Asymmetric Adjustment of Commercial Bank Interest Rates in the Euro Area Implications for Monetary...

8/2/2019 Asymmetric Adjustment of Commercial Bank Interest Rates in the Euro Area Implications for Monetary Policy

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ASYMMETRIC ADJUSTMENT OF COMMERCIAL BANK INTEREST RATES IN

THE EURO AREA: IMPLICATIONS FOR MONETARY POLICY

by

Harald Sander

and

Stefanie Kleimeier

Abstract:

This study provides an empirical analysis of asymmetries in the transmission of policy rate innovations on bank

lending rates. Our study extends on the existing literature by conducting cointegration analyses that explicitly

test for structural breaks and for asymmetric upward and downward adjustment in interest rates. Comparing the

empirical results for 12 European countries reveals that the speed of adjustment of lending rates to policy rate

changes differs widely within the EMU, implying that the ECB is still confronted with an asymmetric EMU that

complicates the conduct of a single monetary policy.

JEL Classification:Numbers: E43, E52, E58, F36

Keywords: Interest Rates, Monetary Policy, European Monetary Union, Asymmetric

Adjustment, Cointegration Analysis, Structural Breaks

The authors are from the University of Applied Sciences Cologne and the Maastricht University, respectively.

S. Kleimeier would like to acknowledge the financial support from METEOR.

All comments are welcome. Please contact:

Prof. Dr. Harald Sander

University of Applied Sciences Cologne

Claudiusstr. 1

50678 KlnGermany

Phone: ++49-208-853691

Fax: ++49-221-8275-3131

e-mail: [email protected]


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Shooting at a moving target in the fog is no easy task.

Dornbusch, Favero and Giavazzi (1998)

The markets are asymmetric; we are not.

Alan Greenspan (1999)

1. Introduction

Since January 1, 1999 the new European Central Bank has to conduct a one-size-fits-all monetary

policy based on her assessment of the average economic conditions of the 11 member countries of the European

Monetary Union (EMU). Next to the usual issues and controversies in monetary policy making this implies three

new challenges: (1) determining the appropriate average monetary policy in case of diverging economic

conditions in the Euro area, (2) dealing with possible asymmetric effects of that monetary policy in different

member countries, i.e. a divergent monetary transmission mechanism which (3) is most likely subject to

dramatic changes (convergence?) as financial market integration and restructuring alongside EMU evolves.

While the first challenge has always been at the heart of the controversies about a common currency and

attracted a lot of public attention in the first half of 1999 as the cyclical position of the Euro area member

countries appeared to diverge1, the second issue has only recently become an important topic in empirical

research. While the latter development is to be welcomed, challenge #3 should remind us that judgements about

the workings of the monetary mechanism that are based on past data could be profoundly misleading in the

context of a regime change. Our paper focuses on the latter two challenges by providing evidence on

symmetries, asymmetries, and changes in the monetary mechanism in EMU member countries with particular

reference to the financial market side of the transmission process.

Since Franco Modigliani (1963) the monetary mechanism has been described to consist of two parts: the

financial market reaction and the wage-price mechanism. While many recent studies have been examining the

impact of monetary policies on the real economy (e.g. Ramaswany and Sloek 1997) our study concentrates on

the financial market reaction. There are a number of good reasons to do so: First, while there is evidence that the

wage-price process is different across Europe, the Lucas principle suggests that this very process may adopt to

the European focus of the ECBs monetary policy (Dornbusch et.al. 1998). Financial markets, however, may be

more resistant to convergence. E.g. Cecchetti (1999. p. 22) argues that ...differences in financial structure are

the proximate cause for these national asymmetries in the monetary policy transmission mechanism, and adds

that unless legal structures are harmonized across Europe, financial structures will remain diverse, and so will


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the monetary transmission mechanism. Kleimeier and Sander (2000) show that the attempt to integrate the

European financial markets by means of regulations (like the 2nd

Banking Directive) alone has brought little

convergence in lending conditions so far. Secondly, given the high proportion of bank finance in Europe relative

to the US/UK - as shown in Table 1 - the lending channel is an important element in the monetary mechanism

in Europe as has been suggested by the advocates of the credit view (e.g. Bernake and Gertler 1995, Kashyap

and Stein 1994). If loans and bonds are imperfect substitutes in the balance sheets of banks and firms, and firms

cannot simply access the capital markets but have to rely on bank finance, the transmission of monetary policy

impulses is necessarily linked to bank behaviour. Third, if the structure of the financial system matters as a

conveyer of monetary policy, these structural differences can lead to asymmetries in European financial

markets reaction and thus monetary policy transmission. In Germany, for example, the close bank-firm

relationship tends to weaken the policy-determined interest rate lending rate link, while in economies like the

British the like is known to be much more direct.

- insert Table 1 here -

Our study provides an empirical analysis of asymmetries in European financial markets by means of

examining how innovations in policy rates are passed onto lending rates as an important element for the speed of

the monetary transmission process. Until recently, the literature has often neglected this issue. Exemptions are

e.g. Cotarelli and Kourelis (1994), who focus on the role of lending rate stickiness and its structural

determinants, Cotarelli, Ferri, and Generale (1995), BIS (1995) and IMF, World Economic Outlook October

(1996). Dornbusch et. al. (1998) review this literature with respect to the financial market reaction in potential

EMU member countries and find that the characteristics of the financial system ....go some way towards

explaining the observed asymmetries in the transmission mechanism. Our study extends on this literature in

four important aspects:

1. The link between policy rates and lending rates is analysed in a cointegration approach that tests and allowsfor structural breaks in order to examine the impact of changing conditions on financial market performance

so far.

2. The speed of adjustment to monetary policy innovations are measured by country differences in the errorcorrection terms of the cointegration regression.

1

In mid-1999 public discussions about increasingly diverging development in production and prices in the EMU

member countries abound. The ECB examines this issue in its July 1999 monthly bulletin.


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3. Recent research has shifted toward analysing asymmetric adjustment in interest rates (see Enders andGranger, 1998; and Scholnick 1996). As adjustments to innovations in monetary policy may differ when the

lending rate is above or below its long run equilibrium level we test also for asymmetric upward and

downward adjustment.

4. Finally we compare cross-country asymmetries in upward and downward adjustments.

In sum, the relationship between national policy interest rates and commercial bank prime lending rates

of EMU member countries is analysed by employing cointegration methodology for the 10 EMU member

countries plus the United Kingdom and Greece in the period of 1984 to 1998, allowing for endogenously

determined structural breaks and asymmetric adjustment towards a long-run equilibrium. Our results will show

that the speed of adjustment of lending rates to innovations in policy interest rates still differs widely across

countries. In five countries we find either no cointegration (France, Germany, Ireland) or statically insignificant

error correction processes (Finland, Spain). In the remaining seven countries adjustment processes are partly

symmetric (UK, Portugal, Italy) and partly asymmetric (Belgium, Luxembourg, Netherlands, Greece). Provided

the introduction of the common currency will not eliminate these differences in the transmission mechanisms

over time, the ECB will be facing the difficult task of formulating and implementing a single monetary policy in

a Euro area where the effects of this policy will remain different across member countries.

2. Data and Methodology

In order to analyse the relationship between central bank policy rates and commercial bank lending

rates, monthly interest rates have been collected from the CD-ROM version of the IMF's International Financial

Statistics (IFS) for the following European countries: Belgium, Finland, France, Germany, Ireland, Italy,

Luxembourg, The Netherlands, Portugal, and Spain as EMU member states and Greece and the United Kingdom

as non-EMU member states.2 As lending rates the rates listed in line 60p of the IFS have been used whereas the

central bank discount rates listed in line 60 have been used as policy rates. Exceptions to this sampling procedure

were the following: Due to changes in central bank policy, rates from line 60a were used for France as of July

1989 and for the Netherlands as of January 1994. For the United Kingdom, no policy rates were available and

money market rates of line 60b have been used instead. For Luxembourg, the Luxembourg lending rates were

2

Austria, Denmark, and Sweden are not included in this study since monthly lending rates were not available

from the IFS for the full period under investigation.


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used but Belgian rates were used as policy rates due to the monetary union between Belgium and Luxembourg.

Descriptive statistics for each interest series are presented in Table 2 for the full sample period of January 1985

to December 1998 and for the post-break period used in the cointegration analysis of January 1994 until

December 1998. The time-series of the respective series are shown in Figure 1.

- insert Table 2 and Figure 1 here -

The cointegration analysis applied in this study proceeds in three steps as promoted by Engle and

Grangers (1987) followed by an extension of Engle and Grangers basic error correction model, which allows

differentiation between an upward and a downward adjustment of interest rates. Before cointegration analysis

can proceed, it must be ensured that all interest rate time series have unit roots. As Kleimeier and Sander (2000)

have shown, time series of European money market and lending rates exhibit structural breaks in the early 1990s

which reflect the changes in the European banking market brought about by the Second Banking Directive. Such

a structural break has two specific implications for cointegration analysis. First, if a structural break at an priori

unknown point in time is present in a time series, the unit root tests proposed by Engle and Granger (1987) have

very little power. Better specified test statistics as proposed by Banerjee, Lumsdaine, and Stock (1992) which are

consistent even in the presence of structural breaks will therefore need to be employed. Second, a time period

free of structural breaks in the cointegration relationship has to be identified otherwise the interpretation of the

cointegration vector will result in misleading conclusions. As Quandt (1960), Andrews (1993), Diebold and

Chen (1996), and Hansen (1992) show, a supremum F test allows the exact determination of the timing of such a

structural break. Once the break has been determined, the complete cointegration analysis can then be conducted

for the pre and post-break periods separately. In particular, our study will focus on the post-break period only.

More formally, our methodology can be described as follows: In order to establish whether interest

rates or spreads are I(1), two sets of test statistics will be employed based on regressions on levels as well as first

differences for each national interest rate series zt. The first set includes the t- and F-tests proposed by Engle and

Granger. The second set includes tests particularly designed to provide reliable results in the presence of a

structural break. The t- and F-tests are based on a level regression includes next to lagged observations of the

interest rate in question zt-1 also a trend variable T and on the corresponding regression for first differences:

(1) zt = + zt-1 + zt-1 + T + t


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(1B) 2zt = + zt-1 +

2zt-1 + T + t

The null hypothesis stating that the series follow random walks corresponds to H0: =0 for the t-statistic and to

H0: ==0 for the F-statistic.

In the presence of structural breaks at an -priory unknown point in time, the above two unit root tests

have very little power. Better specified are the following test statistics proposed by Banerjee, Lumsdaine, and

Stock (1992). Using equation (1A) and (1B), recursive minimum -statistics can be calculated in order to test the

null-hypothesis of=03. Furthermore, sequential unit root tests that distinguish between a shift in the mean or the

trend of the series can be calculated based on the following regressions for levels and first differences:

(2) zt = + zt-1 + zt-1 + T + D + t

(2B) 2zt = + zt-1 +

2zt-1 + T + D+ t

where D indicates a dummy variable. For the mean-shift tests, D is coded as 1 if t > k and 0 otherwise. For the

trend-shift tests, D is coded as t if t > k and 0 otherwise. Here, both minimum -tests regarding H0: =0 and

maximum F-tests regarding H0: ==0 can be calculated and compared to the critical values4.

Once the I(1) characteristic has been established, cointegration testing can commence. First, it has to be

established whether or not the cointegration vector is characterised by a structural break and if so, when this

break takes place. This is important since in the presence of a structural break, the standard cointegration tests

such as those proposed by Engle and Granger have low power, i.e. the rejection frequency of the ADF test is

clearly reduced (e.g. Gregory et. al., 1996). The cointegration relationship is described by equation (3) using the

3

This unit root test is based on a series of sub-samples which span one quarter of the total sample each and

comprise data from t = 1 to k, t = 2 to k+1, until t = n to T. The recursive min- is found as the smallest t(k/T)

over all sub-samples. To reject the null-hypothesis, the calculated min -value which has to be smaller than thecritical value.4 In particular, a series of regressions is run on the full sample so that different k can be chosen in accordance

with Banerjee et als suggestion to move k through the mid-70% of the total sample. Similar to the recursive test,

a minimum -value is calculated as the smallest t(k/T) over all sub-samples.


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lending rate y t for the individual country as the dependent variable and the policy rate xt of the same country as

the independent variable:

(3) yt = 1 + 2 xt + ut

To test for structural breaks a supremum F (supF) test is calculated. This test was first proposed by Quandt

(1960) and has recently been the focus of various studies (e.g. Andrews 1993, Diebold and Chen 1996, Hansen

1992). This test can be seen as a rolling Chow test and is more flexible than the standard Chow test because it

allows simultaneously to test for the significance and the timing of a structural break in the cointegration

relationship5. If a break is present, the cointegration analysis will proceed focussing on the post-break period

only.

Following Engle and Granger (1987), Durbin-Watson (DW) statistics are obtained from equation (3),

followed by Dickey-Fuller (DF) and augmented Dickey-Fuller (ADF) tests. The Dickey-Fuller tests are based on

the residuals of the cointegration regression

(4) ut = - ut-1 + t

where the t-statistic for the estimated coefficient provides an indication regarding the cointegration of the two

series. The augmented Dickey-Fuller test is obtained from the regression

(5) ut = -0 ut-1 + iiut -i + t

Once cointegration is established, the corresponding error correction model (ECM) will be estimated in

order to investigate the speed of adjustment of lending rates to changes in policy rates. Here, both a symmetric

ECM as well as an asymmetric ECM is estimated. This distinction allows us to investigate possible differences

in adjustment when rates are above versus below their equilibrium level. To find the correct specification of the

5

In particular, a series of standard Chow tests are conducted for a series of different break points k, which move

through the mid-70% of the sample. SupF equals the largest Chow F-statistic and is compared to critical values

as reported by Hansen (1992). The sequence of F-statistics can give an indication about the timing of the break.


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ECM, the procedure suggested by Engle and Granger (1987) is followed. First, an unrestricted vector

autoregression (UVAR) is estimated based on the regression

(6) yt = 0 + 1 yt-1 + 2 xt-1 + iyiyt -i + ixixt -i + t

with a maximum lag structure of i=12. From this regression, the significant lagged first differences of the

exogenous and endogenous variables are identified and included in the final ECM in combination with any error

correction terms ECT obtained from the estimated errors that were found significant in the cointegration

regressions stated in equation (3). Note also that the same lag-structure is used for the symmetric as for the

asymmetric ECM. The speed of adjustment in the symmetric ECM can now be found by regressing

(7) yt = 0 + 1 ECTt-1 + iyiyt -i + ixixt -i + t

The estimated coefficient 1of the ECT measures the speed of adjustment. For example an estimated 1of -0.2

indicates that if there is a shock to the variable y t which changes its value relative to the equilibrium relationship

to the cointegrated series xt, then one fifth of the divergence is eliminated in the following period.

In the asymmetric model, a distinction is being made to whether the interest rates are below or above

their equilibrium levels6. The ECT from the cointegration regression is separated into two components such that

(8) ECT+

t = ECTt if ECTt > mean(ECT)

ECT+

t = 0 otherwise

and

(9) ECT-t = ECTt if ECTt < mean(ECT)

ECT-t = 0 otherwise

The speed of adjustment in the asymmetric ECM can now be found by regressing

6

A similar approach has been used by Scholnick (1996), who however focuses on short-run dynamics different

to the ones used here is equation (6) and (7).


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(9) yt = 0 + 1 ECT+t-1 + 2 ECT

-t-1 + iyiyt -i + ixixt -i + t

The estimated coefficient 1of ECT+

measures the speed of adjustment when rates are above their equilibrium

level, whereas the estimated coefficient 2of ECT-

measures the speed of adjustment when rates are below their

equilibrium level. A result of1 = -0.3 versus 2=-0.6 would indicate that if a shock to variable yt which raises

its value relative to the equilibrium relationship to the cointegrated series xt, it takes only half as long for the

divergence to be eliminated than if a shock to variable yt decreases its value relative to the equilibrium

relationship to the cointegrated series xt. Finally, an F-test regarding the null-hypothesis 1 = 2 indicates

whether the speed of adjustment is significantly different for above- and below-equilibrium levels.

3. Results and conclusions

Table 3 provides an overview of the different unit root test statistics employed in this study to test

whether or not the interest rate series under consideration fulfil the requirement of being I(1). Overall, we are

confident that cointegration analysis can proceed for all national series with the exception of Ireland, where

lending rates appear to be I(0). Thus, special care should be taken when interpreting the results for Ireland in the

remainder of the paper.


Table 4 provides evidence for the presence of a structural break in the cointegration relationship in each

country with the exception of France. For the other countries the break occurs between August 1987 and

December 1993. These breaks are similar to those detected by Kleimeier and Sander (2000) and can be attributed

to the changes in the national banking systems as brought about by the second banking directive. As it is the

objective of this study to focus on the transmission mechanism as it was in place right at the introduction of the

EMU, the cointegration analysis will only focus on the post-break period. Consequently, a sample period free of

breaks and common to all countries will be selected which ranges from January 1994 until December 1998.



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The main results of our study are summarized in Table 5 and visualised in Figure 2. Looking first at the

Durbin-Watson and the Dickey-Fuller test statistics reveals that on the broadest level, two groups of countries

exist in Europe: Those for which cointegration could be established implying an existing lending channel for the

transmission of monetary policy and those for which cointegration could not be established. France, Germany,

and Ireland belong to the latter group, whereas the remaining countries belong to the former group. Note,

however, whereas the evidence in favour of cointegration is strong for Belgium, Italy, the Netherlands, Portugal,

and Spain, only marginal evidence could be found for Finland, Luxembourg, Greece, and the United Kingdom.

For these nine countries for which some level of cointegration could be detected, the estimated coefficients of

the error correction terms in the symmetric and asymmetric ECM reveal a further separation of countries into

two groups: Those for which the adjustment of lending rates to a policy rate shock is symmetric and those for

which the adjustment is asymmetric. For Finland, Italy, Portugal, Spain, and UK the F-test reported in the last

column of Table 5 is not significant and therefore 1, the coefficient of the symmetric ECT is relevant. In these

five countries, the speed of adjustment differs widely. In Finland, Italy, and Spain the coefficient is

insignificantly different from zero indicating that even if cointegration could statistically be found, the time of

adjustment is infinitively long. For Portugal and the UK, the estimated coefficient of 0.121 and 0.166

respectively indicate that lending rates fully adjust to shocks in policy rates within 6 to 8 months. In Belgium,

Luxembourg, the Netherlands, and Greece the adjustment of lending rates to policy rate changes is asymmetric

in nature as the F-statistics in Table 5 indicates. For all countries in this group, the adjustment is faster if rates are

above the equilibrium level as is indicated by the finding that 1 is smaller than 2. It is interesting to note that

the divisions between cointegrated versus non-cointegrated interest rates and between symmetrically versus

asymmetrically adjusting interest rates do not correspond neither to the distinction into EMU members and non-

members, nor to that of EMU-core and non-core members (see also Dornbusch et. al., 1998). Overall, our

findings indicate the presence of cross-country differences in the adjustment processes of commercial bank

interest rates to policy rate changes within and outside the Euro area.

In sum, our study confirms that monetary policy in the Euro area is still to be conducted under the

conditions of an "asymmetric EMU" of which the differences in the way the different banking systems in Euro

area countries work are arguably among the most important ones7. We found not only that the speed of

adjustment is different across countries of actual and prospective EMU member countries, but also that this

7

For a most recent statement on the "asymmetric EMU" see Corsetti and Pesenti in their September 1999 paper

presented at the Brookings panel.


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speed differs in terms of an asymmetric upward and downward adjustment process. Such asymmetries are

present in some but not all countries under investigation, suggesting the necessity to include asymmetric models

in the analysis. While optimists hope that the elimination of currency risks may contribute to an institutional

harmonization within EMU the evidence provided here suggests that for the nearer future asymmetries will

continue to influence the monetary mechanism within the Euro area.


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Table 1: The Relative Importance of Bank Finance in Europe

Panel A: The Relative Importance of Bank Finance in Europe by Countries in 1996

Country Market Capitalization as a

Percentage of GDP

Corporate Debt as a

Percentage of GDP

Bank Loans as a Percentage

of all forms of Finance

EMU Members

Austria 15 46 65

Belgium 45 60 49

Finland 50 34 39France 38 49 49

Germany 29 58 55

Ireland 18 13 80

Italy 21 37 50

Netherlands 96 48 53Portugal 23 19 62

Spain 42 11 58

Members of the EU not in EMU

Denmark 41 105 25

Greece 20 3 48

Sweden 99 73 32United Kingdom 150 45 37

Other Countries

Japan 67 39 59

USA 111 64 21

Source: Stephen G. Cecchetti, Legal Structure, Financial Structure, and the Monetary Transmission

Mechanism, Federal Reserve Bank of New York Economic Policy Review, July 1999, p.16

Panel B: The Relative Importance of Bank Finance in the Euro Area, USA and Japan in June 1999a

(as percentage of GDP)

Euro Area USA Japan

Bank Loans 100.4 48.4 107.0

Outstanding domestic debt securities 88.8 164.6 126.5

- issues by corporates 3.3 29.0 14.6

- issued by financial institutions 31.0 45.4 18.8

- issued by the public sector 54.5 90.2 93.1

Stock Market Capitalization 71.1 163.3 137.7

Source: ECB Monthly Bulletin, January 2000, p.39, own calculationsa

All data are June 1999 except for stock market capitalization which are October 1999


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Table 2: Monthly Policy and Lending Rates for EMU Members and Non-Members

Policy Rates Lending RatesCOUNTRY

PeriodMean Standard

Deviation

Mean Standard

Deviation

Belgium

01:1985 12:1998 6.58 2.75 10.10 2.22

01:1994 12:1998 3.29 0.87 7.86 1.00

Finland

01:1985 12:1998 6.75 1.83 9.03 5.1801:1994 12:1998 4.56 0.59 6.49 1.17

France

01:1985 12:1998 7.35 2.58 8.95 1.54

01:1994 12:1998 4.09 0.98 7.13 0.76

Germany

01:1985 12:1998 4.50 1.85 10.43 1.71

01:1994 12:1998 3.25 0.96 10.12 1.01

Greece

01:1985 12:1998 19.19 1.81 23.73 3.82

01:1994 12:1998 18.19 2.71 21.79 3.41

Ireland

01:1985 12:1998 9.06 2.44 9.25 3.10

01:1994 12:1998 6.50 0.54 6.27 0.62

Italy

01:1985 12:1998 10.60 3.03 13.31 2.61

01:1994 12:1998 7.15 1.53 10.68 1.78

Luxembourg01:1985 12:1998 6.58 2.75 7.13 1.17

01:1994 12:1998 3.29 0.87 5.87 0.57

Netherlands

01:1985 12:1998 4.93 1.90 8.99 2.26

01:1994 12:1998 3.19 0.99 6.80 0.92

Portugal

01:1985 12:1998 13.40 5.66 17.45 5.67

01:1994 12:1998 7.25 2.33 11.39 2.97

Spain

01:1985 12:1998 10.74 3.56 11.87 3.6901:1994 12:1998 6.70 1.80 7.72 1.96

United Kingdom

01:1985 12:1998 9.11 3.26 9.33 3.11

01:1994 12:1998 6.06 0.92 6.38 0.69


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15

Table 3: Unit Root Tests for Time Series of Monthly National Interest Rates from January 1985 until December 1998Levels First Differences

t(b) F recursive

min mean-shift

min mean-shift

max Ftrend-shift

min trend-shift

max Ft(b) F recursive

min mean-shift

min mean-shift

max Ftrend-shift

min trend-shift

max F

Country

Policy Rates

Belgium -1.72 1.50 -1.72 -1.89 8.78 -1.98 9.04 -9.14 41.81 -9.14 -7.77 49.48 -7.82 49.82

Finland -1.35 1.08 -1.41 -2.50 17.24 -3.25* 21.02* -7.40 27.47 -7.40 -6.28 35.26 -6.31 32.93

France -1.69 2.21 -1.69 -3.18 17.36 -3.87* 22.13* -7.77 30.18 -7.77 -6.78 35.14 -6.82 33.61

Germany -0.66 0.81 -1.27 -1.89 17.62 -2.51* 18.92* -8.39 35.16 -8.39 -7.17 61.43 -7.22 53.60

Greece -0.71 1.16 -1.43 -2.13 8.85 -2.26 8.83 -8.62 37.14 -8.62 -7.37 49.20 -7.42 47.41

Ireland -1.97 3.11 -2.49 -2.15 8.44 -2.18 9.09 -7.43 27.63 -7.44 -6.28 29.54 -6.33 30.00Italy -1.21 1.13 -1.69 -1.53 8.65 -1.62 10.37 -6.78 23.02 -6.95 -5.79 28.89 -5.82 28.42

Luxembourg -1.72 1.50 -1.72 -1.89 8.78 -1.98 9.04 -9.14 41.81 -9.14 -7.77 49.48 -7.82 49.82

Netherlands -1.07 0.68 -1.16 -1.87 15.01 -2.38 15.98 -6.70 22.48 -6.70 -5.88 33.55 -5.91 30.96

Portugal -2.78 3.89 -2.79 -2.48 11.63 -2.68 13.15 -14.13 99.87 -14.13 -11.91 112.90 -12.00 110.74

Spain -2.50 3.70 -2.57 -2.39 7.37 -2.40 7.22 -6.01 18.06 -6.01 -5.06 21.25 -5.10 26.73

United Kingdom -1.56 1.29 -1.56 -1.72 9.06 -1.69 10.27 -9.64 46.48 -9.64 -8.13 53.06 -8.18 56.58

Lending Rates

Belgium -1.47 1.10 -1.49 -2.50 10.93 -2.77 11.42 -8.70 37.86 -8.70 -7.38 42.00 -7.43 43.51

Finland -1.63 1.34 -1.25 -1.82 14.48 -2.61* 16.74* -6.45 20.84 -6.45 -5.56 29.89 -5.60 25.89

France -1.41 1.01 -1.47 -2.14 10.77 -2.52 11.64 -9.23 42.58 -9.23 -7.86 48.43 -7.91 53.33

Germany -0.23 1.02 -1.41 -1.19 19.11* -1.92* 22.55* -6.97 24.32 -6.97 -5.88 49.94 -5.93 46.68

Greece -0.35 3.68 -1.05 -2.24 9.90 -2.62 10.31 -8.36 34.95 -8.36 -7.09 40.31 -7.13 42.22

Ireland -3.93* 7.72* -3.93* -3.31 26.47* -3.35* 24.16* -9.00 40.51 -9.00 -7.59 54.52 -7.64 50.28

Italy -2.64 3.61 -3.03* -2.90 7.68 -2.96 9.29 -5.91 17.54 -5.92 -5.12 25.59 -5.13 26.20

Luxembourg -1.41 1.00 -1.48 -1.77 10.78 -2.37 13.32 -9.02 40.67 -9.02 -7.60 50.42 -7.65 49.16

Netherlands -0.93 0.68 -1.27 -1.87 13.22 -2.30 13.44 -8.83 39.10 -8.83 -7.64 50.31 -7.68 50.17

Portugal -1.37 0.94 -1.41 -1.58 9.70 -1.70 13.51 -9.63 46.36 -9.63 -8.14 57.78 -8.20 61.72

Spain -2.00 2.53 -2.00 -1.96 6.70 -2.24 7.51 -7.00 24.49 -7.00 -5.90 26.96 -5.94 32.07United Kingdom -1.72 1.54 -1.72 -1.82 7.62 -1.70 10.59 -6.94 24.18 -6.94 -5.85 28.55 -5.89 30.46Note: t(b) and F give unit-root test-statistics which ignore the possible presence of a structural break. The remaining test statistics allow for the presence of a structural break of unknown timing. The critical values for 100

observations are as follows: -3.46 (1%), -2.88 (5%), -2.57 (10%) for the t(b) test; 8.73 (1%), 6.49 (5%), 5.47 (10%) for the F test; -4.62 (2.5%), -2.88 (5%), -2.57 (10%) for the recursive min test; -5.07 (2.5%), -4.80 (5%), -4.54 (10%) for the mean-shift min test; 20.83 (2.5%), 18.62 (5%), 16.20 (10%) for the mean-shift max F test; -4.76 (2.5%), -4.48 (5%), -4.20 (10%) for the trend-shift min test; and 16.30 (2.5%), 14.80 (5%), 13.64 (10%)for the trend-shift max F test. * indicates that based on the respective test statistics these series might be considered I(0) at the 5% level.


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Table 4: Structural Break Test in the National Cointegration Vector betweenPolicy Rates and Lending Rates from January 1985 to December 1998

Country supF Break pointBelgium 509.3 March 1991

Finland 181.7 January 1989

France 12.0 August 1994

Germany 354.0 February 1993

Greece 140.3 May 1993

Ireland 20.5 September 1992

Italy 78.8 September 1992

Luxembourg 122.1 March 1991

Netherlands 32.8 December 1993Portugal 41.5 May 1992

Spain 63.7 August 1987

United Kingdom 15.9 September 1992Note: Based on the critical values reported by Hansen (1992) the breaks for all countriesexcept France are significant.


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18

Table 5: Cointegration of Lending Rates (LR) and Policy Rates (PR) in the Period between January 1994 until December 1998

Country Cointegration Regression

(t-statistics)

DW ADF(k)1

1(t-statistic)

11

(t-statistic)1

2(t-statistic)

1F-test for H0: 1 = 2(significance level)

EMU member countries

Belgium LR = 4.24 + 1.10 PR

(31.62) (27.92)

1.364* -6.332 (0)* -0.598

(-6.785)

-0.771

(-5.981)

-0.361

(-2.292)

3.254

(0.077)

Finland LR = -2.43 + 1.95 PR

(-14.55) (53.87)

0.884* -2.499 (0) -0.073

(-0.906)

-0.106

(-0.672)

-0.044

(-0.312)

0.060

(0.807)

France LR = 4.20 + 0.72 PR

(27.22) (19.57)

0.196 -2.737 (0)

-1.367 (1,12)

-0.219

(-3.198)

-0.273

(-2.762)

-0.152

(-1.361)

0.584

(0.448)

Germany LR = 6.97 + 0.97 PR

(39.79) (18.69)

0.219 -1.975 (0)

-1.577 (4)

-0.076

(-2.214)

-0.092

(-1.462)

-0.048

(-0.491)

0.094

(0.761)

Ireland LR = -0.28 + 1.01 PR

(-0.59) (13.73)

0.320 -2.255 (0) 0.039

(0.268)

-0.072

(-0.177)

0.099

(0.391)

0.085

(0.772)

Italy LR = 2.53 + 1.14 PR

(13.14) (43.33)

1.311* -5.116 (0)* 0.188

(2.985)

0.309

(2.242)

0.108

(1.054)

0.978

(0.328)

Luxembourg LR = 3.95 + 0.59 PR

(30.79) (15.54)

0.485** -2.409 (0) -0.138

(-1.830)

-0.359

(-2.902)

0.132

(0.928)

4.888

(0.031)

Netherlands LR = 3.91 + 0.91 PR

(48.97) (38.03)

0.723* -3.817 (0)** -0.042

(-0.358)

-0.579

(-2.029)

0.376

(1.610)

4.209

(0.046)

Portugal LR = 3.29 + 1.12 PR

(5.41) (14.08)

1.419* -5.543 (0)* -0.121

(-2.909)

-0.153

(-2.779)

-0.011

(-0.084)

0.769

(0.384)

Spain LR = 0.49 + 1.07 PR

(3.74) (56.61)

0.730* -3.309 (0)***

-3.399 (5)**

0.084

(0.545)

0.212

(0.907)

-0.169

(-0.446)

0.535

(0.467)

Non-EMU member countries

Greece LR = 1.15 + 1.17 PR

(1.15) (21.58)

0.326*** -1.947 (0)

-1.429 (9,12)

-0.043

(-0.528)

-0.424

(-2.620)

0.334

(2.083)

7.130

(0.010)

United Kingdom LR = 2.53 + 0.64 PR

(7.91) (12.18)

0.387** -2.612 (0)

-2.890 (12)***

-0.166

(-1.853)

-0.102

(-0.900)

-0.297

(-1.786)

0.875

(0.354)Note: DW gives the Durbin-Watson statistics. The critical values for rejecting the null hypothesis of non-cointegration are 0.511 (1%), 0.386 (5%) and 0.322 (10%) for 100 observation. ADF (k) gives the t statistic for in the (augmented) DickeyFuller regression. k, given in brackets, gives the lags used in augmented Dickey Fuller regression, so that k=0 represents the simple Dickey-Fuller regression. The critical values for 100 observations are 4.07 (1%), 3.37 (5%), and 3.03 (10%) for the

Dickey Fuller regression, and 3.77 (1%), 3.17 (5%), and 2.84 (10%) for the augmented Dickey Fuller regression. The error correction term (ECT) is given in the last column for which also t-values are reported in brackets.1 The lag structures for the ADF(k) test and the symmetric as well as the asymmetric ECM are determined using all significant lags from k=1 to 12.

* indicates that cointegration can be assumed at 1% significance level. ** indicates that cointegration can be assumed at 5% significance level. *** indicates that cointegration can be assumed at 10% significance level.


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Figure 1: National Central Bank Policy and Commercial Bank Lending Rates from Janaury 1984 to December 1998

Panel A: Belgium

Panel B: Finland

Panel C: France

Panel D: Germany

Panel E: Ireland

Panel F: Italy

0

5

10

15

December-81

December-82

December-83

December-84

December-85

December-86

December-87

December-88

December-89

December-90

December-91

December-92

December-93

December-94

December-95

December-96

December-97

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December-99

December-00

0

5

10

15

December-81

December-82

December-83

December-84

December-85

December-86

December-87

December-88

December-89

December-90

December-91

December-92

December-93

December-94

December-95

December-96

December-97

December-98

December-99

December-00

0

5

10

15

December-81

December-82

December-83

December-84

December-85

December-86

December-87

December-88

December-89

December-90

December-91

December-92

December-93

December-94

December-95

December-96

December-97

December-98

December-99

December-00

0

5

10

15

December-81

December-82

December-83

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December-88

December-89

December-90

December-91

December-92

December-93

December-94

December-95

December-96

December-97

December-98

December-99

December-00

0

10

20

30

December-81

December-82

December-83

December-84

December-85

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December-87

December-88

December-89

December-90

December-91

December-92

December-93

December-94

December-95

December-96

December-97

December-98

December-99

December-00

10

20

30


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Figure 1 (continued)

Panel G: Luxembourg

Panel H: The Netherlands

Panel I: Portugal

Panel J: Spain

Panel K: Greece

Panel L: The United Kingdom

0

5

10

15

December-81

December-82

December-83

December-84

December-85

December-86

December-87

December-88

December-89

December-90

December-91

December-92

December-93

December-94

December-95

December-96

December-97

December-98

December-99

December-00

0

5

10

15

December-81

December-82

December-83

December-84

December-85

December-86

December-87

December-88

December-89

December-90

December-91

December-92

December-93

December-94

December-95

December-96

December-97

December-98

December-99

December-00

0

10

20

30

December-81

December-82

December-83

December-84

December-85

December-86

December-87

December-88

December-89

December-90

December-91

December-92

December-93

December-94

December-95

December-96

December-97

December-98

December-99

December-00

0

10

20

30

December-81

December-82

December-83

December-84

December-85

December-86

December-87

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December-89

December-90

December-91

December-92

December-93

December-94

December-95

December-96

December-97

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December-99

December-00

0

10

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3040

December-81

December-82

December-83

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December-93

December-94

December-95

December-96

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December-98

December-99

December-00

5

10

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20


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Figure 2: Error Correction Term Coefficients

-0.8

-0.6

-0.4

-0.2

0.0

0.2

0.4

Belgium

Finland

France

Germany

Ireland

Italy

Luxembourg

Netherlands

Portugal

Spain

Greece

United

Kingdom

Note: For each country, the left-hand-side bar represents the ECT associated with above equilibrium rates whereas the right-hand-sidebar indicates the ECT associated with below-equilibrium rates. - Non-colored bars indicate that the ECT is not significantly different

from zero or that cointegration could not be established.

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