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).

The United States recorded a Government Debt to GDP of 122.30 percent of the country's Gross Domestic Product in 2023. This dataset provides - United States Government Debt To GDP - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The Interest Expense on Debt Outstanding dataset provides monthly and fiscal year-to-date values for interest expenses on federal government debt, that is, the cost to the U.S. for borrowing money (calculated at a specified rate and period of time). U.S. debt includes Treasury notes and bonds, foreign and domestic series certificates of indebtedness, savings bonds, Government Account Series (GAS), State and Local Government Series (SLGS) and other special purpose securities. While interest expenses are what the government pays to investors who loan money to the government, how much the government pays in interest depends on both the total federal debt and the interest rate investors charged when they loaned the money. This dataset is useful for those who wish to track the cost of maintaining federal debt.

Graph and download economic data for Federal Debt: Total Public Debt (GFDEBTN) from Q1 1966 to Q4 2024 about public, debt, federal, government, and USA.

Russia recorded a Government Debt to GDP of 14.90 percent of the country's Gross Domestic Product in 2023. This dataset provides - Russia Government Debt To GDP - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Private Debt to GDP in the United States decreased to 216.50 percent in 2023 from 224.50 percent in 2022. United States Private Debt to GDP - values, historical data, forecasts and news - updated on March of 2025.

Germany recorded a Government Debt to GDP of 62.90 percent of the country's Gross Domestic Product in 2023. This dataset provides the latest reported value for - Germany Government Debt to GDP - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Maintain the State of Oklahoma debt per capita at less than the national average every year through 2018.

This data set contains debt outstanding for local government Issuers, including cities, community college districts, counties, hospital districts, independent school districts, other special districts and water districts. Not included are obligations of less than one-year maturity and special obligations not requiring Attorney General approval. Excludes commercial paper and Build America Bond subsidies. Excludes conduit debt. Data includes tax rate, taxable values, pledge, population, total principal, total interest and total debt service.

TDMentions: A Dataset of Technical Debt Mentions in Online Posts (version 1.0)

TDMentions is a dataset that contains mentions of technical debt from Reddit, Hacker News, and Stack Exchange. It also contains a list of blog posts on Medium that were tagged as technical debt. The dataset currently contains approximately 35,000 items.

Data collection and processing

The dataset is mainly collected from existing datasets. We used data from:

• the archive of Reddit posts by Jason Baumgartner (available at https://pushshift.io,
• the archive of Hacker News available at Google's BigQuery (available at https://console.cloud.google.com/marketplace/details/y-combinator/hacker-news), and the Stack Exchange data dump (available at https://archive.org/details/stackexchange).
• the GHTorrent project
• the GH Archive

The data set currently contains data from the start of each source/service until 2018-12-31. For GitHub, we currently only include data from 2015-01-01.

We use the regular expression tech(nical)?[\s\-_]*?debt to find mentions in all sources except for Medium. We decided to limit our matches to variations of technical debt and tech debt. Other shorter forms, such as TD, can result in too many false positives. For Medium, we used the tag technical-debt.

Data Format

The dataset is stored as a compressed (bzip2) JSON file with one JSON object per line. Each mention is represented as a JSON object with the following keys.

• id: the id used in the original source. We use the URL path to identify Medium posts.
• body: the text that contains the mention. This is either the comment or the title of the post. For Medium posts this is the title and subtitle (which might not mention technical debt, since posts are identified by the tag).
• created_utc: the time the item was posted in seconds since epoch in UTC.
• author: the author of the item. We use the username or userid from the source.
• source: where the item was posted. Valid sources are:
  • HackerNews Comment
  • HackerNews Job
  • HackerNews Submission
  • Reddit Comment
  • Reddit Submission
  • StackExchange Answer
  • StackExchange Comment
  • StackExchange Question
  • Medium Post
• meta: Additional information about the item specific to the source. This includes, e.g., the subreddit a Reddit submission or comment was posted to, the score, etc. We try to use the same names, e.g., score and num_comments for keys that have the same meaning/information across multiple sources.

This is a sample item from Reddit:

{
 "id": "ab8auf",
 "body": "Technical Debt Explained (x-post r/Eve)",
 "created_utc": 1546271789,
 "author": "totally_100_human",
 "source": "Reddit Submission",
 "meta": {
  "title": "Technical Debt Explained (x-post r/Eve)",
  "score": 1,
  "num_comments": 0,
  "url": "http://jestertrek.com/eve/technical-debt-2.png",
  "subreddit": "RCBRedditBot"
 }
}

Sample Analyses

We decided to use JSON to store the data, since it is easy to work with from multiple programming languages. In the following examples, we use jq to process the JSON.

How many items are there for each source?

lbzip2 -cd postscomments.json.bz2 | jq '.source' | sort | uniq -c

How many submissions that mentioned technical debt were posted each month?

lbzip2 -cd postscomments.json.bz2 | jq 'select(.source == "Reddit Submission") | .created_utc | strftime("%Y-%m")' | sort | uniq -c

What are the titles of items that link (meta.url) to PDF documents?

lbzip2 -cd postscomments.json.bz2 | jq '. as $r | select(.meta.url?) | .meta.url | select(endswith(".pdf")) | $r.body'

Please, I want CSV!

lbzip2 -cd postscomments.json.bz2 | jq -r '[.id, .body, .author] | @csv'

Note that you need to specify the keys you want to include for the CSV, so it is easier to either ignore the meta information or process each source.

Please see https://github.com/sse-lnu/tdmentions for more analyses

Limitations and Future updates

The current version of the dataset lacks GitHub data and Medium comments. GitHub data will be added in the next update. Medium comments (responses) will be added in a future update if we find a good way to represent these.

Context

The World Bank is an international financial institution that provides loans to countries of the world for capital projects. The World Bank's stated goal is the reduction of poverty. Source: https://en.wikipedia.org/wiki/World_Bank

Content

This dataset contains both national and regional debt statistics captured by over 200 economic indicators. Time series data is available for those indicators from 1970 to 2015 for reporting countries.

For more information, see the World Bank website.

Fork this kernel to get started with this dataset.

Acknowledgements

https://bigquery.cloud.google.com/dataset/bigquery-public-data:world_bank_intl_debt

https://cloud.google.com/bigquery/public-data/world-bank-international-debt

Citation: The World Bank: International Debt Statistics

Dataset Source: World Bank. This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source - http://www.data.gov/privacy-policy#data_policy - and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.

Banner Photo by @till_indeman from Unplash.

Inspiration

What countries have the largest outstanding debt?

https://cloud.google.com/bigquery/images/outstanding-debt.png" alt="enter image description here"> https://cloud.google.com/bigquery/images/outstanding-debt.png

The tables and interactive maps below allow users to explore the ratio of debt to income by state, metropolitan statistical area, and county for each year since 1999. Household debt is calculated from Federal Reserve Bank of New York (FRBNY) Consumer Credit Panel/Equifax Data, and household income is reported by the Bureau of Labor Statistics.

Statistics on student debt, including the average debt at graduation, the percentage of graduates who owed large debt at graduation and the percentage of graduates with debt who had paid it off at the time of the interview, are presented by the province of study and the level of study. Estimates are available at five-year intervals.

This dataset has various calculations of debt burden. The data is represented as percentages and will be updated twice per year in the Preliminary and Executive Budgets.

Households Debt in the United States decreased to 70.50 percent of GDP in the third quarter of 2024 from 70.70 percent of GDP in the second quarter of 2024. This dataset provides - United States Households Debt To Gdp- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Key information about United States Household Debt

• United States Household Debt reached 18,036.0 USD bn in Dec 2024, compared with the reported number of 17,943.0 USD bn in the previous quarter
• US Household Debt: USD mn data is updated quarterly, available from Mar 1999 to Dec 2024
• The data reached an all-time high of 18,036.0 USD bn in Dec 2024 and a record low of 4,540.0 USD bn in Mar 1999

• In the latest reports, United States Household Debt accounted for 61.7 % of the country's Nominal GDP in Dec 2024
• Money Supply M2 in United States increased 21,533.8 USD bn YoY in Dec 2024
• United States Foreign Exchange Reserves was measured at 34.9 USD bn in Dec 2024
• The Foreign Exchange Reserves equaled 0.1 Months of Import in Dec 2024
• United States Domestic Credit reached 30,648.3 USD bn in Mar 2024, representing an drop of 0.3 % YoY

The financial indicators are based on data compiled according to the 2008 SNA "System of National Accounts, 2008". Many indicators are expressed as a percentage of Gross Domestic Product (GDP) or as a percentage of Gross Disposable Income (GDI) when referring to the Households and NPISHs sector. The definition of GDP and GDI are the following:

Gross Domestic Product:
Gross Domestic Product (GDP) is derived from the concept of value added. Gross value added is the difference of output and intermediate consumption. GDP is the sum of gross value added of all resident producer units plus that part (possibly the total) of taxes on products, less subsidies on products, that is not included in the valuation of output [System of National Accounts, 2008, par. 2.138]. GDP is also equal to the sum of final uses of goods and services (all uses except intermediate consumption) measured at purchasers’ prices, less the value of imports of goods and services [System of National Accounts, 2008, par. 2.139]. GDP is also equal to the sum of primary incomes distributed by producer units [System of National Accounts, 2008, par. 2.140].

Gross Disposable Income:
Gross Disposable Income (GDI) is equal to net disposable income which is the balancing item of the secondary distribution income account plus the consumption of fixed capital. The use of the Gross Disposable Income (GDI), rather than net disposable income, is preferable for analytical purposes because there are uncertainty and comparability problems with the calculation of consumption of fixed capital. GDI measures the income available to the total economy for final consumption and gross saving [System of National Accounts, 2008, par. 2.145].

Definition of Debt:
Debt is a commonly used concept, defined as a specific subset of liabilities identified according to the types of financial instruments included or excluded. Generally, debt is defined as all liabilities that require payment or payments of interest or principal by the debtor to the creditor at a date or dates in the future. Consequently, all debt instruments are liabilities, but some liabilities such as shares, equity and financial derivatives are not debt [System of National Accounts, 2008, par. 22.104]. According to the SNA, most debt instruments are valued at market prices. However, some countries do not apply this valuation, in particular for securities other than shares, except financial derivatives (AF33). In this dataset, for financial indicators referring to debt, the concept of debt is the one adopted by the SNA 2008 as well as by the International Monetary Fund in “Public Sector Debt Statistics – Guide for compilers and users” (Pre-publication draft, May 2011). Debt is thus obtained as the sum of the following liability categories, whenever available / applicable in the financial balance sheet of the institutional sector:special drawing rights (AF12), currency and deposits (AF2), debt securities (AF3), loans (AF4), insurance, pension, and standardised guarantees (AF6), and other accounts payable (AF8). This definition differs from the definition of debt applied under the Maastricht Treaty for European countries. First, gross debt according to the Maastricht definition excludes not only financial derivatives and employee stock options (AF7) and equity and investment fund shares (AF5) but also insurance pensions and standardised guarantees (AF6) and other accounts payable (AF8). Second, debt according to Maastricht definition is valued at nominal prices and not at market prices.

To view other related indicator datasets, please refer to:
Institutional Investors Indicators [add link]
Household Dashboard [add link]

Covers data on bonds issued in Washington State since 2000 Search by issuer name, user name, or date range Many official statements and bond covenants for bonds issued since 2008 can be viewed and downloaded No password required

Using state-dependent local projections and historical US data, we find that government spending multipliers are considerably larger in periods of private debt overhang. In particular, while multipliers are below or close to one in low private debt states, we find significant crowding-in of private spending in periods of debt overhang, resulting in multipliers that are much larger than one. In high private debt episodes, more government purchases even reduce the ratio of government debt to gross domestic product. These results are robust for the type of shocks, and when we control for the business cycle, financial crises, deleveraging episodes, government debt overhang, and the zero-lower-bound.

The MTA Debt Outstanding dataset provides detailed information of MTA’s outstanding principal from its bond issuances. The information is provided by credit and by specific bond series and is shown in dollars in millions. The dataset shows the original issuances amount, Bond Purchase Agreement sale date, the final maturity date, how much of the series is outstanding in fixed rate, variable, or synthetic fixed, and the total outstanding. Additionally, the dataset indicates the true interest cost (TIC) for the specific bond series.