Assessing Statistical Systems

1. Assessing Statistical Systems Graham Eele – World Bank, Development Data Group

2. Overview • Why assess statistical systems? • Overview of the assessment process • Some tools and frameworks • Indicators of statistical capacity building

3. In many developing countries • Information that is needed is not available • Data that are collected are not fully analyzed or used • Limited confidence in the quality and integrity of official statistics in many countries

4. From a vicious to a virtuous cycle? Low demand Stronger demand Low resources More resources Poor output Better output • Stronger demand • MDG, poverty reduction strategies, agricultural policies • Better output • National Strategies for the Development of Statistics • More resources • Government budget, aid from development partners

5. Assessing statistical capacity • Outputs • Statistical products and services • Intermediate processes • Statistical operations and procedures • Organization and management • Inputs • Financial and human resources • Legislative and regulatory framework • Statistical and physical infrastructure

6. Looking at outputs • Assessing data quality • The Data Quality Assessment Framework (DQAF) • Data coverage and dissemination • Comparison with international frameworks and good practice • General Data Dissemination System (GDDS) • Meeting users needs • Balance between supply and demand • Anticipation of new needs and demands

7. Intermediate processes • Statistical operations and procedures • Appropriateness and correspondence with good practice • Quality awareness and control • Communications with providers and actions to protect privacy • Assessing management and coordination • Reducing the burden on respondents • Financial management and control • Human resource management • Effectiveness of logistics

8. Inputs • Financial and human resources • Levels and trends in budgets • Numbers and levels of skills/training • Legislative and regulatory framework • Compliance with fundamental principles • Statistical infrastructure • Adequacy of registers, sampling frames etc, • Physical infrastructure • Adequacy of buildings, computers and communications equipment

9. Data Quality Assessment Framework • Monitors the quality of economic and social data, covering: • Quality of the statistical product • Quality of the statistical agency • Used by IMF for data component of Reports on Standards and Codes • Six dimensions of quality 0. Prerequisites; 1. Integrity; 2. Methodological soundness; 3. Accuracy and reliability; 4. Serviceability; 5. Accessibility

10. General Data Dissemination System • Sets out objectives for data production and dissemination in four “dimensions”: • Data: coverage, periodicity, and timeliness • Quality • Integrity • Access by the public • Provides a framework for development • National authorities set their own priorities and timing to achieve their objectives • Covers economic, financial and socio-demographic data and can be extended

11. SWOT analysis • Effectiveness of a statistical system is determined by • What it produces and the services it provides • Its functional and organizational structure • Analysis, based on discussions with stakeholders, should cover • Internal organization (strengths and weaknesses) • External environment (opportunities and threats)

12. Measuring statistical capacity • World Bank’s Statistical Capacity Indicator • Provides an overall assessment of statistical capacity • Can be used to compare capacity between agencies and countries and over time • Covers three dimensions of capacity • Statistical practice • Data collection activities • Availability of specific indicators

13. Statistical capacity indicator