A list of other microdata sources outside of the DLI and ISR.

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

A public-use microdata sample focusing on the older population created from the 1990 census. This sample consists of 3 percent of households with at least one member aged 60 or older. Although, the highest age presented is age 90, this allows analysis of data on the very old for most states with a reasonable degree of reliability. Since data for all members in households containing a person 60 years and over will be on the file, users will be able to analyze patterns such as living arrangements and sources of household income from which older members may benefit. Additionally, users will be able to augment the PUMS-O sample with a PUMS file. The Census Bureau has issued two regular PUMS files for the entire population. One PUMS file will contain 1 percent of all households; the other PUMS file will contain 5 percent of all households. Both files have most sample data items, and differ only in geographical composition. The 1-percent file contains geographic areas that reflect metropolitan vs. non-metropolitan areas. The 5-percent file shows counties or groups of counties as well as large sub-county areas such as places of 100,000 or more. The geography on the 5-percent PUMS file matches that of the PUMS-O file. Since data for different households are present on the two files, users can merge the PUMS-O file with the 5-percent PUMS to construct an 8-percent sample. However, weighted averages must be constructed for any estimates created because each sample yields state-level estimates. Thus, it is possible to analyze substate areas even for the very old. In states where the geographic areas identified on the PUMS-O and the 5-percent PUMS are coterminous with State Planning and Service Areas (used by service providers in relation to the Older Americans Act), the Planning and Service Areas are identified. * Dates of Study: 1990-2000 Links: 1980: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/08101 2000: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/04204

Public Use Microdata AreaThis feature layer, utilizing National Geospatial Data Asset (NGDA) data from the U.S. Census Bureau (USCB), displays Public Use Microdata Areas (PUMAs) in the United States. Per USCB, "nesting within states, or equivalent entities, PUMAs cover the entirety of the United States, Puerto Rico, Guam, and the U.S. Virgin Islands. PUMA delineations are subject to population, building block geography, geographic nesting, and contiguity criteria. Each PUMA is identified by a 5-character numeric census code that may contain leading zeros and a descriptive name.”Data currency: This cached Esri federal service is checked weekly for updates from its enterprise federal source (Public Use Microdata Areas) and will support mapping, analysis, data exports and OGC API – Feature access.Data.gov: TIGER/Line Shapefile, 2019, Series Information for the 2010 Census Public Use Microdata Area (PUMA) State-basedGeoplatform: TIGER/Line Shapefile, 2019, Series Information for the 2010 Census Public Use Microdata Area (PUMA) State-basedFor more information, please visit: Public Use Microdata Areas (PUMAs)For feedback please contact: Esri_US_Federal_Data@esri.comNGDA Data SetThis data set is part of the NGDA Governmental Units, and Administrative and Statistical Boundaries Theme Community. Per the Federal Geospatial Data Committee (FGDC), this theme is defined as the "boundaries that delineate geographic areas for uses such as governance and the general provision of services (e.g., states, American Indian reservations, counties, cities, towns, etc.), administration and/or for a specific purpose (e.g., congressional districts, school districts, fire districts, Alaska Native Regional Corporations, etc.), and/or provision of statistical data (census tracts, census blocks, metropolitan and micropolitan statistical areas, etc.). Boundaries for these various types of geographic areas are either defined through a documented legal description or through criteria and guidelines. Other boundaries may include international limits, those of federal land ownership, the extent of administrative regions for various federal agencies, as well as the jurisdictional offshore limits of U.S. sovereignty. Boundaries associated solely with natural resources and/or cultural entities are excluded from this theme and are included in the appropriate subject themes."To access other NGDA content that may interest you: NGDA Content

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: Yes - Vacant units: No - Households: Yes - Individuals: Yes - Group quarters: No

UNIT DESCRIPTIONS: - Households: One of more individuals who normally reside together under the same roof and take food in the same kitchen, including temporary stay aways and excluding temporary visitors.

Universe

Not specified

Kind of data

Census/enumeration data [cen]

Sampling procedure

MICRODATA SOURCE: National Sample Survey Organization, Government of India

SAMPLE DESIGN: Drawn by the NSSO, details not specified

SAMPLE UNIT: Household

SAMPLE FRACTION: .09%

SAMPLE SIZE (person records): 667,848

Mode of data collection

Face-to-face [f2f]

Research instrument

A single form that consists of 7 sections: 1) identification of sample household, 2) household characteristics, 3) demographic particulars and current activity during the preceding week, 4) usual activity and migration, 5) usual activity and migration, 6) follow up questions for working persons, and 7) follow up questions for persons who attended domestic duties.

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 2022, contain data on approximately one percent of the United States population.

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

This dataset, prepared by the Inter-university Consortium for Political and Social Research, comprises 1 percent of the cases in the second release of CENSUS OF POPULATION AND HOUSING, 1990 UNITED STATES: PUBLIC USE MICRODATA SAMPLE: 1-PERCENT SAMPLE (ICPSR 9951). As 1 percent of the 1-Percent Public Use Microdata Sample (PUMS), the file constitutes a 1-in-10,000 sample, and contains all housing and population variables in the original 1-Percent PUMS. Housing variables include area type, state and area of residence, farm/nonfarm status, type of structure, year structure was built, vacancy and boarded-up status, number of rooms and bedrooms, presence or absence of a telephone, presence or absence of complete kitchen and plumbing facilities, type of sewage, water source and heating fuel used, property value, tenure, year moved into house/apartment, type of household/family, type of group quarters, language spoken in household, number of persons, related children, own/adopted children, and stepchildren in the household, number of persons and workers in the family, status of mortgage, second mortgage, and home equity loan, number of vehicles available, household income, sales of agricultural products, payments for rent, mortgage, and property tax, condominium fees, mobile home costs, and costs for electricity, water, heating fuel, and flood/fire/hazard insurance. Person variables cover age, sex, and relationship to householder, educational attainment, school enrollment, race, Hispanic origin, ancestry, language spoken at home, citizenship, place of birth, year of immigration, place of residence in 1985, marital status, number of children ever born, presence and age of own children, military service, mobility and personal care limitations, work limitation status, employment status, employment status of parents, occupation, industry, and class of worker, hours worked last week, weeks worked in 1989, usual hours worked per week, temporary absences from work, place of work, time of departure for work, travel time to work, means of transportation to work, number of occupants in vehicle during ride to work, total earnings, total income, wages, and salary income, farm and nonfarm self-employment income, Social Security income, public assistance income, retirement income, and rent, dividend, and net rental income. (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/ICPSR06150.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

[Metadata] 2010 Census Public Use Microdata Areas (PUMA). Source: US Census Bureau.

The 2020 Census Production Settings Demographic and Housing Characteristics (DHC) Approximate Monte Carlo (AMC) method seed Privacy Protected Microdata File (PPMF0) and PPMF replicates (PPMF1, PPMF2, ..., PPMF50) are a set of microdata files intended for use in estimating the magnitude of error(s) introduced by the 2020 Census Disclosure Avoidance System (DAS) into the 2020 Census Redistricting Data Summary File (P.L. 94-171), the Demographic and Housing Characteristics File, and the Demographic Profile.

The PPMF0 was the source of the publicly released, official 2020 Census data products referenced above, and was created by executing the 2020 DAS TopDown Algorithm (TDA) using the confidential 2020 Census Edited File (CEF) as the initial input; the official location for the PPMF0 is on the United States Census Bureau FTP server, but we also include a copy of it here for convenience. The replicates were then created by executing the 2020 DAS TDA repeatedly with the PPMF0 as its initial input.

Inspired by analogy to the use of bootstrap methods in non-private contexts, U.S. Census Bureau (USCB) researchers explored whether simple calculations based on comparing each PPMFi to the PPMF0 could be used to reliably estimate the scale of errors introduced by the 2020 DAS, and generally found this approach worked well.

The PPMF0 and PPMFi files contained here are provided so that external researchers can estimate properties of DAS-introduced error without privileged access to internal USCB-curated data sets; further information on the estimation methodology can be found in Ashmead et. al 2024.

The 2020 DHC AMC seed PPMF0 and PPMF replicates have been cleared for public dissemination by the USCB Disclosure Review Board (CBDRB-FY22-DSEP-004). The PPMF0 and PPMF replicates contain all Person and Units attributes necessary to produce the 2020 Census Redistricting Data Summary File (P.L. 94-171), the Demographic and Housing Characteristics File, and the Demographic Profile for both the United States and Puerto Rico, and include geographic detail down to the Census Block level. They do not include attributes specific to either the Detailed DHC-A or Detailed DHC-B products; in particular, data on Major Race (e.g., White Alone) is included, but data on Detailed Race (e.g., Cambodian) is not included in the PPMF0 and replicates.

This presentation provides a brief outline of the main sources and uses of labour data and describes issues of access to data.

[Metadata] - 2015 Census Public Use Microdata Areas (PUMA) with population figures from American Community Survey 5-year estimates. Source: U.S. Census Bureau, 2016.

The American Community Survey (ACS) is an ongoing survey that provides data every year ... the 5-year estimates from the ACS are "period" estimates that represent data collected over a period of time, from 2011 to 2015. For more information about the ACS, please visit https://www.census.gov/programs-surveys/acs/.

Analysis unit

Persons, households, and dwellings

UNITS IDENTIFIED: - Dwellings: yes - Vacant Units: Yes - Households: yes - Individuals: yes - Group quarters: yes

UNIT DESCRIPTIONS: - Dwellings: no - Households: Dwelling places with fewer than ten persons unrelated to a household head, excluding institutions and transient quarters. - Group quarters: Institutions, transient quarters, and dwelling places with ten or more persons unrelated to a household head.

Universe

Residents of the 50 states (not the outlying areas).

Kind of data

Population and Housing Census [hh/popcen]

Sampling procedure

MICRODATA SOURCE: U.S. Census Bureau

SAMPLE SIZE (person records): 11343120.

SAMPLE DESIGN: 1-in-20 national random sample drawn by the U.S. Census Bureau

Mode of data collection

Face-to-face [f2f]

Research instrument

The 1980 census employed a single long form questionnaire completed by one-half of housing units in places with a population under 2,500 and one-sixth of other housing units.

Income data has been used extensively by researchers to better understand the economic well-being of Canadians. To meet the needs of these users, Statistics Canada has produced numerous cross-sectional public use microdata files (PUMFs). PUMFs for the Survey of Consumer Finance (SCF) were released until reference year 1997. With the end of the SCF, PUMFs for the Survey of Labour and Income Dynamics (SLID) were produced for reference years 1996 to 2011. The Canadian Income Survey (CIS) was introduced for the 2012 reference year. The CIS is a cross-sectional survey developed to provide information on the income and income sources of Canadians, with their individual and household characteristics. It is a short questionnaire which is asked of a sub-sample of respondents to the Labour Force Survey (LFS), gathering information on labour market activity, school attendance, support payments, child care expenses, inter-household transfers, personal income, food security and characteristics and costs of housing. The CIS content is supplemented with information from the LFS on individual and household characteristics (e.g. age, educational attainment, main job characteristics, and family type) and with tax data for income and income sources (Statistics Canada, 2021). The CIS PUMF is an anonymized microdata file that contains only a subset of variables that are available on the CIS master file. Various techniques have been employed to protect CIS respondents against the risk of disclosure.

This data collection contains a stratified 1-percent sample of households, with separate records for each household, each "sample line" respondent, and each person in the household. These records were encoded from microfilm copies of original handwritten enumeration schedules from the 1950 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). The data collection was constructed from and consists of 20 independently-drawn subsamples stored in 20 discrete physical files. The 1950 Census had both a complete-count and a sample component. Individuals selected for the sample component were asked a set of additional questions. Only households with a sample line person were included in the 1950 Public Use Microdata Sample. The collection also contains records of group quarters members who were also on the Census sample line. Each household record contains variables describing the location and composition of the household. The sample line records contain variables describing demographic characteristics such as nativity, marital status, number of children, veteran status, education, income, and occupation. The person records contain demographic variables such as nativity, marital status, family membership, 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/ICPSR08251.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

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.

This data collection contains basic demographic, social, and economic data for each member of interviewed households during the eight waves of the 1991 Panel of SIPP. Variables include age, sex, race, ethnic origin, marital status, household relationship, education, and veteran status. Limited data are provided on housing unit characteristics such as number of units in structure and tenure. Core questions, repeated at each interview, cover monthly labor force activity, types and amounts of monthly income, and participation in various cash and noncash benefit programs for each month of the survey period. Data for employed persons include number of hours and weeks worked, earnings, and weeks without a job. Nonworkers are classified as unemployed or not in the labor force. In addition to income data associated with labor force activity, nearly 50 other types of income data are provided. Several variables are included for use in identifying longitudinal households and persons in them and to aid in analysis. (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/ICPSR02036.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.

This presentation outlines the data available from the Canadian Centre for Justice Statistics (CCJS), such as police data (including Uniform Crime Reporting), criminal courts data, corrections data, family law data, and victimization data.

These data from the 1990 Census comprise a sample of households with at least one person 60 years and older, plus a sample of persons 60 years and older in group quarters. The data are grouped into housing variables and person variables. Housing variables include area type, state and area of residence, farm/nonfarm status, type of structure, year structure was built, vacancy and boarded-up status, number of rooms and bedrooms, presence or absence of a telephone, presence or absence of complete kitchen and plumbing facilities, type of sewage facilities, type of water source, type of heating fuel used, property value, tenure, year moved into house/apartment, type of household/family, type of group quarters, household language, number of persons in the household, number of persons and workers in the family, status of mortgage, second mortgage, and home equity loan, number of vehicles available, household income, sales of agricultural products, payments for rent, mortgage and property tax, condominium fees, mobile home costs, and cost of electricity, water, heating fuel, and flood/fire/hazard insurance. Person variables cover age, sex, relationship to householder, educational attainment, school enrollment, race, Hispanic origin, ancestry, language spoken at home, citizenship, place of birth, year of immigration, place of residence in 1985, marital status, number of children ever born, military service, mobility and personal care limitation, work limitation status, employment status, occupation, industry, class of worker, hours worked last week, weeks worked in 1989, usual hours worked per week, temporary absence from work, place of work, time of departure for work, travel time to work, means of transportation to work, total earnings, total income, wages and salary income, farm and nonfarm self-employment income, Social Security income, public assistance income, retirement income, and rent, dividends, and net rental income. (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/ICPSR06219.v1. We highly recommend using the ICPSR version as they may make this dataset available in multiple data formats in the future.