Equity Returns and Monetary Policy:
Evidence from the UK
Georgios Chortareas*
John Nankervis**
and
Emmanouil Noikokyris***
April 2009
Abstract
This paper is an empirical study of the relationship between equity prices and monetary
policy in the UK. The results, produced by an event study like methodology, indicate that
equity prices react significantly and in an opposite direction to monetary policy shocks.
Moreover, we find that although equities react significantly both to timing and level shocks in
monetary policy, the latter trigger more significant reactions. The introduction of an Inflation
Targeting regime has triggered changes in this relationship, altering the direction of equities
response to both timing and level shocks. On days when there is a release of an Inflation
Report the timing shocks appear to exert stronger effects than the level shocks, suggesting
that the Inflation Report reveals valuable information about the timing of policy shocks. The
Minutes of the MPC do not appear to trigger significant reactions on the same day; however,
we find evidence that a release indicating a unanimous decision causes significant
overreactions at the following MPC meeting. Finally, the effects from a monetary policy
action are not only restricted on the day of the announcement but they extent for a period of
up to 8 trading days ahead.
JEL. No.: G14, E44, E52.
Keywords: Monetary Policy, Inflation Targeting Framework, Event Studies.
* Department of Economics, University of Athens, 14 Euripidou Str., 105 53 Athens, Greece email: gchortar@econ.uoa.gr
** Finance Group, Essex Business School, University of Essex, Wivenhoe Park, Colchester, CO4 3SQ, UK email:
jcnank@essex.ac.uk
*** Finance Group, Essex Business School University of Essex, Wivenhoe Park, Colchester, CO4 3SQ, UK email:
enoiko@essex.ac.uk
1. Introduction
This paper is an empirical examination of the relationship between monetary policy
and equity prices in the UK. This relationship has seen much attention lately, as it features in
major monetary policy debates about whether central banks should intervene in the capital
markets to correct for any pricing misalignments. The increased emphasis that is attributed to
the stock price channel of monetary policy has made the examination of this relationship a
top priority in the agenda of policymakers, and Bernanke and Gertler (2000) even claim that
the effects of monetary policy on asset prices might overshadow inflation stability as the
primary objective of central banks.
In this paper we address issues concerning the following three research objectives.
First, we examine the contemporaneous relationship between monetary policy shocks and
equity prices, and in particular we extract quantitative estimates of the equities’ reaction to
changes both in the timing and the level of future policy actions. Second, we provide some
empirical evidence about the effects from two types of communication from the Bank of
England (hereafter, the Bank), the Inflation Report and the Minutes of the MPC. Finally, we
examine whether the effects of monetary policy on equities materialise in full on the day of
the policy decision, or the period of adjustment to the new monetary policy conditions
extends for some days after the decision. The analysis in this paper contributes to the
discussion about the relationship between monetary policy and asset prices by providing
evidence from the UK equity market which is up to now scant.
A discussion about the role of the Bank to the financial markets cannot be undertaken
independently from a detailed analysis of the effects that monetary policy actions can have on
1
financial assets in the first place. The identification of monetary policy’s effects on equities
can provide us initially with evidence regarding the significance of the stock market channel
of transmission, as for such a channel of transmission to exist the monetary policy actions
should exhibit some kind of impact on equities. Although the objectives of monetary policy
refer to macroeconomic variables, the equity market constitutes a favourable area to conduct
research about the effects of monetary policy as there the most direct effects of monetary
policy materialise. This is an easy to grasp concept once one realises that if a monetary policy
decision has informational value for investors this, according to the efficient markets
paradigm, should be reflected in equities in a timely and unbiased manner.
Theoretically, two different traditional mechanisms of how monetary policy affects
equity prices exist (Mishkin, 1996). In the monetarist tradition a fall in the money supply
results in a reduction in consumer spending which in turn leads to a fall in the demand and
hence the price of stocks. The traditional Keynesian approach on the other hand suggests that
a rise in interest rates drives investors to rebalance their portfolios including more bonds than
stocks, in this way reducing the demand and hence the price of the stocks. Although the
initial point of these two approaches is different, they both indicate that a monetary policy
tightening (expansion) affects the financing conditions in the market and can have significant
downward (upward) effects on stock market prices.
The recent trend in policymaking has been to attribute the real effects of monetary
policy mainly to its ability to shape inflation expectations and not just to the determination of
the level of a nominal interest rate (see indicatively King, 2005; Bernanke, 2004). The
inherent difficulty in quantifying expectations impedes the accurate estimation of the real
effects of monetary policy, and thus complicates the work of central banks to achieve their
macroeconomic objectives. The MPC of the Bank acknowledges the significance of
2
expectations in the transmission mechanism of monetary policy and for this reason it has
introduced the Inflation Targeting regime since 19971. Although the overall efficiency of a
monetary policy regime requires an assessment of its capacity to help economy recover when
it is confronted with a serious downturn, in this paper we focus our attention on the effects
from improved communication which constitutes an important feature of this new regime.
The reason for this is that under such a framework communication obtains a central role in
the efficient conduct of monetary policy, as it can be used along with the direct interest rate
setting function of the Bank to trigger the desired reactions in the economy and make future
policy actions more predictable.
The existing empirical evidence regarding the relationship between equities and
monetary policy mainly concerns the US and the bulk of the evidence supports the hypothesis
that a contractionary (expansionary) monetary policy action is associated with a drop (hike)
in equity prices2. The size of the reported responses depends on the sample selected, the
empirical methodology used, and the identification of the monetary policy shocks. However,
in all cases the response size is large enough to signify on the one hand that central banks’
actions are an important input in asset pricing models, and to support on the other hand the
existence of a stock market channel of monetary policy transmission. Moreover, the rising
importance of expectations in the identification of the effects of monetary policy has
motivated researchers’ search for asymmetries in the relationship between equities and
monetary policy shocks. The ambiguity in the factors that change expectations in the
1
The starting date for the inflation targeting framework in this paper is considered to be June 1997, after the
establishment of the Monetary Policy Committee (MPC hereafter) setting. The reason for this is that until May
1997 the monetary policy decisions were taken by the Chancellor of Exchequer, and this could create
uncertainty about the rationale of the action (Bernanke et al, 1999).
2
Ehrmann and Fratzscher, 2004; Farka, 2009; Bernanke and Kuttner, 2005; Craine and Martin, 2003;
Thorbecke, 1997; Murdzhev and Tomljanovich, 2006; Honda and Kuroki, 2006; Rigobon and Sack, 2004;
Lastrapes, 1998, Darrat, 1990; Fair, 2002; Jensen, Mercer and Johnson, 1996; Jensen and Mercer, 2002; Bredin
et al, 2007
3
financial markets suggests that the impact of monetary policy actions on them is likely to
differ across the different policy decisions, and as a result the reaction of the equities is likely
to be asymmetric.
A popular categorisation of monetary policy shocks that has only recently been
developed is that between “timing” and “level” shocks (Bernanke and Kuttner, 2005; Farka,
2009; Kearns and Manners, 2006; Gürkaynak et al, 2005). In particular, the timing shocks
refer to news about moving forward or postponing an expected policy action, while the level
shocks refer to an unexpected change in the future level of interest rates. Intuition and
empirical evidence suggest that persistent changes in the expectations about the level of
future policy rates would exert larger impact on equities than changes in the expectations
about the timing of a policy action (Bernanke and Kuttner, 2005; Farka, 2009). However
there is also empirical evidence from Gürkaynak et al. (2005) which contradicts this finding,
and the explanation they put forward is that the rise in equity prices following the better
economic output as this is associated with positive level shocks is offset by the negative
reaction of equities to higher discount rates.
Other cases of asymmetries in the relationship between equity returns and monetary
policy shocks that have seen much attention are those attributable to overreactions to “bad
news”, to the direction of the policy actions, and to inactions of the Bank on a day of an MPC
meeting (“non-announcement effects”). Bomfim (2001) has found that in the US the arrival
of bad news (positive shocks) causes overreactions in the equity market, while the results of
Bernanke and Kuttner (2005) support symmetric reactions. Moreover, the examination of the
differences in markets’ response across tightening and easing policy actions, can reveal
whether monetary policy actions can be used in a similar manner both to increase and
decrease equity prices. The evidence about this type of asymmetric response in the US is still
4
inconclusive; Lobo (2000) reports an overreaction to rate hikes while Bernanke and Kuttner
(2005) find no evidence in favour of this asymmetry. Finally, since King (2005) states that
under the new regime “market interest rates react to what the central bank is expected to do
[...] without making large moves in official interest rates” it would be useful to examine
whether this pattern holds for the equity markets as well (Roley and Sellon, 1998; Bernanke
and Kuttner, 2005). Considerable attention has also been drawn to the identification of the
response of stock portfolios and industries to monetary policy shocks and in this vein we also
examine in this paper the response of “size” and “value” portfolios (Perez-Quiros and
Timmermann, 2000; Thorbecke, 1997 and Ehrmann and Fratzscher, 2004).
In the second part of this paper we address the issue of improved communication
under the Inflation Targeting regime. The transparency, which constitutes a basic feature of
this new regime, is reputed to offer new ways of monetary policy transmission and to
reinforce the efficiency of central banks’ actions (Bernanke, 2004 Reeves and Sawicki, 2007;
King, 2007). In this vein, we examine the effects from Vickers’s (1998) “two main vehicles”
of transparency, the Inflation Report and the MPC minutes, on equity prices as the
identification of their effects on financial market expectations can be used to shed some light
to the way that it can be employed by central banks to implement their policies.
If the Bank wants to utilise the Inflation Report and the Minutes of the MPC to
“increase awareness and understanding of its activities”, it should have a clear view initially
as to how these types of communication are perceived by financial market participants. It
needs an assessment of the relevance of these types of communication for the markets and of
the way that their effects materialise. The Bank claims that an Inflation Report “sets out the
detailed economic analysis and inflation projections on which the Bank's MPC bases its
interest rate decisions”. Preliminary evidence on its role, set out in Fracasso et al. (2003),
5
suggests that an Inflation Report of improved quality is associated with the diminished
impact of stock prices on monetary policy. Moreover, empirical evidence about the Minutes’
release indicates that the voting records add to the transparency and that they do not appear to
trigger any unnecessary volatility in cases of divided opinions among MPC members
(Gerlach-Kristen, 2004; Siklos, 2003). King (2007), on the other hand, asserts that the voting
pattern is not a suitable means for forecasting future policy actions; the pattern should be
perceived primarily as a guideline of how members of the MPC assess recent economic
developments.
Existing empirical research has studied how the communication method has affected
the magnitude of the surprises in the financial markets and whether the desired reactions of
asset prices occur (Ehrmann and Fratzscher, 2007). Reeves and Sawicki (2007), and Kohn
and Sack (2003) examine the effects of the publications on the volatility of the prices of some
financial assets, omitting however to provide any results for the direction of the reactions.
Ehrmann and Fratzscher (2007) use a somewhat more refined technique, albeit subject to
criticism due to the subjectivity in extracting the news from the communication, and the
focus of their research is apart from examining the effects of communication on the monetary
policy shocks also to examine the effects of communication on the level and the volatility of
the financial asset prices. The existing evidence regarding the effects of the release of Bank’s
Inflation Report and the MPC’s Minutes suggests that although it achieves to reduce the
volatility of the surprises and to trigger reactions in the financial markets, the magnitude of
these effects is smaller than those occurring from the Fed and the ECB’s communication
(Ehrmann and Fratzscher, 2007; Reeves and Sawicki, 2007).
In this paper we examine how the benchmark relationship between equities and
monetary policy shocks is affected by the Bank’s communication. Reeves and Sawicki
6
(2007) and Kohn and Sack (2003) distinguish the monetary policy shocks from the
communications’ shocks and measure the reactions of asset prices on the latter. In this paper
we measure the reactions of equities to monetary policy news extracted from the
communication of the Bank, and unlike Ehrmann and Fratzscher (2007) we choose to extract
the monetary policy information from monetary policy shocks on the day of the release. We
postulate that the monetary policy shocks on days of a communication encapsulate any
monetary policy news from the communication released on that day, and as a result their comovement with equities reveals the way expectations about monetary policy change due to
these publications.
Moreover, in this paper we examine whether the effects from monetary policy actions
materialise only on the day of the announcement or their effects materialise for a period
following the announcement. The monetary policy action is an event acutely observed by the
markets and the effects from a change in the levels of interest rates is not likely to be one-off
on the day of the announcement, not only because a monetary policy action might proxy for
changes in other macroeconomic variables relevant for asset pricing, but also because the
markets might need more than one day to fully adjust to the new monetary conditions. The
identification of the time horizon of the impact from a monetary policy action offers
policymakers and investors more information for decision making, and for assessing and
measuring the ultimate effects from monetary policy on equities.
2. UK monetary policy and the equity market.
2.1 The impact of UK Monetary Policy on Equity Prices.
7
The identification of the effects of monetary policy actions on equities undertaken in
this section follows the “event-study” like methodology popularised by Bernanke and Kuttner
(2005). A pioneering attempt to employ such empirical frameworks in the examination of the
central banks actions’ impact on asset prices has been undertaken by Cook and Hahn (1989).
The empirical implementation of this specification involves the estimation of the following
model:
ri    iiUK   i ,
(1)
where ri stands for the daily stock market returns, iiUK is the raw change of the policy rate
and the “event days” i are the days when a change in monetary policy rate took place. The
error term is assumed to be orthogonal to the regressor and under this assumption the model
does not have any omitted variables and/or endogeneity problems.
Endogeneity and omitted variables insert bias into the estimation as other factors not
reflecting monetary policy enter this relationship. The endogeneity problem arises as it is
likely that the relationship between monetary policy and equities does not have only one
direction, as the equity prices might also affect the monetary policy (see indicatively,
Rigobon and Sack, 2003). As far as the omitted variables problem is concerned, this is due to
the fact that both monetary policy proxies and equities are likely to be affected by other
variables during the “event window”. The potential bias inserted in our estimation due to
these two issues can be addressed by using high frequency data, as a short estimation period
reduces the possibility that the effects from other news enter our relationship.
The utilisation of daily data is a well established method to address these issues.
Some studies, however, have employed intra-day data claiming that this provides stronger
evidence (Andersson, 2007; Gürkaynak et al 2005; Farka, 2009). Farka (2009) claims that
8
employing intra-day data yields stronger equity responses while Gürkaynak et al. (2005)
claims that the results are virtually the same except for some few observations when the
reactions are stronger. In any case, for a paper mainly oriented towards uncovering the
general trend in this relationship, conservatism is not such an undesirable feature and for this
reason we will use daily data, as in Bernanke and Kuttner (2005).
Another controversial issue when dealing with the empirical estimation of the effects
of monetary policy on asset prices is the identification of the proxy for the monetary policy
action. The utilisation of raw changes in policy rates is not likely to provide strong evidence
as it fails to incorporate the fact that central banks’ actions are to a great extent expected by
the market, and for this reason, current research opts for the utilisation of monetary policy
shocks. A number of studies in this stream of research use residuals from VAR models to
identify the monetary policy shocks and the appeal of this method owes to its simplicity and
its atheoretical structure (Thorbecke, 1997; Patelis, 1997; Lastrapes, 1998). However, this
method, although it is well established among researchers, is not free from criticism, and thus
the most up-to-date technique has been the utilisation of revisions in expectations extracted
from market instruments (Rudebusch, 1998; Kuttner, 2001)
The benchmark empirical specification of Bernanke and Kuttner (2005), given by:
ri  a  1exi   2 surp i   i ,
(2)
proposes a decomposition of the raw policy change into a proxy for the expected (exi) and a
proxy for the unexpected element of monetary policy (surpi). The extraction of the expected
and unexpected elements of monetary policy actions used in this paper follows the technique
developed by Kuttner (2001), and is defined as follows:
surp i  f i  f i 1
exi  iiUK  surp i
9
.
(3).
This technique suggests that monetary policy shocks can be defined as the change in the rate
of a short term interest rate futures contract (fi) on a day of a policy announcement, and the
expected component as the difference between the actual policy change and the surprise
component.
The absence of a futures instrument which tracks the Bank’s policy rate in the UK
financial markets has lead researchers to seek for alternative measures and what has been
used so far are the 1-month Libor, the 3-months Libor, and the 3-months sterling futures rate
(Kearns and Manners, 2006; Bredin et al., 2007; Ehrmann and Fratzscher, 2007). The dataset
used in our estimations spans from the rate hike of the 26th November 1982 until the rate hike
of the 9th November 2006 and includes 118 “events”. In Figure 1, we plot the changes of the
3-month sterling futures rate, which is the proxy most commonly utilised by the Bank in its
publications to imply future interest rate expectations. The reduced volatility it exhibits
during the period after the introduction of the Inflation Targeting regime in 1993 can be
perceived as indicative of the improved transparency under this new regime, and stands
supportive of King’s (1997) assertion, that within a transparent system the news does not
occur from the MPC meetings, but from economic news.
- Figure 1 somewhere here In Table 1, we print the results from the empirical estimation of models (1) and (2),
and our results are generally consistent with theoretical priors and previous empirical
research, and show that monetary policy shocks and equity prices are negatively associated.
The weak reaction of equities to raw changes in policy rates reflects the fact that the actions
of the Bank are to a great extent expected by the market. The empirical implementation of the
benchmark model (2), the results of which are printed in the other three rows of Table 1,
provides a clearer view, as they signify a strong negative impact to monetary policy surprises
10
both numerically and statistically and much larger R2 values. The lack of an impact from the
expected component of monetary policy is usual in this stream of research and this reinforces
the idea that the decomposition of monetary policy actions to expected and unexpected
components is a prerequisite for the accurate estimation of monetary policy effects (Bernanke
and Kuttner, 2005; Bredin et al., 2007; Fatum and Scholnick, 2008).
- Table 1 somewhere here –
In the fifth column of Table 1 we report the impact of monetary policy shocks on
equities but by employing the “identification through heteroscedasticity” methodology of
Rigobon and Sack (2004). This methodology, details of which can be found in the
abovementioned article, returns unbiased proxies for the stock market reaction by employing
an instrumental variables approach. The estimation using this technique returns a slightly
larger coefficient estimate, as is also the case in Rigobon and Sack (2004), suggesting that the
least squares estimation suffers from the endogeneity problem, however the magnitude of this
bias is not significant enough to compromise the validity of our results.
Event study frameworks generally are confronted with issues regarding the selection
of the “events”, as some observations might exert disproportionate effects on the outcome of
the estimation. In Figure 2, we plot the equity returns and the surprise element along with a
trendline, and apart from the negative relationship between them, we also observe that some
observations depart significantly from the general trend. To remedy any sample selection
problems and ensure that some outlier observations will not dominate our results, we control
for the existence of some outlier observations by using the method utilised in Bernanke and
Kuttner (2005) which is described in Figure 3. The observations identified as outliers using
this procedure are those on the 23rd of October 1987, the 8th of October 1990, and the 22nd of
11
March 1991 with influence statistics larger than 0.20 whereas the vast majority have statistics
smaller than 0.02.
- Figure 2 somewhere here The three candidate outlier observations concern large equity responses to monetary
policy actions during periods characterised by economic turbulence. The rate cut of October
1987 follows “Black Monday” on the 19th of October 1987 and is associated with a large
drop in equity prices. The rate cut of October 1990 was met very euphorically by the market,
as it signified a measure against the slowdown in the economy, at a point when the UK
monetary policy entered the Exchange Rate Mechanism, and its flexibility to initiate actions
was naturally hampered. Finally, the rate cut of March 1991 is associated with a significant
decrease in equities during a period when the economic situation was unclear due to the
recession. As a test of robustness we repeat the tests of Table 1 after the exclusion of the
outliers and we report the results in Panel B where we observe that our coefficient estimates
are essentially unaffected.
- Figure 3 somewhere here The symmetric model of Bernanke and Kuttner (2005) presented so far might miss
out some important aspects of this relationship, as not all monetary policy actions are likely
to exert homogeneous effects on future policy expectations (Bernanke and Kuttner, 2005;
Farka, 2009). A monetary policy shock can reflect both the change in the timing of the policy
action (“timing shocks”), and the change in the future trajectory of policy rates (“level
shocks”). The definitions of the level and the timing shocks used in the analysis of this paper
are those typically encountered in similar research, and follow those of Kearns and Manners
(2006). In particular, the level shocks are extracted as the change in the 3-month sterling
12
futures rate, while the timing shocks are defined as the difference between the path shocks
and the current month shocks taken from the change in the 1-month Libor. The definition of
the level shocks suggests that a positive (negative) level shock is indicative of expectations
about higher (lower) interest rates in the following three months. On the other hand, from the
definition of the timing shocks it is suggested that positive (negative) timing shocks are
indicative of postponements (advancements) in the policy action.
The equation used for the examination of the equities’ reaction to timing and path
shocks is:
ri  a  1timi   2 surp i   i
(4)
and the results from estimating this equation, reported in Table 2, are generally consistent
with those in Bernanke and Kuttner (2005) and Farka (2009) for the US, and signify that
level shocks have a larger impact on equities than do timing shocks. Moreover, the
coefficient estimate for the timing shocks is statistically significant and positive in value and
this suggests that the market perceives positively (negatively) the postponements
(advancements) of policy actions. We also consider the effects of timing and level shocks on
inflation expectations and as we see in Table 2, inflation expectations respond mainly, and
positively, to news about changes in the near-term level of interest rates. The five year-ahead
inflation expectations respond also to timing shocks, but as we observe in Panel B of Table 2
this impact is highly contingent on the inclusion of the outlier observations.
The policy reform in 1997 constitutes an important factor which is likely to cause
changes in the relationship between equities and monetary policy shocks, and for this reason
we measure the equity reactions across the two subperiods by estimating the equation:
ri  a  1timi   2 surp i   3 timi  post  97 i    4 surp i  post  97 i    i .
13
(5)
In the third row of Table 2, we present the results from this estimation and they exhibit an
interesting pattern which should be interpreted cautiously as it is only significant at a 10%
confidence level. The opposite signs of the coefficient estimates of the interactive terms
capturing the additional impact after 1997 suggest that the relationships reverse during this
period. The level shocks after 1997 are associated positively with equity returns, while the
timing shocks are associated negatively. Providing an explanation for this pattern requires
further research about the transmission channels of monetary policy which is beyond the
focus of this paper; however, a preliminary explanation for the positive association of level
shocks with equities could be that the level of interest rates is perceived as indicative of
future economic growth. The negative association of timing shocks with equities could be
explained by the rising uncertainty due to the postponement of a policy action during a
regime of transparency where policy actions are to a great extent predictable as is apparent in
Figure 1.
Another case of asymmetric equity reactions which is examined in this paper are the
reactions on days of MPC meetings when no policy decision is taken. In the first line of Panel
A in Table 3 we report the results from the estimation of equation (4), but now the sample
also includes those observations coinciding with days of MPC meetings when no policy
decision took place; similarly to Bernanke and Kuttner (2005). Although the coefficient
estimates are more or less the same, the R2 value is significantly reduced suggesting that these
observations do not explain the negative relationship between monetary policy shocks and
equity returns. To address explicitly this issue, we estimate the equation given by:
ri  a  1timi   2 surp i   3 timi  post  97 i    4 surp i  post  97 i 
  5 (timi  noci )   6 ( surp i  noci )   i
14
,
(6)
which includes interactive terms capturing the additional impact on days of Bank’s inactions,
and are calculated by the use of a binary dummy noci taking the value of 1 on days of policy
inactions and zero otherwise. The coefficient estimates of the interactive terms, presented in
Table 2, are both statistically insignificant suggesting that on these days stock market’s
reaction to timing and level shocks is immaterial.
Two other cases of possible asymmetric reactions examined are those due to the
direction of the policy actions, and the sign of the shocks, and are estimated by the following
equations:
ri  a  1timi   2 surp i   3 timi  inc i    3 surp i  inc i    i
(7)
ri  a  1timi   2 surp i   3 timi  posi    3 surp i  posi    i .
(8)
The direction of the policy surprise is examined by the estimation of equation (7) which
utilises, as in Bernanke and Kuttner (2005), a binary dummy inci taking the value of 1 for
observations coinciding with rate increases and zero otherwise, and the results presented in
Panel B of Table 3 do not support the validity of such an asymmetry. This result suggests that
the Bank can use its interest rate policy instrument in a similar manner both to increase and
decrease stock prices. In a similar vein, we examine the symmetry of the benchmark model
with regards to the sign of the shock by estimating equation (8). The policy dates coinciding
with hawkish market expectations are captured by the binary dummy posi, and the results
from this estimation, reported in Panel C of Table 3, again are not indicative of overreactions
to the arrival of bad news.
In Table 4, we report the results from the examination of the effects of monetary
policy on some suitably constructed portfolios, according to their market capitalisation and
their book-to market ratios. The empirical model used is that in (4) but now ri refers to the
15
returns of “size” and “value” portfolios. The method used for constructing “size” and “value”
portfolios is described in Table 4 and generally it follows that of Fama and French (1993).
The results indicate that in contrast to the situation in the US, as can be seen in Thorbecke
(1997) and Perez-Quiros and Timmermann (2000), the response of the small portfolio is
paradoxically not larger than that of the large portfolio. This finding contradicts the
hypothesis that smaller companies are more vulnerable to monetary policy risk, and a
possible explanation for this could be the smaller scale assets that these types of companies
have. The large and the value portfolio follow a pattern more or less similar to that of the
market, while the timing shocks are more important than level shocks for the growth
portfolio. What could be explaining the latter is that the cash flows of a growth portfolio are
further out in the future and as such a change in the timing of a policy change has a larger
impact on its current price than it would on the other portfolios.
2.2 The Bank’s Communication and the Equities’ Response.
The publications of the Inflation Report and the Minutes of the MPC prompt lengthy
discussions among market participants, as although no policy decisions are taken on these
days, they reveal information to the market not only about the future course of monetary
policy, but also about the future economic output. In this paper, we extract the co-movement
between equities and monetary policy shocks on days of communication, in order to assess
how the news about the future interest rates from these two types of publications is perceived
by the market. To start with, we examine how the release of the Inflation Report affects the
relationship between the monetary policy shocks and the equity returns. This publication
16
features among the most prominent channels through which the Bank transmits information
to the public, and the examination of its role is conducted by the estimation of the two
following equations:
ri  a  1 surp i   i
.
(9)
ri  a  1tim1   2 surp i   i
We employ an event-study approach as in the previous section, but now the event days i are
the days of an Inflation Report release. Although the quarterly schedule of the report’s release
leaves few degrees of freedom, some interesting results arise.
The results from this examination, printed in Panel A of Table 5, reveal that the
decomposition of the policy shocks to a timing and a level component facilitates the
examination of the effects from the release of the Inflation Report. When equity returns are
regressed on monetary policy shocks on these days we find that there is no particular pattern
in this relationship, as was found by Reeves and Sawicki (2007). The decomposition of
policy shocks to timing and level components, however, signifies significant equity responses
to both types of shocks with those to timing shocks being more significant. The strong
reaction to timing shocks suggests that the projections included in the Inflation Report seem
to have important information about the timing of the realisation of the future monetary
policy actions, which is valued more than the information conveyed regarding the future level
of interest rates. What seems to be the case about the information content of the Inflation
Report, according to the results presented, is that the forward looking projections included in
the Inflation Report mainly inform the markets about when to expect the changes in monetary
policy, and less about what changes to expect.
-Table 5 somewhere here –
17
In Panel A of Table 5 we also report the effects that the publication of an Inflation
Report can have on inflation expectations. Intuition suggests that the Bank’s projections
about future inflation expectations are relevant for the market, and hence it is expected that
on these days any shock would be associated with a change in the expectations about future
inflation. Indeed, our results lend support to this hypothesis, as we find that the reaction
coefficient is positive, large in size, and statistically significant, contradicting the results
reported in Ehrmann and Fratzscher (2007). Moreover, from the decomposition of policy
shocks to timing and level components it is extracted that inflation expectations respond only
to news about a change in the future level of interest rates, while the timing reaction estimate
is statistically insignificant.
The efficiency of the Inflation Report as a means of communication depends not only
on the quality of its content, but also on the timing of its release (Geraats, 2006). A central
bank communication close to a monetary policy meeting might insert bias in the market
expectations about future policy actions, and hence cause overreactions. One straightforward
way to examine whether there is an impact from the release of the Inflation Report during the
next and the past MPC meeting is to examine the behaviour of our relationship on the 38
policy meetings following and preceding the releases. The model we are using is:
ri  a  1timi   2 surpi   3 (timi  post  97i ) 
 4 ( surpi  post  97i )   5 (timi  inff i )   6 ( surpi  inff i )   i
(10)
and the binary dummy inffi takes the value of 1 for observations either following, or
preceding the Inflation Report releases, and 0 otherwise, and the sample includes also the
meetings of the MPC when no policy change took place. Also included in this equation are
the interactive terms which capture the additional impact after 1997. The results presented in
18
Panels B and C of Table 5 and are not indicative of any particular pattern on these specific
dates.
The publication of the Minutes of the MPC meetings, which also includes the MPC
members’ individual votes, constitutes the other building block of the improved
contemporary communication scheme of the Bank which is examined in this paper. In the
Minutes of an MPC meeting one finds the first official explanation of the past policy
decisions, and thus it constitutes a first-class opportunity for the markets to see how the
members of the MPC assess the current economic developments (King, 2007). Moreover, the
voting pattern per se is likely to reveal further information concerning the level of uncertainty
in the financial markets, as a unanimous decision suggests that all committee members
perceive the economic developments the same way and as a corollary this reinforces the
information content of monetary policy decisions.
To start with the empirical examination, we initially employ the event study
methodology of (9) in order to extract the impact of monetary policy shocks on equities on
days i when the Minutes of the MPC are released. Our results, printed in Panel A of Table 6,
signify a positive correlation between monetary policy shocks and equities which is only
marginally significant at the 10% level of significance. This result stands supportive to
King’s (2007) assertion that this publication mainly reveals the way that the MPC members
perceive the future economic output, and are not indicative of the future monetary policy
stance. Moreover, the monetary policy news extracted from the release of the Minutes is
strongly positively associated with inflation expectations, but the magnitude of this effect is
smaller than that from the release of an Inflation Report. The inclusion of the timing shocks
does not offer much to our empirical examination, since the equities’ reaction proxies both to
the timing and to the level shocks are statistically insignificant.
19
-Table 6 somewhere here –
The voting pattern of the MPC members, also reported in the Minutes of the MPC, is
another issue which has triggered heated debates among policymakers not only as to whether
they should be published, but also as to whether they can impair the effectiveness of the
communication. Ehrmann and Fratzscher (2007) for instance, raise some doubts regarding the
efficiency of the MPC’s Minutes because of the individualistic approach that the members of
the MPC follow in their voting behaviour with the many cases of dissent voting. Although the
same day effects of the release of the Minutes of the MPC on the stock market do not appear
to be very strong, the effects of a unanimous decision release might materialise at a policy
meeting following this release since after all the Minutes encapsulate news about the
discussion surrounding the monetary policy decisions.
The empirical model we estimate to capture the additional impact on policy meetings
following a unanimous decision is:
ri  a  1timi   2 surp i   3 (timi  post  97 i ) 
(11)
 4 ( surp i  post  97 i )   5 (timi  unai )   6 ( surp i  unai )   i
where unai is a binary dummy variable taking the value of 1 for observations following the
41 releases of MPC meetings showing unanimous decisions, and zero otherwise. What we
observe from the estimation of this model is that for policy meetings following a unanimous
decision there is a strong additional negative association between level shocks and equities
and a strong additional positive association between timing shocks and equities. Moreover
the interactive dummies capturing the additional impact for the period after 1997 also
increase in value. Initially this result suggests that the voting pattern of the MPC is a
significant factor of the equity market reaction. What could be a possible explanation for this
20
pattern is that a unanimous decision is perceived by investors indicative of a certain economic
output, and thus a shock to the following meeting is suggestive of significant revisions and
could result in overreactions.
2.3 Delayed and Before-the-Announcement Effects of a Monetary Policy Action.
In this last section we examine whether the effects from a monetary policy action
materialise in full on the day of a monetary policy meeting, or they are dispersed across a
number of days following the announcement. This kind of research is particularly popular
when examining the reaction of exchange rates to macroeconomic announcements, and its
results can show if the event study methodology employed in the previous section misses out
a significant component of the effects of monetary policy shocks on equities (see, e.g., Evans
and Lyons, 2005 and Fatum and Scholnick, 2008).
In the empirical analysis, we test whether the monetary policy actions exert some kind
of delayed effects which do not materialise on the same day of the announcement, but up to jdays ahead. We concentrate our attention on the period after the introduction of the MPC
framework, as any discussion about delayed effects is more meaningful under a regime when
the markets know when to expect a decision. The empirical methodology used is that in
equation (12), which essentially involves a linear regression of the j-period ahead daily equity
returns on the timing and the level shocks on days i when a policy action occurred, and is
similar to the one employed by Fatum and Scholnick (2008). This way we capture the comovement between the equities and the monetary policy shock for a period of 10 trading days
after the action of the Bank.
21
The results from estimation of equation:
ri  j  a  1, j timi   2, j surp i   i  j
(12)
are printed in Table 7 and signify that monetary policy actions exert significant delayed
effects for a period up to 8 trading days after a change in the policy rate occurred. For the first
3 days the equity markets appear to be positively correlated with level shocks, while this
relationship changes direction during the later days of our sample and becomes negative
when the markets apparently price the effects of higher discount rates on equities. As far as
the timing shocks are concerned, a similar pattern arises as during the first three days they
appear to be negatively correlated with equity returns while in the later days the correlation
becomes positive.
3.
Conclusion
The debate among policymakers about the role of central banks in financial markets,
and the increased emphasis that is attributed to the stock market channel of monetary policy
transmission has brought the identification of the effects of monetary policy on equities to the
forefront of academic research. Moreover, in an economic environment where the role of
expectations has become a sine qua non to discussions about the effects of monetary policy,
the recent turn towards Inflation Targeting regimes cannot be ignored and should be included
as an important parameter in any empirical examination of such effects.
In the first section of our analysis we consider the contemporaneous relationship
between Bank’s actions and equity returns, and several aspects of this relationship are
22
examined. Initially, our results highlight the importance of the decomposition of policy
actions to unexpected and expected components, as the equities’ reaction on raw policy
actions are undersized and thus misleading as to the actual impact. Another case we consider
in this paper are the effects on equities of monetary policy shocks signifying changes in the
level of the future interest rates and those signifying changes in the timing of the interest
rates. The level shocks exert larger impact on equities than the timing shocks, the latter
however are significant enough to indicate that investors perceive news about postponements
(advancements) as good (bad) news.
An interesting result obtained in this paper is that for the period after the introduction
of the Inflation Targeting regime in 1997, the relationship between equities and monetary
policy shocks reverses and the timing shocks are negatively associated with equities while the
level shocks are positively associated. This change in the pattern should be further examined
in accordance with the transmission channels of monetary policy through equity prices. As
regards the effects of the timing shocks under the new regime, the postponements are bad
news signifying possibly more uncertainty, while the advancements are good news reducing
the uncertainty.
The case of some asymmetric responses is examined in the second section of this
paper. The direction of the policy actions and the sign of the shocks do not cause asymmetric
reactions in the equity market, while on the policy meeting days when no action has been
taken the equities do not respond. Moreover in this paper we categorise firms according to
their market capitalisation and their book-to-market ratios, and we find significant variations
in the monetary policy effects according to the type of the firm.
In our analysis we focus our attention on the effects of two types of communication
utilised by the Bank under the new regime, the Inflation Report and the Minutes of the MPC.
23
We find that the Inflation Report reveals important news to investors especially as regards the
timing of future policy actions. The Minutes of the MPC do not trigger large reactions to the
equity markets although we find indications that on these days markets react to the economic
news from the Minutes. Finally, we find empirical evidence that markets’ reactions to MPC
meetings are stronger after the news about a unanimous decision suggesting a shock
following a unanimous decision causes overreactions in the market.
In the last section of this paper we examine the time horizon of the effects from
monetary policy actions. Our results indicate that during the period after 1997, delayed
effects are significant and strong up to 8 trading days after the action. This result poses new
challenges for the empirical examination of the effects of monetary policy actions on equities
as the event study frameworks miss out the delayed effects.
24
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26
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27
5. Tables and Figures
Table 1
The response of the UK equities to monetary policy.
In the first row the results of regression ri = α + β ΔiiUK + εi are printed, and they display the response of
stock market returns to raw monetary policy changes. ri is the daily return on the FTSE All Share stock market
index, ΔiiUK is the raw daily change in the repo rate of the Bank of England calculated on the day of a policy
announcement i, and εi is the error term which is assumed to be orthogonal to the regressors. In the next three
rows the results from the Bernanke and Kuttner (2005) model ri = α + β1 exi + β2 surpi + εi are printed, where
exi is the expected, surpi is the unexpected part of monetary policy and εi is the error term which is assumed to
be orthogonal to the regressors. In this paper we consider three proxies for the unexpected component of
monetary policy deriving from the 1-month Libor, the 3-month Libor, and the 3-month sterling futures rate. In
the fifth row the reaction of equities to monetary policy shocks are presented by utilising the estimation
technique developed by Rigobon and Sack (2004). In the second Panel the results of the benchmark regression
after the exclusion of the outlier observations are printed. The t statistics which are reported in parentheses are
calculated using Newey-West estimates of standard errors.
Panel A: Full sample
a
ΔiiUK
exi
surpi
(1-m
Libor)
surpi
(3-m
Libor)
surpi
(3-m
futures)
R2
DW stat
-0.66
(-5.06)***
-
-
-
-
0.14
1.49
ri
-0.13
(-1.23)
-0.07
(-074)
-
0.23
(0.79)
-1.84
(-5.35)***
-
-
0.24
1.60
ri
-0.09
(-0.89)
-
0.02
(0.12)
-
-1.82
(-6.64)***
-
0.24
1.45
ri
-0.12
(-1.14)
-
-0.18
(-0.87)
-
-
-1.68
(-3.95)***
0.21
1.49
ri
-0.01
(-0.07)
-
-
-
-
-1.98
(-3.81)***
-
-
ri
Panel B: Excluding outliers
ri
-0.12
(-1.21)
-0.64
(-4.90)***
-
-
-
-
0.15
1.60
ri
-0.06
(-0.69)
-
0.06
(0.22)
-1.63
(-5.15)***
-
-
0.22
1.69
ri
-0.07
(-0.73)
-0.09
(-0.99)
0.01
(0.07)
-
-1.73
(-6.67)***
-
0.22
1.59
-
-
0.23
1.64
-
-
-
-
ri
ri
-
-0.06
(-0.31)
-0.21
(-1.09)
-
-1.75
(-6.15)***
-1.99
(-5.31)***
(*/**/*** means that t statistics are significant at the 10%/ 5%/1%level respectively)
28
Figure 1
The unexpected component of monetary policy decisions
This graph depicts the unexpected component of monetary policy as calculated by the methodology of Kuttner
(2001). The surprise component is defined as the daily difference in the 3-month sterling futures contract on the
day of a policy decision.
29
Figure 2
Scatterplot of equity returns and monetary policy surprises
This Figure prints a scatterplot of the UK equity returns and the monetary policy surprises as extracted by
market-based instruments and are depicted in Figure 1. The scatterplot includes 118 observations that are
described in section 2.1 in the main text.
30
Figure 3
Influence statistics of the observations of the benchmark model
This Figure prints the influence statistic of each observation in the benchmark model of Bernanke and Kuttner
(2005). The relative effect of each observation is estimated by the formula ΔβιΤΣΔβι, where Σ is the estimated
covariance matrix and Δβι is the change in the estimated coefficient vector after excluding observation i.
31
Table 2
Timing vs Level Surprises
In the first row the results from regression ri = α + β1 timi + β2 surpi + εi are printed where timi represents the
shocks due to the timing of the monetary policy actions described in the main body of the text, and surpi
represent the shocks due to the change in the expected level of the policy rate, defined as the change in 3-month
sterling futures rate. The second row reports the results from regression einfli = α + β1 timi + β2 surpi + εi where
einfli stands for the five year ahead inflation expectations implied from the inflation linked bonds. The third row
reports results from regression ri = α + β1 exi + β2 timi + β3 surpi+ β4 (timi x post-97i) + β5 (surpi x post-97i) + εi
where post-97i is binary dummy taking the value of 1 for observations after 1997 and zero otherwise. Equations
with dependent variable including the term (outliers) report the results from regressions after the exclusion of
the outliers. The t statistics which are reported in parentheses are calculated using Newey-West estimates of
standard errors.
Panel A: Full sample
a
timi
surpi
(timi x
post-97i)
(surpi x
post-97i)
R2
DW stat
ri
-0.06
(-0.68)
1.25
(1.85)*
-1.88
(-6.03)***
-
-
0.25
1.56
einfli
0.11
(0.53)
2.09
(2.13)**
3.47
(6.19)***
-
-
0.31
1.63
ri
-0.09
(-0.94)
1.43
(1.97)*
-1.94
(-5.69)***
-5.81
(-1.93)*
3.50
(1.76)*
0.29
1.52
Panel B: Excluding Outliers
ri
0.86
(1.73)*
-1.94
(-7.05)***
-
-
0.25
1.67
(outliers)
-0.07
(-0.81)
einfli
(outliers)
0.10
(0.49)
1.77
(1.61)
3.71
(6.08)***
-
-
0.29
1.50
ri
-0.07
(-0.76)
1.06
(2.06)**
-1.99
(-6.78)***
-5.44
(-1.81)*
3.58
(1.79)*
0.29
1.65
(outliers)
(*/**/*** means that t statistics are significant at the 10%/ 5%/1%level)
32
Table 3
Asymmetries in Equities’ Market Response.
In Panel A the results from regression ri = α + β1 timi + β2 surpi+ β3 (timi x post-97i) + β4 (surpi x post-97i) + β5
(timi x noci) + β6 (surpi x noci) + εi are reported, where noci is a binary dummy taking the value of 1 for days of
MPC meetings when no policy action is taken. In Panel B the results from regression ri = α + β1 timi + β2 surpi+
β3 (timi x inci) + β4 (surpi x inci) +εi. are printed where inci is a binary dummy taking the value of 1 for
observations coinciding with rate hikes and zero otherwise. In Panel C the results from regression ri = α + β1
timi + β2 surpi+ β3 (timi x posi) + β4 (surpi x posi) +εi. are printed where posi is a binary dummy taking the value
of 1 for observations coinciding with positive shocks and zero otherwise. Equations with dependent variable
ri(outliers) report the results from regressions after the exclusion of the outliers. The t statistics which are
reported in parentheses are calculated using Newey-West estimates of standard errors.
Panel A: No actions in monetary policy
a
timi
surpi
(timi x
post-97i)
(surpi x
post-97i)
(surpi x
noci)
(timi x
noci)
R2
DW stat
ri
-0.09
(-1.26)
1.14
(2.46)*
-1.83
(-5.56)***
-
-
-
-
0.14
1.69
ri
-0.08
(-1.17)
1.43
(1.96)*
-1.94
(-5.73)***
-5.81
(-2.04)**
3.50
(1.58)
6.39
(1.21)
-0.78
(-0.18)
0.20
1.68
ri
-0.08
(-1.07)
0.79
(1.72)*
-1.85
(-7.04)***
-
-
-
-
0.13
1.75
-0.07
(-1.03)
1.05
(2.05)
-1.99
(-6.80)***
-5.43
(-1.93)**
3.57
(1.66)*
6.42
(1.22)
-0.76
(-0.18)
0.19
1.77
(outliers)
ri
(outliers)
Panel B: Monetary Policy effects on policy hikes
a
timi
surpi
(timi x
post-97i)
(surpi x
post-97i)
(surpi x
inci)
(timi x
inci)
R2
DW stat
ri
-0.17
(-1.36)
2.60
(2.01)**
-2.56
(-5.20)***
-6.52
(-2.19)**
3.86
(1.96)*
0.73
(1.08)
-1.89
(-1.37)
0.31
1.53
ri
-0.11
(-0.94)
1.70
(1.85)*
-2.43
(-4.34)***
-5.86
(-1.92)*
3.83
(1.84)*
0.53
(0.72)
-0.93
(-0.89)
0.29
1.65
(timi x
post-97i)
-6.06
(-1.82)*
-5.10
(-1.64)
(surpi x
post-97i)
3.66
(1.79)*
3.61
(1.69)*
(surpi x
posi)
0.33
(0.35)
0.48
(0.60)
(timi x
posi)
-0.47
(-0.30)
0.80
(0.76)
R2
DW stat
0.29
1.53
0.29
1.64
(outliers)
Panel C: Shock Sign Asymmetries
ri
ri
(outliers)
a
timi
surpi
-0.10
(-0.87)
-0.11
(-1.00)
1.75
(1.14)
0.59
(0.59)
-2.17
(-3.07)***
-2.28
(-3.77)***
(*/**/*** means that t statistics are significant at the 10%/ 5%/1%level)
33
Table 4
Monetary Policy on Size and Book to Market Portfolios
This table presents the results from regression ri = α + β1 exi + β2 timi + β3 surpi + εi which examines the effects
of timing and level monetary policy shocks on UK equity portfolios constructed with regards to their market
capitalisation values and their book-to-market ratios in a similar vein to Fama and French (1993). The small
portfolio consists of the decile 1 returns of the FTSE All Share firms rebalanced according to their market value
on June every year, while the large portfolio is the decile 10. The value portfolio consists of the decile 10
returns of the FTSE All Share firms rebalanced according to the book to market ratio on June every year, while
the growth portfolio is the decile 1. The t statistics which are reported in parentheses are calculated using
Newey-West estimates of standard errors.
Panel A: full sample
a
timi
surpi
R2
DW stat
ri
small
0.17
(1.98)*
1.01
(1.98)**
-1.26
(-4.11)***
0.15
1.64
ri
l arg e
-0.06
(-0.61)
0.82
(1.37)
-1.76
(-6.36)***
0.19
1.59
ri
value
-0.08
(-0.81)
1.04
(1.83)*
-2.46
(-4.50)***
0.31
2.01
growth
-0.19
(-1.62)
1.51
(1.69)*
-1.19
(-1.93)*
0.10
1.54
ri
Panel B:Excluding Outliers
a
timi
surpi
R2
DW stat
ri
small
0.17
(1.98)**
0.78
(1.83)*
-1.14
(-5.00)***
0.12
1.52
ri
l arg e
-0.05
(-0.47)
0.50
(1.03)
-1.85
(-5.83)***
0.19
1.66
ri
value
-0.11
(-1.03)
0.87
(1.46)
-2.25
(-4.27)***
0.25
1.91
growth
-0.18
(-1.67)*
0.71
(1.13)
-1.27
(-2.50)**
0.08
1.65
ri
(*/**/*** means that t statistics are significant at the 10%/ 5%/1%level)
34
Table 5
The UK equity market and the Inflation Report releases.
In the first row of Panel A the results from regression ri = α + β surpi + εi are printed while in the third row we
replace the ri with einfli. In the second row of Panel A, we print the results from regression ri = α + β1 timi + β2
surpi + εi while in the fourth row we replace ri with einfli. The dataset in this estimation spans from the Inflation
Report release of August 1997 until that of November 2006 and includes 38 observations. In Panel B the results
from regression ri = α + β1 timi + β2 surpi + β3 (surpi x post-97i) + β4 (timi x post-97i) + β5 (surpi x inffi) + β6
(surpi x inffi) + εi are reported where inffi is a binary dummy taking the value of 1 at a policy meeting following
the release of an Inflation Report and zero otherwise. The sample size includes 200 events and spans from the
rate hike of November 1982 until November 2006 and includes also the dates of MPC meetings when no action
took place. In Panel C the results from the same regression as in Panel B are reported, but now inffi is a binary
dummy taking the value of 1 at a policy meeting preceding the release of an Inflation Report and zero otherwise.
Equations with dependent variable including the term (outliers) report the results from regressions after the
exclusion of the outliers. The t statistics which are reported in parentheses are calculated using Newey-West
estimates of standard errors.
Panel A: The effects on equities from the release of the Inflation Report
a
timi
surpi
R2
DW stat
ri
-0.09
(-0.86)
-
-0.34
(-0.11)
0.00
1.66
ri
-0.13
(-1.24)
6.75
(2.74)***
-5.47
(-1.74)*
0.11
1.80
einfli
0.28
(0.83)
-
34.46
(3.20)***
0.26
2.35
einfli
0.26
(0.80)
3.48
(0.30)
31.81
(2.92)***
0.27
2.37
Panel B: inffi takes the value of 1 for MPC meetings following the release of an Inflation Report
(surpi x
(timi x
(surpi x
(timi x
a
timi
surpi
post-97i)
post-97i)
inffi)
inffi)
-0.10
1.42
-1.94
4.42
-5.24
0.67
0.61
ri
(-1.41)
(1.96)*
(-5.69)***
(1.52)
(-2.21)**
(0.14)
(0.11)
ri
-0.09
1.05
-1.99
4.53
-4.87
0.57
0.67
(-1.29)
(2.04)**
(-6.74)***
(1.55)
(-2.10)**
(0.11)
(0.13)
(outliers)
Panel C: inffi takes the value of 1 for MPC meetings preceding the release of an Inflation Report
(surpi x
(timi x
(surpi x
(timi x
a
timi
surpi
post-97i)
post-97i)
infri)
infri)
-0.10
1.42
-1.94
6.46
-5.51
-4.16
1.27
ri
(-1.28)
(1.96)* (-5.69)***
(2.39)**
(-2.90)***
(-1.03)
(0.30)
ri
-0.08
1.05
-1.99
6.54
-5.14
-4.18
1.30
(-1.15)
(2.04)**
(-6.75)***
(2.41)**
(-2.81)**
(-1.04)
(0.31)
(outliers)
(*/**/*** means that t statistics are significant at the 10%/ 5%/1%level)
35
R2
DW stat
0.18
1.71
0.17
1.79
R2
DW stat
0.19
1.70
0.18
1.79
Table 6
The UK equity market and the MPC Minutes releases.
In the first row of Panel A the results from regression ri = α + β surpi + εi are printed while in the third row we
replace the ri with einfli and the regression is einfli = α + β surpi + εi. The dataset in this examination spans from
the Minutes’ release of July 1997 until that of December 2006 and includes 114 observations. In the second row
of Panel A we report results from regression ri = α + β1 timi + β2 surpi + εi while in the fourth row we replace ri
with einfli. In Panel B the results from regression ri = α + β1exi + β2 timi + β3 surpi + β4 (surpi x post-97i) + β5
(timi x post-97i) + β6 (surpi x unai) + β7 (surpi x unai) + εi are reported. The sample size includes 200 events and
spans from the rate hike of November 1982 until November 2006 and includes also the dates of MPC meetings
when no action took place. The binary dummy unai takes the value of 1 at a policy meeting following the
release of the Minutes indicating a unanimous decision of the MPC. Equations with dependent variable
including the term (outliers) report the results from regressions after the exclusion of the outliers. The t statistics
which are reported in parentheses are calculated using Newey-West estimates of standard errors.
Panel A
a
timi
surpi
R2
DW stat
ri
-0.16
(-1.52)
-
4.89
(1.81)*
0.03
1.90
ri
-0.17
(-1.60)
2.49
(0.90)
2.54
(0.67)
0.03
1.91
einfli
0.06
(0.32)
-
22.48
(4.53)***
0.17
1.81
einfli
0.05
(0.26)
2.56
(0.42)
20.08
(2.31)**
0.17
1.79
Panel B
ri
ri
(outliers)
a
timi
surpi
-0.06
(-0.86)
-0.05
(-0.71)
1.44
(1.96)*
1.06
(2.05)**
-1.94
(-5.81)***
-1.99
(-6.93)***
(surpi x
post-97i)
8.96
(3.68)***
9.06
(3.73)***
(timi x
post-97i)
-7.27
(-4.04)***
-6.91
(-4.01)***
(*/**/*** means that t statistics are significant at the 10%/ 5%/1%level)
36
(surpi x
omoi)
-15.98
(-5.00)***
-16.07
(-5.03)***
(timi x
omoi)
12.69
(4.23)***
12.80
(4.26)***
R2
DW
stat
0.24
1.73
0.24
1.82
Table 7
Delayed Effects of Monetary Policy.
In this Table we print the results of regression ri+j = α + β1 timi + β2 surpi + εi for j=0, 10. The t statistics which
are reported in parentheses are calculated using Newey-West estimates of standard errors.
R2
DW stat
0.25
1.56
0.16
1.81
0.05
1.79
0.16
1.48
0.17
1.84
0.25
2.78
0.21
1.98
0.06
1.73
0.10
1.63
2.22
(0.95)
0.04
1.98
-1.17
(-0.94)
0.02
2.34
ri , j 8
a
-0.06
(-0.68)
0.00
(0.04)
-0.22
(-0.82)
0.17
(1.04)
0.06
(0.31)
-0.01
(-0.15)
-0.08
(-0.61)
0.21
(1.16)
0.08
(0.37)
timi
1.25
(1.85)*
-6.17
(-2.28)**
-4.48
(-0.96)
-6.88
(-2.37)**
7.76
(1.93)*
3.73
(2.13)**
3.66
(2.49)**
3.48
(1.64)
3.45
(1.12)
surpi
-1.88
(-6.03)***
3.78
(1.76)*
1.98
(0.65)
2.74
(1.47)
-3.95
(-1.35)
-4.67
(-4.59)***
-4.47
(-3.74)***
-3.11
(-1.61)
-4.32
(-2.15)**
ri , j 9
0.07
(0.44)
-2.57
(-0.88)
ri , j 10
0.02
(0.22)
1.90
(0.91)
ri , j o
ri , j 1
ri , j  2
ri , j 3
ri , j  4
ri , j 5
ri , j  6
ri , j  7
(*/**/*** means that t statistics are significant at the 10%/ 5%/1%level)
37