United Nations Economic Commission for Europe Statistical Division Statistical framework to mainstream gender in economics Enrico Bisogno Meeting of experts on Mainstreaming Gender into Economic Policies Geneva, 9-10 July 2007
Piera Tortora Slide 2Geneva, 9-10 July 2007 Introduction Statistics as an important instrument towards gender equality Very important in those countries where political discourse traditionally incorporates gender equality need to scrape the surface
Piera Tortora Slide 3Geneva, 9-10 July 2007 Quality approach to improve statistics Relevance Accuracy Accessibility Timeliness Interpretability Based on international standards
Piera Tortora Slide 4Geneva, 9-10 July 2007 Approach within SPECA program: Tiers Many different needs/gaps exist: how to prioritize? How to build a strategy? A framework based on tiers, with different degrees of feasibility and targeting different groups of users
Piera Tortora Slide 5Geneva, 9-10 July 2007 Four tiers Tier 1: Data produced and based on standard methods Tier 2: Data could be produced on the bases of existing sources, but they are not. In other cases, data are not produced according to international standards Tier 3: Data not yet available in official statistics, very relevant, but no standard in place Tier 4: Qualitative assessments difficult to include in a statistical frame
Piera Tortora Slide 6Geneva, 9-10 July 2007 Tier 1 Data produced and based on standard methods Challenges: Make data collection regular Not all countries able to collect these data Improve dissemination Facilitate use of data
Piera Tortora Slide 7Geneva, 9-10 July 2007 Tier 1: examples Unemployment and employment rates Employment by status (own-account worker, employer, employee, etc.) Basic welfare information, such as number of pensioners and children in preschools
Piera Tortora Slide 8Geneva, 9-10 July 2007 Tier 1: examples for challenges Data dissemination: some publications available, but on-line databases are still rare Labour force surveys not yet regular in some countries Link between data and policies: to what extent national strategies are benchmarked against indicators?
Piera Tortora Slide 9Geneva, 9-10 July 2007 Tier 2 Data could be produced on the bases of existing sources, but they are not Data are not produced according to international standards Challenges: Make full use of available sources Standardize definitions so that data become more relevant and comparable
Piera Tortora Slide 10Geneva, 9-10 July 2007 Tier 2: examples Data on entrepreneurship, such as % enterprises/farms managed by women Informal employment Employment by family status Gender pay gap
Piera Tortora Slide 11Geneva, 9-10 July 2007 Tier 2: examples for challenges Work to improve selected indicators (for example gender pay gap) Improve LFS to incorporate informal employment Improve business statistics (registers) Produce data for sub-national levels
Piera Tortora Slide 12Geneva, 9-10 July 2007 Tier 3 Data not yet available in official statistics Very relevant and needed, but no standard in place Challenges: Develop new standards and definitions Identify appropriate sources
Piera Tortora Slide 13Geneva, 9-10 July 2007 Tier 3: examples Access to economic assets (land, loans, etc.) Intra-household distribution of income Gender attitudes
Piera Tortora Slide 14Geneva, 9-10 July 2007 Tier 4 Qualitative assessments Qualitative targets Examples: Improve education system Improve governance
Piera Tortora Slide 15Geneva, 9-10 July 2007 Questions What are the most relevant statistical challenges in your country? Where is the priority: the use of data? the link between data and research or between data and policies? Relevance and/or accuracy of selected indicators? At what level: national or regional?