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Dataset Description
This dataset contains the actual and predicted federal funds target rate for the United States from 1990 to 2023. The federal funds target rate is the interest rate at which depository institutions lend their excess reserves to each other overnight. It is set by the Federal Open Market Committee (FOMC) and is a key tool used by the Federal Reserve to influence the economy.
The dataset includes the following five columns:
Release Date: The date on which the data was released by the Federal Reserve. Time: The time of day at which the data was released. Actual: The actual federal funds target rate. Predicted: The predicted federal funds target rate. Forecast: The forecast federal funds target rate.
Data Usage
This dataset can be used for a variety of purposes, including: - Analyzing trends in the federal funds target rate over time. - Forecasting the future path of the federal funds target rate. - Assessing the effectiveness of monetary policy. - Data Quality
The data for this dataset is of high quality. The Federal Reserve is a reputable source of data and the data is updated regularly.
Data Limitations
The data for this dataset is limited to the United States. Additionally, the data does not include information on the factors that influenced the Federal Open Market Committee's decision to set the federal funds target rate.
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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.
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.
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.
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?
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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.
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The benchmark interest rate in the United States was last recorded at 4 percent. This dataset provides the latest reported value for - United States Fed Funds Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.
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Brazil Federal Funds Rate (Selic): Per Month data was reported at 1.060 % per Month in Apr 2025. This records an increase from the previous number of 0.960 % per Month for Mar 2025. Brazil Federal Funds Rate (Selic): Per Month data is updated monthly, averaging 1.215 % per Month from Jul 1986 (Median) to Apr 2025, with 466 observations. The data reached an all-time high of 82.040 % per Month in Feb 1990 and a record low of 0.130 % per Month in Feb 2021. Brazil Federal Funds Rate (Selic): Per Month data remains active status in CEIC and is reported by Central Bank of Brazil. The data is categorized under Global Database’s Brazil – Table BR.MC002: Lending Rate: Central Bank of Brazil. [COVID-19-IMPACT]
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The benchmark interest rate in Japan was last recorded at 0.50 percent. This dataset provides - Japan Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.
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The benchmark interest rate in Pakistan was last recorded at 11 percent. This dataset provides - Pakistan Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.
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TwitterReal time prices in the diamond market are reflected by the so-called Diamond Financial Index (DFX) which is available on a daily base since April 2018.
As diamond prices are influenced by many factors like trade barriers, political instability, operational disruptions like mine closures or economic downturns resp. upturns, it is not an easy task to predict the development of future diamond prices.
To predict prices, indicators are needed. Empirical findings support the argument that diamond prices respond to economic downturns resp. upturns and are therefore also correlated with inflation rates and interest rates resp. fed rates. Also gold prices could be an indicator for the development of diamond prices.
Because the US are playing quite a big role in the diamond business, the following US rates can be considered:
o inflation rate (10-year breakeven inflation rate) o interest rate (10-year treasury inflation-indexed security, constant maturity, risk-free) o fed rate (effective federal funds rate)
Moreover, gold prices could be considered as an indicator.
The following five datasets have been downloaded from the following websites and merged to one dataset:
o diamond price (DFX): https://www.investing.com/indices/get-diamonds-general o inflation rate: https://fred.stlouisfed.org/series/T10YIE o interest rate: https://fred.stlouisfed.org/series/DFII10 o fed rate: https://fred.stlouisfed.org/series/DFF o gold price: https://www.boerse-online.de/rohstoffe/historisch/goldpreis/usd/
To merge the datasets, date has been used as index. A few missing values in the datasets have been filled in by copying the value from the day before (see file "diamond_data_merged_with_other_variables.csv").
Please note: I added one additional version of the dataset where ID is used as index (not date). Missing values are not filled in in this version (see file "df_diamond_data_merged_with_other_variables.csv"). I would recommend using the dataset "diamond_data_merged_with_other_variables.csv" with date as index.
The following questions could be answered:
o How did diamond prices, inflation rate, interest rate, fed rate and gold price develop since 2018? o How is the correlation between diamond prices and inflation rate, interest rate, fed rate and gold prices? o How will diamond prices develop in the future?
When it comes to price prediction machine learning has been successful in predicting stock market prices through a host of different time series models. There is also a limited but quite restrictive application in predicting cryptocurrency prices. Often neural networks like LSTM (Long Short Term Memory) are used. LSTM oder other models, e.g. ARIMA, could be also used here.
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The benchmark interest rate in Thailand was last recorded at 1.50 percent. This dataset provides - Thailand Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.
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TwitterDespite extensive research interest in the last decade, the banking literature has not reached a consensus on the impact of bank mergers on deposit rates. In particular, results on the dynamics of deposit rates surrounding bank mergers vary substantially across studies. In this paper, we aim for a comprehensive empirical analysis of a bank merger’s impact on deposit rate dynamics. We base the analysis on a unique dataset comprising deposit rates of 624 US banks with a monthly frequency for the time period 1997-2006. These data are matched with individual bank and local market characteristics and the complete list of bank mergers in the US. The data allow us to track the dynamics of bank mergers while controlling for the rigidity of the deposit rates and for a range of merger, bank, and local market features. An innovation of our work is the introduction of an econometric approach for estimating the change of the deposit rates given their rigidity.
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This dataset contains a comprehensive collection of indicators which dictate the housing prices in the United States.
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The benchmark interest rate In the Euro Area was last recorded at 2.15 percent. This dataset provides - Euro Area Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.
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The benchmark interest rate in Mexico was last recorded at 7.25 percent. This dataset provides - Mexico Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.
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The benchmark interest rate in Russia was last recorded at 16.50 percent. This dataset provides the latest reported value for - Russia Interest Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.
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The benchmark interest rate in Turkey was last recorded at 39.50 percent. This dataset provides the latest reported value for - Turkey Interest Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.
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The benchmark interest rate in Brazil was last recorded at 15 percent. This dataset provides - Brazil Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.
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The benchmark interest rate in India was last recorded at 5.50 percent. This dataset provides - India Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.
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The benchmark interest rate in Switzerland was last recorded at 0 percent. This dataset provides - Switzerland Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.
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Graph and download economic data for U.S. Dollars to U.K. Pound Sterling Spot Exchange Rate (DEXUSUK) from 1971-01-04 to 2025-11-28 about United Kingdom, exchange rate, currency, rate, and USA.
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The benchmark interest rate in Germany was last recorded at 4.50 percent. This dataset provides - Germany Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.
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Dataset Description
This dataset contains the actual and predicted federal funds target rate for the United States from 1990 to 2023. The federal funds target rate is the interest rate at which depository institutions lend their excess reserves to each other overnight. It is set by the Federal Open Market Committee (FOMC) and is a key tool used by the Federal Reserve to influence the economy.
The dataset includes the following five columns:
Release Date: The date on which the data was released by the Federal Reserve. Time: The time of day at which the data was released. Actual: The actual federal funds target rate. Predicted: The predicted federal funds target rate. Forecast: The forecast federal funds target rate.
Data Usage
This dataset can be used for a variety of purposes, including: - Analyzing trends in the federal funds target rate over time. - Forecasting the future path of the federal funds target rate. - Assessing the effectiveness of monetary policy. - Data Quality
The data for this dataset is of high quality. The Federal Reserve is a reputable source of data and the data is updated regularly.
Data Limitations
The data for this dataset is limited to the United States. Additionally, the data does not include information on the factors that influenced the Federal Open Market Committee's decision to set the federal funds target rate.