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 Slide 2

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 Slide 3

4. From a vicious to a virtuous cycle? Slide 4 Low demand Low resources Poor output Stronger demand More resources 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 Slide 5

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 Slide 6

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 Slide 7

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 Slide 8

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 Slide 9

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 Slide 10

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) Slide 11

12. Measuring statistical capacity Slide 12 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 Slide 13 2008 Statistical Capacity Indicator (on a scale of 0-100) IndicatorMozambiqueAll Countries Overall6465 Statistical Practice 4056 Data Collection 8062 Indicator Availability 7377