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.

Graph and download economic data for Core Consumer Price Inflation for Pakistan (PAKPCPICOREPCHPT) from 2000 to 2025 about Pakistan, consumer prices, core, REO, consumer, inflation, and rate.

This study examines the determinants influencing the likelihood of Sub-Saharan African (SSA) countries seeking assistance from the International Monetary Fund (IMF). The IMF, as a global institution, aims to promote sustainable growth and prosperity among its member countries by supporting economic strategies that foster financial stability and collaboration in monetary affairs. Utilising panel-probit regression, this study analyses data from thirty-nine SSA countries spanning from 2000 to 2022, focusing on twelve factors: Current Account Balance (CAB), inflation, corruption, General Government Net Lending and Borrowing (GGNLB), General Government Gross Debt (GGGD), Gross Domestic Product Growth (GDPG), United Nations Security Council (UNSC) involvement, regime types (Closed Autocracy, Electoral Democracy, Electoral Autocracy, Liberal Democracy) and China Loan. The results indicate that corruption and GDP growth rate have the most significant influence on the likelihood of SSA countries seeking IMF assistance. Conversely, factors such as CAB, UNSC involvement, LD and inflation show inconsequential effects. Notable, countries like Sudan, Burundi, and Guinea consistently rank high in seeking IMF assistance over various time frames within the observed period. Sudan emerges with a probability of more than 44% in seeking IMF assistance, holding the highest ranking. Study emphasises the importance of understanding SSA region rankings and the variability of variables for policymakers, investors, and international organisations to effectively address economic challenges and provide financial assistance.

India Inflation Nowcast: Contribution: International Reserves: RBI: FX Reserve: INR: Position in the IMF data was reported at 0.828 % in 12 May 2025. This stayed constant from the previous number of 0.828 % for 05 May 2025. India Inflation Nowcast: Contribution: International Reserves: RBI: FX Reserve: INR: Position in the IMF data is updated weekly, averaging 0.438 % from Jul 2020 (Median) to 12 May 2025, with 254 observations. The data reached an all-time high of 12.707 % in 08 Jul 2024 and a record low of 0.000 % in 03 Apr 2023. India Inflation Nowcast: Contribution: International Reserves: RBI: FX Reserve: INR: Position in the IMF data remains active status in CEIC and is reported by CEIC Data. The data is categorized under Global Database’s India – Table IN.CEIC.NC: CEIC Nowcast: Inflation: Headline.

The World Economic Outlook (WEO) database contains selected macroeconomic data series from the statistical appendix of the World Economic Outlook report, which presents the IMF staff's analysis and projections of economic developments at the global level, in major country groups and individual countries. The WEO dataset is released twice a year: April and September/October. Please fill out this online form for access to the confidential version--not for redistribution or transfer to any unauthorized third party. The public version is available on the IMF website.

The IMF's World Economic Outlook uses a "bottom-up" approach in producing its forecasts; that is, country teams within the IMF generate projections for individual countries. These are then aggregated, and through a series of iterations where the aggregates feed back into individual countries' forecasts, forecasts converge to the projections reported in the WEO.

Because forecasts are made by the individual country teams, the methodology can vary from country to country and series to series depending on many factors. To get more information on a specific country and series forecast, you may contact the country teams directly; from the Countries tab on the IMF website. (From: https://www.imf.org/en/Publications/WEO/frequently-asked-questions#:~:text=%2Ddatabase%2FDisclaimer.-,Q.,generate%20projections%20for%20individual%20countries.)

India Inflation Nowcast: Contribution: International Reserves: RBI: FX Reserve: USD: Position in the IMF data was reported at 0.978 % in 12 May 2025. This stayed constant from the previous number of 0.978 % for 05 May 2025. India Inflation Nowcast: Contribution: International Reserves: RBI: FX Reserve: USD: Position in the IMF data is updated weekly, averaging 0.348 % from Jul 2020 (Median) to 12 May 2025, with 254 observations. The data reached an all-time high of 16.090 % in 08 Mar 2021 and a record low of 0.000 % in 07 Apr 2025. India Inflation Nowcast: Contribution: International Reserves: RBI: FX Reserve: USD: Position in the IMF data remains active status in CEIC and is reported by CEIC Data. The data is categorized under Global Database’s India – Table IN.CEIC.NC: CEIC Nowcast: Inflation: Headline.

Graph and download economic data for Core Consumer Price Inflation for Iraq (IRQPCPICOREPCHPT) from 2005 to 2025 about Iraq, consumer prices, core, REO, consumer, inflation, and rate.

Graph and download economic data for Core Consumer Price Inflation for Jordan (JORPCPICOREPCHPT) from 2010 to 2025 about Jordan, consumer prices, core, REO, consumer, inflation, and rate.

Monaco MC: Inflation:(GDP) Gross Domestic ProductDeflator: Linked Series data was reported at 5.303 % in 2023. This records an increase from the previous number of 3.221 % for 2022. Monaco MC: Inflation:(GDP) Gross Domestic ProductDeflator: Linked Series data is updated yearly, averaging 1.326 % from Dec 1990 (Median) to 2023, with 34 observations. The data reached an all-time high of 5.303 % in 2023 and a record low of -0.241 % in 2004. Monaco MC: Inflation:(GDP) Gross Domestic ProductDeflator: Linked Series data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Monaco – Table MC.World Bank.WDI: Inflation. Inflation as measured by the annual growth rate of the GDP implicit deflator shows the rate of price change in the economy as a whole. This series has been linked to produce a consistent time series to counteract breaks in series over time due to changes in base years, source data and methodologies. Thus, it may not be comparable with other national accounts series in the database for historical years.;World Bank staff estimates based on World Bank national accounts data archives, OECD National Accounts, and the IMF WEO database.;;

Context

The IMF Economic Indicators Dataset is a comprehensive collection of economic data from the International Monetary Fund (IMF). This dataset provides insights into various key economic metrics that are crucial for assessing the economic health and performance of countries worldwide.

Content:

The dataset consists of individual files, each representing a specific economic indicator. Here is an overview of the included indicators:

Current Account forecast

Inflation forecast

Budget Balance forecast

Investment Economic forecast

Unemployment rate forecast

Description:

This dataset provides key economic indicators from various countries between 2010 and 2023. The dataset includes monthly data on inflation rates, GDP growth rates, unemployment rates, interest rates, and stock market index values. The data has been sourced from reputable global financial institutions and is suitable for economic analysis, machine learning models, and forecasting economic trends.

Data Sources:

The data has been generated to simulate real-world economic conditions, mimicking information from trusted sources like: - World Bank for GDP growth and inflation data - International Monetary Fund (IMF) for macroeconomic data - OECD for labor market statistics - National Stock Exchanges for stock market index values

Columns:

1. Date: The specific date (in Year/Month/Day format) representing when the data was collected.
2. Country: The country the data pertains to (e.g., USA, Germany, Japan).
3. Inflation Rate (%): The rate of inflation for that country, showing how fast prices for goods and services are increasing.
4. GDP Growth Rate (%): The percentage growth of the country’s Gross Domestic Product (GDP), indicating economic expansion or contraction.
5. Unemployment Rate (%): The percentage of the working-age population that is unemployed.
6. Interest Rate (%): The central bank's interest rate, used to control inflation and influence the economy.
7. Stock Index Value: The value of the country’s main stock market index, reflecting the performance of the stock market.

Potential Uses: - Economic Analysis: Researchers and analysts can use this dataset to study trends in inflation, GDP growth, unemployment, and other economic factors. - Machine Learning: This dataset can be used to train models for predicting economic trends or market performance. Financial Forecasting: Investors and economists can leverage this data for forecasting market movements based on economic conditions. - Comparative Studies: The dataset allows comparisons across countries and regions, offering insights into global economic performance.

Based on IMF forecasts from April 2025, the real GDP growth in industrial countries will slow in 2030, only growing by *** percent. This is because of the impact of the high global inflation rates. On the other hand, the GDP of emerging and developing countries is expected to grow by around * percent both in 2022, 2030, and 2024.

Graph and download economic data for Consumer Price Inflation for Morocco (MARPCPIPCHPT) from 2000 to 2025 about Morocco, consumer prices, REO, consumer, inflation, and rate.

The inflation rate in the United States is expected to decrease to 2.1 percent by 2029. 2022 saw a year of exceptionally high inflation, reaching eight percent for the year. The data represents U.S. city averages. The base period was 1982-84. In economics, the inflation rate is a measurement of inflation, the rate of increase of a price index (in this case: consumer price index). It is the percentage rate of change in prices level over time. The rate of decrease in the purchasing power of money is approximately equal. According to the forecast, prices will increase by 2.9 percent in 2024. The annual inflation rate for previous years can be found here and the consumer price index for all urban consumers here. The monthly inflation rate for the United States can also be accessed here. Inflation in the U.S.Inflation is a term used to describe a general rise in the price of goods and services in an economy over a given period of time. Inflation in the United States is calculated using the consumer price index (CPI). The consumer price index is a measure of change in the price level of a preselected market basket of consumer goods and services purchased by households. This forecast of U.S. inflation was prepared by the International Monetary Fund. They project that inflation will stay higher than average throughout 2023, followed by a decrease to around roughly two percent annual rise in the general level of prices until 2028. Considering the annual inflation rate in the United States in 2021, a two percent inflation rate is a very moderate projection. The 2022 spike in inflation in the United States and worldwide is due to a variety of factors that have put constraints on various aspects of the economy. These factors include COVID-19 pandemic spending and supply-chain constraints, disruptions due to the war in Ukraine, and pandemic related changes in the labor force. Although the moderate inflation of prices between two and three percent is considered normal in a modern economy, countries’ central banks try to prevent severe inflation and deflation to keep the growth of prices to a minimum. Severe inflation is considered dangerous to a country’s economy because it can rapidly diminish the population’s purchasing power and thus damage the GDP .

Abstract

Key components of the WFSO database cover the prevalence of severe food insecurity, including estimates for countries lacking official data, population sizes of the severely food insecure, required safety net financing, and corresponding estimates expressed on the Integrated Phase Classification (IPC) scale. Data is presented in a user-friendly format.

WFSO data primarily relies on hunger and malnutrition data from the State of Food Security and Nutrition in the World (SOFI) report, led by the Food and agriculture Organization (FAO) in collaboration with multiple UN agencies. WFSO complements SOFI data by providing estimates for unreported countries. Historical estimates are produced with a machine learning model leveraging World Development Indicators (WDI) for global coverage. This model has been extended to express outputs on the IPC scale by converting estimates using a nonlinear beta regression estimated on a normalized range, and distributionally adjusted using a smooth threshold transformation.

Financing needs for safety nets are calculated similarly to past approaches by the International Development Association (IDA) to assess food insecurity response needs (IDA (2020) and IDA (2021)). Preliminary estimates and projections rely on the same model and incorporate International Monetary Fund (IMF)'s World Economic Outlook (WEO) growth and inflation forecasts. WEO data reflects the IMF's expert analysis from various sources, including government agencies, central banks, and international organizations.

Minor gaps in WDI data inflation data are replaced with unofficial WEO estimates. Minor inflation data gaps not covered by both, are replaced with unofficial inflation estimates from the World Bank's Real Time Food Prices (RTFP) data.

The WFSO is updated three times a year, coinciding with IMF's WEO and SOFI releases. It provides food security projections that align with economic forecasts, aiding policymakers in integrating food security into economic planning.

The WFSO database serves various purposes, aiding World Bank economists and researchers in economic analysis, policy recommendations, and the assessment of global financing needs to address food insecurity.

Additionally, the WFSO enhances transparency in global food security data by tracking regional and global figures and breaking them down by individual countries. Historical estimates support research and long-term trend assessments, especially in the context of relating outlooks to past food security crises.

Geographic coverage

World

Geographic coverage notes

191 countries and territories mutually included by the World Bank's WDI and IMF's WEO databases. The country coverage is based on mutual inclusion in both the World Bank World Development Indicators database and the International Monetary Fund’s World Economic Outlook database. Some countries and territories may not be covered. Every attempt is made to provide comprehensive coverage. To produce complete historical predictions, missing data in the WDI are completed with unofficial data from the WEO and the World Bank's RTFP data when inflation data is not available in either database. Final gaps in the WDI and WEO are interpolated using a Kernel-based pattern-matching algorithm. See background documentation for equations.

Analysis unit

Country

Kind of data

Process-produced data [pro]

The dataset contains 41265 observations and 21 variables. Each row represents a specific observation or data point. The variables in the dataset include: hpi_type: Type of housing price index data (e.g., traditional, developmental, distress-free, non-metro). hpi_flavor: Flavor of the housing price index data (e.g., purchase-only, all-transactions, expanded-data). frequency: Frequency of the data (e.g., monthly, quarterly). level: Level of geography (e.g., USA or Census Division, State, MSA, Puerto Rico). place_name: Name of the place (e.g., region, state, metropolitan area). place_id: Identifier for the place (e.g., abbreviation, CBSA code). yr: Year of the data. period: Period of the data (e.g., month, quarter). index_nsa: Index, non seasonally adjusted. index_sa: Index, seasonally adjusted. Gross domestic product, constant prices: GDP at constant prices in national currency. Gross domestic product per capita, constant prices: GDP per capita at constant prices. Gross domestic product per capita, current prices: GDP per capita at current prices. Gross domestic product based on purchasing-power-parity (PPP) share of world total: GDP based on PPP as a share of world total GDP. Inflation, average consumer prices: Average consumer price inflation index. Volume of imports of goods and services: Volume change in imports of goods and services. Volume of exports of goods and services: Volume change in exports of goods and services. Unemployment rate: Percentage of total labor force unemployed. Current account balance: Balance of payments current account balance. Date: Date of the data. GSPC.Close: Closing price of the S&P 500 index.

About Dataset

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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 Pakistan decreased to 6.10 percent in November from 6.20 percent in October of 2025. This dataset provides the latest reported value for - Pakistan Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Graph and download economic data for Core Consumer Price Inflation for United Arab Emirates (AREPCPICOREPCHPT) from 2009 to 2010 about United Arab Emirates, consumer prices, core, REO, consumer, inflation, and rate.

Tanzania TZ: Inflation:(GDP) Gross Domestic ProductDeflator: Linked Series data was reported at 5.072 % in 2017. This records a decrease from the previous number of 6.157 % for 2016. Tanzania TZ: Inflation:(GDP) Gross Domestic ProductDeflator: Linked Series data is updated yearly, averaging 10.002 % from Dec 1990 (Median) to 2017, with 28 observations. The data reached an all-time high of 31.170 % in 1994 and a record low of 5.037 % in 2014. Tanzania TZ: Inflation:(GDP) Gross Domestic ProductDeflator: Linked Series data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Tanzania – Table TZ.World Bank: Inflation. Inflation as measured by the annual growth rate of the GDP implicit deflator shows the rate of price change in the economy as a whole. This series has been linked to produce a consistent time series to counteract breaks in series over time due to changes in base years, source data and methodologies. Thus, it may not be comparable with other national accounts series in the database for historical years.; ; World Bank staff estimates based on World Bank national accounts data archives, OECD National Accounts, and the IMF WEO database.; ;