In 2024, the finance, insurance, real estate, rental, and leasing industry contributed the highest amount of value to the GDP of the U.S. at 21.2 percent. The construction industry contributed around four percent of GDP in the same year.

United States US: GDP: Growth: Gross Value Added: Services data was reported at 2.621 % in 2015. This records an increase from the previous number of 2.221 % for 2014. United States US: GDP: Growth: Gross Value Added: Services data is updated yearly, averaging 2.335 % from Dec 1998 (Median) to 2015, with 18 observations. The data reached an all-time high of 4.456 % in 1999 and a record low of -1.772 % in 2009. United States US: GDP: Growth: Gross Value Added: Services data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Gross Domestic Product: Annual Growth Rate. Annual growth rate for value added in services based on constant local currency. Aggregates are based on constant 2010 U.S. dollars. Services correspond to ISIC divisions 50-99. They include value added in wholesale and retail trade (including hotels and restaurants), transport, and government, financial, professional, and personal services such as education, health care, and real estate services. Also included are imputed bank service charges, import duties, and any statistical discrepancies noted by national compilers as well as discrepancies arising from rescaling. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The industrial origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 3.; ; World Bank national accounts data, and OECD National Accounts data files.; Weighted Average; Note: Data for OECD countries are based on ISIC, revision 4.

In 2024, the finance, real estate, insurance, rental, and leasing industry added the most value to the GDP of the United States. In that year, this industry added 6.2 trillion U.S. dollars to the national GDP. Gross Domestic Product Gross domestic product is a measure of how much a country produces in a certain amount of time. Countries with a high GDP tend to have large economies, for example, the United States. However, GDP does not take into consideration the cost of living and inflation rates, so it is not a good measure of the standard of living. GDP per capita at purchasing power parity is thought to be more reflective of living conditions within a particular country. U.S. GDP California added the largest amount of value to the real GDP of the U.S. in 2022. California was followed by Texas and New York. In California, the professional and business services industry was the most valuable to GDP in 2022. In New York, the finance, insurance, real estate, rental, and leasing industry added the most value to the state GDP. While the business sector added the highest value to the U.S. real GDP in 2021, it was the information industry that had the biggest percentage change in value added to the GDP between 2010 and 2021.

Graph and download economic data for Nominal Gross Domestic Product for United States (NGDPSAXDCUSQ) from Q1 1950 to Q2 2025 about GDP and USA.

This dataset contains historical quarterly data for the U.S. Real Gross Domestic Product, from the first quarter of 1947 to the Q2 2023. Real GDP is an inflation-adjusted measure that reflects the value of all goods and services produced by an economy in a given year, expressed in base-year prices, and is often considered an indicator of a country's standard of living.

The dataset has two columns:

Date: The end of the respective quarter (in MM/DD/0YYYY format). Value: The Real GDP at the end of the respective quarter.

Inspiration: Real GDP is a comprehensive measure of U.S. economic activity and a key tool for economic decision-making and forecasting. Real GDP is used by economists, policy-makers, researchers, and investors to understand the growth and performance of the U.S. economy over time.

Usability: The Real GDP data can be used for a variety of purposes:

Economic Analysis: It can be used for macroeconomic analysis and forecasting. Policy Understanding: It can help understand the impact and effectiveness of economic policies implemented by the U.S. government. Investment Analysis: GDP growth impacts financial markets, and this data can help investors understand and forecast market trends. Education: It can be used in classrooms for teaching economics, finance, and related disciplines.

This statistic presents data regarding the digital economy as percentage of the total economy (GDP) in the United States from 2005 to 2018. During the most recently measured period, the digital economy accounted for nine percent of current-dollar value added to the overall U.S. economy. In 2018, the GDP of the United States amounted to 20.58 trillion U.S. dollars with a digital economy value added of 1.85 trillion U.S. dollars.

United States US: GDP: % of Manufacturing: Medium and High Tech Industry data was reported at 41.166 % in 2015. This stayed constant from the previous number of 41.166 % for 2014. United States US: GDP: % of Manufacturing: Medium and High Tech Industry data is updated yearly, averaging 49.199 % from Dec 1990 (Median) to 2015, with 26 observations. The data reached an all-time high of 51.786 % in 1998 and a record low of 38.398 % in 1996. United States US: GDP: % of Manufacturing: Medium and High Tech Industry data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Gross Domestic Product: Share of GDP. The proportion of medium and high-tech industry value added in total value added of manufacturing; ; United Nations Industrial Development Organization (UNIDO), Competitive Industrial Performance (CIP) database; ;

United States US: GDP: % of GDP: Gross Value Added: Industry: Manufacturing data was reported at 11.601 % in 2016. This records a decrease from the previous number of 11.919 % for 2015. United States US: GDP: % of GDP: Gross Value Added: Industry: Manufacturing data is updated yearly, averaging 12.807 % from Dec 1997 (Median) to 2016, with 20 observations. The data reached an all-time high of 16.022 % in 1997 and a record low of 11.601 % in 2016. United States US: GDP: % of GDP: Gross Value Added: Industry: Manufacturing data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Gross Domestic Product: Share of GDP. Manufacturing refers to industries belonging to ISIC divisions 15-37. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 3. Note: For VAB countries, gross value added at factor cost is used as the denominator.; ; World Bank national accounts data, and OECD National Accounts data files.; Weighted average; Note: Data for OECD countries are based on ISIC, revision 4.

The United States gross domestic product (GDP) was forecast to reach over 30.1 trillion U.S. dollars in 2025. Furthermore, by 2035, it is expected to surpass 43.9 trillion U.S. dollars. GDP refers to the market value of all final goods and services produced within a country in a given period.

Out of all 50 states, New York had the highest per-capita real gross domestic product (GDP) in 2024, at 92,341 U.S. dollars, followed closely by Massachusetts. Mississippi had the lowest per-capita real GDP, at 41,603 U.S. dollars. While not a state, the District of Columbia had a per capita GDP of more than 210,780 U.S. dollars. What is real GDP? A country’s real GDP is a measure that shows the value of the goods and services produced by an economy and is adjusted for inflation. The real GDP of a country helps economists to see the health of a country’s economy and its standard of living. Downturns in GDP growth can indicate financial difficulties, such as the financial crisis of 2008 and 2009, when the U.S. GDP decreased by 2.5 percent. The COVID-19 pandemic had a significant impact on U.S. GDP, shrinking the economy 2.8 percent. The U.S. economy rebounded in 2021, however, growing by nearly six percent. Why real GDP per capita matters Real GDP per capita takes the GDP of a country, state, or metropolitan area and divides it by the number of people in that area. Some argue that per-capita GDP is more important than the GDP of a country, as it is a good indicator of whether or not the country’s population is getting wealthier, thus increasing the standard of living in that area. The best measure of standard of living when comparing across countries is thought to be GDP per capita at purchasing power parity (PPP) which uses the prices of specific goods to compare the absolute purchasing power of a countries currency.

United States US: GDP: PPP data was reported at 19,390,604.000 Intl $ mn in 2017. This records an increase from the previous number of 18,624,475.000 Intl $ mn for 2016. United States US: GDP: PPP data is updated yearly, averaging 11,892,799.000 Intl $ mn from Dec 1990 (Median) to 2017, with 28 observations. The data reached an all-time high of 19,390,604.000 Intl $ mn in 2017 and a record low of 5,979,589.000 Intl $ mn in 1990. United States US: GDP: PPP data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Gross Domestic Product: Purchasing Power Parity. PPP GDP is gross domestic product converted to international dollars using purchasing power parity rates. An international dollar has the same purchasing power over GDP as the U.S. dollar has in the United States. GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in current international dollars. For most economies PPP figures are extrapolated from the 2011 International Comparison Program (ICP) benchmark estimates or imputed using a statistical model based on the 2011 ICP. For 47 high- and upper middle-income economies conversion factors are provided by Eurostat and the Organisation for Economic Co-operation and Development (OECD).; ; World Bank, International Comparison Program database.; Gap-filled total;

In 2021, the agriculture sector contributed around 0.94 percent to the Gross Domestic Product (GDP) of the United States. In that same year, 17.61 percent came from industry, and the service sector contributed the most to the GDP, at 76.4 percent.

The Gross Domestic Product (GDP) in Vietnam was worth 476.39 billion US dollars in 2024, according to official data from the World Bank. The GDP value of Vietnam represents 0.45 percent of the world economy. This dataset provides the latest reported value for - Vietnam GDP - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

This dataset provides values for GDP reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Graph and download economic data for Shares of gross domestic product: Imports of goods and services (B021RE1A156NBEA) from 1929 to 2024 about Shares of GDP, imports, goods, services, GDP, and USA.

Historical dataset showing U.S. GDP by year from 1960 to 2023.

Graph and download economic data for Value Added by Industry: Retail Trade as a Percentage of GDP (VAPGDPR) from Q1 2005 to Q2 2025 about value added, retail trade, private industries, percent, sales, retail, private, industry, GDP, and USA.

United States US: GDP: Gross Value Added at Factor Cost: Industry data was reported at 3,516.382 USD bn in 2016. This records a decrease from the previous number of 3,523.003 USD bn for 2015. United States US: GDP: Gross Value Added at Factor Cost: Industry data is updated yearly, averaging 2,895.448 USD bn from Dec 1997 (Median) to 2016, with 20 observations. The data reached an all-time high of 3,525.303 USD bn in 2014 and a record low of 1,991.845 USD bn in 1997. United States US: GDP: Gross Value Added at Factor Cost: Industry data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Gross Domestic Product: Nominal. Industry corresponds to ISIC divisions 10-45 and includes manufacturing (ISIC divisions 15-37). It comprises value added in mining, manufacturing (also reported as a separate subgroup), construction, electricity, water, and gas. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 3. Data are in current local currency.; ; World Bank national accounts data, and OECD National Accounts data files.; ; Note: Data for OECD countries are based on ISIC, revision 4.

In 2025, Brazil and Mexico were expected to be the countries with the largest gross domestic product (GDP) in Latin America and the Caribbean. In that year, Brazil's GDP could reach an estimated value of 2.3 trillion U.S. dollars, whereas Mexico's amounted to almost 1.8 trillion U.S. dollars. GDP is the total value of all goods and services produced in a country in a given year. It measures the economic strength of a country and a positive change indicates economic growth.

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:/...