The file contains the following information Section Desc Sub Section Desc ADP NO Project Name

This report to Congress provides information on the performance of states on seven national outcome categories and also includes data on contextual factors and findings of analyses conducted across states.

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Executive Summary

Contextual Factors

State Performance on Outcome Measures

Conclusion and Recommendations for Further Investigation

Child Welfare Outcomes Data Site

Introduction to the Child Welfare Outcomes, Data, and Analysis

Outcome Measures

Context Data

Data Sources

Data Analyses in the Report

The Child Welfare Outcomes Report Data Site

Chapter 1: Child Welfare Outcomes Demographic Data

National Child Population

Children in Foster Care

Foster Care Entry Rates

Children Waiting for Adoption and Children Adopted

Summary

Chapter 2: Keeping Children Safe

Child Victims and Child Fatalities

Range of State Performance on Safety-Related Outcome Measures

Changes Over Time in State Performance on Measures of Maltreatment Recurrence and Maltreatment of Children in Foster Care

Summary of Findings Regarding Keeping Children Safe

Chapter 3: Finding Permanent Homes for Children in Foster Care

Range of Performance in Achieving Permanency for Children in Foster Care

Changes Over Time in State Performance on Measures of Achieving Permanency

Summary of Findings Regarding Achieving Permanency for Children in Foster Care

Chapter 4: Achieving Timely Reunifications and Adoptions for Children in Foster Care

Caseworker Visits

Timeliness of Reunifications

Changes Over Time in State Performance With Regard to Achieving Timely Reunifications

Timeliness of Adoptions

Changes Over Time in State Performance With Regard to Timeliness of Adoptions

Summary of Findings Regarding Achieving Reunifications and Adoptions in a Timely Manner

Chapter 5: Achieving Stable and Appropriate Placement Settings for Children in Foster Care

Changes Over Time in State Performance on Measures of Achieving Stable and Appropriate Placement Settings for Children in Foster Care

Summary of Findings Regarding Achieving Stable and Appropriate Placements for Children in Foster Care

Chapter 6: State Comments on Performance Relevant to the Seven National Child Welfare Outcomes

Appendix A: Adoption and Safe Families Act of 1997 (Pub. L. 105—89)

Appendix B: Child Welfare Outcomes Report: Outcomes and Measures

Appendix C: Caseworker Visits

Appendix D: Child Welfare Outcomes Report: Data Sources and Elements

Appendix E: Child Maltreatment 2017: Summary of Key Findings

Appendix F: The AFCARS Report: FY 2017 Estimates

Appendix G: Data-Quality Criteria

Metadata-only record linking to the original dataset. Open original dataset below.

Since 2015, the number of recipients of social welfare in Sweden has decreased steadily. Whereas more than 415,000 people received social welfare in Sweden in 2015, it had sunk below 300,000 in 2022. However, even though the total number of recipients has decreased, the value of the total benefits has increased since 2017.

To help people reach a reasonable standard of living

The social welfare benefits in Sweden are administered by the National Board of Health and Welfare (Socialstyrelsen in Swedish). The aim of the benefits is to help people in need to reach a reasonable standard of living through monthly benefits. The amount of the average monthly payment was around 9,100 Swedish kronor in 2022.

 Benefits in foreign and Swedish households

Looking at households with Swedish-born and foreign-born citizens, the most common group of recipients was Swedish-born single men living without children. However, when looking at couples with children, far more foreign-born citizens received social benefits.

The file contains the following information Department District Department Item Description (Basic Pay, Housing Rent, Medical Charges etc)

Laos LA: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: 2017 PPP per day data was reported at 2.900 Intl $/Day in 2018. This records an increase from the previous number of 2.580 Intl $/Day for 2012. Laos LA: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: 2017 PPP per day data is updated yearly, averaging 2.740 Intl $/Day from Dec 2012 (Median) to 2018, with 2 observations. The data reached an all-time high of 2.900 Intl $/Day in 2018 and a record low of 2.580 Intl $/Day in 2012. Laos LA: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: 2017 PPP per day data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Laos – Table LA.World Bank.WDI: Social: Poverty and Inequality. Mean consumption or income per capita (2017 PPP $ per day) of the bottom 40%, used in calculating the growth rate in the welfare aggregate of the bottom 40% of the population in the income distribution in a country.;World Bank, Global Database of Shared Prosperity (GDSP) (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).;;The choice of consumption or income for a country is made according to which welfare aggregate is used to estimate extreme poverty in the Poverty and Inequality Platform (PIP). The practice adopted by the World Bank for estimating global and regional poverty is, in principle, to use per capita consumption expenditure as the welfare measure wherever available; and to use income as the welfare measure for countries for which consumption is unavailable. However, in some cases data on consumption may be available but are outdated or not shared with the World Bank for recent survey years. In these cases, if data on income are available, income is used. Whether data are for consumption or income per capita is noted in the footnotes. Because household surveys are infrequent in most countries and are not aligned across countries, comparisons across countries or over time should be made with a high degree of caution.

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

Abstract

Iraq successfully conducted two rounds of Integrated Household Socioeconomic Survey (IHSES), nationally representative multi-topic budget surveys, in 2007 and 2012. The surveys allowed an analysis of a range of socio-economic indicators and the estimation of poverty trends. To provide more frequent poverty estimates, Continuous Household Survey (CHS) was implemented in 2014 on a sub-sample of IHSES clusters. However, the fieldwork was disrupted in the summer of 2014 in some parts of the country due to the deterioration in the security situation. The third round of IHSES, planned for 2017, could not take place on time as well. At the same time, the ongoing security and budget crises made it more important than ever to monitor key socio-economic indicators. The objective of the 2017 rapid welfare monitoring survey (SWIFT) was to provide interim estimates of welfare and well-being until another survey comparable in scope and coverage to IHSES could be fielded.

Geographic coverage

Although the security situation had improved since 2014, many parts of the country were still insecure 2017. Thus, nine out of ten districts in Nineveh governorate, the seat of Daesh-occupied Iraq, were intentionally excluded from the sampling frame. As the data collection proceeded, five additional districts – 3 in Anbar, 1 in Baghdad, and 1 in Salah al-din – were judged to be too insecure for fieldwork so the selected enumeration areas from these areas were replaced with other clusters from the same governorate. Thus, the final sample covers only 106 of 120 districts in the country.

Analysis unit

Individual and Household

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2009 census of dwellings, the most recent sampling frame available for Iraq, served as the sampling frame for the SWIFT survey. Given the large number of people displaced within the country since 2014, the survey was designed to capture a representative sample of internally displaced persons. Furthermore, given the prevalence of Syrian refugees in the Kurdistan region, the survey also sampled refugee households in Kurdistan. A socioeconomic survey of camp residents was conducted by CSO and KRSO in 2017 so to avoid duplication of effort, the camp residents were excluded from the SWIFT survey. Informal ad-hoc settlements that have been constructed since the last update of sampling frame were included in the survey through household listing operation in the sampled enumeration areas. The survey was designed to cover all governorates, including areas in Nineveh deemed safe for field visits.

The sampling design followed a nested logic. All households in the sample responded to a short questionnaire. The short form collected information on the following core non-monetary indicators of well-being: household roster, education attainment, labor market variables, dwelling characteristics, access to basic services, asset ownership, transfers and assistance (public and private), incidence of shocks, and subjective well-being. A random subset of the sampled households also responded to the complete list of questions on household expenditure. The full sample was designed to be representative for each governorate. The expenditure sub-sample was representation at the regional level, where each region comprises three to five governorates.

Within each governorate, the out-of-camp sample was selected in two stages as following. First, using the exhaustive list of Census Enumeration Areas as Primary Sampling Units (PSUs), between 60 to 150 EAs in each governorate was selected using Probability Proportional to Size (PPS) criteria, with the number of households in each area as the measure of size. Listing exercise was conducted in the selected areas to update the list of households. In the second stage, using households as secondary sampling units (SSUs), six households were selected in each cluster with equal probability from the post-listing sampling frame. The sample of households in the second stage was stratified by residence status. In selecting six households from a cluster, three each of IDP and non-IDP households were selected in the non-Kurdistan region. In the Kurdistan region, two each of IDP, non-IDP, and refugee households were selected. If an enumeration area in Kurdistan had fewer than two refugee or IDP households, the gap was filled by randomly selecting resident households from the same enumeration area. Likewise, if a PSU in the rest of Iraq had fewer than three IDP households, the shortfall was met by resident households to reach a total of 6 households per PSU.

Expenditure information was collected from a subsample of households from a subsample of enumeration areas. In Kurdistan, one household each of residents, IDPs, and refugees in a subset of clusters responded to the expenditure questions and in Rest of Iraq, one household each of residents and IDPs answered the expenditure questions.

Sampling deviation

Due to insecurity, the survey could be implemented in only 106 of 120 districts (qhadas) in the country.

Mode of data collection

Computer Assisted Personal Interview [capi]

In the fiscal year 2023, total social benefits in Japan amounted to around ***** trillion Japanese yen. ******** were the largest category at about **** trillion yen. It was followed by ************ and ******* and others, which includes long-term care.

Abstract

The 2017-18 Bangladesh Demographic and Health Survey (2017-18 BDHS) is a nationwide survey with a nationally representative sample of approximately 20,250 selected households. All ever-married women age 15-49 who are usual members of the selected households or who spent the night before the survey in the selected households were eligible for individual interviews. The survey was designed to produce reliable estimates for key indicators at the national level as well as for urban and rural areas and each of the country’s eight divisions: Barishal, Chattogram, Dhaka, Khulna, Mymensingh, Rajshahi, Rangpur, and Sylhet.

The main objective of the 2017-18 BDHS is to provide up-to-date information on fertility and fertility preferences; childhood mortality levels and causes of death; awareness, approval, and use of family planning methods; maternal and child health, including breastfeeding practices and nutritional status; newborn care; women’s empowerment; selected noncommunicable diseases (NCDS); and availability and accessibility of health and family planning services at the community level.

This information is intended to assist policymakers and program managers in monitoring and evaluating the 4th Health, Population and Nutrition Sector Program (4th HPNSP) 2017-2022 of the Ministry of Health and Family Welfare (MOHFW) and to provide estimates for 14 major indicators of the HPNSP Results Framework (MOHFW 2017).

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Children age 0-5
• Woman age 15-49
• Community

Universe

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

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for the 2017-18 BDHS is nationally representative and covers the entire population residing in non-institutional dwelling units in the country. The survey used a list of enumeration areas (EAs) from the 2011 Population and Housing Census of the People’s Republic of Bangladesh, provided by the Bangladesh Bureau of Statistics (BBS), as a sampling frame (BBS 2011). The primary sampling unit (PSU) of the survey is an EA with an average of about 120 households.

Bangladesh consists of eight administrative divisions: Barishal, Chattogram, Dhaka, Khulna, Mymensingh, Rajshahi, Rangpur, and Sylhet. Each division is divided into zilas and each zila into upazilas. Each urban area in an upazila is divided into wards, which are further subdivided into mohallas. A rural area in an upazila is divided into union parishads (UPs) and, within UPs, into mouzas. These divisions allow the country as a whole to be separated into rural and urban areas.

The survey is based on a two-stage stratified sample of households. In the first stage, 675 EAs (250 in urban areas and 425 in rural areas) were selected with probability proportional to EA size. The sample in that stage was drawn by BBS, following the specifications provided by ICF that include cluster allocation and instructions on sample selection. A complete household listing operation was then carried out in all selected EAs to provide a sampling frame for the second-stage selection of households. In the second stage of sampling, a systematic sample of an average of 30 households per EA was selected to provide

statistically reliable estimates of key demographic and health variables for the country as a whole, for urban and rural areas separately, and for each of the eight divisions. Based on this design, 20,250 residential households were selected. Completed interviews were expected from about 20,100 ever-married women age 15-49. In addition, in a subsample of one-fourth of the households (about 7-8 households per EA), all ever-married women age 50 and older, never-married women age 18 and older, and men age 18 and older were weighed and had their height measured. In the same households, blood pressure and blood glucose testing were conducted for all adult men and women age 18 and older.

The survey was successfully carried out in 672 clusters after elimination of three clusters (one urban and two rural) that were completely eroded by floodwater. These clusters were in Dhaka (one urban cluster), Rajshahi (one rural cluster), and Rangpur (one rural cluster). A total of 20,160 households were selected for the survey.

For further details on sample selection, see Appendix A of the final report.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The 2017-18 BDHS used six types of questionnaires: (1) the Household Questionnaire, (2) the Woman’s Questionnaire (completed by ever-married women age 15-49), (3) the Biomarker Questionnaire, (4) two verbal autopsy questionnaires to collect data on causes of death among children under age 5, (5) the Community Questionnaire, and the Fieldworker Questionnaire. The first three questionnaires were based on the model questionnaires developed for the DHS-7 Program, adapted to the situation and needs in Bangladesh and taking into account the content of the instruments employed in prior BDHS surveys. The verbal autopsy module was replicated from the questionnaires used in the 2011 BDHS, as the objectives of the 2011 BDHS and the 2017-18 BDHS were the same. The module was adapted from the standardized WHO 2016 verbal autopsy module. The Community Questionnaire was adapted from the version used in the 2014 BDHS. The adaptation process for the 2017-18 BDHS involved a series of meetings with a technical working group. Additionally, draft questionnaires were circulated to other interested groups and were reviewed by the TWG and SAC. The questionnaires were developed in English and then translated into and printed in Bangla. Back translations were conducted by people not involved with the Bangla translations.

Cleaning operations

Completed BDHS questionnaires were returned to Dhaka every 2 weeks for data processing at Mitra and Associates offices. Data processing began shortly after fieldwork commenced and consisted of office editing, coding of open-ended questions, data entry, and editing of inconsistencies found by the computer program. The field teams were alerted regarding any inconsistencies or errors found during data processing. Eight data entry operators and two data entry supervisors performed the work, which commenced on November 17, 2017, and ended on March 27, 2018. Data processing was accomplished using Census and Survey Processing System (CSPro) software, jointly developed by the United States Census Bureau, ICF, and Serpro S.A.

Response rate

Among the 20,160 households selected, 19,584 were occupied. Interviews were successfully completed in 19,457 (99%) of the occupied households. Among the 20,376 ever-married women age 15-49 eligible for interviews, 20,127 were interviewed, yielding a response rate of 99%. The principal reason for non-response among women was their absence from home despite repeated visits. Response rates did not vary notably by urbanrural residence.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: nonsampling errors and sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2017-18 Bangladesh Demographic and Health Survey (BDHS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2017-18 BDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability among all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

Sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95% of all possible samples of identical size and design.

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2017-18 BDHS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed in SAS, using programs developed by ICF. These programs use the Taylor linearization method to estimate variances for survey estimates that are means, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

Note: A more detailed description of estimates of sampling errors are presented in APPENDIX B of the survey report.

Data

Get data of Health and Family Welfare Statistics - 2017, it provides health and family welfare performance statistics on the various facets of the health and family welfare programmes in India . It includes data on Population and Vital Statistics indicators, Performances of Family Welfare Programmes, Targets/Need Assessed and Achievements of Maternal Health Activities, Child Health, findings of Surveys on Health and Family Welfare Key Indicators [These surveys inter-alia include, National Family Health Survey (NFHS), District Level Household and Facility Survey (DLHS), Annual Health Survey (AHS), Coverage Evaluation Survey (CES) etc.], information on selected indicators from Annual Health Survey (AHS) and Concurrent Evaluation of National Health Mission, information on Infrastructure etc.

In the fiscal year 2023, social insurance contributions accounted for **** percent of the social security revenue in Japan. Contributions by insured persons accounted for **** percent of the revenue, which amounted to around *** trillion Japanese yen in the same year.

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.”

Graph and download economic data for SNAP Benefits Recipients in Merced County, CA (CBR06047CAA647NCEN) from 1989 to 2022 about Merced County, CA; Merced; SNAP; nutrition; food stamps; benefits; food; CA; and USA.

Abstract

Monitoring of External Migration Situation in Armenia through Sample Survey Program commissioned by the State Committee of Science of the Republic of Armenia and being currently implemented by Russian–Armenian (Slavonic) University.

The Socio-Demographic Research Center of the Slavonic University (“Research Center”) has been engaged in analyzing migration decisions in Armenia as part of its ongoing Three-Year Program on monitoring migration through collection of household survey data and is therefore uniquely placed to analyze the situation with regards to migration in 2017. The 2017 household survey of migration conducted by “Research Center” is a follow-up survey (repeated cross-section) to those conducted in the years 2015 and 2016.

The survey gives an opportunity to: - Assess the influence of external migration on living conditions of households; - Restructure the whole timetable of trips done by migrant members of households prior to the monitoring; - Measure migration potential of population; - Analyze separate survey questionnaires for returned migrants and migrants staying abroad to reveal the issues they face abroad and after arrival to Armenia, a cause–effect relationship of the phenomenon, etc.

Geographic coverage

National

Analysis unit

Individuals and Households

Kind of data

Sample survey data [ssd]

Sampling procedure

Similar to the studies done in 2015 and 2016, this year methodology of the study has been based on multistage stratified and cluster sampling. At the primary stage of sampling the research group has determined that unit of observation is a household. The sample size: 2100 households.

Mode of data collection

Face-to-face [f2f]

Research instrument

The main instrument of the study is the survey questionnaire, which consists of the Tittle Page and 5 sections: Section 1. Welfare and remittances Section 2. Socio-demographic and economic characteristics of household members Section 3. The schedule of migration departures and arrivals from the given settlement of present and absent h/h members since 2014 Section 4. Returnees from abroad Section 5. Those who are abroad

Chad Survey Mean Consumption or Income per Capita: Total Population: 2017 PPP per day data was reported at 3.880 Intl $/Day in 2022. This records an increase from the previous number of 3.810 Intl $/Day for 2018. Chad Survey Mean Consumption or Income per Capita: Total Population: 2017 PPP per day data is updated yearly, averaging 3.845 Intl $/Day from Dec 2018 (Median) to 2022, with 2 observations. The data reached an all-time high of 3.880 Intl $/Day in 2022 and a record low of 3.810 Intl $/Day in 2018. Chad Survey Mean Consumption or Income per Capita: Total Population: 2017 PPP per day data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Chad – Table TD.World Bank.WDI: Social: Poverty and Inequality. Mean consumption or income per capita (2017 PPP $ per day) used in calculating the growth rate in the welfare aggregate of total population.;World Bank, Global Database of Shared Prosperity (GDSP) (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).;;The choice of consumption or income for a country is made according to which welfare aggregate is used to estimate extreme poverty in the Poverty and Inequality Platform (PIP). The practice adopted by the World Bank for estimating global and regional poverty is, in principle, to use per capita consumption expenditure as the welfare measure wherever available; and to use income as the welfare measure for countries for which consumption is unavailable. However, in some cases data on consumption may be available but are outdated or not shared with the World Bank for recent survey years. In these cases, if data on income are available, income is used. Whether data are for consumption or income per capita is noted in the footnotes. Because household surveys are infrequent in most countries and are not aligned across countries, comparisons across countries or over time should be made with a high degree of caution.

This statistic shows the results of a survey on the extent of agreement with the statement that immigrants are a burden on the welfare system in Denmark in 2017. The majority of respondents, or ** percent, tended to agree with this statement, while ** percent tended to disagree.

Jamaica Survey Mean Consumption or Income per Capita: Bottom 40% of Population: 2017 PPP per day data was reported at 8.130 Intl $/Day in 2021. This records a decrease from the previous number of 8.990 Intl $/Day for 2018. Jamaica Survey Mean Consumption or Income per Capita: Bottom 40% of Population: 2017 PPP per day data is updated yearly, averaging 8.560 Intl $/Day from Dec 2018 (Median) to 2021, with 2 observations. The data reached an all-time high of 8.990 Intl $/Day in 2018 and a record low of 8.130 Intl $/Day in 2021. Jamaica Survey Mean Consumption or Income per Capita: Bottom 40% of Population: 2017 PPP per day data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Jamaica – Table JM.World Bank.WDI: Social: Poverty and Inequality. Mean consumption or income per capita (2017 PPP $ per day) of the bottom 40%, used in calculating the growth rate in the welfare aggregate of the bottom 40% of the population in the income distribution in a country.;World Bank, Global Database of Shared Prosperity (GDSP) (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).;;The choice of consumption or income for a country is made according to which welfare aggregate is used to estimate extreme poverty in the Poverty and Inequality Platform (PIP). The practice adopted by the World Bank for estimating global and regional poverty is, in principle, to use per capita consumption expenditure as the welfare measure wherever available; and to use income as the welfare measure for countries for which consumption is unavailable. However, in some cases data on consumption may be available but are outdated or not shared with the World Bank for recent survey years. In these cases, if data on income are available, income is used. Whether data are for consumption or income per capita is noted in the footnotes. Because household surveys are infrequent in most countries and are not aligned across countries, comparisons across countries or over time should be made with a high degree of caution.

The Citizen Survey - The Norwegian Labour and Welfare Administration, 2017 is a part of the Citizen Survey which is conducted by the Public Management and eGovernment (DIFI) and is one of the largest surveys of public administration in Norway. It will provide a better knowledge base for assessing the development of public services across sectors, and provide knowledge that can contribute to the further development of public enterprises in the long term. The population survey says something about how satisfied residents and users are with their municipality and with the large services / businesses in the administration. The results from the survey provide increased insight into users' perceptions of companies in the areas of education and culture, health, care and government agencies. Kantar TNS is responsible for data collection in 2017.

The 2017 population survey consists of a population section and a user section. The population section provides an overall picture of the inhabitants' view of the municipality of residence, including an assessment of the municipal services and trust in politicians and the administration. The user section maps experiences with 22 selected public services in the areas of education and culture, health, care and government agencies.

China Survey Mean Consumption or Income per Capita: Bottom 40% of Population: 2017 PPP per day data was reported at 6.220 Intl $/Day in 2020. This records an increase from the previous number of 4.780 Intl $/Day for 2015. China Survey Mean Consumption or Income per Capita: Bottom 40% of Population: 2017 PPP per day data is updated yearly, averaging 5.500 Intl $/Day from Dec 2015 (Median) to 2020, with 2 observations. The data reached an all-time high of 6.220 Intl $/Day in 2020 and a record low of 4.780 Intl $/Day in 2015. China Survey Mean Consumption or Income per Capita: Bottom 40% of Population: 2017 PPP per day data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s China – Table CN.World Bank.WDI: Social: Poverty and Inequality. Mean consumption or income per capita (2017 PPP $ per day) of the bottom 40%, used in calculating the growth rate in the welfare aggregate of the bottom 40% of the population in the income distribution in a country.;World Bank, Global Database of Shared Prosperity (GDSP) (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).;;The choice of consumption or income for a country is made according to which welfare aggregate is used to estimate extreme poverty in the Poverty and Inequality Platform (PIP). The practice adopted by the World Bank for estimating global and regional poverty is, in principle, to use per capita consumption expenditure as the welfare measure wherever available; and to use income as the welfare measure for countries for which consumption is unavailable. However, in some cases data on consumption may be available but are outdated or not shared with the World Bank for recent survey years. In these cases, if data on income are available, income is used. Whether data are for consumption or income per capita is noted in the footnotes. Because household surveys are infrequent in most countries and are not aligned across countries, comparisons across countries or over time should be made with a high degree of caution.

The statistic shows the goals set by a company when activating company welfare programs in 2017 in Italy. According to the survey, ** percent of the employees declared they create a corporate climate.