1

Nationalekonomiska Institutionen

Was the Euro interest rate too low for Ireland?

- A time series analysis of the pre-EMU period in light

of the Taylor Rule

Författare: Sharkah Francis & Pawela Oliver

Handledare: Erixon Lennart

Kurs: EC6901 Kandidatuppsats i nationalekonomi

Termin: VT2010

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Abstract

This paper focuses on the application of the Taylor Rule to estimate a counter-

option nominal interest rate suitable for Ireland during the post EMU era. We used

an Ordinary Least Square regression method to estimate the Taylor rule

coefficients, from which we calculate a Taylor type rule interest rate based on the

economic indicators in the post EMU era. The reason behind this study is to

assess the probable benefits Ireland gained or lost upon joining the EMU. To do

so the Taylor Rule is set as a counter-option to the European Central Bank’s

interest rate to show another outcome as rendered by the theoretical rule. We

address the question of loosing monetary policy as a counter-cyclical tool in the

economy as well as the constituency of the European Optimum Currency Area.

We also analyse the reliability of our induced Taylor rule. We found that the

interest rate set by the ECB are not in response to the economic realities in

Ireland.

Acknowledgement

We thank our supervisor associate professor Lennart Erixon for his guidance and

engagement during the entire project.

Keywords: Monetary policy, EMU, Optimum Currency Area, Taylor rule.

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Contents

1. Introduction……………………………………………………………………4

1.1 Background of the study…………………………………………………….4

1.2 Objective of the study……………………………………………………….6

2. Theoretical background……………………………………………………….7

2.1 Theory of Optimal Currency Area…………………………………………..7

2.2 The Taylor Rule……………………………………………………………..9

3. Earlier studies………………………………………………………………...12

4. Empirical Section……………………………………………………………13

4.1 The Regression Model……………………………………………………..13

4.2 Regression Technique and Problems………………………………………14

4.3 Statistical sources and limitations………………………………………….16

4.4 Choice of time period………………………………………………………18

5. Regression result and analysis………………………………………………19

6. Conclusion…………………………………………………………………….21

References……………………………………………………………………….23

Appendix………………………………………………………………………...25

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1. Introduction

1.1 Background of the study

Ireland was once referred to as the “Celtic Tiger”, the best performing economy in

the euro zone. It was hailed across the globe as a model for other countries to

follow, prompting policy makers and investors from around the globe to flock to

Ireland to learn about the secrets behind its economic performance. However this

success was short lived, as Ireland became the euro zone’s first member country to

officially slide into a recession during the present global financial crisis. Ireland

has regulation encouraging foreign direct investment, whereby the economic

growth experienced from 1989, which created the basis for the housing market

growth. A mix of high levels of employment, higher incomes, immigration and

even features in the housing tax system created a greater demand for housing in

Ireland. Inevitably Ireland’s entry into the EMU added more salt into its injuries,

when the ECB led nominal and real short-term interest rates fell sharply.

The housing market as an interest rate sensitive sector of the economy contributed

to the growth trend experienced in Ireland between 2000 and 2006, which in turn

potentially created conditions that put the nation into its present financial

situation. The collapse of the construction industry and the export sector has

created a drop in income and property sales tax revenue, leaving a big hole in the

country’s public finances that has resulted in an increase in government

borrowing. Although the Irish government is not in the same position as it once

was to influence the low interest rates that prevails in the euro zone, it could have

provided fiscal stimulus to avoid the problem, as was done in Finland for instance,

but instead it had to increase taxes and cut on public spending – measures that are

further aggravating the financial problem.

Ireland being an export-dependent economy implies that the economic standings

of its trading partners also affect its potential of getting out of the financial crisis

sooner. The US and the UK are two of Irelands largest trading partners, hence a

mixture of deepening recessions in these countries, with a sharp rise in the value

of the euro against the pound sterling and dollar further worsens the financial

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problem. Ireland’s membership in the EMU therefore means that the necessary

real exchange rate adjustment can only be brought about through changes in

domestic prices – including wages. Whilst the leading majority of the Unions

members were showing reports of collapse, the Irish economy held relatively well

against the storm. Assuming that the ECB follows through on its policy to

maintain the union’s price stability goal calculated mainly on the inflation rate,

M3 expansion, and GDP growth in given member country’s we can easily

establish that the ECB will allow a lower interest rate than needed for Ireland.

When the euro was introduced in 1999, the question most economists around the

globe posed was: how would a single macroeconomic policy framework satisfy

the requirements of such a diverse group of economies with no federal budget

system as in the case of the USA? Fiscal policies are still at the discretion of

national governments, but even so there are rigid conditions under which these

policies should be used. Individual governments within the EMU could no longer

influence exchange rates, and more importantly, control over their individual

monetary policies was lost. When Ireland joined the EMU in 1999 it completely

lost sovereignty over its monetary policy and in the process lowering its nominal

interest rate from 6 to 3 percent. It effectively lost control over the boom it was

already experiencing and since then inflation in consumer prices has risen well

above the EU average. One of the benefits Ireland was getting rid of exchange

rates fluctuations with other EMU countries, but the consequences have been

worsened competitiveness for its export industry, and an eventual cost crisis –

chiefly in the housing sector. While monetary policy is no longer available as an

instrument of domestic policy, fiscal policy is the only tool that could be used to

stimulate the economy, but yet under stringent conditions.

The lessons of the first years of membership is that the focus of fiscal policy

within Ireland needs to change, and that the EU institutions also need to focus

more clearly on the needs of the Euro area rather than on those of individual

regional economies. The simplest way to estimate a counter-option to the ECB

rate is by applying the Taylor rule.

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1.2 Objective of the study

We will seek to estimate a monetary policy for Ireland in the framework of the

Taylor rule during 1990-2009, which specifies that the real policy rate reacts to

two crucial variables: deviations of inflation from its targeted level and deviations

of real GDP from its long-run potential. The rule sets the nominal policy rate

equal to the rate of inflation plus an equilibrium real interest rate and the weighted

average of these deviations. It suggests that, if inflation is equal to the inflation

target level, and that the unemployment rate is equal to the equilibrium rate of

unemployment, then the central bank should set the nominal interest rate equal to

its target level.

Our main question is: At what level would the nominal interest rate stand if

Ireland weren’t in the EMU? The reason behind this research is primarily the

concern of a sovereign nation’s own good. The main benefits of joining the union

are located within a broad spectrum of economical endowments. If these

endowments are granted by surrendering pieces of a nation’s independence, at

least in an economical sense, then primarily, the arguments, benefits, and

endowments for joining must be of such gargantuan stature to offset the losses.

Considering that these principals have been surrendered then surely the grants

must be given. The empirical evidence suggests otherwise and the position of the

Irish economy might be juxtaposed to that of the rest of the Union.

We will apply the Ordinary least Square (OLS) regression method on a time series

data collected from databases of the Central Statistical Office (CSO) in Ireland

and Eurostat, in order to estimate the reaction coefficients for a Taylor type rule

for Ireland for the period 1990-2000. To estimate these coefficients we conduct

two separate regressions; the first on a quarterly time series data from the first

quarter of 1990 to the last quarter of 1995, and the second on a quarterly time

series data from the first quarter of 1997 and the last quarter of 2000. We will then

extract the coefficients from these two separate regressions together with averages

of the real interest rate, inflation rate and GDP gap between the periods of 1990-

2009 and from which calculate an estimate of a nominal interest rate for Ireland.

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This paper is structure as follows. In section 2, we will present the theoretical

background on the theory of optimal currency area and the Taylor rule. Section 3

will summarize earlier studies done on Ireland’s monetary policy treated under the

framework of the Taylor rule. Section 4 is the empirical section. In section 5, we

will present our results, and analysis. Finally, in section 6 some concluding

remarks.

2. Theoretical background

2.1 Theory of Optimal Currency Area

The debates in economics over the desirability of a currency union in Europe

began with Robert Mundell's 1961 introduction of the concept of an optimal

currency area, with the core properties of trade integration, factor mobility, fiscal

federalism, cyclical convergence, and wage- and price flexibility. Proponents of

the EMU argue that the project has been successful in terms of reduced trade

barriers within Europe. Mundell (1961) argued that a monetary union should be

no larger than the area over which similar business cycles typically prevailed or

over which labour is easily mobile. A currency union larger than that will allow

localized recessions and high levels of unemployment, about which monetary

policy can do nothing. Taking into account the contrast that existed between the

expansionary boom in the Netherlands and Ireland during the early years of their

memberships, most studies suggest that the business-cycle conditions differ

amongst EMU member states from the unset, and that the no bailout clause in the

Maastricht treaty could have even made the present situations of localized

recessions worse for most of these countries. The differences in labour unions,

languages and cultures also remain a major barrier to labour mobility.

The United States, appears to meets Mundell’s criterion for an optimal currency

area as compared to Europe. One of several reasons prompting quick adjustments

to asymmetrical shocks within the United States is the adoption of a cross-regional

fiscal transfer policy. Charles Goodhart (1995), argues that in the absence of

flexible markets – particularly labour markets – the effects of asymmetrical

shocks on inter-state inequalities of income can be mitigated only by

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re-distributional federal taxation system, and that their effects on cyclical changes

in incomes and employment can be lessened by the stabilising properties of fiscal

measures.1 During the late 80’s, the United States as a whole was in a period of

considerable prosperity and appeared to need a restrictive monetary policy. The

Dallas Federal Reserve District, however, was in a recession, caused by a sharp

decline in the prices of oil and natural gas, and would have benefited from

relatively easy money. The policy of the Federal Reserve Board was determined

by the apparent needs of eleven districts rather than one, meaning that Texas and

neighbouring states had to survive a monetary policy that was inappropriate for

their needs. Within the United States, the federal government absorbs about 35

percent of the costs of a localized recession through reduced tax receipts and

increased transfer payments. There are no such fiscal arrangements in Europe,

which means that a localized recession in Ireland will not be partially absorbed by

the other members of the European Union through reduced tax payments and

increased transfer payments. The cost of the present recession in Ireland is hence

carried entirely by the Irish government without any help from Brussels, making

its localized recession considerably more painful.

Nils Gottfries (2003) found that to have the same interest rate within the EMU and

the same exchange rate against other countries out of the EMU could be

problematic if developments in a member country differ greatly from others

within the union as a whole and that the problem of asymmetrical shocks would

be inevitable, just as in the case of Ireland and Germany during their first year of

membership in the EMU. He also agued that the ECB succeeded in establishing a

common nominal interest rate but failed to establish a common and stable

inflation within the union. With this background, having a common nominal

interest rate within the euro zone, would further strengthen asymmetrical shocks

within the union.

1 http://www.prospect-magazine.co.uk/article_details.php?id=5195

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2.2 The Taylor Rule

The interest rate targeting scheme that has become widely known as the Taylor

rule was first presented by John Taylor (1993) for illustrative purposes. By linking

interest rate decisions directly to inflation and economic activities, Taylor offered

a convenient tool for studying monetary policy while abstracting from a detailed

analysis of the demand and supply of money. The Taylor rule has become a

widely used tool in macroeconomic policy analysis, partly due to its simplicity

and partly because it captures some key macroeconomic variables.

He argued that since central banks affect spending through the interest rate, a

central bank should then think directly in terms of the choice of an interest rate

rather than in terms of the rate of money growth as proposed by Milton

Friedman.2 While the optimal nature of this rule has attracted increased attention

in series of economic journals and empirical studies, no country in the west seems

to have taken any definite step in implementing the Taylor rule formally.

Nonetheless the rule has proven to predict the behaviour of monetary policy quite

well especially in the United States, and Germany over the past 15 years. Since

Taylor’s initial formulation of the rule in 1993, economists around the world have

modified it in different ways, to analyze reaction functions for numerous central

banks in the OECD countries.

The Taylor rule stipulates the level of policy rates to be a function of the output

gap, divergences of actual rates of inflation from a target, and the equilibrium

level of interest rates. In other words the Taylor rule uses inflation and gross

domestic product to predict changes in the nominal interest rate. It is typically

expressed as:

(1)

2The Milton Friedman’s k-percent rule (Friedman, 1960), draws on the equation of exchange

expressed in growth rate: , where is the rate of inflation and

and are respectively, price level, money stock, money velocity and real output. It

proposes that central banks should select a constant growth of money, k, to correspond to the sum

of a desired inflation target, , and the economy’s potential growth rate, , and adjusting for

any secular trend in the velocity of money, .

tttt yri 2

*

1

* )(

qvm pvmp ,, q

* *q*v

10

Where is the nominal interest rate at time t, is the equilibrium real interest

rate, is the average inflation for the previous four quarters (including the

current one) at time t, and is usually measured by core CPI, is the

deviation of the inflation rate from its target level , and is

the deviation of output from its full-employment level, . The four

parameters, , , and for the United States were taken by Taylor as,

respectively, 2 percent, 2 percent, 0.5 and 0.5, under the assumption that the

central bank has the information on current output and inflation. and

indicate the sensitivity of the nominal interest rate changes to each of the two gaps

– inflation and output respectively.

Taylor predicts that central banks will increase interest rates when inflation rises

above the target level or output moves above its full-employment level, and vice

versa. The nominal interest rate component, , defines the level at which the

nominal interest rate would settle were inflation stable at its target rate and output

maintaining its full-employment level. The inflation gap component, ,

indicates that when inflation rises above its target level, the central bank raises the

nominal interest rate by a multiple of the difference – an action that slows money

growth, which in turn reduces future inflation. The output gap component,

, indicates that when output falls short of its full-employment

potential, the central bank lowers the nominal interest rate – an action that

stimulates economic growth, raising output towards its potential.

Taylor found that his rule neatly described the US Federal Reserve's decision-

making process, and it is now widely used by forecasters to estimate the desired

level for policy rates. The most attractive quality of the Taylor rule is that it is a

simple equation that seeks to explain a key macroeconomic relationship. More

recently Rudebusch and Svensson (1998) reinforced that the Taylor rule stabilizes

both inflation and output reasonably well in varieties of macroeconomic models.

Orphanides (2007) argues that the Taylor rule offers a simple and transparent

framework with which to organize the discussion of systematic monetary policy,

ti*r

t

)( * t

* tttt YYYy /)( *

tY *

tY

*r * 1 2

1 2

tr *

)( *

1 t

)( *

2 tt YY

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but on the other hand is not likely to be useful using real-time data. On a

conference held on John Taylor’s contribution to monetary theory and policy on

October 12, 2007, Donald Kohn, the vice chairman at that time of the federal

reserve bank of Dallas, also commented on the simplicity of the Taylor rule as it is

helpful in the central bank’s communication with the general public and that it

helps financial market participants from a baseline for expectations regarding

future courses of monetary policy. He however also mentioned that the Taylor

rule has some limitations, including that fact that it only captures small number of

variable, that are not enough to describe fully the state of a complex economy like

that of the United States. But despite its flaws as a practical tool, it is a quite

useful tool in evaluating historical monetary policy regimes. Judd and Rudebusch

(1998) and numerous others have estimated values of key parameters using data

for previous Federal Reserve governorships, using the Taylor rule.

The original Taylor rule (1993) in itself is backward-looking, but has over the

years undergone various modifications as researchers try to make it more

appropriate to suit the different types of economies. Due to rational expectations

in macroeconomic models, one major modification to the original Taylor rule has

been to incorporate forward-looking behaviours of central banks reaction

functions. The forward-looking models are often used by forecasters, in making

the short-term interest rate a function of central bank expectations of output gap

and inflation rather than their contemporaneous values. As monetary conditions

are also influenced by exchange rate movements, another major modification to

the original Taylor rule has been the incorporation of some form of exchange rate

variable into the Taylor-type equations. But several studies however, suggest that

the inclusion of an exchange rate variable in a Taylor-type equation is not helpful

for inflation and output stabilisation, because exchange rate misalignments could

be very protracted, and would not seem as a desirable feature to rely on a general

rule that would significantly bias monetary policy.

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3. Earlier studies

Over the past two decades, the Taylor rule, have attracted increased attention of

economic analysts, policymakers, and the media all over the globe. The rule has

become more appealing in recent times with the apparent breakdown in the

relation between money growth and inflation as proposed in Friedman’s k-percent

rule. The historical analysis and the reaction function are often employed to

conduct empirical analyses in the Taylor rule framework.

In recent years there have also been studies conducted on developments of trends

and cycles in real GDP and inflation in the European Monetary Union (EMU)

member countries under the framework of the Taylor rule. For example, Crowley

and Lee (2008) conducted an empirical studies based on the Taylor rule and in

combination with counterfactual statistical techniques, on the extent to which the

European Central Bank (ECB) respond to evolving economic conditions in its

member states as opposed to the euro area as a whole. Their results indicated that

the ECB’s monetary policy rates have been particularly close to the interest rates

of Germany, and countries with similar economic conditions to that of Germany –

this includes Austria, Belgium, the Netherlands and France. However, their

coefficient estimates for the future inflation variable varied widely across the

member countries. The estimate for the euro area as a whole differed remarkably

from those of individual countries, with the estimates for Finland, Greece, Ireland,

Italy and Spain to be relatively higher, suggesting aggressive responses to

expected inflation from these countries. They suggested in their study that since

the economies of the euro area have been quite unsynchronized, ECB policy

actions, might have been adequate for the euro area as a whole, but too loose

especially for faster growing countries such as Greece and Ireland and too tight

for slower growing countries, such as France.

However, there have only been few studies done solely on Ireland’s individual

membership in the EMU under the framework of the Taylor rule. For example,

Honohan (2006) looked at whether both the exchange rate and interest rate have

had the effect of increasing the scale and frequency of exogenous shocks hitting

the Irish economy. In particular how key variables in the remainder of the

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economy – which are the share of construction in total employment, house prices,

inward migration and labour competitiveness – have responded to the largest of

these shocks. He found that the implementation of the euro has triggered sizeable

exogenous shocks to the Irish economy – in particular interest rate shocks. He also

confirms that the interest rate movements have deviated widely from what a

standard Taylor monetary policy rule would have counselled. The most important

shock, according to him, has been associated with the large and sustained initial

fall in nominal interest rates in the start of the EMU, which have had lasting

effects on property prices, construction activity and the capacity of the labour

market to absorb sizeable net immigration, despite a sharp deterioration in wage

competitiveness since 2002. According to Honohan, the Taylor rule stipulates an

interest rate almost 5% higher than that set by the ECB during the years 2000-

2005. Given that the rate was set at 1% throughout 2005 the ECB would have to

raise it to 6% to accommodate the Irish economy and send nothing less but a

shock to the rest of the Euro area economies.

4. Empirical Section

4.1 The Regression Model

For our purpose, we would rewrite equation (1) above into a suitable regression

model as follows:

(2)

where: , ,and . The equation:

provides estimates of the weights on inflation and output in the

Taylor rule and on the speed of adjustment to the rule. The nominal interest rate,

, is the dependent variable, while the inflation, , and the output gap, , are the

tttt yi 210

*)*( 10 r )1( 11 22

*)*( 10 r

ti

t ty

14

independent variables. This specification of the Taylor rule does not contain the

interest rate smoothing term.3

The four parameter value for, , , and were taken by Taylor in his 1993

presentation as, respectively, 2 percent, 2 percent, 0.5 and 0.5, under the

assumption that the central bank has the information on current output and

inflation, and strictly following the rule. The parameter values were taken as

and , but if this is not the case, then following

conditions must hold: and , otherwise the system would be

unstable. Taylor (1999) referred to the second condition as the “Taylor Principle”.

Also, if the intercept in Equation 2 is negative then either real interest rate is

negative or target level of inflation is high. We have used the 2 percent parameter

for and the averages over for every sample in our model. We estimate the

real interest rate by subtracting the available inflation rate values from the

available nominal interest rate values. Our estimate of the average interest rate for

Ireland is 6,7 percent between the period of 1990 and 2000.

4.2 Regression Technique and problems

Our objective is to estimate a Taylor rule for Ireland and not the actual policy

reaction function, hence our task will be to estimate the coefficients and

in equation 2 by running a simple Ordinary Least Square (OLS) regression on it

for the period prior to the EMU era. Once we have the values for these three

coefficients from running a regression on the contemporaneous data between 1990

and 2000, we will then use average values for inflation, , and the trend GDP,

for the period between 2000 and 2009 to manually calculate an estimate of a

nominal interest rate for Ireland.

3 Central banks often adjust interest rates by slowly bringing the rates towards a desired target

level. To allow for interest rate smoothing, some researchers incorporate an interest rate smoothing

term (see for instance, Judd and Rudebusch (1998)).

*r * 1 2

5,1,1 10 5,02

11 02

* *r

10, 2

t ty

15

However, in running an Ordinary Least Square (OLS) regression, we are aware of

certain problems that could arise and make our regression results biased and

inconsistent:

The problem of non-stationary series (or unit root): For an OLS estimation on

a time series data to be valid, the error term must be time-invariant, that is,

stationary. In a situation where we have unit roots, the values from previous

periods in the time series data are carried forward to current periods. As such the

values of the random error will never fade away, and the continuous build-up of

the errors will create problems that the non-stationary series will tend to towards

an infinite variance. Furthermore, if the dependent variable and the explanatory

variables in a regression are both non-stationary, the model will have spuriously

insignificant result and high even if the two variables are unrelated. To

address this problem we will take first differences in the time series data in order

to eliminate both the autoregressive component and the unit root, which will in

turn lower the dramatically.

Simultaneity problem: This is a case in which we have some of the regressors

that are endogenous (or when not all the explanatory variables are exogenous) and

are therefore likely to be correlated with the error term. To identify this problem,

we will run a Hausman specification error test to check whether an endogenous

regressor is correlated with the error term.4 If we identify such a problem, we will

correct it by resorting to a two-stage least square (2SLS) approach; whereby we

regress each endogenous variable on all the exogenous variables of the system,

and then use the predicted values of the endogenous variables to estimate the

structural equations of the model.

Autocorrelation problem: one common problem in time series analysis is a

problem of positive first-order autocorrelation, which arise when the error term in

one time period is positively correlated with the error term in the previous time

period. This leads to downward-biased standard errors and thus to incorrect

statistical test and confidence intervals. We will test for this problem by

4 The null hypothesis of no bias in the OLS estimate can be rejected with a probability of 0.003 in

conducting a Hausman test.

2R

2R

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conducting the Durbin-Watson test at a 5 or 1% level of significance. We will

correct this problem, by regressing the dependent variable on its value lagged one

period, the explanatory variables of the model and the explanatory variables

lagged one period.

4.3 Statistical sources and limitations

The main part of the raw data sample was obtained from the Central Statistical

Office (CSO) of Ireland and Eurostat. Data spanning pre-EMU period was

obtained directly from CSO Ireland with a total of 24 observations, whilst data

spanning the transition and post-EMU period was obtained through Eurostat with

a total of 52 observations (see tables 1 and 2 respectively). We have divided the

regression analysis into two parts: (1) preceding EMU period and (2) the transition

to EMU period. The data sample consists of only a small number of observations

consisting of monthly observations on GDP, inflation and nominal interest rate

covering the period 1990-1995 from the Irish Central Statistical office (CSO), and

quarterly observations on the same variables covering the period 1997-2009 from

the Eurostat database. The GDP is measured in millions of euros, while the

inflation- and nominal interest rates are measured in percentage points. Data on

GDP between the first quarter of 1996 and the last quarter of the same year is

unavailable from both institutions.

The Taylor rule requires quarterly series, which make it rather difficult to estimate

the dynamic version of the model. For this reason, and due to the unavailability of

quarterly data between the periods of 1990-1995, we resorted to interpolation in

order to derive quarterly data from the available monthly data.5 Beside the three

mentioned variables, the Taylor rule also requires expected inflation, potential

GDP, and real interest rate, which are unavailable from our respective data

sources. The lack of data on expected inflation is due to the fact that the Irish

Central Statistical Office (CSO) never did forecasts during the pre EMU era.6 We

5 We averaged in excel all the variables that are in monthly series over three months of each

quarter, by creating in the data sheet with appropriate in the last month of each quarter.

6 We assume that an appropriate inflation target for Ireland is 2% as the SCB and the Swedish

inflation target levels.

17

applied the Hodrick-Prescott filter (HP-filter) to the GDP data in order to extract a

trend GDP from the actual GDP. The filter, decomposes the time series data into

growth and cyclical components, and interprets the growth component to be the

potential GDP, which is measured as the percentage deviation from the fitted

trend. Figure 1 in the appendix shows the actual series and the fitted trends for

output.

The reason we chose the filter approach over the Okun’s law –and production

function approaches is mainly due to three of several reasons. (i) It is a convenient

method that works well on historical time-series data. (ii) It only interprets one

economic indicator. (iii) It follows the data closely which renders the bias of

analytical judgement void. This being an empirical study gives a strong base for

its use, but we are however aware of some significant shortcomings in using the

HP-filter. (i) It does not account for trends in the other economic factors occurring

outside of the GDP, such as structural changes in the factor of production. (ii) It

has some troubles with estimating precise values due to kinks/disturbances in the

economic cycle. (iii) The filter proposes a trend rather than potential GDP because

it does not yield an estimate level of output that is consistent with stable inflation.

We have deemed the time span as well as the relatively stable history of Ireland’s

economy to be adequate for the implementation of the filter. However, to avoid

non-stationary trends in the time series data, we have resorted in taking the first

differences on all the variables in order to eliminate the problems that could arise

from the presence of a unit root. Figure 2 in contrast to Figure 1 (see appendix),

shows the improvement made in the data after taking the first difference.

The inflation was calculated from the two CPI-indexes which were available at

both Eurostat and CSO Ireland. The first data period is from 1990-2000 with the

CPI base from 1989 and the second is from 2000 to 2009 with a CPI base from

1996. The inflation was calculated by subtracting the CPI from the current year by

the preceding year. Then the sum was divided by the CPI given from the

preceding year and the result was multiplied by a 100. This gives a percentile

indicator of the inflation change for each quarter. Figure 3 (see appendix) shows

the trend in inflation between 1990 and 2009. The summary of the data sets can be

viewed in the tables below. They are divided into two, in order to give a clearer

18

and simplified insight into the variables present. The scope and time span of the

study becomes well defined as you can view the differences of the two periods

accordingly.

Table 1: Descriptive statistics for data between 1990-1995

Table 2: Descriptive statistics for data between 1997-2009

4.4 Choice of time period

The time period chosen for the study is 1990-2009. This is based on the fact that

we can observe an adequate amount of data before and after Ireland’s entry to the

EMU system. The main argument for conducting the study through such a time

period is to give reasonable estimate of the weights on inflation and output gap.

Furthermore it gives weight to the whole analysis as a broad time spectrum is used

Variable Obs Mean Std. Dev. Min Max

Inflation 24 0.0061417 0.0035812 -0.0018 0.0134

Real GDP 24 17904.35 1425.236 16433.25 20542.75

Trend GDP 24 17904.33 1336.906 15940.24 20285.62

GDP Gap 24 -0.0000257 0.0225438 -0.0410691 0.0490878

Real

Interest rate 24 0.0865125 0.023485 0.0545 0.1357

Variable Obs Mean Std. Dev. Min Max

Inflation 52 0.0076923 0.0128637 -0.0118 0.08

Real GDP 52 33004.92

6432.052 20593 42602

Trend GDP 52 33004.92 6308.019 20968.97 40574.63

GDP Gap 52 -0.0002787 0.0271283 -0.0638732 0.0643157

Real

Interest rate 52 0.0347154 0.0188033 -0.05 0.0655

19

which can therefore help remove possible discrepancies from the data. Another

aspect is that studies tampering the matter of the Taylor rule and Ireland did not

include this specified time period.

5. Regression result and analysis

To estimate what nominal interest rate Ireland would have set if it weren’t in the

EMU, we adopted the Taylor rule methodology. We have estimated the Taylor

rule coefficients by conducting an OLS regression on quarterly data for the period

1990-1995 and 1997-2000 respectively. We then used the coefficients from these

regressions as weights on the averages of inflation and GDP gap for the periods of

1990-2009. Table 3 and 4 report the estimates from the regressions done on the

data for 1990-1995 and 1997-2000 respectively. Table 5 shows the estimated

nominal interest rate for Ireland for the whole sample, with averages over the

variables used in the manual calculation of the interest rate.

Table 3: Regression result 1990-1995

Variable Coefficient Standard Error t

Inflation -0.0800713 0.3687862 -0.22

Gap 0.0405271 0.0427637 0.95

intercept -0.0022439 0.0021873 -1.03

F-statistic: 0.46, Number of observations:24

Table 4: Regression result 1997-2000

Variable Coefficient Standard Error t

Inflation -0.1207992 0.2029273 -0.60

Gap 0.0607676 0.0695343 0.87

intercept -0.0004262 0.0017514 -0.24

F-statistic: 0.38, Number of observations:16

20

Table 5: Estimation table

Variables 1990-1995 1997-2000 2001-2009 2009

Real interest rate 0.0865 0.0465 0.0294 0.0269

Inflation 0.0061 0.0078 0.0078 -0.0062

GDP Gap -0.0000257 -0.000996 0.0000402 -0.0460043

Estimated nominal

interest rate 10.7 6.7(6.7) 5.0(5.1) 4.7(4.7)

Note: The variables (real interest- and inflation rates in percentage points) are calculated as the

averages over the four-quarters from the first quarter to the last quarter of every sample (i.e.1990-

1995, 1997-2000 and 2001-2009). In parenthesis are the nominal interest rates calculated using the

coefficients extracted from the second regression. The end-of-sample inflation is average inflation

over the final four quarters of 2009. The estimated nominal interest rate is circa 7.5%, calculated

from the averages of 10.7, 6.7 and 5.0.

We did simulations using our estimated Taylor rule coefficients from the first

regression and paired it with simulations with induced Taylor rule coefficients to

see how the interest rate trends would have looked like had Ireland control over its

monetary policy and if they strictly followed the Taylor rule. We have these

simulations in figures 3 (see appendix). Not surprisingly we can see from figure 3

that Ireland should have had an interest rate some where between 8-10 percent for

at least some time if it hadn’t joined the EMU in 1999. Our calculation is

somewhat consistent with what figure 4 in the appendix predicts. We could then

conclude that with the booming economic activities in Ireland before and after its

entry into the EMU, the country should have been operating under interest rates

far over the ECB’s average. Plotting an induced Taylor rule in figure 4, was more

of a guide to see if we had used the rule properly.

The results from both regressions show low statistical significance levels for the

Taylor rule coefficients. In any case, our task is to use the Taylor rule framework

to estimate the weights on inflation and GDP gap rather than testing whether the

Taylor rule holds for Ireland. Besides the estimated weights on inflation and GDP

gap are to some extent reliable, because the results from the Durbin-Watson

coefficient tests conducted to check for first-order autocorrelation indicates

21

acceptable levels of autocorrelation.7 Table 6 (see appendix) shows the result from

the Durbin-Watson test. We have not used the ARMA model, which might have

entirely eliminated the problem. However, most studies suggest that the problem

of autocorrelation often imply model misspecification, which may arise from

missing variables. In our case we think this problem arose most likely from the

use of the HP-filter, which does not capture other trends in the other economic

factors occurring outside of the GDP. Another explanation for the autocorrelation

might be due to the Irish central bank’s practice of interest rate smoothing.

We also conducted a Hausman test which showed no sign of simultaneity. The

residual series from these estimated coefficients in equation 2 are stationary as the

null of the unit root in the Dickey-Fuller test is easily rejected at conventional

levels of significance. The results from the Dickey-Fuller tests are shown in tables

7 and 8 (see appendix) for the respective periods.

6. Conclusion

We began the study with a goal of estimating a counter-option nominal interest

rate to that of the ECB average. Our results indicate that an appropriate nominal

interest rate for Ireland should be roughly 7.5 percent, rather than the circa 3

percent fixed by the European Central Bank upon its entry into the EMU. This is

consistent with Honohan’s prediction of an approximate 6 percent. We conclude

therefore that the interest rate in the EMU is not set in response to the economic

realities in Ireland.

In light of the estimated data it is relevant to remember the criteria for the

introduction of the Euro, that is to say, the creation of an Optimum Currency

Area. The criteria concentrate mainly on the aspects of intra-European trade,

mobility of the European labour force, similarity of economic structure and fiscal

federalism. Albeit in a state of probing, the EMU was implemented as a means to

7 The value of d in the Durbin-Watson coefficient test for first-order autocorrelation ranges from 0

to 4. A value of 2 indicates no autocorrelation; 0 indicates positive autocorrelation; and 4 indicates

negative autocorrelation.

22

fulfil the political goals of the EU through economic co-integration. As previously

stated the union would, amongst others, lead to benefits of increased trade,

monetary efficiency gain and countries with a history of volatile inflation would

experience a stabilizing effect through the common currency8. The counter

argument for the introduction of the common currency is best described by the

term economic stability loss. Namely, the ability of a country to counter-act

cyclical changes as well as asymmetric shocks in the economy is given to a

supranational entity, the ECB. The main tool for conducting such policy was

through a nation’s central bank and the broad spectrum associated with monetary

policy. The lack of an independent interest rate is in theory supposed to be offset

by a pro-active fiscal policy. This argument is not approved by post-Keynesian

economists who argue that the Maastricht Treaty does not allow for a possibly

needed fiscal deficit. Furthermore, the union may become characterized by

specialization as explained by the Heckscher-Ohlin model which may worsen

asymmetrical shocks when they occur. This may be the case with Ireland. An

example would be that the country experienced another inflation rate trend than

that of Netherland although both countries’s had to pass the admission criteria for

the EMU.

From our findings the loss of autonomy over Ireland’s monetary policy has

complicated its economic management. In theory the fiscal policy should sustain

the economy in the absence of a monetary policy. In light of the optimum

currency area the Irish case has shown that due to circumstances as demographics,

booming housing and the export industry, asymmetric shocks are inevitable as the

countries within the EMU are unsynchronized. Therefore it should be stated that

the EMU should introduce a type of federal budget system similar to that of the

United States in order to minimize the asymmetrical shocks.

8 Optimal Currency Areas* (2002); Alberto Alesina, Robert J. Barro, Silvana Tenreyro; page 7.

23

References

Blanchard, Oliver, (2006), Macroeconomics, 4th

Edition, Pearson Publication

Carare, Alina and Robert Tchaidze, (2005), ” The Use and Abuse of Taylor Rules:

How Precisely Can We Estimate Them?”, IMF Working Paper, WP/05/148

Chamie, Nick, Alan DeSerres and René Lalonde,(1994), “Optimum Currency

Areas and Shock Asymmetry: a comparison of Europe and the United States”,

Bank of Canada, Working paper 94-1.

Crowley, Patrick M. and Jim Lee, (2008), “ Do All Fit One Size? An Evaluation

of the ECB Policy Response to the Changing Economic Conditions in Euro Area

Member States” Texas A&M University-Corpus Christi

Gotfries, Nils, (2003), “Ränta och Växelkurs I och Utanför EMU” Ekonomisk

Debatt 2003:4

Judd, John P. and Glenn D. Rudebusch, (1998), “ Taylor’s Rule and the Fed:

1970-1997”, FRBSF Economic Review 1998:3.pp. 3-16

Honohan, Patrick and Anthony J. Leddin, (2006), “Ireland in the EMU: More

Shocks, Less Insulation?” Economic and Social Review, Vol.37, No. 2,

Summer/Autumn, pp. 263-294.

Honohan, Patrick and Philip R. Lane , (2004), “Exchange Rates and Inflation

under EMU: An update”, Centre for Economic Policy Research Discussion, Paper

4583, August.

Kenneth Kuttner, (1994), “Estimating Potential Output as a Latent Variable”,

Journal of Business and Economic Statistics, vol. 12, no. 3 (July).

24

Mundell, R. ,(1961), “ A Theory of Optimum Currency Area”, American

economic Review 51:657-665.

Orphanides, Athanasios, (2007), “Taylor Rules” Board of Governors of the

Federal Reserve System (January)

Taylor, John B., 1993, “Discretion Versus Policy Rules in Practice,” Carnegie-

Rochester Conference series on Public Policy, Vol 39 (December), pp. 195-214.

Electronic Sourses

http://www.prospect-magazine.co.uk/article_details.php?id=5195

http://ec.europe.eu/economy_finance/publications/countryfocus_en.htm

25

Inflation

-2,00%

0,00%

2,00%

4,00%

6,00%

8,00%

10,00%

Year

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Inflation

Appendix

Descriptive statistics

Figure 1: GDP and trend GDP between 1990- 2009

Figure 2: GDP and trend GDP between 1990- 2009, after taking the first difference

Figure 3: Inflation trend between 1990-2009

Sources: Eurostat and CSO Ireland. Note: the downward kink in figure 1 indicates the

unavailability of data for 1996.

0

10000

20000

30000

40000

50000Ye

ar

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GDP and GDP Trend

GDP

Trend GDP

-8,00%

-6,00%

-4,00%

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2,00%

4,00%

6,00%

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GDP gap differentiated

GDP gap

GDP gap differentiated

26

Regression diagnoses

Table 6: The Durbin-Watson test result

Test 1990-1995 1997-2000

Durbin-Watson statistic 1.436003 1.270489

Table 7: Dickey-Fuller test results for period 1990-1995

Variable Test Statistic Z(t) 5% Critical Value P-value for Z(t)

Gap differentiated -5.593 -3.000 0.0000

Inflation

differentiated -8.683 -3.000 0.0000

Interest rate

differentiated -3.271 -3.000 0.0162

Table 8: Dickey-Fuller test results for period 1997-2000

Variable Test Statistic Z(t) 5% Critical Value P-value for Z(t)

Gap differentiated -9.002 -3.000 0.0000

Inflation

differentiated -5.835 -3.000 0.0000

Interest rate

differentiated -2.754 -3.000 0.0652

Note: the Z(t) for the differentiated interest rate passed a 10% critical value which was -2.630.

Simulation

Figure 4: Estimated Taylor Rule diagram

-2,00%

0,00%

2,00%

4,00%

6,00%

8,00%

10,00%

12,00%

1990 1991 1992 1993 1994 1995

Taylor Rule 1990-1995

Actual

Induced Taylor rule

27

The empirical model.

The Taylor rule as presented by Taylor (1993) can be expressed as follows:

tttt yri 2

*

1

* )(

(1)

Where, ti represent the nominal interest rate taken as monetary policy instrument

at time t, t the average inflation for the previous four quarters (including the

current one) at time t, and ** /)( tttt YYYy represents the GDP gap or trend

GDP (the parameters *r = * =2% and 1 = 2 =0.5%, were given by Taylor) It is

should be fairly straightforward to directly conduct a regression on equation (1) as

written in the following model:

tttt yi 3

*

210 )( (2)

Where we have, 121

*

0 ,1, r , and 23 . Since we have two constant

terms *r and * , it would be impossible to estimate them independently and

simultaneously. Also, the t and the )( * t variables are nearly identical,

since * is a constant. As a result we will have a total of two explanatory

variables that are perfectly linearly correlated. Thus proceeding with the model in

equation (2), will make it impossible for us to isolate the effects of these two

individual explanatory variables ( i.e *r and t ) on the dependent variable ( ti ),

because the system of normal equations will contain at least two equations that are

not independent, as such yielding OLS coefficients that may be statistically

insignificant. To make equation (1) suitable for regression and to avoid the

problem of perfect multicollinearity, we transformed the functional relationship

and to drop one of the highly collinear variables, that is, the )( * t term.

Rearranging equation (1):

ttt

T

t yri 2

*

11

*

28

tt

T

t yri 2

*

11

* )1( (1)

Now we can form the regression specification model:

tttt yi 210 (3)

Where:

*)*( 10 r (4)

)1( 11 (5)

22 (6)

If the central bank is strictly following the Taylor rule, then the parameter values

will become 5,1,1 10 and 5,02 in equations 4, 5 and 6 respectively.

But if this is not the case, then following conditions must hold: 11 and 02 ,

otherwise the system would be unstable. Taylor (1999) referred to the second

condition as the “Taylor Principle”. If the intercept in Equation (3) is negative

then either real interest rate is negative or target level of inflation is high.

The manual calculation of the Taylor rule

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9590

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0097

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