Statistical Requirements for National Development Strategies

1. Regional Meeting of Heads of Statistics and Planning:Statistics 2020 – Developing sustainable national and regional statistical capacitiesSession 3.4: User and Policy Dimension‘Statistical Requirements for National Development Strategies’Wednesday 14 July 2010 David Smith Deputy Head and Senior Economist UN-ESCAP Pacific Office, Suva, Fiji

2. Planners demand for statistics • For national plan preparation and monitoring • Macro-economic forecasting and framework for budget • For sector plan preparation and monitoring including SWAps • For policy development e.g. on key cross-sectoral issues such as gender, youth • For reporting on international commitments such as MDG progress, Pacific Plan, Cairns Compact.

3. Data sources for planners • National statistical offices • Line ministries and departments • Central bank • Ad hoc studies by consultants/academics • Aid donor reports.

4. Statistics for National Development Plans • Preparation of the national plan • Short burst of heavy demand • Mid term review of the plan • Shorter burst • Monitoring the plan implementation – steady demand over time • Quarterly • Annually • Periodically.

5. Data requirements and Principles of national planning • Data requirements flow from structure of the national plan • Usually based on strategic planning principles • Typically it follows a hierarchy as follows……

6. Strategic plan hierarchy Vision/Goals statement Guiding Principles Situation analysis Key issues/problems Key policy areas / Sectors Policy objective 1 Policy objective 2 Policy objective 2 Policy objective 3 Policy objective 3 Strategy 1.1 Strategy 1.2 Strategy 1.3 Strategy 2.1 Strategy 2.2 Strategy 2.3 Actions Actions Actions Actions Actions Actions

7. Evidence based policy…….. • Strategic plan hierarchy: policy objectives are based on the ‘evidence’ provided by the situation analysis. • But this requires skills in data analysis, interpretation of causes and effects, identification of key issues, developing policies to correctly address those issues. • These ‘policy development’ skills need building in most PICs. • Using ‘evidence’ to make policy can minimise influence of other criteria, e.g.*: • Power and influence of sectional interests • Corruption • Political ideology • Arbitrariness • Anecdote. * Scott C., “Measuring up to the Problem”, Paris 21, Jan 2005

8. Hierarchy of Plans and Policies: National Strategic Development Plan, Vision, Strategy (can contain Development Goals, situation analysis, medium term strategic policy objectives) Sector Plans (often included in national plan) (Policy objectives and strategies for the various sectors of the economy e.g. youth employment, education policy) Corporate plans(Ministry operational plans) (Policy objectives and strategies of sector ministries which may be different from sectors above) Budgetary and donor allocations (recurrent budget, development/capital budget, aid resources) Development outputs and outcomes (Activities, projects, programmes of government, NGOs, donors, communities)

9. Data requirements: national plan Situation Analysis • Economic data: • GDP trends including sector trends. • Employment including the informal sector. • Wages/income. • Population trends, including GDP per capita • Expenditure breakdown of aggregate demand, especially to show consumption and investment (including FDI) trends. • Trade and the balance of payments – exports and imports including breakdown by principal products. • Fiscal trends – revenue, expenditure, deficit and debt • Monetary: Money supply, Foreign exchange reserves, Inflation, exchange rate movements, interest rates.

10. Data requirements: national plan Situation Analysis 2 • Social data: • Quality of life measures such as the UN’s Human Development Index. • Poverty and income levels. • Access to basic infrastructure such as water and sanitation and telecommunications, and financial services. • Health data – disease prevalence as well as input data such as doctor and nurse to population ratios. • Education – access by geographical area, pass rates, completion rates. • Statistics on disadvantaged groups such as youth, women, squatters. • Urban rural trends and their implications for urban services such as water and sanitation access.

11. Data requirements: national plan Situation Analysis 3 • Environmental (from MDGs): • Proportion of land area covered by forest • CO2 emissions, total, per capita and per $1 GDP (PPP) • Consumption of ozone-depleting substances • Proportion of fish stocks within safe biological limits • Proportion of total water resources used • Proportion of terrestrial and marine areas protected • Proportion of species threatened with extinction • Proportion of population using an improved drinking water source • Proportion of population using an improved sanitation facility • Proportion of urban population living in slums.

12. Data requirements: Policy objectives • Well specified policy objectives should be SMART: • Specific - Objectives should specify what you want to achieve. • Measurable - you should be able to measure whether you are meeting the objective or not. • Achievable - are the objectives you set, achievable and attainable? • Realistic - Can you realistically achieve the objectives with the resources you have? • Time-bound - When do you want to achieve the set objectives?

13. SMART objectives: examples • Objective: To improve access to primary education; • Strategy 1: accelerate the class room building programme focusing on under-served rural areas • Indicator/target 1: number of new class rooms completed per annum from 15 to 25 by 2011. [Data from Ministry] • Indicator/target 2: net enrolment rate for primary school from 70% to 85% by 2011. [Data from Ministry and NSO].

14. Monitoring the national plan – and national development • If plan objectives are SMART, then indicators already well specified. • But, monitoring efforts hampered when: • Indicators are vague; • Many other factors contribute to changes in the indicator – poor choice of indicator; • data is only available infrequently; • Monitoring the indicators requires expensive surveys.

15. Monitoring the national plan – and national development 2 • Trend towards more rigorous monitoring emphasising outcome indicators. • Monitoring systems present in most PICs: • Mid term reviews of national plans; • End of term reviews of national plans; • Regular monitoring of finance, personnel, projects, aid donor programmes, cabinet decisions.

16. Types of monitoring indicators • Input - financial, physical and human resources applied to a budget program or project that supports the plan implementation. • Process – used to assess the content and quality of activities, procedures, methods, and interventions specified in the plan. • Output – delivery of goods or services to target populations. • Outcome/Impact – how the targeted population has benefited in terms of better education or health outcomes or higher incomes, better diet etc..

17. Data availability • NSOs provide outcome/impact data: • Key question is how plans have affected household incomes/opportunities; • But pop censuses and household surveys are infrequent; • Therefore hard to gauge progress except over the longer term; • Leads to frustrated planners and politicians! • Other indicators largely collected through internal government systems.

18. Example from Vanuatu • M&E policy recently developed: • Major projects – quarterly (input, process) • Cabinet decisions – 6 monthly (process) • PAA (national development plan) - annually through an Annual Development Report (outcome/impact) • Problems encountered with PAA monitoring: • Vague indicators, cause and effect not clear • Deciding a baseline and target and specific data needed • Database establishment and maintenance.

19. Increasing demand for monitoring:national governments • Public sector reforms – doing more with less • Employment contracts • Performance targets • Financial management reforms • More responsible fiscal outcomes • Focus on outputs and outcomes.

20. Increasing demand for monitoring:development partners • Managing for Development Results or Results Based Management. • Sector Wide Approaches – SWAps. • Aid effectiveness declarations/agendas. • Cairns Compact. • MDGs have highlighted the importance of monitoring outcomes at a country level. Raises demand for statistics and therefore for building NSO capacity.

21. Future demand? • More household data • Better employment figures • Geographical breakdown of all data • Environmental data • Regular administrative data, and • More timely and accurate data!!

22. Planners and statistics • Involve national and sector planners in NSO planning, especially in NStDSs. • Planners need to improve skills in evidence-based policy development: • Data analysis • Interpretation of data • Presentation of data – ‘visualisation’.

23. Vinaka