The monthly inflation rate and unemployment rate in Belgium, France, Germany, Italy, Poland, and Spain from 2020 to 2021. I simply put the data in one file since you need to download them separately if you get them from the link. These economics indicator might help for the Kaggle competition Tabular Playground Series September 2022.

Here are the data sources for the inflation rate and the unemployment rate

Unemployment Rate in the United States increased to 4.20 percent in July from 4.10 percent in June 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.

This dataset includes economic statistics on inflation, prices, unemployment, and pay & benefits provided by the Bureau of Labor Statistics (BLS). This public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery .

Abstract

This dataset includes economic statistics on inflation, prices, unemployment, and pay & benefits provided by the Bureau of Labor Statistics (BLS)

Documentation

Update frequency: Monthly Dataset source: U.S. Bureau of Labor Statistics Terms of use: This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source - http://www.data.gov/privacy-policy#data_policy - and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset. See the GCP Marketplace listing for more details and sample queries: https://console.cloud.google.com/marketplace/details/bls-public-data/bureau-of-labor-statistics

Unemployment Rate in Brazil decreased to 5.80 percent in June from 6.20 percent in May of 2025. This dataset provides the latest reported value for - Brazil Unemployment Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Unemployment Rate in Germany remained unchanged at 6.30 percent in July. This dataset provides the latest reported value for - Germany Unemployment Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Context

The Bureau of Labor Statistics (BLS) is a unit of the United States Department of Labor. It is the principal fact-finding agency for the U.S. government in the broad field of labor economics and statistics and serves as a principal agency of the U.S. Federal Statistical System. The BLS is a governmental statistical agency that collects, processes, analyzes, and disseminates essential statistical data to the American public, the U.S. Congress, other Federal agencies, State and local governments, business, and labor representatives. Source: https://en.wikipedia.org/wiki/Bureau_of_Labor_Statistics

Content

Bureau of Labor Statistics including CPI (inflation), employment, unemployment, and wage data.

Update Frequency: Monthly

Querying BigQuery Tables

Fork this kernel to get started.

Acknowledgements

https://bigquery.cloud.google.com/dataset/bigquery-public-data:bls

https://cloud.google.com/bigquery/public-data/bureau-of-labor-statistics

Dataset Source: http://www.bls.gov/data/

This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source - http://www.data.gov/privacy-policy#data_policy - and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.

Banner Photo by Clark Young from Unsplash.

Inspiration

What is the average annual inflation across all US Cities? What was the monthly unemployment rate (U3) in 2016? What are the top 10 hourly-waged types of work in Pittsburgh, PA for 2016?

Analysis of ‘Inflation and Unemployment’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/harisonmwangi/inflation-and-unemployment on 30 September 2021.

--- Dataset description provided by original source is as follows ---

Context

Annual data on inflation and unemployment for countries and regions in the world.

Content

Annual data on inflation and unemployment for countries and regions in the world. Retrieved from World Development Indicators data bank.

Inspiration

The main aim of the data is to explore the relationship between inflation and unemployment rates. Does the Phillips curve in economics still exist, or is it some spurious correlation of data in the '60s?

--- Original source retains full ownership of the source dataset ---

The table Employment hours earnings is part of the dataset Bureau of Labor Statistics Unemployment and Inflation, available at https://columbia.redivis.com/datasets/ymdq-1a9mgdxff. It contains 7900689 rows across 7 variables.

Unemployment Rate in China remained unchanged at 5 percent in June. This dataset provides - China Unemployment Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Unemployment rate, participation rate, and employment rate by educational attainment, gender and age group, annual.

Unemployment Rate in Japan remained unchanged at 2.50 percent in June. This dataset provides the latest reported value for - Japan Unemployment Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Inflation Rate in the United States increased to 2.70 percent in June from 2.40 percent in May of 2025. This dataset provides - United States Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Ireland IE: NAIRU: Equilibrium Unemployment Rate data was reported at 7.152 % in 2022. This records an increase from the previous number of 7.136 % for 2021. Ireland IE: NAIRU: Equilibrium Unemployment Rate data is updated yearly, averaging 8.407 % from Dec 1990 (Median) to 2022, with 33 observations. The data reached an all-time high of 12.280 % in 1990 and a record low of 7.136 % in 2021. Ireland IE: NAIRU: Equilibrium Unemployment Rate data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Ireland – Table IE.OECD.EO: Non-Accelerating Inflation Rate of Unemployment (NAIRU): Forecast: OECD Member: Annual. NAIRU - Equilibrium unemployment rate The equilibrium unemployment rate (code NAIRU) is estimated using a Kalman filter in a Phillips curve framework which assumes inflation expectations are anchored at the central bank’s inflation target . The NAIRU is then projected forward from the last estimated period using a simple autoregressive rule, exceptionally modified to account for recent labour market reforms, until the end of the forecasting horizon More details on methodology in Rusticelli E., Turner D. and M. C. Cavalleri (2015), Incorporating anchored inflation expectations in the Phillips Curve and in the derivation of OECD measures of equilibrium unemployment, OECD Economics Department Working Papers No.1231 OECD, Economics Department Working Papers: Incorporating anchored inflation expectations in the Phillips Curve and in the derivation of OECD measures of equilibrium unemployment:https://www.oecd-ilibrary.org/economics/incorporating-anchored-inflation-expectations-in-the-phillips-curve-and-in-the-derivation-of-oecd-measures-of-equilibrium-unemployment_5js1gmq551wd-en

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 remained unchanged at 7.50 percent in the second quarter of 2025 from 7.50 percent in the first 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.

The data sheet of our study, based on Corruption, Suicide, Inflation, Unemployment, and Economic growth of the American region.

Norway NO: NAIRU: Equilibrium Unemployment Rate data was reported at 3.514 % in 2022. This records an increase from the previous number of 3.480 % for 2021. Norway NO: NAIRU: Equilibrium Unemployment Rate data is updated yearly, averaging 3.462 % from Dec 1985 (Median) to 2022, with 38 observations. The data reached an all-time high of 4.744 % in 1993 and a record low of 2.775 % in 1985. Norway NO: NAIRU: Equilibrium Unemployment Rate data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Norway – Table NO.OECD.EO: Non-Accelerating Inflation Rate of Unemployment (NAIRU): Forecast: OECD Member: Annual. NAIRU - Equilibrium unemployment rate The equilibrium unemployment rate (code NAIRU) is estimated using a Kalman filter in a Phillips curve framework which assumes inflation expectations are anchored at the central bank’s inflation target . The NAIRU is then projected forward from the last estimated period using a simple autoregressive rule, exceptionally modified to account for recent labour market reforms, until the end of the forecasting horizon More details on methodology in Rusticelli E., Turner D. and M. C. Cavalleri (2015), Incorporating anchored inflation expectations in the Phillips Curve and in the derivation of OECD measures of equilibrium unemployment, OECD Economics Department Working Papers No.1231 OECD, Economics Department Working Papers: Incorporating anchored inflation expectations in the Phillips Curve and in the derivation of OECD measures of equilibrium unemployment:https://www.oecd-ilibrary.org/economics/incorporating-anchored-inflation-expectations-in-the-phillips-curve-and-in-the-derivation-of-oecd-measures-of-equilibrium-unemployment_5js1gmq551wd-en

This paper derives optimal monetary policy rules in setups where certainty equivalence does not hold because either central bank preferences are not quadratic, and/or the aggregate supply relation is nonlinear. Analytical results show that these features lead to sign and size asymmetries, and nonlinearities in the policy rule. Reduced-form estimates indicate that US monetary policy can be characterized by a nonlinear policy rule after 1983, but not before 1979. This finding is consistent with the view that the Fed's inflation preferences during the Volcker-Greenspan regime differ considerably from the ones during the Burns-Miller regime. The file MONTHLY.TXT contains monthly data between 1970.1 and 2000.12 arranged in five columns; the file QUARTERLY.TXT contains quarterly data between 1960.1 and 2000.4 arranged in five columns. The headings OBS, FFRATE, INF, IPI, and UNRATE denote, respectively, the date, Federal Funds rate, CPI inflation rate, Index of Industrial Production, and Unemployment Rate. Additional details can be found the section entitled 3.1 DATA of the paper.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

What is the relationship between unemployment and inflation?

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data