There has been a lively academic discussion on the question of how important German interest rates are in the setting of interest rates in European Monetary System (EMS) member countries. 2/ The dominant position of German interest rates has been supported by a number of empirical results purporting to show evidence of: greater short-run exchange rate stability and a reduction in the response of D-Mark cross rates with other EMS currencies to changes in the U.S. dollar/D-Mark exchange rate (Rogoff 1985, Giavazzi and Giovannini 1986, and Artis 1987); zero risk premium between the U.S dollar and the German Mark but a nonzero risk premium between the German Mark and other EMS currencies (Taylor and Artis 1988); uni-directional Granger-causality from German to other EMS interest rates (Karfakis and Moschos 1990, Biltoft and Boersch 1992, and Katsimbris and Miller 1993); and evidence of uni-directional Granger-Sims causality from German broad money supply to that in other EMS members (Kutan 1991).
On the other hand, the dominant position of Germany in the setting of EMS interest rates has been rejected by: arguments that the EMS as a whole had a strong anti-inflationary bias (Padoa-Schioppa 1983, Artis and Taylor 1994); empirical support that developments in U.S. interest rates also were important in explaining EMS interest rate linkages (von Hagen and Fratianni 1990, de Grauwe 1992, Katsimbris and Miller 1993); and tests showing the German monetary base was not an important determinant of that of other EMS members (Fratianni and von Hagen 1990).
A useful framework for the analysis of EMS interest rate linkages was proposed by Fratianni and von Hagen (1990) who argued that German dominance could be established if: (a) monetary policies in the rest of the world did not Granger-cause the policies of other EMS members; (b) no two-way Granger-causality existed between the policies of EMS countries; and (c) German monetary policy Granger-caused policies in other EMS countries. In this note we employ cointegration and Granger-causality techniques within this framework. First, we investigate whether there exist long-run comovements between German and other EMS members’ interest rates. Second, we examine whether short-run changes in German interest rates convey information about future movements in other EMS interest rates, and vice versa. Third, we examine the role of U.S. interest rates in EMS interest rate linkages.
In this setting, German dominance of EMS interest rate movements implies: (a) uni-directional Granger causality running from German interest rates to other EMS interest rates; and (b) that the impact of the rest of the world’s monetary policy (represented here by developments in U.S. interest rates) on EMS interest rates is dominated by movements in German interest rates. Our results suggest that there are systematic interest rate relationships in the long-run between German and other EMS interest rates, and that in the short-run the interest rate linkage either stems from German to other European interest rates or is bidirectional. When allowance is made for the influence of U.S. interest rates on EMS interest rate linkages, there is less evidence of unidirectional causality stemming from German interest rates.
Engle and Granger (1987) show that if two series are integrated of order 1, 1(1), Granger causality must exist in at least one direction in, at least, the 1(0) variables. In the case where two series are cointegrated of order 1(1), a VAR model can be constructed in terms of the levels of the data or in terms of their first differences with the addition of an error-correction term to capture the short-run dynamics and to reduce the possibility of identifying "spurious causality". Inclusion of the error-correction term introduces an additional channel through which Granger-causality can be detected. According to Granger (1988), independent variables "cause" the dependent variable either if the error-correction term carries a significant coefficient or the first difference independent variables are jointly significant.
The testing procedure involves three steps. The first step is test the order of integration of the natural logarithm of the interest rate series. This can be done by computing the augmented Dickey-Fuller (ADF) test statistics which test for the presence of unit roots under the alternative hypothesis that the interest rates series are stationary around a fixed time trend.
Conditional upon the outcome, the second step is to test for cointegration of the interest rate series using the Johansen and Juselius (1990) maximum likelihood approach. If cointegration exists, then either uni-directional or bidirectional Granger-causality must exist in at least the 1(0) variables. In fact, there is a strong presumption that domestic and foreign interest rates are cointegrated based on the presumed stationarity of the expected exchange rate and the risk premium. As such, the test for cointegration uses the regression equation:
where Ig and Ie are the German and relevant EMS country interest rates, respectively, and θ is not restricted to 1, reflecting such factors as interest income taxation and possible measurement errors.
The third step is to carry out a standard Granger causality test augmented with an appropriate error-correction term derived from the long-run cointegrating relationship in equation (1). For valid inferences to be derived, such tests need to be undertaken on 1(0) variables. Assuming the levels of the interest rate series are 1(0) (and cointegrated), the appropriate formulation of a Granger-type test of causality (which must be applied to the stationary series) is:
where Δ is the difference operator, Ig and Ie are as previously defined, ECt-i is the error-correction term derived from the long-run cointegrating relationship, and ∊t and μt are zero-mean, serially uncorrelated random error terms. In equation (2) causality implies Ie “Granger-causing” Ig provided that some δi is not zero. Similarly, in Equation (3) Ig is “Granger-causing” Ie if some øi is not zero. Note that if the German and respective EMS interest rate are not cointegrated, then the error-correction term is dropped from equations (2) and (3) in the Granger-causality tests. To implement the Granger-causality test, F-statistics are calculated under the null hypothesis that all the coefficients of δi ɸi respectively, equal zero. As the results from Granger-causality tests are sensitive to the selection of lag length, results are presented from equations using the minimum final prediction error (FPE) criterion suggested by Akaike (1969) to determine the appropriate lag length.
III. Data and Results
Our empirical analysis uses monthly short-term interest rates from the International Financial Statistics data tape for Belgium, Denmark, France, Germany, Ireland, Italy, the Netherlands, Spain, the United Kingdom (U.K.), and the U.S. 3/ Data are from April 1979 to August 1992, which covers the inception of the EMS until the month before the so-called “Black Wednesday” of September 16, 1992.
Table 1 presents the ADF test statistics for the log levels and first differences of the interest rate series. From the results, the null hypothesis that the levels of the series contain unit roots cannot be rejected; however, on first-difference data the results reject the hypothesis of a unit root in all cases—i.e., in level form the interest rate series are 1(1) but in first difference form they are 1(0). Trace statistics for the cointegration of German and other EMS interest rates are presented In panel (a) of Table 2. The hypothesis of a single cointegrating vector is not rejected at the 5 percent level of significance in the case of German interest rates and those of Belgium, Denmark, France, the Netherlands, and the U.K., and at the 10 percent level in the case of Italy. On the basis of such results we conclude that these interest rate series are cointegrated and therefore causally related. These results contrast sharply with those of Karfakis and Moschos (1990) and Katsimbris and Miller (1993), who found no evidence of cointegration using residual based (Engle and Granger 1987) cointegration analysis. The finding of cointegration should not be a surprise given integrated capital markets and the discipline of a formal exchange rate mechanism, even though for part of the sample period some members had a looser exchange rate relationship and/or made use of capital controls. Causality test results from estimates of equations (2) and (3) are presented in Table 3. In the case where cointegration is indicated, the Granger-causality tests include the error correction term. The F-statistics find evidence of Granger-causality stemming from German interest rates to interest rates in Belgium, France, Spain, and the U.K., and evidence of bidirectional causality between German interest rates and those in Denmark, the Netherlands and Italy. No Granger-causality is found between German and Irish interest rates.
|(a) German interest rates and those of:|
|(b) U.S. interest rates and those of:|
|Germany -> Belgium||25.3651**||—||3.8400*|
|Belgium -> Germany||—||2.4481||−6.9692**|
|Germany -> Denmark||4.7607*||—||−4.7109*|
|Denmark -> Germany||—||3.3722*||2.2652*|
|Germany -> France||5.0787*||—||−1.8821|
|France -> Germany||—||0.8241||3.1563*|
|Germany -> Ireland||1.8332||—||—|
|Ireland -> Germany||—||1.6542||—|
|Germany -> Italy||1.9030||—||−0.8360|
|Italy -> Germany||—||0.5912||3.0622*|
|Germany -> Netherlands||7.0544**||—||−5.2263**|
|Netherlands -> Germany||—||5.5881*||1.0832|
|Germany -> Spain||5.4872*||—||—|
|Germany -> Germany||—||5.1291*||—|
|Germany -> U.K.||2.9957*||—||−7.6824**|
|U.K. -> Germany||—||0.5006||1.2858|
Katsimbris and Miller (1993) and de Grauwe (1991) argue that U.S. interest rates have an important causal influence on EMS interest rates. Our results find little evidence of a cointegrating relationship between the U.S. and EMS interest rates and that in the short-run U.S. interest rate developments did not change the pattern of EMS interest rate linkages markedly. Panel (b) of Table 2 gives trace statistics for the cointegration of U.S. interest rates on EMS interest rates, including Germany. Only in the cases of Belgium and France is the hypothesis of a single cointegrating vector not rejected at the 5 percent level. Results from trivariate Granger-causality tests, which include U.S. interest rates as a lagged dependent variable, and the error correction term in the cases of Belgium and France, are presented in Table 4. U.S. interest rates appear to convey information about short-run linkages between German and other EMS interest rates in the cases of Belgium, Denmark, France, Italy, and the Netherlands. The F-statistics indicate unidirectional Granger-causality stemming from German interest rates in two cases (France and Spain) rather than four previously, bidirectional causality in five cases (Belgium, Denmark, Ireland, Italy, and the Netherlands) as opposed to three previously, and again no causal relation between German and U.K. interest rates. In sum, the inclusion of U.S. interest rates shift the balance of the Granger causality test toward bidirectional causality. This result is consistent with the arbitrage activity which is to be expected from efficient capital markets.
|Germany -> Belgium||17.5838**||—||—||−4.5216*|
|Belgium -> Germany||—||5.1088**||3.1680||0.9054|
|Germany -> Denmark||2.5008*||—||0.7150||—|
|Denmark -> Germany||—||2.7844*||2.9571*||—|
|Germany -> France||6.2034**||—||6.6778**||−2.4928*|
|France -> Germany||—||1.6579||1.4985||1.7209|
|Germany -> Ireland||1.8580||—||0.3276||—|
|Ireland -> Germany||—||1.9669||4.4419*||—|
|Germany -> Italy||1.5527||—||2.0482||—|
|Italy -> Germany||—||0.6352||3.0275*||—|
|Germany -> Netherlands||9.4455**||—||4.1985*||—|
|Netherlands -> Germany||—||7.4798**||—||—|
|Germany -> Spain||6.2264**||—||0.0503||—|
|Spain -> Germany||—||3.6312||2.8207||—|
|Germany -> U.K.||0.3949||—||0.0067||—|
|U.K. -> Germany||—||0.2537||3.6727||—|
This note has examined interest rate linkages within the EMS. Cointegration tests suggest the existence of a long-run equilibrium relationship between German and most other EMS interest rates. This finding may be attributable to integrated financial markets and the discipline of a formal exchange rate mechanism, even though for part of the sample period some members had a looser exchange rate relationship and/or made use of capital controls. Bivariate VAR analysis suggests that Granger-causality stems either from German interest rates to other EMS interest rates or is bidirectional. When allowance is made for the influence of U.S. interest rates, the pattern of Granger causality is predominantly bidirectional. This result is consistent with the arbitrage activity which is to be expected from efficient capital markets.
AkaikeH. “Fitting Autoregressive Models for Prediction” Annals of the Institute of Statistical Mathematics Vol. 21 (1969) pp. 243–47.
ArtisMichael J. “The European Monetary System: An Evaluation” Journal of Policy Modelling Vol. 9 (1987) pp. 175–98.
ArtisMichael J. and Mark P.Taylor “The Stabilizing Effect of the ERM on Exchange Rates and Interest Rates” Staff PapersInternational Monetary Fund (Washington) Vol. 41 (1994) pp. 123–48.
BiltoftKarsten and ChristianBoersch “Interest Rate Causality and Asymmetry in the EMS” Open Economies Review Vol. 3 (1992) pp. 297–306.
de GrauwePaulIs the EMS a DM-zone? In A.Steinherr and D.Weiserbs(eds)Evolution of the International and Regional Monetary Systems. (London: Macmillan1991).
DickeyDavid A. and Wayne A.Fuller “Distribution of Estimates of Autoregressive Time Series with Unit Root” Journal of the American Statistical Association Vol. 74 (1979) pp. 27–31.
EngleRobert F. and Clive W.J.Granger “Co-integration and Error Correction: Representation, Estimation, and Testing.” Econometrica Vol. 55 (1987) pp. 251–76.
FratianniMichele and Jurgenvon Hagen “German Dominance in the EMS: the Empirical Evidence” Open Economics Review Vol. 1 (1990) pp. 67–87.
GiavazziFrancesco and AlbertoGiovannini “The EMS and the Dollar” Economic Policy (1986) pp. 456–85.
GrangerClive W.J. “Some Recent Developments in the Concept of Causality” Journal of Econometrics Vol. 39 (1988) pp. 199–211.
JohansenSoren and KatrinaJuselius “Maximum Likelihood Estimation and Inference on Cointegration—With Applications to the Demand for Money” Oxford Bulletin of Economics and Statistics Vol. 52 (1990) pp. 169–210.
KarfakisJ. Costas and DemetriosM. Moschos “Interest Rate Linkages within the European Monetary System: A Time Series Analysis” Journal of Money Credit and Banking Vol. 22 (1990) pp. 388–94.
KatsimbrisGeorge M. and StephenM. Miller “Interest Rate Linkages within the European Monetary System: Further Analysis” Journal of Money Credit and Banking Vol. 25 (1993) pp. 771–79.
KutanAl “German Dominance in the European Monetary System: Evidence from Money Supply Growth Rates” Open Economies Review Vol. 2 (1991) pp. 285–94.
Padoa-SchioppaTomasoEuropean Monetary System 5th Report and Evidence. (London: House of Lords Select Committee1983).
RogoffKenneth “Can Exchange Rate Stability be Achieved without Monetary Convergence?” European Economic Review Vol. 28 (1985) pp. 93–115.
von HagenJurgen and MicheleFratianni “German Dominance in the EMS: Evidence From Interest Rates” Journal of International Money and Finance Vol. 9 (1990) pp. 358–75.