HLEG thematic workshop on Measurement of Well Being and Development in Africa, 12-14 November 2015, Durban, South Africa, More information at: www.oecd.org/statistics/measuring-economic-social-progress

1. By Grace Bediako
National Development Planning
Commission
Ghana
Improving Statistics for Monitoring the
Sustainable Development Goals in
Africa

2. Increasing demand for statistics
 National development plans, policies –
 situational analysis,
 monitoring and evaluation
 Millennium Development Goals (MDGs)
 8 goals, 21 targets and 60 official indicators
 Sustainable Development Goals (SDGs)
 17 goals, 169 targets, > 200 indicators
 Before MDGs
 Beijing Conference (the Forth International Women’s
Conference)
 Reported on every 5 years
 Statistical Analysis (The World’s Women) every five years
 BUT no systematic monitoring

3. Why statistics
 From this conference
 Importance of statistics
 What purposes statistics serve
 What are some of the persistent challenges with
availability of statistics and quality of data
 Issues of concepts and definitions
 Level of production of data
 Comparability, and consistency of definitions and methods
 With adoption of the sustainable development
goals (SDGs)
 Another era of global monitoring begins as the old
era of the MDGs monitoring ends
 There are lessons

4. A page from MDGs final report..

5. 5
The Beijing Platform for Action
Calls on national, regional and international statistical
institutions to:
 Ensure that statistics related to individuals are
collected, compiled, analysed and presented by
sex and age, and reflect problems, issues and
questions related to women and men in society
(para. 206 (a)).
 Response not so substantial

6. Data collection …
 Regular sources
 Censuses (population, business, agriculture, etc)
 Sample surveys (the focus of statistical offices, but
not sufficient)
 Administrative record- and register-based (not
developed)

7. Census taking in Africa
Population Census
round
Number
conducted
1985-1994 (1990) 44
1995-2004 (2000) 39
2005-2014 (2010) 50

8. Distribution of national sample surveys, by type and
period – MICS and DHS most predominant surveys
Survey type 1990-2000 2001-
2014
1990-
2014
Living Standards Measurement Survey
(LSMS)
11 14 25
Labour Force Survey (LFS) 12 43 55
Household Income and expenditure
Survey (HIES)
47 41 88
Multiple Indicator Cluster Survey (MICS) 41 61 102
Demographic and Health Survey (DHS) 59 105 164
Core Welfare Indicators Questionnaire
(CWIQ) Survey
6 34 40
All 176 298 474
Source: Compiled by the UNECA from the database of the International Household
Survey Network (IHSN)

9. Expanding survey topics…
 Other sources (yet to be mainstreamed)
 Surveys on emerging issues (time-use, gender-
based violence, entrepreneurship, assets, )
 Administrative data (crime statistics, environment,
climate, etc.)

10. What else do we learn …
 Increasing demand through the use of statistics
helps to enhance data availability in some fields
 But improvement of statistics overall requires some
deliberate actions
 Gender statistics is still not in the mainstream of
statistics production
 Sex disaggregated data not increased much, and
not presented sufficiently
 Few new major sources developed
 Continued reliance on surveys for statistics that civil
registration best suited for

11. Reporting with gender statistics in
MDGs

12. Not just any statistics
 The SDGs have under goal 17, two targets on data,
monitoring and accountability; which are:
 “By 2020, enhance capacity-building support to
developing countries, including for least developed
countries and small island developing States, to
increase significantly the availability of high-quality,
timely and reliable data disaggregated by income,
gender, age, race, ethnicity, migratory status,
disability, geographic location and other
characteristics relevant in national contexts.
 By 2030, build on existing initiatives to develop
measurements of progress on sustainable
development that complement gross domestic
product, and support statistical capacity-building in
developing countries.”

13. Change in working age population, 12 years and older, by rural/urban and
sex, 1990, 2000, and 2010 (per cent)

14. Distribution of heads of agricultural households by age group and locality
type, 2010

15. If only…

16. 16
Topical issues from the Beijing Platform
for Action
 Disaggregation of statistics by sex and age, reflecting gender issues
in all statistics about individuals (Para. 206 (a))
 Collection, compilation, analysis and presentation of gender
statistics on a regular basis (Para, 206 (b))
 Developing and testing appropriate indicators and research
methodologies,…involving women’s studies centres and research
organisations (Para. 206 (c))
 Improving data collection on various issues, including: (Para. 206 (e.
f. j))
 the full contribution of women and men to the economy, on the unremunerated
work, unemployment and underemployment in the labour market
 victims and perpetrators of all forms of violence against women
 Strengthening vital statistical systems (Para. 206 (i))
 Improving concepts and methods in …(Para. 206 (k,h))
 poverty among women and men, including their access to resources
 on the participation of women and men with disabilities, including their access to
resources.

17. 17
Promoting quality and use…
 Ensure the regular production of statistical publication
on gender that presents and interprets topical data on
women and men in a form suitable for a wide range of
non-technical users (Para. 207 (a))
 Ensure that producers and users of statistics in each
country regularly review the adequacy of official
statistical system and its coverage of gender issues,
and prepare a plan for needed improvements, where
necessary. (Para. 207 (b))
 Use more gender sensitive data in the formulation of
policy and implementation of programmes and
projects (Para. 207 (d))

18. 19
Revisiting Beijing -- Adopting a gender
perspective in statistics production
 Identification of topics that represent concerns about
gender relations, opportunities, and participation for
investigation
 Close collaboration among data producers and sustained
communication between producers and users of statistics
 Selection of statistics to be collected to highlight gender
issues in society
 Formulation of concepts and definitions that adequately
reflect the diversities of women and men in society and
capture the different aspects of their lives
 Development of data collection methods that take account
stereotypes and social and cultural factors that might
produce gender-based biases.
 Disaggregation of data by age and sex, and other
dimensions
 Development of analyses and presentation of data that
can easily reach policy makers, planners and the largest
audience possible.

19. SDGs – a pledge to leave no one
behind
Would require deliberate actions:
 Collect more relevant data
 Make disaggregated data widely available
 Systematic analysis of available data

20. 9 October 201321
Thank you