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ESTIMATION OF REAL EXCHANGE RATE MISALIGNMENT IN MALAYSIA

A. Omerbegovic', Sarajevo Graduate School of Business G. Sivalingam, Monash University

Abstract REAL EXCHANGE RATES IN SOUTH EAST ASIA

We estimate the Equilibrium Real Exchange Rate (ERER) prior to the 1997 East Asian currency crisis in Malaysia using the reduced form single equation general equilibrium approach. The ERER is obtained from the distribution of observable variables of Real Exchange Rate (RER) and the fundamental determinants of ERER, which include the terms of trade, the resource balance, sustainable values of net capital flows, the sectoral productivity differentials, the composition of government spending and the openness of the trade regime. The cointegration and error correction mechanism are shown to be consistent with the assumptions of the theoretical models relating the RER and the fundamentals so that they are considered appropriate econometric tools in estimating of the relationship between the fundamentals and RER, given the time series properties of RER and the fundamentals, which are found to be nonstationary. Based on the estimated cointegrating equation relating fundamentals and RER, the ERER is simply obtained by substituting permanent values of fundamentals into the estimated cointegrating relationship. The ERER estimated in the above manner is compared to the actual RER to provide the estimate of RER misalignment prior to the 1997 East Asian currency crisis. The RER misalignment estimates obtained in Malaysia indicate that the real exchange rate was overvalued by 16% at the end of 1996, using the Two Step Engle-Granger (1987) Cointegratoin and the Error Correctoin Mechanism. Using Cointegration and the Error Correction Model of Lim and Stein (1995) we find that the real exchange rate was overvalued by 11.5% in Malaysia at the end of 1996. Overall, the findings of this work suggest that the underlying economic fundamentals are a consistent predictor of the 1997 East Asian currency crisis in Malaysia.

1 INTRODUCTION Malaysia experienced a large devaluation of its currency in 1997 as a consequence of the East Asian currency crisis (Kim, 2000). Theories that emerged in the aftermath of the currency crisis have been grouped into two, that is, (i) those that attempt to explain the crisis in terms of the underlying fundamental variables of the crisis economies and (ii) those that attempt to explain the crisis in terms of the effect of moral hazard, speculative forces and contagion (Corsetti, Pesenti and Roubini, 1998) The theories that combine the two factors have also emerged in an attempt to explain the currency crisis mechanism, in the form of third generation currency crisis models like that of Chang and Velasco (1998) and Krugman (1998). The occurrence of the twin crisis, or the phenomenon of the banking system crisis occurring at the same time with the currency crisis gave rise to the twin crisis theory, which studies links between the banking and currency crisis (Kaminsky and Reinhart, 1999). 1.1 The Real Exchange Rate (RER) Misalignment Approach To Currency Crisis

Theories that attempt to explain the devaluation of currencies as a result of the 1997 East Asian Crisis in terns of fundamental variables postulate that nominal devaluation is a consequence of the real exchange rate being in dis-equilibrium or misaligned. This presumes that there is some equilibrium real exchange rate (ERER) value from which the actual real exchange rate (RER) diverges. The divergence between the RER and the ERER is due to the slow adjustment of nominal wages, capital stock and the level of net international indebtedness to their steady state equilibrium1 level; and/or due to the slow adjustment of the actual real exchange rate to permanent changes in policy and exogenous fundamentals2 that affect the equilibrium real exchange rate due to market rigidities and imperfections (Kaminsky, 1988); and/or other transitory influences on the underlying fundamentals3 affecting the economy (Edwards, 1989; Williamson, 1994). The prolonged deviation of RER from the equilibrium in terms of a real exchange rate overvaluation, can lead to the worsening of the trade balance, speculative attacks, increased foreign debt, fall in the rate of investment, productivity as well as overall growth4 (Gylfason, 2002). This approach makes the exchange rate policy relevant as nominal devaluation can bring fast adjustment of RER towards its long run equilibrium level. (Isard and Faruqee, 1998) It therefore follows that nominal devaluation can follow as a result of RER overvaluation and is seen as an equilibrating move since it brings the economy closer to its long run equilibrium. (Edwards, 1989) In the ideal situation

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These variables are also referred to as the predetermined variables since they differ from other fundamentals. These variables while they may be fixed at any given moment, evolve endogenously over time, influenced not only by the policy and exogenous variables, but also by the current and expected future values of the endogenous variables. Unlike predetermined variables, "policy" variables follow dynamic path that may or may not be affected by the current state of the economy. The exogenous variables are by definition independent of the current state of the domestic economy. 2 See footnote 1 above for definition of policy and exogenous variables. 3 All of the variables in footnote 1 are referred to as fundamentals that affect ERER. 4 Using data for a large sample of developed and developing countries, Razin and Collins (1997) find that "very high" overvaluations appear to be associated with slower economic growth. However, "moderate" under-valuations appear to be associated with more rapid economic growth. Under-valuations however could cause other problems such as higher rates of imported inflation.

countries with larger nominal exchange rate devaluations should have larger RER overvaluation5. The RER misalignment has been estimated for South East Asian countries using various approaches to measure ERER. At the center stage in testing the hypothesis of RER misalignment is determination of the equilibrium real exchange rate6 associated with the underlying fundamental variables. Since RER is the single most important relative price in an open economy, which affects the price of every tradable good and service and indirectly the value of every resource that flows into the production of those goods and services, it adjusts on the way towards equilibrium, to bring about internal balance (in terms of the goods and labor market) and external balance (in terms of sustainable current account deficits)7. (Kemme and Roy, 2002) The outline of this paper is as follows: Section 2 motivates our approach to studying the relationship between ERER and the fundamentals in Malaysia. The single equation reduced form approach to ERER allows us to adopt the general equilibrium approach to ERER despite the limitation of data for fundamentals that are found in equilibrium. The empirical model of relationship of fundamentals to ERER is established in section 3 and the constructs for fundamentals are defined. Section 4 estimates the relationship between fundamentals and RER and estimates the ERER based on permanent estimates of fundamentals. Section 5 concludes with evaluating the RER misalignment hypothesis in terms of explaining the nominal devaluation experienced by Malaysia as a result of the 1997 East Asian currency crisis based on the estimated relationship between fundamentals and RER. 2 SINGLE EQUATION REDUCED FORM GENERAL EQUILIBRIUM APPROACH TO ERER DETERMINATION IN DEVELOPING COUNTRIES

The ERER can be estimated from a single equation relating RER and fundamentals. The single equation relating ERER and fundamentals is a reduced form solution of an unspecified simultaneous equation system of the theoretical models of the likes of Edwards (1989), Stein (1995), and Montiel (1999). The approach rests on the argument that to the extent that the time horizon is long enough, one should expect fundamentals to eventually revert to their sustainable levels and be picked-up by time series-based methods. (Elbadawi and Soto, 1996) The approach also assumes that RER converges to ERER eventually, so that ERER, expressed as a linear function of fundamentals, can be obtained from the actual RER and fundamental variables. (Kaminsky, 1988).

RER overvaluation results if RER is at more appreciated level from ERER, RER undervaluation results when RER is at more depreciated level than ERER. 6 In the literature equilibrium real exchange rate is interchangeably referred to as long-run equilibrium real exchange rate (LRER) and equilibrium real exchange rate (ERER). Since equilibrium real exchange rate implies that fundamentals are in their steady state value for equilibrium to occur we simply refer to long run equilibrium real exchange rate as equilibrium real exchange rate. 7 This RER associated with internal and external equilibrium was termed as equilibrium real exchange rate (ERER) by Nurkse (1945).

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2.1 The Theoretical Model Of The Relationship Between ERER And The Fundamentals The single equation which expresses ERER as a linear function of fundamental variables is the steady state solution of some theoretical framework used to model the economy, given conditions of internal and external equilibrium. (Edwards (1989), Stein (1995), Montiel (1999)) The fundamental variables of trade policy, sectoral productivity differentials, share of spending on nontraded goods, external terms of trade and resource balance do not have readily available corresponding economic constructs in reality so that they have to be proxied. We explicitly define the constructs used to represent fundamental determinants of ERER in this text and justify their use based on the existing literature. The analytical framework of the Montiel's model modified to accommodate features important for small developing countries (Baffes et al.(1999)) shows that the stock equilibrium concept of external balance in theoretical model is consistent with a sequence of "flow" restrictions on the trade balance when countries are rationed in international financial market8, which allows us to treat trade surplus as one of fundamental determinants in empirical estimation of ERER. The ERER is therefore a vector of permanent values of its fundamental determinants. The fundamental determinants are obtained by solving the theoretical model for condition of internal and external equilibrium. Our theoretical model is based on Baffes et al. extension of Montiel (1999) to accommodate features of small open economies characteristic of Malaysia. The equilibrium real exchange rate is therefore given by Equation 1: e*=e*( gN, gT, b, *, µ, , t) Equation 1

The equilibrium exchange rate of a small open economy is therefore a function of government consumption on traded (gT) and nontraded goods (gN), trade surplus (b), differential productivity growth in traded sector relative to nontradable sector (µ), transaction costs associated with private spending (*), stance of trade policy ( ) and the external terms of trade (t). Other factors that exert change in any of these variables influence e*. The postulated effects of change in fundamental determinants of trade policy stance, external terms of trade, composition of government spending, sectoral productivity differentials and resource balance are consistent with the existing literature. The improvement in the external terms of trade, increase in productivity differential in favor

That is when they face an upward sloping supply curve of external loans. This assumption seams reasonable for small developing economies. See Baffes, et al. (1999: 411-412).

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of traded goods and increased government consumption of nontraded goods cause ERER appreciation. The relaxation of trade barriers and improvement of resource balance cause ERER depreciation. The model is consistent with the role of short-run dynamics which arise from wage price stickiness, costs of labor mobility, gradual asset adjustment and other possible fractions not considered that cause real exchange rate dis-equilibrium and provide the role for nominal devaluation to bring adjustment towards ERER consistent with the RER misalignment approach to currency crisis. The reduced form solution of ERER presented in Equation 1 is the basis of the single equation reduced form general equilibrium approach. Our empirical methodology developed in Section 3 is designed to capture this long-term relationship between ERER and the fundamental determinants using historical data on actually observed RER and fundamental determinants. Since fundamental determinants themselves required in this estimation do not have corresponding constructs in economic reality they are proxied. The constructs used to proxy fundamental determinants are derived from existing practices in the literature. We proxy the external terms of trade by ratio of export unit value to import unit value. Composition of government spending is proxied by share of investment in GDP. Sectoral productivity differential is proxied by ratio of GDP/labor at home relative to GDP/labor group average for OECD. Trade policy stance is captured by construct of openness measures as ratio of trade volume measure to GDP. And finally resource balance is given by the difference between exports of goods and nonfactor services and imports of goods and nonfactor services. These proxies are henceforward referred to as fundamentals. Next section proceeds to develop empirical methodology designed to capture the long term relationship between ERER and fundamentals with an objective of measuring ERER. To measure unobservable ERER from observable variables of RER and fundamentals we rely on features of the theory of ERER, which postulates that RER diverges from ERER only due to short run dynamics so that RER eventually converges to ERER enabling us to estimate ERER using actual RER and fundamentals (Kaminsky, 1988).

3.THE EMPIRICAL MODEL OF ERER ESTIMATION The linear relationship between ERER and fundamentals, which is central to single equation reduced form general equilibrium approach, has been adopted to represent either linear relationship between simple transformations of ERER and fundamentals such as logarithms (Elbadawi and Soto (1996), Baffes, Elbadawi and O'Conell (1999), Atiqur Rahman and Abdul Basher (2002), Xiaopu (2002)) or it has been taken to hold at levels of variables (Lim and Stein (1995), Rajan and Siregar (2002)). The empirical applications that adopt the assumption of linearity under simple transformations often result in mixing of variables that are transformed (i.e. logarithmic transformations of variables) and

variables that are taken at levels due to certain fundamentals having some negative observations9 (Edwards (1989), Tzanninis (1999)). To avoid this problem we follow those studies that assume that linearity of relationship holds at levels, and our empirical analysis therefore studies the relationship between the levels of variables of RER and fundamentals. Assuming that relationship between equilibrium real exchange rate and the fundamentals is linear in levels, enables us to express the model of equilibrium real exchange rate by Equation 2: et*=bFt* Equation 2

where, et* is the equilibrium real exchange rate, Ft* is the vector of permanent or sustainable values of fundamentals, and b is the vector of long run parameters of interest. (Elbadawi and Soto (1996), Kemme and Roy (2002)) To estimate long parameters, b, we need empirical model that is consistent with Equation 2 but relates observable variables. Since ERER is unobservable variable, estimation of b in Equation 2 from observable variables depends on two important features of the equilibrium real exchange rate theory: (a) Equation 2 comes from steady state relationship between actual values of real exchange rate and fundamentals so that we can estimate b by relating actual RER and fundamentals, and (b) the steady state is dynamically stable, that is, that the economy eventually converges to equilibrium given any instabilities. The shocks that cause the exchange rate to diverge from its (possibly new) equilibrium in the short run should produce eventual convergence to the relationship in Equation 2 in the absence of new shocks. (Baffes, Elbadawi and O'Connel (1999)). Translated into stochastic terms the first feature of the theory means that the disturbance term wt in Equation 3 is a mean-zero stationary random variable. et*=bFt*+wt Equation 3

where b is the cointegrating vector and wt is an uncorrelated random disturbance. The second feature of the equilibrium is captured by general error correction model10 given by Equation 4 below. (Elbadawi and Soto (1996), Atiqur Rahman and Abdul Basher (2002)) det=a(et-1-b'Ft-1)+(j=1,p) µj det-j +(j=0,p) j'dFt-j + vt

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Equation 4

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The most common example is the resource balance variable which has negative values and is not logarithmically transformed. This equation is just re-parameterization of the unrestricted pth order autoregressive distributed lag (ADL) representation of ln et. (see Montiel 1999: 417)

where Ft is the vector of fundamentals and vt is an independent and identically distributed, mean-zero, stationary random variable. Assuming that all variables are either stationary or I(1) in levels Equation 4 implies Equation 3 and for 2<a<0 the corresponding ERER is stable. Here changes in the exchange rate are a function of the difference between the last period exchange rate and the predicted long run value of b'Ft-1, plus short term period to period adjustments to both the previous period exchange rate and the current and previous period vector of macro fundamentals, n periods in the past. a, b', nj and yj' are parameters to be estimated and vt is an error term. The equilibrium exchange rate is then the predicted value from this equation based on a given vector of macroeconomic fundamentals, Ftp, assumed to be sustainable long run equilibrium values. (Kemme and Roy, 2002) Equation 4 embodies the central insight of the single equation approach: that the ERER can be identified econometrically as that unobservable function of the fundamentals towards which the actual RER gravitates over time (Kaminsky (1988), Elbadawi (1994), Elbadawi and Soto (1994, 1996). Our econometric work in this paper takes the form of versions of equation (4). 3.1 Two Step Engle-Granger (1987) Cointegration and Error Correction Mechanism Engle and Granger (1987) demonstrated an equivalence between cointegration and error correction for nonstationary variables. In the nonstationary case, therefore, Equation 3, which implies cointegration, also implies that the real exchange rate has a reduced-form error correction representation- that is one that is similar to Equation 4 but with contemporaneous values of the fundamentals excluded. It is this reduced form error correction equation that is estimated in the second step of the Engle-Granger (1987) method in Equation 5. The error correction mechanism allows that short run disequilibrium be treated as "equilibrium error" and used to tie short-term behavior of RER to its long-run value. Therefore, in the second step, lagged residuals from the static regression in Equation 3 can be used in place of the equilibrium error on the right-hand side of a reduced form error correction equation below (Gujarati, 1995:724) det=a + bdFt + cut-1 + zt Equation 5

where d denotes first difference; ut-1 is the one-period lagged value of the residual from regression (Equation 3), the empirical estimate of the equilibrium error term; and z is the error term with usual properties. The alternative way to obtain parameters b in case of I(1) variables is to obtain it directly from general error correction mechanism in Equation 4 but since general error correction mechanism above requires that the short term parameters and long term parameters are estimated simultaneously, the studies which are faced with small samples, including ours,

follow the empirical methodology to estimation of cointegration and error correction mechanism provided by the two-step Engle-Granger (1987) procedure.11 (Rahman and Basher, 2002) Nevertheless, the alternative in small samples is provided in the form of Lim and Stein's (1995) modification of the general error correction mechanism. 3.2 Cointegration and Error Correction Mechanism of Lim and Stein (1995) The general error correction mechanism in Error! Reference source not found. 4 offers the alternative to estimating parameter b with the advantage of being able to encompass variety of short run dynamics, which depend on the nature of nominal rigidities and real rigidities that have little or no effect on the set of variables that enter the long run equilibrium, while retaining consistency with the long run specification. The unrestricted error specification allows the data maximum scope for determining their actual pattern, while retaining consistency with the long-run specification. (Avallone and Rault, 2002) However, estimation of unrestricted error correction of Equation 4 is difficult to estimate given the available sample size. The small sample size raises question about the power of unit root based econometric techniques so that alternative estimators are recommended. The unrestricted model of Equation 6 is the form that Equation 4 usually takes form since only one lag of variables on the right hand side are taken in order to maintain reasonable degrees of freedom (Rahman and Basher, 2002). det=a(et-1-b'Ft-1)+y'dFt + vt Equation 6

The unrestricted general error-correction model of Equation 6 requires simultaneous estimation of long run cointegrating parameters (b') and short run parameters (y'), which may pose a problem in estimations with small number of observations. Lim and Stein (1995) provide alternative by taking single proxy for the change in fundamentals (dFt), in order to estimate the version of the Equation 4 using least squares (LS) estimation techniques. Starting from the steady state relationship for equilibrium real exchange rate provided by Equation 2 above, Lim and Stein (1995) assume dynamic system equation in relationship between e and exogenous fundamental determinants F: et=aet-1+bFt+cFt-1+u Equation 7

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The results of the estimation using econometric specification of adjusted ECM proposed by Stein (1995) are only used to check the consistency of the long run parameters b obtained using the two step Engle-Granger (1987) procedure. The results of this technique take second place to those obtained using Engle-Granger (1987) procedure due to assumptions involved in the econometric specifications. The main concern being the introduction of proxy for change in fundamentals through some market measure.

Supposing that Ft=Ft-1 so that expectations of the change in endogenous variable are zero E(det)=0, transforms the steady state into Equation: et*=aet*+bFt-1+cFt-1 Which can easily be transformed into et*=bF(t-1) Equation 9 Equation 8

To obtain this cointegrating vector et=bFt-1, Lim and Stein (1995) show by empirical manipulation that steady state is represented by the following equation e=bF(-1)+a [e(-1)-bF(-1)]+c dF+ u Equation 10 Where e represents actual real exchanger rate, and F represents fundamental determinants and u is error term. The first term is the cointegrating equation and the second term is the error correction. Following Phillips-Loretan technique, set et and Ft can be matched with no lags (Campbell and Perron 1991:190), so that the final equation estimated takes the form: e=bF+a [e(-1)-bF(-1)]+c dF+ u Equation 11 Since estimation of short-term effects y (in equation Equation 6) associated with dF term would have required large number of parameters to be estimated simultaneously, this short term effect of change in fundamentals dF is proxied by the market measure. Changes in fundamentals dF shift the IS and IS' curves in Stein's analytical model and produce interest rate differential (r-r'), which leads to portfolio adjustments and capital flows which then produce convergence. To avoid simultaneous equation problem this interest rate differential is measured by the real long-term interest differential lagged by one time period. The procedure takes second place to two step Engle-Granger (1987) due to assumptions involved in the econometric specifications. The main concern being the introduction of proxy for change in fundamentals through some market measure. 3.3 Calculating ERER After long run parameters b of Equation 3 are estimated using appropriate econometric tool given unit root properties of the data series estimation of sustainable fundamentals F* is next step in measurement of ERER. The sustainable fundamentals are then combined with b to arrive at ERER, that is ERER=bF*.

We capture the effect of sustainability of the net capital flows and other fundamentals on ERER prior to the currency crisis in Malaysia in this step. The estimation of value of sustainable fundamentals involves some methodological issues. Time series based (or data based) permanent values of fundamentals are by nature of construction of cointegration methodology unable to detect substantial misalignment (Elbadawi, 1999:443) We follow methodology of Baffes, Elbadawi and O'Connell (1999) in using counterfactual estimate of net sustainable capital flows assuming that estimated long-run parameters of cointegrating equation are invariant to class of distributional shifts under consideration12 since we consider the net capital flows to be the fastest changing variable influencing ERER. Compared to the time-series based estimates or ex post approaches which rely on datagenerating processes of the fundamentals, counterfactual estimates are ex ante modeling of the fundamentals which are motivated by positive and normative reasons. Positive reason for counterfactual estimates is to avoid difficulties faced by the time series decomposition method or moving average in distinguishing persistent but unsustainable changes in the fundamentals from genuinely sustainable changes. Normative reasons lie in answering what would happen if fundamentals were to change. Both of these reasons motivate construction of a path for fundamentals in question which is in line with a plausible notion of sustainability. (Baffes, Elbadawi and O'Conell, 1999) Since we are interested to test changes in equilibrium real exchange rate if net capital inflows were to change the counterfactual estimation of sustainable level of the capital flows determine the resource balance variable used to calculate ERER. We do this by excluding part of "unsustainable" net capital inflows used to finance resource balance following the argument by Williamson and Mahar (1998), we differentiate between private direct investment, which tends to be long-term in nature, and liquid private portfolio investment, by excluding 50% of former and 100% of the later from net capital inflows to arrive at the "sustainable" resource balance. The other fundamental determinants of ERER should also be in their permanent state in equilibrium. In the case of exogenous variables and those that adjust very slowly the time series based estimates of their sustainable values are used. Time series estimates of sustainable values of fundamentals are obtained using moving average technique along the methodology of Edwards (1994) and Baffes et al. (1999)

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Estimating misalignment using sustainable value of fundamentals is done using time paths for the fundamentals that are not used in estimating long run parameters. This does not pose a problem under super-exogeneity assumption, which holds when the vector of long run parameters in equation e=bF is relevant for assessing the effect of alternative paths for the fundamentals. This assumption is along the weak exogeneity assumption key ingredient of the single equation methodology. This however requires super-strong exogeneity to hold which requires invariance of the parameters of interest to the class of distributional shifts under consideration. (Engle, Hendry and Richard 1983) The invariance property is taken as a maintained hypothesis rather than being tested as it is sensitive to the particular class of interventions under study. Single equation approach can provide fully efficient estimation and inference based on conditional estimation on fundamentals when these fundamentals are weakly exogenous. This condition holds when the parameters that describe relationship of ERER to fundamentals can be directly recovered from the distribution of the real exchange rate conditional on the fundamentals (and the past) and there are no cross-equation restrictions linking the parameters of this conditional model with those of the marginal model for the fundamentals. In this case marginal distribution of fundamentals holds no information to estimating the parameters of interest. Elbadawi (1999:421) This assumption is implied in estimation of ERER (e*) from single equation e=bF.

which use moving averages to estimate permanent values of fundamentals used in ERER calculation. Moving averages technique is appropriate for both nonstationary and stationary variables and avoids presumptions of permanent component and judgmental nature involved in its estimation13 in series which may be misidentified as nonstationary due to our small sample. At the same time moving average technique allows us to recognize that even stationary variables may have long-lasting movements. If current value of the variable is far from its unconditional mean using moving averages allows the ERER to move in response to current values of the fundamentals even if they are ultimately temporary (Baffes et al., 1999:444). ERER calculation as "sustainable" RER, which is the fitted RER in which the fundamentals have been replaced by their sustainable values14, enables us to calculate the RER misalignment for Malaysia. Given the equilibrium real exchange rate the misalignment can be calculated as: mt=et*-et Equation 12 Once the misalignment is calculated we have determined whether the currency is overvalued or undervalued prior to the currency crisis and may make statements about the RER misalignment hypothesis in Malaysia prior to 1997 East Asian currency crisis. The test of hypothesis of RER misalignment is evaluated by comparing the extent of nominal devaluation experienced in the year of 1997 of currency crisis occurence to the extent of RER misalignment measured as of the end of 1996 following the literature which evaluates RER misalignment hypothesis using annual data series (Atiqur Rahman and Abdul Basher (2002), Xiaopu (2002)).

4 EMPIRICAL ANALYSIS: ESTIMATION OF ERER MISALIGNMENT IN MALAYSIA In this section we estimate the misalignment of the real exchange rates in Malaysia on the eve of the 1997 East Asian currency crisis using the reduced form single equation methodology linking the real exchange rate to a set of fundamental variables (Edwards (1989), Razin and Collins (1997)).

Nonstationary series have both transitory and permanent components, with the permanent component corresponding to the underlying stochastic trend. In the case of nonstationary variables sustainable values of the variables are assumed to correspond to the permanent component. This permanent component is estimated by Beveridge-Nelson method which views fundamentals as ARIMA(p,1,q) process. Autoregressive and moving average parts generate stationary fluctuations about an underlying random walk (Beveridge and Nelson, 1981). Movements generated by unit-root are permanent and are extracted as an estimate of the sustainable component of the respective fundamental variable.

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The equilibrium real exchange rate is then the predicted value from cointegrating equation (et=bFt) based on a given vector of macroeconomic fundamentals, Ft*, assumed to be sustainable long run equilibrium values, et*=bFt*.

We begin by defining and documenting the sources of data in section 4.1. Section 4.2 reports results of the time series properties of the data. Section 4.3 tests the existence of cointegrating relationship between the fundamentals and data. Section 4.4 proceeds to estimate the long run parameters b of the ERER vector (et*=b*Ft) using the appropriate econometric tools given the time series properties of the data. Section 4.5 calculates the ERER given the sustainable values of fundamentals, where counterfactual estimate of sustainable resource balance given sustainable net capital flows and time series estimates of slower adjusting fundamentals is combined with the estimated parameters b. Section 4.6 calculates the degree of RER misalignment as the difference between the ERER estimated in section 4.5 and the actual RER. 4.1 Definition and Measurement of the Variables The variables found in the reduced form single equation are the actual real exchange rate (et) and the fundamental determinants of the equilibrium real exchange rate (Ft), which include the terms of trade , sectoral productivity differential, openness of the economy, the resource balance to GDP ratio and the investment share. (i) Real exchange Rate, e (RER) On theoretical grounds defining the real exchange rate as the relative price of tradable to nontradable goods is preferable. We however experiment with the measure of trade weighted multilateral index of relative price to the general price index as a proxy for real exchange rate, following the literature. (Edwards (1989), Stein (1995), Baffes et al. (1999)). We use the multilateral trade weighted index as a measure of RER. The real exchange rate provides the implied measure of external competitiveness of a country relative to another country. In evaluating competitiveness it is necessary to use or construct a broad multilateral index of the real exchange rate, which provides a measure of the degree of competitiveness of a country relative to a group of its trading partners. (Edwards, 1989:88) We construct the multilateral index of the real exchange rate using the methodology of Edwards (1989: 88) which is represented by Equation 13 below to measure the competitiveness of Malaysia against her largest trading partners: multilateral RERjt= ((i=1,k) ai Eit Pit*) / Pjt Equation 13

In the above equation the multilateral RERjt is the index of the multilateral real exchange rate in period t for country j; Eit is an index of the nominal exchange rate between country i and country j in period t; i=1..k refers to the k partner countries used in the construction of the multilateral RER index; ai is the weight corresponding to partner i in the computation of multilateral RERjt; Pit* is the price index of partner i in period t; and Pjt is the price index of the home country in period t. An increase in the value of this index of

multilateral RER reflects real depreciation, whereas a decline implies a real appreciation of the domestic currency. In the construction of the multilateral RER indexes the following procedure was followed: 1) The weights used (ai) were trade weights constructed using data from the International Monetary Fund publication "Direction of Trade Statistics"; 2) The countries chosen were the 5 largest trading partners who accounted for 80 percent of the trade with Malaysia over the period 1970-1996; 3) in all cases the nominal exchange rate (Eij) were implied cross exchange rates between these countries and their trading partners. We constructed multilateral RER indexes using both CPI and GDP deflators as measures of general price levels in the foreign and the domestic economy. We compared these measures to test whether they differ significantly since the CPI (which reflects the cost of imported goods) and the GDP deflator (which reflects the cost of exports) based measures of external RER may diverge over the long term due to changes in productivity, tariffs and terms of trade.15 Typically, when the terms of trade improve, the GDP deflator will rise faster than the CPI. But when the TOT deteriorates the opposite will happen. Hence, the real exchange rate indexes computed using these price indexes will diverge. Our results did not find significant difference between multilateral RER indexes based on CPI and GDP deflators in accordance with Edwards's (1989:90) observation of multilateral RER indexes for 12 developing countries where the choice of price deflator did not result in significant difference between the RER indexes. Hence, we choose to use the CPI based measure of RER as a matter of congruence and simplicity. 2. Terms of Trade (TOT). The terms of trade is ratio of PX/PM , where PX and PM are export and import price indexes. 3. Openness or OPEN is defined as the ratio of imports (IMP) to GDP (GDP) all in current prices: OPEN=IMP/GDP.16 4. Resource balance to GDP Ratio (RESGDP). The value of exports at constant prices (EXPKP) minus the value of imports at constant prices (IMPKP), divided by the GDP at constant prices (GDPKP). EXPKP has been adjusted by the domestic terms of trade (TOTD), which are defined as the ratio of the export price deflator to the import price deflator. Thus RESGDP=(EXPKP*TOTD-IMPKP)/GDPKP. 5. Investment Share (ISHARE). The ratio of gross investment at constant prices (IGROSS) to the sum of private consumption (PCONK), government consumption

15

The effects of changes in productivity and tariffs are best analyzed using two and three good internal RER but are expected to be less dramatic then terms of trade change impact on external measures of RER. (Montiel, 1999:89) 16 We also experiment with the following variables: OPEN2 is the ratio of the value of imports at current prices (IMPKP) plus exports at constant prices (EXPKP) to GDP at constant prices (GDPKP). OPEN2=(IMPKP+EXPKP)/GDPKP. OPEN3 is the ratio of imports at constant prices to domestic absorption at constant prices: OPEN3=IMPKP/(GDPKP-(EXPKP-IMPKP)).

(GCONK), and gross investment, all of which are measured at constant prices: ISHARE=IGROSS/(PCONK+GCONK+IGROSSK). 6. The Balassa-Samuelson Proxy (BS). Since sectoral productivity measures are not available across the countries over the sample length, following the methodology of Baffes et al. (1999) the average labor producitivity growth relative to the developed world is used as a proxy for fundamental determinant of sectoral productivity differential. The average labor productivity growth in developed world is proxied by the OECD group average following the Baffes et al. (1999) application to developing countries of Burkina Faso and Cote d'Ivoire. A lagged 3-year weighted moving average of the ratio of home country GDP per worker to the OECD GDP per worker, using the World Development Indicators world tables for these variables. The measure of the OECD GDP per worker was constructed by summing the OECD GDP and dividing by the total number of OECD workers. We denote the ratio (R) of GDPs per worker in year t as R(t): BS(t)=(3/6)*R(t-1)+(2/6)*R(t-2)+(1/6)*R(t-3). The data were obtained from two sources: 1) the IMF, International Financial Statistics; b) the World Bank Development Indicators (WDI), published by the World Bank. 4.2 Time Series Properties Of Data Series Table 1 present the results of the standard Augmented Dickey-Fuller (ADF) (1979) statistics and the Philipps-Perron (PP) test (1988), which are used to assess the unit root properties of the data. The MacKinnon critical values (1991) are reported alongside of the results of the ADF and the PP tests.

Table 1: Tests for Stationarity: Malaysia ADF RER TOT RESGDP OPEN BS3 ISHARE -0.6577 -3.2289 -3.5348 0.1815 0.6154 0.1450 PP -0.6531 -4.5137 -3.9870 0.4123 2.33804 0.2297 Decision I(1) I(1) I(1) I(1) I(2) I(1)

Notes: test assumption includes constant in test equation

For the Augmented Dickey-Fuller statistics (ADF), the MacKinnon critical values are: 1%=-3.7076, 5%=-2.9798, 10%=-2.6290. Critical values for the PP test are: 1%=-3.6959, 5%=-2.9750, 10%=-2. Sample period is 1970 to 1997. The test value of the critical values performed on the variables indicate that the test value is greater in absolute terms than the critical value when the data series are considered stationary. When the test value is less than the critical value the test is performed on the first difference of the data series. If the test value exceeds the critical value then the first difference of the data series is stationary, so that the data series at that level are considered to possess unit root (I(1)). The results obtained from the standard ADF and the PP test suggest that the variables under consideration exhibit unit root properties17, that is they are integrated of order one (and their first differences are stationary. 4.3 Test of Cointegration Since the relevant data series used in the empirical analysis are nonstationary (integrated of order one) it follows that a cointegrating regression can potentially be formed if the series are found to be cointegrated. Table 2 contains the Johansen (1998) test for the number of cointegrating vectors for Malaysia. The Johansen (1988) cointegration imposes a restriction on the reduced form or VAR representation of the joint distribution of the real exchange rate and its fundamentals. (Baffes, Elbadawi and Connell, 1999) We use a lag length of one for the underlying VAR system; this is very restrictive even for annual data, but a longer length leaves us with very few degrees of freedom. The null hypothesis for these tests is that the number of cointegrating vectors relating n nonstationary variables is less than or equal to r (where r<n). Comparing the estimated likelihood ratios in column 2 to the asymptotic critical values in column 3, we see (row 1) that the hypothesis of no cointegration (r=0) can be rejected in favor of at most one cointegrating vector. In row 2, the hypothesis of one cointegrating vector cannot be rejected in favor of more than one. The asymptotic tests therefore indicate one cointegrating vector for Malaysia at the 1 % confidence interval. (see Table 2). The Johansen maximum-likelihood procedure which tests for the number of cointegrating vectors in Table 2, shows that we have 1 cointegrating vector for Malaysia.

17

This is with the exception of BS variable in Malaysia and Thailand which are stationary when differentiated twice, that is they are integrated of order two (I(2)). We difference this variable once in order to bring all variables to the same order of integration, that is I(1). Recently, techniques have emerged to estimate relationship between variables of different order of integration (see Phillips (1995) and Phillips and Chang (1995)). We consider benefit of cointegration tools more useful in capturing theoretical premises of the methodology and therefore consider differentiating this variable to be more useful.

Table 2: Malaysia- Johansen maximum likelihood procedure for testing the number of cointegrating vectors The variable set is (RER, ISHARE, DHBS, TOT, RESGDP, OPEN ) Max. eig. Stat . Null Likelihood Ratio Max. eig. Stat. [99% crit] (1) (2) [99% crit] (4) (3) R=0 140.95 94.15 103.18 R<=1 74.29 68.52 76.07 R<=2 40.25 47.21 54.46 R<=3 16.83 29.68 35.65 R<=4 5.11 15.41 20.04

Notes: Test assumption: linear deterministic trend in data. Intercept in cointegrating equation and test VAR.

4.4 Estimation of Cointegrating Relationship Between RER and Fundamentals The existence of cointegration between the variables of RER and the fundamentals suggests that the econometric techniques of Cointegration and Error Correction Mechanism, are appropriate for estimating the relationship between RER and its fundamental determinants. We estimate the cointegrating parameters, b, in using the two step Engle-Granger (1987) cointegration and error correction methodology (1987). We report the results of the alternative technique of the Cointegration and Error Correction Mechanism of Lim and Stein (1995) to check the consistency in the direction of the estimated long-run parameters from the two step Engle-Granger (1987) Cointegration and Error Correction Mechanism and as a way of improving the robustness of the estimated parameters given the questionable performance of the unit root techniques in small samples.

4.4.1 Two-Step Engle-Granger (1987) Cointegration And Error Correction Mechanism Estimation Results In this section we present the empirical estimation results for the two-step Engle-Granger (1987) Cointegration and Error Correction Mechanism. We first estimate the long run cointegrating relationship by estimating Equation 2 using the OLS technique by relating actual real exchange rate (e) to actual values of fundamentals (F). The results of this estimation are provided in Table 3 for Malaysia. et*=bFt*+wt The explicit form of Equation 3 tested is Equation 14: Equation 3

RER=c(1)+c(2)*RESGDP+c(3)*TOT+c(4)*ISHARE+c(5)*BS+c(6)*OPEN+wt Equation 14 Cointegration implies that the residuals of Equation 3, wt are stationary, and this restriction provides a test for cointegration18. Table 3 provides results of this EngleGranger (1987) two-step procedure test for cointegration. There is strong evidence of cointegration in each case, as indicated by the unit-root test applied to the estimated residuals: in each case the calculated values reject nonstationarity in favor of stationarity at standard levels19. Finally, we examine the short-term dynamics of real exchange rate, e, by estimating an error correction model of Equation 15 where residuals from static regression (wt) in Equation 3, are used in place of the equilibrium error on the right hand side of the error correction equation to tie short-term behavior of RER (e) to its long-run value. det=a + bdFt + c wt-1 + zt Equation 15

where d denotes first difference; wt-1 is the one-period lagged value of the residual from Equation 3, the empirical estimate of the equilibrium error term; and z is the error term with usual properties. The explicit form of Equation 15 tested is Equation 16: dREER=c(1)+c(2)*dRESGDP+c(3)*dTOT+c(4)*dISHARE+c(5)*dBS+c(6)*dOPEN+c( 7)*w(t-1) +zt Equation 16 Table 3 provides results of estimation of Equation 16 for Malaysia.

Baffes, Elbadawi and O'Connel (1999) note that estimates of b from the static regression are super-consistent, approaching the true parameters at a rate proportional to the sample size rather than the square root of the sample size; and they remain so even in the absence of weak exogeneity. 19 Note that the critical values for this test are more demanding than when testing for a unit root in a single variable, since the OLS estimation tends to induce stationarity in the residual. (Gujarati, 1995)

18

Table 3: Step One Engle-Granger (1987) Cointegration and Error Correction ProcedureLong Run Parameter Estimates : Malaysia Variable Coefficient TOT OPEN RESGDP DBS ISHARE Coefficient t-stat 1.009135 -0.504358 2.693593 2.291381 -6.918238 -2.292183 4.663288 -1.947477 12.36119 5.360572 -1.590110 -2.557359 2-tail significance 0.0001 0.0644 0.0000 0.0000 0.1261 0.0180

Dependent variable: RER Notes: Adjusted R-Square=0.952774; Durbin-Watson=1.209646 UROOT(N,0)= -4.156013 ; ADF critical value 5%= -2.9798

ADF

(e-bF):

Table 4 Results On Engle-Granger (1987) Two Step Procedure For Testing Cointegration Unit root test of the residuals from the long run relations Long run equation (4.1) ADF Test Statistics Order of Integration Malaysia -4.156013 I(0) MacKinnon (1991) critical values for rejection of null of no cointegration are 2.98 and 2.62 at 5% and 10% levels respectively. Table 5 Short Run Dynamics: Malaysia (Two-Step EngleGranger (1987) Cointegration and Error Correction Mechanism) Variable Coefficient ERR(-1) DTOT DOPEN DRESGDP D(DBS) DISHARE Notes: Dependent Watson=1.656269 Coefficient t-stat 0.011155 -0.452445 -0.463282 1.787222 1.439288 -7.266500 -1.096955 variable: 0.625031 -2.063297 -1.183857 3.563527 1.516212 -1.620321 -1.021820 Adjusted 2-tail significance 0.5390 0.0523 0.2503 0.0019 0.1451 0.1208 0.3191 R-Square=0.478659; Durbin-

DRER;

4.4.2 Cointegration and Error Correction Mechanism of Lim and Stein (1995) We identified equation 11 as one way of empirically specifying the relationship between ERER and its fundamental determinants. In this section we estimate the cointegration parameters b of this equation using single equation method20 of constrained general error correction specification. In this way we control for short-term dynamics while estimating long-run parameters of fundamental determinants (b). This approach solves for the problem of persistence in the residual estimates of the cointegration vector in the two-step Engle-Granger (1987) procedure21, which is cause of bias in small sample. Taking account of short run dynamics in this case offers superior estimates (Banerjee and others 1993). The Cointegration and Error Correction Mechanism of Lim and Stein (1995) as presented in Equation 17 below is used to estimate long run parameters of fundamental determinants, b, while controlling for short term dynamics. The short run parameters associated with dF component of unrestricted error correction mechanism are measured by (r-r')(-1) following the methodology of Lim and Stein (1995). The explicit form of tested is Equation 17: R=[c(1)+c(2)*RESGDP+c(3)*TOT+c(4)*ISHARE+c(5)*BS]+c(6)*[R(-1)-c(1)c(2)*RESGDP(-1)-c(3)*TOT(-1)-c(4)*ISHARE(-1)-c(5)*BS(-1)]+c(7)*(r-r')(-1)+e Equation 17 Table 6 present the results of the estimation of Equation 17 for Malaysia.

20

Single equation methods: two-step Engle-Granger (1987) method and unrestricted error-correction specification have been utilized extensively in recent literature on developing countries with the justification that they offer superior performance in small samples compared to a systems approach of Johansen (1988) based on estimation of the full VAR (Hargreaves, 1994). Two-step Engle-Granger (1987) method applies OLS to a static regression relating the levels of the real exchange rate and its fundamentals. Cointegration implies that residuals from this equation are stationary and this restriction is a test for cointegration. Engle and Granger (1987) proved that under nonstationarity of variables cointegration and error correction are equivalent. Therefore, the implication of cointegration also means that real exchange rate has a reduced form error correction representation. This reducedform error correction equation is estimated in the second step of the procedure. Lagged residuals from the static regression in the first step are used in place of equilibrium errors on the right hand side of a reduced form error-correction equation.

21

Table 6: The Cointegrationa and Error Correction Mechanism of Lim and Stein (1995): Malaysia The equation for the real exchange rate of Malaysia 1970-1997 Number of observations:27; Variable Coefficient t-stat 2-tail significance Coefficient TOT RESGDP OPEN DBS ISHARE Error Correction Term 1.285875 -0.698179 1.775009 1.784111 -5.618495 -0.632741 0.818082 3.576458 -2.050190 2.381523 3.867247 -1.199262 -0.610927 4.001207 0.0019 0.0537 0.0273 0.0010 0.2444 0.5481 0.0007

Notes: Adjusted R-Square=0.962678; Durbin-Watson=1.9261 ADF (e-bF): UROOT(N,0)=-3.532738; ADF critical value 5%=-2.9850 ; The estimates for the short run parameters proxy (r-r')(-1) were insignificant and were excluded in the empirical estimations reported in Table 6. The potential problem of interpretations and of the simulations based on Equation 11 results from the introduction of the real interest gap (r-r') as a proxy for dF, which in effect introduces short run (for example cyclical) factors as explanatory variables in the calculation of ERER, whereas it is supposed to capture the adjustment of ERER to medium term values of long term fundamental variables. This would mean that simulations of ERER based on fitted values of Equation 17 would simply be generating the short run equilibrium rather than ERER. (Montiel, 1999: 254) Due to the problems involved in estimation of Equation 17 mentioned above we give priority to the long-term parameters b obtained by two-step Engle-Granger (1987) Cointegration and Error Correction Mechanism procedure. 4.5 Calculating ERER Once the long run parameters b in Equation 3 relating RER and the fundamentals are estimated, the next step in the calculation of ERER is the estimation of sustainable fundamentals F* so that ERER (e*) is given by e*=bF*. Since our objective is to test changes in ERER given the net sustainable capital flows, the resource balance variable is calculated by determining sustainable levels of capital flows. The sustainable resource balance is given as actual resource balance from which 100 percent of FPI and 50 percent of FDI are deducted following the methodology of Williamson and Mahar (1998), which considers liquid portfolio investments as volatile

and unsustainable. We also take the permanent values of productivity, terms of trade, openness and investment share in GDP by smoothing the time series by using 3 year moving averages. Compared to the RESGDP variable, which is very sensitive to sustainability of capital inflows, TOT is exogenous variable for small open economy of Malaysia. While this variable fluctuates substantially from year to year we have no basis on which to question the sustainability of its long-run movements. We therefore use time series based estimate of sustainable value of this variable by obtaining three year simple moving average. The sustainability criterion for ISHARE, which represents the ratio of investment to GDP in constant price, is its consistency with a desired long-run growth rate of GDP per capita (Baffes et al., 1999:463). The high ISHARE values observed in Malaysia prior to the crisis and already high openness of the economy prior to the crisis are considered to be at the desired level and slow changing compared to resource balance so that we use moving average of actual investment levels for Malaysia as permanent values of these fundamentals. The effect of trade liberalization undertaken in the 1980s and import content of investment already reflected in high value of openness variable observed leaves conclusion that trade policy was already very open and moving average of actual openness variable is used for Malaysia. These variables are considered as slower changing so that their permanent values are obtained as moving average of data series. The ERER is then obtained as a fitted value of the estimated long run cointegrating equation using the sustainable values of fundamentals. This ERER is referred to as "sustainable" ERER and is reported in column three of Table 7 for Malaysia for the two step Engle-Granger (1987) Cointegration and Error Correction Mechanism. Combination of the sustainable fundamentals with parameters of the General Error Correction Mechanism of Lim and Stein (1995) is reported in column three of Table 8. 4.6 Calculating The Degree of Misalignment The degree of misalignment can be calculated as percentage difference between the real exchange rate and the equilibrium value of the RER. We measure misalignment as the difference between ERER estimated using sustainable values of fundamentals and the actual RER. "Sustainable" RER is the fitted RER in which the fundamentals have been replaced by their sustainable values. The "fitted RER" is the one estimated from the cointegrating regression using actual values of fundamentals. Presentation of "fitted RER" helps us illustrate that calculation of sustainable values of net capital flows is a necessary step for a meaningful estimation of ERER as temporary responses to unsustainable fundamentals should not be taken as an indicator of long run overvaluation or under-valuation. This question can be answered only by looking at how sustainable those movements itself are. (Avallone and Rault, 1999) Table 7 report the observed RER, sustainable ERER as well as fitted RER for Malaysia, obtained from the cointegrating equation estimated. The last column of Table 7, shows

the gap between the observed and equilibrium real exchange rates using the "sustainable" simulations for the equilibrium rate. The gap between these two series provides a measure of the real exchange rate misalignment. Since our RER is measured as index where 100=1 the difference between RER and ERER is equal to percent overvaluation/undervaluation. Table 8 reports the observed RER, sustainable ERER as well as fitted RER for Malaysia obtained based on the Cointegration and Error Correction Mechanism of Lim and Stein (1995). The last column of Table 8, shows the gap between the observed and equilibrium real exchange rates using the "sustainable" simulations for the equilibrium rate. The gap between these two series provides a measure of real exchange rate misalignment.

Table 7: Observed and Equilibrium RER Indexes for Malaysia 1970 to 1997 (1970=100) (Two Step Engle-Granger (1987) Cointegration And Error Correction Mechanism) Column Year 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1 Observed 1.00 1.04 1.05 1.01 0.99 1.03 1.09 1.12 1.21 1.17 1.20 1.23 1.15 1.13 1.11 1.17 1.44 1.57 1.74 1.74 1.78 1.87 1.77 1.85 1.96 1.93 1.76 1.81 2 Fitted 1.10 1.07 1.04 0.95 1.06 1.13 1.15 1.07 1.11 1.24 1.27 1.19 1.13 1.07 1.07 1.21 1.42 1.57 1.63 1.73 1.78 1.84 1.65 1.74 1.95 2.00 1.86 1.88 3 "Sustainable " 4 Misalignment

1.13 1.17 1.26 1.11 1.16 1.26 1.33 1.34 1.36 1.30 1.33 1.37 1.42 1.50 1.49 1.74 1.83 1.86 2.03 2.08 1.88 2.03 2.11

-12.34 -11.80 -13.27 0.84 4.60 -7.00 -9.96 -8.58 -15.51 -13.10 -16.30 -14.71 1.60 4.72 17.02 0.03 -2.85 0.74 -12.99 -10.94 4.49 -4.97 -16.54

Note: The observed RER is the one used in the econometric analysis. The fitted RER is the one estimated from the cointegration regression. The "sustainable" RER is the fitted RER in which the fundamentals have been replaced by their sustainable counterparts. The RESGDP sustainable is equal to actual RESGDP adjusted for the change in RESGDP required in case of capital flows outflows comprising 100 percent of foreign portfolio inflows and 50 percent of foreign direct investment. The OPEN, ISHARE, TOT and BS sustainable are given by 3 year moving averages. Misalignment is defined as 100(sustainable RERobserved RER)/observed RER.

Table 8: Observed and Equilibrium RER Indexes for Malaysia 1970 to 1997 (1970=100) (Cointegration and Error Correction Mechanism of Lim and Stein (1995)) Column Year 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1 Observed 1.00 1.04 1.05 1.01 0.99 1.03 1.09 1.12 1.21 1.17 1.20 1.23 1.15 1.13 1.11 1.17 1.44 1.57 1.74 1.74 1.78 1.87 1.77 1.85 1.96 1.93 1.76 1.81 2 Fitted 1.21 1.20 1.21 1.13 1.20 1.25 1.25 1.19 1.21 1.29 1.28 1.26 1.24 1.21 1.20 1.28 1.48 1.56 1.59 1.66 1.69 1.74 1.62 1.70 1.84 1.89 1.80 1.83 3 "Sustainable " 4 Misalignment

1.26 1.28 1.34 1.22 1.24 1.30 1.35 1.37 1.41 1.38 1.39 1.42 1.45 1.51 1.49 1.67 1.74 1.76 1.91 1.95 1.79 1.91 1.99

-21.22 -19.39 -18.56 -7.93 -2.64 -9.91 -11.40 -10.75 -18.79 -17.94 -20.05 -17.87 -0.70 3.81 17.38 4.27 2.53 6.09 -7.44 -5.17 9.35 0.71 -11.46

Note: The observed RER is the one used in the econometric analysis. The fitted RER is the one estimated from the cointegration regression. The "sustainable" RER is the fitted RER in which the fundamentals have been replaced by their sustainable counterparts. The RESGDP sustainable is equal to actual RESGDP adjusted for the change in RESGDP required in case of capital flows outflows comprising 100 percent of foreign portfolio inflows and 50 percent of foreign direct investment. The OPEN, ISHARE, TOT and BS sustainable are given by 3 year moving averages. Misalignment is defined as 100(sustainable RERobserved RER)/observed RER.

Figure 1 presents graphically the percent misalignment for Malaysia for each year from 1970 to 1997 based on the results of the Two Step Engle-Granger (1987) Procedure. Since our RER is measured as index where 100=1, the difference between RER and ERER is equal to percent overvaluation/undervaluation, with the minus sign representing overvaluation and the positive sign indicating undervaluation of RER. Figure 2 presents the percent misalignment for Malaysia for each year from 1970 to 1997 based on estimation using Cointegration and Error Correction Mechansim of Lim and Stein (1995).

Real Exchange Rate Misalignment: Malaysia

20.00 15.00 10.00 Misalignment (%) 5.00 0.00

19 72 19 84 19 82 19 90 19 94 19 70 19 78 19 92 19 80 19 76 19 74 19 86 19 88

-5.00 -10.00 -15.00 -20.00

Year misalignment

Note: Negative (positive) value indicates RER overvaluation (undervaluation).

Figure.1 Misalignment Malaysia (as percent difference between real exchange rate and ERER) Two Step Engle-Granger (1987) Cointegration and Error Correction Mechanism

19 96

Real Exchange Rate Misalignment: Malaysia

20.00 15.00 10.00 RER Misalignment 5.00 0.00

19 70 19 74 19 76 19 78 19 80 19 82 19 84 19 86 19 88 19 90 19 92 19 72

-5.00 -10.00 -15.00 -20.00 -25.00

Year misalignment

Note: Negative (positive) value indicates RER overvaluation (undervaluation).

Figure.2 Misalignment- Malaysia: Cointegration and Error Correction Mechanism of Lim and Stein (1995)

5 CONCLUSION Recognizing the endogeneity of the equilibrium real exchange rate and adopting a mild and testable assumption that the distance between the actual and the equilibrium real exchange rate is a stationary random variable, justifies the use of the cointegration method for estimating the long-run relationship between the real exchange rate and its fundamentals. Since the methodology adopted assumes that the economy was in internal and external equilibrium on average over the sample period, it implies that the average degree of misalignment in the sample will tend, by construction, to be small, if depending on only the time series estimates of sustainable value of fundamental variable of resource balance. To observe the impact of change in sustainable value of net capital flows on ERER we performed counterfactual simulations for this fundamental. We find that in Malaysia, the real exchange rate was overvalued by 16% at the end of 1996, using the Two Step Engel Granger Methodology. Using the Cointegration and Error Correction Model of Lim and Stein (1995) we find the real exchange rate to be overvalued by 11.5% in Malaysia at the end of 1996. In our counterfactual estimation for Malaysia, the smaller trade deficit associated with the outflow of volatile international financial flows produces a

19 96

19 94

depreciation of the equilibrium rate and therefore tends to increase the estimated degree of misalignment prior to the 1997 East Asian currency crisis. This is evident in higher sustainable RER (ERER), or more depreciated value of sustainable RER compared to the fitted RER value calculated using the actual resource balance variable.

3

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