The Global Welfare Dataset (GLOW) is a cross-national panel dataset that aims at facilitating comparative social policy research on the Global North and Global South. The database includes 381 variables on 61 countries from years between 1989 and 2015. The database has four main categories of data: welfare, development, economy and politics.The data is the result of an original data compilation assembled by using information from several international and domestic sources. Missing data was supplemented by domestic sources where available. We sourced data primarily from these international databases:Atlas of Social Protection Indicators of Resilience and Equity – ASPIRE (World Bank)Government Finance Statistics (International Monetary Fund)Social Expenditure Database – SOCX (Organisation for Economic Co-operation and Development)Social Protection Statistics – ESPROSS (Eurostat)Social Security Inquiry (International Labour Organization)Social Security Programs Throughout the World (Social Security Administration)Statistics on Income and Living Conditions – EU-SILC (European Union)World Development Indicators (World Bank)However, much of the welfare data from these sources are not compatible between all country cases. We conducted an extensive review of the compatibility of the data and computed compatible figures where possible. Since the heart of this database is the provision of social assistance across a global sample, we applied the ASPIRE methodology in order to build comparable indicators across European and Emerging Market economies. Specifically, we constructed indicators of average per capita transfers and coverage rates for social assistance programs for all the country cases not included in the World Bank’s ASPIRE dataset (Austria, Belgium, Bulgaria, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Luxembourg, Netherlands, Norway, Poland, Portugal, Romania, Slovak Republic, Slovenia, Spain, Sweden, Switzerland, and United Kingdom.)For details, please see:https://glow.ku.edu.tr/about

The Organisation for Economic Co-operation and Development (OECD) Social and Welfare Statistics (previously Social Expenditure Database) available via the UK Data Service includes the following databases:

The OECD Social Expenditure Database (SOCX) has been developed in order to serve a growing need for indicators of social policy. It includes reliable and internationally comparable statistics on public and mandatory and voluntary private social expenditure at programme level. SOCX provides a unique tool for monitoring trends in aggregate social expenditure and analysing changes in its composition. The main social policy areas are as follows: old age, survivors, incapacity-related benefits, health, family, active labour market programmes, unemployment, housing, and other social policy areas.

The Income Distribution database contains comparable data on the distribution of household income, providing both a point of reference for judging the performance of any country and an opportunity to assess the role of common drivers as well as drivers that are country-specific. They also allow governments to draw on the experience of different countries in order to learn "what works best" in narrowing income disparities and poverty. But achieving comparability in this field is also difficult, as national practices differ widely in terms of concepts, measures, and statistical sources.

The Child Wellbeing dataset compare 21 policy-focussed measures of child well-being in six areas, chosen to cover the major aspects of children’s lives: material well being; housing and environment; education; health and safety; risk behaviours; and quality of school life.

The Better Life Index: There is more to life than the cold numbers of GDP and economic statistics. This Index allows you to compare well-being across countries, based on 11 topics the OECD has identified as essential, in the areas of material living conditions and quality of life.

The Social Expenditure data were first provided by the UK Data Service in March 2004.

This dataset shows the monthly count of new and completed investigations conducted by Child Welfare Services, broken down by type and outcome. The dataset includes statistics for both traditional Investigation Responses and for Alternative Responses. An Alternative Response is intended to increase engagement and service usage through a collaborative partnership with families in cases where there is no Child Protective Services history and the referral suggests low risk of harm to the child. A completed Investigation Response can have one of three outcomes: (1) allegation indicated -- credible evidence found which has not been satisfactorily refuted; (2) allegation ruled out – credible evidence found that the abuse did not occur; and (3) allegation unsubstantiated – insufficient evidence found to support a finding of indicated or ruled out abuse. This dataset is updated quarterly.

The Comparative Welfare States Dataset contains statistics and indices on welfare state, economic, institutional, political, policy and demographic topics. Data is available for 22 rich democracies worldwide covering the period 1960-2013.

Abstract copyright UK Data Service and data collection copyright owner. The Organisation for Economic Co-operation and Development (OECD) Social and Welfare Statistics (previously Social Expenditure Database) available via the UK Data Service includes the following databases: The OECD Social Expenditure Database (SOCX) has been developed in order to serve a growing need for indicators of social policy. It includes reliable and internationally comparable statistics on public and mandatory and voluntary private social expenditure at programme level. SOCX provides a unique tool for monitoring trends in aggregate social expenditure and analysing changes in its composition. The main social policy areas are as follows: old age, survivors, incapacity-related benefits, health, family, active labour market programmes, unemployment, housing, and other social policy areas. The Income Distribution database contains comparable data on the distribution of household income, providing both a point of reference for judging the performance of any country and an opportunity to assess the role of common drivers as well as drivers that are country-specific. They also allow governments to draw on the experience of different countries in order to learn "what works best" in narrowing income disparities and poverty. But achieving comparability in this field is also difficult, as national practices differ widely in terms of concepts, measures, and statistical sources. The Child Wellbeing dataset compare 21 policy-focussed measures of child well-being in six areas, chosen to cover the major aspects of children’s lives: material well being; housing and environment; education; health and safety; risk behaviours; and quality of school life. The Better Life Index: There is more to life than the cold numbers of GDP and economic statistics. This Index allows you to compare well-being across countries, based on 11 topics the OECD has identified as essential, in the areas of material living conditions and quality of life. The Social Expenditure data were first provided by the UK Data Service in March 2004. Main Topics: Topics covered by the database include:old-age cash benefitsdisability cash benefitsoccupational injury and diseasesickness benefitsservices for the elderly and disabled peoplesurvivorsfamily cash benefitsfamily servicesactive labour market programmesunemployment healthhousing benefitsother contingencies

Weekly recipient numbers for the Pandemic Unemployment Payment (PUP). The PUP is a weekly payment for employees and the self-employed who lost employment due to the COVID-19 public health emergency. Figures are updated on a weekly basis (Wednesdays at 11am). The figures Refer to the number of persons receiving a PUP each week. Arrears payments may be due in some cases; recipient numbers reflect the week of the Entitlement period, rather than the week of payment. The EUR 203 rate of payment increased to EUR 208 in the first week of January 2022, in line with Budget 2022. The age band refers to the age band of the recipient as of 31st December in the year the payment issued.

Proportion of households working age social welfare was majority of household income

The data contained in this data set were collected by a project entitled "Comparative Welfare States in the 21st Century" directed by David Brady, Evelyne Huber, and John D. Stephens. The project was supported in 2011-13 by grants from the National Science Foundation ("Collaborative Research: Comparative Welfare States: A Public Use Archival Dataset,” SES 1059959 and 1061007). Additional support was provided by the Morehead Alumni Distinguished Professorship and the Margaret and Paul A. Johnston Professorships (funding the Gerhard E. Lenski, Jr. Distinguished Professorship) in the College of Arts and Sciences at the University of North Carolina at Chapel Hill. Some further support was provided by Duke University and the WZB Berlin Social Science Center. An earlier version of this dataset was assembled by Evelyne Huber, Charles Ragin, and John Stephens in the 1990s. That project was supported in 1990-92 by a grant from the National Science Foundation (Grant # SES 9108716). Major categories include: wage and salary data, social spending, revenue and welfare state institutions data, labour force and labour institutions data, demographic data, macroeconomic data (Penn world tables, mark 6.1), political variables.

Included in this data set are data elements that will help the public identify all the programs currently funded by the New York State Office of Children and Family Services' (OCFS) Division of Child Welfare and Community Services (CWCS). Data elements include the name of the provider agency, the business address and phone number, the county served, type of program, funding source, description of services, contract dates, contract number, funding level and the agencies website, where available

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

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.

The welfare magnet hypothesis holds that immigrants are likely to relocate to regions with generous welfare benefits. Although this assumption has motivated extensive reforms to immigration policy and social programs, the empirical evidence remains contested. In this study, we assess detailed administrative records from Switzerland covering the full population of social assistance recipients between 2005 and 2015. By leveraging local variation in cash transfers and exogenous shocks to benefit levels, we identify how benefits shape within-country residential decisions. We find limited evidence that immigrants systematically move to localities with higher benefits. The lack of significant welfare migration within a context characterized by high variance in benefits and low barriers to movement suggests that the prevalence of this phenomenon may be overstated. These findings have important implications in the European setting, where subnational governments often possess discretion over welfare and parties frequently mobilize voters around the issue of “benefit tourism.”

Social Assistance Payrolls in the United States increased to 19.40 Thousand in June from 17.10 Thousand in May of 2025. This dataset includes a chart with historical data for the United States Social Assistance Payrolls.

The project undertook fieldwork with three sets of respondents: semi-structured interviews with 52 key informants/policy stakeholders (not included in archive for anonymity reasons), 27 focus groups with frontline welfare practitioners who implement policy; and repeat qualitative longitudinal interviews with a diverse sample of 481 welfare service users (WSU) who were subject to conditionality. Each person was invited to interview three times. WSU were sampled to inform 9 different policy areas (ASB / Disability / Ex-Offenders/ Homelessness / Jobseeking / Lone Parents / Migrants / Social Housing / Universal Credit). The fieldwork took place in a range of cities across England and Scotland. For further details about the context and methods of Welfare Conditionality, please see www.welfareconditionality.ac.uk.In the UK the use of conditional welfare arrangements that combine elements of sanction and support which aim to 'correct' the 'problematic' behaviour of certain welfare recipients are now an established part of welfare, housing, criminal justice and immigration systems. A strong mainstream political consensus exists in favour of conditionality, whereby many welfare entitlements are increasingly dependent on citizens first agreeing to meet particular compulsory duties or patterns of approved behaviour. Conditionality is currently embedded in a broad range of policy arenas (including unemployment benefit systems, family intervention projects, street homelessness interventions, social housing, and asylum legislation) and its use is being extended to cover previously exempt groups e.g. lone parents and disability benefit recipients. However, assumptions about the benefits and usefulness of conditionality in changing the behaviour of social welfare recipients remain largely untested. This project has two key aims. First, to advance understanding about the role of conditionality in promoting and sustaining behaviour change among a diversity of welfare recipients over time. Second, to consider the circumstances in which the use of conditionality may, or may not, be ethically justified. We aim to address gaps in existing knowledge by establishing an original and comprehensive evidence base on the efficacy and ethicality of conditionality across a range of social policy fields and diverse groups of welfare service users. We will use a range of methods to achieve these aims. Initially, we will review relevant literature, statistical data sources and policy documents. To help inform and critically interrogate our approach, we have secured the involvement of leading international scholars who will participate in a series of expert panel seminars convened in the early stages of the study. We will also conduct 'consultation workshops' with welfare recipients and practitioners to feed into research design (these workshops will be held again towards the end of the study to reflect on emerging findings). Following on from this we will undertake fieldwork with three sets of respondents: 1. semi-structured interviews with 40 'elite' policymakers; 2. 24 focus groups (with 6-10 respondents) with frontline welfare practitioners who implement policy; and 3. repeat qualitative longitudinal interviews with a diverse sample of 400 welfare recipients who are subject to conditionality. Each person will be interviewed three times giving a total of 1200 interviews. The elite interviews will explore the reasons why policymakers introduce conditional welfare policies and their understandings of how they might promote behavioural change. The focus groups will consider both what frontline practitioners think should happen (ethically) and what they think would/does happen (in practice) when conditionality is implemented. The three rounds of repeat qualitative longitudinal interviews with welfare recipients will provide a meaningful way to examine the transitions, adaptations and coping strategies of individuals subject to conditionality, how these may change over time, and why there may be diverse outcomes for different people. Fieldwork will take place in a variety of locations in England and Scotland, including the cities of London, Manchester, Salford, Sheffield, Glasgow and Edinburgh. This will allow for a comparative analysis of the interplay between shared social security law and the different policy and legal frameworks on housing, homelessness and criminal justice that exist in England and Scotland. All interviews will be audio recorded and transcribed (with permission). The new data generated will then be analysed to explore commonalities and differences between the perspectives of policymakers, frontline workers and welfare recipients. Findings will be disseminated to policymaker, practitioner, academic and welfare service user audiences. Qualitative semi-structured interviews with key informants, focus groups with welfare street-level bureaucrats, and repeat semi-structured qualitative longitudinal interviews with a diversity of welfare service users subject to welfare conditionality(three waves over a two-year period).

The Food Assistance Program provides Electronic Benefit Transfer (EBT) cards that can be used to buy groceries at supermarkets, grocery stores and some Farmers Markets. This dataset provides data on the number of households, recipients and cash assistance provided through the Food Assistance Program participation in Iowa by month and county starting in January 2011 and updated monthly.

Beginning January 2017, the method used to identify households is based on the following: 1. If one or more individuals receiving Food Assistance also receives FIP, the household is categorized as FA/FIP. 2. If no one receives FIP, but at least one individual also receives Medical Assistance, the household is categorized as FA/Medical Assistance. 3. If no one receives FIP or Medical Assistance, but at least one individual receives Healthy and Well Kids in Iowa or hawk-i benefits, the household is categorized as FA/hawk-i. 4. If no one receives FIP, Medical Assistance or hawk-i , the household is categorized as FA Only.

Changes have also been made to reflect more accurate identification of individuals. The same categories from above are used in identifying an individual's circumstances. Previously, the household category was assigned to all individuals of the Food Assistance household, regardless of individual status. This change in how individuals are categorized provides a more accurate count of individual categories.

Timing of when the report is run also changed starting January 2017. Reports were previously ran on the 1st, but changed to the 17th to better capture Food Assistance households that received benefits for the prior month. This may give the impression that caseloads have increased when in reality, under the previous approach, cases were missed.

This presentation is part of an ongoing series of analyses of the impact of housing benefit and other welfare changes. This latest version includes possible impacts of recent government announcements on welfare.

The study of Indiana's Child Welfare reform was designed to identify community professionals' perceptions of the Department of Child Services (DCS) following the release of a pilot program to reform child welfare in the state of Indiana. In December, 2005, the pilot project was officially rolled out in three regions of the state. The three chosen regions of the state included 11 county agencies with both urban and rural population centers. Together these regions represented 28% of the state's CHINS (Child In Need of Service) population and 20% of the child fatalities for 2004. This study represents data collected to identify perceptions of the DCS by sending a survey to professionals in the 11 pilot and 12 comparison counties. The survey questions were arranged by categories of safety, permanency, well-being, DCS goals, the reform, team meetings, and demographics. Nine separate instruments were developed and disseminated for each community group. The community professionals surveyed included: Court Appointed Special Advocates (CASAs), foster parents, judges, Law Enforcement Agencies (LEAs), medical and public health professionals, schools, social service professionals, and mental health professionals. Survey instruments were tailored to each audience, with questions that were derived from the DCS "Framework for Individualized Needs-Based Child Welfare Service Provisions," which outlined the agency's core practice values and principles.

GPIIA10 - Majority Social Welfare Income Source. Published by Central Statistics Office. Available under the license Creative Commons Attribution 4.0 (CC-BY-4.0).Majority Social Welfare Income Source...

The California Work Pays Demonstration Project (CWPDP) was intended to assess the effects of recent changes in Aid to Families With Dependent Children (AFDC) provisions. The project documents the dynamics of family poverty and welfare use in California. Part 1, Overview Data: Cases contains one record for each CWPDP case sampled between October 1992 and March 1997. For each case, seven data presence indicator variables identify the presence of data in each of the data file types. Four observation variables identify the number of case-months records observed in the Four County Cases file, the number of person records observed in the Four County Persons and Assistance History Persons files, and the first month during which AFDC participation is observed in the Assistance History Persons file. Fifteen survey detail variables identify survey participation, interview completion, respondent's person number and date of birth, and the survey record number. Parts 2-5, Four County Data: Cases, contain case-month records for all control and experimental cases selected to be a part of the study between October 1992 and March 1997 for any month (beginning with the month selected) during which an assistance unit received AFDC of food stamps. Each case-month record contains county administrative data for eligible family size and type, income, and cash and food stamp assistance amounts. These files are identical to the Four County Data: Cases files in County Welfare Administrative Data Version 4. Parts 6-9, Four County Data: Persons, contain records for each person observed associated with any control or experimental case selected to be part of the study between October 1992 and March 1997. Records include nonconfidential demographic information and monthly values for aid type and eligibility. These files are identical to the Four County Data: Persons files in County Welfare Administrative Data Version 4. Parts 10-13, Assistance History Data: Aggregate, contain case-month records that summarize information for the months of January 1987 through December 1996 about the public assistance program participation and eligibility of persons associated with sampled cases. This dataset was constructed from the Assistance History Data: Persons datasets (Parts 14-17) that contain persons associated with the study units. Parts 14-17, Assistance History Data: Persons, contain the Medi-Cal and program participation history of each person associated with the assistance units for cases selected between October 1992 and March 1997. This dataset does not include information about persons who left the assistance unit before the month sampled. Each record includes program participation information for each month from January 1987 through December 1996, a total of 120 months, as well as demographic information. Parts 18-21, Medi-Cal Payments Data: Cases, contain one record for each case selected to be part of the CWPDP sample between December 1992 and March 1997. This dataset contains the Medi-Cal payments made for each case in the study for the month of December 1992 and quarterly from 1993 through the fourth quarter of 1997. University of California Data Archive and Technical Assistance receives this data from California Department of Social Services-Research Branch (CDSS-RB) by quarter (not month), aggregated to case number. Therefore, the data in these files are aggregated payments information for all assistance units with the same case number, whether or not that assistance unit is part of the CWPDP sample. These files are identical to the Medi-Cal Payments Data: Cases files in County Welfare Administrative Data Version 3.

This dataset summarizes the number of dependent children (less than 18 years old) removed from households due to parental drug abuse. The data indicates if the dependent children were placed in kinship care or not. The total number of children in this data set are provided by the U.S. Census Bureau’s American Community Survey (ACS), which publishes 5 year estimates of the population. The most recent year of entries in this data set may be available before the corresponding ACS population estimates for that year are published. In that case, the data set uses values from the most recently published ACS estimates and notes the year from which those estimates are pulled. These values are updated once the Census Bureau releases the most recent estimates.” *Kinship care refers to the care of children by relatives or, in some jurisdictions, close family friends (often referred to as fictive kin). Relatives are the preferred resource for children who must be removed from their birth parents because it maintains the children's connections with their families. *The Adoption and Foster Care Analysis and Reporting System (AFCARS) definition of parental drug abuse is “Principal caretaker’s compulsive use of drugs that is not of a temporary nature.”