COMMISSION STAFF WORKING DOCUMENT REFINING THE MIP SCOREBOARD Technical Changes to the Scoreboard and Auxiliary Indicators 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)
Date: 2013-11-13
Institutions: European Commission
Subjects: budgetary equilibrium, economic disparity, economic indicator, macroeconomics













EUR-Lex - 52013SC0790 - EN











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52013SC0790

COMMISSION STAFF WORKING DOCUMENT REFINING THE MIP SCOREBOARD Technical Changes to the Scoreboard and Auxiliary Indicators 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/2013/0790 final */










1.         
Background and motivation

The Macroeconomic
Imbalance Procedure (MIP) was established in December 2011 and was implemented
for the first time in 2012[1].
It aims at detecting, preventing and correcting macroeconomic imbalances that
would jeopardise the functioning of the EU and euro area economies. Through a
number of steps, the MIP should identify trends which could lead to 'booms and
busts' and help in deciding the appropriate policy reactions to mitigate and
manage these risks.
Every year the
Commission adopts the Alert Mechanism Report (AMR), which is the initial
screening device and the first step of the procedure, whereby the Commission
identifies Member States warranting detailed scrutiny. A crucial tool in the
elaboration of the AMR is the MIP scoreboard - a set of eleven early warning
indicators intended to screen internal and external macroeconomic imbalances in
the Member States. The scoreboard acts as a first filter in a broader process
seeking to disentangle the existence and seriousness of macroeconomic
imbalances in the Member States. In this process, the scoreboard is used in
combination with additional indicators and all available information to ensure
a non-mechanical interpretation based on sound economic judgement. Throughout
2011-12, work on defining the scoreboard indicators and thresholds was led by
the Commission[2].
Comments from the European Parliament[3]
and the Council[4]
were taken into account. The Commission also benefited from the expertise and
input of the EPC (and its working group LIME), and views by the ESRB. The
scoreboard was completed in autumn 2012, in time for the second AMR, when the
indicator on the financial sector liabilities was added[5].
By focusing attention on
observed and potential risks of imbalances that could significantly impede the
proper functioning of the economy of a Member States, the euro area or the EU,
the  scoreboard has been successfully applied to identify the Member States for
which more in-depth analysis appears warranted. However, it is now possible to draw
on the experience of two rounds of implementation of the MIP and application of
the alert mechanism making, and to consider a number of adjustments.
In line with the MIP
legislation, in 2014 there will be a more complete evaluation of the first
three years of implementing the MIP[6].
In the context of amendments expected for 2014 it is also relevant to emphasize
that new statistical standards will become applicable with the entry into force
of ESA 2010[7],
as well as of the latest IMF balance of payments (BOP) manual[8].
At this point in time
though, while maintaining the scoreboard stable and simple, only adjustments to
the scoreboard that will not constitute an entire overhaul and that can be
implemented easily and quickly already for the AMR of the autumn 2013 are
considered. To this end, the present note looks at a number of changes that
could be considered within such a mandate: 
·      Better data available for existing indicators;
·      Improvements to the data transformations related to certain
indicators;
·      Updating of thresholds necessary as a consequence of the above two
changes[9];
·      Issues that could be considered after a comparison of the statistics
and indicators used in the MIP scoreboard and ESRB dashboard[10].
Beyond
these issues related to the scoreboard proper, the note also discusses changes
to some of the auxiliary indicators that contribute to complement and qualify
the reading of the scoreboard, as well as some presentational issues that could
improve the transparency and communication qualities of the scoreboard. 
Furthermore, a few
variables have been identified in the Commission Communication 'Strengthening
the Social Dimension of the Economic and Monetary Union'[11], to be added
to the auxiliary indicators used for the economic reading of the MIP
scoreboard. This would allow a better understanding of the social dimension of
risks implied by imbalances, including social developments during the
adjustment. Such improved knowledge would ultimately help to identify policy
measures to correct imbalances, while minimising the social consequences of the
latter. These indicators are not further discussed in this technical note. 
The remainder of this
note reviews in detail the suggested adjustments to scoreboard indicators.
Section 2 discusses suggested changes for the headline scoreboard indicators.
Section 3 presents the changes proposed for the auxiliary indicators used for
the economic reading of the scoreboard. Finally, Section 4 deals with some
presentational aspects.

2.                      
Adjustments to the MIP Scoreboard Indicators 

This section presents
and discusses adjustments that could be considered for a number of the
scoreboard indicators, namely the real effective exchange rate, the private
sector debt and private sector credit flows. It also raises issues on the
indicators on export market shares and house prices.

2.1.                
Real Effective Exchange Rate (REER) based on
harmonised index of consumer prices

The REER indicator has
been based on a harmonised index of consumer prices relative to a panel of the
35 most important trading partners. Among the EU trading partners, some
emergent countries have not been taken into account so far, namely, China,
Brazil, Russia, South Korea and Hong-Kong. Moreover, Croatia, as new EU member
will also be added to the computations. The use of 35 partners only, rather
than a wider set of trading partners, was at the time of the development of the
initial scoreboard related to the availability of data. Having
overcome these data issues, the number of trading partners of each Member State
can now be extended to 41[12]. This
reflects better the increasing role of some emerging economies[13]. 
This change implies that
the indicator will now take into account about 76 percent of the world exports
instead of only 58 percent with the current panel (Figure 1). This extension of
the basket of trade competitors would especially matter for Member States
having important trade links with these additional emergent countries. For
instance, in 2011, exports to China account for 5, 4 and 3 percent of the
exports of Germany, Finland and France respectively, while Russia amounts to 9,
11 and 17 percent of the exports of Finland, Estonia and Lithuania
respectively. Brazil accounts for 2½ percent of the exports of Portugal.
 Figure 1. Coverage of World Exports 
 Source: Eurostat 
Given the extension in
the number of trading partners, and to ensure consistency, there is a need to
recalculate the thresholds. However, using the same statistical approach and
the period (1995-2007), the panel of trading partners would not impact the
level of the rounded thresholds[14].
 Definition || Previously || Percentage change over three years of the real effective exchange rate (REER) based on consumer price index (HICP/CPI), relative to 35 other industrial countries (ICs)[15] 
 Suggested || Percentage change over three years of the real effective exchange rate (REER) based on consumer price index (HICP/CPI), relative to 41 other industrial countries (ICs)[16] 
 Transformation ||   || 
 Source ||   || DG ECFIN 
 Thresholds[17] (calculated for the period 1995-2007) || Previously || - Euro area Member States: +/–5%. - Non-euro area Member States: +/–11%. 
 Suggested || - Euro area Member States: +/–5% - Non-euro area Member States: +/–11% 
Comparing Tables A and
B, it can be noted that: 
(a) considering the
indicators beyond the indicative threshold (i.e. hereafter referred as
"flashes") both indicators show similar results for most years.
However, for 2012, on the basis of the data currently available, the number of
observations beyond the thresholds increases substantially,
(b) deviations between
"flashing" observations and thresholds have widened.
These aspects reflect
the better representation of emergent countries in the set of trading partners
as well as their relevance for the losses of competitiveness of a number of EU
Member States.
Table A –
Percentage change (3 years) of REER based on HICP (35 trading partners).
Thresholds: +/-5% - +/- 11%
   || 2001 || 2002 || 2003 || 2004 || 2005 || 2006 || 2007 || 2008 || 2009 || 2010 || 2011 || 2012 
 BE || -3.9 || -1.9 || 5.2 || 5.3 || 4.9 || 1.5 || 1.5 || 4.4 || 4.2 || 1.4 || -0.6 || -2.7 
 BG || 11.5 || 15.4 || 14.4 || 10.9 || 8.9 || 11.2 || 12.0 || 20.2 || 18.6 || 10.8 || 3.1 || -1.7 
 CZ || 6.5 || 20.6 || 14.9 || 8.5 || 3.5 || 11.5 || 14.0 || 24.4 || 13.7 || 12.8 || 0.3 || 2.1 
 DK || -3.5 || -1.1 || 8.1 || 6.8 || 4.2 || -0.5 || 0.1 || 3.2 || 5.7 || 0.9 || -1.7 || -6.2 
 DE || -8.8 || -5.8 || 5.0 || 6.4 || 4.8 || 0.1 || 0.6 || 2.4 || 3.2 || -2.9 || -3.9 || -7.0 
 EE || 2.6 || 3.9 || 9.3 || 7.0 || 6.9 || 6.5 || 9.5 || 15.1 || 13.8 || 6.2 || 0.8 || -0.1 
 IE || -2.2 || 4.5 || 17.5 || 17.6 || 12.0 || 3.4 || 4.1 || 8.0 || 5.3 || -4.9 || -9.1 || -11.2 
 EL || -5.2 || -3.6 || 9.0 || 9.5 || 6.8 || 2.4 || 1.9 || 4.0 || 5.1 || 4.1 || 3.1 || -2.2 
 ES || -2.1 || 1.0 || 8.8 || 9.7 || 7.9 || 4.3 || 4.2 || 6.2 || 5.0 || 0.7 || -1.3 || -3.5 
 FR || -7.7 || -3.9 || 6.5 || 8.1 || 6.0 || 0.8 || 0.2 || 2.7 || 2.9 || -1.2 || -3.2 || -5.9 
 HR || -1.9 || 4.7 || 6.4 || 3.6 || 3.7 || 5.4 || 4.4 || 7.3 || 6.0 || 3.3 || -3.2 || -5.7 
 IT || -5.6 || -2.0 || 8.8 || 9.9 || 6.9 || 1.1 || 0.7 || 3.2 || 3.9 || -0.9 || -2.1 || -4.2 
 CY || -3.5 || 0.8 || 8.1 || 8.1 || 6.7 || 1.3 || 0.2 || 3.1 || 3.7 || 1.7 || -0.9 || -2.9 
 LV || 13.3 || 5.0 || -7.1 || -6.9 || -4.4 || 4.8 || 11.1 || 24.1 || 23.7 || 8.7 || -0.6 || -4.6 
 LT || 15.9 || 15.2 || 6.7 || 4.2 || 1.1 || 0.9 || 4.5 || 12.3 || 16.9 || 9.3 || 3.6 || -2.5 
 LU || -1.6 || 0.1 || 4.5 || 5.8 || 6.6 || 4.0 || 3.3 || 4.0 || 4.0 || 2.0 || 0.8 || -1.1 
 HU || 12.2 || 20.5 || 20.1 || 17.7 || 9.2 || 3.0 || 7.9 || 9.2 || 8.0 || -0.4 || -3.3 || 0.8 
 MT || -0.6 || 1.8 || 5.9 || 7.4 || 5.6 || 4.0 || 3.2 || 7.0 || 5.9 || 0.7 || -3.0 || -4.8 
 NL || 0.0 || 3.2 || 10.9 || 7.2 || 3.2 || -1.1 || -1.0 || 0.7 || 2.8 || -0.9 || -1.6 || -4.6 
 AT || -5.0 || -3.2 || 3.1 || 3.7 || 2.6 || -0.5 || -0.4 || 0.9 || 2.1 || -1.3 || -1.0 || -2.9 
 PL || 20.0 || 19.0 || -4.6 || -16.2 || -1.5 || 13.6 || 18.7 || 16.1 || -3.8 || -0.5 || -10.9 || 3.3 
 PT || -0.3 || 2.3 || 9.6 || 8.2 || 5.3 || 1.4 || 1.5 || 2.7 || 1.3 || -2.2 || -1.9 || -2.5 
 RO || -1.1 || 14.5 || -1.6 || -1.4 || 16.3 || 29.3 || 37.5 || 10.6 || -4.9 || -10.1 || -2.3 || 0.0 
 SI || -2.3 || 0.0 || 4.9 || 4.4 || 1.5 || -1.0 || 0.8 || 3.8 || 5.4 || 2.3 || -0.1 || -2.4 
 SK || 9.6 || 15.8 || 17.8 || 26.8 || 27.3 || 19.5 || 19.4 || 26.0 || 27.1 || 11.8 || 4.3 || -1.6 
 FI || -4.7 || -1.4 || 7.7 || 5.7 || 2.5 || -2.5 || -1.4 || 2.4 || 5.3 || 0.2 || -1.3 || -5.2 
 SE || -12.0 || -7.6 || 0.3 || 10.3 || 3.9 || -2.5 || -2.6 || -0.9 || -8.3 || -2.6 || 3.9 || 12.1 
 UK || -2.3 || -2.0 || -7.6 || -1.6 || -2.9 || 3.0 || 1.2 || -10.4 || -19.9 || -19.7 || -7.1 || 8.2 
Source:
DG ECFIN.
Notes:
(i) The shadow cells correspond to the values of
the indicator breaching the threshold;   
(ii) Date of extraction of the data: November,
1st 2013.
Table
B - Percentage change (3 years) of REER based on HICP (41 trading partners).
Thresholds: +/-5% - +/- 11%
   || 2001 || 2002 || 2003 || 2004 || 2005 || 2006 || 2007 || 2008 || 2009 || 2010 || 2011 || 2012 
 BE || -3.8 || -2.1 || 6.0 || 6.3 || 5.0 || 0.5 || 0.2 || 3.4 || 3.9 || 0.5 || -1.6 || -4.3 
 BG || 11.5 || 12.4 || 13.6 || 11.5 || 8.4 || 9.2 || 9.9 || 18.5 || 18.4 || 9.7 || 1.9 || -4.0 
 CZ || 6.7 || 19.5 || 15.1 || 9.2 || 3.5 || 10.3 || 12.7 || 23.4 || 13.7 || 12.0 || -0.6 || 0.4 
 DK || -3.4 || -1.6 || 8.6 || 7.7 || 4.1 || -1.7 || -1.3 || 2.1 || 5.5 || 0.1 || -2.5 || -7.7 
 DE || -8.3 || -6.1 || 5.9 || 7.5 || 4.6 || -1.5 || -1.5 || 0.9 || 2.9 || -3.8 || -4.9 || -8.9 
 EE || 3.8 || 0.8 || 8.6 || 7.3 || 5.8 || 3.5 || 6.5 || 12.6 || 13.7 || 4.7 || -0.8 || -3.4 
 IE || -2.2 || 4.3 || 18.3 || 18.4 || 12.1 || 2.7 || 3.1 || 7.3 || 5.0 || -5.5 || -9.7 || -12.2 
 EL || -5.6 || -5.4 || 9.0 || 10.4 || 6.4 || 0.3 || -0.4 || 2.4 || 4.9 || 2.9 || 1.8 || -4.5 
 ES || -1.5 || 1.0 || 9.9 || 10.8 || 7.8 || 3.1 || 2.7 || 5.2 || 4.6 || -0.3 || -2.6 || -5.2 
 FR || -7.5 || -4.0 || 7.7 || 9.4 || 6.0 || -0.5 || -1.5 || 1.5 || 2.6 || -2.3 || -4.5 || -7.8 
 HR || -1.7 || 2.5 || 6.2 || 4.1 || 2.9 || 2.8 || 1.8 || 5.3 || 5.8 || 2.0 || -4.5 || -8.3 
 IT || -5.0 || -2.3 || 9.8 || 11.0 || 6.8 || -0.4 || -1.2 || 1.8 || 3.6 || -1.9 || -3.3 || -6.2 
 CY || -3.1 || -1.5 || 8.1 || 9.7 || 6.9 || 0.2 || -1.2 || 2.2 || 3.5 || -0.1 || -3.0 || -5.8 
 LV || 14.9 || 2.5 || -7.5 || -6.5 || -5.3 || 1.8 || 7.7 || 20.8 || 23.5 || 6.7 || -2.5 || -8.5 
 LT || 18.7 || 11.0 || 5.3 || 4.4 || -0.2 || -2.6 || 0.9 || 9.0 || 16.7 || 7.3 || 1.7 || -6.7 
 LU || -1.5 || 0.0 || 5.1 || 6.6 || 6.7 || 3.3 || 2.4 || 3.4 || 3.8 || 1.2 || 0.0 || -2.3 
 HU || 12.7 || 19.6 || 20.3 || 18.3 || 9.1 || 1.8 || 6.6 || 8.1 || 7.9 || -1.2 || -4.2 || -1.2 
 MT || -0.4 || 1.9 || 7.2 || 9.0 || 6.0 || 2.8 || 1.2 || 5.8 || 5.8 || -0.8 || -5.1 || -7.7 
 NL || 0.1 || 2.9 || 11.5 || 8.0 || 3.3 || -2.1 || -2.1 || -0.1 || 2.7 || -1.6 || -2.5 || -6.0 
 AT || -4.9 || -3.6 || 3.6 || 4.6 || 2.6 || -1.6 || -1.8 || -0.1 || 2.0 || -2.1 || -1.9 || -4.7 
 PL || 20.9 || 17.3 || -4.6 || -15.6 || -1.9 || 11.6 || 16.4 || 14.4 || -3.9 || -1.4 || -11.6 || 1.3 
 PT || 0.1 || 2.4 || 10.5 || 9.0 || 5.4 || 0.7 || 0.6 || 2.1 || 1.0 || -3.1 || -3.1 || -4.0 
 RO || -1.2 || 13.6 || -1.3 || -0.5 || 16.6 || 28.1 || 35.9 || 9.6 || -4.9 || -10.8 || -3.3 || -1.9 
 SI || -2.4 || -1.5 || 4.7 || 4.8 || 1.0 || -2.8 || -1.2 || 2.2 || 5.2 || 1.2 || -1.1 || -4.5 
 SK || 9.8 || 15.0 || 18.0 || 27.5 || 27.2 || 18.4 || 18.2 || 25.0 || 27.0 || 10.9 || 3.4 || -3.2 
 FI || -4.3 || -2.8 || 8.1 || 6.8 || 1.7 || -5.6 || -4.9 || -0.4 || 4.9 || -1.3 || -2.8 || -8.3 
 SE || -11.5 || -7.9 || 1.1 || 11.5 || 3.9 || -3.8 || -4.2 || -2.0 || -8.5 || -3.4 || 2.9 || 10.1 
 UK || -2.1 || -2.1 || -6.7 || -0.4 || -2.8 || 1.8 || -0.4 || -11.2 || -19.9 || -20.5 || -8.3 || 5.8 
Source:
DG ECFIN.
Notes:
(i) The shadow cells correspond to the values of
the indicator breaching the threshold;
(ii) Date of extraction of the data: November,
1st 2013.

2.2.                
World Export Market Shares

The scoreboard includes
an indicator of the evolution of the Member States' shares in world export
markets over a five-year period.  When the scoreboard was defined, the aim of
considering such an indicator was to capture trend losses in export
performance.
The indicator has a
number of characteristics which raised some issues in the first two
applications of the MIP:
(a) the current
indicator compares the latest observation with the observation of 5 years
before, without considering the intermediate years; as a result it is very
sensitive to the starting year, and changes in the indicator may depend both on
recent developments as well as the year-on-year changes of five years before.
This is particularly relevant at this stage with data up to 2012, as in 2008-9
there were very large reductions in export trade flows towards of all EU Members
States, even if this was partially or fully recovered afterwards;
(b) the deterioration of
export performance is visible across the board. The rise of emergent countries
in the world trade impacts all Member States and all advanced economies suffer
from losses as the world trade structure is changing. While these changes are a
fact and appear reflected in the downward trend of world export market shares
of Member States, this indicator fails to provide an appropriate a context for
this phenomenon – i.e.it does not disentangle losses in market shares
that are specific to each country from those that concern all advanced
economies. Moreover losses in export market shares for the advanced economies
have accelerated in recent years while the threshold was calculated taking into
account a longer period. These losses have been more important than those that
occurred during the years for which the threshold was calculated (1995-2007);
as a result, for many EU economies there have been many observations below the
threshold of –6 percent (Figure 2). This means simply identifying the indicator
"flashes" does not allow to properly distinguish Member States.
 Figure 2. Number of threshold breaches for the Export Market Shares Indicator 
 Source: Eurostat 
The latter issue
regarding the indicator of the world export market shares in the scoreboard is
more of a conceptual nature and is linked to the benchmark that has to be
considered for assessing the export performance of the Member States. All
advanced economies have been adversely affected by a fierce competition with
the emergent countries. It is, therefore, relevant to complement the world
export market share indicator with information that compares losses common to
all advanced economies with those that are specific to each country. While a
comparison of the Member States export market shares with other advanced
economies is feasible, the world market share should not be replaced. Instead,
it should be complemented with an auxiliary indicator. This is further discussed
in section 3.2[18].
No suggestion is
currently put forward to address the aspect of sensitivity to the starting
period of the calculation mentioned above. While the topic of export market
shares will have to be revisited, for the time being it is preferable to keep
the series as they stand. The Commission will continue to interpret this series
by looking into its overall development, rather than simply comparing the
latest observation with the threshold.

2.3.                
Private Sector Debt

As regards
the indicator for private sector debt there are two issues that can be
considered at this stage:
-
Consolidation of debt data within the different domestic sectors and
- Including
or excluding specific debt instruments for the measurement of debt.
Both issues
are also relevant for the private sector credit growth indicator discussed
below in section 2.4[19].
2.3.1. Issues of consolidation
Excessive indebtedness,
in particular, in the non-financial private sector stands as a major source of
risks for the economic activity and for financial stability. High private debt
increases the vulnerability of an economy to negative business cycle shocks, as
well as to changes in interest rates. 
Debt of the
non-financial private sectors (households and non-financial corporations (NFC)
can be measured in consolidated or non-consolidated terms. Consolidated data
present each sector as if it were a single entity: intra-sector assets and
liabilities offset each other and only those vis-à-vis other sectors are
reported. Non-consolidated debt gives the total gross indebtedness of the
sector, including debts between two entities of the same sector, including
entities of a corporate group, notably loans granted by mother companies to
subsidiaries. The issue of consolidation is highly relevant in the non-financial
corporations (NFC) sector given financial loans between corporates of the same
group[20].
During the initial
design of the Scoreboard in 2011 and 2012, the variables selected as indicators
of private sector debt and private sector credit flow were defined in
non-consolidated terms. Although the use of consolidated data was then
considered preferable, the choice of non-consolidated debt figures was
essentially due to the fact that only non-consolidated data were available for
all Member States (e.g. UK data were missing), and full availability was
a required characteristic for all indicators in the scoreboard. For the
Member States for which consolidated debt figures were available, these were
included as an auxiliary indicator (without thresholds) thus qualifying the
non-consolidated figures.
After technical work by
Eurostat and the Member States' statistical institutes, consolidated debt data
are now available for all Member States. Therefore the fundamental reason in
favour of the use of non-consolidated data in the scoreboard no longer applies.
Consequently, the Commission now proposes to swap the scoreboard and the
auxiliary indicator for private sector debt so that the headline indicator
reflects consolidated data, which is more suitable in providing an accurate
picture of the total indebtedness of the private sector. Thus, the
current indicator on private sector debt (based on non-consolidated data) will
not be dropped, but considered as a part of the auxiliary indicators.
Advantages of consolidated
debt data
At the time of the
initial design of the Scoreboard, the Commission acknowledged that
non-consolidated data presented some drawbacks, and it signaled that a
re-assessment of the relative merits of consolidated versus non-consolidated
data would be performed once the availability of consolidated data improves[21].This section
presents two sets of issues that justify the use of consolidated data as the
headline scoreboard indicator of private debt and private sector credit flow,
while using non-consolidated figures as an additional variable in support of
the economic reading of the scoreboard. The first set of issues focuses on the
conceptual advantages of consolidated debt in the analysis of macroeconomic
imbalances. The second one, in turn, presents statistical issues that adversely
affect the comparability of non-consolidated figures across Member States and
over time. 

Conceptual issues

Consolidated data
describe a sector as a single economic entity. Consolidated debt corresponds,
by and large, to the amount of funds that the sector receives from other
sectors. In the MIP context this is relevant as it reflects trends that have
the potential of affecting the economic activity (which is especially useful
for measuring the credit boom-type of imbalances). During the expansion phase
new debt flows finance additional consumption and investment, possibly
generating associated imbalances (e.g. reallocation of resources to
certain productive sectors, asset price booms), while in the downturn phase
this can have negative consequences for economic activity, if debt levels need
to be reduced. 
Detailed debt figures
could allow capturing additional risks coming from the distribution of debt
within the sector. For that purpose it would however necessary to be able to
distinguish two types of intra-sector loans. In non-consolidated data all
intra-group lending (e.g. between the mother company and its resident
subsidiaries) appears identically to inter-group lending (e.g., loans to
associated companies that are not fully controlled subsidiaries, or loans to
independent companies). When looking at contagion and stability issues, there
are fundamental differences between intra-group loans and loans granted by
banks to independent companies. An increase in intra sector or intra group debt
may merely reflect institutional, corporate financing, accounting and tax
practices, rather than an effective increase in the non-financial sector
indebtedness.
Accurate data on
intra-group transactions are unfortunately not available in all Member States,
but they are likely to constitute a large majority of intra-sector liabilities.
Since the intra-group financing practices likely differ across Member States
(due to differences in tax systems, national financial markets, firm structures,
etc.), there are comparability issues for non-consolidated figures. 
Statistical issues 
In addition to the
conceptual issues detailed above, debt data are also affected by
heterogeneities in national statistical practices for two reasons: The definition
of statistical entity and practices for the collection of data. Figure 3
presents consolidated and non-consolidated NFC debt figures and the
corresponding gap for the EU Member States. The gap ranges from 0 percent to 93
percent of GDP, but it is in many cases implausibly small. Some of this
heterogeneity across Member States reflects actual differences in the financing
of non-financial corporations, but a significant part is simply due to
differences in statistical practices. This means that, in practice, the
non-consolidated data are less comparable among Member States than the
consolidated data, also on statistical grounds.
 Figure 3: Non-consolidated and consolidated NFC debt, % of GDP, 2011 
 ||     Plausible                                  Implausible 
 || Source: Eurostat. || 
The method used to
define the statistical unit, i.e. the lowest degree of granularity
within a sector, strongly affects the compilation non-consolidated data. Based
on Eurostat standards, the statistical unit (or institutional entity) should
correspond to the concept of enterprise (a key criterion being the autonomy of
decision). The enterprise is not necessarily a single legal entity: it can
group several legal entities. Similarly, an enterprise should be distinguished
from the concept of enterprise group. Following the EUROSTAT work in the Task
Force on Data Consolidation, it appears that there are significant differences
in national application of the concept of enterprise for statistical purposes.
Some Member States tend to assimilate the institutional entity to the legal
entity, which may lead to an overestimation of non-consolidated data, while
others use the enterprise group as the institutional entity, which hence may
tend to underestimate the non-consolidated data. 
Consolidated data are
less biased with respect to these heterogeneities, as by definition all
intra-sector assets and liabilities are being offset, independently of the
definition of the institutional unit for statistical purposes. With the
forthcoming application of the ESA 2010 standards, several Member States will redefine
the implementation of the institutional entity concept at this occasion with a
view to progressively making these definitions uniform in all Member States.
This will affect the non-consolidated debt figures in several Member States.
For example, France is expected to redefine the institutional entity from the
legal entity to the enterprise concept, which may lead to a strong reduction of
the reported non-consolidated data. 
Moreover, the national
practices in compiling consolidated and non-consolidated figures differ among
Member States. In most cases, a bottom-up approach is used: the statistical
office starts with aggregating consolidated debt figures and then adds an
estimate of intra-sector loans. Alternatively, a top-down approach can be used
by other Member States, whereby the statistical office starts with
non-consolidated data and subtracts an estimate of the intra-sector loans. Some
of the Member States applying the bottom-up approach may be unable to estimate
intra-sector lending (e.g. Denmark and the Netherlands). The
underestimation of non-consolidated debt figures can be in those cases severe
and may lead to significant comparability problems. The fact that the gap
between the two variables is so low on Figure 3 is therefore in some cases a
result of the non-consolidated data being underestimated, rather than the
consolidated data being overestimated. On balance, the use of consolidated
figures appears as a more appropriate choice, given that it, at worst,
overestimates debt figures for a minority of Member States that use the
top-down approach and are unable to estimate intra-sector transactions[22]. 
Moreover, turning to
consolidated private sector debt data would also be more consistent with the
public debt figures, which are consolidated.
In conclusion, the
availability of consolidated private debt data for all Member States has led to
a re-assessment of the relative merits of both types of data for the purposes
of the MIP surveillance. Based on economic and statistical considerations, it appears
that the use of consolidated data is both analytically sounder and
statistically more robust. Given that the main hurdle of the use of
consolidated data as headline indicator (data unavailability for some Member
States) has been resolved, the replacement of the indicators seems warranted.
Non-consolidated data should nevertheless continue to be used as an additional
indicator for the economic reading of the scoreboard. Going forward, further
analytical work and statistical progress is warranted on intra-sector
liabilities cross-border lending[23].
2.3.2. The measurement of private sector debt:
pension schemes and derivatives
A second issue regarding
the indicator on private sector debt is related to the differences between the
definition of debt for the scoreboard with the one used by the ESRB with
respect to
(i) financial
derivatives, and
(ii) pension schemes.
The indicator on private
sector debt in the scoreboard has been defined as the sum of loans and
securities other than shares, including financial derivatives. The ESRB
considers, in its dashboard, a definition of the private sector debt which
differs from the one in the MIP scoreboard since companies' pension reserve
liabilities are included and financial derivatives are excluded. Although,
there is no formal reason for using exactly the same indicator, the fact that
different organisations use different variables warrants further discussion to
determine what would be the most appropriate definition.
(i) Financial
derivatives: 
When designing the scoreboard,
the aim of a private sector debt indicator was to assess vulnerabilities to
changes in the business cycles, inflation and interest rate, as the crisis
showed that excessive private sector indebtedness implies higher risks for
growth, financial stability and thus greater vulnerability to economic shocks.
To this end, when the scoreboard was first designed, all the loans and
securities other than shares were considered. At that time, the appropriateness
of the inclusion of the derivatives among the securities was not discussed
in-depth. 
It is now proposed to
exclude the derivatives from the definition of the private sector debt since it
would allow for a clearer economic interpretation of scoreboard indicator, and
therefore aligning the scoreboard definition with the ESRB definition in this
respect. 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.
Moreover, statistical
compilation practices for the recording of debt arising from derivatives show
some differences and more work is needed to reach full statistical
harmonisation. Therefore, removing derivatives from the definition improves the
comparability of data among the EU Member States. Table D-1 presents the values
of the financial derivatives (as percent of GDP). As one can note, this item
only accounts for a very small part of the private sector liabilities, and
their exclusion would not have any practical consequence of the MIP
implementation.
(ii) Pension reserve
liabilities:
Pension liabilities have
not been included in the scoreboard definition of private sector debt, while
they have been included in the definition of the ESRB dashboard. At this point
in time it is preferable not to include pension liabilities in the scoreboard
definition of the private sector debt given that such inclusion would induce
problems of consistency. Comparability issues are caused by the heterogeneity
of social protection systems across Member States, which makes a consistent
cross-country comparison difficult, and would reduce the meaningfulness of a
common threshold for all Member States. In this sense, a major limitation to
comparability is that pension schemes are not always reflected in the companies'
balance sheets. Taking an example, in Member States as the UK most private
pension schemes are autonomous, i. e., settled by the employers but managed by
an independent pension fund. Such schemes are to be classified in the financial
corporations sector (S.12) as a pension fund. In other Member States however,
many private pension schemes are non-autonomous, that is, managed by the
employer itself and are therefore classified in the sector of the
(non-financial corporation) employer S.11.
In light of the elements
above, while recognising the importance of pension debt liabilities as
unconditional liabilities, it is suggested however that pension liabilities
remain outside the MIP private sector debt definition. Given the heterogeneity
featuring pension schemes, including them would reduce the transparency of the
indicator and hamper the interpretation of the threshold common to all Member
States. 
 Definition ||   || Private Sector Debt (PSD) as percent of GDP 
 Transformation || Previously || with PSD = F3, F4 for S11 and S14_S15[24] 
 Suggested ||  with PSD = F33[25], F4 for S11 and S14_S15    
 Source ||   || Eurostat data (National Accounts) 
 Thresholds (over the period 1995-2007) || Previously || +160% 
 Suggested ||  +133% 
2.3.3. Impact on data
Table C and D below
present the figures for the scoreboard private debt indicator when (i) the
indicator is currently computed and, (ii) when the all changes proposed above (i.e.
use of consolidated data and exclusion of derivatives) are implemented
respectively.
When the two suggested
changes (i.e. use of consolidated data and exclusion of financial
derivatives) are applied, the values of the indicator on private debt are
reduced substantially, but with large differences among Member States. By far,
the main source of the change comes from moving to consolidated data.
For consistency reasons,
the threshold has been recalculated (following the same statistical approach
based on the distribution of the indicator's values as it is currently done)[26]. When both
changes proposed are considered, the threshold is also, as expected,
significantly reduced and passes from 160 percent of
GDP to
133 percent of GDP. However, as a comparison of tables C and D
shows, the number of observation above the threshold is only slightly
different.
In 2010 and 2011, the
number of observations in excess of the threshold is almost the same when using
the previous and the new definitions and thresholds. However, for Member States
(e.g. Denmark or Cyprus), which have been reporting consolidated data as
non-consolidated ones, the revised threshold means that the observations exceed
the threshold by a much larger margin than previously. Moreover for the Member
States for which the consolidation matters the most the difference between the
observations and the threshold may change substantially. For example, Belgium
which with the current indicator is above the threshold all over the period by
a large margin (Table C), is only slightly above the threshold in recent years
with the adjusted indicator (Table D). For Belgium, this issues was properly
discussed in the different in-depth reviews 
Table C – Private Sector
Debt (as percent of GDP), non-consolidated data and including financial
derivatives            
Threshold: 160 percent of GDP
   || 2001 || 2002 || 2003 || 2004 || 2005 || 2006 || 2007 || 2008 || 2009 || 2010 || 2011 || 2012 
 BE || 180 || 180 || 194 || 188 || 186 || 194 || 204 || 219 || 230 || 234 || 244 || 248 
 BG || 48 || 48 || 58 || 74 || 91 || 100 || 132 || 144 || 154 || 151 || 144 || 142 
 CZ || 60 || 61 || 56 || 57 || 57 || 61 || 66 || 73 || 76 || 77 || 79 || 82 
 DK || 177 || 176 || 178 || 186 || 202 || 215 || 224 || 237 || 251 || 243 || 237 || 239 
 DE || 135 || 136 || 137 || 132 || 129 || 127 || 123 || 123 || 126 || 120 || 117 || 116 
 EE || 81 || 91 || 98 || 111 || 122 || 150 || 159 || 164 || 172 || 148 || 136 || 130 
 IE || 157 || 154 || 157 || 166 || 190 || 217 || 223 || 277 || 309 || 314 || 330 || 332 
 EL || 65 || 68 || 72 || 79 || 90 || 98 || 107 || 119 || 123 || 128 || 130 || 130 
 ES || 132 || 140 || 148 || 160 || 177 || 200 || 215 || 221 || 227 || 230 || 225 || 215 
 FR || 124 || 124 || 124 || 127 || 132 || 137 || 143 || 150 || 157 || 158 || 159 || 162 
 HR || 55 || 64 || 70 || 74 || 82 || 94 || 104 || 117 || 128 || 137 || 134 || 132 
 IT || 87 || 90 || 93 || 98 || 103 || 110 || 118 || 122 || 128 || 130 || 128 || 129 
 CY || 164 || 171 || 165 || 172 || 209 || 205 || 225 || 243 || 263 || 280 || 291 || 303 
 LV || 49 || 54 || 62 || 75 || 95 || 122 || 128 || 132 || 147 || 140 || 125 || 112 
 LT || 29 || 30 || 36 || 42 || 53 || 64 || 82 || 82 || 88 || 80 || 70 || 67 
 LU || 0 || 0 || 0 || 0 || 0 || 161 || 205 || 406 || 457 || 393 || 382 || 371 
 HU || 67 || 71 || 85 || 87 || 102 || 111 || 126 || 156 || 171 || 154 || 169 || 155 
 MT ||   ||   ||   || 167 || 171 || 183 || 190 || 198 || 223 || 226 || 226 || 218 
 NL || 191 || 195 || 203 || 205 || 211 || 213 || 211 || 211 || 225 || 225 || 222 || 223 
 AT || 127 || 127 || 129 || 128 || 132 || 144 || 152 || 157 || 158 || 165 || 165 || 165 
 PL || 43 || 49 || 48 || 43 || 44 || 52 || 59 || 72 || 72 || 74 || 80 || 79 
 PT || 184 || 188 || 193 || 193 || 200 || 209 || 223 || 240 || 251 || 250 || 254 || 256 
 RO || 30 || 34 || 36 || 36 || 42 || 68 || 107 || 115 || 123 || 76 || 75 || 74 
 SI || 64 || 67 || 71 || 75 || 85 || 91 || 106 || 118 || 127 || 128 || 128 || 125 
 SK || 49 || 53 || 49 || 49 || 52 || 55 || 64 || 69 || 74 || 73 || 76 || 76 
 FI || 125 || 127 || 134 || 137 || 142 || 147 || 151 || 169 || 179 || 183 || 179 || 185 
 SE || 203 || 181 || 178 || 179 || 188 || 192 || 216 || 249 || 266 || 252 || 254 || 257 
 UK || 155 || 165 || 165 || 171 || 181 || 187 || 191 || 205 || 207 || 196 || 192 || 190 
Source:
EUROSTAT
Notes:
(i) The shadow cells correspond to the values of
the indicator breaching the threshold;
(ii) Date of extraction of the data: November,
1st 2013.
Table
D – Private Sector Debt (as percent of GDP), consolidated data and excluding
financial derivatives       
Threshold: 133 percent of GDP
   || 2001 || 2002 || 2003 || 2004 || 2005 || 2006 || 2007 || 2008 || 2009 || 2010 || 2011 || 2012 
 BE || 109 || 109 || 111 || 112 || 109 || 109 || 116 || 146 || 144 || 140 || 150 || 146 
 BG || 29 || 33 || 42 || 59 || 75 || 94 || 130 || 138 || 143 || 141 || 133 || 132 
 CZ || 53 || 54 || 49 || 50 || 51 || 56 || 61 || 66 || 69 || 70 || 72 || 72 
 DK ||   ||   || 178 || 186 || 202 || 215 || 224 || 237 || 251 || 243 || 237 || 239 
 DE || 128 || 127 || 127 || 123 || 121 || 118 || 114 || 113 || 116 || 111 || 108 || 107 
 EE || 62 || 68 || 75 || 86 || 97 || 116 || 128 || 144 || 155 || 143 || 129 || 129 
 IE || 155 || 152 || 155 || 164 || 187 || 214 || 219 || 257 || 281 || 283 || 301 || 306 
 EL || 63 || 67 || 71 || 78 || 89 || 97 || 106 || 118 || 122 || 128 || 129 || 129 
 ES || 114 || 121 || 132 || 143 || 161 || 185 || 200 || 206 || 213 || 213 || 206 || 194 
 FR || 106 || 106 || 106 || 107 || 112 || 116 || 120 || 127 || 135 || 136 || 138 || 141 
 HR || 55 || 64 || 70 || 74 || 82 || 94 || 104 || 117 || 128 || 137 || 134 || 132 
 IT || 83 || 86 || 90 || 94 || 100 || 107 || 114 || 119 || 125 || 126 || 126 || 126 
 CY || 164 || 171 || 165 || 168 || 204 || 200 || 220 || 238 || 258 || 274 || 285 || 299 
 LV || 47 || 51 || 60 || 71 || 91 || 115 || 119 || 123 || 143 || 135 || 117 || 92 (p) 
 LT || 29 || 30 || 35 || 40 || 50 || 62 || 76 || 78 || 85 || 76 || 66 || 63 
 LU ||   ||   ||   ||   ||   || 135 || 164 || 399 || 400 || 339 || 328 || 317 
 HU || 63 || 66 || 77 || 77 || 91 || 98 || 111 || 140 || 149 || 133 || 147 || 131 
 MT ||   ||   ||   || 131 || 135 || 146 || 149 || 154 || 170 || 167 || 162 || 155 
 NL || 188 || 192 || 198 || 201 || 207 || 209 || 208 || 208 || 221 || 221 || 219 || 219 
 AT || 127 || 127 || 129 || 128 || 132 || 132 || 134 || 139 || 147 || 150 || 148 || 147 
 PL || 37 || 45 || 47 || 41 || 43 || 49 || 55 || 69 || 69 || 71 || 76 || 75 
 PT || 166 || 169 || 176 || 176 || 184 || 192 || 203 || 216 || 225 || 222 || 222 || 224 
 RO || 27 || 31 || 33 || 33 || 39 || 45 || 58 || 67 || 73 || 75 || 74 || 73 
 SI || 59 || 60 || 64 || 68 || 78 || 84 || 98 || 108 || 115 || 117 || 115 || 114 
 SK || 48 || 52 || 48 || 48 || 51 || 54 || 63 || 67 || 72 || 70 || 73 || 73 
 FI || 96 || 104 || 109 || 112 || 121 || 124 || 128 || 142 || 153 || 154 || 150 || 158 
 SE || 151 || 161 || 159 || 159 || 167 || 170 || 187 || 212 || 225 || 212 || 211 || 212 
 UK || 150 || 158 || 158 || 163 || 173 || 179 || 181 || 190 || 195 || 183 || 180 || 179 
Source:
EUROSTAT
Notes:
(i) The shadow cells correspond to the values of
the indicator breaching the threshold;
(ii) The thresholds are calculated as before,
i.e. over the period 1995-2007. However, as for non-consolidated data, a complete
data from many Member States are only available for a shorter period (data for
all Member States are only available since 2006);
(iii) Date of extraction of the data: November,
1st 2013.
(iv) p= provisional.
Table
D-1 – Financial derivatives (as percent of GDP), consolidated data
   || 2001 || 2002 || 2003 || 2004 || 2005 || 2006 || 2007 || 2008 || 2009 || 2010 || 2011 || 2012 
 BE || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0 
 BG || 0 || 0 || 0 || 0 || 0.1 || 0.2 || 0 || 0.2 || 0.1 || 0.1 || 0.1 || 0.2 
 CZ || 0.3 || 0.7 || 0.4 || 0.4 || 0.1 || 0.1 || 0.1 || 1.8 || 1.1 || 0.6 || 0.8 || 1.4 
 DK ||   ||   || 0 || 0 || 0 || 0 || 0.1 || 0 || 0 || 0 || 0 || 0 
 DE ||   ||   ||   ||   ||   ||   ||   ||   ||   ||   ||   ||   
 EE || 0.1 || 0 || 0 || 0 || 0 || 0.1 || 0.1 || 0.1 || 0.2 || 0.5 || 0.3 || 0.4 
 IE || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0.2 || 0.3 || 0.4 || 0.1 
 EL || 2 || 1.1 || 0.8 || 0.8 || 0.9 || 0.7 || 0.8 || 0.8 || 0.5 || 0.5 || 0.9 || 1.2 
 ES || 0 || 0 || 0 || 0 || 0 || 0.3 || 0.2 || 0.9 || 1 || 0.9 || 1 || 1.2 
 FR || 0.2 || 0.2 || 0.1 || 0.1 || 0.1 || 0.1 || 0.2 || 0.3 || 0.1 || 0 || 0 || 0 
 HR || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0 
 IT || 0.8 || 0.5 || 0.5 || 0.5 || 0.3 || 0.2 || 0.3 || 0.4 || 0.4 || 0.4 || 0.4 || 0.4 
 CY || 0.2 || 0.1 || 0 || 0 || 0 || 0.2 || 0 || 0 || 0 || 0.1 || 0.1 || 0 
 LV || 0 || 0 || 0.1 || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0.1 || 0 
 LT || 0 || 0.1 || 0 || 0 || 0 || 0 || 0 || 0.1 || 0.1 || 0.1 || 0.1 || 0.2 
 LU ||   ||   ||   ||   ||   || 0 || 0 || 0 || 0 || 0 || 0 || 0 
 HU || 0.2 || 0.3 || 0.8 || 0.7 || 0.5 || 0.4 || 0.5 || 0.9 || 0.4 || 0.6 || 1.2 || 0.8 
 MT ||   ||   ||   || 0.1 || 0 || 0 || 0.1 || 0.1 || 0.1 || 0.2 || 0.2 || 0.3 
 NL || 0 || 0 || 1.6 || 1.5 || 1.3 || 1.4 || 1.3 || 2 || 1.5 || 1.8 || 1.7 || 1.6 
 AT || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0.1 || 0.1 || 0.1 
 PL || 0 || 0 || 0 || 0 || 0.2 || 0.2 || 0.3 || 0.7 || 0.4 || 0.3 || 0.6 || 0.5 
 PT || 0 || 0 || 0 || 0.1 || 0 || 0 || -0.2 || 0.4 || 0.6 || 0.6 || 1.1 || 1.4 
 RO || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0 || 0 
 SI || 0 || 0.1 || 0.1 || 0 || 0.1 || 0.1 || 0.2 || 0.6 || 0.4 || 0.5 || 0.4 || 0.4 
 SK || 0.2 || 0.2 || 0.2 || 0.2 || 0.2 || 0.2 || 0.1 || 0.3 || 0.1 || 0.1 || 0.2 || 0.1 
 FI || 0.4 || 0.6 || 1 || 1 || 1.4 || 0.8 || 0.8 || 2.7 || 2.3 || 2.1 || 3.4 || 2.7 
 SE || 1.3 || 1.6 || 1.5 || 1.8 || 1.3 || 0.7 || 1.2 || 3.9 || 1.6 || 1.5 || 2 || 2 
 UK || 0 || 0 || 0 || 1.2 || 1.7 || 1.7 || 1.5 || 3.5 || 2.4 || 2.5 || 3.2 || 2.8 
Source:
EUROSTAT
Note:
Date of extraction of the data: November, 1st 2013.

2.4.                
Private Sector Credit 

Following the
proposals for the indicator of private sector debt, the indicator for private
credit flows should be computed in a consistent way with the now available
consolidated data and with the exclusion of derivatives from the definition of
the indicator. 
 Definition ||   || Private sector credit flow (PSCF) as percent of GDP ( non-consolidated data) 
 Transformation || Previously || with PSCF = F3, F4 liabilities for S11 and S14_S15[27] 
 Suggested || with PSCF = F33[28], F4 liabilities for S11 and S14_S15 
 Source ||   || Eurostat data (National Accounts) 
 Threshold (over the period 1995-2007)   || Previously || +15% 
 Suggested || +14% 
Tables E and F below
present the values of the indicator on private sector debt as it is currently
computed in the scoreboard and how it would be after the two changes (i.e.
use of consolidated data and exclusion of derivatives) are applied
respectively. 
To ensure consistency
the threshold has been recalculated (following the same statistical approach
based on the distribution of the indicator's values as it is currently done)[29]. The
threshold is slightly affected by the changes proposed for the credit indicator
and is set at the level of 14 percent of GDP. In addition, since the values of
the indicator are somewhat reduced by the proposed changes, the number of
observations above the threshold is somehow reduced.
Table E – Private Sector Credit
Flows (as percent of GDP), non-consolidated data and including financial derivatives     
Threshold: 15 percent of GDP
   || 2001 || 2002 || 2003 || 2004 || 2005 || 2006 || 2007 || 2008 || 2009 || 2010 || 2011 || 2012 
 BE || 16 || 9 || 20 || 4 || 5 || 18 || 21 || 22 || 12 || 16 || 22 || 7 
 BG || 16 || 6 || 14 || 20 || 22 || 21 || 40 || 39 || 10 || 3 || 2 || 3 
 CZ || -3 || 4 || -3 || 6 || 3 || 7 || 9 || 9 || 1 || 3 || 3 || 3 
 DK || 20 || 13 || 6 || 19 || 25 || 25 || 19 || 18 || -2 || 7 || -2 || 6 
 DE || 5 || 3 || 1 || -2 || -1 || 2 || 2 || 1 || -2 || 1 || 2 || 1 
 EE || 20 || 22 || 22 || 27 || 27 || 40 || 32 || 13 || 0 || -5 || 3 || 3 
 IE ||   || 18 || 9 || 25 || 37 || 50 || 25 || 36 || 2 || 0 || 16 || -4 
 EL || 11 || 8 || 11 || 12 || 15 || 17 || 17 || 17 || 4 || 1 || -3 || -7 
 ES || 19 || 17 || 17 || 22 || 28 || 37 || 27 || 12 || -3 || 4 || -2 || -10 
 FR || 10 || 5 || 4 || 7 || 9 || 11 || 13 || 9 || 2 || 5 || 6 || 4 
 HR ||   || 14 || 11 || 10 || 13 || 19 || 18 || 18 || 5 || 8 || 0 || -2 
 IT || 8 || 6 || 7 || 8 || 10 || 11 || 13 || 7 || 1 || 4 || 2 || -1 
 CY || 12 || 12 || 5 || 19 || 48 || 11 || 39 || 35 || 15 || 25 || 21 || 10 
 LV || 9 || 10 || 14 || 18 || 27 || 43 || 37 || 14 || -6 || -9 || -3 || 1 
 LT || 2 || 4 || 8 || 10 || 15 || 19 || 27 || 9 || -12 || -5 || 0 || 0 
 LU ||   ||   ||   ||   ||   || 14 || 34 || -16 || 35 || -22 || 4 || -4 
 HU || 10 || 15 || 18 || 13 || 17 || 18 || 22 || 29 || 5 || -22 || 7 || -3 
 MT || 0 || 0 || 0 || 6 || 16 || 16 || 15 || 22 || 24 || 20 || 12 || -2 
 NL || 14 || 12 || 10 || 7 || 15 || 13 || 10 || 8 || 7 || 5 || 3 || 1 
 AT || 8 || 5 || 7 || 4 || 8 || 7 || 16 || 7 || -4 || 7 || 8 || 3 
 PL || 4 || 1 || 2 || 2 || 5 || 10 || 12 || 12 || 4 || 4 || 7 || 4 
 PT || 22 || 12 || 9 || 10 || 14 || 17 || 24 || 22 || 7 || 5 || 1 || -6 
 RO || 7 || 9 || 8 || 9 || 12 || 23 || 34 || 28 || 8 || 2 || 2 || 1 
 SI || 0 || 9 || 9 || 10 || 14 || 14 || 24 || 18 || 4 || 2 || 2 || -4 
 SK || 4 || 8 || 4 || 3 || 8 || 9 || 10 || 12 || 3 || 3 || 3 || 3 
 FI || 2 || 6 || 9 || 9 || 8 || 13 || 15 || 20 || -1 || 7 || 5 || 8 
 SE || 15 || 1 || 3 || 6 || 12 || 13 || 29 || 26 || 9 || 7 || 10 || -1 
 UK || 16 || 18 || 15 || 15 || 17 || 17 || 18 || 13 || -5 || -2 || 1 || 3 
Source:
EUROSTAT
Notes:
(i) The shadow cells correspond to the values of
the indicator breaching the threshold;
(ii) Date of extraction of the data: November,
1st 2013.
Table F – Private Sector
Credit Flows (as percent of GDP), consolidated data and excluding financial
derivatives            
Threshold: 14
percent of GDP
   || 2001 || 2002 || 2003 || 2004 || 2005 || 2006 || 2007 || 2008 || 2009 || 2010 || 2011 || 2012 
 BE || 2 || 5 || 6 || 7 || 2 || 5 || 13 || 22 || -1 || 4 || 18 || -2 
 BG || 6 || 8 || 12 || 19 || 19 || 29 || 43 || 35 || 5 || 3 || 2 || 3 
 CZ || -3 || 4 || -3 || 6 || 5 || 9 || 10 || 9 || 1 || 2 || 3 || 1 
 DK || 19 || 12 || 7 || 19 || 25 || 25 || 19 || 18 || -2 || 7 || -2 || 6 
 DE || 4 || 1 || 1 || -2 || -1 || 1 || 2 || 1 || -1 || 0 || 2 || 2 
 EE || 14 || 15 || 14 || 16 || 23 || 35 || 30 || 8 || -11 || -5 || 0 || 5 
 IE ||   || 18 || 9 || 25 || 36 || 49 || 24 || 20 || -4 || -2 || 15 || -2 
 EL || 11 || 8 || 11 || 12 || 15 || 17 || 17 || 17 || 4 || 0 || -4 || -7 
 ES || 15 || 15 || 18 || 20 || 28 || 36 || 27 || 12 || -2 || 1 || -5 || -11 
 FR || 9 || 5 || 5 || 6 || 9 || 10 || 12 || 10 || 4 || 5 || 6 || 4 
 HR ||   || 14 || 11 || 10 || 13 || 19 || 18 || 18 || 5 || 8 || 0 || -2 
 IT || 9 || 7 || 7 || 8 || 10 || 11 || 12 || 7 || 2 || 5 || 3 || -1 
 CY || 12 || 13 || 5 || 15 || 47 || 10 || 39 || 35 || 15 || 24 || 20 || 10 
 LV || 8 || 10 || 14 || 17 || 26 || 41 || 35 || 13 || -7 || -9 || -6 || -1 (p) 
 LT || 2 || 4 || 8 || 9 || 15 || 19 || 23 || 11 || -10 || -5 || -1 || 0 
 LU ||   ||   ||   ||   ||   || 12 || 17 || -18 || -15 || -24 || 1 || -5 
 HU || 9 || 14 || 16 || 12 || 15 || 16 || 20 || 30 || 1 || -21 || 8 || -6 
 MT ||   ||   ||   || 4 || 14 || 13 || 9 || 16 || 16 || 11 || 4 || -2 
 NL || 14 || 12 || 12 || 9 || 15 || 13 || 10 || 8 || 6 || 5 || 3 || 0 
 AT || 8 || 5 || 7 || 4 || 8 || 7 || 9 || 7 || 3 || 3 || 4 || 3 
 PL || 3 || 1 || 2 || 2 || 4 || 9 || 12 || 12 || 4 || 3 || 7 || 3 
 PT || 19 || 11 || 11 || 8 || 14 || 15 || 21 || 17 || 5 || 4 || -2 || -5 
 RO || 5 || 9 || 8 || 9 || 12 || 15 || 19 || 15 || 0 || 2 || 2 || 1 
 SI || 0 || 7 || 9 || 9 || 13 || 14 || 22 || 16 || 3 || 2 || 1 || -3 
 SK || 4 || 8 || 4 || 3 || 8 || 9 || 10 || 11 || 3 || 3 || 3 || 3 
 FI || 4 || 11 || 6 || 7 || 13 || 9 || 13 || 16 || 0 || 7 || 4 || 9 
 SE || 12 || 6 || 5 || 7 || 14 || 10 || 22 || 20 || 5 || 4 || 6 || 2 
 UK || 15 || 16 || 14 || 13 || 15 || 17 || 15 || 10 || -7 || -1 || -1 || 3 
Source:
EUROSTAT
Notes:
(i) The shadow cells correspond to the values of
the indicator breaching the threshold;
(ii) The thresholds are calculated as before,
i.e.over the period 1995-2007. However, as for non-consolidated data, a
complete data from many Member States are only available for a shorter period
(data for all Member States are only available since 2006)
(iii) Date of extraction of the data: November,
1st 2013.
(iv) p= provisional.
House Prices 
An issue
concerning the indicator on residential house prices is related to differences
between the definition of the MIP scoreboard indicator and the one used by the
ESRB. Differences regarding the indicator on house prices between the MIP
scoreboard and the ESRB's dashboard exist in two respects: (i) the computation
of the indicator, (ii) data sources.
(i)
Computation:
In the
scoreboard, the headline indicator on houses prices is currently defined as the
year percentage change in the house price index (HPI) relative to a consumption
deflator, while the auxiliary indicator is defined as the three - year
percentage change in the nominal HPI. The HPI measures price developments of
all residential properties purchased by households, independently of their
final use and their previous owners. As regard the ESRB, developments in the
housing market are captured by the use of HPI with two indicators: (a) annual
change in nominal HPI, and (b) estimates of the over/undervaluation of HPI. The
latter estimates being the result of an average of four different valuation
methods: price-to-income ratio, price-to-rent ratio (in both cases
overvaluation is calculated with respect to each country`s long term average)
and two model-based measures (whereby overvaluation is calculated with respect
to equilibrium values). 
(ii) Data sources:
The MIP scoreboard
indicator on residential property prices relies essentially on the harmonised
HPI provided by EUROSTAT. HPI data are regularly transmitted to Eurostat by
Member States according to the legal framework entered into force in February
2013[30].
For time series analyses, other data sources such as the ECB (in the
Residential Property Price Indicator database) and the OECD are used as a
complement. EUROSTAT is still working to provide longer time series for the
HPI, starting possibly in the mid- 1990s. Since autumn 2012, EUROSTAT, the ECB,
the OECD and the BIS are all working in a joint approach for the construction
of longer House Price Index series[31].
Hence, taking into
consideration both the methods and the data source used for the computation, it
is proposed not to change the indicator for residential property prices and to
keep it as it is currently defined in the MIP scoreboard. 

3.         
Other indicators used for the economic reading of the
scoreboard

To help the economic
interpretation of scoreboard, the alert mechanism report (AMR) has shown data
on a series of auxiliary indicators. These indicators cover namely the
following areas: (i) macroeconomic conditions, (ii) competitiveness, (iii)
labour markets, (iv) house prices, and (v) private sector indebtedness. This
section suggests a number of changes in these indicators, on FDI inflows,
export performance vis-à-vis the OECD, and terms of trade. More importantly, as
per Commission Communication 'Strengthening the Social Dimension of the
Economic and Monetary Union'[32],
a number of other social indicators, without thresholds has been identified. 

3.1.                
Inward FDI stocks 

To help the economic interpretation
of developments on the external side of the economy an indicator of FDI inflows
has been considered as a part of the auxiliary indicators.
It is suggested to
complement the analysis of FDI by having an indicator on inward FDI stocks in
order to support specifically the analysis of the NIIP headline indicator
(Table G). As a major component of the NIIP position, this indicator has been
already actively used for the economic reading in the AMR and the analysis in
in-depth reviews on several occasions.
Table G –
Inward FDI stocks (as percent of GDP)
   || 2001 || 2002 || 2003 || 2004 || 2005 || 2006 || 2007 || 2008 || 2009 || 2010 || 2011 || 2012 
 BE ||   || 90.8 || 102.4 || 118.7 || 133.6 || 147.3 || 158.7 || 177.2 || 197.2 || 200 || 209.9 || 195.3 
 BG || 21.6 || 23.1 || 27.6 || 36.4 || 50.6 || 67.3 || 83.7 || 89.4 || 97.8 || 98 || 95.1 || 95.2 
 CZ || 40.1 || 45.4 || 43.2 || 43.7 || 47.9 || 49.7 || 55.5 || 56.9 || 61.5 || 63.6 || 62.9 || 67.6 
 DK || 42.4 || 38.1 || 37.4 || 35.5 || 40.1 || 38 || 40.4 || 36.7 || 37.1 || 34.1 || 33.5 || 32.4 
 DE || 22.5 || 23.7 || 24.6 || 24 || 24.7 || 27.4 || 28.3 || 26.9 || 28.3 || 28.9 || 28.3 || 28.5 
 EE || 51.3 || 51.9 || 63.7 || 76.1 || 85.5 || 72 || 70.9 || 72.5 || 83.5 || 86.9 || 80.8 || 84.2 
 IE || 129.4 || 133.4 || 125.5 || 101.6 || 85.1 || 66.9 || 73 || 75.1 || 107 || 135.2 || 138.1 || 157.1 
 EL || 10.8 || 9.5 || 10.3 || 11.3 || 12.8 || 15 || 16.2 || 11.7 || 12.6 || 11.8 || 10.8 || 9.7 
 ES || 29.6 || 33.6 || 34.3 || 35.6 || 35.8 || 35.6 || 37.8 || 38.9 || 41.9 || 45 || 46.1 || 46.8 
 FR || 22.4 || 23.8 || 26.3 || 28.5 || 43.9 || 46.8 || 44.9 || 33.6 || 38.2 || 40.7 || 36.9 || 40.8 
 HR || 16.9 || 20.7 || 22.7 || 28.3 || 34.1 || 52.4 || 70.4 || 47.3 || 56.5 || 59.7 || 54.4 || 54.9 
 IT || 10.4 || 9.9 || 11.1 || 12.2 || 14 || 15.9 || 16.5 || 15 || 16.6 || 15.8 || 16.6 || 17.6 
 CY ||   || 42.1 || 46 || 49.8 || 53.7 || 72.4 || 78.1 || 69.8 || 75.8 || 75.2 || 89.3 || 90 
 LV || 28.8 || 28.7 || 27.8 || 31.5 || 32.5 || 36 || 35.6 || 35.5 || 43.4 || 45 || 46.1 || 46.5 
 LT || 21.8 || 25.2 || 23.9 || 25.7 || 33 || 34.8 || 35.8 || 28.4 || 34.5 || 36.2 || 35.6 || 36.7 
 LU ||   || 2046 || 2356.1 || 2541.9 || 2557.5 || 2576.2 || 2721.2 || 2911.5 || 3617.9 || 3690.7 || 4219.6 || 4309.6 
 HU || 50.6 || 47.6 || 53.6 || 53.7 || 59.3 || 64.9 || 65.9 || 62.3 || 72.5 || 71.4 || 73.6 || 80.8 
 MT || 63.7 || 50.6 || 56.8 || 64 || 73.8 || 95.4 || 101.1 || 96.5 || 105.2 || 190 || 180.5 || 180.7 
 NL || 71.7 || 71.7 || 76.1 || 77.6 || 79.2 || 77.7 || 91.1 || 78 || 78 || 74.7 || 78.3 || 77.3 
 AT || 18.6 || 19.3 || 19.9 || 23.3 || 53.5 || 56.3 || 70.4 || 68.4 || 75 || 67.8 || 64.8 || 65.4 
 PL || 21.1 || 22.9 || 25.7 || 28.1 || 30.1 || 34.5 || 36.9 || 38.2 || 39.3 || 45.1 || 45.4 || 45.7 
 PT || 30.4 || 30.3 || 33.4 || 32.9 || 34.8 || 41.8 || 46.3 || 41.8 || 47.2 || 48.4 || 50.5 || 55 
 RO || 22.4 || 17.2 || 20.1 || 24.1 || 27.8 || 33.9 || 37.1 || 37.8 || 42.2 || 43 || 42.8 || 44.6 
 SI || 14.2 || 17 || 20 || 20.5 || 21.4 || 22 || 28.2 || 30.4 || 30 || 30.8 || 32.4 || 33.2 
 SK || 19.2 || 23.4 || 31.1 || 35.6 || 40.5 || 46.6 || 47.3 || 54.2 || 58.1 || 57.2 || 58.2 || 59.5 
 FI || 19.6 || 22.6 || 27.3 || 27.7 || 29.5 || 32.3 || 34.6 || 32.3 || 34.3 || 36.3 || 36.6 || 38 
 SE || 41.8 || 43 || 44.9 || 49.1 || 49.4 || 53 || 60.3 || 68 || 76.1 || 69.8 || 68.1 || 64 
 UK || 35.2 || 31.5 || 31 || 31.6 || 38.7 || 42.8 || 43 || 45.7 || 46 || 52.8 || 49.9 || 53.7 
Source:
EUROSTAT
Note: Date of extraction of
the data: November, 1st 2013. 

3.2.                
Export performance compared with advanced
countries

As elaborated above (see
section 2.2), the rise of emergent countries in the world trade impacts all EU
members and all advanced economies suffer losses as the world trade structure
is changing. The indicator on world market shares does not disentangle losses
in market shares that are specific to each country and those that concern all
advanced economies. To better understand the causes behind the losses in export
market shares, a new auxiliary indicator is suggested: it compared the export
performance of each country with the export performance of a group of advanced
countries (Table H)[33].
 Definition || Percentage change over five years in export (EXP) market shares (goods and services, values) within advanced countries (AC) 
 Transformation || 
 Source || Eurostat data (Balance of Payments statistics) 
Comparing this indicator
on the export performance across industrialised countries (based on national
accounts data) with the current scoreboard indicator of world export market
shares (based on Balance of Payment data) has to be done with caution due to
the difference of data source. However, one can note that the performance
indicator against peers provides a picture of the performance of Member States
which is much more favourable (Figure 4). Negative performances appear for most
Member States in 2006 onwards, and UK, records negative performance since 2001.
Eastern Members States display positive export performance in line with their
catching-up profile.
 Figure 4. Export Performance Benchmark compared with world and advanced economies (2012 data) 
 Source: Eurostat 
Table H – Percentage
change (over five year) of export performance compared with advanced countries
   || 2001 || 2002 || 2003 || 2004 || 2005 || 2006 || 2007 || 2008 || 2009 || 2010 || 2011 || 2012 
 BE ||   ||   ||   ||   || 0.4 || -6.6 || -0.9 || -3.3 || -2.3 || -6.7 || -3.1 || -6 
 BG || 2.2 || 14.9 || 38.9 || 63.5 || 52.9 || 58.1 || 58.5 || 49.7 || 28.9 || 25 || 25.9 || 15.8 
 CZ || 19.1 || 36.7 || 31.2 || 55.6 || 54.2 || 40.5 || 39 || 37.2 || 19.9 || 19.9 || 14.9 || 5.8 
 DK || -0.2 || 15.7 || 18.2 || 6.6 || 12.6 || 7.7 || 0.9 || 3.2 || 3.3 || -7.9 || -10.5 || -10 
 DE || -3.7 || 7.1 || 9.2 || 14.2 || 20.8 || 15 || 12.7 || 6.5 || 4.1 || 2.3 || 0 || -4 
 EE || 51.2 || 27.2 || 27.4 || 47.3 || 53.8 || 52.9 || 53.8 || 38 || 18.5 || 7.9 || 19.9 || 17.7 
 IE || 66.8 || 64.5 || 35 || 21.6 || 14.9 || -2.9 || -6.9 || -11.4 || 3.2 || -5.1 || -5.6 || -7.5 
 EL || 75.5 || 59.3 || 61.1 || 31.3 || 15.3 || 5.7 || 14.7 || 13.7 || -6.2 || -13 || -12.7 || -19 
 ES || 4.5 || 9.9 || 12.8 || 10.6 || 14.4 || 7.5 || 6.9 || -2.9 || 1.1 || -2.6 || -0.8 || -5.6 
 FR || -9 || -5.2 || -7.4 || -5.3 || -1.8 || -6.7 || -9.4 || -11.7 || -1.9 || -5.3 || -3.3 || -5 
 HR ||   ||   ||   || 46.5 || 45.3 || 26 || 22.3 || 4.3 || 0.8 || -7.7 || -11.8 || -16.8 
 IT || -14 || -8.3 || -6.8 || -0.1 || 2.8 || -2.9 || 0.1 || -5.8 || -10.5 || -12.1 || -12.2 || -15.7 
 CY || -0.4 || 4.5 || 5.9 || 1.4 || 6 || -8.8 || -1.9 || -4.3 || -0.9 || -12.3 || -10.2 || -18.9 
 LV || 16.9 || 17.1 || 17.4 || 40.1 || 55.7 || 46.5 || 60.9 || 58.6 || 43.5 || 23.9 || 32.8 || 24.2 
 LT || 27.7 || 26.8 || 46.4 || 86.6 || 92.8 || 66.9 || 44.4 || 57.3 || 33.4 || 23.7 || 34.4 || 42.9 
 LU || 28.1 || 30.3 || 25 || 25.7 || 27.3 || 32.8 || 41.6 || 30 || 20.5 || 7.7 || -2.7 || -9.7 
 HU || 67.8 || 47 || 52.5 || 44.3 || 42 || 29.8 || 33.5 || 28.1 || 16.1 || 7.5 || 3.7 || -9.1 
 MT || -2.4 || 12.5 || 3 || -8.4 || -15 || 0.4 || -2.9 || 6.9 || 20.2 || 26.6 || 19.5 || 15.5 
 NL || -6.5 || -1.1 || 4.2 || 5.4 || 10.3 || 6.1 || 7.4 || 1.8 || 2.1 || -0.5 || -1.4 || -2.7 
 AT || -2.2 || 9.5 || 9.4 || 13.6 || 22.2 || 12.4 || 11.2 || 6.1 || -0.2 || -7.2 || -6.2 || -12.9 
 PL || 22.4 || 26.3 || 29.8 || 67.4 || 60.8 || 52.6 || 57.1 || 56.6 || 39.3 || 30.7 || 21.2 || 12 
 PT || -4.9 || 4.3 || 3.9 || 3.9 || 4.5 || 5 || 4.4 || -2.5 || -1.2 || 0.4 || -1.9 || -7.2 
 RO || 23.6 || 43.8 || 69.4 || 85.3 || 78.5 || 67.9 || 57.8 || 59.2 || 44.5 || 31.9 || 32.6 || 17.1 
 SI || -4.6 || 8.4 || 10.3 || 25.7 || 37.7 || 32.2 || 32.3 || 26.1 || 16.3 || 4.8 || 0.4 || -11.5 
 SK || 23.5 || 29.3 || 50.5 || 74.4 || 70.3 || 76.9 || 92.6 || 71.1 || 52.2 || 42.9 || 30.7 || 15.1 
 FI || -3.3 || 2.2 || -0.2 || 5.9 || 1.8 || 3.2 || 4.8 || 6.2 || -7.3 || -12.9 || -17.8 || -23.5 
 SE || -10.1 || -5.1 || -2.1 || 0.8 || 3.1 || 9.8 || 10.3 || 2.5 || -8.5 || -5.6 || -6.5 || -10.2 
 UK || -0.7 || -4 || -5.3 || -5.1 || -3.1 || -1.2 || -10 || -14.9 || -14.2 || -16.4 || -18.6 || -10.5 
Source:
EUROSTAT
Note: Date of extraction of
the data: November, 1st 2013. 

3.3.                
Terms of trade

Amongst the current
auxiliary indicators, there is an indicator on world export market shares in
volume (for goods and services)[34]
aiming at supporting the scoreboard indicator on world export market shares.
However, export market shares in volume which exclude price effects from export
flows, lead to volatile aggregates difficult to interpret. Moreover, the
indicator depends on the year which is used a base year. Also one may dispute
the meaningfulness of the indicator when assessing competitiveness. 
In order to complement
the headline indicator on export market shares, it is proposed to add an
indicator on the evolution of the terms of trade (i.e. ratio of prices
exports to prices on imports)[35].
The indicator on terms of trade will be used to qualify export performance by
providing information in terms of the return of domestic exports.
Concerning its
computation, the indicator on terms of trade is computed following the same
methodology used for the current scoreboard indicator on export market shares (i.e.
percentage change over five years). Table I – below – presents the values of the
proposed auxiliary indicator on terms of trade.
 Definition || Percentage change over five years in terms of trade (TE) 
 Transformation || 
 Source || AMECO 
Table I – Percentage change (over five
years) of terms of trade
   || 2001 || 2002 || 2003 || 2004 || 2005 || 2006 || 2007 || 2008 || 2009 || 2010 || 2011 || 2012 
 BE || -2.6 || -1 || -2.2 || -1.8 || -0.2 || -1 || -2 || -4.1 || 0.1 || -1.1 || -1.8 || -2.1 
 BG || 10.7 || 13.2 || 7 || 7.5 || 1.7 || 6.4 || 6.9 || 4.7 || 5.2 || 8.2 || 3.5 || 2.4 
 CZ || 0.1 || 3.9 || 0 || 1 || 2.1 || -2.2 || -3.9 || -5 || -3.5 || -3 || -2.2 || -3.6 
 DK || 1.2 || 2.2 || 3.2 || 4.4 || 5.5 || 5.2 || 3.4 || 4.1 || 2.3 || 3.8 || 1.8 || 2.1 
 DE || -3.8 || 0.1 || -0.5 || -1.2 || 1.5 || 0.1 || -1.6 || -4.2 || -0.3 || -0.5 || -1.2 || -2.2 
 EE || 8.6 || 7.4 || 9.5 || 11.6 || 10.6 || 10.8 || 10.7 || 6.9 || 6.9 || 3.3 || 0.2 || -3.4 
 IE || -0.3 || 0.4 || -0.6 || -1.2 || 0.2 || -1.7 || -4 || -5.4 || -3.2 || -4.3 || -6.2 || -4.4 
 EL ||   ||   ||   ||   || 4.1 || 3.1 || 1.5 || -1.4 || -2.2 || -1.4 || -2.2 || -3.8 
 ES || 0.3 || 3.6 || 2.8 || 2.5 || 6.3 || 4.5 || 2 || -1 || 3.6 || 0.7 || -2.7 || -5.3 
 FR || -0.7 || 1.1 || -0.3 || -1.7 || -0.3 || -2 || -2.5 || -3.2 || 0.4 || 0.3 || -0.4 || -2.4 
 HR || 5.8 || 3.6 || 3.8 || 8.1 || 7.6 || 8.4 || 7.7 || 6.6 || 5.2 || 5.6 || 4.4 || 2.5 
 IT || -2.9 || -0.8 || -1.9 || -2.7 || 0.6 || -3.2 || -3.9 || -7.7 || -1.7 || -2.4 || -2.2 || -4.3 
 CY || 2.6 || 0.9 || 0.2 || 2.2 || 0.9 || 0.1 || 3.9 || 2.4 || -0.2 || 1.3 || 0.4 || -1.6 
 LV || -2.4 || 4.1 || 2.2 || 1.3 || 3.5 || 1.2 || 7.4 || 3 || 0.9 || 2 || 6.3 || -1.3 
 LT || 10.6 || 6.6 || 9.9 || 14.4 || 9.3 || 6.5 || 7.3 || 10.5 || -2.8 || -3 || -1 || -2.6 
 LU || -5.4 || -1 || 4.2 || 0.9 || 3.6 || 6.5 || 6 || 1.2 || 2.7 || 4.9 || 3.5 || 3.1 
 HU || 0.9 || 0.2 || -1.3 || -0.7 || -0.2 || -2.2 || -3.1 || -3.5 || -2.6 || -1 || -1.1 || -2.3 
 MT ||   ||   ||   ||   || 1.9 || 3.5 || 2.7 || -0.7 || -0.4 || -1.9 || -0.9 || -1.4 
 NL || 2.6 || 2.6 || 2.2 || 1.9 || 2.3 || 0.7 || -0.5 || -0.5 || 0.2 || -1.6 || -1.2 || -1.6 
 AT || -2.2 || -0.1 || 0.3 || 0.1 || 0.8 || -0.2 || -2.3 || -3.8 || -2.2 || -2.6 || -4 || -4.3 
 PL || -6.4 || -5.7 || -7.8 || -3.6 || 3.3 || 3.2 || 5.6 || 4.2 || 4.4 || 1.8 || 0.2 || -2.8 
 PT || 2.1 || 2.9 || 0.5 || -1.4 || 0.2 || 0.4 || -0.5 || -3.2 || 1.9 || 2.8 || 0.6 || -0.1 
 RO || 14.7 || 13 || 9.1 || 11.8 || 11 || 17.6 || 26.9 || 28.3 || 25 || 22.5 || 18.4 || 10.5 
 SI || -0.3 || 1.2 || 1.5 || 0.1 || 1.2 || -0.8 || -1.7 || -4.1 || 0.6 || -1.5 || -2.4 || -4.3 
 SK || 2.5 || -2 || 0 || 1 || -1.9 || -2.2 || -3.3 || -4.4 || -5 || -5.6 || -5.5 || -5.6 
 FI || -4.7 || -3 || -6.1 || -5.3 || -5.2 || -9.7 || -10.1 || -10.6 || -7.5 || -6.2 || -4.8 || -5.7 
 SE || -6.3 || -7.5 || -6.9 || -5.7 || -5.8 || -4.7 || -1.8 || -2.3 || -0.5 || 0.6 || 0.3 || -1.3 
 UK || 5 || 3.3 || 3.7 || 2.7 || 2.1 || 0.6 || -0.7 || -2.8 || -3.6 || -2.4 || -3.3 || -3.6 
Source:
EUROSTAT
Note: Date of extraction of
the data: November, 1st 2013.

4.         
Presentational aspects

Several indicators
appear in the scoreboard as moving averages spanning over several years. This
concerns in particular the current account balance[36], the real
effective exchange rate[37],
world export market shares[38],
unit labour costs[39], and unemployment rate[40]. 
In order to facilitate
the economic reading of the scoreboard, it is suggested to include in the
scoreboard table for each indicator defined as an average over time of time the
latest annual observation. The indicative threshold would keep referring
to the scoreboard indicator proper defined as moving averages. Tables J
illustrate how the scoreboard would look like. This improves the
reading and transparency of the scoreboard given that processes of accumulation
and winding-down imbalances extend over several years.

Table
J-1 – Scoreboard 2011 (Date of extraction of the data: November, 1st 2013)

Table J-2 – Auxiliary indicators 2011 (Date of extraction
of the data: November, 1st 2013)
Table J-3 – Auxiliary
indicators 2011, continued (Date of extraction of the data: November,
1st 2013)
Table J-4 - Scoreboard
2012 (Date of extraction of the data: November, 1st 2013)
            Table J-5
– Auxiliary indicators 2012 (Date of extraction of the data: November,
1st 2013)
Table J-3 – Auxiliary indicators 2012,
continued (Date of extraction of the data: November, 1st
2013)
[1]               Regulation (EU) No 1176/2011 of the European
Parliament and of the Council of 16 November 2011 on the prevention and
correction of macroeconomic imbalances (OJ L 306, 23.11. 2011, p. 25)
[hereinafter MIP Regulation].
[2]               Views of the ESRB on the Envisaged Scoreboard
Indicators Relevant for Financial Market Stability, 9 December 2011.
[3]               European Parliament Resolution of 15 December
2011 on the Scoreboard for the surveillance of macroeconomic imbalances:
envisaged initial design, 2011/2926.
[4]                      Council Conclusions
on an
early warning scoreboard for the surveillance of macroeconomic imbalances,
15781/2/11 REV 2.
[5]                      'Completing
the Scoreboard for the MIP: Financial Sector Indicator,' SWD (2012) 389 final
of 14.11.2012, available at:
http://ec.europa.eu/economy_finance/economic_governance/documents/
alert_mechanism_report_2013_financial_sector_en.pdf.
[6]                      See
MIP Regulation, in particular Article 16. This review also applies to other
acts of the '6-pack'.
[7]                      Regulation (EC) No 549/2013
(OJ L 174, 26.6 .2013, p. 1).
[8]                      The 6th edition of the IMF BOP has been integrated into
Union law by Regulation
(EC) No 555/2012 (OJ L 166, 27.6.2012).
[9]               The same technique and period of time which is
currently used for the computation of the thresholds is considered, i.e.
a statistical approach based on the distributions of the indicators' values
over the period 1995-2007. In order to exclude the effects of the crisis on the
indicative thresholds, and ensure that the thresholds for the several
indicators are consistent, the years beyond 2007 are not considered for this
purpose.
[10]             The ESRB risk dashboard is a set of quantitative and
qualitative indicators to identify and measure systemic risk in the EU
financial system. It is updated and revised on a regular basis (see http://www.esrb.europa.eu/pub/pdf/dashboard/130620_ESRB_risk_dashboard.pdf?3ce8dc49333a58f430d11e92610d30a3).
The MIP scoreboard differs from the ERSB risk dashboard mainly in the sense
that its scope is not limited to the risks in the EU financial system but it
covers risks of harmful imbalances emerging from the external and internal
sides of the economy.
[11]             COM(2013) 960, 2.10.2013. 
[12]             41 countries: 27 Member States (i.e. without the
Member State concerned) plus US, Japan, Switzerland, Norway, Canada, Australia,
New Zealand, Mexico, Turkey, South Korea, China, Hong-Kong, Russia and Brazil. 
[13]             As soon as quality data will be available, the
Commission services will consider a further extension to the REER to other trading
partners so as to include further important trading partners such as India, Taiwan
and Singapore.
[14]             Since the thresholds have been rounded up the extension
of the set of trading partners has no material impact on the thresholds. For
the current scoreboard the calculated indicator was +/- 4.2 percent for the
euro area Member States and +/- 10.2 percent for the non-euro area Member
States, whereas for the adjusted indicator the calculated thresholds are +/-4.6
percent and +/- 10.6 percent, respectively.
[15]             35 countries: 26 EU Member States (excluding the
country for which the indicator is calculated) plus US, Japan, Switzerland,
Norway, Canada, Australia, New Zealand, Mexico and Turkey. 
[16]             41 countries: 27 EU Member States (excluding the
country for which the indicator is calculated)  plus US, Japan, Switzerland,
Norway, Canada, Australia, New Zealand, Mexico, Turkey and   South Korea,
Russia, Brazil, Hong-Kong and China. 
[17]             For the REER indicator, differentiated thresholds have
been adopted for euro area and non-euro area. The idea is to capture at the
same time the nominal exchange rate variability for non-euro area Member States
 and (partly) the real appreciation in catching-up Member States. Thus, for the
euro area Member States the thresholds of the series of  change over three
years of the REER based on HICP/CPI were computed as the
upper and lower quartile of the distribution (for the euro area) over the
period 1995-2007 (statistical approach). As concerns
non-euro area Member States, the thresholds refer to the thresholds for the
euro area Member States +/- 6 percent which is the standard deviation of the distribution (for the euro area) of the
change over three years of the REER based on HICP/CPI over
the period 1995-2007. For more details, see 'Scoreboard
for the Surveillance of Macroeconomic Imbalances,' European Economy-Occasional
Papers, 92.
[18]             Instead of comparing with the performance of other
advanced economies, one could use the EU average as benchmark. This option
however is not retained since the EU export performance has been below what
could be considered as an appropriately ambitious target.
[19]             It should be clarified that the private sector debt
refers to non-government, non-financial sector debt, i.e. non-financial
corporates, households and non-profit institutions.
[20]             Consolidation has a negligible impact on the households'.
Some Member States (e.g. SE, FI, RO, FR) report both consolidated and
non-consolidated data which is made available as such by Eurostat, figures are
quasi identical for the two concepts. Thus, while the use of consolidated data
is mainly relevant for non-financial corporations (NFC), the total represented
under the scoreboard indicators of private sector debt and credit flows do not
raise taxonomic concerns and could be considered consolidated. 
[21]              See
the European Commission (2012), 'Scoreboard for the surveillance of
macroeconomic imbalances,' European Economy-Occasional Papers, 92, for a
description of the design of the scoreboard and technical explanations.
[22]             For these cases full
consolidation can be considered incomplete, in particular in what regards
cross-border debt; larger Member States a larger share of inter-company debt
occurs within the resident economy and a larger share of debt is subject to
consolidation. In contrast, for smaller Member States a larger share of loans
comes from non-resident non-financial corporations, and therefore is not
subject to consolidation in national accounts. Issues of cross-border
consolidation will have to be considered in the future.
[23]             More in general, future work
should also consider whether data on accounts payable and trade credits should
be added to the private sector debt scoreboard definition. But the impact is
expected to be small.
[24]             F3, F4 refer to securities other than shares and loans respectively.
S11 and S14_S15 refer to non-financial corporations and households and non-profit
institutions serving households.
[25]             F33 refers to securities other than shares, excluding
financial derivatives
[26]             The threshold corresponds of the upper quartile of the
indicator distribution.
[27]             F3, F4 refer to securities other than shares and loans respectively.
S11 and S14_S15 refer to non-financial corporations and households; non-profit
institutions serving households.
[28]             F33 refers to securities other than shares, excluding
financial derivatives.
[29]             The threshold corresponds of the upper quartile of the
indicator's distribution.
[30]             Commission Regulation (EU) No 93/2013 of 1 February
2013 laying down detailed rules for the implementation of Council Regulation
(EC) No 2494/95 concerning harmonised indices of consumer prices, as regards
establishing owner-occupied housing price indices (OJ L 33, 2.2.2013, p. 14).
[31]             As concerns the ESRB indicator, the underlying residential property prices (RPP)
indices, were based on the data used to compile pilot series before the adoption of the EU Regulation
on house price indices. Now, as the regulation has entered into force, the ESRB
is revising its residential property prices database and will progressively
switch to the EU harmonised series. Presently, only 13 Members States are
covered by the ESRB data.
[32]             COM(2013) 960, 2.10.2013. 
[33]             The group of advanced economies is defined here
conventionally as the OECD countries. For the moment, national account data are
used for this purpose. Once Balance of Payment data would be available, it
would be used for the computation of the indicator on export performance.
[34]             Note that for the first AMR, due to data availability
issues, the indicator on world export market share in volume (provided by UN
COMTRADE) only considered goods. For the second AMR, we changed the data source
and we used WEO IMF series for having an indicator on world export market share
in volume considering both goods and services.
[35]             The terms of trade indicate the ratio of the change of
export prices of goods and services to the change of import prices of goods and
services. They are equal to the ratio of the price index for exports of goods
and services to the price index for imports of goods and services. However, it
has to be taken into account that the terms of trade are based on National
Accounts data which means that this indicator do not fully match Balance of
Payment data. 
[36]             Three year backward moving average
of the current account balance expressed in % of GDP.
[37]             Percentage change (three years) of real
effective exchange rate with HICP deflators relative to 35 other industrial
countries. 
[38]                    Percentage
change (five years) in world export market shares.
[39]                    Percentage
change (three years) in unit labour costs.
[40]             Percentage change (three years) in unemployment.