General Household Survey, Panel 2010-2011
Nigeria, 2010 - 2011
National Bureau of Statistics
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September 10, 2020
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September 10, 2020
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Identification
Survey ID Number
NGA_2010-2011_GHS-W1_v01_EN_M_v01_A_OCS
Title
General Household Survey, Panel 2010-2011
Country
| Name | Country code |
|---|---|
| Nigeria | NGA |
Study type
Living Standards Measurement Study [hh/lsms]
Series Information
The Nigeria General Household Survey panel component (GHS-Panel) is part of a larger, regional project in Sub-Saharan Africa to improve agricultural statistics. The GHS-Panel is a nationally representative survey of approximately 5,000 households. The 2010-2011 GHS-Panel is the first round of the survey.
Abstract
The GHS is a cross-sectional survey of 22,000 households throughout the country. The panel component (GHS-Panel) is now being applied to 5,000 households of the GHS and covers multiple agricultural activities. The focus of this panel component is to improve data from the agriculture sector and link this to other facets of household behaviour and characteristics. The GHS-Panel drew heavily on the HNLSS and the NASS to create a new survey instrument and method to shed light on the role of agriculture in households' economic wellbeing. The NBS implemented the first stage (Post Planting) of the first wave of the GHS-Panel in 2010. This panel is a subset of the full GHS (or GHS-Cross Section) that will be finished in 2011.) It is envisaged that the GHS-Panel will be carried out every two years while the GHS-Cross Section will be carried out annually.
The specific outputs and outcomes of the revised GHS with panel component are:
- Development of an innovative model for collecting agricultural data in conjunction with household data;
- Development of a model of inter-institutional collaboration between NBS and the FMA&RD and NFRA, inter alia, to ensure the relevance and use of the new GHS;
- Building the capacity to generate a sustainable system for the production of accurate and timely information on agricultural households in Nigeria.
- Comprehensive analysis of poverty indictors and socio-economic characteristics.
The specific outputs and outcomes of the revised GHS with panel component are:
- Development of an innovative model for collecting agricultural data in conjunction with household data;
- Development of a model of inter-institutional collaboration between NBS and the FMA&RD and NFRA, inter alia, to ensure the relevance and use of the new GHS;
- Building the capacity to generate a sustainable system for the production of accurate and timely information on agricultural households in Nigeria.
- Comprehensive analysis of poverty indictors and socio-economic characteristics.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Households, Individuals, Agricutural plots
Scope
Notes
The survey covers a wide range of socio-economic topics which are highlighted in three different questionnaires used for data collection:
HOUSEHOLD
- Household Identification and Location
- Household Roster / Demographic Characteristics
- Education
- Labour
- Credit and Savings
- Household Assets
- Non-farm Enterprises
- Meals Away from Home
- Household Food Expenditures
- Food Security
- Other Income
AGRICULTURE
- Household Identification and Location
- Plot Roster
- Land Inventory
- Input Costs
- Fertilizer Acquisition
- Seed Acquisition
- Planting Field Crops
- Marketing of Agricultural Surplus
- Animal Holdings
- Animal Costs
- Extension
- Network Roster
COMMUNITY / PRICE
- Community Identification
- Respondent Characteristics
- Food Prices
- Labour
- Land Prices and Credit
HOUSEHOLD
- Household Identification and Location
- Household Roster / Demographic Characteristics
- Education
- Labour
- Credit and Savings
- Household Assets
- Non-farm Enterprises
- Meals Away from Home
- Household Food Expenditures
- Food Security
- Other Income
AGRICULTURE
- Household Identification and Location
- Plot Roster
- Land Inventory
- Input Costs
- Fertilizer Acquisition
- Seed Acquisition
- Planting Field Crops
- Marketing of Agricultural Surplus
- Animal Holdings
- Animal Costs
- Extension
- Network Roster
COMMUNITY / PRICE
- Community Identification
- Respondent Characteristics
- Food Prices
- Labour
- Land Prices and Credit
Topics
| Topic | Vocabulary |
|---|---|
| Agriculture & Rural Development | FAO |
| Infrastructure | FAO |
| Food (production, crisis) | FAO |
Coverage
Geographic Coverage
National, the survey covered all the 36 states and Federal Capital Territory (FCT).
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| National Bureau of Statistics | Federal Republic of Nigeria |
Producers
| Name | Affiliation | Role |
|---|---|---|
| The World Bank | Technical assistance | |
| Federal Ministry of Agriculture and Rural Development | Federal Republic of Nigeria | Technical assistance |
| Federal Ministry of Water Resources | Federal Republic of Nigeria | Technical assistance |
| National Food Reserve Agency | Federal Republic of Nigeria | Technical assistance |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| Federal Government of Nigeria | GovNGA | Funded the study |
Sampling
Sampling Procedure
Sample Design
The GHS-Panel (Post Planting 2010), like all household surveys in the country, is based on the Master Sample Frame, This Frame is based on the 2006 Housing and Population Census conducted by the National Population Commission (NpopC). The census includes approximately 662,000 enumeration areas (EAs) throughout the country. From the census, the Master Frame was constructed at the local government area (LGA). In 668 LGAs, 30 EAs were scientifically selected. The remaining six LGAs are found in FCT, Abuja. Forty EAs were scientifically selected in each of these 6 LGAs. This gives a total of 23,280 EAs selected nationally. This is the Master Frame.
From the Master Frame a master sample frame, called the National Integrated Survey of Households 2007/2012 Master Sample Frame (NISH-MSF) was developed. The NISHMSF was constructed by pooling the LGAs in the Master Frame by state. Thereafter, a systematic sample of 200 EAs was selected with equal probability across all LGAs within the state. Furthermore, the NISH EAs in each state were divided into 20 replicates of 10 EAs each. However, the sample EAs for most national household surveys such as the GHS are based on a sub-sample of the NISH-MSF, selected as a combination of replicates from NISH-MSF frame. For the GHS-Panel, the sample is a subset of the EAs selected for the GHS.
Sample Framework
The sample frame includes all thirty-six (36) states of the federation and Federal Capital Territory (FCT), Abuja. Both urban and rural areas were covered and in all, 500 clusters/EAs were canvassed and 5,000 households were interviewed. These samples were proportionally selected in the states such that different states have different samples.
Sample Selection
The GHS Panel Survey used a two stage stratified sample selection process.
First Stage
The Primary Sampling Units (PSUs) were the Enumeration Areas (EAs). These were selected based on probability proportional to size (PPS) of the total EAs in each state and FCT, Abuja and the total households listed in those EAs.
Second Stage
The second stage involved the systematic selection of ten (10) households per EA. This involved obtaining the total number of households listed in a particular EA, and then calculating a Sampling Interval (S.I) by dividing the total households listed by ten (10). The next step is to generate a random start 'r' from the table of random numbers which stands as the 1st selection. The second selection is obtained by adding the sampling interval to the random start. For each of the next selections, the sampling interval was added to the value of the previous selection until the 10th selection is obtained. Determination of the sample size at the household level was based on the experience gained from previous rounds of the GHS, in which 10 HHs per EA are usually selected and give robust estimates.
The GHS-Panel (Post Planting 2010), like all household surveys in the country, is based on the Master Sample Frame, This Frame is based on the 2006 Housing and Population Census conducted by the National Population Commission (NpopC). The census includes approximately 662,000 enumeration areas (EAs) throughout the country. From the census, the Master Frame was constructed at the local government area (LGA). In 668 LGAs, 30 EAs were scientifically selected. The remaining six LGAs are found in FCT, Abuja. Forty EAs were scientifically selected in each of these 6 LGAs. This gives a total of 23,280 EAs selected nationally. This is the Master Frame.
From the Master Frame a master sample frame, called the National Integrated Survey of Households 2007/2012 Master Sample Frame (NISH-MSF) was developed. The NISHMSF was constructed by pooling the LGAs in the Master Frame by state. Thereafter, a systematic sample of 200 EAs was selected with equal probability across all LGAs within the state. Furthermore, the NISH EAs in each state were divided into 20 replicates of 10 EAs each. However, the sample EAs for most national household surveys such as the GHS are based on a sub-sample of the NISH-MSF, selected as a combination of replicates from NISH-MSF frame. For the GHS-Panel, the sample is a subset of the EAs selected for the GHS.
Sample Framework
The sample frame includes all thirty-six (36) states of the federation and Federal Capital Territory (FCT), Abuja. Both urban and rural areas were covered and in all, 500 clusters/EAs were canvassed and 5,000 households were interviewed. These samples were proportionally selected in the states such that different states have different samples.
Sample Selection
The GHS Panel Survey used a two stage stratified sample selection process.
First Stage
The Primary Sampling Units (PSUs) were the Enumeration Areas (EAs). These were selected based on probability proportional to size (PPS) of the total EAs in each state and FCT, Abuja and the total households listed in those EAs.
Second Stage
The second stage involved the systematic selection of ten (10) households per EA. This involved obtaining the total number of households listed in a particular EA, and then calculating a Sampling Interval (S.I) by dividing the total households listed by ten (10). The next step is to generate a random start 'r' from the table of random numbers which stands as the 1st selection. The second selection is obtained by adding the sampling interval to the random start. For each of the next selections, the sampling interval was added to the value of the previous selection until the 10th selection is obtained. Determination of the sample size at the household level was based on the experience gained from previous rounds of the GHS, in which 10 HHs per EA are usually selected and give robust estimates.
Weighting
When a sample of households is selected for a survey, these households represent the entire population of the country. To accurately use the data sets, the data must be weighted to reflect the distribution of the full population in the country. A population weight was calculated for the panel households. This weight variable (WGHT) has been included in the household dataset: Section A (SECTA). When applied, this weight will raise the sample households and individuals to national values adjusting for population concentrations in various areas.
Data Collection
Dates of Data Collection
| Start | End | Cycle |
|---|---|---|
| 2010-08 | 2010-10 | Post-planting |
| 2011-02 | 2011-04 | Post-harvest |
Data Collection Mode
Face-to-face [f2f]
Data Processing
Data Editing
This survey used concurrent data entry approach. In this method, the fieldwork and data entry were handled by each team assigned to the state. Each team consisted of a field supervisor, 2-4 interviewers and a data entry operator. Immediately after the data were collected in the field by the interviewers and supervisors (the supervisors administered the community questionnaires and collected data on prices), the questionnaires were handed over to the supervisor to be checked and documented. At the end of each day of fieldwork, the questionnaires were then passed to the data entry operator for entry. After the questionnaires were entered, the data entry operator generated an error report which reported issues including out of range values and inconsistencies in the data. The supervisor then checked the report, determined what should be corrected, and decided if the field team needed to revisit the household to obtain additional information. The benefits of this method are that it allows one to:
- Capture errors that might have been overlooked by a visual inspection only,
- Identify errors early during the field work so that if any correction required a revisit to the household, it could be done while the team was still in the EA
The CSPro software was used to design the specialized data entry program that was used for the data entry of the questionnaires.
- Capture errors that might have been overlooked by a visual inspection only,
- Identify errors early during the field work so that if any correction required a revisit to the household, it could be done while the team was still in the EA
The CSPro software was used to design the specialized data entry program that was used for the data entry of the questionnaires.
Other Processing
Data Cleaning
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, as explained above, designed to highlight many of the errors that occurred during the fieldwork. At this stage 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. This problem was 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 households and individuals 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 plot 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.
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, as explained above, designed to highlight many of the errors that occurred during the fieldwork. At this stage 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. This problem was 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 households and individuals 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 plot 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.
Access policy
Contacts
| Name | Affiliation | URL | |
|---|---|---|---|
| LSMS Data Manager | The World Bank | [email protected] | http://go.worldbank.org/QJVDZDKJ60 |
| Information Desk | National Bureau of Statistics | [email protected] | http://www.nigerianstat.gov.ng/index.php/ |
Confidentiality
The users shall not take any action with the purpose of identifying any individual entity (i.e. person, household, enterprise, etc.) in the micro dataset(s). If such a disclosure is made inadvertently, no use will be made of the information, and it will be reported immediately to FAO
Access conditions
Micro datasets disseminated by FAO shall only be allowed for research and statistical purposes. Any user which requests access working for a commercial company will not be granted access to any micro dataset regardless of their specified purpose. Users requesting access to any datasets must agree to the following minimal conditions:
- The micro dataset will only be used for statistical and/or research purposes;
- Any results derived from the micro dataset will be used solely for reporting aggregated information, and not for any specific individual entities or data subjects;
- The users shall not take any action with the purpose of identifying any individual entity (i.e. person, household, enterprise, etc.) in the micro dataset(s). If such a disclosure is made inadvertently, no use will be made of the information, and it will be reported immediately to FAO;
- The micro dataset cannot be re-disseminated by users or shared with anyone other than the individuals that are granted access to the micro dataset by FAO.
- The micro dataset will only be used for statistical and/or research purposes;
- Any results derived from the micro dataset will be used solely for reporting aggregated information, and not for any specific individual entities or data subjects;
- The users shall not take any action with the purpose of identifying any individual entity (i.e. person, household, enterprise, etc.) in the micro dataset(s). If such a disclosure is made inadvertently, no use will be made of the information, and it will be reported immediately to FAO;
- The micro dataset cannot be re-disseminated by users or shared with anyone other than the individuals that are granted access to the micro dataset by FAO.
Citation requirements
Use of the dataset must be acknowledged using a citation which would include:
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
National Bureau of Statistics, Federal Republic of Nigeria. Nigeria General Household Survey (GHS), Panel 2010, Wave 1 Ref. NGA_2010_GHSP-W1_v03_M. Dataset downloaded from [url] on [date].
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
National Bureau of Statistics, Federal Republic of Nigeria. Nigeria General Household Survey (GHS), Panel 2010, Wave 1 Ref. NGA_2010_GHSP-W1_v03_M. Dataset downloaded from [url] on [date].
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
Metadata production
DDI Document ID
DDI_NGA_2010-2011_GHS-W1_v01_EN_M_v01_A_OCS_FAO
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Development Economics Data Group | DECDG | The World Bank | Documentation of the DDI |
| Office of Chief Statistician | OCS | Food and Agriculture Organization | Adoption of metadata for FAM |
DDI Document version
NGA_2010-2011_GHS-W1_v01_EN_M_v01_A_OCS_v01