Families of tax filers; Single-earner and dual-earner census families by number of children (final T1 Family File; T1FF).

Since 1960, the U.S. Department of Agriculture has provided estimates of expenditures on children from birth through age 17. This technical report presents the most recent estimates for married- couple and single-parent families using data from the 2011-15 Consumer Expenditure Survey (all data presented in 2015 dollars). Data and methods used in calculating annual child-rearing expenses are described. Estimates are provided for married-couple and single-parent families with two children for major components of the budget by age of child, family income, and region of residence. For the overall United States, annual child-rearing expense estimates ranged between $12,350 and $13,900 for a child in a two-child, married-couple family in the middle-income group. Adjustment factors for households with less than or greater than two children are also provided. Expenses vary considerably by household income level, region, and composition, emphasizing that a single estimate may not be applicable to all families. Results of this study may be of use in developing State child support and foster care guidelines, as well as public health and family-centered educational programs. i

A national sample survey dataset covering a wide variety of issues on American family life beginning in 1987-88 and at two subsequent timepoints1992-93 and 2001-03. Topics covered included detailed household composition, family background, adult family transitions, couple interactions, parent-child interactions, education and work, health, economic and psychological well-being, and family attitudes. The first wave interviewed 13,017 respondents, including a main cross-section sample of 9,643 persons aged 19 and over plus an oversample of minorities and households containing single-parent families, step-families, recently married couples, and cohabiting couples. In each household, a randomly selected adult was interviewed. In addition, a shorter, self-administered questionnaire was filled out by the spouse or cohabiting partner of the primary respondent. Interviews averaged about 100 minutes, although interview length varied considerably with the complexity of the respondent''s family history. In 1992-94, an in-person interview was conducted of all surviving members of the original sample, the current spouse or cohabiting partner, and with the baseline spouse or partner in cases where the relationship had ended. Telephone interviews were conducted with focal children who were aged 5-12 and 13-18 at baseline. Short proxy interviews were conducted with a surviving spouse or other relative in cases where the original respondent died or was too ill to interview. A telephone interview was conducted with one randomly selected parent of the main respondent. In 2001-03, telephone interviews were conducted with: Surviving members of the original respondents who had a focal child age 5 or over at baseline; the baseline spouse/partner of these original respondents, whether or not the couple was still together; the focal children who were in the household and aged 5-18 at baselinemost of whom were interviewed at wave 2; and all other original respondents age 45 or older in 2000, and their baseline spouse/partner. Oversamples: Blacks, 9.2%; Mexican-Americans, 2.4%; Puerto Ricans, 0.7% * Dates of Study: 1987-2003 * Study Features: Longitudinal, Minority Oversampling * Sample Size (original respondents): ** Wave I (1987-88): 13,017 ** Wave II (1992-93): 10,007 ** Wave III (2001-03): 8,990 Links: * Wave I (ICPSR): http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06041 * Wave II (ICPSR): http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06906 * Wave III (ICPSR): http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/00171

Families of tax filers; Census families by family type and family composition including before and after-tax median income of the family (final T1 Family File; T1FF).

The Census Bureau determines that a person is living in poverty when his or her total household income compared with the size and composition of the household is below the poverty threshold. The Census Bureau uses the federal government's official definition of poverty to determine the poverty threshold. Beginning in 2000, individuals were presented with the option to select one or more races. In addition, the Census asked individuals to identify their race separately from identifying their Hispanic origin. The Census has published individual tables for the races and ethnicities provided as supplemental information to the main table that does not dissaggregate by race or ethnicity. Race categories include the following - White, Black or African American, American Indian or Alaska Native, Asian, Native Hawaiian or Other Pacific Islander, Some other race, and Two or more races. We are not including specific combinations of two or more races as the counts of these combinations are small. Ethnic categories include - Hispanic or Latino and White Non-Hispanic. This data comes from the American Community Survey (ACS) 5-Year estimates, table B17001. The ACS collects these data from a sample of households on a rolling monthly basis. ACS aggregates samples into one-, three-, or five-year periods. CTdata.org generally carries the five-year datasets, as they are considered to be the most accurate, especially for geographic areas that are the size of a county or smaller.Poverty status determined is the denominator for the poverty rate. It is the population for which poverty status was determined so when poverty is calculated they exclude institutionalized people, people in military group quarters, people in college dormitories, and unrelated individuals under 15 years of age.Below poverty level are households as determined by the thresholds based on the criteria of looking at household size, Below poverty level are households as determined by the thresholds based on the criteria of looking at household size, number of children, and age of householder.number of children, and age of householder.

Abstract copyright UK Data Service and data collection copyright owner.

The Annual Population Survey (APS) household datasets are produced annually and are available from 2004 (Special Licence) and 2006 (End User Licence). They allow production of family and household labour market statistics at local areas and for small sub-groups of the population across the UK. The household data comprise key variables from the Labour Force Survey (LFS) and the APS 'person' datasets. The APS household datasets include all the variables on the LFS and APS person datasets, except for the income variables. They also include key family and household-level derived variables. These variables allow for an analysis of the combined economic activity status of the family or household. In addition, they also include more detailed geographical, industry, occupation, health and age variables.

For further detailed information about methodology, users should consult the Labour Force Survey User Guide, included with the APS documentation. For variable and value labelling and coding frames that are not included either in the data or in the current APS documentation, users are advised to consult the latest versions of the LFS User Guides, which are available from the ONS Labour Force Survey - User Guidance webpages.

Occupation data for 2021 and 2022
The ONS has identified an issue with the collection of some occupational data in 2021 and 2022 data files in a number of their surveys. While they estimate any impacts will be small overall, this will affect the accuracy of the breakdowns of some detailed (four-digit Standard Occupational Classification (SOC)) occupations, and data derived from them. None of ONS' headline statistics, other than those directly sourced from occupational data, are affected and you can continue to rely on their accuracy. Further information can be found in the ONS article published on 11 July 2023: Revision of miscoded occupational data in the ONS Labour Force Survey, UK: January 2021 to September 2022

End User Licence and Secure Access APS data
Users should note that there are two versions of each APS dataset. One is available under the standard End User Licence (EUL) agreement, and the other is a Secure Access version. The EUL version includes Government Office Region geography, banded age, 3-digit SOC and industry sector for main, second and last job. The Secure Access version contains more detailed variables relating to:

• age: single year of age, year and month of birth, age completed full-time education and age obtained highest qualification, age of oldest dependent child and age of youngest dependent child
• family unit and household: including a number of variables concerning the number of dependent children in the family according to their ages, relationship to head of household and relationship to head of family
• nationality and country of origin
• geography: including county, unitary/local authority, place of work, Nomenclature of Territorial Units for Statistics 2 (NUTS2) and NUTS3 regions, and whether lives and works in same local authority district
• health: including main health problem, and current and past health problems
• education and apprenticeship: including numbers and subjects of various qualifications and variables concerning apprenticeships
• industry: including industry, industry class and industry group for main, second and last job, and industry made redundant from
• occupation: including 4-digit Standard Occupational Classification (SOC) for main, second and last job and job made redundant from
• system variables: including week number when interview took place and number of households at address

The Secure Access data have more restrictive access conditions than those made available under the standard EUL. Prospective users will need to gain ONS Accredited Researcher status, complete an extra application form and demonstrate to the data owners exactly why they need access to the additional variables. Users are strongly advised to first obtain the standard EUL version of the data to see if they are sufficient for their research requirements.


Main Topics:
Topics covered include: household composition and relationships, housing tenure, nationality, ethnicity and residential history, employment and training (including government schemes), workplace and location, job hunting, educational background and qualifications.

Abstract copyright UK Data Service and data collection copyright owner.The Health Survey for England (HSE) is a series of surveys designed to monitor trends in the nation's health. It was commissioned by NHS Digital and carried out by the Joint Health Surveys Unit of the National Centre for Social Research and the Department of Epidemiology and Public Health at University College London.The aims of the HSE series are:to provide annual data about the nation’s health;to estimate the proportion of people in England with specified health conditions;to estimate the prevalence of certain risk factors associated with these conditions;to examine differences between population subgroups in their likelihood of having specific conditions or risk factors;to assess the frequency with which particular combinations of risk factors are found, and which groups these combinations most commonly occur;to monitor progress towards selected health targetssince 1995, to measure the height of children at different ages, replacing the National Study of Health and Growth;since 1995, monitor the prevalence of overweight and obesity in children.The survey includes a number of core questions every year but also focuses on different health issues at each wave. Topics are revisited at appropriate intervals in order to monitor change. Further information about the series may be found on the NHS Digital Health Survey for England; health, social care and lifestyles webpage, the NatCen Social Research NatCen Health Survey for England webpage and the University College London Health and Social Surveys Research Group UCL Health Survey for England webpage. Changes to the HSE from 2015:Users should note that from 2015 survey onwards, only the individual data file is available under standard End User Licence (EUL). The household data file is now only included in the Special Licence (SL) version, released from 2015 onwards. In addition, the SL individual file contains all the variables included in the HSE EUL dataset, plus others, including variables removed from the EUL version after the NHS Digital disclosure review. The SL HSE is subject to more restrictive access conditions than the EUL version (see Access information). Users are advised to obtain the EUL version to see if it meets their needs before considering an application for the SL version. The HSE 2007 was designed to provide data at both national and regional level about the population living in private households in England. The sample comprised two components; the core (general population) sample and a boost sample of children aged 2-15. The core sample was designed to be representative of the population living in private households in England and should be used for analyses at the national level. For the HSE core sample, all adults aged 16 years or older at each household were selected for the interview (up to a maximum of ten adults). However, a limit of two was placed on the number of interviews carried out with children aged 0-15. For households with three or more children, interviewers selected two children at random. At boost addresses interviewers screened for households containing at least one child aged 2-15 years. For households which included eligible children, up to two were selected by the interviewer for inclusion in the survey. Interviewing was conducted throughout the year to take account of seasonal differences. For the second edition (April 2010), three new children's Body Mass Index (BMI) variables have been added to the individual data file (bmicat1, bmicat2, bmicat3). The original variables (bmicut1, bmicut2, bmicut3) are unreliable and should not be used. Further information is available in the documentation and on the Information Centre for Health and Social Care Health Survey for England web page. Main Topics: For adult respondents, the HSE 2007 focused on knowledge, attitudes and behaviour on key aspects of lifestyle - smoking, drinking, eating and physical activity. Both adults and children were asked about their views on what constitutes healthy behaviour, their knowledge of government recommendations and the factors that may encourage or discourage healthy behaviour. A secondary focus was the impact of the smokefree legislation. The 2007 survey allowed an initial examination of the effect of the legislation by looking at adults' and children's smoking behaviour and their exposure to other people's smoke, pre and post 1 July 2007 (the date the legislation came into effect). As well as questions being asked, saliva samples were taken and tested for cotinine, an indicator of recent nicotine exposure. Questionnaire interviews were followed by a nurse visit, both using computer assisted interviewing (CAPI) and self completion booklets. Parents of children aged 0-12 years were asked about their children, with the child interview including questions on physical activity and fruit and vegetable consumption. Children aged 13-15 were interviewed themselves. Standard Measures: Strengths and Difficulties Questionnaire (SDQ) Multi-stage stratified random sample Face-to-face interview Self-completion Clinical measurements Physical measurements CAPI 2007 ACCIDENTS ACUPUNCTURE AGE ALCOHOL USE ALCOHOLIC DRINKS ANTHROPOMETRIC DATA ANXIETY ATTITUDES BACTERIAL AND VIRUS... BEDROOMS CARDIOVASCULAR DISE... CHILD BEHAVIOUR CHILD CARE CHILD DEVELOPMENT CHILD NUTRITION CHILDREN CHRONIC ILLNESS CLINICAL TESTS AND ... CLUBS COHABITATION CONCENTRATION CONFECTIONERY CONFUSION COOKING CULTURAL IDENTITY CYCLING DAIRY PRODUCTS DAY CARE DEBILITATIVE ILLNESS DENTAL CARE DIABETES DIET AND EXERCISE DIGESTIVE SYSTEM DI... ECONOMIC ACTIVITY EDIBLE FATS EDUCATIONAL BACKGROUND EMOTIONAL DEVELOPMENT EMOTIONAL STATES EMPLOYEES EMPLOYMENT EMPLOYMENT HISTORY ENDOCRINE DISORDERS ETHNIC GROUPS EXERCISE PHYSICAL A... England FAMILIES FAMILY BENEFITS FATHERS FOOD FRIENDS FRUIT FURNISHED ACCOMMODA... GARDENING GENDER General health and ... HAPPINESS HEADS OF HOUSEHOLD HEALTH HEALTH ACT 2006 HEALTH ADVICE HEALTH CONSULTATIONS HEALTH PROFESSIONALS HEALTH SERVICES HEARING IMPAIRMENTS HEART DISEASES HEIGHT PHYSIOLOGY HOSPITAL OUTPATIENT... HOSPITALIZATION HOURS OF WORK HOUSEHOLD INCOME HOUSEHOLDS HOUSEWORK HOUSING BENEFITS HOUSING TENURE HUMAN SETTLEMENT Health care service... ILL HEALTH INCOME INDUSTRIES INFANTS INJURIES INVESTMENT RETURN JOB HUNTING LANDLORDS LEGUMES LOCAL COMMUNITY FAC... MARITAL STATUS MEAT MEDICAL CARE MEDICAL DIETS MEDICAL PRESCRIPTIONS MEDICINAL DRUGS MEDITATION MEMBERSHIP MEMORY DISORDERS MENTAL DISORDERS MENTAL HEALTH MILK MOTHERS MOTOR PROCESSES MOTOR VEHICLES MUSCULOSKELETAL SYSTEM NATIONAL BACKGROUND NERVOUS SYSTEM DISE... NURSES OCCUPATIONAL PENSIONS OCCUPATIONAL QUALIF... ORGANIZATIONS ORTHOPAEDICS OSTEOPATHY PAIN PASSIVE SMOKING PHYSICAL ACTIVITIES PHYSICAL MOBILITY PHYSICIANS PREGNANCY PREMATURE BIRTHS PRESERVED FOODS PRIVATE PERSONAL PE... QUALIFICATIONS RENTED ACCOMMODATION RESIDENTIAL MOBILITY RESPIRATORY TRACT D... SALT SAVOURY SNACKS SELF EMPLOYED SELF ESTEEM SKIN DISEASES SMOKING SMOKING CESSATION SMOKING RESTRICTIONS SOCIAL CLASS SOCIAL NETWORKS SOCIAL PARTICIPATION SOCIAL SECURITY BEN... SOCIAL SUPPORT SOCIO ECONOMIC STATUS SPORT STATE RETIREMENT PE... STRESS PSYCHOLOGICAL SUPERVISORY STATUS SURGERY TAX RELIEF TIED HOUSING TOBACCO UNDERAGE DRINKING UNFURNISHED ACCOMMO... VASCULAR DISEASES VEGETABLES VISION IMPAIRMENTS VITAMINS WAGES WALKING WEIGHT PHYSIOLOGY YOUTH YOUTH CLUBS

For more information, please visit HART.ubc.ca. Housing Assessment Resource Tools (HART) This dataset includes 18 tables which draw upon data from the 2006 Census of Canada. The tables are a custom order and contains data pertaining to core housing need and characteristics of households. 16 of the tables each cover a different geography in Canada: one for Canada as a whole, one for all Canadian census divisions (CD), and 14 for all census subdivisions (CSD) across Canada. The last two tables contains the median income for all geographies. Statistics Canada used these median incomes as the "area median household income (AMHI)," from which they derived some of the variables within the Shelter Costs/Household Income dimension. Included alongside the data tables is a guide to HART's housing need assessment methodology. This guide is intended to support independent use of HART's custom data both to allow for transparent verification of our analysis, as well as supporting efforts to utilize the data for analysis beyond what HART did. There are many variables in the data order that we did not use that may be of value for others. The dataset is in Beyond 20/20 (.ivt) format. The Beyond 20/20 browser is required in order to open it. This software can be freely downloaded from the Statistics Canada website: https://www.statcan.gc.ca/eng/public/beyond20-20 (Windows only). For information on how to use Beyond 20/20, please see: http://odesi2.scholarsportal.info/documentation/Beyond2020/beyond20-quickstart.pdf https://wiki.ubc.ca/Library:Beyond_20/20_Guide Custom order from Statistics Canada includes the following dimensions and variables: Geography: - Country of Canada, all CDs & Country as a whole - All 10 Provinces (Newfoundland, Prince Edward Island (PEI), Nova Scotia, New Brunswick, Quebec, Ontario, Manitoba, Saskatchewan, Alberta, and British Columbia), all CSDs & each Province as a whole - All 3 Territories (Nunavut, Northwest Territories, Yukon), all CSDs & each Territory as a whole The global non-response rate (GNR) is an important measure of census data quality. It combines total non-response (households) and partial non-response (questions). A lower GNR indicates a lower risk of non-response bias and, as a result, a lower risk of inaccuracy. The counts and estimates for geographic areas with a GNR equal to or greater than 50% are not published in the standard products. The counts and estimates for these areas have a high risk of non-response bias, and in most cases, should not be released. Universe: Full Universe: Private Households in Non-farm Non-band Off-reserve Occupied Private Dwellings with Income Greater than zero. Households examined for Core Housing Need: Private, non-farm, non-reserve, owner- or renter-households with incomes greater than zero and shelter-cost-to-income ratios less than 100% are assessed for 'Core Housing Need.' Non-family Households with at least one household maintainer aged 15 to 29 attending school are considered not to be in Core Housing Need, regardless of their housing circumstances. Variables: Housing indicators in Core Housing Universe (3) 1. Total - Private Households by core housing need status 2. Households examined for core housing need 3. Households in core housing need Tenure Including Presence of Mortgage and Subsidized Housing; Household size (11) 1. Total - Household tenure and mortgage status 2. Owners 3. With mortgage 4. Without mortgage 5. Renters 6. Total - Household size 7. 1 person 8. 2 persons 9. 3 persons 10. 4 persons 11. 5 or more persons Shelter costs groups/statistics (20) 1. Total – Private households by household income proportion to AMHI_1 2. Households with income 20% or under of area median household income (AMHI) 3. Households with income 21% to 50% of AMHI 4. Households with income 51% to 80% of AMHI 5. Households with income 81% to 120% of AMHI 6. Households with income 121% or over of AMHI 7. Total – Private households by household income proportion to AMHI_2 8. Households with income 30% and under of AMHI 9. Households with income 31% to 60% of AMHI 10. Households with income 61% or more of AMHI 11. Total – Private households by shelter cost proportion to AMHI_1 12. Households with shelter cost 0.5% and under of AMHI 13. Households with shelter cost 0.6% to 1.25% of AMHI 14. Households with shelter cost 1.26% to 2% of AMHI 15. Households with shelter cost 2.1% to 3% of AMHI 16. Households with shelter cost 3.1% or over of AMHI 17. Total – Private households by shelter cost proportion to AMHI_2 18. Households with shelter cost 0.75% or under of AMHI 19. Households with shelter cost 0.76% to 1.5% of AMHI 20. Households with shelter cost greater than or equal to 1.6% of AMHI Selected characteristics of the households (47) 1.Total - Household type 2. Census-family households 3. One-census-family households 4. Couple-family households 5. With children 6. Without children 7. Lone-parent-family households 8. Multiple-family households...

This dataset includes two tables which were custom ordered from Statistics Canada. One table includes variables on housing characteristics (condominium status, total number of bedrooms, structural type and tenure), and households (household size, household type, age of primary household maintainer). One table includes information on shelter cost to income ratio and total shelter cost by tenure, household type, and household income. The dataset is in Beyond 20/20 (.ivt) format. The Beyond 20/20 browser is required in order to open it. This software can be freely downloaded from the Statistics Canada website: https://www.statcan.gc.ca/eng/public/beyond20-20 (Windows only). For information on how to use Beyond 20/20, please see: http://odesi2.scholarsportal.info/documentation/Beyond2020/beyond20-quickstart.pdf https://wiki.ubc.ca/Library:Beyond_20/20_Guide Custom order from Statistics Canada TABLE 3 includes the following dimensions and variables: Geography: Toronto CMA & Vancouver CMA to the census tract level Age of Household maintainer: Age groups are divided into 9 year intervals starting at age 15 and ending at category 75 and above Condominium status: Condominium, not a condominium Tenure: Owner, renter Household size: From one person up to 5 or more persons Structural type: -Single detached house -Apartment with 5 or more stories -Other dwelling -Semi-detached house -Row house -Apartment, detached duplex -Apartment, building with fewer than 5 stories -Other single attached house -Movable dwelling Total number of bedrooms: From no bedrooms to 4 or more bedrooms Household type: -Census-family households -With children -Without children -Multiple census-family households -Non-census family household TABLE 4 includes the following dimensions and variables: Geography: Toronto CMA, Vancouver CMA Total Shelter cost: under $500 to over $3000 in intervals ranging from $250 to $500 Tenure: Owner (with and without mortgage), renter Household type: -Census-family households -One-family households -Couple family households -With children -Without children -Lone-parent households -Multiple census-family households -Non-census-family households -One person households -Two person households Shelter cost to income ratio: less than 15%, 15-30%, 30-50%, 50% or more, not applicable Household income: in intervals of 10,000 up to the category of $100,000 or more Original file name: EO2969 - Table 3 Tenure and dwelling_Toronto and Vancouver 2006.ivt EO2969 - Table 4 (Part 1) Cost income household_Toronto and Vancouver_2006.ivt

MIPI-HHoT is a dataset of minimum income adequacy indicators, produced using the Hypothetical Household Tool (HHoT) plugin of the European microsimulation model, EUROMOD. Its purpose is to provide internationally comparable indicators of minimum incomes for four model households (Single, Couple, Couple with two children and Lone parent with two children) in three income situations (Minimum wage-earning household, Non-working social assistance-receiving household and Old-age household without access to contributory pensions). In doing so it continues the work of the CSB-Minimum Income Protection Indicators database (CSB-MIPI) of the University of Antwerp's Herman Deleeck Centre for Social Policy (CSB), and contributes to the wider knowledge of income protection, social assistance and anti-poverty measures in Europe.

The full data set is presented in Marchal, Siöland & Goedemé (2018), forthcoming working paper from the CSB. This initial release contains household incomes of included households and income situations for the period 2009-2017.

Long-term longitudinal dataset with information on generational links and socioeconomic and health conditions of individuals over time. The central foci of the data are economic and demographic, with substantial detail on income sources and amounts, wealth, savings, employment, pensions, family composition changes, childbirth and marriage histories, and residential location. Over the life of the PSID, the NIA has funded supplements on wealth, health, parental health and long term care, housing, and the financial impact of illness, thus also making it possible to model retirement and residential mobility. Starting in 1999, much greater detail on specific health conditions and health care expenses is included for respondent and spouse. Other enhancements have included a question series about emotional distress (2001); the two stem questions from the Composite International Diagnostic Interview to assess symptoms of major depression (2003); a supplement on philanthropic giving and volunteering (2001-03); a question series on Internet and computer use (2003); linkage to the National Death Index with cause of death information for more than 4,000 individuals through the 1997 wave, updated for each subsequent wave; social and family history variables and GIS-linked environmental data; basic data on pension plans; event history calendar methodology to facilitate recall of employment spells (2001). The reporting unit is the family: single person living alone or sharing a household with other non-relatives; group of people related by blood, marriage, or adoption; unmarried couple living together in what appears to be a fairly permanent arrangement. Interviews were conducted annually from 1968 through 1997; biennial interviewing began in 1999. There is an oversample of Blacks (30%). Waves 1990 through 1995 included a 20% Hispanic oversample; within the Hispanic oversample, Cubans and Puerto Ricans were oversampled relative to Mexicans. All data from 1994 through 2001 are available as public release files; prior waves can be obtained in archive versions. The special files with weights for families are also available. Restricted files include the Geocode Match File with information for 1968 through 2001, the 1968-2001 Death File, and the 1991 Medicare Claims File. * Dates of Study: 1968-2003 * Study Features: Longitudinal, Minority Oversampling * Sample Size: 65,000+ Links * ICPSR Series: http://www.icpsr.umich.edu/icpsrweb/ICPSR/series/00131 * ICPSR 1968-1999: Annual Core Data: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/07439 * ICPSR 1968-1999: Supplemental Files: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/03202 * ICPSR 1989-1990: Latino Sample: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/03203

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

BackgroundDespite the significant public health burden of maternal mental health disorders in sub-Saharan Africa (SSA), limited data are available on their effects on early childhood development (ECD), nutritional status, and child health in the region.AimsThis study investigated the association between maternal mental health and ECD, nutritional status, and common childhood illnesses, while controlling for biological, social, financial, and health-related factors and/or confounders.MethodAs part of the Innovative Partnership for Universal and Sustainable Healthcare (i-PUSH) program evaluation study, initiated in November 2019, a cohort of low-income rural families, including pregnant women or women of childbearing age with children under five, was recruited for this study. A total of 24 villages were randomly selected from a list of villages near two health facilities. Following a census to identify eligible households, 10 households per village were randomly selected. Data collection included maternal mental health, assessed using Centre for Epidemiological Studies Depression (CES-D) scale, ECD, nutritional status (anthropometric measurements), and common childhood illnesses, their symptoms, and healthcare utilization. This study presents a cross-sectional analysis of the data drawn from endline survey of 299 target mothers and 315 children.ResultsThe majority of the mothers were aged between 25 and 34 years. The mean age of children was 3.2 years, with 53% being male. The overall maternal mental health score, as measured by the CES-D scale, was 28. Children of mothers with higher CES-D scores exhibited poorer ECD domains, lower nutritional status indicators, and increased incidence of ill-health in the previous two weeks, in both unadjusted and adjusted analyses. Individual, parental, and household factors—including maternal age, household wealth index, and decision-making regarding child healthcare—were significantly associated with children’s development, nutrition status, and health outcomes.ConclusionChildren of mothers with low mental health scores demonstrated suboptimal developmental outcomes, nutritional status, and overall well-being, particularly for those from impoverished households. These findings suggest that improving the socioeconomic conditions of low-income households is essential for promoting children’s development, nutritional status, and well-being. Longitudinal studies are needed to further investigate the impact of maternal mental health on child development, nutrition, and health outcomes, considering additional factors across the maternal, newborn, and child health continuum.Trial registration for the parent and nested studyClinicalTrials.gov (NCT04068571), AEA Registry (AEARCTR-0006089) and PACTR (PACTR202204635504887).

To download the 2004 dataset go to: http://sds.ukzn.ac.za/default.php?11,0,0,0,0 The third round of the KwaZulu-Natal Income Dynamics Study (KIDS) dataset contains information on the socio-economic circumstances of households. This third round conducted in 2004 re-interviewed households contacted in 1993 and 1998. It is based on the Project for Statistics on Living Standards and Development (PSLSD). The 2004 questionnaire is based on the original 1993. It includes the collection of anthropometric data from children aged 6 years or less. New modules include the administration of a literacy test to children aged 7-9 years, a module on employment histories, and a module on the Child Support Grant (CSG). Also, several existing modules have been expanded or amended, including the information on deaths in the household, the module on health and caring, that on social capital and the information collected on children. The third round of the study interviewed 867 households containing core members from 760 of the households contacted in 1993. For 180 of these 760 ‘dynasties’, information was also collected on next generation households that had split off from them. Between 1993 and 2004, attrition rates appear to be within acceptable limits, although young adults and smaller, and perhaps poorer, households are underrepresented. The age distribution of the resident members of th e core and next generation households matches that of the African and Indian population of KwaZulu-Natal reported by Census 2001. The mortality results suggest that the proportion of people at ages 20-44 dying between the second and third rounds was nearly three times the proportion dying between the first two rounds. The pattern of income distribution is one of increasing poverty and inequality since 1993, although the partial reversal of these trends in the post-1998 period is hopeful as are signs of relative prosperity among those that established independent next-generation households. In addition, access to services has generally improved. The 2004 data collection was administered by researchers at the International Food Policy Research Institute (IFPRI), the University of KwaZulu-Natal (UKZN), the University of Wisconsin-Madison. The funding for the project was provided by the UK Department for International Development (DFID) through Department of Social Development (DSD), the National Research Foundation, the Norwegian Research Council, USAID, and the Mellon Foundation. The South Africa: KwaZulu-Natal I ncome Dynamics Study (KIDS), 2004 was a collaborative project of the International Food Policy Research Institute (IFPRI), the University of KwaZulu-Natal (UKZN), the University of Wisconsin-Madison, the London School of Hygiene and Tropical Medicine (LSHTM), and the Norwegian Institute of Urban and Regional Studies (NIBR).

This dataset includes two tables which were custom ordered from Statistics Canada. One table includes information on shelter cost to income ratio and total shelter cost by tenure, household type, and household income. The other table includes variables on housing characteristics (total number of bedrooms, structural type, and tenure), and households (household size, household type, and age of primary household maintainer). The dataset is in Beyond 20/20 (.ivt) format. The Beyond 20/20 browser is required in order to open it. This software can be freely downloaded from the Statistics Canada website: https://www.statcan.gc.ca/eng/public/beyond20-20 (Windows only). For information on how to use Beyond 20/20, please see: http://odesi2.scholarsportal.info/documentation/Beyond2020/beyond20-quickstart.pdf https://wiki.ubc.ca/Library:Beyond_20/20_Guide Custom Order from Statistics Canada TABLE 1 includes the following dimensions and variables: Geography: Toronto CMA & Vancouver CMA to the census tract level Tenure: Owner (with and without mortgage), renter, subsidized, not subsidized Shelter Cost to Income Ratio: less than 15%, 15-30%, 30-50%, 50% or more, not applicable Household Type: -Census-family households -One-census family households without additional persons -One couple census family without other persons in the household -With children -Without children -One lone-parent census family without other persons in the household -One-census-family households with additional persons -One couple census family household with additional persons -One lone-parent census family with additional persons in the household -With children -Without children -One lone-parent census family with other persons in the household -Multiple census-family households -Non-census family household -One person households -Two or more person non-census households Total Shelter Cost: under $500 to over $3000 in intervals of $250 and $500 Household Income: in intervals of $10,000 up to $100,000 or more TABLE 2 includes the following dimensions and variables: Geography: Toronto CMA & Vancouver CMA to the census tract level Total number of bedrooms: No bedrooms to 4 or more bedrooms Tenure: Owner, renter Structural type: -Single detached house -Apartment with 5 or more stories -Other attached dwelling -Semi-detached house -Row house -Apartment or flat in a duplex -Apartment, building with fewer than 5 stories -Other single attached house -Movable dwelling Age of Household Maintainer: Begins at 15 and continues in 9 year intervals until 75 and over. Condominium Status: Condominium, not a condominium Household Type: -Census-family households -With children -Without children -Multiple census-family households -Non-census family household Household Size: One person up to 5 or more persons Original file names: EO2969 - Table 1 (Part 1) Cost income household _Toronto and Vancouver 2016.ivt EO2969 - Table 2 Tenure and dwelling_Toronto and Vancouver 2016.ivt

Abstract

A strong evidence base is needed to understand the socioeconomic implications of the COVID-19 pandemic for the Solomon Islands. High Frequency Phone Surveys (HFPS) are designed to collect data on the evolving implications of the COVID-19 pandemic over several years. This data is the second of at least five planned rounds of mobile surveys. The first round of survey was already completed in late June 2020. Round 2 interviewed 2,882 households across the country in December 2020 and early January 2021, on topics including awareness of COVID-19, employment, and income, coping strategies, and public trust and security.

Geographic coverage

Urban and rural areas of Solomon Islands.

Analysis unit

Households, Individuals

Universe

Respondents aged 18 and over.

Kind of data

Sample survey data [ssd]

Sampling procedure

As the objective of the survey was to measure changes as the pandemic progresses, Round Two data collection sought to re-contact all 2,665 households contacted in Round One. The protocols for re-contact were a maximum of 3 attempts per caller shift, spaced between 1.5 and 2.5 hours apart depending on whether the phone was busy or there was no answer, and 15 attempts in total. Of the Round One households, 1,048 were successfully re-contacted. In Round One, Honiara was over-represented in the World Bank HFPS (constituting 32.8 percent of the survey sample). All other provinces were deemed under-represented, with the largest differences being for Makira-Ulawa, which represented 3.9 percent of the survey sample compared to 7.2 percent of the population in the census, and Guadalcanal, which represented 14.3 percent of the survey sample compared to 21.4 percent of the population in the census. Urban areas constituted almost half (49.2 percent) of the survey sample, compared to a quarter (25.6 percent) of the census. To reach the target sample size of at least 2500 households, 1,833 replacement households were added to the World Bank survey. The target geographic distribution for the survey was based on the population distribution across provinces from the preliminary 2019 census results. According to the population census, Honiara constituted almost one quarter (18.0 percent) of the total population. Compensating factors for these differences were developed and included in the re-weighting calculations.

The majority of these were replaced through Random Digit Dialing, but the project did attempt to leverage contact information from ward-level focal points for the Rural Development Project (RDP) in provinces underrepresented in Round One. Of the 145 RDP contacts provided to the call center, 41 were reached, who in turn provided 379 numbers which were attempted as part of regular call schedule. Overall, the sample size achieved for the second round of the HFPS was 2,882 households.

Due to the limited sample sizes outside of Honiara, most results are disaggregated into only three geographic regions: Honiara, other urban areas, and rural areas. For more information on sampling, please refer to the report provided in the External Resources.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Cleaning operations

At the end of data collection, the dataset was cleaned by the World Bank team. This included formatting, and correcting results based on monitoring issues, enumerator feedback and survey changes. Data was edited using STATA. The data is presented in two data sets: household data set and individual data set. The total number of observations in the household data set is 2,882 and is 4,279 in the individual data set. The individual data set contains employment information for some household members. The household data set contains information about public services, income, coping strategies, and awareness of COVID-19.

Response rate

Re-contact was attempted with all households from the World Bank Round Two HFPS sample, by phone, for follow up interviews for the UNICEF SIAS. Up to 5 re-contact call attempts were made per house, resulting in 1530 households being interviewed successfully including households without children. Of these households, a total of 1197 had at least one child (aged 0 to 14 years of age). While the goal was to recontact at least 1500 households with at least one child in the household, this was not possible due to lower than hoped for response rate. Given the time elapsed between the Round Two HFPS and the UNICEF SIAS, the response rate may have suffered because of some households changing phone numbers.

Response rate for returning households: 39.32%

In the financial year 2021, a majority of Indian households fell under the aspirers category, earning between 125,000 and 500,000 Indian rupees a year. On the other hand, about three percent of households that same year, accounted for the rich, earning over 3 million rupees annually. The middle class more than doubled that year compared to 14 percent in financial year 2005.

Middle-class income group and the COVID-19 pandemic

During the COVID-19 pandemic specifically during the lockdown in March 2020, loss of incomes hit the entire household income spectrum. However, research showed the severest affected groups were the upper middle- and middle-class income brackets. In addition, unemployment rates were rampant nationwide that further lead to a dismally low GDP. Despite job recoveries over the last few months, improvement in incomes were insignificant.

Economic inequality

While India maybe one of the fastest growing economies in the world, it is also one of the most vulnerable and severely afflicted economies in terms of economic inequality. The vast discrepancy between the rich and poor has been prominent since the last three decades. The rich continue to grow richer at a faster pace while the impoverished struggle more than ever before to earn a minimum wage. The widening gaps in the economic structure affect women and children the most. This is a call for reinforcement in in the country’s social structure that emphasizes access to quality education and universal healthcare services.

Abstract

The World Bank and UNHCR in collaboration with the Kenya National Bureau of Statistics and the University of California, Berkeley are conducting the Kenya COVID-19 Rapid Response Phone Survey to track the socioeconomic impacts of the COVID-19 pandemic, the recovery from it as well as other shocks to provide timely data to inform a targeted response. This dataset contains information from eight waves of the COVID-19 RRPS, which is part of a panel survey that targets refugee household and started in May 2020. The same households were interviewed every two months for five survey rounds, in the first year of data collection, and every four months thereafter, with interviews conducted using Computer Assisted Telephone Interviewing (CATI) techniques. The sample aims to be representative of the refugee and stateless population in Kenya. It comprises five strata: Kakuma refugee camp, Kalobeyei settlement, Dadaab refugee camp, urban refugees, and Shona stateless. Waves 1-7 of this survey include information on household background, service access, employment, food security, income loss, transfers, health, and COVID-19 knowledge. Wave 8 focused on how households were exposed to shocks, in particular adverse weather shocks and the increase in the price of food and fuel, but also included parts of the previous modules on household background, service access, employment, food security, income loss, and subjective wellbeing. The data is uploaded in three files. The first is the hh file, which contains household level information. The 'hhid', uniquely identifies all household. The second is the adult level file, which contains data at the level of adult household members. Each adult in a household is uniquely identified by the 'adult_id'. The third file is the child level file, available only for waves 3-7, which contains information for every child in the household. Each child in a household is uniquely identified by the 'child_id'. The duration of data collection and sample size for each completed wave was: Wave 1: May 14 to July 7, 2020; 1,328 refugee households Wave 2: July 16 to September 18, 2020; 1,699 refugee households Wave 3: September 28 to December 2, 2020; 1,487 refugee households Wave 4: January 15 to March 25, 2021; 1,376 refugee households Wave 5: March 29 to June 13, 2021; 1,562 refugee households Wave 6: July 14 to November 3, 2021; 1,407 refugee households Wave 7: November 15, 2021, to March 31, 2022; 1,281 refugee households Wave 8: May 31 to July 8, 2022: 1,355 refugee households The same questionnaire is also administered to nationals in Kenya, with the data available in the WB microdata library: https://microdata.worldbank.org/index.php/catalog/3774

Geographic coverage

National coverage covering rural and urban areas

Analysis unit

Individual and Household

Universe

All persons of concern for UNHCR

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample aims to be representative of the refugee and stateless population in Kenya. It comprises five strata: Kakuma refugee camp, Kalobeyei settlement, Dadaab refugee camp, urban refugees, and Shona stateless, where sampling approaches differ across strata. For refugees in Kakuma and Kalobeyei, as well as for stateless people, recently conducted Socioeconomic Surveys (SES), were used as sampling frames. For the refugee population living in urban areas and the Dadaab camp, no such household survey data existed, and sampling frames were based on UNHCR's registration records (proGres), which include phone numbers. For Kakuma, Kalobeyei, Dadaab and urban refugees, a two-step sampling process was used. First, 1,000 individuals from each stratum were selected from the corresponding sampling frames. Each of these individuals received a text message to confirm that the registered phone was still active. In the second stage, implicitly stratifying by sex and age, the verified phone number lists were used to select the sample. Until wave 7 sampled households that were not reached in earlier waves were also contacted along with households that were interviewed before. In wave 8 only households that had previously participated in the survey were contacted for interview. The “wave” variable represents in which wave the households were interviewed in. For the stateless population, all the participants of the Shona socioeconomic survey (n=400) were included in the RRPS, because of limited sample size. The sampling frames for the refugee and Shona stateless communities are thus representative of households with active phone numbers registered with UNHCR.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

The questionnaire included 12 sections Section 1: Introduction Section 2: Household background Section 3: Travel patterns and interactions Section 4: Employment Section 5: Food security Section 6: Income Loss Section 7: Transfers Section 8: Subjective welfare (50% of sample) Section 9: Health Section 10: COVID Knowledge Section 11: Household and Social Relations (50% of sample) Section 12: Conclusion

Cleaning operations

Variable names were kept constant across survey waves. For questions that remained exactly the same across survey waves, data points for all waves can be found under one variable name. For questions where the phrasing changed (even in a minimal way) across waves, variable names were also changed to reflect the change in phrasing. Extended missing values are used to indicate why a value is missing for all variables. The following extended missing values are used in the dataset: · .a for 'Don't know' · .b for 'Refused to respond' · .c for 'Outliers set to missing' · .d for 'Inconsistency set to missing' (used for employment data as explained below) · .e for 'Field Skipped' (where an error in the survey tool caused the question to be missed) · .z for 'Not administered' (as the variable was not relevant to the observation) More detailed data on children was collected between waves 3 and 7, compared to waves 1, 2 and 8. In waves 1 and 2, data on children, e.g. on their learning activities, was collected for all children in a household with one question. Therefore, variables related to children are part of the 'hh' data for waves 1 and 2. Between waves 3 and 7, questions on children in the household were asked for specific children. Some questions covered all children, while others were only administered to one randomly selected child in the household. This approach allows to disaggregate data at the level of the child household members, and the data can be found in the 'child' data set. The household level weights can be used for analysis of the children's data. In wave 8, detailed information on children was dropped, as the questionnaire focused on other topics. The education status of household members, except for the respondent, was imputed for rounds 1 and 2. For rounds 1 and 2, only the education status of the respondent was elicited, while for later rounds the education status for each household member was asked. In order to evaluate outcomes by the household member's education status, information on education was imputed for waves 1 and 2, using the information provided for all household members in waves 3, 4, and 5. This resulted in additional information on the education status for household members in round 1 and 2, which was not yet available for earlier versions of this data. Some questions are not asked repeatedly across waves such that their values were imputed. For some questions, answers are not possible or unlikely to change within two months between survey waves such that households were not asked about them in all waves. The questions on assets owned before March 2020 were only asked to households when they are interviewed for the first time. The questions on the dwelling's wall and floor material as well as the household's connection to the power grid was not asked for all households in wave 2 and 3, where only new households and those who moved were covered by these questions. Questions on the main source of electricity in the households and types of assets owned were not asked in wave 8. The missing values those variables have when they were not asked, are imputed from the answers given in earlier waves. Improved quality insurance algorithms lead to minor revisions to wave 1 to 5 data. Based on additional data checks, the team has made minor refinements to wave 1 to 5 data. The identification of the household members that were the respondent or the household head was refined in the rare cases where it was not possible to interview the same respondent as in previous waves for a given household such that another adult was interviewed. For this reason, for about 2 percent of observations the household head status was assigned to an incorrect household member, which was corrected. For <1 percent of households the respondent did not appear in adult level dataset. For about 1 percent of observations in wave 5 the respondent appeared twice in the adult level dataset. Data from questions on COVID-19 vaccinations from wave 7 was dropped from the dataset. Due to significantly higher self-reported vaccination rates compared to official administrative records, data on vaccinations was deemed unreliable, most likely due to social desirability bias. Consequently, questions on vaccination status and questions using the vaccination data as a validation criterion were dropped from the datasets.

The phone survey was conducted to gather data on the socio-economic impacts of COVID-19 crisis, as well as the Hunga Tonga-Hunga Ha'apai volcanic eruption and tsunami in Tonga. Round 2 interviewed 2,503 households both in urban and rural regions of the country from July 2022 to August 2022. Survey topics included employment and income, food security, coping strategies, access to health services, asset ownership, and preparedness. Purpose of Round 2 survey was to continue tracking the impact of the crises after Round 1, which was completed in April, 2022 - May, 2022. Additionally, round 2 survey besides the household information, gathers data on individual level that was not included in Round 1. Two individual datasets explore adult employment and child education. While these findings are not without their caveats due to the lack of baseline data, constraints of the mobile phone survey methodology, and data quality constraints, they represent the best estimates to date and supplement other data on macroeconomic conditions, exports, firm-level information, etc. to develop an initial picture of the impacts of the crises on the population.

Version 01: Cleaned, labelled and anonymized version of the Master file.

• HOUSEHOLD DATASET: Basic Information, Vaccine, Health, Education, Food Insecurity, Employment, Income, Coping Strategies, Assets
• ADULT EMPLOYMENT DATASET: Basic Information, Employment

• CHILD EDUCATION DATASET: Basic Information, Child Education

• Collection start: 2022

• Collection end: 2022

The Rental Report time series dataset provides detailed time-series statistics for some key Rental Report data from the March quarter of 2000 to the December quarter of 2017. This specific dataset presents statistics on affordable rental properties by the 2016 Local Government Areas geographic level.

Affordable rental properties are those within 30 per cent of gross income for low-income households. The rental thresholds are taken from the household incomes for whom that number of bedrooms is a minimum:

• For one-bedroom properties, we have taken the income of singles on Newstart allowance;

• For two-bedroom properties, we have taken a single parent pensioner with one child aged under 5;

• For three-bedroom properties, we have taken a couple on Newstart with two children;

• For four-bedroom properties, we have taken a couple on Newstart with four children.

  The Rental Report provides the most accurate information on the private rental market in Victoria. The data come from records kept by the Residential Tenancies Bond Authority (RTBA). The RTBA is responsible for receiving, registering and refunding all bonds associated with private residential leases in Victoria.

For more information please visit the Department of Health and Human Services.