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

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

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

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

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

Summarizes the U.S. government's total outstanding debt at the end of each fiscal year from 1789 to the current year.

The United States recorded a Government Debt to GDP of 124.30 percent of the country's Gross Domestic Product in 2024. This dataset provides - United States Government Debt To GDP - actual values, historical data, forecast, chart, statistics, economic calendar and news.

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).

Government Debt in the United States decreased to 36211469 USD Million in June from 36215818 USD Million in May of 2025. This dataset provides - United States Government Debt- actual values, historical data, forecast, chart, statistics, economic calendar and news.

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.

The short survey on current issues relating to government spending and public debt was conducted by the opinion research institute forsa on behalf of the Press and Information Office of the Federal Government. In the survey period from 18.03.2024 to 20.03.2024, the German-speaking population aged 14 and over was asked in telephone interviews (CATI) about their attitudes to government spending and government debt. In particular, the focus is on the assessment of the debt brake and various options for reforming it. Respondents were selected using a multi-stage random sample as part of a multi-topic survey (policy BUS) including landline and mobile phone numbers (dual-frame sample). Assessment of Germany´s overall financial situation in terms of income and expenditure; assessment of Germany´s debt burden compared to most other industrialized countries; opinion on government debt (government debt should generally be avoided, is generally not a problem, only makes sense if it is used for investments for the future); government spends too much vs. too little money on various political and social tasks (health and care, defense, social affairs, climate protection, housing, integration of immigrants, pensions); opinion on the state only taking out new larger loans in exceptional emergency situations such as natural disasters (debt brake should remain as it is, it should be reformed or it should be abolished completely); evaluation of various proposals for reforming the debt regulation (change the debt limit so that the state can generally take on more debt than before, create a transitional rule so that even in the year following an emergency situation it is still possible to take on slightly more debt than usual, allow higher debt to be taken on if the economic situation is worse than expected, allow higher debt to be taken on for defense spending, allow higher debt to be taken on for investments in climate protection, allow higher debt to be taken on for investments in infrastructure such as roads and railways). Demography: sex; age; education; income level low, medium, high (net equivalent income); city size; party preference in the next federal election; voting behavior in the last federal election. Additionally coded were: Respondent ID; region west/east; weighting factor. Die Kurzumfrage über aktuelle Fragen zu Staatsausgaben und Staatsschulden wurde vom Meinungsforschungsinstitut forsa im Auftrag des Presse- und Informationsamtes der Bundesregierung durchgeführt. Im Erhebungszeitraum 18.03.2024 bis 20.03.2024 wurde die deutschsprachige Bevölkerung ab 14 Jahren in telefonischen Interviews (CATI) zu ihren Einstellungen zu Staatsausgaben und Staatsschulden befragt. Insbesondere geht es um die Bewertung der Schuldenbremse bzw. um verschiedene Möglichkeiten, sie zu reformieren. Die Auswahl der Befragten erfolgte durch eine mehrstufige Zufallsstichprobe im Rahmen einer Mehrthemenbefragung (Politik-BUS) unter Einschluss von Festnetz- und Mobilfunknummern (Dual-Frame Stichprobe). Bewertung der finanziellen Lage Deutschlands insgesamt bezogen auf Einnahmen und Ausgaben; Einschätzung der Schuldenlast Deutschlands im Vergleich zu den meisten anderen Industriestaaten; Meinung zu Staatsschulden (Schulden des Staates sollten grundsätzlich vermieden werden, sind grundsätzlich kein Problem, sind nur dann sinnvoll, wenn sie für Investitionen für die Zukunft eingesetzt werden); Staat gibt zu viel vs. zu wenig Geld aus für verschiedene politische und gesellschaftliche Aufgaben (Gesundheit und Pflege, Verteidigung, Soziales, Klimaschutz, Wohnungsbau, Integration von Zugewanderten, Renten); Meinung zur Neuaufnahme größerer Kredite durch den Staat nur in außergewöhnlichen Notsituationen wie z.B. Naturkatastrophen (Schuldenbremse sollte so bestehen bleiben wie sie ist, sie sollte reformiert werden oder sie sollte vollständig abgeschafft werden); Bewertung verschiedener Vorschläge zur Reform der Schuldenregelung (die Schuldengrenze verändern, damit der Staat generell mehr Schulden aufnehmen kann als bisher, eine Übergangsregel schaffen, sodass man auch im Jahr nach einer Notsituation noch etwas mehr Kredite aufnehmen kann als gewöhnlich, die Aufnahme höherer Schulden erlauben, wenn die Wirtschaftslage schlechter ist als erwartet, die Aufnahme höherer Schulden erlauben für Verteidigungsausgaben, die Aufnahme höherer Schulden erlauben für Investitionen in den Klimaschutz, die Aufnahme höherer Schulden erlauben für Investitionen in die Infrastruktur wie Straßen und Schienen). Demographie: Geschlecht; Alter; Bildung; Einkommenslage niedrig, mittel, hoch (Nettoäquivalenzeinkommen); Ortsgröße; Parteipräferenz bei der nächsten Bundestagswahl; Wahlverhalten bei der letzten Bundestagswahl. Zusätzlich verkodet wurde: Befragten ID; Region West/Ost; Gewichtungsfaktor.

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]

This dataset contains debts, obligations, and orders placed by Washington State Candidates and Political committees for the last 10 years as reported to the PDC on Schedule B to the C4 Summary Report.

Loans are not included in this dataset. Loans, however, are a debt but are contained in the Loan dataset.

For candidates, the number of years is determined by the year of the election, not necessarily the year the expenditure was reported. For political committees, the number of years is determined by the calendar year of the reporting period.

Candidates and political committees choosing to file under "mini reporting" are not included in this dataset. See WAC 390-16-105 for information regarding eligibility.

This dataset is a best-effort by the PDC to provide a complete set of records as described herewith and may contain incomplete or incorrect information. The PDC provides access to the original reports for the purpose of record verification.

Descriptions attached to this dataset do not constitute legal definitions; please consult RCW 42.17A and WAC Title 390 for legal definitions and additional information regarding political finance disclosure requirements.

CONDITION OF RELEASE: This publication constitutes a list of individuals prepared by the Washington State Public Disclosure Commission and may not be used for commercial purposes. This list is provided on the condition and with the understanding that the persons receiving it agree to this statutorily imposed limitation on its use. See RCW 42.56.070(9) and AGO 1975 No. 15.

The dataset and replication package of the study "A continuous open source data collection platform for architectural technical debt assessment".

Abstract

Architectural decisions are the most important source of technical debt. In recent years, researchers spent an increasing amount of effort investigating this specific category of technical debt, with quantitative methods, and in particular static analysis, being the most common approach to investigate such a topic.

However, quantitative studies are susceptible, to varying degrees, to external validity threats, which hinder the generalisation of their findings.

In response to this concern, researchers strive to expand the scope of their study by incorporating a larger number of projects into their analyses. This practice is typically executed on a case-by-case basis, necessitating substantial data collection efforts that have to be repeated for each new study.

To address this issue, this paper presents our initial attempt at tackling this problem and enabling researchers to study architectural smells at large scale, a well-known indicator of architectural technical debt. Specifically, we introduce a novel approach to data collection pipeline that leverages Apache Airflow to continuously generate up-to-date, large-scale datasets using Arcan, a tool for architectural smells detection (or any other tool).

Finally, we present the publicly-available dataset resulting from the first three months of execution of the pipeline, that includes over 30,000 analysed commits and releases from over 10,000 open source GitHub projects written in 5 different programming languages and amounting to over a billion of lines of code analysed.

Analysis of ‘Evolution of debt vulnerabilities in Africa’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/evadrichter/evolution-of-debt-distress-in-hipc-countries on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Evolution of Debt Vulnerability Classifications in Sub-Saharan African Heavily Indebted Poor Countries

This data contains debt distress vulnerability classifications for thirty Sub-Saharan African countries that have been granted debt relief under the Heavily Indebted Poor Countries (HIPC) initiative. At the turn of the century, heavily indebted countries (most of which were located in Sub-Saharan Africa) were granted large-scale cancellations of external debt owed to the World Bank, International Monetary Fund, and African Development Bank. Since then, the debt sustainability of these countries has been closely monitored by the IMF and World Bank under the Debt Sustainability Analysis for Low Income Countries (DSA for LIC). This DSA has been conducted in Low-Income countries since 2005.

This dataset contains the external debt distress classifications for 30 Sub-Saharan African countries that have been granted debt reductions under the HIPC scheme from 2005 to 2019. If there was no DSA conducted in a year, the DSA classification of the previous year is shown.

Acknowledgements

Data collected by me from documents on https://www.imf.org/en/Publications/DSA.

--- Original source retains full ownership of the source dataset ---

This dataset is extracted from https://en.wikipedia.org/wiki/List_of_countries_by_future_gross_government_debt. Context: There s a story behind every dataset and heres your opportunity to share yours.Content: What s inside is more than just rows and columns. Make it easy for others to get started by describing how you acquired the data and what time period it represents, too. Acknowledgements:We wouldn t be here without the help of others. If you owe any attributions or thanks, include them here along with any citations of past research.Inspiration: Your data will be in front of the world s largest data science community. What questions do you want to see answered?

Japan recorded a Government Debt to GDP of 236.70 percent of the country's Gross Domestic Product in 2024. This dataset provides the latest reported value for - Japan Government Debt to GDP - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Over the past 40 years, private creditors have been the primary source of portfolio capital for developing countries, and capital flows from private creditors to developing countries have increased dramatically. The flow of capital to developing countries presents opportunities; creditors have new investment opportunities, and developing countries are able to finance investment and consumption. But financial integration has also posed challenges. Most develo ping countries still cannot borrow in international capital markets, and creditors have difficulty recovering investments after governments default due to lack of enforcement of international debt contracts. This dissertation presents three essays that examine how politics shape interactions between developing countries and private creditors in the market for sovereign lending. The first essay considers the international allocation of credit. Existing research argues that democracies are more creditworthy than autocracies, but empirical tests have failed to discover such a ``democratic advantage.'' Using a panel dataset of more than 130 developing countries between 1980 and 2000, I s how that creditors are more likely to lend to democracies than autocracies. The second essay examines a government's decision to repay its debt or default. Developing countries with close ties to developed countries expect to be bailed out after default and expectations of a bailout increase the likelihood of default. Using a panel dataset of more than 100 developing countries between 1975 and 2004, I show that developing countries with political and economic ties to developed countries are more likely to default and are more likely to secure debt relief a fter defaulting than other developing countries. The third essay analyzes debt restructuring after default. Using a game theoretic model, I show how high domestic political costs of adjustment result in favorable restructurings. I argue that mixed regimes are particularly fragile and pay higher costs of adjustment than either full-fledged democracies or autocracies. Using a new dataset on debt reschedulings during the 1980s debt crisis, I find evidence that creditors provide fa vorable restructuring terms to mixed regimes. Overall, the dissertation demonstrates how specific political factors affect creditor-debtor interactions in sovereign debt markets.

Public authorities are required by Section 2800 of Public Authorities Law to submit annual reports to the Authorities Budget Office that includes a schedule of the authorities’ debt. The dataset consists of a schedule of debt reported by State Authorities that covers 8 fiscal years, which includes fiscal years ending in the most recently completed calendar year.