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 GHS is a household survey that has been executed annually by Stats SA since 2002. The survey in its present form was instituted as a result of the need identified by the Government of South Africa to determine the level of development in the country and the performance of programmes and projects on a regular basis. The survey was specifically designed to measure multiple facets of the living conditions of South African households, as well as the quality of service delivery in a number of key service sectors. The GHS covers six broad areas, namely: education, health, social development, housing, household access to services and facilities, food security and agriculture.

Geographic coverage

The nine provinces of South Africa

Analysis unit

Households Individuals

Universe

The target population of the survey consists of all private households in all nine provinces of South Africa and residents in workers' hostels. The survey does not cover other collective living quarters such as students' hostels, old-age homes, hospitals, prisons and military barracks, and is therefore only representative of non-institutionalised and non-military persons or households in South Africa.

Kind of data

Données échantillonées [ssd]

Sampling procedure

The sample design for the GHS 2012 was based on a master sample (MS) that was originally designed for the QLFS and was used for the first time for the GHS in 2008. This master sample is shared by the Quarterly Labour Force Surveys (QLFS), General Household Survey (GHS), Living Conditions Survey (LCS), Domestic Tourism Survey and the Income and Expenditure Surveys (IES).

The master sample used a two-stage, stratified design with probability-proportional-to-size (PPS) sampling of PSUs from within strata, and systematic sampling of dwelling units (DUs) from the sampled primary sampling units (PSUs). A self-weighting design at provincial level was used and MS stratification was divided into two levels. Primary stratification was defined by metropolitan and non-metropolitan geographic area type. During secondary stratification, the Census 2001 data were summarised at PSU level. The following variables were used for secondary stratification; household size, education, occupancy status, gender, industry and income.

Census enumeration areas (EAs) as delineated for Census 2001 formed the basis of the PSUs. The following additional rules were used: · Where possible, PSU sizes were kept between 100 and 500 dwelling units (DUs); · EAs with fewer than 25 DUs were excluded; · EAs with between 26 and 99 DUs were pooled to form larger PSUs and the criteria used was same settlement type; · Virtual splits were applied to large PSUs: 500 to 999 split into two; 1 000 to 1 499 split into three; and 1 500 plus split into four PSUs; and · Informal PSUs were segmented.

A Randomised Probability Proportional to Size (RPPS) systematic sample of PSUs was drawn in each stratum, with the measure of size being the number of households in the PSU. Altogether approximately 3 080 PSUs were selected. In each selected PSU a systematic sample of dwelling units was drawn. The number of DUs selected per PSU varies from PSU to PSU and depends on the Inverse Sampling Ratios (ISR) of each PSU.

For more Information on sampling please view technical notes (P47) in the statistical release

Mode of data collection

Interview face à face [f2f]

Research instrument

The questionnaire covers five core areas of importance with sections on education, health, non-remunerated trips undertaken by the household, housing, and household access to services and facilities. These are covered in four sections, each focusing on a particular aspect. Depending on the need for additional information, the questionnaire is adapted on an annual basis. New sections may be introduced on a specific topic for which information is needed or additional questions may be added to existing sections. Likewise, questions that are no longer necessary may be removed.

Contents of the GHS questionnaire - Cover page: Household information, response details, field staff information, result codes, etc. - Flap: Demographic information (name, sex, age, population group, etc.) - Section 1: Biographical information (education, health, disability, welfare) - Section 2: Economic activities - Section 3:Household information (type of dwelling, ownership of dwelling, electricity, water and sanitation,environmental issues, services, transport, etc.) - Section 4: Food security, income and expenditure (food supply, agriculture, expenditure, etc.)

Response rate

The national response rate for the survey was 94,1%.

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.

Dataset contains counts and measures for households from the 2013, 2018, and 2023 Censuses. Data is available by statistical area 2.

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The variables included in this dataset are for households in occupied private dwellings (unless otherwise stated). All data is for level 1 of the classification (unless otherwise stated):

• Count of households in occupied private dwellings
• Access to telecommunication systems (total responses)
• Household crowding index for levels 1 and 2
• Household composition
• Number of usual residents in household
• Average number of usual residents in household
• Number of motor vehicles
• Sector of landlord for households in rented occupied private dwellings
• Tenure of household
• Total household income
• Median ($) total household income
• Weekly rent paid by household for households in rented occupied private dwellings
• Median ($) weekly rent paid by household for households in rented occupied private dwellings.

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Download lookup file from Stats NZ ArcGIS Online or embedded attachment in Stats NZ geographic data service. Download data table (excluding the geometry column for CSV files) using the instructions in the Koordinates help guide.

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Footnotes

Geographical boundaries

Statistical standard for geographic areas 2023 (updated December 2023) has information about geographic boundaries as of 1 January 2023. Address data from 2013 and 2018 Censuses was updated to be consistent with the 2023 areas. Due to the changes in area boundaries and coding methodologies, 2013 and 2018 counts published in 2023 may be slightly different to those published in 2013 or 2018.

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Caution using time series

Time series data should be interpreted with care due to changes in census methodology and differences in response rates between censuses. The 2023 and 2018 Censuses used a combined census methodology (using census responses and administrative data), while the 2013 Census used a full-field enumeration methodology (with no use of administrative data).

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About the 2023 Census dataset

For information on the 2023 dataset see Using a combined census model for the 2023 Census. We combined data from the census forms with administrative data to create the 2023 Census dataset, which meets Stats NZ's quality criteria for population structure information. We added real data about real people to the dataset where we were confident the people who hadn’t completed a census form (which is known as admin enumeration) will be counted. We also used data from the 2018 and 2013 Censuses, administrative data sources, and statistical imputation methods to fill in some missing characteristics of people and dwellings.

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Data quality

The quality of data in the 2023 Census is assessed using the quality rating scale and the quality assurance framework to determine whether data is fit for purpose and suitable for release. Data quality assurance in the 2023 Census has more information.

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Concept descriptions and quality ratings

Data quality ratings for 2023 Census variables has additional details about variables found within totals by topic, for example, definitions and data quality.

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Household crowding

Household crowding is based on the Canadian National Occupancy Standard (CNOS). It calculates the number of bedrooms needed based on the demographic composition of the household. The household crowding index methodology for 2023 Census has been updated to use gender instead of sex. Household crowding should be used with caution for small geographical areas due to high volatility between census years as a result of population change and urban development. There may be additional volatility in areas affected by the cyclone, particularly in Gisborne and Hawke's Bay. Household crowding index – 2023 Census has details on how the methodology has changed, differences from 2018 Census, and more.

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Using data for good

Stats NZ expects that, when working with census data, it is done so with a positive purpose, as outlined in the Māori Data Governance Model (Data Iwi Leaders Group, 2023). This model states that "data should support transformative outcomes and should uplift and strengthen our relationships with each other and with our environments. The avoidance of harm is the minimum expectation for data use. Māori data should also contribute to iwi and hapū tino rangatiratanga”.

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Confidentiality

The 2023 Census confidentiality rules have been applied to 2013, 2018, and 2023 data. These rules protect the confidentiality of individuals, families, households, dwellings, and undertakings in 2023 Census data. Counts are calculated using fixed random rounding to base 3 (FRR3) and suppression of ‘sensitive’ counts less than six, where tables report multiple geographic variables and/or small populations. Individual figures may not always sum to stated totals. Applying confidentiality rules to 2023 Census data and summary of changes since 2018 and 2013 Censuses has more information about 2023 Census confidentiality rules.

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Measures

Measures like averages, medians, and other quantiles are calculated from unrounded counts, with input noise added to or subtracted from each contributing value during measures calculations. Averages and medians based on less than six units (e.g. individuals, dwellings, households, families, or extended families) are suppressed. This suppression threshold changes for other quantiles. Where the cells have been suppressed, a placeholder value has been used.

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Percentages

To calculate percentages, divide the figure for the category of interest by the figure for 'Total stated' where this applies.

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Symbol

-997 Not available

-999 Confidential

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Inconsistencies in definitions

Please note that there may be differences in definitions between census classifications and those used for other data collections.

Abstract

Annual Household Survey 2012-2013 is a nation- wide household survey, data collection operation of which was conducted from December 2012 to July 2013. The AHS consists of multiple topics related to household information including demography, education, housing facilities, consumption and labour force. However the survey is primarily focused on the annual household consumption and current labour force statistics. The food consumption and labour force related information was collected for past 7 days of the reference period whereas for other information related to non-food was past 12 months. Therefore, the result of the survey refers to the year 2012-201313. The results of AHS are presented in this statistical report covering five sections of the survey questionnaire. Structurally, the report contains six chapters including 42 tables, 21 figures and 5 appendices. Since the design of the survey questionnaire has followed the concepts and definitions adopted in Nepal Living Standards Surveys and Nepal Labour Force Surveys especially to capture household consumption aggregates and the current labour force related information respectively, the data analysis and tabulation is also done accordingly.

Objectives The objectives of Annual Household Survey 2012-2013 are: • to estimate the label and structure of household consumption expenditure each year; • to measure unemployment and underemployment on yearly basis; • to collect information on the areas of demography, literacy, housing facilities etc; and • to create an annual database of household sector.

The survey is intended to support the National Accounts estimates, particularly of household sector. Moreover, the survey will explore the possibility of consumption based poverty measurement also.

Geographic coverage

The survey covers the whole country(National), Ecological belts( Mountain , Hill , Terai), rural and urban.

Analysis unit

Household and Induvisual

Universe

• All households in the country determined on the basis of the usual place of their residence (de jure househols). The households of diplomatic missions, the institutional households (like people living in schools hostels, prisons, army camps and hospitals) were excluded from the survey.
• All persons aged 5 years and above household members.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample frame from the National Population and Housing Census 2011 is being used for sampling of AHS 2012-2013. The Annual Household Survey 2012-2013 is the multi-stage random sampling design with equal PSUs or households distributed between urban and rural areas considering the heterogeneous labour force activities to provide a detailed picture of employment situation in the urban areas. So the prescribed 200 PSUs are divided equally in two parts, i.e., 100 PSUs each for urban and rural. The design has applied the concept of master sample frame. The sample size for the survey has been estimated at 3000 households in 200 Primary Sampling Units (PSUs). These 200 PSU shave been equally distributed between two study domains, viz. Urban Nepal and Rural Nepal. The PSUs were selected with Probability Proportional to Size, the measure of size being the square root of the number of households in each ward. Fifteen households were selected for the interview from each of the selected PSU using Systematic Sampling. The technical note of the sampling procedure is given at Appendix I of report AHS 2012-2013 .

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire of AHS 2012/13 survey contains five sections. The first section contains individual or demographic information. Section two, three and four includes on household consumption including housing and housing expenses, food expenses and home production, and non-food expenses, consumption of durables and own account production respectively. The last section deals with current economic activity or labour force. The food consumption part of the questionnaire has covered broad food categories only. The household consumption part of the questionnaire has been designed in line with that of Nepal Living Standards Survey. Likewise, for the labour force part, it has followed the structure of Nepal Labour Force Survey 2008, but in current basis only. A 16-paged household questionnaire with 5 sections and 4 appendices in Nepali language was administered in the AHS. The English translation of the questionnaire has been presented at Appendix II of AHS 2012/13 report.

Cleaning operations

Data entry and data verification of Annual Household Survey 2012-2013was conductaed at field. For this task, a simple and clear data entry programme was developed in CSPro software, and each team was given a personal computer having the entry program so that every team could be able to enter the interviewed household data in the respective field area. In other words, data entry and data verification work was done in the field residing in the corresponding PSU. Therefor both mannual and batch editing was carried out and CSPro programme wsa used for consistancy checking.

Response rate

The survey enumerated 1485 (99%) sample households from 99 PSUs out of 100 PSUs of rural area. As regards to urban sample, all 1500 (100%) sample household from 100 PSUs are interviewed. Thus, in total 2985 (99.5%) households were enumerated in the survey.

The General Household Survey (GHS), ran from 1971-2011 (the UKDS holds data from 1972-2011). It was a continuous annual national survey of people living in private households, conducted by the Office for National Statistics (ONS). The main aim of the survey was to collect data on a range of core topics, covering household, family and individual information. This information was used by government departments and other organisations for planning, policy and monitoring purposes, and to present a picture of households, families and people in Great Britain. In 2008, the GHS became a module of the Integrated Household Survey (IHS). In recognition, the survey was renamed the General Lifestyle Survey (GLF). The GLF closed in January 2012. The 2011 GLF is therefore the last in the series. A limited number of questions previously run on the GLF were subsequently included in the Opinions and Lifestyle Survey (OPN).

Secure Access GHS/GLF
The UKDS holds standard access End User Licence (EUL) data for 1972-2006. A Secure Access version is available, covering the years 2000-2011 - see SN 6716 General Lifestyle Survey, 2000-2011: Secure Access.

History
The GHS was conducted annually until 2011, except for breaks in 1997-1998 when the survey was reviewed, and 1999-2000 when the survey was redeveloped. Further information may be found in the ONS document An overview of 40 years of data (General Lifestyle Survey Overview - a report on the 2011 General Lifestyle Survey) (PDF). Details of changes each year may be found in the individual study documentation.

EU-SILC
In 2005, the European Union (EU) made a legal obligation (EU-SILC) for member states to collect additional statistics on income and living conditions. In addition, the EU-SILC data cover poverty and social exclusion. These statistics are used to help plan and monitor European social policy by comparing poverty indicators and changes over time across the EU. The EU-SILC requirement was integrated into the GHS/GLF in 2005. After the closure of the GLF, EU-SILC was collected via the Family Resources Survey (FRS) until the UK left the EU in 2020.

Reformatted GHS data 1973-1982 - Surrey SPSS Files
SPSS files were created by the University of Surrey for all GHS years from 1973 to 1982 inclusive. The early files were restructured and the case changed from the household to the individual with all of the household information duplicated for each individual. The Surrey SPSS files contain all the original variables as well as some extra derived variables (a few variables were omitted from the data files for 1973-76). In 1973 only, the section on leisure was not included in the Surrey SPSS files. This has subsequently been made available, however, and is now held in a separate study, General Household Survey, 1973: Leisure Questions (SN 3982). Records for the original GHS 1973-1982 ASCII files have been removed from the UK Data Archive catalogue, but the data are still preserved and available upon request.

Abstract

The main purpose of a Household Income and Expenditure Survey (HIES) was to present high quality and representative national household data on income and expenditure in order to update Consumer Price Index (CPI), improve statistics on National Accounts and measure poverty within the country.

The main objectives of this survey - update the weight of each expenditure item (from COICOP) and obtain weights for the revision of the Consumer Price Index (CPI) for Funafuti - provide data on the household sectors contribution to the National Accounts - design the structure of consumption for food secutiry - To provide information on the nature and distribution of household income, expenditure and food consumption patterns household living standard useful for planning purposes - To provide information on economic activity of men and women to study gender issues - To generate the income distribution for poverty analysis

The 2010 Household Income and Expenditure Survey (HIES) is the third HIES that was conducted by the Central Statistics Division since Tuvalu gained political independence in 1978.

This survey deals mostly with expenditure and income on the cash side and non cash side (gift, home production). Moreover, a lot of information are collected:

at a household level: - goods possession - description of the dwelling - water tank capacity - fruits and vegetables in the garden - livestock

at an individual level: - education level - employment - health

Geographic coverage

National Coverage: Funafuti and /Outer islands.

Analysis unit

• Household level
• Individual level

Universe

The scope of the 2010 Household Income and Expenditure Survey (HIES) was all occupied households in Tuvalu. Households are the sampling unit, defined as a group of people (related or not) who pool their money, and cook and eat together. It is not the physical structure (dwelling) in which people live. HIES covered all persons who were considered to be usual residents of private dwellings (must have been living in Tuvalu for a period of 12-months, or have intention to live in Tuvalu for a period of 12-months in order to be included in the survey). Usual residents who are temporary away are included as well (e.g., for work or a holiday).

All the private household are included in the sampling frame. In each household selected, the current resident are surveyed, and people who are usual resident but are currently away (work, health, holydays reasons, or border student for example. If the household had been residing in Tuvalu for less than one year: - but intend to reside more than 12 months => he is included - do not intend to reside more than 12 months => out of scope.

Kind of data

Sample survey data [ssd]

Sampling procedure

The Tuvalu 2010 Household Income and Expenditure Survey (HIES) outputs breakdowns at the domain level which is Funafuti and Outer Islands. To achieve this, and to match the budget constraint, a third of the households were selected in both domains. It was decided that 33% (one third) sample was sufficient to achieve suitable levels of accuracy for key estimates in the survey. So the sample selection was spread proportionally across all the islands except Niulakita as it was considered too small. The selection method used is the simple random survey, meaning that within each domain households were directly selected from the population frame (which was the updated 2009 household listing). All islands were included in the selection except Niulakita that was excluded due to its remoteness, and size.

For selection purposes, in the outer island domain, each island was treated as a separate strata and independent samples were selected from each (one third). The strategy used was to list each dwelling on the island by their geographical position and run a systematic skip through the list to achieve the 33% sample. This approach assured that the sample would be spread out across each island as much as possible and thus more representative.

Population and sample counts of dwellings by islands for 2010 HIES Islands: -Nanumea: Population: 123; sample: 41 -Nanumaga: Population: 117; sample: 39 -Niutao: Population: 138; sample: 46 -Nui: Population: 141; sample: 47 -Vaitupu: Population: 298; sample: 100 -Nukufetau: Population: 141; sample: 47 -Nukulaelae: Population: 78; sample: 26 -Funafuti: Population: 791; sample: 254 -TOTAL: Population: 1827; sample: 600.

Mode of data collection

Face-to-face [f2f]

Research instrument

3 forms were used. Each question is writen in English and translated in Tuvaluan on the same version of the questionnaire. The questionnaire was highly based on the previous one (2004 survey).

Household Schedule This questionnaire, to be completed by interviewers, is used to collect information about the household composition, living conditions and is also the main form for collecting expenditure on goods and services purchased infrequently.

• composition of the household and demographic profile of each members
• dwelling information
• dwelling expenditure
• transport expenditure
• education expenditure
• health expenditure
• land and property expenditure
• household furnishing
• home appliances
• cultural and social payments
• holydays/travel costs
• Loans and saving
• clothing
• other major expenditure items

Individual Schedule There will be two individual schedules: - health and education - labor force (individual aged 15 and above) - employment activity and income (individual aged 15 and above): wages and salaries working own business agriculture and livestock fishing income from handicraft income from gambling small scale activies jobs in the last 12 months other income childreen income tobacco and alcohol use other activities seafarer

Diary (one diary per week, on a 2 weeks period, 2 diaries per household were required) The diaries are used to record all household expenditure and consumption over the two week diary keeping period. The diaries are to be filled in by the household members, with the assistance from interviewers when necessary. - All kind of expenses - Home production - food and drink (eaten by the household, given away, sold) - Goods taken from own business (consumed, given away) - Monetary gift (given away, received, winning from gambling) - Non monetary gift (given away, received, winning from gambling).

Cleaning operations

Consistency of the data: - each questionnaire was checked by the supervisor during and after the collection - before data entry, all the questionnaire were coded - the CSPRo data entry system included inconsistency checks which allow the National Statistics Office staff to point some errors and to correct them with imputation estimation from their own knowledge (no time for double entry), 4 data entry operators. 1. presence of all the form for each household 2. consistency of data within the questionnaire

at this stage, all the errors were corrected on the questionnaire and on the data entry system in the meantime.

• after data entry, the extreme amount of each questionnaire where selected in order to check their consistency. at this stage, all the inconsistency were corrected by imputation on CSPRO editing.

Response rate

The final response rates for the survey was very pleasing with an average rate of 97 per cent across all islands selected. The response rates were derived by dividing the number of fully responding households by the number of selected households in scope of the survey which weren't vacant.

Response rates for Tuvalu 2010 Household Income and Expenditure Survey (HIES): - Nanumea 100% - Nanumaga 100% - Niutao 98% - Nui 100% - Vaitupu 99% - Nukufetau 89% - Nukulaelae 100% - Funafuti 96%

As can be seen in the table, four of the islands managed a 100 per cent response, whereas only Nukufetau had a response rate of less than 90 per cent.

Further explanation of response rates can be located in the external resource entitled Tuvalu 2010 HIES Report Table 1.2.

Sampling error estimates

The quality of the results can be found in the report provided in this documentation.

Abstract

The GHS is an annual household survey conducted by Stats SA since 2002. The survey replaced the October Household Survey (OHS) which was introduced in 1993 and was terminated in 1999. The survey is an omnibus household-based instrument aimed at determining the progress of development in the country. It measures, on a regular basis, the performance of programmes as well as the quality-of-service delivery in a number of key service sectors in the country. The GHS covers six broad areas, namely education, health and social development, housing, household access to services and facilities, food security, and agriculture.

Geographic coverage

National coverage

Analysis unit

• Household
• Individual

Universe

The target population of the survey consists of all private households in all nine provinces of South Africa and residents in workers' hostels. The survey does not cover other collective living quarters such as students' hostels, old-age homes, hospitals, prisons and military barracks, and is therefore only representative of non-institutionalised and non-military persons or households in South Africa.

Kind of data

Sample survey data [ssd]

Sampling procedure

The General Household Survey (GHS) uses the Master Sample frame which has been developed as a general-purpose household survey frame that can be used by all other Stats SA household-based surveys having design requirements that are reasonably compatible with the GHS. The GHS 2015 collection was based on the 2013 Master Sample.

This Master Sample is based on information collected during the 2011 Census conducted by Stats SA. In preparation for Census 2011, the country was divided into 103 576 enumeration areas (EAs). The census EAs, together with the auxiliary information for the EAs, were used as the frame units or building blocks for the formation of primary sampling units (PSUs) for the Master Sample, since they covered the entire country and had other information that is crucial for stratification and creation of PSUs.

There are 3324 primary sampling units (PSUs) in the Master Sample with an expected sample of approximately 33000 dwelling units (DUs). The number of PSUs in the current Master Sample (3324) reflect an 8.0% increase in the size of the Master Sample compared to the previous (2008) Master Sample (which had 3080 PSUs). The larger Master Sample of PSUs was selected to improve the precision (smaller coefficients of variation, known as CVs) of the GHS estimates.

The Master Sample is designed to be representative at provincial level and within provinces at metro/non-metro levels. Within the metros, the sample is further distributed by geographical type. The three geography types are Urban, Tribal and Farms. This implies, for example, that within a metropolitan area, the sample is representative of the different geography types that may exist within that metro. The sample for the GHS is based on a stratified two-stage design with probability proportional to size (PPS) sampling of PSUs in the first stage, and sampling of dwelling units (DUs) with systematic sampling in the second stage.

Caution must be exercised when interpreting the results of the GHS at low levels of disaggregation. The sample and reporting are based on the provincial boundaries as defined in December/January 2006. These new boundaries resulted in minor changes to the boundaries of some provinces, especially Gauteng, North West, Mpumalanga, Limpopo, Eastern Cape and Western Cape. In previous reports the sample was based on the provincial boundaries as defined in 2001, and there will therefore be slight comparative differences in terms of provincial boundary definitions.

Details of the sampling procedure can be found in Report No. P0318 available from Statistics South Africa and attached to this Survey as an external resource.

Mode of data collection

Face-to-face [f2f]

Research instrument

A single survey questionnaire was administered for each household.

The questionnaire comprises of the following sections: Section 1: Household Specific Functioning Section 2: Health and General Functioning Section 3: Social Security and Religion Section 4: Economic Activities Section 5: General Household Information and Service Delivery Section 6: Communication and Transport Section 7: Health, Welfare and Food Security Section 8: Household Livelihoods Section 9: Mortality in the Last 12 Months Section 10: Interviewer Summary Section

Response rate

National level response rate was 90.48%.

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

Abstract

The GHS is an annual household survey which measures the living circumstances of South African households. The GHS collects data on education, health, and social development, housing, access to services and facilities, food security, and agriculture.

Geographic coverage

National coverage

Analysis unit

Households and individuals

Universe

The survey covers all de jure household members (usual residents) of households in the nine provinces of South Africa, and residents in workers' hostels. The survey does not cover collective living quarters such as student hostels, old age homes, hospitals, prisons, and military barracks.

Kind of data

Sample survey data [ssd]

Sampling procedure

From 2015 the General Household Survey (GHS) uses a Master Sample (MS) frame developed in 2013 as a general-purpose sampling frame to be used for all Stats SA household-based surveys. This MS has design requirements that are reasonably compatible with the GHS. The 2013 Master Sample is based on information collected during the 2011 Census conducted by Stats SA. In preparation for Census 2011, the country was divided into 103576 enumeration areas (EAs). The census EAs, together with the auxiliary information for the EAs, were used as the frame units or building blocks for the formation of primary sampling units (PSUs) for the Master Sample, since they covered the entire country, and had other information that is crucial for stratification and creation of PSUs. There are 3324 primary sampling units (PSUs) in the Master Sample, with an expected sample of approximately 33000 dwelling units (DUs). The number of PSUs in the current Master Sample (3324) reflect an 8,0% increase in the size of the Master Sample compared to the previous (2008) Master Sample (which had 3080 PSUs). The larger Master Sample of PSUs was selected to improve the precision (smaller coefficients of variation, known as CVs) of the GHS estimates. The Master Sample is designed to be representative at provincial level and within provinces at metro/non-metro levels. Within the metros, the sample is further distributed by geographical type. The three geography types are Urban, Tribal and Farms. This implies, for example, that within a metropolitan area, the sample is representative of the different geography types that may exist within that metro.

The sample for the GHS is based on a stratified two-stage design with probability proportional to size (PPS) sampling of PSUs in the first stage, and sampling of dwelling units (DUs) with systematic sampling in the second stage. After allocating the sample to the provinces, the sample was further stratified by geography (primary stratification), and by population attributes using Census 2011 data (secondary stratification).

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

Data was collected with a household questionnaire and a questionnaire administered to a household member to elicit information on household members.

Data appraisal

Since 2019, the questionnaire for the GHS series changed and the variables were also renamed. For correspondence between old names (GHS pre-2019) and new name (GHS post-2019), see the document ghs-2019-variables-renamed.

Abstract

The Household Living Conditions Survey 2012 provides information on poverty analysis in Ukraine. The results of the household survey are used in Ukraine for analyzing various issues, among which poverty, access to material benefits, subjective self-evaluation by households of their level of well-being are of special priority. The data obtained through this survey makes it possible to carry out methodologically comparative poverty studies using almost all above criteria.

The data can be used to analyze the following: - social-demographic characteristics of household members; - expenditures and consumption; - income and other resources, including those coming from subsidiary farming; - housing conditions; - availability of durable goods; - evaluation of health conditions and access to medical goods and services; - evaluation of well-being level and economic expectations; - access to certain goods and services; - access to information and communication technologies.

Geographic coverage

National, except some settlements within the territories suffered from the Chernobyl disaster.

Analysis unit

• Households,
• Individuals.

A household is a totality of persons who jointly live in the same residential facilities of part of those, satisfy all their essential needs, jointly keep the house, pool and spend all their money or portion of it. These persons may be relatives by blood, relatives by law or both, or have no kinship relations. A household may consist of one person (Law of Ukraine "On Ukraine National Census of Population," Article 1). As only 0.50% households have members with no kinship relations (0.65% total households if bachelors are excluded), the contemporary concepts "household" and "family" are very close.

Universe

Whole country, all private households. The survey does not cover collective households, foreigners temporarily living in Ukraine as well as the homeless.

Kind of data

Sample survey data [ssd]

Sampling procedure

The survey covers only private households. The sample does not include marginal population groups (individuals without permanent place of residence, etc.). Annual full rotation of respondents is used. Every five years survey territories are rotated. The territorial sampling excludes residential areas that are located in the exclusion and compulsory resettlement zone affected by radioactive contamination as a result of the Chernobyl nuclear power station accident. Sampling is done by stratified multistage probability sampling methods. The sampling methodology ensures that each household has a certain non-zero probability of being selected.

Mode of data collection

Face-to-face [f2f]

Research instrument

The household living conditions survey includes three components and uses various survey tools to obtain information.

I. Collecting general data on a household - basic interview. Interviewing of households takes place at the survey commencement stage based on the adequate questionnaire program on general basic household features: household composition, housing facilities, availability and use of land plots, cattle and poultry, and also characteristics of household members: anthropometric data, education, employment status, etc. In addition, while interviewing, the interviewer completes a household composition check card to trace any changes during the entire survey period.

II. Observation of household expenditures and incomes over a quarter. For the observation, two survey tools are used: Weekly diary of current expenditures, which is completed directly by a household twice a quarter. In the diary respondents (households) record all daily expenditures in details (e.g. for purchased foodstuffs - product description, its weight and value, and place of purchase). In addition, a household puts into the diary information on consumption of products produced in private subsidiary farming or received as a gift.

Households are evenly distributed among rotation groups, who complete diaries in different week days of every quarter. Assuming that the two weeks data are intrinsic for the entire quarter, the single time period of data processing (quarter) is formed by means of multiplying diary data by ratio 6.5 (number of weeks in a quarter divided on the number of weeks when diary records were made). Inclusion of foodstuffs for long-time consumption is done based on quarterly interview data.

Quarterly questionnaire is used in quarterly interviewing of households in the first month following the reporting quarter. At this state, we collect data on large and irregular expenditures, in particular those relating to the purchase of foodstuffs for long-time consumption (e.g. sacks, etc.), and also data on household incomes. Since recalling all incomes and expenditures made in a quarter is uneasy, households make records during a quarter in a special 'Quarterly expenditures log'.

The major areas for quarterly observation are the following: - structure of consumer financial expenditures for goods and services; - structure of other expenditures (material aid to other households, expenditures for private subsidiary farming, purchase of real estate, construction and major repair of housing facilities and outbuildings, accumulating savings, etc); - importance of private subsidiary farming for household welfare level (receipt and use of products from private subsidiary farming for own consumption, financial income from sales of such products, etc.); - structure of income and other financial sources of a household. We separately study the income of every individual household member (remuneration of labor, pension, scholarship, welfare, etc.) and the income in form payments to a household as a whole (subsidies for children, aid of relatives and other persons, income from - sales of real estate and property, housing and utility subsidies, use of savings, etc.).

III. Single-time topical interviews Questionnaires are used for quarterly interviewing.

Quarterly topical interviews covered the following: - household expenditures for construction and repair of housing facilities and outbuilding; - availability in a household of durable goods; - assessment by households members of own health and accessibility of selected medical services; - self-assessment by a household of adequacy of its income; - a household's access to Internet.

Abstract

The Cambodia Socio-Economic Survey (CSES) asks questions to a country wide sample of households and household members about housing conditions, education, economic activities, household production and income, household level and structure of consumption, health, victimization, etc. There are also questions related to people in the labour force, e.g. labour force participation.

Poverty reduction is a major commitment by the Royal Government of Cambodia. Accurate statistical information about the living standards of the population and the extent of poverty is an essential instrument to assist the Government in diagnosing the problems, in designing effective policies for reducing poverty and in monitoring and evaluating the progress of poverty reduction. The Millennium Development Goals (MDG) has been adopted by the Royal Government of Cambodia and a National Strategic Development Plan (NSDP) has been developed. The MDGs are also incorporated into the “Rectangular Strategy of Cambodia”.

Cambodia is still a predominantly rural and agricultural society. The vast majority of the population get their subsistence in households as self-employed in agriculture. The level of living is determined by the household's command over labour and resources for own-production in terms of land and livestock for agricultural activities, equipments and tools for fishing, forestry and construction activities and income-earning activities in the informal and formal sector. The CSES aims to estimate household income and consumption/expenditure as well as a number of other household and individual characteristics.

The main objective of the survey is to collect statistical information about living conditions of the Cambodian population and the extent of poverty. The survey can be used for identifying problems and making decisions based on statistical data.

The main user is the Royal Government of Cambodia (RGC) as the survey supports monitoring the National Strategic Development Plan (NSDP) by different socio-economic indicators. Other users are university researchers, analysts, international organizations e.g. the World Bank and NGO’s. The World Bank has published a report on poverty profile and social indicators using CSES 2007 data . In this regard, the CSES continues to serve all stakeholders involved as essential instruments in order to assist in diagnosing the problems and designing their most effective policies. The CSES micro data at NIS is available for research and analysis by external researchers after approval by Senior Minister of Planning. The interesting research questions that could be put to the data are many; NIS welcomes new research based on CSES data.

General Objectives: CSES 2016 will continue the work started through CSES 2004 and the annual CSES 2007 to 2014 and would primarily aim at producing information needed for planning and policy making for reduction of poverty in Cambodia. Reduction of poverty has been given high priority in Cambodia's National Strategic Development Plan (NSDP 2009-2013). In addition to this, the survey data help in various other ways in developmental planning and policy making in the country. They would also prove useful for the production of National Accounts in Cambodia.

A long-term objective of the entire project is to build national capability in NIS for conducting socio-economic surveys and for utilizing survey data for planning for national development and social welfare.

Specific Objectives: Among specific objectives, the following deserve special mention: 1) Obtain data on infrastructural facilities in villages, especially facilities for schooling and health care and associated problems. 2) Obtain data on retail prices of selected food, non-food and medicine items prevailing in the villages. 3) Collect data on utilization of education, housing and land ownership 4) Collect data on household assets and outstanding loans. 5) Collect data on household's construction activities. 6) Collect information on maternal health, child health/care. 7) Collect information on health care seeking and expenditure of the household members related to illness, injury and disability. 8) Collect information on economic activities including the economic activities for children aged between 5 and 17 years. 9) Collect information on victimization by the household 10) Collect information on the presence of the household members.

Geographic coverage

National Phnom Penh / Other Urban / Other Rural

Analysis unit

• Households
• Individuals

Universe

All resident households in Cambodia

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling design in the CSES 2016 survey is a three-stage design. In stage one a sample of villages is selected, in stage two an Enumeration Area (EA) is selected from each village selected in stage one, and in stage three a sample of households is selected from each EA selected in stage two.

Stage 1: A random sample of PSUs was selected from each stratum. The sampling method was systematic PPS (PPS=sampling with probability proportional to size). The size measure used was the number of households in the PSU according to the sampling frame.

Stage 2: One EA was selected by Simple Random Sampling (SRS), in each village selected in stage 1.

Stage 3: In each selected EA a sample of 10 households was selected. The selection of households was done in the field by the supervisors/interviewers. All households in selected EAs were listed by the enumerator. The sample of households was then selected from the list by systematic sampling with a random start (the start value controlled by NIS).

Mode of data collection

Face-to-face [f2f]

Research instrument

Three different questionnaires or forms were used in the survey:

Form 1: Household listing sheets to be used in the sampling procedure in the enumeration areas.

Form 2: Village questionnaire answered by the village leader about economy and infrastructure, crop production, health, education, retail prices and sales prices of agriculture, employment and wages, and recruitment of children for work outside the village.

Form 3: Household questionnaire with questions for each household member, including modules on migration, education and literacy, housing conditions, crop production, household liabilities, durable goods, construction activities, nutrition, fertility and child care, child feeding and vaccination, health of children, mortality, current economic activity, health and illness, smoking, HIV/AIDS awareness, and victimization.

The interviewer is responsible for filling up Form 1 and Form 3 to respondents. For Form 2, the supervisors will be asked to canvass this form. In case that the supervisors are absent for any reason, the interviewers may be also asked to help fill up this form (Form 2).

Cleaning operations

The NIS team commenced their work of checking and coding and coding in begining of February after the first month of fieldwork was completed. Supervisors from the field delivered questionaires to NIS. Sida project expert and NIS Survey Manager helped in solving relevant matters that become apparent when reviewing questionires on delivery.

Response rate

The CSES 2016 enjoyed almost a 100 percent response rate. The high response rate together with close and systematic fieldwork supervision by the core group members were a major contribution for achieving high quality survey results.

Sampling error estimates

In order to provide a basis for assessing the reliability or precision of CSES estimates, the estimation of the magnitude of sampling error in the survey data were computed. Since most of the estimates from the survey are in the form of weighted ratios, thus variances for ratio estimates are computed.

The Coefficients of Variation (CV) on national level estimates are generally below 4 percent. The exception is the CV for total value of assets where there are rather high CVs especially in the urban areas, which should be expected.

The CVs are somewhat higher in the urban and rural domains but still generally below 7 percent. For the five zones, the average CVs are in the range 5 to 13 percent with a few exceptions where the CVs are above 20 percent. For provinces the CVs for food consumption are 9 percent on average.

The sample take within Primary Sampling Units (PSU) was set to 10 households per PSU in the CSES 1999. When data on variances became available, it was possible to make crude calculations of the optimal sample take within PSU. Calculations on some of the central estimates in the CSES 1999 show that the design effects in most cases are in the range 1 to 5.

Intra-cluster correlation coefficients have been calculated based on the design effects. These correlation coefficients are somewhat high. The reason is that the characteristics that are measured tend to be concentrated (clustered) within the PSUs. The optimal sample size within PSUs under different assumptions on cost ratios and intra-cluster correlation coefficients was then calculated. The cost ratio is the average cost for adding a village to the sample divided by the average cost of including an extra household in the sample. In the CSES, it was chosen to adopt a fairly low cost ratio due to the fact that the interview time per household is long. Under this assumption the optimal sample size is probably around 10 households per village for many of the CSES indicators.

The Armenian Household Budget Survey (HBS) 1996 was designed to be a nationally representative survey capable of measuring the standard of living in the Republic of Armenia (ROA) through the collection of data on the family, demographic, socio-economic and financial status of households. The survey was conducted in November - December 1996, on the whole territory of the republic by the State Department of Statistics (SDS) of ROA with technical and financial assistance from the World Bank.The data collected included information on household composition, housing conditions, education level of household members, employment and income, savings, borrowing, as well as details on levels of expenditure including those on food, non-food, health, tourism and business. The survey covered about 100 villages and 28 towns. The size of the sample was 5,040 households of which 4,920 responded which makes the survey the largest carried out in Armenia to date and one with a very high response rate for a transition economy. The expenditure part of the data was collected using two different methods administered for different households. The methods are: recall method in which households were asked, during the interview, about their expenditures made during the last 30 days preceding the date of the interview; and a diary method where households were given a diary they used to record details about their income and expenditure on a daily basis for 30 days during the interview period. About 25% of the total sample of interviewed households used diaries and 75% used the recall method. The unit of study in the survey was the household, defined as a group of co-resident individuals with a common living budget. As will be explained in detail, the AHBS 96 was generally designed as a two stage stratified sampling, but for large urban areas with an almost definite probability of being selected, a one stage sampling was adopted.The Armenian HBS 1996 is not a standard Living Standards Measurement Study (LSMS) survey - the questionnaire used is more limited in scope and much different in format from a typical LSMS. This survey used no community or price questionnaires; it did not use most of LSMS’ prototypical fieldwork and data quality procedures, and the technical assistance did not come from the LSMS group in the World Bank. Nonetheless, the goals are some what LSMS-like and the data is certainly worth archiving. They are therefore being entered into the LSMS archives to guarantee their future accessibility to World Bank and other users.

Abstract

The Household Income and Expenditure Survey is a survey collecting data on income, consumption and expenditure patterns of households, in accordance with methodological principles of statistical enquiries, which are linked to demographic and socio-economic characteristics of households. A Household Income and expenditure Survey is the sole source of information on expenditure, consumption and income patterns of households, which is used to calculate poverty and income distribution indicators. It also serves as a statistical infrastructure for the compilation of the national basket of goods used to measure changes in price levels. Furthermore, it is used for updating of the national accounts.

The main objective of the NHIES 2009/2010 is to comprehensively describe the levels of living of Namibians using actual patterns of consumption and income, as well as a range of other socio-economic indicators based on collected data. This survey was designed to inform policy making at the international, national and regional levels within the context of the Fourth National Development Plan, in support of monitoring and evaluation of Vision 2030 and the Millennium Development Goals. The NHIES was designed to provide policy decision making with reliable estimates at regional levels as well as to meet rural - urban disaggregation requirements.

Geographic coverage

National Coverage

Analysis unit

Individuals and Households

Universe

Every week of the four weeks period of a survey round all persons in the household were asked if they spent at least 4 nights of the week in the household. Any person who spent at least 4 nights in the household was taken as having spent the whole week in the household. To qualify as a household member a person must have stayed in the household for at least two weeks out of four weeks.

Kind of data

Sample survey data [ssd]

Sampling procedure

The targeted population of NHIES 2009/2010 was the private households of Namibia. The population living in institutions, such as hospitals, hostels, police barracks and prisons were not covered in the survey. However, private households residing within institutional settings were covered. The sample design for the survey was a stratified two-stage probability sample, where the first stage units were geographical areas designated as the Primary Sampling Units (PSUs) and the second stage units were the households. The PSUs were based on the 2001 Census EAs and the list of PSUs serves as the national sample frame. The urban part of the sample frame was updated to include the changes that take place due to rural to urban migration and the new developments in housing. The sample frame is stratified first by region followed by urban and rural areas within region. In urban areas further stratification is carried out by level of living which is based on geographic location and housing characteristics. The first stage units were selected from the sampling frame of PSUs and the second stage units were selected from a current list of households within each selected PSU, which was compiled just before the interviews.

PSUs were selected using probability proportional to size sampling coupled with the systematic sampling procedure where the size measure was the number of households within the PSU in the 2001 Population and Housing Census. The households were selected from the current list of households using systematic sampling procedure.

The sample size was designed to achieve reliable estimates at the region level and for urban and rural areas within each region. However the actual sample sizes in urban or rural areas within some of the regions may not satisfy the expected precision levels for certain characteristics. The final sample consists of 10 660 households in 533 PSUs. The selected PSUs were randomly allocated to the 13 survey rounds.

Sampling deviation

All the expected sample of 533 PSUs was covered. However a number of originally selected PSUs had to be substituted by new ones due to the following reasons.

Urban areas: Movement of people for resettlement in informal settlement areas from one place to another caused a selected PSU to be empty of households.

Rural areas: In addition to Caprivi region (where one constituency is generally flooded every year) Ohangwena and Oshana regions were badly affected from an unusual flood situation. Although this situation was generally addressed by interchanging the PSUs betweensurvey rounds still some PSUs were under water close to the end of the survey period. There were five empty PSUs in the urban areas of Hardap (1), Karas (3) and Omaheke (1) regions. Since these PSUs were found in the low strata within the urban areas of the relevant regions the substituting PSUs were selected from the same strata. The PSUs under water were also five in rural areas of Caprivi (1), Ohangwena (2) and Oshana (2) regions. Wherever possible the substituting PSUs were selected from the same constituency where the original PSU was selected. If not, the selection was carried out from the rural stratum of the particular region. One sampled PSU in urban area of Khomas region (Windhoek city) had grown so large that it had to be split into 7 PSUs. This was incorporated into the geographical information system (GIS) and one PSU out of the seven was selected for the survey. In one PSU in Erongo region only fourteen households were listed and one in Omusati region listed only eleven households. All these households were interviewed and no additional selection was done to cover for the loss in sample.

Mode of data collection

Face-to-face [f2f]

Research instrument

The instruments for data collection were as in the previous survey the questionnaires and manuals. Form I questionnaire collected demographic and socio-economic information of household members, such as: sex, age, education, employment status among others. It also collected information on household possessions like animals, land, housing, household goods, utilities, household income and expenditure, etc.

Form II or the Daily Record Book is a diary for recording daily household transactions. A book was administered to each sample household each week for four consecutive weeks (survey round). Households were asked to record transactions, item by item, for all expenditures and receipts, including incomes and gifts received or given out. Own produce items were also recorded. Prices of items from different outlets were also collected in both rural and urban areas. The price collection was needed to supplement information from areas where price collection for consumer price indices (CPI) does not currently take place.

Cleaning operations

The questionnaires received from the regions were registered and counterchecked at the survey head office. The data processing team consisted of Systems administrator, IT technician, Programmers, Statisticians and Data typists.

Data capturing

The data capturing process was undertakenin the following ways: Form 1 was scanned, interpreted and verified using the “Scan”, “Interpret” & “Verify” modules of the Eyes & Hands software respectively. Some basic checks were carried out to ensure that each PSU was valid and every household was unique. Invalid characters were removed. The scanned and verified data was converted into text files using the “Transfer” module of the Eyes & Hands. Finally, the data was transferred to a SQL database for further processing, using the “TranScan” application. The Daily Record Books (DRB or form 2) were manually entered after the scanned data had been transferred to the SQL database. The reason was to ensure that all DRBs were linked to the correct Form 1, i.e. each household’s Form 1 was linked to the corresponding Daily Record Book. In total, 10 645 questionnaires (Form 1), comprising around 500 questions each, were scanned and close to one million transactions from the Form 2 (DRBs) were manually captured.

Response rate

Household response rate: Total number of responding households and non-responding households and the reason for non-response are shown below. Non-contacts and incomplete forms, which were rejected due to a lot of missing data in the questionnaire, at 3.4 and 4.0 percent, respectively, formed the largest part of non-response. At the regional level Erongo, Khomas, and Kunene reported the lowest response rate and Caprivi and Kavango the highest. See page 17 of the report for a detailed breakdown of response rates by region.

Data appraisal

To be able to compare with the previous survey in 2003/2004 and to follow up the development of the country, methodology and definitions were kept the same. Comparisons between the surveys can be found in the different chapters in this report. Experiences from the previous survey gave valuable input to this one and the data collection was improved to avoid earlier experienced errors. Also, some additional questions in the questionnaire helped to confirm the accuracy of reported data. During the data cleaning process it turned out, that some households had difficulty to separate their household consumption from their business consumption when recording their daily transactions in DRB. This was in particular applicable for the guest farms, the number of which has shown a big increase during the past five years. All households with extreme high consumption were examined manually and business transactions were recorded and separated from private consumption.

Abstract

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

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

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

Geographic coverage

National

Analysis unit

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

Universe

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

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Frame The list of households obtained from the 2001/2 Ethiopian Agricultural Sample Enumeration (EASE) was used as a frame to select EAs from the rural part of the country. On the other hand, the list consisting of households by EA, which was obtained from the 2004 Ethiopian Urban Economic Establishment Census, (EUEEC), was used as a frame in order to select sample enumeration areas for the urban HICE survey. A fresh list of households from each urban and rural EA was prepared at the beginning of the survey period. This list was, thus, used as a frame in order to select households from sample EAs.

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

Category I: Rural: - This category consists of the rural areas of eight regional states and two administrative councils (Addis Ababa and Dire Dawa) of the country, except Gambella region. Each region was considered to be a domain (Reporting Level) for which major findings of the survey are reported. This category comprises 10 reporting levels. A stratified two-stage cluster sample design was used to select samples in which the primary sampling units (PSUs) were EAs. Twelve households per sample EA were selected as a Second Stage Sampling Unit (SSU) to which the survey questionnaire were administered.

Category II:- Major urban centers:- In this category all regional capitals (except Gambella region) and four additional urban centers having higher population sizes as compared to other urban centers were included. Each urban center in this category was considered as a reporting level. However, each sub-city of Addis Ababa was considered to be a domain (reporting levels). Since there is a high variation in the standards of living of the residents of these urban centers (that may have a significant impact on the final results of the survey), each urban center was further stratified into the following three sub-strata. Sub-stratum 1:- Households having a relatively high standards of living Sub-stratum 2:- Households having a relatively medium standards of living and Sub-stratum 3:- Households having a relatively low standards of living. The category has a total of 14 reporting levels. A stratified two-stage cluster sample design was also adopted in this instance. The primary sampling units were EAs of each urban center. Allocation of sample EAs of a reporting level among the above mentioned strata were accomplished in proportion to the number of EAs each stratum consists of. Sixteen households from each sample EA were inally selected as a Secondary Sampling Unit (SSU).

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

Mode of data collection

Face-to-face [f2f]

Abstract copyright UK Data Service and data collection copyright owner.

The General Household Survey (GHS), ran from 1971-2011 (the UKDS holds data from 1972-2011). It was a continuous annual national survey of people living in private households, conducted by the Office for National Statistics (ONS). The main aim of the survey was to collect data on a range of core topics, covering household, family and individual information. This information was used by government departments and other organisations for planning, policy and monitoring purposes, and to present a picture of households, families and people in Great Britain. In 2008, the GHS became a module of the Integrated Household Survey (IHS). In recognition, the survey was renamed the General Lifestyle Survey (GLF). The GLF closed in January 2012. The 2011 GLF is therefore the last in the series. A limited number of questions previously run on the GLF were subsequently included in the Opinions and Lifestyle Survey (OPN).

Secure Access GHS/GLF
The UKDS holds standard access End User Licence (EUL) data for 1972-2006. A Secure Access version is available, covering the years 2000-2011 - see SN 6716 General Lifestyle Survey, 2000-2011: Secure Access.

History
The GHS was conducted annually until 2011, except for breaks in 1997-1998 when the survey was reviewed, and 1999-2000 when the survey was redeveloped. Further information may be found in the ONS document An overview of 40 years of data (General Lifestyle Survey Overview - a report on the 2011 General Lifestyle Survey) (PDF). Details of changes each year may be found in the individual study documentation.

EU-SILC
In 2005, the European Union (EU) made a legal obligation (EU-SILC) for member states to collect additional statistics on income and living conditions. In addition, the EU-SILC data cover poverty and social exclusion. These statistics are used to help plan and monitor European social policy by comparing poverty indicators and changes over time across the EU. The EU-SILC requirement was integrated into the GHS/GLF in 2005. After the closure of the GLF, EU-SILC was collected via the Family Resources Survey (FRS) until the UK left the EU in 2020.

Reformatted GHS data 1973-1982 - Surrey SPSS Files
SPSS files were created by the University of Surrey for all GHS years from 1973 to 1982 inclusive. The early files were restructured and the case changed from the household to the individual with all of the household information duplicated for each individual. The Surrey SPSS files contain all the original variables as well as some extra derived variables (a few variables were omitted from the data files for 1973-76). In 1973 only, the section on leisure was not included in the Surrey SPSS files. This has subsequently been made available, however, and is now held in a separate study, General Household Survey, 1973: Leisure Questions (SN 3982). Records for the original GHS 1973-1982 ASCII files have been removed from the UK Data Archive catalogue, but the data are still preserved and available upon request.

The main GHS consisted of a household questionnaire, completed by the Household Reference Person (HRP), and an individual questionnaire, completed by all adults aged 16 and over resident in the household. A number of different trailers each year covering extra topics were included in later (post-review) surveys in the series from 2000.

• The household questionnaire covered the following topics: household information, accommodation type, housing tenure/costs, and consumer durables including vehicle ownership.
• The individual questionnaire included data from the household dataset, and additional sections on migration/citizenship/national identity/ethnicity, employment, pensions, education, health, child care, smoking, drinking, family information, financial situation, and income.
  

Abstract

The 2013 NDHS is part of the worldwide Demographic and Health Surveys (DHS) programme funded by the United States Agency for International Development (USAID). DHS surveys are designed to collect data on fertility, family planning, and maternal and child health; assist countries in monitoring changes in population, health, and nutrition; and provide an international database that can be used by researchers investigating topics related to population, health, and nutrition.

The overall objective of the survey is to provide demographic, socioeconomic, and health data necessary for policymaking, planning, monitoring, and evaluation of national health and population programmes. In addition, the survey measured the prevalence of anaemia, HIV, high blood glucose, and high blood pressure among adult women and men; assessed the prevalence of anaemia among children age 6-59 months; and collected anthropometric measurements to assess the nutritional status of women, men, and children.

A long-term objective of the survey is to strengthen the technical capacity of local organizations to plan, conduct, and process and analyse data from complex national population and health surveys. At the global level, the 2013 NDHS data are comparable with those from a number of DHS surveys conducted in other developing countries. The 2013 NDHS adds to the vast and growing international database on demographic and health-related variables.

Geographic coverage

National coverage

Analysis unit

• Households
• Children aged 0-5
• Women aged 15 to 49
• Men aged 15 to 64

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Design The primary focus of the 2013 NDHS was to provide estimates of key population and health indicators, including fertility and mortality rates, for the country as a whole and for urban and rural areas. In addition, the sample was designed to provide estimates of most key variables for the 13 administrative regions.

Each of the administrative regions is subdivided into a number of constituencies (with an overall total of 107 constituencies). Each constituency is further subdivided into lower level administrative units. An enumeration area (EA) is the smallest identifiable entity without administrative specification, numbered sequentially within each constituency. Each EA is classified as urban or rural. The sampling frame used for the 2013 NDHS was the preliminary frame of the 2011 Namibia Population and Housing Census (NSA, 2013a). The sampling frame was a complete list of all EAs covering the whole country. Each EA is a geographical area covering an adequate number of households to serve as a counting unit for the population census. In rural areas, an EA is a natural village, part of a large village, or a group of small villages; in urban areas, an EA is usually a city block. The 2011 population census also produced a digitised map for each of the EAs that served as the means of identifying these areas.

The sample for the 2013 NDHS was a stratified sample selected in two stages. In the first stage, 554 EAs-269 in urban areas and 285 in rural areas-were selected with a stratified probability proportional to size selection from the sampling frame. The size of an EA is defined according to the number of households residing in the EA, as recorded in the 2011 Population and Housing Census. Stratification was achieved by separating every region into urban and rural areas. Therefore, the 13 regions were stratified into 26 sampling strata (13 rural strata and 13 urban strata). Samples were selected independently in every stratum, with a predetermined number of EAs selected. A complete household listing and mapping operation was carried out in all selected clusters. In the second stage, a fixed number of 20 households were selected in every urban and rural cluster according to equal probability systematic sampling.

Due to the non-proportional allocation of the sample to the different regions and the possible differences in response rates, sampling weights are required for any analysis using the 2013 NDHS data to ensure the representativeness of the survey results at the national as well as the regional level. Since the 2013 NDHS sample was a two-stage stratified cluster sample, sampling probabilities were calculated separately for each sampling stage and for each cluster.

See Appendix A in the final report for details

Mode of data collection

Face-to-face [f2f]

Research instrument

Three questionnaires were administered in the 2013 NDHS: the Household Questionnaire, the Woman’s Questionnaire, and the Man’s Questionnaire. These questionnaires were adapted from the standard DHS6 core questionnaires to reflect the population and health issues relevant to Namibia at a series of meetings with various stakeholders from government ministries and agencies, nongovernmental organisations, and international donors. The final draft of each questionnaire was discussed at a questionnaire design workshop organised by the MoHSS from September 25-28, 2012, in Windhoek. The questionnaires were then translated from English into the six main local languages—Afrikaans, Rukwangali, Oshiwambo, Damara/Nama, Otjiherero, and Silozi—and back translated into English. The questionnaires were finalised after the pretest, which took place from February 11-25, 2013.

The Household Questionnaire was used to list all usual household members as well as visitors in the selected households. Basic information was collected on the characteristics of each person listed, including age, sex, education, and relationship to the head of the household. For children under age 18, parents’ survival status was determined. In addition, the Household Questionnaire included questions on knowledge of malaria and use of mosquito nets by household members, along with questions regarding health expenditures. The Household Questionnaire was used to identify women and men who were eligible for the individual interview and the interview on domestic violence. The questionnaire also collected information on characteristics of the household’s dwelling unit, such as source of water, type of toilet facilities, materials used for the floor of the house, and ownership of various durable goods. The results of tests assessing iodine levels were recorded as well.

In half of the survey households (the same households selected for the male survey), the Household Questionnaire was also used to record information on anthropometry and biomarker data collected from eligible respondents, as follows: • All eligible women and men age 15-64 were measured, weighed, and tested for anaemia and HIV. • All eligible women and men age 35-64 had their blood pressure and blood glucose measured. • All children age 0 to 59 months were measured and weighed. • All children age 6 to 59 months were tested for anaemia.

The Woman’s Questionnaire was also used to collect information from women age 50-64 living in half of the selected survey households on background characteristics, marriage and sexual activity, women’s work and husbands’ background characteristics, awareness and behaviour regarding AIDS and other STIs, and other health issues.

The Man’s Questionnaire was administered to all men age 15-64 living in half of the selected survey households. The Man’s Questionnaire collected much of the same information as the Woman’s Questionnaire but was shorter because it did not contain a detailed reproductive history or questions on maternal and child health or nutrition.

Cleaning operations

CSPro—a Windows-based integrated census and survey processing system that combines and replaces the ISSA and IMPS packages—was used for entry, editing, and tabulation of the NDHS data. Prior to data entry, a practical training session was provided by ICF International to all data entry staff. A total of 28 data processing personnel, including 17 data entry operators, one questionnaire administrator, two office editors, three secondary editors, two network technicians, two data processing supervisors, and one coordinator, were recruited and trained on administration of questionnaires and coding, data entry and verification, correction of questionnaires and provision of feedback, and secondary editing. NDHS data processing was formally launched during the week of June 22, 2013, at the National Statistics Agency Data Processing Centre in Windhoek. The data entry and editing phase of the survey was completed in January 2014.

Response rate

A total of 11,004 households were selected for the sample, of which 10,165 were found to be occupied during data collection. Of the occupied households, 9,849 were successfully interviewed, yielding a household response rate of 97 percent.

In these households, 9,940 women age 15-49 were identified as eligible for the individual interview. Interviews were completed with 9,176 women, yielding a response rate of 92 percent. In addition, in half of these households, 842 women age 50-64 were successfully interviewed; in this group of women, the response rate was 91 percent.

Of the 5,271 eligible men identified in the selected subsample of households, 4,481 (85 percent) were successfully interviewed.

Response rates were higher in rural than in urban areas, with the rural-urban difference more marked among men than among women.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: nonsampling errors and sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview

Structure of households by number of children in household and statistical regions, 2006-2017

Detailed household information in regards to income, age, and race, in Marin County. Data is sourced from American Community Survey 5-Year Estimates, which is updated annually. This dataset is automatically updated by Socrata; please contact support@socrata.com if you encounter any questions or issues.

Abstract

The Cambodia Inter-censal Population Survey, 2013 was conducted with the following objectives:

i. To strengthen the capacity of the staff of NIS and the provincial and district staff in demographic data collection; and

ii. To provide information to government and data users on population and household characteristics such as household size, age, sex, marital status, literacy and educational characteristics, economic characteristics, fertility, mortality and migration as well as housing and household characteristics and amenities. This should be useful to the government to evaluate the Rectangular Strategy Plan in achieving its intended goals. It will help outline priority goals and strategies to reduce poverty rapidly, and develop Cambodia Millennium Development Goals (CMDG’s) and other Socioeconomic Development Goals. It will also be useful to the National Institute of Statistics (NIS) in improving data availability and accessibility and in utilization of data until the 2018 census information is made available.

Geographic coverage

National Provincial

Analysis unit

Units of Analysis: 1. Individual 2. Household 3. Province

Universe

Population and housing units of all regular households in Cambodia excluding special settlements and institutional households

Kind of data

Sample survey data [ssd]

Mode of data collection

Face-to-face [f2f]

Research instrument

The draft questionnaires for the CIPS 2013 were more or less on the 2008 General Census pattern. Some modifications, however, were made by adding new questions on

(i) whether children aged 0-14 living with own mother (ii) whether a person's mother is alive and (iii) details of deaths in households in the last one year with focus on maternal mortality.

Questions mentioned at (i) and (ii) were intended respectively to estimate fertility (by application of own child method) and mortality (by application of orphan hood method). The questions to be included were carefully considered by a Working Group of Cambodia Inter-Censal Population Survey 2013, whose members were mostly from Ministries, NGOs and International Agencies. The Questionnaires were tested twice in the field (both urban and rural) by NIS staff in November 2012. The purpose of the pre-test was to have a full-dressed rehearsal of the whole process and particularly to test the questions in the field so as to make corrections in wording or definitions and to estimate the time taken for enumeration area mapping, house listing, sampling and enumeration of selected household. Based on the pre-test experience the questionnaires were modified and finalized.

Two types of questionnaires were used in the CIPS 2013: Form A House-list and Form B Household Questionnaire.

The Form A was used to collect information on buildings containing one or more households during the preliminary round preceding survey night (March 3, 2013). The information collected related to: construction material of wall, roof and floor, whether it is a wholly or partly residential building, number of households within the building, name and sex of head of household and number of persons usually living in the household.

The Form B, which has five parts, was used for survey enumeration in the period closely following the reference time.

In Part I, information on usual members of the selected household present on survey night, visitors present as well as usual members absent on survey night, was collected.

Part II was used to collect information on each usual member of the household and each visitor present on survey night. The information collected included: full name, relationship to household head, sex, age, natural mother, child aged 0-14 living with own mother, marital status, age at first marriage, mother tongue, religion, place of birth, previous residence, duration of stay, reason for migration, literacy, full time education and economic characteristics.

Part III was used to collect information on females of reproductive age (15-49) as well as children born to these women.

The information collected in part IV related to household conditions and facilities: main source of light, main cooking fuel used, whether toilet facility is available, main source of drinking water and number of living rooms occupied by household.

Part V was used to record the following information in respect of deaths in the household within the last one year:- name of deceased, sex, relationship to head of household, age at death, whether the death has been registered with the civil authorities or not, the cause of death and maternal mortality information.

Cleaning operations

The completed records (Forms A, Form B, Form I, Form II, Map, and other Forms) were systematically collected from the provinces by NIS Survey Coordinators on the due date and submitted to the team receptionist at NIS. NIS Survey Coordinators formed into three teams of two persons were trained from March 7 to 10 to receive and arrange the completed forms and maps for processing after due checking form the field.

Control forms were prescribed by DUC to record every form without any omission. These records were carefully checked, registered and stored in the record room. Editing and coding of the questionnaires were done manually, after which the questionnaires were submitted to the computer section for further processing.

The instruction for editing and coding were revised and expanded. Training on editing and coding was conducted for senior staff, who in turn had to train other editors and coders. The purpose of the editing process was to remove matters of obvious inconsistency, incorrectness and incompleteness, and to improve the quality of data collected. Coding had to be done very carefully in respect of birthplace and previous place of residence by using the district and province codes, and occupation and industry by using the UN International Standard Classification of Occupation (ISCO) and the International Standard Industrial Classification (ISIC) respectively. For these purposes, NIS utilized staff with sound knowledge and experience of the survey and its concepts. Those who worked as trainers or supervisors were put on this job supplemented by well-trained and tested staff. Editing and Coding was done by two teams (each with six editors and one team leader); so that one of the editors who was trained specifically in occupation/industry coding should do that coding for columns 20 and 22 of part 2 household questionnaire. The work of team members was completely checked by the Team leaders. The training on editing and coding was done from 23 to 26 March. The manual processing commenced on March 29 and was completely done by the end of May 2013.

Response rate

Response rate is 95 per cent.

Sampling error estimates

Calculations of sampling errors have been made for some estimates of totals, means and proportions for variables in Form B (annex 3).

The software used for the calculations is STATA 8.0. For the calculations presented here we have assumed that stratification was done on provinces and urban/rural (an implicit57 stratification on province and urban/rural was used for the sample selection).

In seven of the 45 strata there are only one PSU (EA) selected. This causes a problem for the standard error calculations. It is not possible get standard errors in these strata. In these strata we have split the sole EA in two parts and defined the parts as two PSUs.

The standard errors are generally rather small for estimates for major domains like urban/rural and men/women. The coefficients of variation (CV)1 are below 1% in many cases. The coefficients of variation are substantially higher for provincial estimates, especially for provinces with a small sample (e.g. province19). Design effects (Deff) have been calculated for some estimates. They are, as expected, quite low for estimates of demographic characteristics. They are considerably higher for estimates of socio-economic characteristics like employment status (also as expected). For the demographic characteristics "age at first marriage" and "marital status" we find design effects below 5 for major domains like men/women and urban/rural. The socio-economic characteristics are typically more "clustered" than the demographic characteristics, this shows up in generally higher design effects. For the major domain estimates we find design effects up to 20 and occasionally very high values of 200 or more. These "freak" values occur when the sample in terms of number of PSUs is small and when the PSU averages (or proportions) show large variation. One example is the design effect of 285 for the estimate of proportion of government employees in urban areas. The proportion is varying substantially between the 102 PSUs in the domain, the range is from 0 % to75%.