100+ datasets found
  1. Pension Insurance Data Tables

    • catalog.data.gov
    • s.cnmilf.com
    • +2more
    Updated Nov 12, 2020
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    Pension Benefit Guaranty Corporation (2020). Pension Insurance Data Tables [Dataset]. https://catalog.data.gov/dataset/pension-insurance-data-tables
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    Dataset updated
    Nov 12, 2020
    Dataset provided by
    Pension Benefit Guaranty Corporationhttp://www.pbgc.gov/
    Description

    Find out about retirement trends in PBGC's data tables. The tables include statistics on the people and pensions that PBGC protects, including how many Americans are in PBGC-insured pension plans, how many get PBGC benefits, and where they live. This data set will be updated periodically. (Updated annually)

  2. National Health Insurance Premium Classification Table

    • data.gov.tw
    csv
    Updated Jun 2, 2025
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    National Health Insurance Administration (2025). National Health Insurance Premium Classification Table [Dataset]. https://data.gov.tw/en/datasets/20251
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    csvAvailable download formats
    Dataset updated
    Jun 2, 2025
    Dataset authored and provided by
    National Health Insurance Administration
    License

    https://data.gov.tw/licensehttps://data.gov.tw/license

    Description

    National Health Insurance Premium Classifications Data

  3. Medical Expenditure Panel Survey (MEPS) Insurance Component Complete Table...

    • catalog.data.gov
    • healthdata.gov
    • +2more
    Updated Jun 20, 2025
    + more versions
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    Agency for Healthcare Research and Quality, Department of Health & Human Services (2025). Medical Expenditure Panel Survey (MEPS) Insurance Component Complete Table Series PDFs [Dataset]. https://catalog.data.gov/dataset/medical-expenditure-panel-survey-meps-insurance-component-complete-table-series-pdfs
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    Dataset updated
    Jun 20, 2025
    Description

    The Medical Expenditure Panel Survey Insurance Component (MEPS-IC) is an annual survey of private employers and State and local governments. The MEPS-IC produces national and State level estimates of employer-sponsored insurance, including offered plans, costs, employee eligibility, and number of enrollees. PDF files are available for complete sets of table series on employer-based health insurance at the national, state, and metropolitan area levels. The MEPS-IC is sponsored by the Agency for Healthcare Research and Quality and is fielded by the U.S. Census Bureau.

  4. 2023 American Community Survey: B27018 | Public Health Insurance by Ratio of...

    • data.census.gov
    + more versions
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    ACS, 2023 American Community Survey: B27018 | Public Health Insurance by Ratio of Income to Poverty Level in the Past 12 Months by Age (ACS 1-Year Estimates Detailed Tables) [Dataset]. https://data.census.gov/table/ACSDT1Y2023.B27018
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    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ACS
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2023
    Description

    Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2023 American Community Survey 1-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..The health insurance coverage category names were modified in 2010. See https://www.census.gov/topics/health/health-insurance/about/glossary.html#par_textimage_18 for a list of the insurance type definitions..Beginning in 2017, selected variable categories were updated, including age-categories, income-to-poverty ratio (IPR) categories, and the age universe for certain employment and education variables. See user note entitled "Health Insurance Table Updates" for further details..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

  5. 2016 Group Life Insurance Experience Committee Report

    • soa.org
    txt
    Updated Oct 1, 2016
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    Society of Actuaries (2016). 2016 Group Life Insurance Experience Committee Report [Dataset]. https://www.soa.org/resources/experience-studies/2016/2016-group-life-mortality-study/
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    txtAvailable download formats
    Dataset updated
    Oct 1, 2016
    Dataset provided by
    Society of Actuarieshttp://www.soa.org/
    Time period covered
    2010 - 2013
    Area covered
    United States of America
    Description

    Mortality and morbidity experience data from 2010 through 2013 on group insurance policies

  6. f

    Life expectancy (life years) free of stroke, affected by stroke, and total...

    • plos.figshare.com
    xls
    Updated May 31, 2023
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    Juliane Tetzlaff; Siegfried Geyer; Fabian Tetzlaff; Jelena Epping (2023). Life expectancy (life years) free of stroke, affected by stroke, and total life expectancy at age 50 by sex, period, and income group. [Dataset]. http://doi.org/10.1371/journal.pone.0227541.t004
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    xlsAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Juliane Tetzlaff; Siegfried Geyer; Fabian Tetzlaff; Jelena Epping
    License

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

    Description

    Life expectancy (life years) free of stroke, affected by stroke, and total life expectancy at age 50 by sex, period, and income group.

  7. Life Insurance Supplementary Statistical Tables

    • data.gov.au
    • researchdata.edu.au
    • +1more
    excel (.xlsx), pdf
    Updated Feb 26, 2015
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    Australian Prudential Regulation Authority (2015). Life Insurance Supplementary Statistical Tables [Dataset]. https://data.gov.au/data/dataset/activity/life-insurance-supplementary-statistical-tables
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    pdf, excel (.xlsx)Available download formats
    Dataset updated
    Feb 26, 2015
    Dataset provided by
    Australian Prudential Regulation Authorityhttp://www.apra.gov.au/
    License

    Attribution 3.0 (CC BY 3.0)https://creativecommons.org/licenses/by/3.0/
    License information was derived automatically

    Description

    The Life Insurance Supplementary Statistical Tables contains aggregate level data about Sources of profit, Assets backing policy liabilities and Policy liabilities.

  8. ACS Health Insurance Coverage Variables - Boundaries

    • hub.arcgis.com
    • legacy-cities-lincolninstitute.hub.arcgis.com
    • +4more
    Updated Dec 7, 2018
    + more versions
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    Esri (2018). ACS Health Insurance Coverage Variables - Boundaries [Dataset]. https://hub.arcgis.com/maps/a1574f4bb84f4da78b60fa0c8616eaa1
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    Dataset updated
    Dec 7, 2018
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This layer shows health insurance coverage by type and by age group. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the percent uninsured. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B27010 (Not all lines of this ACS table are available in this feature layer.)Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

  9. 2023 American Community Survey: B27001E | Health Insurance Coverage Status...

    • data.census.gov
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    ACS, 2023 American Community Survey: B27001E | Health Insurance Coverage Status by Age (Native Hawaiian and Other Pacific Islander Alone) (ACS 1-Year Estimates Detailed Tables) [Dataset]. https://data.census.gov/table/ACSDT1Y2023.B27001E?q=United+States+Populations+and+People&t=Health+Insurance&g=795XX00US3603809
    Explore at:
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ACS
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2023
    Description

    Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2023 American Community Survey 1-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..The health insurance coverage category names were modified in 2010. See https://www.census.gov/topics/health/health-insurance/about/glossary.html#par_textimage_18 for a list of the insurance type definitions..Beginning in 2017, selected variable categories were updated, including age-categories, income-to-poverty ratio (IPR) categories, and the age universe for certain employment and education variables. See user note entitled "Health Insurance Table Updates" for further details..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

  10. G

    Property and casualty insurance companies statements of estimated revenues...

    • ouvert.canada.ca
    csv, html, xml
    Updated Jan 17, 2023
    + more versions
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    Statistics Canada (2023). Property and casualty insurance companies statements of estimated revenues and expenses [Dataset]. https://ouvert.canada.ca/data/dataset/ba67a0fc-6623-4437-81be-949b19685ae6
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    xml, html, csvAvailable download formats
    Dataset updated
    Jan 17, 2023
    Dataset provided by
    Statistics Canada
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Description

    This table contains 37 series, with data for years 1973 - 1990 (not all combinations necessarily have data for all years), and is no longer being released. This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada); Revenues and expenses (37 items: Net income;Net income before extraordinary transactions;Net income before taxes;Underwriting gain; ...).

  11. G

    National balance sheet, segregated funds of life insurance companies,...

    • open.canada.ca
    csv, html, xml
    Updated Jan 17, 2023
    + more versions
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    Statistics Canada (2023). National balance sheet, segregated funds of life insurance companies, annual, 1961 - 2011 [Dataset]. https://open.canada.ca/data/dataset/3d49797b-3ec7-4704-a87b-ffce9fe56bb7
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    html, csv, xmlAvailable download formats
    Dataset updated
    Jan 17, 2023
    Dataset provided by
    Statistics Canada
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Description

    This table contains 42 series, with data for years 1961 - 2011 (not all combinations necessarily have data for all years), and is no longer being released. This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada);  Valuation (2 items: Book value; Market value);  Categories (21 items: Total assets; Non-financial assets; Non-residential structures; Machinery and equipment; ...).

  12. Health Insurance Marketplace

    • kaggle.com
    zip
    Updated May 1, 2017
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    US Department of Health and Human Services (2017). Health Insurance Marketplace [Dataset]. https://www.kaggle.com/datasets/hhs/health-insurance-marketplace
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    zip(868821924 bytes)Available download formats
    Dataset updated
    May 1, 2017
    Dataset provided by
    United States Department of Health and Human Serviceshttp://www.hhs.gov/
    Authors
    US Department of Health and Human Services
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    The Health Insurance Marketplace Public Use Files contain data on health and dental plans offered to individuals and small businesses through the US Health Insurance Marketplace.

    median plan premiums

    Exploration Ideas

    To help get you started, here are some data exploration ideas:

    • How do plan rates and benefits vary across states?
    • How do plan benefits relate to plan rates?
    • How do plan rates vary by age?
    • How do plans vary across insurance network providers?

    See this forum thread for more ideas, and post there if you want to add your own ideas or answer some of the open questions!

    Data Description

    This data was originally prepared and released by the Centers for Medicare & Medicaid Services (CMS). Please read the CMS Disclaimer-User Agreement before using this data.

    Here, we've processed the data to facilitate analytics. This processed version has three components:

    1. Original versions of the data

    The original versions of the 2014, 2015, 2016 data are available in the "raw" directory of the download and "../input/raw" on Kaggle Scripts. Search for "dictionaries" on this page to find the data dictionaries describing the individual raw files.

    2. Combined CSV files that contain

    In the top level directory of the download ("../input" on Kaggle Scripts), there are six CSV files that contain the combined at across all years:

    • BenefitsCostSharing.csv
    • BusinessRules.csv
    • Network.csv
    • PlanAttributes.csv
    • Rate.csv
    • ServiceArea.csv

    Additionally, there are two CSV files that facilitate joining data across years:

    • Crosswalk2015.csv - joining 2014 and 2015 data
    • Crosswalk2016.csv - joining 2015 and 2016 data

    3. SQLite database

    The "database.sqlite" file contains tables corresponding to each of the processed CSV files.

    The code to create the processed version of this data is available on GitHub.

  13. G

    Selected indicators of dental insurance coverage, by age group and gender

    • open.canada.ca
    • www150.statcan.gc.ca
    • +1more
    csv, html, xml
    Updated Oct 24, 2024
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    Statistics Canada (2024). Selected indicators of dental insurance coverage, by age group and gender [Dataset]. https://open.canada.ca/data/dataset/ef6b0daa-8ef1-451a-8a7e-bf92ab69f2ff
    Explore at:
    csv, xml, htmlAvailable download formats
    Dataset updated
    Oct 24, 2024
    Dataset provided by
    Statistics Canada
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Description

    This table allows users to explore the latest data related to dental insurance coverage in Canada.

  14. G

    Ordinary sales results of life insurance in Canada

    • open.canada.ca
    • www150.statcan.gc.ca
    csv, html, xml
    Updated Jan 17, 2023
    + more versions
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    Statistics Canada (2023). Ordinary sales results of life insurance in Canada [Dataset]. https://open.canada.ca/data/en/dataset/30dd6e0f-13d5-4694-afb9-da2ff0efa142
    Explore at:
    xml, html, csvAvailable download formats
    Dataset updated
    Jan 17, 2023
    Dataset provided by
    Statistics Canada
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Area covered
    Canada
    Description

    This table contains 3 series, with data for years 1997 - 2010 (not all combinations necessarily have data for all years), and was last released on 2010-08-30. This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...), Type of sales (3 items: Annualized premium sales; total; Number of policies sold; total; Face amount sales; total ...).

  15. s

    2025 Life Insurance Premium Table

    • staging.simplelifecover.com.au
    • keepinsuranceco.com.au
    Updated Jun 17, 2025
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    Simple Life Cover (2025). 2025 Life Insurance Premium Table [Dataset]. https://staging.simplelifecover.com.au/life-insurance-costs
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    Dataset updated
    Jun 17, 2025
    Dataset authored and provided by
    Simple Life Cover
    License

    https://simplelifecover.com.au/terms-and-conditionshttps://simplelifecover.com.au/terms-and-conditions

    Variables measured
    Gender, Age Band, Smoking Status, Monthly Premium Range
    Description

    Average monthly premiums for life insurance in Australia in 2025 by age, gender, and smoking status.

  16. d

    Statistical table of insured and additional insured persons under...

    • data.gov.tw
    csv, json +2
    Updated Oct 1, 2025
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    Bureau of Labor Insurance, MOL (2025). Statistical table of insured and additional insured persons under agricultural insurance - by region and age group division [Dataset]. https://data.gov.tw/en/datasets/75259
    Explore at:
    json, xml, csv, webservicesAvailable download formats
    Dataset updated
    Oct 1, 2025
    Dataset authored and provided by
    Bureau of Labor Insurance, MOL
    License

    https://data.gov.tw/licensehttps://data.gov.tw/license

    Description

    Please provide the text to be translated into English.

  17. d

    Insurance industry statistics and its branch institutions table (monthly...

    • data.gov.tw
    csv
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    Financial Supervisory Commission, Insurance Bureau, Insurance industry statistics and its branch institutions table (monthly report)_NEW [Dataset]. https://data.gov.tw/en/datasets/104108
    Explore at:
    csvAvailable download formats
    Dataset authored and provided by
    Financial Supervisory Commission, Insurance Bureau
    License

    https://data.gov.tw/licensehttps://data.gov.tw/license

    Description

    Insurance industry and its branch institution statistics table (monthly report)

  18. ACS Health Insurance by Age by Race Variables - Boundaries

    • gis-for-racialequity.hub.arcgis.com
    • community-climatesolutions.hub.arcgis.com
    • +4more
    Updated Nov 17, 2020
    + more versions
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    Esri (2020). ACS Health Insurance by Age by Race Variables - Boundaries [Dataset]. https://gis-for-racialequity.hub.arcgis.com/maps/0bdb1479d3554ae59337a0eb47b17afb
    Explore at:
    Dataset updated
    Nov 17, 2020
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This layer shows health insurance coverage sex and race by age group. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. Sums may add to more than the total, as people can be in multiple race groups (for example, Hispanic and Black)This layer is symbolized to show the percent of population with no health insurance coverage. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B27010, C27001B, C27001C, C27001D, C27001E, C27001F, C27001G, C27001H, C27001I (Not all lines of these tables are available in this layer.)Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

  19. 2022 American Community Survey: B27013 | Private Health Insurance by Work...

    • data.census.gov
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    ACS, 2022 American Community Survey: B27013 | Private Health Insurance by Work Experience by Sex (ACS 1-Year Estimates Detailed Tables) [Dataset]. https://data.census.gov/table/ACSDT1Y2022.B27013?tid=ACSDT1Y2022.B27013
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    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Authors
    ACS
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    2022
    Description

    Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2022 American Community Survey 1-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Logical coverage edits applying a rules-based assignment of Medicaid, Medicare and military health coverage were added as of 2009 -- please see https://www.census.gov/library/working-papers/2010/demo/coverage_edits_final.html for more details. Select geographies of 2008 data comparable to the 2009 and later tables are available at https://www.census.gov/data/tables/time-series/acs/1-year-re-run-health-insurance.html. The health insurance coverage category names were modified in 2010. See https://www.census.gov/topics/health/health-insurance/about/glossary.html#par_textimage_18 for a list of the insurance type definitions..Beginning in 2017, selected variable categories were updated, including age-categories, income-to-poverty ratio (IPR) categories, and the age universe for certain employment and education variables. See user note entitled "Health Insurance Table Updates" for further details..The 2022 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

  20. S

    South Korea Non Life Insurance: Direct Premium Written: Casualty: ACE...

    • ceicdata.com
    Updated Jun 13, 2020
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    CEICdata.com (2020). South Korea Non Life Insurance: Direct Premium Written: Casualty: ACE American [Dataset]. https://www.ceicdata.com/en/korea/non-life-insurance-direct-premium-written-casualty
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    Dataset updated
    Jun 13, 2020
    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Jun 1, 2020 - Mar 1, 2023
    Area covered
    South Korea
    Variables measured
    Insurance Market
    Description

    Non Life Insurance: Direct Premium Written: Casualty: ACE American data was reported at 30,474.000 KRW mn in Mar 2023. This records a decrease from the previous number of 88,857.000 KRW mn for Dec 2022. Non Life Insurance: Direct Premium Written: Casualty: ACE American data is updated quarterly, averaging 47,701.000 KRW mn from Mar 2017 (Median) to Mar 2023, with 25 observations. The data reached an all-time high of 88,857.000 KRW mn in Dec 2022 and a record low of 16,687.000 KRW mn in Mar 2018. Non Life Insurance: Direct Premium Written: Casualty: ACE American data remains active status in CEIC and is reported by General Insurance Association of Korea. The data is categorized under Global Database’s South Korea – Table KR.RG036: Non Life Insurance: Direct Premium Written: Casualty.

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Pension Benefit Guaranty Corporation (2020). Pension Insurance Data Tables [Dataset]. https://catalog.data.gov/dataset/pension-insurance-data-tables
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Pension Insurance Data Tables

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25 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Nov 12, 2020
Dataset provided by
Pension Benefit Guaranty Corporationhttp://www.pbgc.gov/
Description

Find out about retirement trends in PBGC's data tables. The tables include statistics on the people and pensions that PBGC protects, including how many Americans are in PBGC-insured pension plans, how many get PBGC benefits, and where they live. This data set will be updated periodically. (Updated annually)

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