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GOOD PRACTICES IN TECHNICAL COOPERATION FOR STATISTICS

This document provides guiding principles and criteria for good practices in technical cooperation in statistics, with a focus on partnerships, demand-led approaches, flexibility, and professional standards. It emphasizes the importance of dialogue between users and producers of statistics and highlights the policy considerations necessary to support the development of national statistical systems.

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GOOD PRACTICES IN TECHNICAL COOPERATION FOR STATISTICS

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  1. GOOD PRACTICES IN TECHNICAL COOPERATION FOR STATISTICS Paris 21 Meeting Paris, France, June 2000

  2. UN Statistical Commission, 30th session, March 1999 • Some guiding principles for good practices in technical cooperation in statistics • Two workshops on Improving Technical Cooperation in Statistics were held in The Netherlands, to discuss the need for and content and structure of the document • Principal authors: Tony Williams (UK) and Ronald Luttikhuizen (The Netherlands)

  3. What is technical cooperation in statistics? • The exchange and development of know-how and technical expertise in order to build capacities to produce and use statistics • Wide range of activities: from informal contacts in international working groups and meetings to in-depth programs to improve statistics • One central condition: partnership, sharing common goals

  4. Purpose of the Guiding Principles • To help partners in the technical cooperation process to create their own models, but based on acknowledged successful practices • To encourage countries to make optimal use of statistics and commit themselves to improving the national statistical system

  5. Criteria for good practice (1) • Technical cooperation in statistics should: • Be demand-led, based on user requirements and relative priorities • Set within a well-balanced overall strategic framework • Consider human and other resource development strategies

  6. Criteria for good practice (2) • Technical cooperation in statistics should: • Consider organizational and institutional development, in addition to technical work areas • Be flexible and take account of local situations, culture, policy environment and stage of statistical development

  7. Criteria for good practice (3) • Technical cooperation in statistics should: • Complement national resources, while empowering national statistical systems and governments to take the lead • Address the needs of regional groupings of countries where a common approach can be effective, supporting cooperation between or within regional groupings

  8. Criteria for good practice (4) • Technical cooperation in statistics should: • Recognize heterogeneity of countries • Be well designed, by using logical framework approaches and specifying objectives and success criteria in advance • Promote full participation and address the concerns of all main stakeholders

  9. Criteria for good practice (5) • Technical cooperation in statistics should: • Be implemented according to professional standards, using the most appropriate model of cooperation • Integrate staff training in a way that optimizes its effect on objectives of the project

  10. Criteria for good practice (6) • Technical cooperation in statistics should: • Use appropriate monitoring and evaluating mechanisms, exchange of experience, lesson learning • Be coordinated between donors and the different national players to avoid duplication, encourage complementarity and synergy

  11. Criteria for good practice (7) • Technical cooperation in statistics should, finally: • RECOGNIZE THAT DEVELOPING A STATISTICAL SYSTEM CAN TAKE A LONG TIME

  12. General policy considerations (1) • Some general policy considerations are relevant to the consideration of technical cooperation in statistics: • Role of statistics at the national level • Define statistical needs precisely and explicitly • Dialogue between users and producers

  13. General policy considerations (2) • Importance of statistics must be recognized by national authorities, by supporting: • Proper legal and institutional setting • Adequate and motivated staff • Accommodation, equipment and software • Commitment to good management practices • Awareness of Fundamental Principles of official statistics

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