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The exchange rate and the monetary transmission mechanism in Germany F. Smets and R. Wouters This paper was presented at the conference on General Equilibrium and Monetary Transmission, held at De Nederlandsche Bank, Amsterdam, 4-6 November 1998. The other papers presented at this conference are also published as DNB Staff Reports. DNB Staff Reports 1999, No.35 De Nederlandsche Bank ©1999 De Nederlandsche Bank NV Corresponding author: F. Smets e-mail: [email protected] Aim and scope of DNB Staff Reports are to disseminate research done by staff members of the Bank to encourage scholarly discussion. Editorial Committee: Martin M.G. Fase (chairman), Peter van Bergeijk, Peter Koeze, Marga Peeters, Bram Scholten, Job Swank, Bert Groothoff (secretary). Subscription orders for DNB Staff Reports and requests for specimen copies should be sent to: De Nederlandsche Bank NV External Relations and Information Department Westeinde 1 P.O. Box 98 1000 AB Amsterdam The Netherlands Internet: www.dnb.nl The exchange rate and the monetary transmission mechanism in Germany Frank Smets and Raf Wouters THE EXCHANGE RATE AND THE MONETARY TRANSMISSION MECHANISM IN GERMANY∗ Frank Smets and Raf Wouters ABSTRACT For the conduct of monetary policy under floating exchange rates it is important to understand the role of the exchange rate in the monetary transmission mechanism (MTM). The timing and the magnitude of the effects of a change in the exchange rate on output and inflation may be quite different from traditional interest rate channels, thereby affecting optimal policy. In this paper we examine the exchange rate channel in the MTM in Germany by estimating an identified VAR model. Two features of the results are highlighted. The effect of a policy shock on the exchange rate accelerates the pass-through of policy into prices and leads to a different response of the various components of GDP. We then show that these qualitative effects can be duplicated in a general equilibrium model for a semi-small open economy with sticky prices and wages that is calibrated to capture the main features of the German economy. ∗ This paper was written while the first author was at the BIS. The views espressed are solely our own, and not necessarily those of the BIS, the ECB or the National Bank of Belgium. Correspondence: Frank Smets, European Central Bank, Kaiserstrasse 29, D-60311 Frankfurt am Main, tel: 49-69-1344 6550, fax: 49-69-1344 6000, e-mail: [email protected]; Raf Wouters, National Bank of Belgium, tel: 32-2-221 2803, fax: 32-2-221 3162. -1- INTRODUCTION Recently an increasing number of papers have analysed the implications of the openness of an economy for the conduct of monetary policy under floating exchange rates and explicit inflation targeting more specifically 1. This is of considerable interest as most of the inflation targeting regimes have been established in small open economies 2. One implication of openness is that the conventional interest rate channels in the monetary transmission mechanism (MTM) are supplemented by significant exchange rate channels. Understanding the role of the exchange rate in the MTM is important because the timing and the magnitude of the effects of a change in the exchange rate on output and inflation may be quite different, thereby affecting optimal policy. The important role of the exchange rate in the practical conduct of policy in open economies is also reflected in the use by a number of central banks of a so-called monetary conditions index (MCI) – a weighted average of a short-term interest rate and an exchange rate – to assess the stance of monetary policy. In such MCIs the relative weight on the exchange rate depends on its relative importance in affecting aggregate demand 3. Identified Vector Autoregressions (VARs) are a useful tool to empirically examine the MTM because they allow to separate the endogenous reaction of the monetary authorities to developments in the economy from exogenous monetary impulses. The estimated effects of such policy shocks can then be used to assess the validity of calibrated dynamic general equilibrium (CDGE) models by comparing them with the theoretical impulse response functions of those models. In contrast to VAR-models, such structural models can be used to do policy analysis 4. Because of its focus on the United States, both the VAR and CDGE literatures have often ignored the open-economy aspects of the monetary transmission mechanism. For example, in the recent extensive survey of the VAR literature on the effects of monetary policy by Christiano et al (1998) only two pages are devoted to the open economy. More recently, an increasing number of studies have looked at other countries than the United States and have been confronted with the crucial role of the exchange rate in both the identification of the policy shocks and in the transmission mechanism 5. Similarly, the question of monetary policy in an open economy has received little attention in the CGE literature. Various authors have examined whether and how 1 See, for example, Svensson (1998), Conway et al (1998), Bharucha and Kent (1998), Ball (1998). 2 See Svensson (1998) for references to the large literature on inflation targeting. 3 MCIs therefore ignore other exchange rate channels such as the direct price effect. For a discussion of the usefulness of MCIs see Gerlach and Smets (1998) and Eika et al (1997). 4 See Christiano et al (1998) for a lucid explanation of this research strategy in the context of monetary policy. 5 See, for example, Clarida and Gertler (1997), Bernanke and Mihov (1997), Cushman and Zha (1997), Smets (1997), Kim and Roubini (1995) and Barran et al (1997). -2- two-country general equilibrium models can explain international comovements of output, exchange rates and asset returns 6. Only a few, however, have explicitly analysed the various exchange rate channels in a small open-economy model 7. In this paper we attempt to fill this gap. First, we provide evidence on the role of the exchange rate in the MTM in a relatively open economy by estimating an identified VAR model using quarterly data series for Germany over the post Bretton Woods period. In contrast to other VAR studies that have analysed the German economy, we focus in particular on the open-economy aspects both by emphasising the role of the exchange rate in the identification of the monetary policy shocks and by examining how the policy transmission through the exchange rate may alter the effects of policy on output and prices. To do so, we analyse the effects of a policy tightening on the different components of GDP including exports and imports and various price indices such as the GDP deflator and export and import prices. In the second part of the paper, we then show that the estimated qualitative effects of a policy shock can be duplicated in a general equilibrium model for a semi-small open economy that is calibrated to capture the main features of the German economy. Following Kollman (1997) and Svensson (1998), the model features an open economy with two varieties of goods, domestically produced and import goods, and with sticky prices and wages. Several characteristics of the monetary transmission mechanism in an open economy are common to the empirical and theoretical impulse response functions. With sticky prices, a monetary policy tightening results in a substantial real appreciation of the exchange rate. Moreover, in the presence of a risk premium the exchange rate may continue to appreciate before falling back to its long-run equilibrium. This real appreciation has two clearly discernible effects. First, its immediate impact is to lower the prices of imported goods. This accelerates the impact of a policy tightening on consumer prices in two ways. It reduces the prices of imported consumer goods. It also reduces the price of imported intermediate goods thereby reducing the marginal cost of firms. Second, the loss of competitiveness following the real appreciation has substitution effects as both domestic and foreign demand will shift towards goods produced abroad. This leads to a fall in net exports and a fall in output putting further pressure on domestic prices. 6 See, for example, Chari, Kehoe and McGratten (1996), Backus, Kehoe and Kydland (1995), Kollman (1998). 7 Two exceptions are Kollman (1997) and Svensson (1998). -3- 1 THE MONETARY TRANSMISSION MECHANISM IN GERMANY In this section we describe the VAR model we use to analyse the effects of a monetary policy shock on the German economy. We, first, describe the estimated VAR and some of the diagnostics. Then, we discuss our strategy to identify monetary policy shocks. The basic results are discussed in the third subsection. Finally, the fourth and fifth subsections contain some extensions and a short evaluation of the results. 1.1 The VAR-model The variables included in each of the estimated VAR-models can be partitioned into four groups. The first group consists of US real GDP, y tf , and the US federal funds rate, stf . These variables are included to capture world economic and financial conditions which are bound to have significant effects on an open economy such as the German one 8. In all of the results reported below we assume that both of these foreign variables are exogenous to the German block of the VAR-model. In other words, while US output and interest rates influence the German variables, there is no feedback from the German to the US variables (Cushman and Zha, 1997). The second group of variables consists of the two goal variables of the central bank: German real GDP, y t , and the German consumer price index, cpt . The third group includes the two financial variables which capture the stance of monetary policy in an open economy: the German day-today rate, st , and the real trade-weighted DM exchange rate, xt . Finally, the last group consists of other variables that are included in the VAR to analyse their response to a policy shock. In the benchmark model this group includes German real net exports, nxt , German import prices, mpt , and German export prices, xpt 9. In the extended VARs discussed below additional variables are included in this fourth group. 8 Initially we also included a world commodity price index. However, as removing this variable did not appear to affect the estimated impulse responses, we excluded it from the VAR to increase the degrees of freedom. 9 To overcome the problem of the break in the statistical series due to reunification in 1991, the West-German and allGerman series on GDP, net exports and prices were spliced in the first quarter of 1991. Net exports refers to the log difference between exports and imports of goods and services in the national accounts. The terms of trade is the corresponding log difference between the export and import deflator. The trade-weighted DM exchange rate is calculated by the BIS. With the exception of the interest rates, all variables are measured in percentage logs. -4- Using standard notation, the vector of endogenous variables in the benchmark model can thus be [ written as: x’’t = y tf st f yt cpt st xt nxt mpt ] xpt . The benchmark VAR- model is then given by: xt = A( L) xt −1 + u t , (1) where ut is the vector of reduced-form residuals. Equation (1) is estimated using quarterly data over the post-Bretton Woods period 1974:1-1997:4. In contrast to many other VAR studies on the monetary transmission mechanism, we use quarterly data in order to be able to analyse the effects of a policy shock on the various components of GDP which are only available on a quarterly basis. The post-Bretton Woods sample was chosen because it captures a reasonably stable policy regime in which the Bundesbank pursued monetary policy under floating exchange rates using money aggregates as intermediate targets. We can not reject stability over this sample using a series of tests suggested by Bernanke and Mihov (1998). Finally, following Sims (1980) a sequence of likelihood ratio tests was used to determine the lag length of 3 quarters. 1.2 The identification of monetary policy shocks In order to identify the monetary policy shocks from the reduced-form residuals in equation (1), we use a block-recursive short-run identification scheme as in Sims (1980), Christiano et al. (1998) and Bernanke and Mihov (1998). In this scheme the US variables are assumed to contemporaneously cause the German variables. Similarly, German output and inflation are assumed to be contemporaneously predetermined with respect to the two financial variables, the German interest rate and exchange rate. In other words, the current day-to-day rate and the exchange rate may respond to current output and inflation shocks, but not vice versa, i.e. policy or exchange rate shocks have only lagged effects on output and inflation. Finally, in order not to restrict the effects of a policy shock on the other variables, these are ordered last. Within each of the blocks a recursive identification scheme which corresponds to the ordering of the variables in equation (1) is implemented. The only exception is the identification within the policy block, where a recursive identification structure is inappropriate. To see this, consider the following short-run reduced-form model: -5- uts = α1ε tp + α 2ε tx , utx = β1ε tp + β 2ε tx (2) (3) where the left-hand variables are the interest rate and exchange rate residuals after the effects of the other shocks have been removed and ε tp and ε tx denote a policy shock and an exchange rate shock respectively. A recursive identification scheme would imply that either α 2 or β1 is equal to zero. Consider first equation (3). Obviously, with free international capital mobility innovations in the policy rate will have an immediate impact on the exchange rate ( β1 > 0 ) through the interest rate parity condition. A causal ordering whereby the exchange rate innovations come before the interest rate innovations is thus inappropriate. Alternatively, one could restrict α 2 in equation (2) to be equal to zero, effectively assuming that the central bank does not contemporaneously respond to exchange rate shocks. While such an assumption may be appropriate for a large, relatively closed, economy such as the United States (Eichenbaum and Evans, 1995), it is not convincing for open economies, in particular with quarterly data. Grilli and Roubini (1995) have shown that in open economies this assumption can lead to an exchange rate puzzle, i.e. a tightening of the policy instrument leads to a depreciation of the exchange rate. As discussed below this is also the case in our data set. Various alternative strategies have been followed in the literature to solve the identification problem in equations (2) and (3). One commonly applied strategy is to use instrumental variables to estimate the effect of an exchange rate shock on the interest rate ( α 2 ). Under the assumption that the monetary authority does not directly respond to the foreign interest rate, one possible instrument is the foreign interest rate innovation (Bernanke and Mihov (1997), Kim and Roubini (1995) and Clarida and Gertler (1997)). The latter three studies include a bilateral dollar-DM exchange rate in the VAR and use the US interest rate as the instrument. Because we use a tradeweighted exchange rate in our VAR, this assumption is less attractive in this paper 10. 10 When we apply this identification strategy to our data set, we find that α 2 is implausibly large, but very imprecisely estimated. The implicit short-run weight on the exchange rate is about 0.5. -6- Cushman and Zha (1997) apply the Sims and Zha (1998) identification scheme to an open economy VAR for Canada. They assume that the central bank only responds to current financial variables (such as the exchange rate) which are contemporaneously observed. In contrast, the central bank does not react to current output and prices which are only observed with a lag. However, the exchange rate is affected by all variables in the VAR including current output and prices. Under these assumptions, current output and price innovations can be used as instruments to estimate the policy reaction to the exchange rate. Because our model is estimated on quarterly data, the assumption that the central bank has no information about current output and prices is inappropriate, making this identification scheme less appealing for our purposes. Finally, a number of authors have used foreign exchange rates to identify exchange rate shocks. Smets (1997) for France and Italy and Shioji (1998) for Spain use the bilateral dollar-DM exchange rate as an instrument to estimate the response of policy to exchange rate shocks. For European countries other than Germany this works nicely because of the well-known stylised fact that changes in the bilateral dollar-DM rate often lead to pressures on their bilateral exchange rate with the DM. A somewhat different identification strategy is to use institutional knowledge of the central bank’s operating procedures to distinguish policy from exchange rate shocks. Mojon (1998) uses the spread between the day-to day rate and the tender rate to identify exchange rate shocks in France since 1987. This procedure is attractive because a description of French operating procedures reveals that the central bank often allowed exchange market pressures to show up in this spread. Smets (1996) suggests that rather than estimating the response of the policy rate to exchange rate pressures one could use the weight ( ω ) used by central banks in monetary conditions indices (MCIs) to solve the identification problem. In this case the policy shock can be defined as: ε tp = (1 − ω )u ts + ω u tx (4) Comparing equations (2) and (3) with (4), the relative weight of the exchange rate in the MCI is given by ω = −α 2 /( β 2 − α 2 ) . Since one would expect α 2 , which captures the effect of exchange rate shocks on the domestic interest rate, to be non-positive (an appreciation of the exchange rate leads to a fall in policy rates) and β 2 to be positive, this weight should lie between zero and one in a successful identification scheme. -7- Graph 1 Estimates of the weight on the exchange rate (ω) in Germany (Estimation period: 1975:1-97:4) 10-year moving window estimates 2.0 1.5 1.5 1.0 1.0 Omega Omega Recursive estimates 2.0 0.5 0.5 0.0 0.0 -0.5 -0.5 -1.0 -1.0 1985 1987 1989 1991 1993 1995 1997 1985 1987 1989 1991 1993 1995 1997 If the value of ω were known as in Canada and New Zealand where the central banks use an MCI as operating target variable, then the identification problem is potentially solved as one can define the policy shock according to (4). However, the Bundesbank has never used an MCI in conducting monetary policy. We therefore follow Smets (1997) and empirically estimate the weight over the sample period by running the following regression using innovations in the bilateral yen-dollar rate as an instrument: uts = −ω /(1 − ω )utx (5) Over the whole sample the point estimate of ω is 0.26 with a t-statistic of 2.16. Graph 1 which gives the recursive estimates of ω , shows that there is no evidence of instability over the sample period. The right-hand panel which plots 10-year moving window estimates shows that the weight was very imprecisely estimated during the 1970s, but is since then quite precisely estimated at around 0.20. The point estimate of ω comes surprisingly close to the MCI weight that international organisations have used to measure the policy stance in Germany 11. In what follows we will identify a policy shock by imposing a weight of 0.25 in equation (4) 12. 11 For example, see IMF (1996, p.16) and OECD (1996, p.31) 12 The two-step procedure proposed in Smets (1997) has the advantage that in estimating the weight one can use information that is not included in the VAR-model. In this paper we verified that including the yen-dollar rate in the VAR-model does not materially affect the reported results. -8- 1.3 The effects of a monetary policy shock on the German economy Graph 2 shows the effects of a policy shock on real GDP, the CPI index, the day-to-day interest rate, the real effective exchange rate (in the left-hand panel) and real net exports, the terms of trade, import prices and the nominal trade balance (in the right-hand panel). First consider the left-hand panel of Graph 2. A monetary policy tightening is characterised by a significant increase in the day-to-day rate and a sharp real appreciation of the exchange rate. Consumer prices fall relatively quickly and after some pause continue to fall after two years. Real GDP falls significantly after two quarters and then returns to baseline. Several features of these impulse response patterns are worth noting. First, the interest rate tightening is relatively modest compared to a typical tightening in closed economy VAR-models for the US economy (For example, Christiano et al (1998)). The policy rate increases by only 15 basis points on impact and returns to zero after three quarters. This finding is quite common in the literature on open-economy VARs. One example is Cushman and Zha (1997), who find that a monetary policy tightening leads to an immediate rise in the 3-month Treasury bill rate of less than five basis points. Similarly, using a different identification scheme Kim and Roubini (1995) estimate typical interest rate tightenings of less than 20 basis points for the G7 countries excluding the United States. These findings are in contrast with VAR-models that treat these countries as closed economies and do not include the foreign interest rate. For example, Gerlach and Smets (1995) estimate three-variable identified VARs for the G7 countries and find that over the period 1979-1993 a typical policy shock consists of an interest rate tightening of more than 40 basis points 13. Second, while the interest rate tightening is relatively small, the effect on the exchange rate is very strong. This is somewhat of a puzzle as the exchange rate response is much larger than one would expect on the basis of the uncovered interest rate parity theory. In addition, the exchange rate continues to appreciate for two quarters, which is in contrast with the overshooting hypothesis. The hump-shaped exchange rate response to a monetary policy shock was also noted by Eichenbaum and Evans (1995) for the United States. One possible explanation is that our identification procedure puts too much weight on the exchange rate innovations in the measurement of the monetary policy shock. Graph 3 plots the estimated impulse responses for 13 A likely explanation is that in this case both domestic and foreign policy shocks are included. -9- Graph 2 The effects of a monetary policy shock in Germany (Estimation period: 75:1-97:4) 0.16 0.16 0.00 0.08 -0.16 Real trade balan Real GDP 0.00 -0.08 -0.16 -0.32 -0.48 -0.64 -0.80 -0.24 -0.96 -0.32 -1.12 0 5 10 15 20 -0.00 0 5 10 15 20 0 5 10 15 20 0 5 10 15 20 0 5 10 15 20 0.75 -0.05 Terms of trade Consumer prices 0.50 -0.10 -0.15 -0.20 0.25 0.00 -0.25 -0.30 -0.25 0 5 10 15 20 0.25 0.32 0.20 0.16 0.00 Import prices Day-to-day rate 0.15 0.10 0.05 0.00 -0.16 -0.32 -0.48 -0.64 -0.05 -0.80 -0.10 -0.96 0 5 10 15 20 1.50 0.25 1.25 0.00 Nom. trade balan Real exchange ra 1.00 0.75 0.50 0.25 -0.25 -0.50 0.00 -0.25 -0.75 0 5 10 15 20 different assumed weights on the exchange rate. From the second column it is clear that halving the weight on the exchange rate, increases the size of the typical interest rate tightening, while it lowers the effect on the exchange rate making the overall picture more consistent with interest rate parity. Third, in closed economy VAR-models the typical output and inflation response is that output falls quite rapidly, while prices respond with a considerable lag and often not very significantly (Christiano et al (1998)). In contrast, in our open economy VAR, the direct price effect of an exchange rate appreciation on import prices is quite strong, leading to a much more rapid and significant negative response of consumer prices. In the next subsection we analyse this direct price channel by comparing the effects on various price indices. The crucial role of the direct - 10 - Graph 3 Sensitivity to different exchange rate weights Real GDP Omega=0.00 Omega=0.125 0.2 0.2 0.1 0.1 0.1 -0.0 -0.0 -0.0 -0.1 -0.1 -0.1 -0.2 -0.2 -0.2 -0.3 -0.3 0 5 10 15 CPI Interest rate 5 10 15 20 0.10 0 0.05 0.05 0.05 -0.00 -0.00 -0.05 -0.05 -0.05 -0.10 -0.10 -0.10 -0.15 -0.15 -0.15 -0.20 -0.20 -0.20 -0.25 -0.25 -0.30 -0.30 5 10 15 20 10 15 20 0.36 0.30 0.30 0.30 0.24 0.24 0.24 0.18 0.18 0.18 0.12 0.12 0.12 0.06 0.06 0.00 0.00 -0.06 -0.06 -0.12 10 15 20 5 10 15 20 1.50 1.50 1.25 1.25 1.25 1.00 1.00 1.00 0.75 0.75 0.75 0.50 0.50 0.50 0.25 0.25 0.25 0.00 0.00 0.00 -0.25 -0.25 -0.25 -0.50 -0.50 -0.50 0 5 10 15 20 0 5 10 15 20 0.25 0.00 0.00 0.00 -0.25 -0.25 -0.50 -0.50 -0.50 -0.75 -0.75 -0.75 -1.00 -1.00 5 10 15 20 5 10 15 20 0.8 0.8 0.6 0.6 0.6 0.4 0.4 0.4 0.2 0.2 0.2 0.0 0.0 0.0 -0.2 -0.2 -0.2 -0.4 0 5 10 15 20 15 20 0 5 10 15 20 0 5 10 15 20 0 5 10 15 20 10 15 20 -1.25 0 0.8 -0.4 10 -1.00 -1.25 0 5 0.25 -0.25 -1.25 0 -0.12 0 1.50 0.25 20 0.06 0.00 -0.06 5 15 -0.30 5 0.36 0 10 -0.25 0 0.36 -0.12 5 0.10 -0.00 0 Exchange rate -0.4 0 20 0.10 Trade balance -0.3 -0.4 -0.4 Terms of trade Omega=0.25 0.2 -0.4 0 5 10 15 20 0 5 exchange rate channel in explaining these results can also be seen from comparing the estimated impulse responses with those obtained from assuming a zero weight on the exchange rate innovation in the measured monetary policy shock (the left-hand column of Graph 3). Without a positive exchange rate response prices fall much less significantly. Also note that, as in Grilli and Roubini (1995), this identification scheme leads to an exchange rate puzzle. The right-hand panel of Graph 2 shows the effects of the policy tightening on the real and nominal trade balance and the terms of trade. As import prices respond much stronger to the exchange rate appreciation than export prices, the terms of trade improves significantly. This relative price effect leads to an improvement in the nominal trade balance. However, the real appreciation of the exchange rate also has a strong and significant negative impact on real net exports. Overall, this quantity effect dominates the valuation effect, so that the nominal trade balance deteriorates on - 11 - Graph 4 The ordering of the trade balance and the J-curve effect Real trade balance Base case Reverse ordering 0.16 0.16 0.00 0.00 -0.16 -0.16 -0.32 -0.32 -0.48 -0.48 -0.64 -0.64 -0.80 -0.80 -0.96 -0.96 -1.12 -1.12 Terms of trade 0 5 10 15 1.0 1.0 0.8 0.8 0.6 0.6 0.4 0.4 0.2 0.2 0.0 0.0 -0.2 -0.2 0 Import prices 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 -0.4 -0.4 5 10 15 0 20 0.50 0.50 0.25 0.25 0.00 0.00 -0.25 -0.25 -0.50 -0.50 -0.75 -0.75 5 10 15 20 -1.00 -1.00 -1.25 -1.25 0 Nom. trade balance 0 20 5 10 15 20 0.50 0.50 0.25 0.25 0.00 0.00 -0.25 -0.25 -0.50 -0.50 0 5 10 15 20 0 5 10 15 20 -0.75 -0.75 0 5 10 15 20 impact. Thus, in contrast to Cushman and Zha (1997) for Canada we do not find evidence of a Jcurve effect for Germany. Of course, this finding depends in part on the ordering of variables in the VAR. If we assume that monetary policy has no immediate impact on net export volumes, then one can get a J-curve effect as shown in Graph 4. 1.4 Extensions In this section we analyse the effects of the policy shock on alternative price indices and the components of GDP by including these as a tenth variable in the estimated VAR system. The lefthand panel of Graph 5 summarises the effects on various price indices. The strongest effect of the monetary policy tightening is on the prices of tradable goods. Import prices fall on impact by about 30 basis points and continue to fall afterwards to a maximum of 64 basis points below - 12 - -0.00 0.16 -0.05 0.08 -0.10 Real GDP Consumer prices Graph 5 Extended VAR results: effects of a policy shock -0.15 -0.20 -0.25 -0.32 5 10 15 20 0 0.10 -0.0 0.05 -0.2 -0.05 -0.10 -0.15 10 15 20 -0.6 -0.8 -1.0 -1.2 -0.20 -1.4 -0.25 -1.6 0 5 10 15 20 0 0.32 0.32 0.16 0.16 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 0.00 0.00 -0.16 -0.16 Imports Import prices 5 -0.4 -0.00 Exports Export prices 0 -0.32 -0.48 -0.64 -0.32 -0.48 -0.64 -0.80 -0.80 -0.96 -0.96 -1.12 0 5 10 15 20 0 1.5 0.12 1.0 Domestic demand 0.18 0.06 GDP deflator -0.16 -0.24 -0.30 0.00 -0.06 -0.12 -0.18 -0.24 -0.30 5 10 15 20 0.5 0.0 -0.5 -1.0 -1.5 -2.0 0 5 10 15 20 0 0.4 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 0.08 Output per man-hour 0.3 0.2 0.1 Earnings 0.00 -0.08 -0.0 -0.1 -0.2 -0.3 -0.4 -0.5 0.00 -0.08 -0.16 -0.24 -0.32 -0.40 -0.48 -0.56 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 0 5 10 15 20 baseline. Export prices also fall significantly but only after three quarters and by a maximum of only 15 basis points. As noted before, the net impact is a significant improvement of the terms of trade. As the consumer price index contains a significant share of imported goods, it also falls significantly by 10 to 15 basis points in the first three quarters. Domestic prices on the other hand do not fall on impact. In fact both the GDP deflator and nominal earnings rise in the first two quarters after the monetary policy tightening, before falling significantly following the creation of a negative output gap. The right-hand panel of Graph 5 gives the effects of a policy tightening on various components of real GDP. Due to the strong real appreciation of the DM, exports fall significantly following the - 13 - policy tightening. In contrast, imports only start falling when output falls after about two quarters. As a result, the real trade balance deteriorates very significantly putting a drag on output demand. The effect on domestic demand mirrors the development in domestic prices. Domestic demand actually rises following the tightening, before falling significantly below baseline after about a year. This increase in demand is visible in both consumption and investment. One potential explanation is that the strong terms-of-trade improvement has a temporary positive effect on both profits and wages boosting consumption and investment. Another possible explanation is that the real appreciation creates positive wealth effects as Germany was a net foreign creditor over the sample period. A third possible explanation is a misspecification of the policy shocks. If exchange rate shocks also capture expected positive demand shocks, then our identification procedure may result in a temporary rise in demand following a policy tightening. Finally, the lower right-hand graph shows that following a policy tightening productivity falls significantly in line with the fall in output. This suggests that there is significant labour hoarding in response to a fall in aggregate demand. 1.5 Summary of the empirical results Before continuing with the second part of the paper in which we discuss a DGE model for a semismall open economy such as Germany, it is useful to review the main results of the empirical analysis that we want the CGE model to reproduce. First, the interest rate and the exchange rate channel have different effects on the various components of GDP. While a rise in interest rates mainly affects the interest-rate-sensitive components of domestic demand, the associated appreciation of the exchange rate has its most important effect on net exports through relative price effects. As a result the interest rate channel leads to an improvement of the trade balance, while the exchange rate channel leads to a deterioration in the trade balance. Second, the exchange rate has important direct effects on the prices of tradable goods, in particular import prices, making the pass-through of policy to prices much more direct than in closed-economy models. - 14 - 2 THE MTM IN A DGE MODEL OF A SEMI-SMALL OPEN ECONOMY 2.1 A DGE model for a semi-small open economy In this section a small general equilibrium model for an open economy with nominal rigidities is presented. The model is a version of the one considered in Kollman (1997 and 1998) and features monopolistic competition in both goods and labour markets. The economy produces a good that is an imperfect substitute for a foreign imported good. The economy also imports a third good, ’energy’, that is used in fixed proportions in the production process. Nominal prices and wages are sticky and determined through overlapping price and wage contracts à la Calvo (1983). Money is introduced through the money-in-the-utility-function approach. Using this model, we discuss the different channels of the monetary transmission mechanism in an open economy. As in a closed-economy model, the real interest rate affects the intertemporal decisions of households and firms. In addition, the associated change in the exchange rate affects the price level directly through the import price of final goods and indirectly through the cost of imported energy. Finally, the exchange rate also affects output and aggregate demand through relative price and wealth effects. In order to allow for a direct comparison of the theoretical results with the empirical VAR results, monetary policy shocks enter the model directly through an interest rate reaction function, instead of through the money supply equation. As the model does include a well-defined money-demand equation, money becomes endogenous. In the impulse response functions of Graph 6 and 7 we plot the money stock that is consistent with this reaction function 14. Except in the market of exportable goods in which the economy faces a downward sloping demand curve, the economy considered in this model is assumed to be small. As a result, the world variables, and in particular the world interest rate, are considered to be exogenous. With infinite-lived agents and standard utility functions this creates the well-known problem of explosive solution paths for net foreign assets whenever shocks drive the domestic interest rate away from the foreign interest rate. One commonly used solution is to assume finite-lived agents as in Blanchard (1985). In this paper, we take a somewhat different approach by introducing net 14 Traditionally, monetary general equilibrium models of this kind have had difficulties producing a strong liquidity effect. In our model, we get a strong liquidity effect by assuming a small consumption elasticity of money demand. In addition, because of sticky prices, the expected inflation effect is also limited. - 15 - foreign assets in the utility function. This gives rise to a well-defined demand for net foreign assets and introduces a risk-premium in the uncovered interest rate parity condition. In what follows we present a sketch of the main building blocks of the open-economy model. A full description can be found in Wouters (1998). Wouters (1998) also presents the response of the economy to alternative shocks such as a productivity shock, a money demand shock, a foreign demand shock, a public expenditures shock and an energy and foreign price shock. In addition, he performs stochastic simulations in the face of productivity and money shocks to examine whether the model can generate statistics that are close to the historical statistics for Germany. 2.1.1 Technologies and firms The country produces a single final good and a continuum of intermediate goods indexed by j where j is distributed on the unit interval ( j ∈ [0,1]). The final good sector is perfectly competitive and uses as inputs domestic and imported intermediate goods. The final good is used for consumption by the representative household and the government and for investment by the firms that rent out capital. There is monopolistic competition in the markets for intermediate goods: each intermediate good is produced by a single firm. Final good sector The final good is produced using domestic and imported intermediate goods in the following CES technology: [( Yt = y tH ) 1 /(1+γ ) ( ) + y tF ] 1 /(1+γ ) (1+γ ) (6) where γ is a parameter and ytH and y tF are indices of domestic and imported intermediate goods. ytH can be written as: y H t 1 = ∫ y tH, j 0 ( ) 1 /(1+υ ) dj 1+υ (7) where υ is a parameter, and y tH, j denotes the quantity of domestic intermediate good of type j that is used in final goods production, at date t. - 16 - The cost minimisation conditions in the final goods sector can be written as: y Hj ,t p Hj ,t = H p t ytH pH = t Pt − − 1+υ υ y tH and (8) 1+γ γ Yt (9) where p Hj ,t is the price of the home intermediate good j , ptH is the price of the domestically produced composite intermediate good and Pt is the price of the final good. Perfect competition in the final goods market implies that the latter two can be written as: 1 −1 / υ p = ∫ (ptH, j ) dj 0 −υ H t [( Pt = ptH ) −1 / γ (10) ( ) + ptF ] −1 / γ −γ (11) Intermediate goods producers Each intermediate good j is produced by a firm j using the following technology: y j ,t ≤ (1 + ie ) AK αj ,t H 1j−,tα , (12) where y j ,t (1 + ie ) is the firm’s value-added, A is a productivity parameter, K j ,t is the physical capital stock and H j ,t is an index of different types of labor used by the firm. This index is given by: H j ,t 1 1+1φ = ∫ h j ,τ ,t dτ 0 1+φ , (13) where φ is a parameter and h j ,τ ,t is the quantity of type τ labor used by firm j at time t. Energy is used in a fixed proportion, ie , of value-added. - 17 - Cost minimisation implies: h j ,τ ,t w = τ ,t Wt Wt H j ,t Rt K j ,t = − (1+φ ) / φ H j ,t and 1−α α (14) (15) where Rt is the rental rate of capital, wτ ,t is the wage rate for type τ labor and Wt is an aggregate wage index, given by: 1 −1 / φ Wt = ∫ (wτ ,t ) dτ 0 −φ (16) Equation (15) implies that the capital-labour ratio will be identical across intermediate goods producers and equal to the aggregate capital-labour ratio. As the production function exhibits constants returns to scale, the firm’s average and marginal cost are equal and given by: MC t = AC t = Rt i Wt i + s t p te e = + s t pte e K H 1 + ie (1 + ie ) Ft 1 + ie (1 + ie ) Ft i 1 = Wt1−α Rtα (α −α (1 − α ) −(1−α ) ) + s t p te e A 1 + ie (17) where Ft K and Ft H are respectively the marginal value-added of capital and labour, st is the nominal exchange rate and pte is the foreign-currency price of energy. This implies that also the marginal cost is independent of the intermediate good produced. Total demand for firm j ’s good equals the sum of domestic and foreign demand: y j ,t = y Hj ,t + x Hj ,t , (18) where export demand for good j is in turn given by: x Hj ,t p Hj ,t = H p t − 1+υ υ xtH , (19) - 18 - and xtH is aggregate world demand for the country’s exports. Using equations (8), (18) and (19), nominal profits of firm j are then given by: π j ,t = ( p Hj ,t p Hj ,t − MC t ) H p t − 1+υ υ (y H t + xtH ) (20) Each firm j has market power in the market for its own good and maximises expected profits using a discount rate ( βρ t ) which is consistent with the pricing kernel for nominal returns used by the country’s shareholders-households: ρ t + k Vt C+ k 1 = C , where Vt C is the marginal utility of Vt Pt + k consumption at time t (see section 2.1.2). The model of price determination, inspired by Calvo (1983), assumes that firms are not allowed to change their prices unless they receive a random 'price-change signal'. The probability that a given price can be changed in any particular period is constant ( 1 − ς ) and determines the fraction of all prices that are changed in each period. A producer who is 'allowed' to set a new price at time t will maximise the following intertemporal profit function: ∞ ∑ς k =0 k β k Et ρ t + k π t + k (21) Profit maximisation implies the following mark-up equation: ∞ ∑β ς i p H j ,t = (1 + υ ) i =0 i ∞ ∑β ς i i =0 1+υ υ ( ) E t ρ t +i p i H t +i y t +i MCt +i 1+υ υ ( ) Et ρ t +i ptH+i (22) yt +i Equation (22) shows that the price set by firm j , at time t, is a function of expected future marginal costs. The price will be a mark-up over these weighted marginal costs. If prices are perfectly flexible ( ς = 0 ), the mark-up will be constant and equal to 1 + υ . With sticky prices the mark-up becomes variable over time when the economy is hit by exogenous shocks. A positive demand shock lowers the mark-up and stimulates employment, investment and real output. Through this last channel the model obtains a Keynesian character. - 19 - The definition of the price index in equation (10) implies that its law of motion is given by: (p ) H −1 / υ t ( ) = ς ptH−1 −1 / υ ( ) + (1 − ς ) p Hj ,t −1 / υ (23) Finally, using equations (8), (12), (15), (18) and (19) the aggregate demand for capital is given by: αWt yt K t = ∫ K j ,t dj = (1 + ie ) A (1 − α ) Rt 0 1 1−α ptH H pt − 1+ν ν , (24) where ptH is determined by the following law of motion: 1+υ H − υ t (p ) ( ) = ς ptH−1 − 1+υ υ ( ) + (1 − ς ) p Hj ,t − 1+υ υ (25) Capital rental firms Physical capital is a homogenous factor of production that is owned by firms that rent capital to producers of intermediate goods. Capital accumulation is given by: K t +1 + 2 ψ (K t +1 − K t ) = K t (1 − τ ) + I t , 2 Kt (26) where ψ is an adjustment-cost parameter, τ is the depreciation rate and I t is gross investment. Capital rental firms maximise the following profit function: ∞ ∑β k =0 k Et ρ t + k ( Rt + k K t + k − Pt + k I t + k ) , (27) giving rise to the following first-order condition for capital: R Qt = Et βρ t +1 p t +1 Qt +1 − τ + t +1 , p t +1 (28) where Tobin’s Q is given by: Qt = 1 + ψ K t +1 − K t Kt (29) - 20 - 2.1.2 The household sector There is a continuum of households indicated by index τ . Households differ in that they supply a differentiated type of labour. So each household has a monopoly power over the supply of its labour. Each household τ maximises a utility function that is separable in its inputs : ( ) 1 Vt = C tτ 1−σ τ 1−σ 1 M tτ +κ 1 − Γ Pt 1− Γ 1 s t Ftτ +ι 1 − µ Pt 1− µ − lτ ,t (30) Utility depends on consumption of goods, Ctτ , real cash balances, M tτ / Pt , real net foreign assets, st Ftτ / Pt and labour supply lτ ,t . In the benchmark parameterisation the utility function is linear in leisure. Together with the assumption of indivisible labour, this yields an infinite macroeconomic elasticity of labour supply. Households act as price-setters in the labour market. Household τ ’s intertemporal utility function is given by: ∞ Et ∑ β jVtτ+ i , (31) k =0 where β is the discount factor. Households hold money balances M t , domestic government bonds Bt , foreign interest bearing bonds Ft and domestic equity Vt . Bonds are one-period bonds with price bt for the domestic bonds and f t for the foreign bonds. The budget constraint faced by the household is then given by: w Bτ Fτ Vτ Mτ Bτ Fτ Vτ M tτ + bt t + st f t t + d t t = t −1 + t −1 + s t t −1 + d t t −1 + τ ,t lτ ,t − C tτ − Ttτ Pt Pt Pt Pt Pt Pt Pt Pt Pt (32) Households maximise the objective function (31) subject to the intertemporal budget constraint (32) and the demand for their labour given in equation (14). As in the goods market, we assume that wages can only be changed after some random 'wage-change signal' is received. The probability that a particular household can change its nominal wage in period t is constant and equal to 1 − ξ . A household τ which receives such a signal in period t, will thus set a new nominal wage wτ taking into account the probability that it remains unchanged in the future. - 21 - This maximisation yields the following first-order conditions for consumption, wealth allocation and wage-setting, where λt is the Lagrange multiplier, it is the nominal rate of return on domestic bonds ( 1 + it = 1 bt ) and itF is the foreign-currency rate of return on foreign bonds ( 1 + itF = 1 f t ): c V t = λt (33) λt +1 Vt MIP λt βE t = + pt pt pt +1 (34) λ λ βEt t +1 (1 + it ) = t pt +1 pt (35) λ t +1 st +1 Vt sF P λt F βE t (1 + it ) + = pt pt pt +1 s t (36) λ d λ βEt t +1 t +1 = t pt +1 d t pt (37) ∞ wτ ,t = (1 + φ ) 1+φ φ t +i Et ∑ β ξ W i i =0 ∞ i 1+φ φ t +i E t ∑ β i ξ iW i =0 H t +i VC H t +i t +i Pt +i (38) Combining equations (33) and (35) gives the usual first-order condition for consumption growth. Equations (33), (34) and (35) together result in a money demand equation. Real money holdings depend on consumption, with an elasticity that is possibly smaller than one, and the velocity of money depends positively on the interest rate. Equations (35) and (36) give the uncovered interest rate parity condition for nominal exchange rate determination augmented with a risk premium reflecting the household’s preference for net foreign assets. Equation (37) shows that the expected holding return on equity equals the expected one-period interest rate under certainty equivalence. - 22 - Note that equations (33) to (37) have been written in aggregate terms, i.e. the household’s subscript τ has been deleted. Under the assumption that, first, markets are complete and thus consumption growth across households is perfectly correlated and, second, each household starts with the same initial wealth, consumption and asset allocation will be the identical across households (Erceg, 1997). Finally, equation (38) shows that the nominal wage at time t of a household τ that is allowed to change its wage is set so that the present value of the marginal return to working is a mark-up over the present value of marginal cost (the subjective cost of working) 15 . When wages are perfectly flexible ( ξ = 0 ), the real wage will be constant mark-up over the ratio of the marginal disutility of labour and the marginal utility of an additional unit of consumption. Given equation (16), the law of motion of the aggregate wage index is given by: (Wt )−1 / φ = ξ (Wt −1 ) −1 / φ + (1 − ξ )(wτ ,t ) −1 / φ (39) 2.1.3 The government sector For completeness and to get a realistic representation of the final demand components, we also introduce a government sector. However, by assuming that all taxes are lump-sum and that the households have infinite horizons, the behaviour of the private sector will not be affected. The government has to satisfy the following budget restriction: bt Bt = Bt −1 + − , Gt T t pt pt (40) which states that the primary deficit, G − T , and the debt service has to be financed by the emission of new public debt Bt at the current price bt . To rule out explosive debt dynamics, the following endogenous tax behaviour is assumed: B B0 , Tt = g t − p p t t (41) where the reaction coefficient g is greater than the real interest rate ( g > i − π ). This ensures a 15 Standard RBC models typically assume an infinite supply elasticity of labour to get realistic business cycle properties for the behaviour of real wages and employment. An infinite supply elasticity limits the increase of marginal costs and prices following an expansion of output in a model with sticky prices, which helps generating real persistence of monetary shocks. The introduction of nominal wage rigidity in this model makes the simulation outcomes less dependent on this assumption as wages and the marginal cost become less sensitive to output shocks at least over the short term. - 23 - stable public debt at the long term objective B o . 2.1.4 The balance of payments and foreign demand The accumulation of foreign assets Ft is determined by the current account relation: s t f t Ft s t Ft −1 ptH H ptF F pte = + xt − s t y t − st IEt Pt Pt Pt Pt Pt (42) The net foreign asset position depends on the interest payments on existing net foreign assets and the trade balance, which is given by the difference between the real value of exports, X tH , and the real value of imports of final goods, Yt F , and energy inputs, IE t . Energy acts only as an input in the production process: IEt = ie yt 1 + ie (43) The demand for exports is a function of the terms of trade ( st ptF / ptH ) and demand in the rest of the world ( ROWt ): x H t pH = t F st p t −ϑ ROWt (44) 2.1.5 Market equilibrium The final goods market is in equilibrium if production equals demand by consumers, the government and the capital accumulation firms: Yt = C t + Gt + I t (45) The capital rental market is in equilibrium when the demand for capital by the intermediate goods producers equals the supply by the capital rental firms. The labour market is in equilibrium if firms’ demand for labour equals households’ supply. Monetary policy is described by a simple reaction function for the interest rate with stochastic shocks, ε tmp : it = g (it −1 , y t y t − 4 , pt pt − 4 , ε tmp ) (46) - 24 - In order to maintain money market equilibrium, the money supply adjusts endogenously to meet the money demand at those interest rates. In the capital market, equilibrium means that the government debt is held by domestic investors at the market interest rate it (assuming that the country is in a net foreign asset position), and that the net foreign assets are held by investors at the going interest and exchange rates (including a risk premium). 2.1.6 The parameterisation of the model In the benchmark model the following values for the parameters are assumed. The share of capital α in production is set at 0.35 and the parameter for the cost of capital adjustment is 10. In the utility function, we set the coefficient of relative risk aversion σ equal to 2, the coefficient on money balances, Γ , equal to 10, and the coefficient on net foreign assets, µ , equal to 100. The choice of the coefficient of relative risk aversion and the consumption elasticity of the money demand equation guarantees that a monetary expansion will result in a negative liquidity effect on interest rates. The coefficient on net foreign assets is chosen so that in the benchmark case uncovered interest rate parity almost holds. The structure of final demand is given by the following steady-state assumptions: final import/gdp = 0.15, energy import/gdp = 0.10, export/gdp = 0.25, consumption/gdp = 0.58, investment/gdp = 0.22, government expenditures/gdp = 0.20 and net foreign assets/gdp = 0.4. The discount factor is set at 0.99, the rate of depreciation is 0.02 and the capital/gdp ratio is 11.0. The import and export price elasticities are respectively set at 0.33 and 0.90. This corresponds to empirical estimates in export and import equations for Germany as, for example, reported in Bundesbank (1998). The long run coefficients on inflation and growth in the interest rate reaction function correspond with those proposed by Taylor (1983). The coefficient on the lagged interest rate equals 0.85.16 In order to get a specification in which monetary expansions result in persistent effects on real growth and inflation, we set the probability of price and wage changes equal to 0.2, which falls within the acceptable region of empirical estimates. In this case the average duration for a fixed price and wage contract is equal to (1-0.2)/0.2 or four quarters, which is comparable with one- 16 See Clarida et al (1997) and Peersman and Smets (1998) for estimates of the Bundesbank’s monetary policy reaction function. - 25 - year Taylor-type contracts. In similar models, King and Watson (1996) use a value of 0.1, whereas Galí and Gertler (1998) estimate a value of 0.2 in an empirical model for the US. In general, the parameters reflect the economic structure of a large open economy such as Germany17. The model is linearized around the steady state and solved numerically using the Troll software. 2.2 The effects of a monetary policy tightening 2.2.1 The benchmark results Graph 6 plots the impulse response functions to a 100 basis points shock in the interest rate. Due to the interest rate smoothing in the central bank’s reaction function and the response to output growth and inflation, the interest rate gradually falls back to baseline after about five quarters. Money supply responds negatively on impact as a result of the decline in money demand following the interest rate increase. The exchange rate shows a strong appreciation following the restrictive monetary shock. As in Dornbusch (1976), Chari et al. (1996) and Kollman (1997) the exchange rate overshoots its long run equilibrium level, so that the model is potentially able to explain the high volatility of nominal and real exchange rates. In line with the appreciation of the exchange rate, the price of imported energy and imported final goods drops quite dramatically. As a result, the price of final expenditures (consumer prices) falls more strongly and quicker than the price of domestically produced goods, wages and the value added deflator. In fact, when we include backward-looking behaviour in the price and wage equations (not reported), we can get a situation in which the value-added deflator increases before falling in line with the other prices, which is what we found in the VAR results for Germany as reported in Graph 5. In sum, the relative ranking of the various price effects in the theoretical model is very similar to that in the empirical VAR results for Germany. Also in line with the empirical results, the terms of trade improves considerably as import prices react much more strongly than export prices which are partially determined by slowly changing domestic costs. This relative price effect results in an immediate and strong fall in exports, which is consistent with the empirical findings of Section 1. Imports first decrease following the 17 Wouters (1998) compares the statistics of an extensive list of real and nominal variables generated by stochastic simulations of the model with productivity and monetary supply shocks with the historically observed statistics of these variables in Germany. - 26 - Graph 6 The MTM in a DGE-model for a semi-small open economy Benchmark case Interest rate Money Output Exchange rate 2.5 2 1.5 1 0.5 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 -0.5 -1 -1.5 Consumer prices Domestic-goods prices Wages Value-added defl. 1.0000 0.5000 0.0000 -0.5000 -1.0000 -1.5000 -2.0000 -2.5000 -3.0000 -3.5000 -4.0000 -4.5000 Consumption Investment 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Exports Imports Total imports 0.5000 Import prices 0.0000 0.5000 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 0.0000 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 -0.5000 -1.0000 -0.5000 -1.0000 -1.5000 -1.5000 -2.0000 -2.5000 -2.0000 Interest rate Inflation Real interest rate Expected appreciation Net-exports Trade balance Terms-of-trade 2.0000 1.5 1.5000 1 1.0000 0.5 0 -0.5 0.5000 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 0.0000 -1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 -1.5 -0.5000 -2 -1.0000 Average mark-up Marg. Prod. of Labour Producer wage Energy cost Output Capital Labour 0.0000 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 1.0000 -0.5000 0.8000 0.6000 -1.0000 0.4000 -1.5000 0.2000 -0.4000 21 19 17 15 13 9 7 5 11 -0.2000 3 1 0.0000 -2.0000 -2.5000 - 27 - contraction of domestic demand, but then start increasing as the relative price effect dominates the demand effect. The latter pattern does not correspond to the empirical impulse response of imports shown in Graph 5. Because the empirical output effect of the monetary policy tightening is much more persistent, the effect on imports actually never turns positive in the empirical response functions. In both the theoretical and empirical response functions, net exports fall quite significantly. However, in contrast to the empirical results, the positive terms-of-trade effect dominates the negative volume-effect in the determination of the nominal trade balance during the first four quarters. Only after two years the nominal trade balance becomes negative. The trade balance therefore follows a typical J-curve effect in response to a monetary policy shock. Preliminary analysis suggests that this behaviour of the trade balance is quite robust to changes in model assumptions and parameter values including the import and export price elasticities. In sum, the DGE model appears to capture the open-economy aspects of the monetary transmission mechanism in a large open economy quite well. The failure to capture the dynamics of the transmission process of a monetary policy shock has more to do with the lags and the persistence in the effects of a policy shock on output and inflation. As in most of the DGE literature, the maximum effect of policy on output and inflation is contemporaneous, which is clearly in contradiction with most of the empirical literature on the MTM (Christiano et al. (1998)) 18. Another counterfactual result is the fact that labour employed falls immediately with the fall in demand. Given the assumed Cobb-Douglas production function, this gives rise to an immediate increase in labour productivity, which contradicts the fall in output per hour shown in Graph 5. 2.2.2 Some sensitivity analysis Graph 7 compares the effects of a policy shock in the benchmark model with those in a more closed economy, in which the share of exports and imports in GDP is halved compared to the benchmark case. Due to the lower import content the negative effect of a policy shock on prices is 18 Much of the current research on DGE models focuses on this issue. For example, Estrella and Fuhrer (1998) discuss the ability of the Calvo model of price setting to match the inflation persistence in the data. Various extensions of the basic DGE model have been proposed to increase the persistence of the output effects. For example, Jeanne (1998) shows how the response of output to monetary shocks in a model with nominal friction in the goods market becomes large and persistent if it is amplified by real-wage rigidity in the labour market. Fuhrer (1998) illustrate the role of habit formation in the consumption decision to get a gradual and hump-shaped response of real variables to monetary policy shocks. Rotemberg and Woodford (1997) assume that real decisions are made two periods in advance to get a realistic delay in the response of the economy to monetary disturbances. - 28 - Graph 7 The effect of a policy shock in a more closed economy 27 25 23 21 19 17 15 13 9 11 -0.2000 7 0.0000 1 5 1.2 3 Output 1 Interest rate -0.4000 0.8 -0.6000 0.6 -0.8000 0.4 -1.0000 27 25 23 21 19 17 15 -0.2 13 9 11 7 5 -1.4000 3 -1.2000 0 -1.6000 Exchange rate Consumption 0.1000 2.5000 19 21 23 25 27 21 23 25 27 23 25 27 17 15 -0.2000 1.0000 -0.3000 0.5000 -0.4000 -0.5000 27 25 23 21 19 17 -0.6000 17 11 9 7 5 3 0.0000 -0.1000 1 27 25 23 21 19 17 15 13 11 9 7 5 3 1 0.0000 15 Net exports Prices 13 15 13 11 9 7 5 3 1 0.0000 -0.2000 -0.3000 -0.4000 -0.2000 -0.3000 -0.4000 -0.7000 -0.5000 -0.6000 -0.7000 -0.8000 -0.8000 -0.9000 -0.5000 -0.6000 Terms-of-trade Exports Imports 0.5000 2.00000 1.00000 -1.0000 0.50000 -1.5000 27 25 23 21 19 17 15 13 11 9 7 5 3 1 0.00000 -2.0000 21 19 17 15 11 9 5 1 -0.5000 3 0.0000 1.50000 7 -0.1000 19 1.5000 13 -0.1000 11 9 7 5 1 3 0.0000 2.0000 13 1 0.2 - 29 - reduced. Also the effect on net exports is less in absolute value. This is, however, mostly due to the less pronounced effect on imports. Exports themselves are hardly affected. Graph 8 shows the effect of introducing a more significant risk premium by lowering the coefficient, µ , on net foreign assets in the utility function from 100 to 2. In the latter case, the impulse response functions reveal a significant violation of the uncovered interest rate parity condition. Consistent with the empirical findings discussed above, the initial exchange rate appreciation is followed by a further appreciation before the exchange rate falls back to its longrun equilibrium. This result is due to the presence of a risk premium in the interest rate parity condition which is a function of the net foreign asset position (expressed in domestic currency). An appreciation of the domestic currency reduces the ratio of foreign assets to total wealth, thereby reducing the risk premium. As a result, investors accept a lower expected return on foreign assets. Equilibrium is achieved by a further appreciation of the domestic currency which allows for a relative rise in domestic interest rates. The persistent effect on the exchange rate gives rise to a much more persistent negative effect on net exports. However, this does not translate into a more persistent effect on output. As show in Graph 8, the effect on net exports is compensated by a less persistent effect on consumption. Finally, Graphs 9 and 10 compare the benchmark simulation with two alternative degrees of wage and price rigidity. In Graph 9 the alternative model is one in which prices are much more flexible ( ς = 0.8 ). In Graph 10 the alternative model is one in which wages are much more flexible ( ξ = 0.8 ). Graph 9 shows that higher price flexibility considerably reduces the output effects. Prices adjust quite rapidly to their new long-run level and the terms of trade is much less affected. As a result net exports fall much less. As shown in Graph 10, higher wage flexibility has qualitatively very similar effects. As in Erceg (1997), the main effect of wage rigidity is to make the output effects of a monetary policy tightening much more persistent. - 30 - Graph 8 The exchange rate channel and the risk premium 27 25 23 21 19 17 15 13 9 11 7 5 3 1 27 25 23 21 -1.2000 -0.2 19 -1.0000 0 17 -0.8000 0.2 15 -0.6000 0.4 13 -0.4000 0.6 9 0.8 11 -0.2000 7 0.0000 1 1 1.2 5 Output 3 Interest rate -1.4000 Exchange rate Consumption 0.2000 2.5000 0.1000 2.0000 21 23 25 27 23 25 27 23 25 27 17 15 21 -0.3000 19 -0.2000 0.5000 19 1.0000 13 -0.1000 11 9 7 5 1 3 0.0000 1.5000 -0.4000 27 25 23 21 19 17 15 13 11 9 7 5 3 1 0.0000 -0.5000 Net exports Prices 0.0000 17 15 13 11 9 7 5 3 -0.2000 1 27 25 23 21 19 17 15 13 11 9 7 5 3 1 0.0000 -0.2000 -0.4000 -0.6000 -0.4000 -0.8000 -0.6000 -1.0000 -0.8000 -1.2000 -1.4000 -1.0000 -1.6000 Exports Terms-of-trade Imports 1.0000 2.00000 0.5000 1.50000 -1.5000 27 25 23 21 19 17 15 13 11 9 7 5 3 1 0.00000 -2.0000 21 19 17 9 7 5 15 -1.0000 13 0.50000 11 -0.5000 3 1 0.0000 1.00000 - 31 - Graph 9 The MTM with higher price flexibility 27 25 23 21 19 27 25 23 21 -1.4000 Exchange rate 19 21 23 25 27 19 21 23 25 27 23 25 27 17 15 11 9 -0.1000 1.0000 7 0.0000 1.5000 5 0.1000 2.0000 1 2.5000 3 Consumption 13 17 15 13 9 11 7 5 3 1 19 -1.2000 -0.2 17 -1.0000 0 15 -0.8000 0.2 9 -0.6000 0.4 11 -0.4000 0.6 7 0.8 5 -0.2000 3 0.0000 1 1 1.2 13 Output Interest rate -0.2000 0.5000 -0.3000 27 25 23 21 19 17 -0.4000 -0.3000 -0.4000 -0.5000 -0.6000 -0.7000 -0.8000 -0.9000 17 11 9 7 5 3 0.0000 -0.1000 -0.2000 -0.3000 1 27 25 23 21 19 17 15 13 11 9 7 5 3 1 -0.4000 -0.5000 -0.6000 -0.7000 -0.8000 -0.9000 Terms-of-trade Exports Imports 0.5000 2.00000 1.00000 -1.0000 0.50000 -1.5000 27 25 23 21 19 17 15 13 11 9 7 5 3 1 0.00000 -2.0000 21 19 17 15 13 11 9 5 1 -0.5000 3 0.0000 1.50000 7 0.0000 -0.1000 -0.2000 15 Net exports Prices 13 15 13 11 9 7 5 3 1 0.0000 - 32 - Graph 10 The MTM with higher wage flexibility 23 25 27 25 27 25 27 25 27 21 23 23 23 19 21 21 27 25 23 21 19 17 15 13 9 11 7 5 3 -1.4000 Consumption Exchange rate 1.0000 17 15 13 9 7 -0.1000 5 0.0000 1.5000 1 2.0000 3 0.1000 2.5000 11 1 17 -1.2000 -0.2 19 -1.0000 0 19 -0.8000 0.2 15 -0.6000 0.4 13 -0.4000 0.6 9 0.8 11 -0.2000 7 0.0000 1 1 1.2 5 Output 3 Interest rate -0.2000 0.5000 -0.3000 27 25 23 21 19 17 -0.4000 17 11 9 7 5 3 0.0000 -0.1000 1 27 25 23 21 19 17 15 13 11 9 7 5 3 1 0.0000 -0.2000 -0.3000 -0.4000 -0.5000 -0.6000 -0.7000 -0.8000 -0.7000 -0.8000 -0.9000 -0.9000 Terms-of-trade Exports Imports 0.5000 2.00000 1.00000 -1.0000 0.50000 -1.5000 27 25 23 21 19 17 15 13 11 9 7 5 3 1 0.00000 -2.0000 21 19 17 15 13 11 9 5 1 -0.5000 3 0.0000 1.50000 7 -0.1000 -0.2000 -0.3000 -0.4000 -0.5000 -0.6000 15 Net exports Prices 13 15 13 11 9 7 5 3 1 0.0000 - 33 - CONCLUSIONS In this paper we focused on the effects of a monetary policy shock in a large open economy like Germany and the role of the exchange rate channel in the MTM in particular. Using an identified VAR-model we show that a monetary tightening leads to a strong and prolonged real appreciation of the DM exchange rate. This appreciation strengthens the effects of policy on prices through its direct impact on imported goods prices. It also has a strong and significant effect on net exports through the relative price effect. We then show that the estimated qualitative effects of a monetary policy tightening in Germany can be duplicated in a general equilibrium model for a semi-small open economy with sticky prices and wages that is calibrated to capture the main features of the German economy. - 34 - - 35 - REFERENCES Ball, L., 1998, ’Policy rules for open economies’, Research Discussion Paper 9703, Reserve Bank of Australia. Barran, F., V. Coudert and B. Mojon, 1997, ’The transmission of monetary policy in the European countries’, Document de travail CEPII 96-03. Backus, D., P. Kehoe and F. Kydland, 1995, ’International business cycles: theory and evidence’, in: Cooley, T.F. (ed), Frontiers of business cycle research, Princeton University Press. Bernanke, B. and I. Mihov, 1997, ’What does the Bundesbank target?’, European Economic Review, 41, 1025-1054 Bernanke, B. and I. Mihov, 1998, ’Measuring monetary policy’, Quarterly Journal of Economics, 113(3), 869-903. Bharucha, N. and C. Kent, 1998, ’Inflation targeting in a small open economy’, Research Discussion Paper 9807, Reserve Bank of Australia. Blanchard, O., 1985, ’Debt, deficits, and finite Horizons’, Journal of Political Economy, 93(2), 223-247. Bundesbank, 1998, ’The indicator quality of different definitions of the real external value of the Deutsche Mark’, Deutsche Bundesbank, Monthly Report, November 1998, 39-52. Calvo, G., 1983, ’Staggered prices in a utility maximising framework’, Journal of Monetary Economics, 12, 383-398. Chari, V.V., P.J. Kehoe, and E.R. McGratten, 1996, ’Monetary shocks and real exchange rates in sticky price models of international business cycles’, NBER Working Paper 5876. Christiano, L.J., M. Eichenbaum, and C.L. Evans, 1997, ’Sticky price and limited participation models of money: a comparison’, European Economic Review, 41, 1201-1249. Christiano, L.J., M. Eichenbaum, and C.L. Evans, 1998, ’Monetary policy shocks: what have we learned and to what end?’, NBER Working Paper 6400. Clarida, R. and M. Gertler, 1997, ’How the Bundesbank conducts monetary policy’, in Romer, D. and C. Romer (eds), Reducing inflation: motivation and strategy, Chicago, University of Chicago Press. Conway, P., A. Drew, B. Hunt and A. Scott, 1998, ’Exchange rate effects and inflation targeting in a small open economy: a stochastic analysis using FPS’, in BIS (1998), Topics in monetary policy modelling, Conference Papers 6. Cushman, D. and T. Zha, 1997, ’Identifying monetary policy in a small open economy under flexible exchange rates’, Journal of Monetary Economics, 39, 433-448. - 36 - Dornbush, R., 1976, ’Expectations and exchange rate dynamics’, Journal of Political Economy, 84, 1161-76. Eichenbaum, M. and C. Evans, 1995, ’Some empirical evidence on the effects of shocks to monetary policy on exchange rates’, Quarterly Journal of Economics, November 1995, 975-1009. Eika, K.H., N. Ericsson, and R. Nymoen, 1997, ’Understanding a Monetary Conditions Index’, forthcoming in International Finance Discussion Papers, Board of Governors of the Federal Reserve System, Washington. Erceg, C.J., 1997, ’Nominal wage rigidities and the propagation of monetary disturbances’, International Finance Discussion Papers No. 590, Board of Governors of the Federal Reserve System, Washington. Estrella, A. and J.C. Fuhrer, 1998, ’Dynamic inconsistencies: counterfactual implications of a class of rational expectations models’, NBER Universities Research Conference, Cambridge. Fuhrer, J.C., 1998, ’An optimizing model for monetary policy analysis: can habit formation help?’, Working Paper 98(1), Federal Reserve Bank of Boston. Gali, J. and Gertler M., 1988, ’Inflation dynamics: a structural econometric analysis’, Conference paper, Gerzensee, October 1998. Gerlach, S. and F. Smets, 1995, ’The monetary transmission mechanism: evidence from the G7 countries’, CEPR Discussion Paper 1219. Gerlach, S. and F. Smets, 1998, ’MCIs and monetary policy’, forthcoming in European Economic Review. Grilli, V. and N. Roubini, 1995, ’Liquidity and exchange rates: puzzling evidence from the G-7 economies’, Working Paper, Yale University. International Monetary Fund, IMF, 1996, World Economic Outlook, June. Jeanne, O., 1998, ’Generating real persistent effects of monetary shocks: How much nominal rigidity do we really need?’, European Economic Review, 42, 1009-1032. Kim, S. and N. Roubini, 1995, ’Liquidity and exchange rates: a structural VAR approach’, mimeo. King, R.G. and M.W. Watson, 1996, ’Money, prices, interest rates and the business cycle’, The Review of Economics and Statistics, 78(1),35-53. Kollman, R., 1997, ’The exchange rate in a dynamic-optimizing current account model with nominal rigidities : a quantitative investigation’, IMF Working Paper, January 1997. Kollman, R., 1998, ’Explaining international comovements of output and asset returns, and the variability of exchange rates : the role of money and nominal rigidities’, Document ERUDITE No. 98-05. - 37 - Mojon, B., 1998, ’What did French monetary policy do since the last realignment of the Franc?’, mimeo. Organisation for Economic Co-operation and Development, OECD, 1996, Economic Outlook, June. Rotemberg, J.J. and M. Woodford, 1997, ’An optimization-based econometric framework for the evaluation of monetary policy’, NBER Macroeconomics Annual, MIT Press Cambridge, 297346. Roubini, N. and Grilli V., 1995 , ’Liquidity models in open economies: theory and empirical evidence’, NBER Working paper 5313. Shioji, E., 1998, ’Spanish monetary policy: a structural VAR analysis’, Economics Working Paper 215, Universitat Pompeu Fabra. Sims, C.A., 1980, ’Macroeconomics and reality’, Econometrica, 48(1), 1-48. Sims, C.A. and Zha T.A., 1998, ’Does monetary policy generate recessions?’ Federal Reserve Bank of Atlanta, Working Paper 98-12. Smets, F., 1997, ’Measuring monetary policy shocks in France, Germany and Italy: the role of the exchange rate’, Swiss Journal of Economics and Statistics 133(3), 597-616. Svensson, L., 1998, ’Open-Economy Inflation Targeting’, mimeo, Jan 1998. Svensson, L., 1998, ’Inflation targeting as a monetary policy rule’, mimeo, March. Wouters, R., 1998, ’The transmission mechanism of monetary policy in a general equilibrium model for an open economy with sticky nominal prices and wages’, mimeo. - 39 - COMMENTS ON ‘THE EXCHANGE RATE AND THE MONETARY TRANSMISSION MECHANISM IN GERMANY’ BY FRANK SMETS AND RAF WOUTERS Antti Ripatti In their paper “The exchange rate and the monetary transmission mechanism in Germany” Frank Smets and Raf Wouters (hereafter SW) discuss an important aspect of the monetary transmission mechanism in an open economy. By representing a set of stylized facts using VAR and drawing on the German data and by deriving a corresponding dynamic stochastic general equilibrium (DGE) model, they make a significant contribution to better understanding the functioning of monetary policy in an open economy framework. The subject is a very challenging one since open economy issues add to the complexity of the identification of the empirical model and the general equilibrium framework. The work is pioneering in many respects: there are not many examples of measuring monetary policy shocks where the central bank has to take the exchange rate channel into account. The complexity of the DGE modelling easily explodes as the number of sectors in the economy increases. Despite of the notable progress made by SW, there is still room for some, hopefully, minor criticism. 1 The VAR, ‘monetary policy shock’ and the (near) unit roots The study has two parts. The first part contains the impulse responses to ‘monetary policy shocks’ from the VAR with German variables. The second part contains the impulse responses to ‘monetary policy shocks’ from a DGE model. Since the methodology of the study is to compare the impulse responses generated by two dissimilar models, I think it would be useful to try to clarify what is meant by the ‘monetary policy shock’ in each model. The study follows Smets (1997) in identifying the ‘monetary policy shock’ in the VAR; it is a weighted average of the reduced form interest rate and exchange rate innovations. The chosen weight corresponds to monetary conditions index (MCI) with a weight of four. This means that a one percentage point unanticipated change in the day-to-day interest rate corresponds to a four per cent unanticipated - 40 - change in the trade weighted-exchange rate index 1. According to the identification scheme, when generating a surprise the Deutsche Bundesbank is greatly influenced by unforeseen changes in the exchange rates. This contradicts the rhetoric of the Bundesbank, which does not rely on the exchange rate target but on monetary targeting. I believe there is room for more discussion of the motivation for the applied identification scheme. According to graph 3, the impulse responses are sensitive to the choice of MCI weight ω. All the important responses (real GDP, CPI, trade balance, terms-of-trade) are influenced by the choice of weight. Particularly the persistency of the responses is enhanced by the exchange rate channel. The impulse responses differ somewhat from those of Grilli and Roubini (1996). However, one should bear in mind that the studies have a different data set and a different identification scheme. The differences are most striking in the impulse response of the USD/DEM exchange rate to the monetary policy shock. SW report a significant appreciation whereas the exchange rates response in Grilli and Roubini’s study does not differ significantly from zero. Grilli and Roubini’s impulse responses (table 3, 1996) are closer to SW’s alternative where ω = 0 , i.e. the case where monetary policy is not influenced by exchange rates. The impulse responses of some variables decay slowly (unfortunately the time span of the figures covers only five years). This suggests that the system might contain permanent shocks, which is an indication of the nonstationarities in the data set at hand. It is quite likely that – within the class of linear models - the data can be characterized as integrated processes. It is also very likely that there is cointegration among the chosen variables. According to the Granger representation theorem, the estimated VAR can be inverted and impulse responses computed. The study would benefit from consideration of nonstationarity and cointegration. Abadir et al (1998) shows that the unit root might cause a substantial bias in the VAR parameter estimates even in moderate sample sizes 2. They also show that those transformations, which 1 The idea of using the MCI as a reference for monetary policy stance builds on the open economy IS-AS analysis where both the short-term interest rate and the exchange rate influence inflation and output. It has been argued that there is no change in monetary policy, if there is no change in the MCI, i.e. changes in exchange rates can be ‘sterilized’ by the changes in the short-term interest rate. The size of such a change is given by the MCI weight. Consequently, the pure monetary policy shock is the one that influences the level of MCI – not interest rates alone. 2 The bias is an increasing function of the VAR dimensions and a nonmonotonic function of the sample size. The bias problem remains even in the near unit root cases (see Abadir and Hadri, 1998). - 41 - move data significantly away from the unit roots (or near unit roots), e.g. the determination of the cointegrating rank may reduce the bias and the potential for nonmonotonicities. In the present study, the bias-problem is exacerbated by the fact that the dimension of the system is large. The benefits of taking the (near) unit root issue seriously are also emphasized by Phillips (1998). He notes (on page 45) that ‘Our asymptotic analysis shows that in nonstationary VAR models with some roots at or near unity the estimated impulse response matrices are inconsistent at long horizons and tend to random matrices rather than the true impulse responses.’ These empirical issues cast some doubts on the estimated impulse responses. Based on the present study we do not know if the inconsistencies between the theoretical and the empirical models are due to the specification of the theoretical model or the econometric problems of the empirical model. That is, we do not know whether our measurement or the theoretical benchmark is wrong. 2 DGE model The dynamic stochastic general equilibrium (DGE) model presented by SW is very rich. The economy has three types of firms: final good producers who sell on the domestic market only but who face foreign competition; intermediate good producers who may export as well; and a capital renting firm. The economy is a semi-small open economy, where the semi stands for the fact that the exporting firms face a downward-sloping demand curve. In other respects, it is like a small open economy. The utility of the households contains consumption, leisure time, real money balances and real foreign assets. The model also contains rigidities in price formation, wage formation and in adjusting capital stock. Monetary policy follows a Taylor rule type of behaviour. I would like to touch on these last two properties of the model. The issues of the presence of foreign assets in the utility function and the monetary policy rule are discussed in more detail below. The inclusion of foreign assets in the utility function is motivated by the forward premium puzzle 3 . The foreign assets in the utility function create intrinsic demand for these assets and, hence, 3 Grilli and Roubini (1996) summarize the puzzle as follows: “If uncovered interest parity holds, a positive innovation in domestic interest rates relative to foreign ones should be associated with a persistent depreciation of the domestic currency after the impact appreciation, as the positive interest rate differential leads to an expected depreciation of the - 42 - introduce a risk premium into the uncovered interest rate parity (UIP) relationship. One of the main advantages of DGE models is that they can be used for performing welfare analysis. By including additional factors in the utility function, this novel feature of DGE models is damaged. Obstfeld and Rogoff (1998) offer another – more elegant and preferable – choice for generating forward risk premia. They simply use the second order Taylor approximation of the first order condition of their open economy DGE model, which – as in SW – contains imperfect competition and price friction. Another issue, related to the comparison of impulse responses, is the modelling of monetary policy. SW assume that the Bundesbank follows a Taylor-rule type of monetary policy but with additive uncertainty. They assume quite strong interest rate smoothing 4 behaviour; otherwise the weights on inflation and GDP growth are as proposed by Taylor. There is, however, no guarantee that the specified monetary policy rule determines price level. Given the fairly short impulse responses this feature cannot be inferred from the graphs. In addition, it is somewhat odd that the MCI approach that is used in the empirical section is not used in the theoretical section. 3 Comparison of the empirical and the theoretical model The paper could be improved significantly with respect to the examination of the fit of the theoretical model. It would be of value to the reader if at least some of the key impulse responses in the empirical and theoretical models were plotted in the same graph. Now only laborious shape comparison is possible. This informal, subjective comparison lacks statistical foundation. There is room for statistical inference here. There are examples and methods of performing such inference (see, e.g., by Watson 1993, Diebold et al 1998 and Ortega 1998 and the references therein). currency. However, the data show that a positive interest differential is associated with a persistent appreciation of the domestic currency for periods up to two years after the initial monetary policy shock.” 4 The strong interest rate smoothing might arise from the fact that the policy rate (i.e. repo rate in Germany) is kept fixed in the period between interest rate changes (although in Germany the variable rate repo is occasionally applied). Nevertheless, the policy rate (or shock to the policy rate) should be modelled rather as a jump process than a linear autoregressive process. - 43 - Graphing the impulse responses of the empirical and theoretical models in the same figure 5 reveals some inconsistencies. First, the theoretical model has some difficulties in replicating the persistency of responses in the empirical model. As discussed by the authors, an obvious example is GDP. Whereas in the empirical model it is almost constant during the first two quarters after the monetary policy shock, in the theoretical model it declines instantly. This might be due to the fact that in the theoretical model there is a strong and immediate decline in consumption and investment (and in exports), and hence in domestic demand. In the empirical model, domestic demand increases in the first two periods. Moreover, the output effect of the monetary policy shock is fairly persistent in the empirical model but not in the theoretical model. The observed delayed output effect might have something to do with the pricing-to-market behaviour in exports, adjustment costs in investment (not only in capital stock) and/or the liquidity constraint on consumers, whose intertemporal consumption path is not directly influenced by the interest rate shocks. However, when included in the DGE model, any of these features would further complicate such a model. As reported by the authors, the response of imports is another problematic feature in the theoretical model. Given the structure of the theoretical model the source of the problem might lie either in the relative prices of imports, in the elasticity of substitution between imported and domestic products or in aggregate demand. The lagged response of imports in the empirical model (imports do not respond within the first two quarters) possibly has the same roots as in the output case. This is because the theoretical model succeeds in replicating the impulse response pattern of the terms of trade (i.e. the relative price) well but not the output response. I may summarize my discussion as follows: the study has the very ambitious task of measuring the monetary policy shock in a semi-small open economy and building a DGE model to study the empirical facts analytically. The study succeeds in augmenting our knowledge in that field. However, I have doubts about the econometric methods applied in estimating the impulse responses since the empirical model does not take into account the very important – cointegration – feature of the data. This is surprising since there is now wide knowledge of the (near) unit roots and cointegration. It seems, without any reference to any metric, that the theoretical model succeeds in predicting many measured empirical regularities. I still have some difficulties in 5 Because of the different definition of shocks (and difficulties in interpreting their magnitudes) this may not be a straightforward task. - 44 - understanding the motivation of the identification of the monetary policy shock in both models. I consider that these issues need more clarification since the goal of the paper is to study the monetary policy transmission mechanism. - 45 - References Abadir, K. M., K. Hadri, and E. Tzavalis (1999): ‘The influence of VAR dimensions on estimator biases’, forthcoming in Econometrica. Abadir, K. M. and K. Hadri (1998): Is more information a good thing? Bias nonmonotonicity in stochastic difference equations, mimeo, University of York. Bundesbank (1995): Demand for money and currency substitution in Europe. Monthly Report, the Deutsche Bundesbank, 33-49. Diebold, F. X., L. E. Ohanian, and J. Berkowitz (1998): ‘Dynamic Equilibrium Economies: A Framework for Comparing Models and Data’, Review of Economic Studies, 65, 433-452. Grilli, V. and N. Roubini (1996): ‘Liquidity models in open economies: Theory and empirical evidence’, European Economic Review, 40, 847-859. Obstfeld, M. and K. Rogoff (1998): Risk and exchange rates, NBER Working Paper 6694. Ortega, E. (1998): Assessing the fit of simulated multivariate dynamic models, Documento de Trabajo 9821, Banco de España. Phillips, P.C.B: (1998): ‘Impulse responses and forecast error variance asymptotics in nonstationary VARs’, Journal of Econometrics, 83, 21-56. Smets, F. (1997): ‘Measuring monetary policy shocks in France, Germany and Italy: the role of exchange rate’, Swiss Journal of Economics and Statistics, 133, 597-616. Watson, M. (1993): ‘Measures of fit for calibrated models’, Journal of Political Economy, 101, 1011-1041.