Learn the differences between the consumer price index (CPI) and the personal consumption expenditures (PCE) price index. Find out what measures are used to gauge underlying inflation, or the long-term trend in prices, such as median and trimmed-mean inflation rates and core inflation.

Inflation in the table below is defined as the percent change in the CPI from the same month last year. The first column of numbers shows the latest value available from the national authorities and the next two columns show the levels of annual inflation three months and one year prior to the latest release. The data are updated daily. Over long stretches of time - typically years - inflation is a byproduct of the expansion of money supply. In the short run the inflation rate fluctuates with economic growth as recessions slow down the increase in prices and rapid output growth accelerates it. Shits in exchange rates, commodity prices, and natural phenomena like droughts also have an impact. Over time, however, these factors have only a transitory effect and the only variable that matters is money supply growth. The control of inflation is delegated to central banks that typically try to balance between relatively low inflation and low unemployment. For more, you can read our articles about optimal inflation and the causes of inflation in the short run and the long run.

This data is used for examination of inflation- unemployment relationship for 18 countries after 1991. Inflation data is obtained from World Bank database (https://data.worldbank.org/indicator/FP.CPI.TOTL.ZG) and unemployment data is obtained from International Labor Organization (http://www.ilo.org/wesodata/).

Analysis period is different for all countries because of structural breaks determined by single point change point detection algorithm included in changepoint package of Killick & Eckley (2014). Granger-causality is conducted with Toda&Yamamoto (1995) procedure. Integration levels are determined with 3 stationary tests. VAR models are run with vars package (Pfaff, Stigler & Pfaff; 2018) without trend and constant terms. Cointegration test is conducted with urca package (Pfaff, Zivot, Stigler & Pfaff; 2016).

All data files are .csv files. Analyst need to change country index (variable name: j) in order to see individual results. Findings can be seen in the article.

Killick, R., & Eckley, I. (2014). changepoint: An R package for changepoint analysis. Journal of statistical software, 58(3), 1-19.

Pfaff, B., Stigler, M., & Pfaff, M. B. (2018). Package ‘vars’. Online] https://cran. r-project. org/web/packages/vars/vars. pdf.

Pfaff, B., Zivot, E., Stigler, M., & Pfaff, M. B. (2016). Package ‘urca’. Unit root and cointegration tests for time series data. R package version, 1-2.

Toda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of econometrics, 66(1-2), 225-250.

presented in An analysis of pandemic-era inflation in 11 economies, PIIE Working Paper 24-11.

If you use the data, please cite as: Bernanke, Ben, and Olivier Blanchard. 2024. An analysis of pandemic-era inflation in 11 economies. PIIE Working Paper 24-11. Washington: Peterson Institute for International Economics.

Real interest rates describe the growth in the real value of the interest on a loan or deposit, adjusted for inflation. Nominal interest rates on the other hand show us the raw interest rate, which is unadjusted for inflation. If the inflation rate in a certain country were zero percent, the real and nominal interest rates would be the same number. As inflation reduces the real value of a loan, however, a positive inflation rate will mean that the nominal interest rate is more likely to be greater than the real interest rate. We can see this in the recent inflationary episode which has taken place in the wake of the Coronavirus pandemic, with nominal interest rates rising over the course of 2022, but still lagging far behind the rate of inflation, meaning these rate rises register as smaller increases in the real interest rate.

The statistic shows the inflation rate in Spain from 1987 to 2024, with projections up until 2030. The inflation rate is calculated using the price increase of a defined product basket. This product basket contains products and services, on which the average consumer spends money throughout the year. They include expenses for groceries, clothes, rent, power, telecommunications, recreational activities and raw materials (e.g. gas, oil), as well as federal fees and taxes. In 2023, the average inflation rate in Spain increased by about 3.4 percent compared to the previous year. Inflation in Spain As explained briefly above, inflation is commonly defined as the level of prices for goods and services in a country’s economy over a certain time span. It increases when the total money supply of a country increases, causing the money’s value to decrease, and prices to increase again in turn. Nowadays the term “inflation” is used more or less synonymously with “price level increase”. Its opposite is deflation, which, in short, means a decrease of the price level. Spain and its economy have been severely affected by the financial crisis of 2008 (as can be seen above), when the real estate bubble imploded and caused the demand for goods and services to decrease and the unemployment rate in Spain to increase dramatically. Even though deflation only occurred for one year in 2009 and the price level has been increasing since, Spain’s economy still has a long way to go until full recovery. Apart from the inflation rate and the unemployment rate, gross domestic product / GDP growth in Spain and the trade balance of goods in Spain, i.e. the exports of goods minus the imports, are additional indicators of Spain’s desolate condition during the economic crisis and its slow and difficult recovery ever since. Still, there is a silver lining for Spain’s economy. All in all, things seems to be improving economically, albeit slowly; many key indicators are starting to stabilize or even pick up again, while others still have some recovering to do.

Graph and download economic data for FOMC Summary of Economic Projections for the Personal Consumption Expenditures Inflation Rate, Range, High (PCECTPIRH) from 2025 to 2027 about projection, PCE, consumption expenditures, consumption, personal, inflation, rate, and USA.

Dataset Summary

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… See the full description on the dataset page: https://huggingface.co/datasets/aswin1906/countries-inflation.

Inflation rates for the lowest income households were almost always higher than for the highest income households between 2005 and 2021. The biggest difference was seen in December 2008, when the lowest income households experienced inflation rates 0.8 percent greater than the highest income households. In 2021, the difference in the inflation rate experienced by the lowest income households and the highest income households fell considerably, reaching -0.52 percent in July 2021, meaning that inflation was 0.52 percent higher for the highest earners versus the lowest earners.

The Consumer Price Index The consumer price index (CPI) measures the rate of inflation on a basket of goods as a way to document the general inflationary experience of all urban consumers. While this measure of inflation can give us insights into the general price increases of consumer goods, it may not reflect the actual inflation experienced by any given household. Consumers from different income brackets actually behave quite differently when it comes to consumption preferences and their willingness to pay.

Inflation in 2022 2022 was an exceptional year for inflation worldwide due to a multitude of factors relating to the COVID-19 pandemic and the Russian invasion of Ukraine. The inflation rate in the United States reached a high of 9.1 percent during the summer, with consumers experiencing record fuel prices, and increased concerns over the state of the economy. Despite the 2021 figures indicating that inflation has been higher for the highest earners, the pandemic saw U.S. billionaires increase their wealth by 57 percent between March 2020 and March 2022.

Graph and download economic data for Longer Run FOMC Summary of Economic Projections for the Personal Consumption Expenditures Inflation Rate, Central Tendency, Low (PCECTPICTLLR) from 2009-02-18 to 2025-06-18 about projection, PCE, consumption expenditures, consumption, personal, inflation, rate, and USA.

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.

Inflation: Friend or Foe to the Stock Market?

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

We report average expected inflation rates over the next one through 30 years. Our estimates of expected inflation rates are calculated using a Federal Reserve Bank of Cleveland model that combines financial data and survey-based measures. Released monthly.

This dataset holds valuable insights that can be leveraged by researchers, analysts, and policymakers to better understand the complex interactions between financial markets and food price inflation. Here are some potential insights that users could gain from this dataset:

Market-Food Price Correlation: By examining the relationship between financial market data (Open, High, Low, Close) and food price inflation, users can identify potential correlations. For example, they may uncover patterns where food price inflation impacts market sentiment or vice versa.

The statistic shows the inflation rate in India from 1987 to 2024, with projections up until 2030. The inflation rate is calculated using the price increase of a defined product basket. This product basket contains products and services, on which the average consumer spends money throughout the year. They include expenses for groceries, clothes, rent, power, telecommunications, recreational activities and raw materials (e.g. gas, oil), as well as federal fees and taxes. In 2024, the inflation rate in India was around 4.67 percent compared to the previous year. See figures on India's economic growth for additional information. India's inflation rate and economy Inflation is generally defined as the increase of prices of goods and services over a certain period of time, as opposed to deflation, which describes a decrease of these prices. Inflation is a significant economic indicator for a country. The inflation rate is the rate at which the general rise in the level of prices, goods and services in an economy occurs and how it affects the cost of living of those living in a particular country. It influences the interest rates paid on savings and mortgage rates but also has a bearing on levels of state pensions and benefits received. A 4 percent increase in the rate of inflation in 2011 for example would mean an individual would need to spend 4 percent more on the goods he was purchasing than he would have done in 2010. India’s inflation rate has been on the rise over the last decade. However, it has been decreasing slightly since 2010. India’s economy, however, has been doing quite well, with its GDP increasing steadily for years, and its national debt decreasing. The budget balance in relation to GDP is not looking too good, with the state deficit amounting to more than 9 percent of GDP.

Abstract (en): This research focuses on the longer-term monetary relationships in historical data. Charts describing the 10-year average growth rates in the M2 monetary aggregate, nominal GDP, real GDP, and inflation are used to show that there is a consistent longer-term correlation between M2 growth, nominal GDP growth, and inflation but not between such nominal variables and real GDP growth. The data reveal extremely long cycles in monetary growth and inflation, the most recent of which was the strong upward trend in M2 growth, nominal GDP growth, and inflation during the 1960s and 1970s, and the strong downward trend since then. Data going back to the 19th century show that the most recent inflation/disinflation cycle is a repetition of earlier long monetary growth and inflation cycles in the United States historical record. Also discussed is a measure of bond market inflation credibility, defined as the difference between averages in long-term bond rates and real GDP growth. By this measure, inflation credibility hovered close to zero during the 1950s and early 1960s, but then rose to a peak of about 10 percent in the early 1980s. During the 1990s, the bond market has yet to restore the low inflation credibility that existed before inflation turned up during the 1960s. The conclusion is that the risks of starting another costly inflation/disinflation cycle could be avoided by monitoring monetary growth and maintaining a sufficiently tight policy to keep inflation low. An environment of credible price stability would allow the economy to function unfettered by inflationary distortions, which is all that can reasonably be expected of monetary policy, and is precisely what should be expected. (1) The file submitted is the data file 9811WD.DAT. (2) These data are part of ICPSR's Publication-Related Archive and are distributed exactly as they arrived from the data depositor. ICPSR has not checked or processed this material. Users should consult the investigator(s) if further information is desired.

In 2024, only two Latin American or Caribbean country registered deflation in their average consumer prices. St Lucia and Costa Rica had the lowest change compared to the previous year with -0.45 and -0.41 percent, respectively. In contrast, the average inflation rate in Argentina amounted to about 219.89 percent.

Latin America among the highest inflation rates in the world In 2023, the average inflation rate of the region was around 14.41 percent. Which is significantly higher than the global average of 6.78 percent. Some of that is explained by countries such as Venezuela, Argentina, and Suriname ranking in the top then of countries with the highest inflation rate in the world.

Chronic inflation in Latin America Chronic inflation is often defined as persistent high inflation throughout a long time. Some of the common examples of this problem are Venezuela and Argentina, both countries had episodes of hyperinflation, with price increases considerably over 50 percent per month in both cases. The last few years, the global crisis and economic sanctions, attenuated the situation with Argentina reaching once again three-digit inflation and Venezuela exceeding 63,000 percent inflation in 2019.

Expected Inflation Term Structure is a part of the Inflation Expectations indicator of the Federal Reserve Bank of Cleveland.

Inflation Rate in Japan decreased to 3.10 percent in July from 3.30 percent in June of 2025. This dataset provides the latest reported value for - Japan Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Empirical analyses of Cagan’s money demand schedule for hyper-inflation have largely ignored the explosive nature of hyper-inflationary data. It is argued that this contributes to an (i) inability to model the data to the end of the hyper-inflation, and to (ii) discrepancies between “estimated” and “actual” inflation tax. Using data from the extreme Yugoslavian hyper-inflation it is shown that a linear analysis of levels of prices and money fails in addressing these issues even when the explosiveness is taken into account. The explanation is that log real money has random walk behaviour while the growth of log prices is explosive. A simple solution to these issues is found by replacing the conventional measure of inflation by the cost of holding money.

ABSTRACT The main purpose of this work is to conduct a systematic literature review regarding inflation expectations, their determinants, and their implications for policy making in Latin America. The analysis shows the importance of inflation expectations in the countries that use an inflation targeting scheme, while also supporting the idea that inflation expectations can affect other sectors of the economy. As for the determinants of expectations, the findings show the importance of past iterations of expectations, supporting the idea that the inflation expectations are heavily determined by themselves. The amount of research being conducted in this field is not comprehensive. This is even more evident in the Latin American region since it is a recent research field with a meager number of publications, deeming our study useful for future research. The classification process makes it easier to know the most common variables and econometric methods used to find the determinants of inflation expectations and their impact on other economic variables.