Purchasing Power Parity in South East Asian Countries Economies: A Cointegration Approach *

Transcription

1 PURCHASING [Asian Economic Journal POWER 1997, PARITY Vol. 11 No. IN 2] ASIAN ECONOMIES 141 Purchasing Power Parity in South East Asian Countries Economies: A Cointegration Approach * Ahmad Zubaidi Baharumshah Universiti Pertanian Malaysia Mohamed Ariff Monash University This paper presents findings from a study of the long-run purchasing power parity (PPP) conditions in five Asian economies. The cointegration tests using exchange rates and price indices from end-of-quarter observations over the last twenty years reject the PPP proposition for all countries. The absolute version of the PPP hypothesis is tested next by using lower frequency, that is, semi-annual and annual, data. In general these tests also failed to support the long-run PPP hypothesis. Further analysis using the Johansen-Juselius (1990) multivariate approach also failed to support the hypothesis. I. Introduction Purchasing power parity (PPP) states that the exchange rate, defined as domestic currency per unit of foreign currency, should be equal to the ratio of the domestic to the foreign price levels. The theory implies that a currency s purchasing power is equal across countries at least in the long-run. Convergence of prices through exchange rate adjustment is a doctrine of great importance in trade and financial economics theory and practice, and forms one of the foundations for understanding any open economy behaviour. It has received a great deal of attention in the literature and interest in PPP s significance has increased since the early 1970s following the breakdown of the fixed exchange rate regime, when more and more countries shifted exchange rate management away from fixed-rate management of currencies towards some of form of floating. The * We thank the Editor for forwarding anonymous reviewers comments, which were useful in revising the paper. Part of the work for this paper was completed while Mohamed Ariff was visiting Professor of Finance at the Universiti Pertanian Malaysia. The research assistance of Ivan Tan at the National University of Singapore is also acknowledged: the data for this study were extracted from the original database compiled by him. For any remaining errors, we take joint responsibility.

2 ASIAN ECONOMIC JOURNAL 142 research emphasis has also shifted from simply a concern with equilibrium to interest in short-run or long-run equilibrium relationship, the latter using lower frequency data to test not only the PPP relationship but also the relationship in different exchange rate regimes together with the investigation of structural breaks using cointegration tests. Testing the PPP hypothesis is important since findings relating to it are used, implicitly or explicitly, in many of the current international monetary economics research and policy decisions. For example, the early monetary model of the exchange rate by Frenkel and Johnson (1978) assumes continuous PPP, while the sticky-price exchange rate model, which was developed by Dornbusch (1976) to allow for short-run exchange rate deviations from PPP, helped to preserve the PPP as a long-run equilibrium condition for the exchange rates of any two open economies trading with each other. Most of the literature on PPP appears to emanate from studies of this relation for the European, Japanese and United States economies. Generally, empirical studies on PPP using post-1973 data for these economies often report significant and even persistent deviations from equilibrium (Frenkel, 1981; Edison, 1985; Ardeni and Lubian, 1989; Corbae and Ouliaris, 1988). For example, Corbae and Ouliaris (1988) and Edison (1985) use unit-root and cointegration tests to reject PPP for this group of economies. These findings also cast doubt on the ability of the flexible exchange rate system to insulate domestic economies from shocks originating abroad or on the desirability of even the managed or dirty float. Deviations from PPP also explain the inflation dynamics of an economy. As pointed by Dornbusch (1987), real appreciation dampens inflation and real depreciation increases inflation. However, some studies using annual (lowfrequency) data over periods in this century thus, these are long-run tests of PPP obtained results favourable to the long-run PPP (Kim, 1990; Edison, 1987; Manzur and Ariff, 1995). 1 This article reports tests on the long-run PPP relationship. The conventional method for testing PPP is to regress exchange rates on relative prices for pairs of countries and then to test the coefficient restrictions (see, for example, Frenkel, 1981). Standard Wald statistics are computed to determine whether the parameter estimates are consistent with the restrictions embodied in PPP. In this paper, we employ the cointegration analysis suggested by Engle and Granger (1987) to test for the long-run relationship between exchange rates and prices. The cointegration approach has been widely used in applied work ranging from tests of securities market efficiency to purchasing power parity. Several desirable features of this approach have been identified, and widely recognised as being superior to earlier approaches. First, it exploits the non-stationarity 1. Hendry (1986) points out that increasing the sample size by time disaggregation is unlikely to reveal long-run relationship. Some authors argued that high-frequency data over a short horizon may not be able to detect the performance of PPP because the time needed for PPP to be re-established for a pair of countries following any disturbance ranges from two to ten years.

3 PURCHASING POWER PARITY IN ASIAN ECONOMIES 143 properties of the economic variables: in the case of PPP, they relate to the exchange rate and price level variables. Test results based on inappropriate treatment of non-stationary variables are shown to lead to unreliable results. Second, it does not rely on the assumptions of exogeneity or causality among the variables. This is important since simultaneous equation bias may invalidate the results from any tests on PPP. Third, the cointegration theory provides an ideal framework for testing long-run equilibrium relationship implied by economic theory without having to impose any constraint on the short-run dynamics. The paper is organised as follows. Following this introduction, a brief review on the theory of PPP is provided (Section II). This is followed in Section III by a description of the two-step cointegration testing procedure suggested by Engle and Granger (1987). Section IV then presents the data sources and the econometric evidence. Finally, Section V provides a summary and conclusions. The evidence in this article does not support the PPP predictions in any of the five Asian countries. II. Purchasing Power Parity The relationship between exchange rate and price is given by the PPP hypothesis. PPP in its absolute version states that the equilibrium exchange rate between domestic and foreign currencies equals the ratio of domestic to foreign price levels. The relative version of the hypothesis relates equilibrium changes in exchange rates to changes in the ratio of domestic to foreign prices. This study is concerned with testing the absolute version of the hypothesis though we provide one test on a relative version of PPP. Specifically we are interested in the long-run relationship since the short-run version of PPP has been rejected by numerous studies (see Frenkel (1981) as an early example). However, there is no general consensus in the literature on PPP as a long-run relationship in the period following floating (in its different variations) exchange rate management. A fuller treatment of the theory may be found in any of the afore-cited papers, especially Frenkel and Johnson (1978). The Engle and Granger (1987) theory of cointegration can be used to test the absolute version of PPP. If the absolute version of PPP is true, and the nominal exchange rates and price levels follow an integrated process of a specified order, inter-commodity arbitrage actions of traders should force the linear combination of nominal exchange rates and price levels to be cointegrated, so that the series produced will behave in a bounded manner. III. III.1 Testing for Unit Roots and Cointegration Unit Roots For two or more variables to be cointegrated, two conditions must be satisfied. The first is that the series must have similar statistical properties. That is, they

4 ASIAN ECONOMIC JOURNAL 144 must be integrated of the same order. 2 For example, a variable with a constant mean cannot explain the movements of another variable whose mean is increasing over time. The second condition for cointegration is that there should exist some linear combination of the integrated series which is stationary. 3 If exchange rates and price levels are known to be ~I(1), the two variables are said to be cointegrated if a linear combination of them is ~I(0) (that is, producing a stationary series). Hence it is possible for these two variables to have a stable long-run relationship. Two asymptotically equivalent procedures for detecting a unit root in exchange rate and price level data are used in our analysis: (1) the Augmented Dickey-Fuller (ADF) test (Said and Dickey, 1984), and (2) the Phillips and Perron (PP) (1988) test. As explained by Corbae and Ouliaris (1988), both procedures allow for fitted drift in the time series model. The ADF test accounts for temporally dependent and heterogeneously distributed errors by including lagged innovation sequences in the fitted regression. In contrast, the Phillips and Perron test accounts for non-independent and identically distributed process using non-parametric procedure. Since the ADF relies on parametric procedure to correct for autocorrelation and heterogeneity, the Phillips and Perron test is often favoured over the ADF in term of its power. 4 III.2 Cointegration Tests of PPP The equilibrium relationship implied in the absolute version of PPP assumes that perfect commodity arbitrage will ensure that the price of goods produced domestically (expressed in some common currency, say the dollar) will be equal to the price of goods abroad. This absolute version of the PPP relationship can be expressed as P t = E t * P t * (1) where P, E, and P* are the domestic price level, exchange rate and foreign price level respectively. In the short run, it is possible that the equilibrium relationship may not hold. For example, a disturbance (for instance, from monetary shock) will cause a deviation from the PPP. However, in the long run one would expect the shock to be dissipated and neutralized and the deviation from PPP would tend to converge to a long-run equilibrium path (that is, PPP holds in the long run). 2. A purely non-deterministic time series X t is said to be ~I(d), (integrated of order d) if the dth difference series D d X t is a stationary and invertible ARMA process. 3. In general, two I(d) series X t and Y t are said to be cointegrated of order (d, b) if there exists a constant a such that Z = (X t ay t ) is I( b) with b > 0. If b d = 0 the time paths of X t and Y t are constrained by a long-run equilibrium relationship. 4. Another simple test often reported for cointegration analysis is the Sargan-Bhargava Test (1983). The Sargan-Bhargava test is simply the DW statistic in the OLS estimation of the cointegration regression (CRDW).

5 PURCHASING POWER PARITY IN ASIAN ECONOMIES 145 If both the relative prices and nominal exchange rates are integrated of the same order, we can then proceed to run the cointegrating regressions. The logarithmic version of the PPP can be written as e t = α 0 + α 1 (p t ) + ε t (2) where e is (the logarithm of the) nominal exchange rate defined as the domestic price of a foreign currency, p is the logarithm of the series for relative price, α s are the coefficients to be estimated and ε is the disturbance term. The residual in Equation (2) represents the short-run deviation from PPP. A necessary condition for PPP to hold is that ε must follow a stationary process. When ε is produced by a stationary process, deviations from its equilibrium value (mean) are corrected through time. A cointegrated system provides a strong support for the absolute version of PPP. Otherwise, the process will tend to get larger over time and e (exchange rate) and p (prices) will diverge without a bound. To establish the existence of a cointegrating relation, the residuals from Equation (2) are tested for stationarity in their level. The ADF as well as the PP test may be used to test for H 0 : ε t ~ I(1) against H 1 : ε t ~ I(0). Briefly, the DF (Dickey-Fuller) and ADF statistics are defined with respect to an auxiliary regression ε = φε + b ε + v t t 1 j j= 1 n t j t where v t is iid (0, σ 2 ). If the disturbances, v t, in Equation (3) are white noise with n = 0, the appropriate statistic for testing the null hypothesis of no cointegration is the t-ratio of φ in Equation (3) (this leads to the DF statistic). If lagged values of ε t are necessary to induce white noise in Equation (3), the appropriate test parameter is still the t-ratio of φ (ADF statistic). Critical values for the univariate time series provided by Fuller (1976) are not appropriate here. The appropriate critical values for testing the residuals from the cointegration regressions are given in Engle and Yoo (1987) and Engle and Granger (1987). The PP test is asymptotically equivalent to the DF test. Unlike the strict iid error assumption of DF, the conditions imposed on the error sequences are weaker in the PP. As an alternative to the inclusion of lag terms to allow for serial correlation, the PP method uses non-parametric procedure to correct for autocorrelation. Briefly, the PP statistic is the DF t-statistic adjusted by factors that account for heterogeneity of the error process. The test statistics have the same limiting distribution as the corresponding DF statistics (Corbae and Ouliaris, 1986). IV. IV.1 Data Sources, Results and Discussions Data The analysis used in this study is based on quarterly data (1974: Q1 to 1993: Q4) available from IMF International Financial Statistics for five South East (3)

6 ASIAN ECONOMIC JOURNAL 146 Table 1 Unit Root Tests Using Post-1973 Exchange Rates and Relative Prices from Asian Countries (Levels Data) Exchange Rate Relative Price ADF PP ADF PP Rupiah US Dollar 0.494(0) (1) 2.519(0) 2.426(1) Ringgit US Dollar 1.496(0) 1.598(1) 1.742(7) 2.241(1) Pesos US Dollar 0.751(2) 0.164(5) 0.201(1) 0.191(1) Sin $ US Dollar 0.433(2) 0.097(1) 2.454(4) 2.268(1) Baht US Dollar 1.118(0) 1.142(1) 1.468(0) 1.45(1) Note: The null hypothesis is that the series is I(1). Figures in the parentheses for the ADF are the number of lags in auxiliary regression and for PP statistics figures in parentheses are the choice of truncated lag l. The rejection region is {tîr 1 /2t < c} with c = 3.58, 2.93 or 2.60 at a significance level of 1%, 5% or 10% respectively. See Fuller (1976, p. 373) and Dickey and Fuller (1981, p. 1063). Sample period is 1974: Q1 to 1993: Q4. Asian countries: Malaysia, Indonesia, Thailand, the Philippines and Singapore with the US data as reference. The time period covers the recent floatingexchange regime and is long enough to test for PPP as a long-run relationship using the cointegration analysis. Nominal exchange rates are expressed as units of local currency per US dollar. The relative price is the US price index divided by a similar domestic price index. In all cases CPI (consumer price index) is available and the series are seasonally unadjusted. 5 IV.2 Results and Discussions The results of applying the ADF and PP statistics for the unit root test are reported in Table 1. The results suggest that in all cases the level of the logarithms of exchange rates and relative prices (measured by consumer price indices) in the five countries are nonstationary. Thus to achieve stationarity both variables must be first-differenced. The lag length for the unit root tests is chosen so as to guarantee white noise in the residuals. Notice that the ADF (or DF) and PP statistics were significant only for the first-differenced series (see Table 2). Thus, all exchange rate and price series appear to be ~I(1), a condition that violates stationarity assumption. The results reported in Tables 1 and 2 provide the basis for estimating the cointegration equation given by Equation (3). The test of cointegration is to estimate the cointegration regression and conduct unit root test on the residuals 5. For most of the economies, data on the wholesale price index (WPI) are unavailable for our analysis. More recent studies have used the WPI instead of the CPI because the WPI is a better proxy for the prices of tradable goods than the CPI. However, Corbae and Ouliaris (1990) argued that stationarity measurement error due to the use of incorrect price index (or the omission of tariffs adjustment) will not affect the validity of the test of PPP.

7 PURCHASING POWER PARITY IN ASIAN ECONOMIES 147 Table 2 Unit Root Tests Using Post-1973 Exchange Rates and Relative Prices from Asian Countries (Levels Data) Exchange Rate Relative Price ADF PP ADF PP Rupiah US Dollar 4.751(3) 9.119(1) 3.987(3) 7.658(1) Ringgit US Dollar 3.842(4) 7.791(1) 2.505(3) 7.441(1) Pesos US Dollar 3.578(3) 8.171(1) 2.763(6) 6.379(1) Sin $ US Dollar 3.444(5) 8.741(1) 3.726(4) 8.368(1) Baht US Dollar 4.276(3) 8.237(1) 3.418(5) (1) Note: The null hypothesis is that the series is I(1). Figures in the parenthesis for the ADF are the number of lags in auxiliary regression and for PP statistics figures in parenthesis are the choice of truncated lag l. The rejection region is {tîr 1 /2t < c} with c = 3.58, 2.93 or 2.60 at a significance level of 1%, 5% or 10% respectively. See Fuller (1976, p. 373) and Dickey and Fuller (1981, p. 1063). Sample period is 1974: Q1 to 1993: Q4. Table 3 Cointegrating Regressions Using Post-1973 Exchange Rates and Prices from Asian Countries Rupiah-US Dollar e t = p t R 2 = 0.94 CRDW = 0.28 ADF = 3.43(0) PP = 3.41(0) p t = e t R 2 = 0.94 CRDW = 0.28 ADF = 3.70(0) PP = 3.69(1) Ringgit-US Dollar e t = p t R 2 = 0.23 CRDW = 0.18 ADF = 1.88(0) PP = 1.99(1) p t = e t R 2 = 0.23 CRDW = 0.05 ADF = 2.02(0) PP = 1.99(1) Pesos-US Dollar e t = p t R 2 = 0.98 CRDW = 0.51 ADF = 3.50(2) PP = 3.28(2) p t = e t R 2 = 0.98 CRDW = 0.50 ADF = 3.38(2) PP = 3.24(2) Sin $-US Dollar e t = p t R 2 = 0.73 CRDW = 0.19 ADF = 1.75(4) PP = 2.02(2) p t = e t R 2 = 0.72 CRDW = 0.16 ADF = 2.90(4) PP = 2.43(4) Baht-US Dollar e t = p t R 2 = 0.38 CRDW = 0.17 ADF = 1.53(5) PP = 1.95(5) p t = e t R 2 = 0.38 CRDW = 0.32 ADF = 1.37(5) PP = 2.29(5) Note: The null hypothesis is that the series is I(1). The rejection region for sample n = 50 is {tîr 1 /2t < c} with c = 4.12, 3.29 or 2.90 at a significance level of 1%, 5% or 10% respectively. See Engle and Yoo (1987, p. 158). CRDW is the cointegrating regression Durbin- Watson statistic. The critical values for the CRDW are 1.00, 0.78 and 0.69 at significance level of 1%, 5% or 10% respectively. Estimated coefficient standard errors are not reported since they may be misleading (see Engle and Granger (1987)). from the regression. The CRDW, ADF and PP statistics for the cointegration tests of the absolute version of PPP are presented in Table 3. The number of lagged innovations used for Equation (3) varies from 1 to 5. The results given in the table show that e and p for Ringgit-US Dollar, Sin $-US Dollar and

8 ASIAN ECONOMIC JOURNAL 148 Baht-US Dollar are not cointegrated. The residuals of the cointegrating regressions are nonstationary (that is, the process is I(1)). This suggests that the deviations between exchange rates and relative prices persist indefinitely, that is, there is no tendency for e and p to settle together in the long run. However, in the case of Indonesia and the Philippines, Table 3 indicates both variables in the cointegration equations are I(0). The results of both the ADF and PP tests suggest that PPP holds for these two economies. 6 The test for the long-run PPP hypothesis using Equation (3) assumes symmetry and proportionality. As pointed by Ardeni and Lubian (1989) these assumptions may be restrictive, at least for the industrialized economies. 7 Following Ardeni and Lubian, the PPP relationship, without imposing any restrictions on the coefficients, may be written in logarithm form as e t = α 0 + α 1 p t + α 2 p t * + z t (4) where all the variables are as defined above and z t is the equilibrium error. In line with this argument, no a priori restrictions on the coefficients are imposed, so a three-variable cointegration regression is given by Equation (4), which was estimated. 8 The PPP hypothesis may be tested in this case by showing the z t is stationary. The regression results for these tests are summarized in Table 4. Interestingly, the results of this more general specification show that there is no long-run equilibrium relationship between exchange rates and relative prices for all countries. The evidence provided by the CRDW, the ADF and PP test statistics shown in the table leads to the same conclusion. We reported the estimates for the three cases in which the dependent variable is the exchange rate, the domestic price level and the foreign price level respectively (see Table 4). Ardeni and Lubian (1989) reported similar results using the general specification given by Equation (4). We conclude that the results obtained earlier for Indonesia and the Philippines may be due to the symmetry imposed a priori on the exchange and price data. The evidence yielded by applying cointegration tests to the same data set but without imposing the symmetry restriction did not favour PPP. By testing an unrestricted PPP equation, we are able to show that PPP is uniformly rejected for all the economies Note that the CRDW statistic for the cointegartion equation is lower than its critical value, indicating lack of cointegration between e and p in all cases. This result should not affect our conclusion about Indonesia and the Philippines given the low power of the CRDW statistic. 7. For more detail discussion on symmetry, see Frenkel (1980) and Edison (1985). Ardeni and Lubian (1989) showed that by using the more general specification they were able to reject PPP. They argued that the results reported by Taylor and McMahon (1988) with the symmetry restriction imposed were not robust. 8. Proportionality restriction may be imposed in Equation (4) by restricting a 0 = 0, a 1 = 1 and a 2 = 1. The symmetry hypothesis implies that a 0 = 0 and a 1 = a Note that the restricted PPP equation given by Equation (2) would be a test of joint hypothesis of non-cointegration and equal coefficient.

9 PURCHASING POWER PARITY IN ASIAN ECONOMIES 149 Table 4 Cointegrating Regressions Using Post-1973 Exchange Rates and Prices From Asian Countries Rupiah-US Dollar e t = p D t 2.818p F t R 2 = 0.94 CRDW = 0.31 ADF = 2.76(0) PP = 3.50(1) p F t = e t p D t R 2 = 0.99 CRDW = 0.26 ADF = 2.81(1) PP = 2.58(1) p D t = e t p F t R 2 = 0.99 CRDW = 0.31 ADF = 3.04(1) PP = 3.07(1) Ringgit-US Dollar e t = p D t 0.199p F t R 2 = 0.28 CRDW = 0.19 ADF = 1.90(2) PP = 2.90(2) pt F = e t 1.496p D t R 2 = 0.99 CRDW = 0.19 ADF = 1.75(0) PP = 1.95(1) p D t = e t p F t R 2 = 0.99 CRDW = 0.19 ADF = 2.07(7) PP = 2.71(7) Pesos-US Dollar e t = p D t 1.139p F t R 2 = 0.98 CRDW = 0.50 ADF = 3.46(2) PP = 3.27(2) p F t = e t p D t R 2 = 0.97 CRDW = 0.41 ADF = 2.22(2) PP = 2.99(2) p D t = e t p F t R 2 = 0.99 CRDW = 0.50 ADF = 3.53(2) PP = 3.24(2) Sin $-US Dollar e t = P D t 0.394p F t R 2 = 0.74 CRDW = 0.16 ADF = 0.81(2) PP = 1.44(2) p F t = e t 1.695p D t R 2 = 0.97 CRDW = 0.31 ADF = 3.34(4) PP = 2.89(3) p D t = e t p F t R 2 = 0.96 CRDW = 0.32 ADF = 2.87(4) PP = 2.77(4) Bath-US Dollar e t = p D t p F t R 2 = 0.76 CRDW = 0.20 ADF = 2.25(1) PP = 2.06(1) p F t = e t p D t R 2 = 0.99 CRDW = 0.38 ADF = 2.86(0) PP = 2.16(0) p D t = e t p F t R 2 = 0.99 CRDW = 0.37 ADF = 2.72(1) PP = 2.71(1) Note: The null hypothesis is that the series is I(1). The rejection region for sample n = 50 is {tîr 1 / 2t < c} with c = 4.45, 3.75 or 3.36 at a significance level of 1%, 5% or 10% respectively. See Engle and Yoo (1987, p. 158). CRDW is the cointegrating regression Durbin- Watson statistic. The critical values for the CRDW are 1.00, 0.78 and 0.69 at significance level of 1%, 5% or 10% respectively. The estimated coefficient standard errors are not reported since they may be misleading (see Engle and Granger (1987)). The above results were based on quarterly data. However, some authors have argued that the poor performance of PPP or non-cointegration of the exchange rates and price ratios in the earlier studies may be due to the nature of highfrequency data used in the analysis. For example, Frenkel (1986) argues that long-run PPP is most accurately tested using annual data. In this paper, we also examined the long-run relationship by using semi-annual and annual data. The results of the tests using these respecifications of intervalling periods using Equation (4) are summarized in Table 5. In general, we again found no support for the performance of PPP for all the countries concerned using lower frequency data to attest a long-run relationship. The two-step testing procedure of cointegration suggested by Engle and Granger (1987) has faced one major criticism. In a multivariate case like this study (the trivariate model), this procedure may be used to test the null hypothesis of noncointegration against one alternative only. However, Johansen and Juselius (1990) provides estimates of all cointegrating vectors. In this paper we employed the

10 ASIAN ECONOMIC JOURNAL 150 Table 5 Cointegration Tests Using Post 1973 Annual and Semi-annual Data from Asian Countries Biannual Annual ADF PP ADF PP Rupiah US Dollar 1.44(0) 1.48(1) 1.52(0) 1.61(1) Ringgit US Dollar 2.30(0) 2.27(1) 1.72(0) 1.76(1) Pesos US Dollar 2.65(3) 2.88(3) 3.38(0) 3.38(1) Sin $ US Dollar 1.68(1) 2.68(1) 1.21(0) 1.40(1) Baht US Dollar 2.13(0) 2.15(1) 2.03(0) 2.06(1) Note: The null hypothesis is that the series is I(1). The rejection region is {tîr 1 / 2t < c} with c = 4.45, 3.75 or 3.36 at a significance level of 1%, 5% or 10% respectively. Table 6 Johansen-Juselius Cointegration Test Results Using Post-1973 Exchange Rates and Prices Variable Trace Maximum Eigenvalue No.Lags Q(8) p = 0 p 1 p 2 p = 0 p 1 p 2 k Malaysia Indonesia 26.99* * Philippines Singapore Thailand Critical Values at 95% Notes: In all cases a restricted constant is included in the cointegrating equation. p indicates the number of cointegrating vectors. The Ljung-Box Q(8) statistics show no evidence of serial correlation. The test statistics are based on k lag structure of the VAR model. Significance is indicated by * at the 5% level. Johansen and Juselius (1990) maximum likelihood method to the trivariate model and the statistical results are summarised in Table 6. The choice of the lag structure (k) of the VAR model employed in the Johansen- Juselius method was determined by Akaike s FPE criteria. In all cases but one (the case of Indonesia), the null hypothesis of zero cointegrating vector (p = 0) cannot be rejected, based on both the trace and the maximum eigenvalue statistic at the 5% significance level. We also examined the model using higher lag structure but the results did not change substantially especially with respect to the number of cointegrating vectors except in one case. In the case of Indonesia, two equilibrium vectors were identified for k = 8. Thus, PPP as a long-run relationship is not supported by the data in most cases as the series are not cointegrated.

11 PURCHASING POWER PARITY IN ASIAN ECONOMIES 151 V. Summary and Conclusion The aim of this study has been to test the PPP hypothesis as a long-run equilibrium condition in selected Asian economies using the recently developed technique of cointegration of economic time series. The methodology applied is suited to examining departures from long-run equilibria: also, these countries managed their economies by basket-pegging during most of the test period. The essence of cointegration is that although two or more series may be individually nonstationary, there may exist some linear combinations of them which are stationary. The results of this study show that PPP conditions observed in the five Southeast Asian countries namely Malaysia, Singapore, Thailand, the Philippines and Indonesia were not consistent with the prediction of PPP hypothesis, at least in relation to the post-1973 period. Although the levels of exchange rates and prices appear to be nonstationary, no equilibrium relationship appears to hold among them in each cases tested. In other words, these variables are not integrated. This evidence seems to suggest that shocks which lead to discrepancy between domestic and foreign prices are not reflected in the nominal exchange rate movements. This also implies that the real exchange rates in these countries fluctuate widely with no tendency to return to a predetermined path. The failure of the exchange rate to conform to some form of PPP even in the long run strongly suggests that there is no reason for current account balance payments to be balanced in the long run. Adjustment towards an equilibrium position, if any, will be very slow. But imbalances on the current account represent changes in a country s net wealth, so the long-run current account imbalances represent a continually shifting pattern of international wealth with some countries becoming increasingly rich and others becoming increasingly impoverished (Taylor, 1988). Departure from PPP may be rationalized in different ways. For example Engle (1992) offers four explanations for the empirical failure of PPP: (1) barriers to free trade such as tariffs and transportation costs, (2) different consumption preferences across countries, (3) presence of nontraded goods in consumer price indexes, and (4) prices which are sticky in terms of the currency in which the good is consumed. More important, the results of this paper suggest that PPP equilibria have not occurred in low-inflation economies like Malaysia, Singapore and Thailand as well as high-inflation countries like Indonesia and the Philippines. Mole and Lo (1991) reported similar results. However, McNown and Wallace (1989) found that PPP tends to hold for high-inflation economies such as Argentina, Brazil, Chile and Israel, a result only partly consistent with one of our tests. For the high-inflation countries, monetary growth would usually overshadow real factors, and hence may provide more support for PPP.

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