Content

Providing daily updates on global economic developments with coverage of high-income as well as developing countries. Data updates are provided for exchange rates, equity markets, and emerging market bond indices. Monthly data coverage (updated daily and populated upon availability) is provided for consumer prices, high-tech market indicators, industrial production, and merchandise trade.

Context

This Global Economic Monitor dataset provides worldwide economic updates. It covers exchange rates, equity markets, and emerging market bonds daily. Plus, get monthly insights on consumer prices, high-tech markets, industrial production, and trade trends.

Acknowledgment

The primary dataset was retrieved from the World Bank Group's Data Catalog. I would like to express our sincere appreciation to the World Bank for providing the core data used in this dataset.

©️ Image credit: Freepik

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.

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.

Transportation Economic Trends (TET), developed by the Bureau of Transportation Statistics (BTS), highlights transportation's role in the economy and explores changes (trends) over time through a series of interactive charts. TET also explains related concepts and data sources for a general audience.

This dataset provides a historical overview of key global indicators, including Gross Domestic Product (GDP), population growth, and CO2 emissions. It captures economic trends, demographic shifts, and environmental impacts over multiple decades, making it useful for researchers, analysts, and policymakers.

The dataset includes Real GDP (inflation-adjusted), allowing for economic trend analysis while accounting for inflation effects. Additionally, it incorporates CO2 emissions data, enabling studies on the relationship between economic growth and environmental impact.

This dataset is valuable for multiple research areas:

✅ Macroeconomic Analysis – Study global economic growth, recessions, and recovery trends.

✅ Inflation & Monetary Policy – Compare nominal vs. real GDP to assess inflationary trends.

✅ Climate Change Research – Analyze CO2 emissions alongside economic growth to identify sustainability challenges.

✅ Predictive Modeling – Train machine learning models for forecasting GDP, population, or emissions.

✅ Public Policy & Development – Evaluate the impact of economic and environmental policies over time.

This dataset is shared for educational and analytical purposes only.

Page describes the U.S. Department of Transportation, Bureau of Transportation Statistics' Transportation Economic Data offerings.

DMPED is using economic data to drive positive change and build good government for District of Columbia residents. They are focusing on collecting and compiling information about the city, in particular on D.C.’s economic development priorities that create more pathways to the middle class: jobs, quality affordable housing, and community-focused development.This site is an online version of the Deputy Mayor for Planning and Economic Development’s weekly dashboard. This dashboard is also transmitted to the City Administrator, the Mayor, and other senior staff, so they can be aware of economic trends and context. It includes only data that is public, so certain indicators that DMPED uses are not included.

U.S. Economic and Financial Dataset

Dataset Description

This dataset combines historical U.S. economic and financial indicators, spanning the last 50 years, to facilitate time series analysis and uncover patterns in macroeconomic trends. It is designed for exploring relationships between interest rates, inflation, economic growth, stock market performance, and industrial production.

Key Features

• Frequency: Monthly
• Time Period: Last 50 years from Nov-24
• Sources:
  • Federal Reserve Economic Data (FRED)
  • Yahoo Finance

Dataset Feature Description

1. Interest Rate (Interest_Rate):

   • The effective federal funds rate, representing the interest rate at which depository institutions trade federal funds overnight.

2. Inflation (Inflation):

   • The Consumer Price Index for All Urban Consumers, an indicator of inflation trends.

3. GDP (GDP):

   • Real GDP measures the inflation-adjusted value of goods and services produced in the U.S.

4. Unemployment Rate (Unemployment):

   • The percentage of the labor force that is unemployed and actively seeking work.

5. Stock Market Performance (S&P500):

   • Monthly average of the adjusted close price, representing stock market trends.

6. Industrial Production (Ind_Prod):

   • A measure of real output in the industrial sector, including manufacturing, mining, and utilities.

Dataset Statistics

1. Total Entries: 599
2. Columns: 6
3. Memory usage: 37.54 kB
4. Data types: float64

Feature Overview

• Columns:
  • Interest_Rate: Monthly Federal Funds Rate (%)
  • Inflation: CPI (All Urban Consumers, Index)
  • GDP: Real GDP (Billions of Chained 2012 Dollars)
  • Unemployment: Unemployment Rate (%)
  • Ind_Prod: Industrial Production Index (2017=100)
  • S&P500: Monthly Average of S&P 500 Adjusted Close Prices

Executive Summary

This project explores the interconnected dynamics of key macroeconomic indicators and financial market trends over the past 50 years, leveraging data from the Federal Reserve Economic Data (FRED) and Yahoo Finance. The dataset integrates critical variables such as the Federal Funds Rate, Inflation (CPI), Real GDP, Unemployment Rate, Industrial Production, and the S&P 500 Index, providing a holistic view of the U.S. economy and financial markets.

The analysis focuses on uncovering relationships between these variables through time-series visualization, correlation analysis, and trend decomposition. Key findings are included in the Insights section. This project serves as a robust resource for understanding long-term economic trends, policy impacts, and market behavior. It is particularly valuable for students, researchers, policymakers, and financial analysts seeking to connect macroeconomic theory with real-world data.

Potential Use Cases

• Economic Analysis: Examine relationships between interest rates, inflation, GDP, and unemployment.
• Stock Market Prediction: Study how macroeconomic indicators influence stock market trends.
• Time Series Modeling: Perform ARIMA, VAR, or other models to forecast economic trends.
• Cyclic Pattern Analysis: Identify how economic shocks and recoveries impact key indicators.

Snap of Power Analysis

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To ensure sufficient power, the dataset covers last 50 years of monthly data i.e., around 600 entries.

Key Insights derived through EDA, time-series visualization, correlation analysis, and trend decomposition

• Interest Rate and Inflation Dynamics: The interest Rate and inflation exhibit an inverse relationship, especially during periods of aggressive monetary tightening by the Federal Reserve.
• Economic Growth and Market Performance: GDP growth and the S&P 500 Index show a positive correlation, reflecting how market performance often aligns with overall economic health.
• Labor Market and Industrial Output: Unemployment and industrial production demonstrate a strong inverse relationship. Higher industrial output is typically associated with lower unemployment
• Market Behavior During Economic Shocks: The S&P 500 experienced sharp declines during significant crises, such as the 2008 financial crash and the COVID-19 pandemic in 2020. These events also triggered increased unemployment and contractions in GDP, highlighting the interplay between markets and the broader economy.
• Correlation Highlights: S&P 500 and GDP have a strong positive correlation. Interest rates negatively correlate with GDP and inflation, reflecting monetary policy impacts. Unemployment is negatively correlated with industrial production but positively correlated with interest rates.

Link to GitHub Repo

https:/...

Diffusion Index in Japan

The purpose of the Business Watchers Survey is to obtain an accurate and prompt understanding of economic trends in each region with the cooperation of those in a position to observe movements closely related to the local economy, and to provide basic data for making decisions on economic trends.
The survey is conducted from the 25th of each month to the end of the month among 2,050 respondents in 12 regions of the country, selected from appropriate occupations in industries where they can observe phenomena that sensitively reflect trends in representative economic activity items, such as household trends, business trends and employment.
The survey items are: the current condition and outlook of the economy (two to three months ahead compared to the current situation).

Sudan Google Search Trends: Economic Measures: Mortgage Loan data was reported at 0.000 Score in 30 Nov 2025. This stayed constant from the previous number of 0.000 Score for 29 Nov 2025. Sudan Google Search Trends: Economic Measures: Mortgage Loan data is updated daily, averaging 0.000 Score from Dec 2021 (Median) to 30 Nov 2025, with 1461 observations. The data reached an all-time high of 100.000 Score in 25 Apr 2024 and a record low of 0.000 Score in 30 Nov 2025. Sudan Google Search Trends: Economic Measures: Mortgage Loan data remains active status in CEIC and is reported by Google Trends. The data is categorized under Global Database’s Sudan – Table SD.Google.GT: Google Search Trends: by Categories.

Cost of fuel for transportation by year and type. Annual price is average of monthly values.

Promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all : Overall, economic trends in the Pacific region have been positive, yet inconsistent. The restricted economic bases of Pacific Island countries are highly sensitive to external economic shocks (including commodity price fluctuations, supply chain disruptions and financial stress), natural events (such as cyclones, floods and droughts) and costs of adaptation to climate change; nternal employment factors in the Pacific compound these external factors. The size of the informal economy; gender gaps and imbalances; and high youth unemployment/underemployment are issues that can be monitored under Goal 8; Tourism is an important sector of growth and development in the Pacific, providing foreign exchange earnings, employment and income earning opportunities for many Pacifc islanders. Tourism is one of the region’s few economically viable sectors, and its share in national GDPs is monitored in this goal.

Find more Pacific data on PDH.stat.

Contribution of industries to the economy and their use of transportation services to produce goods and services, including number of person employed in transportation occupations.

Unit Economics Analytics Platform Market Outlook

According to our latest research, the global Unit Economics Analytics Platform market size reached USD 2.14 billion in 2024, reflecting robust adoption across diverse industries. The market is projected to grow at a steady CAGR of 16.7% from 2025 to 2033, with the overall market anticipated to reach USD 8.23 billion by 2033. This significant expansion is primarily fueled by the growing need for granular business performance insights, the acceleration of digital transformation initiatives, and the increasing emphasis on data-driven decision-making in modern enterprises.

One of the primary growth factors propelling the Unit Economics Analytics Platform market is the increasing demand for actionable insights that drive profitability at a granular level. Organizations across sectors are seeking advanced analytics tools that enable them to dissect costs, revenues, and margins down to the unit level—be it per product, customer, or transaction. This shift is especially pronounced in industries with complex cost structures and variable pricing strategies, such as retail, e-commerce, and manufacturing. The ability to identify profitable and loss-making segments in real-time empowers businesses to optimize pricing, control costs, and enhance resource allocation, ultimately improving overall profitability and competitiveness.

Additionally, the rapid digitalization of business operations and the proliferation of data sources have amplified the need for sophisticated analytics platforms. Enterprises are leveraging cloud computing, artificial intelligence, and machine learning to process vast amounts of transactional and operational data. Unit Economics Analytics Platforms are increasingly integrating these advanced technologies to provide predictive analytics, scenario modeling, and automated recommendations. As organizations strive to maintain agility in dynamic markets, the demand for platforms that offer scalable, real-time, and customizable analytics solutions continues to surge, further accelerating market growth.

Another significant driver is the evolving regulatory and compliance landscape, particularly in sectors such as BFSI and healthcare. Stricter reporting requirements and the need for transparent financial management have compelled organizations to adopt analytics platforms that ensure accuracy, traceability, and compliance. Furthermore, the rise of subscription-based and usage-based business models has made unit economics analysis a strategic imperative for SaaS providers, telecom companies, and digital marketplaces. These trends collectively underscore the growing importance of Unit Economics Analytics Platforms in enabling sustainable growth and operational excellence.

From a regional perspective, North America currently leads the global market, accounting for the largest share in 2024, owing to its mature digital infrastructure, strong presence of technology vendors, and early adoption of advanced analytics. However, Asia Pacific is expected to witness the highest growth rate during the forecast period, driven by rapid digital transformation, expanding e-commerce ecosystems, and increasing investments in cloud-based analytics solutions. Europe remains a significant market, supported by stringent regulatory frameworks and a strong focus on operational efficiency. Meanwhile, Latin America and the Middle East & Africa are emerging as promising markets, fueled by growing awareness and adoption of analytics-driven business strategies.

Component Analysis

The Unit Economics Analytics Platform market is segmented by component into software and services, each playing a vital role in driving adoption and delivering value to end-users. The software segment dominates the market, accounting for the majority of revenue in 2024. This dominance can be attributed to the continuous evolution of analytics software, which now offers advanced features such as real-time data visualization, customizable dashboards, and AI-powered predictive modeling. These capabilities enable organizations to extract actionable insights from complex datasets, monitor key performance indicators at the unit level, and make informed decisions that directly impact profitability. The demand for user-friendly interfaces and seamless integration with existing enterprise systems further fuels innovation and growth in the software segment.

The servic

Greenland Google Search Trends: Economic Measures: Mortgage Loan data was reported at 0.000 Score in 29 Nov 2025. This stayed constant from the previous number of 0.000 Score for 28 Nov 2025. Greenland Google Search Trends: Economic Measures: Mortgage Loan data is updated daily, averaging 0.000 Score from Dec 2021 (Median) to 29 Nov 2025, with 1460 observations. The data reached an all-time high of 58.000 Score in 13 Mar 2025 and a record low of 0.000 Score in 29 Nov 2025. Greenland Google Search Trends: Economic Measures: Mortgage Loan data remains active status in CEIC and is reported by Google Trends. The data is categorized under Global Database’s Greenland – Table GL.Google.GT: Google Search Trends: by Categories.

This dataset tracks annual student-teacher ratio from 2007 to 2023 for High School Of Economics & Finance vs. New York and New York City Geographic District # 2

The main stock market index of United States, the US500, rose to 6818 points on December 2, 2025, gaining 0.08% from the previous session. Over the past month, the index has declined 0.50%, though it remains 12.70% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from United States. United States Stock Market Index - values, historical data, forecasts and news - updated on December of 2025.

This dataset tracks annual reading and language arts proficiency from 2011 to 2022 for High School Of Economics & Finance vs. New York and New York City Geographic District # 2

Google Search Trends: Economic Measures: Mortgage Loan data was reported at 0.000 Score in 29 Nov 2025. This stayed constant from the previous number of 0.000 Score for 28 Nov 2025. Google Search Trends: Economic Measures: Mortgage Loan data is updated daily, averaging 0.000 Score from Dec 2021 (Median) to 29 Nov 2025, with 1460 observations. The data reached an all-time high of 100.000 Score in 23 Jan 2022 and a record low of 0.000 Score in 29 Nov 2025. Google Search Trends: Economic Measures: Mortgage Loan data remains active status in CEIC and is reported by Google Trends. The data is categorized under Global Database’s Yemen – Table YE.Google.GT: Google Search Trends: by Categories.

Market Overview The global evening economy market experienced a significant decline due to the COVID-19 pandemic, but is expected to rebound strongly in the coming years. The market is projected to grow from USD XXX million in 2025 to USD XXX million by 2033, exhibiting a CAGR of XX% during the forecast period. The increasing urbanization, rising disposable income, and growing preference for nightlife and entertainment are the key drivers of the market growth. The market is segmented into four major types: eating and drinking economy, entertainment economy, nightlife economy, and others. The eating and drinking economy segment holds the largest market share due to the increasing popularity of fine dining, casual dining, and fast food restaurants. Regional Trends The Asia Pacific region is expected to dominate the evening economy market throughout the forecast period. The region is home to some of the world's largest and most vibrant cities, such as Tokyo, Shanghai, and Seoul. These cities offer a wide range of evening entertainment options, from live music and theater to nightclubs and bars. North America and Europe are also major markets for the evening economy, with cities such as New York City, London, and Paris attracting millions of visitors each year. The Middle East and Africa region is expected to witness the fastest growth in the coming years, driven by the increasing disposable income and the growing number of young people in the region.