This statistic shows the unadjusted annual inflation rate and monetary base growth rate in the United States from 1960 to 2019. Historic data is shown in 3-year increments. In 2019, prices went up by 1.6 percent compared to 2018. In the same time frame, the monetary base decreased by approximately 0.8 percent.
Inflation is generally defined as the continued increase in the average prices of goods and services in a given region. Following the extremely high global inflation experienced in the 1980s and 1990s, global inflation has been relatively stable since the turn of the millennium, usually hovering between three and five percent per year. There was a sharp increase in 2008 due to the global financial crisis now known as the Great Recession, but inflation was fairly stable throughout the 2010s, before the current inflation crisis began in 2021. Recent years Despite the economic impact of the coronavirus pandemic, the global inflation rate fell to 3.26 percent in the pandemic's first year, before rising to 4.66 percent in 2021. This increase came as the impact of supply chain delays began to take more of an effect on consumer prices, before the Russia-Ukraine war exacerbated this further. A series of compounding issues such as rising energy and food prices, fiscal instability in the wake of the pandemic, and consumer insecurity have created a new global recession, and global inflation in 2024 is estimated to have reached 5.76 percent. This is the highest annual increase in inflation since 1996. Venezuela Venezuela is the country with the highest individual inflation rate in the world, forecast at around 200 percent in 2022. While this is figure is over 100 times larger than the global average in most years, it actually marks a decrease in Venezuela's inflation rate, which had peaked at over 65,000 percent in 2018. Between 2016 and 2021, Venezuela experienced hyperinflation due to the government's excessive spending and printing of money in an attempt to curve its already-high inflation rate, and the wave of migrants that left the country resulted in one of the largest refugee crises in recent years. In addition to its economic problems, political instability and foreign sanctions pose further long-term problems for Venezuela. While hyperinflation may be coming to an end, it remains to be seen how much of an impact this will have on the economy, how living standards will change, and how many refugees may return in the coming years.
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Money Supply M2 in the United States increased to 21447.60 USD Billion in November from 21311.20 USD Billion in October of 2024. This dataset provides - United States Money Supply M2 - actual values, historical data, forecast, chart, statistics, economic calendar and news.
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Money Supply M0 in the United States decreased to 5614000 USD Million in February from 5614200 USD Million in January of 2025. This dataset provides - United States Money Supply M0 - actual values, historical data, forecast, chart, statistics, economic calendar and news.
In 2023, the money supply in Vietnam amounted to approximately 10.3 percent, indicating an increase from the previous year. In that year, Vietnam recorded an inflation rate of 3.3 percent.
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This paper investigates the long-run and short-run relationship between money supply and inflation in Pakistan, utilizing annual data spanning from 1981 to 2021. The key objective is to assess the impact of monetary policy, specifically money supply, on inflation dynamics in the country. To achieve this, the Autoregressive Distributed Lag (ARDL) bounds testing approach is employed, which is suitable for analyzing cointegration among variables with mixed integration orders. The results reveal both short and long-run cointegration between inflation, money supply, unemployment, and interest rates. Notably, unemployment demonstrates a negative correlation with inflation, while money supply and interest rates exhibit a positive relationship. These findings underscore the importance of dedicated policy measures to manage inflation effectively. The paper concludes by recommending the establishment of a policy implementation body and collaboration between the government and the central bank to ensure financial stability and control inflation through well-calibrated monetary and fiscal policies.
The Eurozone's money supply has experienced significant growth over the past two decades, with the M2 measure reaching approximately 15.6 trillion euros by the end of 2024. This substantial increase from 4.6 trillion euros in 2001 reflects the expanding monetary base in the euro area. However, 2023 marked a notable deviation from this trend, as it was the first year in the observed period where the money supply in the euro area decreased. Components of money supply M2 is a broader measure of money supply that includes cash, checking deposits, and convertible near money. It encompasses the more narrow M1 measure, which consists of the most liquid components, such as currency in circulation and overnight deposits. As of December 2024, the Eurozone's M1 money supply stood at 10.57 trillion euros, while M2 reached 15.6 trillion euros. These figures are used by central banks to forecast inflation and interest rates, playing a crucial role in shaping monetary policy. Comparison with other regions While the Eurozone has seen steady growth in its money supply, other major economies have experienced their own unique trajectories. In the United States, for instance, the M2 money supply reached 20.86 trillion U.S. dollars in 2023, showing a slight decrease from the previous year. Both the Eurozone and the U.S. saw exceptional increases in their money supply during 2020, largely due to quantitative easing measures implemented in response to the COVID-19 pandemic. This global economic event had a profound impact on monetary policies across different regions, influencing the money supply dynamics worldwide.
In 2023, China’s monetary authority, the People’s Bank of China, issued more than 11.9 trillion yuan which was the highest amount issued in one year so far. Over the past years, the value of printed money increased steadily. The issuing of currency was one function of a central bank.
Maintaining price stability
One of the main policy objectives of the People’s Bank of China was to maintain price stability. Typically, countries set the desired inflation target and the central bank implements the necessary policies to achieve the said target. Usually, China keeps its inflation target at around three percent, but in 2021, the inflation rate dropped to under one percent. If the inflation rate is too low, central banks can issue more currency and decrease the interest rate. In the opposite scenario, if the inflation rate is too high central banks try to reduce the amount of money in circulation by increasing the interest rate or decreasing bond prices.
Managing the economy
In capitalist market economies, economies usually undergo a boom and bust cycle. Central banks attempt to counteract this cyclical development to soften the impact for its citizens. For instance, the Chinese government aims to maintain an unemployment rate of around four percent. However, crises such as the 2008 financial crisis and the outbreak of COVID-19 have an unforseen impact on the economy. To lower the employment rate, the People’s Bank engaged specific monetary policies to stimulate the economy with the aim of increasing job creation.
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The enduring discourse regarding the effectiveness of interest rate policy in mitigating inflation within developing economies is characterized by the interplay of structural and supply-side determinants. Moreover, extant academic literature fails to resolve the direction of causality between inflation and interest rates. Nevertheless, the prevalent adoption of interest rate-based monetary policies in numerous developing economies raises a fundamental inquiry: What motivates central banks in these nations to consistently espouse this strategy? To address this inquiry, our study leverages wavelet transformation to dissect interest rate and inflation data across a spectrum of frequency scales. This innovative methodology paves the way for a meticulous exploration of the intricate causal interplay between these pivotal macroeconomic variables for twenty-two developing economies using monthly data from 1992 to 2022. Traditional literature on causality tends to focus on short- and long-run timescales, yet our study posits that numerous uncharted time and frequency scales exist between these extremes. These intermediate scales may wield substantial influence over the causal relationship and its direction. Our research thus extends the boundaries of existing causality literature and presents fresh insights into the complexities of monetary policy in developing economies. Traditional wisdom suggests that central banks should raise interest rates to combat inflation. However, our study uncovers a contrasting reality in developing economies. It demonstrates a positive causal link between the policy rate and inflation, where an increase in the central bank’s interest rates leads to an upsurge in price levels. Paradoxically, in response to escalating prices, the central bank continues to heighten the policy rate, thereby perpetuating this cyclical pattern. Given this observed positive causal relationship in developing economies, central banks must explore structural and supply-side factors to break this cycle and regain control over inflation.
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Graph and download economic data for Monetary Base: Total (BOGMBASE) from Jan 1959 to Feb 2025 about monetary base and USA.
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Graph and download economic data for Monetary Aggregates and Their Components: Broad Money and Components: M3 for United States (MABMM301USM189S) from Jan 1960 to Nov 2023 about M3, broad, monetary aggregates, and USA.
In January 2025, prices had increased by three percent compared to January 2024 according to the 12-month percentage change in the consumer price index — the monthly inflation rate for goods and services in the United States. The data represents U.S. city averages. In economics, the inflation rate is a measure of the change in price level over time. The rate of decrease in the purchasing power of money is approximately equal. A projection of the annual U.S. inflation rate can be accessed here and the actual annual inflation rate since 1990 can be accessed here. InflationOne of the most important economic indicators is the development of the Consumer Price Index in a country. The change in this price level of goods and services is defined as the rate of inflation. The inflationary situation in the United States had been relatively severe in 2022 due to global events relating to COVID-19, supply chain restrains, and the Russian invasion of Ukraine. More information on U.S. inflation may be found on our dedicated topic page. The annual inflation rate in the United States has increased from 3.2 percent in 2011 to 8.3 percent in 2022. This means that the purchasing power of the U.S. dollar has weakened in recent years. The purchasing power is the extent to which a person has available funds to make purchases. According to the data published by the International Monetary Fund, the U.S. Consumer Price Index (CPI) was about 258.84 in 2020 and is forecasted to grow up to 325.6 by 2027, compared to the base period from 1982 to 1984. The monthly percentage change in the Consumer Price Index (CPI) for urban consumers in the United States was 0.1 percent in March 2023 compared to the previous month. In 2022, countries all around the world are experienced high levels of inflation. Although Brazil already had an inflation rate of 8.3 percent in 2021, compared to the previous year, while the inflation rate in China stood at 0.85 percent.
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Graph and download economic data for Real M2 Money Stock (M2REAL) from Jan 1959 to Feb 2025 about M2, monetary aggregates, real, and USA.
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Money Supply M2 in Argentina decreased to 67420887.80 ARS Million in January from 71460823.70 ARS Million in December of 2024. This dataset provides - Argentina Money Supply M2 - actual values, historical data, forecast, chart, statistics, economic calendar and news.
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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.
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)
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)
Stock price prediction
Portfolio optimization
Algorithmic trading
Market sentiment analysis
Risk management
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
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
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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.
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)
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)
Stock price prediction
Portfolio optimization
Algorithmic trading
Market sentiment analysis
Risk management
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
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
The United States M1 money supply reached approximately 18.45 trillion dollars by January 2025, showing a slight uptick from the previous year. This modest increase follows a period of contraction in late 2022 and early 2023, which stood in stark contrast to the dramatic expansion seen from May 2020 onward. The earlier surge was largely attributed to the Federal Reserve's aggressive quantitative easing measures implemented in response to the economic fallout from the COVID-19 pandemic.
The inflation rate in the United States is expected to decrease to 2.1 percent by 2029. 2022 saw a year of exceptionally high inflation, reaching eight percent for the year. The data represents U.S. city averages. The base period was 1982-84. In economics, the inflation rate is a measurement of inflation, the rate of increase of a price index (in this case: consumer price index). It is the percentage rate of change in prices level over time. The rate of decrease in the purchasing power of money is approximately equal. According to the forecast, prices will increase by 2.9 percent in 2024. The annual inflation rate for previous years can be found here and the consumer price index for all urban consumers here. The monthly inflation rate for the United States can also be accessed here. Inflation in the U.S.Inflation is a term used to describe a general rise in the price of goods and services in an economy over a given period of time. Inflation in the United States is calculated using the consumer price index (CPI). The consumer price index is a measure of change in the price level of a preselected market basket of consumer goods and services purchased by households. This forecast of U.S. inflation was prepared by the International Monetary Fund. They project that inflation will stay higher than average throughout 2023, followed by a decrease to around roughly two percent annual rise in the general level of prices until 2028. Considering the annual inflation rate in the United States in 2021, a two percent inflation rate is a very moderate projection. The 2022 spike in inflation in the United States and worldwide is due to a variety of factors that have put constraints on various aspects of the economy. These factors include COVID-19 pandemic spending and supply-chain constraints, disruptions due to the war in Ukraine, and pandemic related changes in the labor force. Although the moderate inflation of prices between two and three percent is considered normal in a modern economy, countries’ central banks try to prevent severe inflation and deflation to keep the growth of prices to a minimum. Severe inflation is considered dangerous to a country’s economy because it can rapidly diminish the population’s purchasing power and thus damage the GDP .
This paper derives optimal monetary policy rules in setups where certainty equivalence does not hold because either central bank preferences are not quadratic, and/or the aggregate supply relation is nonlinear. Analytical results show that these features lead to sign and size asymmetries, and nonlinearities in the policy rule. Reduced-form estimates indicate that US monetary policy can be characterized by a nonlinear policy rule after 1983, but not before 1979. This finding is consistent with the view that the Fed's inflation preferences during the Volcker-Greenspan regime differ considerably from the ones during the Burns-Miller regime. The file MONTHLY.TXT contains monthly data between 1970.1 and 2000.12 arranged in five columns; the file QUARTERLY.TXT contains quarterly data between 1960.1 and 2000.4 arranged in five columns. The headings OBS, FFRATE, INF, IPI, and UNRATE denote, respectively, the date, Federal Funds rate, CPI inflation rate, Index of Industrial Production, and Unemployment Rate. Additional details can be found the section entitled 3.1 DATA of the paper.
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Money Supply M2 in Canada increased to 2679786 CAD Million in January from 2654380 CAD Million in December of 2024. This dataset provides - Canada Money Supply M2 - actual values, historical data, forecast, chart, statistics, economic calendar and news.
This statistic shows the unadjusted annual inflation rate and monetary base growth rate in the United States from 1960 to 2019. Historic data is shown in 3-year increments. In 2019, prices went up by 1.6 percent compared to 2018. In the same time frame, the monetary base decreased by approximately 0.8 percent.