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

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

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.

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

Unemployment Rate in the United States decreased to 4.10 percent in June from 4.20 percent in May 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 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

The misery index is an economic indicator that combines the unemployment rate and the inflation rate. Although it is rare for both unemployment and inflation to be high at the same time, there have been instances of this occurring, such as during episodes of stagflation in the 1970s. Due to high levels of inflation since late 2021, the misery index in March 2023 is at a relatively high rate of 8.49 percent.

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.

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

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

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

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.

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 ---

Table 0.37: Area, population, unemployment rate, inflation rate, gross national income and gross domestic product in selected countries

Australia NAIRU: Equilibrium Unemployment Rate data was reported at 5.413 % in 2022. This records an increase from the previous number of 5.345 % for 2021. Australia NAIRU: Equilibrium Unemployment Rate data is updated yearly, averaging 5.759 % from Dec 1985 (Median) to 2022, with 38 observations. The data reached an all-time high of 8.377 % in 1993 and a record low of 4.951 % in 2007. Australia 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 Australia – Table AU.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 scatter chart displays unemployment (% of total labor force) against inflation (annual %) in Africa. The data is about countries.

The Question “Why unemployment?” is one of the most central topics of economic theory since the great depression. Unemployment remains one of the most important problems of economic policies in industrial countries. Unemployment has different causes and therefore also different countermeasures are required. “Together with the destruction of environment unemployment and inflation are in the focus of economic and political discussions on macroeconomic problems and are considered as the greatest challenges of economic policy. Depending on the level of unemployment there is a higher focus on inflation or on unemployment, if both are on an alarming level at the same time they are in the shot simultaneously. In anyway both issues need to be analyzed together because they are not independent from each other. Experiences from the recent years have shown that combating inflation leads to an increase in unemployment, at least temporarily but probably also permanently. The other way around; combating unemployment may under certain circumstances also lead to an increase in inflation… Unemployment and inflation are macroeconomic problems. The level of both undesirable developments is determined by the relations in the entire economy. Therefor it is necessary to use macroeconomic theory which deals the general economic context for the analysis. Both problems are enhanced by structural factors which also need to be analyzed. In contrast to microeconomic theory which focuses on different individual decision makers, in macroeconomic theory decision makers and decisions are summarized in macroeconomic aggregates. The common procedure is to summarize decision makers into aggregates like “private households”, “enterprises” and “the state” and the decision makers concerning the use of income into “private consumption”, “investments” and “public expenditure” (Kromphardt, Jürgen, 1998: Arbeitslosigkeit und Inflation (unemployment and inflation). 2., newly revised A. Göttingen: Vandenhoeck & Ruprecht, p. 17-18). Macroeconomic approaches on the explanation of unemployment and inflation are highly controversial in economic theory. Therefore the author starts with the attempt to present different explanations for unemployment and inflation from different macroeconomic positions. There are different unemployment: classical unemployment (reason: real wages to high), Keynesian unemployment (reason: demand for goods to low), unemployment due to a lack of working places (reason: capital stock to low). These positions give conflicting explanations and recommendations because they are based on different perceptions of the starting position. Therefor the author confronts central positions with empirical data on the macro level with the following restriction: “It is impossible to prove theories as correct (to verify). This is a reason for the fact that macroeconomic controversies do not come to a conclusion but are continued in a modified way. Furthermore economic statements in this field always affect social and political interests as all economic policies favor or put as a disadvantage interests of distinct social groups in a different way.“ (Kromphardt, a.a.O., S. 20).

Data tables in HISTAT (1) Development of employment: Presented by the development of annual average unemployment rates and the balance of labor force of the institute for labor market and occupation research (IAB, Nuremberg) after the domestic concept(employment with Germany as the place of work) For characterizing the overall economic developments, those values are used which play an important role in the reports of the German central bank: (2) Inflation: Rate of differences in the price index for costs of living compared to the previous year (3) Currency reserves of German federal banks and the German central bank: measure for foreign economic situation and the payment balance of the central bank (4) Development of economic growth: Presented by the nominal and real growth rate of the GDP (5) Inflation rate of the GDP, money supply, growth rate of the price index of the GDP (6) Labor productivity (= GDP per employee, domestic concept) (7) Real wage per employee (8) Exchange rate: DM/$ (monthly averages) (9) Growth of DGP, productivity, economically active population, real incomes, unemployment rate and adjusted wages (10) Time series connected with labor demand (11) GDP, labor volume, employees, working hours and labor productivity (12) Employee compensation, wages and ...

The misery index (the unweighted sum of unemployment and inflation rates) was probably the first attempt to develop a single statistic to measure the level of a population’s economic malaise. In this letter, we develop a dynamic approach to decompose the misery index using two basic relations of modern macroeconomics: the expectations-augmented Phillips curve and Okun’s law. Our reformulation of the misery index is closer in spirit to Okun’s idea. However, we are able to offer an improved version of the index, mainly based on output and unemployment. Specifically, this new Okun’s index measures the level of economic discomfort as a function of three key factors: (1) the misery index in the previous period; (2) the output gap in growth rate terms; and (3) cyclical unemployment. This dynamic approach differs substantially from the standard one utilised to develop the misery index, and allow us to obtain an index with five main interesting features: (1) it focuses on output, unemployment and inflation; (2) it considers only objective variables; (3) it allows a distinction between short-run and long-run phenomena; (4) it places more importance on output and unemployment rather than inflation; and (5) it weights recessions more than expansions.

Czech Republic CZ: NAIRU: Equilibrium Unemployment Rate data was reported at 3.891 % in 2022. This records an increase from the previous number of 3.831 % for 2021. Czech Republic CZ: NAIRU: Equilibrium Unemployment Rate data is updated yearly, averaging 6.107 % from Dec 1995 (Median) to 2022, with 28 observations. The data reached an all-time high of 7.608 % in 1999 and a record low of 3.831 % in 2020. Czech Republic CZ: 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 Czech Republic – Table CZ.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