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.

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]

Key information about Australia Household Debt: % of GDP

• Australia household debt accounted for 116.6 % of the country's Nominal GDP in Mar 2023, compared with the ratio of 118.0 % in the previous quarter.
• Australia household debt to GDP ratio is updated quarterly, available from Jun 1988 to Mar 2023.
• The data reached an all-time high of 129.4 % in Sep 2016 and a record low of 44.2 % in Sep 1988.

• In the latest reports, Australia Household Debt reached 1,957.6 USD bn in Mar 2023.
• Money Supply M2 in Australia increased 4.1 % YoY in Jun 2023.
• Australia Foreign Exchange Reserves was measured at 37.1 USD bn in Jun 2023.
• The Foreign Exchange Reserves equaled 1.5 Months of Import in May 2023.
• Australia Domestic Credit reached 3,627.0 USD bn in May 2023, representing an increased of 1.9 % YoY.
• The country's Non Performing Loans Ratio stood at 0.8 % in Mar 2023, compared with the ratio of 0.8 % in the previous quarter.

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 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.

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 ---

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.

Households Debt in South Africa increased to 62.50 percent of gross income in 2024 from 62.40 percent in 2023. This dataset provides - South Africa Households Debt To Income- actual values, historical data, forecast, chart, statistics, economic calendar and news.

India recorded a Government Debt to GDP of 81.59 percent of the country's Gross Domestic Product in 2023. This dataset provides - India Government Debt To GDP - actual values, historical data, forecast, chart, statistics, economic calendar and news.

World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates. [Note: Even though Global Development Finance (GDF) is no longer listed in the WDI database name, all external debt and financial flows data continue to be included in WDI. The GDF publication has been renamed International Debt Statistics (IDS), and has its own separate database, as well.

Last Updated:01/28/2025

Data contains Following 20 Countries 'Argentina', 'Australia', 'Brazil', 'China', 'France', 'Germany', 'India', 'Indonesia', 'Italy', 'Japan', 'Korea, Rep.', 'Mexico', 'Netherlands', 'Russian Federation', 'Saudi Arabia', 'Spain', 'Switzerland', 'Turkiye', 'United Kingdom', 'United States'

Dataset contains below Development Indicators 'Adolescent fertility rate (births per 1,000 women ages 15-19)', 'Agriculture, forestry, and fishing, value added (% of GDP)', 'Annual freshwater withdrawals, total (% of internal resources)', 'Births attended by skilled health staff (% of total)', 'Contraceptive prevalence, any method (% of married women ages 15-49)', 'Domestic credit provided by financial sector (% of GDP)', 'Electric power consumption (kWh per capita)', 'Energy use (kg of oil equivalent per capita)', 'Exports of goods and services (% of GDP)', 'External debt stocks, total (DOD, current US$)', 'Fertility rate, total (births per woman)', 'Foreign direct investment, net inflows (BoP, current US$)', 'Forest area (sq. km)', 'GDP (current US$)', 'GDP growth (annual %)', 'GNI per capita, Atlas method (current US$)', 'GNI per capita, PPP (current international $)', 'GNI, Atlas method (current US$)', 'GNI, PPP (current international $)', 'Gross capital formation (% of GDP)', 'High-technology exports (% of manufactured exports)', 'Immunization, measles (% of children ages 12-23 months)', 'Imports of goods and services (% of GDP)', 'Income share held by lowest 20%', 'Industry (including construction), value added (% of GDP)', 'Inflation, GDP deflator (annual %)', 'Life expectancy at birth, total (years)', 'Merchandise trade (% of GDP)', 'Military expenditure (% of GDP)', 'Mobile cellular subscriptions (per 100 people)', 'Mortality rate, under-5 (per 1,000 live births)', 'Net barter terms of trade index (2015 = 100)', 'Net migration', 'Net official development assistance and official aid received (current US$)', 'Personal remittances, received (current US$)', 'Population density (people per sq. km of land area)', 'Population growth (annual %)', 'Population, total', 'Poverty headcount ratio at $2.15 a day (2017 PPP) (% of population)', 'Poverty headcount ratio at national poverty lines (% of population)', 'Prevalence of HIV, total (% of population ages 15-49)', 'Prevalence of underweight, weight for age (% of children under 5)', 'Primary completion rate, total (% of relevant age group)', 'Revenue, excluding grants (% of GDP)', 'School enrollment, primary (% gross)', 'School enrollment, primary and secondary (gross), gender parity index (GPI)', 'School enrollment, secondary (% gross)', 'Surface area (sq. km)', 'Tax revenue (% of GDP)', 'Terrestrial and marine protected areas (% of total territorial area)', 'Time required to start a business (days)', 'Total debt service (% of exports of goods, services and primary income)', 'Urban population growth (annual %)

The Worldwide Fixed Income (WFI) Service enables you to keep track of new bond issues or changes in terms and conditions for both corporate and government issuances. Data is sourced globally from stock exchanges, central banks, ministries of finance, lead managers, paying, calculation and transfer agents.

The fixed income data service cover 40 event types including redemption, conversion, defaults and contains static data outlining key terms and conditions and call schedules. EDI can provide you with pricing supplements, offering circulars, term sheets and prospectuses for as many securities as possible subject to availability. It covers approximately 30% of the Fixed Income database. Use cases: Bond Issuance Tracking | Portfolio Risk Management | Portfolio Valuation | Investment Management | Market Analysis

With the service you will have access to: -International debt securities in more than 150 countries A broad range of asset types including: -Convertibles -FRNs -Permanent interest bearing shares -Preferred securities -Treasury bills In addition, where possible we can extend both instruments and geographic coverage to fully cover your portfolio.

Originally in the equity space, Exchange Data International (EDI) moved to the Fixed Income arena following an increased demand from clients to add debt instruments to its coverage. As the firm was approached by a major credit rating agency to build a customised fixed income service, it developed its own Fixed Income service providing global coverage of the debt market. New countries and sources are continually researched and added to enhance geographic coverage and increase the volume of securities in the database. The service provides historical data back from 2007.

Asset Classes Fully covered: • Canadian strip packages without underlying • Cash management bills • Certificate of deposit (tenure more than 28 days) • Commercial papers (tenure more than 28 days) • Convertibles • Corporate bonds • Government bonds • Municipal securities • Short-term corporate Bonds • Short-term government Bonds • Strips (parent needed) • Treasury bills

Covered if in portfolio: • Asset-backed securities (ABS) (securities entered with critical fields and just covered for live • client’s portfolio and Canada; offering documents processed for live clients; corporate actions not maintained) • Certificates (just covered for live client’s portfolio) • Mortgage-backed securities (MBS) (securities entered with critical fields and just covered for live client’s portfolio and Canada, offering documents processed for live clients; corporate actions not maintained) • Musharaka Sukuks (securities entered with critical fields and just covered for live client’s Portfolio; offering documents processed for live clients; corporate actions not maintained) • Structured Products • Genussschein (AT, CH and DE) • Mortgage-pass through certificates • Pass-through certificates In addition, EDI provides a comprehensive global Fixed Income Corporate Action/Event service, to compliment the reference data, including security and issuer level events and distributions.

This paper mainly analyzes the three most salient risks, namely fiscal risk, governance risk and environmental risk host countries of BRI might confront. First, the implementation of BRI is in the context of the rapid rise of public and corporate debt levels, which increases the financial risk and vulnerability of host countries, mostly low-income developing countries. Large scale debt financing, especially in foreign currency and non-concessional terms, may lead to a rapid deterioration of the already increased debt vulnerability in the medium term. Second, most of BRI is carried out under the bilateral cooperation mechanism. The lack of transparency in largescale public project procurement and information disclosure brings governance and geopolitical risks to the host country. Third, the existing infrastructure projects under BRI has shown that the environmental risk of the host country is significantly increased, which poses a great threat to local, sustainable development. This paper mainly analyzes the three most salient host countries of BRI (Belt and Road Initiative) might confront: * Fiscal risk (case study: Laos-China Railway) * Government risk (case study: East Coast Rail Link-ECRL) * Environmental and social risk (Case study: Myitsone Dam in Myanmar)

Objective: The INVEDUC project analyses public attitudes and preferences of citizens regarding different aspects of education policy in eight Western European countries. It also studies to what extent and via which mechanisms public opinion influences processes of policy-making.

Method: The INVEDUC survey of public opinion on education policy was conducted in April in May 2014 in eight Western European countries: Denmark, France, Germany, Ireland, Italy, Spain, Sweden and the United Kingdom. The total number of observations is 8,905 (i.e. between 1,000 and 1,500 for the different countries), drawn from random samples of the respective populations. The interviews were conducted by native speakers via computer-assisted telephone interviewing (CATI) and implemented by TNS Infratest Sozialforschung, Munich.

Questionnaire content: The survey covers the following aspects related to education policy: support for education spending relative to spending for other social policies; preferences for the distribution of education spending across different sectors of the education system (early childhood education and care, general schools, vocational education and training, higher education); willingness to pay taxes for additional spending on education; support for education spending in the face of different fiscal and policy trade-offs (higher taxes, higher public debt, cutbacks in other parts of the welfare state); support for social investment policies vs. social transfers and workfare policies; attitudes and preferences regarding the governance of education (comprehensive education, decentralisation of education governance, division of labor between public and private provision of education, school competition, role of employers in VET). The survey contains a number of experimental components, in particular when measuring the effect of trade-offs on preferences.

Demography: national citizenship; other citizenship; city size; financial situation of household; age (year of birth); sex; highest educational attainment (country-specific); age at completion of full-time education; employment status or age at completion of full-time education; current situation; reasons for part-time employment; occupational status; occupation (ISCO 2008); public service employment; sector; likelihood of own unemployment; net household income (country specific, classified); net personal income; education-related debt; household size; number of children in household; number of children under 10 years of age in household; single parent; trade union membership; parents´ university degree.

Advani, Hughson and Tarrant (2021) model the revenue that could be raised from an annual and a one-off wealth tax of the design recommended by Advani, Chamberlain and Summers in the Wealth Tax Commission’s Final Report (2020). This deposit contains the code required to replicate the revenue modelling and distributional analysis. The modelling draws on data from the Wealth and Assets Survey, supplemented with the Sunday Times Rich List, which we use to implement a Pareto correction for the under-coverage of wealth at the top.Around the world, the unprecedented public spending required to tackle COVID-19 will inevitably be followed by a debate about how to rebuild public finances. At the same time, politicians in many countries are already facing far-reaching questions from their electorates about the widening cracks in the social fabric that this pandemic has exposed, as prior inequalities become amplified and public services are stretched to their limits. These simultaneous shocks to national politics inevitably encourage people to 'think big' on tax policy. Even before the current crisis there were widespread calls for reforms to the taxation of wealth in the UK. These proposals have so far focused on reforming existing taxes. However, other countries have begun to raise the idea of introducing a 'wealth tax'-a new tax on ownership of wealth (net of debt). COVID-19 has rapidly pushed this idea higher up political agendas around the world, but existing studies fall a long way short of providing policymakers with a comprehensive blueprint for whether and how to introduce a wealth tax. Critics point to a number of legitimate issues that would need to be addressed. Would it be fair, and would the public support it? Is this type of tax justified from an economic perspective? How would you stop the wealthiest from hiding their assets? Will they all simply leave? How can you value some assets? What happens to people who own lots of wealth, but have little income with which to pay a wealth tax? And if wealth taxes are such a good idea, why have many countries abandoned them? These are important questions, without straightforward answers. The UK government last considered a wealth tax in the mid-1970s. This was also the last time that academics and policymakers in the UK thought seriously about how such a tax could be implemented. Over the past half century, much has changed in the mobility of people, the structure of our tax system, the availability of data, and the scope for digital solutions and coordination between tax authorities. Old plans therefore cannot be pulled 'off the shelf'. This project will evaluate whether a wealth tax for the UK would be desirable and deliverable. We will address the following three main research questions: (1) Is a wealth tax justified in principle, on economic or other grounds? (2) How should a wealth tax be designed, including definition of the tax base and solutions to administrative challenges such as valuation and liquidity? (3) What would be the revenue and distributional effects of a wealth tax in the UK, for a variety of design options and at specified rates/thresholds? To answer these questions, we will draw on a network of world-leading exports on tax policy from across academia, policy spheres, and legal practice. We will examine international experience, synthesising a large body of existing research originating in countries that already have (or have had) a wealth tax. We will add to these resources through novel research that draws on adjacent fields and disciplines to craft new solutions to the practical problems faced in delivering a wealth tax. We will also review common objections to a wealth tax. These new insights will be published in a series of 'evidence papers' made available directly to the public and policymakers. We will also publish a final report that states key recommendations for government and (if appropriate) delivers a 'ready to legislate' design for a wealth tax. We will not recommend specific rates or thresholds for the tax. Instead, we will create an online 'tax simulator' so that policymakers and members of the public can model the revenue and distributional effects of different options. We will also work with international partners to inform debates about wealth taxes in other countries. The modelling draws on data from the Wealth and Assets Survey, supplemented with the Sunday Times Rich List, which we use to implement a Pareto correction for the under-coverage of wealth at the top.

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 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. Telephone interview: CATI Deutschsprachige Bevölkerung ab 14 Jahren mit einem Festnetz- oder Mobilfunkanschluss German-speaking population aged 14 and over with a landline or mobile phone connection. Wahrscheinlichkeitsauswahl: Mehrstufige Zufallsauswahl; Auswahlverfahren Kommentar: Bei der Auswahl der Befragungsteilnehmer im Rahmen der forsa-Mehrthemenumfrage (Politik-BUS) werden sowohl Festnetz- als auch Mobilfunknummern einbezogen. Die Stichprobenbildung erfolgt daher auf der Grundlage einer kombinierten Festnetz- und Mobilfunkstichprobe (sog. ADM Dual-Frame-Design). Das Verhältnis der Interviews, die über den Mobil-Auswahlrahmen gewonnen werden, zu denen, die über den Festnetzrahmen gewonnen werden, beträgt 30:70. Die Auswahl der Teilnehmer mit einem Festnetzanschluss erfolgt durch eine mehrfach geschichtete, mehrstufige Zufallsstichprobe auf Basis des ADM-Telefonstichproben-Systems. Die Auswahlgrundlage ist das so genannte ADM-Telefon-Mastersample. Ist ein Haushalt mit Festnetzanschluss auf Basis des ADM-Telefon-Mastersamples ausgewählt, so erfolgt auf der zweiten Stufe des Auswahlprozesses die Auswahl der zu befragenden Person innerhalb des Haushalts. Handelt es sich um einen Ein-Personen-Haushalt, so steht die Befragungsperson bereits eindeutig fest. Leben mehrere Personen der Grundgesamtheit im Haushalt, so ermittelt der Interviewer die zu befragende Person mithilfe der sogenannten Geburtstagsmethode.

Philippines recorded a Government Debt to GDP of 60.70 percent of the country's Gross Domestic Product in 2024. This dataset provides - Philippines Government Debt To GDP - actual values, historical data, forecast, chart, statistics, economic calendar and news.