0183808 0 0,8256065

N 27845 27845 27845 27716 27845 27845 27845

supervision Pearson Correlation0,4471127 -0,2912148 -0,0814077 1 0,4186905 -0,0883412 0,1172332

Sig. (2-tailed) 0 0 5,651E-42 . 0 3,825E-49 2,125E-85

N 27716 27716 27716 27716 27716 27716 27716

isco Pearson Correlation0,8620288 -0,580784 -0,01413 0,4186905 1 -0,0480433 -0,1511167

Sig. (2-tailed) 0 0 0,0183808 0 . 1,047E-15 6,76E-142

N 27845 27845 27845 27716 27845 27845 27845

family Pearson Correlation-0,0707871 0,0286063 0,383759 -0,0883412 -0,0480433 1 7,804E-05

Sig. (2-tailed) 2,85E-32 1,804E-06 0 3,825E-49 1,047E-15 . 0,9896102

N 27845 27845 27845 27716 27845 27845 27845

sex Pearson Correlation-0,0687431 0,0107712 0,0013205 0,1172332 -0,1511167 7,804E-05 1

Sig. (2-tailed) 1,586E-30 0,0722807 0,8256065 2,125E-85 6,76E-142 0,9896102 .

N 27845 27845 27845 27716 27845 27845 27845


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Bled, 29 – 30 June 2006

Analysis IV – correlation

The demographic variables are not strongly correlated with each other (sex, age, family status, education), exc. age and family status, it seems that the LFS data are almost perfectly suitable for the ESeC analysis.

The ESeC is highly correlated (58%) with education scale: the higher level of education, the better position on the labour market

The correlation between the ESeC and sex is quite week (7%): men have better position that women

As well the correlation between the ESeC and family status is not great but relevant (7%): married people have higher position that not married.

The weakest relation is between ESeC and age group (5%): older people have slightly higher position that younger.


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Bled, 29 – 30 June 2006

Analysis V

Three islands: Blue-collar workers

(ESeC 8 and 9) with apprenticeship (ISCED 3c)

Technicians with secondary education with GCE (ISCED 3a,b)

Professionals with university degree (ISCED 5a) E

DU

1

ED

U2

ED

U3

ED

U4

ED

U5

ED

U6

ED

U7

ED

U8

ED

U9

ED

U10

ESeC1

ESeC2

ESeC3

ESeC4

ESeC5

ESeC6

ESeC7

ESeC8

ESeC9


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Bled, 29 – 30 June 2006

Analysis VI or Gender view

MEN WOMEN

ED

U1

ED

U2

ED

U3

ED

U4

ED

U5

ED

U6

ED

U7

ED

U8

ED

U9

ED

U10

ESeC1

ESeC2

ESeC3

ESeC4

ESeC5

ESeC6

ESeC7

ESeC8

ESeC9

ED

U1

ED

U2

ED

U3

ED

U4

ED

U5

ED

U6

ED

U7

ED

U8

ED

U9

ED

U10

ESeC1

ESeC2

ESeC3

ESeC4

ESeC5

ESeC6

ESeC7

ESeC8

ESeC9


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Bled, 29 – 30 June 2006

Conclusion notes

The Labour Force Survey is an appropriate data source.

The ESeC seems be a useful tool for gender analyses.

There are generally two ways of coding: for labour force analyses – individuals; for social analyses – households according to

the head of family (or rather family member with higher class of ESeC)


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Bled, 29 – 30 June 2006

Thank you for your attention

czech statistical office prague, czech republic

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