A survey conducted among global brands revealed that talks of a recession in 2023 influence their media budget decisions. Nearly ** percent of the multinationals surveyed agreed or strongly agreed that an economic crisis is taken into consideration when planning advertising and market expenditures for 2023.

Graph and download economic data for Dates of U.S. recessions as inferred by GDP-based recession indicator (JHDUSRGDPBR) from Q4 1967 to Q1 2025 about recession indicators, GDP, and USA.

By April 2026, it is projected that there is a probability of ***** percent that the United States will fall into another economic recession. This reflects a significant decrease from the projection of the preceding month.

In spring 2023, more than half of surveyed consumers in the United States said they could live without buying apparel for a little while if they entered a recession in the next six months. Ranking second, many also said they could put a hold on buying home improvement items during times of economic uncertainty.

This data package includes the underlying data files to replicate the data and charts presented in Egypt’s 2023-24 economic crisis: Will this time be different? by Ruchir Agarwal and Adnan Mazarei, PIIE Policy Brief 24-6.

If you use the data, please cite as: Agarwal, Ruchir, and Adnan Mazarei. 2024. Egypt’s 2023-24 economic crisis: Will this time be different?. PIIE Policy Brief 24-6. Washington, DC: Peterson Institute for International Economics.

The Weekly Economic Index (WEI) of the United States exhibited notable fluctuations between January 2021 and August 2025. Throughout this period, the WEI reached its lowest point at negative **** percent in the third week of February 2021, while achieving its peak at ***** percent in the first week of May 2021. From 2021 through the initial half of 2023, the WEI demonstrated a gradual decline, interspersed with occasional minor upturns. This phase was succeeded by a period characterized by a modest overall increase. What is the Weekly Economic Index? The Weekly Economic Index (WEI) is an index of real economic activity using high-frequency data, used to signal the state of the U.S. economy. It is an index of ** daily and weekly indicators, scaled to align with the four-quarter GDP growth rate. The indicators reflected in the WEI cover consumer behavior, the labor market, and production.

The weekly gross domestic product (GDP) growth rate fluctuated significantly in the United States between January 2021 and April 2023. Between January and April 2021, it increased sharply from ***** percent to ***** percent. From April 2021 onwards, it started to decrease drastically, with slight occasional increases, and reached its lowest value at negative **** percent in November 2022. After November 2022, the weekly GDP growth rate increased notably.

A recession is due in the U.S. in 2023, according to a majority of macroeconomists in a June 2022 survey. Opinions varied, however, on when in 2023 this new recession could start exactly. Most respondents - ** percent - believed the economic downturn most likely start in the first half of 2023. Meanwhile, ** percent said that it would begin in the latter half of that year. Most Americans thought differently on this topic, believing that the country was already experiencing an economic recession in June 2022. The macroeconomists cited both geopolitical tensions and the increasing costs of energy as the main reasons why pressure would remain on U.S. inflation.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

LON:ETX Stock: Are We Headed for a Recession?

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

The Gross Domestic Product (GDP) in the United States expanded 3.30 percent in the second quarter of 2025 over the previous quarter. This dataset provides the latest reported value for - United States GDP Growth Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The National Association of County and City Health Officials' (NACCHO's) Forces of Change Survey was developed as an evolution to NACCHO's Job Losses and Program Cuts surveys, which measured the impact of the economic recession on local health departments' (LHDs) budgets, staff, and programs. Beginning in 2014, NACCHO began conducting the Forces of Change survey yearly in years that the National Profile Study of Local Health Departments (Profile) was not fielded. The Forces of Change Survey continues to measure changes in LHD budgets, staff, programs, and assess more broadly the impact of forces affecting change in LHDs.

View economic output, reported as the nominal value of all new goods and services produced by labor and property located in the U.S.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

IE:TSX Stock: Are We Headed for a Recession?

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

United States (DC)Nonfarm Business: Recession Effect Adjustment data was reported at 99.526 1992=100 in 2023. This stayed constant from the previous number of 99.526 1992=100 for 2022. United States (DC)Nonfarm Business: Recession Effect Adjustment data is updated yearly, averaging 100.000 1992=100 from Dec 1949 (Median) to 2023, with 75 observations. The data reached an all-time high of 100.000 1992=100 in 2009 and a record low of 99.526 1992=100 in 2023. United States (DC)Nonfarm Business: Recession Effect Adjustment data remains active status in CEIC and is reported by Congressional Budget Office. The data is categorized under Global Database’s United States – Table US.A130: NIPA 2018: Potential Gross Domestic Product: Projection.

GDP Counterfactual Tracker: % Change from Pre-Crisis Trend data was reported at 5.430 % in Jan 2023. This records a decrease from the previous number of 6.167 % for Oct 2022. GDP Counterfactual Tracker: % Change from Pre-Crisis Trend data is updated quarterly, averaging -3.061 % from Jan 2020 (Median) to Jan 2023, with 13 observations. The data reached an all-time high of 20.118 % in Apr 2022 and a record low of -19.394 % in Apr 2020. GDP Counterfactual Tracker: % Change from Pre-Crisis Trend data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Ireland – Table IE.OECD.WT: GDP Growth Tracker: Quarterly.

The Gross Domestic Product (GDP) in Taiwan expanded 8.01 percent in the second quarter of 2025 over the same quarter of the previous year. This dataset provides - Taiwan GDP Annual Growth Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

GDP Counterfactual Tracker: % Change from Pre-Crisis Trend data was reported at 6.207 % in Jan 2023. This records a decrease from the previous number of 8.913 % for Oct 2022. GDP Counterfactual Tracker: % Change from Pre-Crisis Trend data is updated quarterly, averaging -3.330 % from Jan 2020 (Median) to Jan 2023, with 13 observations. The data reached an all-time high of 16.657 % in Apr 2022 and a record low of -16.538 % in Apr 2020. GDP Counterfactual Tracker: % Change from Pre-Crisis Trend data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Greece – Table GR.OECD.WT: GDP Growth Tracker: Quarterly.

GDP Counterfactual Tracker: % Change from Pre-Crisis Trend: Low data was reported at 3.210 % in Jan 2023. This records an increase from the previous number of 2.864 % for Oct 2022. GDP Counterfactual Tracker: % Change from Pre-Crisis Trend: Low data is updated quarterly, averaging -3.757 % from Jan 2020 (Median) to Jan 2023, with 13 observations. The data reached an all-time high of 12.001 % in Apr 2022 and a record low of -17.293 % in Apr 2020. GDP Counterfactual Tracker: % Change from Pre-Crisis Trend: Low data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Austria – Table AT.OECD.WT: GDP Growth Tracker: Quarterly.

Bibliographic Data onUkarine Crisis ιn Economics and Business Research Generated by Koutsoupias Nikosstudied in The War in Ukraine as a Global Economic Crisis (2014-2023)an article by Prof. A. Bitzenis and Prof. N. Koutsoupias, University of Macedonia, GreeceVolume in honor of Elias KouskouvelisEdited by The Council for International Relations - Greece (CfIR-GR)Δεδομένα που μελετήθηκαν στο:O Πόλεμος στην Ουκρανία ως Παγκόσμια Οικονομική Κρίση (2014-2023) των Α.Μπιτζενη και Ν.Κουτσουπιαστον τόμο εις μνήμην του καθ. Ηλία Κουσκουβέληεκδ. Συμβουλίου Διεθνών Σχέσεων, Αθήνα, 2024

The Appalachian Regional Commission uses an index-based county economic classification system to identify and monitor the economic status of Appalachian counties. See the methodology for a description of each economic level.In fiscal year 2022, 5 Ohio ARC counties are classified as distressed, 14 are classified as at-risk, 11 are classified as transitional, 2 are classified as competitive, and 0 are classified as attainment. The current number of distressed counties for the entire ARC region is the third-lowest count since pre-recession in 2007. For a list of county classifications, see the downloadable Excel file.https://www.arc.gov/map/county-economic-status-in-appalachia-fy-2023/This layer was created by joining the raw data from the County Economic Status FY 2022 Data table to the Census 2021 county boundary (tl_2021_39_county)The layer contains economic and demographic data for all 88 counties, a definition query is used to display the 32 Appalachian counties.