2 datasets found
  1. T

    INFLATION RATE by Country in EUROPE

    • tradingeconomics.com
    csv, excel, json, xml
    Updated May 28, 2017
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    TRADING ECONOMICS (2017). INFLATION RATE by Country in EUROPE [Dataset]. https://tradingeconomics.com/country-list/inflation-rate?continent=europe
    Explore at:
    json, excel, csv, xmlAvailable download formats
    Dataset updated
    May 28, 2017
    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
    2025
    Area covered
    Europe
    Description

    This dataset provides values for INFLATION RATE reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

  2. N

    Greenwood township, Oscoda County, Michigan annual median income by work...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
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    Neilsberg Research (2025). Greenwood township, Oscoda County, Michigan annual median income by work experience and sex dataset: Aged 15+, 2010-2023 (in 2023 inflation-adjusted dollars) // 2025 Edition [Dataset]. https://www.neilsberg.com/insights/greenwood-township-oscoda-county-mi-income-by-gender/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Feb 27, 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
    Oscoda County, Michigan, Greenwood Township
    Variables measured
    Income for Male Population, Income for Female Population, Income for Male Population working full time, Income for Male Population working part time, Income for Female Population working full time, Income for Female Population working part time
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates. The dataset covers the years 2010 to 2023, representing 14 years of data. To analyze income differences between genders (male and female), we conducted an initial data analysis and categorization. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series (R-CPI-U-RS) based on current methodologies. 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 median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Greenwood township. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

    Key observations: Insights from 2023

    Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Greenwood township, the median income for all workers aged 15 years and older, regardless of work hours, was $34,297 for males and $20,583 for females.

    These income figures highlight a substantial gender-based income gap in Greenwood township. Women, regardless of work hours, earn 60 cents for each dollar earned by men. This significant gender pay gap, approximately 40%, underscores concerning gender-based income inequality in the township of Greenwood township.

    - Full-time workers, aged 15 years and older: In Greenwood township, among full-time, year-round workers aged 15 years and older, males earned a median income of $43,594, while females earned $36,000, leading to a 17% gender pay gap among full-time workers. This illustrates that women earn 83 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.

    Surprisingly, the gender pay gap percentage was higher across all roles, including non-full-time employment, for women compared to men. This suggests that full-time employment offers a more equitable income scenario for women compared to other employment patterns in Greenwood township.

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

    Gender classifications include:

    • Male
    • Female

    Employment type classifications include:

    • Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
    • Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

    Variables / Data Columns

    • Year: This column presents the data year. Expected values are 2010 to 2023
    • Male Total Income: Annual median income, for males regardless of work hours
    • Male FT Income: Annual median income, for males working full time, year-round
    • Male PT Income: Annual median income, for males working part time
    • Female Total Income: Annual median income, for females regardless of work hours
    • Female FT Income: Annual median income, for females working full time, year-round
    • Female PT Income: Annual median income, for females working part time

    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 Greenwood township median household income by race. You can refer the same here

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Share
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Email
Click to copy link
Link copied
Close
Cite
TRADING ECONOMICS (2017). INFLATION RATE by Country in EUROPE [Dataset]. https://tradingeconomics.com/country-list/inflation-rate?continent=europe

INFLATION RATE by Country in EUROPE

INFLATION RATE by Country in EUROPE (2025)

Explore at:
102 scholarly articles cite this dataset (View in Google Scholar)
json, excel, csv, xmlAvailable download formats
Dataset updated
May 28, 2017
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
2025
Area covered
Europe
Description

This dataset provides values for INFLATION RATE reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

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