revisiting purchasing power parity hypothesisin the … · is the nominal exchanger defined in...

Proceedings of the 6th International Conference of the Asian Academy of Applied Business (AAAB) 2013

1

REVISITING PURCHASING POWER PARITY HYPOTHESISIN THE ASEAN-5 COUNTRIES:AN ANALYSISOF PRE- AND POST- ASIAN FINANCIAL CRISIS 1997-1998

Qaiser Munir

School of Business and Economics Universiti Malaysia Sabah

Corresponding E-mail: [email protected]

Kok Sook Ching School of Business and Economics

Universiti Malaysia Sabah

Kasim Mansur School of Business and Economics

Universiti Malaysia Sabah

ABSTRACT

This study re-examines the purchasing power parities (PPPs)in the ASEAN-5 countries to exhibit a comparison of insights on the pre- and post-crisis periods of Asian financial crisis1997-1998. History witnessed the shifts of exchange rate regimes in majority of the ASEAN-5 countriesupon the crisis. This study adopts1997-1998asthe turning point in our analysis.The post-crisis period captures the recent state of PPP after the outbreak of global financial crisis in September 2008. This study applies most recent monthly data from 1968 to 2009 and employ recently developed panel unit root tests that account for cross-sectional dependence. Findings show an interesting discovery asthe validity of PPP hypothesis gains increasing supportonly in the post-crisis period contrasting the result of the pre-crisis period, which seems to suggest the effectiveness of policy choice upon the Asian financial crisis, giving much support towards internal stabilization, advocating monetary autonomy. JEL classification: C12:C33; F31; Keywords:Purchasing power parity; Real exchange rate; Mean-reversion, ASEAN Countries 1. INTRODUCTION

The literature on PPP is abundant mostlyin the seeking of empirical evidence to support the validity ofPPP for countries or region. Research interest that focused on PPP in the ASEAN-5 countriesis among the prominent.There exists evidence of a mean-reverting pattern inthe long-run adjustment process of exchange rates which suggests that the movement of exchange rates is predictable in the long-run, andthat in the long-run exchange rates may have tendency to revert back within the desired band. It has always been importantto policy makers to ensure the stability of exchange rates.Nonetheless, PPP in the ASEAN-5 countries remained as an important research interest as time-varying dynamics appear to be relevant in related studies. This study is driven by the motivation to capture the differences in the pre- and post-crisis periods of Asian financial crisis1997-1998. In addition, PPP gains increased interest in the context of the International Comparison Program (ICP), which developed PPP as the most

mailto:[email protected]


2

robust and appropriate currency converter, as to accurately reflect differences in the levels of prices of goods and services in different countries (see Bishnu, 2004: 4). The role of PPP has always been crucial and should be given full attention by policy makers including the constituent countries of ASEAN-5.

The theory of PPP explains that changes in exchange rates are related to changes in relative prices among countries. As the law of one price states that the prices of a good expressed in the same currency should cost the same everywhere, PPP states that an exchange rate between two countries should equal the ratio of the price level in one country to the price level in the other country (Sawyer and Sprinkle, 2003: 290). This relationshipimpacts on trades, foreign direct investmentandfinancial investments between countries and within a region. If PPP holds, exchange rates will bemoving in a desired band, which in some studies it is supported by the evidence of a mean-reverting process.It is at the interest of policy makers to ensure that the relative prices of a countrydo not severely impacton the movement of exchange rates, while it is also important to have exchange rates that tend to adjust back to their pre-determined equilibrium values. If PPP doesn’t hold, exchange rates will have tendency todeviate from their pre-determined equilibrium values. As mentioned in Sawyer and Sprinkle (2003: 294), PPP should be viewed as a long-run concept, for short run exchange rates can deviate significantly from PPP. The validity of PPP hypothesis gives important consequence to the ASEAN-5 economies, as the stability of exchange rates promotes economic growth of the constituent countries namely Indonesia, Malaysia, Singapore, Thailand, and the Philippines, and also towardsrealizing the ASEAN Economic Community (AEC) by 2015 for regional economic integration. AEC has clearly envisaged the dynamicsof cooperation in various areas to transform ASEAN into a region with free movement of goods, services, investment, and free flow of capital.1The validity of PPP hypothesisaffirms that the exchange rates of ASEAN-5 countries are stable and less vulnerable to shocks in the long-run.

This study aims to re-examine the validity of PPP in ASEAN-5 countries for the pre- and post-crisis periods of Asian financial crisis 1997-1998, by applying recent monthly data spanning from 1968 to 2009,and by utilizing recently developed second generation panel unit root tests.History witnessed the shifts of exchange rate regimes in some of the ASEAN-5 countries upon the pre- and post-crisis periods. On August 14th, 1997, Indonesia experienced a shift from the managed floating exchange regime to a free-floating exchange rate arrangement. In Malaysia, before September 2nd, 1998, the country maintained an exchange rate system that the exchange rate is determined by supply and demand, which was then replaced by a fixed exchange rate system of pegging Malaysian ringgit against US dollar at a rate of RM3.80 per USD1. In Singapore, since 1998 the authority used the exchange rate as an intermediate target allowing Singapore dollar to fluctuate within an undisclosed band, as compared to before 1998 Singapore dollar was allowed to float following supply and demand. Since July 2nd, 1997, Thailand adopted a two-tier currency market which separates the exchange rate for investors who buy baht in domestic and overseas markets. On March 15th, 1998, the Philippines allowed peso to float more freely against US dollar with a band including a six percent limit around the exchange rate of previous day.2Hence, 1997-1998 is the turning point in our analysis. The post-

1 The details of ASEAN Economic Community (AEC) are accessible from the official website of the Association of

Southeast Asian Nations, http://www.aseansec.org/ 2 The details of exchange rate regime for Asian countries are accessible online through the website of The Chinese

University of Hong Kong, http://intl.econ.cuhk.edu.hk/exchange_rate_regime/index.php?cid

http://www.aseansec.org/

http://intl.econ.cuhk.edu.hk/exchange_rate_regime/index.php?cid


3

crisis period is of much interest as it captures the recent state of PPP after the outbreak of the global economic crisis of 2007-2009.

Long-run PPP has been tested by a variety of panel unit root procedures in recent years. Early studies found evidence in support of PPP.This was later overturned by O’Connell (1998) who argued that failing to account for cross-sectional dependence (CSD) can result in an overvaluation of PPP. Recent contributions that attempted to deal with CSD (e.g.: Harris et al. (2003), Moon and Perron (2004), Smith et al. (2004), Ho (2008), Chang and Song (2009), Chortareas and Kapetanios (2009)) contrast with the early literature, failing to garner significant support for PPP.

The remainder of this study is organized as follows. Section 2briefly reviews the empirical literature of PPP in ASEAN-5. Section 3 providesa discussion onthe framework of real exchange rates and datasets. Section 4 discusses the econometric methodology. Section 5 details and illuminates theempirical results.Last section concludes and provides recommendations for policy making.

2. EMPIRICAL LITERATURE REVIEW Literature of PPP in ASEAN-5 countries showed that most studies employed unit root tests and cointegration tests to validate the PPP hypothesis.A number of studies advocate that the adjustment process of exchange rate towards the PPP equilibrium is a linear form such as Ridzuan et al. (2010). Some other studies perceive that exchange rate adjusts in a nonlinear process towards the PPP equilibrium such asLiewet al. (2005) and Baharumshahet al. (2003).

Baharumshahet al. (2003) investigated the mean-reversion version behaviour of ASEAN-5 exchange rates using nonlinear unit root test formulated by Sarno (2001) to show that the real exchange rates of ASEAN-5 countries adjust follow the smooth transition autoregressive (STAR) process. This study applied quarterly data for the period offirst quarter of 1968 to second quarter of 2001, and the data used were the nominal bilateral exchange rates of each ASEAN-5 country’s home currency against US dollar, and the CPI of each of the ASEAN-5 countries and of US. The data on real exchange rate is derived from the relative form of PPP hypothesis, which is effectively the deviation of nominal exchange rate from the PPP equilibrium. Findings showed robust evidence of nonlinear mean reversion for Indonesian rupiah-US dollar, Thailand baht-US dollar, Singaporean dollar-US dollar, and the Philippines peso-US dollar, except for Malaysian ringgit-US dollar.

Liewet al. (2005) investigated the underlying dynamics of the adjustment process of exchange rate deviations with two bilateral exchange rates namely Indonesian rupiah-US dollar and Singaporean dollar-US dollar, and captured the effect of Asian financial crisis 1997-2008 on the adjustment processes. This study applied data on quarterly basis and employed estimations

by using standard linearity test statistics based on Lukkonen, saikkonen and Ter svirta (1988) of which has power against the Exponential Smooth Transition Autoregressive (ESTAR) model. Finding showed that Indonesian rupiah-US dollar with low-speed of adjustment was more adversely affected by the crisis as compared to the exchange rate of Singaporean dollar-US dollar.

Ridzuan et al. (2010) examined the validity of PPP hypothesis in ASEAN-4 and Singapore. The data used werethenominal exchange rates of ASEAN-4, in the form of each home currency of ASEAN-4 against Singapore dollar, and the CPI of eachof the ASEAN-5 countries.This study applied two sample periods including the period before and after the implementation of Common Effective Preferential Tariff (CEPT) Scheme, whereby ADF and PP unit root tests and JJ cointegration test were performed separately for each period. Dummy


4

variable was used to capture economic shock. Findings showed that for the case of Thailand, the Philippines, and Malaysia, PPP holds in the long-run after the implementation of CEPT Scheme and only valid for the relative form of PPP. When VECM analysis was employed, a weaker short-run evidence of PPP was provided for the case of the Philippines indicating that the tendency for the country's nominal exchange rate to diverge in response to economic shock.

3. THE FRAMEWORK OF REAL EXCHANGE RATES AND DATASETS Our bilateral real exchange rate is defined as the nominal exchange rate deflated by a ratio of foreign (USin our case) and domestic price levels:

(1)

Where, is the nominal exchanger defined in local currency units per foreign currency

(US dollar); is the real exchange rate; and and are the domestic and foreign price

levels.We use consumer price indices (henceforth, CPIs) in our study. Taking the logarithm of bothsides of Equation (1) and rearranging the terms yields:

(2)

Following equation shows the model of mean reverting real exchange rate,

(3)

Whereα and ε are constant and error term respectively.From a statistical point of view,

the validity of the PPP hypothesis reduces to aunit-root test of .PPP suggests that real

exchange rate series should be stationary. Therefore,the presence of a unit root in the real exchange rate serieswould imply that PPP does not hold in the long run. If PPP holds, it implies that thenominal exchange rate is corrected for inflation differentials. Nonstationarity in realexchange rates has many macroeconomic implications. For example, Dornbusch(1987) argued that if the real exchange rate depreciates, it could bring a gainin international competitiveness, which in turns could shift employment towards thedepreciating country. Therefore, it is important to establish the empirical validity ofthe PPP theory. Another important implication of nonstationarity in real exchangerate is that the unbounded gains from arbitrage in traded goods are possible. In fact, Parikh and Williams (1998) mentioned that a nonstationary real exchange rate could cause severe macroeconomic disequilibrium which leads to real exchangerate devaluation in order to correct for external imbalance. Datasets Our empirical analysis covers the fiveASEAN countries: Indonesia, Malaysia, the Philippines, Thailand, and Singapore. Monthlydata are employed in our empirical study, and the time span is from January 1968 to November 2009. All the data regarding CPIare based on 2005 = 100, and nominalexchange rates relative to the foreign currency(US dollar)are taken from EconStats(http://www.econstats.com). Each of theCPI and nominal exchange rate series wastransformed into naturallogarithms before the econometric analysis. The full sample is divided into two sub-samples, the pre-crisis period (1968:01-1997:06) and the post-crisis period


5

(1998:4-2009:11), because the crisis may have permanently affected some macroeconomic fundamentals of ASEAN-5 economies. The real exchange rates are displayed in Fig. 1. From this figure, we see wild behaviors for all five time series around 1997, a time of Asian financial crisis. Also, we see a big fluctuation for the Malaysian data set around year 1982. Sporadic wild changes are observed for the Philippines data set. As pointed out in Papell (2000), this is due to the large nominal appreciation and subsequent depreciation of the US dollar in the 1980s caused by a bubble that burst in the middle of 1980s. It seems that all the data sets contain many non-normal observations for which robust tests may be more appropriate than the usual tests. 4. ECONOMETRIC METHODOLOGY In this section we briefly describe the methods that allow for cross-sectional dependence (second generation tests).Moon and Perron (2004) useda factor structure to model cross-sectional dependence. They assume that the error terms are generated by r common factors and idiosyncratic shocks.

0

itiit yy

ittiiit ypy

0

1,

0

ittiit eF /

Where,Ft is a r x 1 vector of common factors and λi is a vector of factor loadings. The

idiosyncratic component eit is assumed to be i.i.d across i and over t. The null hypothesis

corresponds to the unit root hypothesis H0:pi= 1; i = 1,…,N whereas under the alternative the

variable yit is stationary for at least one cross-sectional unit. The testing procedure is as follows: in a first step, data are de-factored, and in a second step, panel unit root test statistics based on de-factored data are proposed.

Moon and Perron (2004) treated the factors as nuisance parameters and suggested pooling de-factored data to construct a unit root test. The intuition is as follows. In order to eliminate the common factors, panel data must be projected onto the space orthogonal to the factor loadings. So, the de-factored data and the de-factored residual no longer have cross-sectional dependencies. Then, it is possible to define standard pooled t-statistics, as in IPS, and

to show their asymptotic normality. Let

poolp be the modified pooled OLS estimator using the

de-factored panel data. Moon and Perron defined two modified t-statistics which have a standard normal distribution under the null hypothesis:

)1,0(,,/2

)1ˆ(

441 NNT

w

pNTMP d

ee

pool

)1,0(,,)(1

)1ˆ(4

2/

1122 NNTw

ZQZtraceNT

pNTMP d

e

eApool

Where, 2

ew denotes the cross-sectional average of the long-run variances 2

eiw of residuals

eit and 4

e denotes the cross-sectional average of 4

eiw . Moon and Perron proposed feasible


6

statistics MP1 and MP2 based on an estimator of the projection matrix and estimators of long-

run variances 2

eiw

In the first step, the panel tests of Choi (2006) apply Elliott et al. (1996) GLS detrending to the panel, thereby removing cross-sectional dependence. In the second step, meta-analytic panel tests from, e.g., Choi (2001) can then be used (see also Maddala and Wu, 1999). Choi (2006) assumes the following two-way error-component model:

),,...,1;,...,1(0 TtNixy itit

Where,

ittiitx

And,

ip

t

itiitit et1

)1(

The test of a panel unit root is formulated as:

ip

t

it iH1

0 1 against

ip

t

itH1

1 1 for a non-zero fraction # i/N

Choi (2006) showed that demeaning iity 0 cross-sectionally gives, for large T,

1..1

1

010 )ˆ(1ˆ:

ti

N

i

itiitit yN

yz

Where,

N

i iaaN 1.

1: . This expression is independent of itand ,0 . Moreover,

., 01.. pt Hence, zit is cross-sectionally independent.

In a second step, one applies meta-analytic panel tests to zit. For instance, run Augmented Dickey-Fuller tests on zit. Then, after having obtained the p-values of the test statistics, these may be combined into panel test statistics as follows:

N

i

im pN

p1

)1)(ln(1

N

i

ipN

Z1

1 )(1

),1

ln(3/

1

12

*

N

i i

i

p

p

NL

Pesaran (2007) proposed a different approach to deal with the problem of cross-

sectional dependencies. He considers a one-factor model with heterogeneous loading factors for residuals. He augments the standard Dickey Fuller or Augmented Dickey Fuller regressions with the cross section average of lagged levels and first-differences of the individual series. If residuals are not serially correlated, the regression used for the ith country is defined as:

ittititiiiit ydycypy 11,


7

Where N

i tit yNy1 1,1 )/1( and

N

i tit yNy1 1,1 )/1( . Let us denote ti(N, T) the t-

statistic of the OLS estimate of pi. The Pesaran’stest is based on these individual cross-sectionally augmented ADF statistics denoted CADF. The idea is to build a modified version of IPSt-bar test based on the average of individual CADF statistic denoted CIPS for cross-sectionally augmented IPS.

),(1

1

TNtN

CIPSN

i

i

All the individual CADF statistics have similar asymptotic null distributions which do not

depend on the factor loadings. But they are correlated due to the dependence on the common factor. Pesaran proposed simulated critical values of CIPS for various samples sizes.

The next approach to model cross-sectional dependencies consists of imposing few or none restrictions on the covariance matrix of residuals (Chang, 2002). Her procedure consists of using a nonlinear instrumental variable (IV thereafter). More precisely, she derived a nonlinear IV estimator of the autoregressive parameter in simple ADF model. She proved that the corresponding t-ratio (denoted Zi) asymptotically converges to a standard normal distribution. Note that this asymptotic Gaussian result is very unusual and entirely due to the nonlinearity of the IV. Moreover, it can be shown that the asymptotic distributions of individual Zi statistics are independent across cross-sectional units. So, panel unit root tests based on the cross-sectional average of individual independent statistics can be implemented. Chang proposed an average IV t-ratio statistic, denoted SN and defined as:

N

i

iZN

SN1

1

This statistic has a limit standard normal distribution. The instruments are generated by

an Instrument Generating Function (IGF thereafter) which corresponds to a nonlinear function F (yit-1) of the lagged values yit-1: Chang provided several examples of regularly integrable IGFs. In our application, we consider two functions in order to assess the sensitivity of the results to the choice of the IGF. The first is IGF1(x) = x exp (- ci /x/) where ci € R is determined by ci= 3 T-1/2 s-1 (Δyit) where S2 (Δyit) is the sample standard error of Δyit. IGF3(x) = I(/x/ < K) * x, where K denotes a truncation parameter.

Breitung and Das (2005) proposeda model while assuming the existence of weak cross-sectional dependence. For that purpose, they wrote the model as a seeminglyunrelated-type system of equations in matrix form:Δyt= φyt−1 + εt, where, Δyt,yt−1 and εtare N × 1 vectors. The cross-sectional correlation is represented bya non-diagonal covariance matrix Ω= E(εtε′t) for all

t, with bounded eigenvalues. They demeaned the data such that ty~ = yt−y0, where y0

representsthe value of the initial observation, and estimated consistently the variance–

covariancematrix of the OLS estimator, which is denoted by

ˆˆ . They then obtained the robustt-

statistic free of size distortions due to contemporaneous cross-sectional correlationfor N and T tending to infinity:


8

)1 ,0(~ˆˆ

~~

ˆ

ˆ

1 11

1 1

ˆ

N

yy

yyt

d

T

t tt

T

t tt

rob

(4)

Harris et al. (2005, HLM) developed a panel stationarity test that is able to handle time-

series and cross-sectional dynamics, thereby allowing for heterogeneity in the deterministic across units. They proposed a test that addresses cross-sectional dependence through a factor model with an unknown number of factors like:

ititiit zxy (5)

ittiit efz

Where,ftis an r ×1 vector of latent factors which needs to be estimated to determinethe

rank, λiis an r×1 vector of loading parameters and eitis the idiosyncratic term foreachi . They further assumed that ftand eitare mutually independent of one another.They then computed the

F

kS test for the estimated components tf and ite jointly, whichis robust to cross-sectional

correlation and serves as a test for the null hypothesis thatthe series zitare stationary for all i. More specifically, the resulting statistic takesthe form:

)1 ,0(~ˆ

ˆˆ

,

Na

CS

d

tk

kF

k

(6)

Where, itz are standardized residuals, tka ,

2 ~ is the long-run variance estimator,

T

kt tkk aTC1 ,

2/1 ~~and

N

i kitittk zza1,

~~~ . It can be shown that F

kS followsa standard normal

distribution even when it is based on residuals with large T andfixed N.Under the HLM (2005) test the null hypothesis implies that all cross-sectional units are stationary against the alternative that at least one unit is nonstationary. 5. EMPIRICAL RESULTS As already been noted, one method of testing the theory of PPP is to test whether the real exchange rate is constant or stationary. If the real exchange rate is stationary, the evidence is in favor of PPP; if it is not, the evidence is against PPP.

First,we examine the stationarityof real exchange rates, to test the empirical validity of PPPhypothesis. For this purpose, we conduct five panel unit root tests,namelyLevin et al. (2002),Imet al. (2003), Maddala and Wu (Fisher-ADF, Fisher-PP, 1999), Breitung (2000) and Hadri (2000). Levin et al. (2002), Breitung (2000), and Hadri (2000) tests all assume that there is a common unit root process that is identical across cross-sections. The first two tests employ a null hypothesis of a unit root while the Hadri (2000) test uses a null of no unit root. The Imet al. (2003), the Fisher-ADF and PP tests all allow for individual unit root processesthat vary across cross-sections. We employ the panel unit root tests which are performed on the level of variable. The model trend is included in the empirical analysis. According to Marcela et al. (2003), allowing for a trend in the data is equivalent to accepting the existence of factors with a systematic influence on the real exchange rate due to Balassa–Samuelson effect and a demand-side bias in favor of non-traded goods. Another argument for inclusion of time trend is motivated by the non-stationary of real exchange rates for traded goods because of menu costs


9

or pricing-to-market strategies. Therefore, we apply the panel unit root tests including constant and trend.

All panel tests that are used are based on the null hypothesis of the presence of a unit root in the series, with the exception of Hadri’s (2000) test, whose hypothesis is that the series are stationary. The tests differ from each other on the restrictions imposed on the autoregressive process of each of the panel series. Thus, the tests of Levin-Lin-Chu (2002), Breitung (2000) and Hadri impose a common persistence parameter to all the series –therefore, if the null is rejected, the alternative would be that all the series are simultaneously stationary for the first two tests and non-stationary for the latter. On the other hand, the tests of Im-Pesaran-Shin (2003), the Fisher-type tests suggested by Maddala and Wu (Fisher-ADF, Fisher-PP, 1999) allow for the autoregressive parameter to change freely among the different cross-sectional variables under consideration. Therefore, the alternative hypothesis in these cases is the presence of a non-null proportion of stationary series of the total.The model trend is included in the empirical analysis. According to Marcela et al. (2003), allowing for a trend in the data is equivalent to accepting the existence of factors with a systematic influence on the real exchange rate due to Balassa–Samuelson effect and a demand-side bias in favor of non-traded goods. Another argument for inclusion of time trend is motivated by the non-stationary of real exchange rates for traded goods because of menu costs or pricing-to-market strategies. Therefore, we apply the panel unit root tests including constant and trend.

The results are presented in TABLE 1 for the full sample and the two sub-samples, pre-financial crisis and post-financial crisis, in Panel A (1968:01-2009:11), Panel B (1968:01-1997:06) and Panel C (1998:04-2009:11), respectively. A precise summary of resultssuggest that the real exchange rates are non-stationary in the full sample and pre-financial crisis periods considered.The null hypothesis of non-stationarity cannot be rejected in all tests with the exception of those of Levin-Lin-Chu at 10% and Hadri at 1% significance levels. Nonetheless, Levin-Lin-Chu and Hadri´s tests both have some limitations. Levin-Lin-Chuimposes strong parametric restrictions which imply that under the alternative hypothesis all series must be stationary and have the same autoregressive parameter. Hadri’s test, on the other hand, has a tendency to over-reject the null hypothesis as it is based on KPSS tests and, as shown by Caner and Kilian (2001), the KPSS statistics tend to reject the stationarity hypothesis more often than they should at the specified significance level. In all, we can conclude that the evidence that has been showed here points to the non-existence of PPP hypothesis in full and pre-financial crisis samples.

However, using the post-financial crisis data we found mixed results of mean reversion to support long-run PPP from different panel unit root tests (Panel C of TABLE 1).The null hypothesis of non-stationarity is rejected in all tests with the exception of those of Levin-Lin-Chu at 10%, Breitung at 10% and Hadri at 1% significance levels. TABLE1: First Generation Panel Unit Root Tests of Real Exchange Rates

U.S. $ based

statistics p-value

Panel A: Full Sample 1968:01-2009:11

Levin, Lee and Chu test 0.076 0.531 Im, Pesaran and Shin w-test 0.529 0.702 ADF — Fisher Chi-square 6.725 0.751 PP — Fisher Chi-square 6.715 0.752


10

Breitung-UB 1.108 0.866 Hadri-z test 13.83* 0.000 Panel B: Pre-financial Crisis Period 1968:01-1997:06

Levin, Lee and Chu test -1.519*** 0.064 Im, Pesaran and Shin w-test -0.889 0.187 ADF — Fisher Chi-square 13.33 0.206 PP — Fisher Chi-square 12.43 0.257 Breitung-UB 0.336 0.632 Hadri-z test 7.474* 0.000 Panel C: Post-financial Crisis Period 1998:04-2009:11

Levin, Lee and Chu test -1.642*** 0.058 Im, Pesaran and Shin w-test -3.202* 0.000 ADF — Fisher Chi-square 33.48* 0.000 PP — Fisher Chi-square 22.89** 0.011 Breitung-UB -1.624*** 0.052 Hadri-z test 7.435* 0.000

Notes: *, ** and *** denotes significant at 1%, 5% and 10% significance level. Optimal lags for IPS and ADF- Fisher are determinedbased on AIC and for Hadri it is Newey–West bandwidth selection using Bartlett kernel. (iv)Probability values for IPS andHadri unit root test is computed assuming asymptotic normalityand for Fisher unit root test using an asymptotic chi-square distribution.Probabilities for the Fisher tests are computed using an asymptotic Chi-square distribution. The LLC test assumes asymptotic normality. The choice of lag levelsfor the Fisher-ADF test is determined by empirical realizations of the Schwarz Information Criterion. The LLC andFisher-PP tests were computed using the Bartlett kernel with automatic bandwidth selection. Results from Second Generation Panel Tests So far, the presentation of the panel statistics has assumed that individuals are cross-section independent. However, this assumption might be restrictive in practice since the analysis of macroeconomic time series for different countries are affected by similar major events that might introduce dependence among individuals in the panel data set. There are different procedures in the literature to deal with cross-section dependence. In this paper we account for cross-section dependence by using Moon andPerron (2004), Chang (2002), Breitung and Das (2005), Harris etal. (2005), Choi(2006), Pesaran (2007) panel unit root tests to account cross-sectional dependence.

As reported in (Panel A)TABLE 2, we fail toreject the null of joint non-stationarity with all tests except HLM (2005) test. While we strongly reject the null of joint stationarity in real exchange rate withMoon and Perron (2004), Harris etal. (2005) and Pesaran (2007) tests (see TABLE 2, Panel B). However, as presented in Panel C of TABLE 2, we strongly reject the null of joint stationarity in real exchange rate with all tests except Chang (2002) test. Taken together; the empirical results so far suggest the PPP is a valid hypothesis in the post-financial crisis period for ASEAN-5 countries under investigation.

TABLE2: Second Generation Panel Unit Root Tests


11

U.S. $ based

statistics p-value

Panel A: Full Sample 1968:01-2009:11

Pm -0.399 0.655

Choi (2002) Z 0.414 0.660

L* 0.410 0.659

Moon and Perron (2004) MP1 -2.369 0.009

MP2 -2.083 0.019

Chang (2002) SN 6.238 0.999 Pesaran (2007) CIPS -1.935 0.930

CIPS -1.935 0.930

Breitung and Das (2005) trob -0.425 0.335

Harris et al. (2005) F

kS 4.192 0.000

Panel B: Pre-financial Crisis Period 1968:01-1997:06

Pm 0.168 0.433

Choi (2002) Z -0.194 0.423

L* -0.249 0.401

Moon and Perron (2004) ta -2.087 0.018

tb -2.594 0.005 Chang (2002) SN 7.555 0.999 Pesaran (2007) CIPS -2.854 0.045

CIPS -2.853 0.045



kS 3.795 0.000

Panel C: Post-financial Crisis Period 1998:04-2009:11

Pm 4.091 0.000

Choi (2002) Z -2.383 0.009

L* -2.955 0.002

Moon and Perron (2004) ta -11.367 0.000

tb -16.190 0.000

Chang (2002) SN 2.737 0.997 Pesaran (2007) CIPS -3.242 0.010

CIPS -3.242 0.010



kS 3.270 0.000

Notes: Pesaran (2007): CIPS is the mean of individual Cross-sectional augmented ADF statistics

(CADF). CIPS denotes the mean of truncated individual CADF statistic.Corresponding p-values are in parentheses. Chang (2002): TheSNstatistic corresponds to the average individual nonlinear IV t-ratio statistics.Critical values of Moon and Perron test are -2.3263 (1%), -1.6449


12

(5%),and -1.2816 (10%).Similarly, the critical values of CIPS tests are -3.0196, -2.8381, and -2.7399 at 1%, 5% and 10% levels, respectively. The critical values of SN test are -2.3263, -1.6449, and -1.2816 at 1%, 5% and 10% levels, respectively. 6. CONCLUSION AND RECOMMENDATIONS We consider the stationarity of real exchange rates in ASEAN-5 economies in order to assess the case for PPP focusing on theUSdollar as numeraire. Weimplement a new set of procedures that allows us to identify themean-reverting series within a panel. This procedure is appliedto panel unit root tests, both conventional as well as recentlydeveloped ones that account for cross-sectional dependence.

Our results show increased evidence of mean-reversion in realexchange rates and therefore strengthen the case in favor ofPPP for the real exchange rates of ASEAN-5 countries in the post-financial crisis period. One novelty of our work is that we are ableto identify the stationary real exchange rates in the panels whileretaining the advantages of panel unit root tests. Moreover, whenwe perform tests for cross-sectional dependence our results remainrobust.

In the case for ASEAN-5 countries, PPP hypothesis is valid only in the post-crisis period suggesting that the shifts of exchange rate regimes upon the crisis are effective in improving the PPPs, as far as we have seen that the PPPsstill uphold in the outbreak of recent global financial crisis. Lewis and Mizen (2000: 377) suggested that when the exchange rate is floating, a country seems to have flexible exchange rates which equilibrate the balance of payments directly, and a country has monetary autonomy in inflation control, favoring internal stabilization of the value of money. As contrast, when the exchange rate is fixed, it would be implying an effort at external stabilization which involves fixing of the value of domestic monetary unit relative to foreign money, and thus in terms of foreign goods and services, causes the requirement of balance of payments equilibrium without unlimited reserves, and therefore scarifying the use of the quantity of money for inflation control. In some countries of ASEAN-5, the policy choice of internal stabilization seems to contribute towards the improvement of PPPs, suggesting monetary autonomy of the constituent countries is likely to gain increasing interest in inflation control. As the PPP hypothesis is validated, it implies that exchange rates are adjustable to pre-determined equilibrium value in the long-run, despite any deviation in the short-run.The countries would likely to preservestable exchange rates which are less vulnerable to shocks.Hence,it suggests apositive outlook for theregional economic integration envisaged by the ASEAN Economic Community by 2015.According to Felmanet al. (2011:1), the bond markets of ASEAN-5 have yet to fully develop even though the inflows of portfolio investment into ASEAN-5 bonds have started. In our opinion, when PPP holds, it strongly benefits the growth of the bond markets.

Finally, on the empirical side, Flôreset al. (1999) and Papell and Theodoridis (2001) indicated that the choice of numeraire currency has substantial effects on the testing results. Allowing more different numeraire currency are good extensions for future research. References


13

Abdul Rahim Ridzuan, and Elsadig Musa Ahmed (2010). "Testing the Validity of Purchasing

Power Parity between ASEAN-4 and Singapore and its connections with CEPT Scheme", paper presented at the Korea and World Economy IX Conference, University of Incheon, Korea.

Ahmad ZubaidiBaharumshah, Liew, V.K.S., and Lau, E. (2003). ―Nonlinear Mean Reversion in Real Exchange Rates: Evidence from the ASEAN-5‖. EconWPA, International Trade Series. No. 0308001, pp. 1-10.

Chang, Y. (2002). ―Nonlinear IV unit root tests in panels with cross-sectional dependency‖. Journal of Econometrics. 110, pp. 261–292.

Choi, I. (2002).―Combination unit root tests for cross-sectionally correlated panels‖. Mimeo, Hong Kong University of Science and Technology.

Dickey, D. A., & Fuller, W. A. (1981). ―Likelihood ratio statistics for autoregressive time series with a unit root‖. Econometrica. 49, pp. 1057–1072.

Dornbusch, R. (1987). ―Exchange rates and prices‖.American Economic Review. 77, pp. 93–106. D. Pant, Bishnu. (2004).―Purchasing Power Parities and the International Comparison Program

in a Globalized World‖.Economics and Research Department Policy Brief Series No. 25, Asian Development Bank.

Felman, J., Gray, S., Goswami, M., Jobst, A., Pradhan, M., Peiris, S., Seneviratne, D. (2011). ―ASEAN5 Bond Market Development: Where Does It Stand? Where Is It Going?‖.IMF Working Paper.WP/11/137.

Gujarati, D.N. (2003).Basic Econometrics.4th Edition. New York: McGraw Hill. Hadri, K. (2000). ―Testing for stationarity in heterogeneous panels‖.Econometrics Journal.3(2),

pp. 148−161. Im, K.S., Pesaran, M. H., and Shin, Y. (2003)."Testing for unit roots in heterogeneous

panels".Journal of Econometrics.Vol.115, pp.53-74. Kwiatkowski, D., Phillips, P., Schmidt, P., & Shin, Y. (1992).―Testing the null hypothesis of

stationarity against the alternative of a unit root: How sure are we thateconomic time series have a unit root?‖.Journal of Econometrics. 54, pp. 159–178.

Levin, A., Lin, C. F., & Chu, C. S. (2002).―Unit root tests in panel data: Asymptotic and finite-sample properties‖. Journal of Econometrics. 108, pp. 1–24.

Kapetanois, G., Shin, Y., and Snell, A. (2003)."Testing for a unit root in the nonlinear STAR framework".Journal of Econometrics.Vol.112, pp.359-379.

Lee, J., and Strazicich, M. (2003).―Minimum Lagrange multiplier unit root test with two structural breaks‖.Review of Economics and Statistics.Vol.85(4), pp. 1082-1089.

Lee, J., and Strazicich, M. (2004).―Minimum LM unit root test with one structural break‖.Manuscript.Department of Economics.Appalachian State University.

Levin, A., Lin. C. F., and Chu, C. (2000)."Unit root tests in panel data: Asymptotic and finite sample properties".Journal of Econometrics.Vol.108, pp. 1-24.

Lewis, M.K. and Mizen, P.D. (2000).Monetary Economics. New York: Oxford University Press, pp. 377.

Liew, K. S., Baharumshah, A. Z., and Lim, K. P. (2005)."Nonlinear Adjustment of Real Exchange Rates towards Purchasing Power Parity and the Asian Financial Crisis".International Journal of Business and Society. Vol. 6(1), pp. 122-140.

Lukkonen, R., Saikkonen, P, and Terasvirta, T. (1988)."Testing Linearity against Smooth Transition Autoregressive Models".Biometrica.Vol.75, pp. 491-499.

Maddala, G. S., & Wu, S. (1999). ―A comparative study of unit root tests with panel data and a new simple test‖. Oxford Bulletin of Economics and Statistics. 61, pp. 631–665.


14

Moon, H. R., &Perron, B. (2004).―Testing for a unit root in panels with dynamic factors‖.Journal of Econometrics.122, pp.81–126.

Newey, W., & West, K. (1994).―Automatic lag selection in covariance matrix estimation‖.Review of Economic Studies. 61, pp.631–653

O'Connell, P. G. J. (1998). ―The overvaluation of purchasing power parity‖.Journal of International Economics. 44, pp. 1–20.

Parikh, A., & Williams, G. (1998).―Modeling real exchange rate behavior: A cross-country study‖.Applied Financial Economics. 8, pp. 577–587.

Pedroni, P. (1999)."Critical Values for Cointegration Tests in Heterogeneous Panels with Multiple Regressors".Oxford Bulletin of Economics and Statistics.Vol.61, pp.653-670.

Pedroni, P. (2004). "Panel Cointegration: Asymptotic and Finite Sample Properties of Pooled Time Series Tests with an Application to the PPP Hypothesis". Econometric Theory.Vol.20(3), pp. 597-625.

Phillips, P. C. B., &Perron, P. (1988).―Testing for a unit root in time series regression‖.Biometrika, 75, pp. 335–346.

Pesaran, M.H., (2004). ―General diagnostic tests for cross sectiondependence in panels‖.IZA Discussion Paper Series. DP N. 1240.Institute for the Study of Labor, Bonn.

Pesaran, M.H., Shin, Y., and Smith, R. (2001).―Bound testing approaches to the analysis of level relationships‖.Journal of Applied Econometrics.Vol.16, pp.289-326.

Reinhart, C., and Rogoff, K. (2004). ―The modern history of exchange rate arrangements: a reinterpretation‖. The Quarterly Journal of Economics. Vol. 119(1), pp. 1-48.

Sawyer, W. C., and Sprinkle, R. L. (2003).International Economics. Pearson Education: New Jersey.

revisiting purchasing power parity hypothesisin the … · is the nominal exchanger defined in...

Documents