Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Government spending in the United States was last recorded at 34.4 percent of GDP in 2023 . This dataset provides - United States Government Spending To Gdp- 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
Cost of food in the United States increased 2.60 percent in February of 2025 over the same month in the previous year. This dataset provides the latest reported value for - United States Food Inflation - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
Measures of monthly UK inflation data including CPIH, CPI and RPI. These tables complement the consumer price inflation time series dataset.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Inflation Rate in India decreased to 3.61 percent in February from 4.31 percent in January of 2025. This dataset provides - India 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 Turkey decreased to 39.05 percent in February from 42.12 percent in January of 2025. This dataset provides the latest reported value for - Turkey Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
Representative items within the Consumer Prices Index including owner occupiers' housing costs, Consumer Prices Index and Retail Prices Index for the basket of goods and services.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
The world has become much more peaceful, and yet, even after adjusting for inflation, global military spending is now three times greater than at the height of the Cold War. These developments have motivated a renewed interest from both policy makers and scholars about the drivers of military spending and the implications that follow. Existing findings on the relationship between threat and arming and arms races and war hinge on the completeness and accuracy of existing military spending data. Moreover, data on military spending is used to measure important concepts from international relations such as the distribution of power, balancing, the severity of states’ military burdens, and arms races. Everything we know about which states are most powerful, whether nations are balancing, and whether military burdens and arms races are growing more or less severe rests on the accuracy of existing military spending estimates.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Inflation Rate in China decreased to -0.70 percent in February from 0.50 percent in January of 2025. This dataset provides - China Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.
Envestnet®| Yodlee®'s Bank Transaction Data (Aggregate/Row) Panels consist of de-identified, near-real time (T+1) USA credit/debit/ACH transaction level data – offering a wide view of the consumer activity ecosystem. The underlying data is sourced from end users leveraging the aggregation portion of the Envestnet®| Yodlee®'s financial technology platform.
Envestnet | Yodlee Consumer Panels (Aggregate/Row) include data relating to millions of transactions, including ticket size and merchant location. The dataset includes de-identified credit/debit card and bank transactions (such as a payroll deposit, account transfer, or mortgage payment). Our coverage offers insights into areas such as consumer, TMT, energy, REITs, internet, utilities, ecommerce, MBS, CMBS, equities, credit, commodities, FX, and corporate activity. We apply rigorous data science practices to deliver key KPIs daily that are focused, relevant, and ready to put into production.
We offer free trials. Our team is available to provide support for loading, validation, sample scripts, or other services you may need to generate insights from our data.
Investors, corporate researchers, and corporates can use our data to answer some key business questions such as: - How much are consumers spending with specific merchants/brands and how is that changing over time? - Is the share of consumer spend at a specific merchant increasing or decreasing? - How are consumers reacting to new products or services launched by merchants? - For loyal customers, how is the share of spend changing over time? - What is the company’s market share in a region for similar customers? - Is the company’s loyal user base increasing or decreasing? - Is the lifetime customer value increasing or decreasing?
Additional Use Cases: - Use spending data to analyze sales/revenue broadly (sector-wide) or granular (company-specific). Historically, our tracked consumer spend has correlated above 85% with company-reported data from thousands of firms. Users can sort and filter by many metrics and KPIs, such as sales and transaction growth rates and online or offline transactions, as well as view customer behavior within a geographic market at a state or city level. - Reveal cohort consumer behavior to decipher long-term behavioral consumer spending shifts. Measure market share, wallet share, loyalty, consumer lifetime value, retention, demographics, and more.) - Study the effects of inflation rates via such metrics as increased total spend, ticket size, and number of transactions. - Seek out alpha-generating signals or manage your business strategically with essential, aggregated transaction and spending data analytics.
Use Cases Categories (Our data provides an innumerable amount of use cases, and we look forward to working with new ones): 1. Market Research: Company Analysis, Company Valuation, Competitive Intelligence, Competitor Analysis, Competitor Analytics, Competitor Insights, Customer Data Enrichment, Customer Data Insights, Customer Data Intelligence, Demand Forecasting, Ecommerce Intelligence, Employee Pay Strategy, Employment Analytics, Job Income Analysis, Job Market Pricing, Marketing, Marketing Data Enrichment, Marketing Intelligence, Marketing Strategy, Payment History Analytics, Price Analysis, Pricing Analytics, Retail, Retail Analytics, Retail Intelligence, Retail POS Data Analysis, and Salary Benchmarking
Investment Research: Financial Services, Hedge Funds, Investing, Mergers & Acquisitions (M&A), Stock Picking, Venture Capital (VC)
Consumer Analysis: Consumer Data Enrichment, Consumer Intelligence
Market Data: AnalyticsB2C Data Enrichment, Bank Data Enrichment, Behavioral Analytics, Benchmarking, Customer Insights, Customer Intelligence, Data Enhancement, Data Enrichment, Data Intelligence, Data Modeling, Ecommerce Analysis, Ecommerce Data Enrichment, Economic Analysis, Financial Data Enrichment, Financial Intelligence, Local Economic Forecasting, Location-based Analytics, Market Analysis, Market Analytics, Market Intelligence, Market Potential Analysis, Market Research, Market Share Analysis, Sales, Sales Data Enrichment, Sales Enablement, Sales Insights, Sales Intelligence, Spending Analytics, Stock Market Predictions, and Trend Analysis
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Cost of food in Canada increased 1.30 percent in February of 2025 over the same month in the previous year. This dataset provides the latest reported value for - Canada Food Inflation - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
The dataset describes the monthly trend of the National Consumer Price Index (NIC), an indicator used to measure inflation, by classes of expenditure. The source of the data is the monthly ISTAT Survey on Consumer Prices. The index base is the year 2015=100. The reference universe is the entire population present in the territory and the set of all goods and services purchased by households with an actual market price. Since January 2016, the consumer price indices NIC are classified according to the new classification ECOICOP (European Classification of Individual Consumption according to Purpose), annexed to the new European Framework Regulation of harmonised indices of consumer prices. The time series is updated from January 2016 to February 2021 Column Note: (i) Index calculated by imputation, because not available or not usable, elementary data representative of 50% and more of the weight of the aggregate This dataset has been issued by the Municipality of Milan. The path to be used to find the original dataset on sisi.comune.milano.it is: sisi.comune.milano.it - Prices and Consumption - Consumer prices - Price index from 2016
Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
License information was derived automatically
This dataset is the Vulnerability Indices for Mortgage, Petroleum and Inflation Risks and Expenditure (VAMPIRE) for Australian Capital Cities for the year of 2006. The data has been calculated for each Census Collection District (CCD) within the Greater Capital City regions following the 2006 Australian Standard Geographical Classification (ASGC). The VAMPIRE index developed at Griffith University's Urban Research Program provides a measure of socio-economic oil price vulnerability in Australian cities based on an analysis of socio-economic indicators from the Australian Bureau of Statistics (ABS) Census Data.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The dataset describes the monthly trend of the Consumer Price Index for the entire national community (NIC), an indicator used to measure inflation, by spending subclasses. The source of the data is the ISTAT monthly survey on consumer prices. The basis of the indices is the year 2015=100. The reference universe is the entire population present in the area and the set of all goods and services purchased by families having an effective market price. Starting from January 2016, the NIC consumer price indices are classified according to the new ECOICOP (European Classification of Individual Consumption according to Purpose) classification, attached to the new European framework regulation of harmonized consumer price indices. The historical series is updated from January 2016 to February 2021. Column Note: (i) Index calculated by imputing, because they are not available or not usable, elementary data representing 50% or more of the weight of the aggregate. This dataset was released by the Municipality from Milan. The path to use to find the original dataset on sisi.comune.milano.it is: sisi.comune.milano.it - Prices and Consumption - Consumer prices - Price index since 2016
Annual indexes for major components and special aggregates of the Consumer Price Index (CPI), for Canada, provinces, Whitehorse, Yellowknife and Iqaluit. Data are presented for the last five years. The base year for the index is 2002=100.
This data package includes the underlying data files to replicate the data, tables, and charts presented in Why Trump’s tariff proposals would harm working Americans, PIIE Policy Brief 24-1.
If you use the data, please cite as: Clausing, Kimberly, and Mary E. Lovely. 2024. Why Trump’s tariff proposals would harm working Americans. PIIE Policy Brief 24-1. Washington, DC: Peterson Institute for International Economics.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Inflation Rate in Lebanon decreased to 15.60 percent in February from 16.10 percent in January of 2025. This dataset provides the latest reported value for - Lebanon Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.
A series for the GDP deflator in index form is produced by the Treasury from data provided by the Office for National Statistics (ONS) and the Office for Budget Responsibility (OBR). The GDP deflator set is updated after every ONS Quarterly National Accounts release (at the end of each quarter) and whenever the OBR updates its GDP deflator forecasts (usually twice a year).
Outturn data are the latest Quarterly National Accounts figures from the ONS, 20 December 2013. GDP deflators from 1955-56 to 2012-13 (1955 to 2012) have been taken directly from ONS Quarterly National Accounts implied deflator at market prices series http://www.ons.gov.uk/ons/datasets-and-tables/data-selector.html?cdid=L8GG&dataset=qna&table-id=N" class="govuk-link">L8GG.
Forecast data are consistent with the Autumn Statement, 05 December 2013.
The detail below aims to provide background information on the GDP deflator series and the concepts and methods underlying it.
GDP deflators can be used by anyone who has an interest in deflating current price nominal data into a “real terms” prices basis. This guide has been written with casual as well as professional users of the data in mind, using language and concepts aimed at as wide an audience as possible.
The GDP deflator can be viewed as a measure of general inflation in the domestic economy. Inflation can be described as a measure of price changes over time. The deflator is usually expressed in terms of an index, i.e. a time series of index numbers. Percentage changes on the previous year are also shown. The GDP deflator reflects movements of hundreds of separate deflators for the individual expenditure components of GDP. These components include expenditure on such items as bread, investment in computers, imports of aircraft, and exports of consultancy services.
The series allows for the effects of changes in price (inflation) to be removed from a time series, i.e. it allows the change in the volume of goods and services to be measured. The resultant series can be used to express a given time series or data set in real terms, i.e. by removing price changes.
A series for the GDP deflator in index form is produced by the Treasury from data provided by the Office for National Statistics (ONS). Forecasts are produced by the Office for Budgetary Responsibility (OBR) and are usually updated around the time of major policy announcements, namely; the Chancellor’s Autumn Statement, and the Budget.
GDP deflators for earlier years (up to and including the most recent year for which full quarterly data have been published) are presented to 3 decimal places. The index for future years has been removed as the forecasts were not as accurate as this detail would suggest. Percentage year-on-year changes are given to two decimal places for earlier years, forecast years are presented to 1 decimal place as published in the Autumn Statement and the Budget.
Gross Domestic Product (GDP) is a measure of the total domestic economic activity. It is the sum of all incomes earned by the production of goods and services within the UK economic territory. It is worth noting that where the earner of the income resides is irrelevant, so long as the goods or services themselves are produced within the UK. GDP is equivalent to the value added to the economy by this activity. Value added can be defined as income
VITAL SIGNS INDICATOR
Housing Affordability (EQ2)
FULL MEASURE NAME
Housing Affordability
LAST UPDATED
December 2022
DATA SOURCE
U.S. Census Bureau: Decennial Census - https://nhgis.org
Form STF3 – https://nhgis.org (1980-1990)
Form SF3a – https://nhgis.org (2000)
U.S. Census Bureau: American Community Survey - https://data.census.gov/
Form B25074 (2009-2021)
Form B25095 (2009-2021)
CONTACT INFORMATION
vitalsigns.info@bayareametro.gov
METHODOLOGY NOTES (across all datasets for this indicator)
The share of income brackets used for different Census and American Community Survey (ACS) forms vary over time. To allow for historical comparisons, the Census Bureau merges housing expenditure brackets into three consistent bins (less than 20 percent, 20 percent to 34 percent, and more than 35 percent) that work for all years. The highest income bracket for renters in the ACS data was $100,000 or more, while the homeowner dataset included brackets for $100,000 to $149,999 and $150,000 and above. These brackets were merged together to allow for uniform comparison across tenure. While some studies use 30 percent as the affordability threshold, Vital Signs uses 35 percent as this is the closest break point using the standardized affordability brackets above.
ACS 1-year data is used for larger geographies – Bay counties and most metropolitan area counties – while smaller geographies rely upon 5-year rolling average data due to their smaller sample sizes. Note that 2020 data uses the 5-year estimates because the ACS did not collect 1-year data for 2020.
Income breakdown data is only provided for one year as it is not possible to compare consistent inflation-adjusted income brackets over time given Census data limitations. For the county breakdown, Napa was missing ACS 1-Year renter data for all years except 2012 and 2013, and Marin was missing ACS 1-Year renter data for 2019 — these counties used 5-Year data for those years.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Inflation Rate in Nigeria decreased to 23.18 percent in February from 24.48 percent in January of 2025. This dataset provides - Nigeria 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 Brazil increased to 5.06 percent in February from 4.56 percent in January of 2025. This dataset provides - Brazil 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
Government spending in the United States was last recorded at 34.4 percent of GDP in 2023 . This dataset provides - United States Government Spending To Gdp- actual values, historical data, forecast, chart, statistics, economic calendar and news.