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.

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?

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.

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.

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:/...

Monthly and long-term United States Interest Rate data: historical series and analyst forecasts curated by FocusEconomics.

The benchmark interest rate in Sweden was last recorded at 1.75 percent. This dataset provides the latest reported value for - Sweden Interest Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

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.

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.

Description:

This dataset provides key economic indicators from various countries between 2010 and 2023. The dataset includes monthly data on inflation rates, GDP growth rates, unemployment rates, interest rates, and stock market index values. The data has been sourced from reputable global financial institutions and is suitable for economic analysis, machine learning models, and forecasting economic trends.

Data Sources:

The data has been generated to simulate real-world economic conditions, mimicking information from trusted sources like: - World Bank for GDP growth and inflation data - International Monetary Fund (IMF) for macroeconomic data - OECD for labor market statistics - National Stock Exchanges for stock market index values

Columns:

1. Date: The specific date (in Year/Month/Day format) representing when the data was collected.
2. Country: The country the data pertains to (e.g., USA, Germany, Japan).
3. Inflation Rate (%): The rate of inflation for that country, showing how fast prices for goods and services are increasing.
4. GDP Growth Rate (%): The percentage growth of the country’s Gross Domestic Product (GDP), indicating economic expansion or contraction.
5. Unemployment Rate (%): The percentage of the working-age population that is unemployed.
6. Interest Rate (%): The central bank's interest rate, used to control inflation and influence the economy.
7. Stock Index Value: The value of the country’s main stock market index, reflecting the performance of the stock market.

Potential Uses: - Economic Analysis: Researchers and analysts can use this dataset to study trends in inflation, GDP growth, unemployment, and other economic factors. - Machine Learning: This dataset can be used to train models for predicting economic trends or market performance. Financial Forecasting: Investors and economists can leverage this data for forecasting market movements based on economic conditions. - Comparative Studies: The dataset allows comparisons across countries and regions, offering insights into global economic performance.

Monthly and long-term Japan Interest Rate data: historical series and analyst forecasts curated by FocusEconomics.

This dataset includes various economic indicators such as stock market performance, inflation rates, GDP, interest rates, employment data, and housing index, all of which are crucial for understanding the state of the economy. By analysing this dataset, one can gain insights into the causes and effects of past recessions in the US, which can inform investment decisions and policy-making.

There are 20 columns and 343 rows spanning 1990-04 to 2022-10

The columns are:

1. Price: Price column refers to the S&P 500 lot price over the years. The S&P 500 is a stock market index that measures the performance of 500 large companies listed on stock exchanges in the United States. This variable represents the value of the S&P 500 index from 1980 to present. Industrial Production: This variable measures the output of industrial establishments in the manufacturing, mining, and utilities sectors. It reflects the overall health of the manufacturing industry, which is a key component of the US economy.

2. INDPRO: Industrial production measures the output of the manufacturing, mining, and utility sectors of the economy. It provides insights into the overall health of the economy, as a decline in industrial production can indicate a slowdown in economic activity. This data can be used by policymakers and investors to assess the state of the economy and make informed decisions.

3. CPI: CPI stands for Consumer Price Index, which measures the change in the prices of a basket of goods and services that consumers purchase. CPI inflation represents the rate at which the prices of goods and services in the economy are increasing.

4. Treasure Bill rate (3 month to 30 Years): Treasury bills (T-bills) are short-term debt securities issued by the US government. This variable represents the interest rates on T-bills with maturities ranging from 3 months to 30 years. It reflects the cost of borrowing money for the government and provides an indication of the overall level of interest rates in the economy.

5. GDP: GDP stands for Gross Domestic Product, which is the value of all goods and services produced in a country. This dataset is taking into account only the Nominal GDP values. Nominal GDP represents the total value of goods and services produced in the US economy without accounting for inflation.

6. Rate: The Federal Funds Rate is the interest rate at which depository institutions lend reserve balances to other depository institutions overnight. It is set by the Federal Reserve and is used as a tool to regulate the money supply in the economy.

7. BBK_Index: The BBKI are maintained and produced by the Indiana Business Research Center at the Kelley School of Business at Indiana University. The BBK Coincident and Leading Indexes and Monthly GDP Growth for the U.S. are constructed from a collapsed dynamic factor analysis of a panel of 490 monthly measures of real economic activity and quarterly real GDP growth. The BBK Leading Index is the leading subcomponent of the cycle measured in standard deviation units from trend real GDP growth.

8. Housing Index: This variable represents the value of the housing market in the US. It is calculated based on the prices of homes sold in the market and provides an indication of the overall health of the housing market.

9. Recession binary column: This variable is a binary indicator that takes a value of 1 when the US economy is in a recession and 0 otherwise. It is based on the official business cycle dates provided by the National Bureau of Economic Research.

Financial Access and Usage

Global Comparative Ratios Across 189 Jurisdictions

By International Monetary Fund [source]

About this dataset

This dataset provides an unprecedented opportunity to explore global financial access and usage trends from 2004-2016 from 189 of the world's reporting jurisdictions—which cover over 99 percent of the total adult population. With 152 time series and 47 indicator ratios, this Financial Access Survey gives insight into ways that access to and usage of financial services differ by households vs small/medium enterprises, life vs non-life insurance, deposits & microfinance institutions as well as credit unions & financial cooperatives. Utilizing this data, we can gain a better understanding of how policies or shifts in the global economy may influence or relate to access or utilization of services in certain regions while having comparable cross-economy comparisons. The IMF Monetary and Financial Statistics Manual Compilation Guide is utilized for all methodologies used in accumulating these datasets, while all data is available “as-is” with no guarantee provided either express or implied. Are you looking for ways to implement insightful macroeconomic analyses? Download FAS 2004–2016 now!

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For more datasets, click here.

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How to use the dataset

The Financial Access Survey provides global supply-side data on access to and usage of financial services by households and firms for 189 reporting jurisdictions, covering 99 percent of the world’s adult population. With a robust selection of time series in this dataset, users can make meaningful insights into trends over time or across countries concerning various indicators related to access and usage of financial services. To help users navigate this large dataset, the following guide explains how to use the data most effectively.

Understanding The Dataset Columns

The columns in the dataset provide information about each indicator such as country name, indicator name, code for that indicator, its attribute (i.e., rate/ratio), when data is available for that particular indicator. Once you have identified an interesting measure/indicator whether it be credit union density or life insurance penetration rate measure in a given country during a certain year period then you can look up those numbers from the rows provided in this dataset .

Understanding The Different Years Available & Comparing Numbers Over Time

It is useful for users to compare different indicators over time by looking at specific years within this dataset which will allow us to see if rates are increasing or decreasing worldwide patterns across these trends among different countries based on these various measures listed provided in this survey such as mortgage lending rate or ratio GDP per capita etc that have been collected . We can therefore make use of our knowledge off economic changes that have occurred over time within certain parts of world , no matter if they are longer term economic effects due increases certain capabilities within a geographical area or shorter term changes due taxation laws by governments etc driving some people either towards using or away from using certain kinds financial products .

#### Comparing Between Countries

This datasets allows us direct comparisons between different countries with regards how many people are currently making use particular types off finances services , we certainly be able analyse current international relationships between services providers as well customers where ever concerned about particular attributes mentioned above whether being deposit interest rates small business credits terms tenders so forth . Knowing more about related dynamics helps build better user experiences with providers who understand needs risks impacts generating larger customer bases globally which often beneficial both parties involved exchange relationship so not forget always keep cross border motif whenever eye process from afar !

Research Ideas

• Comparing the access to and usage of financial services in different countries to better inform research policy decisions.
• Analyzing trends in financial access and usage by jurisdiction over time, to identify areas needing improvement in order to promote financial inclusion and stability.
• Cross-referencing FAS data with macroeconomic indicators such as GDP information to measure the potential impact of changes in level of access on economic growth or other metrics specific to a country or region of interest

Acknowledgements

If you use this dataset in yo...

Monthly and long-term Argentina Interest Rate data: historical series and analyst forecasts curated by FocusEconomics.

The benchmark interest rate in the United Kingdom was last recorded at 4 percent. This dataset provides - United Kingdom Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Monthly and long-term Brazil Interest Rate data: historical series and analyst forecasts curated by FocusEconomics.

Monthly and long-term India Interest Rate data: historical series and analyst forecasts curated by FocusEconomics.

Nepal NP: Real Interest Rate data was reported at -6.207 % pa in 2010. This records an increase from the previous number of -6.823 % pa for 2009. Nepal NP: Real Interest Rate data is updated yearly, averaging 3.657 % pa from Dec 1975 (Median) to 2010, with 29 observations. The data reached an all-time high of 18.214 % pa in 1977 and a record low of -12.173 % pa in 1975. Nepal NP: Real Interest Rate data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Nepal – Table NP.World Bank.WDI: Interest Rates. Real interest rate is the lending interest rate adjusted for inflation as measured by the GDP deflator. The terms and conditions attached to lending rates differ by country, however, limiting their comparability.; ; International Monetary Fund, International Financial Statistics and data files using World Bank data on the GDP deflator.; ;

Context

Interest rates are rising! I thought it would be interesting to see how this compares with historical data.

Content

Simple csv file with 2 columns: date changed and interest rate.

Acknowledgements

Data was collected from the Bank of England website.

FocusEconomics' economic data is provided by official state statistical reporting agencies as well as our global network of leading banks, think tanks and consultancies. Our datasets provide not only historical data, but also Consensus Forecasts and individual forecasts from the aformentioned global network of economic analysts. This includes the latest forecasts as well as historical forecasts going back to 2010. Our global network consists of over 1000 world-renowned economic analysts from which we calculate our Consensus Forecasts. In this specific dataset you will find economic data for Japan Interest Rate.