Professionals from Italian e-commerce players faced inflation's impact on their business. A survey from early 2023 showed that about **** in *** companies had decreased margins to keep similar prices, whereas ** percent of surveyed professionals stated their companies maintained similar prices but reduced discounts.

Since early 2021, inflation has consistently exceeded the Federal Reserve’s target of 2 percent. Using a combination of data, economic theory, and narrative information around historical events, we empirically assess what has caused persistently elevated inflation. Our estimates suggest that both aggregate demand and supply factors, including supply chain disruptions, have contributed significantly to high inflation.

To mitigate the impact of inflation in 2023, most business-to-business (B2B) buyers revised their relationships with key suppliers in France. According to a survey, nearly **** in *** B2B buyers tried to obtain better supplying conditions in order to generate operational savings. As an alternative, ** percent of surveyed buyers simply looked for other suppliers offering better options. Last in the ranking came tasks automation, as ** percent of respondents considered this action effective in facing the inflationary crisis.

In the third quarter of 2024, half of Norwegian companies had problems with increasing purchase prices as a result of rising inflation seen around the world. Moreover, more than 40 percent faced problems due to an unstable economic framework. On the other hand, only 10 percent had issues with lack of credits or financing. As a consequence of the COVID-19 pandemic, as well as the Russian War in Ukraine that started in February 2022, inflation has been surging worldwide. For more information about inflation in the Nordic countries, please visit our dedicated topic page.

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)

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.

Indonesia Business Survey: Inflation Expectation: Construction data was reported at 3.778 % in Dec 2022. This records an increase from the previous number of 3.680 % for Sep 2022. Indonesia Business Survey: Inflation Expectation: Construction data is updated quarterly, averaging 3.646 % from Jun 2013 (Median) to Dec 2022, with 39 observations. The data reached an all-time high of 7.298 % in Sep 2013 and a record low of 3.180 % in Jun 2021. Indonesia Business Survey: Inflation Expectation: Construction data remains active status in CEIC and is reported by Bank Indonesia. The data is categorized under Indonesia Premium Database’s Business and Economic Survey – Table ID.SD008: Business Survey: Inflation Expectation. [COVID-19-IMPACT]

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

https://github.com/user-attachments/assets/1b40e0ca-7d2e-4fbc-8cfd-df3f09e4fdb8">

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

https:/...

We study the impact of targeted price controls on supermarket products in Argentina between 2007 and 2015. Using web-scraping methods, we collected daily prices for controlled and non-controlled goods and examined the differential effects of the policy on inflation, product availability, entry and exit, and price dispersion. We first show that price controls have only a small and temporary effect on inflation that reverses itself as soon as the controls are lifted. Second, contrary to common beliefs, we find that controlled goods are consistently available for sale. Third, firms compensate for price controls by introducing new product varieties at higher prices, thereby increasing price dispersion within narrow categories. Overall, our results show that targeted price controls are just as ineffective as more traditional forms of price controls in reducing aggregate inflation.

During an early 2023 survey among marketing leaders from for-profit companies in the United Kingdom, slightly more than ** percent of the respondents said that inflationary pressures decreased their marketing spending levels. Approximately ** percent of responding marketing leaders stated that inflationary pressures increased their marketing spending levels. On the other hand, around ** percent of the respondents said that inflationary pressures didn't affect their marketing spending levels.

United States BIE: Non-Labour Cost Effect on Price: Moderate Upward Influence data was reported at 55.426 % in Nov 2023. This records a decrease from the previous number of 61.910 % for Aug 2023. United States BIE: Non-Labour Cost Effect on Price: Moderate Upward Influence data is updated quarterly, averaging 55.563 % from Nov 2011 (Median) to Nov 2023, with 48 observations. The data reached an all-time high of 68.932 % in Feb 2013 and a record low of 31.101 % in May 2022. United States BIE: Non-Labour Cost Effect on Price: Moderate Upward Influence data remains active status in CEIC and is reported by Federal Reserve Bank of Atlanta. The data is categorized under Global Database’s United States – Table US.I122: Business Inflation Expectations Survey: Price Change. Business Inflation Expectations Survey Questionnaire: Projecting ahead over the next 12 months, how do you think the following five common influences will affect the prices of your products and/or services?

The Inflation Management Services market is experiencing robust growth, driven by increasing global inflation and the need for businesses to mitigate its impact on profitability and long-term sustainability. The market, estimated at $15 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 12% between 2025 and 2033, reaching approximately $45 billion by 2033. This expansion is fueled by several key factors, including rising energy prices, supply chain disruptions, and increased government intervention to control inflation. Businesses across various sectors, particularly those in manufacturing, retail, and finance, are actively seeking sophisticated strategies to forecast and manage inflation effectively. The increasing adoption of advanced analytics, predictive modeling, and AI-powered solutions further enhances the market's growth trajectory. Consulting firms like McKinsey & Company, Bain & Company, and Deloitte are playing a significant role in providing these services, leveraging their expertise in economic forecasting, financial modeling, and risk management. The market is segmented by service type (e.g., forecasting, hedging, pricing strategies), industry vertical, and geography. Regional growth is expected to be strongest in North America and Europe, driven by high inflation rates and a strong emphasis on corporate financial planning in these regions. While the market presents significant opportunities, challenges such as data scarcity and the complexity of accurately predicting inflation remain. The effectiveness of inflation management services is also contingent on external factors such as government policies and unexpected global events. Despite these constraints, the consistent need to protect profitability and shareholder value, along with the advancement of analytical tools, positions the inflation management services market for continued growth in the foreseeable future. The competitive landscape is characterized by a mix of large consulting firms offering comprehensive solutions and specialized firms focusing on niche areas within inflation management. The market will likely see further consolidation as firms strive to offer end-to-end solutions and expand their geographical reach.

About Dataset

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Global Energy, Food, Consumer, and Producer Price Inflation: A Comprehensive Dataset for Understanding Economic Trends

Key Concepts:

1. Energy Consumer Price Inflation data.
2. Food Consumer Price Inflation data.
3. Headline Consumer Price Inflation data.
4. Official Core Consumer Price Inflation data.
5. Producer Price Inflation data.
6. 206 Countries name, Country code and IMF code.
7. 52 Years data from 1970 to 2022.

The global economy is highly complex, and understanding economic trends and patterns is crucial for making informed decisions about investments, policies, and more. One key factor that impacts the economy is inflation, which refers to the rate at which prices increase over time. The Global Energy, Food, Consumer, and Producer Price Inflation dataset provides a comprehensive collection of inflation rates across 206 countries from 1970 to 2022, covering four critical sectors of the economy.

Finally, the Global Producer Price Inflation dataset provides a detailed look at price changes at the producer level, providing insights into supply chain dynamics and trends. This data can be used to make informed decisions about investments in various sectors of the economy and to develop effective policies to manage producer price inflation.

In conclusion, the Global Energy, Food, Consumer, and Producer Price Inflation dataset provides a comprehensive resource for understanding economic trends and patterns across 206 countries. By examining this data, analysts can gain insights into the complex factors that impact the economy and make informed decisions about investments, policies, and more.

Potential User:

1. Economists and economic researchers
2. Policy makers and government officials
3. Investors and financial analysts
4. Agricultural researchers and policymakers
5. Energy analysts and policy makers
6. Food industry professionals
7. Business leaders and decision makers
8. Academics and students in economics, finance, and related fields

Acknowledgements:

The data were collected from the official website of worldbank.org

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.

United States BIE: Non-Labour Cost Effect on Price: Strong Downward Influence data was reported at 1.111 % in Nov 2023. This records an increase from the previous number of 0.751 % for Aug 2023. United States BIE: Non-Labour Cost Effect on Price: Strong Downward Influence data is updated quarterly, averaging 0.540 % from Nov 2011 (Median) to Nov 2023, with 48 observations. The data reached an all-time high of 2.531 % in Nov 2021 and a record low of 0.000 % in May 2022. United States BIE: Non-Labour Cost Effect on Price: Strong Downward Influence data remains active status in CEIC and is reported by Federal Reserve Bank of Atlanta. The data is categorized under Global Database’s United States – Table US.I122: Business Inflation Expectations Survey: Price Change. Business Inflation Expectations Survey Questionnaire: Projecting ahead over the next 12 months, how do you think the following five common influences will affect the prices of your products and/or services?

In 2023, a survey found that to mitigate the effects of inflation, a significant proportion of micro, small, and medium enterprises (MSMEs) had to resort to different strategies. A share of ** percent of them utilized their personal savings to support the business, while ** percent reduced their business activities. In addition, nearly one-fourth (** percent) attempted to overcome the financial strain by implementing measures such as employee layoffs or salary cuts.

Significant supply chain constraints have increased prices and contributed to soaring inflation rates. These price increases are having a varied effect on Australian businesses.

ABSTRACT The paper argues that in controlling public prices government gets into a trap: this control does not reduce inflation as expect in the first moment and activates factors that will increase it later on. The analysis is developed for government administered prices in the area of energy and employs an input-output model that takes into account the direct and indirect impacts of price changes. When public prices are reduced, the impact on the inflation is small; but, since this create financial difficulties for the public companies, they will either demand government resources and/or price appreciation later on. These will act through price expectations to increase inflation more than proportionally in the future.

Description: This dataset provides a comprehensive overview of monthly inflation rates in Nigeria from March 2003 to June 2024, alongside key economic indicators such as crude oil prices, production levels, and various Consumer Price Index (CPI) components. The data captures important economic trends and is suitable for time series analysis, forecasting, and economic modeling.

The dataset includes the following features:

Inflation Rate: The monthly inflation rate in Nigeria, reflecting the change in consumer prices.

Crude Oil Price: The monthly average price of crude oil, which plays a significant role in Nigeria's economy.

Production and Export: Monthly crude oil production and export figures, representing key components of Nigeria's GDP.

CPI Components: Detailed breakdown of the Consumer Price Index, including food, energy, health, transport, communication, and education.

This dataset is ideal for economists, data scientists, and analysts interested in exploring the dynamics of inflation in a developing economy heavily influenced by oil prices and production. Potential applications include inflation forecasting, economic policy analysis, and studying the impact of global oil prices on domestic inflation.

United States BIE: Sales Level Effect on Price: Strong Downward Influence data was reported at 5.350 % in Nov 2023. This records an increase from the previous number of 2.872 % for Aug 2023. United States BIE: Sales Level Effect on Price: Strong Downward Influence data is updated quarterly, averaging 2.161 % from Nov 2011 (Median) to Nov 2023, with 48 observations. The data reached an all-time high of 10.554 % in Aug 2020 and a record low of 0.256 % in May 2014. United States BIE: Sales Level Effect on Price: Strong Downward Influence data remains active status in CEIC and is reported by Federal Reserve Bank of Atlanta. The data is categorized under Global Database’s United States – Table US.I122: Business Inflation Expectations Survey: Price Change. Business Inflation Expectations Survey Questionnaire: Projecting ahead over the next 12 months, how do you think the following five common influences will affect the prices of your products and/or services?