Interest rate behaviour in europe

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Interest Rate Behaviour in Europe

1. Introduction

1.1 Background

Interest rates are considered center-pieces of macroeconomics because of the impact that they have on the societal, economic and political facets of a state. The recent recession in many developed states in the America and Europe saw an unprecedented degree of coordination and speed in the mode in which cardinal bank engaged in involvement rate cuts. Such actions are founded on the economic justification that the decrease of involvement rates stimulates the economic system through pecuniary enlargement. The inter-woven nature of different states in the globalised epoch comes to the surface during disruptive economic times such as these. This research attempts to analyze the relationships that exist among the different European states ‘ pecuniary policies by analyzing the co-movements among their involvement rates. An effort is besides made to analyze the relationship between the involvement rates in the UK and the US, the two long-time economic spouses. This research uses quantitative methods and patterning techniques to analyze the causal consequence of certain critical factors on the involvement rates of different pecuniary policy governments in Europe.

1.2 Rationale

The recent co-ordinated Acts of the Apostless by the cardinal Bankss of the universe thrust place the importance of taking the mutuality of states into history. Ever since Euro Area was created and all the 16 states adopted a common pecuniary policy and a individual Central bank, the significance of Euro Area has increased in planetary economic sciences. In regional economic sciences, its importance is 2nd to none. It is to be expected that such a big pecuniary country would hold significance influence upon the involvement rate alterations in other provinces in the part. This perceived importance of Euro Area and the importance of analyzing the inter-dependence of different states ‘ pecuniary policies form the implicit in principle for this survey. Euro Area was chiefly created to guarantee that the synergism of the members would take to better economic strength. It would be appropriate to measure this factor through measuring of the impact of Euro Area ‘s pecuniary policy on other provinces ‘ .

1.3 Purposes and Aims

The purpose of this research is to determine the extent of inter-relationships among the pecuniary policies of different pecuniary governments in Europe. The primary aim of this research is to analyze the relationships among the involvement rates in Euro Area and other member provinces of the European Union. Besides, this research besides strives to set up the causal impact of alterations in Euro Area ‘s involvement rates upon the involvement rates in other European Union provinces. The overall intent underlying this research is that it would supply some penetrations into comparative behavior of involvement rates in Europe.

1.4. Methodology

This research is based on empirical research methodological analysis where existent historic informations are used to construct theoretical accounts and validate hypotheses. Quantitative research methods are used to research the relationships among the critical variables whose features are purported to be studied by this research. Two chief quantitative methods used are – Correlation and Regression.

Correlation is a step of the extent of co-movement between two informations series. Correlation measures both the way and the magnitude of alterations in two variables ( Levin and Rubin, 1997 ) . The most popular step of correlativity is based on the covariance between the information series. The expression is presented below:

R = Sxy / [ Sx2 X Sy2 ] 0.5

Where,

ten and y represent the two informations series and

R is the correlativity coefficient.

In this research correlativity analysis is used to determine the relationship

  • between braces of different sorts of short term involvement rates in Euro Area
  • between involvement rates of braces of other European Union economic systems
  • between involvement rate of each one of the member of EU and the involvement rate of Euro Area
  • between LIBOR and US Fed rate

Correlation coefficient, as calculated above, takes a value between -1 and +1. A value of -1 denotes that the two variables move precisely in opposite waies while a value of +1 indicates that the motion of the two variables are absolutely matched. A value of zero denotes the presence of no important correlativity between the variables. Correlation shows merely the extent of co-movement and non causing.

The other quantitative technique used in this research is additive arrested development. Linear arrested development theoretical accounts the alterations in dependant variable as maps of alterations in one or more independent variables. Arrested development is used to mensurate the causal impact that changes in one or more variables have on the dependant variable ( Newbold et al. , 2003 ) . In this research arrested development is used to mensurate the causal impact of money supply and rising prices on the involvement rate of Euro Area. This can be expressed in an equation as follows:

Ii = ai + & A ; szlig ; 1. Mi + & A ; szlig ; 2. Ci

Where,

Ii is the rate of involvement during the period I

Mi is the measure of money supply during period I with coefficient & A ; szlig ; 1

Ci is the rate of rising prices during period I with coefficient & A ; szlig ; 2

The values of betas are tested for void hypotheses that & amp ; szlig ; 1=0 and & A ; szlig ; 2=0 utilizing a t-test. The arrested development map is besides evaluated utilizing a F-test. If the void hypotheses of t-tests get rejected it would be concluded that money supply and rising prices have important impact on the alterations in involvement rates during the period under consideration. If the nothing hypotheses are non rejected so the decision would be that money supply and rising prices do non find the alterations in involvement rates. It is expected that both money supply and rising prices would hold important impact. Besides, it is expected that money supply and rising prices would hold positive coefficient values.

1.5 Outline

The following chapter of this thesis reviews a cross-section of literature that have studied the behavior of involvement rates in Euro Area and greater Europe and makes observations on the footing of the decisions drawn in those researches. The 3rd chapter is concerned with the survey of correlativity between different sets of informations, which has been explained in the earlier subdivision of this chapter. The 4th chapter builds a simple theoretical account to calculate involvement rate of Euro Area from two variables – money supply and rising prices. Finally the decision chapter summarises the treatment in the thesis and spells out the decisions arrived at on the footing of the observations made utilizing assorted analysis methods.

2. Literature Reappraisal

The aim of this research is to analyze the behavior of involvement rates in Europe. A figure of research workers have conducted assorted different researches on the same subject and have made valuable parts to the academic cognition. A reappraisal of the decisions made by some of these research workers would assist to pre-empt the consequences of the empirical research that will be conducted as portion of this survey and would besides assist to compare the consequences of this research to those of the earlier research workers. This chapter of this thesis surveies a cross-section of academic researches that have studied the nature and inter-relationships between different involvement rates in Europe. The first portion of this subdivision focuses on the relationship between involvement rate and rising prices rates in different states of EMU ; the 2nd portion is focussed on fiscal and pecuniary integrating within the EMU and the 3rd subdivision reviews literature that have studied the linkages between EMU and the other states, peculiarly the US.

2.1. Interest Rate and Inflation rates in EMU

The most outstanding characteristic of Economic and Monetary Union ( EMU ) of European Union is that the financial policy of each state is determined by the national authoritiess that rule the peculiar province while the pecuniary policy is determined centrally for all the states in the EMU. The pecuniary policy purposes to accomplish a stable pecuniary status through appropriate control of the rising prices and involvement rates. However rising prices and general economic growing is affected by financial policies followed by each authorities. When a authorities engages in expansionary financial policy funded largely by borrowed capital, it could ensue in hapless quality of growing coupled with high rising prices. Thus the success of cardinal pecuniary policy is dependent upon the financial subject of the member provinces. Knowing this to the full good, the EMU created a ‘Stability and Growth Pact ‘ that requires that the shortage to GDP ratio should non transcend 3 % for any member province. Any province that violated the demands is handed out penalties in the signifier of countenances. The thought of making a stableness and growing treaty is to guarantee that the minimal degree of financial prudence may be ensured so that pecuniary policy can be focussed on stableness of the economic system every bit good as growing. A figure of research workers have enquired into the relationship between financial conditions of members of EU and the impact of financial surpluss on the rising prices rate. When rising prices rate alterations in the province, the existent involvement rates could change across different provinces in the EU even though the nominal involvement rates are all fixed at same degree.

Honohan and Lane ( 2003 ) analyze the rising prices rates in different states of the Economic and Monetary Union ( EMU ) of the European Union. The writers find that the rising prices rates have been significantly different during the period under survey. Particularly, the rising prices rates in the states in the fringe such as Ireland have had systematically high rising prices while Germany ‘s rising prices has been below the Euro Area norm. The writers identify that most of the research workers in this country have tended to concentrate on the productiveness factor. However the writers argue that the productiveness factor derived functions have non yet been taken into history. The on-going differences in rising prices rates across different provinces with the EMU are attributable to the differential impact of Euro failing on the external sectors of each one of the member provinces of the EMU. The writers assert that the productiveness derived functions are yet to be reflected in the rising prices rates and when they get accounted for, the rising prices rates will change even widely and the existent involvement rates in different provinces of EMU will diverge even further. Thus, even though the ECB fixes a individual involvement rate for all of EMU, the existent involvement rates could be different in each state depending on the rising prices rates predominating. In an of import research paper, Faini ( 2005 ) shows how the imprudent financial policies followed by some members of the EMU could do the involvement rates of the full brotherhood to lift. The writer observes that the penalty meted out to the states that violate the stableness and growing treaty by incurring larger than allowed financial shortages is non equal. He states that the impact of a member state running a big financial shortage could be two – foremost, the overall state spread additions and secondly, the involvement rate of the full EMU besides increases.

2.2. Financial and Monetary Integration in EMU

Poghosyan and Haan ( 2007 ) comment that one of the chief aims of the EMU is to accomplish fiscal integrating. The writers study the extent of fiscal integrating utilizing threshold vector error-correction theoretical account. In this theoretical account the dealing costs are analysed and any indicant of co-movements in fiscal environments are noted. This is applied on involvement rates from different fiscal markets in a figure of EMU states. Based on the consequences the writers conclude that “ merely for some state braces and fiscal market sections there is grounds in support of fiscal integrating ” . Borio and Fritz ( 1995 ) study the response of short-run loaning rates to alterations in policy rates utilizing a sample of 12 developed states. The writers identify that the grade of competition in loaning market and lucidity of signal are the two of import factors that determine the extent of relationship between these two rates. Besides, the writers find that there was no asymmetric relationship between these two with regard to additions and lessenings.

Codogno et Al. ( 2003 ) province that EMU is expected to make a well incorporate authorities debt market in Europe. However it is noted that the involvement rates on Euro-denominated bonds issued by different authoritiess in EMU have non converged. Significant spreads are found between them due to grounds such as liquidness and financial conditions predominating in several states, which affect their creditworthiness. Gerlach and Schnabel ( 2000 ) find from their research that between 1990 and 1998, excepting the period of market convulsion during 1992-1993, the involvement rates in EMU moved really closely with mean end product spreads and rates of rising prices. The writers refer to the Taylor regulation, which is vindicated by these findings. Toolsema et Al. ( 2001 ) examine the extent of pecuniary policy transmittal among 6 EMU states – Belgium, France, Germany, Italy, the Netherlands and Spain. They conclude that there was small grounds to turn out that pecuniary policy transmittal was working. They find that major differences exist in the sample both in the short-run and long-term alterations in involvement rates caused by pecuniary policy alterations.

Gerlach and Smets ( 1999 ) , on the footing of their survey of relationships between rising prices and end product spreads in different states in the EMU country, suggest that the ECB should respond to alterations in end product spread in the full part, even if the bank cares merely approximately rising prices as the writers find important relationship between rising prices and end product spreads in different states of the part. Martin ( 2001 ) surveies assorted sorts of convergence that have taken topographic point among different states of the Europe part and conclude that the cardinal bank has a really of import to play in guaranting that existent convergence develops among the different members provinces of the EMU part. The writer finds important range for growing of convergence among the states.

Prior to EMU, Europe had a functional pecuniary cooperation among a figure of provinces in the signifier of Europe Monetary System ( EMS ) . EMS was introduced in 1979 after the prostration of Brettonwoods system. Under EMS, the members states agreed to nail down their currencies on the footing of a pre-determined computation. There was no specific anchor state chosen even though Germany, with its Deutsche Mark, was considered the leader of the system, as its currency was one of the strongest and most stable at that clip. EMS restricted the motions in currency exchange rates within the scope of 2.25 % . EMS is considered the test tally for the greater cooperation in the signifier of EMU, which replaced EMS subsequently down the line. One of the most of import facets of analyzing EMS in comparing to today ‘s EMU is that under EMS, the pecuniary policy was determined independently by the cardinal Bankss of the members of the brotherhood.

Karfakis and Moschos ( 1990 ) analyze the relationships among involvement rates of different members of the old EMS system. The writer conducts Granger Causality tests to place the dependance of involvement rate of each province on that of the other province. The trials show that there existed a unidirectional causality between German involvement rate and the involvement rates of other provinces. Thus the provinces followed the alterations in pecuniary policy of Germany, which was the largest economic system in the Union. The writer asserts that when a figure of states enter into a brotherhood, they tend to follow the tendency set by the largest participant in the brotherhood even though they may hold the freedom to take their ain policies. The writers on the footing of their findings suggest a German laterality theory, which asserts that Germany played the polar function even in EMS where the single provinces could really take their ain policies. Fratianni and von Hagen ( 1990 ) find simple Granger causality trials to be unequal to do the decisions that Karfakis and Moschos ( 1990 ) have made in their research. They use a system of equations, which employ the short term involvement rate variable to capture alterations in the pecuniary policy of single provinces. They besides use United States short-run involvement rates as placeholder for the involvement rates in other states outside the EMS. The writers observe that the alterations in short term involvement rates of the provinces of EMS respond to a figure of different factor including alterations in rising prices and end product growing rates in domestic economic system, alterations in short term involvement rates in other provinces in EMS and besides outside the EMS besides other factors. On the footing of these observations, the writers conclude that “ in the short-run, the EMS is best portrayed as an synergistic web of pecuniary policies, where Germany is an of import participant but non the dominant 1 ” ( p. 21 ) .

Koukouritakis and Michelis ( 2005 ) study the linkages between the term constructions of two of the early entrants into EU ( Germany and France ) and 10 latter entrants ( Cyprus, the Czech Republic, Estonia, Hungary, Latvia, Lithuania, Malta, Poland, the Slovak Republic and Slovenia ) . The writers decompose footings constructions into transitory and lasting constituents. They attempt to analyze the short-run and long-term linkages among the involvement rates. They find that there existed weak short-run but strong long-run relationships among the term constructions of different states in the EU. On the footing of these observations the writers conclude that the states even before they entered into the EU had a wont of closely following the two larger economic systems on Europe – Germany and France.

2.3. Relationship between Interest Rates in Europe and Other states

Cumby and Mishkin ( 1987 ) study the relationship between the involvement rates in the US and the UK and determine the grounds for this relationship. The writers observe that the involvement rates in the US and Europe increased well during the 1970s and 1980s. This rise was seen non merely in nominal involvement rates but besides in existent rates. The writers conclude that “ There is a positive association between motions in U.S. existent rates and those in Europe. However, European existent rates typically do non travel one-for-one with U.S. existent rates, still go forthing open the possibility that European pecuniary policy can act upon domestic economic activity ” .

Bremnes et Al. ( 2001 ) analyze the relationships among the long-run involvement rates in Norway, Germany and the United States utilizing big samples. The writers use a Johanssen multivariate cointegration process to accomplish the research aims. They observe that US involvement rates have a important includes on the alterations in Norse involvement rates every bit good as EU involvement rates, which are applicable to Germany. The writers besides find that Norway ‘s involvement rates were closely associated with those of Germany. Thus the writers conclude that little states tend to tie in their pecuniary policies to that of the big states.

Ehrmann and Fratzscher ( 2004 ) acknowledge that there has been a strong grade of mutuality between the economic and pecuniary policies and public presentations of the European Union and US. However the writers investigate if the nature of this mutuality has undergone any important alteration after the creative activity of EMU within EU. The writers, alternatively of utilizing historic informations, use real-time informations to determine the alterations in the involvement rates of these two pecuniary governments. The writers observe that the mutuality has increased significantly after the creative activity of EMU. It has ever been the instance that changes in of import macroeconomic variables in the US have an of import impact on the alterations in involvement rates in the EU. However after the coming of EMU into image, it is noted that certain of import macroeconomic intelligence from the EU have begun to hold causal impact on the alterations in macroeconomic variables in the US as good. Thus the writers identify that the one-way causality has easy been transformed into bi-directional relationship between these two parts. This, harmonizing to the writers has led to the evident addition in the grade of mutuality between the two economic governments. The writers take this relationship to the following degree by saying that “ US macroeconomic intelligence have become good prima indexs for economic developments in the euro country ” .

2.4. Chapter Summary

The elaborate reappraisal of literature that have studied the relationship among the pecuniary variables of the provinces within the EU and besides outside the EU clearly shows that there are strong linkages seeable among the involvement rates. There are besides really strong pecuniary linkages seeable between the EMU and UK. This shows that the normal involvement rates are to a great extent inter-linked non merely within Europe but besides outside Europe as there are strong relationships found between Interest rates in EMU and US. However, it is observed that are differences in rising prices rates within the provinces that are members of EMU. Besides, the financial policies of the provinces in EMU are besides rather different with some provinces prosecuting in active shortage funding of the economic systems. Due to these built-in fluctuations, rising prices rates differ, which in bend cause broad spread fluctuations in existent involvement rates. These observations could turn out valuable while carry oning empirical questions into the nature and relationships between involvement rates in Europe, within and outside the EMU and EU. The observations made from empirical research in the following chapters of this thesis will be compared to the observations made from literature reappraisal in this chapter.

3. Co-movements of involvement rates

The aim of this research is to determine the behavior and nature of involvement rates in the European states. It is seen that the Europe is dominated by the European Union which comprises 27 states. 16 of these states have unified to organize a individual pecuniary brotherhood under which they portion a individual cardinal bank, pecuniary policy and Euro currency. This group is officially known as Euro Area ( ECB, 2009 ) . It is besides referred to as Euro Area in modern-day literature. For the states in Euro Area, because of individual pecuniary policy and presently, there is merely one set of common involvement derived from the money market ( Gali, 2004 ) . On the other manus, the other members of the European Union have single pecuniary policies and involvement rates. The first portion of this subdivision is concerned with the survey of co-movement of different sorts of involvement rates within the Euro Area. It is followed by an analysis of the co-movement of involvement rates in other EU provinces. The 3rd portion surveies utilizing quantitative methods, the extent of co-movement of involvement rates between EA and each one of the EU states. Finally, the co-movement of involvement rates between UK and US in the signifier of a survey of relationship between LIBOR and US Fed rate is performed. It is believed that the above mentioned surveies would assist to understand the relationship in involvement rates of three of import groups or states – EA, other provinces in EU and US. The results of these surveies are utile in the following chapter which ascertains the impact of other variables on involvement rates of these zones or states. The surveies related to the co-movements of involvement rates, as mentioned above, are conducted utilizing correlativity method which is explained in the earlier chapter of this thesis.

3.1 The Co-movement of involvement rates in Euro Area states

Following tabular array shows the consequences of correlativity between braces of different short and average term involvement rates in the Euro Area.

The above tabular array shows both correlativity coefficients and matching p-values for a void hypothesis trial that the correlativity is zero between the braces of series. It can be seen that all of the involvement rate series have really strong correlativity with each other. The strongest correlativity is found between 3 months Euribor and 1 month Euribor every bit good as between 1 twelvemonth Euribor and 6 months Euribor. The p-values are 0.000 for all braces bespeaking that the void value that correlativity is zero is rejected for each one of the braces.

3.2 Co-movement of Interest Rates in Other EU provinces

Following tabular array shows the consequences of correlativity analysis conducted utilizing short term involvement rates in different states which are portion of the EU but non portion of EA.

In the above tabular array, P values are shown below the correlativity coefficients. It can be seen that there are broad dispersed differences among the different provinces with regard to the relationships between their involvement rates. The involvement rates of Romania and Poland correlate 0.917 and a p-value of 0.000 agencies that the void hypothesis that correlativity is zero can be rejected at 99 % assurance degree. Similarly, Poland and Estonia have a really strong positive correlativity between their involvement rates as indicated by a coefficient value of 0.81 and a p-value of 0.000. Latvia and Estonia portion a really strong relationship and so make Chezh and Denmark. The involvement rates of Sweden and Hungary portion undistinguished negative relationships with that of Denmark. These consequences clearly show that the relationships between braces of provinces in EU which are non portion of EA are assorted at best. While some of their portion important positive relationships, some have undistinguished but negative relationships. Quite surprisingly, the involvement rates in Estonia, Latvia and Poland portion the strongest relationships with the involvement rate in UK. These consequences partially support the observations made in the literature reappraisal. Research workers have noted that the provinces in EA country tend to hold strong relationships among their nominal involvement rates.

3.3 The Co-movement of involvement rates in Euro Area and other EU member provinces

Estonia portions a really strong positive relationship with Euro Area. It is indicated by the correlativity coefficient of 0.946 and p-value of 0.000. UK and Euro Area portion strong positive relationship between their involvement rates. The correlativity coefficient between these involvement rates is 0.694. P-value of 0.000 shows that the void hypothesis that correlativity coefficient is equal to nothing is rejected at 99 % assurance degree. The involvement rates of Hungary and Sweden portion undistinguished negative relationships with the involvement rate of Euro Area.

3.4 The relation between EURIBOR and US involvement rates

This portion of the chapter is concerned with the analysis of co-movement between involvement rates in Europe and the US economic systems. The aim is to place the relationship between the 3 months Euribor and 3 months US Treasury. The end product of the correlativity analysis is provided below.

Pearson correlativity of 3m Euribor and 3m US Treasury = 0.430

P-Value = 0.000

It can be seen that the correlativity coefficient between Euribor and US Treasury measure is 0.43. A p-value of 0.000 shows that the void hypothesis comparing correlativity coefficient to zero is rejected at both 99 % and 95 % assurance degrees. This shows that the short term involvement rates at Europe and US portion a really strong positive relationship. It is observed from the reappraisal of a figure of research workers including Bremnes et Al. ( 2001 ) , Cumby and Mishkin ( 1987 ) and Ehrmann and Fratzscher ( 2004 ) that US and Europe tend to portion really strong pecuniary relationships. Research workers have attributed this to the fact that the two continents have had really strong fiscal and political relationships.

3.5. The relation between LIBOR and US involvement rates

It is necessary to obtain the correlativity coefficient between the involvement rates in UK and US. This is done by utilizing the 3 month US LIBOR and 3 month US Treasury. Following is the consequence of the correlativity analysis

Pearson correlativity of 3m Libor USD and 3m US Treasury = 0.966

P-Value = 0.000

As can be observed, the correlativity coefficient is 0.966 and the P value is 0. This shows that the void hypothesis that there is no important correlativity can be rejected at 95 % and 99 % assurance degrees. In other words, there is a really strong correlativity between short-run involvement rates in US and UK. This matches the observations made in literature reappraisal subdivision where it is noted that a figure of research workers have found empirical relationship between these two states ‘ pecuniary constabularies. This stems from the long-run political and economic association of US and UK. Particularly the pecuniary policies of both these states have been long known to travel in lock-steps with each other.

3.6. Chapter Summary

This chapter analyses the relationship between braces of involvement rates of different provinces in EU, EA and outside Europe. It is observed that there is really strong relationship between involvement rates refering to different clip periods as measured by 1 month, 3 months, 6 months and 1 twelvemonth EURIBOR. An analysis of short-run involvement rate of different provinces in Europe shows that some provinces such as Poland, Latvia and Lithuania portion really strong correlativity with UK LIBOR which indicates that little provinces tend to follow the pecuniary policies of larger economic systems in order to guarantee pecuniary and economic stableness in the states. Among the states outside the EA, Estonia portions the strongest relationship with EU. LIBOR and US Treasury rates are really closely correlated as may be expected on the footing of the strong economic ties that these two states portion with each other.

4. Interest Rates Modelling and Forecasting in Europe

This subdivision of the study is concerned with determining the impact of some of import factors on the alterations in short term involvement rates in Europe. The first portion of this subdivision is concerned with factors impacting involvement rates in Euro Area and the 2nd portion trades with the impact of alterations in Euro Area involvement rates upon other EU provinces ‘ involvement rates.

4.1 Factors impacting Interest rates in EA

This subdivision attempts to pattern the involvement rate alterations in Euro Area utilizing additive arrested development with two forecaster variables – money supply alterations and rising prices ( which is the equivalent of alterations in general monetary value degree ) . Following tabular array shows the consequences obtained from the arrested development map.

It can be observed that the both money supply ( M3 ) and rising prices have negative coefficients bespeaking that negative alterations in these variables cause a positive alteration in involvement rates. This is rather unlike the macroeconomic theory which states an addition in rising prices is countered by the cardinal Bankss through an addition in involvement rates so that the excess supply of money gets sucked back into the system. However the consequences presented here are contradictory to conventional economic wisdom. It may be necessary to determine the significance of these variables. It is seen that the P-values of these two variables are 0.023 and 0.159. Both values are more than 0.01 bespeaking that at 99 % assurance degree, the void hypotheses, that the coefficient of the two forecaster variables are equal to zero, are non rejected. This means that there is no important impact of M3 and rising prices on the involvement rates. The overall strength of the arrested development map is observed from the P-value associated with F-test which is 0.033 in this instance. As this value is besides more than 0.01 it can be concluded that at 99 % assurance degree, the two forecaster variables do non hold any important impact on the alterations in short term involvement rates. The adjusted R-squared value of 4.5 % means that the alteration in money supply and rising prices could together specify merely 4.5 % of the entire alterations in the involvement rates. In short, it can be concluded that money supply and rising prices do non act upon involvement rates.

The ground for this uneven decision could be that the involvement rates do non alter in tandem with money supply and rising prices. The involvement rates have a inclination to dawdle behind the macro economic system as the cardinal bank typically watches the macro economic variables over long term to do alterations in pecuniary policies ( Gali, 2008 ) .

4.2 Factors impacting Interest rates in other EU provinces

It is seen in the earlier subdivision of this chapter that money supply and rising prices do non look to hold any direct impact on the alterations in short term involvement rates in the EA. This portion of the chapter checks the impact of alterations in Euro Area involvement rates upon the alterations in involvement rates in other EU provinces. Following tabular array shows the consequences of 11 arrested development maps performed with involvement rates series of each one of the 11 other provinces in EU as the regressed variable and the 3m Euribor as the regressor variable.

The consequences as given above show that the involvement rate alterations in EA have had important impact on the involvement rates of merely some states. The involvement rates of Estonia, Latvia, Poland, Romania and UK have important positive relationships with the involvement rate alterations in the Euro Area as observed from the positive value of their several coefficients and the p-value of less than 0.01. This observation is based on t-tests performed at 95 % assurance degree. On the other manus some states including Bulgaria, Hungary and Sweden have negative coefficients but with undistinguished values as their p-values are all greater than 0.01. Thus for these states involvement rate alterations in EA have undistinguished but negative impact. For other states such as Denmark, Chezh Republic and Lithuania, the impact is positive but undistinguished. Therefore from the above arrested development consequences it can be concluded that short term involvement rates in EA have important positive impact merely on a smattering states in EU that are non portion of the EA.

5. Time series Analysis

The analysis so far has focussed on the relationships between involvement rates of different economic systems or better different sorts of involvement rates within the same state. This subdivision is focussed on the clip series facet of the information. Since the informations represent the value of the macroeconomic variable for a specific clip period, the uninterrupted set of informations can be considered a clip series. This subdivision analyses the clip series informations utilizing tendency analysis. The presence of stationarity in clip series is tested utilizing autocorrelation map.

5.1. Swerve Analysis

It is indispensable to understand the nature of clip series informations in order to come in it into prognosis theoretical accounts. Most of the prognosis theoretical accounts assume that the clip series follow a additive tendency. However it may non be true. Linear arrested development theoretical accounts assume that the independent variables have a additive causal impact on the dependant variable. However clip series theoretical accounts are built on the footing of the historic values of the same series. The intent of these theoretical accounts is to calculate the future class of the information series. Some of the most popular methods of prediction used are additive, quadtratic and exponential. It is customary to get down with the additive theoretical account to determine the nature of the theoretical account. The truth of the theoretical account is ascertained by comparing modelled informations to the existent information. Some of the cardinal steps of truth of the prognosis theoretical account are MAPE ( Mean Absolute Percent Error ) , Mean Absolute Deviation ( MAD ) and Mean Squared Deviation ( MSD ) . When these steps of mistake are minimised the theoretical account is stated to be acquire better. This subdivision builds the prognosis theoretical accounts for UK involvement rate and EU involvement rates.

5.1.1. 3m LIBOR

First, additive theoretical account is attempted for UK involvement rates. Following is the typical construction of a additive theoretical account

Crosstalk = b0 + b1t + vitamin E

Where

Crosstalk = Data value for period T

T = clip period

The value of b0 and b1 are ascertained utilizing Minitab processs for additive tendency analysis. Following chart shows the equation and the graph for involvement rate informations series for UK

As can be observed, the forecasted value when fitted against the existent value, is rather away and does non stand for the underlying tendency in the information. The negative coefficient means that the incline of the line is negative and so the information is diminishing over clip. However as can be observed from the information, the information series is really an increasing map and non a decreasing map. Besides, the high values of MAD and MSD clearly indicate that the additive prognosis theoretical account may non be appropriate for the UK involvement rate informations series.

Quadratic prognosis theoretical account is used to determine if the information series of UK involvement rates fit good into the quadratic map.

A quadratic theoretical account is built on the footing of the undermentioned construction.

Crosstalk = b0 + b1 T + b2 t2+ vitamin E

Where

Crosstalk = Data value for period T

T = clip period

t2 = squared value of clip period.

Following chart shows the quadratic theoretical account of the information series stand foring UK involvement rates.

As it can be observed easy from the graph shown above, the quadratic theoretical account is able to foretell the motion of the clip series rather accurately. The MAD and MSD mistake steps are both significantly lower than that while utilizing additive tendency theoretical account and so quadratic theoretical account is chosen as the proper tantrum the UK involvement rate informations series. Following is the theoretical account that is obtained utilizing quadratic modeling

Yt = 6.758 – 0.10561*t + 0.001045*t2

Where

Yt is the 3 month LIBOR during clip period T

Exponential smoothing can be used to bring forth better tantrum for the informations than quadratic modeling and additive modeling. Exponential smoothing is a procedure, which learns from the differences between the forecasted value and the existent value and adjusts the prediction factor to stand for the difference. Therefore with every subsequent information point the theoretical account evolves and produces better prognosiss. This is the ground for the broad popularity of exponential smoothing as the prediction method. It is besides observed that this method has the ability to take into history the alterations that take topographic point in the external environment and so the exponential smoothing method ever includes the latest set of informations in its prediction theoretical account.

Exponential smoothing typically takes the undermentioned signifier

Yt = a.xt-1 + ( 1-a ) Yt-1

Where

a is the smoothing factor

Following chart shows the alpha value as calculated utilizing the exponential smoothing method. It besides shows the close correlativity between the fitted values and the existent values.

It can be observed that the Alpha value is positive at 1.4891 and the MAD is 0.0810.This MAD can be compared to the MAD value of 0.3406 obtained from quadratic theoretical account method. Thus it is easy to observe that exponential smoothing does a better occupation of fiting the existent values. Using an alpha value of 1.4891 it may be possible to accurately calculate the hereafter alterations in 3 month LIBOR.

5.1.2. 3m EURIBOR

The tendency analysis of EURIBOR is besides performed to determine the nature of underlying tendency in the clip series. As with the instance of LIBOR, the EU involvement rates are first tantrum into a additive theoretical account. Following is the consequence obtained.

The additive theoretical account estimated from the clip series of 3 month EURIBOR is as follows

Yt = 3.754 – 0.0105t

Where

Yt is 3 month EURIBOR.

It is noted that the MAD and MSD values are significantly high. Besides, the above graph clearly shows that the fitted line is rather different from the existent line and so the theoretical account is non capable of calculating the hereafter motions in EURIBOR accurately. Quadratic modeling method is used to obtain a different theoretical account for the same information series. Following is the chart, which shows the quadratic theoretical account and its tantrum with the existent information.

It can be noted that the MAD and MSD for quadratic theoretical account is significantly less than those for the additive theoretical account estimated. Thus the prognosis theoretical account for 3 month EURIBOR involvement rate informations series can be stated as follows:

Yt = 5.323 – 0.10467*t + 0.000951*t2

Where

Yt is the 3 month LIBOR during clip period T

As seen in the instance of LIBOR, it may be possible to obtain beter prediction by usng the exponential smoothing method for EURIBOR every bit good. Therefore it is necessary to obtain alpha values for Euribor for the period under consideration. Following chart shows the exponential smoothing alpha value every bit good as the tantrum between the existent informations and fitted values of the information series.

The smoothing invariable obtained for EUROBOR is 1.89234. It can be noted that the MAD value for the prediction done utilizing exponential smoothing method is 0.06214 while it was 0.4845 for the quadratic theoretical account used earlier. Thus it is apparent that the exponential smoothing method can bring forth more accurate prognosiss. The alpha value to be used for accurate prediction of EURIBOR is 1.89234.

5.2. Autocorrelation

Another belongings, which is needfully studied while analyzing the clip series informations is autocorrelation. Since the information series represents the alterations in implicit in variables over clip, there is a really high chance that the subsequent alterations may be dependent upon the old alterations in the series. Thus in the series, there may be important correlativity between one information point and subsequent information points. In order to determine if this belongings is present, typically the information series is correlated with itself at specific slowdowns. It is noted that at lower slowdown degrees, autocorrelation tends to be higher than at higher slowdown degrees.

It is possible to carry on hypotheses trials to look into if the information involves any important autocorrelation at a specific slowdown degree. Lung-Box trial is normally used to determine the extent of autocorrelation and its statistical significance. Following is the expression used for Ljung-Box trial.

Q =

Where

N is the sample size

R2t is the autocorrelation at slowdown T

K is the figure of slowdowns that are tested

Following are the hypotheses that are tested

H0: autocorrelation at assorted slowdowns is equal to zero

Hour angle: autocorrelation at assorted legs is non equal to zero

Following graphs show the autocorrelation values of LIBOR and EURIBOR at different slowdown degrees. The ruddy lines denote the statistical significance bounds. Any value of autocorrelaiton which is outside the bound means that the autocorrelation is statistically important boulder clay that lag degree.

At Lag degree of 1, LIBOR has an autocorrelation coefficient of 0.9647 while EURIBOR has 0.9808. It can be noted that EURIBOR has a higher rate of autocorrelation than LIBOR. It is besides noted that the autocorrelation for both the involvement rates are statistically important till slowdown degree 7. The fact that EURIBOR has a higher grade of autocorrelation denotes that the alterations in EURIBOR are extremely dependent upon the old values of the information series. On the other manus, the alterations in LIBOR appear to be more random than EURIBOR.

5.3. Chapter Summary

Interest rate patterning in EA shows that both money supply and rising prices rate do non hold any important relationship with short-run involvement rates. This may be due to the slowdown that is observed between the alterations in pecuniary variables and the alterations in involvement rate as induced by the cardinal bank. A set of arrested development map carried out to determine the impact of alterations in EURIBOR on alterations in involvement rates in different provinces in Europe shows that some states such as Estonia, Latvia, Poland, Romania and UK show important impact of EURIBOR in their involvement rate determinations. Other states have undistinguished relationships. It is observed that exponential smoothing provides the best tantrum of the historic information for both LIBOR and EURIBOR. An analysis of the autocorrelation of these informations series clearly shows that there is important autocorrelation in both these informations series with LIBOR exhibiting somewhat more random alterations than EURIBOR.

6. Decision

One of the most of import aims of the formation of EU is to make fiscal and pecuniary stableness in the part. Besides, the recent behavior of cardinal Bankss to move in tandem while doing important alterations to pecuniary policies inspired this research which attempts to analyze the behavior of involvement rates in Europe utilizing popular quantitative techniques. Correlation analysis shows that the different short term involvement rates within Euro Area have really high grade of correlativity among themselves. On the other manus, merely some states have strong correlativities among their involvement rates among the other provinces of EU. The short term involvement rates in UK and EA correlate significantly and so make the short term involvement rates in UK and US. Arrested development analysis shows that money supply and rising prices do non hold any important prognostic values for the short term involvement rates as the involvement rates typically tend to travel on the footing of long term alterations to the macro economic variables. Finally, it is seen that the involvement rates in some states such as UK, Estonia, Latvia, Poland and Romania exhibit high grade of sensitiveness to alterations in the EA involvement rates. The consequences overall lead to a decision that the Al the involvement rates in Europe do non travel together or acquire influenced by each other. Merely a smattering of states including EA, UK, Estonia, Latvia, Poland and Romania appear to hold achieved measureable degrees of pecuniary integrating. This shows that EU still has a long manner to travel in their aspiration to accomplish fiscal and pecuniary integrating. EA, UK and US portion strong pecuniary relationships as expected on the footing of literature reappraisal. The clip series analysis of LIBOR and EURIBOR shows that alpha value of 1.4891 and 1.8923 severally can be used to obtain accurate prognosiss utilizing exponential smoothing methods. It is noted that EURIBOR has a higher grade of autocorrelation than LIBOR. In other words, LIBOR is more random than EURIBOR. The decision that can be drawn from this observation is that BOE has a wont of doing some speedy unexpected alterations in pecuniary policy than ECB. This decision is barely surprising, given the fact that BOE does non even print a elaborate study whenever the short-run price reduction rates are left unchanged by the Monetary Policy Committee ( MPC ) .

The concluding decision that can be drawn from the statistical trials conducted in this brief research is that the involvement rates in Europe exhibit assorted relationships. While some provinces such as EU, Poland, Latvia and UK portion really strong relationships among their pecuniary policies, other states appear to be largely independent. Even within the European Union there are provinces such as Denmark and Bulgaria, which do non hold any important relationships in footings of involvement rates. Therefore, the observation made in the literature reappraisal, that EU provinces tend to hold strong pecuniary relationships appears merely partially justified by the existent information. However it should be noted that this research is based on a limited set of informations and the consequences may be different when a longer clip skyline is involved. One decision, which emerges strong and resounding, is that both EMU and UK portion really strong pecuniary relationships, which are reflected in the empirical analysis. This besides matches the observations made by a figure of research workers earlier.

Mentions

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