This dataset contains economic indicators for Pakistan spanning from 1986 to 2006 (21 years of data). Here's what the dataset includes: Dataset Overview:

Time Period: 1986-2006 Country: Pakistan Purpose: Inflation forecasting analysis

Variables/Columns:

Year - Time period identifier Inflation - Inflation rates (ranging from about 2.9% to 12.4%) [Column C] - Unlabeled column with values like 16.65, 17.4, 18, etc. GDP Growth - Economic growth rates (ranging from 1% to 7.8%) Unemployment - Unemployment rates (mostly between 3-8%) Broad Money - Monetary supply indicator (values in hundreds) Exports - Export values Imports - Import values Oil rents - Oil-related economic indicator (mostly below 1.0) Remittances - Foreign remittance values

Key Characteristics:

Comprehensive macroeconomic dataset Covers multiple economic indicators that typically influence inflation Suitable for econometric analysis and forecasting models Includes both monetary (broad money, remittances) and real sector variables (GDP, unemployment) Trade variables (exports/imports) for external sector analysis

This appears to be a well-structured dataset for studying inflation dynamics and building forecasting models for Pakistan's economy.

Cost of food in Lebanon increased 23.90 percent in September of 2025 over the same month in the previous year. This dataset provides - Lebanon Food Inflation - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Inflation Rate in Australia increased to 3.80 percent in the fourth quarter of 2025 from 3.20 percent in the third quarter of 2025. This dataset provides the latest reported value for - Australia Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

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.

Core consumer prices in Romania increased 8 percent in October of 2025 over the same month in the previous year. This dataset provides - Romania Core Inflation Rate- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Monthly and long-term Djibouti Inflation data: historical series and analyst forecasts curated by FocusEconomics.

CNBC Economy Articles Dataset is an invaluable collection of data extracted from CNBC’s economy section, offering deep insights into global and U.S. economic trends, market dynamics, financial policies, and industry developments.

This dataset encompasses a diverse array of economic articles on critical topics like GDP growth, inflation rates, employment statistics, central bank policies, and major global events influencing the market. Designed for researchers, analysts, and businesses, it serves as an essential resource for understanding economic patterns, conducting sentiment analysis, and developing financial forecasting models.

Dataset Highlights

Each record in the dataset is meticulously structured and includes:

• Article Titles
• Publication Dates
• Author Names
• Content Summaries
• URLs to Original Articles

This rich combination of fields ensures seamless integration into data science projects, research papers, and market analyses.

Key Features

• Number of Articles: Hundreds of articles sourced directly from CNBC.
• Data Fields: Includes title, publication date, author, article content, summary, URL, and relevant keywords.
• Topics Covered: U.S. and global economy, GDP trends, inflation, employment, financial markets, and monetary policies.
• Format: Delivered in CSV format for easy integration with research tools and analytical platforms.
• Source: Extracted directly from CNBC’s economy news section, ensuring accuracy and relevance.

Use Cases

• Economic Research: Gain insights into U.S. and global economic policies, market trends, and industry developments.
• Sentiment Analysis: Assess the sentiment of economic articles to gauge market perspectives and investor confidence.
• Financial Modeling: Build forecasting models leveraging key economic indicators discussed in the dataset.
• Content Creation: Develop research-backed reports, articles, and presentations on economic topics.

Who Benefits?

• Researchers & Academics studying macro-economics or financial policy.
  
• Data Scientists building AI models, trend analyzers, or economic forecasting tools.
  
• Economists & Analysts need real-world news data for policy analysis.
  
• Content Strategists who write data-backed articles about economic trends.

Why Choose This Dataset?

• No need to manually scrape CNBC — data is pre-extracted and clean.
  
• High-quality economy news metadata enables detailed filtering (by date, author, topic).
  
• Ready for machine learning, sentiment analysis, or building news-based economic models.
  
• Well-suited for trend tracking, policy analysis, and economic forecasting.

Explore More News Datasets

Interested in additional structured news datasets for your research or analytics needs? Check out our news dataset collection to find datasets tailored for diverse analytical applications.

Monthly and long-term Burkina Faso Inflation data: historical series and analyst forecasts curated by FocusEconomics.

Context

Happiness and well-being are essential indicators of societal progress, often influenced by economic conditions such as GDP and inflation. This dataset combines data from the World Happiness Index (WHI) and inflation metrics to explore the relationship between economic stability and happiness levels across 148 countries from 2015 to 2023. By analyzing key economic indicators alongside social well-being factors, this dataset provides insights into global prosperity trends.

Content

This dataset is provided in CSV format and includes 16 columns, covering both happiness-related features and economic indicators such as GDP per capita, inflation rates, and corruption perception. The main columns include:

Happiness Score & Rank (World Happiness Index ranking per country) Economic Indicators (GDP per capita, inflation metrics) Social Factors (Freedom, Social Support, Generosity) Geographical Information (Country & Continent)

Acknowledgements

The dataset is created using publicly available data from World Happiness Report, Gallup World Poll, and the World Bank. It has been structured for research, machine learning, and policy analysis purposes.

Inspiration

How do economic factors like inflation, GDP, and corruption affect happiness? Can we predict a country's happiness score based on economic conditions? This dataset allows you to analyze these relationships and build models to predict well-being trends worldwide.

Monthly and long-term Dominica Inflation data: historical series and analyst forecasts curated by FocusEconomics.

The Consumer Price Index in Rwanda increased 1 percent in October of 2025 over the previous month. This dataset provides - Rwanda Inflation Rate MoM- actual values, historical data, forecast, chart, statistics, economic calendar and news.

In the third quarter of 2024, half of Norwegian companies had problems with increasing purchase prices as a result of rising inflation seen around the world. Moreover, more than 40 percent faced problems due to an unstable economic framework. On the other hand, only 10 percent had issues with lack of credits or financing. As a consequence of the COVID-19 pandemic, as well as the Russian War in Ukraine that started in February 2022, inflation has been surging worldwide. For more information about inflation in the Nordic countries, please visit our dedicated topic page.

This dataset provides a comprehensive collection of monthly U.S. macroeconomic indicators spanning January 2000 to December 2024.

It was designed specifically for machine learning-based inflation forecasting and includes key economic factors historically associated with inflation trends:

• Consumer Price Index (CPI) & Inflation Rate
• Unemployment Rate
• Federal Funds Rate
• M2 Money Supply
• Crude Oil Prices (WTI)
• Producer Price Index (PPI)

Primary Goal: Build predictive models to forecast year-over-year inflation rates

Possible Use Cases:

• Forecasting inflation using machine learning models like XGBoost, Random Forest, or LSTM.
• Studying relationships between macroeconomic factors and inflationary pressure.
• Comparing classical econometric approaches with modern AI-based forecasting techniques.

Structure: Each CSV contains a Date column and corresponding metric values, making it easy to merge and align data for analysis.

License: MIT License – free to use for research and educational purposes.

Monthly and long-term San Marino Inflation data: historical series and analyst forecasts curated by FocusEconomics.

Graph and download economic data for FOMC Summary of Economic Projections for the Personal Consumption Expenditures less Food and Energy Inflation Rate, Median (JCXFEMD) from 2025 to 2028 about core, projection, PCE, consumption expenditures, consumption, personal, median, inflation, rate, and USA.

Since the COVID-19 pandemic, the United States has experienced sharply rising then falling inflation alongside persistent labor market imbalances. This Economic Commentary interprets these macroeconomic dynamics, as represented by the Beveridge and Phillips curves, through the lens of a macroeconomic model. It uses the structure of the model to rationalize the debate about whether the US economy can expect a hard or soft landing. The model is surprised by the resiliency of the labor market as the US economy experienced disinflation. We suggest that the model’s limited ability to capture this resiliency is a feature of using a linear model to forecast the historically unprecedented movements seen after the pandemic among inflation, unemployment, and vacancy rates. We explain how, by adjusting the model to mimic congestion in a tight labor market and greater wage and price flexibility in a high-inflation environment, as during the post-pandemic period, the model can then capture what has been a path consistent with a soft landing.

Monthly and long-term Italy Inflation (CPI, ann. var. %, aop) data: historical series and analyst forecasts curated by FocusEconomics.

Monthly and long-term Bhutan Inflation data: historical series and analyst forecasts curated by FocusEconomics.

This data package includes the underlying data to replicate the charts and calculations presented in US Monetary Policy and the Recent Surge in Inflation, PIIE Working Paper 24-13.

If you use the data, please cite as:

Reifschneider, David. 2024. US Monetary Policy and the Recent Surge in Inflation. PIIE Working Paper 24-13. Washington: Peterson Institute for International Economics.

Dataset

This dataset was created by Usman Yaqoob

Released under Apache 2.0

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