Tackling Rural Poverty - an international perspective

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ASSESSMENT OF CURRENT STATUS OF NATIONAL
STATISTICAL SYSTEM
Prof. Ben Kiregyera NSDS Workshop, Addis Ababa,
Ethiopia 10 August 2005

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What is strategic planning about?
2. WHERE DO WE WANT TO BE? Mission/vision

• WHERE ARE WE NOW?
• Current situation

Statistical capacity
4. HOW DO WE KNOW WE HAVE ARRIVED HOW DO WE
STAY THERE? Monitoring/evaluation/ Sustainability
3. HOW DO WE GET THERE? Strategies/Actions
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ASSESSMENT OF CURRENT STATUS OF NATIONAL
STATISTICAL SYSTEMS
DIAGNOSIS
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• I. WHAT IS A NATIONAL STATISTICAL SYSTEM
  (NSS)?

Arrangements
for
production
,

n
a
d

management

u
s
e

of
statistics

NSS



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• II. WHY ASSESS THE NSS?
• a strong strategy is based on assessment of
  current
• situation (context map)
• in most cases not developing NSDS from scratch
• most countries, will exist NSS
• existing initiatives for improving national
  statistics
• (e.g. GDDS)
• been various assessments of NSSs using DQAF, etc.

Purpose of NSDS will be to build on extend
(leverage from) existing approaches
initiatives to improve existing NSS
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• III. BENCHMARK ASSESSMENT OF NSS
• 1st step in development of NSDS
• Assessment should
• be in-depth and not cursory realistic,
  objective,
• detached and critical
• be benchmarked against international standards,
  frameworks best practices
• lead to understanding of
• adequacy of outputs services
• organization, management
• infrastructure of NSS

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• Characteristics of an effective NSS
• UN Fundamental Principles of Official
  Statistics
• NSS should comply with these for public to have
• trust in official statistics
• 10 Principles
• professional independence
• relevance
• credibility
• respondent relations
• Legal framework
• fundamental pre-requisite for effective NSS
• comprehensive checklist (UN, World Bank, IMF,
• others)

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• Shared direction
• strategic goals and objectives
• Stakeholder-driven and user-focused
• national data needs
• sub-regional data needs (SADC, ECOWAS,
  COMESA)
• International data needs e.g. for MDG
  monitoring
• Versatile (able to quickly respond to changing
  demand for
• data)
• Effectively led and coordinated
• well-resourced well-structured NSO with
  technical
• expertise, organizational systems and
  capacity to lead
• and coordinate NSS

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• Assessment of NSS should lead to understanding
  of
• user requirements for statistical data
• users current and perceived future needs
• adequacy of existing statistics
• gaps in existing and planned data
• priorities for data
• capacity to use data
• availability of statistics
• sources
• availability and access - publication and
  dissemination
• policies
• linkages and coordination arrangements
  user-producer,
• producer-producer, producer-researcher/analy
  st, etc.

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Coordination and collaboration

• Why coordinate, collaborate and network?
• mutual reinforcement
• achieve synergy
• avoid working at cross-purpose and
• destructive rivalries
• avoid production of conflicting data
• Types of coordination
• inter-institutional or horizontal
  coordination
• (break the silo mentality)
• technical coordination (standardization of
• concepts, definitions, classifications,
  etc)
• donor coordination

Generally Weak
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• legal and institutional framework in which
  data are produced
• organizational aspects including
• management of NSS
• human resource policies
• strengths, weaknesses, opportunities and
  threats
• quality of statistics in terms of
• Integrity
• independence of statistical operations
  (provided in Act)
• professional and ethical standards
  (confidentiality, scientific
• objectivity, professional competencies)
• transparency about statistical processes

DQAF
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Methodological soundness sub-regional, regional
and international standards - broad
standards followed e.g. Fundamental Principles
of Official Statistics, GDDS,
International Standard Industrial
Classification - subject-specific
standards and methodologies followed
e.g. System of National Accounts, FAO
guidelines, ILO guidelines, UNESCO
guidelines, etc. Accuracy and reliability
- incompleteness data/many data gaps
- validation of administrative data
- response rates - spatial
coherence in reporting - sampling
error rates
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• Serviceability user consultation, periodicity
  of statistical outputs, timeliness of statistical
  outputs
• User consultations
• - regular and continuing or insufficient,
  ad hoc, far
• between?
• - are user needs sufficiently analyzed,
  collated and
• prioritized?
• - are there serious data gaps?
• periodicity of outputs
• - monthly, quarterly, annually
• - Income and Expenditure Survey (3-5 years)

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• Accessibility effectiveness of
  dissemination, updated metadata

• dissemination and access
• statistics have extrinsic value which lies in
  their power
• to inform processes e.g. planning,
  monitoring
• therefore, statistics have no value unless
  they
• reach those who need them
• are easily understood
• are actually used
• well-defined and forward-looking
  dissemination policy
• based on GDDS principles
• advance publication of release calendar
• simultaneous release of data principle of
• equal access to data
• providing metadata - information about the
  data
• specific statistical products to
  well-targeted users
• use different dissemination media (reports,
• electronic e.g. CDs, web site)
  e-dissemination
• Help-Desk (CBS)

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Timeliness of statistical outputs in Namibia
Statistical Output Frequency Data last collected Reporting
Bank of Namibia Financial reports Quarterly Annual Jan-March Jan-Dec June March
CBS Consumer Prices Stat. Abstract Monthly Annual May June 1998
Min. of Labour Informal Sector Stat. Bulletin 7 years Annual 2001 2004 1997
Min. of Health Health Inform. Report Annual 2003 1997

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• Main sources of data
• Administrative records (line Ministries)
• Are there Management Information Systems
  (MISs)
• Are Statistical Bulletins produced and in time?
• Are there databases
• Constraints to data development
• human capacity (understaffing, and/or limited
  technical skills, competences)
• material resources
• financial resources

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• Surveys (current data)
• household-based surveys
• Household Income Expenditure Survey
• (periodicity)
• Annual Agricultural Survey
• Labour Force Survey (periodicity)
• Demographic and Health Survey (between
• censuses)
• are these surveys coordinated/integrated?
• establishment-based surveys
• frequency of establishment surveys
• business registers
• are these surveys coordinated/integrated?
• other surveys
• Consumer Price Survey
• major constraint data disaggregation,
  sampling errors

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• how data are produced
• methods and procedures
• use of regional international standards
• constraints and problems
• how data are managed i.e. processed,
  analyzed and
• archived
• IT policies strategies
• databases and data warehouses

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Business transformation using IT
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• ICT Infrastructure
• do most institutions have adequate computers
• (numbers, right power, how old are they,
  etc)?
• are there Local Area Networks (LANs) in
  place in
• many institutions?
• are ICT resources optimally utilized?
• has ICT improved communication
• information sharing?
• status of Internet access web sites
• are there IT policies and standards in NSS?
• is GIS capability developed?
• are there databases?
• levels of IT application

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Data cycle
Planning
Stage 1
Stage 2
Implementation
Dissemination
Feedback
Stage 3
Reporting
Processing
Analysis/Interpretation
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Data versus Information
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Data, Information, Knowledge
Informed decisions
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• Main issues in data analysis and reporting
  
• data producers do basic analysis
• (generally poorly, water-is-wet types of
  analysis)
• detailed data analysis is usually not done
• no customized/targeted, value-added
• statistical products and services
• (e.g. special reports on gender,
  nutrition,
• etc)
• shortage of analytical skills at NSOs
• reporting usually poorly done
• lack of analytical skills
• lack of soft skills (communication, etc)
• inadequate partnerships with subject-matter
• specialists and analysts

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• how statistics are disseminated and used
• dissemination policies
• metadata
• data use
• current capacity of the NSS
• Demand side
• capacity to articulate requirements
• capacity to effectively use data for policy
  and
• decision-making
• Supply side
• infrastructure (physical, statistical ICT)
• human and financial resources
• dissemination policies and strategies

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• IV. METHODOLOGY
• Do document review to appreciate
• government policy environment (PRS, etc)
• sub-regional international development
• agenda (MDGs, etc)
• Review international standards and frameworks
• Other country experiences
• Interview key data users
• Government ministries, politicians,
• Public sector (e.g. Central Bank, parastatals)
• Private sector (Chamber of Commerce
• and/or Industry),
• Civil society (NGOs, news media)
• Research Training institutions (Research
• Centres, Universities)
• Donors and international organizations

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• Information from key data users
• What they do
• How they use statistics in their operations
• Availability of statistics and how they may have
• been constrained by lack of data
• Their ability to effectively use data
• Their assessment of existing data criteria
• Their relationship with main data producers
  their
• role in contributing to the development of
  the NSS
• Their current future statistical needs
  priorities
• How they think their needs can best be met within
  
• the context of the NSDS

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• how do you identify key users and collect
  data from them?
• starting point should be NSO mailing list
• divide users into main user groups
• select some manageable users from each group
• visit users, organize small group
  discussions, etc.
• having identified users and their needs,
  proceed to assess
• capacity to meet their needs using PARIS21
  Statistical
• Capacity Building Indicators (SCBIs)

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• interview key data producers mainly in NSO,
  Central Bank
• line ministries and the private sector to
  establish
• inventory of their capacities to meet user needs
• what data they produce
• how they produce data (legal and institutional
  framework, human resources, office
  infrastructure, equipment, communications and
  transport, methods and procedures, systems)
• main constraints and problems they face
• how they co-ordinate with data users and other
  data producers
• how they process, analyse, store data and
  disseminate statistical information
• existence of databases.

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• Interviews at NSO
• management
• professional staff
• administrative staff
• junior staff
• Focus/small group discussions (NSO staff and
• key stakeholders) to
• articulate an ideal profile for the NSO,
• carry out SWOT analysis
• determine resource requirements in terms of
• personnel, office infrastructure,
  equipment,
• communications and transport, and budgets
• develop a prioritized and costed work and
  capacity
• building programme
• identify technical assistance that may be
  required

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• INSTRUMENTS FOR COLLECTING INFORMATION
• Examples

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Thank You