رژیم های مارکوف ـ سوئیچینگ و مدل پولی تعیین نرخ ارز: شواهدی از بازارهای اروپای شرقی و مرکزی

This paper examines the dynamic relationship between the bilateral exchange rates of 10 Central and Eastern European emerging markets against the euro and their fundamentals, using data from the early 1990s to the middle of 2010, within the framework provided by the monetary model of exchange rate determination. Given that these countries have adopted alternative exchange rate regimes over this period, we employed a Markov-switching vector error correction model which allowed for regime shifts in the entire set of parameters and the variance–covariance matrix. The main finding of the analysis was that depending on the nominal exchange rate regime in operation, the adjustment to the long run implied by the monetary model of the exchange rate determination came either from the exchange rate or from the monetary fundamentals. Moreover, based on a Regime Classification Measure, we showed that our chosen Markov-switching specification performed well in distinguishing between the two regimes for all cases.

The seminal works of Meese and Rogoff, 1983a and Meese and Rogoff, 1983b on the forecasting ability of the monetary model to the exchange rate determination led to the emergence of a sizeable literature that attempted to develop alternative model specifications which would take into consideration a set of important features of nominal exchange rates and fundamentals. Engel and Hamilton's (1990) important contribution provided evidence that a Markov-switching model of exchange rate outperforms the naïve random walk model. The intuition behind the Markov-switching models relies on the evidence offered by several studies that the monetary model performs well for some sub-period of the total sample but not for others and also that sudden regimes changes have been observed (Meese, 1990). Frydman and Goldberg (2001) have shown that such regime changes occurred in the case of the dollar-deutschemark exchange rate over the recent float. Mahavan and Wagner (1999), Marsh (2000), Taylor and Peel (2000), Taylor et al. (2001), Clarida et al. (2003), Frömmel et al., 2005a and Frömmel et al., 2005b and De Grauwe and Vansteenkiste (2007) were among the first studies to analyze the monetary model in a Markov-switching model for a set of main bilateral exchange rates and they provided support in favour of a fundamental model. Bacchetta and van Wincoop (2009) argued that large and frequent variations in the relationship between the exchange rate and macroeconomic fundamentals become evident when structural parameters in the economy are unknown and subject to changes. Furthermore, Frömmel et al., 2005a and Frömmel et al., 2005b examined the Real Interest Differential (RID) variant of the monetary model within the Markov-switching approach and showed that in a two-regime model, one regime accurately described the RID monetary model and in addition it exhibited significant out-of-sample forecasting performance. Cheung et al. (2005) argued that the instability of the monetary model in the data generating process might provide an explanation when model specifications that work well in one period do not necessarily work well in another period. Sarno et al. (2004), using the same long span data set of Rapach and Wohar (2002), estimated appropriate Markov Switching-Vector Error Correction Model (MS-VECM) for Belgium, Finland, France, Italy, the Netherlands, Portugal, Spain and Switzerland and provided evidence in support of regime switching in the long run relationship implied by the monetary model. A further interesting result was that monetary fundamentals provided the mechanism of adjustment to the long-run equilibrium during periods of fixed exchange rates whereas the exchange rate adjusted to restore deviations from long-run equilibrium during periods of flexible exchange rate regimes. Sarno and Valente (2009) demonstrated that exchange rate models that use the information content of fundamentals in an optimal way change often which implies frequent shifts in the parameters. Altavilla and De Grauwe (2010), using a model in which chartists and fundamentalists interact, studied the dynamic interaction between the exchange rate and its fundamentals. With the estimation of a Markov-switching model, they found that the relationship between the exchange rate and its fundamentals was unstable. The time-varying nature of the coefficients of the monetary model was further confirmed in a recent study by Beckmann et al. (2009). Lee and Chen (2006) demonstrated that the time series process implied by the Markov-switching models was consistent with the widely used dirty floating exchange rate regime. Moreover, they found that the implied exchange rate process was state-dependent and approximated by an autoregressive representation in each state. Finally, Ducker and Neely (2007) provided strong evidence that the Markov-switching regime models created ex ante trading rules in the foreign exchange market and delivered strong out-of-sample portfolio returns for several major currencies.1 In this paper we further examine the case of regime switching in the relationship between exchange rates and fundamentals. The present analysis is the first to our knowledge that examines the monetary model for the 10 Central and Eastern European (CEE) countries, namely Bulgaria, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, Slovakia and Slovenia, in a time-varying coefficients framework using data from the early 1990s to the middle of 2010. Given that these economies have gone through different states since the beginning of the transition process to become market economies it is expected that nonlinearities and regime-switching behaviour in their foreign exchange markets are likely to be present. More specifically, the transition process that all CEE countries have undergone since the early 1990s led to the establishment of capital markets, the liberalization of the financial and banking sector, and introduced major shifts in fiscal and monetary policy which have caused important structural changes in almost every macroeconomic variable. Therefore one expects to find statistically significant nonlinearities in economic relationships of the kind the present analysis investigates. This presumption is further reinforced by the adoption of different exchange rate regimes during this period, along with the introduction of their currencies in the ERM II. Table 1 provides a summary of the exchange rate regimes adopted by the CEE countries since the beginning of the transition process. We observe that almost all types of exchange rate regimes have been put in force, ranging from currency board to flexible exchange rates. Furthermore, we note that Slovenia became a member of the Eurozone on January 1, 2007, Slovakia joined on January 1, 2009 whereas Estonia adopted the European common currency on January 1, 2011. In addition Latvia and Lithuania have their currencies in the ERM II which is a requirement for the satisfaction of the exchange rate criterion of the Maastricht Treaty. Additionally, during the transition process that these economies have undergone, their macroeconomic fundamentals have shown dramatic structural changes which further reinforces our argument that we should examine for the presence of nonlinearities in the relationship between the exchange rate and fundamentals. Therefore, and in light of the overwhelming evidence of the above mentioned literature, our argument that this group of countries is a perfect case for examining the behaviour of exchange rate regime in relation to macroeconomic factors under the hypothesis of regime switching. Furthermore, abnormal events like the Southeast Asian crisis of 1997, the Russian currency crisis during the spring of 1998, as well as the 2007–2009 global financial crisis have certainly contributed to observable changes in the foreign exchange market and the monetary fundamentals of the CEE economies. Table 1. Exchange rate regimes of the CEE countries. Bulgaria Czech Estonia Hungary Latvia Lithuania Poland Romania Slovakia Slovenia 1992 8 3 2 3 8 8 5 7 3 7 1993 8 3 2 3 8 8 5 7 3 7 1994 8 3 2 3 3 2 5 7 3 7 1995 8 3 2 6 3 2 6 7 3 7 1996 8 6 2 6 3 2 6 7 6 7 1997 2 7 2 6 3 2 6 7 6 7 1998 2 7 2 6 3 2 6 7 7 7 1999 2 7 2 6 3 2 6 7 7 7 2000 2 7 2 6 3 2 8 7 7 7 2001 2 7 2 4 3 2 8 6 7 7 2002 2 7 2 4 3 2 8 6 7 7 2003 2 7 2 4 3 2 8 6 7 7 2004 2 7 2 4 3 2 8 7 7 6 2005 2 7 2* 4 3* 2* 8 7 7* 4* 2006 2 7 2* 4 3* 2* 8 7 7* 4* 2007 2 7 2* 4 3* 2* 8 7 7* 9 2008 2 7 2* 8 3* 2* 8 7 7* 9 2009 2 7 2* 8 3* 2* 8 7 9 9 2010 2 7 2* 8 3* 2* 8 7 9 9 Note: 1: dollarization, 2: currency board, 3: fixed Exchange rates, 4: target zone, 5–6: crawling peg, 7: dirty float, 8: flexible exchange rates, 9: replaced by euro. * Indicates participation in ERM II. Table options An important issue that is partially related to the present study refers to institutional frontloading, i.e. the policy option that was suggested by several authors to increase intervention activities in order to achieve stabilization of the exchange rates on the road to Stage III of the European Monetary Union (EMU) (Begg et al., 1997, De Grauwe, 1996a, De Grauwe, 1996b, De Grauwe and Spaventa, 1997, Obstfeld, 1998 and De Grauwe et al., 1999). This analysis deals with the issue of price dynamics of an asset, here the exchange rate, which is known to be converted into another asset at a specified date and ceases to exist. Therefore, as De Grauwe and Spaventa (1997) showed that such a price dynamics setting could accurately describe the exchange rate movements of the currencies of the European economies that were candidates to adopt the common European currency at the end of Stage III in January 1999. Obstfeld (1998) argued that between the Maastricht Treaty in December 1991 and the end of Stage II of EMU, a central issue has been the exact conversion rate of each national currency to the euro. This indeterminacy of the exact conversion rates has led to the development of several scenarios and to a potential increase in the volatility of the respective exchange rates prior to 31 December 1998.2 Obstfeld (1998) examined thoroughly the alternative strategies that could possibly lead to the determination of the conversion rates. In addition as Obstfeld (1998), De Grauwe, 1996a and De Grauwe, 1996b and Wilfling (2009) argue, since pure preannouncements tend to be inefficient, it is suggested that central banks be ready to intervene in foreign exchange markets in order to ensure that preannounced conversion rates of each national currency vis-à-vis the euro will exactly match the market exchange rate on the last date of Stage II of EMU. It is clear that the expectation formation scheme that agents adopt plays a crucial role in the transition process from a system of floating exchange rate into a fixed exchange rate system on a publicly preannounced fixing conversion factor. Wilfing and Maennig (2001) analyzed the intermediate path of the exchange rate movements in relation to the agents’ beliefs regarding the future exchange rate fixing and their main results provide good economic reasoning for investigating the statistical significance of volatility regime-switching in exchange rates at the announcement date. Recently Wilfling (2009) examined volatility regime-switching in European exchange rates prior to EMU focusing on the intermediate period which is the one during which changes in volatility are observed, is the period between the date-of-first-notice and the date-of-full acceptance is of crucial importance to understanding the exchange rate dynamics. Finally, De Grauwe et al. (1999) and Wilfling (2009) among others argued that this framework of analysis can also be used for future accession countries as well as for the adoption of a currency board. This latter argument could provide further justification for the need to study the exchange rate behaviour of the CEE economies. The econometric analysis is conducted with the implementation of nonlinear Markov-switching regime modeling. We estimated the flexible-price variant of the monetary model for the exchange rate determination based on prior information that cointegration exists between nominal exchange rate and monetary fundamentals. However, our analysis does not deal with the issue of volatility regime-switching estimation of univariate Markov-switching as, for example, is done in Wilfling (2009), but rather focuses on the specific relationship between the exchange rate and the macroeconomic variables and how this link may change over time as different exchange rate regimes are adopted and crucial shifts in macroeconomic policies through the transition to market economies are adopted by the governments of the CEE countries. A novel feature of our analysis is the use of synthetic euro data for the period prior to the introduction of the euro. Our results have shown that nonlinearities in the relationship between the nominal exchange rate and the monetary variables were well captured by the appropriately chosen estimated MS-VECM specification for each case. Furthermore, it was shown that for all CEE economies during fixed exchange rate regimes it is the monetary fundamentals that adjust to restore deviations from long-run equilibrium, whereas in the cases in which a less restricted exchange rate regime has been in force the exchange rate adjusts to take the system back to long-run equilibrium. These alternative adjustment schemes are also reflected by the ex-post (smoothed) transition probabilities. Finally, based on a Regime Classification Measure, we show that our chosen Markov-switching specification performed well in distinguishing between the two regimes for all cases. The rest of the paper is organized as follows. Section 2 presents the flexible-price monetary model and provides the motivation for considering time-varying fundamentals. In Section 3 the Markov-switching regime methodology is discussed. Section 4 presents our empirical results while our summary and concluding remarks are given in Section 5.

This paper studied the monetary model under regime switching. We analyzed the case of the link between exchange rates and monetary fundamentals for the Central and Eastern European countries. We considered the presence of nonlinearities in the relationship between the nominal bilateral exchange rate and macroeconomic fundamentals and we estimated the appropriate Markov-switching vector error correction model. We used monthly data for the period 1994 to mid-2010 for the bilateral nominal exchange rates against the euro and the respective macroeconomic fundamentals. A novel feature of our analysis is that for the pre-EMU period we used synthetic euro data constructed according to the methodology suggested by Beyer et al. (2001). Furthermore, from a methodological point of view it was important to examine the adjustment mechanisms to the long-run equilibrium. Since during the period under examination the CEE countries adopted alternative economic policies in order to join the European Union, our analysis focused on demonstrating whether the exchange rate or the macroeconomic variables were the main vehicle in achieving their target. Therefore, given the adoption by the CEE economies of different types of exchange rate regimes during the period under examination, it was important to reveal whether the adjustment back to equilibrium took place primarily through the nominal exchange rate during periods of floating exchange rates and through monetary fundamentals during periods in which some variant of a fixed exchange rate system was in force. To this end the monetary model provided the appropriate framework to study the behaviour of exchange rate movements in periods of transition. There are several important findings that stem from the present analysis. First for each bilateral exchange rate and the respective macroeconomic variables we were able to capture nonlinearities with the estimation of the appropriate Markov switching regime model with two regimes. The fitted model was quite general since it allowed for regime shifts in the intercept and the complete set of parameters, as well as the variance–covariance matrix. In addition, for all cases the null hypothesis of linearity was rejected when tested against the alternative of a MS-VECM specification. Second, our analysis has clearly shown that during the period when some variant of fixed exchange rates was adopted in each CEE country, the monetary fundamentals adjust to restore deviations from the long-run equilibrium. In contrast during periods with less restricted exchange rate regimes, it was the exchange rate that adjusted to restore any disequilibrium. Finally, the application of the Regime Classification Measure developed by Ang and Bekaert, 2002a and Ang and Bekaert, 2002b showed that our estimated Markov-switching models distinguished very well between the two regimes.