This dataset is about books. It has 1 row and is filtered where the book is Macroeconomic stabilization : fixed exchange rates vs inflation targeting vs price level targeting. It features 7 columns including author, publication date, language, and book publisher.

This folder provides the replication package for the paper “Shades of inflation targeting: insights from fractional integration”, published in 2025 in Macroeconomic Dynamics. The package includes: (i) the README file with instructions; (ii) the dataset on monthly CPI price level series for 36 inflation-targeting economies; (iii) the R code used to transform data and construct seasonally adjusted inflation rate series; and (iv) the Stata do-file used to specify and estimate ARFIMA models. These models are applied to assess the level of fractional integration of CPI inflation rates in 36 economies between 2000 and 2019, and to classify them into four groups of inflation targeting strategies: average IT, strict IT, flexible IT, and uncommitted IT. The materials reproduce the baseline results reported in the paper and provide a novel classification of IT strategies.

Bank of Mexico: Inflation Target data was reported at 3.000 % in 2020. This stayed constant from the previous number of 3.000 % for 2019. Bank of Mexico: Inflation Target data is updated yearly, averaging 3.000 % from Dec 2003 (Median) to 2020, with 18 observations. The data reached an all-time high of 3.000 % in 2020 and a record low of 3.000 % in 2020. Bank of Mexico: Inflation Target data remains active status in CEIC and is reported by Bank of Mexico. The data is categorized under Global Database’s Mexico – Table MX.I001: Consumer Price Index: Inflation Target.

The data and programs replicate tables and figures from "Price-level versus inflation targeting under model uncertainty", by Cateau. Please see the ReadMe file for additional details.

Central Bank of Uruguay: Inflation Target: Upper Limit data was reported at 7.000 % in Jul 2020. This stayed constant from the previous number of 7.000 % for Jun 2020. Central Bank of Uruguay: Inflation Target: Upper Limit data is updated monthly, averaging 7.000 % from Apr 2007 (Median) to Jul 2020, with 160 observations. The data reached an all-time high of 7.000 % in Jul 2020 and a record low of 6.000 % in Jun 2014. Central Bank of Uruguay: Inflation Target: Upper Limit data remains active status in CEIC and is reported by Central Bank of Uruguay. The data is categorized under Global Database’s Uruguay – Table UY.I001: Consumer Price Index: Inflation Target .

Central Bank of Argentina: Inflation Target data was reported at 5.000 % in 2020. This records a decrease from the previous number of 10.000 % for 2019. Central Bank of Argentina: Inflation Target data is updated yearly, averaging 10.000 % from Dec 2018 (Median) to 2020, with 3 observations. The data reached an all-time high of 15.000 % in 2018 and a record low of 5.000 % in 2020. Central Bank of Argentina: Inflation Target data remains active status in CEIC and is reported by Central Bank of Argentina. The data is categorized under Global Database’s Argentina – Table AR.I001: Consumer Price Index: Inflation Target.

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)

Central Bank of Colombia: Inflation Target data was reported at 3.000 % in Mar 2025. This stayed constant from the previous number of 3.000 % for Feb 2025. Central Bank of Colombia: Inflation Target data is updated monthly, averaging 4.000 % from Jan 1993 (Median) to Mar 2025, with 387 observations. The data reached an all-time high of 22.000 % in Dec 1993 and a record low of 3.000 % in Mar 2025. Central Bank of Colombia: Inflation Target data remains active status in CEIC and is reported by Bank of the Republic of Colombia. The data is categorized under Global Database’s Colombia – Table CO.I001: Consumer Price Index: Inflation Target.

ABSTRACT Since the beginning of the Quantitative Theory of Money by David Hume, the relation between money and price level has been analyzed by monetary economists. Nowadays the search for price stability has induced the policymakers to adopt one of three monetary regimes: fixed exchange rate, monetary targeting, or inflation targeting. The present paper makes a comparative analysis among these possibilities highlighting the advantages and disadvantages that belong to each monetary regime.

Consumer Price Indices (CPI) measure changes over time in general level of prices of goods and services that households acquire for the purpose of consumption. CPI numbers are widely used as a macroeconomic indicator of inflation, as a tool by governments and central banks for inflation targeting and for monitoring price stability, and as deflators in the national accounts. CPI is also used for indexing dearness allowance to employees for increase in prices. CPI is therefore considered as one of the most important economic indicators. For construction of CPI numbers, two requisite components are weighting diagrams (consumption patterns) and price data collected at regular intervals. The data refers to group wise all India Consumer Price Index for Rural & Urban with base year 2010. The dataset is published by Central Statistical Office and released on 12th of every month.

Released Under: National Data Sharing and Accessibility Policy (NDSAP).

Contributor: Ministry of Statistics and Programme Implementation.

Domain: Open Government Data (OGD) Platform India.

Source: https://www.data.gov.in/catalog/all-india-consumer-price-index-ruralurban-0

Context

The Federal Reserve sets interest rates to promote conditions that achieve the mandate set by the Congress — high employment, low and stable inflation, sustainable economic growth, and moderate long-term interest rates. Interest rates set by the Fed directly influence the cost of borrowing money. Lower interest rates encourage more people to obtain a mortgage for a new home or to borrow money for an automobile or for home improvement. Lower rates encourage businesses to borrow funds to invest in expansion such as purchasing new equipment, updating plants, or hiring more workers. Higher interest rates restrain such borrowing by consumers and businesses.

Content

This dataset includes data on the economic conditions in the United States on a monthly basis since 1954. The federal funds rate is the interest rate at which depository institutions trade federal funds (balances held at Federal Reserve Banks) with each other overnight. The rate that the borrowing institution pays to the lending institution is determined between the two banks; the weighted average rate for all of these types of negotiations is called the effective federal funds rate. The effective federal funds rate is determined by the market but is influenced by the Federal Reserve through open market operations to reach the federal funds rate target. The Federal Open Market Committee (FOMC) meets eight times a year to determine the federal funds target rate; the target rate transitioned to a target range with an upper and lower limit in December 2008. The real gross domestic product is calculated as the seasonally adjusted quarterly rate of change in the gross domestic product based on chained 2009 dollars. The unemployment rate represents the number of unemployed as a seasonally adjusted percentage of the labor force. The inflation rate reflects the monthly change in the Consumer Price Index of products excluding food and energy.

Acknowledgements

The interest rate data was published by the Federal Reserve Bank of St. Louis' economic data portal. The gross domestic product data was provided by the US Bureau of Economic Analysis; the unemployment and consumer price index data was provided by the US Bureau of Labor Statistics.

Inspiration

How does economic growth, unemployment, and inflation impact the Federal Reserve's interest rates decisions? How has the interest rate policy changed over time? Can you predict the Federal Reserve's next decision? Will the target range set in March 2017 be increased, decreased, or remain the same?

Central Bank of Paraguay: Inflation Target: Upper Limit data was reported at 6.000 % in 2019. This stayed constant from the previous number of 6.000 % for 2018. Central Bank of Paraguay: Inflation Target: Upper Limit data is updated yearly, averaging 6.500 % from Dec 2011 (Median) to 2019, with 9 observations. The data reached an all-time high of 7.500 % in 2013 and a record low of 6.000 % in 2019. Central Bank of Paraguay: Inflation Target: Upper Limit data remains active status in CEIC and is reported by Central Bank of Paraguay. The data is categorized under Global Database’s Paraguay – Table PY.I001: Consumer Price Index: Inflation Target.

Consumer Price Indices (CPI) measure changes over time in general level of prices of goods and services that households acquire for the purpose of consumption. CPI numbers are widely used as a macroeconomic indicator of inflation, as a tool by governments and central banks for inflation targeting and for monitoring price stability, and as deflators in the national accounts. CPI is also used for indexing dearness allowance to employees for increase in prices. CPI is therefore considered as one of the most important economic indicators. For construction of CPI numbers, two requisite components are weighting diagrams (consumption patterns) and price data collected at regular intervals. The data refers to group wise all India Consumer Price Index for Rural & Urban with base year 2010. The dataset is published by Central Statistical Office and released on 12th of every month.

Central Bank of Paraguay: Inflation Target data was reported at 4.000 % in 2019. This stayed constant from the previous number of 4.000 % for 2018. Central Bank of Paraguay: Inflation Target data is updated yearly, averaging 4.500 % from Dec 2011 (Median) to 2019, with 9 observations. The data reached an all-time high of 5.000 % in 2014 and a record low of 4.000 % in 2019. Central Bank of Paraguay: Inflation Target data remains active status in CEIC and is reported by Central Bank of Paraguay. The data is categorized under Global Database’s Paraguay – Table PY.I001: Consumer Price Index: Inflation Target.

ABSTRACT This paper aims to evaluate the performance of the monetary policy of inflation targeting regime in the Latin America countries from 2001 to 2014, with monthly data. For this purpose, a VEC model (vector error correction) is applied to running data to analyze the long-term function and the impulse response function. The results pointed out that the adoption of the target system has contributed to reduce the inflation rate and its volatility and the fluctuations in the rate of growth in activity level. The estimated parameters of the long-term speed of adjustment of the price index have indicated strong reaction by the monetary authorities to change inflation rate via short-term interest rate. These adjustments are also noted in the level of activity and the exchange rate for most countries, but with less level of speed. The impulse response function confirmed these results. Therefore, the monetary policy was effective to control inflation, especially in Peru, Colombia and Chile. In Brazil and Mexico, the effectiveness of monetary policy has only been observed more recently.

The history of inflation in Uruguay has been a constant challenge for the country's economy. Throughout much of the 20th century, Uruguay experienced high levels of inflation, especially in the 1960s and 1970s. Chronic inflation severely affected the purchasing power of citizens and eroded economic stability. However, starting in the 1990s, the country implemented measures to control inflation, including adopting an inflation targeting regime and a more prudent fiscal policy. These measures had a positive impact, achieving a significant reduction in inflation and greater economic stability in Uruguay in recent decades. Although challenges persist, the fight against inflation has been a key objective for the country, aiming to ensure sustainable growth and improve the well-being of its population.

This dataset was generated by the National Institute of Statistic of Uruguay. They are the ones collecting the information to create the Consumer Price Index.

Their web page is: https://www.gub.uy/instituto-nacional-estadistica/datos-y-estadisticas/estadisticas/series-historicas-ipc-base-octubre-2022100

And the name of the original file is: IPC general, Total País (desde 07/1937), Montevideo e Interior (desde 12/2010), base Octubre 2022=100

Consumer Price Indices (CPI) measure changes over time in general level of prices of goods and services that households acquire for the purpose of consumption. CPI numbers are widely used as a macroeconomic indicator of inflation, as a tool by governments and central banks for inflation targeting and for monitoring price stability, and as deflators in the national accounts. CPI is also used for indexing dearness allowance to employees for increase in prices. CPI is therefore considered as one of the most important economic indicators. For construction of CPI numbers, two requisite components are weighting diagrams (consumption patterns) and price data collected at regular intervals. The Central Statistics Office (CSO), Ministry of Statistics and Programme Implementation releases Consumer Price Indices (CPI) on base 2010=100 for all-India and States/UTs separately for rural, urban and combined every month with effect from January, 2011. The data is Published by Central Statistical Office and released on 12th of every month.

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.

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.

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.