Granger Causality Among Pre-Crisis East Asian Exchange Rates. (Running Title: Granger Causality Among Pre-Crisis East Asian Exchange Rates)

Transcription

1 Granger Causaliy Among PreCrisis Eas Asian Exchange Raes (Running Tile: Granger Causaliy Among PreCrisis Eas Asian Exchange Raes) Joseph D. ALBA and Donghyun PARK *, School of Humaniies and Social Sciences (SHSS), Nanyang Technological Universiy, Singapore Absrac We examine Granger causaliy among he exchange raes of eigh Eas Asian economies prior o he Asian crisis. We adop as our general model Engle and Gau s (1997) official band model, and use daily bilaeral US dollar exchange rae daa during January 1991July Our findings provide some empirical suppor for he presence of sysemaic relaionships ha are consisen wih he conagious naure of he Asian crisis. Keywords: causaliy, exchange rae, Eas Asia, conagion, crisis JEL Codes: F31, O53 * Corresponding auhor: Associae Professor Donghyun Park, Room No. S3B1A10, School of Humaniies and Social Sciences (SHSS), Nanyang Technological Universiy, Singapore [ ] adpark@nu.edu.sg [Telephone] (65) [Fax] (65)679417

2 1 Inroducion The Asian currency crisis was marked by a sudden and sharp depreciaion of many regional currencies. While here are a number of explanaions for he crisis, including similar srucural weaknesses, he propagaion of he crisis from one counry o anoher suggess ha conagion effecs may have played a role. In his connecion, our paper invesigaes Granger causaliy among Eas Asia s bilaeral exchange raes visàvis he US dollar in he precrisis period. Such causaliy would lend some suppor o he presence of conagion effecs. Our paper adds o he exising empirical lieraure on conagion effecs and he Asian crisis by making use of Engle and Gau s (1997) official band model. Daa and Model Specificaion Our sudy covers eigh Eas Asian counries Korea, Taiwan, Hong Kong, Singapore, Indonesia, Philippines, Thailand and Malaysia. The firs four are newly indusrialized economies while he laer four are collecively known as he ASEAN4. We use daily bilaeral US dollar exchange rae daa from Daasream and our sample period is beween January 1991 and 1 July We use he causaliy ess developed by Cheung and Ng (1996) in order o examine he causaliy in variance, in he Granger (1969) sense, of wo series using a wosep procedure. The firs sep requires he idenificaion of he appropriae model for he univariae ime series, and he second sep uilizes a crosscorrelaion funcion (CCF) of he sandardized squared residuals o check for causaliy in variance. The ess are robus o disribuional assumpions. In his secion, we idenify he appropriae model for he exchange raes of all he eigh counries. 1 Before 1991, he exchange raes of many Eas Asian counries were based on governmenannounced official raes raher han freely raded raes.

3 We adop as our general model Engle and Gau s (1997) official band model. The model specificaion includes he impac of volailiy on reurns, and a locaion parameer ha ensures consisency of nongaussian QuasiMaximumLikelihood Esimaors (QMLE): y α 0 1h + ε ε 1 3 h h = ; and (1) β β = 0 + 1hi, x 1 β ε β where y is exchange rae reurn given by = 100 log(s / S ), S is he daily exchange y 1 rae of counry h is he condiional variance, ε is he residual, and he erm x is equal o 100 log(si, / T ), where T is he arge exchange rae. The specificaion of he univariae model employs he robus Wald es developed by Bollerslev and Wooldridge (199). Table 1 below repors he resuls of he robuswald specificaion ess. The mos parsimonious specificaion of each series deermines he choice of univariae model. The nogarch(1,1) resricion agains he GARCH(1,1) alernaive canno be rejeced a he 5 percen significance level for Indonesia, he Philippines and Korea. Addiional robus Wald ess for he remaining five cases indicae GARCH(1,1) o be he appropriae specificaion for he exchange raes of Malaysia and Singapore, while MA(1) GARCH(1,1) characerize he exchange raes of Hong Kong and Taiwan. The GARCH(1,1) wihband specificaion is suiable only for he Thai bah. [Inser Table 1 here] 3 Causaliy We define he sandardized squared residuals of he univariae models in secion as: ε ( y µ ) / h = () The erm x specifies he band in he condiional variance equaion. For counries wih undeclared bands, we use x log( S / S ) as he proxy for he band. The coefficien β 3 shows he impac of = previous deviaion of he exchange rae from is arge rae on he magniude of he volailiy. 3

4 where µ is he mean of he exchange rae reurn for counry i. The crosscorrelaion funcion (CCF) of he sample is given by: ( ε j, E( ε j, ))( ε k E( ε )) ˆ ρ k ( ε i, ε ) = (3) j ( ε j, E( ε j, )) ( ε E( ε )) where he subscrips j, and k refer o he firs counry, he second counry, and he lead (k<0) or lag (k>0), respecively. Cheung and Ng (1996) show ha he square roo of he number of observaions muliplied by he sample crosscorrelaion has an asympoic normal disribuion. Therefore, he saisic ( Tˆ ρ ( εi, ε j ) ) may be used o deec causaliy in variance. Given ρ ˆ ( ε i, ε j ) 0, if k>0, hen k he second series lags or Granger causes he firs series, bu if k<0, hen he firs series lags or Granger causes he second series. k equals zero indicaes insananeous causaliy. Bidirecional causaliy may exis if he saisics are significan for boh k>0 and k<0. The maximum value of leads and lags is en. The crosscorrelaion of he sandardized residuals also shows causaliy in mean. However, Cheung and Ng (1996) cauioned ha for some model specificaions, he presence of boh he causaliyinvariance and causaliyinmean may affec he CCF because of he violaion of he independence assumpion in eiher es. In a GARCH(1,1) model, he causaliy in mean may have a large effec on he size of he causaliy in variance es since he condiional variance is a funcion of squared errors, alhough he reverse may no be rue. Table below shows he significan crosscorrelaion leads and lags of he sandardized residuals and residualsquares of he bilaeral raes versus he US dollar. The resuls indicae sysemaic relaionships among he exchange raes, bu mainly in mean raher han in variance. Since only he causaliy in mean exiss in mos cases, and he specified model is eiher nogarch or GARCH(1,1), hen he CCF is no likely o be biased. [Inser Table here] k 4

5 Wihin he ASEAN4, bidirecional causaliy in mean exiss beween Thailand and he Philippines. There is also bidirecional causaliy in mean beween Indonesia and boh he Philippines and Thailand. The direcion of causaliy in mean for Malaysia and he oher ASEAN4 counries is from Malaysia o Indonesia, he Philippines and Thailand, alhough causaliy in variance is bidirecional beween Malaysia and Thailand. Table also indicaes he spillover o Korea, which shows bidirecional causaliy in mean wih Indonesia, Philippines and Thailand. There is also unidirecional causaliy in mean from Malaysia o Korea. For Hong Kong, Singapore and Taiwan, he causaliy is mainly from hem o he ASEAN4. Excepions include bidirecional causaliy in boh mean and variance beween Malaysia and Singapore, and he unidirecional causaliy in mean from he Philippines o Taiwan. For boh mean and variance, here is also causaliy beween Hong Kong and boh Singapore and Taiwan. The causaliy is bidirecional for mean and variance beween Singapore and Taiwan. Insananeous causaliy in mean exiss for mos of he counries excep Souh Korea and Taiwan on one hand and he oher seven Eas Asian counries on he oher. There is also no insananeous causaliy in mean beween Hong Kong and Indonesia. Insananeous causaliy in variance is also presen beween Malaysia and boh Thailand and Singapore, as well as beween Singapore and Thailand. Therefore, our resuls indicae he presence of sysemaic relaionships among Eas Asian bilaeral exchange raes visàvis he US dollar in he precrisis period ha are consisen wih he conagious naure of he Asian currency crisis. Such sysemaic relaionships can help explain how he currency crisis, which originaed in Thailand, quickly spread o oher Souheas Asian counries as well as Korea, resuling in a regionwide crisis. 5

6 References Bollerslev, T. and Wooldridge, J. (199), QuasiMaximum Likelihood Esimaion and Inference in Dynamic Models wih TimeVarying Covariances, Economeric Reviews 11(): Cheung, Y. and Ng, L. (1996), A CausaliyinVariance Tes and is Applicaion o Financial Marke Prices, Journal of Economerics 7(1): Engle, R. and Gau Y. (1997), Condiional Volailiy of Exchange Raes Under A Targe Zone, manuscrip, Universiy of California a San Diego. Granger, C. (1969), Invesigaing Causal Relaions by Economeric Models and Cross Specral Mehods Economerica 37(3):

7 Table 1 Robus Wald Tess a for Models of Bilaeral Raes Versus US Dollars = 100 log(s / S ) ; y = α 0 1h + ε ε 1 3 h ; h ; = β0 + β1h 1 + βε 1 + β3x 1 x 100 log(s / T ) y 1 i, = Null Hypohesis Indonesia c Malaysia d Philippines c Thailand f Hong Kong e S. Korea c Singapore d Taiwan e β 1 =β =0 b α 1 =α = β 3 =0 α 1 =α =0 α 1 =β 3 =0 α = β 3 =0 α 1 =0 α = 0 β 3 = ** * * * * ** ** ** ** ** ** ** ** ** ** ** a The misspecificaion es iniially considers he nogarch as he null hypohesis agains he alernaive of GARCH(1,1). If GARCH(1,1) is no rejeced, hen addiional misspecificaion ess under various null hypoheses are conduced agains he general model (MA(1)GARCH(1,1)Mwihaband) as he alernaive. The mos parsimonious specificaion is chosen for each series. The compuer programs are in RATS 4.3. b To es for nogarch(1,1), he robus Wald es has a null hypohesis of no GARCH(1,1) agains GARCH(1,1) as an alernaive. ( ** ), ( * ) and ( + ) indicae 1%, 5% and 10% levels of significance respecively. c Indonesia, he Philippines and Korea exchange raes do no rejec he nogarch(1,1) specificaion agains he alernaive of GARCH(1,1) a he 5% level of significance. d Addiional robus Wald ess indicae he nonrejecion of he null agains he general model for Malaysia and Singapore, herefore he GARCH(1,1) model is chosen. e The rejecion of he null α 1 =α = β 3 =0, α 1 =α =0, α = β 3 =0, α = 0 bu he nonrejecion of α 1 =β 3 =0, α 1 =0, β 3 =0 a he 5% level of significance for Hong Kong and Taiwan denoe an MA(1)GARCH(1,1) model. f The rejecion of he null α 1 =α =0, α 1 =β 3 =0, and β 3 =0 a he 5% level and α 1 =α = β 3 =0 a he 10 % level of significance and he nonrejecion of α 1 =α =0, α 1 =0, α =0 a he 10 percen and higher level of significance denoe a GARCH(1,1)wihaband model.

8 Table Significan CrossCorrelaion Leads and Lags of Sandardized Residuals in Levels (Upper Diagonal) and Squares (Lower Diagonal) (Bilaeral Raes versus US dollar) Firs Variable Second Indonesia Malaysia Philippines Thailand Hong Kong S. Korea Singapore Taiwan Variable Indonesia 5, 0 5, 0,, 3, 5 5, 0, 5 5,, 5 5, 0, 5 5, 0 Malaysia 0, 3 0, 5 5, 0 0, 1, 4,5 1, 0, 1 Philippines 5, 4, 3,, 0, 1,, 3, 5 5, 0, 1 5, 3, 0, 4, 5 Thailand 4, 0 1 5, 0, 5 5, 0 4 Hong Kong 5 4 1, 4 1, 0,, 5 4, S. Korea 3, 0 Singapore 1, 0, 1 0 5, 1, 5 Taiwan 3, 5, 1, Noes: Significan refers o significance level of 5% or higher. The crosscorrelaion leads and lags of sandardized residuals (causaliy in mean) are shown on he upper diagonal while lower diagonal show he significan lead or lags of he sandardized residual squares (causaliy in variance). A posiive value means ha he second variable lags he firs variable while a negaive value connoes he firs variable lags he second variable. Zero indicaes significan insananeous correlaion. The compuer programs are wrien in RATS