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Czech Statistical Office Prague, Czech Republic

Czech Statistical Office Prague, Czech Republic. ESeC and Gender by Dalibor Holy. 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

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Czech Statistical Office Prague, Czech Republic

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  1. Czech Statistical OfficePrague, Czech Republic ESeC and Gender by Dalibor Holy

  2. 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

  3. The ESeC

  4. 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.

  5. 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)

  6. Analysis II

  7. 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

  8. Correlation matrix

  9. 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.

  10. 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) Analysis V

  11. Analysis VI or Gender view

  12. 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)

  13. Thank you for your attention

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