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Garments And Tourism

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  • 1. Assessment of Cambodia’s 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.

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