countrystat ghana - the first panorama report...

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 2.4.1: 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

----------------------------------------------------------------------------------------------

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



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


GOAL (1): To produce and disseminate comprehensive, integrated, accurate and timely national agricultural statistics in support of national development



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


GOAL (1): To produce and disseminate comprehensive, integrated, accurate and timely national agricultural statistics in support of national development STRATEGIC OBJECTIVE/ PURPOSE


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


GOAL (2): To develop and maintain a national agricultural statistics database



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





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





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


GOAL (3): To coordinate and supervise a national agricultural statistical system



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)


Cycle of

Release and

Date of

Update

Regularity and

Timeliness of

Release

Level of

Disaggregation


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



Cycle of

Release and

Date of

Update

Regularity and

Timeliness of

Release

Level of

Disaggregation


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



Cycle of

Release and

Date of

Update

Regularity and

Timeliness of

Release

Level of

Disaggregation


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



Cycle of

Release and

Date of

Update

Regularity and

Timeliness of

Release

Level of

Disaggregation


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


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)


Cycle of

Release and

Date of

Update

Regularity

and

Timeliness

of Release

Level of

Disaggregation



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


Cycle of

Release and

Date of

Update

Regularity

and

Timeliness

of Release

Level of

Disaggregation



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)


Cycle of

Release and

Date of

Update

Regularity

and

Timeliness

of Release

Level of

Disaggregation



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


Cycle of

Release and

Date of

Update

Regularity and

Timeliness of

Release

Level of

Disaggregation


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


Cycle of

Release and

Date of

Update

Regularity and

Timeliness of

Release

Level of

Disaggregation


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


Cattle, Sheep, Goats, Pigs, horses/donkeys

5. Local movement of Livestock

Monthly/Annual


Cattle, Sheep, Goats, Pigs/Donkeys

6. Local slaughter of Livestock

Monthly/Annual


Cattle, Sheep, Goats, Pigs and others (Dog, Donkey)

Unofficial, slaughtering data not available

7. Pathological conditions from meat inspection

Monthly/Annual


Antemortem findings Postmortem findings

8. Vaccine utilized Monthly/Annual


Vaccines

9. Revenue Generated from provision of service

Monthly/Annual


Money & cheques

38


Cycle of

Release and

Date of

Update

Regularity and

Timeliness of

Release

Level of

Disaggregation


remarks and

Unavailable

statistics

10. Live Animal import

Monthly/Annual


Imported Live Animals Cattle, Sheep, Goats, Pigs and Horses

Origin of Imports not available

11. Imports of poultry and poultry products

Monthly/Annual


Poultry Imports: Day old Chick Parent stock Layer day old chick Broiler day old chick Turkey poult Hatching eggs


12. Meat Imports Monthly/Annual


Meat & Milk Imports: Beef, Buffalo, Mutton, Chevron, pork, processed meat& milk


13. Exportation of livestock, wildlife, poultry and their products

Monthly/Annual


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


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


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


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


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.

53

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-

55

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


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


Survey MOFA (SRID)

58

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)

60

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

61

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)

62

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

63

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

64

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)

65

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

67

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)

68

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)

69

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.

72

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.

73

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.

74

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: [email protected] 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: [email protected] 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: [email protected] 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


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 [email protected] 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-


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: [email protected] 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:

[email protected] Website: www.scghana.com