Living Standards Survey 2003
Nigeria, 2003 - 2004
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Apr 25, 2019
Last modified
Apr 25, 2019
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Identification
Survey ID Number
NGA_2003_LSS_v01_M
Title
Living Standards Survey 2003
Subtitle
First round
Country
| Name | Country code |
|---|---|
| Nigeria | NGA |
Study type
Living Standards Measurement Study [hh/lsms]
Series Information
The scourge of poverty on a significant proportion of the Nigerian Population has been charted in the past by a series of four Consumer Expenditure Surveys Implemented by the then Federal Office of Statistics: in 1960, 1985, 1992 and 1996. Over the 16-year period, the report of the surveys indicated that poverty was most widespread in the rural areas and also feminised. The desire and commitment of the government to tackle the deplorable high incidence of poverty pointed to the need to develop a baseline survey, the Nigeria Living Standard Survey, 2003/2004 for the monitoring and evaluation of the various governments anti-poverty programmes such as National Poverty Eradication Programme (NPEP), National Economic Empowerment and Development Strategy (NEEDS) and Nigeria Millennium Development Goals (MDGs). The findings of this report cut across the various nature, dimensions and characteristics of the poor. The report provided valuable poverty statistics as well as indicators for poverty policy and programme monitoring and evaluation.
Abstract
The national initiatives at poverty tracking started in Nigeria in the early 1990s between Federal Office of Statistics and the World Bank. At the inception, the National Consumer Surveys data set series for 1980-1996 were analysed which charted the profile of poverty in Nigeria. This culminated in a Poverty Profile for Nigeria Report (1980-1996) which has since served as bench-mark for monitoring and evaluation of various government anti-government poverty and policies. The Poverty Profile for Nigeria 2004 is the latest and a good follow-up to the previous one.
With the recognition by the Nigerian Government of the multi-sectoral and multi-dimensional nature of poverty, a number of coordinated programmes and policies had been formulated to combat poverty in all its ramifications. Among the programmes are National Poverty Eradication Programme (NAPEP), the National Economic Empowerment and Development Strategy (NEEDS) and the Millennium Development Goals of the government which are aimed basically at poverty reduction. These programmes require a framework for poverty statistics production, management and tracking.
The Nigeria Living Standard Survey institutionalised by the Federal Office of Statistics provided a major survey mechanism framework for regular production, management and tracking of poverty programmes and policies. The recent Profile of Poverty for Nigeria as elucidated in this report is a commendable effort in providing current, timely and highly relevant poverty statistics and indicators for monitoring and evaluation of anti-poverty programmes and policies. The findings of the report chronicled the magnitude, nature, character and dimensions of poverty in Nigeria in 2004.
With the recognition by the Nigerian Government of the multi-sectoral and multi-dimensional nature of poverty, a number of coordinated programmes and policies had been formulated to combat poverty in all its ramifications. Among the programmes are National Poverty Eradication Programme (NAPEP), the National Economic Empowerment and Development Strategy (NEEDS) and the Millennium Development Goals of the government which are aimed basically at poverty reduction. These programmes require a framework for poverty statistics production, management and tracking.
The Nigeria Living Standard Survey institutionalised by the Federal Office of Statistics provided a major survey mechanism framework for regular production, management and tracking of poverty programmes and policies. The recent Profile of Poverty for Nigeria as elucidated in this report is a commendable effort in providing current, timely and highly relevant poverty statistics and indicators for monitoring and evaluation of anti-poverty programmes and policies. The findings of the report chronicled the magnitude, nature, character and dimensions of poverty in Nigeria in 2004.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Household and individual
Version
Version Description
version 1.2
Version Date
2008-08-30
Version Notes
v1.0 was originally released in 2006
v1.1 was reviewed using the IHSN check list.
- used IHSN template previous version used the default template
v1.2 this combined the expenditure, household and individual ddi's together - also the documentation of the variables
v1.1 was reviewed using the IHSN check list.
- used IHSN template previous version used the default template
v1.2 this combined the expenditure, household and individual ddi's together - also the documentation of the variables
Scope
Notes
Survey was designed to collect household characteristics and demographic, education, health, migration, characteristics for poverty analysis.
Also consuption information was use for CPI rebasing
Also consuption information was use for CPI rebasing
Topics
| Topic | Vocabulary | URI |
|---|---|---|
| consumption/consumer behaviour [1.1] | CESSDA | http://www.nesstar.org/rdf/common |
| economic conditions and indicators [1.2] | CESSDA | http://www.nesstar.org/rdf/common |
| income, property and investment/saving [1.5] | CESSDA | http://www.nesstar.org/rdf/common |
| rural economics [1.6] | CESSDA | http://www.nesstar.org/rdf/common |
| employment [3.1] | CESSDA | http://www.nesstar.org/rdf/common |
| in-job training [3.2] | CESSDA | http://www.nesstar.org/rdf/common |
| unemployment [3.5] | CESSDA | http://www.nesstar.org/rdf/common |
| working conditions [3.6] | CESSDA | http://www.nesstar.org/rdf/common |
| conflict, security and peace [4.1] | CESSDA | http://www.nesstar.org/rdf/common |
| government, political systems and organisations [4.4] | CESSDA | http://www.nesstar.org/rdf/common |
| crime [5.1] | CESSDA | http://www.nesstar.org/rdf/common |
| law enforcement [5.2] | CESSDA | http://www.nesstar.org/rdf/common |
| legal systems [5.3] | CESSDA | http://www.nesstar.org/rdf/common |
| compulsory and pre-school education [6.2] | CESSDA | http://www.nesstar.org/rdf/common |
| vocational education [6.7] | CESSDA | http://www.nesstar.org/rdf/common |
| childbearing, family planning and abortion [8.2] | CESSDA | http://www.nesstar.org/rdf/common |
| general health [8.4] | CESSDA | http://www.nesstar.org/rdf/common |
| health care and medical treatment [8.5] | CESSDA | http://www.nesstar.org/rdf/common |
| housing [10.1] | CESSDA | http://www.nesstar.org/rdf/common |
| children [12.1] | CESSDA | http://www.nesstar.org/rdf/common |
| gender and gender roles [12.6] | CESSDA | http://www.nesstar.org/rdf/common |
| elderly [12.2] | CESSDA | http://www.nesstar.org/rdf/common |
| family life and marriage [12.5] | CESSDA | http://www.nesstar.org/rdf/common |
| social and occupational mobility [12.8] | CESSDA | http://www.nesstar.org/rdf/common |
| youth [12.10] | CESSDA | http://www.nesstar.org/rdf/common |
| community, urban and rural life [13.1] | CESSDA | http://www.nesstar.org/rdf/common |
| cultural and national identity [13.3] | CESSDA | http://www.nesstar.org/rdf/common |
| religion and values [13.5] | CESSDA | http://www.nesstar.org/rdf/common |
| social behaviour and attitudes [13.6] | CESSDA | http://www.nesstar.org/rdf/common |
| social conditions and indicators [13.8] | CESSDA | http://www.nesstar.org/rdf/common |
| time use [13.9] | CESSDA | http://www.nesstar.org/rdf/common |
| fertility [14.2] | CESSDA | http://www.nesstar.org/rdf/common |
| migration [14.3] | CESSDA | http://www.nesstar.org/rdf/common |
| social welfare systems/structures [15.2] | CESSDA | http://www.nesstar.org/rdf/common |
| information technology [16.2] | CESSDA | http://www.nesstar.org/rdf/common |
Keywords
| Keyword |
|---|
| Age |
| sex |
| education |
| literacy |
| health |
| employment |
| agriculture |
| non-farm enterpise |
| consumption |
| expenditure |
| harvest |
| crop |
| occupation |
| income |
| revenue |
| hivaids |
| expenses |
| migration |
| vaccination |
Coverage
Geographic Coverage
National Zone State Lga
Universe
Household members
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| National Bureau of Statistics | Federal Government of Nigeria |
Producers
| Name | Role |
|---|---|
| World Bank | funding |
| Department of International Development | funding |
| European Union | funding |
| The Bristish Council | Technical Assistance |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| Federal Government of Nigeria | FGN | Funding |
| World Bank | WB | Funding |
| Department of International Development | DFID | Funding |
| European Union | EU | Funding |
Other Identifications/Acknowledgments
| Name | Affiliation | Role |
|---|---|---|
| The Bristish Council | DFID | Technical Assistance |
Sampling
Sampling Procedure
SAMPLE DESIGN
The sampling designs for the NLSS was meant to give estimates at National, Zonal and State levels. The first stage was a duster of housing units called Enumeration Area (EA), while the second stage was the housing unit.
SAMPLE SIZE
One hundred and twenty (120 EAs) were selected and sensitized in each state while sixty enumeration areas were selected at the Federal Capital Territory (FCT). Ten E.As with five housing units were studied per month. This meant that fifty housing units were canvassed per month in each state and twenty-five housing units in Abuja.
One hundred and twenty (120) EAs were selected in 12 replicates in each State from the NISH master sample frame in replicates (4-15). However, 60 EAs were selected in the Federal Capital Territory. Five (5) housing units (HUs) were scientifically selected in each of the selected EAs. One replicate consisting of 10 EAs in the State and 5 EAs in the Federal Capital Territory were covered every month. Fifty (50) HUs were covered in each State and 25 HUs in the Federal Capital Territory per month. This implied that the survey had an anticipated national sample size of twenty-one thousand and nine hundred (21,900) HUs for the country for the 12-month survey period. Each State had a sample size of 600 HUs, while the Federal Capital Territory had a sample size of 300. The sample size is robust enough to provide reasonable estimates at national and sub-national (State) levels.
ESTIMATION PROCEDURE The following statistical notations were used:
N = the number of EAs in each State
ni = Size of replicates rth
r = number of replicates in a State
H = number of housing units listed in the ith selected EA.
Xhj = number of housing units selected from ith selected EA.
Wrij = weight of the replicate =????????nhijNxH
Yrij = total value of variable from the ith HU of ith selected EA.
Replicate Estimate (Monthly Estimate) ()??=yWyi
Annual State Estimate ???
NOTE
See page 91 and 92 of the report
The sampling designs for the NLSS was meant to give estimates at National, Zonal and State levels. The first stage was a duster of housing units called Enumeration Area (EA), while the second stage was the housing unit.
SAMPLE SIZE
One hundred and twenty (120 EAs) were selected and sensitized in each state while sixty enumeration areas were selected at the Federal Capital Territory (FCT). Ten E.As with five housing units were studied per month. This meant that fifty housing units were canvassed per month in each state and twenty-five housing units in Abuja.
One hundred and twenty (120) EAs were selected in 12 replicates in each State from the NISH master sample frame in replicates (4-15). However, 60 EAs were selected in the Federal Capital Territory. Five (5) housing units (HUs) were scientifically selected in each of the selected EAs. One replicate consisting of 10 EAs in the State and 5 EAs in the Federal Capital Territory were covered every month. Fifty (50) HUs were covered in each State and 25 HUs in the Federal Capital Territory per month. This implied that the survey had an anticipated national sample size of twenty-one thousand and nine hundred (21,900) HUs for the country for the 12-month survey period. Each State had a sample size of 600 HUs, while the Federal Capital Territory had a sample size of 300. The sample size is robust enough to provide reasonable estimates at national and sub-national (State) levels.
ESTIMATION PROCEDURE The following statistical notations were used:
N = the number of EAs in each State
ni = Size of replicates rth
r = number of replicates in a State
H = number of housing units listed in the ith selected EA.
Xhj = number of housing units selected from ith selected EA.
Wrij = weight of the replicate =????????nhijNxH
Yrij = total value of variable from the ith HU of ith selected EA.
Replicate Estimate (Monthly Estimate) ()??=yWyi
Annual State Estimate ???
NOTE
See page 91 and 92 of the report
Deviations from the Sample Design
Sampling Error (Variance) Estimate The Jacknife indefinite method of variance estimation was used for the survey because the method required replication and clustering. An estimate of State variance was first obtained. Cluster estimate is ()ywijiji???= Mean Estimate rnrz??= Therefore
mean variance is ()rSnrV2=?
where ()()221-?-?=?rnrSr
NOTE
See page 93 of the report
mean variance is ()rSnrV2=?
where ()()221-?-?=?rnrSr
NOTE
See page 93 of the report
Response Rate
The response rate was very high
Weighting
The NLSS, like most household surveys, is based on NISH frame. The NISH design is a two-stage design with EA's as first stage units and households as second stage units. Ten enumeration areas (EAs) were randomly selected each month and five household were systematically selected from the household listing of each selected EAs. Population level estimates are made by multiplying the data for each household by two factors, one equal to the inverse of the probability of selecting that household from the total list of households in its EA, and one equal to the inverse of the probability of selecting that EA from the list of EAs in its state. The selections can be done by treating every unit as the same and using simple random selection or, if the data is available, a more efficient sample can be selected using some size variable known for every unit of the population thought to be correlated with the variables of interest for measurement. So the weighting factor is at the EA level in each state:
where
Nh = the total number of EAs in state h.
nh = the number of sampled EAs in state h.
Mhi = the number of listed households in ith EA of state h.
nhi = the number of sampled households in ith EA of state h.
Xhij = the number of persons in the jth household in ith EA of state h.
Phij = the poverty score for the jth household in ith EA of state h.
So the above will apply to all the individual members in order to give the population. However, the above weighting factor will be multiplied by average household size, when there is need to take the household aggregates to the population.
where
Nh = the total number of EAs in state h.
nh = the number of sampled EAs in state h.
Mhi = the number of listed households in ith EA of state h.
nhi = the number of sampled households in ith EA of state h.
Xhij = the number of persons in the jth household in ith EA of state h.
Phij = the poverty score for the jth household in ith EA of state h.
So the above will apply to all the individual members in order to give the population. However, the above weighting factor will be multiplied by average household size, when there is need to take the household aggregates to the population.
Data Collection
Dates of Data Collection
| Start | End | Cycle |
|---|---|---|
| 2003 | 2004 | 12 months |
Time periods
| Start date | End date | Cycle |
|---|---|---|
| 2003 | 2004 | 12 months |
Data Collection Mode
Face-to-face [f2f]
Supervision
The most important of the supervisor's responsibilities is to ensure that the quality of the data collected and entered is unquestionable. To this end, a number of specific tasks have been assigned.
(i) Publicity: You must supervise the delivery of the letters of introduction to the local authorities and chiefs in the rural areas and, to the households in the urban areas. You will introduce the team and explain the purpose of the survey in each selected cluster. Finding The Selected Household: You should help the interviewers find the selected households, using the maps and information established during the pre-survey stage. You should correct the maps where necessary. Also, help the interviewers to persuade reluctant households to participate. For those households which persist in refusing or those which cannot be traced, it is your responsibility to replace these households with others from the list of replacement households. If the selected household has left the dwelling, and a new household now lives there, then you should select the new household as the replacement household. If the dwelling is now vacant, then you should take the next "replacement" household on your sample list.
(iii) Verification Of Questionnaires: At the end of every visit, you will have to check that the questionnaires have been correctly completed before the team leaves the field. If necessary, you will have to ask the interviewer to go back to the household to complete the questionnaire.
(iv) Observing Interviews: At least thrice every cycle during the survey, you must accompany each interviewer to observe his interview techniques.
(v) Verification of Interview: Every day, you should visit at random, one of the households interviewed on the previous day to ascertain whether the interviewer actually visited the house to conduct an interview.
(vi) Sending the completed questionnaires to the Data Entry Operator. The first round data cover sections 1-8 and the second covers 8-13. At the end of the third visit, when data in sections 1-6 will have been collected, you should send the completed part of the questionnaire to the Data Entry Operator. And at the end of the cycle (seventh visit) you should send the second part (sections 8-13) of the questionnaire to the Data Entry Operator so that she/he enters the data while you leave the cluster.
(vii) Checking The Printouts: After data for each round have been entered in the computer, you should compare the printout with the data on the questionnaires. You should also look for any errors made by the interviewer, using tests for coherence in the computer programme. You will have to mark in red ink, on the printout and on the questionnaire all errors detected by the data entry operator so that the interviewer and the data entry operator can clarify these as soon as possible.
In addition, you will be responsible for collecting information on the localities surveyed (community questionnaire) and also supervise or help collect information on prices. You are also responsible for ALL the industry codes in the questionnaire. As soon as the interviewer finishes administering a section, you should do the coding before sending the questionnaires to the data entry operator. The various tasks and responsibilities for you are explained in detail in the following sections.
(i) Publicity: You must supervise the delivery of the letters of introduction to the local authorities and chiefs in the rural areas and, to the households in the urban areas. You will introduce the team and explain the purpose of the survey in each selected cluster. Finding The Selected Household: You should help the interviewers find the selected households, using the maps and information established during the pre-survey stage. You should correct the maps where necessary. Also, help the interviewers to persuade reluctant households to participate. For those households which persist in refusing or those which cannot be traced, it is your responsibility to replace these households with others from the list of replacement households. If the selected household has left the dwelling, and a new household now lives there, then you should select the new household as the replacement household. If the dwelling is now vacant, then you should take the next "replacement" household on your sample list.
(iii) Verification Of Questionnaires: At the end of every visit, you will have to check that the questionnaires have been correctly completed before the team leaves the field. If necessary, you will have to ask the interviewer to go back to the household to complete the questionnaire.
(iv) Observing Interviews: At least thrice every cycle during the survey, you must accompany each interviewer to observe his interview techniques.
(v) Verification of Interview: Every day, you should visit at random, one of the households interviewed on the previous day to ascertain whether the interviewer actually visited the house to conduct an interview.
(vi) Sending the completed questionnaires to the Data Entry Operator. The first round data cover sections 1-8 and the second covers 8-13. At the end of the third visit, when data in sections 1-6 will have been collected, you should send the completed part of the questionnaire to the Data Entry Operator. And at the end of the cycle (seventh visit) you should send the second part (sections 8-13) of the questionnaire to the Data Entry Operator so that she/he enters the data while you leave the cluster.
(vii) Checking The Printouts: After data for each round have been entered in the computer, you should compare the printout with the data on the questionnaires. You should also look for any errors made by the interviewer, using tests for coherence in the computer programme. You will have to mark in red ink, on the printout and on the questionnaire all errors detected by the data entry operator so that the interviewer and the data entry operator can clarify these as soon as possible.
In addition, you will be responsible for collecting information on the localities surveyed (community questionnaire) and also supervise or help collect information on prices. You are also responsible for ALL the industry codes in the questionnaire. As soon as the interviewer finishes administering a section, you should do the coding before sending the questionnaires to the data entry operator. The various tasks and responsibilities for you are explained in detail in the following sections.
Data Collection Notes
The FOS permanent Field staff who were resident in the enumeration areas were responsible for data collection during the survey. These interviewers conducted interviews with the households. There were seven interviewer visits to each selected household at a minimum of four-day interval in a cycle of 30 days. A dairy of daily consumption and expenditure was used to support the interviews.
Composition of the Team for data Collection
Every State had 20 roving teams, while FCT, Abuja operated with 10 teams. A team was made up of one supervisor and one enumerator.
The teams were structured into two groups, which worked alternatively each month to cover the selected EA.
Supervision and Quality Control
Supervision and Quality Control A number of measures were put in place to ensure that the NLSS data were of good and acceptable quality. For instance, a supervisor was attached to each team to observe interviews and confirm the pre-selected households. He was to verify and edit completed questionnaires. The State officers and zonal controllers conducted regular monitoring visits to the EAs. Headquarters monitoring groups also visited states on quarterly basis, for on-the- spot assessment of the quality of work. An independent firm was engaged to monitor the fieldwork in the States from the commencement to the end of the survey. A World Bank Mission team from Washington also took part in the monitoring exercise.
Retrieval
Completed Questionnaires were sent to zonal offices from the States for onward transmission to the NBS headquarters for data extraction and data processing. The retrieval of records was done on a monthly basis.
Composition of the Team for data Collection
Every State had 20 roving teams, while FCT, Abuja operated with 10 teams. A team was made up of one supervisor and one enumerator.
The teams were structured into two groups, which worked alternatively each month to cover the selected EA.
Supervision and Quality Control
Supervision and Quality Control A number of measures were put in place to ensure that the NLSS data were of good and acceptable quality. For instance, a supervisor was attached to each team to observe interviews and confirm the pre-selected households. He was to verify and edit completed questionnaires. The State officers and zonal controllers conducted regular monitoring visits to the EAs. Headquarters monitoring groups also visited states on quarterly basis, for on-the- spot assessment of the quality of work. An independent firm was engaged to monitor the fieldwork in the States from the commencement to the end of the survey. A World Bank Mission team from Washington also took part in the monitoring exercise.
Retrieval
Completed Questionnaires were sent to zonal offices from the States for onward transmission to the NBS headquarters for data extraction and data processing. The retrieval of records was done on a monthly basis.
Data Collectors
| Name | Abbreviation | Affiliation |
|---|---|---|
| National Bureau of Statistics | NBS | Federal Government of Nigeria |
Questionnaires
Questionnaires
The questionnaire is a structured questionnaire developed as a joint effort of the National Bureau of Statistics, the World Bank and National Planning Commission. After series of meeting and two consultative workshops, seven survey instruments were developed:
Household Diary Record Book.
Questionnaire Part A: Household Questionnaire.
Questionnaire Part B: Household Consumption Questionnaire.
The interviewer's manuals .
Supervisor's manuals.
Occupation and Industry Code Booklets .
Prices Questionnaire.
Household Diary Record Book.
Questionnaire Part A: Household Questionnaire.
Questionnaire Part B: Household Consumption Questionnaire.
The interviewer's manuals .
Supervisor's manuals.
Occupation and Industry Code Booklets .
Prices Questionnaire.
Data Processing
Data Editing
Headquarters Training of Trainers (T0T) The first level of training at the headquarter consisted of three categories of officers, namely, the trainers at the zonal level, fieldwork monitoring officers and data processing officers who were crucial to the successful implementation of the survey.
The intensive and extensive training lasted for five days. Zonal Level Training The training took place in the six zonal FOS [now NBS] offices representing the six geo-political zones of the country. These are Ibadan (South West) Enugu (South East), Calabar (South South), Jos (North Central), Maiduguri (North East) and Kaduna (North West).
The composition of the team from each State to the six different zones were the State officer, one scrutiny officer and two field officers, making four persons per state. Two resource persons from the headquarters did the training with the zonal controllers participating and contributing during the five-day regimented and intensive training. State Level Training
The third level training was at the State level. A total of 40 officers were trained, comprising 20 enumerators, 10 editing staff and 10 supervisors.
The State Statistical Agencies, as a matter policy, contributed 5-10 enumerators. The ten-day exercise was also regimented, intensive and extensive because the enumerators were also crucial for effective implementation of data collection.
The intensive and extensive training lasted for five days. Zonal Level Training The training took place in the six zonal FOS [now NBS] offices representing the six geo-political zones of the country. These are Ibadan (South West) Enugu (South East), Calabar (South South), Jos (North Central), Maiduguri (North East) and Kaduna (North West).
The composition of the team from each State to the six different zones were the State officer, one scrutiny officer and two field officers, making four persons per state. Two resource persons from the headquarters did the training with the zonal controllers participating and contributing during the five-day regimented and intensive training. State Level Training
The third level training was at the State level. A total of 40 officers were trained, comprising 20 enumerators, 10 editing staff and 10 supervisors.
The State Statistical Agencies, as a matter policy, contributed 5-10 enumerators. The ten-day exercise was also regimented, intensive and extensive because the enumerators were also crucial for effective implementation of data collection.
Other Processing
There were five levels of computer edits before analysis took place. This was critical to ensuring the quality and acceptability of the data. Level 1: Control Edits:
These were to ensure the sample integrity. The total households captured must match with master sample list. Level 2: Inter-Questionnaire Structure:
These were required in order to compute the Standard of Living (SOL), quintile distribution or compute per capita value. Mismatches and duplicates were reconciled.
Level 3: Intra-Questionnaire: This was required for sectoral analysis. Information from the roster (age and sex) was matched with respective sections in the questionnaire. Since the household roster was the primary source for computing the universe of subsequent sections, these had to be consistent. Mismatches and duplicates of household members’ identification were rectified. Level 4: Edits: These checks monitor the intra-record consistency. It was important that logical responses and skip patterns were followed. Level 5: General Edits: This checked for outliers and corrections were made through static or dynamic imputation.
Data Analysis The Staff of Computer Management and Information Services (CMIS) of the NBS carried out the data entry of the edited questionnaire and ran programmes to further detect inconsistencies and other related errors as part of the final editing. Tables were then generated from the analyses. Also at the request of the then Federal Office of Statistics, under the British Council Economic Management Capacity Building (EMCAP) Project, a DFID Consultant came to Nigeria to provide technical assistance in the evaluation of dataset.
These were to ensure the sample integrity. The total households captured must match with master sample list. Level 2: Inter-Questionnaire Structure:
These were required in order to compute the Standard of Living (SOL), quintile distribution or compute per capita value. Mismatches and duplicates were reconciled.
Level 3: Intra-Questionnaire: This was required for sectoral analysis. Information from the roster (age and sex) was matched with respective sections in the questionnaire. Since the household roster was the primary source for computing the universe of subsequent sections, these had to be consistent. Mismatches and duplicates of household members’ identification were rectified. Level 4: Edits: These checks monitor the intra-record consistency. It was important that logical responses and skip patterns were followed. Level 5: General Edits: This checked for outliers and corrections were made through static or dynamic imputation.
Data Analysis The Staff of Computer Management and Information Services (CMIS) of the NBS carried out the data entry of the edited questionnaire and ran programmes to further detect inconsistencies and other related errors as part of the final editing. Tables were then generated from the analyses. Also at the request of the then Federal Office of Statistics, under the British Council Economic Management Capacity Building (EMCAP) Project, a DFID Consultant came to Nigeria to provide technical assistance in the evaluation of dataset.
Access policy
Access authority
| Name | URL | |
|---|---|---|
| National Bureau of Statistics | feedback@nigerianstat.gov.ng | http://www.nigerianstat.gov.ng |
Contacts
| Name | Affiliation | URL | |
|---|---|---|---|
| G.O Adewoye | Director Census & Surveys | goadewoye@nigerianstat.gov.ng | http://www.nigerianstat.gov.ng |
| Mrs A.N. Adewimbi | Head of Information and Comnucation Technology Department | taadewnmbi@nigerianstat.gov.ng | http://www.nigerianstat.gov.ng |
| Biyi Fafunmi | Data Curator | biyifafunmi@nigerianstat.gov.ng | http://www.nigerianstat.gov.ng |
| Mrs A. A. Akinsanya | Data Archivist | paakinsanya@nigerianstat.gov.ng | http://www.nigerianstat.gov.ng |
| National Bureau of Statistics | feedback@nigerianstat.gov.ng | http://www.nigerianstat.gov.ng |
Confidentiality
The confidentiality of the individual respondent is protected by law (Statistical Act 2007)
This is published in the Official Gazette of the Federal republic of Nigeria No. 60 vol. 94 of 11th June 2007. See section 26 para.2. Punitive measures for breeches of confidentiality are outlined in section 28 of the same Act.
Access conditions
A comprehensive data access policy is been developed by NBS, however section 27 of the Statistical Act 2007outlines the data access obligation of data producers which includes the realease of properly anonymized micro data.
Citation requirements
National Bureau of Statistics, Nigeria, National Living Standard Survey 2003 v1.2
Disclaimer and copyrights
Disclaimer
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
Copyright
(c)NBS 2007
Metadata production
DDI Document ID
DDI_NGA_2003_LSS_v01_M_WB
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| National Bureau of Statistics | NBS | Federal Republic of Nigeria | Major Producer of Statistics |
Date of Metadata Production
2008-09-03
DDI Document version
Version 1.2
Version 1.3 (July 2012) DDI and ID number fields edited by World Bank for World Bank Microdata Library
Version 1.3 (July 2012) DDI and ID number fields edited by World Bank for World Bank Microdata Library