Inflation occurs when there is a sustained increase in the general price level of goods and services in an economy over time. It impacts various aspects of the economy, including purchasing power, consumer behaviour, savings, and investment. Moderate inflation is typically a sign of a healthy, growing economy, as it encourages spending and investment. However, high or unpredictable inflation can erode the value of money, disrupt financial planning, and lead to economic uncertainty.

To analyze the impact of inflation, we need to compare it with other economic indicators. So, to analyze the impact of inflation on the economy, we will compare it with the exchange rates over time. This comparison is important because exchange rates are influenced by inflation differentials between countries, such that higher inflation in a country generally leads to a weaker currency relative to countries with lower inflation.

This Economic Commentary provides an overview of several frictions and the channels through which they affect economic welfare under elevated trend inflation above 2 percent. These frictions, associated with financial transactions, price and wage stickiness, and cognitive limitations, suggest that inflation imposes significant costs on society. Higher inflation may lead to a steeper Phillips curve, a situation which increases the volatility of inflation and interest rates.

Inflation and its perception by the public are often very different. 🏷 While the Central Bank tracks inflation across a wide range of goods, people typically don't buy all of them every day. 💡 This creates a disconnect between the official inflation data and public perception. But is there a correlation between the two? 🤔

This dataset explores the relationship between inflation as reported by the Central Bank of Russia and inflation expectations as captured in surveys conducted by ВЦИОМ (All-Russian Public Opinion Research Center). 📈 By analyzing both sources of data, we can understand how Russians feel about inflation and how their perception compares with the official statistics.

🗓 Dataset Overview:

• Survey Data: 💬 Data collected from surveys asking Russian citizens about their perception of inflation. The survey categorizes inflation into three levels: "Very High," "Moderate," and "Low."

• Central Bank Data: 🏦 Official data published by the Central Bank of Russia, including year-on-year inflation rates and key interest rates.

Inflation Perception Index: 🔢 The perception index is calculated using a weighted average of survey responses:

Index = ( Very High Inflation × 0.9 + Moderate Inflation × 0.5 + Low Inflation × 0.1) / Count without "I don’t know"

📅 Data Collection:

• Survey Data Source: 📊 ВЦИОМ (All-Russian Public Opinion Research Center) conducts regular surveys on inflation perceptions among Russian citizens. The survey data captures public sentiment on inflation in the last month or two.

• Inflation Data Source: 🏛 Central Bank of Russia provides official inflation statistics (year-on-year) and the key interest rate, which are critical for evaluating economic stability. The inflation target is also included in the dataset.

🧮 Key Columns:

• Date 📅: The date corresponding to each data entry.

• Key Rate, % per year 💰: The official interest rate set by the Central Bank of Russia.

• Inflation, % year-on-year 📉: The year-on-year inflation rate reported by the Central Bank.

• Inflation Target 🎯: The official target for inflation set by the Central Bank.

• Survey Responses 🗣: Data from survey questions about inflation perceptions:

  • Very High Inflation (Survey) 🚨

  • Moderate Inflation (Survey) 📊

  • Low Inflation (Survey) 🌱

  • I do not know (Survey) 🤷‍♂️

• Perception Index 🔢: The calculated index reflecting the general perception of inflation among Russians.

📈 Potential Use Cases:

• Economic Research 📚: Analyze the correlation between official inflation rates and public sentiment regarding inflation.

• Policy Evaluation 📊: Assess the effectiveness of the Central Bank's monetary policies in influencing public perceptions of inflation.

• Forecasting 🔮: Build predictive models for inflation expectations based on public sentiment and official statistics.

• Public Sentiment Analysis 💬: Explore how perceptions of inflation impact consumer behavior and business strategies.

📚 Acknowledgments:

Data Sources: 🏦 Central Bank of Russia (CBR) | 📊 ВЦИОМ (Survey Data)

This dataset contains economic indicators for Pakistan spanning from 1986 to 2006 (21 years of data). Here's what the dataset includes: Dataset Overview:

Time Period: 1986-2006 Country: Pakistan Purpose: Inflation forecasting analysis

Variables/Columns:

Year - Time period identifier Inflation - Inflation rates (ranging from about 2.9% to 12.4%) [Column C] - Unlabeled column with values like 16.65, 17.4, 18, etc. GDP Growth - Economic growth rates (ranging from 1% to 7.8%) Unemployment - Unemployment rates (mostly between 3-8%) Broad Money - Monetary supply indicator (values in hundreds) Exports - Export values Imports - Import values Oil rents - Oil-related economic indicator (mostly below 1.0) Remittances - Foreign remittance values

Key Characteristics:

Comprehensive macroeconomic dataset Covers multiple economic indicators that typically influence inflation Suitable for econometric analysis and forecasting models Includes both monetary (broad money, remittances) and real sector variables (GDP, unemployment) Trade variables (exports/imports) for external sector analysis

This appears to be a well-structured dataset for studying inflation dynamics and building forecasting models for Pakistan's economy.

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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Context:

Inflation is a critical economic indicator that reflects the overall increase in prices of goods and services within an economy over a specific period. Understanding inflation trends on a global scale is crucial for economists, policymakers, investors, and businesses. This dataset provides comprehensive insights into the inflation rates of various countries for the year 2022. The data is sourced from reputable international organizations and government reports, making it a valuable resource for economic analysis and research.

Content:

This dataset includes four essential columns:

1.**Countries:** The names of countries for which inflation data is recorded. Each row represents a specific country.

2.**Inflation, 2022:** The inflation rate for each country in the year 2022. Inflation rates are typically expressed as a percentage and indicate the average increase in prices for that year.

3.**Global Rank:** The rank of each country based on its inflation rate in 2022. Countries with the highest inflation rates will have a lower rank, while those with lower inflation rates will have a higher rank.

4.**Available Data:** A binary indicator (Yes/No) denoting whether complete and reliable data for inflation in 2022 is available for a particular country. This column helps users identify the data quality and coverage.

Potential Use Cases:

-**Economic Analysis:** Researchers and economists can use this dataset to analyze inflation trends globally, identify countries with high or low inflation rates, and make comparisons across regions.

-**Investment Decisions:** Investors and financial analysts can incorporate inflation data into their risk assessments and investment strategies.

-**Business Planning:** Companies operating in multiple countries can assess the impact of inflation on their costs and pricing strategies, helping them make informed decisions.

Data Accuracy: Efforts have been made to ensure the accuracy and reliability of the data; however, users are encouraged to cross-reference this dataset with official sources for critical decision-making processes.

Updates: This dataset will be periodically updated to include the latest available inflation data, making it an ongoing resource for tracking global inflation trends.

Acknowledgments: We would like to express our gratitude to the numerous agencies and organizations that collect and publish inflation data, contributing to the transparency and understanding of economic conditions worldwide.

License: This dataset is provided under an open data license, allowing users to freely use and share the data while adhering to the specified licensing terms.

Feel free to adapt and expand upon this template to create a comprehensive and informative dataset description for your Kaggle publication on global inflation rates for 2022.

In case prices for goods and services go up significantly in 2023, over ** percent of consumers around the world said they would shop less in general and cut down on spending as a response. A fifth of survey respondents said they would look for and purchase cheaper and better value products. Less than **** percent of those surveyed worldwide believed inflation would be unlikely to impact their habits. What does inflation look like? The world entered a new inflation crisis in 2021, driven by a confluence of factors including the COVID-19 pandemic which restricted global supply chains, and the Russian-Ukraine war which exacerbated food and energy shortages. In 2022, global inflation hit **** percent, the highest annual increase in decades. The rate of inflation is estimated to remain high in the near future, at around *** percent in 2023 and *** percent in 2024. Inflation dominated the list of most important problems facing the world according to a survey conducted in October 2023 – leading ahead of poverty and social inequality, crime and violence, and unemployment. In a global consumer trends survey, the majority of respondents said that inflation impacted them completely or a lot – for instance, ***** in ** respondents in the United States admitted they had been seriously impacted. Inflation’s impact on the holidays The end-of-year holiday season is typically regarded as a period of increased retail spending, driven by a series of major shopping events such as Black Friday and Cyber Monday, as well as the public holidays Thanksgiving and Christmas. However, inflation has put a damper on the holiday cheer, with consumers expressing their intentions to cut back spending amid the cost-of-living crisis. In 2022, a significant share of consumers in Europe said they planned to cut at least some related expenses. In fact, ** percent of respondents in the United Kingdom planned to cut all expenses related to Black Friday and Christmas.

Please, if you use this dataset or do you like my work please UPVOTE 👁️

This dataset provides a comprehensive historical record of inflation rates worldwide, covering the period from 1960 to the present. It includes inflation data at the national level for multiple countries and territories, making it a valuable resource for economic analysis, financial forecasting, and macroeconomic research.

Data Source: https://datos.bancomundial.org/indicador/FP.CPI.TOTL.ZG?end=2023&start=1960&view=chart

Key Features:

✅ Global Coverage – Inflation rates for countries across all continents.

✅ Long-Term Data – Over 60 years of historical records, ideal for trend analysis.

✅ Regional Classification – Data categorized by region, sub-region, and intermediate region for in-depth geographic analysis.

✅ Standardized Indicators – Based on CPI (Consumer Price Index) inflation rates from reputable sources.

Potential Use Cases:

📊 Economic Research – Analyze inflation trends and economic cycles.

📈 Financial Forecasting – Predict future inflation and its impact on global markets.

🌍 Policy & Development Studies – Examine regional disparities and economic policies.

📚 Machine Learning Applications – Train predictive models using historical inflation trends.

This dataset is an essential tool for economists, data scientists, and financial analysts looking to explore global inflation patterns and their implications on economic stability.

The Federal Reserve Bank of Cleveland’s Community Issues Survey (CIS) collects information semiannually from direct service providers to monitor economic conditions and identify issues impacting low- and moderate-income (LMI) households in the Fourth District, a region that includes Ohio, western Pennsylvania, eastern Kentucky, and the northern panhandle of West Virginia. On March 3–17, 2025, we surveyed nearly 550 organizations that directly serve LMI individuals and communities across our District and received 104 responses (19 percent response rate). The results of this survey are summarized here and provide insights into how organizations and the households they serve are faring in today’s economy.

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.

The interest rate set by the Federal Reserve is a crucial tool for promoting economic conditions that meet the mandate established by the United States Congress, which includes high employment, low and stable inflation, sustainable economic growth, and the moderation of long-term interest rates. The interest rates determined by the Fed directly influence the cost of credit, making financing either more accessible or more restrictive. When interest rates are low, there is a greater incentive for consumers to purchase homes through mortgages, finance automobiles, or undertake home renovations. Additionally, businesses are encouraged to invest in expanding their operations, whether by purchasing new equipment, modernizing facilities, or hiring more workers. Conversely, higher interest rates tend to curb such activity, discouraging borrowing and slowing economic expansion.

The dataset analyzed contains information on the economic conditions in the United States on a monthly basis since 1954, including the federal funds rate, which represents the percentage at which financial institutions trade reserves held at the Federal Reserve with each other in the interbank market overnight. This rate is determined by the market but is directly influenced by the Federal Reserve through open market operations to reach the established target. The Federal Open Market Committee (FOMC) meets eight times a year to determine the federal funds rate target, which has been defined within a range with upper and lower limits since December 2008.

Furthermore, real Gross Domestic Product (GDP) is calculated based on the seasonally adjusted quarterly rate of change in the economy, using chained 2009 dollars as a reference. The unemployment rate represents the seasonally adjusted percentage of the labor force that is unemployed. Meanwhile, the inflation rate is determined by the monthly change in the Consumer Price Index, excluding food and energy prices for a more stable analysis of core inflation.

The interest rate data was sourced from the Federal Reserve Bank of St. Louis' economic data portal, while GDP information was provided by the U.S. Bureau of Economic Analysis, and unemployment and inflation data were made available by the U.S. Bureau of Labor Statistics.

The analysis of this data helps to understand how economic growth, the unemployment rate, and inflation influence the Federal Reserve’s monetary policy decisions. Additionally, it allows for a study of the evolution of interest rate policies over time and raises the question of how predictable the Fed’s future decisions may be. Based on observed trends, it is possible to speculate whether the target range set in March 2017 will be maintained, lowered, or increased, considering the prevailing economic context and the challenges faced in conducting U.S. monetary policy.

Context

Happiness and well-being are essential indicators of societal progress, often influenced by economic conditions such as GDP and inflation. This dataset combines data from the World Happiness Index (WHI) and inflation metrics to explore the relationship between economic stability and happiness levels across 148 countries from 2015 to 2023. By analyzing key economic indicators alongside social well-being factors, this dataset provides insights into global prosperity trends.

Content

This dataset is provided in CSV format and includes 16 columns, covering both happiness-related features and economic indicators such as GDP per capita, inflation rates, and corruption perception. The main columns include:

Happiness Score & Rank (World Happiness Index ranking per country) Economic Indicators (GDP per capita, inflation metrics) Social Factors (Freedom, Social Support, Generosity) Geographical Information (Country & Continent)

Acknowledgements

The dataset is created using publicly available data from World Happiness Report, Gallup World Poll, and the World Bank. It has been structured for research, machine learning, and policy analysis purposes.

Inspiration

How do economic factors like inflation, GDP, and corruption affect happiness? Can we predict a country's happiness score based on economic conditions? This dataset allows you to analyze these relationships and build models to predict well-being trends worldwide.

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.

The Federal Reserve Bank of Cleveland’s Community Issues Survey (CIS) collects information semiannually from direct service providers to monitor economic conditions and identify issues impacting low- and moderate-income (LMI) households in the Fourth District—a region that includes Ohio, western Pennsylvania, eastern Kentucky, and the northern panhandle of West Virginia. In March 2023, we surveyed more than 600 service providers who directly serve LMI individuals and communities across our District and received 95 responses (15 percent response rate). The results of this survey, summarized here, provide insights into how organizations and the households they serve are faring as they continue to navigate the impacts of inflation.

The travel price index (TPI) published by the U.S. Travel Association includes data on the changes in the consumer price index (CPI) of travel and tourism services in the United States, such as airline fares, lodging, and recreation. In 2023, the TPI went up by 2.5 percent compared to the previous year, while the CPI experienced year-over-year growth of 4.1 percent. As forecast, the TPI and CPI are expected to increase by 1.3 percent and 2.9 percent, respectively, in 2024 over the previous year.

We provide explanations of basic and fundamental concepts on the definition of inflation, measurement of inflation, costs of inflation, the importance of measuring and controlling inflation, the role of the Federal Reserve in inflation, and other concepts such as price indexes, hyperinflation, trend and underlying inflation, measures of inflation like CPI, core CPI, median CPI, trimmed-mean CPI, PCE, core PCE, and trimmed-mean PCE.

This dataset provides annual inflation rates for various countries and regions from 1974 to 2019. It includes information on specific years, inflation percentages, and corresponding country or region codes. The data is useful for analyzing economic trends, comparing inflation rates across regions, and understanding the historical impact of inflation on global economies.

United States Breakeven Inflation: 5-Year data was reported at 2.300 % in 02 Dec 2025. This records a decrease from the previous number of 2.310 % for 01 Dec 2025. United States Breakeven Inflation: 5-Year data is updated daily, averaging 1.980 % from Jan 2003 (Median) to 02 Dec 2025, with 5733 observations. The data reached an all-time high of 3.590 % in 25 Mar 2022 and a record low of 0.140 % in 19 Mar 2020. United States Breakeven Inflation: 5-Year data remains active status in CEIC and is reported by Federal Reserve Bank of St. Louis. The data is categorized under Global Database’s United States – Table US.I: Breakeven Inflation Rate. [COVID-19-IMPACT]

Inflation Rate in India decreased to 0.25 percent in October from 1.44 percent in September of 2025. This dataset provides - India Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Inflation Rate in Brazil decreased to 4.68 percent in October from 5.17 percent in September of 2025. This dataset provides - Brazil Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.