This table aims to show the distribution of welfare of private households, measured by their income, expenditures and wealth. The figures in this table are broken down to different household characteristics. The population consists of all private households with income on January 1st of the reporting year. In the population for the subject low-income households, both student households and households with income only for a part of the year have been excluded. Data available from: 2011 Status of the figures: The figures for 2011 to 2022 are final. The figures for 2023 are preliminary. Changes as of 1 November 2024: Figures for 2022 are finalized. Preliminary figures for 2023 are added. Changes as of 9 February 2022: The preliminary figures for 2020 concerning ‘Mean expenditures’ have been added. The topic 'Mean expenditures' only contains 5-annual data, for 2015 and 2020. The data for 2015 for this topic were still preliminary and are now final. When will new figures be published? New figures will be published in the fall of 2025.

In 2022, welfare expenditure as a share of GDP in Israel reached **** percent. This represented a decline compared to the preceding year, when the share of national expenditure on welfare services reached **** percent. Social spending increased during 2020, as a result of the coronavirus pandemic-related government spending.

China GDP: TI: Health Care, Social Security and Welfare data was reported at 2,751.461 RMB bn in 2021. This records an increase from the previous number of 2,439.612 RMB bn for 2020. China GDP: TI: Health Care, Social Security and Welfare data is updated yearly, averaging 1,002.280 RMB bn from Dec 2004 (Median) to 2021, with 18 observations. The data reached an all-time high of 2,751.461 RMB bn in 2021 and a record low of 262.071 RMB bn in 2004. China GDP: TI: Health Care, Social Security and Welfare data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s National Accounts – Table CN.AA: Gross Domestic Product.

In a survey from 2020, the largest share of companies in Italy declared to not monitor the social impact of the company's corporate welfare services. On the other hand, some ** percent stated to evaluate the effects that their services had on a social level.

Graph and download economic data for Government current expenditures: Income security: Welfare and social services (G160371A027NBEA) from 1959 to 2023 about social assistance, expenditures, government, income, services, GDP, and USA.

South Korea HIES: OU: AME: 2020p: CS: MS: Social Welfare data was reported at 4,411.097 KRW in 2024. This records a decrease from the previous number of 5,424.457 KRW for 2023. South Korea HIES: OU: AME: 2020p: CS: MS: Social Welfare data is updated yearly, averaging 4,968.535 KRW from Dec 2019 (Median) to 2024, with 6 observations. The data reached an all-time high of 5,501.241 KRW in 2019 and a record low of 4,411.097 KRW in 2024. South Korea HIES: OU: AME: 2020p: CS: MS: Social Welfare data remains active status in CEIC and is reported by Statistics Korea. The data is categorized under Global Database’s South Korea – Table KR.H075: 2019 Household Income and Expenditure Survey: 1 or more Members: Other Urban Households: Real: 2020p.

According to a survey published in 2020, the majority of employees in Italy stated that corporate welfare was improving their quality of life. In particular, mostly managers and executives declared to experience a high life quality related to the benefits of corporate welfare. Further data on corporate welfare show that managers and executives represented the largest majority of people working in Italy who were willing to accept an increase in salary or a bonus in form of welfare services.

This data table provides the basic information for California child support cases, such as number of cases per county, the number of cases where the child is currently receiving public assistance, number of cases where the child formerly received public assistance (but no longer does), and the number of cases where the child has never received public assistance. The data is sorted by county and broken into the Current Public Assistance, Former Public Assistance and Never Assisted types, the table will also show the percentage of that county’s total caseload.

This table provides an overview of the key figures on health and care available on StatLine. All figures are taken from other tables on StatLine, either directly or through a simple conversion. In the original tables, breakdowns by characteristics of individuals or other variables are possible. The period after the year of review before data become available differs between the data series. The number of exam passes/graduates in year t is the number of persons who obtained a diploma in school/study year starting in t-1 and ending in t.

Data available from: 2001

Status of the figures:

2024: Most available figures are definite. Figures are provisional for: - causes of death; - youth care; - persons employed in health and welfare; - persons employed in healthcare; - Mbo health care graduates; - Hbo nursing graduates / medicine graduates (university).

2023: Most available figures are definite. Figures are provisional for: - perinatal mortality at pregnancy duration at least 24 weeks; - diagnoses known to the general practitioner; - hospital admissions by some diagnoses; - average period of hospitalisation; - supplied drugs; - AWBZ/Wlz-funded long term care; - physicians and nurses employed in care; - persons employed in health and welfare; - average distance to facilities; - profitability and operating results at institutions. Figures are revised provisional for: - expenditures on health and welfare.

2022: Most available figures are definite. Figures are revised provisional for: - expenditures on health and welfare.

2021: Most available figures are definite, Figures are revised provisional for: - expenditures on health and welfare.f

2020 and earlier: All available figures are definite.

Changes as of 4 July 2025: More recent figures have been added for: - causes of death; - life expectancy; - life expectancy in perceived good health; - self-perceived health; - hospital admissions by some diagnoses; - sickness absence; - average period of hospitalisation; - contacts with health professionals; - youth care; - smoking, heavy drinkers, physical activity; - overweight; - high blood pressure; - physicians and nurses employed in care; - persons employed in health and welfare; - persons employed in healthcare; - Mbo health care graduates; - Hbo nursing graduates / medicine graduates (university); - expenditures on health and welfare; - profitability and operating results at institutions.

Changes as of 18 december 2024: - Distance to facilities: the figures withdrawn on 5 June have been replaced (unchanged). - Youth care: the previously published final results for 2021 and 2022 have been adjusted due to improvements in the processing. - Due to a revision of the statistics Expenditure on health and welfare 2021, figures for expenditure on health and welfare care have been replaced from 2021 onwards. - Due to the revision of the National Accounts, the figures on persons employed in health and welfare have been replaced for all years. - AWBZ/Wlz-funded long term care: from 2015, the series Wlz residential care including total package at home has been replaced by total Wlz care. This series fits better with the chosen demarcation of indications for Wlz care.

When will new figures be published? New figures will be published in December 2025.

The Child Care and Development Fund (CCDF) provides federal money to states and territories to provide assistance to low-income families, to obtain quality child care so they can work, attend training, or receive education. Within the broad federal parameters, States and Territories set the detailed policies. Those details determine whether a particular family will or will not be eligible for subsidies, how much the family will have to pay for the care, how families apply for and retain subsidies, the maximum amounts that child care providers will be reimbursed, and the administrative procedures that providers must follow. Thus, while CCDF is a single program from the perspective of federal law, it is in practice a different program in every state and territory. The CCDF Policies Database project is a comprehensive, up-to-date database of CCDF policy information that supports the needs of a variety of audiences through (1) analytic data files, (2) a project website and search tool, and (3) an annual report (Book of Tables). These resources are made available to researchers, administrators, and policymakers with the goal of addressing important questions concerning the effects of child care subsidy policies and practices on the children and families served. A description of the data files, project website and search tool, and Book of Tables is provided below: 1. Detailed, longitudinal analytic data files provide CCDF policy information for all 50 states, the District of Columbia, and the United States territories and outlying areas that capture the policies actually in effect at a point in time, rather than proposals or legislation. They capture changes throughout each year, allowing users to access the policies in place at any point in time between October 2009 and the most recent data release. The data are organized into 32 categories with each category of variables separated into its own dataset. The categories span five general areas of policy including: Eligibility Requirements for Families and Children (Datasets 1-5) Family Application, Terms of Authorization, and Redetermination (Datasets 6-13) Family Payments (Datasets 14-18) Policies for Providers, Including Maximum Reimbursement Rates (Datasets 19-27) Overall Administrative and Quality Information Plans (Datasets 28-32) The information in the data files is based primarily on the documents that caseworkers use as they work with families and providers (often termed "caseworker manuals"). The caseworker manuals generally provide much more detailed information on eligibility, family payments, and provider-related policies than the CCDF Plans submitted by states and territories to the federal government. The caseworker manuals also provide ongoing detail for periods in between CCDF Plan dates. Each dataset contains a series of variables designed to capture the intricacies of the rules covered in the category. The variables include a mix of categorical, numeric, and text variables. Most variables have a corresponding notes field to capture additional details related to that particular variable. In addition, each category has an additional notes field to capture any information regarding the rules that is not already outlined in the category's variables. Beginning with the 2020 files, the analytic data files are supplemented by four additional data files containing select policy information featured in the annual reports (prior to 2020, the full detail of the annual reports was reproduced as data files). The supplemental data files are available as 4 datasets (Datasets 33-36) and present key aspects of the differences in CCDF-funded programs across all states and territories as of October 1 of each year (2009-2022). The files include variables that are calculated using several variables from the analytic data files (Datasets 1-32) (such as copayment amounts for example family situations) and information that is part of the annual project reports (the annual Book of Tables) but not stored in the full database (such as summary market rate survey information from the CCDF plans). 2. The project website and search tool provide access to a point-and-click user interface. Users can select from the full set of public data to create custom tables. The website also provides access to the full range of reports and products released under the CCDF Policies Data

According to data published in 2020, more than half of employees in Italy would accept an increase in the salary or a bonus in form of welfare services. More specifically, the share of respondents who declared to be in favor reached some ** percent. On the contrary, about ** percent of employees stated to be against.

This dataset, released February 2021, contains statistics relating to the income support recipients of Age pensioners, June 2020; Disability support pensioners, June 2020; Female sole parent pensioners, June 2020; People receiving an unemployment benefit, June 2020; JobSeeker unemployment beneficiaries, June 2020; Young people aged 16 to 21 receiving an unemployment benefit, June 2020; People receiving an unemployment benefit short-term and long-term, June 2017; Low income, welfare-dependent families (with children), June 2017; Children in low income, welfare-dependent families, June 2017; Health Care Card holders, June 2020; Pensioner Concession Card holders, June 2020; Seniors Health Card holders, June 2020; The data is by Local Government Area (LGA) 2016 geographic boundaries. For more information please see the data source notes on the data. Source: Compiled by PHIDU based on data from the Department of Social Services Payment Demographic Data, June 2020; Compiled by PHIDU based on data from the Department of Social Services, June 2017; and the ABS Estimated Resident Population, 30 June 2017; AURIN has spatially enabled the original data. Data that was not shown/not applicable/not published/not available for the specific area ('#', '..', '^', 'np, 'n.a.', 'n.y.a.' in original PHIDU data) was removed.It has been replaced by by Blank cells. For other keys and abbreviations refer to PHIDU Keys.

As of 2022, the total national expenditure on welfare services in Israel amounted to just over *** billion Israeli shekels, which is equivalent to about to 60 billion U.S. dollars. This represented an increase of *** percent compared to the preceding year.

This dataset, released February 2021, contains statistics relating to the income support recipients of Age pensioners, June 2020; Disability support pensioners, June 2020; Female sole parent pensioners, June 2020; People receiving an unemployment benefit, June 2020; JobSeeker unemployment beneficiaries, June 2020; Young people aged 16 to 21 receiving an unemployment benefit, June 2020; People receiving an unemployment benefit short-term and long-term, June 2017; Low income, welfare-dependent families (with children), June 2017; Children in low income, welfare-dependent families, June 2017; Health Care Card holders, June 2020; Pensioner Concession Card holders, June 2020; Seniors Health Card holders, June 2020; The data is by Population Health Area (PHA) 2016 geographic boundaries based on the 2016 Australian Statistical Geography Standard (ASGS). Population Health Areas, developed by PHIDU, are comprised of a combination of whole SA2s and multiple (aggregates of) SA2s, where the SA2 is an area in the ABS structure. For more information please see the data source notes on the data. Source: Compiled by PHIDU based on data from the Department of Social Services Payment Demographic Data, June 2020; Compiled by PHIDU based on data from the Department of Social Services, June 2017; and the ABS Estimated Resident Population, 30 June 2017; AURIN has spatially enabled the original data. Data that was not shown/not applicable/not published/not available for the specific area ('#', '..', '^', 'np, 'n.a.', 'n.y.a.' in original PHIDU data) was removed.It has been replaced by by Blank cells. For other keys and abbreviations refer to PHIDU Keys.

Financial variables of NACE, sector Q (human health and social work), compiled for the Netherlands in accordance with the SBS methodology of Eurostat for population of market-oriented units over 2020 on 4th digit level of NACE (results during research trajectory provided to Eurostat conform Eurostat grant 101022410 - 2020-NL-B5640-EBS).

Covid-19 has affected people in various ways, directly through disease and death, and indirectly through disease containment measures. Understanding how the pandemic and countermeasures agaist it impacted quality of life is valuable for policy makers.

To address and compare the various components of quality of life, a suitable framework is needed, which the capability approach provides. This approach measures quality of life as opportunities, compared to traditional welfarist economics that defines wellbeing as utility.

For this study, we used a capability list from a Swedish governmental investigation (SOU 2015:56) that suggested relevant capabilities for the Swedish situation: Financial situation, Social relations, Health, Housing, Living environment, Occupation, Knowledge, Security, Time balance, and Political and civil rights.

The study was performed in June 2020. In an internet-based survey, we quota-sampled 500 Swedish residents from a commercial web-panel, after population proportions of age, region of residence, education, gender.

The survey started with the informed consent statement, followed by questions on participants’ current baseline capability levels in the ten capability dimensions (Low, Medium, Complete). Next followed questions about perceived changes in capability during 2020 in the ten dimensions on a five-item Likert scale (Much less, Less, Equal, Higher, Much higher). The survey ended with a number of background questions on socio-economic and demographic conditions.

Sampling large numbers of participants using a commercial web panel is administratively more feasible and quicker than other sampling methods, such as for example direct sampling from the general population. Also, the response rate may be higher and data handling easier. On the other hand, it is less transparent how recruitment into the study was performed and web panel participants may not be representative of the population. Those limitations should be kept in mind when analysing the data and interpreting results.

Data were collected with a PHP-based web application for surveys (limesurvey version 4.2.2, https://www.limesurvey.org) hosted on a Umeå university server. The data was collected anonymously.

Explore the progression of average salaries for graduates in Department Of Social Welfare from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Department Of Social Welfare relative to other fields. This data is essential for students assessing the return on investment of their education in Department Of Social Welfare, providing a clear picture of financial prospects post-graduation.

This dataset, released February 2020, contains the female Population projections for years 2020, 2025 and 2030, by 5-year age groups: 0-14, 15-24, 25-44, 45-64, 65+, 70+, 75+, 85+ years.

The data is by Population Health Area (PHA) 2016 geographic boundaries based on the 2016 Australian Statistical Geography Standard (ASGS).

Population Health Areas, developed by PHIDU, are comprised of a combination of whole SA2s and multiple (aggregates of) SA2s, where the SA2 is an area in the ABS structure.

For more information please see the data source notes on the data.

Source: These data are based on customised projections prepared for the Australian Government Department of Health by the Australian Bureau of Statistics and originally published by the Australian Institute of Health and Welfare. PHA data were compiled by PHIDU based on these customised projections for 2020, 2025, and 2030..

AURIN has spatially enabled the original data. Data that was not shown/not applicable/not published/not available for the specific area ('#', '..', '^', 'np, 'n.a.', 'n.y.a.' in original PHIDU data) was removed.It has been replaced by by Blank cells. For other keys and abbreviations refer to PHIDU Keys.

Explore the progression of average salaries for graduates in Industrial Social Welfare from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Industrial Social Welfare relative to other fields. This data is essential for students assessing the return on investment of their education in Industrial Social Welfare, providing a clear picture of financial prospects post-graduation.