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GCP/GLO/208/BMG – CountrySTAT for Sub-Saharan Africa
CountrySTAT GHANA FIRST PANORAMA REPORT
2009 Prepared by: James Ayittey & Godsway Banini Statistics, Research and Information Directorate Ministry of Food and Agriculture, Ghana
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TABLE OF CONTENTS
Page
LIST OF TABLES .... .... .... .... .... ... v
LIST OF FIGURES .... .... .... .... .... ... vi
APPENDIX LIST … … … … … vi
ABBREVIATIONS & ACRONYMS … … … … … vii
ACKNOWLEDGEMENT .... .... .... .... .... ... ix
1. The National Statistics System 1
1.1 Legal framework and Statistical Advisory Bodies … … … 1
1.2 Structure of the National Statistics System … … … 2
1.3 National Strategy for Development of Statistics … … … 4
2. Reference Situation for the Food and Agriculture Statistics System 6
2.1 Legal Framework and Food and Agriculture Statistical Advisory Bodies .. 6
2.2 Structure of the Food and Agriculture Statistics System … … 6
2.3 National Strategy for Food and Agriculture Statistics … … 12
2.4 Human Resources available … … … 21
2.5 Non-Human Resources available … … … 22
2.6 Data Dissemination Policy for Food and Agriculture Statistics … 22
2.7 Modalities of promoting User-Producer Dialogue … … … 23
2.8 Existing Databases and Data Dissemination Tools and Platforms … 23
2.9 Regional Integration and International Technical Assistance received … 24
3. Outputs, Data Sources, and Metadata of Food and Agriculture Statistics 25
3.1 Crops Statistics (including national level and differentiating irrigated
and non-irrigated land); production ([quality, area harvested, yield]),
commodity prices at the farm gate, wholesale, retail, export, import.
Also availability and sources of data for Production quantity of
Processed Crops is requested weight] … … … 26
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3.2 Cocoa Statistics … … … 31
3.3 Statistics on Irrigation … … … 33
3.4 Livestock Statistics (including sub national production [quantity/yield/
carcass weight] and commodity prices at the farm gate, wholesale,
retail, export, import) … … … 35
3.5 Fishery Statistics … … … 39
3.6 Forestry Statistics … … … 42
3.7 Water Resources … … … 43
3.8 Land Use (ha. cropland, irrigated cropland – ha, ownership, legal
tenure, share of agriculture in urban/per-urban, rural area) … … 43
3.9 Food availability for human consumption, External Trade, Population
(Total/male/female/rural/urban/agricultural/non agricultural) including
farm household and rural household and other relevant indicators for the
agricultural sector such as food
- Food security
-Inputs (fertilizers, pesticides, machinery, labour and cost of inputs)
- (Rural) Infrastructure (storage facilities, roads, electrification,
mobile phone coverage)
- Credit (access to, amount, source and geographical distribution)
- Economic (Agriculture Value Added and its disaggregation level;
income distribution (Gini); rural/urban income) … … 45
3.10 Description of national/sub-national commodities codes system
(if existing) … … 51
3.11 Metadata for Available Agricultural Statistics … … 51
4. Overview of User Needs for Food and Agriculture Statistics – Ghana 52
4.1 Public Sector Decision Makers … … … 52
4.2 Private Sector Decision Makers … … … 52
4.3 Limitations of the Available Food and Agriculture Statistics … … 52
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5. Expectations from CountrySTAT and Synergies with on-going
Initiatives – Ghana 70
5.1 Expectation from CountrySTAT and the CountrySTAT for Sub-Saharan Africa
Project … … … 70
5.2 Synergies with on-going initiatives … … … 71
6. Important Factors for the Success of the CountrySTAT
Project – Ghana 72
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LIST OF TABLES Table 2.2: Problems of MOFA Vertical Agricultural Statistical System … 10
Table 2.3.1: Details of Strategic Plan for the Development of Agric Statistics … 13
Table 2.3.2: Details of Strategic Plan for the Development of Agric Statistics … 14
Table 2.3.3: Details of Strategic Plan for the Development of Agric Statistics … 15
Table 2.3.4: Details of Strategic Plan for the Development of Agric Statistics … 16
Table 2.3.5: Details of Strategic Plan for the Development of Agric Statistics … 17
Table 2.3.6: Details of Strategic Plan for the Development of Agric Statistics … 18
Table 2.3.7: Details of Strategic Plan for the Development of Agric Statistics … 19
Table 2.3.8: Details of Strategic Plan for the Development of Agric Statistics … 20
Table 2.4.1: Distribution of SRID Staff by Category … … … 21
Table 2.4.2 Distribution of Professional and Sub-Professional Staff by Unit … 21
Table 2.5: Non-Human Resources Available … … … 22
Table 3.1: Available Data: Crops Sub-Sector … … … 26
Table 3.2: Available Data: Cocoa Sub-Sector … … … 31
Table 3.3: Available Data: Irrigation … … … 33
Table 3.4: Available Data: Livestock Sub-Sector … … … 35
Table 3.5: Available Data: Fisheries Sub-Sector … … … 39
Table 3.6: Available Data: Forestry Sub-Sector … … … 42
Table 3.8: Land Use (Specific to Agriculture) … … … 44
Table 3.9.1: Domestic Food Supply and Demand Position 2008 … … … 45
Table 3.9.2: Quantity and Value of Cereal Imports (1999 – 2007) … … … 46
Table 3.9.3: Daily Energy Requirement Position … … … … 47
Table 3.9.4: Macro-economic indicators (2008) … … … 47
Table 3.9.5: National Average Input Prices (GH ¢) … … … 48
Table 3.9.6a: Commercial Banks Loans and Advances (%) … … … 49
Table 3.9.6b: Secondary Banks Loans and Advances (%) … … … 49
Table 3.9.6c: Basic Information on Banks in Ghana … … … 50
Table 3.9.7: Real Agricultural And Non-Agricultural GDP Growth Rates … 51
Table 4.1: Required Agricultural Statistics for Monitoring the Agricultural Sub-
Sector … … … … 53
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Table 4.2: FASDEP II Required Agricultural Statistical Data for Monitoring
Indicators … … … … 56
Table 4.3: Required Agricultural Statistics to Monitor GPRS Indicators … 63
Table 4.4: Required Agricultural Statistical Data for Monitoring Agricultural Policies
and Strategies of CAADP … … … … 64
Table 4.5: Required Agricultural Statistical Data for Monitoring Millennium
Development Goals (MDGs) … … … … 69
LIST OF FIGURES
Figure 1.1: Model of Stakeholders in the National Statistical System … … 3
Figure 2.1: A Model of the Horizontal Structure of MOFA Agricultural Statistical
System … … … … 8
Figure 2.2: A Model of the Vertical Structure of MOFA Agricultural Statistical
System … … … … 9
Figure 2.3: Proposed Model of the Horizontal Structure of MOFA Agricultural
Statistical System … … … …11
Figure 2.4: Proposed Model of the Vertical Structure of MOFA Agricultural
Statistical System … … … …12
APPENDIX 1: Metadata for Available Agricultural Statistical Data:
A. Metadata for Crop Subsector … … … …73
B. Metadata for Cocoa Subsector … … … …78
C. Metadata for Livestock Subsector … … … …80
D. Metadata for Fisheries Subsector … … … …73
E. Metadata for Irrigation … … … …86
F. Metadata for Forestry Subsector … … … …87
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ACRONYMS
AEA Agricultural Extension Agents AESD Agricultural Engineering Services Directorate AgMIS Agriculture Management Information System APD Animal Production Directorate ASS Agricultural Statistics System BOG Bank of Ghana CAADP Comprehensive Africa Agricultural Development Programme CBO Community Based Organization CEPS Customs, Excise and Preventive Service COCOBOD Ghana Cocoa Board CRIG Cocoa Research Institute of Ghana CSD Crop Services Directorate CSIR Council for Scientific and Industrial Research CSO Central Statistical Office DADU District Agricultural Development Unit DAES Directorate of Agricultural Extension Services DOC Department of Co-operatives DP Development Partner ECOWAS Economic Community of West African States FAO Food and Agriculture Organization FASDEP II Food and Agriculture Sector Development Policy II FBO Farmer Based Organization GDDS General Data Dissemination System GDP Gross Domestic Product GEPC Ghana Export Promotion Council GIDA Ghana Irrigation Development Authority GIS Geographic Information System GMA Ghana Meteorological Agency GOG Government of Ghana GPRS II Growth and Poverty Reduction Strategy II GPS Global Positioning System GSS Ghana Statistical Service HRDMD Human Resource Development and Management Directorate ICT Information and Communication Technology ISSER Institute of Statistical, Social and Economic Research LAN Local Area Network LDP Livestock Development Project LPIU Livestock Planning and Information Unit MDAs Ministries, Departments and Agencies • MDGs Millennium Development Goals MEST Ministry of Environment Science and Technology MISTOWA Market Information Systems and Trade Organizations in West Africa MMDAs Metropolitan, Municipal and District Assemblies MOFA Ministry of Food and Agriculture MOFI Ministry of Fisheries
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MOH Ministry of Health MOLFM Ministry of Lands, Forestry and Mines MOS Management Organizational Structure MOTI/PSI Ministry of Trade and Industry and Presidential Special Initiative NASS National Agricultural Statistical System NEPAD New Partnership for Africa Development NGOs Non-Governmental Organizations NSDS National Strategy for the Development of Statistics NSS National Statistical System PARDIC Public Administration Restructuring and Decentralization Implementation committee PDA Personal Data Assistant PNDC Provisional National Defence Council PPMED Policy Planning Monitoring and Evaluation Directorate PPRSD Plant Protection and Regulatory Services Directorate PSD Private Sector Development PSI President Special Initiative RADU Regional Agricultural Development Unit RST Remote Sensing Technique SDDS Special Data Dissemination Standard SRID Statistics Research and Information Directorate SSA Sub-Saharan Africa SWOT Strength, Weakness, Opportunity and Threat TOR Terms of Reference UN United Nations VSD Veterinary Services Directorate WIAD Women in Agricultural Development WFP World Food Programme WRI Water Research Institute WTO World Trade Organization
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ACKNOWLEDGEMENT
The consultants wish to thank the staff of Statistics Research and Information Directorate (SRID), Ghana Statistical Service (GSS) and other Ministries, Departments and Agencies (MDAs) including members of the CountrySTAT Technical Working Group who provided invaluable information and assistance that facilitated the successful completion of the report.
The consultants also wish to thank Messrs Samuel Oku, Ag Director of SRID and Francis Dzah, Ghana CountrySTAT Project Coordinator, for their valuable advice and comments. Mr. E. T. Opare also deserves commendation for typing and preparation of the report.
Finally, we wish to thank the UN/FAO for offering us the opportunity to prepare this report.
It is our expectation that the report will assist in setting up and developing the CountrySTAT System in Ghana.
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CHAPTER 1
The National Statistical System
1.1 Legal framework and Statistical Advisory Bodies
The National Statistical System (NSS) is not explicitly mentioned as an institution in any legislative document but implied in all the legislative instruments that gave legal backing to the establishment of a Central Statistical Office (CSO) in the country to produce official statistics. The legislative instruments did not only give mandate to the CSO to produce and disseminate official statistics in Ghana, but also tasked it to coordinate and collaborate with Ministries, Departments and Agencies (MDAs) and other organisations, which by the nature of their work, produces official statistics. The following are sections of Acts of parliament which give backing to the institution of the CSO and hence the NSS.
• Section 3 (1) (c) of the Statistical Ordinance of 1951, revised in 1954 stated as part of the duties of the Office of the Government Statistician “to collaborate with departments of Government and with local authorities in the collection, compilation, analysis and publication of statistical records of administrations and departments”.
• Section 1 (2) (c) of the Statistics Act 37 of 1961 that established the Central Bureau of Statistics (CBS) stated among its functions the need to “collaborate with the public services and other official or quasi-official and other organizations in the collection, compilation, analysis and publication of statistical records of or connected with those organizations”.
• Section 9 (1) (d) of the PNDC Law 135 of 1985 mandates the Ghana Statistical Service “to organise a co-ordinated scheme of economic and social statistics relating to Ghana”.
• Again Section 10 of the PNDC Law 135 of 1985 indicated that “Public services and other official or quasi-official organizations or any other organization shall collaborate with the Government Statistician in the collection, compilation, analysis and publication of statistical records of or connected with those organizations.”
• The legislative instruments regarding statistics production in the country also recognized suppliers of raw data for official statistics production and, specified punitive measures if they failed to supply the needed raw data on request (Section 15 of PNDC Law 135).
• The users of official statistics and researchers were also recognized in the legislative instruments. Section 4 (a) indicates that “The Board shall be
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responsible for: Promoting the effective use of statistics and stimulating research activities in all fields of application of statistics”.
Thus, the NSS in Ghana includes all MDAs responsible for gathering statistical data through censuses, surveys and administrative action as well as suppliers of information, users and researchers.
The following are some of the landmarks in the development of statistics in the country which are related to the promulgation of legislative instruments that gave legitimacy to the production of statistics, and hence the legitimacy of the NSS.
• In 1948 the Office of the Government Statistician (OGS) was established as a service agency under the Ministry of Finance;
• In 1961 the Office of the Government Statistician was expanded and named Central Bureau of Statistics as a department under the Ministry of Finance (Statistics Act 37 of 1961);
• In 1970 a building was constructed to house the Central Bureau of Statistics and now the Ghana Statistical Service;
• In 1985 a new legislative instrument, PNDC Law 135, established the Statistical Service (SS) to replace the Central Bureau of Statistics;
• The PNDC Law 135 also made the Statistical Service autonomous reporting to the Office of the Provisional National Defence Council (PNDC) Government through a Management Board – the Statistical Service Board.
1.2 Structure of the National Statistical System
The NSS by definition comprises all the institutions, identifiable groups and individuals who contribute to the production of statistical information as well as those who use the statistical information in diverse ways such as policy formulation, decision-making, planning of developmental activities, research, etc. Thus, the stakeholders in NSS include:
• Suppliers of data
• Producers of statistics and indicators
• Users of statistical data
• Trainers of human resources for statistical work, and
• Providers of financial, material, technical and other support that facilitate statistical activities in the country.
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In principle therefore, every person in the country, in one way or another, qualifies as a stakeholder in the NSS. The structure of the NSS is simplified in the model shown in Figure 1.1 below Figure 1.1 Model of Stakeholders in the National Statistical System
The roles played by the stakeholders are contributions that go to make the NSS function. The roles of the statistical producers are those that many observers recognize in the NSS and therefore consider as important. However, the roles of the other stakeholders, though not very visible to the casual observer, are equally important for the smooth functioning of the system. Suppliers of Data
Every individual resident in Ghana, in one way or another, supplies raw data for statistical production. A particular occasion is when population and housing census is conducted. Many individuals also supply data during specific surveys of target groups such as farmers, fishermen, traders, manufacturers, etc. Many raw data are also gathered through administrative records on individuals. All those institutions that gather raw data through administrative procedures but do not process the raw data to generate statistics are regarded as data suppliers. They include many MDAs, public service providers (Ghana Police Service, Judicial Service, Internal Revenue Service, Prison Service, Customs Excise and Preventive Service, Births and Deaths Registry, Value Added Tax Service), private sector business associations (Association of Ghana Industries, Federation of Association of Ghanaian Exporters).
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Producers of Statistics
The statistics producers are of two categories – those producing official statistics and are all public or quasi public institutions, and those whose statistical outputs are not regarded as official but are equally important and recognized in official circles. The CSO producing official statistics in the country presently is the Ghana Statistical Service (GSS). Many MDAs also produce official statistics, independently or in collaboration with the GSS, on their areas of operation. They include the Ghana Export Promotion Council (GEPC), Ghana Cocoa Board (COCOBOD) and Bank of Ghana (BoG). Some of the MDAs partly or wholly rely on GSS for the statistics they require for decision-making, planning and other activities. The Institutions that produce non-official statistics include training and research institutions, for example the Institute of Social, Statistical and Economic Research (ISSER) of the University of Ghana and other tertiary educational institutions, non-governmental organizations and civil society organizations. Users of Statistics
Many of the MDAs do not only produce statistics, but are also major users of statistics. Thus, some MDAs play multiple roles as data suppliers, producers as well as users of statistics. Other users of statistics include many other public and quasi public institutions, civil society organizations, non-governmental organizations, researchers and students of tertiary institutions, private investors. Users of statistics produced in the country transcend the national borders and sub-regional organizations such as Economic Community of West African States (ECOWAS); regional organizations and institutions such as African Union, Economic Community of Africa, the New Partnership for African Development (NEPAD); and International Organizations such as United Nations agencies, World Bank, International Monetary Fund. Trainers of Human Resource
The training institutions contribute mainly to knowledge, skills and competence development of the human resource for the production and usage of statistics. The local training tertiary institutions offer general certificate, diploma and degree programmes in statistics. Some training institutions offer special or tailor-made short courses, from two to eight weeks to sharpen knowledge and skill. Training workshops are also organized by Non-Governmental Organizations (NGOs), international organizations, development partners, to introduce new ideas, concepts and procedures of statistical production. Providers of Support
The Government of Ghana, and international organizations including, the United Nations, banking and financial institutions, NGOs and development partners provide support to facilitate statistical activities. The support takes many forms including: finance, supply of equipment and logistics, staff training usually in institutions and workshops both locally and abroad. 1.3 National Strategy for Development of Statistics
The preparation of the national strategic plan to develop statistics in the country was undertaken in recognition of the need to improve official statistics in order to:
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• provide quantitative basis for informed decision-making in planning for socio-economic development,
• provide effective and unbiased basis for monitoring development programmes and projects and
• sufficiently evaluate the outcomes of development programmes and projects. The need for a strategic plan also recognizes the constraints in the production of statistics to meet emerging demands such as monitoring the progress of implementation of programmes towards achieving the MDGs and Poverty Reduction targets. The objectives of the strategic plan are therefore as follows:
• To ensure that the NSS is well placed to produce the required statistics to monitor and evaluate the goals and outcomes of developmental programmes and projects;
• To ensure that the NSS is able to attract and retain professional statisticians and obtain adequate funding for statistical activities; and
• To advocate for proper recognition for statistics in planning, decision-making and adequate support for the production of statistics.
The results-measurement agenda has put immense pressure on the national statistical systems and highlighted the inherent weaknesses in the statistical information available nationally. To address the issues of data quality, many developing countries have subscribed to the IMF’s General Data Dissemination System (GDDS), or to the Special Data Dissemination Standard (SDDS). The GDDS for instance promotes coordination among the various agencies responsible for the production and dissemination of official statistics. However, the GDDS does not cover the full range of official statistics required to monitor and evaluate the poverty reduction strategies. The National Strategy for the Development of Statistics (NSDS) is intended to build on what already exists (the GDDS and SDDS), cover statistics needed to monitor and evaluate the poverty reduction strategies and will also address legal and institutional issues, identify technical assistance and training needs, estimate the costs of implementing the strategy and explain how these costs will be financed.
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CHAPTER 2
Reference Situation for the Food and Agriculture Statistics System
2.1 Legal Framework and Food and Agriculture Statistical Advisory Bodies
The Civil Service Law 1993, PNDC L 327 that established the Ministry of Food and Agriculture (MOFA) and the Public Administration Restructuring and Decentralization Implementation Committee (PARDIC) recommended that each sector Ministry maintains four line directorates of
(i) Finance and Administration (F&A) (ii) Human Resource Development and Management (HRD&M) (iii) Policy Planning Monitoring and Evaluation (PPME) (iv) Statistics, Research and Information (SRI).
The mandate of the Statistics Research and Information Directorate (SRID) is to carry out statistical functions for the Ministry of Food and Agriculture (MOFA). The mission of the directorate is to “ensure the generation of relevant and timely statistics and information on agriculture for stakeholders to ensure that agricultural production decisions are based on objective and realistic criteria. Further, to ensure that statistics generated for policy formulation, planning, project implementation, monitoring and evaluation are efficiently communicated within the MOFA and to the general public”. 2.2 Structure of the Food and Agriculture Statistics System
The structure of the agricultural statistical system is a decentralized type. It comprises some directorates of MOFA and some agencies as producers of agricultural and related statistics. The structure also recognizes other stakeholders such as suppliers of data, users of agricultural data, trainers of human resource and providers of financial, technical and material support who play important role in the production and dissemination of agricultural data. The MOFA has three directorates that produce data in three major areas of crops, livestock and fisheries. Thus, the MOFA tends to play a lead role and has some national structure that fades into the national statistical system Two structural dimensions exist in the MOFA Agricultural Statistical System (ASS). These are horizontal and vertical structures. The two structures reflect largely the roles and responsibilities of key stakeholders of the system, producers of agricultural statistics, users of agricultural statistics and/providers agricultural information. 2.2.1 Horizontal Structure
The horizontal structure comprises the MOFA directorates that collect data, compile and disseminate statistical information without reference to the other directorates. There are no linkages among the directorates in their data collection, processing and dissemination. The statistics produced and disseminated independently by the MOFA directorates are
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generally in line with the activities they are mandated to perform. A model structure of the horizontal MOFA agricultural statistical system is shown in Figure 2.1. Some constraints and problems can be identified with the horizontal structure. These include the following:-
• Lack of coordination and collaboration;
• No control over the quality of statistical information produced;
• Low recognition, budgetary and other support for statistical activities in the MOFA directorates beside SRID
• Inadequate training opportunities for staff engaged in statistics compilation in the directorates beside SRID.
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Figure 2.1: A Model of the Horizontal Structure of MOFA Agricultural Statistical System
Users of MOFA MDAs, Researchers, NGOs, Inter. Org., Development Partners, Other Public / Private Inst. Agric. Statistics
Producers of MOFA Agric. Statistics SRID VSD CSD PPRSD PPMED DAES APD WIAD OTHERS MOFI (MOFA Directorates) (LPIU)
Suppliers of Data Data Data Data Data Data Data Data Data Data Data (Sources) Sources Sources Sources Sources Sources Sources Sources Sources Sources Sources
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2.2.2 Vertical Structure The vertical structure of the MOFA agricultural statistical system comprises the head office (Directorate), regional offices and district offices. The three administrative levels in the vertical structure are linked in their roles in the data collection and processing at the district offices, compilation of regional estimates at the regional offices and compilation of national estimates at the head office. The statistical estimates produced at the districts are the inputs in the estimation and compilation of the regional statistics and the regional estimates become the inputs in the estimation and compilation of the national statistics. The final output of the statistical estimates at the head office usually consists of the national, regional and district statistical estimates. The head office distributes the final output to the regions which in turn make copies and distribute to their respective districts. A simple model of the vertical structure of the MOFA ASS is shown in Figure 2.2
Figure 2.2: A Model of the Vertical Structure of MOFA Agricultural Statistical
System
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Compiles Head-Office National Statistics (Directorate) Compiles Regional Office Regional Statistics Collects Data / Compiles Statistics District Office ------------------------------------------------------------------------------------------------
A number of problems and constraints are also identified in the vertical structure since the decentralization of central government authority to the districts in 1997. The previous and current situations as well as the problems that have emerged from the vertical structure of the MOFA ASS are indicated in Table 2.2
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Table 2.2: Problems of MOFA Vertical Agricultural Statistical System
Situation Before
Decentralization
Situation After
Decentralization
Emerging Problems and
Constraints i). Statistical activities carried out at the districts
• Annual crops and livestock survey
• Weekly market prices of food crops and farm input survey
• Weekly marketing cost survey
• Periodic farm-gate (producer) price survey
• Monthly observation of condition of maize fields
ii). Head office authority over district staff
• Staff belonged to Head office
• Paid salaries and other remunerations such as transportation allowance (T&T)
• Hired, promoted, trained and fired staff
• Provide survey equipment
• Provided logistics
• Provided programme of work
iii). Number of Staff Per District
• Annual crops and livestock survey (13 )
• Market price survey (6 ) iv). No. of enumeration areas for crop and livestock survey per district (20) No. of markets covered per district, region and nation-wide:
• Markets per district (2 )
• Markets per region (14-46)
i). Activities Carried out
• Annual crops and livestock survey
• Weekly market prices of food crops and farm inputs
• Weekly marketing cost survey
• Periodic farm-gate (producer) price survey
• Monthly observation of condition of maize fields
ii). No authority of head office over district staff
• Staff controlled by District Agricultural Development Unit (DADU)
• DADU pays salaries and other remunerations such as transportation allowance (T&T)
• MOFA recommends to Head of Civil Service hire, promote, pay salaries and fire staff
• DADU expected to provide survey and other equipment
• DADU expected to provide logistics
• DADU decides work load in addition to collecting data through surveys and processing data for the regional offices and eventually for the head office
iii). Number of staff per district
• Annual crops and livestock survey (7)
• Market price survey (1) iv). No. of enumeration areas for crops and livestock survey per district (8-10)
i). All survey activities continue with the following problems
• Reduced enumeration areas per district and for that matter, regions and nation-wide;
• Maximum of 5 staff assigned per district for the annual crops and livestock surveys; And 1-3 staff per district for prices and marketing cost surveys
• Staff assigned other duties (office / extension) which are usually accorded priority.
• Reduced staff motivation – partly due to delays in paying T&T for field work, increased work load, and lack of focus for work;
• Delays in submission of processed field data to the regions and to the head office
• No replacement of non-functional, faulty and lost field equipment
• Inadequate provision of logistics for field work
• Inadequate training of market survey staff due to lack of funds. Last training in 2004
• DADU financial resources inadequate to cater fully and regularly the requirements for the surveys
• Delays in recruiting staff for survey work when the need arises.
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Situation Before
Decentralization
Situation After
Decentralization
Emerging Problems and
Constraints • Markets nation-wide
(140-460) Head-office budget submitted and allocated by government covered regional and district staff and activities.
No. of markets covered per district, region and nation-wide:
• Markets per district (1)
• Markets per region (7-23)
Markets nation-wide (70-230) District assemblies to pay staff and cover costs of activities from own resources (common fund and mobilized revenue.
2.2.3 Restructuring of MOFA Agricultural Statistical System It has been proposed that both the horizontal and vertical structures of the MOFA agricultural statistical systems be restructured in order to address some of the problems that have emerged due to the decentralization policy in the country. Models of the proposed restructure of the horizontal and vertical MOFA agricultural statistical system are shown in figures 2.3 and 2.4 The restructuring is based on the SRID playing a lead role in the production and dissemination of all MOFA official agricultural statistics and requires a policy that recognizes SRID as such.
Figure 2.3: Proposed Model of the Horizontal Structure of MOFA Agricultural
Statistical System
Users of MOFA MDAs, Researchers, NGOs, Inter. Org. DPs , Other Official Statistics Producer of MOFA S R I D Official Statistics/Dissemination Raw Data MOFA Other Directorates Sources
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Figure 2.4: Proposed Model of the Vertical Structure of MOFA Agricultural
Statistical System Compiles National SRID Statistics Other Directorates Compiles Regional Regional Office Statistics Collects Data / Compiles District Office District Statistics
2.2.4 Issues in Improving MOFA Agricultural Statistical System
The essential conditions for effective and efficient MOFA agricultural statistical system will be very much the same as the proposed horizontal and vertical MOFA systems. Some of the essential conditions which have been identified include effective coordination and collaboration to ensure that data collected are harmonized and that there is sharing of information among producers and all other stakeholders of the system.
2.3 National Strategy for Food and Agriculture Statistics.
A National Strategy for Food and Agriculture Statistics was developed by the Statistics Research and Information Directorate of the Ministry of Food and Agriculture (MOFA) as part of the National Strategy for the Development of Statistics in Ghana. The tables below (Table 2.3.1 – Table 2.3.8) present details of the strategic plan and budget for a 5-year period (2009-2013)
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Table 2.3.1: Details of Strategic Plan for the Development of Agriculture Statistics
GOAL (1): To produce and disseminate comprehensive, integrated, accurate and timely national agriculture statistics in support of national development
STRATEGIC OBJECTIVE/ PURPOSE
ACTIVITIES YEAR 1 US$ ‘000
YEAR 2 US$’000
YEAR 3 US$’000
YEAR 4 US$’000
YEAR 5 US$’000
TOTAL US$’000
1.1 Improve Accuracy of Agriculture Data
Improve statistical methodology, samples selection and survey procedures.
• Consultant to Review current methodology etc and prepare reports.
• Pilot the new methodology etc in 3-5 districts.
• Conduct survey using new methodology in all 170 districts Introduce new survey technologies (GIS) Remote Sensing Techniques.
• Geographic positioning receiver and software processing package.
• Training of staff in use of equipment
• Resource persons allowance Improve training of field survey staff.
• Develop training materials
• Printing training materials for field staff Motivate field staff and supervisors.
• Procure 200 motorcycles per annum for field staff and supervisors
• Provide operating expenses Educate and motivate farmers/respondents.
• Provide a cutlass each for 10 farmers per district.
• Synthesize farmers and publicize survey activities in the districts.
• Provide a certificate of participation for 10 farmers per district.
60.0 20.0 10.0 30.0
330.0 300.0 15.0 15.0
50.0 30.0 20.0
60.0 50.0 10.0 20.0 10.0 5.0 5.0
30.0 - - 30.0
30.0 - 15.0 15.0
30.0 10.0 20.0
60.0 50.0 10.0 20.0 10.0 5.0 5.0
- - - -
10.0 - 5.0 5.0
10.0 10.0 -
60.0 50.0 10.0 20.0 10.0 5.0 5.0
- - - -
10.0 - 5.0 5.0
30.0 10.0 20.0
60.0 50.0 10.0 20.0 10.0 5.0 5.0
- - - -
10.0 - 5.0 5.0
30.0 10.0 20.0
60.0 50.0 10.0 20.0 10.0 5.0 5.0
90.0 20.0 10.0 60.0
390.0 300.0 45.0 45.0
150.0 70.0 80.0
300.0 250.0 50.0 100.0 50.0 25.0 25.0
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Table 2.3.2: Details of Strategic Plan for the Development of Agriculture Statistics cont’d
GOAL (1): To produce and disseminate comprehensive, integrated, accurate and timely national agricultural statistics in support of national development
STRATEGIC OBJECTIVE/ PURPOSE
ACTIVITIES YEAR 1 US$ ‘000
YEAR 2 US$ ‘000
YEAR 3 US$ ‘000
YEAR 4 US$ ‘000
YEAR 5 US$ ‘000
TOTAL US$ ‘000
1.2 Improve reliability of agriculture statistics data products.
Train professional staff on methods and guidelines
• Recruit 4 relevant consultants for training
• Training 30 professional staff (Hiring of venue, payment of DSA and travelling allowance) for SRID (Hq) and Regional staff.
• Document methods and guidelines
• Organize study tours for 30 professional staff
130.0 60.0 30.0 10.0 30.0
60.0 - 30.0 - 30.0
30.0 - - - 30.0
- - - - -
60.0 30.0 20.0 10.0 -
280.0 90.0 80.0 20.0 90.0
1.3 Improve timeliness in data processing and analysis.
Provide necessary and adequate resources to field staff before start of agricultural season.
• Provide field equipments o 850 Prismatic Compasses o 850 Measuring Tapes o 850 Wellington Boots o 850 Rain Coats o 85 Weighing Scales o 850 Programmable Calculators
• Procure 12 4×4 Pick-up vehicles for SRID(Hq) and 10 regional officers to ensure effective monitoring of field activities
o Provide fuel and maintenance o Provide travel allowances
Reward staff submitting completed questionnaires and data on timely basis.
569.0 39.0 5.0 5.0 3.0 3.0 3.0 10.0 400.0 80.0 50.0
10.0
130.0 - - - - - - - - 80.0 50.0
10.0
150.0 - - - - - - - - 100.0 50.0
10.0
250.0 100.0 - - - - - - - 100.0 50.0
10.0
250.0 100.0 - - - - - - - 100.0 50.0
10.0
1349.0 239.0 5.0 5.0 3.0 3.0 3.0 10.0 400.0 460.0 250.0
50.0
15
Table 2.3.3: Details of Strategic Plan for the Development of Agriculture Statistics cont’d
GOAL (1): To produce and disseminate comprehensive, integrated, accurate and timely national agricultural statistics in support of national development
STRATEGIC OBJECTIVE/ PURPOSE
ACTIVITIES YEAR 1 US$ ‘000
YEAR 2 US$ ‘000
YEAR 3 US$ ‘000
YEAR 4 US$ ‘000
YEAR 5 US$ ‘000
TOTAL US$ ‘000
1.4 Improve reporting of surveys and crop performance monitoring.
An operational database established in all District Directorates.
• Purchase 12 large memory computers for 10 districts and SRID(Hq)
• Purchase database server software at SRID (Hq)
• Purchase Server hardware at SRID(Hq)
• Develop and maintain website to disseminate information at SRID(Hq)
• Obtain and maintain broadband internet connectivity
• Purchase accessories, CD Roms, Pen Drives etc.
• Train staff in the operation of database. Wide Area Network developed and data reports introduced, reported/submitted through internet.
• Engage experts to develop wide area network
• Purchase necessary equipment for WAN development
• Pay annual connectivity
590.0 300.0 90.0 100.0 40.0 30.0 10.0 20.0
200.0 50.0 150.0 -
60.0 - - - 10.0 20.0 10.0 20.0
100.0 50.0 50.0 -
40.0 - - - 10.0 20.0 10.0 -
80.0 30.0 50.0 -
40.0 - - - 10.0 20.0 10.0 - - - - -
40.0 - - - 10.0 20.0 10.0 - - - - -
770.0 300.0 90.0 100.0 80.0 110.0 50.0 40.0
380.0 130.0 250.0 -
16
Table 2.3.4: Details of Strategic Plan for the Development of Agriculture Statistics cont’d
GOAL (1): To produce and disseminate comprehensive, integrated, accurate and timely national agricultural statistics in support of national development STRATEGIC OBJECTIVE/ PURPOSE
ACTIVITIES YEAR 1 US$ ‘000
YEAR 2 US$ ‘000
YEAR 3 US$ ‘000
YEAR 4 US$ ‘000
YEAR 5 US$ ‘000
TOTAL US$ ‘000
1.5 Improve data dissemination and access.
Design a dissemination policy.
• Contract a consultant to develop dissemination policy
• Policy workshop to review policy
• Document/publish and disseminate policy document. Create and Maintain accessible database. Publish all survey/studies reports.
• Annual Documents Arrange with Media and Radio Stations to disseminate data.
• Engage 3 National TV Stations, 10 Regional FM Station.
• Engage 3 National Dailies to disseminate data
10.0 5.0 2.0 3.0 50.0
15.0 15.0 20.0
10.0 10.0
- - - - 20.0
15.0 15.0 20.0
10.0 10.0
- - - - 20.0
15.0 15.0 20.0
10.0 10.0
- - - - 20.0
15.0 15.0 20.0
10.0 10.0
- - - - 20.0
15.0 15.0 20.0
10.0 10.0
10.0 5.0 2.0 3.0 130.0 75.0 75.0 20.0
50.0 50.0
1.6 Strengthen SRID capabilities.
Improve on logistics and transport to SRID.
• Office equipment and materials, fax machines, air conditioners, scanners, softwares, zip disks, larger printers
• 1 Office laptop
• 6 computers(desktops)
• 4 vehicles for trekking o 2 4×4 pickup vehicles. o 2 4×4 patrol vehicles.
Employ adequate qualified and supporting staff. Improve on training opportunities including study tours. Reward quality and promote professionalism.
- Institute national awards for excellence Develop attractive terms and conditions of service.
240.0 55.0 15.0 90.0 30.0 50.0 - 150.0
10.0 -
185.0 - 15.0 90.0 30.0 50.0 - 150.0
10.0 -
- - - - - - - 150.0
10.0 -
20.0 20.0 - - - - - 50.0
10.0 -
- - - - - - - -
10.0 -
445.0 75.0 30.0 180.0 60.0 100.0 - 500.0
50.0 -
17
Table 2.3.5: Details of Strategic Plan for the Development of Agriculture Statistics cont’d
GOAL (2): To develop and maintain a national agricultural statistics database
STRATEGIC OBJECTIVE/ PURPOSE
ACTIVITIES YEAR 1 US$ ‘000
YEAR 2 US$ ‘000
YEAR 3 US$ ‘000
YEAR 4 US$ ‘000
YEAR 5 US$ ‘000
TOTAL US$ ‘000
2.1 Develop a National Agriculture Statistics Database at SRID
Review existing agriculture data and database.
• Contract consulting firm to do review Assess data needs of users of agriculture statistics
• Contract consulting firm to do review Develop an agriculture statistics database program and install on SRID and district computers
• Contract consulting firm to develop the program
• Consulting firm to train database specialists to handle the data program at SRID (Hq) and District MoFA directorates.
Recruit or train database specialists to handle the Agriculture Statistics Database program.
60.0 30.0
30.0 30.0
60.0 50.0 10.0
30.0
- - - -
10.0 - 10.0
20.0
- - - - - - -
20.0
- - - - - - -
20.0
- - - - - - -
20.0
60.0 30.0
30.0 30.0
70.0 50.0 20.0
110.0
18
Table 2.3.6: Details of Strategic Plan for the Development of Agriculture Statistics cont’d
GOAL (2): To develop and maintain a national agricultural statistics database
STRATEGIC OBJECTIVE/ PURPOSE
ACTIVITIES YEAR 1 US$ ‘000
YEAR 2 US$ ‘000
YEAR 3 US$ ‘000
YEAR 4 US$ ‘000
YEAR 5 US$ ‘000
TOTAL US$ ‘000
2.2 Conduct an Agriculture Statistics Sample Census
Design suitable agriculture statistics sample census.
• Technical committee workshops and meetings to prepare census plan, census methodology, census questionnaire, census organization etc
Train field staff and supervisors to carry out field data collection.
• Train field enumerators
• Train field supervisors
• Train data capturers and analysts Procure logistics and equipment.
• Equipment
• Vehicles
• Laptops and accessories Implement agriculture statistics sample census.
• Administration and Publicity
• Monitoring of field activities
• Engagement of casual labour
• Field expenses of young graduates
• Field expenses of enumerators and supervisors
• Data entry, processing and analysis.
• Localized cultivated commodities survey
50.0 50.0
210.0 100.0 50.0 60.0
2,000.0 800.0 1,000.0 200.0
2,032.0 400.0 90.0 103.0 90.0 839.0 10.0 500.0
- - - - - - - - - - - - - - - - - -
- - - - - - - - - - - - - - - - - -
- - - - - - - - - - - - - - - - - -
- - - - - - - - - - - - - - - - - -
50.0 50.0
210.0 100.0 50.0 60.0
2,000.0 800.0 1,000.0 200.0
2,032.0 400.0 90.0 103.0 90.0 839.0 10.0 500.0
19
Table 2.3.7: Details of Strategic Plan for the Development of Agriculture Statistics cont’d
GOAL (2): To develop and maintain a national agricultural statistics database
STRATEGIC OBJECTIVE/ PURPOSE
ACTIVITIES YEAR 1 US$ ‘000
YEAR 2 US$ ‘000
YEAR 3 US$ ‘000
YEAR 4 US$’000
YEAR 5 US$ ‘000
TOTAL US$ ‘000
2.3 Expand coverage of annual crop survey.
Design and implement annual survey to cover (a) Tree crops (b) Vegetables (c) livestock
• Develop questionnaire and train field data collectors
• Field enumerators and supervisors to carry out field data collection
• Submitted data analyzed, report prepared, publicized and disseminated
Design survey to provide data for monitoring and evaluation of government policies and programs related to the agriculture sector.
• Conduct livelihood studies with PPMED to create outcome and impact indicators.
• Conduct studies to determine post harvest losses.
200.0 20.0 150.0 30.0
100.0 50.0 50.0
200.0 20.0 150.0 30.0
100.0 50.0 50.0
200.0 20.0 150.0 30.0 - - -
200.0 20.0 150.0 30.0 - - -
200.0 20.0 150.0 30.0
100.0 50.0 50.0
1000.0 100.0 750.0 150.0
300.0 150.0 150.0
20
Table 2.3.8: Details of Strategic Plan for the Development of Agriculture Statistics cont’d
GOAL (3): To coordinate and supervise a national agricultural statistical system
STRATEGIC OBJECTIVE/ PURPOSE
ACTIVITIES YEAR 1 US$ ‘000
YEAR 2 US$ ‘000
YEAR 3 US$ ‘000
YEAR 4 US$ ‘000
YEAR 5 US$ ‘000
TOTAL US$ ‘000
3.1 Develop a National Agriculture Statistics System
Establish a national agricultural statistical committee. � Quarterly meetings of technical committee � Bi-annual workshop of committee
Establish working relationship amongst agricultural statistical agencies.
� Establish working relationships amongst agricultural statistics agencies
� Undertake assessment trips in statistical establishment in the country.
� Publish Agricultural Statistical bulletins.
5.0 3.0 2.0
10.0 5.0 2.0 3.0
5.0 3.0 2.0
10.0 5.0 2.0 3.0
5.0 3.0 2.0
10.0 5.0 2.0 3.0
5.0 3.0 2.0
10.0 5.0 2.0 3.0
5.0 3.0 2.0
10.0 5.0 2.0 3.0
25.0 15.0 10.0
50.0 25.0 10.0 15.0
3.2 Improve coordination, collaboration, networking and information sharing.
Establish collaboration arrangements, mechanisms for networking and Establish mechanisms for information exchange and sharing.
� Contract consultant to review current system and establish
collaborative, networking and mechanisms for information exchange and sharing amongst statistical agencies.
� Establish collaboration arrangements. � Establish and sustain mechanisms for networking
information exchange and sharing.
40.0 10.0 10.0 20.0
40.0 10.0 10.0 20.0
40.0 10.0 10.0 20.0
40.0 10.0 10.0 20.0
40.0 10.0 10.0 20.0
200.0 50.0 50.0 100.0
21
2.4 Human Resources available
Agricultural statistical system in the country has a decentralized structure as such it involves several ministries departments and agencies which have their own human and material resources. Our investigations reveal that side the SRID of the MOFA all other producers of agricultural statistics have a unit with an average of 5 permanent staff. These other producers of agricultural statistics recruit temporary staff as and when needed.
As at January 2009, the SRID has 35 permanent staff comprising 19 professional staff and 16 supporting staff. The supporting staff includes accountants, administrator, stenographers, technical assistants, drivers, cleaners, watchmen and labourers. The professional staff is in two categories - Professional and Sub-professional. The sub-professional staff is further categorized as production officers and technical officers (Tables 2.4.1 & 2.4.2).
Table 2.4.1: Distribution of SRID Staff by Category
Official Designation Number
Percentage
Comment
Agricultural
Economist*
Production Officer
Technical Officer
All
11 60
4 20
4 20
19 100
*Category include staff with training in Agronomy, Animal Science, Administration, Computer Science, Economics and Agricultural Economics
Table 2.4.2: Distribution of Professional and Sub-Professional Staff by Unit
Unit Agricultural
Economist
Production
Officer
Technical
Officer
Total
Staff
Statistics 9 2 1 12
Marketing 1 2 2 5
Information 1 0 1 2
Total 11 4 4 19
It must be stated that SRID is the apex body at MOFA that co-ordinates the data production in the districts across the country. The district offices of the Ministry of Food and Agriculture have Agricultural Extension Agents (AEAs) who carryout annual surveys, conducted by SRID to estimate area cropped, and yield of major crops produced in the country. When more staff is required for a survey or a census, temporary staff are recruited and trained. A mix of teachers, young graduates from the universities, polytechnics and Agriculture Colleges and also secondary school leavers are usually recruited.
22
2.5 Non-Human Resources Available
The non-human resources available for SRID comprise both physical and non-physical assets which are presented in Table 2.5 below. Table 2.5: Non-Human Resources Available
No Item Quantity Remark
1 A block of 10 offices 1 Not adequate for 19 staff
2 Computer 10 Not adequate
3 Printer 6
4 Photocopier 2
5 Scanner 1
6 Fax machine 1
7 Comb binder 1
8 Telephone line 1 Not adequate
9 Motorola intercom 1
10 Software packages 3 ACCESS, SPSS,WEBAGRIS
11 Internet connectivity 1 Not reliable, not adequate
12 Vehicle (pick up) 5 All are over 6 years old
13 Vehicle (4*4) 3 All are over 10 years old
2.6 Data Dissemination Policy for Food and Agriculture Statistics
Neither the MOFA nor the GSS has a dissemination policy for Food and Agriculture Statistics. However, as and when there is the need to publicize the results of a research, a means is found to do so. The agricultural statistics produced by MOFA directorates are released through formal and informal publications. The informal publications are computer printouts with cover page or no cover page. Currently, all the MOFA statistical publications are issued as computer printout. The formal publications are those that are printed by publishing houses. The publications are available in cycles that range from annually, quarterly, monthly, weekly and occasionally and in the form of Bulletins and Newsletters. The first edition of the “Agriculture in Ghana: Facts and Figures 1991” was printed as a booklet. The subsequent editions have been produced as computer printout. In most cases hard copies of the publications are given out on request; and occasionally, soft copies are sent to users through the electronic mail system. Requests are made by users through writing and visit to the offices of the respective directorates of MOFA and the GSS to request the required statistics which are printed from the computer free of charge. The GSS which is the National Statistical Office receives quite a number of requests for agriculture data. Indeed the GSS is often thought of as the first stop for all types of data including agriculture data. An average of about 10 requests a week is made to the Agriculture Statistics Section for data. Requests are received from various groups including International Organizations, researchers (both within and outside the country), students, and also private and public institutions. Workshops are organized to disseminate and discuss survey results and the metadata to stakeholders. Depending on available resources workshops are organized at zonal, regional or at district levels. It is believed that workshops are the most effective means of dissemination
23
as participant are made to understand the issues better apart from getting the original copies of the publications for reference. Both the electronic and print media have been used at one time or the other, as channels to disseminate agriculture statistics produced by MOFA. The print media did not participate in the dissemination of agricultural statistics until recently. Currently, two local weekly newspapers publish the wholesale and retail price statistics produced by MOFA. Both weekly newspapers, namely, The Investor, and Business and Financial Times, publish the weekly wholesale prices of selected food commodities in the regional capitals and four other places, namely, Obuasi, Tema, Techiman and Mankessim. 2.7 Modalities of promoting User-Producer Dialogue
A user-producer workshop was organized by the FAO and the MOFA in 2006 in order to determine the user needs. Ghana Statistical Service organized a number of meetings in 2002-2003 for users and producers for 10 thematic areas including agriculture, under the umbrella of National Committees for Producer and User of Statistics (NACPUS). The aim was to identify the data needs of users and also the sources of data that were required and to encourage collaboration towards promoting the production and use of agriculture data in the country.
Recently, the GSS has developed a national strategy for the development of statistics in collaboration with other stakeholders of the NSS, of which the ASS is a sub-unit. Under the ASS a five-year strategic plan (2009-2013) was designed that seeks to improve the production and dissemination of agriculture statistics in the country through the collaboration of all stakeholders.
2.8 Existing Databases and Data Dissemination Tools and Platforms
Our investigations reveal that all stakeholders involved in the production and dissemination of agricultural statistics use data management tools ranging from the simple Excel spreadsheets to very sophisticated software that have been developed purposely for use in some particular areas of activity. The list below provides information on the institutions and the type of tools used for managing their information.
• SRID – Excel, MSSQL and Crop and Livestock Database Management System built on Access.
• GSS - Excel, GhanaInfo (Ghana version of Development Info, ), Integrated Management Information System (IMIS), which uses REDATAM +SP to develop a system that is used for the management of Census and survey information.
• Forestry – MSSQL
• Veterinary Services Directorate – Trans-boundary Animal Disease Information System
• Meteorological Services Agency – Climate Database Management System
• Fisheries Directorate – Excel
• Bank of Ghana – Price Index Management Analysis (PRIMA) and the Bank Master
• Ministry of Trade, GSS, Customs Excise and Preventive Service (CEPS), Bank of Ghana use Eurotrace for the management of trade data.
24
Some of the tools listed above especially those designed for particular areas of activity also have dissemination features.
2.9 Regional Integration and International Technical Assistance Received
Ghana is a member of the African Commission on Agricultural Statistics (AFCAS). AFCAS brings together experts working in agricultural statistics from all countries in Africa to discuss developments in the field, review concepts and definitions and also share experiences. The country also participates in activities of some other regional organizations including NEPAD’s Comprehensive Africa Agriculture Development Programme (CAADP), ECOWAS Agricultural Policy (ECOWAP) and the Regional Strategic Analysis and Knowledge Support Systems for West Africa (ReSAKSS WA), which provides support to ECOWAS member countries to monitor progress of the MDGs that are related to food security and agricultural development, poverty reduction and CAADP targets. All the stakeholders in the production and dissemination of agricultural statistics have over the years received some technical assistance from some international organizations including the World Bank, the International Monetary Fund (IMF), the International Food Policy Research Institute (IFPRI), the World Food Programme (WFP), the Canadian International Development Agency (CIDA), and the FAO. In particular, the GSS has in recent times (November 2007 to March 2009) received technical assistance from the Wold Bank to review project documents for the next agriculture sample census and to review census instruments, which will be used. Technical assistance received by SRID from the FAO and the World Bank included Provision of technical assistants (experts) to design survey instruments provision of survey equipment under technical assistant projects and training of human resources through workshops, seminars and conferences.
25
CHAPTER 3
Outputs, Data Sources, and Metadata of Food and Agriculture Statistics
3.0 Introduction
This chapter will review the current agricultural data available in all the subsectors and indicate the methodology, trial of data production and the metadata of the data. The chapter will also identify the data requirements to meet the needs of the various sub sectors and the national, regional and global development programmes.
3.1 Crops Statistics
Crop production statistics in Ghana is produced by the Statistics Research and Information Directorate (SRID) through a Multi Round Annual Crop and Livestock (MRACL) Survey. Commodity prices are collected by market enumerators who read markets either weekly or bi-weekly (depending on number of market days in a week). Currently, prices are collected from 140 markets nationwide. Data on the cocoa and Coffee sub-sector is collected and disseminated by the Ghana COCOBOD. Available data on this sub-sector includes output levels, producer prices and volumes of cocoa and Coffee products produced by processing companies. Available data on the sector is provided in the Table 3.1 below.
26
Table 3.1: Available Data: Crops Sub-Sector
Available Statistics Frequency/
Cycle of
Release and
Date of
Update
Regularity and
Timeliness of
Release
Level of
Disaggregation
Commodity/Item Coverage Comments,
Remarks and
Unavailable
Statistics
1. Crop Production Statistics � Area cultivated � Yield � Production (output)
Annual Annual Annual
Regular/Timely Regular/Timely Regular/Timely
National, Regional and District
Cereals: maize, rice, millet, sorghum, Starchy Crops: yam, cassava, plantain, cocoyam Legumes: cowpea, groundnut, soybean
Final estimates out by end of February (preceding year). Tree crop and vegetable production levels unavailable.
2. Crop Production Budget Statistics � Cereals Production
Budget � Legumes Production
Budget � Vegetables Production
Budget � Tree Crops Production
Budget
Annual Annual Annual Annual
Regular/Timely Regular/Timely Regular/Timely Regular/Timely
Agro-Ecological basis and by technology
Cereals: maize, rice, millet, sorghum, Legumes: cowpea, soyabean, groundnut Vegetables: pepper, okro, tomato, garden eggs Tree Crops: mango, citrus, cashew, oil palm
Final estimates out by end of December (same year).
27
Table 3.1: Available Data: Crops Sub-Sector (cont’d)
Available Statistics Frequency/
Cycle of
Release and
Date of
Update
Regularity and
Timeliness of
Release
Level of
Disaggregation
Commodity/Item Coverage Comments,
Remarks and
Unavailable
Statistics
3. Farm Input Availability and Prices Input Supply
� Volume by types of fertilizer imports
� Volume by type of
agrochemical imports � Volume by type of
locally produced certified seeds
Annual Annual Annual
Irregular/ Untimely Regular/ Untimely Irregular/ Untimely
National National National
Fertilizer Imports: NPK, Sulphate of Ammonia, Urea, Nitrate, Cocoa Fertilizer Agrochemicals: Insecticides, Fungicides, Herbicides, Rodenticides Certified Seeds: Maize, rice, Cowpea, Soyabean
Data availability depends on fertilizer and agro-chemicals companies’ responses to data request. Data may be available by end of first quarter (preceding year).
28
Table 3.1: Available Data: Crops Sub-Sector (cont’d)
Available Statistics Frequency/
Cycle of
Release and
Date of
Update
Regularity and
Timeliness of
Release
Level of
Disaggregation
Commodity/Item Coverage Comments,
Remarks and
Unavailable
Statistics
Input Prices
� Retail prices of fertilizer and agrochemicals
� Retail prices of traditional
farm equipment Farm Credit
� Commercial and secondary bank loans and advances to agriculture
� Commercial banks lending rates to agents
Monthly/ Annual Monthly/ Annual Annual Annual
Regular/Timely Regular/Timely Irregular/ Untimely Irregular/ Untimely
National, Regional National, Regional National -Public Institutions -Private Institutions
Fertilizer: NPK, Urea, Sulphate of Ammonia, Agrochemicals: Karate, Round-up, Dursban, Atrazine, Champion, Gramazone Farm Equipment: Hoe, cutlass, matchets, jute sacks, polysacks
Data available for the major inorganic fertilizers, agro-chemicals and traditional farm equipment. Farm credit to different sub-sectors of agriculture and duration (short, medium and long term) is currently unavailable. Disaggregation to the regional and districts not available.
29
Table 3.1: Available Data: Crops Sub-Sector (cont’d)
Available Statistics Frequency/
Cycle of
Release and
Date of
Update
Regularity and
Timeliness of
Release
Level of
Disaggregation
Commodity/Item Coverage Comments,
Remarks and
Unavailable
Statistics
4. Food Commodity Market Prices � Wholesale market prices
of food crops � Retail market prices of
food crops � Farm Gate prices of
food crops
Monthly/ Annual Monthly/ Annual Monthly/ Annual
Regular/ Timely Regular/ Timely Regular/ Timely
National and 14 major markets National and 14 major markets 10 selected districts
Regional Capital Markets plus Tema and Obuasi � Cereals, Legumes, Starchy
Commodities Regional Capital Markets plus Tema and Obuasi Selected Districts: Tamale, Techiman, Ejura, Hohoe, Mankessim, Tarkwa, Sunyani, Asamankese, Bolgatanga, Wa
Data from 133 markets are compiled for the Annual National Wholesale and Retail Statistics.
5. Food Commodity Imports and Exports � Exports of food
commodities � Value of exports of food
commodities � Imports of food
commodities � Value of imports of food
commodities
Annual Annual Annual Annual
Regular/Untimely Regular/Untimely Regular/Untimely Regular/Untimely
National National National National
Food Commodities: Maize, Rice, Millet, Cowpea, Sorghum, Groundnut
Food imports and exports over land are not adequately captured in the statistics.
30
Table 3.1: Available Data: Crops Sub-Sector (cont’d)
Available Statistics Frequency/
Cycle of
Release and
Date of
Update
Regularity and
Timeliness of
Release
Level of
Disaggregation
Commodity/Item Coverage Comments,
Remarks and
Unavailable
Statistics
6. Farm Production Environment (Climatic Conditions) � Rainfall � Temperatures � Early Warning
(Quarterly Cereals Conditions)
� Processed Crops
Quarterly, Annual Quarterly, Annual Quarterly, Annual Annual
Regular/ Untimely Regular/ Untimely Regular/ Untimely Regular
Agro-meteorological Stations (3-4 Agromet. Stations/Region) National, Regional levels National
Agromet. Stations: Takoradi, Sefwi-Bekwai, Axim, Saltpond, Agona Swedru, Dunkwa, Accra, Ada, Tema, Koforidua, Akim Oda, Abetifi, Ho, Kete-Krachi, Akatsi, Kumasi, Ashanti Mampong, Ejura, Sunyani, Wenchi, Goaso, Tamale, Bole, Salaga, Yendi, Bolgatanga, Navrongo, Manga-Bawku, Wa, Babile Industrial Crops including cocoa, coffee, rubber, cotton, tobacco
31
3.2 Cocoa Statistics
Data in the cocoa subsector is collected and disseminated by the Ghana COCOBOD, an institution directly under the office of the president. Available data on the sub-sector includes output levels, producer prices and volumes of cocoa products produced by processing companies. Detailed information on the subsector is presented in Table 3.2 below
Table 3.2: Available Data: Cocoa Sub-Sector
Available Statistics Frequency/
Cycle of
Release and
Date of
Update
Regularity
and
Timeliness
of Release
Level of
Disaggregation
Commodity/Item Coverage Comments, Remarks and
Unavailable Statistics
1. Total Cocoa Beans and Coffee Production 2. Total World Cocoa and Coffee Production 3. Total Cocoa and Coffee and Shipment 4. Cocoa and Coffee Producer Price
Annual Annual Annual and Monthly Annual Annual/ Occasional
Regular/ Timely -do- -do- -do-
National, Regional & Districts By Crop Seasons International/ National By Destinations (Countries) By Port of shipment: Tema, Takoradi By Processing Companies
Cocoa and Coffee Beans Cocoa and Coffee Beans Cocoa Beans, Cocoa Butter, Cocoa Liquor, Cocoa Cake & Cocoa Powder and Coffee Beans Cocoa and Coffee Beans
% of Ghana’s production in World production is calculated from 1 & 2 Reviewed in the course of the year when very necessary
32
Table 3.2: Available Data: Cocoa Sub-Sector (cont’d)
Available Statistics Frequency/
Cycle of
Release and
Date of
Update
Regularity
and
Timeliness
of Release
Level of
Disaggregation
Commodity/Item Coverage Comments, Remarks and
Unavailable Statistics
5. Cocoa and Coffee Farmer Share of World Market Price 6. Volume of Cocoa Beans and Coffee Processed Locally 7. Volumes of Cocoa and Coffee Products Produced 8. Total Revenue From cocoa and Coffee 9. Government Export Duty Payment 10. Government Bonus Payments
Annually, Monthly Annually, Monthly Annually Annually Twice Annually
Regular/ Untimely Regular/ Timely -do- -do- -do- -do-
National Producer Price: Nominal National National, By Processing Companies National, By Processing Companies National National National
Cocoa and Coffee Beans Cocoa and Coffee Beans Cocoa Butter Cocoa Liquor Cocoa Cake Chocolate Cocoa Powder Cocoa Beans Cocoa and Coffee Beverages Cocoa and Coffee Beans Cocoa and Coffee Beans
Reviewed in the course of the year when very necessary Export Duty from Cocoa Butter, Cocoa Liquor & Cocoa Cake unavailable at COCOBOD. Could be Available at CEPS Bonus Payment applies to only Main Crop Season
33
3.3 Statistics on Irrigation
Activities relating to irrigation of available lands and pastures are under the control of the Ghana Irrigation Development Authority (GIDA). A number of irrigation schemes are located at various parts of the country. Data on production from these schemes are available at GIDA. See Table 3.3 below. Table 3.3: Available Data: Irrigation
Available Statistics Frequency/
Cycle of
Release and
Date of
Update
Regularity
and
Timeliness
of Release
Level of
Disaggregation
Commodity/Item Coverage Comments, Remarks and
Unavailable Statistics
1. Inventory of Irrigation Schemes 2. Production from Irrigated Schemes
Annual/ Quarterly Annual/ Quarterly
Regular/ Timely Regular/ Untimely
National, Regional and District Size of Schemes State of Scheme -Rehabilitated -New Schemes National, Regional and District By Type of Scheme
Commodity: Rice, Vegetables (i) Existing GIDA Schemes (ii) Small Farms Irrigation Projects (iii) Small-scale Irrigation Development Project (SSIDP) Commodity: Rice, Vegetables Scheme Types: � Gravity � Furrow Pump � Furrow + Sprinkler
Estimates of potential and actual irrigable areas and outputs are available.
34
Table 3.3: Available Data: Irrigation (cont’d)
Available Statistics Frequency/
Cycle of
Release and
Date of
Update
Regularity
and
Timeliness
of Release
Level of
Disaggregation
Commodity/Item Coverage Comments, Remarks and
Unavailable Statistics
3. Inventory of Dams and Dugouts 4. Production from Dams and Dugouts
Periodic Annual
Regular/ Timely Regular/ Untimely
National, Regional, Districts By Type: � Dam � Dugouts National, Regional, Districts
Crops: Rice, Vegetables Livestock Watering: � Cattle numbers � Sheep/Goats numbers Commodity: Rice, Vegetables
Production statistics from dam and dugouts are obtained from MOFA Extension Agents.
35
3.4 Livestock Statistics
The Veterinary Services Directorate of the Ministry of Food and Agriculture has the responsibility for monitoring developments in the Livestock Sub-sector. They undertake activities relating to disease control and also surveys/censuses to determine the animal population, disease prevalence, movement of livestock, trade in livestock (imports and exports) and animal slaughter. By their activities they are able to generate livestock data which they publish and disseminate to stakeholders. Table 3.4 presents in a matrix form the available statistics on the Sub-sector
Table 3.4: Available Data: Livestock Sub-Sector
Available statistics Frequency/
Cycle of
Release and
Date of
Update
Regularity and
Timeliness of
Release
Level of
Disaggregation
Commodity/item coverage Comments,
remarks and
Unavailable
statistics
1. Livestock Numbers/population
Annual Regular /untimely But the activity was discontinued in 1996 when the Unified Extension came into being.
District/ Regional National
Cattle (breed, Age & Sex group) , sheep, goats, swine (exotic & indigenous), poultry (layers, broilers, cockerels, local fowls, ducks, turkeys, guinea fowls, pigeons, parrots, ostrich), donkey, horses .dogs, cats,
Non-conventional livestock (grasscutter, snail, bees etc)
2. Scheduled (notifiable) disease Outbreaks
Immediately the disease outbreak occurs
Regular/timely especially when the disease is transboundary in nature District reports to National Director and copied to Region
Non-transboundary Disease: District/ Regional National
26 Scheduled Diseases: Rinderpest Contagious Bovine Pleuropneumonia (CBPP) Anthrax Rabies Newcastle Disease Fowl Pox Trypanosomiasis Mange Tuberculosis Black Quarters
Transboundary diseases:
36
Available statistics Frequency/
Cycle of
Release and
Date of
Update
Regularity and
Timeliness of
Release
Level of
Disaggregation
Commodity/item coverage Comments,
remarks and
Unavailable
statistics
Director report to OIE (World Animal Health Organization) AU-IBAR(African Union-Inter Bureau of Animal Resources)
Swine Erysipelas Lumpy Skin Disease Foot And Mouth Dermatophilosis Peste des Petits Ruminants (PPR) African Swine Fever Highly Pathogenic Avian Influenza African Horse Sickness Sheep And Goat Pox Brucellosis Haemorrhagic Septicaemia Glanders Fowl Typhoid Fowl Cholera Gumboro Marek’s Disease Pullorum Contagious Pustular Dermatitis (Orf)
3. Disease Treatment Monthly/ Annual
Regular/Untimely District/Regional, National
Cattle, sheep, goats, pigs, poultry, horses/donkeys
- Immunisation/ Prophylactic Treatment
Monthly/Annual
Regular/Untimely
District/Regional, National
Vaccination against the following disease. PPR in sheep and goats CBPP in cattle Anthrax in cattle, sheep, goats and
37
Available statistics Frequency/
Cycle of
Release and
Date of
Update
Regularity and
Timeliness of
Release
Level of
Disaggregation
Commodity/item coverage Comments,
remarks and
Unavailable
statistics
Deworming/Dipping/ Spraying/Dusting of Livestock and Poultry
Monthly/Annual
Regular/Untimely
District/Regional, National
pigs. Rabies in dogs, cats and monkey Newcastle Disease in poultry Fowl pox in poultry Marek’s disease in poultry Gumboro disease in poultry Brucellosis in cattle Trypanosomiasis in cattle Cattle, Sheep, Goats, Pigs, Horses/Donkeys
4. Castration of livestock
Monthly/Annual
Regular/Untimely District/Regional, National
Cattle, Sheep, Goats, Pigs, horses/donkeys
5. Local movement of Livestock
Monthly/Annual
Regular/Untimely District/Regional, National
Cattle, Sheep, Goats, Pigs/Donkeys
6. Local slaughter of Livestock
Monthly/Annual
Regular/Untimely District/Regional, National
Cattle, Sheep, Goats, Pigs and others (Dog, Donkey)
Unofficial, slaughtering data not available
7. Pathological conditions from meat inspection
Monthly/Annual
Regular/Untimely District/Regional, National
Antemortem findings Postmortem findings
8. Vaccine utilized Monthly/Annual
Regular/Untimely District/Regional, National
Vaccines
9. Revenue Generated from provision of service
Monthly/Annual
Regular/Untimely District/Regional, National
Money & cheques
38
Available statistics Frequency/
Cycle of
Release and
Date of
Update
Regularity and
Timeliness of
Release
Level of
Disaggregation
Commodity/item coverage Comments,
remarks and
Unavailable
statistics
10. Live Animal import
Monthly/Annual
Regular/Untimely District/Regional, National
Imported Live Animals Cattle, Sheep, Goats, Pigs and Horses
Origin of Imports not available
11. Imports of poultry and poultry products
Monthly/Annual
Regular/Untimely District/Regional, National
Poultry Imports: Day old Chick Parent stock Layer day old chick Broiler day old chick Turkey poult Hatching eggs
Origin of Imports not available
12. Meat Imports Monthly/Annual
Regular/Untimely District/Regional, National
Meat & Milk Imports: Beef, Buffalo, Mutton, Chevron, pork, processed meat& milk
Origin of Imports not available
13. Exportation of livestock, wildlife, poultry and their products
Monthly/Annual
Regular/Untimely District/Regional, National
Wildlife Reptile, insects, amphibians, crustacean Pets Parrots, dogs, cats Others drumskins
Destination of Exports not available
39
3.5 Fisheries Statistics
Fisheries statistics is produced by the Directorate of Fisheries of the Ministry of Food and Agriculture. There are two main sources of fish production in the country namely marine and inland. The directorate monitors activities to determine total fish catch and inputs used. Aquaculture is a new development in the country and has very scanty and uncoordinated information. Table 3.5 has information on both marine and inland statistics available. Table 3.5: Available Data: Fisheries Sub-Sector
Available
Statistics
Frequency/
Cycle of Release
and Date of
Update
Regularity and
Timeliness of
Release
Level of
Disaggregation
Commodity/Item Coverage Comments,
Remarks and
Unavailable
Statistics
1. Marine:
(a) Total Marine Fish Production (b) Total Fish Stock Position (c) Total Fish
Annual/Monthly (April of preceding year) Annual/Monthly Quarterly/Annual
Regular/ Untimely Regular/ Untimely Regular/
National, Regional and Landing Sites By Seasons: Fish Stock by Fish
Types: (i) Fish Imports stocked at Tema Cold Stores (ii) Local Fish
By Canoes, Inshore Vessels (purse seine, trawlers), Industrial Vessels, Shrimp Vessels, Paired Vessels, Tuna Vessels Major (June-Sept), Minor (Dec-Feb) and Lean (March-May/Oct-Nov) Fish Types: (i) Red Pandora (Yiyiwa) (ii) Sea Potrams (Sikasika) (iii) Cuttle fish (iv) Sole
Internal Fish Distribution not Available Internal Fish Stock Position and Storage Capacity (service capacity) of cold stores not available.
40
Available
Statistics
Frequency/
Cycle of Release
and Date of
Update
Regularity and
Timeliness of
Release
Level of
Disaggregation
Commodity/Item Coverage Comments,
Remarks and
Unavailable
Statistics
Imports (d) Total Fish Exports (e) Registered Vessels (f) Licensed Vessels (g) Positional Analysis (Vessels Statistics)
Quarterly/Annual Annually Annually Periodic (4-5yrs.)
Untimely Regular/ Untimely Regular/ Untimely -do- Irregular
Production at Landing Beaches Fish Imports by Fish Types: Fish Exports: � Raw � Processed National, Regional and Landing Sites -do- -do-
-do- Tuna, Fish, Shrimps Types of Vessels
2. Inland
Total Inland Fish Production and Productivity � Aquaculture,
Small-scale and Subsistence
Annual/ Quarterly -do-
Regular/Untimely -do-
National, Regional -do-
Total Fish Farms, Ponds and Pond Surface Area Fish Type: Tilapia, Catfish Total No. of Commercial Farms and surface area Fish Type: Tilapia, Catfish
41
Available
Statistics
Frequency/
Cycle of Release
and Date of
Update
Regularity and
Timeliness of
Release
Level of
Disaggregation
Commodity/Item Coverage Comments,
Remarks and
Unavailable
Statistics
� Commercial
Farms � Reservoirs
-do-
-do-
-do-
Census of Reservoirs Reservoirs Surface Area Fish Type: Tilapia, Catfish
42
3.6 Forestry Statistics
The Forestry Commission under the Ministry of Mines and Natural Resources has the responsibility of producing forestry statistics via administrative records. Available statistics on the sub-sector are Export of Wood Products, National Forest Plantation Development, Production of Round Logs and Production of Wood Products. See Table 3.6 below
Table 3.6: Available Data: Forestry Sub-Sector
Available Statistics Frequency/
Cycle of
Release
Regularity and
Timeliness of
Release
Level of
Disaggregation
Commodity/Item Coverage Comments, Remarks
and Unavailable
Statistics
FORESTRY
Export of Wood Products
Monthly
Delay of at least 2 months
International, National
International, National
Statistics broken down into numerous tables and figures
National Forest Plantation Development
Yearly -do- National, Regional
Regional programmes and activities
Statistics presented in several tables
Production of Round Logs
Yearly -do- National National
Production of Wood Products
Yearly -do- National National
43
3.7 Water Resources
The country abounds in quite a number of water resources. The major ones include: (i) Lakes and lagoons: the Volta and Bosumtwi Lakes; Keta and Korle Lagoons. (ii) Waterfalls: the Boti, Kintampo and Wli. (iii)Dams: Vea, Tono, Weija and Kpong. (iv) Rivers: White and Black Volta, Oti, Densu and Pra.
The Ministry of Environment Science and Technology (MEST) handles the policy issues of water resources in the country, however, the Water Research Institute (WRI) of the Council for Scientific and Industrial Research (CSIR) conducts the major water resource research activities. Agricultural related information at the WRI are contained in the following reports:
(a) Catchment Areas and River Lengths of Major Basins in Ghana (b) Operational Data on Water Resources Projects in Ghana (c) Survey of Water Use for Agriculture and Rural Development (d) Assessment of Water Yields of Dawhenya and Ashiaman Reservoirs (e) Development of Improved Water Management Systems for Rice Production in Valley
Bottoms in Ghana (5 Vols: Aframso/Besease/Godenu/Yepeligu/Kpong) (f) Status Report on the Pilot Scheme in Groundwater Utilization in the Accra Plains (g) Hydrology of Waterfalls in Ghana (h) Preliminary Physico-Chemical Studies of Lagoons along the Gulf of Guinea in Ghana
The Ghana Meteorological Agency (GMA) under the Ministry of Transport and Communications provides the climate and weather services to the Government and other identifiable stakeholders. The statistics produced by the GMA include: 1. Climatological Data
� Temperature – maximum and minimum (daily) � Wind (daily) � Relative Humidity (daily) � Sunshine - Direction and Duration (daily)
2. Agro-Meteorological Data � Rainfall – Volume and number of rain days (monthly, yearly) � On-set of Rains � Rainfall Distribution (monthly, yearly)
3.8 Land Use
The total land area of Ghana is about 23,853,900 hectares. Out of this, 13,628,179 hectares representing 57.1% is classified as agricultural land (Table 3.8). Agricultural production is generally dependent on rainfall, although an estimated 6,000 farm enterprises nation-wide were using some means of irrigation. As at 2007, the total area under formal irrigation was around 34,000 hectares whereas the potential area – including inland valleys – that could be developed for irrigation is estimated at 500,000 ha. The Ghana Irrigation Development Authority (GIDA) in 2000 identified 32,000 hectares of under-developed inland valleys throughout the country that could benefit from moisture improvement technologies for food production.
44
Table 3.8: Land Use (Specific to Agriculture)
Type of Land Use Hectares %
Total Land Area (T.L.A.) Agric. Land Area (A.L.A.) Area under cultivation (2007) Total area under irrigation (2007) Area under inland waters Others (forest reserves, savannah woodland, etc)
23,853,900 13,628,179
7,248,000 33,778 1,100,000 9,125,721
100.0 57.1
30.4 0.14
4.6 38.3
Sources: The Ghana Survey Dep’t and MOFA, Accra Note: Percentages will not add up to 100, because area under cultivation is part of agric. land area, while area under irrigation is part of area under cultivation. The principal agricultural produce are:
• Industrial Crops: Cocoa, Oil Palm, Coconut, Coffee, Cotton, Kola, Rubber.
• Starchy Staples: Cassava, Cocoyam, Yam, Maize, Rice, Millet, Sorghum, Plantain.
• Fruits and Vegetables: Pineapple, Citrus, Banana, Cashew, Pawpaw, Mangoes, Tomato, Pepper, Okra, Egg Plant, Onion, Asian Vegetables
45
3.9 Food availability for human consumption, External Trade, Population
3.9.1 Food Security
Ghana’s food self-sufficiency ratio for cereals and starchy staples is considered satisfactory. The food self sufficiency ratio for cereals is estimated at 85% except rice (40%) and almost 100% for starchy staples. The country most often has food surpluses of its staples – maize, cassava, plantain, cocoyam and yam and the Ministry of Food and Agriculture (MOFA) is proposing the establishment of national strategic food security stocks to serve as a check against disasters as well as stabilize the price of food during the lean season. Table 3.9.1 below, shows the domestic food supply and demand position for Ghana in 2008.
Table 3.9.1: Domestic Food Supply and Demand Position 2008
Crop
Total
Domestic
Production
('000 Mt)
Production
Available for
Human
Consumption*
(000 Mt)
Per Capita
Consumption
(Kg/Annum)
Estimated
National
Consumption
('000 Mt)
Deficit/
Surplus
('000 Mt)
Maize 1,244.9 871.4 43.8 1,024.9 (153.5)
Rice (Paddy) 297.1 237.7 - - -
Rice
(Milled)** 178.26 142.6 15.1 353.3 (210.7)
Millet 193.8 135.7 6.4 149.8 (14.1)
Sorghum 331.0 231.7 10.1 236.3 (4.6)
Cassava 9,358.7 6,551.1 152.9 3,577.9 2,973.2
Yam 4,878.0 3,902.4 41.9 980.5 2,921.9
Plantain 3,179.9 2,702.9 84.8 1,984.3 718.6
Cocoyam 1,596.6 1,277.3 57.1 1,336.1 (58.9)
Groundnut 470.1 399.6 12.0 280.8 118.8
Cowpea 179.7 152.7 5.0 117.0 35.7
46
The excess demand of cereals is often met by imports from both ECOWAS sub-region and other parts of the world over the years. In addition, some processed foods are also imported to supplement the nutrition requirements. Table 3.9.2 shows the volume and value of imports of cereals into the country from 1999 to 2007.
Table 3.9.2: Quantity and Value of Cereal Imports (1999 – 2007)
Year Wheat Rice Maize Sorghum
1999 Quantity (Mt) 181,645 241,610 201.21 -
Value $ million 102.7 95 0.07 -
2000 Quantity (Mt) 196,700 187,256 5,050 819
Value $ million 72.03 65.03 0.73 1.18
2001 Quantity (Mt) 168,816 311,513 10,589 4,040
Value $ million 64.25 72.46 1.52 2.75
2002 Quantity (Mt) 182,681 296,953 10,470 5,135
Value $ million 78.59 68.85 2.08 2.25
2003 Quantity (Mt) 147,779 797,705* 163 193
Value $ million 50.7 124.66 0.07 0.002
2004a Quantity (Mt) 247,991 253,905 140 2.6
Value $ million 84.32 119.15 0.086 0.77
2005a Quantity (Mt) 369,733 484,513 54,965 n.a.
Value $ million 99.69 138.94 12.31 n.a.
2006a Quantity (Mt) 254,052 389,660 6,572 0.58
Value $ million 46.37 159.47 1.43 n.a.
2007a Quantity (Mt) 332,299 442,073 596 n.a.
Value $ million 111.38 157.86 0.21 n.a.
Source: Ministry of Trade & Industry, Accra. a Figures from GSS. * Part of this amount may have been trans-shipment to neighbouring countries. However, this could not be
ascertained from the MOTI, PSI.
In terms of daily energy requirement, the carbohydrate, fats and oils available per capita have generally been higher but below for protein, fruits and vegetables (Table 3.9.3).
47
Table 3.9.3: Daily Energy Requirement Position
Type of food Requirement Availability Situation
Carbohydrates 2,218 kcal 3,500 kcal +
Protein 288 kcal 240 kcal -
Fat and Oil 230 kcal 250 kcal +
Fruits and Vegetables 144 kcal 90 kcal -
3.9.2 External Trade in Agriculture
Ghana engages several countries in trade in agricultural commodities - exporting commodities with surplus domestic supply mainly roots and tubers and importing mainly cereals to meet excess domestic demand. Almost all agricultural machinery and inputs such as fertilizers and pesticides are imported. Agricultural trade balance over the years has been positive mainly because of exports of cocoa, which the principal export commodity of the country is. Indeed, the value of cocoa export alone constitutes over 70% of the total value of agricultural exports. 3.9.3 Population
As at March 2000, when the last census was held in Ghana, the population head count was 18,912,079. This was an increase of 53.8 per cent over the 1984 population of 12,296,081 representing an annual average growth of 2.7 per cent. The sex breakdown gives a sex ratio of 97.9 percent compared with 97.3 in 1984; and the population density was 79.3 persons per square kilometre. There were about 3.7 million households with 52.8 percent in the rural areas as against 64 percent recorded in 1984. The total number of the economically active population was about 8.3 million with 4.2 million (50.6%) being males; and about 89 percent of them, made up of 50.5% male and 49.5% female, were employed at the time. Out of the total working population, 53.1 percent were in the agricultural sector with about 43.8 percent residing in the urban areas. Table 3.9.4 presents some macro-economic indicators recorded in 2008 Table 3.9.4: Macro-economic indicators (2008)
Indicator National Agriculture Non-agriculture
GDP (GH ¢) 795.1 267.1 528.0
GDP real growth (%) 7.3 5.1 8.4
Employment (number of people)
7,428,374 53.1 46.9
48
3.9.4 Agricultural Inputs
Farmers in Ghana use a wide range of agricultural inputs in their operations. The major ones include fertilizers, pesticides and machinery. Both family and hired labour used. Table 3.9.5 below shows the cost of input from 2003 to 2008.
Table 3.9.5: National Average Input Prices (GH ¢)
Input Unit 2003 2004 2005 2006 2007
2008
15-15-15 50kg 14.95 18.87 20.22 20.44 21.72
36..31 Sulphate of Ammonia 50kg 10.99 14.22 15.80 17.54 18.10
28.12
Urea 50kg 14.22 18.94 22.94 24.56 25.82
37.13
Round Up 1 litre 6.07 7.06 6.73 6.60 6.24
8..93
Karate 1 litre 7.88 7.91 6.92 6.94 7.10
8.28
Actellic 1 litre 10.79 15.00 14.88 12.83 12.82
11..35
Hoe Single 1.12 1.24 2.38 1.73 2.03
2.26
Cutlass Single 2.56 2.71 3.37 3.37 4.08
3.65
Jute Sac Single 0.80 0.75 0.82 0.89 0.86
0.88
Source: SRID, MOFA
Note: Dollar-Ghana Cedi exchange rate, mid 2008 is 1:1.0166 3.9.5 Credit Support Agriculture
Although agriculture is considered as the dominant sector of the economy, the amount of loan advances to the sector by both commercial and secondary banks is relatively low compared with other sectors such as manufacturing, commerce and services. This is because the banks consider agriculture as a risky venture. See Table 3.9.6a and Table 3.9.6b. As at October 2008 the number of licensed banks operating in the country stood at 26 with branches throughout the country. The number of banks operating in various regions of the country is presented in Table 3.9.6c.
49
Table 3.9.6a: Commercial Banks Loans and Advances (%)
End of
Period
Agric.
Forestry
& Fishing
Mining
& Quar-
rying
Manu
fact-u
ring
Const-
ruction
Electri-
city, Gas
& Water
Commerce & Finance
Import Export Other
Trade Trade
Trans-
port &
Commu-
nication
Ser-
vices
Mis-
cella
neous
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
3.2
2.2
1.6
1.0
10.4
2.1
0.7
1.9
2.6
2.0
7.3
5.5
7.3
4.6
4.4
3.7
4.4
2.5
2.8
2.7
27.5
29.1
32.4
21.6
21.0
17.5
8.0
18.9
18.2
16.3
10.8
12.8
7.3
4.0
7.4
6.3
5.9
3.3
3.1
3.8
1.6
5.7
5.1
3.1
4.3
4.8
0.1
3.6
1.7
1.9
5.0
5.2
4.4
3.6
3.9
3.8
0.2
5.4
7.5
5.1
6.9
2.4
2.5
2.0
2.6
3.3
0.2
2.0
1.5
1.1
20.6
18.0
18.0
11.3
31.8
36.0
54.1
30.3
31.7
33.9
1.3
2.1
2.7
1.4
3.8
4.6
2.7
7.3
4.2
5.1
13.0
11.1
11.9
7.6
10.3
11.1
23.2
12.2
13.2
18.3
2.8
6.0
6.9
3.2
-
6.7
0.6
12.5
13.4
9.7
Source: Ghana Statistical Service; Quarterly Digest of Statistics
Table 3.9.6b: Secondary Banks Loans and Advances (%)
Source: Ghana Statistical Service; Quarterly Digest of Statistics.
End of
Period
Agric.
Forestry
& Fishing
Mining
& Quar-
rying
Manu-
fac-
ring
Cons-
truc-
tion
Electri-
City Gas
& Water
Commerce & Finance
Import Export Other
Trade Trade
Trans-
port &
Commu
nication
Ser-
vices
Mis-
Cella
neous
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
20.2
22.2
23.2
11.0
23.2
10.8
0.1
13.9
10.1
10.6
3.2
4.6
4.1
2.4
4.4
2.6
2.0
2.7
3.2
6.0
18.6
20.2
16.5
8.4
22.5
13.7
27.1
19.8
22.6
21.0
9.5
9.6
10.8
3.6
8.0
4.7
5.6
12.5
8.3
8.4
1.6
2.7
3.3
2.5
1.8
2.2
4.8
2.1
2.5
3.0
4.1
5.8
4.5
1.9
5.3
4.7
9.7
8.3
8.2
7.2
1.3
1.5
3.9
1.0
2.5
1.1
4.6
6.6
4.5
3.0
28.7
18.4
15.6
5.1
8.8
6.3
10.6
8.9
15.2
13.8
1.9
2.1
2.6
2.0
3.6
4.5
4.2
3.4
3.9
3.6
5.9
6.2
6.4
3.6
6.9
3.0
7.1
8.9
13.9
17.2
4.8
6.8
9.2
5.7
12.8
46.5
24.3
12.9
8.1
6.7
50
Table 3.9.6c: Basic Information on Banks in Ghana
NO.
Banking License Category
Year
Established
Number of
Branches**
Geographical
Distribution
of Banks
1.
General Banking License
Barclays Banks of Ghana Ltd.
1917
141
All Regions
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
Class I Banking License(universal)
Ghana Commercial Bank Ltd. International Commercial Bank Ltd. Metropolitan & Allied Bank (Gh) Ltd. SG-SSB Bank* Stanbic Bank Standard Chartered Bank Ghana Ltd. The Trust Bank Ltd. Unibank Ltd. Amalgamated Bank Ltd. CAL Merchant Bank Ltd. ECOBANK Ghana Ltd. First Atlantic Merchant Bank Ltd. Merchant Bank (Gh) Ltd. HFC Bank Agricultural Development Bank Ltd. National Investment Bank Ltd. Prudential Bank Ltd. ARB Apex Bank Fidelity Bank Guaranty Trust Bank Intercontinental Bank United Bank of Africa Zenith Bank (Ghana) Ltd Bank of Baroda Banque Sahelo-Saharienne Pour L’Investissement et le Commerce (BSIC)
1953 1996 1995 1973 1999 1894 1995 2000 1999 1990 1990 1995 1972 2003 1965 1963 1994 2001 2006 2005 2006 2004 2005 2008 2008
144 11 9 39 12 19 16 12 11 12 30 5 14 11 51 25 13 10 8 6 12 18 9 1 1
All Regions 4 Regions 2 Region All Regions 3 Regions 5 Regions 3 Regions 2 Regions 4 Regions 3 Regions 5 Regions 2 Regions 5 Regions 2 Regions All Regions All Regions 3 Regions 2 Regions 3 Regions 4 Regions 5 Regions 4 Regions 1 Region 1 Region
Source: Bank of Ghana
*Formerly known as SSB Bank Ltd.
** Number of banks as at 31st October 2008.
In addition to the above indicated banks, there are some 116 Rural and Unit Banks operating in the rural and
peri-urban setting engaged in deposit mobilization and loan/advances delivery. Again a number of Non-Bank
Financial Institutions abound in Ghana. These are helping in various areas in the agricultural sector. For
example, of the latter is the Export Finance Company Limited providing the following services:
1 Pre and Post-Shipment Credit Schemes
2 Export Refinance Schemes
3 Export Credit Guarantee Scheme
4 Export Insurance Schemes and advisory service
51
3.9.6 Economic
Agricultural value added over the past five years i.e. 2004 – 2008 average 4.8 percent. This represents about 34 to 37 percent contribution to the national Gross Domestic Product (GDP). The cocoa sub-sector alone contributes an average of 9.3 percent to GDP over the period, whereas the average growth rate for the fisheries and forestry sub-sectors average about 5.6 percent and 3.6 percent respectively. For the period 2004-2008 the agriculture sector grew at a yearly average of 4.8 compared with 8.5 for the Non-agricultural sector. See Table 3.9.7 Table 3.9.7: Real Agricultural And Non-Agricultural
Gross Domestic Product (GDP) Growth Rates (2004 - 2008)
Item 2004 2005 2006 2007 2008
Agriculture Sector 7.0 4.1 4.5 3.1 5.1
Crops 3.87 2.97 3.15 3.6 5.22
Livestock 0.43 0.33 0.35 0.40 0.58
Cocoa Production and Marketing 29.9 13.2 2 -3.5 5
Forestry and Logging 4.2 5.6 2.6 2.5 3.5
Fishing 6.2 -1.2 15 5 3
Non-Agriculture 11.6 7 8.1 5.6 10.2
All Sectors 5.6 5.9 6.4 5.7 7.3
3.10 Description of national and sub-national commodities codes system
The Country does not have its own commodities codes; as such it adopts those that have been designed by the international organizations. Some of the coding systems that have been used over the years include the FAO codes – for agriculture surveys and censuses; the International Standard Industrial Classification (ISIC) and the Harmonized System (HS) – used at different times for trade statistics; Classification of Individual Consumption by Purpose (COICOP) and Central Product Classification (CPC) – used at different times for price statistics. 3.11 Metadata for Available Agricultural Statistics
The metadata for the identified available agricultural statistical data presented in this chapter is discussed in the matrices presented in appendix 1 and under the items of unit of measure, agency compiling data contact for additional information and information to copyright. In addition, the methods used in collection and revision, calculation and estimation of the statistics as well as the quality of data including error sources and accuracy of statistics are discussed.
52
CHAPTER 4
OVERVIEW OF USER NEEDS FOR FOOD AND AGRICULTURE
STATISTICS – GHANA
The agricultural sector has been noted to lack the required information that will (a) enable detailed understanding about the performance and contribution of the agricultural sector and sub-sectors, and (b) relate to the objectives and goals of the government and global development programmes including outcomes and impact. The Agricultural Statistics requirements are discussed by looking at the unavailable statistics needed to assist in (a) examining the Agricultural Sub-sectors (Crops, Cocoa, Livestock, Fisheries, Forestry) policies and programmes, (b) monitoring and implementing the National Food and Agricultural Sub-sector Development Programmes (FASDEP II) and the Growth and Poverty Reduction Strategy (GPRS) of the government, and (c) monitoring, implementing and evaluating global development programmes (CAADEP and MDGs) including outcomes and impacts. Relevant data required for the three areas (listed A, B, C and D) are presented in Tables 4.1, 4.2, 4.3, 4.4 and 4.5 below. 4.1 Public Sector Decision Makers
The principal public sector user of agricultural statistics is the Executive through the following institutions:
� The National Development Planning Commission � The Ministries Departments and Agencies � Regional Coordinating Councils and District Assemblies � Research Institutions, Academia � Development Partners and International Organizations � Public Media Houses
4.2 Private Sector Decision Makers
� Industries � Farmers � Traders, Marketing organizations and Agencies � Academic/Research Institutions � NGO’s
4.3 Limitations of the available Food and Agriculture Statistics
� Crop: Not disaggregated fully by small admin units and by sex of producers � Livestock: The available statistics on livestock production are very few and mainly on
the population of selected conventional animal species, namely, cattle, sheep, goats, pigs and poultry (chicken). Data not disaggregated by Districts and Ecological zones
� Fisheries: The available fish production statistics are mainly on catch disaggregated by location of marine and inland waters. The statistics are available annually but the release is untimely.
� Aquaculture fish production is being promoted in the country but the statistics of production is not available.
� Forestry: Data not regular and not disaggregated by small admin units.
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It must be noted that the required data may be relevant for all the three (3) discussed areas. The consultants hence will attempt not to repeat already mentioned required data in all the three (3) discussed areas. A. Unavailable Statistics for the Agricultural Sub-sectors
Unavailable statistics which are very necessary for policy decisions in the agricultural sub- sectors are indicated in Table 4.1 below;
Table 4.1: Required Agricultural Statistics for Monitoring the Agricultural
Sub-Sector
Required Agricultural
Statistics
Level of Disaggregation Source/Method
to obtain
Statistics
Proposed
Responsible MDA
required to provide
Information
Crop Subsector: � Tree Crop, Fruit and
Vegetable Production Statistics
� Post-Harvest Losses, Buffer and Strategic Stock
� Crop Budget
� Percentage increase in Agro-Processing, Agro-Business Enterprise and Micro Enterprise Registration
� Credit to Sub-sectors of Agriculture
� Farm and Non-Farm Household Income
� Input Outlets and Sale
Points � Input Supply
o Volume of Organic Fertilizer
o Volume of Certified
& Improved Seeds, Seedlings and Planting Materials
-National, Regional, Districts -Commodity -Storage, Marketing and Household Losses -Ecological Levels -National, Regional, Districts -Gender -National, Regional, Districts -Commodity -Gender -National, Regional -Ecological Zones -National, Regional, Districts -National, Regional, Districts -National, Regional, Districts -Commodity � Oil Palm Seedlings � Citrus Seedlings � Plantain
Survey Study Expand Crop Coverage Survey Administrative Records GLSS Reports Survey Survey Liaise with relevant Directorates, Project Coordinators
MOFA/SRID MOFA/AESD/ PPMED MOFA/SRID MOFA/SRID/DADU Bank of Ghana GLSS-GSS MOFA/SRID/CSD MOFA/SRID/CSD MOFA/SRID/ PPRSD/CSD
54
� Yam � Cassava � Pineapple
� Food Imports and
Exports over land
-Regions and Districts
Develop survey instruments for commodity movement data
MOFA/SRID/MOTI
Livestock Subsector: � Non-Conventional
Livestock Production
� Live Animals Imports � Livestock Productivity � Local Slaughter of
Livestock � Livestock Feed
Production
-National, Regions, Districts � Type
o Grasscutter o Guinea Fowl o Rabbit o Ostrich o Snails
-National -Entry Points -National, Regional -Commodity -Breeding Stations National, Districts By Type of Specie By Type, Primary, Processed
Study Study Administrative Records -Breeding Stations -Research Institutions Study Study
Ministry of Lands & Forestry MOFA/VSD MOFA/APD MOFA/APD MOFA/APD
Fisheries Subsector:
� Aquaculture Fish
Production
� Number of Inland Water Bodies
-National, Regional & Districts � By Ponds � By Rivers -National, Regional & Districts -Size of Water Bodies
Survey Survey
MOFI MOFI
Forestry Subsector:
Forest Area Cover Forest Reserves
-National, Regional and Districts -Major tree species -National, Regional and
Administrative records and reports
Ministry of Lands and Forestry/ Forestry Commission -do-
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Forest Products Export and Earnings Forest Depletion
Districts -Major products exported -By type of lumbering and activities
Administrative records and reports Administrative records and reports Administrative records and reports
-do- -do-
Forest Development
-National, Regional and Districts (illegal lumbering, chain saw) -Commercial vs. Public
Administrative records and reports
Ministry of Lands and Forestry/ Forestry Commission
56
B. Unavailable Agricultural Statistics Required to Monitor FASDEP-II AND GPRS
Agricultural Statistical data requirements to monitor, implement and evaluate the FASDEP-II and GPRS objectives are discussed below in Tables 4.2 and 4.3 Table 4.2: FASDEP II Required Agricultural Statistical Data for Monitoring
Indicators
Objective 1: Food Security and Emergency Preparedness, and Reduced Income
Variability
FASDEP II
Monitoring
Indicator
Statistics
Required
Level of
Disaggregation /
Suggested*
Source/ Method
to obtain
Statistics
Proposed
Responsible
MDA
required to
provide
Information
*Per capita production of key staple foods per kg/annum except for live animals (crops, livestock products, and fish)
Area cultivated (total ha) Yield per ha. Output (total mt)
i). National, District ii). Agro-ecological zone
Survey Reports
MOFA/SRID/ VSD MOFI
Number of districts and households benefiting from food aid
Volume and type of food aid imports
i). distribution by district ii). distribution by household
Administrative records Survey
MOTI / WFP ISSER*
Percentage change of households with seasonal migrants during lean period in Sudan and Guinea Savannah
Migration estimates
Sudan and Guinea Savannah agro-ecological zones
Survey MOFA/ PPMED
*Share of agricultural incomes spent on food
Incomes of households from farm and non-farm sources Expenditure on food
Farm household Farm household
Survey (GLSS) Survey (GLSS)
GSS GSS
Percentage of child underweight
Body mass weight Weight for age Height for age Weight for height
National, Regional, District -Gender
Survey MOH / Ghana Health Service
Livelihood diversity Number and percentage of diversity groups Number and percentage of farmers using improved
Survey Survey
MOFA / SRID/ PPMED MOFA/DAES
57
technology
Level of poverty based on food security/ insecurity, level of assets and vulnerability, Respective responsive capacity to agricultural development programmes
Farm household poverty and assets Inputs of agric. development programmes
District, Agro-ecological zone Input type District Agro-ecological zone
Survey (GLSS) Survey
GSS MOFA (DADU / RADU)
Number of improved breeds of animal imported / produced and distributed to farmers
Number and type of improved breed imported annually; Number and type distributed to farmers annually
National Agro-ecological zone
Administrative records Administrative records
MOFA (VSD) MOFA (APD, VSD)
*Quantity of fish produced per unit area of pond per cycle
Annual fish pond production Total area of fish pond
National National
Survey Survey
MOFI MOFI
*Total surface water area under fish farming
Size of water ponds Number of water ponds Number of water ponds per holder
National, Regional, District
Survey Survey Survey
MOFI MOFI MOFI
Agro-processing / storage equipment distributed and sold through MOFA
Number and type of equipment distributed and sold
National, Regional and District
Administrative records
MOFA (AESD)
Number of functioning farmer based organizations Their access to services
Number and type of farmer-based organizations Types of services Access channels
National, Regional, District National, District
Administrative records Survey
Dept. of Cooperative MOFA (SRID /AESD/DADU/ RADU)
*Ratio between subsistence crop/livestock and commercial crop/livestock farming
Number of subsistence farmers producing crops Number of subsistence livestock keepers Number of subsistence farmers
National, Regional and District
Survey MOFA (SRID)
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producing crops and keeping livestock species Number of commercial farmers producing crops Number of commercial livestock keepers Number of commercial farmers producing crops and keeping livestock
Trend in productivity of paid farm and non-farm unskilled labour
Daily farm wage per type of activity Wage per contract farm work by type of work Daily non-farm rural unskilled wage per type of activity
District, Agro-ecological zone, gender, age.
Survey (GLSS) Survey (GLSS) Survey (GLSS)
GSS GSS GSS
Objective 3: Sustainable Management of Land and Environment
Natural resource protection: Rural infrastructure developed with environmental mitigation measures
Number of irrigation schemes Number of farm roads
National, Size and agro-ecological location National, District, Agro-ecological zone
Administrative record Administrative record
MORT, GIDA
Natural resource management : Cropping and husbandry practices
Land preparation methods Cropping methods Husbandry practices Soil erosion preventive methods
Crop type, agro-ecological zone
Survey Survey Survey Survey
MOFA (CSD)
Sustainable cropping and husbandry training modules and environmentally friendly actions.
Number and type of training modules Number of
Agro-ecological zone
Administrative records Administrative records
MOFA (CSD) MOFA (CSD)
59
environmentally friendly actions
Objective 4: Increased Competitiveness and Enhanced Integration into Domestic
and International Markets
*Change in export of non-traditional agricultural commodities (mt)
Volume of non-traditional exports by type of commodity / oversea, air & land Value of non-traditional exports by type of commodity / oversea, air and land
National, Regional and District By major commodity: � Pawpaw � Mango � Pineapple � Banana
Administrative Administrative
GEPC / MOTI / GSS GEPC / MOTI / GSS
Number of effective market and extension information centres established
Number of market information centres Location of market information and extension centres Marketing and Extension information packages (brochures)
Districts Survey Survey Survey
MOFA (SRID/DAES) MOFA (SRID/DAES) MOFA (SRID/DAES)
Objective 5: Application of Science and Technology in Food and Agriculture
Development
Extension office to farm household ratio
Number of extension officers Number of farm households per rural community
District and community
Administrative Census
MOFA (DAES) GSS
New technology and good agricultural practices (GAPS) adoption rate in crops and livestock.
Number and type of new technologies demonstrations for crops and livestock farms Number GAPS by type Number of
National, regional, district, agro-ecological zone
Administrative / Survey
MOFA (CSD, APD, DAES)
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farmers using new technologies for crops by gender and crop type Number of farmers using new technologies for livestock keeping by gender and type of livestock
Objective 6: Effective Institutional Coordination; Supporting Policies and
Strategies; Cross-cutting Irrigation
*Percentage of cultivated lands under irrigation (Area developed for formal irrigation / ha).
Land area developed for irrigation Land area that the developed system can irrigate
-Irrigation system developed by regions and districts -Crops cultivated under different systems by regions and districts By commodity
Administrative/ Survey
GIDA
Land intensification ratio in formal developed irrigated areas
Number of cropping cycles per year
Irrigation system per crop
Survey GIDA
Mechanization Running tractor to farmer ratio
Number of serviceable tractors -Import quantity & value -Export quantity & value
Tractor available and hiring centres by regions and districts
Administrative
MOFA/ AESD
Tractor Hiring Centres
Location of hiring centres Estimated population in catchment area Number of
Tractor hiring centre by regions and districts
Administrative MOFA/ AESD
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farmers who request for tractor hiring per month Average waiting time for tractor service Number of acres ploughed by tractors
Animal Traction Centres
Number of animal traction centres Location of animal traction centres Estimated population in catchment area Number of farmers requesting animal traction services/ month Number of hectares ploughed by animal traction
Tractor hiring centre by regions and districts
Administrative Administrative Administrative Administrative Administrative
Farm Mechanization Centres
Number of operational centres Types of services provided Number of farmers requesting services per month
Mechanization centre by regions and districts
Administrative Administrative Administrative
Access to
Agricultural Inputs Fertilizer
Volume and type of imports Number and distribution of fertilizer and
National District, Regional
Administrative Administrative
MOFA (CSD) MOFA (CSD/SRID)
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other inputs outlets
Production , Procurement and Distribution of Vaccines and Biologicals
Volume of production by type of vaccine / biological Number of distribution outlets Retail prices of vaccines and biological
National Regional Region, District Region, District
Survey Administrative Administrative
MOFA (VSD) MOFA (VSD) MOFA (VSD)
Production, Procurement and Distribution of Certified Planting Materials
Volume of production by type of planting material Number of distributors and location of outlets Retail prices of certified planting materials
Agro-ecological zone Region, District Region, District
Administrative Administrative Administrative
PPRSD (Seed Inspection Unit) PPRSD (Seed Inspection Unit) PPRSD (Seed Inspection Unit)
Demographic Indicators
Population and Children ≤5 years
National, Regional, Districts by Gender, Urban and Rural
Population Census
GSS
Modernized Agriculture
Farm household incomes, Non-farm household income
National, Regional, Districts Ecological Zones
Study GLSS-GSS
Ratio between subsistence crop/livestock and commercial crop/livestock farming
National, Regional & Districts -Subsistence Farming -Commercial Farming
Annual Survey Reports
MOFA/SRID
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Table 4.3: Required Agricultural Statistics to Monitor GPRS Indicators
Other
GPRS
Monitoring
Indicators
Statistics
Required
Level of
Disaggregation /
Suggested*
Source/
Method to
obtain
Statistics
Proposed
Responsible
MDA
required to
provide
Information
Macro-Economic Indicators
GDP (local currency units) GDP Real Growth Employment (No. of people)
National, Agriculture, Non-Agriculture National, Agriculture, Non-Agriculture National, Agriculture, Non-Agriculture
Annual Report Annual Report Annual Report
GSS GSS GSS/ME&SW
Socio-Economic Indicators
Poverty
% of population living below: -$1 purchasing power per day -National Poverty Line % of population below minimum level of dietary energy consumption % of children ≤5 years -Underweight -Height for age HIV/AIDS (No. of people affected)
Survey/Study -do- -do- -do- Report Report
GSS GSS GSS GSS GSS/MOH MOH/AIDS Commission
Demographic Indicators
Population and Children ≤5 years
National, Regional, Districts by Gender, Urban and Rural
Population Census
GSS
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C. Agricultural Statistics Requirement to Monitor Comprehensive
Africa Agricultural Development Programme (CAADP)
Agricultural Statistical Data are required to monitor how agricultural policies and strategies are contributing to achievement of the overall national development goals of raising growth and reducing poverty and hunger.
Table 4.4: Required Agricultural Statistical Data for Monitoring Agricultural
Policies and Strategies of CAADP
CAADP
Monitoring
Indicators
Statistics
Required
Level of
Disaggregation
Source/
Method to
obtain
Statistics
Proposed
Responsible
MDA required to
provide
Information
Commodity
markets and
Trade
Production Exports and Imports
Value of Production % Price Support % Tax -Total Value of Exports -Export Tax (% of total value) -Export Quota -Total Value of Imports -Import Tariff (% of total value) -Import Quota
National, Regional and Districts National National Major Staples Exported, Imported and Modern Inputs Used: -Chemical -Fertilizer -Other Chemicals -Seeds -Machinery -Livestock -Others
Annual Survey Report Annual Report -do- Administrative and Annual Reports -do-
MOFA/SRID Min. of Finance CEPS GSS CEPS GSS
Regulatory
Environmental
Policy Food Quality Plant & Animal Health
Scope, Main Instruments, Recent Incidence, Response
Scope:
Commodity, Products Issues Main Instruments: Subsidy, Tax, Quota Recent Incidence: Disease outbreak and extent of damage
Administrative Records and Annual Reports -do-
Ghana Standards Board, Food and Drugs Board, Ministry of Health MOFA (DADU)
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Food Safety Environmental Regulations
Response to Incidence -do- -do-
MOFA (PPRS)
Planning and
Implementation
of Strategies: Agriculture or Food Security Strategy
Number of Strategies Developed Since 2000
3 Top investment areas and share of total budget: -Development Targets poverty at base and at target year -Income at base and at target year -Total GDP/Capital at base and target year -Ag. GDP at base and target year
Annual Reports and Strategic Documents
MOFA/PPMED Budget Division NDPC
Government
Expenditure &
Revenue: Agricultural Sector and Non-Agricultural Sector
Revenue
By Source Total Internally Generated Total Externally Generated
The Medium Term Expenditure Framework and the Annual Budget Estimates
Ministry of Finance MOFA (Budget Division)
Agricultural
and Non-
Agricultural
Actual Expenditure
National, Regional, Districts By Sector By Sub-sector By Recurrent By Development/ Capital By Activities
The Medium Term Expenditure Framework and the Annual Budget Estimates
MOFA, Budget Division Ministry of Finance
Government
Agricultural
Institutions
List of Agricultural Institutions
% of total agric. Expenditure By Sub-sectors (Crop, Livestock, Fisheries & Forestry) % of total agric. Expenditure by functions or service area % of total agric. Expenditure by source of revenue: -Government Aid -Non-Government Sources (Donors,
The Medium Term Expenditure Framework and the Annual Budget Estimates -do-
MOFA/ HRDMD, CSIR, University of Ghana, Cape Coast KNUST MOFA/Budget Division
66
NGOs etc.
% of total agric. expenditure on: -Recurrent -Capital or Development Total No. of approved staff positions, by Gender, by Highest Educational Level attained
Annual Budgets and Statements Administrative Records
MOFA/Budget Division MOFA/HRDMD
Institutions
Engaged in
(A) Research &
Technology
Development
Total No. of staff by Gender
By Highest Educational level attained
Administrative Records
CSIR
(B) Institutions
Engaged in
Extension and
Training
Total No. of staff by Gender
By Highest Educational level attained
Administrative Records
MOFA/DAES/ HRDMD
Agric. Sector
Performance Sector-Wide Modern Input
Use
Agric. GDP Agric. GDP Real Growth (%) Agric. Exports Food Exports Food Imports Land Area (sq. kilometres) Labour Chemical Fertilizers Improved Seed
National and by Sub-sectors National and by Sub-sectors National and by Sub-sectors National and by Sub-sectors National and by Sub-sectors National and by Sub-sectors Total economic active population by gender & by regions Total economic active population in agriculture by gender and by regions Total amount used and by main crops % of total crop area
Annual Survey Report -do- -do- -do- -do- -do- Census Annual Study Reports -do-
GSS GSS GSS GSS GSS MOFA GSS MOFA/CSD MOFA/GLDB/ PPRSD
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Irrigation
% of total crop area % area of irrigated area by crops
-do-
GIDA-MOFA
PRODUCTION Staple Crops Export Crops
Livestock
Land Area and Production Levels % in total value of crop production Farm Gate Price (per mt) Wholesale & Retail (per mt) Land Area Production Levels % in total value of Agric. Exports Producer Price (per mt) Average Export Price ($/mt) Stock of Animals Animal Products
By major crops By major crops By major crops By major crops National, Regional, Districts -do- Major area of production By commodities Total No. of Animals by species, Proportion Improved by species (cattle, poultry, small ruminants, etc.) Meat Milk and Dairy Products Other Products
Annual Survey Report -do- -do- -do- Administrative Records -do- -do- -do- Annual Survey Report Administrative Records
MOFA/SRID MOFA/SRID MOFA/SRID MOFA/SRID MOFA/SRID MOFA/SRID MOFA MOFA (EMQAP)/ GEPC MOFA/APD/ VSD MOFA/APD
Fisheries
Total Land Area % of area under sustainable management practices Total Production % of production from
Total Land Area by (a) Captured (b) Farmed Total production by (a) Captured (b) Farmed Total production by (a) Captured (b) Farmed
Annual Survey Report -do- -do-
MOFA/MOFI (Fisheries Commission) MOFA/MOFI (Fisheries Commission) MOFA/MOFI (Fisheries Commission)
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sustainable management practices
Forestry
Total land area under forest Deforestation: Total area cleared for harvesting Forestation: Total land area planted with new trees Total
Production: Amount of Timber harvested
National, Regional, Districts Proportion of total area under sustainable management practices National, Regional, District National, Regional, Districts National, Regional, Districts Proportion of total area under sustainable management practices
Annual Reports Annual Reports Annual Reports Annual Reports
Ministry of Lands & Forestry (MLF) Ministry of Lands & Forestry (MLF) Ministry of Lands & Forestry (MLF) Ministry of Lands & Forestry (MLF) Ministry of Lands & Forestry (MLF)
Agricultural
Production
Shocks
Types of
Shocks: Flood Drought Fires Civil Unrest Pests/Diseases Other Calamities
By crop commodities cost and value By livestock affected through deaths or displaced By humans affected through deaths or displaced
Annual Reports -do- -do-
MOFA(RADU)
Rainfall
Total Amount of Rainfall Duration of Rainfall
National, Regional and Districts By main season & minor season in major agricultural producing areas By main and minor seasons in major agricultural producing areas
Administrative Records -do- -do-
Ghana Meteorological Agency (GMA) Ghana Meteorological Agency (GMA Ghana Meteorological Agency (GMA)
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D. Agricultural Statistics Requirement to Monitor the Millennium Development
Goals (MDGs)
Agricultural statistics data are of interest to the monitoring of the Millennium Development Goals (MDGs). Specifically, the agricultural statistical data will be needed to monitor Millennium Development Goals 1, 3, 7 and 8. These goals and the required agricultural statistics are indicated in table 4.5 below: Table 4.5: Required Agricultural Statistical Data for Monitoring Millennium
Development Goals (MDGs)
Millennium
Development
Goal (MDG)
The
Millennium
Development
Goal (MDG)
Agricultural
Statistics Data
Required
Reasons for
Data
Requirement
Source/
Method to
obtain
Statistics
Proposed
Responsible
MDA
required to
provide
Information
MDG 1 Halving the proportion of people who suffer from poverty and hunger
Household food security. Proportion of population (by gender) below the minimum level of dietary energy consumption.
To monitor annually data on proportion of population who suffer from hunger.
Study Report GLSS-GSS MOH
MDG 3 Promote gender equality and empower women
Information related to the role of women in agricultural production activities and the participation of rural women in non-farm economic activities.
To monitor progress towards achieving gender equality goals.
Annual Survey Report
MOFA/SRID GSS
MDG 7 Ensure environmental sustainability
Environmental data related to irrigation, soil degradation, use of mineral fertilizers and pesticides. Provide data on the forest land operated by agricultural holdings. Provide land tenure data for agricultural holdings.
To indicate the extent of degradation or otherwise in the agricultural sector. Understanding the effect of security of land tenure on agricultural practices & household food security)
Study Report Admini-strative Records
MOFA (GIDA) MOFA (CSD) MLF
MDG 8 Develop a Agricultural Indicator Study Report GLSS-GSS
70
global partnership for development
household unemployment rate for persons aged 15 to 24 to help provide the relevant data requirement for the rural sector.
requires unemployment rate for persons aged 15-24 in the rural sector.
71
CHAPTER 5
EXPECTATIONS FROM CountrySTAT AND SYNERGIES
WITH ON-GOING INITIATIVES – GHANA
5.1 Expectation from CountrySTAT and the CountrySTAT for Sub-Saharan Africa
Project
Ghana is an agricultural country with over 50 percent of total export earning coming from the sector each year. Currently about 54 percent of the labour force is engaged in agriculture activities. There is therefore the desire of government and people of Ghana to modernize agriculture. This desire coupled with the aim to achieve the MDG1 by 2015 requires that producers of agriculture data harmonize and disseminate available data timely to users including policy makers, researcher and project officers. A good database that can serve as a one-stop centre for fast, easy access to the national statistical information system for food and agriculture is therefore a necessary tool, which hitherto has been missing. A recent (June 2009) enquiry into how producers of agriculture data store their products revealed that many of them save their data in excel, which is not very good for purposes of dissemination. Generally, it is expected that the CountrySTAT software can address the database needs of the country, and thereby facilitate the organization, harmonization and standardization of agriculture data and metadata from various sources; it should also be possible to update the software to take care of changing needs of society and new technologies. In particular, it is expected that CountrySTAT would facilitate the following activities:
• analyses of data for evidence based decision making
• result based monitoring and evaluation
• linking up of different levels of planning – at national, sub-national and regional levels and
• reaching out to large and diverse audience through thematic advocacy This means that CountrySTAT should have the following features:
• a friendly interface for easy navigation
• online data access and query
• options for presenting data in chart format or graphs e.g. bar chart, line graph, pie-chart
• enhanced table wizard features e.g. aggregate function, more options for cross-tabulation, and generation of indicators and frequencies to get output in the form of Tables, Graphs or Maps or a combination of any two or all the three options.
• enhanced map wizard features with options for dot density and chart theme, label nudging, inset and exporting to raster image
• Reports features to store report templates and apply ready-to-use report formats across databases.
CountrySTAT for Sub-Saharan Africa Project, we understand is a vehicle that would convey all the benefits that CountrySTAT has to offer countries in Sub-Saharan Africa. It is envisaged that the project would provide both the technical and material support needed and also develop the capacity of the human resource to execute it.
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5.2 Synergies with on-going initiatives
Currently there are two other initiatives that are on-going namely the Integrated Management Information System (IMIS) and GhanaInfo. IMIS is a database management tool, which uses REDATAM +SP to develop a system that is used for the management of Census and survey information. It was developed some 6 years ago but was introduced in Ghana three years ago with the support of UNFPA. GhanaInfo is the Ghana version of DevInfo, which is also a data management system, which is used for organizing all kinds of socio-economic data. It is jointly implemented by Ghana Statistical Service and the National Development Planning Commission with the support of the UN Country Team. All three systems have some common features though with completely different user interface. All three systems upload raw data from EXCEL and are able to save back in EXCEL and other formats after transformation. They are all web-based and can also operate on stand alone computers or intranet. The CountrySTAT and the GhanaInfo have a more user friendly interface and easy to navigate. The IMIS does not have options for presenting data other than in table format. While there is the possibility to harmonize all three databases the CountrySTAT and the GhanaInfo appear to be more susceptible.
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CHAPTER 6
IMPORTANT FACTORS FOR THE SUCCESS OF THE CountrySTAT
FOR SUB-SAHARAN AFRICA PROJECT
The National Agricultural Statistical System has many stakeholders who play very important roles that together would ensure effectiveness and efficiency. This, however, requires
• proper coordination of the activities and
• high levels of cooperation and collaboration
Any plan to develop the CountrySTAT should include mechanisms to improve coordination among the stakeholders, particularly, the producers of statistics. The stakeholders must be made aware of the importance of their respective roles and contributions that would facilitate the effectiveness and efficiency of the CountrySTAT project and must all be brought on board at the planning stage of the project. Data and metadata are necessary ingredients for the implementation of CountrySTAT. Through effective collaboration the stakeholders can gather a good amount of quality data and metadata to populate the system, which is the ultimate output of the project.
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APPENDIX 1
METADATA FOR AVAILABLE AGRICULTURAL STATISTICAL DATA
A. Metadata for Crop Subsector
Statistical Data Unit of
Measure
Agency Compiling
Data and Contact
for Additional
Information
Information
to
Copyright
Methods used
in Collection,
Revision,
Calculation
and
Estimation of
the Statistics
Quality of Data
including
Error Sources
and Accuracy
of Statistics
Comparability
with
Alternative
Sources
CROP
SUBSECTOR
1. Crop Production Statistics � Area
cultivated � Yield � Production
(output)
Hectares (ha) Metric ton per hectare (mt/ha) Metric ton (mt)
MOFA (SRID) Director, SRID, Box M-37, Accra E-mail: sriddir@gmail.com Tel: 021-664317 -do- -do-
Director, SRID, MOFA -do- -do-
Annual sample survey of farm households from 10 Enumeration Areas per district. Farm measurement of selected holders farms and total area estimate extrapolated from average farm size, number of EAs and total holders covered. Annual crop cutting studies of random selected crop holders from the selected enumeration areas. Estimation by the multiplication of the crop area results by the average crop yield of commodity.
Inadequate enumeration area and household coverage. Underestimation of farm households by enumerators. Enumerators sometimes rely on farmers’ harvested produce for estimation when farm visits are not on time. Data quality affected by errors from the sample estimation of the crop yield and area.
No alternative sources -do- -do-
2. Crop Production Budget on cereals, legumes, vegetables and tree crops � Activities
� Cost of Activities
� Total Cost of Activities
� Revenue
Return on Investment
Quantity of Resource: - Man-days - Number of units Local Currency (GH¢) Local Currency (GH¢) Local Currency (GH¢) Percentage (%)
MOFA (SRID) Ag. Director, SRID, Box M-37, Accra Email: sriddir@gmail.com Tel. No. 021-664317
Director, SRID, MOFA
Developed framework as tool to capture all activities and its associated costs and also expected revenue from marketed output per hectare. The relevant data is collected through survey and is fed into the framework to generate the crop production budget.
Estimation of costs associated with some activities varies greatly within some agro-ecological zones.
MOFA (CSD)
3. Farm Input Availability and Prices. Input Supply � Volume by
types of fertilizer
� Volume by
type of agro-chemical imports
� Volume by
type of locally produced certified seeds
� Retail prices
of fertilizer
Kilogram (kg) Litre (lt) Kilogram (kg) Local Currency (GH¢)
MOFA (SRID) Ag. Director, SRID, Box M-37, Accra Email: sriddir@gmail.com Tel: 021-664317 -do- -do-
Director, SRID, MOFA -do- -do- -do-
Administrative records of imports of major fertilizer companies. Administrative records of MMDAs (PPRSD) and major agro-input dealers. Administrative records of production by MMDAs –
Subjective information from fertilizer companies. Difficult to check the accuracy. Information from agro-dealers may be underestimated and not reflect the true import position. Private seed production may not be accounted for in
GSS – through GCNet Server GSS – through the GCNet Server
75
and agro-chemicals
PPRSD, GLDB Interviews of agro-chemicals and fertilizer agents. Estimation is made from 3-4 agents’ price responses.
the total production. Quality of data is satisfactory.
� Retail prices of traditional farm equipment
Local Currency (GH¢)
MOFA (SRID) Ag. Director, SRID, Box M-37, Accra
Director, SRID, MOFA
Interviews of traders selling farm equipment. Estimate is made of 3-4 agents’ price responses.
Quality of data is satisfactory
Farm Credit � Commercial
and secondary bank loans and advanced to agriculture
� Commercial
banks lending rates to agents
Local Currency (GH¢) Percentage (%)
Bank of Ghana, Research Dept., Box Accra. -do-
Director, Research, Bank of Ghana -do-
Administrative records from submissions made by the various commercial and secondary banks. Administrative records of lending rates.
Quality of data is satisfactory -do-
4. Food Commodity Market Prices � Wholesale
market prices of food crops
� Retail market
prices of food crops
Local Currency (GH¢) Local Currency (GH¢)
MOFA (SRID), Box M-37, Accra -do-
Director, SRID, MOFA -do-
Survey of market prices (daily and weekly). Data is collected by Market Enumerators. Three or four market traders per community are interviewed and the average price estimated per community. -do-
Quality of data is satisfactory -do-
Farm Gate prices of food
Local Currency
MOFA (SRID), Box M-37, Accra
-do- Survey of selected
Quality of data is satisfactory
76
crops
(GH¢)
commodities at the producing and farm sites. Average price is estimated
5. Food Commodity Imports & Exports � Exports of
food commodities
� Value of
exports of food commodities
� Imports of
food commodities
� Value of
imports of food commodities
MT Local Currency (GH¢), US Dollar(US$) MT Local Currency (GH¢) US Dollar (US$)
GSS, Head, Trade Statistics amuzua@yahoo.com MOTI, Director of Research bernard-mfodwo@ yahoo.com GSS MOTI GSS MOTI GSS MOTI
Head, Trade Statistics, GSS Director of Research, MOTI -do- -do-
Data from Customs Declaration formats are captured and analyzed by the Ghana Commodity Net Services. The GCNet then releases preliminary estimates which are reviewed by stakeholder institutes of GSS, MOTI, CEPS and Bank of Ghana. -do- -do-
Quality of data is satisfactory
6. Farm Production Environment (Climatic conditions) � Rainfall -Total -No. of Days � Temperatures -Daily Min. Temp. -Daily Max. Temp. � Relative
Humidity
Millimeters (mm) Number (No.) Degree Centigrade (oC) Percentage (%) Percentage (%) changes
Ghana Meteo. Agency, Box M-3, Accra. Director, GMA -do- -do- MOFA (SRID) Box M-37, Accra
Director, GMA -do- -do- Director, SRID,
Administrative records of daily rainfall collected by rain gauges at synoptic stations Administrative records of daily temperature collected by thermometers
Delay in submission of rainfall data from districts and regions. Delay in submission of data on temperature from districts and regions.
77
� Early
warning (quarterly cereals conditions)
MOFA at synoptic and climatological stations Field observation and interview of farmers on crop conditions.
General and subjective observations of cereal conditions.
78
B. Metadata for Cocoa Subsector
Statistical
Data
Unit of
Measure
Agency
Compiling
Data and
Contact for
Additional
Information
Information
to
Copyright
Methods used in
Collection, Revision,
Calculation and
Estimation of the
Statistics
Quality
of Data
including
Error
Sources
and
Accuracy
of
Statistics
Comparability
with
Alternative
Sources
COCOA
SUB-
SECTOR
1. Total Cocoa Beans Production 2. Total World Cocoa Production 3. Total Cocoa Shipment 4. Cocoa Producer Price 5. Cocoa Farmer Share of World Market Price
Tonnes Tonnes Tonnes GH¢/Tonne Percentage
COCOBOD ICCO & COCOBOD COCOBOD COCOBOD COCOBOD
Data provided by only COCOBOD -do- -do- -do- -do-
Data obtained from weekly purchases submitted by Licensed Buying Companies (LBCs). These are summed up based on Main Crop and Light Crop seasons. The summation of the Main and Light Crops make up the total Production Data is obtained from International Cocoa Organization (ICCO) Reports Data for this is compiled from Cocoa Marketing Company (CMC) shipment invoices on monthly basis This is determined by the Producer Price Review Committee (PPRC).It is revised when deemed necessary This is determined by Gov’t/ COCOBOD through the PPRC. Revised when deemed necessary
Data is of high quality with Accurate Statistics Data is of high quality with Accurate Statistics No Error sources Data is of high quality with Accurate Statistics No sources of error
No alternative sources No alternative sources -do- -do- -do-
79
6. Volume of Local Cocoa Beans Processed Domestically 7. Volume of Types of Processed Cocoa 8. Total Revenue from Cocoa Production 9. Government Export Duty Payment 10. Government Bonus Payment
Tonnes Tonnes GH¢ GH¢ GH¢
COCOBOD COCOBOD COCOBOD COCOBOD COCOBOD
Data provided by only COCOBOD & Companies -do- Data provided by only COCOBOD -do- -do-
This data is collected directly from CMC and the processing Companies This data is collected directly from the Cocoa Processing Companies on monthly basis and summed up to get the annual volumes This is the product of the total cocoa beans produced and the achieved FOB. The total production is obtained as in (1) above. This is determined by Government/ COCOBOD through the percentage FOB sharing by the PPRC. Government/COCOBOD decides on the rate per tonne to be paid as bonus. This rate is multiplied by the declared purchases to arrive at the total amount paid as bonus
High quality data The data is of high quality, giving accurate statistics Data is of high quality and the statistics is accurate -do- -do-
80
C. Metadata for Livestock Subsector
Statistical
Data
Unit of
Measure
Agency
Compiling
Data and
Contact for
Additional
Information
Information
to
Copyright
Methods
used in
Collection,
Revision,
Calculation
and
Estimation
of the
Statistics
Quality of
Data
including
Error
Sources
and
Accuracy of
Statistics
Comparability
with
Alternative
Sources
LIVESTOCK
SUB-
SECTOR 1. Livestock Numbers/ Population
Absolute number
Veterinary Services vsdghana@ gmail.com, geonipah@ yahoo.com
VSD/ MOFA
The method used in collecting this data is counts of animal by species, sex and age in farms, house-holding in villages and towns. Aggregate of these forms the District, Regional and National. livestock Census
The livestock census figure for cattle is fairly accurate. The rest have a large margin of error because of inadequate staff for the exercise and the time constraint.
Sample livestock census
2. Livestock Diseases
Absolute number
Veterinary Services vsdghana@ gmail.com, geonipah@ yahoo.com
VSD/ MOFA
The method used in collecting this data is reporting a critical incident eg .disease outbreak. The report is event based and georeference. The District Veterinary Officer
If the outbreak is reported without laboratory confirmation it is considered suspicion (not very accurate).
Laboratory confirmed Disease outbreak
81
reports the very farm and village/town where the outbreak has occurred to the Director of Vet Services with the copy to District Agric. Director and Regional Vet. Officer. At the Directorate, Risk maps are produced. The Director Of Veterinary Services in turn reports the outbreak to OIE (World Animal Health Organisation)
3. Disease Treatment: -Immunization -Deworming
Absolute number -do-
Veterinary Services vsdghana@ gmail.com, geonipah@ yahoo.com Same
VSD/ MOFA -do-
The method used in collecting this data is registration (records) of numbers of animals vaccinated at any particular time. The aggregation of vaccinated animals in a month is compiled and monthly returns sent to the
Data is accurate. However, a topographic error can occur, which is often rectified through validation by the Epi-Unit staff. -same
82
-Dipping
-do-
Same
-do-
Regional Vet. Office, who also compile that of entire region and send it to the National Directorate - same method- - same method
-same
4. Livestock Castrated 5. Local Movement of Livestock 6. Livestock Slaughtered 7. Pathological conditions from meat inspection 8. Vaccines Utilized 9. Revenue generated from provision of services
Same Same Same Same Doses GH¢
Same Same Same Same Same Same
Same Same Same Same Same Same
Same method Same method Same method Reporting critical incidents (pathological conditions) during meat inspection. The origin of the animal and the slaughter house are geo-referenced. Records of doses of vaccines at beginning of the month and that of end of the month. Record on revenue generated from provision of various
Same Same Same Same Depends on the integrity of the officer in-charge. Depends on the integrity of the officer in-charge.
83
services to farmers and other entrepreneurs
10. Live Animals Imported
Absolute Number
Veterinary Services Directorate vsdghana@ gmail.com
Veterinary Services Directorate
Record of animal passing through the quarantine stations
Doubtful. Most of animal enter through unofficial routes thus escaping the quarantine inspection
11. Imports of Poultry and Poultry Products
Absolute number
-do- -do- Records of Day-old and Chick Parent stock, Layer day-old chick, Broiler day-old chick, Turkey poultry, Hatching eggs
Data is accurate. However, a topographic error can occur, which is often rectified through validation by the Epi-Unit staff
12. Meat Imports
Weight in kgs or tons
-do- -do- Records of meat (Beef, Buffalo, Mutton, Chevron, Port, Processed Meat & Milk) imported through Tema
Same
13. Exportation of livestock, wildlife, poultry and other livestock products
Same -do- -do- Records of wildlife exports including reptiles, insects, amphibians, crustacean, pets such as parrots, dogs, cats and other livestock products like drum skins exported through Kotoka
Wildlife exported through unofficial routes are not captured.
84
International Airport
D. Metadata for Fisheries Subsector
Statistical
Data
Unit of
Measure
Agency
Compiling
Data and
Contact for
Additional
Information
Information
to
Copyright
Methods used
in Collection,
Revision,
Calculation
and
Estimation of
the Statistics
Quality of Data
including
Error Sources
and Accuracy
of Statistics
Comparability
with
Alternative
Sources
FISHERIES
SUB-
SECTOR
1. Marine: (a) Total Marine Fish Production -Canoe -Motor Fishing Vessels (b) Total Fish Stock (c) Total Fish Imports (d) Total Fish Exports
Metric tons (mt) Metric tons (mt) Metric tons (mt) Metric tons (mt) Metric tons (mt)
Fisheries Commission, Marine Fisheries Res. Div., Box Accra -do- FC, Mon. Control & Surveillance Div. -do-
Director, Fisheries Commission, Accra -do- -do- -do-
Use of sample landing sites and fishermen for collecting data. Artfish software used for estimation. Census collection Census collection at major cold stores, on weekly basis at Tema Municipal Assembly. Census collection of fish imports at Tema. Administrative records of exported fish from Tema Municipal Assembly
Main error sources is inadequate number of sampling sites due to understaffing. Use of 50 sites out of total 334 sites. Late submission of data. Inadequate coverage at TMA. Cold stores located at other landing sites and inland not covered. Data collected only on imports for which permit has been issued. Data provided only for exports for which permit has been issued.
No alternative sources -do- -do- Estimates from GSS/MOTI (GEPC) are more realistic and are alternative sources. -do-
(e) Registered Vessels
Number (No.)
Fisheries Comm., Marine
Director, Fisheries Commission
Administrative records of registered
Illegal registration of semi-industrial
85
(f) Licensed Vessels (g) Positional Analysis (Vessel Statistics
Number (No.) Number (No.)
Fisheries Mgt. Div. -do- -do-
Accra
vessels. Administrative records of licensed vessels. Monthly compilation from daily administrative records.
vessels. Irregular submission of data from the regional officers on semi-industrial vessel licensing. Underestimation because of inadequate coverage by understaffing and non-commitment of staff.
2. Inland Total Inland Fish Production and Productivity � Aquaculture
(small-scale and subsistence) -Output -Yield -Surface Area
� Commercial
Farms
Metric tons (mt/ha/year) -do- -do- -do- Hectares Metric tons (mt)
Fisheries Commission Head, Inland Fisheries, Accra -do-
Director, Fisheries Commission Accra
Sampled aquaculture farms used to determine productivity of the farms and this is used to project for the total production of the country. Census survey is conducted to determine production from all commercial farms.
Non-sampling error may be experienced Data quality and accuracy is high.
� Reservoirs
Metric tons (mt)
Fisheries Commission Head, Inland Fisheries, Accra
-do- From available census of reservoirs and their surface areas sampled reservoir data are collected on fish landings and used to project for all reservoirs
Non-sampling errors may be experienced.
86
E. Metadata for Irrigation
Statistical
Data
Unit of
Measure
Agency
Compiling
Data and
Contact for
Additional
Information
Information
to
Copyright
Methods used
in Collection,
Revision,
Calculation
and
Estimation of
the Statistics
Quality of Data
including Error
Sources and
Accuracy of
Statistics
Comparability
with
Alternative
Sources
IRRIGATION 1. Inventory of Irrigation Schemes 2. Production from Irrigated Schemes � Output � Area � Yield 3. Inventory of Dams and Dugouts 4 Production from Dams and Dugouts � Output � Area � Yield
Number (No.) Mt Ha Mt/Ha Number (No.) Mt Ha Mt/Ha
Ghana Irrigation Development Authority, Box M-37, Accra -do- -do- -do-
The Chief Executive, GIDA -do- -do- -do-
Study on irrigation schemes in the country. Estimates are made of the informal irrigation schemes and added to the GIDA formal irrigation schemes. Survey on formal irrigated schemes. Complemented by Administrative reports. Same method Survey/studies on dams and dugouts by Agric. Extension Agents
Accurate on formal irrigation schemes. Underestimation of non-formal schemes. -do- Underestimations as enumerators fail to identify all dams and dugouts. -do-
Water Resources Institute No alternative sources -do- -do-
87
F. Metadata for Forestry Subsector
Statistical
Data
Unit of
Measure
Agency Compiling
Data and Contact for
Additional Information
Information
to
Copyright
Methods
used in
Collection,
Revision,
Calculation
and
Estimation
of the
Statistics
Quality of
Data
including
Error
Sources
and
Accuracy
of
Statistics
Comparability
with
Alternative
Sources
FORESTRY:
Export of Wood Products
Percentage Volume Value (EU)
TIDD of FC Takoradi, Contact: P.O. Box 783/ 515, Takoradi Tel: 031-22921-4 031-22926 Fax: 031-22837 031-22926 Accra Office:
021-401210 021-401227 021-401216\ 021-401231 Fax-Accra:
021-401209 Email: info@tidd.fcghana.com website : www.fcghana.com
Forestry Commission, Timber Industry Development Division (TIDD)
Collection of records from departments with TIDD
Satisfactory
CEPS
National Forest Plantation Development
Area (ha) Amount (GH¢) Percentage (%)
Plantations Department of the Forest Services Division of the Forestry Commission, P.O. Box GP257 Accra, Ghana Tel: 021-401210 021-401227 021-401216\ 021-401231 Fax: 021-401215
Forestry Commission, Plantations Department
Field reports compilation
satisfactory
88
Dept. No.
028-9115496 Email:
infofsd@hq.scghana.com Website: www.scghana.com