1. 1 Analysis and Presentation of Gender Statistics 3 October 2007 Republic of Moldova UNECE Statistical Division

2. 2 Analysis of Gender Statistics Why do Gender Analysis? –Improve design of policies, projects and programs –Measure impact of interventions –Understand differences between genders

3. 3 What is needed for analysis? Sex-disaggregated data Is this enough? NO! National Statistics Offices regularly publish sex- disaggregated data without doing any gender analysis

4. 4 For Example… In many countries, men have higher labour force participation rates than women Sex-disaggregated data shows us this, but we dont know why So, we need more information…..

5. Percent of Economically Active People Aged 20-29 by Sex MenWomen Source: United Nations Economic Commission for Europe, 2000.

6. Percent Economically Active People Aged 20-29 by Sex and the Presence of a Pre-school Child: 1998

7. 7 Presenting Data Presentation is crucial Should attract readers Encourage further analysis A range of formats –Tables –Graphs –Diagrams –Maps

8. 8 Tips for Good Presentation Clear visual message Appropriate heading Convey one finding or a single concept Simple

9. 9 A Good Graph Accurately shows facts Grabs the readers attention Shows trends or changes Is clear and easy to read Has a title and minimal labels Uses colours or patterns to show differences

10. 10 How many statisticians present data

11. 11 Make it Easy to Understand Graphic presentation of data makes it easier to understand Easier to see the differences between men and women

12. 12 Percentage Married at Older Ages by Sex in the US: 2003

13. 13 How we present sex-disaggregated data influences the analyses we make

14. 14

15. 15

16. 16 Both graphs give important, yet different, information

17. 17

18. 18 0.1 -2.2 -3.2 13.4 12.1 1.5 5.1 3.2 5.6 6.7 5.7 7.5 6.1 6.8 5.3 Botswana Zimbabwe Swaziland Russia Belarus India Egypt China Mexico Chile United States France Italy Japan Singapore Female Advantage in Life Expectancy at Birth in Select Countries: 2003 Source: U.S. Census Bureau, International Programs Center, International Data Base.

19. 19 From raw data to easily understood gender statistics Tables and graphs from raw data Gender concern here is Poverty Underlying cause is the lack of means of economic support Closer analysis requires reasons for not being economically active Sources: labour force surveys or population censuses

20. Population ages 10 and over by economic activity status and reasons for not economically active in Tanzania Mainland 1990/91

21. Basic Table 1 Population ages 10 and over by economic activity status Focuses only on economic activity rate Exact numbers rounded to 1,000s and percentages to integers

22. Population ages 10 and over by economic activity status Further simplified Deleted two columns of numbers and included total in 1,000s

23. Basic Table 2 Not economically active ages 10 and over by reasons Focuses only on reasons for being not economically active Exact numbers rounded to 1,000s and percentages to integers

24. Not economically active ages 10 and over by reasons Further simplified Deleted two columns of numbers and included total in 1,000s

25. 25

26. 26 Acknowledgements Victoria Velkoff, US Census Bureau Statistics Sweden Engendering Statistics: A Tool for Change Statistics New Zealand http://www.stats.govt.nz/NR/rdonlyres/A1892BF2-6E4A-4D08-9667-BC5EE45B99F4/0/GraphicsGuidelines.pdf Office of National Statistics UK Statistics Denmark Russian Federal State Statistics Office UNECE Gender Statistics Database