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• September 2011 Calendar
• 2011 Calendar On One Page

EU-28 and EA-19 quarterly net lending (+)/ net borrowing (-),% of GDP, seasonally adjusted dataSource: EurostatIn recent years, has significantly expanded the range of integrated quarterly data on available, providing a timely and increasingly high quality picture of the evolution of government finances in the. The data presented in this article reflect both non-financial and financial (quarterly non-financial and financial accounts for transactions and cover all European Union countries as well as Iceland, Norway and Switzerland.This article is based on data transmitted to Eurostat at the end of September 2019, which includes data coverage of the second quarter of 2019, and follow methodology. It is supplemented by non-financial seasonally adjusted data estimated provided on a voluntary basis by EU and countries' National Statistical Institutes. Eurostat regularly publishes seasonally adjusted and working day adjusted quarterly data on government revenue, expenditure and (+)/ (-), currently for twenty- two, Switzerland and the EU aggregates.In the second quarter of 2019, the seasonally adjusted general government deficit to GDP ratio stood at -0.7% in the euro area (EA-19), an increase compared with -0.6% in the first quarter of 2019.

In the EU-28, the deficit to GDP ratio stood at -0.9%, an increase compared with -0.8% in the previous quarter. Quarterly non-financial accounts for general governmentGovernment revenue and expenditureBoth total revenue and expenditure exhibit a clear seasonality. In order to interpret for the most recent quarters, seasonally adjusted data is presented in addition to the raw data transmitted by (see explanation below).In the second quarter of 2019, seasonally adjusted total government revenue in the euro area amounted to 46.2% of, this is equal to the first quarter of 2019. Total government expenditure in the euro area stood at 47.0% of GDP, an increase compared with 46.9% of GDP in the previous quarter.In the EU-28, total government revenue was 44.9% of GDP in the second quarter of 2019, this is the same as in the previous quarter. Total government expenditure in the EU-28 was 45.8% of GDP, compared with 45.6% in the previous quarter. Figure 3: EA-19 total revenue and total expenditure, seasonally adjusted and non-adjusted data,% of GDPSource: EurostatFrom 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 as well as the effects of renewed economic growth in the EU and the euro area (all seasonally adjusted).

Visible deteriorations in the second and fourth quarters of 2012, were caused by a series of one-off effects in several Member States. Notably, 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. Quarterly financial accounts for general governmentFinancial transactions - assets, liabilities and net financial transactionsThe 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. 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 fourth quarter of 2009 for EU-218.

From the first quarter of 2010 onwards an improvement is visible. Figure 8: EA-19 net financial transactions, transactions in assets and liabilities, billion euroSource: EurostatGovernment financial balance sheetAt the level of the EU-28 and EA-19, a significant rise in the stocks of liabilities has been observed since the third 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 13: Evolution of net financial worth by country,% of GDPSource: EurostatCompared with the second quarter of 2018, the second quarter of 2019 shows a marked deterioration of the balancing item net financial worth for the EU-28. In the second quarter of 2019, net financial worth stood at -61.6% of GDP, while in the second quarter of 2018, net financial worth stood at -61.0% of GDP. The stock of financial assets stood at 39.6% of GDP (up from 39.1% of GDP in the second quarter of 2018), while the stock of liabilities increased from 100.2% of GDP to 101.2% 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. Quarterly gross debt for general governmentAt the end of the second quarter of 2019, the government debt to GDP ratio in the euro area (EA-19) stood at 86.4%, compared with 86.5% at the end of the first quarter of 2019.

Evolution of deficit and debtFigure 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, 2019Q1, percentage of GDPSource: EurostatAt the level of the EU-28, the evolution of general government gross debt during 2016 is strongly influenced by the fluctuation of the British Pound Sterling against the euro.

The majority of the United Kingdom's debt is in national currency, which depreciated against the euro in the first three quarters of 2016 and appreciated in the fourth quarter. For first and second quarter of 2019, the evolution of the British Pound Sterling against the euro also influences strongly the evolution of the EU-28 general government gross debt.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 sourcesFor 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 (0,1,1)(0,1,1), outlier: AO2007-IV, TC2008-IV, AO2014-IV, LS2016-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: AO2003-I, AO2003-III, AO2012-IV, TC2001-IV. Total revenue: No trading days effects, no Easter effect, ARIMA model (1,1,0)(0,1,1), outliers: AO2003-I, TC2007-III, AO2008-III.Denmark: X12-ARIMA. Total expenditure: Log-transformation, no trading days effects, no Easter effect, ARIMA model (1,1,0)(1,0,0), outliers: AO2005-IV, TC2011-I. Total revenue: Log-transformation, trading days effects, no Easter effect, ARIMA model (0,1,0)(0,1,1), outliers: TC2009-II, AO2008-II, TC2009-II, LS2015-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. Saxon killing ground rapidshare full. 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 (the document is available in both English and French). 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), outliers: LS2006-IV, LS2009-III. Total revenue: Log-transformation, ARIMA model (0,1,0)(0,1,1), outlier: AO2006-IV.Lithuania: Tramo-Seats on Demetra+. Total expenditure: Log-transformation, no Easter effect, ARIMA(0,1,1)(0,1,1), outlier AO2011-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 (0,1,2)(0,1,1), 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), outliers: LS2016-I, LS2009-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.

ContextQuarterly accounts of general governmentEurostat 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 section of the Eurostat web site and on the dedicated Statistics Explained page.Data is transmitted according to the ESA2010 transmission programme for QFAGG and QDEBT. QNFAGG data is transmitted under gentlemen's agreement.ESA2010Eurostat publishes quarterly government finance figures based on the European System of Accounts 2010 (ESA 2010) methodology.General governmentQNFAGG and QFAGG and QDEBT statistics cover data for general government as defined in ESA2010, paragraph 2.111.Seasonal adjustment of selected data seriesQuarterly 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.

September 2011 Calendar

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-28 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+).

2011 Calendar On One Page

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.