Itália

The data are three-month interbank rates which are no longer updated. The series represent interest rates of countries which have now joined the euro area.

Banknotes statistics refer to data on outstanding amounts (stocks) and transactions (flows) of euro banknotes and coins, divided into: issued into circulation, returned from circulation, sorted to check authenticity & fitness and sorted to unfit during the reporting period. The dataset includes also data on collector coins issued net of collector coins returned. Data on the number of NCBs and commercial banks branches which provides cash related services are also included. For non-euro area Member States, banknotes and coins in circulation as well as Collector Coins are provided.   European central Bank: Bank notes statistics(BKN), Monthly Update

International Data from European Central Bank

Central Government Statistics of Italy TRANSLATE with xEnglishArabicHebrewPolishBulgarianHindiPortugueseCatalanHmong DawRomanianChinese SimplifiedHungarianRussianChinese TraditionalIndonesianSlovakCzechItalianSlovenianDanishJapaneseSpanishDutchKlingonSwedishEnglishKoreanThaiEstonianLatvianTurkishFinnishLithuanianUkrainianFrenchMalayUrduGermanMalteseVietnameseGreekNorwegianWelshHaitian CreolePersian  TRANSLATE with COPY THE URL BELOW BackEMBED THE SNIPPET BELOW IN YOUR SITEEnable collaborative features and customize widget: Bing Webmaster PortalBack

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

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

Reports - Statistical Releases E.16 Country Exposure Lending Survey and Country Exposure Information Report

This variable consists of the sum of all items of the assets side or the sum of all items of the liabilities side. This indicator gives an idea of the economic importance of credit institutions.

Structural business statistics (SBS) describes the structure, conduct and performance of economic activities, down to the most detailed activity level (several hundred economic sectors). SBS are transmitted annually by the EU Member States on the basis of a legal obligation from 1995 onwards.   SBS covers all activities of the business economy with the exception of agricultural activities and personal services and the data are provided by all EU Member States, Norway and Switzerland, some candidate and potential candidate countries. The data are collected by domain of activity (annex) : Annex I - Services, Annex II - Industry, Annex III - Trade and Annex IV- Constructions and by datasets. Each annex contains several datasets as indicated in the SBS Regulation. The majority of the data is collected by National Statistical Institutes (NSIs) by means of statistical surveys, business registers or from various administrative sources. Regulatory or controlling national offices for financial institutions or central banks often provide the information required for the financial sector (NACE Rev 2 Section K / NACE Rev 1.1 Section J). Member States apply various statistical methods, according to the data source, such as grossing up, model based estimation or different forms of imputation, to ensure the quality of SBSs produced. Main characteristics (variables) of the SBS data category: Business Demographic variables (e.g. Number of enterprises)"Output related" variables (e.g. Turnover, Value added)"Input related" variables: labour input (e.g. Employment, Hours worked); goods and services input (e.g. Total of purchases); capital input (e.g. Material investments) All SBS characteristics are published on Eurostat’s website by tables and an example of the existent tables is presented below: Annual enterprise statistics: Characteristics collected are published by country and detailed on NACE Rev 2 and NACE Rev 1.1 class level (4-digits). Some classes or groups in 'services' section have been aggregated.Annual enterprise statistics broken down by size classes: Characteristics are published by country and detailed down to NACE Rev 2 and NACE Rev 1.1 group level (3-digits) and employment size class. For trade (NACE Rev 2 and NACE Rev 1.1 Section G) a supplementary breakdown by turnover size class is available.Annual regional statistics: Four characteristics are published by NUTS-2 country region and detailed on NACE Rev 2 and NACE Rev 1.1 division level (2-digits) (but to group level (3-digits) for the trade section). More information on the contents of different tables: the detail level and breakdowns required starting with the reference year 2008 is defined in Commission Regulation N° 251/2009. For previous reference years it is included in Commission Regulations (EC) N° 2701/98 and amended by Commission Regulation N°1614/2002 and Commission Regulation N°1669/2003. Several important derived indicators are generated in the form of ratios of certain monetary characteristics or per head values. A list with the available derived indicators is available below in the Annex.

All income received by credit institutions from assets such as loans and advances, treasury bills, fixed income securities. It also includes fees and commissions similar in nature to interest and calculated on a time basis or by reference to the amount of the claim or liability.

A count of the number of all credit institutions active during at least a part of the reference period. Credit institutions are undertakings whose business it is to receive deposits or other repayable funds from the public and to grant credit for their own account.

The number of persons employed is the total number of persons who work in the observation unit as well as persons who work outside the unit who belong to it and are paid by it (e.g. sales representatives, delivery personnel, repair and maintenance teams). Yet the number of persons employed excludes manpower supplied to the unit by other companies.

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

MIR - MFI Interest Rate Statistics

Dataset Source (all series) : TARGET2 system as of May 2008. ECB: Target Balances (TGB), Monthly Update

This is a one-off survey, not intended to be repeated.  Access to finance is crucial to business success and an important factor for economic growth in Europe following the economic crisis in 2007. The purpose of the survey is to:Examine where there may be constraints on the availability of finance, and how those may be changing.Provide evidence on the need for finance (loans, equity and other) in the future, for example to promote growth.Identify the sources from which businesses would wish to obtain this finance.  It is important to be able to compare businesses that have shown sharp growth in recent years with those that have not; and to separate more recently formed businesses from others. As a consequence, the survey will collect information separately for "gazelles" (defined at page 3 below); other high-growth businesses that have been established longer than gazelles; and other businesses. Only businesses with an employment of 10-249 in 2005 and at least 10 employees in 2010 are being covered.

European Central Bank: Bank Lending Survey (BLS)

National Accounts - Volume IIIb - Financial Balance Sheets - Stocks, which record the stocks of financial assets and liabilities by institutional sectors, at the end of the accounting period, and are presented in two tables: Balance sheets for financial assets and liabilities, consolidated and Balance sheets for financial assets and liabilities, non consolidated.

Data are compiled either by Central banks, or Statistical National Institutes. EU data are validated and provided by the European Central Bank whereas non-EU data are provided by national institutions. The sectors for which information is presented are: Total economy (S1) - Non-financial corporations (S11) - Financial corporations (S12) and its sub-sectors (S121 to S125) - General government (S13) and its sub-sectors (1311 to S1314) - Households (S14) - Non-profit institutions serving households (S15) Rest of the world (S2)

Financial Instruments Statistics of Italy TRANSLATE with xEnglishArabicHebrewPolishBulgarianHindiPortugueseCatalanHmong DawRomanianChinese SimplifiedHungarianRussianChinese TraditionalIndonesianSlovakCzechItalianSlovenianDanishJapaneseSpanishDutchKlingonSwedishEnglishKoreanThaiEstonianLatvianTurkishFinnishLithuanianUkrainianFrenchMalayUrduGermanMalteseVietnameseGreekNorwegianWelshHaitian CreolePersian  TRANSLATE with COPY THE URL BELOW BackEMBED THE SNIPPET BELOW IN YOUR SITEEnable collaborative features and customize widget: Bing Webmaster PortalBack

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.

The Financial account, which is the second accumulation account, records financial flows: it indicates the types of financial instruments utilized by the different institutional sectors to acquire financial assets or incur liabilities. Data are compiled either by Central banks, or Statistical National Institutes. EU data are validated and provided by the European Central Bank whereas non-EU data are provided by national institutions.

Financial inclusion is critical in reducing poverty and achieving inclusive economic growth. When people can participate in the financial system, they are better able to start and expand businesses, invest in their children’s education, and absorb financial shocks. Yet prior to 2011, little was known about the extent of financial inclusion and the degree to which such groups as the poor, women, and rural residents were excluded from formal financial systems.  The dataset help us to know about how adults around the world manage their day-to-day finances, the Global Findex allows policy makers, researchers, businesses, and development practitioners to track how the use of financial services has changed over time. The database can also be used to identify gaps in access to the formal financial system and design policies to expand financial inclusion.

A loan, other than held for trading, is considered as non-performing if satisfies either or both of the following criteria: (a) It is a material loan which is more than 90 days past-due; (b) The debtor is assessed as unlikely to pay its credit obligations in full without realisation of collateral, regardless of the existence of any past-due amount or of the number of days past-due. Non -performing loans include defaulted and impaired loans and follow the harmonised definition of the European Banking Authority (EBA) used for supervisory reporting. The MIP indicator is defined as total gross non-performing loans and advances as % of total gross loans and advances (gross carrying amount), for the reporting sector "domestic banking groups and stand-alone banks, foreign controlled subsidiaries and foreign controlled branches, all institutions". Data on domestically controlled banks are consolidated across borders and sectors at the prudential perimeter of consolidation. Data source: European Central Bank (ECB)

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.

Bank profitability statistics are based on financial statements of banks in each Member country and are presented in the standard OECD framework. Although the objective is to include all institutions which conduct ordinary banking business, namely institutions which primarily take deposits from the public and provide finance for a wide range of purposes, the institutional coverage of banks in the statistics available in this database is not the same in each country. Ratios based on various items of the income statements and balance sheets of banks in percentage of some aggregates are also provided to facilitate the analysis of trends in bank profitability of OECD countries.

Insurance Corporations : Balance Sheet Liabilities

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

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

Data cited at : https://www.bis.org/statistics/index.htm   Locational Banking Statistics : Cross-Border Positions, by Residence and Sector of Counterparty

Data cited at : https://www.bis.org/statistics/index.htm   Locational banking statistics: Cross-border positions, by nationality of reporting bank and sector of counterparty    

The Monetary and Financial Statistics (MFS) database contains the aggregated surveys covering: i) Central Bank ii) Depository Corporations and iii) Other Financial Corporations. The key macroeconomic aggregates in this dataset include: i) Monetary base and broad money; ii) Credit aggregates (including credit to the private sector); and iii) Foreign assets and liabilities.   Beginning in 2009, there are two presentations of Monetary Statistics in IFS. The new presentation data follows the Monetary and Financial Statistics Manual (MFSM) and the Monetary and Financial Statistics Compilation Guide (MFSCG), a companion to the MFSM that contains more detailed coverage of the classification, economic sectorization, valuation, and recording of financial assets and liabilities in an economy. The MFSCG gives prominence to the source data for monetary and financial statistics.   The majority of countries use the standardized report forms (SRFs) to report monetary data to the IMF and are presented under SRF Countries.   The old presentation is used for those countries that do not use the SRFs for reporting Monetary data and presented under Non-SRF Countries. The presentation of these countries will be changed to the new presentation when the countries implement the reporting of SRF-based data.   The Monetary and Financial Statistics Manual and Compilation Guide (Manual) updates and merges into one volume methodological and practical aspects of the compilation process for monetary and financial statistics (MFS). Aimed at compilers and users of MFS, it offers a conceptual framework for the collection, compilation, and analytical presentation of monetary data, which provide a critical input for monetary policy formulation and monitoring.   Detailed monetary statistics based on the standardized report forms reflecting the conceptual framework of the above Manual and its predecessors.

Net debt-to-income ratio, after taxes, of non-financial corporations is defined as main financial liabilities divided by net entrepreneurial income (ESA 2010 code: B4N) less current taxes on income and wealth (D5PAY). Main financial liabilities include currency and deposits (AF2), debt securities (AF3) and loans (AF4). Detailed data and methodology on site http://ec.europa.eu/eurostat/sectoraccounts .

The aggregate of net lending/net borrowing of the domestic sectors in the ESA is conceptually the same as the value of net lending/net borrowing in the international accounts. This is because all the resident-to-resident flows cancel out. It is also equal to the opposite of net lending/net borrowing of the rest of the world sector in the ESA. The net lending (+) or borrowing (–) of the total economy is the sum of the net lending or borrowing of the institutional sectors. It represents the net resources that the total economy makes available to the rest of the world (if it is positive) or receives from the rest of the world (if it is negative). The net lending (+) or borrowing (–) of the total economy is equal but of opposite sign to the net borrowing (–) or lending (+) of the rest of the world. The indicator is based on the national accounts data reported to Eurostat by the EU Member States.

This aggregate measures the portion of national disposable income that is not used for final consumption expenditure. Net national saving is the sum of the net savings of the various institutional sectors, according to the ESA 2010 definition.

Non-Financial Corporations of Italy 

The data on contingent liabilities and potential obligations of government are collected in the context of the Enhanced Economic Governance package (the "six-pack") adopted in 2011. In particular, Council Directive 2011/85 on requirements for budgetary frameworks of the Member States requires the Member States to publish relevant information on contingent liabilities with potentially large impacts on public budgets, including government guarantees, non-performing loans, and liabilities stemming from the operation of public corporations, including the extent thereof. The liabilities are called “contingent” in the sense that they are by nature only potential and not actual liabilities. Non-performing loans could imply a potential loss for government if these loans were not repaid. This new data collection represents a step towards further transparency of public finances in the EU by giving a more comprehensive picture of EU Member States’ financial positions3 It is to be underlined that contingent liabilities are not part of the general government (Maastricht) debt as defined in the Council Regulation (EC) No 479/2009 of 25 May 2009 on the application of the Protocol on the excessive deficit procedure annexed to the Treaty establishing the European Community. Eurostat collects and publishes the following indicators: government guarantees, liabilities related to public-private partnerships recorded off-balance sheet of government, liabilities of government controlled entities classified outside general government (public corporations) and non-performing loans. Regarding government controlled entities, it should be mentioned that this refers to  government controlled units, not classified in general government, and which are controlled, directly or indirectly (through other public units), by government. In cases when the government share in a corporation is lower than 50% and government does not have control over an entity, the corporation is not considered as controlled by government. Regarding the control criteria, according to ESA 2010 paragraph 20.18: “Control over an entity is the ability to determine the general policy or programme of that entity (…)”. The criteria to be used for corporations are indicated in ESA 2010 paragraphs 2.38 and further detailed in paragraph 20.309. ESA 2010 paragraph 2.38 specifies that: “General government secures control over a corpo­ration as a result of special legislation, decree or reg­ulation which empowers the government to deter­mine corporate policy. The following indicators are the main factors to consider in deciding whether a corporation is controlled by government:(a) government ownership of the majority of the voting interest; (b) government control of the board or governing body; (c) government control of the appointment and removal of key personnel;(d) government control of key committees in the entity; (e) government possession of a golden share; (f) special regulations; (g) government as a dominant customer; (h) borrowing from government. A single indicator may be sufficient to establish control, but, in other cases, a number of separate indicators may collectively indicate control.”

Other Financial Institutions Excluding Non Money Market Investment Funds: Balance Sheet Liabilities

Other Financial Intermediaries except non MMF Investment of Italy

Pension Funds Statistics of Italy

Pension Funds: Balance Sheet Liabilities

The private sector credit flow represents the net amount of liabilities in which the sectors Non-Financial corporations, Households and Non-Profit institutions serving households (S.11_S.14_S.15) have incurred along the year. The instruments that are taken into account to compile private sector credit flow are Debt securities (F.3) and Loans (F.4). Data are presented in non-consolidated terms, i.e. data take into account transactions within the same sector and expressed in % of GDP and in Million units of national currency. Definitions regarding sectors and instruments are based on the ESA 2010.

The table presents the net flow of debt securities (F.3) for the sectors Non-Financial corporations (S.11), Households (S.14) and Non-Profit institutions serving households (S.15). The debt securities are negotiable financial instruments serving as evidence of debt. Data are presented in non-consolidated terms, i.e. data take into account transactions within the same sector and expressed in % of GDP. Definitions regarding sectors and instruments are based on the ESA 2010.

The table presents the net flow of debt securities (F.3) for the sectors Non-Financial corporations (S.11), Households (S.14) and Non-Profit institutions serving households (S.15). The debt securities are negotiable financial instruments serving as evidence of debt. Data are presented in non-consolidated terms, i.e. data take into account transactions within the same sector and expressed in Million units of national currency. Definitions regarding sectors and instruments are based on the ESA 2010.

The table presents the net flow of loans (F.4) for the sectors Non-Financial corporations (S.11), Households (S.14) and Non-Profit institutions serving households (S.15). The debt securities are negotiable financial instruments serving as evidence of debt. Data are presented in non-consolidated terms, i.e. data take into account transactions within the same sector and expressed in % of GDP. Definitions regarding sectors and instruments are based on the ESA 2010.

The table presents the net flow of loans (F.4) for the sectors Non-Financial corporations (S.11), Households (S.14) and Non-Profit institutions serving households (S.15). The debt securities are negotiable financial instruments serving as evidence of debt. Data are presented in non-consolidated terms, i.e. data take into account transactions within the same sector and expressed in Million units of national currency. Definitions regarding sectors and instruments are based on the ESA 2010.

The table presents the stock of liabilities of loans (F.4) for the sectors Non-Financial corporations (S.11), Households (S.14) and Non-Profit institutions serving households (S.15). The debt securities are negotiable financial instruments serving as evidence of debt. Data are presented in non-consolidated terms, i.e. data take into account transactions within the same sector and expressed in million units of national currency. Definitions regarding sectors and instruments are based on the ESA 2010.

The table presents the stock of liabilities of loans (F.4) for the sectors Non-Financial corporations (S.11), Households (S.14) and Non-Profit institutions serving households (S.15). The debt securities are negotiable financial instruments serving as evidence of debt. Data are presented in non-consolidated terms, i.e. data take into account transactions within the same sector and expressed in % of GDP. Definitions regarding sectors and instruments are based on the ESA 2010.

Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic: Remittance Prices Worldwide Publication: https://datacatalog.worldbank.org/dataset/remittance-prices-worldwide License: http://creativecommons.org/licenses/by/4.0/   Provides data on the cost of sending and receiving relatively small amounts of money from one country to another. Data cover 365 "country corridors" worldwide, from 48 remittance sending countries to 105 receiving countries.

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TRANSLATE with xEnglishArabicHebrewPolishBulgarianHindiPortugueseCatalanHmong DawRomanianChinese SimplifiedHungarianRussianChinese TraditionalIndonesianSlovakCzechItalianSlovenianDanishJapaneseSpanishDutchKlingonSwedishEnglishKoreanThaiEstonianLatvianTurkishFinnishLithuanianUkrainianFrenchMalayUrduGermanMalteseVietnameseGreekNorwegianWelshHaitian CreolePersian  TRANSLATE with COPY THE URL BELOW BackEMBED THE SNIPPET BELOW IN YOUR SITEEnable collaborative features and customize widget: Bing Webmaster PortalBack

The dataset on Statistical discrepancy (Institutional Investors – Financial Balance Sheets) represents the time series of the dataset on Institutional investors' assets and liabilities (7II) along with those of the dataset on Financial Balance Sheets (720), for the financial instruments and institutional sectors which are in common to these two datasets.  Additionally, for each of the above-mentioned time series, a statistical discrepancy is reported in order to show any possible differences which may exist between the two datasets (7II and 720).  In fact, the dataset on Institutional investors' assets and liabilities (7II) constitutes an attempt to better integrate these data in the framework of the System of National Accounts 2008 (SNA 2008).  However, discrepancies may exist and may, for example, be caused by balancing practices (e.g. when sector and counterpart sector data are reconciled) in the compilation of Financial Balance Sheets at a higher level of aggregation, which may not have been carried through at a lower level of aggregation. Moreover, differences may also be caused by the use of different source data.

Consolidated banking statistics - Summary of Foreign Claims (Immediate Counterparty Basis), by Nationality of Reporting Bank, 2017 Q1   Data cited at : https://www.bis.org/statistics/index.htm

Consolidated banking statistics - Summary of Foreign Claims and Other Potential Exposures (Ultimate Risk Basis), by Nationality of Reporting Bank Data cited at : https://www.bis.org/statistics/index.htm