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Graph and download economic data for Federal Debt: Total Public Debt (GFDEBTN) from Q1 1966 to Q1 2025 about public, debt, federal, government, and USA.
Total outstanding debt of the U.S. government reported daily. Includes a breakout of intragovernmental holdings (federal debt held by U.S. government) and debt held by the public (federal debt held by entities outside the U.S. government).
In 2023, the generation X was the age group with the highest amount of auto loan debt in the United States. That group had on average a car loan debt of roughly 27,100 U.S. dollars. Meanwhile, the silent generation had the lowest amount of auto loan debt, amounting to approximately 16,050 U.S. dollars.
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ABSTRACT The federal budget of the United States displayed only 8 surpluses in the whole post-World War II period, the last of which was in 1969. Several theories have been developed in an attempt to explain the persistency of the Federal deficits. Due to the Keynesian/stagnationist views predominant among leftist theorists, emphasis has been put on the analysis of the expenditure side of government finances and its role of supporting aggregate demand. Little if any attention at all was paid to the revenue side, particularly to the impact of diminishing corporate profitability on government tax revenues. This article estimates the tax losses that have resulted from the sharp decrease in profitability in the last 45 years. It concludes by pointing out some wider economic consequences of large deficits, such as the foreign debt of the United States which is the largest in the world, and the present regressive tendencies of the American tax system.
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Key information about Ukraine Government Debt: % of GDP
In 2023, outstanding auto loan debt in the United States reached a value of 1.51 trillion U.S. dollars. The overall value of car loan debt in 2019 amounted to 1.21 trillion U.S. dollars, showing an increase of approximately 300 billion U.S. dollars in three years.
The generation X was the group of people with the highest average credit card balance in the United States in 2023. That year, the average credit card debt of the generation Z amounted to approximately 3,260 U.S. dollars. People in the silent generation had a credit card balance of roughly 3,410 U.S. dollars.
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This is code to replicate the article "Exorbitant Privilege and the Sustainability of US Public Debt".
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This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.
Historical daily stock prices (open, high, low, close, volume)
Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)
Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)
Feature engineering based on financial data and technical indicators
Sentiment analysis data from social media and news articles
Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)
Stock price prediction
Portfolio optimization
Algorithmic trading
Market sentiment analysis
Risk management
Researchers investigating the effectiveness of machine learning in stock market prediction
Analysts developing quantitative trading Buy/Sell strategies
Individuals interested in building their own stock market prediction models
Students learning about machine learning and financial applications
The dataset may include different levels of granularity (e.g., daily, hourly)
Data cleaning and preprocessing are essential before model training
Regular updates are recommended to maintain the accuracy and relevance of the data
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This database consists of structured records of U.S. municipal debt offerings during 2000 through 2023. Each row corresponds to a unique municipal bond offering and covers variables of measurement of issuance date, jurisdiction identifiers (e.g., county, city, state), bond characteristics (e.g., maturity, par value, coupon rate, proceeds use), and geospatial mapping fields of references of their municipal project locations. This data was cleaned, standardized, and geocoded for assembly with resilience investment records and U.S. federal grant awards. Its primary purpose is to enable empirical work on climate-related fiscal vulnerability and economic impacts of adaptation measures like nature-based solutions (NbS). This corresponds to broader work on tracking interactions of local debt trends with the federal climate resilience awards and local credit performance.
The average consumer debt balance in the United States has peaked in 2023 at roughly 104,200 U.S. dollars. However, average consumer debt had decreased between 2010 and 2013, when it reached approximately 85,500 U.S. dollars. Here, consumer debt refers to student and car loans, credit cards, personal loans, mortgages, and other types of debt.
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The United States recorded a trade deficit of 71.52 USD Billion in May of 2025. This dataset provides the latest reported value for - United States Balance of Trade - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.
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View economic output, reported as the nominal value of all new goods and services produced by labor and property located in the U.S.
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Graph and download economic data for Trade Balance: Goods and Services, Balance of Payments Basis (BOPGSTB) from Jan 1992 to May 2025 about BOP, balance, headline figure, trade, goods, services, and USA.
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The database used includes annual frequency data for 43 countries, defined by the IMF as 24 advanced countries and 19 emerging countries, for the years 1992-2018.The database contains the fiscal stress variable and a set of variables that can be classified as follows: macroeconomic and global economy (interest rates in the US, OECD; real GDP in the US, y-o-y, OECD; real GDP in China, y-o-y, World Bank; oil price, y-o-y, BP p.l.c.; VIX, CBOE; real GDP, y-o-y, World Bank, OECD, IMF WEO; GDP per capita in PPS, World Bank); financial (nominal USD exchange rate, y-o-y, IMF IFS; private credit to GDP, change in p.p., IMF IFS, World Bank and OECD); fiscal (general government balance, % GDP, IMF WEO; general government debt, % GDP, IMF WEO, effective interest rate on the g.g. debt, IMF WEO); competitiveness and domestic demand (currency overvaluation, IMF WEO; current account balance, % GDP, IMF WEO; share in global exports, y-o-y, World Bank, OECD; gross fixed capital formation, y-o-y, World Bank, OECD; CPI, IMF IFS, IMF WEO; real consumption, y-o-y, World Bank, OECD); labor market (unemployment rate, change in p.p., IMF WEO; labor productivity, y-o-y, ILO).In line with the convention adopted in the literature, the fiscal stress variable is a binary variable equal to 1 in the case of a fiscal stress event and 0 otherwise. In more recent literature in this field, the dependent variable tends to be defined broadly, reflecting not only outright default or debt restructuring, but also less extreme events. Therefore, following Baldacci et al. (2011), the definition used in the present database is broad, and the focus is on signalling fiscal stress events, in contrast to the narrower event of a fiscal crisis related to outright default or debt restructuring. Fiscal problems can take many forms; in particular, some of the outright defaults can be avoided through timely, targeted responses, like support programs of international institutions. The fiscal stress variable is shifted with regard to the other variables: crisis_next_year – binary variable shifted by 1 year, all years of a fiscal stress coded as 1; crisis_next_period – binary variable shifted by 2 years, all years of a fiscal stress coded as 1; crisis_first_year1 – binary variable shifted by 1 year, only the first year of a fiscal stress coded as 1; crisis_first_year2 - binary variable shifted by 2 years, only the first year of a fiscal stress coded as 1.
As of the last quarter of 2022, Alaska and Hawaii were the states in the U.S. with the highest credit card debt. While the average credit card debt in Alaska amounted to 4,430 U.S. dollars, people from Mississippi only had on average 2,450 U.S. dollars of credit card debt.
KAV 1029 cover memo. Visit https://dataone.org/datasets/sha256%3A7b4b294d78da5d3c34ef539c99a1b4b597391ff234d77485bea04213590d76e4 for complete metadata about this dataset.
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This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.
Historical daily stock prices (open, high, low, close, volume)
Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)
Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)
Feature engineering based on financial data and technical indicators
Sentiment analysis data from social media and news articles
Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)
Stock price prediction
Portfolio optimization
Algorithmic trading
Market sentiment analysis
Risk management
Researchers investigating the effectiveness of machine learning in stock market prediction
Analysts developing quantitative trading Buy/Sell strategies
Individuals interested in building their own stock market prediction models
Students learning about machine learning and financial applications
The dataset may include different levels of granularity (e.g., daily, hourly)
Data cleaning and preprocessing are essential before model training
Regular updates are recommended to maintain the accuracy and relevance of the data
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Graph and download economic data for Delinquency Rate on Credit Card Loans, All Commercial Banks (DRCCLACBS) from Q1 1991 to Q1 2025 about credit cards, delinquencies, commercial, loans, banks, depository institutions, rate, and USA.
Public sector net debt amounted to 95.8 percent of gross domestic product in the United Kingdom during the 2024/25 financial year, or 90 percent when the Bank of England is excluded. UK government debt is at its highest levels since the early 1960s, due to a significant increase in borrowing during the COVID-19 pandemic. After peaking at 251.7 percent shortly after the end of the Second World War, government debt in the UK gradually fell, before a sharp increase in the late 2000s at the time of the global financial crisis. Debt not expected to start falling until 2029/30 In 2024/25, the UK's government expenditure was approximately 1.28 trillion pounds, around 44.7 percent of GDP. This spending was financed by 1.13 trillion pounds of revenue raised, and 151 billion pounds of borrowing. Although the UK government can still borrow money in the future to finance its spending, the amount spent on debt interest has increased significantly recently. Recent forecasts suggest that while the debt is eventually expected to start declining, this is based on falling government deficits in the next five years. Government facing hard choices Hitting fiscal targets, such as reducing the national debt, will require a careful balancing of the books from the current government, and the possibility for either spending cuts or tax rises. Although Labour ruled out raising the main government tax sources, Income Tax, National Insurance, and VAT, at the 2024 election, they did raise National Insurance for employers (rather than employees) and also cut Winter Fuel allowances for large numbers of pensioners. Less than a year after implementing cuts to Winter Fuel, the government performed a U-Turn on the issue, and will make it widely available by the winter of 2025.
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Graph and download economic data for Federal Debt: Total Public Debt (GFDEBTN) from Q1 1966 to Q1 2025 about public, debt, federal, government, and USA.