National Statistical Systems: Principles, organization and activities

1. National Statistical Systems:Principles, organization and activities Development Data Group

2. Summary • Why official statistics? • Understanding statistical systems • Principles of official statistics • Challenges and opportunities • Building capacity Assessing Statistical Capacity and Improving Data Quality for Development

3. Part 1: Why official statistics?

4. The need for official statistics? • All countries need statistical data • To identify issues and problems • To provide a picture of the current situation • To provide the evidence for policy making • To monitor progress • Numerical data • Provide for comparisons • Can be seen to be precise and objective • Can be manipulated • Give access to powerful tools of statistical and mathematical analysis Assessing Statistical Capacity and Improving Data Quality for Development

5. Official statistics as a public good • Official statistics • Collected and published by governments • Mandate generally set out in legislation • Financed from general tax revenue • Public good • Use by one person does not affect others • Costly to produce, but easily disseminated • Value depends on quality, but difficult for users to determine this Assessing Statistical Capacity and Improving Data Quality for Development

6. Part 2: Understanding statistical systems

7. Statistical systems • Almost all countries have set up statistical systems • Part of central government • Organization varies, but even when centralized may involve several agencies • National systems have a dual role • To serve the needs of government • To provide information to the public Assessing Statistical Capacity and Improving Data Quality for Development

8. The statistical process • Statistical agencies apply data collection methods to obtain data from data providers • Data are processed, summarized and disseminated in different statistical products to users • What data to collect is a political issue • What methods to use is a technical question Assessing Statistical Capacity and Improving Data Quality for Development

9. Data providers • Data sources • Households and individuals • Business enterprises, both formal and informal • Public enterprises and service providers • Civil society organizations and other groups • Trade-off between need for data and level of intrusion and cost to providers • Important to maintain confidentiality Assessing Statistical Capacity and Improving Data Quality for Development

10. Data collection • Formal censuses and surveys • Population censuses and household surveys • Business enquiries • Administrative records and MIS • Service delivery • Economic transactions with government • Requirements of legislation • Other methods • Remote sensing • Participatory methods Assessing Statistical Capacity and Improving Data Quality for Development

11. Statistical processes and products • Statistical processes • Data validation and editing • Compilation of summary statistics • Analysis and estimation • Provision of commentary and explanation • Statistical products • Publications, abstracts, digests, reports • Electronic media, including data for further analysis • Publication through the Internet • Reports on methods Assessing Statistical Capacity and Improving Data Quality for Development

12. Data users • Government • Policy makers, planners, analysts and managers • Politicians and legislators • Markets • Domestic and international • The public • Lobbyists, CSOs, individuals etc. • The media • International community • Development agencies and donors Assessing Statistical Capacity and Improving Data Quality for Development

13. Methods and standards Review processes Coordination, Transnational advocacy, data information The international statistical system Use of data Implementation Policies, resources, Measuring development programs, projects progress - MDGs Assessment and analysis Supply of data International National data Global data frameworks Consistent Data processes international Statistical data infrastructure UN specialized Financed by: agencies, IMF, WB, Government budgets, regional agencies multilateral trust funds, and bilateral donors; Supported by technical ICP, environmental assistance and training data, etc. Assessing Statistical Capacity and Improving Data Quality for Development

14. Part 3: Principles of official statistics

15. The theory of official statistics • Users are not easily able to determine the quality of statistics • The UN have developed 10 fundamental principles of official statistics • By following these principles statistical agencies are able to demonstrate their integrity and to build trust and confidence in their products Assessing Statistical Capacity and Improving Data Quality for Development

16. Key principles of official statistics • Meet the needs of users and be made available impartially • Based on professional considerations • Information should be published on methods and procedures • Individual data should be confidential and used only for statistical purposes • Laws, regulations should be made public • Coordination and cooperation is essential • The use of international concepts, classifications and methods promotes efficiency Assessing Statistical Capacity and Improving Data Quality for Development

17. Part 4: Challenges and opportunities

18. Challenges and constraints • Many statistical systems are under stress and under-performing • Lack of demand and limited political support • Inadequate and declining real budgets and over-dependence on donor funding • Staff lack incentives and skills • Products difficult to access and use • Limited feedback from users • Ineffective coordination and management • Many systems are caught in a vicious cycle • Inadequate finance  Poor quality output  Lower demand  Low priority for scarce resources Assessing Statistical Capacity and Improving Data Quality for Development

19. Opportunities for statistics • The PRSP process • Places emphasis on countries, not projects • Generates new demands for statistics • The MDGs • Provide an agreed framework for monitoring development progress • The Monterrey consensus • Focuses on implementation and outcomes Assessing Statistical Capacity and Improving Data Quality for Development

20. Part 5: Building capacity

21. Balancing supply and demand • Capacity building requires building demand as much as improving supply • No formal market for statistics • No price mechanism to provide signals for investment • Need for mechanisms to identify and respond to new demands for data • Need for active marketing of output Assessing Statistical Capacity and Improving Data Quality for Development

22. Improving performance • Improving communications with users • Building trust in products and focusing on data quality • Making better use of existing data • Using new technology to reduce costs and improve efficiency • Improving coordination and management • Making statistical systems more transparent, responsive and accountable Assessing Statistical Capacity and Improving Data Quality for Development

23. Developing a strategy • Identify stakeholders • Broad consultation to build ownership • Assess strengths and weaknesses • Identify investment needs • Prioritize actions • Develop a time-bound plan • Monitor and evaluate progress Assessing Statistical Capacity and Improving Data Quality for Development