Government finance statistics - quarterly data

Data extracted on 22 April 2020.

Planned article update: July 2020.

Highlights


At the end of the fourth quarter of 2019, the government debt to GDP ratio in the euro area stood at 84.1%, compared with 85.9% at the end of the third quarter of 2019.

The highest ratios of government debt to GDP at the end of the fourth quarter of 2019 were recorded in Greece (176.6%), Italy (134.8%) and Portugal (117.7%) and the lowest in Estonia (8.4%), Bulgaria (20.4%) and Luxembourg (22.1%).

In the fourth quarter of 2019, the government deficit to GDP ratio stood at -0.7% in both the euro area and in the EU-27 and remained unchanged in both zones compared with the third quarter of 2019.

EU-28, EU-27 and EA-19 quarterly net lending (+)/ net borrowing (-), % of GDP, seasonally adjusted data
Source: Eurostat (gov_10q_ggnfa)

In recent years, Eurostat has significantly expanded the range of integrated quarterly data on government finance statistics available, providing a timely and increasingly high quality picture of the evolution of government finances in the European Union (EU). The data presented in this article reflect both non-financial and financial (quarterly non-financial and financial accounts for general government transactions and cover all European Union EU-27 countries as well as Iceland, Norway and Switzerland.

This article is based on data transmitted to Eurostat at the end of March 2020, which includes data coverage of the fourth quarter of 2019, and follow ESA 2010 methodology. It is supplemented by non-financial seasonally adjusted data estimated provided on a voluntary basis by EU and EFTA countries' National Statistical Institutes. Eurostat regularly publishes seasonally adjusted and working day adjusted quarterly data on government revenue, expenditure and surplus (+)/ deficit (-), currently for twenty-one Member States, United Kingdom, Switzerland and the EU aggregates.

In the fourth quarter of 2019, the seasonally adjusted general government deficit to GDP ratio stood at -0.7 % in both the euro area (EA-19) and in the EU-27 and remained unchanged compared to the previous quarter of 2019. In both areas, it has increased slightly in comparison with the first quarter of 2019.

Full article


Quarterly non-financial accounts for general government

Government revenue and expenditure

Both total revenue and expenditure exhibit a clear seasonality. In order to interpret trends for the most recent quarters, seasonally adjusted data is presented in addition to the raw data transmitted by EU Member States (see explanation below).

In the fourth quarter of 2019, seasonally adjusted total government revenue in the euro area amounted to 46.4 % of GDP, a decrease compared with 46.6 % of GDP in the third quarter of 2019. Total government expenditure in the euro area stood at 47.1 % of GDP, a decrease compared with 47.3 % of GDP in the previous quarter.

In the EU-27, total government revenue was 46.1 % of GDP in the fourth quarter of 2019, a decrease compared to 46.2 % of GDP in the previous quarter. Total government expenditure in the EU-27 was 46.7 % of GDP, a decrease compared with 46.9 % of GDP in the previous quarter.

Figure 2: EA-19 total revenue and total expenditure, seasonally adjusted and non-adjusted data, billion euro
Source: Eurostat (gov_10q_ggnfa)


Figure 3: EA-19 total revenue and total expenditure, seasonally adjusted and non-adjusted data, % of GDP
Source: Eurostat (gov_10q_ggnfa)

From the third quarter of 2010 onwards, a decreasing trend in the level of the total expenditure-to-GDP ratio is visible, reflecting an absolute decrease in total expenditure in the fourth quarter of 2010 and the first quarter of 2011 as well as the effects of renewed economic growth in the EU and the euro area (all seasonally adjusted). In the fourth quarter of 2012 and in the second quarter of 2013, total expenditure increased slightly in both areas, influenced by interventions to support the banking sector in several Member States, notably in Spain in the fourth quarter of 2012 and in Greece in the second quarter of 2013. Supports for the banking sector in several Member States are also the main reason for the increase in the fourth quarter of 2015.

Table 1: EA-19, EU-27 and EU-28 quarterly net lending (+)/ net borrowing (-), total expenditure and total revenue as a percentage of GDP, seasonally adjusted data
Source: Eurostat (gov_10q_ggnfa), seasonally adjusted data: Eurostat and National Statistical Institutes estimates


Table 2: Quarterly net lending (+)/ net borrowing (-) as a percentage of GDP, seasonally adjusted data
Source: Eurostat (gov_10q_ggnfa), seasonally adjusted data: National Statistical Institute estimates


Table 3: Quarterly net lending (+)/ net borrowing (-) by country, non-seasonally adjusted data
Source: Eurostat (gov_10q_ggnfa)

General government deficit

The difference between general government total revenue and total expenditure is known in ESA2010 terminology as general government net lending (+)/ net borrowing (-) (ESA2010 category B.9) and is usually referred to as government deficit (or surplus). This figure is an important indicator of the overall situation of government finances. It is usually expressed as a percentage of GDP.

In the fourth quarter of 2019, the seasonally adjusted general government deficit to GDP ratio stood at -0.7 % in both the euro area (EA-19) and in the EU-27, remained unchanged compared to the third quarter of 2019.

The lowest deficit to GDP ratio in the available time series occurred in the first quarter of 2018 in both the euro area and the EU-27, when the deficit stood at -0.2 % of GDP in both areas.

Due to the economic and financial crisis, which started in 2008, government's deficits steadily deteriorated and reached -7.1 % of GDP (seasonally adjusted) in the third quarter of 2010 for the euro area and -6.7 % of GDP (seasonally adjusted) in the first quarter of 2010 for the EU-27. The beginning of the consolidation of public finances which can be observed from the fourth quarter of 2010 onwards is due to a reduction in government expenditure in terms of GDP, as well as continued growth in absolute revenue (seasonally adjusted absolute numbers), which outpaced the growth in GDP. From the fourth quarter of 2010 onwards, the seasonally adjusted general government deficit no longer exceeded 5 % of GDP in both the euro area and EU-27. However, from the first quarter of 2011 onwards, general government total expenditure (seasonally adjusted) resumed growth when measured in absolute terms in both the euro area and EU-27. From the fourth quarter of 2013 onwards, the seasonally adjusted general government deficit remained below 3 % in the euro area and the EU-27.

Up to the first quarter of 2018, marked decreases in the deficit are driven by reductions in total expenditure as a percentage to GDP and increases in total revenue as a percentage of GDP. In absolute terms, seasonally adjusted total expenditure remained stable in the EU and euro area, while seasonally adjusted total revenue continued to grow slightly exceeding the growth of nominal GDP. From the second quarter of 2018 onwards the seasonal adjusted deficit remainded between 0.3 and 0.8 % of GDP in the euro area and 0.2 and 0.7 % of GDP in the euro area.

Seasonally adjusted general government deficit

For Italy, the deficit (non-seasonally adjusted) is influenced negatively by operations connected to two bank liquidations in the second quarter of 2017.

For Cyprus, the deficit in the third quarter of 2018 is due to the impact of the restructuring of the Cyprus Cooperative Bank Ltd (CCB), i.e. the sale of the good parts of CCB and the subsequent integration of the remaining public financial defeasance structure into general government accounts.

For Hungary, the relatively large seasonally adjusted deficit in the fourth quarter of 2016 is caused by large capital transfers to other sectors, notably in the context of co-financing payments for EU funds.

For Austria, the large deficit in the fourth quarter of 2014 is largely due to a capital injection treated as capital transfer to implement the HETA defeasance structure, while the relatively low deficit in the fourth quarter of 2013 is due to an auction of mobile phone licences. The comparatively large deficit in the third quarter of 2015 is also due to capital injections treated as capital transfers in the context of HETA.

For Portugal, the large deficit in the fourth quarter of 2015 is explained by support to financial corporations. The large seasonally adjusted deficit in the first quarter of 2017 is explained by a one-off effect - a capital transfer increasing expenditure / deficit towards a financial corporation (recapitalisation of Caixa Geral de Depósitos (CGD)). In quarters of 2018, shifts in the net lending/ net borrowing between quarters are mainly due to the time of payment of certain VAT on imports, a shift of reimbursements of personal income taxes from the third quarter to the second quarter. In addition, exception capital revenue (recuperation of part of the guarantee issued in 2010 to Banco Privado Português) influenced the balance positively. For more information, please consult the press release of INE Portugal.

The large deficit for Slovenia in the fourth quarter of 2013 is mainly caused by capital injections to support financial institutions. This is also the reason for the relatively large deficit in the first quarter of 2013 and the fourth quarter of 2014. In addition to this, there are one-off effects in the third and fourth quarters of 2013 due to court decisions. In contrast to this, the third quarter of 2013 is positively influenced by dividends from the National Central Bank.

For the United Kingdom, the deficit of several quarters since 2012 is positively influenced by dividends from the central bank (Bank of England Asset Purchase Facility).

For Iceland, the large reported surplus in the first quarter of 2016 is due to one-off stability contributions paid by the failed banks.

In the fourth quarter of 2019, improvements (decreases in deficit or increases in surplus) are noted in fifteen EU Member States for which data is published, while increases in the deficit or decreases in the surplus are noted for six Member States.

In Eurobase, seasonally adjusted and calendar day adjusted total revenue and total expenditure data of Member States and EFTA countries, which provide seasonally adjusted and calendar day adjusted data for total revenue, total expenditure and net lending (+)/ net borrowing (-) in addition to the non-seasonally adjusted data, is presented in full detail. This data is provided on a voluntary basis by the National Statistical Institutes.

Figure 4: EA-19 net lending, net borrowing, seasonally adjusted and non-adjusted data, % of GDP and billion euro
Source: Eurostat (gov_10q_ggnfa)


Figure 5: EU-27 components of general government total revenue, billion euro
Source: Eurostat (gov_10q_ggnfa)


Figure 6: EU-27 components of general government total expenditure, billion euro, 2019Q4
Source: Eurostat (gov_10q_ggnfa)

Quarterly financial accounts for general government

Financial transactions - assets, liabilities and net financial transactions

The government financial accounts notably allow for an analysis of how governments finance their deficits or use their surpluses to either reduce their liabilities or acquire financial assets. They include data on financial transactions (net acquisition of financial assets and the net incurrence of financial liabilities) and balance sheet items (stocks of financial assets and liabilities outstanding at the end of each quarter) for general government and its sub-sectors. Variations in stocks are explained both by the transactions and by other factors such as holding gains and losses and other changes in volume. The aim of this section is to present the main characteristics of the general government financial accounts.

From the fourth quarter of 2008 onwards, the fluctuation of transactions in both assets and liabilities has increased sharply due to the economic and financial crisis. The gap between the volume of transactions in assets and liabilities has widened sharply, giving rise to increasing negative figures in net financial transactions (B.9f), which is interpreted as the government deficit/ surplus derived from financial accounts. Contrary to the government deficit/ surplus, net financial transactions are not seasonally adjusted. The increase and peaks in transactions in financial assets can be explained by governments having acquired assets to support financial institutions. The worsening economic climate also led to an increase in government total expenditure, while revenue decreased. For these reasons, governments also needed to incur liabilities.

Net financial transactions continued to deteriorate steadily from the second quarter of 2008 to the first quarter of 2010 for the EA-19 and the EU-27. From the first quarter of 2010 onwards an improvement is visible.

Figure 7: EU-27 net financial transactions, transactions in assets and liabilities, billion euro
Source: Eurostat (gov_10q_ggfa)


Figure 8: EA-19 net financial transactions, transactions in assets and liabilities, billion euro
Source: Eurostat (gov_10q_ggfa)

Government financial balance sheet

At the level of the EU-27 and EA-19, a significant rise in the stocks of liabilities has been observed since the fourth quarter of 2008, together with an increase in assets which was less pronounced. The rise in the stock of liabilities is mainly due to debt securities, which are by far the most important financial instrument on the government liability side. The stock of loan liabilities also increased substantially. The remainder of financial liabilities is mainly 'other accounts, payable'.

Figure 9: EU-27 net financial worth, stock of assets and liabilities, billion euro and % of GDP
Source: Eurostat (gov_10q_ggfa)


Figure 10: EA-19 net financial worth, stock of assets and liabilities, billion euro and % of GDP
Source: Eurostat (gov_10q_ggfa)

The stock of financial assets is mainly held in equity and investment fund shares (for example public corporations), with other accounts receivable, currency and deposits (these exhibit a strong seasonality), loans and debt securities also making up important parts. Loans increased substantially during the financial crisis.

Figure 11: EU-27 stock of assets by financial instrument, % of GDP
Source: Eurostat (gov_10q_ggfa)


Figure 12: EA-19 stock of assets by financial instrument, % of GDP
Source: Eurostat (gov_10q_ggfa)

The difference between the stock of financial assets and liabilities is the balancing item net financial worth.

Figure 13: Evolution of net financial worth by country, % of GDP
Source: Eurostat (gov_10q_ggfa)

Compared with the fourth quarter of 2018, the fourth quarter of 2019 shows a slight deterioration of the balancing item net financial worth for the EU-27. In the fourth quarter of 2019, net financial worth stood at -55.9 % of GDP, while in the fourth quarter of 2018, net financial worth stood at -55.8 % of GDP. The stock of financial assets stood at 41.1 % of GDP (up from 40.5 % of GDP in the fourth quarter of 2018), while the stock of liabilities increased from 96.3 % of GDP to 97.0 % of GDP. The stock of financial assets and liabilities changes due to financial transactions as well to 'other flows' such as revaluations. In recent quarters, government debt securities (liabilities) have notably increased in value in many EU countries, driven by declining interest rates. This affects negatively net financial worth. In the latest quarter of 2019, however, a decrease in the value of debt securities positively impacted net financial worth.

Figure 14: EU-27 stock of liabilities by financial instrument, % of GDP
Source: Eurostat (gov_10q_ggfa)


Figure 15: EA-19 stock of liabilities by financial instrument, % of GDP
Source: Eurostat (gov_10q_ggfa)

Quarterly gross debt for general government

At the end of the fourth quarter of 2019, the government debt to GDP ratio in the euro area (EA-19) stood at 84.1 %, compared with 85.9 % at the end of the third quarter of 2019. In the EU-27, the ratio decreased from 79.3 % to 77.8 %.

Compared with the fourth quarter of 2018, the government debt to GDP ratio fell in both the euro area (from 85.8 % to 84.1 %) and the EU-27 (from 79.6 % to 77.8 %).

The highest ratios of government debt to GDP at the end of the fourth quarter of 2019 were recorded in Greece (176.6%), Italy (134.8%) and Portugal (117.7%) and the lowest in Estonia (8.4%), Bulgaria (20.4%) and Luxembourg (22.1%).

Compared with the third quarter of 2019, three Member States registered an increase in their debt to GDP ratio at the end of the fourth quarter of 2019 and twenty-four a decrease. The increases in the ratio were recorded in Luxembourg (+2.0pp.), Lithuania (+0.6 pp.) and Romania (+0.1 pp.). The largest decreases were recorded in Ireland (-3.7 pp.), Belgium (-3.4 pp.), Portugal (-2.4 pp.), Italy and Cyprus (both -2.3 pp.), Spain, France and Slovenia (all -2.0 pp.).

Compared with the fourth quarter of 2018, four Member States registered an increase in their debt to GDP ratio at the end of the fourth quarter of 2019 and twenty-one a decrease while in France and Italy the ratio remained stable. The largest increases in the ratio were recorded in Lithuania (+2.4 pp.) and Luxembourg (+1.1 pp.) while the largest decreases were recorded in Cyprus (-5.1 pp.), Ireland (-4.8 pp.), Greece (-4.6 pp.), Portugal and Slovenia (both -4.3 pp.).

For Cyprus, the decrease of debt in the third quarter of 2019 is driven by the repayment of foreign sovereign loans.

The decrease of debt in Greece in the first quarter of 2015 is primarily due to the repayment of a loan from EFSF to the HFSF, representing unused funds for the recapitalisation of Greek financial institutions as well as repayments of loans granted by the IMF. The figures in the second quarter of 2016, and all quarters of 2018 are influenced by ESM disbursements. The decrease of debt in the fourth quarter of 2019 is due to the repayment of a loan to the IMF.

Figure 16: General government gross debt, % of GDP, 2019Q4
Source: Eurostat (gov_10q_ggdebt)


Figure 17: Change in general government gross debt, percentage points of GDP, 2019Q4 compared to the previous quarter
Source: Eurostat (gov_10q_ggdebt)


Figure 18: Change in general government gross debt, percentage points of GDP, 2019Q4 compared to the same quarter of the previous year
Source: Eurostat (gov_10q_ggdebt)

Evolution of deficit and debt

Figure 19 shows some of the most important links between the quarterly deficit and the quarterly debt for the euro area. While in general, government gross debt will increase in the presence of a government deficit, this is not necessarily the case in the short-term. It can be seen, that a strong co-movement of net acquisition of financial assets exists with the evolution of quarterly debt. Incurrence of liabilities not in the quarterly government debt (mainly 'other accounts, payable') plays a smaller role.

Figure 19: EA-19 evolution of general government deficit and debt, percentage of GDP
Source: Eurostat (gov_10q_ggdebt)

Since the fourth quarter of 2017, for the euro area, the link between the deficit and the gross debt is mainly explained by net acquisition of financial assets.

Data sources

For the following countries, the estimates are produced by the respective National Statistical Institute, which all follow the “ESS guidelines on seasonal adjustment”:

Belgium: The seasonally adjusted series are computed following an indirect approach. The components of the revenue and of the expenditure of the General Government are seasonally adjusted by means of "Tramo-Seats", taking into account the presence of possible outliers and calendar effects. The model of each component (>20) has been individually validated (no automatic modelling). The absence of residual seasonality after aggregation has been checked. The data are benchmarked on annual totals of the non-adjusted series. The annual benchmarking is computed on each component by means of a multiplicative Denton procedure.

Bulgaria: Tramo-Seats on Demetra +. Total expenditure: no trading days effects, no Easter effect, log-transformation, ARIMA model [(3,0,0)(0,1,1)], outliers: AO[2007-IV], TC[2008-IV], AO[2009-I]AO[2014-IV], LS[2016-I]. Total revenue: no trading days effects, no Easter effect, log-transformation, ARIMA model [(0,1,1)(0,1,1)], no outliers.

Czechia: Tramo-Seats on Demetra +. Total expenditure: No trading days effects, no Easter effect, ARIMA model [(0,1,1)(0,1,1)], outliers: AO[2003-I], AO[2003-III], AO[2012-IV], TC[2001-IV], LS [2016-I]. Total revenue: No trading days effects, no Easter effect, ARIMA model [(0,1,1)(0,1,1)], outliers: AO[2003-I].

Denmark: X12-ARIMA. Total expenditure: Log-transformation, no trading days effects, no Easter effect, ARIMA model [(1,1,0)(1,0,0)], outliers: AO[2005-IV], TC[2011-I]. Total revenue: Log-transformation, trading days effects, no Easter effect, ARIMA model [(0,1,0)(0,1,1)], outliers: TC[2009-II], AO[2008-II], TC[2009-II], LS[2015-I], [2004-I].

Germany: X-12-ARIMA. Total expenditure: Log-transformation, no trading day effects, ARIMA model [(0,1,1) (0,1,1)], outliers AO [1995-I, 1995-III, 2000-III, 2010-III]. Total revenue: Log-transformation, no trading day effects, ARIMA model [(0,1,0) (0,1,1)], no outliers. Estonia: Tramo-Seats on Demetra +. The seasonal adjustment of all time series is done with TRAMO/SEATS using JDemetra+ software. For TE and TR no calendar adjustment has been added as it does not have a notable impact on the results. According to ESS guidelines there is also no temporal consistency forced on the time series in order to provide a more purely seasonally adjusted time series for users.

France: Seasonally adjusted data is transmitted. Working day adjustment is also done when relevant. An indirect method is used. Seasonal adjustment is done using X-12-ARIMA. For more information, you can read INSEE's methodology (starting on page 21) at the following link (the document is available in both English and French): here. Please refer also to the explanatory comment above.

Latvia: Tramo-Seats on JDemetra +. Total expenditure: Log-transformation, ARIMA model [(0,1,1)(0,1,1)], 2 pre-specified outliers: LS[2006-IV], LS[2009-III]. Total revenue: Log-transformation, ARIMA model [(0,1,0)(0,1,1)], pre-specified outlier: AO[2006-IV]. Lithuania: Tramo-Seats on Demetra+. Total expenditure: Log-transformation, no Easter effect, ARIMA[(0,1,1)(0,1,1)], outlier AO[2011-IV]. Total revenue: Log-transpormation, no Easter effect, ARIMA[(0,1,1)(0,1,1)], no outliers.

Luxembourg: All series are seasonally and calendar adjusted with automatic outlier detection and correction. No benchmarking or other adjustments are made. The method used is non-parametric X13 RSA5c with the Luxembourgish calendar. The software used is JDemetra+ (v2.1.0).

Hungary: JDemetra+ TramoSeats method. Hungarian specific calendar is used. Working day, Easter and leap year effects are tested.

Malta: Total expenditure: Tramo-Seats on JDemetra+ 2.2.2, Series has been log-transformed, No trading days effects, No Easter effects, ARIMA model [(0,1,1)(0,1,0)], 2 pre-specified outliers: AO(IV-2003), TC (I-2008). Total revenue: Tramo-Seats on JDemetra+ 2.2.2, Series has been log-transformed, No trading days effects, No Easter effects, ARIMA model [(0,1,1)(0,1,0)], 1 pre-specified outlier: AO(III-2000), AO(IV-2000). The Netherlands: X13-ARIMA on JDemetra+. Total revenue: Log-transformation, no trading day effects, no Easter effect, ARIMA model [(1,0,1)(1,1,0)], outlier: LS [2009-I]. Total expenditure: Log-transformation, no trading day effects, no Easter effect, ARIMA model [(0,1,0)(0,1,1)], outlier: AO [2009-II].

Austria: Tramo-Seats on Demetra +. Total expenditure: Log-transformation, no trading days effects, no Easter effect, ARIMA model [(0,1,1)(0,1,1)], 5 pre-specified outliers: [2004-II], [2004-IV], [2009-IV], [2014-IV], [2015-III]. Total revenue: Log-transformation, no trading days effects, no Easter effect, ARIMA model [(0,0,0)(0,1,1)], 2 pre-specified outliers: LS[2016-I], LS[2009-II].

Poland: Tramo-Seats on JDemetra +. Direct method used. Concurrent adjustment for Q1 each year, current adjustment Q2, Q3, Q4 (model revised once a year). Calendar effects adjustment used. Working days with leap year effect (2 regressors) and Easter effect tested for each series - only significant effects used in final specification. Automatic identification of ARIMA models. Total expenditure: P.2 - log transformation; no calendar effect, ARIMA model [(0,1,1)(0,1,1)], AO(2010-III); P.5 - log transformation; no calendar effect, ARIMA model [(0,1,1)(0,1,1)], outliers: LS (2001-I); AO (2016-I); D.1 - log transformation; no calendar effect, ARIMA model [(0,1,1)(0,1,1)], outlier: AO(2013-IV); D.6M - log transformation; no calendar effect, ARIMA model [(0,1,1)(0,1,1)], outliers: AO(2007-IV); LS(2004-IV); D.4 - log transformation; no calendar effect, ARIMA model [(0,0,0)(0,1,1)], outliers: LS(2013-III), LS(2008-IV); P.29+D.3+… - log transformation, no calendar effect, ARIMA model [(0,1,1), (0,1,0)], outliers: TC[2004-I]; AO[2012-I]; Total revenue: D.2 - log transformation; no calendar effect, ARIMA model [(0,1,1)(0,1,0)], outliers:AO(2004-II), TC(2009-I); D.4 – no-log transformation; no calendar effect, ARIMA model [(0,0,0)(1,0,0)], outliers: TC(2007-III), TC(2012-II); D.5 - log transformation; no calendar effect, ARIMA model [(1,0,0)(0,1,0)], no outliers; D.61 - log transformation; no calendar effect, ARIMA model [(0,1,1)(0,1,1)], outliers: TC(2008-IV), AO(2007-IV), AO(2011-III); P.1+D.7+D9 - log transformation; no calendar effect, ARIMA model [(0,1,1)(0,1,1)], no outliers.

Portugal: X13-ARIMA on Demetra+. A manual pre-treatment is performed by identifying and deducting one-off measures. Additional pre-treatment is applied for outlier detection and correction. The seasonal adjustment is applied to total revenue, expenditure except compensation of employees and compensation of employees. Total revenue: Log-transformation, no trading day effects; no Easter effect; ARIMA model [(0,1,1)(0,1,1)]; outliers: AO[2003-IV], AO[2009-II], SO III [1999 – 2008] (user defined variable). Total expenditure (except compensation of employees): Log-transformation, no trading day effects; no Easter effect; ARIMA model [(1,0,1)(0,1,0)]; outliers: AO (IV-2002), LS (II-2012) Compensation of employees: Log-transformation, no trading day effects; no Easter effect; ARIMA model [(1,1,0)(0,1,1)]; outliers: TC (III-2005), LS (I-2011), LS (I-2012), TC (I-2013), AO (III-2014), SO II [2012 – 2013] (user defined variable), SO IV [2012 – 2016] (user defined variable).

Romania: Tramo-Seats on Demetra+. P.51g series was not log-transformed and the model used was automatic Arima model. Total expenditure was log transformed and the model used was automatic Arima model. Total revenues was log transformed and the model used was automatic Arima model. B.9 is derived indirectly by the difference between seasonally adjusted series of total revenue and total expenditure.

Slovenia: Tramo-Seats on JDemetra +. Total revenue: Log transformation, no trading days effects, no Easter effect, pre-specified outliers LS Q1/2009, AO Q1/2012, LS Q1/2017, ARIMA(0,1,1)(0,1,1). Total expenditure: Log transformation, no trading days effects, no Easter effect, pre-specified outliers AO 2012/Q2, AO Q4/2014, AO Q1/2013, AO Q4/2013, AO Q1/2001, TC Q1/2011, ARIMA(0,1,1)(0,1,1). Gross fixed capital formation: Log transformation, trading days effects (1 variable), holidays effect, no Easter effect, 6 pre-specified outliers LS Q1/2016, LS Q1/2015, AO Q2/2004, LS Q1/2011, TC Q1/2017, TC Q1/2005, 1 detected outlier: AO Q4/2019, ARIMA (0,1,0) (0,1,1). Final consumption expenditure (P3): Log transformation, no trading days effects, no Easter effect, 1 pre-specified outlier TC Q1/2007, 1 detected outlier AO Q3/2019, ARIMA (0,1,0) (0,1,1).

Slovakia: Tramo-Seats on JDemetra +. Total expenditure: Log-transformation, no trading days effects, no Easter effect, ARIMA model [(0,1,1)(0,1,1)], outliers: LS[2000-IV], AO[2015-IV], AO[2002-IV]. Total revenue: Log-transformation, no trading days effects, no Easter effect, ARIMA model [(0,1,1)(0,1,1)], outliers: LS[2001-III], AO[2015-IV].

Finland: The seasonally adjusted series are computed following an indirect approach. The components of the revenue and of the expenditure of the General Government are seasonally adjusted by Tramo-Seats / JDemetra+ 2.0.0, taking into account the presence of possible outliers and calendar effects. The data are benchmarked on annual totals of the non-adjusted series. The annual benchmarking is computed on each component by Denton procedure.

Sweden: Tramo-Seats on Demetra +. Total expenditure: Log-transformation, no trading days effects, no Easter effect, ARIMA model [(0,1,2)(0,1,1)], outlier AO[2010-IV], AO[1998-III]. Total revenue: Log-transformation, no trading days effects, no Easter effect, ARIMA model [(0,1,0)(0,1,1)], AO[2014-IV].

United Kingdom: Adjustment using X-11 algorithm in X-13ARIMA-SEATS. Net borrowing: log transformation, no trading day effects, no Easter effect, ARIMA model [(0,1,1)(0,1,1)], outliers: AO[2008Q3], AO[2012-II], seasonal moving average: 3x3, trend moving average: 5. Total expenditure: No trading day effects, no Easter effects, multiplicative, ARIMA model[(0,1,1)(0,1,1)], outliers: AO[2008Q3], seasonal moving average: 3x5, trend moving average: 5. Total revenue: no trading day effects, no Easter effects, additive, ARIMA model[(0,1,1)(0,1,1)], outliers: LS[2009Q1], AO[2012Q2], seasonal moving average: 3x5, trend moving average: 5. For the purpose of calculation the EU aggregates, B.9 is derived indirectly. Annualised seasonally adjusted data is benchmarked on the annualised non-adjusted data.

Switzerland: The data reported is trend-cycle data. A Denton-Cholette method is used to temporally disaggregate annual data. The quarterly data is extrapolated using smoothed indicators.

Please refer to the country notes on Eurostat's metadata (ESMS) for more important information at country level. Some important notes for recent quarters are replicated below.

France: In 2019Q1, non-seasonally adjusted data on taxes on income (D.51r) decreases strongly due to a change in seasonality. For this reason, the evolution of the seasonally adjusted data differs significantly. Such changes in seasonality are technically complicated to model, hence the seasonally and seasonally and calendar adjusted data for 2019Q1 should be interpreted with caution. The changes in seasonality are primarily due to a new system in the collection of personal income tax (introduction of advance payments and retention at source) and the early repayment of a tax credit in January, introduced in 2019.

Cyprus: The net lending / net borrowing for the third quarter of 2018 includes the impact from the restructuring of the Cyprus Cooperative Bank Ltd (CCB) - sale of the good parts of CCB and the subsequent integration of the remaining public financial defeasance structure into general government accounts.

Gross domestic product

Throughout this publication, gross domestic product (GDP) at current prices (nominal) is used, either using the non-seasonally adjusted or the seasonally and calendar adjusted forms as appropriate.

Context

Quarterly accounts of general government

Eurostat releases quarterly flow and stock data for the general government sector, using an integrated structure which combines the data from quarterly non-financial accounts for general government (QNFAGG), quarterly financial accounts for general government (QFAGG) and quarterly government debt (QGD). An integrated publication combining data from all three tables is released quarterly on the dedicated Government Finance Statistics (GFS) section of the Eurostat web site.

Data is transmitted according to the ESA2010 transmission programme for QFAGG and QDEBT. QNFAGG data is transmitted under gentlemen's agreement.

ESA2010

Eurostat publishes quarterly government finance figures based on the European System of Accounts 2010 (ESA 2010) methodology.

General government

QNFAGG and QFAGG and QDEBT statistics cover data for general government as defined in ESA2010, paragraph 2.111.

Seasonal adjustment of selected data series

Quarterly government finance statistics are reported to Eurostat in the form of non-seasonally adjusted (raw) figures. However, a certain number of the reported series contain seasonal patterns (explained by the link with the seasonality of economic activity and by the budgetary planning and accounting practices of national governments), which make it difficult to carry out a direct meaningful cross-country and time series analysis using non-adjusted data. The same is true for GDP, which reflects the seasonal pattern of all economic activities in the economy.

To overcome this difficulty and thus to gain a better understanding of trends in addition to the non-seasonally adjusted data, seasonally adjusted data is presented for the EU-27 and EA-19 in this article. The seasonal adjustment aims to remove the seasonality linked to this quarterly data.

It should be noted that annualised seasonally adjusted data is not in general equal to annualised non-adjusted data. When using annualised figures, it is more appropriate to use non-seasonally adjusted data. Using seasonally adjusted data is more appropriate when looking at quarter-on-quarter growth rates.

The seasonal adjustment for total revenue and total expenditure is done using an indirect procedure (at country level) using Tramo-Seats on Demetra+). Where available, National Statistical Institutes own estimates are used as input for the aggregates, which are supplied to Eurostat on a gentlemen's agreement basis. Some country level estimates as well as data for the EU aggregates are published on Eurobase. These estimates are supplemented by Eurostat's own estimates for those countries, which do not yet supply their own estimate. This data is labelled confidential and not published.

Net lending (+)/ net borrowing (-) is derived indirectly from the accounting identity: Net lending (+)/ net borrowing (-)= total revenue - total expenditure.

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Main tables

Annual government finance statistics (t_gov_10a)
Government deficit and debt (t_gov_10dd)
Quarterly government finance statistics (t_gov_10q)

Database

Annual government finance statistics (gov_10a)
Government deficit and debt (gov_10dd)
Quarterly government finance statistics (gov_10q)

Dedicated section