Strengthening the use of administrative data to provide gender statistics - Pandolfelli, Lauren; Carter, Karen (International Journal of Population Data Science, 2019)
The 2030 Agenda for Sustainable Development explicitly recognizes the critical role of gender data in monitoring progress toward all 17 Sustainable Development Goals (SDGs). Yet, gaps in gender data vis-à-vis availability, granularity, timeliness and adherence to international standards, compromise the ability of countries to design gender-responsive policies and meet the commitment enshrined in the SDGs to leave no one behind. Administrative data systems are increasingly recognized as an important source for filling gender data gaps, but there has been limited unpacking of what this means at a system level in terms of 1) prioritization, 2) restructuring data flows to ensure data can be appropriately disaggregated, 3) how data needs can be best supported within current systems structures, and 4) key opportunities for national statistical offices and gender specialists to engage administrative data systems. The work aims to identify the specific opportunities, challenges and value of using administrative data more effectively to improve gender-equitable development outcomes; and translate this into practical guidance for national statistical offices and line ministries. While focused primarily on developing countries, the intent is to understand these elements across contexts and levels of system maturity. Issues will be explored through literature review, key informant interviews from government and stakeholder groups, and detailed case studies for three countries at different levels of data system maturity. Work will be undertaken by UNICEF with support of the Inter-Agency and Expert Group on Gender Statistics (IAEG-GS). This body, comprising national statistical systems and international agencies, is the coordinating body of the United Nations Global Gender Statistics Programme. Guidance developed through this work is anticipated to build on existing initiatives to improve cross-sectoral data for development and ensure we “leave no one behind” as we move forward to achieving the SDGs.