ASIAN MONETARY INTEGRATION: A STRUCTURAL VAR APPROACH Zhaoyong Zhang* Naional Universiy of Singapore and Macau Universiy Kiyoaka Sao Yokohama Naional Universiy and Michael McAleer Universiy of Wesern Ausralia * Corresponding auhor: Zhaoyong Zhang, Deparmen of Economics, Naional Universiy of Singapore, 10 Ken Ridge Crescen, Singapore 119260. Tel: +65 68746259, Fax: +65 67752646, E-mail addresses: ecszzy@nus.edu.sg (Zhang), sao@ynu.ac.jp (Sao) and Michael.McAleer@uwa.edu.au (McAleer). The auhors wish o hank Paul De Grauwe, Harry Bloch, Ian Kerr, Ken Clemens, Mansur Masih, Edward Lim, Sadayuki Takii, conference paricipans a MODSIM in Canberra, and seminar paricipans a he Inernaional Cenre for he Sudy of Eas Asian Developmen (ICSEAD), Universiy of Wesern Ausralia, Curin Universiy and Edih Cowan Universiy, for helpful commens and suggesions. This sudy was begun while he firs auhor was visiing ICSEAD, Japan. He wishes o hank ICSEAD for is hospialiy and suppor and UMAC for financial suppor hrough gran RG042/00-01S. The second and hird auhors wish o acknowledge he financial suppor of ICSEAD and an Ausralian Research Council Discovery Gran, respecively. 1
ASIAN MONETARY INTEGRATION: A STRUCTURAL VAR APPROACH Absrac This paper examines wheher forming an opimum currency area (OCA) is viable for he Eas Asian region by esing he symmery of underlying srucural shocks. A srucural vecor auoregression (VAR) mehod is used o idenify he underlying shocks and o examine he correlaion in shocks for specified sample periods. Decomposiion of he variance of shocks and impulse response analysis are used o examine he size and he speed of adjusmens o shocks. The resuls imply ha some sub-regions are poenial candidaes for forming OCAs, as heir shocks are correlaed and small, and he economies adjus rapidly o such shocks. Keywords: Opimum currency area; Vecor auoregressions; Exchange rae; Eas Asian region 2
1. INTRODUCTION The recen regional financial crisis has eroded he credibiliy of unilaeral fixed exchange raes, and correspondingly renewed calls for greaer moneary inegraion and regional exchange rae sabiliy in Eas Asia. 1 One of he proposals raised during he 1998 ASEAN Miniserial Meeing in Hanoi was he idea of having a common currency and exchange rae sysem in he region. The successful launch of he Euro in early 1999 makes a common currency a paricularly ineresing opion for boh ASEAN and Eas Asia (EA). According o [8, 7], he incenive for wo economies o peg heir bilaeral exchange raes rises wih he bilaeral inensiy of rade, flexibiliy of facor markes, and symmery of underlying shocks. By doing so, boh will be able o forsake nominal exchange rae changes as an insrumen of adjusmen and o reap he reducion in ransacions coss associaed wih a common currency. The purpose of his paper is o invesigae and assess he empirical suiabiliy of he Eas Asian economies for poenial moneary inegraion in ligh of he heory of an opimum currency area (OCA). In paricular, we focus on he symmeric naure of underlying shocks across he Eas Asian economies as a precondiion for forming an OCA. This paper is srucured as follows. Secion 2 discusses he heoreical framework and mehodology. The empirical resuls are presened in Secion 3, including he variabiliy and correlaion among he variables, he correlaion of he srucural shocks, a variance decomposiion analysis, and an impulse response analysis, o examine he size 1 Eas Asia is defined as he following 10 counries: Japan, Korea, Taiwan, Hong Kong, Singapore, Malaysia, Indonesia, he Philippines, Thailand and China. 3
of he shocks and he speed of adjusmens o such shocks. Concluding remarks are given in Secion 4. 2. ANALYTICAL FRAMEWORK Early sudies on OCA focused on how he various observable macroeconomic variables, such as GDP growh raes, inflaion raes, exchange raes, ineres raes and sock prices, are correlaed across he economies or he region. [1, 2] are among he firs o idenify he underlying srucural shocks by using he [3] vecor auoregression (VAR) mehod. In his paper, we employ a hree-variable VAR open economy model o examine he shocks according o he OCA lieraure. Following [4, 12], all he variables in he model are expressed in naural logarihms and represen he domesic relaive o foreign levels. Specifically, he hree variables are defined as he domesic oupu relaive o h f foreign oupu, y ( y y ) ; he bilaeral real exchange rae relaive o he US dollar, h f q ; and he domesic price level relaive o he foreign price level, p ( p p ), where superscrips h and f refer o domesic and foreign, respecively. Le x [ y, q, p ] and ε [ ε, ε, ε ] s d m, where represens he firsdifference operaor, and ε s, ε d and ε m denoe supply, demand and moneary shocks, respecively. The srucural model can be wrien as: x = A 0 ε + A1 ε 1 + A2ε 2 + = A( L) ε (1) 4
where A11( L) A12 ( L) A13( L) A ( L) = A21( L) A22 ( L) A23( L). A31( L) A32( L) A33( L) I is assumed ha he srucural shocks ε [ ε, ε, ε ] are serially uncorrelaed and have a covariance marix normalized o he ideniy marix. The model implies ha he macroeconomic variables are subjec o hree srucural shocks. In order o idenify he srucural shocks, he following long run resricions are imposed: (i) only supply shocks affec relaive oupu in he long run; (ii) boh supply and demand shocks affec real exchange raes in he long run; and (iii) moneary shocks have no long run effec on eiher relaive oupu or real exchange raes. These long run resricions amoun o A 12 ( 1) = A13(1) = A23(1) = 0 series of srucural shocks. s d m, which are sufficien o idenify he A i marices and, hence, he The reduced-form VAR model for esimaion is as follows: x = B( L) x + u, (2) 1 where u is a vecor reduced-form disurbance. A moving average (MA) represenaion of equaion (2) is: x = C( L) (3) u where 1 C ( L) = (1 B( L) L) and he lead marix of (L) C is, by consrucion, C =. By 0 I 5
comparing equaions (1) and (3), we obain he relaionship beween he srucural and reduced form disurbances as u ε = A 0. Hence, i is necessary o obain esimaes of A 0 o recover he ime series of srucural shocks ε. As he srucural shocks are muually orhogonal and each shock has a uni variance, he following relaionship beween he covariance marices is obained: C ( 1) ΣC(1) = A(1) A(1) (4) where Σ = Eu u = EA ε ε A = A. If H denoes he lower riangular Choleski 0 0 0 A 0 decomposiion of C ( 1) ΣC(1), hen A ( 1) = H as he long run resricions imply ha A (1) is also lower riangular. Consequenly, A 1 1 = C(1) A(1) = C(1 H. Given an esimae of 0 ) A, he ime series of srucural shocks, ε [ ε, ε, ε ], can be recovered. 0 s d m 3. EMPIRICAL RESULTS 3. 1. Daa The major daa sources used in his paper are IMF: Inernaional Financial Saisics, CD-ROM, China Monhly Saisics, Hong Kong Monhly Diges of Saisics, he websies of he Japan and Taiwan saisics auhoriies, and NUS ESU daabank. Real GDP is used as a proxy for real oupu variables, consumer price index (CPI) as a measure of changes in prices, and he real exchange rae is calculaed using CPI and he bilaeral nominal exchange rae of he Eas Asian economies relaive o he US dollar. All 6
daa are quarerly and seasonally unadjused, excep for real GDP. Daa are ransformed ino he raio of domesic (EA) relaive o foreign (US) levels. In an open-economy framework, srucural shocks esimaed by he srucural VAR mehod end o include he effec of foreign shocks. To he exen ha foreign or global shocks have an influence on he Eas Asian economies, a high correlaion of shocks across he economies does no necessarily exhibi a srong correlaion of counryspecific shocks. Since he economic presence of he USA is subsanial for he Eas Asian economies, we use ransformed variables ha represen he raio of EA levels o he corresponding US levels o remove he effecs of US shocks. The ime series properies of he variables have been invesigaed, and i was found ha mos variables are I(1), based on he Phillips-Perron and KPSS ess. Therefore, he firs differences of all variables are used o ensure he saionariy of he variables. For esimaion of he VAR, one lag is chosen, based on SBIC. The economeric sofware package EViews 4 is used for he empirical analysis. 3.2. Variabiliy and Correlaion of he Variables The variabiliy of nominal bilaeral exchange raes for he 10 Eas Asian economies and he USA are examined for he whole sample period 1983-2000, as well as for he sub-periods 1983-1984, 1985-1996 and 1996-2000. Reference is made o he effecs of he wo regional crises in he 1980s and 1990s, as well as o he separae periods 1983-1993 and 1994-2000 o incorporae he effecs of China s unificaion of is dual exchange raes in early 1994. Due o space limiaions, Table 1 repors resuls for he 7
whole sample period only (he remaining resuls are available on reques). In view of he whole sample period from 1983 o 2000, exchange raes of he Eas Asian economies are relaively sable agains each oher. In all cases, he volailiy of exchange raes agains each oher is below five percen, and agains he US dollar he volailiy is below four percen, wih he excepion of he Indonesian Rupiah. Table 1: Variabiliy of Nominal Exchange Raes, 1983:10-2000:10 US JP CH HK ID KR MA PH SI TH TW US JP CH HK ID KR MA PH SI TH TW 1.000 0.030 1.000 0.033 0.044 1.000 0.003 0.030 0.033 1.000 0.073 0.074 0.081 0.073 1.000 0.032 0.040 0.046 0.032 0.064 1.000 0.023 0.032 0.038 0.024 0.062 0.030 1.000 0.027 0.040 0.042 0.027 0.066 0.034 0.026 1.000 0.013 0.025 0.036 0.013 0.067 0.030 0.018 0.026 1.000 0.030 0.037 0.044 0.030 0.061 0.029 0.022 0.028 0.024 1.000 0.013 0.028 0.036 0.013 0.070 0.030 0.022 0.027 0.014 0.027 1.000 Noe: US: he Unied Saes; JP: Japan; CH: China; HK: Hong Kong; ID: Indonesia; KR: Korea; MA: Malaysia; PH: he Philippines; SI: Singapore; TH: Thailand; TW: Taiwan The 1997 financial crisis sared in Thailand and became a regional crisis shorly hereafer. Indonesia and Korea were hi paricularly hard by his crisis, which caused high volailiy in heir exchange raes agains hose of heir neighbours. The Indonesian Rupiah became he mos volaile currency in he region afer he crisis, followed by he Korean Won and he Thai Bah. However, he res of he Eas Asian economies coninued o display low variabiliy relaive o each oher, even afer he Eas Asian financial crisis. In comparison, he firs economic recession in ASEAN in he mid-1980s and China s unificaion of is dual exchange raes in 1994 did no conribue subsanially o he exchange rae volailiy in he region. 8
The low variabiliy of bilaeral exchange raes in Eas Asia reflecs he progress of is financial marke inegraion [9, 10]. I also reflecs o a cerain exen he symmeric effecs of shocks originaing from he region and he res of he world. To his end, he low variabiliy may imply he possibiliy of furher regional moneary inegraion. We now urn o he examinaion of he correlaions in growh and inflaion of he Eas Asian economies for specified periods (see Tables 2 and 3) 2. Overall, he Eas Asian economies display a less obvious paern in GDP growh compared wih inflaionary movemens, even hough he former has become more correlaed afer he financial crisis. I is ineresing o noe ha he recen financial crisis has changed he correlaion paerns of economic growh and inflaion among he economies concerned. Afer he crisis, he number of significan correlaions in GDP growh has increased among he Eas Asian counries, and beween he USA and he region. However, he financial crisis has changed a number of significan and posiive correlaions in inflaion o insignifican and negaive. These findings have implicaions for forming an OCA in he Eas Asian region. 3. 3. Correlaion of Srucural Shocks The underlying shocks were esimaed by he srucural VAR approach for he Eas Asian economies for 1980Q1-1997Q1 and 1980Q1-2000Q3. I is assumed ha if he correlaion of srucural shocks is posiive, he shocks are considered o be symmeric, and if negaive and/or insignifican, hey are asymmeric. 2 In Tables 2 and 3, GDP growh raes and CPI inflaion raes are calculaed as a percenage change over he corresponding period in he previous year. 9
Table 2: Correlaion of GDP Growh Raes Across he USA and he Eas Asian Economies US Jp Kr Tw HK Si Ml Id Th Ph Ch Panel A: 1981Q1-2000Q3 Unied Saes 1.00 Japan -0.06 1.00 Korea -0.03 0.44 1.00 Taiwan 0.38 0.27 0.45 1.00 Hong Kong 0.21 0.25 0.63 0.68 1.00 Singapore 0.00 0.17 0.34 0.22 0.52 1.00 Malaysia -0.10 0.28 0.54 0.07 0.45 0.75 1.00 Indonesia -0.03 0.43 0.65 0.31 0.58 0.54 0.79 1.00 Thailand -0.16 0.57 0.70 0.26 0.45 0.53 0.70 0.77 1.00 Philippines -0.20 0.04 0.12-0.10 0.14 0.40 0.35 0.20 0.22 1.00 China 0.27-0.01 0.11 0.25 0.17-0.11-0.11 0.10 0.08-0.54 1.00 Panel B: 1981Q1-1997Q1 Unied Saes 1.00 Japan 0.09 1.00 Korea 0.07 0.20 1.00 Taiwan 0.50 0.12 0.53 1.00 Hong Kong 0.31 0.00 0.41 0.73 1.00 Singapore 0.04-0.05 0.01 0.11 0.35 1.00 Malaysia -0.06-0.08-0.13-0.20 0.02 0.70 1.00 Indonesia 0.30-0.10-0.17 0.09 0.23 0.35 0.50 1.00 Thailand -0.04 0.30 0.14 0.07 0.04 0.50 0.47 0.22 1.00 Philippines -0.25 0.06 0.00-0.12 0.05 0.38 0.36 0.23 0.37 1.00 China 0.41-0.26-0.02 0.16 0.11-0.24-0.37-0.36-0.33-0.57 1.00 Panel C: 1997Q2-2000Q3 Unied Saes 1.00 Japan 0.24 1.00 Korea 0.46 0.72 1.00 Taiwan 0.17 0.52 0.48 1.00 Hong Kong 0.68 0.70 0.84 0.69 1.00 Singapore 0.47 0.65 0.77 0.80 0.91 1.00 Malaysia 0.46 0.73 0.91 0.72 0.93 0.93 1.00 Indonesia 0.44 0.61 0.85 0.74 0.90 0.95 0.97 1.00 Thailand 0.60 0.60 0.96 0.30 0.81 0.68 0.83 0.77 1.00 Philippines 0.35 0.55 0.80 0.70 0.84 0.92 0.92 0.97 0.72 1.00 China -0.08-0.08-0.17-0.11-0.01 0.03-0.15-0.06-0.12 0.03 1.00 Noes: 1. Quarerly daa are used for he real GDP growh rae. 2. GDP growh raes denoe he percenage change over he corresponding period in he previous year. 10
Table 3: Correlaion of Inflaion Raes Across he USA and he Eas Asian Economies US Jp Kr Tw HK Si Ml Id Th Ph Ch Panel A: 1981Q1-2000Q3 Unied Saes 1.00 Japan 0.76 1.00 Korea 0.83 0.71 1.00 Taiwan 0.75 0.61 0.90 1.00 Hong Kong 0.53 0.61 0.64 0.53 1.00 Singapore 0.81 0.68 0.77 0.67 0.67 1.00 Malaysia 0.63 0.54 0.75 0.74 0.40 0.74 1.00 Indonesia -0.07-0.01 0.16 0.08-0.18-0.13 0.34 1.00 Thailand 0.62 0.59 0.86 0.77 0.49 0.68 0.73 0.26 1.00 Philippines 0.30 0.41 0.07 0.02 0.26 0.24 0.17 0.05-0.07 1.00 China 0.27-0.01 0.18 0.38 0.53 0.31 0.15-0.30 0.07 0.08 1.00 Panel B: 1981Q1-1997Q1 Unied Saes 1.00 Japan 0.80 1.00 Korea 0.87 0.71 1.00 Taiwan 0.74 0.61 0.91 1.00 Hong Kong 0.53 0.50 0.61 0.54 1.00 Singapore 0.80 0.67 0.79 0.67 0.85 1.00 Malaysia 0.70 0.57 0.76 0.76 0.71 0.83 1.00 Indonesia 0.56 0.46 0.53 0.49 0.46 0.46 0.59 1.00 Thailand 0.76 0.58 0.89 0.85 0.47 0.77 0.75 0.45 1.00 Philippines 0.25 0.37 0.00-0.04 0.17 0.20 0.13 0.27-0.15 1.00 China -0.13-0.34-0.22 0.01-0.01-0.12 0.15-0.04-0.20-0.16 1.00 Panel C: 1997Q2-2000Q3 Unied Saes 1.00 Japan -0.49 1.00 Korea -0.59 0.53 1.00 Taiwan -0.16 0.14 0.51 1.00 Hong Kong -0.56 0.85 0.79 0.24 1.00 Singapore 0.43 0.49-0.01-0.28 0.35 1.00 Malaysia -0.86 0.19 0.72 0.43 0.47-0.63 1.00 Indonesia -0.76-0.01 0.50 0.41 0.24-0.80 0.93 1.00 Thailand -0.63 0.62 0.94 0.40 0.90 0.08 0.70 0.48 1.00 Philippines -0.90 0.25 0.59 0.33 0.46-0.62 0.94 0.94 0.63 1.00 China 0.27 0.65 0.16 0.10 0.56 0.81-0.39-0.54 0.25-0.39 1.00 Noes: 1). Quarerly daa are used for he CPI inflaion rae. 2). CPI inflaion raes denoe he percenage change over he corresponding period in he previous year. 3). The Hong Kong daa sar from 1984Q1 and he China daa sar from 1987Q1. 11
Table 4. Correlaion of Srucural Shocks Across he Eas Asian Economies Jp Kr Tw HK Si Ml Id Th Ph Ch Jp Kr Tw HK Si Ml Id Th Ph Ch Panel A: Supply Shocks (1980Q3-1997Q1) Panel D: Supply Shocks (1980Q3-2000Q3) Japan 1.00 1.00 Korea 0.22 1.00 0.32 1.00 Taiwan 0.28 0.48 1.00 0.33 0.40 1.00 Hong Kong 0.27 0.18 0.47 1.00 0.25 0.34 0.49 1.00 Singapore 0.07 0.19 0.31 0.10 1.00 0.20 0.29 0.42 0.20 1.00 Malaysia 0.27 0.27 0.22-0.01 0.45 1.00 0.36 0.53 0.30 0.13 0.51 1.00 Indonesia 0.08 0.24 0.18-0.14 0.23 0.45 1.00 0.27 0.50 0.37 0.15 0.38 0.50 1.00 Thailand 0.08 0.34 0.20-0.02 0.25 0.27 0.28 1.00 0.13 0.40 0.19 0.05 0.26 0.42 0.35 1.00 Philippines 0.32 0.23 0.21 0.32 0.20 0.22 0.11 0.06 1.00 0.27 0.25 0.19 0.31 0.22 0.24 0.21 0.11 1.00 China 0.00 0.03 0.23 0.25 0.20 0.17 0.14-0.09 0.13 1.00 0.15 0.17 0.29 0.27 0.26 0.20 0.27 0.14 0.20 1.00 Panel B: Demand Shocks (1980Q3-1997Q1) Panel E: Demand Shocks (1980Q3-2000Q3) Japan 1.00 1.00 Korea 0.23 1.00 0.03 1.00 Taiwan 0.26 0.42 1.00 0.41 0.43 1.00 Hong Kong -0.09 0.27 0.00 1.00-0.11 0.21-0.19 1.00 Singapore 0.44 0.16 0.24 0.18 1.00 0.57 0.22 0.47 0.02 1.00 Malaysia 0.28 0.01 0.07 0.20 0.58 1.00 0.15 0.37 0.37 0.09 0.50 1.00 Indonesia 0.20 0.19 0.02 0.03 0.13 0.03 1.00 0.16 0.42 0.31-0.07 0.27 0.27 1.00 Thailand 0.40-0.06 0.07-0.09 0.27 0.36-0.04 1.00 0.09 0.27 0.19 0.05 0.20 0.43 0.07 1.00 Philippines -0.01 0.23 0.19 0.15 0.08 0.05 0.00 0.00 1.00 0.00 0.30 0.27 0.08 0.18 0.15 0.11 0.13 1.00 China -0.08 0.10-0.12 0.11-0.25 0.23 0.12-0.11 0.21 1.00-0.14 0.21-0.05 0.03-0.15 0.17 0.00 0.01 0.20 1.00 Panel C: Moneary Shocks (1980Q3-1997Q1) Panel F: Moneary Shocks (1980Q3-2000Q3) Japan 1.00 1.00 Korea 0.06 1.00 0.02 1.00 Taiwan 0.07 0.23 1.00 0.12 0.25 1.00 Hong Kong 0.13 0.09 0.10 1.00 0.00-0.05-0.04 1.00 Singapore 0.25 0.22-0.02-0.02 1.00 0.22 0.21-0.01-0.24 1.00 Malaysia 0.15 0.24 0.14-0.04 0.55 1.00 0.16 0.30 0.16-0.18 0.52 1.00 Indonesia 0.11 0.24 0.19-0.16 0.16 0.35 1.00 0.03 0.26 0.25 0.01 0.22 0.37 1.00 Thailand 0.32 0.18 0.09 0.49 0.29 0.19-0.12 1.00 0.36 0.19 0.11 0.38 0.23 0.24 0.25 1.00 Philippines -0.01-0.15 0.04 0.29-0.08-0.16-0.01-0.03 1.00 0.00-0.01 0.10 0.22 0.11-0.04 0.18 0.09 1.00 China -0.24 0.33-0.02 0.06 0.12 0.53 0.15 0.07-0.23 1.00-0.26 0.32-0.07 0.21 0.03 0.27 0.08 0.19-0.10 1.00 Noes: The sample period sars from 1983Q3 for Hong Kong and from 1986Q3 for China. The pained figures denoe posiive and significan a he 5 percen level. Significance levels are assessed using Fisher s variance-sabilizing ransformaion, and he null hypohesis is ha he correlaion coefficien is zero [11]. Resuls of correlaions of he hree idenified shocks among he Eas Asian economies for 1980Q1-1997Q1 and 1980Q1-2000Q3 are repored in Table 4. Pained figures indicae ha he correlaion coefficien is posiive and significan a he 5 percen level. I is found ha, for 1980Q1-1997Q1 (Panel A of Table 4), supply shocks are correlaed significanly among Singapore, Malaysia, Indonesia and Thailand. Japan and Korea are posiively and significanly correlaed wih some ASEAN economies. Correlaions are also high among Japan, Korea, Taiwan and Hong Kong. This resul is similar o hose in [2]. However, demand shocks and moneary shocks are less correlaed 12
among hese economies during he sample period (Panels B and C of Table 4). I is ineresing o noe ha he regional financial crisis improved he number of significan correlaions of shocks in hese economies (Panels D-F of Table 4). Those ASEAN economies and NIEs ha displayed high correlaions in heir growh paerns are likely o have similar supply shocks, which end o be permanen. For he res of Eas Asia, asymmeric shocks seem o prevail. However, one should be cauious as including he pos-crisis period in he sample may cause srucural breaks in he series, which would affec esimaion. 3 According o he OCA lieraure, supply shocks are considered o be more informaive for evaluaing he symmery of shocks because esimaed demand and moneary shocks using he srucural VAR mehod end o include he effecs of macroeconomic policies, as well as purely sochasic disurbances [2, 6, 5]. The more (less) ofen are symmeric shocks encounered, he greaer (lesser) are he correlaions in he supply shocks, and he more feasible does i become for hese economies o esablish an OCA. Therefore, our resuls do no display srong suppor for forming an OCA in he enire Eas Asian region. However, hey do sugges ha he OCA is feasible in some subregions, such as among some Asian NIEs and ASEAN counries. 3. 4. Variance Decomposiion Analysis 3 The underlying shocks have been esimaed by he srucural VAR approach using daa from he 1980s and 1990s prior o he financial crisis. The number of significan correlaions of he hree idenified shocks among he Eas Asian economies in he 1990s do no change as much in he 1980s. 13
Variance Decomposiion (VD) analysis is performed o idenify he conribuion of each shock o he hree variables. We decompose variaion in he percenage change of he forecas error variance of changes in real oupu, exchange raes and prices ha are due o each shock a he 1 hrough 20 quarer horizons. Due o space limiaions, Table 5 repors he VD resuls of real exchange raes, oupu and prices a he 1-quarer and 20- quarer horizons only (he remaining resuls are available on reques). In boh sample periods, supply shocks are found o be he predominan shocks accouning for he variabiliy of real oupu in all Eas Asian economies. The supply shocks accoun for over 85 percen of he variabiliy a all horizons for he sample period prior o he crisis, and 64 percen when he pos-crisis period is included. I is ineresing o noe ha he financial crisis has reduced he influence of he supply shocks on real oupu in mos Eas Asian economies, bu has increased he influence in Japan. The economies hardes hi by he recen financial crisis displayed an increasing effec of demand and moneary shocks on real oupu. In conras o real oupu, moneary shocks in boh sample periods are he predominan shocks for he variabiliy of he price level for all Eas Asian economies, excep for Hong Kong and he Philippines. The demand shocks predominae in Hong Kong and he Philippines, accouning for over 50 and 85 percen, respecively. By accommodaing he financial crisis, hese effecs have become enhanced subsanially in Hong Kong, bu become weakened in he Philippines. By including he pos-crisis period, supply shocks become he predominan shocks afer a wo-quarer horizon in Indonesia, and are no influenial in he res of Eas Asia. 14
Table 5. Variance Decomposiion of he Changes in Oupu, Exchange Rae and Price Supply Shock Real Oupu Real Exchange Rae Price Demand Moneary Supply Demand Moneary Supply Demand Shock Shock Shock Shock Shock Shock Shock Panel A: 1980Q3-1997Q1 Panel A: 1980Q3-1997Q1 Panel A: 1980Q3-1997Q1 Moneary Shock Japan 95.5 / 94.3 4.5 / 5.7 0.0 / 0.1 15.3 / 14.1 84.1 / 84.6 0.6 / 1.2 3.5 / 3.3 1.3 / 1.1 95.2 / 95.6 Korea 95.4 / 93.0 0.1 / 0.2 4.5 / 6.9 3.5 / 16.0 90.3 / 80.2 6.2 / 3.8 5.5 / 5.1 7.5 / 7.0 87.0 / 87.8 Taiwan 99.1 / 98.9 0.0 / 0.0 0.9 / 1.1 3.4 / 14.2 87.2 / 78.1 9.5 / 7.7 1.6 / 2.6 9.3 / 8.9 89.0 / 88.5 Hong Kong 98.4 / 97.4 0.4 / 0.9 1.2 / 1.7 0.0 / 0.5 98.8 / 98.6 1.1 / 0.9 1.7 / 2.5 52.8 / 48.8 45.5 / 48.7 Singapore 93.4 / 90.0 3.1 / 3.7 3.5 / 6.3 11.0 / 10.1 82.0 / 78.7 7.0 / 11.2 1.6 / 4.0 25.8 / 25.1 72.6 / 71.0 Malaysia 96.2 / 93.9 0.4 / 0.5 3.4 / 5.5 0.2 / 2.7 99.7 / 97.2 0.1 / 0.1 3.1 / 6.2 5.8 / 9.9 91.2 / 83.9 Indonesia 91.7 / 85.6 5.5 / 10.3 2.7 / 4.1 13.7 / 14.9 80.4 / 75.4 5.8 / 9.7 3.4 / 3.4 2.4 / 2.5 94.2 / 94.0 Thailand 99.1 / 98.6 0.0 / 0.2 0.8 / 1.2 2.1 / 2.3 97.3 / 96.9 0.6 / 0.8 0.2 / 0.3 21.8 / 22.5 78.0 / 77.2 Philippines 92.3 / 89.7 1.2 / 1.8 6.5 / 8.5 3.2 / 3.6 96.8 / 96.3 0.0 / 0.1 0.0 / 3.4 89.0 / 84.9 11.0 / 11.7 China 96.8 / 93.5 2.1 / 3.0 1.1 / 3.5 0.2 / 3.9 69.7 / 61.6 30.1 / 34.5 1.0 / 1.0 34.5 / 34.5 64.5 / 64.6 Panel B: 1980Q3-2000Q3 Panel B: 1980Q3-2000Q3 Panel B: 1980Q3-2000Q3 Japan 99.9 / 99.8 0.1 / 0.1 0.1 / 0.1 5.5 / 5.3 93.9 / 93.6 0.6 / 1.1 8.4 / 8.6 2.8 / 4.0 88.8 / 87.4 Korea 80.2 / 72.1 18.0 / 23.5 1.8 / 4.3 54.1 / 48.8 42.8 / 47.6 3.1 / 3.6 8.7 / 7.9 3.5 / 7.3 87.7 / 84.7 Taiwan 96.8 / 95.7 2.7 / 3.4 0.5 / 0.9 5.2 / 13.8 88.0 / 80.0 6.8 / 6.2 0.9 / 1.7 11.1 / 10.7 88.0 / 87.6 Hong Kong 98.8 / 98.6 0.5 / 0.6 0.7 / 0.7 0.0 / 2.3 83.6 / 87.7 16.4 / 10.0 0.7 / 3.6 88.7 / 78.4 10.6 / 18.1 Singapore 91.2 / 88.8 6.3 / 7.4 2.5 / 3.8 14.8 / 14.9 83.4 / 82.2 1.8 / 2.9 0.8 / 4.0 7.4 / 7.3 91.8 / 88.7 Malaysia 70.7 / 70.6 29.1 / 29.1 0.2 / 0.2 31.8 / 29.3 68.2 / 70.7 0.0 / 0.0 0.2 / 0.9 1.4 / 3.7 98.4 / 95.4 Indonesia 63.7 / 69.0 20.7 / 11.9 15.6 / 19.1 62.5 / 59.8 21.0 / 21.5 16.5 / 18.7 21.8 / 58.4 13.0 / 7.9 65.2 / 33.7 Thailand 70.7 / 76.2 17.8 / 14.1 11.5 / 9.6 39.4 / 39.0 60.4 / 60.6 0.2 / 0.3 7.1 / 15.0 3.7 / 6.5 89.3 / 78.5 Philippines 87.4 / 83.6 3.2 / 4.3 9.4 / 12.1 4.8 / 5.1 94.6 / 93.8 0.6 / 1.1 0.0 / 3.2 79.8 / 76.8 20.2 / 20.1 China 92.3 / 87.5 0.4 / 0.6 7.3 / 11.9 1.3 / 6.6 81.5 / 72.7 17.2 / 20.7 9.1 / 12.8 24.6 / 22.6 66.3 / 64.5 Noes: Enries indicae he percenage change of he forecas error variance in he real exchange rae, oupu and price ha is due o each shock a he 1-quarer and 20-quarer horizons below each shock. The firs column below each shock repors he VD resuls of he corresponding shock a he 1-quarer horizon, and he second column repors he resuls a he 20-quarer horizon. The sample period sars from 1983Q3 for Hong Kong and from 1986Q3 for China. 15
Flucuaions in real exchange raes were predominanly caused by he demand shocks a all horizons for all Eas Asian economies before he financial crisis. The crisis has changed he effecs of demand shocks, especially in he economies hardes hi by he crisis. Supply shocks became he predominan cause of he variabiliy in real exchange raes afer he crisis in Indonesia, Korea and Thailand, and remain srong for all horizons. This finding has imporan policy implicaions for he exchange rae regimes in hese counries. 3. 5. Impulse Response Funcion Analysis Since he esimaed srucural shocks are assumed o have uni variances in he srucural VAR, heir size and adjusmen speed can be inferred by analyzing he associaed impulse response funcions (see [2]). For he size of supply shocks, he long run (20-quarer horizon) effec of a uni shock on changes in real GDP is used. For demand and moneary shocks, he 1-quarer impac on changes in real exchange raes and CPI is chosen as a measure of size. The speed of adjusmen is measured as he share of he response afer 4-quarers in is long run effec (ha is, he response afer a 20-quarer horizon). 4 The larger is he size of he shocks, he more disrupive will be he effecs on an economy. Similarly, he slower is he adjusmen o disurbances, he larger will be he cos of mainaining a fixed exchange rae sysem. Table 6 repors he size of shocks and he speed of adjusmens o shocks. The dynamic impulse responses of real oupu and exchange raes wih respec o 4 Our choice of he ime horizon in calculaing he size of shocks and he speed of adjusmen is somewha arbirary. However, choosing differen horizons as a measure will no change he conclusion. 16
he idenified shocks are consisen wih he resuls using variance decomposiion analysis. As seen in Table 6, he size of he supply shocks is he larges in he mos open economies, such as Singapore, Hong Kong, Malaysia, Thailand and he Philippines. For demand and moneary shocks, China, Indonesia and he Philippines have he bigges sizes. The recen financial crisis has, in general, increased he size of disurbances. As a comparison, he average size of he supply shocks in Eas Asia is almos double ha of 14 European counries for a similar ime period (see [13]). Table 6. Size of Shocks and Speed of Adjusmen o Shocks Supply Shocks Demand Shocks Moneary Shocks Size Speed Size Speed Size Speed Panel A: 1980Q3-1997Q1 Japan 0.013 0.999 0.051 0.997 0.006 0.981 Korea 0.015 0.977 0.014 0.734 0.009 0.966 Taiwan 0.012 1.000 0.019 0.920 0.011 0.981 Hong Kong 0.021 1.000 0.010 0.937 0.005 0.989 Singapore 0.020 0.994 0.018 0.997 0.005 0.998 M alaysia 0.020 0.989 0.023 0.993 0.007 0.995 Indonesia 0.012 0.999 0.045 0.999 0.013 1.000 Thailand 0.019 0.998 0.023 0.990 0.007 0.999 Philippines 0.027 0.984 0.116 1.001 0.036 0.960 China 0.016 1.000 0.055 0.987 0.021 0.984 Average 0.018 0.994 0.037 0.956 0.012 0.985 Panel B: 1980Q3-2000Q3 Japan 0.014 1.000 0.055 0.996 0.006 0.991 Korea 0.022 1.002 0.031 1.008 0.010 1.006 Taiwan 0.013 0.983 0.023 0.921 0.010 0.974 Hong Kong 0.025 0.991 0.009 0.765 0.003 0.675 Singapore 0.022 0.990 0.021 0.996 0.006 1.000 M alaysia 0.026 0.996 0.029 1.001 0.008 0.999 Indonesia 0.030 1.065 0.048 1.093 0.019 1.085 Thailand 0.033 0.939 0.036 0.997 0.008 0.990 Philippines 0.025 0.984 0.107 1.000 0.045 0.970 China 0.016 1.000 0.053 0.996 0.020 0.986 Averag e 0.022 0.995 0.041 0.977 0.013 0.968 17
However, he speed of adjusmen o disurbances in Eas Asia is much faser han in Europe. Mos of he Eas Asian counries ake less han one year o complee he adjusmen o shocks. The pace became even more rapid during he financial crisis. One possible explanaion is ha he labour marke in mos Eas Asian counries is very flexible, so ha i is much easier for hese economies o adjus inernally in response o shocks. 5 These findings suppor he proposal for a common currency arrangemen. According o he OCA lieraure, counries are beer candidaes for a currency arrangemen if heir disurbances are correlaed and small, and if hese counries adjus rapidly o shocks. 4. CONCLUDING REMARKS This paper used a hree-variable VAR model o idenify various ypes of shocks, using more han wo decades of quarerly daa from Eas Asia. The resuls showed ha he exchange raes of he Eas Asian economies are relaively sable. However, hese economies display a less coheren paern in GDP growh han ha of inflaion, hough he former has become more correlaed afer he financial crisis. Prior o he recen financial crisis, supply shocks were correlaed significanly among some ASEAN counries (such as Singapore, Malaysia, Indonesia and Thailand) and Eas Asian counries (such as Hong Kong, Japan, Korea and Taiwan). This resul is similar o he findings in [2]. However, demand shocks and moneary shocks were less correlaed among hese economies during he sample period. 5 One of he popular measures used in hese economies during he financial crisis was o freeze or cu salaries o reduce labour coss and mainain heir compeiiveness. This measure would possibly be difficul o implemen in counries wih srong labour unions. 18
I is ineresing o noe ha he regional financial crisis improved he number of significan correlaions of shocks in hese economies. Those economies ha displayed high correlaions in heir growh paerns were likely o have similar supply shocks, which end o be permanen. For he res of Eas Asia, asymmeric shocks seem o prevail. According o he OCA lieraure, supply shocks are considered o be more informaive for evaluaing he symmery of shocks. The greaer (lesser) are he symmeric shocks ha he economies encouner, he higher (lower) are he correlaions in supply shocks, and he more feasible does i become for hese economies o esablish an OCA. The resuls from VD analysis show ha he supply shocks in he wo sample periods are he predominan shocks for he variabiliy of real oupu in all he Eas Asian economies. Ineresingly he financial crisis has reduced he influence of he supply shocks on real oupu in mos Eas Asian economies, bu has increased he influence in Japan. The economies mos hi by he financial crisis displayed an increasing effec of he demand and moneary shocks on real oupu. In conras, moneary shocks are he predominan shocks for he variabiliy of he price level for all Eas Asian economies, excep for Hong Kong and he Philippines. For he laer, demand shocks are predominan for all horizons. By including he pos-crisis period, supply shocks become he predominan shocks afer a wo-quarer horizon only in Indonesia. The flucuaions in real exchange raes were predominanly caused by he demand shocks for all horizons in Eas Asia economies before he financial crisis. Those economies hardes hi by he financial crisis show ha he supply shocks become he predominan cause of he variabiliy in real exchange raes afer he crisis, and such effecs remain srong for all 19
horizons. This has imporan policy implicaions for he exchange rae regimes in hese counries. The dynamic impulse responses of real oupu and exchange raes wih respec o he idenified shocks are consisen wih he resuls using VD analysis. Alhough he size of he underlying shocks is larger han in Europe, he speed of adjusmens o shocks in Eas Asia is much faser, aking less han one year in mos counries. I is clear ha he flexible labour markes in hese economies have faciliaed he inernal adjusmen process. Overall, he empirical resuls do no display srong suppor for forming an opimum currency area in he Eas Asian region. However, hey do imply ha some subregions are beer candidaes for a currency arrangemen as heir disurbances are correlaed and small, and hese counries adjus rapidly o shocks. 20
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