Assessment of Country Capacity to produce Agriculture Statistics. Mukesh K Srivastava FAO Statistics Division

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Transcription:

Assessment of Country Capacity to produce Agriculture Statistics Mukesh K Srivastava FAO Statistics Division

Outline Work done so far and the road ahead The normative work Concepts of Quality and Capacity Experience of Country Assessments in Asia

Country Assessment: Inception AFCAS/APCAS Country reports (later standard questionnaire) for monitoring progress in agriculture statistics ICAS-V: Kampala, October 2010 Resource partners and key stake holders of the Global Strategy felt the need for a global standard tool for Baseline information Monitoring of progress in building country capacity A core group of experts from FAO, USDA, ABS (expanded to include AfDB, UNECA, ADB, Brazil, Russia) Selection of Pilot Countries (ranking/grouping of countries)

Initial thoughts We need a framework Take into account the work already done Be in line with Global wave of thoughts DQAFs from IMF, WB and UNESCO; EUROSTAT and country frameworks were studied They differed only by shades Similar dimensions and elements of the statistical system were being addressed Focused different aspects of the same issue BUT none addresses issues relted to Agriculture Statistics System specifically

Quality in Official Statistics A review reveals that the quality does not have the same meaning across the Globe, though there is broad consensus on its importance and key characteristics. Distinguish between: Quality of Data Quality of Survey Quality of Statistical system of a Country (Country Assessments of Global Strategy) Quality of Data base National Quality Assessment Frameworks http://unstats.un.org/unsd/dnss/qualitynqaf/nqaf.aspx

Concepts: Scope of quality Product Characteristics Process (computerized eye testing) Inputs Mozzarella di Buffala Vino di Toscana Champagne of specific region of France Formal statements of quality need a framework an agreed set of characteristics/variables on which information is to be provided for comparison Total Quality Management: INPUT- THROUGHPUT- OUTPUT

Capacity vs. Quality Quality is more and ex-post concepts; relates more to some thing that exists Capacity: Ex-ante Inherent to the system (institution, people, capability...) The focus of CAQ is to gauge the Country Capacity to produce Agriculture Statistics, covering a wide range of dimensions and elements.

Country Assessment Questionnaire Wide definition of Agriculture Statistics: Crop, Livestock, Fish, Forests, Rural Development, Agro-processing Industry Scope of assessment has to cover NSO, MOA and other relevant line ministries. Initial Assessment for building generic Indicators on Country Capacity Diagnostics Grouping, ranking, prioritizing countries General panorama of situation in the regions

FAO proposal on Measuring Country Capacity Capacity Indicator I: PREREQUISITES: Institutional Infrastructure Capacity Indicator II: INPUT: Resources Capacity Indicator III: THROUGHPUT: Statistical Methods and Practices Capacity Indicator IV: OUTPUT: Availability of Statistical Information Correspondence with global standards

PREREQUISITES: Institutional Infrastructure Legal framework Coordination in Statistical System Strategic Vision and Planning Integration of Agriculture in the National Statistical System Relevance (user interface)

INPUT: Resources (still debating) Financial Resources Total budget for statistical activities, as percentage of GDP_ broken down by different ministries, departments, NSO Share of agriculture statistics in NSO Budget Share of Statistics in the budget of Ministry of Agriculture Budget of Ministry of Agriculture as percentage of GDP from Agriculture Additional Data needed: GDP, GDP from Agriculture Human Resources Share of agriculture statistics in NSO person years There are issues relating to availability of data and comparability of indicators Perhaps, these indicators can be captured better in Indepth assessments, to capture specificity of countries

THROUGHPUT: Statistical Methods and Practices Statistical software capability Data capture technology IT infrastructure International Classifications General Statistical Activities Agricultural Market and Price Information Agricultural surveys Analysis and use of data

OUTPUT: Availability of Statistical Information Core data availability Timeliness Quality, reliability and consistency of data Data Accessibility Quality Consciousness

Experience in Asia Very diverse set of 59 countries from FAO/ESCAP/ADB SARC, ASEAN, CIS and central Asia, Pacific countries Objective: Preliminary assessments of the capacity of national statistical systems and Identification of countries for in-depth assessments Development of technical assistance, training and research strategies The CAQ was planned to be filled by Internet using Survey Monkey Excel workbook by E-mail No Training (no funds) Limited Pilot testing

Experience in Asia: +ve feedback Returned questionnaires were processed to build Country Capacity Indicators The proposed Normative Framework for assessing Country Capacity was appreciated and broadly accepted by the Regional Steering Group as monitoring tool for GS for preparation of Implementation Plan Capacity Indicators were validated: Meaningful conclusion were possible based upon available data Enough discriminating capacity of the indicators Strong agreement with WB capacity indicators on specific dimensions Indicators showed weak areas in the region where intervention is needed.

Experience in Asia: Challenges Only 50% countries returned by the due date (response rate=42/59) Incomplete response and Non-response: Follow-up lead to improvements Lack of coordination at country level Conflicting information from different agencies No adherence to a single reference date Contradictory responses Responses from only one agency Misunderstanding of English Interpretation of blanks Agency staff assignments (transfers, recruits) Coverage of crops, livestock, fisheries, forestry The quality of response received through mailed questionnaire hampered building some indicators for some countries

Alternative Rating Criteria Given in GS Document (availability of core data based) Giving more weight to 15 core data relted to Food Security Based upon Capacity Indicators: Neutral 18 indicators on 3 dimensions Average of four criteria More acceptable Visible Outliers eliminated

Table 4. Composite (Average of Rating for 3 Methods) Excellent Above Below Limited Average Average Average Iran Armenia Bangladesh Cambodia Afghanistan Japan Australia Bhutan Cook Islands Micronesia Mongolia Azerbaijan Fiji Kazakhstan Nauru Philippines Hong Kong, Georgia China Lao PDR Pakistan India Indonesia Macao, China Timor Leste Malaysia Maldives Myanmar New Zealand Nepal Taiwan, Republic of China Korea Philippines Samoa Thailand Turkmenistan Viet Nam Niue Sri Lanka

0 20 40 60 80 100 Similarity of Capacity Indicators Cap 1_Inputs Cap 3_Throughputs Cap 4_Outputs

0 20 40 60 80 100 Relationship between Inputs Cap 1_inputs Integration Legal frmwk Relevance

0 20 40 60 80 100 Relationship between Throughputs Cap 3_throughputs IT infra Gen stats activities Agr stats act: agric Stats software cap Int'l classification Agr stats act: prices Analysis & use

0 20 40 60 80 100 Relationship between Outputs Cap 4_ outputs Timeliness Accessibility Core data availability Quality, reliability consistency Quality consciousness

Constraints on Agricultural Sector Statistics Constraints: 1=None; 2=Little; 3=Relative ; 4=Significant; 5=Dominant Technical skills of the available statistical staff 2.96 Transport equipment for field activities 2.96 Turnover of professional staff. 2.88 Funds for field-oriented statistical activities vis-à-vis plans. 2.84 Up-to-date information technology software 2.81 Number of field workers for statistical activities 2.76 Up-to-date information hardware 2.73 Number of professional staff at headquarters for statistical activities 2.69 Number of professional staff in the field for statistical activities 2.68 Sound methodology implemented for agricultural surveys 2.54 Building space for office 2.52 Appreciation at the policy-making level for importance of statistical activities 2.38 Level of demand for statistics 2.35 Support at political level in the Government for statistical activities 2.35 Number of support staff at headquarters for statistical activities 2.31 Ave.

Conclusion and Road Ahead Appeal to countries Pay due attention to filling the questionnaire Clarify doubts here Quality of response is more important than the deadline Global Partners and individual experts Work together, as in the past, to establish a common global monitoring system for agriculture statistics Participate in the normative works Country Profiles In-depth assessments: Guidelines under preparation

Thank you very much for your attention!