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 Q1 2025 about recession indicators, GDP, and USA.

This dataset includes various economic indicators such as stock market performance, inflation rates, GDP, interest rates, employment data, and housing index, all of which are crucial for understanding the state of the economy. By analysing this dataset, one can gain insights into the causes and effects of past recessions in the US, which can inform investment decisions and policy-making.

There are 20 columns and 343 rows spanning 1990-04 to 2022-10

The columns are:

1. Price: Price column refers to the S&P 500 lot price over the years. The S&P 500 is a stock market index that measures the performance of 500 large companies listed on stock exchanges in the United States. This variable represents the value of the S&P 500 index from 1980 to present. Industrial Production: This variable measures the output of industrial establishments in the manufacturing, mining, and utilities sectors. It reflects the overall health of the manufacturing industry, which is a key component of the US economy.

2. INDPRO: Industrial production measures the output of the manufacturing, mining, and utility sectors of the economy. It provides insights into the overall health of the economy, as a decline in industrial production can indicate a slowdown in economic activity. This data can be used by policymakers and investors to assess the state of the economy and make informed decisions.

3. CPI: CPI stands for Consumer Price Index, which measures the change in the prices of a basket of goods and services that consumers purchase. CPI inflation represents the rate at which the prices of goods and services in the economy are increasing.

4. Treasure Bill rate (3 month to 30 Years): Treasury bills (T-bills) are short-term debt securities issued by the US government. This variable represents the interest rates on T-bills with maturities ranging from 3 months to 30 years. It reflects the cost of borrowing money for the government and provides an indication of the overall level of interest rates in the economy.

5. GDP: GDP stands for Gross Domestic Product, which is the value of all goods and services produced in a country. This dataset is taking into account only the Nominal GDP values. Nominal GDP represents the total value of goods and services produced in the US economy without accounting for inflation.

6. Rate: The Federal Funds Rate is the interest rate at which depository institutions lend reserve balances to other depository institutions overnight. It is set by the Federal Reserve and is used as a tool to regulate the money supply in the economy.

7. BBK_Index: The BBKI are maintained and produced by the Indiana Business Research Center at the Kelley School of Business at Indiana University. The BBK Coincident and Leading Indexes and Monthly GDP Growth for the U.S. are constructed from a collapsed dynamic factor analysis of a panel of 490 monthly measures of real economic activity and quarterly real GDP growth. The BBK Leading Index is the leading subcomponent of the cycle measured in standard deviation units from trend real GDP growth.

8. Housing Index: This variable represents the value of the housing market in the US. It is calculated based on the prices of homes sold in the market and provides an indication of the overall health of the housing market.

9. Recession binary column: This variable is a binary indicator that takes a value of 1 when the US economy is in a recession and 0 otherwise. It is based on the official business cycle dates provided by the National Bureau of Economic Research.

Graph and download economic data for Equity Market Volatility Tracker: Financial Crises (EMVFINCRISES) from Jan 1985 to Oct 2025 about volatility, uncertainty, equity, financial, 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.

The statisic shows the concern among Americans around the impact of the European financial crisis on the United States economy. According to the source, 15 percent of those polled stated that they were 'not too concerned' about the impact of the European financial crisis on the U.S. economy.

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

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.

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

Abstract The paper aims to analyze the wide range of unconventional monetary policies adopted in the U.S. since the 2007-2008 financial crises, focusing on conceptual aspects, the implementation of different programs and measures adopted by FED, and their effectiveness. It is argued that the use of credit and quasi-debt policies had significant effects on the financial conditions and on a set of macroeconomic variables in the US, such as output and employment. This result raises questions about the effectiveness of conventional monetary policy and the forward guidance, both of which were key elements in the New Macroeconomics Consensus view that preceded the 2007-2008 financial crisis.

U.S. Economic and Financial Dataset

Dataset Description

This dataset combines historical U.S. economic and financial indicators, spanning the last 50 years, to facilitate time series analysis and uncover patterns in macroeconomic trends. It is designed for exploring relationships between interest rates, inflation, economic growth, stock market performance, and industrial production.

Key Features

• Frequency: Monthly
• Time Period: Last 50 years from Nov-24
• Sources:
  • Federal Reserve Economic Data (FRED)
  • Yahoo Finance

Dataset Feature Description

1. Interest Rate (Interest_Rate):

   • The effective federal funds rate, representing the interest rate at which depository institutions trade federal funds overnight.

2. Inflation (Inflation):

   • The Consumer Price Index for All Urban Consumers, an indicator of inflation trends.

3. GDP (GDP):

   • Real GDP measures the inflation-adjusted value of goods and services produced in the U.S.

4. Unemployment Rate (Unemployment):

   • The percentage of the labor force that is unemployed and actively seeking work.

5. Stock Market Performance (S&P500):

   • Monthly average of the adjusted close price, representing stock market trends.

6. Industrial Production (Ind_Prod):

   • A measure of real output in the industrial sector, including manufacturing, mining, and utilities.

Dataset Statistics

1. Total Entries: 599
2. Columns: 6
3. Memory usage: 37.54 kB
4. Data types: float64

Feature Overview

• Columns:
  • Interest_Rate: Monthly Federal Funds Rate (%)
  • Inflation: CPI (All Urban Consumers, Index)
  • GDP: Real GDP (Billions of Chained 2012 Dollars)
  • Unemployment: Unemployment Rate (%)
  • Ind_Prod: Industrial Production Index (2017=100)
  • S&P500: Monthly Average of S&P 500 Adjusted Close Prices

Executive Summary

This project explores the interconnected dynamics of key macroeconomic indicators and financial market trends over the past 50 years, leveraging data from the Federal Reserve Economic Data (FRED) and Yahoo Finance. The dataset integrates critical variables such as the Federal Funds Rate, Inflation (CPI), Real GDP, Unemployment Rate, Industrial Production, and the S&P 500 Index, providing a holistic view of the U.S. economy and financial markets.

The analysis focuses on uncovering relationships between these variables through time-series visualization, correlation analysis, and trend decomposition. Key findings are included in the Insights section. This project serves as a robust resource for understanding long-term economic trends, policy impacts, and market behavior. It is particularly valuable for students, researchers, policymakers, and financial analysts seeking to connect macroeconomic theory with real-world data.

Potential Use Cases

• Economic Analysis: Examine relationships between interest rates, inflation, GDP, and unemployment.
• Stock Market Prediction: Study how macroeconomic indicators influence stock market trends.
• Time Series Modeling: Perform ARIMA, VAR, or other models to forecast economic trends.
• Cyclic Pattern Analysis: Identify how economic shocks and recoveries impact key indicators.

Snap of Power Analysis

https://github.com/user-attachments/assets/1b40e0ca-7d2e-4fbc-8cfd-df3f09e4fdb8">

To ensure sufficient power, the dataset covers last 50 years of monthly data i.e., around 600 entries.

Key Insights derived through EDA, time-series visualization, correlation analysis, and trend decomposition

• Interest Rate and Inflation Dynamics: The interest Rate and inflation exhibit an inverse relationship, especially during periods of aggressive monetary tightening by the Federal Reserve.
• Economic Growth and Market Performance: GDP growth and the S&P 500 Index show a positive correlation, reflecting how market performance often aligns with overall economic health.
• Labor Market and Industrial Output: Unemployment and industrial production demonstrate a strong inverse relationship. Higher industrial output is typically associated with lower unemployment
• Market Behavior During Economic Shocks: The S&P 500 experienced sharp declines during significant crises, such as the 2008 financial crash and the COVID-19 pandemic in 2020. These events also triggered increased unemployment and contractions in GDP, highlighting the interplay between markets and the broader economy.
• Correlation Highlights: S&P 500 and GDP have a strong positive correlation. Interest rates negatively correlate with GDP and inflation, reflecting monetary policy impacts. Unemployment is negatively correlated with industrial production but positively correlated with interest rates.

Link to GitHub Repo

https:/...

Measures of regional economic sentiment, extracted from the Beige Book using natural language processing methods, consistently delivered reliable real-time forecasts of US recessions from the mid-1980s through the COVID-19 pandemic recession. Since then, recession risk probabilities have been choppy, with several false alarms. We attribute this unreliability to a post-2021 disconnect between measures of economic activity and the sentiment of business and community leaders.

View monthly updates and historical trends for US Recession Probability. from United States. Source: Federal Reserve Bank of New York. Track economic data…

Do international lenders of last resort create financial instability by generating moral hazard? The evidence is thin and plagued with measurement error. We use the number of American troops hosted by third countries to measure the strength of American commitment to ensuring the countries’ economic health. We test several hypotheses against a dataset covering about sixty-eight countries between 1960 and 2009. Using evidence from fixed-effects and instrumental-variable models, we find that increasing the number of US troops by one standard deviation above the mean raises the probability of a financial crisis in the host country by up to 13 percentage points. We also investigate the channels through which moral hazard materializes. Countries with more US troops conduct more expansionary fiscal and monetary policies, implement riskier financial regulations, and receive more capital, especially from US banks. While many scholars of international relations view the American overseas military presence as a source of stability, we identify an underexplored mechanism by which it generates instability.

We examine the evolution of real per capita GDP around 100 systemic banking crises. Part of the costs of these crises owes to the protracted nature of recovery. On average, it takes about 8 years to reach the pre-crisis level of income; the median is about 6.5 years. Five to six years after the onset of crisis, only Germany and the United States (out of 12 systemic cases) have reached their 2007-2008 peaks in real income. Forty-five percent of the episodes recorded double dips. Post-war business cycles are not the relevant comparator for the recent crises in advanced economies.

The Weekly Economic Index (WEI) of the United States exhibited notable fluctuations between January 2021 and November 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, culminating in a value of **** percent as of November 1, 2025. 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.

Countries become more politically polarized and fractionalized following financial crises, reducing the likelihood of major financial reforms precisely when they might have especially large benefits. The evidence from a large sample of countries provides strong support for the hypotheses that following a financial crisis, voters become more ideologically extreme and ruling coalitions become weaker, independently of whether they were initially in power. The evidence that increased polarization and weaker governments reduce the chances of financial reform and that financial crises lead to legislative gridlock and anemic reform is less clear-cut. The US debt overhang resolution is discussed as an illustration.

United States NBER: Recorded Recession data was reported at 0.000 Unit in Oct 2018. This stayed constant from the previous number of 0.000 Unit for Sep 2018. United States NBER: Recorded Recession data is updated monthly, averaging 0.000 Unit from Jan 1959 (Median) to Oct 2018, with 718 observations. The data reached an all-time high of 1.000 Unit in Jun 2009 and a record low of 0.000 Unit in Oct 2018. United States NBER: Recorded Recession 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. An interpretation of US Business Cycle Expansions and Contractions data provided by The National Bureau of Economic Research (NBER). A value of 1 is a recessionary period, while a value of 0 is an expansionary period.

This file contains the data and code for the publication "The Federal Reserve's Response to the Global Financial Crisis and Its Long-Term Impact: An Interrupted Time-Series Natural Experimental Analysis" by A. C. Kamkoum, 2023.