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.

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.

Source is Federal Reserve Bank of St. Louis. Retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/"NAME OF MEASURE" Column names are "Name of Measure" from FRED's catalog.

Group 1: Yield Curve Indicators These focus on the shape of the Treasury yield curve, comparing longer-term to shorter-term rates. They are primarily used to: Signal Economic Expectations: A normal curve (longer-term rates higher) suggests expectations of growth and possibly inflation. A flattening or inverted curve (short-term rates near or above long-term) could signal a potential slowdown or recession.

Group 2: Monetary Policy and Market Expectations These spreads look at the difference between Treasury yields and the Federal Funds Rate, the primary tool of monetary policy. They indicate: Market vs. Fed Outlook: Widening spreads could suggest the market expects faster rate hikes or higher long-term inflation than the Fed is signaling. Narrowing spreads could mean the opposite. Risk-Taking: When these spreads widen, it can be a sign of investors moving from safe Treasuries to riskier assets in search of yield.

Group 3: Credit Risk and Market Sentiment These spreads focus on corporate bond yields relative to Treasuries, highlighting the added compensation investors require for holding riskier corporate debt. They signal: Credit Conditions: Widening spreads suggest deteriorating credit conditions or lower risk tolerance among investors. Narrowing spreads suggest the opposite. Economic Confidence: Investors often demand higher premiums for corporate bonds during economic uncertainty, widening these spreads.

Group 4: Breakeven Inflation Rates The breakeven inflation rate represents a measure of expected inflation derived from 30-Year Treasury Constant Maturity Securities (BC_30YEAR) and 30-Year Treasury Inflation-Indexed Constant Maturity Securities (TC_30YEAR). The latest value implies what market participants expect inflation to be in the next 30 years, on average.

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:/...

Inflation Rate in the United States increased to 3 percent in September from 2.90 percent in August of 2025. This dataset provides - United States Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

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.

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.

In June 2024, the European Central Bank (ECB) began reducing its fixed interest rate for the first time since 2016, implementing a series of cuts. The rate decreased from 4.5 percent to 3.15 percent by year-end: a 0.25 percentage point cut in June, followed by additional reductions in September, October, and December. The central bank implemented other cuts in the first half of 2025, setting the rate at 2.15 percent in June 2025. This marked a significant shift from the previous rate hike cycle, which began in July 2022 when the ECB raised rates to 0.5 percent and subsequently increased them almost monthly, reaching 4.5 percent by December 2023 - the highest level since the 2007-2008 global financial crisis. How does this ensure liquidity? Banks typically hold only a fraction of their capital in cash, measured by metrics like the Tier 1 capital ratio. Since this ratio is low, banks prefer to allocate most of their capital to revenue-generating loans. When their cash reserves fall too low, banks borrow from the ECB to cover short-term liquidity needs. On the other hand, commercial banks can also deposit excess funds with the ECB at a lower interest rate. Reasons for fluctuations
The ECB’s primary mandate is to maintain price stability. The Euro area inflation rate is, in theory, the key indicator guiding the ECB's actions. When the fixed interest rate is lower, commercial banks are more likely to borrow from the ECB, increasing the money supply and, in turn, driving inflation higher. When inflation rises, the ECB increases the fixed interest rate, which slows borrowing and helps to reduce inflation.

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)

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.

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.

Graph and download economic data for Inflation, consumer prices for the United States (FPCPITOTLZGUSA) from 1960 to 2024 about consumer, CPI, inflation, price index, indexes, price, and USA.

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.

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The raw data that is used in this dataset is the basic OHLC time series dataset for a gold market of the last 20 years collected and verified from different exchanges. This dataset contains over 8677 daily candle prices (rows) and in order to make it wealthy, extra datasets were merged with it to provide more details to each data frame. The sub-datasets contain historical economic information such as interest rates, inflation rates, and others that are highly related and affecting the gold market movement.

Raw dataset:

Time Range: 1988-08-01 to 2023-11-10 Number of data entries: 4050 Number of features: 4 (open, high, low, close OHLC daily candle price)

What are done to prepare this dataset : 1. Starting Exploratory Data Analysis (EDA) for all the raw datasets. 2. Find and fill in missing days. 3. Merge all the datasets into one master dataset based on the time index. 4. Verify the merge process. 5. Check and remove Duplicates. 6. Check and fill in missing values. 7. Including the basic technical indicators and price moving averages. 8. Outliers Inspection and treatment by different methods. 9. Adding targets. 10. Feature Analysis to identify the importance of each feature. 11. Final check.

After data preparation and feature engineering:

Time Range: 1999-12-30 to 2023-10-01

Number of data entries: 8677

Number of featuers: 28

Features list: open, high, low, close (OHLC daily candle price) dxy_open, dxy_close, dxy_high, dxy_low, fred_fedfunds, usintr, usiryy (Ecnomic inducators) RSI, MACD, MACD_signal, MACD_hist, ADX, CCI (Technical indicators) ROC SMA_10, SMA_20, EMA_10, EMA_20, SMA_50, EMA_50, SMA_100, SMA_200, EMA_100, EMA_200 (Moving avrages)

Targets List: next_1_day_price next_3_day_price next_7_day_price next_30_day_price next_1_day_Price_Change next_3_day_Price_Change next_7_day_Price_Change next_30_day_Price_Change next_30_day_Price_Change next_1_day_price_direction( Up, Same ,Down) next_3_day_price_direction( Up, Same ,Down) next_7_day_price_direction( Up, Same ,Down) next_30_day_price_direction( Up, Same ,Down)

Abbreviations of Features: dxy = US Dollar Index fred_fedfunds= Effective Federal Funds Rate usintr= US Interest Rate usiryy= US Inflation Rate YOY RSI= Relative Strength Index MACD= Moving Average Convergence Divergence ADX= Avrerage Directional Index CCI=Commodity Channel Index ROC= Rate of Change SMA= Simple Moving Average EMA= Exponential Moving Average

📂 Dataset Overview - Rows (Entries): 110 - Columns (Features): 6

Columns Description 1. Date - Format: MMM-YYYY (e.g., Jul-2025) - Monthly observations 1. Inflation_YoY (Year-on-Year Inflation %) - Inflation rate in percentage (YoY basis) - Range: 0.3% – 38% - Average: 11.6% - Can be treated as the dependent variable

1. Oil_Price_USD_Barrel
2. Global crude oil price (USD per barrel)
3. Range: 15.18 – 113.77

4. Average: 62.75

5. Exchange_Rate_PKR_USD

• Pakistani Rupee per US Dollar exchange rate
• Range: 104.6 – 304.8
• Average: 185.0

1. Interest_Rate

• State Bank of Pakistan policy rate (%)
• Range: 6.8% – 21.46%
• Average: 11.8%

1. Money_Supply_M2_Billion
2. Broad Money Supply (M2) in billion PKR
3. Range: 12,486 – 41,786
4. Average: 23,124

📊 Statistical Insights

Inflation Trends: High volatility observed between 2019–2023 (peaking at 38%), while in 2025 inflation dropped to ~3–4%.

Oil Price Relation: Fluctuations in crude oil prices appear linked with inflation movements.

Exchange Rate Impact: The depreciation of PKR from ~104 to 300+ significantly impacted inflation and interest rates.

Interest Rate Policy: Mostly ranged between 7–15%, but spiked to ~21% during currency crisis.

Money Supply Growth: Broad money consistently increased, adding long-term inflationary pressure.

📈**Possible Analyses for Kaggle**

1. Trend Analysis

2. Monthly inflation, oil price, exchange rate visualization.

3. Correlation Study

4. Inflation vs Oil Prices

5. Inflation vs Exchange Rate

6. Inflation vs Interest Rate

7. Forecasting Models

8. Time-Series forecasting (ARIMA, Prophet)

9. Regression models using oil prices, exchange rate, and money supply as predictors

10. Economic Insights

• Impact of global oil shocks on Pakistan’s inflation
• Role of monetary policy in inflation control
• Currency depreciation vs domestic inflation

If you find it useful, please upvote

🇹🇷 USD/TRY + the Central Bank of the Republic of Turkey Economic Indicators Dataset

📌 Overview

This dataset brings together key economic indicators published by The Central Bank of the Republic of Turkey (TCMB) via the EVDS API, including:

• The official USD/TRY exchange rate
• Central Bank’s open market operations data (repo rates, funding)
• Inflation expectations and actual CPI index
• FX swap amounts
• TRY interest rates
• Transaction volumes and market sentiment indicators
• Stock market index (BIST100)

All indicators are structured in a time series format, ideal for: - Macroeconomic research - Forecasting exchange rates - Monetary policy analysis - Financial market sentiment modeling

Data was then cleaned, translated into English, and exported as CSV using pandas.

📁 Column Descriptions

📊 Example Use Cases

✅ Time-series forecasting using exchange rate and macro indicators
✅ Relationship modeling: inflation vs. interest rates vs. FX
✅ Macro financial dashboards
✅ Market reaction analysis post-policy announcements
✅ Econometric & deep learning models for policy simulation

Measures of monthly UK inflation data including CPIH, CPI and RPI. These tables complement the consumer price inflation time series dataset.

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.