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The Promises and Challenges of Gender Data

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Authors: Mayra Buvinic and Eleanor Carey
Presented by Agnes Quisumbing

Publié dans : Données & analyses
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The Promises and Challenges of Gender Data

  1. 1. The Promises and Challenges of Gender Data Authors: Mayra Buvinic and Eleanor Carey Presenter: Agnes Quisumbing
  2. 2. Good Data Form the Backbone of Effective Policy • This chapter examines the state of gender data on rural women and girls in SSA in three ATOR focus areas: • Assets, income and work • Social and political empowerment • Food security and nutrition
  3. 3. Chapter Outline 1. Outlines benefits of improved data, offers guiding principles, and explores methodological issues 2. Selects 32 indicators from SDG and related frameworks to measure the three ATOR outcomes • Assesses availability and quality of these data in 15 SSA countries using research from Open Data Watch (ODW)
  4. 4. Benefits of Improved Data 1. Problems of substandard data are particularly prevalent in SSA and impede full accounting of women’s work 2. Poor data hamper the ability to formulate effective policies to increase women’s productivity in agriculture and improve food security and nutrition 3. Better understanding and measuring rural women’s and girls’ poverty is the first step to effective anti-poverty policy solutions
  5. 5. Guiding Principles for Gender Data Collection 1. Because women’s economic and social roles (especially in rural economies) are interdependent, data need to be generated on both economic and social outcomes, and measures need to track their interdependence 2. Because women’s individual and household choices are linked, data should be generated and analyzed at both the individual and household levels
  6. 6. Good Gender Evidence • Is high quality (data are reliable, valid, representative and free of bias) • Has good coverage across countries, and is produced at regular intervals • Is comparable across countries (concepts, definitions, measures) • Has desirable complexity and granularity • Is parsimonious and policy relevant
  7. 7. Methodological Issues •Income: challenging to capture– sporadic, variable, difficult to disentangle from household income •Assets: preferable to income as measure of women’s economic status– but better as a medium- and long- term indicator, not short-term •Work: previous methodologies failed to capture much of rural women’s work; conceptual advancements made with 19th ICLS •Empowerment: includes an objective outcome dimension and a subjective sense of agency; it is difficult to measure accurately
  8. 8. Current Data Availability: Bridging the Gap Assessment • ODW assessed data for 104 indicators across 15 SSA countries from 2010-2018 • Authors selected 32 indicators that best measured three key outcomes for rural women and girls
  9. 9. Current Data Availability: Bridging the Gap Assessment 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Sex disaggregated at international level Availability at international level Sex disaggregated at national level Availability at national level Availability and Sex Disaggregation Scores for 15 SSA Countries Assets, income, work (20 indicators) Empowerment (6 indicators) Food security and nutrition (6 indicators)
  10. 10. Current Data Availability: Bridging the Gap Assessment • On average, around 70% of all indicators have some data available • Assets, income and work show the lowest availability across countries • Women’s empowerment and food security/nutrition show high availability • Sex disaggregation is an issue in both national and international databases
  11. 11. Current Data Availability: Bridging the Gap Assessment • 15% of assets and 11% of income indicators are sex disaggregated in international data bases, and 35% and 18% in national • Political indicators are more available at the international level (100% vs. 73%), and social indicators at the national (75% vs. 61%) • Food security and nutrition perform best, but there are still gaps in sex disaggregation
  12. 12. Current Data Availability: Bridging the Gap Assessment Availability varies significantly between countries both at the national and international levels
  13. 13. Discussion •Rural women and girls in SSA are a key group to target– but generating good evidence is challenging • Assessing availability of data a basic first step • ODW’s assessment revealed promising results, but shows that sex disaggregation is still a challenge
  14. 14. Recommendations •Recommendations to improve coverage, comparability, granularity, and policy relevance: 1. Collect data at the individual and household levels 2. Invest in efforts to better combine and harmonize data sources to achieve multiple disaggregations 3. Support the widespread implementation of new guidelines and technical assistance to countries in areas that will improve measurement on rural women and girls.
  15. 15. Recommendations 4. Undertake work to agree on methodology for tier III indicators and devise indicators that are better at capturing objective and subjective measures of empowerment. 5. Prioritize disaggregating data by sex for indicators on income and assets. 6. Emphasize secondary analysis of data. 7. Build connections to decision makers to improve the potential for uptake and impact.