The Economic Indicator Service (EIS) aims to deliver economic content to financial institutions on both buy and sell-side and service providers. This new service currently covers 34,351 recurring macro-economic indicators from 135 countries ( as of December 16, 2019 ) such as GDP data, unemployment releases, PMI numbers etc.

Economic Indicator Service gathers the major economic events from a variety of regions and countries around the globe and provides an Economic Events Data feed and Economic Calendar service to our clients. This service includes all previous historic data on economic indicators that are currently available on the database.

Depending on availability, information regarding economic indicators, including the details of the issuing agency as well as historical data series can be made accessible for the client. Key information about EIS: • Cloud-based service for Live Calendar – delivered via HTML/JavaScript application formats, which can then be embedded onto any website using iFrames • Alternatives methods available – such as API and JSON feed for the economic calendar that can be integrated into the company’s system • Live data – updated 24/5, immediately after the data has been released • Historical data – includes a feed of all previous economic indicators available We are currently adding additional indicators/countries from Africa as well as expanding our coverage of Indicators in G20. The calendar includes the following. • Recurring & Non-recurring indicators covering 136 countries across 21 regions. • Indicators showing high, medium, and low impact data. • Indicators showing actual, previous, and forecast data. • Indicators can be filtered across 16 subtypes. • News generation for selected high-impact data. • Indicator description and historical data up to the latest eight historical points with a chart.

This dataset provides a comprehensive view of global economic trends, combining multiple essential indicators for analysis and research. The data focuses on the period from 2020 to 2023 and includes two key components:

1. GDP Per Capita and Inflation (2020–2023)

Scope: Yearly GDP per capita (in USD) and inflation rates per countries over the four-year period.

1. Population (2023)

Scope: The total population of each country at the end of 2023.

The dataset is meticulously compiled from trusted sources:

GDP per capita and inflation data are sourced from the World Bank national accounts data and OECD National Accounts data files.

Population data is derived from the World Bank Data Catalog (Population Ranking).

Potential Applications

Analyze the impact of inflation on economic growth during and after the pandemic.

Examine relationships between GDP per capita and population size.

Compare economic indicators across countries and regions.

Key Features: Clean, structured, and ready-to-use format.

Country-level granularity for detailed comparisons.

Suitable for trend analysis, visualizations, and predictive modeling.

Licensing: This dataset is licensed under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license. You are free to copy, modify, and distribute the data for any purpose, including commercial use, as long as appropriate credit is given to the World Bank.

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 U.S. Census Bureau.s economic indicator surveys provide monthly and quarterly data that are timely, reliable, and offer comprehensive measures of the U.S. economy. These surveys produce a variety of statistics covering construction, housing, international trade, retail trade, wholesale trade, services and manufacturing. The survey data provide measures of economic activity that allow analysis of economic performance and inform business investment and policy decisions. Other data included, which are not considered principal economic indicators, are the Quarterly Summary of State & Local Taxes, Quarterly Survey of Public Pensions, and the Manufactured Homes Survey. For information on the reliability and use of the data, including important notes on estimation and sampling variance, seasonal adjustment, measures of sampling variability, and other information pertinent to the economic indicators, visit the individual programs' webpages - http://www.census.gov/cgi-bin/briefroom/BriefRm.

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:/...

United States USD Trade Weighted Index: Nominal: Other Important Trading Partner data was reported at 168.237 Jan1997=100 in Nov 2018. This records an increase from the previous number of 166.528 Jan1997=100 for Oct 2018. United States USD Trade Weighted Index: Nominal: Other Important Trading Partner data is updated monthly, averaging 96.825 Jan1997=100 from Jan 1973 (Median) to Nov 2018, with 551 observations. The data reached an all-time high of 168.237 Jan1997=100 in Nov 2018 and a record low of 1.998 Jan1997=100 in Jul 1973. United States USD Trade Weighted Index: Nominal: Other Important Trading Partner data remains active status in CEIC and is reported by Federal Reserve Board. The data is categorized under Global Database’s United States – Table US.M016: US Dollar Trade Weighted Index.

United States Loan Officer Survey: SIP: Very Important data was reported at 18.200 % in Apr 2018. This records an increase from the previous number of 13.300 % for Jan 2018. United States Loan Officer Survey: SIP: Very Important data is updated quarterly, averaging 1.850 % from Jan 2008 (Median) to Apr 2018, with 42 observations. The data reached an all-time high of 33.300 % in Jul 2016 and a record low of 0.000 % in Jul 2017. United States Loan Officer Survey: SIP: Very Important data remains active status in CEIC and is reported by Federal Reserve Board. The data is categorized under Global Database’s USA – Table US.KA037: Senior Loan Officer Opinion Survey: Reason for Strong Demand for Commercial & Industrial Loans. Senior Loan Officer Survey Questionnaire: If demand for C&I loans has strengthened over the past three months, how important have been the increase in investment in plant or equipment on the possible reason of change?

United States Loan Officer Survey: SGF: Very Important data was reported at 10.000 % in Apr 2018. This records an increase from the previous number of 0.000 % for Jan 2018. United States Loan Officer Survey: SGF: Very Important data is updated quarterly, averaging 0.000 % from Jan 2008 (Median) to Apr 2018, with 42 observations. The data reached an all-time high of 20.000 % in Oct 2008 and a record low of 0.000 % in Jan 2018. United States Loan Officer Survey: SGF: Very Important data remains active status in CEIC and is reported by Federal Reserve Board. The data is categorized under Global Database’s USA – Table US.KA037: Senior Loan Officer Opinion Survey: Reason for Strong Demand for Commercial & Industrial Loans. Senior Loan Officer Survey Questionnaire: If demand for C&I loans has strengthened over the past three months, how important have been the decrease in customer generated funds on the possible reason of change?

Dataset Overview:

This dataset offers a comprehensive time series analysis of three vital economic indicators in the United States: Gross Domestic Product (GDP), Unemployment Rate, and Consumer Price Index (CPI). Spanning from January 1974 to January 2024, this dataset provides valuable insights into the U.S. economy over the past five decades, capturing periods of growth, recession, and inflation.

Contents:

• GDP Data (gdp_data.csv): Quarterly data on the Gross Domestic Product, measured in billions of dollars, highlighting economic performance and trends over the years.
• Unemployment Data (unemployment_data.csv): Monthly data on the unemployment rate, showing fluctuations in labor market conditions and workforce participation over time.
• CPI Data (cpi_data.csv): Monthly data on the Consumer Price Index for All Urban Consumers (CPI-U), capturing changes in the price level of consumer goods and services and reflecting inflationary trends.

Usage and Applications:

• Economic History Analysis: Examine long-term trends and cycles in U.S. economic performance, including periods of recession and expansion.
• Predictive Modeling: Develop models to forecast future economic conditions based on historical data patterns.
• Policy Impact Studies: Analyze the effects of fiscal and monetary policies on GDP, unemployment, and inflation over time.

Data Sources:

The dataset is sourced from the Federal Reserve Economic Data (FRED) database, maintained by the Federal Reserve Bank of St. Louis. FRED is a comprehensive resource for economic data, widely used by researchers, analysts, and policymakers.

How to Use the Dataset:

• Exploration: Utilize tools like Pandas and Matplotlib in Python to explore and visualize the dataset.
• Time Series Analysis: Apply techniques such as ARIMA, exponential smoothing, and seasonal decomposition to analyze trends and seasonality.
• Comparative Studies: Compare economic performance across different decades and investigate interactions between GDP, unemployment, and CPI.

Note: This dataset is intended for educational and research purposes. Users are encouraged to cite the original data source (FRED) when using this dataset in publications or presentations.

United States Loan Officer Survey: SLA: Very Important data was reported at 0.000 % in Apr 2018. This records a decrease from the previous number of 14.300 % for Jan 2018. United States Loan Officer Survey: SLA: Very Important data is updated quarterly, averaging 12.350 % from Jan 2008 (Median) to Apr 2018, with 42 observations. The data reached an all-time high of 73.300 % in Oct 2008 and a record low of 0.000 % in Apr 2018. United States Loan Officer Survey: SLA: Very Important data remains active status in CEIC and is reported by Federal Reserve Board. The data is categorized under Global Database’s USA – Table US.KA037: Senior Loan Officer Opinion Survey: Reason for Strong Demand for Commercial & Industrial Loans. Senior Loan Officer Survey Questionnaire: If demand for C&I loans has strengthened over the past three months, how important have been the increase in customer borrowing shifted to your bank from other bank or non bank sources because these other sources became less attractive on the possible reason of change?

Short-term business statistics (STS) give information on a wide range of economic activities. All STS data are index data. Additionally, annual absolute values are released for building permits indicators. Percentage changes are also available for each indicator: Infra-annual percentage changes - changes between two consecutive months or quarters - are calculated on the basis of non-adjusted data (prices) or calendar and seasonally adjusted data (volume and value indicators) and year-on-year changes - comparing a period to the same period one year ago - are calculated on the basis of non-adjusted data (prices and employment) or calendar adjusted data (volume and value indicators).

The index data are generally presented in the following forms:

• unadjusted
• calendar adjusted
• calendar and seasonally adjusted.

Depending on the EBS Regulation data are accessible as monthly, quarterly and annual data.

The STS indicators are listed below in five different sectors, reflecting the dissemination of these data in Eurostat’s online database “Eurobase”.

Based on the national data, Eurostat compiles short-term indicators for the EU and euro area. Among these, a list of indicators, called Principal European Economic Indicators (PEEIs) has been identified by key users as being of primary importance for the conduct of monetary and economic policy of the euro area. The PEEIs contributed by STS are marked with * in the text below.

The euro indicators are released through Eurostat's website.

INDUSTRY

• production (volume)*
• turnover: Total, Domestic market and Non-domestic market. A further breakdown of the non-domestic turnover into euro area and non-euro area is available for the euro area countries.
• producer prices (output prices)*: Total, Domestic market and Non-domestic market. A further breakdown of the non-domestic producer prices into euro area and non-euro area is available for the euro area countries.
• import prices*: Total, euro area market, Non euro area market (euro area countries only)
• labour input indicators: Number of employees and self-employed persons, Hours worked by employees, Gross wages and salaries

CONSTRUCTION

• production (volume)*
• building permits indicators*: number of dwellings, square meters of useful floor
• producer (output) prices in construction (if not available, they can be approximated by the construction costs variable)
• labour input indicators: number of employees and self-employed persons, hours worked by employees, gross wages and salaries

TRADE

• volume of sales (deflated turnover)*
• turnover (value)
• labour input indicators: number of employees and self-employed persons, hours worked by employees, gross wages and salaries

SERVICES

• production (volume)*
• turnover (in value)
• labour input indicators: number of employees and self-employed persons, hours worked by employees, gross wages and salaries
• producer prices (output prices)*

MARKET ECONOMY

• total market production (volume)
• registrations
• bankruptcies

National reference metadata of the reporting countries are available in the Annexes to this metadata file.

Graph and download economic data for Number of Large Domestic Banks That Tightened and Reported That Less Favorable Economic Outlook Was a Very Important Reason (SUBLPDCIRTOVLGNQ) from Q3 1990 to Q4 2025 about large, domestic, banks, depository institutions, and USA.

United States Loan Officer Survey: WGF: Other Banks: Very Important data was reported at 0.000 % in Apr 2018. This records a decrease from the previous number of 100.000 % for Jan 2018. United States Loan Officer Survey: WGF: Other Banks: Very Important data is updated quarterly, averaging 0.000 % from Jan 2008 (Median) to Apr 2018, with 42 observations. The data reached an all-time high of 100.000 % in Jan 2018 and a record low of 0.000 % in Apr 2018. United States Loan Officer Survey: WGF: Other Banks: Very Important data remains active status in CEIC and is reported by Federal Reserve Board. The data is categorized under Global Database’s USA – Table US.KA038: Senior Loan Officer Opinion Survey: Reason for Weak Demand for Commercial & Industrial Loans. Senior Loan Officer Survey Questionnaire: If demand for C&I loans has weakened over the past three months, how important have been the increase in customer generated funds on the possible reason of change?

Explore the latest data on Bahrain's oil and non-oil sector GDP at current and constant prices. Gain insights into key economic indicators such as Net Exports, Gross Domestic Saving, and GNI per capita. Access the dataset now!

Net Current Transfer From Abroad, Oil sector GDP, Oil sector % of GDP, Total Final Consumption : Government, Total Final Consumption : Government (Annual Growth), Constant prices, GNDI Per capita (BD), Total Final Consumption : Private (Annual Growth), Total Final Consumption, Net Primary Income and Current Transfer (as % of GDP), Government % of GDP, Non-oil sector % of GDP, Change in Stocks, Population, Gross Fixed Capital Formation : Government, GDP per capita (BD), Gross National Disposable Income (GNDI), Domestic Saving, Gross (% of GDP), Gross Domestic Product (GDP), National Saving, Gross (% of GDP), Net Exports Goods & Services (% of GDP), Gross Fixed Capital Formation : Private, Current Prices, Total Final Consumption % of GDP, Domestic Saving, Gross, Non-oil sector GDP, Total Final Consumption (Annual Growth), Imports of Goods & Services, Oil sector (Annual Growth), National Saving, Gross, GNI per capita (BD), Non-oil sector (Annual Growth), Total Final Consumption : Private, Gross Fixed Capital Formation : Government (% of GDP), Gross Fixed Capital Formation : Private (% of GDP), Net Exports of Goods & Services, Gross National Income (GNI), Private % of GDP, Gross Fixed Capital Formation, Imports of Goods & Services (% of GDP), Gross Fixed Capital Formation (% of GDP), Exports of Goods & Services (% of GDP), Net Lending/Borrowing, BD Million, %, Exports of Goods & Services, Net Primary Income from Abroad, National Accounts, Oil Sector, Non-oil, final consumption, GFCF, exports, imports, Gross Domestic Saving, Gross National Saving, Per capita, GNI, GDI, lending, borrowing, Current prices, Constant prices, Bahrain National Accounts Annual Report

BahrainFollow data.kapsarc.org for timely data to advance energy economics research..

Macroeconomic data is an important source for both institutions and companies to have a rough sense of what government's policies and economy will head to. This dataset can help macroeconomic and fundamental analysts to do research on Chinese market or macroeconomics. Quantitative researchers can also use this dataset as a reference to assist them making better strategies. The SHIBOR rate of different maturities is recorded at daily frequency. Users can construct the yield curve for economic research. Quantitative researchers can use it to see how SHIBOR influences the overall Chinese stock & fixed income market and etc. Many Chinese Indices are also very important in conducting research about Chinese market & economy. These data are also at daily frequency. Other macroeconomic data are recorded in monthly frequency and thus can be used to conduct broader area of economic and financial research and etc.

The report covers the most recently available economic, financial, social, and environmental indicators for the 50 regional members of Asian Development Bank. It discusses trends in development progress and the challenges of achieving inclusive and sustainable economic growth across Asia and the Pacific. This 56th edition also explores how harmonized environmental-economic data can serve as a public good for guiding cooperation toward resilient, sustainable development.

Dataset from Economic Development Board. For more information, visit https://data.gov.sg/datasets/d_3d5e132e513b95c500ff006cdf96c86e/view

This app contains the latest 14 months of unemployment statistics from the U.S. Bureau of Labor Statistics (BLS). The data is offered at the nationwide, state, and county geography levels. Puerto Rico is included. These are not seasonally adjusted values. The layer is updated monthly with the newest unemployment statistics available from BLS. There are attributes in the layer that specify which month is associated to each statistic. Most current month: March 2021 (preliminary values at the state and county level)The attributes included for each month are:Unemployment rate (%)Count of unemployed populationCount of employed population in the labor forceCount of people in the labor forceData obtained from the U.S. Bureau of Labor Statistics. Local Area Unemployment Statistics table download: https://www.bls.gov/lau/#tablesLocal Area Unemployment FTP downloads:State and CountyNationData Notes:This layer is updated automatically when the BLS releases their most current monthly statistics. The layer always contains the most recent estimates. It is updated within days of the BLS's county release schedule. BLS releases their county statistics roughly 2 months after-the-fact. The data is joined to 2019 TIGER boundaries from the U.S. Census Bureau.Monthly values are subject to revision over time.For national values, employed plus unemployed may not sum to total labor force due to rounding.To better understand the different labor force statistics included in this map, see the diagram below from BLS:Esri's U.S. Updated Demographic Data - Population, age, income, sex, race, home value, and marital status are among the variables included in the database. Each year, Esri's Data Development team employs its proven methodologies to update more than 2,000 demographic variables for a variety of U.S. geographies.Data Note: The median household income value divides the distribution of household income into two equal parts. Pareto interpolation is used if the median falls in an income interval other than the first or last. For the lowest interval, <$10,000, linear interpolation is used. If the median falls in the upper income interval of $500,000+, it is represented by the value of $500,001. Additional Esri Resources:Esri DemographicsU.S. 2020/2025 Esri Updated DemographicsEssential demographic vocabularyPermitted use of this data is covered in the DATA section of the Esri Master Agreement (E204CW) and these supplemental terms.

Italy's Gross Domestic Product (GDP) amounted to 2.2 trillion euros in 2024. The Italian economy grew at low rates between 2010 and 2019 and significantly shrank in 2020 following the consequences of the COVID-19 pandemic on the global economy. However, since 2021, GDP has recorded a steady uprise, with remarkably higher growth rates compared to the pre-pandemic period. A difficult outlook for the Italian economy Besides the positive performance recorded right after the COVID-19 pandemic, projections indicate a different outlook. The slow growth of the Italian economy, less than one percent each year from 2025 to 2029, is believed to remove Italy from the giants of the global players. Indeed, by 2028, the ranking of the world's largest economies might appear quite different from the present one. In addition to slow growth, Italy's economy is characterized by large internal disparities. After 160 years of national unity, the country is still very divided, as data on unemployment, GDP, and poverty confirm. National debt: Italy's most difficult challenge Italy still ranks among the top 20 largest economies in the world. However, the large amount of the national debt risks hampering future growth. In 2024, it reached 135 percent of the GDP, equivalent to 3.2 trillion U.S. dollars, and forecasts expect figures to increase over the coming years. By 2029, the debt-to-GDP ratio may hit 137 percent. A large amount of national debt significantly limits the government's possibility to earmark resources for public investments. In fact, a considerable share of the state budget is devoted to reimbursing the debt.

This dataset, identified by the series ID RSXFS, is sourced from the U.S. Census Bureau and is available through the Federal Reserve Economic Data (FRED) system of the St. Louis Fed. It provides a monthly measure of retail sales across the United States. The data represents the total value of sales at retail and food services stores, measured in millions of dollars and adjusted for seasonal variations. It is important to note that the most recent month's value is an advance estimate, which is subject to revision in subsequent months as more comprehensive data becomes available. As a key economic indicator, this series is widely used by economists and analysts to gauge consumer spending and assess the overall health of the U.S. economy.

Suggested Use Cases: - This dataset is highly valuable for economic analysis and can be used to: - Conduct time series analysis and modeling. - Track consumer spending patterns. - Forecast future retail sales. - Analyze the impact of economic events on the retail sector.

License The RSXFS dataset is sourced from the U.S. Census Bureau and is considered Public Domain: Citation Requested. This means the data is freely available for use, but you must cite the source and acknowledge that the data was obtained from FRED. If you plan on using any copyrighted series from other data providers on FRED for commercial purposes, you would need to contact the original data owner for permission.

Data Fields: The dataset primarily contains two columns: - observation_date: The date of the monthly data point, recorded as the first day of each month from January 1992 to July 2025. - RSXFS: The value of advance retail sales in millions of dollars.

Citation and Provenance:
Source: U.S. Census Bureau
Release: Advance Monthly Sales for Retail and Food Services
FRED Link: https://fred.stlouisfed.org/series/RSXFS
Citation: U.S. Census Bureau, Advance Retail Sales: Retail Trade [RSXFS], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/RSXFS, September 8, 2025.