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

The series assigns dates to U.S. recessions based on a mathematical model of the way that recessions differ from expansions. Whereas the NBER business cycle dates are based on a subjective assessment of a variety of indicators, the dates here are entirely mechanical and are calculated solely from historically reported GDP data. Whenever the GDP-based recession indicator index rises above 67%, the economy is determined to be in a recession. The date that the recession is determined to have begun is the first quarter prior to that date for which the inference from the mathematical model using all data available at that date would have been above 50%. The next time the GDP-based recession indicator index falls below 33%, the recession is determined to be over, and the last quarter of the recession is the first quarter for which the inference from the mathematical model using all available data at that date would have been below 50%.

For more information about this series visit http://econbrowser.com/recession-index.

Graph and download economic data for GDP-Based Recession Indicator Index (JHGDPBRINDX) from Q4 1967 to Q4 2024 about recession indicators, percent, GDP, and indexes.

Content

More details about each file are in the individual file descriptions.

Context

This is a dataset from the Federal Reserve Bank of St. Louis hosted by the Federal Reserve Economic Database (FRED). FRED has a data platform found here and they update their information according to the frequency that the data updates. Explore the Federal Reserve Bank of St. Louis using Kaggle and all of the data sources available through the St. Louis Fed organization page!

• Update Frequency: This dataset is updated daily.

Acknowledgements

This dataset is maintained using FRED's API and Kaggle's API.

Cover photo by Eddy Billard on Unsplash
Unsplash Images are distributed under a unique Unsplash License.

December. Hope Waddell Old Students’ Association (HWOSA) Annual Conference, Uyo. Participation

This time series is an interpretation of US Business Cycle Expansions and Contractions data provided by The National Bureau of Economic Research (http://www.nber.org/cycles/cyclesmain.html) (NBER). Our time series is composed of dummy variables that represent periods of expansion and recession. The NBER identifies months and quarters of turning points without designating a date within the period that turning points occurred. The dummy variable adopts an arbitrary convention that the turning point occurred at a specific date within the period. The arbitrary convention does not reflect any judgment on this issue by the NBER's Business Cycle Dating Committee. 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 following a peak and ends on the last day of the period of 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. One version of this time series is represented using the midpoint method (https://fred.stlouisfed.org/series/USRECM) 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. The trough method is used for this series.

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. Here is an example of this time series represented using the peak method (https://fred.stlouisfed.org/series/USRECP).

The data and statistical code deposited here may be used to replicate the findings and tables in Nandi A, Charters TJ, Strumpf EC, Heymann J, Harper S. Economic conditions and health behaviours during the Great Recession. J Epidemiol Community Health 2013;67:12 1038-1046.

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 Fiscal policy played a leading role in the debate on the trajectory of the Brazilian economy in the first half of 2010 to explain the economic slowdown and subsequent recession, both in orthodox and heterodox contributions. Orthodox economics points to uncontrolled public spending as being responsible for the fiscal deterioration, which would have led to worsening agents' expectations and falling investments. Heterodox economics, in a roughly opposite interpretation, points to an inflection of fiscal policy that, reducing spending, particularly investment, at the beginning of the decade, would have compromised the policy-inducing capacity in a demand-led growth model. This article aims to empirically evaluate these explanations. In addition to a descriptive analysis of the data, we propose a vector autoregression (VAR) model to examine how the fiscal policy elements pointed out by each of the perspectives discussed here have affected economic growth. In particular, we aim to investigate whether they are able to explain the downturn and the recession in the period analyzed. The results indicate, contrarily to the orthodox view, that spending did not skyrocket compared to previous governments, and that movements in output tend to precede changes in the fiscal outcome. They also point to the importance of public investment in determining the pace of activity, confirming a central element of the heterodox approach. However, by revealing that up to 2014 public spending continued to grow, indicates the insufficiency of the heterodox thesis to explain the slowdown in previous years and the depth of the subsequent recession. Given this, we present additional explanatory elements to understand the period.

Graph and download economic data for Sahm Rule Recession Indicator (SAHMCURRENT) from Mar 1949 to Jun 2025 about recession indicators, academic data, and USA.

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.

Prior to the 2020 recession, the yield curve was only inverted for 141 days, which was much shorter than the average 248 days preceding the previous five U.S. recessions. For instance, the yield curve was inverted for 235 days between the inversion in January 2006 and the start of the 2007-2009 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.

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 map represents the year(s) which had the most growth in GDP per state in the USA. This is shown by representing the predominant rate of growth between any two years from 1997 to 2016. The map is anchored around the 2008 recession, so that years of predominant growth BEFORE 2008 are in shades of green, and years of predominant growth AFTER 2008 are in shades of blue. The darkest greens had peaks in growth farther in the past, and the darkest shade of blue had the most recent peak in growth.Data is from the US Bureau of Economic Analysis and was downloaded from here. The state boundaries are generalized 2010 state boundaries from the Census Bureau's 2010 MAF/TIGER database. Note-- NAICS Industry detail is based on the 2007 North American Industry Classification System (NAICS).

The statistic shows the gross domestic product (GDP) of the United States from 1987 to 2024, with projections up until 2030. The gross domestic product of the United States in 2024 amounted to around 29.18 trillion U.S. dollars. The United States and the economy The United States’ economy is by far the largest in the world; a status which can be determined by several key factors, one being gross domestic product: A look at the GDP of the main industrialized and emerging countries shows a significant difference between US GDP and the GDP of China, the runner-up in the ranking, as well as the followers Japan, Germany and France. Interestingly, it is assumed that China will have surpassed the States in terms of GDP by 2030, but for now, the United States is among the leading countries in almost all other relevant rankings and statistics, trade and employment for example. See the U.S. GDP growth rate here. Just like in other countries, the American economy suffered a severe setback when the economic crisis occurred in 2008. The American economy entered a recession caused by the collapsing real estate market and increasing unemployment. Despite this, the standard of living is considered quite high; life expectancy in the United States has been continually increasing slightly over the past decade, the unemployment rate in the United States has been steadily recovering and decreasing since the crisis, and the Big Mac Index, which represents the global prices for a Big Mac, a popular indicator for the purchasing power of an economy, shows that the United States’ purchasing power in particular is only slightly lower than that of the euro area.

Recent studies have reported beneficial carryover effects of juvenile development that predict interspecific survival differences at independence. Yet, traits relating to body size (i.e. morphological traits) have proven to be unreliable predictors of juvenile survival within species. Exploring individual variation of growth trajectories and how they covary with physiology could reveal species-specific developmental modes which have implications for our assessments of juvenile quality. Here, we investigated morphological development of European starlings (Sturnus vulgaris) approaching fledging in relation to three components of physiological condition at independence: aerobic capacity, energy state and oxidative status. We found evidence of flexible mass and wing growth which independently covaried with fledgling energy state and aerobic capacity, respectively. By comparison, tarsus and wing length at fledging were unrelated to any physiological trait, while mass was positively associated with principal component scores that comprised aerobic capacity and energy state. Thus, flexible growth trajectories were consistent with ‘developmental plasticity’: adaptive pre-fledging mass recession and compensatory wing growth, which seemingly came at a physiological cost, while fledgling body mass positively reflected overall physiological condition. This highlights how patterns of growth and absolute size may differently reflect fledgling physiology, potentially leading to variable relationships between morphological traits and juvenile fitness.

In 2020, global gross domestic product declined by 6.7 percent as a result of the coronavirus (COVID-19) pandemic outbreak. In Latin America, overall GDP loss amounted to 8.5 percent.

This map portrays the change in Gross Domestic Product (GDP) by state before and after the 2008 USA recession. This is shown by comparing the percent change of GDP from 2000-2008 and the percent change of GDP from 2008-2016. The size of the circles represents the percent change over time. Blue circles represent the growth rate BEFORE 2008Purple circles represent the growth rate AFTER 2008The pop-up is configured to provide a comparison of the two rates.Notice which states had a significant drop in growth, while other states had minimal difference. Data is from the US Bureau of Economic Analysis and was downloaded from here. The state boundaries are generalized 2010 state boundaries from the Census Bureau's 2010 MAF/TIGER database. Note-- NAICS Industry detail is based on the 2007 North American Industry Classification System (NAICS).