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Core consumer prices In the Euro Area increased 2.30 percent in May of 2025 over the same month in the previous year. This dataset provides the latest reported value for - Euro Area Core Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.
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License information was derived automatically
Core consumer prices in Japan increased 3.70 percent in May of 2025 over the same month in the previous year. This dataset provides - Japan Core Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.
The inflation rate for the Retail Price Index (RPI) in the United Kingdom was 4.3 percent in May 2025, down from 4.5 percent in the previous month. From 2021 onwards, prices in the UK rose rapidly, with the RPI inflation rate peaking at 14.2 percent in October 2022. Although inflation fell in subsequent months, it wasn't until July 2023 that inflation fell below double digits, and as of late 2024, the RPI rate was still above three percent. The CPI and CPIH While the retail price index is still a popular method of calculating inflation, the consumer price index (CPI) is the current main measurement of inflation in the UK. There is also an additional price index, which includes some extra housing costs, known as the Consumer Price Index including homer occupiers' costs (CPIH) index, which is seen by the UK's Office of National Statistics as the official inflation rate. As of December 2024, the CPI inflation rate stood at 2.5 percent, while the CPIH rate was 3.5 percent. Core inflation down in 2024 Another way of measuring inflation is to strip out the volatility of energy and food prices and look at the underlying core inflation rate. As of December 2024, this was 3.2 percent, slightly higher than the overall CPI rate, but more aligned with the overall figure than it was in 2022 and 2023. When inflation peaked at 11.2 percent in October 2022, for example, core inflation stood at just 6.5 percent. After energy prices in 2023 fell relative to 2022, the overall inflation rate in the UK declined quite rapidly, with core inflation overtaking the overall rate in July 2023. During the most recent period of high inflation, core inflation peaked at 7.1 percent in May 2023, and while taking longer to fall than the overall figure, has generally been declining since then.
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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.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Inflation Rate in Japan decreased to 3.50 percent in May from 3.60 percent in April of 2025. This dataset provides the latest reported value for - Japan Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.
Just as in many other countries, the housing market in the UK grew substantially during the coronavirus pandemic, fueled by robust demand and low borrowing costs. Nevertheless, high inflation and the increase in mortgage rates has led to house price growth slowing down. According to the forecast, 2024 is expected to see house prices decrease by ***** percent. Between 2024 and 2028, the average house price growth is projected at *** percent. A contraction after a period of continuous growth In June 2022, the UK's house price index exceeded *** index points, meaning that since 2015 which was the base year for the index, house prices had increased by ** percent. In just two years, between 2020 and 2022, the index surged by ** index points. As the market stood in December 2023, the average price for a home stood at approximately ******* British pounds. Rents are expected to continue to grow According to another forecast, the prime residential market is also expected to see rental prices grow in the next years. Growth is forecast to be stronger in 2024 and slow down in the period between 2025 and 2028. The rental market in London is expected to follow a similar trend, with Central London slightly outperforming Greater London.
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Context
The dataset presents a breakdown of households across various income brackets in Rochester Hills, MI, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Rochester Hills, MI reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Rochester Hills households based on income levels.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income Levels:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Rochester Hills median household income. You can refer the same here
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Context
The dataset presents a breakdown of households across various income brackets in Fall River, MA, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Fall River, MA reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Fall River households based on income levels.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income Levels:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Fall River median household income. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Context
The dataset presents a breakdown of households across various income brackets in Troy, NY, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Troy, NY reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Troy households based on income levels.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income Levels:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Troy median household income. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents a breakdown of households across various income brackets in New York, NY, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for New York, NY reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of New York households based on income levels.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income Levels:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for New York median household income. You can refer the same here
The BIS Output Price Index for New Construction (2010): All New Construction for January to March 2014 increased by 1.7% on the previous quarter and by 4.3% year-on-year. Above average increases in output prices, on a quarterly and year-on-year basis, were noted in 2 new work sectors, namely the Private Commercial and Private Housing sectors.
The BIS Output Price Index for Repair and Maintenance Construction (2010): All Repair and Maintenance for January to March 2014 increased by 0.3% on the previous quarter and by 2.7% year-on-year. Much of the increase was accounted for by rises in the Private Housing Repair and Maintenance sector which saw above average output price increases of 3.1% year-on-year.
The BIS Tender Price Index for Public Sector Non-Housing (PUBSEC) January to March 2014 increased by 1.0% on the previous quarter and by 2.7% year-on-year. The BIS Tender Price Index of Social Housing (TPISH) January to March 2014 increased by 1.5% on the previous quarter and by 4.2% year-on-year.
The BIS Resource Cost Indices in January to March 2014 exhibited increasing costs in Building non-housing, house building, infrastructure, and road construction. Plus maintenance for building non-housing and maintenance for house building sectors. The BIS Resource Cost Index of Road Construction (ROCOS) increased by 0.8% on the previous quarter and by 0.8% year-on-year. While, the BIS Resource Cost Index of Infrastructure (FOCOS) increased by 0.5% on the previous quarter but remained unchanged year-on-year.
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Context
The dataset presents a breakdown of households across various income brackets in Napa, CA, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Napa, CA reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Napa households based on income levels.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Income Levels:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Napa median household income. You can refer the same here
Gross value added (GVA) for DCMS sectors (excluding Civil Society) is estimated to have grown by 6.6% in Quarter 2 (April to June) 2021 compared to Quarter 1 in real terms. This follows the easing of coronavirus (COVID-19) restrictions in the UK. By comparison, the whole UK economy grew by 4.8% in Quarter 2 compared to Quarter 1.
These monthly estimates suggest that GVA for DCMS sectors (excluding Civil Society) increased across all three months at 3.3% in April, 2.7% in May, and 1.4% in June 2021. These figures are provisional and will be revised at the next update. Estimates for Quarter 2 2021 are subject to more uncertainty than usual as a result of the challenges faced by the Office for National Statistics estimating GVA in the current conditions.
19 August 2021. The next release will be in November 2021 (provisional).
These Economic Estimates are Official Statistics used to provide an estimate of the economic contribution of DCMS Sectors in terms of gross value added (GVA), for the period January 2019 to June 2021.
Provisional monthly GVA in 2019 and 2020 was first published in March 2021 as an ad hoc statistical release. This current release contains new figures for January to June 2021 and revised estimates for previous months.
Estimates are in chained volume measures (i.e. have been adjusted for inflation) and are seasonally adjusted.
These timely estimates should only be used to illustrate general trends, rather than be taken as definitive figures. These figures will not be as accurate as our annual National Statistics release of gross value added for DCMS sectors (which will be published in Winter 2021).
You can use these estimates to:
You should not use these estimates to:
The findings are calculated based on published ONS data sources including the Index of Services and Index of Production.
These data sources provide an estimate of the monthly change in GVA for all UK industries. However, the data is only available for broader industry groups, whereas DCMS sectors are defined at a more detailed industrial level. For example, GVA for ‘Cultural education’ is estimated based on the trend for all education. Sectors such as ‘Cultural education’ may have been affected differently by COVID-19 compared to education in general. These estimates are also based on the composition of the economy in 2018. Overall, this means the accuracy of monthly GVA for DCMS sectors is likely to be lower for months in 2020 and 2021.
The technical guidance contains further information about data sources, methodology, and the validation and accuracy of these estimates.
Figures are provisional and subject to revision on a monthly basis when the ONS Index of Services and Index of Production are updated. Figures for the latest month will be highly uncertain.
The impact of these revisions is highlighted in the following example; the first estimate of Cultural Sector GVA for October 2020 was £2.2 billion. This has since been revised to £2.5 billion, which is a 15% increase in revised GVA.
These statistics cover the contributions of the following DCMS sectors to the UK economy;
Users should note that there is overlap between DCMS sector definitions and that the Telecoms sector sits wholly within the Digital sector.
Timely estimates of Civil Society GVA are not available at present.
DCMS aims to continuously improve the quality of estimates and better meet user needs. DCMS welcomes feedback on this release. Feedback should be sent to DCMS via email at evidence@dcms.gov.uk.
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Context
The dataset presents a breakdown of households across various income brackets in Oswego, NY, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Oswego, NY reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Oswego households based on income levels.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income Levels:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Oswego median household income. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents a breakdown of households across various income brackets in Grafton County, NH, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Grafton County, NH reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Grafton County households based on income levels.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Income Levels:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Grafton County median household income. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents a breakdown of households across various income brackets in Albuquerque, NM, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Albuquerque, NM reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Albuquerque households based on income levels.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Income Levels:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Albuquerque median household income. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents a breakdown of households across various income brackets in Marysville, WA, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Marysville, WA reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Marysville households based on income levels.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Income Levels:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Marysville median household income. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents a breakdown of households across various income brackets in Meridian, MS, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Meridian, MS reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Meridian households based on income levels.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income Levels:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Meridian median household income. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents a breakdown of households across various income brackets in Sanilac County, MI, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Sanilac County, MI reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Sanilac County households based on income levels.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Income Levels:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Sanilac County median household income. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents a breakdown of households across various income brackets in Madison County, AL, as reported by the U.S. Census Bureau. The Census Bureau classifies households into different categories, including total households, family households, and non-family households. Our analysis of U.S. Census Bureau American Community Survey data for Madison County, AL reveals how household income distribution varies among these categories. The dataset highlights the variation in number of households with income, offering valuable insights into the distribution of Madison County households based on income levels.
Key observations
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Income Levels:
Variables / Data Columns
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.
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/.
This dataset is a part of the main dataset for Madison County median household income. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Core consumer prices In the Euro Area increased 2.30 percent in May of 2025 over the same month in the previous year. This dataset provides the latest reported value for - Euro Area Core Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.