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Board of Governors of the Federal Reserve System
International Finance Discussion Papers
Number 889, January 2007 --- Screen Reader Version*

Markov Switching GARCH Models of Currency Turmoil in Southeast Asia

Celso Brunetti (Johns Hopkins University), Roberto S. Mariano (Singapore Management University), Chiara Scotti (Federal Reserve Board), Augustine H.H. Tan (Singapore Management University)^*

NOTE: International Finance Discussion Papers are preliminary materials circulated to stimulate discussion and critical comment. References in publications to International Finance Discussion Papers (other than an acknowledgment that the writer has had access to unpublished material) should be cleared with the author or authors. Recent IFDPs are available on the Web at http://www.federalreserve.gov/pubs/ifdp/. This paper can be downloaded without charge from the Social Science Research Network electronic library at http://www.ssrn.com/.

Abstract:

This paper analyzes exchange rate turmoil with a Markov Switching GARCH model. We distinguish between two different regimes in both the conditional mean and the conditional variance: "ordinary" regime, characterized by low exchange rate changes and low volatility, and "turbulent" regime, characterized by high exchange rate movements and high volatility. We also allow the transition probabilities to vary over time as functions of economic and financial indicators. We find that real effective exchange rates, money supply relative to reserves, stock index returns, and bank stock index returns and volatility contain valuable information for identifying turbulence and ordinary periods.

Keywords: Currency crises; Financial markets; Banking sector; Regime switching; Volatility.

JEL classification: C13; C22; C52; F31; F34.

1  Introduction

The decade of the nineties witnessed several bank and currency crises.¹ The severity of the crises has motivated researchers to develop early warning systems in order to forestall similar crises. Such early warning systems typically involve some precise definition of a crisis and a mechanism for predicting it. A currency crisis is usually identified as an episode in which there is a sharp depreciation of the currency, a large decline in foreign reserves, a dramatic increase in domestic interest rates or a combination of these elements.

This paper studies exchange rate turmoil, that is, we focus on episodes of extensive exchange rate changes, and we analyze which variables trigger the move from a tranquil period to a turbulent time. Since a currency crisis is not necessarily a turbulent period, and vice versa, our approach identifies currency crises only when they manifest with large exchange rate devaluations. Our modeling strategy relies on the empirical evidence that i) small exchange rate changes are associated with low volatility (ordinary regime) and large exchange rate movements go together with high volatility (turbulence), and ii) exchange rate volatility is not constant in the two regimes. This calls for a GARCH regime switching approach, in which we furthermore allow the transition probabilities to vary over time as functions of economic and financial indicators. Switching volatility models have been used for modeling equity markets (Hamilton and Susmel, 1994; Dueker, 1997; Susmel, 2000), short-term interest rates (Cai, 1994; Gray, 1996; Kalimipalli and Susmel, 2006), emerging equity markets (Susmel, 1998), and exchange rates (Klaassen, 2002; Calvet and Fisher, 2004). However, to the best of our knowledge, this paper is the first application to currency turmoil.

The analysis is applied to four Southeast Asian countries: Thailand, Singapore, the Philippines, and Malaysia. Estimation results support our intuition for modeling exchange rate volatilities. Our results, in fact, show that signals of the July 1997 crisis become apparent in Thailand as early as January, and the probability of getting into a crisis jumps to as much as 82 percent in June 1997.

The literature on financial/currency crises is vast, and it mainly focuses on trying to predict crises in developing countries. There are three methods or approaches for predicting currency crises that have been developed in the literature.

One class of models is the probit regression approach of Frankel and Rose (1996). They use probit analysis on a panel of annual data for 105 developing countries from 1971-92. The hypothesis tested is that currency crashes are positively linked to certain characteristics of capital inflows, such as low shares of foreign direct investments (FDI); low shares of concessional debt or debt from multilateral development banks; and high shares of public-sector, variable short-term, and commercial bank debt. The finding is that currency crises are more likely when foreign interest rates are high, domestic credit growth is high, the real exchange rate is overvalued, the current account deficit and fiscal deficit are large (as a share of GDP), external concessional debt is small, and FDI is small in relation to the total volume of external debt. However, when the model is used to generate out-of-sample predictions for the 1997 Asian Crisis, the forecasts are not successful (Berg and Patillo, 1999a).² More recently Bussiere and Fratzcher (2006) develop a new early warning system model based on a multinomial logit with three outcomes (tranquil, pre-crisis and post-crisis) showing that such a specification leads to a better out-of-sample forecast and solves what they call the `` post-crisis bias.''

A second class of models (Tornell, 1999; IMF, World Economic Outlook, 1998; Radelet and Sachs, 1998; Corsetti Pesenti and Roubini,1999) follows Sachs, Tornell and Velasco (1996) who use cross-country regressions to explain the Tequila (Mexican) crisis of 1995. Using a crisis index defined as the weighted sum of the percentage decrease in foreign reserves and the percentage depreciation of the peso, they conclude that countries have more severe attacks when they have low foreign reserves, their banking systems are weak and their currencies overvalued. Berg and Patillo (1999a) extend the data to 23 other countries and conclude that the Sachs, Tornell and Velasco (1996) model proved to be largely unstable. Specification uncertainty appeared to be as important as parameter uncertainty.

The third class of models, attributed to Kaminsky, Lizondo and Reinhart (1998), is the `` signals approach.'' A crisis is defined as a situation in which a weighted average of monthly percentage depreciations in the currency and monthly percentage declines in reserves exceeds its mean by more than three standard deviations. They use 15 monthly variables to monitor for unusual behavior during a 24-month window prior to a crisis. Threshold levels, beyond which signals would be generated, are specified. Using variants of the signals approach, Kaminsky (1998a and 1998b), Kaminsky and Reinhart (1999), and Goldstein, Kaminsky and Reinhart (2000) claim some success in predicting the Asian crisis.

These approaches have some limitations. For example, the signal approach requires the ex-ante definition of a threshold and the transformation of the variables into binary variables, with a significant loss of information; the logit/probit approach requires the definition of a crisis dummy, with potential misclassifications.

We use a Markov switching approach in which we account for the presence of two potential regimes: ordinary and turbulent. We also recognize the fact that, even within each regime, the volatility of exchange rate returns is not constant, and we therefore include a GARCH specification. The probabilities of switching between the two regimes are time-varying. The attractiveness of this approach is that we do not need to distinguish ex-ante between ordinary and turbulent times, but we let the estimation results supply us with this information. We differ from Mariano et al. (2002) in that we recognize the importance of volatility dynamics, and we enlarge the set of potential explanatory variables to include the M2-reserve ratio, real domestic credit, real effective exchange rate, stock market returns and volatility, and banking sector returns and volatility.

The model can be used for out-of-sample forecasting. Unfortunately, the short sample does not allow us to do so in the current paper (GARCH models require long datasets). Therefore, we only limit our study to understanding the variables and modeling specifications which play a role in comprehending currency turmoil, leaving the out-of-sample forecast exercise to future assessment.

This paper proceeds in Section 2 by motivating the use of a Markov switching GARCH model. Section 3 presents the model. Section 4 illustrates the data used in the estimation. Section 5 presents the estimation results toghether with an analysis of the estimated time-varying transition probabilities. Section 6 concludes the paper.

2  Motivating our Approach

The goal of the paper is to study episodes of high (low) risk and high (low) exchange rate movements.

Our approach consists in modeling the conditional mean and the conditional variance of the exchange rate devaluation. The first and the second order moments of exchange rate devaluation are driven by the same Markov process governed by an unobservable state variable. The underlying assumption is quite simple: low mean values of exchange rate devaluation are associated with low volatility of the exchange rate devaluation, and high devaluation is associated with high volatility. We refer to the latter regime as `` turbulence'' and the former as describing `` ordinary'' market conditions. In addition, the transition probabilities in the Markov process are functions of macroeconomic and/or financial variables. This captures the idea that large exchange rate devaluations and high risk might be driven by exogenous variables.

This approach might lead to identify currency crises. In fact, there is empirical evidence (see below) showing that, at least for the four Southeast Asian countries analyzed in this paper, high risk and high exchange rate devaluation correspond indeed to the 1997 currency crises.

The countries considered are Thailand, Singapore, Malaysia and Philippines. The sample period runs from November 1984 to December 2001.

A difference of our approach from the previous literature is the emphasis on the volatility process of exchange rate movements. To motivate our accent on the volatility of exchange rate returns, we compute a volatility proxy: the range,³ which is defined as the difference between the maximum value of the (log of the) price process over a given interval of time and the minimum value of the (log of the) price process over the same interval

$$l=\max_{0\leq n\leq N}\left[ \ln(P_{n})\right] -\min_{0\leq n\leq N}\left[ \ln(P_{n})\right]$$ (1)

Our data set is composed of monthly observations. The use of monthly data is due to the fact that many macroeconomic data used as explanatory variables for the time varying Markov probabilities, are available only at monthly frequencies. However, nominal exchange rate data is also available at daily frequencies. For each month and for each exchange rate analyzed we selected the highest (log) price and the lowest (log) price to compute the monthly range (see Chou, 2005). Therefore, the time interval $0\leq n\leq N$ in our set up corresponds to a month. Finally, the volatility (standard deviation) proxy is computed as

$$\widehat{\sigma}_{i,t}=\sqrt{\frac{\pi}{8}}l$$ (2)

where $i$ indicates the four different exchange rates analyzed in the paper and $t$ refers to the monthly observation.

Figure 1 graphs the volatility proxy for the Thai baht. Figures for the other three countries look very similar.

2.1  Time-Varying Volatilities Approach

Since Mandelbrot (1963a, 1963b) and Fama (1965) it has been a well know fact that asset return volatility is not constant over time. Moreover, there is a large empirical evidence (among others see Brunetti and Lildholdt, 2002b) showing volatility clustering: large (small) changes in the nominal exchange rate tend to be followed by large (small) changes of either sign. These features are confirmed by our data. Figure 1 shows that volatility changes over time and evolves in clusters.

The GARCH model is able to capture both time varying volatility and volatility clustering. Baillie and Bollerslev (1989) shows that the GARCH class of models is able to capture the volatility dynamics of exchange rates at daily, weekly and monthly frequencies. Even if the GARCH effect dissipates as the length of the sampling interval increases, there is still heteroskedasticity and volatility clustering at monthly frequencies. GARCH(1,1) models have proved to adequately describe exchange rate volatility dynamics.⁴ This is the approach we follow in this paper.

2.2  Markov Regime Switching Approach

As already stated, we model jointly the conditional mean and the conditional variance (volatility) of exchange rate devaluations. The Markov switching regime model adopted relies on two assumptions: i) the volatility process is characterized by two regimes, high volatility and low volatility; ii) the high volatility regime is associated with large exchange rate deviations (high values of the mean process) and the low volatility regime is associated with small exchange rate movements (low values of the mean process). The first assumption is confirmed by Figure 1. For all of the four countries analyzed, the volatility process exhibits periods of very low volatility and periods of very high volatility. Interestingly, the highest volatilities coincide with the 1997 crisis which is the major currency crisis that took place during our sample. Therefore this crisis represents our benchmark.

The onset of the crisis in Thailand, the first country to be hit by the crisis, was on July 1997. The average monthly volatility (standard deviation) in the 12 months after the crisis (July 1997 - June 1998) was more than seven times bigger than in the previous 12 months (July 1996 - June 1997). Similar results also apply to Singapore and Malaysia. For the Philippines the volatility in the twelve months subsequent the beginning of the crisis increased by a factor of 55.

The second assumption simply implies that the same Markov process drives both the mean and the variance of exchange rate returns. Figure 2 displays the scatter plot of exchange rate devaluation and the volatility proxy for Thailand. It is evident that periods of zero or low exchange rate devaluation/appreciation are associated with low risk and periods of severe devaluations are associated with very high exchange rate risk. In the twelve months after the onset of the 1997 crisis the level of the exchange rate devaluation increased by a factor of 8 compared to the 12 months before. Similar results apply to the other three countries. The exchange rate devaluation increased by a factor of 12, 59 and 54 in Singapore, the Philippines and Malaysia respectively, when comparing the twelve months before and after the crisis.

It is interesting to note the asymmetry of exchange rate devaluation and volatility: in periods of high risk the currency devaluates. The largest outliers in Figure 2 refer to the 1997 crisis.

The presence of two regimes - low devaluation and low volatility versus high devaluation and high volatility - motivates the Markov switching approach adopted. It is also evident that within the two regimes volatility is not constant. Hence the need for a GARCH approach.

2.3  Turbulence and Crisis

The modeling strategy adopted is able to identify turbulent periods. Do turbulent periods correspond to currency crises?

A currency crisis is not necessarily a turbulent period, and vice versa. There can be a crisis without any exchange rate devaluation (and of course without any volatility of the exchange rate devaluation). In fact, the government might be able to absorb exchange rate pressures using foreign reserves, interest rates, etc. On the same base the exchange rate might experience turbulence without being in a crisis.

Citing Kaminsky and Reinhart (1999): `` Most often, balance-of-payments crises are resolved through a devaluation of the domestic currency or the flotation of the exchange rate. But central banks can and, on occasion, do resort to contractionary monetary policy and foreign-exchange market intervention to fight speculative attack'' (p.475-6).

Figures 1 and 2 provide overwhelming evidence that the 1997 crisis resolved in a large exchange rate devaluation and high volatility. Our modeling approach distinguishes between turbulent and ordinary periods and identifies currency crises only to the extent that they manifest with large exchange rate devaluations.

3  Time varying probabilities Markov switching GARCH models

Let $y_{t}$ be the first difference of the log nominal exchange rate. The simple GARCH(1,1) model may be written as follows:

$$y_{t} =\mu+\sum_{i=1}^{k}\theta_{i}X_{i,t}+u_{t}$$ (3)

$$u_{t} =\sigma_{t}\varepsilon_{t},\;\varepsilon_{t}\sim nid(0,1)$$ (4)

$$\sigma_{t}^{2}\vert\Omega_{t-1} =\omega+\alpha u_{t-1}^{2}+\beta\sigma _{t-1}^{2}$$ (5)

where $X_{i}$ are the exogenous and/or lagged variables for the mean of the returns, $\theta$ is the corresponding parameter vector and $\Omega_{t-1}$ is the information set available at time $t-1$. For simplicity we are assuming that the innovation term follows a normal distribution. The model is very flexible, and many extensions have been proposed in the literature.

As shown in the previous section, in periods of currency turbulence, exchange rate volatility is often very high ,and we may distinguish between two regimes: a `` ordinary'' regime and a `` turbulence'' regime. The approach we adopt here is similar to Gray (1996) and Dueker (1997). Equations 3 -5 can be written as

$$y_{t} =\mu_{t}+\sum_{i=1}^{k}\theta_{i}X_{it}+u_{t}$$ (6)

$$u_{t} =\sigma_{t}\varepsilon_{t},\;\varepsilon_{t}\sim nid(0,1)$$ (7)

$$\sigma_{t}^{2}\left( S_{t},S_{t-1}...S_{0}\right) =\omega\left( S_{t}\right) +\alpha\left( S_{t-1}\right) u_{t-1}^{2}+\beta\left( S_{t-1}\right) \sigma_{t-1}^{2}\left( S_{t-1}...S_{0}\right)$$ (8)

The constant, $\mu_{t}$, in the conditional mean equation is allowed to switch between two regimes - high mean $\left( \mu_{1}\right)$ and low mean $\left( \mu_{0}\right)$,

$$\mu_{t} =\mu_{1}S_{t}+\mu_{0}\left( 1-S_{t}\right)$$ (9)

$$S_{t} \in\left\{ 0,1\right\} , \forall t$$ (10)

$$\Pr\left( S_{t}=0\vert S_{t-1}=0\right) =p$$ (11)

$$\Pr\left( S_{t}=1\vert S_{t-1}=1\right) =q$$ (12)

where $S_{t}$ is the latent Markov chain of order one. We are assuming that the parameter vector $\theta$ in the conditional mean equation is constant (i.e. it does not switch according to the Markov process), but this assumption can be easily relaxed. The innovation term, $u_{t}$, follows a normal distribution.

The conditional variance, $\sigma_{t}^{2}$, is a function of the entire history of the state variable. This is due to the autoregressive term, $\sigma_{t-1}^{2}$, in the conditional variance equation - see Dueker (1997), Cai (1994) and Hamilton and Susmel (1994). Obviously, it is very demanding to account for all the past history of the state variable. Following Dueker (1997), we adopt an approximation procedure that seems not to cause any problems in the evaluation of the likelihood function. This procedure implies that the conditional variance is a function of only the most recent values of the state variable. Dueker (1997) shows that in a GARCH(1,1) model we need to consider only the most recent four values of the state variable. This means that the conditional variance, $\sigma_{t}^{2}$, is function only of the current state $\left( S_{t}\right)$ and the previous state $\left( S_{t-1}\right)$: $\sigma_{t}^{2}\left( i,j\right) =\sigma_{t}^{2}\left( S_{t}=i,S_{t-1}=j\right)$ . By integrating out $S_{t-1}$, the conditional variance can be written as

$$\sigma_{t}^{2}\left( i,j\right) =\omega\left( S_{t}=i\right) +\alpha\left[ u_{t-1}^{2}\left( j\right) \right] +\beta\left[ \sigma_{t-1}^{2}\left( j\right) \right]$$ (13)

Equation (13) implies that the constant in the conditional variance equation is allowed to switch. In the GARCH(1,1) specification, the unconditional variance is given by $\frac{\omega}{1-\alpha-\beta}$. Therefore, equation (13) allows two unconditional variances: high unconditional variance in `` turbulence'' regimes and low unconditional variance in `` ordinary'' regimes. Following Dueker (1997), $\omega\left( S_{t}\right)$ is parameterized as $g\left( S_{t}\right) \omega$ such that $g\left( S=0\right)$ is normalized to unity.

In this setup the transition probabilities are constant. This seems over-restrictive. Transition probabilities may depend on economic variables. For this reason we introduce time varying probabilities. In our setup transition probabilities are probit functions of economic variables denoted by $Z_{t}$

$$\Pr\left( S_{t}=0\vert S_{t-1}=0\right) =p=\Phi\left( Z_{t-1}^{^{\prime} }\zeta\right)$$ (14)

$$\Pr\left( S_{t}=1\vert S_{t-1}=1\right) =q=\Phi\left( Z_{t-1}^{^{\prime}} \nu\right)$$ (15)

where $\Phi$ denotes the $cdf$ of the normal distribution. A Markov switching regime GARCH model with time varying probabilities is also developed in Gray (1996).

This approach allows forecasting the conditional probability of being in a given regime $\left( i,j\right)$ at time $t+1$ given the information available at time $t$.

Denote $\overset{\symbol{94}}{\xi}_{t\vert t}$ the $\left( N\times1\right)$ vector of conditional probabilities of being in state $\left( 0,1\right)$ conditional on the data until date $t$. Define $\eta_{t}$ as the $\left( N\times1\right)$ vector of the density of $y_{t}$ conditional on $S_{t}$. Following Hamilton (1994), the optimal forecast for each $t$ is computed by iterating the following two equations

$$\widehat{\xi}_{t\vert t} =\frac{\left( \overset{\symbol{94}}{\xi}_{t\vert t-1} \odot\eta_{t}\right) }{\mathbf{1}^{\prime}\left( \overset{\symbol{94}}{\xi }_{t\vert t-1}\odot\eta_{t}\right) }$$ (16)

$$\widehat{\xi}_{t+1\vert t} =\mathbf{P}_{t+1}\mathbf{\cdot}\overset{\symbol{94} }{\xi}_{t\vert t}$$ (17)

where $\mathbf{1}$ is the unit vector, $\mathbf{P}_{t+1}$ is the $\left( N\times N\right)$ Markov transition probability matrix and $\odot$ denotes the element-by-element multiplication.

Recall that $\mathbf{P}_{t}$ is time varying and depends on the previous period values of explanatory variables. We are mainly interested in the turbulent regime. Our approach allows us to compute the probability of moving to a turbulence regime in period $t+1$ given all the available information at time $t$.

The log-likelihood function is given by

$$\ln L_{t}\left( i,j\right) =-\frac{1}{2}\ln\left[ \sigma_{t}^{2}\left( j\right) \right] +\ln\left[ \frac{u_{t-1}^{2}\left( i\right) }{\sigma _{t}^{2}\left( j\right) }\right] -\ln\left[ \sqrt{2\pi}\right]$$ (18)

where $i\in\left\{ 0,1\right\}$ relates to $S_{t}\in\left\{ 0,1\right\}$ and $j\in\left\{ 0,1\right\}$ relates to $S_{t-1}\in\left\{ 0,1\right\}$. The function is maximized following Hamilton (1994).

4  Data Description

Currency crises/turmoil most often reveal themselves in an actual devaluation of the domestic currency or the flotation of the exchange rate. Nevertheless, there are occasions in which central banks wind up adopting contractionary policies. In these cases, crises manifest themselves in interest rate hikes, depletion of reserves, etc. Also, currency crises are sometimes linked to banking/financial sector distresses.⁵

To take into account all facets of currency turmoil, we consider a number of macroeconomic and financial variables: M2/reserves, real domestic credit, real effective exchange rate, banking sector stock index returns and volatility, general stock market index returns and volatility.⁶ In order to get a clearer view of the evolution of turbulent periods we use monthly data, from November 1984 to December 2001.⁷

Exchange rates devaluation/appreciation is simply computed using end of the month log-first difference.

Real effective exchange rate (REER) and interest rate differentials (IRDIFF) are external sector indicators. In particular, the percentage deviation of the REER from a trend is a current account indicator, while the domestic-US real interest rate differential on deposits represents an indicator associated with the capital account. REER is considered as deviation from a trend because not all real appreciations/depreciations necessarily reflect disequilibrium phenomena.

M2/reserves (M2 ratio) together with real domestic credit/GDP (RDC) are financial sector indicators. Both variables are considered in deviation from a trend. In fact, not all the changes in those indicators are symptomatic of a troublesome situation.⁸

Stock index returns (GENRET) and volatility (GENVOL) are indicators of the real sector⁹ linking currency turmoil to economic activity.

In order to stress the link between currency crises and banking problems we introduce returns and volatility of a stock index based on a portfolio (weighted by the capitalization) of banks listed on the stock market (BANKRET and BANKVOL, respectively).¹⁰ We believe these variables could be important indicators for the Southeast Asian crisis we study in this paper.

Citing Kaminsky and Reinhart, `` Of course, this is not an exhaustive list of potential indicators'' (p.481). We have considered only some of the indicators that they suggest and add some others, based on the empirical evidence of the countries that we analyze. However, Edison (2000) suggests that a marked appreciation of the real exchange rate, a high ratio of short-term debt to reserves, a high ratio of M2 to reserves, substantial losses of foreign exchange reserves, and sharply declining equity prices represent the more important indicators of vulnerability.

Figure 3-6 display the evolution of the above indicators for Thailand, Singapore, Philippines and Malaysia.

In all the countries the real effective exchange rate is appreciating relative to its trend during the period before the onset of the 1997 crisis, showing evidence of overvaluation. (Note that the real effective exchange rate follows the UK quotation - i.e. US Dollars per local currency.) For Thailand, the Philippines and Malaysia the REER is 9-10% above the trend in the 12 months preceding the crisis. This is in line with previous literature on currency crises. Domestic-US real interest rate differentials do not indicate any rising expectations of devaluation as the 1997 currency crisis approaches. For all the countries analyzed, in the 12 months before the crisis, IRDIFFs are flat.

Turning now to the financial sector variables, it is possible to note that in Thailand and Malaysia the M2/reserves deviation from trend is positive and significative in size during the period before the onset of the 1997 crisis. This is in line with both a large expansion in M2 and a sharp decline in foreign currency reserves as also pointed out in Kaminsky and Reinhart (1999) for banking and currency crises. In Singapore and Philippines the M2 ratio does not display any considerable deviation from trend.

RDC is above its trend before the 1997 crisis in the Philippines and Malaysia but it is around trend in Thailand and Singapore.

The returns on the stock market index in the 12 months before the 1997 crisis are, on average, negative for all the markets considered. Particularly severe is the drop in the general stock market index in Thailand: the monthly return averages to -7%. Stock market volatility is also very high. The stock market represents the real sector; therefore, the stock market returns volatility may be interpreted as the uncertainty/risk related to the real sector. In the twelve months before the crisis, stock market volatility in Thailand doubles with respect to the average value over the whole sample. Also for Singapore, the Philippines and Malaysia stock market volatility increases.

Currency crises are sometimes evidence of banking sector distress. For this reason we use the banking sector index. In Thailand, the average monthly return of the banking sector is -8% in the 12 months before July 1997. Evidence of banking sector distress is also present in Singapore and Malaysia. In Thailand, the volatility of the banking index return more than doubles in the months before the crisis. Similar results hold for Singapore and Malaysia, but not for the Philippines.¹¹

5  Empirical Results

For each country we estimated several models. To distinguish among models we use the number of explanatory variables in the time varying Markov probabilities. We started from the Switching Regime GARCH with constant transition probabilities. This is `` Model(1,1)'' because it includes only a constant for each probability. The model including an explanatory variable in the time varying Markov probability of the `` ordinary'' state ($p$) is referred to as `` Model(2,1)'' because there is a constant plus an explanatory variable in $p$ and only a constant in $q$.

To select among the different models we use the following criteria:

1. Analysis of the statistical properties of the estimated parameters - i.e. parameters should be well-determined. In this regard, it is important to note that GARCH models, to work properly, require many data points. Unfortunately, the use of monthly frequencies is problematic in this respect. For this reason we consider 90% significance level.
2. The estimated coefficients in the probit representation of the time varying probabilities should have the right sign so that they can have a proper economic interpretation;
3. Transition probabilities: if the model delivers an increase in the probability of getting into the turbulent regime before the onset of the turbulence, we will consider the model as satisfactory. All the turbulent periods in the data set will be considered. However, we will pay particular attention to the 1997 crisis;
4. Models will be compared in terms of the value of the Akaike (AIC) and Schwartz (SIC) information criteria.

In what follows we analyze the estimation results and the transition probabilities of the estimated models.¹² We report both the graph of the filtered transition probabilities and tables showing the behavior of these probabilities over turbulent periods. Providing a formal definition of turbulent periods is beyond the scope of this paper. We identify turbulent periods with severe devaluations. Tables reporting the time-varying probabilities aim to provide evidence about the performance of the estimated models.

Our analysis of the empirical results starts from Thailand, the first country involved in the 1997 crisis.

5.1  Thailand

5.1.1  Estimation Results

Table 1 reports the selected models for Thailand. For comparison we also report the simple Model(1,1) where the Markov probabilities are constant. The simple Model (1,1) reveals the average exchange rate devaluation during `` ordinary'' market conditions is not statistically different from zero and it is associated with a very low volatility (variance) level. In the `` turbulence'' state the average devaluation jumps to 9% (per month) which is associated with a volatility level which is more than 500 times bigger than the `` ordinary'' state. The GARCH parameters, $\alpha$ and $\beta$, are statistically well-defined and in line with the values reported in the literature on exchange rate volatility. In the third column of Table 1 we report the estimated parameters for Model(2,1). This model is characterized by the fact that REER is added as an explanatory variable in $p$, the probability of being in the ordinary state at $t+1$ given the information available at time $t$. As for the simple Model(1,1) the two regimes are evident: low devaluation goes with low volatility and high devaluation goes with high volatility. Interestingly, in the conditional variance equation, $\alpha$ is negative. Nevertheless the conditional variance is always positive¹³ - this is also true for Model (3,1). REER is significant and has the correct sign. Well before the onset of the crises the REER is moving as to anticipate the forthcoming exchange rate devaluation.

Model (3,1) contains REER and M2 ratio as explanatory variables in $p$ while $q$ contains only a constant. Both indicators have the correct sign and are significant. For this model, the volatility in the turbulent regime shifts by a factor of 715. Finally, the two indicators in the last model are REER and the banking index returns. BANKRET has a positive sign. In fact, when the banking sector is performing well (positive returns), the probability of staying in the ordinary state increases. Notice that, for the last model, we were forced to use less observations because the data on the banking index starts in February 1987. AIC and SIC select Model(3,1) with REER and BANKRET as explanatory variables in $p$.

5.1.2  Time-Varying Transition Probabilities

For Thailand, in the period analyzed, the major turbulence was due to the 1997 crisis, which started in July. Table 2 contains the transition probabilities of getting into a turbulent period at time $t+1,$ given the available information up until time $t$ (equation 17), for the selected models - see Table 1.

The second row shows the average of that probability during ordinary periods. The simple Model(1,1) is able neither to anticipate nor to provide any warning of the 1997 crisis. The situation changes when considering Model(2,1). In June 1997, Model (2,1) gives a 14% probability of getting into a crisis in the next month. In absolute terms, the value of 14% is not high. However, in relative terms - i.e. when compared to the average probability in tranquil periods - 14% represents a noticeable jump in the probability level. When we include the M2 ratio and the BANKRET the June 1997 probability of getting into a crisis in the next period jumps to 34% and 82%, respectively.

Figure 7 shows the transition probabilities of the last two models in Table 1. Signals of the 1997 crisis are already apparent in January 1997. We consider this a very good result.

For Thailand the indicators that proved to be important are REER, M2 ratio and bank index returns. It is interesting to note that all the models selected contain the REER as an explanatory variable. Moreover, all models have just a constant in $q$ - the probability of moving from turbulence to ordinary regime - while all the action is in $p$ - the probability of moving from an ordinary regime to a turbulent one.

5.2  Singapore

5.2.1  Estimation Results

Table 3 reports the five selected models for Singapore. The simple Model(1,1) reveals that the exchange rate devaluation exhibits two regimes. In the ordinary regime the currency is, on average, appreciating and the volatility is low. In the turbulent regime the currency is depreciating and the volatility shifts by a factor of 6. The parameter $\beta$ in the GARCH specification is not significantly different from zero. Therefore, all the models in Table 3 follow an ARCH(1) specification. Model(2,1) includes REER in $p$. All the parameters are well-defined. If REER is appreciating, the probability of being in the ordinary period decreases while the probability of being in the turbulent regime increases. This is the reason why in Model (2,2) the REER coefficient is negative in $p$ and positive in $q$. For Singapore, both the banking index returns and the banking index return volatility are important indicators (jointly with REER). They indeed display the expected sign and are significant. AIC selects Model(3,1) with REER and banking index returns as explanatory variables in $p$, while SIC selects Model(2,1) with REER only as an explanatory variable in $p$.

5.2.2  Time-Varying Transition Probabilities

Transition probabilities of the selected models for Singapore are reported in Table 4. We identify three periods of turbulence. The more severe turbulent period coincides with the 1997 crisis, which started in August. The other two turbulent periods are April and October 2001.

Model(2,1) shows that the June 1997 probability to move to a turbulent period in $t+1$ (July) is 35%. This probability is 57% in the next period. Model(2,2) performs even better: in June 1997 the probability of getting into turbulence in $t+1$ is 55%. Models which include the banking return index and the banking return index volatility perform well in detecting all turbulent periods.

Figure 8 graphs the transition probabilities of Model(2,2) with REER in both $p$ and $q$, and Model(3,1) with REER and BANKVOL in $p$. It is evident how both models are able to reveal signs of the turbulent periods experienced by the Singapore dollar. Model(3,1) with REER and BANKVOL already shows symptoms of the 1997 crisis in February 1997.

Real effective exchange rate, bank index returns and volatility are the important indicators for Singapore. Model(2,2) indicates that REER is important in modeling both the probability of being in the ordinary regime and staying in that regime and the probability of being in a turbulent regime and staying in that regime. This is the only model, for all the countries analyzed, where it is important to model $q$ - i.e. $q$ is not constant but varies over time. Combining REER and banking indicators in modeling $p$ produces very interesting results.

5.3  The Philippines

5.3.1  Estimation Results

For the Philippines, the parameter $\beta$ in the conditional variance equation is not statistically important; therefore, the models analyzed reduce to an ARCH specification. Table 5 contains the three selected models. In Model(1,1) all the coefficients are significant at standard significance level. The only two indicators that are important for this country are REER and general stock index returns. The real effective exchange rate in Model(2,2) has the expected negative sign, but it is not statistically important. REER is also not significant in Model(3,1). However, model(1,1) is selected by both AIC and SIC.

5.3.2  Time-Varying Transition Probabilities

The transition probabilities of the three selected models for the Philippines are reported in Table 6. We distinguish four turbulence periods: November 1990, the 1997 crisis that started in July, July 2000, and April 2001. The simple Model(1,1) performs as well as the other models in identifying the turbulent periods.

Figure 9 shows the transition probabilities for the last two models in table 5. The exchange rate devaluation of the Philippine peso is very volatile and shows several periods of appreciation/depreciation. The probabilities exhibit a similar pattern.

Despite sound economic fundamentals (see Figure 5 ) both REER and GENRET are gathering signs of the forthcoming turmoil.

5.4  Malaysia

5.4.1  Estimation Results

The last country analyzed is Malaysia. The data sample is shortened to account for the pegging regime that started in November 1998. Table 7 reports the four selected models. Model(2,1) shows that REER has the correct sign and is significant. This is in line with the evidence provided for the other countries. The M2 ratio¹⁴ reveals to be an important indicator, and the bank index return standard deviation also provides very interesting results. AIC and SIC select Model(3,1) with REER and BANKVOL as explanatory variables in $p$.¹⁵

5.4.2  Time-Varying Transition Probabilities

We identify three periods of turbulence: January 1994, August 1997,¹⁶ and May 1998. All models, but Model(1,1), already show in June 1997 the limbo of the crisis. The performance in anticipating the 1997 crisis is spectacular for two models: Model(3,1) with REER and M2 ratio, and Model(3,1) with REER and BANKVOL. These results are confirmed by Figure 10.

5.5  Summary of the Empirical Results

The results for all the countries analyzed show interesting common features. First, modeling $p$ as time varying produces the best results. Our intuition relies on the fact that $\left( 1-p\right)$ gives the probability of getting into turbulence from the ordinary regime. In our methodology $\left( 1-p\right)$ represents the first channel through which changes in the explanatory variables affect the transition probabilities.

Real effective exchange rate displays an enormous explanatory power in all the countries. In addition, M2 ratio, BANKRET, BANKVOL, GENRET contain valuable information which improves the performance of the models.

6  Conclusions

In this paper we adopt a GARCH Markov switching regime model. The approach consists of jointly modeling the conditional mean and the conditional variance of exchange rate changes. The estimated parameters confirm the importance of modeling volatility dynamics. Stock market and banking sector indexes, together with real effective exchange rates and M2 ratios, play an important role in understanding exchange rate turbulence.

Our approach exhibits several limitations. It is not applicable to countries that are pegging their exchange rate. In fact, in this case, there will not be any variation of the exchange rate and any volatility of the exchange rate. Moreover, we are only able to distinguish turbulent and ordinary regimes. As already discussed, turbulence does not always coincide with currency crises. Finally, we consider only four countries and a major currency crisis. It remains to validate how this methodology would work with other countries and other currency crises. However, an advantage of this approach is that it could be easily used for out-of-sample forecasting, which we leave for further research.

7  Appendix

7.1  Data

We created a data set for Malaysia, the Philippines, Singapore and Thailand composed of five variables: exchange rate return/devaluation, M2 ratio, real domestic credit/GDP, real effective exchange rate devaluation, domestic-US real interest rate differential on deposits, stock index returns and volatility, banking sector return and volatility.

All data, with the exception of the real effective exchange rate and stock index and banking sector index, are retrieved from the International Financial Statistics (IFS) database. The real effective exchange rate is from JP Morgan, while stock data are from Bloomberg.

All the variables are constructed accordingly with the literature on currency crises. See Kaminsky and Reinhart (1999).

M2 ratio is given by the sum of M1 (IFS line 24) and quasi money (IFS line 25) divided by Reserves (IFS line 1l.d) converted into national currency.

Real domestic credit is domestic credit (IFS line 52) divided by CPI (IFS line 64) to obtain domestic credit in real terms and then divided by GDP (IFS line 99b.p.). Monthly GDP is obtained by interpolating quarterly data.

Interest rate differentials are computed as the difference between domestic and US real interest rates on deposits. Real rates are deposit rates (IFS line 60) deflated using consumer prices (IFS line 64).

The real effective exchange rate is a measure of competitiveness and rises if for example domestic inflation exceeds that abroad and the nominal exchange rate fails to depreciate to compensate.

General stock index returns are first difference of the natural logarithm of the stock index.

General index returns volatility is computed using equations (1) and (2).

Banking index returns are first difference of the natural logarithm of the banking index.

Banking index returns volatility is computed using equations (1) and (2).

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Table 1: Thailand - Estimation Results (Standard Error in Parenthesis)

Thailand	Model(1,1)	Model(2,1) REER	Model(3,1) REER M2ratio	Model(3,1) REER BANKRET
$\mu_{0}$	-0.002 (0.036)	-0.005 (0.042)	-0.119 (0.039)	0.010 (0.042)
$\mu_{1}$	9.380 (2.291)	6.983 (2.424)	6.773 (2.425)	4.227 (2.90)
$\omega$	0.023 (0.007)	0.04 (0.006)	0.034 (0.005)	0.049 (0.014)
$g$	597.844 (414.207)	525.816 (103.844)	715.100 (164.832)	488.721 (323.025)
$\alpha$	0.093 (0.045)	-0.047 (0.027)	-0.0509 (0.021)	0.168 (0.092)
$\beta$	0.804 (0.046)	0.849 (0.027)	0.873 (0.018)	0.6182 (0.072)
$p-const$	2.364 (0.268)	2.378 (0.314)	2.852 (0.538)	6.839 (3.856)
$p-REER$		-0.117 (0.066)	-0.168 (0.084)	-0.332 (0.216)
$p-M2ratio$			-0.725 (0.695)
$p-BANKRET$				0.189 (0.121)
$q-const$	1.809 (0.755)	0.929 (0.499)	1.362 (0.539)	0.226 (0.870)
$\theta$	0.237 (0.064)	0.298 (0.062)	0.272 (0.065)	0.282 (0.074)
AIC	2.6010	2.6058	2.5873	2.2849
SIC	2.7469	2.7680	2.7656	2.4636

Table 2: Thailand - Transition Probabilities

Thailand	ERDEV	Model(1,1): Transition Probabilities $(P_{t\vert t-1})$	Model(2,1) REER: Transition Probabilities $(P_{t\vert t-1})$	Model(3,1) REER M2ratio: Transition Probabilities $(P_{t\vert t-1})$	Model(3,1) REER BANKRET: Transition Probabilities $(P_{t\vert t-1})$
ordinary period average	0.078	0.02	0.03	0.03	0.02
Jun-1997	-0.35	0.01	0.14	0.37	0.82
Jul-1997	16.22	0.96	0.82	0.91	0.53
Aug-1997	6.88	0.92	0.54	0.77	0.62
Sep-1997	11.12	0.94	0.77	0.88	0.40
Oct-1997	2.99	0.83	0.50	0.72	0.17
Nov-1997	4.96	0.77	0.37	0.62	0.08
Dec-1997	14.19	0.93	0.68	0.80	0.26
Jan-1998	17.24	0.95	0.75	0.85	0.27

ERDEV - Exchange Rate Devaluation

Table 3: Singapore - Estimation Results (Standard Error in Parenthesis)

Singapore	Model(1,1)	Model(2,1) REER	Model(2,2) REER REER	Model(3,1) REER BANKRET	Model(3,1) REER BANKVOL
$\mu_{0}$	-0.141 (0.078)	-0.156 (0.081)	-0.192 (0.078)	-0.148 (0.077)	-0.135 (0.772)
$\mu_{1}$	0.348 (0.377)	0.375 (0.370)	0.450 (0.301)	0.229 (0.291)	0.208 (0.315)
$\omega$	0.725 (0.123)	0.698 (0.120)	0.677 (0.110)	0.591 (0.105)	0.626 (0.113)
$g$	6.37 (2.375)	5.723 (2.102)	4.710 (1.388)	5.741 (1.679)	5.906 (1.866)
$\alpha$	0.153 (0.147)	0.191 (0.146)	0.239 (0.126)	0.222 (0.129)	0.190 (0.133)
$p-const$	2.067 (0.336)	2.615 (0.775)	2.950 (0.895)	4.683 (3.789)	3.656 (1.794)
$p-REER$		-0.523 (0.365)	-0.590 (0.406)	-0.932 (-0.943)	-0.662 (0.508)
$p-BANKRET$				0.369 (0.295)
$p-BANKVOL$					-0.182 (0.110)
$q-const$	1.294 (0.453)	1.275 (0.431)	2.182 (1.507)	1.004 (0.335)	1.108 (0.379)
$q-REER$			0.481 (0.487)
$\theta$	0.267 (0.074)	0.256 (0.074)	0.240 (0.073)	0.282 (0.073)	0.276 (0.073)
AIC	3.1961	3.1727	3.1805	3.1668	3.1815
SIC	3.3258	3.3186	3.3426	3.3290	3.3436

Standard error in parenthesis

Table 4: Singapore - Transistion Probabilities

Singapore	ERDEV	Model(1,1): Transition Probabilities $(P_{t\vert t-1})$	Model(2,1) REER: Transition Probabilities $(P_{t\vert t-1})$	Model(2,2) REER REER: Transition Probabilities $(P_{t\vert t-1})$	Model(3,1) REER BANKRET: Transition Probabilities $(P_{t\vert t-1})$	Model(3,1) REER BANKVOL: Transition Probabilities $(P_{t\vert t-1})$
Ordinary Period Average	0.15	0.04	0.14	0.15	0.09	0.13
Jun-1997	-0.70	0.03	0.35	0.55	0.37	0.30
Jul-1997	1.39	0.08	0.57	0.57	0.56	0.50
Aug-1997	3.39	0.55	0.85	0.85	0.79	0.82
Sep-1997	1.32	0.42	0.73	0.73	0.62	0.66
Oct-1997	2.60	0.80	0.87	0.87	0.84	0.84
Nov-1997	1.27	0.66	0.75	0.75	0.67	0.68
Dec-1997	4.34	0.90	0.90	0.90	0.84	0.87
Jan-1998	5.88	0.89	0.87	0.87	0.85	0.85
Mar-2001	1.71	0.11	0.24	0.23	0.98	0.42
Apr-2001	2.23	0.17	0.33	0.35	0.83	0.49
Sep-2001	-0.57	0.61	0.68	0.88	0.87	0.73
Oct-2001	3.37	0.90	0.90	0.95	0.84	0.87

ERDEV - Exchange Rate Devaluation

Table 5: The Philippines - Estimation Results (Standard Error in Parenthesis)

The Philippines	Model(1,1)	Model(2,1) REER	Model(3,1) REER GENRET
$\mu_{0}$	0.089 (0.038)	0.088 (0.038)	0.077 (0.041)
$\mu_{1}$	0.634 (0.304)	0.637 (0.300)	0.508 (0.254)
$\omega$	0.119 (0.026)	0.119 (0.026)	0.098 (0.026)
$g$	46.545 (12.717)	45.962 (12.529)	41.347 (12.713)
$\alpha$	0.429 (0.168)	0.421 (0.167)	0.517 (0.176)
$p-const$	1.453 (0.205)	1.511 (0.238)	1.558 (0.328)
$p-REER$		-0.020 (0.034)	-0.027 (0.051)
$p-GENRET$			0.002 (0.038)
$q-const$	1.240 (0.253)	1.271 (0.253)	1.675 (0.389)
$\theta$	0.404 (0.058)	0.402 (0.0597)	0.458 (0.068)
AIC	3.2166	3.2254	3.2726
SIC	3.3463	3.3712	3.4507

Table 6: The Philippines - Transition Probabilities

The Philippines	ERDEV	Model(1,1): Transition Probabilities $(P_{t\vert t-1})$	Model(2,1) REER: Transition Probabilities $(P_{t\vert t-1})$	Model(3,1) REER GENRET: Transition Probabilities $(P_{t\vert t-1})$
ordinary period average	0.06	0.08	0.07	0.08
Oct-1990	1.57	0.61	0.61	0.76
Nov-1990	8.38	0.89	0.90	0.95
Jun-1997	0.04	0.08	0.11	0.12
Jul-1997	4.77	0.89	0.90	0.95
Aug-1997	5.83	0.82	0.83	0.92
Sep-1997	9.92	0.86	0.87	0.93
Oct-1997	6.19	0.78	0.79	0.89
Nov-1997	0.17	0.74	0.74	0.92
Dec-1997	7.40	0.89	0.90	0.95
Jan-1998	13.78	0.83	0.84	0.92
Jun-2000	1.99	0.66	0.66	0.85
Jul-2000	3.89	0.88	0.89	0.95
Aug-2000	1.26	0.76	0.77	0.89
Sep-2000	1.85	0.87	0.88	0.92
Oct-2000	5.05	0.89	0.90	0.95
Mar-2001	0.37	0.80	0.81	0.91
Apr-2001	3.49	0.82	0.83	0.90
May-2001	0.69	0.70	0.71	0.84
Jun-2001	1.86	0.81	0.82	0.87
Jul-2001	3.30	0.86	0.87	0.92

ERDEV - Exchange Rate Devaluation

Table 7: Malaysia - Estimation Results (Standard Error in Parenthesis)

Malaysia	Model(1,1)	Model(2,1) REER	Model(3,1) REER M2ratio	Model(3,1) REER BANKVOL
$\mu_{0}$	-0.20 (0.074)	0.015 (0.072)	-0.040 (0.076)	-0.025 (0.076)
$\mu_{1}$	1.101 (0.992)	1.370 (1.071)	1.232 (0.962)	2.133 (1.542)
$\omega$	0.424 (0.160)	0.531 (0.147)	0.528 (0.147)	0.445 (0.116)
$g$	37.66 (15.48)	37.716 (16.390)	34.084 (14.618)	65.055 (23.434)
$\alpha$	0.238 (0.137)	0.201 (0.140)	0.195 (0.122)	0.000 (0.000)
$\beta$	0.155 (0.142)	0.157 (0.175)	0.129 (0.166)	0.376 (0.129)
$p-const$	1.885 (0.326)	2.498 (0.519)	3.442 (1.086)	4.166 (1.571)
$p-REER$		-0.101 (0.057)	-0.124 (0.095)	-0.189 (0.099)
$p-M2ratio$			-21.184 (10.326)
$p-BANKVOL$				-0.117 (0.077)
$q-const$	0.925 (0.448)	1.209 (0.388)	1.101 (0.345)	1.462 (1.180)
$\theta$	0.261 (0.088)	0.259 (0.087)	0.271 (0.085)	0.269 (0.269)
AIC	3.3701	3.3653	3.3724	3.2960
SIC	3.5381	3.5520	3.5778	3.5148

Table 8: Malaysia - Transition Probabilities

Malaysia	ERDEV	Model(1,1): Transition Probabilities $(P_{t\vert t-1})$	Model(2,1) REER: Transition Probabilities $(P_{t\vert t-1})$	Model(3,1) REER M2ratio: Transition Probabilities $(P_{t\vert t-1})$	Model(3,1) REER BANKVOL: Transition Probabilities $(P_{t\vert t-1})$
Ordinary Period Average	0.05	0.05	0.01	0.01	0.005
Dec-1993	0.78	0.04	0.02	0.01	0.33
Jan-1994	5.30	0.82	0.88	0.86	0.93
Jun-1997	0.40	0.04	0.20	0.18	0.25
Jul-1997	1.96	0.15	0.45	0.94	0.49
Aug-1997	6.41	0.82	0.88	0.86	0.92
Sep-1997	9.40	0.78	0.86	0.84	0.91
Oct-1997	8.89	0.70	0.81	0.78	0.89
Nov-1997	2.99	0.53	0.66	0.61	0.74
Dec-1997	10.62	0.82	0.89	0.86	0.91
Jan-1998	15.68	0.77	0.86	0.84	0.92
Apr-1998	-0.53	0.37	0.50	0.45	0.63
May-1998	2.38	0.34	0.44	0.46	0.49
Jun-1998	4.35	0.57	0.69	0.71	0.67

ERDEV - Exchange Rate Devaluation

Figure 1: Thai baht Volatility

Data for Figure 1: Thai baht Volatility (Percent)

Date	Volatility
1-Nov-84
12-Dec-84	0.533131108
3-Jan-85	0.504816187
1-Feb-85	2.135899004
29-Mar-85	1.678346349
22-Apr-85	1.212405937
16-May-85	1.179411127
20-Jun-85	0.755155505
17-Jul-85	2.550633818
23-Aug-85	2.593750516
5-Sep-85	3.359144941
3-Oct-85	1.038551492
26-Nov-85	2.14847915
2-Dec-85	1.443919638
3-Jan-86	0.328954597
28-Feb-86	0.543997097
19-Mar-86	0.355719253
29-Apr-86	0.830021497
9-May-86	0.667169721
16-Jun-86	0.545025655
23-Jul-86	0.454014733
25-Aug-86	0.33652551
19-Sep-86	0.239823128
16-Oct-86	0.502956969
14-Nov-86	0.286254203
31-Dec-86	0.478366497
29-Jan-87	0.602907353
2-Feb-87	0.338342471
3-Mar-87	0.557678766
28-Apr-87	0.634471299
8-May-87	0.463921242
11-Jun-87	0.437543563
2-Jul-87	0.531682924
31-Aug-87	0.750206648
9-Sep-87	0.267750563
30-Oct-87	0.705620152
30-Nov-87	0.491305589
29-Dec-87	0.769828153
5-Jan-88	0.896306677
1-Feb-88	0.321807616
30-Mar-88	0.496955078
19-Apr-88	0.248871284
2-May-88	0.149322645
13-Jun-88	0.766789481
26-Jul-88	0.417363743
1-Aug-88	0.343240254
12-Sep-88	0.294205737
28-Oct-88	0.814011968
28-Nov-88	0.523151456
2-Dec-88	0.473138918
3-Jan-89	0.669167555
16-Feb-89	0.468853705
1-Mar-89	0.418347133
6-Apr-89	0.319285107
1-May-89	1.143167048
6-Jun-89	0.627869753
5-Jul-89	0.484655988
3-Aug-89	0.897144808
29-Sep-89	0.991834633
3-Oct-89	0.46015605
24-Nov-89	0.218052167
29-Dec-89	0.413636531
29-Jan-90	0.731799366
20-Feb-90	0.438734862
1-Mar-90	0.579794793
26-Apr-90	0.240836987
29-May-90	0.532093336
28-Jun-90	0.193711767
17-Jul-90	0.560062503
29-Aug-90	0.588414716
18-Sep-90	0.443914774
22-Oct-90	1.070809045
7-Nov-90	0.474269713
11-Dec-90	0.720160689
25-Jan-91	0.570030135
13-Feb-91	0.721877098
1-Mar-91	0.98571764
15-Apr-91	0.883667383
28-May-91	0.342436409
3-Jun-91	0.462659351
4-Jul-91	0.389683071
9-Aug-91	0.43839383
30-Sep-91	0.956746933
17-Oct-91	0.58933701
29-Nov-91	0.541073044
6-Dec-91	0.32028935
8-Jan-92	0.618620096
5-Feb-92	0.864027767
2-Mar-92	0.415897297
21-Apr-92	0.269004423
26-May-92	0.466100575
29-Jun-92	0.394590564
2-Jul-92	0.445668699
31-Aug-92	0.546651187
2-Sep-92	0.744551811
19-Oct-92	0.844832
3-Nov-92	0.665744639
22-Dec-92	0.29501368
26-Jan-93	0.294782387
19-Feb-93	0.31916002
22-Mar-93	0.246424647
26-Apr-93	0.645787871
31-May-93	0.422830347
11-Jun-93	0.696016593
1-Jul-93	0.621072545
3-Aug-93	0.398353074
7-Sep-93	0.323083876
8-Oct-93	0.644765632
1-Nov-93	0
16-Dec-93	0.615460721
26-Jan-94	0.270058312
16-Feb-94	0.394901389
30-Mar-94	0.322189434
29-Apr-94	0.347179319
4-May-94	0.273486955
29-Jun-94	0.648099802
12-Jul-94	0.301036801
24-Aug-94	0.300555525
21-Sep-94	0.225822611
27-Oct-94	0.426555007
1-Nov-94	0.351350498
1-Dec-94	0.199811112
18-Jan-95	1.655370197
23-Feb-95	0.350788559
31-Mar-95	0.707808974
19-Apr-95	0.408413384
9-May-95	0.635431391
12-Jun-95	0.203130508
3-Jul-95	0.304080048
1-Aug-95	0.830021497
4-Sep-95	0.473892181
24-Oct-95	0.274576331
23-Nov-95	0.348420237
5-Dec-95	0.124509691
1-Jan-96	0.396776676
26-Feb-96	0.372198918
6-Mar-96	0.173899001
3-Apr-96	0.223053968
9-May-96	0.346767642
19-Jun-96	0.173075647
23-Jul-96	0.370877233
1-Aug-96	0.223053968
4-Sep-96	0.29652598
1-Oct-96	0.246037642
20-Nov-96	0.295245337
6-Dec-96	0.293860829
3-Jan-97	0.874758464
26-Feb-97	0.627144718
3-Mar-97	0.217212373
1-Apr-97	0.554034459
30-May-97	2.672246072
17-Jun-97	6.304017893
1-Jul-97	17.03113386
8-Aug-97	6.378284486
9-Sep-97	4.484438288
2-Oct-97	8.0037271
10-Nov-97	5.255523037
8-Dec-97	8.377333192
1-Jan-98	10.41726004
11-Feb-98	12.17126557
30-Mar-98	9.963089046
29-Apr-98	3.812459986
5-May-98	2.801880044
19-Jun-98	4.249899765
17-Jul-98	2.570485848
4-Aug-98	2.428798112
25-Sep-98	3.33899045
30-Oct-98	4.524486265
26-Nov-98	1.985749865
11-Dec-98	2.17539173
5-Jan-99	1.967284876
15-Feb-99	1.735909788
16-Mar-99	0.819608544
30-Apr-99	1.683184924
11-May-99	0.997801867
22-Jun-99	0.850294007
6-Jul-99	1.04642179
2-Aug-99	1.903872831
6-Sep-99	4.444027048
29-Oct-99	3.05515265
4-Nov-99	1.132056458
23-Dec-99	2.509259239
3-Jan-00	1.10737464
10-Feb-00	1.292805738
23-Mar-00	0.710709291
3-Apr-00	0.61073344
1-May-00	2.053206945
5-Jun-00	0.690848016
3-Jul-00	3.244596529
4-Aug-00	0.903001754
1-Sep-00	2.78693343
2-Oct-00	2.339791511
6-Nov-00	1.327743196
25-Dec-00	2.455500408
31-Jan-01	1.816524488
1-Feb-01	1.218273213
1-Mar-01	2.527414548
2-Apr-01	0.786522555
17-May-01	0.468479322
5-Jun-01	0.512804178
2-Jul-01	0.701720155
31-Aug-01	2.318113533
17-Sep-01	0.947676871
1-Oct-01	0.420294713
30-Nov-01	1.116914134
13-Dec-01	0.854934227

Figure 2: Thai baht - Returns and Standard Deviations

Data for Figure 2: Thai baht - Returns and Standard Deviations (Percent)

Date	ERDEV	Volatility
1-Nov-84
1-Dec-84	1.900560281	0.533131108
1-Jan-85	0.882034384	0.504816187
1-Feb-85	2.243219966	2.135899004
1-Mar-85	0.392787507	1.678346349
1-Apr-85	-2.270776972	1.212405937
1-May-85	0.291226999	1.179411127
1-Jun-85	-0.437159166	0.755155505
1-Jul-85	-1.50821325	2.550633818
1-Aug-85	-0.632089853	2.593750516
1-Sep-85	0.891205304	3.359144941
1-Oct-85	-1.978783997	1.038551492
1-Nov-85	-1.099537144	2.14847915
1-Dec-85	1.626052087	1.443919638
1-Jan-86	-0.037516414	0.328954597
1-Feb-86	-0.677713437	0.543997097
1-Mar-86	-0.264800609	0.355719253
1-Apr-86	0	0.830021497
1-May-86	-0.30349037	0.667169721
1-Jun-86	0.227704083	0.545025655
1-Jul-86	-0.722848877	0.454014733
1-Aug-86	-0.382555937	0.33652551
1-Sep-86	0.076628356	0.239823128
1-Oct-86	0	0.502956969
1-Nov-86	0.610922099	0.286254203
1-Dec-86	-0.190512536	0.478366497
1-Jan-87	-0.99655865	0.602907353
1-Feb-87	-0.154202035	0.338342471
1-Mar-87	-0.774597211	0.557678766
1-Apr-87	-0.194590449	0.634471299
1-May-87	-0.194969841	0.463921242
1-Jun-87	0.544960477	0.437543563
1-Jul-87	0.696327765	0.531682924
1-Aug-87	-0.154321018	0.750206648
1-Sep-87	-0.658534241	0.267750563
1-Oct-87	0.155339837	0.705620152
1-Nov-87	-1.170973567	0.491305589
1-Dec-87	-0.946752634	0.769828153
1-Jan-88	0	0.896306677
1-Feb-88	0.31658119	0.321807616
1-Mar-88	-0.356224402	0.496955078
1-Apr-88	-0.277943399	0.248871284
1-May-88	0	0.149322645
1-Jun-88	0.436422038	0.766789481
1-Jul-88	0.945633524	0.417363743
1-Aug-88	0.156739844	0.343240254
1-Sep-88	-0.039161935	0.294205737
1-Oct-88	-0.668110168	0.814011968
1-Nov-88	-0.950878797	0.523151456
1-Dec-88	0.119355495	0.473138918
1-Jan-89	0.594649919	0.669167555
1-Feb-89	0.236873384	0.468853705
1-Mar-89	0.472070113	0.418347133
1-Apr-89	0.156862777	0.319285107
1-May-89	0.897216863	1.143167048
1-Jun-89	0.658024437	0.627869753
1-Jul-89	-0.464037956	0.484655988
1-Aug-89	0.193610903	0.897144808
1-Sep-89	0.54012477	0.991834633
1-Oct-89	-0.54012477	0.46015605
1-Nov-89	0.038677239	0.218052167
1-Dec-89	-0.426274623	0.413636531
1-Jan-90	-0.077700082	0.731799366
1-Feb-90	-0.077760502	0.438734862
1-Mar-90	0.77489733	0.579794793
1-Apr-90	0.346754345	0.240836987
1-May-90	-0.501254182	0.532093336
1-Jun-90	-0.038662285	0.193711767
1-Jul-90	-0.698489452	0.560062503
1-Aug-90	-0.468384931	0.588414716
1-Sep-90	-0.74612559	0.443914774
1-Oct-90	-1.030120044	1.070809045
1-Nov-90	-0.239234564	0.474269713
1-Dec-90	0.557326283	0.720160689
1-Jan-91	0.119024017	0.570030135
1-Feb-91	-0.397298894	0.721877098
1-Mar-91	1.30514014	0.98571764
1-Apr-91	0.470404631	0.883667383
1-May-91	0.234375107	0.342436409
1-Jun-91	0.467108673	0.462659351
1-Jul-91	-0.038842494	0.389683071
1-Aug-91	-0.116618089	0.43839383
1-Sep-91	-0.389712107	0.956746933
1-Oct-91	-0.273704961	0.58933701
1-Nov-91	-0.195963222	0.541073044
1-Dec-91	-0.43247561	0.32028935
1-Jan-92	-0.236686501	0.618620096
1-Feb-92	0.47281412	0.864027767
1-Mar-92	0.666016174	0.415897297
1-Apr-92	0.078064016	0.269004423
1-May-92	-0.390930912	0.466100575
1-Jun-92	-0.549883554	0.394590564
1-Jul-92	-0.434182644	0.445668699
1-Aug-92	-0.118741356	0.546651187
1-Sep-92	-0.237906536	0.744551811
1-Oct-92	0.198294731	0.844832
1-Nov-92	0.828570532	0.665744639
1-Dec-92	0.078554599	0.29501368
1-Jan-93	0.235294226	0.294782387
1-Feb-93	-0.156801287	0.31916002
1-Mar-93	-0.274995263	0.246424647
1-Apr-93	-0.750250311	0.645787871
1-May-93	-0.039643212	0.422830347
1-Jun-93	-0.039658934	0.696016593
1-Jul-93	0.395883336	0.621072545
1-Aug-93	-0.514954594	0.398353074
1-Sep-93	0.039706175	0.323083876
1-Oct-93	0.277502656	0.644765632
1-Nov-93	0.395101265	0
1-Dec-93	0.354261343	0.615460721
1-Jan-94	0.313848826	0.270058312
1-Feb-94	-0.589276897	0.394901389
1-Mar-94	-0.35524016	0.322189434
1-Apr-94	-0.158290496	0.347179319
1-May-94	-0.19821612	0.273486955
1-Jun-94	-0.238379136	0.648099802
1-Jul-94	-0.678509887	0.301036801
1-Aug-94	0.200040075	0.300555525
1-Sep-94	-0.160000034	0.225822611
1-Oct-94	-0.08009612	0.426555007
1-Nov-94	0.08009612	0.351350498
1-Dec-94	0.479234144	0.199811112
1-Jan-95	-0.119593397	1.655370197
1-Feb-95	-0.199640713	0.350788559
1-Mar-95	-1.044605722	0.707808974
1-Apr-95	-0.811034454	0.408413384
1-May-95	0.406339446	0.635431391
1-Jun-95	0.040543281	0.203130508
1-Jul-95	0.283343642	0.304080048
1-Aug-95	0.845245523	0.830021497
1-Sep-95	0.67905194	0.473892181
1-Oct-95	-0.039816843	0.274576331
1-Nov-95	0.198925866	0.348420237
1-Dec-95	0	0.124509691
1-Jan-96	0.515362885	0.396776676
1-Feb-96	-0.197902301	0.372198918
1-Mar-96	-0.039627502	0.173899001
1-Apr-96	0.158415875	0.223053968
1-May-96	0.039564788	0.346767642
1-Jun-96	0.276516076	0.173075647
1-Jul-96	-0.039455514	0.370877233
1-Aug-96	-0.276625349	0.223053968
1-Sep-96	0.355520817	0.29652598
1-Oct-96	0.393546356	0.246037642
1-Nov-96	-0.039285013	0.295245337
1-Dec-96	0.392157365	0.293860829
1-Jan-97	0.624270463	0.874758464
1-Feb-97	0.852057827	0.627144718
1-Mar-97	0.077101006	0.217212373
1-Apr-97	0.384615859	0.554034459
1-May-97	-0.6933772	2.672246072
1-Jun-97	-0.348499869	6.304017893
1-Jul-97	16.22085633	17.03113386
1-Aug-97	6.881695452	6.378284486
1-Sep-97	11.1193226	4.484438288
1-Oct-97	2.985296315	8.0037271
1-Nov-97	4.955381445	5.255523037
1-Dec-97	14.18617387	8.377333192
1-Jan-98	17.23730659	10.41726004
1-Feb-98	-15.37790708	12.17126557
1-Mar-98	-11.00916242	9.963089046
1-Apr-98	-4.579441396	3.812459986
1-May-98	-0.839379213	2.801880044
1-Jun-98	7.88040983	4.249899765
1-Jul-98	-2.800901229	2.570485848
1-Aug-98	0.942377398	2.428798112
1-Sep-98	-2.854200334	3.33899045
1-Oct-98	-5.781367892	4.524486265
1-Nov-98	-4.504783092	1.985749865
1-Dec-98	-0.550056392	2.17539173
1-Jan-99	0.987933392	1.967284876
1-Feb-99	1.194368161	1.735909788
1-Mar-99	1.206934324	0.819608544
1-Apr-99	0.23964863	1.683184924
1-May-99	-1.662682444	0.997801867
1-Jun-99	-0.297901371	0.850294007
1-Jul-99	0.48701395	1.04642179
1-Aug-99	2.321032564	1.903872831
1-Sep-99	4.914171981	4.444027048
1-Oct-99	-0.95863499	3.05515265
1-Nov-99	-1.867778488	1.132056458
1-Dec-99	-1.483050468	2.509259239
1-Jan-00	-2.280056354	1.10737464
1-Feb-00	0.960776006	1.292805738
1-Mar-00	0.529802564	0.710709291
1-Apr-00	0.18476975	0.61073344
1-May-00	2.525847078	2.053206945
1-Jun-00	0.333718703	0.690848016
1-Jul-00	2.879714019	3.244596529
1-Aug-00	1.654562995	0.903001754
1-Sep-00	2.419668012	2.78693343
1-Oct-00	3.130035494	2.339791511
1-Nov-00	1.220510257	1.327743196
1-Dec-00	-1.452475103	2.455500408
1-Jan-01	0.046436035	1.816524488
1-Feb-01	-1.143936835	1.218273213
1-Mar-01	2.89271587	2.527414548
1-Apr-01	3.518570247	0.786522555
1-May-01	0.06604293	0.468479322
1-Jun-01	-0.529568757	0.512804178
1-Jul-01	0.815251844	0.701720155
1-Aug-01	-1.548018529	2.318113533
1-Sep-01	-1.323631215	0.947676871
1-Oct-01	0.876902752	0.420294713
1-Nov-01	-0.673856997	1.116914134
1-Dec-01	-1.15608224	0.854934227

ERDEV - Exchange Rate Devaluation

Figure 3: Thailand

These panels show the evolution of a number of Thai indicators over the period November 1984 to July 2001 (stock market and banking sector data start in January 1987). REER is the percentage deviation of real effective exchange rate from its trend; IRDIFF is the domestic/U.S. interest rate differential on deposits; ERDEV is the exchange rate change computed using end of the month log-first difference; RDC is the deviation of the ratio between real domestic credit and GDP from its trend; M2ratio is the deviation of the ratio of M2 over reserves from its trend; GENRET and GENVOL are stock index returns and volatility, respectively; BANKRET and BANKVOL are returns and volatility of a stock indexed based on a portfolio of banks listed in the stock market.

Data for Figure 3: Thailand

OBS	ERDEV	REER	M2ratio (Right axis)	RDC	IRDIFF	Bank Index	General Index	BANKRET	GENRET	BANKVOL (Right axis)	GENVOL (Right axis)
1984:11	14.46648374	-1.3853586	-2.051477026	-0.251588333	8.109624393	0	0
1984:12	1.900560281	-0.17081391	-0.920540801	0.025550582	8.786429846	0	0
1985:01	0.882034384	0.94382703	-0.082617139	-0.018169663	8.754341559	0	0
1985:02	2.243219966	2.5586722	0.752380688	0.040037482	8.613109511	0	0
1985:03	0.392787507	2.7737642	0.569949235	0.091988943	8.589186997	0	0
1985:04	-2.270776972	3.8889679	0.235568692	-0.005260849	8.592532387	0	0
1985:05	0.291226999	4.8039554	0.275045659	-0.120993306	9.214002523	0	0
1985:06	-0.437159166	5.3181289	-0.887372053	0.016401749	9.225828913	0	0
1985:07	-1.50821325	5.3305569	0.079667448	0.063519795	9.251384123	0	0
1985:08	-0.632089853	5.2399387	0.595243454	0.181433399	9.204810032	0	0
1985:09	0.891205304	5.9446033	-0.8260283	0.018650429	9.15643929	0	0
1985:10	-1.978783997	3.4425159	0.605786643	0.049557555	9.096684283	0	0
1985:11	-1.099537144	4.2312288	1.653767138	0.257407999	9.203386455	0	0
1985:12	1.626052087	1.5080553	-0.015325377	0.336559663	9.249890388	0	0
1986:01	-0.037516414	1.0700149	0.083528803	0.386081913	6.272815153	0	0
1986:02	-0.677713437	-0.88597777	0.241237245	0.435906992	6.244179769	0	0
1986:03	-0.264800609	-2.5630823	-0.021423309	0.284002675	4.547397797	0	0
1986:04	0	-2.7643966	-0.105839643	0.194036971	5.199768315	0	0
1986:05	-0.30349037	-4.3928409	-0.070225159	-0.046616084	5.169674992	0	0
1986:06	0.227704083	-3.3511433	0.323094293	-0.05200365	5.229040837	0	0
1986:07	-0.722848877	-4.5417267	0.567416238	-0.072166379	5.231798313	0	0
1986:08	-0.382555937	-4.6667815	0.522602664	-0.126381635	6.579669257	0	0
1986:09	0.076628356	-4.5281827	0.150383698	-0.21262893	6.574244333	0	0
1986:10	0	-4.6274811	0.114724912	-0.176953894	6.524249362	0	0
1986:11	0.610922099	-3.6659129	0.297775325	-0.089245042	6.545851983	0	0
1986:12	-0.190512536	-2.9443934	0.246150022	-0.01479624	6.580118422	0	0
1987:01	-0.99655865	-4.0635829	-0.026346693	-0.01505476	6.598252533	96.91	0			3.117515167
1987:02	-0.154202035	-3.9239375	0.662289803	0.042887675	6.642286956	94.67	0	-2.338555261		3.168515461
1987:03	-0.774597211	-2.6256308	-0.066073703	0.03505898	6.661071529	99.08	0	4.553044448		3.860135373
1987:04	-0.194590449	-3.9685642	-0.359363748	-0.000888236	6.644356333	105.87	0	6.628432173		4.489865845
1987:05	-0.194969841	-3.9524567	-0.435663125	-0.165296915	6.597783668	111.75	0	5.405230714		5.726283553
1987:06	0.544960477	-2.8767516	-0.574593502	-0.165667972	6.546145866	120.36	0	7.422301827		4.572324912
1987:07	0.696327765	-1.7406178	-0.696855425	-0.225495091	6.549060849	123.92	313.93	2.914894435		9.167127735	7.332808862
1987:08	-0.154321018	-1.0430245	-0.556358161	-0.238385387	6.508848255	139.72	353.15	12.00042238	11.77228647	5.607760848	6.398757706
1987:09	-0.658534241	-0.98281978	-0.079990415	-0.24321139	5.80222396	155.11	428.19	10.44941227	19.26741265	6.043421132	11.49823407
1987:10	0.155339837	-0.55877953	-0.195917654	-0.152977674	5.848888664	118.39	299.83	-27.01502832	-35.63513749	22.4443779	28.54947549
1987:11	-1.170973567	-1.1696113	0.375423231	-0.135313832	5.741455618	120.81	292.385	2.023480411	-20.01600573	8.506044981	19.83354246
1987:12	-0.946752634	-2.5139838	0.528725074	0.083008185	5.738328718	114.69	284.94	-5.198622716	-4.396873971	7.624034969	11.11760943
1988:01	0	-1.9904846	0.303861297	0.074041037	5.798268068	122.23	318.78	6.367167941	11.22225779	7.470137738	9.534440176
1988:02	0.31658119	-1.0975266	0.0750819	0.021219858	5.701173558	135.96	374.83	10.6456209	16.19713802	8.067198763	10.88363919
1988:03	-0.356224402	-1.8333846	0.218158557	0.02835559	5.671210972	130.87	388.9	-3.815626076	3.684965131	4.53450572	5.079911155
1988:04	-0.277943399	-1.596257	0.339222235	-0.000361194	5.673059944	132.64	413.91	1.343422732	6.232631773	2.273086276	5.188669018
1988:05	0	-1.684215	0.23840796	-0.018868684	5.672911373	131.71	424.93	-0.703615538	2.627589059	1.402018099	2.136868813
1988:06	0.436422038	-0.095219001	0.214070199	-0.001110467	5.681155904	132.7	452.7	0.748840533	6.330520497	1.501721271	4.674720794
1988:07	0.945633524	1.3728877	0.267954682	0.007351202	5.713847195	135.32	457.01	1.955140257	0.947561805	4.421006566	2.507316769
1988:08	0.156739844	2.1222684	0.194203537	-0.065992405	5.030487397	131.31	436.55	-3.008140404	-4.580235624	4.433626067	5.499214618
1988:09	-0.039161935	2.7549908	0.126848652	-0.131568155	4.961475954	130.18	444.61	-0.864283173	1.829457715	1.951517773	1.77631253
1988:10	-0.668110168	1.2729757	-0.045588412	-0.126452322	4.94126386	126.98	418.74	-2.48885144	-5.994729115	1.646244427	4.064551949
1988:11	-0.950878797	-0.62204793	-0.024698989	-0.023848282	4.984793075	121.63	392.86	-4.304594411	-6.379688795	3.06412132	4.735587124
1988:12	0.119355495	-0.52843916	0.135291993	0.146296505	5.022416973	119.89	386.73	-1.440899391	-1.572653918	4.254627843	5.77952905
1989:01	0.594649919	0.15548598	-0.153105036	0.056718572	4.978769375	127.03	433.68	5.784862332	11.45801598	5.13603716	6.658687805
1989:02	0.236873384	0.43144819	-0.337459988	0.040422124	4.22916996	124.04	435.78	-2.38191848	0.483059389	1.903269668	2.161616625
1989:03	0.472070113	1.3011574	-0.398535212	0.031285265	4.2793706	120.57	440.88	-2.83735971	1.163520073	2.418120847	1.69258328
1989:04	0.156862777	0.66629347	-0.346453899	0.059049752	4.30056441	125.68	500.21	4.150849682	12.62552807	3.813519601	7.814602409
1989:05	0.897216863	2.5284461	-0.318241767	0.008934422	4.256448771	122.92	522.54	-2.220525669	4.367352569	1.432306094	5.997309256
1989:06	0.658024437	4.4891585	-0.192350704	-0.050966421	4.218247702	122.01	606.21	-0.743072868	14.85249248	1.469735018	5.542063834
1989:07	-0.464037956	2.8497984	-0.185962847	-0.183342249	4.058351291	127.63	624.13	4.503244441	2.913221931	3.208680572	2.25684887
1989:08	0.193610903	3.0114218	-0.265809342	-0.311774775	3.95066524	123.16	681.92	-3.565112994	8.855366891	2.239013017	6.385072321
1989:09	0.54012477	2.8748868	-0.351416757	-0.287273962	3.922285945	127.53	689.51	3.486730798	1.106885148	3.813273709	3.411504814
1989:10	-0.54012477	1.3408424	-0.186260373	-0.269970973	3.898062671	127.38	695.01	-0.11768861	0.794503356	2.365589449	4.049088863
1989:11	0.038677239	0.5097378	-0.088493472	-0.176875649	3.940969357	129.72	769.83	1.82035365	10.22434773	2.097405828	7.617923801
1989:12	-0.426274623	-0.11807078	-0.082898982	-0.015736583	4.019624434	132.5	870.49	2.120436399	12.28865602	1.356608101	7.756965733
1990:01	-0.077700082	-1.1422625	-0.263267799	0.05395971	4.029373776	130.59	853.72	-1.452000119	-1.945300032	3.050692537	5.163390551
1990:02	-0.077760502	-1.2625085	-0.319099683	-0.064253636	3.940439505	128.74	813.67	-1.426777761	-4.804839278	2.991100711	6.637506754
1990:03	0.77489733	0.8215997	-0.259420217	0.040669759	5.874348891	125.36	851.53	-2.660526858	4.547985303	2.501907867	5.763219745
1990:04	0.346754345	0.810558	-0.118160741	0.142499774	6.443779665	124.38	855.97	-0.784820237	0.520059737	1.718087041	1.809533006
1990:05	-0.501254182	-0.095194662	-0.10272812	0.137397826	6.361964122	136.73	1000.71	9.466678265	15.62296983	11.29533638	10.1367527
1990:06	-0.038662285	-0.19527563	-0.14804166	0.116445174	6.369378853	165.62	1060.22	19.16878293	5.776668569	11.96643835	5.030957514
1990:07	-0.698489452	-0.68929565	-0.194013923	0.169564039	7.628693666	224.57	1114.61	30.4491455	5.002813418	18.40985775	6.440284573
1990:08	-0.468384931	-1.6768519	-0.199684263	0.190860517	7.65147276	204.29	862.75	-9.464690959	-25.61348849	23.06491908	30.90825155
1990:09	-0.74612559	-1.6574937	0.03425744	0.316155052	8.908716575	154.52	641.56	-27.92170152	-29.62222515	19.28063043	24.07559561
1990:10	-1.030120044	1.8693461	-0.044588561	0.1993943	9.238510895	150.66	649.37	-2.52978954	1.209995164	7.98713867	6.611758126
1990:11	-0.239234564	1.4043496	0.071650029	0.249530857	9.797387614	135.91	544.3	-10.30327404	-17.65020967	7.524752248	13.30605477
1990:12	0.557326283	1.8480695	0.210703528	0.390892294	11.68589402	144.26	612.86	5.962432511	11.86359594	4.505666643	8.061829622
1991:01	0.119024017	1.5009604	0.026514509	0.297540627	11.69938153	153.86	658.47	6.442587096	7.17824372	6.533024318	7.685278335
1991:02	-0.397298894	0.76334905	-0.022736962	0.273907278	11.54132544	179.83	769.13	15.59688621	15.53410439	13.82025948	12.45954712
1991:03	1.30514014	2.8354577	0.142319439	0.277925413	10.94057885	183	863.54	1.747419266	11.57802137	3.076769949	7.357775814
1991:04	0.470404631	2.9174557	0.068618355	0.137569772	10.06603315	180.76	876.01	-1.23159683	1.433728678	3.819467788	3.935143671
1991:05	0.234375107	2.4093154	0.011522222	0.0100885	9.96951662	169.53	808.19	-6.414028223	-8.0580327	4.886447235	6.519919476
1991:06	0.467108673	3.3108066	-0.06886975	-0.106427742	11.15500672	158.67	765.21	-6.620332856	-5.464687343	4.516951759	5.739606335
1991:07	-0.038842494	3.5215319	-0.193470282	-0.083746468	11.83210272	154.81	728.7	-2.462801519	-4.888818128	5.176419476	9.23601808
1991:08	-0.116618089	2.5408638	-0.113313288	-0.144817394	12.30371379	145.76	705.65	-6.023712504	-3.214276082	6.173938889	9.247945879
1991:09	-0.389712107	1.2679303	-0.147981647	-0.190696872	9.164675007	138.7	670.79	-4.964810619	-5.06632416	3.910077929	5.64920504
1991:10	-0.273704961	0.30168303	0.014915405	-0.238946918	7.900327096	140.11	638.84	1.011450106	-4.880209048	2.115057507	5.079641284
1991:11	-0.195963222	-0.65901452	0.067147254	-0.186144384	8.511918172	154.19	671.07	9.57577798	4.921942165	9.110949007	4.422414911
1991:12	-0.43247561	-1.6153198	0.088560636	-0.056498012	9.663408021	191.97	711.36	21.91535016	5.830517734	13.01412754	4.34104516
1992:01	-0.236686501	-1.8683444	0.050598503	-0.1327985	7.848976662	195.27	763.45	1.704410643	7.066900385	5.949396083	5.863659076
1992:02	0.47281412	-1.0190878	0.02318559	-0.171717179	7.816462977	230.39	782.85	16.53903088	2.509347213	16.55370563	4.213120306
1992:03	0.666016174	-0.16841982	0.160805358	-0.098633946	6.702515859	247.08	822.72	6.993864573	4.967481732	8.59603008	3.075178652
1992:04	0.078064016	-0.51713938	0.072950215	-0.229843197	4.919038038	229.06	760.97	-7.572819286	-7.802198881	6.0194627	5.957624784
1992:05	-0.390930912	-1.1660338	-0.009472867	-0.430357879	4.796984503	228.26	688.84	-0.349864784	-9.958491183	8.128167945	9.301297521
1992:06	-0.549883554	-1.5158543	-0.058929617	-0.462232057	5.342889298	232.07	751.45	1.655372017	8.699564994	4.180355839	6.988345557
1992:07	-0.434182644	-2.5672715	0.101424007	-0.514536277	7.013204349	230.55	744.42	-0.657129164	-0.93992817	1.966590463	2.448414212
1992:08	-0.118741356	-3.3208503	0.037040484	-0.545514152	6.93764835	237.97	746.51	3.167685665	0.280362105	2.956094138	1.749486253
1992:09	-0.237906536	-3.5769777	0.012680933	-0.622275939	6.938775884	285.86	847	18.33575652	12.62916819	12.12033897	9.105192743
1992:10	0.198294731	-3.1358098	0.003265896	-0.602628967	6.966310618	356.02	940.35	21.94847286	10.45514517	12.40739696	5.62060753
1992:11	0.828570532	-0.59725448	0.139235894	-0.452538798	7.024201599	349.08	865.21	-1.968578675	-8.327989435	4.819309632	9.001762442
1992:12	0.078554599	-0.36100178	0.18820416	-0.328019077	7.633026146	365.7	893.42	4.651220286	3.208454302	2.550004381	3.915891285
1993:01	0.235294226	-0.026700278	0.07444027	0.003093955	7.612993288	458.66	974.48	22.64958697	8.684720034	16.23523389	7.40441948
1993:02	-0.156801287	0.40602651	0.159546082	0.453550114	7.5362063	468.85	937.65	2.197369303	-3.852725035	7.531133719	3.931470212
1993:03	-0.274995263	-0.16244308	0.105342192	1.040483232	7.547328956	429.54	865.23	-8.756801923	-8.03813775	6.575368274	5.186901069
1993:04	-0.750250311	-0.83175889	0.109351643	0.598349539	7.470796905	465.57	845.29	8.054759272	-2.33156038	8.621124284	4.017750414
1993:05	-0.039643212	-1.0015595	0.083213106	0.180470024	7.446648935	443.17	825.71	-4.930901774	-2.343614146	4.653219001	4.102857296
1993:06	-0.039658934	-0.071425688	0.013058759	-0.024898738	7.414383416	459.22	877.52	3.557595445	6.085612482	6.274723712	6.637455577
1993:07	0.395883336	0.65913125	0.046844951	-0.324145898	7.348805818	471.02	928.2	2.53711579	5.61474797	2.726615058	2.961135431
1993:08	-0.514954594	0.19060502	0.094612756	-0.221497799	5.122859737	474.48	963.18	0.731891157	3.699308341	2.357204801	1.644005392
1993:09	0.039706175	-0.57655643	-0.007075595	-0.34415829	5.057798117	480.37	971.44	1.233717277	0.853919653	2.627660999	2.156323087
1993:10	0.277502656	0.45808158	0.026848892	-0.003504828	5.077964185	604.45	1268.34	22.97623134	26.66847311	13.76611045	15.37806717
1993:11	0.395101265	2.3949938	0.151341026	0.592165098	5.100869637	645.16	1309.95	6.51793944	3.228000967	7.966455122	4.511164335
1993:12	0.354261343	2.2346231	0.213337185	1.076518938	4.512307701	761.11	1682.85	16.5279546	25.04998161	8.963588915	14.21381498
1994:01	0.313848826	2.9772461	0.158390393	0.52396626	3.956045318	705.65	1493.45	-7.56585302	-11.9399905	12.76648067	14.19301402
1994:02	-0.589276897	2.0229843	0.070845095	0.061637975	3.906249271	622.38	1372.93	-12.55685252	-8.414173747	7.415181491	5.317270958
1994:03	-0.35524016	0.97175229	0.011298427	-0.393364293	4.393022667	566.78	1239.99	-9.357961729	-10.18438272	7.910441331	8.392554536
1994:04	-0.158290496	0.52332425	0.052089228	-0.032083493	4.397235021	583.11	1266.67	2.840462642	2.128809457	6.27695788	5.807296065
1994:05	-0.19821612	0.077406885	-0.020689461	0.324320347	5.413231279	653.38	1356.87	11.37830418	6.878916707	9.735137227	7.746618143
1994:06	-0.238379136	-0.066329441	-0.086800425	0.692401798	5.350306822	645.67	1273.34	-1.187035223	-6.353720717	5.963511128	6.388560986
1994:07	-0.678509887	-0.90821975	-0.086800616	0.374999748	5.886724226	728.95	1376.88	12.13166052	7.817670044	8.607833509	4.82178036
1994:08	0.200040075	0.051405548	-0.044840022	-0.024133432	5.832915194	829.9	1524.83	12.97000691	10.20628585	8.517527444	5.364855771
1994:09	-0.160000034	-0.98772089	-0.105650749	-0.272009899	5.762643876	798.01	1485.71	-3.91840829	-2.599015596	3.171062505	2.654060767
1994:10	-0.08009612	-1.62587	-0.062193192	-0.132526754	5.765371895	837.82	1528.83	4.868215157	2.860996451	7.155308341	4.270282089
1994:11	0.08009612	-1.263244	0.024362042	0.170824806	5.967177778	774.53	1362.44	-7.85468865	-11.52255271	7.305162801	8.909470502
1994:12	0.479234144	-0.69993249	0.089058335	0.604725527	5.610904156	811.24	1360.09	4.630754751	-0.172633586	6.656509964	4.404799222
1995:01	-0.119593397	-0.835937	0.143381192	0.362722906	5.544704842	738.84	1217.74	-9.348255257	-11.05541922	7.651820609	8.936471142
1995:02	-0.199640713	-1.4712107	0.143169272	0.148863884	5.53318934	760.7	1288.47	2.915767329	5.645878615	4.134572876	4.48495264
1995:03	-1.044605722	-3.5056485	0.204035925	-0.011012027	6.533803266	712.75	1216.68	-6.510833421	-5.732963018	7.303703716	7.871895994
1995:04	-0.811034454	-5.7390434	0.057608995	-0.034661803	5.946341919	744.73	1208.69	4.389100879	-0.658870927	4.199315184	2.64257532
1995:05	0.406339446	-5.1709448	-0.039641866	-0.011867093	6.839231527	877.9	1392.31	16.45109553	14.14271098	10.43185115	7.078332168
1995:06	0.040543281	-4.5005034	-0.133509807	-0.047482893	6.773270159	890.53	1394.77	1.428409917	0.176528886	3.225305798	1.63465818
1995:07	0.283343642	-3.0265112	-0.065147451	-0.166966052	6.726502724	868.14	1383.1	-2.546379912	-0.840217048	5.571361474	4.271693901
1995:08	0.845245523	-0.64744734	-0.045669626	-0.239617532	6.635999659	850.07	1314.9	-2.103429294	-5.056673954	4.092319412	3.218493324
1995:09	0.67905194	-0.26158088	-0.174491343	-0.3754652	6.527720709	864.21	1294.23	1.649709579	-1.58446934	3.878170809	2.998775302
1995:10	-0.039816843	-0.16713594	-0.107196336	0.118110126	6.454512838	874.91	1270.76	1.23052291	-1.830077703	3.502332321	2.765133387
1995:11	0.198925866	-0.26231847	-0.132788912	0.745759813	6.451104716	850.83	1196.62	-2.790868029	-6.011423083	3.956561878	4.676944243
1995:12	0	0.75467722	-0.117186503	1.518058356	6.447743867	905.91	1280.81	6.272761972	6.799177443	3.494213231	2.897725707
1996:01	0.515362885	1.585675	-0.162474688	0.66094796	6.412549746	1100.39	1410.33	19.4479978	9.633102927	12.18791704	3.985342709
1996:02	-0.197902301	1.5324463	-0.182277058	0.062545171	5.652082148	995.82	1321.87	-9.985342304	-6.477631882	5.762259301	4.268186267
1996:03	-0.039627502	2.0966526	-0.173972651	-0.508970066	5.638893903	1004.07	1289.73	0.825050058	-2.46145066	3.654699265	3.803013739
1996:04	0.158415875	2.1798487	-0.169653019	-0.622934809	5.609458718	1029.02	1292.61	2.454515305	0.223053602	4.734971474	3.054248119
1996:05	0.039564788	1.8834441	-0.164029964	-0.676005049	4.632203046	1051.83	1311.91	2.192461129	1.482066045	2.734931086	2.904323413
1996:06	0.276516076	2.2086965	-0.236359542	-0.77331638	4.626313888	1003.22	1247.08	-4.73166774	-5.0679272	3.95378184	3.521144231
1996:07	-0.039455514	2.7567333	-0.205288994	-1.024574821	4.618535363	862.59	1064.04	-15.10306146	-15.87318344	10.7283833	10.99943505
1996:08	-0.276625349	3.3285283	-0.199849587	-1.293302996	4.535409363	918.33	1102.32	6.261731186	3.534406551	3.463059511	3.97798101
1996:09	0.355520817	4.2248636	-0.214517104	-1.360437341	4.534067166	930.95	1099.01	1.364876699	-0.300727514	6.150505448	7.052598915
1996:10	0.393546356	4.8462906	-0.262658379	-1.287711307	4.500481473	713.37	910.33	-26.62053502	-18.83578824	16.14271966	11.38099413
1996:11	-0.039285013	6.0930671	-0.195211549	-1.151386052	4.468140302	741.12	925.97	3.816233561	1.703466558	7.993771955	5.782478705
1996:12	0.392157365	7.8651142	-0.058563901	-0.888623778	3.540926579	630.53	831.57	-16.16018199	-10.75263564	9.113376453	7.499593318
1997:01	0.624270463	11.06193	-0.167904213	-0.757494632	4.228019008	592.82	788.04	-6.166992395	-5.376663031	7.573987432	5.446196516
1997:02	0.852057827	11.482467	-0.076105989	-0.385612588	4.203992823	545.9	727.56	-8.245500282	-7.985238012	8.424963176	5.772742597
1997:03	0.077101006	11.624908	-0.011490468	0.183795692	4.16902954	545.92	705.43	0.003663608	-3.088892391	6.056130967	3.914851362
1997:04	0.384615859	11.48664	0.106507252	-0.013005475	3.930889272	530.59	661.29	-2.848284993	-6.461507312	5.956679792	5.315382066
1997:05	-0.6933772	11.264242	0.648555095	-0.209706706	3.663102857	468.04	566.39	-12.54358326	-15.4909586	10.44913156	10.54446888
1997:06	-0.348499869	11.053496	0.872806063	-0.257622613	3.654484644	391.4	527.28	-17.88237074	-7.155117011	19.89863948	12.05427793
1997:07	16.22085633	-1.3506005	0.497481859	0.442615301	5.633769245	530.4	665.62	30.39013839	23.29872204	22.03073623	11.38967627
1997:08	6.881695452	-1.8538147	1.056570797	0.400427389	5.375142989	369.35	502.23	-36.18867349	-28.1660755	23.09356882	17.4807773
1997:09	11.1193226	-8.1618215	-0.055168551	0.597725751	5.345293072	410	544.54	10.44124557	8.088321947	15.90098669	9.240168226
1997:10	2.985296315	-8.580167	-0.336192863	0.553395814	5.274729987	318.16	447.21	-25.36027588	-19.69131186	18.24397001	13.36059093
1997:11	4.955381445	-9.2138302	0.190527817	0.053142874	5.1900765	273.61	395.47	-15.08506661	-12.2953352	22.8036168	13.81875189
1997:12	14.18617387	-15.167194	-0.441696828	0.313652849	5.184193311	235.06	372.69	-15.18629341	-5.932795609	15.83687579	7.385441267
1998:01	17.23730659	-23.444003	-0.938219057	0.823479342	5.081559038	296.27	495.23	23.14304	28.42753262	32.62125778	23.72027628
1998:02	-15.37790708	-13.346946	-0.351117829	0.13392824	5.654180351	319.23	528.42	7.46406454	6.486912093	9.470205544	9.011170995
1998:03	-11.00916242	-6.2770865	-0.167003891	-0.120197981	5.547650858	263.55	459.11	-19.16687428	-14.06015893	14.53314485	10.13684571
1998:04	-4.579441396	-3.6345586	-0.250544897	0.12570124	5.484012647	231.43	412.13	-12.99656513	-10.79509992	7.38818715	6.417168622
1998:05	-0.839379213	-2.1190619	0.097919789	0.517074825	5.437207445	165.92	325.59	-33.27717075	-23.56999124	20.85337428	13.00934137
1998:06	7.88040983	-5.4300435	-0.036791709	1.32628209	5.182733635	114.52	267.33	-37.07562643	-19.71550708	22.5806924	13.39846898
1998:07	-2.800901229	-3.3668032	0.118714247	0.901513405	6.822801211	98.34	266.72	-15.23186182	-0.228443129	19.73095555	7.658075607
1998:08	0.942377398	-2.7282635	-0.080555698	0.781554922	5.148261443	73.75	214.53	-28.77498668	-21.77498303	16.80945285	12.26050004
1998:09	-2.854200334	-2.8131134	0.194973001	0.487257782	2.507898886	92.25	253.82	22.38212877	16.81757657	23.27717368	13.1049385
1998:10	-5.781367892	-2.2198523	0.280713954	0.192763499	1.942551239	153.92	331.29	51.1930704	26.63687703	37.1338533	21.14086568
1998:11	-4.504783092	2.0532157	0.423709481	-0.174437708	1.37200789	212.16	362.82	32.09077201	9.091271879	24.63582927	10.05223619
1998:12	-0.550056392	1.1079408	0.372552753	-0.191028138	0.771612176	208.6	355.81	-1.692216443	-1.9509963	10.91612745	4.157854834
1999:01	0.987933392	0.54603044	0.403577491	-0.002036477	0.762617526	197.47	363	-5.48318685	2.000595375	13.1156654	7.582872182
1999:02	1.194368161	0.069115165	0.436591175	0.079798197	0.147101723	179.77	340.94	-9.390841801	-6.269632554	15.09292682	8.43473472
1999:03	1.206934324	0.37878766	0.192062678	0.471753686	-0.039310541	195	352.01	8.132130251	3.195307556	13.49094952	6.855047676
1999:04	0.23964863	0.67663576	0.148624828	0.75657268	0.010087136	283.56	459.35	37.44241824	26.61528624	22.90368003	16.90694139
1999:05	-1.662682444	2.564221	0.188613853	1.15666374	0.026229936	276.19	453.6	-2.633470632	-1.25966943	9.298810283	8.027049413
1999:06	-0.297901371	3.443058	0.064458946	1.221521345	-0.17809841	279.26	521.77	1.105421284	14.00111253	8.865705246	10.48672282
1999:07	0.48701395	3.7144832	-0.012366215	0.794845714	-0.379403578	213.05	456.81	-27.06163676	-13.29593282	19.00476595	9.705214741
1999:08	2.321032564	0.67959399	-0.094432328	0.424401263	-0.612026231	198.36	440.27	-7.144331832	-3.687937444	13.58032224	8.421724713
1999:09	4.914171981	-3.6607702	-0.277661303	0.262032244	-0.597219323	174.31	389.49	-12.92482384	-12.2549984	11.91070562	9.556060039
1999:10	-0.95863499	-2.4058171	-0.21100843	0.127822915	-0.595339549	179.55	395.55	2.961839745	1.543901043	9.081534391	6.478993749
1999:11	-1.867778488	-1.1545003	-0.09226364	0.028424299	-1.236313385	190.22	422.12	5.772757638	6.501243234	9.708185036	6.163715098
1999:12	-1.483050468	0.49439372	-0.229053398	-0.367594239	-1.451605062	230.84	481.92	19.35435328	13.24884914	14.42341026	9.630277382
2000:01	-2.280056354	3.2421587	0.115108518	-0.336064908	-1.649812541	231.28	477.57	0.190426787	-0.906737914	9.738187174	7.326607455
2000:02	0.960776006	4.6900541	0.196553595	-0.266724169	-1.858527292	159.71	374.32	-37.0269427	-24.35996995	22.52212852	14.84667916
2000:03	0.529802564	4.539114	0.122851823	-0.159159256	-2.04487612	174.75	400.32	8.999671045	6.715318072	10.38030803	6.541070429
2000:04	0.18476975	3.390047	0.138578029	0.142196852	-2.031047804	174.66	390.4	-0.051515413	-2.509237274	4.432438927	4.578348136
2000:05	2.525847078	3.3432464	0.071768194	0.370962206	-2.474057996	133.65	323.29	-26.76167844	-18.86221013	20.29520042	14.21188586
2000:06	0.333718703	2.6988701	0.049238531	0.033499252	-2.450400952	131.91	325.69	-1.310457072	0.739625548	7.51646776	5.426783919
2000:07	2.879714019	1.5568438	-0.003290848	-0.027509902	-2.646026581	105.53	284.67	-22.31245992	-13.46153941	12.67657793	8.614454255
2000:08	1.654562995	1.2169058	-0.04867828	-0.223727089	-2.662286831	115.19	307.83	8.758766626	7.821706789	9.451422997	6.437705398
2000:09	2.419668012	0.27868621	-0.103894673	-0.700054277	-2.844506047	104.77	277.29	-9.481546757	-10.44837926	8.42699479	7.851100852
2000:10	3.130035494	-1.1582692	-0.132012939	-0.57109155	-2.8242541	108.3	271.84	3.313768264	-1.985023202	7.030654114	6.206393025
2000:11	1.220510257	-1.5944341	-0.165708339	-0.665544827	-2.824999686	110.18	277.92	1.721023804	2.211964457	6.26773799	4.659005057
2000:12	-1.452475103	-0.93020177	-0.117872384	-0.828872547	-2.826221342	109.45	269.19	-0.664756808	-3.191585251	1.551224837	2.094014852
2001:01	0.046436035	-1.1658547	-0.086546791	-0.634467582	-1.928435222	151.82	332.77	32.72277846	21.20341107	23.33067212	13.91752984
2001:02	-1.143936835	0.1983891	-0.055809071	-0.459795201	-2.325640234	148.25	325.2	-2.379557071	-2.301118298	7.545331034	4.89007768
2001:03	2.89271587	-0.33760723	-0.035072124	-0.230086305	-1.883402502	121.53	291.94	-19.8738892	-10.7892076	10.10774959	6.053982713
2001:04	3.518570247	-1.473996	-0.108935306	-0.157698265	-1.452488644	122.24	300.63	0.582517954	2.933197104	6.728994466	4.847836791
2001:05	0.06604293	-1.1108983	-0.087378184	-0.195226331	-1.015651959	122.37	310.13	0.106291658	3.111129167	6.013753018	3.805388648
2001:06	-0.529568757	0.45165314	-0.009093403	-0.003803114	-0.79055775	119.84	322.55	-2.089172223	3.926659857	3.778680933	3.347032131
2001:07	0.815251844	-1.1862878	-0.063134819	0.065168402	-0.798392243	101.2	297.69	-16.90587629	-8.020548638	10.49475486	5.848357661
2001:08	-1.548018529	0.075302698	-0.074649712	0.055644449	-0.580749215	119.07	335.57	16.26127986	11.97779019	10.32703666	7.468704679
2001:09	-1.323631215	0.0365264	0.008926083	-0.031479878	-0.147901884	89.27	277.04	-28.80460703	-19.16686784	20.07982294	14.77457808
2001:10	0.876902752	-0.10251871	-0.044151747	-0.062253606	0.282702565	91.08	275.09	2.0072756	-0.706358324	6.01229662	3.294249536
2001:11	-0.673856997	0.45826283	-0.005532861	-0.023249913	0.713770897	106.14	302.62	15.30207362	9.537957617	11.92322326	8.266748679
2001:12	-1.15608224	1.0189736	0.08932076	-0.002231358	0.930378247	105.91	303.85	-0.216930054	0.405626556	4.338876529	2.594503671

ERDEV - Exchange Rate Devaluation

Figure 4: Singapore

These panels show the evolution of a number of Singaporean indicators over the period November 1984 to July 2001 (stock market data start in January 1985). REER is the percentage deviation of real effective exchange rate from its trend; IRDIFF is the domestic/U.S. interest rate differential on deposits; ERDEV is the exchange rate change computed using end of the month log-first difference; RDC is the deviation of the ratio between real domestic credit and GDP from its trend; M2ratio is the deviation of the ratio of M2 over reserves from its trend; GENRET and GENVOL are stock index returns and volatility, respectively; BANKRET and BANKVOL are returns and volatility of a stock indexed based on a portfolio of banks listed in the stock market.

Data for Figure 4: Singapore

OBS	ERDEV	REER	M2ratio (Right axis)	RDC	IRDIFF	BANKRET (Right axis)	GENRET (Right axis)	BANKVOL	GENVOL
1984:11	-0.92593	7.74261	0.101908	-0.18743	-4.50388	-2.59734		4.509437
1984:12	0.925933	4.437346	0.11959	-0.1426	-4.25225	-0.71871		2.928278
1985:01	1.373019	6.971242	0.073722	-0.33466	-4.53129	4.429495		7.257889	6.93762
1985:02	2.690745	6.742808	0.056595	-0.34759	-4.61295	-0.48259	-0.04309	1.717951	2.02081
1985:03	0	6.65007	0.006194	-0.11528	-4.53369	-1.22492	-2.62176	2.590047	3.358853
1985:04	-1.78576	4.790588	0.008271	-0.03405	-4.88784	-3.54733	-4.5976	2.580228	2.994796
1985:05	0	4.561456	0.01035	-0.05776	-4.41365	3.195745	3.22104	4.105441	3.59222
1985:06	0.449439	3.059439	0.004947	-0.03722	-4.54662	-6.06093	-5.40793	3.798122	3.25305
1985:07	-0.90091	1.280983	-0.00658	-0.38415	-5.0388	-5.60175	-5.08121	4.467135	5.112621
1985:08	0	0.822322	0.018304	-0.35505	-5.32273	-7.94676	-5.46754	5.67072	4.21517
1985:09	0.900907	2.379602	-0.03586	0.199294	-5.24747	5.562372	5.622044	4.709727	4.371747
1985:10	-4.11958	1.84891	-0.0314	0.098028	-4.95547	1.580432	1.049435	3.409534	3.397835
1985:11	-1.41179	3.626171	-0.03385	0.20122	-4.93148	-3.97479	-5.89424	5.990277	6.828537
1985:12	0.472814	0.707178	-0.04256	0.391856	-4.90587	-10.1421	-10.5603	8.542668	6.59321
1986:01	0.470589	0.487474	-0.04926	0.223435	-4.90371	-3.68941	-2.13988	5.423706	5.542604
1986:02	0.468385	-2.13745	-0.05779	0.093435	-4.91958	0.992838	5.334067	3.322234	4.099508
1986:03	0.930239	-3.67212	-0.04891	0.304345	-4.36411	-8.61535	-8.25477	7.627759	6.749033
1986:04	1.379332	-4.92095	-0.05884	0.323376	-3.68282	-2.58149	-2.11022	2.865566	3.234101
1986:05	1.360565	-6.08807	-0.05132	0.1331	-3.64215	11.65682	13.43211	7.304828	8.014463
1986:06	0	-5.07726	-0.07423	-0.1669	-3.59175	14.47094	14.2222	10.14058	9.80169
1986:07	-1.36057	-4.89191	-0.0742	-0.42974	-3.99545	0.950372	1.715108	3.121299	2.343182
1986:08	-1.37933	-4.13503	-0.06069	-0.43468	-2.83621	9.396411	11.7523	6.436505	7.51449
1986:09	0.461895	-4.1093	-0.0415	-0.27515	-3.51535	-4.28488	-3.01618	3.549956	2.855987
1986:10	0.459771	-3.81712	-0.02678	-0.30419	-3.92208	19.53906	20.96173	10.88857	12.24848
1986:11	0.457667	-1.76059	-0.01432	-0.09557	-4.05	-7.54545	-7.9873	5.959147	5.575698
1986:12	0	-1.24156	-0.01684	-0.12144	-4.04312	1.868775	1.583059	2.198854	1.513191
1987:01	-1.84337	-2.86174	-0.00377	0.088722	-4.01792	5.317393	5.543086	4.922796	5.229078
1987:02	-0.4662	-3.92277	-0.0083	0.13951	-3.9683	12.71574	10.61614	8.315588	6.346704
1987:03	0	-3.92609	-0.01377	0.18217	-3.96733	-4.62675	-1.42192	4.734731	4.327576
1987:04	-0.46838	-4.87285	-0.02055	0.166454	-3.93567	2.270618	4.682328	4.429581	4.726228
1987:05	-0.47059	-4.06396	0.044857	1.075612	-3.92187	7.382884	10.13931	4.976114	6.130836
1987:06	0	-3.19995	0.027598	0.640028	-3.8628	0.729326	2.770968	2.446743	2.377058
1987:07	0	-2.18109	0.030659	0.528625	-3.8639	13.53769	10.6871	8.944865	7.054035
1987:08	-0.47281	-1.60745	0.036141	0.974852	-3.82731	4.637455	3.190636	5.707487	3.98532
1987:09	-0.95239	-1.7789	0.020826	0.635264	-4.39309	-2.86132	-3.49251	4.381173	4.833542
1987:10	0	-1.69525	0.030785	0.636425	-4.31163	-42.1867	-52.249	31.82347	38.79509
1987:11	-2.42143	-2.05613	0.032488	0.714224	-4.34486	-6.88673	-4.39415	6.371865	7.248226
1987:12	-1.48151	-3.96111	0.036085	0.708904	-4.4124	-1.55256	0.354014	7.86443	10.08362
1988:01	0.990107	-3.70957	0.010281	0.529881	-4.67497	6.078823	8.544803	6.350866	6.539949
1988:02	-0.49383	-2.80066	-0.00968	0.211804	-4.74412	-1.84097	-0.86761	3.517577	3.773901
1988:03	-0.49628	-3.23322	-0.03005	-0.09978	-4.73213	2.192094	3.016664	5.286106	6.038122
1988:04	-0.49875	-2.90593	-0.05273	-0.41933	-4.68852	3.350478	2.990485	2.478742	2.617046
1988:05	0.498754	-3.01725	-0.02938	-0.57483	-4.67247	-2.73289	1.182625	2.767192	2.253381
1988:06	0.990107	-2.76542	-0.03012	-0.6219	-4.6154	10.33494	9.464339	6.231946	5.518333
1988:07	0.9804	-0.54848	-0.04546	-0.40048	-4.4844	1.874489	4.065369	2.217961	3.094225
1988:08	-0.489	0.135736	-0.03133	-0.51868	-4.87684	-7.38598	-7.99898	11.15029	9.79812
1988:09	0	-0.11059	-0.02013	-0.53766	-4.82125	-3.62361	-2.71068	4.004723	3.650949
1988:10	-0.98523	-0.78527	-0.03725	-0.50415	-4.79374	1.580339	2.075381	3.992732	4.186745
1988:11	-3.0153	-0.38612	-0.02641	-0.44804	-4.70692	-4.62799	-3.09682	3.352124	2.713955
1988:12	-1.02565	-0.31088	0.025421	-0.43024	-4.70124	5.997394	4.961461	4.468673	4.44225
1989:01	0	1.442715	0.000712	-0.17224	-4.60898	7.866076	10.01069	5.570404	6.776282
1989:02	-0.5168	2.076957	0.014858	-0.26881	-5.16234	0.801378	-0.60381	3.196935	2.214204
1989:03	0.516797	1.694041	0.04089	-0.32479	-5.08398	4.412327	5.012718	4.189128	4.211968
1989:04	0.51414	0.996019	0.036684	-0.32195	-4.89383	2.371919	5.578444	4.327906	4.494382
1989:05	0.51151	1.984822	0.026186	-0.22645	-4.79175	6.209247	3.520541	6.314311	2.934561
1989:06	0	2.362313	0.04357	-0.23937	-4.7528	0.59277	2.238664	5.447772	5.448783
1989:07	0	0.930218	0.023246	-0.41186	-4.74061	7.072502	5.52436	6.554697	4.319296
1989:08	0	0.390097	0.022611	-0.4157	-4.73534	-2.00821	-3.61681	3.663898	2.75469
1989:09	1.015237	0.043447	0.020601	-0.42932	-4.70392	-4.47502	-0.99632	3.537502	2.831839
1989:10	-1.01524	-0.70826	0.013581	-0.37212	-4.68406	-4.76899	-4.77414	6.592978	6.653106
1989:11	0	0.636436	0.060752	0.475647	-4.65346	4.185934	4.766066	3.386645	3.624053
1989:12	-2.06193	1.379056	0.032189	-0.15551	-4.59067	3.099219	4.51748	3.332486	3.209021
1990:01	-1.57484	2.121071	0.137781	2.788775	-4.29554	4.383536	3.599235	4.950487	3.050766
1990:02	-1.60003	2.463855	0.030237	-0.08105	-3.94428	3.527443	1.290563	3.790996	4.096436
1990:03	1.069529	2.508637	0.038485	0.193232	-3.76933	-1.44808	1.20636	1.912007	2.052181
1990:04	0	2.756474	0.029055	0.033678	-3.18666	-4.80611	-7.60496	3.008241	3.362022
1990:05	-1.06953	2.20825	0.043536	0.256359	-3.12142	9.051001	11.0604	7.357183	7.634951
1990:06	-0.53908	2.064655	0.005043	0.107149	-2.57569	5.292296	-2.08103	5.874424	1.500161
1990:07	-1.63491	1.626229	-0.0292	-0.11767	-2.39618	0.215617	2.862953	2.079345	2.703945
1990:08	-1.66209	1.293366	-0.05415	-0.54275	-2.22648	-18.7257	-21.7198	18.08966	21.53397
1990:09	-1.12361	0.166348	-0.02993	-0.81209	-2.18113	-15.055	-18.6224	8.51296	10.82763
1990:10	-2.28581	0.245367	-0.03972	-0.23438	-2.17618	6.62669	6.037327	6.548912	7.381364
1990:11	-1.1628	0.830604	0.003229	-0.35256	-2.22535	-0.89208	-4.18698	3.004684	2.411971
1990:12	1.162804	1.122222	0.011506	-0.4547	-1.78042	6.942271	7.409904	4.019038	4.338838
1991:01	1.149438	-0.77967	-0.00964	-0.3444	-2.29816	2.130406	5.369887	3.593069	5.266005
1991:02	-1.72915	-1.07505	0.02327	-0.45524	-1.76444	12.97658	14.53788	8.069735	9.063272
1991:03	2.298952	-0.46383	0.044872	-0.36631	-1.7665	4.0079	3.477991	3.045672	3.516397
1991:04	0.566574	-0.14586	0.000337	-0.22453	-1.21941	-1.70412	2.9491	2.491429	4.137834
1991:05	0	-0.22095	0.006394	-0.1094	-1.20545	1.20066	-0.15747	2.144918	2.133014
1991:06	0.563382	-0.08889	0.005896	-0.0022	-0.80307	-1.25389	-4.59032	1.680518	3.491528
1991:07	-1.12996	0.850522	0.030344	0.652463	-0.72325	0.747875	0.705124	1.687256	2.906412
1991:08	-1.71924	1.297512	0.004684	0.163036	-0.73808	-4.83385	-2.95602	7.05448	7.982677
1991:09	-1.74932	0.552241	0.005058	0.109447	-0.22174	-1.70036	-3.18696	2.492265	3.016442
1991:10	-0.58997	0.514779	0.000229	0.246119	-0.39939	2.19274	3.64087	3.299234	4.500418
1991:11	-1.19049	0.885161	0.012618	0.201229	0.12625	-0.97605	1.83271	2.769257	3.482853
1991:12	-1.20483	2.163383	0.011028	0.316872	0.284654	0.882187	3.20765	1.082396	3.243285
1992:01	-1.21953	2.449381	0.009064	0.361699	-0.14227	2.460773	2.885814	2.255741	2.742359
1992:02	0.611623	1.942942	-0.00375	0.244516	-0.51076	-3.00914	-4.31378	2.975775	2.991582
1992:03	1.212136	1.743679	0.041542	0.234764	-0.4878	-0.03889	-3.48345	1.717927	1.645212
1992:04	0	1.851075	0.012522	0.299912	-0.50284	1.40148	4.517906	1.712494	5.602887
1992:05	-1.21214	1.264488	0.005112	0.341893	-0.51411	1.554886	4.016546	1.529635	3.104982
1992:06	-1.22701	0.383149	0.00643	0.410147	-0.55412	1.520453	-2.16403	2.721842	1.865967
1992:07	-0.6192	-0.6938	0.015618	0.261417	-0.25192	-0.69311	-3.13868	2.136823	4.30343
1992:08	0	-1.16724	-0.00032	0.394698	-0.2794	-2.42059	-6.35973	4.937509	7.427489
1992:09	-0.62305	-1.738	0.003079	0.269012	-0.49793	0.125989	-1.72077	1.570427	2.368626
1992:10	0.623055	-1.00685	0.018168	0.256392	-0.60131	0.475138	1.875013	2.704871	3.575273
1992:11	1.234584	-0.37441	0.013296	0.276228	-0.60207	3.327479	6.851464	1.753211	3.277882
1992:12	0.611623	0.258749	0.008829	0.212232	-0.60712	1.017207	3.13571	1.912342	3.198006
1993:01	0.607905	0.092092	-0.02777	0.120559	-0.61225	2.965655	3.324641	2.081144	2.544864
1993:02	0	-0.17494	-0.04647	0.051533	-0.58786	2.421571	1.457812	1.988056	1.617945
1993:03	-0.6079	-0.6429	-0.01422	-0.02915	-0.77233	-1.36368	0.311558	1.161345	1.860603
1993:04	-1.22701	-1.11234	-0.02711	0.071835	-0.7814	2.151473	5.42277	1.499147	3.42367
1993:05	-0.6192	-1.38378	-0.02475	0.103246	-0.78404	0.372039	4.190683	1.968459	3.784667
1993:06	0.619197	-1.95763	-0.03031	-0.17234	-0.78216	-1.98876	-2.81045	1.731746	3.2681
1993:07	0	-1.33422	-0.04154	-0.48476	-0.79163	1.695165	0.6137	1.209261	1.828109
1993:08	-0.6192	-1.41377	-0.04433	-0.41889	-0.7804	12.5993	12.73586	5.452629	6.994211
1993:09	-0.62305	-2.09636	-0.04537	-0.3274	-0.7634	3.297656	2.026233	2.090871	1.956063
1993:10	-1.8928	0.418001	-0.00662	0.541198	-0.78075	2.297622	8.849972	1.600655	5.380943
1993:11	1.892801	-0.07055	-0.0233	-0.42064	-0.78545	0.967605	-2.32801	2.945884	3.405085
1993:12	0	0.738092	-0.02358	-0.17088	-0.7947	28.10857	18.2265	17.27812	10.61085
1994:01	0	0.944053	-0.05453	-0.08631	-0.5477	-2.29256	-4.93397	8.067849	8.90007
1994:02	-0.62696	0.247395	-0.06338	-0.16035	-0.37241	-0.98622	-2.80755	1.928815	2.287799
1994:03	-0.63092	-0.25188	-0.04584	-0.19753	-0.34851	-13.2153	-12.2632	9.778913	8.813282
1994:04	-1.2739	0.646204	-0.03713	-0.21831	-0.20912	4.679834	10.38838	4.773729	8.108968
1994:05	-0.64309	0.341653	-0.02416	-0.26188	-0.6588	-1.57647	-0.68026	2.259587	2.777535
1994:06	-1.29872	0.034421	-0.00567	-0.28365	-0.66099	-4.28102	-3.6481	3.11879	2.660689
1994:07	-1.31581	-0.87556	0.01637	-0.33395	-0.65694	3.13602	2.116692	3.67825	3.531489
1994:08	-0.66445	-0.68837	0.007403	-0.15752	-0.91366	2.21486	3.180887	1.637493	1.844839
1994:09	-0.6689	-1.40401	0.011688	-0.00769	-0.9027	1.113222	0.980097	1.3804	2.032205
1994:10	-0.6734	-1.12244	0.011598	-0.14526	-0.91214	2.776552	3.151018	2.018919	2.532334
1994:11	-0.67797	-0.34353	0.033899	-0.06881	-0.84397	-4.45107	-6.63896	2.29913	4.511172
1994:12	0	1.432933	0.047456	-0.11702	-1.18962	-0.06256	-0.67143	2.574876	4.520193
1995:01	-1.36988	1.307185	0.069982	0.119037	-1.17729	-6.97556	-8.30836	6.807866	10.11846
1995:02	0	-0.42063	0.063243	0.053712	-1.6667	2.124522	3.839937	1.447875	2.029154
1995:03	-2.09067	-0.85048	0.041385	-0.0255	-1.63858	-0.615	-1.08086	1.309094	2.385442
1995:04	-1.41846	-1.88228	0.016344	0.07067	-1.63872	1.403826	-0.84511	2.229445	1.817745
1995:05	-0.71685	-1.61589	0.023725	0.183868	-1.64211	2.404065	6.861484	3.917882	5.159222
1995:06	0	-2.75105	0.020184	0.013401	-1.80799	-4.07631	-5.05685	3.275737	5.356909
1995:07	0.716849	-2.98738	-0.01331	0.01087	-1.80147	1.802508	1.983795	1.03909	3.010307
1995:08	0.711747	-2.02432	0.004639	0.019436	-1.82771	-3.08462	-2.36117	2.041799	3.042218
1995:09	1.408474	-3.06109	-0.00879	-0.05754	-1.81746	-0.46726	0.228745	1.442261	1.432558
1995:10	-0.70176	-2.79676	-0.01471	-0.13497	-1.80353	-1.53672	-0.48927	1.307162	2.200014
1995:11	-0.70672	-1.33021	0.001597	-0.07248	-1.81337	-0.24762	1.032418	1.279823	2.482092
1995:12	0	-0.26013	0.015503	-0.05189	-1.80724	8.145887	7.546787	4.92328	4.531462
1996:01	0.706717	0.414919	-0.00356	0.035253	-1.77347	2.142691	9.623109	1.962708	6.224193
1996:02	-0.70672	0.396357	-0.004	-0.03069	-1.54918	1.506253	-0.21911	1.607366	2.400679
1996:03	0	0.685594	0.019879	0.02711	-1.50818	-4.09647	-1.89322	3.614996	4.694499
1996:04	0	1.384007	0.01376	0.069793	-1.49581	0.549433	-0.04065	1.128944	1.676256
1996:05	0	0.992925	0.020085	0.025747	-1.50212	-0.97414	-3.16146	2.333869	2.705477
1996:06	0	1.013583	0.019798	-0.02318	-1.50232	-2.12927	-1.09814	1.27657	1.69739
1996:07	0.706717	0.247145	0.015241	0.032301	-1.49302	-6.64315	-9.03968	4.791215	6.162168
1996:08	-0.70672	-0.20529	0.005876	0.046719	-1.48673	1.154881	3.48707	1.443897	2.060436
1996:09	0	-0.14265	0.003441	-0.09007	-1.47469	0.122404	1.113497	1.194354	2.543991
1996:10	0	0.436154	-0.01497	-0.28	-1.45945	-2.8303	-3.57467	1.701106	2.897542
1996:11	-0.71175	1.232232	0.001908	-0.17798	-1.45955	0.760013	6.809422	1.518221	5.894464
1996:12	0	3.346652	-0.00702	-0.0543	-1.46577	0.253357	1.806671	0.926505	1.345927
1997:01	0.711747	4.380399	-0.01283	-0.13387	-1.45687	2.152774	3.151143	1.772296	2.216971
1997:02	0.706717	4.834227	-0.01644	-0.16216	-1.45711	3.024621	0.105518	4.355086	2.587802
1997:03	1.398624	3.808584	-0.02297	-0.103	-1.42996	-3.06273	-8.24213	2.56207	5.111972
1997:04	0	4.203586	-0.02059	-0.08952	-1.43922	-2.87667	-3.90354	2.578743	4.917107
1997:05	0	2.91908	-0.03678	-0.09816	-1.44832	0.835942	7.260087	1.963311	4.577061
1997:06	-0.69687	2.954623	-0.03533	-0.17863	-1.44849	-2.91683	-1.95936	2.652652	2.297475
1997:07	1.388911	2.80957	-0.03056	-0.23854	-1.45471	-0.80425	1.482595	1.010575	2.521957
1997:08	3.390155	1.38307	-0.03276	-0.39255	-1.45788	10.73933	-11.1763	9.332254	8.246763
1997:09	1.324523	0.274078	-0.05712	-0.34206	-1.45209	-1.31408	6.498246	3.001889	7.027324
1997:10	2.597549	-1.41855	-0.04813	-0.32541	-1.44355	-17.9152	-21.0682	11.74456	17.90832
1997:11	1.273903	-1.19597	-0.06043	-0.46845	-1.40134	10.41335	4.936143	4.146596	3.501633
1997:12	4.335044	-0.05925	-0.05143	-0.34642	-0.79039	1.35714	-4.92686	6.380611	7.894848
1998:01	5.88405	-1.70937	-0.0654	-0.24528	0.260135	-32.1295	-16.8202	26.30267	20.27197
1998:02	-5.27982	1.052693	-0.08594	-0.30487	0.321829	17.52387	16.83349	5.43139	5.540003
1998:03	-2.43915	3.426091	-0.06225	-0.18731	0.297766	1.788043	-1.56809	6.425962	5.70882
1998:04	-1.24225	4.809889	-0.0849	-0.23531	0.306444	-7.72596	-9.18964	5.173505	5.657808
1998:05	2.469261	3.00292	-0.04656	-0.21083	0.382975	-8.00867	-14.8226	5.927593	8.515671
1998:06	3.593201	1.403682	-0.0777	-0.18429	0.394114	-14.2445	-14.5724	10.39509	10.87293
1998:07	0.586512	1.010465	-0.04461	-0.19362	0.394424	-6.87232	0.569127	6.375559	4.140035
1998:08	2.312242	-1.67854	-0.05854	-0.17094	0.405579	-26.8373	-16.9832	16.705	10.19713
1998:09	-1.14944	-3.76521	-0.11113	-0.23503	-0.03088	-7.6313	9.273488	8.770759	10.16081
1998:10	-5.34252	-1.3513	-0.11639	0.007663	-0.29396	33.48785	24.8412	23.53549	19.4026
1998:11	0	-0.63832	0.091683	1.679876	-1.31412	23.02891	16.20602	13.42359	11.87274
1998:12	0.607905	-1.42767	0.104056	1.739632	-2.50868	11.19464	-1.69585	9.198794	4.344847
1999:01	1.801851	-3.02072	0.092541	1.456869	-2.52137	7.095867	2.510705	13.14379	6.927264
1999:02	1.183446	-3.01872	0.109626	1.222007	-2.51967	1.549231	-1.14295	6.391534	5.826119
1999:03	1.749316	-3.12273	0.100846	1.298688	-2.52149	16.1676	7.265448	9.614948	4.380087
1999:04	-1.1628	-1.43359	0.064106	1.227123	-2.49468	15.39402	21.6961	8.324758	12.4963
1999:05	0	-1.25192	0.097703	0.97145	-2.498	10.95593	0.932448	11.64613	3.667878
1999:06	0	-1.17827	0.089403	0.905058	-2.49642	14.14984	12.97833	8.235401	8.658803
1999:07	-0.58651	-0.11306	0.075102	0.550691	-2.4872	-0.00959	-1.01682	10.92241	8.518631
1999:08	-1.18345	-0.35665	0.079753	0.194329	-2.70532	1.181698	-1.34182	8.744085	5.853752
1999:09	1.183446	-3.30939	0.059757	-0.18693	-2.68468	2.474922	-4.60278	4.396372	4.615191
1999:10	-1.18345	-2.57161	0.080288	-0.23067	-2.67541	0.486339	1.239608	3.91152	4.245644
1999:11	-0.59702	-1.3434	0.10042	-0.17432	-2.90081	11.27964	8.874521	6.589049	5.302224
1999:12	0	-0.62468	0.086971	-0.07823	-2.90254	15.65247	10.28954	10.79079	7.251474
2000:01	0	-0.11528	0.099776	-0.16045	-2.89555	-12.6777	-10.5962	11.18461	9.199398
2000:02	1.780462	-0.91497	0.078852	-0.18654	-3.06302	-13.8391	-5.04752	10.37196	4.719456
2000:03	1.169604	-1.72353	0.067957	-0.09234	-3.24213	0.773244	0.568529	5.893992	5.768064
2000:04	-0.58309	-0.64066	0.032221	-0.25945	-3.24085	6.103753	1.467199	6.743477	5.699434
2000:05	1.162804	-0.26596	0.001127	-0.27582	-3.67449	-24.5429	-18.6932	15.37998	11.7935
2000:06	0	-1.99896	-0.00823	-0.1921	-3.64823	19.36866	12.68768	10.82801	7.206155
2000:07	0.57637	-1.7392	-0.00964	-0.31484	-3.64422	1.806996	0.647565	2.948388	2.94729
2000:08	-1.15608	0.113942	-0.02436	-0.6482	-3.65394	2.652861	4.600023	5.433265	4.876375
2000:09	1.156082	-1.23881	-0.06341	-0.74383	-3.62651	-7.39523	-7.2769	8.912841	7.824497
2000:10	0.573067	-0.59672	-0.07032	-0.76167	-3.638	4.44568	-1.03132	7.291872	5.806891
2000:11	0	0.641023	-0.05542	-0.55089	-3.63823	-1.71086	-1.23755	5.987538	4.748217
2000:12	-0.57307	2.075264	-0.07141	-0.59733	-3.64443	0.777427	-1.30961	3.84471	3.885425
2001:01	0	1.506819	-0.04526	-0.37567	-2.74587	1.278747	3.29065	6.078598	4.222999
2001:02	0	1.836342	-0.04683	-0.39902	-2.72537	1.376002	-2.22875	2.920891	1.692753
2001:03	1.709443	1.564409	-0.01636	-0.25922	-2.28632	-14.7576	-15.1166	11.40465	10.0678
2001:04	2.23473	0.091439	-0.02383	-0.26605	-1.84488	-1.02836	2.857497	8.309841	5.94784
2001:05	0	0.717759	-0.01796	-0.27723	-1.39425	-4.17466	-3.88655	3.388864	2.988753
2001:06	0.550966	0.943686	-0.00946	-0.15957	-1.16569	5.940449	4.105732	5.763312	2.848425
2001:07	0	1.169493	-0.02614	-0.3118	-1.183	-2.57043	-3.56527	3.775485	3.000141
2001:08	-3.35227	2.695377	-0.01896	-0.22711	-0.96837	1.201999	-2.85608	2.293357	2.623914
2001:09	-0.5698	0.82146	0.023032	0.517082	-0.83901	-15.2178	-20.4607	13.24451	16.78371
2001:10	3.371106	-1.15233	-0.02522	0.507151	-0.56673	6.588995	3.595724	8.193366	4.96189
2001:11	1.098912	-1.1261	-0.01182	0.63655	-0.18539	8.12166	7.782226	10.48035	7.696204
2001:12	0.54496	0.500087	-0.00193	0.632493	-0.03195	11.11234	9.359079	7.376251	5.401725

ERDEV - Exchange Rate Devaluation

Figure 5: Philippines

These panels show the evolution of a number of Philippine indicators over the period November 1984 to July 2001 (stock market and banking sector data start in January 1987 and January respectively). REER is the percentage deviation of real effective exchange rate from its trend; IRDIFF is the domestic/U.S. interest rate differential on deposits; ERDEV is the exchange rate change computed using end of the month log-first difference; RDC is the deviation of the ratio between real domestic credit and GDP from its trend; M2ratio is the deviation of the ratio of M2 reserves from its trend; GENRET and GENVOL are stock index returns and volatility, respectively; BANKRET and BANKVOL are returns and volatility of a stock indexed based on a portfolio of banks listed in the stock market.

Data for Figure 5: Philippines

OBS	ERDEV	REER	M2ratio (Right axis)	RDC	IRDIFF	BANKRET (Right axis)	GENRET (Right axis)	BANKVOL	GENVOL
1984:11	4.142756	3.921835	-0.86372	-0.36782	62.08222
1984:12	-0.50226	7.16534	-3.4742	-1.01523	58.39462
1985:01	-4.53219	13.9613	-1.04037	-0.81479	48.06061
1985:02	-3.86729	19.6124	10.25994	-0.32333	41.64846
1985:03	1.197619	19.72032	16.65111	0.263068	36.62252
1985:04	0	15.1854	3.173184	-0.00045	40.74366
1985:05	0	14.50662	0.572294	-0.28655	35.99903
1985:06	-0.05413	13.78188	-0.35223	-0.5673	34.33621
1985:07	0.593794	11.10809	0.440515	0.135896	29.18957
1985:08	0.107585	7.881203	-5.26213	1.062379	26.45098
1985:09	0.107469	9.796391	-4.12992	2.223377	19.98584
1985:10	0.428725	5.348284	-1.45773	0.902212	16.23411
1985:11	0.213675	5.230834	0.50219	-0.11346	16.13644
1985:12	0.850165	4.937617	2.379378	-1.00112	15.89459
1986:01	0.738011	5.461848	6.05579	-0.80793	14.29513
1986:02	7.192973	-6.0036	7.393801	0.042599	17.42084
1986:03	1.551923	-8.16623	-0.19562	1.115908	19.98053
1986:04	-1.35661	-9.13314	-1.8915	0.696689	17.33949
1986:05	0	-9.91086	-2.9346	0.273293	22.39701
1986:06	0.243605	-10.4053	-2.68764	-0.06609	16.01696
1986:07	-0.48781	-9.32155	-2.91345	0.505991	12.91171
1986:08	-0.09785	-10.9642	-2.39072	1.129072	15.95599
1986:09	0.390816	-9.53707	-2.56463	1.815471	13.55818
1986:10	-0.34188	-7.14319	-3.4359	1.107056	12.58982
1986:11	0	-5.685	-3.14819	0.532603	12.93103
1986:12	0.390625	-3.96439	-5.12396	-0.43518	9.023881
1987:01	-0.29283	-6.18288	-5.37737	-0.31491	7.987301				11.08506
1987:02	0.341547	-7.64172	-5.38759	0.011115	6.639297		-1.48128		4.852914
1987:03	0.146021	-7.44171	-5.12786	0.22755	5.49707		-0.53649		8.408129
1987:04	-0.29226	-7.98314	-5.37552	-0.23364	9.426945		10.21827		7.825637
1987:05	-0.14645	-7.36577	-4.80096	-0.57529	12.97436		7.424673		6.25001
1987:06	-0.04886	-4.48881	-4.74619	-0.78129	9.039884		40.94145		27.00139
1987:07	-0.04889	-0.85096	-5.04329	-0.80835	7.704465		23.42122		20.45761
1987:08	-0.04891	-1.65061	-5.37118	-0.68838	7.692958		-9.53515		15.58419
1987:09	0.779731	-2.78608	-3.56396	-0.23454	9.859612		-33.7253		24.73528
1987:10	0.53256	0.344412	-2.68808	-0.71301	9.407255		0.251959		13.09484
1987:11	0.529739	-1.25715	-0.9576	-0.89459	11.22576		-6.38606		13.2143
1987:12	-0.04804	-0.88881	-2.41388	-0.9954	14.39019		14.17616		14.30366
1988:01	0.192031	-1.24853	-0.32902	-0.6382	11.04152		1.356823		4.279545
1988:02	0.239521	-1.33419	1.047327	-0.17118	10.16014		-8.23721		6.238737
1988:03	0.620083	-1.64361	-0.13487	0.344607	11.68393		-1.05816		4.078096
1988:04	0	-2.7745	-0.43421	-0.13901	15.36264		5.640872		4.638409
1988:05	-0.38113	-2.22447	0.791892	-0.41295	14.663		0.781722		3.914821
1988:06	0	0.709085	2.001485	-0.64388	16.88083		4.888908		5.196947
1988:07	0.333572	2.428906	5.787896	-0.48463	13.56179		2.491765		2.472427
1988:08	0.190114	1.73769	5.759824	-0.1408	12.9223		-10.3897		10.49324
1988:09	0.898139	-0.06203	8.175648	0.423712	14.83947		-11.278		6.969985
1988:10	0.516312	-1.56786	5.519709	-0.15859	12.75193		3.759683		5.166832
1988:11	0.093589	-1.17737	0.892044	-0.45747	13.88809		0.791497		1.772579
1988:12	-0.09359	1.211946	-4.13228	-0.73405	14.06942		14.0057		8.052372
1989:01	-0.09368	3.7027	-2.63888	-0.45787	14.50723		-0.22552		2.871175
1989:02	0.093677	2.097408	-1.11845	0.197123	14.42622		3.106158		4.445056
1989:03	-0.09368	1.698331	1.641108	0.973914	14.648		4.970956		4.297941
1989:04	0.327486	1.507585	7.44318	0.484595	14.94618		9.73486		5.232277
1989:05	0.790886	3.827168	4.994853	0.178914	14.68239		3.933336		6.240477
1989:06	0.462322	5.158973	7.196174	-0.04772	15.71539		-2.8209		3.421899
1989:07	0.963973	2.804627	11.64186	0.149096	15.44868		14.41568		12.68921
1989:08	-0.04569	5.465401	5.717031	0.272221	11.52677		-3.91789		5.072963
1989:09	0.410491	8.342366	4.132631	0.34573	19.34279		1.65954		1.967531
1989:10	-0.04553	10.73622	-1.69491	-0.18081	17.07058		12.94006		9.622054
1989:11	0.635499	8.247077	0.215361	-0.34041	19.03573		1.35911		4.353616
1989:12	1.080119	7.074307	-5.70476	-0.53605	16.75739		-17.1073	3.226176	18.2396
1990:01	0.535716	3.716707	1.435261	-0.18332	20.55026	-2.30587	-5.36826	2.996912	4.530073
1990:02	0.709852	2.072583	4.49898	0.2826	20.95081	4.210312	-2.94434	4.15861	2.412057
1990:03	0.617014	3.039984	1.944016	0.83854	20.72524	0.581735	7.741029	1.981449	8.173885
1990:04	0	3.616812	6.499812	0.430458	23.122	-1.87359	-15.54	1.698956	9.750141
1990:05	0.61323	2.500762	-0.99337	0.265622	23.14754	-7.75995	-13.9483	5.428108	13.83221
1990:06	0.869571	2.489273	0.633743	0.289346	23.31584	3.658052	8.008293	3.702903	15.0696
1990:07	1.971774	1.079615	1.114696	0.437334	22.86493	3.082142	5.482021	3.149436	7.00518
1990:08	3.707986	-1.43112	-0.87871	0.633116	22.25194	-17.5676	-22.4446	13.06418	19.83688
1990:09	3.614851	-2.54591	0.309364	1.146404	23.43377	-13.0452	-31.5746	8.217223	19.90298
1990:10	1.56559	-4.56763	2.292081	0.669541	26.24213	2.943151	11.22129	3.492076	11.50093
1990:11	8.376988	-10.099	3.493877	0.306641	26.96495	7.274784	1.467818	7.639929	8.024717
1990:12	0	-7.84238	2.336931	-0.01731	25.77743	-1.31427	4.805013	4.426708	7.415746
1991:01	0	-6.79947	5.773876	0.259565	26.25708	4.449477	14.72345	6.400256	15.8652
1991:02	0	-11.0714	-1.29879	0.459965	24.87933	22.53172	26.5771	14.43169	19.43186
1991:03	0	-8.35889	-0.44525	0.93215	25.03925	8.154475	11.46036	6.57039	10.09578
1991:04	-0.25031	-6.66177	-3.03103	0.438473	21.50864	6.125396	-3.99871	4.396636	7.653145
1991:05	-0.39462	-6.4794	-3.51711	0.054944	19.84023	7.919247	10.45798	7.411764	7.882561
1991:06	-0.07192	-3.41062	-3.63709	-0.14566	18.09061	-1.93914	-10.2889	4.198684	7.478607
1991:07	-0.64959	-1.75384	-2.64033	-0.11331	16.18275	-3.29928	-4.17376	4.542092	7.203064
1991:08	-1.53232	0.192774	-2.54648	-0.04947	15.65698	-0.85618	0.002936	3.368437	6.805047
1991:09	-0.81211	0.831166	-2.53729	-0.04795	14.69231	-9.19327	-7.9913	8.138387	8.170127
1991:10	0.037058	-0.63672	-2.71039	-0.24047	17.3417	-0.79604	8.865311	2.167742	5.870356
1991:11	-0.93059	1.89099	-2.86812	-0.51256	18.11484	5.317413	5.553052	4.503341	6.339378
1991:12	-0.26212	2.51623	-2.52147	-0.58643	18.66706	0.637907	5.759373	3.133806	3.159892
1992:01	-0.48863	3.54079	-2.92647	-0.51313	17.78454	4.674818	9.335819	2.929507	7.067494
1992:02	-1.44215	2.56629	-2.96855	-0.41079	16.94542	-0.4321	-5.63311	3.354353	6.900238
1992:03	-1.34695	5.194104	-2.90963	-0.22841	15.8373	0.679323	-7.99808	3.136882	4.622402
1992:04	-0.5439	4.525425	-2.01002	-0.43159	14.6546	6.580713	12.16133	4.594797	7.383404
1992:05	1.85262	1.761089	-0.71093	-0.47666	13.79134	3.409046	12.62394	4.682833	10.74319
1992:06	-0.11479	1.501616	-0.51208	-0.62322	13.20887	10.83041	10.07215	7.106339	7.907505
1992:07	-3.34792	4.147403	-0.42923	-0.79282	13.36119	-5.19709	-3.78582	4.792069	4.398291
1992:08	-2.36342	5.598744	0.232081	-0.80311	13.73663	-4.51519	-7.96616	4.458629	6.141991
1992:09	0.242915	6.455646	-0.57331	-0.7224	13.51496	5.234762	1.989917	6.128787	2.785522
1992:10	0.201979	6.317723	-0.78761	-0.91198	13.65842	-1.21131	-3.49275	2.872504	5.353033
1992:11	0.643606	8.384146	-0.69073	-1.03173	12.90731	-7.85205	-7.20496	6.165191	4.677626
1992:12	1.512166	5.853643	-0.44525	-0.94765	12.99491	5.979222	-1.6375	3.912124	5.03244
1993:01	-0.1581	5.524362	-0.84452	-0.96071	11.87144	1.268516	7.562782	1.377419	3.418874
1993:02	0.118601	4.394044	-0.99153	-0.85149	10.44831	7.072714	12.68909	4.596405	8.377734
1993:03	0.23678	2.860047	-1.20558	-0.64751	9.155958	2.640982	-4.44524	4.547075	4.602902
1993:04	2.760136	-2.48058	-1.23124	-0.90994	8.908131	5.372175	9.686352	2.657668	5.873135
1993:05	3.503843	-6.13098	-0.6704	-1.04396	7.298893	7.027152	-1.20464	4.96119	3.149156
1993:06	0.737738	-6.69412	-0.46597	-1.27175	7.330595	-0.6759	-0.51143	1.835037	2.35409
1993:07	1.314367	-6.67257	-0.32673	0.88448	5.094554	12.90534	10.69602	7.788349	6.591537
1993:08	1.368897	-7.86839	0.194321	1.358708	5.130819	3.003258	1.722527	4.481897	2.750113
1993:09	0.996804	-9.78321	0.498751	1.787517	6.128828	12.44042	10.25352	7.744158	5.306193
1993:10	3.241266	-10.7181	0.240943	1.156129	6.414355	4.70242	18.46535	4.620936	13.66899
1993:11	-2.35958	-8.57348	0.478113	0.712004	8.41697	8.205939	-1.48459	10.62971	3.593261
1993:12	-2.45258	-4.84896	0.716237	0.363143	10.99043	21.29059	31.37426	11.91476	19.81028
1994:01	-0.25221	-0.54362	0.578333	0.495166	10.19168	13.50804	-12.054	9.198371	9.549898
1994:02	-0.25284	-2.75616	0.457276	0.790725	10.63419	10.14398	-0.52614	9.540001	4.560564
1994:03	-0.21723	-2.68528	-0.24742	1.298039	10.32703	-1.96059	-5.2844	2.690006	5.857311
1994:04	-0.21771	-2.92946	-0.56303	0.621316	9.626841	-1.72662	4.778688	2.093	5.379107
1994:05	-1.75893	-0.387	-0.3239	0.318948	9.449835	3.105653	6.352785	3.852574	4.648638
1994:06	-0.25912	-1.456	-0.62169	0.126752	8.715024	-6.0421	-9.85403	4.871109	8.221873
1994:07	-1.94617	0.365464	-0.72693	-0.02051	8.885899	5.231244	2.048879	4.687211	6.904488
1994:08	-0.56851	1.779426	-0.52839	-0.00081	7.342928	1.40884	10.47671	2.058891	5.451354
1994:09	-1.53201	0.687888	-0.3342	0.312218	5.42364	4.106702	-6.79842	5.247604	4.750083
1994:10	-2.02736	0.792731	-0.09379	-0.30167	4.787118	3.242713	5.364727	2.60423	4.027996
1994:11	-4.55265	6.095786	0.457012	-0.59299	3.682223	-6.17798	-13.1212	5.026133	9.077655
1994:12	-0.45445	6.198831	1.01102	-0.58365	3.030744	1.43725	3.45552	3.356731	4.880441
1995:01	1.927474	3.603219	0.880953	-0.27658	2.951653	-6.74929	-14.0722	6.074408	10.43791
1995:02	1.651598	-0.39012	1.344028	0.422519	2.790282	1.244819	3.646164	2.399475	4.966587
1995:03	3.262227	-6.98053	1.378047	1.336925	3.178947	-7.47271	-4.80444	6.391031	6.41908
1995:04	0.578371	-9.46729	1.349478	0.856456	4.006245	1.025783	3.031034	2.321127	3.487127
1995:05	-0.61705	-8.14922	0.921376	0.251643	3.797593	10.2656	11.71579	7.000285	8.483121
1995:06	-0.69876	-8.02449	0.630363	-0.25606	5.123214	-0.43118	-0.21376	1.772406	2.886748
1995:07	-0.62525	-8.49068	0.0714	-0.17887	4.315513	10.25818	4.576902	7.064885	4.156249
1995:08	0.780949	-3.94482	0.161405	-0.13422	3.942954	-0.06326	-4.84838	2.444676	3.717704
1995:09	1.0062	-1.08337	0.275009	0.004393	2.991344	-1.8264	-4.81515	2.444947	3.075116
1995:10	0	-1.00249	0.803927	-0.60629	1.330982	-3.25986	-6.62406	14.73854	4.424981
1995:11	0.767169	-1.79827	0.963036	-0.93698	2.074666	-3.82065	-0.75752	6.36695	7.836791
1995:12	0.15273	1.233252	1.036337	-1.20762	1.887653	9.916399	6.038758	6.10446	3.326847
1996:01	0.038146	3.796181	0.844842	-0.7924	3.006231	10.23302	10.65178	8.223678	7.41073
1996:02	-0.2291	2.89453	0.705998	0.189613	4.320337	3.314913	-0.10956	2.510621	2.782331
1996:03	0.152788	3.132048	0.787261	1.128628	4.582169	5.174088	0.627666	3.300687	3.908435
1996:04	-0.03818	4.812285	0.271434	0.437764	3.967308	9.897295	1.275295	5.32322	2.059936
1996:05	-0.03819	6.038572	-0.02157	0.107897	4.506739	8.093874	10.10127	5.593926	7.021068
1996:06	0.03819	8.313906	-0.15006	-0.21849	2.657924	-2.96549	0.766226	2.152926	2.338308
1996:07	0.038175	6.840865	-0.39794	-0.03434	3.514709	-3.27605	-7.83826	4.016365	7.400947
1996:08	0	9.621449	-0.7938	-0.01531	5.160845	6.955008	6.158722	3.303174	2.984077
1996:09	0.152555	8.557184	-0.65014	0.236799	4.339375	-0.95098	-1.59396	1.559982	1.819793
1996:10	0.114264	8.048926	-0.45314	-0.04923	3.965831	-6.60321	-6.71225	5.416655	7.014677
1996:11	0	6.29694	-0.43432	-0.43259	3.895205	7.779424	4.168316	4.875031	2.910367
1996:12	0.076104	9.500928	-0.22634	-0.61371	4.153511	2.289311	2.568536	2.238937	1.799835
1997:01	0.114047	13.06016	-0.09511	-0.38729	3.631118	19.36253	7.629065	12.13367	5.099435
1997:02	0.075959	15.27324	-0.38493	0.116966	3.231051	-6.07436	-3.16568	3.195816	2.704404
1997:03	-0.03797	13.33787	-0.27004	0.868736	2.781184	-2.66308	-2.82357	1.784451	2.302767
1997:04	0.113874	10.95068	-0.14384	0.528622	2.07956	-22.1668	-19.6438	12.9287	11.3066
1997:05	0.037929	9.707397	0.011433	0.233727	2.812362	0.654908	5.91199	8.070943	7.328506
1997:06	0.037915	12.00297	0.202527	-0.04751	2.666221	-1.74386	-0.00854	2.302157	3.166033
1997:07	4.774265	7.731671	1.010901	0.409933	3.39861	-6.9296	-7.1104	9.286874	7.169788
1997:08	5.826209	3.086952	0.393541	0.528345	4.773619	-27.2677	-25.795	18.0828	18.01455
1997:09	9.923885	-3.93828	-0.22045	0.965747	5.811918	-14.0053	1.758849	12.82857	8.362779
1997:10	6.19495	-7.55134	0.060435	0.390728	5.604502	-7.50308	-12.3652	7.699015	11.00358
1997:11	0.173964	-5.95925	0.184481	-0.15276	5.418994	2.660474	-2.57115	2.748774	4.770127
1997:12	7.396312	-9.16852	1.011369	-0.31608	6.465836	-3.52129	5.345159	4.446388	6.761331
1998:01	13.77597	-16.8852	0.439049	0.358592	8.21626	-10.8031	4.128176	14.98998	15.62975
1998:02	-5.41844	-10.4149	0.136346	0.854686	6.359504	29.3091	15.13402	13.83137	7.12512
1998:03	-3.55156	-7.46173	0.311498	1.664916	6.130321	3.565241	-1.23783	4.28095	4.978011
1998:04	-1.44631	-5.32933	-0.3155	0.94012	5.420287	-8.89939	-2.58401	4.111435	2.881189
1998:05	2.212593	-5.52074	-0.35043	0.28876	5.126041	-4.77447	-8.10743	3.981551	7.499889
1998:06	2.760527	-6.03863	-0.14443	-0.12185	4.929738	-15.1145	-13.3468	10.87909	10.44168
1998:07	3.358797	-7.68528	-0.14322	-0.06086	3.819214	-6.20282	-9.06391	7.90573	9.240469
1998:08	2.971216	-9.16258	0.075586	0.286534	4.490301	-26.2801	-29.8906	14.73093	16.16347
1998:09	1.704718	-11.6719	-0.20906	0.422784	2.788139	2.973848	5.498369	6.217473	9.991469
1998:10	-2.05384	-11.9138	-0.14167	-0.27178	3.999462	29.74513	33.16657	24.21823	25.59578
1998:11	-7.12604	-5.38834	0.28399	-0.72156	4.207745	15.42232	11.8259	9.977969	11.77014
1998:12	-2.20234	-5.1945	0.472331	-0.97277	4.67957	1.724837	-0.33366	6.816139	6.693165
1999:01	-1.72974	-2.23098	0.068504	-0.75681	4.521058	6.618748	-0.74587	8.408209	6.577438
1999:02	0.984719	-0.59611	-0.10469	-0.23318	3.995164	0.025888	0.556237	3.922529	3.623828
1999:03	0.334664	1.11194	-0.27948	0.383413	4.017436	7.953395	3.163594	4.967832	3.228258
1999:04	-1.73692	3.795032	-0.43607	-0.12722	2.098845	23.35424	18.22591	14.6351	11.69556
1999:05	-1.05153	5.25496	-0.26787	-0.33856	-0.23544	1.81076	-0.57154	5.298407	5.32978
1999:06	0.158437	6.393251	-0.21645	-0.59827	1.664857	3.145243	2.736379	3.255765	3.718063
1999:07	0.997645	5.311068	-0.20648	-0.44552	1.184333	-5.02313	-5.971	8.575427	9.216065
1999:08	2.527862	2.209129	-0.23309	-0.10779	0.76361	-2.38351	-7.48651	5.394657	8.018995
1999:09	2.291426	0.087784	-0.29974	0.083493	1.226593	-1.78976	-3.63598	3.292737	3.305854
1999:10	0.372718	-0.35277	-0.29375	-0.37314	0.344613	0.868638	-2.91145	6.290365	5.728186
1999:11	0.049591	0.087653	-0.151	-0.61108	0.859893	3.626086	-2.82078	2.617662	2.955241
1999:12	0.691702	-0.39073	-0.03222	-0.91608	1.188188	2.25354	7.938884	4.015477	7.806855
2000:01	-0.46885	1.812294	-0.07932	-0.56666	0.56473	-8.49755	-7.43446	6.847688	5.591158
2000:02	0.345679	2.596955	-0.03112	-0.05449	0.353645	-15.483	-19.197	12.04062	13.82586
2000:03	0.90787	1.663365	-0.30443	0.620732	0.39049	-0.21563	2.393861	2.969815	5.079413
2000:04	0.608793	1.711452	-0.22443	0.235746	-0.90908	-0.38331	-5.06075	2.802843	7.31433
2000:05	1.494004	2.841032	-0.14753	0.043053	-0.44333	-10.2744	-7.80057	8.570512	8.39527
2000:06	1.989173	-0.1482	-0.08741	-0.2285	-0.00865	-3.80687	3.666829	3.776902	4.099646
2000:07	3.885993	-0.95675	-0.04641	-0.05376	0.092806	-10.9301	-7.92103	6.98239	6.141008
2000:08	1.255059	-0.68511	-0.21736	0.032033	-0.16127	7.2958	8.15088	6.283713	5.410996
2000:09	1.853539	-1.53369	-0.06206	0.28936	0.004668	-2.424	-6.93613	3.940331	5.169085
2000:10	5.051687	-5.20289	0.048131	-0.05857	3.121758	-5.84915	-10.7835	4.933932	8.156382
2000:11	3.352041	-7.09297	-0.08471	-0.50456	3.55916	3.421404	8.694214	5.978703	4.631027
2000:12	0.301054	-6.70384	-0.10048	-0.79428	2.604661	7.280888	6.18754	5.484254	4.939142
2001:01	2.121622	-2.43493	-0.0227	-0.37439	2.728459	12.42451	12.11601	10.82788	10.78033
2001:02	-5.40127	-2.68516	0.230551	0.104582	2.22416	-4.11956	-4.45523	2.041912	3.715938
2001:03	0.372055	-2.15335	0.114134	0.870159	2.499297	-2.09937	-10.9322	2.718576	7.676658
2001:04	3.487075	-5.63808	0.164459	0.501534	2.087751	-0.74046	-4.78351	2.471552	4.060001
2001:05	0.69493	-3.1378	0.14903	0.068546	2.902829	1.959422	1.686405	3.12806	4.640879
2001:06	1.862251	-6.95055	0.125913	-0.28206	2.462226	-5.41007	0.553273	4.137745	3.92354
2001:07	3.304665	2.12581	0.095563	-0.1209	2.501743	-2.15957	-3.40319	3.399922	2.475721
2001:08	-2.33829	4.693937	0.168761	-0.06363	2.832971	-4.86037	-7.41876	2.766677	3.785919
2001:09	-1.43358	6.956328	0.198798	0.098257	3.179163	-14.0641	-11.6189	8.408583	8.841683
2001:10	0.932227	7.115153	0.186218	0.16553	3.911386	-13.9874	-12.5903	8.672172	8.692534
2001:11	0.501351	7.372101	0.078434	0.269708	4.838688	11.38554	12.75349	7.277332	8.294976
2001:12	-0.38543	9.828366	-0.08314	0.289778	4.636121	11.23591	3.449864	7.954359	3.960002

ERDEV - Exchange Rate Devaluation

Figure 6: Malaysia

These panels show the evolution of a number of Malaysian indicators over the period November 1984 to July 2001 (banking sector data start in January 1986). REER is the percentage deviation of real effective exchange rate from its trend; IRDIFF is the domestic/U.S. interest rate differential on deposits; ERDEV is the exchange rate change computed using end of the month log-first difference; RDC is the deviation of the ratio between real domestic credit and GDP from its trend; M2ratio is the deviation of the ratio of M2 over reserves from its trend; GENRET and GENVOL are stock index returns and volatility, respectively; BANKRET and BANKVOL are returns and volatility of a stock indexed based on a portfolio of banks listed in the stock market.

Data for Figure 6: Malaysia

OBS	ERDEV	REER	M2ratio (Right axis)	RDC	IRDIFF	BANKRET (Right axis)	GENRET (Right axis)	BANKVAR	GENVAR
1984:11	0.82988	6.999526	-0.08818	-1.07804	2.659002		-2.66561		4.586604
1984:12	0.82988	9.191868	0.017348	-1.17516	2.733337		-0.11853		3.295387
1985:01	2.449102	8.06227	0.235647	-0.92942	2.074022		1.90886		4.915082
1985:02	2.78348	6.909626	0.749325	-0.74848	2.087996		0.290463		3.266435
1985:03	1.169604	6.032271	0.602307	-0.6344	2.096153		-1.43467		3.02453
1985:04	-3.55067	7.528062	0.68588	-0.4251	2.162895		-4.38397		3.484732
1985:05	-0.40242	9.394434	0.438759	-0.39369	2.904763		1.851184		2.932116
1985:06	-0.40404	9.6283	0.245925	-0.35008	0.858782		-6.38614		4.163829
1985:07	0	7.625923	-0.01203	-0.4325	0.802826		1.672967		8.199524
1985:08	-0.40568	6.482895	3E-05	-0.41055	0.789137		-5.56874		3.939343
1985:09	0.809721	8.294279	-0.27034	-0.12906	0.902951		9.959492		8.825027
1985:10	-1.21705	4.154688	-0.22651	0.076186	-0.71713		-2.28307		4.045179
1985:11	-0.81968	3.958158	-0.17347	0.266394	-0.68171		-12.2578		6.948216
1985:12	0	3.698438	-0.14171	0.594471	-0.67988		-9.61781		6.83759
1986:01	0.819677	2.169001	-0.26296	0.614142	-0.69397		-11.2156	7.137016	8.993979
1986:02	0.813013	-1.93694	-0.36653	0.592955	-0.73044	-3.29964	-5.98792	3.826692	5.511048
1986:03	2.400115	-7.52631	-0.2233	0.69853	-0.04709	-6.3533	-3.22592	8.780649	6.924746
1986:04	2.729214	-10.4059	-0.00775	0.898641	0.671604	-14.6774	-10.2894	9.551923	7.796794
1986:05	0	-11.082	0.067837	0.797521	0.653486	-4.99967	10.20532	6.89797	7.088774
1986:06	1.14724	-9.6602	-0.15581	0.776978	0.725743	21.86263	13.66684	15.57373	10.1561
1986:07	0.379507	-9.74523	-0.23588	0.873495	0.700605	-4.49098	-4.39286	5.736507	5.132078
1986:08	-1.14287	-9.04122	-0.01575	1.089043	2.114042	15.12206	11.5688	9.691857	6.982939
1986:09	0.38241	-8.45161	0.204008	1.298807	2.119664	-16.5769	-5.81383	14.76591	6.822417
1986:10	0	-8.57921	-0.10994	0.935239	2.103151	32.95846	19.83233	19.36475	11.2762
1986:11	-0.38241	-4.52625	-0.05191	1.00503	2.080296	-9.93789	-8.52823	9.296721	5.932149
1986:12	-0.38388	-3.59433	-0.15537	1.191521	0.726884	6.840746	1.988503	4.364493	2.211131
1987:01	-0.7722	-4.38479	-0.17357	1.12992	0.785688	8.887354	9.781718	7.866041	7.09795
1987:02	-1.56253	-2.09869	-0.09749	0.865858	-1.51524	17.97363	16.04278	14.21498	8.72531
1987:03	-0.79052	-0.63677	-0.06566	0.58471	-4.12925	-0.21822	-2.9878	5.113702	4.246595
1987:04	-1.19762	0.300347	-0.33838	0.105321	-4.10233	15.54177	12.48794	11.57748	10.41511
1987:05	-0.80646	0.712092	-0.25653	-0.06662	-4.08837	7.501758	11.49284	5.29715	7.233463
1987:06	1.60646	1.097876	-0.34238	-0.1769	-3.73422	1.22324	1.684846	2.515316	2.29986
1987:07	1.188133	1.657062	-0.39257	-0.33337	-4.04534	15.31938	9.021964	10.04799	6.196416
1987:08	0	1.988936	-0.65487	-0.55528	-4.00714	-5.15787	-4.18244	7.245443	6.598641
1987:09	-0.79052	2.592667	-0.45779	-0.6213	-4.63849	-7.46664	-3.53827	5.64616	4.864908
1987:10	0.39604	0.467288	-0.50273	-0.61291	-4.59432	-46.6849	-42.8972	39.38652	37.23104
1987:11	-1.19286	-0.88835	-0.53108	-0.67428	-4.59085	-5.63566	-10.6191	9.773491	9.219421
1987:12	-0.4008	-2.17543	-0.32143	-0.33464	-4.61205	-0.82152	7.120233	7.76036	15.19178
1988:01	1.988137	-3.69506	-0.23051	-0.1693	-4.26621	6.921755	7.967154	8.60303	6.41265
1988:02	1.562532	-3.84822	-0.12219	-0.10569	-4.25153	-2.0402	-4.0146	5.850911	5.185605
1988:03	-0.38835	-3.43561	-0.23503	-0.10899	-4.22058	0.261526	5.167598	2.859285	4.674415
1988:04	0	-3.35768	0.109807	-0.15417	-3.52082	4.481435	8.816117	3.699005	6.04371
1988:05	0.38835	-3.41464	0.22689	-0.19316	-3.16812	15.67138	3.983716	10.25175	3.354553
1988:06	0.386848	-0.30645	0.137229	-0.42197	-3.17792	9.993914	11.54055	6.721934	5.918103
1988:07	1.532597	0.067146	0.190698	-0.43008	-3.17311	0.615119	0.554669	4.298373	4.507211
1988:08	0.757579	0.606438	0.47181	-0.15085	-4.1087	-10.1761	-10.1975	8.36027	8.36523
1988:09	0.376648	0.111706	0.532419	-0.21422	-4.06566	1.38929	2.193496	2.313526	2.278066
1988:10	0.749067	-2.01681	0.097799	-0.34043	-4.03161	-1.27278	2.114627	2.6768	4.172225
1988:11	0	-3.57887	0.055469	-0.33675	-4.04429	-2.05536	0.633807	2.271393	1.672487
1988:12	0.743498	-4.37412	0.044461	-0.33512	-4.06224	0.342024	2.59939	2.676569	2.784335
1989:01	0.738011	-3.40192	0.407639	-0.0961	-3.38557	6.989832	8.867954	4.579431	5.571196
1989:02	0.366973	-3.26136	0.393318	-0.02917	-3.02347	1.617772	0.199534	3.241402	2.194525
1989:03	0.72993	-3.05128	0.405359	-0.1773	-2.97327	2.518993	4.595066	3.24614	3.439328
1989:04	-0.72993	-1.67028	0.31799	-0.14635	-2.92099	3.099834	7.418642	3.578397	4.750662
1989:05	-1.10498	1.483236	0.148164	-0.40207	-2.88953	10.16365	1.660918	7.906903	2.949684
1989:06	0.369686	2.710975	0.272071	-0.48629	-2.8687	0.87522	-0.69113	5.305797	5.321495
1989:07	-1.11318	3.314553	0.144552	-0.60643	-2.86904	9.059519	3.64502	6.046813	2.663978
1989:08	0	3.795393	0.25475	-0.55425	-2.8596	-0.03461	0.138405	2.407437	1.934131
1989:09	0.743498	4.054688	0.11294	-0.54565	-2.21315	6.295785	6.971441	4.001106	2.95865
1989:10	0	3.293369	0.089954	-0.59442	-2.17718	-7.13008	-4.31224	8.458677	7.664609
1989:11	0	2.712084	0.165688	-0.36793	-2.18948	10.57145	6.973334	6.69972	4.892961
1989:12	0	1.911252	-0.01098	-0.19075	-2.19494	13.43106	9.851306	9.798346	6.289443
1990:01	0	0.991106	0.025869	-0.01806	-2.10941	5.268095	1.402255	3.343251	3.792809
1990:02	0	0.951742	0.034788	0.021868	-2.10759	6.643925	5.621095	7.221141	5.468013
1990:03	0.738011	2.493191	0.077752	-0.08572	-2.06226	-0.36979	-3.29998	2.767734	2.457381
1990:04	0.366973	2.415417	0.162211	-0.1477	-2.08103	-11.9274	-11.4291	6.117206	5.234364
1990:05	-1.10498	2.01821	0.069998	-0.32078	-1.33222	12.16826	11.4754	7.88992	7.743405
1990:06	0.369686	1.701193	0.048355	-0.18383	-0.78583	-0.23388	0.133502	3.883998	1.860134
1990:07	0	0.463848	0.048579	-0.09666	-0.73129	8.825126	7.516665	8.097746	4.610813
1990:08	-0.36969	-0.49446	-0.05114	0.070169	-0.34634	-15.6398	-15.3038	17.44712	17.16091
1990:09	0	-1.8744	-0.17792	-0.05488	-0.00171	-18.9222	-16.3917	13.78313	11.52806
1990:10	0	-3.7766	-0.51593	0.154042	0.006909	7.676513	6.866463	9.481268	5.895588
1990:11	-0.37106	-4.10158	-0.14538	0.014167	0.571659	-13.7234	-5.64756	7.126645	2.235886
1990:12	0.371058	-2.94956	-0.2008	0.242768	1.082073	16.22067	8.4965	8.65776	4.904418
1991:01	0.738011	-3.5205	-0.08884	0.419828	1.093288	-0.08987	-1.72655	4.618445	3.978124
1991:02	-0.73801	-3.21416	-0.05731	0.395063	1.02798	10.23521	12.31003	7.206558	7.378733
1991:03	1.470615	-1.93005	-0.01485	0.229609	1.02211	3.797123	4.289665	4.047994	4.986375
1991:04	0.364299	-1.26744	-0.09573	0.352327	1.662795	-3.06196	0.280672	3.104139	2.496527
1991:05	0.362977	-0.92548	-0.08329	0.240709	1.642872	2.127007	6.700914	6.200752	5.798254
1991:06	0.722025	-1.10325	0.035502	0.5355	2.080491	-3.01355	-1.73054	1.905268	1.29357
1991:07	0.359067	-1.19973	0.030056	-0.02241	2.120723	-2.78373	-2.68316	3.718031	3.053297
1991:08	-0.35907	-1.81385	0.044996	-0.35552	2.586805	-8.07553	-8.45994	12.01453	11.30494
1991:09	-0.72202	-2.14444	0.177517	-0.62086	3.430123	-4.1373	-5.72009	3.725776	4.85451
1991:10	-0.36298	-2.79021	0.225868	-0.37256	3.884267	0.982494	1.652648	4.21482	3.373273
1991:11	-0.3643	-3.94974	0.230063	-0.3621	4.399131	-0.17018	0.129761	3.865611	3.249115
1991:12	0	-5.62137	0.163833	-0.09636	5.437976	6.606758	4.435125	4.716505	3.237935
1992:01	-1.84167	-3.90322	0.251112	1.049324	5.390837	0.11154	2.559464	3.104518	2.983019
1992:02	-3.40297	0.507012	0.379703	1.258306	5.255415	10.61207	5.856909	7.479292	4.53853
1992:03	-0.7722	2.8119	0.253185	1.89915	5.142978	-0.86304	-1.97792	2.804785	2.718244
1992:04	-1.1696	3.113972	0.160838	1.233882	5.301889	-0.15903	-0.2667	3.089069	3.031578
1992:05	-0.78741	3.415564	0.164169	0.680019	5.223827	-0.43139	-0.43025	2.446771	1.743507
1992:06	-0.39604	2.018797	0.445783	0.55716	5.45511	0.431387	0.548494	1.987521	1.954208
1992:07	-0.79682	1.725553	0.133203	0.286487	5.867886	3.964496	1.54125	3.41347	3.350368
1992:08	0	1.537576	-0.01022	-0.02263	5.723106	-2.46022	-4.5576	5.188467	5.114303
1992:09	0	0.956489	-0.29188	-0.19933	5.620195	10.80436	4.682209	7.963103	3.996685
1992:10	0	2.383807	-0.40754	-0.08259	5.655491	4.853731	6.279051	4.659746	5.151415
1992:11	0.796817	6.02098	-0.36663	-0.23299	5.572086	-1.00746	0.090399	4.321257	2.217632
1992:12	1.9647	3.869294	-0.05098	0.21964	5.538622	-0.67629	0.321966	2.746142	1.720962
1993:01	1.160555	3.729613	-0.02057	0.278111	5.428229	-1.81667	-3.07013	5.0148	2.203103
1993:02	1.14724	2.702536	0.145366	0.484661	5.085354	4.286459	2.170073	3.710158	2.153958
1993:03	-0.76336	2.788401	0.398742	0.433587	4.970773	-0.21486	0.789741	3.832732	1.126503
1993:04	-1.15608	1.487358	0.353423	0.156692	4.958108	10.0258	11.21759	5.981611	6.417857
1993:05	-0.38835	1.499365	0.549808	-0.10958	4.934012	9.17412	2.150118	7.361571	2.606685
1993:06	0	1.424275	0.505349	-0.36186	4.480236	1.464373	-1.93357	6.31408	3.8643
1993:07	0	1.861839	0.221051	-0.66141	4.446146	4.169482	6.041171	4.623066	4.391711
1993:08	-0.78125	2.511707	-0.02123	-0.61676	4.256755	17.62413	5.388171	10.61518	3.845709
1993:09	0	2.2734	-0.12262	-0.63207	4.14789	1.295345	5.45638	5.584516	2.809158
1993:10	0	2.546266	0.110759	-0.33792	3.923	15.4282	12.96134	10.01479	8.23765
1993:11	0	2.929494	-0.16422	-0.34739	3.883222	2.09668	2.485345	6.498546	4.898859
1993:12	0.781254	3.022096	-0.33524	0.464031	3.835051	44.91144	24.67534	26.85211	14.28119
1994:01	5.304274	-1.47712	-0.8933	0.644211	3.470269	-14.737	-14.1553	15.57254	16.3993
1994:02	1.828204	-5.06955	-0.75251	0.700791	3.192262	1.057789	1.669826	5.106649	4.40464
1994:03	-1.45988	-4.0565	-0.68448	0.79394	3.018319	-14.8264	-16.6777	10.89267	9.852086
1994:04	-1.10907	-3.13891	-0.57901	0.291556	2.292546	8.215267	10.15009	7.818023	8.283403
1994:05	-2.63669	-1.01745	-0.60428	-0.23584	0.924301	-2.54998	-5.93565	2.809036	3.382882
1994:06	-1.15164	-0.49256	-0.56968	-0.62849	0.875507	0.340367	1.78032	3.632152	5.196092
1994:07	0.385357	-2.26462	-0.47948	-0.96607	0.858322	5.935202	1.562493	5.525851	2.879121
1994:08	-1.16055	-0.73397	-0.44138	-1.13195	0.352238	7.696333	9.508808	3.457116	5.334464
1994:09	-0.38986	-1.3008	-0.41465	-1.14048	0.345814	1.958802	-0.02213	4.362354	3.315368
1994:10	0	-2.36523	-0.38553	-1.11619	0.437988	-0.17639	-1.86818	3.450919	2.327515
1994:11	0	-2.22732	-0.42532	-1.04636	0.626298	-7.2016	-9.02789	4.235876	5.493172
1994:12	0	-1.68694	-0.07482	-0.62317	0.560358	-6.14142	-4.22571	4.96171	6.542019
1995:01	0	-2.64382	-0.01508	-0.17501	0.558866	-6.42276	-9.48891	9.156764	8.932976
1995:02	-0.39139	-3.19756	0.016757	0.07254	0.036293	9.131846	10.35316	6.865048	4.433593
1995:03	0	-5.94758	-0.08049	0.502307	0.563265	3.033951	0.451188	5.599321	3.792304
1995:04	-2.78348	-5.69309	-0.08941	0.133909	0.580658	-2.98144	-3.33421	3.375528	3.639141
1995:05	-0.40404	-4.33288	-0.05777	-0.29367	0.557047	18.69298	9.819051	11.71409	6.631012
1995:06	-1.22201	-3.46534	-0.06131	-0.53696	0.56741	-4.03507	-2.25183	3.837567	3.590434
1995:07	0.408999	-3.18856	-0.10295	-0.4653	0.55578	9.12712	3.219515	6.184725	3.027404
1995:08	-0.81968	0.899613	0.131904	-0.35449	0.652437	-3.38645	-4.35094	3.799545	3.468073
1995:09	3.23915	-1.09846	-0.0036	-0.47328	0.74517	-3.85416	-1.43578	2.781488	2.155805
1995:10	0.793655	-2.58047