Appendix I. Estimation Procedures
Bagliano F., C. Favero and F. Franco (1999), “Measuring Monetary Policy with VAR. Models: an Evaluation”, European Economic Review, Vol. 42, 1069-1112.
Barran F., V. Coudert, and B. Mojon (1996), “The Transmission of Monetary Policy in the European Countries”, CEPII Document de travail No. 96-03.
Canova F. and M. Ciccarelli (2000), “Forecasting and Turning Point Prediction in a Bayesian Panel VAR Model”, UPF WP No. AD 2000-05 (revised and resubmitted to the Journal of Econometrics).
Chib S. and E. Greenberg (1995), “Hierarchical Analysis of SUR Models with Extensions to Correlated Serial Errors and Time-Varying Parameter Models”, Journal of Econometrics, 68, 409-431.
Ciccarelli M. (2001), “Testing Restrictions in Normal Data Models Using Gibbs Sampling”, Working Paper AD n. 17, Universidad de Alicante, Alicante.
Ciccarelli M. and A. Rebucci (2001), “Asymmetries in the Transmission Mechanism of European Monetary Policy”, Temi di Ricerca n. 23, Ente Einaudi, Roma.
Clarida R., J. Gali, and M. Gertler (1997), “Monetary Policy Rules in Practice. Some International Evidence”, European Economic Review, Vol. 42, pp. 1033-1067.
Clements B., Z. Kontolemis, and J. Levy (2001), “Monetary Policy under EMU: Differences in the Transmission Mechanism?”, IMF WP/01/102, Washington DC.
Dedola L. and F. Lippi (2000), “The Monetary Transmission Mechanism: Evidence from the Industry Data of Five OECD Countries”, CEPR Discussion Paper 2508.
Doan T., Litterman R., and C. Sims (1984), “Forecasting and Conditional Projections Using Realist Prior Distributions”, Econometric Review, Vol. 3, No. 1, pp. 1-100.
Dornbusch R., C. Favero, and F. Giavazzi (1998), “A Red Letter Day”, CEPR Discussion Paper No. 1804. Published also as “The Immediate Challenge for the European Central Bank,” Economic Policy 26, 17-64.
Ehrmann M. (1998), “Will EMU Generate Asymmetry? Comparing Monetary Policy Transmission Across European Countries”, European University Institute WP No. 98/28.
Gelfand A.E., S. E. Hills, A. Racine-Poon, and A.F.M. Smith (1990), “Illustration of Bayesian Inference in Normal Data Models Using Gibbs Sampling”, Journal of the American Statistical Association, Vol. 85, pp. 972-985.
Gerlach S. and F. Smets (1995), “The Monetary Transmission Mechanism: Evidence from the G-7 Countries”, Bank for International Settlements Discussion Paper.
Giavazzi F. and A. Giovannini (1988), “The Role of Exchange-Rate Regime in a Disinflation”, in Giavazzi, Micossi, Miller (eds.), The European Monetary System, Cambridge University Press, Cambridge.
Giovannetti G. and R. Marimón and (1998), “An EMU with Different Transmission Mechanisms?”, European University Institute, WP No. 98/33.
Guiso L., A.K. Kashyap, F. Panetta, and D. Terlizzese (2000), “Will a common European Monetary Policy Have Asymmetric Effects?”, Economic Perspectives, Federal Reserve Bank of Chicago.
Hallett A. H. and L. Piscitelli (1999), “Does One Size Fit All? A Currency Union with Asymmetric Transmission and a Stability Pact”, mimeo, University of Strathclyde.
Litterman R. (1986), “Forecasting with Bayesian vector Autoregressions: Five Years of Experience”, Journal of Business and Economic Statistics, Vol. 4, 25-38.
Monticelli C. and O. Tristani (1999), “What Does the Single Monetary Policy Do? A SVAR Benchmark for the European Central Bank”, ECB WP No. 2.
Ortega E. and E. Alberola (2000), “Transmission of Shocks and Monetary Policy in the Euro area: An Exercise with NIGEM”, Bank of Spain WP No. 0010.
Peersman G. and F. Smets (1998), “The Taylor Rule: A Useful Monetary Policy Guide for the ECB?”, paper presented at the conference ‘Monetary Policy of the ESCB: Strategic and Implementation Issues’, Bocconi University, Milan.
Peersman G. and F. Smets (2001), “Are The Effects of Monetary Policy in The Euro Area Greater than in Booms?”, European Central Bank, WP No. 52.
Pesaran M. H. and R. Smith (1995), “Estimating Long-Run Relationships from Dynamic Heterogeneous Panels”, Journal of Econometrics, Vol. 68, pp. 79-113.
Rebucci A. (2001), Heterogeneous Panel VARs: Some Methodological Results and Two Macroeconomic Applications, Ph.D. Dissertation (Chapter 2), Queen Mary College, University of London, London.
Ramaswamy R. and T. Sloek (1997), “The Real Effects of Monetary Policy in the European Union: What Are the Differences?” IMF WP No. 97/160.
Sala L. (2001), “Monetary Transmission in the Euro Area: A Factor Model Approach”, mimeo, Universite Libre de Bruxelles, Bruxelles.
Universitat d’Alicant and IMF, respectively. We are grateful to Fabio Canova and Chris Gilbert for discussions and comments on a previous draft of the paper (circulated as ‘Asymmetries in the Transmission Mechanism of European Monetary Policy’). We are thankful also to Luigi Guiso and Fernando Restoy for their suggestions and encouragement, and to Ben Clements, Juan Dolado, Jordi Gali, Andy Hughes-Hallett, Zenon Kontolemis, Peter Ireland, Ron Smith, Javier Valles and participants in seminars at Bank of Spain, Boston College, CEMFI, European Central Bank, ‘Ente Einaudi’-Bank of Italy, IMF for comments and discussions. Ciccarelli’s research was undertaken while he was a research fellow at the Bank of Spain. Remaining errors are ours.
A similar approach is followed by Peersman and Smets (2001) in studying whether monetary policy has asymmetric effects across business cycle states in European countries and by Ortega and Alberola (2000) in analysing the simulated impact of different kinds of shocks in the Euro-area.
A notable early exception is represented by Dornbusch and others (1998), whose empirical evidence is based on a model allowing for limited interdependence between countries, controlling for intra-Europe exchange rate movements, and in which the impact of a ‘coordinated’ change in interest rates can be analysed. More recently, Clements, Kontolemis, and Levy (2001) and Sala (2001) have produced new evidence controlling more thoroughly for heterogeneous preferences, in addition to intra-Europe exchange rate movements and limited interdependence.
There is nothing in our empirical framework that would prevent us from including more than four countries except additional computing costs.
While the inclusion of contemporaneous inflation and output gaps in the information set of policy makers is not controversial, because of the lags with which monetary policy affects activity and the presence of nominal rigidities, the inclusion of the nominal exchange rate—though not uncommon in the literature—might be questioned. Bagliano, Favero, and Franco (1998), however, show that this is not an empirically relevant problem (at least in the case of the U.S.) as they find that the contemporaneous correlation between an exogenous measure of the unexpected component of monetary policy and the DM/US dollar rate is statistically insignificant. Comforted by this evidence on the U.S. case, we include also contemporaneous exchange rate gaps in (1).
All the data used are from the International Financial Statistics database of the IMF, except daily exchange rates which are courtesy of Marcello Pericoli of the Bank of Italy, whom we thank.
Assuming that the coefficient matrix of L0 in At (L) is constant over time renders the posterior distributions analytically tractable and is equivalent to assuming homoschedaticity of the structural residuals.
Note that the relative tightness of the prior distribution given on the elements of At (L) and Bt (L) distinguishes between own and other countries’ monetary policy instruments (the endogenous variables) on the one hand, and between instruments and objectives on the other hand, but does not distinguish between own and other countries’ objectives (the exogenous variables). See appendix for more details on this.
See Giavazzi and Giovannini (1989) and Kenen (1995) on this view of the functioning of the EMR from the mid-1980s onward.
In the specific case of linear restrictions, the restriction matrix R=[Ri,j] has dimension d × Gk, where G and k are defined as before, d = (G - 1) pm, and pm is the number of monetary policy coefficients restricted to be the same across countries. In particular, the null hypothesis that all parameters of the transmission mechanism are equal implies pm = 24. In this case, R has 72 rows, whose values are 1 when i = j,= 1 when j= i + k, and 0 otherwise. The hypothesis that the impact of monetary policy at specific lags, or that its cumulative effect after one or two years, are equal across countries can also be easily accommodated designing R accordingly.
The posterior distributions of the parameters of the reaction function of the four central banks considered are not reported here because of space constraints, but are available on request and are discussed in Ciccarelli and Rebucci (2001). These distributions are symmetric and generally their means have the expected signs. They display also significant parameter time variation, especially until 1992-93 for Germany and 1994-1995 for other countries, and relatively high persistence with an autoregressive coefficient ranging between 0.7 and 0.9 in all countries considered in the second part of the 1990s. Exchange rate volatility appears to matter for all countries considered. Germany’s seems to have reacted mainly to domestic objectives, even though the Bundesbank’s attention appears to have shifted in the run up to EMU from the dollar value of the DM to the external value of the DM vis-a-vis other European currencies. France, Italy, and Spain seem to have had different reaction functions. All three central banks, however, reacted strongly to contemporaneous movements in German interest rates. The behavior of the central bank of Spain is the most peculiar, appearing to be the least constrained by EMS, with its own output gap affecting short term interest rates throughout the period considered.
Even though we use data from January 1985 to December 1998 in the estimation, the first five years of monthly observations are used to initialise the estimation procedure (see appendix). Reported estimates, therefore, run only from January 1991 to December 1998.
This outlier coincides with the beginning of an aggressive, but short-lived, reduction of French official interest rates in the midst of the financial turbulence following the 1992 ERM crisis, not captured by the volatility variable. See Kenen (1995, page 154) on this episode.
All results not reported in this and the next two sections of the paper are available on request.
The series of estimated monetary policy shocks reported in Figure 1 run from January 1991 to December 1998, but we include 24 lags of this variable in the system and we need an additional year of monthly observations to initialize estimation (see appendix).
Recall from section 2.2.3 that a posterior distribution of q1 far apart from that of q can be interpreted as evidence against the null of equality of the relevant parameters of interest.
A comparison with the point estimates of Dornbusch and others (1998) based on a comparable specification is reported by Ciccarelli and Rebucci (2001), showing that none of the estimates is far away from those reported by Dornbusch and others (1998). This gives us confidence that the results reported here are not systematically distorted by any feature of the empirical framework used.
Ortega and Alberola explain the different response of Spain to a common monetary shock with a different sensitiveness to the wealth effect of interest rate changes compared to Germany, France, and Italy.