General Household Survey 2009
Nigeria, 2010
Created on
Apr 25, 2019
Last modified
Apr 25, 2019
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Identification
Survey ID Number
NGA_2009_GHS_v01_M
Title
General Household Survey 2009
Subtitle
Fifth Round
Translated Title
No translation
Country
| Name | Country code |
|---|---|
| Nigeria | NGA |
Study type
Other Household Survey [hh/oth]
Series Information
The National Bureau of Statistics (NBS) in collaboration with the Central Bank of Nigeria (CBN) and the Nigeria Communication Commission (NCC) in 2010 conducted a survey on the socio-economic activities in Nigeria for the year 2009. There is a long history of synergy in statistical project between NBS (formerly FOS) and CBN. It started with the computation of Annual Gross Domestic Product (GDP), the Consumer Price Index (CPI) and Survey of Informal Sector in Nigeria.
The National Agricultural Exportable Crops Survey was conducted by both organisations in the years 2004, 2005, 2006, 2007 and 2008. The collaborative survey on Socio-economic activities in Nigeria between NBS and CBN started in 2004, and continued till 2007 when the National Communication Commission (NCC) joined. The collaboration continued in 2008 and 2009 till the current year 2010 in which the survey is conducted for the 2009 socio-economic activities.
The National Agricultural Exportable Crops Survey was conducted by both organisations in the years 2004, 2005, 2006, 2007 and 2008. The collaborative survey on Socio-economic activities in Nigeria between NBS and CBN started in 2004, and continued till 2007 when the National Communication Commission (NCC) joined. The collaboration continued in 2008 and 2009 till the current year 2010 in which the survey is conducted for the 2009 socio-economic activities.
Abstract
The Geneal 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
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
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Household Analysis
Version
Version Description
Version 1.0 (February, 2012)
Version Date
2010-07-14
Version Notes
Version 1.0 (February, 2012) Data used to generate the tables and the report
Part D Female Contraceptive Prevelance was not related to the other part because the id was missing during printing of the questionnaire
Part D Female Contraceptive Prevelance was not related to the other part because the id was missing during printing of the questionnaire
Scope
Notes
The Socio Economic Survey, General Household -2009 includes:
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.
Par 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.
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.
Par 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.
Topics
| Topic | Vocabulary | URI |
|---|---|---|
| economic conditions and indicators [1.2] | CESSDA | http://www.nesstar.org/rdf/common |
| economic policy [1.3] | 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 |
| agricultural, forestry and rural industry [2.1] | CESSDA | http://www.nesstar.org/rdf/common |
| business/industrial management and organisation [2.2] | CESSDA | http://www.nesstar.org/rdf/common |
| employment [3.1] | CESSDA | http://www.nesstar.org/rdf/common |
| labour relations/conflict [3.3] | CESSDA | http://www.nesstar.org/rdf/common |
| retirement [3.4] | 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 |
| basic skills education [6.1] | 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 |
| natural resources and energy [9.3] | 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 |
| family life and marriage [12.5] | CESSDA | http://www.nesstar.org/rdf/common |
| gender and gender roles [12.6] | CESSDA | http://www.nesstar.org/rdf/common |
| social and occupational mobility [12.8] | CESSDA | http://www.nesstar.org/rdf/common |
| community, urban and rural life [13.1] | CESSDA | http://www.nesstar.org/rdf/common |
| specific social services: use and provision [15.3] | CESSDA | http://www.nesstar.org/rdf/common |
| information technology [16.2] | CESSDA | http://www.nesstar.org/rdf/common |
Coverage
Geographic Coverage
National Zone State Local Government
Geographic Unit
State
Universe
Household
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| National Bureau of Statistics (NBS) | Federal Government of Nigeria (FGN) |
Producers
| Name | Affiliation | Role |
|---|---|---|
| Central Bank of Nigeria | FGN | Collaboration |
| Nigerian Communication Commission | FGN | Collaboration |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| National Bureau of Statistics | NBS | Funding |
| Central Bank of Nigeria | CBN | Funding |
Other Identifications/Acknowledgments
| Name | Affiliation | Role |
|---|---|---|
| Nigerian Commnications Commision | NCC | Collaborating |
Sampling
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.
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.
Deviations from the Sample Design
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).
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).
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%.
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%.
Weighting
The variable (Hweight ) Household weight is computed and attached to the data file.
The formula adopted in calculating the design weights for the survey data (sample results) were as follows:
(i) The probability of selecting an EA within a state was obtained by dividing the total number of EAs sampled in a state by total number of EAs in that particular state. Let this be represented by fj. That is,
fj = Total Number of EAs sampled in a state
Total Number of EAs in that particular State
(ii) Likewise, the probability of selecting an housing unit (HU) within an EA was obtained by dividing the total number of housing units selected in an EA by the total number of housing units (HUs) listed in that particular EA. Let this be represented by fk. That is,
fk = Total Number of HUs selected in an EA
Total Number of HUs listed in that particular EA
Mathematically,
Design weight = Total number of EAs in a state
Total number of EAs sampled in that particular state
X
Total Number of HUs listed in an EA
Total Number of HUs selected in that particular EA
Estimation Procedures:
Let the probability of selecting the EA be fj and the probability of selecting the housing unit be fk. Then the product f = fjfk = 1 where fj = n and fk = h
Wj k N H.
Household Weight (HHWeight )
n h
Ys = N ? H ? X sj k
n j=1 h k=1
n h
= N H ? ? X sj k
n h j=1 k=1
n h
= W s j k ? ? X sj k (Note: W s j k = N . H )
j = 1 k=1 n h
Where:
ˆ
Ys = Estimate for states
N = Total Number of EAs in states
n = Selected number of EAs in states
H = Total number of Housing Units listed in the jth EA
h = Selected number of Housing Units in the jth EA.
Xsj k = Value of the element in the kth housing unit of jth EA in states.
Wsjk = Weight of the element in kth housing unit of the jth EA in states.
The formula adopted in calculating the design weights for the survey data (sample results) were as follows:
(i) The probability of selecting an EA within a state was obtained by dividing the total number of EAs sampled in a state by total number of EAs in that particular state. Let this be represented by fj. That is,
fj = Total Number of EAs sampled in a state
Total Number of EAs in that particular State
(ii) Likewise, the probability of selecting an housing unit (HU) within an EA was obtained by dividing the total number of housing units selected in an EA by the total number of housing units (HUs) listed in that particular EA. Let this be represented by fk. That is,
fk = Total Number of HUs selected in an EA
Total Number of HUs listed in that particular EA
Mathematically,
Design weight = Total number of EAs in a state
Total number of EAs sampled in that particular state
X
Total Number of HUs listed in an EA
Total Number of HUs selected in that particular EA
Estimation Procedures:
Let the probability of selecting the EA be fj and the probability of selecting the housing unit be fk. Then the product f = fjfk = 1 where fj = n and fk = h
Wj k N H.
Household Weight (HHWeight )
n h
Ys = N ? H ? X sj k
n j=1 h k=1
n h
= N H ? ? X sj k
n h j=1 k=1
n h
= W s j k ? ? X sj k (Note: W s j k = N . H )
j = 1 k=1 n h
Where:
ˆ
Ys = Estimate for states
N = Total Number of EAs in states
n = Selected number of EAs in states
H = Total number of Housing Units listed in the jth EA
h = Selected number of Housing Units in the jth EA.
Xsj k = Value of the element in the kth housing unit of jth EA in states.
Wsjk = Weight of the element in kth housing unit of the jth EA in states.
Data Collection
Dates of Data Collection
| Start | End | Cycle |
|---|---|---|
| 2010-03-31 | 2010-04-19 | 26 days |
Time periods
| Start date | End date | Cycle |
|---|---|---|
| 2009 | 2010 | 1yr |
Data Collection Mode
Face-to-face [f2f]
Supervision
As earlier stated the data collection exercise involved team made up of 3 interviewers and 1 supervisor. The supervisor assigns EAs to the interviewers and ensure that their job is properly edited at the end of the day.
Field monitoring and quality check exercises were also carried out during the period of data collection as part of the quality control measures.
The overall supervisor is the Zonal Controller in each zone and State Officers in each state ensure that all field personnel adhere to the rules and regulations on the field.
Retrieval of records was carried out in two stages. The first stage retrieval was implemented by CBN Headquarters Staff during the monitoring visit to the States and zones. The second retrieval was done during the monitoring visit of NBS Headquarters staff. A mop-up exercise was carried out by the NBS State officers and Zonal Controllers for 10 days after the scheduled period for data collection and retrieved records were sent to NBS Headquarters
Field monitoring and quality check exercises were also carried out during the period of data collection as part of the quality control measures.
The overall supervisor is the Zonal Controller in each zone and State Officers in each state ensure that all field personnel adhere to the rules and regulations on the field.
Retrieval of records was carried out in two stages. The first stage retrieval was implemented by CBN Headquarters Staff during the monitoring visit to the States and zones. The second retrieval was done during the monitoring visit of NBS Headquarters staff. A mop-up exercise was carried out by the NBS State officers and Zonal Controllers for 10 days after the scheduled period for data collection and retrieved records were sent to NBS Headquarters
Data Collection Notes
Prior to the commencement of data collection, training was conducted at two levels; Training of trainers and zonal level trainings. This training was to equip trainers and trainees with background information about the survey and what is expected of them. Also, training sessions included classroom teaching, demonstration, mock interviews, role playing, field and home exercises.
In each State, 3 teams were used comprising 3 supervisors and 12 enumerators. A team was made up of one supervisor and four enumerators. Each team covered 20 Enumeration Areas for a period of 26 days. A pair of Enumerators in a team covered 10 EAs. This translated to covering an Enumeration Area for an average of 5 days for the different statistical operations. Each team moved in a roving manner
In each State, 3 teams were used comprising 3 supervisors and 12 enumerators. A team was made up of one supervisor and four enumerators. Each team covered 20 Enumeration Areas for a period of 26 days. A pair of Enumerators in a team covered 10 EAs. This translated to covering an Enumeration Area for an average of 5 days for the different statistical operations. Each team moved in a roving manner
Data Collectors
| Name | Abbreviation | Affiliation |
|---|---|---|
| National Bureau of Statistics | NBS | Federal Government of Nigeria (FGN) |
Questionnaires
Questionnaires
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.
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.
Data Processing
Data Editing
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. .
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. .
Other Processing
The data processing analysis involved Six main stages:
Development of data scanning scren.
Training of data processing staff.
Manual editing and coding.
Data entry and scanning comminting into a data base in SPSS.
Computer editing.
Verification and conversion
The table were then generated usining SPSS.
Development of data scanning scren.
Training of data processing staff.
Manual editing and coding.
Data entry and scanning comminting into a data base in SPSS.
Computer editing.
Verification and conversion
The table were then generated usining SPSS.
Data Appraisal
Estimates of Sampling Error
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
Field monitoring and quality check exercises were also carried out during the period of data collection as part of the quality control measures
Access policy
Access authority
| Name | Affiliation | URL | |
|---|---|---|---|
| National Bureau of Statistics (NBS) | Federal Government of Nigeria (FGN) | feedback@nigerianstat.gov.ng | http://www.nigerianstat.gov.ng |
Contacts
| Name | Affiliation | URL | |
|---|---|---|---|
| National Bureau of Statistics (NBS) | Fedral Government of Nigeria (FGN) | feedback@nigerianstat.gov.ng | http://www.nigerianstat.gov.ng |
| Dr Yemi Kale | Statistician General | sgnbsk@gmail.com | http://www.nigerianstat.gov.ng |
| Mr N.G. Oparaku | Head of Real Sector and Household Statistics Department | ngoparaku@nigerianstat.gov.ng | http://www.nigerianstat.gov.ng |
| Mr E.O. Ekezie | Head of Information and Comnucation Technology Department | eekezie@nigerianstat.gov.ng | http://www.nigerianstat.gov.ng |
| Mr E .I. Fafunmi | Data Access | biyifafunmi@nigerianstat.gov.ng | http://www.nigerianstat.gov.ng |
| Mr R.F. Busari | Head (Systems Programming) | rfbusari@nigerianstat.gov.ng | http://www.nigerianstat.gov.ng |
| Mrs A. A. Akinsanya | Data Archivist | paakinsanya@nigerianstat.gov.ng | http://www.nigerianstat.gov.ng |
| World Bank Microdata Library | World Bank Data Group | microdatalib@worldbank.org |
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, General Household Survey 2009-v.1.0 for the public use (January, 2012) provided by the National Data Archive.http://www.nigerianstat.gov.ng"
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
© NBS 2012
Metadata production
DDI Document ID
DDI_NGA_2009_GHS_v01_M_WB
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| National Bureau of Statistics | NBS | Federal Government of Nigeria (FGN) | Metadata Producer |
Date of Metadata Production
2012-02-08
DDI Document version
Version 1.0 (February, 2012)
Version 1.1 (July 2012) DDI and ID number fields edited by World Bank for World Bank Microdata Library
Version 1.1 (July 2012) DDI and ID number fields edited by World Bank for World Bank Microdata Library