15 datasets found
  1. g

    Distributional Financial Accounts

    • gimi9.com
    • s.cnmilf.com
    • +1more
    Updated Dec 18, 2024
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    (2024). Distributional Financial Accounts [Dataset]. https://gimi9.com/dataset/data-gov_distributional-financial-accounts/
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    Dataset updated
    Dec 18, 2024
    Description

    The Distributional Financial Accounts (DFAs) provide a quarterly measure of the distribution of U.S. household wealth since 1989, based on a comprehensive integration of disaggregated household-level wealth data with official aggregate wealth measures. The data set contains the level and share of each balance sheet item on the Financial Accounts' household wealth table (Table B.101.h), for various sub-populations in the United States. In our core data set, aggregate household wealth is allocated to each of four percentile groups of wealth: the top 1 percent, the next 9 percent (i.e., 90th to 99th percentile), the next 40 percent (50th to 90th percentile), and the bottom half (below the 50th percentile). Additionally, the data set contains the level and share of aggregate household wealth by income, age, generation, education, and race. The quarterly frequency makes the data useful for studying the business cycle dynamics of wealth concentration--which are typically difficult to observe in lower-frequency data because peaks and troughs often fall between times of measurement. These data will be updated about 10 or 11 weeks after the end of each quarter, making them a timely measure of the distribution of wealth.

  2. N

    Income Distribution by Quintile: Mean Household Income in Rich Township,...

    • neilsberg.com
    csv, json
    Updated Jan 11, 2024
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    Neilsberg Research (2024). Income Distribution by Quintile: Mean Household Income in Rich Township, Michigan [Dataset]. https://www.neilsberg.com/research/datasets/94ecf37f-7479-11ee-949f-3860777c1fe6/
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    json, csvAvailable download formats
    Dataset updated
    Jan 11, 2024
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Rich Township, Michigan
    Variables measured
    Income Level, Mean Household Income
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. It delineates income distributions across income quintiles (mentioned above) following an initial analysis and categorization. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series via current methods (R-CPI-U-RS). For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents the mean household income for each of the five quintiles in Rich Township, Michigan, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.

    Key observations

    • Income disparities: The mean income of the lowest quintile (20% of households with the lowest income) is 18,571, while the mean income for the highest quintile (20% of households with the highest income) is 181,062. This indicates that the top earners earn 10 times compared to the lowest earners.
    • *Top 5%: * The mean household income for the wealthiest population (top 5%) is 302,586, which is 167.12% higher compared to the highest quintile, and 1629.35% higher compared to the lowest quintile.

    Mean household income by quintiles in Rich Township, Michigan (in 2022 inflation-adjusted dollars))

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

    Income Levels:

    • Lowest Quintile
    • Second Quintile
    • Third Quintile
    • Fourth Quintile
    • Highest Quintile
    • Top 5 Percent

    Variables / Data Columns

    • Income Level: This column showcases the income levels (As mentioned above).
    • Mean Household Income: Mean household income, in 2022 inflation-adjusted dollars for the specific income level.

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

    Recommended for further research

    This dataset is a part of the main dataset for Rich township median household income. You can refer the same here

  3. High income tax filers in Canada

    • www150.statcan.gc.ca
    • open.canada.ca
    • +1more
    Updated Oct 28, 2024
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    Government of Canada, Statistics Canada (2024). High income tax filers in Canada [Dataset]. http://doi.org/10.25318/1110005501-eng
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    Dataset updated
    Oct 28, 2024
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    This table presents income shares, thresholds, tax shares, and total counts of individual Canadian tax filers, with a focus on high income individuals (95% income threshold, 99% threshold, etc.). Income thresholds are based on national threshold values, regardless of selected geography; for example, the number of Nova Scotians in the top 1% will be calculated as the number of taxfiling Nova Scotians whose total income exceeded the 99% national income threshold. Different definitions of income are available in the table namely market, total, and after-tax income, both with and without capital gains.

  4. N

    Income Distribution by Quintile: Mean Household Income in Money Creek...

    • neilsberg.com
    csv, json
    Updated Mar 3, 2025
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    Neilsberg Research (2025). Income Distribution by Quintile: Mean Household Income in Money Creek Township, Minnesota // 2025 Edition [Dataset]. https://www.neilsberg.com/research/datasets/48348fce-f81d-11ef-a994-3860777c1fe6/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Mar 3, 2025
    Dataset authored and provided by
    Neilsberg Research
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Minnesota, Money Creek Township
    Variables measured
    Income Level, Mean Household Income
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It delineates income distributions across income quintiles (mentioned above) following an initial analysis and categorization. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series via current methods (R-CPI-U-RS). For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset presents the mean household income for each of the five quintiles in Money Creek Township, Minnesota, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.

    Key observations

    • Income disparities: The mean income of the lowest quintile (20% of households with the lowest income) is 24,649, while the mean income for the highest quintile (20% of households with the highest income) is 234,434. This indicates that the top earners earn 10 times compared to the lowest earners.
    • *Top 5%: * The mean household income for the wealthiest population (top 5%) is 365,119, which is 155.74% higher compared to the highest quintile, and 1481.27% higher compared to the lowest quintile.
    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

    Income Levels:

    • Lowest Quintile
    • Second Quintile
    • Third Quintile
    • Fourth Quintile
    • Highest Quintile
    • Top 5 Percent

    Variables / Data Columns

    • Income Level: This column showcases the income levels (As mentioned above).
    • Mean Household Income: Mean household income, in 2023 inflation-adjusted dollars for the specific income level.

    Good to know

    Margin of Error

    Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

    Custom data

    If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

    Inspiration

    Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

    Recommended for further research

    This dataset is a part of the main dataset for Money Creek township median household income. You can refer the same here

  5. Distributions of household economic accounts, wealth indicators, by...

    • www150.statcan.gc.ca
    • data.urbandatacentre.ca
    • +4more
    Updated Apr 14, 2025
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    Government of Canada, Statistics Canada (2025). Distributions of household economic accounts, wealth indicators, by characteristic, Canada, quarterly [Dataset]. http://doi.org/10.25318/3610066401-eng
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    Dataset updated
    Apr 14, 2025
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    Wealth indicators and distributions, by household characteristics such as income quintile, age, housing tenure and composition, Canada, annual 2010 to 2019 and quarterly starting 2020.

  6. Assets and debts by net worth quintile, Canada, provinces and selected...

    • www150.statcan.gc.ca
    • open.canada.ca
    • +2more
    Updated Oct 29, 2024
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    Government of Canada, Statistics Canada (2024). Assets and debts by net worth quintile, Canada, provinces and selected census metropolitan areas, Survey of Financial Security (x 1,000,000) [Dataset]. http://doi.org/10.25318/1110004901-eng
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    Dataset updated
    Oct 29, 2024
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    This table contains 58320 series, with data for years 1999 - 2016 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (20 items: Canada; Atlantic; Newfoundland and Labrador; Prince Edward Island; ...); Assets and debts (27 items: Total assets; Private pension assets; Registered Retirement Savings Plans (RRSPs), Registered Retirement Income Funds (RRIFs), Locked-in Retirement Accounts (LIRAs) and other; Employer-sponsored Registered Pension Plans (EPPs); ...); Net worth quintiles (6 items: Total, all net worth quintiles; Lowest net worth quintile; Second net worth quintile; Middle net worth quintile; ...); Statistics (6 items: Total values; Percentage of total assets or total debts; Number holding asset or debt; Percentage holding asset or debt; ...); Confidence intervals (3 items: Estimate; Lower bound of a 95% confidence interval; Upper bound of a 95% confidence interval).

  7. Income of individuals by age group, sex and income source, Canada, provinces...

    • www150.statcan.gc.ca
    • ouvert.canada.ca
    • +2more
    Updated May 1, 2025
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    Government of Canada, Statistics Canada (2025). Income of individuals by age group, sex and income source, Canada, provinces and selected census metropolitan areas [Dataset]. http://doi.org/10.25318/1110023901-eng
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    Dataset updated
    May 1, 2025
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    Income of individuals by age group, sex and income source, Canada, provinces and selected census metropolitan areas, annual.

  8. T

    United States Money Supply M0

    • tradingeconomics.com
    • zh.tradingeconomics.com
    • +13more
    csv, excel, json, xml
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    TRADING ECONOMICS, United States Money Supply M0 [Dataset]. https://tradingeconomics.com/united-states/money-supply-m0
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    json, excel, xml, csvAvailable download formats
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 31, 1959 - May 31, 2025
    Area covered
    United States
    Description

    Money Supply M0 in the United States decreased to 5648600 USD Million in May from 5732900 USD Million in April of 2025. This dataset provides - United States Money Supply M0 - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  9. a

    Indicator 4.1.2: Completion rate by sex location wealth quintile and...

    • sdgs.amerigeoss.org
    Updated Aug 18, 2020
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    UN DESA Statistics Division (2020). Indicator 4.1.2: Completion rate by sex location wealth quintile and education level (percent) [Dataset]. https://sdgs.amerigeoss.org/datasets/undesa::indicator-4-1-2-completion-rate-by-sex-location-wealth-quintile-and-education-level-percent/data
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    Dataset updated
    Aug 18, 2020
    Dataset authored and provided by
    UN DESA Statistics Division
    Area covered
    Description

    Series Name: Completion rate by sex location wealth quintile and education level (percent)Series Code: SE_TOT_CPLRRelease Version: 2020.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 4.1.2: Completion rate (primary education, lower secondary education, upper secondary education)Target 4.1: By 2030, ensure that all girls and boys complete free, equitable and quality primary and secondary education leading to relevant and effective learning outcomesGoal 4: Ensure inclusive and equitable quality education and promote lifelong learning opportunities for allFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

  10. i

    Richest Zip Codes in Missouri

    • incomebyzipcode.com
    Updated Dec 18, 2024
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    Cubit Planning, Inc. (2024). Richest Zip Codes in Missouri [Dataset]. https://www.incomebyzipcode.com/missouri
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    Dataset updated
    Dec 18, 2024
    Dataset authored and provided by
    Cubit Planning, Inc.
    License

    https://www.incomebyzipcode.com/terms#TERMShttps://www.incomebyzipcode.com/terms#TERMS

    Area covered
    Missouri
    Description

    A dataset listing the richest zip codes in Missouri per the most current US Census data, including information on rank and average income.

  11. T

    Russia National Wealth Fund Liquid Assets

    • tradingeconomics.com
    • fa.tradingeconomics.com
    • +7more
    csv, excel, json, xml
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    TRADING ECONOMICS, Russia National Wealth Fund Liquid Assets [Dataset]. https://tradingeconomics.com/russia/national-wealth-fund-liquid-assets
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    excel, xml, csv, jsonAvailable download formats
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 31, 2008 - Jun 30, 2025
    Area covered
    Russia
    Description

    National Wealth Fund Liquid Assets in Russia decreased to 11700 RUB Billion in June from 11790 RUB Billion in May of 2025. This dataset includes a chart with historical data for Russia National Wealth Fund Liquid Assets.

  12. i

    Richest Zip Codes in North Carolina

    • incomebyzipcode.com
    Updated Dec 18, 2024
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    Cubit Planning, Inc. (2024). Richest Zip Codes in North Carolina [Dataset]. https://www.incomebyzipcode.com/northcarolina
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    Dataset updated
    Dec 18, 2024
    Dataset authored and provided by
    Cubit Planning, Inc.
    License

    https://www.incomebyzipcode.com/terms#TERMShttps://www.incomebyzipcode.com/terms#TERMS

    Area covered
    North Carolina
    Description

    A dataset listing the richest zip codes in North Carolina per the most current US Census data, including information on rank and average income.

  13. w

    Global Financial Inclusion (Global Findex) Database 2014 - Afghanistan,...

    • microdata.worldbank.org
    • catalog.ihsn.org
    • +1more
    Updated Oct 26, 2023
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    Development Research Group, Finance and Private Sector Development Unit (2023). Global Financial Inclusion (Global Findex) Database 2014 - Afghanistan, Angola, Angola...and 151 more [Dataset]. https://microdata.worldbank.org/index.php/catalog/2512
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    Dataset updated
    Oct 26, 2023
    Dataset authored and provided by
    Development Research Group, Finance and Private Sector Development Unit
    Time period covered
    2014
    Area covered
    Angola
    Description

    Abstract

    Financial inclusion is critical in reducing poverty and achieving inclusive economic growth. When people can participate in the financial system, they are better able to start and expand businesses, invest in their children’s education, and absorb financial shocks. Yet prior to 2011, little was known about the extent of financial inclusion and the degree to which such groups as the poor, women, and rural residents were excluded from formal financial systems.

    By collecting detailed indicators about how adults around the world manage their day-to-day finances, the Global Findex allows policy makers, researchers, businesses, and development practitioners to track how the use of financial services has changed over time. The database can also be used to identify gaps in access to the formal financial system and design policies to expand financial inclusion.

    Geographic coverage

    The 2014 Global Findex Database covers around 150,000 adults in more than 140 economies and representing about 97 percent of the world's population. See Methodology document for country-specific geographic coverage details.

    Analysis unit

    Individual

    Universe

    The target population is the civilian, non-institutionalized population 15 years and above.

    Kind of data

    Sample survey data [ssd]

    Frequency of data collection

    Triennial

    Sampling procedure

    As in the first edition, the indicators in the 2014 Global Findex are drawn from survey data covering almost 150,000 people in more than 140 economies-representing more than 97 percent of the world's population. The survey was carried out over the 2014 calendar year by Gallup, Inc. as part of its Gallup World Poll, which since 2005 has continually conducted surveys of approximately 1,000 people in each of more than 160 economies and in over 140 languages, using randomly selected, nationally representative samples. The target population is the entire civilian, noninstitutionalized population age 15 and above. The set of indicators will be collected again in 2017.

    Surveys are conducted face to face in economies where telephone coverage represents less than 80 percent of the population or is the customary methodology. In most economies the fieldwork is completed in two to four weeks. In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households by means of the Kish grid. In economies where cultural restrictions dictate gender matching, respondents are randomly selected through the Kish grid from among all eligible adults of the interviewer's gender.

    In economies where telephone interviewing is employed, random digit dialing or a nationally representative list of phone numbers is used. In most economies where cell phone penetration is high, a dual sampling frame is used. Random selection of respondents is achieved by using either the latest birthday or Kish grid method. At least three attempts are made to reach a person in each household, spread over different days and times of day.

    Mode of data collection

    Other [oth]

    Research instrument

    The questionnaire was designed by the World Bank, in conjunction with a Technical Advisory Board composed of leading academics, practitioners, and policy makers in the field of financial inclusion. The Bill and Melinda Gates Foundation and Gallup Inc. also provided valuable input. The questionnaire was piloted in multiple countries, using focus groups, cognitive interviews, and field testing. The questionnaire is available in 142 languages upon request.

    Questions on cash withdrawals, saving using an informal savings club or person outside the family, domestic remittances, school fees, and agricultural payments are only asked in developing economies and few other selected countries. The question on mobile money accounts was only asked in economies that were part of the Mobile Money for the Unbanked (MMU) database of the GSMA at the time the interviews were being held.

    Sampling error estimates

    Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Asli Demirguc-Kunt, Leora Klapper, Dorothe Singer, and Peter Van Oudheusden, “The Global Findex Database 2014: Measuring Financial Inclusion around the World.” Policy Research Working Paper 7255, World Bank, Washington, D.C.

  14. w

    Sierra Leone - Demographic and Health Survey 2008 - Dataset - waterdata

    • wbwaterdata.org
    Updated Mar 16, 2020
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    (2020). Sierra Leone - Demographic and Health Survey 2008 - Dataset - waterdata [Dataset]. https://wbwaterdata.org/dataset/sierra-leone-demographic-and-health-survey-2008
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    Dataset updated
    Mar 16, 2020
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Sierra Leone
    Description

    The 2008 Sierra Leone Demographic and Health Survey (SLDHS) is the first DHS survey to be held in Sierra Leone. Teams visited 353 sample points across Sierra Leone and collected data from a nationally representative sample of 7,374 women age 15-49 and 3,280 men age 15-59. The primary purpose of the 2008 SLDHS is to provide policy-makers and planners with detailed information on Demography and health. This is the first Demographic and Health Survey conducted in Sierra Leone and was carried out by Statistics Sierra Leone (SSL) in collaboration with the Ministry of Health and Sanitation. The 2008 SLDHS was funded by the Sierra Leone government, UNFPA, UNDP, UNICEF, DFID, USAID, and The World Bank. WHO, WFP and UNHCR provided logistical support. ICF Macro, an ICF International Company, provided technical support for the survey through the MEASURE DHS project. MEASURE DHS is sponsored by the United States Agency for International Development (USAID) to assist countries worldwide in obtaining information on key population and health indicators. The purpose of the SLDHS is to collect national- and regional-level data on fertility and contraceptive use, marriage and sexual activity, fertility preferences, breastfeeding practices, nutritional status of women and young children, childhood and adult mortality, maternal and child health, female genital cutting, awareness and behaviour regarding HIV/AIDS and other sexually transmitted infections, adult health, and other issues. The survey obtained detailed information on these topics from women of reproductive age and, for certain topics, from men as well. The 2008 SLDHS was carried out from late April 2008 to late June 2008, using a nationally representative sample of 7,758 households. The survey results are intended to assist policymakers and planners in assessing the current health and population programmes and in designing new strategies for improving reproductive health and health services in Sierra Leone. MAIN RESULTS FERTILITY Survey results indicate that there has been little or no decline in the total fertility rate over the past two decades, from 5.7 children per woman in 1980-85 to 5.1 children per woman for the three years preceding the 2008 SLDHS (approximately 2004-07). Fertility is lower in urban areas than in rural areas (3.8 and 5.8 children per woman, respectively). Regional variations in fertility are marked, ranging from 3.4 births per woman in the Western Region (where the capital, Freetown, is located) to almost six births per woman in the Northern and Eastern regions. Women with no education give birth to almost twice as many children as women who have been to secondary school (5.8 births, compared with 3.1 births). Fertility is also closely associated with household wealth, ranging from 3.2 births among women in the highest wealth quintile to 6.3 births among women in the lowest wealth quintile, a difference of more than three births. Research has demonstrated that children born too close to a previous birth are at increased risk of dying. In Sierra Leone, only 18 percent of births occur within 24 months of a previous birth. The interval between births is relatively long; the median interval is 36 months. FAMILY PLANNING The vast majority of Sierra Leonean women and men know of at least one method of contraception. Contraceptive pills and injectables are known to about 60 percent of currently married women and 49 percent of married men. Male condoms are known to 58 percent of married women and 80 percent of men. A higher proportion of respondents reported knowing a modern method of family planning than a traditional method. About one in five (21 percent) currently married women has used a contraceptive method at some time-19 percent have used a modern method and 6 percent have used a traditional method. However, only about one in twelve currently married women (8 percent) is currently using a contraceptive method. Modern methods account for almost all contraceptive use, with 7 percent of married women reporting use of a modern method, compared with only 1 percent using a traditional method. Injectables and the pill are the most widely used methods (3 and 2 percent of married women, respectively), followed by LAM and male condoms (less than 1 percent each). CHILD HEALTH Examination of levels of infant and child mortality is essential for assessing population and health policies and programmes. Infant and child mortality rates are also used as indices reflecting levels of poverty and deprivation in a population. The 2008 survey data show that over the past 15 years, infant and under-five mortality have decreased by 26 percent. Still, one in seven Sierra Leonean children dies before reaching age five. For the most recent five-year period before the survey (approximately calendar years 2003 to 2008), the infant mortality rate was 89 deaths per 1,000 live births and the under-five mortality rate was 140 deaths per 1,000 live births. The neonatal mortality rate was 36 deaths per 1,000 live births and the post-neonatal mortality rate was 53 deaths per 1,000 live births. The child mortality rate was 56 deaths per 1,000 children surviving to age one year. Mortality rates at all ages of childhood show a strong relationship with the length of the preceding birth interval. Under-five mortality is three times higher among children born less than two years after a preceding sibling (252 deaths per 1,000 births) than among children born four or more years after a previous child (deaths 81 per 1,000 births). MATERNAL HEALTH Almost nine in ten mothers (87 percent) in Sierra Leone receive antenatal care from a health professional (doctor, nurse, midwife, or MCH aid). Only 5 percent of mothers receive antenatal care from a traditional midwife or a community health worker; 7 percent of mothers do not receive any antenatal care. In Sierra Leone, over half of mothers have four or more antenatal care (ANC) visits, about 20 percent have one to three ANC visits, and only 7 percent have no antenatal care at all. The survey shows that not all women in Sierra Leone receive antenatal care services early in pregnancy. Only 30 percent of mothers obtain antenatal care in the first three months of pregnancy, 41 percent make their first visit in the fourth or fifth month, and 17 percent in have their first visit in the sixth or seventh month. Only 1 percent of women have their first ANC visit in their eighth month of pregnancy or later. BREASTFEEDING AND NUTRITION Poor nutritional status is one of the most important health and welfare problems facing Sierra Leone today and particularly afflicts women and children. The data show that 36 percent of children under five are stunted (too short for their age) and 10 percent of children under five are wasted (too thin for their height). Overall, 21 percent of children are underweight, which may reflect stunting, wasting, or both. For women, at the national level 11 percent of women are considered to be thin (body mass index

  15. T

    United Kingdom Stock Market Index (GB100) Data

    • tradingeconomics.com
    • ko.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jun 13, 2025
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    TRADING ECONOMICS, United Kingdom Stock Market Index (GB100) Data [Dataset]. https://tradingeconomics.com/united-kingdom/stock-market
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    excel, xml, json, csvAvailable download formats
    Dataset updated
    Jun 13, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 3, 1984 - Jul 11, 2025
    Area covered
    United Kingdom
    Description

    United Kingdom's main stock market index, the GB100, fell to 8941 points on July 11, 2025, losing 0.38% from the previous session. Over the past month, the index has climbed 0.63% and is up 8.34% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from United Kingdom. United Kingdom Stock Market Index (GB100) - values, historical data, forecasts and news - updated on July of 2025.

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(2024). Distributional Financial Accounts [Dataset]. https://gimi9.com/dataset/data-gov_distributional-financial-accounts/

Distributional Financial Accounts

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Dataset updated
Dec 18, 2024
Description

The Distributional Financial Accounts (DFAs) provide a quarterly measure of the distribution of U.S. household wealth since 1989, based on a comprehensive integration of disaggregated household-level wealth data with official aggregate wealth measures. The data set contains the level and share of each balance sheet item on the Financial Accounts' household wealth table (Table B.101.h), for various sub-populations in the United States. In our core data set, aggregate household wealth is allocated to each of four percentile groups of wealth: the top 1 percent, the next 9 percent (i.e., 90th to 99th percentile), the next 40 percent (50th to 90th percentile), and the bottom half (below the 50th percentile). Additionally, the data set contains the level and share of aggregate household wealth by income, age, generation, education, and race. The quarterly frequency makes the data useful for studying the business cycle dynamics of wealth concentration--which are typically difficult to observe in lower-frequency data because peaks and troughs often fall between times of measurement. These data will be updated about 10 or 11 weeks after the end of each quarter, making them a timely measure of the distribution of wealth.

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