Inflation Rate in the United States increased to 2.40 percent in May from 2.30 percent in April of 2025. This dataset provides - United States Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Inflation rates experienced by different groups of consumers within a country vary. This is because the prices of goods and services and the expenditure patterns of consumers differ. The published inflation rate is used for important decisions regarding the preservation of consumer purchasing power. These include the adjustment of social grants and minimum wages by government and the benchmarking of returns by investors when making investment decisions. It is thus vital that inflation is measured accurately to ensure the purchasing power of consumers is preserved. Current measures of inflation published by Stats SA are applicable to typical consumers and are not relevant to each individual. This resource supplements a study that seeks to provide a publicly available model that can be used by consumers to calculate their personal rate of inflation.

The Consumer Price Index (CPI) is a measure of the average change over time in the prices paid by urban consumers for a market basket of consumer goods and services. Indexes are available for the U.S. and various geographic areas. Average price data for select utility, automotive fuel, and food items are also available. Prices for the goods and services used to calculate the CPI are collected in 75 urban areas throughout the country and from about 23,000 retail and service establishments. Data on rents are collected from about 43,000 landlords or tenants. More information and details about the data provided can be found at http://www.bls.gov/cpi

Measures of monthly UK inflation data including CPIH, CPI and RPI. These tables complement the consumer price inflation time series dataset.

Inflation Rate In the Euro Area increased to 2 percent in June from 1.90 percent in May of 2025. This dataset provides the latest reported value for - Euro Area Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The Consumer Price Index in the United States increased 0.10 percent in May of 2025 over the previous month. This dataset provides - United States Inflation Rate MoM - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Graph and download economic data for Inflation, consumer prices for the United States (FPCPITOTLZGUSA) from 1960 to 2024 about consumer, CPI, inflation, price index, indexes, price, and USA.

This data package includes the underlying data and files to replicate the calculations, charts, and tables presented in Average Inflation Targeting Would Be a Weak Tool for the Fed to Deal with Recession and Chronic Low Inflation, PIIE Policy Brief 19-16. If you use the data, please cite as: Reifschneider, David, and David Wilcox. (2019). Average Inflation Targeting Would Be a Weak Tool for the Fed to Deal with Recession and Chronic Low Inflation. PIIE Policy Brief 19-16. Peterson Institute for International Economics.

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

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

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

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

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

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

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

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

This data package includes the underlying data to replicate the charts, tables, and calculations presented in Why did inflation rise and fall so rapidly? Lessons from the Korean War, PIIE Working Paper 25-1.

If you use the data, please cite as:

Gagnon, Joseph E., and Asher Rose. 2025. Why did inflation rise and fall so rapidly? Lessons from the Korean War. PIIE Working Paper 25-1. Washington: Peterson Institute for International Economics.

This data package includes the underlying data and files to replicate the calculations, charts, and tables presented in Inflation Targets in Latin America, PIIE Working Paper 19-19.

If you use the data, please cite as: De Gregorio, José. (2019). Inflation Targets in Latin America. PIIE Working Paper 19-19. Peterson Institute for International Economics.

Consumer Prices Index including owner occupiers’ housing costs (CPIH)-consistent inflation rates calculated for different income groups in the UK, by category of spend. Data are for the period 2005 to 2018.

The dataset contains Year and State wise State-wise Average Inflation (CPI) - General, Food and Beverages, Fuel and Light and Housing (Urban)

Note: General: 1. Data for Arunachal Pradesh is not available. 2. For calculating State-wise Consumer Price Index (CPI) inflation in 2020-21 the average CPI Index for ten months has been taken due to unavailability of CPI data for the months of April and May 2020. 3. Figures for Jammu & Kashmir from October 2019 pertain to combined Union Territories of Jammu & Kashmir and Ladakh (erstwhile State of Jammu & Kashmir)

Food and Beverages: 1. Data for Arunachal Pradesh is not available. 2. For 2019-20, annual inflation for all states is calculated using data from April-2019 to February-2020, and for All-India, it is calculated using April-2019 to March-2020 data. 3. For calculating State-wise CPI inflation in 2020-21 the average CPI for eight months has been taken due to unavailability of CPI data for the period April-July 2020. 4. Figures for Jammu & Kashmir from October 2019 pertain to combined Union Territories of Jammu & Kashmir and Ladakh(erstwhile State of Jammu & Kashmir)

Fuel and Light: 1. Data for Arunachal Pradesh is not available. 2. For 2019-20, annual inflation for all states is calculated using data from April-2019 to February-2020, and for All-India, it is calculated using April-2019 to March-2020 data. 3. For calculating State-wise CPI inflation in 2020-21 the average CPI for eight months has been taken due to unavailability of CPI data for the period April-July 2020. 4. Figures for Jammu & Kashmir from October 2019 pertain to combined Union Territories of Jammu & Kashmir and Ladakh (erstwhile State of Jammu & Kashmir)

Housing (Urban): 1. Data for Arunachal Pradesh is not available. 2. For 2019-20, annual inflation for all states is calculated using data from April-2019 to February-2020, and for All-India, it is calculated using April-2019 to March-2020 data. 3. For calculating State-wise CPI inflation in 2020-21 the average CPI for eight months has been taken due to unavailability of CPI data for the period April-July 2020. 4. Figures for Jammu & Kashmir from October 2019 pertain to combined Union Territories of Jammu & Kashmir and Ladakh (erstwhile State of Jammu & Kashmir)

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.

This data package includes the underlying data files to replicate the calculations and charts presented in Soaring demand is driving double-digit import price inflation in the United States, PIIE Policy Brief 22-12.

If you use the data, please cite as: Freund, Caroline (2022). Soaring demand is driving double-digit import price inflation in the United States, PIIE Policy Brief 22-12. Peterson Institute for International Economics.

We report average expected inflation rates over the next one through 30 years. Our estimates of expected inflation rates are calculated using a Federal Reserve Bank of Cleveland model that combines financial data and survey-based measures. Released monthly.

This dataset is about the Inflation for Saudi Arabia for 2009 - Jan 2020 (Base year 2007 & 2013). Data from Saudi Arabian Monetary Authority. Follow datasource.kapsarc.org for timely data to advance energy economics research.Note:- Data found here from January 2018 till January 2020 was 2013 base year CPI calculation- Data found here from October 2009 till December 2017 was 2007 base year CPI calculation.You can find Saudi Arabia Inflation Rate with the latest 2018 base year on KAPSARC Dataportal.

The dataset represents the joint dynamics of Financial Stress Index (FSI), Consumer Price Index (CPI) calculated and provided by the National Bank of Ukraine (NBU) and Gross Domestic Product (GDP) provided by SSSU for Ukraine.

The monthly dataset range is Feb 2004-Feb 2022, the effective balanced range is Jan 2011-Dec 2021.

The daily FSI data is aggregated into monthly series as a period average. The CPI series are monthly. The quarterly GDP data is seasonally adjusted and interpolated into monthly data with the use of ARIMA model and cubic spline method accordingly, converted into year-over-year series (dGDP).

Review of Economics and Statistics: Forthcoming. Visit https://dataone.org/datasets/sha256%3A484a7528969ca82fb4a3ebd26409aa9adc1186c67c1138dbce78e92f7b053b40 for complete metadata about this dataset.

The file "dataset_regression_income.csv" contains a dataset developed in the analysis of inflation heterogeneity for Italian Households in the period 2015-2023.The dataset is the outcome of merging the yearly Household Budget Surveys (HBS) conducted by the Italian National Institute of Statistics (Istat), the Harmonised Index of Consumer Prices (HICP) which is calculated monthly by Istat, according to EU regulations, and the Survey on Households Income and Wealth (SHIW) conducted by Bank of Italy.Mapping price information into consumption decisions and aggregating an individual price index for each household according to a Laspeyres Formula leads to the computation of household-level inflation rates.Furthermore, we compute non-durable equivalent expenditure for each household as a proxy of living standards. The variable is obtained by subtracting durable expenditure from total aggregate expenditure and scaling down by an household equivalent scale (in the benchmark specification, the square root of the household size). The decile distribution of the variable is also computed.Finally, we apply a statistical matching procedure to integrate income information from SHIW data sources. The output is a synthetic dataset containing both expenditure and income information that preserves the joint distribution and correlation structures of the original datasets.The file "ISTAT_MFR_HBS_EUR.csv" is a conversion table that maps ECOICOP items to HBS expenditure voices.