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The 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.
Each record in the dataset is meticulously structured and includes:
This rich combination of fields ensures seamless integration into data science projects, research papers, and market analyses.
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.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Inflation Expectations in the United States increased to 3.40 percent in September from 3.20 percent in August of 2025. This dataset provides - United States Consumer Inflation Expectations- actual values, historical data, forecast, chart, statistics, economic calendar and news.
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
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.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Inflation Rate in Canada increased to 1.90 percent in August from 1.70 percent in July of 2025. This dataset provides - Canada Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Inflation Rate in Jordan decreased to 1.32 percent in August from 1.68 percent in July of 2025. This dataset provides the latest reported value for - Jordan Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.
This dataset includes economic statistics on inflation, prices, unemployment, and pay & benefits provided by the Bureau of Labor Statistics (BLS)
Update frequency: Monthly Dataset source: U.S. Bureau of Labor Statistics Terms of use: This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source - http://www.data.gov/privacy-policy#data_policy - and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset. See the GCP Marketplace listing for more details and sample queries: https://console.cloud.google.com/marketplace/details/bls-public-data/bureau-of-labor-statistics
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset provides values for INFLATION EXPECTATIONS reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.
This dataset was created by Ahmed Helmy
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Inflation Rate in Mozambique increased to 4.79 percent in August from 3.96 percent in July of 2025. This dataset provides - Mozambique Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Cost of food in Nigeria increased 21.87 percent in August of 2025 over the same month in the previous year. This dataset provides - Nigeria Food Inflation - actual values, historical data, forecast, chart, statistics, economic calendar and news.
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
UK price index data at manufacturing, aggregated industry and product group levels. Data supplied from individual manufacturers, importers and exporters. Monthly and annual data.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset provides values for INFLATION RATE MOM reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the median household income across different racial categories in Economy. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.
Key observations
Based on our analysis of the distribution of Economy population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 94.13% of the total residents in Economy. Notably, the median household income for White households is $96,548. Interestingly, White is both the largest group and the one with the highest median household income, which stands at $96,548.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Economy median household income by race. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Core Inflation Rate MoM in the United States remained unchanged at 0.30 percent in August. This dataset includes a chart with historical data for the United States Core Inflation Rate MoM.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
The Consumer Price Index (CPI) for food is a component of the all-items CPI. The CPI measures the average change over time in the prices paid by urban consumers for a representative market basket of consumer goods and services. While the all-items CPI measures the price changes for all consumer goods and services, including food, the CPI for food measures the changes in the retail prices of food items only.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: Web page with links to Excel files For complete information, please visit https://data.gov.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset provides values for INFLATION RATE!S reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.
https://dataverse.harvard.edu/api/datasets/:persistentId/versions/9.0/customlicense?persistentId=doi:10.7910/DVN/4YHTPUhttps://dataverse.harvard.edu/api/datasets/:persistentId/versions/9.0/customlicense?persistentId=doi:10.7910/DVN/4YHTPU
Main data files comprise 22 variables in three subcategories of risk (political, financial, and economic) for 146 countries for 1984-2021. Data are annual averages of the components of the ICRG Risk Ratings (Tables 3B, 4B, and 5B) published in the International Country Risk Guide. Indices include: political: government stability, socioeconomic conditions, investment profile, internal conflict, external conflict, corruption, military in politics, religion in politics, law and order, ethnic tensions, democratic accountability, and bureaucratic quality; financial: foreign debt, exchange rate stability, debt service, current account, international liquidity; and economic: inflation, GDP per head, GDP growth, budget balance, current account as % of GDP. Table 2B provides annual averages of the composite risk rating. Table 3Ba provides historical political risk subcomponents on a monthly basis from May 2001-February 2022. Also includes the IRIS-3 dataset by Steve Knack and Philip Keefer, which covers the period of 1982-1997 and computed scores for six additional political risk variables: corruption in government, rule of law, bureaucratic quality, ethnic tensions, repudiation of contracts by government, and risk of expropriation. Additional data files provide country risk ratings and databanks (economic and social indicators) for new emerging markets for 2000-2009.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the median household incomes over the past decade across various racial categories identified by the U.S. Census Bureau in Economy. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. It also showcases the annual income trends, between 2011 and 2021, providing insights into the economic shifts within diverse racial communities.The dataset can be utilized to gain insights into income disparities and variations across racial categories, aiding in data analysis and decision-making..
Key observations
https://i.neilsberg.com/ch/economy-in-median-household-income-by-race-trends.jpeg" alt="Economy, IN median household income trends across races (2011-2021, in 2022 inflation-adjusted dollars)">
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Economy median household income by race. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Context
The dataset presents the median household income across different racial categories in Hamilton town. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.
Key observations
Based on our analysis of the distribution of Hamilton town population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 87.26% of the total residents in Hamilton town. Notably, the median household income for White households is $73,938. Interestingly, despite the White population being the most populous, it is worth noting that Asian households actually reports the highest median household income, with a median income of $250,001. This reveals that, while Whites may be the most numerous in Hamilton town, Asian households experience greater economic prosperity in terms of median household income.
When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.
Racial categories include:
Variables / Data Columns
Good to know
Margin of Error
Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.
Custom data
If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.
Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.
This dataset is a part of the main dataset for Hamilton town median household income by race. You can refer the same here
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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.
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The 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.
Each record in the dataset is meticulously structured and includes:
This rich combination of fields ensures seamless integration into data science projects, research papers, and market analyses.
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.