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Assessment of Cambodia’s Statistics Capacity

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. The Cambodian Context.

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Assessment of Cambodia’s Statistics Capacity

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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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