This report provides information about the demographics of children and parents at steps in the child welfare system. It is produced in compliance with Local Law 132 of 2022.

This table aims to show the distribution of welfare of persons in the Netherlands, measured by their income. The figures in this table are broken down to different person characteristics.

The population consists of all persons in private households with income on January 1st of the reporting year. In the population for the subject low-income persons, persons in both student households and households with income only for a part of the year have been excluded. The population for the subject economic independence consists of all persons aged from 15 to the OAP-age in private households with income on January 1st of the reporting year, except for students and pupils.

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 November 2024: The preliminary figures for 2023 have been added.

When will new figures be published? New figures will be published in the fall of 2025.

G0104 - SDG 1.3.1 Proportion of the population receiving Social Welfare Payments by County, Year and Statistic. Published by Central Statistics Office. Available under the license Creative Commons Attribution 4.0 (CC-BY-4.0).SDG 1.3.1 Proportion of the population receiving Social Welfare Payments by County, Year and Statistic...

Context

Data related to estimated fraud or payment errors for unemployment and food assistance, used in discussion about alleged widespread fraud and abuse of welfare.

Content

Data pulled from Gov't Websites on February 3rd, 2017.

SNAP rates come from :https://www.fns.usda.gov/sites/default/files/snap/2014-rates.pdf UI Error data comes from : https://www.dol.gov/general/maps/data > > > 2016 IPIA 1-year data [07/01/2015 - 06/30/2016] >> tab: Integrity Rates with CI

Inspiration

Want to plot this against election results or possibly find polling data about alleged abuse of welfare system to match against actual findings

Series Name: Proportion of population with large household expenditures on health (greater than 25percent) as a share of total household expenditure or income (percent)Series Code: SH_XPD_EARN25Release Version: 2021.Q2.G.03 This dataset is the part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 3.8.2: Proportion of population with large household expenditures on health as a share of total household expenditure or incomeTarget 3.8: Achieve universal health coverage, including financial risk protection, access to quality essential health-care services and access to safe, effective, quality and affordable essential medicines and vaccines for allGoal 3: Ensure healthy lives and promote well-being for all at all agesFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

Series Name: [ILO] Proportion of poor population receiving social assistance cash benefit by sex (percent)Series Code: SI_COV_POORRelease Version: 2021.Q2.G.03 This dataset is part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 1.3.1: Proportion of population covered by social protection floors/systems, by sex, distinguishing children, unemployed persons, older persons, persons with disabilities, pregnant women, newborns, work-injury victims and the poor and the vulnerableTarget 1.3: Implement nationally appropriate social protection systems and measures for all, including floors, and by 2030 achieve substantial coverage of the poor and the vulnerableGoal 1: End poverty in all its forms everywhereFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

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 DSS Payment Demographic data set is made up of:

Selected DSS payment data by

• Geography: state/territory, electorate, postcode, LGA and SA2 (for 2015 onwards)

• Demographic: age, sex and Indigenous/non-Indigenous

• Duration on Payment (Working Age & Pensions)

• Duration on Income Support (Working Age, Carer payment & Disability Support Pension)

• Rate (Working Age & Pensions)

• Earnings (Working Age & Pensions)

• Age Pension assets data

• JobSeeker Payment and Youth Allowance (other) Principal Carers

• Activity Tested Recipients by Partial Capacity to Work (NSA,PPS & YAO)

• Exits within 3, 6 and 12 months (Newstart Allowance/JobSeeker Payment, Parenting Payment, Sickness Allowance & Youth Allowance)

• Disability Support Pension by medical condition

• Care Receiver by medical conditions

• Commonwealth Rent Assistance by Payment type and Income Unit type have been added from March 2017. For further information about Commonwealth Rent Assistance and Income Units see the Data Descriptions and Glossary included in the dataset.

From December 2022, the "DSS Expanded Benefit and Payment Recipient Demographics – quarterly data" publication has introduced expanded reporting populations for income support recipients. As a result, the reporting population for Jobseeker Payment and Special Benefit has changed to include recipients who are current but on zero rate of payment and those who are suspended from payment. The reporting population for ABSTUDY, Austudy, Parenting Payment and Youth Allowance has changed to include those who are suspended from payment. The expanded report will replace the standard report after June 2023.

Additional data for DSS Expanded Benefit and Payment Recipient Demographics – quarterly data includes:

• A new contents page to assist users locate the information within the spreadsheet

• Additional data for the ‘Suspended’ population in the ‘Payment by Rate’ tab to enable users to calculate the old reporting rules.

• Additional information on the Employment Earning by ‘Income Free Area’ tab.

From December 2022, Services Australia have implemented a change in the Centrelink payment system to recognise gender other than the sex assigned at birth or during infancy, or as a gender which is not exclusively male or female. To protect the privacy of individuals and comply with confidentialisation policy, persons identifying as ‘non-binary’ will initially be grouped with ‘females’ in the period immediately following implementation of this change. The Department will monitor the implications of this change and will publish the ‘non-binary’ gender category as soon as privacy and confidentialisation considerations allow.

Local Government Area has been updated to reflect the Australian Statistical Geography Standard (ASGS) 2022 boundaries from June 2023.

Commonwealth Electorate Division has been updated to reflect the Australian Statistical Geography Standard (ASGS) 2021 boundaries from June 2023.

SA2 has been updated to reflect the Australian Statistical Geography Standard (ASGS) 2021 boundaries from June 2023.

From December 2021, the following are included in the report:

• selected payments by work capacity, by various demographic breakdowns

• rental type and homeownership

• Family Tax Benefit recipients and children by payment type

• Commonwealth Rent Assistance by proportion eligible for the maximum rate

• an age breakdown for Age Pension recipients

For further information, please see the Glossary.

From June 2021, data on the Paid Parental Leave Scheme is included yearly in June releases. This includes both Parental Leave Pay and Dad and Partner Pay, across multiple breakdowns. Please see Glossary for further information.

From March 2017 the DSS demographic dataset will include top 25 countries of birth. For further information see the glossary.

From March 2016 machine readable files containing the three geographic breakdowns have also been published for use in National Map, links to these datasets are below:

• Statistical Area 2 - SA2

• Commonwealth Electoral Division - CED

• Local Government Area - LGA

Pre June 2014 Quarter Data contains:

Selected DSS payment data by

• Geography: state/territory; electorate; postcode and LGA

• Demographic: age, sex and Indigenous/non-Indigenous

Note: JobSeeker Payment replaced Newstart Allowance and other working age payments from 20 March 2020, for further details see: https://www.dss.gov.au/benefits-payments/jobseeker-payment

For data on DSS payment demographics as at June 2013 or earlier, the department has published data which was produced annually. Data is provided by payment type containing timeseries’, state, gender, age range, and various other demographics. Links to these publications are below:

• Statistical Paper series

Concession card data in the March and June 2020 quarters have been re-stated to address an over-count in reported cardholder numbers.

28/06/2024 – The March 2024 and December 2023 reports were republished with updated data in the ‘Carer Receivers by Med Condition’ section, updates are exclusive to the ‘Care Receivers of Carer Payment recipients’ table, under ‘Intellectual / Learning’ and ‘Circulatory System’ conditions only.

Series Name: [World Bank] Proportion of population covered by social assistance programs (percent)Series Code: SI_COV_SOCASTRelease Version: 2021.Q2.G.03 This dataset is part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 1.3.1: Proportion of population covered by social protection floors/systems, by sex, distinguishing children, unemployed persons, older persons, persons with disabilities, pregnant women, newborns, work-injury victims and the poor and the vulnerableTarget 1.3: Implement nationally appropriate social protection systems and measures for all, including floors, and by 2030 achieve substantial coverage of the poor and the vulnerableGoal 1: End poverty in all its forms everywhereFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

United States US: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate data was reported at 1.310 % in 2016. United States US: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate data is updated yearly, averaging 1.310 % from Dec 2016 (Median) to 2016, with 1 observations. United States US: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Poverty. The growth rate in the welfare aggregate of the bottom 40% is computed as the annualized average growth rate in per capita real consumption or income of the bottom 40% of the population in the income distribution in a country from household surveys over a roughly 5-year period. Mean per capita real consumption or income is measured at 2011 Purchasing Power Parity (PPP) using the PovcalNet (http://iresearch.worldbank.org/PovcalNet). For some countries means are not reported due to grouped and/or confidential data. The annualized growth rate is computed as (Mean in final year/Mean in initial year)^(1/(Final year - Initial year)) - 1. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported. The initial year refers to the nearest survey collected 5 years before the most recent survey available, only surveys collected between 3 and 7 years before the most recent survey are considered. The final year refers to the most recent survey available between 2011 and 2015. Growth rates for Iraq are based on survey means of 2005 PPP$. The coverage and quality of the 2011 PPP price data for Iraq and most other North African and Middle Eastern countries were hindered by the exceptional period of instability they faced at the time of the 2011 exercise of the International Comparison Program. See PovcalNet for detailed explanations.; ; World Bank, Global Database of Shared Prosperity (GDSP) circa 2010-2015 (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).; ; The comparability of welfare aggregates (consumption or income) for the chosen years T0 and T1 is assessed for every country. If comparability across the two surveys is a major concern for a country, the selection criteria are re-applied to select the next best survey year(s). Annualized growth rates are calculated between the survey years, using a compound growth formula. The survey years defining the period for which growth rates are calculated and the type of welfare aggregate used to calculate the growth rates are noted in the footnotes.

Since the mid-1980s, Member States of the WHO European Region have been reporting essential health-related statistics to the Health for All (HFA) family of databases, making it one of WHO’s oldest sources of data. As it is based on reported data, rather than estimates, the HFA family of databases is also particularly valuable.

HFA databases bring together the indicators that are part of major monitoring frameworks relevant to the Region, such as Health 2020 and the Sustainable Development Goals. The indicators cover basic demographics, health status, health determinants and risk factors, as well as health care resources, expenditures and more.

HFA databases allow access to regional, national and some subnational indicators and metadata, which are visualized through interactive online tools in the Health for All explorer. Data, metadata, graphs and maps can be exported or shared online and on social media.

This dataset presents the annual data on monthly average number of recipients of daily unemployment insurance allowances (UI), invalidity insurance pensions (II) and social assistance (SA), in absolute numbers and percentages, by benefit, gender, age group and nationality (Swiss/foreigners), since 2010. Descriptions of the variables in the CSV file are available in the Appendix.

The dataset contains current data on low rent and Section 8 units in PHA's administered by HUD. The Section 8 Rental Voucher Program increases affordable housing choices for very low-income households by allowing families to choose privately owned rental housing. Through the Section 8 Rental Voucher Program, the administering housing authority issues a voucher to an income-qualified household, which then finds a unit to rent. If the unit meets the Section 8 quality standards, the PHA then pays the landlord the amount equal to the difference between 30 percent of the tenant's adjusted income (or 10 percent of the gross income or the portion of welfare assistance designated for housing) and the PHA-determined payment standard for the area. The rent must be reasonable compared with similar unassisted units.

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.

The Social Security Rate in Barbados stands at 23.85 percent. This dataset provides - Barbados Social Security Rate- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Poverty and low-income statistics by visible minority group, Indigenous group and immigration status, Canada and provinces.

Abstract

The National Family Health Survey 2019-21 (NFHS-5), the fifth in the NFHS series, provides information on population, health, and nutrition for India, each state/union territory (UT), and for 707 districts.

The primary objective of the 2019-21 round of National Family Health Surveys is to provide essential data on health and family welfare, as well as data on emerging issues in these areas, such as levels of fertility, infant and child mortality, maternal and child health, and other health and family welfare indicators by background characteristics at the national and state levels. Similar to NFHS-4, NFHS-5 also provides information on several emerging issues including perinatal mortality, high-risk sexual behaviour, safe injections, tuberculosis, noncommunicable diseases, and the use of emergency contraception.

The information collected through NFHS-5 is intended to assist policymakers and programme managers in setting benchmarks and examining progress over time in India’s health sector. Besides providing evidence on the effectiveness of ongoing programmes, NFHS-5 data will help to identify the need for new programmes in specific health areas.

The clinical, anthropometric, and biochemical (CAB) component of NFHS-5 is designed to provide vital estimates of the prevalence of malnutrition, anaemia, hypertension, high blood glucose levels, and waist and hip circumference, Vitamin D3, HbA1c, and malaria parasites through a series of biomarker tests and measurements.

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Children age 0-5
• Woman age 15-49
• Man age 15 to 54

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49, all men age 15-54, and all children aged 0-5 resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

A uniform sample design, which is representative at the national, state/union territory, and district level, was adopted in each round of the survey. Each district is stratified into urban and rural areas. Each rural stratum is sub-stratified into smaller substrata which are created considering the village population and the percentage of the population belonging to scheduled castes and scheduled tribes (SC/ST). Within each explicit rural sampling stratum, a sample of villages was selected as Primary Sampling Units (PSUs); before the PSU selection, PSUs were sorted according to the literacy rate of women age 6+ years. Within each urban sampling stratum, a sample of Census Enumeration Blocks (CEBs) was selected as PSUs. Before the PSU selection, PSUs were sorted according to the percentage of SC/ST population. In the second stage of selection, a fixed number of 22 households per cluster was selected with an equal probability systematic selection from a newly created list of households in the selected PSUs. The list of households was created as a result of the mapping and household listing operation conducted in each selected PSU before the household selection in the second stage. In all, 30,456 Primary Sampling Units (PSUs) were selected across the country in NFHS-5 drawn from 707 districts as on March 31st 2017, of which fieldwork was completed in 30,198 PSUs.

For further details on sample design, see Section 1.2 of the final report.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Four survey schedules/questionnaires: Household, Woman, Man, and Biomarker were canvassed in 18 local languages using Computer Assisted Personal Interviewing (CAPI).

Cleaning operations

Electronic data collected in the 2019-21 National Family Health Survey were received on a daily basis via the SyncCloud system at the International Institute for Population Sciences, where the data were stored on a password-protected computer. Secondary editing of the data, which required resolution of computer-identified inconsistencies and coding of open-ended questions, was conducted in the field by the Field Agencies and at the Field Agencies central office, and IIPS checked the secondary edits before the dataset was finalized.

Field-check tables were produced by IIPS and the Field Agencies on a regular basis to identify certain types of errors that might have occurred in eliciting information and recording question responses. Information from the field-check tables on the performance of each fieldwork team and individual investigator was promptly shared with the Field Agencies during the fieldwork so that the performance of the teams could be improved, if required.

Response rate

A total of 664,972 households were selected for the sample, of which 653,144 were occupied. Among the occupied households, 636,699 were successfully interviewed, for a response rate of 98 percent.

In the interviewed households, 747,176 eligible women age 15-49 were identified for individual women’s interviews. Interviews were completed with 724,115 women, for a response rate of 97 percent. In all, there were 111,179 eligible men age 15-54 in households selected for the state module. Interviews were completed with 101,839 men, for a response rate of 92 percent.

this graph was created in R,PowerBi and Tableau:

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The elderly population refers to the portion of a country's inhabitants who are aged 65 and older. This demographic plays a crucial role in various economic and social analyses, especially when it comes to determining the dependent population. The dependent population consists of those individuals who do not actively participate in the workforce and, as a result, rely on others for essential goods and services. This group primarily includes both the elderly and the youth (typically under 15 years of age).

The concept of the elderly dependency ratio is a significant measure used to understand the burden on the working-age population, which consists of those between the ages of 15 and 64. This ratio is calculated by comparing the number of elderly people to those of working age. A higher elderly dependency ratio indicates a larger proportion of elderly individuals relative to those who are contributing economically, leading to increased demands on social systems such as healthcare, pensions, and other support services.

These demographic shifts have widespread implications for both government policies and private sectors. As the elderly population increases, so too does the pressure on pension systems and healthcare services, necessitating reforms to ensure sustainability. Additionally, the aging population affects broader economic growth and welfare, as fewer people of working age contribute to economic productivity, potentially slowing overall economic expansion.

This indicator, often measured as a percentage of the total population, provides valuable insights into the aging trends within a society and their potential impact on the economy, welfare, and social structures. Understanding these trends is essential for shaping future policies that address the needs of an aging population while maintaining economic stability and growth.

In 2005, BPS do the Social Economic Colletion (PSE05), which aims to get the data in the form of micro poverty households directory that deserves a direct cash assistance (BLT) in 2005-2006. Given the data turns PSE05 considered better results compared to a database available in local government. Nevertheless, it is recognized that the data from PSE05 not perfect. The study of 56 universities found the data from PSE05 still contains 8 percent and 22.36 percent error inclusion exclusion error (Coordinating Minister for People's Welfare 2005). In addition to BLT program, data PSE05 also used in targeting households on several national programs, such as the Health Insurance of the Poor (HIP) and cheap rice program for the poor (Raskin). These programs succeeded in reducing poverty levels, poor households proved as much 17.8 percent in 2006 down to 15.4 percent in 2008. But be aware that the collection PSE05 an activity that is great for BPS, BPS so many other activities are pending at this time. After PSE05 activities, in 2007 the BPS also conducted the data collection for the household conditional direct cash assistance program (Family Hope Program / PKH) in 2007. The collection of data to support this program called Basic Health Care Survey and Education 2007 (SPDKP07). Results from SPDKP07 considered much better than the data from PSE05 because only less inclusion and exclusion errors of his. This is because SPDKP07 implemented only in 953 districts / cities were selected and a much larger budget.

Iran IR: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate data was reported at 1.250 % in 2014. Iran IR: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate data is updated yearly, averaging 1.250 % from Dec 2014 (Median) to 2014, with 1 observations. Iran IR: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Iran – Table IR.World Bank: Poverty. The growth rate in the welfare aggregate of the bottom 40% is computed as the annualized average growth rate in per capita real consumption or income of the bottom 40% of the population in the income distribution in a country from household surveys over a roughly 5-year period. Mean per capita real consumption or income is measured at 2011 Purchasing Power Parity (PPP) using the PovcalNet (http://iresearch.worldbank.org/PovcalNet). For some countries means are not reported due to grouped and/or confidential data. The annualized growth rate is computed as (Mean in final year/Mean in initial year)^(1/(Final year - Initial year)) - 1. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported. The initial year refers to the nearest survey collected 5 years before the most recent survey available, only surveys collected between 3 and 7 years before the most recent survey are considered. The final year refers to the most recent survey available between 2011 and 2015. Growth rates for Iraq are based on survey means of 2005 PPP$. The coverage and quality of the 2011 PPP price data for Iraq and most other North African and Middle Eastern countries were hindered by the exceptional period of instability they faced at the time of the 2011 exercise of the International Comparison Program. See PovcalNet for detailed explanations.; ; World Bank, Global Database of Shared Prosperity (GDSP) circa 2010-2015 (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).; ; The comparability of welfare aggregates (consumption or income) for the chosen years T0 and T1 is assessed for every country. If comparability across the two surveys is a major concern for a country, the selection criteria are re-applied to select the next best survey year(s). Annualized growth rates are calculated between the survey years, using a compound growth formula. The survey years defining the period for which growth rates are calculated and the type of welfare aggregate used to calculate the growth rates are noted in the footnotes.