KENYAN COUNTIES STATISTICS - BUILDING STATISTICAL CAPACITY BUILDING STATISTICAL CAPACITY 12/11/2019 Acknowledgments ACKNOWLEDGMENTS This report was led by Utz Pape (Senior Economist, Poverty & Equity Global Practice) and written together with Mary Ng’endo (Consultant, Poverty & Equity Global Practice) and Laura Abril Rios (Consultant, Poverty & Equity Global Practice) with the contributions of Nduati Maina Kariuki (ET Consultant, Poverty & Equity Global Practice). The team would like to thank the peer reviewers Abdoullahi Beidou (Senior Economist/Statistician, Poverty & Equity Global Practice) and Philip Brynnum Jespersen (Senior Social Development Specialist, Social Development) for their guidance. The World Bank greatly appreciates the time, inputs and support of the Kenya National Bureau of Statistics under the leadership of Zacharia Mwangi (Director General), and the 47 County Statistical Officers as well as the county government staff in Laikipia and Wajir counties that participated in the Key Informant Interviews and in the preparation of this report. This study was funded by the Kenya Accountable Devolution Program with funding from the DANIDA, the UK Department for International Development (DFID), the European Union, Finland, Sweden, and USAID. ii Table of Contents TABLE OF CONTENTS ACKNOWLEDGMENTS........................................................................................................................ II TABLE OF CONTENTS ........................................................................................................................ III ACRONYMS AND ABBREVIATIONS .................................................................................................... IV EXECUTIVE SUMMARY ....................................................................................................................... V SUPPORTING DEVOLUTION IN KENYA THROUGH RELIABLE DATA ....................................................... 1 THE KENYA NATIONAL BUREAU OF STATISTICS................................................................................... 3 1. STRUCTURE, RESPONSIBILITIES AND COUNTY OFFICES STAFFING ..................................................................... 3 a. Data collection flows and procedures ................................................................................................. 7 b. County Statistical Abstracts ............................................................................................................... 10 c. Availability and access to data........................................................................................................... 13 CONCLUSIONS AND RECOMMENDATIONS ....................................................................................... 15 REFERENCES .................................................................................................................................... 19 APPENDICES .................................................................................................................................... 22 APPENDIX A: KEY INFORMANT INTERVIEW GUIDE ............................................................................................. 22 APPENDIX B: COUNTY OFFICES STAFF RESPONSIBILITIES ..................................................................................... 23 APPENDIX C: KNBS DATA COLLECTION FLOWS FOR MAIN ROUTINE SURVEYS ......................................................... 24 APPENDIX D: COUNTY STATISTICAL ABSTRACTS PUBLICATION YEARS AND PROGRESS STATUS .................................... 26 APPENDIX E: FIRST SCHEDULE (STATISTICS ACT 2006 AND BILL AMENDMENT 2019) ............................................. 27 APPENDIX F: COUNTY STATISTICAL ABSTRACTS ELABORATION STEPS .................................................................... 29 APPENDIX G: ADDITIONAL CSA SECTIONS LAIKIPIA 2018-2019 ......................................................................... 31 APPENDIX H: LAIKIPIA AND WAJIR COUNTY STATISTICAL ABSTRACTS CONTENTS .................................................... 35 APPENDIX I: KNBS SERVICES AND PRODUCTS ................................................................................................... 51 APPENDIX J: LIST OF NATIONAL STATISTICS OFFICES WEBSITES WORLDWIDE ........................................................... 52 List of Figures Figure 1: KNBS organigram .............................................................................................................................. 5 List of Tables Table 1: County offices staffing ....................................................................................................................... 6 Table 2: Data portal availability ..................................................................................................................... 13 List of Boxes Box 1: KNBS-MDA examples ............................................................................................................................ 8 iii Acronyms and abbreviations ACRONYMS AND ABBREVIATIONS CDF Constituency Development Fund CIDP County Integrated Development Plan County GDP County Gross Domestic Product CSA County Statistical Abstract CSO County Statistical Officer KENPHIA Kenya Population-based HIV Impact Assessment survey KII(s) Key Informant Interview(s) KNBS (HQ) Kenya National Bureau of Statistics (Headquarters) MDA(s) Ministries, Departments and Agencies MoH Ministry of Health NEMA National Environmental Management Authority NHIF National Hospital Insurance Fund iv Executive summary EXECUTIVE SUMMARY The process of devolution in Kenya requires building the statistical capacity of the county-level statistical offices to ensure timely and high-quality data to monitor progress towards the objectives of devolution and to design evidence-based policies and programs. Over the past two decades, Kenya has strengthened its capacity to collect data for evidence-based decision-making—however, increased efforts to build its county-level statistical capacity are still needed. Kenya has increased its statistical capacity and shown progress in accessibility of data, accuracy and timeliness.1 Nevertheless, irregular and limited county-level statistical outputs reflect the need for further strengthening the Kenyan National Bureau of Statistics’ (KNBS)2 capacity to facilitate homogeneous, timely and high-quality county-level statistics. An essential step to enhance Kenya’s statistical capacity is to analyze the organizational structure of the KNBS at the county-level to better understand its procedures to generate statistical outputs and identify opportunities for improvement. This report contributes to building Kenya’s statistical capacity by providing recommendations based on Key Informant Interviews (KIIs). The interviews were conducted with KNBS headquarter (HQ) staff members and the 47 KNBS County Statistical Officers (CSOs). This report provides an overall picture of the organizational structure of the KNBS and its CSOs, as well as the processes to generate statistics and the differences in the production of statistics across counties. Furthermore, availability and access to data are explored by describing the existing online platforms to download and visualize data. Based on the findings presented in this report, the following practices are recommended to build the KNBS’s county statistical capacity. Strengthening human resources at the county-level is key to ensuring that the statistics generated meet quality standards. The KNBS is led by a Board of Directors, managed by a Director-General and divided into five directorates and 47 county offices. County offices staffing ranges from one to six staff members. However, only four county offices are fully staffed with the required set of qualifications.3 In contrast, all other offices are either under-staffed or staff members do not have any statistics-related university degrees. Additionally, staffing numbers at the county level are expected to drop further due to retirement of 10 staff members, without confirmed replacements. One key recommendation to build the KNBS’s capacity at the county level is to develop clear terms of reference and functional guidelines to hire skilled professionals to properly staff each county office while training the existing workforce to acquire the required skills mix. 1 World Bank, “Development of the National Statistical System Project.� 2 The KNBS is the main government agency in charge of producing official statistics and is responsible for coordinating the National Statistical System (NSS). This report focuses on the KNBS’s processes to generate statistics (mainly at the county level), and how they can be i mproved to enhance Kenya’s statistical capacity. This report does not provide recommendations for building the capacity of administrative data suppliers and as such, limits its scope to the work of the KNBS at the county-level and its intersections with ministries, department, agencies and county governments. 3 According to the information provided in the KIIs, an ideally staffed county office includes one CSO, one deputy CSO and one or two assistants. Nonetheless, terms of reference or functional guidelines are not available for staff members at the county-level. v Executive summary Co-funding partnerships between the KNBS and county governments can ensure the production of County Statistical Abstracts (CSAs). CSAs are milestone KNBS publications that provide county-level statistics. The publication and funding of CSAs in the 47 counties has evolved since its inception in 2015. While each county had an inaugural CSA publication—funded by the KNBS—only Laikipia county has published two subsequent CSAs (2018 and 2019). Laikipia CSAs publications were achieved through the co- funding partnership between the KNBS and the county government. In producing Laikipia’s CSAs, the county governor’s support was crucial. In fact, Laikipia’s governor acknowledges data as a key input for evidence- based decision-making and thus, promotes the production and use of statistics. Thus, co-funding mechanisms can be developed also in other counties by advocacy for evidence-based decision making targeted to the leadership of the counties. This exercise can utilize experiences and lessons learnt from successful county governments promoting the use of statistics. While this approach may be instrumental in securing funds to address the need for generating CSAs, county statistical outputs should not depend on county leadership’s preferences regarding the use of statistics. Therefore, an alternative approach can consist of supplementing KNBS’s budget to allow for funding county statistical outputs, ensuring data accuracy and professional independence. Coupled with that, co-funding collaborations must integrate a neutral and independent entity that assesses risks to avoid potential conflicts of interest. Combined with successful KNBS-county government collaborations, the production of statistics requires effective partnerships between the KNBS and MDAs (Ministries, Departments and Agencies). MDAs play different roles varying depending on the activity. In some activities, MDAs are data providers, while in other activities MDAs are clients who request data and other outputs from the KNBS. Thus, an effective relationship between the KNBS and MDAs is highly beneficial for producing high-quality statistics. Therefore, it is paramount to proactively establish and strengthen partnerships between MDAs and the KNBS by attending regularly to county meetings in which data collection activities and requests are discussed. Equally important, it is recommendable for the KNBS to reinforce its protocols to review the accuracy of data provided by MDAs as well as to strengthen its guidelines for county offices to collect data from MDAs. Such reinforcement can support efforts to improve data quality. Data collected to produce statistics are available on a diverse set of online portals reflecting the lack of a central source that provides easy access to up-to-date data. In Kenya, data can be visualized and downloaded without charges, via national and international portals, such as the KeNADA (National Data Archive), the Kenya Open Data portals, the World Bank Central Data Catalog and the Humanitarian Data Exchange (HDX) provided by OCHA. Furthermore, the Maarifa Centre provides an online platform to document and share experiences, innovations and solutions on Kenya’s devolution process. The lack of a unified system to visualize and download data can hinder efforts to improve accountability of the use of public resources and monitor progress of devolution. A single portal is therefore required in order to simplify the process individuals and organizations can access up-to-date national and county-level disaggregated data. However, it will be of utmost importance to ensure that such a unified data portal is regularly maintained and updated. vi Supporting devolution in Kenya through reliable data SUPPORTING DEVOLUTION IN KENYA THROUGH RELIABLE DATA The ongoing process of devolution in Kenya requires reliable, timely and high-quality data to monitor progress towards constitutional objectives. Devolution is the process of transferring decision-making and implementation powers, functions, responsibilities and resources to elected local governance structures. In Kenya, devolution is based on the supremacy of the Constitution, sovereignty of the people and the principle of public participation.4 The objectives of devolution in Kenya are stated under the Art. 174 of the Constitution:5 6 a. To promote democratic and accountable exercise of power; b. To foster national unity by recognizing diversity; c. To give powers of self-governance to the people and enhance the participation of the people in the exercise of the powers of the State and in making decisions affecting them; d. To recognize the right of communities to manage their own affairs and to further their development; e. To protect and promote the interests and rights of minorities and marginalized communities; f. To promote social and economic development and the provision of proximate, easily accessible services throughout Kenya; g. To ensure equitable sharing of national and local resources throughout Kenya; h. To facilitate the decentralization of State organs, their functions and services, from the capital of Kenya; and, i. To enhance checks and balances and the separation of powers. The achievement of the objectives of devolution in Kenya, requires data to monitor the progress towards the stated objectives. Therefore, the production of reliable, timely and high-quality data on key indicators at the national and county-level is a crucial input to guide policymakers in ensuring that evidence-based policy is generated. Over the past two decades, Kenya has shown progress in data accessibility, accuracy and timeliness—however, increased efforts to build its statistical capacity are still needed.7 In the early 2000s Kenya’s statistical capacity was deteriorated due to:8 • declining budgetary support for the production and dissemination of statistics, • inadequate professional staff at the management and technical levels, • dilapidated statistical infrastructure and information and communication technology equipment, and • loss of relevance due to inadequate engagement with users. In that period, the government of Kenya recognized the need for enhancing its statistical system. For that, a five-year strategic plan and a Statistics Bill were prepared and approved by the cabinet in December 2003.9 The Statistics Bill was enacted by the parliament and endorsed by the president in 4 International Commission of Jurists, Handbook on Devolution: The Kenyan Section of the International Commission of Jurists. 5 National Council for Law Reporting, The Constitution of Kenya. 6 The primary source of legislation on devolution is the Constitution of Kenya 2010 (International Commission of Jurists, Handbook on Devolution: The Kenyan Section of the International Commission of Jurists.) 7 World Bank, “Development of the National Statistical System Project,� 8. 8 World Bank, 1. 9 World Bank, “Development of the National Statistical System Project.� Supporting devolution in Kenya through reliable data 2006. In August 2019, the 2006 Statistics Act was amended and reenacted. Since the inception of the first Statistics Act, Kenya has strengthened its statistical capacity. For instance, the Kenya Integrated Household Budget Survey (KIHBS), the World Bank-supported Kenya Continuous Household Survey (KCHS), and the digital 2019 Kenya Population and Housing Census, reflect an improved national statistical capacity and represent commendable efforts in the production of high-quality statistics. Nevertheless, additional efforts need to be made. Kenya’s overall score for the Statistical Capacity Indicator (SCI)10 in year 2018 was of 56 (in a scale ranging from 0 to 100) slightly lower than the precedent year and the second highest score since year 2013 (SCI score: 52), indicating an increasing trend over the last 6 years—yet, still lower than other countries in the region. 11 Especially at the county level, Kenya’s statistical capacity needs to be further strengthened to guarantee a homogeneous timeliness and quality of statistical outputs produced at the national and county level. The Kenyan National Bureau of Statistics (KNBS) is the main government agency in charge of producing official statistics. The KNBS is also responsible for coordinating the National Statistical System (NSS).12 For that, this report focuses on the KNBS’s processes to generate statistics (mainly at the county level), and how they can be improved to enhance Kenya’s statistical capacity. The KNBS produces official statistics based on national and county-level surveys. With its headquarters in Nairobi and 47 county offices, the KNBS’s role is crucial in ensuring the availability of data to produce reliable statistical information to monitor devolution. In producing statistics, the KNBS’s 47 county offices serve as point of liaison for administrative and county-specific data collection as well as for analyzing county data. The county offices also advocate for the use of county statistics and produce the main county-level outputs namely County Statistical Abstracts (CSAs). Consistent with the large variation in development outcomes across Kenya’s counties, the quality of county statistical outputs varies significantly between them. While some KNBS county offices regularly produce CSAs, others lack the basic human resources required to carry out daily activities. These disparities result in the lack of updated and reliable county-level data. Such lack of data can hinder efforts to generate evidence-based decision-making processes, to design and monitor programs and policies, and to improve accountability for the use of public resources. Evidently, strengthening the statistical capacity of Kenya’s county-level statistics offices is crucial. An essential first step to further enhance Kenya’s statistical capacity is to analyze the structure of the KNBS at the county-level and explore its data production protocols. This report contributes to building Kenya’s statistical capacity by identifying opportunities for improving the KNBS’s work and providing recommendations. While ministries, departments and agencies (MDAs) as well as county governments’ work in collecting data constitute crucial inputs for the KNBS to produce official statistics, this report does not provide recommendations for building the capacity of such entities. As such, this report limits its scope to the work of the KNBS, more narrowly to the KNBS at the county- level and its intersections with MDAs and county governments. 10 World Bank, “Statistical Capacity Indicator Dashboard.� The Statistical Capacity Indicator (SCI) Country Dashboards provide individual country scores for the overall SCI average as well as for the 3 categories, i.e. Methodology, Source Data, and Periodicity. 11 World Bank. The SCI scores for other countries in the region in year 2018 were: Uganda 74, Ethiopia 72, Tanzania 71 and Sudan 65. 12 Kenya National Bureau of Statistics, “KNBS Mandate�; National Council for Law Reporting, The Statistics (Amendment) Act, 2019. 2 The Kenya National Bureau of Statistics Semi-structured Key Informant Interviews (KIIs) with KNBS HQ staff members and the 47 KNBS County Statistical Officers, were carried out to inform the analysis and recommendations. 13 Specifically, this report was prepared to provide an overall picture of the KNBS’s organizational structure, of its processes to generate statistics, the differences in the production of statistics across counties and the lack of data available for public use. Consequently, this report is structured as follows; the first section presents KNBS’s organizational structure and responsibilities. The second section describes the KNBS’s internal processes to collect survey data and to generate statistical reports, followed by the third section which compares the CSAs of Laikipia (2015, 2018 and 2019) and Wajir (2015) and a fourth section with an overview on availability and access to data. Based on the findings presented in the precedent sections, the report concludes with a set of recommendations to improve the KNBS’s statistical capacity at the county-level. THE KENYA NATIONAL BUREAU OF STATISTICS 1. Structure, responsibilities and county offices staffing The KNBS is the main agency of the Government in charge of collecting, analyzing and disseminating statistical data and shall be custodian of official statistics. 14 , 15 According to The Statistics (Amendment) Act, 201916 which was accredited by President Kenyatta as an Act of Law on the 14th August 2019,17 18 the KNBS is responsible for: a. Planning, authorizing, coordinating and supervising all official statistical programs undertaken within the National Statistical System (NSS). b. Establishing standards and ensuring the use of best practices and methods in the production and dissemination of statistical information across the NSS; c. Collecting, compiling, analyzing, abstracting and disseminating statistical information on the matters specified in the First Schedule; d. Conducting the population and housing census every ten years or, in exceptional circumstances, at such times as may be approved by the Cabinet and gazette by the Cabinet Secretary, and such other censuses and surveys as the Board may determine; e. Maintain a comprehensive and reliable national socioeconomic database; f. Developing and maintaining sampling frames of the KNBS; g. Collaborating with and assisting the county governments or any other institutions in the production of official statistics; h. Providing technical advice on statistics to other state entities; i. Promoting co-ordination among producers, users and suppliers of official statistics by forming appropriate sector committees; and j. Designating statistics produced by national statistical system as official statistics on being satisfied that the necessary criteria have been followed. 13 See Appendix A: Key Informant Interview guide 14 Government of Kenya, “The Statistics Act, 2006,� 77. 15 “Official statistics� means statistics produced by the Bureau and any other statistics designated as official by the Director -General. National Council for Law Reporting, The Statistics (Amendment) Act, 2019. 16 National Council for Law Reporting, 712. 17 Standard Digital, “President Uhuru Signs Statistics (Amendment), Accreditation Service Bills into Law.� 18 The Statistics Amendment Act will come into effect once it is gazetted (as of September 2019, the new Act has not been gazetted). 3 The Kenya National Bureau of Statistics The NSS includes producers, suppliers and users of official statistics working under the supervision and co-ordination of the KNBS including ministries, departments and agencies (MDAs).19 The Statistics (Amendment) Act aims at “streamlining the management of [official] statistical information at national and county levels by ensuring that data collection and processing is conducted in accordance with international best practices and standards.�20 21 The amendments introduced in the new law contribute to strengthening Kenya’s statistical capacity. The KNBS is led by a Board of Directors, managed by a Director-General and divided into five directorates and 47 county offices. The management of the KNBS is led by a Board of Directors which consists of: 22 a. A chairman appointed by President; b. The Principal Secretary in the Ministry for the time being responsible for statistics; c. The Principal Secretary Ministry responsible for finance; and d. Five other members appointed by the Cabinet Secretary to represent the bodies for the time being recognized by the Government as representing: i. Private sector; ii. The non-Governmental Organizations; iii. Research institutions; iv. The public universities; and v. The National Council for Population and Development. Furthermore, the Act (Amendment) 2019,23 integrates a Corporation Secretary of the KNBS, who shall be appointed by the Board.24 The Corporation Secretary will be responsible for: a. Co-ordinating the preparation of Board papers and circulating to members of the Boards; b. taking minutes in meetings of the Board and communicating the resolutions of the Board;; c. Ensuring safe custody of the minutes, decisions and documents of the Board; d. Ensuring the safe custody of the seal of the KNBS; e. Drafting legal documents on behalf of the KNBS; f. Attending court proceedings on behalf of the Bureau; g. Advising the Boards on any legal matters; and h. Any other matter that the Boards may direct. At the executive level, the Director-General leads the KNBS and is subject to the direction of the Board. The Director-General’s functions are:25 a. To be responsible for the day-to-day management of the KNBS; b. To manage the funds and property of the KNBS; c. To be responsible for the management of the staff of the KNBS; 19 National Council for Law Reporting, The Statistics (Amendment) Act, 2019, 711. 20 Capital News, “President Kenyatta Signs Statistics (Amendment), Accreditation Service Bills into Law.� 21 National Council for Law Reporting, The Statistics (Amendment) Act, 2019. 22 Government of Kenya, “The Statistics Act, 2006,� 78; National Council for Law Reporting, The Statistics (Amendment) Act, 2019 , 713. 23 National Council for Law Reporting, The Statistics (Amendment) Act, 2019, 714. 24 The position of the Corporation Secretary does not exist in the KNBS yet (September 2019). 25 Government of Kenya, “The Statistics Act, 2006,� 80. 4 The Kenya National Bureau of Statistics d. To prepare for the approval of the Board: i. The annual work programs of the KNBS, and ii. The annual budget, and audited accounts of the KNBS. The Director-General manages five directorates: (a) Population and Social Statistics, (b) Statistical Methods and Standards, (c) Production, (d) Macro-economic Statistics and, (e) Corporate Services. The Senior Manager, Manager, and the County Statistical Officers (CSOs) directly report to the Directorate of Statistical Methods and Standards. 26 At the county level, the KNBS is comprised of technical and support staff. Technical staff includes CSOs, deputy CSOs and statistical assistants whilst support staff is comprised of drivers, secretaries and cleaners (Figure 1). CSOs represent the KNBS at the county level and are the main point of contact between the headquarters and county offices. CSOs carry out both technical and administrative duties with assistance from deputy CSOs and/or statistical assistants. Conversely, statistical assistants27 are involved in data collection and data entry duties, whilst support staff carries out administrative work such as, filing, paperwork and procurement duties (see Appendix B: County offices staff responsibilities). Figure 1: KNBS organigram28 Director-General Directorate of Directorate of Directorate of Directorate of Directorate of statistical methods macro- corporate services population and production and standards (before economic (before 'finance and social statistics statistics administration') 'strategy and development') statistics Senior Manager Manager 47 County Offices* Assistant Manager Technical staff Support staff CSO Secretary, driver, cleaner Deputy CSO Assistants Source: KNBS CSOs29 26 Before the 2019 census, the Senior Manager, Manager, Assistant Manager (in charge of field services and coordination during survey- related activities) and the 47 County Statistical Officers (CSOs) reported directly to the Directorate of Population and Social Statistics. 27 Statistical assistants may perform the following roles: field officers, senior and clerical officers, research assistants and enumerators. 28 County offices staffing varies across counties. Yet, this structure depicts the ideal staffing. 29 This organigram depicts the KNBS organizational structure based on the information provided by KNBS staff during the KIIs carried out for this report. Discrepancies may be identified when comparing this information with the organizational structure depicted on the KNBS website (Kenya National Bureau of Statistics, “KNBS Organization Structure.�). However, according to KNBS staff, recent changes in the institution’s structure have not yet been reflected on the KNBS official website (when this report was written in September 2019). Such adjustments include: a) renaming the Directorate of Strategy and Development (now Statistical Methods and Standards) and the Directorate Finance and Administration (now Corporate Services), and b) the restructuration of the Directorate of Information Technology and its incorporation into the five directorates. Thus, the directorate of IT does not exist anymore as an independent area in the KNBS. 5 The Kenya National Bureau of Statistics County offices staffing ranges from one to six staff members—most of whom do not have statistics- related university degrees. Based on county offices staff members’ experience (gathered through the KIIs), county offices should have one CSO, one deputy CSO and at least one statistical assistant.30 However, in Garissa, Mandera and Wajir, the CSO is the only KNBS staff member, while Kilifi, Machakos, Narok, Taita Taveta and Tana River county offices staffing is comprised of the CSO and one statistical assistant. In contrast Busia, Lamu, Nairobi and Trans Nzoia are the unique county offices which have the ideal staffing.31 At the same time, county offices with the highest number of staff members (one CSO and five assistants) are: Bungoma, Embu, Kisumu, Nakuru and Uasin Gishu. Most county offices are staffed with one to five statistical assistants, with the assistants comprising most county offices staff (Table 1: County offices staffing). However, 21 of them are on long-term assignments away from their corresponding county office and seven of them will retire soon. In terms of academic qualifications, most CSOs and deputy CSOs are graduates in statistics or related fields. Conversely, most statistical assistants do not have a statistics-related university degree—nonetheless, most of them have several years of work experience which may compensate for their lack of academic training. Table 1: County offices staffing No County CSO Deputy CSO Statistical Total staff assistants 1 Baringo 1 0 3 4 2 Bomet 1 0 2* 3 3 Bungoma 1 0 5 (4*) 6 4 Busia 1 1 2 4 5 Elgeyo 1 0 3 4 Marakwet 6 Embu 1 0 5 6 7 Garissa 1 0 0 1 8 Homabay 1 0 3 4 9 Isiolo 1 0 2* 3 10 Kajiado 1 0 3 4 11 Kakamega 1 0 4 (2*) 5 12 Kericho 1 0 3 (1**) 4 13 Kiambu 1 0 2 (1**) 2 14 Kilifi 1 0 1 2 15 Kirinyaga 1 0 3 4 16 Kisii 1 0 2(1*) (1**) 3 17 Kisumu 1 0 5 6 18 Kitui 1 0 2*(2**) 3 19 Kwale 1 0 3 4 20 Laikipia 1 0 2 (1*) 3 21 Lamu 1 1 1 3 22 Machakos 1 0 1 2 23 Makueni 1 2* 3 24 Mandera 1 0 0 1 25 Marsabit 1 0 2 (1*) 3 26 Meru 1** 0 4 5 27 Migori 1 0 2 3 28 Mombasa 1 0 4 5 30 Functional guidelines and terms of reference for staff are not available at the county level. 31 No county office reported to have support staff. 6 The Kenya National Bureau of Statistics No County CSO Deputy CSO Statistical Total staff assistants 29 Muranga 1 0 2* 3 30 Nairobi 1 1 1 3 31 Nakuru 1 0 5 (2**) 6 32 Nandi 1 0 4 5 33 Narok 1 0 1 2 34 Nyamira 1** 0 3 4 35 Nyandarua 1 0 2 3 36 Nyeri 1 0 4 5 37 Samburu 1 0 2 3 38 Siaya 1 0 4 5 39 Taita Taveta 1 0 1 2 40 Tana River 1 0 1 2 41 Tharaka Nithi 1** 0 2 3 42 Trans Nzoia 1 1 2 4 43 Turkana 1 0 1 2 44 Uasin Gishu 1 0 5 6 45 Vihiga 1 0 2* 3 46 Wajir 1 0 0 1 47 West Pokot 1 0 2 3 Total 47 4 114 165 Source: KNBS CSOs * Staff on long-term assignments away from duty station. ** Staff soon retiring. Red boxes: counties with only 1 staff member. Yellow boxes: counties with one CSO and one assistant. Green boxes: counties with the ideal staffing (CSO, deputy CSO and statistical assistants). The lack of human resources in county offices has been exacerbated by the deployment of hired staff to cover the preparatory activities for the 2019 Population and Housing Census. Due to the 2019 census cartographic mapping exercise,32 several county office staff were deployed outside of their duty stations for extended periods of time. To balance the workload and deliver results, CSOs had temporarily hired unpaid interns and volunteers. Additionally, human resources at the county level will soon be reduced due to the retirement of three of the CSOs and seven of the statistical assistants (Table 1: County offices staffingAppendix B: County offices staff), and no staff replacements have been confirmed yet. In 1979, the KNBS carried out a mass recruitment process which explains the increasing number of staff members who will be retiring soon. Almost 40 years later, in 2017, the KNBS rolled out a wave of recruitment in which 40 young professionals with statistics academic backgrounds, were hired. Hence, the KNBS counts on the newly hired recruits who could transition to higher positions vacated by experienced staff. In order for this transition to be successful, the KNBS needs to train these young professionals to effectively perform higher level duties and further strengthen its human capital at the county level. Production of statistics and availability of data a. DATA COLLECTION FLOWS AND PROCEDURES KNBS county offices and directorates work together to collect, compile, and analyze data, as well as to disseminate statistical information. Certain data collection and compilation duties are carried out by county offices. Data analysis, documentation and dissemination activities are usually executed by the directorate of Population and Social Statistics, however—depending on their statistical 32 Kenya National Bureau of Statistics, “Census Cartographic Mapping.� 7 The Kenya National Bureau of Statistics capacity—some county offices contribute to data analysis processes. The directorates of Macroeconomic Statistics, and Production Statistics may also undertake data collection, analysis and dissemination tasks. Consequently, KNBS directorates and county offices need to work together to collect data and produce high-quality statistics. Therefore, effective communication between counties and headquarters is fundamental. KNBS follows a top-down approach to ensure the quality, timeliness and flow of collected data. KNBS HQ is vested with the authority of delegating tasks and allocating funds to county offices for them to carry out data collection and logistical activities for various surveys. While ensuring the timely allocation of financial resources, 33 the KNBS HQ team is responsible for providing guidelines and technical support to produce official statistics at the county level. Such guidelines are key to maintaining the quality standards of survey data, collected by county offices. To ensure a homogenous quality of data, the KNBS HQ team (normally the Production of Statistics Directorate) designs operational manuals which incorporate specific guidelines for data collection and templates to correctly conduct KNBS surveys.34 Operational manuals for specific survey projects are shared by the HQ team with the county office responsible for the data collection and are also available on the KNBS intranet system. Coupled with the support and guidance provided by the KNBS HQ to county offices, successful data collection activities require the recruitment of an additional temporary workforce. Such additional workforce is hired to collect data and may include: interns, volunteers and research assistants, who are trained and supervised by county offices’ staff. Once the data collection phase is successfully completed, the data is compiled by the county offices and sent to the relevant directorate for analysis and publication of results. Lastly, dissemination activities are led by KNBS HQ and undertaken by both the HQ and the county offices, ensuring visibility of statistical outputs at the national and county level. The external partnership with Ministries, Departments and Agencies (MDAs), is crucial in ensuring access to reliable data for national and county-level surveys. As stated on the Local Government Act,35 county governments are required to monitor service delivery and thereafter, collect routine administrative data through MDAs. Thus, administrative data collected by MDAs is a crucial input for monitoring progress, ensure transparency and track service delivery. MDAs are one of the most important counterparts for the KNBS. Depending on the activity, MDAs play different roles. While in some activities, MDAs provide data requested by the KNBS, in other activities MDAs are clients who request data outputs from the KNBS. MDAs and the KNBS have successfully collaborated for the implementation of different projects. An illustration of that is the listing exercise conducted for the ministries of Labour and Social Protection and Finance as well as the HIV impact assessment survey led by the Ministry of Health (Box 1: KNBS-MDA examples). 33 Funds are disbursed only after a budgetary request has been approved by HQ financial management. 34 These manuals include guidelines to design and conduct survey questionnaires, informed consent templates, sample selection from given sampling frames, key definitions for specific survey, among others. 35 National Council for Law Reporting, The Local Government Act. 8 The Kenya National Bureau of Statistics Box 1: KNBS-MDA examples Example 1: Ministry of Labour and Social Protection, and Ministry of Finance survey in collaboration with KNBS HQ and KNBS Murang’a county office. A listing exercise of households and businesses in Murang’a county was jointly commissioned by the Ministry of Labour and Social Protection and the Ministry of Finance to the KNBS HQ and KNBS Murang’a county office. The outputs of this exercise entailed the production of a list of businesses and households ordered into clusters for sampling as well as technical and logistical support. KNBS HQ and county staff coordinated work, and were key in the recruitment of enumerators, supervisors and other field team members, as well in introducing the field team to county officials and key informants. Example 2: Kenya Population-based HIV Impact Assessment (KENPHIA) led by the Ministry of Health in collaboration with KNBS HQ and the 47 KNBS county offices. For the national KENPHIA survey, the Ministry of Health (MoH) HQ collaborated with the KNBS through the directorate of Population and Social Statistics. The MoH provided funding for the KNBS to design the survey questionnaire, estimate the sample and undertake the data collection. Whilst the data was collected by KNBS staff, the supervision and monitoring were jointly carried out by the KNBS HQ and the MoH. Similarly, the data is currently being analyzed by the KNBS and the MoH. A summary sheet is expected to be released in August 2019 while the final report will be ready in May 2020.36 Source: KNBS CSOs Attendance to regular meetings as well as following official processes for data requests have proven to be successful practices for maintaining effective partnerships between the KNBS and MDAs. In some counties, meetings are organized to discuss data collection activities as well as data requests from either the KNBS or an MDA. For instance, Kitui county holds monthly meetings in their national government service delivery group chaired by the county commissioner. Among other topics, such meetings address current data collection efforts as well as updates on data requests. Data requests are placed by the KNBS and MDAs through similar processes which entail the submission of a formal request letter addressed to the person in charge of the MDA or the KNBS. This individual is responsible for ensuring that the request is addressed, and that the request is fulfilled. The request letter describes the data needs as well as the purpose and use of the data. Moreover, the KNBS attaches a template for the MDAs to enter the requested data. According to the KNBS staff, this process has proven to be effective and simple. For instance, to obtain the Ministry of Health’s administrative data (e.g., number of hospital beds, health facilities, annual patients, and most frequent diseases), the KNBS county statistical officer sends a request letter via email, accompanied by a template in which the Ministry enters the requested data and sends it back to the KNBS normally within a few days. As described, county offices carry out coordinating tasks that are fundamental to ensure administrative data from MDAs. While the collaboration process between KNBS-county offices and MDAs appears to function well overall, technical assistance provided by county office staff to MDAs and local administrative statistics suppliers, could contribute to improving the quality of the collected data. The KNBS recurrently collects data for ad hoc and routine surveys which are conducted for the dissemination of national and county-level statistics. Ad hoc surveys are conducted at the request of various clients—including international organizations and government agencies—on mutually 36 PHIA Project, “PHIA Timeline. Kenya.� 9 The Kenya National Bureau of Statistics agreed timelines. An example of an ad hoc survey is the 2018 Kenya Population-based HIV Impact Assessment Survey (KENPHIA) led by the Ministry of Health in collaboration with the KNBS. Conversely, routine surveys are conducted for regular dissemination of data and statistical reports. Routine surveys can be grouped into two depending on the source of the data: (a) household-based surveys, and (b) establishment-based surveys. For household-based surveys socioeconomic data is collected from households selected from a sampling frame. 37 Conversely, data for establishment- based surveys is provided by businesses, firms and also different government ministries (such as the Ministry of Education), departments (such as the Department of Social Development), and agencies (such as schools, hospitals, and parastatal institutions). According to the information provided by the HQ and county offices staff, the main establishment-based routine surveys that the KNBS carries out are:38 39 1. Building and construction statistics survey40 2. Consumer Price Index survey41 3. County Gross Domestic Product (County GDP) survey42 4. Hotel statistics survey43 5. Labor enumeration survey 6. Livestock hides & skin survey 7. Monthly industrial survey of production 8. Retail market price survey Routine surveys are the most common type of KNBS surveys, and are regularly conducted to design future surveys, inform other statistical reports, compute the annual economic survey,44 as well as to produce County Statistical Abstracts (CSAs).45 CSAs constitute the main county statistical output that provide contextualized statistics, instrumental in improving the understanding of county-level needs and trends. b. COUNTY STATISTICAL ABSTRACTS The County Statistical Abstracts (CSAs) are milestone KNBS publications that provide key statistical indicators at the county level. The objective of a CSA is to serve as a key source of statistical information covering various sectors of the economy at the county level. It is expected to provide 37 Kenya National Bureau of Statistics, “Kenya National Bureau of Statistics County Brief. REF: 52/21/A/13(10),� 2013. 38 In addition to routine and ad hoc surveys, the KNBS offers a variety of services and products including technical advice, statistical research and different national and county-level data sets (see Appendix I: KNBS services and products). 39 See Appendix C: KNBS data collection flows for main routine surveys for additional details on each of the routine survey’s data collection timelines, sources and flows. 40 Analyzed data of the Building and construction statistics survey is published in a chapter of the Kenya National Bureau of Statistics, “Economic Survey 2019.� 41 See the price index for June 2019 in Kenya National Bureau of Statistics, “Consumer Price Indices and Inflation Rates for June 2019.� 42 See the gross domestic product report for the first quarter of 2019 in: Kenya National Bureau of Statistics, “Quarterly Gross Domestic Product Report First Quarter, 2019.� 43 Analyzed data of the Hotel statistics survey, the Labor enumeration survey, the Livestock hides & skin survey, the Monthly industrial survey of production and the Retail market price survey is published in the Annual Economic Survey. See the Economic Survey for 2019: Kenya National Bureau of Statistics, “Economic Survey 2019.� 44 Kenya National Bureau of Statistics. 45 Kenya National Bureau of Statistics, “County Statistical Abstracts.� 10 The Kenya National Bureau of Statistics reliable information for planning and policy formulation, as well as for monitoring and evaluation processes. 46 In producing CSAs, the coordination between HQ and county offices to produce CSAs, follows a top-down approach. Correspondingly, the KNBS HQ team develops templates that specify the information to be collected by county offices and presented in CSAs. Such templates are created based on the Statistics Act 2006 First Schedule 47— updated in the Act (amendment) 2019.48 The First Schedule details the statistical information that may be collected, compiled, analyzed, abstracted and published (Appendix E: First schedule). The CSAs are thus elaborated based on these templates that include generic data contents which are tailored for each county—allowing minor county-specific modifications and therefore allowing, comparisons between countiesAppendix F: County Statistical Abstracts elaboration steps KNBS-funded CSA County Government & KNBS co-funded CSA 1 KNBS HQ generates a CSA template, which is discussed Agreements between KNBS and County Government with relevant stakeholders. • Meetings are held between KNBS HQ and County G • Committees are formed (comprised by KNBS HQ, KNBS commissioner). If the county government initiates the discu county, county government, treasury and national to the KNBS Director General, who directs them to the Pop government representatives) to agree on the template the county proposal and discuss possible contents of the contents that will be included in the CSA. forum is organized to present the CSA proposal to the coun be covered. Once the CSA general contents are agree understanding between the county and the KNBS HQ is el • CSA template questionnaires are generated by KNBS in co 2 KNBS HQ and KNBS county offices implement the CSA Joint data collection and supervision data collection. • The county director of economic planning engages other c • Enumerators and data entry clerks are assigned for on agriculture, education, health, water, etc. In most cases data collection work. who shares the templates with the respective department • Agreed-upon data on county indicators is collected. • Enumerators are recruited by the county government bas • KNBS county office (and sometime KNBS HQ) monitor KNBS (i.e., academic background and job experience). data quality and supervise data collection. • A training manual is jointly prepared by the KNBS HQ an • Data collected is compiled and sent to KNBS HQ. enumerators training is conducted by the county governm • Data collection is initiated and supervised by the KNBS cou o Follow-ups on completed template data forms are ini data collection progress. Collected data templates confirm that the needs of both parties have been met 3 KNBS HQ conducts data cleaning, analysis, production Data cleaning, analysis and publication and publication. • Data cleaning and analysis is jointly conducted by county g • KNBS HQ cleans and analyses the data o KNBS HQ is responsible for data validation and if nec i. If necessary, KNBS requests data clarifications trends. • KNBS HQ drafts a report which is submitted to the • A draft report is jointly prepared and approved by KNBS H general direction for approval. • The publication of the approved report is carried out by th • The approved report is published by KNBS. 4 The CSA is launched in an event led by the KNBS with the The CSA is launched by KNBS HQ in collaboration with the cou participation of the county government and relevant • The CSA is launched by the KNBS HQ at county level by MDAs. including other county governors. • CSA hard copies are sent to KNBS HQ, and the respective co and lessons learnt with the directorates. 46 Kenya National Bureau of Statistics. 47 Government of Kenya, “The Statistics Act, 2006.� 48 National Council for Law Reporting, The Statistics (Amendment) Act, 2019, 499. 11 The Kenya National Bureau of Statistics 12 The Kenya National Bureau of Statistics Appendix G: Additional CSA sections Laikipia 2018-2019 Sections / indicators Gross County Product Gross County Product by Economic Activity, at current prices Gross County Product by Economic Activity at constant 2009 Prices Share of GDP by Economic Activity Laikipia County Per Capita GCP Population and vital statistics Population projections by age cohorts and sex Registered Births by Sex in specific sub-counties Main Causes of Deaths by Sex (precedent CSAs only included the top 10 causes of death) Birth and Death by place of occurrence registered in specific sub-counties Labor Public sector wage employment by Sector Employment by Economic activity, Size of Enterprise and Sub-County Monthly Registration of Job Seekers Placement of Job Seekers Public Finance County Revenue by Source Revenue Collection by Revenue Sources Tourism Hotels by classification, bed and conference capacity Hotels Bed Capacity by Sub County Visitor Arrival by Country of origin Visitors by Tourists Attractions Agriculture Map of Agro-Ecological Zones for the County Average Wholesale Prices for Farm Inputs Wholesale Market Prices for Selected Food CommoditieS Retail Price of Some Selected Food Commodities Livestock Estimated livestock population by type Number, quantity and value of animals slaughtered by type of animal and year Quantity and value of other livestock products Number of milk processors by sub-county Annual milk production by sub-county Price of livestock on sale Prices of meat products Prices of Supplementary Livestock Feeds and Minerals by Sub County Prices of Supplementary Livestock Feeds and Minerals by Sub County Prices of Supplementary Livestock Feeds and Minerals by Sub County Livestock Vaccination against Diseases Quantity and Value of Egg Production by Sub-County Fisheries Quantity, Value and Type of Fish Landed in Freshwater bodies Number, Quantity and Value of Fish Ponds by Sub County Co-operatives Active co-operatives by type, membership, share capital and turnover Active co-operatives by sub-county Savings and Credit Co-operative Societies (SACCOs) by sub-county Annual Savings & Credit Co-operative Statistics County Co-operative Development Revolving Fund Disbursement Laikipia County Enterprise Development Revolving Fund Disbursement Water and Sanitation Households with Access to Water and Sanitation Water sources 13 The Kenya National Bureau of Statistics Household Water sources Manufacturing Firms by Type of Industry Energy Main Sources of Lighting Main Sources of Cooking fuel Transport and communications Map of Laikipia County Transport Network Roads network by type and railway line Kilometers of roads covered by type and agency Public Service Vehicle Operating in Laikipia Traffic handled at county airstrip Postal articles and services handled by sub-county Media and Courier Operators County Access to ICT services Public Transport Vehicles Operating in Laikipia and Passengers Recorded Building Statistics Building Plans Approved for Private Ownership in Nanyuki Office Building Plans Approved for Private Ownership in Rumuruti Office Building Plans Approved for Private Ownership in Laikipia County Reported Completion of New Non - Residential Buildings for Private Ownership by Sector Education Pre-primary Schools Enrolments by School Type Pre-primary School Enrolments and Access Indicators Pre-primary Teachers and Pupil-Teacher Ratio Primary Schools Enrolment by Type (public/private) and Sex Primary School Enrolment by Class and Sex Secondary school by type of accommodation Secondary School Enrolment by Type and Sex Secondary School Enrolment by Class, Sex and Sub County Secondary School Enrolment by Class, Sex and Sub County Secondary School Enrolments and Access Indicators Public Secondary School Teachers by Qualification and Sex Student Enrolment in Public Technical Institutions by Sex Students Enrolment in Kenya TVET Laikipia Students Enrolment in Kenya Universities by Faculty Adult Education Centres by Sub County Learners Enrolment in Adult and Continuing Education- Basic Education Learner's Enrolment in Adult and Continuing Education- Secondary School Education Public health Health facilities by level, ownership and constituency National Hospital Insurance Fund (NHIF) registered members per sector in the county Status of Contraceptive Use Full Immunization Coverage Rate of Under One Year Old Children by Sub-County Governance Environmental crimes reported to National Environmental Management Cases registered, and convictions obtained for selected serious crimes Judicial officers by cadre and sex Probation personnel and offenders by sex Police officers by sub-county and sex Social services New Registration of Women and Youth Groups Female participation in public life Registered persons with disabilities by type of disability and sex Beneficiaries of the orphans and vulnerable fund by sub-county Beneficiaries of the elderly persons fund by sub-county 14 The Kenya National Bureau of Statistics Youth enterprise fund by constituency 15 The Kenya National Bureau of Statistics Appendix H: Laikipia and Wajir County Statistical Abstracts contents No Laikipia CSA 2019 Laikipia CSA 2018 Laikipia CSA 2015 Overview of funding institutions: Overview of funding institutions: County Overview of KNBS (funding institut County Government of Laikipia and Government of Laikipia and KNBS, and and: KNBS, and both institutions: both institutions: i • Vision statement • Vision statement • Vision statement • Mission statement • Mission statement • Mission statement • Core values • Core values • Core values • Foreword • Foreword • Foreword ii Acknowledgements Acknowledgements Acknowledgements iii Table of contents Table of contents Table of contents iv List of abbreviations / acronyms List of abbreviations / acronyms List of abbreviations / acronyms v Symbols and conventions Symbols and conventions used Symbols and conventions used Introduction: Structure of county Introduction: Structure of county Introduction: Structure of 1 governments, the county assembly, the governments, the county assembly, the governments, the county assemb county executive county executive county executive Overview of the county Overview of the county Overview of the county 2 • Fig. 1: map – location of Laikipia in Fig 1: map – location of Laikipia in Kenya Fig 1: map – location of Laikipia in K Kenya Administrative and political units Administrative and political units Administrative and political units • Fig. 2: Map of Laikipia County Not included Not included • Table 1: Administrative units by 3 • Table 1: Administrative units by sub- • Table 1: Administrative units b sub-county and surface area (2016- county (2014-2017) county (2014) 2018) • Table 2: Political units (2016- • Table 2: Political units • Table 2: Political units 2018) Land and climate Land and climate Land and climate • Table 1: Surface area by ca • Table 1: Surface area by category • Table 1: Surface area by category (2014) 4 • Table 2: Topography • Table 2: Topography • Table 2: Topography • Table 3: Climate • Table 3: Climate • Table 3: Climate • Table 4: Mean annual rainfall in • Table 4: Mean annual rainfall in Not included millimeters, by station (2014-2018) millimeters, by station (2013-2017) Gross County Product Gross County Product Gross County Product • Table 1: Gross County Product by Economic Activity, 2013 – 2017 at current prices • Table 2: Gross County Product by 5 Economic Activity, 2013 – 2017 at Not included Not included constant 2009 Prices • Table 3: Share of GDP by Economic Activity (2013-2017) • Table 4: Laikipia County Per Capita GCP (2013-2017) Population and vital statistics Population and vital statistics Population and vital statistics • Table 1: Population Projections by Not included Not included 6 Constituency and Sex, (2016-2018) • Table 1: National population in • Table 1: National populat Not included different census years (1969-2009) different census years (1969-2009) 16 The Kenya National Bureau of Statistics • Table 2: Constituency population by • Table 2: Constituency populat Not included sex, density and number of households sex, density and number of hous (2009) (2009) • Table 2: County population • Table 3: County population projection • Table 3: Population projections projection by sex (2011-2018) by sex (2011-2017) cohorts and sex (2010-2014) • Table 3: Population projections by • Table 4: Population projections by Not included age cohorts and sex (2014-2018) age cohorts and sex (2013-2017) • Table 4: Population Projection of • Table 4: Projection of speci • Table 5: Projection of special age Special Age Groups by Age Cohorts and groups by age cohorts and sex groups by age cohorts and sex (2013-2017) Sex (2014-2018) 2014) • Table 5: Expected and reg Not included Not included births and deaths (2013-2014) • Table 5: Registered Births by Sex • Table 6: Registered births by sex and • Table 6: Registered births and and Registration Centre (2014-2018) registration centre (2012-2017) by sex (2013-2014) • Table 6: Registered Births by Sex • Table 7: Registered births by sex in Nanyuki (2016-2018) Laikipia East (2016-2017) • Table 7: Registered Births by Sex Not included in Rumuruti (2017-2018) • Table 8: Main Causes of Deaths by • Table 8: Top ten causes of deaths by Sex in Laikipia County (2016) sex (2016) • Table 9: Main Causes of Deaths by • Table 9: Causes of deaths by sex Sex in Laikipia County (2017) (2017) Not included • Table 10: Main Causes of Deaths N/A by Sex in Laikipia County (2018) • Table 11: Births and Deaths by place of occurrence registered in Nanyuki (2016-2018) Not included • Table 12: Birth and Death by place of occurrence registered in Rumuruti (2016-2018) • Table 13: Birth and Death by place Table 10: Birth and death occurrences by • Table 7: Percentage of reg of occurrence in Laikipia County (2016- place (hospital/home) (2013-2017) births and deaths by place of occur 2018) Labor Labor Labor • Table 1: Public sector wage • Table 1: Public sector wage Table 1: Public sector wage emplo employment by Sector (2016-2018) employment by sub-sector (2015-2017) by sub-sector (2013-2014) • Table 2: Employment by • Table 2: Establishments employing 5 Economic activity, Size of Enterprise or more people by economic activities 7 and Sub-County (2018) (2015-2017) • Table 3: Monthly Registration of Table 3: Monthly registration of job Not included Job Seekers (2016-2018) seekers (2014-2017) • Table 4: Placement of Job Seekers Not included (2016-2018) Money and banking Money and banking Money and banking 8 • Table 1: Financial institutions • Table 1: Financial institutions (2015- • Table 1: Financial institutions (2016-2018) 2017) Public Finance Public finance Public finance • Table 1: County Revenue by Not included Not included 9 Source (2016/17 -2018/19) • Table 1: National Government • Table 1: National Gover Added in Table 2 allocation, county local revenue and grants allocation of funds (2014/15 and 2016/17) 17 The Kenya National Bureau of Statistics • Table 2: NGCDF (National Government Constituencies • Table 2: Constituency Development Development Fund) and NGAAF • Table 2: Constituency Develo Fund (CDF) allocation by constituency (National Government Affirmative Fund (CDF) allocation by constituen (2014/15 and 2017/18) Action Fund) Allocation by Constituency (2016/17-2018/19) • Table 3: Development and • Table 3: Development and recurrent Table 3: County government rec Recurrent Expenditure (2016/17- expenditure (2015/16 and 2016/17) and development expenditure (201 2017/18) • Table 4: Revenue Collection by Table 4: Revenue collection by revenue Not included Revenue Sources (2015/16-2017/18) sources (2014/15 and 2016/17) Trade and Commerce Trade and Commerce Trade and commerce • Table 1: Licensed Business • Table 1: Licensed business • Table 1: Revenue collection Establishments by Economic activity, establishments by sub-county (2015-2017) single business permits (2013-2014 10 Size and Sub County, 2018 • Table 2: Trading centre Not included Not included licensed business establishmen broad category (2013-2014) Tourism Tourism Tourism • Table 1: Hotels by classification, • Table 1: Hotels by classification, bed bed and conference capacity (2014- and conference capacity (2014-2017) 2018) • Table 2: Hotels Bed Capacity by • Table 2: Hotels bed and room capacity 11 Sub County (2015-2018) by zone and sub-county (2015-2017) Not included • Table 3: Visitor Arrival by • Table 3: Bed occupancy by residency Country of origin (2014-2018) (2014-2017) • Table 4: Visitors by Tourists • Table 4: Visitors by tourist attractions Attractions (2016 – 2018) (2015-2017) Agriculture Agriculture Agriculture • Table 1: Agro-Ecological Zones for • Table 1: Agro-Ecological Zones for the • Table 1: Agro-Ecological Zon the County (2016-2018) County (2016-2017) Sub-Zone Patterns • Fig. 3: Map of Agro-Ecological Not included Not included Zones • Table 2: Land Potential by Area • Table 2: Land Potential by Area and • Table 2: Land Potential by Ar and Sub-County (2017- 2018) Sub-County (2014- 2017) Sub-County (2014) • Table 3: Area Cropped, • Table 3: Area Cropped, Production • Table 3: Area Cropped, Prod Production and Value for Major Crops and Value for Major Crops (2015-2017) and Value for Major Crops (2013-2 (2016-2018) • Table 4: Acreage under Irrigation • Table 5: Acreage under Irriga Not included 12 by Type of Crop grown (2016-2018) Type of Crop grown (2013-2014) • Table 5: Horticultural Production • Table 4: Horticultural Production and Not included and Value by Crop (2015-2018) Value by Crop (2014-2017) • Table 6: Average Retail Prices for • Table 6: Average retail prices for farm • Table 4: Average Retail Pric Farm Inputs (2017 and 2018) inputs (2016 and 2017) Farm Inputs (2013-2014) • Table 7: Average Wholesale Prices • Table 5: Average Wholesale Price for Farm Inputs (2017 and 2018) Range for Farm Inputs (2016 and 2017) • Table 7: Agriculture development extension groups (2012-2017) Not included Not included Not included 18 The Kenya National Bureau of Statistics • Table 7: Average commodities in the Major Market Centers with County (2014) • Table 6: Average prices for dry and beans • Table 8: Retail Market Prices for Selected Food Commodities, January - December 2016 • Table 9: Wholesale Market Prices • Table 9: Wholesale Market Prices for for Selected Food Commodities, Selected Food Commodities (2016) January - December, 2016 • Table 10: Retail Price of Some Selected Food Commodities, January - Not included December (2017) Not included • Table 11: Wholesale Price of • Table 8: Wholesale Price of Some Some Selected Food Commodities, Selected Food Commodities, January- January - December, 2017 December (2015) • Table 12: Retail Price of Some Selected Food Commodities, January - Not included December, 2018 • Table 13: Wholesale Price of • Table 10: Wholesale Price of Some Some Selected Food Commodities, Selected Food Commodities, January- January - December, 2018 December (2017) Livestock Livestock Livestock • Table 1: Estimated livestock • Table 1: Estimated livestock Not included population by type (2016-2018) population by type (2014-2017) • Table 2: Number, quantity and • Table 2: Number, quantity and value • Table 1: Animals slaughtered b value of animals slaughtered by type of of animals slaughtered by type of animal (2013-2014) animal and year (2012-2018) and year (2012-2017) • Table 3: Quantity and value of • Table 3: Quantity and value of other Not included other livestock products (2015-2018) livestock products (2014-2017) • Table 4: Quantity and value of • Table 4: Quantity and value of hides • Table 3: Hides and skins prod hides and skins produced (2015-2018) and skins produced (2014-2017) (2013-2014) • Table 2: Milk production by t Not included Not included animal (2013-2014) • Table 5: Number of milk • Table 5: Number of milk processors processors by sub-county (2015-2018) by sub-county (2015-2017) • Table 6: Annual milk production • Table 6: Annual milk production by 13 by sub-county (2015-2018) sub-county (2014-2017) • Table 7: Price of livestock on sale • Table 7: Average prices of livestock on (2015-2018) sale by type (2015-2017) • Table 8: Prices of meat products • Table 8: Price of meat products (2015- (2015-2018) 2017) • Table 9: Prices of Supplementary • Table 9: Prices of supplementary Livestock Feeds and Minerals by Sub livestock feeds and minerals by sub-county Not included County (2016) (2015) • Table 10: Prices of Supplementary • Table 10: Prices of supplementary Livestock Feeds and Minerals by Sub livestock feeds and minerals by sub-county County (2016) (2016) • Table 11: Prices of Supplementary • Table 11: Prices of supplementary Livestock Feeds and Minerals by Sub livestock feeds and minerals by sub-county County (2018) (2017) • Table 12: Livestock Vaccination • Table 12: Livestock vaccination against Diseases (2016-2018) against diseases (2014-2017) 19 The Kenya National Bureau of Statistics • Table 13: Quantity and Value of • Table 13: Quantity and value of egg Egg Production by Sub-County (2016- production by sub-county (2015-2017) 2018) Fisheries Fisheries Fisheries • Table 1: Quantity, Value and Type Table 1: Number, quantity and value of fish • Table 1: Fish ponds by sub- of Fish Landed in Freshwater bodies ponds by sub-county (2014-2017) (2014-2017) (2015-2018) • Table 2: Number, Quantity and Value of Fish Ponds by Sub County Not included Table 2: Fish landed (2013-2014) (2015-2018) Co-operatives Co-operatives Co-operatives Table 1: Savings and Credit Co-op • Table 1: Active co-operatives by • Table 1: Active co-operatives by type, Societies (SACCOs) by type, type, membership, share capital and membership, share capital and turnover membership and turnover ( turnover (2016-2018) (2015-2017) December 2013, 2014) 14 • Table 2: Active co-operatives by • Table 2: Active co-operatives by sub- sub-county (2014-2018) county (2013-2017) • Table 3: Savings and Credit Co- • Table 3: Savings and Credit Co- operative Societies (SACCOs) by sub- operative Societies (SACCOs) by sub- county (2014-2018) county (2013-2017) • Table 4: Annual Savings & Credit Table 4: Annual Savings & Credit Co- Co-operative Statistics (2015-2018) operative Statistics (2014-2017) Not included • Table 5: County Co-operative Development Revolving Fund Disbursement (2016- 2018) • Table 6: Laikipia County Not included Enterprise Development Revolving Fund Disbursement (2015/16- 2018/19) Forestry Forestry Forestry • Table 1: Gazetted forests (2015- • Table 1: Gazetted forests Table 1: Gazetted forests (2013-2017) 15 2018) 2014) • Table 2: Forest production by type Not included Table 2: Forest production by type (2015-2018) Water and Sanitation Water and Sanitation Water and Sanitation • Table 1: Households with Access to • Table 1: Households with Access Water and Sanitation (2015-2018) (in to Water and Sanitation (2015-2018) forestry section) 16 • Table 2: Water sources (2017) (in Access to water indicator is includ • Table 2: Water sources (2017) forestry section) the Appendices • Table 3: Water sources (2018) • Table 4: Household Water sources Not included (2018) Manufacturing Manufacturing Manufacturing 17 • Table 1: Firms by Type of Industry Not included Not included (2017-2018) Energy Energy Energy • Table 1: Electricity connection by • Table 1: Electricity connection by • Table 1: Electricity connect consumer entity (2016-2018) consumer entity (2014-2017) consumer type (2014) 18 • Table 2: Electricity connect Not included consumer institution (2014) Not included • Table 2: Main Sources of Lighting Not included (2018) 20 The Kenya National Bureau of Statistics • Table 3: Main Sources of Cooking fuel (2018) • Table 4: Average monthly pump Table 2: Average monthly pump prices for Table 3: Average monthly pump pri prices for fuel by category (2015-2018) fuel by category (2013-2014) fuel by category (2013-2014) Transport and communications Transport and communications Transport and communications • Figure 4: Map of Laikipia County Not included Transport Network Not included • Table 1: Roads network by type • Table 1: Roads network by type and and railway line (2016-2018) railway line (2015-2017) • Table 2: Urban roads coverage by • Table 2: Urban roads coverage by • Table 1: Urban roads cover type and distance (2016-2018) type and distance (2013-2014) type and distance (2013-2014) • Table 3: Kilometers of roads • Table 3: Kilometres of roads covered covered by type and agency (2016- by type and agency (2015-2017) 2018) Not included Not included Not included • Table 4: Public Service Vehicle Operating in Laikipia (2016 -2018) 19 • Table 5: Traffic handled at • Table 4: Traffic handled at Nanyuki Nanyuki Airstrip (2016-2018) airstrip (2015-2017) • Table 6: Postal services by sub- • Table 5: Postal services by sub-county • Table 2: Postal services (2014 county (2016-2018) (2015-2017) • Table 7: Postal articles and Table 6: Postal articles and services services handled by sub-county (2016- handled by sub-county (2015-2017) 2018) • Table 8: Media and Courier • Table 7: Media and Courier Operators Operators (2016-2018) Not included • Table 9: County Access to ICT services (2018) • Table 10: Public Transport Not included Vehicles Operating in Laikipia and Passengers Recorded (2018) Building Statistics Building Statistics Building Statistics • Table 1: Building Plans Approved for Private Ownership in Nanyuki Office (2016-2018) • Table 2: Building Plans Approved for Private Ownership in Rumuruti 20 Office (2016-2018) • Table 3: Building Plans Approved Not included Not included for Private Ownership in Laikipia County (2016-2018) • Table 4: Reported Completion of New Non - Residential Buildings for Private Ownership by Sector (2016- 2018) Education Education Education 21 • Table 1: Type of educational • Table 1: Type of educational • Table 1: ECD Centres by Ca institutions (2016-2018) institutions (2015-2017) and Sub-County (2013-2014) 21 The Kenya National Bureau of Statistics • Table 2: Table 20.2: Pupil • Table 2: Pupil enrolment in • Table 2: Pupil enrolment in ECDE Enrolment in Early Childhood (Early Childhood Development Edu (Early Childhood Development Education) Development (ECD) Centers by Sex centers bycategory, sex, and sub- centers bycategory, sex (2014-2017) (2015-2018) (2014) • Table 3: Teachers in ECD cen Not included Not included sub-county and sex (2013-2014) • Table 3: Pre-primary Schools • Table 3: Pre-primary Schools Enrolments by School Type (2016- Enrolments by School Type (2015-2017) 2018) • Table 4: Pre-primary School • Table 4: Pre-primary Schools Enrolments and Access Indicators Enrolments and Access Indicators (2015- (2016-2018) 2017) Not included • Table 5: Pre-primary Teachers • Table 5: Pre-primaryTeachers and and Pupil-Teacher Ratio (2016-2018) Pupil-Teacher Ratio (2015-2017) • Table 6: Primary Schools • Table 6 :Primary Schools Enrolment Enrolment by Type (public/private) and by Type and Sex (2015-2017) Sex (2016-2018) • Table 7 :Primary Schools Enrolment • Table 5: Primary School Enrolm by Class and Sex (2015-2017) Class, Sex & Sub-County (2014) • Table 7: Primary School • Table 8a:Primary School Boys Enrolment by Class and Sex (2016- Enrolment by Class and Sub County (2014- 2018) 2016) Not included • Table 8b: Primary School Girls Enrolment by Class and Sub County (2014- 2016) • Table 4: Primary Schools by Ca Not included Not included and Sub-County (2013-2014) • Table 8: Primary Enrolments and • Table 9: Primary Enrolments and Not included Access Indicators (2016-2018) Access Indicators (2015-2017) • Table 9: Trained Public Primary • Table 10: Public Primary School • Table 8: Public Primary School Teachers by Qualification and Teachers by Qualification and Sex (2015- Teachers by Qualification and Sex Sex (2016-2018) 2017) 2014) • Table 9: Private Primary Not included Not included Teachers by Qualification and Sex 2014) • Table 10: Secondary school by • Table 11: Secondary Schools by Type Not included type of accommodation (2016-2018) of Accommodation (2015-2017) • Table 11: Secondary School • Table 12: Secondary Schools • Table 11: Secondary School Enr Enrolment by Type and Sex (2016- Enrolment by Type and Sex (2015-2017) by Category, Class and Sex (2014) 2018) • Table 13a: Secondary School Boys Enrolment by Class and Sub County (2014- • Table 12: Secondary School • Table 12: Secondary School 2016) Enrolment by Class, Sex and Sub Enrolment by Class, Sex and Sub-C County (2017) • Table 13b: Secondary School Girls (2014) Enrolment by Class and Sub County (2014- 2016) • Table 13: Secondary School • Table 14: Secondary Schools • Table 10: Secondary Schoo Enrolment by Class, Sex and Sub Enrolment by Class, Sex and Sub-county category and Sub-County (2013-20 County (2018) (2017) • Table 14: Secondary School Enrolments and Access Indicators Not included Not included (2016-2018) 22 The Kenya National Bureau of Statistics • Table 15: Public Secondary School • Table 15: Public Secondary School • Table 14: Public Secondary Teachers by Qualification and Sex Teachers by Qualification and Sex (2015- Teachers by Qualification and Sex (2016-2018) 2017) 2014) • Table 15: Private Secondary Teachers by Qualification and Sex 2014) • Table 7: candidates in n examinations (Kenya Certifica Primary Education (KCPE), and Certificate of Secondary Education Not included Not included by sex and sub-county (2013-2014) • Table 13: KCSE Candidates by S Sub-County (2013-2014) Not included • Table 16: Youth Polytechn Category and Sub-County (2013-20 • Table 16: Student Enrolment in • Table 16: Student Enrolment in • Table 17: Student Enrolm Public Technical Institutions by Sex Technical Institutions by Sex, 2013-2014 Youth Polytechnics by Sub-Coun (2015-2018) (2015-2017) Sex, 2013-2014 (2013-2014) • Table 17: Laikipia Students Enrolment in Kenya TVET (2016) • Table 18: Laikipia Students Not included Enrolment in Kenya TVET (2017) • Table 19: Laikipia Students Not included Enrolment in Kenya TVET (2018) • Table 18: Teacher Training C by Category (2014) Not included • Table 19: Universities and Uni Campuses by Category (2013-2014 • Table 20: Laikipia Students • Table 17: Laikipia University Student Enrolment in Kenya Universities by Not included Distribution by faculty (2015-2017) Faculty (2015-2018) • Table 21: Adult Education Centres • Table 18: Adult Education Centres by • Table 20: Adult Education Cen by Sub County, (2015-2018) Sub County, (2014-2017) Sub County, (2013-2014) • Table 22: Learners Enrolment in Adult and Continuing Education- Basic Education (2016-2018) • Table 23: Learner's Enrolment in Not included Adult and Continuing Education- Secondary School Education (2016- Not included 2018) • Table 21: Adult Education Enr by Sex and Sub County (2013-2014 Not included • Table 22: CDF Bursary Benef in Secondary and College Constituency (2013-2014) Public health Public health Public health • Table 1: Health facilities by type, 22 • Table 1: Health facilities by type, • Table 1: Health faciliti ownership and constituency (2016- ownership and constituency (2014-2017) ownership and sub-county (2014) 2018) 23 The Kenya National Bureau of Statistics • Table 2: Health facilities by level, ownership and constituency (2016- Not included Not included 2018) • Table 3: Health facilities beds and • Table 2: Hospital beds and cots by • Table 2: Hospital beds and c cots by Sub-County and type of facility constituency and type of facility (2014- constituency and type of facility (2016-2018) 2017) 2014) • Table 4: Outpatient morbidity for • Table 3: Outpatient morbidity for • Table 3: Outpatient morbid patients under 5 years of age by sub- patients under 5 years of age by sub- patients under 5 years of age b county (2016-2018) county (2015-2017) county (2014) • Table 5: Outpatient morbidity for • Table 4: Outpatient morbidity for • Table 4: Outpatient morbid patients at and above 5 years of age by patients at and above 5 years of age by sub- patients at and above 5 years of sub-county (2016-2018) county (2015-2017) sub-county (2014) • Table 6: Registered medical • Table 5: Registered medical Table 5: Registered medical person personnel per cadre (2016-2018) personnel per cadre (2013-2014) cadre (2013-2014) • Table 7: NHIF registered members Table 6: NHIF registered members per per sector in the county (2017-2018) sector in the county (as by 30th June 2018) • Table 8: Status of Contraceptive Use (2018) Not included • Table 9: Full Immunization Not included Coverage Rate of Under One Year Old Children by Sub-County (2018) Governance Governance Governance • Table 1: New Persons Registered • Table 1: New Persons Registered • Table 1: New Persons Reg (NPR) applications, NPR Identification (NPR) applications, NPR Identification (NPR) and duplicate Identif Documents (IDs) processed and Documents (IDs) processed and collected, Documents (IDs) registered, by collected, by sub-county (2016-2018) by sub-county (2015-2017) county (2013-2014) • Table 2: Registered voters by • Table 2: Registered voters by • Table 2: Collected ID cards b constituency (2016-2018) constituency (2016-2017) county (2014) • Table 3: Traffic accidents (2016- • Table 3: Traffic accidents • Table 3: Traffic accidents (2014-2017) 2018) 2014) • Table 4: Reported crimes by • Table 4: Reported crimes by offence • Table 4: Reported crimes by o offence and sub-county (2017-2018) and sub-county (2014-2017) and sub-county (2013-2014) • Table 5: Persons reported to • Table 5: Persons reported to police to • Table 5: Persons reported to police to have committed offences have committed offences against morality to have committed offences against morality and other offences and other offences against persons, by sex morality and other offences a against persons, by sex (2016-2018) (2014-2017) persons, by sex (2013-2014) 23 • Table 6: Environmental crimes • Table 6: Environmental crimes reported to National Environmental reported to National Environmental Not included Management Authority (NEMA) (2016- Management Authority (NEMA), by 2018) constituency (2015-2017) • Table 7: Distribution of magi and judges in law courts by cadre a Not included Not included (2014) • Table 10: Probation personn offenders by sex (2013-2014) • Table 7: Cases registered, and • Table 7: Cases registered, and convictions obtained for selected convictions obtained for selected serious Not included serious crimes (2016-2018) crimes (2015-2017) • Table 8: Cases handled by courts • Table 8: Cases handled by • Table 6: Cases handle (2016-2018) magistrates’ courts (2016-2017) magistrates’ courts by sex (2014) • Table 9: Judicial officers by cadre • Table 9: Judicial officers by cadre and Not included and sex (2017-2018) sex (2016-2017) 24 The Kenya National Bureau of Statistics • Table 10: Convicted prisoners by • Table 10: Convicted prisoners by type • Table 8: Convicted prisoners b type of offences and sex (2016-2018) of offences and sex (2014-2017) of offences and sex (2014) • Table 11: Probation personnel • Table 11: Probation personnel and Not included and offenders by sex (2015-2017) offenders by sex (2015-2017) • Table 11: Offenders • Table 12: Offenders Serving • Table 12: Offenders serving community service and probation Probation, Community Service and community service, probation and and type of offence (2013-2014) Aftercare by Sex and Type of Offence aftercare by sex and type of offence • Table 12: Offenders S in (2016-2018) (2015-2017) Probation by Sex and Type of O (2013-2014) • Table 13: Police officers by sub- Table 13: Police officers by sub-county and Not included county and sex (2015-2018) sex (2014-2017) Social services Social services Social services Not included Not included Not included • Table 1: Registered women groups • Table 1: Registered women • Table 1: New Registration of (2013-2017) (2013/14-2014/15) Women and Youth Groups (2015/16 - • Table 2: Registered youth 2017/18) Not included (2013/14) • Table 2: Funds disbursement by • Table 2: Funds disbursement by • Table 3: Funds disburseme category 2015/16 and 2017/18) category 2013/4 and 2016/7) category (2013/14) • Table 3: Female participation in • Table 3: Female participation in public 24 public life (2016-2018) life (2015-2017) • Table 4: New registrations of • Table 4: Registered persons with persons living with disabilities by type disabilities by type of disability and sex and sex (2016-2018) (2015-2017) • Table 5: Beneficiaries of the • Table 5: Beneficiaries of the orphans orphans and vulnerable children fund and vulnerable children fund by sub- Not included by sub-county (2015/16 and 2017/18) county (2014/5 and 2016/7) • Table 6: Beneficiaries of the • Table 6: Beneficiaries of the elderly elderly persons fund by sub-county persons fund by sub-county (2013/4, (2015/16 and 2017/18) 2014/5 and 2016/7) • Table 7: Youth enterprise fund by Table 7: Youth enterprise fund by constituency (2015-2018) constituency (2014-2017) Appendices Appendices Appendices • Key demographic, health and socio- • Key demographic, health and • Key social economic indicators economic indicators economic indicators 25 Not included Not included Not included • Kenya’s 47 counties • Kenya’s 47 counties • Kenya’s 47 counties Source: County Statistical Abstracts for Laikipia (2015, 2018 and 2019) and Wajir (2015) 25 The Kenya National Bureau of Statistics Appendix I: KNBS services and products Services and products Timeline Charges Basic statistical data • One to two days Free • Also available on KNBS website Technical advice on official • On request/ same day Free statistics Statistical research services • Varies depending on the nature of At a cost research Reference materials • Immediately/same day Free Sale of cartographic maps • One to two weeks At a cost and shape files Sale of published reports • Three days At a cost (cover price) Students’ industrial • Termly Free /terms and conditions attachments apply Source: KNBS customer service charter . The collected data is later sent to the KNBS HQ team who analyses and produces the corresponding CSA. This process varies depending on the source of funding; if the county government co-funds the CSA, every step of its production is carried out in coordination with the county government (Appendix F: County Statistical Abstracts elaboration steps). CSAs funding and publication in the 47 counties has evolved since its inception in 2015. The inaugural CSAs for all the 47 counties were published in 2015. Funding for the publications of these CSAs was provided by KNBS HQ. Subsequent CSAs were to be published annually, however this was not possible due to KNBS HQ funding challenges. Consequently, most counties only have the 2015 CSA publication. Nonetheless, two KNBS county offices: Laikipia (in 2018 and 2019) and West Pokot (in 2017),49 succeeded in having their county governments partnering with KNBS HQ to co-fund the data collection and publication of their abstracts. In Laikipia, the KNBS-county government partnership has been very successful and for two consecutive years (2018-2019), CSAs have been jointly produced. In doing this, the role of the county government and its acknowledgement of data as a key input for evidence-based decision-making have been crucial. In fact, Laikipia County Governor Ndiritu Muriithi, has stated that the 2019 CSA will “help us [the government] design data-based solutions that can work�. 50 Similarly, important efforts have also been carried out by other KNBS county offices to negotiate and secure funding to produce statistical abstracts. Such county offices include: Kiambu, Turkana and West Pokot, which are currently negotiating funding; Kericho, Kitui, and Nandi have ensured funding and are either analyzing collected data or elaborating their CSA drafts; and Narok, which has finalized its 2018 CSA draft and is pending official approval (see Appendix D: County Statistical Abstracts publication years and progress status). County offices achievements in the production of CSAs provide useful lessons to be learnt. Therefore, a comparative analysis was carried out based on Laikipia and Wajir counties’ experiences in producing CSAs. 49 West Pokot county will soon publish its 2018 CSA. 50 Business Daily, “Use of Data to Unlock Investments in Laikipia.� 26 The Kenya National Bureau of Statistics i) The Laikipia and Wajir County Statistical Abstracts Two CSAs are used as example cases to examine the differences in their abstracts structure and inclusion of indicators. Laikipia CSAs (201551 201852 and 201953) and Wajir CSA (201554) represent comparable examples of counties with inaugural statistical abstracts—yet, with important differences in the processes of production of county statistics. On the one hand, Laikipia’s progressive generation of multiple CSAs illustrates that the partnership between the KNBS and the county has brought successful results in terms of ensuring funding to produce CSAs. On the other hand, Wajir county— part of the World Bank’s North and North Eastern Development Initiative (NEDI) to boost shared prosperity—has been selected as a contrasting example of a county which has produced only one abstract due to lack of funding.55 The outcomes of these counties entail useful lessons to be learnt while allowing for the identification of differences and similarities between the 2015 Wajir and Laikipia abstracts as well as between the 2015-2018-2019 Laikipia CSAs. Wajir and Laikipia’s statistical abstracts incorporate 22 sections based on the KNBS template— however, Laikipia’s evolution includes additional sections. While Wajir and Laikipia counties’ abstracts of year 2015 incorporate 22 sections, Laikiapia’s 2018 and 2019 CSAs introduce additional modules. One of the key challenges with the CSAs is that they do not contain a core set of common county performance indicators that are uniform across all 47 counties. For this reason, different CSAs contain a diversity of indicators that, while being part of the First schedule of the Statistics Act (see Appendix E: First schedule (Statistics Act 2006 and Bill Amendment 2019)), vary across counties. Efforts to harmonize the set of indicators used throughout CSAs should be initiated and led by the KNBS to ensure harmonized data. For Wajir (2015) and Laikipia (2015, 2018 and 2019) CSAs, the following list reflects the available sections across the four CSAs (with differences in the number and types of indicators): 1. Introduction 2. Overview of the county 3. Administrative and political units 4. Land and climate 5. Population and vital statistics 6. Labor (not included in Wajir 2015) 7. Money and banking: financial institutions 8. Public finance 9. Trade and commerce 10. Tourism (not included in Laikipia 2015) 11. Agriculture 12. Retail prices and consumer expenditure 13. Livestock 14. Co-operatives 15. Forestry 16. Energy 17. Transport and communications 51 Kenya National Bureau of Statistics, “County Statistical Abstract. Laikipia County,� 2015. 52 Kenya National Bureau of Statistics, “County Statistical Abstract. Laikipia County,� 2018. 53 Kenya National Bureau of Statistics-County Government of Laikipia, “County Statistical Abstract. Laikipia County.� 54 Kenya National Bureau of Statistics, “County Statistical Abstract. Wajir County.� Wajir was selected 55 39 out of the 47 Kenyan counties only have the 2015 CSA and have not produced further CSAs due to lack of funding. 27 The Kenya National Bureau of Statistics 18. Education 19. Public health 20. Governance 21. Social services 22. Key demographic, health and socio-economic indicators Differences across CSAs reflect an evolutionary process which has derived in the creation of more comprehensive CSAs that nonetheless, reflect the interests of the county government. Even if the 2015 Wajir and Laikipia CSAs present useful indicators, further information is needed to more comprehensively describe key economic sectors in the counties. Notably, Laikipia’s 2018-2019 CSAs address this, by incorporating additional indicators which are useful to better illustrate the socioeconomic conditions experienced in the county. For instance, the addition of the Gross County Product to the 2019 Laikipia CSA was under the explicit request of the county government.56 Similarly, the 2018 CSA presents important additional sections that were kept and extended in the 2019 Laikipia CSA. Additional section include: county revenue by source (Public finance); agro-ecological zones (Agriculture); access to water and sanitation; status of contraceptive use (Public health); crime and offenders data disaggregated by sex (Governance) (Appendix G: Additional CSA sections Laikipia 2018- 2019, for a complete list of additions). c. AVAILABILITY AND ACCESS TO DATA Data produced from KNBS surveys is available on various online portals. KNBS data can be accessed free of charge via online databases and offline sources such as surveys and census datasets as well as yearly KNBS reports. “Datasets contain micro-data (records of individual persons and households) while the reports provide macro-data information.� 57 According to the KNBS, there are five portals through which data in Kenya can be accessed—however, only two of them are currently active. The portals listed on the KNBS website include: Table 2: Data portal availability Web Portal Availability KNBS Data Visualization58 Not Available The Kenya Data Portal Not Available Kenya Socio-Economic Database (KenInfo)59 Not Available National Data Archive (KeNADA)60 Available Kenya Open Data61 Available In addition to these portals, the Maarifa Centre62 provides an online platform to document and share experiences, innovations and solutions on Kenya’s devolution process. The Maarifa Centre platform does not grant access to data, however it contains useful information such as fact sheets, budget 56 Even if additions suggested by the County Government may provide relevant and useful information for evidence-based decision-making, it is important to ensure that the KNBS production of statistics is neutral and does generate any potential conflict of interest that may affect the quality of the statistical outputs. 57 Kenya National Bureau of Statistics, “KNBS Data.� 58 Kenya National Bureau of Statistics, “KNBS Data Visualization.� 59 Kenya National Bureau of Statistics, “Kenya Socio-Economic Database (KenInfo).� 60 Kenya National Bureau of Statistics, “National Data Archive (KeNADA).� 61 ICT Authority, “Kenya Open Data.� 62 Maarifa Centre, “Maarifa Centre. Sharing Kenya’s Devolution Solutions.� 28 The Kenya National Bureau of Statistics indicators, and sectorial analyses for each Kenyan county. Its main purpose is to serve as a knowledge sharing and learning online space for capturing lessons and experiences from the 47 County Governments. Data availability is a key component of the relationship between the KNBS and the World Bank. The World Bank extended Kenya a $50 million credit in 2015 through a program known as the Kenya Statistics Program-for-Results. The aim of the program is to support KNBS to generate better and more accessible data to inform policy-makers and contribute to strengthening its capacity. One of the program development outcome indicators is to improve access to official household survey microdata. Within this program, $3.5 million is disbursed against given microdata-related results including $1 million for the launch of the Kenya National Data Archive (KeNADA). The KeNADA is the KNBS’s portal to download official statistics reports and micro-data. The KeNADA portal uses the open-source software NADA Microdata Cataloging Tool—a project of the World Bank Group 63 — provides different types of information on 63 studies: seven censuses and 56 surveys carried out between 1969 and 2018. Information available in the Central Data Catalog varies in depth and quality; while some studies include a results report, questionnaires used, access to microdata and visualization of descriptive data, other studies only provide a broad description.64 Data available in the KeNADA is categorized in two groups depending on its source: a) ‘Public use data files’, contains 45 KNBS micro-datasets that can be downloaded only if an ‘Application for Access to a Public Use Dataset’ was submitted and accepted by the KNBS;65 b) ‘Data available from external repository’, incorporates information from 10 surveys and links to download relevant micro-data from the World Bank Microdata library.66 The KeNADA portal is a significant source for county-level data. Since the promulgation of Kenya’s constitution, the KNBS has produced various surveys designed to be representative at the county level. In order to fulfill key poverty and socio-economic data gaps, the KNBS conducted the 2015/16 Kenya Integrated Household Budget Survey (KIHBS). The 2015/16 KIHBS survey resulted in the KNBS production of peer-reviewed labor, poverty as well as socio-economic indicators at the county level.67 The anonymized microdata used to produce these indicators is available on the KeNADA portal. Additionally, in order to provide data toward updating the system of national accounts and establishing a business register, a survey on small and medium enterprises was conducted, for which county-level microdata is also available on the KeNADA portal. Furthermore, the KeNADA data portal includes data collected in conjunction with MDAs on various topics such as health (Kenya Household Health Expenditure and Utilisation Survey) and housing (National housing survey); these surveys are representative at the county level. The KNBS has conducted analysis designed to provide estimates on the size of each county’s economy. In 2019, the KNBS disseminated the first annual gross county product (GCP) report aimed 63 International Household Survey Network (IHSN), “NADA Microdata Cataloging Tool.� 64 For instance, the Kenya Population Census 1962 only includes the study description. Similarly, the Kenya Survey of Industrial Production, the Kenya Foreign Investment Survey (FIS) 2010, the FIS 2013, the Kenya Multiple Indicator Cluster Survey Fifth Round (Western and North Rift Survey) provide only the questionnaires used and the study description. 65 Kenya National Bureau of Statistics, “Get Microdata.� 66 World Bank Group, “Microdata Library.� 67 The 2015/16 KIHBS produced an extensive range of socio-economic indicators at the county level contained in three reports. These three are the basic report, the basic report on wellbeing and the basic labor force report. 29 The Kenya National Bureau of Statistics at measuring the economy of the 47 Kenyan counties.68 The report provides the sectoral contribution to the economy of each county well as a comparison of the size of each county’s economy in both real and per capita terms. The indicators produced by the report are aimed at estimating the revenue potential across counties, as well as providing information for private sector entities to assess the potential to invest in a given county. While the GCP report provides these useful indicators, this exercise could be improved by making the data available through to an online portal such as the KeNADA or the Maarifa Centre platform. The GCP is an important step toward the production of macroeconomic data at the county level, currently there are no proposals to extend this further such as with the creation of county-level price indices. The Kenya Open Data portal provides access to datasets published by Government institutions, including the KNBS. The Kenya Open Data is a portal developed by the Information and Communication Technology (ICT) Authority69 that makes public Government datasets accessible for free to the public.70 The data on this portal uses published Government data from several sources including MDAs such as the ministries of Finance and Planning, Health and Education, County Governments, and also from the KNBS and the World Bank.71 The Kenya Open Data portal provides aggregated data on some socioeconomic indicators for 42 of the 47 Kenyan counties. Data can be directly downloaded from the platform without an official data request. International organizations also grant access to platforms to download and visualize data. In addition to the data sources provided by the KNBS and the ICT Authority, micro-data from 224 surveys carried out in Kenya can be downloaded from the World Bank Central Data Catalog.72 Added to that, the World Bank provides a data visualization platform where data can also be downloaded. 73 Moreover, data is also available through the Humanitarian Data Exchange (HDX) portal provided by OCHA.74 The HDX hosts 10,012 datasets from 253 locations, including Kenya. There are 37 datasets for Kenya, however, most of them can also be accessed through the KeNADA. Data collected to produce statistics is available on different online portals that, while demonstrating the interest of the Government in granting access to public information, reflects the lack of a central source that provides easy access to up-to-date data. While national platforms provide access to some data, they tend to be difficult to use and often entail lengthy processes to download data. The lack of a unified system to visualize and download data can hinder efforts to: design evidence-based policies and programs (governmental and non-governmental), identify national trends, improve accountability for the use of public resources and transparency, and monitor progress in the administrative devolution. 68 Kenya National Bureau of Statistics, “Gross County Product.� 69 The ICT Authority is a State Corporation under the Ministry of Information Communication and Technology. Established in August 2013, the Authority is tasked with rationalizing and streamlining the management of all Government of Kenya ICT functions. 70 ICT Authority, “Kenya Open Data.� 71 World Bank Group, “Government of Kenya Releases Data to Public on Easy to Use Web Portal.� 72 World Bank, “Central Data Catalog.� 73 World Bank, “Data.� 74 UN OCHA, “The Humanitarian Data Exchange.� 30 Conclusions and recommendations CONCLUSIONS AND RECOMMENDATIONS To ensure that the statistical outputs generated by the KNBS county offices meet quality standards, it is essential to strengthen capacity by hiring skilled personnel. Different county offices are staffed by diverse—and often insufficient—staff members the majority of whom do not have statistics- related university degrees (statistical assistants), while some others do not have enough experience to deliver the needed outcomes (interns and volunteers). Moreover, numerous statistical assistants and CSOs will retire soon. Coupled with the lack of enough and qualified county-level staff, terms of reference and functional guidelines are not available for staff responsibilities at the county level. Therefore, key recommendations for building the KNBS’s capacity at the county level are to hire skilled professionals to properly staff each county office, train the existing workforce to acquire the required skillset for their positions as well as to develop more clearly described roles that are harmonized across counties. Since the KNBS Board of Directors is responsible for determining the structure and staffing levels, as well as to recruit suitable staff,75 its role is crucial in ensuring that county offices have skilled and enough staff. Broadening the functions and roles of KNBS county statistical staff to optimally utilize their skills could support efforts to produce outputs of comparable quality. Besides undertaking logistical and managerial duties, CSOs and deputy CSOs, with statistics-related academic training, could better utilize their technical skills by contributing to county-specific survey data analysis and county-specific reports elaboration. By undertaking such activities, county offices can gain valuable insights that could help them understand the bigger picture of KNBS’s projects as well as the importance of their contribution to such projects. Expanding CSOs and deputy CSOs’ roles could also be beneficial to closing gaps between HQ and county offices as well as to improve communication flows. Moreover, county staff members could also be involved in the planning stages of county-specific surveys—and not only in the implementation stage. This can provide useful inputs for context analysis, needs assessments and development of risk mitigation strategies. Partnerships between the KNBS and MDAs must be nurtured to ensure production of reliable statistics. Regular county meetings can foster the partnerships between MDAs and the KNBS, these forums can be used for the discussion of data collection activities and data requests. Successful meetings are those that are facilitated by a diverse committee team, including the deputy county commissioner as the chairperson, the KNBS CSOs and relevant ministry officials, as in the case of Laikipia and Kitui counties. In Laikipia county, there are monthly meetings chaired by the county commissioner. The county secretary, who is the link person between the national and county governments, is also in attendance. During the 2019 CSA data collection stage, the county secretary undertook significant effort in linking the KNBS county office to the data request providers. Therefore, it is paramount to proactively establish close connections between MDAs and the KNBS by attending regularly to this type of meetings. Equally important, it is recommendable for the KNBS to reinforce its protocols to review the accuracy of data provided by MDAs. Such reinforcement could support efforts to improve the quality of the data. Successful partnerships between the KNBS and county governments have proven to be fundamental to produce CSAs—nonetheless, such collaborations must be carefully handled. The 75 Government of Kenya, “The Statistics Act, 2006,� 79. 31 Conclusions and recommendations case of Laikipia’s progressive elaboration and publication of CSAs, illustrates that partnering with county governments to co-fund CSAs can result in beneficial outputs for both, the KNBS and county governments. Nevertheless, these co-funding collaborations may result in potential conflicts of interest that could severely affect the quality and veracity of the data. For instance, a co-funding county government may try to avoid the inclusion of specific indicators to reflect better county performance or, may try to add information to improve its reputation and gain access to certain national resources. Such collaborations are also prone to generate rent-seeking and concealment of administrative information. Moreover, KNBS-county government co-funding partnerships may affect KNBS’s professional independence for the production and dissemination of statistics without the interference or influence of any individual, interest group or political authority. 76 Partnerships between KNBS and county governments are highly important and necessary—yet, they must be handled carefully. In order to avoid conflicts of interest, co-funding collaborations must integrate a neutral and independent entity that ensures the reliability and veracity of county data provided by MDAs. Taking the above into consideration, the following recommendations are based on Laikipia’s experience, and other KNBS county offices’ strategies to secure both financial and logistical county government support in production of CSAs: 1. A tailored CSA proposal based on the data needs and interests of county governments can determine access to government funds. In Laikipia, the KNBS county office firstly assessed the government’s data needs and interests to formulate a tailored CSA proposal and co- funding request. Once the government’s needs and interests were identified, meetings between the KNBS and the Laikipia governor were held to discuss the utility of the CSA for the county government as well as to agree on key indicators. Such close communication and focus on the county government’s needs and interests were key in ensuring county funding. Therefore, to ensure co-funding, county offices could carry out an assessment of county governments’ needs and interests to elaborate a tailored CSA proposal. Nevertheless, the KNBS should include an independent entity that assesses risks to avoid any potential conflict of interest. 2. The engagement and support of KNBS HQ for KNBS county offices is crucial to build successful partnerships with county governments. According to the Act (Amendment) 2019, “collaborating with and assisting the county governments or any other institutions in the production of official statistics�77 is one of the KNBS’s responsibilities. Therefore, in building successful partnerships with county governments—and ensure funding—the support of the KNBS HQ is crucial especially during early stages of negotiations. Ideally, a KNBS HQ staff member should participate in every meeting in which CSA funding is negotiated with county governments’ leadership. 3. County-level statistical outputs must be the result of an independent process free from political influence. In Laikipia, Makueni and West Pokot counties, the governors acknowledge data as a key input for evidence-based decision-making and thus, promote the production and use of statistics. Therefore, a practical approach in accessing government funding for other counties, is to map county governors’ positions and opinions towards the use of 76 National Council for Law Reporting, The Statistics (Amendment) Act, 2019, 712. 77 National Council for Law Reporting, 712. 32 Conclusions and recommendations statistics. This mapping can derive in the identification of governors with positive tendencies to approach them and initiate a co-funding partnership. While this approach may be instrumental in securing county government funds to address the urgent need for generating CSAs, county outputs must not be influenced by county governors’ opinions. Therefore, ideally the KNBS budget should allow for funding county statistical outputs, ensuring data accuracy and professional independence. 4. CSAs quality should be enhanced by revising and updating the templates provided by the HQ team as well as by creating a harmonized list of indicators. The KNBS-HQ is responsible for providing technical guidelines and templates to produce county-level statistics. Thus, the HQ team must ensure that the quality of the templates meet the needed standards to guarantee successful data collection processes and the production of quality statistics homogeneously available across counties. Therefore, it is recommendable for the KNBS to revise and enhance the CSA templates by selecting key indicators, leaving out tables that may not provide additional information but that on the contrary could result redundant. Such editions can derive in more practical templates for the creation of concise CSAs which are easy to use by different audiences. It is also important to develop a core set of common county performance indicators across all 47 counties and thus, ensure harmonized CSAs containing comparable indicators. Coupled with developing a standardized set of indicators and improved CSA templates, data collection and data quality best practices workshops for the county offices’ staff could improve the quality of the data collected by county staff. Kenya’s statistical capacity can be improved by creating a unified portal to visualize, download data and promote knowledge sharing. The availability of statistical data is not only policy relevant but is also a crucial “input for policy analysis and evaluation conducted by researchers and evaluators outside of government.�78 Improving data access and availability can promote the use of data for analysis carried out by external users, which can improve the quality of statistical agencies processes 79 as well as accountability for the use of public resources and transparency. The Act (Amendment) 2019, recognizes the importance of data availability and access by stating its relevance on the Fundamental Principles of Official Statistics. The Principle number one, acknowledges that “official statistics that meet the test of practical utility should be compiled and made available on an impartial basis by the KNBS to honor citizens’ entitlement to public information�.80 Public information should be made available in a coordinated, systematized and easy-to-access manner. Thus, a unified portal for up-to-date data visualization, national and county-level micro-data download and knowledge sharing (following the Maarifa Centre experience), can support efforts to enhance Kenya’s statistical capacity by improving data availability and access, using state of the art technologies and learning lessons from other national statistics offices worldwide.81 78 National Research Council et al., Ensuring the Quality, Credibility, and Relevance of U.S. Justice Statistics. 79 Abowd, Haltiwanger, and Lane, “Integrated Longitudinal Employer-Employee Data for the United States.� 80 National Council for Law Reporting, The Statistics (Amendment) Act, 2019, 720. 81 See Appendix J: List of national statistics offices websites worldwide. 33 References REFERENCES Abowd, J, J Haltiwanger, and J Lane. “Integrated Longitudinal Employer-Employee Data for the United States.� American Economic Review Papers and Proceedings. 94, no. 2 (2004): 224–29. Business Daily. “Use of Data to Unlock Investments in Laikipia.� 2019. https://www.businessdailyafrica.com/news/Use-of-data-to-unlock-investments-in- Laikipia/539546-5142976-q36lsnz/index.html. Capital News. “President Kenyatta Signs Statistics (Amendment), Accreditation Service Bills into Law.� 2019. https://www.capitalfm.co.ke/news/2019/08/president-kenyatta-signs-statistics- amendment-accreditation-service-bills-into-law/. Government of Kenya. “The Statistics Act, 2006.� Kenya, 2006. ———. The Statistics (Amendment) Bill, 2019, Pub. L. No. 37, 477 (2019). http://www.parliament.go.ke/sites/default/files/2019- 06/Statistics%20%28Amendment%29%20Bill%2C%202019.pdf. ICT Authority. “Kenya Open Data,� 2019. http://www.opendata.go.ke/. International Commission of Jurists, ICJ. Handbook on Devolution: The Kenyan Section of the International Commission of Jurists. Kenya, 2013. International Household Survey Network (IHSN). “NADA Microdata Cataloging Tool.� NADA, 2019. http://nada.ihsn.org/. Kenya National Bureau of Statistics. “Get Microdata,� 2019. http://statistics.knbs.or.ke/nada/index.php/auth/login/?destination=catalog/56/get_microd ata. ———. “Gross County Product,� 2019. https://www.knbs.or.ke/download/gross-county-product- 2019/. Kenya National Bureau of Statistics, KNBS. “Census Cartographic Mapping,� 2017. https://www.knbs.or.ke/census-cartographic-mapping/. ———. “Consumer Price Indices and Inflation Rates for June 2019,� 2019. https://www.knbs.or.ke/consumer-price-indices-and-inflation-rates-for-june-2019/. ———. “County Statistical Abstract. Laikipia County.� Kenya, 2015. ———. “County Statistical Abstract. Laikipia County.� Kenya, 2018. ———. “County Statistical Abstract. Wajir County.� Nairobi, 2015. ———. “County Statistical Abstracts,� 2018. https://www.knbs.or.ke/county-statistical-abstracts/. ———. “Economic Survey 2019,� 2019. https://www.knbs.or.ke/download/economic-survey-2019/. ———. “Kenya National Bureau of Statistics County Brief. REF: 52/21/A/13(10),� 2013. ———. “Kenya Socio-Economic Database (KenInfo),� n.d. http://statistics.knbs.or.ke/keninfo/. ———. “KNBS Data,� 2013. https://www.knbs.or.ke/knbs-data/. ———. “KNBS Data Visualization,� n.d. https://www.knbs.or.ke/knbs-data/Visualizations/. 34 References ———. “KNBS Mandate,� n.d. https://www.knbs.or.ke/knbs-mandate/. ———. “KNBS Organization Structure,� 2018. https://www.knbs.or.ke/organization-structure/. ———. “National Data Archive (KeNADA),� 2019. http://statistics.knbs.or.ke/nada/index.php/home. ———. “Quarterly Gross Domestic Product Report First Quarter, 2019,� 2019. https://www.knbs.or.ke/?s=gross+domestic+product. Kenya National Bureau of Statistics-County Government of Laikipia. “County Statistical Abstract. Laikipia County.� Kenya, 2019. Maarifa Centre. “Maarifa Centre. Sharing Kenya’s Devolution Solutions,� 2019. https://maarifa.cog.go.ke/?tk=1572966266. National Council for Law Reporting. The Constitution of Kenya. Kenya, 2010. ———. The Local Government Act (2010). http://kenyalaw.org/kl/fileadmin/pdfdownloads/Acts/LocalGovernmentAct.pdf. ———. The Statistics (Amendment) Act, 2019 (2019). http://kenyalaw.org/kl/fileadmin/pdfdownloads/AmendmentActs/2019/StatisticsAmendme ntAct2019.pdf. National Research Council, Panel to Review the Programs of the Bureau of Justice Statistics, Committee on National Statistics, and Division of Behavioral and Social Sciences and Education. Ensuring the Quality, Credibility, and Relevance of U.S. Justice Statistics. Washington: The National Academies Press, 2009. PHIA Project. “PHIA Timeline. Kenya.,� 2019. https://phia.icap.columbia.edu/timeline/. Standard Digital. “President Uhuru Signs Statistics (Amendment), Accreditation Service Bills into Law.� 2019. UN OCHA, United Nations Office for the Coordination of Humanitarian Affairs. “The Humanitarian Data Exchange,� 2019. https://data.humdata.org/organization/kenya-national-bureau-of- statistics. World Bank. “Central Data Catalog.� Central Data Catalog. Kenya, 2019. https://microdata.worldbank.org/index.php/catalog?sort_by=rank&sort_order=desc&sk=Ke nya. ———. “Data,� 2019. https://data.worldbank.org/country/kenya?view=chart. ———. “Development of the National Statistical System Project,� 2016. https://ieg.worldbankgroup.org/sites/default/files/Data/reports/ppar_kenya_01042017.pdf . ———. “Statistical Capacity Indicator Dashboard.� Washington DC, 2018. http://datatopics.worldbank.org/statisticalcapacity/SCIdashboard.aspx. World Bank Group. “Government of Kenya Releases Data to Public on Easy to Use Web Portal.� 2011. https://www.worldbank.org/en/news/press-release/2011/07/08/government-kenya- releases-data-public-easy-use-web-portal. 35 References ———. “Microdata Library,� 2019. https://microdata.worldbank.org/. 36 Appendices APPENDICES Appendix A: Key Informant Interview guide82 Questions designed to be asked during the phone-based KIIs with the 47 KNBS county statistical officers and available KNBS HQ staff are as below: 1. Institutional setup: a) How would you describe the statistical capacity in your county, in terms of number of statistical staff and demonstration of interest in production of county-level statistical abstracts, or any other criteria you’d advise? b) Please describe the (a) roles, (b) responsibilities and (c) reporting of any or all of these county statistics staff. 2. County statistical capacity: a) Please share examples of counties that would fit into these 2 categories of statistical capacities, and why? • Low • High b) In which category does [your county/county X] fit in terms of the level of statistical capacity, and why? • Low • Medium • High 3. County-MDAs-KNBS dataflow relationships a) Are you familiar with the term MDA (Ministries, Departments and Agencies) [if not, briefly describe] - how do MDAs fit into the aforementioned relationship? b) Could you describe the data flow for any key indicator from county to MDAs to KNBS HQ? c) Could you describe the institutional framework governing county data collection, production of selected key indicators and observed data flows? 4. Could you provide any recommendations on how to improve county statistics processes? Thank you very much for your time and inputs. 82 This is non-exhaustive list of questions addressed during the KIIs. Additional questions and topics were discussed depending on the respondent. 37 Appendices Appendix B: County offices staff responsibilities83 Staff member Responsibilities CSO Identify statistical units for data collection CSO Carry out pre-tests and piloting data collection instruments Statistical assistant Collect data CSO/Deputy CSO Coordinate and supervise data collection for both household and establishment- based surveys, as well as administrative data CSO/Deputy CSO Capture data for newly developed and updated sampling units CSO/Deputy CSO Update statistical registers and checklists CSO/Deputy CSO Update county specific sampling units from respective sampling frames CSO Update records in the sampling frame databases CSO Update indicators and data collection instruments CSO/Deputy CSO Update and maintain databases on official statistics e.g., county socio-economic data CSO Prepare instruments for the elaboration and update of sampling frames CSO Prepare summary tables on status and usage of the sampling frames CSO Document the data collection procedures used in the national statistical system CSO/Deputy CSO Compile metadata CSO Compute statistical indices CSO/Deputy CSO Compile and collate County Statistical Abstract (CSA) data Deputy CSO Assisting the CSO in preparing CSAs CSO/Deputy CSO Disseminate county level statistics CSO Provide statistical standards and methods guidance to stakeholders at the county level All Provide technical support and product delivery, including: respond to requests for technical advice on official statistics, provide basic statistical data and statistical research services, sell cartographical maps and published reports. CSO Set up control measures for dispatch and receipt of questionnaires CSO/Deputy CSO Following-up on non-response from data providers CSO/Deputy CSO Preparing reports CSO/Deputy CSO Ensure active representation of KNBS in the county through the relevant committees and functions as assigned by the CSO Statistical assistant Data entry, editing and on-line transmission Source: KNBS CSOs 83 This is a non-exhaustive list of responsibilities carried out by county offices staff. Due to the variability in county offices staffing, the staff member in charge of each responsibility may differ across county offices. 38 Appendices Appendix C: KNBS data collection flows for main routine surveys Routine Data collection Data collection Data source Data flow steps survey type frequency timeline Building and Monthly - - County government, 1. Standard template sent from HQ (production directorate, construction department) to CSOs construction housing and public works (also available on KNBS intranet) statistics - Committee in charge of 2. CSOs send official letter to county secretary or executive member in Ministry of Roads and survey construction plans and Public Works to request specific data approvals 3. Data request is forwarded to quantity surveyors, at the county level -Engineers dealing with 4. At the national level, requested data is counterchecked with that of the National Construction building quality standards Authority (complete and approve 5. Data is sent to HQ for analysis forms) 6. HQ analyzes and publishes data in a chapter of the annual Economic survey report Consumer Monthly (for 2nd to 3rd week Selected wholesale and 1. HQ sends spreadsheet template with selected products for data collection (products are coded) Price Index some counties). of every month, retail outlets 2. County data collectors go to selected outlets (shops, markets, etc) to collect prices of selected survey In 2018, it was latest by 22nd coded products conducted in 20 day of each 3. Collected data is sent to HQ counties month 4. HQ analyzes data and publishes compiled inflation rates at the end of each month County Gross Quarterly End of every County departmental 1. Template is sent from HQ (Production directorate) to County Executive Member Domestic year quarter heads 2. Data request assigned to one of the statisticians in the planning department, who takes the Product request, together with an official letter, through each of the main county departments (e.g. (County GDP) Ministries of Agriculture, Health, Livestock, Finance and Tourism) survey 3. Assigned persons in each of the aforementioned departments provide the requested data (usually within one day) 4. Requested data is sent to HQ for analysis – in case of any delays, HQ personnel coordinates the timely provision of data request 5. HQ analyzes and publishes data in the Quarterly Gross Domestic Product Report. Hotel Monthly 3-month data Hotel records. The hotels 1. HQ Macroeconomics directorate personnel liaises with CSOs for survey preparations including statistics collected at the surveyed are determined budgetary allocations survey end of each by the Macroeconomics 2. HQ designs questionnaire templates and operational manuals and sends them to CSOs (also quarter of a directorate by using available on KNBS intranet) year available data. E.g., from 3. CSOs contact and train data collectors, and carry out logistical preparation previous hotels censuses 4. Tracking system outputs depicting key indicators are sent to HQ on a weekly basis to monitor and determining their progress of data collection turn-overs and star- 5. Data collected is compiled and sent to HQ for analysis ratings 6. HQ analyzes and publishes data in a chapter of the annual Economic survey report 39 Appendices Routine Data collection Data collection Data source Data flow steps survey type frequency timeline Labor Annually Data collected 1. KNBS HQ sends questionnaire template to county secretary enumeration as at 30th of 2. CSOS follow up on the request (may sometimes need following up with the planning urvey June every year department) (for the 3. Data is sent to HQ previous 4. HQ analyzes and publishes data in the annual Economic survey report financial year) Livestock Monthly 3-month data District veterinary officers 1. HQ produces template and uploads it to the KNBS intranet hides & skin collected at the 2. CSOs download template questionnaire from the intranet survey end of each 3. CSOs train data collectors quarter of a 4. Data collection is monitored and supervised by CSOs year 5. Data is sent to HQ 6. HQ analyzes and publishes data in the annual Economic survey report Monthly Monthly Selected/available firms 1. HQ produces template and uploads it to the KNBS intranet industrial where cost of production 2. CSOs download template questionnaire from the intranet survey of can be monitored e.g. 3. Data is collected through already trained data collectors who survey selected firms production bread, milk industries 4. Data is sent to HQ 5. HQ analyzes and publishes data in the annual Economic survey report Retail market Weekly Weekly Markets 1. HQ produces template and uploads it to the KNBS intranet price survey 2. CSOs download template questionnaire from the intranet 3. Data is collected through already trained data collectors who survey selected firms 4. Data is sent to HQ 5. HQ analyzes and publishes data in the annual Economic survey report 40 Appendices Appendix D: County Statistical Abstracts publication years and progress status No County Latest CSA Upcoming CSAs progress status* publication year 1 Baringo 2015 - 2 Bomet 2015 - 3 Bungoma 2015 - 4 Busia 2015 - 5 Elgeyo Marakwet 2015 - 6 Embu 2015 - 7 Garissa 2015 - 8 Homabay 2015 - 9 Isiolo 2015 - 10 Kajiado 2015 - 11 Kakamega 2015 - 12 Kericho 2015 In Progress: 2018 CSA data collection is in preparation, questionnaires have been created, and enumerators have been trained. 13 Kiambu 2015 Negotiation: 2019 CSA proposal draft and funding are pending approval. 14 Kilifi 2015 - 15 Kirinyaga 2015 - 16 Kisii 2015 - 17 Kisumu 2015 - 18 Kitui 2015 In Progress: 2018 CSA draft is being prepared. 19 Kwale 2015 - 20 Laikipia 2018 Published: 2019 CSA is available on KNBS website84 21 Lamu 2015 - 22 Machakos 2015 - 23 Makueni 2015 - 24 Mandera 2015 - 25 Marsabit 2015 - 26 Meru 2015 - 27 Migori 2015 - 28 Mombasa 2015 - 29 Muranga 2015 - 30 Nairobi 2015 - 31 Nakuru 2015 - 32 Nandi 2015 In Progress: 2018/19 CSA data in being analyzed. 33 Narok 2015 Finalized: 2017 CSA draft has been complete and is pending approval. 34 Nyamira 2015 - 35 Nyandarua 2015 - 36 Nyeri 2015 - 37 Samburu 2015 - 38 Siaya 2015 - 39 Taita Taveta 2015 - 40 Tana River 2015 - 41 Tharaka Nithi 2015 - 42 Trans Nzoia 2015 - 43 Turkana 2015 Negotiation: 2018/19 CSA is pending government and KNBS approval. 44 Uasin Gishu 2015 - 45 Vihiga 2015 - 46 Wajir 2015 - 47 West Pokot 2017 Negotiation: 2018/9 CSA indicators were agreed, and funding is pending. *Counties without a listed status have not negotiated funding with county governments due to a lack of an established partnership. 84 Kenya National Bureau of Statistics-County Government of Laikipia, “County Statistical Abstract. Laikipia County.� 41 Appendices Appendix E: First schedule (Statistics Act 2006 and Bill Amendment 2019) Matters concerning which statistical information may be collected, compiled, analyzed, abstracted and published. The Statistics Act 200685 The Statistics (Amendment) Bill 201986 1. Population. 1. Population. 2. Vital occurrences and morbidity. 2. Births and deaths. 3. Immigration, emigration, hotels and tourism. 3. Immigration, emigration. 4. Housing. 4. Hotels and Tourism 5. Rents. 5. Housing. 6. Real property. 6. Real property. 7. Land tenure and the occupation and use of land. 7. Land, topography and climate. 8. Finance. 8. Finance and insurance. 9. External finance and balance of payments. 9. International trade, and Balance of payments. 10. Capital investment. 10. Capital investment. 11. Savings. 11. Savings. 12. Income, earnings, profits and interest. 12. Expenditure and consumption. 13. Personal expenditure and consumption. 13. Wholesale and retail trade, repair of motor 14. International and external trade. vehicles and motorcycles. 15. Banking, insurance and finance. 14. Manufacturing. 16. Wholesale and retail trade including agents and brokers. 15. Construction. 17. Manufacturing, building, construction and allied industries. 16. Mining and quarrying. 18. Mining and quarrying, including the prospecting of 17. Agriculture. metallic, nonmetallic, petroleum and natural gaseous 18. Forestry and logging. products. 19. Fishing. 19. Agriculture, including animal husbandry, horticulture and 20. Producer, wholesale and retail prices of allied industries. commodities. 20. Forestry and logging. 21. Employment, earnings and unemployment. 21. Hunting and fishing. 22. Labour. 22. Stock of manufactured and unmanufactured goods. 23. Energy. 23. Producer, Wholesale and retail prices of commodities. 24. Water and sanitation. 24. Storage and warehousing. 25. Transport and storage. 25. Employment and unemployment. 26. County government. 26. Salaries, wages, bonuses, fees allowances and other 27. Community, business and personal services. payments. 28. Arts, entertainment and recreation. 27. Industrial disturbances and disputes. 29. Handicrafts and rural industries. 28. Injuries, accidents and compensation. 30. Cooperatives. 29. Energy. 31. Environment and natural resources. 30. Water undertakings and sanitary services. 32. Informal sector. 31. Transport and communications. 33. Health. 32. Local Government. 34. Nutrition. 33. Community, business, recreation and personal services. 35. Information and communication. 34. Handicrafts and rural industries. 36. Education and literacy. 35. Sweepstakes, lotteries, charitable and other public 37. Governance. collections of money. 38. Peace and security. 36. Hire-purchase. 39. Affirmative action. 37. Co-operatives. 40. Innovation, science and technology. 38. Environment. 41. Research and development. 39. Informal sector. 42. Human development indices. 40. Health and Nutrition. 43. Poverty. 41. Information Technology. 44. Gender. 42. Education and literacy. 45. Food security. 46. Vital and other social statistics. 85 Government of Kenya, “The Statistics Act, 2006,� 93. 86 Government of Kenya, The Statistics (Amendment) Bill, 2019, 487. 42 Appendices 47. Any other matter related to the above. 43 Appendices Appendix F: County Statistical Abstracts elaboration steps KNBS-funded CSA County Government & KNBS co-funded CSA 1 KNBS HQ generates a CSA template, which is discussed Agreements between KNBS and County Government with relevant stakeholders. • Meetings are held between KNBS HQ and County Government leadership (governor and county • Committees are formed (comprised by KNBS HQ, KNBS commissioner). If the county government initiates the discussion, the county government leadership writes county, county government, treasury and national to the KNBS Director General, who directs them to the Population and Social Statistics Directorate to revise government representatives) to agree on the template the county proposal and discuss possible contents of the CSA. If the KNBS initiates the collaboration, a contents that will be included in the CSA. forum is organized to present the CSA proposal to the county assembly and explain how funding needs can be covered. Once the CSA general contents are agreed and funding is secured, a memorandum of understanding between the county and the KNBS HQ is elaborated and approved. • CSA template questionnaires are generated by KNBS in collaboration with county government. 2 KNBS HQ and KNBS county offices implement the CSA Joint data collection and supervision data collection. • The county director of economic planning engages other county departments to ensure access data, e.g., • Enumerators and data entry clerks are assigned for on agriculture, education, health, water, etc. In most cases, the key contact person is the county secretary, data collection work. who shares the templates with the respective departmental data providers. • Agreed-upon data on county indicators is collected. • Enumerators are recruited by the county government based on a set of requirements established by the • KNBS county office (and sometime KNBS HQ) monitor KNBS (i.e., academic background and job experience). data quality and supervise data collection. • A training manual is jointly prepared by the KNBS HQ and the county government and a workshop for • Data collected is compiled and sent to KNBS HQ. enumerators training is conducted by the county government and the KNBS county office. • Data collection is initiated and supervised by the KNBS county office and the county government. o Follow-ups on completed template data forms are initiated by the KNBS county staff to report on the data collection progress. Collected data templates are verified with county department heads to confirm that the needs of both parties have been met. 3 KNBS HQ conducts data cleaning, analysis, production Data cleaning, analysis and publication and publication. • Data cleaning and analysis is jointly conducted by county government staff and KNBS HQ. • KNBS HQ cleans and analyses the data o KNBS HQ is responsible for data validation and if necessary, requests clarifications on observed data i. If necessary, KNBS requests data clarifications trends. • KNBS HQ drafts a report which is submitted to the • A draft report is jointly prepared and approved by KNBS HQ and county government. general direction for approval. • The publication of the approved report is carried out by the official government publisher. • The approved report is published by KNBS. 44 Appendices KNBS-funded CSA County Government & KNBS co-funded CSA 4 The CSA is launched in an event led by the KNBS with the The CSA is launched by KNBS HQ in collaboration with the county government participation of the county government and relevant • The CSA is launched by the KNBS HQ at county level by the governor. Various stakeholders are invited, MDAs. including other county governors. • CSA hard copies are sent to KNBS HQ, and the respective county is invited to KNBS HQ to share experiences and lessons learnt with the directorates. 45 Appendices Appendix G: Additional CSA sections Laikipia 2018-2019 Sections / indicators 2018 2019 Gross County Product Gross County Product by Economic Activity, at current prices X Gross County Product by Economic Activity at constant 2009 Prices X Share of GDP by Economic Activity X Laikipia County Per Capita GCP X Population and vital statistics Population projections by age cohorts and sex X X Registered Births by Sex in specific sub-counties X X Main Causes of Deaths by Sex (precedent CSAs only included the top 10 causes of death) X Birth and Death by place of occurrence registered in specific sub-counties X Labor Public sector wage employment by Sector X X Employment by Economic activity, Size of Enterprise and Sub-County X X Monthly Registration of Job Seekers X X Placement of Job Seekers X X Public Finance County Revenue by Source X Revenue Collection by Revenue Sources X X Tourism Hotels by classification, bed and conference capacity X X Hotels Bed Capacity by Sub County X X Visitor Arrival by Country of origin X X Visitors by Tourists Attractions X X Agriculture Map of Agro-Ecological Zones for the County X Average Wholesale Prices for Farm Inputs X X Wholesale Market Prices for Selected Food CommoditieS X X Retail Price of Some Selected Food Commodities X Livestock Estimated livestock population by type X X Number, quantity and value of animals slaughtered by type of animal and year X X Quantity and value of other livestock products X X Number of milk processors by sub-county X X 46 Appendices Annual milk production by sub-county X X Price of livestock on sale X X Prices of meat products X X Prices of Supplementary Livestock Feeds and Minerals by Sub County X X Prices of Supplementary Livestock Feeds and Minerals by Sub County X X Prices of Supplementary Livestock Feeds and Minerals by Sub County X X Livestock Vaccination against Diseases X X Quantity and Value of Egg Production by Sub-County X X Fisheries Quantity, Value and Type of Fish Landed in Freshwater bodies X X Number, Quantity and Value of Fish Ponds by Sub County X X Co-operatives Active co-operatives by type, membership, share capital and turnover X X Active co-operatives by sub-county X X Savings and Credit Co-operative Societies (SACCOs) by sub-county X X Annual Savings & Credit Co-operative Statistics X X County Co-operative Development Revolving Fund Disbursement X Laikipia County Enterprise Development Revolving Fund Disbursement X Water and Sanitation Households with Access to Water and Sanitation X X Water sources X X Household Water sources X Manufacturing Firms by Type of Industry X Energy Main Sources of Lighting X Main Sources of Cooking fuel X Transport and communications Map of Laikipia County Transport Network X Roads network by type and railway line X X Kilometers of roads covered by type and agency X X Public Service Vehicle Operating in Laikipia X Traffic handled at county airstrip X X Postal articles and services handled by sub-county X X Media and Courier Operators X X 47 Appendices County Access to ICT services X Public Transport Vehicles Operating in Laikipia and Passengers Recorded X Building Statistics Building Plans Approved for Private Ownership in Nanyuki Office X Building Plans Approved for Private Ownership in Rumuruti Office X Building Plans Approved for Private Ownership in Laikipia County X Reported Completion of New Non - Residential Buildings for Private Ownership by Sector X Education Pre-primary Schools Enrolments by School Type X X Pre-primary School Enrolments and Access Indicators X X Pre-primary Teachers and Pupil-Teacher Ratio X X Primary Schools Enrolment by Type (public/private) and Sex X X Primary School Enrolment by Class and Sex X X Secondary school by type of accommodation X X Secondary School Enrolment by Type and Sex X X Secondary School Enrolment by Class, Sex and Sub County X X Secondary School Enrolment by Class, Sex and Sub County X X Secondary School Enrolments and Access Indicators X Public Secondary School Teachers by Qualification and Sex X X Student Enrolment in Public Technical Institutions by Sex X X Students Enrolment in Kenya TVET X Laikipia Students Enrolment in Kenya Universities by Faculty X X Adult Education Centres by Sub County X X Learners Enrolment in Adult and Continuing Education- Basic Education X Learner's Enrolment in Adult and Continuing Education- Secondary School Education X Public health Health facilities by level, ownership and constituency X National Hospital Insurance Fund (NHIF) registered members per sector in the county X X Status of Contraceptive Use X Full Immunization Coverage Rate of Under One Year Old Children by Sub-County X X Governance Environmental crimes reported to National Environmental Management X X Cases registered, and convictions obtained for selected serious crimes X X Judicial officers by cadre and sex X X Probation personnel and offenders by sex X X Police officers by sub-county and sex X X 48 Appendices Social services New Registration of Women and Youth Groups X Female participation in public life X X Registered persons with disabilities by type of disability and sex X X Beneficiaries of the orphans and vulnerable fund by sub-county X X Beneficiaries of the elderly persons fund by sub-county X X Youth enterprise fund by constituency X X 49 Appendices Appendix H: Laikipia and Wajir County Statistical Abstracts contents No Laikipia CSA 2019 Laikipia CSA 2018 Laikipia CSA 2015 Wajir CSA 2015 Overview of funding institutions: Overview of funding institutions: County Overview of KNBS (funding institution) Overview of KNBS (funding County Government of Laikipia and Government of Laikipia and KNBS, and and: institution) and: KNBS, and both institutions: both institutions: i • Vision statement • Vision statement • Vision statement • Vision statement • Mission statement • Mission statement • Mission statement • Mission statement • Core values • Core values • Core values • Core values • Foreword • Foreword • Foreword • Foreword ii Acknowledgements Acknowledgements Acknowledgements Acknowledgements iii Table of contents Table of contents Table of contents Table of contents iv List of abbreviations / acronyms List of abbreviations / acronyms List of abbreviations / acronyms List of abbreviations / acronyms v Symbols and conventions Symbols and conventions used Symbols and conventions used Symbols and conventions used Introduction: Structure of county Introduction: Structure of county Introduction: Structure of county Introduction: Structure of county 1 governments, the county assembly, the governments, the county assembly, the governments, the county assembly, the governments, the county assembly, county executive county executive county executive the county executive Overview of the county Overview of the county Overview of the county Overview of the county 2 • Fig. 1: map – location of Laikipia in Fig 1: map – location of Laikipia in Kenya Fig 1: map – location of Laikipia in Kenya Fig 1: map – location of Wajir in Kenya Kenya Administrative and political units Administrative and political units Administrative and political units Administrative and political units • Fig. 2: Map of Laikipia County Not included Not included Not included • Table 1: Administrative units by 3 • Table 1: Administrative units by sub- • Table 1: Administrative units by sub- • Table 1: Administrative units by sub-county and surface area (2016- county (2014-2017) county (2014) sub-county (2014) 2018) • Table 2: Political units (2016- • Table 2: Political units • Table 2: Political units • Table 2: Political units 2018) Land and climate Land and climate Land and climate Land and climate • Table 1: Surface area by category • Table 1: Surface area by category • Table 1: Surface area by category • Table 1: Surface area by category 4 (2014) (2014) • Table 2: Topography • Table 2: Topography • Table 2: Topography • Table 2: Topography • Table 3: Climate • Table 3: Climate • Table 3: Climate Not included 50 Appendices • Table 4: Mean annual rainfall in • Table 4: Mean annual rainfall in Not included Not included millimeters, by station (2014-2018) millimeters, by station (2013-2017) Gross County Product Gross County Product Gross County Product Gross County Product • Table 1: Gross County Product by Economic Activity, 2013 – 2017 at current prices • Table 2: Gross County Product by 5 Economic Activity, 2013 – 2017 at Not included Not included Not included constant 2009 Prices • Table 3: Share of GDP by Economic Activity (2013-2017) • Table 4: Laikipia County Per Capita GCP (2013-2017) Population and vital statistics Population and vital statistics Population and vital statistics Population and vital statistics • Table 1: Population Projections by Not included Not included Not included Constituency and Sex, (2016-2018) • Table 1: National population • Table 1: National population in • Table 1: National population in Not included trend by sex, households and density different census years (1969-2009) different census years (1969-2009) in census years 1969-2009 • Table 2: Constituency population by • Table 2: Constituency population by Not included sex, density and number of households sex, density and number of households Not included (2009) (2009) • Table 2: County population • Table 3: County population projection • Table 3: Population projections by age • Table 2: Population projections 6 projection by sex (2011-2018) by sex (2011-2017) cohorts and sex (2010-2014) by age and sex (2010-2014) • Table 3: Population projections by • Table 4: Population projections by Not included Not included age cohorts and sex (2014-2018) age cohorts and sex (2013-2017) • Table 4: Population Projection of • Table 4: Projection of special age • Table 5: Projection of special age • Table 3: Population projection Special Age Groups by Age Cohorts and groups by age cohorts and sex (2010- groups by age cohorts and sex (2013-2017) for selected age groups (2013-2014) Sex (2014-2018) 2014) • Table 4: Expected and • Table 5: Expected and registered Not included Not included registered births and deaths (2013- births and deaths (2013-2014) 2014) • Table 5: Registered Births by Sex • Table 6: Registered births by sex and • Table 6: Registered births and deaths • Table 5: Registered births and and Registration Centre (2014-2018) registration centre (2012-2017) by sex (2013-2014) deaths by sex (2013-2014) 51 Appendices • Table 6: Registered Births by Sex • Table 7: Registered births by sex N/A in Nanyuki (2016-2018) Laikipia East (2016-2017) • Table 7: Registered Births by Sex Not included N/A in Rumuruti (2017-2018) • Table 8: Main Causes of Deaths by • Table 8: Top ten causes of deaths by • Table 7: Top 10 causes of deaths Sex in Laikipia County (2016) sex (2016) (2014) • Table 9: Main Causes of Deaths by • Table 9: Causes of deaths by sex Sex in Laikipia County (2017) (2017) Not included • Table 10: Main Causes of Deaths N/A by Sex in Laikipia County (2018) • Table 11: Births and Deaths by Not included place of occurrence registered in Nanyuki (2016-2018) Not included • Table 12: Birth and Death by place of occurrence registered in Rumuruti (2016-2018) • Table 13: Birth and Death by place • Table 6: Registered births and Table 10: Birth and death occurrences by • Table 7: Percentage of registered of occurrence in Laikipia County (2016- deaths by place of occurrence (2013- place (hospital/home) (2013-2017) births and deaths by place of occurrence 2018) 2014) Labor Labor Labor Labor • Table 1: Public sector wage • Table 1: Public sector wage Table 1: Public sector wage employment employment by Sector (2016-2018) employment by sub-sector (2015-2017) by sub-sector (2013-2014) • Table 2: Employment by • Table 2: Establishments employing 5 Economic activity, Size of Enterprise or more people by economic activities 7 and Sub-County (2018) (2015-2017) Not included • Table 3: Monthly Registration of Table 3: Monthly registration of job Not included Job Seekers (2016-2018) seekers (2014-2017) • Table 4: Placement of Job Seekers Not included (2016-2018) Money and banking Money and banking Money and banking Money and banking 8 • Table 1: Financial institutions • Table 1: Financial institutions (2015- • Table 1: Financial institutions • Table 1: Financial institutions (2014) (2016-2018) 2017) (2014) 9 Public Finance Public finance Public finance Public finance 52 Appendices • Table 1: County Revenue by Not included Not included Not included Source (2016/17 -2018/19) • Table 1: National Government • Table 1: National Government • Table 1: National Government Added in Table 2 allocation, county local revenue and grants allocation of funds allocation of funds (2014/15 and 2016/17) • Table 2: NGCDF (National Government Constituencies • Table 2: Constituency Development • Table 2: Constituency Development Fund) and NGAAF • Table 2: Constituency Development Fund (CDF) allocation by constituency Development Fund (CDF) allocation (National Government Affirmative Fund (CDF) allocation by constituency (2014/15 and 2017/18) by constituency Action Fund) Allocation by Constituency (2016/17-2018/19) • Table 3: Development and Table 3: County government • Table 3: Development and recurrent Table 3: County government recurrent Recurrent Expenditure (2016/17- recurrent and development expenditure (2015/16 and 2016/17) and development expenditure (2014/15) 2017/18) expenditure (2014/15) • Table 4: Revenue Collection by Table 4: Revenue collection by revenue Not included Not included Revenue Sources (2015/16-2017/18) sources (2014/15 and 2016/17) Trade and Commerce Trade and Commerce Trade and commerce Trade and commerce • Table 1: Licensed Business • Table 1: Revenue collection • Table 1: Licensed business • Table 1: Revenue collection from Establishments by Economic activity, from single business permits (2013- 10 establishments by sub-county (2015-2017) single business permits (2013-2014) Size and Sub County, 2018 2014) • Table 2: Trading centres and • Table 2: Trading centres and Not included Not included licensed business establishments by licensed business establishments by broad category (2013-2014) broad category (2013-2014) Tourism Tourism Tourism Tourism • Table 1: Hotels by classification, • Table 1: Hotels by classification, bed bed and conference capacity (2014- and conference capacity (2014-2017) 2018) • Table 2: Hotels Bed Capacity by • Table 2: Hotels bed and room capacity Not included 11 Sub County (2015-2018) by zone and sub-county (2015-2017) Not included • Table 3: Visitor Arrival by • Table 3: Bed occupancy by residency Country of origin (2014-2018) (2014-2017) • Table 4: Visitors by Tourists • Table 4: Visitors by tourist attractions • Table 1: Visitors by tourist Attractions (2016 – 2018) (2015-2017) attraction types (2013-2014) 53 Appendices Agriculture Agriculture Agriculture Agriculture • Table 1: Area cropped, • Table 1: Agro-Ecological Zones for • Table 1: Agro-Ecological Zones for the • Table 1: Agro-Ecological Zones and production and value for major crops the County (2016-2018) County (2016-2017) Sub-Zone Patterns (2013-2014) • Fig. 3: Map of Agro-Ecological Not included Not included Zones • Table 2: Land Potential by Area • Table 2: Land Potential by Area and • Table 2: Land Potential by Area and and Sub-County (2017- 2018) Sub-County (2014- 2017) Sub-County (2014) Not included • Table 3: Area Cropped, • Table 3: Area Cropped, Production • Table 3: Area Cropped, Production Production and Value for Major Crops and Value for Major Crops (2015-2017) and Value for Major Crops (2013-2014) (2016-2018) • Table 3: Acreage under • Table 4: Acreage under Irrigation • Table 5: Acreage under Irrigation by Not included irrigation by type of crop grown by Type of Crop grown (2016-2018) Type of Crop grown (2013-2014) (2013-2014) • Table 5: Horticultural Production • Table 4: Horticultural Production and • Table 4: Horticultural Not included and Value by Crop (2015-2018) Value by Crop (2014-2017) production (2013-2014) • Table 6: Average Retail Prices for • Table 6: Average retail prices for farm • Table 4: Average Retail Prices for • Table 2: Average retail prices for 12 Farm Inputs (2017 and 2018) inputs (2016 and 2017) Farm Inputs (2013-2014) farm inputs (2013- 2014) • Table 7: Average Wholesale Prices • Table 5: Average Wholesale Price for Farm Inputs (2017 and 2018) Range for Farm Inputs (2016 and 2017) Not included • Table 7: Agriculture development extension groups (2012-2017) Not included • Table 5: Cereals production (2013-2014) • Table 1: Annual average retail Not included prices (in section: Retail prices) • Table 7: Average commodities prices in the Major Market Centers within the Not included County (2014) Not included • Table 6: Average prices for dry maize and beans • Table 2: Retail market prices for • Table 8: Retail Market Prices for selected commodities, January- Selected Food Commodities, January - Not included December 2014 (in section: Retail December 2016 prices) 54 Appendices • Table 9: Wholesale Market Prices • Table 9: Wholesale Market Prices for for Selected Food Commodities, Selected Food Commodities (2016) January - December, 2016 • Table 10: Retail Price of Some Selected Food Commodities, January - Not included December (2017) • Table 11: Wholesale Price of • Table 8: Wholesale Price of Some Some Selected Food Commodities, Selected Food Commodities, January- Not included January - December, 2017 December (2015) • Table 12: Retail Price of Some Selected Food Commodities, January - Not included December, 2018 • Table 13: Wholesale Price of • Table 10: Wholesale Price of Some Some Selected Food Commodities, Selected Food Commodities, January- January - December, 2018 December (2017) Livestock Livestock Livestock Livestock • Table 1: Estimated livestock • Table 1: Estimated livestock Not included population by type (2016-2018) population by type (2014-2017) • Table 2: Number, quantity and • Table 2: Number, quantity and value • Table 1: Animals slaughtered by type value of animals slaughtered by type of of animals slaughtered by type of animal Not included (2013-2014) animal and year (2012-2018) and year (2012-2017) • Table 3: Quantity and value of • Table 3: Quantity and value of other Not included other livestock products (2015-2018) livestock products (2014-2017) • Table 1: Quantity and value of 13 • Table 4: Quantity and value of • Table 4: Quantity and value of hides • Table 3: Hides and skins production hides and skins produced (2013- hides and skins produced (2015-2018) and skins produced (2014-2017) (2013-2014) 2014) • Table 2: Milk production by type of Not included Not included animal (2013-2014) • Table 5: Number of milk • Table 5: Number of milk processors processors by sub-county (2015-2018) by sub-county (2015-2017) Not included • Table 6: Annual milk production • Table 6: Annual milk production by Not included by sub-county (2015-2018) sub-county (2014-2017) • Table 7: Price of livestock on sale • Table 7: Average prices of livestock on (2015-2018) sale by type (2015-2017) 55 Appendices • Table 8: Prices of meat products • Table 8: Price of meat products (2015- (2015-2018) 2017) • Table 9: Prices of Supplementary • Table 9: Prices of supplementary Livestock Feeds and Minerals by Sub livestock feeds and minerals by sub-county County (2016) (2015) • Table 10: Prices of Supplementary • Table 10: Prices of supplementary Livestock Feeds and Minerals by Sub livestock feeds and minerals by sub-county County (2016) (2016) • Table 11: Prices of Supplementary • Table 11: Prices of supplementary Livestock Feeds and Minerals by Sub livestock feeds and minerals by sub-county County (2018) (2017) • Table 12: Livestock Vaccination • Table 12: Livestock vaccination against Diseases (2016-2018) against diseases (2014-2017) • Table 13: Quantity and Value of • Table 13: Quantity and value of egg Egg Production by Sub-County (2016- production by sub-county (2015-2017) 2018) Fisheries Fisheries Fisheries Fisheries • Table 1: Quantity, Value and Type Table 1: Number, quantity and value of fish • Table 1: Fish ponds by sub-county of Fish Landed in Freshwater bodies ponds by sub-county (2014-2017) (2014-2017) (2015-2018) Not included • Table 2: Number, Quantity and Value of Fish Ponds by Sub County Not included Table 2: Fish landed (2013-2014) (2015-2018) Co-operatives Co-operatives Co-operatives Co-operatives 14 Table 1: Savings and Credit Co-operative • Table 1: Active co-operatives by • Table 1: Active co-operatives by type, • Table 1: Co-operatives by type, Societies (SACCOs) by type, status, type, membership, share capital and membership, share capital and turnover status, membership and turnover membership and turnover (as at turnover (2016-2018) (2015-2017) (2013-2014) December 2013, 2014) • Table 2: Active co-operatives by • Table 2: Active co-operatives by sub- sub-county (2014-2018) county (2013-2017) • Table 3: Savings and Credit Co- • Table 3: Savings and Credit Co- Not included Not included operative Societies (SACCOs) by sub- operative Societies (SACCOs) by sub- county (2014-2018) county (2013-2017) 56 Appendices • Table 4: Annual Savings & Credit Table 4: Annual Savings & Credit Co- Co-operative Statistics (2015-2018) operative Statistics (2014-2017) • Table 5: County Co-operative Development Revolving Fund Disbursement (2016- 2018) • Table 6: Laikipia County Not included Enterprise Development Revolving Fund Disbursement (2015/16- 2018/19) Forestry Forestry Forestry Forestry • Table 1: Gazetted forests (2015- • Table 1: Gazetted forests (2013- • Table 1: Gazetted forests, by Table 1: Gazetted forests (2013-2017) 15 2018) 2014) size (2013-2014) • Table 2: Forest production by type Table 2: Estimates of forest Not included Table 2: Forest production by type (2014) (2015-2018) production by type (2013-2014) Water and Sanitation Water and Sanitation Water and Sanitation Water and Sanitation • Table 1: Households with Access to • Table 1: Households with Access Water and Sanitation (2015-2018) (in to Water and Sanitation (2015-2018) forestry section) Water source and access to 16 • Table 2: Water sources (2017) (in Access to water indicator is included in • Table 2: Water sources (2017) improved sanitation are included in forestry section) the Appendices the Appendices • Table 3: Water sources (2018) • Table 4: Household Water sources Not included (2018) Manufacturing Manufacturing Manufacturing Manufacturing 17 • Table 1: Firms by Type of Industry Not included Not included Not included (2017-2018) Energy Energy Energy Energy • Table 1: Electricity connection by • Table 1: Electricity connection by • Table 1: Electricity connection by consumer entity (2016-2018) consumer entity (2014-2017) consumer type (2014) 18 Not included • Table 2: Electricity connection by Not included Not included consumer institution (2014) 57 Appendices • Table 2: Main Sources of Lighting (2018) Not included • Table 3: Main Sources of Cooking fuel (2018) • Table 1: Average monthly pump • Table 4: Average monthly pump Table 2: Average monthly pump prices for Table 3: Average monthly pump prices for prices for fuel by category (2013- prices for fuel by category (2015-2018) fuel by category (2013-2014) fuel by category (2013-2014) 2014) Transport and communications Transport and communications Transport and communications Transport and communications • Figure 4: Map of Laikipia County Not included Not included Transport Network Not included • Table 1: Roads network by type • Table 1: Roads network by type and • Table 1: Road coverage by type and railway line (2016-2018) railway line (2015-2017) and distance (2014) • Table 2: Urban roads coverage by • Table 2: Urban roads coverage by • Table 1: Urban roads coverage by type and distance (2016-2018) type and distance (2013-2014) type and distance (2013-2014) • Table 3: Kilometers of roads Not included • Table 3: Kilometres of roads covered covered by type and agency (2016- by type and agency (2015-2017) 2018) • Table 3: Telephone services Not included (2014) Not included Not included 19 • Table 4: Public Service Vehicle Operating in Laikipia (2016 -2018) Not included • Table 5: Traffic handled at • Table 4: Traffic handled at Nanyuki Nanyuki Airstrip (2016-2018) airstrip (2015-2017) • Table 6: Postal services by sub- • Table 5: Postal services by sub-county • Table 2: Postal services (2014- • Table 2: Postal services (2014-2015) county (2016-2018) (2015-2017) 2015) • Table 7: Postal articles and Table 6: Postal articles and services services handled by sub-county (2016- handled by sub-county (2015-2017) 2018) • Table 8: Media and Courier Not included Not included • Table 7: Media and Courier Operators Operators (2016-2018) • Table 9: County Access to ICT Not included services (2018) 58 Appendices • Table 10: Public Transport Vehicles Operating in Laikipia and Passengers Recorded (2018) Building Statistics Building Statistics Building Statistics Building Statistics • Table 1: Building Plans Approved for Private Ownership in Nanyuki Office (2016-2018) • Table 2: Building Plans Approved for Private Ownership in Rumuruti Office (2016-2018) 20 • Table 3: Building Plans Approved Not included Not included Not included for Private Ownership in Laikipia County (2016-2018) • Table 4: Reported Completion of New Non - Residential Buildings for Private Ownership by Sector (2016- 2018) Education Education Education Education • Table 1: Education Institutions • Table 1: Type of educational • Table 1: Type of educational • Table 1: ECD Centres by Category by Level, Ownership and Sub-County, institutions (2016-2018) institutions (2015-2017) and Sub-County (2013-2014) 2014* • Table 2: Table 20.2: Pupil • Table 2: Pupil enrolment in ECDE • Table 2: Pupil enrolment in ECDE • Table 2: ECDE (Early Childhood Enrolment in Early Childhood (Early Childhood Development Education) (Early Childhood Development Education) Development Education) Enrolment Development (ECD) Centers by Sex centers bycategory, sex, and sub-county centers bycategory, sex (2014-2017) by Ownership and Sex (2014) (2015-2018) (2014) • Table 3: Teachers in ECD centres by • Table 3: ECDE Enrolment and 21 Not included Not included sub-county and sex (2013-2014) Access Indicators (2014) • Table 3: Pre-primary Schools • Table 3: Pre-primary Schools Enrolments by School Type (2016- Enrolments by School Type (2015-2017) 2018) Not included • Table 4: Pre-primary School • Table 4: Pre-primary Schools Not included Enrolments and Access Indicators Enrolments and Access Indicators (2015- (2016-2018) 2017) • Table 5: Pre-primary Teachers • Table 5: Pre-primaryTeachers and • Table 4: ECDE Teachers by sex and Pupil-Teacher Ratio (2016-2018) Pupil-Teacher Ratio (2015-2017) and Sub county (2014) 59 Appendices • Table 6: Primary Schools • Table 5: Primary Schools • Table 6 :Primary Schools Enrolment Enrolment by Type (public/private) and Enrolment by Ownership and Sex by Type and Sex (2015-2017) Sex (2016-2018) (2014) • Table 7: Primary School • Table 7 :Primary Schools Enrolment • Table 5: Primary School Enrolment by Enrolment by Class, Sex & Sub- by Class and Sex (2015-2017) Class, Sex & Sub-County (2014) County (2014) • Table 7: Primary School • Table 8a:Primary School Boys Enrolment by Class and Sex (2016- Enrolment by Class and Sub County (2014- 2018) 2016) Not included • Table 8b: Primary School Girls Not included Enrolment by Class and Sub County (2014- 2016) • Table 4: Primary Schools by Category Not included Not included and Sub-County (2013-2014) • Table 8: Primary Enrolments and • Table 9: Primary Enrolments and • Table 6: Primary Enrolment and Not included Access Indicators (2016-2018) Access Indicators (2015-2017) Access Indicators (2014) • Table 9: Trained Public Primary • Table 10: Public Primary School • Table 8: Public Primary School School Teachers by Qualification and Teachers by Qualification and Sex (2015- Teachers by Qualification and Sex (2013- Sex (2016-2018) 2017) 2014) Not included • Table 9: Private Primary School Not included Not included Teachers by Qualification and Sex (2013- 2014) • Table 10: Secondary school by • Table 11: Secondary Schools by Type Not included Not included type of accommodation (2016-2018) of Accommodation (2015-2017) • Table 11: Secondary School • Table 12: Secondary Schools • Table 11: Secondary School Enrolment • Table 9: Secondary Schools Enrolment by Type and Sex (2016- Enrolment by Type and Sex (2015-2017) by Category, Class and Sex (2014) Enrolment by Type and Sex (2014) 2018) • Table 13a: Secondary School Boys Enrolment by Class and Sub County (2014- • Table 12: Secondary School • Table 12: Secondary School • Table 8: Secondary School 2016) Enrolment by Class, Sex and Sub Enrolment by Class, Sex and Sub-County Enrolment by Class, Sex & Sub- County (2017) • Table 13b: Secondary School Girls (2014) County (2014) Enrolment by Class and Sub County (2014- 2016) 60 Appendices • Table 13: Secondary School • Table 14: Secondary Schools • Table 10: Secondary Schools by Enrolment by Class, Sex and Sub Enrolment by Class, Sex and Sub-county Not included category and Sub-County (2013-2014) County (2018) (2017) • Table 14: Secondary School • Table 10: Secondary Schools Enrolments and Access Indicators Not included Not included Enrolment and Access Indicators (2016-2018) (2014) • Table 15: Public Secondary School • Table 15: Public Secondary School • Table 14: Public Secondary School • Table 11: Teachers by Schooling Teachers by Qualification and Sex Teachers by Qualification and Sex (2015- Teachers by Qualification and Sex (2013- Level, Type and Sub County (2014) (2016-2018) 2017) 2014) • Table 15: Private Secondary School Teachers by Qualification and Sex (2013- 2014) • Table 7: candidates in national examinations (Kenya Certificate of Not included Primary Education (KCPE), and Kenya Certificate of Secondary Education (KCSE), Not included Not included by sex and sub-county (2013-2014) • Table 13: KCSE Candidates by Sex and Sub-County (2013-2014) • Table 12: Proficiency Test Results Not included (2013-2014) • Table 16: Youth Polytechnics by Category and Sub-County (2013-2014) • Table 16: Student Enrolment in • Table 16: Student Enrolment in • Table 17: Student Enrolment in Public Technical Institutions by Sex Technical Institutions by Sex, 2013-2014 Youth Polytechnics by Sub-County and (2015-2018) (2015-2017) Sex, 2013-2014 (2013-2014) • Table 17: Laikipia Students Not included Enrolment in Kenya TVET (2016) • Table 18: Laikipia Students Not included Not included Enrolment in Kenya TVET (2017) • Table 19: Laikipia Students Enrolment in Kenya TVET (2018) 61 Appendices • Table 18: Teacher Training Colleges by Category (2014) Not included • Table 19: Universities and University Campuses by Category (2013-2014) • Table 20: Laikipia Students • Table 17: Laikipia University Student Enrolment in Kenya Universities by Not included Distribution by faculty (2015-2017) Faculty (2015-2018) • Table 21: Adult Education Centres • Table 18: Adult Education Centres by • Table 20: Adult Education Centres by by Sub County, (2015-2018) Sub County, (2014-2017) Sub County, (2013-2014) • Table 22: Learners Enrolment in Adult and Continuing Education- Basic Education (2016-2018) • Table 23: Learner's Enrolment in Not included Adult and Continuing Education- Secondary School Education (2016- Not included 2018) • Table 21: Adult Education Enrolment by Sex and Sub County (2013-2014) Not included • Table 22: CDF Bursary Beneficiaries in Secondary and Colleges by Constituency (2013-2014) Public health Public health Public health Public health • Table 1: Health facilities by type, • Table 1: Health facilities by type, • Table 1: Health facilities by • Table 1: Health facilities by ownership and constituency (2016- ownership and constituency (2014-2017) ownership and sub-county (2014) ownership and sub-county (2014) 2018) • Table 2: Health facilities by level, 22 ownership and constituency (2016- Not included Not included Not included 2018) • Table 3: Health facilities beds and • Table 2: Hospital beds and cots by • Table 2: Hospital beds and cots by • Table 2: Hospital beds and cots cots by Sub-County and type of facility constituency and type of facility (2014- constituency and type of facility (2013- by constituency and type of facility (2016-2018) 2017) 2014) (2013-2014) 62 Appendices • Table 4: Outpatient morbidity for • Table 3: Outpatient morbidity for • Table 3: Outpatient morbidity for • Table 3: Outpatient morbidity patients under 5 years of age by sub- patients under 5 years of age by sub- patients under 5 years of age by sub- for patients under 5 years of age by county (2016-2018) county (2015-2017) county (2014) sub-county (2014) • Table 5: Outpatient morbidity for • Table 4: Outpatient morbidity for • Table 4: Outpatient morbidity for • Table 4: Outpatient morbidity patients at and above 5 years of age by patients at and above 5 years of age by sub- patients at and above 5 years of age by for patients at and above 5 years of sub-county (2016-2018) county (2015-2017) sub-county (2014) age by sub-county (2014) • Table 6: Registered medical • Table 5: Registered medical Table 5: Registered medical personnel per Table 5: Registered medical personnel per cadre (2016-2018) personnel per cadre (2013-2014) cadre (2013-2014) personnel per cadre (2013-2014) • Table 7: NHIF registered members Table 6: NHIF registered members per per sector in the county (2017-2018) sector in the county (as by 30th June 2018) • Table 8: Status of Contraceptive Use (2018) Not included Not included • Table 9: Full Immunization Not included Coverage Rate of Under One Year Old Children by Sub-County (2018) Governance Governance Governance Governance • Table 1: New Persons Registered • Table 1: New Persons Registered • Table 1: New Persons Registered (NPR) applications, NPR Identification (NPR) applications, NPR Identification (NPR) and duplicate Identification Documents (IDs) processed and Documents (IDs) processed and collected, Documents (IDs) registered, by sub- collected, by sub-county (2016-2018) by sub-county (2015-2017) county (2013-2014) Not included • Table 2: Registered voters by • Table 2: Registered voters by • Table 2: Collected ID cards by sub- constituency (2016-2018) constituency (2016-2017) county (2014) • Table 3: Traffic accidents (2016- • Table 3: Traffic accidents (2013- • Table 3: Traffic accidents (2014-2017) 2018) 2014) 23 • Table 4: Reported crimes by • Table 4: Reported crimes by offence • Table 4: Reported crimes by offence • Table 1: Reported crimes by offence and sub-county (2017-2018) and sub-county (2014-2017) and sub-county (2013-2014) offence and sub-county (2014) • Table 5: Persons reported to • Table 5: Persons reported to police to • Table 5: Persons reported to police police to have committed offences have committed offences against morality to have committed offences against against morality and other offences and other offences against persons, by sex morality and other offences against against persons, by sex (2016-2018) (2014-2017) persons, by sex (2013-2014) Not included • Table 6: Environmental crimes • Table 6: Environmental crimes Not included reported to National Environmental reported to National Environmental 63 Appendices Management Authority (NEMA) (2016- Management Authority (NEMA), by 2018) constituency (2015-2017) • Table 7: Distribution of magistrates and judges in law courts by cadre and sex Not included Not included (2014) • Table 10: Probation personnel and offenders by sex (2013-2014) • Table 7: Cases registered, and • Table 7: Cases registered, and convictions obtained for selected convictions obtained for selected serious Not included serious crimes (2016-2018) crimes (2015-2017) • Table 8: Cases handled by courts • Table 8: Cases handled by • Table 6: Cases handled by (2016-2018) magistrates’ courts (2016-2017) magistrates’ courts by sex (2014) • Table 9: Judicial officers by cadre • Table 9: Judicial officers by cadre and • Table 2: Judicial officers by Not included and sex (2017-2018) sex (2016-2017) cadre and sex (2014) • Table 10: Convicted prisoners by • Table 10: Convicted prisoners by type • Table 8: Convicted prisoners by type Not included type of offences and sex (2016-2018) of offences and sex (2014-2017) of offences and sex (2014) • Table 11: Probation personnel • Table 11: Probation personnel and • Table 3: Probation personnel Not included and offenders by sex (2015-2017) offenders by sex (2015-2017) and offenders by sex (2013-2014) • Table 11: Offenders serving Table 4: Offenders serving • Table 12: Offenders Serving • Table 12: Offenders serving community service and probation by sex community service and probation by Probation, Community Service and community service, probation and and type of offence (2013-2014) sex and type of offence (2013-2014) Aftercare by Sex and Type of Offence aftercare by sex and type of offence • Table 12: Offenders Serving Table 5: Offenders Serving in (2016-2018) (2015-2017) Probation by Sex and Type of Offence Community Service by Sex and Type (2013-2014) of Offence (2013-2014) • Table 13: Police officers by sub- Table 13: Police officers by sub-county and Not included Not included county and sex (2015-2018) sex (2014-2017) Social services Social services Social services Social services 24 • Table 1: Self-help groups by Not included Not included Not included membership, contributions and grants received (2013-2014) 64 Appendices • Table 1: Registered women groups • Table 1: Registered women groups Not included • Table 1: New Registration of (2013-2017) (2013/14-2014/15) Women and Youth Groups (2015/16 - • Table 2: Registered youth • Table 2: Registered youth groups 2017/18) Not included groups by membership and (2013/14) contributions (2013/4) • Table 2: Funds disbursement by • Table 2: Funds disbursement by • Table 3: Funds disbursement by • Table 3: Funds disbursement by category 2015/16 and 2017/18) category 2013/4 and 2016/7) category (2013/14) category (2013/4) • Table 3: Female participation in • Table 3: Female participation in public public life (2016-2018) life (2015-2017) • Table 4: New registrations of • Table 4: Registered persons with persons living with disabilities by type disabilities by type of disability and sex and sex (2016-2018) (2015-2017) • Table 5: Beneficiaries of the • Table 5: Beneficiaries of the orphans orphans and vulnerable children fund and vulnerable children fund by sub- Not included Not included by sub-county (2015/16 and 2017/18) county (2014/5 and 2016/7) • Table 6: Beneficiaries of the • Table 6: Beneficiaries of the elderly elderly persons fund by sub-county persons fund by sub-county (2013/4, (2015/16 and 2017/18) 2014/5 and 2016/7) • Table 7: Youth enterprise fund by Table 7: Youth enterprise fund by constituency (2015-2018) constituency (2014-2017) Appendices Appendices Appendices Appendices • Key demographic, health and socio- • Key demographic, health and socio- • Key social economic indicators • Key social economic indicators economic indicators economic indicators 25 • Percentage of households’ Not included Not included Not included assets ownership (2009) • Kenya’s 47 counties • Kenya’s 47 counties • Kenya’s 47 counties • Kenya’s 47 counties Source: County Statistical Abstracts for Laikipia (2015, 2018 and 2019) and Wajir (2015) 65 Appendices Appendix I: KNBS services and products Services and products Timeline Charges Basic statistical data • One to two days Free • Also available on KNBS website Technical advice on official • On request/ same day Free statistics Statistical research services • Varies depending on the nature of At a cost research Reference materials • Immediately/same day Free Sale of cartographic maps • One to two weeks At a cost and shape files Sale of published reports • Three days At a cost (cover price) Students’ industrial • Termly Free /terms and conditions attachments apply Source: KNBS customer service charter 66 Appendices Appendix J: List of national statistics offices websites worldwide Africa Country Organization Website Country Organization Website Algeria National Office of Statistics (NOS) ons.dz Eritrea National Statistics Office (NSO) ghdx.healthdata.org Institut national de la statistique et de la ine.gov.ao csa.gov.et Angola démographie (INE) Ethiopia Central Statistical Agency (CSA) Direction générale de la statistique et des insae-bj.org stat-gabon.org Benin Institut National de la Statistique Benin (INSAE) Gabon études économiques (DGSEE) Botswana Central Statistics Office (CSO) gov.bw Gambia Gambia Bureau of Statistics (GBOS) gbos.gov.gm/ Burkina Institut national de la statistique et de la insd.bf Ghana Statistical Service (GSS) statsghana.gov.gh Faso démographie (INSD) Ghana Institut de statistiques et d’études économiques isteebu.bi stat-guinee.org Burundi du Burundi (ISTEEBU) Guinea Direction nationale de la statistique (DNS) statistics- Instituto Nacional de Estatistica e Censos stat- Cameroon National Institute of Statistics (INS) cameroon.org Guinea-Bissau (Guinea-Bissau) guinebissau.com Central Institut centrafricain des statistiques, des études African icasees.org knbs.go.ke économiques et sociales (ICASEES) Republic Kenya Kenya national bureau of statistics (KNBS) Cape Verde Instituto Nacional de Estatística ine.cv Lesotho Bureau of Statistics bos.gov.ls Institut national de la statistique, des études Liberia Institute of Statistics and Geo- inseedtchad.com lisgis.gov.lr Chad économiques et démographiques (INSEED) Liberia Information Services (LISGIS) http://www.inse Institut national de la statistique Direction de la Statistique (INSEED) instat.mg Comoros ed.km/ Madagascar (Madagascar) Côte Institut National de la Statistique de Côte ins.ci nsomalawi.mw d'Ivoire d'Ivoire (INS) Malawi National Statistical Office Democratic Republic of ins-rdc.org Ministry of Planning and National planning.gov.mv Congo Institut national de la statistique (INS) Maldives Development Centre national de la statistique et des études cnsee.org Institut national de la statistique (Mali) instat.gov.ml Congo économiques (CNSEE) Mali Direction des statistiques et des études dised.dj Office national de la statistique ons.mr Djibouti démographiques (DISED) Mauritania Central Agency for Public Mobilization and statsmauritius.govm capmas.gov.eg Egypt Statistics (CAPMAS) Mauritius Statistics Mauritius u.org 67 Appendices Equatorial Direction Générale des Statistiques (DGECN) dgecnstat-ge.org hcp.ma Guinea Morocco Haut Commissariat au Plan Mozambiqu National Institute of Statistics (Instituto Nacional ine.gov.mz statssa.gov.za e de Estatística, INE) South Africa Statistics South Africa Namibia Namibia Statistics Authority (NSA) nsa.org.na South Sudan National Bureau of Statistics (NBS) ssnb.org Niger Institut National de la Statistique du Niger (INS) stat-niger.org Sudan Central Bureau of Statistics of Sudan cbs.gov.sd nigerianstat.gov. swazistats.org.sz Nigeria National Bureau of Statistics of Nigeria ng Swaziland Central Statistics Office of Swaziland Rwanda National Institute of Statistics of Rwanda (NISR) statistics.gov.rw Tanzania Bureau of Statistics (Tanzania) nbs.go.tz Sao Tome Instituto Nacional de Estatistica (São Tomé e Direction générale de la statistique et de la ine.st stat-togo.org and Principe Príncipe) Togo comptabilité nationale Agence nationale de la statistique et de la ansd.sn ins.nat.tn Senegal démographie Tunisia National Institute of Statistics (INS) Seychelles National Statistics Bureau nsb.gov.sc Uganda Uganda Bureau of Statistics ubos.org Sierra statistics.sl zamstats.gov.zm Leone Statistics Sierra Leone Zambia Central Statistical Office of Zambia Somalia Directorate of National Statistics dns Zimbabwe Central Statistical Office of Zimbabwe zimstat.co.zw Americas Country Organization Website Country Organization Website Antigua and Statistics Division statistics.gov.ag statinja.gov.jm Barbuda Jamaica Statistical Institute of Jamaica Instituto Nacional de Estadística y National Institute of Statistics, Geography indec.gov.ar inegi.org.mx Argentina Censos (INDEC) Mexico and Data Processing (INEGI) National Institute of Information www.cbs.aw inide.gob.ni Aruba Central Bureau of Statistics (Aruba) Nicaragua Development Bahamas Department of Statistics (Bahamas) gov.bs/statistics Panama Dirección de Estadística y Censo contraloria.gob.pa Dirección General de Estadísticas, barstats.gov.bb dgeec.gov.py Barbados Barbados Statistical Service Paraguay Encuestas y Censos Instituto Nacional de Estadística e sib.org.bz inei.gob.pe Belize Statistical Institute of Belize Peru Informática Bolivia Instituto Nacional de Estadística ine.gob.bo Saint Lucia Government Statistics Department stats.gov.lc Brazilian Institute of Geography and Saint Kitts and ibge.gov.br Statistics Department wpstats.gov.kn Brazil Statistics (IBGE) Nevis Canada Statistics Canada statcan.gc.ca Sint Maarten Central Bureau of Statistics [2] 68 Appendices Foundation General Bureau of Statistical in statistics- ine.cl Chile Instituto Nacional de Estadísticas Suriname Suriname suriname.org National Administrative Department of Statistics (Departamento Administrativo dane.gov.co Trinidad and cso.gov.tt Colombia Nacional de Estadistica) (DANE) Tobago Central Statistical Office Costa Rica Instituto Nacional de Estadística y Censos inec.go.cr Uruguay Instituto Nacional de Estadística ine.gub.uy Cuba Oficina Nacional de Estadísticas (ONE) www.one.cu United States United States Census Bureau census.gov Curaçao Central Bureau of Statistics Curaçao www.cbs.cw United States Bureau of Labor Statistics (BLS) bls.gov Dominican National Center for Education one.gob.do nces.ed.gov Republic Oficina Nacional de Estadistica United States Statistics (NCES) Ecuador Instituto Nacional de Estadística y Censos inec.gob.ec United States Energy Information Administration (EIA) eia.doe.gov National Agricultural Statistics digestyc.gob.sv nass.usda.gov El Salvador Dirección General de Estadística y Censos United States Service (NASS) Guatemala Instituto Nacional de Estadística ine.gob.gt United States Bureau of Justice Statistics (BJS) ojp.usdoj.gov/bjs statisticsguyana. bea.gov Guyana Guyana Bureau of Statistics gov.gy United States Bureau of Economic Analysis (BEA) Institut haïtien de statistique et d’informatique ihsi.ht cdc.gov/nchs Haiti (IHSI) United States National Center for Health Statistics (NCHS) Honduras Instituto Nacional de Estadística y Censos ine.gob.hn Venezuela Instituto Nacional de Estadística ine.gov.ve Europe Institutions from countries marked with † are members of Eurostat's European Statistical System (ESS). Country Organization Website Country Organization Website Albania Institute of Statistics (INSTAT) instat.gov.al Latvia † Central Statistical Bureau of Latvia (CSP) csb.gov.lv Liechtenstein estadistica.ad as.llv.li Andorra Department of Statistics (DS) † Office of Statistics (AS) National Statistical Service of the Republic of armstat.am stat.gov.lt Armenia Armenia (ARMSTAT) Lithuania † Department of Statistics (LSD) Central Service for Statistics and Economic statistiques.public.l statistik.at Austria † Statistics Austria Luxembourg † Studies (STATEC) u State Statistical Committee of the Azerbaijan azstat.org nso.gov.mt Azerbaijan Republic Malta † National Statistics Office (NSO) National Statistical Committee of the Republic of belstat.gov.by monacostatistics.mc Belarus Belarus (BELSTAT) Monaco Monaco Statistics (IMSEE) 69 Appendices Statistical Office of statbel.fgov.be monstat.org Belgium † Statistics Belgium Montenegro Montenegro (MONSTAT) Bosnia and Agency of Statistics of Bosnia and bhas.ba cbs.nl Herzegovina Herzegovina (BHAS) Netherlands † Statistics Netherlands (CBS) North nsi.bg stat.gov.mk Bulgaria † National Statistical Institute (NSI) Macedonia State Statistical Office (DZS) Croatia † Croatian Bureau of Statistics (DZS) dzs.hr Norway † Statistics Norway (SSB) ssb.no Cyprus † Statistical Service of Cyprus (CYSTAT) cystat.gov.cy Poland † Statistics Poland (GUS) stat.gov.pl Czech czso.cz ine.pt Republic † Czech Statistical Office (ČSU) Portugal † Statistics Portugal (INE) Republic of National Bureau of Statistics of the dst.dk statistica.md Denmark † Statistics Denmark Moldova Republic of Moldova (BNS) Estonia † Statistics Estonia stat.ee Romania † National Institute of Statistics (INS) insse.ro Faroe Russian hagstova.fo gks.ru Islands Statistics Faroe Islands Federation Federal State Statistics Service (Rosstat) Office of Economic Planning, Data stat.fi statistica.sm Finland † Statistics Finland San Marino Processing and Statistics (UPECEDS) National Institute of Statistics and Economic Statistical Office of the Republic of insee.fr webrzs.stat.gov.rs France † Studies (INSEE) Serbia Serbia (RZS) Statistical Office of the Slovak geostat.ge susr.sk Georgia National Statistics Office (GeoStat) Slovakia † Republic (SUSR) Statistical Office of the Republic of destatis.de stat.si Germany † Federal Statistical Office of Germany (Destatis) Slovenia † Slovenia (SURS) Greece † Hellenic Statistical Authority (EL.STAT.) statistics.gr Spain † National Statistics Institute (INE) ine.es Hungary † Hungarian Central Statistical Office (KSH) portal.ksh.hu Sweden † Statistics Sweden (SCB) scb.se Iceland † Statistics Iceland statice.is Switzerland † Federal Statistical Office (FSO) bfs.admin.ch Ireland † Central Statistics Office (CSO) cso.ie Turkey Turkish Statistical Institute (TUIK) turkstat.gov.tr Italy † National Institute of Statistics (ISTAT) istat.it Ukraine State Statistics Service of Ukraine ukrstat.gov.ua United esk.rks-gov.net ons.gov.uk Kosovo Kosovo Agency of Statistics (ASK) Kingdom † Office for National Statistics (ONS) Asia Country Organization Website Country Organization Website 70 Appendices Lao People's cso.gov.af Democratic lsb.gov.la Afghanistan Central Statistics Organization Republic Lao Statistics Bureau Bahrain Central Informatics Organization cio.gov.bh Lebanon Central Administration for Statistics (CAS) cas.gov.lb Bangladesh Bangladesh Bureau of Statistics bbs.gov.bd Malaysia Department of Statistics (Malaysia) dosm.gov.my Bhutan National Statistics Bureau nsb.gov.bt Mongolia National Statistical Office nso.mn Burma Central Statistical Organization (Burma) csostat.gov.mm Myanmar Central Statistical Organization mmsis.gov.mm Cambodia National Institute of Statistics of Cambodia nis.gov.kh Nepal Central Bureau of Statistics cbs.gov.np ncsi.gov.om/Pages/ stats.gov.cn China National Bureau of Statistics of China Oman Ministry of National Economy NCSI.aspx Republic of China stat.gov.tw Palestinian pcbs.gov.ps (Taiwan) Statistics Bureau Authority Palestinian Central Bureau of Statistics East Timor Direcção Nacional de Estatística dne.mof.gov.tl Pakistan Pakistan Bureau of Statistics pbs.gov.pk Hong Kong Census and Statistics Department censtatd.gov.hk Philippines Philippine Statistics Authority psa.gov.ph General Authority for Statistics (Saudi mospi.nic.in stats.gov.sa/en/ India Central Statistical Office (India) Saudi Arabia Arabia) Indonesia Statistics Indonesia bps.go.id Sri Lanka Department of Census and Statistics statistics.gov.lk Central organization for statistics and cosit.gov.iq cbssyr.sy Iraq information technology (COSIT) Syria Central Bureau of Statistics in Syria Iran Statistical Centre of Iran amar.org.ir Tajikistan Agency on Statistics stat.tj Israel Israel Central Bureau of Statistics cbs.gov.il Thailand National Statistical Office of Thailand (NSO) web.nso.go.th State Committee of Turkmenistan on Bureau of Statistics stat.go.jp stat.gov.tm Japan Turkmenistan Statistics The Hashemite Kingdom of Jordan-Department United Arab Federal Competitiveness and Statistics http://fcsa.gov.ae/e dos.gov.jo Jordan of Statistics Emirates Authority n-us Agency of the Republic of Kazakhstan on State Committee of the Republic of eng.stat.kz stat.uz Kazakhstan statistics Uzbekistan Uzbekistan on Statistics North Korea Central Bureau of Statistics Vietnam General Statistics Office of Vietnam gso.gov.vn South Korea Statistics Korea (KOSTAT) kostat.go.kr Yemen Central statistical organization (CSO) cso-yemen.org Kyrgyzstan National Statistical Committee of Kyrgyz Republic stat.kg Oceania Country Organization Website Country Organization Website Australia Australian Bureau of Statistics (ABS) abs.gov.au Niue Niue Statistics spc.int/prism/niue 71 Appendices Cook mfem.gov.ck Cook Islands Statistics Office palaugov.net/stats Islands statistics Palau Office of Planning and Statistics (OPS) Papua New National Statistical Office of Papua New statsfiji.gov.fj nso.gov.pg Fiji Fiji Islands Bureau of Statistics Guinea Guinea spc.int/prism/kiri sbs.gov.ws Kiribati Kiribati Statistics Office bati Samoa Statistical Services Division Marshall spc.int/prism/m Solomon spc.int/prism/Solom Islands Office of Management and Statistics arshalls/ Islands Solomon Islands Statistics ons Federated States of Federated States of Micronesia Division of fsmstatistics.fm/ Government of Tonga-Statistics spc.int/to/ Micronesia Statistics Tonga Department spc.int/prism/na spc.int/prism/tuvalu Nauru Nauru Bureau of Statistics uru Tuvalu Central Statistics Division (CSD) New stats.govt.nz vnso.gov.vu Zealand Statistics New Zealand Vanuatu Vanuatu National Statistics Office (VNSO) 72