Interest Rate Behaviour in Europe Essay Example

research aims to assess the degree of interdependence in the monetary policies of different European countries. Its specific goal is to investigate the relationships between interest rates in the Euro Area and other member states of the European Union. Additionally, it seeks to determine if changes in interest rates in the Euro Area have a causal impact on interest rates in other European Union countries. Ultimately, its purpose is to provide insights into comparative behavior of interest rates across Europe.

The study employs empirical research methodology and historical information to establish theoretical explanations, validate hypotheses, and explore connections between crucial variables. The main quantitative research techniques employed include correlation and regression. Correlation gauges the degree of co-movement between two data sets by evaluating the direction and magnitude of variable changes (Levin and Rubin, 1997).The text discusses the popular method of determining correlation by analyzing the covariance between two sets of data. The formula used for this analysis is R = Sxy / [ Sx2 X Sy2 ] 0.5, where x and y represent the two data sets and R is the correlation coefficient. In this study, correlation analysis is applied to determine relationships between different types of short-term interest rates in the Euro Area, between interest rates in various European Union economies, between the interest rate of each EU member and the interest rate of the Euro Area, and between LIBOR and the US Fed rate.

It also states that the calculated correlation coefficient ranges from -1 to +1, with values closer to -1 indicating opposite directions and values closer to +1 suggesting perfect alignment. A value of zero indicates no significant correlation between variables. Furthermore, it

emphasizes that correlation only shows co-movement and does not imply causation.The study utilizes additive regression, a quantitative technique that models the changes in the dependent variable by considering changes in one or more independent variables. Regression is employed to assess how variations in these variables affect the dependent variable (Newbold et al., 2003).

The objective of this study is to evaluate the impact of money supply and inflation on the interest rate in the Euro Area using arrested development. This relationship can be illustrated by the equation: Ii = ai + ?1 Mi + ?2 Ci. In this equation, Ii denotes the interest rate during period I, Mi represents the money supply during period I with coefficient ?1, and Ci reflects the rate of inflation during period I with coefficient ?2. The significance of ?1 and ?2 values is determined through a t-test.

The arrested development map is evaluated using an F-test to determine its effectiveness. If the null hypotheses of t-tests are rejected, it means that both money supply and inflation have a significant influence on changes in interest rates. Conversely, if the null hypotheses are not rejected, it suggests that money supply and inflation do not determine changes in interest rates. The expectation is for both money supply and inflation to have a positive impact on interest rates, as indicated by coefficient values. This chapter of the thesis examines different studies conducted in Europe, including the Euro Area, to gather insights from their findings.

Literature Review

The research aims to analyze the behavior of interest rates in Europe. The third chapter focuses on surveying correlation between different sets of information, as discussed earlier. In the fourth chapter,

a straightforward explanation is presented for calculating the interest rate of the Euro Area using two variables - money supply and inflation. Lastly, the conclusion chapter provides a summary of discussions in this thesis and decisions made based on various analysis methods.

Several researchers have conducted studies on the same subject and provided valuable insights to academic knowledge. Reviewing these researchers' conclusions would help in predicting the outcomes of the planned empirical research for this study and comparing them to previous findings. This chapter examines a collection of academic studies that have analyzed the nature and interrelationships between different interest rates in Europe. The first section focuses on the correlation between interest rates and inflation rates across various countries within EMU, while the second part concentrates on financial and monetary integration within EMU. Additionally, the third section reviews literature exploring connections between EMU and other nations, particularly the US. A noteworthy aspect of European Union's Economic and Monetary Union (EMU) is that each country's fiscal policy is determined by its national government, whereas monetary policy is determined centrally for all EMU countries.

The goal of pecuniary policy is to achieve a stable pecuniary status by appropriately controlling rising prices and involvement rates. However, the impact of rising prices and general economic growth is influenced by the financial policies implemented by each government. If a government adopts an expansionary financial policy primarily funded through borrowing, it can result in poor quality growth and high inflation. Therefore, the effectiveness of central pecuniary policy relies on the financial discipline of the member states. Recognizing this, the EMU established a 'Stability and Growth Pact' which mandates that the deficit to GDP

ratio should not exceed 3% for any member state.

The stability and growth treaty aims to guarantee a certain level of financial responsibility, allowing monetary policy to concentrate on stabilizing and expanding the economy. To enforce these requirements, penalties are imposed on provinces that violate them. Numerous researchers have studied the connection between the financial conditions of EU member states and the impact of financial surpluses on inflation rates. When inflation fluctuates in a province, real interest rates may differ among different EU provinces, even though nominal interest rates remain unchanged. Honohan and Lane (2003) analyze inflation rates in various states within the European Union's Economic and Monetary Union (EMU). The authors discover significant differences in inflation rates during the examined period.

Specifically, the inflation rates in fringe states such as Ireland have consistently been high, while Germany's inflation has remained below the Euro Area average. The authors acknowledge that most researchers in this field have focused on productivity. However, they argue that productivity differentials have not yet been considered. The ongoing differences in inflation rates across different regions within the EMU can be attributed to the varying impact of Euro failure on the external sectors of each member state. The authors assert that the effects of productivity differentials have not yet been reflected in inflation rates and when they are accounted for, inflation rates will vary significantly and interest rates in different EMU member states will also diverge further.

Even though the ECB sets an individual interest rate for all of EMU, the actual interest rates may vary in each country depending on prevailing inflation rates. In a significant research paper, Faini (2005) demonstrates how the imprudent

monetary policies followed by some members of the EMU could cause the interest rates of the entire union to rise. The author notes that the punishment imposed on countries that violate the stability and growth treaty by incurring larger than allowed fiscal deficits is insufficient. He asserts that a member state running a large fiscal deficit could have two consequences - firstly, the overall country spread increases and secondly, the interest rate of the entire EMU also increases.

Poghosyan and Haan (2007) suggest that the main objective of the EMU is to achieve fiscal integration. They conducted a study using a threshold vector error-correction model to examine the level of fiscal integration. This model analyzed transaction costs and identified any indications of co-movement in fiscal environments. The study focused on interest rates from various financial markets in several EMU countries. The authors concluded that there is evidence supporting fiscal integration in only certain country pairs and financial market segments. In a similar vein, Borio and Fritz (1995) investigated how short-term lending rates respond to changes in policy rates across 12 developed countries.

The authors highlight that the level of competition in the lending market and the clarity of signal are significant factors in determining the relationship between these two rates. Additionally, the authors discover that there is no asymmetrical relationship in terms of increases and decreases. Codogno et al. (2003) assert that EMU is anticipated to establish a fully integrated government debt market in Europe. However, it is observed that the interest rates on Euro-denominated bonds issued by various governments in EMU have not converged.

Significant spreads exist between currencies in the European Monetary Union (EMU) due

to factors such as liquidity and prevailing financial conditions in different countries, which impact their creditworthiness (Gerlach and Schnabel, 2000). According to their research, interest rates in the EMU closely corresponded to average output spreads and inflation rates from 1990 to 1998, except during the market turbulence in 1992-1993. This study supports the Taylor rule (Gerlach and Schnabel, 2000). Another study by Toolsema et al. (2001) examines the transmission of monetary policy among six countries in the EMU: Belgium, France, Germany, Italy, the Netherlands, and Spain.

The authors of this study find little evidence to support the effectiveness of monetary policy transmission. They observe major differences in both short-term and long-term interest rate changes resulting from monetary policy alterations. Gerlach and Smets (1999) suggest, based on their examination of the relationship between inflation and output gaps in various countries within the EMU area, that the ECB should respond to changes in output gaps throughout the region, even if inflation is the bank's primary concern. They find a significant relationship between inflation and output gaps in different states of the region. Martin (2001) studies various types of convergence among different European countries and concludes that the central bank plays a crucial role in promoting real convergence among the member states of the EMU area. The author identifies significant potential for convergence growth among these countries.

Before EMU, Europe had a practical monetary cooperation among several states through the Europe Monetary System (EMS). EMS was established in 1979 after the collapse of the Brettonwoods system. In the EMS, member states agreed to fix their currencies based on a predetermined calculation. While Germany's Deutsche Mark was considered the leader due

to its strength and stability, no specific anchor country was chosen.

EMS limited the movements in currency exchange rates to 2.25%. EMS is seen as a precursor to the greater cooperation in the form of EMU, which succeeded EMS later on. One key aspect to note when comparing EMS to today's EMU is that under EMS, each member's central bank independently determined the monetary policy. Karfakis and Moschos (1990) studied the connections between interest rates of various members in the previous EMS system.

The writer performs Granger Causality tests to determine the dependence of involvement rate in each province on the involvement rate of another province. The results show that there was a one-way causality between the involvement rate of Germany and the involvement rates of other provinces. Therefore, the provinces followed the changes in Germany's monetary policy, as Germany was the largest economy in the Union. The writer suggests that when multiple countries join a union, they tend to follow the trend set by the largest member, even if they have the freedom to choose their own policies. Based on their findings, the writers propose a theory of German dominance, which suggests that Germany played a crucial role even in EMS, where individual provinces could theoretically set their own policies. Fratianni and von Hagen (1990) argue that simple Granger causality tests are insufficient to support the conclusions made by Karfakis and Moschos (1990) in their research.

The authors of the text discuss the use of equations that incorporate the variable of short-term interest rates to analyze changes in monetary policy within individual countries. They also utilize United States short-term interest rates as a placeholder for interest rates

in countries outside the European Monetary System (EMS). The authors find that changes in short-term interest rates within EMS countries are influenced by several factors, including inflation and output growth rates within their own economies, as well as short-term interest rates in other EMS countries and countries outside the system. Based on these findings, the authors conclude that in the short term, the EMS can be characterized as an interactive network of monetary policies, in which Germany plays an important role but is not dominant (p. 21). Koukouritakis and Michelis (2005) examine the connections between the term structures of two early EU members (Germany and France) and ten later entrants (Cyprus, the Czech Republic, Estonia, Hungary, Latvia, Lithuania, Malta, Poland, the Slovak Republic, and Slovenia).

The writers break down foundations buildings into temporary and permanent components. They try to analyze the short-term and long-term connections between the interest rates. They discover that there were weak short-term but strong long-term relationships between the yield curves of various countries in the EU. Based on these observations, the writers conclude that even before joining the EU, the countries had a habit of closely tracking the two major economies in Europe - Germany and France.

Cumby and Mishkin (1987) conducted a study to examine the connection between the participation rates in the United States and the United Kingdom and identify the reasons behind this connection. According to the authors, both nominal and real participation rates in the US and Europe witnessed a significant increase during the 1970s and 1980s. The researchers conclude that there is a positive relationship between movements in real interest rates in the US and Europe. However, European

real interest rates generally do not move at the same pace as those in the US.

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Current research suggests that European monetary policy has the potential to influence domestic economic activity despite existing rates. In their study, Bremnes et al. (2001) examine the long-term interest rate relationships in Norway, Germany, and the United States using large samples. They employ a Johanssen multivariate cointegration process to achieve their research goals. The authors find that changes in Norwegian interest rates and European Union interest rates, particularly applicable to Germany, are significantly influenced by U.S. interest rates.< /p >

The authors also find that Norway's interest rates were closely linked to those of Germany. Therefore, the authors conclude that smaller countries tend to align their financial policies with those of larger countries. Ehrmann and Fratzscher (2004) acknowledge the strong interdependence between the economic and monetary policies and performances of the European Union and US. However, the authors investigate whether this interdependence has undergone any significant change after the establishment of EMU within the EU. Instead of using historical data, the authors use real-time data to determine the changes in the interest rates of these two monetary authorities. The authors observe that the interdependence has increased significantly after the establishment of EMU.

The important impact of changes in key macroeconomic variables in the US on EU interest rates has always been evident. However, since the introduction of EMU, it has been observed that significant macroeconomic news from the EU also influences macroeconomic variables in the US. Therefore, the authors suggest that the initial one-way causality has evolved into a bi-directional relationship between these two regions. According to the authors, this

has resulted in a noticeable increase in interdependence between the two economic entities.

The writers argue that US macroeconomic indicators are reliable indicators of economic developments in the eurozone. Extensive literature review has shown strong connections between interest rates among EU member states and between the EU and UK. This indicates that interest rates are interconnected not only within Europe but also outside Europe, with notable relationships found between interest rates in the EMU and the US. However, there are differences in inflation rates among EMU member states.

Besides, the financial policies of the provinces in EMU are also quite different with some provinces pursuing active deficit funding of the economies. Due to these inherent fluctuations, inflation rates vary, which in turn cause wide spread fluctuations in real interest rates. These observations could prove valuable while conducting empirical inquiries into the nature and relationships between interest 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 review in this chapter.

The objective of this study is to investigate the behavior and characteristics of participation rates in European countries. It can be observed that Europe is largely governed by the European Union, which consists of 27 states. Sixteen of these states have formed an economic union in which they share a central bank, monetary policy, and the Euro currency. This collective is officially referred to as the Euro Area (ECB, 2009) and is also commonly known as Euro Area in contemporary literature. In the Euro Area countries, due to a unified monetary policy, there is only one

set of common interest rates derived from the money market (Gali, 2004).

On the other hand, the remaining members of the European Union have independent monetary policies and interest rates. This section first examines the correlation between various types of interest rates within the Euro Area. It then analyzes the correlation between interest rates in other EU member states. The third part utilizes quantitative methods to study the level of correlation between interest rates in the Euro Area and each individual EU country. Lastly, a study on the relationship between LIBOR and the US Fed rate is conducted to investigate the correlation between interest rates in the UK and US.

It is believed that the aforementioned studies would help in understanding the relationship in interest rates among three important groups or states - EA, other states in EU, and US. The results of these studies are useful in the subsequent chapter, which investigates the impact of other variables on interest rates of these zones or states. The studies related to the movements of interest rates, mentioned earlier, are conducted using the correlation method explained in a previous chapter of this thesis. The following table displays the results of correlation between pairs of different short and average term interest rates in the Euro Area.

The table above displays both correlation coefficients and corresponding p-values for a null hypothesis test that the correlation is zero between the pairs of series. It is evident that all of the interest rate series exhibit very strong correlation with each other. The highest correlation is observed between 3 months Euribor and 1 month Euribor, as well as between 1 year Euribor and 6 months

Euribor. The p-values for all pairs are 0.000, indicating that the null hypothesis that correlation is zero is rejected for each pair.

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The table below presents the results of correlation analysis conducted using short-term interest rates in various EU countries that are not part of the Eurozone (EA). In the table, the P values are displayed beneath the correlation coefficients. It is evident that there are significant differences among the different countries in terms of the relationships between their interest rates. The interest rates of Romania and Poland have a correlation coefficient of 0.917 and a P value of 0.000, indicating that the null hypothesis of zero correlation can be rejected with 99% confidence. Similarly, Poland and Estonia exhibit a very strong positive correlation between their interest rates, with a coefficient value of 0.81 and a P value of 0.000.

Latvia and Estonia share a strong relationship, as do Czechia and Denmark. However, the involvement rates of Sweden and Hungary have relatively weak negative relationships with Denmark. These findings clearly indicate that the relationships between pairs of countries in the European Union (EU) that are not part of the Eurozone (EA) are diverse. While some have significant positive relationships, others have weak but negative relationships.

Surprisingly, the involvement rates in Estonia, Latvia, and Poland show the strongest relationships with the involvement rate in the UK. These findings partially support the observations made in the literature review. Researchers have noted that the states in the EA country tend to have strong relationships among their nominal involvement rates.
Estonia has a very strong positive relationship with the Euro Area, as indicated by a correlation coefficient of 0.946

and a p-value of 0.000. The UK and Euro Area also have a strong positive relationship between their involvement rates.

The correlation coefficient between these participation rates is 0.694. A p-value of 0.000 indicates that the null hypothesis, stating that the correlation coefficient is equal to zero, is rejected with 99% confidence. The participation rates of Hungary and Sweden have insignificant negative relationships with the participation rate of the Euro Area. This section of the chapter focuses on analyzing the co-movement between participation rates in Europe and the US economies.

The correlativity analysis aims to determine the relationship between the 3 month Euribor and 3 month US Treasury. The results of the analysis are as follows: Pearson correlativity of 3m Euribor and 3m US Treasury = 0.430 and P-Value = 0.000. This indicates that there is a strong positive relationship between the Euribor and US Treasury measures, with a correlativity coefficient of 0.43. The p-value of 0.000 suggests that the null hypothesis, which compares the correlativity coefficient to zero, is rejected at both 99% and 95% confidence levels. Consequently, it can be concluded that there is a significant correlation between short term interest rates in Europe and the US. This finding is consistent with previous studies conducted by Bremnes et al.

(2001), Cumby and Mishkin (1987), and Ehrmann and Fratzscher (2004) have found that the US and Europe have strong monetary relationships. This is attributed to their strong fiscal and political ties. To determine the correlation coefficient between interest rates in the UK and US, we analyze the 3-month US LIBOR and 3-month US Treasury rates. The results of the correlation analysis show a Pearson correlation of 0.966

and a P-Value of 0. As we can see, the correlation coefficient is 0.966 and the P value is 0.

This demonstrates that the null hypothesis, which suggests that there is no significant correlation, can be rejected with 95% and 99% confidence levels. Essentially, there is a strong correlation between short-term interest rates in the United States and the United Kingdom. This aligns with findings in the literature review section, which highlights that several researchers have observed an empirical relationship between the monetary policies of these two countries. This connection is a result of the longstanding political and economic association between the US and UK. It is widely acknowledged that the monetary policies of both countries have historically moved in tandem.

This chapter examines the correlation between interest rates of different provinces in the European Union (EU), Euro Area (EA), and countries outside of Europe. It is noticed that there is a strong correlation between interest rates measured over different time periods, such as 1 month, 3 months, 6 months, and 1 year EURIBOR. When analyzing short-term interest rates of European countries, it is found that Poland, Latvia, and Lithuania have a strong correlation with the UK LIBOR. This suggests that smaller economies tend to follow the monetary policies of larger economies to ensure stability. Out of the countries outside of the EA, Estonia has the strongest relationship with the EU. Additionally, the LIBOR and US Treasury rates are closely correlated due to the strong economic ties between these two countries.

Interest Rates Modelling and Forecasting in Europe

This section of the study focuses on determining the impact of important factors on changes in short-term interest rates in Europe.

The first part of this section examines the factors affecting interest rates in the Euro Area, while the second part considers the impact of changes in Euro Area interest rates on other EU countries' interest rates. The goal is to model the changes in interest rates in the Euro Area using linear regression with two predictor variables - changes in money supply and inflation (equivalent to changes in general price level). The table below displays the results obtained from the regression analysis. It can be observed that both money supply (M3) and inflation have negative coefficients, indicating that negative changes in these variables lead to positive changes in interest rates.

This contradicts the common macroeconomic theory, which states that when prices rise, central banks increase interest rates in order to reduce the excess supply of money in the system. However, the results presented here challenge this conventional economic wisdom. It is important to assess the significance of these variables. The P-values for M3 and inflation are 0.023 and 0.159, respectively. Both values are greater than 0.01, suggesting that at a 99% confidence level, the null hypotheses - that the coefficients of the two predictor variables are equal to zero - are not rejected. This means that M3 and inflation do not have a significant impact on interest rates.

The arrested development map demonstrates overall strength, as evidenced by the P-value associated with the F-test being 0.033. Given that this value is greater than 0.01, it can be concluded that, with 99% confidence, the two predictor variables do not have a significant impact on the observed changes.