Economic Bulletin. Issue 2/2019.
Date: 2020-07-06
Institutions: European Central Bank
Subjects: economic policy, economic situation, euro area, monetary policy, serial publication

Economic Bulletin 

Issue 2 / 2019 

Contents 

Economic and monetary developments 

Overview 

1 

2

3

4

5

6 

External environment 

Financial developments 

Economic activity 

Prices and costs 

Money and credit 

Fiscal developments 

Boxes 

1

2

3

4 

5 

6 

7 

Characterising the current expansion across non-euro area advanced 
economies: where do we go from here? 

Liquidity conditions and monetary policy operations in the period from 31 
October 2018 to 29 January 2019 

Employment growth and GDP in the euro area 

New features in the Harmonised Index of Consumer Prices: analytical 
groups, scanner data and web-scraping 

A new method for the package holiday price index in Germany and its 
impact on HICP inflation rates 

Interest rate-growth differential and government debt dynamics 

The European Commission’s 2019 assessment of macroeconomic 
imbalances and progress on reforms 

Article 

1 

Taking stock of the Eurosystem’s asset purchase programme after the 
end of net asset purchases 

Statistics 

2 

2 

6 

13 

18 

23 

29 

36 

39 

39 

44 

50 

53 

56 

60 

64 

69 

69 

S1 

ECB Economic Bulletin, Issue 2 / 2019 – Contents 

1 

 
 
 
 
 
 
 
Economic and monetary developments 

Overview 

Based on a thorough assessment of the economic and inflation outlook, the 
Governing Council took a series of monetary policy decisions at its monetary 
policy meeting on 7 March. The weakening in economic data points to a sizeable 
moderation in the pace of the economic expansion that will extend into the current 
year, even though there are signs that some of the idiosyncratic domestic factors 
dampening growth are starting to fade. The persistence of uncertainties related to 
geopolitical factors, the threat of protectionism and vulnerabilities in emerging markets 
appears to be leaving marks on economic sentiment. Moreover, underlying inflation 
continues to be muted. The weaker economic momentum is slowing the adjustment of 
inflation towards the Governing Council’s aim. At the same time, supportive financing 
conditions, favourable labour market dynamics and rising wage growth continue to 
underpin the euro area expansion and gradually rising inflation pressures. Against this 
background, the Governing Council decided to adjust its forward guidance on the key 
ECB interest rates to indicate its expectation that they will “remain at their present 
levels at least through the end of 2019, and in any case for as long as necessary to 
ensure the continued sustained convergence of inflation to levels that are below, but 
close to, 2% over the medium term”, as well as to reiterate its forward guidance on 
reinvestments. Furthermore, the Governing Council decided to launch a new series of 
targeted longer-term refinancing operations (TLTRO-III) and to continue conducting all 
lending operations as fixed rate tender procedures with full allotment at least until the 
end of the reserve maintenance period starting in March 2021. These decisions were 
taken to ensure that inflation remains on a sustained path towards levels that are 
below, but close to, 2% over the medium term. 

Economic and monetary assessment at the time of the Governing 
Council meeting of 7 March 2019 

Global growth momentum continued to moderate in late 2018. Global growth is 
projected to decelerate in 2019, but to stabilise over the medium term. The slowdown 
has been more pronounced in the manufacturing sector, with global trade decelerating 
sharply as a result. Heightened global uncertainties relating to trade disputes, the 
financial stress in emerging market economies last summer and signs of weaker 
growth in China have contributed to the slowdown in global growth and trade. While 
those headwinds are expected to continue to weigh on the global economy this year, 
recent economic policy measures are expected to provide some support. Global trade 
is expected to weaken more significantly this year and to grow in line with activity in the 
medium term. Global inflationary pressures are expected to remain contained, while 
downside risks to global activity have been accumulating. 

Long-term risk-free rates have declined since the Governing Council’s meeting 
in December 2018, in the context of a deterioration in the macroeconomic 

ECB Economic Bulletin, Issue 2 / 2019 – Economic and monetary developments 
Overview 

2 

 
 
outlook and a perceived slowing of the pace of monetary tightening in the 
United States. The prices of euro area risk assets such as equities and corporate 
bonds have recovered amid improved risk sentiment, fuelled in part by greater 
optimism regarding global trade negotiations. In foreign exchange markets, the euro 
has broadly weakened in trade-weighted terms. 

Euro area real GDP growth remained subdued in the fourth quarter of 2018 at 
0.2% quarter on quarter. Incoming information suggests that growth will continue at 
moderate rates in the near term. Data releases have continued to be weak, in 
particular in the manufacturing sector, reflecting the slowdown in external demand 
compounded by some country and sector-specific factors. The impact of these factors 
is turning out to be somewhat longer-lasting, which suggests that the near-term growth 
outlook will be weaker than previously anticipated. Looking ahead, the effect of these 
adverse factors is expected to unwind. The euro area expansion will continue to be 
supported by favourable financing conditions, further employment gains and rising 
wages, and the ongoing – albeit somewhat slower – expansion in global activity. 

This assessment is broadly reflected in the March 2019 ECB staff 
macroeconomic projections for the euro area. These projections foresee annual 
real GDP increasing by 1.1% in 2019, 1.6% in 2020 and 1.5% in 2021. Compared with 
the December 2018 Eurosystem staff macroeconomic projections, the outlook for real 
GDP growth has been revised down substantially in 2019 and slightly in 2020. The 
risks surrounding the euro area growth outlook are still tilted to the downside, on 
account of the persistence of uncertainties related to geopolitical factors, the threat of 
protectionism and vulnerabilities in emerging markets. 

According to Eurostat’s flash estimate, euro area annual HICP inflation 
increased to 1.5% in February 2019, from 1.4% in January. On the basis of current 
futures prices for oil, headline inflation is likely to remain at around current levels 
before declining towards the end of year. Measures of underlying inflation have 
remained generally muted, but labour cost pressures have strengthened and 
broadened amid high levels of capacity utilisation and tightening labour markets. 
Looking ahead, underlying inflation is expected to increase gradually over the medium 
term, supported by the ECB’s monetary policy measures, the ongoing economic 
expansion and rising wage growth. 

This assessment is also broadly reflected in the March 2019 ECB staff 
macroeconomic projections for the euro area, which foresee annual HICP 
inflation at 1.2% in 2019, 1.5% in 2020 and 1.6% in 2021. Compared with the 
December 2018 Eurosystem staff macroeconomic projections, the outlook for HICP 
inflation has been revised down across the projection horizon, reflecting in particular 
the more subdued near-term growth outlook. Annual HICP inflation excluding energy 
and food is expected to be 1.2% in 2019, 1.4% in 2020 and 1.6% in 2021. 

Money growth and credit dynamics moderated in January 2019, but bank 
funding and lending conditions remained favourable. Broad money (M3) growth 
decreased to 3.8% in January 2019, from 4.1% in December 2018. M3 growth 
continues to be backed by bank credit creation, notwithstanding a recent moderation 
in credit dynamics. The annual growth rate of loans to non-financial corporations 

ECB Economic Bulletin, Issue 2 / 2019 – Economic and monetary developments 
Overview 

3 

 
 
declined to 3.3% in January 2019, from 3.9% in December 2018, reflecting a base 
effect but also, in some countries, the typical lagged reaction to the slowdown in 
economic activity, while the annual growth rate of loans to households remained stable 
at 3.2%. Borrowing conditions for firms and households are still favourable, as the 
monetary policy measures put in place since June 2014 continue to support access to 
financing, in particular for small and medium-sized enterprises. The Governing 
Council’s decisions, in particular the new series of TLTROs, will help to ensure that 
bank lending conditions remain favourable going forward. 

The aggregate fiscal stance for the euro area is assessed to have been broadly 
neutral in 2018, but is projected to be mildly expansionary from 2019 onwards. 
This is mainly the result of a loosening fiscal stance in a less favourable 
macroeconomic environment.   

Monetary policy decisions 

Based on the regular economic and monetary analyses, the Governing Council 
made the following decisions: 

• 

• 

• 

• 

First, the key ECB interest rates were kept unchanged. The Governing Council 
now expects the key ECB interest rates to remain at their present levels at least 
through the end of 2019, and in any case for as long as necessary to ensure the 
continued sustained convergence of inflation to levels that are below, but close 
to, 2% over the medium term. 

Second, the Governing Council intends to continue reinvesting, in full, the 
principal payments from maturing securities purchased under the asset purchase 
programme for an extended period of time past the date when it starts raising the 
key ECB interest rates, and in any case for as long as necessary to maintain 
favourable liquidity conditions and an ample degree of monetary 
accommodation. 

Third, the Governing Council decided to launch a new series of quarterly targeted 
longer-term refinancing operations (TLTRO-III), starting in September 2019 and 
ending in March 2021, each with a maturity of two years. These new operations 
will help to preserve favourable bank lending conditions and the smooth 
transmission of monetary policy. Under TLTRO-III, counterparties will be entitled 
to borrow up to 30% of the stock of eligible loans as at 28 February 2019 at a rate 
indexed to the interest rate on the main refinancing operations over the life of 
each operation. Like the outstanding TLTRO-II programme, TLTRO-III will feature 
built-in incentives for credit conditions to remain favourable. Further details on 
the precise terms of TLTRO-III will be communicated in due course. 

Fourth, the Governing Council decided to conduct the Eurosystem’s lending 
operations as fixed rate tender procedures with full allotment for as long as 
necessary, and at least until the end of the reserve maintenance period starting in 
March 2021. 

ECB Economic Bulletin, Issue 2 / 2019 – Economic and monetary developments 
Overview 

4 

 
 
The Governing Council took these decisions to ensure that inflation remains on a 
sustained path towards levels that are below, but close to, 2% over the medium term. 
The decisions will support the further build-up of domestic price pressures and 
headline inflation developments over the medium term. In any event, the Governing 
Council stands ready to adjust all of its instruments, as appropriate, to ensure that 
inflation continues to move towards its aim in a sustained manner. 

ECB Economic Bulletin, Issue 2 / 2019 – Economic and monetary developments 
Overview 

5 

 
 
1 

External environment 

Global growth momentum continued to moderate in late 2018, and surveys suggest 
that it has weakened further in early 2019. The slowdown has been more pronounced 
in the manufacturing sector, with global trade decelerating sharply as a result. 
Heightened global uncertainties relating to the trade dispute between the United 
States and China, the financial stress that was seen in emerging market economies 
last summer and, more recently, signs of weaker growth in China have all contributed 
to the slowdown in global growth and trade. While those headwinds are expected to 
continue to weigh on the global economy this year, recent economic policy measures 
are expected to provide some support. As a result, global growth is projected to 
decrease in 2019, but to stabilise over the medium term. Global trade is expected to 
weaken more significantly this year and to grow in line with activity in the medium term. 
Global inflationary pressures are expected to remain contained, while downside risks 
to global activity have been accumulating. 

Global economic activity and trade 

Global growth momentum moderated further in late 2018. Economic activity in 
advanced economies weakened in the fourth quarter of 2018, with growth slowing in 
both the United States and the United Kingdom. While growth in Japan strengthened 
in that quarter, this followed a contraction in the previous quarter on account of a 
series of natural disasters. Growth in emerging market economies (EMEs) also 
weakened in late 2018 – including in China. 

Survey-based evidence suggests that growth has continued to weaken in early 
2019. The global composite output Purchasing Managers’ Index (PMI) excluding the 
euro area has continued to decline, owing mainly to weakening global manufacturing 
activity. Service sector activity has also moderated recently, although its decline has 
been weaker and from a higher level (see Chart 1). Global manufacturing activity has 
slowed against the backdrop of maturing business cycles in key advanced economies. 
At the same time, the pace of this slowdown has been accentuated by heightened 
uncertainties weighing on the global economy, such as the lingering trade dispute 
between the United States and China, the financial stress that was seen in EMEs last 
summer and, more recently, signs of weaker growth in China. The slowdown in global 
manufacturing activity is also weighing on global trade. 

ECB Economic Bulletin, Issue 2 / 2019 – Economic and monetary developments 
External environment 

6 

 
 
Chart 1 
Global composite output PMI 

(diffusion indices) 

Global composite output excluding the euro area
Global composite output excluding the euro area – long-term average
Global manufacturing output excluding the euro area
Global services excluding the euro area

58

56

54

52

50

48

2012

2013

2014

2015

2016

2017

2018

2019

Sources: Markit and ECB calculations. 
Notes: The latest observations are for February 2019. “Long-term average” refers to the period from January 1999 to January 2019. 

Financial conditions in advanced economies remain accommodative overall, 
while the picture for EMEs remains mixed. Market expectations of further interest 
rate increases in the United States have eased amid a further decline in Treasury 
yields, partly reflecting developments in term premia. In China, financial conditions 
have also eased as policymakers have adopted a looser monetary policy stance in 
response to indications of weakening activity. Following a sharp decline at the end of 
2018 against the backdrop of renewed concerns about the global economy, global 
stock prices have rebounded since the turn of the year. However, global risk sentiment 
has not yet fully recovered, and volatility in financial markets remains elevated. In 
some of the EMEs that were hardest hit by the financial market turbulence last 
summer – including Argentina and Turkey – financial conditions remain relatively tight 
and are continuing to weigh on activity. 

Global growth is projected to soften this year amid increasing headwinds. 
These include weaker global manufacturing activity and trade in an environment of 
high and rising political and policy uncertainty. The sizeable procyclical fiscal stimulus 
in the United States (which includes tax cuts and increased spending) is continuing to 
help drive US and global growth, but the partial federal government shutdown, which 
ended in late January, is expected to weigh on growth in the first quarter of 2019. In 
China, domestic demand is expected to weaken in the first half of this year, as the 
impact of recently implemented policies is likely to kick in with something of a lag. 

Looking further ahead, global growth is projected to stabilise over the medium 
term. Three key forces look set to shape the global economy over the projection 
horizon. First, cyclical momentum is expected to slow in key advanced economies as 
capacity constraints become increasingly restrictive and policy support gradually 
diminishes amid positive output gaps and low unemployment rates. Second, China is 
expected to continue its orderly transition to a weaker growth path that is less 
dependent on investment and exports. And finally, growth is forecast to recover in 

ECB Economic Bulletin, Issue 2 / 2019 – Economic and monetary developments 
External environment 

7 

 
 
 
several key EMEs which are currently going through, or have recently experienced, 
deep recessions. Overall, the pace of global expansion is expected to settle at rates 
below those seen prior to the 2007-08 financial crisis. 

Turning to developments in individual countries, activity in the United States 
has remained relatively robust. The country’s strong labour market, favourable 
financial conditions and fiscal stimulus are continuing to support growth, outweighing 
the adverse impact of the trade dispute with China. The negative impact of the partial 
federal government shutdown is expected to be temporary. Annual headline consumer 
price inflation fell to 1.6% in January from 1.9% in the previous month, largely on 
account of falling energy prices, while consumer price inflation excluding food and 
energy remained unchanged at 2.2%. 

In Japan, recovering domestic demand supported growth in late 2018. This 
recovery followed a sharp contraction in the third quarter on account of a series of 
natural disasters. Looking ahead, the country’s accommodative monetary policy 
stance, its strong labour market and its robust demand for investment (despite a 
weakening external environment) are all projected to support growth. In addition, fiscal 
measures are expected to smooth out the negative impact of the consumption tax 
increase that is scheduled for October of this year. The fact that wage growth remains 
modest (despite a very tight labour market) and inflation expectations are at low levels 
suggests that inflation will remain below the Bank of Japan’s 2% target over the 
medium term. 

In the United Kingdom, heightened political uncertainty is continuing to weigh 
on growth. Even the short-term outlook is subject to considerable uncertainty as a 
result of the forthcoming votes on the EU withdrawal agreement in parliament. Over 
the medium term, growth is expected to remain below its pre-referendum trajectory. 

In central and eastern European countries, growth is projected to moderate 
somewhat this year. Investment growth remains strong, supported by EU funds, and 
consumer spending also remains robust, underpinned by strong labour market 
performance. However, the slowdown in the euro area is weighing on the growth 
outlook for this region. Over the medium term, growth levels in these countries are 
expected to fall back towards potential. 

Growth in China has lost some of its momentum in recent months. Moreover, 
monthly indicators suggest that this trend is likely to continue in early 2019. In order to 
shield the economy from a sharper slowdown, the Chinese authorities have 
announced a number of fiscal and monetary policy measures, which are expected to 
deliver a smooth deceleration in activity this year. Looking further ahead, progress with 
the implementation of structural reforms is projected to result in an orderly transition to 
a more moderate growth path that is less dependent on investment and exports. 

Economic activity in large commodity-exporting countries is projected to 
gradually strengthen. The outlook for growth in Russia is shaped by developments in 
global oil markets, and past declines in oil prices are projected to weigh on activity this 
year. Looking further ahead, economic activity in Russia is expected to gradually 
strengthen, amid constraints imposed by international sanctions and uncertainty 

ECB Economic Bulletin, Issue 2 / 2019 – Economic and monetary developments 
External environment 

8 

 
 
relating to the implementation of structural reforms and spending commitments 
announced last year. Growth in Brazil is also projected to strengthen, supported by 
accommodative financial conditions and declining political uncertainty. 

In Turkey, economic activity contracted significantly in the third quarter of 2018 
as a result of the legacy of last summer’s financial turmoil, high inflation and 
procyclical monetary and fiscal policies. Following a strong adjustment in late 
2018, growth is projected to resume later this year and gradually rise thereafter. 

Global trade growth moderated last year amid significant volatility, with a 
strong performance being recorded in the first half of 2018, followed by a 
relatively sharp deceleration. That slowdown reflects weakening global 
manufacturing activity, heightened trade tensions and, more recently, a significant 
deterioration in trade in Asia – particularly in China. According to CPB data, the 
volume of global merchandise imports fell by 1.2% in December in 
three-month-on-three-month terms, signalling a further weakening of global trade 
momentum in the fourth quarter of 2018 (see Chart 2). Moreover, incoming data 
indicate that global trade growth has remained weak in the first quarter of 2019. 

A temporary truce agreed between the United States and China in December 
2018 put a further escalation of trade tensions on hold. Tariffs on USD 200 billion 
of Chinese exports to the United States had originally been set to rise from 10% to 
25% as of 1 January 2019, but that increase was put on hold as a result of the agreed 
truce. While this sent a positive signal, there remains considerable uncertainty as to 
whether the ongoing trade negotiations will lead to a significant de-escalation of trade 
tensions. Meanwhile, President Trump has recently announced that the truce is to be 
extended, citing progress achieved in those trade negotiations, which means that the 
increase in tariff rates remains on hold. A formal trade agreement between the United 
States and China is currently expected to be signed in late March. Risks remain, 
however, as trade tensions could intensify again and the US administration could 
impose new tariffs on imports from other countries. 

ECB Economic Bulletin, Issue 2 / 2019 – Economic and monetary developments 
External environment 

9 

 
 
Chart 2 
Surveys and global trade in goods 

(left-hand scale: three-month-on-three-month percentage changes; right-hand scale: diffusion indices) 

Global merchandise imports (left-hand scale)
Average global merchandise imports, 1991-2018 (left-hand scale)
Global PMI, manufacturing output (right-hand scale)
Global PMI, new export orders (right-hand scale)

2.5

2.0

1.5

1.0

0.5

0.0

-0.5

-1.0

-1.5

60

58

56

54

52

50

48

46

44

2012

2013

2014

2015

2016

2017

2018

2019

Sources: Markit, CPB Netherlands Bureau for Economic Policy Analysis and ECB calculations. 
Note: The latest observations relate to February 2019 for the PMIs and December 2018 for global merchandise imports. 

Following a robust performance last year, global economic growth is projected 
to weaken this year, before stabilising over the medium term. According to the 
March 2019 ECB staff macroeconomic projections, global real GDP growth (excluding 
the euro area) is projected to fall to 3.5% this year, down from 3.7% in 2018. This 
reflects increasing headwinds to global growth, such as weaker global manufacturing 
activity in an environment of high and rising political and policy uncertainty. Over the 
period 2020-21, it is then projected to stabilise at around 3.6% as a result of a 
slowdown in key advanced economies, China’s transition to a weaker growth path and 
an expected pick-up in growth in several key EMEs. As a result of global growth 
headwinds weighing significantly on global trade, growth in euro area foreign demand 
is projected to slow significantly this year, falling to 2.2%, down from 4.0% in 2018. In 
the medium term, euro area foreign demand is expected to grow in line with activity, as 
the impact of the heightened political and policy uncertainty is expected to gradually 
dissipate. Compared with the December 2018 Eurosystem staff macroeconomic 
projections, global GDP growth has been revised slightly downwards for this year. 
Meanwhile, growth in euro area foreign demand has been revised significantly 
downwards for this year and slightly downwards for next year. These revisions reflect 
disappointing data releases in late 2018, coupled with projected declines in demand 
for imports in China and the rest of emerging Asia, as well as in European economies 
outside the euro area. 

Downside risks to global activity have been accumulating. Despite the temporary 
truce between the United States and China, tail risks stemming from an intensification 
of global trade tensions remain high. A sharper slowdown in China’s economy might 
be more difficult to address using policy stimulus, which will also pose challenges in 
the context of the country’s ongoing rebalancing process. Meanwhile, a “no deal” 
Brexit scenario could have highly adverse spillover effects, especially in Europe, and 
elevated geopolitical uncertainties could weigh on global growth. Finally, some EMEs 

ECB Economic Bulletin, Issue 2 / 2019 – Economic and monetary developments 
External environment 

10 

 
 
 
remain vulnerable to the reversal of capital flows, though the risk of significant 
numbers of EMEs suffering acute stress has recently subsided. 

Global price developments 

Oil prices have remained highly volatile. In the final quarter of 2018, oil prices 
declined amid assurances by Saudi Arabia and Russia that they would offset the effect 
on oil supply of the US sanctions against Iran. That downward pressure then 
intensified, with the US government granting temporary waivers for key importers of 
Iranian oil and US crude oil production standing at a high level amid renewed concerns 
about the global economy. Oil prices then recovered somewhat at the turn of the year 
as the OPEC+ agreement to cut production took effect, amid unexpectedly high levels 
of compliance by the various member countries. Looking ahead, oil prices are 
expected to remain broadly stable at this lower trajectory over the projection horizon. 
Consequently, the oil price assumptions underpinning the March 2019 ECB staff 
macroeconomic projections were around 8.6% lower for this year (and 8.2% and 8.0% 
lower for 2020 and 2021 respectively) relative to assumptions underpinning the 
December 2018 Eurosystem staff macroeconomic projections. Since the cut-off date 
for the March projections, however, the price of oil has increased further, standing 
slightly above USD 65 per barrel on 6 March. 

Global inflationary pressures remain contained. In countries belonging to the 
Organisation for Economic Co-operation and Development (OECD), annual headline 
consumer price inflation averaged 2.4% in December 2018, down from 2.7% in the 
previous month, owing to a decline in the contribution of the energy component (see 
Chart 3). Underlying inflation (excluding food and energy) was also down slightly on 
the previous month, standing at 2.2%. Tight labour market conditions across major 
advanced economies have so far translated into moderate wage increases, and the 
pace of underlying inflation remains subdued. Past declines in oil prices are expected 
to weigh on headline inflation going forward. 

ECB Economic Bulletin, Issue 2 / 2019 – Economic and monetary developments 
External environment 

11 

 
 
Chart 3 
OECD consumer price inflation 

(year-on-year percentage changes; percentage point contributions) 

Energy contribution
Food contribution
Contribution of all items except food and energy                                                                
Inflation excluding food and energy
Inflation including all items

3.5

3.0

2.5

2.0

1.5

1.0

0.5

0.0

-0.5

-1.0

-1.5

2012

2013

2014

2015

2016

2017

2018

2019

Sources: OECD and ECB calculations. 
Note: The latest observations are for January 2019. 

Looking ahead, global inflationary pressures are expected to remain contained. 
Growth in the export prices of the euro area’s competitors is expected to weaken 
sharply this year and remain steady over the medium term. This reflects a declining 
positive contribution from the oil price, which is projected to turn negative in the near 
term and will thus outweigh the upward pressures on underlying inflation stemming 
from diminishing spare capacity at the global level. 

ECB Economic Bulletin, Issue 2 / 2019 – Economic and monetary developments 
External environment 

12 

 
 
 
2

Financial developments 

Since the Governing Council’s meeting in December 2018, global long-term risk-free 
rates have declined in the context of a deterioration in the macroeconomic outlook and 
a perceived slowing of the pace of monetary tightening in the United States. The 
prices of euro area risk assets, such as equities and corporate bonds, have recovered 
amid improved risk sentiment, fuelled in part by a greater sense of optimism regarding 
global trade negotiations. In foreign exchange markets, the euro has broadly 
weakened in trade-weighted terms. 

Long-term yields have declined in both the euro area and the United States. 
During the period under review (13 December 2018 to 6 March 2019), the euro area 
ten-year risk-free overnight index swap (OIS) rate fell to 0.48% (down 23 basis points) 
and the GDP-weighted euro area ten-year sovereign bond yield (see Chart 4) fell to 
0.84% (down 23 basis points). In the United States, the ten-year sovereign bond yield 
fell by 22 basis points over that period to stand at 2.71%, while the equivalent yield in 
the United Kingdom fell 8 basis points to stand at 1.22%. Global long-term yields fell 
following communications from the Federal Reserve System which were interpreted 
by the markets as signalling a slower intended pace of monetary policy tightening. In 
addition to possible spillovers from the United States, euro area bond yields also 
reflected a deterioration in the macroeconomic outlook following a number of worse 
than expected macroeconomic data releases, as well as some reappraisal of the 
monetary policy outlook for the euro area as signalled by the short end of the yield 
curve. 

Chart 4 
Ten-year sovereign bond yields 

(percentages per annum; daily data) 

GDP-weighted euro area average                                                                                           
United Kingdom                                                                                     
United States                                                               
Germany

3.5

3.0

2.5

2.0

1.5

1.0

0.5

0.0

-0.5

01/15 04/15 07/15 10/15 01/16 04/16 07/16 10/16 01/17 04/17 07/17 10/17 01/18 04/18 07/18 10/18 01/19

Sources: Thomson Reuters and ECB calculations. 
Notes: The vertical grey line denotes the start of the review period on 13 December 2018. The latest observations are for 6 March 2019. 

Euro area sovereign bond spreads relative to the risk-free OIS rate remained 
broadly unchanged over the review period. Conditions in sovereign bond markets 
were largely stable throughout that period, with the exception of the Italian market, 

ECB Economic Bulletin, Issue 2 / 2019 – Economic and monetary developments 
Financial developments 

13 

 
 
 
 
where the ten-year spread remained volatile (although it recovered to 2.11 percentage 
points at the end of the review period; see Chart 5). Consequently, the spread between 
the GDP-weighted average of euro area ten-year sovereign bond yields and the 
ten-year OIS rate remained stable over the review period, standing at 0.36 percentage 
points on 6 March. 

Chart 5 
Ten-year euro area sovereign bond spreads vis-à-vis the OIS rate 

(percentage points per annum) 

GDP-weighted euro area average                                                                                           
Germany
France
Italy
Spain
Portugal

4.0

3.5

3.0

2.5

2.0

1.5

1.0

0.5

0.0

-0.5

-1.0

01/16

04/16

07/16

10/16

01/17

04/17

07/17

10/17

01/18

04/18

07/18

10/18

01/19

Sources: Thomson Reuters and ECB calculations. 
Notes: The spread is calculated by subtracting the ten-year OIS rate from the ten-year sovereign bond yield. The vertical grey line 
denotes the start of the review period on 13 December 2018. The latest observations are for 6 March 2019. 

The euro overnight index average (EONIA) averaged -0.37% over the review 
period. Excess liquidity was broadly unchanged at around €1,890 billion. For further 
details of developments in liquidity conditions, see Box 2. 

The EONIA forward curve shifted downwards somewhat over the review period. 
The curve is now below zero for all horizons prior to 2022, reflecting market 
expectations of a prolonged period of negative interest rates (see Chart 6). 

ECB Economic Bulletin, Issue 2 / 2019 – Economic and monetary developments 
Financial developments 

14 

 
 
 
Chart 6 
EONIA forward rates 

(percentages per annum) 

6 March 2019
13 December 2018

2.0

1.5

1.0

0.5

0.0

-0.5

2019

2020

2021

2022

2023

2024

2025

2026

2027

Sources: Thomson Reuters and ECB calculations. 

Broad indices of euro area equity prices increased over the review period amid 
a general improvement in risk sentiment. The equity prices of euro area banks and 
non-financial corporations (NFCs) increased by around 7% over the period (with 
similar increases being observed in the United States), reversing a large percentage 
of the declines seen in the fourth quarter of 2018 (see Chart 7). That recovery in equity 
prices reflected a greater sense of optimism regarding the outlook for global trade and 
was underpinned by communications from the Federal Reserve System which were 
interpreted by the markets as signalling a slowdown in the intended pace of monetary 
policy tightening. At the same time, both short and longer-term corporate earnings 
expectations were revised downwards over the review period, reflecting a perceived 
deterioration in the macroeconomic outlook for the euro area.   

Chart 7 
Euro area and US equity price indices 

(index: 1 January 2015 = 100) 

Euro area banks                                                                                                            
Euro area NFCs                                                                                                     
US banks                                                                                   
US NFCs                                                                                                                      

170

150

130

110

90

70

50

01/15 04/15 07/15 10/15 01/16 04/16 07/16 10/16 01/17 04/17 07/17 10/17 01/18 04/18 07/18 10/18 01/19

Sources: Thomson Reuters and ECB calculations. 
Notes: The vertical grey line denotes the start of the review period on 13 December 2018. The latest observations are for 6 March 2019. 

ECB Economic Bulletin, Issue 2 / 2019 – Economic and monetary developments 
Financial developments 

15 

 
 
 
 
Euro area corporate bond spreads declined over the review period, largely 
reflecting an improvement in risk sentiment. Since December the spread between 
the yield on investment-grade NFC bonds and the risk-free rate has declined by 
around 14 basis points to stand at 78 basis points (see Chart 8). Yields on financial 
sector debt have also declined, resulting in the relevant spread falling by around 18 
basis points. Despite these recent declines, both spreads remain above the levels 
observed a year ago. 

Chart 8 
Euro area corporate bond spreads 

(basis points) 

Financial corporate bond spreads
NFC bond spreads

160

140

120

100

80

60

40

20

0
01/15 04/15 07/15 10/15 01/16 04/16 07/16 10/16 01/17 04/17 07/17 10/17 01/18 04/18 07/18 10/18 01/19

Sources: iBoxx indices and ECB calculations. 
Notes: The vertical grey line denotes the start of the review period on 13 December 2018. The latest observations are for 6 March 2019. 

In foreign exchange markets, the euro broadly depreciated in trade-weighted 
terms over the review period (see Chart 9). Indeed, the nominal effective exchange 
rate of the euro, as measured against the currencies of 38 of the euro area’s most 
important trading partners, fell by 1.2% over that period. In bilateral terms, the euro 
weakened against most currencies. In particular, the euro depreciated slightly against 
the US dollar (by 0.6%) and weakened against most other major currencies, including 
the pound sterling (by 4.3%), the Japanese yen (by 2.1%) and the Chinese renminbi 
(by 3.1%). The euro also depreciated vis-à-vis the currencies of most emerging 
markets, while it appreciated against the currencies of most EU Member States 
outside the euro area. 

ECB Economic Bulletin, Issue 2 / 2019 – Economic and monetary developments 
Financial developments 

16 

 
 
 
Chart 9 
Changes in the exchange rate of the euro vis-à-vis selected currencies 

(percentage changes) 

Since 13 December 2018
Since 6 March 2018

EER-38
Chinese renminbi
US dollar
Pound sterling
Swiss franc
Japanese yen
Polish zloty
Czech koruna
Swedish krona
Russian rouble
Turkish lira
South Korean won
Indonesian rupiah
Hungarian forint
Danish krone
Romanian leu
Taiwan dollar
Brazilian real
Indian rupee
Croatian kuna

-10

-5

0

5

10

15

20

25

30

35

Source: ECB. 
Notes: “EER-38” is the nominal effective exchange rate of the euro against the currencies of 38 of the euro area’s most important trading 
partners. All changes have been calculated using the foreign exchange rates prevailing on 6 March 2019. 

ECB Economic Bulletin, Issue 2 / 2019 – Economic and monetary developments 
Financial developments 

17 

 
 
 
 
 
3

Economic activity 

Euro area real GDP growth remained subdued in the fourth quarter of 2018 at 0.2% 
quarter on quarter, driven by a contraction in the industrial sector. Incoming data 
suggest that growth will continue at moderate rates in the near term. Looking ahead 
the expansion of the euro area economy is expected to continue, supported by 
favourable financing conditions, further employment gains and rising wages, as well 
as the ongoing, albeit somewhat slower, expansion in global activity. The March 2019 
ECB staff macroeconomic projections for the euro area expect annual real GDP to 
increase by 1.1% in 2019, 1.6% in 2020 and 1.5% in 2021. Compared with the 
December 2018 Eurosystem staff macroeconomic projections, the outlook for real 
GDP growth has been revised downwards substantially for 2019 and slightly for 2020. 

Growth in the euro area continued at a slow pace in the fourth quarter of 2018. 
While weak growth mainly reflected a contraction in the industrial sector, it 
remained resilient overall. Real GDP increased by 0.2%, quarter on quarter, in the 
fourth quarter of last year, slightly above the rate in the previous quarter (see Chart 
10). Subdued growth in the fourth quarter was driven by a sharp contraction in the 
industrial sector, while services continued to exhibit stronger dynamics. Domestic 
demand and net trade made positive contributions to growth, increasing by 0.4% and 
0.2% respectively, while changes in inventories had a dampening effect, decreasing 
by 0.4%. Overall, output growth in the fourth quarter led to a yearly rise in GDP of 1.8% 
in 2018, down from 2.4% in the previous year. 

Chart 10 
Euro area real GDP, the Economic Sentiment Indicator and the composite output 
Purchasing Managers' Index 

(quarter-on-quarter percentage growth; diffusion index) 

Real GDP (right-hand scale)
ESI (left-hand scale)
Composite output PMI (left-hand scale)

62

59

56

53

50

47

44

1.2

0.9

0.6

0.3

0.0

-0.3

-0.6

2012

2013

2014

2015

2016

2017

2018

2019

Sources: Markit, European Commission and Eurostat. 
Notes: The Economic Sentiment Indicator (ESI) is standardised and rescaled to have the same mean and standard deviation as the 
Purchasing Managers’ Index (PMI). The latest observations are for the fourth quarter of 2018 for real GDP and February 2019 for the ESI 
and the PMI. 

Employment continued to increase in the fourth quarter of 2018, rising by 0.3% 
quarter on quarter (see Chart 11). Most euro area countries saw an increase in 
employment, which was broadly based across sectors. Currently, the level of 
employment stands close to 3.0% above the pre-crisis peak recorded in the first 

ECB Economic Bulletin, Issue 2 / 2019 – Economic and monetary developments 
Economic activity 

18 

 
 
 
 
quarter of 2008. Taking into account the latest increase, there has been cumulative 
growth in employment in the euro area, with 10 million more persons in employment 
than at the time of the trough in the second quarter of 2013. Continued employment 
growth combined with a drop in GDP growth in 2018 has led to a moderation in 
productivity growth, following a modest pick-up in 2017. Empirically, adjustments in 
employment tend to lag behind declines in output. One reason is that longer-term 
employment contracts cannot be adjusted immediately when firms face a slowdown in 
demand. 

Recent short-term labour market indicators continue to point to positive but 
moderating employment growth in the first quarter of 2019. The euro area 
unemployment rate stood at 7.8% in January 2019, unchanged from December 2018, 
and remains at its lowest level since October 2008. Survey indicators point to a further 
slowdown in employment growth in the first quarter of 2019. 

Chart 11 
Euro area employment, PMI assessment of employment and unemployment 

(quarter-on-quarter percentage changes; diffusion index; percentages of the labour force) 

Employment (left-hand scale)
PMI assessment of employment (left-hand scale)
Unemployment rate (right-hand scale)

0.6

0.4

0.2

0.0

-0.2

-0.4

-0.6

13

12

11

10

9

8

7

2012

2013

2014

2015

2016

2017

2018

2019

Sources: Eurostat, Markit and ECB calculations. 
Notes: The Purchasing Managers' Index (PMI) is expressed as a deviation from 50 divided by 10. The latest observations are for the 
fourth quarter of 2018 for employment, February 2019 for the PMI and January 2019 for the unemployment rate. 

Private consumption growth edged up in the fourth quarter of 2018 and is 
expected to regain further momentum in the quarters ahead, as temporary 
dampening effects wane in an environment of continued strengthening of 
households’ labour income. Private consumption increased by 0.2%, quarter on 
quarter, in the fourth quarter of 2018, following somewhat weaker growth in the third 
quarter. The weakness in household expenditure partly reflected temporary 
bottlenecks in the car sector, affecting the consumption of durable goods, and the 
negative effect of energy price increases on household purchasing power. The crude 
oil price (in euro) increased from the fourth quarter of 2017 to the third quarter of 2018, 
which negatively affected consumption growth, in particular of non-durable goods, i.e. 
food and energy. Subsequently, the oil price declined sharply (before recovering 
somewhat in the last two months). This should support consumption of non-durable 
goods in the near term. Furthermore, employment growth strengthened in the fourth 
quarter of 2018 in an environment of robust wage increases. This implies steady 

ECB Economic Bulletin, Issue 2 / 2019 – Economic and monetary developments 
Economic activity 

19 

 
 
 
growth in households’ real disposable income and supports consumer confidence and 
spending. In addition, while financing conditions remain very favourable, households’ 
net worth improved at a strong rate in the third quarter of 2018.   

Latest indicators also suggest some strengthening of private consumption 
momentum in the course of the year ahead. Recent data on retail sales and car 
registrations indicate moderate but steady growth in consumer spending. The volume 
of retail sales increased by 1.4% in January 2019, following a drop in the previous 
month. As a result, sales stood at 1.5% above their average level in the fourth quarter 
of 2018. The indicator for new passenger car registrations posted its fourth 
consecutive increase in January 2019, rising by 4.8% on a monthly basis. This 
confirms previous expectations for a normalisation in car registrations, following the 
volatile developments triggered by the introduction of the new Worldwide Harmonised 
Light Vehicle Test Procedure (WLTP) on 1 September 2018. In addition, consumer 
confidence increased for a second consecutive month in February, halting the 
declining trend observed throughout most of 2018. The latest improvement reflects 
households’ more benign views regarding their past and future financial situation, as 
well as the expected general economic situation and unemployment. Consumer 
confidence remains above its historical average level and is consistent with ongoing 
steady growth in private consumption.   

The ongoing recovery in housing markets is also expected to continue, albeit at 
a slower pace than in 2018. Housing investment increased by 0.6% in the fourth 
quarter of 2018, reflecting the ongoing recovery in many euro area countries and in the 
euro area as a whole. Although growth over 2018 was slower than the buoyant growth 
experienced in 2017, it remains at solid, healthy levels. In line with these 
developments, recent short-term indicators and survey results point to positive, but 
slowing momentum. Construction production in the buildings segment increased by 
0.2%, quarter on quarter, in the fourth quarter of 2018, recovering from -0.8% in the 
third quarter. The European Commission’s construction confidence indicators for the 
past few months point to positive, albeit weakening, momentum in the fourth quarter 
of 2018 and early 2019. The Purchasing Managers’ Index (PMI) for housing activity 
averaged 52.0 in the last quarter of 2018, but decreased to 50.6 in January 2019. 
However, both the PMI indicators and the European Commission’s confidence 
indicators remain clearly above their long-run averages. 

Business investment in the euro area appears to have lost some momentum in 
the second half of 2018, but fundamentals remain supportive. Available country 
data for some of the larger euro area countries point overall to a slowdown in business 
investment growth in the fourth quarter of 2018. The slowdown in business investment 
partly reflects heightened policy uncertainty and financial volatility in some euro area 
countries. Persistent concerns about global trade developments, the possibility of a 
no-deal Brexit and economic weaknesses in China also appear to have adversely 
affected business confidence. The assessment of export order books and production 
expectations in the capital goods sector continued to worsen in January and February 
2019. However, fundamentals remain supportive of business investment. First, 
capacity utilisation remains well above its long-term average, and a large share of 
manufacturing firms report lack of equipment as a factor limiting production. Second, 

ECB Economic Bulletin, Issue 2 / 2019 – Economic and monetary developments 
Economic activity 

20 

 
 
the ECB’s monetary policy measures continue to support favourable financing 
conditions and access to financing for euro area firms. Third, during the recent period 
of recovery, firms have also used profits to build up a sizeable liquidity overhang.   

Euro area trade in goods continued to grow at a subdued pace at the end of 
2018 and is expected to decline further in the near term. According to the latest 
release of data from the national accounts, in the last quarter of 2018 total euro area 
exports increased by 0.9%, while imports increased by 0.5% on a quarterly basis. 
Incoming data on the monthly trade in goods confirm a poor performance by total euro 
area trade in the fourth quarter, mostly driven by intra-euro area trade. In December 
2018 nominal euro area exports contracted by 0.5%, month on month, with intra-euro 
area exports decreasing even more (by 0.9%). Nominal euro area imports saw a slight 
month-on-month increase of 0.4%. Temporary factors, such as the new regulations on 
vehicle emissions tests, have weighed on exports. However, a generalised decrease 
can be observed across all product categories. The United Kingdom, Turkey and 
China continue to drive the weakness in extra-euro area exports observed in the last 
few months of 2018. Looking ahead leading indicators point to a further reduction in 
extra-euro area exports in the coming months. In February 2019 the manufacturing 
PMI for new export orders outside of the euro area was at its lowest since November 
2012 (46.4), and the European Commission’s assessment went more negative 
compared with January. 

The latest survey results have continued to disappoint and suggest that euro 
area growth is moderating in the short term. The European Commission’s 
Economic Sentiment Indicator remained broadly unchanged in February, standing 
above its long-term average. So far in 2019 the average stands at 106.2, below the 
108.9 average for the last quarter of 2018. Although the indicator declined for the 
industry and construction sectors, this was broadly offset by positive sentiment in 
services, the retail sector and households. The composite output PMI increased 
slightly in February, but the average for the first two months of the first quarter of 2019 
stood below that for the previous quarter (51.4 compared with 52.3). 

Despite the current slowdown, over the medium term the broad-based 
economic expansion is expected to regain traction and to continue over the 
period ahead. The ECB’s accommodative monetary policy continues to strengthen 
domestic demand. Ongoing growth in employment and wages should keep private 
consumption high. At the same time business investment is supported by healthy 
domestic demand, favourable financing conditions and improving balance sheets, and 
housing investment remains strong. 

The March 2019 ECB staff macroeconomic projections for the euro area 
forecast annual real GDP to increase by 1.1% in 2019, 1.6% in 2020 and 1.5% in 
2021 (see Chart 12). Compared with the December 2018 Eurosystem staff 
projections, the outlook for real GDP growth has been revised downwards 
substantially for 2019 and slightly for 2020. The risks surrounding the euro area 
outlook remain tilted to the downside. 

ECB Economic Bulletin, Issue 2 / 2019 – Economic and monetary developments 
Economic activity 

21 

 
 
Chart 12 
Euro area real GDP (including projections) 

(quarter-on-quarter percentage changes) 

1.0

0.5

0.0

-0.5

2012

2013

2014

2015

2016

2017

2018

2019

2020

2021

Sources: Eurostat and the article entitled “March 2019 ECB staff macroeconomic projections for the euro area”, published on the ECB’s 
website on 7 March 2019. 
Notes: The ranges shown around the central projections are based on the differences between actual outcomes and previous projections 
carried out over a number of years. The width of the range is twice the average absolute value of these differences. The method used for 
calculating the ranges, involving a correction for exceptional events, is documented in the “New procedure for constructing Eurosystem 
and ECB staff projection ranges”, ECB, December 2009. 

ECB Economic Bulletin, Issue 2 / 2019 – Economic and monetary developments 
Economic activity 

22 

 
 
 
 
 
4

Prices and costs 

According to Eurostat’s flash estimate, euro area annual HICP inflation increased to 
1.5% in February 2019, up from 1.4% in January. While measures of underlying 
inflation continued to move sideways, domestic cost pressures strengthened and 
broadened amid high levels of capacity utilisation and tightening labour markets. 
Looking ahead underlying inflation is expected to increase gradually over the medium 
term, supported by the ECB’s monetary policy measures, the ongoing economic 
expansion and rising wage growth. This assessment is also broadly reflected in the 
March 2019 ECB staff macroeconomic projections for the euro area, which foresee 
annual HICP inflation at 1.2% in 2019, 1.5% in 2020 and 1.6% in 2021 – revised 
downwards across the projection horizon, reflecting in particular the more subdued 
near-term growth outlook. Annual HICP inflation excluding energy and food is 
expected to be 1.2% in 2019, 1.4% in 2020 and 1.6% in 2021. 

Headline inflation increased in February owing to stronger price increases in 
volatile categories. According to Eurostat’s flash estimate, euro area annual HICP 
inflation increased to 1.5% in February 2019, up from 1.4% in January (see Chart 13). 
This reflected higher inflation rates for the more volatile categories, energy and food, 
while HICP inflation excluding energy and food (HICPX) declined. The higher inflation 
rate for energy reflected upward base effects and a moderate increase in oil prices (in 
euro terms). When discussing HICP data since January 2019, one should note that 
two methodological changes have been introduced that imply revisions to the 
historical data (see Box 4 “New features in the Harmonised Index of Consumer Prices: 
analytical groups, scanner data and web-scraping” and Box 5 “A new method for the 
package holiday price index in Germany and its impact on HICP inflation rates”). 

Chart 13 
Contributions of components to euro area headline HICP inflation 

(annual percentage changes; percentage point contributions) 

HICP
Services
Non-energy industrial goods                                                                                                     
Food
Energy

3.5

3.0

2.5

2.0

1.5

1.0

0.5

0.0

-0.5

-1.0

-1.5

2012

2013

2014

2015

2016

2017

2018

2019

Sources: Eurostat and ECB calculations. 
Notes: The latest observations are for February 2019 (flash estimates). Growth rates for 2015 are distorted upwards owing to a 
methodological change (see Box 5 in this issue of the ECB’s Economic Bulletin). 

ECB Economic Bulletin, Issue 2 / 2019 – Economic and monetary developments 
Prices and costs 

23 

 
 
 
 
Measures of underlying inflation continued their recent sideways movement 
after rising from earlier lows. HICP inflation excluding energy and food was 1.0% in 
February, down from 1.1% in January. It thus continued to hover around the 1% rate 
that it reached after rising from its low in mid-2016. The decrease in February reflected 
a decline in services inflation from 1.6% to 1.3%, while non-energy industrial goods 
inflation remained unchanged at 0.3%. Other measures of underlying inflation, 
including the Persistent and Common Component of Inflation indicator (PCCI) and the 
Supercore indicator,1  which are only available for the period to January, also pointed 
to a continuation of the broad sideways movement of recent months (see Chart 14). 
Nonetheless, each of the statistical and model-based measures remained higher than 
their respective lows in 2016. Looking ahead measures of underlying inflation are 
expected to increase gradually, driven by a further strengthening of wage growth and 
the pick-up observed in domestic producer price inflation. 

Chart 14 
Measures of underlying inflation 

(annual percentage changes) 

HICP excluding energy and food
HICP excluding energy, food, travel-related items and clothing
Supercore
PCCI

3.0

2.5

2.0

1.5

1.0

0.5

0.0

2011

2012

2013

2014

2015

2016

2017

2018

2019

Sources: Eurostat and ECB calculations. 
Notes: The latest observations are for February 2019 (flash estimate) for HICP excluding energy and food and for January 2019 for all 
the other measures. The range of measures of underlying inflation consists of the following: HICP excluding energy; HICP excluding 
energy and unprocessed food; HICP excluding energy and food; HICP excluding energy, food, travel-related items and clothing; the 10% 
trimmed mean; the 30% trimmed mean; and the weighted median of the HICP. Growth rates for HICP excluding energy and food for 2015 
are distorted upwards owing to a methodological change (see Box 5 in this issue of the ECB’s Economic Bulletin). 

Price pressures for non-energy industrial goods increased at the later stages of 
the pricing chain, while signals at the earlier stages were mixed. At the very early 
stages, pipeline price pressures have rebounded, as the annual rate of change in oil 
prices and industrial raw material prices (in euro terms) increased markedly in 
February. Global non-energy producer price inflation, in contrast, declined slightly 
further in January. The previous weak price pressures in the early stages have had an 
impact on import price and producer price inflation for intermediate goods, with both 
continuing to decline since August last year. At the later stages, the year-on-year 
growth of import prices for non-food consumer goods increased to 1.3% in January 
from (a revised downwards) 0.4% in December. Also, domestic producer price 
inflation for these goods increased to 1.0% in January 2019, after recording a stable 

1    For more information on these measures of underlying inflation, see Boxes 2 and 3 in the article 
"Measures of underlying inflation for the euro area", Economic Bulletin, Issue 4, ECB, 2018. 

ECB Economic Bulletin, Issue 2 / 2019 – Economic and monetary developments 
Prices and costs 

24 

 
 
 
                                                                    
0.8% growth in year-on-year terms in the previous three months, and remained above 
its long-term average (see Chart 15). Overall, pressures on consumer goods prices 
remained broadly steady in the later stages of the pricing chain, with some weakness 
in the early stages possibly yet to filter through. 

Chart 15 
Producer and import prices 

(annual percentage changes; percentage point contributions) 

NEER-38 (inverted, left-hand scale)
PPI, domestic sales – non-food consumer goods (right-hand scale)
Extra-euro area import prices – non-food consumer goods (right-hand scale)
Global PPI excluding oil (trade-weighted, left-hand scale)

15

10

5

0

-5

-10

-15

6

4

2

0

-2

-4

-6

2012

2013

2014

2015

2016

2017

2018

2019

Sources: Eurostat and ECB calculations. 
Notes: The latest observations are for February 2019 for NEER-38, January 2019 for domestic PPI, import prices, and global PPI. 
“NEER-38” is the nominal effective exchange rate of the euro against the currencies of 38 of the euro area’s most important trading 
partners. “PPI” measures the monthly development of ex-factory selling prices. 

Recent developments in wage growth signal a continued upward trend and 
support the notion of a gradual build-up in domestic cost pressures. Annual 
growth in compensation per employee increased to 2.5% in the third quarter of 2018, 
compared with 2.2% in the second quarter of 2018. Negotiated wage growth was 2.2% 
in the fourth quarter of 2018, up from 2.1% in the third quarter (see Chart 16). More 
generally, wage growth indicators now stand visibly higher than in the first half of 2016. 
These developments are in line with increasing tightness in the labour market. While 
the early phase of the strengthening of the growth in compensation per employee was 
driven mainly by wage drift, most of the momentum in recent quarters came from the 
rise in the annual growth of negotiated wages, which bolstered confidence in the 
positive outlook for wage growth. 

ECB Economic Bulletin, Issue 2 / 2019 – Economic and monetary developments 
Prices and costs 

25 

 
 
 
Chart 16 
Contributions of components of compensation per employee 

(annual percentage changes; percentage point contributions) 

Compensation per employee growth                          
Negotiated wages                                  
Social security contributions                          
Wage drift               

3.0

2.5

2.0

1.5

1.0

0.5

0.0

-0.5

-1.0

-1.5

2012

2013

2014

2015

2016

2017

2018

Sources: Eurostat and ECB calculations. 
Note: The latest observations are for the third quarter of 2018 for compensation per employee and the fourth quarter of 2018 for 
negotiated wage growth. 

Market and survey-based measures of longer-term inflation expectations have 
fallen somewhat. The five-year inflation-linked swap rate five years ahead stood at 
1.51% on 6 March 2019, 13 basis points lower than the level which prevailed in 
mid-December (see Chart 17). The forward profile of market-based measures of 
inflation expectations continues to point towards a prolonged period of low inflation 
with a gradual return to inflation levels below, but close to, 2%. The risk-neutral 
probability of negative average inflation over the next five years implied by inflation 
options markets is negligible, which suggests that markets currently consider the risk 
of deflation to be very low. According to the ECB Survey of Professional Forecasters 
for the first quarter of 2019, longer-term inflation expectations were 1.8%, slightly 
down from 1.9% compared with the previous survey. 

ECB Economic Bulletin, Issue 2 / 2019 – Economic and monetary developments 
Prices and costs 

26 

 
 
 
Chart 17 
Market-based measures of inflation expectations 

(annual percentage changes) 

One-year rate one year ahead                                                                                
One-year rate two years ahead                                                                               
One-year rate four years ahead                                                                    
One-year rate nine years ahead                                                                      
Five-year rate five years ahead

3.0

2.5

2.0

1.5

1.0

0.5

0.0

2012

2013

2014

2015

2016

2017

2018

2019

Sources: Thomson Reuters and ECB calculations. 
Note: The latest observations are for 6 March 2019. 

The March 2019 ECB staff macroeconomic projections expect underlying 
inflation to increase gradually over the projection horizon. On the basis of the 
information available at mid-February, these projections expect headline HICP 
inflation to average 1.2% in 2019, 1.5% in 2020 and 1.6% in 2021, compared with 
1.6%, 1.7% and 1.8% respectively in the December 2018 Eurosystem staff 
macroeconomic projections (see Chart 18). This pattern reflects a sharp decline in 
HICP energy inflation in 2019, which is mainly accounted for by the strong drop in oil 
prices at the end of 2018 and downward base effects related to their prior increase in 
2018. Looking ahead HICP energy prices are expected to grow at subdued rates 
consistent with the relatively flat oil price futures curve. HICP inflation excluding 
energy and food will be on a gradual upward path supported by the more gradual but 
continued economic recovery and the tightening labour market conditions, leading to 
higher domestic cost pressures. HICP inflation excluding energy and food is expected 
to rise from 1.2% in 2019 to 1.4% in 2020 and 1.6% in 2021, representing a downward 
revision of 0.2 percentage point in each year of the projection horizon. 

ECB Economic Bulletin, Issue 2 / 2019 – Economic and monetary developments 
Prices and costs 

27 

 
 
 
Chart 18 
Euro area HICP inflation (including projections) 

(annual percentage changes) 

HICP

Projection range

3.0

2.5

2.0

1.5

1.0

0.5

0.0

-0.5

2012

2013

2014

2015

2016

2017

2018

2019

2020

2021

Sources: Eurostat and the article entitled “March 2019 ECB staff macroeconomic projections for the euro area”, published on the ECB’s 
website on 7 March 2019. 
Notes: The latest observations are for the fourth quarter of 2018 (actual data) and the fourth quarter of 2021 (projection). The ranges 
shown around the central projections are based on the differences between actual outcomes and previous projections carried out over a 
number of years. The width of the ranges is twice the average absolute value of these differences. The method used for calculating the 
ranges, involving a correction for exceptional events, is documented in the “New procedure for constructing Eurosystem and ECB staff 
projection ranges”, ECB, December 2009. The cut-off date for data included in the projections was 21 February 2019 and thus before the 
revision to historical data in the HICP on account of methodological changes. 

ECB Economic Bulletin, Issue 2 / 2019 – Economic and monetary developments 
Prices and costs 

28 

 
 
 
 
 
5

Money and credit 

Money growth and credit dynamics moderated in January 2019. Broad money growth 
has shown strong resilience in the face of the phasing-out of monthly net purchases 
under the asset purchase programme (APP). At the same time, bank funding and 
lending conditions remained favourable. Net issuance of debt securities by NFCs 
declined significantly in the fourth quarter of 2018, against the background of a 
continuing gradual deterioration in bond market conditions that started in late 2017. 

Broad money growth moderated in January, with rates continuing to hover 
around the level observed since March 2018. The annual growth rate of M3 
decreased to 3.8% in January 2019 from 4.1% in December 2018 (see Chart 19). This 
development shows the resilience of M3 growth in the face of the declining mechanical 
contribution of APP purchases. M3 growth has eased since late 2017, coinciding with 
the phasing-out of net asset purchases. This in turn implies that the APP had a smaller 
positive impact on M3 growth. The narrow money aggregate M1, which includes the 
most liquid components of M3, continued to make a large contribution to broad money 
growth, despite declining to 6.2% in January. Money growth continued to receive 
support from sustained economic expansion and the low opportunity cost of holding 
the most liquid instruments in an environment of very low interest rates. 

Chart 19 
M3, M1 and loans to the private sector 

(annual percentage changes; adjusted for seasonal and calendar effects) 

M3
M1
Loans to the private sector

12

10

8

6

4

2

0

-2

-4

2012

2013

2014

2015

2016

2017

2018

2019

Source: ECB. 
Notes: Loans are adjusted for loan sales, securitisation and notional cash pooling. The latest observation is for January 2019. 

Overnight deposits remained the main contributor to M3 growth. The annual 
growth rate of overnight deposits decreased to 6.4% in January, reflecting the 
moderation in the annual growth of overnight deposits held by NFCs, while the 
expansion of overnight deposits held by households remained stable. Moreover, 
steady growth in currency in circulation speaks against any large-scale substitution of 
cash for deposits in an environment of very low or negative interest rates for the euro 
area as a whole. Short-term deposits other than overnight deposits (i.e. M2 minus M1) 
continued to make a negative contribution to M3 growth, although the spread between 
the interest rates on short-term time deposits and overnight deposits has stabilised 

ECB Economic Bulletin, Issue 2 / 2019 – Economic and monetary developments 
Money and credit 

29 

 
 
 
 
since late 2017. Marketable instruments (i.e. M3 minus M2), which are currently 
growing at a slow pace given the low remuneration of these instruments, had a neutral 
overall impact on M3 growth. 

Credit to the private sector remained the largest driver of broad money growth 
from a counterpart perspective (see Chart 20). In the context of the 
aforementioned phasing-out of monthly net purchases under the APP, the positive 
contribution to M3 growth from general government securities held by the Eurosystem 
decreased further (see the red parts of the bars in Chart 20). This has been largely 
offset by a moderate increase in the contribution from credit to the private sector since 
late 2017 (see the blue parts of the bars in Chart 20). While private credit remained the 
main source of money creation, the decline in the contribution of the APP has recently 
been replaced by external monetary flows (see the yellow parts of the bars in Chart 
20) and credit to the general government (see the light green parts of the bars in Chart 
20). The increasing contribution from net external assets in part reflects investors’ 
preferences for euro area assets in the context of a greater aversion to risk linked to 
higher uncertainty. Moreover, purchases of government securities by commercial 
banks have increasingly stabilised M3 in recent months. These developments mark an 
ongoing shift towards more self-sustained sources of money creation. 

Chart 20 
M3 and its counterparts 

(annual percentage changes; contributions in percentage points; adjusted for seasonal and calendar effects) 

M3
Net external assets
General government debt securities held by the Eurosystem
Credit to general government from MFIs excluding the Eurosystem
Credit to the private sector
Inflows from longer-term financial liabilities and other counterparts

10

8

6

4

2

0

-2

-4

-6

2013

2014

2015

2016

2017

2018

2019

Source: ECB. 
Notes: Credit to the private sector includes MFI loans to the private sector and MFI holdings of debt securities issued by the euro area 
private non-MFI sector. As such, it also covers purchases by the Eurosystem of non-MFI debt securities under the corporate sector 
purchase programme. The latest observation is for January 2019. 

Credit dynamics moderated in January. The annual growth rate of MFI loans to the 
private sector (adjusted for loan sales, securitisation and notional cash pooling) 
declined to 3.0% in January from 3.4% in December (see Chart 19). This was owing to 
a strong decline in the annual growth rate of loans to NFCs to 3.3% in January from 
3.9% in December. Loan growth for firms, which was accompanied by considerable 
heterogeneity across countries, matches historical patterns and can be explained by 
the slowdown in real GDP since early 2018 (see Chart 21). At the same time, the 

ECB Economic Bulletin, Issue 2 / 2019 – Economic and monetary developments 
Money and credit 

30 

 
 
 
annual growth rate of loans to households remained stable at 3.2% in January, also in 
a context of pronounced cross-country heterogeneity (see Chart 22). Lending to the 
private sector continued to be supported by favourable financing conditions, robust 
growth in business investment, improvements in labour markets, mature housing 
markets and growth in both residential investment and private consumption. In 
addition, banks have made progress in consolidating their balance sheets, improving 
profitability and reducing non-performing loans, although the level of such loans has 
remained high in some countries. 

Chart 21 
MFI loans to NFCs in selected euro area countries 

(annual percentage changes) 

Euro area
Germany
France
Italy
Spain
Cross-country dispersion

20

15

10

5

0

-5

-10

-15

2012

2013

2014

2015

2016

2017

2018

2019

Source: ECB. 
Notes: Loans are adjusted for loan sales, securitisation and notional cash pooling. The cross-country dispersion is calculated on the 
basis of minimum and maximum values using a fixed sample of 12 euro area countries. The latest observation is for January 2019. 

ECB Economic Bulletin, Issue 2 / 2019 – Economic and monetary developments 
Money and credit 

31 

 
 
 
Chart 22 
MFI loans to households in selected euro area countries 

(annual percentage changes) 

Euro area
Germany
France
Italy
Spain
Cross-country dispersion

10

5

0

-5

-10

2012

2013

2014

2015

2016

2017

2018

2019

Source: ECB. 
Notes: Loans are adjusted for loan sales and securitisation. The cross-country dispersion is calculated on the basis of minimum and 
maximum values using a fixed sample of 12 euro area countries. The latest observation is for January 2019. 

Bank funding conditions remained favourable by historical standards. In 
January, the composite cost of debt financing for euro area banks remained stable, 
after having progressively increased since the beginning of 2018 (see Chart 23). This 
development reflected unchanged bank bond yields in the euro area as a whole. 
Heterogeneity across countries was considerable, given that political uncertainty was 
high and banks’ access to wholesale funding was uneven. At the same time, the costs 
of deposit funding remained unchanged. The repercussions of higher costs of funding 
through the issuance of debt securities on the overall composite cost of funding for 
banks have been rather limited owing to this type of funding’s limited importance in 
banks’ funding structures. Overall, therefore, bank funding conditions have remained 
favourable, reflecting the ECB’s accommodative monetary policy stance and the 
strengthening of banks’ balance sheets. Moreover, the new series of TLTROs will help 
to ensure that bank lending conditions remain favourable going forward. 

ECB Economic Bulletin, Issue 2 / 2019 – Economic and monetary developments 
Money and credit 

32 

 
 
 
Chart 23 
Banks’ composite cost of debt financing 

(composite cost of deposit and unsecured market-based debt financing; percentages per annum) 

Euro area
Germany
France
Italy
Spain

6

5

4

3

2

1

0

2012

2013

2014

2015

2016

2017

2018

2019

Sources: ECB, Markit iBoxx and ECB calculations. 
Notes: The composite cost of deposits is calculated as an average of new business rates on overnight deposits, deposits with an agreed 
maturity and deposits redeemable at notice, weighted by their corresponding outstanding amounts. The latest observation is for January 
2019. 

Bank lending rates for NFCs and households remained close to their historical 
lows. In January 2019, the composite bank lending rate for NFCs (see Chart 24) 
remained broadly stable at 1.63%, close to the historical low of 1.62% seen in May 
2018. The composite bank lending rate for housing loans remained broadly stable in 
January at 1.82%, also close to its historical low in December 2016 (see Chart 25). 
Composite bank lending rates for loans to NFCs and households have fallen 
significantly and by more than market reference rates since the ECB’s credit easing 
measures were announced in June 2014, while heterogeneity across countries 
remained considerable. Between May 2014 and January 2019 composite lending 
rates on loans to NFCs and households fell by around 130 and 110 basis points, 
respectively. The reduction in bank lending rates for loans to NFCs, as well as for 
loans to small firms (assuming that very small loans of up to €0.25 million are primarily 
granted to small firms), was particularly significant in those euro area countries that 
were most exposed to the financial crisis. This indicates a more uniform transmission 
of monetary policy to bank lending rates across euro area countries and firm sizes. 

ECB Economic Bulletin, Issue 2 / 2019 – Economic and monetary developments 
Money and credit 

33 

 
 
 
Chart 24 
Composite lending rates for NFCs 

(percentages per annum; three-month moving averages) 

Euro area
Germany
France
Italy
Spain
Cross-country standard deviation (right-hand scale)

5

4

3

2

1

0

2.0

1.6

1.2

0.8

0.4

0.0

2012

2013

2014

2015

2016

2017

2018

2019

Source: ECB. 
Notes: The indicator for the total cost of bank borrowing is calculated by aggregating short and long-term rates using a 24-month moving 
average of new business volumes. The cross-country standard deviation is calculated using a fixed sample of 12 euro area countries. 
The latest observation is for January 2019. 

Chart 25 
Composite lending rates for house purchase 

(percentages per annum; three-month moving averages) 

Euro area
Germany
France
Italy
Spain
Cross-country standard deviation (right-hand scale)

5

4

3

2

1

0

1.0

0.8

0.6

0.4

0.2

0.0

2012

2013

2014

2015

2016

2017

2018

2019

Source: ECB. 
Notes: The indicator for the total cost of bank borrowing is calculated by aggregating short and long-term rates using a 24-month moving 
average of new business volumes. The cross-country standard deviation is calculated using a fixed sample of 12 euro area countries. 
The latest observation is for January 2019. 

The annual flow of total external financing to euro area NFCs is estimated to 
have stabilised in the fourth quarter of 2018. Bank lending growth was solid, 
supported by still-favourable credit standards and a further decline in the relative cost 
of bank lending. By contrast, net issuance of securities was negative over the quarter, 
reflecting the moderation of economic growth, lower values of mergers and 

ECB Economic Bulletin, Issue 2 / 2019 – Economic and monetary developments 
Money and credit 

34 

 
 
 
 
acquisitions as well as increases in the cost of market-based financing and 
uncertainty, along with other factors. These developments are, however, becoming 
increasingly heterogeneous across countries.   

In the fourth quarter of 2018 the net issuance of debt securities by NFCs was 
significantly negative amidst a continuing increase in the cost of debt issuance 
during that time. The weakness in net issuance activity in the last quarter of 2018 can 
be partly attributed to the seasonal pattern of the series, but from a more medium-term 
perspective the annual net issuance flows for December 2018 reached the lowest 
reading since May 2016 (see Chart 26), and remain in line with the declining trend that 
started at the beginning of 2017. Market data suggest that the net issuance of debt 
securities by investment-grade issuers increased in the first months of 2019, while it 
remained virtually zero in the high-yield segment. The net issuance of listed shares 
was basically zero in the fourth quarter of 2018. 

Chart 26 
Net issuance of debt securities and quoted shares by euro area NFCs 

(annual flows in EUR billions) 

Debt securities
Quoted shares

125

100

75

50

25

0

-25

12/11

06/12

12/12

06/13

12/13

06/14

12/14

06/15

12/15

06/16

12/16

06/17

12/17

06/18

12/18

Source: ECB. 
Notes: Monthly figures based on a 12-month rolling period. The latest observation is for December 2018. 

In December 2018, the cost of financing for NFCs edged up further. In December 
the overall nominal cost of external financing for NFCs, comprising bank lending, debt 
issuance in the market and equity finance, stood at 4.8%, up from 4.7% in November. 
The current cost of external financing surpasses the historical low of August 2016 by 
57 basis points but remains substantially lower than the level seen in mid-2014, when 
market expectations regarding the introduction of the public sector purchase 
programme began to emerge. 

ECB Economic Bulletin, Issue 2 / 2019 – Economic and monetary developments 
Money and credit 

35 

 
 
 
6 

Fiscal developments 

A mildly expansionary euro area fiscal stance and the operation of automatic 
stabilisers are providing support to economic activity. At the same time, countries 
where government debt is high need to continue rebuilding fiscal buffers. All countries 
should continue to increase efforts to achieve a more growth-friendly composition of 
public finances. Likewise, the transparent and consistent implementation of the 
European Union’s fiscal and economic governance framework over time and across 
countries remains essential to bolster the resilience of the euro area economy. 

Following an improvement last year, the euro area general government budget 
deficit is projected to deteriorate in 2019 and remain broadly stable in the 
following two years.2  Based on data for 2018 that are still incomplete, the general 
government deficit ratio for the euro area is estimated to have stood at 0.5% of GDP, 
compared with 1.0% of GDP in 2017. The fall in 2018 was mainly the result of 
favourable cyclical conditions and declining interest payments. The improvement is 
likely to be reversed this year on account of a significantly lower cyclically adjusted 
primary balance. The higher deficit is also expected to persist over the next two years 
(see Chart 27). 

The outlook for the euro area general government deficit for the next two years 
has deteriorated compared with the December 2018 Eurosystem staff 
macroeconomic projections. The higher deficit is partly the outcome of a lower 
primary balance reflecting policies that are more expansionary than previously 
expected in several of the largest euro area countries. It is also the result of a lower 
cyclical component given that the macroeconomic outlook has been revised 
downwards. 

2    See the “March 2019 ECB staff macroeconomic projections for the euro area”, published on the ECB’s 

website on 7 March 2019.   

ECB Economic Bulletin, Issue 2 / 2019 – Economic and monetary developments 
Fiscal developments 

36 

 
 
                                                                    
Chart 27 
Budget balance and its components 

(percentage of GDP) 

Cyclically adjusted primary balance (net of financial sector support)
Cyclical component                                             
Interest payments                                     
Budget balance                                                       
Financial sector support

1.5

1.0

0.5

0.0

-0.5

-1.0

-1.5

-2.0

-2.5

2017

2018

2019

2020

2021

Sources: ECB and March 2019 ECB staff macroeconomic projections. 
Notes: The data refer to the aggregate general government sector of the euro area. 

The aggregate fiscal stance for the euro area is assessed to have been broadly 
neutral in 2018 but is projected to be mildly expansionary from 2019 onwards.3 
This profile is mainly driven by cuts to direct taxes and social security contributions in 
both Germany and France but it is also a result of relatively dynamic expenditure 
growth in several countries. 

The decline in the euro area aggregate public debt-to-GDP ratio is projected to 
continue at a slower pace. According to the March 2019 ECB staff macroeconomic 
projections, the aggregate general government debt-to-GDP ratio in the euro area is 
expected to decline from 86.8% of GDP in 20174  to 81.1% of GDP in 2021. The 
projected reduction in government debt is supported by both the negative interest 
rate-growth rate differential5  and continued primary surpluses (see Chart 28), 
although deficit-debt adjustments are expected to offset some of these effects. Over 
the projection horizon, the debt ratio is projected to fall or increase only slowly in all 
euro area countries but will continue to far exceed the reference value of 60% of GDP 
in a number of countries. Compared with the December 2018 projections, the decline 
in the aggregate euro area debt-to-GDP ratio is expected to be more subdued over the 
whole horizon. This is mainly due to the increasing interest-growth differential in 2019 
reflecting the downward revision of GDP growth, as well as lower primary balances. 

3    The fiscal stance reflects the direction and size of the stimulus from fiscal policies to the economy, 

beyond the automatic reaction of public finances to the business cycle. It is measured here as the change 
in the cyclically adjusted primary balance ratio net of government support to the financial sector. For more 
details on the concept of the euro area fiscal stance, see the article entitled “The euro area fiscal stance”, 
Economic Bulletin, Issue 4, ECB, 2016. 

4    As the projections usually take the most recent data revisions into account, there might be discrepancies 

compared with the latest validated Eurostat data. 

5    For more information, see the box entitled “Interest rate-growth differential and government debt 

dynamics” in this issue of the Economic Bulletin. 

ECB Economic Bulletin, Issue 2 / 2019 – Economic and monetary developments 
Fiscal developments 

37 

 
 
 
                                                                    
Chart 28 
Drivers of change in public debt 

(percentage points of GDP) 

Primary balance (-)
Deficit-debt adjustment
Interest-growth differential
Consolidated gross debt

Cumulative 
change

2

1

0

-1

-2

-3

-4

-5

-6

-7

-8

2017

2018

2019

2020

2021

2018-21

Sources: ECB and March 2019 ECB staff macroeconomic projections. 
Notes: The data refer to the aggregate general government sector of the euro area. 

Countries need to continue their fiscal policies in full compliance with the 
Stability and Growth Pact. This may include allowing automatic stabilisers to 
operate where appropriate. At the same time, countries where government debt is 
high need to continue rebuilding fiscal buffers. All countries should continue to 
increase efforts to achieve a more growth-friendly composition of public finances. 

ECB Economic Bulletin, Issue 2 / 2019 – Economic and monetary developments 
Fiscal developments 

38 

 
 
 
 
Boxes 

1

Characterising the current expansion across non-euro 
area advanced economies: where do we go from here? 

Prepared by Alina Bobasu, Mariarosaria Comunale, Ramon 
Gomez-Salvador and Lucia Quaglietti 

This box looks at the current phase of the business cycle in major non-euro 
area advanced economies with a view to assessing the factors behind the 
transition to weaker growth. 6  Although growth in non-euro area advanced 
economies has been slowing, signals of a severe slowdown or recession appear 
contained at the current juncture and our baseline scenario remains one of a modest 
economic deceleration.   

From a historical perspective, the current expansion in non-euro area advanced 
economies has been relatively unusual in terms of both length and pace. 
Following the global financial crisis, the recovery in activity started in a context of very 
large output gaps. The global expansion has now entered its tenth year and is on track 
to become the longest on record. Seen in a historical perspective, it has also been 
comparatively shallow, with cumulated GDP growth of less than 20% since 2009, 
which is well below the levels seen in previous expansions (see Chart A). The 
sluggishness of the recovery might be consistent with the view that potential growth 
has fallen in the past decade. 

Chart A 
Amplitude, duration and slope of expansions in non-euro area advanced economies   

(left-hand scale: percentages and quarters; right-hand scale: percentages) 

Amplitude (left-hand scale)
Duration (left-hand scale, quarters)
Slope (right-hand scale)

50

40

30

20

10

0

1.2

1.0

0.8

0.6

0.4

0.2

1970-74

1975-80

1980-81

1982-90

1991-2001

2002-08

2009-18

Source: ECB staff. 
Notes: Advanced economies’ cycles are obtained as a weighted average of the countries in the sample. See the first footnote in this box 
for country coverage. “Amplitude” refers to the percentage change in real GDP from trough to the next peak in an expansion; “duration” 
is defined as the number of quarters from trough to the next peak in an expansion; and “slope” is the ratio of amplitude to duration. 

6    The analysis is based on the following non-euro area countries: United States (US), Japan (JP), United 
Kingdom (UK), Canada (CA), Switzerland (CH), Sweden (SE), Denmark (DK), Norway (NO) and 
Australia (AU). 

ECB Economic Bulletin, Issue 2 / 2019 – Boxes 
Characterising the current expansion across non-euro area advanced economies: where do 
we go from here? 

39 

 
 
 
 
                                                                    
A more in-depth analysis of the dynamics of the business cycle requires a more 
refined definition of its various phases. For the purpose of this box, we combine 
two approaches. First we detect recessions relying on the pure technical definition, i.e. 
a recession implies at least two quarters of decline in the level of real GDP, by adopting 
the Bry-Boschan algorithm. 7  This is referred to in the literature as the “classical” 
approach to business cycle dating.8  Once the dates of recessions have been 
established, we use the cyclical component of GDP, obtained by de-trending real GDP 
levels using estimates of potential GDP growth, to distinguish different phases of 
cyclical expansions.9  We separate movements in the GDP cycle into four additional 
phases according to whether actual GDP is expanding faster or slower than potential, 
and whether the output gap is in positive or negative territory, imposing again a 
minimum of two consecutive quarters in defining each phase.10,11  Chart B presents an 
example of the five phases based on the aggregate of non-euro area advanced 
economies. 

The second step allows us to provide a more refined characterisation of the 
different phases of expansions. Specifically, it allows us to take into account the 
implications stemming from a declining pace of potential growth. By combining 
recessions as identified in step 1 (red-shaded area in Chart B) with the additional 
cyclical phases detected in step 2 (light green, dark green, yellow and orange shaded 
areas) we separate “hard landings”, i.e. outright recessions, from “soft landings”, i.e. 
periods in which economic activity decelerates relative to potential, with the output 
gaps falling into negative territory at times, but without entering a recession.12 

7    See Bry, G. and Boschan, C., “Cyclical Analysis of Time Series: Selected Procedures and Computer 

Programs”, NBER Books, National Bureau of Economic Research, 1971. This method provides a good 
approximation and has been widely used in empirical studies of expansions and recessions. See, for 
example, for G7 and EU countries, Artis, M.J., Kontolemis, Z.G. and Osborn, D.R., “Business Cycles for 
G7 and European Countries”, The Journal of Business, Vol. 70, No 2, April 1997, pp. 249-279; and, for 
the United States, Stock, J.H. and Watson, M.W., “Estimating turning points using large data sets”, 
Journal of Econometrics, Vol. 178, Part 2, January 2014, pp. 368-381. The results are broadly 
comparable with the dating reported by the Centre for Economic Policy Research (CEPR) and the NBER 
for the euro area and the United States respectively, both of which use more comprehensive methods 
that include not only quarterly GDP but also key GDP components, employment and industrial activity, 
among other variables. Recessions are defined as two consecutive quarters of decline in the level of 
GDP. 

8    See Burns, A.F. and Mitchell, W.C., “Measuring Business Cycles”, NBER Books, National Bureau of 

Economic Research, December 1946. 

9    For a similar approach to business cycle dating, see the box entitled “The measurement and prediction of 

the euro area business cycle”, Monthly Bulletin, ECB, May 2011. 

10    The analysis in this box and the ensuing dating of the phases of the business cycle are sensitive to the 
estimates of potential GDP. IMF and ECB estimates of potential growth are utilised. Annual data have 
been interpolated by cubic spline to obtain quarterly frequencies. Estimates of potential growth for the 
period before 1980 are obtained through simple de-trending techniques. 

11    The OECD Composite Leading Indicators follow an alternative approach that focuses on anticipating 

turning points in economic activity. 

12    As a result of the two-step approach, recession phases could follow any of the four expansionary phases, 

although in practice they mostly follow phase C and, to a lesser extent, phases B and D. 

ECB Economic Bulletin, Issue 2 / 2019 – Boxes 
Characterising the current expansion across non-euro area advanced economies: where do 
we go from here? 

40 

 
 
                                                                    
Chart B 
Non-euro area advanced economies business cycle 

(left-hand scale: index (in logs); right-hand scale: percentages) 

GDP level (left-hand scale)
Output gap (right-hand scale)
Recession
Phase A
Phase B
Phase C
Phase D

0.35

0.30

0.25

0.20

0.15

0.10

0.05

0.00

10

8

6

4

2

0

-2

-4

-6

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Source: ECB staff. 
Notes: The chart shows a periodisation of five phases of the business cycle for advanced economies. In a first step we rely on the 
classical approach to business cycle dating in order to separate expansions from recessions, adopting the Bry-Boschan algorithm 
applied to real GDP levels (in logs). The second step separates movements in the cyclical component of real GDP into four phases. 
Phase A refers to periods in which the output gap is still negative but GDP is growing faster than potential. Phase B indicates the case in 
which the output gap is positive with GDP growing faster than potential. In phase C, a positive output gap is associated with GDP 
expanding slower than potential. Lastly, phase D characterises periods in which the output gap is negative and GDP is expanding slower 
than potential. The latest observation is for the fourth quarter of 2018. 

This methodology suggests that in several key advanced economies the output 
gap is currently in positive territory, with activity still expanding faster than 
potential (see Chart C). Our estimates suggest that in the United States, Japan, 
Canada, Switzerland and Denmark output gaps are positive with activity still 
expanding at a faster pace than potential. Sweden, however, might have already 
transitioned into a phase in which activity is increasing at a pace below potential. By 
contrast, the recovery in the United Kingdom, Norway and Australia appears to have 
endured since the Great Recession, but some spare capacities still prevail in these 
economies. 

ECB Economic Bulletin, Issue 2 / 2019 – Boxes 
Characterising the current expansion across non-euro area advanced economies: where do 
we go from here? 

41 

 
 
 
Chart C 
A periodisation of business cycles for selected advanced economies 

(phases) 

Recession
Phase  A
Phase  B
Phase  C
Phase  D

US

JP

UK

CA

CH

SE

DK

NO

AU

0
7
9
1

2
7
9
1

4
7
9
1

6
7
9
1

8
7
9
1

0
8
9
1

2
8
9
1

4
8
9
1

6
8
9
1

8
8
9
1

0
9
9
1

2
9
9
1

4
9
9
1

6
9
9
1

8
9
9
1

0
0
0
2

2
0
0
2

4
0
0
2

6
0
0
2

8
0
0
2

0
1
0
2

2
1
0
2

4
1
0
2

6
1
0
2

8
1
0
2

Source: ECB staff calculations. 
Notes: Recessions are detected using the Bry-Boschan algorithm applied to real GDP levels (in logs). Phase A refers to periods in which 
the output gap is still negative but GDP is growing faster than potential. Phase B indicates the case in which the output gap is positive 
with GDP growing faster than potential. In phase C, a positive output gap is associated with GDP expanding slower than potential. Lastly, 
phase D characterises periods in which the output gap is negative and GDP is expanding slower than potential. The latest observation is 
for the fourth quarter of 2018. 

Past experience suggests that economies can operate above potential for quite 
some time, with economies more likely to experience a soft landing rather than 
outright recessions. Chart C indicates that in economies with positive output gaps 
GDP can grow above potential for about two to three years on average before the 
cycle turns. Moreover, in most cases, economies gradually slow down and experience 
a soft landing. Historical (unconditional) probabilities of transitioning between different 
phases of the business cycle suggest that, following a period in which the output gap is 
positive and growth is expanding at a pace above potential (phase B), about one-third 
of countries experience a recession, while two-thirds transition to a phase of more 
modest growth as activity decelerates below potential growth. 

Our baseline scenario remains one of a modest economic deceleration in 
advanced economies. After peaking in 2017, GDP growth in advanced economies 
started to slow in the first half of 2018, and survey-based indicators point to a further 
moderation at the turn of the year. The slowdown in manufacturing activity appears to 
be particularly pronounced, probably accentuated by growing uncertainties weighing 
on global investment and activity. The latest update of the IMF World Economic 
Outlook suggests that overall growth in the advanced economies will gradually decline 
from 2.3% in 2018 to 2.0% in 2019 and further to 1.7% in 2020, which is broadly in line 
with the March 2019 ECB staff macroeconomic projections.13   

Overall, although growth in non-euro area advanced economies has been 
slowing, signals of a severe slowdown or recession appear contained. This 
notwithstanding, downside risks abound and have increased lately. An exacerbation of 

13    See “March 2019 ECB staff macroeconomic projections for the euro area”, published on the ECB’s 

website on 7 March 2019. 

 
                                                        
trade tensions, for example, or a “no deal” Brexit scenario would negatively affect 
prospects for advanced economies. 

2

Liquidity conditions and monetary policy operations in the 
period from 31 October 2018 to 29 January 2019 

Prepared by Toshi Nakamura and Pamina Karl 

This box describes the ECB’s monetary policy operations during the seventh 
and eighth reserve maintenance periods of 2018, which ran from 31 October 
2018 to 18 December 2018 and from 19 December 2018 to 29 January 2019 
respectively. Throughout this period the interest rates on the main refinancing 
operations (MROs), the marginal lending facility and the deposit facility remained 
unchanged at 0.00%, 0.25% and −0.40% respectively. In parallel, the Eurosystem 
continued to purchase public sector securities, covered bonds, asset-backed 
securities and corporate sector securities as part of its asset purchase programme 
(APP), with a target of €15 billion of net purchases on average per month until the end 
of December 2018. It then entered the reinvestment phase on 1 January 2019. 

Liquidity needs 

In the period under review, the average daily liquidity needs of the banking 
system, defined as the sum of net autonomous factors and reserve 
requirements, stood at €1,511.5 billion, an increase of €51.8 billion compared 
with the previous review period (i.e. the fifth and sixth maintenance periods of 
2018). This rise in liquidity needs was largely the result of an increase in net 
autonomous factors, which grew on average by €51.4 billion to €1,384.5 billion during 
the review period, while minimum reserve requirements increased on average by 
€0.4 billion to €127.1 billion. 

The growth in net autonomous factors was due to an increase in 
liquidity-absorbing factors and a decrease in liquidity-providing factors. Among 
liquidity-absorbing factors, banknotes in circulation and other autonomous factors 
rose on average by €16.8 billion to €1,210 billion and by €18.5 billion to €730.7 billion 
respectively, partly offset by a decline in government deposits of €23.3 billion to 
€236.1 billion. The most significant contribution to the growth in net autonomous 
factors came from a decrease in net assets denominated in euro, which declined on 
average by €46.7 billion to €153.5 billion. Eurosystem liabilities to non-euro area 
residents in euro increased on average by €50.5 billion, reflecting a more pronounced 
seasonal pattern at the year-end than at the quarter-end during the previous review 
period14  and thus contributing negatively to the (liquidity-providing) average net 
assets denominated in euro. 

14    Eurosystem liabilities to non-euro area residents in euro mainly consist of euro-denominated deposits in 
accounts held by non-euro area central banks with the Eurosystem. Quarter-ends, and to a lesser extent 
month-ends, are typically affected by increases in these deposits, as commercial banks are more 
reluctant to accept cash, either in the unsecured or secured market, ahead of balance sheet reporting 
dates. On 31 December 2018 liabilities to non-euro area residents denominated in euro increased to 
€459.3 billion, compared to an average of €315.3 billion during the seventh and eighth maintenance 
periods. This implied a more pronounced effect than that observed on 30 September 2018, when these 
liabilities increased to €301.7 billion, compared to an average of €264.7 billion in the fifth and sixth 
maintenance periods. 

ECB Economic Bulletin, Issue 2 / 2019 – Boxes 
Liquidity conditions and monetary policy operations in the period from 31 October 2018 to 29 
January 2019 

44 

 
 
 
                                                                    
Table A 
Eurosystem liquidity conditions 

Liabilities – liquidity needs 

(averages; EUR billions) 

Current review period: 
31 October 2018 to 29 January 2019 

Seventh and 
eighth 
maintenance 
periods 

Seventh 
maintenance 
period: 
31 October to 
18 December 

Eighth 
maintenance 
period: 
19 December to 
29 January 

Previous review 
period: 
1 August 2018 to 
30 October 2018 

Fifth and sixth 
maintenance 
periods 

Autonomous liquidity factors 

2,176.8 

(+12.0) 

2,162.5 

(-19.3) 

2,193.4 

(+30.9) 

2,164.8 

(+40.9) 

Banknotes in circulation 

1,210.0 

(+16.8) 

1,202.4 

(+8.1) 

1,218.8 

(+16.4) 

1,193.1 

(+16.6) 

Government deposits 

236.1 

(-23.3) 

240.2 

(-43.0) 

231.3 

(-8.9) 

259.4 

(+20.0) 

Other autonomous factors 

730.7 

(+18.5) 

719.9 

(+15.5) 

743.3 

(+23.4) 

712.2 

(+4.3) 

Current accounts 

1,357.6 

(-0.5) 

1,379.4 

(+10.4) 

1,332.1 

(-47.2) 

1,358.0 

(+26.2) 

Monetary policy instruments 

764.9 

(-14.8) 

762.7 

(+4.3) 

767.4 

(+4.6) 

779.7 

(-0.4) 

Minimum reserve requirements1 

127.1 

(+0.4) 

126.8 

(+0.1) 

127.4 

(+0.6) 

126.7 

(+2.5) 

Deposit facility 

637.8 

(-15.2) 

635.9 

(+4.2) 

640.0 

(+4.0) 

653.0 

(-2.9) 

Liquidity-absorbing fine-tuning operations 

0.0 

(+0.0) 

0.0 

(+0.0) 

0.0 

(+0.0) 

0.0 

(+0.0) 

ECB Economic Bulletin, Issue 2 / 2019 – Boxes 
Liquidity conditions and monetary policy operations in the period from 31 October 2018 to 29 
January 2019 

45 

 
 
 
 
Assets – liquidity supply 

(averages; EUR billions) 

Current review period: 
31 October 2018 to 29 January 2019 

Seventh and 
eighth 
maintenance 
periods 

Seventh 
maintenance 
period:   
31 October to 
18 December 

Eighth 
maintenance 
period: 
19 December to 
29 January 

Previous review 
period: 
1 August 2018 to 
30 October 2018 

Fifth and sixth 
maintenance 
periods 

Autonomous liquidity factors 

792.7 

(-39.2) 

802.5 

(-23.0) 

781.3 

(-21.2) 

831.9 

(+10.9) 

Net foreign assets 

639.2 

(+7.4) 

625.1 

(-0.1) 

655.8 

(+30.7) 

631.8 

(+1.9) 

Net assets denominated in euro 

153.5 

(-46.7) 

177.4 

(-22.9) 

125.5 

(-51.9) 

200.1 

(+8.9) 

Monetary policy instruments 

3,379.8 

(+35.7) 

3,375.6 

(+18.1) 

3,384.7 

(+9.1) 

3,344.1 

(+53.0) 

Open market operations 

3,379.7 

(+35.7) 

3,375.5 

(+18.0) 

3,384.6 

(+9.1) 

3,344.0 

(+53.0) 

  Tender operations 

732.5 

(-6.6) 

733.2 

(-1.5) 

731.8 

(-1.5) 

739.1 

(-14.0) 

  MROs 

7.3 

(+2.5) 

6.8 

(-0.1) 

7.9 

(+1.1) 

4.8 

(+2.9) 

  Three-month LTROs 

4.7 

(+0.1) 

4.4 

(+0.7) 

5.0 

(+0.6) 

  TLTRO-I operations 

0.0 

(-5.5) 

0.0 

(-1.5) 

0.0 

(+0.0) 

4.6 

5.5 

(-2.8) 

(-5.6) 

  TLTRO-II operations 

720.5 

(-3.7) 

722.0 

(-0.6) 

718.8 

(-3.1) 

724.2 

(-8.5) 

  Outright portfolios 

2,647.2 

(+42.2) 

2,642.3 

(+19.6) 

2,652.8 

(+10.5) 

2,604.9 

(+67.0) 

  First covered bond purchase programme 

  Second covered bond purchase 

programme 

4.3 

4.0 

(-0.2) 

(-0.0) 

4.3 

4.0 

(-0.1) 

(-0.0) 

4.3 

4.0 

(-0.0) 

(-0.0) 

4.5 

4.0 

(-0.2) 

(-0.2) 

  Third covered bond purchase 

262.3 

(+3.9) 

262.1 

(+2.2) 

262.6 

(+0.5) 

258.4 

(+3.8) 

programme 

  Securities Markets Programme 

73.0 

(-1.2) 

73.0 

(-1.0) 

73.1 

(+0.1) 

74.2 

(-9.3) 

  Asset-backed securities purchase 

27.6 

(+0.3) 

27.7 

(+0.6) 

27.6 

(-0.1) 

27.3 

(-0.2) 

programme 

  Public sector purchase programme 

2,098.7 

(+30.9) 

2,095.0 

(+13.0) 

2,103.1 

(+8.2) 

2,067.8 

(+63.6) 

  Corporate sector purchase programme 

177.1 

(+8.4) 

176.3 

(+4.9) 

178.1 

(+1.9) 

168.7 

(+9.5) 

Marginal lending facility 

0.1 

(+0.0) 

0.1 

(+0.1) 

0.1 

(-0.0) 

0.1 

(-0.0) 

Other liquidity-based information 

(averages; EUR billions) 

Current review period: 
31 October 2018 to 29 January 2019 

Seventh and 
eighth 
maintenance 
periods 

Seventh 
maintenance 
period: 
31 October to 
18 December 

Eighth 
maintenance   
period:   
19 December to 
29 January 

Previous review 
period: 
1 August 2018 to 
30 October 2018 

Fifth and sixth 
maintenance 
periods 

Aggregate liquidity needs 

1,511.5 

(+51.8) 

1,487.2 

(+3.8) 

1,539.9 

(+52.8) 

1,459.8 

(+32.3) 

Autonomous factors2 

1,384.5 

(+51.4) 

1,360.4 

(+3.6) 

1,412.6 

(+52.2) 

1,333.1 

(+29.8) 

Excess liquidity 

1,868.2 

(-16.1) 

1,888.4 

(+14.3) 

1,844.6 

(-43.7) 

1,884.3 

(+20.8) 

ECB Economic Bulletin, Issue 2 / 2019 – Boxes 
Liquidity conditions and monetary policy operations in the period from 31 October 2018 to 29 
January 2019 

46 

 
 
 
 
 
 
 
Interest rate developments 

(averages; percentages) 

Current review period: 
31 October 2018 to 29 January 2019 

Seventh and 
eighth 
maintenance 
periods 

Seventh 
maintenance 
period: 
31 October to 
18 December 

Eighth 
maintenance   
period:   
19 December to 
29 January 

Previous review 
period: 
1 August 2018 to 
30 October 2018 

Fifth and sixth 
maintenance 
periods 

MROs 

0.00 

(+0.00) 

0.00 

(+0.00) 

0.00 

(+0.00) 

0.00 

(+0.00) 

Marginal lending facility 

0.25 

(+0.00) 

0.25 

(+0.00) 

0.25 

(+0.00) 

0.25 

(+0.00) 

Deposit facility 

EONIA 

-0.40 

(+0.00) 

-0.40 

(+0.00) 

-0.40 

(+0.00) 

-0.40 

(+0.00) 

-0.363 

(-0.00) 

-0.360 

(+0.01) 

-0.366 

(-0.01) 

-0.362 

(+0.00) 

Source: ECB. 
Notes: All figures in the table are rounded to the nearest €0.1 billion. Figures in brackets denote the change from the previous review or 
maintenance period. 
1) “Minimum reserve requirements” is a memo item that does not appear on the Eurosystem balance sheet and therefore should not be 
included in the calculation of total liabilities. 
2) The overall value of autonomous factors also includes “items in course of settlement”. 

Liquidity provided through monetary policy instruments 

The average amount of liquidity provided through open market operations – 
including both tender operations and APP purchases – increased by 
€35.7 billion to €3,379.8 billion (see Chart A). This increase was fully attributable to 
net APP purchases, while demand for tender operations decreased slightly. 

Chart A 
Evolution of open market operations and excess liquidity 

(EUR billions) 

Tender operations
Outright portfolios
Excess liquidity

3,500

3,000

2,500

2,000

1,500

1,000

500

0
07/14

Source: ECB. 

01/15

07/15

01/16

07/16

01/17

07/17

01/18

07/18

01/19

The average amount of liquidity provided through tender operations declined 
slightly over the review period, by €6.6 billion to €732.5 billion. This decrease 
was entirely due to a lower average outstanding amount of targeted longer-term 
refinancing operations (TLTROs), which decreased by €9.2 billion. The average 

ECB Economic Bulletin, Issue 2 / 2019 – Boxes 
Liquidity conditions and monetary policy operations in the period from 31 October 2018 to 29 
January 2019 

47 

 
 
 
 
liquidity provided through MROs increased by €2.5 billion to €7.3 billion, which 
partially offset the decline in TLTROs. 

Liquidity provided through the Eurosystem’s monetary policy portfolios 
increased by €42.2 billion to €2,647.2 billion on average, owing to net APP 
purchases, which continued into December 2018. However, the size of the 
increase shrank by €24.8 billion compared to the previous review period. 
Liquidity provided by the public sector purchase programme, the third covered bond 
purchase programme, the corporate sector purchase programme and the 
asset-backed securities purchase programme rose on average by €30.9 billion, 
€3.9 billion, €8.4 billion and €0.3 billion respectively. Redemptions of bonds held 
under the Securities Markets Programme and the previous two covered bond 
purchase programmes totalled €1.3 billion. 

Excess liquidity 

As a consequence of the developments detailed above, average excess 
liquidity decreased slightly compared with the previous review period, by 
€16.1 billion to €1,868.2 billion (see Chart A). This decrease reflects higher net 
autonomous factors, mainly in the eighth maintenance period, driven partly by 
year-end developments in liabilities to non-euro area residents in euro, which were 
only partially offset by the liquidity provided through the APP purchases, which slowed 
down towards the end of December, prior to entering the reinvestment phase on 
1 January. Regarding the allocation of excess liquidity holdings between current 
accounts and the deposit facility, average current account holdings marginally 
declined by €0.5 billion to €1,357.6 billion, and average recourse to the deposit facility 
declined by €15.2 billion to €637.8 billion. 

Interest rate developments 

Overnight unsecured and secured money market rates remained close to the 
ECB deposit facility rate. In the unsecured market, the euro overnight index average 
(EONIA) averaged −0.363%, almost unchanged from the previous review period. The 
EONIA fluctuated between a low of −0.374% observed on 21 December and a high of 
−0.335% observed on 27 December. Regarding the secured market, the spread 
between the average overnight repo rates for the standard and the extended collateral 
baskets in the general collateral (GC) pooling market 15  narrowed. Compared to the 
previous period, the average overnight repo rate for the standard collateral basket 
increased by 2 basis points to −0.417%, while for the extended collateral basket it 
declined by 2 basis points to −0.406%. The 2018 year-end decline in core repo rates 
was less pronounced than the 2017 year-end decline. This suggests that market 
participants have adopted more efficient collateral management practices. In addition, 

15    The GC Pooling market allows repurchase agreements to be traded on the Eurex platform against 

standardised baskets of collateral. 

ECB Economic Bulletin, Issue 2 / 2019 – Boxes 
Liquidity conditions and monetary policy operations in the period from 31 October 2018 to 29 
January 2019 

48 

 
 
                                                                    
the Eurosystem public sector purchase programme securities lending facility 
continued to support the smooth functioning of the repo market. 

ECB Economic Bulletin, Issue 2 / 2019 – Boxes 
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January 2019 

49 

 
 
 
 
3

Employment growth and GDP in the euro area 

Prepared by Vasco Botelho and António Dias da Silva 

This box analyses developments in the euro area labour market with respect to 
recent changes in GDP growth. The labour market remained relatively robust 
throughout 2018, in spite of the slowdown in real GDP growth. A decomposition of 
GDP into labour productivity, labour market outcomes and demographic trends shows 
a larger contribution to real GDP growth from employment (see Chart A). In the first 
three quarters of 2018, economic growth was strongly supported by employment 
growth and by the stable decline in the unemployment rate. These developments 
contrast sharply with trends during the early period of the recovery and highlight the 
strength of the labour market in the euro area against the background of the slowdown 
in GDP growth in 2018. Indeed, despite the considerable heterogeneity observed 
across different euro area countries, the aggregate euro area unemployment rate was, 
in December 2018, at its lowest since October 2008, with the 
employment-to-population ratio higher than in 200816. 

Chart A 
Decomposition of real GDP growth 

(percentages, year-on-year growth rates) 

Real GDP
Productivity (per hour worked)
Average hours worked (per employed worker)
Employment rate (out of the labour force)
Labour force participation (out of total population)
Total population

6%

5%

4%

3%

2%

1%

0%

-1%

-2%

-3%

-4%

-5%

-6%

-7%

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Sources: Eurostat and ECB staff calculations. 
Notes: Real GDP is decomposed into labour productivity (real GDP/total hours worked), average hours worked per employed worker, 
employment rate (total employment/labour force), labour force participation rate (labour force/population) and total population. The 
labour force is defined as the sum of employed and unemployed workers. 

An estimated simple static relationship between employment/unemployment 
and GDP illustrates the good labour market performance since the beginning of 
the recovery in the euro area (see Chart B). Employment growth was 0.4 
percentage point above its expected level at the end of 2018, based on a long-term 
static relationship between employment and GDP growth. These positive employment 

16    Heterogeneity in unemployment rates remains high, as more than 15 percentage points separate the 
highest and lowest rates of euro area countries. The employment-to-population ratio, defined here as 
total employment divided by the segment of the population aged 15-74, increased by 0.8 percentage 
point, from 58.7% to 59.5%, between the third quarter of 2008 and the third quarter of 2018. 

ECB Economic Bulletin, Issue 2 / 2019 – Boxes 
Employment growth and GDP in the euro area 

50 

 
residuals since the start of the recovery became even more accentuated in the last 
three quarters of 2018, as the year-on-year GDP slowdown was not accompanied by a 
proportionate deceleration in employment growth. The positive residuals are also 
translated into positive residuals of growth in total hours, i.e. total hours have grown by 
more than would be expected given the rate of GDP growth. Similarly, the 
unemployment rate also indicates a strong labour market performance, trending below 
its expected value, as estimated by the traditional static Okun’s law. The observed 
strength of the labour market is broad-based across countries17, with the Okun 
relationship consistently showing a stronger than expected labour market 
performance, which may be due to structural reforms that contributed to higher 
employment creation during the recent economic recovery18. 

Chart B 
Residuals from static Okun estimates 

(percentage points) 

Unemployment rate
Total employment
Total hours

1,5

1,0

0,5

0,0

-0,5

-1,0

-1,5

-2,0

-2,5

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Sources: Eurostat and ECB staff calculations. 
Notes: Estimates based on data for the period between the first quarter of 1998 and the third quarter of 2018. Residuals from a static 
Okun relationship that relates the year-on-year changes in the unemployment rate, the year-on-year growth rate in total employment and 
the year-on-year growth rate in total hours to the contemporaneous year-on-year growth rate in real GDP. 

However, the current labour market performance will be dependent on the 
nature of the shocks affecting the observed slowdown in real GDP. A static Okun 
approach conveys a long-term relationship between real GDP growth and labour 
market outcomes, ignoring both short-run and long-run dynamics on the adjustment of 
the labour market to fluctuations in the business cycle. Allowing for a dynamic 
specification to assess the time profile between real GDP growth and labour market 
outcomes would show that the labour market performance depends not only on 
current changes in real GDP growth but also on past GDP innovations19. In addition, 
as the implied Okun elasticities are below unity, fluctuations in real GDP growth might 

17    The exceptions for the third quarter of 2018 are: Italy, with negative employment residuals but positive 

total hour and negative unemployment rate residuals; Estonia, with negative employment and total hour 
residuals but positive unemployment rate residuals; and Malta, with positive employment, total hour and 
unemployment rate residuals. 

18    See, for example, the box entitled “Recent employment dynamics and structural reforms” in the article 

“The employment-GDP relationship since the crisis”, Economic Bulletin, Issue 6, ECB, 2016, and the box 
entitled “Labour and product market regulation, worker flows and output responsiveness” in “Structural 
policies in the euro area”, Occasional Paper Series, No 210, ECB, June 2018. 

19    See the box entitled “A quantitative investigation of the euro area employment-GDP relationship” in “The 

employment-GDP relationship since the crisis”, Economic Bulletin, Issue 6, ECB, 2016. 

ECB Economic Bulletin, Issue 2 / 2019 – Boxes 
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51 

 
 
 
                                                                    
imply a somewhat protracted and mitigated response of total employment, the 
unemployment rate and total hours. Moreover, the current strong labour market 
performance and its subsequent path could also be affected by the specific nature of 
the shocks hitting the economy. 

Overall, these results highlight the strong labour market dynamics since the 
beginning of the recovery and underline the recent robustness of the labour 
market in the face of the recent slowdown in real GDP in 2018. Indeed, while GDP 
growth decelerated by 0.7 percentage point during 2018, employment growth 
decelerated only by 0.2 percentage point, with the static Okun residuals becoming 
even more negative for unemployment and more positive for employment and total 
hours. However, the labour market is also characterised by a protracted response to 
changes in GDP, and that will be one of the various factors influencing how the labour 
market evolves in subsequent quarters. 

ECB Economic Bulletin, Issue 2 / 2019 – Boxes 
Employment growth and GDP in the euro area 

52 

 
 
 
 
4 

New features in the Harmonised Index of Consumer 
Prices: analytical groups, scanner data and web-scraping 

Prepared by Martin Eiglsperger 

Harmonised indices of consumer prices (HICPs) for food, industrial goods, 
services and energy are measures that the ECB uses for its more detailed 
analysis of inflation in the euro area. With the release of the HICPs for January 
2019, these analytical groups - special aggregates - are based on a more exact 
allocation of products. As a result, the distinction between goods and services and 
between unprocessed and processed food is now more precise. This improvement 
has been achieved by deriving special aggregates from the HICP’s generic 
classification – the “European Classification of Individual Consumption according to 
Purpose” (ECOICOP) – which provides a more detailed level of breakdown than the 
product classification used thus far. Another recent enhancement is the extended use 
of supermarket scanner data. “Web-scraping” – an automated approach to collecting 
mass data from websites – is also being more broadly applied. Overall, these changes 
reflect better the actual consumer price developments in the economy, especially 
since they increase the coverage of sales prices. 

The ECB monitors and analyses inflation using the HICP grouped into 
unprocessed food, processed food, industrial goods, services and energy. 
These special aggregates often exhibit distinct properties, such as the greater volatility 
of the HICPs for unprocessed food and for energy. Some measures of underlying 
inflation are derived by excluding some of these special aggregates.20  In general, 
special aggregates are used to better analyse and understand the drivers of inflation. 

Statistical offices in the European Union have introduced a further level of 
detail into the HICP classification by consumption purpose. At its most detailed 
level, ECOICOP includes around 300 sub-categories, for example “Mobile telephone 
equipment” (formerly the most detailed level of breakdown grouped all telephone and 
telefax equipment in one category). “Repair of telephone or telefax equipment” has 
also been grouped as a separate category. Statistical offices are providing 
breakdowns of their national HICPs in accordance with ECOICOP for different time 
spans. While France and Lithuania have back-calculated the entire time series, 
Ireland and Finland have only published data from 2017 onwards. 

Price indices for analytical groups based on the more detailed classification of 
products by consumption purpose have been introduced with the publication 
of the euro area HICP for January 2019. Eurostat, the statistical office of the 
European Union, has calculated these new special aggregates back to January 2017 
for the euro area and the European Union as a whole, as well as for all individual EU 
Member States. The old HICP special aggregates have been replaced. Up to 
December 2016, data for HICP special aggregates remain based on the less detailed 
breakdown, implying a statistical break in the respective time series. Chart A illustrates 
how the more detailed level of product breakdown impacts on the HICPs for 

20    See the article “Measures of underlying inflation for the euro area”, Economic Bulletin, Issue 4, ECB, 

2018. 

ECB Economic Bulletin, Issue 2 / 2019 – Boxes 
New features in the Harmonised Index of Consumer Prices: analytical groups, scanner data 
and web-scraping 

53 

unprocessed food and for industrial goods excluding energy. Apart from the split into 
unprocessed and processed food, the effects of the more detailed data on special 
aggregates are relatively minor. Nevertheless, this may have some implications for the 
forecasting and seasonal adjustment of HICP special aggregates. 

Chart A 
More detailed classification on euro area HICPs for unprocessed food and for 
industrial goods excluding energy 

(index: 2015 = 100) 

Existing breakdown
More detailed breakdown

a) Unprocessed food

b) Industrial goods excluding energy

110

109

108

107

106

105

104

103

102

101

100

104

103

102

101

100

99

98

97

96

95

01/17

05/17

09/17

01/18

05/18

09/18

01/19

01/17

05/17

09/17

01/18

05/18

09/18

01/19

Source: Eurostat. 

Having HICPs for food, goods, services and energy derived from a more 
detailed classification of products by consumption purpose is an important 
improvement. It helps to better identify drivers of inflation, such as wage increases for 
services activities. Econometric modelling of inflation by analytical groups can also be 
expected to benefit from the more precise allocation. 

With the publication of HICPs for January 2019, the use of web-scraped data 
has expanded further; supermarket scanner data are already used by several 
statistical offices. Traditionally, prices in bricks-and-mortar shops are collected by 
price observers, who focus on the prices of the most sold product variants and visit 
outlets at least once a month; for more volatile prices the visits are more frequent. 
While in many EU Member States price collection in shops is still central to HICP data 
sampling, many statistical offices have started or are intensifying the use of scanner 
and web-scraped data. 

These new data collection methods provide considerably more price data, 
reflecting product variability, and they also cover a greater number of shopping 
days sampled within a month. In contrast to the standard survey-based price 
collection in bricks-and-mortar stores, index calculation using scanner data uses 
turnover by product bar codes (Global Trade Item Number, GTIN) or another 
identification code. Prices are derived by dividing the turnover of a certain product, 
identified by its item code, by the amount sold. Scanner data ensure that many more 
products are included over a longer time period. Prices derived from scanner data are 
closer to the average for the month, compared with point-in-time price collection. 

ECB Economic Bulletin, Issue 2 / 2019 – Boxes 
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and web-scraping 

54 

 
 
 
New data collection methods require new statistical approaches. The 
significantly larger volume of data requires statistical offices to treat the data in an 
automated manner. The compilation of product-specific price indices from scanner 
data poses several challenges, in particular the treatment of discount prices and the 
greater purchase volumes triggered by discounts. Low turnover in post-discount 
periods implies that price indices, weighted by sales volumes, tend to be prone to a 
downward drift when established price index formulae are applied.21  In most cases, 
statistical offices that use scanner data currently compile drift-free indices by not 
incorporating index weights derived from concurrent turnover. Statistical researchers 
are currently developing methods to take account of turnover by means of expenditure 
weights while avoiding downward biases.22 

Relaunched products may also cause compilation issues when scanner data 
are used. While maintaining their essential product features, relaunched products 
may change their item code and sell at a higher price. Compiling price indices at the 
level of item codes would not capture such price increases. It is therefore necessary to 
develop methods that identify relaunches also when item codes have changed. 

A larger range of product variants, a greater frequency of recording and higher 
coverage of the reporting month are the three main ways scanner and 
web-scraped data affect the HICP. Scanner data typically refer to a period of two to 
three weeks of a month. HICP flash estimates may cover less than this. Therefore, the 
use of scanner data may occasionally lead to higher and/or more frequent revisions to 
flash estimates. Overall, the larger amount of data implies that monthly price indices 
are more affected by the price setting of supermarkets and internet retailers. For 
example, weekend days, as well as the shopping days before Easter and Christmas, 
are covered better using these new methods. 

Scanner data better indicate sharp changes in prices related to discounts. Sales 
prices around Christmas may have an impact, in particular when scanner data are 
incorporated for the first time, since the HICP formula requires chain-linking over 
December. Generally, with the use of scanner data, sales prices are covered more 
comprehensively, both across time and across products, implying that scanner 
data-based price indices may be significantly more volatile. 

21    See, for example, de Haan, J. and van der Grient, H., “Eliminating chain drift in price indexes based on 

scanner data”, Journal of Econometrics, Vol. 161(1), pp. 36-46, March 2011. 

22  See, for example, Chessa, A., Verburg, J. and Willenborg, L., “A Comparison of Price Index Methods for 
Scanner Data”, presented at the 15th Meeting of the Ottawa Group, 10-12 May 2017, Eltville am Rhein, 
Germany. 

ECB Economic Bulletin, Issue 2 / 2019 – Boxes 
New features in the Harmonised Index of Consumer Prices: analytical groups, scanner data 
and web-scraping 

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5 

A new method for the package holiday price index in 
Germany and its impact on HICP inflation rates 

Prepared by Martin Eiglsperger 

Harmonised indices of consumer prices (HICPs) are regularly updated for 
changes in consumption weights and the items included, and on occasion also 
for methodological improvements. One such improvement is a change in the way 
the price index for package holidays is calculated in the HICP for Germany, which was 
implemented with the HICP release for January 2019. This has led to revisions of 
annual rates of change not only for Germany, but also for the euro area as a whole. 

The German price index for package holidays now shows a more meaningful 
seasonal pattern. While the previous method used seasonal expenditure weights – 
i.e. different weights in the price index for package holidays taken at different times of 
the year – the new approach uses annual weights that are kept fixed over the entire 
year. This means that the price index for package holidays is no longer affected by the 
switch between seasonal weights at the beginning and end of seasons. However, the 
application of fixed weights implies that, during out-of-season periods, when prices for 
seasonal trips are not observable, the missing changes in prices have to be estimated. 
For instance, in summer it is necessary to include estimates for the changes in prices 
of trips normally taken in the winter, and in the winter it is necessary to use estimates 
for the changes in prices in the summer. The estimation is done by means of 
imputation, where changes in holiday prices in out-of-season periods are estimated on 
the basis of the price dynamics of other trips actually conducted in that season. 
Whereas the former approach treated winter and summer holidays separately, the 
new integrated sample also includes destinations to which trips are made over the 
entire calendar year. This establishes a relationship between price developments of 
seasonal trips. 

The methodological change has led to a more pronounced seasonal profile for 
the package holiday price index for Germany and also for the euro area. Chart A 
shows that the index for the euro area has greater seasonal variation than before, with 
higher values in the summer months and lower values in the winter months. While the 
new index varies more between seasonal peaks and troughs, however, its profile is 
less erratic. 

ECB Economic Bulletin, Issue 2 / 2019 – Boxes 
A new method for the package holiday price index in Germany and its impact on HICP inflation 
rates 

56 

 
 
Chart A 
Price index for package holidays for the euro area before and after the revision 

(index: 2015 = 100) 

Before
After

140

130

120

110

100

90

80

70

60

01/12

07/12

01/13

07/13

01/14

07/14

01/15

07/15

01/16

07/16

01/17

07/17

01/18

07/18

01/19

Source: Eurostat. 

The revised data have had a considerable impact on the annual rates of change 
of several aggregates of the euro area HICP for the first year for which the 
methodological change was incorporated; afterwards the impact is more 
moderate (see Chart B). Index numbers from 2015 onwards use data compiled 
according to the new method, while the index for 2014 and before is still based on the 
former treatment of package holidays. The annual rates of change for 2015 are 
calculated using index values that are based on differing methods, and are therefore 
distorted.23  As of 2016, annual growth rates are based entirely on the new method 
and are therefore undistorted. The impact on the annual growth rates for the period 
2016 to 2018 is relatively moderate. 

23    See Eurostat, “Improved calculation of HICP special aggregates and German package holidays 

methodological change”, February 2019, p. 2. 

ECB Economic Bulletin, Issue 2 / 2019 – Boxes 
A new method for the package holiday price index in Germany and its impact on HICP inflation 
rates 

57 

 
 
 
                                                                    
Chart B 
Impact of the methodological change for the German package holiday price index on 
euro area HICP aggregates 

(annual inflation rates) 

Before
After

2.0

1.8

1.6

1.4

1.2

1.0

0.8

0.6

0.4

0.2

0.0

0.4

0.4

0.2

0.2

0.2

0.0

1.8

1.7

1.5

1.5

1.5

1.4

1.4

1.5

1.3

1.2

1.2

1.2

1.1

1.1

1.1

1.0

1.0

1.0

1.0

0.8

0.8

0.8

0.9

0.8

2014

2015

2016

2017

2018

2014

2015

2016

2017

2018

2014

2015

2016

2017

2018

Headline HICP

HICP excluding food and energy

HICP for services

Source: Eurostat. 
Note: The annual growth rates in the HICP for services for the years 2017 and 2018 after the revision are also affected by the introduction 
of a more detailed product classification; see the box entitled “New features in the Harmonised Index of Consumer Prices: analytical 
groups, scanner data and web-scraping” in this issue of the Economic Bulletin. 

Users must look through the distortions in annual growth rates, especially for 
2015, when assessing past inflation developments. This is particularly the case, 
for instance, for euro area HICP inflation excluding food and energy as a measure of 
underlying inflation (see Chart C). The revision of the series distorts the picture of 
successive years of low underlying inflation. For analytical purposes, users can 
correct the series of annual percentage changes in different ways. 24  A simple 
approach to obtaining annual inflation rates that do not comprise data based on 
different methods is to use annual rates of change up to December 2015 based on the 
index before the methodological change, and to use annual growth rates that are 
derived from the index calculated according to the new method from January 2016. 25 

24    Approaches to mitigating the impact of the distortions could be facilitated by the use of time series 

analysis techniques such as seasonal adjustment. 

25    However, this method cannot be used to derive an HICP time series. The HICP is a price index based on 
a Laspeyres-type formula (See Eurostat, “Harmonised Index of Consumer Prices (HICP), Methodological 
Manual”, November 2018, p. 170.), meaning that annual expenditure weights are applied to component 
indices rather than their growth rates. 

ECB Economic Bulletin, Issue 2 / 2019 – Boxes 
A new method for the package holiday price index in Germany and its impact on HICP inflation 
rates 

58 

 
 
 
                                                                    
Chart C 
Euro area HICP inflation excluding food and energy before and after the revision 

(annual rates of change) 

Before
After

1,6

1,4

1,2

1,0

0,8

0,6

0,4

0,2

0,0

01/14

07/14

01/15

07/15

01/16

07/16

01/17

07/17

01/18

07/18

01/19

Source: Eurostat. 

ECB Economic Bulletin, Issue 2 / 2019 – Boxes 
A new method for the package holiday price index in Germany and its impact on HICP inflation 
rates 

59 

 
 
 
 
 
6 

Interest rate-growth differential and government debt 
dynamics 

Prepared by Cristina Checherita-Westphal 

The difference between the average interest rate that governments pay on their 
debt and the nominal growth rate of the economy is a key variable for debt 
dynamics and sovereign sustainability analysis. The change in government debt 
between two years equals the interest paid on the stock of debt, the primary deficit 
(excess of expenditure, excluding interest payments, over revenue), and other factors 
(deficit-debt adjustments). For ratios to GDP, the change in debt is then mainly 
determined by the primary balance and the difference between the interest rate and 
the GDP growth rate. If the interest rate-growth differential (
primary fiscal surplus is needed to stabilise or reduce the debt-to-GDP ratio. The 
higher the initial debt level, the higher the primary surplus will need to be. Conversely, 
a persistently negative
  would imply that debt ratios 
could be reduced even in the presence of primary budget deficits (lower than the debt 
effect induced by the differential).26 

  on government debt 

) is strictly positive, a 

(𝑖𝑖 < 𝑔𝑔)

 𝑖𝑖 − 𝑔𝑔

𝑖𝑖 − 𝑔𝑔

𝑖𝑖 − 𝑔𝑔

  has turned negative in most advanced economies, including 

Recently, 
euro area sovereigns. According to the European Commission’s Autumn 2018 
forecast, all euro area countries except Italy had negative 
differential is projected to increase in 12 euro area countries by 2020, but to remain in 
negative territory for all countries except Italy. 

  in 2017. The 

𝑖𝑖 − 𝑔𝑔

The debate on the role of fiscal policy with a persistently negative interest 
rate-growth differential has been revived by Olivier Blanchard in his 2019 AEA 
Presidential address. 27  Using the US example, Blanchard makes the point that the 
costs of government debt may be smaller than generally assumed in the policy 
discussion. This is because the (US) safe interest rate (a proxy of marginal bond rates) 
is below the nominal GDP growth rate and this is more the historical norm rather than 
  differential, public debt may have no fiscal cost. It 
the exception. With a negative 
may still have welfare costs, but these may also be lower than typically assumed. An 
implication of this proposition would be that the US can sustain (roll-over) high(er) 
debts without significant costs. The author stresses, however, that the purpose of the 
lecture is not to argue for higher debt per se, but to allow for a richer discussion of debt 
policy and appropriate debt rules than is currently the case. 

𝑖𝑖 − 𝑔𝑔

Theoretical models do not provide clear cut conclusions with respect to the 
sign and size of the interest rate-growth differential on government debt. In 

26   

𝑖𝑖𝑡𝑡−𝑔𝑔𝑡𝑡
1+𝑔𝑔𝑡𝑡 � 𝑏𝑏𝑡𝑡−1 −  𝑝𝑝𝑏𝑏𝑡𝑡 + 𝑑𝑑𝑑𝑑𝑑𝑑𝑡𝑡    (𝑒𝑒𝑒𝑒. 1)

Equation 1 (the typical debt accumulation equation) provides a simple accounting framework to 
∆𝑏𝑏𝑡𝑡 = �
decompose the change in the government gross debt-to-GDP ratio (
(i) the “snowball effect”, i.e. the impact of the difference between the average nominal interest rate 
charged on government debt (
) and the nominal GDP growth rate (
ratio in the previous period (
); (ii) the primary budget balance (surplus) ratio (
deficit-debt adjustment as a share of GDP (
affect debt but are not included in the budget balance (such as acquisitions or sales of financial assets). 

) or the stock-flow adjustment, comprising factors that 

) into its key drivers, consisting of: 

) multiplied by the debt-to-GDP 

); and (iii) the 

𝑖𝑖𝑡𝑡
𝑏𝑏𝑡𝑡−1

∆𝑏𝑏𝑡𝑡

𝑝𝑝𝑏𝑏𝑡𝑡

𝑔𝑔𝑡𝑡

27    “Public Debt and Low Interest Rates”, 2019 AEA Presidential Address by Olivier Blanchard (Atlanta, 5 
January 2019). The lecture was essentially a presentation of his recent academic work entitled “Public 
Debt and Low Interest Rates”. 

𝑑𝑑𝑑𝑑𝑑𝑑𝑡𝑡

ECB Economic Bulletin, Issue 2 / 2019 – Boxes 
Interest rate-growth differential and government debt dynamics 

60 

 
 
                                                                    
 
  for economies that operate at their steady state (along a balanced 

general, models are based on the assumption that the inter-temporal budget 
constraint holds, i.e. the present value of future primary surpluses should equal the 
current level of debt (no explosive debt paths). While standard growth theory implies a 
positive 
growth path), including for the safe rate, in overlapping-generation models with 
non-diversifiable uncertainty or models with rational bubbles, a negative 
government debt could co-exist with a dynamically efficient economy. 28  Moreover, it 
must be recognised that such models analyse the “risk-free rate”, while accounting for 
sovereign credit risk or possibility of default would raise the cost of public debt.29 

𝑖𝑖 − 𝑔𝑔

𝑖𝑖 − 𝑔𝑔

  on 

𝑖𝑖 − 𝑔𝑔

  for mature economies over extended 

  values are observed for advanced economies during periods of 

Empirically, the relevant interest rate-growth differential for public debt 
dynamics, as defined above, has been positive for advanced mature economies 
over longer periods. The value of 
periods of time has hovered around one percentage point.30  Positive values are also 
typically observed for the largest euro area economies (see Chart A). On the other 
hand, negative 
overheating or, more generally, for emerging economies. As documented in the 
empirical literature31, the main factors behind the “puzzle” of persistently negative 
differentials in emerging economies are financial repression, including during periods 
of hyperinflation, and to some extent also the income catch-up effect. Finally, the 
primary balance also plays an important role in debt dynamics. Even in the presence 
of negative 
stabilising. In this respect, primary surpluses in most euro area countries have helped 
put debt ratios on a downward path.32 

, large enough primary deficits would prevent debt ratios from 

𝑖𝑖 − 𝑔𝑔

𝑖𝑖 − 𝑔𝑔

Moreover, while the interest rate has followed a clear downward trend since the 
1980s, to a certain extent the GDP growth rate has done so as well. Since the 
1980s in particular, real interest rates in advanced economies have declined and, in 
the wake of the global financial crisis, plummeted to exceptionally low levels. This 
development has often been associated with a decline in the estimated natural or 
neutral rate of interest, which in turn has been linked in many studies to a decline in 
potential output growth.33  There is therefore still a question about the trend in the 

28    Blanchard, O. and Fischer, S., Lectures on Macroeconomics, The MIT Press, Cambridge, 1989, and 

Blanchard (2019), op. cit. 

29    For a summary of this literature, see D’Erasmo, P., Mendoza, E. and Zhang, J., “What is a Sustainable 

Public Debt?”, Handbook of Macroeconomics, Vol. 2B, 2016, pp. 2557-2588. 

30    See Escolano, J., “A Practical Guide to Public Debt Dynamics, Fiscal Sustainability, and Cyclical 

Adjustment of Budgetary Aggregates”, IMF Technical Notes and Manuals, Washington DC, 2010. A 
seminal OECD paper on measures for public debt sustainability (Blanchard et al., 1990) concludes that 
even if the configuration of a negative differential being easily rejected based on theoretical or empirical 
grounds remains “a theoretical curiosum [,…] Still, there is general agreement that the condition of an 
excess in the interest rate over the growth rate probably holds, if not always, at least in the medium and 
long run.” (pp. 15). See Blanchard, O., Chouraqui, J.-C., Hagemann, R. and Sartor, N., “The 
Sustainability of Fiscal Policy: New Answers to an Old Question”, Economic Studies, No 15, OECD, 
Paris, 1990. 

31    See, for instance: Escolano, J., Shabunina, A. and Woo, J., “The Puzzle of Persistently Negative 

Interest-Rate–Growth Differentials: Financial Repression or Income Catch-Up?”, Fiscal Studies, Vol. 
38(2), 2017, pp. 179–217. 

32    According to the Commission’s Autumn 2018 forecast, the euro area primary balance is projected to be in 
surplus (+1.2% of GDP) in 2018, as opposed to deficits in the US (-2.1% of GDP) and Japan (-1.5% of 
GDP). All euro area countries apart from France, Spain and Latvia are projected to have recorded a 
primary surplus in 2018. 

33    See Brand, C., Bielecki, M. and Penalver, A., “The natural rate of interest: estimates, drivers, and 
challenges to monetary policy”, Occasional Paper Series, No 217, ECB, Frankfurt am Main, 2018. 

ECB Economic Bulletin, Issue 2 / 2019 – Boxes 
Interest rate-growth differential and government debt dynamics 

61 

 
 
                                                                    
difference between the two variables, and specifically about the differential that 
applies to government borrowing. 

Chart A 
Interest rate-growth differential on government debt 

(percentage points) 

(𝑖𝑖−𝑔𝑔)

1999-2017
2017
G7 (1966-2010)
Advanced economies (1966-2010)
Emerging economies (1966-2010)

3

2

1

0

-1

-2

-3

-4

Euro area
12

DE

FR

IT

ES

NL

BE

UK

US

JP

. In annual terms, 

Sources: European Commission Autumn 2018 Economic Forecast (AMECO) for 1999-2017 data (bars) and Escolano et al. (2017) for 
1966-2010 data (lines). 
  and the nominal GDP 
Notes: The chart depicts the difference between the average nominal interest rate charged on government debt (
growth rate (
  is defined as the ratio between total interest payment at time t and the debt stock at t-1, then averaged 
over the periods shown in the chart. In general, AMECO series cover the general government debt according to the ESA-2010 definition 
(for the US, federal debt). The horizontal lines represent the average 
  over 1966-2010 (not all countries in the sample available for 
the entire period, as explained in Escolano et al., 2017). Countries shown are the six largest euro area economies. Euro area 12 includes 
Belgium, Germany, Ireland (excluding extreme outliers for the years 2015 and 2016), Greece, Spain, France, Italy, Luxembourg, the 
Netherlands, Austria, Portugal and Finland. The values shown in the chart for euro area 12 represent simple averages of 
the sample. The other country groups are as described in Escolano et al. (2017) and broadly according to the IMF definitions for 
advanced and emerging economies. 

  across 

𝑖𝑖 − 𝑔𝑔

𝑖𝑖 − 𝑔𝑔

𝑔𝑔)

𝑖𝑖)

𝑖𝑖

Empirical literature 34  identifies several factors that influence the dynamics of 
the differential. Population ageing has been found to be a relevant factor in the 
decline of the natural rate of interest, but also in the decline of potential GDP growth.35 
In addition, the literature identifies the “global savings glut” (as proxied by the current 
account surpluses of emerging economies) and the one-off effect of setting up the 
European Monetary Union 36  as relevant factors contributing to the decline of 
across advanced economies. Cyclical conditions and economic policies also seem to 
play an important role. The differential can increase quickly in recessions, especially in 
high-debt countries. More generally, weaker fiscal positions (higher debt and deficits) 
are found to be associated with higher 
averages for euro area 12, taking into account high public debt ratios and the position 
𝑖𝑖 − 𝑔𝑔
in the business cycle. The differential is higher, on average, when public debt is high 
(for the period 1999-2017,1.7 percentage point when debt is greater than or equal to 
90% of GDP versus 0.0 when debt is lower than 90%; similar results are recorded for 
the longer period since 1985). This is partly explained by the position in the cycle: in 

. Table A presents historical 

𝑖𝑖 − 𝑔𝑔

𝑖𝑖 − 𝑔𝑔

34    See, for instance, Escolano et al., op. cit. and Turner, D. and Spinelli, F., “Explaining the 

interest-rate-growth differential underlying government debt dynamics”, OECD Economics Department 
Working Papers, No 919, OECD, Paris, 2011. 

35    See the article entitled “The economic impact of population ageing and pension reforms”, Economic 

Bulletin, Issue 2, ECB, 2018. 

36    While the spread compression at the start of EMU depressed i-g in parts of the euro area, the financial 

and sovereign debt crises triggered very steep reversals of the differential for a period of time. 

ECB Economic Bulletin, Issue 2 / 2019 – Boxes 
Interest rate-growth differential and government debt dynamics 

62 

 
 
 
 
 
 
                                                                    
bad economic times 
as opposed to -0.5 for the period 1999-2017). Nonetheless, in bad economic times, 
countries with higher debt have larger differentials (3.8 as opposed to 2.5).37 

  is much higher than in normal or good economic times (3.0 

𝑖𝑖 − 𝑔𝑔

Table A 
Historical average interest rate-growth differentials 

, taking into account public 

debt and business cycle effects 

(percentage points, euro area 12) 

(𝑖𝑖−𝑔𝑔)

1985-2017 

1999-2017 

1985-2017 

1999-2017 

1985-2017 

1999-2017 

Overall 

0.9 

0.6 

Overall 

0.9 

0.6 

Overall 

2.9 

3.0 

Lower public debt 
(< 90% GDP) 

High public debt 
(≥ 90% GDP) 

0.4 

0.0 

1.9 

1.7 

Normal and good economic 
times (OG ≥ -1.5)   

Bad economic times 
(OG < -1.5) 

0.1 

-0.5 

2.9 

3.0 

Bad economic times and 
lower public debt 
(OG < -1.5 and Debt < 90%) 

Bad economic times and 
high public debt 
(OG < -1.5 and Debt ≥ 90%) 

2.4 

2.5 

3.7 

3.8 

Sources: European Commission AMECO database, extrapolated for the period 1985-2017, where needed, with other sources. 
Notes: Interest rate-growth differentials shown are simple averages across euro area 12 countries (see Chart A) for the respective time 
periods. High debt is defined as a government debt-to-GDP ratio of at least 90%. An output gap of -1.5% is the threshold separating bad 
from normal economic times in the EC (2015) flexibility matrix. Results are similar for a sample of 24 advanced economies, which 
includes the 19 euro area countries, as well as Denmark, Sweden, the United Kingdom, the United States and Japan. 

In the euro area, the current low interest rate-growth differentials on 
government debt should not be taken as an incentive for higher debt levels, 
especially where fiscal space is constrained. High government debt poses 
significant economic challenges.38  While effective public spending and investment 
can increase a country’s medium-term growth potential and mitigate the negative 
cyclical effects of a downturn,39  current high debt levels in many economies are 
restricting these channels, in particular the ability to conduct counter-cyclical fiscal 
policy in bad times. Country-specific and global economic and policy risks require 
policies to limit countries’ vulnerabilities. 

37    An empirical analysis for the euro area 12 sample finds that government debt and deficits 
(contemporaneous, one-year lagged, five-year averages) are significant determinants of 
controlling for output gap, TFP growth, old-age dependency ratio, population growth, short-term interest 
rate, US 

, country and year fixed effects. 

  after 

𝑖𝑖 − 𝑔𝑔

38    For a review of the risks associated with regimes of high debt, see the article entitled “Government debt 

reduction strategies in the euro area”, Economic Bulletin, Issue 3, ECB, 2016. 

𝑖𝑖 − 𝑔𝑔

39    For more details, see the article entitled “The composition of public finances in the euro area”, Economic 

Bulletin, Issue 5, ECB, 2017. 

ECB Economic Bulletin, Issue 2 / 2019 – Boxes 
Interest rate-growth differential and government debt dynamics 

63 

 
 
 
 
 
 
 
                                                                    
7 

The European Commission’s 2019 assessment of 
macroeconomic imbalances and progress on reforms 

Prepared by Nick Ligthart 

On 27 February 2019, the European Commission published its annual 
assessment of macroeconomic imbalances and the progress made with 
structural reforms based on the country-specific recommendations (CSRs) as 
adopted in July 2018. This assessment is a key part of the European Semester 
framework for coordinating economic and fiscal policies across the EU. Within this 
context, the macroeconomic imbalance procedure (MIP) provides a framework for 
assessing macroeconomic imbalances. It aims to prevent the emergence of harmful 
imbalances and to actively correct imbalances where they have already become 
excessive.40 

Macroeconomic imbalances 

According to the Commission, the number of countries experiencing 
imbalances has increased to 13 overall, from 11 in 2018 (see Table A). This year, 
three countries have been assessed as experiencing “excessive imbalances” – Italy, 
Cyprus and Greece. While Italy and Cyprus were also included in this category last 
year, Greece has been included in this exercise for the first time this year as it exited 
its financial assistance programme in summer 2018. Its major challenges are high 
public debt, a negative net international investment position, a very high share of 
non-performing loans, a still-high unemployment rate and low growth potential. Cyprus 
is still facing challenges related to high levels of both non-performing loans and 
external, private and government debt. For Italy, the Commission finds that fiscal 
sustainability risks, as well as broadly stalling reform progress and backtracking, are 
now overshadowing the progress made in previous years. In addition, the Commission 
recategorised two countries in this year’s assessment. Croatia was recategorised from 
“excessive imbalances” to “imbalances”, owing to a decrease of private, public and 
external sector debt, among other factors. Romania was also recategorised, from “no 
imbalances” to “imbalances”, due to factors including reduced competitiveness and a 
widening of current account imbalances. 

40    To identify imbalances, the Commission uses a standardised scoreboard to select countries that require 
an in-depth review. There are three possible outcomes from these in-depth reviews: “no imbalances”, 
“imbalances” or “excessive imbalances”. If the Commission identifies imbalances, the country concerned 
will receive policy recommendations meant to address them. When the imbalances are assessed as 
being so severe that they are found to be “excessive”, the Commission can take further action by 
recommending that the Council activates the excessive imbalance procedure (EIP). 

                                                        
Table A 
European Commission conclusions on the 2019 MIP 

No imbalances 

Imbalances 

BE 

CZ 

DK 

EE 

LV 

LT 

LU 

HU 

MT 

AT 

PL 

SI 

SK 

FI 

UK 

BG 

DE 

IE 

ES 

FR 

HR 

NL 

PT 

RO 

SE 

Excessive 
imbalances and 
corrective arm 
(EIP) activated 

Excessive 
imbalances 

GR 

IT 

CY 

Source: European Commission. 
Notes: The three countries in blue (Croatia, Romania and Greece) are those whose MIP classification changed in 2019. For all countries 
in the “no imbalances” group, the Commission had already assessed that no imbalances existed in the first stage of the procedure – the 
Alert Mechanism Report. Thus, no in-depth review was drafted for any of these countries. 

Despite the persistence of excessive imbalances in some Member States, the 
excessive imbalance procedure has never been triggered since the 
introduction of the MIP in 2012. Under this so-called corrective arm of the MIP, the 
Council can require a Member State experiencing excessive imbalances to submit a 
corrective action plan and can eventually impose fines, if needed. The repeated 
non-activation of the excessive imbalance procedure risks undermining the credibility 
and effectiveness of the overall procedure. Chart A shows that a quarter of EU 
Member States have experienced excessive imbalances that persisted for multiple 
consecutive years. While some countries have managed to reduce the severity of the 
imbalances over time, the persistence of excessive imbalances over several years in 
some countries indicates that the correction of imbalances could be better facilitated 
by the MIP. Applying all available tools – including activating the corrective arm of the 
procedure for countries with excessive imbalances – could increase the procedure’s 
effectiveness and credibility. This has also been explicitly called for by the five 
Presidents in their 2015 report41  and, more recently, by the European Court of 
Auditors42. 

41    Juncker, J.-C. et al., Completing Europe’s Economic and Monetary Union, June 2015. 
42    European Court of Auditors, Audit of the Macroeconomic Imbalance Procedure (MIP), Special Report No 

3, 2018. 

 
 
 
 
 
 
 
                                                        
Chart A 
EU Member States with excessive imbalances 

CY

FR

BG

PT

IT

HR

CY

FR

BG

PT

IT

HR

FR

BG

PT

IT

HR

SI

IT

HR

SI

ES

CY

IT

HR

CY

IT

GR

2012

2013

2014

2015

2016

2017

2018

2019

Source: European Commission. 
Notes: The chart shows those countries assessed by the European Commission as experiencing “excessive imbalances” in the years 
indicated. A country subject to an economic adjustment programme enters the MIP automatically once the programme ends. In 2012 no 
country was assessed as having excessive imbalances. 

Persistent macroeconomic imbalances – whether excessive or not – leave 
Member States vulnerable to adverse macroeconomic shocks and tend to 
increase the probability of recessions, which often carry high social and 
economic costs. While the EU has experienced economic growth for the past seven 
years, uncertainties related to geopolitical factors, the threat of protectionism and 
macroeconomic imbalances pose downside risks to economic activity. It is therefore 
important that countries undertake ambitious reform efforts to strengthen the 
resilience of their economies to adverse shocks. 

Debt levels are still historically high in some Member States, for both 
government and private debt, which makes responding to a downturn or to 
negative shocks more difficult. Higher economic growth has helped to reduce 
debt-to-GDP ratios in recent years, but debt levels in several cases remain very high. 
Corporations have managed to reduce debt levels faster than households. At the 
same time, in a number of countries the high public and private indebtedness is 
reflected in large stocks of external debt, which highlights the need to ensure sufficient 
current account surpluses. 

To support rebalancing and avoid new imbalances in cost competitiveness 
across the EU, accelerating growth in unit labour costs in some countries has 
to be carefully monitored. In particular, in countries with current account surpluses 
that the Commission finds are experiencing a lack of domestic demand and labour 
shortages, unit labour cost growth that is higher than the euro area average might 
facilitate rebalancing among euro area countries. At the same time, a relative 
deterioration of cost competitiveness in more vulnerable countries with relatively high 
unemployment should be monitored carefully so that a reversal of the positive 
adjustment achieved in recent years can be avoided. 

 
Reform progress 

Reforms remain crucial to address these imbalances, and progress on 
recommended reforms is assessed annually by the Commission. Specifically, 
the Commission has reviewed the implementation of the CSRs that were adopted in 
July 2018 by the Council. Each CSR provides a Member State with guidance in a 
specific policy area. 

The Commission assessment again finds only limited progress on 
recommended reforms. The progress made is evaluated using five categories: “no 
progress”, “limited progress”, “some progress”, “substantial progress” and “full 
implementation”.43  Table B summarises this year’s assessments. Out of 73 CSRs, 
none saw full implementation, and substantial progress was made in only two cases. 
For the overwhelming majority of CSRs (more than 90%), the Commission found that 
Member States made at best some or limited progress. On two CSRs, no progress 
was made. According to the Commission methodology, “no progress” means that the 
Member State concerned did not even “credibly announce” measures that would aim 
to address the policy recommendation. Finally, and most concerning, despite being 
very vulnerable, the countries experiencing excessive imbalances did not make 
significantly more reform progress during the last year than the EU average. The same 
is true for the countries experiencing imbalances. Overall, progress on reforms this 
year was as weak as last year.44 

Table B 
European Commission assessment of implementation of the 2018 CSRs 

Not assessed
Full implementation
Substantial progress
Some progress
Limited progress
No progress

BE BG CZ DK DE EE

IE

ES

FR HR

IT

CY

LV

LT

LU HU MT NL AT

PL

PT RO SI

SK

FI

SE UK

CSR 1*
CSR 2
CSR 3
CSR 4
CSR 5

Source: European Commission. 
Notes: CSR 1* assessment excludes compliance with the Stability and Growth Pact, which will be assessed by the European 
Commission later in spring 2019. “Not assessed” applies to cases in which CSR 1 pertains mostly or exclusively to the Stability and 
Growth Pact. 

Progress with reforms has been uneven, and is particularly lacking in the areas 
of product markets and public finances. Somewhat more effort has been made 
concerning aspects of the financial sector and labour markets. At the same time, the 

43    “Full implementation” means that the Member State has implemented all measures needed to address 
the CSR appropriately; “substantial progress” means that the Member State has adopted measures that 
go a long way in addressing the CSR, most of which have been implemented; “some progress” means 
that the Member State has adopted measures that partly address the CSR, and/or it has adopted 
measures that address the CSR but a fair amount of work is still needed to fully address it as only a few 
of the adopted measures have been implemented; “limited progress” means that the Member State has 
announced certain measures but these only address the CSR to a limited extent, and/or it has presented 
non-legislative acts, yet with no further follow-up in terms of implementation; and “no progress” signifies 
that the Member State has not credibly announced or adopted any measures to address the CSR. 
44    See the box entitled “The European Commission’s 2018 assessment of macroeconomic imbalances and 

progress on reforms”, Economic Bulletin, Issue 2, ECB, 2018. 

 
                                                        
Commission even finds cases of backtracking on reforms, for instance regarding the 
long-term sustainability of public finances (including pensions). 

Further reforms to improve the investment environment are essential to 
stimulate well-targeted investment that improves productivity, potential growth 
and resilience. The Commission finds that the highest barriers to investment are low 
quality of institutions and burdensome regulations. Creating an investment-friendly 
environment will help strengthen investment focused on productivity and growth – 
essential at this point in the business cycle. In turn, investment needs to be well 
targeted to be most effective. While investment in education, research, development 
and innovation is needed in most EU countries, it is important that it flows to those 
sectors where it would most increase productivity growth and competitiveness. To this 
end, the Commission has taken the positive step of adding a new annex to the country 
reports. The annex identifies country-specific investment needs and bottlenecks, and 
also aims to better align the use of EU funds with the European Semester’s analysis. 

 
Article 

1 

Taking stock of the Eurosystem’s asset purchase 
programme after the end of net asset purchases 

Prepared by Felix Hammermann, Kieran Leonard, Stefano Nardelli and 
Julian von Landesberger 

Following the Governing Council’s decision in December 2018 to end net asset 
purchases under the Eurosystem’s asset purchase programme (APP), this article 
reviews the implementation and effects of the asset purchases. The APP has proved 
to be an adaptable and effective instrument to ease monetary and financial conditions, 
foster economic recovery, counteract disinflationary pressures and anchor inflation 
expectations, thereby supporting a sustained adjustment in the path of inflation 
towards price stability. The APP has been part of a package of policy measures 
together with negative interest rates on the deposit facility, forward guidance and 
targeted longer-term refinancing operations (TLTROs), jointly creating synergies that 
have enhanced the effectiveness of each of the package’s individual components. 
From an implementation viewpoint, the Eurosystem ensured that asset purchases 
were conducted smoothly and flexibly by striving for market neutrality and mitigating 
unintended side effects for market functioning. 

Whereas net asset purchases have come to an end, principal payments from maturing 
securities purchased under the APP will continue to be reinvested as this, together 
with enhanced forward guidance, provides the monetary accommodation that the 
Governing Council judges to be required for the continued sustained convergence of 
inflation to levels that are below, but close to, 2% over the medium term. 

1 

Introduction 

The APP is part of a package of policy measures that was initiated in mid-2014 
to support the monetary policy transmission mechanism and provide the 
amount of policy accommodation needed to ensure price stability. The room for 
further interest rate cuts had become very limited after monetary conditions were 
eased in the wake of the financial and sovereign debt crises by cutting key interest 
rates and deploying unprecedented measures to support monetary policy 
transmission. The APP, in combination with negative interest rates on the deposit 
facility, forward guidance and TLTROs, has helped the ECB meet its price stability 
objective. The APP comprises the third covered bond purchase programme (CBPP3, 
launched on 20 October 2014), the asset-backed securities purchase programme 
(ABSPP, launched on 21 November 2014), the public sector purchase programme 
(PSPP, launched on 9 March 2015) and the corporate sector purchase programme 
(CSPP, launched on 8 June 2016). APP net asset purchases were conducted until the 
end of December 2018, involving a total amount of €2.6 trillion. A snapshot of the APP 
portfolio in December 2018 shows the PSPP contributing the largest share, 

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purchases 

69 

 
 
accounting for 82% of the total net purchases, followed by the CBPP3 (10%), the 
CSPP (7%) and the ABSPP (1%). The size of the APP portfolio is currently being kept 
stable by reinvesting principal payments from maturing securities. 

2 

The monetary policy rationale for launching the APP 

Following a double-dip recession in the wake of the financial and sovereign 
debt crises, the euro area experienced a prolonged period of deleveraging, an 
atypically shallow recovery and persistently weak inflation. Bank lending 
conditions started to deteriorate and loan volumes (in particular those involving 
non-financial corporations) to contract at the end of 2011. Persistent weakness in the 
underlying growth momentum perpetuated capacity underutilisation, as also visible in 
high levels of unemployment. Inflation rates exhibited a protracted downward trend: in 
the core components, this was due to the general economic weakness, while declines 
in energy and food prices influenced the headline readings. Euro area inflation was 
generally projected to remain weak and fall over time, as reflected in successive 
downward adjustments in macroeconomic projections by most international 
organisations and the ECB (see Chart 1). Euro area annual HICP inflation fell to -0.2% 
in December 2014, and Eurosystem staff macroeconomic projections entailed further 
substantive downward revisions of inflation forecasts, from 1.1% to 0.7% in 2015 and 
from 1.4% to 1.3% in 2016. 

Chart 1 
Actual and projected HICP inflation with revisions 

(percentages, year-on-year) 

HICP inflation
Dec 2018 BMPE
Dec 2014 BMPE

3.0

2.5

2.0

1.5

1.0

0.5

0.0

-0.5

-1.0

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

2021

Sources: Eurosystem staff macroeconomic projections and ECB calculations. 
Notes: The grey lines in the chart refer to projected HICP inflation underpinning the (Broad) Macroeconomic Projection Exercise 
((B)MPE) projection vintages in 2014 and 2018. 

Persistently weak inflation in 2013-2014 contributed to a downtrend in inflation 
expectations and an increasing risk of those expectations becoming unmoored 
from the ECB’s price stability objective. Market-based measures of inflation 
expectations drifted to extraordinarily low levels. At the end of December 2014 the 
option-implied probability density function of euro area inflation indicated that markets 

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70 

 
 
 
assigned a probability of almost 50% to deflation and saw only a marginal probability 
of annual inflation reaching a level close to 2% or above (see Chart 9 below). These 
developments indicated risks that too prolonged a period of low inflation could become 
entrenched in inflation expectations, with adverse consequences for price stability. 

To reverse the downtrend in inflation and forestall a disanchoring of inflation 
expectations, the APP was designed to expand and complement existing 
monetary policy measures. With the APP, announced in January 2015, the PSPP, 
an additional programme consisting of purchases of debt securities issued by public 
entities, was launched to complement the two ongoing asset purchase programmes, 
the CBPP3 and the ABSPP. 

During the period 2015-2018 net asset purchases under the APP were the 
principal instrument of monetary policy and their size and duration were linked 
to achieving a sustained adjustment in the path of inflation towards price 
stability. In January 2015, following the APP announcement, net asset purchases 
were made the principal policy instrument and the Governing Council adopted a 
structured forward guidance. The first building block of this guidance pertained to the 
principal instrument itself and featured a combination of a time-dependent and 
state-dependent formulation. The time-dependent leg stated that the net asset 
purchases were intended to run at a certain monthly pace at least until a specific date 
(see Figure 1). The state-dependent leg established an explicit link to the price 
stability objective (“or beyond, if necessary, and in any case until the Governing 
Council sees a sustained adjustment in the path of inflation consistent with its inflation 
aim”). As shown in Figure 1, following the first announcement in January 2015 the 
Governing Council extended the programme through a series of recalibrations, in 
which the minimum horizon for the monthly purchases was pushed back sequentially 
and the pace of purchases was adjusted as necessary to advance progress towards 
the sustained adjustment. The second building block of the forward guidance 
pertained to the period over which the Governing Council expected that it would not be 
appropriate to raise the key ECB interest rates. In March 2016 the length of that period 
was linked to the end of the net asset purchases. 

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purchases 

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Figure 1 
Summary of the APP and other policy measures between June 2014 and 
December 2018 

APP

Other policy measures

ABSPP-CBPP3
Purchases of ABS and covered bonds

TLTRO-I
Max. maturity in September 
2018 with uptake depending 
on net lending and 
mandatory early repayment

Jun 2014

Sep 2014

PSPP purchases of public sector securities
€60bn monthly purchases until September 2016, 
including ABSPP/CBPP3

Jan 2015

APP recalibration I
Extension to March 2017 and reinvestment of 
principal payments

Dec 2015

APP recalibration II
€80bn monthly purchases 
and higher issue share limit 
for certain issuers

CSPP purchases of 
corporate sector 
securities

Mar 2016

APP recalibration III
€60bn monthly purchases until December 2017, 
minimum remaining maturity for PSPP-eligible 
securities reduced from two years to one and 
purchases below the DFR if necessary

TLTRO-II
No mandatory early 
repayment and minimum 
lending rate at the DFR

Jun 2016

Dec 2016

MRO: 0.15%
MLF: 0.40%
DFR: -0.10%

MRO: 0.05%
MLF: 0.30%
DFR: -0.20%

MRO: 0.05%
MLF: 0.30%
DFR: -0.30% 

MRO: 0.00%
MLF: 0.25% 
DFR: -0.40%

APP recalibration IV
€30bn monthly purchases until September 2018 
(starting from January 2018)

Oct 2017

APP transition
€15bn monthly purchases until December 2018

Jun 2018

APP transition
End of net purchases and reinvestment of maturing 
securities

Dec 2018

Source: ECB.   
Notes: MRO indicates the interest rate on main refinancing operations, MLF the interest rate on the marginal lending facility and DFR the 
interest rate on the deposit facility.   

The Governing Council adopted APP modalities in accordance with the primary 
objective of price stability. APP design features were geared to provide the degree 
of policy accommodation necessary to deliver on the price stability mandate when it 
was hardly possible to lower key interest rates any further. In line with the prohibition 
on monetary financing laid down in Article 123 of the Treaty on the Functioning of the 
European Union, purchases of public sector securities were limited to the secondary 
market. 

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purchases 

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The APP was designed to take into account both market structures and the 
institutional set-up of the euro area. Purchases of public debt instruments were 
guided by the ECB capital key, which specifies the share of the ECB’s capital 
attributable to each of the national central banks. At the same time, private sector 
programmes were based on the market capitalisation of the eligible bonds included in 
the purchases. 

3 

Implementation issues 

3.1 

Market neutrality 

When implementing the APP, the Eurosystem aimed to ensure market neutrality 
in order to minimise the impact on relative prices within the eligible universe 
and unintended side effects on market functioning. For instance, while aimed at 
affecting bond prices, the APP purchases were conducted with a view to preserving 
the price discovery mechanism and limiting distortions in market liquidity. Key features 
designed to ensure market neutrality in APP implementation are detailed below. 

Clear and observable monthly APP targets were defined, with seasonal patterns 
in market liquidity also being taken into account. The average monthly APP target 
set ex ante by the Governing Council was decomposed internally into monthly 
purchase guidance per programme. The programme operating in the most liquid 
market, the PSPP, acted as a buffer to ensure the precise fulfilment of the overall 
monthly purchase target. In addition, the Eurosystem took into account seasonal 
patterns in fixed income market activity, such as the decline in market liquidity from 
mid-July to late August and in December. Purchase activity was front and back-loaded 
around these periods (see Chart 2). In all months, the purchase guidance was 
expressed in monthly totals, rather than strict daily volumes, providing flexibility in the 
day-to-day execution of purchases. 

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purchases 

73 

 
 
Chart 2 
Pace and composition of net APP purchases 

(EUR billions) 

PSPP
CSPP
CBPP3
ABSPP
Average monthly APP target

90

80

70

60

50

40

30

20

10

0

t
c
O

c
e
D

2014

r
a
M

n
u
J

p
e
S

c
e
D

r
a
M

n
u
J

p
e
S

c
e
D

r
a
M

n
u
J

p
e
S

c
e
D

r
a
M

n
u
J

p
e
S

c
e
D

2015

2016

2017

2018

Source: ECB. 
Note: The average monthly APP targets were first set by the ECB Governing Council at the beginning of the PSPP in March 2015.   

Comprehensive ex ante communication on the operational parameters of the 
APP supported the price discovery mechanism. The parameters defined the 
operational scope of the APP through (i) stringent eligibility criteria aligned with the 
procedures in place for the Eurosystem collateral framework45  and using the expertise 
of Eurosystem collateral management experts, (ii) maturity restrictions,46  (iii) the 
exclusion of certain issuers,47  (iv) pricing frameworks to ensure that purchases were 
conducted taking into account available market prices, and (v) different limit 
systems. 48 

The Eurosystem took a rule-based approach to the composition of purchases 
with a view to maintaining adequate diversification across issuers and 
counterparties. APP purchases were broad-based across jurisdictions, maturity 
segments, issuers and types of eligible bond in terms of different coupon types or 
different collateral types, for instance. For the PSPP, the ECB’s capital key provided a 
straightforward, stable guideline for the composition of purchases across jurisdictions. 

45    Assets were thus subject to a minimum credit quality requirement of step 3 on the Eurosystem’s 

harmonised rating scale, which implied having at least one credit rating provided by an external credit 
assessment institution accepted under the Eurosystem credit assessment framework. Assets were also 
required to be euro-denominated and issued and settled within the euro area. For ABSs, the underlying 
debtors were required to be predominantly located within the euro area. 

46    At the end of 2018, the minimum remaining maturity for the PSPP was one year and the maximum 

remaining maturity 30 years. The minimum remaining maturity for the CSPP was six months and the 
maximum remaining maturity 30 years. No maturity restrictions were defined for the CBPP3 or the 
ABSPP. 

47    Securities issued by credit institutions were not eligible for the CSPP. Debt securities of bad banks were 

not eligible for the PSPP. 

48    The issue share limit for the private sector purchase programmes was 70%, with lower limits for the 

CSPP in specific cases. The PSPP issue share limit was 33% of the issued amount outstanding, subject 
to case-by-case verification that it would not lead to the Eurosystem having a blocking majority for the 
purpose of collective action clauses (in which case it was set at 25%). The PSPP issuer limit was also 
33%. 

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The Eurosystem geared its monthly purchase allocation to align a jurisdiction’s 
share in the stock of PSPP purchases as closely as possible with the respective 
share of the ECB capital key by the end of the net asset purchase phase. Chart 3 
illustrates the deviation of the share of cumulative net purchases at the end of 2018 
relative to the ECB capital key for each jurisdiction. For instance, the Eurosystem’s 
stock of German securities at the end of 2018 was 4.5% above the German share of 
the ECB capital key. This surplus equates to €22.3 billion. 

Chart 3 
Deviation in the share of net cumulative purchases relative to the ECB capital key at 
the end of 2018 

(percent) 

20

0

-20

-40

-60

-80

-100

IT

AT

FR

BE

ES

DE

NL

FI

IE

SI

PT MT

SK

LU

LT

LV

CY

EE GR

Source: ECB. 

A relative share of the PSPP stock above the ECB capital key in a jurisdiction 
resulted mechanically from the need to offset downward deviations in other 
jurisdictions. These downward deviations arose for two reasons. First, Greek 
government bonds were ineligible for the PSPP over the entire net asset purchase 
phase. Second, limitations were experienced in the availability of bonds for purchase, 
which arose, for instance, as bonds were held by hold-to-maturity investors or 
because of the overall size of the eligible universe in some jurisdictions. 

APP purchases were executed regularly, while some flexibility was maintained 
to adapt to prevailing market conditions (see Box 1). The Eurosystem aimed to 
maintain a continuous market presence throughout the day, thereby avoiding 
temporary market dominance. Depending on a central bank’s operational modalities, 
flexibility can relate inter alia to the selection of securities to purchase, the timing of 
operations and the overall purchase amount for the day. Moreover, spreading 
purchases flexibly across the different asset classes included in a programme also 
helped to preserve market neutrality. As an example of this flexibility, the share of 
regional government purchases as a proportion of total PSPP purchases fluctuated 
significantly in 2018 (see Chart 4). 

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purchases 

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Chart 4 
Central government, agency and regional government purchases 

(percentage shares of PSPP purchases) 

Central governments
Agencies
Regional governments

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

03/15

09/15

03/16

09/16

03/17

09/17

03/18

09/18

Source: ECB. 

Box 1 
Purchase methods 

Prepared by Bryan Gurhy and Beatriz Sotomayor 

The Eurosystem executed close to 225,000 transactions under the APP between 2014 and 
2018. These transactions were conducted in accordance with the conventions of the respective fixed 
income market and alongside other market participants. Over time, the Eurosystem fine-tuned its 
purchase methods to reflect evolving market conditions. This box describes the main purchase 
elements of the APP. 

All Eurosystem NCBs and the ECB executed APP purchases, with the ECB also coordinating 
the implementation of the programmes. PSPP purchases were conducted by the entire 
Eurosystem. The CBPP3 was executed by a large number of NCBs and the ECB, while six 
specialised NCBs49  bought assets under the CSPP. As of April 2017, ABSPP purchases have been 
conducted exclusively by six NCBs acting as internal asset managers. 50  Prior to that, external asset 
managers and some NCBs had conducted the ABSPP purchases together. 

Purchases under the private sector programmes were conducted alongside other market 
participants in both the primary and the secondary market, with the proportional shares 
varying over time as a reflection of issuance patterns and secondary market liquidity (see 
Chart A). The standard Eurosystem primary market bid size was set with a view to striking a balance 
between supporting individual issuances and drawing on the flexibility offered by secondary market 
purchases. 

49    The six specialised central banks were the Nationale Bank van België/Banque Nationale de Belgique, the 
Deutsche Bundesbank, the Banco de España, the Banque de France, the Banca d’Italia and Suomen 
Pankki − Finlands Bank. 

50    Central banks involved in this task were the Nationale Bank van België/Banque Nationale de Belgique, 
the Deutsche Bundesbank, the Banco de España, the Banque de France, the Banca d’Italia and De 
Nederlandsche Bank. 

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Chart A 
Private programme purchases broken down by primary and secondary market 

(EUR millions) 

CBPP3 PM
CBPP3 SM
CSPP PM
CSPP SM
ABSPP PM
ABSPP SM

40,000

35,000

30,000

25,000

20,000

15,000

10,000

5,000

0

-5,000

Q4

Q1

Q2

Q3

Q4

Q1

Q2

Q3

Q4

Q1

Q2

Q3

Q4

Q1

Q2

Q3

Q4

2014

2015

2016

2017

2018

Source: ECB. 
Notes: Purchases approximated from change in holdings. Negative values for a subcategory indicate that redemptions were greater than gross purchases for 
that period. 

The majority of APP purchases were executed by bilateral trades with counterparties. These 
trades were conducted via major electronic platforms and by voice. Bilateral trading entails 
responding flexibly to market participants’ offers, requesting prices from several counterparties for the 
same security and then trading at the best price. Bilateral trades are particularly well suited to the 
liquidity and heterogeneity of euro area bond markets as they can be tailored to market conditions in 
order to avoid market distortions. For instance, the PSPP purchased securities of 110 issuers,51  while 
other major central banks generally purchased only a single sovereign issuer when implementing 
their large-scale asset purchase programmes. 

The Deutsche Bundesbank, the Banque de France, Lietuvos Bankas and De Nederlandsche 
Bank conducted regular auctions in specific market segments when implementing the PSPP. 
The decision to use auctions reflected the intention to achieve certain volumes while also taking 
account of transparency considerations. In the days before each auction, market participants were 
provided with a list of securities that each NCB was considering buying at prevailing market prices. 
This gave counterparties a well identified “liquidity window” every week to communicate their interest 
in selling specific securities while being guaranteed equal pricing. Some NCBs focussed their 
auctions on illiquid bonds, which were difficult to source bilaterally, while others used auctions for 
liquid bonds to foster price transparency for other market participants. The Eurosystem applied the 
same trading rules to align the purchase price in bilateral trading and reverse auctions with the 
prevailing market offer price. 

Bid wanted in competition (BWIC) is a transaction method specific to the ABS market. BWICs 
are organised by dealers on behalf of investors to sell ABS holdings while ensuring best execution by 
inviting a large range of potential buyers. The ABSPP regularly participated in BWICs for both liquid 
and less liquid jurisdictions and across all ABS collateral types. The share of ABSPP purchases 

51    In addition to the 17 central government issuers, the PSPP purchased securities of 43 PSPP-eligible 
agencies and of 43 regional governments and six EU supranational institutions as well as one 
non-financial corporate. 

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77 

 
 
                                                                    
 
executed through BWICs was relatively low, however, as the Eurosystem aimed to purchase at 
market prices without pushing prices to artificially high levels. The ECB set up a governance structure 
to assess all securities purchased and provide guidance on appropriate market pricing. 

3.2 

Fixed income market liquidity and its interaction with APP 
implementation 

The APP purchases were executed in a way that aimed to safeguard the 
liquidity of euro area fixed income markets. Eurosystem staff regularly assessed 
bond market liquidity indicators. Taken together with market intelligence, these 
assessments indicate that the design of the APP has been successful in mitigating 
potential detrimental effects on market functioning and that the impact of the APP on 
market liquidity has been at most transitory. 52 

Daily purchase modalities, and in particular the day-to-day selection of 
securities to be purchased, were applied with a view to preserving market 
liquidity conditions. The Eurosystem actively incorporated the offers from a broad 
range of counterparties in the daily bond selection. In addition, significant efforts were 
undertaken to avoid buying securities that were scarce, as measured by such metrics 
as relative value indicators, pricing in the repo market and trading volumes. 

The size of individual transactions was responsive to the observed offer sizes. 
For APP transactions, the average secondary market transaction ranged from 
€4 million in the CSPP to €14 million in the PSPP. These averages mask 
compositional heterogeneity, with transaction sizes increasing for more liquid 
securities and declining for illiquid bonds. 

Using a broad set of counterparties facilitated the smooth implementation of 
purchases and fostered competition, with the Eurosystem trading with more 
than 350 counterparties. A very large majority of APP purchases involve 
counterparties located in a different country from the purchasing central bank, which 
also impacted the distribution of Target 2 balances across jurisdictions.53  Individual 
central banks expanded their set of counterparties in order to reach all relevant 
segments of the fixed income market. APP implementation thus avoided persistent 
effects in the micro-structure of bond market segments through the competitive use of 
counterparties. Against this background, the Eurosystem adopted a wide range of 
transparency tools to minimise the informational advantages for eligible 
counterparties. These initiatives helped to level the playing field among financial 
market participants while preserving the timely execution of operations (see Box 2). 

52    See Jurskas et al., “Euro area sovereign bond market liquidity since the start of the PSPP”, Economic 

Bulletin, Issue 2, ECB, 2018, pp. 41-44. 

53    See Box 1 entitled “The ECB’s asset purchase programme and TARGET balances: monetary policy 
implementation and beyond”, Economic Bulletin, Issue 3, ECB 2017, pp. 21-26 and Box 2 entitled 
“TARGET balances and the asset purchase programme”, Economic Bulletin, Issue 7, ECB, 2016, 
pp. 20-23. 

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Box 2 
Providing additional transparency on aggregate APP holdings 

Prepared by Kieran Leonard and Beatriz Sotomayor 

Transparency has played a central role in the APP by allowing market participants to better 
understand how the programmes are implemented. The regular disclosure of information on APP 
purchases and holdings on the ECB website was complemented by additional information on the 
CSPP in a box in the June 2017 issue of the Economic Bulletin.54  Similar data on the aggregate 
holdings of the CBPP3 and the ABSPP are presented below. In addition, the box provides a 
comparison of the weighted average maturity of PSPP net cumulative purchases with the relevant 
eligible universe. 

CBPP3 purchases were broadly oriented towards a market capitalisation-based benchmark of 
eligible securities, with due consideration being given to market liquidity conditions. This 
allowed purchases to be conducted across a broad range of countries on an ongoing basis. The 
Eurosystem was responsive to the availability of individual bonds in day-to-day implementation. 

Table A 
Country and rating distributions of CBPP3 holdings and benchmark at the end of 2018 

Country of risk distribution 

Credit rating distribution 

Jurisdiction 

Holdings 

Benchmark 

Rating 

Holdings 

Benchmark 

FR 

DE 

ES 

IT 

NL 

FI 

AT 

Other euro area 

26.2% 

22.0% 

21.8% 

11.5% 

5.7% 

3.7% 

3.3% 

5.7% 

30.0%  AAA 

22.8%  AA 

15.1%  A 

9.0%  BBB 

8.3% 

4.6% 

4.4% 

5.9% 

68.9% 

28.1% 

2.7% 

0.3% 

76.5% 

20.4% 

2.7% 

0.3% 

Sources: ECB and ECB calculations. 
Notes: The benchmark is constructed using the universe of eligible securities pertaining at the end of 2018. The weights of certain covered bond classes have 
been adjusted lower to reflect their lack of availability and illiquidity. Only bonds with an asset rating are included in the data for the credit rating distribution. The 
ratings are first-best asset ratings. The distributions are by nominal value. 

The market capitalisation approach evolved over time, with the benchmark weights attached 
to certain securities decreasing as some covered bond categories were found to be 
increasingly hard to purchase. For example, the launch of TLTRO-II increased the attractiveness of 
retaining covered bonds as collateral rather than placing them in the market. To account for this, the 
relative weight of retained covered bonds was reduced in the eligible CBPP3 benchmark. 

To accommodate the dynamic nature of the CBPP3-eligible universe, with its variable 
issuance patterns and liquidity conditions across jurisdictions, the market 
capitalisation-based benchmark was updated regularly so as to guide future purchases. This 
evolutionary approach is the main explanation for the differences evident in Table A, where, for 
example, CBPP3 holdings in Spanish covered bonds are considerably higher than the current 
benchmark would imply. At the same time, the share of French covered bonds in the holdings has 
increased over time, guided by an increase in their benchmark weight. The deviations in the rating 

54    See Box 2 entitled “The ECB’s corporate sector purchase programme: its implementation and impact”, 

Economic Bulletin, Issue 4, ECB, 2017, pp. 40-45. 

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distribution between CBPP3 holdings and the current benchmark also reflect the outcome of the 
evolutionary approach. 

Turning to the ABSPP, the cumulative gross purchases have been added to the presentation 
of holdings to provide a more accurate illustration of implementation across the Eurosystem 
(see Table B). This additional information is needed to reflect the faster repayment of ABSs 
compared to other fixed income asset classes, with cumulative gross purchases of €51.6 billion set 
against holdings of only €27.5 billion at end-2018. 

Table B 
Country, collateral and rating distribution of ABSPP holdings and universe at the end of 2018 

Country of risk distribution 

Credit rating distribution 

Jurisdiction  

Gross purchases 

Holdings 

Universe 

Rating 

Holdings 

Universe 

NL 

IT 

DE 

ES 

FR 

IE 

PT 

FI 

BE 

41.4% 

18.7% 

17.2% 

8.2% 

8.0% 

2.5% 

2.3% 

1.0% 

0.7% 

50.1% 

13.5% 

12.7% 

9.8% 

6.9% 

3.7% 

1.6% 

1.0% 

0.7% 

38.1%  AAA 

15.4%  AA 

16.0%  A 

10.8%  BBB 

87.0% 

12.1% 

0.8% 

0.1% 

80.0% 

15.4% 

4.4% 

0.2% 

10.4% 

Collateral type distribution 

4.1% 

Collateral 

Holdings 

Universe 

3.3%  Residential mortgages 

0.6%  Auto loans 

1.3%  Consumer loans 

   Leasing contracts 

   Credit card receivables 

   Loans granted to SME 

71.5% 

19.7% 

6.3% 

1.1% 

0.8% 

0.6% 

61.9% 

20.3% 

8.4% 

6.2% 

1.3% 

1.9% 

Sources: ECB, Bloomberg, company publications. 
Notes: The universe is a theoretical measure of the purchasable senior tranche securities eligible as Eurosystem collateral outstanding at the end of 2018. Credit 
rating distribution based on second-best rating consistent with collateral eligibility. The distributions are by outstanding amount. 

Gross ABSPP purchases were more broadly distributed across jurisdictions than the 
holdings at the end of 2018 would indicate, reflecting the prevalence of different asset types 
in each country. For example, auto ABSs dominate the German ABS market. These securities have 
a much lower weighted average life than residential mortgage backed securities (RMBS), which are 
more common in the Netherlands. Furthermore, the portfolio composition also reflected market 
capitalisation and market liquidity. Core markets with lower yielding securities generally had a higher 
number of actively offered securities, which has led to some over-representation of Dutch RMBS in 
the portfolio, for example. At the same time, non-core and higher yielding securities were largely held 
by hold-to-maturity investors and were not offered to the Eurosystem to the same extent. Moreover, 
there was a higher concentration in securities issued since the start of the ABSPP, given the ability of 
the ABSPP to make primary market purchases and hence purchase larger volumes in these issues. 
This resulted in a lower presence in jurisdictions with less issuance since October 2014, such as 
Spain and Portugal. 

With regard to the PSPP, a comparison of the weighted average maturity (WAM) of cumulative 
net purchases with the WAM of the eligible universe shows that they were broadly in line with 
each other at the end of 2018 (see Table C). The dispersion of WAMs of the eligible universe 
across jurisdictions reflects the past issuance patterns of PSPP-eligible issuers. The WAM measure 
for cumulative net purchases includes the contribution of bonds which are no longer eligible owing to 
a maturity of less than one year and broadly reflects the availability of individual bonds for purchase 

ECB Economic Bulletin, Issue 2 / 2019 – Article 
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purchases 

80 

 
 
  
  
  
  
  
  
  
  
  
across time. Moreover, securities with short to medium-term maturities at the start of the PSPP were 
already extensively held by the Eurosystem as a result of the securities markets programme. These 
holdings limited the ability to purchase such bonds under the PSPP in certain jurisdictions. Therefore, 
the WAM measure for cumulative net purchases in these jurisdictions is higher than would have 
otherwise been the case. 

Table C 
Weighted average maturities by jurisdiction for the PSPP at the end of 2018 

(years) 

Jurisdiction 

BE  DE  EE 

IE  GR  ES  FR 

IT  CY  LV  LT  LU  MT  NL  AT  PT 

SI 

SK 

FI  EU  Total 

Cumulative net purchases 

9.2  6.3  0.0 

8.8  0.0  8.3  7.3  7.5  5.8  8.7  8.5  4.9  10.6  7.2  8.1  7.8  10.6  9.1  7.1  7.5 

7.4 

Eligible universe 

10.1  7.2  0.0 

8.8  0.0  8.2  7.9  7.7  5.1  9.8  9.1  5.7 

9.9  8.2  8.1  7.2  10.2  8.9  7.6  8.2 

7.9 

Notes: The WAM measure for cumulative net purchases in jurisdictions which were purchased under the ECB’s securities markets programme (SMP) is higher 
than would have been the case if many short to medium-term maturity securities had not already been extensively purchased under the SMP. 

3.3 

Securities lending 

APP securities lending facilities addressed challenging repo market conditions. 
Combined with the gradual expansion of PSPP holdings, increasing demand for high 
quality liquid assets in line with regulatory requirements contributed to challenging 
repo market conditions through 2016. The Eurosystem purchases reduced the 
effective availability of securities for market participants, which could have resulted in 
a shortage of bonds to be used as collateral55  and lower market liquidity, while 
possibly impairing the price discovery mechanism. The Eurosystem’s securities 
lending approach served to minimise such unintended consequences of the APP.56 

The Eurosystem conducts securities lending activities, which continue in the 
reinvestment phase of the APP, in a decentralised manner on the basis of 
common principles. The Eurosystem acts as a backstop without curtailing normal 
repo market activity. 57  The institutional set-up of the Eurosystem means that 
securities lending implementation is decentralised and various lending channels are 
used (e.g. bilateral lending or through custodians). As illustrated in the upper panel of 
Chart 5, the share of German government bonds trading “special” – that is trading at a 
premium to general collateral in the repo market – increased markedly in 2016. The 
Eurosystem responded by introducing a number of modifications to the securities 
lending facilities, such as the option to borrow bonds against cash collateral. This was 
introduced in December 2016, effectively increasing the supply of bonds available in 

55    Government bonds are the main type of collateral used in the euro repo markets due to their safety and 

liquidity. 

56    PSPP securities were made available for lending in April 2015, shortly after the start of the purchases. 

Lending of CSPP securities by Eurosystem NCBs is also mandatory, while lending of CBPP3 holdings is 
voluntary. However, holdings from each covered bond jurisdiction are made available for lending by at 
least one Eurosystem central bank. Lending of ABSPP holdings is possible in principle, but no requests 
have been received since the start of the programme. 

57    To ensure this, the lending is conducted at a certain spread against general collateral (for lending against 
securities), and the cash collateral option (for PSPP only) is offered at a rate equal to the lower of the rate 
of the deposit facility minus 30 basis points and the prevailing market repo rate. 

ECB Economic Bulletin, Issue 2 / 2019 – Article 
Taking stock of the Eurosystem’s asset purchase programme after the end of net asset 
purchases 

81 

the repo market and reducing the share of bonds trading special.58  Several other 
beneficiary owners also enhanced their securities lending facilities during this period. 

Chart 5 
Repo market developments for German government bonds – the share of special 
trades in total volume and the evolution of the repo rate 

(percentages) 

Share of special trades
RepoFunds Rate index

100%

80%

60%

40%

20%

0%
0%

-1%

-2%

-3%

-4%

-5%

-6%

07/15

10/15

01/16

04/16

07/16

10/16

01/17

04/17

07/17

10/17

01/18

04/18

07/18

10/18

01/19

Sources: ECB calculations, NEX Data and MTS Markets. 
Notes: Special trades are defined as volume traded at least 25 basis points lower than the cheapest specific German bond on a given 
day. They are expressed as a share of total volume on any given day. 

The PSPP on-loan balance fluctuated, with peaks occurring at quarter-ends and 
ahead of futures delivery dates. At the end of 2017, the market value of bonds lent 
out peaked at €87 billion, €33 billion of which was lent against cash collateral (see 
Chart 6, right panel). The average monthly on-loan balance however stabilised 
between €50 billion and €60 billion since mid-2018, representing 2.4-2.8% of the 
respective monthly PSPP holdings (see Chart 6, left panel). 

58    The overall limit for securities lending against cash collateral was initially set at €50 billion and was 

increased to €75 billion in March 2018, also reflecting the increase in the stock of acquired assets in the 
meantime. 

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purchases 

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Chart 6 
PSPP on-loan balance divided into loans against securities collateral and cash 
collateral 

(EUR billions) 

Loans against securities collateral
Loans against cash collateral

Quarter-ends
Futures deliveries

90

80

70

60

50

40

30

20

10

90

80

70

60

50

40

30

20

10

0
07/15

07/16

07/17

07/18

0
11/17

02/18

05/18

08/18

11/18

Sources: ECB calculations. 
Notes: Amounts are in market value terms. Starting 15 December 2016, the Eurosystem introduced the option of also accepting cash as 
collateral in its PSPP securities lending facilities. 

4 

Transmission and impact on the macroeconomy 

4.1 

Main transmission channels 

The APP has provided a substantial improvement in financing conditions via 
several transmission channels, and each individual policy measure, being part 
of a package of policy measures, has benefitted from reinforcing synergies. 
Evidence based on event studies shows that yields fell significantly across all financial 
market segments following the APP announcement.59  Over the course of APP 
implementation, declining bank lending rates and credit expansion helped to ease 
financing conditions, support a firming of the economic recovery and counter 
disinflationary forces. As documented by a large body of literature, the APP operates 
through three main channels: the signalling channel, the portfolio rebalancing channel 
and the direct pass-through channel.60  The package of policy measures of which the 
APP was part has created mutually reinforcing synergies across the individual 
measures. 

59    See Dell’Ariccia, G., Rabanal, P. and Sandri, D., “Unconventional Monetary Policies in the Euro Area, 
Japan, and the United Kingdom”, Journal of Economic Perspectives, Volume 32, Number 4, Fall 2018, 
pp. 147-172; Altavilla, C., Carboni, G. and Motto, R., “Asset purchase programmes and financial 
markets: lessons from the euro area”, Working Paper Series, No 1864, ECB, November 2015; De Santis, 
R., “Impact of the asset purchase programme on euro area government bond yields using market news”, 
Working Paper Series, No 1939, ECB, July 2016; and De Santis, R. and Holm-Hadulla, F., “Flow effects 
of central bank asset purchases on euro area sovereign bond yields: evidence from a natural 
experiment”, Working Paper Series, No 2052, ECB, May 2017. 

60    For an overview of the channels and further analyses, please see the article entitled “The transmission of 
the ECB’s recent non-standard monetary policy measures”, Economic Bulletin, Issue 7, ECB, 2015, and 
the box entitled “Impact of the ECB’s non-standard measures on financing conditions: taking stock of 
recent evidence”, Economic Bulletin, Issue 2, ECB, 2017. 

ECB Economic Bulletin, Issue 2 / 2019 – Article 
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purchases 

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Via the signalling channel, the APP has underscored the ECB’s intention to 
provide sufficient monetary stimulus for an extended period of time, thereby 
also contributing to anchor policy rate expectations. The APP has enhanced the 
signal that key policy rates would remain low for long. The signalling aspect of central 
banks’ large-scale asset purchases has always been found to be an important 
component of transmission for such policy programmes. This component was 
reinforced in March 2016, when the Governing Council’s communication of the 
expected future rate path was made conditional on the end of net asset purchases.   

Via the portfolio rebalancing channel, the APP has compressed yields across a 
wide range of asset classes, with negative rates on reserves providing 
additional incentives to the rebalancing process. With the price of the purchased 
assets being bid up, their yields decrease. The lower yields induce investors to sell 
these securities, earning the associated capital gain. As sellers may not view holding 
the liquidity received as being a perfect substitute for the assets sold, they reinvest 
and rebalance their portfolios towards other assets, such as securities and loans (see 
also Box 4). This process is reinforced by the negative rates charged on reserves. 61 
Consequently, yields also decreased in other market segments not targeted by the 
central bank purchases, including a rebalancing in non-euro denominated debt and 
equity markets.62 

Within the portfolio rebalancing channel, the extraction of duration risk has 
been a particularly relevant mechanism affecting the term premium component 
of medium and long-term yields (Box 3). Asset purchases decrease the duration 
risk borne by private investors, thus increasing their risk-bearing capacity and 
incentivising them to restore the desired overall risk profile of their portfolio by 
investing in different assets. Therefore, duration extraction affects the pricing of 
maturities and asset classes beyond securities purchased. 

Via the direct pass-through channel, which comes into play for the ABSPP and 
the CBPP3 in particular, the APP has directly improved credit conditions for the 
private non-financial sector. At the same time, the CBPP3 and TLTROs have 
interacted to foster lending to small and medium-size enterprises (SMEs) as well.63 
More generally, TLTROs have alleviated the funding costs for participant banks, thus 
mitigating possible negative effects on bank lending stemming from negative rates on 
reserves. Central bank purchases have raised the price of ABS and covered bonds, 
lowered the market interest rate paid by the originators and encouraged banks to 
create more loans with a view to repackaging them and selling them on. Through this 
mechanism, bond purchases have supported borrowing conditions in the private 
non-financial sector. Similarly, the CSPP has reduced funding costs for firms 
accessing financial markets directly and supported a switch from bank funding to 

61    See Ryan, E. and Whelan, K., “Quantitative Easing and the Hot Potato Effect: Evidence from the Euro 

Area Banks”, Research Technical Paper, Vol. 2019, No. 1, Central Bank of Ireland, 2019.   

62    See “The international dimension of the ECB’s asset purchase programme”, speech by Benoît Cœuré, 
Member of the Executive Board of the ECB, at the Foreign Exchange Contact Group meeting, Frankfurt 
am Main, 11 July 2017. 

63    See the article entitled “MFI lending rates: pass-through in the time of non-standard monetary policy”, 

Economic Bulletin, Issue 1, ECB, 2017. 

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purchases 

84 

 
 
                                                                    
market funding for large firms, thereby freeing up capacity on bank balance sheets to 
finance loans to SMEs.64 

Box 3 
The impact of the APP on the term structure of euro area bond yields – a model-based 
assessment 

Prepared by Fabian Eser, Wolfgang Lemke and Andreea Liliana Vladu 

The term premium component of yields reflects the aggregate duration risk borne by 
investors. Risk-free long-term bond yields have two components: average expectations of 
short-term interest rates over the life of the bond and a term premium. The latter comprises the 
current and future expected risk exposure of individual bonds (their bond-specific duration risk), as 
well as the compensation per unit of risk exposure. This compensation – the “price of risk” – depends 
in turn on the aggregate duration risk to be borne by the market. 

Central bank asset purchases decrease the overall duration risk to be absorbed by private 
investors, thus reducing the price of risk and, in turn, the term premium. Importantly, the effect 
of asset purchases on the term premium depends on the entire path of the duration-weighted bond 
portfolio acquired. For a ten-year bond, lower aggregate duration risk in, say, five years decreases the 
required risk compensation in the future and hence also the term premium today. 

The APP’s impact on the term premium can be estimated using an arbitrage-free term 
structure model.65  The drivers of bond rates are summarised by three factors, one of which reflects 
the “free float of duration risk” in the hands of those market participants who are deemed willing to 
rebalance their bond portfolio when bond prices change.66  The model links current and future 
changes in the free-float to changes in current term premia and can thereby explain how current and 
expected future APP volumes affect the yield curve. 67 

The compression in sovereign yields due to the APP-induced reduction in current and 
expected bond free float is estimated to stand at around 100 basis points for the ten-year 
maturity (Chart A, left panel). The chart illustrates the impact of the APP on term premia across the 
term structure at the time when the PSPP was announced and at the end of net asset purchases in 
December 2018. The term premium impact is larger for longer maturities. 

Looking ahead, the substantial stock of acquired assets and the forthcoming reinvestments 
mean that a sizeable amount of duration risk will continue to be extracted, even after net 

64    See the article entitled “The impact of the corporate sector purchase programme on corporate bond 
markets and the financing of euro area non-financial corporations”, Economic Bulletin, Issue 3, ECB, 
2018. 

65    The model is described in more detail in Eser, F., Lemke, W., Nyholm, K., Radde, S. and Vladu, A., 

Tracing the impact of the ECB’s asset purchase programme on the yield curve, forthcoming as an ECB 
Working Paper in 2019. This has a similar framework to Li, C. and Wei, M., “Term Structure Modeling with 
Supply Factors and the Federal Reserve’s Large-Scale Asset purchase Programs”, International Journal 
of Central Banking, 9(1), 3-39, 2013, which is used by the Federal Reserve to estimate the yield impact of 
large-scale sovereign bond purchases. 

66    Non-financial corporations, households, money market funds and monetary financial institutions 

(excluding the Eurosystem) are considered to be price-sensitive. By contrast, the Eurosystem − in terms 
of both monetary policy and non-monetary policy portfolios − non-euro area official sector holdings (in 
particular central bank foreign exchange reserves), intra-euro area government bond holdings and 
holdings by insurance companies and pension funds are considered to be price-insensitive. 

67    The required free-float projections at each point in time are based on the APP parameters communicated 

by the Governing Council and on private-sector expectations as proxied by survey information. 

ECB Economic Bulletin, Issue 2 / 2019 – Article 
Taking stock of the Eurosystem’s asset purchase programme after the end of net asset 
purchases 

85 

 
 
                                                                    
purchases have ceased (Chart A, right panel). The chart plots the evolution of the ten-year term 
premium compression, based on the projected free float as at the end of net asset purchases. The 
term premium impact gradually fades over time, which reflects the ageing of the portfolio − i.e. its 
gradual loss of duration as the securities held in the portfolio mature − as well as the run-down of the 
portfolio that market participants anticipate will eventually follow the end of the expected horizon of 
reinvestments. 

Chart A 
Estimated impact of the APP on euro area sovereign yields 

Launch of the programme (Q1 2015)
End of net purchases (Q4 2018)

Point estimate
5-95% confidence band

a) Term premia impact across maturities

b) 10-year term premium impact over time

i

s
t
n
o
p
s
i
s
a
B

0

-10

-20

-30

-40

-50

-60

-70

-80

-90

-100

-110

-120

-130

i

s
t
n
o
p
s
i
s
a
B

0

-10

-20

-30

-40

-50

-60

-70

-80

-90

-100

-110

-120

-130

1

2

3

4

5

6

7

8

9

10

2018

2021

2024

2027

2030

2033

Maturity of yields in years

Years

Source: Based on Eser, Lemke, Nyholm, Radde and Vladu (2019). 
Notes: The left panel shows by how much the term premium component of sovereign euro area yields with maturities of one year to ten years are estimated to be 
compressed due to the APP, at the time of the launch of the APP (Q1 2015), as well as at the end of the net purchase phase in December 2018. The right panel 
shows point estimates of the ten-year yield term premia compression over time. The confidence band reflects parameter uncertainty around these point 
estimates, constructed using bootstrap/Monte Carlo resampling techniques. Euro area yields are proxied by the GDP-weighted zero-coupon yields of the four 
largest euro area jurisdictions. 

Quantifying the impact of the APP on the yield curve is subject to several layers of 
uncertainty. Accounting for parameter uncertainty in the model estimation suggests that the impact 
of the APP on ten-year term premia currently lies in a range of 70 to 130 basis points.68  Additional 
sources of uncertainty relate to model specification, the estimation window and the quantification of 
the free float measure. 

The APP has eased financing conditions across asset classes. Liquidity injected 
by the APP has tied up short-term money market interest rates at levels close to the 
ECB’s deposit facility rate and, together with negative rates and forward guidance, 
anchored the expected path of money market rates in line with the intended policy 
stance. Chart 7 shows the estimated accumulated easing impact of the APP across 
asset classes – alongside that from other easing measures – relative to actual asset 
price changes recorded since 2014.69  The APP is estimated to have decreased 
sovereign yields and pushed down yields of bonds issued by non-financial 
corporations (NFCs), and to have contributed to an increase in share prices. 

68    Chart 7 presents further evidence using additional methodological frameworks, together with the impact 

of other measures taken since June 2014. 

69    Box 3 presents further evidence on the impact of the APP. 

ECB Economic Bulletin, Issue 2 / 2019 – Article 
Taking stock of the Eurosystem’s asset purchase programme after the end of net asset 
purchases 

86 

 
 
 
                                                                    
 
 
 
Chart 7 
Impact of policy measures on financial prices and yields 

June and September 2014 policy measures 
APP+DFR
Change 5 February 2019 - 4 June 2014

i

s
t
n
o
p
s
i
s
a
B

0

-25

-50

-75

-100

-125

-150

-175

-200

-225

-250

0

-20

-40

-60

-80

-100

s
e
g
a
t
n
e
c
r
e
P

25

20

15

10

5

0

Euro area

DE

FR

IT

ES

10-year government yields

NFC bond
yield

Euro Stoxx

Source: ECB calculations. 
Notes: The chart shows the impact of the June and September 2014 policy measures, the APP and cuts in the deposit facility rate (DFR) 
on financial prices and yields. The impact of the June and September 2014 policy measures is estimated on the basis of an event-study 
methodology which focuses on the announcement effects of these measures; see the ECB Economic Bulletin article entitled “The 
transmission of the ECB’s recent non-standard monetary policy measures” (Issue 7/2015). The impact of the cuts of the deposit facility 
rate (DFR) rests on the announcement effects of the September 2014 DFR cut, while the impact of the subsequent DFR cuts is difficult to 
disentangle from the simultaneous APP adjustments. Both effects are therefore shown jointly. APP encompasses the effects of the asset 
purchase measures adopted at the Governing Council meetings in January and December 2015, March and December 2016, and 
October 2017. The January 2015 APP impact is estimated on the basis of two event-study exercises considering a broad set of events 
that, starting from September 2014, have affected market expectations about the programme; see Altavilla, C., Carboni, G. and Motto, 
R., op. cit., and De Santis, R., op. cit. The quantification of the impact of the December 2015 policy package on asset prices rests on a 
broad-based assessment comprising event studies and model-based counterfactual exercises. The impact of the March 2016 and 
December 2016 policy packages is assessed using model-based counterfactual exercises. The impact of the October 2017 policy 
package is assessed using two models: a term structure modelling framework similar to the one used in Box 3, and an ISIN-by-ISIN 
regression framework akin to D’Amico, S. and King, T.B., “Flow and stock effects of large-scale treasury purchases: Evidence on the 
importance of local supply”, Journal of Financial Economics, Vol. 108, Issue 2, 2013, pp. 425-448. 

Banks have played a crucial role in the transmission of net asset purchases to 
financing conditions. Bank-based financial intermediation remains very important, 
notwithstanding a trend towards market funding in the financing structure of euro area 
NFCs over the last decade. The APP, acting in conjunction with negative interest rates 
on the deposit facility and TLTROs, has incentivised banks to reinvest the proceeds 
from asset sales into loan creation (see Box 4). 

As a result, bank lending rates have steadily declined and converged across 
euro area countries since mid-2014. Composite lending rates to NFCs currently 
stand close to record lows (see Chart 8, left panel). Model-based results indicate that 
the APP and DFR cuts have led to a reduction of around 50 basis points in bank 
lending rates to NFCs since June 2014 due to their impact on the yield curve. 70 
Previously large dispersions in borrowing costs across euro area countries have 
progressively narrowed to the point of being almost fully reabsorbed. 

70    This estimate compares to an overall decline of 129 basis points in bank lending rates to NFCs between 
June 2014 and October 2018. The estimation is based on lending rate pass-through mechanisms that 
operate via the relationship between government bond yields and bank funding costs, including: 
(i) standard pass-through mechanisms used for the projections, and (ii) pass-through models using 
granular bank balance sheet information. On (ii), see Altavilla, C., Canova, F. and Ciccarelli, M., “Mending 
the broken link: heterogeneous bank lending and monetary policy pass-through”, Journal of Monetary 
Economics, 2019, forthcoming. Additionally, the TLTROs provided further downward pressure on bank 
lending rates. 

ECB Economic Bulletin, Issue 2 / 2019 – Article 
Taking stock of the Eurosystem’s asset purchase programme after the end of net asset 
purchases 

87 

 
 
 
                                                                    
 
Chart 8 
Cost of borrowing for new NFC loans and MFI loans to NFCs 

Euro area
DE
ES
FR
IT

a) Cost of borrowing for new NFC loans

b) MFI loans to NFCs

m
u
n
n
a
r
e
p
s
e
g
a
t
n
e
c
r
e
P

4.5

4.0

3.5

3.0

2.5

2.0

1.5

1.0

s
e
g
n
a
h
c
e
g
a
t
n
e
c
r
e
p

l
a
u
n
n
A

15

10

5

0

-5

-10

-15

-20

2013

2014

2015

2016

2017

2018

2013

2014

2015

2016

2017

2018

Source: ECB. 
Notes: The indicator for the total cost of borrowing is calculated by aggregating short and long-term rates using a 24-month moving 
average of new business volumes. Loans are adjusted for sales, securitisation and notional cash pooling. MFI stands for monetary 
financial institutions. The latest observations are for November 2018. 

The APP is also found to have contributed significantly to the recovery in loan 
growth. NFC loan volumes started growing again with positive rates in mid-2015. 
Model-based simulations suggest that almost half of the annual growth in NFC loan 
volumes in the third quarter of 2018 (4.3%, see Chart 8, right panel) can be attributed 
to the effects of the APP.71  Box 4 provides further details on the bank-based 
transmission of the APP to lending. 

Box 4 
Impact of the APP on lending to enterprises 

Prepared by Miguel Boucinha and Sarah Holton 

All monetary policy measures taken since mid-2014 have helped to support lending 
conditions, which makes it difficult to separate out the impact of each individual measure. 
This identification problem can be addressed by using granular data. It is possible to identify the 
contribution of the APP to lending to enterprises by matching bank-level qualitative information from 
the Bank Lending Survey (BLS) with individual bank balance sheet characteristics and lending flows. 

Granular data show that banks had diverse liquidity inflows associated with the APP. 72  Asset 
purchases increase bank liquidity directly through sales of bonds by banks and indirectly through an 

71    The figure reported corresponds to the average of alternative estimates: (i) DGSE simulations aimed at 
capturing the impact of the APP based on Darracq Pariès, M. and Kühl, M., “The optimal conduct of 
central bank asset purchases,” Working Paper Series, No 1973, ECB, 2016; (ii) estimates of the impact 
of the APP based on a VAR with time-varying parameters and stochastic volatility based on a paper by 
Gambetti, L. and Musso, A., “The macroeconomic impact of the ECB’s expanded asset purchase 
programme (APP)”, Working Paper Series, No 2075, ECB, 2017; (iii) country estimates of the impact of 
unconventional monetary policy shocks based on the multi-country BVAR model from Altavilla, C., 
Giannone, D. and Lenza, M., “The financial and macroeconomic effects of the OMT announcements,” 
International Journal of Central Banking, Vol. 12(3), September 2016, pp. 29-57. 

72    See also Altavilla, C., Canova, F. and Ciccarelli, M., op. cit.; Albertazzi, U., Becker, B. and Boucinha, M., 
“Portfolio rebalancing and the transmission of large-scale asset programmes: evidence from the euro 
area”, Working Paper Series, No 2125, ECB, 2018. 

ECB Economic Bulletin, Issue 2 / 2019 – Article 
Taking stock of the Eurosystem’s asset purchase programme after the end of net asset 
purchases 

88 

 
 
 
 
                                                                    
 
 
 
 
increase in deposits stemming from their customers’ bond sales. Linking the BLS with balance sheet 
data confirms that, on average, banks with higher holdings of sovereign bonds just before the APP 
was launched reported a stronger impact on liquidity from the programme (Chart A, left panel). On 
average, just over 20% of banks reported a positive impact on liquidity from the programme in net 
percentage terms, while for the banks with relatively high holdings of sovereign bonds at the end of 
2014, the net percentage reporting a positive impact increases by 10 percentage points to over 30%. 
The banks that experienced an increase in liquidity owing to the APP could then adjust towards other 
assets, such as loans. 

Banks with larger liquidity inflows associated with the APP are found to have recorded 
stronger loan growth to enterprises following the implementation of the programme. Using 
BLS data on liquidity inflows to identify banks that were more exposed to the policy, the right panel of 
Chart A indicates that this group of banks had higher cumulative loan growth than other banks 
following the introduction of the APP. While Chart A implies that the policy was effective, the trend 
may be driven by other confounding factors such as the macroeconomic environment, bank business 
models and the demand conditions faced by the banks that were more exposed to the policy. To make 
a causal statement regarding the impact of the programme on credit supply, it is necessary to control 
for these factors. Model-based analysis shows that, even after controlling for bank characteristics 
(both time-varying and fixed unobservable features), demand conditions and macroeconomic 
variation, the APP continues to be found a strong driver of higher credit supply for the banks that were 
more exposed to liquidity inflows associated with the APP.73 

Chart A 
Impact of the APP on bank liquidity and lending 

a) Effect of APP on liquidity across banks

b) Cumulative differences between banks 
affected by APP

s
e
g
a
t
n
e
c
r
e
p
t
e
N

0.4

0.3

0.2

0.1

0.0

APP

Total

s
e
t
a
r
h
t
w
o
r
g
y
l
r
e
t
r
a
u
q
n

i
s
e
c
n
e
r
e
f
f
i

D

s
n
a
o

l

C
F
N

f
o

15

10

5

0

-5

High sovereign holding banks

Other banks

06/12

06/13

06/14

06/15

06/16

06/17

Sources: ECB and ECB calculations; Altavilla, Boucinha, Holton and Ongena (2018). 
Notes: The chart on the left hand side shows net percentages, i.e. the difference between the percentage of banks reporting a positive and a negative impact. 
Banks with high sovereign holdings are those that are in the 75th percentile in terms of their holdings of sovereign bonds relative to main assets in 
December 2014. Other banks are the remainder. The chart on the right shows the cumulative differences in quarterly growth rates between banks which on 
average reported that the APP impact on their liquidity position was more positive and other banks. The red line indicates the start of APP purchases in March 
2015. 

73    See Altavilla, C., Boucinha, M., Holton, S. and Ongena, S., “Credit supply and demand in unconventional 

times”, Working Paper Series, No 2202, ECB, 2018. 

ECB Economic Bulletin, Issue 2 / 2019 – Article 
Taking stock of the Eurosystem’s asset purchase programme after the end of net asset 
purchases 

89 

 
 
                                                                    
 
 
 
 
 
 
 
 
 
4.2 

Impact on the euro area economy and inflation, and progress 
towards a sustained adjustment in the path of inflation 

The APP, in conjunction with the other monetary policy measures, has provided 
a substantial contribution to the economic recovery and the formation of 
inflation expectations. According to calculations by Eurosystem staff, the overall 
impact of the policy measures adopted since mid-2014 on the euro area inflation rate 
is estimated to be around 1.9 percentage points cumulatively between 2016 and 2020, 
with the strongest impact being felt in 2016 and 2017 (see Table 1). The impact on real 
GDP growth is of a similar size. 

Table 1 
Impact of non-standard policy measures on euro area inflation and real GDP growth 

Inflation (percentage points) 

Real GDP growth (percentage points) 

2016 

2017 

2018 

2019 

2020 

cumulative 
(2016-2020) 

2016 

2017 

2018 

2019 

2020 

cumulative 
(2016-2020) 

All measures 
taken since 
June 2014 

0.85 

0.49 

0.22 

0.21 

0.16 

1.9 

0.79 

0.48 

0.31 

0.2 

0.08 

1.9 

Sources: Eurosystem staff calculations and NCB country-based models. 
Notes: The table reports the estimated impact of all policy measures adopted since mid-2014. The assessment takes as reference the 
December 2018 BMPE information set. The estimates are derived on the basis of various modelling frameworks, comprising the suite of 
models developed by staff of the ECB and NCBs, as well as the NCBs’ country-based models. Totals may not add up due to rounding. 

In June 2018 the Governing Council signalled that it expected to end the net 
purchases by the end of the year, and in December 2018 the decision to 
terminate the net purchases was confirmed. The decisions taken by the Governing 
Council at different stages of the asset purchase programme to extend, expand, scale 
back and finally end net asset purchases have consistently been informed by its 
assessment of the progress made towards achieving a sustained adjustment in the 
path of inflation. Upon a review of the progress made, in June 2018 the Governing 
Council signalled its anticipation that, subject to incoming data confirming the 
Governing Council’s medium-term inflation outlook, net asset purchases would end in 
December 2018. The end of net asset purchases was indeed confirmed in December 
2018. 

The assessment that the progress was substantial was based on a 
comprehensive review that took into account, among other elements, 
Eurosystem staff macroeconomic projections, measures of price and wage 
pressure, and uncertainties surrounding the inflation outlook. The Governing 
Council’s positive assessment of the progress towards a sustained adjustment of 
inflation that was carried out in June and December 2018 was underpinned by the 
stronger anchoring of longer-term inflation expectations, the underlying strength of 
domestic demand and the continuing ample degree of monetary accommodation, 
which provided grounds for confidence that sustained convergence would continue 
and be maintained even after the end of net asset purchases.   

Over the course of 2018, the medium-term projections for headline inflation had 
moved closer to 2% (see Chart 1). Furthermore, uncertainty surrounding the 
inflation outlook had receded significantly, with the risk of deflation virtually vanishing. 

ECB Economic Bulletin, Issue 2 / 2019 – Article 
Taking stock of the Eurosystem’s asset purchase programme after the end of net asset 
purchases 

90 

 
 
  
Inflation expectations as measured using different sources had been gradually 
improving, and had moved to levels closer to the ECB’s inflation aim. The predictive 
distribution derived from model-based assessments, market-based measures of 
inflation compensation (see Chart 9), and survey-based measures of inflation 
expectations had shown that substantial progress had been achieved. Moreover, 
while measures of underlying inflation remained generally muted, labour cost 
pressures had continued to strengthen amid high levels of capacity utilisation and 
tightening labour markets, thereby providing additional supporting evidence that the 
return of headline inflation towards the ECB’s target was sustainable. 

Chart 9 
Option-implied probability density function of euro area inflation compensation over 
the next two years 

(annual percentage changes, density) 

31 December 2014
31 December 2018

-2.0

-1.0

0.0

1.0

2.0

3.0

4.0

Source: ECB. 
Notes: The chart shows the option-implied probability density function based on two-year zero-coupon inflation options. These 
risk-neutral probabilities may differ significantly from physical, or true, probabilities. They are estimated on the basis of call (“caplets”) and 
put options (“floorlets”) with different strike rates on the (three-month lagged) euro area HICPxT (ex tobacco) index, assuming 
Black-Scholes option pricing and implied volatilities that vary across strike rates (“volatility smile”).   

Finally, the path of future inflation was judged to have become more resilient 
over time, making it less reliant on net asset purchases. Consistent with the 
propagation patterns that are characteristic for standard and non-standard policy 
interventions, the estimated profile of the impact of net additions to the APP portfolio 
had a tendency to diminish progressively over time. Based on this evidence, current 
and future inflation developments could be assessed to be less reliant on net asset 
purchases. 

5 

Outlook 

The Governing Council’s decision in December 2018 to end net asset 
purchases was accompanied by the decision to continue reinvesting the 
principal payments from maturing securities purchased under the APP and to 
enhance its forward guidance on policy rates and reinvestment. In December 
2018 the Governing Council completed the rotation from net asset purchases to policy 
rates as the new principal policy instrument. As regards the first building block of its 

ECB Economic Bulletin, Issue 2 / 2019 – Article 
Taking stock of the Eurosystem’s asset purchase programme after the end of net asset 
purchases 

91 

 
 
 
forward guidance, and similarly to the structure adopted during the period of net asset 
purchases, the rate guidance provided by the Governing Council since December 
2018 features a time-dependent leg (i.e. key ECB interest rates are expected to 
“remain at their present levels at least through the summer of 2019”) and a 
state-dependent leg linking the evolution of policy rates to the price stability objective 
(“and in any case for as long as necessary to ensure the continued sustained 
convergence of inflation to levels that are below, but close to, 2% over the medium 
term”). The second building block of the guidance links the reinvestment horizon 
directly to the principal policy instrument in a chained manner. Accordingly, the 
Governing Council currently states its intention to continue reinvesting, in full, the 
principal payments from maturing securities purchased under the APP for an extended 
period of time past the date when key ECB interest rates would be raised, and in any 
case for as long as necessary to maintain favourable liquidity conditions and an ample 
degree of monetary accommodation. 

During the reinvestment phase, the Eurosystem will continue to adhere to the 
principle of market neutrality built around smooth and flexible implementation. 
To this end, the principal redemptions will be reinvested with a view to allow for a 
regular and balanced market presence. In 2019, APP redemptions will amount to EUR 
203 billion, implying average monthly reinvestments of nearly EUR 17 billion. Limited 
temporary deviations in the overall size and composition of the APP may occur during 
the reinvestment phase for operational reasons. Any adjustment to the portfolio 
allocation across jurisdictions will be gradual and calibrated as appropriate to 
safeguard orderly market conditions. 

Overall, the APP has helped the ECB fulfil its price stability mandate, making it 
an effective instrument in the central bank’s policy toolkit. Alongside other policy 
measures taken since mid-2014, the APP has proved to be an adaptable and effective 
monetary policy instrument, helping the ECB to carry out its mandate. 

ECB Economic Bulletin, Issue 2 / 2019 – Article 
Taking stock of the Eurosystem’s asset purchase programme after the end of net asset 
purchases 

92 

 
 
Statistics

Contents

1 External environment

2 Financial developments

3 Economic activity

4 Prices and costs

5 Money and credit

6 Fiscal developments

Further information

S 2

S 3

S 8

S 14

S 18

S 23

ECB statistics can be accessed from the Statistical Data Warehouse (SDW): 

http://sdw.ecb.europa.eu/

Data from the statistics section of the Economic Bulletin are available from the SDW: 

http://sdw.ecb.europa.eu/reports.do?node=1000004813 

A comprehensive Statistics Bulletin can be found in the SDW: 

http://sdw.ecb.europa.eu/reports.do?node=1000004045 

Methodological definitions can be found in the General Notes to the Statistics Bulletin:

http://sdw.ecb.europa.eu/reports.do?node=10000023

Details on calculations can be found in the Technical Notes to the Statistics Bulletin:

http://sdw.ecb.europa.eu/reports.do?node=10000022

Explanations of terms and abbreviations can be found in the ECB’s statistics glossary:  http://www.ecb.europa.eu/home/glossary/html/glossa.en.html

Conventions used in the tables

 -

.

...

(p)

s.a.

data do not exist/data are not applicable 

data are not yet available

nil or negligible

provisional

seasonally adjusted

n.s.a.

non-seasonally adjusted

ECB Economic Bulletin, Issue 2 / 2019 - Statistics

S 1

1 External environment

1.1 Main trading partners, GDP and CPI

   GDP 1) 
   (period-on-period percentage changes)

   CPI
   (annual percentage changes)

G20 United

States Kingdom

United Japan China Memo item:
euro area

   OECD countries

United Japan China

United
States Kingdom
(HICP)

Memo item:
euro area 2)
(HICP)

excluding food
and energy

2016   
2017   
2018   

2018 Q1   
         Q2   
         Q3   
         Q4   

2018 Sep.   
         Oct.   
         Nov.   
         Dec.   

2019 Jan.   
         Feb.  3) 

1

3.2
3.8
. 

0.9
1.0
0.8
. 

- 
- 
- 
- 

- 
- 

2

1.6
2.2
3.0

0.5
1.0
0.8
0.6

- 
- 
- 
- 

- 
- 

3

1.8
1.8
1.4

0.1
0.4
0.6
0.2

- 
- 
- 
- 

- 
- 

4

0.6
1.9
0.7

-0.2
0.6
-0.7
0.3

- 
- 
- 
- 

- 
- 

5

6.7
6.8
6.6

1.5
1.7
1.6
1.5

- 
- 
- 
- 

- 
- 

Total

7

4.5
9.1
10.4

2.2
2.6
2.9
2.7

2.9
3.1
2.7
2.4

. 
. 

6

2.0
2.4
. 

0.4
0.4
0.2
0.2

- 
- 
- 
- 

- 
- 

8

1.8
1.8
2.1

1.9
2.0
2.2
2.3

2.3
2.3
2.2
2.2

. 
. 

9

1.3
2.1
2.4

2.2
2.7
2.6
2.2

2.3
2.5
2.2
1.9

1.6
. 

10

0.7
2.7
2.5

2.7
2.4
2.5
2.3

2.4
2.4
2.3
2.1

1.8
. 

11

-0.1
0.5
1.0

1.3
0.7
1.1
0.8

1.2
1.4
0.8
0.3

0.2
. 

12

2.0
1.6
2.1

2.2
1.8
2.3
2.2

2.5
2.5
2.2
1.9

1.7
. 

13

0.2
1.5
1.8

1.3
1.7
2.1
1.9

2.1
2.3
1.9
1.5

1.4
1.5

Sources: Eurostat (col. 3, 6, 10, 13); BIS (col. 9, 11, 12); OECD (col. 1, 2, 4, 5, 7, 8).
1) Quarterly data seasonally adjusted; annual data unadjusted.
2) Data refer to the changing composition of the euro area.
3) The figure for the euro area is an estimate based on provisional national data, as well as on early information on energy prices.

1.2 Main trading partners, Purchasing Managers’ Index and world trade

   Purchasing Managers’ Surveys (diffusion indices; s.a.)

   Merchandise
   imports 1) 

   Composite Purchasing Managers’ Index

   Global Purchasing Managers’ Index 2) 

Global 2) United

States Kingdom

United Japan China Memo item: Manufacturing Services
euro area

2016   
2017   
2018   

2018 Q1   
         Q2   
         Q3   
         Q4   

2018 Sep.   
         Oct.   
         Nov.   
         Dec.   

2019 Jan.   
         Feb.   

1

2

3

4

5

51.6
53.2
53.4

53.5
53.9
53.1
53.1

52.4
53.0
53.3
53.1

52.4
52.8

52.4
54.3
55.0

54.6
55.9
54.8
54.7

53.9
54.9
54.7
54.4

54.4
55.5

53.4
54.7
53.3

53.4
54.3
53.9
51.4

54.1
52.1
50.8
51.4

50.3
51.5

50.5
52.5
52.1

52.1
52.3
51.5
52.3

50.7
52.5
52.4
52.0

50.9
50.7

51.4
51.8
52.3

53.0
52.5
52.1
51.5

52.1
50.5
51.9
52.2

50.9
50.7

6

53.3
56.4
54.6

57.0
54.7
54.3
52.3

54.1
53.1
52.7
51.1

51.0
51.9

7

51.7
53.8
53.1

53.7
53.1
52.6
52.0

52.2
51.8
52.0
52.1

50.9
51.0

8

52.0
53.8
53.8

53.5
54.2
53.2
53.5

52.5
53.3
53.8
53.4

53.0
53.4

New export
orders

Global

Advanced
economies

Emerging
market
economies

9

50.1
52.8
50.9

52.3
50.3
49.8
49.9

49.5
50.0
49.8
50.0

49.6
49.6

10

1.2
5.6
4.1

1.3
0.0
2.0
-1.6

2.0
1.6
0.2
-1.6

. 
. 

11

1.4
3.1
2.9

0.6
-0.8
0.8
1.2

0.8
1.5
1.3
1.2

. 
. 

12

1.0
7.3
4.9

1.7
0.4
2.7
-3.3

2.7
1.6
-0.5
-3.3

. 
. 

Sources: Markit (col. 1-9); CPB Netherlands Bureau for Economic Policy Analysis and ECB calculations (col. 10-12).
1) Global and advanced economies exclude the euro area. Annual and quarterly data are period-on-period percentages; monthly data are 3-month-on-3-month percentages. All data

are seasonally adjusted.
2) Excluding the euro area.

ECB Economic Bulletin, Issue 2 / 2019 - Statistics

S 2

 
   
   
   
 
 
 
   
   
   
   
   
 
 
2 Financial developments

2.1 Money market interest rates
(percentages per annum; period averages)

   Euro area 1) 

Overnight
deposits
(EONIA)

1-month
deposits
(EURIBOR)

3-month
deposits
(EURIBOR)

6-month
deposits
(EURIBOR)

12-month
deposits
(EURIBOR)

1

-0.32
-0.35
-0.36

-0.36
-0.36
-0.37
-0.36
-0.36

-0.37
-0.37

2

-0.34
-0.37
-0.37

-0.37
-0.37
-0.37
-0.37
-0.37

-0.37
-0.37

3

-0.26
-0.33
-0.32

-0.32
-0.32
-0.32
-0.32
-0.31

-0.31
-0.31

4

-0.17
-0.26
-0.27

-0.27
-0.27
-0.26
-0.26
-0.24

-0.24
-0.23

5

-0.03
-0.15
-0.17

-0.17
-0.17
-0.15
-0.15
-0.13

-0.12
-0.11

United States

3-month
deposits
(LIBOR)

6

0.74
1.26
2.31

2.32
2.35
2.46
2.65
2.79

2.77
2.68

Japan

3-month
deposits
(LIBOR)

7

-0.02
-0.02
-0.05

-0.04
-0.04
-0.08
-0.10
-0.10

-0.08
-0.08

2016   
2017   
2018   

2018 Aug.   
         Sep.   
         Oct.   
         Nov.   
         Dec.   

2019 Jan.   
         Feb.   

Source: ECB.
1) Data refer to the changing composition of the euro area, see the General Notes.

2.2 Yield curves
(End of period; rates in percentages per annum; spreads in percentage points)

   Spot rates

   Spreads

   Instantaneous forward rates

   Euro area 1), 2) 

Euro area 1), 2) United States United Kingdom

   Euro area 1), 2) 

3 months

1 year

2 years

5 years 10 years

10 years
- 1 year

10 years
- 1 year

10 years
- 1 year

1 year

2 years

5 years 10 years

1

2

3

4

2016   
2017   
2018   

2018 Aug.   
         Sep.   
         Oct.   
         Nov.   
         Dec.   

2019 Jan.   
         Feb.   

-0.93
-0.78
-0.80

-0.63
-0.62
-0.75
-0.67
-0.80

-0.58
-0.57

-0.82
-0.74
-0.75

-0.67
-0.63
-0.73
-0.70
-0.75

-0.60
-0.57

-0.80
-0.64
-0.66

-0.63
-0.55
-0.63
-0.64
-0.66

-0.58
-0.54

-0.47
-0.17
-0.26

-0.23
-0.09
-0.17
-0.23
-0.26

-0.32
-0.28

5

0.26
0.52
0.32

0.37
0.51
0.43
0.37
0.32

0.19
0.23

6

1.08
1.26
1.07

1.04
1.14
1.17
1.06
1.07

0.79
0.80

7

1.63
0.67
0.08

0.41
0.49
0.48
0.30
0.08

0.08
0.17

Source: ECB.
1) Data refer to the changing composition of the euro area, see the General Notes.
2) ECB calculations based on underlying data provided by EuroMTS and ratings provided by Fitch Ratings.

2.3 Stock market indices
(index levels in points; period averages)

8

1.17
0.83
0.51

0.71
0.77
0.67
0.57
0.51

0.45
0.49

9

10

-0.78
-0.66
-0.67

-0.68
-0.59
-0.66
-0.68
-0.67

-0.61
-0.56

-0.75
-0.39
-0.45

-0.46
-0.31
-0.37
-0.45
-0.45

-0.50
-0.44

11

0.35
0.66
0.44

0.50
0.68
0.60
0.50
0.44

0.24
0.27

12

1.35
1.56
1.17

1.28
1.36
1.31
1.28
1.17

1.00
1.06

   Benchmark

Broad
index

50

   Dow Jones EURO STOXX indices

   Main industry indices

United
States

Japan

materials

Basic Consumer Consumer Oil and Financials Industrials Technology Utilities Telecoms Health care Standard
& Poor’s
500

services

goods

gas

Nikkei
225

1

2

3

4

5

6

7

8

9

10

11

12

13

14

2016   
2017   
2018   

321.6 3,003.7
376.9 3,491.0
375.5 3,386.6

2018 Aug.   382.5 3,436.8
         Sep.   376.4 3,365.2
         Oct.    359.0 3,244.5
         Nov.   351.3 3,186.4
         Dec.   335.2 3,057.8

2019 Jan.    340.5 3,088.7
         Feb.   355.0 3,223.1

Source: ECB.

620.7
757.3
766.3

785.2
779.9
733.7
692.3
646.7

662.2
699.4

250.9
268.6
264.9

273.0
265.1
253.2
258.1
247.8

252.1
266.4

600.1
690.4
697.3

711.6
692.5
657.3
649.3
624.8

630.4
667.5

278.9
307.9
336.0

357.5
356.4
349.6
328.6
311.8

315.4
329.9

148.7
182.3
173.1

167.9
168.0
160.1
157.2
146.9

150.2
152.9

496.0
605.5
629.5

653.3
649.7
607.6
589.4
556.0

570.3
598.9

375.8
468.4
502.5

529.4
511.7
483.0
459.6
441.5

448.1
480.6

248.6
272.7
278.8

282.1
278.1
269.0
277.1
283.5

293.2
301.7

326.9
339.2
292.9

288.7
274.6
277.7
293.9
296.3

288.0
285.8

770.9
876.3
800.5

834.2
807.2
783.7
757.5
719.4

718.3
743.0

2,094.7 16,920.5
2,449.1 20,209.0
2,746.2 22,310.7

2,857.8 22,494.1
2,901.5 23,159.3
2,785.5 22,690.8
2,723.2 21,967.9
2,567.3 21,032.4

2,607.4 20,460.5
2,754.9 21,123.6

ECB Economic Bulletin, Issue 2 / 2019 - Statistics

S 3

 
   
 
 
   
   
   
   
   
 
   
   
   
 
2 Financial developments

2.4 MFI interest rates on loans to and deposits from households (new business) 1), 2) 
(Percentages per annum; period average, unless otherwise indicated)

   Deposits

Revolving Extended   Loans for consumption

   Loans for house purchase

Over- Redeem-
night

loans
and
able    an agreed overdrafts

   With

at    maturity of:

notice
of up Up to Over
2
months years years

to 3

2

credit   of rate fixation

Loans
credit
to sole
card   By initial period APRC 3) proprietors
and
unincor-
porated Floating Over 1 Over 5 Over
10
partner- rate and and up and up
to 10 years
years

Floating Over
1
rate and
up to
year
1 year

   By initial period
   of rate fixation

up to
1 year

to 5
years

ships

APRC 3) Composite
cost-of-
borrowing
indicator

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

2018 Feb.    0.04
         Mar.    0.04
         Apr.    0.04
         May    0.04
         June    0.03
         July    0.03
         Aug.    0.03
         Sep.    0.03
         Oct.    0.03
         Nov.    0.03
         Dec.    0.03

2019 Jan. (p)   0.03

0.44
0.45
0.45
0.46
0.46
0.45
0.45
0.45
0.45
0.44
0.43

0.42

0.34
0.35
0.34
0.34
0.33
0.33
0.30
0.30
0.29
0.29
0.30

0.33

0.69
0.67
0.61
0.57
0.63
0.63
0.63
0.69
0.73
0.72
0.77

0.74

6.19
6.14
6.12
6.10
6.05
6.01
6.02
6.05
5.98
5.94
5.87

5.92

16.88
16.89
16.87
16.89
16.84
16.80
16.78
16.71
16.73
16.54
16.55

16.63

4.72
4.71
4.94
4.82
4.50
4.84
5.42
5.28
5.04
4.92
4.91

5.30

5.70
5.57
5.67
5.88
5.64
5.75
5.88
5.74
5.71
5.68
5.47

5.82

6.19
6.05
6.14
6.39
6.11
6.22
6.41
6.27
6.23
6.18
5.98

6.33

2.37
2.34
2.37
2.39
2.31
2.41
2.39
2.38
2.46
2.38
2.30

2.37

1.64
1.63
1.62
1.58
1.60
1.63
1.63
1.60
1.60
1.61
1.61

1.61

1.88
1.85
1.85
1.85
1.81
1.83
1.82
1.81
1.80
1.85
1.80

1.81

1.93
1.95
1.96
1.97
1.97
1.93
1.92
1.91
1.91
1.94
1.91

1.89

1.91
1.91
1.90
1.90
1.88
1.85
1.85
1.85
1.86
1.88
1.84

1.86

2.14
2.15
2.13
2.13
2.12
2.12
2.12
2.09
2.09
2.11
2.10

2.09

16

1.84
1.84
1.83
1.83
1.82
1.81
1.81
1.79
1.80
1.81
1.80

1.82

Source: ECB.
1) Data refer to the changing composition of the euro area.
2) Including non-profit institutions serving households.
3) Annual percentage rate of charge (APRC).

2.5 MFI interest rates on loans to and deposits from non-financial corporations (new business) 1), 2) 
(Percentages per annum; period average, unless otherwise indicated)

   Deposits

Revolving
loans and
Over-   With an agreed overdrafts
night

   maturity of:

   Other loans by size and initial period of rate fixation

   up to EUR 0.25 million

   over EUR 0.25 and up to 1 million

   over EUR 1 million

Floating

Over
rate 3 months
and up to and up to
1 year
3 months

Over
1 year

Floating
rate
and up to
3 months

Over
3 months
and up to
1 year

Over
1 year

Floating

Over
rate 3 months
and up to and up to
1 year
3 months

Over
1 year

Composite
cost-of-
borrowing
indicator

Up to Over
2 years 2 years

1

2

3

2018 Feb.   
0.04
         Mar.   
0.04
         Apr.   
0.04
         May   
0.03
         June    0.04
         July   
0.03
         Aug.   
0.03
         Sep.   
0.03
         Oct.   
0.03
         Nov.   
0.03
         Dec.   
0.03

2019 Jan. (p)   0.03

0.09
0.08
0.06
0.08
0.07
0.08
0.08
0.08
0.08
0.07
0.07

0.07

0.43
0.40
0.32
0.43
0.74
0.38
0.60
0.44
0.52
0.63
0.53

0.56

4

2.36
2.33
2.32
2.28
2.29
2.27
2.25
2.22
2.22
2.19
2.18

2.22

5

2.37
2.41
2.37
2.31
2.27
2.16
2.21
2.21
2.14
2.20
2.21

2.15

6

7

2.49
2.53
2.42
2.47
2.44
2.41
2.42
2.34
2.42
2.40
2.28

2.39

2.33
2.34
2.33
2.38
2.31
2.28
2.35
2.32
2.34
2.34
2.26

2.32

8

1.66
1.67
1.67
1.65
1.64
1.67
1.66
1.65
1.65
1.66
1.61

1.68

9

10

11

12

13

1.63
1.61
1.61
1.61
1.56
1.59
1.63
1.55
1.60
1.60
1.59

1.61

1.74
1.70
1.74
1.74
1.71
1.68
1.74
1.69
1.70
1.69
1.69

1.73

1.18
1.26
1.23
1.07
1.21
1.14
1.10
1.12
1.23
1.20
1.21

1.13

1.35
1.39
1.29
1.22
1.33
1.30
1.27
1.40
1.10
1.35
1.39

1.30

1.64
1.66
1.65
1.65
1.70
1.66
1.69
1.69
1.66
1.69
1.59

1.61

14

1.71
1.73
1.71
1.62
1.68
1.64
1.64
1.65
1.64
1.66
1.64

1.63

Source: ECB.
1) Data refer to the changing composition of the euro area.
2) In accordance with the ESA 2010, in December 2014 holding companies of non-financial groups were reclassified from the non-financial corporations sector to the financial

corporations sector.

ECB Economic Bulletin, Issue 2 / 2019 - Statistics

S 4

 
   
   
   
   
   
   
 
   
   
   
   
   
   
2 Financial developments

2.6 Debt securities issued by euro area residents, by sector of the issuer and initial maturity
(EUR billions; transactions during the month and end-of-period outstanding amounts; nominal values)

   Outstanding amounts

   Gross issues 1) 

Total

MFIs
(including
Euro-

   Non-MFI corporations

   General government Total

   Non-MFI corporations

   General government

Financial
system) corporations

financial
other than FVCs corporations

Non- Central
govern-
ment

Other
general
govern-
ment

Financial
system) corporations

Non-
financial
other than FVCs corporations

MFIs

Central
govern-
ment

Other
general
govern-
ment

MFIs
(including
Euro-

MFIs

1

2

3

4

2015  
2016  
2017  

1,269
1,241
1,241

2018 July   1,313
         Aug.   1,311
         Sep.   1,295
         Oct.   1,280
         Nov.   1,270
         Dec.   1,200

2015  
2016  
2017  

15,250
15,380
15,362

2018 July  15,555
         Aug.  15,564
         Sep.  15,683
         Oct.  15,719
         Nov.  15,802
         Dec.  15,747

517
518
519

526
525
531
525
518
499

3,786
3,695
3,560

3,570
3,578
3,616
3,672
3,697
3,694

147
136
156

178
178
179
171
166
159

3,270
3,234
3,109

3,158
3,167
3,183
3,188
3,215
3,194

.
.
.

.
.
.
.
.
.

.
.
.

.
.
.
.
.
.

5

62
59
70

96
95
89
92
89
72

1,075
1,126
1,185

1,203
1,186
1,206
1,205
1,208
1,212

6

7
Short-term

478
466
438

453
447
444
439
445
424

6,481
6,684
6,865

7,003
7,010
7,055
7,026
7,054
7,020

65
62
57

60
65
52
54
52
47

Long-term

637
641
642

621
622
623
628
629
626

8

9

10

11

12

13

14

347
349
368

436
408
378
411
353
267

216
220
247

220
131
254
215
223
175

161
161
167

191
201
164
184
154
109

68
62
66

54
50
79
60
67
60

37
45
55

77
61
73
66
57
53

46
54
74

55
38
60
61
70
74

.
.
.

.
.
.
.
.
.

.
.
.

.
.
.
.
.
.

33
31
37

48
31
42
46
36
36

14
18
17

16
2
29
14
8
14

82
79
79

79
82
72
77
74
44

80
78
83

87
38
82
69
72
24

34
33
31

42
33
28
38
31
26

9
8
7

8
3
4
10
7
3

Source: ECB.
1) For the purpose of comparison, annual data refer to the average monthly figure over the year.

2.7 Growth rates and outstanding amounts of debt securities and listed shares
(EUR billions; percentage changes)

   Debt securities

   Listed shares

Total

MFIs
(including
Eurosystem)

   Non-MFI corporations

   General government

Total

MFIs

Financial
corporations
other than
MFIs

Non-

Central
financial government

FVCs corporations

Other
general
government

Financial
corporations

Non-
financial
other than corporations

MFIs

1

2

3

4

5

6
Oustanding amount

7

8

9

10

11

2015  
2016  
2017  

16,518.8
16,621.2
16,602.8

2018 July  
16,867.9
         Aug.   16,874.8
         Sep.   16,978.4
         Oct.  
16,999.6
         Nov.   17,072.6
         Dec.   16,947.3

2015  
2016  
2017  

2018 July  
         Aug.  
         Sep.  
         Oct.  
         Nov.  
         Dec.  

Source: ECB.

0.2
0.3
1.3

1.2
1.4
1.8
1.9
2.0
1.7

4,303.2
4,213.3
4,079.7

4,095.9
4,102.8
4,147.2
4,197.4
4,214.6
4,192.7

-7.0
-3.0
-0.5

-0.8
-0.2
0.9
0.9
1.3
1.7

3,417.2
3,369.3
3,264.5

3,335.9
3,345.2
3,361.8
3,358.4
3,381.3
3,353.5

5.8
-1.2
-0.2

0.6
1.2
1.3
2.0
2.5
1.6

.
.
.

.
.
.
.
.
.

.
.
.

.
.
.
.
.
.

1,137.0
1,185.3
1,255.2

1,299.3
1,281.6
1,295.4
1,296.9
1,296.7
1,283.7

6,958.9
7,149.9
7,303.6

7,455.8
7,457.7
7,499.3
7,464.9
7,499.0
7,444.7

Growth rate

4.1
6.5
6.1

5.0
4.2
5.1
4.9
3.7
3.4

1.8
2.2
2.2

2.4
2.2
2.4
2.4
2.4
1.9

702.4
703.5
699.8

681.0
687.5
674.8
682.0
681.0
672.7

0.6
-0.1
0.5

-2.5
-2.6
-3.7
-3.1
-3.6
-4.3

6,814.4
7,089.5
7,954.7

8,168.5
8,019.9
7,955.7
7,546.6
7,475.0
7,030.7

1.1
0.5
1.1

1.2
1.2
1.1
1.0
0.9
0.8

584.3
537.6
612.5

576.1
521.1
543.5
515.4
512.1
465.1

4.2
1.2
6.1

0.4
0.5
0.5
0.5
0.4
-0.1

968.3
1,080.2
1,249.4

1,293.6
1,282.5
1,293.9
1,201.8
1,179.2
1,099.0

1.8
0.9
2.8

4.8
4.7
3.9
3.1
2.9
2.8

ECB Economic Bulletin, Issue 2 / 2019 - Statistics

5,261.9
5,471.6
6,092.8

6,298.8
6,216.3
6,118.4
5,829.4
5,783.6
5,466.6

0.6
0.4
0.3

0.6
0.5
0.5
0.6
0.5
0.4

S 5

 
 
   
   
   
   
   
   
   
   
 
 
 
 
   
   
   
   
   
 
 
2 Financial developments

2.8 Effective exchange rates 1) 
(period averages; index: 1999 Q1=100)

Nominal

Real CPI

Real PPI

Real GDP
deflator

Real ULCM 2)

Real ULCT

Nominal

Real CPI

   EER-19

   EER-38

1

94.4
96.6
98.9

99.6
98.4
99.2
98.5

99.5
98.9
98.3
98.4

97.8
97.4

-0.4

-2.2

2

89.4
91.3
93.3

93.9
92.9
93.5
92.8

93.7
93.2
92.7
92.6

92.0
91.5

-0.5

-2.4

3

90.9
92.0
93.5

94.4
93.2
93.5
93.0

93.7
93.3
92.8
93.0

92.5
92.2

4

85.1
86.0
. 

88.2
87.3
87.8
.

- 
- 
- 
- 

- 
- 

Percentage change versus previous month

-0.4

- 

Percentage change versus previous year

-2.4

- 

5

79.4
78.8
. 

80.1
78.8
79.5
.

- 
- 
- 
- 

- 
- 

- 

- 

6

89.1
89.9
. 

91.8
90.6
91.4
.

- 
- 
- 
- 

- 
- 

- 

- 

7

109.7
112.0
117.9

117.0
117.0
119.2
118.4

120.4
119.0
117.9
118.0

117.3
116.6

-0.6

-0.6

8

88.7
89.9
93.7

93.3
93.2
94.6
93.6

95.4
94.2
93.4
93.2

92.5
91.8

-0.8

-1.8

2016   
2017   
2018   

2018 Q1   
         Q2   
         Q3   
         Q4   

2018 Sep.   
         Oct.   
         Nov.   
         Dec.   

2019 Jan.   
         Feb.   

2019 Feb.   

2019 Feb.   

Source: ECB.
1) For a definition of the trading partner groups and other information see the General Notes to the Statistics Bulletin.
2) ULCM-deflated series are available only for the EER-18 trading partner group.

2.9 Bilateral exchange rates
(period averages; units of national currency per euro)

Chinese Croatian
kuna
renminbi

Czech
koruna

Danish Hungarian Japanese
yen
forint

krone

Polish
zloty

Pound Romanian Swedish
krona
sterling

leu

Swiss
franc

US
Dollar

1

2

3

4

5

6

2016   
2017   
2018   

2018 Q1   
         Q2   
         Q3   
         Q4   

2018 Sep.   
         Oct.   
         Nov.   
         Dec.   

2019 Jan.   
         Feb.   

7.352
7.629
7.808

7.815
7.602
7.915
7.895

7.993
7.948
7.888
7.840

7.750
7.649

7.533
7.464
7.418

7.438
7.398
7.417
7.420

7.429
7.425
7.428
7.404

7.429
7.415

27.034
26.326
25.647

25.402
25.599
25.718
25.864

25.614
25.819
25.935
25.835

25.650
25.726

7.445
7.439
7.453

7.447
7.448
7.455
7.462

7.458
7.460
7.461
7.465

311.438
309.193
318.890

311.027
317.199
324.107
322.995

324.818
323.843
322.330
322.738

120.197
126.711
130.396

133.166
130.045
129.606
128.816

130.535
129.617
128.789
127.878

7

4.363
4.257
4.261

4.179
4.262
4.303
4.299

4.301
4.305
4.302
4.290

319.800
317.908

7.466
7.463
Percentage change versus previous month

124.341
125.280

4.292
4.318

2019 Feb.   

-1.3

-0.2

2019 Feb.   

Source: ECB.

-2.0

-0.3

0.3

1.6

0.0

-0.6

0.8

0.6

Percentage change versus previous year

0.2

2.0

-6.0

3.7

8

9

10

11

12

0.819
0.877
0.885

0.883
0.876
0.892
0.887

0.893
0.883
0.881
0.898

0.886
0.873

-1.5

-1.3

4.4904
4.5688
4.6540

4.6553
4.6532
4.6471
4.6605

4.6471
4.6658
4.6610
4.6536

4.7062
4.7486

0.9

2.0

9.469
9.635
10.258

9.971
10.330
10.405
10.320

10.443
10.384
10.292
10.277

10.269
10.499

2.2

5.6

1.090
1.112
1.155

1.165
1.174
1.144
1.137

1.129
1.141
1.138
1.129

1.130
1.137

1.107
1.130
1.181

1.229
1.191
1.163
1.141

1.166
1.148
1.137
1.138

1.142
1.135

0.6

-0.6

-1.5

-8.1

ECB Economic Bulletin, Issue 2 / 2019 - Statistics

S 6

 
   
   
 
 
 
 
 
 
 
 
 
 
 
 
 
2 Financial developments

2.10 Euro area balance of payments, financial account
(EUR billions, unless otherwise indicated; outstanding amounts at end of period; transactions during period)

   Total 1) 

   Direct
   investment

   Portfolio
   investment

Net
financial
derivatives

   Other investment

Reserve
assets

Assets Liabilities

Net

Assets Liabilities

Assets Liabilities

Assets Liabilities

Memo:
Gross
external
debt

1

2

3
Outstanding amounts (international investment position)

4

5

6

7

8

9

10

11

12

2017 Q4   

2018 Q1   
         Q2   
         Q3   

24,840.3

25,526.8

-686.5

10,675.3

8,735.2

8,550.4

10,967.5

24,898.2
25,526.6
25,832.2

25,761.3
26,196.4
26,425.6

-863.1
-669.8
-593.5

10,643.9
10,828.6
10,939.9

8,825.8
8,922.0
9,011.5

8,532.1
8,743.6
8,883.2

10,933.7
11,010.0
11,099.3

-55.7

-75.8
-83.1
-61.4

5,000.6

5,824.1

669.7

13,890.4

5,124.8
5,347.4
5,396.5

6,001.8
6,264.4
6,314.8

673.2
690.0
673.9

14,134.5
14,369.5
14,450.1

Outstanding amounts as a percentage of GDP

2018 Q3   

224.8

230.0

-5.2

95.2

78.4

77.3

96.6

-0.5

47.0

55.0

5.9

125.8

2018 Q1   
         Q2   
         Q3   
         Q4   

2018 July   
         Aug.   
         Sep.   
         Oct.   
         Nov.   
         Dec.   

440.6
167.7
174.1
-309.8

143.0
31.6
-0.5
91.7
-101.6
-299.9

319.3
105.1
81.3
-428.1

140.1
1.5
-60.4
74.3
-126.4
-376.0

Transactions

121.3
62.6
92.8
118.2

2.9
30.1
59.9
17.4
24.8
76.0

62.7
-2.2
49.1
-108.2

43.1
-2.4
8.4
68.3
-105.9
-70.6

-77.8
-29.7
28.9
-219.7

36.9
8.8
-16.8
-2.7
-97.4
-119.7

192.3
-1.9
41.0
-124.6

20.9
29.0
-8.8
-30.8
-45.3
-48.5

196.5
-41.4
6.3
-123.0

13.4
-42.3
35.2
-17.5
-34.0
-71.5

12-month cumulated transactions

3.1
38.0
33.3
17.9

12.8
14.1
6.4
1.7
9.9
6.3

171.1
127.3
49.5
-100.6

70.6
-12.4
-8.7
53.2
36.5
-190.3

200.7
176.2
46.1
-85.3

89.8
35.1
-78.7
94.5
5.0
-184.8

11.4
6.6
1.2
5.7

-4.4
3.3
2.2
-0.7
3.2
3.2

2018 Dec.   

472.6

77.6

395.0

1.3

-298.3

106.8

38.3

92.4

247.3

337.6

24.8

12-month cumulated transactions as a percentage of GDP

2018 Dec.   

4.1

0.7

3.4

0.0

-2.6

0.9

0.3

0.8

2.2

2.9

0.2

-
-
-
-

-
-
-
-
-
-

-

-

Source: ECB.
1) Net financial derivatives are included in total assets.

ECB Economic Bulletin, Issue 2 / 2019 - Statistics

S 7

 
 
   
   
   
   
   
   
 
 
 
 
 
 
 
 
 
3 Economic activity

3.1 GDP and expenditure components
(quarterly data seasonally adjusted; annual data unadjusted)

Total

   Domestic demand

   External balance 1) 

Total

Private Government
consumption consumption

   Gross fixed capital formation

Changes in
inventories 2)

Total Exports 1)

Imports 1)

   GDP

Total

Total
construction machinery

Intellectual
property
products

1

2

3

4

5

7
Current prices (EUR billions)

6

2015   
2016   
2017   

10,534.3 10,060.1
10,827.7 10,349.6
11,206.0 10,682.9

2017 Q4    2,844.1

2,702.4

2018 Q1    2,865.2
         Q2    2,889.4
         Q3    2,904.4

2,725.4
2,757.3
2,788.1

5,743.1
5,877.4
6,058.2

1,530.7

1,543.7
1,553.4
1,562.3

2,172.5 2,110.8
2,223.3 2,210.8
2,279.5 2,302.8

588.2

1,014.6
1,053.2
1,121.6

287.1

640.4
679.3
716.3

185.4

592.1
604.4
615.0

291.3
297.9
302.0
as a percentage of GDP

184.1
188.8
192.9

576.0

578.3
585.7
587.7

8

9

10

11

12

449.7
472.3
459.2

114.3

115.3
116.4
118.8

33.6
38.2
42.4

7.5

11.3
13.8
23.1

474.3
478.0
523.0

141.7

139.8
132.1
116.2

4,866.6
4,942.9
5,295.5

4,392.3
4,464.9
4,772.5

1,361.5

1,219.8

1,357.4
1,379.2
1,392.3

1,217.7
1,247.1
1,276.0

2017   

100.0

95.3

54.1

20.3

20.5

10.0

6.4

4.1

0.4

4.7

- 

- 

Chain-linked volumes (prices for the previous year)
quarter-on-quarter percentage changes

2018 Q1   
         Q2   
         Q3   
         Q4   

2015   
2016   
2017   

2018 Q1   
         Q2   
         Q3   
         Q4   

2018 Q1   
         Q2   
         Q3   
         Q4   

2015   
2016   
2017   

2018 Q1   
         Q2   
         Q3   
         Q4   

0.4
0.4
0.2
0.2

2.1
2.0
2.4

2.4
2.2
1.6
1.2

0.4
0.4
0.2
0.2

2.1
2.0
2.4

2.4
2.2
1.6
1.2

0.5
0.5
0.6
. 

2.4
2.4
1.7

1.8
1.5
1.9
. 

0.5
0.4
0.5
. 

2.3
2.3
1.6

1.8
1.5
1.8
. 

0.5
0.2
0.1
. 

1.8
2.0
1.6

1.7
1.4
1.0
. 

0.0
0.4
0.3
. 

1.3
1.8
1.2

1.0
1.1
0.9
. 

0.1
1.6
0.7
. 

-0.8
2.4
1.3
. 
annual percentage changes

0.6
1.3
0.2
. 

4.9
4.0
2.6

3.4
2.9
3.7
. 

0.4
2.7
3.9

3.4
4.0
2.2
. 

5.6
5.8
5.0

5.4
6.1
5.8
. 

0.4
0.7
1.1
. 

15.6
4.3
-3.6

0.6
-4.3
4.2
. 

- 
- 
- 
- 

- 
- 
- 

- 
- 
- 
- 

contributions to quarter-on-quarter percentage changes in GDP; percentage points

0.3
0.1
0.1
. 
contributions to annual percentage changes in GDP; percentage points

-0.1
0.2
0.1
. 

0.0
0.1
0.1
. 

0.0
0.3
0.1
. 

0.1
0.1
0.0
. 

0.0
0.0
0.0
. 

1.0
1.1
0.9

0.9
0.7
0.6
. 

0.3
0.4
0.2

0.2
0.2
0.2
. 

1.0
0.8
0.5

0.7
0.6
0.8
. 

0.0
0.3
0.4

0.3
0.4
0.2
. 

0.3
0.4
0.3

0.3
0.4
0.4
. 

0.6
0.2
-0.2

0.0
-0.2
0.2
. 

0.2
-0.1
0.3
. 

0.0
0.1
0.0

-0.1
-0.1
0.3
. 

- 
- 
- 
- 

- 
- 
- 

- 
- 
- 
- 

-0.1
0.0
-0.4
. 

-0.2
-0.4
0.8

0.6
0.7
-0.2
. 

-0.7
1.2
0.1
. 

6.6
3.0
5.2

3.8
4.0
2.8
. 

- 
- 
- 
- 

- 
- 
- 

- 
- 
- 
- 

-0.6
1.3
1.0
. 

7.7
4.2
3.9

2.7
2.7
3.6
. 

- 
- 
- 
- 

- 
- 
- 

- 
- 
- 
- 

Sources: Eurostat and ECB calculations.
1) Exports and imports cover goods and services and include cross-border intra-euro area trade.
2) Including acquisitions less disposals of valuables.

ECB Economic Bulletin, Issue 2 / 2019 - Statistics

S 8

 
 
   
   
   
   
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
3 Economic activity

3.2 Value added by economic activity
(quarterly data seasonally adjusted; annual data unadjusted)

   Gross value added (basic prices)

Total Agriculture, Manufacturing Const-

forestry and
fishing

Infor-
energy and ruction transport, mation

Finance
and
accom- and com- insurance

utilities

Trade,

modation munica-
and food
tion
services

Real Professional,

estate business and ministration,
education,
support
health and
services
social work

Public ad- Arts, enter-
tainment
and other
services

Taxes less
subsidies
on
products

1

2

3

4

5

6

7

8

9

10

11

12

2015   
2016   
2017   

9,461.6
9,715.8
10,048.5

2017 Q4   

2,551.4

2018 Q1   
         Q2   
         Q3   

2,568.6
2,589.8
2,603.3

159.5
158.6
171.3

43.7

43.1
42.9
43.4

Current prices (EUR billions)

1,901.2 468.0
1,962.6 486.8
2,032.8 512.8

1,784.9
1,836.0
1,916.8

519.9 131.5

518.5 134.3
520.7 137.1
521.9 139.6

486.4

490.0
494.1
495.8

433.4
452.7
469.4

119.1

120.9
122.7
123.8

470.2 1,078.0
464.1 1,098.7
455.8 1,129.7

114.0

114.3
114.2
115.0

285.3

287.5
289.5
291.2

as a percentage of value added

1,031.0
1,069.2
1,118.5

284.9

289.3
292.5
294.2

1,805.1
1,849.8
1,897.1

479.7

483.2
488.4
490.0

330.3
337.4
344.4

86.9

87.7
87.8
88.2

1,072.6
1,111.7
1,157.3

292.8

296.5
299.8
301.9

2017   

100.0

1.7

20.2

5.1

19.1

4.7

4.5

11.2

11.1

18.9

3.4

- 

Chain-linked volumes (prices for the previous year)
quarter-on-quarter percentage changes

2017 Q4   

2018 Q1   
         Q2   
         Q3   

2015   
2016   
2017   

2017 Q4   

2018 Q1   
         Q2   
         Q3   

2017 Q4   

2018 Q1   
         Q2   
         Q3   

2015   
2016   
2017   

2017 Q4   

2018 Q1   
         Q2   
         Q3   

0.7

0.4
0.4
0.2

1.9
1.9
2.4

2.8

2.5
2.2
1.6

0.7

0.4
0.4
0.2

1.9
1.9
2.4

2.8

2.5
2.2
1.6

0.8

0.7
-0.5
-0.6

-0.2
-1.4
0.7

2.5

1.3

-0.7
0.3
0.0

3.6
3.4
3.1

3.9

1.2

0.8
1.2
0.6

0.8
1.5
3.2

4.3

0.7

0.3

0.3

0.8
0.5
0.1

1.7
1.3
0.8
annual percentage changes

-0.4
0.6
0.4

2.2
1.7
3.1

3.4

3.6
3.9
4.3

3.7

0.0
0.6
-0.6

0.0

0.2

0.6
0.1
0.3

0.7
0.3
1.1

1.3

0.8

1.1
0.7
0.0

3.0
2.5
4.0

4.4

1.8
1.3
0.4

4.8
5.1
4.3
contributions to quarter-on-quarter percentage changes in value added; percentage points

3.1
2.4
0.9

3.8
3.8
3.8

2.9
2.6
2.1

0.0
0.5
1.0

1.5
1.2
1.2

3.5
3.3
2.6

0.0

0.0
0.0
0.0

0.0
0.0
0.0

0.0

0.0
0.0
0.0

0.3

0.1

0.1

0.0

0.0

0.0

0.1

-0.1
0.1
0.0

0.1
0.1
0.0
contributions to annual percentage changes in value added; percentage points

0.0
0.1
0.0

0.2
0.1
0.0

0.0
0.0
0.0

0.1
0.0
0.0

0.1
0.1
0.0

0.7
0.7
0.6

0.8

0.6
0.5
0.2

0.0
0.1
0.2

0.2

0.2
0.2
0.2

0.4
0.3
0.6

0.6

0.5
0.5
0.4

0.2
0.2
0.2

0.2

0.2
0.2
0.2

0.0
0.0
0.0

0.0

0.0
0.0
0.0

0.1
0.0
0.1

0.2

0.2
0.1
0.1

0.3
0.3
0.4

0.5

0.4
0.4
0.3

0.3

0.3
0.2
0.2

0.8
1.3
1.1

1.2

1.4
1.2
1.0

0.1

0.1
0.0
0.0

0.2
0.2
0.2

0.2

0.3
0.2
0.2

0.2

0.1
0.0
0.2

1.2
1.0
0.9

1.0

1.2
0.7
0.5

0.0

0.0
0.0
0.0

0.0
0.0
0.0

0.0

0.0
0.0
0.0

0.6

0.3
0.6
0.1

3.5
2.7
2.4

2.1

1.6
1.8
1.5

- 

- 
- 
- 

- 
- 
- 

- 

- 
- 
- 

Sources: Eurostat and ECB calculations.

ECB Economic Bulletin, Issue 2 / 2019 - Statistics

S 9

 
 
   
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
3 Economic activity

3.3 Employment 1)
(quarterly data seasonally adjusted; annual data unadjusted)

Total    By employment

   status

   By economic activity

Employ-

ees employed

Self- Agricul- Manufac-
turing,
ture,
energy
forestry
and
and
utilities
fishing

Con-
struc-
tion

Trade,

Infor- Finance

Real Professional, Public adminis-

transport, mation
and
accom-
modation
com-
and food munica-
tion
services

and estate business and
support
services

insur-
ance

Arts,
tration, edu- entertainment
and other
services

cation, health
and
social work

1

2

3

4

5

6

7
Persons employed 

8

9

10

11

12

13

as a percentage of total persons employed

2016   
2017   
2018   

2016   
2017   
2018   

2018 Q1   
         Q2   
         Q3   
         Q4   

2015   
2016   
2017   

2015   
2016   
2017   

2017 Q4   

2018 Q1   
         Q2   
         Q3   

2015   
2016   
2017   

2017 Q4   

2018 Q1   
         Q2   
         Q3   

100.0
100.0
100.0

85.5
85.8
. 

1.4
1.6
1.4

1.5
1.5
1.3
1.3

1.7
2.0
. 

1.9
1.8
1.6
. 

100.0
100.0
100.0

80.3
80.6
81.0

1.2
1.5
1.4

1.8

1.4
1.7
1.6

0.1
0.1
-0.2

0.2

-0.1
0.2
0.3

1.4
1.9
1.9

2.4

2.0
2.2
2.0

0.2
0.2
-0.1

0.4

0.1
0.4
0.5

14.5
14.2
. 

-0.3
-0.5
. 

-0.8
-0.4
-0.3
. 

19.7
19.4
19.0

0.1
-0.3
-0.8

-0.6

-0.9
-0.5
-0.2

0.4
0.0
-0.3

0.1

-0.2
-0.1
0.1

3.2
3.2
. 

-0.4
-0.6
. 

-0.8
-0.4
0.3
. 

4.4
4.3
4.2

-0.5
-0.3
-1.0

-0.6

-1.0
0.4
0.5

0.7
0.2
-0.4

0.6

-0.2
0.8
0.2

Sources: Eurostat and ECB calculations.
1) Data for employment are based on the ESA 2010.

14.8
14.7
. 

0.8
1.2
. 

1.6
1.6
1.2
. 

15.4
15.3
15.3

0.5
0.9
1.2

2.0

1.7
1.8
1.7

0.4
0.1
0.0

0.7

0.1
0.3
0.4

6.0
6.0
. 

24.9
24.9
. 
annual percentage changes

2.8
2.8
. 

0.4
1.8
. 

2.1
2.6
2.5
. 

1.7
1.7
. 

1.5
1.3
1.3
. 

3.0
3.1
. 

2.6
2.6
3.4
. 

2.6
2.5
. 

-0.2
-1.2
. 

-0.9
-0.8
-1.2
. 

Hours worked
as a percentage of total hours worked

25.7
6.7
25.8
6.7
6.7
25.8
annual percentage changes

2.9
3.0
3.0

0.6
0.7
1.9

3.6

2.4
2.7
3.4

1.1
1.7
1.4

1.5

1.2
1.1
1.3

2.7
2.8
3.0

3.1

2.3
3.0
3.7

2.7
2.6
2.6

-0.2
0.2
-1.7

-1.8

-1.0
-0.4
-1.0

Hours worked per person employed
annual percentage changes

1.0
1.0
. 

1.9
1.5
. 

1.5
1.5
0.9
. 

1.0
1.0
1.0

1.4
2.3
2.1

3.5

2.9
1.4
1.2

0.5
0.3
0.1

1.1

0.3
0.1
0.8

-0.3
0.0
-0.3

0.0

-0.3
-0.2
0.0

1.1
-0.1
-0.1

0.0

-0.2
0.4
0.3

0.1
0.4
-0.5

-0.3

0.0
0.4
0.2

0.3
0.4
0.5

1.9

1.3
-0.1
0.3

13.5
13.7
. 

2.7
3.1
. 

3.1
3.0
2.5
. 

13.0
13.2
13.4

3.0
2.9
3.0

3.7

3.2
3.6
3.2

0.2
0.1
-0.1

0.2

0.1
0.6
0.7

24.2
24.2
. 

1.4
1.3
. 

1.2
1.2
1.1
. 

21.9
21.9
21.8

1.2
1.4
1.1

1.3

1.2
1.4
1.1

0.1
0.1
-0.2

0.1

-0.1
0.2
0.0

7.0
7.0
. 

0.7
1.4
. 

0.5
0.8
-0.8
. 

6.2
6.2
6.2

1.1
0.8
0.8

0.7

0.2
0.7
0.2

0.5
0.1
-0.6

-0.5

-0.3
-0.1
1.0

ECB Economic Bulletin, Issue 2 / 2019 - Statistics

S 10

 
 
   
   
   
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
3 Economic activity

3.4 Labour force, unemployment and job vacancies
(seasonally adjusted, unless otherwise indicated)

Labour

Under-
force, employ-
ment,
% of

millions 1)

   Total

labour Millions % of
labour
force 1)
force

   Unemployment

   By age

   By gender

Job
vacancy
rate 2)

   Adult

   Youth

   Male

   Female

Long-term
unemploy-
ment,
% of

labour Millions
force 1)

1

2

3

4

5

% of total 
in 2016 

2016   
2017   
2018   

2018 Q1   
         Q2   
         Q3   
         Q4   

2018 Aug.   
         Sep.   
         Oct.   
         Nov.   
         Dec.   

2019 Jan.   

162.028
162.659
. 

162.591
163.180
163.709
. 

- 
- 
- 
- 
- 

- 

100.0

16.254
14.765
13.393

13.941
13.495
13.156
12.979

13.121
13.108
13.102
12.965
12.871

12.848

4.3
4.1
. 

4.0
3.9
3.6
. 

- 
- 
- 
- 
- 

- 

10.0
9.1
8.2

8.5
8.3
8.1
7.9

8.0
8.0
8.0
7.9
7.8

7.8

5.0
4.4
. 

4.2
3.9
3.6
. 

- 
- 
- 
- 
- 

- 

6

81.7

13.291
12.098
10.957

11.436
11.061
10.750
10.581

10.717
10.695
10.672
10.583
10.489

10.465

% of Millions

% of Millions

% of Millions

labour
force

7

9.0
8.1
7.3

7.7
7.4
7.2
7.1

7.2
7.2
7.1
7.1
7.0

7.0

8

18.3

2.963
2.667
2.436

2.505
2.433
2.407
2.398

2.404
2.414
2.430
2.382
2.382

2.383

labour
force

9

20.9
18.8
17.0

17.6
17.0
16.8
16.6

16.8
16.8
16.9
16.5
16.5

16.5

10

52.2

8.482
7.639
6.902

7.193
6.954
6.800
6.659

6.782
6.779
6.739
6.661
6.578

6.568

labour
force

11

9.7
8.7
7.9

8.2
7.9
7.7
7.6

7.7
7.7
7.7
7.6
7.5

7.5

12

47.8

7.772
7.126
6.491

6.748
6.541
6.356
6.320

6.338
6.329
6.363
6.304
6.292

6.279

% of % of total
posts

labour
force

13

14

10.4
9.5
8.6

8.9
8.7
8.4
8.3

8.4
8.4
8.4
8.3
8.3

8.2

1.7
1.9
2.1

2.1
2.1
2.1
2.3

- 
- 
- 
- 
- 

- 

Sources: Eurostat and ECB calculations.
1) Not seasonally adjusted.
2) The job vacancy rate is equal to the number of job vacancies divided by the sum of the number of occupied posts and the number of job vacancies, expressed as a percentage.

3.5 Short-term business statistics

   Industrial production

   Total
   (excluding construction)

   Main Industrial Groupings

Con- ECB indicator
on industrial
new orders Total

struction
produc-
tion

   Retail sales

Food, Non-food

Fuel

beverages,
tobacco

New
passenger
car regis-
trations

Manu-

Inter- Capital Consumer Energy

facturing mediate
goods

goods

goods

1

2

3

4

5

6

7

8

9

100.0

88.7

32.1

34.5

21.8

11.6

100.0

100.0 100.0

10

40.4

11

52.5

12

7.1

13

100.0

% of total 
in 2015 

2016   
2017   
2018   

2018 Q1   
         Q2   
         Q3   
         Q4   

2018 Aug.   
         Sep.   
         Oct.   
         Nov.   
         Dec.   

2019 Jan.   

2018 Aug.   
         Sep.   
         Oct.   
         Nov.   
         Dec.   

2019 Jan.   

1.6
3.0
1.0

3.1
2.4
0.7
-1.9

1.1
0.6
1.3
-3.0
-4.2

. 

1.2
-0.7
0.1
-1.7
-0.9

. 

1.9
3.9
2.1

4.4
4.6
1.9
-2.0

1.8
2.2
3.7
-4.4
-5.5

. 

annual percentage changes

1.7
1.5
1.3

2.4
2.0
1.0
-0.3

3.1
0.6
0.8
0.4
-2.2

. 

0.5
1.1
-1.5

0.6
-1.9
-1.2
-3.6

-1.0
-1.4
-2.6
-4.0
-4.2

. 

3.1
3.0
2.2

2.5
2.7
2.2
1.4

0.9
3.6
0.8
1.1
0.7

. 

month-on-month percentage changes (s.a.)

1.9
-0.5
0.4
-2.7
-1.5

. 

2.0
-1.0
-0.2
-0.5
-1.5

. 

1.5
-2.0
-1.0
0.2
-0.4

. 

0.7
2.0
-1.4
0.3
-0.4

. 

0.6
7.9
2.5

6.6
3.8
1.5
-1.7

2.4
0.4
-0.2
1.0
-5.7

. 

2.8
-1.1
0.1
2.2
-4.3

. 

1.6
2.3
1.5

1.7
1.7
1.2
1.5

2.3
0.3
2.5
1.9
0.3

2.2

0.4
-0.4
0.7
0.8
-1.4

1.3

1.8
3.4
0.6

3.1
1.8
-0.2
-2.3

-0.2
-0.4
0.0
-3.1
-4.0

. 

0.4
-0.4
0.1
-1.2
0.0

. 

1.8
3.2
1.3

3.4
2.8
0.9
-1.7

1.4
0.9
1.6
-2.9
-4.0

. 

1.2
-0.4
0.1
-1.7
-1.0

. 

1.0
1.4
1.3

1.6
1.2
1.0
1.3

1.8
0.1
2.4
0.8
0.7

2.2

0.4
-0.4
0.7
-0.3
-0.1

0.6

2.1
3.3
1.8

1.8
2.3
1.4
1.7

2.7
0.5
3.0
2.4
-0.1

1.7

0.6
-0.6
0.6
1.5
-2.4

1.7

1.4
0.9
0.6

0.1
0.8
-0.1
1.4

-0.3
0.7
1.1
1.7
1.4

4.3

-0.5
0.8
0.5
0.4
0.1

1.6

Sources: Eurostat, ECB calculations, ECB experimental statistics (col. 8) and European Automobile Manufacturers Association (col. 13).

ECB Economic Bulletin, Issue 2 / 2019 - Statistics

7.2
5.7
0.8

5.3
3.2
3.4
-9.4

30.9
-21.2
-11.8
-8.9
-7.5

-2.5

21.9
-37.1
9.1
6.7
2.5

4.8

S 11

 
   
   
   
   
   
   
   
   
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
   
   
   
   
   
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
3 Economic activity

3.6 Opinion surveys
(seasonally adjusted)

   European Commission Business and Consumer Surveys
   (percentage balances, unless otherwise indicated)

   Purchasing Managers’ Surveys
   (diffusion indices)

Economic   Manufacturing industry Consumer Construction
confidence
sentiment
indicator
indicator

confidence
indicator

Retail
trade
confid-

   Service industries

Services
ence confidence
indicator

indicator

Purchasing
Managers’
Capacity Index (PMI)
for manu-
utilisation
facturing
(%)

facturing
output

Manu- Business Composite
activity
output
for
services

Industrial Capacity
(long-term confidence utilisation
(%)

indicator

average
= 100)

1999-15   

2016   
2017   
2018   

2018 Q1   
         Q2   
         Q3   
         Q4   

2018 Sep.   
         Oct.   
         Nov.   
         Dec.   

2019 Jan.   
         Feb.   

1

99.2

104.1
110.1
111.2

113.2
111.8
110.9
108.9

110.4
109.7
109.5
107.4

106.3
106.1

2

-5.3

-1.8
5.5
6.6

8.9
7.8
5.9
3.6

5.5
4.2
4.4
2.3

0.6
-0.4

3

80.7

81.7
83.2
83.8

84.1
83.9
83.7
83.6

- 
83.6
- 
- 

83.6
- 

4

-12.3

-8.6
-6.0
-5.5

-4.2
-5.2
-5.6
-6.9

-6.2
-5.9
-6.6
-8.3

-7.9
-7.4

5

-15.0

-16.4
-4.2
6.1

4.5
5.5
6.6
7.9

8.3
8.0
8.3
7.3

8.4
6.4

6

-8.7

0.6
2.3
1.3

3.0
0.5
1.9
-0.3

2.7
-0.5
-0.2
-0.1

-2.1
-1.6

7

7.2

11.3
14.6
15.2

16.8
15.1
15.3
13.4

15.2
14.0
14.0
12.2

11.0
12.1

8

- 

88.9
89.8
90.3

90.3
90.4
90.3
90.4

- 
90.1
- 
- 

90.7
- 

9

10

11

51.2

52.5
57.4
54.9

58.2
55.6
54.3
51.7

53.2
52.0
51.8
51.4

50.5
49.3

52.5

53.6
58.5
54.7

58.9
55.1
54.0
51.0

52.7
51.3
50.7
51.0

50.5
49.4

53.0

53.1
55.6
54.5

56.4
54.5
54.4
52.8

54.7
53.7
53.4
51.2

51.2
52.8

12

52.8

53.3
56.4
54.6

57.0
54.7
54.3
52.3

54.1
53.1
52.7
51.1

51.0
51.9

Sources: European Commission (Directorate-General for Economic and Financial Affairs) (col. 1-8) and Markit (col. 9-12).

3.7 Summary accounts for households and non-financial corporations
(current prices, unless otherwise indicated; not seasonally adjusted)

   Households

   Non-financial corporations

Saving Debt Real gross

Financial Non-financial

ratio ratio disposable investment

(gross) 1)

income

investment worth

(gross)

Net Hous-
ing
 2) wealth

share 3)

Profit Saving
ratio
(net)

Debt
ratio 4)

investment

Financial Non-financial
investment
(gross)

Finan-
cing

   Percentage of
   gross disposable
   income (adjusted)

   Annual percentage changes

   Percentage of net
   value added

Percent-
age of
GDP

   Annual percentage changes

2015   
2016   
2017   

2017 Q4   

2018 Q1   
         Q2   
         Q3   

1

2

12.4 94.0
12.3 94.2
11.8 94.1

11.8 94.1

11.8 93.8
12.0 93.8
12.1 93.7

3

1.6
1.8
1.2

1.5

1.8
1.9
1.4

4

2.0
2.0
1.9

1.9

1.9
1.9
1.9

5

6

1.2
6.2
6.9

6.4

5.7
8.4
8.5

3.2
3.4
4.0

4.0

3.6
3.8
3.8

7

2.0
2.8
4.1

4.1

4.5
4.6
5.1

8

34.7
35.2
34.7

34.7

34.8
34.9
34.5

9

6.2
7.7
6.9

6.9

7.0
6.9
6.9

10

138.8
139.0
137.0

137.0

136.8
137.6
137.0

11

5.0
4.9
3.4

3.4

3.0
3.1
2.8

12

7.8
6.2
5.0

1.4

0.0
1.0
8.1

13

2.9
2.9
2.0

2.0

1.6
1.7
1.7

Sources: ECB and Eurostat.
1) Based on four-quarter cumulated sums of both saving and gross disposable income (adjusted for the change in the net equity of households in pension fund reserves).
2) Financial assets (net of financial liabilities) and non-financial assets. Non-financial assets consist mainly of housing wealth (residential structures and land). They also include

non-financial assets of unincorporated enterprises classified within the household sector.

3) The profit share uses net entrepreneurial income, which is broadly equivalent to current profits in business accounting. 
4) Based on the outstanding amount of loans, debt securities, trade credits and pension scheme liabilities.

ECB Economic Bulletin, Issue 2 / 2019 - Statistics

S 12

 
   
   
   
   
 
 
 
 
   
   
   
                                   
   
                 
   
   
   
   
   
 
3 Economic activity

3.8 Euro area balance of payments, current and capital accounts
(EUR billions; seasonally adjusted unless otherwise indicated; transactions)

   Total

   Goods

   Services

   Primary income    Secondary income

   Current account

   Capital
   account 1) 

Credit

Debit

Net Credit

Debit

Credit

Debit

Credit

Debit

Credit

Debit

Credit

Debit

1

2

3

4

5

6

993.0
1,020.4
1,029.7
1,003.8

338.8
348.1
342.8
334.9
340.0
328.9

888.1
924.3
953.5
938.5

316.5
315.4
321.6
308.4
317.4
312.7

104.9
96.1
76.2
65.3

22.3
32.8
21.2
26.5
22.6
16.2

577.5
585.2
591.8
586.2

194.8
199.6
197.3
198.8
196.5
190.8

492.1
505.2
523.0
531.1

173.2
173.6
176.2
179.2
176.9
175.0

218.8
220.9
228.7
225.6

76.2
76.7
75.9
72.5
76.9
76.2

7

189.0
191.8
200.1
191.9

66.7
66.4
67.0
61.3
65.0
65.6

8

168.5
186.2
180.5
163.3

58.6
61.8
60.1
54.1
57.0
52.3

9

147.9
163.5
161.5
146.0

53.3
53.2
55.1
45.7
51.1
49.1

10

28.3
28.1
28.8
28.7

9.2
10.1
9.5
9.5
9.6
9.6

11

59.1
63.8
68.8
69.5

23.3
22.2
23.3
22.2
24.3
22.9

12

9.0
8.1
8.2
18.8

2.9
3.0
2.3
3.3
4.1
11.4

13

6.4
6.4
5.9
11.3

1.9
1.8
2.2
2.2
3.1
6.0

12-month cumulated transactions

2018 Q1   
         Q2   
         Q3   
         Q4   

2018 July   
         Aug.   
         Sep.   
         Oct.   
         Nov.   
         Dec.   

2018 Dec.   

4,046.9

3,704.3

342.6 2,340.7
12-month cumulated transactions as a percentage of GDP

2,051.5

772.8

894.0

698.4

618.9

113.8

261.1

44.1

30.0

2018 Dec.   

35.2

32.2

3.0

20.3

17.8

7.8

6.7

6.1

5.4

1.0

2.3

0.4

0.3

1) The capital account is not seasonally adjusted.

3.9 Euro area external trade in goods 1) , values and volumes by product group 2) 
(seasonally adjusted, unless otherwise indicated)

   Total (n.s.a.)

   Exports (f.o.b.)

   Imports (c.i.f.)

   Total

Memo item:

   Total

   Memo items:

Exports Imports

Intermediate Capital Consump-
tion
goods

goods

goods

Manu-
facturing

Intermediate Capital Consump-
tion
goods

goods

goods

Manu-
facturing

Oil

1

2

3

4

5

6

7

8

9

10

11

12

13

2018 Q1   
         Q2   
         Q3   
         Q4   

2018 July   
         Aug.   
         Sep.   
         Oct.   
         Nov.   
         Dec.   

2018 Q1   
         Q2   
         Q3   
         Q4   

2018 June   
         July   
         Aug.   
         Sep.   
         Oct.   
         Nov.   

2.1
4.3
4.7
3.7

9.4
5.5
-0.6
11.1
2.2
-2.5

2.2
3.0
0.9
. 

3.5
6.3
1.6
-4.7
6.9
-1.6

2.1
5.8
10.0
7.0

14.0
8.7
7.4
14.2
4.6
1.9

2.4
2.5
1.6
. 

2.0
6.6
0.1
-1.8
4.5
-1.5

561.2
566.0
572.4
578.7

189.2
192.7
190.5
194.1
192.4
192.2

125.8
125.6
125.2
. 

126.3
124.7
126.6
124.4
126.8
125.3

Values (EUR billions; annual percentage changes for columns 1 and 2)

270.5
271.3
277.7
. 

91.7
93.5
92.5
93.6
92.7
. 

114.0
117.7
117.0
. 

38.9
38.9
39.2
40.1
40.7
. 

167.9
166.5
167.2
. 

55.2
56.5
55.5
56.3
55.8
. 

470.2
473.8
476.7
480.8

155.9
161.0
159.9
160.6
161.4
158.7

504.5
515.1
530.9
533.5

177.0
176.3
177.6
180.4
176.6
176.6

291.8
300.8
310.1
. 

103.7
102.8
103.6
105.7
101.7
. 

81.0
79.8
86.2
. 

28.7
28.3
29.2
29.1
28.6
. 

Volume indices (2000 = 100; annual percentage changes for columns 1 and 2)

125.5
124.4
125.4
. 

125.2
124.5
126.8
124.9
126.2
124.6

123.5
126.8
124.5
. 

128.4
124.9
124.4
124.2
127.8
128.9

131.5
129.2
127.9
. 

131.3
127.1
129.9
126.7
128.7
126.8

126.2
126.3
125.5
. 

127.1
123.6
127.3
125.7
126.7
126.3

114.4
115.2
115.2
. 

114.9
116.0
115.1
114.5
116.1
113.9

114.9
115.3
114.8
. 

115.6
115.7
114.9
114.0
115.6
112.7

113.0
112.0
118.0
. 

112.3
119.0
117.2
117.7
118.4
113.6

Sources: ECB and Eurostat.
1) Differences between ECB’s b.o.p. goods (Table 3.8) and Eurostat’s trade in goods (Table 3.9) are mainly due to different definitions.
2) Product groups as classified in the Broad Economic Categories.

123.7
126.9
126.6
. 

42.3
42.2
42.2
43.9
43.4
. 

115.2
118.3
115.1
. 

117.3
116.3
114.6
114.4
119.2
117.0

357.8
364.1
372.4
374.7

124.4
123.4
124.6
126.4
125.3
123.0

65.2
65.6
68.4
. 

22.7
23.0
22.7
24.2
21.2
. 

117.6 110.3
119.3 101.7
99.4
119.5
. 
. 

118.5 101.5
120.5 100.3
119.1 102.4
95.6
119.0
98.1
121.1
94.8
118.4

ECB Economic Bulletin, Issue 2 / 2019 - Statistics

S 13

 
   
   
   
   
   
   
   
   
 
 
 
 
 
 
   
   
   
   
   
   
 
 
 
 
4 Prices and costs

4.1 Harmonised Index of Consumer Prices 1)
(annual percentage changes, unless otherwise indicated)

   Total

   Total (s.a.; percentage change vis-à-vis previous period) 2) 

Index:
2015
= 100

   Total

Goods Services

Total
excluding
food and
energy

Total Processed Unpro- Non-energy
industrial
goods

cessed
food

food

Energy
(n.s.a.)

Services

   Administered prices

Total HICP Admini-
stered
prices

excluding
administered
prices

% of total 
in 2019 

2016  
2017  
2018  

2018 Q1   
         Q2   
         Q3   
         Q4   

2018 Sep.   
         Oct.   
         Nov.   
         Dec.   

2019 Jan.   
         Feb.  3) 

1

2

3

4

5

6

100.0 100.0

70.9

55.5

44.5

100.0

100.2
101.8
103.6

102.1
103.8
104.1
104.3

104.4
104.7
104.1
104.1

103.0
103.3

0.2
1.5
1.8

1.3
1.7
2.1
1.9

2.1
2.3
1.9
1.5

1.4
1.5

0.8
1.0
1.0

1.0
1.0
1.0
1.0

1.0
1.2
0.9
0.9

1.1
1.0

-0.4
1.6
2.0

1.1
2.0
2.6
2.3

2.6
2.7
2.4
1.7

1.2
. 

1.1
1.4
1.5

1.4
1.4
1.5
1.5

1.4
1.7
1.4
1.3

1.6
1.3

-
-
-

0.5
0.6
0.5
0.3

0.2
0.2
0.0
-0.3

0.0
0.2

7

14.5

-
-
-

0.5
0.7
0.4
0.2

0.1
0.1
0.1
0.0

0.3
0.2

8

4.5

-
-
-

0.2
0.9
0.5
0.4

1.3
-0.3
-0.5
0.3

0.1
0.7

9

26.4

10

10.1

11

44.5

12

83.6

13

16.4

-
-
-

0.1
0.0
0.1
0.1

0.0
0.0
0.0
0.0

0.0
0.0

-
-
-

1.9
1.9
2.7
1.6

1.3
1.8
0.0
-3.3

-0.9
0.6

-
-
-

0.5
0.5
0.3
0.2

0.1
0.1
0.0
0.0

0.1
0.0

0.2
1.6
1.7

1.2
1.7
2.1
1.8

2.0
2.2
1.8
1.3

1.2
. 

0.3
1.2
2.1

1.8
1.7
2.3
2.6

2.3
2.7
2.7
2.5

2.3
. 

   Goods

   Services

   Food (including alcoholic
   beverages and tobacco)

Total Processed
food

Unpro-
cessed
food

14

19.0

15

14.5

0.9
1.8
2.2

1.7
2.6
2.5
2.0

2.6
2.2
1.9
1.8

1.8
2.4

0.6
1.5
2.1

2.2
2.3
2.1
1.9

2.1
2.1
2.0
1.7

1.8
2.2

16

4.5

1.4
2.4
2.3

0.2
3.3
3.8
2.0

4.3
2.4
1.8
1.8

1.8
2.9

% of total 
in 2019 

2016  
2017  
2018  

2018 Q1   
         Q2   
         Q3   
         Q4   

2018 Sep.   
         Oct.   
         Nov.   
         Dec.   

2019 Jan.   
         Feb.  3) 

   Industrial goods

   Housing

Transport Communi- Recreation Miscel-
and laneous

cation

Total

17

36.5

-1.1
1.5
1.9

0.8
1.6
2.7
2.4

2.6
3.0
2.6
1.6

0.9
. 

Non-energy
industrial
goods

Energy

Rents

18

26.4

0.4
0.3
0.3

0.3
0.2
0.2
0.2

0.2
0.2
0.2
0.2

0.3
0.3

19

10.1

-5.1
4.9
6.4

2.2
5.6
9.5
8.4

9.6
10.8
9.1
5.5

2.7
3.5

20

11.0

1.1
1.3
1.2

1.3
1.2
1.1
1.2

1.1
1.2
1.2
1.2

1.2
. 

21

6.5

1.1
1.2
1.2

1.3
1.2
1.1
1.1

1.1
1.1
1.1
1.1

1.1
. 

22

7.2

0.8
2.1
1.5

1.7
1.3
1.4
1.5

1.3
1.8
1.6
1.2

1.6
. 

personal
care

24

15.3

1.3
2.1
2.0

1.9
1.9
2.2
1.9

2.0
2.5
1.5
1.6

2.2
. 

23

2.6

0.0
-1.1
-0.1

-0.2
0.1
0.2
-0.3

0.0
-0.2
-0.5
-0.3

-0.4
. 

25

8.4

1.2
0.8
1.4

1.2
1.3
1.3
1.7

1.3
1.7
1.7
1.7

1.5
. 

Sources: Eurostat and ECB calculations.
1) Data refer to the changing composition of the euro area.
2) In May 2016 the ECB started publishing enhanced seasonally adjusted HICP series for the euro area, following a review of the seasonal adjustment approach as described

in Box 1, Economic Bulletin, Issue 3, ECB, 2016 (https://www.ecb.europa.eu/pub/pdf/ecbu/eb201603.en.pdf).

3) Estimate based on provisional national data, as well as on early information on energy prices.

ECB Economic Bulletin, Issue 2 / 2019 - Statistics

S 14

 
   
   
   
   
   
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
   
   
   
   
   
   
   
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
4 Prices and costs

4.2 Industry, construction and property prices
(annual percentage changes, unless otherwise indicated)

Total
(index:
2015 = 100)

   Industrial producer prices excluding construction 1)

   Total

   Industry excluding construction and energy

Energy

Manu- Total

facturing

Intermediate Capital
goods

goods

   Consumer goods

Con-
struction
 2)

Residential
property
prices 3)

Experimental
indicator of
commercial
property
prices 3)

Total

Food, Non-
beverages food

and tobacco

% of total 
in 2015 

2016   
2017   
2018   

2018 Q1   
         Q2   
         Q3   
         Q4   

2018 Aug.   
         Sep.   
         Oct.   
         Nov.   
         Dec.   

2019 Jan.   

1

2

3

4

5

6

7

8

9

100.0 100.0

77.3

72.1

28.9

20.7

22.5

16.5

5.9

97.9 -2.1
3.0
3.2

100.8
104.0

-1.4
3.0
2.5

-0.5
2.1
1.5

102.4
103.1
104.9
105.7

104.8
105.4
106.2
105.9
105.1

105.5

1.7
2.8
4.3
4.0

4.3
4.6
4.9
4.0
3.0

3.0

1.6
2.6
3.2
2.3

3.3
3.0
3.2
2.3
1.5

1.0

1.5
1.4
1.5
1.4

1.6
1.5
1.5
1.5
1.3

1.2

-1.6
3.2
2.7

2.4
2.5
3.1
2.5

3.3
2.9
2.7
2.6
2.2

1.7

0.5
0.9
1.0

0.9
1.0
1.1
1.1

1.1
1.1
1.2
1.2
1.1

1.4

0.0
1.9
0.4

0.8
0.3
0.1
0.3

0.1
0.0
0.2
0.2
0.4

0.5

0.0
2.8
0.2

1.0
0.1
-0.3
-0.2

-0.3
-0.4
-0.3
-0.2
0.0

0.0

0.0
0.2
0.7

0.5
0.6
0.7
0.8

0.7
0.7
0.8
0.8
0.8

1.0

10

27.9

-6.9
5.7
8.1

2.0
6.7
12.5
11.1

12.4
13.0
14.6
11.0
7.7

7.3

11

12

13

0.6
2.2
. 

2.4
2.4
2.7
. 

- 
- 
- 
- 
- 

- 

3.4
3.7
. 

4.3
4.2
4.3
. 

- 
- 
- 
- 
- 

- 

5.0
5.1
. 

4.7
4.2
. 
. 

- 
- 
- 
- 
- 

- 

Sources: Eurostat, ECB calculations, and ECB calculations based on MSCI data and national sources (col. 13).
1) Domestic sales only.
2) Input prices for residential buildings.
3) Experimental data based on non-harmonised sources (see https://www.ecb.europa.eu/stats/ecb_statistics/governance_and_quality_framework/html/experimental-data.en.html

for further details).

4.3 Commodity prices and GDP deflators
(annual percentage changes, unless otherwise indicated)

Total Total
(s.a.;
index:
2010
= 100)

Total

   GDP deflators

   Domestic demand

Exports 1)

Imports 1)

consump-

Private Govern-
ment
tion consump-

Gross
fixed
capital
tion formation

Oil prices
(EUR per
barrel)

   Non-energy commodity prices  (EUR)

   Import-weighted 2)

   Use-weighted 2) 

Total Food Non-food Total Food Non-food

1

2

3

4

5

6

7

8

9

10

11

12

13

14

% of total 

2016   
2017   
2018   

2018 Q1   
         Q2   
         Q3   
         Q4   

2018 Sep.   
         Oct.   
         Nov.   
         Dec.   

2019 Jan.   
         Feb.   

106.9
108.0
. 

108.9
109.4
109.8
. 

- 
- 
- 
- 

- 
- 

0.8
1.1
. 

1.4
1.4
1.4
. 

- 
- 
- 
- 

- 
- 

0.5
1.5
. 

1.5
1.8
2.1
. 

- 
- 
- 
- 

- 
- 

0.4
1.4
. 

1.2
1.5
1.8
. 

- 
- 
- 
- 

- 
- 

0.5
1.4
. 

1.5
2.0
1.9
. 

- 
- 
- 
- 

- 
- 

0.7
1.5
. 

1.8
1.9
2.5
. 

- 
- 
- 
- 

- 
- 

-1.4
1.9
. 

0.4
1.0
2.2
. 

- 
- 
- 
- 

- 
- 

-2.5
2.9
. 

0.4
2.0
3.9
. 

- 
- 
- 
- 

- 
- 

  100.0

45.4

54.6 100.0

50.4

39.9
48.1
60.4

54.6
62.6
64.8
59.5

67.6
70.1
57.4
49.8

51.9
56.5

-2.0
5.8
-0.9

-1.4
-3.5
-6.3

-8.9 -14.6
-6.0
2.1
-3.4
2.0
0.1
2.0

0.8
2.6
1.8
1.5

1.3
2.2

-3.0
-0.9
-0.9
2.0

4.0
4.4

-2.8
16.6
4.3

-3.2
10.3
7.1
3.6

4.2
5.7
4.1
1.1

-1.1
0.3

-3.1
6.7
-0.2

-3.7
-1.6
-5.5

-7.6 -12.9
-6.3
1.9
-2.2
3.1
0.2
2.3

2.3
2.9
1.7
2.2

1.5
2.7

-1.0
-0.4
-1.2
2.4

3.8
4.7

15

49.6

-2.3
17.8
5.7

-1.4
11.7
8.8
4.4

5.7
6.4
4.8
2.1

-0.7
0.7

Sources: Eurostat, ECB calculations and Bloomberg (col. 9).
1) Deflators for exports and imports refer to goods and services and include cross-border trade within the euro area.
2) Import-weighted: weighted according to 2009-11 average import structure; use-weighted: weighted according to 2009-11 average domestic demand structure.

ECB Economic Bulletin, Issue 2 / 2019 - Statistics

S 15

 
   
   
   
   
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
   
   
   
   
   
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
4 Prices and costs

4.4 Price-related opinion surveys
(seasonally adjusted)

   European Commission Business and Consumer Surveys
   (percentage balances)

   Purchasing Managers’ Surveys
   (diffusion indices)

   Selling price expectations
   (for next three months)

Manu-
facturing

Retail trade

Services

Construction

Consumer
price trends
over past
12 months

   Input prices

   Prices charged

Manu-
facturing

Services

Manu-
facturing

Services

1999-15   

2016   
2017   
2018   

2018 Q1   
         Q2   
         Q3   
         Q4   

2018 Sep.   
         Oct.   
         Nov.   
         Dec.   

2019 Jan.   
         Feb.   

1

4.2

-0.4
9.2
11.5

12.5
10.3
11.1
11.9

11.9
10.4
12.2
13.0

10.7
8.9

2

- 

2.3
5.1
7.4

6.7
6.9
7.5
8.5

7.4
9.0
7.4
9.2

8.8
8.1

3

- 

4.4
6.9
9.4

9.1
9.4
9.0
10.0

8.4
8.8
10.1
11.1

11.5
9.2

4

-3.6

-7.1
2.5
12.1

10.8
12.1
12.4
13.0

12.0
13.0
12.4
13.6

12.9
12.3

5

31.7

0.3
12.3
20.0

17.2
18.4
20.8
23.5

22.4
24.1
23.6
22.7

18.9
20.0

6

56.7

49.8
64.6
65.4

68.4
65.6
65.2
62.6

63.6
65.1
63.6
59.1

55.7
53.9

7

56.3

53.9
56.3
57.9

57.2
57.6
58.4
58.4

59.1
58.5
58.9
57.9

58.3
58.1

8

- 

49.3
55.1
56.1

57.9
56.5
55.5
54.5

55.7
54.8
54.7
54.1

53.8
52.7

9

49.7

49.6
51.6
52.7

52.9
52.3
52.8
52.7

52.8
52.8
52.8
52.5

53.2
52.7

Sources: European Commission (Directorate-General for Economic and Financial Affairs) and Markit.

4.5 Labour cost indices
(annual percentage changes, unless otherwise indicated)

Total
(index:
2012 = 100)

1

100.0

105.5
107.5
. 

102.6
113.9
106.4
. 

Total

   By component

   For selected economic activities

Wages and
salaries

Employers’ social
contributions

Business economy

Mainly non-business
economy

2

100.0

1.4
1.8
. 

2.0
2.3
2.5
. 

3

74.6

1.4
1.8
. 

1.8
2.0
2.4
. 

4

25.4

1.1
1.8
. 

2.8
3.0
3.0
. 

5

69.3

1.3
1.9
. 

2.3
2.5
2.7
. 

6

30.7

1.5
1.6
. 

1.5
1.7
2.2
. 

Memo item:
Indicator of
negotiated
wages 1)

7

1.4
1.5
2.0

1.7
2.1
2.1
2.2

% of total 
in 2012 

2016   
2017   
2018   

2018 Q1   
         Q2   
         Q3   
         Q4   

Sources: Eurostat and ECB calculations.
1) Experimental data based on non-harmonised sources (see https://www.ecb.europa.eu/stats/ecb_statistics/governance_and_quality_framework/html/experimental-data.en.html

for further details).

ECB Economic Bulletin, Issue 2 / 2019 - Statistics

S 16

 
   
   
   
   
   
   
   
 
 
 
 
   
   
 
 
 
 
 
 
 
 
 
 
4 Prices and costs

4.6 Unit labour costs, compensation per labour input and labour productivity
(annual percentage changes, unless otherwise indicated; quarterly data seasonally adjusted; annual data unadjusted)

Total Total

(index:
2010
=100)

   By economic activity

Agriculture,
forestry

Manu-

Con-
facturing, struction

Trade,

Information
transport, and commu-

and fishing energy and
utilities

accom-
modation and
food services

nication insurance

Finance

Real Professional,

and estate business and ministration,
education,
health and
social work

support
services

Public ad- Arts, enter-
tainment
and other
services

1

2

3

4

5

6
Unit labour costs 

7

8

9

10

11

12

2015   
2016   
2017   

2017 Q4   

2018 Q1   
         Q2   
         Q3   

2015   
2016   
2017   

2017 Q4   

2018 Q1   
         Q2   
         Q3   

2016   
2017   
2018   

2018 Q1   
         Q2   
         Q3   
         Q4   

2015   
2016   
2017   

2017 Q4   

2018 Q1   
         Q2   
         Q3   

2015   
2016   
2017   

2017 Q4   

2018 Q1   
         Q2   
         Q3   

104.6
105.3
106.1

106.4

107.0
107.6
108.4

108.0
109.3
111.1

112.1

112.6
113.3
114.1

103.9
104.7
. 

105.3
105.3
105.3
105.2

109.7
110.8
112.6

113.2

113.8
114.3
114.8

105.2
105.7
106.8

107.1

107.2
107.0
106.7

0.4
0.6
0.8

0.8

1.1
1.6
2.2

1.4
1.2
1.6

1.9

1.9
2.2
2.5

0.6
0.8
. 

0.9
0.6
0.3
-0.1

1.2
1.0
1.7

1.5

1.8
1.9
2.0

0.9
0.5
1.0

0.9

0.9
0.4
0.0

Sources: Eurostat and ECB calculations.

0.4
1.3
0.3

-1.3

0.4
1.0
1.9

1.3
0.2
1.6

2.4

3.0
2.6
1.9

-1.0
1.3
. 

2.7
1.6
0.0
. 

1.4
-0.4
1.3

1.6

2.9
1.1
1.9

0.2
-1.2
1.7

3.1

2.8
0.9
-0.1

-1.4
-1.3
-0.4

-0.6

0.0
1.3
2.6

2.0
1.3
1.5

1.9

1.6
2.1
2.3

2.6
1.9
. 

1.5
0.8
-0.3
. 

1.6
1.2
1.5

1.1

1.4
1.8
1.7

3.1
2.5
1.9

1.9

1.4
0.5
-0.7

0.6
0.6
-0.1

-0.1

-0.5
0.3
1.1

1.2
1.8
1.2

1.6

1.2
1.5
2.4

0.4
1.3
0.3

-0.1

0.6
0.9
1.7

0.7
-0.7
0.8

1.7

0.6
0.4
1.4

Compensation per employee 

1.3
1.3
1.6

1.8

2.0
2.2
2.4

2.7
0.2
1.9

2.4

2.8
2.9
2.4

Labour productivity per person employed

1.1
1.3
. 

1.7
1.2
1.3
. 

0.0
1.4
. 

1.4
1.3
0.7
. 

0.9
1.1
. 

2.2
2.4
0.9
. 

Compensation per hour worked 

0.7
1.7
1.0

0.6

0.3
0.9
1.5

0.2
0.8
1.3

0.7

1.3
1.0
0.4

1.3
0.9
1.9

1.6

2.2
2.1
2.2

1.5
0.2
1.8

2.1

2.9
2.2
2.1

Hourly labour productivity

1.1
0.0
1.7

1.9

1.7
1.5
0.8

0.9
1.0
1.2

0.7

2.4
2.0
0.6

0.5
1.4
-0.5

-1.4

0.8
0.6
0.2

0.8
2.2
0.0

0.1

1.7
1.9
2.4

0.7
0.6
. 

0.9
1.3
2.2
. 

0.7
1.8
0.5

0.3

1.8
1.5
2.2

0.2
0.3
1.1

1.8

1.0
0.9
2.0

2.4
3.8
4.4

4.4

3.3
3.1
3.6

2.0
2.2
4.0

4.1

3.3
2.8
3.9

-1.5
-0.4
. 

0.0
-0.3
0.3
. 

1.4
1.9
3.3

2.1

2.0
2.3
2.7

-0.7
-2.0
-0.9

-2.1

-1.4
-0.2
0.0

1.3
0.6
2.2

2.3

2.2
2.5
3.0

1.6
0.4
3.1

3.3

2.5
2.8
3.0

-0.2
0.8
. 

0.3
0.3
0.1
. 

1.1
0.0
2.8

2.7

2.2
2.1
2.3

0.0
-0.4
0.9

0.7

0.2
-0.3
-0.6

1.4
1.4
1.6

1.7

1.7
2.2
2.4

1.1
1.3
1.5

1.6

1.9
2.3
2.3

-0.1
-0.2
. 

0.2
0.0
-0.1
. 

1.2
1.3
1.6

1.4

1.9
2.0
2.2

-0.4
-0.2
0.0

-0.2

0.3
-0.2
-0.2

1.1
1.5
1.8

1.7

1.6
2.5
2.6

1.8
1.7
1.3

1.6

2.2
2.4
4.0

0.3
-0.5
. 

0.7
-0.1
1.3
. 

1.5
1.5
1.7

1.8

2.0
1.9
2.2

0.1
0.2
0.1

0.4

1.0
0.0
0.3

ECB Economic Bulletin, Issue 2 / 2019 - Statistics

S 17

 
 
   
 
 
 
 
 
 
 
 
 
 
 
 
 
5 Money and credit

5.1 Monetary aggregates 1) 
(EUR billions and annual growth rates; seasonally adjusted; outstanding amounts and growth rates at end of period; transactions during period)

   M3

   M2

   M3-M2

   M1

   M2-M1

Currency Overnight
deposits

in
circulation

Deposits

Deposits
with an redeemable
at notice
agreed
of up to
maturity
of up to
3 months
2 years

Repos

Money
market
fund
shares

Debt
securities
with
a maturity
of up to
2 years

1

2

3

4

5

6

7

8

9

10

11

12

2016   
2017   
2018   

2018 Q1   
         Q2   
         Q3   
         Q4   

2018 Aug.   
         Sep.   
         Oct.   
         Nov.   
         Dec.   

1,075.3
1,111.6
1,162.6

1,116.9
1,133.6
1,150.6
1,162.6

1,143.8
1,150.6
1,154.4
1,158.2
1,162.6

2019 Jan. (p)  

1,167.5

2016   
2017   
2018   

2018 Q1   
         Q2   
         Q3   
         Q4   

2018 Aug.   
         Sep.   
         Oct.   
         Nov.   
         Dec.   

2019 Jan. (p)  

2016   
2017   
2018   

2018 Q1   
         Q2   
         Q3   
         Q4   

2018 Aug.   
         Sep.   
         Oct.   
         Nov.   
         Dec.   

2019 Jan. (p)  

38.1
36.4
50.0

5.3
16.6
16.0
12.1

6.5
6.8
3.9
3.8
4.5

4.9

3.7
3.4
4.5

2.5
3.5
4.1
4.5

3.9
4.1
4.1
4.3
4.5

4.7

6,082.8
6,637.8
7,118.6

6,743.6
6,892.3
7,010.0
7,118.6

6,951.5
7,010.0
7,044.8
7,091.6
7,118.6

7,127.1

541.7
591.8
461.3

102.5
137.7
116.1
105.0

33.8
57.4
31.4
47.7
25.9

11.9

9.7
9.8
6.9

8.4
8.1
7.3
6.9

7.0
7.3
7.3
7.1
6.9

6.4

7,158.1
7,749.4
8,281.2

7,860.5
8,025.8
8,160.5
8,281.2

8,095.3
8,160.5
8,199.3
8,249.7
8,281.2

8,294.6

579.8
628.1
511.3

107.8
154.3
132.1
117.1

40.3
64.2
35.2
51.5
30.4

16.8

8.8
8.8
6.6

7.5
7.4
6.8
6.6

6.5
6.8
6.8
6.7
6.6

6.2

Source: ECB.
1) Data refer to the changing composition of the euro area.

1,330.6
1,197.0
1,128.3

1,170.4
1,178.1
1,126.6
1,128.3

1,140.1
1,126.6
1,137.8
1,125.8
1,128.3

1,124.2

-106.1
-110.5
-71.5

-24.9
4.8
-51.8
0.4

-16.6
-14.1
9.2
-11.8
3.0

-4.1

-7.4
-8.4
-6.0

-8.9
-5.5
-7.4
-6.0

-7.6
-7.4
-6.2
-6.7
-6.0

-6.2

Outstanding amounts

2,221.0
2,261.2
2,294.2

2,260.2
2,270.8
2,285.0
2,294.2

2,281.1
2,285.0
2,290.3
2,295.1
2,294.2

2,298.5

3,551.5
3,458.2
3,422.5

3,430.6
3,448.9
3,411.5
3,422.5

3,421.2
3,411.5
3,428.1
3,420.9
3,422.5

10,709.7
11,207.7
11,703.7

11,291.1
11,474.7
11,572.1
11,703.7

11,516.5
11,572.1
11,627.3
11,670.6
11,703.7

3,422.7

11,717.3

Transactions

16.1
34.3
45.0

7.6
9.8
14.1
13.4

3.9
3.9
5.5
4.8
3.1

5.1

-90.0
-76.2
-26.5

-17.3
14.6
-37.6
13.8

-12.7
-10.3
14.7
-7.0
6.1

1.0

Growth rates

0.7
1.5
2.0

1.6
1.7
1.8
2.0

1.8
1.8
1.8
2.0
2.0

2.0

-2.5
-2.1
-0.8

-2.2
-0.9
-1.4
-0.8

-1.5
-1.4
-1.0
-1.0
-0.8

-0.8

489.8
551.9
484.8

90.5
169.0
94.5
130.9

27.6
53.9
49.9
44.5
36.5

17.8

4.8
5.2
4.3

4.3
4.7
4.3
4.3

4.0
4.3
4.4
4.3
4.3

4.0

69.6
74.7
74.6

71.4
73.7
71.4
74.6

71.8
71.4
72.0
73.8
74.6

75.8

-4.3
6.6
-3.4

-3.1
-0.9
-2.4
3.0

3.2
-0.5
0.4
1.8
0.9

1.2

-5.8
9.5
-4.5

-1.6
5.3
2.0
-4.5

-2.5
2.0
-0.6
-8.1
-4.5

-2.8

523.1
512.0
523.3

511.4
507.8
495.4
523.3

501.7
495.4
505.7
503.5
523.3

516.6

34.3
-10.9
11.3

-0.6
-3.2
-12.6
27.7

-6.7
-6.2
10.3
-2.2
19.6

-7.6

7.0
-2.1
2.2

-4.7
-1.4
-6.7
2.2

-3.6
-6.7
-3.8
-3.1
2.2

-0.1

86.6
71.6
71.6

61.5
65.5
60.5
71.6

63.5
60.5
60.9
58.2
71.6

64.7

18.3
-18.4
-1.7

-9.1
2.3
-4.7
9.8

2.3
-2.6
-0.9
-2.7
13.5

-6.6

26.1
-21.4
-2.3

-27.2
-16.3
-26.0
-2.3

-14.9
-26.0
-17.4
-22.4
-2.3

9.1

679.2 11,388.9
658.4 11,866.0
669.5 12,373.2

644.3 11,935.4
647.1 12,121.8
627.4 12,199.4
669.5 12,373.2

637.0 12,153.5
627.4 12,199.4
638.6 12,266.0
635.4 12,306.1
669.5 12,373.2

657.1 12,374.3

48.3
-22.7
6.2

-12.8
-1.8
-19.7
40.5

-1.2
-9.3
9.8
-3.2
33.9

-13.0

7.6
-3.3
0.9

-7.1
-2.4
-8.1
0.9

-4.7
-8.1
-5.0
-5.8
0.9

0.4

538.0
529.2
491.0

77.7
167.1
74.8
171.4

26.4
44.6
59.7
41.3
70.3

4.8

5.0
4.7
4.1

3.6
4.3
3.5
4.1

3.5
3.5
3.8
3.7
4.1

3.8

ECB Economic Bulletin, Issue 2 / 2019 - Statistics

S 18

 
 
   
   
   
   
   
   
   
 
 
 
 
5 Money and credit

5.2 Deposits in M3 1) 
(EUR billions and annual growth rates; seasonally adjusted; outstanding amounts and growth rates at end of period; transactions during period)

   Non-financial corporations 2) 

   Households 3) 

Total Overnight

With an Redeem- Repos
agreed
maturity
of up to
2 years

able
at notice
of up to
3 months

Total Overnight

With an Redeem- Repos
agreed
maturity
of up to
2 years

able
at notice
of up to
3 months

Financial
corpor-
ations
other than
MFIs and
ICPFs 2)

Insurance

Other
corpor- general
ations govern-
and ment 4)

pension
funds

1

2

3

4

5

7
Outstanding amounts 

6

8

9

10

11

12

13

2016   
2017   
2018   

2018 Q1   
         Q2   
         Q3   
         Q4   

2,093.2
2,255.7
2,335.9

2,260.5
2,296.8
2,323.5
2,335.9

2018 Aug.    2,305.8
         Sep.    2,323.5
         Oct.   
2,316.3
         Nov.    2,322.4
         Dec.    2,335.9

1,630.3
1,801.7
1,901.4

1,821.6
1,855.2
1,891.3
1,901.4

1,872.8
1,891.3
1,892.2
1,892.2
1,901.4

2019 Jan. (p)   2,324.7

1,899.7

2016   
2017   
2018   

2018 Q1   
         Q2   
         Q3   
         Q4   

2018 Aug.   
         Sep.   
         Oct.   
         Nov.   
         Dec.   

2019 Jan. (p)  

2016   
2017   
2018   

2018 Q1   
         Q2   
         Q3   
         Q4   

2018 Aug.   
         Sep.   
         Oct.   
         Nov.   
         Dec.   

2019 Jan. (p)  

131.8
178.8
89.1

156.6
181.5
100.2

8.1
28.9
26.4
25.7

8.4
17.0
3.0
7.2
15.5

-6.5

6.8
8.6
4.0

5.3
4.9
4.6
4.0

4.3
4.6
4.2
3.8
4.0

2.5

22.3
29.1
36.1
12.7

11.6
18.0
1.6
0.3
10.8

2.0

10.4
11.2
5.6

8.1
7.1
6.8
5.6

6.5
6.8
6.0
5.4
5.6

4.4

295.1
285.8
280.8

274.0
277.9
268.0
280.8

268.8
268.0
271.1
275.6
280.8

271.7

-25.2
-3.1
-7.1

-10.8
1.1
-10.0
12.7

-3.5
-1.0
2.2
4.9
5.6

-8.8

-7.9
-1.1
-2.5

-7.7
-5.4
-6.8
-2.5

-7.2
-6.8
-4.7
-3.4
-2.5

-7.0

159.6
159.1
145.9

157.2
156.7
157.3
145.9

157.5
157.3
147.1
146.5
145.9

145.6

0.3
-0.6
-2.8

-2.0
-0.7
0.6
-0.7

0.9
-0.2
0.0
-0.2
-0.6

0.4

0.3
-0.4
-1.8

-0.5
-1.1
-0.6
-1.8

-0.6
-0.6
-1.0
-1.2
-1.8

-0.5

8.2
9.1
7.8

7.6
7.0
6.8
7.8

6.7
6.8
5.9
8.1
7.8

7.8

0.1
1.0
-1.3

-1.4
-0.7
-0.2
1.0

-0.7
0.1
-0.9
2.2
-0.3

0.0

1.4
12.5
-14.5

19.2
7.0
27.4
-14.5

13.8
27.4
5.7
0.5
-14.5

-21.6

6,055.5
6,305.6
6,645.6

6,376.3
6,462.2
6,538.7
6,645.6

6,515.4
6,538.7
6,587.5
6,610.7
6,645.6

3,402.3
3,698.9
4,039.2

3,787.0
3,870.0
3,945.5
4,039.2

3,921.6
3,945.5
3,984.3
4,005.1
4,039.2

6,680.5

4,068.5

Transactions

300.7
255.3
330.1

334.2
304.9
327.5

73.0
83.6
76.5
97.1

25.0
23.3
38.5
23.1
35.4

35.0

81.2
81.7
75.5
89.0

26.6
24.0
37.5
20.9
30.6

29.3

Growth rates

5.2
4.2
5.2

4.0
4.4
4.6
5.2

4.6
4.6
4.7
4.9
5.2

5.3

10.9
9.0
8.8

8.3
8.6
8.4
8.8

8.6
8.4
8.4
8.6
8.8

8.8

644.9
561.9
517.3

543.5
535.2
524.6
517.3

528.2
524.6
520.9
517.9
517.3

517.4

-46.5
-81.6
-45.0

-18.1
-8.8
-10.7
-7.5

-3.9
-3.7
-4.1
-2.9
-0.5

0.1

-6.7
-12.7
-8.0

-12.5
-10.8
-9.9
-8.0

-10.4
-9.9
-9.5
-9.0
-8.0

-7.1

2,006.3
2,044.1
2,088.0

2,044.2
2,055.9
2,067.6
2,088.0

2,063.8
2,067.6
2,081.1
2,086.6
2,088.0

2,093.0

13.9
33.4
47.2

9.0
11.2
11.6
15.4

2.3
3.8
5.0
5.2
5.2

5.1

0.7
1.7
2.3

1.7
1.7
1.9
2.3

1.9
1.9
2.0
2.1
2.3

2.3

2.1
0.7
1.2

1.6
1.1
1.1
1.2

1.8
1.1
1.1
1.2
1.2

1.7

-0.9
-1.3
0.5

0.9
-0.5
0.0
0.1

0.0
-0.8
0.1
0.0
0.0

0.5

-29.3
-65.5
65.1

-42.0
-53.9
-45.8
65.1

-10.7
-45.8
-45.2
-42.4
65.1

-6.2

972.0
994.3
1,002.7

983.2
1,010.3
982.2
1,002.7

974.8
982.2
992.6
1,001.0
1,002.7

976.3

24.2
54.9
-1.5

-9.4
19.9
-29.6
17.5

-16.1
6.6
6.3
8.8
2.5

-26.7

2.5
5.8
-0.2

4.2
5.8
1.0
-0.2

-1.8
1.0
3.0
0.3
-0.2

-1.6

199.5
204.0
200.3

210.6
220.0
211.8
200.3

214.4
211.8
208.3
208.3
200.3

203.7

-28.4
6.2
-4.5

6.8
9.1
-8.2
-12.2

-1.9
-2.6
-3.8
-0.4
-7.9

3.2

-12.5
3.1
-2.2

10.4
12.8
5.2
-2.2

8.1
5.2
2.8
1.6
-2.2

-1.4

383.8
411.1
431.2

415.1
425.6
436.8
431.2

434.2
436.8
440.2
443.8
431.2

440.4

19.1
26.9
18.2

3.6
9.9
11.0
-6.4

9.0
2.4
2.4
3.8
-12.6

9.1

5.2
7.0
4.4

5.3
5.7
4.8
4.4

4.6
4.8
5.1
6.9
4.4

5.9

Source: ECB.
1) Data refer to the changing composition of the euro area.
2) In accordance with the ESA 2010, in December 2014 holding companies of non-financial groups were reclassified from the non-financial corporations sector to the financial

corporations sector. These entities are included in MFI balance sheet statistics with financial corporations other than MFIs and insurance corporations and pension funds (ICPFs).

3) Including non-profit institutions serving households.
4) Refers to the general government sector excluding central government.

ECB Economic Bulletin, Issue 2 / 2019 - Statistics

S 19

 
 
   
   
 
 
 
 
5 Money and credit

5.3 Credit to euro area residents 1) 
(EUR billions and annual growth rates; seasonally adjusted; outstanding amounts and growth rates at end of period; transactions during period)

   Credit to general government

   Credit to other euro area residents

Total

Loans

Debt
securities

Total

   Loans

   Total

Adjusted
loans 2)

To non- To house- To financial To insurance
holds 4) corporations corporations
financial
other than and pension
corpor-
MFIs and
funds
ations 3)
ICPFs 3)

Debt
securities

Equity and
non-money
market fund
investment
fund shares

1

2

3

4

5
Outstanding amounts

6

7

8

9

10

11

12

2016   
2017   
2018   

2018 Q1   
         Q2   
         Q3   
         Q4   

2018 Aug.   
         Sep.   
         Oct.   
         Nov.   
         Dec.   

4,389.3
4,625.9
4,686.9

4,605.0
4,602.9
4,627.4
4,686.9

4,612.1
4,627.4
4,612.0
4,612.6
4,686.9

1,084.0
1,033.3
1,007.4

1,023.1
1,017.7
1,003.5
1,007.4

1,004.0
1,003.5
1,000.6
1,003.4
1,007.4

3,292.1
3,578.7
3,668.1

3,568.0
3,571.0
3,609.9
3,668.1

3,593.9
3,609.9
3,597.4
3,594.3
3,668.1

12,881.4 10,711.1
13,116.4 10,874.1
13,418.6 11,127.4

13,195.9 10,941.2
13,276.2 10,990.8
13,363.0 11,064.5
13,418.6 11,127.4

13,352.8 11,054.9
13,363.0 11,064.5
13,394.2 11,090.4
13,411.9 11,112.4
13,418.6 11,127.4

10,982.1
11,171.2
11,481.7

11,233.7
11,328.3
11,398.1
11,481.7

11,383.1
11,398.1
11,423.6
11,446.1
11,481.7

4,311.4
4,326.5
4,409.2

4,343.8
4,358.1
4,396.8
4,409.2

4,394.3
4,396.8
4,404.2
4,421.2
4,409.2

2019 Jan. (p)   4,685.7

1,006.7

3,667.6

13,453.2 11,157.5

11,499.9

4,409.3

2016   
2017   
2018   

2018 Q1   
         Q2   
         Q3   
         Q4   

2018 Aug.   
         Sep.   
         Oct.   
         Nov.   
         Dec.   

485.9
289.7
92.1

-31.0
34.7
48.0
40.5

14.4
6.7
-9.5
-7.9
57.9

2019 Jan. (p)  

-10.9

2016   
2017   
2018   

2018 Q1   
         Q2   
         Q3   
         Q4   

2018 Aug.   
         Sep.   
         Oct.   
         Nov.   
         Dec.   

2019 Jan. (p)  

12.4
6.6
2.0

3.9
4.0
3.1
2.0

3.3
3.1
2.7
2.1
2.0

2.4

-34.5
-43.3
-28.5

-10.1
-6.0
-16.2
3.8

-6.6
-3.7
-3.3
2.8
4.2

-0.8

-3.1
-4.0
-2.8

-4.0
-3.9
-4.4
-2.8

-4.5
-4.4
-4.3
-3.9
-2.8

-2.8

520.3
332.3
120.7

-20.8
40.3
64.5
36.7

21.1
10.7
-6.3
-11.7
54.7

-10.1

18.7
10.2
3.4

6.5
6.5
5.3
3.4

5.6
5.3
4.8
3.8
3.4

3.9

319.7
361.8
373.0

115.7
85.6
105.2
66.5

29.9
23.8
33.3
26.6
6.6

33.0

2.5
2.8
2.9

2.6
2.8
3.0
2.9

3.0
3.0
3.0
2.9
2.9

2.5

Transactions

259.9
314.8
373.4

94.4
103.7
87.1
88.2

30.5
28.6
20.7
32.1
35.5

20.8

Growth rates

2.4
2.9
3.4

3.0
3.5
3.4
3.4

3.4
3.4
3.3
3.2
3.4

3.0

82.5
82.8
122.4

41.3
17.1
48.6
15.4

13.6
9.3
5.6
22.6
-12.7

3.0

1.9
1.9
2.8

2.3
2.6
3.2
2.8

3.1
3.2
2.8
3.0
2.8

2.2

235.8
273.9
304.8

98.1
55.5
90.9
60.3

31.1
22.5
22.0
29.9
8.4

34.5

2.3
2.6
2.8

2.6
2.9
3.0
2.8

3.0
3.0
2.8
2.8
2.8

2.5

5,449.3
5,598.8
5,741.5

5,633.0
5,659.7
5,701.3
5,741.5

5,693.2
5,701.3
5,716.2
5,731.8
5,741.5

5,758.5

121.1
173.6
167.3

40.1
34.9
49.8
42.6

18.0
14.9
15.5
18.4
8.7

18.2

2.3
3.2
3.0

3.0
3.0
3.1
3.0

3.2
3.1
3.2
3.2
3.0

3.2

836.7
839.2
848.8

851.7
853.2
841.9
848.8

847.2
841.9
849.3
838.7
848.8

862.1

43.2
21.1
-3.1

13.6
-3.4
-12.1
-1.2

-0.2
-6.0
4.7
-11.0
5.1

13.6

5.5
2.5
-0.4

2.0
3.0
-0.4
-0.4

0.8
-0.4
-0.5
-1.8
-0.4

-1.6

113.5
109.6
127.9

112.8
119.8
124.4
127.9

120.2
124.4
120.8
120.7
127.9

127.7

-11.0
-3.5
18.1

3.2
6.9
4.5
3.4

-0.2
4.2
-3.7
0.0
7.2

-0.2

-8.9
-3.1
16.5

-0.3
6.9
11.7
16.5

4.7
11.7
7.4
5.2
16.5

13.0

1,387.4
1,442.4
1,520.1

1,467.4
1,496.6
1,513.8
1,520.1

1,515.3
1,513.8
1,524.7
1,516.8
1,520.1

1,523.5

80.3
64.3
89.5

27.5
29.7
18.6
13.7

4.3
-0.9
12.6
-6.4
7.6

0.3

6.1
4.6
6.2

3.9
4.8
5.9
6.2

6.1
5.9
7.2
6.6
6.2

5.3

782.9
799.8
771.0

787.4
788.7
784.8
771.0

782.6
784.8
779.1
782.8
771.0

772.2

3.6
23.6
-21.2

-9.9
0.4
-4.2
-7.5

-5.5
2.3
-1.3
3.2
-9.3

-1.8

0.5
3.0
-2.7

-0.1
-1.4
-1.1
-2.7

-1.8
-1.1
-1.5
-1.8
-2.7

-2.7

Source: ECB.
1) Data refer to the changing composition of the euro area.
2) Adjusted for loan sales and securitisation (resulting in derecognition from the MFI statistical balance sheet) as well as for positions arising from notional cash pooling services

provided by MFIs.

3) In accordance with the ESA 2010, in December 2014 holding companies of non-financial groups were reclassified from the non-financial corporations sector to the financial

corporations sector. These entities are included in MFI balance sheet statistics with financial corporations other than MFIs and insurance corporations and pension funds (ICPFs).

4) Including non-profit institutions serving households.

ECB Economic Bulletin, Issue 2 / 2019 - Statistics

S 20

 
 
   
   
   
   
 
 
 
 
5 Money and credit

5.4 MFI loans to euro area non-financial corporations and households 1) 
(EUR billions and annual growth rates; seasonally adjusted; outstanding amounts and growth rates at end of period; transactions during period)

   Non-financial corporations 2) 

   Total

Up to 1 year

Over 1 Over 5 years

   Total

Adjusted
loans 4)

and up to
5 years

   Households 3) 

Loans for
consumption

Adjusted
loans 4)

Loans for Other loans

house
purchase

1

2

3

4

5

6

7

8

9

10

Outstanding amounts

2016   
2017   
2018   

2018 Q1   
         Q2   
         Q3   
         Q4   

2018 Aug.   
         Sep.   
         Oct.   
         Nov.   
         Dec.   

2019 Jan. (p)  

2016   
2017   
2018   

2018 Q1   
         Q2   
         Q3   
         Q4   

2018 Aug.   
         Sep.   
         Oct.   
         Nov.   
         Dec.   

2019 Jan. (p)  

2016   
2017   
2018   

2018 Q1   
         Q2   
         Q3   
         Q4   

2018 Aug.   
         Sep.   
         Oct.   
         Nov.   
         Dec.   

2019 Jan. (p)  

4,311.4
4,326.5
4,409.2

4,343.8
4,358.1
4,396.8
4,409.2

4,394.3
4,396.8
4,404.2
4,421.2
4,409.2

4,409.3

82.5
82.8
122.4

41.3
17.1
48.6
15.4

13.6
9.3
5.6
22.6
-12.7

3.0

1.9
1.9
2.8

2.3
2.6
3.2
2.8

3.1
3.2
2.8
3.0
2.8

2.2

4,309.1
4,364.8
4,491.1

4,381.2
4,425.0
4,464.3
4,491.1

4,453.8
4,464.3
4,469.7
4,486.5
4,491.1

4,489.3

100.4
131.8
170.3

39.0
48.2
47.8
35.4

12.5
17.1
3.3
22.7
9.4

-0.8

2.4
3.1
3.9

3.3
4.1
4.3
3.9

4.1
4.3
3.9
4.0
3.9

3.3

1,013.3
987.7
995.7

997.8
986.0
1,000.1
995.7

1,001.3
1,000.1
985.0
989.2
995.7

980.1

-14.7
-0.3
19.0

17.6
-12.2
16.4
-2.9

3.8
-0.1
-16.9
5.7
8.3

-13.6

-1.4
0.0
1.9

2.6
1.4
3.3
1.9

3.1
3.3
0.7
1.3
1.9

-0.4

795.7
820.4
844.6

820.8
828.3
836.2
844.6

835.0
836.2
844.1
850.9
844.6

846.7

43.2
38.0
33.1

6.1
10.3
9.5
7.2

1.7
2.3
8.0
8.3
-9.1

2.3

5.7
4.8
4.1

4.6
5.5
4.5
4.1

5.3
4.5
5.0
5.2
4.1

3.5

2,502.4
2,518.4
2,568.9

2,525.2
2,543.8
2,560.5
2,568.9

2,558.0
2,560.5
2,575.0
2,581.0
2,568.9

2,582.5

Transactions

54.0
45.0
70.3

17.6
19.0
22.6
11.1

8.1
7.0
14.5
8.6
-11.9

14.2

Growth rates

2.2
1.8
2.8

1.5
2.2
2.8
2.8

2.5
2.8
3.0
3.0
2.8

2.8

5,449.3
5,598.8
5,741.5

5,633.0
5,659.7
5,701.3
5,741.5

5,693.2
5,701.3
5,716.2
5,731.8
5,741.5

5,758.5

121.1
173.6
167.3

40.1
34.9
49.8
42.6

18.0
14.9
15.5
18.4
8.7

18.2

2.3
3.2
3.0

3.0
3.0
3.1
3.0

3.2
3.1
3.2
3.2
3.0

3.2

5,728.7
5,865.5
6,023.4

5,904.5
5,940.5
5,978.6
6,023.4

5,972.2
5,978.6
5,996.5
6,010.7
6,023.4

6,037.0

113.8
165.5
188.8

45.5
44.3
47.7
51.3

17.2
14.0
19.1
18.2
13.9

15.1

2.0
2.9
3.2

2.9
3.0
3.1
3.2

3.1
3.1
3.2
3.3
3.2

3.2

615.9
654.0
683.7

663.3
669.8
678.3
683.7

677.3
678.3
681.7
685.6
683.7

687.5

24.1
45.1
40.1

11.3
10.5
10.3
8.1

4.0
1.9
3.7
4.2
0.2

4.1

4.1
7.3
6.2

7.2
7.2
6.9
6.2

7.2
6.9
7.1
6.7
6.2

6.1

4,084.1
4,217.0
4,353.9

4,243.8
4,273.2
4,311.6
4,353.9

4,300.9
4,311.6
4,324.0
4,336.4
4,353.9

4,367.5

105.4
134.3
136.5

27.7
29.0
40.4
39.4

14.0
13.2
12.1
14.1
13.1

14.1

2.7
3.3
3.2

3.0
3.1
3.2
3.2

3.2
3.2
3.3
3.3
3.2

3.5

749.3
727.9
703.9

725.9
716.6
711.4
703.9

715.0
711.4
710.4
709.8
703.9

703.5

-8.4
-5.8
-9.2

1.1
-4.6
-0.9
-4.9

0.0
-0.2
-0.3
0.0
-4.6

0.0

-1.1
-0.8
-1.3

-0.4
-1.1
-0.8
-1.3

-0.8
-0.8
-0.7
-0.8
-1.3

-1.3

Source: ECB.
1) Data refer to the changing composition of the euro area.
2) In accordance with the ESA 2010, in December 2014 holding companies of non-financial groups were reclassified from the non-financial corporations sector to the financial

corporations sector. These entities are included in MFI balance sheet statistics with financial corporations other than MFIs and insurance corporations and pension funds (ICPFs).

3) Including non-profit institutions serving households.
4) Adjusted for loan sales and securitisation (resulting in derecognition from the MFI statistical balance sheet) as well as for positions arising from notional cash pooling services

provided by MFIs.

ECB Economic Bulletin, Issue 2 / 2019 - Statistics

S 21

 
 
   
   
   
   
 
 
 
 
5 Money and credit

5.5 Counterparts to M3 other than credit to euro area residents 1) 
(EUR billions and annual growth rates; seasonally adjusted; outstanding amounts and growth rates at end of period; transactions during period)

   MFI liabilities

   MFI assets

Central
government
holdings 2)

   Longer-term financial liabilities vis-à-vis other euro area residents

Net external
assets

Total

Deposits

Deposits
with an redeemable
at notice
agreed
maturity
of over
3 months
of over
2 years

Debt

Capital
securities and reserves

with a
maturity
of over
2 years

   Other

   Total

Repos
with central
counter-
parties 3)

Reverse
repos to
central
counter-
parties 3)

1

2

3

4

5

6

7

8

9

10

Outstanding amounts

2016   
2017   
2018   

2018 Q1   
         Q2   
         Q3   
         Q4   

2018 Aug.   
         Sep.   
         Oct.   
         Nov.   
         Dec.   

2019 Jan. (p)  

2016   
2017   
2018   

2018 Q1   
         Q2   
         Q3   
         Q4   

2018 Aug.   
         Sep.   
         Oct.   
         Nov.   
         Dec.   

2019 Jan. (p)  

2016   
2017   
2018   

2018 Q1   
         Q2   
         Q3   
         Q4   

2018 Aug.   
         Sep.   
         Oct.   
         Nov.   
         Dec.   

2019 Jan. (p)  

307.7
343.4
378.7

340.8
330.4
403.3
378.7

391.6
403.3
398.1
390.3
378.7

377.2

22.0
39.2
39.0

-2.7
-10.4
76.3
-24.1

36.8
15.3
-5.5
-7.9
-10.8

-1.5

7.8
12.6
11.3

11.9
6.6
14.4
11.3

16.3
14.4
18.1
24.7
11.3

18.9

6,955.9
6,768.4
6,816.6

6,744.7
6,708.6
6,693.6
6,816.6

6,676.1
6,693.6
6,795.5
6,782.9
6,816.6

6,859.1

-122.9
-74.9
47.1

8.0
-10.0
29.8
19.3

-6.6
28.0
14.2
-6.6
11.6

15.4

-1.7
-1.1
0.7

-0.6
-0.9
0.0
0.7

-0.7
0.0
0.6
0.5
0.7

0.8

2,089.5
1,968.3
1,941.4

1,952.7
1,950.7
1,934.8
1,941.4

1,942.9
1,934.8
1,936.3
1,929.9
1,941.4

1,939.8

-71.3
-83.7
-38.6

-17.1
-4.8
-16.2
-0.4

-9.1
-8.4
0.0
-6.1
5.7

-5.8

-3.4
-4.0
-2.0

-4.1
-3.2
-2.8
-2.0

-2.7
-2.8
-1.8
-2.2
-2.0

-1.9

70.9
59.7
56.0

59.4
58.4
56.9
56.0

57.3
56.9
56.6
55.8
56.0

55.6

-8.6
-6.6
-4.9

-1.4
-1.1
-1.5
-0.9

-0.4
-0.5
-0.2
-0.9
0.2

-0.4

-10.9
-9.7
-8.1

-9.8
-10.8
-9.3
-8.1

-9.9
-9.3
-8.7
-9.1
-8.1

-7.7

2,145.9
2,014.1
2,096.0

2,014.7
2,025.6
2,048.5
2,096.0

2,016.1
2,048.5
2,104.4
2,098.7
2,096.0

2,112.5

Transactions

-118.7
-72.0
16.9

9.3
-15.0
19.2
3.4

-5.8
28.1
4.5
-2.3
1.3

16.5

Growth rates

-5.3
-3.4
0.8

-1.5
-2.5
0.0
0.8

-2.6
0.0
0.6
0.8
0.8

0.8

2,649.6
2,726.2
2,723.3

2,717.9
2,673.9
2,653.5
2,723.3

2,659.9
2,653.5
2,698.2
2,698.5
2,723.3

2,751.2

75.7
87.4
73.7

17.2
11.0
28.4
17.2

8.6
8.8
10.0
2.7
4.5

5.1

2.9
3.3
2.8

3.2
2.4
2.3
2.8

2.5
2.3
2.5
2.5
2.8

2.9

1,124.8
935.6
1,026.7

903.8
858.9
881.2
1,026.7

845.8
881.2
993.4
1,036.3
1,026.7

1,066.7

-278.3
-92.3
70.1

53.2
-62.2
38.8
40.2

-6.7
46.2
19.6
45.1
-24.5

24.6

- 
- 
- 

- 
- 
- 
- 

- 
- 
- 
- 
- 

- 

257.0
300.1
436.2

316.2
422.8
424.7
436.2

410.5
424.7
460.0
418.5
436.2

405.1

-90.2
-65.6
41.8

-55.0
88.6
-11.2
19.4

18.9
11.1
25.1
-37.0
31.2

-27.9

- 
- 
- 

- 
- 
- 
- 

- 
- 
- 
- 
- 

- 

205.9
143.5
187.0

135.9
174.1
177.3
187.0

181.4
177.3
167.1
196.1
187.0

199.2

12.8
-60.9
21.8

-7.6
16.4
3.2
9.7

-2.6
-4.1
-10.2
29.0
-9.1

12.2

6.3
-29.7
11.0

-25.6
-3.6
7.7
11.0

24.6
7.7
-9.9
-0.1
11.0

28.2

121.6
92.5
194.9

86.2
183.8
183.0
194.9

189.0
183.0
174.3
204.4
194.9

208.4

-12.0
-27.6
24.2

-6.3
19.4
-0.8
11.9

-3.5
-6.0
-8.7
30.0
-9.5

13.6

-9.0
-22.7
2.2

-22.2
-18.0
4.9
2.2

34.2
4.9
-22.0
-24.6
2.2

22.7

Source: ECB.
1) Data refer to the changing composition of the euro area.
2) Comprises central government holdings of deposits with the MFI sector and of securities issued by the MFI sector.
3) Not adjusted for seasonal effects.

ECB Economic Bulletin, Issue 2 / 2019 - Statistics

S 22

 
 
   
   
   
   
   
 
 
 
 
6 Fiscal developments

6.1 Deficit/surplus
(as a percentage of GDP; flows during one-year period)

   Deficit (-)/surplus (+)

Total

Central
government

State
government

Local
government

1

-2.5
-2.0
-1.6
-1.0

-1.0

-0.8
-0.5
-0.4

2

-2.1
-1.9
-1.7
-1.3

. 

. 
. 
. 

3

-0.2
-0.2
-0.1
0.0

. 

. 
. 
. 

4

0.0
0.1
0.2
0.2

. 

. 
. 
. 

Social
security
funds

5

-0.1
-0.1
0.0
0.1

. 

. 
. 
. 

2014   
2015   
2016   
2017   

2017 Q4   

2018 Q1   
         Q2   
         Q3   

Sources: ECB for annual data; Eurostat for quarterly data.

6.2 Revenue and expenditure
(as a percentage of GDP; flows during one-year period)

   Revenue

Total

   Current revenue

Capital
revenue

Total

   Expenditure

   Current expenditure

Direct
taxes

Indirect
taxes

Net social
contributions

Compen-
Intermediate
sation of consumption

Interest

Social
benefits

employees

Memo item:
Primary
deficit (-)/
surplus (+)

6

0.1
0.3
0.6
1.0

1.0

1.2
1.4
1.5

Capital
expenditure

2014   
2015   
2016   
2017   

2017 Q4   

2018 Q1   
         Q2   
         Q3   

1

2

3

46.7
46.2
46.0
46.1

46.1

46.1
46.1
46.2

46.2
45.7
45.5
45.7

45.7

45.7
45.7
45.8

12.5
12.5
12.6
12.8

12.8

12.9
12.9
12.9

4

13.1
13.0
12.9
12.9

12.9

12.9
12.9
12.9

Sources: ECB for annual data; Eurostat for quarterly data.

5

15.4
15.2
15.2
15.2

15.2

15.2
15.2
15.2

6

0.5
0.5
0.5
0.4

0.4

0.4
0.4
0.4

7

8

49.1
48.3
47.5
47.0

47.0

46.9
46.6
46.6

45.2
44.4
44.0
43.3

43.3

43.1
43.0
43.0

9

10.2
10.0
9.9
9.8

9.8

9.8
9.8
9.8

10

5.3
5.2
5.2
5.1

5.1

5.1
5.1
5.1

11

2.6
2.3
2.1
2.0

2.0

1.9
1.9
1.9

12

23.0
22.7
22.7
22.5

22.5

22.4
22.3
22.3

13

3.9
3.9
3.6
3.8

3.8

3.7
3.7
3.6

6.3 Government debt-to-GDP ratio
(as a percentage of GDP; outstanding amounts at end of period)

Total

   Financial instrument

   Holder

   Original maturity

   Residual maturity

   Currency

Debt   Resident creditors Non-resident
creditors

securities

Up to
1 year

Over
1 year

Up to
Over 1 Over
1 year and up to 5 years
5 years

Euro or
participating
currencies

Other
curren-
cies

Currency Loans

and
deposits

2

3

2.7
2.8
2.7
2.6

2.6

2.6
2.6
2.6

17.1
16.2
15.4
14.2

14.2

14.0
13.7
13.5

2014   
2015   
2016   
2017   

2017 Q4   

2018 Q1   
         Q2   
         Q3   

1

91.8
89.9
89.1
86.8

86.8

86.9
86.3
86.1

4

71.9
70.9
71.0
70.0

70.0

70.3
70.0
70.0

5

43.9
44.1
46.6
47.3

. 

. 
. 
. 

MFIs

6

25.8
27.3
30.5
31.9

. 

. 
. 
. 

7

47.9
45.7
42.5
39.5

. 

. 
. 
. 

8

9.8
9.1
8.8
8.0

. 

. 
. 
. 

9

82.0
80.8
80.3
78.8

. 

. 
. 
. 

10

18.8
17.5
17.1
15.9

. 

. 
. 
. 

11

12

31.8
31.2
29.9
28.8

41.1
41.2
42.1
42.2

. 

. 
. 
. 

. 

. 
. 
. 

13

89.7
87.8
87.0
85.0

. 

. 
. 
. 

14

2.1
2.1
2.1
1.8

. 

. 
. 
. 

Sources: ECB for annual data; Eurostat for quarterly data.

ECB Economic Bulletin, Issue 2 / 2019 - Statistics

S 23

 
   
 
 
   
   
   
   
 
 
   
   
   
   
   
   
 
6 Fiscal developments

6.4 Annual change in the government debt-to-GDP ratio and underlying factors 1) 
(as a percentage of GDP; flows during one-year period)

Change in
debt-to-
GDP ratio 2)

Primary
deficit (+)/
surplus (-)

   Deficit-debt adjustment

Total

   Transactions in main financial assets

Revaluation Other

Total Currency Loans

and
deposits

securities

Debt Equity and
investment
fund shares

effects
and other
changes in
volume

Interest- Memo item:
Borrowing
requirement

growth
differential

2014   
2015   
2016   
2017   

2017 Q4   

2018 Q1   
         Q2   
         Q3   

1

0.2
-1.9
-0.8
-2.2

-2.2

-2.4
-2.9
-2.1

2

-0.1
-0.3
-0.6
-1.0

-1.0

-1.2
-1.4
-1.5

3

4

-0.2
-0.8
0.1
-0.2

-0.2

-0.1
-0.2
0.5

-0.4
-0.5
0.2
0.3

0.4

0.5
0.3
0.8

5

0.2
0.2
0.3
0.5

0.5

0.5
0.2
0.6

6

-0.4
-0.3
-0.1
0.0

0.0

0.0
-0.1
0.0

7

-0.3
-0.3
0.0
-0.2

-0.2

-0.1
-0.1
0.0

8

0.0
-0.1
0.1
0.1

0.1

0.1
0.2
0.2

9

10

0.1
0.0
0.0
-0.1

-0.1

-0.1
-0.1
-0.1

0.2
-0.4
-0.1
-0.3

-0.4

-0.4
-0.3
-0.2

11

0.5
-0.8
-0.3
-1.0

-1.0

-1.1
-1.3
-1.1

12

2.3
1.2
1.6
0.9

0.9

0.8
0.5
1.0

Sources: ECB for annual data; Eurostat for quarterly data.
1) Intergovernmental lending in the context of the financial crisis is consolidated except in quarterly data on the deficit-debt adjustment.
2) Calculated as the difference between the government debt-to-GDP ratios at the end of the reference period and a year earlier. 

6.5 Government debt securities 1) 
(debt service as a percentage of GDP; flows during debt service period; average nominal yields in percentages per annum)

   Debt service due within 1 year 2) 

Total

   Principal

   Interest

Average
residual
maturity
in years 3)

Maturities
of up to 3
months

Maturities
of up to 3
months

   Average nominal yields 4) 

   Outstanding amounts

   Transactions

Total

Floating

Zero
rate coupon

   Fixed rate

Issuance Redemption

1

2

3

4

2016   
2017   
2018   

2017 Q4   

2018 Q1   
         Q2   
         Q3   

2018 Aug.   
         Sep.   
         Oct.   
         Nov.   
         Dec.   

2019 Jan.   

14.1
12.9
13.0

12.9

12.9
12.8
13.1

12.8
13.1
13.3
13.4
13.0

13.3

12.4
11.2
11.4

11.2

11.3
11.2
11.5

11.2
11.5
11.8
11.9
11.4

11.7

4.6
4.2
3.9

4.2

4.2
3.6
3.8

3.8
3.8
3.6
3.7
3.9

4.1

1.7
1.7
1.5

1.7

1.6
1.6
1.6

1.6
1.6
1.6
1.6
1.5

1.5

5

0.4
0.4
0.4

0.4

0.4
0.4
0.4

0.4
0.4
0.4
0.4
0.4

0.4

6

7

8

9

10

6.9
7.1
7.3

7.1

7.2
7.3
7.3

7.2
7.3
7.3
7.3
7.3

7.3

2.6
2.4
2.3

2.4

2.4
2.4
2.3

2.3
2.3
2.3
2.3
2.3

2.3

1.2
1.1
1.1

1.1

1.1
1.1
1.1

1.1
1.1
1.1
1.1
1.1

1.1

-0.1
-0.2
-0.1

-0.2

-0.2
-0.2
-0.1

-0.2
-0.1
-0.1
-0.1
-0.1

-0.1

3.0
2.8
2.7

2.8

2.8
2.8
2.7

2.7
2.7
2.7
2.7
2.7

2.7

Source: ECB.
1) At face value and not consolidated within the general government sector.
2) Excludes future payments on debt securities not yet outstanding and early redemptions.
3) Residual maturity at the end of the period.
4) Outstanding amounts at the end of the period; transactions as 12-month average.

Maturities
of up to 1
year

11

2.9
2.3
2.5

2.3

2.5
2.5
2.6

2.5
2.6
2.5
2.5
2.5

2.5

12

0.2
0.3
0.4

0.3

0.4
0.4
0.4

0.4
0.4
0.4
0.5
0.4

0.4

13

1.2
1.1
0.9

1.1

1.1
0.9
0.9

1.0
0.9
1.0
1.0
0.9

0.9

ECB Economic Bulletin, Issue 2 / 2019 - Statistics

S 24

 
   
   
 
 
   
   
   
   
   
   
   
 
 
6 Fiscal developments

6.6 Fiscal developments in euro area countries
(as a percentage of GDP; flows during one-year period and outstanding amounts at end of period)

Belgium

Germany

Estonia

Ireland

Greece

Spain

France

Italy

Cyprus

1

-3.1
-2.5
-2.4
-0.9

-0.9

-0.9
-0.3
-0.1

107.6
106.5
106.1
103.4

103.4

106.4
105.9
105.4

2

0.6
0.8
0.9
1.0

1.0

1.3
1.9
1.9

74.5
70.8
67.9
63.9

63.9

62.7
61.5
61.0

3

4

5

Government deficit (-)/surplus (+)

0.7
0.1
-0.3
-0.4

-0.4

-0.6
-0.2
0.0

10.5
9.9
9.2
8.7

8.7

8.5
8.3
8.0

-3.6
-1.9
-0.5
-0.2

-0.2

-0.3
-0.3
-0.1

Government debt

104.1
76.8
73.4
68.4

68.4

69.3
69.2
68.8

-3.6
-5.6
0.5
0.8

0.8

1.1
0.9
0.8

178.9
175.9
178.5
176.1

176.1

177.9
177.4
182.2

6

-6.0
-5.3
-4.5
-3.1

-3.1

-2.9
-2.7
-2.7

100.4
99.3
99.0
98.1

98.1

98.7
98.1
98.3

7

-3.9
-3.6
-3.5
-2.7

-2.7

-2.7
-2.8
-2.7

94.9
95.6
98.2
98.5

98.5

99.4
99.1
99.5

8

9

-3.0
-2.6
-2.5
-2.4

-2.4

-2.2
-1.9
-1.8

131.8
131.6
131.4
131.2

131.2

132.8
133.1
133.0

-9.0
-1.3
0.3
1.8

1.8

2.5
3.0
-4.0

108.0
108.0
105.5
96.1

96.1

93.4
104.0
110.9

Latvia

Lithuania Luxembourg

Malta Netherlands

Austria

Portugal

Slovenia

Slovakia

Finland

10

11

-1.5
-1.4
0.1
-0.6

-0.6

0.0
0.3
0.0

40.9
36.8
40.3
40.0

40.0

35.5
36.9
37.1

-0.6
-0.3
0.3
0.5

0.5

0.4
0.7
0.6

40.5
42.6
39.9
39.4

39.4

36.0
35.0
35.0

12

1.3
1.3
1.6
1.4

1.4

1.4
1.5
1.9

22.7
22.2
20.7
23.0

23.0

22.2
22.0
21.7

13

14

15

16

17

18

19

Government deficit (-)/surplus (+)

-1.7
-1.0
0.9
3.5

3.5

3.1
3.9
3.6

63.7
58.6
56.3
50.9

50.2

49.8
49.0
45.9

-2.2
-2.0
0.0
1.2

1.2

1.6
1.9
2.1

Government debt

67.9
64.6
61.9
57.0

57.0

55.1
54.0
52.9

-2.7
-1.0
-1.6
-0.8

-0.8

-0.6
0.2
0.1

84.0
84.8
83.0
78.3

78.3

77.2
76.5
75.6

-7.2
-4.4
-2.0
-3.0

-3.0

-0.7
-1.0
0.0

130.6
128.8
129.2
124.8

124.8

125.4
125.0
125.0

-5.5
-2.8
-1.9
0.1

0.1

0.5
0.6
0.7

80.4
82.6
78.7
74.1

74.1

75.5
72.7
71.0

-2.7
-2.6
-2.2
-0.8

-0.8

-0.7
-0.7
-0.7

53.5
52.2
51.8
50.9

50.9

50.9
51.9
51.5

-3.2
-2.8
-1.7
-0.7

-0.7

-0.7
-0.9
-0.8

60.2
63.6
63.0
61.3

61.3

59.9
59.6
58.8

2014   
2015   
2016   
2017   

2017 Q4   

2018 Q1   
         Q2   
         Q3   

2014   
2015   
2016   
2017   

2017 Q4   

2018 Q1   
         Q2   
         Q3   

2014   
2015   
2016   
2017   

2017 Q4   

2018 Q1   
         Q2   
         Q3   

2014   
2015   
2016   
2017   

2017 Q4   

2018 Q1   
         Q2   
         Q3   

Source: Eurostat.

ECB Economic Bulletin, Issue 2 / 2019 - Statistics

S 25

 
 
 
 
 
 
 
 
 
 
 
 
© European Central Bank, 2019 

Postal address 
Telephone 
Website 

60640 Frankfurt am Main, Germany 
+49 69 1344 0 
www.ecb.europa.eu 

All rights reserved. Reproduction for educational and non-commercial purposes is permitted provided that the source is acknowledged. 

This Bulletin was produced under the responsibility of the Executive Board of the ECB. Translations are prepared and published by the 
national central banks.   

The cut-off date for the statistics included in this issue was 6 March 2019. 

For specific terminology please refer to the ECB glossary (available in English only). 

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ISSN 2363-3417, QB-BP-19-002-EN-N 
ISSN 2363-3417, doi:10.2866/662337, QB-BP-19-002-EN-Q