The Public Use Microdata Samples (PUMS) contain person- and household-level information from the "long-form" questionnaires distributed to a sample of the population enumerated in the 1980 Census. This data collection, containing 5-percent data, identifies every state, county groups, and most individual counties with 100,000 or more inhabitants (350 in all). In many cases, individual cities or groups of places with 100,000 or more inhabitants are also identified. 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. The person record contains demographic items such as sex, age, marital status, race, Spanish origin, income, occupation, transportation to work, and education.

The Survey of Consumer Finances (SCF) is normally a triennial cross-sectional survey of U.S. families. The survey data include information on families' balance sheets, pensions, income, and demographic characteristics.

The Annual Social and Economic Supplement or March CPS supplement is the primary source of detailed information on income and work experience in the United States. Numerous publications based on this survey are issued each year by the Bureaus of Labor Statistics and Census. A public-use microdata file is available for private researchers, who also produce many academic and policy-related documents based on these data. The Annual Social and Economic Supplement is used to generate the annual Population Profile of the United States, reports on geographical mobility and educational attainment, and detailed analysis of money income and poverty status. The labor force and work experience data from this survey are used to profile the U.S. labor market and to make employment projections. To allow for the same type of in-depth analysis of hispanics, additional hispanic sample units are added to the basic CPS sample in March each year. Additional weighting is also performed so that estimates can be made for households and families, in addition to persons.

This data collection is part of a longitudinal survey designed to provide detailed information on the economic situation of households and persons in the United States. These data examine the distribution of income, wealth, and poverty in American society and gauge the effects of federal and state programs on the well-being of families and individuals. There are three basic elements contained in the survey. The first is a control card that records basic social and demographic characteristics for each person in a household, as well as changes in such characteristics over the course of the interviewing period. The second element is the core portion of the questionnaire, with questions repeated at each interview on labor force activity, types and amounts of income, participation in various cash and noncash benefit programs, attendance in postsecondary schools, private health insurance coverage, public or subsidized rental housing, low-income energy assistance, and school breakfast and lunch participation. The third element consists of topical modules, which are series of supplemental questions asked during selected household visits. A topical module was not created for the first wave of the 1986 panel. The topical module for Wave II is considered a Personal History topical module. It includes data on fertility, marital status, migration, recipiency of transfer payments, employment, work disability, and education and training history. Data on family background and household relationships are also provided. Wave III topical module concerns child care arrangements, child support agreements, support for nonhousehold members, job offers, health status and utilization of health care services, long-term care, and disability status of children. Wave IV topical module includes data on assets and liabilities, real estate property and vehicles, retirement expectations and pension plans. The topical module for Wave V includes questions on educational financing and enrollment. Wave VI topical module covers child care arrangements, child support agreements, support for nonhousehold members, work related expenses, housing costs, and energy usage. Wave VII topical module covers assets and liabilities. (Source: downloaded from ICPSR 7/13/10)

Abstract (en): This is a longitudinal survey designed to provide detailed information on the economic situation of households and persons in the United States. These data examine the distribution of income, wealth, and poverty in American society and gauge the effects of federal and state programs on the well-being of families and individuals. There are three basic elements contained in the survey. The first is a control card that records basic social and demographic characteristics for each person in a household, as well as changes in such characteristics over the course of the interviewing period. The second element is the core portion of the questionnaire, with questions repeated at each interview on labor force activity, types and amounts of income, participation in various cash and noncash benefit programs, attendance in postsecondary schools, private health insurance coverage, public or subsidized rental housing, low-income energy assistance, and school breakfast and lunch participation. The third element consists of topical modules, which are a series of supplemental questions asked during selected household visits. Topical modules include some core data to help link individuals to the core files. Topical module data for the 1992 Panel cover the following topics: Topical Module 1 -- welfare and other aid recipiency and employment, Topical Module 2 -- work disability, education and training, marital status, migration, and fertility histories, Topical Module 3 -- extended measures of well-being, including consumer durables, living conditions, and basic needs, Topical Module 4 -- assets and liabilities, retirement expectations and pension plan coverage, real estate, property, and vehicles, Topical Module 5 -- school enrollment and financing, Topical Module 6 -- work schedules, child care, support for nonhousehold members, functional limitations and disabilities, utilization of health care services, and home-based self-employment and size of firm, Topical Module 7 -- selected financial assets, medical expenses and work disability, real estate, shelter costs, dependent care, and vehicles, Topical Module 8 -- school enrollment and financing, Topical Module 9 -- work schedule, child care, child support agreements, child support, support for nonhousehold members, functional limitations and disability, utilization of health care, functional limitations and disability of children, health status and utilization of health care services, and utilization of health care services for children. Parts 26 and 27 are the Wave 5 and Wave 8 Topical Module Microdata Research Files obtained from the Census Bureau. These two topical module files include data on annual income, retirement accounts and taxes, and school enrollment and financing. These topical module files have not been edited nor imputed, although they have been topcoded or bottomcoded and recoded if necessary by the Census Bureau to avoid disclosure of individual respondents' identities. Resident population of the United States, excluding persons living in institutions and military barracks. A multistage, stratified sampling design was used. One-fourth of the sample households were interviewed each month, and households were reinterviewed at four-month intervals. All persons at least 15 years old who were present as household members at the time of the first interview were included for the entire study, except those who joined the military, were institutionalized for the entire study period, or moved from the United States. Original household members who moved during the study period were followed to their new residences and interviewed there. New persons moving into households of members of the original sample also were included in the survey, but were not followed if they left the household of an original sample person. 2002-11-08 Part 26, Wave 5 Topical Module Microdata Research File, and Part 27, Wave 8 Topical Module Research File, have been added to the collection with corresponding PDF documentation. These topical module files have not been edited nor imputed, although they have been topcoded or bottomcoded and recoded if necessary by the Census Bureau to avoid disclosure of individual respondents' identities.1998-08-24 Part 17, Wave 5 Topical Module Microdata File, and Part 25, Wave 9 Topical Module Microdata File, have been added to the collection with corresponding PDF documentation. Beginning with the 1990 Panel, the file structure of SIPP was changed. The un...

This is a special extract of the 2000 Census 5-Percent Public Use Microdata Samples (PUMS) created by the National Archive of Computerized Data on Aging (NACDA). The file combines the individual 5-percent state files for all 50 states, the District of Columbia, and Puerto Rico as released by the United States Census Bureau into a single analysis file. The file contains information on all households that contain at least one person aged 65 years or more in residence as of the 2000 Census enumeration. The file contains individual records on all persons aged 65 and older living in households as well as individual records for all other members residing in each of these households. Consequently, this file can be used to examine both the characteristics of the elderly in the United States as well as the characteristics of individuals who co-reside with persons aged 65 and older as of the year 2000. All household variables from the household-specific "Household record" of the 2000 PUMS are appended to the end of each individual level record. This file is not a special product of the Census Bureau and is not a resample of the PUMS data specific to the elderly population. While it is comparable to the 1990 release CENSUS OF POPULATION AND HOUSING, 1990: [UNITED STATES]: PUBLIC USE MICRODATA SAMPLE: 3-PERCENT ELDERLY SAMPLE (ICPSR 6219), the sampling procedures and weights for the 2000 file reflect the methodology that applies to the 5-percent PUMS release CENSUS OF POPULATION AND HOUSING, 2000 [UNITED STATES]: PUBLIC USE MICRODATA SAMPLE: 5-PERCENT SAMPLE (ICPSR 13568). 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. 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.

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.

SIPP is a nationally representative longitudinal survey that provides comprehensive data about the income and government program participation of individuals and households in the United States. These microdata contain demographic and social characteristic information for each sample member, as well as detailed data on labor force activity, types and amounts of income, and participation in various cash and noncash benefit programs. Questions about these topics were repeated for nine interviews. Each interview covered a four-month reference period, with the first interview covering February 1991 to May 1991.

Abstract

The Household Income and Expenditure Survey (NHIES) 2009 was a survey collecting data on income, consumption and expenditure patterns of households, in accordance with methodological principles of statistical enquiries, which were linked to demographic and socio-economic characteristics of households. A Household Income and expenditure Survey was the sole source of information on expenditure, consumption and income patterns of households, which was used to calculate poverty and income distribution indicators. It also served as a statistical infrastructure for the compilation of the national basket of goods used to measure changes in price levels. It was also used for updating the national accounts.

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

Geographic coverage

National

Analysis unit

• Individuals
• Households

Universe

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

Kind of data

Sample survey data [ssd]

Sampling procedure

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

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

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

Sampling deviation

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

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

Rural areas: In addition to Caprivi region (where one constituency is generally flooded every year) Ohangwena and Oshana regions were badly affected from an unusual flood situation. Although this situation was generally addressed by interchanging the PSUs between survey rounds still some PSUs were under water close to the end of the survey period.

There were five empty PSUs in the urban areas of Hardap (1), Karas (3) and Omaheke (1) regions. Since these PSUs were found in the low strata within the urban areas of the relevant regions the substituting PSUs were selected from the same strata. The PSUs under water were also five in rural areas of Caprivi (1), Ohangwena (2) and Oshana (2) regions. Wherever possible the substituting PSUs were selected from the same constituency where the original PSU was selected. If not, the selection was carried out from the rural stratum of the particular region.

One sampled PSU in urban area of Khomas region (Windhoek city) had grown so large that it had to be split into 7 PSUs. This was incorporated into the geographical information system (GIS) and one PSU out of the seven was selected for the survey. In one PSU in Erongo region only fourteen households were listed and one in Omusati region listed only eleven households. All these households were interviewed and no additional selection was done to cover for the loss in sample.

Mode of data collection

Face-to-face [f2f]

Research instrument

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

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

Cleaning operations

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

Response rate

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

Data appraisal

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

Abstract

The 2021 Tonga HIES is the new update of this kind, after the 2015/2016, 2009 & 2001 versions. This survey aims to provide indicators on Household Living Standard using monetary aspect (amount of income and expenditure), non-monetary aspect (calory consumed, assets own, imputed rents…) and more social approach (education, health, food security status…). Survey outputs have multiple uses in various domains such as public health (food nutrition analysis), economic development (poverty), system of National Account (consumption aggregates), and they represent a key source of information to populate many National SDGs.

Geographic coverage

National coverage.

Analysis unit

Household and Individual.

Universe

Household Income and Expenditure Survey (HIES) covered all persons who were considered to be usual residents of private dwellings.

Kind of data

Sample survey data [ssd]

Sampling procedure

The Tonga 2021 HIES sample design is based on a two stages sample design, where each stage corresponds to a random selection: - Stage 1: random selection of census blocks (using the probability of selection proportional to size) - Stage 2: random selection of households (from the selected blocks). Within each selected blocks, 12 households were randomly selected (uniform probability) The survey aims to disseminate results at strata level where stratas are defined on geographical combination of provinces and urban rural areas. The sample sizes were calculated at the strata level, with the aim of minimizing the sampling error (and relative sampling error) within each strata.

The sampling frame used was the 2016 population census.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The 2021 Tonga Household Income and Expenditure Survey (HIES) questionnaire was developed in English and Tongan language and it follows the Pacific Standard HIES questionnaire structure. It is administered on CAPI using Survey Solution, and the diary is no longer part of the form. All transactions (food, non food, home production and gifts) are collected through different recall sections during the same visit. The traditional 14 days diary is no longer recommended in the region. This new method of implementing the HIES present some interesting and valuable advantages such as: cost saving, data quality, time reduction for data processing and reporting. Only a sub sample of the selected HIES sample was asked to fill a 2-week diary (in addition to the core recall HIES questionnaire). But only the recall sections are used to compute the HIES outputs and aggregates, this sub sample HIES diary was made for research purposes.

Below is a list of all modules in this questionnaire: -Household ID -Demographic characteristics -Education -Health -Functionality -Communication -Alcohol -Other individual expenses -Labour force -Fisheries & hunting -Handicraft -Dwelling -Assets -Home maintenance -Vehicle -International trips -Domestic trips -Household services -Financial support -Other household expenditure -Ceremonies -Remittances -Food insecurity -Livestock & aquaculture -Agriculture parcel -Agriculture vegetables -Agriculture rootcrops -Agriculture other plants -Agriculture fruits -Legal services.

The survey questionnaire can be found in this documentation.

Cleaning operations

Once the data was collected using Survey Solutions, it was then edited on Stata (version 15).

Response rate

The final response rate including replacement from List B can be found below:

-Tongatapu urban: 95% -Tongatapu rural: 93.3% -Vava'u: 92.5% -Ha'apai: 96.1% -Eua: 99.2% -Ongo Niua: 96.6% -Total Tonga: 94.8%

analyze the current population survey (cps) annual social and economic supplement (asec) with r the annual march cps-asec has been supplying the statistics for the census bureau's report on income, poverty, and health insurance coverage since 1948. wow. the us census bureau and the bureau of labor statistics ( bls) tag-team on this one. until the american community survey (acs) hit the scene in the early aughts (2000s), the current population survey had the largest sample size of all the annual general demographic data sets outside of the decennial census - about two hundred thousand respondents. this provides enough sample to conduct state- and a few large metro area-level analyses. your sample size will vanish if you start investigating subgroups b y state - consider pooling multiple years. county-level is a no-no. despite the american community survey's larger size, the cps-asec contains many more variables related to employment, sources of income, and insurance - and can be trended back to harry truman's presidency. aside from questions specifically asked about an annual experience (like income), many of the questions in this march data set should be t reated as point-in-time statistics. cps-asec generalizes to the united states non-institutional, non-active duty military population. the national bureau of economic research (nber) provides sas, spss, and stata importation scripts to create a rectangular file (rectangular data means only person-level records; household- and family-level information gets attached to each person). to import these files into r, the parse.SAScii function uses nber's sas code to determine how to import the fixed-width file, then RSQLite to put everything into a schnazzy database. you can try reading through the nber march 2012 sas importation code yourself, but it's a bit of a proc freak show. this new github repository contains three scripts: 2005-2012 asec - download all microdata.R down load the fixed-width file containing household, family, and person records import by separating this file into three tables, then merge 'em together at the person-level download the fixed-width file containing the person-level replicate weights merge the rectangular person-level file with the replicate weights, then store it in a sql database create a new variable - one - in the data table 2012 asec - analysis examples.R connect to the sql database created by the 'download all microdata' progr am create the complex sample survey object, using the replicate weights perform a boatload of analysis examples replicate census estimates - 2011.R connect to the sql database created by the 'download all microdata' program create the complex sample survey object, using the replicate weights match the sas output shown in the png file below 2011 asec replicate weight sas output.png statistic and standard error generated from the replicate-weighted example sas script contained in this census-provided person replicate weights usage instructions document. click here to view these three scripts for more detail about the current population survey - annual social and economic supplement (cps-asec), visit: the census bureau's current population survey page the bureau of labor statistics' current population survey page the current population survey's wikipedia article notes: interviews are conducted in march about experiences during the previous year. the file labeled 2012 includes information (income, work experience, health insurance) pertaining to 2011. when you use the current populat ion survey to talk about america, subract a year from the data file name. as of the 2010 file (the interview focusing on america during 2009), the cps-asec contains exciting new medical out-of-pocket spending variables most useful for supplemental (medical spending-adjusted) poverty research. confidential to sas, spss, stata, sudaan users: why are you still rubbing two sticks together after we've invented the butane lighter? time to transition to r. :D

The cross-sectional public-use microdata file for the Survey of Labour and Income Dynamics (SLID) is a collection of income, labour and family variables on persons in Canada and their families. SLID is an annual household survey covering the population of the 10 Canadian provinces with the exception of Indian reserves, residents of institutions and military barracks. The Survey of Labour and Income Dynamics began collecting data for reference year 1993. Initially, SLID was designed to be, first and foremost, a longitudinal survey, with primary focus on labour and income and the relationships between them and family composition. Initially, two versions of SLID public-use microdata files were released: the first cross-sectional set covering reference year 1993 and the second longitudinal covering reference years 1993 and 1994. Both cross-sectional and longitudinal public-use files were released. After the release of the 1993 and 1994 files, the decision was made to extend the objectives of SLID to be the primary source of cross-sectional household income data. The type of income data collected by SLID was identical to that of the former household income survey SCF (Survey of Consumer Finances), with the distinction that SLID respondents had the choice of a traditional income interview and granting permission to Statistics Canada to use their T1 income tax data. For many years, the Survey of Consumer Finances had provided public-use microdata files ( PUMFs ) to meet the needs of cross-sectional household income data users. SCF PUMFs were released up to and including reference year 1997. For the purpose of standard publications, Statistics Canada has made the transition from SCF to SLID between 1995 and 1996. Therefore, SLID cross-sectional PUMFs are being made available beginning with reference year 1996. The SLID files have been designed to be analogous to those produced for the SCF.

SIPP is a nationally representative longitudinal survey that provides comprehensive data about the income and government program participation of individuals and households in the United States. Every interview of the 1996 SIPP Panel included a topical module that asked for detailed information on one of a rotating group of topics. These microdata contain data for these rotating topics. Interviews occurred every four months, with the first interview occurring between April 1996 and July 1996.

Abstract

The 2009-2010 HIES collected information on key topics such as family demography, education, health, employment and consumption. The scope of 2009-2010 HIES was broader than the previous survey, with more indicators and more households surveyed, including questions on living standards and other related subject areas. One key goal was to collect data on income and expenditure, and to enable a rebasing of the Consumer Price Index (CPI). This will assist future policy decisions and analysis to be better based on reliable evidence, such that they can better support improvements in the living standards of Papua New Guinea’s people.

As the 2009-2010 HIES was a multi-topic survey, the following types of information were collected:

1. Household level information on housing characteristics, ownership of consumer durables, non- food consumption, access to various types of public services, and incidence and resolution of different types of disputes.

2. Person-level information on age, sex, education, health, employment status, receipt of remittances, and personal security. This was supplemented by anthropometric data for children aged six years or younger.

3. Personal record of all food and nonfood purchases for 14 consecutive days for all household.

Geographic coverage

National

Analysis unit

• Household
• Individual

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample Design PNG is the largest nation in the South Pacific in both land area and population. It is comprised of around 600 islands, and the interior of the country is mountainous. Administratively, the country is divided into 22 provinces, within four geographic regions: Southern Region comprising of the following provinces: Western, Gulf, Central, Milne Bay, Northern Oro, and the National Capital District Highlands Region comprising of the following provinces: Southern Highlands, Enga, Western Highlands, Chimbu, Eastern Highlands, Hela, and Jiwaka Momase Region comprising of the following provinces: Moroboe, Madang, East Sepik, and West Sepik Island Region comprising of Manus, New Ireland, East New Britain, West New Britain, and the Autonomous Region of Bougainville.

A two-stage stratified cluster sample design was used in order to ensure independent estimates for the "rural", "urban", and "metro" areas of each of these regions. "Metro" denotes the two large urban centres of Port Moresby in Southern region and Lae in the Momase region. All the other urban areas in all regions were included in the "urban" stratum. The sample was thus divided into 10 strata. Sample size in each cluster was set to ensure reliable strata-level representative estimates; in addition, the sample size in the metropolitan areas was set large enough to support the development of a new CPI expenditure basket. In each stratum, households were chosen in two stages. In the first stage, using the sampling frame of the 2000 Census, clusters (or Primary Sampling Units) (PSU) were chosen using probability proportional to size. A full listing of households was done in all chosen clusters and a pre-set number of households were then selected randomly from this list. In the non-metropolitan areas, 18 households were chosen per cluster whereas in the metropolitan areas, 6 households were chosen per PSU. Replacement census units or replacement households in each cluster are used in the case of emergencies or when selected households could not be interviewed because of refusal, absence, illness in the family etc, were also selected using the same methodology.

Mode of data collection

Face-to-face [f2f]

Research instrument

The HIES is a complex application with a hierarchical set of questionnaires. For example, the main questionnaire consists of a household roster and other household information, and there are separate questionnaires for eligible members in the household. The data entry application may then contain two levels-one for the household and one for each eligible member in the household. The set of forms corresponding to the household, make up level one. The set of forms corresponding to each eligible member make up level two. Each case would consist of a level one and a variable number of level occurrences for level two. Most applications consist of a single level.

The survey questionnaires contain the following FORMS: 1) From A: Household Control Form 2) Form B: Household Schedule Form 3) Form C: Personal Schedule 4) Form D: Personal Diary 5) Form E: Personal Notepad

US Census American Community Survey (ACS) 2013, 5-year estimates of the key economic characteristics of Public Use Microdata Areas (PUMA) geographic level in Orange County, California. The data contains 397 fields for the variable groups E01: Employment status (universe: population 16 years and over, table X23, 7 fields); E02: Work status by age of worker (universe: population 16 years and over, table X23, 36 fields); E03: Commuting to work (universe: workers 16 years and over, table X8, 8 fields); E04: Travel time to work (universe: workers 16 years and over who did not work at home, table X8, 14 fields); E05: Number of vehicles available for workers (universe: workers 16 years and over in households, table X8, 8 fields); E06: Median age by means of transportation to work (universe: median age, workers 16 years and over, table X8, 7 fields); E07: Means of transportation to work by race (universe: workers 16 years and over, table X8, 64 fields); E08: Occupation (universe: civilian employed population 16 years and over, table X24, 53 fields); E09: Industry (universe: civilian employed population 16 years and over, table X24, 43 fields); E10: Class of worker (universe: civilian employed population 16 years and over, table X24, 19 fields); E11: Household income and earnings in the past 12 months (universe: total households, table X19, 37 fields); E12: Income and earnings in dollars (universe: inflation-adjusted dollars, tables X19-X20, 31 fields); E13: Family income in dollars (universe: total families, table X19, 17 fields); E14: Health insurance coverage (universe: total families, table X19, 17 fields); E15: Ratio of income to Poverty level (universe: total population for whom Poverty level is determined, table X17, 8 fields); E16: Poverty in population in the past 12 months (universe: total population for whom Poverty level is determined, table X17, 7 fields); E17: Poverty in households in the past 12 months (universe: total households, table X17, 9 fields); E18: Percentage of families and people whose income in the past 12 months is below the poverty level (universe: families, population, table X17, 8 fields), and; X19: Poverty and income deficit (dollars) in the past 12 months for families (universe: families with income below Poverty level in the past 12 months, table X17, 4 fields). The US Census geodemographic data are based on the 2013 TigerLines across multiple geographies. The spatial geographies were merged with ACS data tables. See full documentation at the OCACS project github page (https://github.com/ktalexan/OCACS-Geodemographics).

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.

Content

How does your organization use this dataset? What other NYSERDA or energy-related datasets would you like to see on Open NY? Let us know by emailing OpenNY@nyserda.ny.gov.

The Low- to Moderate-Income (LMI) New York State (NYS) Census Population Analysis dataset is resultant from the LMI market database designed by APPRISE as part of the NYSERDA LMI Market Characterization Study (https://www.nyserda.ny.gov/lmi-tool). All data are derived from the U.S. Census Bureau’s American Community Survey (ACS) 1-year Public Use Microdata Sample (PUMS) files for 2013, 2014, and 2015.

Each row in the LMI dataset is an individual record for a household that responded to the survey and each column is a variable of interest for analyzing the low- to moderate-income population.

The LMI dataset includes: county/county group, households with elderly, households with children, economic development region, income groups, percent of poverty level, low- to moderate-income groups, household type, non-elderly disabled indicator, race/ethnicity, linguistic isolation, housing unit type, owner-renter status, main heating fuel type, home energy payment method, housing vintage, LMI study region, LMI population segment, mortgage indicator, time in home, head of household education level, head of household age, and household weight.

The LMI NYS Census Population Analysis dataset is intended for users who want to explore the underlying data that supports the LMI Analysis Tool. The majority of those interested in LMI statistics and generating custom charts should use the interactive LMI Analysis Tool at https://www.nyserda.ny.gov/lmi-tool. This underlying LMI dataset is intended for users with experience working with survey data files and producing weighted survey estimates using statistical software packages (such as SAS, SPSS, or Stata).

Context

This is a dataset hosted by the State of New York. The state has an open data platform found here and they update their information according the amount of data that is brought in. Explore New York State using Kaggle and all of the data sources available through the State of New York organization page!

• Update Frequency: This dataset is updated annually.

Acknowledgements

This dataset is maintained using Socrata's API and Kaggle's API. Socrata has assisted countless organizations with hosting their open data and has been an integral part of the process of bringing more data to the public.

Cover photo by rawpixel on Unsplash
Unsplash Images are distributed under a unique Unsplash License.

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.

These data are derived from the Census Bureau's American Community Survey Public Use Microdata Sample to quantify the availability of and demand for housing at various levels of income (using Area Median Income-AMI) Additional Information about these data can be found:at this link.

This data collection contains basic demographic, social, and economic data for each member of interviewed households during the eight waves of SURVEY OF INCOME AND PROGRAM PARTICIPATION (SIPP) 1990 PANEL (ICPSR 9722). 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 benefits 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.