(i) 12-month inflation: normally considered as inflation rate, is defined as the percentage change in the monthly consumer price index (CPI). For example, the 12-month inflation rate for November 2017 is the percentage change in the CPI of November 2017 and November 2016. (ii) Annual average inflation: is the percentage change in the annual average consumer price index (CPI) of the corresponding months e.g. November 2017 and November 2016. (iii) Source: Kenya National Bureau of Statistics. The latest Kenyan Inflation rates can be downloaded here

This linked dataset contains sample versions of a selection of consumer price inflation tables prepared following the GSS guidance on releasing statistics in spreadsheets.

Core consumer prices in the United States increased 2.80 percent in May of 2025 over the same month in the previous year. This dataset provides - United States Core Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

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.

When inflation occurs in a country, the value of the currency decreases. That means that the purchasing power consumers have with a fixed amount of money decreases. Wages, especially lower and middle class wages, usually increase at a MUCH slower rate than prices of consumer goods; so consumers are likely to make the same wage, but are not able to buy the same amount of goods and services. Consumers in countries with hyperinflation suffer greatly because of this economic phenomenon.

Data was downloaded from: Link

For notes/metadata regarding the definition, measurement, or data collection for a certain country or group can be found by downloading the excel file from the linked webpage.

Original data provider: International Monetary Fund, World Development Indicators. License : CC BY-4.0.

INDICATOR_CODE: FP.CPI.TOTL.ZG

INDICATOR_NAME: Inflation, consumer prices (annual %)

SOURCE_NOTE: Inflation as measured by the consumer price index reflects the annual percentage change in the cost to the average consumer of acquiring a basket of goods and services that may be fixed or changed at specified intervals, such as yearly.
The Laspeyres formula is generally used.

Years included: 1960-2016

The following countries have no values for any year:

• Somalia

• Puerto Rico

• Guam

• US Virgin Islands

The dataset also conains some records that refer to groups of countries, which may be useful for those with no recorded values. Some of those groups are:

• Fragile and conflict affected situations

• Heavily indebted poor countries (HIPC)

• Caribbean small states

• Latin America & Caribbean (excluding high income)

• Latin America & the Caribbean (IDA & IBRD countries)

• East Asia & Pacific (excluding high income)

• East Asia & Pacific (IDA & IBRD countries)

• Least developed countries: UN classification

• Middle East & North Africa (IDA & IBRD countries)

If this data is being used for the Kiva Crowdfunding Data Science for Good event; The following countries (as they are named in this dataset), are named slightly differently in the Kiva dataset (to the best of my knowledge). For example, West Bank in Gaza is referred to as Palestine in the Kiva Dataset.

• Congo, Dem. Rep.

• Congo, Rep.

• Kyrgyz Republic

• Lao PDR

• Myanmar

• West Bank and Gaza

• St. Vincent and the Grenadines

• Virgin Islands (U.S.)

• Yemen, Rep.

Comprehensive database of time series covering measures of inflation data for the UK including CPIH, CPI and RPI.

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.

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

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

Inflation Rate in Iran increased to 38.90 percent in April from 37.10 percent in March of 2025. This dataset provides the latest reported value for - Iran Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

This paper discusses estimation of US inflation volatility using time-varying parameter models, in particular whether it should be modelled as a stationary or random walk stochastic process. Specifying inflation volatility as an unbounded process, as implied by the random walk, conflicts with priors beliefs, yet a stationary process cannot capture the low-frequency behaviour commonly observed in estimates of volatility. We therefore propose an alternative model with a change-point process in the volatility that allows for switches between stationary models to capture changes in the level and dynamics over the past 40 years. To accommodate the stationarity restriction, we develop a new representation that is equivalent to our model but is computationally more efficient. All models produce effectively identical estimates of volatility, but the change-point model provides more information on the level and persistence of volatility and the probabilities of changes. For example, we find a few well-defined switches in the volatility process and, interestingly, these switches line up well with economic slowdowns or changes of the Federal Reserve Chair. Moreover, a decomposition of inflation shocks into permanent and transitory components shows that a spike in volatility in the late 2000s was entirely on the transitory side and characterized by a rise above its long-run mean level during a period of higher persistence.

Context

Harmonised Indices of Consumer Prices (HICPs) are designed for international comparisons of consumer price inflation. HICP is used for example by the European Central Bank for monitoring of inflation in the Economic and Monetary Union and for the assessment of inflation convergence as required under Article 121 of the Treaty of Amsterdam. For the U.S. and Japan national consumer price indices are used in the table.

Content

The Dataset contains Annual average inflation rate of change (%) between 2008-2019 of multiple countries in the EU region along with Turkey, US and Japan.

Source

The HICP - inflation rate dataset is provided by Eurostat. The official links are added below:

Data: https://ec.europa.eu/eurostat/tgm/table.do?tab=table&plugin=1&language=en&pcode=tec00118 Graph: https://ec.europa.eu/eurostat/tgm/graph.do?tab=graph&plugin=1&language=en&pcode=tec00118&toolbox=type Map: https://ec.europa.eu/eurostat/tgm/mapToolClosed.do?tab=map&init=1&plugin=1&language=en&pcode=tec00118&toolbox=types

This table shows inflation, derived inflation and underlying inflation rates. Underlying inflation equals the inflation or derived inflation, excluding certain volatile items or series that are affected by factors other than general economic conditions, for example prices of fuel, vegetables, fruit and government taxes.

Data available from: January 2006 till December 2015

Status of the figures: The figures in this table are final.

Changes as of 16 June 2016: None, this table is stopped.

Changes as of 10 December 2015: On 1 October 2015, the points system for the pricing of rental homes was adjusted by the Dutch national government. As a direct consequence, rental prices of a limited number of dwellings were reduced, which had a downward effect on the average rental price. The effect of this decrease on the rental price indices and imputed rent value could not be determined in time because housing associations announced the impact of rent adjustments only in November. For this reason, the figures of the groups 04100 ‘Actual rentals for housing’ and 04200 ‘Imputed rent value’ over October 2015 have now been adjusted.

The figures of the groups 061100 ‘Pharmaceutical products’, 061200 ‘Other medical products, equipment’, 072200 ‘Fuels and lubricants’ and 083000 ‘Telephone and internet services’ over the months June through September 2015 have been corrected. This has no impact on the headline indices.

The derived CPI decreased by 0.01 index point over August 2015.

The International Macroeconomic Data Set provides data from 1969 through 2030 for real (adjusted for inflation) gross domestic product (GDP), population, real exchange rates, and other variables for the 190 countries and 34 regions that are most important for U.S. agricultural trade. The data presented here are a key component of the USDA Baseline projections process, and can be used as a benchmark for analyzing the impacts of U.S. and global macroeconomic shocks.

Inflation Rate in India decreased to 2.82 percent in May from 3.16 percent in April of 2025. This dataset provides - India Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Harmonised Indices of Consumer Prices (HICPs) are designed for international comparisons of consumer price inflation. HICP is used for example by the European Central Bank for monitoring of inflation in the Economic and Monetary Union and for the assessment of inflation convergence as required under Article 121 of the Treaty of Amsterdam. For the U.S. and Japan national consumer price indices are used in the table.

This dataset has information about the cost of providing General Fund City services per capita of the Full Purpose City population (SD23 measure GTW.A.4). It provides expense information from the annual approved budget document (General Fund Summary and Budget Stabilization Reserve Fund Summary) and population information from the City Demographer's Full Purpose Population numbers. The Consumer Price Index information for Texas is available through the following Key Economic Indicators dataset: https://data.texas.gov/dataset/Key-Economic-Indicators/karz-jr5v.

This dataset can be used to help understand the cost of city services over time.

View more details and insights related to this dataset on the story page: https://data.austintexas.gov/stories/s/ixex-hibp

Splitgraph serves as an HTTP API that lets you run SQL queries directly on this data to power Web applications. For example:

See the Splitgraph documentation for more information.

This dataset contains news headlines relevant to key forex pairs: AUDUSD, EURCHF, EURUSD, GBPUSD, and USDJPY. The data was extracted from reputable platforms Forex Live and FXstreet over a period of 86 days, from January to May 2023. The dataset comprises 2,291 unique news headlines. Each headline includes an associated forex pair, timestamp, source, author, URL, and the corresponding article text. Data was collected using web scraping techniques executed via a custom service on a virtual machine. This service periodically retrieves the latest news for a specified forex pair (ticker) from each platform, parsing all available information. The collected data is then processed to extract details such as the article's timestamp, author, and URL. The URL is further used to retrieve the full text of each article. This data acquisition process repeats approximately every 15 minutes.

To ensure the reliability of the dataset, we manually annotated each headline for sentiment. Instead of solely focusing on the textual content, we ascertained sentiment based on the potential short-term impact of the headline on its corresponding forex pair. This method recognizes the currency market's acute sensitivity to economic news, which significantly influences many trading strategies. As such, this dataset could serve as an invaluable resource for fine-tuning sentiment analysis models in the financial realm.

We used three categories for annotation: 'positive', 'negative', and 'neutral', which correspond to bullish, bearish, and hold sentiments, respectively, for the forex pair linked to each headline. The following Table provides examples of annotated headlines along with brief explanations of the assigned sentiment.

Examples of Annotated Headlines


    Forex Pair
    Headline
    Sentiment
    Explanation




    GBPUSD 
    Diminishing bets for a move to 12400 
    Neutral
    Lack of strong sentiment in either direction


    GBPUSD 
    No reasons to dislike Cable in the very near term as long as the Dollar momentum remains soft 
    Positive
    Positive sentiment towards GBPUSD (Cable) in the near term


    GBPUSD 
    When are the UK jobs and how could they affect GBPUSD 
    Neutral
    Poses a question and does not express a clear sentiment


    JPYUSD
    Appropriate to continue monetary easing to achieve 2% inflation target with wage growth 
    Positive
    Monetary easing from Bank of Japan (BoJ) could lead to a weaker JPY in the short term due to increased money supply


    USDJPY
    Dollar rebounds despite US data. Yen gains amid lower yields 
    Neutral
    Since both the USD and JPY are gaining, the effects on the USDJPY forex pair might offset each other


    USDJPY
    USDJPY to reach 124 by Q4 as the likelihood of a BoJ policy shift should accelerate Yen gains 
    Negative
    USDJPY is expected to reach a lower value, with the USD losing value against the JPY


    AUDUSD

    <p>RBA Governor Lowe’s Testimony High inflation is damaging and corrosive </p>

    Positive
    Reserve Bank of Australia (RBA) expresses concerns about inflation. Typically, central banks combat high inflation with higher interest rates, which could strengthen AUD.

Moreover, the dataset includes two columns with the predicted sentiment class and score as predicted by the FinBERT model. Specifically, the FinBERT model outputs a set of probabilities for each sentiment class (positive, negative, and neutral), representing the model's confidence in associating the input headline with each sentiment category. These probabilities are used to determine the predicted class and a sentiment score for each headline. The sentiment score is computed by subtracting the negative class probability from the positive one.

The consumer price inflation detailed briefing note contains details of the items contributing to the changes in the CPIH (and RPI), details of any notable movements, a summary of the reconciliation of CPIH and RPI, and the outlook, which looks ahead to next month’s release.

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.