GCP/GLO/208/BMG - CountrySTAT for Sub-Saharan
Africa
FIRST PANORAMA REPORT
KENYA
Isaiah Imaita (PhD)
Director Town CampusAfrica Nazarene University
Consultant National Information system & Agricultural statistics
October 2009
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ACKNOWLEDGEMENT
I wish to express my profound gratitude to the CountryStat National Coordinator
Mr. Abner Ingosi for the technical advice and encouragement he gave the consultant.
My thanks also go to all sector ministries consulted and Secretariat for the hospitality,
guidance and technical support that culminated in the production of this document. I
further appreciate the quality information provided by the various stakeholders who were
consulted during the course of undertaking the study.
Finally, I wish to acknowledge the financial support provided by the FAO and the
Kenya National Bureau of Statistics (KNBS) for the support offered and access to the
information.
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EXECUTIVE SUMMARY
The availability of reliable, consistent, comprehensive and timely agricultural data for the development of agricultural sector remains critical. Credible data is required to inform the planning process, compilation of reliable national accounts; monitor sector performance, monitor and evaluate the impact of policies and programmes and contribution to decision-making process.
However, review of food and agricultural statistics indicates although the information base is fairly large and available, the data varies from different sources. The information also not well organized and/or coordinated for easy access, retrieval and analysis, hence failure to satisfy the demands of the increasing data users.
The Kenya National Bureau of Statistics (KNBS) is mandated by Statistical Act 2006 as the official Government agency responsible for official Statistics in the country. To improve the quality of agricultural statistics in general in the country. The directorate of production and nutrition within the bureau is in the process of putting up an Agricultural, Nutrition and Environmental statistics working committee. This will bring together line ministries involved in Food and Agriculture data.
There are four main data collection systems used by the National Statistical Systems (NSS), namely administrative records, censuses, sample surveys and participatory assessments. Administrative records, censuses and surveys foam are sources of quantitative data while participatory assessments are a source of qualitative data.
These collection systems have a major role to play in the development of the NSS. These systems should be coordinated so that they can produce complementary data, which is well recognized. The motivation of combining data from different sources are necessitated by the need to lower the respondent burden, check data consistency, improve the design of data collection instruments and introduce new analytical products, limit surveys and census costs given constraints on statistical budgets and the necessity to provide data on topics or at levels of disegregation not covered by some systems. It is for this reason therefore that the CountrySTAT will assist in harmonizing data from various sources.
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ACRONYMS
CA Competent Authority
CAIS Central Artificial Insemination Services
CBS Central Bureau of Statistics
DAEO Divisional Agricultural Extension Officer
DAO Districts Agricultural Officer
DWFN District Water Fishing Nations
FEO Frontline Extension Officers
FU Farming Units
KEVEVAPI Kenya Veterinary Vaccines Production Institute
KMC Kenya Meat Commissioner
KNBS Kenya National Bureau of Statistics
MDG Millennium Development Goals
MIS Management Information System
MoA Ministry of Agriculture
MoCMD Cooperative and Market Development (),
MoEME Ministry of Environment and Mineral Exploration,
MoFD Ministry of Fisheries
MoL Ministry of Lands
MoLD Ministry of Livestock Development
MoRD Ministry of Regional Development,
MoT Ministry of Trade
MSNKAR Ministry of State for Northern Kenya and Arid Lands,
NASSEP National Sample Survey and Evaluation Programme
NGOs Non-Governmental Organizations
NSS National Statistical System
OP Office of the President
PDA Provincial Director of Agricultural Officer
PDVS Provincial Director of Veterinary Services
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SAGA Semi-Autonomous Government Agency
SMS Subject Matter Specialist
ToR Terms of Reference
UN United Nations
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CONTENTS
ACKNOWLEDGEMENT ...............................................................................................................ii
EXECUTIVE SUMMARY ..............................................................................................................iii
ACRONYMS ..................................................................................................................................... 1
CONTENTS ...................................................................................................................................... 3
LIST OF TABLES ............................................................................................................................. 5
LIST OF FIGURES........................................................................................................................... 6
1.0 INTRODUCTION...................................................................................................................... 7
1.1 Overview .................................................................................................................................7
1.2 The Sector Ministries..............................................................................................................8
1.3 Main Objective ........................................................................................................................8
1.4 Terms of Reference (TOR) .....................................................................................................8
1.5 Methodology Adopted ..........................................................................................................9
1.6 Limitations of the Study ........................................................................................................9
2.0 NATIONAL STATISTICS SYSTEM ................................................................................. 10
2.1 Legal Framework and Advisory Bodies ...........................................................................10
2.2 Structure of the National Statistics System .......................................................................11
2.3 National Strategy for Development of Statistics..............................................................14
3.0. REFERENCE SITUATION FOR THE FOOD AND AGRICULTURE STATISTICS SYSTEM ........................................................................................................... 17
3.1 Legal Framework and Food and Agriculture Statistical Advisory Bodies ..................17
3.2 Human Resources available................................................................................................20
(e) Non-Human Resources available.......................................................................................26
3.3 Data Dissemination Policy for Food and Agriculture Statistics ....................................26
3.45 Modalities of promoting User-Producer Dialogue..........................................................27
3.5 Existing Databases and Data Dissemination Tools and Platforms ...............................27
3.6 Dissemination Tools available are: ....................................................................................27
3.7 Dissemination Platforms .....................................................................................................27
3.8 Regional Integration and International Technical Assistance received .......................27
4. 0 OUTPUTS, DATA SOURCES, AND METADATA OF THE FOOD AND AGRICULTURE STATISTICS.............................................................................................. 40
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5.0 OVERVIEW OF USER NEEDS FOR FOOD AND AGRICULTURE STATISTICS ........................................................................................................................... 45
5.1 Public Sector Decision Makers ...........................................................................................45
5.2 Private Sector Decision Makers ..........................................................................................45
6 EXPECTATIONS FROM COUNTRYSTAT AND SYNERGIES WITH ON-GOING INITIATIVES – COUNTRY NAME ..................................................................... 46
7. IMPORTANT FACTORS FOR THE SUCCESS OF THE COUNTRYSTAT PROJECT – COUNTRY NAME............................................................................................. 47
8.0 ANNEXES I : BIBLIOGRAPHY ............................................................................................ 48
ANNEX II:DATA SETS ................................................................................................................ 49
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LIST OF TABLES
Table 1: Current KNBS Staff Establishment.............................................................................23
Table 2: Optimal Staff Establishment of the MoA ..................................................................24
Table 3: Distribution of Staffing Levels by gender .................................................................24
Table 4: Ministry of Livestock Development Human Resource ...........................................25
Table 5: Expenditure for the Sector Ministries (Kshs Million, 2008/09*) ............................26
Table 6: Production of Food Crops by Province, 2008*..........................................................49
Table 7: Crop Production, 2001 – 2008 (Tons) .........................................................................51
Table 8: Producers Prices for Primary Crops, 2001 – 2008 (Tons) ........................................52
Table 9: Production of Primary Crops, 2001 – 2008 (Tons)....................................................53
Table 10: Tea Production, 2004 – 2008 ......................................................................................54
Table 11: Coffee Production, 2004 – 2008 .................................................................................55
Table 12: Sugar Production, 2004 – 2008 ..................................................................................56
Table 13: Cotton Production, 2004 – 2008.................................................................................56
Table 14: Pyrethrum Production, 2004 – 2008 .........................................................................57
Table 15: Tobacco Production, 2004 – 2008 ..............................................................................57
Table 16: Coconut Production, 2004 – 2008................................................................................58
Table 17: Fresh Horticultural Exports; 2003-2008 .................................................................58
Table 18: Annual Fertilizer Off-take, 2001-2008 (tons) .............................................................59
Table 19: Average Retail Fertilizer Price, 2002-2007 (Kshs/50kg)..........................................61
Table 20: Certified Seeds Production and Importation (2004-2008) .......................................62
Table 21: Livestock Productions .................................................................................................65
Table 22: Fish Exports Value US $ ...............................................................................................66
Table 23: Fish Exports Volume........................................................................................................66
Table 24: Fish Export value..............................................................................................................66
Table 25: Fish Exports Volume........................................................................................................66
Table 26: Production of Fish by Source..........................................................................................67
Table 27 : Value of Fish by Source ..................................................................................................67
Table 28 : Source Fish Productions by Lakes ................................................................................68
Table 29: Quantities of Principal Exports and Imports, 2003 - 2007 ..........................................69
Table 30: Forest Plantation Area, 2003– 2007 ................................................................................71
Table 31: Population Data................................................................................................................72
Table 32: Labor Data .........................................................................................................................72
Table 33: Land Use............................................................................................................................73
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Table 34: Correspondence table of Products.................................................................................74
Table 35: Data Production Frequency............................................................................................77
LIST OF FIGURES
Figure 1: The proposed Structure of the Food and Agriculture Statistics System ..................18
Figure 2: Structure of the CountrySTAT Project ............................................................................19
Figure 3Diagrammatic Representation of Organization Structure............................................21
Figure 4: Diagrammatic Representation of the proposed field organization-short term.......22
Figure 4: Ministry of Agriculture Data Flow ................................................................................32
Figure 5: Ministry of Livestock Development Data Flow...........................................................33
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1.0 INTRODUCTION
1.1 Overview
The agricultural sector is a key contributor to the country’s economic growth as
reflected by its share in Gross Domestic Product (GDP), job creation, food security and
industrial development. The Vision 2030, the country’s new development blue print, has
identified agriculture as key growth drivers in realizing the Vision. Vision 2030 envisions
the agricultural sector to be “an innovative, commercially oriented and modern
agriculture.”
Agricultural sector continues to be the backbone of Kenya’s economy in terms of its
contribution to GDP. It contributes directly 26 percent of the GDP through manufacturing,
distribution and service-related activities with more than one-third of Kenya’s agricultural
produce being exported. The sector also remains the main source of employment and
household income in rural areas where 80 percent of the population live. In addition, the
sector generates about all the country’s food requirements and provides a significant
proportion of raw materials for the agricultural resource-based industrial sector.
The Government has embraced broad-based growth and development strategies in
agriculture to address unemployment, poverty, food insecurity and enhance equity
through Vision 2030 and the first Medium Term Plan (MTP) 2008-12. The sector has
continued to work towards transformation of the agricultural sector to effectively provide
food and nutritional security, increase incomes and gainful employment, promote farmers
productivity and lower cost of agricultural inputs for food production.
The availability of reliable, consistent, comprehensive and timely agricultural data
for the development of agricultural sector is critical. Credible data is required to inform and
understand the planning process; compilation of reliable national accounts; monitor sector
performance; monitor and evaluate the impact of policies and programmes and contribute
decision-making process.
Agricultural data is required by a wide spectrum of stakeholders ranging from
decision makers in Government, the private sector, academia for research and teaching and
the donor community. The quality of agricultural statistics is essential in improving
efficiency, production, marketing and distribution of agricultural commodities.
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Acknowledging the growing concern about the credibility, adequacy and timeliness
of agricultural statistics, the ministry of planning and vision 2030 undertook the
transformation of the to Kenya National Bureau of Statistics (KNBS) formely the Central
Bureau of Statistics (CBS) to a semi-autonomous institution in 2007.
1.2 The Sector Ministries
The sector ministries in the agricultural sector includes ministries of, Livestock
Development (MoLD), Fisheries Development (MoFD), Cooperative and Marketing
(MoCD&M), Trade (MoT), Land (MoL), Environment and Natural Resources (MoE&NR),
and Regional Development (MoRD).
1.3 Main Objective
The main objective of the study was to undertake an evaluation of the available
agricultural, food information and its related information in the country.
1.4 Terms of Reference (TOR)
The specific tasks for undertaking the assessment were as follows:
1. Evaluation of information system and agricultural statistics set-up.
2. Evaluation of available agricultural and food information in the country: coverage,
data types, quality, standardization, management, distribution.
3. Results and products of the information system and agricultural statistics.
4. Evaluation of results and products of the information system and agricultural
statistics.
5. Assessment of needs on agricultural statistical data.
6. Prepare a country report on data requirements and data availability as well as on
required assistance for standardization, integration, management and dissemination
of existing data, evaluation of technical and institutional capacities in the country.
7. Ensure the collection of data in the country for CountrySTAT system, according to a
content to be defined.
8. Provide an Excel file with data and indicators of agricultural and food available for
the 2001-2007 series.
9. Participation in the organization and preparation of the final seminar on the report
validation and preparation.
10. Other tasks deemed necessary by the CountrySTAT team.
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1.5 Methodology Adopted
The study employed the following;
• Desk review of ministries publications and
• Consultations with the ministries data producer and users.
1.6 Limitations of the Study
Some of the unforeseen limitations included lack of cooperation from the consulted
member, data gaps in the available series, unharmonised data sets and most of the
ministries available data was unpublished and unvalidated making it almost impossible to
quote and include it in the report.
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2.0 NATIONAL STATISTICS SYSTEM
2.1 Legal Framework and Advisory Bodies
The Ministry of Planning, National Development and Vision 2030 (MoPND) together
with the Development Partners have been engaged in a statistical capacity building
activities geared towards strengthening the National Statistical System (NSS), including the
Kenya National Bureau of Statistics (KNBS), Line Ministries and other key Government
institutions. The first step among other key activities was to transform the Central Bureau
of Statistics (CBS) to KNBS into a Semi-Autonomous Government Agency (SAGA) through
Statistical Act 2006 with the mandate to coordinating the NSS. Moreover, to facilitate the
process of developing an NSS system the government has continuously increased
budgetary support for KNBS during fiscal years of 2004/05 - 2008/09.
Policy decision makers and stakeholders also played proactive roles in the
development of the NSS by creating demand and supply and maintaining sustainable NSS
systems. There exists a close working environment between the data suppliers including
households, institutions and establishments whose collaboration is vital to the development
and success of any statistical system.
To improve the quality of statistics in the country, the directorate of Production,
nutrition within the KNBS is in the process of putting up an Agricultural, Nutrition and
Environmental statistics working committee expected to be launched soon as the members
has already been appointed. The committee will be geared towards strengthening statistical
databases and identifying additional/new indicators in the productive sector. It will inform
development policy, monitoring and evaluation within the vision 2030 goals1 , the
Millennium Development Goals (MDG)2 and measurement of Gross Domestic Product
(GDP). The committee will also be expected to meet on regular intervals to deliberate and
review the sector data needs and other challenges within the sector. Other National
Statistics Committees and sub-committees on various aspects of statistics also meet on
quarterly basis to deliberate on statistical issues.
1 New long-term development blueprint for the country, to create a “globally competitive and prosperous country with high quality of life by 2030.” 2 A set of quantified & time-bound goals for dramatically improving the human conditions by 2015, agreed by all member states of the United Nations
(UN).
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2.2 Structure of the National Statistics System
The National Statistical System (NSS) in Kenya is defined by a legal framework,
infrastructure and institutional arrangements for collection, management, dissemination
and utilization of official statistics in the country. Official statistics are those
produced/compiled by Government Ministries, Departments and other related agencies.
There has been a global realization of the importance of developing effective and efficient
NSS that will produce good and timely statistics for measuring overall development
process, but more specifically for monitoring the implementation of poverty reduction
strategies. In order to make the NSS effective, it is crucial that the components of the system
are identified and assessed.
The NSS in the country has three inter-dependent components namely data users,
data producers and data suppliers. Data users are the clientele of the data production
systems. It is important to recognize that statistics is produced because users demand.
Data users include;
1. Policy and decision makers in main Government Ministries , Institutions and quasi-Government bodies;
2. Politicians; 3. Local Authorities; 4. Researchers; 5. Universities; 6. Private sector 7. Donor; 8. Development partners and 9. Wider public
2.2.1 Data producers; Institutions involved in data production include; 1. Line Ministries 2. Public sector institutions 3. Research and training institutions 4. Non-Governmental Organizations (NGOs) 5. Private organization.
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2.2.2 Data suppliers Data suppliers vary, but the main ones are;
1. Households 2. Farmers 3. Institutions etc.
2.2.3 MAIN DATA COLLECTION SYSTEMS There are five data collection systems used by the NSS, namely administrative
records, censuses, sample surveys and participatory assessments. Administrative records,
censuses and surveys are sources of quantitative data while participatory assessments are a
source of qualitative data.
(a) Quantitative Data
(i) Administrative Records
Large volumes of socio-economic data are compiled by government departments
and other institutions. They include information on: operations of education, health and
other social services, external trade, balance of payments, government accounts and prices,
agriculture and other economic and social fields.
Administrative data tend to be subject-specific and restricted in coverage and
content by legal and administrative considerations; inconsistent as it is compiled by
different institutions independent of each other and using different methodologies,
definitions, classifications, etc.; and some are of questionable quality. In addition, a lot of
data from this source remain in raw form and are not turned into information for
management. To take full advantage of this simple and cheap source of data, many
institutions are establishing Management Information Systems (MISs) to systematize the
collection and management of administrative data as well as facilitate sharing them with
other stakeholders. These MISs are a rich source of statistical information that will be
invaluable in sector-specific poverty monitoring and especially of intermediate programme
indicators i.e. physical deliverables resulting from government spending.
(ii) Censuses
Censuses are mega-statistical activities that seek to cover the whole population (or
universe) of interest. The most important censuses carried out in Kenya are the Population
and Housing Census, Agricultural Census and Census of Business Establishments.
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Censuses are the main source of benchmark data needed for planning for socio-economic
development.
(iii) Sample Surveys
If properly planned and executed, sample surveys are the main source of up-to-date
and reliable socio -economic and demographic statistics. Other data collection systems e.g.
Population and Housing Census, Vital Registration Systems and Administrative Records
do not always provide the required data in a timely manner mainly because of lack of
coordination and effectiveness. Sample surveys involve data collection from a well-selected
sample from the population. They are cheaper, faster and easier to carry out and usually
they give more accurate estimates than censuses.
(b) Qualitative Data
Participatory assessments and methodologies are becoming increasingly widespread. They
collect qualitative data as opposed to quantitative data usually collected in censuses and
surveys. Participatory assessments are being used a lot to assess poverty from the
perspective of those considered poor. They are based on purposively selected samples and
semi-structured or interactive interviews to collect data, mainly data relating to people’s
judgments, attitudes, preferences, priorities, and/or perceptions about poverty and other
phenomena.
(c) Combining Data from Different Sources
All the above mentioned data collection systems have a major role to play in the
development of the NSS. These systems should be coordinated so that they can produce
complementary data that is well recognized. Indeed, in recent years, the subject of
combining data from different sources has gained considerable attention. The motivation of
combining data from different sources comes from the need to lower the respondent
burden, check data consistency, improve the design of data collection instruments and
introduce new analytical products, limit surveys and census costs given constraints on
statistical budgets and the necessity to provide data on topics or at levels of disaggregation
not covered by some systems.
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2.3 National Strategy for Development of Statistics
The demand for quality statistics for benchmarking national development initiatives
and programmes, and for tracking progress in the country resulted in the strategy for
development of statistics as a key priority. The demand has presented major challenges to a
weak, vulnerable, under-staffed and under-resourced KNBS and the National Statistical
System (NSS) in Kenya. It has on the other hand, presented tremendous opportunities,
particularly with respect to raising the public profile of statistics and harnessing both
national and international resources for statistical development.
To meet the unprecedented increase in demand for statistics, the Government has
embarked on an undertaking to strengthen the national statistical services and improve
data production, dissemination and access. In March, 2003 the Government, with assistance
from development partners formulated a medium-term Strategic Plan for the National
Statistical System. The plan critically assessed data gaps, strengths, weaknesses,
opportunities, and threats to the KNBS and the national statistical system. The plan
identified and prioritized expected statistical user needs, activities required, inputs, outputs
and outcomes to be achieved in order to meet user needs for policy decision-making and
planning.
The plan was designed to cover the main official data producing agencies in the
country KNBS, Ministries of Education, Health, Gender, Transport and Communication,
the Departments of the Judiciary, Police, Prisons, Probation, Civil Registration,
Immigration, the Central Bank of Kenya, the Kenya Revenue Authority, the Monitoring and
Evaluation Unit in the Planning Ministry, Kenya Revenue Authority and research and
academic institutions as collaborating agencies. Subsequently in September, 2003, an
implementation plan for the National Statistical System was firmed up. Its overall purpose
was to operationalize the strategic plan by interpreting and translating the strategic
objectives articulated in the Strategic Plan into actionable plans.
The Government is now in the implementation stage towards the realization of the
NSS. In February, 2004 it started the preparation of a Strategic Implementation Master Plan
(SIMP). The main objective of the SIMP is to guide the process aimed at effectively
managing the comprehensive production and dissemination of official statistics to inform
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national development initiatives and processes, and the maintenance of a socio-economic
database. This SIMP has been compiled by the KNBS in consultation with line ministries,
Government departments, UN organizations, research and training institutions and
assistance from development partners.
The inputs of the partners have been through technical assistance as well as through
participatory workshops and country mission reviews. The World Bank (WB) has been
taking the lead role both in the preliminary work leading to the conceptualization and
compilation of this SIMP.
2.3.1 Proposed Programme
The plan contains proposals towards NSS institutional strengthening with regard to
organizational development in terms of human resource, staffing and development,
investments in building statistical and physical infrastructure, and adoption of better
management practices. The activities included the following;
1. Creation, development and maintenance of a NSS to ensure collection, analysis,
publication and dissemination of integrated, relevant, reliable and timely statistical
information;
2. Establishment of a semi-autonomous institution for coordination, monitoring and
supervision of the NSS and
3. Capacity building in line ministries, departments and parastatals.
2.3.2. Co-ordination
Mechanism involved establishment and put in place, inter-agency coordination on
data collection and dissemination programs and for technical coordination on
establishment and implementation of standards and methodologies through the entire
statistical system, and professional resources. The role of KNBS included initiating an
effective dialogue with data users and respondents and creates statistical awareness which
in turn should contribute to improve user satisfaction and build confidence in statistics.
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2.3.3 Benchmarking
Both Internal and International benchmarking are to apply guided by;
(i) User Satisfaction
(ii) Effective Processes and
(iii) Staff Satisfaction
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3.0. Reference Situation for the Food and Agriculture Statistics System
3.1 Legal Framework and Food and Agriculture Statistical Advisory Bodies
The KNBS is mandated by Statistical Act 2006 to be the official Government Agency
responsible for Statistics in the country. It is responsible for Macroeconomics Statistics,
Labour and Industry statistics, Population and Social statistics, Agriculture, Nutrition and
Environment Statistics and National Sample Survey and Evaluation Framework. In order to
ensure quality Agriculture, Nutrition and Environment Statistics production in the country,
the Bureau is in the process of setting up sub committees to meet on quarterly basis to
discuss issues affecting statistics in the sub-sector. Since the Bureau is the official arm of
Government that deals with statistics, it has a full-fledged department dealing with
agriculture, nutrition and environment statistics as hitherto mentioned above. The
department assists the productive sector in the generation of food and agricultural
statistics. The membership of the proposed committee is drawn from the production sector
ministries responsible for the data production, with the chair of the committee being the
Director of Productive directorate at the KNBS.
The main line ministries and departments generating food and agricultural statistics are:
1. Ministry of Agriculture (MoA),
2. Ministry of Livestock Development (MoLD),
3. Ministry of Fisheries (MoFD),
4. Office of the President (OP),
5. Ministry of Environment and Mineral Exploration (MoE&ME),
6. Ministry of Lands (MoL),
7. Cooperative and Market Development (MoCMD),
8. Ministry of Trade (MoT),
9. Ministry of Regional Development (MoRD),
10. NGOs, and
11. Research Institutions.
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Figure 1: The proposed Structure of the Food and Agriculture Statistics System
A situational analysis on Food and Agriculture Statistics was conducted. This
report will inform the development of strategy for development of Food and
Agricultural Statistics.
Director Production (KNBS)
Director Crops, (MoA)
Director Livestock Production, (MoLP)
Director Fisheries Production, (MoFP)
Research Instituations
Director General (KNBS)
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Figure 2: Structure of the CountrySTAT Project
Technical Working Groups (TWG
National Steering Committee
National Project Coordinator
CountrySTAT
KNBS Ministry of Agri. Research Inst. Private Organization
Other F&Agri. Data Producers
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3.2 Human Resources available
(a). Kenya National Bureau of Statistics Current Organization Structure
The functional Organisation Structure for KNBS provides for the Director General as the overall head of KNBS and reports to the Board of Directors on all matters relating to management and administration of the organisation. The Organizational Structure of KNBS is divided into six Directorates, each with given responsibilities and headed by a Director. The following is a brief description of the respective directorates:
� Directorate of Strategy and Development is responsible for Planning and
Policy, Research and Development, Methods and Standards, and NSS Coordination.
� Directorate of Population and Social Statistics is in charge of Social Statistics, Population Statistics, NASSEP and Cartography.
� Directorate of Macroeconomic Statistics is responsible for External and Financial Statistics, National Accounts, Transport and Tourism Statistics, and Fiscal Statistics.
� Directorate of Production Statistics is responsible for Labour, Industrial, Agriculture, Nutrition and Environment Statistics.
� Directorate of Information and Communication Technology is responsible for Data Processing, Information Systems and Operations, and Information Services.
� Directorate of Finance and Administration is responsible for Finance, Administration and Human Resources Management and Development.
� Director General Office is in charge of Audit and Risk Management, Public Affairs and Corporate Communication, and Procurement.
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Figure 3. Diagrammatic Representation of Organization Structure
Source: KNBSDraft Strategic Plan, 2008-13
Director – General
Manager, Procurement
Manager, Public Affairs & corporate Communication
Manager, Internal Audit and Risk Management
Planning and Policy
Research & Development
Methods and Standards
NSS Coordination
Social Statistics
Population Statistics
NASSEP & Cartography
External & Financial Statistics
National Accounts & Fiscal Statistics
Transport & Tourism Statistics
Labour & Industry Statistics
Agric. Nutrition and Environmental
Statistics
Director, Information Technology
Data Processing
Information Systems & Operations
Information Services
Finance
Administration
HR Management & Development
Board of Directors
Director Strategy & Development
Director, Population & Social Statistics
Director, Macroeconomic
Statistics
Director, Production Statistics
Director, Finance and Administration
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Figure 4: Diagrammatic Representation of the proposed field organization-short term
Source: KNBSDraft Strategic Plan, 2008-13
Director Population & Social Statistics (1)
Senior Manager NASSEP & Cartography (1)
Driver (1)
Enumerator (1) Administrative Assistant (1)
Driver (1)
Enumerator (1) Administrative Assistants (1)
Region (1)
Senior Regional Coordinator Western
Region (1)
RC Western Region (1)
District Statistical Officer (8)
Statistical Assistant (1)
Senior Regional Coordinator Eastern
Region (1)
RC, Eastern Region (1)
District Statistical Officer (8)
Statistical Assistant (1)
Manager NASSEP (1)
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Functions of the Board
i) Formulate and monitor the implementation of policies pertaining to the Bureau;
ii) Determine from, time to time, the structure and staffing levels of the Bureau;
iii) Recruit suitable staff for the Bureau upon such terms and conditions as it may determine;
iv) Promote professionalism and discipline among the staff of the Bureau by facilitating professional training;
v) Approve the Bureau’s Corporate plan, Annual work programmes and Annual Budget; and
vi) Submit to the Minister a quarterly report on the activities of the Bureau. Functions of Director General Office
The KNBS Act stipulates the Director-General responsibilities as follows:
i. Setting the overall strategic direction of the organization; ii. Directing, guiding and driving the effective and accurate production of
population and social, macroeconomics, agriculture, nutrition and environment, and labor and industry statistics (with support from the senior managers of the respective divisions);
iii. Ensuring that official statistics meet internationally acclaimed standards and practices;
iv. Managing relations with key stakeholders, donors and international role players (with the support of the Public Affairs and Corporate Communications Manager); and
v. Improving governance processes to achieve operational excellence in relation to employees satisfaction, managing costs and compliance to legislation.
Table 1: Current KNBS Staff Establishment
Category Establishment Filled Vacant
Professional 69 67 2
Sub-professional 140 107 33
Technical 15 16 0
Administrative 5 6 0 Clericals 706 313 393
Secretaries 29 27 2
Support 64 51 13
Total 1,028 587 443 Source: KNBS Strategic Plan, 2003 -2008
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(b) Ministry of Agriculture
The Ministry’s human resource falls into two broad categories, the Technical and
Supportive departments. The supportive department largely supports the technical in
pursuing the Ministry’s stated objectives. Over the years natural attrition and freeze on
recruitment have over the years resulted in the decrease in the number of staff.
For efficient delivery of services, the Ministry has been implementing reforms in the
area of human resources. Despite the improvements in the staff performance during the
period under review, inadequate staff has often hampered service delivery. This is
explained by the current staff to farmer ratio of 1:978 as compared to the Food and
Agriculture for United Nations (FAO) recommended ratio of 1:400.
Table 2: Optimal Staff Establishment of the MoA
Optimal Technical Staff Inpost Variance 11,860 8,560 3,300
Source: MoA Strategic Plan, 2008-2012.
The current staff numbers are not adequate to satisfy the deployment needs and requirements at various operational levels.
Table 3: Distribution of Staffing Levels by gender
Year Male Female Total
2002/2003 - - 9,298
2003/2004 - - 8,256
2004/2005 4,552 3,273 7,825
2005/2006 4,667 3,292 7,959
2006/2007 4,639 2,699 7,338
2007/2008 4,674 2,613 7,287
2008/2009 5,163 3, 442 8,605
Source: MoA Strategic Plan, PER, 2009.
Although most of the human resource policies in the civil service are centralized, it
has been prudent for the ministry to formulate internally regulated policies which address
its specific needs. The current in-post staff is not adequate to satisfy the deployment
requirements at various functional levels. The optimum establishment for the MOA is
11,860 posts with the total in post of 8,560.
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(c) Ministry of Livestock Development (MOLD)
The livestock sub-sector has a high growth potential and is critical for supporting
both subsistence farmers and pastoralists. It accounts for 42% of Kenya’s agricultural GDP
and 10% of the entire GDP. It employs 50% of the labour force and supplies the domestic
requirements of meat, milk, and dairy products and other livestock products. In addition
livestock products account for 20% of total marketed agricultural products and about 5% of
the total agricultural exports.
Organization of the MOLD
Currently, the Ministry of Livestock Development is composed of two technical
departments; Department of Livestock Production and Department of Veterinary Services.
In addition, it has four Semi Autonomous Government Agencies (SAGAs) namely; Kenya
Dairy Board, Central Artificial Insemination Service (CAIS), Kenya Veterinary Vaccines
Production Institute (KVEVAPI) and Kenya Meat Commission (KMC).
Livestock Data
Livestock Officers have no standard methodologies for sampling stocking
households or computing livestock estimates. The methods may be varying in details from
one officer to the other.
Table 4: Ministry of Livestock Development Human Resource
Department Authorized Establishment In-post
Veterinary Services 8821 2567
Livestock Production 5481 2218
Administration 371 196
Total 14673 4981 Source: MoLD Draft Strategic Plan, 2008-2012
(d) Ministry of Fisheries Development
Currently, both the technical and the administrative department lack sufficient
numbers of adequately trained personnel to man the ministry. There is, therefore, an
urgent need to recruit, and continue training the officers in many public and private sector
areas of the fishing industry such as gear and craft technology, data analysis, quality
control, post-harvest technology, marketing, management, trade and investment
26
negotiations. Training needs assessment should be regularly done to identify areas in need
of training in the ministry. The fisheries sector needs to collaborate with local and
international institutions to achieve these objectives.
(e) Non-Human Resources available
As a parastatal, KNBS relies on the Treasury for its budgetary needs. Most of the funds are
allocated to the recurrent vote where most of the money is spent on personnel related costs.
The development vote is the one that is used for data collection, analysis and dissemination
that are the core functions of the Bureau. The funds are usually inadequate for the bureau
activities.
Table 5: Expenditure for the Sector Ministries (Kshs Million, 2008/09*)
No Ministry Recurrent Development Total
1 Agriculture 7,712.40 4,005.20 11,717.60
2 Livestock Development 2,860.30 1,212.40 4,072.50 3 Cooperative Devt. & Marketing 882.20 219.00 1,101.20
4 Lands 1,440.80 574.40 2,015.20
5 Regional Development Authority 688.40 708.60 1,397.00
6 Environment & Mineral Resources 1,058.10 627.60 1,685.70
7 Tourism 1,222.20 478.00 1,700.20
8 Fisheries Development 723.50 227.50 951.00 9 Trade 1017.90 98.80 1,116.70 Total
17,605.80
8,151.50 25,757.30 Source: ARD Sector Report 2009 & Ministry of Finance * Provisional
3.3 Data Dissemination Policy for Food and Agriculture Statistics
In addition to sharing out analyzed information with stakeholders, the Bureau has
developed a draft policy on dissemination of micro-data and its now sharing out
anonymized information. This includes all statistics published by the Bureau. The bureau
has the following publications;
1. The Economy Survey – Annual Publication
2. The Statistical Abstract-Annual Publication;
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3. Quarterly Economic Surveys
4. Periodical Surveys
3.45 Modalities of promoting User-Producer Dialogue
A forum is to be launched soon for the User-producer dialogue.
3.5 Existing Databases and Data Dissemination Tools and Platforms
� Separate databases exist within line Ministries and KNBS
� Steps have been taken to develop an Integrated Agricultural database
� CountrySTAT will act as a one stop shop for all the agricultural statistics
3.6 Dissemination Tools available are:
� KNBS, MOA and Food Security websites
� Publications
� CD-ROMs
3.7 Dissemination Platforms
� Workshops, Seminars
� Quarterly meetings etc
3.8 Regional Integration and International Technical Assistance received
� The Bureau is closely working with International Organisations.
Consequently, it has received a lot of TA from FAO and other organisations
� The Bureau is part of the development of East African Statistical Database and
COMESA Agricultural statistical database - FAMIS.
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3.4 Data Collection and Dissemination
3.4.1 Ministry of Agriculture
Data collection activities are executed within the framework for statistical
information which is co-ordinated by the Central Planning and Project Monitoring
Department (CPPMU) within the Ministry. The head and technical staff of this department
are professional economists and statisticians seconded to the ministry of agriculture by the
ministry of Planning, National Development and Vision 2030.
The CPPMU department engages the Technical Department through the established
directorates in generating data collection activities as well as designing the procedures and
protocols for data management, analysis and dissemination.
The technical directorates, which are as follows;
i. Directorate of Policy & Agricultural Development Coordination;
ii. Directorate of Land and Crop Development;
iii. Directorate of Agribusiness, Agricultural Information and Market Development; and
iv. Directorate of Extension, Research Liaison & Development.
Agricultural data is scattered in various institutions. These include; National Cereals
and Produce Board (NCPB), Horticultural Crops Development Authority (HCDA), Kenya
Tea Development Agency (KTDA), Coffee Board of Kenya, Research Institutions among
others. Agriculture data from these sources are fragmented and are not always processed,
digitized or stored in a systematic manner. Further, data users such as planners and
researchers often encounter significant challenges in accessing the information. These
include data limitations/gaps, inconsistencies of data, poor data management, lack of data
bases and unavailability.
(a) Process of Data Collection and Information Flow
Actual data collection tasks are undertaken in the farming units and the information
transmitted to the head office (ministry HQs) through structured channels. For all field
activities reflected in the annual work-plan, Provincial Directors of Agriculture (PDA) are
formally briefed by the individual directorates on the nature of tasks involved, the
respective timelines and the necessary logistical arrangements. The same message is
relayed further by the PDAs to the District Agricultural Officers (DAO) who are the actual
29
implementers of the tasks. Fig. 2. provides an illustration of the existing infrastructure for
data collection and the flow of information to the ministry.
At the grass root level, there are Frontline Extension Officers (FEOs) deployed at the
level of Farming Units (FU’s), to maintain direct contact with farmers for purposes of
providing extension services, and also to collect a variety of agricultural data. The FU’s are
created at the Sub-location or Location level, depending on the agricultural workload in
specific districts. Other determinants include the concentration of farm holdings (settlement
patterns) and the dominant terrain. The officers rely mainly on projected estimates based
on the 1999 census data for information regarding the distribution of farm holdings.
The FEOs are expected to present monthly reports on all aspects of extension and
data collection activities during monthly divisional meetings convened by the Divisional
Agricultural Extension Officer (DAEO). The divisional meetings are attended by all
Divisional Subject Matter Specialists (Div. SMS), namely:
i. Divisional Crop Development Officer
ii. Divisional Horticultural Crop Development Officer
iii. Divisional Agribusiness Development Officer
iv. Divisional Home Economics Officer
v. Divisional Environment Officer
Each SMS are technical officer responsible for a specific area of specialization. Their
deployment in a district is generally determined by the prevalence of agricultural activities
that are relevant to their respective areas of expertise. All Divisional SMSs are mandated to
study field reports from each FEO in order to extract details that would enable them to
prepare specialized reports on their respective areas of engagement. The specialized reports
are subsequently merged to constitute a divisional report, which is submitted to the District
Agricultural Officer (DAO) by the DAEO. Each District SMS extracts relevant information
from all divisional reports and prepares a district specialized report. These are merged to
generate a district report, which is submitted to the Provincial Director of Agriculture
(PDA) by the DAO. The final document is a provincial report submitted to the ministry
headquaters by the PDA. It is a consolidated version of all provincial specialized reports,
based on extracts from individual district reports.
The provincial, district and divisional heads are administrative managers. They have
their respective areas of expertise, but may not be authorities in all technical aspects. For
this reason, Subject Matter Specialists have the liberty to discuss and suggest options
regarding technical issues with relevant officers in the lower or upper hierarchies, as long
as the administrative managers concerned are informed.
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(b) Market Prices
Data on market prices mainly originate from market surveys carried out by the
Kenya National Bureau of Statistics and the Agribusiness Department of the Ministry of
Agriculture. Other sources include proxy data from the Kenya Revenue Authority and
Marketing boards.
In the case of market information generated by KNBS, the enumeration involves a
scientifically selected sample of markets from an existing sampling frame. The frame was
first developed in 1977, but has undergone a series of reviews to cope with changes arising
from the dynamics of the economy. Actual data collection follows interview format where
trained enumerators fill respondent-based questionnaires with information from both
buyers and retailers.
Ministry of Agriculture staff similarly obtains wholesale and retail prices from
selected markets in major towns on a daily basis. The data is gathered in stages:
i. by asking wholesalers very early in the morning for wholesale prices
ii. by observing actual retail transactions
iii. by asking retailers
iv. by asking buyers
The reported market price is usually an average calculated for each crop from a
range of price details obtained after a series of observations/interviews. It is however
significant to note that there is usually no interaction between the two groups of data
collectors for purposes of to comparison.
(c) Dissemination
Dissemination is done through the local media, SMS etc on daily and weekly bases.
However, the system is faced with budgetary problems.
(d) Legal and regulatory framework
The legislative and policy framework for the ministry mandates it to provide overall
coordination of the sector and also to provide continuous assessment and review to ensure
the continued relevance of the ministry.
The Ministry uses agricultural data to formulate and monitor policies and
intervention programmes e.g. extension programmes. Such programmes have greater
impact when targeted to particular classes of farmers. Statistics on these classes of farmers
are crucial for targeting specific extension messages and other forms of support - statistics
on how many they are? where are they? What is their condition? Farmers also need
statistical information to make informed decisions. For example, farmers need market
information to determine whether it is worthwhile taking their produce to the market,
31
check on the price they are receiving vis-à-vis prevailing market prices, to decide whether
or not to store produce in anticipation of price changes, decide whether to grow different
crops, etc.
Agricultural surveys are the main source of current agricultural statistics that are
required for monitoring the performance of the agricultural sector. The survey collects data
on performance indicators for the agricultural sector. These indicators include, inter alia,
planted area, yield and production, amounts of inputs used (inorganic fertilizers,
pesticides, improved seeds, etc), use of temporary labour and agricultural prices. However,
the last Agricultural survey was conducted in 1987. And even then, not all the data from
this survey were processed and analyzed due to shortage of trained personnel in data
processing and subsequent loss of questionnaires due to inadequate storage facility. This
therefore means that the benchmark of the statistics currently in use is estimates.
(c) Challenges
i. Lack of a centralized database system;
ii. Lack of a strong dissemination policy at the ministry, leading to weak emphasis on
accountability to users with regard to data accuracy, timeliness and consistency in
data sharing for purposes of informing agricultural policies and processes.
iii. Inadequate supply of computers and related ICT facilities which delays data
transmission to the headquarters, and impairs timeliness in data analysis for
purposes of fulfilling data demands at small area levels. For this reason, information
at the division and district level is often available when it is already outdated.
iv. A weak M&E system, leading to, among other things, inadequate coordination of
data collection, analysis and storage.
32
Figure 5: Ministry of Agriculture Data Flow
Engagement channels
Feedback channels Soource: Data Needs ministry of agriculture
Divisional Subject Matter Specialists
Divisional Agricultural
Extension Officers
District Subject Matter Specialists
Provincial Subject Matter Specialists
Frontline Extension Officers
District Agricultural Officer
PERMANENT SECRETARY
CENTRAL PLANNING & PROJECT MONITORING DEPARTMENT
(Chief Economist)
TECHNICAL DEPARTMENT
(Agricultural Secretary)
Directorate of Policy &
Agricultural Development Coordination.
Directorate of Agribusiness, Agricultural Information &
Market Development
Directorate of Extension,
Research Liaison
& Development
Directorate of Land & Crop
Development
Provincial Directors of Agriculture
33
Figure 6: Ministry of Livestock Development Data Flow
Source: Ministry of Livestock
3.4.2 Ministry of Fisheries Development
The Kenya’s Fisheries sub-sector has potential to contribute significantly to the
National economy through employment creation, foreign exchange earnings, poverty
reduction and food security support. The sub-sector contributed 0.5% to GDP in the year
2006. This contribution could be higher if value addition at the various stages of the supply
chain are considered and post harvest losses minimized. The sub-sector’s growth was
estimated at 4.1% in 2005 (National Economic Survey, 2006).
Fishery is an important economic activity and serves as a livelihood to the fishing
communities in the country. The sector supports about 80,000 directly and about 800,000
people indirectly, assuming a dependency ratio of 1:10. In 2006 a total of 159,776 metric tons
of fish valued at Kshs 8.7 billion was produced in the country. In the same year, fish exports
earned the country approximately KES 5 billion.
The freshwater fisheries especially Lake Victoria supports about 35,000 fishers and
marine fisheries over 8,000 fishers. The majority of these fishers are artisanal using un-
mechanized fishing vessels.
(a) Kenya fisheries resources
Kenya fisheries resources include;
i. Capture fisheries made of marine and inland fisheries
ii. Culture fisheries made of mariculture and fresh water aquaculture
Ministry Headquarters
Provincial Livestock Production Officers
District Livestock Production Officers
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(b) Capture Fisheries
Marine Fisheries Resources
This includes the 12 nautical miles territorial waters and the 200 nautical miles EEZ.
The marine resources have considerable quantity and range of coastal and offshore marine
fisheries resources with good potential for economic development. The Kenyan marine
zone is bordered by a coastline measuring some 420 km in length in a straight line,
expanding to some 880 km when taking into account the actual coastal landscape. Two
main river systems, the Sabaki, just north of Malindi and the Tana about 80 km further
north reach the coast.
Outflow from these rivers enrich the local fishing grounds, which in turn support
commercial concentrations of shrimps (prawns). Much of the coastline is fringed by
mangrove forest and swamp. The total area of the Kenyan EEZ is about 230,000 square Km.
Kenya’s known marine inshore fishing grounds include the rich inshore grounds
around Lamu Archipelago, Ungwana Bay, North Kenya Bank and Malindi Bank. The zone
is exploited predominantly by artisanal fishermen who operate some 4,800 mostly un-
motorized boats to produce around 6,000 – 7,000 MT of fish annually valued at over KShs
500 million. Annual catches have fluctuated between 4,000 and 10,000 MT over more than a
20-year period.
The prawn fishery from which approximately 400 MT are landed each year are
fished by commercial trawlers. The offshore waters of the Kenyan zone yield catches of
large tunas, billfishes and pelagic sharks to foreign fishers.
The offshore fisheries zone is exploited by vessels from Distant Water Fishing
Nations (DWFNs). The main species sought are the highly migratory tunas including
skipjack, yellowfin and bigeye tuna. Some of the fish land in Kenya and transhipped
overseas. Others are landed directly in the Distant Nations. License fees from this earns the
Government approximately KShs 30 million(USD 375,000) per year.
35
(d) Inland fisheries
Kenya is endowed with extensive inland waters, covering in total an area of between
10,500 and 11,500 km2 (depending on rainfall/year), Inland fisheries account for about 96
percent of annual total national production. However it is the country's 6 percent share of
Lake Victoria that accounts for almost all of the national freshwater fishery catch. Other
lakes and rivers of fisheries significance include; Lake Turkana, Baringo and Naivasha.
Major rivers include the Tana, Nzoia, Kuja, Yala and Athi/Sabaki. The fisher exploiting this
resource are generally small scale Planked canoes, often equipped with dhow-rigged sails,
are the usual forms of fishing craft. Gear kits are primarily based on gill nets, long lines,
beach seines and 'mosquito' nets.
(e) Aquaculture
Kenya has great potentials for aquaculture growth. It is endowed with climatic
diversity, natural features and resources that favour the culture of a wide variety of
aquaculture species. However, though not yet quantified, only a small portion of these
resources are utilized.
Aquaculture in Kenya can be categorized into three broad divisions;
i. Warm fresh water aquaculture is dominated by the production of various species of
tilapia and the African catfish (Clarias gariepinus) mainly under semi intensive
systems using earthen ponds.
ii. Cold fresh water aquaculture involves the production of rainbow trout (Oncorynchus
mykiss) under intensive systems using raceways and tanks.
iii. Marine water aquaculture (mariculture) which is underdeveloped
The Tilapine species constitute about 90% of aquaculture production in Kenya.
Polyculture of the Tilapines with the African catfish is sometimes done to enhance
productivity under mixed sex culture systems. The production of the Tilapines and the
African catfish is characterized by low pond productivity mainly due to employment of
low pond management practices. The result has been stagnation of National aquaculture
production over the past few decades. Because of the poor perception of aquaculture as an
economic activity, it has been difficult to promote its commercialization, as most potential
investors are not convinced that aquaculture can be a profitable enterprise. Aquaculture
contributes about 1% of the total national fish production. Currently the total area under
aquaculture stands at 722.4ha which include dam aquaculture. The production from this
utilized area stand at an average of 4,300 MT per year.
(f) Fisheries Data
The Ministry of Fisheries use a standard form for collecting information on volumes
of fish catch at fish landing sites. The officers manning the sites do not undergo technical
training on data collection. Besides this challenge, the Ministry faces a significant staff
shortage. For this reason, most of the landing sites are not manned by ministry staff and the
36
information is generally provided by the fishermen themselves. For example, Lake Victoria
has a record of more than 360 landing sites. It is reported that only about 180 of these are
manned by fisheries staff. A lot of cheating has been detected in the data provided by the
fishermen.
(g) Legal and regulatory framework
Fish Inspection and Quality Assurance (FIQA)
Fish inspection and quality assurance (FIQA) is the mandate of the Competent
Authority (ca). The ca is created under “the fisheries (safety of fish, fishery products and
fish feed) regulations, 2007”, which came into force on 21st September 2007 as Legal Notice
No. 170. The CA has powers to monitor and regulate all aspects of fish handling and
processing. The Ministry responsible for Fisheries development, through the Department of
fisheries, is the CA and has the responsibility to oversee the implementation of these
regulations governing proper monitoring of fish from harvest, sorting, handling,
transportation, processing, and storage. To carry out its mandate, the technical arm of the
CA has twenty one (21) gazetted fish inspectors. The inspectors are well trained and
experienced in HACCP-based inspections. The inspectors are charged mainly with the
responsibility of inspection of the fish production areas, fish processing establishments and
markets, certification of the products and the fishing environment. A further eight (8)
inspectors have been trained but are not yet gazetted.
37
3.5 Co-operative & Marketing Sub-Sector
The Co-operative & Marketing sub-sector is seen as vital vehicle for economic
growth and poverty reduction as it embraces other sectors of the economy, including
agriculture and financial sectors. The co-operative sub-sector contributes significantly to the
GDP by mobilizing domestic savings (currently is estimated at about Ksh.105 billion
representing 31% of the national savings) and controls major agricultural exports of coffee,
tea and dairy products. In addition, the sub sub-sector employs about 250,000 and about
63% of rural and urban populations draw their livelihoods directly or indirectly from sub-
sector.
However, poor management and governance of cooperatives have over the years led
to significant decline in some sectors such as coffee, pyrethrum and urban savings and
credit societies. Thus in ability to correct credible data.
3.5.1 Ministry of Environment and Mineral Exploration
(a) Forestry Policy
The Forest Sector plays vital roles in the livelihood of the Kenyan population
through provision of invaluable forest related goods and services. The most significant
contribution is in the energy supply for domestic and industrial processes, provision of
timber for construction and trees for regulation of water flow. It is estimated that 80% of the
population use biomass energy while urban development and hydro energy rely heavily on
water. Forests will continue to provide essential goods and services such as timber, poles,
fuel-wood, food, medicines, fodder and other non-wood forest products. Forest resources
and forestry development activities also contribute significantly to the national economy by
supplying raw materials for industrial use and creating substantial employment
opportunities and livelihoods. As important as the country forest’s are to the national
economy, their sustainable development and management continues to be hampered by a
number of factors, including inadequate financial resources and the lack of an enabling
policy and legislation. In addition, the increasing population and poverty continue to exert
pressure on the country’s forest resources. This pressure is witnessed in the current
rampant illegal logging, illegal charcoal making and encroachment for agriculture and
settlement. These challenges have undermined the Government’s efforts in achieving
38
sustainable forest management. Kenya is internationally considered to be a low forest cover
country as it has less than 10% of its total land area classified as forest. The Government
will therefore put in place measures to significantly increase the area under forest cover,
with the aim of attaining at least 10% within the next decade. To attain this level of forest
cover, the Government will promote farm forestry, intensify dryland forest management,
involve the private sector in the management of industrial plantations and also promote
community participation in forest management and conservation. The key elements of the
new policy are:-
1. A new forest legislation to implement the policy.
2. Expanded mandate in the management of all types of forests.
3. Involvement of forest adjacent communities and other stakeholders in forest
management and conservation.
4. Forest management planning will be based on an eco-system approach.
5. Appropriate incentives will be provided to promote sustainable use and
management of forest resources.
6. Proposed institutional transformation of the Forest Department into a semi-
autonomous Kenya Forest Service.
This policy will address local and global forestry issues and challenges to ensure fair
contribution of the forestry sector in economic development. The implementation of this
policy is expected to improve the social welfare of the Kenyan population without
compromising environmental conservation.
3.6 Meteorological Data
There is a general agreement among data users regarding the consistency by the
Department of Meteorology on their weather briefs. However, the information which is
relayed through media channels is too general. Farmers would prefer the kind of data that
focuses on small areas and adequately informs their farming decisions. Further, there is a
significant disconnect between the Ministry of Agriculture and the Department of
Meteorology regarding protocols for sharing agro meteorological data. This has lead to
gross underutilization of the ministry’s extension network for influencing agricultural
activity through expert dissemination of weather data. It is important to note that by virtue
of their training on crop sciences and their working relationship with farmers, it is the FEOs
39
who posses both capacity and strategic position to effectively advice farmers on which type
of crops can survive specific weather conditions.
40
4. 0 Outputs, Data Sources, and Metadata of the Food and Agriculture Statistics
4.1 Introduction
The Central Planning Project Monitoring with the Ministries deals with policy and
development planning issues and also provides statistical services to the ministry and its
agencies. It receives information/data from other units/departments of the ministry, other
ministries and government agencies, and is the ministry’s main link with the Kenya
National Bureau of Statistics (KNBS) on agricultural statistics.
Agricultural statistics, which could be defined as the aggregate of numerical
information (administrative data), covers different fields within the agriculture sector such
as; Food Crops, Industrial Crops, Horticultural crops, Agricultural Inputs and Livestock ,
Fisheries, Trade and Forestry.
4.1 Crops Statistics Most of the crops statistics contained in the annual ministry of agriculture
publication known as the Economic Review Agriculture [ERA], the Kenya Bureau of
Statistics Publications, Economic surveys and the Statistical abstracts. The boards under the
ministry of agriculture also provide specific data on production.
4.1.1 Crops production system (i). Small-scale farming: Kenya’s agriculture is predominantly small-scale farming, mainly
in the high potential areas. The small-scale farming sub-sector accounts for 75 percent of the
total agricultural output and 70 percent of marketed agricultural produce. Production is
carried out on farms averaging 0.2 to 3 hectares mostly on commercial basis. Currently, the
sub-sector’s use of improved inputs such as hybrid seed, fertilizers, pesticides and
machinery is relatively low.
(ii). Medium scale farming: Medium scale farms range from 3 to 49 ha. Farmers in this
category are receptive to technology, practice commercial agriculture by investment in
inputs, and marketing of produce as well as borrowing credit for farm development.
41
(iii). Large-scale farming: In Kenya, large-scale farming is practiced on farms averaging 50
hectares for crops. Large-scale farming sub-sector accounts for 30 percent of marketed
agricultural produce. Large-scale farmers are mainly involved in the growing of crops such
as tea, coffee, maize, and wheat for commercial purposes.
4.1.2 Food Crops Statistics
The scope of crop statistics covers crop area and production Statistics. The statistical
information is mainly contained in reports of Ministry of Agriculture and Kenya National
Bureau of Statistics (KNBS). Data on crop area and production are collected by Frontline
Extension Officers at the sub-location level and transmitted upwards ending up at the
Department of Lands and Crop Development in the Ministry’s Head Office where they are
aggregated to give national totals.
The Regional Centre for Mapping of Resources for Development (RCMD) produces
data on early warning systems based on cloud patterns and wind movement which signal
droughts, floods and locust invasion. In addition, RCMD produce resource sensing maps
showing crop and forest areas.
Data for crop prices are produced by the Department of Agri-Business and Market
Development Information in the Ministry of Agriculture. Other sources of Agricultural data
are Kenya Agricultural Research Institute (KARI) which produces statistics on area under
major food crops and yield levels. (Annex table 6)
4.1.3 Industrial Crops Statistics The main industrial crops in Kenya include tea, coffee, sugarcane, cotton, sunflower,
pyrethrum, barley, tobacco, sisal, coconuts, and bixa. Industrial crops contribute 55 percent
of agricultural exports. Among the above crops tea is still one of the leading foreign
exchange earners in the country. . (Annex table 10-16)
4.1.4 Horticulture sub-sector The horticultural sub-sector plays an important role in the Kenyan national economy. The products
include cutflowers, vegetables, fruits, nuts, herbs and spices. . (Annex table 17)
42
Type of Data Collected
In broad terms, statistical information generated by the agriculture sector can be classified
under:-
i. Categories of agricultural land
ii. Number of farm holdings
iii. Acreage under crop
iv. Crop production
v. Soil conservation
vi. Crop protection services
vii. Livestock production/ products
viii. Fisheries production
ix. Inputs
x. Irrigation
xi. Forestry production /services
xii. Agricultural cooperatives
xiii. Market prices
xiv. Weather
xv. Early warning systems
xvi. Staff returns
The Methods of data collection vary by sub-sector, and according to specific types of
information. Whereas the sector ministries use their own resources to generate primary
data on livestock and food crops, they largely rely on marketing bodies to obtain secondary
data on industrial and horticultural crops.
4.2 Livestock Statistics The data available collected by the ministry of livestock includes population by species and
type and livestock products, (Annex table 21)
43
4.3 Fishery Statistics
The data available collected by the ministry of fisheries includes production by region,
import and export of the fish products. . (Annex table 22)
4.4 Forestry Statistics
The data available collected by the forestry includes planted area, changes in forest
plantation and sales of forest products. . (Annex table 30)
4.5 Trade Statistics The data available includes import, export and re-exports of commodities. . (Annex table 29) 4.6 Land under use Data on the sub-section presents how Kenyas land is utilized. The total surface area of Kenya is
about 587,000 km2, out of which the land area is about 576,000 km2 and the area under water is
about 11,000 km2. About 16 percent is High and Medium Potential Land (HMPL) while the
remaining 84 percent is classified as arid and semi-arid lands (ASALs).
. (Annex table 33) 4.7 Description of National/Sub-national commodities codes System The country does not have local commodity codes. Therefore, it is prudent to come up with
local codes for uniformity purpose.
4.8 National classification/nomenclatures and links to international classifications
Some products have international codes. . (Annex table 34)
4.9 Limitations of the available Food and Agriculture Statistics Estimation:- The data is not obtained by physical measurement, but is an eyeball
estimation by local agricultural extension staff. The data is not factual but estimates, and
hence carries a lot of subjectivity. In addition, as the data is transmitted from the field
upwards, other biases are introduced at the provincial level and the Ministrys headquarters
in the process of subjectively adjusting the data from the districts.
44
Data Gaps: - The data set lack some gaps which need to be filled.
Lack of Capacity:-There is limited capacity both human and financial;
45
5.0 Overview of User Needs for Food and Agriculture Statistics
5.1 Public Sector Decision Makers
Public sector generally consumes most of the agricultural indicators that are generated. The
indicators range from agricultural production, consumption, imports and exports. The
decision makes include; Permanent Secretatary, KFSSG, lead agencies, and NCPB.
5.2 Private Sector Decision Makers
The private sector is also concerned with production of agricultural commodities, food
consumption statistics, cost of agricultural inputs, statistics on agricultural machineries and
marketing outlets. Public sector uses national statistic data for short and long term planning
and decision-making.
46
6 Expectations from CountrySTAT and Synergies with on-going Initiatives – Country Name
CountrySTAT is an important FAO initiative that aims at assisting countries in
developing a one-stop shop for all agricultural data. In Kenya, we had the privilege of
participating in the pilot phase of the initiative and appreciated the importance of the
system. We have identified officers who would be fully responsible for the development
and maintenance of the system in the country.
• The system is owned by the implementing ministrys’as a platform to disseminate
agricultural and other statistical works.
47
7. Important Factors for the Success of the CountrySTAT project – Country Name
In order for the project to succeed in Kenya, a number of factors need to be put into
consideration. Among these factors are:
� Availability of a powerful computer system and its accessories
� Identification of dedicated officers to be trained on the system and thereafter
domesticate and maintain it on a regular basis
� Provision of funds for data compilation and maintenance of the system
� Provision of technical backstopping on the system operations.
� Establishment of baseline data at the district.
48
8.0 ANNEXES I : Bibliography
Government of Kenya-Ministry of Agriculture and Livestock Development: Economic
Review of Agriculture 2005.
Government of Kenya-Ministry of Agriculture and Livestock Development: Economic
Review of Agriculture 2006.
Government of Kenya-Ministry of Agriculture and Livestock Development: Economic
Review of Agriculture 2007.
Government of Kenya-Ministry of Agriculture, the Central Planning and Project
Monitoring Unit: Economic Review of Agriculture 2008.
Government of Kenya-Ministry of Agriculture, the Central Planning and Project
Monitoring Unit: Economic Review of Agriculture 2009
Government of Kenya-Ministry of Livestock and Fisheries Development: Strategic Plan of
the Ministry (2005-2009) Draft Report.
Government of Kenya-Ministry of Livestock and Fisheries Development (Fisheries
Department): Fisheries Annual Statistical Bulletin 2002.
Government of Kenya-Ministry of Livestock and Fisheries Development, National
Agriculture and Livestock Extension Programme, Annual Report (July 2006-June 2007)
KIPPRA, 2007: The Kenya Agricultural Sector Data Compendium Vol. 1, Overview and
General Statistics.
Magazi-Apuuli J.B: Integrated Framework for the Development of Agricultural Statistics in
Uganda.
Mukasa J.B & Magazi-Apuuli J.B., 2001: Development of Food and Agricultural Statistics
within the Overall Framework of the National Statistical System-Example of Uganda
~ 49 ~
Annex II: Data Sets
Food Crops
Table 6: Production of Food Crops by Province, 2008*
Province Crop
Indicator Rift Valley Nyanza Eastern Western Coast Central North Eastern Nairobi
Total
Crop area (ha) 549,448 254,355 508,135 238,009 92,139 146,383 3,606 1,682 1,793,757
Bags (90 Kgs) 17,290,944 1,407,175 2,045,219 4,022,667 609,029 912,240 392 14,553 26,302,219
Maize
Yield (Bag/ha) 31 6 4 17 7 6 1 9 15
Crop area (ha) 314,827 0 8,245 538 0 6,663 0 0 330,273
Bags 3,075,852 0 530,835 14,736 0 115,818 0 0 3,737,241
Wheat
Yield (Bag/ha) 10 0 64 27 0 17 0 0 11
Crop area (ha) 13,572 0 1,040 0 0 65 0 0 14,677
Bags 453,220 0 41,455 0 0 800 0 0 495,475
Barley
Yield (Bag/ha) 33 0 40 0 0 12 0 0 34
Crop area (ha) 118,927 155,542 171,570 159,041 1,875 1,790 7 1,675 610,428
Bags 997,271 631,910 545,859 489,235 9,616 219,714 8 7,624 2,901,237
Beans
Yield (Bag/ha) 8 4 3 3 5 123 1 5 5
Crop area (ha) 0 3,427 0 485 1,932 10,871 19 0 16,734
Bags (50 Kgs) 0 207,620 0 29,558 6,112 193,460 878 0 437,628
Rice
Yield (Bag/ha) 0 61 0 61 3 18 46 0 26
Crop area (ha) 3,414 34,407 52,240 12,799 879 205 97 0 104,041
Bags 41,237 236,285 253,171 68,676 2,517 457 567 0 602,910
Sorghum
Yield (Bag/ha) 12 7 5 5 3 2 6 0 6
Crop area (ha) 5,141 9,315 34,426 3,983 146 144 0 0 53,155
Bags 64,878 156,581 132,563 71,593 904 409 0 0 426,928
Millet
Yield (Bag/ha) 13 17 4 18 6 3 0 0 8
Crop area (ha) 1,288 4,734 131,098 4,322 6,695 0 0 21 148,157
Bags 6,243 25,737 436,650 26,154 37,943 0 0 83 532,810
Cow Peas
Yield (Bag/ha) 5 5 3 6 6 0 0 4 4
Crop area 371 2,135 83,704 1,302 3,893 47 0 0 91,452
Bags 5,579 10,172 257,868 7,226 15,813 150 0 0 296,808
Green Grams
Yield (Bag/ha) 15 5 3 6 4 3 0 0 3
Crop area 66 0 10,402 0 0 4,696 0 0 15,163
Bags 711 0 50,067 0 0 531 0 0 51,309
Dolichos
Yield (Bag/ha) 11 0 5 0 0 9 0 0 3
Crop area (ha) 255 0 194,174 0 463 1,067 0 0 195,959
Bags 2,899 0 927,811 0 1,908 2,491 0 0 935,109
Pigeon Peas
Yield (Bag/ha) 11 0 5 0 4 2 0 0 5
~ 50 ~
Province Crop
Indicator Rift Valley Nyanza Eastern Western Coast Central North Eastern Nairobi
Total
Crop area (ha) 4,769 35,867 6,632 14,732 731 0 0 55 62,785
Tons 100,016 599,554 40,894 148,221 5,763 0 0 333 894,781
Sweet Potatoes
Yield (Tons/ha) 21 17 6 10 8 0 0 6 14
Crop area (ha) 662 18,010 8,101 17,144 10,745 0 0 11 54,673
Tons 15,740 339,214 57,555 194,646 143,614 0 0 195 750,964
Cassava
Yield (Tons/ha) 24 19 7 11 13 0 0 18 14
Crop area (ha) 68 0 717 1,453 0 0 0 16 2,254
Tons 502 0 4,469 11,639 0 0 0 262 16,872
Arrow Root
Yield (Tons/ha) 7 0 6 8 0 0 0 16 7
Crop area (ha) 808 808
Tons 6,123 6,123
Yams
Yield (Tons/ha) 8 8
Crop area (ha) 260 351 1,827 2,438
Bags 449 1,570 17,303 19,322
Soya Beans
Yield (Bag/ha) 2 4 9 8
Crop area (ha) 1,004 18,976 1,026 4,092 0 0 0 0 25,098
Bags 8,192 78,427 5,259 31,282 0 0 0 0 123,160
Yield (Bag/ha) 8 4 5 8 0 0 0 0 5
Ground Nuts
Value (Mil. Kshs) 115,170
Coconut Crop area (ha) 0 40,761 40,761
Bags 0 59,897 59,897
Yield (Bag/ha) 0 1 1
Value (Mil. Kshs) 22 22
Crop area (ha) 26,249
Bags 15,597
Yield (Bag/ha) 1
Cashew nut Value (Mil. Kshs) 17 Source: Department of Land and Crops Development and Management, MoA, Provincial Annual Reports. * Provisional
~ 51 ~
Table 7: Crop Production, 2001 – 2008 (tons)
Production of Primary Crops
Year 2001 2002 2003 2004 2005 2006 2007 2008*
Product code Product
15 Wheat 257,255 307,523 379,034 397,005 365,696 358,061 354,249 336,688
27 Rice 44,996 44,996 40,498 49,290 57,942 64,840 47,256 21,881
56 Maize 2,757,620 2,411,007 2,713,561 2,454,930 2,918,157 3,247,777 2,928,793 2,369,569
83 Sorghum 116,724 115,700 127,343 86,580 150,127 131,188 147,365 54,316
79 Millet 61,072 72,327 63,731 75,171 59,481 79,207 119,599 38,462
176 Beans 370,862 481,225 429,183 232,074 375,820 531,800 383,900 261,137
197 Pigeon Peas 93,537 93,296 98,378 105,571 94,950 116,841 95,637 84,168
195 Cowpeas 49,264 59,428 46,967 29,321 36,242 87,808 83,251 47,958
125 Cassava 608,493 601,976 421,317 388,713 566,400 656,633 397,705 750,964
122 Sweet Potatoes 598,680 513,485 587,700 546,309 671,709 724,646 811,531 894,781
137 Yams 7,898 7,584 8,007 7,086 7,238 8,001 6,905 6,123
156 Sugar cane 3,550,792 4,501,363 4,204,055 4,660,995 4,800,820 4,932,839 5,204,214 5,176,670
249 Coconut 58,706 61,052 56,937 69,245 61,824 6,607 6,617 10,400
~ 52 ~
Table 8: Producers Prices for Primary Crops, 2001 – 2008 (Tons) Producers Prices for Primary Crops
Year 2001 2002 2003 2004 2005 2006 2007 2008*
Product Product
15 Wheat 18,411 17,244 19,089 22,167 18,211 19,044 33,333 28,889
27 Rice 26,250 16,060 16,150 26,000 16,250
56 Maize 8,800 11,689 15,089 16,467 15,144 14,444 13,333 27,778
83 Sorghum 14,656 18,956 20,978 24,444 18,889 13,933 12,222 13,667
79 Millet 23,456 25,856 28,611 31,111 26,667 18,889 28,889 30,000
176 Beans 30,956 27,300 31,478 33,333 27,778 28,222 48,889 50,000
197 Pigeon Peas 26,667 28,889 31,111 33,333 31,111 30,067 33,333 35,556
195 Cowpeas 17,778 19,444 20,000 27,778 22,222 28,333 32,222 34,444
125 Cassava 7,144 6,779 7,504 8,000 6,500 6,500 10,000 9,000
122 Sweet Potatoes 15,021 14,101 13,871 15,500 14,500 14,600 17,500 16,500
137 Yams
156 Sugar cane 2,015 2,015 1,800 1,800 1,910 2,027 2,249 2,400
249 Coconut 11,700 11,200 13,500 16,000 16,600 11,300 12,000 12,500
~ 53 ~
Table 9: Production of Primary Crops, 2001 – 2008 (tons)
Production of Primary Crops
Year 2001 2002 2003 2004 2005 2006 2007 2008*
Product Product
15 Wheat 129,209 144,794 151,135 145,359 159,477 150,488 104,176 130,273
27 Rice 13,200 13,000 10,781 13,322 15,940 23,106 16,457 16,734
56 Maize 1,707,403 1,592,315 1,670,914 1,819,817 1,760,618 1,888,185 1,615,304 1,793,757
83 Sorghum 136,078 144,294 148,985 123,155 122,368 163,865 155,550 104,041
79 Millet 104,292 118,700 108,343 129,750 92,430 137,711 128,114 53,155
176 Beans 870,357 928,651 879,032 872,070 1,034,477 995,391 846,327 610,428
197 Pigeon Peas 164,001 164,453 183,612 195,308 180,240
195 Cowpeas
125 Cassava
122 Sweet Potatoes
137 Yams
156 Sugar cane
249 Coconut
~ 54 ~
Table 10: Tea Production, 2004 – 2008
Year 2004 2005 2006 2007 2008*
Area (ha) 48,800 48,600 51,300 51,010 50,605
Production
Tons 132,100 130,800 119,401 139,990 134,963
Estates
Yield (tons/ha) 2.7 2.7 2.3 3.11 2.8
Area (ha) 88,000 92,700 95,780 98,180 107,115
Production
Tons 192,600 197,700 191,177 229,610 210,854
Small Holders
Yield (tons/ha) 2.2 2.1 2.0 2.7 2.4
Total Area (ha) 136,800 141,300 147,080 149,190 157,720
Total Production (tons) 324,700 328,500 310,578 369,600 345,817
Price of Black Tea (per 100 kg) 12,696 11,824 14,642 11,846
Consumption (million kgs) 13.6 14.0 16.5 17.6 17.4
Exports (million kgs) 333.8 349.7 313.7 345 383
Exports (million Kshs.) 43,446.7 42,862.9 47,297.4 43.2 62.2
Source: Tea Board of Kenya
~ 55 ~
Table 11: Coffee Production, 2004 – 2008
Year 2004 2005 2006 2007 2008
Area (ha) 42,000 42,000 42,000 42,000 40,680
Production
Estates Tons 18,473 20,745 21,257 25,000 19,740
Area (ha) 128,000 128,000 128,000 120,720 122,040
Production
Small Holders Tons 29,958 24,500 27,046 28,368 22,260
Estate 3 0.5 0.5 0.6 0.5
Yield (tons/ha) Small Scale 0.2 0.2 0.2 0.2 0.2
Total crop area (ha) 170,000 170,000 170,000 162,720 162,720
Total Production (tons) 48,431 45,245 48,303 53,368 42,000
Price of processed coffee (per 100 kg) 12,696 11,824 10,952 19,561 Na
Local Consumption (tons) 1,937 1,810 1,932 1,960 1,680
Exports (million Kshs.) 7,135.20 8,224.70 8,704.30 8,803.00 9,300.00
Total Value (billion Kshs.) 6.7 8.33 8.7 8.89 Na
Source: Coffee Board of Kenya Local consumption at 4 percent of the total production
~ 56 ~
Table 12: Sugar Production, 2004 – 2008
Year 2004 2005 2006 2007 2008
Under Cane 131,507 144,765 147,730 158,568 169,421Area (ha)
Harvested 54,191 56,537 54,621 59,201 54,465
Sugarcane production (tons) 4,660,995 4,800,820 4,932,839 5,204,214 5,176,670
Yield of Sugarcane (tons/ha) 73.8 71.5 70.89 70.87 72.9
Price of Cane (Kshs./tons) 1,800 1,910 2,027 2,249 2,400
Sugar Production (tons) 516,803 488,997 475,670 520,404 517,667
National Consumption (tons) 669,914 695,622 718,396 741,190 751,523
Domestic price of sugar (Kshs/ton) 33,810 48,449 52,547 57,063 52,240
Exports (tons) 11,580 21,760 13,533 20,842 27,900
Imports (tons) 164,020 167,235 166,280 230,011 218,607
Imports (million Kshs) 3,823 4,048 4,801 7,299 6,885
Source: Kenya Sugar Board
Table 13: Cotton Production, 2004 – 2008
Year 2004 2005 2006 2007 2008*
Area (ha) 30,000 32,357 36,277 35,929 43,035
Production of Seed Cotton (tons) 18,000 19,414 22,492 24,993 25,155
Price of Seed cotton (Kshs./kg) 19.0 20.0 21.0 20.0 22.0
Yield (tons/ha) 0.60 0.60 0.60 0.69 0.70
Total Value of Seed cotton (million Kshs) 342 388 472 1,250 553
Source: Cotton Secretariat * Provisional
~ 57 ~
Table 14: Pyrethrum Production, 2004 – 2008
Year 2004 2005 2006 2007 2008*
Area (ha) 10,950 3,522 6,325 5,120 3,916
Production of Dry Flower (tons) 2,207 1,003 762.7 906.3 776
Price of Dry Flower (Kshs./kg) 73 73 73 108.75 73.73
Yield (tons/ha) 0.2 0.2 0.2 0.3 0.2
Exports (tons of pyrethrum extract) 133 124 130 142 -
Local Value (Kshs mil) 305.7 158.1 133.1 229.84 -
NB: The dry flowers have 1.4% pyrethrin content. Source: Pyrethrum Board of Kenya (PBK) & Department of Land and Crops Development and Management * Provisional
Table 15: Tobacco Production, 2004 – 2008
Year 2004 2005 2006 2007 2008*
Area (ha) 16,360 10,296 12,179 13,379 12,586
Production (tons of dry leaves) 13,983 15,959 17,605 11,153 10,397
Price of Dry Leaves (Kshs./kg) 65 65 65 65 66
Yield (kgs/ha) 855 1,550 1,400 834 826
Exports (tons) 24,503 15,431 - - -
Total Local Value (Kshs. mil) 909 1,037 1,144 725 835
Source: Department of Land and Crops Development and Management * Provisional
~ 58 ~
Table 16: Coconut Production, 2004 – 2008
Year 2004 2005 2006 2007 2008*
Area under Crop (ha)
43,162 37,293 37,137 37,813 40,761
Production (tons) 69,245 61,824 61,117 61,874 59,897
Yield (tons/ha) 1.6 1.7 1.6 1.6 1.5
Unit Price (Kshs./kg) 11.2 11.2 11.3 12.0 12.5
Total Value (million Kshs.) 775.5 692.4 690.6 742.5 748.7Source: Department of Land and Crops Development and Management
Table 17: Fresh Horticultural Exports; 2003-2008
Year 2004 2005 2006 2007 2008*
Fruits and Nuts
Volume of Exports in tons 20,089.70 18,522 15,405 15,671 17,123
Value (million Kshs) 1,803.00 2,049.90 1,737 1,797 2,071
Vegetables
Volume of Exports in tons 52,805 61,220 61,348 84,313 82,345
Value (million Kshs) 11,820.50 13,574.60 17,823 20,799 16,129
Cut flowers
Volume of Exports in tons 66,805 82,056 86,480 91,192 93,639
Value (million Kshs) 18,092 22,238 23,561 42,374 39,766
Totals
Volume of Exports in tons 139,726 162,196 164,021 191,176 193,107
Value (million Kshs) 31,721 37,998 43,319 64,970 57,966
Source: HCDA.
~ 59 ~
Table 18: Annual Fertilizer Off-take, 2001-2008 (tons)
TYPE OF FERTILIZER 2001/02 2002/03 2003/04 2004/05 2005/06 2006/07 2007/08 2008/2009
PLANTING
DAP 98,285 116,295 105,724 150,569 136,254 164,964 155,212 158,973
MAP 10,476 31,674 1,144 3,420 2,157 2,712 3,932 5,013
TSP - 3,948 4,622 201 599 3,198 9,157 9,299
SSP 470 1,970 3,999 2,010 6,000 4,980 20,221 18,307
NPK20:20:0 2,416 16,952 13,761 2,945 9,036 7,982 9,658 14,283
NPK23:23:0 10,868 21,987 8,567 10,300 18,713 16,175 21,831 20,118
Sub Total 122,516 192,825 137,817 169,445 172,760 200,011 220,012 225,993
TOP-DRESSING
CAN 44,560 59,801 30,700 51,456 59,739 69,714 78,080 84,939
ASN 850 630 - - - 500 543 2,100
UREA 37,557 24,288 45,084 25,017 41,071 28,554 29,982 30,128
SA 5,325 425 4,005 - 1,029 1,340 1,514 2,943
Sub Total 88,292 85,144 70,617 76,473 101,839 100,107 110,119 120,110
TEA
NPK25:5:5:5s 78,531 52,000 64,764 76,375 58,276 69,550 76,556 79,458
NPK25:5:5:3.95s+2.6MgO - - 348 - -
NPK22:21:17 - - 20 - 21 7 3 -
NPK22:6:12+5S 220 12,083 185 - 2,327 768 800 -
Sub Total 78,751 64,083 47,168 76,375 60,624 70,325 77,359 79,458
COFFEE
NPK18:4:12 3,658 7,514 2,150 - - - 1,500 1,685
NPK20:10:10 6,157 2,765 888 - 10,053 3,317 3,616 3,827
NPK17:17:17: 12,227 2,377 5,209 2,948 16,717 15,517 15,601 18,769
NPK16:16:16 - - - - 210 -
Sub Total 22,042 12,656 16,985 2,948 26,980 18,834 20,717 24,281
TOBACCO
NPK12:2:43 - - - - -
NPK8:16:24+MgO+0.1%B - - 252 542 - -
NPK15:15:6+4MgO+0.1%B - - - - -
NPK16:12:24 - - - - -
NPK5:15:25 - - - - -
NPK13:9:21+MgO - - - - -
NPK10:4.7:0.2 - - - - -
Sub Total - - 252 542 - -
~ 60 ~
TYPE OF FERTILIZER 2001/02 2002/03 2003/04 2004/05 2005/06 2006/07 2007/08 2008/2009
SPECIALISED
MgNo3 929 1,595 799 208 420 738 836 1,012
MgSo4 4,160 2,071 3,221 1,026 3,150 3,040 3,070 3,715
CN 2,769 2,913 6,916 3,997 900 597 615 744
MOP/SOP 1,125 1,593 6,121 12,510 10,396 6,411 7,115 8,609
AN 312 219 623 749 2,746 1,006 1,207 1,460
Iron chelate 2,285 5 57 10 2,020 2,427 2,937
Potassium Nitrate 201 813 2,298 644 2,083 2,187 2,646
NPK28:28:0 174 2,736 - - - 605
NPK19:19:19 234 2,314 11 42 118 539 550 666
NPK19:19:19+M.E+1%MgO 1,915 20 - - 4 25 30
Ferrous sulphate 172 563 1,780 - 1,475 1,987 2,100 2,541
Organic fertilizer 816 8,320 9,865 - 1,000 1,250 1,513
Others 2,756 2,367 - 6,808 1,877 1,514 1,650 1,816
Sub Total 17,848 25,528 31,691 25,994 21,082 20,938 23,033 26,176
GRAND-TOTAL 329,449 335,009 312,440 351,776 383,285 410,214 451,239 476,018
Source: Department of Agribusiness, Market Development and Agricultural Information *Provisional
~ 61 ~
Table 19: Average Retail Fertilizer Price, 2002-2007 (Kshs/50kg)
Fertilizer Type 2002/03 2003/04 2004/05 2005/06 2006/07 2007/08 2008/09*
SSP 850 850 1,100 1,100 1,075 1,650 4,500
TSP 1,150 1,500 1,600 1,680 1,680 3,400 4,483
DAP 1,125 1,500 1,680 1,700 1,730 3,800 2,246
MAP 975 1,450 1,680 1,700 1,625 3,800 3,675
ASN 925 1,250 1,300 1,350 1,300 1,850 3,675
CAN 900 1,250 1,350 1,350 1,375 2,000 3,625
SA 750 1,250 1,300 1,300 1,125 1,850 2,350
UREA 900 1,250 1,400 1,450 1,600 3,100 2,550
NPK 20:20:0 1,100 1,350 1,600 1,600 1,630 3,000 4,500
NPK 20:10:10 1,100 1,250 1,350 1,400 1,450 3,000 4,483
NPK 25:5:5 950 1,250 1,400 1,400 1,420 3,150 2,246
NPK 17-17-17 980 1,250 1,400 1,450 1,620 3,150 3,675
KCL 1,100 1,250 1,400 1,400 1,420 2,400 3,675
NPK 23:23:0 1,065 1,400 1,600 1,600 1,630 3,050 3,625
Source: Department of Agribusiness, Market Development and Agricultural Information * Provisional Prices as at end of March, 2009
~ 62 ~
Table 20: Certified Seeds Production and Importation (2004-2008)
Quantities locally produced and imported Crop Description
2004 2005 2006 2007 2008
Local production (KG) 1394248 1650650 1626900 1946260 1086050
Imports (KG) 0 0 0 - 0
Total (KG) 1394248 1650650 1626900 1946260 1086050
Barley
Imports (as % of Total) 0 0 0 - -
Local production (KG) 392647 607958 172960 375247 440123
Imports (KG) 261378 567851 0 1288149 0
Total (KG) 654025 1175809 172960 1663396 440123
Beans
Imports (as % of Total) 40 48 0 77 -
Local production (KG) 0 12090 2820 31250 0
Imports (KG) 0 0 0 0 0
Total (KG) 0 12090 2820 31250 0
Oats
Imports (as % of Total) 0 0 0 0 0
Local production (KG) 500 181 454 0 0
Imports (KG) 352 228 454 345 27
Total (KG) 852 408 907 345 27
Flower
Imports (as % of Total) 41 56 50 100 100
Local production (KG) 69591 55878 0 14565 0
Imports (KG) 25250 6244 0 0 0
Total (KG) 94841 62122 0 14565 0
Herbage
Imports (as % of Total) 27 10 0 0 0
Local production (KG) 24881203 24215835 28978043 28827950 22974031
Imports (KG) 1351032 2345544 3022287 2937700 2504207
Total (KG) 26232235 26561379 32000330 31765650 25478238
Maize
Imports (as % of Total) 5 9 9 9 10
Local production (KG) 54139 45147 32576 58817 0
Imports (KG) 3050 0 0 500 0
Total (KG) 57189 45147 32576 59317 0
Millet
Imports (as % of Total) 5 0 0 1 0
Local production (KG) 536250 473508 0 0 34100
Imports (KG) 443591 444398 0 0 483162
Total (KG) 979841 917906 0 0 517262
Peas
Imports (as % of Total) 45 48 0 0 93
Local production (KG) 0 19240 7300 0 3573
Imports (KG) 0 0 0 0 0
Total (KG) 0 19240 7300 0 3573
Pigeon peas
Imports (as % of Total) 0 0 0 0 0
Finger Millet Local production (KG) 0 0 3242 0 67075
~ 63 ~
Quantities locally produced and imported Crop Description
2004 2005 2006 2007 2008
Imports (KG) 0 0 0 0 0
Total (KG) 0 0 3242 0 67075
Imports (as % of Total) 0 0 0 0 0
Local production (KG) 0 0 102180 0 145336
Imports (KG) 0 0 0 0 0
Total (KG) 0 0 102180 0 145336
Cow peas
Imports (as % of Total) 0 0 0 0 0
Local production (KG) 0 0 24622 37924 133631
Imports (KG) 0 0 0 0 0
Total (KG) 0 0 24622 37924 133631
Green Grams
Imports (as % of Total) 0 0 0 0 0
Local production (KG) 0 0 369 1279 0
Imports (KG) 0 0 0 0 0
Total (KG) 0 0 369 1279 0
Ground Nuts
Imports (as % of Total) 0 0 0 0 0
Local production (KG) 0 0 28791 329 98717
Imports (KG) 0 0 602 6215 10915
Total (KG) 0 0 29393 6544 109632
Pasture
Imports (as % of Total) 0 0 2 95 10
Local production (KG) 0 0 488 1850 0
Imports (KG) 0 0 0 0 139
Total (KG) 0 0 488 1850 139
Soya Beans
Imports (as % of Total) 0 0 0 0 100
Local production (KG) 0 400 4853 34600 0
Imports (KG) 0 0 0 0 0
Total (KG) 0 400 4853 34600 0
Cotton
Imports (as % of Total) 0 0 0 0 0
Local production (KG) 297693 230662 492410 551170 606239
Imports (KG) 0 18000 10000 3000 8000
Total (KG) 297693 248662 502410 554170 614239
Sorghum
Imports (as % of Total) 0 7 2 1 1
Local production (KG) 63669 145246 148718 551170 204850
Imports (KG) 9210 13200 28200 3000 927
Total (KG) 72879 158446 176918 554170 205777
Sunflower
Imports (as % of Total) 13 8 16 1 0
Local production (KG) 13 0 0 0 0
Imports (KG) 13 0 0 0 0
Total (KG) 25 0 0 0 0
Tobacco
Imports (as % of Total) 50 0 0 0 0
Local production (KG) 423516 579627 1685598 71503 129758Vegetables
Imports (KG) 225155 451741 1712285 8105784 1243102
~ 64 ~
Quantities locally produced and imported Crop Description
2004 2005 2006 2007 2008
Total (KG) 648671 1031368 3397883 8177287 1372860
Imports (as % of Total) 35 44 50 57 91
Local production (KG) 1045214 1842592 1369281 1194350 3127710
Imports (KG) 0 0 0 0 0
Total (KG) 1045214 1842592 1369281 1194350 3127710
Wheat
Imports (as % of Total) 0 0 0 0 0
Source: KEPHIS
~ 65 ~
Livestock Data.
Table 21: Livestock Productions
P roduc t io n a nd S a le o f L iv e s to c k a n d D a iry P rodu c ts , 2 003 - 2 007P roduc t io n a nd S a le o f L iv e s to c k a n d D a iry P rodu c ts , 2 003 - 2 007P roduc t io n a nd S a le o f L iv e s to c k a n d D a iry P rodu c ts , 2 003 - 2 007P roduc t io n a nd S a le o f L iv e s to c k a n d D a iry P rodu c ts , 2 003 - 2 007
UN IT 2003 2004 2005 2006 2007*
M n. L itres 203 274 340 361 423
W ho lem ilk and c ream M n. L itres 131 178 191 225 290
B u tte r and ghee .. .. T onnes 215 563 1 ,261 1 ,549 1 ,752
C heese .. .. .. " 361 328 270 243 215
C a ttle and C a lves .. .. .. '000 H ead 1 ,669 1 ,641 1 ,786 1 ,911 1 ,720
S heep and G oa ts .. .. " 4 ,289 3 ,851 4 ,220 4 ,775 5 ,014
P igs .. .. .. " 175 172 180 176 167
* P rov is iona l.
L IVESTOCK S LAUGHTERED
RECORDED M ILK PRODUCT ION
M ILK PROCESSED :
~ 66 ~
Fisheries
Table 22: Fish Exports Value US $
Year 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Product Product
Fish 181,536 176,858 140,922 115,254 146,957 178,684 211,730 200,013 178,326 153,930 137,021 257,419
Table 23: Fish Exports Volume
Year 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Product Product
Fish 18839 17037 17816 18145 20510 23825 42210 22563 28240 33147 36368 14812
Table 24: Fish Export value
Year 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Product Product
Fish 89,771 104,596 75,718 31,603 7,151 64,044 2,666,509 341,800 388,103 406,755
Table 25: Fish Exports Volume
Year 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Product Product
Fish 6162 4285 1529 2199 299 45 57 30 29 53
~ 67 ~
Table 26: Production of Fish by Source
Year 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Product Product Region
Fish Fresh Water 191806 191179 155945 178755 197961 187794 174788 157938 173081 209441 197876 157810 121366 112720 127700 139026 151711 128888
Marine 9,972 7,458 7,194 4,336 4,903 6,054 6,296 6,106 6,332 5,271 4,763 6,466 6,861 6,968 7,037 6,823 6,959 7,467
Table 27 : Value of Fish by Source
Year 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Product Product Region
Fish Fresh Water 8,360 8,715 20,812 20,189 18,784 25,855 36,157 27,466 37,526 35,503 38,810 47,228 58,988 57,388 56,197 50,183 53,197 62,297
Marine 20,774 19,631 27,446 36,152 50,809 57,626 55,305 61,919 50,317 59,844 59,668 71,930 73,654 69,952 82,222 65,110 71,307 81,809
~ 68 ~
Table 28 : Source Fish Productions by Lakes
2003200320032003 2004200420042004 2005200520052005 2006200620062006 2007*2007*2007*2007*
Lake Victoria. .. 105,866 115,747 133,526 143,908 151,934
Lake Turkana . .. 4,047 4,180 2,493 4,559 4,660
Lake Naivasha 39 62 108 189 190
Lake Baringo 0 63 43 68 72
Lake Jipe 73 40 74 109 112
Tana River Dams 474 839 950 1,024 1,118
Fish Farming 1,012 1,035 1,047 1,012 1,120
Other areas . .. 1,176 843 785 842 904
TOTAL . .. 112,687 122,809 139,026 151,711 160,110
5,819 6,192 5,862 6,023 6,123
756 1,206 441 436 476
393 407 520 500 512
GRAND TOTAL . 119,655 130,614 145,849 158,670 167,221
Freshwater fish . 6,468,618 7,182,213 7,207,619 8,070,557 8,197,334
Marine fish . .. 286,116 327,592 305,871 334,624 345,768
Crustaceans . .. 176,347 221,106 99,278 123,105 135,106
Other marine products 24,963 29,895 39,098 38,485 40,957
TOTAL TOTAL TOTAL TOTAL 6,956,044 6,956,044 6,956,044 6,956,044 7,760,806 7,760,806 7,760,806 7,760,806 7,651,8667,651,8667,651,8667,651,866 8,566,7718,566,7718,566,7718,566,771 8,719,1658,719,1658,719,1658,719,165
Other marine products.
Value - KSh' 000
Source: Fisheries Department
* * * * Provisional
Quantities - Tonnes:
Freshwater fish
Marine fish . ..
Crustaceans . .. ..
~ 69 ~
Trade
Table 29: Quantities of Principal Exports and Imports, 2003 - 2007
Quantities of Principal Exports and Imports, 2003 - 2007 Commodity Unit of Quantity 2002 2003 2004 2005 2006 2007*
DOMESTIC EXPORTS Fish and fish preparations .. .. .. .. Tonne 18,252 19,462 17,779 18,352 15,296 10,821Maize(raw) .. .. Tonne 158,753 3,128 24,078 10,854 22,344 27,750Meals and flours of wheat .. .. .. .. Tonne 1,793 345 38 139 622 688Horticulture 1 .. .. Tonne 262,931 294,214 274,186 298,464 301,007 389,247Sugar confectionery .. .. .. .. .. .. .. Tonne 18,815 20,519 23,971 31,114 29,130 30,873
Coffee, unroasted .. .. Tonne 49,479 58,650 50,069 46,962 45,739 55,151Tea .. .. .. .. .. .. .. .. .. Tonne 272,707 262,175 275,307 341,171 318,896 370,245Beer made from malt .. .. .. .. .. 000 Lt. 535 17,269 502 2,943 16,438 44,549
Tobacco and tobacco manufactures .. .. Tonne 15,078 12,368 24,503 15,153 19,634 24,555
Hides and Skins .. .. .. .. .. .. .. .. .. Tonne 7,181 13,910 18,542 15,683 11,875 2,416Sisal .. .. .. .. .. .. .. .. .. Tonne 19,482 21,723 20,895 21,079 22,095 22,031
Stone, sand and gravel Tonne 26,244 30,308 40,878 58,956 97,231 151,172Fluorspar .. .. .. .. .. .. .. .. .. Tonne 98,883 78,507 85,054 102,719 98,126 71,736Soda Ash .. .. .. .. .. .. .. .. .. Tonne 301,622 330,755 318,550 321,429 317,258 437,035Pyrethrum Extract .. .. .. .. .. .. .. .. Tonne 81 123 133 124 122 18
Petroleum Products .. .. .. .. .. .. .. .. Mn. Lt. 338 3 44 204 98 210
~ 70 ~
Quantities of Principal Exports and Imports, 2003 - 2007 Commodity Unit of Quantity 2002 2003 2004 2005 2006 2007*
DOMESTIC EXPORTS Animal and Vegetable oils .. .. .. .. Tonne 43,064 47,534 40,297 44,362 44,152 50,297
Medicinal and pharmaceutical products .. .. Tonne 3,974 3,871 4,910 8,370 7,943 10,244Essential oils .. .. .. .. .. .. .. Tonne 23,624 78,878 36,354 48,077 43,300 53,373Insecticides and fungicides .. .. .. .. Tonne 1,725 1,531 1,922 2,281 3,408 1,549
~ 71 ~
Table 30: Forest Plantation Area, 2003– 2007
Type of ForestType of ForestType of ForestType of Forest 2003200320032003 2004200420042004 2005200520052005 2006200620062006 2007*2007*2007*2007*
Indigenous Trees. .. … 12.3 12.3 12.3 12.3 12.3
Exotic Trees… …. … … … 92.5 98.7 98.7 98.7 98.7
Total …. .. .. .. . .. … .. . 104.8 111 111 111.0 111.0
Fuel Wood and Poles
Exotic Trees… …. … … … 20.3 21.3 21.3 21.3 21.3
TOTAL AREA. .. ..TOTAL AREA. .. ..TOTAL AREA. .. ..TOTAL AREA. .. .. 125.1 132.3 132.3 132.3 132.3
*Provisional
‘000 Hectares
Source: Kenya Forest Service
~ 72 ~
Table 31: Population Data
Population in the Census Years
Year 1948 1962 1969 1979 1989 1999
Indicator
Total Population 5,406 8,636 10,943 15,327 21,445 28,687
Male 5,376 7,607 10,628 14,206
Female 5,567 7,720 10,815 14,481
Rural 14,499 20,120 18,690
Urban 828 1,325 9,997
Table 32: Labor Data
Labor
Year 1999 2005/2006
Indicator
Total Economically active population 12,396 14,564
Males Economically active population 6,375 7,407
Females Economically active population 6,020 7,157
Total Economically active population in agric* - 6,937
Males Economically active population in agric* - 3,134
Females Economically active population in agric* - 3,803
* Excludes the unemployed
- Data not available
~ 73 ~
Table 33: Land Use
Land and Water Area
Year 2007
Indicator
Land Area 581
Water Area 11
Total 592
~ 74 ~
Table 34: Correspondence table of Products
Correspondence table between National and International ClassificatioCorrespondence table between National and International ClassificatioCorrespondence table between National and International ClassificatioCorrespondence table between National and International Classifications for Kenyans for Kenyans for Kenyans for Kenya
Local CategoryLocal CategoryLocal CategoryLocal Category Local product codeLocal product codeLocal product codeLocal product code Local productLocal productLocal productLocal product FAO codeFAO codeFAO codeFAO code FAO productFAO productFAO productFAO product
CerealsCerealsCerealsCereals 1 Maize 56 Maize
10 Wheat 15 Wheat
20 Barley 44 Barley
30 Rice 27 Rice Paddy
40 Sorghum 83 Sorghum
50 Millet 79 Millets
60 Oats 75 Oats
Cereal PrCereal PrCereal PrCereal Productsoductsoductsoducts 11 Wheat Flour 16 Flour of Wheat
2 Maize Flour 58 Flour of Maize
51 Millet Flour 80 Flour of Millet
41 Sorghum Flour 83 Flour of Millet
PulsesPulsesPulsesPulses 50 Beans 176 Beans
60 Cow peas 195 Cow Peas
70 Green Grams 211 Green Grames
80 Dolichos 211 Pulse Nes
90 Pigeon Peas 197 Pigeon Peas
Roots & TubersRoots & TubersRoots & TubersRoots & Tubers 100 Sweet Potatoes 122 Sweet Potatoes
110 Arrow roots 149 Roots & Tubers
120 Cassava 125 Cassava Manioc
130 Yams 137 Yams
140 Irish Pototoes 161 Potatoes
Oil CropsOil CropsOil CropsOil Crops 150 Soya Beans 236 Soya Beans
160 Ground nuts 242 Ground Nuts
170 Sun Flower 267 Sun Flower Seed
180 Simsim 289 Oil Seed Nes
190 Peanuts 242 Oil Seed Nes
NutsNutsNutsNuts 200 Coconuts 249 Coco Nuts
210 Cashewnuts 217 Cashew Nuts
Nut ProductsNut ProductsNut ProductsNut Products 201 Coconuts Milk 234 Nuts Nes
202 Immature coconut-(Madafu) 234 Nuts Nes
~ 75 ~
Industrial CropsIndustrial CropsIndustrial CropsIndustrial Crops 220 Tea 667 Tea
230 Coffee 565 Coffee
240 Sugar Cane 156 Sugar Cane
250 Refined Sugar 164 Sugar, Refined
260 Molasses 165 Molasses
261 Sugar beet 159 Beet Sugar
270 Cotton 339 Oil Seed Nes
280 Pyrethrum 754 Pyrethrum
290 Bixa
300 Tobacco 826 Tobacco
Horticultural Crops Horticultural Crops Horticultural Crops Horticultural Crops
FruitsFruitsFruitsFruits 310 Avocado 572 Avocados
320 Mangoes 571 Mangoes
330 Passion Fruits 603 Fruits, Tropical nes
340 Pineapple 574 Pneapple
350 Apple 515 Apples
360 Banana 486 Bananas
370 Oranges 490 Oranges
380 Lemons 498 Lemons and Limes
390 Pawpaw 603 Fruits, Fresh nes
400 Water Melon 567 WaterMelons
410 Plums 536 Plums
420 Strawberry 544 Strawberries
430 Guava 603 Fruits, Tropical
440 Pears 521 Peers
VegetableVegetableVegetableVegetable 450 Garden Peas 417 Peas, Green
460 Cabbages 358 Cabbages
470 Kales 463 Vegetable, FRESH NES
480 Tomatoes 388 Tomatoes, Fresh
490 Carrots 426 Carrots
500 Spinach 373 Spinach
510 Onion 403 Onions
520 Snow/Snap Peas 463 Vegetable, FRESH NES
530 Irish Pototoes 116 Potatoes
540 Chillies 401 Chillies
550 Asian Vegetables 463 Vegetable, FRESH NES
560 Chick Peas 191 Chick Peas
570 Indigenous Vegetables 463 Vegetable, FRESH NES
~ 76 ~
LivestockLivestockLivestockLivestock 580 Cattle 866 Cattles
590 Sheep 976 Sheeps
600 Goats 1016 Goats
610 Chickens 1057 Chickens Fowl
620 Pigs 1043 Pgis, domestic pigs
630 Camels 1126 Camels
640 Ostrich 1171 Live Animals Nes
650 Donkey 1169 Live Animals, Non-Food Nes
660 Horses 1083 Horses
670 Ducks 1068 Ducks
680 Geese 1072 Geese
690 Turkey 1079 Turkey
700 Rabbits 1140 Rabbits
Livestock ProductsLivestock ProductsLivestock ProductsLivestock Products 710 Beef 867 Meat of Cattle
720 Pork 1035 Meat of Pig
730 Mutton 977 Meat of Sheep
740 Chilken Meat 1058 Chicken Meat
750 Camel Meat 1127 Camel Meat
760 Chevon 1017 Meat of Goat
770 Cow Milk 882 Cow Milk
780 Goats Milk 1020 Goats Milk
790 Camels Milk 1130 Camel Milk
800 Cheese 901 Cheese from whole milk
810 Dried whole powder 897 Dry cow milk
820 Dried Skim-Powder 898 skim milk of cow
830 Butter 885 Butter of cow milk
840 Ghee 887 ghee from cow
850 Hen Eggs 1058 Chicken Eggs
860 Honey 1182 Honey
Local Codes are Secretariate Generated.Local Codes are Secretariate Generated.Local Codes are Secretariate Generated.Local Codes are Secretariate Generated.
~ 77 ~
Table 35: Data Production Frequency
IndicatorIndicatorIndicatorIndicator PerPerPerPeriodicityiodicityiodicityiodicity
Total Land Area under each major crop Annual
Expected harvest by crop type
(i) Quantity
(ii) (ii) Area
(iii) (iii) Value
Annual
Crop production Annual
Fisheries production Annual
Forestry production Annual
Agricultural value added
Agricultural contribution to GDP Annual
Food imports
Major agricultural imports
Major agricultural exports
Agricultural credit disbursed
Agricultural labour force
National agricultural budget
Number of holdings per extension worker Annual
Farm gate prices (i) Crops Monthly / Annual
Price of pesticides Annual
Price of fertilizers Annual
Price of herbicides Annual
Price of labour Annual
Price of arcaricides Annual
Price of implements and equipment Annual
Price of major feeds Annual
Yield for each major crop Annual
~ 78 ~
Total land under irrigation Annual
Agriculture Produce Price Index Annual
Crop Yield Annual
Fish yield Annual
Percentage change in Yield Annual
Price Index (Crops) Annual
Amount of pesticides used Annual
Amount of fertilizers used Annual
Amount of herbicides Annual
Amount of labour After 5 years / Seasonal
Amount of arcacides Annual
Agricultural implements and equipment / machinery by type Annual
Total Fish Landed or harvested by weight,and value Annual
Total Fish Landing Sites Once in Two years
Total Number of Crafts by type Once in Two years
Fishing Gears by type Once in Two years
Fishers Once in Two years
Number of meals per day Annual
Number of meals per day Annual
Household food purchases Annual
Per capita consumption expenditure on Milk Annual
Per capita consumption expenditure on meat Annual
Per capita consumption expenditure on fruits Annual
Per capita expenditure on starches and grains Annual
Per capita consumption expenditure on vegetables Annual
Per capita consumption expenditure on food supplements Annual
Total Livestock grazing area Annual
Livestock production Annual
~ 79 ~
Farm gate prices (i) livestock Monthly / Annual
Yield of Livestock Annual
Amount of livestock feeds Annual
Price Index (livestock)
Amount of Vet drugs / Vaccines Annual
Livestock numbers
Livestock numbers by species
Offtake rate
Hides and skins
Meat production
Per capita meat consumption
Milk production
Livestock exports
Livestock imports
Livestock contribution to GDP
