African Centre for Statistics Economic Commission for Africa

Contents Existing data collection mechanisms Coordination Data quality Data collection burden on countries Increase use of technology Data collection from Internet sources Data exchange standards Metadata Recommended data flow

Existing data collection mechanisms Common questionnaire Excel based questionnaire Focal points in NSOs Data collection missions Gaps in data presented in yearbooks Done in ad-hoc basis Resource intensive Country websites Informal Networks

Existing data collection mechanisms contd… Country websites 47 NSOs have presence on the web (88%) 34 NSOs have some form of data on the web (62%) Often PDF Not timely Lack metadata

CountryWebsite Algeriahttp:// Angolahttp:// Beninhttp:// Botswanahttp:// Burkina Fasohttp:// Burundi Cameroonhttp:// Cape Verdehttp:// Centrafricainehttp:// Tchadhttp:// Comoros Congohttp:// Côte d’Ivoirehttp:// DR Congo Djibouti finances.dj/statist.htm Egypthttp:// Guinée Equatorial Eritrea Ethiopiahttp:// Gabonhttp:// Gambia, The istics.htm Ghanahttp:// Guinéehttp:// Guinée-Bissauhttp:// Kenyahttp:// Lesothohttp:// CountryWebsite Lesothohttp:// Liberiahttp:// Libya Madagascarhttp:// Malawihttp:// Malihttp:// Mauritaniahttp:// Mauritiushttp:// Marochttp:// Mozambiquehttp:// Namibiahttp:// Nigerhttp:// Nigeriahttp:// Rwandahttp:// Sao Tomé Senegalhttp:// Seychelleshttp:// Sierra Leonehttp:// Somalia South Africahttp:// Sudanhttp://cbs.gov.sd/ Swazilandhttp:// Tanzaniahttp:// Togohttp:// Tunisiehttp:// Ugandahttp:// Zambiahttp:// Zimbabwehttp:// Southern Sudan

Existing data collection mechanisms (contd…) Informal Networks Breaks bureaucracy Fast for quick demand Not officially endorsed Ad-hoc

Data sources Member states National statistical offices Central banks Ministries and national authorities United Nations specialized agencies International Organizations IMF World Bank NGOs

Data needs Economic Trade Social Statistics Finance and Monetary Infrastructure MDGs …..

Coordination RRSF ASCC The joint African Statistical Yearbook A joint Statistical Database AfricaInfo

RRSF The Reference Regional Strategic Framework for Statistical Capacity Building in Africa (RRSF) External Stakeholders: Sub-regional organizations, regional organizations, international agencies and organizations and bilateral donors Stakeholders use nationally produced Statistics. Over the years, provided technical and financial assistance to African countries to build statistical capacity and collect various types of statistical data. Have important stake in Africa’s national statistical systems.

RRSF contd…. External Stakeholders in Africa’s National Statistical Source: RRSF document, Page 21

RRSF contd…. Recommendations of RRSF related to data: 14. Create an inter-ministerial committee of users and sectoral producers, chaired by a high-level person, that would meet regularly, and technical working groups or task forces for key sectoral areas to determine the core set of national statistics to produce 16. Identify the minimum data sets that meet the priority needs for each economic/policy sector, keeping in mind the costs of and capacities available to produce data on a sustainable basis 17. Use a balanced mix of administrative records, censuses, and sample surveys to meet the priority data needs of key data users in a timely, cost-effective and efficient manner so as to produce data of adequate quality 19. Evaluate each new data request to determine the extent to which it can be met by available administrative records without resorting to a new or expanded sample survey 20. Negotiate with the custodians of administrative information to determine how the data can be shared within the legal framework

ASCC The African Statistical Coordination Committee Following the successful design of RRSF, major regional institutions AfDB, AUC, ACBF, UNECA agreed that their respective statistical activities to be coordinated Formed ASCC in The ASCC meets annually The ASCC reports to management of respective institutions and to the Statistical Commission Africa (StatCom-Africa) Terms of reference include: Reviewing statistical programmes in Africa; Organizing joint statistical programmes; Organizing expert groups and meetings; and Publishing a joint African Statistical Yearbook.

The African Statistical Yearbook History of ASYB ASYB was an annual publication by respective organizations ASYB publications started in 1972 ECA has been publishing the ASYB on its own until 2008 African Statistical Coordination Committee Joint statistical yearbook and Joint statistical database

Member State Member States Member State REC SRO ECA Central Database Statistical Domains Regional Organizations International Organizations Sub-Regional Organizations United Nations Data Flow to ECA Central Data Store

Data collection burden on countries Without collaboration and co-ordination, countries would be continually burdened by similar data requests and the indicators Data release calendars Creation of Data-hub at NSOs Push and pull models in data provision Push Model: NSO notifies clients that data is available Pull model: Clients make data request to NSO

Increase use of technology Automatic ways of data capturing Development of country and sub-regional database Use of web which is an inexpensive means data exchange SDMX

Data collection from Internet sources Lack of standard Not regularly updated Often PDF

Data exchange standards SDMX Statistical Data and Metadata Exchange 7 institutions sponsoring ISO Recommendation Since 2001 Macro/Aggregate data DDI Data Document Initiative Microdata IHSN

Data quality Putting in place a range of quality assurance instruments in different stages of data compilation. RRSF 47. Undertake methodological research and development to enhance data quality Data validation mechanisms

Metadata Often forgotten As important as the data assisting to understand the concepts Assisting in analysis, interpretation assisting search and navigation Difficult to use data without it RRSF 6. Develop documentation on statistical standards and methodologies applied in data collection

Conclusions Overlapping of RECs and SROs All required domains are not covered by RECs Metadata Use of IT tools Lack of human resources related to statistics for coordination of statistical compilation No databases at NSO and SROs