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.