Equal Pay research in Hungary and Belgium Bussum, the Netherlands April 15, 2008 Szilvia Borbely
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
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
Hungarian database of 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 Female Male Wage gap% 2118
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
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
Some example Source WageIndicator dataset Sept Sept. 2006; BérBarométer 5000 dataset, October 2006, Hungary
Some example
Problems, questions Minimum requirement of sample number Time schedule (database development:2006/ yearly wage rise) Gross or net wage? Use hourly or monthly wage? Methodology to calculate the pay gap