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11 th Five-Year Plan: M&E Indicators and the Statistical Underpinnings

11 th Five-Year Plan: M&E Indicators and the Statistical Underpinnings. Wang Pingping October 2006. The Preliminary M&E Framework for the 11th Five-Year Plan: Introduction. Five Guiding Principles – “Five Balances” 20 Goals – 4 goals for each Balance 80 candidate indicators.

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11 th Five-Year Plan: M&E Indicators and the Statistical Underpinnings

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  1. 11th Five-Year Plan:M&E Indicators and the Statistical Underpinnings Wang Pingping October 2006

  2. The Preliminary M&E Framework for the 11th Five-Year Plan: Introduction • Five Guiding Principles – “Five Balances” • 20 Goals – 4 goals for each Balance • 80 candidate indicators

  3. The Preliminary M&E Framework for the 11th Five-Year Plan: A Snap Shot

  4. Selecting Indicators: from an indicator database • Economic indicators: Measuring economic performance drawing upon the national accounts, the balance of payments covering current and capital account transactions, price statistics, fiscal data and monetary and banking aggregates. • Social indicators linked to the Five Balances to reflect key policy concerns: education, health, urbanization, poverty, social security, gender, ethnic minorities etc. • Environmental and natural resource linked indicators linked to resource use (energy, land, forestry and water use,) levels of pollution and expenditures on abatement

  5. Initial Set of Candidate Indicators

  6. Assessing Data Availability for the Indicators • Periodically disseminated: 41 • Collected but not disseminated: 24 • Not collected: 7 • Inconsistent among agencies: 8

  7. Ongoing Work to Refine the Indicators • Suggestions from Brainstorm Meeting with Local Experts • Number of indicators could be reduced • Candidate indicators to be deleted: e.g., • 38. Percent of GDP in agriculture, industry and tertiary. • 67. Total fertility rate • 68. Commitment to WTO • Candidate indicators to be added: e.g., • Percent of rural women giving birth in hospital • Number of people who joined the Workers Union

  8. Input Indicators

  9. Work to Refine the Input Indicators • Suggestions from Brainstorm Meeting with Local Experts • The input indicators are very important • Nobody domestically has ever designed an input matrix at the national level • In addition to investment as % of GDP, should include as % of government revenue and so on.

  10. China’s Statistical System

  11. Assessment on Statistical System • Key Strengths: • Strong and sustained political support • Visionary NBS leadership committed to change; greater client focus and transparency. • Good infrastructure, especially in the IT area • Willing international partners, multilateral and bilateral providing technical assistance

  12. Assessment on Statistical System • Weaknesses: • Less than clear division of responsibilities between components of the statistical system • Absence of institutional mechanisms for coordination; data sharing, introduction of uniform methods and standards • Statistical infrastructure (Frames, Registers, Classifications) inadequately developed • Statistical work suffers from insufficient funding and human resources, especially the survey teams and lower-level statistical agencies • There are still relatively big data gaps, statistics on tertiary industry are incomplete, public information are not clearly categorized, insufficient data consistency.

  13. Assessment on Statistical System • Opportunities • Window of opportunity provided by the preparation of a Strategic Master Plan for statistical reforms that would permit the pursuit of institutional reforms including the definition of responsibilities of the different components of the system; • Adoption of a focused Work Program which will center on the data collection priorities linked to the goals of the 11th Five Year Plan in order to respond to the new demands;

  14. Assessment on Statistical System • Threats: • Without a full package of reforms the statistical system will be unable to deliver data outputs demanded by users and provide better statistical services for the policy making process; • Growing loss of confidence by users on statistical outputs • Increased respondent resistance

  15. Next Steps • Understand the need and requirement to data • Make formal and proper arrangement about the data collecting and dissemination at NBS and relevant agencies • Require NBS to clean and analyze the data • Strengthen statistical capacity • Set up consultant group to evaluate

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