Graph and download economic data for Real-time Sahm Rule Recession Indicator (SAHMREALTIME) from Dec 1959 to Jun 2025 about recession indicators, academic data, and USA.

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.

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 Jun 2025 about peak, trough, recession indicators, and USA.

This time series is an interpretation of Organisation of Economic Development (OECD) Composite Leading Indicators: Reference Turning Points and Component Series data, which can be found at http://www.oecd.org/std/leading-indicators/oecdcompositeleadingindicatorsreferenceturningpointsandcomponentseries.htm. The OECD identifies months of turning points without designating a date within the month that turning points occurred. The dummy variable adopts an arbitrary convention that the turning point occurred at a specific date within the month. The arbitrary convention does not reflect any judgment on this issue by the OECD. Our time series is composed of dummy variables that represent periods of expansion and recession. A value of 1 is a recessionary period, while a value of 0 is an expansionary period. For this time series, the recession begins on the 15th day of the month of the peak and ends on the 15th day of the month of the trough. This time series is a disaggregation of the monthly series. For more options on recession shading, see the note and links below.

The recession shading data that we provide initially comes from the source as a list of dates that are either an economic peak or trough. We interpret dates into recession shading data using one of three arbitrary methods. All of our recession shading data is available using all three interpretations. The period between a peak and trough is always shaded as a recession. The peak and trough are collectively extrema. Depending on the application, the extrema, both individually and collectively, may be included in the recession period in whole or in part. In situations where a portion of a period is included in the recession, the whole period is deemed to be included in the recession period.

The first interpretation, known as the midpoint method, is to show a recession from the midpoint of the peak through the midpoint of the trough for monthly and quarterly data. For daily data, the recession begins on the 15th of the month of the peak and ends on the 15th of the month of the trough. Daily data is a disaggregation of monthly data. For monthly and quarterly data, the entire peak and trough periods are included in the recession shading. This method shows the maximum number of periods as a recession for monthly and quarterly data. The Federal Reserve Bank of St. Louis uses this method in its own publications. The midpoint method is used for this series.

The second interpretation, known as the trough method, is to show a recession from the period following the peak through the trough (i.e. the peak is not included in the recession shading, but the trough is). For daily data, the recession begins on the first day of the first month following the peak and ends on the last day of the month of the trough. Daily data is a disaggregation of monthly data. The trough method is used when displaying data on FRED graphs. A version of this time series represented using the trough method can be found at:

https://fred.stlouisfed.org/series/CANRECD

The third interpretation, known as the peak method, is to show a recession from the period of the peak to the trough (i.e. the peak is included in the recession shading, but the trough is not). For daily data, the recession begins on the first day of the month of the peak and ends on the last day of the month preceding the trough. Daily data is a disaggregation of monthly data. A version of this time series represented using the peak method can be found at:

https://fred.stlouisfed.org/series/CANRECDP

The OECD CLI system is based on the "growth cycle" approach, where business cycles and turning points are measured and identified in the deviation-from-trend series. The main reference series used in the OECD CLI system for the majority of countries is industrial production (IIP) covering all industry sectors excluding construction. This series is used because of its cyclical sensitivity and monthly availability, while the broad based Gross Domestic Product (GDP) is used to supplement the IIP series for identification of the final reference turning points in the growth cycle.

Zones aggregates of the CLIs and the reference series are calculated as weighted averages of the corresponding zone member series (i.e. CLIs and IIPs).

Up to December 2008 the turning points chronologies shown for regional/zone area aggregates or individual countries are determined by the rules established by the National Bureau of Economic Research (NBER) in the United States, which have been formalized and incorporated in a computer routine (Bry and Boschan) and included in the Phase-Average Trend (PAT) de-trending procedure. Starting from December 2008 the turning point detection algorithm is decoupled from the de-trending procedure, and is a simplified version of the original Bry and Boschan routine. (The routine parses local minima and maxima in the cycle series and applies censor rules to guarantee alternating peaks and troughs, as well as phase and cycle length constraints.)

The components of the CLI are time series which exhibit leading relationship with the reference series (IIP) at turning points. Country CLIs are compiled by combining de-trended smoothed and normalized components. The component series for each country are selected based on various criteria such as economic significance; cyclical behavior; data quality; timeliness and availability.

OECD data should be cited as follows: OECD Composite Leading Indicators, "Composite Leading Indicators: Reference Turning Points and Component Series", http://www.oecd.org/std/leading-indicators/oecdcompositeleadingindicatorsreferenceturningpointsandcomponentseries.htm (Accessed on date)

We propose an optimal filter to transform the Conference Board Composite Leading Index (CLI) into recession probabilities in the US economy. We also analyse the CLI's accuracy at anticipating US output growth. We compare the predictive performance of linear, VAR extensions of smooth transition regression and switching regimes, probit, non-parametric models and conclude that a combination of the switching regimes and non-parametric forecasts is the best strategy at predicting both the NBER business cycle schedule and GDP growth. This confirms the usefulness of CLI, even in a real-time analysis.

Probability of Recession: United States data was reported at 0.995 % in Mar 2025. This records a decrease from the previous number of 1.031 % for Feb 2025. Probability of Recession: United States data is updated monthly, averaging 1.564 % from Jan 1980 (Median) to Mar 2025, with 543 observations. The data reached an all-time high of 87.972 % in May 2020 and a record low of 0.021 % in Jan 1980. Probability of Recession: United States data remains active status in CEIC and is reported by CEIC Data. The data is categorized under World Trend Plus’s CEIC Leading Indicator – Table US.S002: Probability of Recession.

Graph and download economic data for Leading Indicators OECD: Reference Series: Gross Domestic Product: Original Series for the Russian Federation (LORSGPORRUQ659S) from Q1 1996 to Q3 2021 about leading indicator, Russia, and GDP.

Probability of Recession: Euro Area data was reported at 1.506 % in Mar 2025. This records a decrease from the previous number of 1.828 % for Feb 2025. Probability of Recession: Euro Area data is updated monthly, averaging 5.278 % from Jan 1996 (Median) to Mar 2025, with 351 observations. The data reached an all-time high of 70.141 % in Mar 2009 and a record low of 0.016 % in Jul 2021. Probability of Recession: Euro Area data remains active status in CEIC and is reported by CEIC Data. The data is categorized under World Trend Plus’s CEIC Leading Indicator – Table EU.S002: Probability of Recession: Euro Area.

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.

Graph and download economic data for OECD based Recession Indicators for Sweden from the Peak through the Period preceding the Trough (DISCONTINUED) (SWERECDP) from 1960-02-01 to 2022-09-30 about peak, trough, Sweden, and recession indicators.

The Great Recession was a period of economic contraction which came in the wake of the Global Financial Crisis of 2007-2008. The recession was triggered by the collapse of the U.S. housing market and subsequent bankruptcies among Wall Street financial institutions, the most significant of which being the bankruptcy of Lehman Brothers in September 2008, the largest bankruptcy in U.S. history. These economic convulsions caused consumer confidence, measured by the Consumer Confidence Index (CCI), to drop sharply in 2007 and the beginning of 2008. How does the Consumer Confidence Index work? The CCI measures household's expectation of their future economic situation and, consequently, their likely future spending and savings decisions. A score of 100 in the index would indicate a neutral economic outlook, with consumers neither being optimistic nor pessimistic about the near future. Scores below 100 are then more pessimistic, while scores above 100 indicate optimism about the economy. Consumer confidence can have a self-fulfilling effect on the economy, as when consumers are pessimistic about the economy, they tend to save and postpone spending, contracting aggregate demand and causing the economy to slow down. Conversely, when consumers are optimistic and willing to spend, this can have a reinforcing effect as wages and employment may rise when consumers spend more. CCI and the Great Recession As the reality of the trouble which the U.S. financial sector was in set in over 2007, consumer confidence dropped sharply from being slightly positive, to being deeply pessimistic by the Summer of 2008. While confidence began to slowly rebound up until September 2008, with the panic caused by Lehman's bankruptcy and the freezing of new credit creation, the CCI plummeted once more, reaching its lowest point during the recession in February 2008. The U.S. government stepped in to prevent the bankruptcy of AIG in 2008, promising to do the same for any future possible failures in the financial system. This 'backstopping' policy, whereby the government assured that the economy would not be allowed to fall further into crisis, along with the Federal Reserve's unconventional monetary policies used to restart the economy, contributed to a rebound in consumer confidence in 2009 and 2010. In spite of this, consumers still remained pessimistic about the economy.

The Weekly Economic Index (WEI) of the United States exhibited notable fluctuations between January 2021 and June 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.

Graph and download economic data for Dates of U.S. recessions as inferred by GDP-based recession indicator (JHDUSRGDPBR) from Q4 1967 to Q4 2024 about recession indicators, GDP, and USA.

From the Summer of 2007 until the end of 2009 (at least), the world was gripped by a series of economic crises commonly known as the Global Financial Crisis (2007-2008) and the Great Recession (2008-2009). The financial crisis was triggered by the collapse of the U.S. housing market, which caused panic on Wall Street, the center of global finance in New York. Due to the outsized nature of the U.S. economy compared to other countries and particularly the centrality of U.S. finance for the world economy, the crisis spread quickly to other countries, affecting most regions across the globe. By 2009, global GDP growth was in negative territory, with international credit markets frozen, international trade contracting, and tens of millions of workers being made unemployed.

Global similarities, global differences

Since the 1980s, the world economy had entered a period of integration and globalization. This process particularly accelerated after the collapse of the Soviet Union ended the Cold War (1947-1991). This was the period of the 'Washington Consensus', whereby the U.S. and international institutions such as the World Bank and IMF promoted policies of economic liberalization across the globe. This increasing interdependence and openness to the global economy meant that when the crisis hit in 2007, many countries experienced the same issues. This is particularly evident in the synchronization of the recessions in the most advanced economies of the G7. Nevertheless, the aggregate global GDP number masks the important regional differences which occurred during the recession. While the more advanced economies of North America, Western Europe, and Japan were all hit hard, along with countries who are reliant on them for trade or finance, large emerging economies such as India and China bucked this trend. In particular, China's huge fiscal stimulus in 2008-2009 likely did much to prevent the global economy from sliding further into a depression. In 2009, while the United States' GDP sank to -2.6 percent, China's GDP, as reported by national authorities, was almost 10 percent.

Is the US headed into a recession? IBISWorld takes a look into key recession indicators by individual US industries.

This paper proposes a model to predict recessions that accounts for non-linearity and a structural break when the spread between long- and short-term interest rates is the leading indicator. Estimation and model selection procedures allow us to estimate and identify time-varying non-linearity in a VAR. The structural break threshold VAR (SBTVAR) predicts better the timing of recessions than models with constant threshold or with only a break. Using real-time data, the SBTVAR with spread as leading indicator is able to anticipate correctly the timing of the 2001 recession.

We use the yield curve to predict future GDP growth and recession probabilities. The spread between short- and long-term rates typically correlates with economic growth. Predications are calculated using a model developed by the Federal Reserve Bank of Cleveland. Released monthly.

Graph and download economic data for OECD based Recession Indicators for OECD and Non-member Economies from the Peak through the Trough (DISCONTINUED) (OECDNMERECDM) from 1960-02-01 to 2022-02-28 about OECD and Non-OECD, peak, trough, and recession indicators.

We consider tests of forecast encompassing for probability forecasts, for both quadratic and logarithmic scoring rules. We propose test statistics for the null of forecast encompassing, present the limiting distributions of the test statistics, and investigate the impact of estimating the forecasting models' parameters on these distributions. The small-sample performance is investigated, in terms of small numbers of forecasts and model estimation sample sizes. We show the usefulness of the tests for the evaluation of recession probability forecasts from logit models with different leading indicators as explanatory variables, and for evaluating survey-based probability forecasts.

The Global Financial Crisis of 2008-09 was a period of severe macroeconomic instability for the United States and the global economy more generally. The crisis was precipitated by the collapse of a number of financial institutions who were deeply involved in the U.S. mortgage market and associated credit markets. Beginning in the Summer of 2007, a number of banks began to report issues with increasing mortgage delinquencies and the problem of not being able to accurately price derivatives contracts which were based on bundles of these U.S. residential mortgages. By the end of 2008, U.S. financial institutions had begun to fail due to their exposure to the housing market, leading to one of the deepest recessions in the history of the United States and to extensive government bailouts of the financial sector.

Subprime and the collapse of the U.S. mortgage market

The early 2000s had seen explosive growth in the U.S. mortgage market, as credit became cheaper due to the Federal Reserve's decision to lower interest rates in the aftermath of the 2001 'Dot Com' Crash, as well as because of the increasing globalization of financial flows which directed funds into U.S. financial markets. Lower mortgage rates gave incentive to financial institutions to begin lending to riskier borrowers, using so-called 'subprime' loans. These were loans to borrowers with poor credit scores, who would not have met the requirements for a conventional mortgage loan. In order to hedge against the risk of these riskier loans, financial institutions began to use complex financial instruments known as derivatives, which bundled mortgage loans together and allowed the risk of default to be sold on to willing investors. This practice was supposed to remove the risk from these loans, by effectively allowing credit institutions to buy insurance against delinquencies. Due to the fraudulent practices of credit ratings agencies, however, the price of these contacts did not reflect the real risk of the loans involved. As the reality of the inability of the borrowers to repay began to kick in during 2007, the financial markets which traded these derivatives came under increasing stress and eventually led to a 'sudden stop' in trading and credit intermediation during 2008.

Market Panic and The Great Recession

As borrowers failed to make repayments, this had a knock-on effect among financial institutions who were highly leveraged with financial instruments based on the mortgage market. Lehman Brothers, one of the world's largest investment banks, failed on September 15th 2008, causing widespread panic in financial markets. Due to the fear of an unprecedented collapse in the financial sector which would have untold consequences for the wider economy, the U.S. government and central bank, The Fed, intervened the following day to bailout the United States' largest insurance company, AIG, and to backstop financial markets. The crisis prompted a deep recession, known colloquially as The Great Recession, drawing parallels between this period and The Great Depression. The collapse of credit intermediation in the economy lead to further issues in the real economy, as business were increasingly unable to pay back loans and were forced to lay off staff, driving unemployment to a high of almost 10 percent in 2010. While there has been criticism of the U.S. government's actions to bailout the financial institutions involved, the actions of the government and the Fed are seen by many as having prevented the crisis from spiraling into a depression of the magnitude of The Great Depression.