GCP/GLO/208/BMG - CountrySTAT for Sub-Saharan Africa

FIRST PANORAMA REPORT

UGANDA

E.S.K. Muwanga-Zake (PhD)

Institute of Statistics & Applied Economics, Makerere University

CONSULTANT IN NATIONAL INFORMATION SYSTEM AND AGRICULTURAL

STATISTICS

August 2009

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TABLE OF CONTENTS

1. The National Statistics System ....................................................................................... 1

1.1 Legal Framework and Statistical Advisory Bodies .................................................. 1 1.2 Structure of the National Statistical System (NSS) .................................................. 1 1.3 National Strategy for Development of Statistics ...................................................... 2

2. Reference Situation for the Food and Agriculture Statistics System.............................. 3 2.1. Legal Framework and Food and Agriculture Statistical Advisory Bodies .............. 3 2.2. Structure of the Food and Agriculture Statistics System......................................... 3

2.2.0 Introduction........................................................................................................ 3 2.2.1 The Current Status of Food and Agricultural Statistics ..................................... 4 2.2.2 The Uganda Bureau of Statistics (former Statistics Department, MFPED) ...... 5 2.2.3 The Population and Housing Census (PHC) 2002, Agricultural Module.......... 5 2.2.4 The Livestock Census - 2007 and Census of Agriculture (PCA) 2008/09........ 6 2.2.5 The Permanent Agricultural Statistical System (PASS) 2004, 2005 and 2006/7..................................................................................................................................... 6 2.2.6 Informal Cross Border Trade (ICBT) – Oct 2003 to Jun 2005 and 2006 .......... 6 2.2.7 The Ministry of Agriculture, Animal Industry and Fisheries (MAAIF)............ 6 2.2.8 Department of Agricultural Planning: Statistical Unit....................................... 7 2.2.9 The Animal Resources and Fisheries Directorate.............................................. 7 2.2.10 Department of Fisheries Resources (DFR) ...................................................... 7 2.2.11 Department of Plant Protection........................................................................ 8 2.2.12 Semi-Autonomous Bodies under MAAIF ....................................................... 8 2.2.13 Ministry of Lands, Water and Environment; Department of Meteorology .. 12 2.2.14 Ministry of Local Government Information Co-ordination System (LoGICS).................................................................................................................................... 12 2.2.15 Bank of Uganda ............................................................................................. 12 2.2.16 Ministry of Tourism, Trade and Industry ...................................................... 13 2.2.17 Other Parastatal, Regulatory and Industry-Specific Bodies .......................... 14 2.2.18 Others............................................................................................................. 14

2.3. National Strategy for Food and Agriculture Statistics........................................... 17 2.4. Human Resources Available.................................................................................. 18 2.5. Non-Human Resources Available.......................................................................... 18 2.6. Data Dissemination Policy for Food and Agriculture Statistics. ........................... 18 2.7. Modalities of Promoting User-Producer Dialogue ................................................ 18 2.8. Existing Databases and Data Dissemination Tools and Platforms ........................ 20 2.9. Regional Integration and International Technical Assistance Received................ 20

3. Existing Databases and Data Dissemination Tools ...................................................... 21 3.1. Crops Statistics....................................................................................................... 21

3.1.1 MAAIF/UBOS Annual Publications ............................................................... 21 3.1.2. MAAIF and UBOS Surveys ........................................................................... 22 3.1.3. The Uganda Bureau of Statistics (UBOS), the Bank of Uganda (BOU) and Uganda Revenue Authority (URA) .......................................................................... 24 3.1.4 Agricultural Censuses ...................................................................................... 30 3.1.5 The Directorate of Crop Resources, MAAIF................................................... 32 3.1.6 Semi-Autonomous Bodies under MAAIF ....................................................... 32

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3.1.7. The Community Information System (CIS) ................................................... 35 3.2. Livestock Statistics ................................................................................................ 37 3.3. Fisheries Statistics.................................................................................................. 37 3.4. Forestry Statistics................................................................................................... 38 3.5. Water Resources .................................................................................................... 40 3.6. Land Use ................................................................................................................ 41 3.7. Agricultural Population, Inputs, Infrastructure, Credit, Food Availability, and Prices............................................................................................................................. 42

3.7.1. Agricultural Population................................................................................... 42 3.7.2 Agricultural Inputs (fertilizers, pesticides, machinery, labour and cost of inputs) ....................................................................................................................... 42 3.7.3 (Rural) Infrastructure ( agricultural storage facilities, roads, electrification, mobile phone coverage) ............................................................................................ 43 3.7.4 Credit (access to, amount, source and geographical distribution) ................... 43 3.7.5 Food Availability and Economic (Agriculture Value Added and its dis-aggregation level; income distribution (Gini); rural/urban income)......................... 43 3.7.6 Price Information ............................................................................................. 44

3.8. Description of national/ sub-national commodities codes system (if existing) ..... 47 3.9. National classification/ nomenclatures and links to international classifications (if existing)......................................................................................................................... 50 3.10. Consumption, Trade and other relevant Indicators for the Agriculture sector .... 50 3.11. Limitations of the available Food and Agriculture Statistics............................... 50 3.12. Summary of Chapter 3 ......................................................................................... 51

4. Overview of User Needs for Food and Agriculture Statistics Uganda......................... 53 4.1. The Demand for Agricultural Statistics ................................................................. 53 4.2. Public Sector Decision Makers.............................................................................. 54 4.3. Private Sector Decision Makers............................................................................. 55

5.0. Expectations from Country STAT and synergies with ongoing Initiatives in Uganda............................................................................................................................................ 57 6. Important Factors for the success of Country STAT project- Uganda. ...................... 58 7. Expectations from the Consultative Meeting- Uganda................................................. 59 TABLES

Table 3.8.1: Crop Groups, Names, Ugandan and FAO Codes 47 Table 3.8.2: Codes Developed for Crop Condition and State 48 Table 3.8.3: Quantity Codes 49

ANNEXES

ANNEX 3.1: INVENTORY OF AGRICULTURAL STATISTICS PRODUCED 60 ANNEX 3.2. METADATA DICTIONARY- CROP PROTECTION 73

ANNEX 3.3. METADATA DICTIONARY- ANIMAL PRODUCTION AND MARKETING 75

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LIST OF ACYRONYMS

AIS Agricultural Information System BOP Balance of Payments BoU Bank of Uganda CDO Cotton Development Organisation; DDA Diary Development Authority EA Enumeration Areas, EU European Union EPRC Economic Policy Research Centre FAO United Nations, Food and agriculture Organisation FEWSNET Famine Early Warning Systems Network ICBT Informal Cross Border Trade, IITA International Institute of Tropical Agriculture LoGICS Ministry of Local Government Information Co-ordination System M&E Monitoring & Evaluation MAAIF Ministry of Agriculture, Animal Industry and Fisheries MDA Government Ministries, Departments and Agencies MFPED Ministry of Finance, Planning and Economic Development MoES Ministry of Education & Sports MoH, Ministry of Health MoLG, Ministry of Local Government MTEF Medium-Term Expenditure Framework, MTTI Ministry of Tourism, Trade & Industry NAADS; National Agricultural Advisory Service NAGRIC & DB National Animal Genetic Resource Centre Data Bank NARO/S National Agricultural Research Organisation/System; NASCC National Agricultural Statistics Consultative Committee NASTC National Agricultural Statistics Technical Committee NCAL National Census of Agriculture and Livestock NIMES National Integrated Monitoring and Evaluation Strategy NSO National Statistical Office NSS National Statistics System PASS Permanent Agricultural Statistics System, PCA Pilot Census of Agriculture PEAP Poverty Eradication Action Plan PHC Population and Housing Census PMA Programme for Modernisation of Agriculture PNSD Plan for National Statistical Development SSPS Sector Strategic Plans for Statistics UBOS Uganda Bureau of Statistics UCDA Uganda Coffee Development Authority UCDA Uganda Coffee Development Authority UGCEA Uganda Ginners and Cotton Exporters’ Association UNDP United Nations Development Programme UNHS Uganda National Household Survey UNICEF United Nations Children Fund

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UPF Uganda Poverty Fund URA Uganda Revenue Authority USAID United States Agency for International Development UTCC Uganda Trypanosomiasis Control Council WFP World Food Programme

1. The National Statistics System In Uganda, the National Statistics System (NSS) is highly decentralized and has many players with the Uganda Bureau of Statistics (UBOS) as the central coordinating agency. These include Government Ministries, Departments and Agencies (MDAs) both public and private. Some of these MDAs have entered into formal arrangements, i.e. Memoranda of Understanding, for the collection and sometimes publication of specific statistics. Institutionally, the NSS brings together all key stakeholders and institutions in the field of producing, supplying and using statistics. UBOS is the agency responsible for coordinating, monitoring and supervising the NSS in Uganda, and ensuring that international and national standards are adhered to. Presently, the linkages within the NSS are inconsistent, informal and relatively weak. There is no comprehensive common understanding of the actual implications of the activities of one sector with respect to others. Nevertheless, there is consensus that coordination and collaboration among data producers and users is needed to (i) prevent duplication of effort and generation of inconsistent data, (ii) achieve cost-effectiveness in utilization of scarce resources, (iii) avoid working at cross-purposes, and (iv) produce higher quality data. 1.1 Legal Framework and Statistical Advisory Bodies

UBOS was established by an Act of Parliament – The UBOS Act of June 1998 - to succeed the then Statistics Department of the Ministry for Planning. In addition to coordinating the NSS, UBOS is charged with the collection, analysis and publication of integrated, relevant, reliable and timely statistical information. The UBOS Act is currently under review to make it into a NSS Act. It is no longer tenable for a country with a decentralized National Statistical System (NSS) to have a Statistics Act for the National Statistical Office (NSO) rather than for the NSS. Within the framework of the Plan for National Statistical Development (PNSD), discussed below, there will be revision of the statistical legislation and institutional re-engineering to improve coordination and synergy within the national statistical system. Among the strategies under institutional re-organization will be the re-establishment of the common statistical cadre; strengthening coordination arrangements between data producers and users, among data producers and between data producers and the donor community; and establishment of an all inclusive National Statistical Data Bank which will be a one stop centre and authoritative source of official statistics in Uganda. 1.2 Structure of the National Statistical System (NSS)

The NSS includes all agencies in Uganda, whether Government or not; under any enactment or otherwise; responsible for gathering statistical data through either surveys or administrative action (Statistical Act, 1998).

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1.3 National Strategy for Development of Statistics In order to strengthen the NSS, the Plan for National Statistical Development (PNSD) - Uganda’s version of the NSDS was developed. PNSD is a framework for strengthening statistical capacity across the entire NSS for results based management. The paradigm shift, which emphasizes management for results, focuses on performance and the achievement of outputs, outcomes and impact. PNSD is meant to address issues of structure, sustainability and modification of relationships between key actors in NSS, harmonization and implementation of planned activities financed by Government and Development Partners. The PNSD is a medium term plan covering five years (2006/7- 2010/11). UBOS is now working with sectors to address weaknesses in the NSS by developing a Plan for National Statistical Development (PNSD). The PNSD will pull together Sector Strategic Plans for Statistics (SSPS) for key sectors in the Government of Uganda, and allow for development of the other sectors over the lifetime of the first PNSD. The PNSD will put together the various key sectors and the main outputs will be:

1. A report on the current status of Uganda’s Statistical System, 2. Sector Strategic Plans for Statistics (SSPS) 3. A National Statistics Development Strategy report and; 4. A detailed three year plan related to the Medium-Term Expenditure Framework

(MTEF) with clear mechanisms for its implementation. The PNSD underpins the notion of identity, and fostering of collaboration and co-operation among sectors engaged in data production and utilization. The PNSD implementation start up activities involved statistical advocacy, improving physical, information technology and statistical infrastructure, statistics inventories as well as improving skills across the participating sectors. This will be subsequently followed by, data development - standards, data audit, and matching production to the policy making cycle. At the PNSD - Annual review for Phase I Ministries, Departments and Agencies (MDAs), (between 3-5 December, 2008) sectors assessed their performance levels to date in regard to level of statistical development. The outcome was:

Level One: Advanced Stage: UBOS, BoU, MoH, MoES Level Two: Intermediate Stage: MTTI, MAAIF, MoLG, UPF Level Three: Initial Stage: Nil

Where sectors in the Advanced Stage have the necessary structures, clear funding mechanisms for statistics, and their data is demanded and used as compared to the intermediate whose structures are not well developed, and the data production is not harmonized across the departments, including inadequately managed information.

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2. Reference Situation for the Food and Agriculture Statistics System 2.1. Legal Framework and Food and Agriculture Statistical Advisory Bodies

Food and Agricultural Statistics is collected under the UBOS Act with UBOS mandating the various institutions discussed below to collect the various data. In some cases these mandates have been formalised by Memoranda of Understanding. Secondly, there is a National Agricultural Statistics Technical Committee (NASTC) comprising of the main stakeholders in Agricultural Statistics which provides a forum for discussion on concepts, methods and other technical issues on Agricultural Statistics. There is also supposed to be a policy level, National Agricultural Statistics Coordination Committee (NASCC). These are discussed further in Section 2.7. Secondly, as with other surveys and censuses, specific technical and policy committees are set up whenever a national survey or census is being organised by either UBOS or MAAIF or any other major statistics agencies. 2.2. Structure of the Food and Agriculture Statistics System

2.2.0 Introduction The agricultural statistics system in Uganda is also decentralized. There are several agencies involved in collecting various aspects of Food and Agricultural Statistics (FAS). The main ones are:

i) Uganda Bureau of Statistics (formerly Statistics Department, MFPED) ii) Ministry of Agriculture, Animal Industry and Fisheries (MAAIF) iii) There are seven semi autonomous bodies that receive policy guidance from

MAAIF and collect some data, mainly for their own operations, including: National Agricultural Research Organisation/System (NARO/S); Cotton Development Organisation (CDO); Uganda Coffee Development Authority (UCDA); Diary Development Authority (DDA); National Animal Genetic Resource Centre Data Bank (NAGRIC & DB); National Agricultural Advisory Service (NAADS); and Uganda Trypanosomiasis Control Council (UTCC)

iv) Agricultural Policy Secretariat (formerly Agricultural Secretariat in the Bank of Uganda) – Now closed but a new Domestic Resource Cost Division has now been opened in BOU

v) Ministry of Tourism, Trade and Industry: The Marketing, Cooperative and Planning Departments

vi) Ministry of Local Government. vii) Bank of Uganda: The Research Department and Trade & External Debt

Department

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viii) Other Parastatal, industry based and Regulatory Bodies: - Uganda Export Promotion Board - Uganda Tea Growers Association

- Sugar Plantation Association; - Uganda Flowers Exporters Association - Uganda Vanilla Association - International Institute of Tropical Agriculture (IITA)- FOODNET, FEWSNET

ix) Other agriculture-related bodies - International and Bilateral Organisations like UNICEF, USAID, FAO, EU

- Uganda Cooperative Alliance and private consultancies - PMA Secretariat The respective data collection activities are outlined below. 2.2.1 The Current Status of Food and Agricultural Statistics

With support from Food and Agriculture Organization (FAO) and the World Bank, a data needs assessment and a review of the status of agricultural statistics was carried out in Uganda in 1999 and early 2000. The review covered the whole system and developed an Integrated Framework for Agricultural Statistics in Uganda in March 2000. The key conclusions were as follows.

(i) The history of the development of agricultural statistics in Uganda is not very different from other developing countries in the region. It has been marked by a number of initiatives at different times to build capacity and to establish regular data collection and compilation programs, but, for a variety of reasons, it has not been possible to sustain them when direct support provided by different donors has come to an end.

(ii) Although there are many different producers of agricultural related data in the country, these data collection efforts are not coordinated and the agricultural statistics system as a whole is “fragile, vulnerable and unsustainable”.

(iii) The quality of the data that are available is questioned by users and is largely not used.

(iv) There are many data gaps. (v) The system as then constituted was unable to meet the demands for food and

agricultural statistics. Since the Framework for the Development of Agricultural Statistics in Uganda was prepared, some new activities have been completed as indicated below.

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2.2.2 The Uganda Bureau of Statistics (former Statistics Department, MFPED) This is the lead and coordinating agency for all data collection activities in the country and is therefore involved in FAS data collection. It provides national and regional annual food and agricultural data. UBOS has taken the following measures to improve the FAS:

i) Made a crop survey a core module of the UNHS in 1995/6, 1999/2000 and 2005/06

ii) Created an Agricultural Statistics Section (ASS) within the Directorate of Business and Industry Statistics (BIS); it is hoped that ASS will eventually become a full Directorate,

iii) Carried out a FAS Data Needs Assessment Study in August 1999. iv) Hold a FAS Stakeholders’ Workshop in October 1999. v) Designed a Framework for the Development of Agricultural Statistics in

2000, vi) Piggy-backed an Agricultural Module onto the Uganda 2002 Population

Housing Census, vii) Conducted a pilot Census of Agriculture in 2003 viii) Spearheaded the Permanent Agricultural Statistics System (PASS), 2004,

and the PASS Surveys in 2005 and 2006/07 ix) Participated in the Livestock Census in 2008, and x) Spearheaded the Uganda Census of Agriculture in 2008/2009

In the 1994/95 round, a Diagnostic Agricultural Crop Survey was carried out under the Second Monitoring Survey (SMS) to establish the operational feasibility of obtaining reasonably reliable estimates of production of major food crops at national level through the Inquiry Method. This was expected to be more cost-effective and less cumbersome than the objective method used in censuses of agriculture and post-census agricultural surveys implemented by MAAIF. The Crop Survey Module collected data on household characteristics; holding characteristics; planted area; and crop output, sales and prices. Thereafter, Crop Surveys have been included as core modules in the household surveys. 2.2.3 The Population and Housing Census (PHC) 2002, Agricultural Module The Population and Housing Census (PHC) 2002 was conducted between the 13th and 20th September 2002. It included an Agricultural Module (AM) whose main purpose was to provide appropriate sampling frames for a detailed Census of Agriculture and Livestock and other subsequent agricultural surveys. Since the AM was administered on a universal basis and therefore covered all households engaged in agricultural activities in Uganda, it is a unique source of data that should be subjected to further analyses to obtain more value.

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2.2.4 The Livestock Census - 2007 and Census of Agriculture (PCA) 2008/09 The Pilot Census of Agriculture (PCA) 2003 was conducted in 10 districts during the first agricultural season 2003. Districts were stratified on an ad hoc basis according to expert judgment of agricultural farm structures and production types in Uganda. Within each district sub-counties were stratified according to agricultural zones. Three (3) Parishes each with two (2) Enumeration Areas (EA) were randomly selected. All households in the selected EA were listed. Based on the listing, 15 holdings in each EA were randomly selected for detailed interviews as well as for area and yield measurements with repeated visits. Due to funding and other issues a Livestock Census was carried out in 2007 and was followed with a Census of Agriculture in 2008/09. These two were jointly carried out by MAAIF and UBOS. 2.2.5 The Permanent Agricultural Statistical System (PASS) 2004, 2005 and 2006/7 With Norwegian funding, UBOS in cooperation with MAAIF, conducted a pilot Permanent Agricultural Statistics System (PASS) in five districts during both the first and second agricultural seasons of 2004. In 2005, PASS was extended to 10 districts. Under PASS, data was captured using scanning technology. A report for the pilot PASS was prepared and disseminated. PASS 2006/7 was carried out in another eight districts. For PASS 2005 and 2006/7, scanning and data cleaning activities were undertaken , but reports have not yet been produced. After that the implementation of PASS will depend on funding being availed by the Local and Central Governments and other stakeholders. However, the Norwegian funding came to an end after the PASS 2006/7 data collection was completed. 2.2.6 Informal Cross Border Trade (ICBT) – Oct 2003 to Jun 2005 and 2006 The Uganda Bureau of Statistics (UBOS), the Bank of Uganda (BOU) and Uganda Revenue Authority (URA) carries out the ICBT Survey since October 2003, which was a baseline, followed by surveys from 2004 to date. The ICBT collects data on informal cross border trade necessary for estimating the magnitude of unrecorded trade, revenue loss due to informal trade activities to augment the current account of the Balance of Payments (BOP). 2.2.7 The Ministry of Agriculture, Animal Industry and Fisheries (MAAIF) Production of agricultural data started in Uganda way back during colonial times when the ministry responsible for agriculture established an Agricultural Reporting Service through which data was administratively reported. Between 1963 and 1965, the first

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Census of Agriculture was conducted. Reports are available and it is not intended to cover these in detail during this consultancy. A National Census of Agriculture and Livestock (NCAL) was conducted during 1990/91 with funding from UNDP and technical support from FAO. There were two follow-up annual sample surveys in 1991/92 and 1992/93 agricultural years. Currently, the Ministry functions through two directorates namely: The Directorate of Crop Resources and that of Animal Resources. In addition, there is the Department of Fisheries Resources; an Agricultural Planning Department and a number of allied autonomous bodies. 2.2.8 Department of Agricultural Planning: Statistical Unit

The main source of data is the Statistical Unit within the Department of Agricultural Planning, which is directly under the Monitoring and Evaluation Section. Its main functions include the following;

o Provision of relevant agricultural sector information o Design and implementation of agricultural surveys o Maintenance of a comprehensive database for the Agricultural sector o Monitoring and Evaluation of projects and programmes in the Agricultural sector

The Statistics Unit also works with UBOS to up-date annual data and collaborating on the implementation of PASS as described above.

2.2.9 The Animal Resources and Fisheries Directorate The current data in the Department of Animal Production and Marketing, and the Department of Livestock Health and Entomology, under the Animal Resources and Fisheries Directorate, is based on projections that try to take into consideration, migrations, disease outbreak and droughts as they have occurred over the last twelve months. Information is also sought from the Farming in Tsetse Fly Control Areas (FITCA) project in which periodic surveys are carried out. Information is availed on number of species of animals affected; number of movement permits issued and quarantine measures undertaken.

2.2.10 Department of Fisheries Resources (DFR)

Data collection on fisheries dates back to 1927-33, when a survey of Lake Victoria and other Lakes like Tanganyika in East Africa was carried out. This followed a recommendation to start a data collection system for our lakes in 1933 including Lake Victoria. A number of Institutions were put in place including East Africa Fisheries

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Organisation (EAFRO) later, UFFRO continued at various stages to find the best approaches to collect good data for management of the lakes using local fish inspectors- the Fish Guards. Later, Fisheries Assistants were trained to improve this service.

Subsequently, the data collected, in case of Uganda, was submitted by districts. Secondly, data analysis was done at Fisheries Headquarters in Entebbe. Finally, supervision of extension officers was the duty of District Fisheries Officers (DFOs) and overseen by MAAIF Headquarters.

2.2.11 Department of Plant Protection Crop protection zones have been identified and 34 new inspectors have been deployed and are charged with collecting data in this respect. The Department occasionally collects data especially on the disease and pest outbreaks and some records do exist in the area of phyto-sanitary issues. 2.2.12 Semi-Autonomous Bodies under MAAIF

There are seven semi autonomous bodies that are operationally autonomous but receive policy guidance from MAAIF and each of these collects some data, mainly for its own operations.

i) National Agricultural Research System and Organisation (NARS/NARO) ii) Cotton Development Organization (CDO) iii) National Agricultural Advisory Services (NAADS) iv) Uganda Coffee Development Authority (UCDA) v) Diary Development Authority (DDA), vi) National Animal Genetic Resource Centre Data Bank (NAGRIC & DB) vii) Uganda Trypanosomiasis Control Council (UTCC)

There is also a Programme for Modernising Agriculture (PMA) Secretariat. PMA is the Ugandan government’s economic policy for the Poverty Eradication Action Plan (PEAP) framework for modernizing agriculture. Within the PMA framework, the major focus is to transform subsistence agriculture to commercial agriculture. More and better commercial agriculture means that rural poverty can start to be eradicated. The PMA Secretariat does not, however, directly collect any data. PMA data needs will be discussed later. (i) The National Agricultural Research System and Organisation (NARS/NARO) The National Agricultural Research Act, 2005 provides for the development of an agricultural research system for Uganda, hereby referred to as the National Agricultural Research System (NARS), for the purpose of improving agricultural research services delivery, financing and management. The NARS means a cross section of stakeholders whether in public or private sector; and comprises of the organisation, public agricultural

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research institutes, universities and other tertiary institutions, farmer groups, civil society organisation, private sector and any other entity engaged in the provision of agricultural research services. The NARS institutional framework encompass Public as well as Private sector institutions in implementing agricultural research, and promoting vertical and horizontal linkages with other national, regional and international institutions. The objectives of agricultural research in Uganda are to:

a) Transform agricultural production into a modern science-based market

oriented agriculture capable of greater efficiency, profitability and of sustaining growth in the agricultural sector while contributing to poverty eradication;

b) Promote agriculture and related industry for the purposes of contributing to the improvement of the quality of life and livelihoods of the people, having regard to the protection of the environment; and

c) Support the development and implementation of national policy with relevant information and knowledge.

The overall goal of the NARS is to address challenges presented in the Plan for Modernisation of Agriculture (PMA) strategy and National Agricultural Research Policy (NARP) principles to provide research services that address in a sustainable manner, the needs and opportunities of the majority poor. There is a National Agricultural Research Organisation (NARO) which is the apex body for guidance and coordination of all agricultural research activities in the national agricultural research system in Uganda. NARO is a Public Institution established by an act of Parliament, which was enacted on 21st November 2005. NARO is a body corporate with perpetual succession and a common seal. The National Agricultural Research Organisation has a secretariat headed by the Director General, the chief executive responsible for the day-to-day operations and administration of the secretariat. The Public Agricultural Research Institutes are semi-autonomous research management Entities under the policy guidance of the National Agricultural Research Organisation for the purpose of providing agricultural research services. Public agricultural research institute are autonomous in their operations relating to the implementation of its programmes, allocation and management of its resources in accordance with its approved annual programmes and budget as approved by the council. The public agricultural research institutes are of two categories:

a) National Agricultural Research Institutes, which manage and carry out

agricultural research of a strategic nature and of national importance; and

b) Zonal Agricultural Research and Development Institutes, which manage and carry out Agricultural research whether applied or adaptive for a specific agro-ecological zone.

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(ii) Cotton Development Organization (CDO) The CDO was established in 1994 by an Act of Parliament, it has the responsibility to monitor the production, processing, and marketing of cotton so as to enhance the quality of lint exported and locally sold, to promote the distribution of high quality cotton seed and generally to facilitate the development of the cotton industry. The Cotton Development Organisation mobilizes and encourages farmers to form farmer groups for easier delivery of services and access to credit and collective bargaining at marketing time.

CDO has assisted in the formation and evolvement of a Private Sector body; the Uganda Ginners and Cotton Exporters’ Association (UGCEA). The ginners support cotton production and productivity. The ginners’ strategy focuses mainly on the registration of cotton farmers (farmers Group Formation) in their areas, thus creating a reliable data bank to ensure that planting seed is only supplied to genuine cotton farmers to curb seed wastage.

(iii) National Agricultural Advisory Services (NAADS) Programme

The Programme for Modernisation of Agriculture (PMA), whose overall objective is to enhance production, competitiveness and incomes, has an ambitious agenda of policy and institutional reform across seven pillars, the key one being improving delivery of agricultural extension through the new National Agricultural Advisory Services (NAADS) program (MFPED 2004). NAADS became operational in 2001 and is an innovative public-private extension service delivery approach.

NAADS was initiated in 2001/02 in six trailblazing districts, expanded into ten additional districts in 2002/03 and thirteen additional districts in 2003/04 and 2004/05. By 2005, NAADS was operating in nearly 30% of the sub-counties in Uganda. In July 2006, it was reported to be operating in 63 districts, and is expected to cover the entire country within the next three years.

NAADS promotes development of farmer organizations and empowers them to procure advisory services, manage linkage with marketing partners and conduct demand-driven monitoring and evaluation (M&E) of the advisory services and their impacts. Under the NAADS approach, Participatory Monitoring and Evaluation (PME) involve the active involvement of farmers in the generation and analysis of data about programme activities, outputs and impact.

Farmer involvement is maintained through the various levels:

� Farmer Groups (FGs) � Parish Co-ordination Committees (PCCs) � Sub-County Farmer Forum (SCFF)

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The PME mechanism creates an effective forward and backward channel of information sharing about the quality of advisory services, all aimed at improving the quality of services and group development processes.

(iv) Uganda Coffee Development Authority (UCDA)

The Uganda Coffee Development Authority (UCDA) was established by statutory mandate in 1991 following the liberalization of the coffee industry. The statute mandates UCDA to promote and oversee the development of the coffee industry through research, quality assurance and improved marketing. This statute was later amended in 1994 and the Coffee Regulations 1994 aimed at streamlining the industry came into force.

(v) Diary Development Authority (DDA)

Until 1994, The Dairy Corporation, a public company that monopolised the formal market for pasteurised milk and other dairy products, dominated the dairy industry. Since then, the dairy sector has undergone considerable transformation leading to substantial growth and increased private sector participation. Accordingly, the role of Government in this sector has changed from direct participation in milk production, processing and marketing to creating an enabling environment in which farmers and private investors could grow and develop the dairy industry. Recently, co-operative societies have developed and many of them are involved in milk collection and marketing. Some have gone into milk processing. The Uganda Dairy Industry Stakeholders’ Association (UDISA), an organisation of all stakeholders in the dairy industry was recently formed.

Dairy Development Authority (DDA) is a statutory body which falls under Ministry of Agriculture, Animal Industry and Fisheries (MAAIF). It was established by the Dairy Industry Act, 1998 and was mandated to take up the regulatory and developmental functions of the Dairy Sector. Its operations in the Dairy Industry began on 1st June 2000.

The Mission of DDA is to provide development and regulatory services that will ensure increased production and consumption of milk, sustainable and profitable dairy industry sector that will contribute to economic development and improved nutritional standards in Uganda. DDA’s overall objective is to provide proper coordination and efficient implementation of all policies designed to achieve and maintain self sufficiency in the production of milk in Uganda by promoting production and competition in the dairy industry and monitoring the market for milk and dairy products.

DDA also came up with a Diary Master Plan Study in Milk Shed Area that involved collecting information on milk production, collection and marketing.

(vi) National Animal Genetic Resource Centre Data Bank (NAGRIC & DB)

Founded in 2004 and has not set up data collection mechanisms.

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(vii) Uganda Trypanosomiasis Control Council (UTCC)

This agency keeps data on the affected areas.

2.2.13 Ministry of Lands, Water and Environment; Department of Meteorology

The Department is mandated to monitor weather and climate and advise planners and decision makers.

• Has data on rainfall, wind (speed/direction) sunshine hours and evaporation rates BUT with different levels of complexness;

• Generated through observations/recording;

• Need to increase reliability of data through increasing scope and coverage, and installation of automatic weather stations (from 20 to 100);

• Produces a monthly bulletin for MAAIF which depicts average amounts of rainfall Vis-à-vis 30-year means and compared with previous month;

• Supplies daily forecasts to MAAIF.

There is a linkage between the Meteorology Department and Early Warning and Agricultural Statistics Unit in MAAIF. MAAIF uses data from Meteorology to advise farmers on what to plant basing on the critical minimums for each of the production processes right from planting to harvesting. The data so far generated is relatively reliable but there is need to provide more user specific information. 2.2.14 Ministry of Local Government Information Co-ordination System (LoGICS).

Objectives of LoGICS are to:

• improve efficiency and effectiveness of managing service delivery by LGs;

• ensure LGs adherence to set standards and regulations, such as accountability of funds, compliance with tender regulations and financial regulations;

• ensure that all departmental information/data needs are met to support the mandated management functions of the MoLG, LGs and other key stakeholders;

• build a one-stop resource center at the MoLG headquarters where all stakeholders & users of information can access data on decentralization and its implementation in Uganda.

2.2.15 Bank of Uganda

As far as FAS is concerned, Bank of Uganda is participating in the Informal Cross-Border Trade (ICBT) Survey under the Trade and External Debt Department (TEDD) as discussed above. Secondly, the Bank, through the Research Function, has set up a system to collect regular data on Domestic Resource Costs (DRC) and construct a proxy Index of Agricultural Production (IAP). Thirdly, the its Research Department carries out a Bank

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Lending Survey twice a year (end June and end December). The main objectives of the survey are to:

i.) Capture developments in bank lending in Uganda and to establish the lending conditions and standards in the banking sector during the reference period; ii.) Enhance the BOU’s knowledge of loan financing conditions in Uganda among deposit-taking institutions; And hence, iii.) Assess monetary and economic developments as an input into monetary policy decisions.

Questionnaires are sent out to all the commercial banks. 2.2.16 Ministry of Tourism, Trade and Industry The key functions of the Ministry include; collecting, processing, analyzing and disseminating national and international information on the respective sectors hence providing vital input necessary to improve rational decision making. The trade sub-sector is composed of the internal and external trade sectors. The trade sector is charged with the responsibility of developing, facilitating and promoting internal and external trade. The functions of this department includes among others:

i.) Generating and disseminating critical market information to the country’s business community.

ii.) Sensitizing the business community on the availability of trade opportunities, export procedures and market requirements.

The trade department is supplemented by the Uganda Export Promotion Board (UEPB), a statutory body whose specific mandate is export development, promotion and coordination of export activities. The UEPB was created by an Act of Parliament in 1996 and is based in Kampala. It has four divisions namely; Market and Product Development; Promotion and Publicity; Management Information systems; and Finance and Administration. The medium to long-term objectives of the trade department include; providing market information in order to improve production, trade and marketing services in the country. UEPB provides the following information in international markets to assist exporters

� Commodity Price Information � Quality Standards � Market Opportunities � Export Documentation � Export Incentives

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The Board handles export permit requests, value added tax applications, and other paperwork. It provides detailed information to Ugandan companies about current trade agreements, tariffs, trade policies, and other relevant areas of the international trade environment. The Board provides a voice for exporters in Uganda's government and financial administration.

2.2.17 Other Parastatal, Regulatory and Industry-Specific Bodies

� Uganda Tea Growers Association; � Sugar Plantation Association; � Uganda Flowers Exporters Association (UFEA) � Uganda Vanilla Association; � Cocoa Project; � Uganda Commodity Exchange � Eastern Africa Grain Exchange � Other agriculture-related bodies.

2.2.18 Others These include:

� International and Bilateral Organisations like UNICEF, USAID, FAO, EU � Uganda Cooperative Alliance � Makerere University various Faculties and Departments related to agriculture

and/or statistics.

FEWSNET

The Famine Early Warning Systems Network (FEWSNET) a USAID-Washington funded activity carries out regular monitoring and reporting and provides executive decision-makers with an overview of the food security situation in Africa, Central America, Caribbean and Afghanistan. It provides accurate, timely and actionable information to prevent hunger-related deaths, mitigate food insecurity and strengthen livelihoods. It also develops information networks and builds local capacity for information generation and dissemination. It is understood that the current funding for the programme in Uganda is up to 2010. The main objectives of this component is to build a multi-disciplinary, well coordinated, user-driven, credible and visible system that would provide early warning data and information on:

• crop and agro-meteorological conditions;

• crop production forecasts;

• agricultural prices;

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• stocks and procurements;

• food imports/exports;

• food security situation and nutrition. Institutional framework for the FEWSNET would include a number of collaborating institutions, agricultural statistical committees and the Early Warning Secretariat.

a) Collaborating Institutions The following institutions were expected to play an active role in the development and implementation of the system:

• The Ministry responsible for Agriculture, Animal Resources and Fisheries,

• Department of Meteorology

• Uganda Bureau of Statistics

• District Administrations

• Ministry of Health

• Ministry of Finance, Planning and Economic Development

• NGO’s

• Donors and international organizations (WFP, FAO, UNICEF, USAID, etc).

b) Secretariat for the Early Warning System was to be the Early Warning Unit The Stakeholders Workshop in October, 1999 had recommended that the Early Warning Unit and Statistics Section of MAAIF should be combined, strengthened, and up-graded within the Planning Department of the MAAIF. The Early Warning and Statistics Section (EW &SS) would play a nodal coordinating role for the EWS and also function as the Secretariat for the EWS. This Section would, in particular, be responsible for:

• coordinating early warning activities in collaborating institutions,

• schedule and act as secretariat to the EWC and EWTC,

• collect and collate data and information from collaborating institutions and other sources e.g., from the Central Bank, international organizations, NGO’s, private traders, etc., and

• Produce on a regular basis and distribute widely a Food Security Bulletin, Agro-meteorological Update and ad hoc reports as necessary.

In addition to strengthening the Early Warning and Statistics Section, there was need to support early warning activities in collaborating institutions. In particular, the Agro-meteorological Unit, the Department of Meteorology and the Uganda Bureau of Statistics needed special support. Subsequently, UBOS organised a number of consultancies under SSASP funding.

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The FOODNET Strategy, International Institute of Tropical Agriculture (IITA) FOODNET is a regional ASARECA Research for Development Network focusing on Market analysis and enterprise development. FOODNET works with a range of partners in Eastern and Central Africa, from both the public and private sector with the aim of strengthening market led research and implementing commercially focused projects. The FOODNET goal is to contribute to sustainable agricultural development by enhancing trade and providing access to new value-added market opportunities. FOODNET is developing methods, information and interventions that lead towards greater market efficiency and valued added processing in the agricultural sector. The network’s activities are implemented through a portfolio of regional projects that are funded through competitive and commissioned grants. FOODNET is implemented by the International Institute of Tropical Agriculture (IITA). The Outputs are:

1. Strengthening Regional Trade Intelligence and Market Information Services; 2. Market research and agro-enterprise development; 3. Capacity building and scaling up processes; 4. Technical support services for agro-enterprise development.

The FOODNET team collects, analyses and delivers information to its clients through:

• Data collection: market agents record daily and wholesale and retail price data from four markets in Kampala (Kisenyi, Owino, Kalererwe and Nakawa) and also collect weekly prices of 28 commodities from 19 district markets across the country;

• Market intelligence: FOODNET analysts, provide information on supply and demand conditions in key sub-sectors and specific information regarding volumes traded and quality requirements;

• Market analysis: Information from the field is carefully reviewed to ensure data accuracy and thereafter analysed to provide clients with price trends, information on crop conditions and insight into the reasons for price movements. In addition to providing data, this information is also developed into a script for radio transmission;

• Information dissemination: Analysed data is relayed to farmers on a weekly basis via FM Radio in eight local languages. The data is also sent to policy makers, traders and development agencies through, E-Mail, internet, SMS, WORLDSPACE, newspapers and workshops. Dissemination through SMS is instant and very helpful for those with no electronic mail list. One needs to download the message menu, write the item required e.g. MAIZE and send to 198. Information on the daily prices can be received instantly. This is a joint effort between MTN and FOODNET;

• Training farmer groups: In addition to providing reliable data, FOODNET is also developing educational information for farmers, so that they can understand and use market information more effectively.

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2.3. National Strategy for Food and Agriculture Statistics

The Ministry of Agriculture, Animal Industry and Fisheries (MAAIF ) was identified as one of the nine Ministries, Departments and Agencies (MDAs) that are being covered in the first phase of the PNSD. In the PNSD report for Uganda, there are the following relevant and specific recommendations for MAAIF and Bank of Uganda:

i) Ministry of Agriculture, Animal Industry and Fisheries (MAAIF)

� Setting up a unified statistics unit covering crops, livestock and fisheries sub-sectors;

� Setting up an Agricultural Information System (AIS) (Annual Programme); � Preparing and participating in agriculture censuses; � Updating framework for data collection; � Training staff of statistics unit in IT, statistics and other areas including

secondments and attachments depending on the actual needs.

ii) Bank of Uganda

� Improving coordination and collaboration arrangements with providers of primary data;

� Improving data production processes; � Maintaining a strong data system; � Ensuring that non-reporting Institutions are compelled to report through non

provision of licenses; � Training staff of statistics unit in IT, statistics and other areas including

secondments and attachments depending on the actual needs. Further, as part of the development of the Plan for National Statistical Development (PSND), UBOS contracted an Agricultural Statistician (National Consultant), to support MAAIF to prepare a data collection plan for the Sector’s Statistics (crops, livestock and fisheries) with the following tasks:

i) To identify and visit all the major institutions or agencies currently collecting or compiling any agricultural statistics;

ii) To prepare a formal inventory of the different data systems; iii) To review the data collected, methodology, procedures used, coverage,

availability, levels of aggregation, quality, frequency of up-dating, and utility; iv) To review major data needs related to agriculture- Management Information

System (MIS), monitoring the Programme for the Modernisation Agriculture (PMA), Gross Domestic Product (GDP) statistics, PEAP monitoring etc;

v) To review data gaps and priorities for addressing these in line with the national and sector plans;

vi) Propose a strategy for developing a feasible and realistic data collection plan. The plan presents low, medium and high case financing scenarios, includes annual and multi-annual data collection calendars and presents trade-offs (e.g. agricultural census or annual agricultural surveys);

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vii) Hold the final discussions within existing decision-making structures i.e. Agricultural Sectoral Committee of PMA, and/or the National Agricultural Statistics Technical Committee (NASTC) at a national workshop, build consensus and prepare a final report.

The consultants report “A Data Collection Plan for Agricultural Statistics in Uganda” was submitted early in 2007. 2.4. Human Resources Available

MAAIF currently has two statisticians as a result of restructuring of the Ministry in the early 1990s. UBOS has five statisticians directly responsible for agricultural statistics. However, temporary staff is recruited by UBOS and MAAIF when conducting censuses and surveys. For example, 12 Statisticians were temporarily appointed to assist with the on-going Uganda Census of Agriculture, 2008/09. At District level the Planning units handle all the Statistics in collaboration with different departments handling agriculture. The other agencies have different staffing levels. Indeed, very few have fully-fledged statistics offices. 2.5. Non-Human Resources Available

MAAIF has insufficient equipment (hardware, software, vehicles) and limited budget for statistical activities. On the other hand, UBOS acquired some equipment as preparations to conduct the census of agriculture are on-going. The challenge is sustainability. 2.6. Data Dissemination Policy for Food and Agriculture Statistics.

Normally, the policy for data dissemination for large surveys and censuses is six months after the end of the data collection exercise. For quarterly surveys it is 6-8 weeks from the end of reference period. The annual UBOS Statistical Abstract is released just before the Budget Speech in June. 2.7. Modalities of Promoting User-Producer Dialogue

The agricultural data users and producers committee and main forum for discussion on concepts, methods and other technical issues on Agricultural Statistics is the National Agricultural Statistics Technical Committee (NASTC) comprising of the main stakeholders in Agricultural Statistics, including:

• The Commissioner for Agricultural Planning, (MAAIF) as Chairperson;

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• The Director, Business and Industry Statistics (BIS) (UBOS) as Head of the Secretariat

• The members are: o Deputy Executive Director, Statistical Production & Development

(UBOS); o Director of Population and Social Statistics (UBOS); o Representatives from

� the Institute of Statistics & Applied Economics (ISAE), Makerere University;

� the Ministry of Local Government; � the Ministry of Gender, Labour, and Social Development; � the Bank of Uganda; � the Ministry of Finance, Planning and Economic Development; � the National Agricultural Research Organisation; � the National Agricultural Advisory Services; � the Meteorology Department; � the Uganda Coffee Development Authority; � the Cotton Development Organization; � FEWS-NET (USAID); � the Plan for Modernisation of Agriculture (PMA) Secretariat; and � the Uganda National Farmers Federation.

The NASTC , is expected to meet at least once a quarter to:

i) Review and approve work plans for agricultural censuses, surveys and other pertinent data collection systems;

ii) Review budgets; iii) Provide technical guidance on issues relating to sample design, quality

control, questionnaire design, etc; iv) Review manuals for guidance of district statisticians and advise on

backstopping agricultural statistics work in districts; v) Review all existing agricultural statistics with a view to revising them in light

of new findings; vi) Advise on the diffusion of good practice in the development of agricultural

statistics; vii) Clear publications on agricultural statistics before dissemination takes place;

and viii) Any other duty as assigned by the policy level National agricultural Statistics

Coordination Committee (NASCC).

Unfortunately, the NASCC has never been constituted.

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2.8. Existing Databases and Data Dissemination Tools and Platforms

Databases are owned by the agencies which generate the data, but data is shared with UBOS, according to need especially when generating data for the Annual Statistical Abstract. Data dissemination is in hardcopies (publications), CDs and summaries are posted on the website. www.ubos.org. Other databases are shown in Annex 3.1 under the respective agencies. 2.9. Regional Integration and International Technical Assistance Received

There is an initiative by the East African Community Secretariat on harmonization of methodologies, concepts and definitions in conducting censuses of agriculture starting with the current programme for the Censuses of Agriculture 2010. Both UBOS and MAAIF have jointly received technical assistance and training in the current programme for the Uganda Census of Agriculture (UCA) from FAO, World Bank and DFID. There has also been training by FAO on the CountrySTAT programme. UBOS had earlier received assistance from the Norwegian Government to establish a Permanent Agricultural Statistics System (PASS). The Royal Norwegian Government, through its Agency for Development Cooperation (NORAD) provided US$600,000 per annum for three years under the Support to Strengthen Agricultural Statistics Project (SSASP). The project supported start-up activities on: Data Management; Institutional Capacity Building; Village Registration System/Agricultural Reporting Service; Early Warning System and conducting of a Pilot Census of Agriculture (PCA) during the first season of 2003 (i.e., January to June 2003). This project also supported the Permanent Agricultural Statistics System (PASS) activities. This could not however be sustained when the funding stopped.

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3. Existing Databases and Data Dissemination Tools This chapter discusses the existing data and dissemination tools. However, an inventory is given in ANNEX 3.1. 3.1. Crops Statistics

Data is available from MAAIF/UBOS annual publications; Surveys and Censuses. These are outlined below. The Directorate of Crop Resources also has data on crop protection. Finally, data from the Semi-Autonomous Bodies under MAAIF is discussed. 3.1.1 MAAIF/UBOS Annual Publications The FAS data published annually in the Statistical Abstract are mostly imputed. The main source of base year estimates of food crop production has been the 1989/90 Household Budget Survey (HBS) conducted by the UBOS predecessor, (the then Statistics Department of the Ministry of Finance, Planning and Economic Development (MFPED)). The existing methodology, which has been in place since the HBS, uses consumption data as the starting point. Consumption of each food crop, as recorded in Household Surveys, is converted to estimated Value Added equivalent, by making allowance for many factors, including an estimate for districts excluded from the specific survey for whatever reason, exports, non-household consumption (e.g. in hospitals, refuge camps, boarding schools, etc.), inputs in manufacturing and restaurant meals, use as seed and feed, and intermediate consumption. Seasonal crop patterns are estimated on a crop-by-crop basis using some data and information provided by MAAIF, Agricultural Statistics Unit. The calculated Value Added is then moved by estimated percentage changes in production as advised by MAAIF. These estimates are discussed in detail with MAAIF officials, and are made half-yearly, in order to calculate real growth for both fiscal and calendar years. Data on cash crops – mainly coffee, cotton and tea continue to be compiled by the statutory bodies established to handle the development and marketing of the respective crop. However, some of this data is marketed quantities rather than actual production, though most of the production is marketed.

The Metadata for the Crops Sector

i) Data type/ Indicator: Data is given on crop area planted and production for selected food crops. The crops covered are plantains; cereals (finger millet, maize, sorghum, rice, wheat); root crops (sweet potatoes, Irish potatoes, cassava); pulses

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(beans, field peas, cow peas, pigeon peas); and others (ground nuts, soya beans, sim-sim, sun flower); ii) Definition and standard classification: Classification are given by plantains, cereals, root crops, pulses, others; iii) Scope/coverage of data: All major crops covered at national level only; iv) Sources of data produced: Imputation adjusted in discussion with MAAIF v) Compilation practices in the data production: see above

vi) Method of computation: see above vii) Accessibility and availability of data: published annually in the Statistical Abstract by UBOS. Published around June before MFPED Budget speech. Accessible at Web site: www.ubos.org; E-Mail; ubos@ubos.org; UBOS also has a Resource Centre; viii) Accounting conventions: semi-annually (seasonally) ix) Collection and limitations: MAAIF data on trends, but not on levels, is utilized. The constant price estimates so derived are then inflated by CPI data on individual crops, to obtain estimates in current prices. There has been a tendency over the years for MAAIF estimates of trends to overstate real growth, so regular reviews of aggregate estimates for the sector, in association with MAAIF officials, are conducted, in order to maintain reconciliation with estimates based on consumption data.

3.1.2. MAAIF and UBOS Surveys MAAIF has carried out Annual Agricultural Statistics Surveys in 1964/65, 1966, 1991/92 and 1992/93. These were scientific sample surveys and followed the censuses of agriculture, mentioned in Section 2.7. Data is available in hard copies in the UBOS library. Unfortunately, the Government could not sustain the survey system. Secondly, Crop Surveys have been included as core modules in the following UBOS household surveys:

(i) The Second Monitoring Survey (SMS) - 1994/95 (ii) The Third Monitoring Survey (TMS) - 1995/96 (iii) The Uganda National Household Survey (UNHS) - 1999/00 (iv) The Uganda National Household Survey (UNHS) - 2005/06 (v) The National Service Delivery Surveys (NSDS) - 2000, 2004 and 2008

i) The Second Monitoring Survey (SMS) - 1994/95 The Statistics Department and then UBOS carried out household surveys in 1989, 1992/3 and 1993/4. However, collection of agricultural statistics started with the SMS in 1994/5. The SMS included the socio-economic household survey and added a Diagnostic Crop-Survey to explore the possibility of getting reliable estimates of production of major crops by Inquiry Method i.e. the subjective method of asking farmers or by observation by the field staff rather than carrying out actual measurements of area and

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yield/production. The SMS had a survey period of about six months only. Consequently many of the results may be affected by seasonal fluctuations

ii) The Third Monitoring Survey (TMS) - 1995/96 From 1995/96, the survey series was renamed as the Uganda National Household Survey (UNHS) and in that year the survey had the Crop Survey as the core module along with the continuing socio-economic and community surveys. After the experience from SMS, the Inquiry Method was again used i.e. farmers’ estimates of crop area and production. The survey was implemented in collaboration with MAAIF. Limited structural and current agricultural data was collected on:

• Number of Holdings and Characteristics;

• Number of Agricultural Workers;

• Land Ownership and Cultivation; and

• Crops – area, yield, production and sales iii) The Uganda National Household Survey (UNHS) - 1999/2000 The 1999/2000 report gives data with comparisons to 1995/96. It is not clear whether adjustments were made before making these comparisons. iv) The Uganda National Household Survey (UNHS) - 2005/2006 The Agricultural Module covered the household crop farming enterprise particulars with emphasis on land, crop area, inputs, outputs and other allied characteristics. The purpose of this module was to give a better descriptive picture of Uganda’s farm economy, and a deeper insight into factors affecting farm incomes. These would provide a better understanding of the influence of farmers’ resources and marketing opportunities on farm-household income among other characteristics. The components included: investments on land, crop areas, labour and non labour inputs for both the Second Season 2004 and First Season 2005, crop disposition, land rights, disputes and certificates; livestock, small animals and poultry reared or owned, expenditure on livestock and agricultural extension services and technologies. The UNHS Agricultural Module had the overall objective of collecting data for estimating agricultural production namely crop production and livestock numbers. More specifically, the following data was collected:

• Data on current land holdings and ownership;

• Crop plot numbers by parcels operated within the Enumeration Area (EA) and within the District;

• The data was divided between pure and mixed cropping with an indication of the percentages of the mixtures;

• Data was also collected on the holders’ pre-harvest and post-harvest estimates;

• Agricultural sales and prices at the holding level;

• The price data collection was preceded by first screening as to whether anything was sold during the past month; if so, the volume sold the last time and the price at which it was sold ; and,

• Livestock and poultry numbers. Data on all these surveys is available at national and regional level as hardcopy reports in UBOS.

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v) The Pilot Permanent Agricultural Statistics System (Pilot PASS) 2004, 2005 and 2006/07 The broad objective of the pilot PASS was to develop and put in place a cost-effective, sustainable, credible and robust system of agricultural data (on crop area and production, and livestock and poultry numbers) collection at district level, in order to meet the data needs of district local governments for their planning. Data collection was carried out twice a year (where there are two seasons). Data was collected on a sample basis for the small and medium holdings and on a complete enumeration basis for the Private Large Scale and Institutional Farms. The pilot programme provided the opportunity to test procedures and determine costs with some accuracy. Once fully implemented, PASS was therefore expected to meet the stakeholders’ basic need for effective and regularly updated information on agricultural production at the district level in Uganda. Unfortunately, future funding is yet to be ascertained The Pilot PASS covered five districts. This was followed with surveys in 2005 and 2006/7 in another ten and seven districts, respectively. Unfortunately, the data and report for the 2005 and 2006/07 rounds are not yet finalized. vi) The National Service Delivery Surveys (NSDS) 2000, 2004 and 2008 Government has the obligation to provide services to its citizens and to steer economic growth and development through provision of public services. The public service is the main implementing machinery for national development programmes and specifically, the delivery of public services. The NSDS has been institutionalised by Government as a key instrument to monitor and evaluate the service delivery. Under the Public Service Reform Programme, two NSDSs were conducted in 2000 and 2004. The overall objective of the third NSDS 2008 was to provide a comprehensive assessment of the trends in service delivery in the areas that were covered in the previous surveys and to obtain a baseline position in the additional areas that were brought on board. The study was conducted in all regions of Uganda and covered the sectors of education, health, agriculture, infrastructure, water and sanitation, energy, justice, law and order, and public sector management and accountability. The survey established the availability, accessibility, cost and utilization of services and whether service recipients were satisfied with service delivery in terms of coverage, quantity and quality. In each of the sectors covered, the survey provides feedback from service recipients regarding areas where progress has been made and positive trends in service delivery. Likewise, for each area covered, the Survey Report also highlights areas where challenges are still being encountered. 3.1.3. The Uganda Bureau of Statistics (UBOS), the Bank of Uganda (BOU) and Uganda Revenue Authority (URA) External Trade Statistics and the Informal Cross Border Trade (ICBT) - October

2003 to June 2005 and 2006

UBOS, BOU and URA make monthly estimates of external trade data. These cover the major exports and imports and are published in the UBOS Statistical Abstract. However,

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a lot informal cross-border trade is not covered. So since October 2003 the three institutions have been carrying out the Informal Cross Border Trade (ICBT) Surveys. The ICBT is an economic survey covering the transactions in goods across Uganda’s borders that are not recorded by Uganda customs’ authorities. Many of these are agricultural commodities. The major objective of the survey is to establish the magnitude of unrecorded trade between Uganda and her neighbours in order to improve the coverage of external trade statistics for Balance of Payments and National Accounts compilation. The specific objectives are to: establish the direction of trade for transacted goods (Country of Destination/Origin); estimate flows in terms of values and quantities; provide a comparative analysis of recorded and unrecorded trade including net trade balances; generate monthly and annual ICBT estimates for Balance of Payments and National Accounts compilation; and establish the position of Uganda in terms of comparative and competitive advantage under ICBT arrangement. The survey between October 2003 and June 2005 was executed in three phases. Phase I, II and III each covering a period of four months, with the intention of covering a full calendar year which is long enough to capture seasonality and generate sufficient information for estimating ICBT activities. Phase I pilot field activities commenced in October 2003 and ended in January 2004. The results for this phase were disseminated in August 2004. The pilot survey provided an opportunity to test data collection instruments and formed a firm basis for the main survey. The main survey, Phase II and III, covered selected weeks over a period of ten months, from the month of August and September 2004, and February, March, April, May and June 2005, respectively. The split of this main survey into two different years was due to financial constraints. The information generated therefore could provide indicative estimates about ICBT transactions. Using interpolation, extrapolation and time series methods to estimate un-monitored months, a longer data series was produced. Fourteen border stations that were known to have high concentration of informal trade transactions were selected; four along Uganda-Kenya border; six along Uganda-DR Congo border; two along Uganda-Rwanda border; and one each along Uganda-Tanzania and Uganda-Sudan borders were monitored for a period of 140 days (each having 14 days monitored) in ten months. The actual border posts are shown in Annex 3.1. The results of all three phases have been merged to generate a dataset that partially captures seasonal variations/effects. These are in the Informal Cross Border Trade Survey Report, June 2005. Sampling Procedure The first stage involved determining the total number of customs stations to constitute the population size. The customs stations that are known to have informal trade transactions and are strategically situated at the frontier between Uganda and her neighbors comprised the entire population. This implies that inland ports were not considered for monitoring. Others customs stations excluded are those located in insecure places and do not experience any informal trade activities. Other considerations in defining the population were availability of supporting government institutions (like immigrations, revenue offices and police stations), easy accessibility and the volume of unrecorded trade involved. The sampling frame therefore consisted of a list of all customs stations (twenty

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seven) in the population domain selected using the above criteria. This was made possible by prior assessment visits by the technical team. The fourteen customs posts were then purposively sampled for monitoring in order to generate estimates for unrecorded trade. Overall, the customs posts selected for monitoring in 2003 to 2005 and 2006 constituted approximately 90 percent of both formal and informal trade flows and are spread all over the five neighbouring countries. The use of purposive sampling technique in selecting border posts for monitoring was found appropriate in this peculiar situation. Purposive sampling involves selecting sample units according to a purposive principle to achieve desired objective. Although this method is subject to bias and less efficient compared to stratified sampling, proper application of it with adequate knowledge of the population characteristics could provide a representative sample to generate sufficient information on the population parameters. The technique was found useful in minimizing resource wastage on sampling units (border posts) that are insignificant or experiencing minimal informal activities, which would have otherwise been selected in the random process. Selection of Weeks for Monitoring Due to resource constraints, it has not been possible to monitor ICBT activities for a full month. The next stage therefore required specification of two weeks randomly selected from each month for monitoring. The method devised was to divide the month into four weeks, whereby two weeks in a month were monitored and the flows for the remaining two weeks estimated. Survey Organization The UBOS and BOU senior staff carry out regular monthly coordination and supervision of ICBT fieldwork activities to minimise none sampling errors and ensure compliance to best practices. At every border station, at least two enumerators are engaged in the collection of data during the monitoring weeks. The team of enumerators is composed of persons who have been rigorously trained and are have adequate knowledge of the local languages at the given border stations. Enumerators also work hand in hand with the Immigration and Revenue Officials. The business community including those dealing in informal trade at border stations assists in identifying goods whenever required. Data Processing and Analysis The ICBT data processing is jointly done by the collaborating institutions after submission of field returns. Up-rating of survey results is done in order to generate monthly estimates from two weeks data for each month monitored. The up rating of survey results is based on the following assumptions: The supply and demand for industrial and other products from either side of the border are fairly constant throughout the months of border monitoring; The supply and demand of agricultural products fluctuate depending on the season, whether planting or harvesting season and the day of the week (e.g. market day); The average value of flows (imports/exports) for a day of the week, say Tuesday is multiplied by the number of times Tuesday occurs in a month. The procedure is repeated for all the days of the week and a sum of the values estimated to get the monthly estimates; Trade transaction through other crossing points in the neighborhood of the monitored border stations are estimated individually based on qualitative monthly reports that are compiled by the supervisors after every monitoring

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month. Therefore, the reported percentage yields the estimated trade that cross via the neighbourhood of each monitored border station. Data Revision and Integration The ICBT survey results reveal significant flow of both industrial and agricultural goods between Uganda and her neighbours, with Uganda being an overall net informal exporter to her neighbours. The ICBT findings have been fully incorporated into the Balance of Payment Statistics current account for the years 2002 to 2007. Further revisions are expected in merchandise trade figures after completion of commodity coding using internationally recommended HS and SITC nomenclatures and isolation of re-exports. Data Limitations The ICBT survey has some of the following limitations:

i) The surveys do not cover all the border stations in the country. ii) There is also no monitoring along the lakes and at Entebbe international

airport. Some of the borderstations that are not covered may have significant amount of informal cross border trade flows;

iii) Trade occurring at night and beyond stipulated time of monitoring 7.00 am to 6 pm is not covered;

iv) The porous nature of the Ugandan borders and failure to monitor all cross border sites may lead to underestimation of the volumes of informal trade flows;

v) The surveys take at most two weeks of border monitoring instead of four weeks in a month, thus failing to capture the transactions for the entire months in which border monitoring take place;

vi) The Direct Observation technique does not accurately estimate the quantities of some traded items especially where assorted goods are involved in one package. Other estimation problems arise as a result of items being transported in non-transparent packages, and those in bulk like sugar canes, fruits etc. Assignment of values, quantities and units of measure to some unique commodities is not accurately done because of the nature of the goods traded at respective border stations.

Thus, the limitations render the survey procedures unable to cover 100 percent of the trade in all the monitored sites. The following measures are taken to address limitations (iv), (v) and to a significant extent (vi) stated above: a) Data verification, which included validation, consistency checks and coding in line with international merchandise trade statistics recommendations; b) Data up-rating.

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Limitation (ii) has not been addressed because of failure to find conclusive technical solution at the moment. Limitation (i) was partially tackled through ICBT border expansion program implemented during 2007/08 financial year ICBT Survey for 2007 and 2008 Institutional and Funding Arrangement The survey between October 2003 and June 2005 and then 2006 was jointly funded by the Bank of Uganda and UBOS, under the DFID economic statistics support. BOU and UBOS have continued to provide technical and financial support to the informal trade survey since 2003. Uganda Revenue Authority (URA) was an active participant until late 2005 when it became constrained by human resource to participate in the survey. The BOU has made a provision for ICBT funding from her annual budgetary allocation in Trade and External Debt Department (TEDD) and created a specific section in TEDD to organize the ICBT surveys. The UBOS funds were provided by the Multi-agency Integrated Framework for Trade through TRACE Project of the Ministry of Tourism, Trade and Industry (MTTI). The other stakeholders who enabled smooth running of the survey include the Immigration Department, the Uganda Police, the Business Community and the Local Leaders at various border posts. Scope and Coverage for ICBT 2007 and 2008 The ICBT survey initially covered fourteen selected border posts. The other border posts had been left out due to financial constraints, poor communication (i.e. transport, telecommunications), insecurity and low trade volumes. However, after the signing of the Comprehensive Peace Agreement (CPA) between the North and Southern Sudan, political stability returned to Southern Sudan and DRC, where new crossing points started experiencing unprecedented flows necessitating further border expansion for ICBT monitoring. During the Financial Year 2007/08, the ICBT Technical Team added six new border posts and three bus terminals under ICBT border expansion program. This was aimed at widening the scope and coverage of informal trade activities that kept soaring as security improved in the neighboring countries. Twenty border stations were selected for monitoring. In addition to these, three bus terminals added were; Arua/Juba, Kampala/Kigali, Kampala/Juba. Transactions through bus terminals are included in their respective borders of exit or entry. Details are given in Annex 3.1. ii) Consumer Price Index (CPI) - UBOS

In order to compute the monthly CPI, UBOS collects retail price data from Kampala, Jinja, Mbale, Masaka, Mbarara, Gulu and Arua. Plans are underway to collect data from more centres including more rural-based markets. Average Retail Prices are therefore published monthly with the CPI press release. The list of commodities includes food items. Data is published monthly. The prices data is collected by UBOS staff purchasing the commodities. This takes care of any price deductions and/or increases. iii) Domestic Resource Costs (DRC) and Index of Agricultural Production (IAP) -

BOU

Following the closure of the former Agricultural Secretariat (AGSEC) of BOU in 1996 and of MFPED in 2002, a glaring information gap on profitability and competitiveness of

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Uganda’s exports was created. The collection of necessary data for analysis of cost of production, marketing, processing and export which are all required for estimation of profitability of exports was one of the main responsibilities of AGSEC. Sadly, there were no other institutions in the country doing similar analysis; hence the large vacuum left behind following its closure. Consequently the Bank and the Ministry of Finance, Planning and Economic Development (MFPED) started experiencing serious lack of data on profitability of exports. In accordance with its mandate of maintaining price stability, the BOU is required to monitor exchange rate movements and effect on the profitability of Uganda’s exports. Therefore, in 2007 the BOU in agreement with MFPED decided to implement a project aimed at studying the establishment of its own institutional framework to compile domestic resource cost ratios (DRC) and index of agricultural production (IAP). The DRC ratios are used to measure the competitiveness and comparative advantage in the production and marketing of a country’s tradables. On the other hand, IAP is used to provide an indicator of the production trends of a country’s agricultural sector relative to a given base period. The broad objective of the DRC/IAP project of BOU is to identify and establish an institutional framework and a system for compilation of DRC ratios and IAP statistics on a regular basis, and to produce reports on the two statistics regularly. The main purpose of the DRC/IAP reports would be to document and publish DRC ratios and the IAP values for ready use by BOU and any other interested parties. For DRC, commodities contributing at least 0.5% of total value of export earnings, while for IAP crops contributing 0.1% of agricultural GDP were used. By using these criteria 17 commodities and 27 crops were selected for DRC and IAP, respectively. So far three DRC reports covering different numbers of commodities have been produced. The first one was produced in July 2007 covering beans, coffee, cotton, education, fish, flower, maize, tea, tobacco and tourism. The second one followed in February 2008 covering beans, cobalt, cocoa, coffee, cotton, education, fish, flower, hides and skins, maize, tea, tobacco, tourism, and vanilla. By the end of December 2008, the team had produced the third report of the DRC, covering 12 commodities, namely beans, cocoa, coffee, cotton, education, fish, flowers, tea, vanilla, hides & skins, maize, and tourism. Methodology and System for Data Collection A system of data collection through sample surveys using questionnaires administered to individuals and /or groups of farmers, traders, processors and exporters and through Focus Group Discussions has been established. Each DRC commodity has a specific set of questionnaires given the differences in the activities by commodity and stage in the chain of activities from production to export. The first IAP report, also disseminated during the February workshop, was compiled using data collected between February and December 2008. In the absence of more frequent data on agricultural production, the team designed a possible proxy to compute

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the IAP based on the monthly export figures for the cash crops, and the internally marketed quantities of food crops, collected from a sample of markets and exported quantities. Dissemination Workshops Dissemination workshops are a prerequisite for keeping stakeholders informed of the project’s activities by discussing the reports together so that they make their input. So far, three stakeholders’ workshops have been held. The first one was held in December 2006 soon after the inception of the project; followed by a second one held in May 2007 and the most recent one in February 2009. As a result of these workshops, the Bank has forged partnership with stakeholders, which has translated into ease of data sharing. Uganda Bureau of Statistics (UBOS) is the most important partner partly as a legal requirement in collecting and publishing of the statistical data, but also in data sharing. A data bank section has been purposefully created in the Division to take care of the data that will be generated, and make sure that loss of data is not repeated as was the case after the closure of the Agricultural Secretariat. The data will be put on the BOU web-page.

3.1.4 Agricultural Censuses MAAIF has carried out the 1963/65 Census of Agriculture; the 1991/2 National Census of Agriculture and Livestock (NCAL) and together with UBOS the on-going Uganda Census of Agriculture (UCA) 2008/9. These have been sample censuses and covered all crops and livestock. Unfortunately, results from the NCAL and the subsequent surveys were contentious and never fully used. There have been several reviews stressing the weaknesses of NCAL and the subsequent annual surveys. Annex 3.2 of the consultants report on A Data Collection Plan for Agricultural Statistics in Uganda, 2007 gives a summary of the reviews that have been carried out on NCAL 1990/91. Only hard copies of the reports are available in various libraries. There are hardly any primary data in soft copies except incomplete sets with individual officers.

Livestock Census 2008 Under funding from the African Development Bank (ADB), MAAIF secured a loan to implement the National Livestock Productivity Improvement Programme (NLPIP) which has several components one of which is the Livestock Census (Inventory). The goal of NLPIP is to achieve economic growth and poverty reduction in line with the sector goal. The project objective is to contribute to poverty eradication by improving productivity and marketing in the livestock industry in general and meat sub-sector in particular, to ensure availability of quality products for both the domestic and export markets. It was agreed that sampling would be used with emphasis in the cattle corridor. A Task-force composed of staff from UBOS and MAAIF was established to assist in conducting the Livestock Census. It prepared the budget, implementation plan, draft questionnaires and manuals. A Sampling Consultant was recruited. Enumeration for the National Livestock Census (NLC) for Uganda was conducted nationwide in February 2008. After the data was processed, a team from the Secretariat for the Plan for the

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Modernisation of Agriculture (PMA), the Institute for Statistics and Applied Economics (ISAE) at Makerere University, and the Kampala office of the International Food Policy Research Institute (IFPRI) worked from January to June 2009 with the data to create the statistical abstract tables on the census. The team did this work on behalf of MAAIF and UBOS. The NLC was a large sample survey consisting of about 950,000 households. As such, sample weighting factors were used to generate population-level estimates for each characteristic that is presented in the tables. The standard errors are also presented. The NLC was conducted in all the 80 districts (as of July 2007). The enumeration exercise was carried out during the period of 18th – 25th February 2008 under the authority of the Uganda Bureau of Statistics Act, 1998. The NLC was therefore, a big step by the Government to establish a livestock database in all districts in order to support policy and planning for future livestock strategies. Data and information on Livestock, Poultry and other Domestic Animals included; Particulars of the Household head; Production systems, enterprises and land ownership; Goats population; Sheep population; Pigs population; Poultry/ birds population and eggs; Rabbits population; Horses, donkeys, and camels population; Farm infrastructure, equipment and implements; Apiary and Beehives; Labour employed by source and by sex; Cattle population, milk production and milk sales.

Scope/Coverage This census covered both household-based farms as well as institutional farms. While a complete enumeration of all institutional farms was conducted in all districts; a representative sample of household-based farms was enumerated. As mentioned earlier, the NLC was carried out in all the 80 districts of Uganda. A representative sample of at least 50 Enumeration Areas (EAs) was selected in each district - an EA is an area with a population of about 200 households covering part, one or more neighboring villages/LCIs. The number of selected EAs in each district depended on the number of livestock rearing households in the district. Countrywide a total of 8,870 EAs were selected. By design, all households in the selected EAs were supposed to be enumerated. Data Collection Instruments Two main instruments were used during data collection, namely: the household questionnaire and the Institutional farms questionnaire. The household questionnaire was used to gather information from households, while the institutional farms questionnaire was used to gather information from the Institutional farms. Summary Results of the National Livestock Census A Summary Report on the major livestock species is presented in A Summary Report Of The National Livestock Census, 2008 of 27th May, 2009. It includes numbers of cattle, goats, sheep, pigs, chicken, ducks and turkeys by Regions. Although Karamoja is not recognized as a Region, the figures for Karamoja have been separated because of the large numbers of livestock in that area. The District figures are in the Appendix tables. Graphical distribution of the above livestock species is also shown. Other species still to be analyzed include; rabbits, donkeys, camels, horses, geese and Guinea fowls. Tables

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will also be generated showing households owning livestock, indigenous and exotic/cross breed numbers, labour use of households that engage in livestock rearing, diary production, chicken egg production, farm infrastructure, equipment and implement ownership by livestock raising households. Three reports are currently under preparation, namely: A full National Livestock Census Report-including a general report (with detailed tables on most of the variables on which data was collected)-; an administrative report (detailing how the entire survey was managed); and Thematic maps report that will contain shaded area and dot maps showing information on selected variables at various administrative levels where possible.

3.1.5 The Directorate of Crop Resources, MAAIF Crop protection zones have been identified and 34 new inspectors have been deployed and are charged with collecting data in this respect. The Department occasionally collects data especially on the disease and pest outbreaks and some records do exist in the area of phyto-sanitary issues. This directorate has limited manpower in terms of numbers and Statistics skills. The directorate is not hooked on the internet. Computers are not enough and those that exist are quite old. Some files on statistics may exist but they are scattered and not updated. Annex Table 3.2. gives the metadata on crop protection. 3.1.6 Semi-Autonomous Bodies under MAAIF

i) The National Agricultural Advisory Services (NAADS) One of NAADS key principles is empowering farmers. It concentrates on empowering communities (specifically farmer groups) to do voluntary reporting. This is achieved through Farmers’ Groups (FGs), Parish Coordination Committees (PCCs), and Sub-County Farmers’ Fora (SCFFs). Findings from a pilot PME study indicated that farmers have the capacity to conduct PME if initially well guided and trained. The PME methodology was found to strengthen community enthusiasm and participation in the NAADS processes. NAADS Secretariat mostly collects administrative data. In order to monitor outcomes on sustainable and increased production, productivity and profitability of enterprises, NAADS has limited coverage and the idea of using farmer groups also has low reporting levels since their education levels are also low. However, it is necessary to continue sensitising all stakeholders on benefits of reporting, facilitating and empowering farmers to compile their own data which others can also benefit from.

Baseline Surveys As soon as a sub-county has been added to the programme and farmer groups have been formed, the NGOs enter into contact with the groups and start the process of incorporating them in the NAADS system. At this time they need to collect details on land, crops and livestock, natural resource management, farm income and expenditure, gender relations, wealth ranking, etc. together with the groups. This data serves the enterprise selection process at group level. In 2004, baseline surveys were conducted in

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eight districts1. While the surveys lack essential technical information, the reports provide solid socio-economic data and do indeed offer a basis for planning and policy decisions. But not to measure programme performance. Because that is what it was supposed to do.

ii) The Uganda Coffee Development Authority (UCDA) UCDA produces statistics related to:

a) Monthly and then annual coffee procurements, processing and exports by

destination, by grade, type

b) Daily coffee prices – local and international by type, grade – indicative, lowest

and highest and volumes sold.

c) Average yield per tree and per unit area per coffee type.

d) Total number of coffee tree in production by type (needs updating).

e) Total number of trees planted under the coffee replanting programme 1996 to

date)

f) Average costs for establishment and maintenance of a clonal coffee garden (needs

updating).

g) Characterization of clonal coffee, (needs updating for new areas).

h) Survival rates of new planted trees per district.

i) Number of coffee villages established.

j) Detailed time series on cost structure at the farms, primary processors and

exporters for 1991/92 - 2004/05.

k) Exporter procurement and exports.

l) Average monthly exchange rate which assists UCDA in computation of monthly

access collection and contribution of coffee to GDP.

m) List of clonal nursery operators, their location and capacity of nurseries.

n) Coffee seeds distributed by UCDA.

o) Estimate of coffee trees affected by Coffee Wilt Disease by year by district. This

is done by carrying out surveillance studies. A study was carried out in 1996 on

Coffee Wilt Disease.

UCDA produces fairly high quality statistics related to marketing operations including the costs of production, processing, marketing and exporting coffee. The major weakness is that UCDA, and indeed anybody else, does not generate data on coffee area, yield and production at the farm level. So data reported as “production” is only procured quantities. There are the following experiences with data collection methods:

• The rate of accuracy is not easy to keep up. However, there is a model at Headquarters, used for this purpose.

• Delay in getting monthly reports from the field.

• District Coffee Coordinators compile required data supplied by sub-county officers whose quality is so far satisfactory.

1 Arua, Bushenyi, Busia, Kabale, Kabarole, Lira, Mbarara and Soroti

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• No facilitation below the district. They have motorcycles that they use to go to the field.

iii) Diary Development Agency (DDA) The DDA compiles data on cattle population; dairy farming; milk supply by district; registered raw milk processors and dealers; milk coolers; identified sources and transport routes for milk; milk products, viz. pasteurized milk, UHT Milk, cheese, ice-cream, yoghurt and butter; milk pricing. It is clear most of the data is at the marketing and processing level and not directly at the milk production stage. iv) The Uganda National Farmers Federation (UNFFE) The objectives of the UNFFE include:

a) To lobby and advocate for farmer friendly agricultural policies b) To unite farmers’ organisations and agro-based industries/service organisations

under one umbrella organisation as a common front for the promotion, co-ordination and safeguarding of their activities and interests.

c) To improve farmers incomes and welfare through increasing the quality and quantity of there produce on a sustained basis.

The mandate of UNFFE includes among other things:

a) Distribute farm inputs/implements and market members produce through their trading and business arm – Uganda Farmers Agribusiness Ltd (UFAL)

b) Provision of marketing information c) Provide agricultural-related and other information to the farming fraternity and

the public through the farmers voice newspaper. UNFFE provides technical and advisory information on market prices, crop production and management practices for a number of crops, livestock (cattle & goat), apiary and fish farming. The market information provided by UNFFE is mainly on input and output prices. Officials of UNFFE visit major input importers like MAGRIC, Quality Chemicals, Farm Inputs Care Centre (FICA) Limited, Eastern Africa Seed Company, etc. The information obtained is on types and sale prices of different inputs i.e. herbicides, pesticides, insecticides, fumigants, fungicides, fertilizers, seeds, sprayers and tools as well as their packaging; location of the company selling inputs giving their physical location, e-mail address (if any) and the contact person. Information on output prices is got from the web page of FOODNET for major crops by region. The above information is sent to the member organizations as well as the upcountry offices in each district except for the newly created districts. This information will then flow down to the farmers groups or directly to individual farmers. The input information is sent out twice a year since it does not change that often. Currently UNFFE has not been active for the last five months as far as sending output information is concerned because of the absence of an IT person. However the target had been to send output information out at least every three months if it was not for financial constraints.

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Because of the above problem, UNFFE had gone into an arrangement with FOODNET, paid 20 million shillings so that they could air input and output price information on 6 radio stations. All that UNFFE had to do was to send information to their branches upcountry about the time of airing. The major constraint that is faced by UNFFE is lack of funds. This has affected the frequency of dissemination of information to their beneficiaries. The IT person is no longer full time but only comes in when it is absolutely necessary. The website of UNFFE is also not regularly updated. An official of UNFFE talked to could not even remember when it was last updated. He also agreed that the information should be more frequently updated and that the radio would be a better media to use than the hard copies they send to their branches. These copies are just put on the notice board and since some of the farmers are illiterate, the radio would serve them better. The publications of UNFFE include Farmers Voice newspaper and UNFFE update, both issued out monthly. v) Uganda Fish Processors and Exporters Association (UFPEA) UFPEA Mission “is to set up mechanisms to ensure full participation of members in promoting Uganda fish product, working in partnership with government with respect to policies and programmes in the fisheries sector, promoting sustainable use of fisheries resources and promoting quality assurance in fish processing". UFPEA has lists of their members and contacts which are useful in case one wants to carry out a survey or study of the sector.

vi) Uganda Flower Exporters Association (UFEA) UFEA was established in 1995 and its membership composes 20 flower farms. A Board of Directors, assisted by an Executive Director, governs it. The Association is charged with capacity building and industry development and has this far lobbied for funds from Development Partners for this effort. In addition, it lobbies for a better operating environment for further growth of the industry and arranges training programmes for members in order to improve management at the flower farms. UFEA has a Fresh Flowers Handling Facility, which handles the flower exports of all the UFEA members and therefore keeps data on flower exports; Agencies like UNFFE, UFPEA and UFEA are very useful in data collection as they provide a good check on any data collected like exports. 3.1.7. The Community Information System (CIS) i) Background This is a recently introduced initiative by government under the Rural Development Strategy (RDS) just like the AIS under MAAIF. This System is expected to collect basic information from communities and help monitor household welfare. According to the National Budget Framework Paper for the Financial Years 2005/06 and 2007/08, the objectives of the RDS include increasing farm productivity and household outputs, adding value to production and ensuring a stable market for selected agricultural

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products. One way of monitoring these objectives is through the establishment of a well organized CIS to regularly report on the human population that exists in a given location and their characteristics, their economic status, the income of their households and the overall welfare of the communities in which they live. UBOS was assigned the responsibility of developing the CIS to help inform policy makers at all levels about the status and changes in levels of wellbeing of all communities in Uganda. ii) Objectives of CIS:- The CIS is aimed at regularly collecting basic information from all communities to help monitor household welfare as well as promoting effective utilization of information at all levels of planning. The specific objectives include:

a) Identifying communities by their characteristics, needs, opportunities and obstacles to development

b) Empowering communities to make informed decisions using readily available micro up-to-date data/information

c) Providing a basis for making plans at both national and local levels. d) Supporting the monitoring and implementation of Government programmes.

iii) Data Collection for CIS Basic data/information on education, health, water and sanitation, agriculture production, cooperative groups, existing micro-finance institutions and services will be collected. This basic information will be collected at three levels. These are the individual level to determine the characteristics of every person in the community; the household level to determine household welfare status and the community level to understand access to basic services by the community. Two corresponding questionnaires and their contents have been developed as follows:

a) CIS Form1: Administered at household level and collects data on: � Personal characteristics – Name, Age, sex, relationship to household head,

marital status, education, economic activity; � Household assets – land and housing, transport and communication,

livestock and poultry, crops(number of plots and production) � Credit and Loans during last 12 months (liabilities) � Vital Events during last 12 months.

b) CIS Form 2: Administered at community level collects information on: � Access to primary and secondary school, markets, electricity, safe water,

health facilities, micro finance institutions, roads and cooperative societies CIS is to enable macro information to be collected on the current levels of productivity, food stocks, cultivated areas and outputs and to establish a rural reporting system to enable regular reporting. CIS is also required to generate reports on human population, household characteristics and overall welfare of communities. Therefore, it was agreed that CIS be implemented under two components:

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a) Macro data covering a whole range of sectors and; b) Micro data covering agricultural output changes.

UBOS is the lead agency for macro information while MAAIF (Statistics Unit) is the lead agency for component two, although the two agencies work closely on both. 3.2. Livestock Statistics

Data from the Livestock census 2008 has been discussed in section 3.1.4. Base year livestock numbers published in the UBOS Statistical Abstract are based on Household Budget Survey (HBS) 1989 and movements in stock are based on data provided by the Department of Animal Production and Marketing in MAAIF. Annex Table 3.3 gives the metadata on animal production and marketing. The Department of Animal Production and Marketing & Department of Livestock Health and Entomology under the Animal Resources and Fisheries Directorate collect data through veterinary inspections/ regulations and entomology data from administrative sources. The Department of Livestock Health and Entomology on the other hand, also collects data on;

� Reported outbreaks and control, affected species etc. and is captured either actively or passively.

� Veterinary inspections/regulations and entomology yield data from administrative intervention and participating farmer organizations, respectively.

There are however, the following problems in Livestock Health and Entomology, and Animal Production and Marketing:

• Almost all the information is not orderly especially data on levels of endemic diseases (e.g. worms) collected by local governments

• Information on productivity differentials of several animal breeds is lacking

• Information given is generated through projections which do not consider socio-economic changes thus rendering it unreliable.

Therefore, all the above mentioned data is still required using acceptable and reliable methodologies including data on rangeland and pasture seed production. All the data is published in reports. There is as yet, no internet connection. 3.3. Fisheries Statistics

Base year fisheries estimates given in the UBOS Statistical Abstract are also derived from Household Budget Survey, 1989 and these are extrapolated using annual catch data on both catch levels and values provided by the Department of Fisheries Resources of MAAIF. There are the following problems in the information on Fisheries Resources:

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• The available data is mostly in hard copies, finding specific copies is big problem

• There is no internet connection 3.4. Forestry Statistics

Government of Uganda, in 1998 adopted a policy to restructure many government departments including the Forestry Department. It recognized an urgent need for a change in the policy, legal framework and institutions controlling forestry in the country. The Forestry Department was no longer appropriate for the task and therefore a need for it to be divested. It was decided that a new institutional arrangement was needed hence the Forestry Inspection Division, the National Forestry Authority (NFA) and the District Forestry Services were set up. Government of Uganda worked with DFID, Norway, GTZ, UNDP, FAO and the EU towards this institutional change since 1999. So, the NFA became operational in 2003 under section 52 of The National Forestry and Tree Planting Act and was launched on the 26th April 2004. The establishment of the National Forestry Authority was preceded by the development of the new Forestry Policy (2001) and the National Forest Plan (2002). These were to provide for a framework for distribution of roles and responsibilities amongst sector stakeholders and not just the Forestry Department. The NFA reports to government through the Minister responsible for forestry, and is supervised by a Board of Directors. The structure provides for:

• economic and efficient use of resources: forest reserves, money, people, physical and biological assets,

• accountability for areas of work undertaken by divisions, coordination units, ranges, sectors, beats and individuals,

• co-ordination of different parts of the organisation to ensure they work towards a common goal.

The organisational structure translates into 335 employees that are deployed both at headquarter and in the field. There is developed a human resources manual together with administrative policies developed that make NFA staff a well-motivated team. Biomass Monitoring Reports This is an activity within the public good arena that the National Forestry Authority is tasked to carry out. The monitoring process compromises of field data collection, processing, and statistical analysis based on sample plots systematically distributed across the country at every 5 by 10 km grid intersection. This FY, five hundred (500) plots were planned for measurement mainly from western Uganda. However, it was

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realized that about 413 more plots needed to be measured. This brought the number of plots measured to 913 . The data has been captured and analysed. Mapping of Land Cover and Use The mapping section of the National Forestry Authority is one of the most robust map production laboratories in the country at the moment. This financial year, there have been efforts to standardize, modernize and update the available data sets to meet the increasing customer needs. In this effort, 11 scenes of Land-sat satellite images were purchased, 2 of them have been rectified and 1 scene interpreted and ready for use. Five (5) staff have undertaken capacity building training session in the use of GeoVis software and ArcGIS, the most user friendly map production softwareavailable. It is hoped that this will improve on the effectiveness and efficiency of the map production process at NFA and therefore more revenue. A number of services and products have been offered to the private sector. Among the prominent services are the assessment of biomass resources in Masindi District for Ministry of Energy and the mapping of locations of PV solar systems in the Country for Private Sector Forum. Among the products are the maps both digital and analogue with the former being the most lucrative product. Internally, the mapping unit has had several internal services rendered to the Field Operations Division. The main services are the production of Central Forest Reserve Boundary maps and field based operation maps. Inventory & Surveys The demand for inventory and survey services has been mainly internal, with the Field Operations Division requesting special resource assessments in the following areas:

• Commercial volumes in eucalyptus fire lines in Lendu, leading to correction of volume estimates from 100,000 m3 to 246,000m3.

• Demarcation of Felling coupes in eucalyptus fire lines

• Assessment of burned areas in Central Forest Reserves

• Assessment of scattered trees in areas previously harvested

• Developing a Harvesting Plan for FY 2004/5

• Demarcation of Sand Blocks in Kalangalo Central Forest Reserves

• Demarcation of plots allocated to Tree Farmers issue with tree planting licenses

• A Germany Development Organisation (Deutscher EntwicklungsDienst – DED) hired the services of the NFA to carry out an assessment of the impact of refugee settlement in Madi-Okollo refugee settlement.

The NFA also signed Memorandum of Understanding with MAAIF to undertake rangeland biomass inventories in 29 cattle corridor districts under the National Livestock Productivity Improvement Project, funded by African Development Bank.

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3.5. Water Resources

The mandate of the Ministry of Water, Lands and Environment is to promote and ensure the rational and sustainable utilisation and development and safeguard of land and water resources and environment, for social and economic welfare and development as well as for regional and international peace. Water is life and provision of safe and adequate drinking water is a fundamental human right as enshrined in the Constitution of the Republic of Uganda. Water also contributes directly to socio- economic development of the country and is essential for hydropower production, irrigation, livestock, fishing, mining, wildlife, industries, water transport, maintaining the environment etc The water resources management functions are performed by the Directorate of Water Development in the Ministry of Water and Environment through the Water Resources Management Department located at Entebbe. The Ministry is thus responsible for sustainable and integrated management of the water resources of the country. The recently prepared Water Resources Management reform strategy has however proposed to decentralize management of water resources to a catchment to ensure that all stakeholders actively participate in management of the country’s water resources. This is in line with the various Acts of Parliament such as the Water Act Cap 152, Local Government Act etc. In order to address water resources problems facing the country a number of water resources management functions are carried out namely monitoring, assessment and regulation. Water resources regulation is a function carried out to control overexploitation and pollution of water resources so as to ensure availability of adequate water for all socio-economic activities now and in the future. Water resources regulation is provided for in the Water Act Cap 152, the National Water Policy, and the Water Action Plan and is carried out through the Water Permits System. Regulation of water resources involves administration of water (surface and groundwater) abstraction permits, drilling permits, wastewater discharge permits, hydraulic works construction permits and easement certificates. The Department of Meteorology is a Government of Uganda Institution, under the Ministry of Water and Environment. It plays its specialised role of providing climate and weather services to Government and other stakeholders engaged in national development activities in the Country. It provides Current Seasonal Forecast and Monthly Agro-meteorological Bulletins. The Department of Meteorology establishes and maintains a weather station network across the country. At each of the weather station, weather observations are made daily and the weather records are kept at the Department Headquarters. The weather records are provided to any interested end user on request.

• Seasonal Rainfall Forecasts Bearing in mind that the agricultural production is rain-fed dependant, and there is an increase in the irregularity of seasonal rainfall, the Department provides ahead of time, rainfall forecasts of seasons for the farming communities.

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• Monthly Agro-meteorological Bulletins In addition to seasonal rainfall forecasts, the Department provides monthly agro-meteorological bulletin in which advice is given on performance of previous monthly weather conditions and weather outlook for the next month.

In addition to provision of weather data, the Department process the data to provide tailor made climate information products to the end user as needed. As weather influences crosscuts a number of development activities at different time scales, the Department provides a range of weather forecasts to different users which include aviation, agriculture construction. Realising the scientific nature weather and climate services, the Department provides training to different stakeholders in various issues which include use of climate information products, weather observation and others as required by the user. 3.6. Land Use

Some data on land cover i.e. Area (Sq.Km), Open Water, Permanent Wetland, Area Excluding Open water and Permanent wetland and District Perimeter (Kms) is obtained from the National Forestry Authority. A lot of this data was collected in the Biomass Study in the 1990s and is up-dated regularly. Mapping of Land cover/use

The mapping section of the National Forestry Authority is one of the most robust map production laboratories in the country at the moment. This financial year, there have been efforts to standardize, modernize and update the available data sets to meet the increasing customer needs. In this effort, 11 scenes of Land-sat satellite images were purchased, 2 of them have been rectified and 1 scene interpreted and ready for use. Five (5) staff have undertaken capacity building training session in the use of GeoVis software and ArcGIS, the most user friendly map production software available. It is hoped that this will improve on the effectiveness and efficiency of the map production process at NFA and therefore more revenue. A number of services and products have been offered to the private sector. Among the prominent services are the assessment of biomass resources in Masindi District for Ministry of Energy and the mapping of locations of PV solar systems in the Country for Private Sector Forum. Among the products are the maps both digital and analogue with the former being the most lucrative product. Internally, the mapping unit has had several internal services rendered to the Field Operations Division. The main services are the production of Central Forest Reserve Boundary maps and field based operation maps.

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Biomass Monitoring Reports

This is an activity within the public good arena that the National Forestry Authority is tasked to carry out. The monitoring process compromises of field data collection, processing and statistical analysis and is based on sample plots systematically distributed across the country at every 5 by 10 km grid intersection. Inventory and Surveys

The demand for inventory and survey services has been mainly internal within the NFA. However, the NFA also signed Memorandum of Understanding with the Ministry of Agriculture Animal Industry and Fisheries (MAAIF) to undertake rangeland biomass inventories in 29 cattle corridor districts under the National Livestock Productivity Improvement Project, funded by African Development Bank. Data on modes of land tenure and ownership legal tenured; is collected in the household surveys. Most of this data is also published in the UBOS Statistical Abstract. The Directorate of Land and Environment plans, advises and coordinates the implementation of regulatory and supportive activities on land management and environment protection. The Directorate of Lands and Environment in turn comprises of the Department of Lands and Surveys, Physical Planning Department, Department of Land Registration, Forestry Department, Meteorology Department and the Department of Environment Affairs under the Wetlands Programme. 3.7. Agricultural Population, Inputs, Infrastructure, Credit, Food Availability, and

Prices

3.7.1. Agricultural Population

Data on the agricultural population is available from the Population and Housing Censuses 2002 and the various National Household Surveys i.e. total/male/female/rural/urban/agricultural/non-agricultural) including farm household and rural household 3.7.2 Agricultural Inputs (fertilizers, pesticides, machinery, labour and cost of inputs) The Agricultural Secretariat in the Bank of Uganda had a National Inputs Co-ordination Unit (NICU), which among other things collected data on the import and production of agricultural inputs. So since the closure of the Agricultural Secretariat in BOU in 1996, there has not been a clear collection of this data. However, recently the Uganda National Agro-input Dealers Association (UNADA) has been formed.

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There are different categories of UNADA membership: i) Full members are active agro-input dealers. This category is divided into the following classes, each with their own requirements, rights and benefits:

a) Description b) New Retailer c) Established Retailer (>2 yrs) d) Potential Distributor e) Associations/ Groups f) Distributor g) Supplier

ii) Associate Members: This category is open to interested individuals that have not yet completed training or have not yet opened their business. Associate membership is limited to a two-year period.

iii) Working Partners: This category is open to interested institutions, companies, organizations or businesses involved in related enterprises.

Through the Association, members gain access to price and product information, bulk purchase discounts, delivery services and market information. This data has not yet been compiled. Use of agricultural inputs is however covered in the national household surveys agricultural modules. 3.7.3 (Rural) Infrastructure ( agricultural storage facilities, roads, electrification, mobile phone coverage) Data on infrastructure used for agriculture is available from the national household surveys. 3.7.4 Credit (access to, amount, source and geographical distribution) There is a Research Department Bank Lending Survey (mentioned in Section 2.2.15). The survey provides credit data to all sectors, including the agricultural sector and lenders report policy/standards regarding the overall availability of loans to corporate and households. Use of agricultural credit at the household level is covered in the national household surveys. 3.7.5 Food Availability and Economic (Agriculture Value Added and its dis-aggregation level; income distribution (Gini); rural/urban income) There is very little direct current data on food availability. However, data on value added is given in the National Accounts published in the UBOS Statistical Abstract.

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3.7.6 Price Information Before the liberalization of marketing of agricultural produce in the early 1990’s, State Marketing Boards and Farmers’ Organizations particularly agricultural marketing cooperatives, were the main sources of marketing information for the stakeholders. To fill the vacuum left behind by liberalization, a government run Market News Service (MNS) was set up under the Ministry of Trade and Industry. It was initially funded by FAO until 1993 when it’s funding was taken over by USAID’s PL-480 Food Security Fund. While the information collected was of some use to planning institutions, it was of little use to farmers and in 1999, the services were discontinued. Thereafter, with support from USAID – ACDI- VOCA under FOODNET, A market prices broadcasting project that disseminated information using private and community radios was launched in late 1999. This product was developed and moved to CIAT with support of ABCD/ASPS. Currently, a number of organizations are investing in Ag MIS for example Uganda Commodity Exchange with support from IICD, DFID and ABCD/ASPS. ABCD/ASPS working with the Ministry of Trade and Industry, are looking into the possibilities of privatizing the collection; analysis and marketing the agricultural market information with the aim of reducing the cost of services and address it sustainability. Agricultural price information has been available from FOODNET and the Eastern Africa Grain Council. So far no study has been carried out to establish how they compare. The FOODNET funding run out in the middle of this year and has been taken over by INFOTRADE under FIT Uganda. i) FOODNET

The agricultural price and market information dissemination for Uganda includes:

a) Weekly price data for 16 towns plus four markets in Kampala that includes retail and wholesale prices for the 16 towns; retail and off-lorry for the four markets in Kampala. b) Daily price data for Kampala that gives off-lorry, wholesale and retail prices for four markets in Kampala. The daily Kampala prices for the four markets come out late morning/early afternoon. Local Market Information Service

There is a collaborative project between FOODNET and the National Agricultural Advisory Development services (NAADS) to cover the districts of Arua, Soroti, Kibale Tororo and Mukono. The aim of this pilot project is to develop a localised market information service that meets the marketing needs of the farming and trading community at the district level. The achieve this, the project hires a marketing extension officer who will collect, analysis and then feed back timely market news to the community via radio, newspapers and through meetings.

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The service aims to empower farmers with up to date, accurate information on the market conditions in their locality. This information will enable farmers to negotiate for better market prices based on an informed position. In addition to the provision of market information, the project also includes an educational element that will help farmers to use the information more effectively. Farmers can improve their bargaining powers in many ways and the educational information will provide information on the benefits of collective marketing and also how to gain better prices, by working with traders to supply larger quantities of better quality produce. All of these elements are essential to the NAADS mandate, which aims to encourage farmers to “Produce what they can sell”, rather than “trying to sell what they have produced.” FOOODNET in association with NAADS is developing this new service in the 6 trail-blazing districts of Soroti, Tororo, Mukono, Kibale, Kabale and Arua. The specific activities of the marketing officers are to:

� Collect market information from four markets in each district. � Focus on the data collection on commodities that are specific to the local

markets. � Broadcast the market news in two, two-minute programmes. � Broadcast a weekly round up of the marketing news in the district.

Types of market information collected

The MIS project collects primary and secondary market information on:

� Off lorry, wholesale and retail prices. � Trade volumes in major commodity markets. � Demand and supply conditions in markets. � Quality of produce in markets. � General weather conditions. � Production and price projections. � Market news from Uganda, the East African region and around the world.

Use of market information

Farmers can make use of market information to:

� Negotiation for better prices. � Decide where to sell. � Check on prices they are getting. � Decide whether or not to store. � Decide whether to grow “out of season.” � Decide whether to grow different crops.

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� Decide whether to add value through processing. � Work with other farmers to bulk up commodities. � Decide when to sell their commodities.

Radio dissemination

Three types of radio programmes are used to disseminate market information on crop and commodities.

� Two short radio broadcasts, each of two minutes on Tuesdays and Thursdays.

� A 15 minute programme at the end of each week giving an overview to the national market and a learning programme discussing market opportunities.

� A learning programme for market information will be incorporated and run at the national level.

Highlights

� Weather and various commodities reviews � District briefs

ii) INFOTRADE under FIT Uganda

To promote value addition through private public sector partnership, INFOTRADE which is a set-up under FIT Uganda Ltd, is embarking on agricultural market information dissemination mainly targeting the rural poor farmers and traders. This is aimed at enhancing commercialization of agriculture thus improving household incomes. The data collection and dissemination is very similar to that of FOODNET. Data is collected on about 28 commodities and covers Kampala (5 markets), Jinja, Kiboga, Tororo, Soroti, Kapchorwa, Mbale, Arua, Hoima, Kasese, Kisoro, Lira and Masaka. It is hoped to add Koboko, Gulu, Luwero and Mbarara in due course. iii) The Eastern Africa Grain Council (EAGC)

EAGC is based on interested stakeholders actively engaged in the grain market chain (production, trade, processing, finance, transport, export/import, warehousing, inputs, etc.). One of the objectives of EAGC is to manage market data and generate information exchange in the East African Region. The information is disseminated through the web-site (www.ratin.net), SMS and printed copies. To get prices in US Dollars per Metric Tonne by SMS: type maize or beans or rice or millet or sorghum and send to 8000 for Kenya, 7197 for Uganda and 15711 for Tanzania. To get prices in local currency; type commodity currency unit and send to the numbers stated above.

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3.8. Description of national/ sub-national commodities codes system (if existing) The Crop Groups, Names and Codes used in UCA 2008 and UNHS and the respective FAO code are shown in the Table below. Table 3.8.1: Crop Groups, Names, Ugandan and FAO Codes

Crop Group Crop Name

Ugandan Code

FAO Code

Crop Group Crop Name

Ugandan Code

FAO Code

Wheat 0111 15

Beans (Dry/Green) 0711 176/414

Maize (Green) 0112 56 (446)

Broad Beans 0721

Rice 0113 27

Chick Peas 0731 191

Sorghum 0114 83

Cow Peas 0741 195

Barley 0115 44

Lentils 0751 201

Oats 0117 75

Peas (Dry/Green) 0771 187/417

Millets 0118 79

Pigeon Peas 0781 197

Mixed Cereals 1191 103

5. Leguminous crops

Leguminous crops n.e.c 0791

1. Cereals

Other 1192

Sugar beet 0811 157

Asparagus 0212 367

Sugar cane 0821 157

Cabbages 0213 358

Sweet sorghum 0831

Cauliflowers & broccoli

0214 393

6. Sugar crops

Other sugar crops n.e.c 0891 161

Lettuce 0215 372

(Seed) Cotton 9211 328

Spinach 0216 373

Flax, Hemp 9213 773/777/336

Chicory 0217 372

Other temporary fibre crops

9219

Other leafy/ stem vegetables n.e.c

0219 463

Tobacco 0961 826

Cucumber 0221 397

7. 0ther crops

Other crops-temporary 9911

Egg plant 0222 399

Avocado 0311 572

Tomatoes 0223 388

Banana (Food)/Plantains

3121 489

Water melons 0224 567

Banana (Sweet) 3122 486

Pumpkin 0226 394

Banana (Beer) 3123

Other fruit bearing vegetables

0229 603/619

Mangoes 0315 571

Carrots 0231 426

Pawpaw (papayas) 0316 (600)

Turnips 0232 426

Pineapples 0317 574

Garlic 0233 406

Other 0319

Onions 0234 402/403

Grape fruit & pomelos 0321 507

Other root,bulbs or tuberous vegetables n.e.c

0239

Lemon and Limes 0322 497

Mushroom 0241 449

Oranges 0323 490

2.Vegetables and Melons

Vegetables n.e.c (Legumious)

0291 420

Tangerines & Mandarines

0324 495

Soya Beans 0411 236

Other citrus fruits 0329 512 3. Oil seed crops

Groundnuts/Peanuts 0421 242

8. Fruits and Nuts

Strawberries 0345 544

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Crop Group Crop Name

Ugandan Code

FAO Code

Crop Group Crop Name

Ugandan Code

FAO Code

Caster Beans/seed 0431 265

Currants 0341 550

Linseed 0432 333

Apples 0351 515

Mustard seed 0433 292

Apricots 0352 526

Simsim/sesame 0437 289

Pears 0355 521

Sunflower 0438 267

Plums 0356 536

Irish Potatoes 0511 116

Cashew nuts 0362 217

Sweet Potatoes 0521 122

Coffee Arabica (old) 6111 -

Cassava 0531 125

Coffee Robusta (old) 6112 -

Yams 0541 137

Coffee Arabica (new) 6113

-

4. Root/ Tuber Crops with High Starch or Insulin content

Other root crops and tubers n.e.c

0591 149

Coffee Robusta (clonal) 6114

-

Coffee, Green - 656

Tea 0612 667

Cocoa 0614 661

9. Beverages and spice crops

Other Beverages n.e.c 0619

Condition and State Codes were made up specifically for Uganda as shown in Table below. However, these are only used in the data collection and analysis by UBOS and MAAIF. Table 3.8.2: Codes Developed for Crop Condition and State

Crop type Condition and State

Code Name Description Code

111/112 Wheat/Barley Dry – grain 45

Dry at harvest - with shell 32

Dry after additional drying – with shell 42

120 Rice

Dry after additional drying – grain 45

Green harvested – with shell/cob and with stalk 11

Green harvested – with shell/cob without stalk 12

Green harvested – in the cob 13

Fresh/raw harvested – with shell/cob and with stalk 21

Fresh/raw harvested – with shell/cob without stalk 22

Fresh/raw harvested – in the cob 23

Dry at harvest – with shell/cob and with stalk 31

Dry at harvest – with shell/cob without stalk 32

Dry at harvest – in the cob 33

Dry after additional drying – in the cob 43

130 Maize

Dry after additional drying – grain 45

Fresh/raw harvested – state not applicable 29

Dry at harvest – state not applicable 39

Dry after additional drying – state not applicable 49

141/142/150 Millet/Sorghum

Dry after additional drying – grain 45

Green harvested – in the pods 14

Fresh/raw harvested – in pods 24

210/222/223/320 Beans/Field peas/Cow peas/Pigeon peas/Soya beans

Dry after additional drying – grain 45

Fresh/raw harvested – with shell 22 310 Groundnuts

Dry after additional drying – with shell 42

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Crop type Condition and State

Code Name Description Code

Dry after additional drying – grain 45

Dry at harvest – grain 35 330/340 Sunflower/Sim-sim

Dry after additional drying – grain 45

410/420/430/440/ 610/620/640/740/ 741/742

Cabbages/Tomatoes/Carrots/Onions/ Irish potatoes/Sweet potatoes/Yams/Bananas

Fresh/raw harvested – state not applicable 29

Fresh/raw harvested – state not applicable 29 630 Cassava

Dry after additional drying – state not applicable 49

520/530 Cotton/Tobacco Dry after additional drying – state not applicable 49

Fresh/raw harvested – in pods 24

Dry after additional drying – In pods or shell/husks 44

811/812/813 Coffee

Dry after additional drying – grain 45

Fresh/raw harvested – in pods or shell/husks 24 820 Cocoa

Dry after additional drying – grain 45

830 Tea Fresh/raw harvested – state not applicable 29

Similarly Unit of Quantity Codes were also made up specifically for Uganda Table 3.8.3 Quantity Codes Sr. No

Unit Code

1 Kilogram (kg) 01

2 Gram (g) 02

3 Litre (l) 03

4 Small cup with handle (Akendo) 04

5 Sack (120 kg) 09

6 Sack (100 kg) 10

7 Sack (80 kg) 11

8 Sack (50 kg) 12

9 Sack (unspecified) 13

10 Jerrican (20 l) 14

11 Jerrican (10 l) 15

12 Jerrican (5 l) 16

13 Jerrican (3 l) 17

14 Jerrican (2 l) 18

15 Jerrican (1 l) 19

16 Tin (20 l) 20

17 Tin (5 l) 21

18 Plastic basin (20 l) 22

19 Kimbo/Cowboy/Blueband Tin (2 kg) 29

20 Kimbo/Cowboy/Blueband Tin (1 kg) 30

21 Kimbo/Cowboy/Blueband Tin (0.5kg) 31

22 Cup/Mug (0.5 l) 32

23 Basket (20 kg) 37

24 Basket (10 kg) 38

25 Basket (5 kg) 39

26 Basket (2 kg) 40

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3.9. National classification/ nomenclatures and links to international classifications

(if existing) The Crop Codes given in Table 3.8.1 and used in UCA 2008 and UNHS are based on the International Classifications and are therefore comparable. However, Condition and State Codes were made up specifically for Uganda. In any case, these are only used in the data collection and analysis by UBOS and MAAIF. Similarly Unit of Quantity Codes were also made up specifically for Uganda. 3.10. Consumption, Trade and other relevant Indicators for the Agriculture sector

Data for consumption is from the UBOS National Household Surveys; Import/Export Statistics are compiled by TEDD of Bank of Uganda and UBOS from Uganda Revenue Authority (URA) data complimented by data from other agencies like the Ministry of Tourism, Trade and Industry; parastatals. While Consumer Price Indices (CPI) from UBOS includes food crops in the basket of goods. 3.11. Limitations of the available Food and Agriculture Statistics

It is clear from the inventory that there are many producers who are not coordinated; the existing data are not harmonized or consistent between sources and are scattered among institutions collecting them and finally , there are many data gaps. It could therefore be concluded that, currently there is very little basic current agricultural statistics being collected namely; crop area, yield, production, livestock inventory and products at the holding/farm level. The two main responsible institutions – MAAIF and UBOS – are only planning to put in place systems to collect these data. So what is available is data from the past surveys and censuses and other organizations. Further, PASS has been supported by a project funded by the Norwegian Government, but this comes to an end of PASS 2006/7. So future funding is not clear. Data from past surveys and censuses This includes – UNHS data from UBOS; NCAL 1990/91 and other Annual Agricultural Statistics Surveys from MAAIF. Data from various sources are not directly comparable for various reasons. For example, data from UNHS sometimes has different districts covered, different sample sizes, different seasons, etc. Therefore some adjustments are required before comparisons could be made. Unfortunately, the primary data from these surveys and censuses has, generally, not been well stored. Incomplete soft copies are sometimes only available with individual officers who sometimes have retired from service. This will make organizing it very difficult. However, further efforts should be made to re-compile the data. Other Organisations Other agencies including – NAADS, FEWSNET, FOODNET, UCDA, CDO, etc. collect specific or specialized data for their own needs. The NAADS reporting system still has

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problems as shown in section 3.4.1 above. This needs to be further streamlined. Data will also be needed to measure the ultimate impact which can only be done at the farm/holding level. NAADS proposes to carry out an Impact Study in two years time. UBOS/MAAIF should participate, or even better, the required data should be incorporated in AIS/PASS. UCDA and CDO do not have production data at the farm/holding level. Neither does FOODNET collect data at the farm-gate or marketed quantities. These are therefore also data gaps which could be included in AIS/PASS. 3.12. Summary of Chapter 3

As far as data quality is concerned, a discussion of the quality of the NCAL 1990/91 is attached as Annex 3.1 of the consultants report “A Data Collection Plan for Agricultural Statistics in Uganda” submitted early in 2007. The UNHS data is only available at national and regional level. Often the CVs for the less frequently produced commodities are very high at the regional level. The price data from FOODNET is generally good, except that it is collected from quotes by the respective players in the market, rather than carrying out actual purchases A Special Report by FAO/GIEWS Review of Crop and Food Situation in Uganda of 27 September 2006 made the following conclusions: Agricultural planning and programming are seriously constrained by lack of reliable agricultural statistics. Available agricultural statistics are of poor quality, and some can be misleading. There is an urgent need for a periodic and systematic agricultural data generating mechanism, including the carrying out of the agricultural census, that has long been in planning.

Available agricultural statistics are of poor quality, some can be misleading; and there are serious gaps as well. The last published comprehensive agricultural census carried out in Uganda was in 1965. Another census of agriculture was carried out in 1990/91 and there were two follow-up annual sample surveys in 1991/92 and 19992/93 agricultural years. Unfortunately, results from the latest census and the subsequent surveys were contentious and never fully used. Further, the Government could not sustain the survey system.

The Integrated Framework for Agricultural Statistics in Uganda in March 2000, concluded that the system of agricultural statistics was, “fragile, vulnerable and unsustainable”, and unable to meet the of data users. For instance, there is a lack of benchmark data on the agricultural sector. MAAIF has not been able to conduct Annual Agriculture Surveys since mid 1970s. This means in essence, that benchmark and structural-type of agricultural data in Uganda are substantially out of date. This has led to lack of synergy and cost effectiveness in addition to the lack of mechanisms for promoting ‘best practices’ in agricultural data production.

Indeed, a number of features of the system bring into question the reliability of annual production data for all but the “traditional” export crops. Data sets on staple crops such as

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maize show that the estimates of production are made at the national level and then the same growth rate is applied to each district. Consolidated data on agricultural practices are not available at any level. For livestock, the situation is no better.

Given the importance of the agricultural sector, lack of a reliable regular data collection system is of serious concern. There is an urgent need for implementing the several recommendations put forward by recent studies for generation of data concerning various aspects of agriculture.

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4. Overview of User Needs for Food and Agriculture Statistics Uganda

The importance of agriculture in the Ugandan economy is widely accepted. The sector as a whole accounts for as much as 21 per cent of Gross Domestic Product and for more than 90 percent of export revenue. In addition, the sector provides for about 80 percent of total employment and is major source of livelihoods for more than 70 percent of the population. At the same time, poverty in Uganda is very largely a rural phenomenon and most of the poor rely directly on agriculture for much of their income. It is clear that sustained economic growth and poverty reduction can only happen if there are both, growth in total agricultural output and substantial increases in agricultural productivity. 4.1. The Demand for Agricultural Statistics

While challenges for data supply have been well articulated and strategies for dealing with them reasonably developed, the data demand situation is not adequately understood. It is not only important to clearly identify the needs for data in the existing development frameworks, but also necessary to recognise that new initiatives will require additional data. The issues of adequacy and timeliness of data must be addressed to ensure effective formulation, monitoring and evaluation of policies and development outcomes.

The demand for agricultural statistics derives from a number of sources and processes and it is important that the agricultural Sector Strategic Plan Statistics (SSPS) not only addresses current needs, but also provides sufficient flexibility to address future needs, which are not yet identified. Key requirements for agricultural statistics include the following;

(i) To monitor progress with high level national strategies, especially with the Poverty Eradication Action Plan (PEAP). Agricultural indicators to monitor targets identified under Pillar two of the PEAP include: the growth rates of agriculture value added; the proportion of total agricultural output that is marketed; the proportion of total value added of agriculture that is exported, the proportion of households with land titles of agricultural production; and the proportion of household with general land titles;

(ii) To monitor indicators and progress with sectoral strategies, especially the recent Rural Development Initiative;

(iii) To report on progress towards international agreements and goals that Uganda has signed up to, especially the Millennium Development Goals (MDGs);

(iv) To support the development of appropriate agricultural policies to promote growth , job creation and poverty reduction;

(v) To support the day-to-day implementation of agricultural policies, programs and projects;

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(vi) To provide information to farmers and other participants in different agricultural related markets, to support effective investment decisions;

(vii) To monitor food security and to provide the information to support interventions where required;

(viii) To provide information generally to allow the public at large and other organizations to participate more effectively in the development debate.

There have been several reviews of food and agricultural data needs, gaps and priorities in Uganda. These include:

(i) PhD Research by Muwanga-Zake 1983/87; (ii) Data Producers and Users Workshop Report (Crested Crane Hotel, Jinja)

2nd to 6th November, 1987; (iii) Workshop for Data Producers and Users 20th and 21st September, 1995; (iv) Data needs to monitor PMA/PEAP; (v) The Data Needs Assessment Study in August 1999; (vi) Various reviews for the PCA 2003 and PASS; (vii) MAAIF Retreat (5th-8th December, 2005); (viii) Framework for the development of Agricultural Statistics in Uganda.

Of course, the methods used to determine the data needs and priorities in all these reviews have not all been clear or rigorous, but they give some guidance. The studies are however, all in the past and going forward data needs will have to be identified for the monitoring and evaluation of the National Development Plan (NDP) which is under preparation and related agriculture plan. 4.2. Public Sector Decision Makers

Data is required by the following:

i) National Integrated Monitoring and Evaluation Strategy Secretariat, ii) Government Ministries, Departments and Agencies – MAAIF, MFPED,

BOU – especially Research Departments, PMA, NAADS, EPRC, and the NPD which is under preparation.

iii) Academic Institutions - Universities iv) Districts and lower administrative units/sub-counties v) Development partners and international agencies

The National Integrated Monitoring and Evaluation Strategy (NIMES) Secretariat is located in the Office of the Prime Minister (OPM) which is functionally responsible for coordination, monitoring and evaluation of GoU policies, programmes and projects. The NIMES is a framework for ensuring that the culture of evidence-based decision-making is entrenched in the public sector. It aims at harmonizing existing systems of data collection, reporting and review in order to encourage, facilitate and promulgate the use

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of Monitoring and Evaluation information in policy making and resource allocation at all levels of government in Uganda. Its key objectives are to:

• ensure that a sound evidence base is available to inform decision making in national policy frameworks such as the PEAP;

• enhance M&E capacity in Uganda;

• ensure that key stakeholders have a forum for articulating data and information needs;

• coordinate M&E initiatives in Uganda by providing mechanisms which align the existing M&E initiatives with identified data and information needs.

The public service reform programme created a number of Departments and Executive Agencies that operate more or less independently of their parent Ministries. These generate and use statistics in the process of undertaking their work. The major ones include agencies such as NARO, NAADS, NEMA, UCDA, NFA, etc. Other producers, suppliers and users of statistics in Uganda are varied according to their mandates and responsibilities. Government Ministries issue policies and regulations, set standards, inspect, supervise, monitor and evaluate performance, and provide technical support and advice to local governments to enable them to execute their mandate. Local Governments are a key source of statistics arising out of administrative action. For example, there are returns at sub-county and even district levels related to agriculture. Training and Research Institutions play a role in statistical capacity development through training, using statistics and by participating effectively in mining of statistics databases through policy related research and analysis. The Institute of Statistics and Applied Economics (ISAE) in Makerere University is the key training institute and both students and staff use a lot of data in learning and research. Similarly, the agricultural research institutes under NARO generate and use data in their activities. Development Partners (Donors) and international agencies, for their part, provide funding and technical assistance. They also use statistics to identify sectoral areas that need financial and technical support, and to monitor development results. 4.3. Private Sector Decision Makers

Data is required by the following:

i) Manufacturers, Traders, Farmers, Banking Institutions; ii) Media; iii) Individual Researchers and Development Practitioners.

The Private Sector on the other hand seeks for statistics to make sound investment decisions. The private sector also produces data and is an important source of statistical information especially from surveys of establishments and enterprises.

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The Media help in raising the profile of statistics by using data to support their reports and by publishing statistics regularly. In general, Civil Society in performing their functions, produce and use data and statistics to monitor programmes and for advocacy and awareness purposes, thus helping raising the profile of statistics in the country.

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5.0. Expectations from Country STAT and synergies with ongoing

Initiatives in Uganda. It is expected, that CountrySTAT will provide technical assistance to support collaborative efforts in the National Statistical System with special emphasis on Food and

Agricultural Statistics. There are three main areas of activity in regard to Data Management, where the basic objective is to make best use of the data that have already been collected. It is suggested that the first requirement is to undertake a formal inventory of the different data systems that are being collected and compiled. To ascertain, as far as possible their quality and the extent to which they can be used for different purposes. Further, to compile a detailed description of the methods and procedures used – what is often referred as metadata. This initial exercise was started as part of the preparation of the SPSS with the consultants report on “A Data Collection Plan for Agricultural Statistics in Uganda”, which was submitted early in 2007. It has now been largely covered under this consultancy. Once the inventory has been completed and data sources have been identified and documented, the next step should be to develop an integrated agricultural database. The need for an integrated database, that would provide access to data on different aspects of agricultural activity, has already been identified. The main aim is to create a single point of access to the data for users, both inside and outside government. The establishment of such a database requires careful design and implementation. Rather than having to design the structure from scratch, clearly Uganda will benefit from work already carried out by FAO under Country STAT. The advantages of using the FAO process include being able to use an existing structure that is consistent with both international statistics and neighboring countries. The software is supported by FAO, is available free of charge and it should be possible to access technical support and assistance as required. The third area of development will include data analysis and harmonization. This will need to be coordinated by UBOS, and should provide for a process of eventually designating specific indicators and statistics as official statistics. It is expected that MAAIF will also need some technical assistance to support both the development of the integrated database as the data analysis and harmonization work. Allowance to technical assistance for one or two years should be included in the SSPS. Unfortunately, there is currently very little current FAS being collected by the two main institutions – MAAIF and UBOS. Secondly, data from the various sources are not directly comparable. Therefore some adjustments will be required. Thirdly, the primary data from the past censuses and surveys is largely not readily available. All these greatly reduce the value of the database except for the future.

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6. Important Factors for the success of Country STAT project-

Uganda. Coordinated approach in the implementation of Country STAT between MAAIF, UBOS and other stakeholders in agricultural statistics. Development of Institutional Capacity

Discussion of the development of institutional capacity in the different agencies involved in the agricultural statistics system will depend on a number of things. Together with the progress in regard to other proposals this included the possibility of establishing a single cadre for professional statisticians working in the public service in Uganda. In particular is it recommended that plans for human resource development should include training for data producers at both the professional and sub-professional levels; further, training and support for the data users. For the latter it may be useful to distinguish between general training in statistical literacy for a large number of users and higher level technical training for specialized analysts and planners. In developing proposals for capacity building, it will also be important to ensure that the comparative advantage of different agencies is both, identified and utilized. It is expected, for example, that UBOS should continue to develop, manage and implement large-scale household and other surveys. It will not make sense for this capacity to be duplicated elsewhere. Funding for capacity building will be required for UBOS, MAAIF and the other agencies concerned with FAS. Secondly, it has been assumed that some capacity building will be available under the general UBOS and MAAIF. Thirdly, data entry and analysis will be done in UBOS for the first two years as capacity is built in MAAIF. The training and support for data users will be carried out during the sensitization and publication of reports for the various surveys and censuses.

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7. Expectations from the Consultative Meeting- Uganda

• Clear elaboration of the CountrySTAT program and steps of implementation;

• Shared experiences from other countries and regional blocs on the African continent;

• Agreed position on what form assistance can be provided to countries in the implementation of CountrySTAT.

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ANNEX: 3.1: INVENTORY OF AGRICULTURAL STATISTICS PRODUCED

Inventory of Stats. Produced Design/Methodology

-Admin. Records

-Surveys/Censuses

-Coverage

Frequency

of Up-Dating

Publications/

Report

E-Mail/Web-site

Remarks/ Level of Disagr

(Admin Level & Gender)

UBOS Uganda Bureau Of Statistics, P.O Box 7186, Tel: +256 41 706000,

Fax: +256 41 237553/230370 Kampala, Uganda Website: www.ubos.org. Email: ubos@ubos.org

Statistical Abstract

Annual National FAS:

-Procurements – coffee, tea & tobacco -Area & Prod. Food crops -Fish catch by water body -Livestock Nos:

-Most data imputed. -Coffee, cotton and tea compiled by the respective statutory bodies.

National aggregates only.

E-Mail: ubos@ubos.org Web-page: www.ubos.org

Tel: 256-414-706000;

Fax: 256-414-237553.

National & Regional

External Trade Statistics & Informal Cross

Border Trade (ICBT) – October 2003 to

June 2005 and 2006

Official and informal trade data The scope of the ICBT 2006 includes: - Composition, quantity and value of commodities traded - Transport means - Direction of trade Specific objectives were to: • determine the nature and composition of commodities transacted under informal trade • establish the direction of trade for informally traded goods (i.e. country of destination /origin); • estimate flows in terms of values and quantities; • provide a comparative analysis of recorded and unrecorded trade including net trade balances; • generate monthly and annual ICBT estimates for BOP and National Accounts Statistics compilation and; • establish the position of Uganda in terms of

Ext trade Stats covers all official exports & Imports ICBT covered selected weeks on 14 main customs stations that experience large informal trade flows

Official trade is monthly while ICBT data is semi-annual and data is given by border post

UBOS & BOU web-pages www.bou.or.ug Uganda Bureau of Statistics and Bank of Uganda (2005, 2006, 2007 and 2008) Informal Cross-border Trade Reports.

• In the East, Malaba, Busia, Lwakhakha and Suam River stations along the Kenyan border;

• In the West, Bunagana, Ishasha and Mpondwe along DRC border;

• Mirama Hills and Katuna along the Rwanda border.

• In the Northwest, Paidha/Padea, Vurra, and Odramachaku located along DRC border

• In the South, Mutukula along the Tanzania border and

• Oraba on the Sudan border

61

Inventory of Stats. Produced Design/Methodology

-Admin. Records

-Surveys/Censuses

-Coverage

Frequency

of Up-Dating

Publications/

Report

E-Mail/Web-site

Remarks/ Level of Disagr

(Admin Level & Gender)

comparative and competitive advantage under the informal trading arrangement.

ICBT 2007 & 2008

Scope and objectives as for earlier ICBT

Added six new border posts and three bus terminals

The six additions are: -Sono, Kenya border; Kikagati Tanzania border; Cyanika - Rwanda border. Ntoroko and Goli - DRC border Nimule/Bibia - Sudan border

SMS – 1994/5

-Socio-econ. Characteristics - Inputs/outputs of HH Enterprises -Community Stats. At RC1 - Agric. Diagnostic Survey

Sample Design: Same as FMS

except with modifications at

HH level to take care of

diagnostic survey.

Sample size: -4925 households.

Sampling frame -1991 Population and Housing Census

Entire country

Available in the

library/staff copies also

exist

Primary data- Agric. Data Not

available within UBOS/ National

& Regional

TMS – 1995/6

-Socio-econ. Characteristics - Inputs/outputs of HH Enterprises -Community Stats. At RC1 - Crop Survey as core module

Sample Design: stratified

multistage sampling. Each

district was a separate stratum

with further sub-stratification

as district town, other urban

areas and rural areas.

Sample sizes: 5,526 households

Sampling frame-1991 Population and Housing Census

Entire country

except parts of

Kitghum and Moyo

Available in the

library/staff copies also

exist

There is specific report

on agric. Stats.

Primary data-Available in

UBOS/ National

& Regional

UNHS 1999/2000

-Socio-econ. Characteristics - Inputs/outputs of HH Enterprises -Community Stats. At RC1 - Crop Survey as core module

A 2 stage sampling design with EAs being selected using the frame based on PPS.

Sample size: 10,700 households

Sampling frame: 1991 Pop. & Housing Census

Entire country Except Gulu Kitgum, Kasese, and Bundibugyo Districts due to insecurity

Available in soft copy in the NAS. This includes all the documentation viz (manuals, questionnaires etc)

Primary data is available in NAS, stored in MS-Access data bases./ National & Regional And some selected districts and gender

UNHS 2005/06

-Socio-econ. Characteristics - Inputs/outputs of HH Enterprises

A 2 stage sampling design with EAs being selected using the PHC 2002 Agric. Module frame

Mid-term report published in March, 2006

Primary data is available in NAS, stored in Stata 9 Data files/

National, Regional, rural urban

62

Inventory of Stats. Produced Design/Methodology

-Admin. Records

-Surveys/Censuses

-Coverage

Frequency

of Up-Dating

Publications/

Report

E-Mail/Web-site

Remarks/ Level of Disagr

(Admin Level & Gender)

-Community Stats. At RC1 - Crop Survey as core module

based on PPS. At second stage an exhaustive list of households was generated in each selected EA from which 10 HHs were drawn using SRS. For internally displaced persons, a three –stage sampling design was used. (IDP camps – blocks

within IDP-households within

blocks)

Sampling frame: 2002 PHC Sample Size: 753 EAs yielding approximately 7500 households

Entire country

residence and some selected

districts and gender

PHC Agric. Module 2002

Report gives -No: of crop-plots planted during the first agricultural season of 2002; -type of crop stand; -livestock and poultry Nos: (by local and exotic/improved breeds) and information about fish farming.

Census- Main objective was to build sampling frame for subsequent agric. surveys and censuses

Entire country

Sept. 2002 Decinial

Reports both in hard and Soft copy are available.

CDs, NAS/National

Regional, District Sub-county and gender

PCA – 2003

Aim was to test methodology and questionnaires

Survey- Two-stage stratified sampling design.

10 districts

Masaka, Wakiso Mbale, Iganga Nakapriprit Lira, Arua Kabarole, Kabale

Reports both in hard and Soft copy are available.

CDs, NAS/ Selected Districts but sample sizes considered too small to give estimates.

Pilot PASS-2004

Data includes;

(i) Crops � Crop area measured by GPS tool, � Crop production estimates by holders, � Prices and sales � Crop forecasts by holders (ii) Tree Crop Numbers and Produce (iii) Numbers and sales of Livestock and

Survey- 2 stage stratified sampling design.

5 districts Masaka Sembabule Kabarole, Mbale Arua, Annual (ideal)

Reports both in hard and Soft copy are available.

CDs, NAS/ Selected Districts

63

Inventory of Stats. Produced Design/Methodology

-Admin. Records

-Surveys/Censuses

-Coverage

Frequency

of Up-Dating

Publications/

Report

E-Mail/Web-site

Remarks/ Level of Disagr

(Admin Level & Gender)

Poultry (iv) Type and Number of beehives (v) Number of Fish by Species and Sales

Derived Products, Production and Sales (Milk, Eggs, Honey, Wax, Skins and Hides)

Quantity produced and sold and value

PASS 2005

Data collected: As for PASS 2004

Survey- 2 stage stratified sampling design.

10 districts of Kiboga, Kyenjojo, Pader, Moroto, Busia, Kaberamaido, Kamuli, Kabale, Bushenyi and Jinja

Annual (ideal)

No report yet

Being captured/ Selected Districts

PASS 2007/8

Data collected: As for PASS 2004

8 Districts of Kumi, Wakiso, Luwero, Kasese, Lira, Kisoro, Rukungiri and Tororo

No report yet Being captured/ Selected Districts

National Service Delivery Survey 2004 &

2008:

Data includes:

• HH involvement in agric. Activities

• Major crops grown

• Agric. Inputs – use, types, source, quality, access,, source of mkt info

• Ext services – demand, availability & utilization, source, channels of access, quality, trends, constraints

• Mkt Info on agric produce – source

• Credit facilities – access & challenges

Muli-stage stratified sampling – 1st stage – Eas and 2nd stage HHs

Whole country – surveys in 2000, 2004 & 2008

2008 Survey Report published in May 2009

National and estimates based on 17 groups of districts with similar characteristics

64

Inventory of Stats. Produced Design/Methodology

-Admin. Records

-Surveys/Censuses

-Coverage

Frequency

of Up-Dating

Publications/

Report

E-Mail/Web-site

Remarks/ Level of Disagr

(Admin Level & Gender)

MAAIF P.O Box 102,Tel: +256 41 320987/9, 320004. Fax: +256 41 321047, 321010 Entebbe, Uganda.

Website: http://www.agriculture.go.ug. Email: psmaaif@infocom.co.ug

Statistics Section

-1965 Census

-1990/91 NCAL & Subsequent Annual

Surveys

Hard Copies of reports available. Soft copies of primary data not available

Livestock Census 2006/7 A range of livestock production characteristics Livestock, Poultry and other Domestic Animals included; Particulars of the Household head; Production systems, enterprises and land ownership; Goats population; Sheep population; Pigs population; Poultry/ birds population and eggs; Rabbits population; Horses, donkeys, and camels population; Farm infrastructure, equipment and implements; Apiary and Beehives; Labour employed by source and by sex; Cattle population, milk production and milk sales

The NLC was a large sample survey consisting of about 950,000 households

A Summary Report on the major livestock species is presented in A Summary Report of The National Livestock Census, 2008 of 27th May, 2009. Three reports are currently under preparation, namely: A full National Livestock Census Report-including a general report; an administrative report; and Thematic maps report. Will be available on MAAIF & UBOS web-pages

-National, regional, and district-level estimates --Estimates for the Karamoja zone (Abim, Kaabong, Kotido, Moroto, and Nakapiripirit districts) are also provided

65

Inventory of Stats. Produced Design/Methodology

-Admin. Records

-Surveys/Censuses

-Coverage

Frequency

of Up-Dating

Publications/

Report

E-Mail/Web-site

Remarks/ Level of Disagr

(Admin Level & Gender)

Department of Animal Production and

Marketing & Department of

Livestock Health and Entomology

Data exists on;

• Amount of livestock products produced and marketed.

• Livestock population and production systems.

• Production and consumption levels.

• Livestock sales.

• Slaughters

• Prices

• Exports and imports

• Reported outbreaks and control of diseases and affected species, etc.

Data collected mostly through administrative recording.

Annual National, Regional and District

Department of Fisheries Resources

(DFR):Data types available:

• Monitoring, control and surveillance data,

• Frame Survey Data,

• Fish Catch Assessment data,

• Industrial Processing,

• Fish Exports.

Forestry Statistics collected by the

National Forestry Authority (NFA) Biomass Monitoring Reports Mapping of Land cover/use Inventory & Surveys

Web site: http://www.nfa.org.ug

Water Resources :

Ministry of Water, Lands and Environment

1 .The Director Directorate of Water Development (DWD) P.O. Box 20026, Luzira Tel . 505945 Fax:

66

Inventory of Stats. Produced Design/Methodology

-Admin. Records

-Surveys/Censuses

-Coverage

Frequency

of Up-Dating

Publications/

Report

E-Mail/Web-site

Remarks/ Level of Disagr

(Admin Level & Gender)

505941 e-mail director@dwd.co.ug

2. The Commissioner, Water Resources Management epartment (WRMD) P.O. Box 19, Entebbe Plot 12 Mpigi Road, Entebbe Tel. 321914 or 321342 Fax 321368

e-mail wrmd@dwd.co.ug Web-page:

www.mwle.go.ug

Land Use/Cover

National Forestry Authority

• Biomass Survey up-dated annually

National & District data by Area (Sq.Km). Open Water Permanent Wetland Area Excl. Open water & Permanent wetland District Perimeter (Kms)

Head Office Plot 10/20, Spring

Road, P.O. Box 70863,

Kampala - Uganda

Tel +256-414-230365/6,

+256-414-360400, 264035/6

Fax +256-414-230369 Email:

info@nfa.org.ug Also in UBOS Statistical Abstract

The Department of Meteorology,

provides climate and weather services

• Current Seasonal Forecast

• The Commissioner Department of Meteorology 10th floor, Post Building Clement

67

Inventory of Stats. Produced Design/Methodology

-Admin. Records

-Surveys/Censuses

-Coverage

Frequency

of Up-Dating

Publications/

Report

E-Mail/Web-site

Remarks/ Level of Disagr

(Admin Level & Gender)

• Monthly Agro-meteorological Bulletins

• Seasonal Rainfall Forecasts

• Monthly Agro-meteorological Bulletins

Hill Rd P. O. Box. 7025 Kampala Uganda Tel: 256-414-251798 Fax: 256-414-251797 Email: com.met@meteo-uganda.net & met.info@meteo-uganda.net

NAADS

• The NAADS Secretariat mostly collects administrative data from interviews of the stakeholders and through the Farmers’ Fora at the various levels starting with the Farmers’ Groups at the village level.

• Baseline surveys

• Participatory M&E system

Web-page: www.naads.or.ug

National and covered Districts

and Sub-counties

NARO

The various National and Zonal Institutes have crop/livestock specific information. NARO’s main function is to carry out research and develop appropriate technologies aimed at increasing productivity.

There is a data management and statistical services project in NARO and its being strengthened.

Web-page: www.naro.go.ug

There is no central statistics data bank.

UCDA

• Monthly and then annual coffee procurements, processing and exports by destination, by grade, type

• Daily coffee prices – local and international by type, grade – indicative, lowest and highest and volumes sold.

• Average yield per tree and per unit area per coffee type.

• Total number of coffee tree in production by type (needs updating).

• Total number of trees planted under the coffee replanting programme 1996 to date)

Data administratively collected Web-page: www.ugandacoffee.org

• Daily Market Reports

• UCDA Monthly Reports • UCDA Annual Reports • Manuals on Coffee Production, Nursery Management and Post-harvest handling

• SMS Price

National and coffee zones or

districts

68

Inventory of Stats. Produced Design/Methodology

-Admin. Records

-Surveys/Censuses

-Coverage

Frequency

of Up-Dating

Publications/

Report

E-Mail/Web-site

Remarks/ Level of Disagr

(Admin Level & Gender)

• Average costs for establishment and maintenance of a clonal coffee garden (needs updating).

• Characterization of clonal coffee, (needs updating for new areas).

• Survival rates of new planted trees per district.

• Number of coffee villages established.

• Detailed time series on cost structure at the farms, primary processors and exporters for 1991/92 - 2004/05.

• Exporter procurement and exports.

• Average monthly exchange rate which assists UCDA in computation of monthly access collection and contribution of coffee to GDP.

• List of clonal nursery operators, their location and capacity of nurseries.

• Coffee seeds distributed by UCDA.

• Estimate of coffee trees affected by Coffee Wilt Disease by year by district.

• Average national estimate of coffee trees affected by Coffee Wilt Disease. This is done by carrying out surveillance studies. A study was carried out 1996 on Coffee Wilt Disease.

information facility

Cotton Development Organisation (CDO)

and the Uganda Ginners and Cotton

Exporters’ Association (UGCEA) Production (in bales) trends and earnings – Cotton lint production; earnings from exports;

earnings by farmers.PPPp P

Annual data E-mail: cdo@africaonline.co.ug Web-page: http:/cdouga.org Tel: 256-41-232968 / 259538 Fax: 256-41-232975

69

Inventory of Stats. Produced Design/Methodology

-Admin. Records

-Surveys/Censuses

-Coverage

Frequency

of Up-Dating

Publications/

Report

E-Mail/Web-site

Remarks/ Level of Disagr

(Admin Level & Gender)

Dairy Development Authority (DDA) Data available on: cattle population; dairy farming; milk supply by district; registered raw milk processors and dealers; milk coolers; identified sources and transport routes for milk; milk products, viz. pasteurized milk, UHT Milk, cheese, ice-cream, yoghurt and butter; milk pricing.

Imputations from MAAIF data but mostly from admin. records of purchases, processing and sales

E-Mail: dda@afsat.com Near Fairway Hotel P O Box 34006 Kampala Telephone: 343901/343883; Fax:250270

Uganda Dairy Stakeholders’ Association

E-Mail:

lol@africaonline.co.ug Plot 42 Windsor Crescent P.O. Box 29273, Kampala Tel: 4259134;

Uganda National Farmers

Federation (UNFFE): The market information provided by UNFFE is mainly on input and output prices. The information obtained is on types and sale prices of different inputs i.e. herbicides, pesticides, insecticides, fumigants, fungicides, fertilizers, seeds, sprayers and tools as well as their packaging; location of the company selling inputs giving their physical location, e-mail address (if any) and the contact person.

Officials of UNFFE visit major input importers like MAGRIC, Quality Chemicals, Farm Inputs Care Centre (FICA) Limited, Eastern Africa Seed Company, etc. Information on output prices is got from the web page of FOODNET for major crops by region.

Uganda Oilseeds Processors Association

(UOSPA)

E-Mail: oilseeds@starcom.co.ug

P. O. Box 2215 Kampala Telephone: 342504; Fax: 342504

FEWSNET

Alerts food status & classifies the respective countries into Emergencies, Warnings and Watch. Highest priority. Urgent action is required for the first two. While preparedness and monitoring is required for the last one. The population at risk and food aid

Uses mostly secondary data from other sources viz. MAAIF, UBOS, FOODNET; and special reports from the distressed areas.

Depends on type of emergency.

Web-page: www.fews.net

Depends on distressed area. In Uganda currently coverage is for Northern Uganda

70

Inventory of Stats. Produced Design/Methodology

-Admin. Records

-Surveys/Censuses

-Coverage

Frequency

of Up-Dating

Publications/

Report

E-Mail/Web-site

Remarks/ Level of Disagr

(Admin Level & Gender)

beneficiaries are also given.

FOODNET

• Weekly retail and wholesale prices for some food crops, beef and goat meat, chicken, fish and milk

• Market Studies – regional & country

• Agro-enterprises

The NEW Market Information Service,

Collect market information from 4 markets in each district.

-Radio Programmes -SMS Messages -Tel: 077373093; 077221162, 0414-223445 -Reports -E-Mail: mis@iitaesarc.co.ug -Web-pages: www.foodnet.cgiar.org www.tradenet.biz www.ugandamarkets.com

Districts of Kampala, Arua, Gulu, Hoima, Iganga, Jinja, Kabale, Kasese, Kibaale, Kiboga, Lira, Luwero, Masaka, Masindi, Mbale, Mbarara, Rakai, Soroti, Tororo

The Eastern Africa Grain Council (EAGC) EAGC manages market data and generates information exchange in the East African Region.

Information is disseminated through the web-site (www.ratin.net), SMS and printed copies. To get prices in US$ per Metric Tonne by SMS: type maize or beans or rice or millet or sorghum and send to 8000 for Kenya, 7197 for Uganda and 15711 for Tanzania. To get prices in local currency; type commodity currency unit and send to the numbers stated above.

Uganda Export Promotion Board (UEPB).

Deals with promotion and co-ordination of all export related activities that lead to export growth

Sources of Data UEPB gets its data from the following sources

The UEPB has a Resource Centre which is open to the general public.

71

Inventory of Stats. Produced Design/Methodology

-Admin. Records

-Surveys/Censuses

-Coverage

Frequency

of Up-Dating

Publications/

Report

E-Mail/Web-site

Remarks/ Level of Disagr

(Admin Level & Gender)

Trade Information Generation and

Dissemination System Produce and disseminate through the computer-based MIS, market information on:-

i. Highlights of international market prices for a few selected exports of Uganda. Other comprehensive price information can be found in useful listed web-sites that the UEPB staff review.

ii. Tariffs for target markets by product/sector

iii. Periodic price information and trend analysis by product/sector

iv. Import procedures and documentation requirements by target markets

v. Standards and quality requirement by countries and by product

vi. Details of duty preferences and exemptions given to Ugandan exports by target countries

vii. Details of Uganda’s exports to target countries by product, volume, value and percentage contributions.

viii. List of importers by target markets and by product/sector

ix. Exporters Directory for Agriculture, Handicraft and Manufacturing Sectors. Agriculture includes: Honey and Bee-wax; Cereals/Pulses/Oil Seeds and essential oils; Coffee; tea; tobacco; cotton; cut-flowers and plants; Fish and Fish Products; Fish; Vegetables; and Spices

x. Product Profiles (Costs of Production, Background Information and Marketing) for Okra; Avocado; Beans; Bird-eye Chillies; Vanilla; Cut-flowers; Pineapples;

i. Data on exports and imports are taken from UBOS

ii. Market information and opportunities are compiled by the Board staff through E-Mails from correspondents from outside the country and online publications and journals. UEPB also subscribes to some international agencies that supply the various data.

iii. The Importers and Exporters Directory is derived from registering interested importers and exporters

iv. The product profiles were compiled by consultants in

Web-page :http://ugandaexportsonline.com/drise

There are Trade

Information and

Publications from time

to time including:

- Cotton and Textiles Sector Profile - Processed Fruits Profile - Natural Ingredients Market Information Brief -Cereal and Grain Value Added Products Profile

72

Inventory of Stats. Produced Design/Methodology

-Admin. Records

-Surveys/Censuses

-Coverage

Frequency

of Up-Dating

Publications/

Report

E-Mail/Web-site

Remarks/ Level of Disagr

(Admin Level & Gender)

Banana; Ginger; Hot pepper; and Passion Friuts

2004

Uganda Flower Exporters Association Lists of members www.ufea.com Uganda Tea Association www.tea&coffee_net Ministry of Trade & Industry

The key functions of the Ministry include; collecting, processing, analyzing and disseminating national and international information on the respective sectors. The functions of the trade department of the ministry includes among others;

i.) Generating and disseminating critical market information to the country’s business community.

ii.) Sensitizing the business community on the availability of trade opportunities, export procedures and market requirements.

www.mttitourism.co www.mtti.go.ug

73

ANNEX 3.2. METADATA DICTIONARY- CROP PROTECTION Data Type/

Indicator

Definitions

and

Standard

classifications

Scope/

coverage of

data

Sources of

Data

Compilation

practices

Method of

computation

Accessibility

&

availability of

data

Accounting

conventions

Comments

&

Limitations

Agricultural Chemicals

Registered agricultural chemical imports

Pesticides, herbicides & fertilizers (2002-07) in Litres/Kg. Regulatory bodies & NEMA targeted

Applications for imports of agricultural chemical products & fertilizers; Activity reports

Import permits used in trade

Summation of monthly imports for the year

Tabular and graphical format presentation; graphical format dissemination of information

• Monthly generation of data

• Ugx10M budgetary estimate

Limited logistical support

Surveillance records

Surveillance of pest & disease incidences

Surveillance counts for crop pests & diseases. Decision makers in MAAIF targeted

Activity reports from departmental & district agricultural staff.

Met requests for surveillance from the respective districts

Summation of surveillances done by agricultural staff

Tabular format presentation: horizontal bar dissemination format

• Quarterly generation of data

• Ugx 30M budgetary estimate

Limited logistical support

Agricultural Seed Production

Area (Ha) of seed inspected & certified

Area (Ha) of seed inspected & certified from 2006-08. Hectares & MT esp. for anticipated production. Decision makers in MAAIF agreed

Private commercial seed producers; Activity report

Inspection of seed production fields

Summation of the area (Ha) of seed planted, approved & rejected under the various crops by variety for each season.

Tabular format presentation: Tabular dissemination format

• Annual generation of data

• Ugsh 30M budgetary estimate

Limited logistical support; Req’t of comprehensive descriptors to ease description

Crop products exports

Volumes of agricultural crop products exported through

Crop produce including coffee, flowers, cocoa,

Produce exporters; Activity reports

Inspections of agricultural in stores and at exit points fro exports

Summation of the total export volumes by product.

Tabular and graphical presentation: graphical format dissemination

• Monthly generation of data

• Ugx25M budgetary

Limited logistical support

74

Data Type/

Indicator

Definitions

and

Standard

classifications

Scope/

coverage of

data

Sources of

Data

Compilation

practices

Method of

computation

Accessibility

&

availability of

data

Accounting

conventions

Comments

&

Limitations

MAAIF assorted fruits & vegetables (2002-08); in Kgs, volume of cut stems &/or boxes; Policy makers in Parliament, MFPED & decision makers in MAAIF.

estimate

Source: MAAIF

75

ANNEX 3.3. METADATA DICTIONARY- ANIMAL PRODUCTION AND MARKETING Data Type/

Indicator

Definitions and

Standard

classifications

Scope/

coverage

of data

Sources of

Data

Compilation

practices

Method of

computation

Accessibility

&

availability of

data

Accounting

conventions

Comments &

Limitations

Livestock numbers

Cattle, goats, sheep, pigs and chicken

Districts Monthly, quarterly and annual reports

Vaccination registers and survey reports

Summation of numbers registered from the various sub-countries. Estimations and projections from survey reports

Reports None Limited logistical support

Animal production levels

Milk & Milk products (Kgs/ Lts), Meat (Kg/ tones), Hides (Kgs) Skin (numbers) Eggs (numbers)

Districts, regions and National

Monthly, quarterly and annual reports

Survey reports Estimations and projections from survey reports

Reports None Limited logistical support Availability of appropriate survey tools

Animal products for export

Milk & Milk products (Kgs/ Lts), Meat (Kg/ tones), Hides (Kgs) Skin (numbers)

National Private sector activity reports

Inspections of processing & marketing firms

Summations of export quantities for the year

Reports None Limited logistical support; Availability of appropriate survey tools

Market Prices

As many livestock products on the market as possible

District and regional markets

Market surveys by private sector

Survey reports Figures from various district markets

Reports, communication / media ( Tele-communications and magazines / news papers)

None Limited logistical support; Availability of appropriate survey tools

Source: MAAIF