Card, David, and DellaVigna, Stefano, (2020) "What Do Editors Maximize? Evidence from Four Economics Journals." Review of Economics and Statistics 102:1, 195-217.

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Abstract

Tourism statistics traditionally represent an important field of official statistics, since they contribute significantly to the economic and market analysis of the tourism sector in Palestine.

Palestine attracts many tourists who come to tour its highly valued religious and historical sites. The household sample survey conducted from 24 March 2015 to 31 May 2015. Tourism is a key to many countries economy thanks to its significant contribution to GDP. For this reason, PCBS established a statistical program to monitor and produce reliable and timely statistics on the main indicators of tourism activity. This program began in 1996 with the implementation of the Hotel Survey, which provides periodic data on accommodation statistics.

Geographic coverage

Palestine

Analysis unit

Household the Palestine

Universe

It consists of all Palestinian households who are staying normally in Palestine during 2015.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame was based on master sample which was update in 2013-2014 for (Expenditure and Consumption Survey (PECS) and Multiple Indicator Cluster Survey (MICS)) surveys, and the frame consists from enumeration areas. These enumeration areas are used as primary sampling units (PSUs) in the first stage of the sampling selection.

Sample size: The sample size is 7,690 households for Palestine level, 6,609 households responded.

Sampling Design: Two stage stratified cluster (PPS) sample as following:

First stage: selection of a PPS random sample of 370 enumeration areas.

Second stage: A random systematic sample of 20 households from each enumeration area selected in the first stage.

Sample strata: The population was divided by: 1- Governorate 2- locality type (urban, rural, camps)

Mode of data collection

Face-to-face [f2f]

Research instrument

The tourism questionnaire was design of the accordance with similar international experiences and with international standards and recommendations for the most important indicators, taking into account the special situation of Palestine.

Cleaning operations

The data processing stage consisted of the following operations: 1.Editing and coding prior to data entry: all questionnaires were edited and coded in the office using the same instructions adopted for editing in the field.

2.Data entry: The Domestic and Outbound Tourism Survey questionnaire was programmed and the data were entered into the computer in the offices in Nablus, Hebron, Ramallah and Gaza. At this stage, data were entered into the computer using a data entry template developed in Access. The data entry program was prepared to satisfy a number of requirements: ·To prevent the duplication of questionnaires during data entry. ·To apply checks on the integrity and consistency of entered data. ·To handle errors in a user friendly manner. ·The ability to transfer captured data to another format for data analysis using statistical analysis software such as SPSS.

Response rate

Response rate was 89.5%

Sampling error estimates

Data of this survey may be affected by sampling errors due to use of a sample and not a complete enumeration. Therefore, certain differences are expected in comparison with the real values obtained through censuses. Variances were calculated for the most important indicators and the variance table is attached with the final report. There is no problem with the dissemination of results on national.

Abstract

The Environmental Economic survey was implemented with the main objective of providing reliable data of environmental reality on the economic establishments in the Palestinian Territory, including the methods used to handle the solid waste and wastewater. It includes also the role of the local authority in providing the suitable environment that will reduce the negative effect of the different types of pollution on the economic sector.

Geographic coverage

All of the economic establishments in the Palestinian Territory.

Analysis unit

Palestinian economic establishments

Kind of data

Sample survey data [ssd]

Sampling procedure

Target Population All the Palestinian economic establishments included in the Economic Series Survey sample in the Palestinian Territory.

Sample Design The sample is a single-stage stratified cluster random sample. It includes 3,922 Palestinian economic establishments distributed according to the economic activities and governorates.

Sample Frame The sampling frame was based on the Establishments' Census-2007 conducted by PCBS.

Stratification Three levels of stratification were followed in designing the sample of the economic Survey including: 1.Stratification by Region: the establishments were classified to regions: the West Bank and Gaza Strip 2.Stratification by economic activity. 3.Stratification by employers group.

The sample of the environmental economic survey is a partial sample of size 3544 from the economic series survey. There was a sample of size 368 from the establishments that do not hold accounts.

Mode of data collection

Face-to-face [f2f]

Research instrument

The environmental questionnaire was designed according to international standards and recommendations for the most important indicators, taking into account the special situation of Palestine. Many visits for economic establishments were made in order to improve the survey tools and to test the questionnaire before implementing the survey; consequently some modifications were made on the questionnaire and on the instructions following the visits.

Cleaning operations

The data processing stage contain of the following operations: Editing before data entry: all questionnaires were edited again in the office using the same instructions adopted for editing in the fields.

Data entry: In this stage data were entered into the computer, using Access database. The data entry program was prepared to satisfy a number of requirements such as: - Duplication of the questionnaire on the computer screen. - Logical and consistency check of data entered. - Possibility for internal editing of questions answers. - Maintaining a minimum of digital data entry and fieldwork errors. - User-Friendly handling. Possibility of transferring data into another format to be used and analyzed using other statistical analytical systems such as SAS and SPSS.

Response rate

Response rate = 81.9%

Sampling error estimates

Sampling Errors These types of errors evolved as a result of studying a part of the society and not all of it, and because this survey is sample based, the data of this survey will be affected by sampling errors due to using a sample and not the whole frame of the society, and therefore differences appear compared with the actual values that could be obtained through a census. For this survey, variance calculations were made for amounts of water consumed in the economic establishments by region and activity, and the main source of obtaining water in the economic establishments by region and activity.

Data appraisal

Non Sampling Errors Several measures were adopted to minimize the effects of these errors. The interviewers, editors and coders underwent intensive training and were provided with fieldwork manuals to consult when facing any problem.

The data entry program was designed in a way that allows error detection and correction. This applies particularly to logical errors that might not be discovered before data entry operations. A consistency check was also performed to assure accuracy after data entry.

These errors are due to non-response cases as well as the implementation of surveys. In this survey, these errors emerged because of (a) the special situation of the questionnaire itself which depends on type of estimation; (b) diversity of sources (e.g. the interviewers, respondent, editors, coders, data entry operator, etc). It is important to mention that 5% from the sample of this survey was re-interviewed, and the results of this re-interview were reported by the supervisors. The re-interview shows the variance in estimation by interviewers for quantities of water consumed and solid waste produced, when the interviewer who answers for the main survey questionnaire is different from the one who answers the re-interview questionnaire.

Comparability: The data of the environmental economic survey is comparable time; the results when comparing the data between different geographical comparing the data of this survey with the data of previous rounds were no significant differences.

Data Quality Assurance Procedures: Several measures were made to ensure quality control in the survey including ensuring fieldworkers had main skills before the start of data collection, and integrity in data collection.

Abstract

Objectives of the Survey The main objective of this survey is to provide statistical data on ICT for the enterprises in the Palestinian Territory. The specific objectives can be summarized in the following: ·Enriching ICT statistical data on the actual use and access by the economic enterprises of ICT. ·Identifying the characteristics of the tools and means of ICT used in the economic activity, the type of economic activity and size of enterprises. ·Providing opportunity for international and regional comparisons which helps in knowing the location of the Palestinian Territory among the technological world countries. ·Assisting planners and policy makers in understanding the current status of the Technology-Based Economy in the Palestinian Territory, which helps to meet the future needs of the Palestinian economy.

Geographic coverage

The Data are representative at region level (West Bank, Gaza Strip),

Analysis unit

• Enterprises

Universe

The enterprises in the Palestinian Territory

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Size and Design Frame

Target Population The target population consists of all operating private establishments in the Palestinian Territ.

Sampling Frame The sampling frame is the list of all operating private establishments enumerated in the Establishments Census 2007.

Sample Size The sample size is 1,905 establishments, of which 1,591 are establishments in the West Bank and 314 establishments in Gaza Strip.

Mode of data collection

Face-to-face [f2f]

Research instrument

In light of identifying data requirements, the survey instrument was developed following a review of international recommendations and experiences of countries in this area, and the experience of the BICT survey 2007 that implemented by PCBS. In addition to identification information and data quality control, BICT survey 2009 instrument consists of one main section studied the mechanisms and characteristics of use and access for the basic tools of ICT such as telephone, mobile phone, computer, internet, intranet, extranet, and e-commerce transactions on technology by the economic establishments in the Palestinian Territory. The survey aims mainly to provide comprehensive statistical data on the availability of the means, access and use of ICT tools in the establishments by the major economic activities, employment size, places and different goals as well as main features for the use of ICT.

Cleaning operations

Data Editing The project's management developed a clear mechanism for editing the data and trained the team of editors accordingly. The mechanism was as follows: · Receiving completed questionnaires on a daily basis; · Checking each questionnaire to make sure that they were completed and that the data covered all eligible enterprises. Checks also focused on the accuracy of the answers to the questions. Returning the uncompleted questionnaires as well as those with errors to the field for completion

Response rate

The survey sample consists of about 3,011 establishments; 1,905 establishments completed the interview, of which 1,591 establishments were in the West Bank and 314 establishments in Gaza Strip. The response rate was 66.0%.

Abstract

The Geneal Household Survey 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, 2007and 2008, the collaboration incorporated Nigerian Communications commission (NCC).

The purpose of the surveys or collaboration include among others: (i) To conduct multipurpose surveys to generate social and economic data series for 2009 and the first quarter of 2010

(ii) To enable NBS/CBN/NCC fulfil their mandate in production of current and credible statistics to monitor and evaluate the State of the economy and the various government programmes such as NEEDS, MDGs and 7 Point Agenda.

The key objectives of the survey include:

i) Collection of relevant statistics to facilitate the production of GDP

ii) Production of data to aid economic analysis on non-oil outputs such as Manufacturing, Agriculture and Services

iii) Production of State and Local Government Finance Statistics, Producer Price Index (PPI), Oil Sector Statistics and Flow of Funds

Collection of current socio-economic statistics in Nigeria to assist in policy formulation and aid the monitoring and evaluation of various government programmes at National and sub-national levels

Geographic coverage

National Zone State Local Government

Analysis unit

Household Analysis

Universe

Household

Kind of data

Sample survey data [ssd]

Sampling procedure

The General Household Survey and the National Agricultural Sample Survey designs derived from NBS 2007/12 NISH sample design. The 2007/12 NISH sample design is a 2-stage, replicated and rotated cluster sample design with Enumeration Areas (EAs) as first stage sampling units or Primary Sampling Units (PSUs) while Households constituted the second stage units (secondary sampling units). The households were the Ultimate Sampling Units for the multi-subject survey.

Generally, the NISH Master Sample in each State is made up of 200 EAs drawn in 20 replicates. A replicate consists of 10 EAs. Replicates 10-15, subsets of the Master Sample were studied for modules of the NISH.

The GHS was implemented as a NISH module. three replicates were studied per State including the FCT, Abuja. With a fixed-take of 15 HHs systematically selected per EA, 450 HHs thus were selected for interview per State including the FCT, Abuja. Hence, nationally, a total of 16,650 HHs were drawn from the 1,110 EAs selected for interview for the GHS. The selected EAs (and hence the HHs) cut across the rural and urban sectors.

Sampling deviation

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).

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire for the GHS 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.

This section were divided into eleven parts.

Part A: Identification code, Response status, Housing characteristics/amenities and Information communication Technology (ICT). Part B: Socio-demographic characteristics and Labour force characteristics Part C: Information about the people in the household who were absent during the period of the survey. Part D: Female contraceptive only, and children ever born by mothers aged 15 years and above Part E: Births of children in the last 12 months, and trained birth attendant used during child delivery. Part F: Immunization of children aged 1 year or less and records of their vaccination Part G: Child nutrition, exclusive breast feeding and length of breast feeding. Part H: Deaths in the last 12 months, and causes of such deaths. Part I: Health of all members, of the household and health care providers. Part J: Household enterprises, income and profit made from such activities. Part K: Household expenditure, such as school fees, medical expenses, housing expenses, remittance, cloth expenses, transport expenses and food expenses.

Cleaning operations

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 by the subject mater group. The questionnaires were processed at the zones. On completion, computer editing was also carried out to ensure the integrity of the data. .

Response rate

At National level ,out of the expected 1,110 EAs, all were covered which showed 100% retrieval rate. (by the table 1.12 on page 196 of the report)

At household level, out of the 16,650 expected to be covered, 16,355 were canvassed which showed 98% retrieval.

At sector level (Urban/Rural), 28.4% were recorded for Urban while Rural recorded 71.6%.

Sampling error estimates

No sampling error estimate

Data appraisal

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 Headquarters 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

Abstract

The General Household Survey-Panel (GHS-Panel) is implemented in collaboration with the World Bank Living Standards Measurement Study (LSMS) team as part of the Integrated Surveys on Agriculture (ISA) program. The objectives of the GHS-Panel include the development of an innovative model for collecting agricultural data, interinstitutional collaboration, and comprehensive analysis of welfare indicators and socio-economic characteristics. The GHS-Panel is a nationally representative survey of approximately 5,000 households, which are also representative of the six geopolitical zones. The 2023/24 GHS-Panel is the fifth round of the survey with prior rounds conducted in 2010/11, 2012/13, 2015/16 and 2018/19. The GHS-Panel households were visited twice: during post-planting period (July - September 2023) and during post-harvest period (January - March 2024).

Geographic coverage

National

Analysis unit

• Households • Individuals • Agricultural plots • Communities

Universe

The survey covered all de jure households excluding prisons, hospitals, military barracks, and school dormitories.

Kind of data

Sample survey data [ssd]

Sampling procedure

The original GHS‑Panel sample was fully integrated with the 2010 GHS sample. The GHS sample consisted of 60 Primary Sampling Units (PSUs) or Enumeration Areas (EAs), chosen from each of the 37 states in Nigeria. This resulted in a total of 2,220 EAs nationally. Each EA contributed 10 households to the GHS sample, resulting in a sample size of 22,200 households. Out of these 22,200 households, 5,000 households from 500 EAs were selected for the panel component, and 4,916 households completed their interviews in the first wave.

After nearly a decade of visiting the same households, a partial refresh of the GHS‑Panel sample was implemented in Wave 4 and maintained for Wave 5. The refresh was conducted to maintain the integrity and representativeness of the sample. The refresh EAs were selected from the same sampling frame as the original GHS‑Panel sample in 2010. A listing of households was conducted in the 360 EAs, and 10 households were randomly selected in each EA, resulting in a total refresh sample of approximately 3,600 households.

In addition to these 3,600 refresh households, a subsample of the original 5,000 GHS‑Panel households from 2010 were selected to be included in the new sample. This “long panel” sample of 1,590 households was designed to be nationally representative to enable continued longitudinal analysis for the sample going back to 2010. The long panel sample consisted of 159 EAs systematically selected across Nigeria’s six geopolitical zones.

The combined sample of refresh and long panel EAs in Wave 5 that were eligible for inclusion consisted of 518 EAs based on the EAs selected in Wave 4. The combined sample generally maintains both the national and zonal representativeness of the original GHS‑Panel sample.

Sampling deviation

Although 518 EAs were identified for the post-planting visit, conflict events prevented interviewers from visiting eight EAs in the North West zone of the country. The EAs were located in the states of Zamfara, Katsina, Kebbi and Sokoto. Therefore, the final number of EAs visited both post-planting and post-harvest comprised 157 long panel EAs and 354 refresh EAs. The combined sample is also roughly equally distributed across the six geopolitical zones.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The GHS-Panel Wave 5 consisted of three questionnaires for each of the two visits. The Household Questionnaire was administered to all households in the sample. The Agriculture Questionnaire was administered to all households engaged in agricultural activities such as crop farming, livestock rearing, and other agricultural and related activities. The Community Questionnaire was administered to the community to collect information on the socio-economic indicators of the enumeration areas where the sample households reside.

GHS-Panel Household Questionnaire: The Household Questionnaire provided information on demographics; education; health; labour; childcare; early child development; food and non-food expenditure; household nonfarm enterprises; food security and shocks; safety nets; housing conditions; assets; information and communication technology; economic shocks; and other sources of household income. Household location was geo-referenced in order to be able to later link the GHS-Panel data to other available geographic data sets (forthcoming).

GHS-Panel Agriculture Questionnaire: The Agriculture Questionnaire solicited information on land ownership and use; farm labour; inputs use; GPS land area measurement and coordinates of household plots; agricultural capital; irrigation; crop harvest and utilization; animal holdings and costs; household fishing activities; and digital farming information. Some information is collected at the crop level to allow for detailed analysis for individual crops.

GHS-Panel Community Questionnaire: The Community Questionnaire solicited information on access to infrastructure and transportation; community organizations; resource management; changes in the community; key events; community needs, actions, and achievements; social norms; and local retail price information.

The Household Questionnaire was slightly different for the two visits. Some information was collected only in the post-planting visit, some only in the post-harvest visit, and some in both visits.

The Agriculture Questionnaire collected different information during each visit, but for the same plots and crops.

The Community Questionnaire collected prices during both visits, and different community level information during the two visits.

Cleaning operations

CAPI: Wave five exercise was conducted using Computer Assisted Person Interview (CAPI) techniques. All the questionnaires (household, agriculture, and community questionnaires) were implemented in both the post-planting and post-harvest visits of Wave 5 using the CAPI software, Survey Solutions. The Survey Solutions software was developed and maintained by the Living Standards Measurement Unit within the Development Economics Data Group (DECDG) at the World Bank. Each enumerator was given a tablet which they used to conduct the interviews. Overall, implementation of survey using Survey Solutions CAPI was highly successful, as it allowed for timely availability of the data from completed interviews.

DATA COMMUNICATION SYSTEM: The data communication system used in Wave 5 was highly automated. Each field team was given a mobile modem which allowed for internet connectivity and daily synchronization of their tablets. This ensured that head office in Abuja had access to the data in real-time. Once the interview was completed and uploaded to the server, the data was first reviewed by the Data Editors. The data was also downloaded from the server, and Stata dofile was run on the downloaded data to check for additional errors that were not captured by the Survey Solutions application. An excel error file was generated following the running of the Stata dofile on the raw dataset. Information contained in the excel error files were then communicated back to respective field interviewers for their action. This monitoring activity was done on a daily basis throughout the duration of the survey, both in the post-planting and post-harvest.

DATA CLEANING: The data cleaning process was done in three main stages. The first stage was to ensure proper quality control during the fieldwork. This was achieved in part by incorporating validation and consistency checks into the Survey Solutions application used for the data collection and designed to highlight many of the errors that occurred during the fieldwork.

The second stage cleaning involved the use of Data Editors and Data Assistants (Headquarters in Survey Solutions). As indicated above, once the interview is completed and uploaded to the server, the Data Editors review completed interview for inconsistencies and extreme values. Depending on the outcome, they can either approve or reject the case. If rejected, the case goes back to the respective interviewer’s tablet upon synchronization. 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. Additional errors observed were compiled into error reports that were regularly sent to the teams. These errors were then 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 approved by the Data Editor. After the Data Editor’s approval of the interview on Survey Solutions server, the Headquarters also reviews and depending on the outcome, can either reject or approve.

The third stage of cleaning involved a comprehensive review of the final raw data following the first and second stage cleaning. Every variable was examined individually for (1) consistency with other sections and variables, (2) out of range responses, and (3) outliers. However, special care was taken to avoid making strong assumptions when resolving potential errors. Some minor errors remain in the data where the diagnosis and/or solution were unclear to the data cleaning team.

Response

Abstract

The immediate objective of the Survey is the development of institutional capacity of the National Institute of Statistics (NIS) of the Ministry of Planning (MOP) to implement a demand driven multi-purpose living standards household survey based data collection system which produces regular, timely and relevant feed back to government policy makers. The project has provided technical assistance for the conduct of two large scale multi-objective national household surveys, the first one in 1997 and the second to be conducted in 1998/99. The primary objective of Cambodia Socio-Economic Survey (CSES) 1997 was to obtain data for the measurement of living standards in geographic stratification and different segments of the Cambodian society. The other objectives were to provide information needed by a variety of users such as government institutions, donor agencies, non- government organizations; to assist NIS to train its staff in planning, designing and conducting a household based survey system and institutionalize survey taking capability. The expansion of the scope of the survey to meet the data needs of a wide variety of users and thus minimize the duplication of household surveys and promote the acceptance of CSES as the national household survey programme was also an important objective.

Geographic coverage

The sample was designed to provide estimates of the indicators at :

National (24 provinces) Phnom Penh, Other Urban and Other Rural Plain, Tonle Sap, Coastal, and Plateau/Mountain

Analysis unit

• Individual

• Household

Universe

Select sample households from non-institutional households (All regular residents in Cambodia) in Cambodia.

Kind of data

Sample survey data [ssd]

Sampling procedure

A two stage stratified sampling design with the villages as the first stage units (PSU's) and households as the second stage units(SSU's) was used in the sampling strategy:

1. First Stage Selection

In the first stage the villages or primary sampling units ( PSU’s ) were drawn from

each domain. Within the three domains the villages were arranged by geographic codes with

the villages grouped within communes and the communes within districts and districts within

the provinces providing for some implicit stratification. The villages that had geographic

codes also had the reported number of households based on the frame. The latter was used as

the measure of size (MOS) in deriving the cumulated list for sampling. The sample villages

were selected using the systematic sampling method with a random start with probability

proportional to size method (PPS). The selection of sample villages was carried out through

the use of a computer program.

1. The Second Stage Selection

For each selected village (PSU) a field listing was undertaken and let the actual

number of households listed in the PSU be Mhi

• ,

then the probability of selecting a household in the i th PSU in the h th domain is

ph( j / i ) = nh / Mhi

where nh is equal to 10 in domains 1 and 2 and 15 for domain 3. Circular systematic

random sampling with a random start was used to select households. The sampling interval

would be equal to the current estimate of households in the PSU ascertained through the

listing operation divided by 10 in the urban domains and 15 in the rural domain..

Please see Sample Selection in report or technical report of external resources

Sampling deviation

The sampling design for the CSES 1997 considered several factors including the precision of data required by the users, the capacity of the national statistics office to conduct the survey, and most importantly the time constraint imposed to complete survey field work before the end of July 1997. Taking into account these factors, and specially the experience gained from the two socio-economic surveys conducted in 1993/94 and 1996, including estimates of feasible work loads, a sample of 6000 households to be selected from 474 villages was considered to be sufficient and manageable.

The design also took into consideration the need for separate analyses of three geographical domains, namely Phnom Penh, other urban areas aggregated together, and the rural area. In deciding the sample allocation to the three domains, it was decided that a size of around 1000 households would be adequate for the first two domains and the rest should be allocated to Domain 3 - Rural area, since it was envisaged that more detailed analysis of the poverty groups in this domain would be undertaken.

Mode of data collection

Face-to-face [f2f]

Research instrument

The CSES 1997 questionnaire comprises 4 forms, namely:

Form 1: Listign of Households in the Village

Form 2: Village Questionnaire

Form 3: Core Questionnaire for Households

Form 4: Social Sector Household Module

Cleaning operations

All completed questionnaires were brought to NIS for processing. Although completed questionnaires were checked and edited by supervisors in the field, specially because of the length of questionnaires and the complexity of the topics covered the need for manual editing and coding by trained staff was accepted as an essential priority activity to produce a cleaned data file without delay. In all, 39 staff comprising 35 processing staff and 4 supervisors were trained for three days by the project staff. An instruction manual for manual editing and coding was prepared and translated into Khmer for the guidance of processing staff. Manual processing of questionnaires commenced in mid August 1997.

In order to produce an unedited data file, keying in the data as recorded by field enumerators and supervisors, (without subjecting data to manual edit as required by the Analysis Component Project staff), it was necessary to structure manual editing as a two-phase operation. Thus in the first phase, the processing staff coded the questions such as those on migration, industry, and occupation which required coding. Editing was restricted to selected structural edits and some error corrections. These edits were restricted to checking the completeness and consistency of responses, legibility, and totaling of selected questions. Error corrections were made without canceling or obliterating the original entry made by the enumerator, by inserting the correction close to the original entry.

Much of the manual editing was carried out in the second phase, after key entry and one hundred percent verification and extraction of error print outs. A wide range of errors had to be corrected which was expected in view of the complexity of the survey and the skill background of the enumeration and processing staff. The manual edits involved the correction of errors arising from incorrect key entry, in-correct/ failure to include identification, miss-coding of answers, failure to follow skip patterns, misinterpretation of measures, range errors, and other consistency errors.

Response rate

Despite the length of the questionnaire, the respondents had cooperated with the survey staff and provided answers to both questionnaires and it was possible to achieve a 100% response rate. At this stage it is not possible to comment on item non-response, and completeness of information provided by the respondents, and the respondent’s fatigue arising from the length of the interviews which may have had a bearing on these issues.

Sampling error estimates

The results obtained from the survey are subject to sampling errors. Sampling errors in surveys occur as a result of limiting the survey observations to a subset rather than the whole population. These errors are related to the sample size selected and sampling design adopted in the survey. In order to maintain these errors within acceptable levels, the efficient sampling design with the sample allocation described earlier was adopted.

In addition to sampling errors, the estimates are also subject to non-sampling errors that arise in different stages of any survey operation. These include

• errors that are introduced at the preparatory stage

• errors committed during data collection including those committed by interviewers and respondents

• processing errors

The first item includes errors arising from questionnaire design, preparation of definitions and instructions, preparation of table formats etc. The other two categories are clear from the terminology used. The use of trained enumerators and processing staff and careful organization and thorough supervision are essential to control and minimize these errors.

As already referred to, it was possible to obtain responses from all the villages and

households that were sampled, and thus it was not necessary to adjust the data for non-response. Thus the bias that is introduced into the estimates as a result of non-response was avoided.

The standard error of a survey estimate provides a measure of how far the survey estimate is likely to vary from the true population value(i.e. parameter ) as a result of having collected the data on a sample basis rather through a complete census. The standard error se(r) of a survey estimate is by definition

se( r ) = var( r )^1/2

The relative standard error or coefficient of variation ( cv ), on the other hand provides a measure of the relative variance of a survey estimate; that is the magnitude of the estimated sampling error relative to the magnitude of the estimate itself. The cv that is expressed as a proportional error

Abstract

The Socio-Economic Survey of Cambodia (SESC) 1996 is a two-round sample survey of households in Cambodia conducted by the National Institute of Statistics (NIS) of the Ministry of Planning and sponsored by the Asian Development Bank (ADB) in collaboration with UNICEF, UNDP/CARERE and ILO. This survey is second in the series, the first SESC being conducted in four rounds beginning in October 1993 to September 1994 and funded by the UNDP and ADB.

The first round of the SESC 1996 was conducted in May-June and the second round was in November-December. The survey entrailed listing and recording of the characteristics of each individual person in the sample households. It gathered data on the demographic, social and economic characteristics of the population as well as on household and housing characteristics. The information collected are vital in making rational plans and programs for the country.

Geographic coverage

A. National, Urban and Rural

B. Phnom Penh, Other Urban and Other Rural

C. The 10 Domains:

   1. Banteay Meanchey

   2. Battambang 

   3. Kampong Thom 

   4. Pursat

   5. Ratanakiri 

   6. Siem Reap 

   7. Svay Rieng

   8. Phnom Penh

   9. Other Urban

  10. Other Rural

The SESC 1996 covered 87.26 per cent of Cambodian villages.

Analysis unit

1. Individuals

2. Household

Universe

All non-institutional households in Cambodia (All regular resident households in Cambodia)

Kind of data

Sample survey data [ssd]

Sampling procedure

The SESC used a stratified two-stage probability sampling technique with the following areas as domains of analysis: Banteay Meanchey, Battambang, Kampong Thom, Pursat, Ratanak Kiri, Siem Reap, Svay Rieng, Phnom Penh, Other Urban, and Other Rural. The number of strata was increased to come up with estimates for the above mentioned provinces.

For each survey round, 390 primary sampling units (PSUs) or a total of 780 PSUs (villages) for the two rounds were selected using the linear systematic sampling with a random start method, with probability proportional to size. The number of households in the village was used as a measure of size. These information are based on the population database compiled in the National Institute of Statistics, Ministry of Planning, and from several sources including a gazetteer of the Geographic Department, a village file constructed in 1993 by the United Nations Transitional Authority in Cambodia (UNTAC), population statistics of Battambang province constructed by the United Nations High Commissioner for Refugees (UNHCR), and supplemental population estimates supplied by the Ministry of Interior and the Municipality of Phnom Penh. The merger of these multiple sources constitutes the sampling frame for the Socio-Economic Survey of Cambodia (SESC) 1996.



The households constituted the secondary sampling units (SSUs). From each PSU, 10 or 20 households were selected systematically with a random start. The method of selecting the samples is explained in the next section.



The first stage of sample selection involved the drawing of sample villages from each stratum. Within each stratum, villages were arranged by geographic codes and the number of households for every village based on the sample frame records was cumulated. Sample villages were selected using the linear systematic sampling with random start method, with probability proportional to size (pps). The number of households in the village was used as a measure of size. Sample village selection was done through the use of a computer program.



For each sample village (PSU), a field listing operation was undertaken except for large villages. Large villages were segmented first, comprising about 300 households or less based on the current household estimates by the commune or village leaders. A segment was then chosen randomly in which a complete listing of households was done. This entailed carrying out a complete canvass of the PSU in order to make a current and complete listing of households contained within. The procedure involved creating a sketch map for the PSU where physical boundaries in the village and the location of each household were sketched. Canvassing, on the other hand, entailed a systematic covering of the entire village following a prescribed path of travel in order to make sure that all housing units in which the households reside will be accounted for.



After the listing operation was completed, a fixed sample size of 10 households was selected in each PSU for the following strata: Banteay Meanchey, Phnom Penh, Pursat, Siem Reap, Other Urban and Other Rural, while 20 households werer selected from each PSU for Battambang, Kampong Thom, Ratanakiri and Svay Rieng. The selection was carried out using circular systematic random sampling with a random start. The sampling interval was equal to the current household estimates in the PSU divided by 10 or 20, as the case maybe.



The sampling strategy required the selection of a total of 9,000 sample households from 780 sample villages for the two rounds.

Sampling deviation

Pailin was excluded from the sampling frame due to security issues.

Mode of data collection

Face-to-face [f2f]

Research instrument

Listed below are the forms that used during the field enumeration:

SESC Form 1 - Listing Sheet: This is a sheet wherein buildings, housing units and households within an enumeration pertaining to population of households are listed

SESC Form 2 - Household Questionnaire: This is the basic SESC questionnaire which was used for interviewing and recording information about a household. This questionnaire contains information on the following: demographic, social and economic characteristics of the population, household and housing characteristics. The Questionnaire consists of 4 parts, namely:

1. Part II - Demographic and Economic Characteristics of the Household Population

2. Part III - Child Labour (For Children 5 - 17 Years Old)

3. Part IV - Health and Nutritional Status of Children Under 5 Years Old

4. Part V - Household and Housing Particulars

SESC Form 3 - Appointment Slip: This form is used to set an appointment with the household head (or spouse) in case the interviewer was unable to interview anyone during the first visit. The date and time of next visit is jotted down in the form.

Cleaning operations

All completed questionnaires were brought to NIS for processing. Although completed questionnaires were checked and edited by supervisors in the field, especially because of the length of questionnaires and the complexity of the topics covered the need for manual editing and coding by trained staff was accepted as an essential priority activity to produce a cleaned data file without delay. Processing staff and supervisors were trained for three days by the project staff. An instruction manual for manual editing and coding was prepared and translated into Khmer for the guidance of processing staff.

In order to produce an unedited data file, keying in the data as recorded by field enumerators and supervisors, (without subjecting data to manual edit as required by the Analysis Component Project staff), it was necessary to structure manual editing as a two-phase operation. Thus in the first phase, the processing staff coded the questions such as those on migration, industry, and occupation which required coding. Editing was restricted to selected structural edits and some error corrections. These edits were restricted to checking the completeness and consistency of responses, legibility, and totalling of selected questions. Error corrections were made without cancelling or obliterating the original entry made by the enumerator, by inserting the correction close to the original entry.

Much of the manual editing was carried out in the second phase, after key entry and one hundred percent verification and extraction of error print outs. A wide range of errors had to be corrected which was expected in view of the complexity of the survey and the skill background of the enumeration and processing staff. The manual edits involved the correction of errors arising from incorrect key entry, in-correct/ failure to include identification, miss-coding of answers, failure to follow skip patterns, misinterpretation of measures, range errors, and other consistency errors.

Response rate

100%

Sampling error estimates

It has to be noted that the data were obtained through a sample survey and are therefore subject to both sampling and nonsampling errors. Sampling errors are those that are related to the sample size and the kind of samples selected. Non-sampling errors include those such as errors committed by the interviewers in recording

responses, errors made by respondents and coding errors. Moreover, the 1996 population and other estimates from the SESC may not be directly comparable with estimates based from other surveys because of differences in the sampling frame, survey design and concepts used. The concepts used in this survey are found

Abstract

Censuses are principal means of collecting basic population and housing statistics required for social and economic development, policy interventions, their implementation and evaluation.The census plays an essential role in public administration. The results are used to ensure: • equity in distribution of government services • distributing and allocating government funds among various regions and districts for education and health services • delineating electoral districts at national and local levels, and • measuring the impact of industrial development, to name a few The census also provides the benchmark for all surveys conducted by the national statistical office. Without the sampling frame derived from the census, the national statistical system would face difficulties in providing reliable official statistics for use by government and the public. Census also provides information on small areas and population groups with minimum sampling errors. This is important, for example, in planning the location of a school or clinic. Census information is also invaluable for use in the private sector for activities such as business planning and market analyses. The information is used as a benchmark in research and analysis.

Census 2011 was the third democratic census to be conducted in South Africa. Census 2011 specific objectives included: - To provide statistics on population, demographic, social, economic and housing characteristics; - To provide a base for the selection of a new sampling frame; - To provide data at lowest geographical level; and - To provide a primary base for the mid-year projections.

Geographic coverage

National

Analysis unit

Households, Individuals

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Research instrument

About the Questionnaire : Much emphasis has been placed on the need for a population census to help government direct its development programmes, but less has been written about how the census questionnaire is compiled. The main focus of a population and housing census is to take stock and produce a total count of the population without omission or duplication. Another major focus is to be able to provide accurate demographic and socio-economic characteristics pertaining to each individual enumerated. Apart from individuals, the focus is on collecting accurate data on housing characteristics and services.A population and housing census provides data needed to facilitate informed decision-making as far as policy formulation and implementation are concerned, as well as to monitor and evaluate their programmes at the smallest area level possible. It is therefore important that Statistics South Africa collects statistical data that comply with the United Nations recommendations and other relevant stakeholder needs.

The United Nations underscores the following factors in determining the selection of topics to be investigated in population censuses: a) The needs of a broad range of data users in the country; b) Achievement of the maximum degree of international comparability, both within regions and on a worldwide basis; c) The probable willingness and ability of the public to give adequate information on the topics; and d) The total national resources available for conducting a census.

In addition, the UN stipulates that census-takers should avoid collecting information that is no longer required simply because it was traditionally collected in the past, but rather focus on key demographic, social and socio-economic variables.It becomes necessary, therefore, in consultation with a broad range of users of census data, to review periodically the topics traditionally investigated and to re-evaluate the need for the series to which they contribute, particularly in the light of new data needs and alternative data sources that may have become available for investigating topics formerly covered in the population census. It was against this background that Statistics South Africa conducted user consultations in 2008 after the release of some of the Community Survey products. However, some groundwork in relation to core questions recommended by all countries in Africa has been done. In line with users' meetings, the crucial demands of the Millennium Development Goals (MDGs) should also be met. It is also imperative that Stats SA meet the demands of the users that require small area data.

Accuracy of data depends on a well-designed questionnaire that is short and to the point. The interview to complete the questionnaire should not take longer than 18 minutes per household. Accuracy also depends on the diligence of the enumerator and honesty of the respondent.On the other hand, disadvantaged populations, owing to their small numbers, are best covered in the census and not in household sample surveys.Variables such as employment/unemployment, religion, income, and language are more accurately covered in household surveys than in censuses.Users'/stakeholders' input in terms of providing information in the planning phase of the census is crucial in making it a success. However, the information provided should be within the scope of the census.

1. The Household Questionnaire is divided into the following sections:
2. Household identification particulars

3. Individual particulars Section A: Demographics Section B: Migration Section C: General Health and Functioning Section D: Parental Survival and Income Section E: Education Section F: Employment Section G: Fertility (Women 12-50 Years Listed) Section H: Housing, Household Goods and Services and Agricultural Activities Section I: Mortality in the Last 12 Months The Household Questionnaire is available in Afrikaans; English; isiZulu; IsiNdebele; Sepedi; SeSotho; SiSwati;Tshivenda;Xitsonga

4. The Transient and Tourist Hotel Questionnaire (English) is divided into the following sections:

5. Name, Age, Gender, Date of Birth, Marital Status, Population Group, Country of birth, Citizenship, Province.

6. The Questionnaire for Institutions (English) is divided into the following sections:

7. Particulars of the institution

8. Availability of piped water for the institution

9. Main source of water for domestic use

10. Main type of toilet facility

11. Type of energy/fuel used for cooking, heating and lighting at the institution

12. Disposal of refuse or rubbish

13. Asset ownership (TV, Radio, Landline telephone, Refrigerator, Internet facilities)

14. List of persons in the institution on census night (name, date of birth, sex, population group, marital status, barcode number)

15. The Post Enumeration Survey Questionnaire (English)

These questionnaires are provided as external resources.

Cleaning operations

Data editing and validation system The execution of each phase of Census operations introduces some form of errors in Census data. Despite quality assurance methodologies embedded in all the phases; data collection, data capturing (both manual and automated), coding, and editing, a number of errors creep in and distort the collected information. To promote consistency and improve on data quality, editing is a paramount phase in identifying and minimising errors such as invalid values, inconsistent entries or unknown/missing values. The editing process for Census 2011 was based on defined rules (specifications).

The editing of Census 2011 data involved a number of sequential processes: selection of members of the editing team, review of Census 2001 and 2007 Community Survey editing specifications, development of editing specifications for the Census 2011 pre-tests (2009 pilot and 2010 Dress Rehearsal), development of firewall editing specifications and finalisation of specifications for the main Census.

Editing team The Census 2011 editing team was drawn from various divisions of the organisation based on skills and experience in data editing. The team thus composed of subject matter specialists (demographers and programmers), managers as well as data processors. Census 2011 editing team was drawn from various divisions of the organization based on skills and experience in data editing. The team thus composed of subject matter specialists (demographers and programmers), managers as well as data processors.

The Census 2011 questionnaire was very complex, characterised by many sections, interlinked questions and skipping instructions. Editing of such complex, interlinked data items required application of a combination of editing techniques. Errors relating to structure were resolved using structural query language (SQL) in Oracle dataset. CSPro software was used to resolve content related errors. The strategy used for Census 2011 data editing was implementation of automated error detection and correction with minimal changes. Combinations of logical and dynamic imputation/editing were used. Logical imputations were preferred, and in many cases substantial effort was undertaken to deduce a consistent value based on the rest of the household’s information. To profile the extent of changes in the dataset and assess the effects of imputation, a set of imputation flags are included in the edited dataset. Imputation flags values include the following: 0 no imputation was performed; raw data were preserved 1 Logical editing was performed, raw data were blank 2 logical editing was performed, raw data were not blank 3 hot-deck imputation was performed, raw data were blank 4 hot-deck imputation was performed, raw data were not blank

Data appraisal

Independent monitoring and evaluation of Census field activities Independent monitoring of the Census 2011 field activities was carried out by a team of 31 professionals and 381 Monitoring

Abstract

The Ethiopian Rural Socioeconomic Survey (ERSS) is a collaborative project between the Central Statistics Agency (CSA) of Ethiopia and the World Bank Living Standards Measurement Study- Integrated Surveys on Agriculture (LSMS-ISA) team. The objective of the LSMS-ISA is to collect multi-topic panel household level data with a special focus on improving agriculture statistics and the link between agriculture and other sectors of the economy. The project also aims to build capacity, share knowledge across countries, and improve survey methodologies and technology.

The specific objectives of the ERSS are: - Development of an innovative model for collecting agricultural data in conjunction with household data; - Strengthening the capacity to generate a sustainable system for producing accurate and timely information on agricultural households in Ethiopia; - Development of a model of inter-institutional collaboration between the CSA and relevant federal and local government agencies as well as national and international research and development partners; and - Comprehensive analysis of household income, well-being, and socio-economic characteristics of households in rural areas and small towns.

Geographic coverage

Regional Coverage

Analysis unit

Households

Kind of data

Sample survey data [ssd]

Sampling procedure

The ERSS sample is designed to be representative of rural and small town areas of Ethiopia. The ERSS rural sample is a sub-sample of the AgSS while the small town sample comes from the universe of small town EAs. The ERSS sample size provides estimates at the national level for rural and small town households. At the regional level, it provides estimates for four regions including Amhara, Oromiya, SNNP, and Tigray.

The sample is a two-stage probability sample. The first stage of sampling entailed selecting primary sampling units , which are a sample of the CSA enumeration areas (EAs). For the rural sample, 290 EAs were selected from the AgSS EAs. The AgSS EAs were selected based on probability proportional to size of the total EAs in each region. For small town EAs, a total of 43 EAs were selected. In order to ensure sufficient sample in the most populous regions (Amhara, Oromiya, SNNP, and Tigray), quotas were set for the number of EAs in each region. The sample is not representative for each of the small regions including Afar, Benshangul Gumuz, Dire Dawa, Gambella, Harari, and Somalie regions. However, estimates can be produced for a combination of all smaller regions as one "other region" category.

The second stage of sampling was the selection of households to be interviewed in each EA. For rural EAs, a total of 12 households are sampled in each EA. Of these, 10 households were randomly selected from the sample of 30 AgSS households. The AgSS households are households which are involved in farming or livestock activities. Another 2 households were randomly selected from all other households in the rural EA (those not involved in agriculture or livestock). In some EAs, there is only one or no such households, in which case, less than two non-agricultural households were surveyed and more agricultural households were interviewed instead so that the total number of households per EA remains the same.

In the small town EAs, 12 households are selected randomly from the listing of each EA, with no stratification as to whether the household is engaged in agriculture/livestock. Households were not selected using replacement. Thus, the final number of household interviewed was slightly less than the 3,996 as planned in the design.

Mode of data collection

Face-to-face paper [f2f]

Cleaning operations

Most of the interviews were carried out using paper and pen interviewing method. The completed paper questionnaires were sent to the CSA headquarters in Addis Ababa. The questionnaires were first checked by editors for completeness and consistency. The editors checked completeness (taking inventory) and cross-checked the questionnaires with the EA codebook. Questionnaires with inconsistent responses or with errors were corrected by contacting the branch offices or, in some cases, by sending the questionnaires back to the field. Checked questionnaires were keyed by data entry clerks at the head office using CSPro data entry application software.

Computer assisted personal interviewing (CAPI) was implemented, as a pilot, in 33 of the 333 EAs using SurveyBe data collection software.

The data cleaning process was done in two stages. The first step was at the CSA head office using the CSA's data cleaning staff. The CSA data cleaning staff used the CSpro data cleaning application to capture out of range values, outliers, and skip inconsistencies from the batch error reports. Once the errors were flagged in the batch error report the hard copy of the original questionnaire was retrieved and checked if the errors were at the data collection, editing, or entry level. Editing and entry level errors were corrected at the head office. Field level errors were communicated with the branch offices in the regions. The second level of data cleaning was done using Stata program to check for inconsistencies.

Response rate

A total of 3,969 households were interviewed with a response rate of 99.3 percent.

Abstract

The presence of adequate and current statistical data in various economic sectors that are considered essential for development planning, socio-economic policy formulation and economic analysis is vital in promoting the economic development of a country. Based on this general objective, the Central Statistical Agency (CSA) has been conducting surveys of various economic activities, of which, the annual Large and Medium Scale Manufacturing Industries survey is one.

Manufacturing is defined here according to International Standard Industrial Classification (ISIC Revision-3.1) as “the physical or chemical transformation of materials or components into new products, whether the work is performed by power-driven machines or by hand, whether it is done in a factory or in the worker's home, and whether the products are sold at wholesale or retail. The assembly of the component parts of manufactured products is also considered as manufacturing activities.”

CSA has been publishing results of the survey of Manufacturing and Electricity Industries on annual basis since 1968 Ethiopian Calendar to provide users with reliable, comprehensive and timely statistical data on these sectors. In this respect, this survey, which is conducted on annual basis, is the principal source of industrial statistics on large and medium scale manufacturing industries in the country.

The main objectives of the annual survey of Large and Medium Scale Manufacturing and Electricity Industries are to: 1.Obtain basic statistical data that are essential for policy makers, planners and researchers by major industrial group. 2.Collect basic quantitative information on employment, volume of quantitative information on employment, volume of production and raw materials, structure and performance of the country's Large and Medium Scale Manufacturing and Electricity Industries. 3.Compile statistical data which will be an input to the System of National Accounts (SNA), on Large and Medium Scale Manufacturing and Electricity establishments as a whole and by major industrial group. 4.Obtain the number of proprietors engaged in these sectors and find out the major problems that create stumbling blocks for their activities.

Geographic coverage

National

Analysis unit

Establishment/ Enterprise

Universe

The universe of the large and medium scale manufacturing survey is confined to those establishments which engaged 10 persons and above and use power-driven machines and covers both public and private industries in all Regions of the country.

Kind of data

Census/enumeration data [cen]

Sampling procedure

Not applicable - the survey enumerated all manufacturing industries/ enterprises that qualified as large and medium manufacturing industry category.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questinnaire contains the following sections/ items:

Item 1.1. Adress of the establishments: This section has varibles that identify the questionnaire uniquely. The variables are; Killil, Zone, Wereda, Town, Higher, Kebele, House no, Year, ISIC, Establishmnet no, Eelephone no and P.O.Box codes or numbers.

Item 1.2. Address of Head Office if Separated From Factory: In this section information about factory head office is collected (if the factory is separated from the head office). The varibles used to collect the information are; Killil, Zone, Wereda, Town, Higher, Kebele, House no, Telephone no and P.O.Box.

Item 2. Basic Information About The Establishment: This section has questions related to basic information about the establishment.

Item 3.1. Number of Persons Engaged: This section has variables (questions) that used to collect establishment's employees number by employees occupation.

Item 3.2. Number of Persons Engaged by Educational Status: This section has varabils (questions) that used to collect establishment's employees number by their educational status.

Item 3.3. Number of Persons Engaged by Age Group: Contains variables that used to collect information about employees number by employees age group.

Item 3.4. Wages and Salaries and Other Employee Benefits Paid: This section has variables related to wages and other employees benefits by employee occupation.

Item 3.5. Number of Permanent Employees by Basic Salary Group: This section has variables related to salary groups by sex of employees

Item 4.1. Products and By-products: This section has questions related to product produced, produced quantity and sales.

Item 4.2. Service and Other Receipts: Contains questions related to income from different source other than selling the products.

Item 5. Value of Stocks: Contains questions that related to information about materials in the stock.

Item 6.1. Cost and Quantity of Raw Materials, Parts and Containers Used: This section has questions related to principal raw materials, raw material type, quantity, value and source (local or imported).

Item 6.2. Other Industrial Costs: This sections has questions related to other industrial costs including cost of energy and other expenses.

Item 6.3. Other Non-industrial Expenses: Contains questions related to non-industrial expenses like license fee, advertising, stationary, etc.

Item 6.4. Taxes Paid: This section has questions related to taxes like indirect tax and income tax.

Item 7. Fixed Assets and Investment: This section has questions related to fixed assets and investment on fixed assests and working capital.

Item 8.1. Annual Production at Full Capacity: This section has questions about quantity and value of products if the establishment uses its full capacity.

Item 8.2. Estimated Value and Quantity of Raw Materials Needed, at Full Capacity: This section has questions about the estimate of quantity and value of raw materials that needed to function at full capacity.

Item 8.3. The three major problems that prevented the establishment from operating at full capacity.

Item 8.4. The three major problems that are facing the establishment at present.

Cleaning operations

Editing, Coding and Verification: A number of quality control steps were taken to ensure the quality of data. The first step taken in this direction was, to revise the questionnaire, to make it easier for internal consistency checking or editing, both at field and office level. Furthermore, based on this revised questionnaire, revised instruction manual with field editing procedures were prepared in Amharic for both enumerators and supervisors (field editors). Using this manual, some editing and coding were carried out by field editors during the data collection stage.

After the majority of the completed questionnaires were brought back to head office, final editing, coding and verification were performed by editors, statistical technicians and statisticians. Finally, the edited and coded questionnaires were checked and verified by other senior professionals.

Data Entry, Cleaning and Tabulation: The data were entered and verified on personal computers using CSpro (Census and Survey Processing System) Software. Fifteen CSA data entry staff and one data cleaner participated in this activity for fifteen days with close supervision of the activities by two professionals. Then, the data entered were cleaned hundred percent using personal computers in combination with manual cleaning for some serious errors. Finally, the tabulation of the results was processed using the same software by one programmer with technical assistance from Industry, Trade and Services Statistics Department staff.

Abstract

The Indonesia Demographic and Health Survey (IDHS), which is part of the Demographic and Health Surveys (DHS) Project, is one of prominent national surveys in the field of population, family planning, and health. The survey is not only important nationally for planning and evaluating population, family planning, and health developments, but is also important internationally since IDHS has been designed so uniquely that it can be compared with similar surveys in other developing countries.

The 1997 Indonesia Demographic and Health Survey (IDHS) is a follow-on project to the 1987 National Indonesia Contraceptive Prevalence Survey (NICPS), the 1991 IDHS, and the 1994 IDHS. The 1997 IDHS was expanded from the 1994 survey to include a module on family welfare; however, unlike the 1994 survey, the 1997 survey no longer investigated the availability of family planning and health services. The 1997 IDHS also included as part of the household schedule a household expenditure module that provided a means of identifying the household's economic status.

The 1997 IDHS was specifically designed to meet the following objectives: - Provide data concerning fertility, family planning, maternal and child health, maternal mortality, and awareness of AIDS that can be used by program managers, policymakers, and researchers to evaluate and improve existing programs - Provide data about availability of family planning and health services, thereby offering an opportunity for linking women's fertility, family planning, and child care behavior with the availability of services - Provide household expenditure data that which can be used to identify the household's economic status - Provide data that can be used to analyze trends over time by examining many of the same fertility, mortality, and health issues that were addressed in the earlier surveys (1987 NICPS, 1991 IDHS and 1994 IDHS) - Measure changes in fertility and contraceptive prevalence rates and at the same time study factors that affect the changes, such as marriage patterns, urban/rural residence, education, breastfeeding habits, and the availability of contraception - Measure the development and achievements of programs related to health policy, particularly those concerning the maternal and child health development program implemented through public health clinics in Indonesia - Provide indicators for classifying families according to their welfare status.

Geographic coverage

National

Analysis unit

• Household
• Children under five years
• Women age 15-49
• Men

Kind of data

Sample survey data

Sampling procedure

Indonesia is divided into 27 provinces. For the implementation of its family planning program, the National Family Planning Coordinating Board (NFPCB) has divided these provinces into three regions as follows:

• Java-Bali: DKI Jakarta, West Java, Central Java, DI Yogyakarta, East Java, and Bali
• Outer Java-Bali I: Dista Aceh, North Sumatra, West Sumatra, South Sumatra, Lampung, West Nusa Tenggara, West Kalimantan, South Kalimantan, North Sulawesi, and South Sulawesi
• Outer Java-Ball II: Riau, Jambi, Bengkulu, East Nusa Tenggara, East Timor, Central Kalimantan, East Kalimantan, Central Sulawesi, Southeast Sulawesi, Maluku, and Irian Jaya

The 1990 Population Census of Indonesia shows that Java-Bali accounts for 62 percent of the national population, Outer Java-Bali I accounts for 27 percent, and Outer Java-Bali II accounts for 11 percent. The sample for the 1997 IDHS was designed to produce reliable estimates of fertility, contraceptive prevalence and other important variables for each of the provinces and urban and rural areas of the three regions.

In order to meet this objective, between 1,650 and 2,050 households were selected in each of the provinces in Java-Bali, 1,250 to 1,500 households in the ten provinces in Outer Java-Bali I, and 1,000 to 1,250 households in each of the provinces in Outer Java-Bali II, for a total of 35,500 households. With an average of O.8 ever-married women 15-49 per household, the sample was expected to yield approximately 28,000 women eligible for the individual interview.

Note: See detailed description of sample design in APPENDIX A of the survey report.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 1997 IDHS used three questionnaires: the household questionnaire, the questionnaire on family welfare, and the individual questionnaire for ever-married women 15-49 years old. The general household and individual questionnaires were based on the DHS Model "A" Questionnaire, which is designed for use in countries with high contraceptive prevalence. Additions and modifications to the model questionnaire were made in order to provide detailed information specific to Indonesia. The questionnaires were developed mainly in English and were translated into Indonesian. One deviation from the standard DHS practice is the exclusion of the anthropometric measurement of young children and their mothers. A separate survey carried out by MOH provides this information.

The household questionnaire includes an expenditure schedule adapted from the core Susenas questionnaire model. Susenas is a national household survey carried out annually by CBS to collect data on various demographic and socioeconomic indicators of the population. The family welfare questionnaire was aimed at collecting indicators developed by the NFPCB to classify families according to their welfare status. Families were identified from the list of household members in the household questionnaire. The expenditure module and the family welfare questionnaire were developed in Indonesian.

Cleaning operations

The first stage of data editing was carried out by the field editors who checked the completed questionnaires for thoroughness and accuracy. Field supervisors then further examined the questionnaires. In many instances, the teams sent the questionnaires to CBS through the regency/municipality statistics offices. In these cases, no checking was done by the PSO. In other cases, Technical Coordinators are responsible for reviewing the completeness of the forms. At CBS, the questionnaires underwent another round of editing, primarily for completeness and coding of responses to open-ended questions. The data were processed using microcomputers and the DHS computer program, ISSA (Integrated System for Survey Analysis). Data entry and office editing were initiated immediately after fieldwork began. Simple range and skip errors were corrected at the data entry stage. Data processing was completed by February 1998, and the preliminary report of the survey was published in April 1998.

Response rate

A total of 35,362 households were selected for the survey, of which 34,656 were found. Of the encountered households, 34,255 (99 percent) were successfully interviewed. In these households, 29,317 eligible women were identified, and complete interviews were obtained from 28,810 women, or 98 percent of all eligible women. The generally high response rates for both household and individual interviews were due mainly to the strict enforcement of the rule to revisit the originally selected household if no one was at home initially. No substitution for the originally selected households was allowed. Interviewers were instructed to make at least three visits in an effort to contact the household or eligible woman.

Note: See summarized response rates by place of residence in Table 1.2 of the survey report.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (I) non-sampling errors and (2) sampling errors. Non-sampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 1997 IDHS to minimize this type of error, non-sampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 1997 IDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

A sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95 percent of all possible samples of identical size and design.

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 1997 IDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the 1997 IDHS is the ISSA Sampling Error Module. This module

Abstract

The Palestinian Central Bureau of Statistics (PCBS) strives to keep abreast of developments on the domestic and international arenas and to provide official statistics in all areas pertinent to Palestinian society. The survey of Democratic Governance is a new area in the Palestinian official statistics that came to meet the needs of users and to provide comparable statistics on the regional and international levels.

The Palestinian Central Bureau of Statistics has decided to include Democratic Governance in its program as part of PCBS' efforts to provide comprehensive statistical indicators in specialized subjects. Statistics on Democratic Governance has become one of the main requirements of the development of societies and will serve the needs of users including decision and policy makers.

Statistical indicators on Democratic Governance cover many aspects of social, economic, and environmental life, and go in line with the indicators of the Millennium Development Goals. These indicators provide the basis to monitor the status of human rights and governance in any country as well as support the national social and economic system.

This report addresses the most important results of the Democratic Governance survey that was carried out by the Palestinian Central Bureau of Statistics during the period from 09/02/2010 till 03/05/2010. . The report presents relevant results related to the rule of law in the Palestinian Territory, public office, and election. The results also covers the performance of the Palestinian Legislative Council (PLC), the government, and civil society. In addition, the report presents relevant indicators on the freedom of opinion and expression, freedom of press, access to information, and the freedom to affiliate with and form political parties. In addition, the results cover women's rights, the right to education, health, and labor.

The Palestinian Central Bureau of Statistics hopes that the findings of this report will be effectively utilized to enable decision and policy makers to identify required policies and procedures for further improvement and development and to better serve the Palestinian citizen.

Geographic coverage

All Palestinian households

Analysis unit

Person 18 years or over

Universe

The survey covered all the Palestinian persons 18 years or over who are a usual residence in the Palestinian Territory.

Kind of data

Sample survey data [ssd]

Sampling procedure

Listing of all Enumeration Areas (EAs) that were used in the Population, Housing, and Establishment census 2007. Each Enumeration Area consists, on the average, of 120-150 housing units.

Sample size The sample size of the survey was estimated to about 3000 households in the West Bank and Gaza Strip. Sample design The sample is stratified clustered systematic random sample. The design is comprised of three phases: 1. Random sample of 150 enumeration areas 2. Selection of (20) household from each enumeration area, selected in phase one, using systematic random manner 3. Selection of a person (aged 18 years or more) in the field from the selected households; and KISH TABLES were used in the selection of persons (alternating one male and the next female) to ensure indiscriminate selection.

Sample strata Distribution of the sample was stratified by 1. Governorate (16) 2. Locality Type (Urban, Rural, Camps)

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey questionnaire on Democratic Governance is the main instrument for data collection, and thus its design took into consideration the standard technical specifications to facilitate the collection, processing and analysis of data. Because this type of specialized surveys is new to PCBS, relevant experiences of other countries and international best practices were thoroughly reviewed to ensure the contents and design of the survey's instruments are within international standards. The survey's questionnaire includes the following basic components:

Identification data: The identification data constitutes the key that uniquely identifies each questionnaire. The key consists of the questionnaire' serial number, locality code, and governorate code. The classification of localities is according to the Standard Administrative Classification that was adopted by a national committee composed of representatives of various national institutions, and applied by PCBS in the Population, Housing and Establishment Censuses 2007.

Data quality control: A set of quality controls were developed and incorporated into the different phases of the survey including field operations, office editing, office coding, data processing, and survey documentation.

Survey's main indicators: The first section of the questionnaire includes identification data about the geographical location and the population. Other sections include data about: the rule of law, the right to access public office, election, the performance of the Palestinian Legislative Council (PLC), government and civil institutions, freedom of opinion and expression, the press and the right to information, freedom to affiliate with and form political parties, the right to education, health, employment and housing.

Cleaning operations

Data processing phase includes many interdependent activities that aim to electronically capture the collected data to be ready for analysis. These activities are: 1. Office editing: Questionnaires were reviewed according to rules specified in special editing manual specifically designed for the survey. The purpose of this activity was to ensure that the questionnaires had no consistency errors, and no uncompleted questionnaires. 2. Programming and data entry stage: This stage included preparation of the data entry programs, setting up the data entry control rules to avoid data entry errors, and validation queries to examine the data after its being electronically captured.

Response rate

Response rate was 100% in the Palestinian Territory.

Sampling error estimates

1. Statistical Errors: Sampling rather than comprehensive enumeration has been used to collect data in this survey. Therefore it is liable to two types of errors affecting the quality of survey data, sampling (statistical errors) and non-sampling errors (non-statistical errors). Statistical errors mean the errors resulting from sample designing and this is computed simply. Variance and effect of sample design has been computed for the Palestinian Territory, the West Bank and Gaza Strip.

2. Non-Statistical Errors: Non-statistical errors, on the other hand, could not be determined easily, due to the diversity of sources from which they may arise, e.g., the interviewer, respondent, editor, coder, and data entry operator.

Data appraisal

The data of this survey is of a high quality

Abstract

This survey intends to: -

· Measure the labour force or economically active population size in relation to the general population in the country. · Identify and analyse the factors leading to the emergence and growth of Labour Force in the country. · Monitor the labour force participation. · Identify and measure the informal sector from within the labour force. · Monitor other Key Indicators of the Labour Market such as employment rates,unemployment rates, hours of work, average income and/or wages etc.

Furthermore, the survey seeks to examine the relationships of socio-economic factors such as education, health, social security, employment within the labour force, and more importantly to measure the causes and effects of children’s involvements in economic activities with special focus on the conditions and environment under which affected children operate.

The main objective of the 2012 LFS was to collect data on the social and economic activities of the population, including detailed information on employment, unemployment, underemployment, wages, informal sector, general characteristics of the labour force and economically inactive population. The survey was designed to specifically measure and monitor Key Indicators of the Labour Market (KILM) such as employment levels, unemployment, income and child labour in Zambia. However, indicators on child labour are not part of this 2012 LFS report. There will be a separate report on child labour later. The measurement of the KILM was with a view to informing users and policy-makers for decision-making. The methodology used in carrying out the survey and the design of questionnaire conform to internationally acceptable standards.

Geographic coverage

The 2012 Labour Force Survey (LFS) was a nation-wide survey covering household population in all the ten provinces and, in both rural and urban areas. The survey covered a representative sample of 11, 520 households, which were selected at two stages. In the first stage, 576 Standard Enumeration Areas (SEAs) were selected from a sampling frame developed from the 2010 Census of Population and Housing. In the second stage, households in each of the selected SEA were first listed/updated and then 20 households for enumeration were selected. The total sample of 11,520 households was first allocated between rural, urban and the provincial domains in proportion to the population of each domain according to the 2010 Census results.

Analysis unit

The unit of analysis was Households and Individuals ( Men and Women of 5 years and older). Additionally, the analysis focused on national level at both rural/urban and provincial level. The micro-data has provisions to generate major indicators at district and constituency levels. As much as possible the micro-data have also been analyzed by sex and age.

Universe

The survey covered all de jure household members (usual residents) in non-institutionalised housing units, all women and men aged 5 years and older

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample was designed to allow separate estimates at national level for rural and urban areas. Further, it also allowed for provincial estimates. A cluster, which is equivalent to a Standard Enumeration Area (SEA), was the primary sampling unit in the ?rst stage. In the second stage, a household was a sampling unit for enumeration purposes. Zambia is administratively divided into ten provinces. Each province is in turn subdivided into districts. For statistical purposes each district is subdivided into Census Supervisory Areas (CSAs) and these are in turn demarcated into Standard Enumeration Areas (SEAs). The Census mapping exercise of 2006-2010 in preparation for the 2010 Census of Population and Housing, demarcated the CSAs within wards, wards within constituencies and constituencies within districts. As at the time of the survey, Zambia had 74 districts, 150 constituencies, 1,430 wards and about 25,000 SEAs. Information borne on the list of SEAs from the sampling frame also includes number of households and the population size as at the last update of the SEA. The number of households determined the selection of primary sampling units (PSU). The SEAs are stratifed as urban and rural. The total sample of 11,520 households was first allocated between rural, urban and the provincial domains in proportion to the population of each domain according to the 2010 Census results. The proportional allocation does not however allow for reliable estimates for lower domains like district, ward or constituency. Adjustments to the proportional allocation of the sample were made to allow for reasonable comparison to be achieved between strata or domains. Therefore, disproportionate allocation was adopted, for the purpose of maximizing the precision of survey estimates. The disproportionate allocation is based on the optimal square root allocation method designed by Leslie Kish. The sample was then selected using a stratifed two-stage cluster design.

Sampling deviation

There was no deviation from sample design.

Mode of data collection

Face-to-face [f2f]

Research instrument

Two types of questionnaires (Form A and Forma B) were used to collect data from the household members. Form A was used in the first stage for listing purposes while Form B was used in the second stage for collecting detailed data from the selected households. It was a requirement for each household member to provide responses during the face-to-face interview to the questions that were asked.

The main questionnaire has ten sections namely:

a. Demographic Characteristics b. Education, Literacy and Skills Training c. Economic Activity d. Employment e. Hours of Work and Underemployment f. Income g. Unemployment/Job Search h. Previous Work Experience i. Household Chores j. Working Conditions (i.e. Forced labour)

Cleaning operations

Data editing took place at a number of stages throughout the processing. These included:

1. Field editing
2. Office editing and coding
3. During data entry
4. Structure checking and completeness
5. Secondary editing
6. Strucural checking of SAS data files

Response rate

At the end of the field work and editing in the provinces, a total of at least 11,000 of completed questionnaires, representing a 99.8 percent response rate were sent to Head Office for data processing.

Data appraisal

A series of data quality tables and graphs are available to review the quality of the data and in addition to this, external resources such as the 2012 Labour Force Survey report has been attached.

Abstract

The Central Statistical Agency (CSA) has been providing labour force and related data at different levels and with varying details in their content. These include the 1976 Addis Ababa Manpower and Housing Sample Survey, the 1978 Survey on Population and Housing Characteristics of Seventeen Major Towns, the 1980/81 and 1987/88 Rural Labour Force Surveys, the 1984 and 1994 Population and Housing Census, and 2003 and 2004 Urban Bi-annual Employment Unemployment Survey. The 1996 and 2002 Surveys of Informal Sector and most of the household surveys undertaken by the Agency also provide limited information on the area. Still pieces of information in relation to that of employment can also be derived from small, large and medium scale establishment surveys. Till the 1999 Labour Force Survey (LFS) there hasn't been a comprehensive national labour force survey representing both urban and rural areas. This 2005 LFS is the second in the series.

The 2005 National Labor Force Survey was designed to provide statistical data on the size and characteristics of the economically active and the non-active population of the country, both in urban and rural areas. The data will be useful for policy makers, planners, researchers, and other institutionsand individuals engaged in the design, implementation and monitoring of human resource development plans, programs and projects. The specific objectives of this survey are to: - generate data on the size of work force that is available to participate in production process; - determine the status and rate of economic participation of different sub-groups of the population; - identify those who are actually contributing to the economic development (i.e., employed) and those out of the sphere; - determine the size and rate of unemployed population; - provide data on the structure of the working population; - obtain information about earnings from paid employment; - identify the distribution of employed population working in the formal/informal enterprises; and - provide time series data and trace changes over time.

Geographic coverage

Like the National Labour Force Survey of 1999, it covered both the urban and rural areas of all regions. Exceptions are Gambella Region, where only the urban parts of the region are covered, Affar Region with only zone one and zone three were covered and Somali Region where only Shinile, Jijiga and Liben zones were covered.

Analysis unit

• HouseHold (HH)
• Household Member

Universe

The survey is mainly aimed at providing information on the economic characteristics of the population aged 10 years and over,

Kind of data

Données échantillonées [ssd]

Sampling procedure

2.1 COVERAGE The 2005 (1997 E.C) Labour Force Sample Survey covered all rural and urban parts of the country except all zones of Gambella Region excluding Gambella town, and the non-sedentary population of three zones of Afar & six zones of Somali regions. In the rural parts of the country it was planned to cover 830 Enumeration Areas (EAs) and 24,900 households. All planned EAs were actually covered by the survey; however, due to various reasons it was not possible to conduct the survey in 39 sample households. Ultimately 100.00 % EAs and 99.84% household were covered by the survey. Regarding urban parts of the country it was initially planned to cover 995 EAs and 29,850 households. Eventually 100% of the EAs and 99.24% of the households were successfully covered by the survey.

2.2 SAMPLING FRAME The list of households obtained from the 2001/2 Ethiopian Agricultural Sample Enumeration (EASE) is used to select EAs from the rural part of the country. For urban sample EAs on the other hand the list consisting of households by EA, which was obtained from the 2004 Ethiopian Urban Economic Establishment Census, (EUEEC) was used as a frame. A fresh list of households from each urban and rural EA was prepared at the beginning of the survey period. The list was then used as a frame for selecting sample households of each EAs.

2.3 SAMPLE DESIGN For the purpose of the survey the country was divided into three broad categories. That is; rural, major urban center and other urban center categories.

Category I: Rural: - This category consists of the rural areas of 8 regions and two city administrations found in the country. Regarding the survey domains, each region or city administration was considered to be a domain (Reporting Level) for which major findings of the survey are reported. This category totally comprises 10 reporting levels. A stratified two-stage cluster sample design was used to select samples in which the primary sampling units (PSUs) were EAs. Households per sample EA were selected as a second Stage Sampling Unit (SSU) and the survey questionnaire finally administered to all members of sample households

Category II:- Major urban centers:- In this category all regional capitals and 15 other major urban centers that had a population size of 40,000 or more in 2004 were included. Each urban center in this category was considered as a reporting level. The category has totally 26 reporting levels. In this category too, in order to select the samples, a stratified two-stage cluster sample design was implemented. The primary sampling units were EAs. Households from each sample EA were then selected as a Second Stage Unit.

Category III: - Other urban centers: Urban centers in the country other than those under category II were grouped into this category. Excluding Gambella a domain of other urban centers is formed for each region. Consequently 7 reporting levels were formed in this category. Harari, Addis Ababa and Dire Dawa do not have urban centers other than that grouped in category II. Hence, no domain was formed for these regions under this category. Unlike the above two categories a stratified three stage cluster sample design was adopted to select samples from this category. The primary sampling units were urban centers and the second stage sampling units were EAs. Households from each EA were finely selected at the third stage and the survey questionnaires administered for all of them.

To have more informations on th sampling view the report (Page 8)

Mode of data collection

Interview face à face [f2f]

Research instrument

The questionnaire was organized in to five sections; Section - 1 Area identification of the selected household: this section dealt with area identification of respondents such as region, zone, wereda, etc.,

Section -2 Socio- demographic characteristics of households: it consisted of the general sociodemographic characteristics of the population such as age, sex, education, status and type of disability, status and types of training, marital status and fertility questions.

Section - 3 Productive activities during the last seven days: this section dealt with a range of questions which helps to see the status and characteristics of employed persons in a current status approach such as hours of work in productive activities, occupation, industry, employment status, and earnings from employment. Also questions included are hours spent on fetching water, collection of firewood, and domestic chores and place of work.

Section - 4 Unemployment and characteristics of unemployed persons: this section focused on the size and characteristics of the unemployed population.

Section - 5 Economic activities during the last twelve months: this section covered the usual economic activity status (refereeing to the long reference period), number of weeks of employment /unemployment/inactive, reasons for inactivity, employment status, whether working in the agricultural sector or not and the proportion of income gainedfrom non-agricultural sector.

The questionnaire used in the field for data collection was prepared in Amharic language. Most questions have pre-coded answers.

Cleaning operations

During the fieldwork, the field supervisors, statisticians and the heads of branch statistical offices have checked the filled-in questionnaires and carried out some editing. However, the major editing and coding operation was carried out at the head office. All urban questionnaires were subjected to complete manual editing, while most of rural questionnaires were partially edited. All the edited questionnaires were again fully verified and checked for consistency before they were submitted to the data entry. This system of data processing was followed on the assumption that, there is less complication of activities in rural areas than urban centers.

After the data was entered, it was again verified using the computer edit specification prepared earlier for this purpose, the entered data were checked for consistencies and then computer editing or data cleaning was made by referring back to the filled-in questionnaire. This is an important part of data processing operation in attaining the required level of data quality. Consistency checks and re-checks were also made based on tabulation results. Computer programs used in data entry, machine editing and tabulation were prepared using the Integrated Microcomputer Processing System (IMPS).

Abstract

The population and housing census (PHC) is the unique source of reliable and comprehensive data about the size of population and also on major socio-economic & socio-demographic characteristics of the country. It provides data on geographic and administrative distribution of population and household in addition to the demographic and socio-economic characteristics of all the people in the country. Generally, it provides for comparing and projecting demographic data, social and economic characteristics, as well as household and housing conditions at all levels of the country’s administrative units and dimensions: national, regional, districts and localities. The data from the census is classified, tabulated and disseminated so that researchers, administrators, policy makers and development partners can use the information in formulating and implementing various multi-sectorial development programs at the national and community levels. Data on all key variables namely area, household, population, economic activity, literacy and education, fertility and child survival, housing conditions and sanitation are collected and available in the census data. The 2021 PHC in Ghana had an overarching goal of generating updated demographic, social and economic data, housing characteristics and dwelling conditions to support national development planning activities.

Geographic coverage

National Coverage , Region , District

Analysis unit

• Individuals
• Households
• Emigrants
• Absentee population
• Mortality
• Type of residence (households and non household)

Universe

All persons who spent census night (midnight of 27th June 2021) in Ghana

Kind of data

Census/enumeration data [cen]

Sampling procedure

This 10% sample data for the 2021 PHC is representative at the district/subdistrict level and also by the urban rural classification.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

GSS developed two categories of instruments for the 2021 PHC: the listing form and the enumeration instruments. The listing form was only one, while the enumeration instruments comprised six questionnaires, designated as PHC 1A, PHC 1B, PHC 1C, PHC 1D, PHC 1E and PHC 1F. The PHC 1A was the most comprehensive with the others being its subsets.

1. Listing Form: The listing form was developed to collect data on type of structures, level of completion, whether occupied or vacant and use(s) of the structures. It was also used to collect information about the availability, number and types of toilet facilities in the structures. It was also used to capture the number of households in a structure, number of persons in households and the sex of the persons residing in the households if occupied. Finally, the listing form was used to capture data on non-household populations such as the population in institutions, floating population and sex of the non-household populations.

2. PHC 1A: The PHC 1A questionnaire was used to collect data from all households in the country. Primarily, it was used to capture household members and visitors who spent the Census Night in the dwelling of the household, and their relationship with the head of the household. It was also used to collect data on homeless households. Members of the households who were absent were enumerated at the place where they had spent the Census Night. The questionnaire was also used to collect the following household information: emigration; socio-demographic characteristics (sex, age, place of birth and enumeration, survival status of parents, literacy and education; economic activities; difficulty in performing activities; ownership and usage of information, technology and communication facilities; fertility; mortality; housing characteristics and conditions and sanitation.

3. PHC 1B: The PHC 1B questionnaire was used to collect data from persons in stable institutions comprising boarding houses, hostels and prisons who were present on Census Night. Other information that was captured with this instrument are socio-demographic characteristics, literacy and education, economic activities, difficulty in performing activities; ownership and usage of information, technology and communication facilities; fertility; mortality; housing characteristics and conditions and sanitation.

4. PHC 1C: The PHC 1C questionnaire was used to collect data from persons in “unstable” institutions such as hospitals and prayer camps who were present at these places on Census Night. The instrument was used to capture only the socio-demographic characteristics of individuals.

5. PHC 1D: The PHC 1D questionnaire was used to collect data from the floating population. This constitutes persons who were found at airports, seaports, lorry stations and similar locations waiting for or embarking on long-distance travel, as well as outdoor sleepers on Census Night. The instrument captured the socio-demographic information of individuals.

6. PHC 1E: All persons who spent the Census Night at hotels, motels and guest houses were enumerated using the PHC 1E. The content of the questionnaire was similar to that of the PHC 1D.

7. PHC 1F: The PHC 1F questionnaire was administered to diplomats in the country.

Cleaning operations

The Census data editing was implemented at three levels: 1. data editing by enumerators and supervisors during data collection 2. data editing was done at the regional level by the regional data quality monitors during data collection 3. Final data editing was done at the national level using the batch edits in CSPro and STATA Data editing and cleaning was mainly digital.

Response rate

100 percent

Data appraisal

A post Enumeration Survey (PES) was conducted to assess the extent of coverage and content error.

Abstract

The presence of adequate and current statistical data in various economic sectors that are considered essential for development planning, socio-economic policy formulation and economic analysis is vital in promoting the economic development of a country. Based on this general objective the Central Statistical Agency (CSA) has been conducting surveys of various economic activities, of which, the annual Large and Medium Scale Manufacturing Industries survey is one.

Manufacturing is defined here according to International Standard Industrial Classification (ISIC Revision-3) as "the physical or chemical transformation of materials or components into new products, whether the work is performed by power-driven machines or by hand, whether it is done in a factory or in the worker's home, and whether the products are sold at wholesale or retail. The assembly of the component parts of manufactured products is also considered as manufacturing activities."

CSA has been publishing results of the survey of Manufacturing and Electricity Industries on annual basis since 1968 E .C. to provide users with reliable, comprehensive and timely statistical data on theses sectors. In this respect, this survey, which is conducted and annual basis, is the principal source of industrial statistics on large and medium scale manufacturing industries in the country.

The general objective of Manufacturing and Electricity Industries Survey is to collect basic quantitative information on the country's manufacturing that is essential for planning, policy making, monitoring, System of National Accounts (SNA) and evaluation of the performance and structure of the manufacturing industries, and ensure the smooth supply of inputs and production of commodities and deal with the problems that crop up in the sector.

The specific objectives of Manufacturing and Electricity Industries Survey are to gauge the total number of proprietors/manufacturing industries, employment, income obtained, and volume and value of production and inputs, value added and other variables of interest. The specific objectives also enable to reveal the distribution of manufacturing industries across the regions and major towns of the country, the sector's contribution to the economy, the investment situation, etc.

Geographic coverage

National

Analysis unit

Establishment/ Enterprise

Universe

The universe of the large and medium scale manufacturing survey is confined to those establishments which engaged 10 persons and above and use power-driven machines and covers both public and private industries in all Regions of the country.

Kind of data

Census/enumeration data [cen]

Sampling procedure

Not applicable - the survey enumerated all manufacturing industries/ enterprises that qualified as large and medium manufacturing industry category.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questinnaire contains the following sections/ items:

Section 1.1 - Address of the establishments: This section has variables that identify the questionnaire uniquely. The variables are; Killil, Zone, Wereda, Town, Higher, Kebele, House no, Year, ISIC, Establishment number, Telephone number and P.O. Box codes or numbers.

Section 1.2 - Address of Head Office if different from Factory: In this section information about the factory head office is collected (if the factory is separated from the head office). The variables used to collect the information are; Killil, Zone, Wereda, Town, Higher, Kebele, House no, Telephone no and P.O. Box.

Section 2 - Basic Information about the establishment: This section has questions related to basic information about the establishment.

Section 3.1 - Number of Persons Engaged: This section has variables (questions) that used to collect establishment's employees number by employees occupation.

Section 3.2 - Wages and Salaries and Other Employee Benefits Paid: This section has variables related to wages and other employees' benefits by employee occupation.

Section 3.3 - Number of Permanent Employees by Basic Salary Group: This section has variables related to salary groups by sex of employees

Section 4.1 - Products and By-products: This section has questions related to product produced, produced quantity and sales.

Section 4.2 - Service and Other Receipts: Contains questions related to income from different source other than selling the products.

Section 5 - Value of Stocks: Contains questions that related to information about materials in the stock.

Section 6.1 - Cost and Quantity of Raw Materials, Parts and Containers Used: This section has questions related to principal raw materials, raw material type, quantity, value and source (local or imported).

Section 6.2 - Other Industrial Costs: This section has questions related to other industrial costs including cost of energy and other expenses.

Section 6.3 - Other Non-industrial Expenses: Contains questions related to non-industrial expenses like license fee, advertising, stationary, etc.

Section 6.4 - Taxes Paid: This section has questions related to taxes like indirect tax and income tax.

Section 7.1 - Type and Value of Fixed Assets: This section has questions related to fixed assets of the establishment.

Section 7.2 - Annual Investment by Type and Source: This section has questions related to investment on fixed assets and working capitals.

Section 8.1 - Annual Production at Full Capacity: This section has questions about quantity and value of products if the establishment uses its full capacity.

Section 8.2 - Estimated Value and Quantity of Raw Materials Needed, at Full Capacity: This section has questions about the estimate of quantity and value of raw materials that needed to function at full capacity.

Section 8.3 - The percentage of the 1994 production as compared to the factory's production at full capacity

Section 8.4 - The three major problems that prevented the establishment from operating with full capacity.

Section 8.5 - Reason for lack of market if there is a problem of getting market.

Section 8.6 - About whether the factory made applied for a loan.

Section8.7 - Reason for not solving shortage of working capital if there is a shortage of working capital.

Section 8.8 - The three major problems that are facing the establishment at present.

Section 8.9 - Whether the factory faced problem during export.

Section 8.10 - Three major problems faced during export.

Cleaning operations

Editing, Coding and Verification: A number of quality control steps were taken to ensure the quality of data. The first step taken in this direction was, to revise the questionnaire, to make it easier for internal consistency checking or editing, both at field and office level. Furthermore, based on this revised questionnaire, revised instruction manual with field editing procedures were prepared in Amharic for both enumerators and supervisors (field editors). Using this manual, some editing and coding were carried out by field editors during the data collection stage.

After the majority of the completed questionnaires were brought back to head office, final editing, coding and verification were performed by editors, statistical technicians and statisticians. Finally, the edited and coded questionnaires were checked and verified by other senior professionals.

Data Entry, Cleaning and Tabulation The data were entered and verified on personal computers using CSpro (Census and Survey Processing System) Software. Twelve CSA data entry staff and one data cleaner participated in this activity for fifteen days with close supervision of the activities by two professionals. Then, the data entered were cleaned using personal computers in combination with manual cleaning for some serious errors. Finally, the tabulation of the results was processed using the same software by one programmer with technical assistance from Industry, Trade and Services Statistics Department staff.

Abstract

The presence of adequate and current statistical data in various economic sectors that are considered essential for development planning, socio-economic policy formulation and economic analysis is vital in promoting the economic development of a country. Based on this general objective, the Central Statistical Authority (CSA) has been conducting surveys of various economic activities of which the annual Large and Medium Scale Manufacturing Industries survey is one.

Manufacturing is defined here according to International Standard Industrial Classification as "the physical or chemical transformation of materials or components into new products, whether the work is performed by power-driven machines or by hand, whether it is done in a factory or in the worker's home, and whether the products are sold at wholesale or retail. The assembly of the component parts of manufactured products is also considered as manufacturing activities."

The survey questionnaire is designed to answer questions about number of establishments, number of persons engaged, wages and salaries paid by industrial group, sex, nationality and occupation, paid-up capital, gross value of production, industrial and non-industrial costs. value added, operating surplus, quantity of production and raw materials conusmed, fixed assets, investment and production capacity and etc..

The main objectives of the annual survey of Large and Medium Scale Manufacturing and Electricity Industries are to: 1.Obtain basic statistical data that are essential for policy makers, planners and researchers by major industrial group. 2.Collect basic quantitative information on employment, volume of quantitative information on employment, volume of production and raw materials, structure and performance of the country's Large and Medium Scale Manufacturing and Electricity Industries. 3.Compile statistical data which will be an input to the System of National Accounts (SNA), on Large and Medium Scale Manufacturing and Electricity establishments as a whole and by major industrial group. 4.Obtain the number of proprietors engaged in these sectors and find out the major problems that create stumbling blocks for their activities.The identification of the problems is required for planning and executing any type of government intervention program.

Geographic coverage

National

Analysis unit

Establishment

Universe

The universe of the large and medium scale manufacturing survey is confined to those establishments which engaged 10 persons and above and use power-driven machines and covers both public and private industries.

Kind of data

Census/enumeration data [cen]

Sampling procedure

The survey covers all large and medium manufacturing industries which engage 10 persons or more and use power-driven machines

Mode of data collection

Face-to-face [f2f]

Research instrument

The questinnaire contains the following sections/ items:

Section 1.1. Adress of the establishments: This section has varibles that identify the questionnaire uniquely. The variables are; Killil, Zone, Wereda, Town, Higher, Kebele, House no, Year, ISIC, Establishmnet no, Eelephone no and P.O.Box codes or numbers.

Section 1.2. Address of Head Office if Separated From Factory: In this section information about factory head office is collected (if the factory is separated from the head office). The varibles used to collect the information are; Killil, Zone, Wereda, Town, Higher, Kebele, House no, Telephone no and P.O.Box.

Section 2. Basic Information About The Establishment: This section has questions related to basic information about the establishment.

Section 3.1. Number of Persons Engaged: This section has variables (questions) that used to collect establishment's employees number by employees occupation.

Section 3.2. Wages and Salaries and Other Employee Benefits Paid: This section has variables related to wages and other employees benefits by employee occupation.

Section 3.3. Number of Permanent Employees by Basic Salary Group: This section has variables related to salary groups by sex of employees

Section 4.1. Products and By-products: This section has questions related to product produced, produced quantity and sales.

Section 4.2. Service and Other Receipts: Contains questions related to income from different source other than selling the products.

Section 5. Value of Stocks: Contains questions that related to information about materials in the stock.

Section 6.1. Cost and Quantity of Raw Materials, Parts and Containers Used: This section has questions related to principal raw materials, raw material type, quantity, value and source (local or imported).

Section 6.2. Other Industrial Costs: This sections has questions related to other industrial costs including cost of energy and other expenses.

Section 6.3. Other Non-industrial Expenses: Contains questions related to non-industrial expenses like license fee, advertising, stationary, etc.

Section 6.4. Taxes Paid: This section has questions related to taxes like indirect tax and income tax.

Section 7.1. Type and Value of Fixed Assets: This section has questions related to fixed assets of the establishment.

Section 7.2. Annual Investment by Type and Source: This section has questions related to investment on fixed assets and working capitals.

Section 8.1. Annual Production at Full Capacity: This section has questions about quantity and value of products if the establishment uses its full capacity.

Section 8.2. Estimated Value and Quantity of Raw Materials Needed, at Full Capacity: This section has questions about the estimate of quantity and value of raw materials that needed to function at full capacity.

Section 8.3. The three major problems that prevented the establishment from operating at full capacity.

Section 8.4. The three major problems that are facing the establishment at present.

Cleaning operations

Editing, Coding and Verification: A number of quality control steps were taken to ensure the quality of data. The first step taken in this direction was, to revise the questionnaire, to make it easier for internal consistency checking or editing, both at field and office level. Furthermore, based on this revised questionnaire, revised instruction manual with field editing procedures were prepared in Amharic for both enumerators and supervisors (field editors). Using this manual, some editing and coding were carried out by field editors during the data collection stage. After the majority of the completed questionnaires were brought back to head office, final editing, coding and verification were performed by 11 editors and 6 statistical technicians and statisticians. Finally, the edited and coded questionnaires were checked and verified by other senior professionals.

Data Entry, Cleaning and Tabulation: The data were entered and verified on personal computers IMPS (Integrated Microcomputer Processing System) Software. Twelve-two CSA data entry staff and one data cleaner participated in this activity for seven days with close supervision of the activities by two professionals. Then, the data entered were cleaned using personal computers in combination with manual cleaning for some serious errors. Finally, the tabulation of the results was processed using the IMPS (Integrated Microcomputer Processing System) software by two programmer with technical assistance from Industry, Trade and Services Statistics Department staff.

Abstract

The presence of adequate and current statistical data in various economic sectors that are considered essential for development planning, socio-economic policy formulation and economic analysis is vital in promoting the economic development of a country. Based on this general objective, the Central Statistical Authority (CSA) has been conducting surveys of various economic activities of which the annual Large and Medium Scale Manufacturing Industries survey is one.

Manufacturing is defined here according to International Standard Industrial Classification as "the physical or chemical transformation of materials or components into new products, whether the work is performed by power-driven machines or by hand, whether it is done in a factory or in the worker's home, and whether the products are sold at wholesale or retail. The assembly of the component parts of manufactured products is also considered as manufacturing activities."

The survey questionnaire is designed to answer questions about number of establishments, number of persons engaged, wages and salaries paid by industrial group, sex, nationality and occupation, paid-up capital, gross value of production, industrial and non-industrial costs. value added, operating surplus, quantity of production and raw materials conusmed, fixed assets, investment and production capacity and etc..

The main objectives of the annual survey of Large and Medium Scale Manufacturing and Electricity Industries are to: 1.Obtain basic statistical data that are essential for policy makers, planners and researchers by major industrial group. 2.Collect basic quantitative information on employment, volume of quantitative information on employment, volume of production and raw materials, structure and performance of the country's Large and Medium Scale Manufacturing and Electricity Industries. 3.Compile statistical data which will be an input to the System of National Accounts (SNA), on Large and Medium Scale Manufacturing and Electricity establishments as a whole and by major industrial group. 4.Obtain the number of proprietors engaged in these sectors and find out the major problems that create stumbling blocks for their activities.The identification of the problems is required for planning and executing any type of government intervention program.

Geographic coverage

National

Analysis unit

Establishment

Universe

The universe of the large and medium scale manufacturing survey is confined to those establishments which engaged 10 persons and above and use power-driven machines and covers both public and private industries.

Kind of data

Census/enumeration data [cen]

Sampling procedure

The survey covers all large and medium manufacturing industries which engage 10 persons or more and use power-driven machines

Mode of data collection

Face-to-face [f2f]

Research instrument

The questinnaire contains the following sections/ items:

Section 1.1. Adress of the establishments: This section has varibles that identify the questionnaire uniquely. The variables are; Killil, Zone, Wereda, Town, Higher, Kebele, House no, Year, ISIC, Establishmnet no, Eelephone no and P.O.Box codes or numbers.

Section 1.2. Address of Head Office if Separated From Factory: In this section information about factory head office is collected (if the factory is separated from the head office). The varibles used to collect the information are; Killil, Zone, Wereda, Town, Higher, Kebele, House no, Telephone no and P.O.Box.

Section 2. Basic Information About The Establishment: This section has questions related to basic information about the establishment.

Section 3.1. Number of Persons Engaged: This section has variables (questions) that used to collect establishment's employees number by employees occupation.

Section 3.2. Wages and Salaries and Other Employee Benefits Paid: This section has variables related to wages and other employees benefits by employee occupation.

Section 3.3. Number of Permanent Employees by Basic Salary Group: This section has variables related to salary groups by sex of employees

Section 4.1. Products and By-products: This section has questions related to product produced, produced quantity and sales.

Section 4.2. Service and Other Receipts: Contains questions related to income from different source other than selling the products.

Section 5. Value of Stocks: Contains questions that related to information about materials in the stock.

Section 6.1. Cost and Quantity of Raw Materials, Parts and Containers Used: This section has questions related to principal raw materials, raw material type, quantity, value and source (local or imported).

Section 6.2. Other Industrial Costs: This sections has questions related to other industrial costs including cost of energy and other expenses.

Section 6.3. Other Non-industrial Expenses: Contains questions related to non-industrial expenses like license fee, advertising, stationary, etc.

Section 6.4. Taxes Paid: This section has questions related to taxes like indirect tax and income tax.

Section 7.1. Type and Value of Fixed Assets: This section has questions related to fixed assets of the establishment.

Section 7.2. Annual Investment by Type and Source: This section has questions related to investment on fixed assets and working capitals.

Section 8.1. Annual Production at Full Capacity: This section has questions about quantity and value of products if the establishment uses its full capacity.

Section 8.2. Estimated Value and Quantity of Raw Materials Needed, at Full Capacity: This section has questions about the estimate of quantity and value of raw materials that needed to function at full capacity.

Section 8.3. The three major problems that prevented the establishment from operating at full capacity.

Section 8.4. The three major problems that are facing the establishment at present.

Cleaning operations

Editing, Coding and Verification: A number of quality control steps were taken to ensure the quality of data. The first step taken in this direction was, to revise the questionnaire, to make it easier for internal consistency checking or editing, both at field and office level. Furthermore, based on this revised questionnaire, revised instruction manual with field editing procedures were prepared in Amharic for both enumerators and supervisors (field editors). Using this manual, some editing and coding were carried out by field editors during the data collection stage. After the majority of the completed questionnaires were brought back to head office, final editing, coding and verification were performed by 9 statisticians and statistical technicians and 10 editors. Finally, the edited and coded questionnaires were checked and verified by other senior professionals.

Data Entry, Cleaning and Tabulation: The data were entered and verified on personal computers IMPS (Integrated Microcomputer Processing System) Software. Twelve CSA data entry staff and one data cleaner participated in this activity for fifteen days with close supervision of the activities by two professionals. Then, the data entered were cleaned using personal computers in combination with manual cleaning for some serious errors. Finally, the tabulation of the results was processed using the IMPS (Integrated Microcomputer Processing System) software by one programmer with technical assistance from Industry, Trade and Services Statistics Department staff.