Abstract

The Tanzania Demographic and Health Survey (TDHS) is part of the worldwide Demographic and Health Surveys (DHS) programme, which is designed to collect data on fertility, family planning, and maternal and child health.

The primary objective of the 1999 TRCHS was to collect data at the national level (with breakdowns by urban-rural and Mainland-Zanzibar residence wherever warranted) on fertility levels and preferences, family planning use, maternal and child health, breastfeeding practices, nutritional status of young children, childhood mortality levels, knowledge and behaviour regarding HIV/AIDS, and the availability of specific health services within the community.1 Related objectives were to produce these results in a timely manner and to ensure that the data were disseminated to a wide audience of potential users in governmental and nongovernmental organisations within and outside Tanzania. The ultimate intent is to use the information to evaluate current programmes and to design new strategies for improving health and family planning services for the people of Tanzania.

Geographic coverage

National. The sample was designed to provide estimates for the whole country, for urban and rural areas separately, and for Zanzibar and, in some cases, Unguja and Pemba separately.

Analysis unit

• Households
• Children under five years
• Women age 15-49
• Men age 15-59

Kind of data

Sample survey data

Sampling procedure

The TRCHS used a three-stage sample design. Overall, 176 census enumeration areas were selected (146 on the Mainland and 30 in Zanzibar) with probability proportional to size on an approximately self-weighting basis on the Mainland, but with oversampling of urban areas and Zanzibar. To reduce costs and maximise the ability to identify trends over time, these enumeration areas were selected from the 357 sample points that were used in the 1996 TDHS, which in turn were selected from the 1988 census frame of enumeration in a two-stage process (first wards/branches and then enumeration areas within wards/branches). Before the data collection, fieldwork teams visited the selected enumeration areas to list all the households. From these lists, households were selected to be interviewed. The sample was designed to provide estimates for the whole country, for urban and rural areas separately, and for Zanzibar and, in some cases, Unguja and Pemba separately. The health facilities component of the TRCHS involved visiting hospitals, health centres, and pharmacies located in areas around the households interviewed. In this way, the data from the two components can be linked and a richer dataset produced.

See detailed sample implementation in the APPENDIX A of the final report.

Mode of data collection

Face-to-face

Research instrument

The household survey component of the TRCHS involved three questionnaires: 1) a Household Questionnaire, 2) a Women’s Questionnaire for all individual women age 15-49 in the selected households, and 3) a Men’s Questionnaire for all men age 15-59.

The health facilities survey involved six questionnaires: 1) a Community Questionnaire administered to men and women in each selected enumeration area; 2) a Facility Questionnaire; 3) a Facility Inventory; 4) a Service Provider Questionnaire; 5) a Pharmacy Inventory Questionnaire; and 6) a questionnaire for the District Medical Officers.

All these instruments were based on model questionnaires developed for the MEASURE programme, as well as on the questionnaires used in the 1991-92 TDHS, the 1994 TKAP, and the 1996 TDHS. These model questionnaires were adapted for use in Tanzania during meetings with representatives from the Ministry of Health, the University of Dar es Salaam, the Tanzania Food and Nutrition Centre, USAID/Tanzania, UNICEF/Tanzania, UNFPA/Tanzania, and other potential data users. The questionnaires and manual were developed in English and then translated into and printed in Kiswahili.

The Household Questionnaire was used to list all the usual members and visitors in the selected households. Some basic information was collected on the characteristics of each person listed, including his/her age, sex, education, and relationship to the head of the household. The main purpose of the Household Questionnaire was to identify women and men who were eligible for individual interview and children under five who were to be weighed and measured. Information was also collected about the dwelling itself, such as the source of water, type of toilet facilities, materials used to construct the house, ownership of various consumer goods, and use of iodised salt. Finally, the Household Questionnaire was used to collect some rudimentary information about the extent of child labour.

The Women’s Questionnaire was used to collect information from women age 15-49. These women were asked questions on the following topics: · Background characteristics (age, education, religion, type of employment) · Birth history · Knowledge and use of family planning methods · Antenatal, delivery, and postnatal care · Breastfeeding and weaning practices · Vaccinations, birth registration, and health of children under age five · Marriage and recent sexual activity · Fertility preferences · Knowledge and behaviour concerning HIV/AIDS.

The Men’s Questionnaire covered most of these same issues, except that it omitted the sections on the detailed reproductive history, maternal health, and child health. The final versions of the English questionnaires are provided in Appendix E.

Before the questionnaires could be finalised, a pretest was done in July 1999 in Kibaha District to assess the viability of the questions, the flow and logical sequence of the skip pattern, and the field organisation. Modifications to the questionnaires, including wording and translations, were made based on lessons drawn from the exercise.

Response rate

In all, 3,826 households were selected for the sample, out of which 3,677 were occupied. Of the households found, 3,615 were interviewed, representing a response rate of 98 percent. The shortfall is primarily due to dwellings that were vacant or in which the inhabitants were not at home despite of several callbacks.

In the interviewed households, a total of 4,118 eligible women (i.e., women age 15-49) were identified for the individual interview, and 4,029 women were actually interviewed, yielding a response rate of 98 percent. A total of 3,792 eligible men (i.e., men age 15-59), were identified for the individual interview, of whom 3,542 were interviewed, representing a response rate of 93 percent. The principal reason for nonresponse among both eligible men and women was the failure to find them at home despite repeated visits to the household. The lower response rate among men than women was due to the more frequent and longer absences of men.

The response rates are lower in urban areas due to longer absence of respondents from their homes. One-member households are more common in urban areas and are more difficult to interview because they keep their houses locked most of the time. In urban settings, neighbours often do not know the whereabouts of such people.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1) 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 TRCHS to minimise this type of error, nonsampling 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 TRCHS 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 TRCHS sample is the result of a two-stage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the TRCHS is the ISSA Sampling Error Module (SAMPERR). This module used the Taylor linearisation method of variance estimation for survey estimates that are means or proportions. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rate

Note: See detailed sampling error calculation in the APPENDIX B

Abstract

The study included four separate surveys:

1. The LSMS survey of general population of Serbia in 2002

2. The survey of Family Income Support (MOP in Serbian) recipients in 2002 These two datasets are published together.

3. The LSMS survey of general population of Serbia in 2003 (panel survey)

4. The survey of Roma from Roma settlements in 2003 These two datasets are published together separately from the 2002 datasets.

Objectives

LSMS represents multi-topical study of household living standard and is based on international experience in designing and conducting this type of research. The basic survey was carried out in 2002 on a representative sample of households in Serbia (without Kosovo and Metohija). Its goal was to establish a poverty profile according to the comprehensive data on welfare of households and to identify vulnerable groups. Also its aim was to assess the targeting of safety net programs by collecting detailed information from individuals on participation in specific government social programs. This study was used as the basic document in developing Poverty Reduction Strategy (PRS) in Serbia which was adopted by the Government of the Republic of Serbia in October 2003.

The survey was repeated in 2003 on a panel sample (the households which participated in 2002 survey were re-interviewed).

Analysis of the take-up and profile of the population in 2003 was the first step towards formulating the system of monitoring in the Poverty Reduction Strategy (PRS). The survey was conducted in accordance with the same methodological principles used in 2002 survey, with necessary changes referring only to the content of certain modules and the reduction in sample size. The aim of the repeated survey was to obtain panel data to enable monitoring of the change in the living standard within a period of one year, thus indicating whether there had been a decrease or increase in poverty in Serbia in the course of 2003. [Note: Panel data are the data obtained on the sample of households which participated in the both surveys. These data made possible tracking of living standard of the same persons in the period of one year.]

Along with these two comprehensive surveys, conducted on national and regional representative samples which were to give a picture of the general population, there were also two surveys with particular emphasis on vulnerable groups. In 2002, it was the survey of living standard of Family Income Support recipients with an aim to validate this state supported program of social welfare. In 2003 the survey of Roma from Roma settlements was conducted. Since all present experiences indicated that this was one of the most vulnerable groups on the territory of Serbia and Montenegro, but with no ample research of poverty of Roma population made, the aim of the survey was to compare poverty of this group with poverty of basic population and to establish which categories of Roma population were at the greatest risk of poverty in 2003. However, it is necessary to stress that the LSMS of the Roma population comprised potentially most imperilled Roma, while the Roma integrated in the main population were not included in this study.

Geographic coverage

The surveys were conducted on the whole territory of Serbia (without Kosovo and Metohija).

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample frame for both surveys of general population (LSMS) in 2002 and 2003 consisted of all permanent residents of Serbia, without the population of Kosovo and Metohija, according to definition of permanently resident population contained in UN Recommendations for Population Censuses, which were applied in 2002 Census of Population in the Republic of Serbia. Therefore, permanent residents were all persons living in the territory Serbia longer than one year, with the exception of diplomatic and consular staff.

The sample frame for the survey of Family Income Support recipients included all current recipients of this program on the territory of Serbia based on the official list of recipients given by Ministry of Social affairs.

The definition of the Roma population from Roma settlements was faced with obstacles since precise data on the total number of Roma population in Serbia are not available. According to the last population Census from 2002 there were 108,000 Roma citizens, but the data from the Census are thought to significantly underestimate the total number of the Roma population. However, since no other more precise data were available, this number was taken as the basis for estimate on Roma population from Roma settlements. According to the 2002 Census, settlements with at least 7% of the total population who declared itself as belonging to Roma nationality were selected. A total of 83% or 90,000 self-declared Roma lived in the settlements that were defined in this way and this number was taken as the sample frame for Roma from Roma settlements.

Planned sample: In 2002 the planned size of the sample of general population included 6.500 households. The sample was both nationally and regionally representative (representative on each individual stratum). In 2003 the planned panel sample size was 3.000 households. In order to preserve the representative quality of the sample, we kept every other census block unit of the large sample realized in 2002. This way we kept the identical allocation by strata. In selected census block unit, the same households were interviewed as in the basic survey in 2002. The planned sample of Family Income Support recipients in 2002 and Roma from Roma settlements in 2003 was 500 households for each group.

Sample type: In both national surveys the implemented sample was a two-stage stratified sample. Units of the first stage were enumeration districts, and units of the second stage were the households. In the basic 2002 survey, enumeration districts were selected with probability proportional to number of households, so that the enumeration districts with bigger number of households have a higher probability of selection. In the repeated survey in 2003, first-stage units (census block units) were selected from the basic sample obtained in 2002 by including only even numbered census block units. In practice this meant that every second census block unit from the previous survey was included in the sample. In each selected enumeration district the same households interviewed in the previous round were included and interviewed. On finishing the survey in 2003 the cases were merged both on the level of households and members.

Stratification: Municipalities are stratified into the following six territorial strata: Vojvodina, Belgrade, Western Serbia, Central Serbia (Šumadija and Pomoravlje), Eastern Serbia and South-east Serbia. Primary units of selection are further stratified into enumeration districts which belong to urban type of settlements and enumeration districts which belong to rural type of settlement.

The sample of Family Income Support recipients represented the cases chosen randomly from the official list of recipients provided by Ministry of Social Affairs. The sample of Roma from Roma settlements was,as in the national survey, a two-staged stratified sample, but the units in the first stage were settlements where Roma population was represented in the percentage over 7%, and the units of the second stage were Roma households. Settlements are stratified in three territorial strata: Vojvodina, Beograd and Central Serbia.

Mode of data collection

Face-to-face [f2f]

Research instrument

In all surveys the same questionnaire with minimal changes was used. It included different modules, topically separate areas which had an aim of perceiving the living standard of households from different angles. Topic areas were the following: 1. Roster with demography. 2. Housing conditions and durables module with information on the age of durables owned by a household with a special block focused on collecting information on energy billing, payments, and usage. 3. Diary of food expenditures (weekly), including home production, gifts and transfers in kind. 4. Questionnaire of main expenditure-based recall periods sufficient to enable construction of annual consumption at the household level, including home production, gifts and transfers in kind. 5. Agricultural production for all households which cultivate 10+ acres of land or who breed cattle. 6. Participation and social transfers module with detailed breakdown by programs 7. Labour Market module in line with a simplified version of the Labour Force Survey (LFS), with special additional questions to capture various informal sector activities, and providing information on earnings 8. Health with a focus on utilization of services and expenditures (including informal payments) 9. Education module, which incorporated pre-school, compulsory primary education, secondary education and university education. 10. Special income block, focusing on sources of income not covered in other parts (with a focus on remittances).

Response rate

During field work, interviewers kept a precise diary of interviews, recording both successful and unsuccessful visits. Particular attention was paid to reasons why some households were not interviewed. Separate marks were given for households which were not interviewed due to refusal and for cases when a given household could not be found on the territory of the chosen census block.

In 2002 a total of 7,491 households were contacted. Of this number a total of 6,386 households in 621 census rounds were interviewed. Interviewers did not manage to collect the data for 1,106 or 14.8% of selected households. Out of this number 634 households or

Abstract

During October 1996 Statistics South Africa recorded the details of people living in more than nine million households in South Africa, as well as those in hostels, hotels and prisons. Census 1996 was the first nation wide census since the splitting up of the country under apartheid after 1970 and sought to apply the same methodology to everyone: visiting the household, and obtaining details about all its members from a representative who was either interviewed, or else filled in the questionnaire in their language of choice.

Geographic coverage

The survey had national coverage

Analysis unit

Households and individuals

Universe

The survey covered households and household members in households in the nine provinces of South Africa.

Kind of data

Sample survey data

Sampling procedure

A sample of 1600 Enumerator Areas (EA's) was produced in conjunction with the sample for the 1996 Population Census post-enumeration survey. A two stage sampling procedure was applied in the following manner.

The first stratification was done by province, as well as by type of EA (formal or informal urban areas, commercial farms, traditional authority areas or other non-urban areas). Originally eight hundred EA's were allocated to each strata by province proportionately. Later some adjustments were made to ensure adequate representation of smaller provinces such as the Northern Cape. Independent systematic samples of EA's were drawn for each stratum within each province. The sampling frame that was used was constructed from the preliminary database of EA's which was established during the demarcation and listing phase of the 1996 population census. In the second phase 10 households were drawn from each EA on the western and eastern side of the EA drawn for the post enumeration survey. This meant 10 households per EA in 1600 different EA's, that is 16 000 households in total.

Mode of data collection

Face-to-face [f2f]

Research instrument

The data files in the October Household Survey 1996 (OHS 1996) correspond to the following sections in the questionnaire:

House: Data from FLAP, Section 1 and Section 7 Person: Data from Section 2 Worker: Data from Section 3 Migrant: Data from Section 4 Death: Data from Section 5 Births: Data from Section 6 - This data had a considerable number of problems and will not be published. Income: Data from Section 7 (included in House) Domestic: Data from Section 8

Data appraisal

Questionnaire: The October Household Survey 1996 questionnaire had incorrect FLAP data. No Population Group question was indicated on the FLAP. DataFirst notified Statistics SA who supplied a corrected questionnaire which is the one now available with the dataset.

Household IDs: In the previous version of the 1996 October Household Survey dataset archived by DataFirst the HHID were not unique. This was corrected in the first version disseminated by DataFirst, version 1. Version 1.1 keeps this correction, but data users should check versions not obtained from DataFirst and replace these with the latest version available from DataFirst.

Linking Files: The Metadata for the OHS 1996 provides an explanation for merging the files in the files in the OHS 1996 dataset: "The data from different files can be linked on the basis of the record identifiers. The record identifiers are composed of the first few fields in each file. Each record contains the three fields Magisterial District, Enumeration area, and Visiting point number. These eleven digits together constitute a unique household identifier. All records with a given household identifier, no matter which file they are in, belong to the same household. For individuals, a further two digits constituting the Person number, when added to the household identifier, creates a unique individual identifier. Again, these can be used to link records from the PERSON and WORK files. The syntax needed to merge information from different files will differ according to the statistical package used (October Household Survey 1996: Metadata: General Notes: 2).” According to the above, to generate household IDs it is necessary to use a combination of magisterial district number (mdnumber), enumeration area number (eanumber) and visiting point number (vpnumber). To generate person IDs it is necessary to use the above with the person number (personnu).

These variables are named as such in the OHS 1996 House, OHS 1996 Births, OHS 1996 Migrant, OHS 1996 Deaths, OHS 1996 Household Income Other, OHS 1996 Other, OHS 1996 Domestic and OHS 1996 Flap data files. However, in the OHS 1996 Worker and OHS 1996 Person data files the variable for magisterial district number is “distr”, the variable for Enumeration Area is “ea” and the variable for visiting point number is called "visp”. The variable for person number in these files is called “respno”.

The metadata provided to DataFirst with this dataset does not discuss these changes.

October Household Survey 1996 Births file: Births data was collected by Section 6 of the OHS 1996 questionnaire, completed for all women younger than 55 years who had ever given birth. The metadata for this survey from Statistics SA states that “This data had a considerable number of problems and will not be published” The dataset provided by DataFirst therefore does not include the original “births” file. Those in possession of this file from unofficial versions of the dataset should note the following problems with the data in the OHS 1996 births file:

Variable name: eegender Question 6.2: Is/was (the child) a boy or a girl? Valid range: 1 (boy) - 2 (girl) Data quality issue: There is a third response value of 0 with no description

Variable name: livinghh Question 6.4: If alive: Is (the child) currently living with this household? Valid range: 1 (yes) - 2 (no) Data quality issue: This variable has an additional response value (0), which has no description

Variable name: agealive Question 6.5: If alive: How old is he/she? This question was asked of all women younger than 55 years who have ever given birth to provide the age of their living children. Data quality issue: responses range from 0-77 for age of child (assuming age 99 is for missing responses) which is outside the plausible range.

Variable name: agenaliv Question 6.6: If dead: How old was (the child) when he/she died? Data quality issue: The format of the age at death variable is not clear

Variable name: datebirt Question 6.7: [All children]: In what year and month was (the child) born? Data quality issue: There are problems with the format of the date of birth variable

Variable name: wherebor Question 6.8: [All children]: Where was (the child) born? Data quality issue: There are only three options for the place of birth in the questionnaire (in a hospital, in a clinic and elsewhere), but the data has 10 response values (0-9) with no explanation for this in the metadata.

Variable name: regstere Question 6.9 [All children] Was the birth registered? Valid range: 1(yes) - 2 (no) Data quality issue: There are 4 response values (0-3) for this variable

Abstract

The basic goal of this survey is to provide the necessary database for formulating national policies at various levels. It represents the contribution of the household sector to the Gross National Product (GNP). Household Surveys help as well in determining the incidence of poverty, and providing weighted data which reflects the relative importance of the consumption items to be employed in determining the benchmark for rates and prices of items and services. Generally, the Household Expenditure and Consumption Survey is a fundamental cornerstone in the process of studying the nutritional status in the Palestinian territory.

The raw survey data provided by the Statistical Office was cleaned and harmonized by the Economic Research Forum, in the context of a major research project to develop and expand knowledge on equity and inequality in the Arab region. The main focus of the project is to measure the magnitude and direction of change in inequality and to understand the complex contributing social, political and economic forces influencing its levels. However, the measurement and analysis of the magnitude and direction of change in this inequality cannot be consistently carried out without harmonized and comparable micro-level data on income and expenditures. Therefore, one important component of this research project is securing and harmonizing household surveys from as many countries in the region as possible, adhering to international statistics on household living standards distribution. Once the dataset has been compiled, the Economic Research Forum makes it available, subject to confidentiality agreements, to all researchers and institutions concerned with data collection and issues of inequality. Data is a public good, in the interest of the region, and it is consistent with the Economic Research Forum's mandate to make micro data available, aiding regional research on this important topic.

Geographic coverage

The survey data covers urban, rural and camp areas in West Bank and Gaza Strip.

Analysis unit

1- Household/families. 2- Individuals.

Universe

The survey covered all the Palestinian households who are a usual residence in the Palestinian Territory.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample and Frame:

The sampling frame consists of all enumeration areas which were enumerated in 1997; the enumeration area consists of buildings and housing units and is composed of an average of 120 households. The enumeration areas were used as Primary Sampling Units (PSUs) in the first stage of the sampling selection. The enumeration areas of the master sample were updated in 2003.

Sample Design:

The sample is a stratified cluster systematic random sample with two stages: First stage: selection of a systematic random sample of 299 enumeration areas. Second stage: selection of a systematic random sample of 12-18 households from each enumeration area selected in the first stage. A person (18 years and more) was selected from each household in the second stage.

Sample strata:

The population was divided by: 1- Governorate 2- Type of Locality (urban, rural, refugee camps)

Sample Size:

The calculated sample size is 3,781 households.

Target cluster size:

The target cluster size or "sample-take" is the average number of households to be selected per PSU. In this survey, the sample take is around 12 households.

Detailed information/formulas on the sampling design are available in the user manual.

Mode of data collection

Face-to-face [f2f]

Research instrument

The PECS questionnaire consists of two main sections:

First section: Certain articles / provisions of the form filled at the beginning of the month,and the remainder filled out at the end of the month. The questionnaire includes the following provisions:

Cover sheet: It contains detailed and particulars of the family, date of visit, particular of the field/office work team, number/sex of the family members.

Statement of the family members: Contains social, economic and demographic particulars of the selected family.

Statement of the long-lasting commodities and income generation activities: Includes a number of basic and indispensable items (i.e, Livestock, or agricultural lands).

Housing Characteristics: Includes information and data pertaining to the housing conditions, including type of shelter, number of rooms, ownership, rent, water, electricity supply, connection to the sewer system, source of cooking and heating fuel, and remoteness/proximity of the house to education and health facilities.

Monthly and Annual Income: Data pertaining to the income of the family is collected from different sources at the end of the registration / recording period.

Second section: The second section of the questionnaire includes a list of 54 consumption and expenditure groups itemized and serially numbered according to its importance to the family. Each of these groups contains important commodities. The number of commodities items in each for all groups stood at 667 commodities and services items. Groups 1-21 include food, drink, and cigarettes. Group 22 includes homemade commodities. Groups 23-45 include all items except for food, drink and cigarettes. Groups 50-54 include all of the long-lasting commodities. Data on each of these groups was collected over different intervals of time so as to reflect expenditure over a period of one full year.

Cleaning operations

Raw Data

Both data entry and tabulation were performed using the ACCESS and SPSS software programs. The data entry process was organized in 6 files, corresponding to the main parts of the questionnaire. A data entry template was designed to reflect an exact image of the questionnaire, and included various electronic checks: logical check, range checks, consistency checks and cross-validation. Complete manual inspection was made of results after data entry was performed, and questionnaires containing field-related errors were sent back to the field for corrections.

Harmonized Data

• The Statistical Package for Social Science (SPSS) is used to clean and harmonize the datasets.
• The harmonization process starts with cleaning all raw data files received from the Statistical Office.
• Cleaned data files are then all merged to produce one data file on the individual level containing all variables subject to harmonization.
• A country-specific program is generated for each dataset to generate/compute/recode/rename/format/label harmonized variables.
• A post-harmonization cleaning process is run on the data.
• Harmonized data is saved on the household as well as the individual level, in SPSS and converted to STATA format.

Response rate

The survey sample consists of about 3,781 households interviewed over a twelve-month period between January 2004 and January 2005. There were 3,098 households that completed the interview, of which 2,060 were in the West Bank and 1,038 households were in GazaStrip. The response rate was 82% in the Palestinian Territory.

Sampling error estimates

The calculations of standard errors for the main survey estimations enable the user to identify the accuracy of estimations and the survey reliability. Total errors of the survey can be divided into two kinds: statistical errors, and non-statistical errors. Non-statistical errors are related to the procedures of statistical work at different stages, such as the failure to explain questions in the questionnaire, unwillingness or inability to provide correct responses, bad statistical coverage, etc. These errors depend on the nature of the work, training, supervision, and conducting all various related activities. The work team spared no effort at different stages to minimize non-statistical errors; however, it is difficult to estimate numerically such errors due to absence of technical computation methods based on theoretical principles to tackle them. On the other hand, statistical errors can be measured. Frequently they are measured by the standard error, which is the positive square root of the variance. The variance of this survey has been computed by using the “programming package” CENVAR.

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 programme for the World Census of Agriculture 2000 is the eighth in the series for promoting a global approach to agricultural census taking. The first and second programmes were sponsored by the International Institute for Agriculture (IITA) in 1930 and 1940. Subsequent ones up to 1990 were promoted by the Food and Agriculture Organization of the United Nations(FAO). FAO recommends that each country should conduct at least one agricultural census in each census programme decade and its programme for the World Census of Agriculture 2000 for instance corresponds to agricultural census to be undertaken during the decade 1996 to 2005. Many countries do not have sufficient resources for conducting an agricultural census. It therefore became an acceptable practice since 1960 to conduct agricultural census on sample basis for those countries lacking the resources required for a complete enumeration.

In Nigeria's case, a combination of complete enumeration and sample enumeration is adopted whereby the rural (peasant) holdings are covered on sample basis while the modern holdings are covered on complete enumeration. The project named “National Agricultural Sample Census” derives from this practice. Nigeria through the National Agricultural Sample Census (NASC) participated in the 1970's, 1980's, 1990's programmes of the World Census of Agriculture. Nigeria failed to conduct the Agricultural Census in 2003/2004 because of lack of funding. The NBS regular annual agriculture surveys since 1996 had been epileptic and many years of backlog of data set are still unprocessed. The baseline agricultural data is yet to be updated while the annual regular surveys suffered set back. There is an urgent need by the governments (Federal, State, LGA), sector agencies, FAO and other International Organizations to come together to undertake the agricultural census exercise which is long overdue. The conduct of 2006/2008 National Agricultural Sample Census Survey is now on course with the pilot exercise carried out in the third quarter of 2007.

The National Agricultural Sample Census (NASC) 2006/08 is imperative to the strengthening of the weak agricultural data in Nigeria. The project is phased into three sub-projects for ease of implementation; the Pilot Survey, Modern Agricultural Holding and the Main Census. It commenced in the third quarter of 2006 and to terminate in the first quarter of 2008. The pilot survey was implemented collaboratively by National Bureau of Statistics.

The main objective of the pilot survey was to test the adequacy of the survey instruments, equipments and administration of questionnaires, data processing arrangement and report writing. The pilot survey conducted in July 2007 covered the two NBS survey system-the National Integrated Survey of Households (NISH) and National Integrated Survey of Establishment (NISE). The survey instruments were designed to be applied using the two survey systems while the use of Geographic Positioning System (GPS) was introduced as additional new tool for implementing the project.

The Stakeholders workshop held at Kaduna on 21st-23rd May 2007 was one of the initial bench marks for the take off of the pilot survey. The pilot survey implementation started with the first level training (training of trainers) at the NBS headquarters between 13th - 15th June 2007. The second level training for all levels of field personnels was implemented at headquarters of the twelve (12) concerned states between 2nd - 6th July 2007. The field work of the pilot survey commenced on the 9th July and ended on the 13th of July 07. The IMPS and SPSS were the statistical packages used to develop the data entry programme.

Geographic coverage

State

Analysis unit

Household based of fish farmers

Universe

The survey covered all de jure household members (usual residents), who were into fish production

Kind of data

Census/enumeration data [cen]

Sampling procedure

The survey was carried out in 12 states falling under 6 geo-political zones. 2 states were covered in each geo-political zone. 2 local government areas per selected state were studied. 2 Rural enumeration areas per local government area were covered and 3 Fishing farming housing units were systematically selected and canvassed .

Sampling deviation

There was deviations from the original sample design

Mode of data collection

Face-to-face [f2f]

Research instrument

The NASC fishery questionnaire was divided into the following sections: - Holding identification: This is to identify the holder through HU serial number, HH serial number, and demographic characteristics. - Type of fishing sites used by holder. - Sources and quantities of fishing inputs. - Quantity of aquatic production by type. - Quantity sold and value of sale of aquatic products. - Funds committed to fishing by source and others

Cleaning operations

The data processing and analysis plan involved five main stages: training of data processing staff; manual editing and coding; development of data entry programme; data entry and editing and tabulation. Census and Surveys Processing System (CSPro) software were used for data entry, Statistical Package for Social Sciences (SPSS) and CSPro for editing and a combination of SPSS, Statistical Analysis Software (SAS) and EXCEL for table generation. The subject-matter specialists and computer personnel from the NBS and CBN implemented the data processing work. Tabulation Plans were equally developed by these officers for their areas and topics covered in the three-survey system used for the exercise. The data editing is in 2 phases namely manual editing before the data entry were done. This involved using editors at the various zones to manually edit and ensure consistency in the information on the questionnaire. The second editing is the computer editing, this is the cleaning of the already enterd data. The completed questionnaires were collated and edited manually (a) Office editing and coding were done by the editor using visual control of the questionnaire before data entry (b) Cspro was used to design the data entry template provided as external resource (c) Ten operator plus two suppervissor and two progammer were used (d) Ten machines were used for data entry (e) After data entry data entry supervisor runs fequency on each section to see that all the questionnaire were enterd

Response rate

Both Enumeration Area (EA) and Fish holders' level Response Rate was 100 per cent.

Sampling error estimates

No computation of sampling error

Data appraisal

The Quality Control measures were carried out during the survey, essentially to ensure quality of data

Abstract

The Liberia Demographic and Health Survey (LDHS) was conducted as part of the worldwide Demographic and Health Surveys (DHS) program, in which surveys are being carried out in countries in Africa, Asia, Latin America, and the Middle East. Liberia was the second country to conduct a DHS and the first country in Africa to do so. THe LDHS was a national-level survey conducted from February to July 1986, covering a sample of 5,239 women aged 15 to 49.

The major objective of the LDHS was to provide data on fertility, family planning and maternal and child health to planners and policymakers in Liberia for use in designing and evaluating programs. Although a fair amount of demographic data was available from censuses and surveys, almost no information existed concerning family planning, health, or the determinants of fertility, and the data that did exist were drawn from small-scale, sub-national studies. Thus, there was a need for data to make informed policy choices for family planning and health projects.

A more specific objective was to provide baseline data for the Southeast Region Primary Health Care Project. In order to effectively plan strategies and to eventually evaluate the progress of the project in meeting its goals, there was need for data to indicate the health situation in the two target counties prior to the implementation of the project. Many of the desired topics, such as immunizations, family planning use, and prenatal care, were already incorporated into the model DHS questionnaire; nevertheless, the LDHS was able to better accommodate the needs of this project by adding several questions and by oversampling women living in Sinoe and Grand Gedeh Counties.

Another important goal of the LDHS was to enhance tile skills of those participating in the project for conducting high-quality surveys in the future. Finally, the contribution of Liberian data to an expanding international dataset was also an objective of the LDHS.

Geographic coverage

National

Analysis unit

• Households
• Children age 0-5
• Women age 15 to 49
• Men

Kind of data

Sample survey data

Sampling procedure

The sample for the Liberia Demographic and Health Survey was based on the sampling frame of about 4,500 censal enumeration areas (EAs) that were created for the 1984 Population Census. It was decided to eliminate very remote EAs prior to selecting the sample. The definition of remoteness used was "any EA in which the largest village was estimated to be more than 3-4 hours' walk from a road." According to the 1984 census, the excluded areas represent less than 3 percent of the total number of households in the country. Since the major analytic objective of the LDHS was to adequately estimate basic demographic and health indicators including fertility, mortality, and contraceptive prevalence for the whole country and the two sub-universes (Since and Grand Gedeh Counties), it was decided to oversample these two counties. Consequently, three explicit sub-universes of EAs were created: (1) Since County, (2) Grand Gedeh County, and (3) the rest of the country.

The design provided a self-weighted sample within each sub-universe, but, because of the oversampling in Sinoe and Grand Gedeh Counties, the sample is not self-weighting at the national level. Eligible respondents for the survey were women aged 15-49 years who were present the night before the interview in any of the households included in the sample selected for the LDHS.

The total sample size was expected to be about 6,000 women aged 15-49 with a target by sub-universe of 1,000 each in Sinoe and Grand Gedeh Counties and 4,000 in the rest of the country. It was decided that a sample of approximately 5,500 households selected through a two-stage procedure would be appropriate to reach those objectives. Sampling was carried out independently in each sub-universe. In the rest of the country sub-universe, counties were arranged for selection in serpentine order from the northwest (Cape Mount County) to the southeast (Maryland County). In the first stage EAs were selected systematically with probability proportional to size (size = number of households in 1984). Twenty-four EAs were selected in each of Sinoe and Grand Gedeh Counties and 108 EAs in the rest of the country.

See full sample procedure in the survey final report.

Mode of data collection

Face-to-face

Research instrument

The Liberia Demographic and Health Survey (LDHS) utilized two questionnaires: One to list members of the selected households (Household Questionnaire) and the other to record information from all women aged 15-49 who were present in the selected households the night before the interview (Individual Questionnaire).

Both questionnaires were produced in Liberian English and were pretested in September 1985. The Individual Questionnaire was an early version of the DHS model questionnaire. It covered three main topics: (1) fertility, including a birth history and questions concerning desires for future childbearing, (2) family planning knowledge and use, and (3) family health, including prevalence of childhood diseases, immunizations for children under age five, and breasffeeding and weaning practices.

Cleaning operations

Data from the questionnaires were entered onto microcomputers at the Bureau of Statistics office in Monrovia. The data were then subjected to extensive checks for consistency and accuracy.

Errors detected during this operation were resolved either by referring to the original questionnaire, or, in some cases, by logical inference from other information given in the record. Finally, dates were imputed for the small number of cases where complete dates of important events were not given.

Response rate

Out of the total of 6,1306 households selected, 14.5 percent were found not to be valid households in the field, either because the dwelling had been vacated or destroyed, or the household could not be located or did not exist. Of the 5,609 households that were found to exist, 90 percent were successfully interviewed. In the households that were interviewed, a total of 5,340 women were identified as being eligible for individual interview (that is, they were aged 15-49 and had spent the night before the interview in the selected household). This represents an average of slightly over one eligible woman per household.

The response rate for eligible women was 98 percent. The main reason for nonresponse was the absence of the woman. Similar data are presented by sample subuniverse.

Sampling error estimates

The results from sample surveys are affected by two types of errors: (1) nonsampling error and (2) sampling error. Nonsampling error is due to mistakes made in carrying out field activities, such as failure to locate and interview the correct household, errors in the way questions are asked, misunderstanding of the questions on the part of either the interviewer or the respondent, data entry errors, etc. Although efforts were made during the design and implementation of the Liberia Demographic and Health Survey to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

The sample of women selected in the LDHS is only one of many samples of the same size that could have been selected from the same population, using the same design. Each one would have yielded results that differed somewhat from the actual sample selected. The variability observed between all possible samples constitutes sampling error, which, although it is not known exactly, can be estimated from the survey results. Sampling error is usually measured in terms of the "standard error" of a particular statistic (mean, percentage, etc.), which is the square root of the variance of the statistic across all possible samples of equal size and design.

The standard error can be used to calculate confidence intervals within which one can be reasonably assured the true value of the variable for the whole population falls. For example, for any given statistic calculated from a sample survey, the value of that same statistic as measured in 95 percent of all possible samples of identical size and design will fall within a range of plus or minus two times the standard error of that statistic.

If the sample of women had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the LDHS sample design depended on stratification, stages, and clusters and consequently, it was necessary to utilize more complex formulas. The computer package CLUSTERS was used to assist in computing the sampling errors with the proper statistical methodology.

Data appraisal

Information on the completeness of date reporting is of interest in assessing data quality. With regard to dates of birth of individual women, 42 percent of respondents reported both a month and year of birth, 21 percent gave a year of birth in addition to current age, and 37 percent gave only their ages. With regard to children's dates of birth in the birth history, 85 percent of births had both month and year reported, 12 percent had year and age reported, 1 percent had only age reported, and 2 percent had no date information.

Abstract

The Integrated Living Conditions Survey (ILCS), conducted annually by the NSS National Statistical Service of the Republic of Armenia, formed the basis for monitoring living conditions in Armenia. The ILCS is a universally recognized best-practice survey for collecting data to inform about the living standards of households. The ILCS comprises comprehensive and valuable data on the welfare of households and separate individuals which gives the NSS an opportunity to provide the public with up to date information on the population’s income, expenditures, the level of poverty and the other changes in living standards on an annual basis.

Geographic coverage

Urban and rural communities

Analysis unit

• Households;
• Individuals.

Kind of data

Sample survey data [ssd]

Sampling procedure

During the 2001-2003 surveys two-stage random sample was used; the first stage covered the selection of settlements - cities and villages, while the second stage was focused on the selection of households in these settlements. The surveys were conducted on the principle of monthly rotation of households by clusters (sample units). In 2002 and 2003 the number of households was 387 with the sample covering 14 cities and 30 villages in 2002 and 17 cities and 20 villages in 2003.

During the 2004-2006 surveys the sampling frame for the ILCS was built using the database of addresses for the 2001 Population Census; the database was developed with the World Bank technical assistance. The database of addresses of all households in Armenia was divided into 48 strata including 12 communities of Yerevan city. The households from other regions (marzes) were grouped according to the following three categories: big towns with 15,000 and more population; villages, and other towns. Big towns formed 16 strata (the only exception was the Vayots Dzor marz where there are no big towns). The villages and other towns formed 10 strata each. According to this division, a random, two-step sample stratified at marz level was developed. All marzes, as well as all urban and rural settlements were included in the sample population according to the share of population residing in those settlements as percent to the total population in the country. In the first step, the settlements, i.e. primary sample units, were selected: 43 towns out of 48 or 90 percent of all towns in Armenia were surveyed during the year; also 216 villages out of 951 or 23 percent of all villages in the country were covered by the survey. In the second step, the respondent households were selected: 6,816 households (5,088 from urban and 1,728 from rural settlements). As a result, for the first time since 1996 survey data were representative at the marz level.

During the 2007-2012 surveys the sampling frame for ILCS was designed according to the database of addresses for the 2001 Population Census, which was developed with the World Bank technical assistance. The sample consisted of two parts: core sample and oversample.

1) For the creation of core sample, the sample frame (database of addresses of all households in Armenia) was divided into 48 strata including 12 communities of Yerevan city. The households from other regions (marzes) were grouped according to three categories: large towns (with population of 15000 and higher), villages and other towns. Large towns formed by 16 groups (strata), while the villages and towns formed by 10 strata each. According to that division, a random, two-step sample stratified at the marz level was developed. All marzes, as well as all urban and rural settlements were included in the sample population according to the share of households residing in those settlements as percent to the total households in the country. In the first step, using the PPS method the enumeration units (i.e., primary sample units to be surveyed during the year) were selected. 2007 sample includes 48 urban and 18 rural enumeration areas per month. 2) The oversample was drawn from the list of villages included in MCA-Armenia Rural Roads Rehabilitation Project. The enumeration areas of villages that were already in the core sample were excluded from that list. From the remaining enumeration areas 18 enumeration areas were selected per month. Thus, the rural sample size was doubled. 3) After merging the core sample and oversample, the survey households were selected in the second step. 656 households were surveyed per month, from which 368 from urban and 288 from rural settlements. Each month 82 interviewers had conducted field work, and their workload included 8 households per month. In 2007 number of surveyed households was 7,872 (4,416 from urban and 3,456 from rural areas).

For the survey 2013 the sample frame for ILCS was designed in accordance with the database of addresses of all private households in the country developed on basis of the 2001 Population Census results, with the technical assistance of the World Bank. The method of systematic representative probability sampling was used to frame the sample. For the purpose of drawing the sample, the sample frame was divided into 32 strata including 12 communities of Yerevan City (currently, the administrative districts). According to this division, a two-tier sample was drawn stratified by regions and by Yerevan. All regions and Yerevan, as well as all urban and rural communities were included in the sample in accordance to the shares of their resident households within the total number of households in the country. In the first round, enumeration areas - that is primary sample units to be surveyed during the year - were selected. The ILCS 2013 sample included 32 enumeration areas in urban and 16 enumeration areas in rural communities per month. The households to be surveyed were selected in the second round. A total of 432 households were surveyed per month, of which 279 and 153 households from urban and rural communities, respectively. Every month 48 interviewers went on field work with a workload of 9 households per month.

The sample frame for 2014-2016 was designed in accordance with the database of addresses of all private households in the country developed on basis of the 2011 Population Census results, with the technical assistance of the World Bank. The method of systematic representative probability sampling was used to frame the sample.
For drawing the sample, the sample frame was divided into 32 strata including 12 communities of Yerevan City (currently, the administrative districts). According to this division, a two-tier sample was drawn stratified by regions and by Yerevan. All regions and Yerevan, as well as all urban and rural communities were included in the sample in accordance to the shares of their resident households within the total number of households in the country. In the first round, enumeration areas - that is primary sample units to be surveyed during the year - were selected. The ILCS 2014 sample included 30 enumeration areas in urban and 18 enumeration areas in rural communities per month. The method of representative probability sampling was used to frame the sample. At regional level, all communities were grouped into two categories - towns and villages. According to this division, a two-tier sample was drawn stratified by regions and by Yerevan. All regions and Yerevan, as well as all rural and urban communities were included in the sample in accordance to the shares of their resident households within the total number of households in the country. In the first round, enumeration districts - that is primary sample units to be surveyed during the year - were selected. The ILCS 2015 sample included 30 enumeration districts in urban and 18 enumeration districts in rural communities per month.

Mode of data collection

Face-to-face [f2f]

Research instrument

The Questionnaire is filled in by the interviewer during the least five visits to households per month. During face-to-face interviews with the household head or another knowledgeable adult member, the interviewer collects information on the composition and housing conditions of the household, the employment status, educational level and health condition of the members, availability and use of land, livestock, and agricultural machinery, monetary and commodity flows between households, and other information.

The 2011 survey questionnaire had the following sections: (1) "List of Household Members", (2) "Migration", (3) "Housing and Dwelling Conditions", (4) "Employment", (5) "Education", (6) "Agriculture", (7) "Food Production", (8) "Monetary and Commodity Flows between Households", (9) "Health (General) and Healthcare", (10) "Debts", (11) "Subjective Assessment of Living Conditions", (12) "Provision of Services", (13) "Social Assistance", (14) "Households as Employers for Service Personnel", and (15) "Household Monthly Consumption of Energy Resources".

The Diary is completed directly by the household for one month. Every day the household would record all its expenditures on food, non-food products and services, also giving a detailed description of such purchases; e.g. for food products the name, quantity, cost, and place of purchase of the product is recorded. Besides, the household records its consumption of food products received and used from its own land and livestock, as well as from other sources (e.g. gifts, humanitarian aid). Non-food products and services purchased or received for free are also recorded in the diary. Then, the household records its income received during the month. At the end of the month, information on rarely used food products, durable goods and ceremonies is recorded, as well. The records in the diary are verified by the interviewer in the course of 5

Abstract

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 100% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE PALESTINIAN CENTRAL BUREAU OF STATISTICS

The basic goal of the Household and Consumption Survey is to provide a necessary database for formulating national policies at various levels. This survey provides the contribution of the household sector to the Gross National Product (GNP). It determines the incidence of poverty, and provides weighted data which reflects the relative importance of the consumption items to be employed in determining the benchmark for rates and prices of items and services. Furthermore, this survey is a fundamental cornerstone in the process of studying the nutritional status in the Palestinian territory.

The raw survey data provided by the Statistical Agency were cleaned and harmonized by the Economic Research Forum, in the context of a major project that started in 2009. During which extensive efforts have been exerted to acquire, clean, harmonize, preserve and disseminate micro data of existing household surveys in several Arab countries.

Geographic coverage

The Data are representative at region level (West Bank, Gaza Strip), locality type (urban, rural, camp) and governorates.

Analysis unit

1- Household/family. 2- Individual/person.

Universe

All Palestinian households who are usually resident in the Palestinian Territory during 2011.

Kind of data

Sample survey data [ssd]

Sampling procedure

THE CLEANED AND HARMONIZED VERSION OF THE SURVEY DATA PRODUCED AND PUBLISHED BY THE ECONOMIC RESEARCH FORUM REPRESENTS 100% OF THE ORIGINAL SURVEY DATA COLLECTED BY THE PALESTINIAN CENTRAL BUREAU OF STATISTICS

Sample and Frame: The sampling frame consists of all enumeration areas which were enumerated in 2007, each numeration area consists of buildings and housing units with average of about 120 households in it. These enumeration areas are used as primary sampling units PSUs in the first stage of the sampling selection.

Sample Size: The calculated sample size for the Expenditure and Consumption survey 2011 is about 4,317 households, 2,834 households in West Bank and 1,483 households in Gaza Strip.

Sample Design: The sample is a stratified cluster systematic random sample with two stages: First stage: selection of a systematic random sample of 215 enumeration areas. Second stage: selection of a systematic random sample of 24 households from each enumeration area selected in the first stage.

Note: in Jerusalem Governorate (J1), 14 enumeration areas were selected. In the second stage, a group of households from each enumeration area were chosen using the 2007 census method of delineation and enumeration to obtain 24 responsive households. This ensures household response is the maximum to comply with the percentage of non-response as set in the sample design.

Enumeration areas were distributed to twelve months and the sample for each quarter covers sample strata (Governorate, locality type)

Sample strata: The population was divided by: 1- Governorate 2- Type of Locality (urban, rural, refugee camps)

Mode of data collection

Face-to-face [f2f]

Research instrument

The PECS questionnaire consists of two main sections:

First: Survey's Questionnaire Part of the questionnaire is to be filled in during the visit at the beginning of the month, while the other part is to be filled in at the end of the month. The questionnaire includes: Control Sheet: Includes household's identification data, date of visit, data on the fieldwork and data processing team, and summary of household's members by gender. Household Roster: Includes demographic, social, and economic characteristics of household's members. Housing Characteristics: Includes data like type of housing unit, number of rooms, value of rent, and connection of housing unit to basic services like water, electricity and sewage. In addition, data in this section includes source of energy used for cooking and heating, distance of housing unit from transportation, education, and health centers, and sources of income generation like ownership of farm land or animals. Food and Non-Food Items: includes food and non-food items, and household record her expenditure for one month. Durable Goods Schedule: Includes list of main goods like washing machine, refrigerator, TV. Assistances and Poverty: Includes data about cash and in kind assistances (assistance value, assistance source), also collecting data about household situation, and the procedures to cover expenses. Monthly and Annual Income: Data pertinent to household's income from different sources is collected at the end of the registration period.

Second: List of Goods The classification of the list of goods is based on the recommendation of the United Nations for the SNA under the name Classification of Personal Consumption by purpose. The list includes 55 groups of expenditure and consumption where each is given a sequence number based on its importance to the household starting with food goods, clothing groups, housing, medical treatment, transportation and communication, and lastly durable goods. Each group consists of important goods. The total number of goods in all groups amounted to 667 items for goods and services. Groups from 1-21 includes goods pertinent to food, drinks and cigarettes. Group 22 includes goods that are home produced and consumed by the household. The groups 23-45 include all items except food, drinks and cigarettes. The groups 50-55 include durable goods. The data is collected based on different reference periods to represent expenditure during the whole year except for cars where data is collected for the last three years.

Registration Form The registration form includes instructions and examples on how to record consumption and expenditure items. The form includes columns: * Monetary: If the good is purchased, or in kind: if the item is self produced. * Title of the service of the good * Unit of measurement (kilogram, liter, number) * Quantity * Value

The pages of the registration form are colored differently for the weeks of the month. The footer for each page includes remarks that encourage households to participate in the survey. The following are instructions that illustrate the nature of the items that should be recorded: * Monetary expenditures during purchases * Purchases based on debts * Monetary gifts once presented * Interest at pay * Self produced food and goods once consumed * Food and merchandise from commercial project once consumed * Merchandises once received as a wage or part of a wage from the employer.

Cleaning operations

Raw Data

Data editing took place through a number of stages, including: 1. Office editing and coding 2. Data entry 3. Structure checking and completeness 4. Structural checking of SPSS data files

Harmonized Data

• The Statistical Package for Social Science (SPSS) is used to clean and harmonize the datasets.
• The harmonization process starts with cleaning all raw data files received from the Statistical Agency.
• Cleaned data files are then all merged to produce one data file on the individual level containing all variables subject to harmonization.
• A country-specific program is generated for each dataset to generate/ compute/ recode/ rename/ format/ label harmonized variables.
• A post-harmonization cleaning process is then conducted on the data.
• Harmonized data is saved on the household as well as the individual level, in SPSS and converted to STATA format.

Response rate

The survey sample consisted of 5,272 households, weights were modified to account for the non-response rate. The response rate was 88%.

Total sample size = 5,272 Households Household completed = 4317 Households Traveling households = 66 Households Unit does not exist = 48 Households No one at home = 135 Households Refused to cooperate = 347 Households Vacant housing unit = 222 Households No available information = 6 Households Other= 30 Households

Response and non-response rates formulas:

Percentage of over-coverage errors = Total cases of over-coverage*100% Number of cases in original sample = 5% Non-response rate = Total cases of non-response*100% Net sample size = 12% Net sample = Original sample - cases of over-coverage Response rate = 100% - non-response rate= 88%

Sampling error estimates

The impact of errors on data quality was reduced to a minimum due to the high efficiency and outstanding selection, training, and performance of the fieldworkers.

Procedures adopted during the fieldwork of the survey were considered a necessity to ensure the collection of accurate data, notably: 1- Develop schedules to conduct field visits to households during survey fieldwork. The objectives of the visits and the data collected on each visit were predetermined. 2- Fieldwork editing rules were applied during the data collection to ensure corrections were implemented before the end of fieldwork activities 3- Fieldworkers were instructed to provide details in cases of extreme expenditure or consumption by the household. 4- Questions on income were postponed until the final visit at the end of the month 5- Validation rules were embedded in the data processing systems, along with procedures to verify data entry and data edit.

Cluster-level summary statistics of population sizes, participation rates, wealth indices, age and sex distribution.

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

Censuses are principal means of collecting basic population and housing statistics required for social and economic development, policy interventions, their implementation and evaluation. The Post-Apartheid South African government has conducted three Censuses, in 1996, 2001 and 2011.

Geographic coverage

The South African Census 2011 has national coverage.

Analysis unit

Households and individuals

Universe

The South African Census 2011 covered every person present in South Africa on Census Night, 9-31 October 2011 including all de jure household members and residents of institutions.

Kind of data

Census/enumeration data

Sampling procedure

The sampling frame for the PES was the complete list of Census 2011 EAs, amounting to 103 576 EAs. The primary sampling units (PSUs) were the Census EAs. The principle for selecting the PES sample is that the EA boundaries for sampled EAs should have well defined boundaries, and these boundaries should correspond with those of Census EAs to allow for item-by-item comparison between the Census and PES records. The stratification and sampling process followed will allow for the provision of estimates at national, provincial, urban (geography type = urban) and non-urban (geography type = farm and traditional) levels, but estimates will only be reliable at national and provincial levels. The sample of 600 EAs was selected and allocated to the provinces based on expected standard errors which were based on those obtained in PES 2001. Populations in institutions (other than Workers' Hostels), floating and homeless individuals were excluded from the PES sample.

The data files in the dataset include Household, Person, and Mortality files. The 10% sample for the Mortality data file was sampled separately and is not the same as the 10% sample for Household file and Person file.

Mode of data collection

Face-to-face

Research instrument

Three sets of questionnaires were developed for Census 2011: 1. Questionnaire A - the household questionnaire - administed to the population in a household set-up including those households that were found within an institution, such as staff residences 2. Questionnaire B - the population in transit (departing) and those on holiday on reference night (9/10 October 2011). The homeless were also enumerated using this set of questions 3. Questionnaire C - the institutions questionnaire administered to the population in collective living quarters (people who spent census night 9/10 October 2011 at the institution)

A Post-Enumeration Survey was carried out after the census, which used a PES questionnaire.

Sampling error estimates

Comparison of Census 2011 with previous Censuses requires alignment of the data to 2011 municipal boundaries Questions on disability asked in former censuses were replaced in census 2011 with General health and functioning questions. Misreporting on general health and functioning for children younger than five years means data for this variable are only profiled for persons five years and older.

Data appraisal

The dataset does not have a code list for the “geotype” variable which has 3 values (1,2,3).

Abstract

The Ethiopia Socioeconomic Survey (ESS) is a collaborative project between the Central Statistics Agency of Ethiopia (CSA) 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, household-level panel data with a special focus on improving agriculture statistics and generating a clearer understanding of 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.

ESS is a long-term project to collect panel data. The project responds to the data needs of the country, given the dependence of a high percentage of households in agriculture activities in the country. The ESS collects information on household agricultural activities along with other information on the households like human capital, other economic activities, access to services and resources. The ability to follow the same households over time makes the ESS a new and powerful tool for studying and understanding the role of agriculture in household welfare over time as it allows analyses of how households add to their human and physical capital, how education affects earnings, and the role of government policies and programs on poverty, inter alia. The ESS is the first panel survey to be carried out by the CSA that links a multi-topic household questionnaire with detailed data on agriculture.

Geographic coverage

National coverage

Analysis unit

Households

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

SAMPLING PROCEDURE The sampling frame for the new ESS4 is based on the updated 2018 pre-census cartographic database of enumeration areas by CSA. The ESS4 sample is a two-stage stratified probability sample. The ESS4 EAs in rural areas are the subsample of the AgSS EA sample. That means, the first stage of sampling in the rural areas entailed selecting enumeration areas (i.e. the primary sampling units) using simple random sampling (SRS) from the sample of the 2018 AgSS enumeration areas (EAs). The first stage of sampling for urban areas is selecting EAs directly from the urban frame of EAs within each region using systematically with PPS. This is designed in way that automatically results in a proportional allocation of the urban sample by zone within each region. Following the selection of sample EAs, they are allocated by urban rural strata using power allocation which is happened to be closer to proportional allocation.

The second stage of sampling for the ESS4 is the selection of households to be surveyed in each sampled EA using systematic random sampling. From the rural EAs, 10 agricultural households are selected as a subsample of the households selected for the AgSS and 2 non-agricultural households are selected from the non-agriculture households list in that specific EA. The non-agriculture household selection follows the same sampling method i.e. systematic random sampling. One important issue to note in ESS4 sampling is that the total number of agriculture households per EA remains 10 even though there are less than 2 or no non-agriculture households are listed and sampled in that EA.

For urban areas, a total of 15 households are selected per EA regardless of the households' economic activity. The households are selected using systematic random sampling from the total households listed in that specific EA. Table 3.2 presents the distribution of sample households for ESS4 by region, urban and rural stratum. A total of 7527 households are sampled for ESS4 based on the above sampling strategy.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The survey consisted of five questionnaires, similar with the questionnaires used during the previous rounds with revisions based on the results of the previous rounds as well as on identified areas of need for new data.The household questionnaire was administered to all households in the sample; multiple modules in the household questionnaire were administered per eligible household members in the sample. The community questionnaire was administered to a group of community members to collect information on the socio-economic indicators of the enumeration areas where the sample households reside.

The three agriculture questionnaires consisting of a post-planting agriculture questionnaire, post-harvest agriculture questionnaire and livestock questionnaire were administered to all household members (agriculture holders) who are engaged in agriculture activities. A holder is a person who exercises management control over the operations of the agricultural holdings and makes the major decisions regarding the utilization of the available resources. S/he has technical and economic responsibility for the holding. S/he may operate the holding directly as an owner or as a manager. Hence it is possible to have more than one holder in single sampled households. As a result we have administered more than one agriculture questionnaire in a single sampled household if the household has more than one holder.

(a) Household questionnaire: The household questionnaire provides information on education; health (including anthropometric measurement for children); labor and time use; financial inclusion; assets ownership and user right; food and non-food expenditure; household nonfarm activities and entrepreneurship; food security and shocks; safety nets; housing conditions; physical and financial assets; credit; tax and transfer; and other sources of household income. Household location is geo-referenced in order to be able to later link the ESS data to other available geographic data sets (See Appendix 1 for discussion of the geo-data provided with the ESS).

(b) Community questionnaire: The community questionnaire solicits information on infrastructure; community organizations; resource management; changes in the community; key events; community needs, actions and achievements; and local retail price information.

(c) Agriculture questionnaire: The post-planting and post-harvest agriculture questionnaires focus on crop farming activities and solicit information on land ownership and use; land use and agriculture income tax; farm labor; inputs use; GPS land area measurement and coordinates of household fields; agriculture capital; irrigation; and crop harvest and utilization. The livestock questionnaire collects information on animal holdings and costs; and production, cost and sales of livestock by products.

Cleaning operations

Final data cleaning was carried out on all data files. Only errors that could be clearly and confidently fixed by the team were corrected; errors that had no clear fix were left in the datasets. Cleaning methods for these errors are left up to the data user.

OTHER PROCESSING The electronic datasets are organized by questionnaire with the following labels on file names in parentheses: household (hh), community (com), post-planting agriculture (pp), post-harvest agriculture (ph), and livestock (ls). The data within each questionnaire do not contain any constructed variables. For example, the ESS data provide most all variables needed to construct an estimate of total household consumption, but the data set does not contain an estimated value of total consumption. The only compiled data that are included with the ESS files are the geo-spatial variables.

Response rate

ESS4 planned to interview 7,527 households from 565 enumeration areas (EAs) (Rural 316 EAs and Urban 249 EAs). A total of 6770 households from 535 EAs were interviewed for both the agriculture and household modules. The household module was not implemented in 30 EAs due to security reasons (See the Basic Information Document for additional information on survey implementation).

Abstract

In October 2001, South Africans were enumerated to collect information on persons and households throughout the country, using a uniform methodology. Household data collected included data on each household and each person present in the household on Census night, as well as data on services available to the household. Data on household residents, and residents of hostels and the other types of collective living quarters was also captured, as well as data on individuals who spent census night in institutions and hotels.

Geographic coverage

The South African Census 2001 has national coverage.

Analysis unit

The units of analysis for the South Africa Census 2001 were households and individuals

Universe

The South African Census 2001 covered every person present in South Africa on Census Night, 9-10 October 2001 including all de jure household members and residents of institutions.

Kind of data

Census/enumeration data [cen]

Sampling procedure

The data in the South African Census 2001 dataset is a 10% unit level sample drawn from Census 2001 as follows: 1) Households: • A 10% sample of households in housing units, and • A 10% sample of collective living quarters (both institutional and non-institutional) and the homeless.

2) Persons: • A sample consisting of all persons in the households and collective living quarters, and the homeless, drawn for the samples described above

3) Mortality: • A sample consisting of all mortality information for the households in housing units drawn in the 10% sample of households.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three questionnaires were administered for the South African Census 2001, questionnaire A (for persons in households), questionnaire B (for persons in institutions) and questionnaire C (for institutions). The Household questionnaire covered household characteristics, such as dwellling type, home ownership, household assets, access to services and energy sources. A component of the questionnaire captures fertility data. Both the household and persons in institutions questionnaires collected data on individuals' characteristics, including age, population group, language, religion, citizenship, migration, mortality and disability, as well as means of travel. Economic characteristics of individuals included employment activities and data on unemployment.

Cleaning operations

The following publication can be consulted for a detailed account of the editing undertaken for the South African Census 2001: Computer editing specifications / Statistics South Africa. Pretoria: Statistics South Africa, 2003 369p. [Report No. 03-02-43 (2001)]. ISBN 0-621-34566-0.

Data appraisal

As part of the quality check for Census 2001, a Post-Enumeration Survey (PES) was conducted in November 2001, approximately one month after the census. Fieldworkers re-visited a scientifically selected sample of almost 1% of the census enumeration areas, to do an independent recount. The published census results are adjusted for undercount according to the findings of the PES. In addition to the check on coverage, the PES also involved an independent re-measurement of the basic characteristics of the population. Details on this process are available in the publication:

Statistics South Africa. 2004. Census 2001: post-enumeration survey: results and methodology. Report no. 03-02-17 (2001).

Abstract

The sample survey on households' budgets is the method of state statistical observation on living standards of population. The frame of the study and dissemination of budget survey data is defined by the following goals: to collect data on distribution of population by levels of prosperity; to get weighting indicators to calculate a consumer price index; to get data to compile accounts of household sector for the system of national accounts.

The survey on households budgets is conducted in all regions of the Russian Federation and covers 47,800 households. The returns of the survey are compiled quarterly and for a year as a whole.

Starting from 1997 two-stage random sampling built up by territorial principle has been used to form sample frame of households. A final unit of the selection is a household. Collective households consisting of persons who are for a long period in hospitals, in special retirement houses for the elders, boarding schools and other institutional organizations are not included in the sample survey.

Data is collected through face-to-face interviews and households expenditure diaries.

Geographic coverage

Survey covers the entire territory of the Russian Federation, with the exception of the Chechen Republic.

Analysis unit

• Households,
• Individuals.

Universe

All private households and population in them living on the territory of the Russian Federation, with the exception of the Chechen Republic.

Kind of data

Sample survey data [ssd]

Sampling procedure

Two-stage probability sampling with stratification and random sampling on each stage was considered the most adequate for household sample totality. The base for sampling is:

On the first stage: aggregation of folders (enumeration districts) formed on the base of 1994 Microcensus dataset. Aggregation of folders is composed on regional level, for urban and rural population separately. Each folder (enumeration district) has a number assigned, where its belonging to certain administrative region (by region code) and locality (by locality code) is indicated.

On the second stage: totality of microcensus forms for a separate household within the enumeration district selected on the first stage.

Stratification is aimed at creating a representative household sample, reflecting territorial peculiarities of population distribution, its demographic and socio-economic structure.

During actual sampling for each subject of the Russian Federation were created tables, containing numbers of microcensus enumeration districts and microcensus forms included into the sampling. The selection of enumeration districts and forms was conducted on Federal level.

Four variants of selection were created within each enumeration district: the first is aimed at primary sampling per se; the second is aimed at replacing inaccessible households on this stage; third and fourth variants are aimed at replacing households withdrawed in the course of survey. The list of households addresses was created on regional level basing on information from the above mentioned tables.

Mode of data collection

Face-to-face [f2f]

Research instrument

HBS program represents a set of the following kinds of questionnaires differing by data collection period:

Household Diary is designated to record household's daily expenditures by certain types of expenditures and consumption within two consequent weeks of a quarter. Households are keeping diaries in accordance with a special rotation scheme. The procedure of households data collection using two-week diary records is organized on a rotation basis within one sample area. For this purpose the household sample totality surveyed by each interviewer is divided into 12 strata. The interviewer compiles rotation groups by lot. Once the households have been divided into rotation groups, the interviewer enters households numbers into the household quarterly rotation scheme developed for these purposes. The rotation scheme is developed in such a way that each group is updated with 2 to 3 households weekly (depending on the sample area: urban or rural territory).

Household Register (Log Book) is designated to record household's expenditures on those days of the quarter when the household does not keep the Diary. Diary and Register is kept by the person administering all or part of total money, who is engaged in housekeeping most of all and is informed about other household's members expenditures, i.e. responsible person.

Questionnaire for Household Budget Survey (quarter) contains questions focused on collecting information for three months of the quarter prior to data collection.

Questionnaire for Household Budget Survey (annual) records information as at the end of forth quarter of the last (reporting) year. This information relates only to households surveyed within the fourth quarter.

Abstract

The dataset is a relational dataset of 8,000 households households, representing a sample of the population of an imaginary middle-income country. The dataset contains two data files: one with variables at the household level, the other one with variables at the individual level. It includes variables that are typically collected in population censuses (demography, education, occupation, dwelling characteristics, fertility, mortality, and migration) and in household surveys (household expenditure, anthropometric data for children, assets ownership). The data only includes ordinary households (no community households). The dataset was created using REaLTabFormer, a model that leverages deep learning methods. The dataset was created for the purpose of training and simulation and is not intended to be representative of any specific country.

The full-population dataset (with about 10 million individuals) is also distributed as open data.

Geographic coverage

The dataset is a synthetic dataset for an imaginary country. It was created to represent the population of this country by province (equivalent to admin1) and by urban/rural areas of residence.

Analysis unit

Household, Individual

Universe

The dataset is a fully-synthetic dataset representative of the resident population of ordinary households for an imaginary middle-income country.

Kind of data

ssd

Sampling procedure

The sample size was set to 8,000 households. The fixed number of households to be selected from each enumeration area was set to 25. In a first stage, the number of enumeration areas to be selected in each stratum was calculated, proportional to the size of each stratum (stratification by geo_1 and urban/rural). Then 25 households were randomly selected within each enumeration area. The R script used to draw the sample is provided as an external resource.

Mode of data collection

other

Research instrument

The dataset is a synthetic dataset. Although the variables it contains are variables typically collected from sample surveys or population censuses, no questionnaire is available for this dataset. A "fake" questionnaire was however created for the sample dataset extracted from this dataset, to be used as training material.

Cleaning operations

The synthetic data generation process included a set of "validators" (consistency checks, based on which synthetic observation were assessed and rejected/replaced when needed). Also, some post-processing was applied to the data to result in the distributed data files.

Response rate

This is a synthetic dataset; the "response rate" is 100%.

Abstract

The Integrated Survey of Living Standards (ISLS), renamed in 2004 to Integrated Survey of Living Conditions Survey (ILCS) is conducted annually by the NSS National Statistical Service of the Republic of Armenia, formed the basis for monitoring living conditions in Armenia. The ILCS is a universally recognized best-practice survey for collecting data to inform about the living standards of households. The ILCS comprises comprehensive and valuable data on the welfare of households and separate individuals which gives the NSS an opportunity to provide the public with up to date information on the population’s income, expenditures, the level of poverty and the other changes in living standards on an annual basis.

Geographic coverage

Urban and rural communities

Analysis unit

• Households;
• Individuals.

Kind of data

Sample survey data [ssd]

Sampling procedure

During the 2001-2003 surveys two-stage random sample was used; the first stage covered the selection of settlements - cities and villages, while the second stage was focused on the selection of households in these settlements. The surveys were conducted on the principle of monthly rotation of households by clusters (sample units). In 2002 and 2003 the number of households was 387 with the sample covering 14 cities and 30 villages in 2002 and 17 cities and 20 villages in 2003.

During the 2004-2006 surveys the sampling frame for the ILCS was built using the database of addresses for the 2001 Population Census; the database was developed with the World Bank technical assistance. The database of addresses of all households in Armenia was divided into 48 strata including 12 communities of Yerevan city. The households from other regions (marzes) were grouped according to the following three categories: big towns with 15,000 and more population; villages, and other towns. Big towns formed 16 strata (the only exception was the Vayots Dzor marz where there are no big towns). The villages and other towns formed 10 strata each. According to this division, a random, two-step sample stratified at marz level was developed. All marzes, as well as all urban and rural settlements were included in the sample population according to the share of population residing in those settlements as percent to the total population in the country. In the first step, the settlements, i.e. primary sample units, were selected: 43 towns out of 48 or 90 percent of all towns in Armenia were surveyed during the year; also 216 villages out of 951 or 23 percent of all villages in the country were covered by the survey. In the second step, the respondent households were selected: 6,816 households (5,088 from urban and 1,728 from rural settlements). As a result, for the first time since 1996 survey data were representative at the marz level.

During the 2007-2012 surveys the sampling frame for ILCS was designed according to the database of addresses for the 2001 Population Census, which was developed with the World Bank technical assistance. The sample consisted of two parts: core sample and oversample.

1) For the creation of core sample, the sample frame (database of addresses of all households in Armenia) was divided into 48 strata including 12 communities of Yerevan city. The households from other regions (marzes) were grouped according to three categories: large towns (with population of 15000 and higher), villages and other towns. Large towns formed by 16 groups (strata), while the villages and towns formed by 10 strata each. According to that division, a random, two-step sample stratified at the marz level was developed. All marzes, as well as all urban and rural settlements were included in the sample population according to the share of households residing in those settlements as percent to the total households in the country. In the first step, using the PPS method the enumeration units (i.e., primary sample units to be surveyed during the year) were selected. 2007 sample includes 48 urban and 18 rural enumeration areas per month. 2) The oversample was drawn from the list of villages included in MCA-Armenia Rural Roads Rehabilitation Project. The enumeration areas of villages that were already in the core sample were excluded from that list. From the remaining enumeration areas 18 enumeration areas were selected per month. Thus, the rural sample size was doubled. 3) After merging the core sample and oversample, the survey households were selected in the second step. 656 households were surveyed per month, from which 368 from urban and 288 from rural settlements. Each month 82 interviewers had conducted field work, and their workload included 8 households per month. In 2007 number of surveyed households was 7,872 (4,416 from urban and 3,456 from rural areas).

For the survey 2013 the sample frame for ILCS was designed in accordance with the database of addresses of all private households in the country developed on basis of the 2001 Population Census results, with the technical assistance of the World Bank. The method of systematic representative probability sampling was used to frame the sample. For the purpose of drawing the sample, the sample frame was divided into 32 strata including 12 communities of Yerevan City (currently, the administrative districts). According to this division, a two-tier sample was drawn stratified by regions and by Yerevan. All regions and Yerevan, as well as all urban and rural communities were included in the sample in accordance to the shares of their resident households within the total number of households in the country. In the first round, enumeration areas - that is primary sample units to be surveyed during the year - were selected. The ILCS 2013 sample included 32 enumeration areas in urban and 16 enumeration areas in rural communities per month. The households to be surveyed were selected in the second round. A total of 432 households were surveyed per month, of which 279 and 153 households from urban and rural communities, respectively. Every month 48 interviewers went on field work with a workload of 9 households per month.

The sample frame for 2014-2016 was designed in accordance with the database of addresses of all private households in the country developed on basis of the 2011 Population Census results, with the technical assistance of the World Bank. The method of systematic representative probability sampling was used to frame the sample.
For drawing the sample, the sample frame was divided into 32 strata including 12 communities of Yerevan City (currently, the administrative districts). According to this division, a two-tier sample was drawn stratified by regions and by Yerevan. All regions and Yerevan, as well as all urban and rural communities were included in the sample in accordance to the shares of their resident households within the total number of households in the country. In the first round, enumeration areas - that is primary sample units to be surveyed during the year - were selected. The ILCS 2014 sample included 30 enumeration areas in urban and 18 enumeration areas in rural communities per month. The method of representative probability sampling was used to frame the sample. At regional level, all communities were grouped into two categories - towns and villages. According to this division, a two-tier sample was drawn stratified by regions and by Yerevan. All regions and Yerevan, as well as all rural and urban communities were included in the sample in accordance to the shares of their resident households within the total number of households in the country. In the first round, enumeration districts - that is primary sample units to be surveyed during the year - were selected. The ILCS 2015 sample included 30 enumeration districts in urban and 18 enumeration districts in rural communities per month.

Mode of data collection

Face-to-face [f2f]

Research instrument

The Questionnaire is filled in by the interviewer during the least five visits to households per month. During face-to-face interviews with the household head or another knowledgeable adult member, the interviewer collects information on the composition and housing conditions of the household, the employment status, educational level and health condition of the members, availability and use of land, livestock, and agricultural machinery, monetary and commodity flows between households, and other information.

The 2001 survey questionnaire had the following sections: (1) "List of Household Members", (2) "Housing Facilities", (3) "Migration", (4) "Education", (5) "Agriculture", (6) "Monetary and Commodity Flows between Households", (7) "Health (General) and Healthcare", (8) "Savings and Debts", (9) "Social Assistance".

The Diary is completed directly by the household for one month. Every day the household would record all its expenditures on food, non-food products and services, also giving a detailed description of such purchases; e.g. for food products the name, quantity, cost, and place of purchase of the product is recorded. Besides, the household records its consumption of food products received and used from its own land and livestock, as well as from other sources (e.g. gifts, humanitarian aid). Non-food products and services purchased or received for free are also recorded in the diary. Then, the household records its income received during the month. At the end of the month, information on rarely used food products, durable goods and ceremonies is recorded, as well. The records in the diary are verified by the interviewer in the course of 5 mandatory visits to the household during the survey month.

The Survey Diary has the following sections: (1) food purchased during the day, (2) food consumed at home

Abstract

Survey based Harmonized Indicators (SHIP) files are harmonized data files from household surveys that are conducted by countries in Africa. To ensure the quality and transparency of the data, it is critical to document the procedures of compiling consumption aggregation and other indicators so that the results can be duplicated with ease. This process enables consistency and continuity that make temporal and cross-country comparisons consistent and more reliable.

Four harmonized data files are prepared for each survey to generate a set of harmonized variables that have the same variable names. Invariably, in each survey, questions are asked in a slightly different way, which poses challenges on consistent definition of harmonized variables. The harmonized household survey data present the best available variables with harmonized definitions, but not identical variables. The four harmonized data files are

a) Individual level file (Labor force indicators in a separate file): This file has information on basic characteristics of individuals such as age and sex, literacy, education, health, anthropometry and child survival. b) Labor force file: This file has information on labor force including employment/unemployment, earnings, sectors of employment, etc. c) Household level file: This file has information on household expenditure, household head characteristics (age and sex, level of education, employment), housing amenities, assets, and access to infrastructure and services. d) Household Expenditure file: This file has consumption/expenditure aggregates by consumption groups according to Purpose (COICOP) of Household Consumption of the UN.

Geographic coverage

National

Analysis unit

• Individual level for datasets with suffix _I and _L
• Household level for datasets with suffix _H and _E

Universe

The survey covered all de jure household members (usual residents).

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLE DESIGN FOR ROUND 4 OF THE GLSS A nationally representative sample of households was selected in order to achieve the survey objectives.

Sample Frame For the purposes of this survey the list of the 1984 population census Enumeration Areas (EAs) with population and household information was used as the sampling frame. The primary sampling units were the 1984 EAs with the secondary units being the households in the EAs. This frame, though quite old, was considered inadequate, it being the best available at the time. Indeed, this frame was used for the earlier rounds of the GLSS.

Stratification In order to increase precision and reliability of the estimates, the technique of stratification was employed in the sample design, using geographical factors, ecological zones and location of residence as the main controls. Specifically, the EAs were first stratified according to the three ecological zones namely; Coastal, Forest and Savannah, and then within each zone further stratification was done based on the size of the locality into rural or urban.

SAMPLE SELECTION EAs A two-stage sample was selected for the survey. At the first stage, 300 EAs were selected using systematic sampling with probability proportional to size method (PPS) where the size measure is the 1984 number of households in the EA. This was achieved by ordering the list of EAs with their sizes according to the strata. The size column was then cumulated, and with a random start and a fixed interval the sample EAs were selected.

It was observed that some of the selected EAs had grown in size over time and therefore needed segmentation. In this connection, such EAs were divided into approximately equal parts, each segment constituting about 200 households. Only one segment was then randomly selected for listing of the households.

Households At the second stage, a fixed number of 20 households was systematically selected from each selected EA to give a total of 6,000 households. Additional 5 households were selected as reserve to replace missing households. Equal number of households was selected from each EA in order to reflect the labour force focus of the survey.

NOTE: The above sample selection procedure deviated slightly from that used for the earlier rounds of the GLSS, as such the sample is not self-weighting. This is because, 1. given the long period between 1984 and the GLSS 4 fieldwork the number of households in the various EAs are likely to have grown at different rates. 2. the listing exercise was not properly done as some of the selected EAs were not listed completely. Moreover, it was noted that the segmentation done for larger EAs during the listing was a bit arbitrary.

Mode of data collection

Face-to-face [f2f]

Key Table Information.Table Title.Island Areas: Summary Statistics for Domestic and Nondomestic Corporations for Puerto Rico: 2022.Table ID.ISLANDAREASIND2022.IA2200SIZE05.Survey/Program.Economic Census of Island Areas.Year.2022.Dataset.ECNIA Economic Census of Island Areas.Source.U.S. Census Bureau, 2022 Economic Census of Island Areas, Core Statistics.Release Date.2024-12-19.Release Schedule.The Economic Census occurs every five years, in years ending in 2 and 7.2022 Economic Census of Island Areas tables are released on a flow basis from June through December 2024.For more information about economic census planned data product releases, see 2022 Economic Census Release Schedule..Dataset Universe. The dataset universe consists of all establishments that are in operation for at least some part of 2022, are located in Puerto Rico, have paid employees, and are classified in one of eighteen in-scope sectors defined by the 2022 NAICS..Sponsor.U.S. Department of Commerce.Methodology.Data Items and Other Identifying Records.Number of establishmentsSales, value of shipments, or revenue ($1,000)Annual payroll ($1,000)First-quarter payroll ($1,000)Number of employeesOperating expenses ($1,000)Total inventories, beginning of year ($1,000)Total inventories, end of year ($1,000)Range indicating imputed percentage of total sales, value of shipments, or revenueRange indicating imputed percentage of total annual payrollRange indicating imputed percentage of total employeesEach record includes a LFO code, which represents a specific legal form of organization category.The data are shown for legal form of organization.Definitions can be found by clicking on the column header in the table or by accessing the Economic Census Glossary..Unit(s) of Observation.The reporting units for the Economic Census of Island Areas are employer establishments. An establishment is generally a single physical location where business is conducted or where services or industrial operations are performed..Geography Coverage.The data are shown for employer establishments and firms that vary by industry:At the Territory level for Puerto RicoFor information about economic census geographies, including changes for 2022, see Geographies..Industry Coverage.The data are shown at the 2-digit 2022 NAICS code levels for selected economic census sectors and geographies.For information about NAICS, see Economic Census Code Lists..Sampling.The Economic Census of Island Areas is a complete enumeration of establishments located in the islands (i.e., all establishments on the sampling frame are included in the sample). Therefore, the accuracy of tabulations is not affected by sampling error..Confidentiality.The Census Bureau has reviewed this data product to ensure appropriate access, use, and disclosure avoidance protection of the confidential source data (Project No. 7504609, Disclosure Review Board (DRB) approval number: CBDRB-FY24-0044).The primary method of disclosure avoidance protection is noise infusion. Under this method, the quantitative data values such as sales or payroll for each establishment are perturbed prior to tabulation by applying a random noise multiplier (i.e., factor). Each establishment is assigned a single noise factor, which is applied to all its quantitative data value. Using this method, most published cell totals are perturbed by at most a few percentage points.To comply with disclosure avoidance guidelines, data rows with fewer than three contributing establishments are not presented. For more information on disclosure avoidance, see Methodology for the 2022 Economic Census- Island Areas..Technical Documentation/Methodology.For detailed information about the methods used to collect data and produce statistics, see Methodology for the 2022 Economic Census- Island Areas.For more information about survey questionnaires, Primary Business Activity/NAICS codes, and NAPCS codes, see Economic Census Technical Documentation..Weights.Because the Economic Census of Island Areas is a complete enumeration, there is no sample weighting..Table Information.FTP Download.https://www2.census.gov/programs-surveys/economic-census/data/2022/sector00.API Information.Economic census data are housed in the Census Bureau Application Programming Interface (API)..Symbols.D - Withheld to avoid disclosing data for individual companies; data are included in higher level totalsN - Not available or not comparableS - Estimate does not meet publication standards because of high sampling variability, poor response quality, or other concerns about the estimate quality. Unpublished estimates derived from this table by subtraction are subject to these same limitations and should not be attributed to the U.S. Census Bureau. For a description of publication standards and the total quantity response rate, see link to program methodology page.X - Not applicableA - Relative standard error of 100% or morer - Reviseds - Relative standard error exceeds 40%For a complete lis...

Abstract

Socio-Economic Conditions Survey 2018 is a key Palestinian official statistical aspects; it also falls within the mandate of the Palestinian Central Bureau of Statistics (PCBS) to provide updated statistical data on the society conditions and provide data on the most important changes in socio-economic indicators and its trends. The survey came in response to users' needs for social and economic statistical data, and in line with the national policy agenda and the sustainable development agenda. The indicators of Socio-Economic Conditions Survey 2018 covers many socio-economic and environmental aspects, and establishes a comprehensive database on those indicators. its coverage of a set of sustainable development indicators that are considered as a national and international entitlement. The objective of this survey is to provide a comprehensive database on the most important changes that have taken place in the system of social and economic indicators that PCBS works on, which covers many socio-economic and environmental indicators. It also responds to the needs of many partners and users.The indicators that have been worked on in this survey cover the Demographic characteristics of household members, Characteristics of the housing unit where household lives, Household income, expenses, and consumption, Agricultural and economic activities of households, Methods used by households to withstand and adapt to their economic conditions, Availability of basic services to Palestinian households, Assistance received by households and assessment of such assistance, the needs of the Palestinian households to be able to withstand the conditions, the reality of the Palestinian individual's suffering and the quality of life, Sustainable development objectives. for the survey's relevant indicators.

Geographic coverage

National level: State of Palestine. Region level: (West Bank, and Gaza Strip).

Analysis unit

Households, and individuals

Universe

The target population includes all Palestinian households and individuals with regular residency in Palestine during the survey's period (2018)

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling and Frame The Sample of the survey is a three-stage stratified cluster systematic random sample of households residing in Palestine. Target Population The target population includes all Palestinian households and individuals with regular residency in Palestine during the survey's period (2018). Focus was given to individuals aged 18 years and above to complete an annex to the questionnaire, designed for this age group. Sampling Framework In previous survey rounds, sampling was based on census 2007, which includes a list of enumeration areas. An enumeration area is a geographic region with buildings and housing units averaging 124 housing units. In the survey design, they are considered as Primary Sampling Units (PSUs) at the first stage of selecting the sample. Enumeration areas of 2007 were adapted to the enumeration areas of 2017 to be used in future survey rounds. Target sample buildings were set up in 2015 electronically by using Geographic Information Systems (GIS), where the geospatial join tool was used within Arc Map 10.6 to identify the buildings selected in the first stage of the sample design of 8,225 households taken from the general frame buildings for enumeration areas of 2007 which falls within the boundaries of enumeration areas that were updated during the population, housing and establishments census 2017. Only the buildings for the year 2017 were used to link the sites of the sample buildings to the targeted enumeration areas, to ensure tracking households that moved after 2015. Sample Size The survey sample comprised 11,008 households at the total level, where 9,926 households responded, they are divided as follows: 1. Fixing the sample of the survey on the Impact of Israeli Aggression on Gaza Strip in 2014 and Socio-Economic Conditions of the Palestinian Households - Main Findings, which was conducted in 2015, with a sample of 8,225 households in the previous round (household-panel),where 7,587 households responded. 2. Sample of new households that consisted of separated individuals (split households) totaled 2,783 households, where 2,339 households responded. Sample Design Three-stage stratified cluster systematic random sample: Stage I: Selection of enumeration areas represented in the previous round of the survey on the socioeconomic conditions 2015 including 337 enumeration areas, in addition to enumeration areas in which individuals separated from their households and formed new households and households that changed their place of residence and address to other enumeration areas. Stage II: Visit the same households from previous round of survey on socioeconomic conditions 2015(25 households in each enumeration area). Households that changed their place of residence or registered address will be tracked in the existing database to search for the updated data registered in questionnaire. Individuals separated from their households from the previous round and formed new households or joined new households were tracked. Stage III: A male and female member of each household in the sample (old and new) were selected for stage III among members aged 18 years and above, using Kish (multivariate) tables to fill in the questionnaire for household members aged 18 years and above. Taking into account that the household whose number is an even number in the sample of the enumeration area, we choose a female and the family whose number is an odd number we choose a male. Sample Strata The population was divided into the following strata: 1. Governorate (16 Governorates in the West Bank including those parts of Jerusalem, which were annexed by Israeli occupation in 1967 (J1) as a separated stratum, and the Gaza Strip). 2. Locality type (urban, rural, camp). 3. Area C (class C, non-C) as an implicit stratum. Domains 1. National level: State of Palestine. 2. Region level: (West Bank, and Gaza Strip). 3. Governorate (16 Governorates in the West Bank including those parts of Jerusalem, which were annexed by Israeli occupation in 1967, and Gaza Strip). 4. The location of the Annexation wall and Isolation (inside the wall, outside the wall). 5. Locality type (urban, rural, camp). 6. Refugee status (refugee, non-refugee). 7. Sex (male, female). 8. Area C (class C, non-C).

Sampling deviation

There are no deviations in the proposed sample design

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The questionnaire is the key tool for data collection. It must be conforming to the technical characteristics of fieldwork to allow for data processing and analysis. The survey questionnaire comprised the following parts: · Part one: Identification data. · Part two: Quality control · Part three: Data of households' members and social data. · Part four: Housing unit data · Part five: Assistance and Coping Strategies Information · Part six: Expenditure and Consumption · Part seven: Food Variation and Facing Food Shortage · Part eight: Income · Part nine: Agricultural and economic activities. · Part ten: Freedom of mobility · In addition to a questionnaire for individuals (18 years old and above): Questions on suffering and life quality, assessment of health, education, administration (Ministry of the Interior) services and information technology.

The language used in the questionner is Arabic with an English questionner

Cleaning operations

Data Processing Data processing was done in different ways including: Programming Consistency Check 1.Tablet applications were developed in accordance with the questionnaire's design to facilitate collection of data in the field. The application interfaces were made user-friendly to enable fieldworkers collect data quickly with minimal errors. Proper data entry tools were also used to concord with the question including drop down menus/lists. 2.Develop automated data editing mechanism consistent with the use of technology in the survey and uploading the tools for use to clean the data entered into the database and ensure they are logic and error free as much as possible. The tool also accelerated conclusion of preliminary results prior to finalization of results. 3.GPS and GIS were used to avoid duplication and omission of counting units (buildings, and households). In order to work in parallel with Jerusalem (J1) in which the data was collected in paper, the same application that was designed on the tablets was used and some of its properties were modified, there was no need for maps to enter their data as the software was downloaded on the devices after the completion of the editing of the questionnaires Data Cleaning 1.Concurrently with the data collection process, a weekly check of the data entered was carried out centrally and returned to the field for modification during the data collection phase and follow-up. The work was carried out thorough examination of the questions and variables to ensure that all required items are included, and the check of shifts, stops and range was done too. 2.Data processing was conducted after the fieldwork stage, where it was limited to conducting the final inspection and cleaning of the survey databases. Data cleaning and editing stage focused on: ·Editing skips and values allowed. ·Checking the consistency between different the questions of questionnaire based on logical relationships. ·Checking on the basis of relations between certain questions so that a list of non-identical cases was extracted,