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Equal Pay research in Hungary and Belgium Bussum, the Netherlands April 15, 2008 Szilvia Borbely
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EQUAL project „Equal pay for equal work!” January 2005-April 2008 Target Adapting and making to function innovative tool to increase female equal opportunities Tools Website Database Content development Partnership
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Specialities Adapting Dutch wageindicator Combination of methods to create database Including target persons to create database (needs assessment and training element) Database: cross-country comparability Developing trade union strategies
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Hungarian database of 10000 samples Representativity (male/female, age,scholarity,regions, NACE (19/29), ISCO) Disparities –regional (max32%, min7% White collar (26%), blue collar (19%) Gross wage EUR Net wage EUR Female531367 Male 670447 Wage gap% 2118
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TCA I Explanation of gender wage gap Belgium – 16,5% Function related variables - characteristics of the jobs of men and women – complexitiy of jobs Person-related variables-education Company-related variable: low Hungary-structural effect (-7%)+high discrimination effect (26%) due mainly to: Jobs requiring higher or middle education (4%) Education – higher education (23%) Years in work (11-20 years: 35%) Growing % of women in workplace: negative discrimination effect
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TCA II: Working conditions of women and men with focus on the reconciliation of duties at work and in the family Working time Full-time, part-time Organisation of working time Flexibility and security Flexibility in work-time organisation Working contracts as condition of labour market flexibility Training as condition of re-entrance into the labour market and labour market security Stress at work
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Some example Source WageIndicator dataset Sept. 2004-Sept. 2006; BérBarométer 5000 dataset, October 2006, Hungary
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Some example
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Problems, questions Minimum requirement of sample number Time schedule (database development:2006/2007 - yearly wage rise) Gross or net wage? Use hourly or monthly wage? Methodology to calculate the pay gap
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