Context

Understanding global economic dynamics, specifically the trends in inflation rates, is paramount for policymakers, economists, and researchers. This dataset, covering the years 1980 to 2024, offers a comprehensive perspective on inflation across various countries. The primary focus is on dissecting the data based on country-specific indicators, providing valuable insights into the multifaceted factors influencing economic environments on a global scale.

Content

The dataset comprises crucial columns including country name, indicator type, and annual average inflation rates from 1980 to 2024. This extensive collection of information facilitates detailed analysis and correlation studies, enabling researchers to uncover patterns and trends. By examining the nuanced relationships between country-specific indicators and inflation rates, valuable conclusions can be drawn about the complexities of global economic dynamics over the years. This dataset serves as a valuable resource for anyone seeking to delve into the intricacies of inflation trends and their implications across diverse nations.

Dataset Structure:

This dataset (global_inflation_data.csv) covering from 1980 to 2024 consists of the following columns:

Acknowledgment

The primary dataset was retrieved from the World Bank. I sincerely thank the team for providing the core data used in this dataset.

© Image credit: Freepik

Price quote data (for locally collected data only) and consumption segment indices that underpin consumer price inflation statistics, giving users access to the detailed data that are used in the construction of the UK’s inflation figures. The data are being made available for research purposes only and are not an accredited official statistic. From October 2024, private school fees and part-time education classes have been included in the consumption segment indices file. For more information on the introduction of consumption segments, please see the Consumer Prices Indices Technical Manual, 2019. Note that this dataset was previously called the consumer price inflation item indices and price quotes dataset.

About Dataset

https://www.tbsnews.net/sites/default/files/styles/big_2/public/images/2021/03/12/inflation_1.jpg" alt="Inflation hits nine-year high in June | undefined">###

Global Energy, Food, Consumer, and Producer Price Inflation: A Comprehensive Dataset for Understanding Economic Trends

Key Concepts:

1. Energy Consumer Price Inflation data.
2. Food Consumer Price Inflation data.
3. Headline Consumer Price Inflation data.
4. Official Core Consumer Price Inflation data.
5. Producer Price Inflation data.
6. 206 Countries name, Country code and IMF code.
7. 52 Years data from 1970 to 2022.

The global economy is highly complex, and understanding economic trends and patterns is crucial for making informed decisions about investments, policies, and more. One key factor that impacts the economy is inflation, which refers to the rate at which prices increase over time. The Global Energy, Food, Consumer, and Producer Price Inflation dataset provides a comprehensive collection of inflation rates across 206 countries from 1970 to 2022, covering four critical sectors of the economy.

Finally, the Global Producer Price Inflation dataset provides a detailed look at price changes at the producer level, providing insights into supply chain dynamics and trends. This data can be used to make informed decisions about investments in various sectors of the economy and to develop effective policies to manage producer price inflation.

In conclusion, the Global Energy, Food, Consumer, and Producer Price Inflation dataset provides a comprehensive resource for understanding economic trends and patterns across 206 countries. By examining this data, analysts can gain insights into the complex factors that impact the economy and make informed decisions about investments, policies, and more.

Potential User:

1. Economists and economic researchers
2. Policy makers and government officials
3. Investors and financial analysts
4. Agricultural researchers and policymakers
5. Energy analysts and policy makers
6. Food industry professionals
7. Business leaders and decision makers
8. Academics and students in economics, finance, and related fields

Acknowledgements:

The data were collected from the official website of worldbank.org

Inflation Rate in India decreased to 0.25 percent in October from 1.44 percent in September of 2025. This dataset provides - India Inflation Rate - 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 dataset is about countries per year in Israel. It has 64 rows. It features 4 columns: country, country full name, and inflation.

Inflation Rate in Spain decreased to 3 percent in November from 3.10 percent in October of 2025. This dataset provides the latest reported value for - Spain Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Inflation Rate in Germany remained unchanged at 2.30 percent in November. This dataset provides the latest reported value for - Germany Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Under "Worldwide Inflation Based Database'' there are 4 sheets. Among them, the two are of data-sheets and the rest of the two are chart-typed sheets. However, between the two of the datasheets, one’s name is "Worldwide Inflation Rate in 2022”. Noted that this datasheet's table name is " Worldwide Inflation Rate in 2022''. Moreover, under this data table, there are three fields (“Country"; " Inflation rate-year over year"; "Date"), three columns, and, 185 rows. Also, each row contains 3 cells, and so, 185 rows contain 555 cells. And also, each column contains 185 cells, so, 3 columns contain 555 cells. In addition to, focusing on the two fields' ("Country", "Inflation rate-year over year") data of the datasheet.

"Inflation Rate of Countries" named "Line" type-based chart has been made. On this chart, “Country” field values are on the horizontal axis. Whereas, “Inflation rate-year over year” field values are on the vertical axis. However, the chart shows that Zimbabwe’s highest raking inflation, and its rate is 269%, and also, its time-scale continuity is up to on 22 October,2022. On the other hand, the negative scale of the inflation rate is in South Sudan which rate is -2.50, also, its time-scale is up to on 22 August,2022.

Basically, the chart has been made following “Data Shorting Descending Process’’, and, operating focused on the field (“Inflation rate-year over year’’) ‘s data.

And, another data sheet’s table name is “COUNTRY WISE INFLATION RTAE-2’’. This table contains two fields( “Country’’; “Inflation rate-year over year’’; ), 2 columns, 185 rows. Also, each row contain two cells, and so, 185 rows contain 370 cells. Whereas, each column contains 185 cells, and so, 2 columns contain 370 cells. However, on the basis of this datasheet, “Ascending typed Shorting Process” has been operated after the accomplishment of “Filtering” process. On the basis of it, “Inflation rate- year over year’’ named “line-type” chart has been created. On this chart, “Country” named field values are on horizontal axis, whereas, “Inflation rate-year over year “ named field values are on the vertical axis.

Be that as it may, the chart shows that South Sudan’s inflation rate is on the lower negative scale. In the opposite side, Lebanon’s inflation rate is at the highest level after Zimbabwe.

Inflation Rate in Turkey decreased to 32.87 percent in October from 33.29 percent in September 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.

Inflation Rate in Romania decreased to 9.80 percent in October from 9.90 percent in September of 2025. This dataset provides - Romania Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Inflation Rate in Thailand decreased to -0.76 percent in October from -0.72 percent in September of 2025. This dataset provides the latest reported value for - Thailand Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

This dataset provides values for INFLATION RATE reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Inflation is generally defined as the continued increase in the average prices of goods and services in a given region. Following the extremely high global inflation experienced in the 1980s and 1990s, global inflation has been relatively stable since the turn of the millennium, usually hovering between three and five percent per year. There was a sharp increase in 2008 due to the global financial crisis now known as the Great Recession, but inflation was fairly stable throughout the 2010s, before the current inflation crisis began in 2021. Recent years Despite the economic impact of the coronavirus pandemic, the global inflation rate fell to 3.26 percent in the pandemic's first year, before rising to 4.66 percent in 2021. This increase came as the impact of supply chain delays began to take more of an effect on consumer prices, before the Russia-Ukraine war exacerbated this further. A series of compounding issues such as rising energy and food prices, fiscal instability in the wake of the pandemic, and consumer insecurity have created a new global recession, and global inflation in 2024 is estimated to have reached 5.76 percent. This is the highest annual increase in inflation since 1996. Venezuela Venezuela is the country with the highest individual inflation rate in the world, forecast at around 200 percent in 2022. While this is figure is over 100 times larger than the global average in most years, it actually marks a decrease in Venezuela's inflation rate, which had peaked at over 65,000 percent in 2018. Between 2016 and 2021, Venezuela experienced hyperinflation due to the government's excessive spending and printing of money in an attempt to curve its already-high inflation rate, and the wave of migrants that left the country resulted in one of the largest refugee crises in recent years. In addition to its economic problems, political instability and foreign sanctions pose further long-term problems for Venezuela. While hyperinflation may be coming to an end, it remains to be seen how much of an impact this will have on the economy, how living standards will change, and how many refugees may return in the coming years.

This data is used for examination of inflation- unemployment relationship for 18 countries after 1991. Inflation data is obtained from World Bank database (https://data.worldbank.org/indicator/FP.CPI.TOTL.ZG) and unemployment data is obtained from International Labor Organization (http://www.ilo.org/wesodata/).

Analysis period is different for all countries because of structural breaks determined by single point change point detection algorithm included in changepoint package of Killick & Eckley (2014). Granger-causality is conducted with Toda&Yamamoto (1995) procedure. Integration levels are determined with 3 stationary tests. VAR models are run with vars package (Pfaff, Stigler & Pfaff; 2018) without trend and constant terms. Cointegration test is conducted with urca package (Pfaff, Zivot, Stigler & Pfaff; 2016).

All data files are .csv files. Analyst need to change country index (variable name: j) in order to see individual results. Findings can be seen in the article.

Killick, R., & Eckley, I. (2014). changepoint: An R package for changepoint analysis. Journal of statistical software, 58(3), 1-19.

Pfaff, B., Stigler, M., & Pfaff, M. B. (2018). Package ‘vars’. Online] https://cran. r-project. org/web/packages/vars/vars. pdf.

Pfaff, B., Zivot, E., Stigler, M., & Pfaff, M. B. (2016). Package ‘urca’. Unit root and cointegration tests for time series data. R package version, 1-2.

Toda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of econometrics, 66(1-2), 225-250.

This dataset is about countries per year in Angola. It has 64 rows. It features 4 columns: country, country full name, and inflation.

This dataset enlists the details about annual inflation percentage of most countries in the world by consumer prices from 1960 through 2018. Indicator Name as per the World Bank for this dataset is "Inflation, consumer prices (annual %)" and its code is "FP.CPI.TOTL.ZG".

Inflation Rate in Malawi increased to 29.10 percent in October from 28.70 percent in September of 2025. This dataset provides the latest reported value for - Malawi 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.

Context

The Federal Reserve sets interest rates to promote conditions that achieve the mandate set by the Congress — high employment, low and stable inflation, sustainable economic growth, and moderate long-term interest rates. Interest rates set by the Fed directly influence the cost of borrowing money. Lower interest rates encourage more people to obtain a mortgage for a new home or to borrow money for an automobile or for home improvement. Lower rates encourage businesses to borrow funds to invest in expansion such as purchasing new equipment, updating plants, or hiring more workers. Higher interest rates restrain such borrowing by consumers and businesses.

Content

This dataset includes data on the economic conditions in the United States on a monthly basis since 1954. The federal funds rate is the interest rate at which depository institutions trade federal funds (balances held at Federal Reserve Banks) with each other overnight. The rate that the borrowing institution pays to the lending institution is determined between the two banks; the weighted average rate for all of these types of negotiations is called the effective federal funds rate. The effective federal funds rate is determined by the market but is influenced by the Federal Reserve through open market operations to reach the federal funds rate target. The Federal Open Market Committee (FOMC) meets eight times a year to determine the federal funds target rate; the target rate transitioned to a target range with an upper and lower limit in December 2008. The real gross domestic product is calculated as the seasonally adjusted quarterly rate of change in the gross domestic product based on chained 2009 dollars. The unemployment rate represents the number of unemployed as a seasonally adjusted percentage of the labor force. The inflation rate reflects the monthly change in the Consumer Price Index of products excluding food and energy.

Acknowledgements

The interest rate data was published by the Federal Reserve Bank of St. Louis' economic data portal. The gross domestic product data was provided by the US Bureau of Economic Analysis; the unemployment and consumer price index data was provided by the US Bureau of Labor Statistics.

Inspiration

How does economic growth, unemployment, and inflation impact the Federal Reserve's interest rates decisions? How has the interest rate policy changed over time? Can you predict the Federal Reserve's next decision? Will the target range set in March 2017 be increased, decreased, or remain the same?