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1 Economics Leers 73 (2001) locae/ econbase Esimaion of direc and indirec impac of oil price on growh Tilak Abeysinghe* Deparmen of Economics, Naional Universiy of Singapore, 10Ken Ridge Crescen, Singapore , Singapore Received 12 April 2000; acceped 13 March 2001 Absrac Using a new mehodology, his paper measures he direc and indirec effecs of oil prices on GDP growh of 12 economies. Because of he indirec effec, which is ransmied hrough a rade marix, even he ne oil exporers like Indonesia and Malaysia canno escape he negaive influence of high oil prices Elsevier Science B.V. All righs reserved. Keywords: VARX model; Trade marix; Direc and indirec effecs JEL classificaion: E3; Q4 1. Inroducion The specre of anoher oil shock emerged in Sepember A number of sudies ha followed he influenial work of Hamilon (1983) have esablished ha such oil price increases have caused conracions in he US economy (see Hamilon, 2000, and Refs. herein). Of paricular ineres o us in his sudy are he Souheas and Eas Asian economies, which were baered by he Asian financial crisis. There has been widespread concern over how high oil prices impinge on heir recovery process (ADB, 2000; Abeysinghe and Wilson, 2000). Using a VARX mehodology, his noe provides an assessmen of he direc and indirec impac of oil prices on he GDP growh of 12 economies. 2. Mehodology High oil prices affec open economies boh direcly and indirecly. The indirec effec works hrough an economy s rading parners. For example, Malaysia and Indonesia are ne oil exporers and *Tel.: ; fax: address: (T. Abeysinghe) / 01/ $ see fron maer 2001 Elsevier Science B.V. All righs reserved. PII: S (01)

2 148 T. Abeysinghe / Economics Leers 73 (2001) major rading parners of Singapore. Singapore is an oil imporer. While higher oil prices impac negaively on Singapore s GDP growh, Malaysia and Indonesia reap he benefis in erms of higher expor revenues. This in urn increases heir impors from Singapore. The ne effec of oil prices on Singapore, herefore, depends on he magniude of hese direc and indirec effecs. To measure boh he direc and indirec effecs we need a muli-equaion framework. For his we use a srucural VARX model formulaed in Abeysinghe (2000a,b). Using reduced form bilaeral expor funcions, Abeysinghe derived he following model o link up he GDP series hrough a rade marix: p p p (B* W)y 5 l 1O(B* W )y 1O G x 1???1O G x 1 (1) 0 j 2j 2j 1j 12j kj k2j j51 j50 j50 where y is an (n31) vecor of GDP growh series, x i(i 5 1,...,k) are (n31) vecors of growh raes of oher explanaory variables, B and G values are unknown parameer marices and is a random vecor wih zero mean and Var(e )5V. W is a known marix of weighs made up of bilaeral expor shares such ha ow 5 1, ( j 5 1,2,...,n 2 1; i ± j). The aserisk indicaes he elemen-wise ij (Hadamard) produc of he wo marices. For n53 and p51 he parameer marices ake he form: b 2 b f b b 1 w w B 5 2 b 1 2 b, B 5 b f b, W 5 w 1 w b 2 b 1 b b f w w 1 and G values are diagonal. The mos imporan feaure of his model is ha he effecive parameer marices (B* i W), i 5 0,1,..., p, change over ime due o he changing weigh marix W (see Abeysinghe, 2000a, for more deails). The oher explanaory variables (x i) ener he model eiher hrough he expor funcion or hrough he oher componens of he GDP ideniy. Oil prices affec consumpion expendiure, invesmen expendiure and he rade balance direcly, and play a legiimae role in he model. Afer esimaing he model, we can derive he impulse responses of oupu growh wih respec o changes in oil prices (o ) from y 5 l* 1 R(L)o 1 u w 21 w p where R(L) 5 B (L) G(L), B (L) 5 (B* 0 W) 2 (B* 1 W)L 2???2(Bp* W)L, and G(L) 5 G01 G1L 1 p???1g pl. For he counry i, he iih diagonal elemen of R(L) provides he direc impac of oil prices on he GDP growh and he ij ( j 5 1,2,...,n 2 1; i ± j) off-diagonal erms provide he impac hrough he (n21) rading parners. Unlike he sandard VARs, model (2) does no produce fixed impulse responses. They change as he rading paern changes. In he model, we use 12-quarer moving averages of expor shares so ha W changes only slowly over ime. (2) 3. Daa and esimaion This sudy covers he same se of economies modeled in Abeysinghe (2000a), namely ASEAN4 (Indonesia, Malaysia, Philippines, Thailand), NIE4 (Hong Kong, Souh Korea, Singapore, Taiwan),

3 T. Abeysinghe / Economics Leers 73 (2001) China, Japan, USA, and he res of OECD as a group (ROECD). While he counries in he OECD are he major rading parners of ASEAN4 and NIE4, here has been a subsanial increase in inraregional rade wihin he laer groups. Therefore, hese 12 economies form a logical se in an assessmen of inernaional ransmission of shocks hrough rade. The compuaional deails of he 12 quarerly GDP series and he corresponding 132 bilaeral expor shares are given in Abeysinghe (2000a). In our model yi5dln(y i), where Yi is he consan dollar seasonally adjused GDP of counry i. An imporan quesion is how o incorporae oil prices ino he model. Sudies on he US have esablished ha he effec of oil prices on growh is asymmeric. Alhough a rise in oil price has a significan negaive effec on growh, a fall in oil price does no cause an economic expansion (Hamilon, 2000). Following his lieraure we ried a number of measures designed o capure his 1 i i i i asymmeric effec. By defining real oil price as o 5Dln(O? E /P ), where O is oil price in $US, E is he exchange rae of counry i agains he $US and Pi is he CPI of counry i, we examined he effec of posiive and negaive oi as in Mork (1989), volailiy adjused posiive and negaive oil price 2 shocks as in Lee e al. (1995), volailiy adjused posiive and negaive o as in Hamilon (2000), curren oil price relaive o he annual average as a varian of Davis e al. (1997) and an IV esimaor using Hamilon s (2000) quaniy-dummy variable for pas oil shocks as an insrumen. Alhough all hese produce expeced resuls for he US economy, hey produce insignifican and quesionable resuls for he oher counries. We, herefore, revered o he following simple formulaion ha allows for a symmeric effec of oil price on growh. As in Hamilon s IV formulaion, if oil price changes are ruly exogenous, he symmeric effec seems quie plausible especially for he oil producers in our sample, Indonesia and Malaysia. Preliminary esimaes based on D ln(o), D ln(o? E ) and D ln(o? E /P ), as measures of o, show i i i i similar resuls. A closer examinaion of a daa plo shows ha he changes in oil price is so dominan ha he above conversions do no have much effec on he variaion in oil prices. The only marked deparure of D ln(o) from he oher wo occurs in Indonesia during he period of Asian crisis. Because of he similariy of esimaes we carried ou our analysis based on oi5dln(o? E i). Moreover, i is no difficul o verify ha, since oil price affecs he CPI inflaion in a disribued lag manner, D lnpi can 3 be subsiued away wih a sufficien number of lags of D ln(o? E ) in he model. For he oil price we use he $US spo price of Bren crude oil, which is available only since 1982Q1. This consrains our sample o he period 1982Q1 2000Q2. The exchange rae we use for he 4 ROECD is he German Mark agains he $US. As in Abeysinghe (2000a) we se he maximum lag lengh in (1) o p54. For Indonesia a (0,1) dummy was used for he Asian crisis period. Since yi values and possibly oi are endogenous, we esimaed he model equaions by 2SLS using four lags of each yi and four lags of oi as insrumens. An F-es on he coefficiens of oil price in individual equaions shows ha he coefficiens are in general saisically insignifican. However, he i i 1 In our iniial work we used he US oil price series WPI0561 downloaded from Hamilon s websie. 2 These are one-sep forecas errors of real oil price from an AR(6) model wih a GARCH(1,1) error process. 3 From a heoreical poin of view wha we need is he relaive price of oil, relaive o he price of a close subsiue. The real price of oil defined above seems o be a poor proxy for he relaive price because of he direc dependence of CPI on oil price. I should also be noed ha he common pracice of comparing he curren levels of nominal and real prices of oil could be misleading, because he gap beween he wo can be increased arbirarily simply by pushing he base of CPI far back ino he pas. 4 The Bren price is from he Inernaional Energy Agency and he average exchange raes are from IFS.

4 150 T. Abeysinghe / Economics Leers 73 (2001) sum of hese coefficiens remains persisenly negaive for oil imporers and posiive for oil exporers. I should be noed here ha hese ess do no consider he indirec effecs ha we are ineresed in. Wha we require are ess on he impulse responses. Theoreical work on his aspec remains o be done wihin he framework of our model. As poined ou by Kilian and Chang (2000) exising mehodologies do no necessarily provide reliable confidence inervals for large VAR models. 4. Direc and indirec effecs Afer esimaing he model parameers, he impulse responses were generaed by fixing he average W marix a 52000Q2. The cumulaive impulse responses (muliplier effecs) of GDP growh in response o a 50% increase in oil price are ploed up o 20 quarers in Fig. 1. Some graphs show he presence of seasonal effecs. Table 1 provides a summary. The long run effecs repored in he able are he average effecs over quarers. Mos of he impulse responses end oward zero afer abou 12 quarers. This exercise reveals some useful observaions. Boh Indonesia and Malaysia are ne oil exporers. The direc impac of high oil prices on hese wo is posiive. They, however, canno escape he conracionary effec coming hrough he rading parners. In he long run, hey also lose ou. This resul is likely o hold in general for oil exporing open economies. All he oher economies in he sudy are ne oil imporers. Boh direc and indirec effecs on hem are negaive. Singapore is an ineresing case. Since Indonesia and Malaysia are wo major rading parners of Singapore, he indirec effec of high oil prices on Singapore is slighly posiive iniially. However, as Indonesia and Malaysia sar o feel he pinch, Singapore will also experience a larger negaive indirec effec. Singapore and Taiwan appear o have similar long run effecs. Surprisingly, he indirec effec on Taiwan is much smaller compared o Singapore. Philippines and Thailand seem o be he wors affeced followed by Souh Korea. Boh Hong Kong and China are no much affeced, mainly due o he China-effec. China is an oil producer. During he pas 7 years, however, China has become a ne oil imporer. Neverheless, he impac of high oil prices on China is small. Hong Kong seems o be insulaed by China, which has emerged as he major rading parner of Hong Kong. Fig. 1 provides an ineresing conras beween USA and ROECD. The direc impac of oil price on he US economy is much larger han he indirec effec whereas he opposie holds for ROECD. This reflecs he fac ha US is relaively a closed economy and ROECD is a collecion of small open economies. Japan seems o fall in beween. 5. Conclusion The resuls of his exercise show ha he ransmission effec of oil prices on growh may no be ha imporan for a large economy like he US bu i could play a criical role in small open economies. We also have o bear in mind ha he acual working of a new shock depends on how i ineracs wih he consumer and invesor confidence jus as we have seen during he Asian financial crisis. Furher

5 T. Abeysinghe / Economics Leers 73 (2001) Fig. 1. Direc, indirec and oal impac of a 50% increase in oil price on GDP growh. Direc (box line), Indirec (plus line), Toal (solid line).

6 152 T. Abeysinghe / Economics Leers 73 (2001) Table 1 Impac of a 50% increase in oil price on GDP growh (%) Direc Impac Toal impac hrough impac rading parners Indonesia Afer 4 qrs Long run Malaysia Afer 4 qrs Long run Philippines Afer 4 qrs Long run Thailand Afer 4 qrs Long run Hong Kong Afer 4 qrs Long run S Korea Afer 4 qrs Long run Singapore Afer 4 qrs Long run Taiwan Afer 4 qrs Long run China Afer 4 qrs Long run Japan Afer 4 qrs Long run US Afer 4 qrs Long run Res of OECD Afer 4 qrs Long run effors are needed o obain more refined and sronger esimaes of oil price elasiciies for he counries in our sudy. Acknowledgemens I would like o hank Peer Wilson and seminar paricipans of a Press Conference held on Ocober 3, 2000 a he Naional Universiy of Singapore for heir commens on he preliminary work on his subjec. Research assisance by Wasana Karunarahne and Rajaguru Gulasekaran is also grealy appreciaed. This research was parially suppored by an NUS research gran R References Abeysinghe, T., 2000a. The Asian crisis, rade links and oupu mulipliers: a srucural VAR approach. Working Paper, Deparmen of Economics, Naional Universiy of Singapore, hp:// ecs/.

7 T. Abeysinghe / Economics Leers 73 (2001) Abeysinghe, T., 2000b. Thai meldown and ransmission of recession wih ASEAN4 and NIE4. In: Claessens, S. and Forbes, K. (Eds.), Inernaional financial conagion: how i spreads and how i can be sopped. Kluwer Academic Publishing, Dordrech. Forhcoming, hp:// conagion). Abeysinghe, T., Wilson, P., Could high oil prices derail Asian recovery? Press Release, Economeric Sudies Uni, Deparmen of Economics, Naional Universiy of Singapore, hp:// ecs/ cener/ esu/ oilprice.pdf. Asian Developmen Bank, Asia Recovery Repor 2000 Ocober Issue. Asia Recovery Informaion Cener, ADB, Manila, Philippines. Davis, S.J., Loungani, P., and Mahidhara, R., Regional labor flucuaions: oil shocks, miliary spending, and oher driving forces. Working Paper, Universiy of Chicago. Hamilon, J., Oil and he macroeconomy since World War II. Journal of Poliical Economy 91, Hamilon, J., Wha is an oil shock? NBER Working paper No Kilian, L., Chang, P.L., How accurae are confidence inervals for impulse responses in large VAR models? Economics Leers 69, Lee, K., Ni, S., Rai, R.A., Oil shocks and he macroeconomy: he role of price variabiliy. The Energy Journal 16, Mork, K.A., Oil and he macroeconomy when prices go up and down: An exension of Hamilon s resuls. Journal of Poliical Economy 91,

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