DO EUROPEAN CENTRAL BANK’S STATEMENTS STEER
INTEREST RATES IN THE EURO ZONE?*
by
MARIE MUSARD-GIES
IXIS Corporate Investment Bank and University of Orleans (LEO)
In this study, we aim at testing whether press conferences held after the
meeting of the European Central Bank’s monetary policy council steer
market interest rates in the Euro zone. To meet this goal, we quantify the
statements according to whether they are neutral, hawkish or dovish. We
show, using a principal components analysis, that market interest rates
react significantly to the bias in statements, and more particularly to
changes in statements from one meeting to the next. Moreover, we find
that the short end of the yield curve reacts more sharply to statements
than the long segment: the effect of statements peaks on interest rates
with a maturity of 6 or 12 months and is smaller for the longer maturities.
Using non-parametric tests confirms our previous results.
1Introduction
Recent studies highlight the role played by the Fed’s statements on the day of
the Federal Open Market Committee (FOMC) meeting. ‘It’s not what they
do, it’s what they say’: this was the sort of thing one could read in financial
papers in 2004.
1
The statement that followed the 28 January 2004 meeting led
to ‘record’ reactions in the Treasuries market: two- and five-year interest rates
rose 21 and 25 basis points, respectively, in the half hour that followed the
announcement (i.e. the largest moves recorded in the past 15 years). This
excessive reaction was triggered by what the Fed had said, and not by what
it had done: the decision to leave interest rates unchanged was perfectly
expected by the financial markets, but the FOMC’s decision to delete the
sentence ‘policy accommodation can be maintained for a considerable
period’ and replace it by ‘the Committee believes it can be patient in removing

anticipate the monetary policy decisions. As a result, the response of interest
rates to the publication of macroeconomic data depends on the degree of
transparency in the conduct of monetary policy. The theory of efficient
markets predicts that the prices of financial instruments will always reflect all
available information. If markets are efficient, interest rates should adjust
virtually instantaneously after the release of data that modify financial
markets’ expectations concerning monetary policy. Transparency therefore
causes financial markets to adjust their interest rate expectations as soon as
macroeconomic data are published, in advance of any action by the central
bank. In this vein, Haldane and Read (2000) show that a reduction in the
markets’ uncertainty about the central bank’s reaction function implies that
market prices will react less to monetary policy changes since market partici-
pants are better able to anticipate them and more fully to news about the state
of the economy, in particular macroeconomic data releases on which the
reaction function is conditioned. Consequently, markets react to macroeco-
nomic announcements they view as important arguments to the monetary
policy reaction function and, moreover, react more strongly to those unan-
ticipated data releases that have greater impact on potential future monetary
policy. Thus, in a world where the central bank’s reaction function was
known to the market participants with certainty, one would in principle
observe no financial asset price reactions at the time of monetary policy
changes, but significant reactions to the release of surprise macroeconomic
data that occur before the monetary policy action date.
Insofar as monetary policy decisions are now largely predictable, and
consequently well expected, one should ask what the role of central banks is in
the implementation of monetary policy if financial markets are themselves able
to digest and factor the new information into interest rates. Do central banks
have the possibility to make monetary policy more effective? Clear communi-
cation helps to increase the predictability of monetary policy decisions, and
thus causes financial markets to adjust their interest rate very quickly and well

In this paper, we study the effect of European Central Bank (ECB)
communication on interest rates of different maturities. More precisely, we
aim at testing whether the statement made during the press conference that
follows the announcement of the ECB’s decision about the main refinancing
rate, for its part, has an impact on interest rates. To do so, we are going to
look whether the tone of the ECB’s statement (which we are going to codify)
or the change in the tone from the previous statement explains changes in the
Euro zone’s short- and long-term interest rates. We briefly review, in Section
2, empirical studies on central bank communication. Section 3 then discusses
the issue of how to measure communication. This is followed by our empiri-
cal analysis of the effectiveness of ECB statements in influencing Euro zone
interest rates in the desired way in Section 4. Section 5 presents the results.
Section 6 concludes.
2Empirical Studies on Central Bank Communication
The empirical literature
3
on central bank communication is quite small,
partly reflecting the difficulty of measuring it, partly due to the relatively
3
References related to theoretical models estimating the impact of communication are older and
numerous. We can refer to surveys on the transparency: the most recent is Carpenter (2004);
other surveys are those of Geraats (2002) and Hahn (2002).
The Manchester School118
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Journal compilation © 2006 Blackwell Publishing Ltd and The University of Manchester 2006
recent adoption of transparency as a major characteristic of central bank
policy. These papers analyze the effect of central bank communication on
asset prices. Most studies test whether communication affects exchange rates:
Jansen and de Haan (2003) find some effect from ECB statements on the
volatility of the Euro and Fratzscher (2004) finds more systematic

President and other Governing Council members to a very similar extent.
Finally, they find that US markets react to statements both about monetary
policy inclination and the economic outlook, whereas UK and Euro area
markets respond mostly only to communication about monetary policy.
4
Finally, the paper of Rosa and Verga (2005), in a similar vein to our
study, analyzes the communication content of ECB press conferences. These
4
This difference probably reflects, according to Ehrmann and Fratzscher, the different market
perceptions of policy reaction functions.
ECB’s Statements and Interest Rates 119
© 2006 The Author
Journal compilation © 2006 Blackwell Publishing Ltd and The University of Manchester 2006
authors construct an indicator to capture inflation and real economy risks
and conclude that market expectations at different maturities (from one to six
months) react to ECB communications. This paper covers a short-term time
horizon (from October 2001 to September 2004) that captures only a period
of increasing interest rates. Moreover, the authors have limited their analysis
to the meetings in which the ECB did not change the main refinancing rate.
All these studies conclude that central bank communication has signifi-
cant influences on the expectations of financial markets. The study of Rosa
and Verga (2005) is most closely related to our approach. We extend this
literature by analyzing the effect of ECB statements on the yield curve in
order to assess if ECB communication affects the short end and the long end
of the yield curve differently.
3Measuring Communication:How Do We Quantify the
Contents of ECB’s Statements?
In this section, we turn to the issue of how to measure communication. As our
objective is to test whether and to what extent ECB’s statements affect market
interest rates, on the day of the press conference that follows the announce-

codifying work, however.
The Manchester School120
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Journal compilation © 2006 Blackwell Publishing Ltd and The University of Manchester 2006
and associated risks that we ascribe a ‘rating’ to the statement (e.g. a scenario
of growth equal to its potential with upside risks and a rise in inflation and
with also upside risks in the medium term will be deemed very hawkish).
Rosa and Verga (2005) use specific expressions or code words that are
used frequently in the ECB press conference in order to translate the quali-
tative information into an index. Nevertheless, their indicator relies only on
the ‘synthetic judgments’ part of the introductory statement
6
and most of the
time the synthetic judgment is only a small part of the whole communication.
Consequently, this quantification by only some expressions has some draw-
backs: some very important but uncommon expressions can be missed by an
automatic analysis. Moreover, a precise coding would require an analysis of
the grammatical structure of sentences: indeed, meaning and strength of
keywords often depends on the context of the sentence.
Another study is the one of Gerlach (2004): it relies on the editorial of the
ECB monthly bulletin. This analysis is a more subjective one: he does not
construct a glossary of words based on a few lines only to construct an index.
For each editorial, using information synthesizing the overall reading of the
editorial, he allocates a different value to the three dimensions: inflation, real
activity and M3. Consequently, this approach allows reading ‘between the
lines’ and therefore is more subjective than the systematic approach of Rosa
and Verga (2005).
Our study is based on two coding principles merging these preceding
ideas. First, one is like the Rosa and Verga (2005) study with some slight
differences: it relies on the automatic analysis of the keywords of the whole

Our study covers a time horizon from January 1999 to October 2004,
7
which yields 66 observations (on the other hand, the Rosa and Verga (2005)
study is based on only 30 observations). The final codification we obtain is
presented in Appendix A (Table A1). We compared (Appendix A, Fig. A1)
our codification of statements with that carried out by Gerlach (2004). We
take the sum of the ratings set by Gerlach or calculate a weighted average
(with larger weight for ‘activity’ and ‘inflation’ ratings, i.e. 40 per cent, than
for the rating relative to M3, i.e. 20 per cent). We conclude that our assess-
ment of ECB statements is quite similar to the one drawn upon by Gerlach
when we look at the weighted average of his ratings. The only major differ-
ence concerns 2004, when ECB statements were relatively hawkish in our
opinion, while he deems them to have been neutral.
Note that the tone of ECB statements (Appendix A, Table A2) is more
often hawkish than accommodating even though, in four out of the six years
of observation, growth in the Euro zone was lower than its potential growth
rate (for the ECB, potential growth is close to 2–2.25 per cent). Simulta-
neously, the inflation target has exceeded 2 per cent every year except in 1999
(and inflation is the objective of the ECB’s monetary policy).
4Data and Methods
We aim at testing whether information from the ECB’s press conferences
have effects on financial market expectations, i.e. whether day-to-day change
in short- and long-term interest rates around the ECB meeting is related to
the tone of the statement. We use approaches that are common in the ‘event-
studies’ of finance literature: ordinary least squares regressions analysis,
where ECB statements are represented by our dummy D
ECB
that codifies the
tone of the statement, and non-parametric tests in order to test the robustness
of our previous results.

month Euribor and 12-month Euribor spot rates. With respect to long-term
interest rates for the Euro zone, we use the price of German futures contracts
(which are the benchmark of the Euro zone yield curve), two-year (Schatz),
five-year (Bobl) and 10-year (Bund) rates. A future contract is a binding
agreement between two parties to make a particular exchange on a specified
date t in the future.
9
The interest of working on contracts (for the long
segment) rather than spot rates lies in the fact that, generally speaking,
futures are far more reactive (and thus factor in any additional information
far faster). All these data (Euribor spot rates for the short end and futures
contract for the long end of the yield curve) can be downloaded from
Datastream.
10
In the event-study literature, authors regress the change in asset prices on
the change in policy rate:
11
ΔΔRk
ttt
=+ +
αβ ε
(1)
where DR
t
stands for the change in asset prices and Dk
t
stands for the change
in monetary policy rate. For example, in Cook and Hahn (1989), Dk
t
stands

expected changes in the funds rate target.
Finally, if we suppose that monetary policy is perfectly predictable, the
surprise on the day of the monetary policy meeting is no longer provided by
the decision about the policy rate, but rather by the content of the statement
of the central bank. Indeed, in the Euro zone, as underlined in the introduc-
tion of this paper, market interest rates have predicted Euro area interest
rates comparatively well up to three months in advance.
12
Bernoth and von
Hagen (2004) conclude that the policy decisions of the ECB have been pre-
dictable on average: they show that, since May 2001, markets were not
surprised by the decisions on the rates of the ECB.
However, we have to note that in May 2001 the ECB decision was
largely unexpected. As soon as early 2001, the markets were expecting a
rate cut by the ECB. Nevertheless, the ECB did not change its key interest
rate in February, March, or even in April 2001, whereas the economic slow-
down seemed to justify a rate cut (inflation was admittedly still high despite
the fall in oil prices and was picking up again in March–April but this was
mainly the result of the mad cow disease, i.e. an external supply shock).
Even as the markets were banking on a rate cut, the ECB’s statements
remained neutral. The fact that its statements did not change from one
month to the next should not have led to fluctuations in interest rates and
yet they were trending downwards: at this point in time, the markets
believed in economic indicators more than in the ECB. In fact, it eased its
monetary policy in May, thus comforting the markets, while still making
rather neutral statements, as inflation had precisely peaked in this month at
its highest level since the launch of the European Monetary Union at 3.1
per cent (but 3.4 per cent according to its measure at the time, which was
subsequently revised).
Consequently, in order to take into consideration the fact that a few

ments and S stands for the unexpected component of the monetary policy
decision (called the ‘surprise’ of monetary policy).
The question, then, is how to extract a measure of the surprise. We
need to use forward interest rates in order to extract financial market expec-
tations. More precisely, we will look at forward interest rates one week
before the day of the press conference and compute a surprise as the dif-
ference between the ECB main refinancing rate on the day of the meeting
and the forward rate one week ahead. A forward interest rate is an interest
rate that is specified now for a loan that will occur at a specified future
date.
14
A standard assumption holds that a forward interest rate is the sum of
two components: first, a liquidity premium (also called a term premium);
second, an expectation concerning the spot rate that will hold at the time.
Thus, a one-week rate one week forward of x per cent might be considered to
be a consensus expectation of market participants that the one-week spot rate
will equal x per cent in one week (the liquidity premium is considered to
be insignificant for a maturity of one week). The underlying concept of this
assumption is the so-called expectations hypothesis of the term structure: two
equivalent investment options should have the same expected return, other-
wise investors would arbitrage away any differences. With the exception of a
term premium, there should be no difference in the returns from holding a
long-term bond or rolling over a sequence of short-term bonds. To compute
a forward rate, we use the following formula:
f
dd
=
−
−
FV 1

rd
(4)
where r
1
stands for the spot rate for d
1
days and r
2
for the spot rate for d
2
days.
It would be relevant to compute a one-week rate one week forward
(having the same maturity as the main refinancing rate): we would need the
one-week and two-week Euribor spot rates to compute this one-week
forward rate. Unfortunately, the data for the two-week Euribor spot rate are
available only from October 2001. Consequently, we will compute a three-
week rate one week forward by using the one-week and the one-month
Euribor spot rates (by assuming that the difference between one-week and
three-week interest rates is insignificant). The measure of the surprise in
policy rate on the day i of the press conference is given by
Srf
ii i
=−
−7
(5)
where the index i denotes here the day of the ECB meeting and has a daily
frequency and r
i
stands for the new (i.e. after the decision of the Governing
Council) ECB main refinancing rate on the day of the ECB press conference.

this enables us to interpret the relative weight of each interest rate in the axes
derived from our PCA. Initially, we carry out a PCA on all interest rates
(short- and long-term interest rates), and then we subsequently carry out a
PCA on short-term interest rates exclusively and then on long-term interest
rates.
5.1.1 Interest Rates React Far More to the Change in the Tone from One
Statement to the Next Than to the Statement in Absolute Terms. When we
carry out the PCA of changes in short- and long-term interest rates, we obtain
a first factor that explains 52 per cent of the variance of all the changes in
short- and long-term interest rates. This factor is well linked to all the changes
in short- and long-term interest rates: the weights of each market interest rate
in the first principal component range between 0.34 and 0.43 if we look at the
first eigenvector (Table 1) which means that the series are weighted in a
virtually identical manner in this first factor. Consequently, this first factor
satisfactorily represents the common moves in short- and long-term interest
rates in the Euro zone.
We now estimate via ordinary least squares the relationship between the
first factor, called PC
1
, derived from our PCA and our variable D
ECB
that
codifies the statement between -2 and +2 (equation (6)). The estimation
obtained is presented in Table 2.
15
15
Note that the value of the coefficient of our dummy D
ECB
cannot be interpretable economically
since we have used changes in short-term interest rates but also from the opposites of

the meeting. On the other hand, the explanatory power is relatively low
(R
2
= 0.09). We then seek to improve the estimate by proposing a variant of
our variable that codifies ECB statements: we build a new variable that
reflects changes in the ECB statement’s tone in comparison with the tone of
the previous month. The new variable DD
ECB,t
= D
ECB,t
- D
ECB,t-1
is introduced
in our equation:
PC
,ECB,1 tttt
DS=+ + +
αβ γ ε
Δ
(7)
The estimation is presented in Table 3. Now, the correlation between the
first axis derived from the PCA and the change in the tone of the statement
between two ECB meetings appears clearly. Our dummy variable in difference
is far more significant and this variable allows us to explain far better our main
component of short-term interest rates and long-term interest rates. The
coefficient of the variable remains positive: thus, if the statement becomes
more hawkish, Euro interest rates tend to rise, and, vice versa, if the statement
moves from hawkish to neutral, or from neutral to dovish, interest rates will
then trend downwards. The markets do not react so much to the statement in
absolute terms as to changes in the statement. Thus, if the statement is hawkish

corresponds to the slope of the yield curve. Indeed, if we look again at the
second eigenvector in Table 1, we can see that weights are positive on long-
term interest rates and negative on short-term rates. Considering that the
slope of the yield curve is defined as the difference between long-term rates
and short-term rates, the second principal component corresponds to the
slope of the yield curve. We can also point out that the third factor corre-
sponds to the curvature of the yield curve. These results are common in the
finance literature; see Litterman and Scheinkman (1991) and Wu (2003) for a
review of some of the latest studies that have explored the macroeconomic
determinants of the yield curve.
The second component explains here 32 per cent of the variance of all the
changes in short- and long-term interest rates. The estimation (Table 4)
reveals that the tone of statements has no effect on the slope of the yield
curve, which is consistent with our previous results (we find indeed that
statements have a simultaneous effect on both short- and long-term rates).
PC
,ECB,2 tttt
DS=+ + +
αβ γ ε
Δ
(8)
Finally, we find that ECB communication has no effect on the slope yield
curve: short- and long-term interest rates react to the content of the intro-
ductory statements of the ECB press conference. Now, we will use the same
methodology to refine our analysis in order to assess the differentiated effect
of ECB statements first on short-term interest rates and then on long-term
interest rates.
5.1.2 The Impact of ECB’s Statements on Short-term Interest rates. When
we carry out a PCA of Euro zone short-term interest rates, we obtain a first
Table 4

variable in difference
(Table 5).
Our dummy D
ECB
in difference is also significant for long-term interest
rates: it allows us to explain 12 per cent of the change in long-term interest
rates (or, more precisely, 12 per cent of 92 per cent of the information
contained in the Schatz, Bobl and Bund contracts). Hence ECB communica-
tion has effects on financial markets: more precisely, changes in the tone of
the introductory statement that follows the monetary policy council meeting
plays a significant role in moves in short- and long-term interest rates in the
Euro zone. Thus, we have shown that the statements could explain up to 28
per cent of the fluctuations in short-term interest rates and about 12 per cent
of the fluctuations in long-term interest rates. Consequently, the short end of
the yield curve reacts more noticeably to the contents of the statement than
Table 5
Estimation of Equation
PC st, lt
ECB,1
k
ttt
DSk=+ + + =
(
)
αβ γ ε
Δ
Where st Stands for Short-term
Interest Rates and lt Stands for Long-term Interest Rates
a t stat b t stat g t stat R
2

tttt
=+ + +
βγε
ECB,
(9)
where DR
t
is the day-to-day change in interest rate around the ECB meeting,
all data being centered and reduced. As regards long rates, we use contracts
and thus a change in price with the opposite sign. The results of various
regressions are shown in Appendix B (Table B1).
The estimations confirm the role played by the change in the tone of
ECB statements. Thus, our variable that codifies the statement is always
significant and its coefficient is positive; when the statement becomes more
hawkish, the interest rates of the yield curve rise. Conversely, it can be seen
that the statements seem to have a maximum effect on medium-term interest
rates: indeed, the significance of ECB communication is the highest at 6 and
12 months. The unexpected component of monetary policy decisions is not
significant for each maturity, consistent with our previous results.
Moreover, the explanatory power of ECB statements for changes in
interest rates is the highest for these maturities. Beyond one year, the effect of
statements fades: the significance and the explanatory power decreases with
the maturity. Here, the result is quite surprising insofar as the statements
would apparently have a greater impact on five-year interest rates than on
two-year interest rates.
5.3 Non-parametric Statistics
In this section, we present another methodology of the impact of ECB
communication on market interest rates using non-parametric tests. Non-
16
We have concluded that ECB communication has no effect on the slope of the yield curve

dovish, market interest rates will then trend downwards. Nevertheless, when
the tone of the ECB statement remains the same between two months, the
relationship is more variable. We will then test for a difference between the
three subgroups.
We employ a methodology used by Clare and Courtenay (2001) by
splitting the sample period into days when the ECB statement becomes more
hawkish or more dovish. We use the split between more dovish or more
hawkish days to investigate the pattern of market reactions to ECB state-
ments. Our sample is divided in three subgroups: first, days when the tone of
the ECB statement becomes more hawkish (DD
ECB
=+1) and the opposite
case when the ECB statement becomes more dovish (DD
ECB
=-1). The last
subgroup contains days when the tone of the statement remains the same
between two consecutive monetary policy meetings (DD
ECB
= 0). The differ-
ences in market reactions to ECB statements between days where the tone of
the ECB statement becomes more hawkish or more dovish are tested using a
non-parametric statistic. The non-parametric test that we use is the Kruskal–
Wallis test that is given by
H
NN
R
n
N
k
k

n
i
k
i
=
=
Σ
1
,
is the rank sum for series k. This test statistic is distributed
X
2
(K - 1) under the null hypothesis of equal medians.
The results of the Kruskal–Wallis test to assess the significance of the
differences between more hawkish, more dovish or neutral days are given in
Appendix D, Table D1. They indicate that the test for equality failed: we
reject the null hypothesis for all market interest rates (except for the one-
month Euribor rate). The medians of the three subgroups differ. These results
confirm our previous conclusion: the reaction of market interest rates
depends on the change in the ECB’s statement in comparison with the state-
ment of the previous month. We can now present a more precise analysis by
running the non-parametric test for only two series; i.e. we want to compare
the medians between two subgroups only.
We perform now the same test, but our objective is to test the equality of
medians between two subsamples. The results are given in Table D2. We
calculate the Kruskal–Wallis statistic by using first the split between more
hawkish versus more dovish days (DD
ECB
= 1 versus DD
ECB

the tone of the speech becomes accommodating.
6Conclusion
Central communication is fundamental in terms of explaining moves in
interest rates, around ECB meetings but also more generally speaking.
ECB’s Statements and Interest Rates 133
© 2006 The Author
Journal compilation © 2006 Blackwell Publishing Ltd and The University of Manchester 2006
Anticipating short-term moves in interest rates between the day before a
meeting of the ECB’s Governing Council and the day of the meeting sup-
poses predicting not only changes in intervention rates but also the tone of
the ECB’s statement (in addition to other possible determinants such as US
data, for example). Our findings suggest that ECB communication on
meeting days (press conferences delivered after the announcement of mon-
etary policy decisions) significantly influences expectations of future mon-
etary policy. More precisely, financial markets react to the change in the
tone of the statement (rather than the absolute tone). Moreover, we show
that ECB communication affects more sharply the short end of the yield
curve: the size of the communication effect is maximal for maturities of 6
and 12 months—hence the importance of the ex ante information about
this statement, notably via interviews in the press of Council members (and
the importance of ‘rumors’ or ‘leaks’), and hence also the introduction of a
degree of subjectivity, in the interpretation of the words of the central bank
governor. Of course, the impact of monetary policy communication has to
be judged in the light of other news events which can have a much larger
effect on the market, such as international developments, domestic macro-
economic data releases etc.
In the USA, communications of the Fed particularly steered long-term
rates over these last months. Several speeches of Fed’s governors, such as
Bernanke (2004a, 2004b) and Kohn (2005), emphasize the role of central
bank communication for the effectiveness of monetary policy. As evidence

Date D
ECB
7 Jan 1999 0 8 Nov 2001 -1
4 Feb 1999 -1 6 Dec 2001 0
4 Mar 1999 -1 3 Jan 2002 0
8 Apr 1999 -1 7 Feb 2002 0
6 May 1999 -1 7 Mar 2002 0
2 Jun 1999 0 4 Apr 2002 0
15 Jul 1999 0 2 May 2002 1
9 Sep 1999 1 6 Jun 2002 1
7 Oct 1999 1 4 Jul 2002 1
4 Nov 1999 1 12 Sep 2002 0
2 Dec 1999 1 10 Oct 2002 0
5 Jan 2000 1 7 Nov 2002 -1
3 Feb 2000 1 5 Dec 2002 -1
2 Mar 2000 2 9 Jan 2003 -1
30 Mar 2000 2 6 Feb 2003 -1
13 Apr 2000 2 6 Mar 2003 -1
11 May 2000 2 3 Apr 2003 -1
8 Jun 2000 2 8 May 2003 -1
6 Jul 2000 2 5 Jun 2003 -1
14 Sep 2000 2 10 Jul 2003 -1
5 Oct 2000 2 4 Sep 2003 -1
19 Oct 2000 2 2 Oct 2003 0
2 Nov 2000 2 6 Nov 2003 1
14 Dec 2000 1 4 Dec 2003 1
1 Feb 2001 1 8 Jan 2004 1
1 Mar 2001 0 5 Feb 2004 1
11 Apr 2001 0 4 Mar 2004 1
10 May 2001 0 1 Apr 2004 1

6 months -0.05 -0.46 1.20 4.90*** 0.63 0.88 0.28
12 months -0.02 -0.21 1.19 4.94*** 0.20 0.28 0.29
2 years -0.11 -0.76 0.64 2.37** 1.27 1.58 0.10
5 years -0.08 -0.62 0.81 3.05** 0.92 1.16 0.13
10 years -0.04 -0.32 0.78 2.91* 0.36 0.45 0.12
Note: *Significant at the 90 per cent level; **significant at the 95 per cent level; ***significant at the 99 per cent
level.
The Manchester School136
© 2006 The Author
Journal compilation © 2006 Blackwell Publishing Ltd and The University of Manchester 2006
Appendix C
Descriptive Statistics for the Day-to-day Change in Market Interest Rates
Table C1
Mean of Series (First Difference)
Maturity DD
ECB
=-1 DD
ECB
= 0 DD
ECB
= 1
1 month -0.032 -0.005 0.002
3 months -0.024 -0.003 0.006
6 months -0.021 -0.002 0.018
12 months -0.023 -0.002 0.044
2 years -0.009 0.031 0.146
5 years -0.031 0.029 0.371
10 years -0.092 0.046 0.487
Table C2
Medians of Series (First Difference)

Table D2
Test for Equality of Medians between Two Subgroups (Kruskal–Wallis Statistic and
p value)
Maturity DD
ECB
= 1/-1 DD
ECB
= 1/0 DD
ECB
= 0/-1
1 month 2.46 0.116 3.05 0.081* 0.49 0.482
3 months 5.22 0.022** 6.05 0.013** 1.93 0.164
6 months 6.61 0.010*** 9.65 0.001** 3.86 0.049**
12 months 9.00 0.002*** 11.87 0.000*** 3.47 0.062***
2 years 4.59 0.032** 6.05 0.013** 0.06 0.798
5 years 5.22 0.022** 9.28 0.002*** 0.26 0.609
10 years 4.59 0.032** 8.044 0.004*** 0.62 0.428
Note: *Significant at the 90 per cent level; **significant at the 95 per cent level; ***significant at the 99 per cent
level.
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