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Chart and table of population level and growth rate for the Kano, Nigeria metro area from 1950 to 2025.
Estimate population figures at state administrative level and different age groups
National
18 of the 37 states in Nigeria were selected using procedures described in the methodology report
Sample survey data [ssd]
A. Sampling Frame The sampling frame was the 2006 National Population Census. For administrative purposes, Nigeria has 36 states and the Federal Capital Territory. These states are grouped into six geopolitical zones - the North Central, North East, North West, South East, South South and South West. The states in turn are divided into 776 Local Governments. The demographic and political characteristics of the states vary considerably. For example, the number of component local government areas in the states ranges from 8 in Bayelsa State (in the South South) to 44 in Kano State (in the North West). Likewise state populations vary widely from 1.41 million in the Abuja Federal Capital Territory to 9.38 million in Kano State. The National Bureau of Statistics splits the country further into 23, 070 enumeration areas (EAs). While the enumeration areas are equally distributed across the local government areas, with each local government area having 30 enumeration areas, the differences in the number of local government areas across states implies that there are also huge differences in the number of enumeration areas across states. Appendix table 1 summarizes the population according to the 2006 population census (in absolute and proportionate numbers), number of local government areas, and number of enumeration areas in each state .
Given the above, a stratified random sampling technique was thought to be needed to select areas according to population and the expected prevalence of migrants. The National Bureau of Statistics (NBS) provided a randomly selected set of enumeration areas and households spread across all states in the Federation from the 2006 sampling frame. Every state in Nigeria has three senatorial zones (often referred to as North, Central and South or East, Central and West). The NBS sample enumeration areas were distributed such that within each state, local government areas from each senatorial zones were included in the sample, with Local Governments in each state nearly evenly distributed between rural and urban areas. In all, a total of 3188 enumeration areas were selected. These enumeration areas were unevenly spread across States; some states in the North West (Kano, Katsina, and Jigawa), and a few in the South South (Akwa Ibom and Delta) had over 100 enumeration areas selected while others such as Imo and Abia in the South East, and Borno, Gombe and Taraba in the North East, had as few as 20 enumeration areas selected. This selection partially reflected the relative population distribution and number of Local Government Areas in the component states. Annex Table B shows details of the states and geopolitical regions, their shares in population of the country, the number of Local Government Areas and enumeration areas in each state and the number of enumeration areas given in the NBS list that formed the frame for the study.
B. The Sample for the Migration Survey
a. Sample Selection of States, Local Governments and Enumeration Areas Originally, the intention was to have proportionate allocation across all states, using the population of each state in the 2006 Census to select the number of households to be included in the sample. But it was later recognized that this would not yield enough migrant households, particularly those with international migrants, especially as the total number of households that could likely be covered in the sample to was limited to 2000. Consequently, a disproportionate sampling approach was adopted, with the aim of oversampling areas of the country with more migrants. According to Bilsborrow (2006), this approach becomes necessary because migrants are rare populations for which a distinct disproportionate sampling procedure is needed to ensure they are adequately captured. Given the relative rareness of households with out-migrants to international destinations within the 10 year reference period (selected by the World Bank for all countries) prior to the planned survey, sampling methods appropriate for sampling rare elements were desirable, specifically, stratified sampling with two-phase sampling at the last stage.
Establishing the strata would require that there be previous work, say from the most recent Census, to determine migration incidence among the states. However, the needed census data could not be obtained from either the National Bureau of Statistics or the National Population Commission. Therefore, the stratification procedure had to rely on available literature, particularly Hernandez-Coss and Bun (2007), Agu (2009) and a few other recent, smaller studies on migration and remittances in Nigeria. Information from this literature was supplemented by expert judgement about migration from team members who had worked on economic surveys in Nigeria in the past. Information from the literature and the expert assessment indicated that migration from households is considerably higher in the South than in the North. Following this understanding, the states were formed into two strata- those with high and those with low incidence of migration. In all, 18 States (16 in the South and 2 in the North) were put into the high migration incidence stratum while 19 states (18 in the North and 1 in the South) were classified l into the low migration incidence stratum (column C of Appendix Table 1).
The Aggregate population of the 18 states in the high migration incidence stratum was 67.04 million, spread across 10,850 Enumeration areas. Thus, the mean population of an EA in the high migration stratum was 6179. In turn, the aggregate population of the 19 states in the low migration incidence stratum was 72.95 million spread across 12,110 EAs yielding a mean EA population of 6024. These numbers were close enough to assume the mean population of EAs was essentially the same. To oversample states in the high stratum, it was decided to select twice as high a proportion of the states as in the low stratum. To further concentrate the sample and make field work more efficient in being oriented to EAs more likely to have international migrants, we decided to select randomly twice as many LGAs in each state in the high stratum states as in the low stratum states.
Thus, 12 states were randomly selected with probabilities of selection proportionate to the population size of each state (so states with larger populations were accordingly more likely to fall in the sample) from the high stratum states. Then two LGAs were randomly selected from each sample state and 2 EAs per sample LGA (one urban, one rural) to yield a total of 12 x 2 x 2 or 48 EAs in the high stratum states. For the low stratum, 6 states were randomly selected. From each of these, 1 LGA was randomly picked and 2 EAs were selected per sample LGA to give a total of 6 x 1 x 2 or 12 EAs in the low stratum. This yielded a total of 60 EAs for both strata. Given the expected range of 2000 households to be sampled, approximately 67 households were to be sampled from each local government area or 34 households from each enumeration area.
So far, the discussion has assumed two groups of households - migrant and non-migrant households. However, the study was interested in not just lumping all migrants together, but rather in classifying migrants according to whether their destination was within or outside the country. Migrant households were thus subdivided into those with former household members who were international migrants and those with former household members who were internal migrants. Three strata of households were therefore required, namely:
The selection of states to be included in the sample from both strata was based on Probabilities of Selection Proportional to (Estimated) Size or PPES. The population in each stratum was cumulated and systematic sampling was performed, with an interval of 12.16 million for the low stratum (72.95 million divided by 6 States), and 5.59 million for the high stratum (67.04 million divided by 12 States). This yields approximately double the rate of sampling in the high migration stratum, as earlier explained. Using a random start between 0 and 12.16, the following states were sampled in the low stratum: Niger, Bauchi, Yobe, Kano, Katsina, and Zamfara. In the high stratum, states sampled were Abia, Ebonyi, Imo, Akwa Ibom, Delta, Edo, Rivers, Lagos, Ondo, Osun and Oyo. Given its large population size, Lagos fell into the sample twice. The final sample, with LGAs and EAs moving from North to South (i.e. from the low to the high stratum states) is presented in Table 1 below.
The sample was concentrated in the South since that is where it was expected that more households have international migrants. It was expected that the survey would still also be reasonably representative of the whole country and of both internal migrant and non-migrant households through weighting the data. To this effect, field teams were asked to keep careful track at all stages of the numbers of people and households listed compared to the number in the
Nigeria is the African country with the largest population, counting over 230 million people. As of 2024, the largest city in Nigeria was Lagos, which is also the largest city in sub-Saharan Africa in terms of population size. The city counts more than nine million inhabitants, whereas Kano, the second most populous city, registers around 3.6 million inhabitants. Lagos is the main financial, cultural, and educational center in the country. Where Africa’s urban population is booming The metropolitan area of Lagos is also among the largest urban agglomerations in the world. Besides Lagos, another most populated citiy in Africa is Cairo, in Egypt. However, Africa’s urban population is booming in other relatively smaller cities. For instance, the population of Bujumbura, in Burundi, could grow by 123 percent between 2020 and 2035, making it the fastest growing city in Africa and likely in the world. Similarly, Zinder, in Niger, could reach over one million inhabitants by 2035, the second fastest growing city. Demographic urban shift More than half of the world’s population lives in urban areas. In the next decades, this will increase, especially in Africa and Asia. In 2020, over 80 percent of the population in Northern America was living in urban areas, the highest share in the world. In Africa, the degree of urbanization was about 40 percent, the lowest among all continents. Meeting the needs of a fast-growing population can be a challenge, especially in low-income countries. Therefore, there will be a growing necessity to implement policies to sustainably improve people’s lives in rural and urban areas.
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LGAs with the type of hotspots based on mean annual incidence rate and proportion of years with reported cholera cases.
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Cholera hotspots classification based on statistical method (SaTScan).
The Nigerian states of Sokoto and Taraba had the largest percentage of people living below the poverty line as of 2019. The lowest poverty rates were recorded in the South and South-Western states. In Lagos, this figure equaled 4.5 percent, the lowest rate in Nigeria.
A large population in poverty
In Nigeria, an individual is considered poor when they have an availability of less than 137.4 thousand Nigerian Naira (roughly 334 U.S. dollars) per year. Similarly, a person having under 87.8 thousand Naira (about 213 U.S. dollars) in a year available for food was living below the poverty line according to Nigerian national standards. In total, 40.1 percent of the population in Nigeria lived in poverty.
Food insecurity on the rise
On average, 21.4 percent of the population in Nigeria experienced hunger between 2018 and 2020. People in severe food insecurity would go for entire days without food due to lack of money or other resources. Over the last years, the prevalence with severe food among Nigerians has been increasing, as the demand for food is rising together with a fast-growing population.
The 2004 Nigeria DHS EdData Survey (NDES) was a nationally representative sample survey covering 4,268 households, 3,987 parent/guardians, 81 independent children age 13-16, and 9,695 children age 4-16. The primary objective of the 2004 NDES is to provide upto date household-based information on education among children of primary and secondary school age in order to inform the development, monitoring, and evaluation of education programmes in Nigeria. The survey focuses on the factors influencing household decisions about children’s school attendance. In addition, information is available on school attendance, costs of schooling (monetary and non-monetary) and parent/guardian attitudes about schooling. The 2004 NDES was the first education survey of its kind in Nigeria, and was linked to the 2003 Nigeria Demographic and Health Survey (DHS). The survey report (available under External Resources) presents information on adult educational attainment, children’s characteristics and rates of school attendance, absenteeism among primary school pupils and secondary school students, household expenditures on schooling and other contributions to schooling, and parent/guardian perceptions of schooling, among other topics.
The sample size for both the 2003 Nigeria DHS survey and the 2004 NDES was sufficiently large to provide estimates for indicators at the national level, by urban-rural residence, and at the regional level for most indicators. Twelve survey teams trained by the National Population Commission (NPC), in collaboration with the Federal Ministry of Education (FMOE), conducted the survey from February to July 2004.
National Coverage
Individuals Households
Sample survey data [ssd]
The sample for the 2004 NDES is based on the sampling frame for the 2003 Nigeria DHS survey, which was designed to provide estimates of health and demographic indicators for the country as a whole, urban and rural areas, and six geo-political zones (hereafter referred to as regions). This discussion will first address the sample design for the 2003 Nigeria DHS survey, then the subsequent design for the 2004 NDES.
The 2003 Nigeria DHS sample points (clusters) were systematically selected from a list of enumeration areas (EAs) defined in the 1991 Population Census. A total of 365 clusters was drawn from the census sample frame. After selecting the 365 clusters, the NPC trained teams to conduct the comprehensive listing of households and to update maps in the selected clusters. Following the listing operation, households to be included in the 2003 Nigeria DHS survey were selected, with the number of households selected per cluster being inversely proportional to the size of the cluster. In the 2003 Nigeria DHS sampling frame, the number of households by region was disproportional to population size, in order to have adequate numbers of cases for reporting by region. For both the 2003 Nigeria DHS survey and the 2004 NDES, the sample was constructed to allow for separate estimates for key indicators in each of the six geo-political regions in Nigeria (North Central, North East, North West, South East, South South, and South West), with the result that the sample is not selfweighting at the national level.
Of the 365 clusters selected for the 2003 Nigeria DHS survey, 362 were successfully sampled. For the 2004 NDES, all of the 362 clusters completed for the 2003 Nigeria DHS survey were selected, and within those clusters, all households with children in the eligible child age range (4-16) were selected, comprising 4,563 households with one or more children age 4-16. Of these 362 clusters, 360 clusters were successfully completed for the 2004 NDES.
Of the 4,563 potential households selected, the 2004 NDES fieldwork teams successfully interviewed 4,268 households. The main reason that potential households were not interviewed was that the household had moved.
Face-to-face [f2f]
Four questionnaires were used for the 2004 NDES: 1. The Household Questionnaire 2. The Parent/Guardian Questionnaire 3. The Eligible Child Questionnaire 4. The Independent Child Questionnaire These are all available under Appendix D of the Survey Report available under External Resources.
The Household questionnaire listed all of the people who were members of the household at the time the household was surveyed during the 2003 Nigeria DHS survey. The three purposes of the 2004 NDES Household Questionnaire were to: - Confirm that the household was the same household surveyed by the 2003 Nigeria DHS survey; - Identify which children were eligible (qualified) to be covered by the Eligible Child Questionnaire and those eligible to have anthropometric and literacy/numeracy data collected about them; and - Identify a parent or guardian as the respondent for each eligible child. Children who were age 4-16 at the time of the 2003 Nigeria DHS survey were eligible to be covered by the Eligible Child Questionnaire. Children age 4-9 at the time of the 2003 Nigeria DHS survey had their height and weight measured, and children age 4-12 were given a literacy/numeracy test.
The Parent/Guardian Questionnaire collected background information on each parent/guardian respondent and on general education issues. Information was collected on the parent/guardian’s age, education, literacy, and religion. Questions were asked about the walking time and distance to the nearest primary and secondary schools, as well as household support of and participation in school activities. Parent/guardians were also asked about their views on school quality, the benefits and disadvantages of schooling, and reproductive health and HIV/AIDS education. In addition, information was collected on each primary school attended by the children for whom the parent/guardian responded, including the school type, location, and the reason for selection of that school.
The Eligible Child Questionnaire collected different kinds of information about each eligible child age 4-16, depending on the child’s schooling status. While the subject of the Eligible Child Questionnaire was the individual child and his/her schooling, the respondent for the questionnaire was the child’s parent/guardian, as the purpose of the questionnaire was to collect information on issues from the parent/guardian’s perspective. Data were collected on the following topics, according to a child’s schooling status: • Schooling background and participation during the 2003-2004 school year (attended school during the 2003-2004 school year, dropped out of school, or never attended school) • Frequency of and reasons for pupil absenteeism, household expenditures on schooling, and other costs of schooling (for children who attended school during the 2002-2003 school year) • Reasons for dropping out of school (for children who had dropped out of school) • Reasons for not attending school during the 2003-2004 school year (for children who had never attended school) • Children’s eating patterns
The Independent Child Questionnaire was used to interview directly a small percentage of the children age 13-16 in the selected households, rather than collecting information from a parent/guardian respondent. Independent children included those age 13-16 who were the head of the household, or the spouse of the head, or the son-in-law or daughter-in-law of the household head. Because these children did not have a parent/guardian who could answer questions about their schooling decisions, these children were interviewed directly. The same information was collected from these children themselves that otherwise would have been collected in the Eligible Child Questionnaire, and in terms of analysis, the data were grouped with data on other children in the eligible child age range.
The questionnaires were translated from English into three local languages—Hausa, Igbo, and Yoruba. Pretest training and fieldwork took place from 22 September to 4 October, 2003. For this exercise, six interviewers were trained (two per local language). The questionnaires were tested in Awka and Nibo (in Anambra State), Ibadan (in Oyo State), and Kano (in Kano State) in all languages, including English.
All questionnaires for the NDES were returned to the NPC headquarters in Abuja for data processing. Data processing consisted of office editing, the coding of open-ended questions, data entry, verification, and correcting of the computer-identified errors. A team of two data entry supervisors, a questionnaire administrator, three office editors, and ten data entry clerks processed the data. Data entry and editing started in late February, using the computer package CSPro (Census and Survey Processing System), which was specifically designed to process data from large-scale household surveys of this type. Data tables were produced using CSPro.
A total of 4,354 households were occupied, of which 4,268 were successfully interviewed, for an overall response rate of 98 percent. The household response rate was similar in urban and rural areas. In the interviewed households, 9,695 children were found and Eligible Child Questionnaires were completed for all of these children. In addition, 90 independent children were identified and interviews were completed with 81 of them, producing a response rate of 90 percent.
The estimates from a sample survey are affected by two types of errors: (1)
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Cholera clusters.
The 2021 Nigeria Malaria Indicator Survey (NMIS) was implemented by the National Malaria Elimination Programme (NMEP) of the Federal Ministry of Health (FMoH) in collaboration with the National Population Commission (NPC) and National Bureau of Statistics (NBS).
The primary objective of the 2021 NMIS was to provide up-to-date estimates of basic demographic and health indicators related to malaria. Specifically, the NMIS collected information on vector control interventions (such as mosquito nets), intermittent preventive treatment of malaria in pregnant women, exposure to messages on malaria, care-seeking behaviour, treatment of fever in children, and social and behaviour change communication (SBCC). Children age 6–59 months were also tested for anaemia and malaria infection. The information collected through the NMIS is intended to assist policymakers and programme managers in evaluating and designing programmes and strategies for improving the health of the country’s population.
National coverage
Sample survey data [ssd]
The sample for the 2021 NMIS was designed to provide most of the survey indicators for the country as a whole, for urban and rural areas separately, and for each of the country’s six geopolitical zones, which include 36 states and the Federal Capital Territory (FCT). Nigeria’s geopolitical zones are as follows: • North Central: Benue, Kogi, Kwara, Nasarawa, Niger, Plateau, and FCT • North East: Adamawa, Bauchi, Borno, Gombe, Taraba, and Yobe • North West: Jigawa, Kaduna, Kano, Katsina, Kebbi, Sokoto, and Zamfara • South East: Abia, Anambra, Ebonyi, Enugu, and Imo • South South: Akwa Ibom, Bayelsa, Cross River, Delta, Edo, and Rivers • South West: Ekiti, Lagos, Ogun, Osun, Ondo, and Oyo
The 2021 NMIS used the sample frame for the proposed 2023 Population and Housing Census (PHC) of the Federal Republic of Nigeria. Administratively, Nigeria is divided into states. Each state is subdivided into local government areas (LGAs), each LGA is divided into wards, and each ward is divided into localities. Localities are further subdivided into convenient areas called census enumeration areas (EAs). The primary sampling unit (PSU), referred to as a cluster unit for the 2021 NMIS, was defined on the basis of EAs for the proposed 2023 PHC.
A two-stage sampling strategy was adopted for the 2021 NMIS. In the first stage, 568 EAs were selected with probability proportional to the EA size. The EA size is the number of households residing in the EA. The sample selection was done in such a way that it was representative of each state. The result was a total of 568 clusters throughout the country, 195 in urban areas and 373 in rural areas.
For further details on sample design, see Appendix A of the final report.
Face-to-face [f2f]
Three questionnaires were used in the 2021 NMIS: the Household Questionnaire, the Woman’s Questionnaire, and the Biomarker Questionnaire. The questionnaires, based on The DHS Program’s model questionnaires, were adapted to reflect the population and health issues relevant to Nigeria. After the questionnaires were finalised in English, they were translated into Hausa, Yoruba, and Igbo.
The processing of the 2021 NMIS data began immediately after the start of fieldwork. As data collection was being completed in each cluster, all electronic data files were transferred via the IFSS to the NPC central office in Abuja. Data files were registered and checked for inconsistencies, incompleteness, and outliers. The field teams were alerted on any inconsistencies and errors. Secondary editing, carried out in the central office, involved resolving inconsistencies and coding open-ended questions. The biomarker paper questionnaires were compared with electronic data files to check for any inconsistencies in data entry. Data entry and editing were carried out using the CSPro software package. Concurrent processing of the data offered a distinct advantage because it maximised the likelihood of the data being error-free and accurate. Timely generation of field check tables also allowed for effective monitoring. Secondary editing of the data was completed in February 2022. The data processing team coordinated this exercise at the central office.
A total of 14,185 households were selected for the survey, of which 13,887 were occupied and 13,727 were successfully interviewed, yielding a response rate of 99%. In the interviewed households, 14,647 women age 15-49 were identified for individual interviews. Interviews were completed with 14,476 women, yielding a response rate of 99%.
The estimates from a sample survey are affected by two types of errors: nonsampling errors and sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and in data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, or incorrect data entry. Although numerous efforts were made during the implementation of the 2021 Nigeria Malaria Indicator Survey (NMIS) to minimise this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.
Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2021 NMIS is only one of many samples that could have been selected from the same population, using the same design and expected sample size. Each of these samples would yield results that differ somewhat from the results of the selected sample. Sampling errors are a measure of the variability among all possible samples. Although the exact degree of variability is unknown, it can be estimated from the survey results.
Sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, and so on), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95% of all possible samples of identical size and design.
If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2021 NMIS sample was the result of a multistage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed via SAS programmes developed by ICF. These programmes use the Taylor linearisation method to estimate variances for estimated means, proportions, and ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.
Sampling errors tables are presented in Appendix B of the final report.
Data Quality Tables
See details of the data quality tables in Appendix C of the final report.
From January 2022 and February 2023, the Nigerian government allocated the highest disbursements to Delta, Akwa Ibom, Rivers, Bayelsa, Lagos, Kano, and Enugu. These states received over 100 billion Naira each, with Delta receiving almost ***** billion Naira. The FAAC (Federal Account Allocation Committee) disbursements represent the funds given to states and regions. They are allocated in proportion to each state population and, consequently, to the number of local governments in the state.
The 2007 Nigeria Enterprise Survey was part of the UK Department for International Development/World Bank Group Investment Climate Program (ICP) that was launched by the Minister of Finance in August 2007. This program was a response to the request from the Nigeria Federal Minister of Finance to the World Bank Group and UK Department for International Development (DFID) to assist in the development of a diagnostic base on which enterprise and investment climate constraints could be measured and benchmarked internally across the 36 states and the Federal Capital Territory of Nigeria and internationally against key comparator countries, particularly the "BRIC" countries (Brazil, Russia, India and China).
The survey was conducted between September 2007 and February 2008. Data from 2387 establishments was analyzed. The survey was administered across 11 states (Abia, Anambra, Abuja, Bauchi, Cross Rivers, Enugu, Kaduna, Kano, Lagos, Ogun and Sokoto) and included manufacturing and services firms of different sizes.
The objective of the Enterprise Surveys is to obtain feedback from companies in client countries on the state of the private sector as well as to help in building a panel of enterprise data that will make it possible to track changes in the business environment over time, thus allowing, for example, impact assessments of reforms. Through face-to-face interviews with firms in the manufacturing and services sectors, the survey assesses the constraints to private sector growth and creates statistically significant business environment indicators that are comparable across countries.
The standard Enterprise Survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, and performance measures. Over 90% of the questions objectively ascertain characteristics of a country’s business environment. The remaining questions assess the survey respondents’ opinions on what are the obstacles to firm growth and performance.
National
The primary sampling unit of the study is the establishment. An establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.
The whole population, or the universe, covered in the Enterprise Surveys is the non-agricultural economy. It comprises: all manufacturing sectors according to the ISIC Revision 3.1 group classification (group D), construction sector (group F), services sector (groups G and H), and transport, storage, and communications sector (group I). Note that this population definition excludes the following sectors: financial intermediation (group J), real estate and renting activities (group K, except sub-sector 72, IT, which was added to the population under study), and all public or utilities sectors.
Sample survey data [ssd]
The sample includes 2387 establishments: 1891 enterprises have at least 5 full-time employees and 496 are micro establishments with less than 5 full-time workers.
The sample for enterprises with more than four employees was designed using stratified random sampling with strata defined by region, sector and firm size.
Establishments located in 11 states - Abia, Anambra, Abuja, Bauchi, Cross Rivers, Enugu, Kaduna, Kano, Lagos, Ogun and Sokoto - were interviewed.
Following the ISIC (revision 3.1) classification, the following industries were targeted: all manufacturing sectors (group D), construction (group F), retail and wholesale services (subgroups 52 and 51 of group G), hotels and restaurants (group H), transport, storage, and communications (group I), and computer and related activities (sub-group 72 of group K). For establishments with five or more full-time permanent paid employees, this universe was stratified according to the following categories of industry: 1. Manufacturing: Food and Beverages (Group D, sub-group 15); 2. Manufacturing: Garments (Group D, sub group 18); 3. Manufacturing: Other Manufacturing (Group D excluding sub-groups 15 and 18); 4. Retail Trade: (Group G, sub-group 52); 5. Rest of the universe, including: • Construction (Group F); • Wholesale trade (Group G, sub-group 51); • Hotels, bars and restaurants (Group H); • Transportation, storage and communications (Group I); • Computer related activities (Group K, sub-group 72).
Size stratification was defined following the standardized definition used for the Enterprise Surveys: small (5 to 19 employees), medium (20 to 99 employees), and large (more than 99 employees). For stratification purposes, the number of employees was defined on the basis of reported permanent full-time workers.
The sampling frame of establishments with 5 employees and more was built with lists sourced from the Nigeria Manufacturer Association, the National Bureau of Statistics in Abia, Anambra, Abuja, Cross River, Enugu, Kaduna, Lagos, the ministry of commerce and industry in Ogun, Kano, Bauchi, and from the Abuja Business Directory, the Sokoto Business Directory. This master list was used to set the target sample size for each stratum. During the survey period, the list was updated as new information regarding establishments that had closed or were out-of-scope was gathered. The final population size in all strata and locations was 771018 with the vast majority of establishments operating in the micro and manufacturing strata. The sample (including the entire rest of universe and retail sample in each state) was selected at random from the master list by a computer program.
In this survey, the micro establishment stratum covers all establishments of the targeted categories of economic activity with less than 5 employees. The implementing agency (EEC Canada) selected an aerial sampling approach to estimate the population of establishments and select the sample in this stratum for all states of the survey.
First, to randomly select individual micro establishments for surveying, the following procedure was followed: i) select districts and specific zones of each district where there was a high concentration of micro establishments; ii) count all micro establishments in these specific zones; iii) based on this count, create a virtual list and select establishments at random from that virtual list; and iv) based on the ratio between the number selected in each specific zone and the total population in that zone, create and apply a skip rule for selecting establishments in that zone.
The districts and the specific zones were selected at first according to local sources. The EEC team then went in the field to verify the sources and to count micro establishments. Once the count for each zone was completed, the numbers were sent back to EEC head office in Montreal.
At the head office, the count by zone was converted into one list of sequential numbers for the whole survey region, and a computer program performed a random selection of the determined number of establishments from the list. Then, based on the number that the computer selected in each specific zone, a skip rule was defined to select micro establishments to survey in that zone. The skip rule for each zone was sent back to the EEC field team.
In Nigeria, enumerators were sent to each zone with instructions how to apply the skip rule defined for that zone as well as how to select replacements in the event of a refusal or other cause of non-participation.
Face-to-face [f2f]
The current survey instruments are available: - Core Questionnaire + Manufacturing Module [ISIC Rev.3.1: 15-37] - Core Questionnaire + Retail Module [ISIC Rev.3.1: 52] - Core Questionnaire [ISIC Rev.3.1: 45, 50, 51, 55, 60-64, 72] - Micro Establishments Questionnaire (for establishments with 1 to 4 employees).
The "Core Questionnaire" is the heart of the Enterprise Survey and contains the survey questions asked of all firms across the world. There are also two other survey instruments - the "Core Questionnaire + Manufacturing Module" and the "Core Questionnaire + Retail Module." The survey is fielded via three instruments in order to not ask questions that are irrelevant to specific types of firms, e.g. a question that relates to production and nonproduction workers should not be asked of a retail firm. In addition to questions that are asked across countries, all surveys are customized and contain country-specific questions. An example of customization would be including tourism-related questions that are asked in certain countries when tourism is an existing or potential sector of economic growth.
The survey topics include firm characteristics, gender participation, access to finance, annual sales, costs of inputs/labor, workforce composition, bribery, licensing, infrastructure, trade, crime, competition, capacity utilization, land and permits, taxation, informality, business-government relations, innovation and technology, registration, and performance measures. The questionnaire also assesses the survey respondents' opinions on
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Chart and table of population level and growth rate for the Kano, Nigeria metro area from 1950 to 2025.