100+ datasets found
  1. U.S. projected annual inflation rate 2010-2029

    • statista.com
    Updated Aug 21, 2024
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    Statista (2024). U.S. projected annual inflation rate 2010-2029 [Dataset]. https://www.statista.com/statistics/244983/projected-inflation-rate-in-the-united-states/
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    Dataset updated
    Aug 21, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    The inflation rate in the United States is expected to decrease to 2.1 percent by 2029. 2022 saw a year of exceptionally high inflation, reaching eight percent for the year. The data represents U.S. city averages. The base period was 1982-84. In economics, the inflation rate is a measurement of inflation, the rate of increase of a price index (in this case: consumer price index). It is the percentage rate of change in prices level over time. The rate of decrease in the purchasing power of money is approximately equal. According to the forecast, prices will increase by 2.9 percent in 2024. The annual inflation rate for previous years can be found here and the consumer price index for all urban consumers here. The monthly inflation rate for the United States can also be accessed here. Inflation in the U.S.Inflation is a term used to describe a general rise in the price of goods and services in an economy over a given period of time. Inflation in the United States is calculated using the consumer price index (CPI). The consumer price index is a measure of change in the price level of a preselected market basket of consumer goods and services purchased by households. This forecast of U.S. inflation was prepared by the International Monetary Fund. They project that inflation will stay higher than average throughout 2023, followed by a decrease to around roughly two percent annual rise in the general level of prices until 2028. Considering the annual inflation rate in the United States in 2021, a two percent inflation rate is a very moderate projection. The 2022 spike in inflation in the United States and worldwide is due to a variety of factors that have put constraints on various aspects of the economy. These factors include COVID-19 pandemic spending and supply-chain constraints, disruptions due to the war in Ukraine, and pandemic related changes in the labor force. Although the moderate inflation of prices between two and three percent is considered normal in a modern economy, countries’ central banks try to prevent severe inflation and deflation to keep the growth of prices to a minimum. Severe inflation is considered dangerous to a country’s economy because it can rapidly diminish the population’s purchasing power and thus damage the GDP .

  2. o

    Rural Inflation Project

    • openicpsr.org
    Updated Jul 1, 2025
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    Scott Loveridge (2025). Rural Inflation Project [Dataset]. http://doi.org/10.3886/E235003V1
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    Dataset updated
    Jul 1, 2025
    Dataset provided by
    Michigan State University
    Authors
    Scott Loveridge
    License

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

    Description

    Testing methods of gathering data on rural inflation.

  3. Inflation Nowcasting

    • clevelandfed.org
    json
    Updated Mar 10, 2017
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    Federal Reserve Bank of Cleveland (2017). Inflation Nowcasting [Dataset]. https://www.clevelandfed.org/indicators-and-data/inflation-nowcasting
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    jsonAvailable download formats
    Dataset updated
    Mar 10, 2017
    Dataset authored and provided by
    Federal Reserve Bank of Clevelandhttps://www.clevelandfed.org/
    License

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

    Description

    The Federal Reserve Bank of Cleveland provides daily “nowcasts” of inflation for two popular price indexes, the price index for personal consumption expenditures (PCE) and the Consumer Price Index (CPI). These nowcasts give a sense of where inflation is today. Released each business day.

  4. o

    Data and Code for: Estimating the Optimal Inflation Target from Trends in...

    • openicpsr.org
    Updated Feb 10, 2022
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    Klaus Adam; Henning Weber (2022). Data and Code for: Estimating the Optimal Inflation Target from Trends in Relative Prices [Dataset]. http://doi.org/10.3886/E162161V1
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    Dataset updated
    Feb 10, 2022
    Dataset provided by
    American Economic Association
    Authors
    Klaus Adam; Henning Weber
    License

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

    Time period covered
    1996 - 2016
    Area covered
    United Kingdom
    Description

    This repository provides the data and MatLab code producing the figures and tables in "Estimating the Optimal Inflation Target from Trends in Relative Prices" by Klaus Adam and Henning Weber, American Economic Journal: Macroeconomics, forthcoming as of Febuary 2022.

  5. BIL and IRA Funded Projects, Fiscal Years 2022-2025

    • catalog.data.gov
    • s.cnmilf.com
    • +2more
    Updated May 9, 2025
    + more versions
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    Bureau of Indian Affairs (BIA) (2025). BIL and IRA Funded Projects, Fiscal Years 2022-2025 [Dataset]. https://catalog.data.gov/dataset/bipartisan-infrastructure-law-bil-funded-projects-fiscal-years-2022-23-32e7a
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    Dataset updated
    May 9, 2025
    Dataset provided by
    Bureau of Indian Affairshttp://www.bia.gov/
    Description

    On November 15, 2021, President Biden signed the Bipartisan Infrastructure Law (BIL), which invests more than $13 billion directly in Tribal communities across the country and makes Tribal communities eligible for billions more. For further explanation of the law please visit https://www.congress.gov/bill/117th-congress/house-bill/3684/text. These resources go to many Federal agencies to expand access to clean drinking water for Native communities, ensure every Native American has access to high-speed internet, tackle the climate crisis, advance environmental justice, and invest in Tribal communities that have too often been left behind. On August 16, 2022, President Biden signed the Inflation Reduction Act into law, marking the most significant action Congress has taken on clean energy and climate change in the nation’s history. With the stroke of his pen, the President redefined American leadership in confronting the existential threat of the climate crisis and set forth a new era of American innovation and ingenuity to lower consumer costs and drive the global clean energy economy forward. More information on this can be found here: https://www.whitehouse.gov/cleanenergy/inflation-reduction-act-guidebook/. This dataset illustrates the locations of Bureau of Indian Affairs projects funded by the Bipartisan Infrastructure Law and Inflation Reduction Act in Fiscal Year 2022, 2023, and 2024. The points illustrated in this dataset are the locations of Bureau of Indian Affairs projects funded by the Bipartisan Infrastructure Law and Inflation Reduction Act in Fiscal Year 2022 and 2023. The locations for the points in this layer were provided by the persons involved in the following groups: Division of Water and Power, DWP, Ecosystem Restoration, Irrigation, Power, Water Sanitation, Dam Safety, Branch of Geospatial Support, Bureau of Indian Affairs, BIA.GIS point feature class was created by Bureau of Indian Affairs - Branch Of Geospatial Support (BOGS), Division of Water and Power (DWP), Ecosystem Restoration, Irrigation, Bureau of Indian Affairs (BIA), Tribal Leaders Directory: https://www.bia.gov/service/tribal-leaders-directory/tld-csvexcel-dataset, The Department of the Interior | Strategic Hazard Identification and Risk Assessment Project: https://www.doi.gov/emergency/shira#main-content

  6. d

    \"Targeted Price Controls on Supermarket Products\". Review of Economics and...

    • search.dataone.org
    • dataverse.harvard.edu
    Updated Nov 22, 2023
    + more versions
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    Aparicio, Diego; Cavallo, Alberto (2023). \"Targeted Price Controls on Supermarket Products\". Review of Economics and Statistics (Forthcoming) [Dataset]. http://doi.org/10.7910/DVN/EUKNAU
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    Dataset updated
    Nov 22, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Aparicio, Diego; Cavallo, Alberto
    Description

    We study the impact of targeted price controls on supermarket products in Argentina between 2007 and 2015. Using web-scraping methods, we collected daily prices for controlled and non-controlled goods and examined the differential effects of the policy on inflation, product availability, entry and exit, and price dispersion. We first show that price controls have only a small and temporary effect on inflation that reverses itself as soon as the controls are lifted. Second, contrary to common beliefs, we find that controlled goods are consistently available for sale. Third, firms compensate for price controls by introducing new product varieties at higher prices, thereby increasing price dispersion within narrow categories. Overall, our results show that targeted price controls are just as ineffective as more traditional forms of price controls in reducing aggregate inflation.

  7. o

    Replication data for: Public Debt and Changing Inflation Targets

    • openicpsr.org
    Updated Oct 1, 2016
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    Michael U. Krause; Stéphane Moyen (2016). Replication data for: Public Debt and Changing Inflation Targets [Dataset]. http://doi.org/10.3886/E114060V1
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    Dataset updated
    Oct 1, 2016
    Dataset provided by
    American Economic Association
    Authors
    Michael U. Krause; Stéphane Moyen
    Description

    What are the effects of a higher central bank inflation target on the burden of real public debt? Several recent proposals have suggested that even a moderate increase in the inflation target can have a pronounced effect on real public debt. We consider this question in a New Keynesian model with a maturity structure of public debt and an imperfectly observed inflation target. We find that moderate changes in the inflation target only have significant effects on real public debt if they are essentially permanent. Moreover, the additional benefits of not communicating a change in the inflation target are minor.

  8. F

    Producer Price Index by Industry: Engineering Services: All Other...

    • fred.stlouisfed.org
    json
    Updated Jul 16, 2025
    + more versions
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    (2025). Producer Price Index by Industry: Engineering Services: All Other Non-Building Related Engineering Projects [Dataset]. https://fred.stlouisfed.org/series/PCU541330541330203
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    jsonAvailable download formats
    Dataset updated
    Jul 16, 2025
    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: Engineering Services: All Other Non-Building Related Engineering Projects (PCU541330541330203) from Dec 2009 to Jun 2025 about engineering, services, PPI, industry, inflation, price index, indexes, price, and USA.

  9. Average inflation rate in the United Kingdom 1980-2030

    • statista.com
    • ai-chatbox.pro
    Updated Jun 18, 2025
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    Statista (2025). Average inflation rate in the United Kingdom 1980-2030 [Dataset]. https://www.statista.com/statistics/270384/inflation-rate-in-the-united-kingdom/
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    Dataset updated
    Jun 18, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United Kingdom
    Description

    In 2024, the average inflation rate in the United Kingdom was approximately 2.53 percent. Between 1980 and 2024, the figure dropped by around 14.32 percentage points, though the decline followed an uneven course rather than a steady trajectory. The inflation is forecast to decline by about 0.53 percentage points from 2024 to 2030, fluctuating as it trends downward.This indicator measures inflation based upon the year-on-year change in the average consumer price index, expressed in percent. The latter expresses a country's average level of prices based on a typical basket of consumer goods and services.

  10. o

    Data and Code for: Expected and Realized Inflation in Historical Perspective...

    • openicpsr.org
    Updated Apr 5, 2022
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    Carola Binder; Rupal Kamdar (2022). Data and Code for: Expected and Realized Inflation in Historical Perspective [Dataset]. http://doi.org/10.3886/E166881V1
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    Dataset updated
    Apr 5, 2022
    Dataset provided by
    American Economic Association
    Authors
    Carola Binder; Rupal Kamdar
    License

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

    Time period covered
    1911 - 2022
    Area covered
    United States
    Description

    These are the replication files to produce the figures and table in our Journal of Economic Perspectives paper about the relationship between actual and expected inflation in historical perspective.

  11. o

    Data and Code for: Learning-through-Survey in Inflation Expectations

    • openicpsr.org
    delimited
    Updated Mar 31, 2022
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    Gwangmin Kim; Carola Binder (2022). Data and Code for: Learning-through-Survey in Inflation Expectations [Dataset]. http://doi.org/10.3886/E166481V1
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    delimitedAvailable download formats
    Dataset updated
    Mar 31, 2022
    Dataset provided by
    American Economic Association
    Authors
    Gwangmin Kim; Carola Binder
    License

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

    Area covered
    United States
    Description

    These files contain the code and data for the journal article "Learning-through-Survey in Inflation Expectations," American Economic Journal: Macroeconomics.When surveys rely on repeat participants, this raises the possibility that survey participation may affect future responses, perhaps by prompting information acquisition between survey waves. We show that these "learning-through-survey" effects are large for household inflation expectations. Repeat survey participants generally have lower inflation expectations and uncertainty, particularly if their initial uncertainty was high. Consequently, repeat participants may be more informed about or attentive to inflation. This has important implications: for example, inflation expectations of new participants are more influenced by oil prices, and estimates of the elasticity of intertemporal substitution are lower for new participants.

  12. F

    Producer Price Index by Industry: Engineering Services: Transportation...

    • fred.stlouisfed.org
    json
    Updated Jul 16, 2025
    + more versions
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    (2025). Producer Price Index by Industry: Engineering Services: Transportation Engineering Projects [Dataset]. https://fred.stlouisfed.org/series/PCU541330541330201
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jul 16, 2025
    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: Engineering Services: Transportation Engineering Projects (PCU541330541330201) from Dec 2009 to Jun 2025 about engineering, transportation, services, PPI, industry, inflation, price index, indexes, price, and USA.

  13. Replication data for: International Competition and Inflation: A New...

    • search.datacite.org
    • openicpsr.org
    Updated 2010
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    Luca Guerrieri; Christopher Gust; J. David López-Salido (2010). Replication data for: International Competition and Inflation: A New Keynesian Perspective [Dataset]. http://doi.org/10.3886/e114187
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    Dataset updated
    2010
    Dataset provided by
    DataCitehttps://www.datacite.org/
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    Luca Guerrieri; Christopher Gust; J. David López-Salido
    Description

    We develop and estimate an open economy New Keynesian Phillips Curve (NKPC) in which variable demand elasticities give rise to movements in desired markups in response to changes in competitive pressure from abroad. A parametric restriction yields the standard NKPC under constant elasticity and no role for foreign competition to influence domestic inflation. Foreign competition plays an important role in accounting for the behavior of traded goods price inflation. Foreign competition accounted for more than half of a 4 percentage point decline in domestic goods price inflation in the 1990s. Our results also provide evidence against demand curves with a constant elasticity. (JEL E12, E22, E31, F14, F41)

  14. 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

  15. o

    Data and Code for: Measuring Inflation Expectations in Interwar Britain

    • openicpsr.org
    Updated Sep 6, 2022
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    Jason lennard (2022). Data and Code for: Measuring Inflation Expectations in Interwar Britain [Dataset]. http://doi.org/10.3886/E179361V1
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    Dataset updated
    Sep 6, 2022
    Dataset provided by
    London School of Economics
    Authors
    Jason lennard
    License

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

    Area covered
    United Kingdom
    Description

    What caused the recovery from the British Great Depression? A leading explanation - the “expectations channel” - suggests that a shift in expected inflation lowered real interest rates and stimulated consumption and investment. However, few studies have measured, or tested the economic consequences of, inflation expectations. In this paper, we collect high-frequency information from primary and secondary sources to measure expected inflation in the United Kingdom between the wars. A VAR model suggests that inflation expectations were an important source of the early stages of economic recovery in interwar Britain.

  16. Global Inflation-adjusted cost of onshore wind projects 2022, by country

    • statista.com
    Updated Apr 17, 2025
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    Statista (2025). Global Inflation-adjusted cost of onshore wind projects 2022, by country [Dataset]. https://www.statista.com/statistics/1477349/adjusted-costs-of-onshore-wind-projects-by-country/
    Explore at:
    Dataset updated
    Apr 17, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2022
    Area covered
    Worldwide
    Description

    In 2022, South Korea was the country with the highest inflation-adjusted cost for land-based wind projects worldwide, at 1,700 U.S. dollars per kilowatt. Germany came in second place at 1,679 U.S. dollars per kilowatt.

  17. N

    Rhodes, IA 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). Rhodes, IA Median Household Income Trends (2010-2021, in 2022 inflation-adjusted dollars) [Dataset]. https://www.neilsberg.com/research/datasets/91c9c50a-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
    Iowa, Rhodes
    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 Rhodes, 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 Rhodes increased by $26,129 (61.97%), 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 9 years and declined for 2 years.

    https://i.neilsberg.com/ch/rhodes-ia-median-household-income-trend.jpeg" alt="Rhodes, IA 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 Rhodes median household income. You can refer the same here

  18. Price change on annual basis of 32 different building materials in the U.S....

    • statista.com
    Updated Jun 15, 2022
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    Statista (2025). Price change on annual basis of 32 different building materials in the U.S. 2014-2025 [Dataset]. https://www.statista.com/statistics/1046602/inflation-construction-materials-us/
    Explore at:
    Dataset updated
    Jun 15, 2022
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Mar 2014 - Jun 2025
    Area covered
    United States
    Description

    Building materials made of steel, copper and other metals had some of the highest price growth rates in the U.S. in the first half of 2025 in comparison to the previous year. The growth rate of the cost of several construction materials was slightly lower than in late 2024. It is important to note, though, that the figures provided are Producer Price Indices, which cover production within the United States, but do not include imports or tariffs. This might matter for lumber, as Canada's wood production is normally large enough that the U.S. can import it from its neighboring country. Construction material prices in the United Kingdom Similarly to these trends in the U.S., at that time the price growth rate of construction materials in the UK were generally lower 2024 than in 2023. Nevertheless, the cost of some construction materials in the UK still rose that year, with several of those items reaching price growth rates of over **** percent. Considering that those materials make up a very big share of the costs incurred for a construction project, those developments may also have affected the average construction output price in the UK. Construction material shortages during the COVID-19 pandemic During the first years of the COVID-19 pandemic, there often were supply problems and material shortages, which created instability in the construction market. According to a survey among construction contractors, the construction materials most affected by shortages in the U.S. during most of 2021 were steel and lumber. This was also a problem on the other side of the Atlantic: The share of building construction companies experiencing shortages in Germany soared between March and June 2021, staying at high levels for over a year. Meanwhile, the shortage of material or equipment was one of the main factors limiting the building activity in France in June 2022.

  19. HUD: Renewal Funding Inflation Factors

    • datalumos.org
    Updated Feb 14, 2025
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    United States Department of Housing and Urban Development (2025). HUD: Renewal Funding Inflation Factors [Dataset]. http://doi.org/10.3886/E219407V1
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    Dataset updated
    Feb 14, 2025
    Dataset authored and provided by
    United States Department of Housing and Urban Developmenthttp://www.hud.gov/
    License

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

    Time period covered
    2012 - 2024
    Description

    Renewal Funding Inflation Factors are used in the allocation of Housing Choice Voucher funds among Public Housing Agencies. Prior to FY 2012, these factors were called Renewal Funding Annual Adjustment Factors. In the FY 2012 HUD Appropriations bill, Congress changed the name of these factors in recognition of HUD’s new methodology for calculating the factors, which now take advantage of ongoing PD&R research aimed at better understanding the drivers of change in per-unit-costs (PUC) in the voucher program. Renewal Funding Inflation Factors have been developed to account for the expected annual change in average PUC in the voucher program using historical program data, coupled with several economic indices used to capture key components of the economic climate which also assist in explaining the changes in PUC.

  20. Z

    Inflation Reduction Act Energy Communities

    • data.niaid.nih.gov
    • zenodo.org
    Updated Jul 15, 2024
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    Isaac, Cecelia (2024). Inflation Reduction Act Energy Communities [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_7192015
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    Dataset updated
    Jul 15, 2024
    Dataset authored and provided by
    Isaac, Cecelia
    License

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

    Description

    The Inflation Reduction Act of 2022 (IRA) became law on August 8, 2022. Under the law, new qualifying renewable and/or carbon-free electricity generation projects constructed in certain areas of the US, called energy communities, are eligible for bonus worth an additional 10% to the value of the production tax credit or a 10 percentage point increase in the value of the investment tax credit. The IRA does not explicitly map or list these specific communities. Instead, eligible communities are defined by a series of qualifications:

    a brownfield site,

    a metropolitan statistical area (MSA) or non-metropolitan statistical area with either (a) 0.17% or greater employment or (b) 25% or greater local tax revenues related to the extraction, processing, transport, or storage of coal, oil, or natural gas; and an unemployment rate at or above the national average for the previous year, or

    a census tract containing or adjacent to (a) a coal mine closed after December 31, 1999 or (b) a coal-fired electric generating unit retired after December 31, 2009.

    These maps and data layers contain GIS data for coal mines, coal-fired power plants, fossil energy related employment, and brownfield sites. Each record represents a point, tract or metropolitan statistical area and non-metropolitan statistical area with attributes including plant type, operating information, GEOID, etc. The input data used includes:

    Brownfields – Source: EPA. No analysis was performed on this data layer. However, tract polygon layers have a column denoting brownfield presence (0 for no brownfield site, 1 if the tract contains a brownfield somewhere within the polygon).

    Eligible Employment MSAs (“Final_Employment_Qualifying_MSAs”) – Source: US Census County Business Patterns. MSAs and non-MSA regions with employment over 0.17% in the fossil fuel industry (defined here as NAICS codes 211, 2121, 213, 23712, 324, 4247, and 486) and unemployment greater than or equal to 3.9% (the average national unemployment rate in 2021, according to the Bureau of Labor Statistics).

    --Possibly Eligible MSAs (“FossilFuel_Employment_Qualifying_MSAs”) are MSA and non-MSA regions that meet or exceed the 0.17% employment in the fossil fuel industry threshold but do not exceed the unemployment threshold.

    --Relevant columns include:

      a) SUM_nhgis0: Total employment in 2020.
    
    
      b) SUM_nhgis1: Total unemployment in 2020.
    
    
      c) P_Unemp: Percent unemployment in 2020.
    
    
      d) Q_Unemp: Boolean column indicating if the MSA or non-MSA’s unemployment rate is at or above the national average of 3.9%.
    
    
      e) FF_Qual: Boolean column indicating if the MSA or non-MSA had employment in the fossil fuel industry at or above 0.17% in the past 11 years.
    
    
      f) final_Qual: Boolean column indicating if an MSA or non-MSA qualifies for both unemployment rate and fossil fuel employment under the IRA.
    

    Retired Power Plants – Source: EIA via HFLID. Qualifying power plants were selected by use of coal in at least one generator, and if they were retired (RET_DATE) on or after January 1, 2010. This data goes through December 2021.

    --Adjacent tract data was derived by Cecelia Isaac using ESRI ArcGIS Pro.

    Abandoned Coal Mines – Source: MSHA. Mines labeled “Abandoned”, “Abandoned and Sealed” or “NonProducing” between January 1, 2000 and September 2022.

    --Adjacent tract data was derived by Cecelia Isaac using ESRI ArcGIS Pro.

    5) US State Borders– Source: IPUMS NHGIS.

    Also included here are polygon shapefiles for Onshore Wind and Solar Candidate Project Areas from Princeton REPEAT. These files have been updated to include columns related to the energy communities.

    New columns include:

    CoalPlantTract: Boolean column indicating if the CPA is within a tract that qualifies because of a retired coal plant.

    CoalMineTract: Boolean column indicating if the CPA is within a tract that qualifies because of a closed coal mine.

    FossilFuelEmp: Boolean column indicating if the CPA is within an MSA or non-MSA with greater than or equal to 0.17% employment in the fossil fuel industry.

    UnempQualification: Boolean column indicating if the CPA is within an MSA or non-MSA with greater than or equal to 0.17% employment in the fossil fuel industry.

    MSA_non_to: The code of the MSA or non-MSA area that contains the CPA.

    P_Unemp: The percent unemployment of the MSA or non-MSA that contains the CPA in 2021.

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Statista (2024). U.S. projected annual inflation rate 2010-2029 [Dataset]. https://www.statista.com/statistics/244983/projected-inflation-rate-in-the-united-states/
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U.S. projected annual inflation rate 2010-2029

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49 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Aug 21, 2024
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
United States
Description

The inflation rate in the United States is expected to decrease to 2.1 percent by 2029. 2022 saw a year of exceptionally high inflation, reaching eight percent for the year. The data represents U.S. city averages. The base period was 1982-84. In economics, the inflation rate is a measurement of inflation, the rate of increase of a price index (in this case: consumer price index). It is the percentage rate of change in prices level over time. The rate of decrease in the purchasing power of money is approximately equal. According to the forecast, prices will increase by 2.9 percent in 2024. The annual inflation rate for previous years can be found here and the consumer price index for all urban consumers here. The monthly inflation rate for the United States can also be accessed here. Inflation in the U.S.Inflation is a term used to describe a general rise in the price of goods and services in an economy over a given period of time. Inflation in the United States is calculated using the consumer price index (CPI). The consumer price index is a measure of change in the price level of a preselected market basket of consumer goods and services purchased by households. This forecast of U.S. inflation was prepared by the International Monetary Fund. They project that inflation will stay higher than average throughout 2023, followed by a decrease to around roughly two percent annual rise in the general level of prices until 2028. Considering the annual inflation rate in the United States in 2021, a two percent inflation rate is a very moderate projection. The 2022 spike in inflation in the United States and worldwide is due to a variety of factors that have put constraints on various aspects of the economy. These factors include COVID-19 pandemic spending and supply-chain constraints, disruptions due to the war in Ukraine, and pandemic related changes in the labor force. Although the moderate inflation of prices between two and three percent is considered normal in a modern economy, countries’ central banks try to prevent severe inflation and deflation to keep the growth of prices to a minimum. Severe inflation is considered dangerous to a country’s economy because it can rapidly diminish the population’s purchasing power and thus damage the GDP .

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