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Macroeconomic Impacts of the Interest Rate Shocks in the Selected Euro Area Countries

Macroeconomic Impacts of the Interest Rate Shocks in the Selected Euro Area Countries The following paper aims at analysing the impact of a shock in interest rate on selected economic variables in the five European Union member countries (Germany, France, Netherlands, Belgium and Luxembourg). The analysis shall be done through the VAR method where we will use the approach of the recursive Cholesky decomposition of the variancecovariance matrix. We expect that the results of the analysis will enable us to determine the shock impact on the development of the selected variables. The data necessary for the analysis will be taken from the IMF, BIS, Eurostat and ECB statistics collected in the time period 2002 - 2012. Keywords: Transmission Mechanism; Interest Rate; Nominal Effective Exchange Rate; Inflation; VAR; Cholesky Decomposition; Impulse-Response Function JEL Classification: F 36, F41, E52 1. Introduction The objective of the European monetary policy is to maintain price stability in all member states of the euro area through the single monetary policy. The last four years reviewed whether the single European monetary policy is able to achieve its main objective and thus create a stable economic environment for overall macroeconomic developments in the euro area and for its individual members. To analyze the ability of common monetary policy to influence the development of macroeconomic indicators, it is necessary to study ECB´s monetary policy transmission mechanism. This should allow influencing the development of other economic variables and ultimately, the development of the price level by regulating the official interest rates. The figure below (Figure 1) provides illustration of the main transmission channels of ECB monetary policy decisions. Source: ECB Figure 1. Transmission mechanism of monetary policy In our analysis, we will be interested in interest rates transmission channel and its impact on inflation, nominal effective exchange rate - NEER and GDP development. In this paper we will analyse, if shock in interest rates (monetary shock) will have a desirable impact on selected macroeconomic indicators (inflation, NEER, Journal of Advanced Studies in Finance GDP). We will estimate models based on the fundamental assumptions of the transmission mechanism of monetary policy. The recent crisis significantly affected the evolution of the euro area, so we divided our analysis into two periods ­ The first one covers the period from the first quarter of 2002 to the fourth quarter 2007. The second period covers also the years of the economic crisis (2002Q1012Q2). Selection of the countries Germany, France, Netherlands, Belgium and Luxembourg, reflects the size and influence of these economies in the euro area. The actual problems that affected economies such as Greece, Spain, and Ireland, have not yet manifested in selected countries. We will also be able to follow the shock impact on the observed indicators for the whole euro area and compare it with the results for the reporting countries. Finally, we could also conclude if the model is able to explain global performance across the euro area and the individual results of euro area countries. 2. Overview of the literature Many recent studies focused on the European monetary policy and monetary transmission mechanism. Crespo-Cuaresma, Reininger (Crespo-Cuaresma, Reininger 2007) studied the interest rate pass-through in five Central and Eastern European countries - the Czech Republic, Hungary, Poland, Slovakia and Slovenia. The pass - through appears similar in these countries and is higher than in core euroarea countries. Karagiannis, Panagopoulos, Vlamis (Karagiannis, Panagopoulos, Vlamis 2010) examined the interest rate transmission mechanism for the Eurozone and the USA. For an efficient monetary policy, any change in the central bank policy rate is meant to be transmitted to retail interest rates, ultimately influencing consumer and business lending rates and therefore aggregate domestic demand and output. They reveal the relative importance of the central bank and Money market rates as policy vehicle variables in the two banking systems. Chionis, Leon (Chionis, Leon 2006) examined the transmission process of the policy rate to the lending and deposit rates in Greece for the period 1996­2004 within bivariate cointegration and error correction framework. As a consequence of the common monetary policy the bank rates become much more responsive to the policy rate in terms of impact multipliers and speed of convergence to the equilibrium rates. They stated that positive effects of the monetary policy have not fully arrived at the debtors and investors yet. Badarau, Levieuge (Badarau, Levieuge 2011) analyze how financial heterogeneity can accentuate the cyclical divergences inside a monetary union that faces technological, monetary, budgetary and financial shocks. They show that a common monetary policy contributes to worsening cyclical divergences, in comparison with monetary policies that would be nationally conducted. Güntner (Güntner 2011) stated that the degree of monopolistic competition in the banking sector has a sizeable impact on the pass-through of changes in the policy rate. In particular, a more competitive market for bank credit amplifies the efficiency of monetary policy. Égert, Moons, Garretsen, Aarle, Fornero (Égert, Moons, Garretsen, Aarle, Fornero 2007) analyzes monetary policy in a stylized New - Keynesian model. Using simulations of the estimated model, it is analyzed how these aspects might affect monetary policy of the ECB and macroeconomic fluctuations in the Euro Area. Macroeconomic adjustments and monetary policy were shown to depend crucially upon the monetary policy regime: whether monetary policy was implemented under commitment, discretion or a rule-based framework was seen to have important consequences. Their analysis highlighted the role of external factors and fiscal policy for monetary policy in the Euro Area. Not only will the interest rate channel of monetary policy determine outcomes, but also the exchange rate channel, via pass-through and competitiveness effects. Designing monetary and fiscal regimes in the Euro Area is very much interdependent and conditional upon the economic structure and presence of different types of shocks. Brissimis, Skotida (Brissimis, Skotida 2008) examined the optimal design of monetary policy in the European monetary union in the presence of structural asymmetries across union member countries. Based on a two-country, forward-looking, general equilibrium model, which is estimated for two euro area countries (Germany and France), they showed that there are gains to be achieved by the ECB taking into account the heterogeneity of economic structures. They stated that it is important that the ECB takes into consideration national characteristics in formulating its monetary policy, especially in view of more countries joining the European monetary union in the future. Vlaar (Vlaar 2004) investigated the monetary transmission mechanism within the European Monetary Union. He concluded that permanently reducing the inflation objective depresses output in the first year, but has no real effects in the long run. His results indicated that aggregate demand shocks are most important during the first year, after which aggregate supply shocks dominate. Fourcans, Vranceanu (Fourcans, Vranceanu 2007) analysed the European central bank monetary policy over the period 1999006. They inferred some policy recommendations and pointed out that the bank appears to react significantly to future inflation deviations from the objective, but also directly to changes in real activity. For a bank like the ECB, the main concern should be the building of credibility. The focus on real activity may be premature, and may put at risk the euro zone performance in the longrun. Sondermann, Bohl, Siklos (Sondermann, Bohl, Siklos 2009) analyzes the first part of the stock market channel of monetary policy in the euro area. They find heterogeneous reactions of euro area stock markets to unexpected ECB's interest rate decisions. In general, they find ECB's decisions to be well anticipated by stock markets. Mirdala (Mirdala 2009) analyze the ability of the exchange rate to weaken or eventually to strengthen the transmission of the external inflation pressures to the national economy in the Czech Republic, Hungary, Poland and the Slovak republic. Sinicakova, Pavlickova (Sinicakova, Pavlickova 2011) stated that the period of crisis threatened the position of the Taylor-type rules and similar monetary rules in the application of monetary policy. It seemed that the Taylor rules were not valid any more. They have compared the formulations of monetary rules in several countries and they have calculated a monetary rule for Slovakia. Bartokova (Bartokova 2010) explains the functioning of a monetary transmission in general, and then focuses on the particular types of transmission channels used by each of the central banks in V4 countries. These countries were mainly focusing on the maintaining of price and exchange rate stability at the beginning of the transformation process. 3. Data and econometric model For the purpose of estimating the effect of the interest rate exogenous shocks on economy of the country we have used the quarterly data from 2002Q1 to 2012Q2 (42 observations) for three macroeconomic indicators gross domestic product, inflation (domestic consumer price index), NEER for each country from the group being analysed (Germany, France, Belgium, Netherlands and Luxembourg). Time series for the gross domestic product are seasonally adjusted. The data were taken from the IMF, Bank for international settlements, Eurostat, ECB and statistics. In order to analyze the transmission of the interest rate shocks, we shall use the VAR method ­ vector autoregressive methodology. This method belongs to the most successful, flexible and easily usable methods to analyse time series of more variables. The final causal impacts of unexpected shocks on the variables being examined are summarized in the impulse response functions. For our purposes we shall use the approach of the recursive Cholesky decomposition of the variance-covariance matrix. Before using the results of econometric analysis it is necessary to test the time series for stationarity and cointegration. Stationarity of time series is an important precondition of an econometric analysis quality. We shall determine stationarity through the unit root test using the ADF ­ Augmented Dickey - Fuller Test and the PP ­ Phillips ­ Perron Test. Both of the tests verify the zero hypotheses that the time series are non-stationary. The unit root test performed on the values and particularly on the first differentials of the time series has rejected the zero hypotheses, thus it has proven the existence of stationarity in the time series being monitored. After verification of stationarity it is necessary to carry out the Johansen´s cointegration test in order to verify existence of a long - term balance relationship among the variables. Cointegration testing is also important for distinguishing between real and false regression. The results of the Johansen´s cointegration test have proven that there are no stable relations among the variables, i.e. the variables are not cointegrated. The results of the unit root and cointegration tests are not reported here. They are available upon request from the author. 4. Results and discussion We create two models: The first model will analyze the impact of monetary policy shock - shock in the official interest rate on the development of 3-month Money market interest rates in the euro area and the development of 3month Euribor - Yt = [it, iet ] (it- 3 -month Money market interest rates, iet- 3- month Euribor). The second model is based on the assumption that the first model is working and that the shock in the official interest rate is transferred to Euribor. In this second model, we will analyze the impact of shocks in 3-month Euribor on the development of GDP, inflation rate and NEER in the euro area and in selected individual countries - Yt = [yt, et pt] (yt- gross domestic product, et- NEER, pt ­ consumer price index). 4.1 Effects of Interest rate shock on mmir and euribor Firstly we will analyze the impact of the shock in the official interest rate on the development of Euribor and Money market interest rate. Based on assumptions about the functioning of the interest rate transmission Journal of Advanced Studies in Finance mechanism, change in official interest rates should be passed on money market interest rates and then on bank rates. If we follow the evolution of interest rates (Figure2) in the period 2002012Q2 we can conclude that they have very similar development. We also noted the upward trend of monitored interest rates in the period 20052008 and the sharp decline in 2009 and 2010. CBIR_EU EURIB3M MMIR_3M Figure 2. The evolution of interest rates Source: Eurostat, ECB We studied the impact of shock in the official interest rate on the development of 3-month money market interest rate (MMIR) and the 3- month Euribor, based on the quarterly data for the period 2002007. On the basis of the analysis performed through the VAR method we may form the course of impulse-response functions in the following charts that show responses of MMIR in eurozone and Euribor to the Cholesky one standard deviation shocks. We would expect that a positive shock in official interest rates cause the same reaction in MMIR and Euribor. This reaction is relatively weak and can be observed in the following figure (Figure 3). Response to Cholesky One S.D. Innovations Response of EURIB3M to CBIR_EU Response of MMIR_3M to CBIR_EU -1 -1 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 Figure 3. Response of Euribor and MMIR Source: Author's calculations. Moving the period to second quarter 2012 (period 2002012Q2) reaction is relatively stronger and the highest response comes with lag of three quarters. At the end of the period the reaction disappears (see Figure 4). On this basis, we might conclude that the transmission of the official interest rate shock on Euribor and MMIR was of the same nature. Response to Cholesky One S.D. Innovations Response of MMIR_3M to CBIR_EU Response of EURIB3M to CBIR_EU -1 -1 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 Figure 4. Response of Euribor and MMIR Source: Author's calculations. 4.2. Effects of interest rate shock on GDP Development of GDP in the reporting countries during the period 2002 012Q2 was very similar to that of the entire euro zone (see figure 5, where 2005=100%). By 2007, GDP globally grew. In certain countries such as Luxembourg we can follow a stronger growth, in others such as France, the growth was slower. In 2008 all the countries were influenced by crisis and compared to 2007, GDP even declined. After this year, the GDP growth trend re-establishes. GDP_EU_SA GDP_DE_SA GDP_FR_SA GDP_BE_SA GDP_NL_SA GDP_LU_SA *EU=eurozone, DE=Germany, FR= France, BE = Belgium, NL= Netherlands, LU= Luxembourg Source: IMF Figure 5. Development of GDP The basic hypothesis for the reaction of GDP to interest rate shock is that a positive shock in interest rate (3 - month Euribor) may have a negative impact on further development of the GDP. We can expect that a rise of interest rates causes a decline of the major components of GDP - demand, investment, and thus with a certain time lag will have a negative impact on the development of the total GDP. The reaction of the shock can be observed in figure 6, which shows the response for the countries based on data up to 2007. We can state that in the case of euro area, we verified the basic hypothesis. Response of GDP to a shock in interest rate is negative and increases with the lag of five quarters. A very similar reaction has GDP development in Germany, France and Belgium. Weak response can be observed in the Netherlands and the basic hypothesis is not verified in the case of Luxembourg,One S.D. Innovations ± 2 S.E. Responseinterest rates has a positive Response to Cholesky One S.D. Innovations ± 2 S.E. Response to Cholesky where a positive shock in to Cholesky One S.D. Innovations ± 2 S.E. reaction of GDP. -1 -1 -1 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 Response to Cholesky One S.D. Innovations ± 2 S.E. Response of NEER_EU to EURIB3M Response of GDP_BE_SA to EURIB3M Response to Cholesky One S.D. Innovations ± 2 S.E. Response to Cholesky One S.D. Innovations ± 2 S.E. Response of NEER_DE to EURIB3M Response of GDP_NL_SA to EURIB3M Response of NEER_FR to EURIB3M Response of GDP_LU_SA to EURIB3M -1-1 *EU=eurozone, DE=Germany, FR= France, BE = Belgium, NL= Netherlands, LU= Luxembourg Response of P_EU to to EURIB3M Response of NEER_BE EURIB3M Response of P_DE to to EURIB3M Response of NEER_NLEURIB3M Response of P_FR to EURIB3M Response of NEER_LU to EURIB3M Figure 6. Response of GDP (by 2007) 0 0 Source: Author's calculations. With extending the monitored period up to 2012Q2, model verified the basic hypothesis with a lag of six quarters in all reported countries except Luxembourg (see Figure 7). In this case, the reaction is positive, and again at the end of the reporting period disappears. Response to Cholesky One S.D. Innovations ± 2 S.E. Response Response to to EURIB3M Response to Cholesky One S.D. Innovations ± 2 S.E. of P_LU Cholesky One S.D. Innovations ± 2 S.E. 0 -1 -1 0 1 2 3 4 5 6 7 8 9 10 -1 1 1 2 3 Journal of Advanced Studies in Finance *EU=eurozone, DE=Germany, FR= France, BE = Belgium, NL= Netherlands, LU= Luxembourg Source: Author's calculations. Figure 7. Response of GDP (by 2Q2012) 4.3 Effects of interest rate shock on NEER Another observed reaction on the interest rates shock is the reaction of the nominal effective exchange rates (NEER). NEER is a weighted average value of a country's bilateral exchange rate to all the currencies of the relevant trade partners of a country. The weights are determined by the importance a home country places on all other currencies traded within the pool, as measured by the balance of trade. (NBS, Investopedia). Based on the figure 8, we can follow the evolution of NEER in the individual's monitored countries and for the whole euro area. It can be concluded again, that the development of individual countries is very similar to that for the whole euro area.The development of NEER for euro zone is the most unstable while relatively stable development of NEER shows the case of Luxembourg. During the reporting period, NEER gradually appreciated in selected counties over 2002009 (except 2005) and also depreciated over 2010012Q2. NEER_EU NEER_DE NEER_FR NEER_BE NEER_NL NEER_LU *EU=eurozone, DE=Germany, FR= France, BE = Belgium, NL= Netherlands, LU= Luxembourg Figure 8. Development of NEER Response to Cholesky One S.D. Innovations ± 2 S.E. Response to Cholesky One S.D. Innovations ± 2 S.E. Response to Cholesky One S.D. Innovations ± 2 S.E. Source: Bank for international settlements The basic hypothesis in this case expects that a positive shock in interest rates will cause NEER 1 1 1 appreciation and thus a positive response of IRF function. The basic hypothesis was confirmed for the results in 0 0 0 the case of euro area. The initial reaction is only slightly positive, but its intensity increases with the distance of the two quarters. Impulse is lost after nine quarters. Similar, but not as strong reaction can be observed in the -1 case of France and Luxembourg. The basic hypothesis was not verified in the case of Germany, Belgium and the Netherlands (see 5Figure7 9).8 9 10 1 2 3 4 6 1 2 3 4 5 6 7 8 9 10 ResponseResponse of NEER_EU to EURIB3M ± 2 S.E. to Cholesky One S.D. Innovations ResponseResponse of NEER_DE to EURIB3M ± 2 S.E. to Cholesky One S.D. Innovations ResponseResponse of NEER_FR to EURIB3M ± 2 S.E. to Cholesky One S.D. Innovations Response of GDP_BE_SA to EURIB3M Response of GDP_NL_SA to EURIB3M Response of GDP_LU_SA to EURIB3M 2 1 1 0 0 -1 -1 -1 -1 1 2 3 4 5 6 7 8 9 10 3 1 2 3 4 5 6 7 8 9 10 1 1 Response of P_EU to EURIB3M Response of P_DE to EURIB3M Response of P_FR to EURIB3M Response of NEER_BE to EURIB3M Response of NEER_NL to EURIB3M Response of NEER_LU to EURIB3M 2 1 1 0 0 -1 -1 -1 -1 1 2 3 4 5 6 7 8 9 10 1 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 Response of *EU=eurozone, DE=Germany, FR= France, BE = Belgium, NL= Netherlands, LU= Luxembourg P_LU to EURIB3M Source: Author's calculations. 0 -1 Figure 9. Response of NEER (by 2007) 1 -1 -1 1 2 3 4 5 6 7 8 9 10 1 2 3 4 1 2 3 4 5 6 7 8 9 10 Response to Cholesky One S.D. Innovations ± 2 S.E. Response to Cholesky One S.D. Innovations ± 2 S.E. Response to Cholesky One S.D. Innovations ± 2 S.E. Journal of Advanced Studies in Finance 0.5 By including the crisis in the reporting period and moving the period to second quarter 2012, the NEER .0 reaction in some cases changed. We -1 state that in all reported countries, as well as for the euro area, the can basic hypothesis of NEER positive response to the positive shock in interestrates is verified. However, a positive -1.5 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 7 8 9 3 4 5 6 8 9 Response comes One S.D. Innovations ± 2 quarters 2 reaction to Choleskyup with a lag of fourS.E. 1 with the highest 7Innovations ±102 S.E.seven quarters (see6 Figure 10).±102 S.E. Response to Cholesky One S.D. intensity after Response to Cholesky One S.D. Innovations Response of GDP_BE_SA to EURIB3M Response of NEER_EU to EURIB3M 2 2 1 1 0 0 Response of GDP_NL_SA to EURIB3M Response of NEER_DE to EURIB3M 2 2 1 1 0 0 Response of GDP_LU_SA to EURIB3M Response of NEER_FR to EURIB3M Response of NEER_BE to EURIB3M Response of P_EU to EURIB3M .2 0 .0 2 2 1 1 0 0 -1 -.2 -.4 *EU=eurozone, DE=Germany, FR= France, BE = Belgium, NL= Netherlands, LU= Luxembourg Response of P_LU to EURIB3M Figure 10. Response of NEER (by 2Q 2012) 1 Source: Author's calculations. 0 4.4. Effects of interest rate shock on inflation -1 The verification of the price level reaction to the interest rates shock is one of the most important results of the model. 3We4 assume 7that a 9positive shock in interest rate will have a negative reaction in the evolution of the 1 2 5 6 8 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 9 10 price level in euro area, as well as in the monitored countries. 8 Behaviour of inflation in the euro area over the period 2002 - 2007 is relatively stable. Since the end of 2007 to the end of the reporting period the development of inflation has been relatively volatile. A similar trend can be observed in all surveyed countries with the most volatile inflation behaviour in the case of Belgium (see Figure 11). P_EU P_DE P_FR P_BE P_NL P_LU *EU=eurozone, DE=Germany, FR= France, BE = Belgium, NL= Netherlands, LU= Luxembourg Source: IMF Figure 11. Development of inflation rate As already mentioned, the basic hypothesis expects that positive shock in interest rate will cause a negative reaction in the evolution of the price level and the negative course of IRF functions performed through the VAR method. Based on the analysis of data till 2007, we can monitor the progress of IRF functions (see Figure 12). The basic hypothesis was confirmed in the euro zone with the lag of one quarter, but in the mid-term 1 2 3 4 5 6 7 8 9 1 4 5 6 8 9 10 Response 2 Cholesky One S.D. 7 10 to 3 Innovations ± 2 S.E. Response to Cholesky One S.D. Innovations ± 2 S.E. Response2to Cholesky 5 One 6S.D. Innovations10 2 S.E. ± 1 3 4 7 8 9 Response of GDP_BE_SA to EURIB3M Response of NEER_EU to EURIB3M Response of GDP_NL_SA to EURIB3M Response of NEER_DE to EURIB3M Response of GDP_LU_SA to EURIB3M Response of NEER_FR to EURIB3M the reaction disappears. A similar reaction can also be observed in the case of France and Luxembourg, for Belgium, the reaction is lagged by-1 five quarters. In the case of Germany and Netherlands the reaction is 1 2 controversial. It should be noted that in all cases the reaction is relatively weak. 3 4 5 6 7 8 9 10 -1 -1 -1 Response of NEER_BE to EURIB3M Response of P_EU to EURIB3M 0 .0 -1 -.2 -.2 -1 -1 -.2 -.4 -.4 Response to Cholesky One S.D. Innovations ± 2 S.E. Response to Cholesky One S.D. Innovations ± 2 Response to Cholesky One S.D. Innovations ± 2 S.E. S.E. -.4 2 3 5 6 7 Response 4of GDP_EU_SA 8 EURIB3M to 9 10 3 4 5 6 7 8 10 Response of GDP_DE_SA to9 EURIB3M 4 5 6 Response 4 5 6 of GDP_FR 9to EURIB3M 7 8 10 .4 .2 Response of P_LU to EURIB3M .4 .2 .0 -.2 -.4 -1 -.2 -.4 -1 -.2 -.4 -1 Response to Cholesky One S.D. Innovations ± 2 S.E. 1 2 3 4 5 6 7 8 9 10 1 2 3 43 5 4 6 5 7 6 8 7 9 8 10 9 1 2 1 2 10 1 1 2 33 44 5 5 6 6 7 7 8 8 9 910 10 10 Response to Cholesky One S.D. Innovations ± 2 S.E. 2 3 4 Cholesky One 8 9 Innovations ± 2 S.E. Response to 5 6 7 S.D. Response of GDP_BE_SA to EURIB3M Response of NEER_FR to EURIB3M Response of NEER_EU to EURIB3M *EU=eurozone, DE=Germany, FR= France, 2BE = Belgium,of NEER_DE to EURIB3M Luxembourg Response NL= Netherlands, LU= 2 2 1 1 Source: Author's calculations. 0 0 -1 Response of GDP_NL_SA to EURIB3M Response of GDP_LU_SA to EURIB3M Figure 12. Response of inflation (by 2007) 1 Including the years 2008 to 2012 (the second quarter) in the analyzed -1 period, the reaction of IRF functions -1 is-1 more significant. The lag of reaction -1 however has shifted to six quarters. In-1the case of Netherlands, the basic 1 2 4 6 7 8 10 hypothesis 3is not 5verified (see 9Figure 1 We expected a stronger9 and intensive 2response5 of 6price level to a 13). 2 3 4 5 6 7 8 10 1 3 4 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 3 4 5 1 2 3 4 5 6 7 8 9 10 shock in2 interest rate.6 7 8 9 10 Response of NEER_BE to EURIB3M Response of P_EU to EURIB3M 1.0 1 0.5 0 0.0 -1 -1 -1 -1.0 1 -1.0 -1.0 Response of P_LU to EURIB3M *EU=eurozone, DE=Germany, FR= France, BE = Belgium, NL= Netherlands, LU= Luxembourg Figure 13. Response of inflation (by 2Q 2012) Source: Author's calculations Journal of Advanced Studies in Finance Conclusion The aim of the analysis was to investigate the response of macroeconomic variables to a shock in interest rate. In this way, we wanted to analyze the ability of the monetary policy and transmission mechanism to influence selected indicators for the whole euro area, as well as of the selected countries. We examined two models. In the first model, we studied the reaction of the money market interest rates and Euribor to shock in official interest rate, where we verified the basic hypothesis. The second model analyzed the impact of interest rate shocks on GDP, NEER and inflation in the two studied periods. First period ends in 2007 before the crisis, the second period ends in second quarter of 2012 which already includes crisis period. The first examined indicator was GDP. Here, the basic hypothesis indicates that the positive shock in interest rate should cause the negative reaction of GDP. During the first observed period basic hypothesis was verified for the cases of euro zone and other countries except Netherlands and Luxembourg. The reaction of Netherlands was weak and the basic hypothesis for the case of Luxembourg must be rejected. In the second period, the model confirms the basic hypothesis but with the lag of six quarters in the case of all monitored countries except Luxembourg, where this hypothesis must be rejected again. The basic hypothesis for reaction of second monitored indicator ­ NEER expect that positive interest rate shock causes the positive reaction of NEER behaviour. This hypothesis was verified for euro zone, France and Luxembourg in the first observed period. Hypothesis was not verified for Germany, Belgium and Netherlands. Moving the period to second quarter 2012, the basic hypothesis of NEER positive response, in all reported countries, as well as for the euro area, was verified but with the lag of four quarters. For the last analysed indicator ­ inflation, the basic hypothesis of negative reaction to interest rate shock was verified during the first monitored period for the case of euro zone, France, Luxembourg and Belgium. We did not verify basic hypothesis in the case of Germany and Netherlands. For the second analysed period, the basic hypothesis is verified only with the lag of six quarters and the hypothesis is rejected in the case of Netherlands. The results of our analysis are not clear in all cases and weak especially for the case of inflation, so we cannot clearly confirms the high efficiency of the transmission mechanism. Therefore, it is certainly necessary to continue the analysis and explored model. Acknowledgement This paper was written in connection with scientific project VEGA no. 1/0973/11. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Advanced Studies in Finance de Gruyter

Macroeconomic Impacts of the Interest Rate Shocks in the Selected Euro Area Countries

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Abstract

The following paper aims at analysing the impact of a shock in interest rate on selected economic variables in the five European Union member countries (Germany, France, Netherlands, Belgium and Luxembourg). The analysis shall be done through the VAR method where we will use the approach of the recursive Cholesky decomposition of the variancecovariance matrix. We expect that the results of the analysis will enable us to determine the shock impact on the development of the selected variables. The data necessary for the analysis will be taken from the IMF, BIS, Eurostat and ECB statistics collected in the time period 2002 - 2012. Keywords: Transmission Mechanism; Interest Rate; Nominal Effective Exchange Rate; Inflation; VAR; Cholesky Decomposition; Impulse-Response Function JEL Classification: F 36, F41, E52 1. Introduction The objective of the European monetary policy is to maintain price stability in all member states of the euro area through the single monetary policy. The last four years reviewed whether the single European monetary policy is able to achieve its main objective and thus create a stable economic environment for overall macroeconomic developments in the euro area and for its individual members. To analyze the ability of common monetary policy to influence the development of macroeconomic indicators, it is necessary to study ECB´s monetary policy transmission mechanism. This should allow influencing the development of other economic variables and ultimately, the development of the price level by regulating the official interest rates. The figure below (Figure 1) provides illustration of the main transmission channels of ECB monetary policy decisions. Source: ECB Figure 1. Transmission mechanism of monetary policy In our analysis, we will be interested in interest rates transmission channel and its impact on inflation, nominal effective exchange rate - NEER and GDP development. In this paper we will analyse, if shock in interest rates (monetary shock) will have a desirable impact on selected macroeconomic indicators (inflation, NEER, Journal of Advanced Studies in Finance GDP). We will estimate models based on the fundamental assumptions of the transmission mechanism of monetary policy. The recent crisis significantly affected the evolution of the euro area, so we divided our analysis into two periods ­ The first one covers the period from the first quarter of 2002 to the fourth quarter 2007. The second period covers also the years of the economic crisis (2002Q1012Q2). Selection of the countries Germany, France, Netherlands, Belgium and Luxembourg, reflects the size and influence of these economies in the euro area. The actual problems that affected economies such as Greece, Spain, and Ireland, have not yet manifested in selected countries. We will also be able to follow the shock impact on the observed indicators for the whole euro area and compare it with the results for the reporting countries. Finally, we could also conclude if the model is able to explain global performance across the euro area and the individual results of euro area countries. 2. Overview of the literature Many recent studies focused on the European monetary policy and monetary transmission mechanism. Crespo-Cuaresma, Reininger (Crespo-Cuaresma, Reininger 2007) studied the interest rate pass-through in five Central and Eastern European countries - the Czech Republic, Hungary, Poland, Slovakia and Slovenia. The pass - through appears similar in these countries and is higher than in core euroarea countries. Karagiannis, Panagopoulos, Vlamis (Karagiannis, Panagopoulos, Vlamis 2010) examined the interest rate transmission mechanism for the Eurozone and the USA. For an efficient monetary policy, any change in the central bank policy rate is meant to be transmitted to retail interest rates, ultimately influencing consumer and business lending rates and therefore aggregate domestic demand and output. They reveal the relative importance of the central bank and Money market rates as policy vehicle variables in the two banking systems. Chionis, Leon (Chionis, Leon 2006) examined the transmission process of the policy rate to the lending and deposit rates in Greece for the period 1996­2004 within bivariate cointegration and error correction framework. As a consequence of the common monetary policy the bank rates become much more responsive to the policy rate in terms of impact multipliers and speed of convergence to the equilibrium rates. They stated that positive effects of the monetary policy have not fully arrived at the debtors and investors yet. Badarau, Levieuge (Badarau, Levieuge 2011) analyze how financial heterogeneity can accentuate the cyclical divergences inside a monetary union that faces technological, monetary, budgetary and financial shocks. They show that a common monetary policy contributes to worsening cyclical divergences, in comparison with monetary policies that would be nationally conducted. Güntner (Güntner 2011) stated that the degree of monopolistic competition in the banking sector has a sizeable impact on the pass-through of changes in the policy rate. In particular, a more competitive market for bank credit amplifies the efficiency of monetary policy. Égert, Moons, Garretsen, Aarle, Fornero (Égert, Moons, Garretsen, Aarle, Fornero 2007) analyzes monetary policy in a stylized New - Keynesian model. Using simulations of the estimated model, it is analyzed how these aspects might affect monetary policy of the ECB and macroeconomic fluctuations in the Euro Area. Macroeconomic adjustments and monetary policy were shown to depend crucially upon the monetary policy regime: whether monetary policy was implemented under commitment, discretion or a rule-based framework was seen to have important consequences. Their analysis highlighted the role of external factors and fiscal policy for monetary policy in the Euro Area. Not only will the interest rate channel of monetary policy determine outcomes, but also the exchange rate channel, via pass-through and competitiveness effects. Designing monetary and fiscal regimes in the Euro Area is very much interdependent and conditional upon the economic structure and presence of different types of shocks. Brissimis, Skotida (Brissimis, Skotida 2008) examined the optimal design of monetary policy in the European monetary union in the presence of structural asymmetries across union member countries. Based on a two-country, forward-looking, general equilibrium model, which is estimated for two euro area countries (Germany and France), they showed that there are gains to be achieved by the ECB taking into account the heterogeneity of economic structures. They stated that it is important that the ECB takes into consideration national characteristics in formulating its monetary policy, especially in view of more countries joining the European monetary union in the future. Vlaar (Vlaar 2004) investigated the monetary transmission mechanism within the European Monetary Union. He concluded that permanently reducing the inflation objective depresses output in the first year, but has no real effects in the long run. His results indicated that aggregate demand shocks are most important during the first year, after which aggregate supply shocks dominate. Fourcans, Vranceanu (Fourcans, Vranceanu 2007) analysed the European central bank monetary policy over the period 1999006. They inferred some policy recommendations and pointed out that the bank appears to react significantly to future inflation deviations from the objective, but also directly to changes in real activity. For a bank like the ECB, the main concern should be the building of credibility. The focus on real activity may be premature, and may put at risk the euro zone performance in the longrun. Sondermann, Bohl, Siklos (Sondermann, Bohl, Siklos 2009) analyzes the first part of the stock market channel of monetary policy in the euro area. They find heterogeneous reactions of euro area stock markets to unexpected ECB's interest rate decisions. In general, they find ECB's decisions to be well anticipated by stock markets. Mirdala (Mirdala 2009) analyze the ability of the exchange rate to weaken or eventually to strengthen the transmission of the external inflation pressures to the national economy in the Czech Republic, Hungary, Poland and the Slovak republic. Sinicakova, Pavlickova (Sinicakova, Pavlickova 2011) stated that the period of crisis threatened the position of the Taylor-type rules and similar monetary rules in the application of monetary policy. It seemed that the Taylor rules were not valid any more. They have compared the formulations of monetary rules in several countries and they have calculated a monetary rule for Slovakia. Bartokova (Bartokova 2010) explains the functioning of a monetary transmission in general, and then focuses on the particular types of transmission channels used by each of the central banks in V4 countries. These countries were mainly focusing on the maintaining of price and exchange rate stability at the beginning of the transformation process. 3. Data and econometric model For the purpose of estimating the effect of the interest rate exogenous shocks on economy of the country we have used the quarterly data from 2002Q1 to 2012Q2 (42 observations) for three macroeconomic indicators gross domestic product, inflation (domestic consumer price index), NEER for each country from the group being analysed (Germany, France, Belgium, Netherlands and Luxembourg). Time series for the gross domestic product are seasonally adjusted. The data were taken from the IMF, Bank for international settlements, Eurostat, ECB and statistics. In order to analyze the transmission of the interest rate shocks, we shall use the VAR method ­ vector autoregressive methodology. This method belongs to the most successful, flexible and easily usable methods to analyse time series of more variables. The final causal impacts of unexpected shocks on the variables being examined are summarized in the impulse response functions. For our purposes we shall use the approach of the recursive Cholesky decomposition of the variance-covariance matrix. Before using the results of econometric analysis it is necessary to test the time series for stationarity and cointegration. Stationarity of time series is an important precondition of an econometric analysis quality. We shall determine stationarity through the unit root test using the ADF ­ Augmented Dickey - Fuller Test and the PP ­ Phillips ­ Perron Test. Both of the tests verify the zero hypotheses that the time series are non-stationary. The unit root test performed on the values and particularly on the first differentials of the time series has rejected the zero hypotheses, thus it has proven the existence of stationarity in the time series being monitored. After verification of stationarity it is necessary to carry out the Johansen´s cointegration test in order to verify existence of a long - term balance relationship among the variables. Cointegration testing is also important for distinguishing between real and false regression. The results of the Johansen´s cointegration test have proven that there are no stable relations among the variables, i.e. the variables are not cointegrated. The results of the unit root and cointegration tests are not reported here. They are available upon request from the author. 4. Results and discussion We create two models: The first model will analyze the impact of monetary policy shock - shock in the official interest rate on the development of 3-month Money market interest rates in the euro area and the development of 3month Euribor - Yt = [it, iet ] (it- 3 -month Money market interest rates, iet- 3- month Euribor). The second model is based on the assumption that the first model is working and that the shock in the official interest rate is transferred to Euribor. In this second model, we will analyze the impact of shocks in 3-month Euribor on the development of GDP, inflation rate and NEER in the euro area and in selected individual countries - Yt = [yt, et pt] (yt- gross domestic product, et- NEER, pt ­ consumer price index). 4.1 Effects of Interest rate shock on mmir and euribor Firstly we will analyze the impact of the shock in the official interest rate on the development of Euribor and Money market interest rate. Based on assumptions about the functioning of the interest rate transmission Journal of Advanced Studies in Finance mechanism, change in official interest rates should be passed on money market interest rates and then on bank rates. If we follow the evolution of interest rates (Figure2) in the period 2002012Q2 we can conclude that they have very similar development. We also noted the upward trend of monitored interest rates in the period 20052008 and the sharp decline in 2009 and 2010. CBIR_EU EURIB3M MMIR_3M Figure 2. The evolution of interest rates Source: Eurostat, ECB We studied the impact of shock in the official interest rate on the development of 3-month money market interest rate (MMIR) and the 3- month Euribor, based on the quarterly data for the period 2002007. On the basis of the analysis performed through the VAR method we may form the course of impulse-response functions in the following charts that show responses of MMIR in eurozone and Euribor to the Cholesky one standard deviation shocks. We would expect that a positive shock in official interest rates cause the same reaction in MMIR and Euribor. This reaction is relatively weak and can be observed in the following figure (Figure 3). Response to Cholesky One S.D. Innovations Response of EURIB3M to CBIR_EU Response of MMIR_3M to CBIR_EU -1 -1 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 Figure 3. Response of Euribor and MMIR Source: Author's calculations. Moving the period to second quarter 2012 (period 2002012Q2) reaction is relatively stronger and the highest response comes with lag of three quarters. At the end of the period the reaction disappears (see Figure 4). On this basis, we might conclude that the transmission of the official interest rate shock on Euribor and MMIR was of the same nature. Response to Cholesky One S.D. Innovations Response of MMIR_3M to CBIR_EU Response of EURIB3M to CBIR_EU -1 -1 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 Figure 4. Response of Euribor and MMIR Source: Author's calculations. 4.2. Effects of interest rate shock on GDP Development of GDP in the reporting countries during the period 2002 012Q2 was very similar to that of the entire euro zone (see figure 5, where 2005=100%). By 2007, GDP globally grew. In certain countries such as Luxembourg we can follow a stronger growth, in others such as France, the growth was slower. In 2008 all the countries were influenced by crisis and compared to 2007, GDP even declined. After this year, the GDP growth trend re-establishes. GDP_EU_SA GDP_DE_SA GDP_FR_SA GDP_BE_SA GDP_NL_SA GDP_LU_SA *EU=eurozone, DE=Germany, FR= France, BE = Belgium, NL= Netherlands, LU= Luxembourg Source: IMF Figure 5. Development of GDP The basic hypothesis for the reaction of GDP to interest rate shock is that a positive shock in interest rate (3 - month Euribor) may have a negative impact on further development of the GDP. We can expect that a rise of interest rates causes a decline of the major components of GDP - demand, investment, and thus with a certain time lag will have a negative impact on the development of the total GDP. The reaction of the shock can be observed in figure 6, which shows the response for the countries based on data up to 2007. We can state that in the case of euro area, we verified the basic hypothesis. Response of GDP to a shock in interest rate is negative and increases with the lag of five quarters. A very similar reaction has GDP development in Germany, France and Belgium. Weak response can be observed in the Netherlands and the basic hypothesis is not verified in the case of Luxembourg,One S.D. Innovations ± 2 S.E. Responseinterest rates has a positive Response to Cholesky One S.D. Innovations ± 2 S.E. Response to Cholesky where a positive shock in to Cholesky One S.D. Innovations ± 2 S.E. reaction of GDP. -1 -1 -1 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 Response to Cholesky One S.D. Innovations ± 2 S.E. Response of NEER_EU to EURIB3M Response of GDP_BE_SA to EURIB3M Response to Cholesky One S.D. Innovations ± 2 S.E. Response to Cholesky One S.D. Innovations ± 2 S.E. Response of NEER_DE to EURIB3M Response of GDP_NL_SA to EURIB3M Response of NEER_FR to EURIB3M Response of GDP_LU_SA to EURIB3M -1-1 *EU=eurozone, DE=Germany, FR= France, BE = Belgium, NL= Netherlands, LU= Luxembourg Response of P_EU to to EURIB3M Response of NEER_BE EURIB3M Response of P_DE to to EURIB3M Response of NEER_NLEURIB3M Response of P_FR to EURIB3M Response of NEER_LU to EURIB3M Figure 6. Response of GDP (by 2007) 0 0 Source: Author's calculations. With extending the monitored period up to 2012Q2, model verified the basic hypothesis with a lag of six quarters in all reported countries except Luxembourg (see Figure 7). In this case, the reaction is positive, and again at the end of the reporting period disappears. Response to Cholesky One S.D. Innovations ± 2 S.E. Response Response to to EURIB3M Response to Cholesky One S.D. Innovations ± 2 S.E. of P_LU Cholesky One S.D. Innovations ± 2 S.E. 0 -1 -1 0 1 2 3 4 5 6 7 8 9 10 -1 1 1 2 3 Journal of Advanced Studies in Finance *EU=eurozone, DE=Germany, FR= France, BE = Belgium, NL= Netherlands, LU= Luxembourg Source: Author's calculations. Figure 7. Response of GDP (by 2Q2012) 4.3 Effects of interest rate shock on NEER Another observed reaction on the interest rates shock is the reaction of the nominal effective exchange rates (NEER). NEER is a weighted average value of a country's bilateral exchange rate to all the currencies of the relevant trade partners of a country. The weights are determined by the importance a home country places on all other currencies traded within the pool, as measured by the balance of trade. (NBS, Investopedia). Based on the figure 8, we can follow the evolution of NEER in the individual's monitored countries and for the whole euro area. It can be concluded again, that the development of individual countries is very similar to that for the whole euro area.The development of NEER for euro zone is the most unstable while relatively stable development of NEER shows the case of Luxembourg. During the reporting period, NEER gradually appreciated in selected counties over 2002009 (except 2005) and also depreciated over 2010012Q2. NEER_EU NEER_DE NEER_FR NEER_BE NEER_NL NEER_LU *EU=eurozone, DE=Germany, FR= France, BE = Belgium, NL= Netherlands, LU= Luxembourg Figure 8. Development of NEER Response to Cholesky One S.D. Innovations ± 2 S.E. Response to Cholesky One S.D. Innovations ± 2 S.E. Response to Cholesky One S.D. Innovations ± 2 S.E. Source: Bank for international settlements The basic hypothesis in this case expects that a positive shock in interest rates will cause NEER 1 1 1 appreciation and thus a positive response of IRF function. The basic hypothesis was confirmed for the results in 0 0 0 the case of euro area. The initial reaction is only slightly positive, but its intensity increases with the distance of the two quarters. Impulse is lost after nine quarters. Similar, but not as strong reaction can be observed in the -1 case of France and Luxembourg. The basic hypothesis was not verified in the case of Germany, Belgium and the Netherlands (see 5Figure7 9).8 9 10 1 2 3 4 6 1 2 3 4 5 6 7 8 9 10 ResponseResponse of NEER_EU to EURIB3M ± 2 S.E. to Cholesky One S.D. Innovations ResponseResponse of NEER_DE to EURIB3M ± 2 S.E. to Cholesky One S.D. Innovations ResponseResponse of NEER_FR to EURIB3M ± 2 S.E. to Cholesky One S.D. Innovations Response of GDP_BE_SA to EURIB3M Response of GDP_NL_SA to EURIB3M Response of GDP_LU_SA to EURIB3M 2 1 1 0 0 -1 -1 -1 -1 1 2 3 4 5 6 7 8 9 10 3 1 2 3 4 5 6 7 8 9 10 1 1 Response of P_EU to EURIB3M Response of P_DE to EURIB3M Response of P_FR to EURIB3M Response of NEER_BE to EURIB3M Response of NEER_NL to EURIB3M Response of NEER_LU to EURIB3M 2 1 1 0 0 -1 -1 -1 -1 1 2 3 4 5 6 7 8 9 10 1 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 Response of *EU=eurozone, DE=Germany, FR= France, BE = Belgium, NL= Netherlands, LU= Luxembourg P_LU to EURIB3M Source: Author's calculations. 0 -1 Figure 9. Response of NEER (by 2007) 1 -1 -1 1 2 3 4 5 6 7 8 9 10 1 2 3 4 1 2 3 4 5 6 7 8 9 10 Response to Cholesky One S.D. Innovations ± 2 S.E. Response to Cholesky One S.D. Innovations ± 2 S.E. Response to Cholesky One S.D. Innovations ± 2 S.E. Journal of Advanced Studies in Finance 0.5 By including the crisis in the reporting period and moving the period to second quarter 2012, the NEER .0 reaction in some cases changed. We -1 state that in all reported countries, as well as for the euro area, the can basic hypothesis of NEER positive response to the positive shock in interestrates is verified. However, a positive -1.5 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 7 8 9 3 4 5 6 8 9 Response comes One S.D. Innovations ± 2 quarters 2 reaction to Choleskyup with a lag of fourS.E. 1 with the highest 7Innovations ±102 S.E.seven quarters (see6 Figure 10).±102 S.E. Response to Cholesky One S.D. intensity after Response to Cholesky One S.D. Innovations Response of GDP_BE_SA to EURIB3M Response of NEER_EU to EURIB3M 2 2 1 1 0 0 Response of GDP_NL_SA to EURIB3M Response of NEER_DE to EURIB3M 2 2 1 1 0 0 Response of GDP_LU_SA to EURIB3M Response of NEER_FR to EURIB3M Response of NEER_BE to EURIB3M Response of P_EU to EURIB3M .2 0 .0 2 2 1 1 0 0 -1 -.2 -.4 *EU=eurozone, DE=Germany, FR= France, BE = Belgium, NL= Netherlands, LU= Luxembourg Response of P_LU to EURIB3M Figure 10. Response of NEER (by 2Q 2012) 1 Source: Author's calculations. 0 4.4. Effects of interest rate shock on inflation -1 The verification of the price level reaction to the interest rates shock is one of the most important results of the model. 3We4 assume 7that a 9positive shock in interest rate will have a negative reaction in the evolution of the 1 2 5 6 8 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 9 10 price level in euro area, as well as in the monitored countries. 8 Behaviour of inflation in the euro area over the period 2002 - 2007 is relatively stable. Since the end of 2007 to the end of the reporting period the development of inflation has been relatively volatile. A similar trend can be observed in all surveyed countries with the most volatile inflation behaviour in the case of Belgium (see Figure 11). P_EU P_DE P_FR P_BE P_NL P_LU *EU=eurozone, DE=Germany, FR= France, BE = Belgium, NL= Netherlands, LU= Luxembourg Source: IMF Figure 11. Development of inflation rate As already mentioned, the basic hypothesis expects that positive shock in interest rate will cause a negative reaction in the evolution of the price level and the negative course of IRF functions performed through the VAR method. Based on the analysis of data till 2007, we can monitor the progress of IRF functions (see Figure 12). The basic hypothesis was confirmed in the euro zone with the lag of one quarter, but in the mid-term 1 2 3 4 5 6 7 8 9 1 4 5 6 8 9 10 Response 2 Cholesky One S.D. 7 10 to 3 Innovations ± 2 S.E. Response to Cholesky One S.D. Innovations ± 2 S.E. Response2to Cholesky 5 One 6S.D. Innovations10 2 S.E. ± 1 3 4 7 8 9 Response of GDP_BE_SA to EURIB3M Response of NEER_EU to EURIB3M Response of GDP_NL_SA to EURIB3M Response of NEER_DE to EURIB3M Response of GDP_LU_SA to EURIB3M Response of NEER_FR to EURIB3M the reaction disappears. A similar reaction can also be observed in the case of France and Luxembourg, for Belgium, the reaction is lagged by-1 five quarters. In the case of Germany and Netherlands the reaction is 1 2 controversial. It should be noted that in all cases the reaction is relatively weak. 3 4 5 6 7 8 9 10 -1 -1 -1 Response of NEER_BE to EURIB3M Response of P_EU to EURIB3M 0 .0 -1 -.2 -.2 -1 -1 -.2 -.4 -.4 Response to Cholesky One S.D. Innovations ± 2 S.E. Response to Cholesky One S.D. Innovations ± 2 Response to Cholesky One S.D. Innovations ± 2 S.E. S.E. -.4 2 3 5 6 7 Response 4of GDP_EU_SA 8 EURIB3M to 9 10 3 4 5 6 7 8 10 Response of GDP_DE_SA to9 EURIB3M 4 5 6 Response 4 5 6 of GDP_FR 9to EURIB3M 7 8 10 .4 .2 Response of P_LU to EURIB3M .4 .2 .0 -.2 -.4 -1 -.2 -.4 -1 -.2 -.4 -1 Response to Cholesky One S.D. Innovations ± 2 S.E. 1 2 3 4 5 6 7 8 9 10 1 2 3 43 5 4 6 5 7 6 8 7 9 8 10 9 1 2 1 2 10 1 1 2 33 44 5 5 6 6 7 7 8 8 9 910 10 10 Response to Cholesky One S.D. Innovations ± 2 S.E. 2 3 4 Cholesky One 8 9 Innovations ± 2 S.E. Response to 5 6 7 S.D. Response of GDP_BE_SA to EURIB3M Response of NEER_FR to EURIB3M Response of NEER_EU to EURIB3M *EU=eurozone, DE=Germany, FR= France, 2BE = Belgium,of NEER_DE to EURIB3M Luxembourg Response NL= Netherlands, LU= 2 2 1 1 Source: Author's calculations. 0 0 -1 Response of GDP_NL_SA to EURIB3M Response of GDP_LU_SA to EURIB3M Figure 12. Response of inflation (by 2007) 1 Including the years 2008 to 2012 (the second quarter) in the analyzed -1 period, the reaction of IRF functions -1 is-1 more significant. The lag of reaction -1 however has shifted to six quarters. In-1the case of Netherlands, the basic 1 2 4 6 7 8 10 hypothesis 3is not 5verified (see 9Figure 1 We expected a stronger9 and intensive 2response5 of 6price level to a 13). 2 3 4 5 6 7 8 10 1 3 4 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 3 4 5 1 2 3 4 5 6 7 8 9 10 shock in2 interest rate.6 7 8 9 10 Response of NEER_BE to EURIB3M Response of P_EU to EURIB3M 1.0 1 0.5 0 0.0 -1 -1 -1 -1.0 1 -1.0 -1.0 Response of P_LU to EURIB3M *EU=eurozone, DE=Germany, FR= France, BE = Belgium, NL= Netherlands, LU= Luxembourg Figure 13. Response of inflation (by 2Q 2012) Source: Author's calculations Journal of Advanced Studies in Finance Conclusion The aim of the analysis was to investigate the response of macroeconomic variables to a shock in interest rate. In this way, we wanted to analyze the ability of the monetary policy and transmission mechanism to influence selected indicators for the whole euro area, as well as of the selected countries. We examined two models. In the first model, we studied the reaction of the money market interest rates and Euribor to shock in official interest rate, where we verified the basic hypothesis. The second model analyzed the impact of interest rate shocks on GDP, NEER and inflation in the two studied periods. First period ends in 2007 before the crisis, the second period ends in second quarter of 2012 which already includes crisis period. The first examined indicator was GDP. Here, the basic hypothesis indicates that the positive shock in interest rate should cause the negative reaction of GDP. During the first observed period basic hypothesis was verified for the cases of euro zone and other countries except Netherlands and Luxembourg. The reaction of Netherlands was weak and the basic hypothesis for the case of Luxembourg must be rejected. In the second period, the model confirms the basic hypothesis but with the lag of six quarters in the case of all monitored countries except Luxembourg, where this hypothesis must be rejected again. The basic hypothesis for reaction of second monitored indicator ­ NEER expect that positive interest rate shock causes the positive reaction of NEER behaviour. This hypothesis was verified for euro zone, France and Luxembourg in the first observed period. Hypothesis was not verified for Germany, Belgium and Netherlands. Moving the period to second quarter 2012, the basic hypothesis of NEER positive response, in all reported countries, as well as for the euro area, was verified but with the lag of four quarters. For the last analysed indicator ­ inflation, the basic hypothesis of negative reaction to interest rate shock was verified during the first monitored period for the case of euro zone, France, Luxembourg and Belgium. We did not verify basic hypothesis in the case of Germany and Netherlands. For the second analysed period, the basic hypothesis is verified only with the lag of six quarters and the hypothesis is rejected in the case of Netherlands. The results of our analysis are not clear in all cases and weak especially for the case of inflation, so we cannot clearly confirms the high efficiency of the transmission mechanism. Therefore, it is certainly necessary to continue the analysis and explored model. Acknowledgement This paper was written in connection with scientific project VEGA no. 1/0973/11.

Journal

Journal of Advanced Studies in Finance – de Gruyter

Published: Dec 1, 2012

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