1. Introduction

Monetary policy affects economic activity and

inflation through a series of channels, which are

collectively known as the transmission

mechanism. Changes in the monetary

authority’s policy rate are generally transmitted

into changes in the market and retail interest

rates, which can affect households’

consumption and saving decisions, firms’

investment and borrowing behaviour and finally

output and inflation. In a flexible exchange rate

economy, changes in the policy rate also affect

the value of the domestic currency vis-à-vis

other currencies, influencing the

competitiveness of domestic exports and

imports, and ultimately affecting net trade and

hence aggregate demand. In addition to this,

exchange rates can also have a direct effect

on consumer price inflation, via domestically

consumed imported goods.

The Monetary Conditions Index (MCI) was

developed in the early 1990s with the aim of

providing information on the stance of monetary

policy taking into account both the interest rate

and the exchange rate channels. It is a

weighted average of the short-term interest rate

and exchange rate. Initially it was used as an

operational target by the Bank of Canada and

Reserve Bank of New Zealand, but

subsequently its role diminished due to

problems in its construction and interpretation,

and it is now used less frequently and only as

one indicator amongst many in monetary policy

analysis.

With this in mind, it is not the aim of

this paper to contribute to the current

conjunctural monetary analysis, but rather to

discuss the origins of the MCI and to highlight

some limitations and issues relating to its

implementation and use.

With the increasing financial complexity of the

modern economy, growing attention is paid to

how other financial variables including the price

of various asset classes affect the economy.

Moreover, policy makers have placed an

increased emphasis on financial stability

considerations given that changes in financial

variables affect wealth and balance sheet

considerations of various sectors in the

economy. This has led to an interest in the

development of Financial Conditions Indices

(FCI), which seek to provide a simple measure

of how financial market variables impact on the

economy above and beyond the standard

interest rate and exchange rate channels.

However, in many senses the FCI can be seen

as an extension of the earlier MCI. Moreover,

many of the methodological difficulties

associated with the construction of the MCI, as

well as many of the caveats and criticisms, are

also germane to FCIs.

The article proceeds as follows: Section 2

describes the MCI and its construction in more

detail, and identifies possible uses for the

index. Section 3 outlines the various important

issues related to the index regarding both its

methodology and its interpretation, while

section 4 looks at the MCI for some major

economies, and briefly discusses its

movements over the past decade. This article

also includes two boxes: the first provides

greater technical information on the choice of

weights used to estimate unobservable

elements of the MCI, while the second box is

based on a case study of the Canadian and

New Zealand MCI.

2. A description of the MCI

The MCI, which was first developed by the

Bank of Canada in the early 1990s, is

calculated based on a weighted average of

changes in short-term interest rates and

exchange rates relative to some reference

period. It aims to provide information on the

economy and inflation for monetary policy

analysis. A change in the index indicates how

‘tight’ or ‘loose’ monetary conditions in the

economy are, relative to a certain reference

level.

The most obvious benefits of the MCI are that it

is straightforward, easy to understand, and, in

the past, was seen as a better indicator than

just focusing on interest rates, given the role of

the exchange rate in the transmission

mechanism. Even though it was used by

central banks, international organisations, as

well as financial corporations in different ways

over the years, it has various shortcomings.

It is

difficult to operationalise given that it combines

a monetary policy tool (interest rate) and a

macroeconomic outcome (the exchange rate)

and a lot of judgement is required for its

calculation.

A Discussion of the Monetary

Condition Index 70 Quarterly Bulletin 01 / January 10

2.1 Definition

The basic formula for the MCI is as follows:

MCI = −[θ1(Rt − R*) + θ2 ((et − e*) × 100)]

(Equation 1)

• Rt represents the level of the short term

interest rate, and et is the log of the

effective exchange rate at a particular

point in time t

2

. If e increases it implies

that the domestic currency is

appreciating. Either real or nominal rates

for each of these variables can be used.

Short-term money market rates are used,

as they are closely aligned to the policy

rate, and the decisions by monetary

authorities transmit quickly into these

rates.

• The asterisk denotes the reference level

of each of the respective variables. In

theory, the reference or base levels for

the variables should reflect ‘‘neutral’’

economic conditions, but in practice this

is difficult to operationalise, hence a

simple average over a period of time is

generally used3

. Rather than focusing on

the absolute levels of the variables,

changes in the variables with respect to

this base level are used. If the (Rt − R*)

or respectively the (et − e*) component is

positive it means that the current interest

rate, or respectively the exchange rate,

is higher than that observed on average

during the reference period.

• The weights applied to interest and

exchange rates, θ1 and θ2 respectively,

typically add up to unity. The ratio θ1/θ2

reflects the relative impact of the interest

rate and exchange rate on the economy

as measured by either aggregate

demand or prices, although the former

method appears to be much more 2

The short-term rate usually employed is the 3-month interbank

rate, and the effective exchange rate is a weighted average of

bilateral exchange rates against major trading partners.

The

difference in the log of the exchange rate is mulitplied by 100 in

order to express it as a percentage. 3 Ideally, optimal or equilibrium levels of the interest rate and

exchange rate could be used, estimated from a Taylor type rule or

an equilibrium exchange rate model, but in practice these are

exceptionally difficult to accurately estimate.

prevalent in the literature4

. Therefore, if

there is a rise of θ1 percentage points in

the interest rate, it will have the same

effect on the policy goal as a θ2 percent

appreciation of the domestic currency,

so that a larger ratio will mean a weaker

overall affect of the exchange rate in the

MCI.

There are a number of possible

methods to derive these weights, which

are outlined in Box 1.

• Finally, a negative sign is usually

attached to the overall computation of

the index so that, when there is a

decline (increase) in the index, as

defined by Equation 1 above, it indicates

that monetary conditions have tightened

(loosened)5

.

2.2 Possible uses

In the implementation of policy, monetary

authorities focus on a number of variables, from

the ultimate target (frequently inflation) at one

end of the spectrum to the policy instruments

(such as the short-term interest rate) at the

other. Due to long lags and the indirect

connections between the target and the

instruments, monetary authorities resort to

operational targets6

, information variables and

indicators that link the two.

These intermediate

variables or targets are closely linked to the

ultimate target and are influenced by changes

in the policy instrument (Freedman, 1994). The

MCI falls within this group of intermediate

measures, and can be used as an indicator or

operational target in the conduct of monetary

policy.

When the Bank of Canada developed the MCI

in the early 1990s, it was used as an

operational target in the design of monetary

policy, and was then subsequently used in the

same way by the Reserve Bank of New

4 Some commentators criticised the practice of deriving the weights

from an aggregate demand function when the overall target was

inflation, as was the case in Canada and New Zealand.

However,

one of the reasons for focusing on aggregate demand is,

‘‘because it is the output gap, along with expected inflation, that is

the principal driving force behind increases and decreases in the

inflationary pressures and it is changes in aggregate demand that

are a key determinant of changes in the output gap’’ (Freedman,

1994).

5 The rationale for the negative sign is that tighter monetary

conditions generally bear down on activity levels and looser policy

generally does the reverse.

6 The operational target of monetary policy is an economic variable,

which the central bank aims to control by use of its monetary

policy instruments. It is the variable the level of which the

monetary policy decision-making committee of the central bank

actually decides upon in each of its meetings (Bindseil, 2004).

A Discussion of the Monetary

Condition Index

Quarterly Bulletin 01 / January 10 71

Box 1: Calculating the MCI weights

The MCI, as outlined in Equation 1, contains certain unobservable elements that

need to be estimated, namely the reference levels for the interest and exchange

rates, and the weights attached to deviations between these variables and their

respective reference levels. Overall, the size of θ1/θ2 should capture the effect of

percentage point changes in the interest rate relative to a percentage change in

the exchange rate and its accuracy is conditional on the particular model used

for estimation. This box reviews the different methods used in the literature to

estimate the weights.

Batini and Turnball (2002) posit that there are

three main methods for estimating the MCIs’

weights:

Single Equation based MCIs

One of the most common ways of deriving the

weights based on the above rationale involves

estimating an aggregate demand function,

similar to the following:

∆yt = α ∆ Rt + β ∆ et + x + error

Where ∆ is the first difference operator which

captures the change in the variable over time1

,

y is Gross Domestic Product (GDP), R is the

interest rate and e is the exchange rate.

The

subscript t refers to the current or latest time

period. Overall, this function seeks to discover

the effect of changes in interest rates,

exchange rates and other economic variables,

represented by x in the equation above (i.e.

current and lagged values for GDP of main

trading partners), on GDP.

From this equation,

α and β, the partial derivatives of the interest

and exchange rates respectively, can act as

the weights θ1 and θ2, so that the ratio of the

coefficients in equation 1, θ1/θ2, equals the ratio

α/β.

Multiple Equation based MCIs

There are also more elaborate multiple

equation-based methods. These methods

involve estimating and simulating structural

macro-econometric models in which the

weights are then obtained from a system of

equations rather than just one.

The weights can

also very often be estimated using vector

autoregressive models (VARs), with time series

of GDP, exchange rates and interest rates.

Subsequently, impulse response functions

(IRFs) are derived. The IRFs measure the

response of GDP to individual shocks in both

the interest rate and the exchange rate.

The

weights θ1 and θ2 are then based on a

cumulative average responsiveness of GDP to

shocks in the interest and exchange rate

respectively over a certain number of quarters.

A critical element in the use of this approach is

the correct identification of shocks to the

relevant variables.

Many banks and

international organisations use the weights

estimated from existing structural

macroeconomic models, for example the OECD

bases its weights on results from their Interlink

Model.

MCIs based on large macroeconometric models, especially those that

contain a monetary policy reaction function, are

more instructive as they take account of more

features of the economy.

Trade share based MCI

This final method is simpler to calculate. The

exchange rate weight is based on the long run

exports-to-GDP ratio and the interest rate

weight is simply one minus this ratio.

The

rationale is that this net trade component

captures the effect of the exchange rate on

GDP relative to interest rates.

However, it is

used less frequently given the simplicity in

relation to the estimation of the weights and,

consequently, the lack of detail about the

effects of the relevant variables on the

economy.

Overall, the multiple equation based model is

generally deemed to be optimal, as it takes

account of the cumulative lagged impact of the

different variables.

The dynamics of the

underlying model are very important; a model

that takes account of the different lags at which

an economy responds to changes in interest

rates and exchanges rates would perhaps

deliver a more accurate index. If a model is too

simple, or fails to take into account key

characteristics of behaviour, the measurement

of the weights can be flawed, meaning that the

MCI itself is built on erroneous foundations.

1

The operator is defined as ∆yt = yt − yt−1, which is the change in

GDP from the previous period.

A Discussion of the Monetary

Condition Index

72 Quarterly Bulletin 01 / January 10

Zealand between 1997 and 1999 (see Box 2).

The rationale for adopting this policy was that it

may be difficult to predict the response of the

foreign exchange market to a change in the

policy rate (Gerlach and Smets, 2000).

The

theory of uncovered interest rate parity7

suggests that interest rates and exchange rates

are related in a systematic way, although

empirically this relationship does not always

hold.

Hence, there is still no completely clear

understanding of the interaction between

interest rates and exchange rates.

Above is wrong

The method used in the case of the operational

target, which was particular to these two

countries, involved having an inflation target8

and deriving a solution for future interest rates

and exchange rates consistent with the target

after having taken into account domestic and

foreign economic conditions.

Using these

projections the bank was able to derive the so called ‘desired’ MCI level, which could

represent a range of values rather than point

estimates.

The forward-looking focus of this

approach took into account the lags between

the monetary policy stance or changes in it and

the effect on the rate of inflation9

. If the actual

level of the MCI deviated from the desired

path, the Bank would use the tools at its

disposal (for example, the overnight rate) to

adjust the index accordingly.

It is important to note that using the MCI as an

operational target does not imply an automatic

reaction to all exchange rate changes, since

the target level of the MCI varies in response to

shocks that affect the exchange rate.

In the

case of an aggregate demand shock, the

desired level of the MCI will change, whereas if

there is a credibility shock, the target MCI level

should remain unchanged ceteris paribus.

As

Charles Freedman, the deputy Governor of the

Bank of Canada at the time put it,

‘‘A lot of judgement goes into it, and there

is a lot of cross-checking against important

information variables such as the rate of

growth of monetary aggregates10’’.

7 The theory of uncovered interest rate parity states that ‘‘the

exchange rate against a foreign currency deviates from its

expected value at some future time by the size of the interest rate

differential (over the appropriate horizon) with that country’’

(Stevens, 1998).

8 Canada had an inflation range of 1-3 per cent and New Zealand

had a target of 0-3 per cent. 9 For Canada, Freedman (1995) estimated that monetary actions

would influence the rate of inflation in about 6 to 8 quarters ahead.

10 Excerpt from remarks made by Deputy Governor Freedman to the

Conference on International Developments and Economic

Outlook for Canada, 15 June 1995.

The use of the MCI as an operational target

diminished over time, due to pitfalls that

emerged when the index was used in this

capacity. In particular there was great

uncertainty regarding the source of exchange

rate movements. A more detailed look at these

problems in Canada and New Zealand, are

discussed in Box 2.

With the MCI’s relevance as an operational

target declining, it has increasingly been used

as an indicator in monetary policy analysis.

In

this capacity, monetary policy tools are no

longer used to adjust the level of the index to a

desired path, but rather it merely helps to

inform policy makers of the current stance of

monetary conditions, and whether they are

tighter or looser relative to other periods.

3. An evaluation of the MCI

The MCI presents some problems both at the

level of construction and in terms of its

conceptual and empirical foundations, which

are outlined in this section.

3.1 Methodological Issues in constructing

a MCI

In constructing a MCI, an initial technical issue

is to determine the appropriate weights.

Since

the weights of the components are not directly

observable, but are based on econometric

estimates, they are highly sensitive to the

model used (see Box 1) — i.e. the MCI ratio

can suffer from model uncertainty.

The main

pitfalls involved in deriving the weights

therefore, vary between the models used and

are consequently model dependent.

The

principal problems include capturing the

correct dynamics of the relationship, as interest

rates and exchange rates can affect the

economy at different speeds, and parameter

constancy, which requires that the coefficients

from the models used to calculate the weights,

must not change depending on the time period

used

11. If these problems are not adequately

dealt with, the weights that are derived risk

being erroneous and may provide an

inaccurate picture of monetary conditions (Eika

et al. (1996) and Batini and Turnball (2002)).

11 For a further and more detailed discussion of the econometric

problems involved in calculating the MCI weights please refer to

Eika et al. (1996) and Batini and Turnbull (2002).

A Discussion of the Monetary

Condition Index

Quarterly Bulletin 01 / January 10 73

Box 2: MCIs as an operational target — problems in practice

A number of difficulties and challenges emerged during the period in which the

MCI was used as an operational target by both the Bank of Canada (BoC) and

the Reserve Bank of New Zealand in the 1990s.

Some examples of these

problems are highlighted in this box.

While the MCI appeared to be attractive as an

operational target for the BoC, it became

evident that there were a number of

shortcomings.

Firstly, there was a tendency on

the part of some observers to treat the MCI as

a precise short-term target for policy, while the

Bank indicated that it should not be treated as

a narrow, precise measure.

Secondly, the

markets started to treat all exchange rate

movements as portfolio readjustments on the

part of investors (portfolio shocks) and,

therefore, came to expect an offsetting interest

rate adjustment every time there was a

movement in the exchange rate, whether or not

such an adjustment was appropriate.

In

addition, the central bank itself had to make a

judgement on the source and likely persistence

of the shock to the exchange rate, in order to

decide on the appropriate response.

Indeed,

this caused problems in 1998, when the rapid

depreciation of the Canadian Dollar produced

accusations of a myopic central bank (Robson,

1998), whereas the BoC argued that the

depreciation signalled looser than desired

monetary conditions that warranted sharp

increases in the policy interest rate.

Given the difficulties mentioned, less emphasis

was placed on the role of the MCI as a

Related to this, even if the model for deriving

the weights is correctly specified and manages

to accurately capture the effects of the interest

rate and the exchange rate on the economy,

over a certain period of time, there is always

the possibility that the monetary transmission

mechanism itself (the effect of the interest rate

and the exchange rate on output) can change

over time for a variety of reasons.

Therefore it is

vital to monitor this system and ideally to

ensure that any changes to how monetary

impulses are transmitted to inflation are

recognised in the MCI. In practice this may be

difficult to achieve.

measure of monetary conditions in the late

1990s and the early part of the current decade.

Subsequently, the MCI was discontinued from

being published by the BoC (2006), and has

not been used as an input into monetary policy

decisions.

Problems also emerged in New Zealand over

the period when the Reserve Bank of New

Zealand employed the MCI as an operational

target (mid-1997-March 1999).

In particular,

interest rates were increased as an automatic

response to a depreciation of the New Zealand

Dollar (NZ$), with little evidence that those

interest rate increases were warranted.

As a

result, interest rates were increased at a time

when a serious drought caused severe water

shortages in New Zealand, the Asian crisis

evolved (1997/1998) and as output growth in

the country turned negative.

Given the

circumstances, this may not have been the

most appropriate action.

Following the

difficulties encountered, the Reserve Bank of

New Zealand subsequently acknowledged that

they ‘‘were slow to recognise the joint impact of

the Asian crisis and the beginning of an

extended drought through 1997 and early

1998’’. They subsequently discontinued using

the MCI in this capacity.

A further technical issue is whether MCIs

should be calculated in terms of real or

nominal variables.

Theoretically, it would seem

preferable to express the MCI on the basis of

real variables as the real MCI takes account of

inflation movements. It is also generally

believed that rational agents consider the real

rather than nominal rates in their consumption

and investment decisions.

However, there is

evidence that individuals can suffer from

money illusion whereby they consider the

nominal rather than the real variables in their

decision making (Akerloff and Shiller, 2009)

(Fehr and Tyran, 2001). Peeters (1999) and

Gerlach and Smets (2000) also put forward the

A Discussion of the Monetary

Condition Index

74 Quarterly Bulletin 01 / January 10

argument that economic behaviour often reacts

on the basis of nominal interest rates in the

short run. Furthermore, the nominal MCI seems

to be a reasonable approximation for the real

MCI in the short run, in the context of a low

inflation environment. See Costa (2000b) and

the ECB (2002).

There are also other factors justifying the use of

nominal variables.

For example, a nominal MCI

may be easier to construct and is also timelier

as inflation data needed for the real measure

are only available on a monthly basis, as

opposed to the daily availability of nominal

interest and exchange rate data.

However, it

should be noted that in a period of high

inflation, the nominal index is likely to show

more pronounced tightening than the real

indices.

The selection of the MCI components is also

an issue that has received more attention in

recent years.

Since the MCI components

should be in line with the nature of the

monetary transmission mechanism and with the

appropriate structure of the relevant economy,

it has been argued that other factors, such as

long-term interest rates12 and asset prices (i.e.

house prices and stock prices), should also be

included in the MCI.

For the euro area, long term interest rates play an important role in the

monetary transmission mechanism, as

investment and consumption behaviour is often

dependent upon long-term rates.

Taking into account the increasing debate over

the role played by asset prices in the monetary

transmission mechanism, through wealth

effects and balance sheet effects, the Financial

Conditions Index (FCI) has been developed in

recent years.

Policy makers and international

organisations often use the FCI in their

assessment of the monetary policy stance.

However, the definition of FCIs differs across

methodologies. While some researchers

compute FCIs that measure the

tightness/accommodativeness of financial

factors relative to their historical average in

terms of an effective policy rate (e.g. Guichard

12

For countries in which long-term financing relationships play a

major role, it would be logically consistent to include a long-term

interest rate. Fixed long-term interest rates exert a larger

influence on consumption and investment decisions in several

countries in Continental Europe, relative to the Anglo-Saxon

countries (Costa, 2000).

and Turner, 2008),

others measure the

estimated contribution to growth from financial

shocks in a given quarter (Swiston, 2008).

The FCI extends the MCI approach by

including other financial variables, including

stock prices, asset prices and long-term

interest rates13, but similar to the MCI, the index

still suffers from certain criticisms, such as

model dependency, ignored dynamics and

parameter inconsistency.

While a full

discussion on such an index is beyond the

scope of this article, a number of interesting

findings are worth noting.

Based on research at

the BoC, which suggested that asset prices

may offer important information about future

inflationary pressures, Gauthier, Graham and

Liu (2004) estimate a number of FCIs for

Canada.

They find that the FCI outperforms the

MCI in many areas, and also that house prices,

equity prices and bond risk premium, in

addition to short and long-term interest rates

and the exchange rate, are significant in

explaining output in Canada.

Goodhart and

Hofmann (2001), also find that house and share

prices are important variables in such an index

for G7 countries, and that the FCI contains

useful information about future inflationary

pressures.

A more recent example of the FCI’s

use is illustrated in a recent paper by Beaton,

Lalonde and Luu (2009).

It looks at the

development and increasing importance of

financial conditions in the US during the current

crisis.

They find that financial conditions have

had a large negative impact on US GDP

growth in the current recession14 and that the

monetary easing undertaken by the Federal

Reserve over the recent financial crisis has not

been sufficient to offset the tightening of

financial conditions.

A final point related to the selection of the

components is that neither money nor credit

plays a role in standard representations of a

MCI.

For example, the same level of a MCI

could be consistent with various rates of

monetary growth, and in no way calls into

question the importance of the money supply in

13

More recently, lending standards have also been included in

FCIs to account for non-price credit conditions (Guichard and

Turner, 2008).

14 Their FCI suggests that financial factors subtracted between 4

and 7 percentage points from quarterly annualised growth in

2009 Q1.

A Discussion of the Monetary

Condition Index

Quarterly Bulletin 01 / January 10 75

the economy or ultimately the monetary nature

of inflation.

This is particularly relevant when

there are quantity constraints or credit

rationing. Given these shortcomings, the MCI

should be interpreted with caution regardless

of whether it is being used as an operational

target, or merely as one indicator among

many.

3.2 Interpretation Issues

Irrespective of the difficulties in constructing a

MCI, interpreting changes in it in terms of their

significance for current monetary policy is not

easy.

Whether it is appropriate or not for a

central bank to make a policy change in

response to a change in the MCI (in the case

of the MCI being an operational target)

depends on the factors underlying changes in

the components.

A given movement of the MCI

may have different consequences in terms of

the final policy objective.

In particular, it is

important to determine the nature of shocks

causing movements in the exchange rate, and

not mechanically follow movements in

individual components, as highlighted in the

case of New Zealand in Box 2.

Furthermore,

Siklos (2000) believes that the simplicity of

MCIs implies a loss of information when the

effects of the component variables are

aggregated, as it can obscure the movements

of the individual components.

King (1997) also

makes the point that ‘‘any attempt to construct

a simple monetary conditions index is akin to

adding together apples and oranges’’,

particularly given that the exchange rate is not

a policy instrument and therefore MCIs mix

variables that are not of the same nature.

Given the difficulty in determining whether any

particular reference period is ‘‘neutral’’ (Banque

de France Bulletin Digest, 1996), most

implementations focus on changes in the index

compared with previous periods, to ascertain if

monetary conditions have tightened or

loosened, rather than looking at the absolute

levels of the index.

It is important to note that

historical averages do not necessarily

represent neutral conditions and furthermore,

structural changes in the economy and

differences in cyclical conditions may also

affect what is understood as neutral conditions.

4. Constructing the MCIs

The following section focuses on developments

in MCIs for the euro area, the UK and the US

over the past decade.

It is important to

emphasise that the purpose of this section is

not to speculate as to which weights may be

best or even to assess the extent to which the

MCIs portray an accurate picture of the

monetary stance.

For each country, there are many plausible

alternative weights specified by various

institutions and academics.

The choice of the

weights can affect the overall level of the index

and also the rate of change of the indices.

In

this analysis, a weight of 6:1 is used for the

euro area, which is used by the European

Commission15,

and weights of 3:1 and 10:1 are

used for the UK and the US respectively.

The

latter weights have been applied by the IMF in

the past.

In terms of the data used in the

construction of the MCI for each country/area,

the short-term interest rate is proxied by the

three-month money market rate while a broad

trade weighted exchange rate proxies the

exchange rate variable.

These series are then

deflated by consumer price indices16.

Finally,

the base/reference periods refer to the average

of both interest and exchange rates from 1993

to present.

4.1 MCIs in Practice

Referring to Chart 1, it is evident that over the

sample period (1999-2009) for the euro area,

there appears to have been a marked

tightening in monetary conditions post 2005,

which is consistent with increasing interest

rates.

Despite the significant economic

developments since the financial crisis, the

MCI, while volatile, has not shown any

substantial changes in its trend.

Meanwhile, the

MCI for the UK shows its only major shift in

trend from around 2007 on.

At this point both

interest rates and exchange rates contributed

to looser monetary conditions.

The movement

of the US MCI during the sample period has

been more variable, and has tended to track

changes in the interest rate, given this

15 This ratio was derived from simulations of the OECD Interlink

Model. 16 Ex-ante real short-term interest rates were also calculated (using

inflation 3-months forward), but the results were very similar.

Brian Twomey