By November 2025, it is projected that there is a probability of 33.56 percent that the United States will fall into another economic recession. This reflects a significant decrease from the projection of the preceding month.
https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain
Graph and download economic data for Dates of U.S. recessions as inferred by GDP-based recession indicator from Q4 1967 to Q3 2024 about recession indicators, GDP, and USA.
The Long Depression was, by a large margin, the longest-lasting recession in U.S. history. It began in the U.S. with the Panic of 1873, and lasted for over five years. This depression was the largest in a series of recessions at the turn of the 20th century, which proved to be a period of overall stagnation as the U.S. financial markets failed to keep pace with industrialization and changes in monetary policy. Great Depression The Great Depression, however, is widely considered to have been the most severe recession in U.S. history. Following the Wall Street Crash in 1929, the country's economy collapsed, wages fell and a quarter of the workforce was unemployed. It would take almost four years for recovery to begin. Additionally, U.S. expansion and integration in international markets allowed the depression to become a global event, which became a major catalyst in the build up to the Second World War. Decreasing severity When comparing recessions before and after the Great Depression, they have generally become shorter and less frequent over time. Only three recessions in the latter period have lasted more than one year. Additionally, while there were 12 recessions between 1880 and 1920, there were only six recessions between 1980 and 2020. The most severe recession in recent years was the financial crisis of 2007 (known as the Great Recession), where irresponsible lending policies and lack of government regulation allowed for a property bubble to develop and become detached from the economy over time, this eventually became untenable and the bubble burst. Although the causes of both the Great Depression and Great Recession were similar in many aspects, economists have been able to use historical evidence to try and predict, prevent, or limit the impact of future recessions.
https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain
Graph and download economic data for Real-time Sahm Rule Recession Indicator (SAHMREALTIME) from Dec 1959 to Feb 2025 about recession indicators, academic data, and USA.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
United States Recession Probability data was reported at 14.120 % in Oct 2019. This records a decrease from the previous number of 14.505 % for Sep 2019. United States Recession Probability data is updated monthly, averaging 7.668 % from Jan 1960 (Median) to Oct 2019, with 718 observations. The data reached an all-time high of 95.405 % in Dec 1981 and a record low of 0.080 % in Sep 1983. United States Recession Probability data remains active status in CEIC and is reported by Federal Reserve Bank of New York. The data is categorized under Global Database’s United States – Table US.S021: Recession Probability.
United States banking professionals believed in Q2 2022 that a Fed overcorrection was a probable cause for a recession. 51 percent of the respondents believed that the too fast and too highly increasing Fed rates would result in an economic recession. 25 percent of the respondents predicted that a recession would occur because of supply chain problems, while five percent mentioned the conflict in Eastern Europe as the main cause for a possible recession.
https://fred.stlouisfed.org/legal/#copyright-citation-requiredhttps://fred.stlouisfed.org/legal/#copyright-citation-required
Graph and download economic data for NBER based Recession Indicators for the United States from the Period following the Peak through the Trough (USREC) from Dec 1854 to Feb 2025 about peak, trough, recession indicators, and USA.
https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain
Graph and download economic data for GDP-Based Recession Indicator Index (JHGDPBRINDX) from Q4 1967 to Q3 2024 about recession indicators, percent, GDP, and indexes.
https://www.kappasignal.com/p/legal-disclaimer.htmlhttps://www.kappasignal.com/p/legal-disclaimer.html
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.
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)
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)
Stock price prediction
Portfolio optimization
Algorithmic trading
Market sentiment analysis
Risk management
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
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
https://www.kappasignal.com/p/legal-disclaimer.htmlhttps://www.kappasignal.com/p/legal-disclaimer.html
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.
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)
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)
Stock price prediction
Portfolio optimization
Algorithmic trading
Market sentiment analysis
Risk management
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
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
In October 2024, the Sahm recession indicator was 0.43, a slight decrease from the previous month. The Sahm Rule was developed to flag the onset of an economic recession more quickly than other indicators. The Sahm Rule signals the start of a recession when the three-month moving average of the national unemployment rate rises by 0.50 percentage points or more relative to its low during the previous 12 months.
https://www.kappasignal.com/p/legal-disclaimer.htmlhttps://www.kappasignal.com/p/legal-disclaimer.html
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.
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)
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)
Stock price prediction
Portfolio optimization
Algorithmic trading
Market sentiment analysis
Risk management
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
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
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
United States - Dates of U.S. recessions as inferred by GDP-based recession indicator was 0.00000 +1 or 0 in July of 2024, according to the United States Federal Reserve. Historically, United States - Dates of U.S. recessions as inferred by GDP-based recession indicator reached a record high of 1.00000 in April of 1969 and a record low of 0.00000 in January of 1968. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Dates of U.S. recessions as inferred by GDP-based recession indicator - last updated from the United States Federal Reserve on March of 2025.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
We show that a simple and intuitive three-parameter equation fits remarkably well the evolution of the gross domestic product (GDP) in current and constant dollars of many countries during times of recession and recovery. We then argue that this equation is the response function of the economy to isolated shocks, hence that it can be used to detect large and small shocks, including those which do not lead to a recession; we also discuss its predictive power. Finally, a two-sector toy model of recession and recovery illustrates how the severity and length of recession depends on the dynamics of transfer rate between the growing and failing parts of the economy.
The Weekly Economic Index (WEI) of the United States exhibited notable fluctuations between January 2021 and March 2025. Throughout this period, the WEI reached its lowest point at negative 0.98 percent in the third week of February 2021, while achieving its peak at 10.27 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 10 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.
This paper asks whether the slow recovery of the US economy from the trough of the Great Recession was anticipated, and identifies some of the factors that contributed to surprises in the course of the recovery. We construct a narrative using news reports and government announcements to identify policy and financial shocks. We then compare forecasts and forecast revisions of GDP to the narrative. Successive financial and fiscal shocks emanating from Europe, together with self-inflicted wounds from the political stalemate over the US fiscal situation, help explain the slowing of the pace of an already slow recovery.
The American Recovery and Reinvestment Act (ARRA) was passed by the U.S. congress in February 2009, authorizing the federal government to spend up to 800 billion U.S. dollars on stimulating the economy. With the election of Barack Obama to the U.S. Presidency in November 2008, the priority of the policy response to the Great Recession and Global Financial Crisis shifted from aiming to backstop the financial system, to trying to stimulate economic growth through tax cuts, infrastructure spending, and improving public services. By 2011, around 500 billion had been disbursed to government departments or agencies, with the greatest beneficiaries being Health and Human Services, the Treasury Department, and the Department of Education. The act was the signature economic policy initiative of the Obama administration and has been credited by some for preventing the recession from spiraling into a crisis of the magnitude of the Great Depression. The size of the stimulus package also galvanized opposition from Republicans, however, with the Tea Party movement arising to oppose the Obama administration's economic policies, while the Republicans retook control of congress in the 2010 midterm elections.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
United States NBER-Based Recession Indicators from the Peak Through the Trough data was reported at 0.000 Unit in 18 Mar 2025. This stayed constant from the previous number of 0.000 Unit for 17 Mar 2025. United States NBER-Based Recession Indicators from the Peak Through the Trough data is updated daily, averaging 0.000 Unit from Dec 1854 (Median) to 18 Mar 2025, with 62199 observations. The data reached an all-time high of 1.000 Unit in 15 Apr 2020 and a record low of 0.000 Unit in 18 Mar 2025. United States NBER-Based Recession Indicators from the Peak Through the Trough data remains active status in CEIC and is reported by Federal Reserve Bank of St. Louis. The data is categorized under Global Database’s United States – Table US.S079: NBER-Based Recession Indicators.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
United States FRB Recession Risk data was reported at 0.133 % in Feb 2025. This records an increase from the previous number of 0.121 % for Jan 2025. United States FRB Recession Risk data is updated monthly, averaging 0.194 % from Jan 1973 (Median) to Feb 2025, with 626 observations. The data reached an all-time high of 1.000 % in Oct 2008 and a record low of 0.022 % in Jul 2003. United States FRB Recession Risk data remains active status in CEIC and is reported by Federal Reserve Board. The data is categorized under Global Database’s United States – Table US.S078: FRB Recession Risk.
In June 2022, a public opinion poll found that the majority of Americans currently believe the United States is experiencing an economic recession. In that survey, 59 percent of respondents said that the U.S. is currently in recession and 23 percent said the opposite.
By November 2025, it is projected that there is a probability of 33.56 percent that the United States will fall into another economic recession. This reflects a significant decrease from the projection of the preceding month.