Irelande

Composite Indicator of Systemic Stress (CISS)

The consolidated banking statistics (CBS) measure international banking activity from a nationality perspective, focusing on the country where the banking group's parent is headquartered. While residence-based data such as the locational banking statistics indicate where positions are booked, they do not always identify where underlying decisions are made. This is because banking offices in one country may operate within a business model decided by the group's controlling parent, which may be headquartered in another country. The CBS capture the worldwide claims of banking groups based in reporting countries and exclude intragroup positions, similar to the consolidation approach followed by banking supervisors. The CBS provide several different measures of banking groups' country risk exposures, on either an immediate counterparty or an ultimate risk basis. The most appropriate exposure measure depends on the issue being analysed. The benchmark measure in the CBS is foreign claims, which capture credit to borrowers outside a banking group's home country.   Measure for all Combinations - Amounts Outstanding / Stocks   Note: Under "Reporting country" they have removed "Euro Area".   Data cited at : https://www.bis.org/statistics/index.htm

Below Parameters are common for all combinations : Frequency - Quarterly Measure -Amounts Outstanding / Stocks CBS Bank Type - Domestic Banks CBS Reporting Basis - Immediate Counterparty Basis Balance Sheet Position - Total Claims Type of Instruments - All Instruments Remaining Maturity - All Maturities Currency Type of Booking Location - All Currencies Counterparty Sector - All Sectors Data cited at : https://www.bis.org/statistics/index.htm

COFR presents data on fiscal transparency. It provides an overview of fiscal reporting, including whether fiscal data are available for all of the general government, whether the government reports a balance sheet, and whether spending and revenue are reported on a cash or accrual basis. It also derives specific indices of the coverage of public institutions, fiscal flows, and fiscal stocks.

The data set on credit to the non-financial sector captures borrowing activity by the government sector and the private non-financial sector in more than 40 economies. Quarterly data on credit to the government sector cover on average 20 years, while those on credit to the private non-financial sector on average more than 45 years. The statistics follow the framework of the System of National Accounts.   Data cited at: Bank for International Settlements (2024), Credit to the non-financial sector, BIS WS_TC 2.0 (data set), https://data.bis.org/topics/TOTAL_CREDIT/data.

>The Securities Industry and Financial Markets Association (SIFMA) prepared this material for informational purposes only. SIFMA obtained this information from multiple sources believed to be reliable as of the date of publication; SIFMA, however, makes no representations as to the accuracy or completeness of such third party information. SIFMA has no obligation to update, modify or amend this information or to otherwise notify a reader thereof in the event that any such information becomes outdated, inaccurate, or incomplete. >The Securities Industry and Financial Markets Association (SIFMA) brings together the shared interests of hundreds of securities firms, banks and asset managers. SIFMA's mission is to support a strong financial industry, investor opportunity, capital formation, job creation and economic growth, while building trust and confidence in the financial markets. SIFMA, with offices in New York and Washington, D.C., is the U.S. regional member of the Global Financial Markets Association (GFMA). For more information, visit www.sifma.org.

The Financial Freedom Index is based on 15 indicators and sub-indicators. For this tabular overview of the entire index the 6 types of tax rates and 3 international taxation indicators have been combined as one "tax score." The other six main indicators are shown as they appear on the "By Indicator" pages. Due to lack of data for some countries, not all nations have been included in the ranking. A score of 1.00 is most favorable, i.e., a 1.00 "tax score" translates into low taxes, as a 1.00 "cost of living score" translates into low living costs.

The financial indicators in this dataset are derived from OECD countries’ financial accounts (transactions): they give a picture of the short-term behavior of institutional sectors. They comprise for instance: Net financial transactions of the general government, as a percentage of Gross Domestic Product (GDP), which corresponds to the general government deficit; Transactions in financial assets of Households and NPISHs, as a percentage of Households Gross Disposable Income (GDI); Transactions in liabilities of Households and NPISHs, as a percentage of GDI.

The financial indicators in this dataset are constructed from OECD countries’ financial balance sheets (stocks): these ratios are considered as relevant to analyse the position and performance of the various institutional sectors. They comprise for instance: Financial net worth of Households and NPISHs, as a percentage of GDI; Non-financial corporations debt to equity ratio; Private sector debt; Leverage of the banking sector; General government debt, as a percentage of GDP.

Eurostat Dataset Id:ei_bsfs_m Six qualitative surveys are conducted on a monthly basis in the following areas: manufacturing industry, construction, consumers, retail trade, services and financial services. Some additional questions are asked on a quarterly basis in the surveys in industry, services, financial services, construction and among consumers. In addition, a survey is conducted twice a year on Investment in the manufacturing sector. The domain consists of a selection for variables from the following type of survey: Industry monthly questions for: production, employment expectations, order-book levels, stocks of finished products and selling price. Industry quarterly questions for:production capacity, order-books, new orders, export expectations, capacity utilization, Competitive position and factors limiting the production. Construction monthly questions for: trend of activity, order books, employment expectations, price expectations and factors limiting building activity. Construction quarterly questions for: operating time ensured by current backlog. Retail sales monthly questions for: business situation, stocks of goods, orders placed with suppliers and firm's employment. Services monthly questions for: business climate, evolution of demand, evolution of employment and selling prices. Services quarterly question for: factors limiting their business Consumer monthly questions for: financial situation, general economic situation, price trends, unemployment, major purchases and savings. Consumer quarterly questions for: intention to buy a car, purchase or build a home, home improvements. Financial services monthly questions for: business situation, evolution of demand and employment Financial services quarterly questions for: operating income, operating expenses, profitability of the company, capital expenditure and competitive position Monthly Confidence Indicators are computed for industry, services, construction, retail trade, consumers (at country level, EU and euro area level) and financial services (EU and euro area). An Economic Sentiment indicator (ESI) is calculated based on a selection of questions from industry, services, construction, retail trade and consumers at country level and aggregate level (EU and euro area). A monthly Euro-zone Business Climate Indicator is also available for industry. The data are published: as balance i.e. the difference between positive and negative answers (in percentage points of total answers)as indexas confidence indicators (arithmetic average of balances),at current level of capacity utilization (percentage)estimated months of production assured by orders (number of months)Unadjusted (NSA) and seasonally adjusted (SA)

Eurostat Dataset Id:ei_bsfs_q Six qualitative surveys are conducted on a monthly basis in the following areas: manufacturing industry, construction, consumers, retail trade, services and financial services. Some additional questions are asked on a quarterly basis in the surveys in industry, services, financial services, construction and among consumers. In addition, a survey is conducted twice a year on Investment in the manufacturing sector. The domain consists of a selection for variables from the following type of survey: Industry monthly questions for: production, employment expectations, order-book levels, stocks of finished products and selling price. Industry quarterly questions for:production capacity, order-books, new orders, export expectations, capacity utilization, Competitive position and factors limiting the production. Construction monthly questions for: trend of activity, order books, employment expectations, price expectations and factors limiting building activity. Construction quarterly questions for: operating time ensured by current backlog. Retail sales monthly questions for: business situation, stocks of goods, orders placed with suppliers and firm's employment. Services monthly questions for: business climate, evolution of demand, evolution of employment and selling prices. Services quarterly question for: factors limiting their business Consumer monthly questions for: financial situation, general economic situation, price trends, unemployment, major purchases and savings. Consumer quarterly questions for: intention to buy a car, purchase or build a home, home improvements. Financial services monthly questions for: business situation, evolution of demand and employment Financial services quarterly questions for: operating income, operating expenses, profitability of the company, capital expenditure and competitive position Monthly Confidence Indicators are computed for industry, services, construction, retail trade, consumers (at country level, EU and euro area level) and financial services (EU and euro area). An Economic Sentiment indicator (ESI) is calculated based on a selection of questions from industry, services, construction, retail trade and consumers at country level and aggregate level (EU and euro area). A monthly Euro-zone Business Climate Indicator is also available for industry. The data are published: as balance i.e. the difference between positive and negative answers (in percentage points of total answers)as indexas confidence indicators (arithmetic average of balances),at current level of capacity utilization (percentage)estimated months of production assured by orders (number of months)Unadjusted (NSA) and seasonally adjusted (SA)

The Financial Soundness Indicators (FSIs) were developed by the IMF, together with the international community, with aim of supporting analysis and assessing strengths and vulnerabilities of financial systems. The Statistics Department of the IMF, disseminates data and metadata on selected FSIs provided by participating countries. For a description of the various FSIs, as well as the consolidation basis, consolidation adjustments, and accounting rules followed, please refer to the concepts and definitions document in the document tab. Reporting countries compile FSI data using different methodologies, which may also vary for different points in time for the same country. Users are advised to consult the accompanying metadata to conduct more meaning cross-country comparisons or to assess the evolution of a given FSI for any of the countries.

Data cited at: Financial Soundness Indicators (FSI), Reporting Entities, The International Monetary Fund. The Reporting entities dataset provides information on the structure, size, and coverage of the financial institutions that are used for compiling financial soundness indicators. It provides a better understanding of the structure of the reporting entities in terms of the type of institution, number of entities, size of assets, and type of control. Reporting entities are domestically incorporated entities but are divided into two: domestically controlled and foreign controlled. The concepts of residency criterion and control are determined based on FSI Guide methodology which is in line with international best practices such as Systems of National Accounts. Data on reporting entities cover the branches,

Foreign Direct Investment, Sector Wise in India

Public deficit/surplus is defined in the Maastricht Treaty as general government net borrowing/lending according to the European System of Accounts. The general government sector comprises central government, state government, local government, and social security funds. The relevant definitions are provided in Council Regulation 479/2009, as amended.

Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic: Global Financial Development Publication: https://datacatalog.worldbank.org/dataset/global-financial-development License: http://creativecommons.org/licenses/by/4.0/   The Global Financial Development Database is an extensive dataset of financial system characteristics for 206 economies. The database includes measures of (1) size of financial institutions and markets (financial depth), (2) degree to which individuals can and do use financial services (access), (3) efficiency of financial intermediaries and markets in intermediating resources and facilitating financial transactions (efficiency), and (4) stability of financial institutions and markets (stability).For a complete description of the dataset and a discussion of the underlying literature, see: Martin Cihak; Asli Demirguc-Kunt; Erik Feyen; and Ross Levine, 2012. "Benchmarking Financial Systems Around the World." World Bank Policy Research Working Paper 6175, World Bank, Washington, D.C.

Global Financial Stability Report, October 2023: Financial and Climate Policies for a High-Interest-Rate Era

The FAS is the key source of global supply-side data on financial inclusion, encompassing data on access to and usage of financial services by firms and households that can be compared across countries and over time. Contains 180 time series and 65 indicators that are expressed as ratios to GDP, land area, or adult population to facilitate cross-economy comparisons. Provision of FAS data is voluntary.

Insurance Corporations : Balance Sheet Liabilities

Data retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/   This dataset contains forecast data from the dataset: https://knoema.com/FREDID2018Oct 

Data cited at: International Financial Statistics (IFS), The International Monetary Fund. The International Financial Statistics database covers about 200 countries and areas, with some aggregates calculated for selected regions, plus some world totals. Topics covered include balance of payments, commodity prices, exchange rates, fund position, government finance, industrial production, interest rates, international investment position, international liquidity, international transactions, labor statistics, money and banking, national accounts, population, prices, and real effective exchange rates. The International Financial Statistics is based on various IMF data collections. It includes exchange rates series for all Fund member countries plus Anguilla, Aruba, China, PR: Hong Kong, China, PR: Macao, Montserrat, and the Netherlands Antilles. It also includes major Fund accounts series, real effective exchange rates, and other world, area, and country series. Data are available for most IMF member countries with some aggregates calculated for select regions, plus some world totals. National Accounts, Indicators of Economic Activity, Labor Markets, Prices, Government and Public Sector Finance, Financial Indicators, Balance of Payments, International Investment Position, International Reserves, Fund Accounts, External Trade, Exchange Rates, and Population.

The Data Template on International Reserves and Foreign Currency Liquidity is an innovative single framework that integrates the concept of international reserves and foreign currency liquidity by covering data on on-balance-sheet and off-balance-sheet international financial activities of country authorities as well as supplementary information. It aims to provide a comprehensive account of official foreign currency assets and drains on such resources arising from various foreign/domestic currency liabilities and commitments of the authorities.

Data cited at : https://www.bis.org/statistics/index.htm

The Financial Statistics dataset contains predominantly monthly statistics, and associated statistical methodological information, for the 36 OECD member countries and some selected other countries. The dataset itself contains financial statistics on 4 separate subjects: Monetary Aggregates, Interest Rates, Exchange Rates, and Share Prices. The data series presented within these subjects have been chosen as the most relevant financial statistics for which comparable data across countries is available. In all cases a lot of effort has been made to ensure that the data are internationally comparable across all countries presented and that all the subjects have good historical time-series’ data to aid with analysis. All data are available monthly, and are presented as either an index (where the year 2015 is the base year) or as a level depending on which measure is seen as the most appropriate and/or useful in the economic analysis context.

National Accounts - Volume IIIa - Financial Accounts - Flows, which record, by type of financial instruments, the financial transactions between institutional sectors, and are presented in two tables: Financial accounts, consolidated and Financial accounts, non-consolidated.

National Accounts - Volume IIIa - Financial Accounts - Flows, which record, by type of financial instruments, the financial transactions between institutional sectors, and are presented in two tables: Financial accounts, consolidated and Financial accounts, non-consolidated.

Pension Funds: Balance Sheet Liabilities

The Principal Global Indicators (PGI) dataset provides internationally comparable data for the Group of 20 economies (G-20) and economies with systemically important financial sectors that are not members of the G-20. The PGI facilitates the monitoring of economic and financial developments for these jurisdictions. Launched in 2009, the PGI website is hosted by the IMF and is a joint undertaking of the Inter-Agency Group of Economic and Financial Statistics (IAG).

This database covers the universe of systemic banking crises for the period 1970-2009, and also includes data on the resolution and fiscal and economic costs of banking crises. Note: Laeven, Luc and Fabian Valencia, 2010, Resolution of Banking Crises: The Good, the Bad, and the Ugly, IMF working paper 10/146.

The total financial sector liabilities measures the evolution of the sum of all liabilities (which includes Currency and deposits, Debt securities, Loans, Equity and investment fund shares/units, Insurance, pensions and standardised guarantee schemes, Financial derivatives and employee stock options and Other accounts payable) of the financial corporations sector. Data are presented in consolidated terms (i.e. data do not take into account transactions within the same sector), in % of GDP and by instruments.

The total financial sector liabilities measures the evolution of the sum of all liabilities (which includes Currency and deposits, Debt securities, Loans, Equity and investment fund shares/units, Insurance, pensions and standardised guarantee schemes, Financial derivatives and employee stock options and Other accounts payable) of the financial corporations sector. Data are presented in consolidated terms (i.e. data do not take into account transactions within the same sector), in Million units of national currency and by instruments.

The total financial sector liabilities measures the evolution of the sum of all liabilities (which includes Currency and deposits, Debt securities, Loans, Equity and investment fund shares/units, Insurance, pensions and standardised guarantee schemes, Financial derivatives and employee stock options and Other accounts payable) of the financial corporations sector. Data are presented in non-consolidated terms (i.e. data take into account transactions within the same sector), in % of GDP and by instruments.

The total financial sector liabilities measures the evolution of the sum of all liabilities (which includes Currency and deposits, Debt securities, Loans, Equity and investment fund shares/units, Insurance, pensions and standardised guarantee schemes, Financial derivatives and employee stock options and Other accounts payable) of the financial corporations sector. Data are presented in non-consolidated terms (i.e. data take into account transactions within the same sector), in Million units of national currency and by instruments.

The total financial sector liabilities measures the evolution of the sum of all liabilities (which includes Currency and deposits, Debt securities, Loans, Equity and investment fund shares/units, Insurance, pensions and standardised guarantee schemes, Financial derivatives and employee stock options and Other accounts payable) of the financial corporations sector. Data are presented in consolidated terms (i.e. data do not take into account transactions within the same sector), in % of GDP and for the sub-sectors: Central bank; Deposit-taking corporations except the central bank; MMF; Non-MMF investment funds; Other financial intermediaries, except insurance corporations and pension funds; Financial auxiliaries; Captive financial institutions and money lenders; Insurance corporations and Pension funds.

The total financial corporations sector liabilities measures the evolution of the sum of all liabilities (which includes Currency and deposits, Debt securities, Loans, Equity and investment fund shares/units, Insurance, pensions and standardised guarantee schemes, Financial derivatives and employee stock options and Other accounts payable) of the financial corporations sector. Data are presented in consolidated terms (i.e. data do not take into account transactions within the same sector), in Million units of national currency and for the sub-sectors: Central bank; Deposit-taking corporations except the central bank; MMF; Non-MMF investment funds; Other financial intermediaries, except insurance corporations and pension funds; Financial auxiliaries; Captive financial institutions and money lenders; Insurance corporations and Pension funds.

The total financial sector liabilities measures the evolution of the sum of all liabilities (which includes Currency and deposits, Debt securities, Loans, Equity and investment fund shares/units, Insurance, pensions and standardised guarantee schemes, Financial derivatives and employee stock options and Other accounts payable) of the financial corporations sector. Data are presented in non-consolidated terms (i.e. data take into account transactions within the same sector), in % of GDP and for the sub-sectors: Central bank; Deposit-taking corporations except the central bank; MMF; Non-MMF investment funds; Other financial intermediaries, except insurance corporations and pension funds; Financial auxiliaries; Captive financial institutions and money lenders; Insurance corporations and Pension funds.

The total financial sector liabilities measures the evolution of the sum of all liabilities (which includes Currency and deposits, Debt securities, Loans, Equity and investment fund shares/units, Insurance, pensions and standardised guarantee schemes, Financial derivatives and employee stock options and Other accounts payable) of the financial corporations sector. Data are presented in non-consolidated terms (i.e. data take into account transactions within the same sector), in million units of national currency and for the sub-sectors: Central bank; Deposit-taking corporations except the central bank; MMF; Non-MMF investment funds; Other financial intermediaries, except insurance corporations and pension funds; Financial auxiliaries; Captive financial institutions and money lenders; Insurance corporations and Pension funds.

The total financial sector liabilities measures the evolution of the sum of all liabilities (which includes Currency and deposits, Debt securities, Loans, Equity and investment fund shares/units, Insurance, pensions and standardised guarantee schemes, Financial derivatives and employee stock options and Other accounts payable) of the financial corporations sector. The data are presented in consolidated terms, i.e. data do not take into account transactions within the same sector. The data are expressed as 1 year % change, % of GDP and in Million units of national currency.

The total financial corporations sector liabilities measures the evolution of the sum of all liabilities (which includes Currency and deposits (F2), Debt securities (F3), Loans (F4), Equity and investment fund shares (F5), Insurance, pensions and standardised guarantees (F6), Financial derivatives and employee stock options (F7) and Other accounts payable (F8)) of the financial corporations sector (S12). Data are presented in non-consolidated terms, i.e. data take into account transactions within the same sector. Data are presented as 1 year % change, % of GDP and in Million units of national currency. Definitions regarding sectors and instruments are based on the ESA 2010. The MIP indicator is expressed as year over year growth rate, with an indicative threshold 16.5%. The headline indicator is calculated as 1 year % change.

U.S. Financial Firms Liabilities: Data by Type, Country and Region

The G20 Basic Set of Financial Inclusion data repository includes detailed data from users and providers of financial services. The Basic Set measures both access to financial services (“supply-side” data) and usage of services (“demand-side” data). The Basic Set covers both individuals and small and medium sized enterprises (SME’s) and includes data from three sources and 192 countries. The five basic set indicators are as follows: 1.The percentage of adults with a formal account; 2. The percentage of adults that use formal credit; 3. The percentage of SME’s with a formal account; 4. The percentage of SME’s that use formal credit; and 5. Bank branch penetration.