This statistic shows the national debt of the emerging market and developing economies from 2020 to 2024 in relation to gross domestic product (GDP), with projections up until 2030. The figures are aggregated and refer to the whole country respectively, and include the debts of the state, the communities, the municipalities and the social insurances. In 2024, the national debt of the emerging market and developing economies amounted to approximately 69.47 percent of GDP.

The Emerging Markets Bond Index (EMBI+), commonly known as "riesgo país" in Spanish speaking countries, is a weighted capitalization market benchmark that measures the financial returns obtained each day by a selected portfolio of government bonds from emerging countries. It is measured in base points, which reflect the difference between the return rates paid by emerging countries' government bonds and those offered by U.S. government securities, considered a safety benchmark. In 2023, Venezuela had the highest EMBIG, amounting to more than 21,422 points. Bolivia followed second, with an index of over 2,200. In the same period, the Latin American economies with the lowest sovereign risk was Uruguay and Chile, with EMBIG levels below 140 basis points.

Public debt for the Pacific island countries and territories per year.

Find more Pacific data on PDH.stat.

This replication package contains all Python Jupyter notebooks required to reproduce every table and figure in the paper Argentina: The Honor Student—By Merit and By Mistake. A Natural Experiment on “Information Effects”, including the Online Appendix. Each result is generated by its own notebook. A README accompanies the project as a whole, providing instructions and additional details.

Brazil is Latin America's largest economy based on annual gross domestic product. As of July 2024, Brazil's Emerging Markets Bond Index stood at 228 points, almost 29 points higher than at the same period one year earlier. This index is a weighted capitalization market benchmark that measures the financial returns obtained each day by a selected portfolio of government bonds from emerging countries.The EMBI+, more commonly known as "risco país" in Portuguese, is measured in base points. These show the difference between the return rates paid by emerging countries' government bonds and those offered by the U.S. Treasury. Based on Brazil's EMBI as of October 27, 2020, the annual return rates of Brazilian sovereign debt titles were estimated to be 315 index points higher than those offered by U.S. Treasury bills. This difference is known as "spread".

Denmark recorded a Government Debt to GDP of 31.10 percent of the country's Gross Domestic Product in 2024. This dataset provides - Denmark Government Debt To GDP - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The dataset included with this article contains three files describing and defining the sample and variables for VAT impact, and Excel file 1 consists of all raw and filtered data for the variables for the panel data sample. Excel file 2 depicts time-series and cross-sectional data for nonfinancial firms listed on the Saudi market for the second and third quarters of 2019 and the third and fourth quarters of 2020. Excel file 3 presents the raw material of variables used in measuring the company's profitability of the panel data sample

Graph and download economic data for ICE BofA Emerging Markets Corporate Plus Index Total Return Index Value (BAMLEMCBPITRIV) from 1998-12-31 to 2025-12-01 about return, emerging markets, corporate, indexes, and USA.

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12064410%2F5d593c922def359a7cfc25b87eff667e%2Fus%20debt%20flag.png?generation=1676702443974125&alt=media" alt="">

DAY ~11,000 (April 1st, 1993 to Present-Day)

This is a dataset that tracks several figures regarding US debt (to the penny) since 1993.

All data are official figures from the U.S. Treasury that have been compiled and structured by myself. Dates on the weekend (Saturday and Sunday), as well as federal holidays, are excluded from the debt tracker because the Treasury's fiscal data do not account for those days. Recent political debates in the US over the potential raising of the debt ceiling has inspired me to create this dataset. Personally, I believe that the issue will continue to dominate political discourse due to the increasing polarization between Democrats and Republicans.

Data Sources

The primary data source used was the U.S. Treasury's official website, which publishes fiscal data pertaining to the American government. Considering the meticulous documentation of federal spending by the Treasury, no other authority is more equipped to provide insight on US debt.

1. U.S. Treasury's FiscalData Website - The United States Department of the Treasury published daily updates on the national debt since April 1st, 1993. However, intragovernmental holdings and total public debt outstanding have only been accounted for at the end of each fiscal year since 1997. Daily updates for those two statistics officially began since March 31st, 2005.
2. U.S. Treasury's Finance Guide to the National Debt - The United States Department of the Treasury released a detailed overview of the national debt and how it operates in conjunction with American society. The guide mainly provided essential contextual knowledge needed to create a meaningful dataset.

Statistics Being Tracked

• Debt Held by the Public
• Intragovernmental Holdings
• Total Public Debt Outstanding

Dataset History

2023-02-17 - Dataset is created (10,914 days after temporal coverage start date).

GitHub Repository - The same data but on GitHub.

Code Starter

Link to Notebook Important: Each new record is accumulated data from previous days.

The compiled database covers 60 years of recent financial history of 47 economies and is first to include the 2018 crisis in Turkey and the 2020 sovereign debt crisis in Argentina. It covers such variables as debt/gdp levels for different sectors of the economy (state, households, nonfinancial and financial sector), credit/gdp gap, residential property price statistics,

The paper is focused on early warning indicators of financial crises applicable to Russia. Using the stepwise regression approach the author identifies early warning indicators for banking and currency crises in advanced and emerging market economies. The proposed prediction model for banking crisis in Russia and emerging market economies includes credit gap and real residential property price index growth. The author explores the possibility of inclusion of residential property price index into the informational base for the countercyclical capital buffer estimation by the Bank of Russia. An analysis of currency crises indicates that private debt-to-service ratio contains useful information for prediction of currency crisis in Russia and emerging market economies.

Compiled data is based on statistics published by Bank for International Settlements, Institute for International Finance and Joint External Debt Hub.

Key information about Sweden Government Debt: % of GDP

• Sweden Government debt accounted for 33.3 % of the country's Nominal GDP in Jun 2025, compared with the ratio of 34.8 % in the previous quarter.
• Sweden government debt to GDP ratio data is updated quarterly, available from Mar 1996 to Jun 2025.
• The data reached an all-time high of 67.4 % in Dec 1996 and a record low of 30.8 % in Jun 2023.

CEIC calculates quarterly Government Debt as % of Nominal GDP from quarterly Government Debt and rolling sum of quarterly Nominal GDP. Eurostat provides Government Debt in EUR. Statistics Sweden provides Nominal GDP in local currency. The Riksbank average market exchange rate is used for currency conversions.


Related information about Sweden Government Debt: % of GDP

• In the latest reports, Sweden National Government Debt reached 231.4 USD bn in Jun 2025.
• The country's Nominal GDP reached 169.1 USD bn in Sep 2025.

Index Time Series for iShares J.P. Morgan EM High Yield Bond ETF. The frequency of the observation is daily. Moving average series are also typically included. The fund will invest at least 80% of its assets in the component securities of the underlying index, and the fund will invest at least 90% of its assets in fixed income securities of the types included in the underlying index that BFA believes will help the fund track the underlying index. The index tracks the performance of below investment-grade U.S. dollar-denominated, emerging market fixed and floating-rate debt securities issued by corporate, sovereign, and quasi-sovereign entities.

Graph and download economic data for ICE BofA Emerging Markets Corporate Plus Index Option-Adjusted Spread (BAMLEMCBPIOAS) from 1998-12-31 to 2025-12-01 about emerging markets, option-adjusted spread, corporate, indexes, and USA.

Annual data on the structure of general government gross debt - Maastricht debt (ESA table 28A) is provided according to the European System of Accounts ESA 2010 Transmission Programme (Regulation (EU) No 549/2013, as amended by Regulation (EU) No 2023/734) and covers all EU Member States.

The majority of the 2330 collected data series are provided on a voluntary basis, but 36 series are to be provided on a compulsory basis (subject to derogations provided for in Commission implementing decision 2014/403).

The data is structured into the following data sets:

General government gross debt by subsector, by initial (original) maturity, by financial instrument and by sector of debt holder (gov_10dd_ggd): Containing data for general government and the subsectors by financial instrument, original maturity and counterpart sector. A breakdown for gross debt at variable interest is also included. A few series on transactions rather than balance sheets complement this collection.

• General government gross debt by currency of issuance (denomination) (gov_10dd_dcur): Containing data for general government and central government by currency denomination. It also includes the few series on transactions by currency denomination.
• Remaining maturity and average remaining maturity of debt (gov_10dd_rmd): The dataset contains data for general government and central government gross debt broken down by remaining maturity. Data for general government gross debt at variable interest by remaining maturity are also included here. The average remaining maturity of general government and central government gross debt is a part of this collection.
• Apparent cost of the debt (gov_10dd_acd): This may be defined as the interest rate applicable to the total Maastricht debt (AF.2, AF.3, and AF.4). It is a rate published on the basis of data supplied by compilers for general government and central government.
• Government guarantees (contingent liabilities) (gov_10dd_guar): Containing data for general government and central government on guarantees broken down by counterpart sector. Guarantees consist of on-off and standardised guarantees. Standardised guarantees reported within total guarantee amounts are guarantees that are usually issued in large numbers and for fairly small amounts, with similar features, for example mortgage loan guarantees, student loan guarantees etc. An estimate for expected loss can be made for standardised guarantees - this is expensed when the standardised guarantees are granted. The stock of guarantees are contingent liabilities and they are not part of general government gross debt.

In 2024, the gross government debt of China amounted to an estimated ** percent of the country's gross domestic product (GDP), compared to ** percent for Russia. For China, this was an increase over 2001 levels, when the gross government debt amounted to ** percent of the country's GDP. Russia, on the other hand, has reduced this figure from 2001 levels, when gross government debt was ** percent of the country's GDP.

Emerging markets face large and persistent fluctuations in sovereign spreads. To what extent are these fluctuations driven by local shocks versus financial conditions in advanced economies? To answer this question, we develop a neoclassical business cycle model of a world economy with an advanced country, the North, and many emerging market economies, the South. Northern households invest in domestic stocks, domestic defaultable bonds, and international sovereign debt. Over the 2008-2016 period, the global cycle phase, the North accounts for 68% of Southern spreads' fluctuations. Over the whole 1994-2024 period, however, Northern shocks account for less than 20% of these fluctuations.

Annual data on the structure of general government gross debt - Maastricht debt (ESA table 28A) is provided according to the European System of Accounts ESA 2010 Transmission Programme (Regulation (EU) No 549/2013, as amended by Regulation (EU) No 2023/734) and covers all EU Member States.

The majority of the 2330 collected data series are provided on a voluntary basis, but 36 series are to be provided on a compulsory basis (subject to derogations provided for in Commission implementing decision 2014/403).

The data is structured into the following data sets:

General government gross debt by subsector, by initial (original) maturity, by financial instrument and by sector of debt holder (gov_10dd_ggd): Containing data for general government and the subsectors by financial instrument, original maturity and counterpart sector. A breakdown for gross debt at variable interest is also included. A few series on transactions rather than balance sheets complement this collection.

• General government gross debt by currency of issuance (denomination) (gov_10dd_dcur): Containing data for general government and central government by currency denomination. It also includes the few series on transactions by currency denomination.
• Remaining maturity and average remaining maturity of debt (gov_10dd_rmd): The dataset contains data for general government and central government gross debt broken down by remaining maturity. Data for general government gross debt at variable interest by remaining maturity are also included here. The average remaining maturity of general government and central government gross debt is a part of this collection.
• Apparent cost of the debt (gov_10dd_acd): This may be defined as the interest rate applicable to the total Maastricht debt (AF.2, AF.3, and AF.4). It is a rate published on the basis of data supplied by compilers for general government and central government.
• Government guarantees (contingent liabilities) (gov_10dd_guar): Containing data for general government and central government on guarantees broken down by counterpart sector. Guarantees consist of on-off and standardised guarantees. Standardised guarantees reported within total guarantee amounts are guarantees that are usually issued in large numbers and for fairly small amounts, with similar features, for example mortgage loan guarantees, student loan guarantees etc. An estimate for expected loss can be made for standardised guarantees - this is expensed when the standardised guarantees are granted. The stock of guarantees are contingent liabilities and they are not part of general government gross debt.

Content

More details about each file are in the individual file descriptions.

Context

This is a dataset hosted by the World Bank. The organization has an open data platform found here and they update their information according the amount of data that is brought in. Explore the World Bank using Kaggle and all of the data sources available through the World Bank organization page!

• Update Frequency: This dataset is updated daily.

Acknowledgements

This dataset is maintained using the World Bank's APIs and Kaggle's API.

Cover photo by NA on Unsplash
Unsplash Images are distributed under a unique Unsplash License.

Emerging market economies (aggregate) - Credit from All sectors to General government at Nominal value, Percentage of GDP (using PPP exchange rates), Adjusted for breaks

The Fiscal Monitor surveys and analyzes the latest public finance developments, it updates fiscal implications of the crisis and medium-term fiscal projections, and assesses policies to put public finances on a sustainable footing.

Country-specific data and projections for key fiscal variables are based on the April 2020 World Economic Outlook database, unless indicated otherwise, and compiled by the IMF staff. Historical data and projections are based on information gathered by IMF country desk officers in the context of their missions and through their ongoing analysis of the evolving situation in each country; they are updated on a continual basis as more information becomes available. Structural breaks in data may be adjusted to produce smooth series through splicing and other techniques. IMF staff estimates serve as proxies when complete information is unavailable. As a result, Fiscal Monitor data can differ from official data in other sources, including the IMF's International Financial Statistics.

The country classification in the Fiscal Monitor divides the world into three major groups: 35 advanced economies, 40 emerging market and middle-income economies, and 40 low-income developing countries. The seven largest advanced economies as measured by GDP (Canada, France, Germany, Italy, Japan, United Kingdom, United States) constitute the subgroup of major advanced economies, often referred to as the Group of Seven (G7). The members of the euro area are also distinguished as a subgroup. Composite data shown in the tables for the euro area cover the current members for all years, even though the membership has increased over time. Data for most European Union member countries have been revised following the adoption of the new European System of National and Regional Accounts (ESA 2010). The low-income developing countries (LIDCs) are countries that have per capita income levels below a certain threshold (currently set at $2,700 in 2016 as measured by the World Bank's Atlas method), structural features consistent with limited development and structural transformation, and external financial linkages insufficiently close to be widely seen as emerging market economies. Zimbabwe is included in the group. Emerging market and middle-income economies include those not classified as advanced economies or low-income developing countries. See Table A, "Economy Groupings," for more details.

Most fiscal data refer to the general government for advanced economies, while for emerging markets and developing economies, data often refer to the central government or budgetary central government only (for specific details, see Tables B-D). All fiscal data refer to the calendar years, except in the cases of Bangladesh, Egypt, Ethiopia, Haiti, Hong Kong Special Administrative Region, India, the Islamic Republic of Iran, Myanmar, Nepal, Pakistan, Singapore, and Thailand, for which they refer to the fiscal year.

Composite data for country groups are weighted averages of individual-country data, unless otherwise specified. Data are weighted by annual nominal GDP converted to U.S. dollars at average market exchange rates as a share of the group GDP.

In many countries, fiscal data follow the IMF's Government Finance Statistics Manual 2014. The overall fiscal balance refers to net lending (+) and borrowing ("") of the general government. In some cases, however, the overall balance refers to total revenue and grants minus total expenditure and net lending.

The fiscal gross and net debt data reported in the Fiscal Monitor are drawn from official data sources and IMF staff estimates. While attempts are made to align gross and net debt data with the definitions in the IMF's Government Finance Statistics Manual, as a result of data limitations or specific country circumstances, these data can sometimes deviate from the formal definitions.