{"doc_desc":{"title":"National  Agricultural Sample Census Pilot (Private Farmer)-Fishery-2007","idno":"DDI-NGA-NBS-NASCPILOT-FISH-2007-v1.0","producers":[{"name":"National Bureau of Statistics","abbr":"NBS","affiliation":"FGN","role":"Data Producer"}],"prod_date":"2009-10-20","version_statement":{"version":"Version 1.0(October, 2009)"}},"study_desc":{"title_statement":{"idno":"NGA-NBS-NASCPILOT-FISH-2007-v1.0","title":"National  Agricultural Sample Census Pilot (Private Farmer) Fishery-2007","sub_title":"Fourth round","alternate_title":"NASCPILOT-Fish-2007","translated_title":"No translation"},"authoring_entity":[{"name":"National Bureau of Statistics","affiliation":"Federal Government of Nigeria"}],"oth_id":[{"name":"Department of Agriculture","affiliation":"Nigerian Universities","email":"","role":"Technical support"},{"name":"Farmers Associations","affiliation":"Nigerian Farmers","email":"","role":"Technical support"}],"production_statement":{"producers":[{"name":"Federal Ministry of Agriculture and Rural Development (FMA&RD)","abbr":"FMA&WR","affiliation":"FGN","role":"Collaboration"}],"copyright":"\u00a9 NBS 2009","prod_date":"2006-07-20","funding_agencies":[{"name":"Federal Government of Nigeria","abbr":"FGN","role":"Funding"},{"name":"European Union","abbr":"EU","role":"Funding"},{"name":"Food And Agricultural Organisation","abbr":"FAO","role":"Funding"},{"name":"United Nations Development Programe","abbr":"UNDP","role":"Funding"},{"name":"United State Department of Authority","abbr":"USDA","role":"Funding"},{"name":"United Nation","abbr":"UNICEF","role":"Funding"},{"name":"World Bank","abbr":"WB","role":"Funding"}]},"distribution_statement":{"distributors":[{"name":"National Bureau of Statistics","abbr":"NBS","affiliation":"FGN","uri":""}],"contact":[{"name":"Dr V.O. Akinyosoye","affiliation":"Statistician General","email":"voakinyosoye@nigerianstat.gov.ng","uri":"http:\/\/www.nigerianstat.gov.ng"},{"name":"Dr G.O Adewoye","affiliation":"Director Real Sector and Household Statistics Department","email":"goadewoye@nigerianstat.gov.ng","uri":"http:\/\/www.nigerianstat.gov.ng"},{"name":"Mr E.O. Ekezie","affiliation":"Head of  Information and Comnucation Technology Department","email":"eekezie@nigerianstat.gov.ng","uri":"http:\/\/www.nigerianstat.gov.ng"},{"name":"Mr E .I. Fafunmi","affiliation":"Data Curator","email":"biyifafunmi@nigerianstat.gov.ng","uri":"http:\/\/www.nigerianstat.gov.ng"},{"name":"Mr R.F. Busari","affiliation":"Head (Systems Programming)","email":"rfbusari@nigerianstat.gov.ng","uri":"http:\/\/www.nigerianstat.gov.ng"},{"name":"Mrs A.A.Akinsanya","affiliation":"Data Archivist","email":"paakinsanya@nigerianstat.gov.ng","uri":"http:\/\/www.nigerianstat.gov.ng"},{"name":"National Bureau of Statistics","affiliation":"Fedral Government of Nigeria (FGN)","email":"feedback@nigerianstat.gov.ng","uri":"http:\/\/www.nigerianstat.gov.ng"}]},"series_statement":{"series_name":"Agricultural Census [ag\/census]","series_info":"This is a pilot study on the Fish production aspect of NASC 2007\nNigeria conducted the last round of the Agricultural Census in 1993\/94. Since 1993\/94 the Agricultural data situation in Nigeria has slid backward and can best be described as weak. There was lack of inter-censual surveys to update the census, hence the need to address the weak agricultural situation in the country.  \n\n There is a strong need to collect current base-line data on the structure and character of agriculture in Nigeria and to disaggregate agricultural data to address planning on the various Governments reform agenda on agriculture, poverty and food security.\n\nThe NASC will address the weakness in Agricultural Statistics production in Nigeria. National Agricultural Sample Census (NASC) will also cover the 36 States including the FCT Abuja and the 774 LGAs."},"version_statement":{"version":"Version 1.0(October, 2009)","version_date":"2009-10-20","version_notes":"Version 1.0: Data used to generate the tables and the report (June, 2009)\n                      Further editing on the data set  released for public use(October, 2009)"},"study_info":{"topics":[{"topic":"consumption\/consumer behaviour [1.1]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"rural economics [1.6]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"agricultural, forestry and rural industry [2.1]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"business\/industrial management and organisation [2.2]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"employment [3.1]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"working conditions [3.6]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"basic skills education [6.1]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"vocational education [6.7]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"plant and animal distribution [9.4]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"environmental degradation\/pollution and protection [9.1]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"TRANSPORT, TRAVEL AND MOBILITY [11]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"gender and gender roles [12.6]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"land use and planning [10.2]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"community, urban and rural life [13.1]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"},{"topic":"information technology [16.2]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"}],"abstract":"The programme for the World Census of Agriculture 2000 is the eighth in the series for promoting a global approach to agricultural census taking.  The first and second programmes were sponsored by the International Institute for Agriculture (IITA) in 1930 and 1940.  Subsequent ones up to 1990 were promoted by (FAO).  Food and Agriculture Organization of the United Nations recommends that each country should conduct at least one agricultural census in each census programme decade and its programme for the World Census of Agriculture 2000 for instance corresponds to Agricultural Census to be undertaken during the decade 1996 to 2005.  Many countries do not have sufficient resources for conducting an agricultural census.  It therefore became an acceptable practice since 1960 to conduct agricultural census on sample basis for those countries lacking the resources required for a complete enumeration. \n\n In Nigeria's case, a combination of complete enumeration and sample enumeration is adopted whereby the rural (peasant) holdings are covered on sample basis while the modern holdings are covered on complete enumeration.  The project named \u201cNational Agricultural Sample Census\u201d derives from this practice.  Nigeria through the National Agricultural Sample Census (NASC) participated in the 1970's, 1980's, 1990's programmes of the World Census of Agriculture.  Nigeria failed to conduct the Agricultural Census in 2003\/2004 because of lack of funding.   The NBS regular annual agriculture surveys since 1996 had been epileptic and many years of backlog of data set are still unprocessed.  The baseline agricultural data is yet to be updated while the annual regular surveys suffered set back.  There is an urgent need by the Governments (Federal, State, LGA), sector agencies, FAO and other International Organizations to come together to undertake the agricultural census exercise which is long overdue.  The conduct of 2006\/2008 National Agricultural Sample Census Survey is now on course with the pilot exercise carried out in the third quarter of 2007. \n\nThe National Agricultural Sample Census (NASC) 2006\/08 is imperative to the strengthening of the weak agricultural data in Nigeria.  The project is phased into three sub-projects for ease of implementation; the Pilot Survey, Modern Agricultural Holding and the Main Census.  It commenced in the third quarter of 2006 and to terminate in the first quarter of 2008.  The pilot survey was implemented collaboratively by National Bureau of Statistics.\n\nThe main objective of the Pilot Survey was to test the adequacy of the survey instruments, equipments and administration of questionnaires, data processing arrangement and report writing.  The Pilot survey conducted in July 2007 covered the two NBS survey system-the National Integrated Survey of Households (NISH) and National Integrated Survey of Establishment (NISE).  The survey instruments were designed to be applied using the  two survey systems while the use of Geographic Positioning System (GPS) was introduced as additional new tool for implementing the project.\n\nThe Stakeholders workshop held at Kaduna on 21st-23rd May 2007 was one of the initial bench marks for the take off of the Pilot Survey.  The Pilot Survey implementation started with the first level training (Training of Trainers) at the NBS Headquarters between 13th - 15th June 2007.  The second level training for all levels of field personnels was implemented at Headquarters of the twelve (12) concerned states between 2nd - 6th July 2007.  The field work of the Pilot Survey commenced on the 9th July and ended on the 13th of July 07.  The IMPS and SPSS were the statistical packages used to develop the data entry programme.","time_periods":[{"start":"2007-07-09","end":"2007-07-13","cycle":"5 days"}],"coll_dates":[{"start":"2007-07-09","end":"2007-07-13","cycle":"5 days"}],"nation":[{"name":"Nigeria","abbreviation":"NGA"}],"geog_coverage":"State","analysis_unit":"Household based of fish farmers","universe":"The survey covered all de jure household members (usual residents),  who were into Fish.production","data_kind":"Census\/enumeration data [cen]","notes":"The scope covered in this pilot exercise included \n\n     -    Type of fishing activity\n     -    Fish Production and sales\n     -    Fishing input by type\n     -    Employment by gender\n     -    Sources of Funds\n     -     Pond capacity\n     -     Preservation methods"},"method":{"data_collection":{"data_collectors":[{"name":"National Bureau of Statistics","abbr":"NBS","role":"","affiliation":"Federal Government of Nigeria(FGN)"}],"sampling_procedure":"12 states  were purposely selected in the country.\n 2 states from each of the 6 geo-political zones. \n 2 LGAs per selected state were studied.\n 2  Rural EAs per LGA were  covered and \n 3 Fishing farming Housing Units were systematically selected and canvassed .\nHowever, more fishing farming housing units were over sampled in the six (6) reported States","sampling_deviation":"There was deviations from the original sample design","coll_mode":["Face-to-face [f2f]"],"research_instrument":"The NASC fishery questionnaire was divided into sections:\n\n* Holding identification:   This is to identify the holder through HU serial number, HH serial number, and demographic characteristics. \n* Type of fishing sites used by holder. \n* Sources and quantities of fishing inputs. \n* Quantity of aquatic production by type.\n* Quantity sold and value of sale of aquatic products.\n* Funds committed to fishing by source and others","sources":[{"name":"","origin":"","characteristics":""}],"coll_situation":"Four Enumeration areas were canvassed in each state for data collection. \n\nThe period of data collection was for five days by four teams made of two enumerators and one supervisor per team. Eight enumerators and four supervisors will do the work in each state selected. Data to be canvassed are household data namely listing, holding questionnaires, (crop, livestock\/poultry and fisheries). \n\nA team made up of two enumerators and one supervisor was responsible for data collection. The duration of data collection was five days.","act_min":"The headquarters staff  and state officer accompanied one team per day to supervise both the interviewers and supervisors on daily basis.  Apart from the daily supervision by the headquarters staff and state officer, they also skim checked all the completed questionnaires. \nThe zonal controllers also monitored the field work in their respective zones.\n\nTwo officers were trained in the state. The training was scheduled to last for five days. The Coordinators and Consultants also participated in the training.\n\nAfter the training one officer was retained to carry out spot\/skim check of records while the other officers returned to Headquarters. Those responsible to do this assignment were staff of NBS and FMA&WR .\n\nThe monitoring and quality check exercise was to last for five days also. Coordinators and Consultants fro the Headquarters participated in  the monitoring and quality checks work","weight":"The formula adopted in calculating the design weights for the survey data (sample results) were as follows:\n\n(i)\tThe probability of selecting an EA within a state was obtained by dividing the total number of EAs sampled in a             \n                 state by total number of EAs in that particular state. Let this be represented by fj. That is,\n                  fj      = \t(Total Number of EAs sampled in a state)\/(Total Number of EAs in that particular State) \n\n(ii)\tLikewise, the probability of selecting an housing unit (HU) within an EA was obtained by dividing the total number                \n               of housing units selected in an EA  by the total number of housing units (HUs) listed in that particular EA. Let this be \n               represented by fk. That is,\n               fk     = \t(Total Number of HUs selected in an EA)\/(Total Number of HUs listed in that particular EA)\n               \nThen the product (fj) x (fk) represented by f is the sampling fraction for each of the corresponding study unit (Enumeration Area) for all the 48EAs canvassed throughout the 12 states of the Federation. The inverse of the sampling fraction is known as the design weight and was applied accordingly to all the study units.\n\nMathematically,\nDesign weight =    ((Total number of EAs in a state)\/(Total number of EAs sampled in that particular state))\tX ((Total Number of HUs listed in an EA)\/(Total Number of HUs selected in that particular EA))\n\nThe above value was obtained for each of the 48EAs canvassed throughout the 36 states of the Federation. Thereafter, adjustment factors were applied to adjust for the non-responses.","cleaning_operations":"The data processing and analysis plan involved five main stages: training of data processing staff; manual editing and coding; development of data entry programme; data entry and editing and tabulation. Census and Surveys Processing System (CSPro) software were used for data entry, Statistical Package for Social Sciences (SPSS) and Census and Surveys Processing System (CSPro) for editing and a combination of SPSS, Statistical Analysis Software (SAS) and EXCEL for table generation.   The subject-matter specialists and computer personnel from the NBS and CBN implemented the data processing work.  Tabulation Plans were equally developed by these officers for their areas and topics covered in the three-survey system used for the exercise.\nThe data editing is in 2 phases namely manual editing before the data entry were done. 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 enterd data.\nThe completed questionnaires were collated and edited manually\n(a)  Office editing and coding were done by the editor using visual control of the questionnaire before data entry\n(b)  Cspro was used to design the data entry template provided as external resource\n(c)  Ten operator plus two suppervissor and two progammer were used\n(d)  Ten machines were used for data entry \n(e)  After data entry data entry supervisor runs fequency on each section to see that all the questionnaire were enterd"},"method_notes":"Data were processed in clusters, with each cluster being processed as a complete unit through each stage of data processing.  Each cluster goes through the following steps:\nData entry was done at the HQ since it was a pilot.\n\n1) Questionnaire reception\n2) Office editing and coding\n3) Data entry\n4) Structure and completeness checking\n5) Verification entry\n6) Comparison of verification data\n7) Back up of raw data\n8) Secondary editing\n9) Edited data back up\nAfter all clusters are processed, all data is concatenated together and then the following steps are completed for all data files:\n10) Export to SPSS in 4 files \n11) Recoding of variables needed for analysis\n12) Adding of sample weights\n13) Structural checking of SPSS files\n16) Production of analysis tabulations","analysis_info":{"response_rate":"Both Enumeration Area (EA) and Fish holders' level  Response Rate was 100 per cent.","sampling_error_estimates":"No computation of sampling error","data_appraisal":"The Quality Control measures were carried out during the survey, essentially to ensure quality of data"}},"data_access":{"dataset_use":{"conf_dec":[{"txt":"The confidentiality of the individual respondent is protected by law (Statistical Act 2007)\nThis 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.","required":"yes","form_no":"","form_uri":""}],"contact":[{"name":"National Bureau of Statistics","affiliation":"FGN","email":"feedback@nigerianstat.gov.ng","uri":"http:\/\/www.nigerianstat.gov.ng"}],"cit_req":"National Bureau of Statistics, Nigeria, National  Agricultural Sample Cencuse Pilot (Private Farmer) Fisheries 2007-v1.0","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.","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."}}},"schematype":"survey"}