This survey was done as part of the LSMS-Integrated Surveys on Agriculture project.
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 behavior 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.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
- Agricultural Plots
Data revision includes: Ancillary data
(a) geo data: the revised data files include a set of ancillary geo-data files, in which additional, outside data has been linked based on longitude/latitude of households and plots. In addition, the location of enumeration areas (with an offset) is being made available for users who want to link the GHS panel to other geo-referenced data sources. Details on these files are in the Basic Information Document.
(b) non-standard agricultural conversion factors for agricultural harvest quantities have been included.
Additional data includes:
The survey covers a wide range of socio-economic topics which are highlighted in three different questionnaires used for data collection.
- Household Identification and Location
- Household Roster / Demographic Characteristics
- Credit and Savings
- Household Assets
- Non-farm Enterprises
- Meals Away From Home
- Household Food Expenditures
- Food Security
- Other Income
COMMUNITY / PRICE
- Community Identification
- Respondent Characteristics
- Food Prices
- Land Prices and Credit
National, the survey covered all the 36 states and Federal Capital Territory (FCT).
Producers and sponsors
National Bureau of Statistics
Federal Republic of Nigeria
The World Bank
Federal Ministry of Agriculture and Rural Development
Federal Republic of Nigeria
Federal Ministry of Water Resources
Federal Republic of Nigeria
National Food Reserve Agency
Federal Republic of Nigeria
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.
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.
The GHS Panel Survey used a two stage stratified sample selection process.
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.
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.
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.
Dates of Data Collection
Data Collection Mode
Among the tasks and responsibilities of the supervisors were:
- Examining questionnaires in order to make sure that each interview has been carried out correctly and in full. If reports from data entry require returning to the household, the supervisor must communicate the necessary information that is missing from the questionnaire.
- Visiting some of the households that the interviewers had visited. He/she must repeat some sections of the questionnaire in order to verify that the interviewer recorded that household’s answers correctly
- Observe interviewers during the interview process in order to evaluate the method of asking questions
- Discuss the work with the interviewers and evaluate the work from the data entry reports
- The supervisor is the link between the interviewer and the field management team. Hence, he/she must be informed of any difficulties or problems that the interviewer may encounter. If the interviewer does not understand a procedure, he/she must ask the supervisor for advice.
Data Collection Notes
Fieldwork started on 31st of August, 2010 and was carried out simultaneously throughout the country till mid October, 2010. All three (3) questionnaires; Household, Agriculture and Community were used to collect information on Post-Planting activities. Data were collected by teams comprised of a supervisor, 2-4 interviewer(s) and a data entry operator. The number of team(s) varied from state to state depending on the sample size (number of EAs selected. The teams moved in a roving manner and data collection lasted for between 25 – 35 days.
National Bureau of Statistics
The survey consisted of two household questionnaires and one community questionnaire. The first designated by ‘HOUSEHOLD QUESTIONNAIRE’ was administered to all households in the sample. The second questionnaire ‘AGRICULTURE QUESTIONNAIRE was administered to all households engaged in agriculture activities such as crop farming, livestock rearing and other agricultural and related activities. The third Community Questionnaire was administered to the community to collect information on the socio-economic indicators of the community.
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.
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.
To use the data from the 2010-2011 GHS-Panel Survey, the Nigerian National Bureau of Statistics (NBS) asks that you fill in a Data User Agreement. This agreement allows the NBS to know who is using their data and the types of studies being done by users.
By filling out this form, you not only comply with the agreements reached by all parties in implementing the survey, but also help us to keep you informed about any additional information related to the Nigeria 2010-2011 GHS-Panel Survey.
The form states, among other things, that downloading the data obligates you to cite the source of the data and to send copies of papers to the Nigeria National Bureau of Statistics and the LSMS Division of the World Bank. Once you have submitted the form, you will be sent to a page containing links to the data files. If your browser doesn't support forms (or fails to forward you to the data page upon completing the form), contact LSMS <mailto:email@example.com> and you will receive instructions on how to progress to the page with the data files.
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 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.
DDI Document ID
Development Data Group
The World Bank
Documentation of the DDI
Date of Metadata Production
DDI Document version
Version 01: (March 2012)
Version 02: (November 2013)
The revisions include:
1) Additional data cleaning including checks of the paper questionnaires and consistency checks between the two visits. Labels in the data file have been improved. All the data files have the same naming structure as before.
2) Documentation: the Basic Information Document has been revised with more details on some aspects of the field work, including use of photos for non-standard food quantities.
Two datasets included in the documentation.
Food items photo included in the documentation.