Austria

Source: UNECE Statistical Database, compiled from national official sources Definition: An ambassador is a diplomatic official accredited to a foreign sovereign or government, or to an international organisation, to serve as the official representative of his or her own country. In everyday usage it applies to the top ranking government representative stationed in a foreign country. .. - data not available Country: Belarus Including consuls genaral Country: Cyprus Reference period (2008): data refer to 2009 Country: Cyprus Territorial change (2006 onward): Government controlled area only. Country: Finland Reference period (2013): situation in March 3, 2014 Country: Georgia Territorial change (1995 onward): Data do not cover Abkhazia AR and Tskhinvali Region. Country: Iceland Data refers to number at end of year. Country: Kazakhstan 1990: data refer to 1992-1994; 1995: data refer to 1999. Country: Latvia Change in definition (1995 - 2012): Data refer to Ambassadors, Ambassadors-at-large, Consuls General, Vice Consuls. Country: Montenegro 2008: data refer to 2009. Country: Slovakia Reference period (2015): Data refer to October 20, 2015. Data refer to heads of Diplomatic missions of the Slovak Republic (Ambassadors, Charge d?affaires, Consul General etc.) Country: Spain 2013 data correspond to 24 January 2014. 2015 data correspond to 15 July 2015. Country: Switzerland Change in definition (1980 - onwards): Data include only heads of missions, i.e. exclude collaborators with ambassador title.

The data correspond to quarterly financial accounts for the general government sector and follows the ESA2010 methodology. The data covers financial transactions and balance sheet items for general government (consolidated and non-consolidated) and its subsectors. This includes a number of financial instruments (F.1, F.2, F.3, F.4, ...) as well as some balancing items such as net financial transactions, net financial worth and net financial assets and liabilties. Data are available in million of euro, million of national currency (average exchange rates are used for transactions and end of period exchange rates are used for stocks) and as a percentage of GDP (for transactions quarterly GDP is used; for stocks a rolling sum of the last four quarters is used). In the table gov_10a_ggfa, annualised quarterly financial accounts for general government are presented. For financial transactions, data is summed over the four quarters of each year. For the conversion from national currency into euro, the yearly average exchange rate is used. For balance sheet items (stocks), the annualised data corresponds to the data of the fourth quarter. The percentage of GDP data of annualised data uses annual GDP transmitted by the Member States. In the course of the annualisation, small rounding differences may be amplified. Geographic coverage: EU and euro area. Main data sources are the tables provided according to the European Parliament and Council Regulation (EU) N° 549/2013 of 21 May 2013 (OJ No L174/1).

Data are the result of the annual structure of government debt survey and cover the EU countries as well as Norway. The following series are available: Central government gross debt by initital maturity and sector of debt holder; State government gross debt by initital maturity and sector of debt holder; Local government gross debt by initital maturity and sector of debt holder; Social security funds gross debt by initital maturity and sector of debt holder; General government gross debt by initital maturity and sector of debt holder; Debt by currency of issuance; Government guarantees (contingent liabilities); Average remaining maturity of debt; Apparent cost of the debt; Market value of debt.

Data are the result of the annual structure of government debt survey and cover the EU countries as well as Norway. The following series are available: Central government gross debt by initital maturity and sector of debt holder; State government gross debt by initital maturity and sector of debt holder; Local government gross debt by initital maturity and sector of debt holder; Social security funds gross debt by initital maturity and sector of debt holder; General government gross debt by initital maturity and sector of debt holder; Debt by currency of issuance; Government guarantees (contingent liabilities); Average remaining maturity of debt; Apparent cost of the debt; Market value of debt.

Data are the result of the annual structure of government debt survey and cover the EU countries as well as Norway. The following series are available: Central government gross debt by initital maturity and sector of debt holder; State government gross debt by initital maturity and sector of debt holder; Local government gross debt by initital maturity and sector of debt holder; Social security funds gross debt by initital maturity and sector of debt holder; General government gross debt by initital maturity and sector of debt holder; Debt by currency of issuance; Government guarantees (contingent liabilities).

CGPITRT: Central government personal income tax rates and threshold   This table reports statutory central government personal income tax rates for wage income plus the taxable income thresholds at which these statutory rates apply. The table also reports basic/standard tax allowances, tax credits and surtax rates. The information is applicable to a single person without dependents. The threshold, tax allowance and tax credit amounts are expressed in national currencies Tapered means that the tax relief basic amount is reduced with increasing income Further explanatory notes may be found in the Explanatory Annex This data represents part of the data presented within the Excel file “Personal income tax rates and thresholds for central governments - Table I.1”. The Data for 1981 to 1999 is not included here within as not all the data for these years is either available, or can be verified. The OECD tax database provides comparative information on a range of tax statistics - tax revenues, personal income taxes, non-tax compulsory payments, corporate and capital income taxes and taxes on consumption - that are levied in the 34 OECD member countries.” Tax policy Analysis homepage OECD Tax Database Taxing Wages Dissemination format(s) This data is also presented through the OECD Tax database webpage. OECD Tax Database

Committee on Contributions: Contributions received for 2020 for the United Nations Regular Budget As of 23 September 2020, 121 Member States have paid their regular budget assessments in full.   Net assessment Date is the "Date of Payment" and Number of Member States values as at month end.

Source: UNECE Statistical Database, compiled from national official sources. Definition: A ministry is a department of a government, led by a minister. A minister (sometimes called secretary) is a politician who holds significant public office in a national cabinet and is entrusted with the management of a division of governmental activities. A cabinet is a body of high-ranking members of government, typically representing the executive branch. Core ministries include: Cabinet of Prime Minister, Ministry of Home Affairs, Ministry for Foreign Affairs, Ministry of Finance, Ministry of Defence, Ministry of Justice. General note: Reference period: any fixed date of the year. .. - data not available Country: Estonia 2015: Data refers to composition after September 14, 2015. 2014: Data refers to composition between November 17, 2014 to April 9, 2015. Country: Georgia Territorial change (2004 onward): Data do not cover Abkhazia AR and Tskhinvali Region. Country: Israel 1990: data refer to average from 1988-1990, 1995: data refer to average from 1992-1995, 2000: data refer to average from 1999-2001. Country: Latvia Reference period (1990): data refer to 1991. Country: Moldova, Republic of Additional information (1980): Data include the territory of the Transnistria and municipality of Bender Country: Moldova, Republic of Additional information (1990): Data include the territory of the Transnistria and municipality of Bender Data exclude the territory of the Transnistria and municipality of Bender Country: Moldova, Republic of Additional information (1995 onward): Data exclude the territory of the Transnistria and municipality of Bender Country: Montenegro Additional information (2006): Ministry for Defense was formed in 2006. Country: Portugal 2008: data refer to 2009. Country: Slovakia Data for 2014 refer to 15 March. Data for 2015 refer to 20 November. Country: Switzerland Change in definition (1980 - onwards): All the 7 ministers in Switzerland are considered as being head of a Core Ministry.

Data are the result of the annual structure of government debt survey and cover the EU countries as well as Norway. The following series are available: Central government gross debt by initital maturity and sector of debt holder; State government gross debt by initital maturity and sector of debt holder; Local government gross debt by initital maturity and sector of debt holder; Social security funds gross debt by initital maturity and sector of debt holder; General government gross debt by initital maturity and sector of debt holder; Debt by currency of issuance; Government guarantees (contingent liabilities).

Tables show earmarked grants classified into the 10 functions (or policy areas) for which they are disbursed. Functions are the same as used in the Classification of Functions of Government (COFOG) by the System of National Accounts. A 'miscellaneous' category has been added to these 10 functions to allow for situations where a precise breakdown by function is not available.

20.1. Source data

Data cited at:  CBS StatLine databank https://opendata.cbs.nl/statline/portal.html?_la=en&_catalog=CBS Publication: Invest.climate;functioning of government international comparison 1990-2012 https://opendata.cbs.nl/portal.html?_la=en&_catalog=CBS&tableId=71159eng&_theme=974 License: http://creativecommons.org/licenses/by/4.0/   This Dataset provides an international overview of several aspects of how the government functions in relation to the investment climate. The functioning of the apparatus of government is about two roles, namely: (1) the government corrects markets that do not work well. It is expressed by the degree in which the government exerts influence on economic activity (for example by state control, sect-oral and ad hoc state support and rules for starting up a business); (2) the government as a market party, for example as a supplier of online basic public services. Note: Comparable definitions are used to compare the figures presented internationally. The definitions sometimes differ from definitions used by Statistics Netherlands. The figures in this table could differ from Dutch figures presented elsewhere on the website of Statistics Netherlands.    

Final consumption expenditure by general government includes the value of goods and services purchased or produced by general government and directly supplied to private households for consumption purposes.

The IMF’s Fiscal Decentralization Dataset compiles indicators widely used by academics and policymakers to assess recent trends, conduct benchmark analysis, and identify the causes, and consequences of fiscal decentralization for a global sample of IMF members.   Fiscal decentralization indicators are computed using fiscal data on flows and stocks of the general government sector disaggregated between central and subnational government subsectors (state/provincial/regional, and local) measured within the framework of the Government Finance Statistics Manual, 2014.

Data are the result of the annual structure of government debt survey and cover the EU countries as well as Norway. The following series are available: Central government gross debt by initital maturity and sector of debt holder; State government gross debt by initital maturity and sector of debt holder; Local government gross debt by initital maturity and sector of debt holder; Social security funds gross debt by initital maturity and sector of debt holder; General government gross debt by initital maturity and sector of debt holder; Debt by currency of issuance; Government guarantees (contingent liabilities).

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.

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.

The general government deficit/surplus is defined in the Maastricht Treaty as general government net lending (+)/net borrowing (-) 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.

These indicators present total expenditure of general government devoted to three different socio-economic functions (according to the Classification of the Functions of Government - COFOG), expressed as a ratio to GDP. The COFOG divisions covered are 'health', 'education' and 'social protection'.

General government gross fixed capital formation (ESA 2010 code P.51g) consists of resident producers' acquisitions, less disposals of fixed assets during a given period plus certain additions to the value of non-produced assets realised by the productive activity of government producer or units. Fixed assets are produced assets used in production for more than one year.

The Treaty on the Functioning of the European Union defines this indicator as the ratio of government debt outstanding at the end of the year to gross domestic product at current market prices. For this calculation, government debt is defined as the total consolidated gross debt at nominal value in the following categories of government liabilities (as defined in ESA 2010): currency and deposits (AF.2), debt securities (AF.3) and loans (AF.4). The general government sector comprises the subsectors of central government, state government, local government and social security funds. For further methodological guidance and interpretation, please refer to the Eurostat Manual on Government Deficit and Debt. Total government gross debt in million EUR is shown as well.

The indicator is defined (in the Maastricht Treaty) as consolidated general government gross debt at nominal (face) value, outstanding at the end of the year in the following categories of government liabilities (as defined in ESA 2010): currency and deposits, debt securities and loans. The general government sector comprises the subsectors: central government, state government, local government and social security funds.

The data correspond to quarterly government debt. Public debt is defined in the Maastricht Treaty as consolidated general government gross debt at nominal (face) value, outstanding at the end of the year. Data for the general government sector are consolidated between subsectors at the national level. Data are non-seasonally adjusted.

The general government gross debt is defined in the Maastricht Treaty as consolidated general government gross debt at nominal value, outstanding at the end of the year in the following categories of government liabilities (as defined in ESA 2010): currency and deposits (AF.2), debt securities (AF.3), and loans (AF.4). General government sector includes the following subsectors: central government, state government, local government and social security funds. Basic data are expressed in national currency, converted into euro using end-year exchange rates for the euro provided by the European Central Bank (ECB). The debt of the Euro area and EU aggregates is consolidated by removal of the loans that Member States have granted to other Member States. In order to reflect economic and technological developments and meet user needs, in September 2014 the new national accounting framework ESA 2010 replaced the previous framework ESA 95. This led to revisions of the time series for all Member States (please see Eurostat press release for the impact of the revisions on the government deficit and debt ratios). The changes to government debt relate to the classification of certain entities into government.

For the purpose of the Excessive Deficit Procedure (EDP) in the Economic and monetary union (EMU), as well as for the Growth and Stability Pact, the current Protocol 12, annexed to the 2012 consolidated version of the Treaty on the Functioning of the European Union, provides a complete definition of government debt: debt means total gross debt at nominal value outstanding at the end of the year and consolidated between and within the sectors of general government. This definition is supplemented by Council Regulation (EC) No 479/2009, as amended by the Commission Regulation (EU) No 220/2014 (which has only updated references to ESA 2010 instruments) specifying the components of government debt with reference to the definitions of financial liabilities in ESA 2010. In this context, the stock of government debt in the Excessive Deficit Procedure (EDP debt) is equal to the sum of liabilities, at the end of year, of all units classified within the general government sector (S.13) in the following categories: AF.2 (currency and deposits) + AF.3 (debt securities) + AF.4 (loans). Basic data are expressed in national currency, converted into euro using end-year exchange rates for the euro provided by the European Central Bank (ECB). The MIP headline indicator is calculated as: [GGDt/GDPt]*100. The indicative threshold is 60% of GDP. The data are expressed in millions of units of national currency and in % of GDP.

The quarterly government debt data are conceptually consistent with the corresponding annual data compiled on a national accounts (EDP and ESA 2010) basis. For the purpose of the Excessive Deficit Procedure (EDP) in the Economic and monetary union (EMU), as well as for the Growth and Stability Pact, the current Protocol 12, annexed to the 2012 consolidated version of the Treaty on the Functioning of the European Union, provides a complete definition of government debt: debt means total gross debt at nominal value outstanding at the end of the year and consolidated between and within the sectors of general government. This definition is supplemented by Council Regulation (EC) No 479/2009, as amended by the Commission Regulation (EU) No 220/2014 (which has only updated references to ESA 2010 instruments) specifying the components of government debt with reference to the definitions of financial liabilities in ESA 2010. The data are expressed in million units of national currency and in % of GDP. Data are non-seasonally adjusted. The differences between the annual and quarterly debt figures may arise as a result of different timetables in the transmission on revised data. Annual EDP data notified by Member States in April and October are the subject of a thorough verification by Eurostat, which can lead to a revision of past quarterly data.

General government gross fixed capital formation (ESA 2010 code P.51g) consists of resident producers' acquisitions, less disposals of fixed assets during a given period plus certain additions to the value of non-produced assets realised by the productive activity of government producer or units. Fixed assets are produced assets used in production for more than one year.

General government output (ESA 2010 code P.1) consists of the products created by general government institutional units (i.e. units within the subsectors central government, state government, local government or social security funds). ESA 2010 category P.1 includes three types of output: market output, output for own final use and non-market output.

The indicator measures the general government total expenditure on law courts according to the classification of the functions of government (COFOG). This includes expenditure on administration, operation or support of civil and criminal law courts and the judicial system, including enforcement of fines and legal settlements imposed by the courts and operation of parole and probation systems; legal representation and advice on behalf of government or on behalf of others provided by government in cash or in services. Law courts include administrative tribunals, ombudsmen and the like, and exclude prison administrations. In computing the per capita indicator, the average National Accounts (NA) population data of the reference year is used as denominator (calculated as the arithmetic mean of the population on 1st January of two consecutive years).

Text from source:Please note that this content is no longer being updated. The tax rate information on this page was last updated in January 2021 and the below historical tax rate data is available for reference only. For the latest information and insights on Global Tax rates, and what they may mean for your organization, please speak with your local KPMG Tax professional. Thank you.

Government Finance Statistics (GFS) form the basis for fiscal monitoring in Europe. Annual government deficit and debt statistics are reported to the European Commission in the framework of the Excessive Deficit Procedure (EDP). Government revenue and expenditure, annual and quarterly, are reported by Member States under the ESA 95 transmission programme.  General government net borrowing/net lending (deficit/surplus), and general government debt, form two of the convergence criteria for EMU. The following series are as reported in the EDP tables:Deficit/surplus of the general government sector;General government debt;General government gross fixed capital formation;General government primary balanceIntergovernmental lending within the EU and euro area in the context of the financial crisis.  Total general government revenue and total general government expenditure annual series are reported by national authorities in ESA table 2 of the ESA 95 transmission programme.  General government deficit/surplus and general government debt quarterly series are reported by national authorities in ESA tables 25 and 28, respectively, of the ESA 95 transmission programme.

10-year government bond yields are reference rates, based on government bonds with a maturity close to 10 years.

10-year government bond yields are reference rates, based on government bonds with a maturity close to 10 years.

This table presents data on Government appropriations or outlays for RD (GBAORD) by socio-economic objective (SEO), using the NABS 2007 classification i.e.: Exploration and exploitation of the Earth, Environment, Exploration and exploitation of space, Transport, telecommunication and other infrastructures, Energy, Industrial production and technology, Health, Agriculture, Education, Culture, recreation, religion and mass media, Political and social systems, structures and processes, General advancement of knowledge: RD financed from General University Funds (GUF), General advancement of knowledge: RD financed from sources other than GUF, Defence. Please note that in this new NABS 2007 classification, the three socio-economic objectives -- Education, Culture, recreation, religion and mass media, and Political and social systems, structures and processes -- were previously grouped under a single objective: Social structures and relationships. At the time of this publication there is no breakdown of historical data into the three new SEOs. Another issue relating to the transition from NABS 1993 to NABS 2007 is that what was formerly Other civil research is now to be distributed among the other chapters. This distribution has not yet been done in this database. Therefore, until the countries are in a position to provide breakdown according to the NABS 2007 classification, in some cases GBAORD by SEO is greater than the sum of its chapters.

Government debt is defined as total gross debt at nominal value outstanding at the end of the year and consolidated between and within the sectors of general government. This definition is supplemented by Council Regulation (EC) No 479/2009, as amended by the Commission Regulation (EU) No 220/2014 (which has only updated references to ESA 2010 instruments) specifying the components of government debt with reference to the definitions of financial liabilities in ESA 2010. In this context, the stock of government debt in the Excessive Deficit Procedure (EDP debt) is equal to the sum of liabilities, at the end of year, of all units classified within the general government sector (S.13) in the following categories: AF.2 (currency and deposits) + AF.3 (debt securities) + AF.4 (loans). Basic data are expressed in national currency, converted into euro using end-year exchange rates for the euro provided by the European Central Bank (ECB).

Government Finance Statistics (GFS) form the basis for fiscal monitoring in Europe, most notably for the statistics related to the Excessive Deficit Procedure (EDP). The EDP is established in the Treaty and specified in the Stability and Growth Pact legislation. The Member States report data related to the EDP to the Commission (Eurostat) which, in turn, is responsible for providing the data to the Council. European GFS, including the statistics for the EDP, are produced in accordance with the European System of Accounts 2010 (ESA 2010), the EU manual for national accounts, which in September 2014 replaced the previous version of the national accounting framework ESA 95. It is supplemented by further interpretation and guidance from Eurostat, in particular the Manual on Government Deficit and Debt. Council Regulation 479/2009 as amended requires that Member States report government deficit/surplus (hereinafter deficit) and debt data related to the EDP twice per year: before 1 April and 1 October for the preceding four calendar years and a forecast for the current year. The data are reported in harmonised tables. These tables are designed specifically to provide a consistent framework, with a link to national budgetary aggregates and between the deficit and changes in the debt. They should be fully consistent with GFS data delivered to Eurostat in the ESA 2010 transmission programme. The EDP notification tables contain for general government and its sub sectors: Table 1: Summary table on deficit and debt, including auxiliary indicators (Gross Fixed Capital Formation, Interest and Gross Domestic Product - GDP)Tables 2A - 2D: Transition from the working balance to the deficit/surplus for general government sub sectorsTables 3A - 3E: Transition from the deficit/surplus to the change in debt for general government and its sub sectorsTable 4: Supplementary data. The data are presented in the Eurostat's Statistics Database in national currency, euro/ECU, and percentage of GDP. In order to reflect economic and technological developments and meet user needs, in September 2014 the new national accounting framework ESA 2010 replaced the previous framework ESA 95. This led to revisions of the time series for all Member States (please see Eurostat press release for the impact of the revisions on the government deficit and debt ratios). The main changes relate to the classification of certain entities into government and the treatment of transactions related to pension schemes. Also the concept of government deficit was changed as regards treatment of interest on swaps and forward rate agreements (Commission Regulation 220/2014 amending the Council Regulation 479/2009), according to which these flows are now recorded as financial transaction in line with the core ESA accounting framework.

Government effectiveness captures perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government's commitment to such policies. The Worldwide Governance Indicators report on six broad dimensions of governance for 215 countries over the period 1996-2014: Voice and Accountability, Political Stability and Absence of Violence, Government Effectiveness, Regulatory Quality, Rule of Law and Control of Corruption.

To view the original national data please open the questionnaires. Source: Joint Forest Europe / UNECE / FAO Questionnaire on Pan-European Indicators for Sustainable Forest Management. Country: Russian Federation The source of the data of Russian Federation is the National Report for the Joint Forest Europe / UNECE / FAO reporting on quantitative pan-European indicators 2011.

Government final consumption expenditure (ESA 2010, 3.98) includes two categories of expenditures: the value of goods and services produced by general government itself other than own-account capital formation, and purchases by general government of goods and services produced by market producers that are supplied to households - without any transformation - as social transfers in kind. Values are seasonally adjusted (SA). The ESA 2010 (European System of Accounts) regulation may be referred to for more specific explanations on methodology.

Government final consumption expenditure (ESA 2010, 3.98) includes two categories of expenditures: the value of goods and services produced by general government itself other than own-account capital formation, and purchases by general government of goods and services produced by market producers that are supplied to households - without any transformation - as social transfers in kind. Data are calculated as chain-linked volumes (i.e. data at previous year's prices, linked over the years via appropriate growth rates). Growth rates 'q/q-1 (sca)' with respect to the previous quarter and 'q/q-4 (sca)' with respect to the same quarter of the previous year are calculated from calendar and seasonally adjusted figures while growth rates 'q/q-4 (nsa)' with respect to the same quarter of the previous year are calculated from raw data.

National Accounts of Costa Rica

This dataset provides a comprehensive view of the functions, or socioeconomic objectives, that government aims to achieve through various kinds of expenditure, comprising detailed classifications of general public service, defense, public order and safety, economic affairs, environment protection, housing and community services, health, recreation, culture and religion, education, and social protection services.

This dataset provides a comprehensive view of government expense, including detailed classifications of compensation of employees, use of goods and services, consumption of fixed capital, interest payable, subsidies payable, grants payable, social benefits, and other expense.

This dataset provides a comprehensive view of government revenue, including detailed classifications of taxes, social contributions, grants receivable, and other revenue.

This dataset provides an overview of government’s cash flows, as summarized in the Statement of Sources and Uses of Cash, for those countries compiling GFS on a noncash basis (for example, an accrual basis) and are also including a cash flow statement.

This dataset provides a comprehensive view of the integrated balance sheet. In other words, changes between the opening and closing stock positions in assets and liabilities are explained through transactions, holding gains/losses, and other changes in the volume of assets and liabilities. Data on net investment in non-financial assets – a component of total expenditure – on its components and related stock positions are provided.

This dataset provides an overview of government operations and stock positions, as well as several derived balances. The Statement of Government Operations shows revenue and expense, with their main components, the operating balance and net lending/net borrowing, as well as financing. The Balance sheet shows stock positions in assets and liabilities, with their main components, as well as net worth and net financial worth. In addition, data on gross debt and net debt are included.

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.”

Source: UNECE Statistical Database, compiled from national official sources. Definition: A ministry is a department of a government, led by a minister. A minister (sometimes called a secretary) is a politician who holds significant public office in a national cabinet and is entrusted with the management of a division of governmental activities. A cabinet is a body of high-ranking members of government, typically representing the executive branch. .. - data not available Country: Austria 1980: data refer to 1979. 1995: data refer to 1994. Country: Belarus Change in definition (2001 - 2015): Data include ministers, chairmen of state committees subordinated to the Government of the Republic of Belarus. Country: Belgium 2011: data refer to december 2011. Country: Cyprus Reference period (1980): Data refer to 1979. Country: Cyprus Reference period (1995): Data refer to 1994. Country: Cyprus Territorial change (1980 - 2013): Government controlled area only. Country: Estonia 2015: Data refers to composition after September 14, 2015. 2014: Data refers to composition between November 17, 2014 to April 9, 2015. Country: Georgia 1980: data refer to 1979. 1995: data refer to 1994. Country: Israel Additional information (2013): 2013 data - starting from 18/3/2013 Country: Israel Reference period (1990): data refer to average from 1988-1990 Country: Israel Reference period (1995): data refer to average from 1992-1995 Country: Israel Reference period (2000): data refer to average from 1999-2001. Country: Moldova, Republic of Additional information (1980): Data include the territory of the Transnistria and municipality of Bender Country: Moldova, Republic of Additional information (1990): Data include the territory of the Transnistria and municipality of Bender Data exclude the territory of the Transnistria and municipality of Bender Country: Moldova, Republic of Additional information (1995 onward): Data exclude the territory of the Transnistria and municipality of Bender Country: Russian Federation Reference period (2000 - 2013): Data refer to the situation as of 1st of January of the following year. Country: Slovakia Data for 2014 refer to 15 March. Data for 2015 refer to 20 November.

Main revenue and expenditure items of the general government sector, notified by national authorities in Table 2 of the ESA2010 transmission programme. Data are presented in millions of Euro, millions of national currency units and percentages of GDP. Geographic coverage: EU and euro area, Iceland, Norway and Switzerland. Main sources of data: National authorities (National Statistical Institutes)

The indicator refers to Government Budget Appropriations or Outlays on R&D (GBAORD). GBAORD data measure government support to research and development (R&D) activities, or, in other words, how much priority governments place on the public funding of R&D. GBAORD data are built up using the guidelines laid out in the proposed standard practice for surveys of research and experimental development, the OECD’s Frascati Manual from 2002. GBAORD data are broken down by socio-economic objectives in accordance to the nomenclature for the analysis and comparison of scientific programmes and budgets (NABS 2007).

Data are the result of the annual structure of government debt survey and cover the EU countries as well as Norway. The following series are available: Central government gross debt by initital maturity and sector of debt holder; State government gross debt by initital maturity and sector of debt holder; Local government gross debt by initital maturity and sector of debt holder; Social security funds gross debt by initital maturity and sector of debt holder; General government gross debt by initital maturity and sector of debt holder; Debt by currency of issuance; Government guarantees (contingent liabilities).

Data cited at: ICTD/UNU-WIDER, ‘Government Revenue Dataset’, 2018, https://www.wider.unu.edu/project/government-revenue-dataset' ICTD Government Revenue Dataset, 2018 A major obstacle to cross-country research on the role of revenue and taxation in development has been the weakness of available data. Government Revenue Dataset (GRD), developed through the International Centre for Tax and Development (ICTD), is aimed at overcoming this obstacle. It meticulously combines data from several major international databases, as well as drawing on data compiled from all available International Monetary Fund (IMF) Article IV reports. It achieves marked improvements in data coverage and accuracy, including a standardized approach to revenue from natural resources, and holds the promise of significant improvement in the credibility and robustness of research in this area. Dataset contains Central, General and merged government revenue data reported as % of GDP.

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. 

Within the last 12 months before the survey for private purposes. Derived variable on use of eGovernment services. Individuals used at least one of the following services: for obtaining information from public authorities websites, for downloading official forms, for submitting completed forms.

Within the last 12 months before the survey.

Data given in this domain are collected annually by the National Statistical Institutes and are based on Eurostat's annual model questionnaires on ICT (Information and Communication Technologies) usage in households and by individuals. The model questionnaire changes every year. The changes of questions in the MQ are required by the evolving situation of information and communication technologies. Large part of the data collected are used in the context of the follow up of the Digital Single Market process (Monitoring the Digital Economy & Society  2016-2021). This conceptual framework follows the 2011 - 2015 benchmarking framework, the i2010 Benchmarking Framework and the eEurope 2005 Action Plan. ICT usage data are also used in the Consumer Conditions Scoreboard (purchases over the Internet) and in the Employment Guidelines (e-skills of individuals). The aim of the European ICT surveys is the timely provision of statistics on individuals and households on the use of Information and Communication Technologies at European level. Data for this collection are supplied directly from the surveys with no separate treatment. Coverage: The characteristics to be provided are drawn from the following list of subjects: access to and use of ICTs by individuals and/or in households,use of the Internet and other electronic networks for different purposes by individuals and/or in households,ICT security and trust,ICT competence and skills,barriers to the use of ICT and the Internet,perceived effects of ICT usage on individuals and/or on households,use of ICT by individuals to exchange information and services with governments and public administrations (e-government),access to and use of technologies enabling connection to the Internet or other networks from anywhere at any time (ubiquitous connectivity).Breakdowns (see details of available breakdowns): Relating to households: by region of residence (NUTS 1, optional: NUTS 2)by geographical location: less developed regions, transition regions, more developed regionsby degree of urbanisation (till 2012: densely/intermediate/sparsely populated areas; from 2012: densely/thinly populated area, intermediate density area) by type of householdby households net monthly income (optional) Relating to individuals: by region of residence (NUTS1, optional: NUTS 2)by geographical location: less developed regions, transition regions, more developed regionsby degree of urbanisation: (till 2012: densely/intermediate/sparsely populated areas; from 2012: densely/thinly populated area, intermediate density area)by genderby country of birth, country of citizenship (as of 2010, optional in 2010)by educational level: ISCED 1997 up to 2013 and ISCED 2011 from 2014 onwards.by occupation: manual, non-manual; ICT (coded by 2-digit ISCO categories)/non-ICT (optional: all 2-digit ISCO categories)by employment situationby age (in completed years and by groups)legal / de facto marital status (2011-2014, optional) Regional breakdowns (NUTS) are available only for a selection of indicators disseminated in the regional tables in Eurobase (Regional Information society statistics by NUTS regions (isoc_reg): Households with access to the internet at homeHouseholds with broadband accessIndividuals who have never used a computerIndividuals who used the internet, frequency of use and activitiesIndividuals who used the internet for interaction with public authoritiesIndividuals who ordered goods or services over the internet for private useIndividuals who accessed the internet away from home or work

Data on grants by type is not available for all OECD countries. A partial dataset is available for one or more years in the following countries: Austria, Belgium, Canada, Estonia, France, Greece, Iceland, Ireland, Italy, Netherlands, Poland, Portugal. No data on grants by type is available for Germany, Israel, New Zealand, Slovak Republic, United Kingdom, United States. The different types of grants are defined as follows: Earmarked grants An earmarked grant is a grant that is given under the condition that it can only be used for a specific purpose. Non-earmarked grants Non-earmarked grants can be spent as if they were the receiving sub-national government's own (non-earmarked) tax revenues. Mandatory grants Mandatory grants (entitlements) are legal, rules-based obligations for the government that issues the grant. This requires that both the size of the grant and the conditions under which it is given be laid down in a statute or executive decree and that these conditions be both necessary and sufficient. Discretionary grants Discretionary grants, and the conditions under which they are given, are not determined by rules but decided on an ad hoc, discretionary basis. Discretionary grants are often temporary in nature and include, for example, grants for specific infrastructural projects or emergency aid to a disaster area. Matching grants Matching grants are grants designed to complement sub-national contributions. Matching grants are dependent on normative or actual spending for services for which the grants are earmarked or on local revenue collection related to these services. Non-matching grants Non-matching grants are grants not directly linked to any sub-national contribution. Current grants Current grants are grants assumed to be spent on either current or capital expenditures. Capital grants Capital grants are grants assumed to be spent only on capital expenditures.

Data are collected directly from countries using a FAO questionnaire, which was developed in partnership with the International Monetary Fund, as the IMF collects global data on government expenditures and is the international organization responsible for developing guidelines on the Classification of Functions of Government (COFOG). The FAO questionnaire obtains additional detail relevant to Agriculture and Rural Development not available from the IMF questionnaire. The FAO dataset consists of a time series, from 2000 onwards, of government expenditures in terms of expenditures in: (1) Total; (2) Economic affairs; (3) Agriculture, Forestry, Fishing and Hunting, along with its three disaggregated subsectors of Agriculture, Forestry and Fishing; and 4) Environmental Protection. In addition, expenditures in each detailed function are further disaggregated into recurrent and capital expenditures, the latter of which serves as a proxy for expenditures in investment goods. Additional indicators include the total share of government expenditures allocated to agriculture, and an agriculture orientation index (ratio of the total share of government expenditures to agriculture, over the total share of GDP from agricultural value-added). Though the goal is to have complete and consistent coverage for all countries, relatively low response rates for this new domain and country level differences in data collection and reporting creates some challenges in providing a complete and consistent global dataset.

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 and can materialise as actual government liabilities only if certain specific conditions prevail. Non-performing loans could imply a potential loss for government if these loans were not repaid by their original debtor. 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 positions. 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 (government assets). 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.”

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.”

Data are the result of the annual structure of government debt survey and cover the EU countries as well as Norway. The following series are available: Central government gross debt by initital maturity and sector of debt holder; State government gross debt by initital maturity and sector of debt holder; Local government gross debt by initital maturity and sector of debt holder; Social security funds gross debt by initital maturity and sector of debt holder; General government gross debt by initital maturity and sector of debt holder; Debt by currency of issuance; Government guarantees (contingent liabilities).

Long term government bond yields are calculated as monthly averages (non seasonally adjusted data). They refer to central government bond yields on the secondary market, gross of tax, with a residual maturity of around 10 years. The bond or the bonds of the basket have to be replaced regularly to avoid any maturity drift. This definition is used in the convergence criteria of the Economic and Monetary Union for long-term interest rates, as required under Article 121 of the Treaty of Amsterdam and the Protocol on the convergence criteria. Data are presented in raw form. Source: European Central Bank (ECB)

Data are the result of the annual structure of government debt survey and cover the EU countries as well as Norway. The following series are available: Central government gross debt by initital maturity and sector of debt holder; State government gross debt by initital maturity and sector of debt holder; Local government gross debt by initital maturity and sector of debt holder; Social security funds gross debt by initital maturity and sector of debt holder; General government gross debt by initital maturity and sector of debt holder; Debt by currency of issuance; Government guarantees (contingent liabilities); Average remaining maturity of debt; Apparent cost of the debt; Market value of debt.

.. - data not available Source: UNECE Statistical Database, compiled from national and international official sources (Inter-Parliamentary Union). Definition: Members of parliament are the persons elected to the lower or single house by the persons entitled to vote in the country. The parliament is the legislative or deliberative assembly; one or more chambers or assemblies that form (or form part of) the legislature of a country. Data refer to the lower or single house. General note: Data refer to 1st July of the reference year. Country: Bosnia and Herzegovina 1980: data refer to 1978. Country: Bulgaria 1995: data refer to 1997. Country: Canada 1995: data refer to 1997 Country: Croatia In 1980 and 1990, the Croatian Parliament was differently structured (there were more deputies, there was no division on upper and lower house of parliament). Country: Cyprus 1995: data refer to 1997. Geographical coverage: data refer to Government controlled areas only. Country: Czechia Until 1992 data refer to deputies of Czech National Council, later to members of the Chamber of Deputies of the Czech Republic. Country: Estonia 1990: data refer to 1992 when the first parliament elections took place. Country: France 1980: data refer to the 1981 election. Country: Georgia Excluding Abkhaz AR and Tskhinvali Region. Country: Germany In 1990, the total number of members was increased because of German reunification. 1995: data refer to 1994 Country: Greece 1995: data refer to 1996 Country: Israel 1995: data refer to 1996 Country: Italy 1995: data refer to 1996 Country: Lithuania 1990: data refer to 1992. 1995: data refer to 1996. Country: Norway 1980: data refer to 1981. 1990: data refer to 1989. Country: Poland 1995: data refer to 1997 Country: Romania 1995: data refer to 1996 Country: Slovakia 1990: data refer to 1992. Country: Slovenia 1995: data refer to 1992 Country: Spain 1995: data refer to 1996 Country: Switzerland 1980: data refer to 1979. 1990: data refer to 1991. 2000: data refer to 1999. 2001: data refer to 2003 Country: United States 1995: date refer to 1996

It provides a faithful image, to the greatest extent possible, of the aggregates and balances of the general government sector in the SNA 1993 conceptual framework. In addition, it brings to light two relevant aggregates that do not belong to this conceptual frame work: the Total Revenue and the Total Expenditure of the general government sector. Unit of measure used - National currency; current prices. Expressed in millions.

Annual National Accounts>General Government Accounts>750. General Government Debt-Maastricht   Unit of measure used: National currency; current prices. Expressed in millions   Statistical population: Government debt as defined in the Maastricht Treaty (Source : Eurostat). Available for Europeans countries only. In the Protocol on the excessive deficit procedure annexed to the Maastricht Treaty, government debt is defined as the debt of the whole general government sector: gross, consolidated and nominal value (face value). It excludes the other accounts payable (AF.7), as well as, if they exist, insurance technical reserve (AF.6).

It provides a breakdown of government expenditure according to their function. To meet this end, economic flows of expenditure must be aggregated according to the Classification of the Functions of Government (COFOG).

National Health Accounts (NHA) provides evidence to monitor trends in health spending for all sectors- public and private, different health care activities, providers, diseases, population groups and regions in a country. It helps in developing nationals

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.”

The Community Innovation Survey (CIS) is a survey of innovation activity in enterprises. The harmonised survey is designed to provide information on the innovativeness of sectors by type of enterprises, on the different types of innovation and on various aspects of the development of an innovation, such as the objectives, the sources of information, the public funding or the expenditures. The CIS provides statistics broke down by countries, type of innovators, economic activities and size classes. The survey is currently carried out every two years across the European Union, some EFTA countries and EU candidate countries. In order to ensure comparability across countries, Eurostat, in close cooperation with the countries, has developed a standard core questionnaire starting with the CIS3 data collection, along with an accompanying set of definitions and methodological recommendations. The concepts and underlying methodology of the CIS are also based on the Oslo Manual — second edition of 1997 and third edition of 2005 (see link at the bottom of the page). Up to CIS 2010, CIS results were collected under Commission Regulation (EC) No 1450/2004. A new Regulation will apply from CIS 2012 (EC No 995/2012). The data presented in these tables refer to enterprises with ‘10 employees or more’ active in the sectors to be covered under the Regulation (cf. NACE CORE). Further activities may be covered on a voluntary basis. Most statistics are based on a reference period of three years, but some use one calendar year. Since CIS 2008, the survey has included an ad-hoc module. It consists of a set of questions focusing on a special theme. The themes are different in each survey wave, allowing data to be obtained on specific issues beyond the data usually collected. Overview over time: Initially, the CIS data collection was carried out every four years. The first collection (CIS Light) was launched in 1993 as a pilot exercise and the second (CIS2) was carried out in 1997/1998 for most countries except Greece and Ireland, where it was launched in 1999. The third survey (CIS3) was conducted in 2000/2001 for most participating countries with the exception of Norway, Iceland, Luxembourg and Greece, where it was launched in 2002. As from 2004, the survey has been carried out every two years. CIS4 was conducted in the 25 EU Member States (as for 2004), Iceland, Norway, Bulgaria and Romania. The survey was launched in 2005 with a three-year reference period 2002 to 2004 for most indicators. The fifth survey CIS 2006 was carried out in all 25 EU Member States (as for 2006), Norway, Bulgaria, Romania, Croatia and Turkey. It was launched in 2007, mostly for the reference period 2004 to 2006. As regards CIS 2008, 26 Member States (all except Greece), Iceland, Norway, Croatia and Turkey took part in the survey. CIS 2008 was launched in 2009 with a three-year reference period 2006 to 2008 for most indicators. Changes were made to the CIS 2008 questionnaire to bring it into line with the third revision of the Oslo Manual, 2005 edition, by giving greater weight to organisational and marketing innovation. CIS 2008 was complemented by an ad-hoc module on innovation with environmental benefits. The seventh Community Innovation Survey, CIS 2010, had 31 participating countries (all the EU 27 Member States (except Greece), Iceland, Norway, Croatia, Serbia and Turkey) and reported most results for the reference period 2008-2010. CIS 2010 also follows the recommendations of the Oslo Manual and reports indicators on four types of innovation: product, process, organisational and marketing. However, despite implementation of the recommendations of the third edition of the Oslo Manual, the question on innovation expenditures is still limited to product and process innovation in order to maintain continuity with earlier versions of the CIS. Furthermore, generally fewer questions are asked about organisational and marketing innovation than about product and process innovation. While the European innovation statistics use the aggregated national data, the microdata sets can be accessed by researchers via the SAFE Centre of Eurostat in Luxembourg or via the microdata on CD-ROM releases in more anonymised form; some countries also provide access to their micro-data at similar safe centres.

The Community Innovation Survey (CIS) is a survey of innovation activity in enterprises. The harmonised survey is designed to provide information on the innovativeness of sectors by type of enterprises, on the different types of innovation and on various aspects of the development of an innovation, such as the objectives, the sources of information, the public funding or the expenditures. The CIS provides statistics broke down by countries, type of innovators, economic activities and size classes. The survey is currently carried out every two years across the European Union, some EFTA countries and EU candidate countries. In order to ensure comparability across countries, Eurostat, in close cooperation with the countries, has developed a standard core questionnaire starting with the CIS3 data collection, along with an accompanying set of definitions and methodological recommendations. The concepts and underlying methodology of the CIS are also based on the Oslo Manual — second edition of 1997 and third edition of 2005 (see link at the bottom of the page). Up to CIS 2010, CIS results were collected under Commission Regulation (EC) No 1450/2004. A new Regulation will apply from CIS 2012 (EC No 995/2012). The data presented in these tables refer to enterprises with ‘10 employees or more’ active in the sectors to be covered under the Regulation (cf. NACE CORE). Further activities may be covered on a voluntary basis. Most statistics are based on a reference period of three years, but some use one calendar year. Since CIS 2008, the survey has included an ad-hoc module. It consists of a set of questions focusing on a special theme. The themes are different in each survey wave, allowing data to be obtained on specific issues beyond the data usually collected. Overview over time: Initially, the CIS data collection was carried out every four years. The first collection (CIS Light) was launched in 1993 as a pilot exercise and the second (CIS2) was carried out in 1997/1998 for most countries except Greece and Ireland, where it was launched in 1999. The third survey (CIS3) was conducted in 2000/2001 for most participating countries with the exception of Norway, Iceland, Luxembourg and Greece, where it was launched in 2002. As from 2004, the survey has been carried out every two years. CIS4 was conducted in the 25 EU Member States (as for 2004), Iceland, Norway, Bulgaria and Romania. The survey was launched in 2005 with a three-year reference period 2002 to 2004 for most indicators. The fifth survey CIS 2006 was carried out in all 25 EU Member States (as for 2006), Norway, Bulgaria, Romania, Croatia and Turkey. It was launched in 2007, mostly for the reference period 2004 to 2006. As regards CIS 2008, 26 Member States (all except Greece), Iceland, Norway, Croatia and Turkey took part in the survey. CIS 2008 was launched in 2009 with a three-year reference period 2006 to 2008 for most indicators. Changes were made to the CIS 2008 questionnaire to bring it into line with the third revision of the Oslo Manual, 2005 edition, by giving greater weight to organisational and marketing innovation. CIS 2008 was complemented by an ad-hoc module on innovation with environmental benefits. The seventh Community Innovation Survey, CIS 2010, had 31 participating countries (all the EU 27 Member States (except Greece), Iceland, Norway, Croatia, Serbia and Turkey) and reported most results for the reference period 2008-2010. CIS 2010 also follows the recommendations of the Oslo Manual and reports indicators on four types of innovation: product, process, organisational and marketing. However, despite implementation of the recommendations of the third edition of the Oslo Manual, the question on innovation expenditures is still limited to product and process innovation in order to maintain continuity with earlier versions of the CIS. Furthermore, generally fewer questions are asked about organisational and marketing innovation than about product and process innovation. While the European innovation statistics use the aggregated national data, the microdata sets can be accessed by researchers via the SAFE Centre of Eurostat in Luxembourg or via the microdata on CD-ROM releases in more anonymised form; some countries also provide access to their micro-data at similar safe centres.

University of Oxford baseline measure of variation in governments’ responses is the COVID-19 Government Response Stringency Index. This composite measure is a simple additive score of seven indicators measured on an ordinal scale, rescaled to vary from 0 to 100. Please note that this measure is for comparative purposes only, and should not necessarily be interpreted as rating of the appropriateness or effectiveness of a country's response.   Data cited at: Hale, Thomas and Samuel Webster (2020). Oxford COVID-19 Government Response Tracker. Data use policy: Creative Commons Attribution CC BY standard.

Share of EU population covered by the new Convenant of Mayors per Member State, as the ratio between the population of the cities that have signed in a country and the total population of that country.

The indicator measures confidence among EU citizens in a selection of EU institutions: the European Parliament, the European Commission, and the European Central Bank. It is expressed as the share of positive opinions (people who declare that they tend to trust) about the institutions. Citizens are asked to express their confidence levels by choosing the following alternatives: ‘tend to trust’, ‘tend not to trust’ and ‘don’t know’ or ‘no answer’. The indicator is based on the Eurobarometer, a survey which has been conducted twice a year since 1973 to monitor the evolution of public opinion in the Member States. The indicator only displays the results of the autumn survey.

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).

Data given in this domain are collected annually by the National Statistical Institutes and are based on Eurostat's annual model questionnaires on ICT (Information and Communication Technologies) usage in households and by individuals. The model questionnaire changes every year. The changes of questions in the MQ are required by the evolving situation of information and communication technologies. Large part of the data collected are used in the context of the follow up of the Digital Single Market process (Monitoring the Digital Economy & Society  2016-2021). This conceptual framework follows the 2011 - 2015 benchmarking framework, the i2010 Benchmarking Framework and the eEurope 2005 Action Plan. ICT usage data are also used in the Consumer Conditions Scoreboard (purchases over the Internet) and in the Employment Guidelines (e-skills of individuals). The aim of the European ICT surveys is the timely provision of statistics on individuals and households on the use of Information and Communication Technologies at European level. Data for this collection are supplied directly from the surveys with no separate treatment. Coverage: The characteristics to be provided are drawn from the following list of subjects: access to and use of ICTs by individuals and/or in households,use of the Internet and other electronic networks for different purposes by individuals and/or in households,ICT security and trust,ICT competence and skills,barriers to the use of ICT and the Internet,perceived effects of ICT usage on individuals and/or on households,use of ICT by individuals to exchange information and services with governments and public administrations (e-government),access to and use of technologies enabling connection to the Internet or other networks from anywhere at any time (ubiquitous connectivity).Breakdowns (see details of available breakdowns): Relating to households: by region of residence (NUTS 1, optional: NUTS 2)by geographical location: less developed regions, transition regions, more developed regionsby degree of urbanisation (till 2012: densely/intermediate/sparsely populated areas; from 2012: densely/thinly populated area, intermediate density area) by type of householdby households net monthly income (optional) Relating to individuals: by region of residence (NUTS1, optional: NUTS 2)by geographical location: less developed regions, transition regions, more developed regionsby degree of urbanisation: (till 2012: densely/intermediate/sparsely populated areas; from 2012: densely/thinly populated area, intermediate density area)by genderby country of birth, country of citizenship (as of 2010, optional in 2010)by educational level: ISCED 1997 up to 2013 and ISCED 2011 from 2014 onwards.by occupation: manual, non-manual; ICT (coded by 2-digit ISCO categories)/non-ICT (optional: all 2-digit ISCO categories)by employment situationby age (in completed years and by groups)legal / de facto marital status (2011-2014, optional) Regional breakdowns (NUTS) are available only for a selection of indicators disseminated in the regional tables in Eurobase (Regional Information society statistics by NUTS regions (isoc_reg): Households with access to the internet at homeHouseholds with broadband accessIndividuals who have never used a computerIndividuals who used the internet, frequency of use and activitiesIndividuals who used the internet for interaction with public authoritiesIndividuals who ordered goods or services over the internet for private useIndividuals who accessed the internet away from home or work

These splits make it possible to characterize the structure of public finances in OECD countries according to the different types of welfare state. This, in turn, makes it possible for countries to compare themselves with other relevant member countries and may stimulate the national policy debate about questions such as decentralization, redistribution, privatization, the role of the non?profit sector and the application of user fees. Recommended uses and limitations The methodology applied to make the required splits has been developed since 2004 and has gradually become more accurate. The most recent methodology, used in the PFED of 2009, makes use of second level COFOG data and has been applied in a test procedure on five European countries (of which three are OECD countries) that have provided second level COFOG data to Eurostat. In the course of 2007 and 2008, more countries made available second level COFOG data to Eurostat.

The main objective of the research is to address the theoretical and empirical problems of how political institutions of high quality can be created and maintained. The second objective is to study the effects of Quality of Government on a number of policy areas, such as health, environment, social policy, and poverty. Data citation: Teorell, Jan, Aksel Sundström, Sören Holmberg, Bo Rothstein, Natalia Alvarado Pachon, Cem Mert Dalli, Rafael Lopez Valverde & Paula Nilsson. 2024. The Quality of Government Standard Dataset, version Jan24. University of Gothenburg: The Quality of Government Institute, https://www.gu.se/en/quality-government doi:10.18157/qogstdjan24

The data correspond to quarterly financial accounts for the general government sector and follows the ESA2010 methodology. The data covers financial transactions and balance sheet items for general government (consolidated and non-consolidated) and its subsectors. This includes a number of financial instruments (F.1, F.2, F.3, F.4, ...) as well as some balancing items such as net financial transactions, net financial worth and net financial assets and liabilties. Data are available in million of euro, million of national currency (average exchange rates are used for transactions and end of period exchange rates are used for stocks) and as a percentage of GDP (for transactions quarterly GDP is used; for stocks a rolling sum of the last four quarters is used). In the table gov_10a_ggfa, annualised quarterly financial accounts for general government are presented. For financial transactions, data is summed over the four quarters of each year. For the conversion from national currency into euro, the yearly average exchange rate is used. For balance sheet items (stocks), the annualised data corresponds to the data of the fourth quarter. The percentage of GDP data of annualised data uses annual GDP transmitted by the Member States. In the course of the annualisation, small rounding differences may be amplified. Geographic coverage: EU and euro area. Main data sources are the tables provided according to the European Parliament and Council Regulation (EU) N° 549/2013 of 21 May 2013 (OJ No L174/1).

'Quarterly government debt' is defined as the total gross debt at nominal value outstanding at the end of each quarter for the general government sector (ref. Regulation  (EU) No 549/2013, Annex B transmission programme, definition of general government sector ESA 2010 §2.111). Data are measured in million Euro, million of national currency units, percentage of GDP and percentage of total consolidated debt. Data cover EU Member States and Norway. Quarterly data on government debt is provided according to the provisions of the European System of Accounts ESA 2010 (Regulation (EU) No 549/2013). Data is transmitted by national authorities (National Statistical Institutes, National Central Banks or Ministries of Finance).

The data correspond to quarterly non-financial accounts for the general government sector which are conceptually consistent with the corresponding annual data compiled on a national accounts (ESA2010) basis. The data sets contain quarterly general government total expenditure and total revenue figures, as well as their breakdowns by relevant categories and the resulting quarterly government deficit/surplus.

This database provides a set of indicators that reflect the level and structure of central government support for business R&D; in form of R&D; tax incentives and direct funding across OECD member countries and ten non-member economies (Argentina, Brazil, Bulgaria, Croatia, Cyprus, People's Republic of China, Romania, Russian Federation, and South Africa). This includes time-series indicators of tax expenditures for R&D;, based on the latest 2017 OECD data collection on tax incentive support for R&D; expenditures that was completed in July 2017. These estimates of the cost of R&D; tax relief have been combined with data on direct R&D; funding, as compiled by National Statistical Offices based on reports from firms, in order to provide a more complete picture of government efforts to promote business R&D.; The latest indicators and information on R&D; tax incentives also feature on the dedicated OECD website Measuring R&D; tax incentives.Tax expenditures are deviations from a benchmark tax system (OECD, 2010) and countries use different national benchmarks. Available estimates typically reflect the sum of foregone tax revenues – on an accruals basis – and refunds where applicable, with no or minimal adjustments for behavior effects. Some countries only report claims realised in a given year (cash basis), while others report losses to government on an accrual basis, excluding claims referring to earlier periods and including claims for current R&D; to be used in the future. For general and country-specific notes on the estimates of government tax relief for R&D; expenditures (GTARD), see http://www.oecd.org/sti/rd-tax-stats-gtard-notes.pdfThe sources for the other indicators (direct funding of BERD, BERD and GDP) include the OECD databases on Main Science and Technology Indicators and Eurostat R&D; statistics.

Data given in this domain are collected on a yearly basis by the National Statistical Institutes or Ministries and are based on the annual Eurostat Model Questionnaires on ICT (Information and Communication Technologies) usage and e-commerce in enterprises. Large part of the data collected are used in the context of the 2011 - 2015 benchmarking framework (endorsed by i2010 High Level Group in November 2009) for the Digital Agenda Scoreboard, Europe's strategy for a flourishing digital economy by 2020. This conceptual framework follows the i2010 Benchmarking Framework which itself followed-up the eEurope 2005 Action Plan. The aim of the European ICT usage surveys is to collect and disseminate harmonised and comparable information on the use of Information and Communication Technologies in enterprises and e-commerce at European level. Coverage: The characteristics to be provided are drawn from the following list of subjects: ICT systems and their usage in enterprises,use of the Internet and other electronic networks by enterprises,e-commerce,e-business processes and organisational aspects,use of ICT by enterprises to exchange information and services with governments and public administrations (e-government),ICT competence in the enterprise and the need for ICT skills,barriers to the use of ICT, the Internet and other electronic networks, e-commerce and e-business processes,ICT expenditure and investment,ICT security and trust,use of ICT and its impact on the environment (Green ICT),access to and use of the Internet and other network technologies for connecting objects and devices (Internet of Things),access to and use of technologies providing the ability to connect to the Internet or other networks from anywhere at any time (ubiquitous connectivity).Breakdowns:by size class,by NACE categories,by region (until 2010)

This collection provides users with data concerning R&D expenditure and R&D personnel broken down by following institutional sectors: business enterprise (BES), government (GOV), higher education (HES), private non-profit (PNP) with the total of sectors. All data are broken down by the above mentioned sectors of performance. The R&D expenditure is further broken down by source of funds, by type of costs, by economic activity (NACE Rev.2), by size class, by type of R&D, by fields of science, by socio-economic objectives and by regions (NUTS 2 level). Besides R&D expenditures in basic unit National currency (MIO_NAC) the following units are available: Euro (MIO_EUR), Euro per inhabitant (EUR_HAB) Purchasing Power Standard (MIO_PPS), Purchasing Power Standard at 2005 prices (MIO_PPS_KP05), Purchasing Power Standard per inhabitant at constant 2005 prices (PPS_KP05_HAB), Percentage of GDP (PC_GDP) and Percentage of total R&D expenditure (PC_TOT - for the breakdown by source of funds). R&D personnel data is available in full-time equivalent (FTE), in head count (HC), as a % of employment and as a % of labour force. The data is further broken down by occupation, by qualification, by gender, by size class, by citizenship, by age groups, by fields of science, by economic activity (NACE Rev.2) and by regions (NUTS 2 level). The periodicity of R&D data is biennial except for the key R&D indicators (R&D expenditure, R&D personnel and Researchers by sectors of performance) which are transmitted annually by the EU Member States on the basis of a legal obligation from 2003 onwards. Some other breakdowns of the data may appear on annual basis based on voluntary data provisions. The data are collected through sample or census surveys, from administrative registers or through a combination of sources. R&D data are available for following countries and country groups: - All EU Member States, plus Candidate Countries, EFTA Countries, the Russian Federation, China, Japan, the United States and South Korea. - Country groups: EU-28, EU-15 and EA-18. R&D data are compiled in accordance to the guidelines laid down in the Proposed standard practice for surveys of research and experimental development - Frascati Manual (FM), OECD, 2002 .

This collection provides users with data concerning R&D expenditure and R&D personnel broken down by following institutional sectors: business enterprise (BES), government (GOV), higher education (HES), private non-profit (PNP) with the total of sectors. All data are broken down by the above mentioned sectors of performance. The R&D expenditure is further broken down by source of funds, by type of costs, by economic activity (NACE Rev.2), by size class, by type of R&D, by fields of science, by socio-economic objectives and by regions (NUTS 2 level). Besides R&D expenditures in basic unit National currency (MIO_NAC) the following units are available: Euro (MIO_EUR), Euro per inhabitant (EUR_HAB) Purchasing Power Standard (MIO_PPS), Purchasing Power Standard at 2005 prices (MIO_PPS_KP05), Purchasing Power Standard per inhabitant at constant 2005 prices (PPS_KP05_HAB), Percentage of GDP (PC_GDP) and Percentage of total R&D expenditure (PC_TOT - for the breakdown by source of funds). R&D personnel data is available in full-time equivalent (FTE), in head count (HC), as a % of employment and as a % of labour force. The data is further broken down by occupation, by qualification, by gender, by size class, by citizenship, by age groups, by fields of science, by economic activity (NACE Rev.2) and by regions (NUTS 2 level). The periodicity of R&D data is biennial except for the key R&D indicators (R&D expenditure, R&D personnel and Researchers by sectors of performance) which are transmitted annually by the EU Member States on the basis of a legal obligation from 2003 onwards. Some other breakdowns of the data may appear on annual basis based on voluntary data provisions. The data are collected through sample or census surveys, from administrative registers or through a combination of sources. R&D data are available for following countries and country groups: - All EU Member States, plus Candidate Countries, EFTA Countries, the Russian Federation, China, Japan, the United States and South Korea. - Country groups: EU-28, EU-15 and EA-18. R&D data are compiled in accordance to the guidelines laid down in the Proposed standard practice for surveys of research and experimental development - Frascati Manual (FM), OECD, 2002 .

The indicator measures the proportion of women in national parliaments and national governments. The national parliament is the national legislative assembly and the indicator refers to both chambers (lower house and an upper house, where relevant). The count of members of a parliament includes the president/speaker/leader of the parliament. The national government is the executive body with authority to govern a country or a state. Members of government include both senior ministers (having a seat in the cabinet or council of ministers, including the prime minister) and junior ministers (not having a seat in the cabinet). In some countries state-secretaries (or the national equivalent) are considered as junior ministers within the government (with no seat in the cabinet) but in other countries they are not considered as members of the government.

Source: UNECE Statistical Database, compiled from national official sources by UNECE Statistical Division and UN Women. Definition:Indicator 5.5.1(b) measures the proportion of positions held by women in local government.It is expressed as a percentage of elected positions held by women in legislative/ deliberative bodies of localgovernment. Read more about this on the UNECE Statistical Glossary. Country: Albania 2017: Administrative data based on most recent election results at municipal level (2015) and post-election replacements. Country: Andorra From 2015 onwards: Administrative data. Country: Armenia 2018: Administrative data. Data coverage include regional and community level, including Yerevan city. Country: Azerbaijan 2018: Administrative data based on most recent election results (2014). Country: Belarus 2018: Administrative data based on most recent election results (2018). Country: Belgium 2018: Administrative data based on most recent election results (2018) from the Istitute for the Equality of Women and Men. Country: Bosnia and Herzegovina 2018: Administrative data based on most recent election results (2016). Country: Bulgaria 2018: Administrative data based on most recent election results (2015). Country: Canada 2018: Data based on most recent election results (2015) at municipal level obtained by NSO from Local Government Associations. Country: Croatia 2018: Administrative data based on most recent election results (2017). Country: Czechia 2018: Administrative data based on most recent election results at the level of regions (2016), municipalities (2018) and city districts (2018). Country: Denmark 2018: Administrative data based on most recent election results (2017) Country: Estonia Administrative data Country: Finland 2018: Administrative data based on most recent election results (2017). Country: France 2018: Administrative data based on most recent election results at the level of communes (2014), departments (2015) and regions (2015). Data cover Metropolitan France and the territories of Guadeloupe, Martinique, Guyane, La Reunion and Mayotte. Country: Georgia 2018: Administrative data based on most recent election results (2017). Country: Germany 2018: Administrative data based on most recent election results (around year 2017). Country: Hungary 2018: Administrative data based on most recent election results (2014), provided by the Electoral Management Body of the country. Country: Iceland 2018: Administrative data based on most recent election results (2018). Country: Ireland 2018: Administrative data based on most recent election results (2014). Country: Israel 2018: Administrative data based on most recent election results (2018). Country: Italy 2018: Administrative data on municipalities provided by the Ministry of Interior. Country: Kazakhstan 2018: Administrative data. Country: Latvia 2018: Administrative data based on most recent election results (2017) Country: Liechtenstein 2019: Administrative data based on most recent election results (2019). Country: Lithuania 2018: Administrative data based on most recent election results (2015). Country: Luxembourg 2018: Administrative data based on most recent local election (2017). Country: Malta 2017: Administrative data Country: Montenegro 2017: Data on municipal councillors provided by NSO based on information from local government association. Municipality Tuzi not covered. Country: Netherlands 2018: Administrative data Country: Norway 2018: Administrative data based on most recent election results (2015). Country: Poland Data based on censuses/surveys. Country: Republic of Moldova 2018: Administrative data based on most recent election results (2015). Data exclude the territory of Transnistria and municipality of Bender. Country: Romania 2018: Administrative data based on most recent election results (2016). Country: San Marino Indicator not applicable / No elected deliberative bodies of local government. Country: Serbia 2018: Administrative data based on most recent election results (up to 2016) Country: Slovakia 2018: Administrative data based on most recent election results (2018). Country: Slovenia 2018: Administrative data collected by Ministry of Public Administration, reflecting 2018 local elections results. Country: Spain 2018: Administrative data based on most recent election results at the level of municipalities (2015) and provinces (2017). Country: Sweden 2018: Administrative data based on most recent election results (2018). Country: Switzerland 2018: Data based on most recent municipal elections (2018) provided by NSO based on information from the Union of Swiss cities. Country: Turkey 2018: Administrative data based on most recent election results (2014) at the level of metropolitan municipalities, municipalities and provinces.

The supplementary table on accrued-to-date  pension entitlements in social insurance (pensions in National Accounts) is compiled in accordance with the European System of Accounts (ESA 2010) and is transmitted by EU Member States, EEA Members (Norway, Iceland) and Switzerland following the ESA2010 transmission programme (Table 29) established by the Regulation (EU) No 549/2013 of the European Parliament and of the Council of 21 May 2013 on the European system of national and regional accounts in the European Union, annexes A and B respectively). By introducing this table, ESA 2010 added enhanced reporting on pensions, covering both entitlements of pension schemes recorded in the core national accounts, and unfunded "pay-as-you-go" pension schemes managed by general government. The latters' entitlements are excluded from the core national accounts and are considered as contingent liabilities. However, full coverage of all pension schemes in one table provides a complete overview of organisation of pension social insurance in a given country and enhances cross-country analysis of pension entitlements of households. At the same time, it should be stressed that accrued-to-date pension entitlements in social insurance are not a measure of the sustainability of public finances and not part of government debt. The European reporting system on age-related expenditure is multifaceted. National accountants focus in this dataset on already earned (accrued-to-date) pension entitlements of current persons employed and current pensioners, whereas the Economic Policy Committee (EPC) is analysing the impact of ageing on European societies from a wider angle. The EPC'S Ageing Report includes estimates for pension entitlements (and related contributions) being accrued in the future. Data are presented by means of two tables: 1.  "Accrued-to-date pension entitlements in social insurance" (nasa_10_pens1) The table gives an overview of accumulation of pension entitlements by all types of social insurance pension schemes (defined contribution vs. defined benefit schemes, private vs. general government schemes, core accounts schemes vs. social security schemes) in a given period due to pension contributions, payment of pension benefits and other changes. 2. "Sensitivity analysis of accrued-to-date pension entitlements in general government pension schemes outside of core national accounts" (nasa_10_pens2) The data on unfunded general government pension schemes outside of core national accounts are based on actuarial calculations. Thus, the results for pension entitlements depend to a large extent on the underlying assumptions. To ensure a consistent approach and cross-country data comparability, actuarial assumptions for these schemes in ESA 2010 Table 29 are aligned with those proposed by the EPC Ageing Working group (AWG), including the discount rate to calculate present value of pension entitlements. Actuarial assumptions are regularly reviewed by the AWG in the framework of 3-yearly Ageing reports. Analysis shows that the discount rate is the most important parameter that impacts on the resulting value of pension entitlements. Therefore, table 2 shows how the outcome of actuarial calculations varies based on a different choice of discount rate. Three scenarios are presented as follows under SECTOR dimension: S13_BC – base case scenario with current discount rate 5% in nominal terms (3% in real terms) S13_SC1 –scenario with discount rate 1 percentage point less than in base case S13_SC3 –scenario with discount rate 1 percentage point higher than in base case Data, as far as they are available, are expressed in national currency and millions of euro in current prices. In line with ESA2010 Transmission programme requirements data series start from 2015 and are to be transmitted on 3-yearly basis. Countries may transmit longer time series or transmit data annually on voluntary basis.

Data on Government Budget Appropriations or Outlays on Research and Development (GBAORD) refer to budget provisions, not to actual expenditure, i.e. GBAORD measures government support for R&D using data collected from budgets. The GBAORD indicator should be seen as a complement to indicators based on surveys of R&D performers, which are considered to be a more accurate but less timely way of measuring R&D activities. In this table, total GBAORD is expressed as a percentage of total general government expenditure.

Data are the result of the annual structure of government debt survey and cover the EU countries as well as Norway. The following series are available: Central government gross debt by initital maturity and sector of debt holder; State government gross debt by initital maturity and sector of debt holder; Local government gross debt by initital maturity and sector of debt holder; Social security funds gross debt by initital maturity and sector of debt holder; General government gross debt by initital maturity and sector of debt holder; Debt by currency of issuance; Government guarantees (contingent liabilities).

Data are the result of the annual structure of government debt survey and cover the EU countries as well as Norway. The following series are available: Central government gross debt by initital maturity and sector of debt holder; State government gross debt by initital maturity and sector of debt holder; Local government gross debt by initital maturity and sector of debt holder; Social security funds gross debt by initital maturity and sector of debt holder; General government gross debt by initital maturity and sector of debt holder; Debt by currency of issuance; Government guarantees (contingent liabilities).

The subnational government finance dataset presents data on the institutional organisation at local and regional levels as well as on public finance. Financial data cover the general government sector and subnational government subsector (state and local government levels) in the 35 OECD member countries and in the EU. Four main dimensions are presented: expenditure (including investment), revenue, budget balance and debt. The dataset is released as a beta version. Data at country level are derived mainly from the OECD National Accounts harmonised according to the new standards of the System of National Accounts (SNA) 2008, implemented by most OECD countries since December 2014. They are complemented by data from Eurostat, IMF (Australia, Chile), and national statistical institutes for some countries or indicators (in particular, territorial organisation). Data were extracted in February 2017 and are from 2015, unless otherwise specified

This domain provides users with data concerning Government Budget Appropriations or Outlays on R&D (GBAORD). GBAORD data are measuring government support to research and development (R&D) activities, or, in other words, how much priority Governments place on the public funding of R&D. GBAORD data are built up using the guidelines laid out in the Proposed standard practice for surveys of research and experimental development - Frascati Manual, OECD, 2002 (See annex at the bottom of the page). GBAORD data are broken down by:   - Socio-economic objectives (SEOs) in accordance to the Nomenclature for the analysis and comparison of scientific programmes and budgets (NABS 2007) - (See annex at the bottom of the page).   - Funding mode into: project funding and institutional funding (non-mandatory data). Part of GBAORD, which is allocated to transnational cooperation in R&D, is further broken down into three specific categories: transnational public R&D performers; Europe-wide transnational public R&D programmes and bilateral or multilateral public R&D programmes established between Member State governments or with EFTA and candidate countries. Besides in basic unit National currency (MIO_NAC) the following units are available: Euro (MIO_EUR), Euro per inhabitant (EUR_HAB) Purchasing Power Standard (MIO_PPS), Purchasing Power Standard at 2005 prices (MIO_PPS_KP05), Purchasing Power Standard per inhabitant at constant 2005 prices (PPS_ HAB_KP05), Percentage of GDP (PC_GDP), Percentage of total GBAORD (PC_GBA - for the breakdowns by socio-economic objectives and by funding mode), Percentage of total transnationally coordinated R&D (PC_TOT - for the breakdown by category), Percentage of government expenditure (PC_GEXP). The periodicity of the GBAORD data is annual. Data are collected corresponding to the two legally established deadlines:   - June data collection: Preliminary GBAORD data are provided to Eurostat 6 months after the end of the calendar year (June). This data are targeted to be disseminated in Eurobase in September.   - December data collection: Final GBAORD data are provided to Eurostat 12 months after the end of the calendar year (December). This data are targeted to be disseminated in Eurobase in the following February. GBAORD data are available for following countries and country groups:   - All EU Member States, Iceland, Norway, Switzerland,  Turkey, the Russian Federation, Japan, the United States and South Korea.   - Country groups: EU28, EU15 and EA18.

Total general government expenditure is defined in ESA 2010 8.100 and chapter 20 by reference to a list of categories: intermediate consumption, gross capital formation, compensation of employees, other taxes on production, subsidies, payable property income, current taxes on income, wealth, etc., social benefits other than social transfers in kind, social transfers in kind - purchased market production, other current transfers, adjustments for the change in pension entitlements, capital transfers and acquisitions less disposals of non-financial non-produced assets.

Total general government revenue is defined in ESA 2010 8.100 and chapter 20 by reference to a list of categories: market output, output for own final use, payments for non-market output, taxes on production and imports, other subsidies on production, receivable property income, current taxes on income, wealth, etc., net social contributions, other current transfers and capital transfers.

Government Finance Statistics (GFS) form the basis for fiscal monitoring in Europe, most notably for the statistics related to the Excessive Deficit Procedure (EDP). The EDP is established in the Treaty and specified in the Stability and Growth Pact legislation. The Member States report data related to the EDP to the Commission (Eurostat) which, in turn, is responsible for providing the data to the Council. European GFS, including the statistics for the EDP, are produced in accordance with the European System of Accounts 2010 (ESA 2010), the EU manual for national accounts, which in September 2014 replaced the previous version of the national accounting framework ESA 95. It is supplemented by further interpretation and guidance from Eurostat, in particular the Manual on Government Deficit and Debt. Council Regulation 479/2009 as amended requires that Member States report government deficit/surplus (hereinafter deficit) and debt data related to the EDP twice per year: before 1 April and 1 October for the preceding four calendar years and a forecast for the current year. The data are reported in harmonised tables. These tables are designed specifically to provide a consistent framework, with a link to national budgetary aggregates and between the deficit and changes in the debt. They should be fully consistent with GFS data delivered to Eurostat in the ESA 2010 transmission programme. The EDP notification tables contain for general government and its sub sectors:Table 1: Summary table on deficit and debt, including auxiliary indicators (Gross Fixed Capital Formation, Interest and Gross Domestic Product - GDP)Tables 2A - 2D: Transition from the working balance to the deficit/surplus for general government sub sectorsTables 3A - 3E: Transition from the deficit/surplus to the change in debt for general government and its sub sectorsTable 4: Supplementary data. The data are presented in the Eurostat's Statistics Database in national currency, euro/ECU, and percentage of GDP. In order to reflect economic and technological developments and meet user needs, in September 2014 the new national accounting framework ESA 2010 replaced the previous framework ESA 95. This led to revisions of the time series for all Member States (please see Eurostat press release for the impact of the revisions on the government deficit and debt ratios). The main changes relate to the classification of certain entities into government and the treatment of transactions related to pension schemes. Also the concept of government deficit was changed as regards treatment of interest on swaps and forward rate agreements (Commission Regulation 220/2014 amending the Council Regulation 479/2009), according to which these flows are now recorded as financial transaction in line with the core ESA accounting framework.

Government Finance Statistics (GFS) form the basis for fiscal monitoring in Europe, most notably for the statistics related to the Excessive Deficit Procedure (EDP). The EDP is established in the Treaty and specified in the Stability and Growth Pact legislation. The Member States report data related to the EDP to the Commission (Eurostat) which, in turn, is responsible for providing the data to the Council. European GFS, including the statistics for the EDP, are produced in accordance with the European System of Accounts 2010 (ESA 2010), the EU manual for national accounts, which in September 2014 replaced the previous version of the national accounting framework ESA 95. It is supplemented by further interpretation and guidance from Eurostat, in particular the Manual on Government Deficit and Debt. Council Regulation 479/2009 as amended requires that Member States report government deficit/surplus (hereinafter deficit) and debt data related to the EDP twice per year: before 1 April and 1 October for the preceding four calendar years and a forecast for the current year. The data are reported in harmonised tables. These tables are designed specifically to provide a consistent framework, with a link to national budgetary aggregates and between the deficit and changes in the debt. They should be fully consistent with GFS data delivered to Eurostat in the ESA 2010 transmission programme. The EDP notification tables contain for general government and its sub sectors: Table 1: Summary table on deficit and debt, including auxiliary indicators (Gross Fixed Capital Formation, Interest and Gross Domestic Product - GDP)Tables 2A - 2D: Transition from the working balance to the deficit/surplus for general government sub sectorsTables 3A - 3E: Transition from the deficit/surplus to the change in debt for general government and its sub sectorsTable 4: Supplementary data. The data are presented in the Eurostat's Statistics Database in national currency, euro/ECU, and percentage of GDP. In order to reflect economic and technological developments and meet user needs, in September 2014 the new national accounting framework ESA 2010 replaced the previous framework ESA 95. This led to revisions of the time series for all Member States (please see Eurostat press release for the impact of the revisions on the government deficit and debt ratios). The main changes relate to the classification of certain entities into government and the treatment of transactions related to pension schemes. Also the concept of government deficit was changed as regards treatment of interest on swaps and forward rate agreements (Commission Regulation 220/2014 amending the Council Regulation 479/2009), according to which these flows are now recorded as financial transaction in line with the core ESA accounting framework.

Data cited at: UN E-Government Knowledgebase - https://publicadministration.un.org/egovkb/en-us/ 1. The EGDI is based on a comprehensive Survey of the online presence of all 193 United Nations Member States, which assesses national websites and how e-government policies and strategies are applied in general and in specific sectors for delivery of essential services. The assessment rates the e-government performance of countries relative to one another as opposed to being an absolute measurement. The results are tabulated and combined with a set of indicators embodying a country’s capacity to participate in the information society, without which e-government development efforts are of limited immediate use. Although the basic model has remained consistent, the precise meaning of these values varies from one edition of the Survey to the next as understanding of the potential of e-government changes and the underlying technology evolves. This is an important distinction because it also implies that it is a comparative framework that seeks to encompass various approaches that may evolve over time instead of advocating a linear path with an absolute goal. 2. E-Government Development Index-EGDI Very High-EGDI (Greater than 0.75) High-EGDI (Between 0.50 and 0.75) Middle-EGDI (Between 0.25 and 0.50) Low-EGDI (Less than 0.25)

Data given in this domain are collected annually by the National Statistical Institutes and are based on Eurostat's annual model questionnaires on ICT (Information and Communication Technologies) usage in households and by individuals. The model questionnaire changes every year. The changes of questions in the MQ are required by the evolving situation of information and communication technologies. Large part of the data collected are used in the context of the follow up of the Digital Single Market process (Monitoring the Digital Economy & Society  2016-2021). This conceptual framework follows the 2011 - 2015 benchmarking framework, the i2010 Benchmarking Framework and the eEurope 2005 Action Plan. ICT usage data are also used in the Consumer Conditions Scoreboard (purchases over the Internet) and in the Employment Guidelines (e-skills of individuals). The aim of the European ICT surveys is the timely provision of statistics on individuals and households on the use of Information and Communication Technologies at European level. Data for this collection are supplied directly from the surveys with no separate treatment. Coverage: The characteristics to be provided are drawn from the following list of subjects: access to and use of ICTs by individuals and/or in households,use of the Internet and other electronic networks for different purposes by individuals and/or in households,ICT security and trust,ICT competence and skills,barriers to the use of ICT and the Internet,perceived effects of ICT usage on individuals and/or on households,use of ICT by individuals to exchange information and services with governments and public administrations (e-government),access to and use of technologies enabling connection to the Internet or other networks from anywhere at any time (ubiquitous connectivity).Breakdowns (see details of available breakdowns): Relating to households: by region of residence (NUTS 1, optional: NUTS 2)by geographical location: less developed regions, transition regions, more developed regionsby degree of urbanisation (till 2012: densely/intermediate/sparsely populated areas; from 2012: densely/thinly populated area, intermediate density area) by type of householdby households net monthly income (optional) Relating to individuals: by region of residence (NUTS1, optional: NUTS 2)by geographical location: less developed regions, transition regions, more developed regionsby degree of urbanisation: (till 2012: densely/intermediate/sparsely populated areas; from 2012: densely/thinly populated area, intermediate density area)by genderby country of birth, country of citizenship (as of 2010, optional in 2010)by educational level: ISCED 1997 up to 2013 and ISCED 2011 from 2014 onwards.by occupation: manual, non-manual; ICT (coded by 2-digit ISCO categories)/non-ICT (optional: all 2-digit ISCO categories)by employment situationby age (in completed years and by groups)legal / de facto marital status (2011-2014, optional) Regional breakdowns (NUTS) are available only for a selection of indicators disseminated in the regional tables in Eurobase (Regional Information society statistics by NUTS regions (isoc_reg): Households with access to the internet at homeHouseholds with broadband accessIndividuals who have never used a computerIndividuals who used the internet, frequency of use and activitiesIndividuals who used the internet for interaction with public authoritiesIndividuals who ordered goods or services over the internet for private useIndividuals who accessed the internet away from home or work