This statistic shows the average annual change in real GDP per capita in the United States from President Hoover to Obama, as of 2011. The biggest economic growth happened during Franklin D. Roosevelt's presidency. The Real Gross Domestic Product per capita increased by 5.25 percent each year.

Additional information on President Barack Obama’s first term economic policy performance

“It’s the economy, stupid” as the now famous saying by former President Bill Clinton goes is often used to demonstrate the importance continuants place on the economy’s performance. Appointed to President of the United States in 2008, President Obama entered the job in the early stages of a global economic crisis. The unemployment rate in the United States since 1990 demonstrates that Obama oversaw a reduction in unemployment rate since an initially sharp increase to over 9 percent in 2009 and 2010. Prior to the reduction, public approval of President Obama and the Republicans in congress in handling the economy shows that the public’s trust in Obama waned from 61 percent in February 2009 to 42 percent in November 2011. The fluctuation of America’s economy meant that Obama’s first term saw him reach an average of 76 thousand private sector jobs created per month as of June 2012, leaving him sixth in private sector job creation on the list of post-war presidents.

As leader of the most economically influential country on the planet, praise and criticism of Obama’s economic performance is also a global issue. In 2012, opinion on Obama’s management of global economic issues by country demonstrates the variety in opinion held in and across countries. While countries such as Britain and Germany whose economies appeared to be recovering held Obama’s economic policy in a positive light, opinion was more negative in Egypt and Greece were the economic situation was less optimistic.

In 2025, the United States had the largest economy in the world, with a gross domestic product of over 30 trillion U.S. dollars. China had the second largest economy, at around 19.23 trillion U.S. dollars. Recent adjustments in the list have seen Germany's economy overtake Japan's to become the third-largest in the world in 2023, while Brazil's economy moved ahead of Russia's in 2024. Global gross domestic product Global gross domestic product amounts to almost 110 trillion U.S. dollars, with the United States making up more than one-quarter of this figure alone. The 12 largest economies in the world include all Group of Seven (G7) economies, as well as the four largest BRICS economies. The U.S. has consistently had the world's largest economy since the interwar period, and while previous reports estimated it would be overtaken by China in the 2020s, more recent projections estimate the U.S. economy will remain the largest by a considerable margin going into the 2030s.The gross domestic product of a country is calculated by taking spending and trade into account, to show how much the country can produce in a certain amount of time, usually per year. It represents the value of all goods and services produced during that year. Those countries considered to have emerging or developing economies account for almost 60 percent of global gross domestic product, while advanced economies make up over 40 percent.

There is substantial evidence that voters’ choices are shaped by assessments of the state of the economy and that these assessments, in turn, are influenced by the news. But how does the economic news track the welfare of different income groups in an era of rising inequality? Whose economy does the news cover? Drawing on a large new dataset of U.S. news content, we demonstrate that the tone of the economic news strongly and disproportionately tracks the fortunes of the richest households, with little sensitivity to income changes among the non-rich. Further, we present evidence that this pro-rich bias emerges not from pro-rich journalistic preferences but, rather, from the interaction of the media’s focus on economic aggregates with structural features of the relationship between economic growth and distribution. The findings yield a novel explanation of distributionally perverse electoral patterns and demonstrate how distributional biases in the economy condition economic accountability.

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.

This dataset contains almost 100K rows of Economic data by US state and county. It's from the Bureau of Economic Analysis -> https://bea.gov

The data covers 32 economic categories like Personal Income, Unemployment Insurance Compensation, Net Earnings etc.

Here's a notebook that shows a simple example of getting specific data from the BEA files -> https://www.kaggle.com/davidbroberts/economic-profile-by-county

Take a look at some of my other economics datasets:

• US Quarterly Income 1948 - 2020 -> https://www.kaggle.com/davidbroberts/us-quarterly-personal-income-1948-2020
• US Personal Expenditures by State 1997-2019 -> https://www.kaggle.com/davidbroberts/us-personal-expenditures-by-state-19972019
• US Gross Domestic Product by State 1997-2020 -> https://www.kaggle.com/davidbroberts/us-gdp-by-state-19972020
• US Employment by Industry 2001-2019 ->https://www.kaggle.com/davidbroberts/us-employment-by-industry-2001-2019

I find economic data fascinating and I'm not sure why.

Thanks to https://unsplash.com/@bartos for the splash pic!

Replication Files for Amiti M., S. Redding, and D. Weinstein (2020) "Who's Paying for the U.S. Tariffs? A Longer-Term Perspective"

In 2024 the real gross domestic product (GDP) of the United States increased by 2.8 percent compared to 2023.
What does GDP growth mean? Essentially, the annual GDP of the U.S. is the monetary value of all goods and services produced within the country over a given year. On the surface, an increase in GDP therefore means that more goods and services have been produced between one period than another. In the case of annualized GDP, it is compared to the previous year. In 2023, for example, the U.S. GDP grew 2.5 percent compared to 2022. Countries with highest GDP growth rate Although the United States has by far the largest GDP of any country, it does not have the highest GDP growth, nor the highest GDP at purchasing power parity. In 2021, Libya had the highest growth in GDP, growing more than 177 percent compared to 2020. Furthermore, Luxembourg had the highest GDP per capita at purchasing power parity, a better measure of living standards than nominal or real GDP.

Say you need an accurate forecast of future GDP or inflation. What’s your best bet—the economist who was hot last year or the forecaster in the middle? The record indicates it’s tough to consistently beat the median prediction.

General Abstract/Purpose (70 words): Data were collected to assist in cost-benefit analysis of flood mitigation actions that could be taken by the U.S. and Canada to prevent structural damage and associated costs and losses in future flood conditions, including conditions worse than the historical record flooding in spring of 2011. Data were commissioned to revise or fill gaps in estimates from structural damage modeling software commonly used for depth-damage economic assessments of flood impacts. The Summary text that immediately follows this introductory sentence offers overview information, but also includes context and detail that is not present in the Word document ("Principal Indicator Combo SET - REVIEW FINAL v2.docx") that constitutes the main body of this data release, supported by Excel files (that are copied without formatting in csv files for each Excel tab). Lake Champlain is a relatively large lake bordered by New York on the western side and Vermont on the eastern side, whose uppermost region spans the U.S.-Canadian border. The 436 mi^2 (1,130 km^2) lake sits within a 9,277 mi^2 (23,900 km^2) basin, and Champlain’s only drainage point is north into Canada via the Richelieu River into the province of Quebec. About 75% of the Lake Champlain shoreline of New York is within Adirondack State Park, covering all or part of Clinton, Essex, and Washington counties. Of Vermont’s 14 counties, Franklin, Chittenden, and Addison Counties border Lake Champlain, while Grand Isle is surrounded by Champlain and at its northern edge the Canadian border. Development and anthropogenic modifications, especially over the last 50 years, have converted wetlands, changed the timing and flows of water, and increased impervious surface area including new residences in floodplains on both sides of the border. Occasionally there is damaging flooding, with significant economic damages in New York, Vermont, and Quebec. With flood stage at 99.57’ (30.35m) and major flooding from 101.07’ (30.81m) over sea level, a 101.4’ (30.91m) flood in 1993 broke the previous recorded high flood in 1869. Following the third heaviest recorded snow, almost no seasonal snowmelt, then heavy rains, the spring of 2011 brought record flooding more than one foot over the 1993 record to 102.77’ (31.32m), expanding the lake’s area by 66 mi^2 (106.2 km^2, or about 5.8%). From reaching flood stage to peak and then returning to a lake level below flood stage took around six weeks. Wind-to-wave-driven erosion was up to 5 feet (1.5m) above static lake elevation in some areas. The record flood height (102.77’) is often reported as 103.07’ or 103.27’ in Burlington, owing to different vertical and horizontal datums and digital elevation models (DEMs), and some wave action. In a 1976 flood the U.S. side incurred more than 50% of the economic damages, but in 2011, Quebec experienced some 80% of structural and economic damages estimated at $82 million. Tropical Storm Irene hit the area in August of 2011 and did far more damage on the American side, for example spurring $29 million in home and business repair loans for damage across 12 of Vermont’s 14 counties. Co-reporting across the two events for 2011 confounded some data, making it impossible to separately identify spring flooding numbers. Following the Boundary Waters Treaty between the U.S. and Canada in 1909, from 1912 the International Joint Commission (IJC) handles boundary water issues between the two countries. The IJC Lake Champlain Richelieu River (LCRR) Study Project is a bi-national (U.S., Canada) multi-agency effort to assess flood risk and flood mitigation options as they affect potential structural damages and wider non-structural damages that include secondary economic, community, and psychological effects. Key economic parts of the report to the IJC LCRR Study Board are calculated using a new tool developed for the study project, an Integrated Socio-Economic-Environmental (ISEE) model, with forecasting for damages up to 105.57’ flood (105.9’, or 106’ [32.3m] for short, by alternative datum and DEMs, as apply in some of the modeling and estimations herein). There is also a Collaborative Decision Support Tool (CDST) that also processes non-structural economic damages, costs, or losses as inputs. CDST is a pared-down version of ISEE that applies historical estimates but does not project outcomes for higher floods in the future. Outputs from this data release are inputs to the ISEE or the CDST for calculations of the benefit-to-cost ratios projected to follow different structural interventions. For example adding a weir in the Richelieu River yielded a greater-than-one benefit-to-cost ratio in late-stage modeling, whereas a dam on either side, or an entirely new canal on the Canadian side, were never entertained as cost feasible or even appropriate. USGS economists were contracted to supply economic “principal indicators” for potential U.S.-side depth-damage effects from lake-rise flooding. The scope of this analysis is limited by several factors associated with the objectives of the IJC LCRR Study Board. Damages from tributary flooding were defined out of a project focused on joint-management options for mitigating flood effects, as tributary flows would be managed only by the U.S. Uncommonly low Lake Champlain levels were also ultimately considered as a stakeholder concern (the weir option also addressed this concern). It is standard to model economic damages to structures and related economic costs due to flooding using the FEMA-designed Hazus®-MH (Multi-Hazard) Flood Model of structural damages (https://www.fema.gov/flood-maps/products-tools/hazus; the Hazus-MH Technical Manual, 2011, 569pp, which explains definitions and parameterization of the tool rather than use of the tool itself, is a frequently referred source here). “Hazus” (tool) modeling is used in the LCRR Study Board research to estimate structural damages at different flood depths, and the primary work presented in this data release estimates depth-damage values for “Principal Indicators” (PIs) that were defined to supplement or alternatively estimate results from applying Hazus, where gaps exist or where straight Hazus values may be questionable in the LCRR context. A number of Principal Indicators were estimated on the Canadian and U.S. sides, where no PIs include any estimates for repair of structural damage, as those calculations are done separately using the Hazus tool (or the ISEE model application with Hazus outputs as inputs). In the final list, the USGS team produced estimates for six PIs: temporary lodging costs, residential debris clean-up and disposal, damage to roads and bridges, damage to water treatment facilities, income loss from industrial or commercial properties, and separately and specifically recreation sector income loss. So associated with residential damage, the costs of securing emergency and longer-term lodging when a household is displaced by lake-rise flooding are estimated, and the costs of cleaning up and removing and disposing of debris from residential property damage are estimated. In the public sector, costs of clean up and repair of damages to roads and bridges from lake-rise flooding are calculated, as are damages and potential revenue losses from flood mitigation measures and service reductions where public or private water utilities are inundated by lake-rise flooding. In the commercial sector, revenue losses from being closed for business due to flooding are calculated outside of the recreation sector, and then also for the recreation sector as lakeside campgrounds, marinas, and ferry services (where the last is also used for local commercial traffic). All of these PIs are characterized by being little-discussed in the literature. To derive information necessary to bound economic estimates for each of the 6 PIs, consultation with subject-matter experts in New York and Vermont (or at agencies covering these areas) was employed more often than anything in peer-reviewed literature specifically applied. Depth-damage functions that result are not formal mathematical functions, and across the six PIs calculations and results tend to be in increments of one foot or more. Results thus suggest magnitudes of costs that comply with reasonable scenario assumptions for a small but fairly consistent set of flood depths from 99.57’ to 105.57’, where the latter value is almost three feet (1m) above the historic maximum flood. Nothing reported in these estimates is empirically deterministic, or capable of including probabilistic error margins. Simplifying assumptions serve first to actually simplify the calculations and legibility of estimated results, and second to avoid the impression that specifically calibrated empirical estimations are being conducted. This effort offers plausible, logical, reliable, and reproducible magnitudes for estimates, using a method that can be easily modified if better information becomes available for future estimations. Certain worksheets and specific results are withheld to avoid the outright identification of specific businesses (or homes). Facts in this abstract generally attribute to: International Lake Champlain-Richelieu River Study Board, 2019. The Causes and Impacts of Past Floods in the Lake Champlain-Richelieu River Basin – Historical Information on Flooding, A Report to the International Joint Commission, 108pp (https://ijc.org/en/lcrr). Some supplemental factual support is from: Lake Champlain Basin Program, 2013. Flood Resilience in the Lake Champlain Basin and Upper Richelieu River, 93 pp (https://ijc.org/en/lcrr).

Whether the activities of lawyers might hamper economic growth has been hotly contested over the past three decades. Contradictory conclusions have flowed from evidence that typically has focused on the impact of lawyers on the growth rates of countries. Disputes over definitions and samples that vary among countries have colored portions of these debates. We surmount many of these issues by adopting a 50-state panel covering the period 2005-2018 for the United States and by utilizing widely accepted variables regarding economic activity and who is considered a lawyer. Further, we utilize two distinct measures of the activity of lawyers and find that an increased presence of lawyers reduces per capita real economic growth. Separately, we also find that an increased presence of lawyers reduces the level of per capita real income.

Graph and download economic data for Real-time Sahm Rule Recession Indicator (SAHMREALTIME) from Dec 1959 to Sep 2025 about recession indicators, academic data, and USA.

We examine the effects of constituents, special interests, and ideology on congressional voting on two of the most significant pieces of legislation in US economic history. Representatives whose constituents experience a sharp increase in mortgage defaults are more likely to support the Foreclosure Prevention Act, especially in competitive districts. Interestingly, representatives are more sensitive to defaults of their own-party constituents. Special interests in the form ofhigher campaign contributions from the financial industry increase the likelihood of supporting the Emergency Economic Stabilization Act. However, ideologically conservative representatives are less responsive to both constituent and special interests. (JEL D72, G21, G28)

Each year, researchers at Harvard's Growth Lab release growth forecasts for the upcoming decade as well as annual rankings of countries by economic complexity. The Economic Complexity Index (ECI) ranking is a measure of the amount of capabilities and knowhow of a given country determined by the diversity, ubiquity, and complexity of the products it exports. Growth projections are calculated through a process largely based on determining whether a country's economic complexity is higher or lower than expected given its level of income. We expect countries whose economic complexity is greater than we would expect for its level of income to grow faster than those that are "too rich" for their current level of complexity. In this data, a country's growth projection value for a given year is for the decade beginning with that year. For example, a value in a 2017 row is the projection of annualized growth for 2017–2027.

This dataset presents statistics on: the number of establishments; sales, value of shipments, or revenue; annual payroll; and number of employees whose NAICS classification has changed between the current and the previous economic censuses. Data are shown for 6-digit current economic census NAICS industries and their 8-digit previous economic census NAICS components for the U.S. Includes only establishments of firms with paid employees.

United States US: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate data was reported at 1.310 % in 2016. United States US: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate data is updated yearly, averaging 1.310 % from Dec 2016 (Median) to 2016, with 1 observations. United States US: Survey Mean Consumption or Income per Capita: Bottom 40% of Population: Annualized Average Growth Rate 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: Poverty. The growth rate in the welfare aggregate of the bottom 40% is computed as the annualized average growth rate in per capita real consumption or income of the bottom 40% of the population in the income distribution in a country from household surveys over a roughly 5-year period. Mean per capita real consumption or income is measured at 2011 Purchasing Power Parity (PPP) using the PovcalNet (http://iresearch.worldbank.org/PovcalNet). For some countries means are not reported due to grouped and/or confidential data. The annualized growth rate is computed as (Mean in final year/Mean in initial year)^(1/(Final year - Initial year)) - 1. The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported. The initial year refers to the nearest survey collected 5 years before the most recent survey available, only surveys collected between 3 and 7 years before the most recent survey are considered. The final year refers to the most recent survey available between 2011 and 2015. Growth rates for Iraq are based on survey means of 2005 PPP$. The coverage and quality of the 2011 PPP price data for Iraq and most other North African and Middle Eastern countries were hindered by the exceptional period of instability they faced at the time of the 2011 exercise of the International Comparison Program. See PovcalNet for detailed explanations.; ; World Bank, Global Database of Shared Prosperity (GDSP) circa 2010-2015 (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).; ; The comparability of welfare aggregates (consumption or income) for the chosen years T0 and T1 is assessed for every country. If comparability across the two surveys is a major concern for a country, the selection criteria are re-applied to select the next best survey year(s). Annualized growth rates are calculated between the survey years, using a compound growth formula. The survey years defining the period for which growth rates are calculated and the type of welfare aggregate used to calculate the growth rates are noted in the footnotes.

The discovery of oil has had a huge impact on economics and politics within the Middle East, as well as the region’s relationship with the west and the way regional standards of living. Before the discovery of oil, fishing and pearling were the primary economic sectors of many Gulf States. After the discovery of oil and due to the immense value of oil, many Middle East countries made oil their economic focus, changing livelihood of their people in just a few decades. One example is Kuwait, whose economy focused mainly on fishing and pearling prior to the discovery of oil in 1934. Now, oil extraction and processing accounts for 50% of the country’s GDP, 90% of export earnings, and 75% of government revenues1. Typically, the more oil a country exports the less economically diverse it is. Booz & Company did a study to look at the economic diversity of the Gulf States, which are very oil-rich, in comparison to the rest of the world, and found that the economic diversity of the GCC (the countries of Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates) was much lower than that of European or other “western” states3. Since oil is a nonrenewable resource it will become important for these countries to diversify their economies and become independent of oil as reserve levels decline. Recently, attempts of economic diversification have been made in several oil diverse nations such as the aluminum smelting industry in Bahrain, Qatar, and the UAE, taken up as an attempt to diversify their economy6; however, the reason that the industry of aluminum smelting has grown in these counties is because aluminum smelting requires immense amounts of oil. Therefore, the economics of these counties is in reality not that diversified. The Export Diversity Index is defined as the number of prominent commodities a country exports. Goods made from the same derivative, such as crude oil and petroleum products, were categorized as belonging in the same industry for simplicity purposes. The data represented in the map was obtained from lists of each country's ten most lucrative exports, and the index ranges on a scale of 1 to 10 different exports4. We noticed that the countries with the greatest volume oil resources had the lowest score on the index because more goods they produced were related to the oil industry. The map of oil reserves gives a good visual representation of which Middle Eastern countries are the most oil-rich, and shows a high concentration of marks in the Gulf states, particularly the in the Persian Gulf where off-shore reserves are located. The countries with the lowest score on the index were Saudi Arabia (with a score of 2), Kuwait (4), Bahrain (2), and Qatar (2). It is interesting to note that although other countries may have high concentrations of certain resources within their borders it is only the oil-rich countries that have the lowest levels of export diversity. The only exceptions to this trend are countries with a government that has made particularly strong efforts to become less oil-reliant, such as the United Arab Emirates7. Although, we recognize that a country's economic diversity also accounts for its domestic economy, which generally relies heavily on the country's exports. Therefore this analysis concludes that the Export Diversity Index is an indicator of a country's economic index. The data we have compiled has implications for the future of many of the Gulf States, especially Saudi Arabia, as the international community attempts to wean itself off of fossil fuels.Amanda Doyle, March 2012WORKS CITED1.“Kuwait Economy”. Encycopedia of the Nations, Advameg, Inc. 2011. http://www.nationsencyclopedia.com/Asia-and-Oceania/Kuwait-ECONOMY.html.2.Burke, Edmund, and Yaghoubian, David N. Struggle and Survival in the Modern Middle East. 2nd ed. University of California Press: Berkley, CA, 2006.3.“Economic Diversification”. The Ideation Center. 2011. http://www.ideationcenter.com/home/ideation_article/economic_diversification.4."UN Data: Country Profile”. UN Division of Statistics, United Nations. 2011. http://data.un.org/CountryProfile.aspx5."USGS identifies potential giant oil and gas fields in Israel/Palestine”. EnerGeoPolitics. 2010. http://energeopolitics.com/2010/04/09/usgs-identifies-potential-giant-oil-and-gas-fields-in-israelpalestine/6. "A Summary of Existing and New-Buuild Smelters in the Middle East". Aluminium International Today. January /February 2009. http://www.improvingperformance.com/papers/Primary%20Article%20AIT.pdf.7. "UAE to Diversify Economy - To Reduce Dependence on Oil and Natural Gas Revenues". Oil Gas Articles. 2011. http://www.oilgasarticles.com/articles/416/2/UAE-to-Diversify-Economy---To-Reduce-Dependence-on-oil-and-Natural-Gas-Revenues/Page2.html?PHPSESSID=e10561d4a9d2cf87f64fbdeb2e00f65d.

International dollars are a hypothetical currency that is used to make meaningful comparisons of monetary indicators of living standards.

Figures expressed in international dollars are adjusted for inflation within countries over time, and for differences in the cost of living between countries.

The goal of such adjustments is to provide a unit whose purchasing power is held fixed over time and across countries, such that one international dollar can buy the same quantity and quality of goods and services no matter where or when it is spent.

Read more in our article: What are Purchasing Power Parity adjustments and why do we need them? Similarly, the history of economic growth is also the history of how large global inequalities emerged – in nutrition, health, education, basic infrastructure, and many other dimensions. In some countries, the quantity and quality of the goods and services underpinning these outcomes grew substantially over the past two centuries; in others, they did not.

Of course, economic growth does not reflect everything we value. On Our World in Data we provide thousands of measures that try to capture these many different dimensions, covering topics such as biodiversity, pollution, time use, human rights and democracy.

United States US: Market Capitalization: Listed Domestic Companies: % of GDP data was reported at 165.651 % in 2017. This records an increase from the previous number of 146.862 % for 2016. United States US: Market Capitalization: Listed Domestic Companies: % of GDP data is updated yearly, averaging 102.679 % from Dec 1980 (Median) to 2017, with 38 observations. The data reached an all-time high of 165.651 % in 2017 and a record low of 39.352 % in 1981. United States US: Market Capitalization: Listed Domestic Companies: % of GDP 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: Financial Sector. Market capitalization (also known as market value) is the share price times the number of shares outstanding (including their several classes) for listed domestic companies. Investment funds, unit trusts, and companies whose only business goal is to hold shares of other listed companies are excluded. Data are end of year values.; ; World Federation of Exchanges database.; Weighted average; Stock market data were previously sourced from Standard & Poor's until they discontinued their 'Global Stock Markets Factbook' and database in April 2013. Time series have been replaced in December 2015 with data from the World Federation of Exchanges and may differ from the previous S&P definitions and methodology.

United States US: Market Capitalization: Listed Domestic Companies data was reported at 32,120.703 USD bn in 2017. This records an increase from the previous number of 27,352.201 USD bn for 2016. United States US: Market Capitalization: Listed Domestic Companies data is updated yearly, averaging 11,322.354 USD bn from Dec 1980 (Median) to 2017, with 38 observations. The data reached an all-time high of 32,120.703 USD bn in 2017 and a record low of 1,263.561 USD bn in 1981. United States US: Market Capitalization: Listed Domestic Companies 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: Financial Sector. Market capitalization (also known as market value) is the share price times the number of shares outstanding (including their several classes) for listed domestic companies. Investment funds, unit trusts, and companies whose only business goal is to hold shares of other listed companies are excluded. Data are end of year values converted to U.S. dollars using corresponding year-end foreign exchange rates.; ; World Federation of Exchanges database.; Sum; Stock market data were previously sourced from Standard & Poor's until they discontinued their 'Global Stock Markets Factbook' and database in April 2013. Time series have been replaced in December 2015 with data from the World Federation of Exchanges and may differ from the previous S&P definitions and methodology.

Graph and download economic data for Real Disposable Personal Income (DSPIC96) from Jan 1959 to Aug 2025 about disposable, personal income, personal, income, real, and USA.