50 years+ of historical inflaction, interest and unemployment rates by country

data source: https://data.worldbank.org cover image credit: https://www.pexels.com/photo/one-dollar-bill-3943739/

The Volcker Shock was a period of historically high interest rates precipitated by Federal Reserve Chairperson Paul Volcker's decision to raise the central bank's key interest rate, the Fed funds effective rate, during the first three years of his term. Volcker was appointed chairperson of the Fed in August 1979 by President Jimmy Carter, as replacement for William Miller, who Carter had made his treasury secretary. Volcker was one of the most hawkish (supportive of tighter monetary policy to stem inflation) members of the Federal Reserve's committee, and quickly set about changing the course of monetary policy in the U.S. in order to quell inflation. The Volcker Shock is remembered for bringing an end to over a decade of high inflation in the United States, prompting a deep recession and high unemployment, and for spurring on debt defaults among developing countries in Latin America who had borrowed in U.S. dollars.

Monetary tightening and the recessions of the early '80s

Beginning in October 1979, Volcker's Fed tightened monetary policy by raising interest rates. This decision had the effect of depressing demand and slowing down the U.S. economy, as credit became more expensive for households and businesses. The Fed funds rate, the key overnight rate at which banks lend their excess reserves to each other, rose as high as 17.6 percent in early 1980. The rate was allowed to fall back below 10 percent following this first peak, however, due to worries that inflation was not falling fast enough, a second cycle of monetary tightening was embarked upon starting in August of 1980. The rate would reach its all-time peak in June of 1981, at 19.1 percent. The second recession sparked by these hikes was far deeper than the 1980 recession, with unemployment peaking at 10.8 percent in December 1980, the highest level since The Great Depression. This recession would drive inflation to a low point during Volcker's terms of 2.5 percent in August 1983.

The legacy of the Volcker Shock

By the end of Volcker's terms as Fed Chair, inflation was at a manageable rate of around four percent, while unemployment had fallen under six percent, as the economy grew and business confidence returned. While supporters of Volcker's actions point to these numbers as proof of the efficacy of his actions, critics have claimed that there were less harmful ways that inflation could have been brought under control. The recessions of the early 1980s are cited as accelerating deindustrialization in the U.S., as manufacturing jobs lost in 'rust belt' states such as Michigan, Ohio, and Pennsylvania never returned during the years of recovery. The Volcker Shock was also a driving factor behind the Latin American debt crises of the 1980s, as governments in the region defaulted on debts which they had incurred in U.S. dollars. Debates about the validity of using interest rate hikes to get inflation under control have recently re-emerged due to the inflationary pressures facing the U.S. following the Coronavirus pandemic and the Federal Reserve's subsequent decision to embark on a course of monetary tightening.

Unemployment Rate in the United States increased to 4.40 percent in September from 4.30 percent in August of 2025. This dataset provides the latest reported value for - United States Unemployment Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Graph and download economic data for Noncyclical Rate of Unemployment (NROU) from Q1 1949 to Q4 2035 about NAIRU, projection, long-term, unemployment, rate, and USA.

Context

The Federal Reserve sets interest rates to promote conditions that achieve the mandate set by the Congress — high employment, low and stable inflation, sustainable economic growth, and moderate long-term interest rates. Interest rates set by the Fed directly influence the cost of borrowing money. Lower interest rates encourage more people to obtain a mortgage for a new home or to borrow money for an automobile or for home improvement. Lower rates encourage businesses to borrow funds to invest in expansion such as purchasing new equipment, updating plants, or hiring more workers. Higher interest rates restrain such borrowing by consumers and businesses.

Content

This dataset includes data on the economic conditions in the United States on a monthly basis since 1954. The federal funds rate is the interest rate at which depository institutions trade federal funds (balances held at Federal Reserve Banks) with each other overnight. The rate that the borrowing institution pays to the lending institution is determined between the two banks; the weighted average rate for all of these types of negotiations is called the effective federal funds rate. The effective federal funds rate is determined by the market but is influenced by the Federal Reserve through open market operations to reach the federal funds rate target. The Federal Open Market Committee (FOMC) meets eight times a year to determine the federal funds target rate; the target rate transitioned to a target range with an upper and lower limit in December 2008. The real gross domestic product is calculated as the seasonally adjusted quarterly rate of change in the gross domestic product based on chained 2009 dollars. The unemployment rate represents the number of unemployed as a seasonally adjusted percentage of the labor force. The inflation rate reflects the monthly change in the Consumer Price Index of products excluding food and energy.

Acknowledgements

The interest rate data was published by the Federal Reserve Bank of St. Louis' economic data portal. The gross domestic product data was provided by the US Bureau of Economic Analysis; the unemployment and consumer price index data was provided by the US Bureau of Labor Statistics.

Inspiration

How does economic growth, unemployment, and inflation impact the Federal Reserve's interest rates decisions? How has the interest rate policy changed over time? Can you predict the Federal Reserve's next decision? Will the target range set in March 2017 be increased, decreased, or remain the same?

In 2025, it was estimated that over 163 million Americans were in some form of employment, while 4.16 percent of the total workforce was unemployed. This was the lowest unemployment rate since the 1950s, although these figures are expected to rise in 2023 and beyond. 1980s-2010s Since the 1980s, the total United States labor force has generally risen as the population has grown, however, the annual average unemployment rate has fluctuated significantly, usually increasing in times of crisis, before falling more slowly during periods of recovery and economic stability. For example, unemployment peaked at 9.7 percent during the early 1980s recession, which was largely caused by the ripple effects of the Iranian Revolution on global oil prices and inflation. Other notable spikes came during the early 1990s; again, largely due to inflation caused by another oil shock, and during the early 2000s recession. The Great Recession then saw the U.S. unemployment rate soar to 9.6 percent, following the collapse of the U.S. housing market and its impact on the banking sector, and it was not until 2016 that unemployment returned to pre-recession levels. 2020s 2019 had marked a decade-long low in unemployment, before the economic impact of the Covid-19 pandemic saw the sharpest year-on-year increase in unemployment since the Great Depression, and the total number of workers fell by almost 10 million people. Despite the continuation of the pandemic in the years that followed, alongside the associated supply-chain issues and onset of the inflation crisis, unemployment reached just 3.67 percent in 2022 - current projections are for this figure to rise in 2023 and the years that follow, although these forecasts are subject to change if recent years are anything to go by.

CSI: Expected Inflation: Next 5 Yrs data was reported at 2.400 % in Jul 2018. This records a decrease from the previous number of 2.600 % for Jun 2018. CSI: Expected Inflation: Next 5 Yrs data is updated monthly, averaging 2.900 % from Feb 1979 (Median) to Jul 2018, with 382 observations. The data reached an all-time high of 9.700 % in Feb 1980 and a record low of 2.300 % in Dec 2016. CSI: Expected Inflation: Next 5 Yrs data remains active status in CEIC and is reported by University of Michigan. The data is categorized under Global Database’s USA – Table US.H030: Consumer Sentiment Index: Unemployment, Interest Rates, Prices and Government Expectations. The questions were: 'What about the outlook for prices over the next 5 to 10 years? Do you think prices will be higher, to go up, on the average, during the next 12 months?' and 'By about what percent per year do you expect prices to go up or down, on the average, during the next 5 to 10 years?'

Description:

This dataset provides key economic indicators from various countries between 2010 and 2023. The dataset includes monthly data on inflation rates, GDP growth rates, unemployment rates, interest rates, and stock market index values. The data has been sourced from reputable global financial institutions and is suitable for economic analysis, machine learning models, and forecasting economic trends.

Data Sources:

The data has been generated to simulate real-world economic conditions, mimicking information from trusted sources like: - World Bank for GDP growth and inflation data - International Monetary Fund (IMF) for macroeconomic data - OECD for labor market statistics - National Stock Exchanges for stock market index values

Columns:

1. Date: The specific date (in Year/Month/Day format) representing when the data was collected.
2. Country: The country the data pertains to (e.g., USA, Germany, Japan).
3. Inflation Rate (%): The rate of inflation for that country, showing how fast prices for goods and services are increasing.
4. GDP Growth Rate (%): The percentage growth of the country’s Gross Domestic Product (GDP), indicating economic expansion or contraction.
5. Unemployment Rate (%): The percentage of the working-age population that is unemployed.
6. Interest Rate (%): The central bank's interest rate, used to control inflation and influence the economy.
7. Stock Index Value: The value of the country’s main stock market index, reflecting the performance of the stock market.

Potential Uses: - Economic Analysis: Researchers and analysts can use this dataset to study trends in inflation, GDP growth, unemployment, and other economic factors. - Machine Learning: This dataset can be used to train models for predicting economic trends or market performance. Financial Forecasting: Investors and economists can leverage this data for forecasting market movements based on economic conditions. - Comparative Studies: The dataset allows comparisons across countries and regions, offering insights into global economic performance.

CSI: Expected Inflation: Next 5 Yrs: Down data was reported at 4.000 % in May 2018. This records an increase from the previous number of 3.000 % for Apr 2018. CSI: Expected Inflation: Next 5 Yrs: Down data is updated monthly, averaging 3.000 % from Feb 1979 (Median) to May 2018, with 380 observations. The data reached an all-time high of 13.000 % in Mar 1982 and a record low of 1.000 % in Apr 2014. CSI: Expected Inflation: Next 5 Yrs: Down data remains active status in CEIC and is reported by University of Michigan. The data is categorized under Global Database’s USA – Table US.H030: Consumer Sentiment Index: Unemployment, Interest Rates, Prices and Government Expectations. The questions were: 'What about the outlook for prices over the next 5 to 10 years? Do you think prices will be higher, to go up, on the average, during the next 12 months?' and 'By about what percent per year do you expect prices to go up or down, on the average, during the next 5 to 10 years?'

This scatter chart displays unemployment (% of total labor force) against inflation (annual %) in Georgia. The data is about countries per year.

I have compiled this dataset from publicly available data sources. It contains daily S&P 500 index price, trading volume, monthly Inflation rate, monthly unemployment rate and monthly CPI numbers for last 50 years. Motivation behind this dataset is for users to attempt to create ML/AI based models to predict the future prices of the index. Feel free to create new datasets utilizing this data and adding more relevant features that you can find that can impact the price of the index

Using the statistical technique of fuzzy clustering, regimes of inflation and unemployment are explored for the United States, the United Kingdom and Germany between 1871 and 2009. We identify for each country three distinct regimes in inflation/unemployment space. There is considerable similarity across the countries in both the regimes themselves and in the timings of the transitions between regimes. However, the typical rates of inflation and unemployment experienced in the regimes are substantially different. Further, even within a given regime, the results of the clustering show persistent fluctuations in the degree of attachment to that regime of inflation/unemployment observations over time. The economic implications of the results are that, first, the inflation/unemployment relationship experiences from time to time major shifts. Second, that it is also inherently unstable even in the short run. It is likely that the factors which govern the inflation/unemployment trade off are so multi-dimensional that it is hard to see that there is a way of identifying periods of short run Phillips curves which can be assigned to particular historical periods with any degree of accuracy or predictability. The short run may be so short as to be meaningless. The analysis shows that reliance on any kind of trade off between inflation and unemployment for policy purposes is entirely misplaced.

Unemployment Rate in France increased to 7.70 percent in the third quarter of 2025 from 7.60 percent in the second quarter of 2025. This dataset provides the latest reported value for - France Unemployment Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

CSI: Expected Inflation: Next Yr: Down data was reported at 1.000 % in May 2018. This stayed constant from the previous number of 1.000 % for Apr 2018. CSI: Expected Inflation: Next Yr: Down data is updated monthly, averaging 3.000 % from Jan 1978 (Median) to May 2018, with 485 observations. The data reached an all-time high of 23.000 % in Dec 2008 and a record low of 0.000 % in Oct 1999. CSI: Expected Inflation: Next Yr: Down data remains active status in CEIC and is reported by University of Michigan. The data is categorized under Global Database’s USA – Table US.H030: Consumer Sentiment Index: Unemployment, Interest Rates, Prices and Government Expectations. The questions were: 'During the next 12 months, do you think that prices in general will go up, or go down, or stay where they are now?' and 'By what percent do you expect prices to go up, on the average, during the next 12 months?'

Inflation Rate in the United States increased to 3 percent in September from 2.90 percent in August of 2025. This dataset provides - United States Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

CSI: Expected Inflation: Next Yr: Up by 6-9% data was reported at 3.000 % in May 2018. This stayed constant from the previous number of 3.000 % for Apr 2018. CSI: Expected Inflation: Next Yr: Up by 6-9% data is updated monthly, averaging 5.000 % from Jan 1978 (Median) to May 2018, with 485 observations. The data reached an all-time high of 26.000 % in Apr 1978 and a record low of 1.000 % in Sep 2010. CSI: Expected Inflation: Next Yr: Up by 6-9% data remains active status in CEIC and is reported by University of Michigan. The data is categorized under Global Database’s USA – Table US.H030: Consumer Sentiment Index: Unemployment, Interest Rates, Prices and Government Expectations. The questions were: 'During the next 12 months, do you think that prices in general will go up, or go down, or stay where they are now?' and 'By what percent do you expect prices to go up, on the average, during the next 12 months?'

Graph and download economic data for Natural Rate of Unemployment (Short-Term) (DISCONTINUED) (NROUST) from Q1 1949 to Q4 2031 about NAIRU, short-term, projection, unemployment, rate, and USA.

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

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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

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Since the COVID-19 pandemic, the United States has experienced sharply rising then falling inflation alongside persistent labor market imbalances. This Economic Commentary interprets these macroeconomic dynamics, as represented by the Beveridge and Phillips curves, through the lens of a macroeconomic model. It uses the structure of the model to rationalize the debate about whether the US economy can expect a hard or soft landing. The model is surprised by the resiliency of the labor market as the US economy experienced disinflation. We suggest that the model’s limited ability to capture this resiliency is a feature of using a linear model to forecast the historically unprecedented movements seen after the pandemic among inflation, unemployment, and vacancy rates. We explain how, by adjusting the model to mimic congestion in a tight labor market and greater wage and price flexibility in a high-inflation environment, as during the post-pandemic period, the model can then capture what has been a path consistent with a soft landing.

This dataset provides a comprehensive collection of monthly U.S. macroeconomic indicators spanning January 2000 to December 2024.

It was designed specifically for machine learning-based inflation forecasting and includes key economic factors historically associated with inflation trends:

• Consumer Price Index (CPI) & Inflation Rate
• Unemployment Rate
• Federal Funds Rate
• M2 Money Supply
• Crude Oil Prices (WTI)
• Producer Price Index (PPI)

Primary Goal: Build predictive models to forecast year-over-year inflation rates

Possible Use Cases:

• Forecasting inflation using machine learning models like XGBoost, Random Forest, or LSTM.
• Studying relationships between macroeconomic factors and inflationary pressure.
• Comparing classical econometric approaches with modern AI-based forecasting techniques.

Structure: Each CSV contains a Date column and corresponding metric values, making it easy to merge and align data for analysis.

License: MIT License – free to use for research and educational purposes.