General Household Survey, Panel 2012-2013
Nigeria, 2012 - 2013
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Reference ID
NGA_2012-2013_GHS-W2_v01_EN_M_v01_A_OCS
Producer(s)
National Bureau of Statistics (NBS)
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Sep 09, 2020
Last modified
Nov 08, 2022
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Identification
Survey ID Number
NGA_2012-2013_GHS-W2_v01_EN_M_v01_A_OCS
Title
General Household Survey, Panel 2012-2013
Country
| Name | Country code |
|---|---|
| Nigeria | NGA |
Study type
Living Standards Measurement Study [hh/lsms]
Series Information
This General Household Survey-Panel is the second round of Panel surveys, previously conducted in 2011/2012 of a long-term project to collect panel data on households, their characteristics, welfare and their agricultural activities. The survey is the result of a partnership that NBS has established with the Federal Ministry of Agriculture and Rural Development (FMA&RD), the National Food Reserve Agency (NFRA), the Bill and Melinda Gates Foundation (BMGF) and the World Bank (WB). Under this partnership, a method to collect agricultural and household data in such a way as to allow the study of agriculture's role in household welfare over time was developed.
The GHS-Panel is the first panel survey to be carried out by NBS.
The GHS-Panel is the first panel survey to be carried out by NBS.
Abstract
In the past decades, Nigeria has experienced substantial gaps in producing adequate and timely data to inform policy making. In particular, the country is lagging behind in producing sufficient and accurate agricultural production statistics. The current set of household and farm surveys conducted by the NBS covers a wide range of sectors. Except for the Harmonized National Living Standard Survey (HNLSS) which covers multiple topics, these different sectors are usually covered in separate surveys none of which is conducted as a panel. As part of the efforts to continue to improve data collection and usability, the NBS has revised the content of the annual General household survey (GHS) and added a panel component. The GHS-Panel is conducted every 2 years covering multiple sectors with a focus to improve data from the agriculture sector.
The Nigeria General Hosehold Survey-Panel, is the result of a partnership that NBS has established with the Federal Ministry of Agriculture and Rural Development (FMARD), the National Food Reserve Agency (NFRA), the Bill and Melinda Gates Foundation (BMGF) and the World Bank (WB). Under this partnership, a method to collect agricultural and household data in such a way as to allow the study of agriculture's role in household welfare over time was developed. This GHS-Panel Survey responds to the needs of the country, given the dependence of a high percentage of households on agriculture activities in the country, for information on household agricultural activities along with other information on the households like human capital, other economic activities, access to services and resources. The ability to follow the same households over time, makes the GHS-Panel a new and powerful tool for studying and understanding the role of agriculture in household welfare over time as it allows analyses to be made of how households add to their human and physical capital, how education affects earnings and the role of government policies and programs on poverty, inter alia.
The objectives of the survey are as follows
1. Allowing welfare levels to be produced at the state level using small area estimation techniques resulting in state-level poverty figures
2. With the integration of the longitudinal panel survey with GHS, it will be possible to conduct a more comprehensive analysis of poverty indicators and socio-economic characteristics
3. Support the development and implementation of a Computer Assisted Personal Interview (CAPI) application for the paperless collection of GHS
4. Developing an innovative model for collecting agricultural data
5. Capacity building and developing sustainable systems for the production of accurate and timely information on agricultural households in Nigeria.
6. Active dissemination of agriculture statistics
The second wave consists of two visits to the household: the post-planting visit occurred directly after the planting season to collect information on preparation of plots, inputs used, labour used for planting and other issues related to the planting season. The post-harvest visit occurred after the harvest season and collected information on crops harvested, labour used for cultivating and harvest activities, and other issues related to the harvest cycle.
The Nigeria General Hosehold Survey-Panel, is the result of a partnership that NBS has established with the Federal Ministry of Agriculture and Rural Development (FMARD), the National Food Reserve Agency (NFRA), the Bill and Melinda Gates Foundation (BMGF) and the World Bank (WB). Under this partnership, a method to collect agricultural and household data in such a way as to allow the study of agriculture's role in household welfare over time was developed. This GHS-Panel Survey responds to the needs of the country, given the dependence of a high percentage of households on agriculture activities in the country, for information on household agricultural activities along with other information on the households like human capital, other economic activities, access to services and resources. The ability to follow the same households over time, makes the GHS-Panel a new and powerful tool for studying and understanding the role of agriculture in household welfare over time as it allows analyses to be made of how households add to their human and physical capital, how education affects earnings and the role of government policies and programs on poverty, inter alia.
The objectives of the survey are as follows
1. Allowing welfare levels to be produced at the state level using small area estimation techniques resulting in state-level poverty figures
2. With the integration of the longitudinal panel survey with GHS, it will be possible to conduct a more comprehensive analysis of poverty indicators and socio-economic characteristics
3. Support the development and implementation of a Computer Assisted Personal Interview (CAPI) application for the paperless collection of GHS
4. Developing an innovative model for collecting agricultural data
5. Capacity building and developing sustainable systems for the production of accurate and timely information on agricultural households in Nigeria.
6. Active dissemination of agriculture statistics
The second wave consists of two visits to the household: the post-planting visit occurred directly after the planting season to collect information on preparation of plots, inputs used, labour used for planting and other issues related to the planting season. The post-harvest visit occurred after the harvest season and collected information on crops harvested, labour used for cultivating and harvest activities, and other issues related to the harvest cycle.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Households
Scope
Notes
The 2012-13 Nigeria General Household Survey (Panel) covered the following topics:
HOUSEHOLD (Post Planting and Harvest)
- Household identification including geographic area identification information
- Household roster
- Education
- Labor
- Labor option
- Credit and savings
- Financial capability
- Household assets
- Non-farm enterprise and income generating activities
- Meals outside the home
- Food consumption and expenditure
- Non-food expenditure
- Food security
- Other household income
AGRICULTURE (Post Planting and Harvest)
- Household identification including geographic area identification information
- Plot roster
- Land inventory
- Land tenure
- Planting labor
- Input costs
- Fertilizer acquisition
- Seed acquisition
- Planter field crops
- Marketing of agricultural surplus
- Animal Holdings
- Animal costs
- Agriculture by-product
- Extension service
COMMUNITY
- Community identification
- Respondent characteristics
- Food prices
- Labor
- Land prices and credit
HOUSEHOLD (Post Planting and Harvest)
- Household identification including geographic area identification information
- Household roster
- Education
- Labor
- Labor option
- Credit and savings
- Financial capability
- Household assets
- Non-farm enterprise and income generating activities
- Meals outside the home
- Food consumption and expenditure
- Non-food expenditure
- Food security
- Other household income
AGRICULTURE (Post Planting and Harvest)
- Household identification including geographic area identification information
- Plot roster
- Land inventory
- Land tenure
- Planting labor
- Input costs
- Fertilizer acquisition
- Seed acquisition
- Planter field crops
- Marketing of agricultural surplus
- Animal Holdings
- Animal costs
- Agriculture by-product
- Extension service
COMMUNITY
- Community identification
- Respondent characteristics
- Food prices
- Labor
- Land prices and credit
Topics
| Topic | Vocabulary | URI |
|---|---|---|
| consumption/consumer behaviour [1.1] | CESSDA | Link |
| economic conditions and indicators [1.2] | CESSDA | Link |
| income, property and investment/saving [1.5] | CESSDA | Link |
| agricultural, forestry and rural industry [2.1] | CESSDA | Link |
| business/industrial management and organisation [2.2] | CESSDA | Link |
| working conditions [3.6] | CESSDA | Link |
| domestic political issues [4.2] | CESSDA | Link |
| specific diseases and medical conditions [8.9] | CESSDA | Link |
| plant and animal distribution [9.4] | CESSDA | Link |
| land use and planning [10.2] | CESSDA | Link |
| specific social services: use and provision [15.3] | CESSDA | Link |
Coverage
Geographic Coverage
National Coverage
Universe
Agricultural farming household members.
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| National Bureau of Statistics (NBS) | Federal Government of Nigeria (FGN) |
Producers
| Name | Affiliation | Role |
|---|---|---|
| Federal Ministry of Agriculture and Rural Development | Federal Governent of Nigerian (FGN) | Technical Assistance |
| National Food Reserve Agency | Federal Governent of Nigerian (FGN) | Technical Assistance |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| Federal Government of Nigeria | FGN | Funding |
| The World Bank | WB | Funding |
| Bill and Melinda Gates Foundation | BMGF | Funding |
Other Identifications/Acknowledgments
| Name | Affiliation | Role |
|---|---|---|
| Federal Ministry of Water Resources | FMWR | Technical Assistance |
| Federal Department of Agricultural Extension | FDAE | Technical Assistance |
Sampling
Sampling Procedure
The sample is designed to be representative at the national level as well as at the zonal (urban and rural) levels. The sample size of the GHS-Panel (unlike the full GHS) is not adequate for state-level estimates.
The sample is a two-stage probability sample:
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. A total of 500 EAs were selected using this method.
Second Stage:
The second stage was the selection of households. Households were selected randomly using 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 was to generate a random start 'r' from the table of random numbers which stands as the 1st selection. Consecutive selection of households was obtained by adding the sampling interval to the random start.
Determination of the sample size at the household level was based on the experience gained from previous rounds of the GHS, in which 10 households per EA are usually selected and give robust estimates.
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 had different samples sizes depending on the total number of EAs in each state.
Households were not selected using replacement. Thus the final number of household interviewed was slightly less than the 5,000 eligible for interviewing. The final number of households interviewed was 4,986 for a non-response rate of 0.3 percent. A total of 27,533 household members were interviewed. In the second, or Post-Harvest Visit, some household had moved as had individuals, thus the final number of households with data in both points of time (post planting and post harvest) is 4,851, with 27,993 household members.
The sample is a two-stage probability sample:
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. A total of 500 EAs were selected using this method.
Second Stage:
The second stage was the selection of households. Households were selected randomly using 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 was to generate a random start 'r' from the table of random numbers which stands as the 1st selection. Consecutive selection of households was obtained by adding the sampling interval to the random start.
Determination of the sample size at the household level was based on the experience gained from previous rounds of the GHS, in which 10 households per EA are usually selected and give robust estimates.
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 had different samples sizes depending on the total number of EAs in each state.
Households were not selected using replacement. Thus the final number of household interviewed was slightly less than the 5,000 eligible for interviewing. The final number of households interviewed was 4,986 for a non-response rate of 0.3 percent. A total of 27,533 household members were interviewed. In the second, or Post-Harvest Visit, some household had moved as had individuals, thus the final number of households with data in both points of time (post planting and post harvest) is 4,851, with 27,993 household members.
Response Rate
The response rate was very high. Response rate after field work was calculated to be 93.9% while attrition rate was 6.1% for households. During the tracking period, 52.4% of the attrition was tracked while at the end of the whole exercise, the response rate was: Post Harvest: 97.1%
Weighting
A population weight was calculated for the panel households. This weight variable (wght) has been included in the household dataset: Section A (secta_plantingw1 for post-planting and secta_harvestw1 for post-harvest). 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 |
|---|---|---|
| 2012-09 | 2012-11 | Post- Planting |
| 2013-02 | 2013-04 | Post- Harvest |
Data Collection Mode
Face-to-face paper [f2f]
Data Processing
Data Editing
Data Entry
This survey used a 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, 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.
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. 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 data sets 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.
This survey used a 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, 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.
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. 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 data sets 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.
Data Appraisal
Estimates of Sampling Error
No sampling error
Access policy
Contacts
| Name | Affiliation | URL | |
|---|---|---|---|
| Statistician General | National Bureau of Statistics | [email protected] | Link |
| Director of ICT | National Bureau of Statistics | [email protected] | Link |
| Deputy-Director: Household Statistics Division | National Bureau of Statistics | [email protected] | Link |
| Consultant | World Bank | [email protected] | Link |
| Head: Data Management Division | National Bureau of Statistics | [email protected] | Link |
| Head: Systems Programming | National Bureau of Statistics | [email protected] | Link |
| Data Archivist | National Bureau of Statistics | [email protected] | Link |
| National Bureau of Statistics | National Bureau of Statistics | [email protected] | Link |
| LSMS Data Manager | The World Bank | [email protected] | Link |
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 2007 outlines the data access obligation of data producers which includes the release of properly anonymized micro data.
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
Example:
Nigeria National Bureau of Statistics (NBS). Nigeria General Household Survey, Panel 2012-2013, Wave 2. Ref. NGA_2012_GHSP-W2_v02_M. Dataset downloaded from http://go.worldbank.org/BY4SLL0380 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
Example:
Nigeria National Bureau of Statistics (NBS). Nigeria General Household Survey, Panel 2012-2013, Wave 2. Ref. NGA_2012_GHSP-W2_v02_M. Dataset downloaded from http://go.worldbank.org/BY4SLL0380 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_2012-2013_GHS-W2_v01_EN_M_v01_A_OCS_FAO
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Office of Chief Statistician | OCS | Food and Agriculture Organization | Metadata adapted for FAM |
| National Bureau of Statistics | NBS | Federal Government of Nigeria | Metadata Producer |
| World Bank, Development Data Group | DECDG | The World Bank | Reviewed the metadata |
DDI Document version
NGA_2012-2013_GHS-W2_v01_EN_M_v01_A_OCS_v01