-
Journal of International Money and Finance
23 (2004) 461492
www.elsevier.com/locate/econbase
ding author. T .ress: gh.sander CorresponE-mail add0261-5606/$ -
see front matt
doi:10.1016/j.jimonn.2004.0el.: +49-221-82753419; fax:
+49-221-82753131
@t-online.de (H. Sander).er# 2004 Elsevier Ltd. All rights
reserved.2.001Convergence in euro-zone retail banking?What interest
rate pass-through tells us aboutmonetary policy transmission,
competition
and integration
Harald Sander a,b,, Stefanie Kleimeier b,ca Faculty of Economics
and Business Administration, Claudiusstr.1, University of Applied
Sciences
Cologne, 50678 Koln, Germanyb METEOR Fellow, Tongersestraat 53,
Maastricht University, 6211 LM Maastricht, The Netherlands
c Limburg Institute of Financial Economics, Tongersestraat 53,
Maastricht University,
6211 LM Maastricht, The Netherlands
Abstract
This study aims at unifying the empirical research on
interest-rate pass-through in theeuro zone. After endogenously
determining structural breaks we select optimal pass-throughmodels,
which allow for thresholds and asymmetric adjustment. By applying
these models tomonetary policy shocks as well as cost-of-funds
changes, we show that in post-break periodsmonetary policy
transmission has become faster, that heterogeneity across the euro
zone hasdecreased in some banking markets, and that more
competition improves the pass-throughpredominantly in deposit
markets. As national characteristics are still important
pass-through determinants, convergence remains incomplete and
monetary policy will continue tooperate in a heterogeneous euro
zone.# 2004 Elsevier Ltd. All rights reserved.
JEL classication: E43; E52; E58; F36
Keywords: Interest rates; Monetary policy; European Monetary
Union; European banking; Competition
in banking; European nancial integration; Banking structure;
Asymmetric adjustment; Cointegration
analysis; Threshold cointegration; Structural breaks
-
1. Introduction
How uniform is the monetary transmission process in the euro
zone? Given thedominant role of bank nance in the euro zone, banks
are important conveyers ofmonetary policy impulses.1 However,
banking markets are often considered to be
H. Sander, S. Kleimeier / Journal of International Money and
Finance 23 (2004) 461492462more resistant to convergence than other
parts of the monetary transmission mech-anism. As such, divergences
in national banking market structures and competitionas well as a
lack of euro-zone banking market integration can be expected to
leadto heterogeneous eects of monetary policy across the euro-zone
economies.Recent literature has therefore focused on empirical
analyses of the pass-through
of monetary policy impulses to retail banking interest rates in
the euro zone.2
Overall, these studies agree that there is a substantial degree
of short-run bankinterest rate stickiness. Furthermore, all studies
nd considerable dierences in thepass-through not only across
dierent bank lending and deposit rates but alsoacross countries.
These dierences are typically attributed to the divergent
struc-tures of national nancial systems. However, the single
currency is often perceivedto be a unifying force by making the
pass-through faster, more complete and morehomogeneous over the
recent years. Nevertheless, the dierences in the results
ofpass-through studies remain large and can be attributed mainly to
four factors: (1)the choice of the exogenous market interest rate,
(2) the length and timing of thesample periods, particularly with
respect to the treatment of possible structuralbreaks, (3) the
chosen methodology for the pass-through analysis, and (4) thedesign
of the analysis of pass-through determinants.In this study we
provide a unifying analysis of the euro-zone pass-through mech-
anism by addressing these four issues: First, the pass-through
is investigated byusing both proxies for monetary policy rates as
well as proxies for the banks costof funds. The rst approach
focuses on the transmission of monetary policy impul-ses into the
nancial sector while the second approach highlights the role of
com-petition and market structures. Both approaches can be found in
the literature andshould therefore be viewed as complementary. Our
unifying analysis allows for adirect comparison. Second, we
investigate if and when the pass-through has chan-ged between 1993
and 2002 by not postulating, but endogenously searching
forstructural breaks. Third, we estimate a large variety of
pass-through models,including threshold and asymmetric adjustment
models. The model nally used foreach retail rate in each country is
automatically selected according to statisticalcriteria set a
priori. Finally, we investigate the determinants of the size, speed
andconvergence of the pass-through process.The results of our study
can be summarized as follows: First, the euro-zone pass-
through mechanisms have undergone considerable structural
changes in the past
1 See Bernanke and Gertler (1995) and Kashyap and Stein (1993)
for a discussion of the dierent
transmission channels of monetary policy.2 This literature
includes BIS (1994), Cottarelli et al. (1995), Borio and Fritz
(1995), Mojon (2000), de
Bondt (2002), de Bondt et al. (2002); Kleimeier and Sander
(2002, 2003), Sander and Kleimeier (2002),
and Toolsema, Sturm and de Haan (2002), Heinemann and Schuler
(2003).
-
decade. However, these structural breaks do not necessarily
coincide with theintroduction of the single currency but have often
occurred much earlier. Thisresult contests exogenously setting the
break point in January 1999. One wouldthen eventually attribute the
observed changes in the pass-through process to theintroduction of
the single currency, while it may in fact reect the impact of
earlierchanges in EU banking market regulation, or expectational
eects in the run up toEMU, or the impact of lower money market rate
volatility prior to 1999. A secondresult is that during the
post-break period the pass-through of monetary policy
features of national nancial markets as well as macroeconomic
factors such as
463H. Sander, S. Kleimeier / Journal of International Money and
Finance 23 (2004) 461492interest-rate volatility, structural
ination and growth can explain a considerablepart of the
pass-through heterogeneity. However, legal and cultural
dierencesremain statistically signicant determinants. We therefore
conclude that neitherstructural convergence of nancial systems
across countries nor a single monetarypolicy regime can be expected
to fully homogenize the euro-zone pass-through inthe near
future.
2. Data and methodology
2.1. Data selection
We investigate the pass-through process for ten dierent loan and
deposit ratesin ten euro-zone countries over the period from
January 1993 until October 2002.These rates are available from the
ECB with a monthly frequency.3 We comparethe monetary policy
approach with the cost-of-funds approach. For the for-mer we use
the overnight money market rate as a proxy for the monetary
policystance. For the industrial organization inspired
cost-of-funds approach we follow
3 The ECB provides data for the following retail interest rate:
overdrafts on cash accounts (N1), mort-
gage loans to households (N2), consumer loans to households
(N3), short-term loans to enterprises
(N4), medium and long-term loans to enterprises (N5), and other
lending rates (N6), current account
deposits (N7), time deposits (N8), savings accounts (N9), and
other deposit rates (N10). Whereas some
national series start as early as 1980, data for a larger number
of EMU member countries are available
only since the mid 1990s. Considering potential disturbing eects
of the EMS crisis on our results, we
decided to focus on the period after 1992. We include Austria,
Belgium, Finland, France, Germany,
Ireland, Italy, Netherlands, Portugal, and Spain in our
sample.impulses has improved with respect to lending but not to
deposit rates. We alsond that there is no improvement over time in
the pass-through of cost-of-fundschanges. Furthermore, and in
contrast to some earlier studies, we nd an incom-plete long-run
pass-through for most retail rates. Interesting also, the size of
thepass-through is typically higher the shorter maturity of the
lending rate. However,the grip that monetary policy now has on
long-term lending rates, such as mort-gage rates, has also
improved. Whilst the pass-through mechanism has generallyremained
heterogeneous across euro-zone countries, the market for short-term
cor-porate lending has become more homogeneous, thus conveying the
statisticalpicture of a more integrated market. Finally, we nd that
the distinct structural
-
de Bondt (2002) by selecting the market interest rate with the
highest correlation
with the respective retail lending or deposit rate as a proxy
for the cost of funds. In
our study, this leads to the choice of the 10-year rate as the
cost of funds rate for
mortgages, the 12-months rate for consumer loans, the 1-month
rate for short-term
This specication avoids spurious regression problems but leads
to a loss of
H. Sander, S. Kleimeier / Journal of International Money and
Finance 23 (2004) 461492464information about long-run
relationships. Fortunately, this information can be
recovered if BR and M are cointegrated. The VAR then needs to be
augmented by
an (lagged) error correction term (ECT):
DBRt Xki1
bBR;iDBRti b1DMt Xni1
bM;iDMti bECTECTt1 et: 3
4 The main data source is Datastream. More details are given in
Sander and Kleimeier (2005) avail-
able as LIFE Working Paper WP04-005 at
http://www.fdewb.unimaas.nl/nance/workingpapers/.5 Whenever an
optimal lag length has to be determined, the minimum AIC criterion
is used allowing
for a maximum of four lags.corporate loans, the 6-months rate
for medium- and long-term corporate loans, the
1-month rate for current account deposits, and the 3-months rate
for time deposits
and savings accounts. For the analysis of the structural
determinants of the pass-
through process, we collect a large number of banking market
descriptors from
recent publications of the ECB (2000, 2002) and the OECD.
Moreover, the usual
macro-economic and nancial development control variables are
collected.4
2.2. The empirical pass-through model
Our empirical pass-through analysis employs a unifying approach
that utilizes
VAR and cointegration methodologies allowing for asymmetric and
threshold
adjustment. Traditionally, the pass-through process has simply
been modeled as a
VAR process (Cottarelli and Kourelis, 1994):
BRt b0 Xki1
bBR;iBRti b1Mt Xni1
bM;iMti et; 1
where BRt and Mt are lending and market rates, respectively, and
k and n indi-
cate the optimal lag lengths.5 However, it is important to
recognize that the time
series for interest rates typically exhibit an I(1) property. In
this case, the empirical
pass-through model is best estimated using rst dierences:
DBRt Xki1
bBR;iDBRti b1DMt Xni1
bM;iDMti et: 2
-
The ECT measures the deviation from the long-run equilibrium,
which can beobtained from the estimated error of the cointegration
regression:
BRt h0 hMt ut: 4We estimate the appropriate version of the
pass-through model as either Eqs. (1)
and (2), or (3) depending on the time series and cointegration
properties of theinterest rate series.6 In all specications, the
impact multiplier is estimated by thecoecient b1. A value of less
than 1 indicates sluggish adjustment, also known as
465H. Sander, S. Kleimeier / Journal of International Money and
Finance 23 (2004) 461492lending rate stickiness. The long-run
relationship between market rates and retailrates is given by Eq.
(4) and can be interpreted either as a cointegration relation-ship
or as the long-run solution of the VAR. The long-term multiplier h
can bedirectly obtained from estimating Eq. (4) if the rates are
cointegrated. Otherwise,the long-term multiplier has to be
calculated from (1) or (2) as:
h b1 Pn
i1 bM;i1Pki1 bBR;i : 5
A full pass-through in the long run is reected by h 1. An
imperfect pass-through h < 1 could be caused by a less than
perfect elasticity of demand forbanking products, the existence of
market power, a lack of market contestability,switching costs, or
information asymmetries. If the long-run pass-through is foundto be
overshooting h > 1 in lending markets, this can be interpreted
as a situationwhere banks increase lending rates to compensate for
higher risks instead ofrationing credit.7
Given the major developments in the euro zone since 1992, the
long-run relation-ship may be subject to structural changes.
However, unlike other pass-throughstudies we do not exogenously
postulate a break point and then test for its pres-ence. Instead,
we determine the presence and timing of the break endogenously
byestimating a supremum F (supF) test for Eq. (4). This test can be
interpreted as arolling test where standard Chow tests are
conducted for a series of dierent breakpoints, which move through
the mid-80% of the sample period.8 On the base ofthese tests we
constructwhen appropriatepre- and post-break periods for
everynational retail interest rate. This allows us to obtain
additional information on thetiming of structural changes and to
estimate pass-through models for break-freesample periods.
6 We employ various tests to establish whether or not the
interest rate series exhibit unit roots. Given
the likely presence of a structural break, we conduct standard
unit root tests for the pre- and post-break
periods. For the full period we additionally estimate unit root
tests, which are valid in the presence of a
structural break. Details are available in Sander and Kleimeier
(2004).7 De Bondt (2002) discusses a model where banks price higher
default probabilities into lending rates.
His perfect-competition model assumes that banks are able to
distinguish between risky and non-risky
borrowers.8 For details on this test see Andrews (1993), Diebold
and Chen (1996), Hansen (1992). SupF equals
the largest Chow F-statistic and is compared to critical values
as reported by Hansen (1992).
-
H. Sander, S. Kleimeier / Journal of International Money and
Finance 23 (2004) 461492466While most pass-through studies focus on
symmetric adjustment towardthe long-run equilibrium, we have
advocated in a previous study (Sander andKleimeier, 2002) that
threshold and asymmetric adjustment mechanisms shouldboth be
considered for two main reasons: First, retail rate adjustment
patterns inthe euro zone are indeed frequently either asymmetric or
occur only beyond a cer-tain threshold. Thus, they should not be
ignored. Second, using models with asym-metries allows us to detect
cointegration in cases where there are asymmetries andwhere other
methods would thus fail to detect cointegration and wrongly
re-directthe researcher to the pass-through model of Eq. (2).We
include ve asymmetric specications for the adjustment of interest
rates.
Consider rst the symmetric pass-through model. Here the ECT is
dened as
ECTt1 ut1 6
and cointegration testing is based on the DurbinWatson (DW),
DickeyFuller(DF) and augmented DickeyFuller (ADF) tests. As the rst
asymmetric modelwe consider the threshold autoregressive model
(TAR0) developed by Tong(1983). The model distinguishes whether the
explained interest rate is above orbelow its equilibrium level.
Thus, the TAR0 allows for asymmetric adjustmentdepending on the
sign of the equilibrium deviation. For example, if the moneymarket
rate decreases without an immediate adjustment of the lending rate,
weobtain a positive realization of the error term ut. When in this
case the auto-regressive decay is faster than in the case of money
market rate increases, the lend-ing rate adjustment is faster
downward than upward. For this TAR0 model, theECT is dened as
ECTt1 It ut1 1 It ut1 7
where It represents a Heaviside indicator for dierent states of
ut1 such that
It 1 if ut1 00 if ut1 < 0
: 8
Using this denition we estimate Eq. (9):
Dut Itq1ut1 1 Itq2ut1 Xmi1
q2iDuti et: 9
Cointegration testing takes the form of a modied ADF test. The
null of no coin-tegration is rejected if the estimated F-statistic
for H0: q1 q2 0 is statisticallysignicant based on critical values
provided by Enders and Siklos (2000). If coin-tegration is
established, an F-test for H0: q1 q2 indicates the presence of
asym-metry.The second asymmetric model (TAR) is a modication of the
TAR0 in the
sense that the threshold is now allowed to deviate from zero.
The rationale is thatretail rates may adjust dierently to a
disequilibrium once a certain minimum devi-
-
ation in one direction is exceeded. For the TAR model, the
Heaviside indicator inconjunction with Eq. (7),9 is dened as
467H. Sander, S. Kleimeier / Journal of International Money and
Finance 23 (2004) 461492It 1 if ut1 a00 if ut1 < a0: 10
Following Chan (1993), the optimal threshold a0 is found by
searching over themid-80% of the distribution of ut and selecting
the model for which the residualsum of squares is minimized.
Cointegration and asymmetry testing proceeds withthe
above-described F-tests.The third variation is a Band-TAR model
(B-TAR), which can reect both
interest rate stickiness, driven by menu-cost behavior of banks,
as well as interestrate smoothing. For example, menu-cost behavior
could be relevant if we nd coin-tegration only outside a band
bordered by a0 and a0. For the B-TAR model, theHeaviside indicator
in conjunction with Eq. (7) is now dened as
Ijt I1t 1 if ut1 a0 and 0 otherwiseI2t 1 if jut1j < a0 and 0
otherwiseI3t 1 if ut1 a0 and 0 otherwise
8 0 leading to theM-TAR specication.The objective of the
methodology employed in this study is to obtain the optimal
October 1996 for the monetary policy approach and December 1996
for the cost-of-funds approach. Note that dierent banking market
segments in dierent coun-
H. Sander, S. Kleimeier / Journal of International Money and
Finance 23 (2004) 461492468tries show dierent breakpoints. In
particular, for Spain, Portugal, and Italy break-points are as
early as 1995 and 1996, possibly showing the impact of the run-up
toEMU with reduced money market rate volatility and ination
convergence.Another early starter is Ireland where some breakpoints
are already found inDecember 1993.
3.2. Size and speed of the euro-zone pass-through
The optimal pass-through model is estimated for all break-free
periods for themonetary policy and cost-of-funds approach,
respectively. Table 2 illustrates ourresults by reporting the
unweighted averages of the obtained multipliers10. In thelong run,
with the possible exception of short-term corporate loans, the size
of thepass-through process is still far from complete. For the
monetary policy approach
10 The details of this analysis including all individual country
and rate multipliers can be found in
Sander and Kleimeier (2004).pass-through model rather than
arbitrarily selecting one. As such, we identifybreak-free
sub-periods. We then proceed with unit root testing. If the rates
are I(0),we estimate the pass-through model as in Eq. (1). If the
rates are I(1), we rst esti-mate all ve asymmetric TAR-type models,
select the best asymmetric model basedon the AIC criterion, and
test this best model for asymmetric cointegration. Ifasymmetric
cointegration is conrmed, we estimate the pass-through model as
inEq. (3) with the appropriate asymmetric ECT. If asymmetric
cointegration is rejec-ted, we test for symmetric cointegration
andif conrmedinclude a symmetricECT in the pass-through model of
Eq. (3). If symmetric cointegration is also rejec-ted, the
pass-through model is estimated according to Eq. (2) without any
ECT.Finally, based on the selected pass-through model multipliers
are obtained for avariety of positive and negative interest rate
shocks.
3. Pass-through and monetary transmission
3.1. Structural changes in euro-zone banking
The euro-zone banking system has undergone dramatic structural
changes in thepast decade driven by not only the introduction of
the single currency but also the1992/93 ERM crisis and EU
regulatory changes, including the 2nd Banking Direc-tive. Our
analysis indicates that the endogenously determined structural
breaks inthe long-run relationship between market and retail rates
already occur beforeJanuary 1999. The results reported in Table 1
reveal that the average breakpoint is
-
Table1
Structuralbreaksinthelong-runrelationship
Country
Bankrate
Monetarypolicy
approach
Cost-of-fundsapproach
supFa
Breakpoint
supFa
Breakpoint
Austria
N2mortgage
loansto
households
196.25
July-97
14.41
February-99
N3consumerloansto
households
253.10
September-98
188.86
August-97
N4short-termloansto
enterprises
196.26
August-97
236.56
August-97
N7currentaccountdeposits
221.39
Novem
ber-99
200.23
Novem
ber-99
N8timedeposits
199.14
March-97
220.36
March-97
Belgium
N2mortgage
loansto
households
89.26
August-95
60.78
May-98
N3consumerloansto
households
319.18
Decem
ber-95
182.81
Decem
ber-95
N4.1short-termloansto
enterprises
48.19
April-95
54.69
March-95
N4.2short-termloansto
enterprises
21.25
January-94
24.45
Decem
ber-93
N5mediumandlong-termloansto
enterprises
65.56
October-95
38.12
August-96
N8timedeposits
23.91
Decem
ber-93
26.79
Decem
ber-93
N9savingsaccounts
226.14
Decem
ber-95
221.73
Decem
ber-95
Finland
N2mortgage
loansto
households
105.93
September-96
99.64
March-94
N3consumerloansto
households
101.80
September-96
86.25
September-97
N5mediumandlong-termloansto
enterprises
56.00
January-96
47.41
April-98
N7currentaccountdeposits
49.11
February-97
46.62
February-98
N8timedeposits
170.27
August-97
193.92
Novem
ber-99
France
N4short-termloansto
enterprises
132.42
June-97
150.03
June-97
N5mediumandlong-termloansto
enterprises
222.29
March-97
169.78
April-97
N8timedeposits
11.38
January-00
insignicant
8.24
January-00
insignicant
N9savingsaccounts
112.11
May-98
104.56
May-98
GermanyN2mortgage
loansto
households
56.62
October-96
36.16
June-95
N3consumerloansto
households
442.05
February-97
480.06
March-97
N4short-termloansto
enterprises
71.72
July-00
81.82
February-03
N5mediumandlong-termloansto
enterprises
11.22
January-00
insignicant
9.99
January-00
insignicant
N8.1timedeposits
40.30
September-99
22.97
September-99
N8.2timedeposits
22.35
September-99
9.06
January-00
insignicant
N9.1savingsaccounts
935.80
September-99
732.66
September-99
N9.2savingsaccounts
36.67
October-95
33.47
Novem
ber-95
Ireland
N1overdraftsoncash
accounts
128.80
Decem
ber-98
145.26
Decem
ber-98
(continued
onnextpage)
469H. Sander, S. Kleimeier / Journal of International Money and
Finance 23 (2004) 461492
-
Table1(continued)
Country
Bankrate
Monetarypolicy
approach
Cost-of-fundsapproach
supFa
Breakpoint
supFa
Breakpoint
Ireland
N2mortgage
loansto
households
61.51
August-99
49.53
March-94
N4short-termloansto
enterprises
33.00
Novem
ber-95
35.15
Decem
ber-93
N5mediumandlong-termloansto
enterprises
40.68
Decem
ber-93
70.41
Decem
ber-93
N6otherlendingrates
45.07
January-00
4.66
January-00
insignicant
N9.1savingsaccounts
149.76
Decem
ber-93
152.03
Decem
ber-93
N9.2savingsaccounts
129.03
Decem
ber-93
205.33
Decem
ber-93
Italy
N2mortgage
loansto
households
69.42
Decem
ber-97
131.97
May-98
N4.1short-termloansto
enterprises
31.26
February-95
30.09
July-99
N4.2short-termloansto
enterprises
39.91
February-95
21.20
June-94
N5mediumandlong-termloansto
enterprises
48.08
Novem
ber-97
43.01
Decem
ber-96
N7currentaccountdeposits
70.21
February-95
44.16
February-95
N8timedeposits
110.97
September-97
102.79
January-97
Nether-
lands
N2mortgage
loansto
households
61.82
September-96
41.20
June-95
N4short-termloansto
enterprises
30.02
August-97
66.16
August-98
N7currentaccountdeposits
466.47
Decem
ber-98
466.47
Decem
ber-98
N8.1timedeposits
64.49
Novem
ber-95
51.29
Novem
ber-95
N8.2timedeposits
65.67
Decem
ber-95
56.09
Decem
ber-95
Portugal
N2mortgage
loansto
households
98.82
September-97
58.86
Decem
ber-95
N3consumerloansto
households
178.60
April-95
73.79
April-98
N4.1short-termloansto
enterprises
100.14
July-94
235.71
October-99
N4.2short-termloansto
enterprises
173.12
February-95
74.02
Novem
ber-99
N8.1timedeposits
43.22
January-96
13.83
Novem
ber-00
N8.2timedeposits
47.58
February-96
32.09
July-96
Spain
N2mortgage
loansto
households
69.89
September-96
69.89
September-96
N3consumerloansto
households
111.60
Novem
ber-96
103.25
March-94
N4short-termloansto
enterprises
9.52
September-96
12.18
Novem
ber-96
N5mediumandlong-termloansto
enterprises
59.41
March-96
60.49
September-94
N7currentaccountdeposits
48.46
February-95
99.52
January-95
N8timedeposits
80.42
March-96
113.56
Decem
ber-93
aThesupFtestisbasedontheestimatedcoe
cientforEq.(4)usingmonthlydata
forthefullsampleperiodofJanuary
1993to
October2002.Statistical
signicance
ofthebreakpointisestablished
basedoncriticalvaluesreported
byHansen(1992).
H. Sander, S. Kleimeier / Journal of International Money and
Finance 23 (2004) 461492470
-
Table2
Theaveragepass-throughprocessanditsasymmetries
Retailrates
Period
Statis-
tica
Multipliersfora+1%
shock
Asymmetriesinmultipliersb
+1%versus1
%shock
+1%versus+0.25%shock
impact
1 mth
3 mths
6 mths
12
mths
long-
run
1 mth
3 mths
6 mths
12
mths
1 mth
3 mths
6 mths
12
mths
PanelA:The
Monetary
Policy
Approach
All
pre
average
0.20
0.31
0.42
0.49
0.53
0.56
1.00
0.98
0.98
0.98
1.00
1.00
1.00
0.99
stddev
0.17
0.23
0.29
0.31
0.31
0.32
0.00
0.10
0.08
0.06
0.00
0.08
0.07
0.06
post
average
0.20
0.37
0.48
0.53
0.54
0.57
1.00
1.01
0.99
0.99
1.00
1.00
0.99
0.99
stddev
0.17
0.28
0.31
0.33
0.36
0.38
0.00
0.13
0.11
0.08
0.00
0.07
0.07
0.06
Alllending
pre
average
0.20
0.33
0.46
0.54
0.58
0.62
1.00
0.98
0.99
0.99
1.00
1.00
1.01
1.00
stddev
0.15
0.23
0.31
0.33
0.34
0.35
0.00
0.10
0.07
0.03
0.00
0.06
0.03
0.01
post
average
0.22
0.43
0.56
0.62
0.65
0.68
1.00
1.02
1.00
1.00
1.00
1.00
1.00
1.00
stddev
0.15
0.26
0.30
0.31
0.34
0.37
0.00
0.16
0.13
0.07
0.00
0.06
0.05
0.01
Alldeposit
pre
average
0.20
0.28
0.38
0.43
0.46
0.47
1.00
0.97
0.97
0.97
1.00
1.00
0.99
0.99
stddev
0.20
0.24
0.25
0.26
0.27
0.26
0.00
0.10
0.09
0.09
0.00
0.09
0.10
0.09
post
average
0.17
0.27
0.35
0.38
0.38
0.40
1.00
0.98
0.97
0.97
1.00
0.99
0.99
0.99
stddev
0.20
0.27
0.30
0.31
0.32
0.34
0.00
0.06
0.08
0.09
0.00
0.08
0.09
0.09
N2mortgageloans
tohouseholds
pre
average
0.14
0.22
0.32
0.43
0.52
0.54
1.00
1.02
1.01
1.00
1.00
1.02
1.01
1.00
stddev
0.12
0.19
0.26
0.32
0.39
0.34
0.00
0.05
0.04
0.01
0.00
0.05
0.04
0.01
post
average
0.21
0.45
0.55
0.57
0.57
0.62
1.00
0.97
0.95
0.96
1.00
0.99
0.98
1.00
stddev
0.18
0.28
0.29
0.29
0.29
0.32
0.00
0.10
0.10
0.08
0.00
0.03
0.04
0.01
N3consumerloans
tohouseholds
pre
average
0.16
0.27
0.36
0.42
0.46
0.63
1.00
0.98
0.98
0.98
1.00
1.00
1.00
1.00
stddev
0.13
0.24
0.30
0.34
0.35
0.51
0.00
0.05
0.05
0.05
0.00
0.00
0.00
0.00
post
average
0.17
0.37
0.49
0.55
0.56
0.60
1.00
1.03
1.01
1.00
1.00
1.01
1.01
1.00
stddev
0.12
0.33
0.43
0.51
0.54
0.53
0.00
0.05
0.02
0.00
0.00
0.03
0.02
0.00
N4short-termloans
toenterprises
pre
average
0.24
0.43
0.58
0.68
0.71
0.74
1.00
0.98
0.99
1.00
1.00
0.98
1.00
1.00
stddev
0.16
0.22
0.31
0.31
0.30
0.29
0.00
0.08
0.02
0.00
0.00
0.09
0.02
0.00
post
average
0.24
0.46
0.67
0.77
0.84
0.87
1.00
1.08
1.05
1.03
1.00
0.99
1.00
1.00
stddev
0.15
0.22
0.23
0.21
0.27
0.36
0.00
0.24
0.19
0.09
0.00
0.06
0.07
0.02
N5mediumandlong-
term
loansto
enterprises
pre
average
0.22
0.32
0.44
0.49
0.50
0.51
1.00
0.94
0.96
0.97
1.00
1.01
1.01
0.99
stddev
0.19
0.25
0.36
0.36
0.36
0.36
0.00
0.19
0.15
0.05
0.00
0.03
0.05
0.05
(continued
onnextpage)
471H. Sander, S. Kleimeier / Journal of International Money and
Finance 23 (2004) 461492
-
Table2(continued)
Retailrates
Period
Statis-
tica
Multipliersfora+1%
shock
Asymmetriesinmultipliersb
+1%versus1
%shock
+1%versus+0.25%shock
impact
1 mth
3 mths
6 mths
12
mths
long-
run
1 mth
3 mths
6 mths
12
mths
1 mth
3 mths
6 mths
12
mths
PanelA:The
Monetary
Policy
Approach
post
average
0.24
0.38
0.42
0.46
0.49
0.50
1.00
0.96
0.97
0.99
1.00
0.97
0.98
1.00
stddev
0.14
0.28
0.24
0.22
0.22
0.23
0.00
0.06
0.03
0.02
0.00
0.06
0.03
0.01
N7currentaccount
deposits
pre
average
0.06
0.10
0.15
0.19
0.21
0.23
1.00
0.91
0.92
0.96
1.00
1.05
1.03
1.02
stddev
0.08
0.13
0.18
0.21
0.22
0.22
0.00
0.21
0.14
0.07
0.00
0.11
0.07
0.05
post
average
0.04
0.09
0.16
0.21
0.23
0.22
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
stddev
0.08
0.14
0.22
0.29
0.32
0.32
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
N8timedeposits
pre
average
0.28
0.39
0.52
0.60
0.64
0.64
1.00
0.99
0.97
0.96
1.00
0.97
0.96
0.96
stddev
0.23
0.25
0.21
0.16
0.15
0.16
0.00
0.05
0.09
0.12
0.00
0.10
0.12
0.12
post
average
0.26
0.40
0.50
0.53
0.53
0.57
1.00
0.96
0.94
0.94
1.00
0.98
0.97
0.97
stddev
0.22
0.28
0.27
0.27
0.28
0.31
0.00
0.08
0.10
0.12
0.00
0.11
0.13
0.13
N9savings
accounts
pre
average
0.14
0.20
0.27
0.30
0.31
0.33
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
stddev
0.10
0.16
0.22
0.25
0.25
0.23
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
post
average
0.11
0.18
0.22
0.21
0.21
0.20
1.00
1.01
1.01
1.01
1.00
1.01
1.01
1.01
stddev
0.13
0.24
0.28
0.28
0.27
0.25
0.00
0.03
0.03
0.02
0.00
0.03
0.03
0.02
PanelB:The
CostofFundsApproach
All
pre
average
0.33
0.43
0.55
0.61
0.63
0.65
1.00
1.00
0.98
1.00
1.00
1.01
1.01
1.01
stddev
0.29
0.25
0.31
0.32
0.32
0.34
0.00
0.07
0.26
0.20
0.00
0.06
0.04
0.05
post
average
0.33
0.42
0.53
0.58
0.60
0.60
1.00
1.03
1.03
1.03
1.00
1.04
1.05
1.06
stddev
0.31
0.27
0.30
0.30
0.34
0.34
0.00
0.12
0.17
0.20
0.00
0.17
0.30
0.37
Alllending
pre
average
0.31
0.46
0.60
0.69
0.72
0.73
1.00
1.00
1.02
1.03
1.00
1.00
1.01
1.01
stddev
0.19
0.25
0.31
0.31
0.31
0.33
0.00
0.09
0.19
0.24
0.00
0.03
0.03
0.05
post
average
0.33
0.45
0.60
0.66
0.71
0.69
1.00
1.05
1.06
1.06
1.00
1.04
1.08
1.10
stddev
0.22
0.22
0.25
0.26
0.31
0.31
0.00
0.13
0.21
0.26
0.00
0.21
0.39
0.47
Alldeposit
pre
average
0.35
0.39
0.49
0.50
0.51
0.54
1.00
1.00
0.93
0.95
1.00
1.02
1.01
1.00
stddev
0.39
0.26
0.31
0.30
0.29
0.31
0.00
0.04
0.33
0.13
0.00
0.08
0.05
0.04
post
average
0.34
0.39
0.44
0.46
0.45
0.47
1.00
1.00
0.99
0.98
1.00
1.03
1.01
1.00
stddev
0.40
0.33
0.34
0.33
0.32
0.35
0.00
0.08
0.07
0.06
0.00
0.10
0.07
0.05
H. Sander, S. Kleimeier / Journal of International Money and
Finance 23 (2004) 461492472
-
N2mortgageloansto
households
pre
average
0.24
0.37
0.54
0.59
0.66
0.60
1.00
1.04
1.10
1.13
1.00
0.98
1.02
1.03
stddev
0.21
0.31
0.41
0.37
0.39
0.37
0.00
0.15
0.35
0.45
0.00
0.06
0.05
0.09
post
average
0.22
0.31
0.43
0.55
0.67
0.65
1.00
1.06
1.12
1.15
1.00
1.00
1.03
1.04
stddev
0.20
0.23
0.23
0.29
0.44
0.44
0.00
0.15
0.34
0.44
0.00
0.08
0.06
0.09
N3consumerloansto
households
pre
average
0.32
0.47
0.43
0.58
0.61
0.63
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
stddev
0.21
0.26
0.26
0.31
0.36
0.37
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
post
average
0.20
0.32
0.46
0.54
0.56
0.56
1.00
0.99
1.00
1.00
1.00
1.00
1.00
1.00
stddev
0.09
0.15
0.22
0.30
0.34
0.35
0.00
0.02
0.00
0.00
0.00
0.00
0.00
0.00
N4short-termloansto
enterprises
pre
average
0.33
0.52
0.71
0.81
0.85
0.91
1.00
0.98
0.97
0.97
1.00
1.01
1.00
1.01
stddev
0.17
0.23
0.28
0.29
0.28
0.28
0.00
0.05
0.07
0.06
0.00
0.01
0.01
0.01
post
average
0.42
0.55
0.73
0.75
0.77
0.72
1.00
0.11
1.08
1.07
1.00
1.11
1.20
1.24
stddev
0.26
0.21
0.21
0.21
0.24
0.20
0.00
0.17
0.20
0.21
0.00
0.34
0.65
0.80
N5mediumandlong-
term
loansto
enterprises
pre
average
0.39
0.45
0.62
0.71
0.69
0.67
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
stddev
0.22
0.18
0.20
0.23
0.20
0.24
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
post
average
0.44
0.53
0.71
0.75
0.77
0.76
1.00
1.06
1.01
0.99
1.00
1.02
1.02
1.01
stddev
0.19
0.21
0.20
0.22
0.24
0.28
0.00
0.10
0.03
0.03
0.00
0.05
0.06
0.03
N7currentaccount
deposits
pre
average
0.10
0.17
0.22
0.25
0.25
0.25
1.00
1.00
1.00
1.00
1.00
1.00
1.00
1.00
stddev
0.09
0.18
0.24
0.25
0.25
0.24
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
post
average
0.10
0.18
0.23
0.27
0.28
0.28
1.00
0.97
0.98
0.99
1.00
1.01
1.00
1.00
stddev
0.10
0.16
0.20
0.25
0.28
0.28
0.00
0.07
0.07
0.02
0.00
0.03
0.02
0.10
N8timedeposits
pre
average
0.51
0.50
0.67
0.67
0.68
0.70
1.00
1.01
1.00
0.98
1.00
1.04
1.01
1.01
stddev
0.44
0.20
0.27
0.22
0.20
0.21
0.00
0.05
0.04
0.05
0.00
0.11
0.06
0.06
post
average
0.50
0.54
0.64
0.65
0.64
0.66
1.00
1.01
1.00
0.97
1.00
1.05
1.03
1.00
stddev
0.47
0.32
0.31
0.27
0.25
0.27
0.00
0.11
0.09
0.05
0.00
0.15
0.10
0.07
N9savings
accounts
pre
average
0.17
0.25
0.32
0.33
0.35
0.37
1.00
0.99
0.73
0.90
1.00
1.00
1.00
1.00
stddev
0.16
0.21
0.21
0.28
0.29
0.26
0.00
0.05
0.66
0.25
0.00
0.01
0.00
0.00
post
average
0.12
0.15
0.17
0.17
0.17
0.17
1.00
1.01
1.00
1.00
1.00
1.00
1.00
1.00
stddev
0.13
0.17
0.19
0.20
0.20
0.20
0.00
0.02
0.01
0.01
0.00
0.01
0.00
0.00
aThereported
statisticsaretheunweightedaverage(average)andthestandard
deviation(std
dev)oftheestimatedmultipliersbasedontheoptimalpass-
through
model.
bAsymmetriesinmultipliersaredened
asthemultiplierfora+1%
changedivided
bythemultiplierforthe1
%or+0.25%change,respectively.
473H. Sander, S. Kleimeier / Journal of International Money and
Finance 23 (2004) 461492
-
we nd long-run multipliers for loans on average around 0.6 to
0.7. For deposits,the average even lies below 0.5. For the
cost-of-funds approach the obtained long-run multipliers are
somewhat higher but also fall short of a full pass-through.11
Viewed from an industrial organization perspective, the latter
result indicates thateuro-zone banking markets may exhibit some
form of imperfect competition, suchas market power, lack of
contestability, switching costs, or informational asymme-tries.
Turning to the short run, our impact and intermediate multipliers
indicate thepresence of severe price rigidities for both
approaches. Nevertheless, the results
H. Sander, S. Kleimeier / Journal of International Money and
Finance 23 (2004) 461492474also show remarkable increases in the
intermediate multipliers for the post-breakperiod. This reects
faster price adjustments for some banking products, parti-cularly
mortgages, consumer loans, and short-term loans to enterprises.
Regardingmortgages, it is striking that the eciency of the
pass-through process hasincreased with respect to monetary policy
impulses while the role of cost of fundshas diminished in the
short-run adjustment. Possibly the increasing use of exiblerate
mortgages is reected in these results. Consequently, and as argued
by Sellon(2002) in the context of the US, monetary policy targeted
at short-term marketrates has increased its impact on the cost of
mortgages. In consumer lending,though some improvements have been
taking place, the pass-through remainsamong the least perfect. For
corporate loans the picture is mixed. Regarding short-term
corporate loans, the already fast and almost complete monetary
policy pass-through has improved over time while the cost-of-funds
6-months, 12-months, andlong-run multipliers have decreased. The
opposite picture emerges for longer-termcorporate loans. Given the
nature of these loans a market rate with a matchedmaturity might be
a better explanatory variable.12
In summary, the multipliers seem to indicate that the size and
speed of the pass-through have improved in the post-break period.
However, this observation is onlyvalid for the lending rates
reaction to monetary policy innovations. For the cost-of-funds
approach the results are less clear-cut. To prove these points
statisticallywe regress the size and speed of the pass-through on
post-break, country, and ratedummies.13 Size is dened as the value
of the long-run multiplier (h). Speed isdened as the impact and
intermediate multipliers relative to the long-run multi-plier. The
results are shown in Table 3. They conrm that the size of the
pass-through has not improved signicantly in the post-break period.
However, a stat-istically signicant increase in the speed of the
pass-through process in the periodfrom 1 to 6 months is clearly
identiable for the monetary policy approach but not
11 This result does not depend on the choice of the market rate
proxy and is thus standing in contrast
to the studies by de Bondt (2002) and de Bondt et al. (2002).
Given the partly dierent approaches and
timing of the structural breaks, reconciling these dierences
remains an important task for future
research.12 It could be argued that monetary policy targeted at
short-term interest rates has only an improved
inuence on the short-term rather than long-term lending rates to
enterprises. If, for example, the cen-
tral bank wants to inuence the cost of investment borrowing of
small and medium size enterprises it
appears that she should particularly consider her policys impact
on longer-term market rates.13 We are grateful to Robert DeYoung
for suggesting this regression framework.
-
Table3
Countryandmarketdeterminantsoftheinterest-ratepass-through
Independentvariableb
Dependentvariablea
Size
Speed
Convergence
long-run
impact
1mth
3mth
6mth
12mths
rlong-run
blong-run
PanelA:The
Monetary
Policy
Approach
Constant
0.561
0.464
0.753
0.696
0.752
0.840
0.357
3.454
4.269
4.164
5.974
5.906
8.504
10.603
2.162
1.426
Pre-break-m
ultiplier
4.226
1.877
Austria
0.054
0.206
0.182
0.194
0.188
0.156
0.057
0.672
0.372
1.664
1.301
1.483
1.911
1.765
0.309
0.258
Belgium
0.222
0.019
0.200
0.005
0.071
0.100
0.171
1.993
1.724
0.178
1.620
0.046
0.824
1.285
1.056
0.906
Finland
0.051
0.235
0.470
0.247
0.151
0.085
0.069
1.446
0.361
1.941
3.433
1.933
1.569
0.986
0.385
0.602
Germany
0.026
0.055
0.150
0.280
0.243
0.163
0.075
0.500
0.207
0.521
1.245
2.496
2.882
2.156
0.479
0.240
Ireland
0.144
0.167
0.091
0.246
0.212
0.146
0.057
0.569
1.045
1.426
0.688
1.993
2.280
1.753
0.327
0.246
Italy
0.218
0.117
0.173
0.111
0.159
0.105
0.220
1.013
1.619
1.024
1.341
0.919
1.755
1.292
1.303
0.421
Netherlands
0.072
0.093
0.013
0.222
0.222
0.114
0.005
1.019
0.505
0.771
0.098
1.744
2.329
1.330
0.027
0.433
Portugal
0.289
0.353
0.370
0.155
0.054
0.033
0.197
1.336
2.116
3.054
2.825
1.266
0.590
0.397
1.152
0.573
Spain
0.134
0.297
0.403
0.089
0.082
0.184
0.088
0.448
0.983
2.574
3.095
0.732
0.894
2.242
0.515
0.197
N3-consumer-loans-to-households
0.018
0.069
0.010
0.019
0.030
0.090
0.114
3.974
0.150
0.694
0.090
0.179
0.378
1.267
0.769
1.988
N4-short-term-oans-to-enterprises
0.250
0.126
0.051
0.016
0.026
0.036
0.249
0.287
2.622
1.563
0.554
0.187
0.407
0.632
2.086
0.165
(continued
onnextpage)
475H. Sander, S. Kleimeier / Journal of International Money and
Finance 23 (2004) 461492
-
Table3(continued)
Independentvariableb
Dependentvariablea
Size
Speed
Convergence
long-run
impact
1mth
3mth
6mth
12mths
rlong-run
blong-run
N5-m
edium-andlong-termloansto
enterprises
0.021
0.065
0.016
0.014
0.033
0.015
0.026
1.302
0.213
0.772
0.172
0.161
0.503
0.245
0.213
0.781
N7-currentaccountdeposits
0.392
0.053
0.021
0.009
0.010
0.029
0.593
2.740
3.318
0.525
0.182
0.082
0.120
0.410
4.001
1.210
N8-timedeposits
0.006
0.072
0.016
0.031
0.050
0.028
0.151
0.795
0.062
0.916
0.185
0.374
0.812
0.511
1.302
0.504
N9-savingsaccounts
0.201
0.073
0.207
0.079
0.039
0.032
0.264
2.423
1.725
0.736
1.856
0.755
0.502
0.449
1.806
1.234
N6/N10-otherlendingordepositratesc
0.364
0.272
0.115
0.034
0.019
0.001
0.358
0.306
1.567
1.381
0.515
0.162
0.124
0.011
1.227
0.078
Post-breakdummy
0.001
0.071
0.164
0.157
0.092
0.036
0.116
0.017
1.563
3.188
3.269
2.540
1.108
1.721
Adjusted
R2
34.3%
24.3%
29.9%
27.7%
24.2%
8.8%
26.7%
10.7%
Numberofobservations
114
114
114
114
114
114
114
56
PanelB:The
CostofFundsApproach
Constant
0.642
0.735
0.567
0.786
0.749
0.891
0.380
5.425
5.349
5.571
5.248
7.371
9.439
14.668
2.718
2.619
Pre-break-m
ultiplier
5.954
3.363
Austria
0.034
0.400
0.051
0.046
0.214
0.170
0.092
0.753
0.254
2.735
0.424
0.388
2.432
2.526
0.592
0.353
Belgium
0.024
0.139
0.094
0.086
0.215
0.156
0.014
0.395
0.196
1.035
0.854
0.790
2.657
2.531
0.101
0.198
Finland
0.097
0.396
0.095
0.136
0.120
0.158
0.093
1.478
0.735
2.727
0.801
1.156
1.377
2.362
0.601
0.687
Germany
0.066
0.159
0.201
0.108
0.213
0.140
0.110
1.396
0.547
1.195
1.845
1.002
2.660
2.283
0.781
0.709
Ireland
0.199
0.067
0.277
0.285
0.334
0.203
0.026
2.154
1.597
0.493
2.467
2.577
4.053
3.215
0.182
1.073
H. Sander, S. Kleimeier / Journal of International Money and
Finance 23 (2004) 461492476
-
Italy
0.131
0.339
0.000
0.001
0.182
0.128
0.077
1.361
1.044
2.462
0.003
0.013
2.199
2.014
0.530
0.665
Netherlands
0.048
0.335
0.054
0.053
0.174
0.133
0.058
0.261
0.365
2.302
0.450
0.450
1.9860
1.986
0.374
0.124
Portugal
0.145
0.328
0.110
0.031
0.158
0.121
0.091
5.531
1.146
2.354
0.9640
0.279
1.881
1.881
0.618
2.699
Spain
0.282
0.389
0.055
0.067
0.138
0.147
0.025
1.469
2.235
2.807
0.484
0.601
1.657
2.304
0.173
0.706
N3-consumerloansto
households
0.111
0.069
0.116
0.008
0.024
0.062
0.087
3.498
1.113
0.622
1.281
0.089
0.364
1.228
0.745
2.187
N4-shortterm
loansto
enterprises
0.154
0.002
0.053
0.050
0.011
0.047
0.208
1.063
1.864
0.017
0.709
0.6850
0.203
1.1210
2.166
0.751
N5-m
ediumandlongterm
loans
0.049
0.065
0.102
0.160
0.131
0.013
0.112
2.141
toenterprises
0.469
0.571
1.094
1.732
1.914
0.255
0.923
1.247
N7-currentaccountdeposits
0.439
0.060
0.186
0.131
0.053
0.041
0.408
5.063
4.088
0.510
1.914
1.367
0.748
0.751
3.260
2.687
N8-timedeposits
0.002
0.185
0.113
0.120
0.032
0.060
0.153
2.688
0.025
2.021
1.512
1.619
0.589
1.420
1.578
2.023
N9-savingsaccounts
0.299
0.108
0.054
0.065
0.093
0.123
0.271
2.456
2.876
0.948
0.577
0.706
1.357
2.339
2.237
1.465
N6/N10otherlendingordepositratesc
0.640
0.159
0.008
0.463
0.360
0.455
0.427
3.024
3.050
0.691
0.041
2.482
2.590
4.277
1.746
0.843
postbreakdummy
0.052
0.030
0.049
0.069
0.052
0.039
0.042
1.039
0.556
1.103
1.552
1.586
1.561
0.723
Adjusted-R
237.5%
8.6%
7.4%
10.2%
10.8%
15.6%
23.0%
18.9%
Numberofobservations
115
115
115
115
115
115
115
57
aThedependentvariablesoftheseOLSregressionsarethemultipliersfora+1%
shock
inthemonetary
policy
orcostoffundsrate.
bForeach
independentvariabletheestimatedcoe
cientisreported
inthetoprowandthetstatisticisreported
initalicsinthebottomrow.
cTheother
ratesreferto
N10other
depositratesforthemonetary
policy
approach
andN6other
lendingratesforthecostoffundsapproach.In
each
case,theseratesaccountforonly2observationsinthesample.
477H. Sander, S. Kleimeier / Journal of International Money and
Finance 23 (2004) 461492
-
for the cost-of-funds approach. Broadly speaking, monetary
policy actions thattarget overnight money market rates have
increased in relevance as compared tothe role of cost of funds.With
respect to country specics, the monetary policy approach indicates
a
somewhat larger pass-through size in Portugal and possibly Italy
but a smaller onefor Belgium. Speed is signicantly lower for
Portugal, Finland, and Spain for the 1-month horizon but higher for
Germany, Ireland, and the Netherlands within the 3-to 6-months
horizon. For the cost-of-funds approach we nd a signicant
larger
H. Sander, S. Kleimeier / Journal of International Money and
Finance 23 (2004) 461492478pass-through size only for Spain, while
in the speed regressions the dummies forthe various countries
reveal a very heterogeneous picture. One conclusion thatmight
emerge from this comparative analysis is that the country-specic
responsesare more uniform to monetary policy rate changes than to
measures of cost offunds.14
With respect to specic markets, the monetary policy approach
indicates asignicantly larger pass-through size for short-term
corporate loans and a smallersize for current account and saving
deposits. These results are in line with theMonti-Klein model of
the monopolistic or oligopolistic banking rm, whichpredicts that
smaller elasticities imply higher intermediation margins.15
Sincethe case can be made that interest changes may have a larger
impact on theshort-run funding choice of borrowers than on the
wealth of depositors, the latterssupply of deposits may be
comparatively less elastic, hence leading to a smallerand/or slower
pass-through for deposits. Regarding speed we do not
identifysignicant market-specic changes but this result might be a
consequence ofthe denition of the speed variable in the presence of
size changes in the samedirection.
3.3. Asymmetries in the euro-zone pass-through
For the majority of the national retail interest rates, the
pass-through mechan-isms are most accurately described by
asymmetric models. We select them in 51%of all cases for the
cost-of-funds approach and in 46% of all cases for the
monetarypolicy approach. From the pre- to the post-break period,
the share of cases wherethe asymmetric model is selected increases
from 42% to 60% and from 29% to 62%,respectively. This strengthens
our case to utilize all proposed asymmetric modelsfor empirically
determining the optimal pass-through model. Furthermore, thisresult
also implies that the majority of interim multipliers are now
dependent onthe direction and size of the market interest rate
shock.16
14 This may, however, also indicate intrinsic problems with the
cost-of-funds approach, which applies
eventually not appropriatelya uniform cost-of-funds variable for
each type of retail rate for all coun-
tries.15 For a discussion of various versions of the Monti-Klein
model see e.g. Freixas and Rochet (1997).16 Note that the
multiplier asymmetries reported in Table 2 are qualitatively
dierent from the notion
of asymmetry in the TAR modelling. However, given that most of
our interim multipliers are smaller
than unity, we can associate a positive interest rate shock with
a negative ECT and thus a below-equilib-
rium state. Consequently, the two types of asymmetry are
somewhat comparable.
-
In Table 2, asymmetries regarding the direction of the shocks
are illustrated bydividing the multipliers for the positive 1%
shock by the multiplier for the negative1% shock. Deviations from
unity indicate asymmetries. For example, a ratio of 1.1implies that
a positive shock has a 10% higher impact than a negative shock.17
In
can be made for the monetary policy approach. On average,
mortgages reactalmost symmetrically to monetary policy rate shocks.
However, our individual
479H. Sander, S. Kleimeier / Journal of International Money and
Finance 23 (2004) 461492country multipliers reveal a large number
of cases where a relatively faster down-ward adjustment takes
place.18 Regarding deposits, on average asymmetries showthe
expected pattern in both approaches but diminish over timepossibly
due torecent developments in nancial markets. Nevertheless, faster
downward adjust-ments of time deposit rates are still
present.Another type of asymmetry is reected in the impact of large
versus small shocks
on retail interest rates. The last four columns in each Panel of
Table 2 givethe relative multiplier for a large +1% versus a small
+0.25% interest rate shock.A ratio larger than unity implies that
the retail rate reacts more strongly tolarge shocks. While the
overall picture in the monetary policy approach isone of symmetry,
this is not true for the cost-of-funds approach. In line withthe
menu cost argument, mortgages, short-term corporate loans, andto
alesser extenttime deposits react faster to large than to small
shocks in the cost offunds.
4. Pass-through and retail banking market integration
Pass-through studies are increasingly regarded important for
assessing the degreeof nancial integration in the euro-zone retail
banking market. Although retailinterest rates have been somewhat
converging, this is not necessarily an indicationof an integrated
market. In Kleimeier and Sander (2002, 2003) we have shown
thateuro-zone retail banking markets are still not integrated when
cointegration is con-sidered as an integration indicator and have
arrived at a No, No, and Maybeproposition with respect to the
integration of mortgage, consumer lending, and
17 It should, however, be recalled that these data are averages
and could easily be misinterpreted. If
some countries are faster in upward adjustments and others in
downward adjustments, the average
would still be 1. In such cases, however, a high standard
deviation can reveal the underlying asymmetry.18 Individual country
multipliers can be obtained from Sander and Kleimeier
(2004).imperfectly competitive banking markets one would expect a
faster upward adjust-ment for loans rates because the degree of
asymmetry is negatively correlated withthe elasticity of the
respective loan demand. For deposits, one would expect
fasterdownward adjustment again depending on the respective
elasticities. This theoreti-cal reasoning is largely conrmed by the
average ratios for lending and depositrates. This result is
strongest for loans in the cost-of-funds approach where mort-gages
and short-term corporate loans exhibit the highest degree of
asymmetry.Long-term corporate loans, for which a higher demand
elasticity can be reasoned,exhibit a more symmetric behavior.
Similar observations, though to a lesser degree,
-
short-term corporate lending markets.19 However, with a single
monetary policyand well-integrated wholesale nancial markets, a
fast and homogeneous pass-through would create a uniform behavior
of euro-zone retail interest rates.Our regression results reported
in Table 3 have already shown an increased
speed of the pass-through in the post-break period once we
control for countryand market characteristics. In order to test
whether or not the pass-through pro-
loans indicating more convergence in this market. For current
account and savingsaccount rates the positive coecient indicates
higher heterogeneity. The b-conver-
H. Sander, S. Kleimeier / Journal of International Money and
Finance 23 (2004) 461492480gence measure is borrowed from the
empirical growth literature.21 According tothis concept, growth
rates are negatively related to initial levels. Thus, countrieswith
initially low multipliers for a given retail rate should see them
growing fasterover time, while countries with initially higher
multipliers see them growing lessfast or even declining. We nd some
evidence for b-convergence for the monetarypolicy approach but not
for the cost-of-funds approach. The dummy for short-term corporate
loans is again positive. In sum, the evidence for a more
homo-geneous pass-through processwith the eventual exception of
short-run corporatelendingremains very limited and lends some
support to our No-No-Maybehypothesis.
5. Pass-through and banking market structure
5.1. Pass-through determinants
In this section we investigate potential determinants of the
pass-through processby making use of the estimated multipliers. We
particularly analyze the role ofnancial market structures after
controlling for macroeconomic determinant fac-tors. Regarding
macroeconomic variables, it has been advocated that money mar-ket
rate volatility is positively correlated with bank interest rate
margins (Saunders
19 This argument has also been made by the European Commissions
Economic and Financial Com-
mittee in a special report (EFC, 2002) and by Cabral et al.
(2002).20 Note that the subscripts indicate country j (Austria to
Spain) and period t (pre-break, post-break).
Thus, each long-run multiplier is compared to the cross-country
average long-run multiplier for its
respective period.21 See Durlauf and Quah (1999).cess has become
more homogenous in the euro zone, we regress two types of
con-vergence measuresb and r convergenceon post-break, country, and
ratedummies. r-convergence measures the variation of the long-run
multiplier and isdened as jhj,t hMean,tj/hMean,t.20 Therefore, a
negative coecient for this dummyindicates less variation and
consequently more convergence. The results are alsoshown in Table
3. The r-convergence regression reveals a slight increase in
hetero-geneity in the post-break period for the monetary policy
approach. No signicantchanges are detectable for the cost-of-funds
approach. Whereas country dummiesdo not play a role, we nd a
signicantly negative dummy for short-term corporate
-
and Schumacher, 2000) and negatively correlated with the
pass-through (Cottarelliand Kourelis, 1994; Mojon, 2000; de Bondt
et al., 2002). Other relevant macro-economic control variables are
structural ination, economic growth, and nancialdevelopment.22
Secondly, we collect four sets of variables describing the
nancialstructure of the euro zone: (1) market structure concerning
size and concentration,(2) bank protability and bank health, (3)
availability of alternative nance, and(4) foreign bank activities.
Following the tradition in the literature, we regress
thepass-though determinants directly on the multipliers.23 Our
analysis concentrateson the multipliers obtained from the monetary
policy approach for three reasons:First, retail interest rates
collected by the ECB are very heterogeneous acrossEurope, e.g. with
respect to the maturity structure of the loans or deposits.
Thus,selecting a cost-of-funds rate with a common maturity for all
countries is rather
481H. Sander, S. Kleimeier / Journal of International Money and
Finance 23 (2004) 461492arbitrary. Second, the monetary policy rate
has gained importance relative to cost-of-funds rate. Finally, as
monetary policy aects both, the cost-of-funds and theretail rate,
the monetary policy approach already covers an important part of
thecost-of-funds channel, particular when taking into account
forward looking beha-vior by market participants.
5.2. The role of competition
In the spirit of the industrial organization approach to
banking, higher concen-tration and lower competition are expected
to lead to a faster and larger pass-through. It is theoretically
not clear whether a concentration ratio or a Herndahlindex is the
most appropriate measure for market concentration (see Berger
andHannan, 1989). Therefore, we opt for an internal competition
index that avera-ges the ve-rm concentration ratio (CR5) and the
Herndahl index.24 To accountfor dierences across markets these
indicators are obtained for both, loan anddeposits markets. In a
similar way we construct a foreign competition indexwhich is
composed of the number of foreign bank branches and subsidiaries
andthe share of non-resident intermediated liabilities (loans) or
non-resident inter-mediated assets (deposits), respectively.Table 4
presents the results. We nd that more internal competition leads to
a
signicant reduction in price rigidities as indicated by the
internal competition
22 Financial development is typically measured by a ratio of
nancial assets or liabilities to GDP with
the view that the higher the ratio, the higher the degree of
nancial system development and the faster
the pass-through. The two most common measures are broad money
to GDP, reecting nancial dee-
pening on the asset side, and private credit to GDP, the most
comprehensive indicator of nancial
activities of intermediaries. We have employed both measures but
report only the results for credit to
GDP as this indicator performs better in the regressions.23 In
contrast to the speed regression reported in Table 3, we now focus
directly on the multipliers. This
choice is driven by the fact that increased competition could
lead to an increase in both, the short- and
long-run multiplier, so that speed may not change at all.24 Each
variable is transformed into an index number ranging from 0 to 1
with 1 indicating the highest
expected impact on the pass-through multipliers. For example, a
high concentration ratio results in a
low index number, which enters our internal competition
variable. Consequently, we expect a positive
coecient for this variable in the panel regression.
-
coecient in the regressions for the impact multiplier and for
the 1-month multi-
pliers. This coecient does, however, become insignicant from
three months
onwards and no long-run impact can be established. Surprisingly,
the coecient
H. Sander, S. Kleimeier / Journal of International Money and
Finance 23 (2004) 461492482for foreign competition is signicant but
has the wrong sign in all regressions. This
result as well as the missing long-run eect of internal
competition could be caused
by dierences between the loan and deposit markets.
Theoretically, the competition
eect should be more pronounced for deposit rates as these are
less aected by
informational imperfections than loans, which are more prone to
moral hazard and
adverse selection problems. To capture these dierences we
introduce deposit slope
dummies for both competition indicators. Our modied regressions
now show a
signicant positive impact of more internal and foreign
competition in the deposit
market in the short- and in the long run. Furthermore, the
results indicate that less
competition leads to faster downward than upward adjustment of
deposit rates.
This type of asymmetry is in line with our theoretical priors.
Regarding loans, a
signicant impact of internal competition can no longer be
established. This result
probably points to the more important role of other market
imperfections such as
the lack of contestability, switching cost, informational
imperfections, and thus
credit rationing in loan markets.25
With respect to the macroeconomic variables our results conrm
the positive
role of reduced volatility in the money market. This is,
however, only true for loan
rates and even there the eect diminishes over time as a
reduction in volatility does
not aect the long-run pass-through. In deposit markets, lower
volatility decreases
both the short- and long-term pass-through. High ination
typically leads to a
lower pass-through in deposit markets but not in lending
markets, possibly reect-
ing the role of market power. High growth is uniformly found to
increase the pass-
through in the long- but not in the short-run. Financial
development plays only a
marginally positive role.After controlling for nancial market
structure and macroeconomic dierences,
some retail rate dummies still remain statistically signicant.
In line with industrial
organization reasoning, short-term corporate loans show a higher
pass-through
while current and savings accounts markets exhibits more
stickiness. Country char-
acteristics are also persistent. Cecchetti (1999) hypothesizes
that cultural and legal
dierences may obstruct the convergence process in the euro zone.
To test this
hypothesis we include Cecchettis legal family dummies, in
particular a dummy for
the German legal system (used for Austria and Germany), for the
Scandinavian
legal system (used for Finland), and for the English legal
system (used for Ireland).
The results suggest that in particular in the German legal
system the pass-through
is signicantly lower.
25 A remaining puzzle is the statistically signicant and
negative coecient for foreign competition in
the loan market. This could possibly indicate that foreign banks
prefer to enter markets with low pass-
through.
-
Table4
Structuraldeterminantsoftheinterestr
atepassthroughforthemonetary
policy
approach:Theroleofcompetition
Independentvariablesa
Dependentvariable
impactmultiplier
1month
multiplier
3monthsmultiplier
+1%
shock
+1%
shock
1%
shock
1%
shock
+1%
shock
+1%
shock
1%
shock
1%
shock
Constant
0.492
0.601
0.435
0.573
0.435
0.573
0.509
0.711
0.430
0.631
2.871
3.587
1.753
2.307
1.753
2.307
1.812
2.603
1.460
2.197
internalcompetition
0.213
0.146
0.300
0.178
0.300
0.178
0.227
0.064
0.224
0.076
2.223
1.407
2.161
1.155
2.161
1.155
1.443
0.378
1.356
0.426
internalcompetition
deposit
0.196
0.303
0.303
0.420
0.397
1.963
2.045
2.045
2.577
2.316
foreigncompetition
0.289
0.488
0.419
0.625
0.419
0.625
0.563
0.885
0.536
0.875
2.102
3.370
2.107
2.910
2.107
2.910
2.503
3.751
2.270
3.523
foreigncompetition
deposit
0.346
0.313
0.313
0.513
0.561
2.838
1.729
1.729
2.583
2.680
money
marketvolatility
0.083
0.094
0.126
0.137
0.126
0.137
0.122
0.140
0.096
0.115
2.262
2.685
2.372
2.630
2.372
2.630
2.042
2.452
1.525
1.910
money
market
volatilityd
eposit
0.162
0.165
0.243
0.240
0.243
0.240
0.267
0.266
0.249
0.250
3.435
3.642
3.563
3.580
3.563
3.580
3.465
3.610
3.070
3.220
ination
0.026
0.016
0.006
0.016
0.006
0.016
0.029
0.044
0.012
0.029
1.119
0.698
0.185
0.466
0.185
0.466
0.739
1.187
0.296
0.740
inationd
eposit
0.063
0.114
0.110
0.162
0.110
0.162
0.122
0.203
0.111
0.197
2.433
3.878
2.913
3.717
2.913
3.717
2.863
4.256
2.496
3.923
growth
0.036
0.046
0.014
0.024
0.014
0.024
0.016
0.000
0.045
0.028
1.381
1.840
0.365
0.646
0.365
0.646
0.367
0.010
1.001
0.648
creditto
GDP
0.051
0.024
0.232
0.193
0.232
0.193
0.198
0.144
0.241
0.189
0.508
0.251
1.584
1.346
1.584
1.346
1.197
0.911
1.391
1.137
N4short-termloans
toenterprises
0.029
0.047
0.138
0.155
0.138
0.155
0.211
0.239
0.187
0.217
0.678
1.145
2.246
2.563
2.246
2.563
3.030
3.581
2.558
3.088
N7currentaccount
deposits
0.192
0.183
0.285
0.276
0.285
0.276
0.375
0.360
0.399
0.384
3.358
3.353
3.445
3.415
3.445
3.415
3.998
4.052
4.059
4.101
(continued
onnextpage)
483H. Sander, S. Kleimeier / Journal of International Money and
Finance 23 (2004) 461492
-
Table4(continued)
Independentvariablesa
Dependentvariable
impactmultiplier
1month
multiplier
3monthsmultiplier
+1%
shock
+1%
shock
1%
shock
1%
shock
+1%
shock
+1%
shock
1%
shock
1%
shock
N9savings
accounts
0.175
0.300
0.244
0.371
0.244
0.371
0.255
0.454
0.271
0.482
3.136
4.536
3.023
3.783
3.023
3.783
2.785
4.215
2.823
4.249
Germanlegalsystem
0.173
0.211
0.227
0.271
0.227
0.271
0.163
0.228
0.164
0.231
2.367
2.989
2.145
2.583
2.145
2.583
1.357
1.983
1.303
1.908
Scandinavianlegal
system
0.197
0.228
0.291
0.334
0.291
0.334
0.350
0.411
0.396
0.456
2.392
2.864
2.441
2.836
2.441
2.836
2.597
3.178
2.800
3.343
English
legalsystem
0.461
0.611
0.418
0.582
0.418
0.582
0.274
0.524
0.060
0.319
2.352
3.173
1.473
2.039
1.473
2.039
0.853
1.673
0.178
0.968
Adjusted
R2
29.5%
35.9%
37.0%
40.1%
37.0%
40.1%
39.7%
45.9%
38.2%
44.1%
independentvariablesa
dependentvariable
6monthsmultiplier
12monthsmultiplier
longr
unmultiplier
+1%
shock
+1%
shock
1%
shock
1%
shock
+1%
shock
+1%
shock
1%
shock
1%
shock
Constant
0.484
0.696
0.345
0.561
0.350
0.577
0.242
0.493
0.213
0.485
1.688
2.498
1.153
1.936
1.149
1.948
0.748
1.587
0.608
1.442
internalcompetition
0.185
0.006
0.180
0.015
0.154
0.069
0.125
0.078
0.068
0.151
1.155
0.032
1.077
0.082
0.901
0.375
0.692
0.407
0.348
0.723
internalcompetition
deposit
0.469
0.437
0.529
0.523
0.565
2.825
2.525
2.994
2.822
2.814
foreigncompetition
0.605
0.918
0.468
0.824
0.539
0.851
0.352
0.751
0.441
0.876
2.635
3.815
1.951
3.289
2.207
3.325
1.361
2.801
1.570
3.012
foreigncompetition
deposit
0.472
0.581
0.445
0.636
0.696
2.330
2.752
2.063
2.813
2.838
money
marketvolatility
0.094
0.110
0.080
0.100
0.057
0.073
0.060
0.082
0.010
0.014
1.532
1.895
1.254
1.646
0.874
1.178
0.876
1.267
0.128
0.203
H. Sander, S. Kleimeier / Journal of International Money and
Finance 23 (2004) 461492484
-
money
market
volatilityd
eposit
0.287
0.282
0.283
0.283
0.285
0.276
0.291
0.289
0.231
0.229
3.643
3.750
3.436
3.611
3.401
3.453
3.279
3.452
2.392
2.518
ination
0.051
0.065
0.047
0.064
0.074
0.087
0.080
0.099
0.050
0.071
1.286
1.716
1.143
1.639
1.771
2.176
1.800
2.351
1.030
1.545
inationd
eposit
0.137
0.216
0.134
0.224
0.145
0.224
0.146
0.247
0.129
0.239
3.147
4.430
2.951
4.416
3.149
4.329
2.986
4.552
2.426
4.058
growth
0.052
0.036
0.079
0.061
0.086
0.070
0.093
0.073
0.125
0.104
1.191
0.874
1.728
1.403
1.848
1.587
1.899
1.582
2.350
2.059
creditto
GDP
0.118
0.059
0.181
0.123
0.082
0.016
0.140
0.073
0.149
0.075
0.701
0.368
1.025
0.736
0.455
0.095
0.736
0.404
0.719
0.387
N4shorttermloans
toenterprises
0.269
0.295
0.227
0.258
0.296
0.321
0.261
0.295
0.215
0.252
3.790
4.347
3.060
3.645
3.919
4.444
3.259
3.898
2.472
3.072
N7currentaccount
deposits
0.412
0.399
0.441
0.425
0.430
0.417
0.462
0.444
0.483
0.463
4.312
4.395
4.421
4.505
4.234
4.322
4.281
4.390
4.124
4.223
N9savingsaccounts
0.249
0.442
0.287
0.509
0.230
0.421
0.277
0.524
0.248
0.518
2.675
4.024
2.946
4.443
2.322
3.602
2.630
4.277
2.172
3.898
Germanlegalsystem
0.110
0.176
0.091
0.163
0.056
0.125
0.033
0.115
0.002
0.087
0.899
1.501
0.714
1.332
0.431
0.998
0.242
0.878
0.013
0.612
Scandinavianlegal
system
0.384
0.451
0.392
0.457
0.358
0.431
0.319
0.395
0.282
0.364
2.793
3.414
2.730
3.323
2.449
3.071
2.058
2.686
1.673
2.281
English
legalsystem
0.027
0.276
0.233
0.042
0.271
0.017
0.449
0.139
0.567
0.229
0.082
0.863
0.679
0.126
0.778
0.051
1.215
0.389
1.413
0.592
adjusted
R2
45.0%
50.7%
42.7%
48.9%
45.2%
50.9%
40.9%
48.2%
35.4%
43.4%
Note:Thesamplesize
foreach
regressionis102observationspooledacrossperiods(pre-break,post-break),countries(Austriato
Spain),andrates(N
1to
N10).
aForeach
independentvariabletheestimatedcoe
cientisreported
inthetoprowandthet-statisticisreported
initalics
inthebottom
row.Theesti-
matesarebasedonanOLSregression.
485H. Sander, S. Kleimeier / Journal of International Money and
Finance 23 (2004) 461492
-
5.3. The role of banking market structure and monetary policy
eectiveness
The pass-through analysis can also be employed to investigate
the role of nan-cial markets in the eectiveness of monetary policy
transmission. Kashyap andStein (1997) and Cecchetti (1999) have
argued that a composite measure of mon-etary policy eectiveness,
consisting of measures of bank health, number ofbanks, and
availability of alternative nance, can explain the high level of
monet-ary policy eectiveness in Europe. They argue that small and
unhealthy banks aremore heavily aected by shocks and that the
transmission to the real economy willbe stronger the less
alternative nance is available. We employ a similar eective-
H. Sander, S. Kleimeier / Journal of International Money and
Finance 23 (2004) 461492486ness indicator. As we concentrate on the
nancial market side of the transmissionprocess only, we do make
some adjustments, particularly by adding a measure forbanking
market competition. Our eectiveness indicator is thus composed of
fourdimensions: Internal competition, alternative nance, bank
health, and importanceof small banks.26 The rationale might be as
follows: A monetary tightening mightshift the loan supply curve
especially of small and unhealthy banks. Whether thisleads to a
fast increase in lending rates depends on the elasticity of the
loandemand curve and the degree of lending rate stickiness or
credit rationing in thecredit market. For any given monetary shock,
the less competitive the market andthe less elastic the demand for
loans, i.e. the less alternative nance is available, thelarger will
be the increase in lending rates.27 Consequently, we expect a
positiveimpact of our eectiveness indicator on the pass-through.In
Table 5 the results of our regression analyses are reported.
Overall, our eec-
tiveness indicator has the expected positive sign and is
signicant for all multipliersexcept the impact multiplier.
Moreover, the eectiveness indicator becomes moreimportant the
longer the time-horizon of the multiplier. As far as foreign
compe-tition is concerned, the coecient has the wrong sign but is
not statistically signi-cant. However, when introducing a deposit
slope dummy, foreign competition hasa positive eect in the deposit
markets. With respect to the macroeconomic vari-ables, we can again
conrm the positive role of reduced money market rate vola-tility
particularly over the rst six months. In a similar manner, both,
higherination and less nancial development lead to a slower
pass-through, but theeects are only statistically signicant in the
rst few months. During this timeeconomic growth seems unimportant.
However, in the longer term, higher growth
26 More specically, we dene eectiveness as the equally weighted
average of internal competition,
alternative nance, and bank size and health. The denitions for
the 3 elements in this indicator are:
Internal competition CR5Herfindahl=2 with both variables based
on either loans or deposits,respectively; alternative finance
publicly traded firms stock market capitalization
intermediatedliabilities=3; bank size and health loan provisions
operating cost number of banks=3. Again,for building the index each
included variable was transformed into an index number ranging from
0 to 1
with 1 indicating the highest expected impact on the
pass-through multipliers.27 This contradicts the view that more
alternative nancesuch as high stock market capitalization
will lead to a more competitive banking market and thus faster
pass-through. In fact, it appears that our
indicators for the availability of alternative nance are
negatively correlated with the pass-through mul-
tipliers thus supporting the loan demand-side view.
-
Table5
Structuraldeterminants
oftheinterest-rate
pass-through
forthemonetary
policy
approach:Therole
ofbankingmarket
structure
andmonetary
policy
eectiveness
Independentvariablesa
Dependentvariable
impactmultiplier
1month
multiplier
3monthsmultiplier
+1%
shock
+1%
shock
1%
shock
1%
shock
+1%
shock
+1%
shock