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WORKING DRAFT 24 April 2012

GUIDELINES ON COMPILING

COUNTRY CAPACITY INDICATORS TO PRODUCE AGRICULTURAL STATISTICS

1.Introduction …………..To be written………………………..

Global Strategy needs For monitoring progress over time Mix of objective and subjective: self assessment Ready tool for ranking countries Responses to be validated through in-depth assessments , leading to more precise

indicators. On some indicators (resources) information in sufficient through self-reporting

responses; supplementary information needed from addition published sources.

2. Structure of Indicators …….. To come ……………………………..

Dimensions measured Elements

Capacity Indicator I

Institutional Infrastructure (PREREQUISITES)

1.1 Legal framework

1.2 Coordination in Statistical System

1.3 Strategic Vision and Planning

1.4 Integration of Agriculture in the National Statistical System

1.5 Relevance (user interface)

Capacity Indicator II Resources (INPUT DIMESNION)

2.1 Financial Resources2.2 Human Resources

Capacity Indicator III

Statistical Methods and Practices

(THROUGHPUT DIMENSION)

3.1 Statistical software capability

3.2 Data capture technology

3.3 IT infrastructure

3.4 International Classifications

3.5 General Statistical Activities

3.6 Agricultural Market and Price Information

3.7 Agricultural surveys

3.8 Analysis and use of data

Capacity Indicator IV

Availability of Statistical Information

(OUTPUT DIMENSION)

4.1 Core data availability

4.2 Timeliness

4.3 Quality, reliability and consistency of data

4.4 Data Accessibility

4.5 Quality Consciousness

3. Indicator qualities and correspondence with other similar indicators

…..to be written……

Robust: capture ranking SMART Cover the entire production line: infrastructure to output, follow on TQM

concepts In line with other existing frameworks Based on self-reporting questionnaire: could be easily repeated over time

without much investment and costs

4. Indicator definitions, relevant questions and the scoring criteria Capacity indicator I: Institutional Infrastructure

A number of pre-conditions are needed for smooth and efficient functioning of any system. All public stsstitical activities need a legal authority to undertake the operations of field data collection. The legal frame work for statistical operations in country also defines ”who is responsible for doing what?”. It is not uncommon to see that a number of agencies are involved in collection of statistics on a sectors. Thus there is a need for coordination of national efforts with a view to reducing not only the cost, effort and response burden but also to avoid duplicate and inconsistent statistics. Integration of agriculture statistics in the national statistical system provides greater scope of analysis of data. Mechanisms to maintain channels of communication between data producers and data users ensures that data collected by the stsstitical systems remains relevant to the needs of policy making.

This indicator provides a summary of measurements on the five main elements of the dimension relating to intuitional infrastructure as defined below. The overall score on this indicator is taken as the Geometric mean of the scores on the five indicators which measure the five elements of this dimension of the quality of the agriculture statistical system. Geometric mean (GM) has been chosen specifically to highlight the weakness in the system. In calculation of the GM equal weight is assigned to the score on each of the elements.

1.1 Legal frameworkThe legal framework and enabling legislation is a fundamental prerequisite of any statistical systems. The legal framework defines the mandate of the statistical agency, its reporting relationship to government, responsibilities, the use and application of sound statistical practices, legal authority for collecting data and conduct surveys, and most importantly the legislative authority to protect the confidentiality of individually identifiable information collected for statistical purposes.

Relevant Questions1.2.1 Is there a legal or statutory basis for statistical activities in the country in general?If “Yes” to 1.2.1, Is it operational?1.2.2 Does there exist a legal basis for collection of agricultural statistics?12.2a If “Yes” to 1.2.2, how adequate is the legal framework for agriculture statistics?Please answer with a code. (1) Fully (2) Workable (3) Somewhat adequate (4) Somewhat inadequate (5) Totally inadequate

Scoring criteriaMax. Score=5 marks

If. 1.2.1 Yes 1 markNo 0 marks

Operational Yes 1 markNo 0 marks


If 1.2.2a Fully adequate 2 marksWorkable 2 marksSomewhat adequate 1 markSomewhat inadequate 0 marksTotally inadequate (inapplicable)

0 marks

Indicator = (Country Score/ Maximum Marks) x 100

1.2 Coordination in Statistical SystemMost countries require a statistical coordinating authority because multiple governmental organizations are often involved in the collection of data on agriculture, forestry, and fisheries. A coordination mechanism also ensures that the various data producers adhere to a common set of standards. Compliance with the standards established by the coordinating authority prevents duplication of efforts as well as the publication of conflicting data from different reporting agencies. The coordination mechanisms also provide a common forum for securing resources for the agriculture statistics system and the governance it provides enables the ministries and agencies involved in the collection of agricultural data to integrate agriculture into the preparation of national strategies for the development of statistics.

Relevant Questions1.2.3 Does there exist an active National Statistics Council, Board or Committee? (Tick if Yes)1.2.4 If ’’Yes’’ to 1.2.3, does the mandate of the National Statistics Council, Board or Committee cover:1.2.4.a Crop and livestock statistics?1.2.4.b Forestry and environment statistics?1.2.4.c Aquaculture and fishery statistics?1.2.4.d Water resource statistics?1.2.4 e Rural development statistics?

Scoring criteriaMax. Score= 5 marks

If. 1.2.3 Yes No MarkNo 0 marks

If. 1.2.4 Yes (all) 5 marks1.2.4 a Crop and livestock statistics? 1 mark1.2.4.b Forestry and environment

statistics?1 mark

1.2.4.c Aquaculture and fishery statistics? 1 mark1.2.4.d Water resource statistics? 1 mark1.2.4.e Rural development statistics? 1 mark


1.3 Strategic Vision and PlanningStatistical offices exist in order to provide current statistical information. But long-run sustainability and growth of their activities depends, first and foremost, on their ability to evolve and adapt to the socio-economic developments in the country, new and emerging government priorities, and annual government budget allocations.

A strategic vision and planning system is essential for bringing together the relevant external signals (including budget parameters) and the proposed internal responses to them. While a strategy sets the direction and path of development, selected on the basis of conscious choices made under a give set of constraints, a plan is needed to implement the strategy in a phases manner so that the overall objectives are achieved. Size of the plan may be adjusted depending upon the resource availability on year-to- year basis but a strategy remains fairly stable over its life time.

The strategy should include the identification of priority areas for development and investment, and areas to be de-emphasized, as well as procedural guidance on for example how large an efficiency gain is expected from each area, how large a slice of the program must be identified as having relatively lower priority, what are the investments needed in order to realize the efficiencies.

Strategic vision should be addressing a long list of issues that include the development of national strategies for statistics and where such strategies are in place, review them to determine where

revisions are needed. It also includes building a network of statisticians and supporting staff including data collectors. The education of staff on statistical methodology for sampling, survey design, data compilation, and data analysis is another key component as is the implementation of an integrated survey framework, and data management system. The acquisition and replacement programs for vehicles, computers, software, and other technical equipment is another strategic issue as is the need to develop a vision for disseminating data and responding to requests.

The strategic vision should also include an effective means of avoiding duplication of effort, of profiting from potential synergies and of benefiting from available infrastructure.

Relevant Questions1.4.6 Does there exist any national Strategy/Plan/Programme specific to agriculture sector?1.4.7 If ‘’Yes‘’ to 1.4.6, is agriculture sector strategy integrated into the NSDS?1.4.8 If ‘’No’’ to 1.4.6, is its design in process or intended?Use Codes: 1=Under development ; 2=Planned; 3=Not planned

Scoring criteriaMax. Score= 6 marks

If. 1.4.6 Yes 3 marksNo 0 marks

If 1.4.7 Yes 3 marksNo 0 marks

If 1.4.8 Under development 2 marksPlanned 1 markNot planned 0 marks

Indicator = (Country Score/ Maximum Score) x 100

1.4 Integration of Agriculture in the National Statistical SystemThe governance of statistical capacity and its development across various ministries and agencies collecting and publishing agriculture statistics are critical to any successful integration initiative. In most countries statistical responsibilities are decentralized and ministries of agriculture produce the agriculture statistics. There does not, however, appear to be any advantage between centralized and decentralized statistical systems. National Statistical Offices have experience applying statistical methods and using sample frames, experience that line ministries often lack. Line ministries are, however, likely to have greater technical knowledge about agriculture, forestry, fisheries, and land use and perhaps field staff to undertake frequent statistical activities.

The integration of agricultural statistics into a country’s national statistical system does not mean that all responsibilities fall on the national statistical office, the ministry of agriculture, or any other agency in particular. It does, however, mean that the organizations with overlapping data needs accept a common vision, concepts, and definitions, a master sample frame, an integrated survey framework, and database principles. Integrating agriculture into the national system changes the focus of statistical capacity building. This capacity building would focus on strategies and actions to integrate agricultural statistics into the national statistical system making agriculture a key element of the national strategies for the development of statistics.

Relevant Questions1.4.1 Does the country have a National Strategy, Plan or Programme for the development of statistics (e.g. National Strategy for Development of Statistics (NSDS) or National Action/Master Plan)?1.4.5 If “Yes” to 1.4.1, does the strategy include programme of work for the sub-sector relating to: (Tick the relevant one)

1.4.5.a Crop and livestock statistics1.4.5.b Fishery and aquaculture statistics1.4.5.c Forestry and environment statistics1.4.5.d Water resources1.4.5.e Rural development1.4.6 Does there exist any national Strategy/Plan/Programme specific to agriculture sector?1.4.7 If ‘’Yes‘’ to 1.4.6, is agriculture sector strategy integrated into the NSDS?3.1.5 Were the questions on the participation in agricultural or related activities of the household (agricultural holding) included in the questionnaire used in the last population census?3.5.1.6 The last agricultural census covered: (Tick the appropriate row from the list below, as applicable )CropsLivestockAquacultureFisheryForestry related to agricultureWater related to agricultureOther income generating activities in rural area3.5.1.7.a The Agricultural Census used the cartographic material and administrative boundaries used for the population census? 3.5.1.7.b Few questions to collect information on participation of household in agriculture sector were included in the population census, to get sampling frame for agricultural census or a detailed module?

Scoring criteria

No 0 marksIf 1.4.7 Yes 1 mark


No 0 marksIf 3.5.1.6 If it covered any of the fishery, aquaculture,

forestry, water , rural activities domains1 mark

If it covered only crops and livestock. 0 marksIf 3.5.1.7a Yes 1 mark

No 0 marks If 3.5.1.7 b Yes 1 mark

No 0 marksIndicator = (Country Score/ Maximum Score) x 100

Please note that the scoring criteria give greater credit to statistical programs with a wide coverage of subsectors within the statistical planning process.

1.5 Relevance (User interface)The relevance of statistical information reflects the degree to which it meets the real needs of clients. It is concerned with whether the available information sheds light on the issues of most importance to users. Assessing relevance is a subjective matter dependent upon the varying needs of users. The challenge is to weigh and balance the conflicting needs of current and potential users to produce a program that goes as far as possible in satisfying the most important needs within given resource constraints.

Relevant Questions1.5.1 Does there exist an official forum for dialogue between suppliers and users of agricultural statistics (also including water, environment, forestry, fisheries, and rural development) in the country?

1.5.2 If ‘’Yes’’ to 1.5.1, are regular meetings of such a forum held?1.5.3 If ‘’No’’ to 1.5.1, is there at least an informal forum for dialogue between producers and users of agricultural statistics?1.5.4 Are there well established channels for receiving feedback from users of agricultural statistics (web contact, e-mails, etc.)?1.5.5 If “Yes” to 1.5.1, 1.5.3 or 1.5.4, what is your assessment of the level of dialogue between users and producers. Use Codes: 1= Extensive; 2= Adequate; 3=Moderate; 4=Somewhat; 5=Inadequate1.5.6 If ‘’Yes’’ to 1.5.1 or 1.5.3, please indicate which of the following are represented in the forum (formal or informal)?1.5.6.a Planning bodies (Ministry of Planning or National Planning Commission)1.5.6.b Ministry of Finance/Treasury1.5.6.c Line ministries and departments (like Water Resources, Environment, Forestry, Fisheries)1.5.6.d Central Bank1.5.6.e Representatives of academic and research community1.5.6.f Chamber of commerce1.5.6.g Media1.5.6.h Representatives of socio- professional bodies1.5.6.i Private sector representatives1.5.6.j Development partners (Donors, NGO’s, etc.)1.5.6.k Other, specify



If 1.5.2 Yes 1 markNo 0 marks



If 1.5.5 Extensive/ Adequate 2 marksModerate/ Somewhat 1 markInadequate 0 marks

If 1.5.6 Give one mark to Yes to anyone in the cluster below.Planning bodies,,Ministry of Finance/Treasury/ Central Bank 1 markLine ministries and departments 1 markRepresentatives of academic and research community/ Representatives of socio- professional bodies

1 mark

Media/Chamber of commerce 1 markPrivate sector representatives Development partners (Donors, NGO’s, etc.)

1 mark


Capacity Indicator II: Resources

This indicator is critical to show whether country has adequate resources to undertake the statistical activities. The two most important resources needed for undertaking statistical activities involving field data collection are existence of qualified permanent manpower to plan and lead the execution of activities and financial resources to hire the temporary manpower and meet incidental expenditure.

Data available from self-reporting questionnaires of Country Assessment has been insufficient to compile these Indicators. These indicators are prposed to Complied through in-depth assessment using also the budgetary and macro-economic data.

2.1 Financial ResourcesAdequate funding is a prerequisite for all national statistics programs. Statistical offices in both developed and developing countries Governments especially governments of developing countries struggle with their development priorities. As statistical programs do not produce one bowl of rice, build one road, save a life, or teach a child, they face stiff competition for scarce government funds. For a number of years the government priorities for the collection and reporting of reliable agriculture statistics has also been paralleled by a general lack of donor interest.

Agriculture statistics face an additional dilemma as they are often outside the national statistics system. The system for agriculture and food statistics is often fragmented, with responsibility divided among the ministries of for example, agriculture, fisheries, forestry, land, and water.

Few developing countries have invested adequate funding into food and agriculture statistics to keep up with the increasing demand for reliable statistics on the sector. Assessing whether or not government funding for agriculture and food statistics is a challenge. Although the level of funding is a key indicator of whether funding may be adequate it does not on its own a provide a definitive answer.

The assessment of whether a statistical program is adequately funded is complex. Data collection costs represent one of the largest costs of a statistical operation. Countries with extensive administrative data bases, highly educated populations and the ability to survey by telephone or Internet have distinct advantages in data collection over those who do not and who must conduct most surveys in the field using face-to-face personal interviews.

Given that the data on financial resources budgets are often coming from many line ministries and departments within a country, coordination of the country’s response often appears to be a challenge when two or more agencies accept responsibility to answer some of the same questions but provide different information. It has consequently been difficult to come up with consistent and reliable indicators at this stage of the assessment process. More reliable indicators should, however, be available from the proposed in-depth assessments and, in the future, from a revised version of the questionnaire. However, once reliable data are available, the indicators suggested below could be used. These would need additional information from the National Accounts of the country, usually accessible on the web.

Relevant QuestionsFinancial resources1 (for the current year in local currency) Name of currency used for reporting: ..................................Exchange rate at the beginning of the current financial year: 1 US$ =........................local currency

Total Of which for agricultural

statistics1

3.11.1 Total national budget for statistical activities (estimate)

3.11.1a National regular budget for staff activities 3.11.1b National regular budget for staff training

3.11.1c National regular budget for non-staff activities (travel, consultancies, IT purchases etc.).

3.11.2 Total project budget for statistical activities (estimate)

Additional Data needed: GDP GDP from Agriculture

Indicator1: Total NSO budget for statistical activities, as percentage of GDP, broken down by different ministries/departmentsIndicator2: Share of agriculture statistics in NSO Budget Indicator3: Share of agriculture statistics in NSO person yearsIndicator4: Share of Statistics in the budget of Ministry of AgricultureIndicator4: Budget of Ministry of Agriculture as percentage of GDP from AgricultureScores: Presented in slabs: to be prepared after calculation of data from all countries.

2.2 Human ResourcesThe primary means by which a statistical office meets its objectives is through the knowledge, experience and motivation of its staff. Staff must not only be technically expert but also aware of quality issues, and able to develop and implement practices and methods to meet objectives. The availability of qualified and talented staff to programs and projects is therefore critical as is the need for the statistical office to invest in on-going training and skills up-grading for all staff to be able to take advantage of technological changes and advances.

Statistical programs and offices need professional staff with a variety and mix of different skills. Subject-matter staff bring knowledge of content, client needs, and relevance. Statisticians and mathematicians bring their expertise on sample designs and selection, and data quality trade-offs, especially with respect to accuracy, timeliness and cost. Field operations staff bring experience in operational methods, and concerns for practicality, efficiency, and respondents. The IT systems expert brings a systems view, and knowledge of technology standards.

Relevant QuestionsHuman resources and training for statistical activities (present)

Total For agricultural statistics

3.12.1 Number of regular professional staff in the headquarters

3.12.2 Number of regular professional staff in the regional/local offices

3.12.3 Number of regular support staff in the headquarters

3.12.4 Number of regular support staff in the regional/local offices

3.12.5 Number of project professional staff in the regional/local offices

3.12.6 Number of project support staff in the country

3.12.7 Number of staff members trained in national training institutions during the last 12 months

3.12.7a Professional staff3.12.7b Support staff

3.12.8 Number of statistical staff that attended training courses (of one week or more) abroad in the last 12 months?

3.12.9 Is there a regular training programme for statistical staff?

(Tick if ‘’Yes’’)

Indicator1: Share of agriculture statistics in NSO manpowerIndicator 2: Percentage of staff, which received training last year. Indicator3: Percentage of professional staff with bachelor/Master degree in Statistics in different ministries departments. Indicator4: Percentage of support staff with qualifications in Basic Statistics in different ministries departments.

Capacity indicator III: Statistical Methods and Practices

This indicator gives an overall picture of statistical activities undertaken in the countries and the level of professionalism in doing these. While the sub-indicators representing the first four elements of this dimension focus on the technical capabilities of the statistical organizations in the country, the last four sub-indicators focus on the statistical activities, and the analysis and use of the data collected. The combined indicator is coiled as geometric mean of all the eight indicators.

3.1 Statistical software capabilityThe use of computers and statistical software for processing, analysing, disseminating and archiving statistical information is good statistical practice that plays a major role in ensuring data quality and providing the statistical office the means for data quality assurance.

Relevant Questions3.9.6 Software and Other IT Systems Used in the NSOa. SPSS, SAS, STATA (statistical analysis software)b. ACCESS, CSPRO (data entry, edit, and imputation software) c. PC-AXIS, Oracle, SDMX (data base software)

Scoring criteria Max. Score= 3 marks

If. 3.9.6a. Yes 1 mark

No 0 marksb. Yes 1 mark

No 0 marksc. Yes 1 mark

No 0 marksIndicator = (Country Score/ Maximum Marks) x 100

3.2 Data capture technology The data collection technologies used by statistical offices and ministries provide an indication of the degree to which they have been able to acquire and use advanced equipment and digital technologies for their field collection operations.

Computer technology and Geographical Positioning System (GPS) equipment in the hands of interviewers and field staff enables them to enter data at the time of the interview. This does not only eliminate all data entry errors of commission and omission but also the technology offers the precision of GPS, and the possibility for linking remotely sensed data with data compiled using conventional respondent surveys. With data entry at the time of the interview, data processing is also often faster and not subject to the potential data capture bottlenecks that are often associated with centralized data entry operations.

Relevant Questions3.9.7 a Personal interview 3.9.7 b Computer Assisted Telephone Interview (CATI) 3.9.7 e Personal Data Assistant (PDA) 3.9.7 f Computer Assisted Personal interview (CAPI)

3.9.7.c Manual data entry into computer3.9.7 d Personal interview and Scanning of questionnaires.

3.9.7 g Geographical Position System (GPS) 3.9.7 h Compass and Measuring Tapes


If 3.9.7 b or3.9.7e or 3.9.7f Yes 1 markIf 3.9.7 b and 3.9.7e and 3.9.7f No 0 marksIf 3.9.7 d Yes 1 markIf 3.9.7 d No 0 marksIf 3.9.7 g Yes 1 markIf 3.9.7 g No 0 marks

Indicator (Country Score/ Maximum Marks) x 100

3.3 IT InfrastructureThe IT infrastructure provides an indication of the degree to which the statistical offices and their staff are equipped to process, analyse, disseminate, and archive information. Although the presence of the equipment and the accessibility to computers by individual employees is not a measure of the effectiveness of its use, the number of employees per computer it is a necessary condition prerequisite for data quality assurance and efficient data processing and a key indicator for assessing the capacity of the statistical office and its statistical programs.

Relevant Questions3.9.8 Number of PCs in use in National Statistical Office: 3.9.9 Number of computer servers installed for data storage and communication

Scoring criteriaMax. score= 3 marks

If. 3.9.8 No. of PCs/Person in NSO ≥1 pc 2 mark If 3.9.8 No of PCs/Person up to .5 pc 1 markIf 3.9.8 No of PCs/Person < .5 pc 0 markIf 3.9.9 Yes (At least one) 1 markIf 3.9.9 No 0 marks

Indicator = (Country Score/ Maximum Marks) x 100 Persons = all headquarter staff (professional + support) engaged in statistical activity

3.4 International ClassificationsAdoption of International Classification Systems is a key component for integrating data within the country and facilitating the unambiguous preparation of the country’s national accounts ensuring the nations country data is comparable to the data from other countries.

Relevant QuestionsISIC (International Standard Industrial Classification)CPC (Central Product Classification)SITC (Standard International Trade Classification)HS (Harmonized Commodity Description and Coding System)


If International ISIC Yes 1 mark

No 0 marks CPC Yes 1 mark

No 0 marks SITC Yes 1 mark

No 0 marks HS Yes 1 mark

No 0 marks

3.5 General Statistical ActivitiesThe information on general statistical activities profiles some of what are defined as “Core Statistics” in the Global Strategy for Improving Agriculture and Rural Statistics. The statistics are elements of a country’s key socio-economic indicators complimenting and supplementing the statistics available from an agriculture statistics program and are an indication of the depth and breadth of the information system for agriculture and food. Relevant Questions 3.1.4.a The latest Population Census has been conducted during the last 10 years or planned in next 2 years? (modified from the questionnaire)3.2.3 The most recent year for which National Accounts data are available.3.2.5 Are the quarterly estimates of agriculture production prepared and published?3.4.1 Is a Consumer Price Index (CPI) published in the country?3.4.5 Is a Wholesale Price Index (WPI) published in the country?3.6.2 Are the estimates of rural household income available?


3.1.4 a Yes 1 marks3.2.3 If one year lag 2 marks If two year

More that 21 mark

0 marks3.2.5 Yes 1 mark3.4.1 Yes 1 mark

No 0 marks3.4.5 Yes 1 mark

No 0 mark3.6.2 Yes 1 mark

No 0 markIndicator = (Country score /Maximum Marks) x 100

3.6 Agricultural Markets and Price Information Food and agriculture price data are defined as “Core Statistics” by the Global Strategy for Improving Agriculture and Rural Statistics. As such they are a key component of the agriculture statistics system.

Responsibility for agriculture markets and price information is usually distributed among a number of government ministries and statistical offices, as they are collected at a number of points along the food chain beginning at the farm gate through to the markets and shops in the urban centres. In addition there is often at least one statistical program in place for agriculture and livestock product markets, one for fisheries and another for forestry products. The amount, frequency, and availability of price data are all important measures of statistical system development.

Price data compliment and supplement agriculture production statistics and are often a means of evaluating coherence in the agriculture statistics. In addition, they can also serve as an early warning indicator of local production expectations from the current crop in advance of the first available yield and production estimates. Price data at various points in the food chain can be key to assessing the adequacy of local food supplies. Sharply rising prices usually indicate local shortages and falling prices often indicate surpluses that can be transported to other parts of the country.

Relevant Questions 3.4.2 Does the CPI report indices of important agricultural commodities used for direct consumption separately?3.4.3 Does there exist an index to monitor agricultural input prices?3.4.6 Does the WPI report indices separately for:Crop commodities?Livestock products?Fish and related products?3.4.7 Is an index of agricultural producer prices published in the country? 3.5.3.1 Do the systems for collecting and disseminating price and related information from the major wholesale markets of agricultural commodities exist in the country?3.5.3.2 Agricultural price collection covers sub - sectors:3.5.3.2 a Crops3.5.3.2 b Livestock3.5.3.2 c Fish and aquaculture products


3.4.2 Yes 1 markNo 0 marks


3.4.6 Crops 1 markLivestock 1 markFish and related products 1 mark If no separate reports or no WPI 0 marks


3.5.3.1 Yes 1 markNo 0 marks

3.5.3.2 a Crops 1 mark3.5.3.2 b Livestock 1 mark3.5.3.2 c Fish and aquaculture products 1 mark


3.7 Agricultural surveysAll of the surveys listed in this indicator are defined in the “Global Strategy for Improving Agriculture and Rural Statistics” as “the minimum set of agriculture production data for all countries.

The “core” items and associated data are the basis of the framework for the agricultural and rural components of the National Strategies for the Development of Statistics (NSDS). The set of core data items are the minimum requirements for the building blocks to establish methodology and to integrate agriculture and rural statistics into the national system.

The designation of core data starts with basic production statistics for the major crop items, livestock, aquaculture, fishery products, and forestry; and continues with agricultural inputs, socio-economic data, land cover, and public expenditures on agriculture and food.

Relevant Questions 3.5.1.2 Please indicate the year of the last agricultural census3.5.2.1 Crop surveys for major crops3.5.2.1 a Have any crop production surveys been conducted during the last 5 years?

3.5.2.1 b Have any crop yield surveys been conducted during the last 5 years?3.5.2.1 c Have any costs of production surveys for crops been conducted during the last 10 years?3.5.2.1 d Has any survey to estimate post-harvest losses been carried out in the country?3.5.2.2 Livestock surveys for main livestock3.5.2.2a Have any livestock enumeration surveys been conducted during the last 5 years?3.5.2.2b Have any livestock growth and production parameter surveys been conducted during the last 10 years?3.5.2.2c Has any enumeration survey/census been conducted specifically for nomadic and pastoral livestock populations during the last 10 years?3.5.2.3 Fishery surveys3.5.2.3a Have any fish and aquaculture production surveys been carried out during the last 5 years for:Marine capture fisheries?Inland capture fisheries?Aquaculture?3.5.2.3b Have sample based survey been conducted to monitor production for:

Marine capture fisheries?Inland capture fisheries?Aquaculture?

3.5.2.4 Water surveys3.5.2.4a Has any surveys been carried out during the last 10 years to provide information on:

Area equipped for irrigation by type of Irrigation?Area actually irrigated?Crops irrigated?Water withdrawal for irrigation (of crops or forests)? Water used for livestock?

3.5.2.5 Forestry surveys3.5.2.5b Is information on wood energy consumption collected in household surveys?


If 3.5.1.2 within last 10 years 2 markwithin last 20 years 1 markmore than 20 years 0 mark

3.5.2.1 a Yes 1 markNo 0 mark

3.5.2.1 b Yes 1 markNo 0 marks

3.5.2.1 c Yes 1 markNo 0mark

3.5.2.1 d Yes 1 mark No 0 mark3.5.2.2a Yes 1 mark

No 0 marks3.5.2.2b Yes 1 mark

No 0 mark3.5.2.2c Yes 1 mark

No 0 marks3.5.2.3a Yes (at least one) 1 mark 3.5.2.3b Yes (at least one) 1 mark 3.5.2.4a Yes ( area irrigated or equipped for irrigation) 1 mark

No ( neither area irrigated nor equipped for irrigation)

0 marks

3.5.2.5b Yes (crops irrigated or water withdrawal or water use)

1 mark

No (neither crops irrigated nor water withdrawal or water use)

0 marks


3.8 Derived Statistics and Analysis A strong internal analytic program contributes to an improved understanding of the needs of external analysts both in and out of government. In turn, such an understanding is a critical prerequisite for support of emerging data needs. Furthermore, good analysts have a strong personal motivation to explore issues and can, therefore, champion the development of new initiatives within the statistical office. They do so by drawing attention to the role potential new information could have in illuminating issues of public policy and this makes a vital contribution in maintaining the relevance of statistical information.

Data analysis also serves several purposes in the management of quality, including an important role in maintaining relevance. While its primary purposes may be to advance understanding and to discover further insights from existing statistical outputs, it also provides a valuable source of feedback on the adequacy and completeness of the statistical data. By identifying questions the data cannot answer it pinpoints gaps and weaknesses in the data holdings. The development of certain longitudinal surveys, several record linkage activities, the creation of a metadata base, harmonized calibration, and attention to data integration and standardization of concepts are among the initiatives that can be attributed, at least in part, in response to obstacles faced in undertaking analysis.

The use of analytic frameworks such as the System of National Accounts, food and commodity balance sheets and agri-environmental indicators, integrate and reconcile data coming from different sources and also play an important role in assessing the coherence in the data, and identifying gaps and weaknesses.

Relevant Questions 3.2.4 Are the following economic accounts are compiled in the country for agriculture sector?3.2.4a Production account3.2.4b Generation of income account3.2.4c Allocation of primary income account3.2.4d Capital accounts3.2.4e Other (income) accounts3.2.5 Are estimates of quarterly production from agriculture sector prepared and published in the country?3.4.4 Is an Index Number of Terms of Trade for Agriculture published in the country? 3.7.1 Are the food balance sheets compiled in the country, and the latest year?3.7.2 Are agri-environmental indicators compiled in the country, and the latest year?

Scoring criteria Max. score=8 marks

If 3.2.4 ≥ 3 YESs 2 marks< 3 YESs 1 mark NO for all the four questions 0 mark

3.2.5 If Yes 1 mark If No 0 mark3.4.4 If Yes 1 mark

No 0 mark3.7.1 If Yes with one year lag 2 marks

If Yes with more than one year lag 1 markIf No 0 marks

3.7.2 If Yes with one year lag 2 marksIf Yes with more than one year lag 1 mark

If No 0 marks Indicator = (Country Score/ Maximum Marks) x 100

Capacity Indicator IV : Availability of Statistical Information

4.1 Core data availabilityThe minimum set of core data includes statistics about the production of major crop, livestock, aquaculture and fisheries, and forestry products. The second requirement is for economic data on the agricultural holding, including inputs and outputs. The third requirement is to collect data on the use of fertilizers, chemicals, tillage method and other land use activities to monitor how agricultural production affects the environment. The fourth requirement is to measure the social well being of the farm and rural households.

Core data availability is reported in the FAO Country Assessment Questionnaire “Section 2, Core Data Availability, second column”. Respondents were asked to report on the availability (available or not available) of specific statistics that have been identified as the minimum core requirements of all agriculture statistics systems.

The indicator on Core Data Availability gives an idea of the extent to which an statistical system is producing the core sent of data. This is indicator is measure of the volume of available data on specific domains, viz. Economic, Social, Environmental and Geographic, or sub-domains like Production, Trade, and Stocks .

The indicators are summary indicators of the responses by statistical domain and not by the individual statistical estimates in an effort to reduce the amount of detail and facilitate analysis. For example, the Crops domain is a summary of the responses regarding the availability of statistics on 1) crop areas (areas planted and harvested), 2) crop yields, and 3) crop production (quantity and values). The Livestock domain would consequently be the aggregate of the responses on the availability of livestock statistics and Fishery, fishery statistics.

It also does not appear that summarizing the individual component statistics by “domain” results in any significant loss of information. The individual statistical estimates within a “domain” appear to exhibit similar attributes with respect to their availability, timeliness, quality, reliability, consistency, and data accessibility, as they are most often from the same source data or survey program with a shared methodology and statistical procedures.

Although the questionnaire contains 71 data items, it is proposed that the indicator be based on 59 data items identified as core for the Global Strategy; See Annex 1 of the Strategy (FAO, 2010). Using the responses in the questionnaire, one can identify specific areas where the availability of data is weak. However, for the purpose of an overall assessment of the country situation, it will be sufficient to use a single indicator based on the entire set of 59 data items.

The limitation of the results arise out of interpretation of blank cells (unanswered questions) in the questionnaire, which may mean either “data not available” or “no response”. For compiling the indicator the “no response” has been treated as “data not available”. This aggregate indicator does not distinguish between “data not available ” and “data not relevant”. It is to be noted that the data on fishery and aquaculture may not be equally relevant for all countries.

.....To be ddiscussed....

Data availability indicator = { (Number of data items on which data is available)*100/ 59}

4.2 Timeliness The timeliness of statistical information refers to the delay between the reference point (or the end of the reference period) to which the information pertains, and the date on which the information becomes available. It is typically involved in a trade-off against accuracy. The timeliness of information will influence its relevance.This indicator is also based on responses to the same 59 data items listed in Annex 1. The response in column 4, Section 2 is used for compiling this indicator.

The indicator is calculated in two steps:

STEP 1: Calculate the “Modal Year of data availability” which is the most frequent year among the reported years of availability of data for the 59 items.

STEP 2: Assign scores to the county as follows:

4.3 Quality, reliability and consistency of dataThe quality, reliability and consistency of the statistical data are essentially the degree to which the information correctly describes the phenomena it was designed to measure. It is usually characterized in terms of error in statistical estimates and is traditionally decomposed into bias (systematic error) and variance (random error) components. It may also be described in terms of the major sources of error that potentially cause inaccuracy (e.g., coverage, sampling, nonresponse, and response errors).

Quality, reliability, and consistency measures are based on the overall assessments provided by the FAO focal points in each country in Column 4, Section 2 of the Assessment Questionnaire. The responses are essentially qualitative evaluations of the available statistical estimates for each data item. There may situations where the estimates of major crops are “Highly reliable” but those of minor crops are “Unacceptable” . It is assumed that the focal points have responded on the basis of quality of estimates for the most important crops for the country. This indicator is expected to be calculated based on responses for the 59 data items. In case of not response, it is restricted to the available responses.

The indicator is calculated in two steps:

STEP 1: Calculate the “Modal Quality of the available data”, which is the most frequent reported grade of quality ( Highly reliable, reliable, acceptable, workable and unacceptable) for the available data on the 59 items.

STEP 2: Assign scores to the country as follows:

Scoring criteria Max. score=3marks

If the “Modal Year of data availability” = Year of Survey 3 marksIf the “Modal Year of data availability” = 1 year before Year of Assessment

2 marks

If the “Modal Year of data availability” = 2 years before the Year of Assessment

1marks

If the “Modal Year of data availability” > 2 years before the Year of Assessment

0 marks

Scoring criteria


4.4 Data AccessibilityThe accessibility of statistical information refers to the ease with which it can be obtained from the statistical agency. This includes the ease with which the existence of information can be ascertained, as well as the suitability of the form or medium through which the information can be accessed. The cost of the information may also be an aspect of accessibility for some users.

Due to data limitation this indicator is based on the information on the facilities in the National Statistics Office. Generally, it is expected that the Ministry of Agriculture will also have the similar facilities. Differences, if any among the agencies can be identified better at the time of an in-depth country assessment.

Relevant questions

3.9.1 Does the National Statistics Office have a website for hosting official statistics for the country?3.9.3 Does there exist any database for official statistics?3.9.4 If ‘’Yes’’ to 3.9.3, is the database accessible to external users on internet?

Scoring criteria

Max. score= 3 marksIf 3.9.1 Yes 1 mark



No 0 marksIndicator = (Country Score/ Maximum Marks) x 100

4.5 Quality ConsciousnessQuality consciousness is normally assessed based on evidence that the statistical office not only follows sound statistical practices (statistical methodology) and has established procedures to minimize sampling and non-sampling errors but that it documents and makes this information readily accessible to the public, in the form of written reports, for all statistical estimates.

Success in the management of quality requires a shared concern for, and pride in, quality among employees and managers at all levels of the statistical office. Acceptable quality is not achieved through managerial edicts but through attention to client needs coupled with the sound application of knowledge and expertise by employees at many levels. Policies and programs aimed at ensuring the availability of a motivated and competent workforce at all times are a crucial supporting element of the management of quality.

The statistical agency should strive to build quality into all its programs and products. The quality of its official statistics should be founded on the use of sound scientific methods, adapted over time to

Max. score=5 marksIf Highly Reliable or Yes 5 marks Reliable Yes 4 marks Acceptable Yes 3 marks Workable Yes 2 marksIf 5 Unacceptable Yes 1 mark

meet changing client needs, to budgetary circumstances, to the changing reality that the statistical office aims to measure, and to the capacity of respondents to supply source data.

Most operations and functions of the statistical office have an impact on the quality of the information. The management of quality should therefore be an integral part of the management of every program, and an important component of corporate management.

A significant feature of the management of quality is the balancing of quality objectives against the constraints of financial and human resources, the goodwill of respondents in providing source data, and competing demands for greater quantities of information. The management of quality is not the maximization of quality at all costs, but the achievement of an appropriate balance between the quantity and quality of information yielded by the statistical programs and the resources available. Within individual programs the challenge is to make the appropriate trade-offs between the evolving needs of clients, costs, respondent burden, and the various dimensions of quality.

Relevant questions

3.8.1 Is the methodology of national agricultural surveys accessible to public?3.8.2 Are the sampling errors published for most national surveys?3.8.4 Are Technical Reports of Post-enumeration Surveys on the quality of the survey data collected published?






5. Presentation of Country Profiles

An example of graphical presentation of country profile based on standard assessment of country capacity to produce agricultural statistics is given below.

Over - all country capacity

Institutional Infrastructure

Statistical Methods and Practice Availability of statistical information

0

50

100

Capacity indicator IInstitutional Infrastructure

Legal framework

Coordination in Statistical System

Strategic vision and planningIntegration of Agriculture in the NSS

Relevance

10

60

110100

100

100100

90.9

Capacity indicator IIIStatistical Methods and Practices

Statistical software capability

Data capture technology

IT infratsructure

International classifications

General statistical activities

Agricultural price information

Specialized agricultural survey

Analysis and use of data

0

50

100

67

67

67

10086

2014

25

Capacity indicator IVAvailability of Statistical Information

.

Timeliness

Core data availability

Quality reliability and consistency of data Data accesibility

Quality consciousness

0

50

100

67

71

80

100

33

6. Country grouping to monitor progress There does not exist a unique method for grouping the countries according to the level of their statistical development. However, a number of meaningful groupings are possible using the above indicators. The transition of countries from a group to other group could then be monitored, once criteria for grouping based on indicators is fixed.

Some literature on the subject suggests use of a Composite Indicator based on weighted average of indicators on different dimensions. While this type of composite indictors serve a useful purpose as reflected in the weighting diagram, these are often criticised as being subjective and having limited general use. It is therefore proposed to present the profile of the country based on indicators measuring key dimensions and their elements defining the country capacity.

One possible criteria, avoiding subjectivity, could be implemented as follows, after scores of all the countries in the population, say a continent, have been obtained on all the three dimensions.

Step 1: Calculate the three Quartiles of the distribution of scores on each of the three dimensions.

Step 2: Verify the status of each country on each on the three dimensions with respect to respective quartiles of that dimension.

Step 3: Assign group to countries as follows.

GROUP 1 (Least developed): On at least two of the three dimensions the country is measured as being below the first quartile.

GROUP 2 (Developing with constraints): The country is below the first quartile on only one out of the three dimensions. The limitations on this dimension may perhaps be acting as the binding constraints to improvement of agriculture statistics.

GROUP 3 (Developing): At least one dimension the country is below the median of the distribution, and the country is not part of any of the above two groups.

GROUP 4 (Progressive): The country is not in any of the three above groups and also has at least one dimension below the third quartile.

GROUP 5 (Developed): On all the dimensions the country is above the third quartile.The grouping is explained below on the basis of schematic diagram below.

To come..

With the improvements over time the distribution of the scores over the three dimensions will also be changing. However, to ensure the over time comparability some Benchmark Scores could be used for categorizations. These benchmark scores (or the thresholds for categorization) will remain unchanged throughout the period of monitoring. The thresholds could be based on the distributions obtained in the baseline assessments; they will be closer to quartile but not exactly the same as the estimated quartiles.

Chapter 8 of the Implementation Plan of the Global Strategy to Improve Agriculture Statistics (FAO, 2011) suggests a criteria to select pilot countries for priority attention. This categorization is also expected to result in the similar groupings as would be obtained from the method based on quartiles or thresholds. However, it should be noted that this method considers only a few of the elements of country capacity to produce agriculture statistics.

7. References [FAO/WB, 2010] Global strategy to improve agricultural and rural statistics. Economic and sector

work.

[FAO, 2012] Improving Statistics for Food Security, Sustainable Agriculture and Rural Development - An Action Plan to Implement the Global Strategy. Draft

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