Strategic Plan for Agricultural and Rural Statistics (SPARS)

STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 i Republic of Namibia Namibia Statistics Agency November 2024 STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 ii TABLE OF CONTENTS LIST OF TABLES iv LIST OF FIGURES iv FOREWORD v ACRONYMS vi ACKNOWLEDGEMENTS ix EXECUTIVE SUMMARY x CHAPTER 1 - BACKGROUND 1 1.1 Introduction 1 1.2 Basic information on the Global Strategy 1 1.3 Objectives and Rationale 2 1.4 SPARS Development Process 2 1.5 Policy context and demand for agricultural and rural statistics 4 1.5.1 Overview of the agricultural sector in Namibia 4 1.5.2 Agricultural Sector Statistics Plan (SSP-A) 4 1.5.3 National Development Plans 5 1.5.4 Sustainable Development Goals 5 1.6 Integration of Agriculture and Rural Statistics into the NSDS 8 1.7 Key stakeholders 8 1.8 Assessment of User Satisfaction and Needs 9 CHAPTER 2 - EVALUATION OF THE NATIONAL AGRICULTURAL STATISTICS SYSTEM (NASS) 10 2.1 Methodology Overview 10 2.2 Overview of the National Statistics System (NSS) 10 2.2.1 Administrative structure of the country 10 2.2.2 Legal and administrative framework for the collection of statistics 11 2.2.3 Structure of the National Statistics System 11 2.2.4 Strategic frameworks 12 2.2.5 Dialogue with data users 12 2.3 Core Data Availability 12 2.3.1 Economic domain 12 2.3.2 Social domain 16 2.3.3 Environmental domain 17 2.3.4 Geographical location domain 18 2.4 On-going Data Collection Activities 19 2.4.1 Population Census 21 2.4.2 Agriculture Census 21 2.4.3 National Accounts Statistics 21 2.4.4 Adoption of classifications 22 2.4.5 Price Indices 22 2.4.6 Food and Agricultural Surveys Conducted 22 2.4.7 Household Budget Survey 22 2.4.8 Availability of derived statistics and indicators in the country 23 2.4.9 Quality consciousness in statistics 23 STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 iii 2.4.10 Information technology 23 2.4.11 Transport Infrastructure 23 2.4.12 Financial resources 23 2.4.13 Human resources and training for statistical activities 23 2.4.14 International cooperation in agricultural statistics 24 2.5 Critical Constraints in the Agriculture Statistics System 24 2.6 Main Statistical Activities and Critical Constraints of the Sub-Sectors 26 2.6.1 Crop and livestock 26 2.6.2 Fisheries and aquaculture 26 2.6.3 Forestry, natural resources and environment 27 2.7 Agricultural Statistics Capacity Indicator 27 2.7.1 Overall ASCI 27 2.7.2 Prerequisite dimension 28 2.7.3 Input dimension 28 2.7.4 Throughput dimension 28 2.7.5 Output dimension 28 2.8 Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis 28 CHAPTER 3 - STRATEGIC PLANNING 30 3.1 Strategic Areas 30 3.2 Strategic Direction 31 3.2.1 Vision statement 31 3.2.2 Mission statement 31 3.2.2 Core values 31 3.3 Strategic Objectives, Outputs, and Activities 31 3.4 Implementation 36 3.4.1 Implementation arrangements 36 3.4.2 Action plan 37 3.4.3 Monitoring and Evaluation Plan 37 3.4.4 Financing 38 REFERENCES 39 ANNEXURES 40 ANNEX I - SWOT ANALYSIS 40 ANNEX II - ACTION PLAN 42 ANNEX III - SPARS LOG FRAMEWORK 43 ANNEX IV - SPARS BUDGET 48 STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 iv Table 1: Sustainable Development Goals relevant to agriculture sector 7 Table 2: Availability, sources, responsible institution, and quality/reliability of minimum core data under the economic domain 13 Table 3: Minimum core data availability, source, responsible institutions, and quality/reliability under the economic statistical domain 13 Table 4: Availability, source, responsible institution, and quality of minimum core data types under the social domain. 14 Table 5: Availability, source, responsible institution, and quality of minimum core data types under the environmental domain. 18 Table 6: Availability, source, responsible institution, and quality of minimum core data types under the environmental domain. 19 Table 7: Summary of official data collection activities done by the NSA. 20 Table 8: Ranking of critical constraints from the perspective of the NSA. 24 Table 9: Ranking of critical constraints from the perspective of the MFMR. 26 Table 10: Strategic objectives, outputs, and activities 32 Table 11: Estimated cost of SPARS 2024/25 - 2029/30 (excluding costs of sample surveys) 38 Figure 1: Organization of the SPARS process in Namibia 3 List of Tables List of Figures STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 v Foreword The Strategic Plan for Agricultural and Rural Statistics (SPARS) in Namibia will enhance agricultural and rural statistical coverage, meet regional and international demands, integrate the agricultural sector effectively into national strategic plans, and improve administrative data quality and accessibility. The decline in the quantity and quality of agricultural statistics in many countries across the world, resulted in the adoption of the Global Strategy (GS) for improving Agricultural and Rural Statistics by the United Nations in 2010. It is within this framework and African Action plan of Global Strategy (GS) for improving Agricultural and Rural Statistics that Namibia developed the SPARS. The growing need for reliable agricultural and rural statistics, driven by national policies and international agendas like the Sustainable Development Goals (SDGs) and CAADP, underscores the importance of a comprehensive SPARS. SPARS in Namibia sets out medium and long-term objectives and targets for the development of agricultural and rural statistics, covering all sub-sectors (‘Crop and Livestock’, ‘Environment, Forestry and natural resources’ and ‘Fisheries and Aquaculture’). The SPARS was developed following guidelines prepared by FAO, with some modifications that factor in the local situation in Namibia and the need to be integrated into the National Strategy for the Development of Statistics (NSDS). This strategic document has been designed in a participatory and inclusive manner. The preparations of this plan were led by a Design Team comprising key stakeholders in the NSS. Technical working groups were formed at the subsector level, comprising stakeholders in the agriculture sector who are involved as producers, users, or both. Each of the technical working groups contributed comprehensively to the in-depth assessment of agricultural statistics in their respective subsectors. On behalf of the Government of Republic of Namibia and the Namibia Statistics Agency (NSA), I acknowledge with thanks the Food and Agriculture Organization of the United Nations (FAO) for providing technical assistance and funding towards the development of SPARS for Namibia. In addition, the Ministry of Agriculture, Water and Land Reform (MAWLR), the Ministry of Environment, Forestry and Tourism (MEFT), and the Ministry of Fisheries and Marine Resources (MFMR) for their participation, guidance, and support throughout the development process. ALEX SHIMUAFENI STATISTICIAN-GENERAL & CEO STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 vi AAC Aquaculture Advisory Council AALS Affirmative Action Loan Scheme ACLRA Agricultural (Commercial) Land Reform Act ADAPT Advanced Data Planning Tool ADP Agricultural Development Programme AfDB African Development Bank AMTA Agro-Marketing and Trading Agency ASCIs Agricultural Statistics Capacity Indicators BCC Benguela Current Commission CAADP Comprehensive Africa Agriculture Development Programme CAoN Charcoal Association of Namibia CBD Convention on Biological Diversity CBNRM Community-based Natural Resource Management CCAMLR Commission for the Conservation of Antarctic Marine Living Resources CCU Climate Change Unit CLRA Communal Land Reform Act CPC Central Product Classification DEA Department of Environmental Affairs Development Programme Development Programme ECI Extreme Climate Index EEZ Exclusive Economic Zone EIA Environmental Impact Assessment EINRE Environmental Information and Natural Resource Economics EIS Environmental Information Service EMP Environmental Management Plan FAO Food and Agriculture Organization of the United Nations FIMS Fisheries Information Management Systems FOA Fisheries Observer Agency GDP Gross Domestic Product GIS Geographic Information System GIZ German Agency for International Cooperation GMO Genetically Modified Organisms GSARS Global Strategy for Improving Agricultural and Rural Statistics HACCIADEP Harambee Comprehensively Coordinated and Integrated Agricultural HPP Harambee Prosperity Plan HPP2 Harambee Prosperity Plan 2021-2025 HS Harmonized Commodity Description and Coding System ICCAT International Commission for the Conservation of Atlantic Tunas IdCA In-depth Capacity Assessment INC Initial National Communication ISIC International Standard Industrial Classification IUU Illegal, Unreported, and Unregulated Fishing KPIs Key Performance Indicators LLPBN Livestock and Livestock Products Board of Namibia LTO Lead Technical Officer MAWLR Ministry of Agriculture, Water and Land Reform MEA Multilateral Environmental Agreements MEFT Ministry of Environment, Forestry and Tourism MFMR Ministry of Fisheries and Marine Resources MIS Management Information Systems Acronyms STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 vii MRAC Marine Resources Advisory Council MSP Marine Spatial Planning MSP Market Share Promotion N-BiG Namibia Biomass Industry Group N-CLAS Namibia Communal Land Administration System NAB Namibia Agronomic Board NAMP-FW National Aquaculture Master Plan for Freshwater Aquaculture NAMSIP Namibia Agricultural Mechanisation and Seed Improvement Project NAP National Agricultural Policy NAPWU Namibia Public Workers Union NASP Namibia’s National Aquaculture Strategic Plan NASS National Agricultural Statistics System NBSAP2 Namibia Second National Biodiversity Strategy and Action Plan NCCC National Climate Change Committee NDP National Development Plan NDP5 Fifth National Development Plan NEPAD New Partnership for Africa’s Development NFCPT Namibia Fish Consumption Promotion Trust NGFFM National Guidelines on Fires and Fire Management NNF Namibia Nature Foundation NPC National Planning Commission NPOA-SSF Namibia’s National Plan of Action for Small Scale Fisheries NRP National Resettlement Programme NSA Namibia Statistics Agency NSDS National Strategy for the Development of Statistics NSFR National Strategic Food Reserve NSS National Statistics System OADC Open Access Data Centre PTO Permission to Occupy RFMO Regional Fisheries Management Organizations SADC Southern African Development Community SASSCAL Science Service Centre for Climate Change and Adaptive Land Management SDC Sector Development Committee SDGs Sustainable Development Goals SEA Strategic Environmental Impact Assessment SEAFO South East Atlantic Fisheries Organization SNC Second National Communication SPARS Strategic Plan for Agriculture and Rural Statistics SQ Structured Questionnaire SSCC Sector Statistics Coordinators Committee SSP Sector Statistics Plan SSP-A Sector Statistics Plan for Agriculture SWOT Strengths, Weaknesses, Opportunities, and Threats TCP Technical Cooperation Project TNC Third National Communication TWG Technical Working Group UNCCD United Nations Convention to Combat Desertification UNCLOS United Nation Convention on Law of the Sea UNCSD United Nations Commission on Sustainable Development UNECA United Nations Economic Commission for Africa UNFCCC United Nations Framework Convention on Climate Change UNVNR United Nations Voluntary National Review VMS Vessel Monitoring System WDI World Development Indicators WFP World Food Programme STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 viii STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 ix The development of the Strategic Plan for Agricultural and Rural Statistics (SPARS) in Namibia has been a collaborative effort involving various stakeholders and partners. We extend our sincere appreciation to all those who have contributed to the creation of this vital national document. Firstly, we would like to thank the Namibia Statistics Agency (NSA), the Ministry of Agriculture, Water and Land Reform (MAWLR), the Ministry of Environment, Forestry and Tourism (MEFT), as well as the Ministry of Fisheries and Marine Resources (MFMR) for their leadership, guidance, and support throughout the development process. Their commitment to strengthening the statistical infrastructure and promoting evidence-based decision-making in the agricultural and rural sectors has been instrumental in shaping SPARS. We acknowledge the valuable technical expertise and assistance provided by the Food and Agriculture Organization (FAO). Their contributions in aligning SPARS with international standards and best practices have enhanced the quality and relevance of the plan. We also express our gratitude to the various ministries, government agencies, research institutions, civil society organizations, and private sector entities that actively participated in consultations, workshops, and reviews to ensure the comprehensiveness and inclusivity of SPARS. Furthermore, we appreciate the support and collaboration of our international partners and development agencies, who have contributed resources, knowledge, and experience to strengthen agricultural statistics and promote sustainable development in Namibia. Finally, we recognize the dedication and hard work of the project team, consultants, experts, and all individuals involved in the development and validation of SPARS. Your commitment to excellence and innovation has resulted in a robust and strategic framework that will guide our efforts in improving agricultural and rural statistics for the benefit of Namibia’s development. Thank you to everyone involved for your valuable contributions to SPARS. ACKNOWLEDGEMENTS STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 x The Strategic Plan for Agricultural and Rural Statistics (SPARS) in Namibia is a comprehensive initiative aligned with the Global Strategy (GS) for improving agricultural and rural statistics. Adopted in 2010, the GS aims to strengthen statistical capacity in developing countries and integrate agriculture into National Statistics Systems (NSS) for sustainable development. Africa has been proactive in implementing the GS through the Action Plan for Africa, with Namibia actively engaging in SPARS development. This collaboration involves key stakeholders like the Namibia Statistics Agency (NSA), the Ministry of Agriculture, Water, and Land Reform (MAWLR), the Ministry of Environment, Forestry and Tourism (MEFT) as well as the Ministry of Fisheries and Marine Resources (MFMR), supported by FAO technical assistance. The objectives of SPARS align with Namibia’s National Development Plans, including NDP5 and the Harambee Prosperity Plan II, focusing on economic growth, social transformation, and sustainability. SPARS addresses the growing demand for reliable agricultural statistics driven by national policies and international agendas like the Sustainable Development Goals (SDGs) and the Comprehensive Africa Agriculture Development Programme (CAADP). Integration with the Agriculture Sector Statistics Plan (SSP-A) ensures synergy and efficiency, leveraging ongoing initiatives for better statistical outcomes. The policy context emphasizes the importance of agricultural statistics in decision-making for food security, climate action, and sustainable development, as outlined in the SDGs. The development process of SPARS in Namibia follows FAO guidelines, emphasizing phases such as launching, assessment, consultation, and planning. Key stakeholders from various sectors are involved, ensuring a bottom up approach and effective coordination within the NSS. Despite challenges like limited dialogue platforms, SPARS aims to enhance statistical coverage, meet international standards, and improve data utilization for evidence-based policy and practice. The integration of SSP-A and alignment with national development plans provide a robust framework for SPARS implementation, contributing to Namibia’s agricultural and rural development objectives. Chapter 2 presents the results of the assessment phase of the SPARS development, in which the current agricultural and rural statistics system is evaluated, data gaps and weaknesses are identified, and the country’s capacity to improve agricultural and rural statistics is examined. This provides the basis for determining the necessary actions to improve statistics and how the SPARS should be designed to achieve this goal. Much of the material in this chapter is taken from the IdCA report. The Global Strategy for Agricultural and Rural Statistics (GSARS) aims to enhance countries’ capacities in developing sustainable agricultural statistics systems integrated within the NSS. This involves using international standards and methods to produce essential core data. Central to this goal is the In-depth Capacity Assessment (IdCA), which evaluates various aspects such as the country’s agricultural and rural statistics status, agrarian structure, development priorities, institutional processes, stakeholders’ perspectives, strengths, and weaknesses. The IdCA employs a Standardized Questionnaire for Capacity Assessment to comprehensively assess these elements. The IdCA report serves as a reference and guiding document for developing the Strategic Plan for Agricultural and Rural Statistics (SPARS). The outcomes of the IdCA inform the design of SPARS, which is a dynamic document addressing resource needs, support requirements, and sustainable improvements in the agricultural statistical system. The IdCA report highlights country-specific gaps in the agricultural statistical system, identifies resource EXECUTIVE SUMMARY STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 xi needs for technical assistance, training, and research support. Thus, SPARS builds upon the foundation laid by the IdCA report, aiming to meet the ambitions outlined in the Global Strategy for Agricultural and Rural Statistics. A three-day consultative workshop was conducted with key stakeholders to envision and map the development of agricultural and rural statistics in Namibia for the next five years (2024/25-2029/30). The primary objective was to create a strategic plan that enhances the production, processing, and dissemination of quality agricultural and rural statistics, aligning with user needs and supporting evidence-based decision-making and policy planning. The core components of the Strategic Plan outlined in chapter 3 include strategic issues, strategic direction, strategic objectives, outputs, and activities, implementation, and budget. The strategic issues were derived from the evaluation of the National Statistics System (NSS) and National Agricultural Statistics System (NASS) and identified as crucial for strategic planning. These issues encompassed areas such as standards, financial resources, capacity building, collaboration, scope expansion, disaggregation of statistics, and awareness. To address these strategic areas effectively, the Strategic Plan delineates a strategic direction comprising a Vision, Mission, Core Values, strategic objectives, outputs, and activities as follows: Vision statement A well-resourced and coordinated National Agricultural Statistics System that supports evidence-based planning, that is responsive to user needs. Mission statement To implement a sustainable National Agricultural Statistics System (NASS) that provides comprehensive data and statistics using innovative and harmonized methods for the collection, processing, and dissemination of statistics. Core values The core values for Namibian SPARS, were adopted from the NSDS: • Accuracy: Endeavour to produce statistics with a high degree of precision • Accountability: Take absolute responsibility in their statistical productions and stakeholders’ engagement. • Timeliness: Strive to produce and disseminate statistics in accordance with their Advanced Release Calendar (ARC). • Transparency: Proactively make available methods and standards used in data production and dissemination processes. STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 xii The strategic goals, outputs, and activities were formulated based on the identified strategic issues, vision, and mission. These include initiatives to address standards fragmentation, enhance financial resources, build capacity, improve collaboration and coordination, expand the scope and disaggregation of statistics, and raise awareness. A comprehensive strategy matrix outlines the strategic objectives, associated outputs, and activities, providing a roadmap for developing a robust and responsive National Agricultural Statistics System (NASS). The implementation phase of Namibia’s Strategic Plan for Agriculture and Rural Statistics (SPARS) is highlighted as a crucial stage where meticulous planning translates into tangible outcomes. The success of the strategic plan hinges on careful execution, resource allocation, and stakeholder commitment. Key elements include: Implementation Arrangements: Led by the Namibia Statistics Agency (NSA) in collaboration with the Sector Statistics Coordinators Committee (SSCC), the implementation will be overseen by a SPARS Secretariat within NSA. This Secretariat will focus on coordination, execution, and reporting. Emphasis will be placed on stakeholder engagement and effective utilization of resources. Action Plan: Detailed in Annex II, the action plan outlines activities, responsible parties, timeframes, and inter relationships between activities. It includes a quarterly breakdown for the initial years and broader overviews for subsequent years, with progress subject to annual reporting and endorsement. Monitoring and Evaluation (M&E) Plan: Essential for success, the M&E system ensures the attainment of strategic goals and monitors inputs, activities, and outputs. It includes a logical framework with performance indicators, baseline, mid-line, and endline targets, means of verification, and core assumptions. Annual reporting, mid-term evaluation in 2026/27, and final evaluation in 2029/30 are integral to tracking progress, identifying issues, and recommending adjustments. Financing: The costs of implementing the SPARS for the period 2024/25 to 2028/29 are estimated at N$608,038,344.38, which is approximately U$34,692,513.87. This necessitates substantial mobilisation of resources to ensure effective implementation of the SPARS. Overall, the implementation phase is crucial for translating strategic plans into actionable outcomes, with a strong emphasis on coordination, stakeholder engagement, monitoring, evaluation, and adequate resource mobilization. STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 1 1.1 Introduction This Chapter presents basic information on the Global Strategy, the objectives and rationale for preparing the SPARS and the methodology used in its development. It also covers the adoption of agricultural and rural statistics concepts from the Global Strategy; the policy context and demand for agricultural data, and the integration of SPARS into the National Strategy for Development of Statistics (NSDS). Additionally, the chapter identifies key stakeholders from all subsectors of agriculture who participated in the preparation of SPARS. 1.2 Basic information on the Global Strategy Due to the decline in the quantity and quality of agricultural statistics in many countries across the world, the Global Strategy (GS) for improving Agricultural and Rural Statistics was adopted in 2010 at the meeting of the United Nations Statistical Commission in New York. The GS provides a framework for enhancing agricultural statistics to enable countries to meet emerging data needs for policy making, food security, research, etc. The strategy aims to: (i) strengthen the statistical capacity of developing countries to produce reliable statistics on food security, sustainable agriculture, and rural development; and (ii) provide a long-term vision for the development of agricultural statistical systems in these countries. The GS is centred on three pillars: I. The production of a minimum set of data to meet the current and future needs, including those of policy makers and other users. II. Proper integration of agriculture into the National Statistics System (NSS). III. Fostering sustainability of agriculture in the NSS through governance of the statistical system and the strengthening of the statistical capacity building of countries. Scope of Implementation Africa has taken the lead in implementing the Global Strategy (GS) by creating the Action Plan for Africa. This plan strategically allocates responsibilities among key institutions: • The African Development Bank (AfDB) is tasked with providing technical assistance and governance support to African countries. • The United Nations Economic Commission for Africa (UNECA) is responsible for training initiatives. • The Food and Agriculture Organization of the United Nations (FAO) is designated to conduct research. This collaborative effort aims to leverage the strengths of each institution for the effective advancement of agricultural and rural development across the continent. To actualize the Action Plan for Africa, participating countries are urged to formulate a Strategic Plan for Agricultural and Rural Statistics (SPARS), integrating it into their National Strategy for the Development of Statistics (NSDS). This SPARS acts as a comprehensive blueprint for enhancing agricultural statistics over the long term. In response to this initiative, Namibia has proactively addressed deficiencies in its agricultural statistical system by initiating the development of its SPARS. Consequently, the Namibia Statistics Agency (NSA) and the Ministry of Agriculture, Water, and Land Reform (MAWLR) have collaborated to seek technical support from FAO for the implementation of SPARS in Namibia. This plan covers three subsectors of agriculture as follows: CHAPTER 1 - BACKGROUND STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 2 • Crop and Livestock • Environment, Forestry and Natural Resources (areas related to agriculture) • Fisheries and Aquaculture 1.3 Objectives and Rationale The agricultural sector plays a pivotal role in Namibia, directly or indirectly supporting 70 percent of the population. Challenges within this sector have been addressed in national development plans like the Fifth National Development Plan (NDP5) and the Harambee Prosperity Plan II, focusing on economic progression, social transformation, environmental sustainability, and good governance. The Namibia Statistics Agency (NSA) has developed a Strategic Plan aligned with NDP5 and is finalizing the Agriculture Sector Statistics Plan (SSP) and the National Strategy for the Development of Statistics (NSDS) for 2022/23-2026/27. The growing need for reliable agricultural and rural statistics, driven by national policies and international agendas like the Sustainable Development Goals (SDGs) and the Comprehensive Africa Agriculture Development Programme (CAADP), underscores the importance of a comprehensive strategic plan for agricultural and rural statistics (SPARS). The integration of the SSP into SPARS is crucial to avoid duplication and ensure resource efficiency. This integration aligns with efforts to harmonize and consolidate agricultural statistics nationally and respond effectively to regional and international statistical requirements. The development of SPARS is part of a broader global strategy to improve Agricultural and Rural Statistics, with similar plans implemented in Africa and Asia Pacific over the past five years. The planned National Strategy for the Statistical Development of Statistics Strategy (NSDS) aims to integrate statistical activities efficiently within the National Statistics System (NSS), emphasizing the role of agricultural statistics in decision-making for food, agriculture, and rural development. The development of SPARS in Namibia is expected to enhance agricultural and rural statistical coverage, meet regional and international demands, integrate the agricultural sector effectively into national strategic plans, and improve administrative data quality and accessibility. Additionally, the collaboration with organizations like the Food and Agriculture Organization (FAO) enables the adoption of innovative tools like ADAPT, contributing to enhanced data planning and management. Agriculture statistics in this context encompass a broad spectrum, including crop, livestock, forestry, fishery, and aquaculture statistics. This highlights the comprehensive nature of SPARS in addressing data needs across various agricultural domains. 1.4 SPARS Development Process The SPARS development in Namibia followed the guidelines prepared by FAO, with some modifications to account for the local situation in Namibia and the need to harmonize with other related processes, such as the NSDS. As the SPARS guidelines highlight, the strategic plan followed the following phases: Launching: This phase covered the design phase steps: Acknowledgement, understanding and preparing, overall management and political commitment. The launching phase aimed to prepare the draft roadmap. It had the following main objectives: (1) Drafting of the roadmap. (2) Establishment of teams and subcommittees: In Namibia, SPARS will be under the Namibia Statistics Agency (NSA). The Ministry of Agriculture, Water and Land Reform (MAWLR), the Ministry of Environment, Forestry and Tourism (MEFT) and the Ministry of Fisheries and Marine Resources (MFMR) will be closely involved. The NSA as lead on SPARS, will enable synergies between the agricultural and the statistics strategies to be STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 3 realized and coordination strengthened. The SPARS process proposes the establishment of decision-making committees in line with the NSDS, led by the Statistician General (SG) of the NSA, with heads of ministries forming part of this executive committee known as the Statistics Development Committee (SDC). A second level of technical experts who will report to the SDC will include specialists from subsectors, MAWLR, MEFT and MFMR, known as the Sector Statistics Coordinators’ Committee (SSCC). There will also be a technical working group or national task team, comprising focal points people from the various agencies for the day to-day functions of the SPARS (the governance of SPARS is illustrated in Figure 1), and concluding the SPARS recruitment processes. (3) Holding information meetings. (4) Organizing an inception workshop and validating the roadmap. Statistics Development Committee (SDC) Sector Statistics Coordinators’ Committee (SSCC) National Technical Working Group/Design Team Sub sectoral – Technical Working Group (S-TWG) Crop & Livestock Environment, Forestry & Natural Resources Fisheries & Aquaculture Figure 1: Organization of the SPARS process in Namibia STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 4 Assessment: This phase focused on a detailed review of the current processes and products that make up agricultural and rural statistics in Namibia. The output of this phase includes a number of indicators of the current capacity of the NSS. The assessment phase included the following: (1) Preparation of evaluation documents based on subsector evaluations. (2) Holding a national workshop to present sector evaluation findings, and (3) Approval of the evaluation document. Consultation: This phase is characterized by an extensive stakeholder consultative process. Consultation forms the core role of the SPARS process. If the strategy is to be effective and properly implemented, it is important that it is widely supported and agreed to by stakeholders. Stakeholders included: the main producers of agricultural and rural statistics, users of statistics, including government offices, ministries and agencies, researchers, the private sector, development partners and farmers and farming communities. Planning: The main objective for the planning phase were: (1) Preparation of a synthesis of the strategic objectives and action plans based on the sub-sectors’ work. (2) Preparation of the SPARS document, integrating the results of the assessment phase, the vision, mission, activity timelines, costed action plans, and the system for monitoring and evaluation. (3) Development of a financial plan for SPARS implementation. (4) Presentation of the document at national level. (5) Government approval of the strategy. 1.5 Policy context and demand for agricultural and rural statistics 1.5.1 Overview of the agricultural sector in Namibia Agriculture is a crucial sector in Namibia, supporting about 70% of the population directly or indirectly, particularly in the subsistence sector. Over the last decade, it has been the largest employer in the country, contributing around 23% to employment, and its contribution to GDP has averaged about 7.9% (NSA, 2022; World Bank, 2022). The sector is characterized by two primary activities: commercial farming, which covers 44% of the land but accommodates only 10% of the population, and subsistence farming, which occupies 41% of the land and supports about 60% of the population (MAWLR, 2017; GIZ, 2022). Limited access to markets and quality inputs, such as seeds suitable for drought conditions, contributes to low productivity and income in the subsistence sector. Namibia’s agricultural sector encompasses livestock farming, crop farming, forestry, fishing, and fish processing. Livestock farming is predominant, contributing significantly to primary agricultural production, with cattle raising prominent in central and northern regions and sheep and goat farming in arid southern regions. The sector is well-developed, capital-intensive, and export-oriented, although subsistence livestock farming is prevalent in the northern communal lands. Poultry production, including ostrich farming, dairy farming, game farming, trophy hunting, and pig farming, are also vital sub-sectors contributing to the sector’s diversity and economic impact. Despite its arid climate, Namibia produces a variety of crops, including cereals like maize, wheat, and pearl millet, as well as fruits and horticulture products. Horticulture covers a range of vegetables produced under irrigation, while cereals are cultivated both under irrigation and rainfed and are staple crops. The fishing industry, considered separately but often discussed alongside agriculture, is a significant contributor to Namibia’s economy, particularly in terms of employment and export earnings. The marine fisheries industry is highly productive, with key species like, pilchard, anchovy, monk, tuna, hake, and horse mackerel supporting the country’s fishing sector’s growth and economic contributions. 1.5.2 Agricultural Sector Statistics Plan (SSP-A) The genesis of the Sector Statistics Plan for Agriculture (SSP-A) is the NSDS. The SSP-A is a four-year plan (2020 STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 5 2024) that is being implemented by the Ministry of Agriculture Water and Land Reform (MAWLR). Its Vision is to ensure that the MAWLR is a “reliable and accountable provider of agriculture statistics”. Furthermore, its Mission is to “produce, disseminate and promote the use of timely, quality agricultural statistics for evidence based planning and decision making.” The SSP-A achieves its Vision and Mission has four core strategic objectives: • Strengthen statistical capacity and structure. • Strengthen management and ensure sufficient funding for statistics. • Improve ICT infrastructure and integration. • Strengthen the production of quality statistics and improve awareness, dissemination, and use of statistics. As the implementation of SSP-A is ongoing, it is crucial that the development of Namibia SPARS incorporates it. Specifically, the initial step in designing SPARS for the crop and livestock sub-sector should be based on SSP-A. This approach ensures that the designed SPARS capitalizes on and extends the achievements of SSP-A. Additionally, it ensures that the SPARS design incorporates the experiences and lessons learned from the implementation of the SSP-A. 1.5.3 National Development Plans Namibia’s Vision 2030, established in 2004, outlines a future where the country is advanced, industrialized, and self-sufficient, with a focus on peace, prosperity, and political stability. The vision emphasizes sustainable development, people-centred growth, and collaboration as fundamental principles. This long-term blueprint guides Namibia’s developmental aspirations and plans, aiming to restore human dignity, maximize individual potential, and create a conducive environment for growth. The implementation of Vision 2030 is carried out through a series of National Development Plans (NDPs) and Harambee Prosperity Plans (HPPs). These plans, including NDP2, NDP3, NDP4, NDP5, and HPPII, serve as tools to address Namibia’s social and economic challenges. Agriculture plays a central role in these strategies, with NDP5 identifying it as a key driver for transitioning Namibia into a proactive, high-performing economy. HPPII specifically targets private strategic investments in agriculture, aiming to enhance productivity, food security, and job creation through partnerships and capital infusion. To support the implementation of NDPs, HPPs, and Vision 2030, various agriculture policies and strategies have been developed. These frameworks outline specific goals, strategies, programs, and projects for the agriculture sector, with performance indicators to track progress. These indicators, detailed in tables within the document, help monitor the impact of agricultural policies and strategies on achieving desired outcomes related to development plans and Vision 2030’s objectives. 1.5.4 Sustainable Development Goals The 2030 Agenda for Sustainable Development Goals (or SDGs) is one of the international planning frameworks that exerts the demand for agriculture statistics in Namibia. The Sustainable Development Goals (SDGs) underscore the importance of achieving sustainable agriculture and agri-food systems, food security and mitigation of deforestation. These aspirations are integral to 6 of the 17 SDGs established in transforming our world: 2030 Agenda for Sustainable Development, namely: SDG2, SDG5, SDG12, SGD13, SDG14 and SDG 15. These SDGs focus on ending hunger, poverty reduction, protection and restoration of water-related ecosystems, conservation of marine resources and combating climate change. Consequently, the production of agricultural-related statistics will be crucial for measuring the achievements of Agenda 2030 targets and indicators as presented in Table 1. STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 6 STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 7 8 Table 1: Sustainable Development Goals relevant to agriculture sector Goal Indicators SDG 2: End hunger, achieve food security and improve nutrition and promote sustainable agriculture. ✔ 2.1.2: Prevalence of moderate or severe food insecurity in the population. ✔ 2.3.1 The volume of production per labour unit by classes of farming/pastoral/forestry enterprise size. ✔ 2.3.2: The average income of small-scale food producers, by sex and indigenous status. ✔ 2.4.1: Proportion of agricultural area under productive and sustainable agricultural practices. ✔ 2.a.1: Agriculture Orientation Index for government expenditure. ✔ 2.c.1: Food price anomalies. SDG 5: Achieve gender equality and empower all women and girls ✔ 5.a.1: (a) Proportion of total agricultural population with ownership and secure rights over agricultural land, by sex; and (b) share of women among owners and rights-bearers of agricultural land, by type of tenure. SDG 12: Ensure sustainable consumption and production patterns ✔ 12.3.1 (a) Food loss index SDG 13: Climate Action – Take urgent action to combat climate change and its impacts. ✔ 13.2.1: The number of countries with nationally determined contributions, long-term strategies, national adaptation plans, strategies as reported in adaptation and national communication. SDG 14: Life below water - conserve and sustainably use oceans, seas, and marine resources for sustainable development. ✔ 14.4.1: The proportion of fish stocks within biologically sustainable levels. ✔ 14.6.1: Degree of implementation of international instruments aiming at combating illegal, unreported and unregulated fishing. ✔ 14.7.1: Sustainable fisheries as a percentage of GDP in small island developing states, least developed countries, and all countries. SDG 15: Life on Land Protect, restore, and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification and halt and reverse land degradation and halt biodiversity loss. ✔ 15.1.1: Forest area as a proportion of total land area. ✔ 15.1.2: The proportion of important sites for terrestrial and freshwater biodiversity covered by protected areas, by ecosystem type. ✔ 15.2.1: Progress towards sustainable forest management ✔ 15.3.1: The proportion of land degraded over a total land area. ✔ 15.4.1: Coverage by protected areas of important sites for mountain biodiversity. ✔ 15.6.1: The number of countries that have adopted legislative, administrative and policy frameworks to ensure fair and equitable sharing of benefits. ✔ 15.8.1: The proportion of countries adopting relevant national legislation and adequately resourcing the prevention or control of invasive alien species. ✔ 15.9.1: (a) The number of countries that have established national targets under or like Aichi Biodiversity Target 2 of the Strategic Plan for Table 1: Table 1: Sustainable Development Goals relevant to agriculture sector Goal Indicators STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 8 9 Goal Indicators Biodiversity 2011–2020 in their national biodiversity strategy and action plans and the progress reported towards these targets. (b) Integration of biodiversity into national accounting and reporting systems, defined as the implementation of the System of Environmental Economic Accounting. 1.6 Integration of Agriculture and Rural Statistics into the NSDS The development of SPARS in Namibia coincided with the development of its NSDS. SPARS in Namibia addresses gaps identified through the NSDS, aiming to integrate the agriculture sector more comprehensively. A notable sector not addressed by the NSDS is fisheries and aquaculture, which SPARS incorporates using a bottom-up approach. The NSDS is expected to provide the country with a strategy for developing statistical capacity across the entire NSS. It will offer a vision for where the NSS should be in five years and sets milestones for achieving this vision. The NSDS presents a comprehensive and unified framework for continually assessing evolving user needs and priorities for statistics and for building the capacity needed to meet these needs in a more coordinated, synergistic and efficient manner. Additionally, it will provide a framework for mobilizing, harnessing, and leveraging resources (both national and international) and a basis for effective and results-oriented strategic management of the NSS. As part of preparing the NSDS, NSA intends to revise its institutional framework and coordination function in statistical development by enhancing stakeholders' participation. In addition, Sectoral Statistics Committees were established. Also, for purposes of coordination with other producers and users in the agriculture sector, the NSA, in collaboration with agriculture sector line ministries, offices and agencies (OMAs), has established a working committee titled Sector Statistics Coordinators Committee (SSCC) and the more senior Sector Development Committee (SDC). 1.7 Key stakeholders Institutions that support Namibia’s NSS include the NSA and various Ministries, statutory boards, and institutions. The main institutions that support the NSS include: 1. Ministry of Agriculture, Water, and Land Reform (MAWLR) 2. Namibian Agronomic Board (NAB), for crop-related data and statistics Goal Indicators 1.6 Integration of Agriculture and Rural Statistics into the NSDS The development of SPARS in Namibia coincided with the development of its NSDS. SPARS in Namibia addresses gaps identified through the NSDS, aiming to integrate the agriculture sector more comprehensively. A notable sector not addressed by the NSDS is fisheries and aquaculture, which SPARS incorporates using a bottom-up approach. The NSDS is expected to provide the country with a strategy for developing statistical capacity across the entire NSS. It will offer a vision for where the NSS should be in five years and sets milestones for achieving this vision. The NSDS presents a comprehensive and unified framework for continually assessing evolving user needs and priorities for statistics and for building the capacity needed to meet these needs in a more coordinated, synergistic and efficient manner. Additionally, it will provide a framework for mobilizing, harnessing, and leveraging resources (both national and international) and a basis for effective and results-oriented strategic management of the NSS. As part of preparing the NSDS, NSA intends to revise its institutional framework and coordination function in statistical development by enhancing stakeholders’ participation. In addition, Sectoral Statistics Committees were established. Also, for purposes of coordination with other producers and users in the agriculture sector, the NSA, in collaboration with agriculture sector line ministries, offices and agencies (OMAs), has established a working committee titled Sector Statistics Coordinators Committee (SSCC) and the more senior Sector Development Committee (SDC). 1.7 Key stakeholders Institutions that support Namibia’s NSS include the NSA and various Ministries, statutory boards, and institutions. The main institutions that support the NSS include: 1. Ministry of Agriculture, Water, and Land Reform (MAWLR) 2. Namibian Agronomic Board (NAB), for crop-related data and statistics 3. Livestock and Livestock Products Board Namibia (LLPBN) and Veterinary Services, for livestock-related data and statistics 4. Argo-Marketing and Trade Agency (AMTA), for data related to the National Strategic Food Reserve (NSFR) as well as trade statistics 5. Ministry of Fisheries and Marine Resources (MFMR) 6. Confederation of Namibian Fishing Association 7. Namibia Fish Consumption Promotion Trust (NFCPT) 8. Fishery Observer Agency (FOA) 9. Institutions of higher learning 10. Ministry of Environment, Forestry and Tourism (MEFT) for forestry and agri-environmental data 11. Namibia Nature Foundation (NNF) 12. Charcoal Association of Namibia (CAoN) 13. Namibia Biomass industry Group (N-BiG) STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 9 14. Centre for Research, Information, Action in Africa Southern Africa - Development and Consulting (CRIAA SA-DC) 15. Namibia Meteorological Services weather and rain related data 16. The Environmental Investment Fund (EIF) 17. The Namibian Association of CBNRM Support Organisations (NACSO) 18. Namibia Public Workers Union (NAPWU) for labour statistics 19. Namibia Agriculture Union (NAU) 20. Namibia National Farmers’ Union 21. Namibia Emerging Commercial Farmers’ Union (NECFU) 1.8 Assessment of User Satisfaction and Needs The assessment findings reveal a significant lack of official and informal dialogue platforms in Namibia for communication between suppliers and users of agricultural statistics. This absence poses challenges across statistical production, dissemination, and utilization, as it hinders the relevance and responsiveness of statistical production to user needs. Without such forums, the NSS, represented by the NSA, may struggle to understand specific information requirements and priorities, leading to data that isn’t readily applicable to crucial agricultural sector issues. Additionally, the absence of dialogue platforms hampers the effectiveness and accessibility of statistical dissemination. Valuable data may remain within the NSS, failing to reach its intended recipients and undermining informed decision-making in areas like crop yields, market trends, and resource allocation. This lack of transparency limits the potential impact of data on agricultural development and decision-making processes. Moreover, the dearth of dialogue avenues constrains the utilization of statistics for evidence-based policy and practice. Without direct engagement with data users, it becomes challenging to evaluate how statistics are applied, identify application gaps, and rectify potential misuse or misinterpretation. Establishing formal and/or informal dialogue platforms between the NSA and data users is crucial to complete the feedback loop, ensure relevance and accessibility of agricultural statistics, promote collaboration, enhance dissemination methods, and ultimately improve the efficiency and responsiveness of the NSS in Namibia. STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 10 CHAPTER 2 - EVALUATION OF THE NATIONAL AGRICULTURAL STATISTICS SYSTEM (NASS) In Chapter 1, information on the launching phase of the SPARS in Namibia was presented. Agricultural sector development issues were discussed, emphasizing the need for agricultural and rural statistics to monitor progress in national development plans. The framework for the collection of statistics in Namibia and the integration of agricultural and rural statistics into the national statistics system was outlined. Key stakeholders were also identified. Chapter 2 presents the results of the assessing phase of the SPARS development. This phase involved evaluating the current agricultural and rural statistics system, identifying data gaps and weaknesses, and examining the country’s capacity to improve these statistics. This provides the basis for determining what action is needed to improve statistics and how the SPARS should be designed to achieve this end. Much of the material in this chapter is derived from the IdCA report. 2.1 Methodology Overview The Global Strategy for Agricultural and Rural Statistics (GSARS) aims to enhance countries’ capacities to develop sustainable agricultural statistics systems integrated within the National Statistics System (NSS). This involves employing international standards and methods to produce essential core data. The In-Depth Capacity Assessment (IdCA) is central to this goal, focusing on evaluating various aspects such as the country’s agricultural and rural statistics status, agrarian structure, development priorities, institutional processes, stakeholders’ perspectives, strengths, and weaknesses. The IdCA utilizes a Standardized Questionnaire for Capacity Assessment to assess these elements comprehensively. The IdCA report serves as a reference and guiding document for developing the Strategic Plan for Agricultural and Rural Statistics (SPARS). The outcomes of the IdCA inform the design of SPARS, which is a dynamic document addressing resource needs, support requirements, and sustainable improvements in the agricultural statistical system. The IdCA report highlights country-specific gaps in the agricultural statistical system, identifies resource needs for technical assistance, training, and research support. Thus, SPARS builds upon the foundation laid by the IdCA report, aiming to meet the ambitions outlined in the Global Strategy for Agricultural and Rural Statistics. 2.2 Overview of the National Statistics System (NSS) 2.2.1 Administrative structure of the country Administrative structures are fundamental in overseeing and coordinating diverse aspects of a country, including agriculture and rural statistics. Namibia’s democratic system operates across three tiers: national, regional, and local levels. At the national level, governance is executed by the executive, legislative, and judiciary branches, guiding overall agricultural and rural development strategies, setting national priorities, and distributing resources to regional administrations. Beneath the national sphere, Namibia’s 14 distinct regions function as semi-autonomous entities responsible for implementing central policies within their boundaries. Each region hosts a regional council elected by residents, overseeing services like agriculture and playing a crucial role in agricultural data collection and dissemination. Further decentralization occurs at the local level, where 121 constituencies form the smallest administrative units. Led by elected councillors, these constituencies serve as primary points of contact for rural communities. Their involvement in data collection, such as farmer interviews and surveys, contributes significantly to STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 11 capturing ground-level realities and enriching national agricultural statistics. This tiered administrative structure presents both opportunities and challenges for agricultural statistics production and dissemination. While decentralization allows for region-specific and community-driven data collection, potentially leading to more accurate information, it also brings the challenge of ensuring data quality consistency across regions. Effective dissemination of statistics down to the local level remains a crucial challenge, requiring bridging the communication gap between national data and local needs for effective agricultural development in Namibia. Namibia’s legal and administrative framework for statistics, anchored on the Statistics Act of 2011, establishes the Namibia Statistics Agency (NSA) as the central authority for official statistics. The NSA oversees data collection across ministries and agencies, ensures standardization and quality, and collaborates with specific ministries and government institutions for sector-specific data collection mandates. Despite efforts like the Data Collection Processing and Dissemination Policy and the Namibia Quality Assurance Framework for Statistics (NQAFS), challenges persist in standardizing data collection practices across key data producers, especially in the agriculture sector. This necessitates strong coordination between the NSA and other agencies for quality and accessible agricultural statistics. 2.2.2 Legal and administrative framework for the collection of statistics Namibia’s In-depth Capacity Assessment (IdCA) reveals that the country has a robust legal and administrative framework for statistics, primarily governed by the Statistics Act of 2011. This act established the Namibia Statistics Agency (NSA) as the central authority for official statistics, ensuring standardization and quality in data collection across ministries and agencies. Specific ministries and government institutions, such as MAWLR, MFMR, MEFT, Namibia Agronomic Board, and Livestock and Livestock Products Board, have internal mandates for data collection within their sectors. The Statistics Act of 2011 empowers the NSA to designate statistics as “official,” indicating adherence to rigorous quality standards. Despite the implementation of a Data Collection Processing and Dissemination Policy to guide responsible practices, standardization of data collection practices across key data producers, especially in the agriculture sector, remains a challenge. In response, the NSA is developing the Namibia Quality Assurance Framework for Statistics (NQAFS) to set benchmarks for data collection, processing, and analysis. Administratively, the Statistics Committee, delegated by the NSA Board, oversees statistics development in Namibia, covering various sub-sectors including crops, livestock, forestry, environment, aquaculture, fishery, water resources, and rural statistics. The key challenge lies in standardizing statistical practices across key data producers, a gap that the NQAFS aims to address, ensuring a seamless flow of quality data across the statistical system. 2.2.3 Structure of the National Statistics System The NSS in Namibia is decentralized by sector to ensure comprehensive and coordinated data collection and dissemination. At its core is the NSA, which is responsible for developing and implementing statistical standards and methodologies, collecting and compiling official statistics, and conducting data analysis and dissemination. Sector ministries such as the Ministry of Agriculture, Water and Land Reform (MAWLR) play a crucial role in gathering sector-specific data and collaborating with the NSA on larger surveys. Additionally, regional councils contribute local-level data, especially in agriculture, through farmer interviews, surveys, and engagement with extension services. Data users, including policymakers, researchers, development partners, and the public, are essential stakeholders in the NSS. The Statistics Act of 2011 mandates the NSA to coordinate the activities and needs of these stakeholders. However, effective communication and dissemination strategies remain a challenge, as there is no formal allocation of responsibility among different agencies producing statistics, and existing coordination mechanisms are weakly effective. Therefore, strong coordination and data management practices STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 12 between the NSA and complementing agencies are needed to ensure quality and accessible agricultural statistics for all stakeholders. Overall, Namibia’s NSS adopts a collaborative approach, leveraging the expertise of various entities to create a comprehensive and reliable statistical system for informed policy and development in the agricultural sector and beyond. This multi-layered structure presents both opportunities and challenges, highlighting the importance of effective coordination and data management practices to meet the needs of all stakeholders involved. 2.2.4 Strategic frameworks The NSA of Namibia oversees the Agricultural Statistics and related Cross-cutting Areas, operating under the legal framework established by the Statistics Act of 2011. This framework, coupled with the institutional mandates assigned to various line ministries and research organizations, guides the production of statistical data as part of their regular activities. The NSA was established by the Statistics Act with the responsibility to gather, compile, analyse, publish, and disseminate statistical information. As the custodian of official statistics, the NSA maintains a national socio-economic database. The Act also empowers the NSA to coordinate and supervise the NSS, which includes entities involved in producing, utilizing, and supplying statistical data. However, the current legal and institutional framework falls short of fully reflecting the agriculture sector’s role within the NSS. The current legal framework in Namibia does not comprehensively address the statistical needs of the agriculture sector. Recognizing this gap, Namibia developed the National Strategy for the Development of Statistics (NSDS) to enhance statistical capacity across various sectors. However, the NSDS did not adequately cover the Fisheries and Aquaculture sectors. Therefore, the Strategic Plan for Agricultural and Rural Statistics in Namibia (SPARS NAM) is developed to specifically address the statistical requirements of these sectors, ensuring a more holistic approach to agricultural statistical development in the country. 2.2.5 Dialogue with data users The assessment findings highlight the absence of official and informal dialogue platforms between suppliers and users of agricultural statistics in Namibia. This absence poses significant challenges across the entire statistical process, from production to utilization. Without these forums, the relevance and responsiveness of statistical production to user needs diminish, leading to potential gaps in addressing critical issues in the agricultural sector. The lack of consistent feedback and engagement with stakeholders like policymakers, farmers, and researchers also hinders the National Statistics System (NSS), particularly the Namibia Statistics Agency (NSA), in understanding specific information needs and priorities. This can result in data collection that may not be readily applicable or utilized to address crucial agricultural challenges. Furthermore, the absence of dialogue forums impacts the dissemination and accessibility of agricultural statistics. Valuable data might remain confined within the NSS, failing to reach its intended audience and impeding informed decision-making. This lack of transparency and accessibility not only limits the potential impact of the data on agricultural development but also hinders evidence-based policymaking. Establishing formal and/or informal dialogue platforms between the NSA and data users is crucial to address these challenges. These platforms can foster collaboration, identify data needs, improve dissemination strategies, and ultimately enhance the relevance, accessibility, and utilization of agricultural statistics for informed decision-making and effective policy formulation in Namibia. 2.3 Core Data Availability 2.3.1 Economic domain Namibia’s NSS provides a detailed overview of the availability, sources, and quality of minimum core data in the economic domain. Table 3 presents this information, including the responsible institutions and the reliability of the data. The data presented in Table 3, as well as summarized in Table 2, is extracted from Section STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 13 2.1 of Module I of the Standardized Questionnaire (SQ). Namibia’s NSS produces 55 out of the 63 required minimum core data types in the economic domain. However, there are 8 data types that are not produced, including water quality, forage quantity and value, aquatic seeds quantity and value, wholesale prices, agriculture input prices, and water pricing. Administrative records are the primary source of minimum core data, accounting for about 53.6%, followed by estimates/forecasts (25%), censuses (19.6%), and special surveys (1.8%). 17 core data, accounting for about 53.6%, followed by estimates/forecasts (25%), censuses (19.6%), and special surveys (1.8%). Table 2: Availability, sources, responsible institution, and quality/reliability of minimum core data under the economic domain Element Metric Count Percentage Availability Available 55 87% Not Available 8 13% Source of data Administrative records 30 54% Estimates/Forecasts 14 24% Censuses 11 20% Special surveys 1 2% Responsible institution Namibian Agronomic Board 5 9% Livestock and Livestock Products Board 3 5% Ministry of Agriculture, Water and Land Reform 6 11% Ministry of Environment, Forestry, and Tourism 6 11% Ministry of Fisheries and Marine Resources 2 4% Ministry of Finance and Public Enterprises 5 9% Namibia Revenue Agency 14 25% Namibia Statistics Agency 15 27% Quality/Reliability of data1 Workable 19 34% Acceptable 12 21% Highly Reliable 11 20% Reliable 14 25% 1Quality/Reliability is measured on an ordinal scale; thus: Highly Reliable > Reliable > Acceptable > Workable. The key producers of most minimum core data are the Namibia Statistics Agency (NSA) and NAMRA. Despite the wider coverage of minimum core data, the quality of most data in the Table 2: Availability, sources, responsible institution, and quality/reliability of minimum core data under the economic domain Element Metric Count Percentage STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 14 The key producers of most minimum core data are the Namibia Statistics Agency (NSA) and NAMRA. Despite the wider coverage of minimum core data, the quality of most data in the economic domain is classified as “workable,” indicating lower-end data quality due to varying methodologies and definitions used in data collection, particularly from administrative records. Table 3: Minimum core data availability, source, responsible institutions, and quality/reliability under the economic statistical domain 18 economic domain is classified as "workable," indicating lower-end data quality due to varying methodologies and definitions used in data collection, particularly from administrative records. Table 3: Minimum core data availability, source, responsible institutions, and quality/reliability under the economic statistical domain Element Data type Availabilit y1 Source2 Institution3 Quality4 Production Crop production: quantity ✔ AR NAB Workable Crop production: value ✔ AR NAB Workable Crop yield per area ✔ AR NAB Workable Area planted and harvested ✔ AR NAB Workable Livestock production: quantity ✔ AR LLPBN Workable Livestock production: value ✔ AR LLPBN Workable Fishery and aquaculture production: quantity ✔ AR MFMR Acceptable Fishery and aquaculture production: value ✔ AR MFMR Acceptable Forest production of wood: quantity ✔ AR MEFT Acceptable Forest production of wood: value ✔ AR MEFT Acceptable Forest production of non-wood: quantity ✔ AR MEFT Acceptable Forest production of non-wood: value ✔ AR MEFT Acceptable External trade Export: quantity ✔ AR NSA Acceptable Export: value ✔ AR NSA Acceptable Import: quantity ✔ AR NSA Acceptable Import: value ✔ AR NSA Acceptable Stock of capital resources Livestock Inventories ✔ E/F MAWLR Workable Agricultural machinery ✔ E/F MAWLR Workable Stocks of main crops: quantity ✔ E/F MAWLR Workable Land and use ✔ C MAWLR Workable Irrigated areas ✔ AR NAB Workable Types of crop production systems ✔ C NAB Highly Reliable Irrigated crops ✔ C NAB Highly Reliable Quantity of water used ✔ C NSA Highly Reliable Element Data type Source2Availability y1 Institution3 Quality4 STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 15 19 Water quality x Inputs Fertilizer quantity ✔ AR NS A Reliable Fertilizer value ✔ AR NSA Reliable Pesticide quantity ✔ AR NS A Reliable Pesticide value ✔ AR NSA Reliable Seeds quantity ✔ AR NSA Reliable Seed value ✔ AR NSA Reliable Animal Feed quantity ✔ AR NSA Acceptable Animal Feed value ✔ AR NAMRA Acceptable Forage quantity x Forage value x Animal vaccines and drugs quantity ✔ E/F NAMRA Workable Animal vaccines and drugs value ✔ E/F NAMRA Workable Aquatic seeds quantity x Aquatic seeds value x Agro processing Main crops ✔ E/F MAWLR Workable Post-harvest losses ✔ E/F MAWLR Workable Main livestock (and livestock products) ✔ E/F LLPBN Reliable Fish: quantity ✔ E/F MFMR Reliable Fish: value ✔ E/F MFMR Reliable Prices Producer prices ✔ E/F NSA Workable Wholesale prices x Consumer prices ✔ SS NSA Highly Reliable Agric. Input prices x E/F NSA Workable Agric. Export prices ✔ E/F NSA Workable Agric. Import prices ✔ E/F NSA Workable Investments, subsidies, or taxes Public investment in agriculture ✔ AR MFPE Reliable Agricultural subsidies ✔ AR MFPE Reliable Fishery access fees ✔ AR MFPE Reliable Public expenditure for fishery management ✔ AR MFPE Reliable STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 16 20 Fishery subsidies ✔ AR MFPE Reliable Water pricing x Rural infrastructur e services Area equipped for irrigation ✔ C NSA Highly Reliable Crop markets ✔ C NSA Highly Reliable Livestock markets ✔ C NSA Highly Reliable Rural roads (Km) ✔ C NSA Highly Reliable Railways (Km) ✔ C NSA Highly Reliable Communication ✔ C NSA Highly Reliable Banking and insurance ✔ C NSA Highly Reliable 1Availability: tick (✔) means available, and cross (x) means not available. 2Source of data: C. Census; SS. Sample survey; AR. Administrative records; and E/F. Estimates/forecasts. 3Responsible institutions: LLPBN. Livestock and Livestock Products Board; NAB. Namibian Agronomic Board; NSA. Namibia Statistics Agency; MAWLR.Ministry of Agriculture Water and Land Reform; MFMR. Ministry of Fisheries and Marine Resources; MFPE. Ministry of Finance and Public Enterprises; and NAMRA. Namibia Revenue Agency. 4Quality/Reliability of data: High reliability > Reliable > Acceptable > Workable > Unacceptable. 2.3.2 Social domain Namibia's NSS demonstrates full compliance with minimum core data requirements in the social domain, as outlined in Table 4 sourced from Section 2.1 of Module I of the Standardized Questionnaire (SQ). The NSS produces all essential core data within this domain, primarily sourced from Sample Surveys like the Namibia Labour Force Survey (NLFS) and Namibia Household Income and Expenditure Survey, conducted by the Namibia Statistics Agency (NSA) using standardized methodologies and definitions. This adherence to standards ensures highly reliable quality in the minimum core data within the social domain, despite the latest available data being from 2018. Table 4: Availability, source, responsible institution, and quality of minimum core data types under the social domain. Data type Availability1 Source2 Institution3 Quality4 Population dependent on agriculture ✔ SS NSA High reliable Agricultural workforce (by gender) ✔ SS NSA High reliable Fishery workforce (by gender) ✔ SS NSA High reliable 2.3.2 Social domain Namibia’s NSS demonstrates full compliance with minimum core data requirements in the social domain, as outlined in Table 4 sourced from Section 2.1 of Module I of the Standardized Questionnaire (SQ). The NSS produces all essential core data within this domain, primarily sourced from Sample Surveys like the Namibia Labour Force Survey (NLFS) and Namibia Household Income and Expenditure Survey, conducted by the Namibia Statistics Agency (NSA) using standardized methodologies and definitions. This adherence to standards ensures highly reliable quality in the minimum core data within the social domain, despite the latest available data being from 2018. STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 17 Table 4: Availability, source, responsible institution, and quality of minimum core data types under the social domain 20 Fishery subsidies ✔ AR MFPE Reliable Water pricing x Rural infrastructur e services Area equipped for irrigation ✔ C NSA Highly Reliable Crop markets ✔ C NSA Highly Reliable Livestock markets ✔ C NSA Highly Reliable Rural roads (Km) ✔ C NSA Highly Reliable Railways (Km) ✔ C NSA Highly Reliable Communication ✔ C NSA Highly Reliable Banking and insurance ✔ C NSA Highly Reliable 1Availability: tick (✔) means available, and cross (x) means not available. 2Source of data: C. Census; SS. Sample survey; AR. Administrative records; and E/F. Estimates/forecasts. 3Responsible institutions: LLPBN. Livestock and Livestock Products Board; NAB. Namibian Agronomic Board; NSA. Namibia Statistics Agency; MAWLR.Ministry of Agriculture Water and Land Reform; MFMR. Ministry of Fisheries and Marine Resources; MFPE. Ministry of Finance and Public Enterprises; and NAMRA. Namibia Revenue Agency. 4Quality/Reliability of data: High reliability > Reliable > Acceptable > Workable > Unacceptable. 2.3.2 Social domain Namibia's NSS demonstrates full compliance with minimum core data requirements in the social domain, as outlined in Table 4 sourced from Section 2.1 of Module I of the Standardized Questionnaire (SQ). The NSS produces all essential core data within this domain, primarily sourced from Sample Surveys like the Namibia Labour Force Survey (NLFS) and Namibia Household Income and Expenditure Survey, conducted by the Namibia Statistics Agency (NSA) using standardized methodologies and definitions. This adherence to standards ensures highly reliable quality in the minimum core data within the social domain, despite the latest available data being from 2018. Table 4: Availability, source, responsible institution, and quality of minimum core data types under the social domain. Data type Availability1 Source2 Institution3 Quality4 Population dependent on agriculture ✔ SS NSA High reliable Agricultural workforce (by gender) ✔ SS NSA High reliable Fishery workforce (by gender) ✔ SS NSA High reliable 21 Aquaculture workforce (by gender) ✔ SS NSA High reliable Household income ✔ SS NSA High reliable 1Availability: tick (✔) means available, and cross (x) means not available. 2Source of data: C. Census; SS. Sample Survey; AR. Administrative records; and E/F. Estimates/forecasts. 3Responsible institutions: LLPBN. Livestock and Livestock Products Board; NAB. Namibian Agronomic Board; NSA. Namibia Statistics Agency; MAWLR.Ministry of Agriculture Water and Land Reform; MFMR. Ministry of Fisheries and Marine Resources; MFPE. Ministry of Finance and Public Enterprises; and NAMRA. Namibia Revenue Agency. 4Quality/Reliability of data: High reliable > Reliable > Acceptable > Workable > Unacceptable. 2.3.3 Environmental domain The Namibian NSS faces limitations in the availability of minimum core data within the environmental domain, as summarized in Table 5 sourced from Section 2.1 of Module I of the Standardized Questionnaire (SQ). The NSS currently collects and produces only one minimum core data type in this domain, specifically emissions due to agriculture. This data is sourced from estimates/forecasts generated by the Ministry of Environment, Forestry, and Tourism (MEFT) through the Greenhouse Gas (GHG) inventory. Despite using standardized methodologies and definitions, these data are not validated by the Namibia Statistics Agency (NSA), resulting in a workable quality level, indicating lower quality. Thus, while efforts are made to produce environmental data, the lack of validation contributes to the lower quality of minimum core data within the environmental domain in Namibia's NSS. Table 5 Availability, source, responsible institution, and quality of minimum core data types under the environmental domain. Data type Availability1 Source2 Institution3 Quality4 Soil degradation x Water pollution due to agriculture x Emissions due to agriculture ✔ E/F MEFT Workable Water pollution due to aquaculture x Emissions due to aquaculture x 1Availability: tick (✔) means available, and cross (x) means not available. 2Source of data: C. Census; SS. Sample Survey; AR. Administrative records; and E/F. Estimates/forecasts. 3Responsible institutions: LLPB. Livestock and Livestock Products Board of Namibia; NAB. Namibian Agronomic Board; NSA. Namibia Statistics Agency; MAWLR.Ministry of Agriculture Water and Land Reform; Data type Availibilty1 Source2 Institution3 Quality4 2.3.3 Environmental domain The Namibian NSS faces limitations in the availability of minimum core data within the environmental domain, as summarized in Table 5 sourced from Section 2.1 of Module I of the Standardized Questionnaire (SQ). The NSS currently collects and produces only one minimum core data type in this domain, specifically emissions due to agriculture. This data is sourced from estimates/forecasts generated by the Ministry of Environment, Forestry, and Tourism (MEFT) through the Greenhouse Gas (GHG) inventory. Despite using standardized methodologies and definitions, these data are not validated by the Namibia Statistics Agency (NSA), resulting in a workable quality level, indicating lower quality. Thus, while efforts are made to produce environmental data, the lack of validation contributes to the lower quality of minimum core data within the environmental domain in Namibia’s NSS. STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 18 21 Aquaculture workforce (by gender) ✔ SS NSA High reliable Household income ✔ SS NSA High reliable 1Availability: tick (✔) means available, and cross (x) means not available. 2Source of data: C. Census; SS. Sample Survey; AR. Administrative records; and E/F. Estimates/forecasts. 3Responsible institutions: LLPBN. Livestock and Livestock Products Board; NAB. Namibian Agronomic Board; NSA. Namibia Statistics Agency; MAWLR.Ministry of Agriculture Water and Land Reform; MFMR. Ministry of Fisheries and Marine Resources; MFPE. Ministry of Finance and Public Enterprises; and NAMRA. Namibia Revenue Agency. 4Quality/Reliability of data: High reliable > Reliable > Acceptable > Workable > Unacceptable. 2.3.3 Environmental domain The Namibian NSS faces limitations in the availability of minimum core data within the environmental domain, as summarized in Table 5 sourced from Section 2.1 of Module I of the Standardized Questionnaire (SQ). The NSS currently collects and produces only one minimum core data type in this domain, specifically emissions due to agriculture. This data is sourced from estimates/forecasts generated by the Ministry of Environment, Forestry, and Tourism (MEFT) through the Greenhouse Gas (GHG) inventory. Despite using standardized methodologies and definitions, these data are not validated by the Namibia Statistics Agency (NSA), resulting in a workable quality level, indicating lower quality. Thus, while efforts are made to produce environmental data, the lack of validation contributes to the lower quality of minimum core data within the environmental domain in Namibia's NSS. Table 5 Availability, source, responsible institution, and quality of minimum core data types under the environmental domain. Data type Availability1 Source2 Institution3 Quality4 Soil degradation x Water pollution due to agriculture x Emissions due to agriculture ✔ E/F MEFT Workable Water pollution due to aquaculture x Emissions due to aquaculture x 1Availability: tick (✔) means available, and cross (x) means not available. 2Source of data: C. Census; SS. Sample Survey; AR. Administrative records; and E/F. Estimates/forecasts. 3Responsible institutions: LLPB. Livestock and Livestock Products Board of Namibia; NAB. Namibian Agronomic Board; NSA. Namibia Statistics Agency; MAWLR.Ministry of Agriculture Water and Land Reform; Table 5 Availability, source, responsible institution, and quality of minimum core data types under the environmental domain. Data type Availibilty1 Source2 Institution3 Quality4 2.3.4 Geographical location domain Namibia’s National Statistics System (NSS) demonstrates strong performance in the availability of minimum core data within the geographical domain, as outlined in Table 6 sourced from Section 2.1 of Module I of the Standardized Questionnaire (SQ). The NSS collects and produces all minimum core data types in this domain, particularly the geo-coordinates of statistical units (constituencies, region, country). These data are sourced from the population census and the National Spatial Data Infrastructure (NSDI), both under the mandate of the Namibia Statistics Agency (NSA). This adherence to standardized methodologies and data collection practices ensures highly reliable quality in the minimum core data within the geographical domain, indicating a high level of quality and reliability. STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 19 22 MFMR. Ministry of Fisheries and Marine Resources; MFPE. Ministry of Finance and Public Enterprises; MEFT. Ministry of Environment, Forestry, and Tourism; and NAMRA. Namibia Revenue Agency. 4Quality/Reliability of data: High reliable > Reliable > Acceptable > Workable > Unacceptable. 2.3.4 Geographical location domain Namibia's National Statistics System (NSS) demonstrates strong performance in the availability of minimum core data within the geographical domain, as outlined in Table 6 sourced from Section 2.1 of Module I of the Standardized Questionnaire (SQ). The NSS collects and produces all minimum core data types in this domain, particularly the geo-coordinates of statistical units (constituencies, region, country). These data are sourced from the population census and the National Spatial Data Infrastructure (NSDI), both under the mandate of the Namibia Statistics Agency (NSA). This adherence to standardized methodologies and data collection practices ensures highly reliable quality in the minimum core data within the geographical domain, indicating a high level of quality and reliability. Table 6: Availability, source, responsible institution, and quality of minimum core data types under the environmental domain. Data type Availability1 Source2 Institution3 Quality4 Geo-coordinate of the statistical unit (constituencies, region, country) ✔ C NSA Highly Reliable Satellite Imagery ✔ C NSA Highly Reliable 1Availability: tick (✔) means available, and cross (x) means not available. 2Source of data: C. Census; SS. Sample Survey; AR. Administrative records; and E/F. Estimates/forecasts. 3Responsible institutions: LLPBN. Livestock and Livestock Products Board; NAB. Namibian Agronomic Board; NSA. Namibia Statistics Agency; MAWLR.Ministry of Agriculture Water and Land Reform; MFMR. Ministry of Fisheries and Marine Resources; MFPE. Ministry of Finance and Public Enterprises; MEFT. Ministry of Environment, Forestry, and Tourism; and NAMRA. Namibia Revenue Agency. 4Quality/Reliability of data: High reliable > Reliable > Acceptable > Workable > Unacceptable. 2.4 On-going Data Collection Activities This section comprises three main components, namely, main statistical activities, existing data gaps, and critical constraints in the agriculture statistics system. The insights presented in this section are synthesized from the information extracted from Module II of the SQ. One of the focus areas of the IdCA is the assessment of current data collection activities in the agricultural sector, particularly those using standardized methodologies and procedures. The main statistical activities in Namibia include the Population and Housing Census, Agriculture Census, National Labour Force Survey (NLFS), Namibia Household Income and Expenditure Table 6: Availability, source, responsible institution, and quality of minimum core data types under the environmental domain. Data type Availibilty1 Source2 Institution3 Quality4 2.4 On-going Data Collection Activities This section comprises three main components, namely, main statistical activities, existing data gaps, and critical constraints in the agriculture statistics system. The insights presented in this section are synthesized from the information extracted from Module II of the SQ. One of the focus areas of the IdCA is the assessment of current data collection activities in the agricultural sector, particularly those using standardized methodologies and procedures. The main statistical activities in Namibia include the Population and Housing Census, Agriculture Census, National Labour Force Survey (NLFS), Namibia Household Income and Expenditure Survey (NHIES), and National Accounts. These activities produce vital data and statistics that are used in evidence-based policy formulation, implementation, and management. Although Namibia has consistently conducted these crucial surveys, the NLFS and NHIES have not been conducted as scheduled. Consequently, this has affected the timely availability of critical statistics and data on household living conditions, poverty, inequality, and unemployment. In general, the major statistical activities are centralized in Namibia and carried out by the NSA through its functional structure, the Census Department. The various data collection activities undertaken by the NSA are summarized in Table 7. STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 20 Table 7: Summary of official data collection activities done by the NSA. 24 have not been conducted as scheduled. Consequently, this has affected the timely availability of critical statistics and data on household living conditions, poverty, inequality, and unemployment. In general, the major statistical activities are centralized in Namibia and carried out by the NSA through its functional structure, the Census Department. The various data collection activities undertaken by the NSA are summarized in Table 7. Table 7: Summary of official data collection activities done by the NSA Census/survey Planned Frequency Last Conducted Example of topics Population and Housing Census Decennial (every 10 years) 2023 Population size, age, sex, education, housing conditions, access to basic services Census of Agriculture Decennial (every 10 years) 2013/2014 Land use, crop production, livestock numbers, farm machinery, irrigation, farm labour Namibia Demographic and Health Survey (NDHS) Every 5 years 2013 Fertility, family planning, maternal and child health, nutrition, HIV/AIDS, malaria, vaccination coverage. Financial Inclusion Survey (FIS) Periodic 2017 Access to financial services, use of financial products, savings and borrowing patterns, financial literacy National Labour Force Survey (NLFS) Periodic (every year) 2018 Employment, unemployment, labour force participation, wages, job types Namibia Household Income and Periodic (every five years) 2015/2016 Household income and expenditure patterns, poverty levels, living standards 25 Expenditure Survey (NHIES) Monthly price collection survey Monthly March 2024 Inflation rate, change in prices of goods and services Profiling survey for the business register Periodic (last in 2019-21) 2019-21 Number of businesses, employment, sales, revenue, investment Annual economic survey Annual 2022 Gross Domestic Product (GDP), economic growth, sectoral contributions to GDP 2.4.1 Population Census The 2023 Namibian Population and Housing Census aimed to achieve two vital objectives: painting a comprehensive picture of the nation's demographics and living conditions and providing crucial data for informed policy formulation and resource allocation. Firstly, the census sought to update detailed information on the size, composition, and distribution of Namibia's population. This included collecting data on age, sex, gender, education levels, and marital status, offering insights into population growth trends, internal migration patterns, and demographic shifts within different regions. Additionally, the census covered vital information on household characteristics, including housing structure, access to basic amenities like water and sanitation, and ownership of essential household goods. This data sheds light on living conditions across urban and rural areas, highlighting regions and communities facing particular challenges. Secondly, the census data serves as a vital foundation for developing evidence-based policies and allocating resources effectively. Knowing the precise number of people living in specific areas, their educational attainment, and the types of housing they occupy, allows policymakers to tailor interventions and services to meet the real needs of different communities. This could involve allocating education resources based on population density and age distribution, or prioritizing infrastructure development in regions with inadequate sanitation facilities. Ultimately, the 2023 Namibian Population and Housing Census aimed to empower policymakers to make informed decisions that contribute to a more equitable and prosperous future for all Namibians. Census/survey Planned frequency Last Conducted Example of topics STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 21 2.4.1 Population Census The 2023 Namibian Population and Housing Census aimed to achieve two vital objectives: painting a comprehensive picture of the nation’s demographics and living conditions and providing crucial data for informed policy formulation and resource allocation. Firstly, the census sought to update detailed information on the size, composition, and distribution of Namibia’s population. This included collecting data on age, sex, gender, education levels, and marital status, offering insights into population growth trends, internal migration patterns, and demographic shifts within different regions. Additionally, the census covered vital information on household characteristics, including housing structure, access to basic amenities like water and sanitation, and ownership of essential household goods. This data sheds light on living conditions across urban and rural areas, highlighting regions and communities facing particular challenges. Secondly, the census data serves as a vital foundation for developing evidence-based policies and allocating resources effectively. Knowing the precise number of people living in specific areas, their educational attainment, and the types of housing they occupy, allows policymakers to tailor interventions and services to meet the real needs of different communities. This could involve allocating education resources based on population density and age distribution, or prioritizing infrastructure development in regions with inadequate sanitation facilities. Ultimately, the 2023 Namibian Population and Housing Census aimed to empower policymakers to make informed decisions that contribute to a more equitable and prosperous future for all Namibians. 2.4.2 Agriculture Census The 2013/14 Namibian Agriculture Census had two major objectives: firstly, to establish a baseline of agricultural production and structural variables for both commercial and communal farming sectors, at national and regional levels. This provided detailed data on land use, crop production, livestock numbers, farm machinery, irrigation, farm labour, and farm characteristics, offering a comprehensive snapshot of the agricultural landscape at the time. Secondly, the census aimed to provide statistical data to improve planning and decision-making within the agricultural sector, fulfilling Namibia’s need for a robust socio-economic database and satisfying information requirements for national development goals. This data could be used to inform policies aimed at increasing agricultural productivity, improving rural livelihoods, and strengthening Namibia’s food security. 2.4.3 National Accounts Statistics The National Accounts in Namibia serve as the primary framework for measuring and understanding the health and performance of the nation’s economy. Their main purpose is threefold: • Providing a comprehensive picture of economic activity: The National Accounts measure the total value of goods and services produced in Namibia (Gross Domestic Product or GDP), along with its components like household consumption, government spending, investment, and trade. This gives a bird’s eye view of the size and structure of the economy, revealing which sectors contribute most to overall output. • Monitoring economic growth and performance: By tracking changes in GDP and other key indicators over time, the National Accounts allow policymakers and analysts to assess the pace and trajectory of economic growth. This data is crucial for evaluating the effectiveness of economic policies, identifying potential challenges like inflation or recession, and informing decisions aimed at promoting sustainable economic development. • Informing resource allocation and policy formulation: Detailed statistics on different sectors, income levels, and expenditure patterns within the National Accounts provide valuable insights for allocating resources efficiently and formulating effective economic policies. For instance, identifying sectors with high growth potential can guide investment decisions, while data on poverty levels can inform targeted social protection programs. Beyond these essential functions, the National Accounts also: • Contribute to international comparisons: Standardized National Accounts data allows Namibia to benchmark its economic performance against other countries and regions, facilitating the exchange of STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 22 best practices and attracting foreign investment. • Enhance transparency and accountability: The robust and publicly available data on the economy provided by the National Accounts promote transparency in government operations and enhance accountability by holding policymakers responsible for managing the economy effectively. In summary, the National Accounts are a vital tool for understanding and managing the Namibian economy. They provide comprehensive data for making informed decisions about resource allocation, policy formulation, and ultimately, achieving sustainable economic growth and development for all Namibians. 2.4.4 Adoption of classifications The Namibia Statistics Agency has adopted several international classifications, including the International Standard Industrial Classification (ISIC), Central Product Classification (CPC), and Harmonised Commodity Description and Coding System (HS). However, it has not adopted the Standard International Trade Classification (SITC) or the Classification of Functions of Government (COFOG) classifications. 2.4.5 Price Indices A price index survey is essential as it helps to measure the changes in prices of goods and services over time. This information is crucial for policymakers, and consumers to make informed decisions. The Namibia Statistics Agency (NSA) releases data on the Consumer Price Index (CPI). However, Namibia does not have indices to monitor agricultural input prices, agricultural terms of trade, as well as agriculture price index. Additionally, there is no published index for agricultural producer prices in the country. 2.4.6 Food and Agricultural Surveys Conducted The most recent agriculture census in Namibia was conducted in 2013/2014. Namibia has a legal framework for conducting agricultural censuses and utilizes a list frame for this purpose. The 2013/2014 agriculture census covered a wide range of topics including crops, livestock, aquaculture, fisheries, forestry related to agriculture, water resources related to agriculture, and other income-generating activities in rural areas. The agricultural census utilized cartographic materials and administrative boundaries that were also used for the population census. Additionally, a few questions related to household participation in the agricultural sector were included in the population census to gather information for the sampling frame used in the agricultural census. The next scheduled agricultural census is planned to take place in the year 2026/2027. It is worth noting that the Namibia Statistics Agency (NSA) does not conduct specific agricultural surveys for crops, livestock, fisheries, water, and forestry. These responsibilities fall under the purview of specific line ministries within the country. 2.4.7 Household Budget Survey The Namibia Statistics Agency (NSA) is responsible for conducting household budget surveys in the country. The Namibian Household Income and Expenditure Survey (NHIES) plays a crucial role in understanding the economic welfare and living standards of the Namibian population. Its primary purpose is to collect comprehensive data on household income and expenditure patterns across the country. This encompasses: • Income sources: Analysing wages, salaries, business income, agricultural income, and other sources of income for households. • Expenditure patterns: Understanding how households spend their money on food, housing, healthcare, education, transportation, and other essential goods and services. • Poverty measurement: Utilizing the data to calculate poverty indicators like the national poverty rate and the depth of poverty, highlighting the extent and severity of poverty in Namibia. • Living standards: Assessing the overall well-being of Namibian households by considering income, expenditure, and consumption patterns alongside access to basic amenities and resources. STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 23 By providing these insights, the NHIES fuels crucial decision-making processes at both national and regional levels. It informs targeted social protection programs, poverty reduction strategies, and allocation of resources to ensure equitable development across the country. Additionally, the data aids in monitoring progress towards national development goals and international commitments such as the SDGs, allowing policymakers to track progress and identify areas requiring further intervention. Overall, the NHIES stands as a vital tool for understanding economic vulnerability and disparities in Namibia, ultimately aiming to improve the lives of all citizens by informing policies that promote inclusive and sustainable economic growth. The most recent household budget survey conducted in the country took place in 2018, and the next survey is scheduled for 2024. 2.4.8 Availability of derived statistics and indicators in the country Based on the assessment, it was noted that the country does not compile information pertaining to food balance sheet, agri-environmental statistics. Compiling a food balance sheet and agri-environmental statistics are crucial for the country as it provides insights of the state of the food supply and demand. Policymakers, planners, and academics require this data in order to keep an eye on food security, schedule the distribution of food, and evaluate the population’s nutritional needs. 2.4.9 Quality consciousness in statistics It is commendable that the Namibia Statistics Agency (NSA) makes the methodology of national agricultural surveys accessible to the public, including information on sampling errors and post-enumeration surveys. This transparency helps to ensure the credibility and reliability of the data collected. However, it is important to note that technical reports on the quality of surveys are not published in the country. Publishing technical reports on survey quality is crucial for providing further detail on the accuracy, reliability, and overall quality of the data collected. 2.4.10 Information technology The Namibia Statistics Agency (NSA) maintains a website for hosting the official statistics of the country. This website complements the database where official statistics are stored, which is accessible to external users. The NSA uses various software and IT-related systems, including SPSS, SAS, STATA, ACCESS, CSPRO, SDMX, Excel, and others for data analysis and management. This practice of sharing statistics is commendable, as it enhances transparency and easy accessibility of statistics to external users. 2.4.11 Transport Infrastructure Based on the in-depth assessment, the Namibia Statistics Agency (NSA) has a total of 54 four-wheeled vehicles that are used and available for statistical activities in the country. 2.4.12 Financial resources Allocating sufficient financial resources to statistical activities is important as it enables the collection, processing, and analysis of data which is crucial for evidence-based decision making and policy formulation. Therefore, without adequate resources, statistical activities may be compromised, leading to incomplete or inaccurate information. According to the assessment report, the Namibia Statistics Agency (NSA) allocated a total budget of N$779,276,427 for statistical activities, with N$105,200 specifically designated for agricultural statistics. 2.4.13 Human resources and training for statistical activities Human resources and training are essential for the Namibia Statistics Agency (NSA) to effectively carry out its statistical activities. Through training, staff acquire knowledge and skills necessary to collect, analyse, and interpret data accurately. In addition, training programs help build staff capacity, enabling them to take on more complex tasks and stay updated on the latest statistical methodologies and technologies. A total of 8 staff members from the Economics department attended a Supervisory Management Development STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 24 training at NIPAM in the last 12 months. Due to resource reallocation for the upcoming Census 2023, all training activities have been suspended. Although there are regular training programs for statistical staff, sponsored training is not adequately regulated, as it occurs. 2.4.14 International cooperation in agricultural statistics In the past three years, the NSA has received technical assistance for agricultural statistics activities from key donors, including the Food and Agriculture Organization (FAO), the United Nations Population Fund (UNFPA), and the World Bank. 2.5 Critical Constraints in the Agriculture Statistics System Section 2 of Module II in the Standardized Questionnaire (SQ) outlines commonly reported constraints faced by statistical systems in developing countries, focusing on their impact on agricultural statistics development. Representatives from the Namibia Statistics Agency (NSA) contributed their perceptions on these constraints, using an ordinal scale with three measurement levels: sufficient, insufficient/somewhat, and dominant constraint. A “dominant constraint” signifies that improving the situation would significantly enhance agricultural statistics, while “sufficient” indicates no substantial impact from improvement, and “insufficient/ somewhat” implies potential impact on agricultural statistics status. Table 8 presents the results of the constraints ranking by the NSA, identifying eight dominant constraints crucial for improving agricultural statistics in Namibia. These include enhancing technical skills among statistical staff, raising awareness at the policy-making level about statistical activities’ importance, garnering political support for statistical activities, allocating funds for field-oriented statistical activities, providing transport equipment for fieldwork, ensuring adequate office space, implementing sound methodologies for agricultural surveys, and reducing turnover among professional staff. Addressing these constraints is fundamental for the successful development and implementation of the Strategic Plan for Agricultural and Rural Statistics (SPARS) in Namibia, forming the essential pillars for its progress and effectiveness. Table 8: Ranking of critical constraints from the perspective of the NSA. 30 Although there are regular training programs for statistical staff, sponsored training is not adequately regulated, as it occurs. at 2.4.13 International cooperation in agricultural statistics In support of agricultural statistics, the NSA received technical assistance (during the last three years) for agricultural statistics activities from key donors, including the Food and Agriculture Organization (FAO), the United Nations Population Fund (UNFPA), and the World Bank. 2.5 Critical Constraints in the Agriculture Statistics System Section 2 of Module II in the Standardized Questionnaire (SQ) outlines commonly reported constraints faced by statistical systems in developing countries, focusing on their impact on agricultural statistics development. Representatives from the Namibia Statistics Agency (NSA) contributed their perceptions on these constraints, using an ordinal scale with three measurement levels: sufficient, insufficient/somewhat, and dominant constraint. A "dominant constraint" signifies that improving the situation would significantly enhance agricultural statistics, while "sufficient" indicates no substantial impact from improvement, and "insufficient/somewhat" implies potential impact on agricultural statistics status. Table 8 presents the results of the constraints ranking by the NSA, identifying eight dominant constraints crucial for improving agricultural statistics in Namibia. These include enhancing technical skills among statistical staff, raising awareness at the policy-making level about statistical activities' importance, garnering political support for statistical activities, allocating funds for field-oriented statistical activities, providing transport equipment for fieldwork, ensuring adequate office space, implementing sound methodologies for agricultural surveys, and reducing turnover among professional staff. Addressing these constraints is fundamental for the successful development and implementation of the Strategic Plan for Agricultural and Rural Statistics (SPARS) in Namibia, forming the essential pillars for its progress and effectiveness. Table 8: Ranking of critical constraints from the perspective of the NSA. Constraints Extent1 Number of professional staff at headquarters for statistical activities N/A Number of support staff at headquarters for statistical activities N/A Number of professional staff in the field for statistical activities N/A 31 Number of field workers for statistical activities N/A Technical skills of the available statistical staff 3 Appreciation at the policy-making level for importance of statistical activities 3 Support at political level in the Government for statistical activities 3 Up-to-date information technology hardware 2 Up-to-date information technology software 2 Funds for field-oriented statistical activities vis-à-vis plans. 3 Transport equipment for field activities 3 Building space for office 3 Sound methodology implemented for agricultural surveys 3 Level of demand for statistics 1 Turnover of professional staff 3 1Response code: (1) Sufficient; (2) Insufficient/Somewhat; (3) Dominant constraint; and (N/A) not applicable. 2.6 Main Statistical Activities and Critical Constraints of the Sub-Sectors 2.6.1 Crop and livestock Statistics for the crop and livestock sub sectors are generally collected through the Population Census, Census of Agriculture, Namibia Household Income and Expenditure Survey (NHIES), and Namibia Labour Force Survey (NLFS). The Population Census is implemented by the NSA, while the Census of Agriculture is implemented by NSA in collaboration with the MAWLR. The NHIES and NLFS are sample surveys that are done by the NSA. The MAWLR has not implemented sample surveys for the major crops and livestock since 2003. As such, the primary source of crop and livestock statistics are the Population Census, Census of Agriculture, NHIES, and NFLS. Apart from the Census of Agriculture that is decennially, the other sources provide limited agriculture and rural statistics as the objectives of the surveys are much broader than the agriculture and rural sector. Administrative records particularly from the Namibian Agronomic Board (NAB) and the Livestock and Livestock Products Board of Namibia are also primary data sources for crop and livestock statistics, respectively. These administrative records provide production, marketing, hectare coverage and price statistics on major crops and livestock. 2.6.2 Fisheries and aquaculture The following information is derived from the IdCA on the major statistical activities and performance of the fishing and aquaculture subsector: 31 Number of field workers for statistical activities N/A Technical skills of the available statistical staff 3 Appreciation at the policy-making level for importance of statistical activities 3 Support at political level in the Government for statistical activities 3 Up-to-date information technology hardware 2 Up-to-date information technology software 2 Funds for field-oriented statistical activities vis-à-vis plans. 3 Transport equipment for field activities 3 Building space for office 3 Sound methodology implemented for agricultural surveys 3 Level of demand for statistics 1 Turnover of professional staff 3 1Response code: (1) Sufficient; (2) Insufficient/Somewhat; (3) Dominant constraint; and (N/A) not applicable. 2.6 Main Statistical Activities and Critical Constraints of the Sub-Sectors 2.6.1 Crop and livestock Statistics for the crop and livestock sub sectors are generally collected through the Population Census, Census of Agriculture, Namibia Household Income and Expenditure Survey (NHIES), and Namibia Labour Force Survey (NLFS). The Population Census is implemented by the NSA, while the Census of Agriculture is implemented by NSA in collaboration with the MAWLR. The NHIES and NLFS are sample surveys that are done by the NSA. The MAWLR has not implemented sample surveys for the major crops and livestock since 2003. As such, the primary source of crop and livestock statistics are the Population Census, Census of Agriculture, NHIES, and NFLS. Apart from the Census of Agriculture that is decennially, the other sources provide limited agriculture and rural statistics as the objectives of the surveys are much broader than the agriculture and rural sector. Administrative records particularly from the Namibian Agronomic Board (NAB) and the Livestock and Livestock Products Board of Namibia are also primary data sources for crop and livestock statistics, respectively. These administrative records provide production, marketing, hectare coverage and price statistics on major crops and livestock. 2.6.2 Fisheries and aquaculture The following information is derived from the IdCA on the major statistical activities and performance of the fishing and aquaculture subsector: STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 25 2.6 Main Statistical Activities and Critical Constraints of the Sub-Sectors 2.6.1 Crop and livestock Statistics for the crop and livestock sub-sectors are generally collected through the Population Census, Census of Agriculture, Namibia Household Income and Expenditure Survey (NHIES), and Namibia Labour Force Survey (NLFS). The Population Census is implemented by the NSA, while the Census of Agriculture is implemented by NSA in collaboration with the MAWLR. The NHIES and NLFS are sample surveys that are done by the NSA. The MAWLR has not implemented sample surveys for the major crops and livestock since 2003. As such, the primary source of crop and livestock statistics are the Population Census, Census of Agriculture, NHIES, and NFLS. Apart from the Census of Agriculture that is decennially, the other sources provide limited agriculture and rural statistics as the objectives of the surveys are much broader than the agriculture and rural sector. Administrative records, particularly from the Namibian Agronomic Board (NAB) and the Livestock and Livestock Products Board of Namibia are also primary data sources for crop and livestock statistics, respectively. These administrative records provide production, marketing, hectare coverage and price statistics on major crops and livestock. 2.6.2 Fisheries and aquaculture The following information is derived from the IdCA on the major statistical activities and performance of the fishing and aquaculture subsector: The MFMR does not produce information on the consumer price index. However, the Namibia Statistical Agency (NSA) publishes information on the consumer price index for fish and fisheries products, as well as other products produced in the country. • The MFMR conducts marine capture fishery surveys, as well as surveys on inland capture fisheries but not for aquaculture, with the most recent surveys being conducted in 2023. These surveys utilize sample based surveys to monitor production and rely on logbook-based reporting on standard forms. • The MFMR does not compile food balance sheets and agri-environmental indicators. • The methodology for fishery and aquaculture surveys conducted by the MFMR is available to the public. In addition, technical reports on survey quality, including sample errors, are published. However, no post enumeration surveys on the quality of data collected are carried out. • The MFMR uses various software and IT systems for statistical activities, including SPSS, ACCESS, Excel, PASGER, R, Surfer, JABBA, LBB, and ADMB. To gather and capture survey data, the MFMR utilizes personal interviews, manual data entry into computers, scanning of questionnaires, personal data assistants, geographic positioning systems (GPS), and measuring tapes. • The MFMR uses several databases for capturing fishery survey data, including the Fisheries Information Management Systems (FIMS), Fishery Information Performance System (FIPS), and Eco-Data. However, no database is available for storing aquaculture statistics. • The MFMR headquarters has 39 PCs dedicated to agricultural statistics, while the field offices have 306 PCs. Additionally, there are a total of four computer servers for data storage and communication at the headquarters and three servers at the field offices. • The MFMR headquarters and regional offices have a total of 19 four-wheeled vehicles that are utilized for field work and other operations. • For the budget year 2022/2023, a total of N$138,914,382 was allocated for all directorates within the MFMR. This allocation includes N$128,457,963 for salaries, N$9,656,419 for staff training, and N$800,000 for non-staff activities such as travel and IT purchases. For statistics purposes the directorate of Policy Planning and Economics, Operations and Aquaculture received N$106,438,102 from the total budget, with N$98,218,963 allocated to salaries and N$8,219,139 for staff training. • As of November 2023, the MFMR had a staff complement of 479 regular professional and support staff. At the headquarters, there are 30 regular professional staff, with 26 dedicated to agricultural statistics. The regional/local offices have 381 regular professional staff, with 108 dedicated to agricultural statistics. STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 26 34 Appreciation at the policy-making level for importance of statistical activities 2 Support at political level in the Government for statistical activities 2 Up-to-date information technology hardware 2 Up-to-date information technology software 2 Funds for field-oriented statistical activities vis-à-vis plans. 2 Transport equipment for field activities 1 Building space for office 2 Sound methodology implemented for agricultural surveys 2 Level of demand for statistics 1 Turnover of professional staff [1] 2 1Response code: (1) Sufficient; (2) Insufficient/Somewhat; (3) Dominant constraint; and (N/A) not applicable. 2.6.3 Forestry, natural resources and environment The sub-sector includes water, land and forestry dimensions and their related ecosystems. The main statistical activities are reported by the sub-sector are described below, as presented in the IdCA: ● Most of the main statistical data is provided by the MAWLR every year, focusing on land, water, fertilizer, and pesticide; however, the data is only covering specific portions of the country, depending on the resource area. The latest available data for the sub-sector was collected in 2022, mainly through sample surveys. The core data that is not yet included some water-related aspects such as pollution and irrigation, forage, animal vaccines, soil degradation and emissions. ● Environment and natural resources indicators in the country are presented through the National Accounts Statistics by the NSA, derived from past historical data collected. Although the National Water Accounting was conducted, other agri environmental indicators such land and forestry national accounts have not yet been completed. ● A water survey was conducted in 2022, covering crops and irrigated areas but lacked certain essential agricultural data. No forestry survey was conducted, and no statistical system is dedicated to forestry activities. Additionally, there are 56 regular support staff at the headquarters, 0 dedicated to agricultural statistics, 12 support staff at the regional/local offices, and 0 dedicated to agricultural statistics. In the last 12 months, 2 professional staff have been supported for training in national training institutes. In addition, only 1 staff member attended training for short courses overseas. It should be noted that the ministry has a regular training program for statistical staff, however not sufficient. • Over the past three years, the MFMR has benefited from technical assistance initiatives in the field of aquaculture from China, Iceland, and Japan. • The MFMR plays a significant role in conducting surveys and collecting statistical information on fishery production in the country. While the ministry does not compile certain types of statistical information, it utilizes various IT systems and infrastructure to support its statistical activities. The budget allocation and staff complement reflect the importance placed on statistical work within the MFMR. Critical constraints: The MFMR regards typical constraints faced by agriculture statistics systems in developing countries either as insufficient/somewhat, sufficient, or dominant. The following codes were used for grading, and results are presented in Table 9: Response code: (1) Sufficient; (2) Insufficient/Somewhat; (3) Dominant constraint. The number of field workers for statistical activities, and the technical skills of the available statistical staff were regarded as dominant constraints for the MFMR. Table 9: Ranking of critical constraints from the perspective of the MFMR. 33 ● As of November 2023, the MFMR had a staff complement of 479 regular professional and support staff. Of these, 30 regular professional staff are based at the headquarters, with 26 dedicated to agricultural statistics. The regional/local offices have 381 regular professional staff, with 108 dedicated to agricultural statistics. Additionally, there are 56 regular support staff at the headquarters, 0 dedicated to agricultural statistics, 12 support staff at the regional/local offices, and 0 dedicated to agricultural statistics. In the last 12 months, 2 professional staff have been supported for training in national training institutes. In addition, only 1 staff member attended training for short courses overseas. It should be noted that the ministry has a regular training program for statistical staff, however not sufficient. ● Over the past three years, the MFMR has benefited from technical assistance initiatives in the field of aquaculture from China, Iceland, and Japan. The MFMR plays a significant role in conducting surveys and collecting statistical information on fishery production in the country. While the ministry does not compile certain types of statistical information, it utilizes various IT systems and infrastructure to support its statistical activities. The budget allocation and staff complement reflect the importance placed on statistical work within the MFMR. Critical constraints: The MFMR regards typical constraints faced by agriculture statistics systems in developing countries either as insufficient/somewhat, sufficient, or dominant. The following codes were used for grading and results are presented in Table 9: Response code: (1) Sufficient; (2) Insufficient/Somewhat; (3) Dominant constraint. The number of field workers for statistical activities, and the technical skills of the available statistical staff were regarded as dominant constraints for the MFMR. Table 9: Ranking of critical constraints from the perspective of the MFMR. Constraints Extent1 Number of professional staff at headquarters for statistical activities 2 Number of support staff at headquarters for statistical activities 2 Number of professional staff in the field for statistical activities 2 Number of field workers for statistical activities 3 Technical skills of the available statistical staff 3 STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 27 2.6.3 Forestry, natural resources and environment The sub-sector includes water, land and forestry dimensions and their related ecosystems. The main statistical activities are reported by the sub-sector are described below, as presented in the IdCA: • Most of the main statistical data is provided by the MAWLR every year, focusing on land, water, fertilizer, and pesticide. However, the data is only covering specific portions of the country, depending on the resource area. The latest available data for the sub-sector was collected in 2022, mainly through sample surveys. Some core data still lacks coverage, including aspects related to water pollution, irrigation, forage, animal vaccines, soil degradation, and emissions. • Environment and natural resources indicators in the country are presented through the National Accounts Statistics by the NSA, derived from past historical data collected. Although the National Water Accounting was conducted, other agri-environmental indicators such land and forestry national accounts have not yet been completed. • A water survey was conducted in 2022, covering crops and irrigated areas but lacked certain essential agricultural data. No forestry survey was conducted, and no statistical system is dedicated to forestry activities. • The sub-sector results indicate positive practices in the transparency and accessibility of water and land surveys. The methodology is accessible to the public, and sampling errors are published for most national surveys. Forestry lacks similar practices. • The sector also contributes data to the national Consumer Price Index (CPI) through the National Household Income and Expenditure Survey. Specific indicators include electricity charges, fuel, charcoal, refuse collection and others. • With regards to information technology, the MAWLR lacks a website for official statistics. There is no confirmation of an accessible database. There is limited information on software and IT-related systems. Various methods used for data collection; however, specific software details are unavailable. • The water and land reform departments at the MAWLR head office and regional/local offices has nine regular professional staff each, along with an equal number of regular support staff with training at the headquarters. Forestry sector has sufficient staff and vehicles for statistical activities; however, training is required. • The sector benefits from international technical assistance in covering agricultural statistics. Donors and development partners include German Development Cooperation (GIZ), Global Environment Facility (GEF), Food and Agriculture Organization (FAO), World Food Programme (WFP) and others. 2.7 Agricultural Statistics Capacity Indicator The approach to capacity assessment, as presented in the IdCA Report, involves using a shared standard questionnaire with a core set of questions applicable universally across countries and regions. This methodology ensures consistency in the assessment process and promotes global comparability of data. The framework used is the FAO’s Agriculture and Rural Statistics Capacity Assessment Framework, detailed in the FAO Handbook of 2013. In Namibia, Modules I and II of the standard questionnaires were canvassed and completed by the NSA, while Module III of the standard questionnaire was completed by the MAWLR, MEFT, and MFMR. 2.7.1 Overall ASCI The overall capacity for producing reliable and timely agricultural data is encapsulated in the Agriculture Statistics Capacity Index (ASCI) value. The ASCI values range between 0%-100%, with 100% indicating adequate capacity and 0% indicating inadequate capacity. In Namibia, the assessment was completed in 2013, 2015, 2017 and 2023. Generally, Namibia’s ability and capacity to generate reliable and timely agricultural data shows a decreasing trend. At the baseline in 2013, the estimated ASCI value was 65%, and the estimated 2023 value is 55%. This observed decrease in the capacity to produce reliable and timely agriculture data rationalizes the development and implementation of SPARS. STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 28 Therefore, in order to improve the capacity for agricultural statistics in Namibia, the SPARS should include targeted interventions addressing weaknesses in the prerequisites, input, and output dimensions which are discussed further below. 2.7.2 Prerequisite dimension A critical weakness in the effective running of the National Agricultural Statistics System (NASS) in Namibia is the lack of platforms for dialogue between producers and uses of agricultural data and statistics. Addressing this weakness is critical to ensure relevant data is collected and the needs of various stakeholders are addressed. 2.7.3 Input dimension The allocation of financial, staffing, training, and physical resources is a critical constraint that affects the production of reliable and timely agriculture data and statistics in Namibia. As such, it is crucial that the Namibian SPARS include interventions for leveraging existing resources as well as mobilizing additional resources to improve the availability, quality, and quantity of agricultural data and statistics. 2.7.4 Throughput dimension The lack of agricultural surveys and inability to provide agriculture market price information are the key gaps in the existing agriculture statistics system in Namibia. As such, the Namibian SPARS should include interventions that address these gaps. Additionally, the capacity to undertake agriculture statistics activities in Namibia is further hindered by lack of statistical software capabilities, data collection technologies, and information technology infrastructure. 2.7.5 Output dimension The availability of the minimum set of core data has improved significantly during the assessment period 2013 2023. However, timeliness, data quality, and data accessibility require improvements as decreasing trends are observed in these elements. As such, the Namibian SPARS should include interventions that improve the timely provision of data and statistics; address data quality issues; and make data and statistics accessible to users. 2.8 Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis This section presents the strengths, weaknesses, opportunities, and threats (SWOT) analysis of Namibia’s NASS including main sub-sectoral stakeholders (MAWLR, MEFT and MFMR). The SWOT analysis in this section is synthesized from the 2022 Sector Statistics Plan for Agriculture (Department of Agriculture, Namibia, 2023), 2023-2026 Sector Statistics Plan for Environment (Department of Environment, 2023) and the 2023-2027 NSDS (Namibia Statistics Agency, 2023). The SWOT analysis also includes insights based on desktop reviews of existing legal and institutional frameworks related to agricultural and rural statistics carried out across sub sectors, and the standardized Country Assessment Questionnaire. The results are shown in Annex I, while the summaries are presented below. Strengths • The strengths identified encompass strong national statistics legislation and the presence of statistics units/divisions across various sectors. • Additionally, there are existing databases for capturing and storing data at NSA, MAWLR, and MFMR, supported by a robust data collection infrastructure. • A skilled workforce at sub-sectoral levels, coupled with professional statistical competencies at NSA, facilitates surveys and data analysis for agriculture. • The established data sources and multiple channels for data dissemination, including bulletins and websites, ensure effective information sharing. • The ability to implement international standards and methodologies is evident, with access to international support, funding, and investments from organizations such as SADC, FAO and others. • Moreover, the NSA boasts an established ICT infrastructure. STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 29 Weaknesses • The challenges identified relate to poor coordination and collaboration within key sectors, leading to uncoordinated decision-making, policy formulation, and non-harmonized standards and data collection calendars. • There is a notable lack of professional skills, with limited training and high staff turnover, resulting in insufficient data and poor data management. • Financial constraints hinder consistent annual statistical activities. • The production of statistics is compromised by fragmented databases, data gaps, and non-uniform methodologies, which is further exacerbated by poor quality administrative data found in non-user-friendly formats. • There is a lack of advocacy for statistical awareness, with many statistics remaining unknown. Limited funds and outdated infrastructure, including old computers and inadequate office space, further impede progress. • There is an absence of robust methodologies for agricultural, water, and forestry surveys, and key sub sectors fail to collect data on essential indicators such as price index, food balance sheets, and agri environmental indicators. Opportunities • The Sector Statistics Committee (SSC) exists to promote statistical production, usage, and advocacy for evidence-based planning. This provides significant potential formal collaboration in data collection and standardized methodologies across the sector, and integrating current databases found at sub-sector level. • The established standards from both NSA and international bodies can aid the adoption of national and international standards, classifications, and methodologies; especially at sub-sectoral level to revamp administrative data towards national statistics. • There is a growing demand for official statistics, facilitated by advances in innovative technologies, data collection methods, and reporting. • Data sharing opportunities with regional and international partners are expanding, and digital platforms and communication channels are being leveraged to enhance the dissemination of statistics to broader audiences. • Additionally, there is positive stakeholder support and willingness to contribute to the NASS vision. Threats • As in many countries, the main threat to efforts to improve the agricultural statistics system is the lack of funds. Internal financial constraints are significantly hindering the implementation of surveys and statistical activities, leading to a reliance on external donors, whose support is diminishing. • Statistics hold a low strategic priority in the country, with resources often allocated to competing social and environmental challenges. • There is a conflict in enabling statistics legislation across various sectors, due to low political support. • Additionally, there is a significant dependence on external parties, such as farmers and private stakeholders, for industry data, especially in sectors like biomass and charcoal production. STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 30 CHAPTER 3 - STRATEGIC PLANNING This chapter presents the outcomes of the Planning Phase of the SPARS development process - i.e., Strategic Planning. A three-day consultative workshop was conceived, with key data producers and users, to envision and map the development of agricultural and rural statistics in Namibia for the next five years, 2024/25 2029/30. The ultimate purpose of the workshop was to develop a strategic plan to improve production, processing, dissemination of quality agricultural and rural statistics that not only meets user needs, but also supports decision making and evidence-based policy planning and evaluation. This chapter presents the core components of the Strategic Plan, including strategic issues, strategic direction, strategic objectives, outputs, activities, implementation, and budget. The strategic issues section presents key issues synthesized from the outcomes of the evaluation of the NSS and NASS (i.e., refer to Chapter 2) and considered to have strategic significance. It is on the basis of the strategic issues that the remaining components of the Strategic Plan were conceptualized and designed. The strategic direction presents the Vision, Mission, and Core Values (i.e., adopted from the NSDS) together with the strategic objectives, outputs, and activities. The implementation section presents the implementation arrangement, action plan, monitoring and evaluation plan, and financing/ budget for the strategic plan. 3.1 Strategic Areas The assessment of the NSS and NASS identified a plethora of limitations, weaknesses, and challenges. These issues were synthesized into six strategic issues that were considered during strategic planning. These issues were: 1. Standards: Addressing the fragmentation in data collection practices among key data producers is imperative to ensure the adherence to national and international statistics standards. The absence of a standardized framework for producing, processing, and disseminating administrative data further compounds this challenge. Thus, it is essential to promote widespread adoption of established standards and best practices across all stages of statistical operations. Additionally, the development or adoption of comprehensive standards specifically tailored to administrative data is necessary. By fostering compliance with these standards, including those pertaining to administrative data, we can bolster the quality and comparability of data and statistics generated by diverse producers. 2. Financial: While the NASS currently generates a minimum set of core data, its quality remains suboptimal due to various contributing factors. These include reliance on administrative data with uncertain production practices, model estimations based on outdated survey data, and financial constraints hindering robust statistical activities. To address this, it is imperative to mobilize adequate financial resources to support timely execution of core statistical tasks, particularly surveys. Investing in infrastructure and technology upgrades is equally crucial to enhance the overall efficiency and quality of statistical outputs. 3. Capacity Building: Enhancing the capacity and utilization of technological systems for statistical operations is essential for improving data collection, processing, and dissemination. The assessment of NASS revealed the prevalence of outdated computer systems and databases among key data producers, leading to compatibility issues with modern technologies. Moreover, the lack of integration between ministry databases and government systems impedes data accessibility. Hence, prioritizing investments in integrated databases and staff training is paramount to leverage technological advancements, thereby enhancing the accuracy, accessibility, and timeliness of statistical outputs. 4. Collaboration and Coordination: Effective collaboration and coordination among stakeholders within NASS are imperative for optimizing the statistical ecosystem. The current lack of robust platforms for facilitating such collaboration results in fragmented efforts and inefficient resource utilization. While bilateral Memorandums of Understanding (MoUs) between the NSA and stakeholders address specific issues, they STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 31 often neglect sector-wide concerns. Therefore, enhancing mechanisms, including establishing collaborative platforms, is vital for fostering partnerships and communication among stakeholders. This approach will enable synergies and minimize duplication of efforts, ultimately enhancing the efficiency of statistical endeavours. 5. Expanding the Scope and Disaggregation of Statistics: Expanding the scope and granularity of statistical data produced by NASS is essential for gaining comprehensive insights into agriculture and rural sectors. The assessment identified several critical data topics that are currently overlooked, alongside limitations in disaggregation, particularly in administrative records. Thus, broadening the range of data topics and enhancing disaggregation capabilities are pivotal for facilitating nuanced analysis and informed decision making in policy formulation, implementation, and evaluation. 6. Awareness: Addressing the prevailing lack of awareness regarding the significance of agricultural and rural statistics is crucial for prioritizing and adequately funding statistical initiatives. This gap in understanding contributes to the neglect of vital sample surveys such as agricultural, water, and forestry surveys. Moreover, inadequate dissemination of statistical reports further exacerbates this issue. To rectify this, there is a need to develop and implement a robust communication and advocacy strategy. By enhancing stakeholder awareness of the value of statistical data, we can garner increased support and recognition for statistical initiatives, ultimately amplifying their impact. Overall, addressing these strategic areas through targeted interventions will be key to enhancing the quality, relevance, and accessibility of agricultural and rural statistics, ultimately supporting evidence-based decision making and policy formulation in these sectors. 3.2 Strategic Direction Based on the strategic issues presented above, this section presents a strategic framework highlighting the Vision, Mission, and Core Values, as well as the strategic objectives, outputs, and activities. 3.2.1 Vision statement A well-resourced and coordinated National Agricultural Statistics System that supports evidence-based planning, that is responsive to user needs. 3.2.2 Mission statement To implement a sustainable NASS that provides comprehensive data using innovative and harmonized methods for the collection, processing, and dissemination of agricultural and rural statistics. 3.2.3 Core values The following are the core values for Namibian SPARS, which were adopted from the NSDS: • Accuracy: NASS endeavours to produce statistics with a high degree of precision • Accountability: NASS that takes absolute responsibility in their statistical productions and stakeholders • Timeliness: NASS strives to produce and disseminate statistics in line with their Advanced Release Calendar (ARC) • Transparency: NASS proactively make available methods and standards used in their data production and dissemination processes 3.3 Strategic Objectives, Outputs, and Activities Based on the strategic issues, vision, and mission, six strategic objectives and their associated outputs and activities were formulated. Table 10 outlines the strategic foundation of SPARS in Namibia. It highlights the strategic areas with their concomitant strategic objectives, outputs, and activities. The strategic areas that the Namibian SPARS will focus on have been highlighted above. As such, the discussion below Table 10 presents a cursory overview of the strategic objectives and their associated outputs and activities. STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 32 Table 10: Strategic objectives, outputs, and activities 43 ➔ Accountability: NASS that takes absolute responsibility in their statistical productions and stakeholders. ➔ Timeliness: NASS strives to produce and disseminate statistics in line with their Advanced Release Calendar (ARC). ➔ Transparency: NASS proactively make available methods and standards used in their data production and dissemination processes. 3.3 Strategic Objectives, Outputs, and Activities Based on the strategic issues, vision, and mission, six strategic objectives and their associated outputs and activities were formulated. Table 10 outlines the strategic foundation of SPARS in Namibia. It highlights the strategic areas with their concomitant strategic objectives, outputs, and activities. The strategic areas that the Namibian SPARS will focus on have been highlighted above. As such, the discussion below Table 10 presents a cursory overview of the strategic objectives and their associated outputs and activities. Table 10: Strategic objectives, outputs, and activities Strategic Area Objectives Outputs Activities Standards 1 To promote the use of and adherence to national and international standards and best practices in all statistical production, processing, and dissemination. 1.1 Increased Use of Statistical Standards and Methods. 1.1.1 Conduct a comprehensive mapping of statistical methods and standards across key data producers for both surveys and administrative data. 1.1.2 Conduct needs assessment for standardising data production processes across key producers. 1.1.3 To sensitise and train key data producers on statistical standards. 1.1.4 Improving data collection, processing, and dissemination activities to meet the statistical standards across key data producers. 44 1.1.5 Develop a Standard for Administrative Data. 1.2 Improved Data Comparability. 1.2.1 Conduct data comparability assessments across key producers. 1.2.2 Review and update the Namibia Compendium of Statistical and Spatial concepts and definitions. 1.2.3 Develop a Compendium of best practice methods for collecting agriculture and rural statistics. Financial 2 To mobilize financial resources for the timely undertaking of agriculture and rural statistical activities. 2.1 Increased Budget Allocation. 2.1.1 Compile budgets for statistical activities on the statistical calendar. 2.1.2 Conduct advocacy engagements to lobby for funding the statistical activities. 2.2 Diversified Funding Sources. 2.2.1 Develop and implement a financial resource mobilization strategy. 2.3 Improved Budgeting Efficiency. 2.3.1 Track budget execution rate based on allocated funds. Capacity Building 3 To strengthen capacity and the use and development of modern technological systems for collecting, processing, and disseminating agriculture and rural statistics. 3.1 Enhanced Staff Capacity. 3.1.1 Conduct needs assessment for statistical production using latest technologies. 3.1.2 Conduct targeted training workshop on relevant up-to-date technologies for data collection, processing, management, and dissemination. 3.1.3 Promote knowledge sharing among key data producers on new technology and systems for collecting, processing, and disseminating statistics. 3.2 Improved Data Collection Efficiency. 3.2.1 Identify and evaluate new technologies for data collection, processing and dissemination e.g., GIS and remote sensing. 3.2.2 Invest in technology infrastructure for GIS and remote sensing 3.3 Streamlined data management and dissemination systems. 3.3.1 Invest in an integrated and interactive agricultural statistical management system. 3.3.2 Develop databases at the Ministry of Fisheries and Marine Resource (MFMR) and Ministry of Environment, Forestry and Tourism (MEFT) that can be integrated with the Office of the Prime Minister (OPM) system. 3.3.3 Linking the databases at the Ministry of Fisheries and Marine Resource (MFMR) and Ministry of Environment, Forestry and Tourism (MEFT) to OPM system integration. 3.3.4 Expand the data exchange initiative (UXP) by NSA with OPM to other key data producers in the agriculture sector Collaboration and coordination 4 To strengthen stakeholder 4.1.1 Undertake a mapping exercise to identify key stakeholders that will be Strategic Area Objectives Outputs Activities STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 33 45 collaboration and coordination. 4.1 Established Stakeholder Engagement Mechanisms. included as part of the SPARS Secretariat (i.e., Sector Statistics Coordinators Committee). 4.1.2 Establish a Sector-Wide Memorandum of Understanding (MoU) for SPARS Implementation (including a validation workshop of minimum set of core data; data sharing agreements). 4.1.3 Strengthen the SPARS Secretariat (i.e., Sector Statistics Coordinators Committee) to provide ongoing guidance and feedback on statistical activities 4.1.4 Organize regular stakeholder forums (users and producers). 4.2 Improved Data Relevance for Stakeholders. 4.2.1 Develop targeted training sessions for stakeholders on data access, interpretation, and utilization. 4.2.2 Conduct user satisfaction surveys. 4.3 Streamlined statistical production, processing, and dissemination practices. 4.3.1 Develop a statistical calendar for the SPARS period and regularly update it. 4.3.2 Establish joint data collection initiatives. Expanding the scope and disaggregation of agriculture and rural statistics. 5 To expand the scope and enhance the disaggregation of agriculture and rural statistics. 5.1 Expanded indicator coverage to gather information from diverse subject areas and to enhance disaggregation. 5.1.1 Review and improve existing data collection tools for administrative records. 5.1.2 Conduct stakeholder consultations on new data topics. 5.2 Enhance data collection tools and methods. 5.2.1 Improve and/or develop tools and methods used for data collection e.g., remote sensing, surveying, sampling, mobile data collection tools, etc. 5.3 An integrated survey program that address existing data gaps. 5.3.1 Regularly prioritize areas for survey implementation based on the significance of data gaps and their impact on decision making. 5.3.2 Implement an integrated censuses and surveys. (See annex) Awareness 6 To strengthen awareness about the importance and use of national agriculture and rural statistics. 6.1 Increased data advocacy. 6.1.1 Identify and appoint a SPARS champion in Cabinet. (Consider technical champion) 6.1.2 Develop and implement strategy for advocacy. 6.1.3 Conduct and participate in stakeholder engagements. 6.1.4 Create various communication products for different statistical themes targeting different audiences. 6.1.5 Conduct media briefings or press releases for Namibia’s national agriculture and rural statistics. 44 1.1.5 Develop a Standard for Administrative Data. 1.2 Improved Data Comparability. 1.2.1 Conduct data comparability assessments across key producers. 1.2.2 Review and update the Namibia Compendium of Statistical and Spatial concepts and definitions. 1.2.3 Develop a Compendium of best practice methods for collecting agriculture and rural statistics. Financial 2 To mobilize financial resources for the timely undertaking of agriculture and rural statistical activities. 2.1 Increased Budget Allocation. 2.1.1 Compile budgets for statistical activities on the statistical calendar. 2.1.2 Conduct advocacy engagements to lobby for funding the statistical activities. 2.2 Diversified Funding Sources. 2.2.1 Develop and implement a financial resource mobilization strategy. 2.3 Improved Budgeting Efficiency. 2.3.1 Track budget execution rate based on allocated funds. Capacity Building 3 To strengthen capacity and the use and development of modern technological systems for collecting, processing, and disseminating agriculture and rural statistics. 3.1 Enhanced Staff Capacity. 3.1.1 Conduct needs assessment for statistical production using latest technologies. 3.1.2 Conduct targeted training workshop on relevant up-to-date technologies for data collection, processing, management, and dissemination. 3.1.3 Promote knowledge sharing among key data producers on new technology and systems for collecting, processing, and disseminating statistics. 3.2 Improved Data Collection Efficiency. 3.2.1 Identify and evaluate new technologies for data collection, processing and dissemination e.g., GIS and remote sensing. 3.2.2 Invest in technology infrastructure for GIS and remote sensing 3.3 Streamlined data management and dissemination systems. 3.3.1 Invest in an integrated and interactive agricultural statistical management system. 3.3.2 Develop databases at the Ministry of Fisheries and Marine Resource (MFMR) and Ministry of Environment, Forestry and Tourism (MEFT) that can be integrated with the Office of the Prime Minister (OPM) system. 3.3.3 Linking the databases at the Ministry of Fisheries and Marine Resource (MFMR) and Ministry of Environment, Forestry and Tourism (MEFT) to OPM system integration. 3.3.4 Expand the data exchange initiative (UXP) by NSA with OPM to other key data producers in the agriculture sector Collaboration and coordination 4 To strengthen stakeholder 4.1.1 Undertake a mapping exercise to identify key stakeholders that will be STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 34 Strategic Objective # 1: To promote the use of and adherence to national and international standards and best practices in all statistical production, processing, and dissemination. This objective aims to enhance the quality and reliability of statistical data by ensuring alignment with established standards and best practices. Through various outputs and activities, the objective seeks to address existing disparities in data collection practices and promote uniformity across key data producers. The following is a description of the envisaged outputs and activities for this objective: Output 1.1: Increased Use of Statistical Standards and Methods. This output focuses on fostering widespread adoption of statistical standards and methods among key data producers. Activities include conducting a comprehensive mapping of statistical standards across key data producers for both survey and administrative data; conduct needs assessments for standardising data production process across key producers; sensitising and training key data producers on statistical standards, and improving data collection, processing, and dissemination activities to meet the statistical standards across key data producers; and develop a Standard for Administrative Data. Output 1.2: Improved Data Comparability. This output targets enhancing the comparability of statistical data across different producers. Activities involve conducting data comparability assessments; review and update the Namibia Compendium of Statistics and Spatial Concepts and Definitions; and developing a Compendium of Best Practice Methods for collecting agriculture and rural statistics. Strategic Objective # 2: To mobilize financial resources for the timely undertaking of statistical activities. This objective focuses on securing adequate financial resources to support timely execution of statistical activities. Through various outputs and activities, the objective aims to address budgetary constraints and ensure sustained funding for statistical initiatives. The following is a description of the envisaged outputs and activities for this objective: Output 2.1: Increased Budget Allocation. This output aims to secure increased budget allocation for statistical activities. Activities include compiling budgets for statistical activities, conducting advocacy engagements to lobby for funding, and implementing measures to track budget execution rates. Output 2.2: Diversified Funding Sources. This output targets diversifying funding sources to reduce reliance on limited financial streams. Activities involve developing and implementing a resource mobilization strategy to attract funding from various sources. Output 2.3: Improved Budgeting Efficiency. This output seeks to enhance the efficiency of budget utilization for statistical activities. Activities include tracking budget execution rates based on allocated funds and 45 collaboration and coordination. 4.1 Established Stakeholder Engagement Mechanisms. included as part of the SPARS Secretariat (i.e., Sector Statistics Coordinators Committee). 4.1.2 Establish a Sector-Wide Memorandum of Understanding (MoU) for SPARS Implementation (including a validation workshop of minimum set of core data; data sharing agreements). 4.1.3 Strengthen the SPARS Secretariat (i.e., Sector Statistics Coordinators Committee) to provide ongoing guidance and feedback on statistical activities 4.1.4 Organize regular stakeholder forums (users and producers). 4.2 Improved Data Relevance for Stakeholders. 4.2.1 Develop targeted training sessions for stakeholders on data access, interpretation, and utilization. 4.2.2 Conduct user satisfaction surveys. 4.3 Streamlined statistical production, processing, and dissemination practices. 4.3.1 Develop a statistical calendar for the SPARS period and regularly update it. 4.3.2 Establish joint data collection initiatives. Expanding the scope and disaggregation of agriculture and rural statistics. 5 To expand the scope and enhance the disaggregation of agriculture and rural statistics. 5.1 Expanded indicator coverage to gather information from diverse subject areas and to enhance disaggregation. 5.1.1 Review and improve existing data collection tools for administrative records. 5.1.2 Conduct stakeholder consultations on new data topics. 5.2 Enhance data collection tools and methods. 5.2.1 Improve and/or develop tools and methods used for data collection e.g., remote sensing, surveying, sampling, mobile data collection tools, etc. 5.3 An integrated survey program that address existing data gaps. 5.3.1 Regularly prioritize areas for survey implementation based on the significance of data gaps and their impact on decision making. 5.3.2 Implement an integrated censuses and surveys. (See annex) Awareness 6 To strengthen awareness about the importance and use of national agriculture and rural statistics. 6.1 Increased data advocacy. 6.1.1 Identify and appoint a SPARS champion in Cabinet. (Consider technical champion) 6.1.2 Develop and implement strategy for advocacy. 6.1.3 Conduct and participate in stakeholder engagements. 6.1.4 Create various communication products for different statistical themes targeting different audiences. 6.1.5 Conduct media briefings or press releases for Namibia’s national agriculture and rural statistics. STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 35 implementing measures to optimize resource allocation. Strategic Objective # 3: To strengthen capacity and the use of systems and technology for collecting, processing, and disseminating statistics. This objective aims to enhance the capacity of stakeholders and leverage technology to improve statistical operations. Through various outputs and activities, the objective seeks to address gaps in skills and infrastructure to support data collection, processing, and dissemination. Output 3.1: Enhanced Staff Capacity. This output focuses on building the capacity of staff involved in statistical production. Activities include conducting needs assessments, organizing training workshops on relevant technologies, and promoting knowledge sharing among stakeholders. Output 3.2: Improved Data Collection Efficiency. This output targets enhancing the efficiency of data collection processes through technological advancements. Activities involve identifying and evaluating new technologies, investing in technology infrastructure, and leveraging GIS and remote sensing technologies. Output 3.3: Streamlined Data Management and Dissemination Systems. This output aims to streamline data management and dissemination systems to improve accessibility and usability. Activities include investing in integrated management systems, developing databases for key ministries, and facilitating integration between different databases. Strategic Objective # 4: To strengthen stakeholder collaboration and coordination. This objective focuses on enhancing collaboration and coordination among stakeholders involved in statistical activities. Through various outputs and activities, the objective aims to foster partnerships, improve stakeholder engagement, and enhance the relevance of statistical data for decision-making. Output 4.1: Established Stakeholder Engagement Mechanisms. This output aims to establish effective mechanisms for engaging stakeholders in statistical activities. Activities include mapping key stakeholders; Establishing a Sector-Wide Memorandum of Understanding (MoU) for SPARS Implementation; and strengthening the SPARS Secretariat (i.e., Sector Statistics Coordinators Committee), and providing ongoing guidance and feedback. Output 4.2: Increased Stakeholder Participation. This output targets increasing stakeholder participation in statistical initiatives. Activities involve organizing regular forums, developing training programs, establishing joint data collection initiatives, and facilitating data sharing agreements. Output 4.3: Improved Data Relevance for Stakeholders. This output focuses on ensuring that statistical data meets the needs of stakeholders. Activities include conducting validation workshops for core data; developing training sessions for stakeholders on data utilization, and enhancing stakeholder engagement in data interpretation processes; and conducting a user satisfaction survey that will include questions on perceived quality of agricultural and rural statistics and the services provided, extent to which statistics influence, policies and/or decisions, ease and effectiveness of obtaining access to these statistics, and information about the users, such as background, frequency of use, complexity and level of detail required. Strategic Objective # 5: To expand the scope and disaggregation of statistics. . This objective aims to broaden the scope and granularity of statistical data to provide more comprehensive insights. Through various outputs and activities, the objective seeks to expand data coverage, enhance data collection tools and methods, and improve disaggregation capabilities. Output 5.1: Expanded Indicator Coverage and Enhanced Disaggregation. This output targets expanding the coverage of statistical indicators and enhancing disaggregation capabilities. Activities include reviewing data collection tools, conducting stakeholder consultations, and collecting or including new variables or data topics in planned surveys. STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 36 Output 5.2: Enhance Data Collection Tools and Methods. This output focuses on improving data collection tools and methods to enhance efficiency and accuracy. Activities include developing and improving tools for data collection, such as remote sensing and mobile data collection, to ensure robust data gathering processes. Output 5.3: An Integrated Survey Program. This output seeks to close existing data gaps in agricultural and rural statistics within Namibia. Its activities commence with a comprehensive assessment scrutinizes existing data sources and methodologies, pinpointing areas where information inadequacies hinder informed decision making. Subsequently, its second activity prioritizes survey implementation by weighing the significance of data gaps against their potential impact on policy formulation and program planning, ensuring efficient resource allocation. This culminates into another activity, where a meticulously crafted timeline and budget are established, harmonizing survey activities with the broader statistical calendar to ensure timeliness and fiscal prudence. Strategic Objective # 6: To strengthen awareness about the importance of national agriculture and rural statistics. This objective aims to increase awareness of the significance of agricultural and rural statistics among stakeholders. Through various outputs and activities, the objective seeks to advocate for statistical initiatives, engage stakeholders through communication strategies, and disseminate statistical information effectively. Output 6.1: Increased Data Advocacy. This output targets increasing advocacy efforts to raise awareness of the importance of agricultural and rural statistics. Activities include appointing a SPARS champion, developing advocacy strategies, engaging stakeholders through various channels, and conducting media briefings or press releases. By addressing these strategic objectives through the outlined outputs and activities, the Strategic Plan for Agriculture and Rural Statistics (SPARS) for Namibia endeavours to enhance the quality, accessibility, and relevance of statistical data to support evidence-based decision-making and policy formulation in the agricultural and rural sectors. 3.4 Implementation The implementation of this strategic plan marks a pivotal juncture in its trajectory, embodying the culmination of meticulous planning and strategic foresight. It is during this critical phase that the efficacy of the strategic plan is put to the test, where the meticulous execution of outlined strategies and concerted efforts of all stakeholders become imperative. The success of the strategic plan hinges on the meticulous execution of delineated activities, the judicious allocation of resources, and the unwavering commitment of all involved parties. With the implementation phase serving as the crucible wherein aspirations are transformed into tangible outcomes, its effective execution paves the way for the realization of expected results, shaping the trajectory of agricultural and rural development in Namibia. Thus, the diligence and dedication invested in this phase stand as the harbinger of success, underscoring its pivotal role in the attainment of overarching objectives and the advancement of agriculture and rural statistics in Namibia. To this end, this section provides an overview of the implementation arrangements as well as the action plan for this strategic plan. 3.4.1 Implementation arrangements The implementation of Namibia’s Strategic Plan for Agriculture and Rural Statistics (SPARS) from the 2024/25 to 2029/30 financial year will be led by the Namibia Statistics Agency (NSA), in close collaboration with the Sector Statistics Coordinators Committee (SSCC) that was constituted in the design of the SPARS. The NSA will assume the role of the Secretariat for the SPARS, with specific units within the agency—namely, Agriculture, Data Quality Assurance, and NSS Coordination—being designated as responsible for its coordination and execution. As such, the NSA with the representatives of MAWLR, MFMR, MEFT in the SSCC will constitute a SPARS Secretariat that will operationalize the implementation of SPARS. The SPARS Secretariat will report to the SDC, among the committee that was constituted in the design of the SPARS. The role of the SDC is to provide strategic direction for the implementation of SPARS. STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 37 Furthermore, it would be crucial, during implementation, for the SPARS Secretariat to actively engage key stakeholders that were instrumental in the development of this SPARS. Their contribution through resource allocation and participation in planned activities, along with an emphasis on effective data utilization, statistical advocacy, capacity building, financing, and coherent governance mechanisms, will be instrumental in realizing the SPARS objectives. It is imperative that the implementation of this SPARS primarily focuses on enhancing institutional and organizational capacities and leveraging key drivers of strategic success, including human resources, streamlined processes, and innovative technologies. Therefore, it is imperative for the designated SPARS Secretariat to put in place a sector-wide MoU - i.e., as proposed by Activity 4.1.2 - to facilitate the smooth execution of the SPARS. 3.4.2 Action plan The action plan for implementing the SPARS is outlined in Annex II. It delineates activities corresponding to each output and sub-output, specifying the responsible party, scheduled timeframe, and inter-relationships between activities. During the initial two years of SPARS implementation (2024 and 2025), the action plan provides a quarterly breakdown of activities. Subsequent years offer a broader overview of planned activities for each year. Detailed annual action plans will be formulated as part of the SPARS annual reports and presented for endorsement by the SPARS Secretariat. 3.4.3 Monitoring and Evaluation Plan A Monitoring and Evaluation (M&E) Plan is indispensable for ensuring the successful execution of the Strategic Plan for Agriculture and Rural Statistics (SPARS). The primary objectives of the M&E system are twofold: to ensure the attainment of SPARS’s strategic goals and to monitor the inputs, activities, and outputs of SPARS. This approach enables stakeholders to gauge the trajectory of SPARS implementation, empowering the SPARS Secretariat to enact corrective measures to meet performance targets effectively. The M&E system for SPARS in Namibia is structured upon a logical framework, detailed in Annex III. This framework delineates performance indicators for SPARS’s vision, strategic objectives, and outputs, along with baseline, mid-line, and endline targets or anticipated trends for each indicator. Moreover, the logical framework elucidates means of verification and core assumptions. The performance indicators for the vision are derived from those utilized by the African Development Bank (AfDB) in its Country Assessment for Capacity to collect, produce, and disseminate agricultural and rural statistics. Thus, the evaluation of SPARS’s vision incorporates indicators such as the Agriculture Statistics Capacity Index (ASCI), prerequisite dimension score, input dimension score, throughput dimension score, and output dimension score, with verification conducted using the AfDB framework for assessing capacity in agricultural and rural statistics. Each indicator includes status updates for the baseline year (2023/24) alongside targets for the midline (2026/27) and end-line (2029/30) years. Additionally, the logical framework defines performance indicators for each output, with the baseline status of these indicators estimated during 2023/24. Anticipated trends for these indicators indicate a progressive increase for mid-line (2026/27) and end-line (2029/30) years, verified through annual, mid-line, and end-line reports prepared by the SPARS Secretariat. The SPARS Secretariat will produce an annual report outlining progress in implementing the SPARS action plan, highlighting potential issues affecting output delivery or strategic objective achievement. This report will be submitted to the Statistics Development Committee (SDC) for review during its annual meeting, encompassing: • Progress on the action plan, including activities conducted and outputs generated. • Financial overview of SPARS activities. • Updated action plan and financing scheme for the ensuing year. • Trends in output performance indicators. • Identifiable problems and proposed solutions. STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 38 A mid-term evaluation is slated for 2026/27, with the SPARS Secretariat, supported by national/international consultants if necessary, drafting an evaluation report. This report will assess SPARS performance against 2026/27 targets outlined in the logical framework, potentially recommending adjustments to inputs, activities, or outputs, subject to review and endorsement by the SDC. A final evaluation will be conducted in 2029/30, led by the SPARS Secretariat with requisite support. This evaluation will scrutinize SPARS achievements vis-à-vis targets and its contribution toward agricultural and rural statistics’ strategic goals and vision in Namibia. Additionally, the final evaluation will document lessons learned and proffer recommendations for further developments in Namibia’s agricultural and rural statistics system. 3.4.4 Financing To successfully implement the SPARS action plan, it will be necessary to mobilize considerable resources. The tentative costs for implementing the SPARS activities for the period, 2024/25-2029/30, is estimated at N$608,038,344.38, which is U$34,692,513.87. The breakdown of the estimated cost by activities is presented in Annex IV and summarized by strategic objective in the table below. However, it important to note that the propose of appointing a SPARS Coordinator, as suggested in Implementation Arrangement, section 3.4.1, has not been costed. Should the propose of the SPARS Coordinator be endorsed, it will be important to include the associated costs into the overall SPARS budget. Table 11: Estimated cost of SPARS 2024/25 - 2029/30 (excluding costs of sample surveys) Strategic Objectives ShareBudget (N$’000) Strategic objective 5 is by far the costliest accounting for approximately 94% of the SPARS budget. This strategic objective includes outputs and activities related to data collection through censuses and sample surveys. Most of the funds required to implement these activities are secured through government budgetary allocations. STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 39 Share REFERENCES Africa Development Bank (2012). Strategy for the harmonization of statistics in Africa. African Development Bank. Retrieved from https://au.int/sites/default/files/documents/34580-doc-34577-doc-shasa ii strategy eng full web.pdf Carfagna, E., Vogel, F., et al. (2012). Action plan of the global strategy to improve agricultural and rural statistics. FAO. FAO (2016). Strategic Plans for Agricultural and Rural Statistics. Food; Agriculture Organization of the United Nations (FAO). Retrieved from https://www.fao.org/3/cb3126en/CB3126EN.pdf GIZ (Deutsche Gesellschaft für Internationale Zusammenarbeit). (2022). Sector Brief Namibia: Agriculture. Retrieved from https://www.giz.de/en/downloads/giz2022-en-namibia-agriculture.pdf GRN. (2020). Harambee prosperity plan II 2021-2025. Windhoek. Namibia. Retrieved from http://hppii.gov. na/wp-content/uploads/2021/03/HPP2.pdf Ministry of Environment, Forestry and Tourism. (2023). Sector statistics plan for the department of environment. MAWLR (Ministry of Agriculture, Water and Land Reform). (2023). Sector statistics plan for the department of agriculture. MAWLR (Ministry of Agriculture, Water and Land Reform). (2017). Concept Note - Harambee Comprehensively Coordinated and Integrated Agricultural Development Programme (HACCIADEP). Namibia Statistics Agency. (2021a). National statistics system Namibia. Namibia Statistics Agency. Retrieved from https://nsa.nsa.org.na/wp-content/uploads/2023/07/NSDS-Report.pdf Namibia Statistics Agency (2021b). NSA strategic plan. Namibia Statistics Agency. Retrieved from https://cms. my.na/assets/documents/p1btu9v8um1jj33fpn6r15dd12n94.pdf Namibia Statistics Agency (2023). Namibia statistical development strategy 2023/24-2026/27. Retrieved from https://nsa.nsa.org.na/wp-content/uploads/2023/07/NSDS-Report.pdf NPC. (2004). Vision 2030: Namibia’s long-term vision for sustainable development. Retrieved from https:// www.npc.gov.na/wp-content/uploads/2021/11/vision 2030.pdf NPC. (2017). Namibia’s 5th National Development Plan (NDP5), 2017-2022. Windhoek. Namibia. Retrieved from https://www.npc.gov.na/wp-content/uploads/2021/11/NDP5.pdf Statistics act 9 of 2011. (2011). Namibia Government. Retrieved from https://www.lac.org.na/laws/ annoSTAT/Statistics%20Act%209%20of%202011.pdf UNDESA. (2022). The sustainable development goals report 2022. New York, USA: United Nations. Retrieved from https://unstats.un.org/sdgs/report/2022/The-Sustainable-Development-Goals-Report-2022.pdf World Bank. (2022). World Development Indicators. Retrieved from https://databank.worldbank.org/source/ world-development-indicators STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 40 ANNEXURES ANNEX I - SWOT ANALYSIS SWOT (strengths, weaknesses, opportunities, threats) analysis of Namibia’s National Agricultural Statistics System (NASS) including main sub-sectoral stakeholders; MAWLR, MEFT and MFMR. 54 ANNEXURES ANNEX I - SWOT ANALYSIS SWOT (strengths, weaknesses, opportunities, threats) analysis of Namibia’s National Agricultural Statistics System (NASS) including main sub-sectoral stakeholders; MAWLR, MEFT and MFMR. Strengths Weaknesses · Strong national statistics legislation. · Presence of Statistics Units/Divisions in various sectors. · Existing databases for capture and storing data at NSA, MAWLR and MFMR; with well-established data collection infrastructure. · Presence of a skilled workforce at sectoral levels and core statistical competencies at NSA capable of conducting surveys and analysing data. · Availability of transportation for field activities. · Established data sources and various channels for data dissemination such as reports, bulletins, and websites. · Ability to implement international agreements, standards, and methodologies. · Access to international support, funding and investments from organizations like SADC, FAO and others to strengthen statistical production. · Established ICT infrastructure at NSA. · Coordination: poor coordination and collaboration within the key sectors; poor coordination of policies towards statistical production; uncoordinated decision making in the sector; lack of harmonised standards and data collection calendars are not harmonised · Skills: insufficient professional skills, advanced software skills; training within sector is generally not prioritized; loss of skilled staff due to high staff turnover; limited field workers for statistical activities. · Financial resources: insufficient funding; no budget lines for consistent annual statistical activities. · Production of statistics: poor data collection, management, analysis and reporting: fragmented databases, data gaps, no harmonised methodology for statistics in the sector; non-user-friendly data format; poor data quality especially for administrative data. · Reporting and data dissemination is not consistent and often not sufficient to reach a wide range of recipients. · Statistical awareness and use: Poor advocacy for statistical awareness; not all statistics are known. · Limited funds, ICT advancement for early warning, building space for office; old computers · Insufficient sound methodology implemented for agricultural, water and forestry surveys. · Key sub-sectors do not collect data on price index, food balance sheets and Agri environment indicators. Opportunities Threats Strengths Weaknesses STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 41 54 ANNEXURES ANNEX I - SWOT ANALYSIS SWOT (strengths, weaknesses, opportunities, threats) analysis of Namibia’s National Agricultural Statistics System (NASS) including main sub-sectoral stakeholders; MAWLR, MEFT and MFMR. Strengths Weaknesses · Strong national statistics legislation. · Presence of Statistics Units/Divisions in various sectors. · Existing databases for capture and storing data at NSA, MAWLR and MFMR; with well established data collection infrastructure. · Presence of a skilled workforce at sectoral levels and core statistical competencies at NSA capable of conducting surveys and analysing data. · Availability of transportation for field activities. · Established data sources and various channels for data dissemination such as reports, bulletins, and websites. · Ability to implement international agreements, standards, and methodologies. · Access to international support, funding and investments from organizations like SADC, FAO and others to strengthen statistical production. · Established ICT infrastructure at NSA. · Coordination: poor coordination and collaboration within the key sectors; poor coordination of policies towards statistical production; uncoordinated decision making in the sector; lack of harmonised standards and data collection calendars are not harmonised · Skills: insufficient professional skills, advanced software skills; training within sector is generally not prioritized; loss of skilled staff due to high staff turnover; limited field workers for statistical activities. · Financial resources: insufficient funding; no budget lines for consistent annual statistical activities. · Production of statistics: poor data collection, management, analysis and reporting: fragmented databases, data gaps, no harmonised methodology for statistics in the sector; non-user-friendly data format; poor data quality especially for administrative data. · Reporting and data dissemination is not consistent and often not sufficient to reach a wide range of recipients. · Statistical awareness and use: Poor advocacy for statistical awareness; not all statistics are known. · Limited funds, ICT advancement for early warning, building space for office; old computers · Insufficient sound methodology implemented for agricultural, water and forestry surveys. · Key sub-sectors do not collect data on price index, food balance sheets and Agri-environment indicators. Opportunities Threats 55 · Potential for improving and integrating current databases. · Mechanisms exist for formal collaboration in data collection and standardized methodologies (MoUs signed with NSA) · Existence of Sector Statistics Committee (SSC) to enhance the need for statistical production and usage, and advocacy for evidence-based planning. · Existence of the National Statistics Development Strategy. · Standards from NSA & internationally exist. · Increased use of national and international standards, classifications, and methodologies/ guidelines · Improved regional and international collaborations to improve synergies, knowledge sharing and capacity building to enhance statistical skills. · Improved coordination with NSA and other sectors to execute statistical functions · Increasing demand for official statistics · Advances in innovative technologies, data collection methods and reporting. · Data sharing opportunities with regional and international partners · Leveraging digital platforms and communication channel to improve the dissemination of statistics to wider audiences · Positive support from stakeholders and willingness to contribute to the NASS vision, willing partners both locally and internationally for collaboration and support. · Training facility in the field of Statistics · Leveraging digital platforms and communication channels to improve the dissemination of statistics to wider audiences. · Financial constraints to facilitate the implementation of surveys and other statistical activities; reliance on external donors for sufficient funds and diminishing development partners’ support · Low strategic priority for statistics in the country; competing priority for resources due to social and environmental challenges · Conflict in enabling statistics legislations across the sectors · Failure to meet stakeholder expectations · Dependence on external parties such as farmers and private stakeholders for industry for various data (e.g., biomass/charcoal production industry) Opportunities Threats STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 42 ANNEX II - ACTION PLAN STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 42 ANNEX II - ACTION PLAN 56 ANNEX II - ACTION PLAN 2026/27 2027/28 2028/29 Q3 Q4 Q1 Q2 Q3 Q4 Output 1.1 Increased Use of Statistical Standards and Methods 1.1.1 Conduct a comprehensive mapping of statistical methods and standards across key data producers for both surveys and administrative data 1 NSA 1.1.2 Conduct needs assessment for standardising data production processes across key producers 1 NSA 1.1.3 To sensitise and train key data producers on statistical standards 1 NSA 1.1.4 Improve data collection, processing, and dissemination activities to meet the statistical standards across key data producers 1 NSA 1.1.5 Develop a standard for administrative data 1 NSA Output 1.2 Improved Data Comparability 1.2.1 Conduct data comparability assessments across key producers 1 NSA 1.2.2 Review and update the Namibia compendium of Statistical and Spatial concepts and definitions 1 NSA 1.2.3 Develop a compendium of best practice methods for collecting agriculture and rural statistics 1 NSA Output 2.1 Increased Budget Allocation 2.1.1 Compile annual budgets for statistical activities on the statistical calendar 1 NSA/MAWLR/MFMR/MEFT 2.1.2 Conduct advocacy engagements to lobby for funding the statistical activities 1 NSA/MAWLR/MFMR/MEFT Output 2.2 Diversified Funding Sources 2.2.1 Develop and implement a financial resource mobilization strategy 1 NSA Output 2.3 Improved Budgeting Efficiency 2.3.1 Track budget execution rate based on allocated funds 1 NSA/MAWLR/MFMR/MEFT Output 3.1 Enhanced Staff Capacity 3.1.1 Conduct needs assessment for statistical production using latest technologies 1 NSA 3.1.2 Conduct targeted training workshop on relevant up-to-date technologies for data collection, processing, management, and dissemination 1 NSA 3.1.3 Promote knowledge sharing among key data producers on new technology and systems for collecting, processing, and disseminating statistics 1 NSA Output 3.2 Improved Data Collection Efficiency 3.2.1 Identify and evaluate new technologies for GIS and remote sensing 1 NSA/MAWLR/MFMR/MEFT 3.2.2 Invest in technology infrastructure for GIS and remote sensing 1 NSA/MAWLR/MFMR/MEFT Output 3.3 Streamlined data management and dissemination systems 3.3.1 Invest in an integrated and interactive agricultural statistical management system 1 NSA 3.3.2 Develop databases at the Ministry of Fisheries and Marine Resource (MFMR) and Ministry of Environment, Forestry and Tourism (MEFT) that can be integrated with the Office of the Prime Minister (OPM) system 1 MFMR/MEFT 3.3.3 Linking the databases at the Ministry of Fisheries and Marine Resource (MFMR) and Ministry of Environment, Forestry and Tourism (MEFT) to OPM system integration 1 MFMR/MEFT 3.3.4 Expand the data exchange initiative (UXP) by NSA with OPM to other key data producers in the agriculture sector 1 NSA Output 4.1 Established Stakeholder Engagement Mechanisms 4.1.1 Undertake a mapping exercise to identify key stakeholders that will be included as part of the SPARS Secretariat (i.e., Sector Statistics Coordinators Committee) 1 NSA 4.1.2 Establish a Sector-Wide Memorandum of Understanding (MoU) for SPARS Implementation (including a validation workshop of minimum set of core data; data sharing agreements) 1 NSA/MAWLR/MFMR/MEFT/MURD 4.1.3 Strengthen the SPARS Secretariat (i.e., Sector Statistics Coordinators Committee) to provide ongoing guidance and feedback on statistical activities 1 NSA/MAWLR/MFMR/MEFT/MURD 4.1.4 Organize regular stakeholder forums (users and producers) 1 NSA Output 4.2 Improved Data Relevance for Stakeholders 4.2.1 Develop and conduct targeted training sessions for stakeholders on data access, interpretation, and utilization 1 NSA 4.2.2 Conduct user satisfaction surveys 1 NSA Output 4.3 Streamlined Statistical Production, Processing, and Dissemination practices 4.3.1 Develop a statistical calendar for the SPARS period and regularly update it 1 NSA 4.3.2 Establish joint data collection initiatives 1 NSA Output 5.1 Expanded indicator coverage to gather information from diverse subject areas and to enhance disaggregation 5.1.1 Review existing data collection tools for administrative records 1 NSA/MAWLR/MFMR/MEFT 5.1.2 Conduct stakeholder consultations on new data topics 1 NSA Output 5.2 Enhance data collection tools and methods 5.2.1 Improve and/or develop tools and methods used for data collection e.g., remote sensing, surveying, sampling, mobile data collection tools, etc 1 NSA/MAWLR/MFMR/MEFT Output 5.3 An integrated survey and censuses program that address existing data gaps 5.3.1 Conduct a comprehensive assessment to identify existing data gaps in agricultural and rural statistics 1 NSA 5.3.2 Prioritize areas for survey implementation based on the significance of data gaps and their impact on decision-making 1 NSA 5.3.3 Establish a clear timeline and budget for survey implementation, ensuring alignment with overall statistical calander 1 NSA 5.3.4a Aquaculture and Inland Survey 1 MFMR/NSA 5.3.4b Stock Assessment Surveys 1 MFMR/NSA 5.3.4c Marine Fisheries Employmeent Verification Survey 1 MFMR/NSA 5.3.4d Angling Survey MFMR 5.3.4e Fish Consumption Survey 1 NFCPT/MFMR/NSA 5.3.4f Marine Fish Price Survey (adminstration records) 1 MFMR/NSA 5.3.4g Wood Biomass Quantification Survey 1 MEFT/NSA 5.3.4h Aboveground Biomass Layers Production 1 MEFT/NSA 5.3.4i National Forestry Inventory 1 MEFT/NSA 5.3.4j Census of Agriculture 1 NSA/MAWLR/MURD/MEFT 5.3.4k Annual Agriculture Survey 1 NSA/MAWLR/MURD/MEFT 5.3.4l Water Accounts 1 MEFT/MAWLR/NSA/MURD Output 6.1 Increased data advocacy 6.1.1 Identify and appoint a SPARS champion in Cabinet 1 NSA 6.1.2 Develop and implement strategy for advocacy 1 NSA 6.1.3 Conduct and participate in stakeholder engagements 1 NSA/MAWLR/MFMR/MEFT 6.1.4 Create various communication products for different statistical themes targeting different audiences 1 NSA/MAWLR/MFMR/MEFT 6.1.5 Conduct media briefings or press releases for Namibia’s national agricultural and rural statistics 1 NSA/MAWLR/MFMR/MEFT Monitoring and Evaluation Annual progress report 1 NSA Mid-term evaluation 1 NSA Final evaluation 1 NSA Outputs/Activities Timeline Responsible Institutions/Stakeholders2024/25 2025/26 STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 43 ANNEX III - SPARS LOG FRAMEWORK STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 43 ANNEX III - SPARS LOG FRAMEWORK 57 ANNEX III - SPARS LOG FRAMEWORK SPARS Element Performance Indicators Baseline 2023/24 Mid-line 2026/27 End line 2028/29 Verification Assumptions Vision: A well resourced and coordinated National Agricultural Statistics System that supports evidence-based planning, that is responsive to user needs. Agriculture Statistics Capacity Index (ASCI): capacity to effectively produce, collect, and disseminate agricultural and rural statistics 53% 60% 80% AfDB’s Country Assessment of Agriculture Statistics System A country assessment of agriculture statistics system will be done following the AfDB methodology Effective implementation of SPARS Prerequisites dimension score: extent to which the foundations for the effective running of the National Agricultural Statistics System (NASS) are in place 71% 80% 90% Input dimension score: the ability of a country to allocate sufficient resources to carry out statistical activities 26% 40% 70% Throughput dimension score: the capacity to undertake statistical activities in a professional and cost-effective manner. 56% 65% 75% Output dimension score: the availability of data and its level of accessibility to users both at national and international levels for policy formulation and decision-making. 62% 70% 80% Strategic Objective 1: To promote the use of and adherence to national and international standards and best practices in all statistical production, processing, and dissemination. Output 1.1 Increased Use of Statistical Standards and Methods Percentage of key data producers trained on statistical standards and methods. TBC > > Annual report Mid-term review report Effective implementation of the activities related to the outputs STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 44 58 Number of data collection practices standardized based on established standards. TBC > > End of plan period evaluation report Number of administrative data sources adopting the developed standard. TBC > > Output 1.2 Improved Data Comparability Number of producers trained on metadata creation and application. TBC > > Rate of adoption of harmonized statistical definitions and methodologies. TBC > > Output 1.3 Streamlined statistical production, processing, and dissemination practices Percentage of statistical activities conducted according to the statistical calendar. TBC > > Percentage of budget allocated and utilized for statistical activities. TBC > > Strategic Objective 2: To mobilize financial resources for the timely undertaking of statistical activities Output 2.1 Increased Budget Allocation Percentage increase in budget allocation for statistical activities. TBC > > Annual report Mid-term review report End of plan period evaluation report Effective implementation of the activities related to the outputs Rate of budget execution for statistical activities. TBC > > Output 2.2 Diversified Funding Sources Number of new funding sources secured for statistical activities. TBC > > Percentage of budget derived from diversified funding sources. TBC > > Effectiveness of resource mobilization strategy, measured through funds raised. TBC > > STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 45 59 Output 2.3 Improved Budgeting Efficiency Percentage of budget allocated and utilized for planned statistical activities. TBC > > Strategic Objective 3: To strengthen capacity and the use of systems and technology for collecting, processing, and disseminating statistics Output 3.1 Enhanced Staff Capacity Percentage of staff trained on relevant technologies and methodologies. TBC > > Annual report Mid-term review report End of plan period evaluation report Effective implementation of the activities related to the outputs Number of knowledge-sharing initiatives implemented among stakeholders. TBC > > Output 3.2 Improved Data Collection Efficiency Percentage improvement in data collection efficiency, measured through time and cost savings. TBC > > Number of new technologies identified and adopted for data collection. TBC > > Level of investment in technology infrastructure, assessed through budget allocation. TBC > > Output 3.3 Streamlined data management and dissemination systems Percentage improvement in data accessibility and usability. TBC > > Number of integrated management systems implemented. TBC > > Level of database development achieved for key ministries. TBC > > Strategic Objective 4: To strengthen stakeholder collaboration and coordination Output 4.1 Established Stakeholder Engagement Mechanisms Number of stakeholder engagement mechanisms established. TBC > > Annual report Mid-term review report Effective implementation of the activities related to the outputs STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 46 60 Level of participation in MoU implementation. TBC > > End of plan period evaluation report Effectiveness of technical working groups in facilitating stakeholder engagement. TBC > > Output 4.2 Increased Stakeholder Participation Percentage increase in stakeholder participation in statistical initiatives. TBC > > Number of joint data collection initiatives established. TBC > > Effectiveness of data sharing agreements in promoting collaboration. TBC > > Output 4.3 Improved Data Relevance for Stakeholders Percentage improvement in perceived data quality and relevance. TBC > > Strategic Objective 5: To expand the scope and disaggregation of statistics Output 5.1 Expanded indicator coverage to gather information from diverse subject areas and to enhance disaggregation Percentage increase in the coverage of statistical indicators. TBC > > Annual report Mid-term review report End of plan period evaluation report Effective implementation of the activities related to the outputs Number of new variables or data topics included in planned surveys. TBC > > Level of improvement in data disaggregation capabilities. TBC > > Output 5.2 Enhance data collection tools and methods Number of new data collection tools developed or improved. TBC > > Level of investment in technology infrastructure for data collection. TBC > > STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 47 61 Effectiveness of new tools in enhancing data collection efficiency. TBC > > Output 5.3 An integrated survey program that address existing data gaps Percentage of existing data gaps identified and addressed. TBC > > Timeliness of survey implementation, compared to established timelines. TBC > > Level of alignment between survey activities and the statistical calendar. TBC > > Strategic Objective 6: To strengthen awareness about the importance of national agriculture and rural statistics Output 6.1 Increased data advocacy Number of advocacy activities conducted to raise awareness of agricultural and rural statistics. TBC > > Annual report Mid-term review report End of plan period evaluation report Effective implementation of the activities related to the outputs Appointing of a SPARS Champion in Cabinet √ √ Notes: TBC means To Be Collected; “<” means increasing trend; and “√” means done or achieved STRATEGIC PLAN FOR AGRICULTURAL AND RURAL STATISTICS 2024/25 – 2028/29 48 ANNEX IV - SPARS BUDGET 65 2024/25 2025/26 2026/27 2027/28 2028/29 Total Amount Output 1.1 Increased Use of Statistical Standards and Methods 3,210.52 1.1.1 Conduct a comprehensive mapping of statistical methods and standards across key data producers for both surveys and administrative data 1 25.00 25.00 1.1.2 Conduct needs assessment for standardising data production processes across key producers 1 25.00 100.00 125.00 1.1.3 To sensitise and train key data producers on statistical standards 1 557.00 601.56 649.68 701.66 2,509.90 1.1.4 Improve data collection, processing, and dissemination activities to meet the statistical standards across key data producers 1 100.00 108.00 116.64 125.97 450.61 1.1.5 Develop a standard for administrative data 1 100.00 100.00 Output 1.2 Improved Data Comparability 316.99 1.2.1 Conduct data comparability assessments across key producers 1 54.00 62.99 116.99 1.2.2 Review and update the Namibia compendium of Statistical and Spatial concepts and definitions 1 100.00 100.00 1.2.3 Develop a compendium of best practice methods for collecting agriculture and rural statistics 1 100.00 100.00 Output 2.1 Increased Budget Allocation 483.93 2.1.1 Compile annual budgets for statistical activities on the statistical calendar 1 25.00 27.00 29.16 31.49 112.65 2.1.2 Conduct advocacy engagements to lobby for funding the statistical activities 1 80.00 88.00 96.80 106.48 371.28 Output 2.2 Diversified Funding Sources 412.32 2.2.1 Develop and implement a financial resource mobilization strategy 1 250.00 50.00 54.00 58.32 412.32 Output 2.3 Improved Budgeting Efficiency 80.00 2.3.1 Track budget execution rate based on allocated funds 1 20.00 20.00 20.00 20.00 80.00 Output 3.1 Enhanced Staff Capacity 1,626.10 3.1.1 Conduct needs assessment for statistical production using latest technologies 1 120.00 150.00 270.00 3.1.2 Conduct targeted training workshop on relevant up-to-date technologies for data collection, processing, management, and dissemination 1 601.56 661.72 1,263.28 3.1.3 Promote knowledge sharing among key data producers on new technology and systems for collecting, processing, and disseminating statistics 1 20.00 22.00 24.20 26.62 92.82 Output 3.2 Improved Data Collection Efficiency 15,188.00 3.2.1 Identify and evaluate new technologies for GIS and remote sensing 1 20.00 21.60 41.60 3.2.2 Invest in technology infrastructure for GIS and remote sensing 1 4,665.60 5,038.85 5,441.96 15,146.40 Output 3.3 Streamlined data management and dissemination systems 5,428.53 3.3.1 Invest in an integrated and interactive agricultural statistical management system 1 1,333.33 1,440.00 1,555.20 4,328.53 3.3.2 Develop databases at the Ministry of Fisheries and Marine Resource (MFMR) and Ministry of Environment, Forestry and Tourism (MEFT) that can be integrated with the Office of the Prime Minister (OPM) system 1 600.00 600.00 3.3.3 Linking the databases at the Ministry of Fisheries and Marine Resource (MFMR) and Ministry of Environment, Forestry and Tourism (MEFT) to OPM system integration 1 50.00 50.00 3.3.4 Expand the data exchange initiative (UXP) by NSA with OPM to other key data producers in the agriculture sector 1 200.00 150.00 100.00 450.00 Output 4.1 Established Stakeholder Engagement Mechanisms 1,189.84 4.1.1 Undertake a mapping exercise to identify key stakeholders that will be included as part of the SPARS Secretariat (i.e., Sector Statistics Coordinators Committee) 1 20.00 20.00 40.00 4.1.2 Establish a Sector-Wide Memorandum of Understanding (MoU) for SPARS Implementation (including a validation workshop of minimum set of core data; data sharing agreements) 1 30.00 40.00 70.00 4.1.3 Strengthen the SPARS Secretariat (i.e., Sector Statistics Coordinators Committee) to provide ongoing guidance and feedback on statistical activities1 80.00 86.40 93.31 100.78 108.84 469.33 4.1.4 Organize regular stakeholder forums (users and producers) 1 100.00 110.00 121.00 133.10 146.41 610.51 Output 4.2 Improved Data Relevance for Stakeholders 2,210.09 4.2.1 Develop and conduct targeted training sessions for stakeholders on data access, interpretation, and utilization 1 612.70 673.97 741.37 2,028.04 4.2.2 Conduct user satisfaction surveys 1 55.00 60.50 66.55 182.05 Output 4.3 Streamlined Statistical Production, Processing, and Dissemination practices 588.72 4.3.1 Develop a statistical calendar for the SPARS period and regularly update it 1 300.00 60.00 66.00 72.60 498.60 4.3.2 Establish joint data collection initiatives 1 20.00 21.60 23.33 25.19 90.12 Output 5.1 Expanded indicator coverage to gather information from diverse subject areas and to enhance disaggregation 1,725.00 5.1.1 Review existing data collection tools for administrative records 1 250.00 275.00 525.00 5.1.2 Conduct stakeholder consultations on new data topics 1 300.00 300.00 300.00 300.00 1,200.00 Output 5.2 Enhance data collection tools and methods 532.79 5.2.1 Improve and/or develop tools and methods used for data collection e.g., remote sensing, surveying, sampling, mobile data collection tools, etc 1 120.00 128.40 137.39 147.01 532.79 Output 5.3 An integrated survey and censuses program that address existing data gaps 569,798.61 5.3.1 Conduct a comprehensive assessment to identify existing data gaps in agricultural and rural statistics 1 473.45 473.45 5.3.2 Prioritize areas for survey implementation based on the significance of data gaps and their impact on decision making 1 55.70 55.70 5.3.3 Establish a clear timeline and budget for survey implementation, ensuring alignment with overall statistical calander1 557.00 557.00 5.3.4a Aquaculture and Inland Survey 1 300.00 408.15 708.15 5.3.4b Stock Assessment Surveys 1 50,000.00 54,000.00 58,320.00 62,985.60 68,024.45 293,330.05 5.3.4c Marine Fisheries Employmeent Verification Survey 1 250.00 270.00 291.60 314.93 340.12 1,466.65 5.3.4d Angling Survey 100.00 108.00 116.64 125.97 136.05 586.66 5.3.4e Fish Consumption Survey 1 3,000.00 3,000.00 5.3.4f Marine Fish Price Survey (adminstration records) 1 20.00 21.60 23.33 25.19 27.21 117.33 5.3.4g Wood Biomass Quantification Survey 1 600.00 648.00 699.84 1,947.84 5.3.4h Aboveground Biomass Layers Production 1 400.00 503.88 903.88 5.3.4i National Forestry Inventory 1 9,000.00 9,450.00 9,922.50 10,418.63 38,791.13 5.3.4j Census of Agriculture 1 1,298.30 77,167.00 5,495.47 83,960.77 5.3.4k Annual Agriculture Survey 1 49,000.00 46,000.00 45,400.00 140,400.00 5.3.4l Water Accounts 1 3,500.00 3,500.00 Output 6.1 Increased data advocacy 2,090.72 6.1.1 Identify and appoint a SPARS champion in Cabinet 1 40.00 42.40 44.94 47.64 174.98 6.1.2 Develop and implement strategy for advocacy 1 500.00 120.00 132.00 145.20 897.20 6.1.3 Conduct and participate in stakeholder engagements 1 120.00 132.00 145.20 159.72 556.92 6.1.4 Create various communication products for different statistical themes targeting different audiences 1 60.00 66.00 72.60 79.86 278.46 6.1.5 Conduct media briefings or press releases for Namibia’s national agricultural and rural statistics 1 30.00 33.00 36.30 39.93 43.92 183.15 Monitoring and Evaluation 3,156.19 Annual progress report 1 150.00 159.00 168.54 178.65 656.19 Mid-term evaluation 1 1,000.00 1,000.00 Final evaluation 1 1,500.00 1,500.00 608,038.34 34,692.51 Grand Total (N$` 000) Grand Total (US$` 000) @ 1U$=N$17.5265 Outputs/Activities Budget Estimates (N$'000)