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

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 ---

Background: This study investigates the influence of regional minimum wages (RMW), gross domestic product (GDP), and inflation on Indonesia's unemployment rates from 2012 to 2020. Methods: Multiple linear regression analysis examines the relationships between these economic variables. Findings: The findings reveal that RMW significantly negatively affects unemployment rates, indicating that a 1% increase in the minimum wage leads to a 3.951% decrease in unemployment, ceteris paribus. GDP also exhibits a significant negative influence, aligning with Okun's law, which suggests an inverse relationship between economic growth and unemployment. In contrast, inflation does not significantly impact unemployment rates during the studied period. Collectively, the three variables positively and significantly affect Indonesia's unemployment rate, with an adjusted R-squared value of 0.749. This implies that 74.9% of the variation in unemployment can be explained by GDP, inflation, and minimum wages, while other factors account for the remaining 25.1%. Conclusion: The study highlights the complex interplay between these macroeconomic indicators and unemployment, providing insights for policymakers to develop effective strategies for managing employment challenges in Indonesia. Novelty/Originality of this article: This empirical analysis reveals the dynamic relationship between RMW, GDP, inflation, and unemployment in Indonesia (2012—2020). The findings provide an evidence-based basis for formulating more effective and responsive employment and economic policies for Indonesia's labour market conditions.

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

Data supports Working Paper 713, "Is There a Stable Relationship between Unemployment and Future Inflation? Evidence from U.S. Cities." https://minneapolisfed.org/research/wp/wp713.pdf

This data is used for article of macroeconomic of some Asian countries in long period which explained about four Asian countries, such as Indonesia, Malaysia, Singapore, and South Korea. This data has taken from World Bank Development Indicators (WDI) database and is formed by Vector Auto Regression (VAR) model, then empirical result is executed by Granger causality model on E-views 11 program to gauge the relationship between gross domestic product, exchange rate, inflation rate, foreign direct investment, net export, government expenditures, unemployment rate, and savings. The results showed that most of gross domestic product of sample and other macro-economy variables have not causality relationship.

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

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

Estimates of the natural rate of unemployment are important in many macroeconomic models used by economists and policy advisors. This paper shows how such estimates might benefit from closer attention to regional developments. Regional business cycles do not move in lock-step, and greater dispersion among regions can affect estimates of the natural rate of unemployment. There is microeconomic evidence that employers are more reluctant to cut wages than they are to raise them. Accordingly, the relationship between wage inflation and vacancies is convex: An increase in vacancies raises wage inflation at an increasing rate. The authors' empirical results are consistent with this and indicate that if all else had remained constant, the reduction in the dispersion of regional unemployment rates between 1982 and 2000 would have meant a two-percentage-point drop in the natural rate of aggregate unemployment.

The relationships between real wages, output per capita, inflation and unemployment in Italy between 1970 and 1994 are modelled using a cointegrated vector autoregression. There is evidence of a change in the underlying equilibria and in the dynamic evolution of the variables, probably associated with the substantial changes in many sectors of the Italian economy after 1979. Alternative ways to model structural change in the Italian labour market are considered. In adopting a split-sample approach the results favour an hysteresis interpretation of unemployment.

The inflation rate in the United States declined significantly between June 2022 and May 2025, despite rising inflationary pressures towards the end of 2024. The peak inflation rate was recorded in June 2022, at *** percent. In August 2023, the Federal Reserve's interest rate hit its highest level during the observed period, at **** percent, and remained unchanged until September 2024, when the Federal Reserve implemented its first rate cut since September 2021. By January 2025, the rate dropped to **** percent, signalling a shift in monetary policy. What is the Federal Reserve interest rate? The Federal Reserve interest rate, or the federal funds rate, is the rate at which banks and credit unions lend to and borrow from each other. It is one of the Federal Reserve's key tools for maintaining strong employment rates, stable prices, and reasonable interest rates. The rate is determined by the Federal Reserve and adjusted eight times a year, though it can be changed through emergency meetings during times of crisis. The Fed doesn't directly control the interest rate but sets a target rate. It then uses open market operations to influence rates toward this target. Ways of measuring inflation Inflation is typically measured using several methods, with the most common being the Consumer Price Index (CPI). The CPI tracks the price of a fixed basket of goods and services over time, providing a measure of the price changes consumers face. At the end of 2023, the CPI in the United States was ****** percent, up from ****** a year earlier. A more business-focused measure is the producer price index (PPI), which represents the costs of firms.

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

This study is carried out to empirically examine the implication of unemployment and inflation on poverty level in Nigeria from 1980-2014. Three variables are used in this paper which are Poverty level, Unemployment Rate and Inflation Rate. The variables were subjected to unit root test and they were all stationary at first difference I(1). Using the Johansen test, the variables were found to be co-integrated at 5% level of significance. Vector Auto Regressive (VAR) Model was used to determine the short-run relationship between the variables and the forth lag was selected based on the lag selection criterion. Forecast Error Variance Decomposition (FEVD) was obtained using the cholesky decomposition of the VAR residual. The result obtained showed the proportion of the variations in Poverty, inflation and unemployment rate attributed to their respective lag values. Granger causality test was carried out from the VAR model, and the result indicated that there is a bi-causality between inflation and poverty. There is two-way causality between unemployment rate and poverty. There is one-way causality between unemployment rate and inflation rate. From the conclusion, it recommended that since unemployment causes poverty in Nigeria, government should review the education curriculum which will include practical skill acquisition programme in the educational system so as to produce graduates that are employers of labour rather than employment seekers. The government should give incentives to producers to enable them increase domestic production which will bring down price level. Nigerian government should strive to reduce poverty level by formulating and implementing poverty reduction programme like social security which will reduce inflation and unemployment rate and will lead to economic growth.

During the period beginning roughly in the mid-1980s until the Global Financial Crisis (2007-2008), the U.S. economy experienced a time of relative economic calm, with low inflation and consistent GDP growth. Compared with the turbulent economic era which had preceded it in the 1970s and the early 1980s, the lack of extreme fluctuations in the business cycle led some commentators to suggest that macroeconomic issues such as high inflation, long-term unemployment and financial crises were a thing of the past. Indeed, the President of the American Economic Association, Professor Robert Lucas, famously proclaimed in 2003 that "central problem of depression prevention has been solved, for all practical purposes". Ben Bernanke, the future chairman of the Federal Reserve during the Global Financial Crisis (GFC) and 2022 Nobel Prize in Economics recipient, coined the term 'the Great Moderation' to describe this era of newfound economic confidence. The era came to an abrupt end with the outbreak of the GFC in the Summer of 2007, as the U.S. financial system began to crash due to a downturn in the real estate market.

Causes of the Great Moderation, and its downfall

A number of factors have been cited as contributing to the Great Moderation including central bank monetary policies, the shift from manufacturing to services in the economy, improvements in information technology and management practices, as well as reduced energy prices. The period coincided with the term of Fed chairman Alan Greenspan (1987-2006), famous for the 'Greenspan put', a policy which meant that the Fed would proactively address downturns in the stock market using its monetary policy tools. These economic factors came to prominence at the same time as the end of the Cold War (1947-1991), with the U.S. attaining a new level of hegemony in global politics, as its main geopolitical rival, the Soviet Union, no longer existed. During the Great Moderation, the U.S. experienced a recession twice, between July 1990 and March 1991, and again from March 2001 tom November 2001, however, these relatively short recessions did not knock the U.S. off its growth path. The build up of household and corporate debt over the early 2000s eventually led to the Global Financial Crisis, as the bursting of the U.S. housing bubble in 2007 reverberated across the financial system, with a subsequent credit freeze and mass defaults.

Unemployment Rate in China decreased to 5 percent in May from 5.10 percent in April of 2025. This dataset provides - China Unemployment Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

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

Unemployment Rate in Japan remained unchanged at 2.50 percent in May. 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.

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

Economic welfare is essential in the modern economy since it directly reflects the standard of living, distribution of resources, and general social satisfaction, which influences individual and social well-being. This study aims to explore the relationship between national income accounting different attributes and the economic welfare in Pakistan. However, this study used data from 1950 to 2022, and data was downloaded from the World Bank data portal. Regression analysis is used to investigate the relationship between them and is very effective in measuring the relationship between endogenous and exogenous variables. Moreover, generalized methods of movement (GMM) are used as the robustness of the regression. Our results show that foreign direct investment outflow, Gross domestic product growth rate, GDP per capita, higher Interest, market capitalization, and population growth have a significant negative on the unemployment rate, indicating the rise in these factors leads to a decrease in the employment rate in Pakistan. Trade and savings have a significant positive impact on the unemployment rate, indicating the rise in these factors leads to an increase in the unemployment rate for various reasons. Moreover, all the factors of national income accounting have a significant positive relationship with life expectancy, indicating that an increase in these factors leads to an increase in economic welfare and life expectancy due to better health facilities, many resources, and correct economic policies. However, foreign direct investment, inflation rate, lending interest rate, and population growth have significant positive effects on age dependency, indicating these factors increase the age dependency. Moreover, GDP growth and GDP per capita negatively impact age dependency. Similarly, all the national income accounting factors have a significant negative relationship with legal rights that leads to decreased legal rights. Moreover, due to better health facilities and health planning, there is a negative significant relationship between national income accounting attributes and motility rate among children. Our study advocated the implications for the policymakers and the government to make policies for the welfare and increase the social factors.