special report - research.natixis.com

SPECIAL REPORT
ECONOMIC RESEARCH
August 2014 - N°113
Sylvain Broyer, Johannes Gareis
Will the ECB’s TLTROs feed through to the real economy?
Even if there is decent demand from banks, we do not believe that TLTROs will boost bank lending and in
turn have a huge impact on the real economy. In an optimistic scenario TLTROs would boost lending volumes
2% above the counterfactual. In this Special Report we provide evidence that the weak lending activity in the
euro area is mainly driven by weak economic and tight credit conditions in vulnerable euro area countries
due to high credit risks of borrowers. TLTROs, however, cannot eliminate these risks. Thus, they are unlikely
to eliminate fully the divergence in bank lending rates among EMU countries. Overall, our findings highlight
that the European Central Bank alone cannot solve the underlying weaknesses in the euro area and therefore
assign a greater role to fiscal policy (stimulus package, European bad bank) or even strengthen the case for
helicopter money.
TLTROs – The ECB’s new big bazooka
The main features of the upcoming TLTROs are well known:
in the first two allowances (18 September and 11 December
2014), banks will be allowed to borrow up to 7% of the total
amount of their non-financial private sector loans (“stock”),
excluding loans to households for house purchase,
outstanding on 30 April 2014 (chart 1). Loans to households
are excluded from this measure to avoid imbalances on the
housing market.
95
77 75
54
29
Malta
Latvia
Estonia
Slovenia
Cyprus
Slovakia
Luxembourg
Ireland
Finland
Greece
Portugal
Austria
10 10 8 8 7
4 2 1 1 1 1 0
Belgium
Netherlands
Italy
Spain
15
France
As regards the potential take-up of banks, we expect that
TLTROs will possibly attract decent demand, although we
believe that the EUR 1trn volume mentioned by Draghi in
early June should not be within reach (see also Natixis Flash
No. 542, July 2014). However, we do not think that the
TLTROs will have a huge impact on banks’ lending rates,
especially in the euro area periphery, which appear to be
driven by high credit risks of borrowers. TLTROs, however,
cannot eliminate this risk factor. Accordingly, we expect that
TLTROs are unlikely to boost lending volumes with respect to
the counterfactual.
100
90
80
70
60
50
40
30
20
10
0
Germany
The success of the ECB’s targeted long-term refinancing
operations (TLTROs) will depend on banks’ TLTROs take-up,
the level of bank interest rates on loans to the real economy
and on the amount of bank lending to the real economy and
thus inflation and growth.
Chart 1
Intial TLTRO allowance by country (EUR bn)
Sources : ECB, Natixis
From March 2015 to June 2016, banks will be able to borrow
each quarter up to three times the cumulative amount of their
net lending to the real economy (“flow”), excluding loans to
households for house purchase, in excess of a specific
benchmark. The benchmark depends on whether a bank was
positive or negative net lender in the 12-month period to 30
April 2014 (chart 2).
SP EC I AL R EP OR T
macroeconomic scenario of a gradual euro area recovery
(see chart 13 below) and with leading indicators, such as the
ECB’s Bank Lending Survey (chart 4A and chart 4B).
Chart 2
Eligible net lending from May 2013 to April 2014 by
country (EUR bn)
3 2
5
0
-9
-2
1
Chart 4A
ECB's Bank Lending Survey and credit flows, nonfinancial corporations
0
-3 0
0 -2
-6 -8 -8
0
Bank loans to non-financial corprotions (seas. adj.
monthly flow, EUR bn)
-44
ECB BLS: expected demand for loans (3 quarter lead,
rhs)
Malta
Latvia
Estonia
Slovenia
Cyprus
Slovakia
Luxembourg
Ireland
Finland
Greece
Portugal
Austria
Belgium
Netherlands
Italy
Spain
France
-80
Germany
10
0
-10
-20
-30
-40
-50
-60
-70
-80
-90
80
40
60
30
40
20
20
10
0
0
Sources : ECB, Natixis
-20
For those banks that had increased lending up until April
2014 the benchmark monthly net lending is set at zero. For
those banks that had been deleveraging in the 12-month
period until April 2014, the benchmark is split: there is one
benchmark until April 2015, which is the average monthly net
lending to the real economy in the 12-month period to April
2014 extrapolated for 12 months. Then, from May 2015 to
April 2016, the benchmark is fixed at zero (chart 3).
-10
-40
-20
Sources : ECB, Natixis
-60
-30
04
05
06
07
08
09
10
11
12
13
14
15
Chart 4B
ECB's Bank Lending Survey and credit flows,
consumer credit
Bank loans to households (seas. adj. monthly flow,
EUR bn)
ECB BLS: expected demand for loans (3 quarter
lead, rhs)
Chart 3
Euro area: Eligible net lending and benchmark
caclulated on the basis of net lending from May
2013 to April 2014 (index, April 2014=100)
106
6
104
30
4
106
Outstanding amount of eligible loans
Benchmark for negative net lenders
Benchmark for positive net lenders
40
104
20
2
10
0
0
-10
-2
102
102
-20
-4
-30
Sources : ECB, Natixis
100
100
98
98
Sources : ECB, Natixis
96
01.13
96
07.13
01.14
07.14
01.15
07.15
01.16
The TLTROs are attractive for banks, because they can
easily lock in very low interest rates (refi rate plus 10bp) for a
prolonged period of time (until at max September 2018). At
the worst, banks that did not meet the given lending targets
have to repay those funds, without a penalty, but no sooner
than September 2016. In addition, there are no specific
penalties for the use of the TLTROs for government bond
carry trades.
In particular, we believe that the lending benchmarks
attached to the TLTROs are rather generous, for both
positive and negative net lenders. While the former only have
to continue expand net lending to obtain TLTROs, the latter
can continue deleveraging until April 2015, although at a
slower rate than in the 12-month period before April 2014.
Indeed, the ECB’s lending statistics available for May and
June already indicate that the euro area’s credit cycle is
turning to positive territory, with the non-financial private
sector loans falling by -1.7% in June, the slowest rate of
decline since June last year. In general, a slower rate of
contraction in private sector credit is consistent with our
-6
-40
03
04
05
06
07
08
09
10
11
12
13
14
Finally, in our opinion, there is no stigma attached to using
the TLTROs, given the purpose of the TLTROs to support
lending to the real economy. In fact, if the ECB decides to
publish a list of banks that use TLTROs, analogously to the
Bank of England under its FLS programme, banks that are
absent from the list could be exposed to criticism (see Natixis
Special Report No. 86, June 2014).
Can the ECB’s TLTROs boost bank lending?
The main problem in seeking to understand whether the
ECB’s TLTRO’s will eventually feed through to the real
economy lies in the difficulty of isolating supply and demandside factors of the loan developments in the euro area.
For example, credit demand naturally tends to decline in a
period of weak economic growth as investments become
increasingly unattractive. At the same time, banks cut credit
supply in a recession as the balance sheets of borrowers
weaken and demand a compensation for the elevated risk by
imposing stricter credit standards on borrowers and by
increasing lending rates. As a result, aggregate bank lending
declines. However, besides these real factors which
determine the supply of credit, a prominent role is also played
by bank-related factors such as funding availability and bank
balance sheet constraints. That is, weak bank lending can
N° 113 I 2
SP EC I AL R EP OR T
also be the result of constraints imposed by banks due to a
rise in banks borrowing costs and capital shortage, such that
borrowers’ investment decision exclusively relies on the
availability of bank credit if they do not have access to capital
markets. Thus, such additional credit supply restrictions have
the potential to further weaken economic growth, which could
result in a vicious circle of weaker economic momentum and
tighter credit supply conditions.
The ECB’s TLTRO should be seen within this context. In
particular, the aim of the ECB’s TLTRO’s is to help prevent
limited availability of bank loans due to bank-related factors
from slowing down the economic recovery in the euro area.
Indeed, a main consequence of the recent crisis and financial
fragmentation has been the breakdown in the monetary
transmission of monetary policy in vulnerable euro area
countries. That is, despite ultra-low policy rates, bank lending
rates have been remaining stubbornly high in the periphery
(chart 5) and credit conditions have been tightened by more
in vulnerable countries than in the core countries (chart 6).
This, together with adverse demand effects, largely explain
the relatively sharp decline in credit in these countries (chart
7).
Chart 5
Bank lending rates for non-financial corporations
across the euro area
Refi rate
3-month EURIBOR
Core (DE, FR, NL)
Periphery (IT,ES,PT)
Euro area
7
7
6
6
5
5
4
4
3
3
2
2
1
1
Sources : ECB, Natixis
0
0
03
1200
04
05
06
07
08
09
10
11
12
13
14
Chart 6
Cumulative change in credit standards on loans to
non-financial corporations
(2008:Q4-2014Q2)
1000
800
600
400
200
0
DE
FR
NL
IT
ES
PT
Sources : ECB, Natixis
Chart 7
Growth of loans to non-financial corporations,
adjusted for sales and securitisation
(YoY as %)
Core (DE, FR, NL)
Periphery (IT,ES,PT)
Euro area
25
25
20
20
15
15
10
10
5
5
0
0
-5
-5
-10
-10
Sources : ECB, Natixis
-15
-15
04
05
06
07
08
09
10
11
12
13
14
To gain further insights into the drivers of tighter credit
conditions across the euro area, especially in terms of bank
lending rates for loans to non-financial corporations, we use
an extended version of an otherwise standard pass-through
model for selected individual country level bank lending rates.
Specifically, changes in bank lending rates, which are
measured by the ECB’s composite cost of borrowing
indicator, are regressed on own lags, simultaneous and
lagged changes of a reference market rate (3-month
EURIBOR) and on measures of the credit channel. Hereto,
we use sovereign bond yields and the unemployment rate as
factors of risk, while the former measures the aggregate
credit risks at the country level, which is closely related to
banks funding costs, while the latter proxies demand-side risk
indicators, i.e. the risk that borrowers will default. This
approach makes it possible to differentiate between the
various factors (market reference rates and risk factors
related to banks and borrowers) affecting bank lending rates
to non-financial corporations (see appendix for modelling
details).
Chart 8 shows the actual change in bank lending rates to
non-financial corporations between December 2010 and
December 2013 in the selected euro area economies and the
estimated contribution of market reference rates, and
different risk factors. As is evident, our econometric analyses
suggests that especially the deteriorating macroeconomic
environment, as measured by the unemployment rate, has
put a marked upward pressure on bank lending rates for nonfinancial corporations in vulnerable countries such as Italy,
Spain and Portugal since the onset of the euro crisis in 2012.
This means that the significant downward adjustments in the
market reference rate since then has not translated into an
overall reduction in bank lending rates in these countries,
reflecting a breakdown in the monetary policy transmission
channel. Contrary to this, we find that the bank lending rates
in the core countries such as Germany, France and the
Netherlands can be largely explained by the developments in
the market reference rate, while the risk factors related to
banks and borrowers play a secondary role in the fluctuations
of bank lending rates.
N° 113 I 3
SP EC I AL R EP OR T
Chart 8
Breakdown of changes in lending rates to nonfinancial corporations by explanatory factors (%)
(Dec 2010 to Dec 2013)
Chart 10
Breakdown of changes in lending rates to nonfinancial corporations by explanatory factors (%)
(Dec 2010 to June 2012)
2.0
2.0
2.0
2.0
1.5
1.5
1.5
1.5
1.0
1.0
1.0
1.0
0.5
0.5
0.5
0.5
0.0
0.0
0.0
0.0
-0.5
-0.5
-0.5
-0.5
-1.0
-1.0
-1.0
-1.0
-1.5
-1.5
-1.5
-2.0
-2.0
Sources : Natixis
-2.0
DE
FR
NL
IT
Residual
Sovereign bond yield
Change in lending rate (rhs)
ES
PT
DE
Unemployment rate
3-month EURIBOR
Chart 9
Spreads of 10-year sovereign bond yields with
respect to Germany
(percentage points)
1400
France
Italy
Spain
Portugal
Netherlands
1200
1000
800
1200
400
400
200
200
0
0
10
ES
-2.0
PT
Unemployment rate
3-month EURIBOR
Overall, our model estimates highlight the importance of both
supply-side and demand-side risk factors as potential drivers
of banks’ lending rates for loans to non-financial corporations
in vulnerable euro area countries such as Italy, Spain and
Portugal. We furthermore can present evidence that the
effects of these factors have varied over time. According to
our results, demand-side factors appear to be the most
important factors for lending rates in vulnerable euro area
countries since late 2012. These results are consistent with
the ECB’s Bank Lending Survey, which shows that risk
perceptions have remained the main factor in contributing to
tighter credit conditions for non-financial corporations in the
euro area in the recent past (chart 11).
Chart 11
Euro area: Factors contributing to the net tightening
of credit standards on loans to non-financial
corporations
800
600
09
IT
1000
600
08
NL
FR
Residual
Sovereign bond yield
Change in lending rate (rhs)
At the same time, our model estimates are also consistent
with the conventional wisdom that greater sovereign risks,
especially with the intensification of the sovereign debt crisis
in 2010 and the subsequent massive increase in sovereign
bond yields (chart 9) have contributed to the difficult credit
conditions in the euro area periphery.
1400
-1.5
Sources : Natixis
11
12
13
14
Sources : Datastream, Natixis
To this end, we illustrate in chart 10 the actual change in
bank lending rates between December 2010 and the peak of
the euro area debt crisis in mid-2012. As is evident from the
chart, tensions in the sovereign debt market indeed can
explain the bulk of the increase in bank lending rates in the
vulnerable euro area countries, while bank lending rates in
Germany, France and the Netherlands closely followed the
movements in the market reference rate from December
2010 to June 2012.
Risk perceptions
Cost of funds and balance sheet constraints
Competition
70
70
60
60
50
50
40
40
30
30
20
20
10
10
0
0
-10
-10
Sources : ECB
-20
-20
08
09
10
11
12
13
14
The empirical analysis suggests that the effect of TLTROs on
bank lending rates should be limited. Having said that, we
think that the ECB’s TLTROs are a welcome step and should
contribute to a further decrease in bank funding costs and we
expect that, to the extent that banks use TLTROs to fund
purchases of other assets, such as government bonds, the
decline in government bond yields should gradually feed
through to bank funding costs in the vulnerable countries.
However, TLTROs are unlikely to eliminate fully the
divergence in bank lending rates observed since the outbreak
of the euro area debt crisis in 2010, as credit risks of
borrowers are likely to fall only gradually in the euro area
periphery, in line with the persistently weak domestic
conditions (chart 12).
N° 113 I 4
SP EC I AL R EP OR T
Chart 13
Euro area: Eligible net lending to non-financial
corporations and benchmark caculated on the basis
of net lending to non-financial corporations from
May 2013 to April 2014 (index, April 2014 = 100)
Chart 12
Unemplyoment rate (%)
Germany
France
Italy
Netherlands
Portugal
Spain (rhs)
28
18
25
15
23
13
20
10
18
15
8
13
5
10
3
8
08
09
10
11
12
13
14
Sources : Eurostat
Here, we use a credit demand model to illustrate that
TLTROs are unlikely to boost lending volumes relative to the
counterfactual. Based on the standard determinants of the
demand function for loans, loans to non-financial corporations
are estimated as a function of real GDP and the cost of loans,
which is measured by the composite cost of borrowing
indicator for non-financial corporations (see appendix for
modelling details):
+
−
lt = f ( yt , lrt ).
Outstanding amount of eligible loans
Counterfactual (no TLTROs)
Benchmark
TLTROs and gradual decline in lending rate
TLTROs and immediate drop in lending rate
104
103
102
101
100
99
98
97
Sources : ECB, Natixis
96
01/13 01/13 01/13 01/14 01/14 01/15 01/15 01/15
104
103
102
101
100
99
98
97
96
As is apparent from the chart, TLTROs are unlikely to boost
lending volumes significantly above the counterfactual and
our results suggest that the impact of a decline in the bank
lending rate on the loan development is generally limited.
Even in the most optimistic scenario, in which the spread
between the bank lending rate and the 3-month EURIBOR
drops immediately to its pre-crisis average level of 150 bp,
the outstanding amount of loans to non-financial corporations
would not be dramatically higher with respect to the
counterfactual. This finding suggests that weak economic
growth plays a prominent role in the weak lending activity in
the euro area.
In doing so, we make the standard assumption that the credit
market is predominately demand driven and that the causality
runs from real GDP and interest rates to loans. Clearly, this
assumption can be challenged, as the mere coincidence of
the credit cycle and economic activity may also be explained
from a supply side perspective (see discussion above).
Nevertheless, this approach still allows getting an idea about
the volume of new lending in a scenario with TLTROs beyond
the trajectory expected so far.
Chart 13 shows the evolution of loans to non-financial
corporations based on our own forecasts for real GDP,
inflation and interest rates and take the potential effect of
TLTROs on lending activity into account by assuming that the
spread between the lending and the market reference rate (3month EURIBOR) declines only gradually and reaches its
pre-crisis average level in Q2 2016, which is 150 bp. The
counterfactual (without TLTROs) assumes that the interest
rate spread remains unchanged at 260 bp over the
forecasting horizon. To complete the picture, we include a
scenario, in which the interest rate falls immediately to its precrisis average level.
N° 113 I 5
SP EC I AL R EP OR T
Appendix
Modelling the interest rate pass-through in the euro area
To estimate the interest rate pass-through across euro area
countries, we extend the standard pass-through model to the
extend to accommodate the impact of other factors than the
reference market interest rate that affect bank lending rates.
In particular, to incorporate the tensions on the sovereign
bond market, which stand for a factor of supply-side risk, we
add sovereign bond yields to the standard model. Moreover,
we include the unemployment rate to the model to replicate
demand-side risk factors (credit risks of borrowers). The final
model is described by the following error correction
framework:
N
J
K
n =0
j =1
k =1
∆lrt = a 0 + ∑ λn ∆rt − n + ∑ δ j ∆lrt − j + ∑ µ k ∆st − k
S
+ ∑ φ s ∆u t − s + α (lrt −1 − βrt −1 − β1 st −1 − β 2 u t −1 ) + ε t ,
yields and the unemployment rate have, in general, an effect
on bank lending rates, which is in particular relevant for the
vulnerable countries in the euro area such as Italy, Spain,
and Portugal. Most notably, however, we do not find that
sovereign bond yields and the unemployment rate plays a
role in bank lending rates in France.
Modelling loans to non-financial corporations in the euro
area
Based on the classical assumptions that the credit market is
predominately demand driven, we model loans as a function
of GDP and the lending rate. The model is estimated in the
following error correction framework:
N
(
where
term equilibrium, while the coefficient β captures the longrun elasticity of the bank lending rate to the market reference
rate. The coefficients as related to the lags of the first
difference of the variables measures the short-run pass
through. The model is estimated with monthly data over the
period from January 2003 to June 2014. The selection of the
lag length in the model is performed with the basic diagnosis
criteria. Table A1 displays the results.
n =0
+ α log l
s =1
where lr denotes the bank lending rate (composite interest
rate for loans to non-financial corporations), r is the
reference market rate (3-month EURIBOR), s stands for the
sovereign bond yield and u is the unemployment rate. The
coefficient α represent the speed of adjustment to the long-
J
K
j =1
k =1
log(ltr ) = a 0 + ∑ δ j log ltr− n + ∑ δ j log y t − j + ∑ µ k lrt r− k
ltr
r
t −1
− β log y t −1 − β1lr
r
t −1
)+ ε ,
t
stands for the outstanding amount of loans to non-
financial corporations (adjusted for sales and securitization)
in real terms,
yt
is real GDP and
lrt r−1
is the real lending
rate (composite cost interest rate for loans to non-financial
corporations adjusted for inflation). Prices are measured by
HICP index. All series except the interest rate are expressed
in logs and are seasonally adjusted. We use quarterly data
for the euro area over the period starting in the first quarter of
2003 to the second quarter of 2014. The lag length is 3.
Table A2 displays results.
Table A2: Loans to non-financial
corporations for the euro area
EA
Table A1: Interest rate pass-trough in the euro area
DE
FR
IT
ES
NL
PT
GDP
3.8**
Interest rate
-0.12*
ECM
3M EURIBOR 0.58*** 0.60*** 0.77*** 1.22*** 0.74*** 0.63***
Sovereign
bond yield 0.30***
0.15
1.15*** 0.18**
0.00 0.25***
Unem ploym ent rate
0.03**
0.23
0.25*** 0.16*** 0.07*** 0.14***
ECM
-0.30*** -0.23*** -0.07*** -0.15*** -0.40*** -0.17**
Short-term
passthrough
0.70*** 0.40*** 0.55*** 0.74*** 0.58***
R-squared
78%
55%
72%
68%
72%
0.11
48%
Notes: Significance at the 1, 5, and 10% levels: ***,**,*; For France we excluded th
simultaneous change of the market reference rate in the regression equation
Source: Natixis
Overall, we find that the long-term pass through from Euribor
to the corporate lending rate is in the range from around 0.5
to 0.8 (excluding Spain’s overshooting), which points to a less
than complete pass-through of market interest rates to
lending rates. In addition, we find that bank lending rates are
relatively sticky. The immediate adjustment coefficients to
changes in market rates fluctuate around 0.4 to 0.8. In terms
of the impact of sovereign bond yields and the unemployment
rate on bank lending rates, we find that both sovereign bond
R-squared
-0.02***
95%
Notes: Significance at the 1,5, and 10%
levels: ***,**,*;
Source: Natixis
We find that the coefficient of the error correction term in the
model equation is statistically different from zero, which
confirms the existence of a long-run relationship between real
loans, real GDP and real interest rates. The magnitude of the
coefficient is rather small, indicating that a deviation of loans
from the long-run equilibrium is corrected only gradually. The
signs of the coefficients for real GDP and real interest rates
allows to interpret the long-run relation between real loans,
real GDP and real interest rates as a long-run demand
equation for loans. We find a relatively high GDP elasticity of
around 4. As for the real interest rate, our estimated
coefficient of -0.12 is rather low. This relatively low interest
rate elasticity may be due to the short data span and may
reflect the balance sheet adjustment in the banking sector
towards the end of the observation period.
N° 113 I 6
SP EC I AL R EP OR T
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