100+ datasets found
  1. T

    Norway Inflation Rate

    • tradingeconomics.com
    • zh.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jun 10, 2025
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    TRADING ECONOMICS (2025). Norway Inflation Rate [Dataset]. https://tradingeconomics.com/norway/inflation-cpi
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    excel, csv, json, xmlAvailable download formats
    Dataset updated
    Jun 10, 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 31, 1950 - Jun 30, 2025
    Area covered
    Norway
    Description

    Inflation Rate in Norway remained unchanged at 3 percent in June. This dataset provides - Norway Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  2. T

    South Korea Inflation Rate

    • tradingeconomics.com
    • zh.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jun 3, 2025
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    TRADING ECONOMICS (2025). South Korea Inflation Rate [Dataset]. https://tradingeconomics.com/south-korea/inflation-cpi
    Explore at:
    csv, json, xml, excelAvailable download formats
    Dataset updated
    Jun 3, 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 31, 1966 - Jun 30, 2025
    Area covered
    South Korea
    Description

    Inflation Rate in South Korea increased to 2.20 percent in June from 1.90 percent in May of 2025. This dataset provides the latest reported value for - South Korea Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  3. Replication dataset for PIIE PB 24-2, The Inflation Surge in Europe by...

    • piie.com
    Updated May 25, 2024
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    Patrick Honohan (2024). Replication dataset for PIIE PB 24-2, The Inflation Surge in Europe by Patrick Honohan (2024). [Dataset]. https://www.piie.com/publications/policy-briefs/2024/inflation-surge-europe
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    Dataset updated
    May 25, 2024
    Dataset provided by
    Peterson Institute for International Economicshttp://www.piie.com/
    Authors
    Patrick Honohan
    Area covered
    Europe
    Description

    This data package includes the underlying data files to replicate the data and charts presented in The Inflation Surge in Europe by Patrick Honohan, PIIE Policy Brief 24-2.

    If you use the data, please cite as: Honohan, Patrick. 2024. The Inflation Surge in Europe. PIIE Policy Brief 24-2. Washington, DC: Peterson Institute for International Economics.

  4. J

    The global component of inflation volatility (replication data)

    • journaldata.zbw.eu
    • jda-test.zbw.eu
    txt, zip
    Updated Dec 7, 2022
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    Andrea Carriero; Francesco Corsello; Massimiliano Marcellino; Andrea Carriero; Francesco Corsello; Massimiliano Marcellino (2022). The global component of inflation volatility (replication data) [Dataset]. http://doi.org/10.15456/jae.2022327.072333
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    txt(3439), zip(2270564)Available download formats
    Dataset updated
    Dec 7, 2022
    Dataset provided by
    ZBW - Leibniz Informationszentrum Wirtschaft
    Authors
    Andrea Carriero; Francesco Corsello; Massimiliano Marcellino; Andrea Carriero; Francesco Corsello; Massimiliano Marcellino
    License

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

    Description

    Global developments play an important role for domestic inflation rates. Earlier literature has found that a substantial amount of the variation in a large set of national inflation rates can be explained by a single global factor. However, inflation volatility has been typically neglected, although it is clearly relevant both from a policy point of view and for structural analysis and forecasting. We study the evolution of inflation rates in several countries, using a novel model that allows for commonality in both levels and volatilities, in addition to country-specific components. We find that inflation volatility is indeed important, and a substantial fraction of it can be attributed to a global factor that is also driving inflation levels and their persistence. The extent of commonality among core inflation rates and volatilities is substantially smaller than for overall inflation, which leaves scope for national monetary policies. Finally, we show that the point and density forecasting performance of the model is good relative to standard benchmarks, which provides additional evidence on its reliability.

  5. Consumer price inflation consumption segment indices and price quotes

    • ons.gov.uk
    • cy.ons.gov.uk
    csv
    Updated Jun 18, 2025
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    Office for National Statistics (2025). Consumer price inflation consumption segment indices and price quotes [Dataset]. https://www.ons.gov.uk/economy/inflationandpriceindices/datasets/consumerpriceindicescpiandretailpricesindexrpiitemindicesandpricequotes
    Explore at:
    csvAvailable download formats
    Dataset updated
    Jun 18, 2025
    Dataset provided by
    Office for National Statisticshttp://www.ons.gov.uk/
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Description

    Price quote data (for locally collected data only) and consumption segment indices that underpin consumer price inflation statistics, giving users access to the detailed data that are used in the construction of the UK’s inflation figures. The data are being made available for research purposes only and are not an accredited official statistic. From October 2024, private school fees and part-time education classes have been included in the consumption segment indices file. For more information on the introduction of consumption segments, please see the Consumer Prices Indices Technical Manual, 2019. Note that this dataset was previously called the consumer price inflation item indices and price quotes dataset.

  6. T

    Egypt Core Inflation Rate

    • tradingeconomics.com
    • pl.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jul 9, 2025
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    TRADING ECONOMICS (2025). Egypt Core Inflation Rate [Dataset]. https://tradingeconomics.com/egypt/core-inflation-rate
    Explore at:
    excel, json, xml, csvAvailable download formats
    Dataset updated
    Jul 9, 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 31, 2005 - Jun 30, 2025
    Area covered
    Egypt
    Description

    Core consumer prices in Egypt increased 11.40 percent in June of 2025 over the same month in the previous year. This dataset provides - Egypt Core Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  7. w

    Dataset of demonym and inflation of countries per year in China (Historical)...

    • workwithdata.com
    Updated Apr 9, 2025
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    Work With Data (2025). Dataset of demonym and inflation of countries per year in China (Historical) [Dataset]. https://www.workwithdata.com/datasets/countries-yearly?col=country%2Cdate%2Cdemonym%2Cinflation&f=1&fcol0=country&fop0=%3D&fval0=China
    Explore at:
    Dataset updated
    Apr 9, 2025
    Dataset authored and provided by
    Work With Data
    License

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

    Area covered
    China
    Description

    This dataset is about countries per year in China. It has 64 rows. It features 4 columns: country, demonym, and inflation.

  8. T

    Jordan Inflation Rate

    • tradingeconomics.com
    • ko.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jul 11, 2025
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    TRADING ECONOMICS (2025). Jordan Inflation Rate [Dataset]. https://tradingeconomics.com/jordan/inflation-cpi
    Explore at:
    csv, excel, xml, jsonAvailable download formats
    Dataset updated
    Jul 11, 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 31, 1977 - Jun 30, 2025
    Area covered
    Jordan
    Description

    Inflation Rate in Jordan increased to 2 percent in June from 1.98 percent in May of 2025. This dataset provides the latest reported value for - Jordan Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  9. w

    Monthly food price inflation estimates by country - Afghanistan, Armenia,...

    • microdata.worldbank.org
    Updated Jul 9, 2025
    + more versions
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    Bo Pieter Johannes Andrée (2025). Monthly food price inflation estimates by country - Afghanistan, Armenia, Bangladesh...and 33 more [Dataset]. https://microdata.worldbank.org/index.php/catalog/4509
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    Dataset updated
    Jul 9, 2025
    Dataset authored and provided by
    Bo Pieter Johannes Andrée
    Time period covered
    2008 - 2025
    Area covered
    Bangladesh
    Description

    Abstract

    Food price inflation is an important metric to inform economic policy but traditional sources of consumer prices are often produced with delay during crises and only at an aggregate level. This may poorly reflect the actual price trends in rural or poverty-stricken areas, where large populations reside in fragile situations. This data set includes food price estimates and is intended to help gain insight in price developments beyond what can be formally measured by traditional methods. The estimates are generated using a machine-learning approach that imputes ongoing subnational price surveys, often with accuracy similar to direct measurement of prices. The data set provides new opportunities to investigate local price dynamics in areas where populations are sensitive to localized price shocks and where traditional data are not available.

    Geographic coverage notes

    The data cover the following areas: Afghanistan, Armenia, Bangladesh, Burkina Faso, Burundi, Cameroon, Central African Republic, Chad, Congo, Dem. Rep., Congo, Rep., Gambia, The, Guinea, Guinea-Bissau, Haiti, Indonesia, Iraq, Kenya, Lao PDR, Lebanon, Liberia, Libya, Malawi, Mali, Mauritania, Mozambique, Myanmar, Niger, Nigeria, Philippines, Senegal, Somalia, South Sudan, Sri Lanka, Sudan, Syrian Arab Republic, Yemen, Rep.

  10. Producer price inflation (MM22)

    • ons.gov.uk
    • cy.ons.gov.uk
    xlsx
    Updated Feb 19, 2025
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    Office for National Statistics (2025). Producer price inflation (MM22) [Dataset]. https://www.ons.gov.uk/economy/inflationandpriceindices/datasets/mm22producerpriceindices
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    xlsxAvailable download formats
    Dataset updated
    Feb 19, 2025
    Dataset provided by
    Office for National Statisticshttp://www.ons.gov.uk/
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Description

    UK price index data at manufacturing, aggregated industry and product group levels. Data supplied from individual manufacturers, importers and exporters. Monthly and annual data.

  11. n

    Data from: Controlling for p-value inflation in allele frequency change in...

    • data.niaid.nih.gov
    • search.dataone.org
    • +2more
    zip
    Updated Nov 14, 2016
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    Petri Kemppainen; Bernt Rønning; Thomas Kvalnes; Ingerid J. Hagen; Thor Harald Ringsby; Anna M. Billing; Henrik Pärn; Sigbjorn Lien; Arild Husby; Bernt-Erik Sæther; Henrik Jensen; Bernt-Erik Saether (2016). Controlling for p-value inflation in allele frequency change in experimental evolution and artificial selection experiments [Dataset]. http://doi.org/10.5061/dryad.vv527
    Explore at:
    zipAvailable download formats
    Dataset updated
    Nov 14, 2016
    Dataset provided by
    Norwegian University of Life Sciences
    Norwegian University of Science and Technology
    University of Helsinki
    Authors
    Petri Kemppainen; Bernt Rønning; Thomas Kvalnes; Ingerid J. Hagen; Thor Harald Ringsby; Anna M. Billing; Henrik Pärn; Sigbjorn Lien; Arild Husby; Bernt-Erik Sæther; Henrik Jensen; Bernt-Erik Saether
    License

    https://spdx.org/licenses/CC0-1.0.htmlhttps://spdx.org/licenses/CC0-1.0.html

    Area covered
    Norway
    Description

    Experimental evolution studies can be used to explore genomic response to artificial and natural selection. In such studies, loci that display larger allele frequency change than expected by genetic drift alone are assumed to be directly or indirectly associated with traits under selection. However, such studies report surprisingly many loci under selection, suggesting that current tests for allele frequency change may be subject to p-value inflation and hence be anti-conservative. One factor known from genome wide association (GWA) studies to cause p-value inflation is population stratification, such as relatedness among individuals. Here we suggest that by treating presence of an individual in a population after selection as a binary response variable, existing GWA methods can be used to account for relatedness when estimating allele frequency change. We show that accounting for relatedness like this effectively reduces false positives in tests for allele frequency change in simulated data with varying levels of population structure. However, once relatedness has been accounted for, the power to detect causal loci under selection is low. Finally, we demonstrate the presence of p-value inflation in allele frequency change in empirical data spanning multiple generations from an artificial selection experiment on tarsus length in two wild populations of house sparrow, and correct for this using genomic control. Our results indicate that since allele frequencies in large parts of the genome may change when selection acts on a heritable trait, such selection is likely to have considerable and immediate consequences for the eco-evolutionary dynamics of the affected populations.

  12. T

    Somalia Inflation Rate

    • tradingeconomics.com
    • pl.tradingeconomics.com
    • +13more
    csv, excel, json, xml
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    TRADING ECONOMICS, Somalia Inflation Rate [Dataset]. https://tradingeconomics.com/somalia/inflation-cpi
    Explore at:
    json, csv, xml, excelAvailable 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
    Dec 31, 1961 - Mar 31, 2025
    Area covered
    Somalia
    Description

    Inflation Rate in Somalia increased to 3.90 percent in March from 3.20 percent in February of 2025. This dataset provides - Somalia Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  13. T

    Iceland Inflation Rate

    • tradingeconomics.com
    • tr.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jun 27, 2025
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    TRADING ECONOMICS (2025). Iceland Inflation Rate [Dataset]. https://tradingeconomics.com/iceland/inflation-cpi
    Explore at:
    json, xml, excel, csvAvailable download formats
    Dataset updated
    Jun 27, 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
    Apr 30, 1989 - Jun 30, 2025
    Area covered
    Iceland
    Description

    Inflation Rate in Iceland increased to 4.20 percent in June from 3.80 percent in May of 2025. This dataset provides - Iceland Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  14. T

    INFLATION RATE MOM by Country Dataset

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Jul 18, 2013
    + more versions
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    TRADING ECONOMICS (2013). INFLATION RATE MOM by Country Dataset [Dataset]. https://tradingeconomics.com/country-list/inflation-rate-mom
    Explore at:
    json, xml, csv, excelAvailable download formats
    Dataset updated
    Jul 18, 2013
    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
    World
    Description

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

  15. N

    Camp Wood, TX annual median income by work experience and sex dataset: Aged...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
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    Neilsberg Research (2025). Camp Wood, TX 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/research/datasets/a5086784-f4ce-11ef-8577-3860777c1fe6/
    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
    Texas, Camp Wood
    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 Camp Wood. 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 Camp Wood, the median income for all workers aged 15 years and older, regardless of work hours, was $10,852 for males and $22,601 for females.

    Contrary to expectations, women in Camp Wood, women, regardless of work hours, earn a higher income than men, earning 2.08 dollars for every dollar earned by men. This analysis indicates a significant shift in income dynamics favoring females.

    - Full-time workers, aged 15 years and older: In Camp Wood, for full-time, year-round workers aged 15 years and older, the Census reported a median income of $24,049 for females, while data for males was unavailable due to an insufficient number of sample observations.

    As there was no available median income data for males, conducting a comprehensive assessment of gender-based pay disparity in Camp Wood was not feasible.

    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 Camp Wood median household income by race. You can refer the same here

  16. T

    United States Consumer Inflation Expectations

    • tradingeconomics.com
    • it.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jun 9, 2025
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    TRADING ECONOMICS (2025). United States Consumer Inflation Expectations [Dataset]. https://tradingeconomics.com/united-states/inflation-expectations
    Explore at:
    json, excel, xml, csvAvailable download formats
    Dataset updated
    Jun 9, 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
    Jun 30, 2013 - Jun 30, 2025
    Area covered
    United States
    Description

    Inflation Expectations in the United States decreased to 3 percent in June from 3.20 percent in May of 2025. This dataset provides - United States Consumer Inflation Expectations- actual values, historical data, forecast, chart, statistics, economic calendar and news.

  17. N

    Grace City, ND annual median income by work experience and sex dataset: Aged...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
    Share
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    Cite
    Neilsberg Research (2025). Grace City, ND 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/research/datasets/a5182f92-f4ce-11ef-8577-3860777c1fe6/
    Explore at:
    json, csvAvailable 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
    Grace City, North Dakota
    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 Grace City. 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 Grace City, the Census Bureau did not report the median income for all workers aged 15 years and older, regardless of work hours, for both males and females due to an insufficient number of sample observations.

    Due to unavailability of income data for both males and females, conducting a comprehensive analysis of gender-based pay disparity in the city of Grace City was not possible.

    - Full-time workers, aged 15 years and older: In Grace City, for full-time, year-round workers aged 15 years and older, the Census reported a median income of $63,750 for females, while data for males was unavailable due to an insufficient number of sample observations.

    As there was no available median income data for males, conducting a comprehensive assessment of gender-based pay disparity in Grace City was not feasible.

    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 Grace City median household income by race. You can refer the same here

  18. T

    Czech Republic Core Inflation Rate

    • tradingeconomics.com
    • ru.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jun 14, 2025
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    TRADING ECONOMICS (2025). Czech Republic Core Inflation Rate [Dataset]. https://tradingeconomics.com/czech-republic/core-inflation-rate
    Explore at:
    xml, csv, excel, jsonAvailable download formats
    Dataset updated
    Jun 14, 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 31, 2007 - Jun 30, 2025
    Area covered
    Czechia
    Description

    Core consumer prices in Czech Republic increased 2.96 percent in June of 2025 over the same month in the previous year. This dataset provides - Czech Republic Core Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  19. N

    Greenport Town, New York annual median income by work experience and sex...

    • neilsberg.com
    csv, json
    Updated Feb 27, 2025
    + more versions
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    Neilsberg Research (2025). Greenport Town, New York 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/research/datasets/a518f694-f4ce-11ef-8577-3860777c1fe6/
    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
    Greenport
    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 Greenport town. 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 Greenport town, the median income for all workers aged 15 years and older, regardless of work hours, was $34,670 for males and $42,820 for females.

    Contrary to expectations, women in Greenport town, women, regardless of work hours, earn a higher income than men, earning 1.24 dollars for every dollar earned by men. This analysis indicates a significant shift in income dynamics favoring females.

    - Full-time workers, aged 15 years and older: In Greenport town, among full-time, year-round workers aged 15 years and older, males earned a median income of $54,111, while females earned $79,250

    Contrary to expectations, in Greenport town, women, earn a higher income than men, earning 1.46 dollars for every dollar earned by men. This analysis showcase a consistent trend of women outearning men, when working full-time or part-time in the town of Greenport town.

    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 Greenport town median household income by race. You can refer the same here

  20. T

    Canada Inflation Rate

    • tradingeconomics.com
    • es.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jun 24, 2025
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    TRADING ECONOMICS (2025). Canada Inflation Rate [Dataset]. https://tradingeconomics.com/canada/inflation-cpi
    Explore at:
    json, excel, csv, xmlAvailable download formats
    Dataset updated
    Jun 24, 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 31, 1915 - May 31, 2025
    Area covered
    Canada
    Description

    Inflation Rate in Canada remained unchanged at 1.70 percent in May. This dataset provides - Canada Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Share
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TwitterTwitter
Email
Click to copy link
Link copied
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TRADING ECONOMICS (2025). Norway Inflation Rate [Dataset]. https://tradingeconomics.com/norway/inflation-cpi

Norway Inflation Rate

Norway Inflation Rate - Historical Dataset (1950-01-31/2025-06-30)

Explore at:
11 scholarly articles cite this dataset (View in Google Scholar)
excel, csv, json, xmlAvailable download formats
Dataset updated
Jun 10, 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 31, 1950 - Jun 30, 2025
Area covered
Norway
Description

Inflation Rate in Norway remained unchanged at 3 percent in June. This dataset provides - Norway Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

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