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Assessing the Capacity of Statistical Systems

Assessing the Capacity of Statistical Systems. Development Data Group. Summary. Overview of the assessment process Some tools and frameworks Assessing organization and management Indicators of statistical capacity building. Part 1: Overview of the assessment process.

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Assessing the Capacity of Statistical Systems

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  1. Assessing the Capacity of Statistical Systems Development Data Group

  2. Summary • Overview of the assessment process • Some tools and frameworks • Assessing organization and management • Indicators of statistical capacity building Assessing Statistical Capacity and Improving Data Quality for Development

  3. Part 1: Overview of the assessment process

  4. Assessing statistical capacity • The statistical system • Inputs • Financial and human resources • Legislative and regulatory framework • Statistical and physical infrastructure • Intermediate processes • Statistical operations and procedures • Organization and management • Outputs • Statistical products and services Assessing Statistical Capacity and Improving Data Quality for Development

  5. 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 Assessing Statistical Capacity and Improving Data Quality for Development

  6. Intermediate processes • Reviewing statistical operations and procedures (DQAF and GDDS) • Appropriateness and correspondence with good practice • Communications with providers and actions to reduce data burden and protect privacy • Quality awareness and control • Assessing management and coordination • Financial management and control • Human resource management • Effectiveness of logistics Assessing Statistical Capacity and Improving Data Quality for Development

  7. Inputs • Financial and human resources • Levels and trends in recurrent and development 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 Assessing Statistical Capacity and Improving Data Quality for Development

  8. Part 2: Some tools and frameworks

  9. Data Quality Assessment Framework • Monitors the quality of economic and social data: • Quality of the statistical product • Quality of the statistical agency • Used by IMF for data part of Reports on Standards and Codes (ROSCs) • Monitors extent to which observed procedures follow good practice Assessing Statistical Capacity and Improving Data Quality for Development

  10. Coverage • General DQAF as well as separate frameworks for: • Main economic statistics frameworks: • National accounts; Balance of payments; Government finance; Money and banking; Consumer price index • Socio-demographic statistics (being prepared by World Bank) • Income poverty (completed); Education; Health; Population (in preparation) Assessing Statistical Capacity and Improving Data Quality for Development

  11. Structure • Six dimensions of quality 0.Prerequisites of quality • Integrity • Methodological soundness • Accuracy and reliability • Serviceability • Accessibility • Hierarchical structure • Dimensions • Elements • Indicators • Focal issues and key points Assessing Statistical Capacity and Improving Data Quality for Development

  12. GDDS • 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 Assessing Statistical Capacity and Improving Data Quality for Development

  13. Participation • Voluntary and involves three actions: 1.Commitment to use the GDDS as a framework for statistical development 2.Designation of a country coordinator 3. Publication of metadata, descriptions of– • current statistical production and dissemination practices • plans for short- and longer-term improvements • need for support including technical assistance Assessing Statistical Capacity and Improving Data Quality for Development

  14. Coverage • Economic and financial data – responsible agencies and main data series • Real sector • Fiscal sector • Financial sector • External sector • Socio-demographic data – responsible agencies and main data series • Population • Health • Education • Poverty Assessing Statistical Capacity and Improving Data Quality for Development

  15. Part 3: Assessing the organization and management of statistical agencies

  16. One approach • Effectiveness of a statistical system is determined by • The products it produces and the services it provides • Its functional and organizational structure • Carry out a SWOT analysis of • The internal organization • The external environment in which the system operates Assessing Statistical Capacity and Improving Data Quality for Development

  17. Internal organization • Structure • Coordination • Human resources • Infrastructure • Management systems Assessing Statistical Capacity and Improving Data Quality for Development

  18. External environment • Statistical legislation and regulations • Budgets • Accountability and reporting • Relationships with users • Public image Assessing Statistical Capacity and Improving Data Quality for Development

  19. Part 4: Indicators of statistical capacity building

  20. Assessing capacity • 16 quantitative indicators • Resources • Inputs • Statistical products • 18 qualitative indicators • Environment • Core statistical processes • Quality of statistical products Assessing Statistical Capacity and Improving Data Quality for Development

  21. The quantitative indicators • Resources • Annual budget - recurrent and development, locally and externally funded • Inputs • Data sources – censuses, surveys and administrative data • Statistical products • Media and topics covered Assessing Statistical Capacity and Improving Data Quality for Development

  22. Using quantitative indicators • Provide rough measure of extent of statistical activities • Usefulness limited by: • Lack of benchmarks • Do not measure efficiency or effectiveness • Need to be interpreted using contextual information provided by qualitative indicators Assessing Statistical Capacity and Improving Data Quality for Development

  23. Qualitative indicators • Cover a broader view of factors determining capacity • Based on DQAF Framework • Six indicators on institutional prerequisites • Two indicators on data integrity • One indicator on methodological soundness • Four indicators on accuracy and reliability • Three indicators on serviceability • Two indicators on accessibility Assessing Statistical Capacity and Improving Data Quality for Development

  24. Coverage • Legal and institutional environment • Professional and cultural setting • Methodological expertise • Adequacy of data sources • Analytical and processing capacity and quality control • Relevance of products to users needs • Effectiveness of dissemination Assessing Statistical Capacity and Improving Data Quality for Development

  25. Measurement and recording • Quantitative indicators use four point assessment scale • Level 1 – largely underdeveloped • Level 2 – developing but with observed deficiencies • Level 3 – moderately well developed • Level 4 – highly developed, in line with good practice Assessing Statistical Capacity and Improving Data Quality for Development

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