Abstract

The National Bureau of Statistics (NBS) was established with the Statistics Act of 2007 and the merger of the Federal Office of Statistics (FOS) and the National Data Bank (NDB). Nigeria has a Federal System of government with 36 States and a Federal Capital Territory and 774 Local Government Areas. Each Federal Ministry, Department and Agency has a Director of Statistics. Each state has a Director of Statistics and a Head of statistics Unit at the Local Government level. These and the Statistical Institutes constitute Nigeria's National Statistical System (NSS) which is coordinated by the NBS. The Nigeria National Data Archive was established to: Promote best practice and international standards for the documentation of microdata amongst data producers in the country Provide equitable access to microdata in the interest of all citizens Ensure the long term preservation of microdata and the related metadata, and their continued viability and usability The Data Archive holds NBS datasets from 1999 to the current year.

Analysis unit

Households, individuals, and establishments

Kind of data

Administrative records and survey data

Nigeria NBS Forecast: Real GDP data was reported at 84,064,363.500 NGN mn in 2019. This records an increase from the previous number of 79,596,971.230 NGN mn for 2018. Nigeria NBS Forecast: Real GDP data is updated yearly, averaging 69,144,885.840 NGN mn from Dec 2011 (Median) to 2019, with 9 observations. The data reached an all-time high of 84,064,363.500 NGN mn in 2019 and a record low of 57,511,041.770 NGN mn in 2011. Nigeria NBS Forecast: Real GDP data remains active status in CEIC and is reported by National Bureau of Statistics of the Federal Republic of Nigeria. The data is categorized under Global Database’s Nigeria – Table NG.A021: GDP: Forecast: National Bureau of Statistics.

Nigeria NBS Forecast: Real GDP: YoY data was reported at 5.610 % in 2019. This stayed constant from the previous number of 5.610 % for 2018. Nigeria NBS Forecast: Real GDP: YoY data is updated yearly, averaging 5.310 % from Dec 2011 (Median) to 2019, with 9 observations. The data reached an all-time high of 6.220 % in 2014 and a record low of 2.970 % in 2015. Nigeria NBS Forecast: Real GDP: YoY data remains active status in CEIC and is reported by National Bureau of Statistics of the Federal Republic of Nigeria. The data is categorized under Global Database’s Nigeria – Table NG.A021: GDP: Forecast: National Bureau of Statistics.

Abstract

The main objectives of the 2018/19 NLSS are: i) to provide critical information for production of a wide range of socio-economic and demographic indicators, including for benchmarking and monitoring of SDGs; ii) to monitor progress in population's welfare; iii) to provide statistical evidence and measure the impact on households of current and anticipated government policies. In addition, the 2018/19 NLSS could be utilized to improve other non-survey statistical information, e.g. to determine and calibrate the contribution of final consumption expenditures of households to GDP; to update the weights and determine the basket for the national Consumer Price Index (CPI); to improve the methodology and dissemination of micro-economic and welfare statistics in Nigeria.

The 2018/19 NLSS collected a comprehensive and diverse set of socio-economic and demographic data pertaining to the basic needs and conditions under which households live on a day to day basis. The 2018/19 NLSS questionnaire includes wide-ranging modules, covering demographic indicators, education, health, labour, expenditures on food and non-food goods, non-farm enterprises, household assets and durables, access to safety nets, housing conditions, economic shocks, exposure to crime and farm production indicators.

Geographic coverage

National coverage

Analysis unit

Households

Universe

The survey covered all de jure households excluding prisons, hospitals, military barracks, and school dormitories.

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLING PROCEDURE The 2018/19 NLSS sample is designed to provide representative estimates for the 36 states and the Federal Capital Territory (FCT), Abuja. By extension. The sample is also representative at the national and zonal levels. Although the sample is not explicitly stratified by urban and rural areas, it is possible to obtain urban and rural estimates from the NLSS data at the national level. At all stages, the relative proportion of urban and rural EAs as has been maintained. Before designing the sample for the 2018/19 NLSS, the results from the 2009/10 HNLSS were analysed to extract the sampling properties (variance, design effect, etc.) and estimate the required sample size to reach a desired precision for poverty estimates in the 2018/19 NLSS.

EA SELECTION: The sampling frame for the 2018/19 NLSS was based on the national master sample developed by the NBS, referred to as the NISH2 (Nigeria Integrated Survey of Households 2). This master sample was based on the enumeration areas (EAs) defined for the 2006 Nigeria Census Housing and Population conducted by National Population Commission (NPopC). The NISH2 was developed by the NBS to use as a frame for surveys with state-level domains. NISH2 EAs were drawn from another master sample that NBS developed for surveys with LGA-level domains (referred to as the “LGA master sample”). The NISH2 contains 200 EAs per state composed of 20 replicates of 10 sample EAs for each state, selected systematically from the full LGA master sample. Since the 2018/19 NLSS required domains at the state-level, the NISH2 served as the sampling frame for the survey. Since the NISH2 is composed of state-level replicates of 10 sample EAs, a total of 6 replicates were selected from the NISH2 for each state to provide a total sample of 60 EAs per state. The 6 replicates selected for the 2018/19 NLSS in each state were selected using random systematic sampling. This sampling procedure provides a similar distribution of the sample EAs within each state as if one systematic sample of 60 EAs had been selected directly from the census frame of EAs.

A fresh listing of households was conducted in the EAs selected for the 2018/19 NLSS. Throughout the course of the listing, 139 of the selected EAs (or about 6%) were not able to be listed by the field teams. The primary reason the teams were not able to conduct the listing in these EAs was due to security issues in the country. The fieldwork period of the 2018/19 NLSS saw events related to the insurgency in the north east of the country, clashes between farmers and herdsman, and roving groups of bandits. These events made it impossible for the interviewers to visit the EAs in the villages and areas affected by these conflict events. In addition to security issues, some EAs had been demolished or abandoned since the 2006 census was conducted. In order to not compromise the sample size and thus the statistical power of the estimates, it was decided to replace these 139 EAs. Additional EAs from the same state and sector were randomly selected from the remaining NISH2 EAs to replace each EA that could not be listed by the field teams. This necessary exclusion of conflict affected areas implies that the sample is representative of areas of Nigeria that were accessible during the 2018/19 NLSS fieldwork period. The sample will not reflect conditions in areas that were undergoing conflict at that time. This compromise was necessary to ensure the safety of interviewers.

HOUSEHOLD SELECTION: Following the listing, the 10 households to be interviewed were selected from the listed households. These households were selected systemically after sorting by the order in which the households were listed. This systematic sampling helped to ensure that the selected households were well dispersed across the EA and thereby limit the potential for clustering of the selected households within an EA. Occasionally, interviewers would encounter selected households that were not able to be interviewed (e.g. due to migration, refusal, etc.). In order to preserve the sample size and statistical power, households that could not be interviewed were replaced with an additional randomly selected household from the EA. Replacement households had to be requested by the field teams on a case-by-case basis and the replacement household was sent by the CAPI managers from NBS headquarters. Interviewers were required to submit a record for each household that was replaced, and justification given for their replacement. These replaced households are included in the disseminated data. However, replacements were relatively rare with only 2% of sampled households not able to be interviewed and replaced.

Sampling deviation

Although a sample was initially drawn for Borno state, the ongoing insurgency in the state presented severe challenges in conducting the survey there. The situation in the state made it impossible for the field teams to reach large areas of the state without compromising their safety. Given this limitation it was clear that a representative sample for Borno was not possible. However, it was decided to proceed with conducting the survey in areas that the teams could access in order to collect some information on the parts of the state that were accessible.

The limited area that field staff could safely operate in in Borno necessitated an alternative sample selection process from the other states. The EA selection occurred in several stages. Initially, an attempt was made to limit the frame to selected LGAs that were considered accessible. However, after selection of the EAs from the identified LGAs, it was reported by the NBS listing teams that a large share of the selected EAs were not safe for them to visit. Therefore, an alternative approach was adopted that would better ensure the safety of the field team but compromise further the representativeness of the sample. First, the list of 788 EAs in the LGA master sample for Borno were reviewed by NBS staff in Borno and the EAs they deemed accessible were identified. The team identified 359 EAs (46%) that were accessible. These 359 EAs served as the frame for the Borno sample and 60 EAs were randomly selected from this frame. However, throughout the course of the NLSS fieldwork, additional insurgency related events occurred which resulted in 7 of the 60 EAs being inaccessible when they were to be visited. Unlike for the main sample, these EAs were not replaced. Therefore, 53 EAs were ultimately covered from the Borno sample. The listing and household selection process that followed was the same as for the rest of the states.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Two sets of questionnaires – household and community – were used to collect information in the NLSS2018/19. The Household Questionnaire was administered to all households in the sample. The Community Questionnaire was administered to the community to collect information on the socio-economic indicators of the enumeration areas where the sample households reside.

Household Questionnaire: The Household Questionnaire provides information on demographics; education; health; labour; food and non-food expenditure; household nonfarm income-generating activities; food security and shocks; safety nets; housing conditions; assets; information and communication technology; agriculture and land tenure; and other sources of household income.

Community Questionnaire: The Community Questionnaire solicits information on access to transported and infrastructure; community organizations; resource management; changes in the community; key events; community needs, actions and achievements; and local retail price information.

Cleaning operations

CAPI: The 2018/19 NLSS was conducted using the Survey Solutions Computer Assisted Person Interview (CAPI) platform. The Survey Solutions software was developed and maintained by the Development Economics Data Group (DECDG) at the World Bank. Each interviewer and supervisor was given a tablet which they used to

Abstract

The Multiple Indicator Cluster Survey (MICS) is a primary source of information on women and children as it provides statistical indicators that are critical for the measurement of human development. It is an international household survey programme developed by United Nations Children’s Fund (UNICEF). The MICS is designed to collect statistically sound and internationally comparable estimates of key indicators that are used to assess the situation of children and women in the areas of health, education, child protection and HIV/AIDS. It can also be used as a data collection tool to generate data for monitoring the progress towards national goals and global commitments which aimed at promoting the welfare of children and women such as MDGs and SDGs.

OBJECTIVES

The primary objectives of Multiple Indicator Cluster Survey (MICS) Nigeria 2016-17 are:

• To provide up-to-date information for assessing the situation of children and women in Nigeria;

• To generate data for the critical assessment of the progress made in various programme areas, and to identify areas that require more attention;

• To contribute to the generation of baseline data for the SDG;

• To furnish data needed for monitoring progress toward goals established in the post Millennium Declaration and other internationally agreed goals, as a basis for future action;

• To provide disaggregated data to identify disparities among various groups to enable evidence based actions aimed at social inclusion of the most vulnerable.

Geographic coverage

National, rural/urban, states as well as the 6 geo-political zones of Nigeria.

Analysis unit

• Individuals

• Households

Universe

All household members (usual residents), all women age 15-49 years, all men age 15-49 years and all children under 5 years of age.

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLE SIZE AND SAMPLE ALLOCATION

The sample size for the Nigeria MICS5 was calculated as 37,440 households.

The principal domain of reporting to which the sample size n refers in this calculation is the state. For this sample design, determination of the sample size is based on the indicator stunting prevalence in under-5 children as the design variable. The results from the MICS4 of 2011 reported stunting prevalence at 35.8 percent at the national level. This estimate had a relatively high design effect (deff) of 4.85, indicating a large clustering effect for this characteristic. However, with the more efficient sample design for the MICS 2016-17 it was expected that the deff will be lower, so a value of 3.5 was assumed for the deff in calculating the sample size. The value for pb (percentage of children aged 0-4 years in the total population) based on the results of the MICS4 2011 and NDHS 2013 is 17.1; and Average Size (average household size) is 5.0. For state-level results, it is reasonable to use a relative margin of error (RME) of 18%. Based on previous survey results, the household response rate is assumed to be 95%.

For 34 states and the FCT Abuja a sample of 60 EAs was selected per state and 16 households per EA, which gives a sample size of 960 households in each of these states. Six (6) replicates containing ten (10) EAs/clusters each was selected from the NISH2 master sample for each of these states. In the case of Kano and Lagos States, additional results were needed at the level of the three senatorial districts in each state. Therefore, a sample of 40 EAs per senatorial district was selected in these two states from the NISH2 master sample, for a total of 120 sample EAs and 1,920 sample households in each state. The total sample size for Nigeria was 37,440 households. And the selection of 16 households per EA slightly reduces the design effects compared to the MICS 2011, in which 20 households were selected per EA

SAMPLING FRAME AND SELECTION OF CLUSTERS

The MICS sample clusters were selected from the NISH2 master sample, based on the 2006 census frame. For the NISH2 master sample the census enumeration areas were defined as primary sampling units (PSUs), stratified by state. The first stage of sampling for MICS was completed by selecting the required number of enumeration areas from the NISH2 master sample for each of the 36 states of the federation and FCT Abuja which cut across urban and rural areas.

LISTING ACTIVITIES

Since the sampling frame (the 2006 Census) was not up-to-date, a new listing of households was conducted in November 2015 for all the sample enumeration areas prior to the selection of households. For this purpose, listing teams were formed who visited all of the selected enumeration areas and listed all households in each enumeration area. Selected staff of the National Bureau of Statistics (NBS) in all the states carried out the listing exercise. Six (6) teams were constituted that carried out the listing exercise in each state except Lagos and Kano where twelve teams were constituted respectively. Each team comprises of 2 enumerators and one (1) supervisor who supervised two (2) teams. There were three (3) supervisors in each of the 35 states, and six (6) supervisors for Lagos and Kano states respectively. The listing exercise lasted for twelve (12) days. Out of the 2,340 enumeration areas selected for the household listing, one hundred and one (101) of them were not visited because they were inaccessible due to insecurity during the listing exercise.

SELECTION OF HOUSEHOLDS

Lists of households were prepared by the listing teams in the field for each enumeration area. The households were then sequentially numbered from 1 to N (the total number of households in each enumeration area) at the National Bureau of Statistics (Field Services and Methodology Department), where the selection of 16 households in each enumeration area was carried out using random systematic selection procedures.

The survey also included a questionnaire for individual men aged 15 to 49 years. It was administered in eight out of sixteen sampled households. Households with even number in each sample cluster were selected and all eligible men were interviewed.

Within each state, a sub-sample of 30 enumeration areas was systematically selected for the water quality test. In each of these sampled EAs, a systematic sub sample of three households out of sixteen (16) MICS sample households was selected for the water quality tests.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaires are based on the MICS5 questionnaire3 model (English version), customized and pre-tested in Cross River, Enugu, Gombe, Lagos, Kaduna, Kano, Nasarawa and Oyo states in April 2016. Based on the results of the pre-test, modifications were made to the wording of the questionnaires. A copy of the Nigeria MICS questionnaires is provided as Related Material.

In addition to the administration of questionnaires, salt iodization and water quality tests were conducted. Weight and height of children age under 5 years were also measured.

Cleaning operations

Data were analyzed using the Statistical Package for Social Scientists (SPSS) software, Version 21. Model syntax and tabulation plans developed by UNICEF MICS team were customized and used for this purpose.

Response rate

Out of 37,440 households sampled, 35,747 households were visited, 34,289 were found to be occupied and 33,901 were successfully interviewed, representing a household response rate of 98.9 percent.

In the interviewed households, 36,176 women (age 15-49 years) were identified. Of these, 34,376 were successfully interviewed, yielding a response rate of 95.0 percent within the interviewed households.

The survey also sampled men (age 15-49), but required only a subsample. All men (age 15-49) were identified in 17,868 households selected for the men questionnaire; 16,514 men (age 15-49 years) were listed in the household questionnaires. Questionnaires were completed for 15,183 eligible men, which corresponds to a response rate of 91.9 percent within eligible interviewed households.

There were 28,578 children under age five listed in the household questionnaires. Questionnaires were completed for 28,085 of these children, which corresponds to a response rate of 98.3 percent within interviewed households.

Overall response rates of 93.9, 90.9 and 97.2 are calculated for the individual interviews of women, men, and under-5s, respectively.

Sampling error estimates

The sample of respondents selected in the Multiple Indicator Cluster Survey (MICS) 2016 is only one of the samples that could have been selected from the same population, using the same design and size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between the estimates from all possible samples. The extent of variability is not known exactly, but can be estimated statistically from the survey data.

The following sampling error measures are presented in this appendix for each of the selected indicators:

• Standard error (se): Standard error is the square root of the variance of the estimate. For survey indicators that are means, proportions or ratios, the Taylor series linearization method is used for the estimation of standard errors. For more complex statistics, such as fertility and mortality rates, the Jackknife repeated replication method is used for standard error estimation.

• Coefficient of variation (se/r) is the ratio of the standard error to the value (r) of the indicator, and is a measure of the relative sampling error.

• Design

NBS Forecast: Inflation data was reported at 8.540 % in 2019. This records a decrease from the previous number of 8.670 % for 2018. NBS Forecast: Inflation data is updated yearly, averaging 9.490 % from Dec 2011 (Median) to 2019, with 9 observations. The data reached an all-time high of 12.220 % in 2012 and a record low of 7.980 % in 2014. NBS Forecast: Inflation data remains active status in CEIC and is reported by National Bureau of Statistics of the Federal Republic of Nigeria. The data is categorized under Global Database’s Nigeria – Table NG.I005: Inflation Rate: Forecast: National Bureau of Statistics: Annual.

Abstract

The Nigeria Labour Force Survey (NLFS) is a statistical survey designed to collect comprehensive data on employment, unemployment, and other characteristics of the population labour force. It provides quarterly estimates of the main labour force statistics with sufficient precision at the national level. This report contains findings from the Nigeria Labour Force Survey (NLFS) for the second quarter of 2024. The statistics are measured based on the labour force framework as guided by the international standard for labour market statistics for international comparability and the specific data requirements for the country.

The main objective of the NLFS is to collect basic statistics on the labour market situation in Nigeria and make labour statistics available to support government policies and programmes for effective planning, and for the private sector to support investment decision-making aimed at improving the employment situation in the country. The Labour Force Survey also serves as a tool for monitoring progress towards national goals and global commitments with an overarching goal of promotingthe welfare of the Nigerian population while ensuring the availability of labour market statistics to feed into the global sustainable development goals agenda. Labour is often one of the most important factors of production and is a major determinant of the economic system globally. Therefore, it is imperative to know whether people are working or not, how long they work, and the nature of the jobs they are engaged in.

The NLFS enables key labour market statistics and the employment situation to be monitored periodically in Nigeria. The indicators include the labour force participation rate, employment-to-population ratio, unemployment rate, time-related underemployment, self-employment, labour underutilisation, and other key job characteristics.

Geographic coverage

National Zone State Sector

Analysis unit

Individual

Universe

Household Members

Kind of data

Sample survey data [ssd]

Sampling procedure

The target sample for the entire year is 35,520 households divided across 12 months, meaning the target sample for each quarter is 8,880 households. After small levels of non-response and replacement, the final sample for Q1 2024 is 8,836 households across the 36 states including the FCT.

Sampling deviation

No Deviations

Mode of data collection

Face-to-face [f2f]

Research instrument

A structured questionnaire was used for NLFS. A household questionnaire was administered in each household, which collected various information on Identification, Demographic Characteristics(inclusion of disability questions for 5 years or older), Education, Employed at work,Temporarily absence, Agricultural work and Market Orientation, Characteristics of main and secondary job, Unemployent and out of labour.Some of the questions were administered at household level while others were at individual level.

Cleaning operations

Real - Time data editing took place at different stages throughout the processing which includes: 1) Data editing and cleaning 2) Structure checking and completeness 3) Secondary editing 4) Structural checking of data files

Response rate

The household response rate is 100%.

Sampling error estimates

The margin of error of each quarter is 1% for national estimates.

Data appraisal

A series of data quality tables and graphs are available in the reports.

Abstract

The General Household Survey is a brainchild of the National Bureau of Statistics (NBS) and is often referred to as Regular survey carried out on quarterly basis by the NBS over the years. In recent times, starting from 2004 to be precise, there is a collaborative effort between the NBS and the CBN in 2004 and 2005 and in 2006, 2007and 2008, the collaboration incorporated Nigerian Communications commission (NCC).

The purpose of the surveys or collaboration include among others: (i) To conduct multipurpose surveys to generate social and economic data series for 2009 and the first quarter of 2010

(ii) To enable NBS/CBN/NCC fulfil their mandate in production of current and credible statistics to monitor and evaluate the State of the economy and the various government programmes such as NEEDS, MDGs and 7 Point Agenda.

The key objectives of the survey include:

i) Collection of relevant statistics to facilitate the production of GDP

ii) Production of data to aid economic analysis on non-oil outputs such as Manufacturing, Agriculture and Services

iii) Production of State and Local Government Finance Statistics, Producer Price Index (PPI), Oil Sector Statistics and Flow of Funds

Collection of current socio-economic statistics in Nigeria to assist in policy formulation and aid the monitoring and evaluation of various government programmes at National and sub-national levels

Geographic coverage

National Zone State Local Government

Analysis unit

Household Analysis

Universe

Household

Kind of data

Sample survey data [ssd]

Sampling procedure

The General Household Survey and the National Agricultural Sample Survey designs derived from NBS 2007/12 NISH sample design. The 2007/12 NISH sample design is a 2-stage, replicated and rotated cluster sample design with Enumeration Areas (EAs) as first stage sampling units or Primary Sampling Units (PSUs) while Households constituted the second stage units (secondary sampling units). The households were the Ultimate Sampling Units for the multi-subject survey.

Generally, the NISH Master Sample in each State is made up of 200 EAs drawn in 20 replicates. A replicate consists of 10 EAs. Replicates 10-15, subsets of the Master Sample were studied for modules of the NISH.

The GHS was implemented as a NISH module. three replicates were studied per State including the FCT, Abuja. With a fixed-take of 15 HHs systematically selected per EA, 450 HHs thus were selected for interview per State including the FCT, Abuja. Hence, nationally, a total of 16,650 HHs were drawn from the 1,110 EAs selected for interview for the GHS. The selected EAs (and hence the HHs) cut across the rural and urban sectors.

Sampling deviation

Variance Estimate (Jackknife Method) Estimating variances using the Jackknife method will require forming replicate from the full sample by randomly eliminating one sample cluster [Enumeration Area (EA) at a time from a state containing k EAs, k replicated estimates are formed by eliminating one of these, at a time, and increasing the weight of the remaining (k-1) EAs by a factor of k/(k-1). This process is repeated for each EA.

For a given state or reporting domain, the estimate of the variance of a rate, r, is given by k Var(r ) = (Se)2 = 1 S (ri - r)2 k(k-1) i=1

where (Se) is the standard error, k is the number of EAs in the state or reporting domain.

r is the weighted estimate calculated from the entire sample of EAs in the state or reporting domain.
ri = kr - (k - 1)r(i), where

r(i) is the re-weighted estimate calculated from the reduced sample of k-1 EAs.

To obtain an estimate of the variance at a higher level, say, at the national level, the process is repeated over all states, with k redefined to refer to the total number of EAs (as opposed to the number in the states).

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire for the GHS is a structured questionnaire based on household characteristics with some modifications and additions. The House project module is a new addition and some new questions on ICT.

The questionnaires were scaned.

This section were divided into eleven parts.

Part A: Identification code, Response status, Housing characteristics/amenities and Information communication Technology (ICT). Part B: Socio-demographic characteristics and Labour force characteristics Part C: Information about the people in the household who were absent during the period of the survey. Part D: Female contraceptive only, and children ever born by mothers aged 15 years and above Part E: Births of children in the last 12 months, and trained birth attendant used during child delivery. Part F: Immunization of children aged 1 year or less and records of their vaccination Part G: Child nutrition, exclusive breast feeding and length of breast feeding. Part H: Deaths in the last 12 months, and causes of such deaths. Part I: Health of all members, of the household and health care providers. Part J: Household enterprises, income and profit made from such activities. Part K: Household expenditure, such as school fees, medical expenses, housing expenses, remittance, cloth expenses, transport expenses and food expenses.

Cleaning operations

The data editing is in 2 phases namely manual editing before the questionnaires were scanned. This involved using editors at the various zones to manually edit and ensure consistency in the information on the questionnaire.

The second editing is the computer editing, this is the cleaning of the already scanned data by the subject mater group. The questionnaires were processed at the zones. On completion, computer editing was also carried out to ensure the integrity of the data. .

Response rate

At National level ,out of the expected 1,110 EAs, all were covered which showed 100% retrieval rate. (by the table 1.12 on page 196 of the report)

At household level, out of the 16,650 expected to be covered, 16,355 were canvassed which showed 98% retrieval.

At sector level (Urban/Rural), 28.4% were recorded for Urban while Rural recorded 71.6%.

Sampling error estimates

No sampling error estimate

Data appraisal

The Quality Control measures were carried out during the survey, essentially to ensure quality of data. There were three levels of supervision involving the supervisors at the first level, CBN staff, NBS State Officers and Zonal Controllers at second level and finally the NBS/NCC Headquarters staff constituting the third level supervision. Field monitoring and quality check exercises were also carried out during the period of data collection as part of the quality control measures

Abstract

The General Household Survey is a brainchild of the National Bureau of Statistics (NBS) and is often referred to as a regular survey carried out on quarterly basis by the NBS over the years. In recent times, starting from 2004 to be precise, there is a collaborative effort between the NBS and the CBN in 2004 and 2005 and in 2006 the collaboration incorporated Nigerian Communications commission (NCC).

The main reason for conducting the survey was to enable the collaborating agencies fulfil their mandate in the production of current and credible statistics, to monitor and evaluate the status of the economy and the various government programmes such as the National Economic Empowerment and Development Strategy (NEEDS) and the Millennium Development Goals (MDGs).

The collaborative survey also assured the elimination of conflicts in data generated by the different agencies and ensured a reliable, authentic national statistics for the country.

Geographic coverage

National Coverage

Analysis unit

Household

Universe

Household

Kind of data

Sample survey data [ssd]

Sampling procedure

The GHS was implemented as a NISH module. Six replicates were studied per state including the FCT, Abuja. With a fixed-take of 10 HUs systematically selected per EA, 600 HUs thus were selected for interview per state including the FCT, Abuja. Hence, nationally, a total of 22,200 HUs were drawn from the 2,220 EAs selected for interview for the GHS. The selected EAs (and hence the HUs) cut across the rural and urban sectors.

The General Household Survey and the National Agricultural Sample Survey designs derived from NBS 2007/12 NISH sample design. The 2007/12 NISH sample design is a 2-stage, replicated and rotated cluster sample design with Enumeration Areas (EAs) as first stage sampling units or Primary Sampling Units (PSUs) while Housing Units constituted the second stage units (secondary sampling units). The housing units were the Ultimate Sampling Units for the multi-subject survey.

First Stage Selection: Generally, the NISH Master Sample in each state is made up of 200 EAs drawn in 20 replicates. A replicate consists of 10 EAs. Replicates 4 - 9, subsets of the Master Sample were studied for modules of the NISH. Sixty EAs were selected with equal probability from the list of EAs in each state of the federation and FCT, Abuja.

Second Stage Selection: In each selected EA, a listing of housing units was carried out. The result provided the frame for the second stage selection. Ten housing units were selected systematically in each EA after the completion of the listing exercise. Thereafter, all the households within the selected HUs were interviewed using GHS questionnaire.

At EAs level, out of the expected 2,220 EAs 2,204 were covered (by the table on page 177 of the report) and TABLE 1.6 RETRIEVAL STATUS OF GHS RECORDS.

At housing units level, out of the 22,200 expected to be covered, 21,796 were canvassed. (same as above)

AS PER DATA SET At EAs level, out of the expected 2,220 EAs 2,204 were covered. At housing units level, out of the 22,200 expected to be covered, 18,355 were canvassed.

Sampling deviation

Variance Estimate (Jackknife Method) Estimating variances using the Jackknife method will require forming replicate from the full sample by randomly eliminating one sample cluster [Enumeration Area (EA) at a time from a state containing k EAs, k replicated estimates are formed by eliminating one of these, at a time, and increasing the weight of the remaining (k-1) EAs by a factor of k/(k-1). This process is repeated for each EA.

For a given state or reporting domain, the estimate of the variance of a rate, r, is given by k Var(r ) = (Se)2 = 1 S (ri - r)2 k(k-1) i=1

where (Se) is the standard error, k is the number of EAs in the state or reporting domain.

r is the weighted estimate calculated from the entire sample of EAs in the state or reporting domain.
ri = kr - (k - 1)r(i), where

r(i) is the re-weighted estimate calculated from the reduced sample of k-1 EAs.

To obtain an estimate of the variance at a higher level, say, at the national level, the process is repeated over all states, with k redefined to refer to the total number of EAs (as opposed to the number in the states).

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire for the GHS is a structured questionnaire based on household characteristics with some modifications and additions. The House project module is a new addition and some new questions on ICT.

The questionnaires were scaned.

This section were divided into eleven parts.

Part A: Identification code, Response status, Housing characteristics/amenities and Information communication Technology (ICT). Part B: Socio-demographic characteristics and Labour force characteristics Part C: Information about the people in the household who were absent during the period of the survey. Part D: Female contraceptive only, and children ever born by mothers aged 15 years and above Part E: Births of children in the last 12 months, and trained birth attendant used during child delivery. Part F: Immunization of children aged 1 year or less and records of their vaccination Part G: Child nutrition, exclusive breast feeding and length of breast feeding. Part H: Deaths in the last 12 months, and causes of such deaths. Part I: Health of all members, of the household and health care providers. Part J: Household enterprises, income and profit made from such activities. Part K: Household expenditure, such as school fees, medical expenses, housing expenses, remittance, cloth expenses, transport expenses and food expenses.

Cleaning operations

The data editing is in 2 phases namely manual editing before the questionnaires were scanned. This involved using editors at the various zones to manually edit and ensure consistency in the information on the questionnaire.

The second editing is the computer editing, this is the cleaning of the already scanned data by the subject mater group. The questionnaires were processed at the zones. On completion, computer editing was also carried out to ensure the integrity of the data. .

Response rate

At National basis, 99.3 percent response rate was acheived at EA level .

While 82.7 percent was acheived at housing units level.

Sampling error estimates

No sampling error estimate

Data appraisal

The Quality Control measures were carried out during the survey, essentially to ensure quality of data. There were three levels of supervision involving the supervisors at the first level, CBN staff, NBS State Officers and Zonal Controllers at second level and finally the NBS/NCC Headquarters staff constituting the third level supervision.

Abstract

The programme for the World Census of Agriculture 2000 is the eighth in the series for promoting a global approach to agricultural census taking. The first and second programmes were sponsored by the International Institute for Agriculture (IITA) in 1930 and 1940. Subsequent ones up to 1990 were promoted by the Food and Agriculture Organization of the United Nations(FAO). FAO recommends that each country should conduct at least one agricultural census in each census programme decade and its programme for the World Census of Agriculture 2000 for instance corresponds to agricultural census to be undertaken during the decade 1996 to 2005. Many countries do not have sufficient resources for conducting an agricultural census. It therefore became an acceptable practice since 1960 to conduct agricultural census on sample basis for those countries lacking the resources required for a complete enumeration.

In Nigeria's case, a combination of complete enumeration and sample enumeration is adopted whereby the rural (peasant) holdings are covered on sample basis while the modern holdings are covered on complete enumeration. The project named “National Agricultural Sample Census” derives from this practice. Nigeria through the National Agricultural Sample Census (NASC) participated in the 1970's, 1980's, 1990's programmes of the World Census of Agriculture. Nigeria failed to conduct the Agricultural Census in 2003/2004 because of lack of funding. The NBS regular annual agriculture surveys since 1996 had been epileptic and many years of backlog of data set are still unprocessed. The baseline agricultural data is yet to be updated while the annual regular surveys suffered set back. There is an urgent need by the governments (Federal, State, LGA), sector agencies, FAO and other International Organizations to come together to undertake the agricultural census exercise which is long overdue. The conduct of 2006/2008 National Agricultural Sample Census Survey is now on course with the pilot exercise carried out in the third quarter of 2007.

The National Agricultural Sample Census (NASC) 2006/08 is imperative to the strengthening of the weak agricultural data in Nigeria. The project is phased into three sub-projects for ease of implementation; the Pilot Survey, Modern Agricultural Holding and the Main Census. It commenced in the third quarter of 2006 and to terminate in the first quarter of 2008. The pilot survey was implemented collaboratively by National Bureau of Statistics.

The main objective of the pilot survey was to test the adequacy of the survey instruments, equipments and administration of questionnaires, data processing arrangement and report writing. The pilot survey conducted in July 2007 covered the two NBS survey system-the National Integrated Survey of Households (NISH) and National Integrated Survey of Establishment (NISE). The survey instruments were designed to be applied using the two survey systems while the use of Geographic Positioning System (GPS) was introduced as additional new tool for implementing the project.

The Stakeholders workshop held at Kaduna on 21st-23rd May 2007 was one of the initial bench marks for the take off of the pilot survey. The pilot survey implementation started with the first level training (training of trainers) at the NBS headquarters between 13th - 15th June 2007. The second level training for all levels of field personnels was implemented at headquarters of the twelve (12) concerned states between 2nd - 6th July 2007. The field work of the pilot survey commenced on the 9th July and ended on the 13th of July 07. The IMPS and SPSS were the statistical packages used to develop the data entry programme.

Geographic coverage

State

Analysis unit

Households who are rearing livestock or kept poultry

Universe

Livestock or poultry household

Kind of data

Census/enumeration data [cen]

Sampling procedure

The survey was carried out in 12 states falling under 6 geo-political zones. 2 states were covered in each geo-political zone. 2 local government areas per selected state were studied. 2 Rural enumeration areas per local government area were covered and 3 Livestock/poultry farming housing units were systematically selected and canvassed.

Sampling deviation

No Deviation

Mode of data collection

Face-to-face [f2f]

Research instrument

The NASC livestock and poultry questionnaire was divided into the following sections: - Identification/description of holdings - Funds, employment and earnings/wages - Livestock - Poultry - Fixed assets - Sales - Stock - Subsidy

Cleaning operations

The data processing and analysis plan involved five main stages: training of data processing staff; manual editing and coding; development of data entry programme; data entry and editing and tabulation. Census and Surveys Processing System (CSPro) software were used for data entry, Statistical Package for Social Sciences (SPSS) and CSPro for editing and a combination of SPSS, Statistical Analysis Software (SAS) and EXCEL for table generation. The subject-matter specialists and computer personnel from the NBS and CBN implemented the data processing work. Tabulation Plans were equally developed by these officers for their areas and topics covered in the three-survey system used for the exercise. The data editing is in 2 phases namely manual editing before the data entry were done. This involved using editors at the various zones to manually edit and ensure consistency in the information on the questionnaire. The second editing is the computer editing, this is the cleaning of the already enterd data. The completed questionnaires were collected and edited manually (a) Office editing and coding were done by the editor using visual control of the questionnaire before data entry (b) Cspro was used to design the data entry template provided as external resource (c) Ten operator plus two suppervissor and two progammer were used (d) Ten machines were used for data entry (e) After data entry data entry supervisor runs fequency on each section to see that all the questionnaire were enterd

Response rate

The response rate at EA level was 100 percent, while 99.3 percent was recorded at housing units level.

Sampling error estimates

No computation of sampling error

Data appraisal

The Quality Control measures were carried out during the survey, essentially to ensure quality of data. There were two levels of supervision involving the supervisors at the first level, NBS State Officers and Zonal Controllers at second level and finally the NBS Headquarters staff constituting the second level supervision.

Abstract

Four federal agencies namely, National Bureau of Statistics (NBS), Central Bank of Nigeria (CBN), Federal Ministry of Agriculture & Rural Development (FMA&RD), and Federal Ministry of Commerce (FMC), jointly conducted three survey rounds through the National Survey of Agricultural Exportable crop Commodities (NSAEC). It is believed that the survey results would give both government and non-governmental agencies ample opportunity to address the paucity of reliable agricultural data in Nigeria.

The survey included 14 export crops: cashew, cocoa, coffee, garlic, ginger, groundnut, arabic gum, palm oil, rubber, sesame seeds, shea nuts, sugar cane, and tea.

This dataset is based on the third round of the National Survey of Agricultural Export Commodities. Previous rounds were conducted in 2002/2003 and 2004/2005.

The major objectives of the survey included:

i. To ascertain the spread of the cultivation of each of the fourteen export crops within Nigeria in terms of area cultivated by state.

ii. To provide national baseline data on agricultural export commodities.

iii. To provide structural data on agricultural export commodities in Nigeria.

iv. To obtain socio-economic data and demographic characteristics of holders within households.

v. To provide production estimates at national and state levels.

Geographic coverage

National and state

Analysis unit

Household

Universe

Household export crop holders

Kind of data

Sample survey data [ssd]

Sampling procedure

A 2-stage sample design was employed.

In the first stage, 192 Local Government Areas (LGAs) from the complete list of 774 LGAs were selected nationwide. Next 10 enumeration areas (EAs), demarcated by the National Population Commission during the 1991 population census, were systematically selected from each sampled LGA, for a total of 1,920 EAs.

In the second stage, 10 export crop farming housing units were systematically selected from each sampled EA (provided there were more than 10 farming housing units in the EA). Where there were 10 or less farming housing units no selection was required, and all available housing units were studied.

Sampling deviation

Of the expected 1,920 EAs only 1,855 were found to have export crops and were eventually studied. Out of the 18,550 export crop farm housing units expected to be covered, 16,310 were canvassed.

Mode of data collection

Face-to-face [f2f]

Research instrument

Agricultural Holding Questionnaire:

Section I: Holding Identification Section Ii: Access to Land
Section Iii: Source of Funds
Section Iv: Export Crop Farming Section Vii: Market Channel Section Viii: Quantity Sold Section X: Quantity Consumed
Section Xi: Use of Fertilizer
Section Xii: Use of Pesticides Section Xiii: Use of Improved Seedling/Seed

Some modifications were made on the 2003 questionnaire.

Cleaning operations

All questionnaires were retrieved from the field by the enumerators and submitted to the sub-offices. Next the questionnaires were organized according to EAs and were taken to the NBS state offices and finally to the zonal offices. Three NBS zonal headquarters (Ibadan, Kaduna and Enugu) were chosen for the last destination of retrieval of the questionnaires. In the case of southwest and north-central zones were merged together for the submission their records at NBS zonal headquarters in Ibadan. Northwest and northeast zones were combined to submit their records at NBS zonal headquarters in Kaduna. Finally, the southeast and southern zones were joined together to submit their records to NBS zonal headquarters in Enugu.

The completed questionnaires were collated and edited manually:

a. Office editing and coding were done by the editor using visual control of the questionnaire before data entry b. Imps was used to design the data entry template provided as an external resource c. Six operators plus two supervisor and two programmers were used d. Six machines were used for data entry e. After data entry, supervisors run frequencies on each section to see that all the questionnaire were entered f. Conversion programs were written to convert the data to SPSS also provided as an external resource

Response rate

On a national basis, 100% response rate was acheived at the LGA level and 96.61% at the EA level. While 87.92% was acheived at the export crop farming housing units level.

Sampling error estimates

No sampling error estimate

Abstract

The General Household Survey is a brainchild of the National Bureau of Statistics (NBS) and is often referred to as a regular survey carried out on quarterly basis by the NBS over the years. In recent times, starting from 2004 to be precise, there is a collaborative effort between the NBS and the CBN in 2004 and 2005 and in 2006, 2007and 2008, the collaboration incorporated Nigerian Communications commission (NCC).

The main reason for conducting the survey was to enable the collaborating agencies fulfil their mandate in the production of current and credible statistics, to monitor and evaluate the status of the economy and the various government programmes such as the National Economic Empowerment and Development Strategy (NEEDS) and the Millennium Development Goals (MDGs).

The collaborative survey also assured the elimination of conflicts in data generated by the different agencies and ensured a reliable, authentic national statistics for the country.

Geographic coverage

National Coverage

Analysis unit

Household

Universe

Household

Kind of data

Sample survey data [ssd]

Response rate

At National basis, 99.3 percent response rate was acheived at EA level .

While 82.7 percent was acheived at the housing units level.

Sampling error estimates

No sampling error estimate

Data appraisal

Quality control measures were carried out during the survey, essentially to ensure quality of data. There were three levels of supervision involving the supervisors at the first level, CBN staff, NBS State Officers and Zonal Controllers at second level and finally the NBS/NCC Headquarters staff constituting the third level supervision.

Nigeria NBS Forecast: Nominal GDP data was reported at 134,950,445.870 NGN mn in 2019. This records an increase from the previous number of 124,332,323.630 NGN mn for 2018. Nigeria NBS Forecast: Nominal GDP data is updated yearly, averaging 94,268,428.580 NGN mn from Dec 2011 (Median) to 2019, with 9 observations. The data reached an all-time high of 134,950,445.870 NGN mn in 2019 and a record low of 62,980,397.220 NGN mn in 2011. Nigeria NBS Forecast: Nominal GDP data remains active status in CEIC and is reported by National Bureau of Statistics of the Federal Republic of Nigeria. The data is categorized under Global Database’s Nigeria – Table NG.A021: GDP: Forecast: National Bureau of Statistics.

NBS: Forecast: Total Trade: YoY data was reported at 11.640 % in 2019. This records a decrease from the previous number of 17.310 % for 2018. NBS: Forecast: Total Trade: YoY data is updated yearly, averaging 10.340 % from Dec 2011 (Median) to 2019, with 9 observations. The data reached an all-time high of 48.750 % in 2011 and a record low of -24.300 % in 2015. NBS: Forecast: Total Trade: YoY data remains active status in CEIC and is reported by National Bureau of Statistics of the Federal Republic of Nigeria. The data is categorized under Global Database’s Nigeria – Table NG.JA004: Trade Statistics: Year on Year Growth: Forecast: National Bureau of Statistics: Annual.

Abstract

NASC is an exercise designed to fill the existing data gap in the agricultural landscape in Nigeria. It is a comprehensive enumeration of all agricultural activities in the country, including crop production, fisheries, forestry, and livestock activities. The implementation of NASC was done in two phases, the first being the Listing Phase, and the second is the Sample Survey Phase. Under the first phase, enumerators visited all the selected Enumeration Areas (EAs) across the Local Government Areas (LGAs) and listed all the farming households in the selected enumeration areas and collected the required information. The scope of information collected under this phase includes demographic details of the holders, type of agricultural activity (crop production, fishery, poultry, or livestock), the type of produce or product (for example: rice, maize, sorghum, chicken, or cow), and the details of the contact persons. The listing exercise was conducted concurrently with the administration of a Community Questionnaire, to gather information about the general views of the communities on the agricultural and non-agricultural activities through focus group discussions.

The main objective of the listing exercise is to collect information on agricultural activities at household level in order to provide a comprehensive frame for agricultural surveys. The main objective of the community questionnaire is to obtain information about the perceptions of the community members on the agricultural and non-agricultural activities in the community.

Additional objectives of the overall NASC program include the following: · To provide data to help the government at different levels in formulating policies on agriculture aimed at attaining food security and poverty alleviation · To provide data for the proposed Gross Domestic Product (GDP) rebasing

Geographic coverage

Estimation domains are administrative areas from which reliable estimates are expected. The sample size planned for the extended listing operation allowed reporting key structural agricultural statistics at Local Government Area (LGA) level.

Analysis unit

Agricultural Households.

Universe

Population units of this operation are households with members practicing agricultural activities on their own account (farming households). However, all households in selected EAs were observed as much as possible to ensure a complete coverage of farming households.

Kind of data

Census/enumeration data [cen]

Sampling procedure

An advanced methodology was adopted in the conduct of the listing exercise. For the first time in Nigeria, the entire listing was conducted digitally. NBS secured newly demarcated digitized enumeration area (EA) maps from the National Population Commission (NPC) and utilized them for the listing exercise. This newly carved out maps served as a basis for the segmentation of the areas visited for listing exercise. With these maps, the process for identifying the boundaries of the enumeration areas by the enumerators was seamless.

The census was carried out in all the 36 States of the Federation and FCT. Forty (40) enumeration Areas (EAs) were selected to be canvassed in each LGA, the number of EAs covered varied by state, which is a function of the number of LGAs in the state. Both urban and rural EAs were canvassed. Out of 774 LGAs in the country, 767 LGAs were covered and the remaining 7 LGAs (4 in Imo and 3 in Borno States) were not covered due to insecurity (99% coverage). In all, thirty thousand, nine hundred and sixty (30,960) EAs were expected to be covered nationwide but 30,546 EAs were canvassed.

The Sampling method adopted involved three levels of stratification. The objective of this was to provide representative data on every Local Government Area (LGA) in Nigeria. Thus, the LGA became the primary reporting domain for the NASC and the first level of stratification. Within each LGA, eighty (80) EAs were systematically selected and stratified into urban and rural EAs, which then formed the second level of stratification, with the 80 EAs proportionally allocated to urban and rural according to the total share of urban/rural EAs within the LGA. These 80 EAs formed the master sample from which the main NASC sample was selected. From the 80 EAs selected across all the LGAs, 40 EAs were systematically selected per LGA to be canvassed. This additional level selection of EAs was again stratified across urban and rural areas with a target allocation of 30 rural and 10 urban EAs in each LGA. The remaining 40 EAs in each LGA from the master sample were set aside for replacement purposes in case there would be need for any inaccessible EA to be replaced.

Details of sampling procedure implemented in the NASC (LISTING COMPONENT). A stratified two-phase cluster sampling method was used. The sampling frame was stratified by urban/rural criteria in each LGA (estimation domain/analytical stratum).

First phase: in each LGA, a total sample of 80 EAs were allocated in each strata (urban/rural) proportionally to their number of EAs with reallocations as need be. In each stratum, the sample was selected with a Pareto probability proportional to size considering the number of households as measure of size.

Second phase: systematic subsampling of 40 EAs was done (10 in Urban and 30 in Rural with reallocations as needed, if there were fewer than 10 Urban or 30 Rural EAs in an LGA). This phase was implicitly stratified through sorting the first phase sample by geography.

With a total of 773 LGAs covered in the frame, the total planned sample size was 30920 EAs. However, during fieldwork 2 LGAs were unable to be covered due to insecurity and additional 4 LGAs were suspended early due to insecurity. For the same reason, replacements of some sampled EAs were needed in many LGAs. The teams were advised to select replacement units where possible considering appurtenance to the same stratum and similarity including in terms of population size. However about 609 EAs replacement units were selected from a different stratum and were discarded from data processing and reporting.

Sampling deviation

Out of 774 LGAs in the country, 767 LGAs were covered and the remaining 7 LGAs (4 in Imo and 3 in Borno states) were not covered due to insecurity (99% coverage).

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The NASC household listing questionnaire served as a meticulously designed instrument administered within every household to gather comprehensive data. It encompassed various aspects such as household demographics, agricultural activities including crops, livestock (including poultry), fisheries, and ownership of agricultural/non-agricultural enterprises.

The questionnaire was structured into the following sections:

Section 0: ADMINISTRATIVE IDENTIFICATION Section 1: BUILDING LISTING Section 2: HOUSEHOLD LISTING (Administered to the Head of Household or any knowledgeable adult member aged 15 years and above).

Cleaning operations

Data processing of the NASC household listing survey included checking for inconsistencies, incompleteness, and outliers. Data editing and cleaning was carried out electronically using the Stata software package. In some cases where data inconsistencies were found a call back to the household was carried out. A pre-analysis tabulation plan was developed and the final tables for publication were created using the Stata software package.

Sampling error estimates

Given the complexity of the sample design, sampling errors were estimated through re-sampling approaches (Bootstrap/Jackknife)

Abstract

To facilitate the use of data collected through the high-frequency phone surveys on COVID-19, the Living Standards Measurement Study (LSMS) team has created the harmonized datafiles using two household surveys: 1) the country’ latest face-to-face survey which has become the sample frame for the phone survey, and 2) the country’s high-frequency phone survey on COVID-19.

The LSMS team has extracted and harmonized variables from these surveys, based on the harmonized definitions and ensuring the same variable names. These variables include demography as well as housing, household consumption expenditure, food security, and agriculture. Inevitably, many of the original variables are collected using questions that are asked differently. The harmonized datafiles include the best available variables with harmonized definitions.

Two harmonized datafiles are prepared for each survey. The two datafiles are: 1. HH: This datafile contains household-level variables. The information include basic household characterizes, housing, water and sanitation, asset ownership, consumption expenditure, consumption quintile, food security, livestock ownership. It also contains information on agricultural activities such as crop cultivation, use of organic and inorganic fertilizer, hired labor, use of tractor and crop sales.
2. IND: This datafile contains individual-level variables. It includes basic characteristics of individuals such as age, sex, marital status, disability status, literacy, education and work.

Geographic coverage

National coverage

Analysis unit

• Households
• Individuals

Universe

The survey covered all de jure households excluding prisons, hospitals, military barracks, and school dormitories.

Kind of data

Sample survey data [ssd]

Sampling procedure

See “Nigeria - General Household Survey, Panel 2018-2019, Wave 4” and “Nigeria - COVID-19 National Longitudinal Phone Survey 2020” available in the Microdata Library for details.

Mode of data collection

Computer Assisted Personal Interview [capi]

Cleaning operations

Nigeria General Household Survey, Panel (GHS-Panel) 2018-2019 and Nigeria COVID-19 National Longitudinal Phone Survey (COVID-19 NLPS) 2020 data were harmonized following the harmonization guidelines (see “Harmonized Datafiles and Variables for High-Frequency Phone Surveys on COVID-19” for more details).

The high-frequency phone survey on COVID-19 has multiple rounds of data collection. When variables are extracted from multiple rounds of the survey, the originating round of the survey is noted with “_rX” in the variable name, where X represents the number of the round. For example, a variable with “_r3” presents that the variable was extracted from Round 3 of the high-frequency phone survey. Round 0 refers to the country’s latest face-to-face survey which has become the sample frame for the high-frequency phone surveys on COVID-19. When the variables are without “_rX”, they were extracted from Round 0.

Response rate

See “Nigeria - General Household Survey, Panel 2018-2019, Wave 4” and “Nigeria - COVID-19 National Longitudinal Phone Survey 2020” available in the Microdata Library for details.

China resumed the release of youth unemployment data in January 2024 after publication had been suspended for six months, using a new statistical methodology. Youth unemployment hit a record high of 21.3 percent in June 2023 after having increased for several years in a row, when a spokesman of the National Bureau of Statistics of China announced that the statistical methodology for calculating age specific unemployment rates needed improvement and publication would be temporarily suspended. The new methodology does not include university students anymore, resulting in a youth unemployment rate of **** percent in June 2025. Youth jobless figures fluctuate over the year and normally peak in July in China, when the largest number of graduates enter the job market.

Unemployment Rate in China remained unchanged at 5 percent in June. This dataset provides - China Unemployment Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Geographic coverage

National coverage

Analysis unit

households/individuals

Kind of data

survey

Frequency of data collection

Yearly

Sampling procedure

Sample size:

Abstract

The Nigerian General Household Survey (GHS) is implemented in collaboration with the World Bank Living Standards Measurement Study (LSMS) team as part of the Integrated Surveys on Agriculture (ISA) program and was revised in 2010 to include a panel component (GHS-Panel). The objectives of the GHS-Panel include the development of an innovative model for collecting agricultural data, inter- institutional collaboration, and comprehensive analysis of welfare indicators and socio-economic characteristics. The GHS-Panel is a nationally representative survey of 5,000 households, which are also representative of the geopolitical zones (at both the urban and rural level). The households included in the GHS-Panel are a sub-sample of the overall GHS sample households. This survey is the third wave of the GHS-Panel, which was implemented in 2015-2016.

Geographic coverage

National Coverage

Analysis unit

Households

Universe

Household Members

Kind of data

Sample survey data [ssd]

Sampling procedure

The GHS sample is comprised of 60 Primary Sampling Units (PSUs) or Enumeration Areas (EAs) chosen from each of the 37 states in Nigeria. This results in a total of 2,220 EAs nationally. Each EA contributes 10 households to the GHS sample, resulting in a sample size of 22,200 households. Out of these 22,000 households, 5,000 households from 500 EAs were selected for the panel component and 4,916 households completed their interviews in the first wave. Given the panel nature of the survey, some households had moved from their location and were not able to be located by the time of the Wave 3 visit, resulting in a slightly smaller sample of 4,581 households for Wave 3.

In order to collect detailed and accurate information on agricultural activities, GHS-Panel households are visited twice: first after the planting season (post-planting) between August and October and second after the harvest season (post-harvest) between February and April. All households are visited twice regardless of whether they participated in agricultural activities. Some important factors such as labour, food consumption, and expenditures are collected during both visits. Unless otherwise specified, the majority of the report will focus on the information collected during the post-planting visit.

Mode of data collection

Face-to-face paper [f2f]

Cleaning operations

The data cleaning process was done in a number of stages. The first step was to ensure proper quality control during the fieldwork. This was achieved in part by using the concurrent data entry system which was designed to highlight many of the errors that occurred during the fieldwork. Errors that are caught at the fieldwork stage are corrected based on re-visits to the household on the instruction of the supervisor. The data that had gone through this first stage of cleaning was then sent from the state to the head office of NBS where a second stage of data cleaning was undertaken. During the second stage the data were examined for out of range values and outliers. The data were also examined for missing information for required variables, sections, questionnaires and EAs. Any problems found were then reported back to the state where the correction was then made. This was an ongoing process until all data were delivered to the head office.

After all the data were received by the head office, there was an overall review of the data to identify outliers and other errors on the complete set of data. Where problems were identified, this was reported to the state. There the questionnaires were checked and where necessary the relevant households were revisited and a report sent back to the head office with the corrections.

The final stage of the cleaning process was to ensure that the household- and individual-level datasets were correctly merged across all sections of the household questionnaire. Special care was taken to see that the households included in the data matched with the selected sample and where there were differences these were properly assessed and documented. The agriculture data were also checked to ensure that the plots identified in the main sections merged with the plot information identified in the other sections. This was also done for crop-by-plot information as well.