The estimated median household income and estimated median family income are two separate measures: every family is a household, but not every household is a family. According to the U.S. Census Bureau definitions of the terms, a family “includes a householder and one or more people living in the same household who are related to the householder by birth, marriage, or adoption,”[1] while a household “includes all the people who occupy a housing unit,” including households of just one person[2]. When evaluated together, the estimated median household income and estimated median family income provide a thorough picture of household-level economics in Champaign County.

Both estimated median household income and estimated median family income were higher in 2023 than in 2005. The changes in estimated median household income and estimated median family income between 2022 and 2023 were not statistically significant. Estimated median family income is consistently higher than estimated median household income, largely due to the definitions of each term, and the types of household that are measured and are not measured in each category.

Median income data was sourced from the U.S. Census Bureau’s American Community Survey (ACS) 1-Year Estimates, which are released annually.

As with any datasets that are estimates rather than exact counts, it is important to take into account the margins of error (listed in the column beside each figure) when drawing conclusions from the data.

Due to the impact of the COVID-19 pandemic, instead of providing the standard 1-year data products, the Census Bureau released experimental estimates from the 1-year data. This includes a limited number of data tables for the nation, states, and the District of Columbia. The Census Bureau states that the 2020 ACS 1-year experimental tables use an experimental estimation methodology and should not be compared with other ACS data. For these reasons, and because data is not available for Champaign County, no data for 2020 is included in this Indicator.

For interested data users, the 2020 ACS 1-Year Experimental data release includes datasets on Median Household Income in the Past 12 Months (in 2020 Inflation-Adjusted Dollars) and Median Family Income in the Past 12 Months (in 2020 Inflation-Adjusted Dollars).

[1] U.S. Census Bureau. (Date unknown). Glossary. “Family Household.” (Accessed 19 April 2016).

[2] U.S. Census Bureau. (Date unknown). Glossary. “Household.” (Accessed 19 April 2016).

Sources: U.S. Census Bureau; American Community Survey, 2023 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using data.census.gov; (17 October 2024).; U.S. Census Bureau; American Community Survey, 2022 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using data.census.gov; (18 September 2023).; U.S. Census Bureau; American Community Survey, 2021 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using data.census.gov; (3 October 2022).; U.S. Census Bureau; American Community Survey, 2019 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using data.census.gov; (7 June 2021).; U.S. Census Bureau; American Community Survey, 2018 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using data.census.gov; (7 June 2021).;U.S. Census Bureau; American Community Survey, 2017 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (13 September 2018).; U.S. Census Bureau; American Community Survey, 2016 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (14 September 2017).; U.S. Census Bureau; American Community Survey, 2015 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (19 September 2016).; U.S. Census Bureau; American Community Survey, 2014 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2013 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2012 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2011 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2010 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2009 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2008 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2007 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2006 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (16 March 2016).; U.S. Census Bureau; American Community Survey, 2005 American Community Survey 1-Year Estimates, Table S1903; generated by CCRPC staff; using American FactFinder; (16 March 2016).

VITAL SIGNS INDICATOR
Poverty (EQ5)

FULL MEASURE NAME
The share of the population living in households that earn less than 200 percent of the federal poverty limit

LAST UPDATED
January 2023

DESCRIPTION
Poverty refers to the share of the population living in households that earn less than 200 percent of the federal poverty limit, which varies based on the number of individuals in a given household. It reflects the number of individuals who are economically struggling due to low household income levels.

DATA SOURCE
U.S Census Bureau: Decennial Census - http://www.nhgis.org
1980-2000

U.S. Census Bureau: American Community Survey - https://data.census.gov/
2007-2021
Form C17002

CONTACT INFORMATION
vitalsigns.info@mtc.ca.gov

METHODOLOGY NOTES (across all datasets for this indicator)
The U.S. Census Bureau defines a national poverty level (or household income) that varies by household size, number of children in a household, and age of householder. The national poverty level does not vary geographically even though cost of living is different across the United States. For the Bay Area, where cost of living is high and incomes are correspondingly high, an appropriate poverty level is 200% of poverty or twice the national poverty level, consistent with what was used for past equity work at MTC and ABAG. For comparison, however, both the national and 200% poverty levels are presented.

For Vital Signs, the poverty rate is defined as the number of people (including children) living below twice the poverty level divided by the number of people for whom poverty status is determined. The household income definitions for poverty change each year to reflect inflation. The official poverty definition uses money income before taxes and does not include capital gains or non-cash benefits (such as public housing, Medicaid and food stamps).

For the national poverty level definitions by year, see: US Census Bureau Poverty Thresholds - https://www.census.gov/data/tables/time-series/demo/income-poverty/historical-poverty-thresholds.html.

For an explanation on how the Census Bureau measures poverty, see: How the Census Bureau Measures Poverty - https://www.census.gov/topics/income-poverty/poverty/guidance/poverty-measures.html.

American Community Survey (ACS) 1-year data is used for larger geographies – Bay counties and most metropolitan area counties – while smaller geographies rely upon 5-year rolling average data due to their smaller sample sizes. Note that 2020 data uses the 5-year estimates because the ACS did not collect 1-year data for 2020.

To be consistent across metropolitan areas, the poverty definition for non-Bay Area metros is twice the national poverty level. Data were not adjusted for varying income and cost of living levels across the metropolitan areas.

For information on economic census geographies, including changes for 2012, see the economic census Help Center..Includes only establishments of firms with payroll. See Table Notes for more information. Data based on the 2012 Economic Census. For information on confidentiality protection, sampling error, nonsampling error, and definitions, see Methodology..Table NameFinance and Insurance: Subject Series - Misc Subjects: Credit Card Services Income by Selected Industries for the U.S.: 2012ReleaseScheduleThe data in this file are scheduled for release in June 2016.Key TableInformationSee Methodology. for information on data limitations.UniverseThe universe of this file is all establishments of firms with payroll in business at any time during 2012 and classified in Finance and Insurance (Sector 52).GeographyCoverageThe data are shown at the United States level only.IndustryCoverageThe data are shown for selected 5- through 7-digit 2012 NAICS codes.Data ItemsandOtherIdentifyingRecordsThis file contains data on:. Establishments. Revenue. Distribution of credit card services income.Each record includes an INCCCARD code which represents a specific source of credit card services income category.FTP DownloadDownload the entire table athttps://www2.census.gov/econ2012/EC/sector52/EC1252SXSB06.zipContactInformation. U.S. Census Bureau, Economy Wide Statistics Division. Data User Outreach and Education Staff. Washington, DC 20233-6900. Tel: (800) 242-2184. Tel: (301) 763-5154. ewd.outreach@census.gov. . .Symbols:D - Withheld to avoid disclosing data for individual companies; data are included in higher level totalsN - Not available or not comparableFor a complete list of all economic programs symbols, see the Symbols Glossary.Source: U.S. Census Bureau, 2012 Economic Census.Note: The data in this file are based on the 2012 Economic Census. To maintain confidentiality, the U.S. Census Bureau suppresses data to protect the identity of any business or individual. The census results in this file contain sampling and nonsampling error. Data users who create their own estimates using data from this file should cite the U.S. Census Bureau as the source of the original data only. For the full technical documentation, see Methodology link in above headnote.

The Alberta Savings Trust Fund (Heritage Fund) is Alberta’s main long-term savings fund, producing income to support government programs essential to Albertans. This document contains definitions of commonly used terms related to the Heritage Fund.

For information on economic census geographies, including changes for 2012, see the economic census Help Center..Includes only establishments of firms with payroll. See Table Notes for more information. Data based on the 2012 Economic Census. For information on confidentiality protection, sampling error, nonsampling error, and definitions, see Methodology..Table Name Finance and Insurance: Subject Series - Misc Subjects: Brokering or Dealing Services Income by Selected Industries for the U.S.: 2012ReleaseScheduleThe data in this file are scheduled for release in June 2016.Key TableInformationSee Methodology. for information on data limitations.UniverseThe universe of this file is all establishments of firms with payroll in business at any time during 2012 and classified in Finance and Insurance (Sector 52).GeographyCoverageThe data are shown at the United States level only.IndustryCoverageThe data are shown for selected 6-digit 2012 NAICS codes.Data ItemsandOtherIdentifyingRecordsThis file contains data on:. Establishments. Revenue. Distribution of brokering or dealing services income.Each record includes an INCBORD code which represents a specific brokering or dealing services income category.FTP DownloadDownload the entire table athttps://www2.census.gov/econ2012/EC/sector52/EC1252SXSB09.zipContactInformation. U.S. Census Bureau, Economy Wide Statistics Division. Data User Outreach and Education Staff. Washington, DC 20233-6900. Tel: (800) 242-2184. Tel: (301) 763-5154. ewd.outreach@census.gov. . .Symbols:D - Withheld to avoid disclosing data for individual companies; data are included in higher level totalsN - Not available or not comparableFor a complete list of all economic programs symbols, see the Symbols Glossary.Source: U.S. Census Bureau, 2012 Economic Census.Note: The data in this file are based on the 2012 Economic Census. To maintain confidentiality, the U.S. Census Bureau suppresses data to protect the identity of any business or individual. The census results in this file contain sampling and nonsampling error. Data users who create their own estimates using data from this file should cite the U.S. Census Bureau as the source of the original data only. For the full technical documentation, see Methodology link in above headnote.

BackgroundIncome composition is highly associated with individual financial sustainability and income inequality at the macro level. Although studies have investigated the effects of disability on wage income, few studies have investigated the effects of disability on income composition or on various types of income other than wage income.MethodsWe sampled 72,000 households using tax data sourced from the Taiwan Ministry of Finance in 2015. Data for each household member were traced back to 1999. We identified 23,346 individuals with disabilities and matched them with 34,145 individuals without disabilities. Eight income types were identified. A two-way fixed-effect analysis was performed to determine the effects of disability on changes in each income type. Fractional probit models were estimated to determine the effects of disability on the proportion of each income type in total income at different ages.ResultsWage income constitutes the largest proportion of income in Taiwan. The total income is estimated to increase by 10.4% (P < 0.001) after disability onset. Moreover, most income categories did not experience a decline following the onset of disability. We also noted a significant interaction effect between disability status and age on the proportion of each income type in total income.ConclusionThe effect of disability on income varied across different sources of income. The income composition observed for the individuals with disabilities changed considerably at various ages. Accordingly, policies should be designed to ensure long-term sustainability of income sources for individuals with disabilities.

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.

VITAL SIGNS INDICATOR
Poverty (EQ5)

FULL MEASURE NAME
The share of the population living in households that earn less than 200 percent of the federal poverty limit

LAST UPDATED
January 2023

DESCRIPTION
Poverty refers to the share of the population living in households that earn less than 200 percent of the federal poverty limit, which varies based on the number of individuals in a given household. It reflects the number of individuals who are economically struggling due to low household income levels.

DATA SOURCE
U.S Census Bureau: Decennial Census - http://www.nhgis.org
1980-2000

U.S. Census Bureau: American Community Survey - https://data.census.gov/
2007-2021
Form C17002

CONTACT INFORMATION
vitalsigns.info@mtc.ca.gov

METHODOLOGY NOTES (across all datasets for this indicator)
The U.S. Census Bureau defines a national poverty level (or household income) that varies by household size, number of children in a household, and age of householder. The national poverty level does not vary geographically even though cost of living is different across the United States. For the Bay Area, where cost of living is high and incomes are correspondingly high, an appropriate poverty level is 200% of poverty or twice the national poverty level, consistent with what was used for past equity work at MTC and ABAG. For comparison, however, both the national and 200% poverty levels are presented.

For Vital Signs, the poverty rate is defined as the number of people (including children) living below twice the poverty level divided by the number of people for whom poverty status is determined. The household income definitions for poverty change each year to reflect inflation. The official poverty definition uses money income before taxes and does not include capital gains or non-cash benefits (such as public housing, Medicaid and food stamps).

For the national poverty level definitions by year, see: US Census Bureau Poverty Thresholds - https://www.census.gov/data/tables/time-series/demo/income-poverty/historical-poverty-thresholds.html.

For an explanation on how the Census Bureau measures poverty, see: How the Census Bureau Measures Poverty - https://www.census.gov/topics/income-poverty/poverty/guidance/poverty-measures.html.

American Community Survey (ACS) 1-year data is used for larger geographies – Bay counties and most metropolitan area counties – while smaller geographies rely upon 5-year rolling average data due to their smaller sample sizes. Note that 2020 data uses the 5-year estimates because the ACS did not collect 1-year data for 2020.

To be consistent across metropolitan areas, the poverty definition for non-Bay Area metros is twice the national poverty level. Data were not adjusted for varying income and cost of living levels across the metropolitan areas.

Croatia Household and NPISH: Compensation of Employees Received by Households data was reported at 270.625 HRK bn in 2024. This records an increase from the previous number of 257.790 HRK bn for 2023. Croatia Household and NPISH: Compensation of Employees Received by Households data is updated yearly, averaging 161.546 HRK bn from Dec 1995 (Median) to 2024, with 30 observations. The data reached an all-time high of 270.625 HRK bn in 2024 and a record low of 53.654 HRK bn in 1995. Croatia Household and NPISH: Compensation of Employees Received by Households data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Croatia – Table HR.OECD.EO: Household Sector Account: Forecast: Non OECD Member: Annual. WSSH-Compensation of employees received by households Compemsation of employees in the context of the allocation of primary income account received by the households Compensation of employees: http://stats.oecd.org/glossary/detail.asp?ID=396 Primary Income Account: http://stats.oecd.org/glossary/detail.asp?ID=93

For information on economic census geographies, including changes for 2012, see the economic census Help Center..Table Name Finance and Insurance: Subject Series - Misc Subjects: Brokering and Dealing Services Income by Selected Industries for the U.S.: 2012ReleaseScheduleThe data in this file are scheduled for release in June 2016.Key TableInformationSee Methodology. for information on data limitations.UniverseThe universe of this file is all establishments of firms with payroll in business at any time during 2012 and classified in Finance and Insurance (Sector 52).GeographyCoverageThe data are shown at the United States level only.IndustryCoverageThe data are shown for selected 5- through 7-digit 2012 NAICS codes.Data ItemsandOtherIdentifyingRecordsThis file contains data on:. Establishments. Revenue. Distribution of brokering and dealing services income.Each record includes an INCBAND code which represents a specific brokering and dealing services income category.FTP DownloadDownload the entire table athttps://www2.census.gov/econ2012/EC/sector52/EC1252SXSB08.zipContactInformation. U.S. Census Bureau, Economy Wide Statistics Division. Data User Outreach and Education Staff. Washington, DC 20233-6900. Tel: (800) 242-2184. Tel: (301) 763-5154. ewd.outreach@census.gov. . .Includes only establishments of firms with payroll. See Table Notes for more information. Data based on the 2012 Economic Census. For information on confidentiality protection, sampling error, nonsampling error, and definitions, see Methodology..Symbols:D - Withheld to avoid disclosing data for individual companies; data are included in higher level totalsN - Not available or not comparableFor a complete list of all economic programs symbols, see the Symbols Glossary.Source: U.S. Census Bureau, 2012 Economic Census.Note: The data in this file are based on the 2012 Economic Census. To maintain confidentiality, the U.S. Census Bureau suppresses data to protect the identity of any business or individual. The census results in this file contain sampling and nonsampling error. Data users who create their own estimates using data from this file should cite the U.S. Census Bureau as the source of the original data only. For the full technical documentation, see Methodology link in above headnote.

Global Medical Terminology Sharing market size 2025 was XX Million. Medical Terminology Sharing Industry compound annual growth rate (CAGR) will be XX% from 2025 till 2033.

This filtered view provides annual personal income estimates for State of Iowa counties produced by the U.S. Bureau of Economic Analysis for the most recent year reported. Data includes the following estimates: personal income and per capita personal income.

Personal income is defined as the sum of wages and salaries, supplements to wages and salaries, proprietors’ income, dividends, interest, and rent, and personal current transfer receipts, less contributions for government social insurance. Personal income is the income received by, or on behalf of all persons residing in the Iowa county, regardless of the duration of residence, except for foreign nationals employed by their home governments in Iowa. Per capita personal income is personal income divided by the Census Bureau’s annual midyear (July 1) population estimates for the county.

More terms and definitions are available on https://apps.bea.gov/regional/definitions/.

According to Cognitive Market Research, the global Medical Terminology Software market size is USD 1.5 billion in 2024 and will expand at a compound annual growth rate (CAGR) of 19.2% from 2024 to 2031. Market Dynamics of Medical Terminology Software Market

Key Drivers for Medical Terminology Software Market

Healthcare organizations' terminology content is characterized by disparity and fragmentation- At present, healthcare ecosystems are highly fragmented in terms of infrastructure and content. A health delivery organization may oversee 40 or more distinct IT systems, each of which has its own clinical terminology content and infrastructure. Organizations are unable to capitalize on isolated clinical data as a result of these terminology divisions, which has an impact on downstream activities, including data analytics. The issue is further exacerbated when a health system endeavors to exchange data with other healthcare partners. The pertinent data is dispersed across numerous healthcare organizations in a multitude of isolated systems in that scenario. A significant impediment to national initiatives to enhance interoperability, full disclosure, and collaboration within the healthcare system is the absence of a unified clinical vocabulary across a multitude of independent systems.
Governmental initiatives to promote the adoption of health care information technology is anticipated to drive the Medical Terminology Software market's expansion in the years ahead.

Key Restraints for Medical Terminology Software Market

Lack of enthusiasm for employing terminology solutions in lieu of conventional methods poses a serious threat to the Medical Terminology Software industry.
The market also faces significant difficulties related to IT infrastructure constraints in developing nations.

Introduction of the Medical Terminology Software Market

Around the globe, there is a significant growth in the demand for medical terminology software to facilitate proper patient treatment and reduce healthcare errors. It facilitates the management of patient records in healthcare facilities, and it is extensively employed in clinical trials, insurance claims and payments, and public health monitoring, among other applications. In order to save patients' lives, the market is attributed to be driven by the increasing demand for medical terminology solutions in hospitals worldwide, which are used to organize patient data, reduce medical mistakes, and retain extensive healthcare information. In addition, the global market's expansion in the years ahead would be facilitated by numerous government initiatives that are promoting the implementation of HCIT to improve clinical data operations.

The data proposed here correspond to the number of beneficiaries and aid expenditure of the Personalised Home Autonomy Allowance (APAD), paid for the year 2023, by GIR (Iso-resource group, which is a scale for assessing the dependency of the person) and by canton of the municipality of the emergency home. IRMs shall correspond to the following degrees of loss of autonomy: Gir: Iso-resources group | Degrees of dependency ---|--- Gir 1 | A person confined to bed or chair, whose mental functions are severely impaired and who requires an indispensable and continuous presence of intervenors Gir 2 | · A person confined to bed or chair, whose mental functions are not totally impaired and whose condition requires care for most activities of everyday life Person whose mental functions are impaired, who is able to move, but who requires constant monitoring Gir 3 | Person who has retained all or part of his mental autonomy, partially his locomotor autonomy, but who needs daily and several times a day help with body care Gir 4 | Either someone who does not take care of his transfers alone but who, once lifted, can move inside his housing, but who needs help for the toilet and dressing · Either someone who does not have locomotor problems, but who needs help with body care and meals APAD is an allowance for people aged 60 and over with loss of autonomy (see also glossary in metadata). There are no income conditions to benefit from it but the amount allocated depends on the level of income. Metadata Link to metadata Additional resources * Data DREES website: DREES (Directorate for Research, Studies, Evaluation and Statistics) is a directorate of the central administration of the Ministries of Health and Social Affairs. Its website offers, under the disability and invalidity tab, data on departmental social assistance expenditure under the Personalised Independence Allowance (APA), including APA at home, by department, since 1999. * Service-public.fr website: https://www.service-public.fr/individuals/your rights/F10009 The "Public Service" website is the official website of the French administration, the single portal for administrative intelligence and access to online services, created in partnership with national and local administrations. It offers various information on APA at home (see glossary) and a simulator for calculating the amount remaining to be borne after deduction of public aid for accommodation in EHPAD (APA in institutions, see glossary) * Website for the elderly.gouv.fr: https://www.pour-les-personnes-agees.gouv.fr/preserver-son-autonomie-s-informer-et-anticiper/perte-d-autonomie-evaluation-et-droits/lallocation-personnalisee-dautonomie-apa The ‘for the elderly’ website is the government’s national information and guidance portal for elderly people with loss of autonomy and their relatives. It offers various information relating to the APA (access conditions, etc.). * Website of the Seine-Maritime Department: and https://www.seinemaritime.fr/docs/plaquette-apa.pdf The website "Seine-Maritime.fr" is the official website of the Department of Seine-Maritime. It offers various downloadable forms relating to the APA (first application, renewal, etc.). It also offers for download a brochure presenting the APA published by the Seine-Maritime Department.

This table contains data on the revenue and expenditure, the balance of claims and the operating balance of the general government sector. In addition, some additional data on income and expenditure are presented (memorandum items). The terms used are in line with the National Accounts. The National Accounts are based on the international definitions of the European System of Accounts (ESA 2010). To increase the accessibility of the table, in some cases common definitions of income and expenditure categories are used instead of the terms from the National Accounts. The relevant National Accounts term is then mentioned in the notes. The data presented corresponds to the publications on the National Accounts. There may be minor temporary differences with the publications of the National Accounts due to the fact that the published figures of the government accounts are sometimes more current.

The data in this table have been consolidated, i.e. the elimination of flows between them. As a result, the expenditure and revenues of the subsectors do not add up to the total expenditure and revenue of the general government. Payments from, for example, the empire to the municipalities are part of the government’s expenditure and the income of municipalities. They do not count for the expenditure and revenue of the general government, because they are payments from the government to the government.

Data available from: Annual figures from 1995 to 2017, quarterly figures from 1999 to 2017.

Status of the figures: The figures in this table are definitive for the period 1995-2014. The quarters of 2015 have the status for now. The 2015 annual figures are final. The 2016 and 2017 figures have the status for now. As this table has been discontinued, the data will no longer be definitive.

Changes as of 6 July 2018: None, this table has been discontinued.

When are new figures coming? No longer applicable. This table is followed by Government revenue; transactions and public sectors and public expenditure; transactions and public sectors. See paragraph 3.

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 …Show full descriptionThe 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. Local Government Area has been updated to reflect the Australian Statistical Geography Standard (ASGS) 2020 boundaries from March 2021. Commonwealth Electorate Division has been updated to reflect the Australian Statistical Geography Standard (ASGS) 2018 boundaries from March 2019. SA2 has been updated to reflect the Australian Statistical Geography Standard (ASGS) 2016 boundaries from March 2019. Prior to this Australian Statistical Geography Standard (ASGS) 2011 was used. 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: 2016 SA2 2011 SA2 2018 Commonwealth Electoral Division 2016 Commonwealth Electoral Division 2013 Commonwealth Electoral Division 2020 Local Government Area 2018 Local Government Area 2014 Local Government Area 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 Occasional Paper series, Numbers 1 & 7 Concession card data in the March and June 2020 quarters have been re-stated to address an over-count in reported cardholder numbers.

The Annual Statistical Supplement, 2015 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than 250 statistical tables convey a wide range of information about those programs from beneficiary counts and benefit amounts to the status of the trust funds. The tables also contain data on Medicare, Medicaid, veterans' benefits, and other related income security programs. The Supplement also includes summaries of the history of the major programs and of current legislative developments and a glossary of terms used in explaining the programs and data.

Children living in households with income below the national poverty line