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.

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.

The 2020 recession did not follow the trend of previous recessions in the United States because only six months elapsed between the yield curve inversion and the 2020 recession. Over the last five decades, 12 months, on average, has elapsed between the initial yield curve inversion and the beginning of a recession in the United States. For instance, the yield curve inverted initially in January 2006, which was 22 months before the start of the 2008 recession. A yield curve inversion refers to the event where short-term Treasury bonds, such as one or three month bonds, have higher yields than longer term bonds, such as three or five year bonds. This is unusual, because long-term investments typically have higher yields than short-term ones in order to reward investors for taking on the extra risk of longer term investments. Monthly updates on the Treasury yield curve can be seen here.

Abstract (en): The US Social Security Disability Insurance (SSDI) program is designed to provide income support to workers who become unable to work because of a severe, long-lasting disability. In this study, we use administrative data to estimate the effect of labor market conditions, as measured by the unemployment rate, on the number of SSDI applications, the number and composition of initial allowances and denials, and the timing of applications relative to disability onset. We analyze the period of the Great Recession, and compare this period with business cycle effects over the past two decades, from 1992 through 2012.

Smoothed recession probabilities for the United States are obtained from a dynamic-factor markov-switching model applied to four monthly coincident variables: non-farm payroll employment, the index of industrial production, real personal income excluding transfer payments, and real manufacturing and trade sales. This model was originally developed in Chauvet, M., "An Economic Characterization of Business Cycle Dynamics with Factor Structure and Regime Switching," International Economic Review, 1998, 39, 969-996.

For additional details, including an analysis of the performance of this model for dating business cycles in real time, see: Chauvet, M. and J. Piger, ""http://pages.uoregon.edu/jpiger/research/published-papers/chauvet-and-piger_2008_jour.pdf">A Comparison of the Real-Time Performance of Business Cycle Dating Methods (https://pdfs.semanticscholar.org/f2ed/8fac87c0c82c3d85ca64ee9846658d8810fb.pdf?_ga=2.168797348.404457612.1561570817-1723670870.1561570817)," Journal of Business and Economic Statistics, 2008, 26, 42-49.

For additional details as to why this data revises, see FAQ 3 (http://pages.uoregon.edu/jpiger/us_recession_probs.htm).

During the period beginning roughly in the mid-1980s until the Global Financial Crisis (2007-2008), the U.S. economy experienced a time of relative economic calm, with low inflation and consistent GDP growth. Compared with the turbulent economic era which had preceded it in the 1970s and the early 1980s, the lack of extreme fluctuations in the business cycle led some commentators to suggest that macroeconomic issues such as high inflation, long-term unemployment and financial crises were a thing of the past. Indeed, the President of the American Economic Association, Professor Robert Lucas, famously proclaimed in 2003 that "central problem of depression prevention has been solved, for all practical purposes". Ben Bernanke, the future chairman of the Federal Reserve during the Global Financial Crisis (GFC) and 2022 Nobel Prize in Economics recipient, coined the term 'the Great Moderation' to describe this era of newfound economic confidence. The era came to an abrupt end with the outbreak of the GFC in the Summer of 2007, as the U.S. financial system began to crash due to a downturn in the real estate market.

Causes of the Great Moderation, and its downfall

A number of factors have been cited as contributing to the Great Moderation including central bank monetary policies, the shift from manufacturing to services in the economy, improvements in information technology and management practices, as well as reduced energy prices. The period coincided with the term of Fed chairman Alan Greenspan (1987-2006), famous for the 'Greenspan put', a policy which meant that the Fed would proactively address downturns in the stock market using its monetary policy tools. These economic factors came to prominence at the same time as the end of the Cold War (1947-1991), with the U.S. attaining a new level of hegemony in global politics, as its main geopolitical rival, the Soviet Union, no longer existed. During the Great Moderation, the U.S. experienced a recession twice, between July 1990 and March 1991, and again from March 2001 tom November 2001, however, these relatively short recessions did not knock the U.S. off its growth path. The build up of household and corporate debt over the early 2000s eventually led to the Global Financial Crisis, as the bursting of the U.S. housing bubble in 2007 reverberated across the financial system, with a subsequent credit freeze and mass defaults.

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)

This paper examines the association between the Great Recession and real assets among families with young children. Real assets such as homes and cars are key indicators of economic well-being that may be especially valuable to low-income families. Using longitudinal data from the Fragile Families and Child Wellbeing Study (N = 4,898), we investigate the association between the city unemployment rate and home and car ownership and how the relationship varies by family structure (married, cohabiting, and single parents) and by race/ethnicity (White, Black, and Hispanic mothers). Using mother fixed-effects models, we find that a one percentage point increase in the unemployment rate is associated with a -0.5 percentage point decline in the probability of home ownership and a -0.7 percentage point decline in the probability of car ownership. We also find that the recession was associated with lower levels of home ownership for cohabiting families and for Hispanic families, as well as lower car ownership among single mothers and among Black mothers, whereas no change was observed among married families or White households. Considering that homes and cars are the most important assets among middle and low-income households in the U.S., these results suggest that the rise in the unemployment rate during the Great Recession may have increased household asset inequality across family structures and race/ethnicities, limiting economic mobility, and exacerbating the cycle of poverty.

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 the first day of the period of the peak and ends on the last day of the period before the trough. For more options on recession shading, see the notes 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. A version of this time series represented using the midpoint method can be found at:

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

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/JPNREC

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. The peak method is used for this series.

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)

The Covid-19 pandemic saw growth fall by 2.2 percent, compared with an increase of 2.5 percent the year before. The last time the real GDP growth rates fell by a similar level was during the Great Recession in 2009, and the only other time since the Second World War where real GDP fell by more than one percent was in the early 1980s recession. The given records began following the Wall Street Crash in 1929, and GDP growth fluctuated greatly between the Great Depression and the 1950s, before growth became more consistent.

Abstract copyright UK Data Service and data collection copyright owner.

This is a qualitative data collection. To understand the processes and motivations behind changes in labour market behaviour during periods of economic recession, this research project recorded the experiences and views of couple-households exposed to job loss in the Great Recession. Conducted as part of a larger ESRC-funded quantitative project, qualitative interviews were carried out with a purposive sample derived from the Understanding Society Innovation Panel. (The Understanding Society Innovation Panel is an annual panel survey that collects a wide range of information about the economic and social circumstances of those living in 1500 households across Britain.) Using the wealth of longitudinal information in the Understanding Society Innovation Panel, a sampling frame of approximately 150 couple households was identified where someone had either lost their job or was working reduced hours in the period 2008 to 2011. A carefully selected sample of 17 households were followed up and in-depth interviews were conducted with the couple-member who had experienced job loss and, where possible, their partner. The selection process was designed to assemble a sample reflecting a diverse range of household and family profiles; namely, couples with and without children, older and younger children; the pre-retirement phase; a range of incomes; and labour market areas across England more and less affected by the recession. Wherever feasible, partners were interviewed separately to allow each participant the opportunity to express their personal views most freely. Overall this led to 30 interviews, each of about 45 minutes in length. Fieldwork took place between October 2012 and February 2013 and consent was obtained verbally. The research design incorporates the ability to link the interview transcripts to Understanding Society Innovation Panel survey data for future combined analysis of qualitative and quantitative material, subject to Special Licence.


Main Topics:

Topics covered in the in-depth interviews include: contextual details surrounding the job loss event, the extent to which job loss was anticipated, change and continuities in joint labour supply (including the division of domestic labour), consumption and expenditure practices, decision making processes and intra-household bargaining, job seeking behaviour, the use of social networks, outlook and expectations for the future.

The objective of this study is to explore the impact of working capital management on firms’ financial performance in China’s agri-food sector from 2006 to 2021. In addition, we analyze whether this impact is the same during the 2008 financial crisis and the 2020 COVID-19 crisis. Working capital management is measured by working capital investment policy (measured by current assets to total assets ratio), working capital financing policy (measured by current liabilities to total assets ratio), cash conversion cycle, and net working capital ratio. The results reveal that current assets to total assets ratio and net working capital ratio positively influence financial performance measured through return on assets (ROA), while current liabilities to total assets ratio and cash conversion cycle negatively influence ROA. We also find that the relationship between working capital management and financial performance is more affected during COVID-19 than in the 2008 financial crisis. The findings might provide important implications for company managers to make optimal working capital management practices, depending on the economic environment.

In June 2024, the European Central Bank (ECB) began reducing its fixed interest rate for the first time since 2016, implementing a series of cuts. The rate decreased from 4.5 percent to 3.15 percent by year-end: a 0.25 percentage point cut in June, followed by additional reductions in September, October, and December. The central bank implemented other cuts in early 2025, setting the rate at 2.4 percent in April 2025. This marked a significant shift from the previous rate hike cycle, which began in July 2022 when the ECB raised rates to 0.5 percent and subsequently increased them almost monthly, reaching 4.5 percent by December 2023 - the highest level since the 2007-2008 global financial crisis. How does this ensure liquidity? Banks typically hold only a fraction of their capital in cash, measured by metrics like the Tier 1 capital ratio. Since this ratio is low, banks prefer to allocate most of their capital to revenue-generating loans. When their cash reserves fall too low, banks borrow from the ECB to cover short-term liquidity needs. On the other hand, commercial banks can also deposit excess funds with the ECB at a lower interest rate. Reasons for fluctuations
The ECB’s primary mandate is to maintain price stability. The Euro area inflation rate is, in theory, the key indicator guiding the ECB's actions. When the fixed interest rate is lower, commercial banks are more likely to borrow from the ECB, increasing the money supply and, in turn, driving inflation higher. When inflation rises, the ECB increases the fixed interest rate, which slows borrowing and helps to reduce inflation.

The Federal Reserve's balance sheet has undergone significant changes since 2007, reflecting its response to major economic crises. From a modest *** trillion U.S. dollars at the end of 2007, it ballooned to approximately **** trillion U.S. dollars by May 2025. This dramatic expansion, particularly during the 2008 financial crisis and the COVID-19 pandemic - both of which resulted in negative annual GDP growth in the U.S. - showcases the Fed's crucial role in stabilizing the economy through expansionary monetary policies. Impact on inflation and interest rates The Fed's expansionary measures, while aimed at stimulating economic growth, have had notable effects on inflation and interest rates. Following the quantitative easing in 2020, inflation in the United States reached * percent in 2022, the highest since 1991. However, by *************, inflation had declined to *** percent. Concurrently, the Federal Reserve implemented a series of interest rate hikes, with the rate peaking at **** percent in ***********, before the first rate cut since ************** occurred in **************. Financial implications for the Federal Reserve The expansion of the Fed's balance sheet and subsequent interest rate hikes have had significant financial implications. In 2023, the Fed reported a negative net income of ***** billion U.S. dollars, a stark contrast to the ***** billion U.S. dollars profit in 2022. This unprecedented shift was primarily due to rapidly rising interest rates, which caused the Fed's interest expenses to soar to over *** billion U.S. dollars in 2023. Despite this, the Fed's net interest income on securities acquired through open market operations reached a record high of ****** billion U.S. dollars in the same year.

Shows the daily level of the federal funds rate back to 1954. The fed funds rate is the interest rate at which depository institutions (banks and credit unions) lend reserve balances to other depository institutions overnight, on an uncollateralized basis. The Federal Open Market Committee (FOMC) meets eight times a year to determine the federal funds target rate.

The objective of this study is to explore the impact of working capital management on firms’ financial performance in China’s agri-food sector from 2006 to 2021. In addition, we analyze whether this impact is the same during the 2008 financial crisis and the 2020 COVID-19 crisis. Working capital management is measured by working capital investment policy (measured by current assets to total assets ratio), working capital financing policy (measured by current liabilities to total assets ratio), cash conversion cycle, and net working capital ratio. The results reveal that current assets to total assets ratio and net working capital ratio positively influence financial performance measured through return on assets (ROA), while current liabilities to total assets ratio and cash conversion cycle negatively influence ROA. We also find that the relationship between working capital management and financial performance is more affected during COVID-19 than in the 2008 financial crisis. The findings might provide important implications for company managers to make optimal working capital management practices, depending on the economic environment.

The U.S. federal funds rate peaked in 2023 at its highest level since the 2007-08 financial crisis, reaching 5.33 percent by December 2023. A significant shift in monetary policy occurred in the second half of 2024, with the Federal Reserve implementing regular rate cuts. By December 2024, the rate had declined to 4.48 percent. What is a central bank rate? The federal funds rate determines the cost of overnight borrowing between banks, allowing them to maintain necessary cash reserves and ensure financial system liquidity. When this rate rises, banks become more inclined to hold rather than lend money, reducing the money supply. While this decreased lending slows economic activity, it helps control inflation by limiting the circulation of money in the economy. Historic perspective The federal funds rate historically follows cyclical patterns, falling during recessions and gradually rising during economic recoveries. Some central banks, notably the European Central Bank, went beyond traditional monetary policy by implementing both aggressive asset purchases and negative interest rates.

Graph and download economic data for Total Unemployed, Plus All Persons Marginally Attached to the Labor Force, Plus Total Employed Part Time for Economic Reasons, as a Percent of the Civilian Labor Force Plus All Persons Marginally Attached to the Labor Force (U-6) (U6RATE) from Jan 1994 to May 2025 about marginally attached, part-time, labor underutilization, workers, 16 years +, labor, household survey, unemployment, and USA.

In 1990, the unemployment rate of the United States stood at 5.6 percent. Since then there have been many significant fluctuations to this number - the 2008 financial crisis left millions of people without work, as did the COVID-19 pandemic. By the end of 2022 and throughout 2023, the unemployment rate came to 3.6 percent, the lowest rate seen for decades. However, 2024 saw an increase up to four percent. For monthly updates on unemployment in the United States visit either the monthly national unemployment rate here, or the monthly state unemployment rate here. Both are seasonally adjusted. UnemploymentUnemployment is defined as a situation when an employed person is laid off, fired or quits his work and is still actively looking for a job. Unemployment can be found even in the healthiest economies, and many economists consider an unemployment rate at or below five percent to mean there is 'full employment' within an economy. If former employed persons go back to school or leave the job to take care of children they are no longer part of the active labor force and therefore not counted among the unemployed. Unemployment can also be the effect of events that are not part of the normal dynamics of an economy. Layoffs can be the result of technological progress, for example when robots replace workers in automobile production. Sometimes unemployment is caused by job outsourcing, due to the fact that employers often search for cheap labor around the globe and not only domestically. In 2022, the tech sector in the U.S. experienced significant lay-offs amid growing economic uncertainty. In the fourth quarter of 2022, more than 70,000 workers were laid off, despite low unemployment nationwide. The unemployment rate in the United States varies from state to state. In 2021, California had the highest number of unemployed persons with 1.38 million out of work.

View data of the S&P 500, an index of the stocks of 500 leading companies in the US economy, which provides a gauge of the U.S. equity market.