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Document 52013SC0791

COMMISSION STAFF WORKING DOCUMENT STATISTICAL ANNEX Accompanying the document REPORT FROM THE COMMISSION TO THE EUROPEAN PARLIAMENT, THE COUNCIL, THE EUROPEAN CENTRAL BANK AND THE EUROPEAN ECONOMIC AND SOCIAL COMMITTEE Alert Mechanism Report 2014 (prepared in accordance with Articles 3 and 4 of Regulation (EU) No 1176/2011 on the prevention and correction of macroeconomic imbalances

/* SWD/2013/0791 final */

52013SC0791

COMMISSION STAFF WORKING DOCUMENT STATISTICAL ANNEX Accompanying the document REPORT FROM THE COMMISSION TO THE EUROPEAN PARLIAMENT, THE COUNCIL, THE EUROPEAN CENTRAL BANK AND THE EUROPEAN ECONOMIC AND SOCIAL COMMITTEE Alert Mechanism Report 2014 (prepared in accordance with Articles 3 and 4 of Regulation (EU) No 1176/2011 on the prevention and correction of macroeconomic imbalances /* SWD/2013/0791 final */


Introduction

European Union economic policy frameworks rely more than ever on timely and high quality socio-economic statistics. The rapid development of EU economic governance along with the growing statistical needs represent a major challenge for the European Statistical System.

In the field of Macroeconomic Imbalances Procedure, the ESS has taken a number of initiatives to enhance the standards and methods used for the compilation of underlying data as well as to strengthen the quality assurance framework. Significant progress has been achieved since the publication of the Alert Report Mechanism 2013. The results of several improvement actions have been incorporated in the statistics presented in the 121 tables grouped by headline and auxiliary indicators in this Statistical Annex.

The scoreboard data are primarily derived from data compiled by the European Statistical System (ESS) and the European System of Central Banks (ESCB).

The MIP Scoreboard consists of eleven headline indicators covering the major sources of macroeconomic imbalances:

- 3 year backward moving average of the current account balance in % of GDP

- net international investment position in % of GDP

- 3 years percentage change of the real effective exchange rate (42 industrial countries) based on HICP/CPI deflators

- 5 years percentage change of export market share (share of world exports)

- 3 years percentage change in nominal unit labour cost.

- year-on-year change in deflated[1] house prices

- private sector credit flow in % of GDP

- private sector debt in % of GDP

- general government sector debt in % of GDP

- 3 year backward moving average of unemployment rate

- year-on-year change of total financial sector liabilities

Supplementing the headline indicators, a list of 28 auxiliary indicators provides additional information on aspects linked to the general macroeconomic situation, nominal and real convergence inside and outside the EU and the euro area, and detailed data on the external liabilities, including foreign direct investment and net external debt. They also enhance the information base for understanding potential imbalances, as well as the adjustment capacity of the economy. Additionally, to allow a better understanding of the risks and to help identifying relevant policy measures, eight additional indicators on social issues have been added to the list of auxiliary indicators used for the economic reading. The auxiliary indicators developments are presented in chapters 2 and 5.

The cut-off date for the data in this document was 1 November 2013.

Changes to the statistical methodology and underlying data

In order to ensure that the scoreboard can adapt to future macroeconomic challenges and can profit from better statistical information, the composition of the scoreboard indicators may evolve over time.

Compared to the AMR 2013, the definition of three headline indicators has been modified to take account of better statistical information: the real effective exchange rate, private sector credit flow and private sector debt. The changes are discussed in detail below. Furthermore, the underlying data used for the headline indicator on house price developments is now based on a harmonised methodology following the adoption of Regulation (EC) 93/2013.

External imbalances

As regards Balance of Payments statistics, the most significant improvements come from the bilateral exchange between Member States of data on Foreign Direct Investment (FDI) positions and transactions. This aims to harmonise and improve statistics on FDI, and it is particularly important from the perspective of data analysis and quality assessment of the headline indicator on net international investment position.

Concerning Real Effective Exchange Rate (REER) up until the current MIP exercise, the indicator was computed against a panel of 35[2] other trading partners. By adding Croatia, as a new Member State, to the basket and improving the coverage to include China, Brazil, Russia, South Korea and Hong-Kong, the number of trading partners of each Member State has been extended to 41. This allows better accounting for the increasing role of some emerging economies when measuring competitiveness. The Commission will consider extending the basket of trading partners further when data of sufficient quality for additional emerging countries become available.

Internal imbalances

Among the statistical gaps highlighted by the financial and economic crisis, real estate price statistics was considered one of the areas to be urgently developed. Particular attention has been devoted to developing internationally comparable House Price Indices (HPI). At the beginning of 2013, with the entering into force of the reference legislation[3], the monitoring of changes in house prices is now based on data regularly compiled by Member States and transmitted to Eurostat.

Compared with other indicators, HPIs have shorter historical coverage, for some Member States the series only start in 2009. The European Commission, ECB, OECD, and BIS continue to work on backward data calculation aiming at increasing the length of back series by using all available data. To strengthen the knowledge base of the use and compilation of HPIs globally, Eurostat has been leading the drafting of an international handbook on residential property price indices. The handbook was officially released in April 2013. Finally to enhance the relevance of HPI and its economic reading, Eurostat works on the metadata on housing statistics which will be published by the end of 2013.

In the field of government finance statistics Eurostat continues to implement its strengthened verification procedures. An inventory of Excessive Deficit Procedure (EDP) processes, which includes a public commitment on the quality of EDP statistics, was made public in January 2013. Eurostat checks the application of general methodological rules and its methodological decisions related to the general government sector debt by analysing the data reported by Member States in the EDP notification tables, questionnaire related to the notification tables, supplementary tables on financial crisis, as well as through discussions with national authorities during EDP standard dialogue visits. In addition to that, Member States may ask Eurostat to provide formal advice on specific cases.

The debt of the non-financial private sectors (non-financial corporations, households and non-profit institutions serving households) can be measured in consolidated or non-consolidated terms. Consolidated debt corresponds, by and large, to the amount of funds that the sector receives from other sectors. Non-consolidated debt gives the total gross indebtedness of the sector, including debts between two entities of the same sector. The issue of consolidation is highly relevant in the non-financial corporations (NFC) sector whereas its effect in the household sector is negligible.

From an economic point of view, there is a fundamental difference between intra-group loans and loans contracted by two independent companies. Intra-groups loans do not constitute an imbalance, they merely reflect institutional, corporate financing, accounting and tax practices. In contrast, loans between two independent companies could signal deficiencies in the financial intermediation role of the financial sector, generating fragility in the NFC sector.

Since consolidated data of non-financial corporations were not available for all Member States at the time of the first release of the MIP Scoreboard, non-consolidated data were used, although consolidated data were considered preferable. To address this issue and to develop further practical guidelines on statistical consolidation of data, a technical Task Force was set up. The result of the significant efforts by Eurostat, statistical institutes and central banks in Member States, is that all Member States now produce consolidated financial data.

Based on conceptual (economic) and statistical considerations, the use of consolidated data is both analytically sounder and statistically more robust. Non-consolidated data will, nevertheless, continue to be used as an additional indicator for the economic reading of the scoreboard.

At the same time, it was proposed to exclude financial derivatives from the definition of the private sector debt since it would allow for a clearer economic interpretation of scoreboard indicator. Private sector debt in the scoreboard has been defined as the sum of loans and securities other than shares, including financial derivatives. Removing derivatives from the definition improves the comparability of data among the EU Member States. In fact, the aim of this indicator is to capture liabilities contracted as funding sources, while derivatives are mostly used for either (short-term) hedging or speculation. This item accounts for a very small part of the private sector liabilities, and their exclusion would not have any practical consequence of the MIP implementation.

Quality issues relating to the MIP indicators

Overall, most of the MIP relevant data are produced in statistical frameworks or domains (National Accounts, Balance of Payments, Labour Market Statistics, etc.) with a long track record and well-known quality profiles. As regards the interpretation of the MIP indicators and the related data, it should be noted that

· some issues related to the house price indicator are flagged in the relevant tables;

· in the area of Financial Accounts and Balance of Payments, new and better information frequently leads to revisions of historical data. This concerns especially the stock indicators (private debt and net international investment positions),

· some historical data for Croatia may not be fully comparable with data from other Member States;

Improving the quality framework

In order to ensure that the political decision process and the implementation monitoring are successful, it is essential that the statistical information is relevant and fit for the purpose. For that reason, the scoreboard indicators are regularly reviewed and the underlying statistical methodology is constantly improved.

To enhance the quality framework for the MIP statistics and in response to the request of the ECOFIN Councils of 8 November 2011 and 13 November 2012, the Commission adopted on 7 June 2013 a proposal for a Regulation of the European Parliament and of the Council on the provision and quality of statistics for the macroeconomic imbalances procedure (COM(2013) 342 final). This draft Regulation aims to ensure the statistical monitoring of MIP relevant data by Eurostat as well as issues linked to compilation and transmission of data and metadata by Member States, monitoring of data quality by Eurostat, reporting/communication to the different stakeholders and to the European Parliament and the Council.

The draft Regulation itself sets out the general principles of the statistical quality monitoring system. At the same time, Eurostat is developing in detail the ways in which the statistical monitoring framework could be applied (quality assessment, inventories of data sources and methods, quality reports by Member States, missions to Member States, specific controls, actors involved, assessment reports, etc.). This will be based on a thorough analysis of existing regulations and frameworks. In particular, a systematic assessment of procedures, inventories of sources and methods, statistical quality reports, and, not least, the data provided will identify the statistical domains for which the adherence with the principles laid down in the  European Statistics Code of Practice need further examination. At the same time, the analysis should identify means to streamline requirements and practices, to avoid duplications, enhance synergies, and limit burden.

Ongoing improvement of the underlying statistical information

In parallel with the discussions on a general quality framework, the statistical systems (ESS and ESCB) continue with regular assessment of quality issues for the MIP relevant data and continuous improvement of methodology and basic information.

For example, the inclusion of Census-2011 results is an important source of improved population estimates and it will potentially lead to revisions for unemployment data in a number of Member States. The Census results might also affect the indicator on Unit Labour Cost if the corresponding employment figures are changed.

The general frameworks for the compilation of MIP relevant statistics will undergo changes in 2014 with the introduction of new manuals for national accounts (ESA 2010 replacing ESA 95) and balance of payments (BPM6 replacing BPM5). This is the results of several years of work by statisticians. It will also open up for new and relevant macroeconomic data available at the end of 2014. Most Member States will at the same time update their production systems for national accounts and balance of payment. The combined effect of methodological changes and improved production systems may lead to further revisions of data towards the end of 2014.

Table of contents || || || || || ||

|| || || || || ||

Chapter 1: Tables by year - Headline indicators || || || || || ||

|| || || || || ||

Table 1.1:  MIP scoreboard 2012 || || || || || || 10

Table 1.2:  MIP scoreboard 2011 || || || || || || 11

Table 1.3:  MIP scoreboard 2010 || || || || || || 12

Table 1.4:  MIP scoreboard 2009 || || || || || || 13

Table 1.5:  MIP scoreboard 2008 || || || || || || 14

Table 1.6:  MIP scoreboard 2007 || || || || || || 15

Table 1.7:  MIP scoreboard 2006 || || || || || || 16

Table 1.8:  MIP scoreboard 2005 || || || || || || 17

Table 1.9:  MIP scoreboard 2004 || || || || || || 18

Table 1.10: MIP scoreboard 2003 || || || || || || 19

|| || || || || ||

Chapter 2: Tables by year - Auxiliary indicators used in the economic reading of the MIP scoreboard

|| || || || || ||

Table 2.1:  Auxiliary indicators 2012 || || || || || || 20

Table 2.1 (continued):  Auxiliary indicators 2012 || || || || || || 21

Table 2.2:  Auxiliary indicators 2011 || || || || || || 22

Table 2.2 (continued):  Auxiliary indicators 2011 || || || || || || 23

Table 2.3:  Auxiliary indicators 2010 || || || || || || 24

Table 2.3 (continued):  Auxiliary indicators 2010 || || || || || || 25

Table 2.4:  Auxiliary indicators 2009 || || || || || || 26

Table 2.4 (continued):  Auxiliary indicators 2009  || || || || || 27

Table 2.5:  Auxiliary indicators 2008 || || || || || || 28

Table 2.5 (continued):  Auxiliary indicators, 2008 || || || || || 29

Table 2.6:  Auxiliary indicators 2007 || || || || || || 30

Table 2.6 (continued):  Auxiliary indicators 2007  || || || || || 31

Table 2.7:  Auxiliary indicators 2006 || || || || || || 32

Table 2.7 (continued):  Auxiliary indicators  2006 || || || || || 33

Table 2.8:  Auxiliary indicators  2005 || || || || || || 34

Table 2.8 (continued):  Auxiliary indicators 2005 || || || || || || 35

Table 2.9:  Auxiliary indicators  2004 || || || || || || 36

Table 2.9 (continued):  Auxiliary indicators  2004  || || || || || 37

Table 2.10:  Auxiliary indicators 2003 || || || || || || 38

Table 2.10 (continued):  Auxiliary indicators 2003  || || || || || 39

|| || || || || ||

Chapter 3: Tables by indicator || || || || || ||

|| || || || || ||

Table 3.1:  3 year average of Current Account Balance as % of GDP || || || || 40

Table 3.2:  Current Account Balance as % of GDP (BoP data) || || || || 41

Table 3.3:  Net International Investment Position as % of GDP || || || || 42

Table 3.4:  % change (3 years) of Real Effective Exchange Rate (42 IC) with HIPC deflators || 43

Table 3.5:  % y-o-y change in Real Effective Exchange Rate (42 IC) with HIPC deflators || || 44

Table 3.6:  % change (5 years) in Export Market Shares || || || || || 45

Table 3.7:  % y-o-y change in Export Market Shares || || || || || 46

Table 3.8:  % change (3 years) in Nominal ULC || || || || || || 47

Table 3.9:  % y-o-y change in Nominal ULC || || || || || || 48

Table 3.10:  % y-o-y change in Deflated House Prices || || || || || 49

Table 3.11:  Private Sector Credit Flow as % of GDP – CO || || || || 50

Table 3.12:  Private Sector Debt as % of GDP - CO || || || || || 51

Table 3.13:  General Government sector Debt as % of GDP || || || || 52

Table 3.14:  3 years average of Unemployment Rate || || || || || 53

Table 3.15:  Unemployment Rate || || || || || || 54

Table 3.16:  % y-o-y change in Total Financial Sector Liabilities || || || || 55

Table 3.17:  Total Financial Sector Liabilities - millions, national currency || || || 56

Table 3.18:  % y-o-y change in real GDP || || || || || || 57

Table 3.19:  Gross Fixed Capital Formation as % of GDP || || || || || 58

Table 3.20:  Gross Domestic Expenditure on R&D as % of GDP || || || || 59

Table 3.21:  Net Lending / Borrowing as % of GDP, BoP data || || || || 60

Table 3.22:  Net External Debt as % of GDP || || || || || || 61

Table 3.23:  FDI Inflows as % of GDP || || || || || || 62

Table 3.24:  Inward FDI Stocks as % of GDP || || || || || || 63

Table 3.25:  Net Trade Balance of Energy Products as % of GDP || || || || 64

Table 3.26:  % change (3 years) in REER vs. EA || || || || || 65

Table 3.27:  % change (5 years) in Terms of Trade || || || || || 66

Table 3.28:  % change (5 years) Export Performance vs. Advanced Economies || || || 67

Table 3.29:  % y-o-y change in Export Market Shares, goods and services,  volume || || 68

Table 3.30:  % y-o-y change in Labour Productivity || || || || || 69

Table 3.31:  % change (10 years) in Nominal ULC || || || || || 70

Table 3.32:  % change (10 years) in ULC performance relative to the EA || || || 71

Table 3.33:  % change (3 years) in Nominal House Prices || || || || || 72

Table 3.34:  Residential Construction as % of GDP || || || || || 73

Table 3.35:  Private Sector Debt as % of GDP, NCO || || || || || 74

Table 3.36:  Financial Sector Leverage (debt to equity in %) || || || || 75

Table 3.37:  % y-o-y change in Employment || || || || || || 76

Table 3.38:  Activity Rate (15-64 years) || || || || || || 77

Table 3.39:  Long-term Unemployment Rate (% of active population) || || || || 78

Table 3.40:  Youth Unemployment Rate (% of active population in the same age group) || || 79

Table 3.41:  Young People not in Employment, Education or Training (% of total population) || || 80

Table 3.42:  People At-risk of Poverty or Social Exclusion (% of total population) || || || 81

Table 3.43:  At-risk of Poverty Rate (% of total population) || || || || || 82

Table 3.44:  Severe Material Deprivation  (% of total population) || || || || 83

Table 3.45:  Persons Living in Households with Very Low Work Intensity (% of total population) || 84

|| || || || || ||

Chapter 4: Tables by Member States - Headline indicators || || || ||

|| || || || || ||

Table 4.1:  The MIP scoreboard for Belgium || || || || || || 85

Table 4.2:  The MIP scoreboard for Bulgaria || || || || || || 86

Table 4.3:  The MIP scoreboard for the Czech Republic || || || || || 87

Table 4.4:  The MIP scoreboard for Denmark || || || || || || 88

Table 4.5:  The MIP scoreboard for Germany || || || || || || 89

Table 4.6:   The MIP scoreboard for Estonia || || || || || || 90

Table 4.7:   The MIP scoreboard for Ireland || || || || || || 91

Table 4.8:  The MIP scoreboard for Greece || || || || || || 92

Table 4.9:   The MIP scoreboard for Spain || || || || || || 93

Table 4.10:  The MIP scoreboard for France || || || || || || 94

Table 4.11:  The MIP scoreboard for Croatia || || || || || || 95

Table 4.12:   The MIP scoreboard for Italy || || || || || || 96

Table 4.13:   The MIP scoreboard for Cyprus || || || || || || 97

Table 4.14:   The MIP scoreboard for Latvia || || || || || || 98

Table 4.15:   The MIP scoreboard for Lithuania || || || || || || 99

Table 4.16:   The MIP scoreboard for Luxembourg || || || || || 100

Table 4.17:   The MIP scoreboard for Hungary || || || || || || 101

Table 4.18:   The MIP scoreboard for Malta || || || || || || 102

Table 4.19:   The MIP scoreboard for the Netherlands || || || || || 103

Table 4.20:  The MIP scoreboard for Austria || || || || || || 104

Table 4.21:  The MIP scoreboard for Poland || || || || || || 105

Table 4.22:  The MIP scoreboard for Portugal || || || || || || 106

Table 4.23:   The MIP scoreboard for Romania || || || || || || 107

Table 4.24:   The MIP scoreboard for Slovenia || || || || || || 108

Table 4.25:   The MIP scoreboard for Slovakia || || || || || || 109

Table 4.26:  The MIP scoreboard for Finland || || || || || || 110

Table 4.27:  The MIP scoreboard for Sweden || || || || || || 111

Table 4.28:  The MIP scoreboard for the United Kingdom || || || || || 112

|| || || || || ||

Chapter 5: Tables by Member States - Auxiliary indicators used in the economic reading of the MIP scoreboard

|| || || || || ||

Table 5.1:  Auxiliary indicators for Belgium || || || || || || 113

Table 5.1 (continued):  Auxiliary indicators for Belgium || || || || || 114

Table 5.2:  Auxiliary indicators for Bulgaria || || || || || || 115

Table 5.2 (continued):  Auxiliary indicators for Bulgaria || || || || || 116

Table 5.3:  Auxiliary indicators for Czech Republic || || || || || 117

Table 5.3 (continued):  Auxiliary indicators for Czech Republic || || || || 118

Table 5.4:  Auxiliary indicators for Denmark || || || || || || 119

Table 5.4 (continued):  Additional indicators for Denmark || || || || || 120

Table 5.5:  Auxiliary indicators for Germany || || || || || || 121

Table 5.5 (continued):  Auxiliary indicators for Germany || || || || || 122

Table 5.6:  Auxiliary indicators for Estonia || || || || || || 123

Table 5.6 (continued):  Auxiliary indicators for Estonia || || || || || 124

Table 5.7:  Auxiliary l indicators for Ireland || || || || || || 125

Table 5.7 (continued):  Auxiliary l indicators for Ireland || || || || || 126

Table 5.8:  Auxiliary indicators for Greece || || || || || || 127

Table 5.8 (continued):  Auxiliary indicators for Greece || || || || || 128

Table 5.9:  Auxiliary indicators for Spain || || || || || || 129

Table 5.9 (continued):  Auxiliary indicators for Spain || || || || || 130

Table 5.10:  Auxiliary indicators for France || || || || || || 131

Table 5.10 (continued):  Auxiliary indicators for France || || || || || 132

Table 5.11:  Auxiliary indicators for Croatia || || || || || || 133

Table 5.11 (continued):  Auxiliary indicators for Croatia || || || || || 134

Table 5.12:  Auxiliary indicators for Italy || || || || || || 135

Table 5.12 (continued):  Auxiliary indicators for Italy || || || || || 136

Table 5.13:  Auxiliary indicators for Cyprus || || || || || || 137

Table 5.13 (continued):  Auxiliary indicators for Cyprus || || || || || 138

Table 5.14:  Auxiliary indicators for Latvia || || || || || || 139

Table 5.14 (continued):  Auxiliary indicators for Latvia || || || || || 140

Table 5.15:  Auxiliary indicators for Lithuania || || || || || || 141

Table 5.15 (continued):  Auxiliary indicators for Lithuania || || || || || 142

Table 5.16:  Auxiliary indicators for Luxembourg || || || || || || 143

Table 5.16 (continued):  Auxiliary indicators for Luxembourg || || || || 144

Table 5.17:   Auxiliary indicators for Hungary || || || || || || 145

Table 5.17 (continued):  Auxiliary indicators for Hungary || || || || || 146

Table 5.18:  Auxiliary indicators for Malta || || || || || || 147

Table 5.18 (continued):  Auxiliary indicators for Malta || || || || || 148

Table 5.19:   Auxiliary indicators for Netherlands || || || || || 149

Table 5.19 (continued):  Auxiliary indicators for Netherlands || || || || 150

Table 5.20:  Auxiliary indicators for Austria || || || || || || 151

Table 5.20 (continued):  Auxiliary indicators for Austria || || || || || 152

Table 5.21:  Auxiliary indicators for Poland || || || || || || 153

Table 5.21 (continued):  Auxiliary indicators for Poland || || || || || 154

Table 5.22:  Auxiliary indicators for Portugal || || || || || || 155

Table 5.22 (continued):  Auxiliary indicators for Portugal || || || || || 156

Table 5.23:  Auxiliary indicators for Romania || || || || || || 157

Table 5.23 (continued):  Auxiliary indicators for Romania || || || || || 158

Table 5.24:  Auxiliary indicators for Slovenia || || || || || || 159

Table 5.24 (continued):  Auxiliary indicators for Finland || || || || || 160

Table 5.25:  Auxiliary indicators for Slovakia || || || || || || 161

Table 5.25 (continued):  Auxiliary indicators for Slovenia || || || || || 162

Table 5.26:  Auxiliary indicators for Finland || || || || || || 163

Table 5.26 (continued):  Auxiliary indicators for Slovakia || || || || || 164

Table 5.27:  Auxiliary indicators for Sweden || || || || || || 165

Table 5.27 (continued):  Auxiliary indicators for Sweden || || || || || 166

Table 5.28:  Auxiliary indicators for United Kingdom || || || || || 167

Table 5.28 (continued):  Auxiliary indicators for United Kingdom || || || || 168

           

[1] Final consumption expenditure of households and non-profit institutions serving households deflator

[2] EU27 countries plus Australia, Canada, United States, Japan, Norway, New Zealand, Mexico, Switzerland, and Turkey

[3] Commission Regulation (EU) 93/2013 as regards establishing owner-occupied housing price indices

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