IDS WageIndicator Conference ‘Going Global’ Louisa Potter and Simone Melis Incomes Data Services Amsterdam, 16 April

IDS The International Gender Pay Gap Comparing WageIndicator and ILO data

IDS Outline  Global data from ILO  WageIndicator findings  Visualizing the gap  Comparing ILO and WI results  Methodological issues  Debate: towards a single WI methodology?

IDS Global data  Analysis of pay gap in 63 countries; 30 European, 33 across the rest of the world  Global average 15.6 per cent (excluding Bahrain 16.5 per cent)  Results generally more positive in Europe, Oceania and Latin America, with Europe taking the lead  Data deficiencies in a number of countries, particularly across Africa and Asia

IDS Global data (2)  Europe - Average pay gap 14.5 per cent Overall decline in pay gap over the last decade Job segregation by gender has a negative effect on pay gap (i.e. UK)  Americas - North America: lack of official data Larger pay gap in Canada (27.5%) & USA (22.4%) than world average Latin America: mixed picture due to large informal economies

IDS Global data (3)  Oceania - Pay gap lower than world average: Australia 14.1% & New Zealand 13.8% Mixed picture on progress  Africa - Insufficient data  Asia - Pay gap significantly higher than world average Large variation due to the nature of individual country labour markets and quality of official data, i.e. Bahrain (-40%), Japan (33.4%), Mongolia (16.1%) and Sri Lanka (7.3%)

IDS WageIndicator findings  12 countries covering almost respondents  Average gap ranges between 13 (Brazil) and 23 per cent (Poland)  Pay gap is higher in female-dominated work environments than in typical male dominated work environments  The gender pay gap by NACE industry breakdown

IDS WageIndicator findings (2)  Part-time vs. full-time hours  The relationship between trade union membership and the gender pay gap  The public-private sector divide  Does education matter?

IDS Visualizing the global gap

IDS Visualizing the European gap

IDS Comparing ILO and WI results CountryILO/Eurostat data sources Wage Indicator database Belgium7.0 (provisional)13.3 Brazil17.7 (2004)12.9 Finland20.0 Hungary Germany Netherlands18.0 (2005)20.8 Poland Spain United Kingdom20.0 (2005)15.7

IDS Methodological issues  Defining the gender pay gap  Calculating earnings  Availability and reliability of data  Sample size/response rate  Type of employee  Data collection

IDS Debate: Towards a single WI methodology?  Adjusted or unadjusted?  Weighted?  Hourly/weekly/annual earnings data?  Data collection period?