1. UNECE Work Session on Gender Statistics 6-8 october 2008 Geneva 1 Economic Indicators for Gender Analysis Some observations Ko Oudhof Statistics Netherlands

2. UNECE Work Session on Gender Statistics 6-8 october 2008 Geneva 2 Papers in the session Gender and Economic Statistics –Heather Dryburgh, Statistics Canada Gender Pay Gap: Data availability and measurement issues –Elisa Benes, UNECE Statistical Division Measuring gender equality in the economy in countries of Central Asia –Ewa Zimny and Enrico Bisogno, UNECE Who benefits more? Benefit of the government by gender. A Dutch example of gender budget analysis –Saskia Keuzenkamp, Statistics Netherlands Social Accounting Matrix (SAM) –Maria Isabel Quintela, National Statistical Institute, Portugal

3. UNECE Work Session on Gender Statistics 6-8 october 2008 Geneva 3 Abstract starting point: social process FACTOR/ CAUSE ACTORS & POSITIONSEFFECT Non- gendered --- (?) Non- gendered Male → → Female Institutional

4. UNECE Work Session on Gender Statistics 6-8 october 2008 Geneva 4 Gendering Economic Indicators (1) WITHIN ACTORS/POSITIONS – male/female paid work participation – occupational segregation – within households (roles, decisions) EFFECTS – genderised contribution to GDP (informal work) – genderised consumption (markets) CAUSES – genderised consequencies of budgets – equality policy

5. UNECE Work Session on Gender Statistics 6-8 october 2008 Geneva 5 Gendering Economic Indicators (2) UNECE: Measurement/data gender pay gap Cause ≠ Male/Female ≠ Effect Netherlands Gendering tertiary income (government budget) More general and more monetary than most GBA’s Institutional  Male/Female ≠ Effect

6. UNECE Work Session on Gender Statistics 6-8 october 2008 Geneva 6 Gendering Economic Indicators (3) Portugal Social accounting matrix Institutional  (compensation) Male/Female (labour input)  Institutional Canada Available data on labour market, time use, income etc. and possible gaps Available: Cause ≠ Male/Female ≠ Effect Gap 1: Institutional  male/female ≠ Effect Gap 2: Cause ≠ Male/female  Institutional

7. UNECE Work Session on Gender Statistics 6-8 october 2008 Geneva 7 IF YES? - QUESTIONS (≈ reflections Canada) Papers raise questions for other countries: Would it be conceivable to genderise the elements? –Yes, it has been done, look at papers Would it have any use to do it? –Idem, but what considering the national context? Would it be feasible? –Considering policy as well as data needs Would it deserve any priority? Would it be possible to bring about any priority? When should it start?

8. UNECE Work Session on Gender Statistics 6-8 october 2008 Geneva 8 AND BEYOND THAT…. Why not the ultimate model: –Male/Female Cause  Male/Female  Male/Female Effect Gender pay gap –Entepreneurs etc  pay gap –Pay gap  economic contribution Tertairy income –Decision makers  income – tertiary income  social participation SAM –Entepreneurs etc  paid labour –Paid labour  Entrepreneurs etc.

9. UNECE Work Session on Gender Statistics 6-8 october 2008 Geneva 9 IF YES? - QUESTIONS Questions for all (?) countries: Would it be conceivable to genderise the elements? Would it have any use to do it? Would it be feasible? Would it deserve any priority? Would it be possible to bring about any priority? When should it start?