1. Workshop on Improving Gender Statistics in Rwanda Session 2 Gender Statistics in Rwanda Serena Hotel, Lake Kivu March 25-27, 2014 1

2. Learning Objectives By the completion of the Session, participants should understand and become familiar with: The context and background for gender statistics in Rwanda; The Gender Statistics Framework, its organization and contents; The main gender statistics products in Rwanda, how they are disseminated and who uses them; How the GSF compares to other international gender statistics, in particular the UN Minimum Set of Gender Indicators; and What are the main areas or sectors for which additional data are needed; Primary references: NISR and GMO 2013. National Gender Statistics Report, 2013. UNSD. 2012. Minimum Set of Gender Indicators. GLOBAL FORUM ON GENDER STATISTICS ESA/STAT/AC.253/101, 27-29 March 2012, Dead Sea, Jordan. http://unstats.un.org/unsd/gender/Jordan_Mar2012/Minimum%20List%20of%20Indicators.pdf 2

3. Gender Statistics in Rwanda: background and context Rwanda has adopted a National Gender Policy (NGP, 2010) and a Plan of Action to ensure effective gender mainstreaming and full participation of women in all activities related to nation’s socio-economic development. The NGP mandates the development of comprehensive monitoring and evaluation and a sex-disaggregated data collection system at national and local levels for effectively monitoring and assessing progress on implementing the national gender policy. In 2012, NISR and GMO, with financial and technical support from UN Women/UN Delivering as One (DaO), established a comprehensive Gender Statistics Framework (GSF) to encourage the use of sex-disaggregated data for evidence-based planning, monitoring progress and policy formulation. The NISR, the GMO, MIGEPROF and other government agencies (including line ministries) use the sex-disaggregated and gender-relevant data collected by NISR to monitor progress on gender mainstreaming and on gender differences in such sectors as public sector and government, health, education and employment. 3

4. The Gender Statistics Framework: organization and contents The GSF covers 13 different development sectors and areas (see report): The GSF comprises indicators compiled from surveys, censuses and administrative data collected at the national, regional and district levels, although data for all indicators may not be available for all districts. The GSF contains around 300 indicators disaggregated by sex, age, rural/urban and other criteria, e.g., marriage status (see report) The GSF includes all possible indicators from survey reports and other sources for which there were data available. NISR plans to review the list of indicators and/or evaluate specific indicators – e.g., using the data from the recent census to add more indicators 4 1. Population & Youth8. Decision-making & Governance 2. Education9. Infrastructure, ICT & Media 3. Health & Nutrition10. Trade & Business 4. Work/Employment & Time use11. Industry & Processing 5. Social protection & Disasters management12. Agriculture, Livestock & Forestry 6. Justice13. Income & Access to Finance 7. Environment & Natural Resources

5. The Gender Statistics Framework: data sources The NISR has the lead or coordinating role in producing the gender statistics, in collaboration with the GMO. NISR’s program on Gender Statistics covers three areas: – Production of Gender Statistics Publications and organization of Policy Fora – Operationalization of the Gender Statistics Framework – Trainings in Gender Statistics The NISR identifies, extracts, compiles, publishes and disseminates the data from censuses and surveys it conducts, and from collections conducted by line ministries such as MINEDUC, MINISANTE (HMIS), MINAGRI, MIDIMAR or MINECOFIN, and from administrative data records. Handout 2.1 provides a list of the main data sources that are used ort could be used to produce the gender statistics in the GSF. 5

6. The Gender Statistics Framework: data sources (2) Currently, sex-disaggregated or gender-relevant data can be accessed or obtained only from published reports or compilations such as the GSF report, – This means that data are not really up-to-date because publications take some time to be completed and launched. – Setting up an electronic mechanism to disseminate the data soon after it is collected and before it is published would make it possible to disseminate the data in a timely manner and provide more data to more users. – The data should be disseminated in a matrix format such as Excel so that users can create their own tables and conduct their own analysis. The NISR could extract and include in the GSF data from other sources, such as the Manpower or establishment surveys (see handout 2.1), – Ensure all the data collection efforts it leads disaggregate data by sex, analyze the data by gender and report the findings by sex, and – Work with other data collectors to improve coverage of gender. – This is particularly important in the areas of economic resources and on gender-based violence. – EICV Thematic Report on Gender is a good example of gender analysis and a good gender statistics publication. Session 4 will cover this topic in more detail. 6

7. Gender statistics products and dissemination in Rwanda Using data compiled under the GSF, NISR publishes periodic Gender Statistics Publications highlighting the status of gender equality in key development sectors. NISR has published a number of reports for 2012 and 2013, including: – National Gender Statistics Report – 2013 – Gender Statistics reports by district – in 2013, for Kigali City, Western, Northern, southern and Eastern provinces – Gender Statistics: the Public Sector in Rwanda, 2012 – EICV Thematic Report – Gender, 2012 – Access to Finance – Gender Statistics Publication, vol. 2, 2012 NISR also publishes short notes or press releases to disseminate the findings of its gender reports, such as: “Women make up majority among civil servants in Rwanda's healthcare industry” and “Employment rate, higher for women than men in Rwanda.” Handout 2.2 has a list of publications addressing gender from the NISR website. 7

8. Gender statistics products and dissemination in Rwanda (2) Most of the data produced by NISR are well known by potential official users – the Districts Development Plans developed in 2012 were based on the data produced from EICV-3 and DHS-4 both carried out in 2010-2011. – At national level, the baselines to produce the EDPRS-2 (coordinated by the Ministry of Finance and Economic Planning) are based on the data produced by NISR NISR website has a page on gender statistics and there is open access to most of the data, but other potential users may not know about their existence or how to use them to support policy making or advocacy. Data dissemination and use could be increased and facilitated by a gender statistics portal with links to different data sources, information about gender data collection efforts, and tools and training resources for users and producers. The gender web portal would need to be complemented with stronger and sustained producer-user communications and interaction, a communications campaign to inform and educate about the benefits and use of gender statistics; widespread distribution of short thematic reports using the data, and their use in advocacy efforts to promote greater gender equality or women’s well-being. This topic will be covered in more detail in session 6 of the workshop. 8

9. Comparing the GSF to the International Standards The GSF statistics are probably consistent with international standards since they have been extracted and compiled from reliable data sources such as censuses and surveys that follow international standards – There does not seem to be any notable departures that would affect their international comparability – However, it would be necessary to have the statistics metadata in order to compare them to international standards. (session 5) How does the list of indicators in the GSF compare with the UN Minimum Set of Gender Indicators (UNMSGI) – Handout 2.3. provides the full list of UNMSGI indicators and how they are covered by the GSF – UNSD added 6 sub-indicators to the original list of 52 for a total of 58 quantitative indicators, which are included in the handout with a letter after their number – The next slide provides a summary of the comparison 9

10. Comparing GSF to UN Minimum Set (2) UNMSGI Rwanda GSF Alternative indicatorsMissing Table 1, List of quantitative gender indicators and sub-indicators, by domain Economic structures--work, employment and time use227510 Education141103 Health and related services12804 Public life & decision making5401 Human rights of women and the girl child*5022 Total5830720 * Indicator about female genital mutilation is not applicable or relevant for Rwanda 10 The GSF does not include the 15 UN qualitative indicators and sub-indicators related to national norms (Table 2 of the UN MSGI)

11. Comparing the GSF to the International Standards (3) How does the list compare with the UN Minimum Set of Gender Indicators (UNMSGI)? – The GSF contains 30 out of 58 indicators and sub-indicators included in the UNMSGI – An additional 7 indicators could be produced based on the GSF statistics – But 20 indicators are missing and there are no data in the GSF to compute them – The main gap in coverage is in the area of economic structures followed by health. Education is the best covered area – Aligning the GSF with the UNMSGI would require mining other data sources available in Rwanda – However, covering all the UNMSGI indicators may require revising current data collection instruments or adding to them to collect additional data – The GSF is flexible and NISR is open to adding more relevant indicators to the list. 11

12. UNMSGI Indicators for which there are not data in the GSF 12 List of missing gender indicators, by domain I. Economic structures, participation in productive activities and access to resources N=10 5 Proportion of employed who are working as contributing family workers, by sex 9 Informal employment as a percentage of total non-agricultural employment, by sex 12 Proportion of adult population owning land, by sex 13 Gender gap in wages 14 Proportion of employed working part-time, by sex 15 Employment rate of persons aged 25-49 with a child under 3 living in a household and with no children living in the household, by sex 16 Proportion of children under age 3 in formal care 17 Proportion of population using the Internet, by sex 18 Proportion of population using mobile/cellular telephones, by sex 19 Access to mass media and information and communications Technology II. Education N=3 25 Share of female science, engineering, manufacturing and construction graduates at tertiary level 27 Net intake in first grade of primary education, by sex 31 Education attainment of population aged 25 and over, by sex III. Health and related services N=4 37 Smoking prevalence among persons aged 15 and over, by sex 40 Access to antiretroviral drug, by sex 41 Life expectancy at age 60, by sex 42 Adult mortality by cause and age groups IV. Public life and decision-making N=1 46 Percentage of female police officers V. Human rights of women and the girl child* N=2 relevant indicators 49 Proportion of women aged 15-49 subjected to physical or sexual violence in past 12 months by persons other than an intimate partner 51 Percentage of women aged 20-24 years old who were married or in a union before age 18 *Indicator 50 Prevalence of female genital mutilation/cutting is not relevant for Rwanda

13. NISR’s efforts and the GSF have made much progress on gender statistics in Rwanda, but there are still a few gaps or areas that could be improved by: Regularly collecting and reporting more statistics and indicators on economics and health and related services, and for all districts. Adding information about Rwanda’s gender commitments, e.g., Vision 2020, EDPRS, NGP, National Employment Policy and concerned sector policies and strategies Improving coverage of gender issues in regular data collection efforts—such as surveys or censuses—and working with other data collectors to fill the data gaps by improving collection and reporting of sex-disaggregated and gender-relevant statistics This topic will be covered in more detail in sessions 3 and 4. NISR is working to improve the quality and availability of gender statistics by: – Adding UN MSGI indicators for which there are data available – Exploring other data sources for additional indicators—e.g., the 2012 census – Collaborating with GMO to identify other relevant gender indicators to include – Dropping non-relevant indicators from the GSF Main areas or sectors for which additional data are needed 13

14. Exercise 2 1.How well does the GSF cover the main areas of gender statistics? What key areas are missing or missing indicators? What are the key gaps? 2.Based on your experience as data producer or user, what recommendations would you propose to fill the gaps not covered in the GSF? 3.What would you do--in general and in your own work-- to improve the data and statistics on gender? 14