Private farmer-Crop-2006
Third edition
Nigeria, 2007
Identification
NGA-NBS-CROP-2006-v1.0
Private farmer-Crop-2006
Third edition
NBS-CROP-2006
No translation
| Name | Country code |
|---|---|
| Nigeria | NGA |
Agricultural Survey [ag/oth]
This Private farmer-Crop is the 3rd in the series of Collaborative effort of the National Bureau of Statistics (NBS), Central Bank of Nigeria (CBN) and the Nigeria Communications Commission previously conducted in 2004, 2005 and 2006 being the current one. However the Private farmer-Crop is a regular survey of the National Bureau of Statistics conducted on quarterly basis before the collaboration was initiated.
The Private farmer-Crop 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 the collaboration incorporated Nigerian Communications commission (NCC). The main reason of for conducting the survey was to enable the collaborating agencies fulfil their mandate in the production of current and credible statistics, to monitor and evaluate the status of the economy and the various government programmes such as the National Economic Empowerment and Development Strategy (NEEDS) and the Millennium Development Goals (MDGs).
The collaborative survey also assured the elimination of conflicts in data generated by the different agencies and ensured a reliable, authentic national statistics for the country.
Sample survey data [ssd]
Household based of crop farmers
Version
version 1.0
2008-09-05
Scope
National Integrated Survey of Households (NISH) The scope covered under the National Integrated Survey of Households include topics and subjects like: Household Composition; Household Amenities, Health, Education, Employment, Female Contraceptive Prevalence, Births and Deaths in last 12 months, Child Immunization and Child Malnutrition, Ownership and Access to Information and Communication Technology (ICT), Voluntary or social work (Non-profit Institutions), operation of ICT business outfit, Housing project, Crop Production, Livestock Production, Poultry Keeping, Farming Inputs and Processing and Storage Facilities. (ii) National Integrated Survey of Establishments (NISE)
Holding identification
Section I Holding Characteristics
Section II Access to Land
Section III Access to Credit and Funds Used
Section IV Sources of inputs/equipment
Section V(a) Production input utilization; quantity and cost
Section V(b) Production input utilization; quantity and cost
Section V(c) Input utilization; quantity and cost
Section VI: Other Farm Expenditures
Section VII Persons engaged in crop farming
Section VII Wages of persons engaged in crop farming
Section VIII Area and Production
Section IX Consumption from own production
Section X Sales from own production (farmgate)
Section XI Sales from own production (open market)
Section XII Record what you set aside (as seedling, gift, etc) from own production
Section XIII Post harvest losses
Section XIV Which of the following own processing facilities do you use in your farm
Section XV Own storage facilities
Section XVI Market Channel
Section XVII Export Channel
Section XVIII Forestry
Section XIX Impressionistic Questions
| Topic | Vocabulary | URI |
|---|---|---|
| consumption/consumer behaviour [1.1] | 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 |
| working conditions [3.6] | CESSDA | http://www.nesstar.org/rdf/common |
| basic skills education [6.1] | CESSDA | http://www.nesstar.org/rdf/common |
| vocational education [6.7] | CESSDA | http://www.nesstar.org/rdf/common |
| environmental degradation/pollution and protection [9.1] | CESSDA | http://www.nesstar.org/rdf/common |
| plant and animal distribution [9.4] | CESSDA | http://www.nesstar.org/rdf/common |
| land use and planning [10.2] | CESSDA | http://www.nesstar.org/rdf/common |
| TRANSPORT, TRAVEL AND MOBILITY [11] | CESSDA | http://www.nesstar.org/rdf/common |
| children [12.1] | CESSDA | http://www.nesstar.org/rdf/common |
| elderly [12.2] | CESSDA | http://www.nesstar.org/rdf/common |
| gender and gender roles [12.6] | 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 |
| information technology [16.2] | CESSDA | http://www.nesstar.org/rdf/common |
Coverage
National Zone State
Crop Farming Household
Producers and sponsors
| Name | Affiliation |
|---|---|
| National Bureau of Statistics (NBS) | Fedral Government of Nigeria (FGN) |
| Name | Affiliation | Role |
|---|---|---|
| Central Bank of Nigeria | Fedral Government of Nigeria (FGN) | collaboration |
| Nigerian Commnications Commision | Fedral Government of Nigeria (FGN) | collaboration |
| Name | Abbreviation | Role |
|---|---|---|
| National Bureau of Statistics | NBS | Funding |
| Central Bank of Nigeria | CBN | Funding |
Sampling
National Agricultural Sample Survey design derived from NBS 2005/07 NISH sample design. The 2005/07 NISH
sample design is a 2-stage, replicated and rotated cluster sample design with Enumeration Areas (E.As) as first stage sampling units or Primary Sampling Units (PSUs) while Housing Units constituted the second stage units (secondary sampling units).
The housing units were the Ultimate Sampling Units for the multi-subject survey.
Generally, the NISH Master Sample in each state is made up of 120 EAs drawn in 12 replicates. A replicate consists of 10 E.As. Subsets of the Master Sample are studied for modules of the NISH.
Six (6) replicates were studied for private farmers in each state and three (3) replicates for Abuja (FCT).
Total sample sizes of 32,850 Farming Housing Units (FHUs) were drawn from 2,190 EAs. In each state, 900 FHUs drawn from 60 EAs were studied. Four hundred and fifty (450) FHUs from 30 EAs were studied in (FCT), Abuja. The listings of housing units in the selected EAs were updated before they were stratified into farming and non-farming housing units. The farming housing units were further stratified into Crop Farming Housing Units (CFHU), Livestock Farming Housing Units (LFHU) and Fishing Farming Housing Units (FFHUs). In each EA, 5 FHUs were studied for crop farming, 5 FHUs were covered for livestock and 5 FHUs for fishery. At each level of selection, housing units were systematically selected using different random start.
Table 1.2 reflects the stratification procedure prior to selection within each sub-population.
All households in the HUs that qualified as farming households were served with relevant private farmers questionnaires.
Out of the expected 2,190 EAs, 1,963 were studied.
A total of 11, 075 holders were canvassed from 10,950 crop farming housing units because there were more than one (1) holder in some crop farming housing units
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).
The response rate at EA level was 89.64 percent
The variable (rf ) raising factor 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)
Then the product (fj) x (fk) represented by f is the sampling fraction for each of the corresponding study unit (Enumeration Area) for all the 1,920EAs canvassed throughout the 36 states of the Federation and FCT, Abuja. The inverse of the sampling fraction is known as the design weight and was applied accordingly to all the study units.
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))
The above value was obtained for each of the 2,190EAs canvassed throughout the 36 states of the Federation and FCT, Abuja. Thereafter, adjustment factors were applied to adjust for the non-responses.
Survey instrument
The questionnaire for the crop 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
DATA PROCESSING/ANALYSIS The data processing analysis involved six main stages: development of data entry program; training of data processing staff; manual editing and coding; data entry and scanning; computer editing, verification and conversion and table generation. Integrated Microcomputer Processing Systems (IMPS) was one of the specialized Statistical packages used to develop the data entry program. The Disk Operating System (DOS) version of the software can support multiple screens required to capture data from the various survey instruments. With the introduction of scannable questionnaires for General Household and Modern Agricultural Holding, another new software package called Teleform was used. The indicators on household surveys were obtained using the Statistical Package for Social Scientists (SPSS) while the indicators on establishment surveys were obtained using MS-ACCESS and MS-EXCEL. Others indicators on Prices, Trade, National Accounts and Agricultural Survey made use of MS-Office (Access and Excel). The tabulation and analysis of the three survey systems were implemented by diligent and capable staff of the collaborative agencies.
Data collection
| Start | End | Cycle |
|---|---|---|
| 2007-03-03 | 2007-03-26 | 23 days |
| Start date | End date | Cycle |
|---|---|---|
| 2007-03-03 | 2007-03-26 | 23 days |
- Face-to-face [f2f]
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
Retrieval of records was carried out in two stages. The first stage retrieval was implemented by CBN Headquarter Staff during the monitoring visit to the states and zones. The second retrieval was done during the monitoring visit of NBS Headquarter 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 sent to NBS headquarters.
Table 1.7 depicted the retrieval position of Private farmers survey.
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. The crop production Survey a household based exercise, in each state of the federation 3 teams were used comprising of 3 supervisors and 12 enumerators. A team was made up of one Supervisor and four Enumerators. Each team covered 20 Enumeration Areas (EA) for a period of 22 days. A pair of enumerators in a team covered 10 EAs.
Data processing
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.
Data appraisal
The population of the country is Large and due to limited fund, census enumeration of crop farmers is not visible. To reduce Sampling Error selecting of crop farmers was based on State of the Federation.
QUALITY CONTROL AND RETRIEVAL OF RECORD
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 Headquarter 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.
Data Access
| Name | Affiliation | URL | |
|---|---|---|---|
| National Bureau of Statistics (NBS) | Fedral Government of Nigeria (FGN) | http://www.nigerianstat.gov.ng | feedback@nigerianstat.gov.ng |
| Is signing of a confidentiality declaration required? | Confidentiality declaration text |
|---|---|
| yes | 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. |
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.
National Bureau of Statistics, Nigeria, Private farmer-Crop Survey (NGA) 2006-v.1.0
Disclaimer and copyrights
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.
(c) 2007, NBS
Contacts
| Name | Affiliation | URL | |
|---|---|---|---|
| G.O Adewoye | Director Census & Surveys | goadewoye@nigerianstat.gov.ng | http://www.nigerianstat.gov.ng |
| A.N.Adewimbi | Head of Information and Comnucation Technology Department | taadewnmbi@nigerianstat.gov.ng | http://www.nigerianstat.gov.ng |
| Biyi Fafumi | Data Curator | biyifafunmi@nigerianstat.gov.ng | http://www.nigerianstat.gov.ng |
| Mr R.F. Busari | ICT | rfbusari@nigerianstat.gov.ng | http://www.nigerianstat.gov.ng |
| A.A.Akinsanya | Data Archivist | paakinsanya@nigerianstat.gov.ng | http://www.nigerianstat.gov.ng |
| National Bureau of Statistics (NBS) | Fedral Government of Nigeria (FGN) | feedback@nigerianstat.gov.ng | http://www.nigerianstat.gov.ng |
Metadata production
DDI-NGA-NBS-CROP-2006-v1.0
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| National Bureau of Statistics | NBS | FGN | Data Producer |
2008-09-03
Metadata version
Version 1.0