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Authors: Naman Keita (FAO), Nwanze Okidegbe, Sanjiva Cooke (World Bank), Tim Marchant, Consultant Presented by N. Keita,

WYE CITY GROUP MEETING ON STATISTICS ON RURAL DEVELOPMENT AND AGRICULTURE HOUSEHOLD INCOME , Rome 11-12 June 2009.

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Authors: Naman Keita (FAO), Nwanze Okidegbe, Sanjiva Cooke (World Bank), Tim Marchant, Consultant Presented by N. Keita,

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  1. WYE CITY GROUP MEETING ON STATISTICS ON RURAL DEVELOPMENT AND AGRICULTURE HOUSEHOLD INCOME , Rome 11-12 June 2009 Session 3 Topic 3Developing countries’ perspective: Selecting a core set of Indicators for Monitoring and Evaluation in Agriculture and Rural Development in Less-than-Ideal Conditions and implications for countries statistical system Authors:Naman Keita (FAO), Nwanze Okidegbe, Sanjiva Cooke (World Bank), Tim Marchant, Consultant Presented by N. Keita, Senior Statistician, FAO World Bank

  2. PRESENTATION OUTLINE • Agriculture and Rural Development Policy Issues in Developing Countries and M&E framework for tracking Results • The analytical framework • The Indicators • The data framework • Capacity of National Statistical Systems

  3. 1.ARD POLICY ISSUES AND M&E FRAMEWORK Developed countries: agriculture is less and less the economic base of rural areas. Developing countries: agricultural base of the economy with: • 40% of the workers • over 20% of their GDP • around 75% of the poor still live in rural areas and • the proportion of rural population to total population is comprised between 59.5% in less developed regions in 2000 (estimate of 56.8 % in 2005) and 74.8% in least developed countries (72.3 % in 2005) The major policy issues are related to: • sustainable agriculture and rural development and • long term improvement of the people’s living standard, particularly the rural population including food security

  4. 1.ARD POLICY ISSUES AND M&E FRAMEWORK • Sector-wide approach (SWAP) to ARD Programmes  growing demand for verifiable evidence of the results and impacts of development programs. • Most indicators are focused on performance and relate mainly to inputs and outputs (used to populate management information systems). • Results indicators have become increasingly prominent in the wake of recent international resolutions such as the Paris Declaration on Aid Effectiveness in 2005 and the Monterrey Consensus on Financing for Development in 2002. • Emphasis on aid effectiveness and results-based development  need to demonstrate the impacts of their projects and programs  shifted the focus of M&E from a concentration on inputs and outputs to a concentration on outcomes and impacts. • To measure outcomes and impacts imply the use of indicators that are based on reliable data, and on the capacity to systematically collect and analyze that information. • In most developing countries conditions are “less-than-ideal.” Information is irregular and often lacking altogether . • Strengthening capacity for M&E begins at the national and sub-national levels, where addressing the weaknesses of national statistical systems is a common priority.

  5. The ideal environment for establishing a good M&E system is where: there is a strong and consistent demand for information. the concept of "management by results" is widely practised. timely and relevant information is being systematically used to improve decision-making and to advance the process of development. systems are in place to ensure that reliable and relevant data and information are available when needed. The less-than-ideal condition, on the other hand, is where: demand for information is weak. evidence is not used to inform decision-making. the stock and flow of timely information are irregular and unreliable and statistical capacity is weak. 1. ARD POLICY ISSUES AND M&E FRAMEWORK

  6. Impact Outputs Inputs Outcomes 2. ANALYTICAL FRAMEWORK • Logframe • Tracking inputs and outputs • Public Expenditure Tracking System (PETS) and Quantitative Service Delivery Survey (QSDS) • Focus of this Sourcebook on: Measuring results (outcomes andimpact) • Early outcomes • Later outcomes Defining a core set of priority indicators for ARD programs

  7. 3. INDICATORSDifficulties with the measurement of agricultural output

  8. 3. INDICATORSFrequency of Monitoring various Indicators Medium to Long Run (maybe 5 years by the time surveys are carried out) Impact Indicators (Ultimate goal) Outcome Indicators (behavioral change) Medium Term - Ideally annually – maybe every 2 – 3 years Output Indicators (Goods and Services) Short – Medium Term - Ideally more than once a year or annually Input Indicators (Material, financial, human) Short Term - Ideally every three months or annually Issues – Cost and Capacity

  9. 3. INDICATORSWhat makes a Good Indicator? • SSPECIFIC and SENSITIVE to the changes induced as a result of actions taken • MMEASURABLE progress can be shown and is not easily manipulated • AATTAINABLE and APPLICABLE to the policy action taken • RRELEVANT to the areas in question • TTIME BOUND and TRACKABLE by showing changes over time Could also be RAVES • Reliable • Appropriate • Valid • Easy to collect • Sensitive and specific

  10. 3. INDICATORSCOUNTRY VALIDATIONS • Countries: Cambodia, Nicaragua, Nigeria, Senegal, Tanania • Purpose: Test the conceptual framework and a preliminary list of indicators against country capacity (M&E and Statistics), practice and learn lessons • Findings • All countries are engaged in strengthening and rationalising the national M&E System in parallel with Statistical reform (NSDS) • Countries are at different stages regarding M&E and statistical development (Examples of Senegal and Tanzania) • Disconnect between M&E and Statistical System • Outcome: Revised list of indicators, framework and good practices • Emerging Issues and challenges: • Decentralization and devolution=>implication for M7E and Stat system • Linkage and articulation between M&E and Statistics system • Linkages with international agencies

  11. 3. INDICATORSResults of the country validation studies

  12. 3. INDICATORS MENU of 86 indicators Arranged by:*Sub-sectors and thematic areasA. Sector-Wide Indicators for Agriculture and Rural DevelopmentB. Specific Indicators for Sub-sectors of Agriculture and Rural Development(1-Crops, 2-Livestock, 3-Fisheries and Aquaculture, 4-Forestry, 5-Rural Micro and SME Finance, 6-Agriculture Research and Extension, 7-Irrigation and Drainage, 8- Agri-Business)C. Indicators for Thematic Areas related to Agriculture and Rural Development(1-Community-based rural development, 2-Natural Resources Management, 3-Land Policy and Administration)*Early outcome and long-term indicators

  13. 3. INDICATORSNineteen priority indicators(MAIN CRITERIA USED: RELEVANCE, COMPARABILITY, AVAILABILITY)

  14. 4. DATA FRAMEWORK : Sources of data

  15. 4. DATA FRAMEWORK : TOOLSSurveys vs. non-formal appraisal methods Direct measurement Household budget survey Censuses Questionnaire (quantitative) Questionnaire (Qualitative) P.P.A CWIQ Sentinel site surveillance LSMS Structured interview Case study Purposive selection Quota sampling Small prob. sample Large prob. sample Census Beneficiary assessment Open meetings Participant observation Community Surveys Conversations Windscreen survey Subjective assessments

  16. 4. DATA FRAMEWORK • Applying the tools for M&E analysis • Comparisons over time • Baseline surveys • Panel surveys • Comparisons over space • Counterfactual comparisons (with and without) • Does the National Statistical System have the capacity to deliver?

  17. 4. DATA FRAMEWORK

  18. 5. CAPACITY OF NATIONAL STATISTICAL SYSTEMS Main problems common to many developing countries: • limited staff and capacity of the units that are responsible of for collection, compilation, analysis and dissemination of agricultural statistics; • lack of adequate technical tools, packages and framework to support countries data production efforts; • insufficient funding allocated of agricultural statistics from development partners and national budget; • lack of institutional coordination which results in the co-existence of not harmonised and integrated data sources; • lack of capacity to analyse data in a policy perspective which results in a significant waste of resources as large amounts of raw data are not properly used; • difficult access to existing data by users with no metadata and indication of quality

  19. 5. CAPACITY OF NATIONAL STATISTICAL SYSTEMSOpportunities  growing interest in the monitoring and evaluation of national development programmes=>growing interest in the rehabilitation of the NSS NSDS process Global strategy will provide: • the framework to integrate a core set of agricultural and rural statistics into the national and international statistical systems, • identify a suite of methodologies for the data collection, provide a framework for integrating agricultural and rural statistics with the overlapping data requirements of other sectors, and address the need to improve statistical capacity. • propose a governance structure for coordination not only between the national statistical organisations and other country ministries, but also between national statistical organisations of other countries, donors, and regional and international organisations. Global Strategy to be discussed by senior experts during the upcoming International Statistical Institute Satellite meeting to be held 13-14 August 2009 in Maputo, Mozambique

  20. TRACKING RESULTS IN AGRICULTURE AND RURAL DEVELOPMENT IN LESS-THAN-IDEAL CONDITIONS A Sourcebook of indicators for monitoring and evaluation World Bank

  21. Thank You!

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