A data set of cross-nationally comparable microdata samples for 15 Economic Commission for Europe (ECE) countries (Bulgaria, Canada, Czech Republic, Estonia, Finland, Hungary, Italy, Latvia, Lithuania, Romania, Russia, Switzerland, Turkey, UK, USA) based on the 1990 national population and housing censuses in countries of Europe and North America to study the social and economic conditions of older persons. These samples have been designed to allow research on a wide range of issues related to aging, as well as on other social phenomena. A common set of nomenclatures and classifications, derived on the basis of a study of census data comparability in Europe and North America, was adopted as a standard for recoding. This series was formerly called Dynamics of Population Aging in ECE Countries. The recommendations regarding the design and size of the samples drawn from the 1990 round of censuses envisaged: (1) drawing individual-based samples of about one million persons; (2) progressive oversampling with age in order to ensure sufficient representation of various categories of older people; and (3) retaining information on all persons co-residing in the sampled individual''''s dwelling unit. Estonia, Latvia and Lithuania provided the entire population over age 50, while Finland sampled it with progressive over-sampling. Canada, Italy, Russia, Turkey, UK, and the US provided samples that had not been drawn specially for this project, and cover the entire population without over-sampling. Given its wide user base, the US 1990 PUMS was not recoded. Instead, PAU offers mapping modules, which recode the PUMS variables into the project''''s classifications, nomenclatures, and coding schemes. Because of the high sampling density, these data cover various small groups of older people; contain as much geographic detail as possible under each country''''s confidentiality requirements; include more extensive information on housing conditions than many other data sources; and provide information for a number of countries whose data were not accessible until recently. Data Availability: Eight of the fifteen participating countries have signed the standard data release agreement making their data available through NACDA/ICPSR (see links below). Hungary and Switzerland require a clearance to be obtained from their national statistical offices for the use of microdata, however the documents signed between the PAU and these countries include clauses stipulating that, in general, all scholars interested in social research will be granted access. Russia requested that certain provisions for archiving the microdata samples be removed from its data release arrangement. The PAU has an agreement with several British scholars to facilitate access to the 1991 UK data through collaborative arrangements. Statistics Canada and the Italian Institute of statistics (ISTAT) provide access to data from Canada and Italy, respectively. * Dates of Study: 1989-1992 * Study Features: International, Minority Oversamples * Sample Size: Approx. 1 million/country Links: * Bulgaria (1992), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/02200 * Czech Republic (1991), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06857 * Estonia (1989), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06780 * Finland (1990), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06797 * Romania (1992), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06900 * Latvia (1989), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/02572 * Lithuania (1989), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/03952 * Turkey (1990), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/03292 * U.S. (1990), http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06219

Abstract

This study is an experiment designed to compare the performance of three methodologies for sampling households with migrants:

• a stratified sample using the census to sample census tracts randomly, in which each household is then listed and screened to determine whether or not it has a migrant, with the full length questionnaire then being applied in a second phase only to the households of interest;
• a snowball survey in which households are asked to provide referrals to other households with migrant members;
• an intercept point survey (or time-and-space sampling survey), in which individuals are sampled during set time periods at a prespecified set of locations where households in the target group are likely to congregate.

Researchers from the World Bank applied these methods in the context of a survey of Brazilians of Japanese descent (Nikkei), requested by the World Bank. There are approximately 1.2-1.9 million Nikkei among Brazil’s 170 million population.

The survey was designed to provide detail on the characteristics of households with and without migrants, to estimate the proportion of households receiving remittances and with migrants in Japan, and to examine the consequences of migration and remittances on the sending households.

The same questionnaire was used for the stratified random sample and snowball surveys, and a shorter version of the questionnaire was used for the intercept surveys. Researchers can directly compare answers to the same questions across survey methodologies and determine the extent to which the intercept and snowball surveys can give similar results to the more expensive census-based survey, and test for the presence of biases.

Geographic coverage

Sao Paulo and Parana states

Analysis unit

Japanese-Brazilian (Nikkei) households and individuals

The 2000 Brazilian Census was used to classify households as Nikkei or non-Nikkei. The Brazilian Census does not ask ethnicity but instead asks questions on race, country of birth and whether an individual has lived elsewhere in the last 10 years. On the basis of these questions, a household is classified as (potentially) Nikkei if it has any of the following: 1) a member born in Japan; 2) a member who is of yellow race and who has lived in Japan in the last 10 years; 3) a member who is of yellow race, who was not born in a country other than Japan (predominantly Korea, Taiwan or China) and who did not live in a foreign country other than Japan in the last 10 years.

Kind of data

Sample survey data [ssd]

Sampling procedure

1) Stratified random sample survey

Two states with the largest Nikkei population - Sao Paulo and Parana - were chosen for the study.

The sampling process consisted of three stages. First, a stratified random sample of 75 census tracts was selected based on 2000 Brazilian census. Second, interviewers carried out a door-to-door listing within each census tract to determine which households had a Nikkei member. Third, the survey questionnaire was then administered to households that were identified as Nikkei. A door-to-door listing exercise of the 75 census tracts was then carried out between October 13th, 2006, and October 29th, 2006. The fieldwork began on November 19, 2006, and all dwellings were visited at least once by December 22, 2006. The second wave of surveying took place from January 18th, 2007, to February 2nd, 2007, which was intended to increase the number of households responding.

2) Intercept survey

The intercept survey was designed to carry out interviews at a range of locations that were frequented by the Nikkei population. It was originally designed to be done in Sao Paulo city only, but a second intercept point survey was later carried out in Curitiba, Parana. Intercept survey took place between December 9th, 2006, and December 20th, 2006, whereas the Curitiba intercept survey took place between March 3rd and March 12th, 2007.

Consultations with Nikkei community organizations, local researchers and officers of the bank Sudameris, which provides remittance services to this community, were used to select a broad range of locations. Interviewers were assigned to visit each location during prespecified blocks of time. Two fieldworkers were assigned to each location. One fieldworker carried out the interviews, while the other carried out a count of the number of people with Nikkei appearance who appeared to be 18 years old or older who passed by each location. For the fixed places, this count was made throughout the prespecified time block. For example, between 2.30 p.m. and 3.30 p.m. at the sports club, the interviewer counted 57 adult Nikkeis. Refusal rates were carefully recorded, along with the sex and approximate age of the person refusing.

In all, 516 intercept interviews were collected.

3) Snowball sampling survey

The questionnaire that was used was the same as used for the stratified random sample. The plan was to begin with a seed list of 75 households, and to aim to reach a total sample of 300 households through referrals from the initial seed households. Each household surveyed was asked to supply the names of three contacts: (a) a Nikkei household with a member currently in Japan; (b) a Nikkei household with a member who has returned from Japan; (c) a Nikkei household without members in Japan and where individuals had not returned from Japan.

The snowball survey took place from December 5th to 20th, 2006. The second phase of the snowballing survey ran from January 22nd, 2007, to March 23rd, 2007. More associations were contacted to provide additional seed names (69 more names were obtained) and, as with the stratified sample, an adaptation of the intercept survey was used when individuals refused to answer the longer questionnaire. A decision was made to continue the snowball process until a target sample size of 100 had been achieved.

The final sample consists of 60 households who came as seed households from Japanese associations, and 40 households who were chain referrals. The longest chain achieved was three links.

Mode of data collection

Face-to-face [f2f]

Research instrument

1) Stratified sampling and snowball survey questionnaire

This questionnaire has 36 pages with over 1,000 variables, taking over an hour to complete.

If subjects refused to answer the questionnaire, interviewers would leave a much shorter version of the questionnaire to be completed by the household by themselves, and later picked up. This shorter questionnaire was the same as used in the intercept point survey, taking seven minutes on average. The intention with the shorter survey was to provide some data on households that would not answer the full survey because of time constraints, or because respondents were reluctant to have an interviewer in their house.

2) Intercept questionnaire

The questionnaire is four pages in length, consisting of 62 questions and taking a mean time of seven minutes to answer. Respondents had to be 18 years old or older to be interviewed.

Response rate

1) Stratified random sampling 403 out of the 710 Nikkei households were surveyed, an interview rate of 57%. The refusal rate was 25%, whereas the remaining households were either absent on three attempts or were not surveyed because building managers refused permission to enter the apartment buildings. Refusal rates were higher in Sao Paulo than in Parana, reflecting greater concerns about crime and a busier urban environment.

2) Intercept Interviews 516 intercept interviews were collected, along with 325 refusals. The average refusal rate is 39%, with location-specific refusal rates ranging from only 3% at the food festival to almost 66% at one of the two grocery stores.

The Urban Household Sample of the 1860 United States Census was designed to supplement the Bateman-Foust rural sample with observations from urban areas. The sample covers both northern and southern towns and cities and permits examination of female occupations and labor force participation rates. Information on individuals includes occupation, city of residence, age, sex, race, dollar value of real and personal property owned, whether American or foreign born, and literacy. The second release of this collection adds nine constructed variables, including several weight variables, collapsed occupation, ICPSR state code, region, and unique internal family and household identifier numbers.

This study was conducted under the auspices of the Center for Studies in Demography and Ecology at the University of Washington. It is a nationally representative sample of the population of the United States in 1900, drawn from the manuscript returns of individuals enumerated in the 1900 United States Census. Household variables include region, state and county of household, size of household, and type and ownership of dwelling. Individual variables for each household member include relationship to head of household, race, sex, age, marital status, number of children, and birthplace. Immigration variables include parents' birthplace, year of immigration and number of years in the United States. Occupation variables include occupation, coded by both the 1900 and 1950 systems, and number of months unemployed. Education variables include number of months in school, whether respondents could read or write a language, and whether they spoke English.

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Dwelling

UNITS IDENTIFIED: - Dwellings: No - Households: Yes - Individuals: Yes - Group quarters: Yes

UNIT DESCRIPTIONS: - Group quarters: A collective household is a group of persons that does not live in an ordinary household, but lives in a collective establishment, sharing meal times.

Universe

Residents of France, of any nationality. Does not include French citizens living in other countries, foreign tourists, or people passing through.

Kind of data

Census/enumeration data [cen]

Sampling procedure

SAMPLE UNIT: Private dwellings and individuals for group quarters and compte a part

SAMPLE FRACTION: 5%

SAMPLE UNIVERSE: The microdata sample includes mainland France and Corsica.

SAMPLE SIZE (person records): 2,934,758

Mode of data collection

Face-to-face [f2f]

Research instrument

Form 1A for dwelling consists of (1) dwelling characteristics, (2) List A. permanent occupants of the dwelling, (3) List B. household members who do not live in the dwelling of enumeration, and (4) building characteristics; Form 2B. Individual form.

Abstract

The survey on financial literacy among the citizens of Bosnia and Herzegovina was conducted within a larger project that aims at creating the Action Plan for Consumer Protection in Financial Services.

The conclusion about the need for an Action Plan was reached by the representatives of the World Bank, the Federal Ministry of Finance, the Central Bank of Bosnia and Herzegovina, supervisory authorities for entity financial institutions and non-governmental organizations for the protection of consumer rights, based on the Diagnostic Review on Consumer Protection and Financial Literacy in Bosnia and Herzegovina conducted by the World Bank in 2009-2010. This diagnostic review was conducted at the request of the Federal Ministry of Finance, as part of a larger World Bank pilot program to assess consumer protection and financial literacy in developing countries and middle-income countries. The diagnostic review in Bosnia and Herzegovina was the eighth within this project.

The financial literacy survey, whose results are presented in this report, aims at establishing the basic situation with respect to financial literacy, serving on the one hand as a preparation for the educational activities plan, and on the other as a basis for measuring the efficiency of activities undertaken.

Geographic coverage

Data collection was based on a random, nation-wide sample of citizens of Bosnia and Herzegovina aged 18 or older (N = 1036).

Analysis unit

Household, individual

Universe

Population aged 18 or older

Kind of data

Sample survey data [ssd]

Sampling procedure

SUMMARY

In Bosnia and Herzegovina, as is well known, there is no completely reliable sample frame or information about universe. The main reasons for such a situation are migrations caused by war and lack of recent census data. The last census dates back to 1991, but since then the size and distribution of population has significantly changed. In such a situation, researchers have to combine all available sources of population data to estimate the present size and structure of the population: estimates by official statistical offices and international organizations, voters? lists, list of polling stations, registries of passport and ID holders, data from large random surveys etc.

The sample was three-stage stratified: in the first stage by entity, in the second by county/region and in the third by type of settlement (urban/rural). This means that, in the first stage, the total sample size was divided in two parts proportionally to number of inhabitants by entity, while in the second stage the subsample size for each entity was further divided by regions/counties. In the third stage, the subsample for each region/county was divided in two categories according to settlement type (rural/urban).

Taking into the account the lack of a reliable and complete list of citizens to be used as a sample frame, a multistage sampling method was applied. The list of polling stations was used as a frame for the selection of primary sampling units (PSU). Polling station territories are a good choice for such a procedure since they have been recently updated, for the general elections held in October 2010. The list of polling station territories contains a list of addresses of housing units that are certainly occupied.

In the second stage, households were used as a secondary sampling unit. Households were selected randomly by a random route technique. In total, 104 PSU were selected with an average of 10 respondents per PSU. The respondent from the selected household was selected randomly using the Trohdal-Bryant scheme.

In total, 1036 citizens were interviewed with a satisfactory response rate of around 60% (table 1). A higher refusal rate is recorded among middle-age groups (table 2). The theoretical margin of error for a random sample of this size is +/-3.0%.

Due to refusals, the sample structure deviated from the estimated population structure by gender, age and education level. Deviations were corrected by RIM weighting procedure.

MORE DETAILED INFORMATION

IPSOS designed a representative sample of approximately 1.000 residents age 18 and over, proportional to the adult populations of each region, based on age, sex, region and town (settlement) type.

For this research we designed three-stage stratified representative sample. First we stratify sample at entity level, regional level and then at settlement type level for each region.

Sample universe:

Population of B&H -18+; 1991 Census figures and estimated population dynamics, census figures of refugees and IDPs, 1996. Central Election Commision - 2008; CIPS - 2008;

Sampling frame:

Polling stations territory (approximate size of census units) within strata defined by regions and type of settlements (urban and rural) Polling stations territories are chosen to be used as primary units because it enables the most reliable sample selection, due to the fact that for these units the most complete data are available (dwelling register - addresses)

Type of sample:

Three stage random representative stratified sample

Definition and number of PSU, SSU, TSU, and sampling points

• PSU - Polling station territory Definition: Polling stations territories are defined by street(s) name(s) and dwelling numbers; each polling station territory comprises approximately 300 households, with exception of the settlements with less than 300 HH which are defined as one unite. Number of PSUs in sample universe: 4710
• SSU - Household Definition: One household comprises people living in the same apartment and sharing the expenditure for food
• TSU - Respondent Definition: Member of the HH , 18+ Number of TSUs in sample universe: = 2.966.766
• Sampling points Approximately 10 respondents per one PSU, total 104

Stratification, purpose and method

• First level strata: Federation of B&H Republika Srpska Brc ko District
• Second level strata: 10 cantons 2 regions -
• Third level strata: urban and rural settlements
• Purpose: Optimisation of the sample plan, and reducing the sampling error

• Method: The strata are defined by criteria of optimal geographical and cultural uniformity

• Selection procedure of PSU, SSU, and respondent Stratification, purpose and method

• PSU Type of sampling of the PSU: Polling station territory chosen with probability proportional to size (PPS) Method of selection: Cumulative (Lachirie method)

• SSU Type of sampling of the SSU: Sample random sampling without replacement Method of selection: Random walk - Random choice of the starting point

• TSU - Respondent Type of sampling of respondent: Sample random sampling without replacement Method of selection: TCB (Trohdal-Bryant scheme)

• Sample size N=1036 respondents

• Sampling error Marginal error +/-3.0%

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey was modelled after the identical survey conducted in Romania. The questionnaire used in the Financial Literacy Survey in Romania was localized for Bosnia and Herzegovina, including adaptations to match the Bosnian context and methodological improvements in wording of questions.

Cleaning operations

Before data entry, 100% logic and consistency controls are performed first by local supervisors and once later by staff in central office.

Verification of correct data entry is assured by using BLAISE system for data entry (commercial product of Netherlands statistics), where criteria for logical and consistency control are defined in advance.

Response rate

• Nobody at home: 2,8%
• Eligible person is not home: 2,8%
• Refusal : 32,79%
• Given up after a minimum of two visits: 0,82%
• Other (excluded after control): 0,29%
• Finished: 60,5%

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2023 American Community Survey 1-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..The 60 years and over column of data refers to the age of the householder for the estimates of households, occupied housing units, owner-occupied housing units, and renter-occupied housing units lines..The age specified on the population 15 years and over, population 25 years and over, population 30 years and over, civilian population 18 years and over, civilian population 5 years and over, population 1 years and over, population 5 years and over, and population 16 years and over lines refer to the data shown in the "Total" column while the second column is limited to the population 60 years and over..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

The Census of Population and Housing is one of the most important surveys carried out by ISTAT. It is conducted every ten years from 1861, and the main objectives are: the count of the whole population and the recognition of its structural characteristics; updating and revision of civil registers; the definition of the legal population for juridical and electoral purposes; the collection of information about the number and structural characteristics of houses and buildings. The Census collects information about demographic and family structure of the population, the types of their households, their level of education, their employment status, and other informations on residents population. In 2011, for the first time, some information of socio-economic character were measured on a sample basis through the use of two types of questionnaire: one in a reduced form, with a few questions, including indispensable information for the production of the data required by the European Union with an high spatial detail, and one in complete form. In particular, Istat provides a 1% sample data (594,247 cases) released in two separate datasets: the first file (individui) refers to persons usually resident in private households and in Institutional households and the second one (alloggi) refers to living quarters. In urban areas with at least 20,000 inhabitants a sample was selected by a simple random sampling without replacement procedure of one third of the families. A complete version (long form) of the questionnaire has been sent to the sample, while a short version the questionnaire has been sent to all other inhabitants. web-based self-administered questionnaire (CAWI)

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Household

UNITS IDENTIFIED: - Dwellings: No - Vacant units: No - Households: Yes - Individuals: Yes - Group quarters: Yes (institutional)

UNIT DESCRIPTIONS: - Dwellings: Not available - Households: An individual or group of people who inhabit part or all of the physical or census building, usually live together, who eat from one kitchen or organize daily needs together as one unit. - Group quarters: A special household includes people living in dormitories, barracks, or institutions in which daily needs are under the responsibility of a foundation or other organization. Also includes groups of people in lodging houses or buildings, where the total number of lodgers is ten or more.

Universe

All population residing in the geographic area of Indonesia regardless of residence status. Diplomats and their families residing in Indonesia were excluded.

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: Statistics Indonesia

SAMPLE DESIGN: Geographically stratified systematic sample (drawn by MPC).

SAMPLE UNIT: Household

SAMPLE FRACTION: 10%

SAMPLE SIZE (person records): 20,112,539

Mode of data collection

Face-to-face [f2f]

Research instrument

L1 questionnaire for buildings and households; L2 questionnaire for permanent residents; and L3 questionnaire for non-permanent residents (boat people, homeless persons, etc).

Geographic coverage

The survey covered the whole of the Indian Union except (i) Leh (Ladakh) and Kargil districts of Jammu & Kashmir (for central sample), (ii) interior villages of Nagaland situated beyond five kilometres of the bus route and (iii) villages in Andaman and Nicobar Islands which remain inaccessible throughout the year.

Analysis unit

Household, Individual

Universe

The following rules regarding the population to be covered were applied in listing of households and persons:

1. Under-trial prisoners in jails and indoor patients of hospitals, nursing homes etc., are to be excluded, but residential staff therein will be listed while listing is done in such institutions. The persons of the first category will be considered as normal members of their parent households and will be counted there. Convicted prisoners undergoing sentence will be outside the coverage of the survey.

2. Floating population, i.e., persons without any normal residence will not be listed. But households residing in open space, roadside shelter, under a bridge, etc., more or less regularly in the same place, will be listed.

3. Foreign nationals will not be listed, nor their domestic servants, if by definition the latter belong to the foreign national's household. If, however, a foreign national becomes an Indian citizen for all practical purposes, he or she will be covered.

4. Persons residing in barracks of military and paramilitary forces (like police, BSF, etc.) will be kept outside the survey coverage due to difficulty in conduct of survey therein. However, civilian population residing in their neighbourhood, including the family quarters of service personnel, are to be covered. Permission for this may have to be obtained from appropriate authorities.

5. Orphanages, rescue homes, ashrams and vagrant houses are outside the survey coverage. However, persons staying in old age homes, students staying in ashrams/ hostels and the residential staff (other than monks/ nuns) of these ashrams may be listed. For orphanages, although orphans are not to be listed, the persons looking after them and staying there may be considered for listing.

DEFINITION OF A HOUSEHOLD:

A group of persons normally living together and taking food from a common kitchen will constitute a household. It will include temporary stay-aways (those whose total period of absence from the household is expected to be less than 6 months) but exclude temporary visitors and guests (expected total period of stay less than 6 months). Even though the determination of the actual composition of a household will be left to the judgment of the head of the household, the following procedures will be adopted as guidelines.

(i) Each inmate (including residential staff) of a hostel, mess, hotel, boarding and lodging house, etc., will constitute a single-member household. If, however, a group of persons among them normally pool their income for spending, they will together be treated as forming a single household. For example, a family living in a hotel will be treated as a single household.

(ii) In deciding the composition of a household, more emphasis is to be placed on 'normally living together' than on 'ordinarily taking food from a common kitchen'. In case the place of residence of a person is different from the place of boarding, he or she will be treated as a member of the household with whom he or she resides.

(iii) A resident employee, or domestic servant, or a paying guest (but not just a tenant in the household) will be considered as a member of the household with whom he or she resides even though he or she is not a member of the same family.

(iv) When a person sleeps in one place (say, in a shop or in a room in another house because of space shortage) but usually takes food with his or her family, he or she should be treated not as a single member household but as a member of the household in which other members of his or her family stay.

(v) If a member of a family (say, a son or a daughter of the head of the family) stays elsewhere (say, in hostel for studies or for any other reason), he/ she will not be considered as a member of his/ her parent's household. However, he/ she will be listed as a single member household if the hostel is listed.

Kind of data

Sample survey data [ssd]

Sampling procedure

Outline of sample design: A stratified multi-stage design has been adopted for the 64th round survey. The first stage units (FSU) was the 2001 census villages (Panchayat wards in case of Kerala) in the rural sector and Urban Frame Survey (UFS) blocks in the urban sector. However, for the newly declared towns and out growths (OGs) in census 2001 for which UFS had not yet been done, each individual town/ OG was considered as an FSU. The ultimate stage units (USU) was be households in both the sectors. In case of large FSUs i.e. villages/ towns/ blocks requiring hamlet-group (hg)/ sub-block (sb) formation, one intermediate stage was the selection of two hgs/ sbs from each FSU.

Sampling Frame for First Stage Units: For the rural sector, the list of 2001 census villages (Panchayat wards for Kerala) constitute the sampling frame. For the urban sector, the list of latest available Urban Frame Survey (UFS) blocks and for non-UFS towns list of such towns/ OGs was considered as the sampling frame.

Stratification: Within each district of a State/ UT, generally speaking, two basic strata were formed: i) rural stratum comprising of all rural areas of the district and (ii) urban stratum comprising of all the urban areas of the district. However, within the urban areas of a district, if there were one or more towns with population 10 lakhs or more as per population census 2001 in a district, each of them formed a separate basic stratum and the remaining urban areas of the district was considered as another basic stratum. For a few districts, particularly in case of Tamil Nadu, if total number of towns in the district for which UFS was not yet done exceeds certain number, all such towns taken together formed another basic stratum. Otherwise, they were merged with the UFS towns for stratification.

Sub-stratification in the Rural sector: If "r" be the sample size allocated for a rural stratum, the number of sub-strata formed is "r/4?. The villages within a district as per frame were first arranged in ascending order of population. Then sub-strata 1 to "r/4" were demarcated in such a way that each sub-stratum comprised a group of villages of the arranged frame and have more or less equal population.

Sub-stratification in the Urban sector: If "u" be the sample size for a urban stratum, "u/4" number of sub-strata were formed. The towns within a district, except those with population 10 lakhs or more and also the non-UFS towns, were first arranged in ascending order of population. Next, UFS blocks of each town were arranged by IV unit no. × block no. in ascending order. From this arranged frame of UFS blocks of all the towns, "u/4? number of sub-strata were formed in such a way that each sub-stratum had more or less equal number of FSUs. For towns with population 10 lakhs or more, the urban blocks were first arranged by IV unit no. × block no. in ascending order. Then "u/4? number of sub-strata were formed in such a way that each sub-stratum had more or less equal number of blocks. All non-UFS towns taken together within the district formed one sub-stratum.

Total sample size (FSUs): 12688 FSUs for central sample and 13624 FSUs for state sample have been allocated at all-India level.

Allocation of total sample to States and UTs: The total number of sample FSUs is allocated to the States and UTs in proportion to population as per census 2001 subject to a minimum sample allocation to each State/ UT. While doing so, the resource availability in terms of number of field investigators had been kept in view.

Allocation of State/ UT level sample to rural and urban sectors: State/ UT level sample was allocated between two sectors in proportion to population as per census 2001 with 1.5 weightage to urban sector subject to the restriction that urban sample size for bigger states like Maharashtra, Tamil Nadu etc. should not exceed the rural sample size. A minimum of 8 FSUs was allocated to each state/ UT separately for rural and urban areas. Further the State level allocation for both rural and urban have been adjusted marginally in a few cases to ensure that each stratum gets a minimum allocation of 4 FSUs.

==========

More information on the sampling methodology is available in the document " Instructions to Field Staff - Volume-I"

Mode of data collection

Face-to-face [f2f]

Research instrument

In the 64th round survey, a separate schedule on employment and unemployment (Schedule 10.2), with provision for collecting information on migration particulars, will be canvassed.

The broad structure of the employment and unemployment part of Schedule 10.2 will be the same as that of the schedule canvassed during the NSS 60th round with the following modifications: a) Information on vocational training will not be collected. b) Particulars of persons unemployed on all the 7 days will not be collected in the present round.

The scope for collecting information on migration particulars has been enlarged with the provision for collecting information on: a) Migration particulars of the households which migrated to the place of enumeration during the last 365 days, such as location of last usual residence, pattern of migration and reason for migration. b) Particulars of out-migrants who migrated out to other village/ town, from the household, any time in the past, such as present place of residence, reason for migration, period

The 1940 Census Public Use Microdata Sample Project was assembled through a collaborative effort between the United States Bureau of the Census and the Center for Demography and Ecology at the University of Wisconsin. The collection contains a stratified 1-percent sample of households, with separate records for each household, for each "sample line" respondent, and for each person in the household. These records were encoded from microfilm copies of original handwritten enumeration schedules from the 1940 Census of Population. Geographic identification of the location of the sampled households includes Census regions and divisions, states (except Alaska and Hawaii), standard metropolitan areas (SMAs), and state economic areas (SEAs). Accompanying the data collection is a codebook that includes an abstract, descriptions of sample design, processing procedures and file structure, a data dictionary (record layout), category code lists, and a glossary. Also included is a procedural history of the 1940 Census. Each of the 20 subsamples contains three record types: household, sample line, and person. Household variables describe the location and condition of the household. The sample line records contain variables describing demographic characteristics such as nativity, marital status, number of children, veteran status, wage deductions for Social Security, and occupation. Person records also contain variables describing demographic characteristics including nativity, marital status, family membership, education, employment status, income, and occupation. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR at https://doi.org/10.3886/ICPSR08236.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

The American Community Survey (ACS) Public Use Microdata Sample (PUMS) contains a sample of responses to the ACS. The ACS PUMS dataset includes variables for nearly every question on the survey, as well as many new variables that were derived after the fact from multiple survey responses (such as poverty status).Each record in the file represents a single person, or, in the household-level dataset, a single housing unit. In the person-level file, individuals are organized into households, making possible the study of people within the contexts of their families and other household members. Individuals living in Group Quarters, such as nursing facilities or college facilities, are also included on the person file. ACS PUMS data are available at the nation, state, and Public Use Microdata Area (PUMA) levels. PUMAs are special non-overlapping areas that partition each state into contiguous geographic units containing roughly 100,000 people each. ACS PUMS files for an individual year, such as 2019, contain data on approximately one percent of the United States population.

This layer contains 2010-2014 American Community Survey (ACS) 5-year data, and contains estimates and margins of error. The layer shows children by age group by parents' labor force participation. This is shown by tract, county, and state boundaries. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis.This layer is symbolized to show the percent of children with no available (residential) parent in the labor force. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Vintage: 2010-2014ACS Table(s): B23008 Data downloaded from: Census Bureau's API for American Community Survey Date of API call: November 11, 2020National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer has associated layers containing the most recent ACS data available by the U.S. Census Bureau. Click here to learn more about ACS data releases and click here for the associated boundaries layer. The reason this data is 5+ years different from the most recent vintage is due to the overlapping of survey years. It is recommended by the U.S. Census Bureau to compare non-overlapping datasets.Boundaries come from the US Census TIGER geodatabases. Boundary vintage (2014) appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

This layer shows Population by Age and Sex. This is shown by state and county boundaries. This service contains the 2018-2022 release of data from the American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the Total population ages 65 and over. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2018-2022ACS Table(s): B01001, B01002, DP05Data downloaded from: Census Bureau's API for American Community Survey Date of API call: January 18, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:Boundaries come from the Cartographic Boundaries via US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates, and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto Rico. The Counties (and equivalent) layer contains 3221 records - all counties and equivalent, Washington D.C., and Puerto Rico municipios. See Areas Published. Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells.Margin of error (MOE) values of -555555555 in the API (or "*****" (five asterisks) on data.census.gov) are displayed as 0 in this dataset. The estimates associated with these MOEs have been controlled to independent counts in the ACS weighting and have zero sampling error. So, the MOEs are effectively zeroes, and are treated as zeroes in MOE calculations. Other negative values on the API, such as -222222222, -666666666, -888888888, and -999999999, all represent estimates or MOEs that can't be calculated or can't be published, usually due to small sample sizes. All of these are rendered in this dataset as null (blank) values.

The Public Use Microdata Samples (PUMS) from the 1980 Census contain person- and household-level information from the "long-form" questionnaires distributed to a sample of the population enumerated in the 1980 Census. The B Sample contains information for each state, and for households and persons residing in metropolitan areas that are too small to be separately identified and/or that cross state boundaries. Standard Metropolitan Statistical Areas (SMSAs) and county groups are defined differently here than in the A Sample [CENSUS OF POPULATION AND HOUSING, 1980 [UNITED STATES]: PUBLIC USE MICRODATA SAMPLE (A SAMPLE): 5-PERCENT SAMPLE (ICPSR 8101)]. Most states cannot be identified in their entirety. As a percentage of the l-Percent Public Use Microdata Sample (B Sample) [CENSUS OF POPULATION AND HOUSING, 1980 [UNITED STATES]: PUBLIC USE MICRODATA SAMPLE (B SAMPLE): 1-PERCENT SAMPLE (ICPSR 8170)], this file constitutes a 1-in-1000 sample, and contains all household- and person-level variables from the original B Sample. Household-level variables include housing tenure, year structure was built, number and types of rooms in dwelling, plumbing facilities, heating equipment, taxes and mortgage costs, number of children, and household and family income. Person-level variables include sex, age, marital status, race, Spanish origin, income, occupation, transportation to work, and education. (Source: retrieved from ICPSR 06/15/2011)

The 1961 Census Microdata for Great Britain: 9% Sample: Secure Access dataset was created from existing digital records from the 1961 Census. It comprises a larger population sample than the other files available from the 1961 Census (see below) and so contains sufficient information to constitute personal data, meaning that it is only available to Accredited Researchers, under restrictive Secure Access conditions. See Access section for further details.

The file was created under a project known as Enhancing and Enriching Historic Census Microdata Samples (EEHCM), which was funded by the Economic and Social Research Council with input from the Office for National Statistics and National Records of Scotland. The project ran from 2012-2014 and was led from the UK Data Archive, University of Essex, in collaboration with the Cathie Marsh Institute for Social Research (CMIST) at the University of Manchester and the Census Offices. In addition to the 1961 data, the team worked on files from the 1971 Census and 1981 Census.

The original 1961 records preceded current data archival standards and were created before microdata sets for secondary use were anticipated. A process of data recovery and quality checking was necessary to maximise their utility for current researchers, though some imperfections remain (see the User Guide for details).

Three other 1961 Census datasets have been created; users should obtain the other datasets in the series first to see whether they are sufficient for their research needs before considering making an application for this study (SN 8275), the Secure Access version:

• SN 8272 - 1961 Census Microdata Individual File for Great Britain: 5% Sample, which contains information on individuals in larger local authorities;
• SN 8273 - 1961 Census Microdata Household File for Great Britain: 0.95% Sample, which links household members together to allow individuals to be understood within their household context. SNs 8272 and 8273 are both available to registered UK Data Service users based in the United Kingdom (see Access section for non-UK access restrictions); and
• SN 8274 - 1961 Census Microdata Teaching Dataset for Great Britain: 1% Sample: Open Access, which can be used as a taster file and is freely available for anyone to download under an Open Government Licence.

NOTE: Data based on a sample except in P3, P4, H3, and H4. For.information on confidentiality protection, sampling error,.nonsampling error, definitions, and count corrections see.http://www.census.gov/prod/cen2000/doc/sf3.pdf

Abstract

National Labor Force Survey (SAKERNAS) is a survey that is designed to observe the general situation of workforce and also to understand whether there is a change of workforce structure between the enumeration period. Since the survey was initiated in 1976, it has undergone a series of changes affecting its coverage, the frequency of enumeration, the number of households sampled and the type of information collected. It is the largest and most representative source of employment data in Indonesia. For each selected household, the general information about the circumstances of each household member that includes the name, relationship to head of household, sex, and age were collected. Household members aged 10 years and over will be prompted to give the information about their marital status, education and employment.

SAKERNAS is aimed to gather informations that meet three objectives: 1.Employment by education, working hours, industrial classification and employment status, 2.Unemployment and underemployment by different characteristics and efforts on looking for work, 3.Working age population not in the labor force (e.g. attending schools, doing housekeeping and others).

The data for annual SAKERNAS was gathered in August 2002 covered all provinces in Indonesia with 68.608 households, scattered both in rural and urban areas and representative until provincial level. The main household data is taken from core questionnaire of SAK2002-AK.

Geographic coverage

National coverage*, including urban and rural area, representative until provincial level.

*) Although covering all of Indonesia, there are some circumstances when not all provincial were covered. For example, in 2000, the Province of Maluku excluded in SAKERNAS because horizontal conflicts occurred there. Also, the separation of East Timor from Indonesia in 1999 also changed the scope of SAKERNAS for the years to come. After that, due to the expansion of regional autonomy as a consequence, the proportion of samples per Province is also changed, as in 2006 when the number of provinces are already 33. However, the difference is only on the number of influential scope/level but not to the pattern. On the other hand, changes in the methodology (including sample size) over time is likely to affect the outcome, for example in years 2000 and 2001, when sample size is only 32.384 and 34.176 the level of data presentation is only representative to island level, (insufficient sample size even to make it representative to provincial level).

Analysis unit

Individual

Universe

The survey covered all de jure household members (usual residents), aged 10 years and over that resident in the household. However, Diplomatic Corps households, households that are in the specific enumeration area and specific households in the regular enumeration area are not chosen as a sample.

Kind of data

Sample survey data

Sampling procedure

Annual SAKERNAS 2002 was implemented in the whole territory of the Republic of Indonesia with a total sample of about 68.608 households, both in rural and urban areas and representative until provincial level. Diplomatic Corps households, households that are in the specific enumeration area and specific households in the regular enumeration area are not chosen as a sample.

The sampling method* for annual SAKERNAS 2002 is two-stages cluster sampling design with census block as the primary sampling unit (PSU) and households as the ultimate sampling unit. PSUs were selected with probability proportional to size. A number of households were taken randomly from selected PSUs. However, there is documentation explained about how the sample size was determined at the domain level, or stratification measures that were implemented and also, the sample size allocation across strata, and also detail information about sample frame**.

The sampling for the urban areas and rural areas is done separately, and by following this procedure: 1. In the first stage, from the sample frame of census block, selected some census block number with probability proportional to size (pps) to the number of household size. 2. At the second stage, from each selected census blocks selected some households in linear systematic household sampling.The first stage sample selection is done by the BPS, while the second level is done by the supervisor/examiner of SAKERNAS.

*) Sampling method used is varied in different years. For example, in SAKERNAS period of 1986-1989 sampling method used is the method of rotation, where most of the households selected at one period was re-elected in the following period. This often happens on quarterly SAKERNAS on that period. At other periods often use multi-stages sampling method (two or three stages depend on whether sub block census included or not), or a combination of multi stages sampling also with rotation method (e.g. SAKERNAS 2006).

**) Commonly, annual SAKERNAS sample frame comes from the last population census result undertaken before SAKERNAS. For example, for annual SAKERNAS 2003 used sample frame derived from "listing process" of household results of Population Census 2000. Also can refer to sampling frame of some periodic household based census like Economic Census, e.g. block census sample frame of SAKERNAS 2007 formed using Economic Census 2006 result. In the other hand sample frame used for quarterly SAKERNAS is from the list of households obtained from National Socio-Economic Survey (SUSENAS) Core activities held before Sakernas, e.g. for quarterly SAKERNAS 2002/2003 activities, used sample frame which derived from households of the selected districts of SUSENAS 2002.

Mode of data collection

Face-to-face

Research instrument

In SAKERNAS, the questionnaire has been designed in a simple and concise way. It is expected that respondents will understand the aim of question of survey and avoid the memory lapse and uninterested respondents during data collection. Furthermore, the design of SAKERNAS's questionnaire remains stable in order to maintain data comparison.

A household questionnaire was administered in each selected household, which collected general information of household members that includes name, relationship with head of the household, sex and age. Household members aged 10 years and over were then asked about their marital status, education and occupation.

Cleaning operations

Stages of data processing in Sakernas are through process of: - Batching - Editing - Coding - Data Entry - Validation - Tabulation

Sampling error estimates

Sampling error results are presented at the end of the publication of The State of Labor Force in Indonesia and in publication of The State of Workers in Indonesia.

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Households and Group Quarters

UNITS IDENTIFIED: - Dwellings: No - Vacant units: Yes

UNIT DESCRIPTIONS: - Households: Dwelling places excluding institutions and transient quarters. - Group quarters: No threshold was applied; in order for a household to be considered group quarters in 2000, it had to be on the list of group quarters that is continuously maintained by the Census Bureau.

Universe

Residents of Puerto Rico.

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: U.S. Census Bureau

SAMPLE UNIT: Household

SAMPLE FRACTION: 5%

SAMPLE SIZE (person records): 189,828

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2000 census used a long form questionnaire. Long Form Sampling Entities (LFSEs) were used to determine sampling rates. If the smallest LFSE that included all or any part of a block had an estimated housing unit count of less than 800, the housing units in the block were sampled at a 1-in-2 rate. If it had an estimated housing unit count of 800 or more but less than 1,200, units were sampled at a 1-in-4 rate. If a block was not in either of the two previous categories, and was part of an interim census tract with 2,000 or more estimated housing units, units were sampled at a 1-in-8 rate. Housing units in all remaining blocks were sampled at a 1-in-6 rate. When all sampling rates were taken into account across the nation, approximately 1 out of every 6 housing units was included in the Census 2000 sample.

Response rate

UNDERCOUNT: No official estimates

Abstract

The Lao PDR Multiple Indicator Cluster Survey (MICS) 2006 is the third Multiple Indicator Cluster Survey undertaken by the Department of Statistics (Former NSC) of the Ministry of Planning and Investment in close collaboration with the Hygiene and Prevention Department of Ministry of Health. For the purposes of MICS3 a number of additional nutrition indicators were included, with the aim of strengthening the planning and management of the national nutrition programme. A separate National Nutrition Survey report has been produced to document the findings from the nutrition component of the survey.

The 2006 Lao PDR Multiple Indicator Cluster Survey has as its primary objectives: • To provide up-to-date information for assessing the situation of children and women in the Lao PDR; • To furnish data needed for monitoring progress toward goals established in the Millennium Declaration, the goals of A World Fit For Children (WFFC), and other internationally agreed upon goals, as a basis for future action; • To contribute to the improvement of data and monitoring systems in the Lao PDR and to strengthen technical expertise in the design, implementation, and analysis of such systems.

The 2006 Lao PDR MICS is a nationally representative sample survey which was conducted between March and June 2006. In the 5,894 households successfully interviewed nationally in the survey, 33,100 household members were listed. Of these, 16,467 were males and 16,633 were females. The average household size found in the survey was 5.6.

Geographic coverage

National

Analysis unit

• Households
• Individuals

Universe

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

Kind of data

Sample survey data [ssd]

Sampling procedure

The primary objective of the sample design for the Lao PDR Multiple Indicator Cluster Survey was to produce statistically reliable estimates of most indicators, at the national level, for urban and rural areas with road access and without road access, and for the three regions (North, Central and South) of the country. Urban and rural areas with road access and rural areas without road access in each of the three regions were defined as the sampling domains.

A multi-stage, stratified cluster sampling approach was used for the selection of the survey sample.

The target sample size for the Lao MICS was calculated as 6,000 households. For the calculation of the sample size, the key indicator used was the TT coverage among women who had given birth in the past 12 months.

The 2005 census frame was used for the selection of clusters. Census enumeration areas were defined as primary sampling units (PSUs), and were selected from each of the sampling domains by using systematic PPS (probability proportional to population size) sampling procedures, based on the estimated population size of the enumeration areas from the 2005 Population Census. The first stage of sampling was thus completed by selecting the required number of enumeration areas from each of the three regions by urban and rural with road access and without road access areas separately.

Although the sample was designed to collect information from 6,000 households, it was known in advance that one village only had 15 households, therefore the total expected number of households was 5,995. Of the selected enumeration areas, all but two were visited during the fieldwork period. The two missing enumeration areas were replaced in the field with villages of similar area type. The sample was stratified by region and is not self-weighting. For reporting national level results, sample weights are used.

Since the sample frame (the 2005 Population Census) was up to date, household lists in all selected enumeration areas were not updated prior to the selection of households.

Lists of households were prepared by the listing teams in the field for each enumeration area. The households were then sequentially numbered from 1 to n (the total number of households in each enumeration area) at the National Statistics Centre, where selection of 20 households in each enumeration area was carried out using systematic selection procedures.

The sampling procedures are more fully described in "Multiple Indicator Cluster Survey 2006 - Final Report" pp.135-136.

Mode of data collection

Face-to-face [f2f]

Research instrument

Three sets of questionnaires were used in the survey: 1) a household questionnaire which was used to collect information on all de jure household members, the household, and the dwelling; 2) a women’s questionnaire administered in each household to all women aged 15-49 years; and 3) an under-5 questionnaire, administered to mothers or caretakers of all children under five living in the household. The questionnaires included the following modules:

The Household Questionnaire included the following modules: o Extended household listing o Education o Water and Sanitation o Household Characteristics o Insecticide Treated Nets o Child Labour o Child Discipline o Disability o Salt Iodisation and Consumption of Fortifiable Centrally-processed Foods

The Questionnaire for Individual Women was administered to all women aged 15-49 years living in the households, and included the following modules: o Pregnancy o Tetanus Toxoid o Maternal and Newborn Health o Attitudes Towards Domestic Violence o Anthropometry assessments on women of reproductive age o Collection of blood and urine from women of reproductive age

The Questionnaire for Children Under Five was administered to mothers or caretakers of children under five years of age living in the households. Normally, the questionnaire was administered to mothers of under-5 children; in cases when the mother was not listed in the household roster or was not home, a primary caretaker for the child was identified and interviewed. The questionnaire included the following modules: o Birth Registration and Early Learning o Child Development o Vitamin A o Breastfeeding o Care of Child Illness o Malaria among Under Five o Immunization o Anthropometry o Collection of blood and stool samples (In the subset of nutrition clusters only - results of biochemical analyses of these samples can be found in the nutrition report)

The questionnaires are based on the MICS3 model questionnaire. From the MICS3 model English version, the questionnaires were translated into Lao and were pre-tested in four villages of Vientiane Capital during January 2006. Based on the results of the pre-test, modifications were made to the wording and translation of the questionnaires.

Cleaning operations

Data were entered using the CSPro software. The data were entered on 14 microcomputers and carried out by 14 data entry operators and four data entry supervisors. In order to ensure quality control, all questionnaires were double entered and internal consistency checks were performed. However due to unfamiliarity in using the CSPro software, the final consistency checks and the correction in data files were performed using the Statistical Package for Social Sciences (SPSS) software instead. Procedures and standard programmes developed under the global MICS3 project and adapted to the Lao PDR questionnaire were used throughout, except for the final step in consistency checks. Data processing began in May 2006 and was completed in August 2006.

Response rate

Of the 5,995 households selected for the sample, 5,991 were found to be occupied. Of these, 5,894 were successfully interviewed for a household response rate of 98.4 percent. In the interviewed households, 7,703 women (age 15-49) were identified. Of these, 7,387 were successfully interviewed, yielding a response rate of 95.9 percent. In addition, 4,204 children under five were listed in the household questionnaire. Questionnaires were completed for 4,136 of these children, which corresponds to a response rate of 98.4 percent. Overall response rates of 94.3 and 96.8 are calculated for the women’s and under-5’s interviews respectively. Response rates were similar across all regions and areas.

Sampling error estimates

The sample of respondents selected in the Lao PDR Multiple Indicator Cluster Survey is only one of the samples that could have been selected from the same population, using the same design and size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. The extent of variability is not known exactly, but can be estimated statistically from the survey results.

The following sampling error measures are presented in this appendix for each of the selected indicators: • Standard error (se): Sampling errors are usually measured in terms of standard errors for particular indicators (means, proportions etc). Standard error is the square root of the variance. The Taylor linearisation method is used for the estimation of standard errors. • Coefficient of variation (se/r) is the ratio of the standard error to the value of the indicator • Design effect (deff) is the ratio of the actual variance of an indicator, under the sampling method used in the survey, to the variance calculated under the assumption of simple random sampling. The square root of the design effect (deft) is used to show the efficiency of the sample design. A deft value of 1.0 indicates that the sample design is as efficient as a simple random sample, while a deft value above 1.0 indicates the increase in the