{"doc_desc":{"title":"HOUSEHOLD BUDGET SURVEY 2000-2001","idno":"TZA-NBS-HBS-2000-2001-v01.","producers":[{"name":"NATIONAL BUREAU OF STATISTICS","abbreviation":"NBS","affiliation":"MINISTRY OF STATE PRESIDENTS OFFICE PLANNING AND PRIVATISATION","role":"DATA PRODUCER"},{"name":"Accelerated Data Program","abbreviation":"ADP","affiliation":"PARIS21","role":"Review of the metadata"}],"prod_date":"2010-03-16","version_statement":{"version":"Version 1.0"}},"study_desc":{"title_statement":{"idno":"TZA-NBS-HBS-2000-v01","title":"NATIONAL HOUSEHOLD BUDGET SURVEY 2000-2001","alt_title":"HBS 2000"},"authoring_entity":[{"name":"NATIONAL BUREAU OF STATISTICS","affiliation":"MINISTRY OF STATE PRESIDENT,S OFFICE PLANNING AND PRIVATISATIONM"}],"oth_id":[{"name":"TANZANIA,S POVERTY REDUCTION STRATEGY","affiliation":"REPOA","email":"","role":"TECHNICAL ASSISTANCE"},{"name":"UNIVESITY OF DAR-ES-SALAAM","affiliation":"UDSM","email":"","role":"TECHNICAL ASSISTANCE"},{"name":"WORLD BANK","affiliation":"WB","email":"","role":"TECHNICAL ASSISTANCE"},{"name":"OXFORD POLICY MANAGEMENT","affiliation":"OPM","email":"","role":"TECHNICAL ASSISTANCE"},{"name":"PATRICK WARD,TRUDY OWENS","affiliation":"CFSOAE","email":"","role":"TECHNICAL ASSISTANCE"},{"name":"AHMED MAKBEL","affiliation":"DVI","email":"","role":"TECHNICAL ASSISTANCE"},{"name":"JEFF MWAIJONGA","affiliation":"DVI","email":"","role":"TECHNICAL ASSISTANCE"},{"name":"GOODCHANCE AMINIEL","affiliation":"DVI","email":"","role":"TECHNICAL ASSISTANCE"}],"production_statement":{"producers":[{"name":"MINISTRY OFS TATE PRESIDENT,S OFFICE PLANNING AND PRIVATISATION","affiliation":"","role":"TECHNICAL ASSISTANCE"},{"name":"Arthur Mwakapugi","affiliation":"","role":"TECHNICAL ASSISTANCE"},{"name":"Professor Joseph Semboja","affiliation":"","role":"TECHNICAL ASSISTANCE"},{"name":"Dr.Servacius Likwelile","affiliation":"","role":"TECHNICAL ASSISTANCE"},{"name":"Proffesor H.K.R.Amani","affiliation":"","role":"TECHNICAL ASSISTANCE"},{"name":"Alice Nkhoma-Wamuza","affiliation":"","role":"TECHNICAL ASSISTANCE"},{"name":"Prof,Marjorie Mbilinyi","affiliation":"","role":"TECHNICAL ASSISTANCE"},{"name":"Valerie Leach","affiliation":"","role":"TECHNICAL ASSISTANCE"},{"name":"Arthur van Diesen","affiliation":"","role":"TECHNICAL ASSISTANCE"},{"name":"Proffesor. Beno Ndulu","affiliation":"","role":"TECHNICAL ASSISTANCE"},{"name":"Alana Albee","affiliation":"","role":"TECHNICAL ASSISTANCE"},{"name":"Tomoko Enoki","affiliation":"","role":"TECHNICAL ASSISTANCE"},{"name":"Jackson Biswaro","affiliation":"","role":"TECHNICAL ASSISTANCE"}],"copyright":"@ 2010     NATIONAL BUREAU OF STATISTICS","funding_agencies":[{"name":"SWEDEN INTERNATIONAL DEVELOPEMENT AGENCY","abbreviation":"SIDA","role":"FINANCIAL ASSISTANCE"},{"name":"CANADA INTERNATIONAL DEVELOPEMENT AGENCY","abbreviation":"CIDA","role":"FINANCIAL ASSISTANCE"},{"name":"JAPAN INTERNATIONAL DEVELOPEMENT AGENCY","abbreviation":"JICA","role":"FINANCIAL ASSISTANCE"},{"name":"DANISH INTERNATIONAL DEVELOPEMENT AGENCY","abbreviation":"DANIDA","role":"FINANCIAL ASSISTANCE"},{"name":"United Kingdom Department for International Developement","abbreviation":"(UK DFID)","role":"FINANCIAL ASSISTANCE"},{"name":"United State","abbreviation":"USAID","role":"FINANCIAL ASSISTANCE"},{"name":"United Nation Developement Program","abbreviation":"UNDP","role":"FINANCIAL ASSISTANCE"}]},"distribution_statement":{"contact":[{"name":"Director General","affiliation":"National Bureau of Statistics","email":"dg@nbs.go.tz","uri":"www.nbs.go.tz"}]},"series_statement":{"series_name":"Income\/Expenditure\/Household Survey [hh\/ies]"},"version_statement":{"version":"Version 1.0","version_date":"2002-07-01"},"study_info":{"keywords":[{"keyword":"Economic,condition and indicators","vocab":"CESSDA","uri":"http\/\/www.nesstar.org\/rdf\/common"},{"keyword":"Income\/propety and investiment\/savings","vocab":"CESSDA","uri":"http\/\/www.nesstar.org\/rdf\/common"},{"keyword":"Rural economics\/general health\/housing","vocab":"CESSDA","uri":"http\/\/www.nesstar.org\/rdf\/common"},{"keyword":"Basic skills education","vocab":"CESSDA","uri":"http\/\/www.nesstar.org\/rdf\/common"},{"keyword":"ECONOMICS [1]","vocab":"CESSDA","uri":"http\/\/www.nesstar.org\/rdf\/common"},{"keyword":"housing [10.1]","vocab":"CESSDA","uri":"http\/\/www.nesstar.org\/rdf\/common"},{"keyword":"land use and planning [10.2]","vocab":"CESSDA","uri":"http\/\/www.nesstar.org\/rdf\/common"}],"topics":[{"topic":"ECONOMICS [1]","vocab":"CESSDA","uri":"http:\/\/www.nesstar.org\/rdf\/common"}],"abstract":"This report presents the findings of 2000-2001 Tanzania Household Budget Survey(HBS).It focuses on poverty- monitoring indicators and offers a set of baseline mesurements for the future.Data on key poverty indicators are presented for each region. Trends over the 1990s are also assessed by comparison with the 1991\/92 HBS. \n\nThe HBS collected information on a range of individual and household characteristics. These included;\n\n   *household members, education,economic activities, and health status\n   *household expenditure, consumption and income\n   *ownership of consumer goods and assets\n   *housing structure and materials\n   *household access to services and facilities, and \n   *food security","time_periods":[{"start":"2000-05","end":"2001-06","cycle":""}],"coll_dates":[{"start":"2000-05","end":"2001-06","cycle":""}],"nation":[{"name":"TANZANIA","abbreviation":"TZA"}],"geog_coverage":"NATIONAL COVERAGE","geog_unit":"CLUSTERS","analysis_unit":"Individuals and  households,","universe":"The survey covered all de jure household members","data_kind":"Sample survey data [ssd]","notes":"The Scope of Household Budget Survey is; Identification Particulars, Household Particulars, Household Facilities, Housing Particulars, Distances to Socio-Economic Facilities, Purchase of Durable Items and other Services, Household Assets, Food Security, Annual Household Income, Daily Consumption Expenditure"},"method":{"data_collection":{"data_collectors":[{"name":"NATIONAL BUREAU OF STATISTICS","abbreviation":"NBS","affiliation":"MINISTRY OFSTATE PRESIDENT,S OFFICE PLANNING AND  PRIVATISATION"}],"sampling_procedure":"The sample of households interviewed in the 2000\/2001 HBS was selected in two stage.In the first stage  1,161 small areas called  Primary Sampling Units (PSUs) were selected throughout the  country.In the  second stage.  24  households were initialy selected in each PSU.\n\nThe  sampled households are located in the National Master Sample (NMS) of PSUs. The NMS is a generalised set of area units that can be used as PSUs for conducting various household surveys. It is a fixed sample of rural and urban clusters, which among other things, make possible the  performance of a  continuous survey programme as well as ad hoc sample surveys. the NMS has four modules, A,A+B,A+B+C and A+B+C+D, which can provide urban and rural estimates at National, Zonal, Regional  and District levels respectively.\n\nThe HBS 2000\/01 used Module A+B+C of the NMS comprising 621 urban EAS and 540 rural villages drawn from each of the 20 regions of  Mainland Tanzania. In the second stage,24 households were selected using systematic random sampling(SRS) from stratified lists of  households complied from each of the sampled PSUs. These lists were stratified into high, middle and low socio-economic groups based on socio-economic data collected during the listing exercise. The stratification and selection of households was conducted in the NBS head office and interviewers were supplied with a list of pre-selected households for interview,\n\nRURAL frame.The initial rural NMS frame was based on the 1978 Population Census and later updated with information from the 1988 Population Census.At the beginning, a ward or group of wards was used as Primary Sampling Unit (PSU), but later a village was used insted. The rural frame of the NMS was divided into :normal: large town surroundings; and Low density; strata. In total.150 strata were created and 2 to 8 PSUs (villages) were selected from each stratum to come up with the samp;e of  villages that can provide estimates for each region of  Mainland Tanzania (Module A+B+C).These villages were selected using the probability proportional to size (PPS) selection procedure. The PSUs (villages) for Module A of the rural NMS are automatically included in the regional sample.\n\nURBAN frame: The urban frame for the NMS was the sample used for 1988 Population Census detailed questionnaire. For each district in a region, a list of  the urban EAs was compiled and a specific number of EAs was  selected from this frame using the systematic random  sampling(SRS) procedure to produce the regional urban sample.","sampling_deviation":"The final sample analysed for the 2000\/01 HBS consisted of 22,178 households, a large sample for any household budget survey. Three PSUs were lost entirely from the sample. Households were included in the  analysis if they had at least one record in both the roster and the monthly diary. The weights were calculated for this group of household.\n\nField supervisors were supplied with a list of twelve :replacement: households drawn as a separate sample at the same time as the main household sample, to be used if a sampled household could not be interviewed for the duration of the survey. The 2000\/01 HBS sample had a high level of replacement of households that were not interviewed-around12 per cent.\n\nA total of 4,823 households  were analysed for the 1991\/92 sample. Losses were higher; levels of replacement were lower (Table A1.2). In both surveys, households that were  part of the  initial selectionons constitute around 85 per cent of the  sample analysed.","coll_mode":["Face-to-face [f2f]"],"research_instrument":"The questionnaires contain information related to;Household Particulars, Household Facilities, Household Assets, Household Income, Distance to socio-Economic Facilities, Purchase of Durable items and other Services,Food security;","coll_situation":"The National Bureau of Statistics began preparations for the 2000-2001 Household Badget Survey in late 1999 and training of the fieldworkers took place in March 2000. Fieldwork began in May 2000 for ten regions and in June 2000 for the remaining ten. It lasted for twelve months in each region, with all fieldwork being completed by June2001.The2000\/01 sample was much larger than previous Household Budget Survey in order to provide estimates of key poverty measures fo each of twenty regions of Tanzania mainland.It initially covered 1,161 small geographical areas. these were used as primary sampling units(PSUs).If fully implemented, a total of 27,864 households would have been interviewed. However,it was decided during implementation that a number of rural PSUs would be excluded from second six months of the survey as a cost saving mesure.The anticipated final sample then become 22,584 households. Two household were enumerated each month of the survey in each PSU.Enumerators, resident in or near the PSU. conducted an initial interview with the two households at the beginning of the survey month. They then visited the households during that month on regular basis to record household transactions, covering expenditure, consumption and income. These visits were scheduled to take place every day for households without a literate member and every two to three days for others.Enumerators were supervised by field supervisors working out of the NBS regional offices. Supervisors collected and cheked questionnaires, which were then sent to the head office  for data entry. Data entry, using the data programme IMPS, went parallel with fieldwork and was completed by July2001. Automated data consistency checking procedures were run on the entered data during fieldwork.The field staff were informed of the errors identified by these programmes and ,where possible,a team in the head office corrected them.Additional consistency checks and cleaning continued until November2001 and the analysis was completed by June2002.","act_min":"The National Bureau of Statistics began preparations for the 2000-2001 Household Badget Survey in late 1999 and training of the fieldworkers took place in March 2000. Fieldwork began in May 2000 for ten regions and in June 2000 for the remaining ten. It lasted for twelve months in each region, with all fieldwork being completed by June2001.The2000\/01 sample was much larger than previous Household Budget Survey in order to provide estimates of key poverty measures fo each of twenty regions of Tanzania mainland.It initially covered 1,161 small geographical areas. these were used as primary sampling units(PSUs).If fully implemented, a total of 27,864 households would have been interviewed. However,it was decided during implementation that a number of rural PSUs would be excluded from second six months of the survey as a cost saving mesure.The anticipated final sample then become 22,584 households. Two household were enumerated each month of the survey in each PSU.Enumerators, resident in or near the PSU. conducted an initial interview with the two households at the beginning of the survey month. They then visited the households during that month on regular basis to record household transactions, covering expenditure, consumption and income. These visits were scheduled to take place every day for households without a literate member and every two to three days for others.Enumerators were supervised by field supervisors working out of the NBS regional offices. Supervisors collected and cheked questionnaires, which were then sent to the head office  for data entry. Data entry, using the data programme IMPS, went parallel with fieldwork and was completed by July2001. Automated data consistency checking procedures were run on the entered data during fieldwork.The field staff were informed of the errors identified by these programmes and ,where possible,a team in the head office corrected them.Additional consistency checks and cleaning continued until November2001 and the analysis was completed by June2002.","weight":"DAR-ES-SALAM.First stage sampling weights for Dar-es-salaam are those used for Module A because the PSUs are the same. The EAs from the 1988 Census sample were srtatified into proxy income levels and combined for all districts within the Dar-es-salaam region. They were then selected independently within each level using the SRS procedure. Details on how these weights were calculated are found in ;the National Master Sample (NMS)-Technical Report; (cited above) The formula for calculating the weights is;\n\nWhere;\nWhk= First stage weight for an EA in stratum k of cluster h\nVhJAhk=the proportion of the sample that falls into districts h to the selection interval\n\nNh=number of EAs in district h\n\nnh=number of sampled EAs in district h\nAhk=number of EAs in district h and NMS stratum k\nak=number of sample EAs in NMS stratum k\nWhen the multiple of the selection interval is completely within stratum k of district h, the proportion Vh\/Ahk becomes I.\nOther Urban. For other urban areas,a sample of about 30 EAs was targeted for each region contributed a certain porportion of the 30 EAs.The EAs were then selected independently from each district in the region using the SRS procedure. EAs. representing municipalities and other urban areas in Moduke A of the NMS were automatically included in the regional sample. The formula for calculating the weights for  an EA in district j of region i is given by;\nWhere;\nWij=First stage weight for a selected EA in district j of region i\nTij=total number of urban EAs in district  j of region i\nCij=number of selected urban EAs for the census sample in district j of region i\nSij=number of selected urban EAs for the NMS (Module A+B+C) in district j of region i\n Rural.The rural NMS (Module A+B+C)has been used by a number of previous agricultural surveys. The first stage selection of PSUs was done using the PPS sampling procedure. The formula for the first stage weights is as follows;\n\nWhere;\nWij=first stage weight for a selected village j from stratum i\nni=number of villages selected from stratum i\nPi=1998 population of stratum i\npij=1998 population of village j from stratum i","cleaning_operations":"A number of data consistency cheks were undertaken early in the fieldwork to assess quality and to assist in the development of the data processing system.These identified a large number of problems in the data  coming in from the field, which reflected in part the ambitious size of the survey.The errors identified included consumption unit miscoding,miscoding of transactions, out of range unit prices and problems in the identifier variables. As a consequence, automatic consistency cheking programmes were strengthened and a data editing team was created. where possible,errors were corrected at the data processing centre and the field teams were notified of the problems. This resolved a large number of problems.","method_notes":"Additional cleaning was also carried out at the analysis. The main area in which additional cleaning was required was in the consumption\/expenditure information, particularly in the household diary which consisted of over 5.6 million records.similar cleaning was required in the 1991\/92 data. under-reporting of household size was also identified as problem. On the whole ,there were few other problems in the data by the time it was analysed. there was some evidence of age heaping;- a tendency for individuals to round their reported ages to certain memorable digits(10,15,20,ect)- as is common in most developing country survey; There was also some over-reporting of four year olds. which is likely to be due to interviewers mis-recording ages to avoid completing the extra questions for respondents of five and above,Other data quality issues are  discussed together with the analysis to which they are relevant"},"analysis_info":{"response_rate":"The 2000\/01 HBS inteviewed 98 per cent of the (revised) intended sample size. It did so by relatively frequent use of replacement households, selected from a list provided by the head office. Almost 12 per cent of households included in the final analysis were replacements. The 1991\/92 HBS Suffered higher levels of losses but used smaller proportion of replacements.The use of  replacements is not usually considered good practice in sampling, since it runs the risk of estimates being biased by replacement with non comparable households.However,it was considered necessary because of the large sample size and demanding character of the data collection process.","sampling_error_estimates":"Table A1.4 shows standard errors and confidence intervals around a number of estimates, calculated in STATA. It also presents the results of statistical tests for  a significant difference between the 2000\/01 and 1991\/92 estimates, for the total population and each of  the  three areas. While STATA allows the specification of  sample design in  the calculation of sampling errors, identifying the srata and PSUs used, it is  not possible to specify fully the complexity of the design of the HBS 2000\/01. The standard errors, confidence intervals and tests are therefore approximate."}},"data_access":{"dataset_use":{"conf_dec":[{"txt":"Confidentiality of respodents is guaranteed by section 20 of Tanzania Statistics act number 1 of 2002\nBefore being granted access to the dataset, all users have formally agree:\n1.all identifying information such as the name and address of respondent has been removed; and\n2.the information is disclosed in a manner that is not likely to enable the identification of the \nparticular person or undertaking or business to which it relates.\n3.not attempt to identify any particular person or undertaking or business;\n4.use of information for research or statistically purpose only;\n5.not to disclose the information to any other person, organization\n6.when required by the Director General, return all documents made available to him to the Director General;\n7.comply with the directions given by the Director General relating to the records.\n8.every person involved in the research or statistical project for which information is disclosed pursuant to this section shall make the declaration of secrecy set out in the first schedule.","required":"yes","form_no":"","uri":""}],"contact":[{"name":"NATIONAL BUREAU OF STATISTICS","affiliation":"MINISTRY OF STATE PRESIDENT,S OFFICE PLANNING AND PRIVATISATION","email":"dg@nbs.go.tz","uri":"www.nbs.go.tz"}],"cit_req":"\"NATIONAL BUREAU OF STATISTICS, HOUSEHOLD BUDGET SURVEY 2000-2001(HBS 2000-2001) VERSION 1.0 OF THE PUBLIC USE DATASET(JULY2002) PROVIDED BY NATIONAL BUREAU OF STATISTICS, www.nbs.go.tz\"","conditions":"Tanzania NBS considered three levels of accessibility: \n\n1) Public use files, accessible by all\n2) Licensed datasets, accessible under certain conditions\n3) Datasets only accessible on location, for certain datasets\n\nThe dataset has been anonymized and available as a public use dataset. It accessible to all for statistical and research purposes only, under the following terms and conditions:\n1.The data and other material will not be redistributed or sold to other individuals, institutions, or organization without the written agreement of the National Bureau of Statistics.\n2.The data will be used for statistical and scientific research purposes only. They will be used solely for reporting of aggregated information, and not for investigation of specific individuals or organizations.\n3.No attempt will be made to produce links among dataset provided by the National Bureau of Statistics, or among data from the (National Bureau of Statistics) and other datasets that could identify individuals or organizations\n4.No attempt will be made to re-identify respondents, and no use will be made of the identify of any person or establishment discovered inadvertently. Any such discovery would immediately be reported to the National Bureau of Statistics.\n5.Any books, articles, conference papers, theses, dissertations, reports, or other publications that employ data obtained from the National Bureau of Statistics will cite the source of data in accordance with the Citation Requirement provided with each dataset.","disclaimer":"The user of the data acknowledges that National Bureau of Statistics is the  origional collector of thedata.the authorized distributor of the data.and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences without a written agreement from the National Bureau of statistics."}}},"schematype":"survey"}