Assessing the Capacity of Statistical Systems Development Data Group

Assessing Statistical Capacity and Improving Data Quality for Development Session 3 Slide 2 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

Assessing Statistical Capacity and Improving Data Quality for Development Session 3 Slide 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 Session 3 Slide 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 Session 3 Slide 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 Session 3 Slide 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

Part 2: Some tools and frameworks

Assessing Statistical Capacity and Improving Data Quality for Development Session 3 Slide 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 Session 3 Slide 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 Session 3 Slide 11 Structure Six dimensions of quality 0.Prerequisites of quality 1.Integrity 2.Methodological soundness 3.Accuracy and reliability 4.Serviceability 5.Accessibility Hierarchical structure Dimensions Elements –Indicators –Focal issues and key points

Assessing Statistical Capacity and Improving Data Quality for Development Session 3 Slide 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 Session 3 Slide 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 Session 3 Slide 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

Part 3: Assessing the organization and management of statistical agencies

Assessing Statistical Capacity and Improving Data Quality for Development Session 3 Slide 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 Session 3 Slide 17 Internal organization Structure Coordination Human resources Infrastructure Management systems

Assessing Statistical Capacity and Improving Data Quality for Development Session 3 Slide 18 External environment Statistical legislation and regulations Budgets Accountability and reporting Relationships with users Public image

Part 4: Indicators of statistical capacity building

Assessing Statistical Capacity and Improving Data Quality for Development Session 3 Slide 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 Session 3 Slide 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 Session 3 Slide 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 Session 3 Slide 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 Session 3 Slide 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 Session 3 Slide 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