Assessment of Cambodia

1
Assessment of Cambodias Statistics Capacity

• Prepared by Zia A. Abbasi
• IMF Multi-sector Statistics Advisor, Cambodia
• for the
• International Conference on Improving Statistics
  for Measuring Development Results June 4-5,
  2003, Washington, D.C.
• Hosted by the World Bank

2
The Cambodian Context

• A small economy with low GDP per capita
• Agriculture, garments and tourism based
• Growing workforce and underemployment
• Human Development Index 130 out of 173
• Poverty rate of 36 and poor education and
  health access and
• A small government revenue base.

3
The Statistics Environment

• Annual appropriations for statistics are
  estimated at 0.2 of budget, of which 427,000 or
  25 is allocated to the National Institute of
  Statistics (NIS)
• Lack of an effective legal and institutional
  environment
• Statistics decentralized with everything else,
  and limited coordination and integration
• Limited donor coordination and variable
  development and
• Significant statistical activities of
  non-government organizations.

4
The Demand for Development Statistics

• Economic growth and poverty reduction
• Millennium Development Goals
• National Poverty Reduction Strategy
• Macroeconomic stability and economic and finance
  reforms
• Education, health, agriculture and rural
  development priorities and
• Administrative, legal and judicial reforms.

5
Statistics Capacity Development 1993 to 2002

• General Data Dissemination System adopted
• Statistics Law and Sub-decrees drafted
• Improvements in planning, policies and
  procedures
• Improvements in coordination and organization
• Improvements in staffing and skills development
• Improvements in financing and the priority
  mission group initiative
• Increasing awareness of the need for quality and
• Increasing donor cooperation and coordination.

6
Statistics Capacity Development 1993 to 2002
(continued)

• Improvements in the range and quality of
  macroeconomic statistics
• Increased economic survey capacity and improving
  administrative collections
• Significant improvements in the range and quality
  of socio-demographic statistics and
• Increased household survey capacity and
  improvements in selected social datasets based on
  administrative data.
• Unfortunately, environment and natural statistics
  have not improved.

7
Statistics Capacity Development 1993 to 2002
(continued)

• Improvements in user access and dissemination
• A growing range of publications
• Increased use of electronic dissemination
• The NIS Website and Data Users Service Center
• An expanded and improved Statistics Yearbook and
• A draft data dissemination strategy.
• The significant role played by donors across
  government and the increasing level of
  coordination within the donor community.

8
Recent Statistics Capacity Development Initiatives

• Review of Statistics Capacity in Cambodia (July
  2002) and the Partnerships in Statistics Capacity
  Building Workshop (October 2002)
• Workshop outcomes
• Increased awareness and understanding
• Greater government commitment and
• Increased donor interest and commitment.

9
Recent Statistics Capacity Development
Initiatives (continued)

• Specific areas of interest and/or commitment
• Prerequisites of quality and statistics (I.e.
  legislation, planning, governance, coordination,
  resources and dissemination) Government, JICA,
  UK-DFID, UNDP and World Bank
• Macroeconomic statistics ADB and IMF
• Economic statistics ADB, FAO, JICA/JOCV
• Socio-demographic and poverty statistics UNDP,
  UNICEF, UNESCO, UNFPA, World Bank, GTZ, JICA, WHO
  and others.

10
Key Data Issues Prerequisites of Quality

• An integrated and appropriately financed National
  Statistical System
• Enactment and enforcement of statistics
  legislation and regulations
• Regular user consultation and the establishment
  of the Statistics Advisory Council
• Formal coordination and institutional
  arrangements, and the Statistics Coordination
  Committee
• Acceptance of the role of the NIS and leveraging
  of its data collection and processing capacity

11
Key Data Issues Prerequisites of Quality
(continued)

• A gradual increase in government appropriations
  to at least 1 of budget, and continuing and
  coordinated donor support.
• Appropriate staffing and remuneration, and an
  integrated skills development strategy, including
  regular surveys to build experience
• Appropriate facilities, computing and other
  equipment
• Progressive implementation of quality assessment
  and
• Effective planning, monitoring and evaluation of
  statistics activities and development.

12
Key Data Issues Integrity and Methodological
Soundness

• Independence of statistics and autonomy of the
  NIS and other statistics units
• Transparent statistical policies and procedures
  developed and implemented
• Improved ethical standards as part of overall
  civil service reforms and
• Progressive implementation of internationally
  accepted standards, in terms of data coverage and
  scope, concepts, definitions, classifications,
  and other standards.

13
Key Data Issues Accuracy and Reliability

• Need for regular and integrated establishment and
  household surveys, and economic censuses to
  address significant gaps in source data
• Need to establish an integrated business
  register
• Need for quality assessment and improvement of
  administrative and survey data
• Need for the assessment and improvement of
  statistical methods, processes and procedures
  and
• Strengthening intermediate and final outputs.

14
Key Data Issues Accessibility and Serviceability

• Implementation of GDDS and other standards and
  requirements (e.g. ASEAN), in relation to
  consistency, periodicity, and timeliness of data
  dissemination, and revision policy and practices
  
• Need to significantly improve data and metadata
  access (e.g. implement data dissemination
  strategy)
• Need to improve documentation and dissemination
  of metadata and
• Strengthen data user services.

15
Measuring Data Quality and Statistics Capacity

• Frameworks and other assessment tools
• GDDS Framework officially adopted and being
  implemented
• Data Quality Assessment Framework, being applied
  selectively
• PARIS21 Statistics Capacity Building Indicators
  and
• Various other assessment tools used by donors
  (e.g. UNDP in relation to MDG data requirements).

16
Conclusion - Critical Success Factors

• Greater awareness and understanding amongst
  government and the donor community
• Appropriate financing and integrated development
  (e.g. the 4 STA-TCAP concept)
• Ownership and commitment
• Champions and leaders in government
• Pragmatic, coordinated and integrated donor
  support.
• Thank you.