Assessing Statistical Systems
Graham Eele – World Bank,
Development Data Group
Overview
• Why assess statistical systems?
• Overview of the assessment process
• Some tools and frameworks
• Indicators of statistical capacity building
Slide 2
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
From a vicious to a virtuous cycle?
Low
demand
Stronger
demand
Low
resources
Poor
output
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
Slide 4
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
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
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
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
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
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
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
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
Slide 12
Statistical capacity indicator
2008 Statistical Capacity Indicator
(on a scale of 0-100)
Indicator
Mozambique
All
Countries
Overall
Statistical
Practice
64
40
65
56
Data
Collection
80
62
Indicator
Availability
73
77
Slide 13