Abstract

The household registration system known as ho khau has been a part of the fabric of life in Vietnam for over 50 years. The system was used as an instrument of public security, economic planning, and control of migration, at a time when the state played a stronger role in direct management of the economy and the life of its citizens. Although the system has become less rigid over time, concerns persist that ho khau limits the rights and access to public services of those who lack permanent registration in their place of residence. Due largely to data constraints, however, previous discussions about the system have relied largely on anecdotal or partial information.

Drawing from historical roots as well as the similar model of China’s hukou, the ho khau system was established in Vietnam in 1964. The 1964 law established the basic parameters of the system: every citizen was to be registered as a resident in one and only household at the place of permanent residence, and movements could take place only with the permission of authorities. Controlling migration to cities was part of the system’s early motivation, and the system’s ties to rationing, public services, and employment made it an effective check on unsanctioned migration. Transfer of one’s ho khau from one place to another was possible in principle but challenging in practice.

The force of the system has diminished since the launch of Doi Moi as well as a series of reforms starting in 2006. Most critically, it is no longer necessary to obtain permission from the local authorities in the place of departure to register in a new location. Additionally, obtaining temporary registration status in a new location is no longer difficult. However, in recent years the direction of policy changes regarding ho khau has been varied. A 2013 law explicitly recognized the authority of local authorities to set their own policies regarding registration, and some cities have tightened the requirements for obtaining permanent status.

Understanding of the system has been hampered by the fact that those without permanent registration have not appeared in most conventional sources of socioeconomic data. To gather data for this project, a survey of 5000 respondents in five provinces was done in June-July 2015. The samples are representative of the population in 5 provinces – Ho Chi Minh City, Ha Noi, Da Nang, Binh Duong and Dak Nong. Those five provinces/cities are among the provinces with the highest rate of migration as estimated using data from Population Census 2009.

Geographic coverage

5 provinces – Ho Chi Minh City, Ha Noi, Da Nang, Binh Duong and Dak Nong.

Analysis unit

Household

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling for the Household Registration Survey was conducted in two stages. The two stages were selection of 250 enumeration areas (50 EAs in each of 5 provinces) and then selection of 20 households in each selected EA, resulting in a total sample size of 5000 households. The EAs were selected using Probability Proportional to Size (PPS) method based on the square number of migrants in each EA, with the aim to increase the probability of being selected for EAs with higher number of migrants. “Migrants” were defined using the census data as those who lived in a different province five years previous to the census. The 2009 Population Census data was used as the sample frame for the selection of EAs. To make sure the sampling frame was accurate and up to date, EA leaders of the sampled EAs were asked to collection information of all households regardless of registration status at their ward a month before the actual fieldwork. Information collected include name of head of household, address, gender, age of household’s head, household phone number, residence registration status of household, and place of their registration 5 years ago. All households on the resulting lists were found to have either temporary or permanent registration in their current place of residence.

Using these lists, selection of survey households was stratified at the EA level to ensure a substantial surveyed population of households without permanent registration. In each EA random selection was conducted of 12 households with temporary registration status and 8 households with permanent registration status. For EAs where the number of temporary registration households was less than 12, all of the temporary registration households were selected and additional permanent registration households were selected to ensure that each EA had 20 survey households. Sampling weights were calculated taking into the account the selection rules for the first and second stages of the survey.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The questionnaire was mostly adapted from the Vietnam Household Living Standard Survey (VHLSS), and the Urban Poverty Survey (UPS) with appropriate adjustment and supplement of a number of questions to follow closely the objectives of this survey. The household questionnaire consists of a set of questions on the following contents:

• Demographic characteristics of household members with emphasis on their residence status in terms of both administrative management (permanent/temporary residence book) and real residential situation. • Education of household members. Beside information on education level, the respondents are asked whether a household member attend school as “trai-tuyen” , how much “trai-tuyen” fee/enrolment fee, and difficulty in attending schools without permanent residence status. • Health and health care, collecting information on medical status and health insurance card of household members. • Labour and employment, asking household member’s employment status in the last 30 days; their most and second-most time-consuming employment during the last 30 days; and whether they had been asked about residence status when looking for job. • Assets and housing conditions. This section collects information on household’s living conditions such as assets, housing types and areas, electricity, water and energy. • Income and expenditure of households. • Social inclusion and protection. The respondents are asked whether their household members participate in social organizations, activities, services, contribution; whether they benefit from any social project/policy; do they have any loans within the last 12 months; and to provide information about five of their friends at their residential area. • Knowledge on the Law of Residence, current regulations on conditions for obtaining permanent residence, experience dealing with residence issues, and opinion on current household registration system of the respondents.

Cleaning operations

Managing and Cleaning the Data

Data were managed and cleaned each day immediately upon being received, which occurred at the same time as the fieldwork surveys. At the end of each workday, the survey teams were required to review all of the interviews conducted and transfer collected data to the server. The data received by the main server were downloaded and monitored by MDRI staff.

At this stage, MDRI assigned a technical team to work on the data. First, the team listened to interview records and used an application to detect enumerators’ errors. In this way, MDRI quickly identified and corrected the mistakes of the interviewers. Then the technical team proceeded with data cleaning by questionnaire, based on the following quantity and quality checking criteria.

• Quantity checking criteria: The number of questionnaires must be matched with the completed interviews and the questionnaires assigned to each individual in the field. According to the plan, each survey team conducted 20 household questionnaires in each village. All questionnaires were checked to ensure that they contained all essential information, and duplicated entries were eliminated. • Quality checking criteria: Our staff performed a thorough examination of the practicality and logic of the data. If there was any suspicious or inconsistent information, the data management team re – listened to the records or contacted the respondents and survey teams for clarification via phone call. Necessary revisions would then be made.

Data cleaning was implemented by the following stages: 1. Identification of illogical values; 2. Software – based detection of errors for clarification and revision; 3. Information re-checking with respondents and/or enumerators via phone or through looking at the records; 4. Development and implementation of errors correction algorithms; The list of detected and adjusted errors is attached in Annex 6.

Outlier detection methods The data team applied a popular non - parametric method for outlier detection, which can be done with the following procedure: 1. Identify the first quartile Q1 (the 25th percentile data point) 2. Identify the third quartile Q3 (the 75th percentile data point) 3. Identify the inter-quartile range(IQR): IQR=Q3-Q1 4. Calculate lower limits (L) and upper limits (U) by the following formulas: o L=Q1-1.5*IQR o U=Q3+1.5*IQR 5. Detect outliers by the rule: An observation is an outlier if it lies below the lower bound or beyond the upper bound (i.e. less than L or greater than U)

Data Structure The completed dataset for the “Household registration survey 2015” includes 9 files in STATA format (.dta): • hrs_maindata: Information on the households, including: assets, housing, income, expenditures, social inclusion and social protection issues, household registration procedures • hrs_muc1: Basic information on the

Abstract

The National Survey of Household Income and Expenditure (ENIGH) aims to provide a statistical overview of the behavior of household income and expenditure in terms of its amount, origin and distribution. In addition, it offers information on the occupational and sociodemographic characteristics of the members of the household, as well as the characteristics of the housing infrastructure and household equipment.

The ENIGH is part of the Information System of National Interest (IIN), which means that the results obtained from this project are mandatory for the Federation, the states and the municipalities, in order to contribute to national development.

In 1984, a trend began to broaden the objectives and homogenize the methodology, taking into account international recommendations and the information requirements of the different users, taking care of historical comparability.

Periodicity: Since 1992 it has been carried out biennially (every two years) with the exception of 2005 when an extraordinary survey was carried out.

Target population: It is made up of the households of nationals or foreigners, who usually reside in private homes within the national territory.

Selection Unit: Private home. The dwellings are chosen through a meticulous statistical process that guarantees that the results obtained from only a part of the population (sample) can be generalized to the total.

Sampling Frame: INEGI's multi-purpose framework is made up of demographic and cartographic information obtained from the 2010 Population and Housing Census.

Observation unit: The home.

Unit of analysis: The household, the dwelling and the members of the household.

Thematic coverage:

Characteristics of the house. Residents and identification of households in the dwelling. Sociodemographic characteristics of the residents of the dwelling. Home equipment, services. Activity condition and occupational characteristics of household members aged 12 and over. Total current income (monetary and non-monetary) of households. Financial and capital perceptions of households and their members. Current monetary expenditure of households. Financial and capital expenditures of households.

The different concepts of the ENIGH are governed by recommendations agreed upon in international conventions, for example:

The resolutions and reports of the 18 International Conferences on Labour Statistics, of the International Labour Organization (ILO).

The final report and recommendations of the Canberra Group, an expert group on "Household Income Statistics".

Manual of Household Surveys. Department of International Economic and Social Affairs, Bureau of Statistics. United Nations, New York, 1987.

They are also articulated with the CNational Accounts and with the Household Surveys carried out by the INEGI.

Sample size: At the national level, including the ten-one, there are 93,186 private homes.

Survey period: The collection of information will take place between August 11 and November 18 of this year. Throughout this period, ten cuts are made, each organized in ten days; Therefore, each of these cuts will be known as tens (see calendar in the annex).

Workload: According to the meticulousness in the recording of information in this project, a load of six interviews in private homes per dozen has been defined for each interviewer. The number of interviews may decrease or increase according to several factors: non-response, recovery from non-response, or additional households.

Geographic coverage

National and at the state level - Urban: localities with 2,500 or more inhabitants - Rural: localities with less than 2,500 inhabitants

Analysis unit

The household, the dwelling and the members of the household.

Universe

The survey is aimed at households in the national territory.

Kind of data

Probabilistic household survey

Sampling procedure

The design of the exhibition for ENIGH-2018 is characterized by being probabilistic; consequently, the results obtained from the survey are generalized to the entire population of the study domain; in turn, it is two-stage, stratified and by clusters, where the ultimate unit of selection is the dwelling and the unit of observation is the household.

The ENIGH-2018 subsample was selected from the 2012 INEGI master sample, this master sample was designed and selected from the 2012 Master Sampling Framework (Marco Maestro de Muestreo (MMM)) which was made up of housing clusters called Primary Sampling Units (PSU), built from the cartographic and demographic information obtained from the 2010 Population and Housing Census. The master sample allows the selection of subsamples for all housing surveys carried out by INEGI; Its design is probabilistic, stratified, single-stage and by clusters, since it is in them that the dwellings that make up the subsamples of the different surveys were selected in a second stage. The design of the MMM was built as follows:

Formation of the primary sampling units (PSU)

First, the set of PSUs that will cover the national territory is built.

The primary sampling units are made up of groups of dwellings with differentiated characteristics depending on the area to which they belong, as specified below:

a) In high urban areas

The minimum size of a PSU is 80 inhabited dwellings and the maximum is 160. They can be made up of:

• A block. • The union of two or more contiguous blocks of the same AGEB. • The union of two or more contiguous blocks of different AGEBs in the same locality. • The union of two or more contiguous blocks from different localities, which belong to the same size of locality.

b) In urban complement: The minimum size of a PSU is 160 inhabited dwellings and the maximum is 300. They can be made up of:

• A block. • The union of two or more contiguous blocks of the same AGEB. • The union of two or more contiguous blocks of different AGEBs in the same locality. • The union of two or more contiguous blocks from different AGEBs and localities, but from the same municipality.

c) In rural areas: The minimum size of a PSU is 160 inhabited dwellings and the maximum is 300. They can be made up of:

• An AGEB. • Part of an AGEB. • The union of two or more adjoining AGEBs in the same municipality. • The union of an AGEB with a part of another adjoining AGEB in the same municipality.

The total number of PSUs formed was 240,912.

Stratification

Once the set of PSUs has been constructed, those with similar characteristics are grouped, that is, they are stratified.

The political division of the country and the formation of localities differentiated by their size, naturally form a geographical stratification.

In each federal entity there are three areas, divided into zones.

High urban, Zone 01 to 09, Cities with 100,000 or more inhabitants.

Urban complement, Zone 25, 35, 45 and 55, From 50,000 to 99,999 inhabitants, 15,000 to 49,999 inhabitants, 5,000 to 14,999 inhabitants, 2,500 to 4,999 inhabitants.

Rural, Zone 60, Localities with less than 2,500 inhabitants.

At the same time, four sociodemographic strata were formed in which all the PSUs in the country were grouped, this stratification considers the sociodemographic characteristics of the inhabitants of the dwellings, as well as the physical characteristics and equipment of the same, expressed through 34 indicators built with information from the 2010 Population and Housing Census*, for which multivariate statistical methods were used.

In this way, each PSU was classified into a single geographical and a sociodemographic stratum.

As a result, there are a total of 683 strata throughout the country.

Selection of the PSUs of the master sample The PSUs of the master sample were selected by means of a sampling with probability proportional to the size.

Sample size For the calculation of the sample size of the ENIGH-2018, the average total current income per household was considered as a reference variable.

Sampling deviation

As a result of the sum of the 87,826 homes selected and 1,312 additional homes that were found in those homes, the total amounted to 89,138 households.

Mode of data collection

Face-to-face [f2f]

Research instrument

Six collection instruments will be used to collect information in each household, four of which concentrate information on the household as a whole.

These are:

• Household and housing questionnaire
• Household expenditure questionnaires
• Daily expenditure booklet

In the other three, individual information is recorded for people:

• Questionnaire for people aged 12 or over
• Questionnaire for people under 12 years of age
• Questionnaire for household businesses

Cleaning operations

Capture activities

The capture consisted of transferring the information from the questionnaires that were fully answered to electronic means through IKTAN, in accordance with the procedures established for the capture process of the ENIGH 2018.

The Person in Charge of Capture and Validation, together with his work team, began the capture of the questionnaires collected by each Interviewer, organized by packages of questionnaires of each page with the result of a complete interview, following the established order:

• Household and housing questionnaire. • Questionnaires for people under 12 years of age. • Questionnaires for people aged 12 and over. • Questionnaires for home businesses. • Household expenditure questionnaire. • Daily expenses booklet.

In addition, the IKTAN made it possible to record and know the progress or conclusion of workloads.

Validation activities

In parallel to the capture, the state coordination

Slovenia Income per Household Member: Mean data was reported at 14,017.000 EUR in 2024. This records an increase from the previous number of 12,838.000 EUR for 2023. Slovenia Income per Household Member: Mean data is updated yearly, averaging 8,746.000 EUR from Dec 2008 (Median) to 2024, with 17 observations. The data reached an all-time high of 14,017.000 EUR in 2024 and a record low of 7,532.000 EUR in 2008. Slovenia Income per Household Member: Mean data remains active status in CEIC and is reported by Statistical Office of the Republic of Slovenia. The data is categorized under Global Database’s Slovenia – Table SI.H013: Household Income and Expenditure: per Capita.

Numbers and percentages of children in working, mixed and workless households for local authorities, annual.

The Household Market and Nonmarket Activities (HUS) project started as a joint research project between the Industrial Institute for Economic and Social Research (IUI) and Göteborg University in 1980. The ambition was to build a consistent longitudinal micro data base on the use of time, money and public services of households. The first main survey was carried out in 1984. In addition to a contact interview with the selected individuals, all designated individuals participated in a personal interview and two telephone interviews. All respondents were asked about their family background, education, marital status, labor market experience, and employment. In addition, questions about the household were asked of the head of household, concerning family composition, child care, health status, housing, possession of vacation homes, cars, boats and other consumption durables. At the end of the personal interview the household head had to fill out a questionnaire including questions about financing of current home, construction costs for building a house, house value and loans, imputation of property values and loans, additions/renovations 1983, maintenance and repairs, leasing, sale of previous home, assets and liabilities, and non-taxable benefits. All the respondents had to fill out a questionnaire including questions about tax-return information 1983, employment income, and taxes and support payments. Two telephone interviews were used primarily to collect data on the household´s time use and consumption expenditures. The 1986 HUS-survey included both a follow-up of the 1984 sample (panel study) and a supplementary sample. The 1986 sample included 1) all respondents participating in the 1984 survey, 2) the household heads, partners and third persons who should have participated in 1984 but did not (1984 nonresponse), 3) those individuals who started living together after the 1984 interview with an selected individual who participated or was supposed to participate in 1984, 4) members of the 1984 household born in 1966 or 1967. If entering a new household, for example because of leaving their parental home, the household head and his/her partner were also interviewed. Respondents participating in the 1984 survey were interviewed by telephone in 1986. Questions dealt with changes in family composition, housing, employment, wages and child care, and it was not only recorded whether a change had occurred, and what sort of change, but also when it occurred. The respondents also received a questionnaire by mail with questions mainly concerning income and assets. Respondents not participating in the earlier survey were interviewed in person and were asked approximately the same questions as in the 1984 personal interview. The 1988 HUS-survey was considerably smaller than the previous ones. It was addressed exclusively to participants in the 1986 survey, and consisted of a self-enumerated questionnaire with a nonrespondent follow-up by telephone. The questions dealt with changes in housing conditions, employment and household composition. The questionnaire also contained some questions on household income. In many respect the 1991 HUS-survey replicated the 1988 survey. The questions were basically the same in content and range, and the survey was conducted as a self-enamurated questionnaire sent out by mail. This time, however, in contrast to the 1988 survey, an attempt was made to include in the survey the new household members who had moved into sample households since 1986, as well as young people who turned 18 after the 1986 survey. Earlier respondents received a questionnaire by mail containing questions about their home, their primary occupation and weekly work hours since May 1988 (event-history data), earnings in 1989, 1990 and 1991, household composition and any changes in it that might have occurred since 1988, child care and some questions on income. New respondents were also asked about their education and labor-market experience. With respect to its design and question wording, the 1993 survey is a new version of the 1986 survey. The survey is made up of four parts: 1) the panel survey, which was addressed mainly to respondents in the 1991 survey, with certain additions; 2) the so-called supplementary survey, which focused on a new random sample of individuals; 3) the so-called nonresponse survey, which encompassed respondents who had participated in at least one of the earlier surveys but had since dropped out; 4) the time-use survey, which included the same sample of respondents as those in the panel and supplementary surveys. Individuals in the nonresponse group were not included in the time-use survey. Most of the questions in the first three surveys were the same, but certain questions sequences were targeted to the respondents in a specific survey. Thus certain retrospective questions were asked of the nonresponse group, while specific questions on social background, labor market experience etc. were addressed to new respondents. In the case of respondents who had already participated in the panel, a combined contact and main interview was conducted by telephone, after which a self-enumerated questionnaire was sent out to each respondent by mail. The panel sample also included young people in panel households who were born in 1973 or 1974 as well as certain new household members who had not previously been interviewed. These individuals, like new respondents, were not interviewed by telephone until they had been interviewed personally. Thus technically they were treated in the same manner as individuals in the supplementary sample. The new supplementary sample was first contacted by telephone and then given a fairly lengthy personal interview, at the conclusion of which each respondent was asked to fill out a written questionnaire. In this respect the survey design for the nonresponse sample was the same as for the supplementary sample. The nonresponse sample also included young people born in 1973 or 1974 as well as certain new household members. The time-use interviews were conducted by telephone. For each respondent two days were chosen at random from the period from February 15, 1993 to February 14, 1994 and the respondents were interviewed about their time use during those two days. If possible, the time-use interviews were preceded by the other parts of the survey, but this was not always feasible. In each household the household head and spouse/partner were interviewed, as well as an additional person in certain households. Questions regarding the household as a whole were asked of only one person in the household, preferably the household head. As in earlier surveys, data from the interviews was subsequently supplemented by registry data, but only for those respondents who had given their express consent. There is registry information for 75-80 percent of the sample. The telephone interview is divided into following sections: administrative data; labor market experience; employment; job-seekers; not in labor force; education; family composition; child care; health status; other household members; housing conditions; vacation homes; and cars and boats. The questionnaire was divided into twelve sections: sale of previous home; acquisition of current home; construction costs for building a home; house value and loans; repairs; insurance; home-related expenses; sale of previous home; assets; household income; taxes; and respondent income 1992. The 1996 telephone interview is divided into following sections: administrative data; labor market experience; employment; job-seekers; not in labor force; education; family composition; child care; health status; other household members; housing conditions; vacation homes; cars and boats; and environment. The questionnaire was divided into twelve sections: sale of previous home; acquisition of current home; construction costs for building a home; house value and loans; repairs; insurance; home-related expenses; sale of previous home; assets; household income; taxes; and respondent income 1995. The 1998 telephone interview is divided into following sections: administrative data; labor market experience; employment; job-seekers; not in labor force; education; family composition; child care; health status; other household members; housing conditions; vacation homes; cars and boats; and municipal service. The questionnaire was divided into nine sections: sale of previous home; house value and loans; insurance; home-related expenses; assets; household income; inheritances and gifts; black-market work; and respondent income 1997.

Analysis unit

Woman, Birth, Child, Birth, Man, Household Member

Universe

Ever-married women age 15-49, Births, Children age 0-4, All persons

Kind of data

Demographic and Household Survey [hh/dhs]

Sampling procedure

MICRODATA SOURCE: Department of Statistics [Jordan] and Macro International.

SAMPLE UNIT: Woman SAMPLE SIZE: 10876

SAMPLE UNIT: Birth SAMPLE SIZE: 43460

SAMPLE UNIT: Child SAMPLE SIZE: 10426

SAMPLE UNIT: Member SAMPLE SIZE: 82460

Mode of data collection

Face-to-face [f2f]

Analysis unit

Woman, Birth, Child, Birth, Man, Household Member

Universe

Ever-married women age 15-49, Births, Children age 0-4, Ever-married men age 15-49, All persons

Kind of data

Demographic and Household Survey [hh/dhs]

Sampling procedure

MICRODATA SOURCE: National Institute of Population Studies (NIPS) [Pakistan], and ICF.

SAMPLE UNIT: Woman SAMPLE SIZE: 15068

SAMPLE UNIT: Birth SAMPLE SIZE: 50495

SAMPLE UNIT: Child SAMPLE SIZE: 12708

SAMPLE UNIT: Man SAMPLE SIZE: 3691

SAMPLE UNIT: Member SAMPLE SIZE: 100869

Mode of data collection

Face-to-face [f2f]

Households, persons by number of active members in the household in the last week and average size of the household. National. Households resident in main family dwellings by number of active members in the last week.

Abstract

The Statistical Office of the Republic of Serbia has been conducting the Household Budget Survey since 2003 according to international standards and recommendations of Eurostat, International Labor Organization and Unites Nations to provide for international data comparability.

The survey collects data on cash expenses of households for food, clothes and footwear, rent, fuel and lightening, health care, education, traffic, hygiene, culture, etc. It also gathers information on household income, dwelling conditions, as well as data on the level of supply with durable consumer goods.

The Household Budget Survey is used for: - analysis of structural changes in consumption resulting from changes in economy, - construction of poverty line on the basis of which is determined the level of social assistance, - calculating personal consumption of the population in National Accounts, as well as for calculating Consumer Price Index (CPI), - calculation of quantity or value of consumption of specific products and services.

Two hundred households are interviewed every fifteen days, resulting in 4,800 households annually. The data is collected using two methods: diary keeping and face-to-face interviews. A household keeps an individual consumption diary for fifteen days, documenting items and services of individual consumption. In interviews, the reference period for durable goods is twelve months, for semi-durable goods is three months, and for income, agriculture, hunting and fishing is three months.

Geographic coverage

National

Analysis unit

A survey unit is a single- or several-member household, selected according to the sample plan. Household members are the following persons: - Pupils and students are considered members of a household, regardless the time spent outside his/her household (schools, universities); - Household members, temporarily absent (persons in compulsory military service, serving the sentence in prison less than a year) are included in the survey; - Daily or weekly migrants, persons who work or go to school in other place in the country or abroad and have economic relations with household (with no household there) where they stay more than a month during a year, are also considered as household members and temporarily absent persons; - Persons who stay longer in other place in the country or abroad (a year and more), but rarely come or absolutely don’t come to the place of resident place are considered as long-term absents and are excluded from the survey; - Subtenants (lodgers) who live in same dwelling or house with household, but do not eat together with household members, are not included into members of that household, but are separate household with residence on that address and are surveyed as separate household in that housing unit.

Universe

The survey covers all private households in Serbia. HBS does not cover collective households (hospitals, prisons, monasteries, boarding schools and similar). But, if a person stays in a collective household for less than six month, then he or she is included the survey.

Kind of data

Sample survey data [ssd]

Sampling procedure

A two-stage stratified sample is used in the survey, with enumerative districts as primary units and households as secondary ones.

Basic geographical strata are Central Serbia (without Belgrade), Belgrade, and Vojvodina. Primary units (enumerative districts) were classified according to the 1991 Census into two contingents - urban (city) and rural (village) depending on the type of settlement they belonged to.

Every fifteen days 40 enumerated districts have been chosen (200 households). Last stratification step (determined by number of households) is grouping of primary units by size. For each formed contingent of the enumerated districts, relevant primary units have been arranged according to number of households. Thus, two size strata with same or approximate total number of households were formed. Sample allocation of primary units by geographical strata that is, by areas - urban and rural, is proportional to the number of observation units in those contingents. Enumerative districts with at least 30 households in the urban area, and those with at least 15 households in rural area were used for determining the scope for primary units selection.

Primary units (enumerative districts) were selected within the sample with likelihood of selection proportional to the number of households within them. Within the selected primary units, by simple random selection, five households were selected. The substitution of households is not predicted. New households, formed within the chosen household in the same housing unit have been surveyed, too.

Mode of data collection

Face-to-face [f2f]

Research instrument

Researchers collect data with the help of face-to-face interviews and diaries that are kept by household members.

Diaries gather expenditure information on the following items: - food, - alcohol, tobacco, - other household non-durables (such as newspapers, batteries), - clothing, footwear, - other personal non-durables (such as perfume), - household services (for example, plumbing services), - personal services (such as driving lessons, haircuts), - all items except durables.

Questionnaires collect other expenditure data, with the respondent completing the interview by a mix of recall and use of documentation. COICOP classification is used to code expenditure items.

Abstract

The survey provides statistically sound and internationally comparable data essential for developing evidence-based policies and programmes, and for monitoring progress toward national goals and global commitments. The Kiribati Social Development Indicator Survey (SDIS) results are critically important for the purposes of Sustainable Development Goal (SDG) monitoring, as the survey produces information on 32 global SDG indicators adopted by the National Development Indicators framework, either in their entirety or partially.

The 2018-19 Kiribati SDIS has as its primary objectives: • To provide high quality data for assessing the situation of children, adolescents, women and households in KSDIS; • To furnish data needed for monitoring progress toward national goals, as a basis for future action; • To collect disaggregated data for the identification of disparities, to inform policies aimed at social inclusion of the most vulnerable; • To validate data from other sources and the results of focused interventions; • To generate data on national and global SDG indicators; • To generate internationally comparable data for the assessment of the progress made in various areas, and to put additional efforts in those areas that require more attention; • To generate behavioural and attitudinal data not available in other data sources.

Geographic coverage

National Coverage: covering rural-urban areas and for the five district/island groups of the country (South Tarawa, Northern Gilbert, Central Gilbert, Southern Gilbert, and Line and Phoenix groups).

Analysis unit

-Household; -Household member; -Mosquito nets; -Women in reproductive age; -Birth history; -Men in reproductive age; -Mothers or primary caretakers of children under 5; -Mothers or primary caretakers of children age 5-17.

Universe

The survey covered all de jure household members (usual residents), all women aged between 15 to 49 years, all men aged between 15 to 49 years, all children under 5 and those aged 5 to 17 living in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

-SELECTION PROCESS: The sample for the Kiribati Social Development Indicator Survey (SDIS) 2018-19 was designed to provide estimates for a large number of indicators on the situation of children and women at the national, rural-urban, South Tarawa, Northern Gilbert, Central Gilbert, Southern Gilbert and Line and Phoenix group. The urban and rural areas within each district were identified as the main sampling strata and the sample of households was selected in two stages. Within each stratum, a specified number of census Enumeration Areas (EAs) were selected systematically with probability proportional to size. After a household listing was carried out within the selected enumeration areas, a systematic sample of 3280 households was drawn in each sample enumeration area. All of the selected enumeration areas were visited during the fieldwork period.

A multi-stage, stratified cluster sampling approach was used for the selection of the survey sample. The sampling frame was based on the full/national household listing (mini-census) conducted in 2018 because the last census (2015) could not be used as a sampling frame as the EA boundaries differed from the 2010 Kiribati Census. The primary sampling units (PSUs) selected at the first stage were the enumeration areas (EAs) defined for the census enumeration.

-SAMPLE SIZE AND SAMPLE ALLOCATION: Since the overall sample size for the Kiribati SDIS partly depends on the geographic domains of analysis that are defined for the survey tables, the distribution of EAs and households in Kiribati from the 2018 Household Listing /Mini Census sampling frame was first examined by region, urban and rural strata.

The overall sample size for the Kiribati SDIS was calculated as 3,280 households. For the calculation of the sample size, the key indicator used was the underweight prevalence among children age 0-4 years. Since the survey results are tabulated at the regional level, it was necessary to determine the minimum sample size for each region.

For the calculation, r (underweight prevalence) was assumed to be 15 percent based on the national estimate from the Demographic and Health SUrvey (DHS) 2009. -The value of deff (design effect) was taken as 1.0 based on the estimate from the DHS 2009, -pb (percentage of children age 0-4 years in the total population) was taken as 12 percent, -AveSize (mean household size) was taken as 6.0 based on the 2018 mini-Census, and the response rate was assumed to be 98 percent, based on experience from the DHS 2009. -It was decided that an RME of at most 20 percent was needed for the district/island group estimates; this would result in an RME of 10 percent for the national estimate. The calculations resulted in a total sample size of 3,280 households, with the sample sizes in the districts varying between 515 and 780. The sample size in South Tarawa (urban) was adjusted upwards from 780 to 1,080 households in order to improve the precision in urban/rural comparisons. The sample sizes in the other districts/island groups were reduced by 75 households each.

The number of households selected per cluster for the Kiribati SDIS was determined as 20 households, based on several considerations, including the design effect, the budget available, and the time that would be needed per team to complete one cluster.

Census enumeration areas were selected from each of the sampling strata by using systematic probability proportional to size (pps) sampling procedures, based on the number of households in each enumeration area from the 2018 Mini- Census frame. The first stage of sampling was thus completed by selecting the required number of sample EAs (specified in Table SD.2) from each of the five district/Island groups.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

-QUESTIONNAIRE DESCRIPTION: Six questionnaires were used in the survey: 1) a household questionnaire to collect basic demographic information on all de jure household members (usual residents), the household, and the dwelling; 2) a water quality testing questionnaire administered in 4 households in each cluster of the sample; 3) a questionnaire for individual women administered in each household to all women age 15-49 years; 4) a questionnaire for individual men administered in every second household to all men age 15-49 years; 5) an under-5 questionnaire, administered to mothers (or caretakers) of all children under 5 living in the household; and 6) a questionnaire for children age 5-17 years, administered to the mother (or caretaker) of one randomly selected child age 5-17 years living in the household.

The questionnaires were based on the Multiple Indicator Cluster Surveys 6 (MICS6) standard questionnaires except for questionnaire for individual women/men had some add-on questions and/or modules from the Demographic and Health Surveys (DHS) programme. From the MICS6 model English version, the questionnaires were customised and translated into Kiribati language and were pre-tested in South Tarawa during September, 2018. Based on the results of the pre-test, modifications were made to the wording and translation of the questionnaires. A copy of the Kiribati Social Development Indicator Survey (SDIS) 2018-19 questionnaires is provided in the External Resources of this documentation.

-COMPOSITION OF THE QUESTIONNAIRES: The questionnaires included the following modules: -Household questionnaire: List of household members, Education, Household characteristics, Social transfers, Household energy use, Dengue, Water and sanitation, Handwashing, Salt iodisation.

-Water Quality Testing questionnaire: Water quality tests, Water quality testing results.

-Individual Women questionnaire: Background, ICT, Fertility/Birth history, Desire for last birth, Maternal and newborn health, Post-natal health checks, Contraception, Unmet need, Attitudes toward domestic violence, Victimisation, Marriage/union, Adult functioning, Sexual behaviour, HIV/AIDS, STI, Tobacco and alcohol use, Domestic violence, Life satisfaction.

-Individual Men questionnaire: Background, ICT, Fertility, Contraception, Unmet need, Attitudes toward domestic violence, Victimisation, Marriage/union, Adult functioning, Sexual behaviour, HIV/AIDS, STI, Circumcision, Tobacco and alcohol use, Life satisfaction.

-Children Under 5 questionnaire: Background, Birth registration, Early childhood development, Chil discipline, Child functioning, Breastfeeding and dietary intake, Immunisation, Care of illness, Anthropometry.

-Children Age 5-17 Years questionnaire: Background, Child labour, Child discipline, Child functioning, Parental involvment, Foundational learning skills.

Cleaning operations

Data were received at the National Statistical Office's central office via Internet File Streaming System (IFSS) integrated into the management application on the supervisors' tablets. Whenever logistically possible, synchronisation was daily. The central office communicated application updates to field teams through this system.

During data collection and following the completion of fieldwork, data were edited according to editing process described in detail in the Guidelines for Secondary Editing, a customised version of the standard MICS6 documentation.

Data editing took place at a number of stages throughout the processing (see Other processing), including: a) During data collection b) Structure checking and completeness c) Secondary editing d) Structural checking of SPSS data files

Detailed documentation of the editing of

Background: Clean water is an essential part of human healthy life and wellbeing. More recently, rapid population growth, high illiteracy rate, lack of sustainable development, and climate change; faces a global challenge in developing countries. The discontinuity of drinking water supply forces households either to use unsafe water storage materials or to use water from unsafe sources. The present study aimed to identify the determinants of water source types, use, quality of water, and sanitation perception of physical parameters among urban households in North-West Ethiopia.

Methods: A community-based cross-sectional study was conducted among households from February to March 2019. An interview-based a pretested and structured questionnaire was used to collect the data. Data collection samples were selected randomly and proportional to each of the kebeles' households. MS Excel and R Version 3.6.2 were used to enter and analyze the data; respectively. Descriptive statistics using frequencies and percentages were used to explain the sample data concerning the predictor variable. Both bivariate and multivariate logistic regressions were used to assess the association between independent and response variables.

Results: Four hundred eighteen (418) households have participated. Based on the study undertaken,78.95% of households used improved and 21.05% of households used unimproved drinking water sources. Households drinking water sources were significantly associated with the age of the participant (x2 = 20.392, df=3), educational status(x2 = 19.358, df=4), source of income (x2 = 21.777, df=3), monthly income (x2 = 13.322, df=3), availability of additional facilities (x2 = 98.144, df=7), cleanness status (x2 =42.979, df=4), scarcity of water (x2 = 5.1388, df=1) and family size (x2 = 9.934, df=2). The logistic regression analysis also indicated that those factors are significantly determining the water source types used by the households. Factors such as availability of toilet facility, household member type, and sex of the head of the household were not significantly associated with drinking water sources.

Conclusion: The uses of drinking water from improved sources were determined by different demographic, socio-economic, sanitation, and hygiene-related factors. Therefore, ; the local, regional, and national governments and other supporting organizations shall improve the accessibility and adequacy of drinking water from improved sources in the area.

Japan Incl Living Expenditure Index (LEI): Number Household Member data was reported at 95.400 2015=100 in May 2018. This records a decrease from the previous number of 103.600 2015=100 for Apr 2018. Japan Incl Living Expenditure Index (LEI): Number Household Member data is updated monthly, averaging 103.300 2015=100 from Jan 1981 (Median) to May 2018, with 449 observations. The data reached an all-time high of 145.300 2015=100 in Dec 1990 and a record low of 88.900 2015=100 in Oct 1981. Japan Incl Living Expenditure Index (LEI): Number Household Member data remains active status in CEIC and is reported by Statistical Bureau. The data is categorized under Global Database’s Japan – Table JP.H068: Living Expenditure Index: Adj by Distribution of Household by No of Household Member&Age of Household Head.

The theme of this year's survey is "Orange County: Approaching the 1990s. The survey is designed to provide an extensive analysis of issues affecting the next decade. The sample size is 1,085 Orange County adult residents.Online data analysis & additional documentation in Link below. Methods The Orange County Annual survey was directed by Mark Baldassare, a professor of social ecology at UC Irvine. For the survey, 1,085 adult orange County residents were interviewed by telephone Sept. 6 to 23. In Orange County, where more than 97 percent of households have telephones, this method of interview gives highly representative data.Interviewing was conducted on weekend days and weekday nights, using a random sample of 4,500 listed and unlisted telephone numbers. These were generated by computer from a list of working blocks of telephone exchanges. The telephone sample was generated by Pijacki and Associates of Shoreham, N.Y. The field work was conducted at the Center for Survey Research by UCI's Public Policy Research Organization.Of the telephone numbers called, 23 percent resulted in completed interviews and 15 percent were refusals. The completion rate for the survey (completions divided bycompletions plus refusals) was 61 percent.Other telephone outcomes included the following: 21 percent disconnected numbers; 3 percent computer or fax lines; 15 percent businesses and other non-Orange County households; 20 percent persistent no answers and l percent persistently unavailable respondents. Two percent were not completed because of language problems, including non-English speaking households, and hearing impairment.Within a-household, respondents were chosen for interview using the Troldahl-Carter method. This method randomly selects a household member from a grid that includes information on the number of adult household members and the number of adult men in the household. Up to six callbacks were attempted per telephone number.Each interview included 90 questions and took an average of 20 minutes to complete. Most interviews ranged in length from 15 to 25 minutes.The surveys were designed in three stages over several months. In the first stage, UCI undergraduate students conducted face-to-face, interviews on Orange County topics with randomly selected adult residents. The second stage involved feedback on questions and topics from the annual survey's Steering Committee, Advisory Committee and colleagues. The final stage included pre-tests by students, followed by final revisions of the questions.The interview began with questions about housing, moving preferences, consumer confidence and perceptions of life in Orange County. These were followed by questions on growth, transportation and crime issues. A major section of the interview was then devoted to questions about air pollution and the Air Quality Management Plan. Later in the interview, we turned to the topics of charities. The conclusion of the survey was devoted to questions about work and commuting patterns, personal characteristics, household status and political attitudes.The survey's validity was checked by comparing the sample's characteristics to available information on Orange County's population. We compared the 1989 survey results to the 1980 U.S. Census, previous annual surveys and other recent survey data. Age, income and other demographic features of our sample were comparable with those noted in other studies.For data analyses, we statistically weighted the sample to represent the actual regional distribution of Orange County residents. The 1989 population estimates for north, west, central and south county regions were issued by the Demographic Research Unit, County of Orange.Other efforts were made to correct for possible errors in the course of interviewing and data processing. Approximately 10 percent of the completed interviews were verified through callbacks. All questionnaires were checked by the interviewer supervisor immediately after completion. Finally, keypunched data were double-checked for all cases in the survey sample.The sampling error for this survey is +/3 percent at the 95 percent confidence level. This means that 95 times out of 100, the results will-be within 3 percentage pointsof what they would be if all adults in Orange County were interviewed. The sampling error for any subgroup would be larger.Sampling error is just one type of error to which surveys are subject. Results may also influenced by factors such as question wording, survey timing and other aspects of survey design.

Abstract

Within the frame of PCBS' efforts in providing official Palestinian statistics in the different life aspects of Palestinian society and because the wide spread of Computer, Internet and Mobile Phone among the Palestinian people, and the important role they may play in spreading knowledge and culture and contribution in formulating the public opinion, PCBS conducted the Household Survey on Information and Communications Technology, 2014.

The main objective of this survey is to provide statistical data on Information and Communication Technology in the Palestine in addition to providing data on the following: -

· Prevalence of computers and access to the Internet. · Study the penetration and purpose of Technology use.

Geographic coverage

Palestine (West Bank and Gaza Strip) , type of locality (Urban, Rural, Refugee Camps) and governorate

Analysis unit

Household. Person 10 years and over .

Universe

All Palestinian households and individuals whose usual place of residence in Palestine with focus on persons aged 10 years and over in year 2014.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling Frame The sampling frame consists of a list of enumeration areas adopted in the Population, Housing and Establishments Census of 2007. Each enumeration area has an average size of about 124 households. These were used in the first phase as Preliminary Sampling Units in the process of selecting the survey sample.

Sample Size The total sample size of the survey was 7,268 households, of which 6,000 responded.

Sample Design The sample is a stratified clustered systematic random sample. The design comprised three phases:

Phase I: Random sample of 240 enumeration areas. Phase II: Selection of 25 households from each enumeration area selected in phase one using systematic random selection. Phase III: Selection of an individual (10 years or more) in the field from the selected households; KISH TABLES were used to ensure indiscriminate selection.

Sample Strata Distribution of the sample was stratified by: 1- Governorate (16 governorates, J1). 2- Type of locality (urban, rural and camps).

Sampling deviation

-

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey questionnaire consists of identification data, quality controls and three main sections: Section I: Data on household members that include identification fields, the characteristics of household members (demographic and social) such as the relationship of individuals to the head of household, sex, date of birth and age.

Section II: Household data include information regarding computer processing, access to the Internet, and possession of various media and computer equipment. This section includes information on topics related to the use of computer and Internet, as well as supervision by households of their children (5-17 years old) while using the computer and Internet, and protective measures taken by the household in the home.

Section III: Data on persons (aged 10 years and over) about computer use, access to the Internet and possession of a mobile phone.

Cleaning operations

Preparation of Data Entry Program: This stage included preparation of the data entry programs using an ACCESS package and defining data entry control rules to avoid errors, plus validation inquiries to examine the data after it had been captured electronically.

Data Entry: The data entry process started on 8 May 2014 and ended on 23 June 2014. The data entry took place at the main PCBS office and in field offices using 28 data clerks.

Editing and Cleaning procedures: Several measures were taken to avoid non-sampling errors. These included editing of questionnaires before data entry to check field errors, using a data entry application that does not allow mistakes during the process of data entry, and then examining the data by using frequency and cross tables. This ensured that data were error free; cleaning and inspection of the anomalous values were conducted to ensure harmony between the different questions on the questionnaire.

Response rate

Response Rates= 79%

Sampling error estimates

There are many aspects of the concept of data quality; this includes the initial planning of the survey to the dissemination of the results and how well users understand and use the data. There are three components to the quality of statistics: accuracy, comparability, and quality control procedures.

Checks on data accuracy cover many aspects of the survey and include statistical errors due to the use of a sample, non-statistical errors resulting from field workers or survey tools, and response rates and their effect on estimations. This section includes:

Statistical Errors Data of this survey may be affected by statistical errors due to the use of a sample and not a complete enumeration. Therefore, certain differences can be expected in comparison with the real values obtained through censuses. Variances were calculated for the most important indicators.

Variance calculations revealed that there is no problem in disseminating results nationally or regionally (the West Bank, Gaza Strip), but some indicators show high variance by governorate, as noted in the tables of the main report.

Non-Statistical Errors Non-statistical errors are possible at all stages of the project, during data collection or processing. These are referred to as non-response errors, response errors, interviewing errors and data entry errors. To avoid errors and reduce their effects, strenuous efforts were made to train the field workers intensively. They were trained on how to carry out the interview, what to discuss and what to avoid, and practical and theoretical training took place during the training course. Training manuals were provided for each section of the questionnaire, along with practical exercises in class and instructions on how to approach respondents to reduce refused cases. Data entry staff were trained on the data entry program, which was tested before starting the data entry process.

Several measures were taken to avoid non-sampling errors. These included editing of questionnaires before data entry to check field errors, using a data entry application that does not allow mistakes during the process of data entry, and then examining the data by using frequency and cross tables. This ensured that data were error free; cleaning and inspection of the anomalous values were conducted to ensure harmony between the different questions on the questionnaire.

The sources of non-statistical errors can be summarized as: 1. Some of the households were not at home and could not be interviewed, and some households refused to be interviewed. 2. In unique cases, errors occurred due to the way the questions were asked by interviewers and respondents misunderstood some of the questions.

Abstract

Time use surveys are crucial instruments in social science research that provide valuable insights into how individuals allocate their time across various activities. These surveys systematically capture and quantify the amount of time people spend on diverse pursuits, such as work, leisure, household chores, and personal care. The data collected through time use surveys offer researchers a comprehensive understanding of societal trends, patterns, and dynamics, shedding light on evolving social structures, economic activities, and cultural practices. By examining how individuals distribute their time, researchers can discern patterns related to gender roles, socioeconomic disparities, and lifestyle changes. Time use surveys also play a pivotal role in informing public policy and program development, guiding decisions on issues ranging from labor market regulations to family support systems. Furthermore, these surveys contribute to the advancement of our understanding of human behavior and well-being, offering a nuanced perspective on the complexities of modern life and its impact on individuals and societies. As such, time use surveys are indispensable tools for scholars, policymakers, and social scientists alike, fostering a deeper comprehension of the intricate interplay between time allocation and various socio-economic factors.

Geographic coverage

Governorate (16 governorates in west bank and Gaza strip) Locality type (urban, rural, camps)

Analysis unit

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

Universe

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

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame of the survey consists of a list of enumeration areas from the population and buildings and establishments census which was implemented by PCBS in 2007 (the enumeration area is a geographical area contains number of households of about 124 households in average).The enumeration areas will be used as primary sampling units in sampling design (PSUs). Sample Size The sample size of the survey is 5,903 Palestinian households. Sampling Design After determining the sample size, the sample type is three-stage stratified cluster sample as following: 1- First stage: selecting systematic sample of 220 clusters (enumeration areas). 2- Second stage: selection sample of 21 responded households from each EA selected in the first stage (we use the area sampling to get this number of responded households). 3- Third stage: selection two individuals male and female (10 years and more) from each household selected in second stage using random kish tables. The population was divided to strata by: 1- Governorate (16 governorates in west bank and Gaza strip) 2- Locality type (urban, rural, camps) Target population of the survey consists of all Palestinian individuals of age group 10 years and over, who are living normally with their households in Palestine in 2012/2013 .

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey questionnaire is the main tool for data collection and was designed on the basis of international surveys specially designed for time use surveys, as well as on the basis of the recommendations of the workshop on time use surveys held in Jordan in 2010. This was organized by ESCWA in cooperation with UNSD to develop a questionnaire for a time use survey and coding manual, along with adding activities related to the Palestinian context compatible with the coding manual of the United Nations of 2006. The questionnaire meets the technical specifications for the field work phase and data processing and analysis requirements. The questionnaire included several sections: 1. Household Members Background Details:
These include household members, relationship to the head of household, gender, date of birth and age, in addition to other demographic and economic data for the household as a whole. 2. Household Questionnaire:
This includes questions related to the household in terms of type of housing unit, material used as flooring in the housing unit, primary fuel type used in cooking, goods and services available, monthly household income, and other indicators. 3. Daily Record Questionnaire: This part of the questionnaire comprised two time records: in the first record, one male member of the household aged 10 years and above is selected at random and in the second record, one female household member aged 10 years and above is selected at random. The day was divided into periods of time of up to 30 minutes each from midnight until six am and [00] 10 minutes for each period during the day from six am until twelve o'clock at night. The record also contains information that shows whether the activity was performed for a fee or financial return or not. Any secondary activity is also recorded. This information identifies the respondent performing these activities, with whom and the means of transportation or venue where the individual performed the various activities throughout the day (during a 24-hour period).

Response rate

The sample size of the survey was 5,903 households and 4,605 households were completed. Weights were adjusted to compensate for the non-response cases. The response rate in the survey in Palestine was 79.6% for households, and 98.1% for the individuals , where 8,560 completed the questionnaire out of 8,779 individuals.

A survey conducted in 2020 revealed that ** percent of the respondents who lived on their own in the United Kingdom (UK) always checked the protein content when buying food, compared to ***** percent of the respondents who lived with *** other people. A share of ** percent of the respondents from households with **** members stated that they never looked at the protein content of the food they were buying.

Background
The Labour Force Survey (LFS) is a unique source of information using international definitions of employment and unemployment and economic inactivity, together with a wide range of related topics such as occupation, training, hours of work and personal characteristics of household members aged 16 years and over. It is used to inform social, economic and employment policy. The LFS was first conducted biennially from 1973-1983. Between 1984 and 1991 the survey was carried out annually and consisted of a quarterly survey conducted throughout the year and a 'boost' survey in the spring quarter (data were then collected seasonally). From 1992 quarterly data were made available, with a quarterly sample size approximately equivalent to that of the previous annual data. The survey then became known as the Quarterly Labour Force Survey (QLFS). From December 1994, data gathering for Northern Ireland moved to a full quarterly cycle to match the rest of the country, so the QLFS then covered the whole of the UK (though some additional annual Northern Ireland LFS datasets are also held at the UK Data Archive). Further information on the background to the QLFS may be found in the documentation.

Household datasets
Up to 2015, the LFS household datasets were produced twice a year (April-June and October-December) from the corresponding quarter's individual-level data. From January 2015 onwards, they are now produced each quarter alongside the main QLFS. The household datasets include all the usual variables found in the individual-level datasets, with the exception of those relating to income, and are intended to facilitate the analysis of the economic activity patterns of whole households. It is recommended that the existing individual-level LFS datasets continue to be used for any analysis at individual level, and that the LFS household datasets be used for analysis involving household or family-level data. From January 2011, a pseudonymised household identifier variable (HSERIALP) is also included in the main quarterly LFS dataset instead.

Change to coding of missing values for household series
From 1996-2013, all missing values in the household datasets were set to one '-10' category instead of the separate '-8' and '-9' categories. For that period, the ONS introduced a new imputation process for the LFS household datasets and it was necessary to code the missing values into one new combined category ('-10'), to avoid over-complication. This was also in line with the Annual Population Survey household series of the time. The change was applied to the back series during 2010 to ensure continuity for analytical purposes. From 2013 onwards, the -8 and -9 categories have been reinstated.

LFS Documentation
The documentation available from the Archive to accompany LFS datasets largely consists of the latest version of each volume alongside the appropriate questionnaire for the year concerned. However, LFS volumes are updated periodically by ONS, so users are advised to check the ONS LFS User Guidance page before commencing analysis.

Additional data derived from the QLFS
The Archive also holds further QLFS series: End User Licence (EUL) quarterly datasets; Secure Access datasets (see below); two-quarter and five-quarter longitudinal datasets; quarterly, annual and ad hoc module datasets compiled for Eurostat; and some additional annual Northern Ireland datasets.

End User Licence and Secure Access QLFS Household datasets
Users should note that there are two discrete versions of the QLFS household datasets. One is available under the standard End User Licence (EUL) agreement, and the other is a Secure Access version. Secure Access household datasets for the QLFS are available from 2009 onwards, and include additional, detailed variables not included in the standard EUL versions. Extra variables that typically can be found in the Secure Access versions but not in the EUL versions relate to: geography; date of birth, including day; education and training; household and family characteristics; employment; unemployment and job hunting; accidents at work and work-related health problems; nationality, national identity and country of birth; occurrence of learning difficulty or disability; and benefits. For full details of variables included, see data dictionary documentation. The Secure Access version (see SN 7674) has more restrictive access conditions than those made available under the standard EUL. Prospective users will need to gain ONS Accredited Researcher status, complete an extra application form and demonstrate to the data owners exactly why they need access to the additional variables. Users are strongly advised to first obtain the standard EUL version of the data to see if they are sufficient for their research requirements.

Changes to variables in QLFS Household EUL datasets
In order to further protect respondent confidentiality, ONS have made some changes to variables available in the EUL datasets. From July-September 2015 onwards, 4-digit industry class is available for main job only, meaning that 3-digit industry group is the most detailed level available for second and last job.

Review of imputation methods for LFS Household data - changes to missing values
A review of the imputation methods used in LFS Household and Family analysis resulted in a change from the January-March 2015 quarter onwards. It was no longer considered appropriate to impute any personal characteristic variables (e.g. religion, ethnicity, country of birth, nationality, national identity, etc.) using the LFS donor imputation method. This method is primarily focused to ensure the 'economic status' of all individuals within a household is known, allowing analysis of the combined economic status of households. This means that from 2015 larger amounts of missing values ('-8'/-9') will be present in the data for these personal characteristic variables than before. Therefore if users need to carry out any time series analysis of households/families which also includes personal characteristic variables covering this time period, then it is advised to filter off 'ioutcome=3' cases from all periods to remove this inconsistent treatment of non-responders.

Occupation data for 2021 and 2022 data files

The ONS has identified an issue with the collection of some occupational data in 2021 and 2022 data files in a number of their surveys. While they estimate any impacts will be small overall, this will affect the accuracy of the breakdowns of some detailed (four-digit Standard Occupational Classification (SOC)) occupations, and data derived from them. Further information can be found in the ONS article published on 11 July 2023: https://www.ons.gov.uk/employmentandlabourmarket/peopleinwork/employmentandemployeetypes/articles/revisionofmiscodedoccupationaldataintheonslabourforcesurveyuk/january2021toseptember2022" style="background-color: rgb(255, 255, 255);">Revision of miscoded occupational data in the ONS Labour Force Survey, UK: January 2021 to September 2022.

Abstract

The 2009 Samoa Demographic and Health Survey (SDHS) is a national survey covering all four regions of the country. The survey was designed to collect, analyze, and disseminate information on housing and household characteristics, education, maternal and child health, nutrition, fertility and family planning, gender, and knowledge and behaviour related to HIV/AIDS and sexually transmitted infections (STI).

The 2009 SDHS is the first DHS survey to be undertaken in Samoa both by the health sector and for an improved health system. The planning and implementation of the survey was carried out jointly by the Samoa Bureau of Statistics (SBS) and the Ministry of Health (MOH) with the technical assistance and guidance of ICF Macro. The Ministry of Women, Community and Social Development assisted by facilitating community support for the survey through villages and mayors.

The Samoa DHS is part of a worldwide survey program. The international MEASURE DHS program is designed to:

• Assist countries in conducting household sample surveys to periodically monitor changes in population, health, and nutrition. • Provide an international database that can be used by researchers investigating topics related to population, health, and nutrition.

As part of the international DHS program, surveys are being carried out in countries in Africa, Latin America and the Caribbean, Asia, Eastern Europe and the Middle East. Data from these surveys are used to better understand the population, health, and nutrition situation in Samoa.

Geographic coverage

National Regional Urban and Rural

Analysis unit

individual (woman aged 15-49, man aged 15-54), household

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49 and men aged 15-54 years

Kind of data

Sample survey data [ssd]

Sampling procedure

The Survey used a two-stage sample based on the 2006 Population and Housing Census (PHC) to allow reliable estimation of key demographic and health indicators such as fertility, contraceptive prevalence, and infant and child mortality for each of the four geographic regions in Samoa.

The population covered in the 2009 SDHS is the universe of all women age 15-49 in Samoa in a sample of 2,247 selected households. Every other household selected for the women's samplev was also eligible for the men's sample (men age 15-54).

The primary sampling unit (PSU) for the 2009 SDHS was the cluster. The first stage involved selecting clusters from the master sample frame (the 2006 Population and Housing Census). In the second stage, all the households in each selected cluster were listed. Households were then systematically selected from each cluster for participation in the survey. The design did not allow for replacement of clusters or households.

The sample was designed to include10 percent of the households in rural areas and 12 percent of the households in the urban areas. The sample was designed to permit detailed analysis of most indicators for the national level, for urban and rural areas separately, and for each of the four regions (Apia Urban Area, North West Upolu, Rest of Upolu, and Savaii). Overall, a total of 296 primary sampling units or clusters were selected, 104 in urban areas and 196 in the rural areas. Because Samoan household do not move frequently, a fresh household listing was not deemed to be necessary. Instead, a list from the November was used. In the urban clusters, 5 households were selected per cluster, whereas in the rural clusters, 10 households were selected per cluster. The number of clusters in each of the four geographical regions was calculated by diving the total allocated number of households by the sample taken of 5 for Apia Urban Area (the number of households of households in the urban EAs) and 10 for other regions (the number of households for rural EAs). In each region EAs were stratified by urban location first and then by rural location. Clusters were selected systematically, with propability proportional to size.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three questionnaires were used in the SDHS: a Household Questionnaire, a Women's Questionnaire, and a Men's Questionnaire. The household and individual questionnaires were based on model survey instruments developed in the MEASURE DHS program. The model questionnaires were adapted to meet the current needs of Samoa. Each household selected for the SDHS was eligible for interview with the Household Questionnaire.

The Household Questionnaire was used to list all usual members of and visitors to the selected households and to collect information on the socio-economic status of the household. It was also used to identify the women and men who were eligible for the individual interview (i.e., women age 15-49 and men age 15-54).

The Women's Questionnaire was used to collect information from all women age 15-49 years and covered the following topics: - background characteristics (education, residential history, media exposure, etc.) - birth history - antenatal, delivery, and postnatal care - knowledge, attitudes, and use of family planning methods - fertility preferences; marriage, woman's work, and husband's background characteristics - breastfeeding and infant feeding practices; vaccinations and childhood illnesses - childhood mortality - knowledge of and attitudes toward aids and other sexually transmitted diseases - knowledge of and attitudes toward tuberculosis - other health issues.

The Men's Questionnaire, administered to all men age 15-54 years living in every other Household (i.e. half of the sample households), collected information similar to that on the Women's Questionnaire but was shorter because it did not contain questions on reproductive history, maternal and child health, and nutrition.

After finalization of the questionnaires in English, they were translated into Samoan.

Cleaning operations

The processing of the SDHS results began shortly after the fieldwork started. Data editing was first done in the field by the field editors and supervisors. Completed and edited questionnaires for each cluster were packed and delivered to the SDHS centre at Motootua where they were entered and edited by data processing personnel. The data processing team was composed of 15 data entry operators, 1 data entry supervisor with 2 assistants and 7 office editors working in two shifts. Data operators and supervisors went through a one-week training programme with the technical assistance of ICF Macro. Data were entered using CSPro, a programme specially developed for use in household based surveys and censuses. All data were entered twice (100 percent verification). The concurrent processing of the data was an advantage because the survey technical staff were able to advise field teams of problems detected during the data entry using tables generated to check various data quality parameters. As a result, specific feedback was given to the teams to improve their performances. The data entry and editing phase of the survey was completed in February 2010.

Response rate

The Samoa DHS 2009 selected 2,247 households for the sample, of which 2,066 were found occupied at the time of the fieldwork. Of these 1947 households were successfully interviewed yielding a household response rate of 94 percent.

In the households interviewed, a total of 3,033 eligible women aged 15-49 were identified, of whom 2657 were interviewed (respond rate of 88 percent). For eligible men aged 15-54 were identified in the sub-sample a total of 1,689 but only 1,307 were successfully interviewed (respond rate of 77 percent).

By area, response rates for households and women are slightly lower in urban (82 and 86 percent, respectively) than in rural areas (95 and 86 percent, respectively). For men on the other hand, response rate is higher in urban areas, 81 percent, than in rural areas, 76 percent.

The principal reason for non-response for eligible women and men was the failure to find them at home despite repeated visits to the households. The substantially lower response rates for men reflect the more frequent and longer absences of men from the home.

Response rates by region and the details on the calculation of the response rates can be found in Appendix A of the 2009 SDHS report.

Sampling error estimates

Sampling errors for the 2009 SDHS were calculated using a Macro SAS procedure. This procedure used the Taylor linearization 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 rates.

Sampling errors for the 2009 SDHS are calculated for selected variables considered to be of primary interest. The results are presented in Appendix B of the 2009 SDHS report for the country as a whole, for urban and rural areas, and for the four geographical regions. Standard errors, design effect, relative standard errors and 95 percent confidence limits for each statistic of a variable are presented in the tables of the Appendix. Details on sampling error calculation are also provided.

In summary, for the total sample, the value of the DEFT, averaged over all variables, is 1.05. This means that, due to multi-stage clustering of the sample, the average standard error is increased by a factor of 1.05 over that in an equivalent simple random sample.

Data appraisal

Data quality tables and were generated to assess the quality and reliability of the 2009 SDHS data.

Abstract

Domestic Violence Survey 2005 was designed to provide data and indicators about the types and acts of violence against women, children, unmarried females, and the elderly.

Geographic coverage

The sample is cluster, random, and systematic of two stages: First stage: Selecting cluster, random, and systematic sample of 234 enumeration areas. Second stage: Selecting random sample of households from the selected enumeration areas of the first stage; 18 households were selected from each enumeration area selected during the first stage.

Analysis unit

Household, individual

Universe

·Ever-married women aged (15-64) Years ·Children aged (5-17) Years ·Unmarried women aged (18 years and over) ·Elderly 65 years and Over

Kind of data

Sample survey data [ssd]

Sampling procedure

The number of households in the sample was 4,212 households: 2,772 in the West Bank and 1,440 in the Gaza Strip.

The sampling frame consists of a comprehensive sample selected from the Population, Housing, and Establishment Census 1997. The comprehensive sample consists of geographic areas of close size (with an average of 150 households); these are the enumeration areas used in the Census. These areas where used as PSUs at the first stage of sample selection.

The sample is cluster, random, and systematic of two stages: First stage: Selecting cluster, random, and systematic sample of 234 enumeration areas. Second stage: Selecting random sample of households from the selected enumeration areas of the first stage; 18 households were selected from each enumeration area selected during the first stage.

The selection of individuals from the household was so that one married female using the tables of Kish if more than one exist, the selection of one child aged 5-17 years using the tables of Kish, the selection of one unmarried female aged 18 to 64 years using the tables of Kish and the selection of all the elderly 65 years and over.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire of the Domestic Violence Survey consists of five main sections; they are:

Section one: Contains introductory data, quality control items, and a list of the household members including data about demographic, social, and economic characteristics such as age, sex, education, employment status, marital status, and refugee status.

Section two: Deals with ever-married women aged 15-64. This section measures types and forms of physical, psychological, and sexual violence a husband subjects his wife to and the types and forms of physical, psychological, and sexual violence a wife subjects her husband to. The section also deals with the political violence of the Israeli forces and settlers.

Section three: Deals with children aged 5-17 and measures the psychological and physical abuse a child is exposed to according to mother's perspective.

Section four: This section deals with unmarried women aged 18 and over and measures the physical and psychological violence females are exposed to by household member.

Section five: This section deals with elderly people aged 65 and over and measures the psychological and physical abuse they are exposed to by household member whom they reside or do not reside with, and the diseases and disabilities they suffer from.

Cleaning operations

Data editing took place at a number of stages through the processing including: 1. office editing and coding 2. during data entry 3. structure checking and completeness 4. structural checking of SPSS data files

Response rate

" The overall response rate for the survey was %98.5

Sampling error estimates

Detailed information on the sampling Error is available in the Survey Report.

Data appraisal

The advisor of the Domestic Violence Survey reviewed the data for the purpose of evaluating its quality and logic. Some specialist on violence also reviewed the data; they affirmed the data quality. Also, the data evaluation was done through reviewing some regional and international studies and comparison with their results. In general, the entire stages of checks proved the accuracy and high quality of the data.

Abstract

As in the previous Demographic and Health Surveys (DHS) conducted in 1990, 1997, 2002 and 2007 in Jordan, the primary objective of the 2009 Jordan Population and Family Health Survey (JPFHS) is to provide reliable estimates of demographic parameters, such as fertility, family planning, fertility preferences, and child mortality as well as the nutritional status of women and children. The data from these surveys can be used by program managers and policy makers to evaluate and improve existing programs. In addition, the JPFHS data will be useful to researchers and scholars interested in analyzing demographic trends in Jordan, as well as those conducting comparative, regional, or cross-national studies.

The content of the 2009 JPFHS has been significantly decreased from the 2007 survey: it does not include data on mother and child health, reproductive health, women’s status, domestic violence, and early childhood development. However, a sub-sample of women age 15-49 and children age 6-59 months were tested to measure the prevalence of anemia. Height and weight of all women age 15-49 and children age five and under were also measured to assess their nutritional status.

Geographic coverage

National

Analysis unit

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

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLE DESIGN

The 2009 JPFHS sample was designed to produce reliable estimates of major survey variables for the country as a whole, urban and rural areas, each of the 12 governorates, and Badia and non-Badia areas. To ensure comparability with the previous surveys, the sample was also designed to provide estimates for the three regions, North, Central and South. The grouping of the governorates into the regions is as follows: the North region consists of Irbid, Jarash, Ajloun, and Mafraq; the Central region consists of Amman, Madaba, Balqa, and Zarqa; and the South region consists of Karak, Tafiela, Ma'an, and Aqaba.

The 2009 JPFHS sample was designed using the 2004 Population and Housing Census as the sampling frame. The sampling frame was stratified by governorate, major cities, other urban, and other rural within each stratum. A two-stage sampling procedure was employed. First, blocks were selected systematically as primary sampling units (PSUs) with a probability proportional to the size of the PSU. A total of 930 PSUs were selected at this stage. In the second stage, a fixed number of 16 households were selected as final sampling units in each PSU, resulting in a sample size of about 15,000 households. Blood testing (for anemia) and the measurements of height and weight were conducted among eligible individuals in the selected households in 465 PSUs (half of the sample).

UPDATING OF SAMPLING FRAME

Prior to the main fieldwork, mapping operations were carried out and the sample units/blocks were selected and then identified and located in the field. The selected blocks were delineated, and the outer boundaries were demarcated with special signs. During this process, the numbers on buildings, housing units, and households were updated, listed, and documented, along with the name of the owner/tenant of the housing unit and the name of the household head. These activities were completed during the second quarter of 2009.

Note: See detailed description of sample design in APPENDIX A of the final report which is presented in this documentation.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2009 JPFHS used two questionnaires—namely, the Household Questionnaire and the Individual Questionnaire. Both questionnaires were developed in English and Arabic, based on the questionnaires used in the 2007 survey, in collaboration with ICF Macro. The Household Questionnaire was used to list all usual members and visitors of the sampled households and to obtain information on each household member’s age, sex, educational attainment, relationship to the head of household, and marital status. In addition, questions were included on the socioeconomic characteristics of the household, such as source of water, sanitation facilities, and availability of durable goods.

The Household Questionnaire was also used to identify women who were eligible for the individual interview: ever-married women age 15-49. In addition, in half of the households, all women age 15-49 and children under five years of age were measured to determine nutritional status. Children age 6-59 months and women age 15-49 were tested for anemia.

The household and women’s questionnaires were based on the DHS standard questionnaire. Additions and modifications to the model questionnaire were made in order to provide detailed information specific to Jordan, using experience gained from the 1990, 1997, 2002, and 2007 JPFHS. For each ever-married woman age 15-49, information on the following topics was collected: • Respondent’s general background • Birth history • Family planning • Marriage • Fertility preferences • Respondent’s employment

In addition, information on births and pregnancies, contraceptive use and discontinuation, and marriage during the five years prior to the survey was collected using a monthly calendar for this purpose.

As previously mentioned, anthropometric data were collected during the 2009 JPFHS in a subsample of 50 percent of clusters. All women age 15-49 and children age 0-4 in these households were measured using Shorr height boards and weighed using electronic Seca scales. In addition, a drop of capillary blood was taken from these women and children age 6-59 months to measure, in the field, their hemoglobin level using the HemoCue system. Hemoglobin testing was used to estimate the prevalence of anemia.

Response rate

A total of 14,872 households were selected for the survey from the sampling frame; among those selected households, 13,959 households were found. Of those households, 13,577 (97 percent) were successfully interviewed. In those households, 10,401 eligible women were identified, and complete interviews were obtained with 10,109 of them (97 percent of all eligible women). The overall response rate (the household’s response rate multiplied by the eligible woman response rate) was about 95 percent.

Note: See summarized response rates by place of residence in Table 1.1 of the final report which is presented in this documentation.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: non-sampling errors and 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 2009 Jordan Population and Family Health Survey (JPFHS) to minimize this type of error, non-sampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2009 JPFHS 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 among 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 2009 JPFHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the 2009 JPFHS is a Macro SAS procedure. This procedure used the Taylor linearization 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 rates.

Note: See detailed estimate of sampling error calculation in APPENDIX B of the report which is presented in this documentation.

Data appraisal

Data Quality Tables - Household age distribution - Age distribution of eligible and interviewed women - Completeness of reporting - Births by calendar years - Reporting of age at death in days - Reporting of age at death in months - Nutritional status of children (JPFHS 2002 based on the WHO Child Growth Standards)

Note: See for the detail in APPENDIX C of the final report which is presented in this documentation.