62 datasets found
  1. F

    Consumer Price Index for All Urban Consumers: Services Less Energy Services...

    • fred.stlouisfed.org
    json
    Updated Jun 11, 2025
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    (2025). Consumer Price Index for All Urban Consumers: Services Less Energy Services in U.S. City Average [Dataset]. https://fred.stlouisfed.org/series/CUSR0000SASLE
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jun 11, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    United States
    Description

    Graph and download economic data for Consumer Price Index for All Urban Consumers: Services Less Energy Services in U.S. City Average (CUSR0000SASLE) from Jan 1967 to May 2025 about energy, urban, consumer, services, CPI, inflation, price index, indexes, price, and USA.

  2. R

    Republic of the Congo Inflation - data, chart | TheGlobalEconomy.com

    • theglobaleconomy.com
    csv, excel, xml
    Updated Feb 26, 2018
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    Globalen LLC (2018). Republic of the Congo Inflation - data, chart | TheGlobalEconomy.com [Dataset]. www.theglobaleconomy.com/Republic-of-the-Congo/Inflation/
    Explore at:
    csv, xml, excelAvailable download formats
    Dataset updated
    Feb 26, 2018
    Dataset authored and provided by
    Globalen LLC
    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, 1986 - Dec 31, 2023
    Area covered
    Republic of the Congo
    Description

    The Republic of the Congo: Inflation: percent change in the Consumer Price Index: The latest value from 2023 is 4.3 percent, an increase from 3 percent in 2022. In comparison, the world average is 9.9 percent, based on data from 160 countries. Historically, the average for the Republic of the Congo from 1986 to 2023 is 3.7 percent. The minimum value, -3.9 percent, was reached in 1992 while the maximum of 42.4 percent was recorded in 1994.

  3. F

    Research Consumer Price Index: All Items

    • fred.stlouisfed.org
    json
    Updated Jun 11, 2025
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    (2025). Research Consumer Price Index: All Items [Dataset]. https://fred.stlouisfed.org/series/CPIEALL
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jun 11, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    Graph and download economic data for Research Consumer Price Index: All Items (CPIEALL) from Dec 1982 to May 2025 about 62 and older, consumer prices, all items, consumer, CPI, inflation, price index, indexes, price, and USA.

  4. N

    Utah Median Household Income Trends (2010-2021, in 2022 inflation-adjusted...

    • neilsberg.com
    csv, json
    Updated Jan 11, 2024
    + more versions
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    Neilsberg Research (2024). Utah Median Household Income Trends (2010-2021, in 2022 inflation-adjusted dollars) [Dataset]. https://www.neilsberg.com/research/datasets/91f76751-73f0-11ee-949f-3860777c1fe6/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Jan 11, 2024
    Dataset authored and provided by
    Neilsberg Research
    License

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

    Area covered
    Utah
    Variables measured
    Median Household Income, Median Household Income Year on Year Change, Median Household Income Year on Year Percent Change
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. It presents the median household income from the years 2010 to 2021 following an initial analysis and categorization of the census data. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series via current methods (R-CPI-U-RS). For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset illustrates the median household income in Utah, spanning the years from 2010 to 2021, with all figures adjusted to 2022 inflation-adjusted dollars. Based on the latest 2017-2021 5-Year Estimates from the American Community Survey, it displays how income varied over the last decade. The dataset can be utilized to gain insights into median household income trends and explore income variations.

    Key observations:

    From 2010 to 2021, the median household income for Utah increased by $9,531 (12.54%), as per the American Community Survey estimates. In comparison, median household income for the United States increased by $4,559 (6.51%) between 2010 and 2021.

    Analyzing the trend in median household income between the years 2010 and 2021, spanning 11 annual cycles, we observed that median household income, when adjusted for 2022 inflation using the Consumer Price Index retroactive series (R-CPI-U-RS), experienced growth year by year for 8 years and declined for 3 years.

    https://i.neilsberg.com/ch/utah-median-household-income-trend.jpeg" alt="Utah median household income trend (2010-2021, in 2022 inflation-adjusted dollars)">

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.

    Years for which data is available:

    • 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021

    Variables / Data Columns

    • Year: This column presents the data year from 2010 to 2021
    • Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific year
    • YOY Change($): Change in median household income between the current and the previous year, in 2022 inflation-adjusted dollars
    • YOY Change(%): Percent change in median household income between current and the previous year

    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 Utah median household income. You can refer the same here

  5. F

    Producer Price Index by Industry: Mineral Wool Manufacturing: Building...

    • fred.stlouisfed.org
    json
    Updated May 15, 2015
    + more versions
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    (2015). Producer Price Index by Industry: Mineral Wool Manufacturing: Building Batts, Blankets, and Rolls, R-19 or over [Dataset]. https://fred.stlouisfed.org/series/PCU32799332799312
    Explore at:
    jsonAvailable download formats
    Dataset updated
    May 15, 2015
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    Graph and download economic data for Producer Price Index by Industry: Mineral Wool Manufacturing: Building Batts, Blankets, and Rolls, R-19 or over (PCU32799332799312) from May 1982 to Jun 2007 about wool, minerals, buildings, manufacturing, PPI, industry, inflation, price index, indexes, price, and USA.

  6. R

    Republic of the Congo Inflation forecast - data, chart |...

    • theglobaleconomy.com
    csv, excel, xml
    Updated Mar 1, 2018
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    Globalen LLC (2018). Republic of the Congo Inflation forecast - data, chart | TheGlobalEconomy.com [Dataset]. www.theglobaleconomy.com/Republic-of-the-Congo/inflation_outlook_imf/
    Explore at:
    excel, xml, csvAvailable download formats
    Dataset updated
    Mar 1, 2018
    Dataset authored and provided by
    Globalen LLC
    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, 1981 - Dec 31, 2030
    Area covered
    Republic of the Congo
    Description

    The Republic of the Congo: Inflation forecast: The latest value from 2030 is 3 percent, unchanged from 3 percent in 2029. In comparison, the world average is 3.65 percent, based on data from 182 countries. Historically, the average for the Republic of the Congo from 1981 to 2030 is 3.47 percent. The minimum value, -13.01 percent, was reached in 1988 while the maximum of 28.8 percent was recorded in 1995.

  7. F

    Equity Market Volatility Tracker: Macroeconomic News and Outlook: Inflation

    • fred.stlouisfed.org
    json
    Updated Jul 4, 2025
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    (2025). Equity Market Volatility Tracker: Macroeconomic News and Outlook: Inflation [Dataset]. https://fred.stlouisfed.org/series/EMVMACROINFLATION
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jul 4, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    Graph and download economic data for Equity Market Volatility Tracker: Macroeconomic News and Outlook: Inflation (EMVMACROINFLATION) from Jan 1985 to Jun 2025 about volatility, uncertainty, equity, inflation, and USA.

  8. Shoe-Leather Costs of Inflation and Policy Credibility

    • icpsr.umich.edu
    Updated Apr 30, 1999
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    Pakko, Michael R. (1999). Shoe-Leather Costs of Inflation and Policy Credibility [Dataset]. http://doi.org/10.3886/ICPSR01197.v1
    Explore at:
    Dataset updated
    Apr 30, 1999
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    Pakko, Michael R.
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/1197/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/1197/terms

    Area covered
    United States
    Description

    Inflation can cause costly misallocations of resources as consumers seek to protect the purchasing power of their nominal assets. This research deals with the nature of these distortions, known as "shoe-leather costs," in a model where the demand for money is motivated by a shopping-time constraint. While the estimates of the shoe-leather costs of long-run inflation (implied by this model) are generally consistent with previous studies, the research shows that the transition between inflation rates can involve dynamics that alter the nature of these welfare effects. Specifically, the benefits of a disinflation policy are mitigated by the gradual adjustment of the economy in response to a lower inflation rate. This transition can be particularly protracted when there is uncertainty about the credibility of the disinflation policy.

  9. J

    Output and inflation in the long run (replication data)

    • jda-test.zbw.eu
    • journaldata.zbw.eu
    txt, zip
    Updated Nov 4, 2022
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    Neil R. Ericsson; John S. Irons; Ralph W. Tryon; Neil R. Ericsson; John S. Irons; Ralph W. Tryon (2022). Output and inflation in the long run (replication data) [Dataset]. https://jda-test.zbw.eu/dataset/output-and-inflation-in-the-long-run
    Explore at:
    txt(14551), zip(2235580)Available download formats
    Dataset updated
    Nov 4, 2022
    Dataset provided by
    ZBW - Leibniz Informationszentrum Wirtschaft
    Authors
    Neil R. Ericsson; John S. Irons; Ralph W. Tryon; Neil R. Ericsson; John S. Irons; Ralph W. Tryon
    License

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

    Description

    Cross-country regressions explaining output growth often obtain a negative effect from inflation. However, that result is not robust, due to the selection of countries in sample, temporal aggregation, and omission of consequential variables in levels. This paper demonstrates some implications of these mis-specifications, both analytically and empirically. In particular, for most G-7 countries, annual time series of inflation and the log-level of output are cointegrated, thus rejecting the existence of a long-run relation between output growth and inflation. Typically, output and inflation are positively related in these cointegrating relationships: a price markup model helps to interpret this surprising feature.

  10. Kaluga Region Inflation

    • jp.knoema.com
    csv, json, sdmx, xls
    Updated Jan 18, 2021
    + more versions
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    Knoema (2021). Kaluga Region Inflation [Dataset]. https://jp.knoema.com/atlas/R%C3%BAssia/Kaluga-Region/Inflation
    Explore at:
    xls, csv, json, sdmxAvailable download formats
    Dataset updated
    Jan 18, 2021
    Dataset authored and provided by
    Knoemahttp://knoema.com/
    Time period covered
    Jan 1, 2020 - Mar 1, 2020
    Area covered
    Kaluga Oblast
    Variables measured
    Inflation for goods and services
    Description

    102.8 (% change from the corresponding period of the previous year) in 2020年3月. The consumer price index (CPI) measures the average % change from the same period previous year in prices that consumers pay for a basket of goods and services , commonly known as inflation.

  11. Buryatia, Republic of Inflation

    • jp.knoema.com
    csv, json, sdmx, xls
    Updated Jan 18, 2021
    + more versions
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    Knoema (2021). Buryatia, Republic of Inflation [Dataset]. https://jp.knoema.com/atlas/R%C3%BAssia/Buryatia-Republic-of/Inflation
    Explore at:
    json, xls, sdmx, csvAvailable download formats
    Dataset updated
    Jan 18, 2021
    Dataset authored and provided by
    Knoemahttp://knoema.com/
    Time period covered
    Jan 1, 2020 - Mar 1, 2020
    Area covered
    Buryatia
    Variables measured
    Inflation for goods and services
    Description

    103.2 (% change from the corresponding period of the previous year) in 2020年3月. The consumer price index (CPI) measures the average % change from the same period previous year in prices that consumers pay for a basket of goods and services , commonly known as inflation.

  12. N

    Richland, WA Median Household Income Trends (2010-2021, in 2022...

    • neilsberg.com
    csv, json
    Updated Jan 11, 2024
    + more versions
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    Neilsberg Research (2024). Richland, WA Median Household Income Trends (2010-2021, in 2022 inflation-adjusted dollars) [Dataset]. https://www.neilsberg.com/research/datasets/91ca885f-73f0-11ee-949f-3860777c1fe6/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Jan 11, 2024
    Dataset authored and provided by
    Neilsberg Research
    License

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

    Area covered
    Washington, Richland
    Variables measured
    Median Household Income, Median Household Income Year on Year Change, Median Household Income Year on Year Percent Change
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. It presents the median household income from the years 2010 to 2021 following an initial analysis and categorization of the census data. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series via current methods (R-CPI-U-RS). For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset illustrates the median household income in Richland, spanning the years from 2010 to 2021, with all figures adjusted to 2022 inflation-adjusted dollars. Based on the latest 2017-2021 5-Year Estimates from the American Community Survey, it displays how income varied over the last decade. The dataset can be utilized to gain insights into median household income trends and explore income variations.

    Key observations:

    From 2010 to 2021, the median household income for Richland increased by $1,406 (1.59%), as per the American Community Survey estimates. In comparison, median household income for the United States increased by $4,559 (6.51%) between 2010 and 2021.

    Analyzing the trend in median household income between the years 2010 and 2021, spanning 11 annual cycles, we observed that median household income, when adjusted for 2022 inflation using the Consumer Price Index retroactive series (R-CPI-U-RS), experienced growth year by year for 5 years and declined for 6 years.

    https://i.neilsberg.com/ch/richland-wa-median-household-income-trend.jpeg" alt="Richland, WA median household income trend (2010-2021, in 2022 inflation-adjusted dollars)">

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.

    Years for which data is available:

    • 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021

    Variables / Data Columns

    • Year: This column presents the data year from 2010 to 2021
    • Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific year
    • YOY Change($): Change in median household income between the current and the previous year, in 2022 inflation-adjusted dollars
    • YOY Change(%): Percent change in median household income between current and the previous year

    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 Richland median household income. You can refer the same here

  13. Z

    _Attention what is it like [Dataset]

    • data.niaid.nih.gov
    • explore.openaire.eu
    • +1more
    Updated Mar 7, 2021
    + more versions
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    Dinis Pereira, Vitor Manuel (2021). _Attention what is it like [Dataset] [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_780412
    Explore at:
    Dataset updated
    Mar 7, 2021
    Dataset authored and provided by
    Dinis Pereira, Vitor Manuel
    License

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

    Description

    R Core Team. (2016). R: A language and environment for statistical computing. R Foundation for Statistical Computing.

    Supplement to Occipital and left temporal instantaneous amplitude and frequency oscillations correlated with access and phenomenal consciousness (https://philpapers.org/rec/PEROAL-2).

    Occipital and left temporal instantaneous amplitude and frequency oscillations correlated with access and phenomenal consciousness move from the features of the ERP characterized in Occipital and Left Temporal EEG Correlates of Phenomenal Consciousness (Pereira, 2015, https://doi.org/10.1016/b978-0-12-802508-6.00018-1, https://philpapers.org/rec/PEROAL) towards the instantaneous amplitude and frequency of event-related changes correlated with a contrast in access and in phenomenology.

    Occipital and left temporal instantaneous amplitude and frequency oscillations correlated with access and phenomenal consciousness proceed as following.

    In the first section, empirical mode decomposition (EMD) with post processing (Xie, G., Guo, Y., Tong, S., and Ma, L., 2014. Calculate excess mortality during heatwaves using Hilbert-Huang transform algorithm. BMC medical research methodology, 14, 35) Ensemble Empirical Mode Decomposition (postEEMD) and Hilbert-Huang Transform (HHT).

    In the second section, calculated the variance inflation factor (VIF).

    In the third section, partial least squares regression (PLSR): the minimal root mean squared error of prediction (RMSEP).

    In the last section, partial least squares regression (PLSR): significance multivariate correlation (sMC) statistic.

  14. W

    Tuva, Republic of Services Inflation

    • knoema.com
    csv, json, sdmx, xls
    Updated May 15, 2020
    + more versions
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    Knoema (2020). Tuva, Republic of Services Inflation [Dataset]. https://knoema.com/atlas/R%C3%BAssia/Tuva-Republic-of/Services-Inflation
    Explore at:
    csv, sdmx, xls, jsonAvailable download formats
    Dataset updated
    May 15, 2020
    Dataset authored and provided by
    Knoema
    Time period covered
    Feb 1, 2020 - Apr 1, 2020
    Area covered
    Tuva Republic
    Variables measured
    Services Inflation
    Description

    In April 2020, services inflation for Tuva, Republic of was 104.6 % change from the corresponding period of the previous year. Services inflation of Tuva, Republic of increased from 104.6 % change from the corresponding period of the previous year in February 2020 to 104.6 % change from the corresponding period of the previous year in April 2020 growing at an average annual rate of 0.00%.

  15. Replication dataset and calculations for PIIE PB 15-7, Quantity Theory of...

    • piie.com
    Updated May 1, 2015
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    William R. Cline (2015). Replication dataset and calculations for PIIE PB 15-7, Quantity Theory of Money Redux? Will Inflation Be the Legacy of Quantitative Easing?, by William R. Cline. (2015). [Dataset]. https://www.piie.com/publications/policy-briefs/quantity-theory-money-redux-will-inflation-be-legacy-quantitative-easing
    Explore at:
    Dataset updated
    May 1, 2015
    Dataset provided by
    Peterson Institute for International Economicshttp://www.piie.com/
    Authors
    William R. Cline
    Description

    This data package includes the underlying data and files to replicate the calculations, charts, and tables presented in Quantity Theory of Money Redux? Will Inflation Be the Legacy of Quantitative Easing?, PIIE Policy Brief 15-7. If you use the data, please cite as: Cline, William R. (2015). Quantity Theory of Money Redux? Will Inflation Be the Legacy of Quantitative Easing?. PIIE Policy Brief 15-7. Peterson Institute for International Economics.

  16. Monthly core inflation rate Singapore 2020-2024

    • ai-chatbox.pro
    • statista.com
    Updated May 5, 2025
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    R. Hirschmann (2025). Monthly core inflation rate Singapore 2020-2024 [Dataset]. https://www.ai-chatbox.pro/?_=%2Ftopics%2F13160%2Fthe-2025-general-elections-in-singapore%2F%23XgboD02vawLYpGJjSPEePEUG%2FVFd%2Bik%3D
    Explore at:
    Dataset updated
    May 5, 2025
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    R. Hirschmann
    Area covered
    Singapore
    Description

    In March 2025, core inflation in Singapore was at 0.5 percent, down from 0.6 percent in the previous month. The core inflation rate in Singapore has been declining since a high of 5.5 percent in February 2023. The core inflation measures by the Monetary Authority of Singapore excludes accommodation and transport.

  17. N

    North Carolina Median Household Income Trends (2010-2021, in 2022...

    • neilsberg.com
    csv, json
    Updated Jan 11, 2024
    + more versions
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    Neilsberg Research (2024). North Carolina Median Household Income Trends (2010-2021, in 2022 inflation-adjusted dollars) [Dataset]. https://www.neilsberg.com/research/datasets/91aa585e-73f0-11ee-949f-3860777c1fe6/
    Explore at:
    json, csvAvailable download formats
    Dataset updated
    Jan 11, 2024
    Dataset authored and provided by
    Neilsberg Research
    License

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

    Area covered
    North Carolina
    Variables measured
    Median Household Income, Median Household Income Year on Year Change, Median Household Income Year on Year Percent Change
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. It presents the median household income from the years 2010 to 2021 following an initial analysis and categorization of the census data. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series via current methods (R-CPI-U-RS). For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset illustrates the median household income in North Carolina, spanning the years from 2010 to 2021, with all figures adjusted to 2022 inflation-adjusted dollars. Based on the latest 2017-2021 5-Year Estimates from the American Community Survey, it displays how income varied over the last decade. The dataset can be utilized to gain insights into median household income trends and explore income variations.

    Key observations:

    From 2010 to 2021, the median household income for North Carolina increased by $3,925 (6.38%), as per the American Community Survey estimates. In comparison, median household income for the United States increased by $4,559 (6.51%) between 2010 and 2021.

    Analyzing the trend in median household income between the years 2010 and 2021, spanning 11 annual cycles, we observed that median household income, when adjusted for 2022 inflation using the Consumer Price Index retroactive series (R-CPI-U-RS), experienced growth year by year for 7 years and declined for 4 years.

    https://i.neilsberg.com/ch/north-carolina-median-household-income-trend.jpeg" alt="North Carolina median household income trend (2010-2021, in 2022 inflation-adjusted dollars)">

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.

    Years for which data is available:

    • 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021

    Variables / Data Columns

    • Year: This column presents the data year from 2010 to 2021
    • Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific year
    • YOY Change($): Change in median household income between the current and the previous year, in 2022 inflation-adjusted dollars
    • YOY Change(%): Percent change in median household income between current and the previous year

    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 North Carolina median household income. You can refer the same here

  18. N

    Stuart, FL Median Household Income Trends (2010-2021, in 2022...

    • neilsberg.com
    csv, json
    Updated Jan 11, 2024
    + more versions
    Share
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    Cite
    Neilsberg Research (2024). Stuart, FL Median Household Income Trends (2010-2021, in 2022 inflation-adjusted dollars) [Dataset]. https://www.neilsberg.com/research/datasets/91e945f1-73f0-11ee-949f-3860777c1fe6/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Jan 11, 2024
    Dataset authored and provided by
    Neilsberg Research
    License

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

    Area covered
    Stuart, Florida
    Variables measured
    Median Household Income, Median Household Income Year on Year Change, Median Household Income Year on Year Percent Change
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. It presents the median household income from the years 2010 to 2021 following an initial analysis and categorization of the census data. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series via current methods (R-CPI-U-RS). For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset illustrates the median household income in Stuart, spanning the years from 2010 to 2021, with all figures adjusted to 2022 inflation-adjusted dollars. Based on the latest 2017-2021 5-Year Estimates from the American Community Survey, it displays how income varied over the last decade. The dataset can be utilized to gain insights into median household income trends and explore income variations.

    Key observations:

    From 2010 to 2021, the median household income for Stuart increased by $5,772 (10.72%), as per the American Community Survey estimates. In comparison, median household income for the United States increased by $4,559 (6.51%) between 2010 and 2021.

    Analyzing the trend in median household income between the years 2010 and 2021, spanning 11 annual cycles, we observed that median household income, when adjusted for 2022 inflation using the Consumer Price Index retroactive series (R-CPI-U-RS), experienced growth year by year for 5 years and declined for 6 years.

    https://i.neilsberg.com/ch/stuart-fl-median-household-income-trend.jpeg" alt="Stuart, FL median household income trend (2010-2021, in 2022 inflation-adjusted dollars)">

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.

    Years for which data is available:

    • 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021

    Variables / Data Columns

    • Year: This column presents the data year from 2010 to 2021
    • Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific year
    • YOY Change($): Change in median household income between the current and the previous year, in 2022 inflation-adjusted dollars
    • YOY Change(%): Percent change in median household income between current and the previous year

    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 Stuart median household income. You can refer the same here

  19. N

    Midland County, TX Median Household Income Trends (2010-2021, in 2022...

    • neilsberg.com
    csv, json
    Updated Jan 11, 2024
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Neilsberg Research (2024). Midland County, TX Median Household Income Trends (2010-2021, in 2022 inflation-adjusted dollars) [Dataset]. https://www.neilsberg.com/research/datasets/91881726-73f0-11ee-949f-3860777c1fe6/
    Explore at:
    csv, jsonAvailable download formats
    Dataset updated
    Jan 11, 2024
    Dataset authored and provided by
    Neilsberg Research
    License

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

    Area covered
    Texas, Midland County
    Variables measured
    Median Household Income, Median Household Income Year on Year Change, Median Household Income Year on Year Percent Change
    Measurement technique
    The data presented in this dataset is derived from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. It presents the median household income from the years 2010 to 2021 following an initial analysis and categorization of the census data. Subsequently, we adjusted these figures for inflation using the Consumer Price Index retroactive series via current methods (R-CPI-U-RS). For additional information about these estimations, please contact us via email at research@neilsberg.com
    Dataset funded by
    Neilsberg Research
    Description
    About this dataset

    Context

    The dataset illustrates the median household income in Midland County, spanning the years from 2010 to 2021, with all figures adjusted to 2022 inflation-adjusted dollars. Based on the latest 2017-2021 5-Year Estimates from the American Community Survey, it displays how income varied over the last decade. The dataset can be utilized to gain insights into median household income trends and explore income variations.

    Key observations:

    From 2010 to 2021, the median household income for Midland County increased by $21,211 (28.61%), as per the American Community Survey estimates. In comparison, median household income for the United States increased by $4,559 (6.51%) between 2010 and 2021.

    Analyzing the trend in median household income between the years 2010 and 2021, spanning 11 annual cycles, we observed that median household income, when adjusted for 2022 inflation using the Consumer Price Index retroactive series (R-CPI-U-RS), experienced growth year by year for 10 years and declined for 1 years.

    https://i.neilsberg.com/ch/midland-county-tx-median-household-income-trend.jpeg" alt="Midland County, TX median household income trend (2010-2021, in 2022 inflation-adjusted dollars)">

    Content

    When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.

    Years for which data is available:

    • 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021

    Variables / Data Columns

    • Year: This column presents the data year from 2010 to 2021
    • Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific year
    • YOY Change($): Change in median household income between the current and the previous year, in 2022 inflation-adjusted dollars
    • YOY Change(%): Percent change in median household income between current and the previous year

    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 Midland County median household income. You can refer the same here

  20. J

    International evidence on the efficacy of new‐Keynesian models of inflation...

    • journaldata.zbw.eu
    txt
    Updated Dec 8, 2022
    Share
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    Oleg Korenok; Stanislav Radchenko; Norman R. Swanson; Oleg Korenok; Stanislav Radchenko; Norman R. Swanson (2022). International evidence on the efficacy of new‐Keynesian models of inflation persistence (replication data) [Dataset]. http://doi.org/10.15456/jae.2022319.1307980160
    Explore at:
    txt(32070), txt(1682), txt(28252), txt(26226), txt(30039), txt(29967), txt(21789), txt(26364), txt(18533)Available download formats
    Dataset updated
    Dec 8, 2022
    Dataset provided by
    ZBW - Leibniz Informationszentrum Wirtschaft
    Authors
    Oleg Korenok; Stanislav Radchenko; Norman R. Swanson; Oleg Korenok; Stanislav Radchenko; Norman R. Swanson
    License

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

    Description

    We take an agnostic view of the Phillips curve debate, and carry out an empirical investigation of the relative and absolute efficacy of Calvo sticky price (SP), sticky information (SI), and sticky price with indexation models (SPI), with emphasis on their ability to mimic inflationary dynamics. We look at evidence for a group of 13 OECD countries, and consider three alternative measures of inflationary pressure, including the output gap, labor share, and unemployment. We find that the SPI model is preferable to the Calvo SP and the SI models because it captures the type of strong inflationary persistence that has in the past characterized the economies in our sample. However, two caveats to this conclusion are that improvement in performance is driven mostly by lagged inflation and that the SPI model overemphasizes inflationary persistence. There appears to be room for improvement in all models in order to induce them to better track inflation persistence.

Share
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Email
Click to copy link
Link copied
Close
Cite
(2025). Consumer Price Index for All Urban Consumers: Services Less Energy Services in U.S. City Average [Dataset]. https://fred.stlouisfed.org/series/CUSR0000SASLE

Consumer Price Index for All Urban Consumers: Services Less Energy Services in U.S. City Average

CUSR0000SASLE

Explore at:
2 scholarly articles cite this dataset (View in Google Scholar)
jsonAvailable download formats
Dataset updated
Jun 11, 2025
License

https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

Area covered
United States
Description

Graph and download economic data for Consumer Price Index for All Urban Consumers: Services Less Energy Services in U.S. City Average (CUSR0000SASLE) from Jan 1967 to May 2025 about energy, urban, consumer, services, CPI, inflation, price index, indexes, price, and USA.

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