Oil price volatility and real effective exchange rate: the case of Thailand

Transcription

1 MPRA Munch Personal RePEc Archve Ol prce volaly and real effecve exchange rae: he case of Thaland Koman Jranyakul Naonal Insue of Developmen Admnsraon July 204 Onlne a hps://mpra.ub.un-muenchen.de/60204/ MPRA Paper No , posed 26 November :3 UTC

2 [Workng Paper, 204] Ol prce volaly and real effecve exchange rae: he case of Thaland Koman Jranyakul, School of Developmen Economcs, Naonal Insue of Developmen Admnsraon, Bangkok, Thaland. Emal: Absrac: The man objecve of hs sudy s o drecly examne he relaon beween real ol prce and real effecve exchange rae n Thaland durng July 997 o December 203. Under he floang exchange rae regme, blaeral exchange raes are expeced o flucuae more han under he fxed exchange rae regme. The monhly daa of real effecve exchange rae ndex and real ol prce are used. The resuls from hs sudy reveal ha here s no conegraon and causaly n levels of he wo seres. However, an ncrease n ol prce volaly causes real exchange rae volaly o ncrease. Ths man fndng gves some polcy mplcaons o polcy makers. Keywords: Ol prce, real exchange rae, bvarae GARCH, volaly spllover.. Inroducon I s wdely known n he economc leraure ha ol prce shocks can mpose economc mpacs on boh ol-exporng and ol-mporng counres. In addon, here wll be a wealh ransfer from ol-mporng o ol exporng counres due o an ncrease n he prce of ol (Krugman, 980). Many emprcal sudes have focused on he mpac of real ol prce on real exchange rae. However, prevous resuls on he relaonshp beween crude ol prces and exchange raes seem o be ambguous. Amano and van Norden (998) fnd ha here exss a sable lnkage beween ol prce shocks and he US real effecve exchange rae over he pos- Breon Wood perod. Ther fndng suggess ha ol prces can be he domnan source of perssen exchange rae shocks. Chaudhur and Danel (998) fnd he evdence showng ha ol prce s he man source of he US real exchange rae flucuaons. Akram (2004) fnds a non-lnear negave relaonshp beween ol prces and he Norwegan exchange rae. An ncrease n he prce of ol leads o an apprecaon of he exchange rae. Chen and Chen (2007) fnd ha here s a lnk beween real ol prces and real exchange raes n he G-7 counres. A rse n ol prces leads o a real deprecaon. In addon, real ol prces can forecas fuure real exchange rae movemens. Huang and Guo (2007) fnd ha real ol prce

3 shocks lead o mnor apprecaon of he long-erm real exchange rae n Chna, a large Asan counry ha s dependen on mpored ol. Lzardo and Mollck (200) fnd ha ol prces play an mporan role n he moneary model of exchange raes,. e., ol prces sgnfcanly explan movemens n he value of he US dollar agans major currences. Ther resuls show ha an ncrease n real ol prces causes a sgnfcan deprecaon of he US dollar agans ne ol-exporng counres currences, bu causes an apprecaon of ol-mporng counres currences. Hasanov (200) employs error correcon model and conegraon ess o examne he mpac of real ol prce on real exchange rae of Azerbajan and fnds ha real ol prce mpose a posve mpac on real exchange rae n he long run. In esng co-movemens beween ol prce and exchange rae, Reboredo (202) fnds ha co-movemens beween ol prce and a range of currences are generally weak. Ghosh (20) examnes he relaonshp beween crude ol prce and exchange rae usng daly daa for Inda and fnds ha an ncrease n ol prce changes causes a deprecaon of he rupee/us dollar. Turhan e al. (203) fnd ha a rse n ol prces causes an apprecaon of emergng economes currences agans he US dollar. Beckmann and Czudaj (203) use he rade-weghed US effecve exchange raes and he prces of ol o examne he relaonshp beween hem. They employ Markovswchng vecor error correcon model o es he lnk beween ol prces and effecve exchange raes (boh nomnal and real erms). One of her man fndngs s ha boh nomnal and real effecve exchange raes dsplay a smlar paern o ol prce shocks,.e., an ncrease n real ol prces leads o an apprecaon of he exchange raes. Few emprcal sudes have focused on he mpac of ol prce volaly on exchange raes. Rckne (2009) fnds ha he co-movemens beween ol prce and real exchange raes n he sample of 33 ol-exporng counres are condonal on polcal and legal nsuons. Specfcally, currences n counres wh srong bureaucraces are less affeced by ol prce varaon. Englama e al. (200) examne he relaonshp ol prce and exchange rae volaly n Ngera. They fnd ha exchange rae volaly s posvely nfluenced by ol prce volaly. Thaland has swched from fxed o floang exchange rae regme snce July 997. The adopon of floang exchange rae regme has caused flucuaons n blaeral nomnal exchange raes ha are raded n he counry. Therefore, he real effecve exchange rae, he rade weghed ndex, has been subsanally affeced. Fgure shows he evoluon of he real effecve exchange rae and real ol prce volaly. Afer he counry has adoped he floang exchange rae regme, he behavor of real effecve exchange rae appears o be ndependen 2

4 of real ol prce volaly (derved from he GARCH model n Secon 2). The hgh volaly of real ol prce durng 2008 and 2009 dd no seem o cause more flucuaons n he real effecve exchange rae. Therefore, should be expeced ha real ol prce volaly mgh no affec he real effecve exchange rae. However, here mgh exs volaly spllover from ol o foregn exchange markes a. Real effecve exchange rae movemens 240 Ol prce volaly b. Ol prce volaly Fgure Real effecve exchange rae and real ol prce volaly The man objecve of hs paper s o nvesgae wheher ol prce uncerany affecs he real effecve exchange rae under he floang exchange rae regme. Monhly daa of real effecve exchange rae and real ol prces from July 997 o December 203 are used. The 3

5 wo-sage approach, whch comprses a bvarae GARCH model and he sandard Granger causaly es, s adoped. The man fndng s ha real ol prce volaly (uncerany) does no cause real effecve exchange rae of deprecae or apprecae, bu real ol prce volaly does cause real exchange rae volaly (uncerany) o ncrease. Real exchange rae uncerany can mpose a sgnfcanly negave mpac on he counry expors and cause rade defcs. The presen paper s srucured as follows: Secon 2 descrbes he daa used n he analyss and economerc mehodology peranng o a bvarae generalzed auoregressve condonal heeroscedasc (GARCH) model and causaly es. Secon 3 presens emprcal resuls and fndngs. The las secon gves concludng remarks. 2. Mehodology Ths secon descrbes he daa and esmaon mehods used n hs sudy. 2. Daa Monhly daa of consumer prce ndex, he real effecve exchange rae ndex, and crude ol prce are used n hs sudy. The real effecve exchange rae ndex and consumer prce ndex are obaned from he Bank of Thaland. The Bren crude ol prce seres expressed n dollar per barrel s obaned from Energy Informaon Admnsraon. The daa se covers he perod from July 997 o December 203 wh 98 observaons. 2 Real ol prce s calculaed by mulplyng crude ol prce by he dollar exchange rae and deflang by consumer prce ndex. Movemens n real effecve exchange rae (r ) and real ol prce (r ) are he percenage raes of change of real effecve exchange rae ndex and real crude ol prce. Summary sascs of real ol movemens and real effecve exchange rae changes are repored n Table 2. Average monhly rae of real exchange rae change s whereas he average monhly ol prce rae of change s.232. The Jarque-Bera normaly es rejecs he null of a normal dsrbuon of boh seres, ndcang ha leas squares esmaon s no suable. Ths s he perod of he floang exchange rae regme. 2 In fac, he sze and sgnfcance of parameers n he condonal varance depend on he daa frequency beng used. Monhly daa se allows for a longer me span and can capure he long-run mpac of one varable on oher varables. 4

6 Table. Descrpve sascs and un roo es r r Mean Sandard devaon Skewness Kuross Jarque-Bera sasc (p-value=0.000) DF-GLS wh consan -5,36 [0] (p-value=0.000) (p-value=0.037) [0] (p-value=0.000) Noe: r sands for he percenage change n real effecve exchange rae, and r sands for he percenage change n real ol prce. The number n parenhess s he probably of accepng he null of normaly. The modfed Dckey-Fuller (DF-GLS) es developed by Ello e al. (996) s used o deermne saonary propery of he raes of change n real effecve exchange rae and real ol prce. Ths es s beleved o be more powerful han he radonal un roo ess. The resuls show ha he wo seres are saonary due o he rejecon of he null hypohess ha he seres conan un roo. The saonary propery of he wo seres enables one o perform he esmaon of a bvarae GARCH model and o es for causaly beween he wo seres. 2.2 Mehodology Three procedures can be used o deec he lnkages beween real effecve exchange rae and real ol prce. They are he followngs Conegraon es The exsence of conegraon beween real effecve exchange rae and he prce of ol mples ha he prce of ol adequaely capures he domnan source of perssen real exchange rae movemens. Pesaran e al. (200) proposed an alernave procedure n esng for conegraon called a condonal auoregressve dsrbued lag (ARDL) model and error correcon mechansm. The ARDL (:p, q) model s specfed as: 5

7 p q L = µ + α L + β L + e () j= 0 j where denoes frs dfference, L s he log of real effecve exchange rae ndex, L denoes he log of real ol prce. The lag orders are p and q, respecvely. They may be he same or dfferen. To deermne he opmal numbers of lagged frs dfferences n he specfed ARDL model, he grd search can be used o selec a parsmonous model ha s free of seral correlaon. By addng lagged level of he wo varables no equaon () as shown n equaon (2), he compued F-sasc for deecng conegraon can be obaned. p q L + γ 2L + α L + β j= 0 L = µ + γ L + e (2) j The compued F-sasc s compared wh he crcal values. If he compued F-sasc s greaer han he upper bound crcal F-sasc, conegraon exss. If he compued F- sasc s smaller han he lower bound F-sasc, conegraon does no exs. In case he compued F-sasc s beween he upper and lower bound F-sasc, he resul s nconclusve. Unlke oher echnques ha can be used o es for conegraon, reparameerzaon of he model no he equvalen vecor error correcon s no requred. Furhermore, hs procedure can an be appled o he mxed beween I(0) and I() resuled from un roo ess, bu no for I(2) seres. The resuls of un roo ess from Table show ha he order of negraon of he wo seres does no exceed one Non-causaly es Toda and Yamamoo (995) develop he es for causal relaonshp beween varables as an alernave o he sandard Granger (969) causaly es. Ths non-causaly es n a bvarae vecor auoregressve (VAR) model havng k lags can be conduced n her level of seres. The opmal lag lengh (k) can be deermned by Schwarz nformaon creron (SIC). The es s performed n a VAR model of order k* = k + d max, where d max s he maxmum ancpaed order of negraon of he seres. Rambald and Doran (996) ndcae ha he valdy of he es usng he modfed Wald sascs for lnear or non-lnear resrcon does no depend on he order of negraon of he seres, specfcally he seres can be I(0), I() or I(2). Wheher he varables n he model Granger cause each oher s esed n he jon resrcons where all coeffcens are zero. The VAR model for non-causaly es s specfed as: 6

8 k k+ dmax k k+ dmax L = a0 + L + α j L j + β L + β j L j + u j= k+ j= k+ α (3) and k k+ dmax k k+ dmax L = a + L + γ j L j + δ L + δ j L j + u2 j= k+ j= k+ γ (4) The error erms n he VAR model are assumed o be whe nose. Snce he exra lagged varables are ncluded n he model, he causaly es s conduced by esng for zero resrcons of he coeffcens of all lag varables. Equaon (3) s used o es wheher real ol prce (L) Granger causes real effecve exchange rae (L) whle equaon (4) s used o es wheher real effecve exchange rae (L) Granger causes real ol prce (L). The man advanage of hs es s ha one does no need o know a pror wheher he varables are conegraed as long as he order of negraon of seres does no exceed he lag lengh of he specfed VAR model The wo-sep approach The wo-sep approach s employed o explan he relaonshp beween ol prce volaly and real exchange rae volaly. In he frs sep, a bvarae generalzed auoregressve heeroskedasc model wh consan condonal correlaon (ccc-garch) model proposed by Bollerslev (990) s employed o generae real exchange rae and ol prce volales. In he second sep, hese generaed seres along wh real effecve exchange rae change and he rae of change n real ol prce seres employed n he sandard Granger (969) causaly es. Pagan (984) crczes hs procedure because produces he generaed seres of volaly or uncerany. When hese generaed seres are used as regressors n Granger causaly es, he model mgh be msspecfed. However, he man advanage of he wo-sep procedure s ha provdes room for he ably o esablsh causaly beween varables. 3 The sysem equaons n a ccc-garch(,) model comprses he followng fve equaons. p p r = a,0 + a, r + b, r + e, (5) 3 The curren value of one varable mgh no affec he curren value of anoher varable, bu some of s lags mgh do. 7

9 p r = a2,0 + a, r + e2, (6) 2, h = + α,ε + β,h µ (7) = µ α ε β (8) 2, h 2 + 2, + 2,h h, / 2 / 2 = ρ2 ( h ) ( h ) (9) where r s he rae of change n real effecve exchange rae, and r s he rae of change n real ol prce, h s he condonal varance of real effecve exchange rae, h s he condonal varance of real ol prce, and h, s he condonal covarance of he wo varables. The consan condonal correlaon s ρ 2. The sysem equaons can be esmaed smulaneously. The sandard Granger causaly es s performed n he followng equaon. k k k k = a+ y + β x, + γ x2, + φ x3, y α + u (0) where y s a dependen varable, and x, x 2, and x 3 are ndependen varables. If any ndependen varable causes he dependen varable, here should be a leas one sgnfcan coeffcen of ha lagged ndependen varable. Ths also ndcaes ha he F-sasc n he sandard causaly es mus show sgnfcance for each par of varables. In he presen sudy, he sequence of varables ha wll ener no a vecor auoregresson s {r, r, h, h }, {r, r, h, h }, {h, r, r, h }, and {h, r, r, h }. The opmal lag lengh s deermned by SIC. I should be noed ha all varables n he es mus be saonary. An unresrced vecor auoregressve (VAR) model s used o deec he sgn of lagged varables. 3. Emprcal Resuls The grd search for he parsmonous ARDL (p, q) model dscovers ha he ARDL(,) s free of seral correlaon, resulng from usng Lagrange mulpler (LM) seral correlaon es. The ch-square sasc (χ 2 (2)) of he LM es = 3.93 wh p-value = 0.4 leads o he concluson ha he null hypohess of no seral correlaon n he resduals s acceped. By 8

10 addng he lagged level of he par of varables (L and L) o he ARDL(,) model, he compued F-sasc resulng from esng equaon (2) agans equaon () s Ths compued F-sasc s below he lower bound crcal value a he 0 percen level of 4.04 n Table CI() case III provded by Pesaran e al. (200). Therefore, he null hypohess of no conegraon canno be rejeced. Therefore, here s no long-run relaonshp beween real effecve exchange rae and real sock prce. The non-causaly es n a VAR model of equaons (3) and (4) usng level of he wo seres s performed wh he opmal lag of wo deermned by SIC plus he ancpaed order of negraon of one. The lag (k + d max ) s hree. The resuls are repored n Table 2. Table 2 Resuls of non-causaly es beween L and L Null hypohess Modfed Wald sasc p-value L does no cause L (+) L does no cause L 6.64 (+) Msspecfcaon ess for he VAR model Tes sasc p-value LM JB WH Noe: L sands for log of real effecve exchange rae, and L sands for log of real ol prce. (+) ndcaes he posve sum of he coeffcen of lagged varables, whch s posve causaon. LM s he Lagrange mulpler es for seral correlaon up o he hrd order n he resduals, JB s he Jarque-Bera sasc for esng he null hypohess ha he resduals are mulvarae normal, and WH s he Whe heeroskedascy es of he resduals. The resuls n Table 2 show ha here are bdreconal posve causaons beween real ol prce and real effecve exchange rae. However, he level of sgnfcance s only a 0 percen. 9

11 Furher ess are conduced o examne he msspecfcaon of he augmened VAR(3) model used n he analyss. The LM es sasc ndcaes he accepance of he null hypohess ha here s no seral correlaon n he resduals up o he hrd order of lags. Furhermore, he WH es shows ha he null hypohess of no ARCH effec can be rejeced a he percen level of sgnfcance. In addon, he JB sasc shows ha he resduals are no mulvarae normal. Therefore, he augmened VAR(3) model s no suable for non-causaly es. In oher words, he resuls n Table 2 mgh no be relable. Up o hs pon, here s no long-run relaonshp beween real effecve exchange rae and real ol prce, and here s unrelable non-causaly es n he level of seres. Therefore, can be concluded ha conegraon and non-causaly ess canno deec he mpac of real ol prce on real effecve exchange rae. 4 However, he wo-sep procedure can deec some aspecs of he lnk beween real ol prce and real effecve exchange rae. The resuls of he esmae of he bvarae GARCH(, ) model n he sysem equaons, equaons (5) (9), are repored n Table 3. Table 3 Resuls from he bvarae GARCH(,) esmaon Mean equaons: r = *** r 0.226*** r r (.259) (4.763) (-2.79) (-.257) r = * r (0.287) (.824) (-sasc n parenhess) Varance and covarance equaons: 2, h *** *** *** h = ε 4 Ths fndng seems o suppor he resuls found n Reboredo (202), bu s no n lne wh he fndng by Ghosh (20), Beckman and Czudaj (203) and Turhan e al. (203). 0

12 (4.424) (3.20) (3.832) 2, h ** h = ε (0.852) (2.205) (4.48) h, = 0.36 **( h ) / 2 ( h ) / 2 (-.694) (-sasc n parenhess) Sysem dagnosc es: Q(6) = (p-value=0.7) Noe: r and r sands for he percenage raes of change n real effecve exchange rae and ol prce respecvely. The condonal varances, h for real effecve exchange rae and h for real ol prce. The condonal covarance s h,. ***, ** and * denoes sgnfcance a he, 5 and 0 percen, respecvely. Q(k) s he Box-Perce sasc es for he resduals obaned from sysem resdual Pormaneau ess for auocorrelaons. Table 4 Resuls of Granger causaly es Hypohess F-sasc p-value r does no cause r.828 (-) 0.64 r does no cause h 2.65 (+) 0.8 h does no cause r.85 (-) h does no cause h 3.3**(+) Noe: r and r sands for he percenage raes of change n real effecve exchange rae and ol prce respecvely. The condonal varances, h for real effecve exchange rae and h for real ol prce. ** denoes sgnfcance a he 5 percen level.

13 Assumng he condonal correlaon (ρ 2 ) s consan, he model performs well. 5 The esmaed condonal correlaon s whch s sgnfcan a he 5 percen level. Ths correlaon ndcaes ha he wo varables are nerdependen wh negave relaonshp. The sandard Granger causaly es s hus performed on four saonary seres. The resuls are repored n Table 4. The resuls n Table 4 show ha real ol prce change ends o cause he real effecve exchange rae o decrease (apprecae), bu ends o cause s volaly o ncrease. In addon, real ol prce volaly ends o cause he real effecve exchange rae o decrease or apprecae. However, hese hree resuls are no sascally sgnfcan. Fnally, real ol prce volaly posvely causes real effecve exchange rae volaly. Ths resul s sgnfcan a he 5 percen level. Therefore, can be concluded ha here s volaly ransmsson from real ol prce o real effecve exchange rae durng he perod of floang exchange rae regme. In oher words, a rse n real ol prce rsk can cause an ncrease n real exchange rae rsk and vce versa. Ths fndng s n lne wh evdence found by Englama e al. (200). Response o Cholesky One S.D. Innovaons Fgure 2. Response of real effecve exchange rae volaly o ol prce volaly 5 The esmaed parameers of ARCH (ε 2 -) and GARCH (h ) erms are non-negave. Furhermore, he sum of he coeffcens of he ARCH and GARCH erms s for he condonal varance equaon of he rae of change n real effecve exchange rae and for he condonal varance equaon of he rae of change n real ol prce. Therefore, he wo condonal varance seres are saonary. The sysem s also free of seral correlaon because he Q(6) sasc has he p-value ha accep he null hypohess of no seral correlaon n he sysem resduals. 2

14 The mpulse response n Fgure 2 shows ha real exchange rae volaly respond negavely o real ol prce volaly n he fve-monh perod and respond posvely o real ol prce volaly aferward and never dsspae. In he evens of rsng real exchange rae volaly caused by real ol prce volaly, he counry s rade balance can be affeced. If real exchange rae volaly adversely affecs boh expors and mpors, he rade balance wll be mproved when he sze of he mpac of volaly on expors s relavely smaller han he sze of he mpac of volaly on mpors. Oherwse, he rade balance wll be harmed. Even hough he cenral bank can mplemen sound moneary polcy measures o sablze some major currences, such as he US dollar, Japanese yen, and Euro currency, flucuaons of nomnal ol prce canno be conrolled. Therefore, seems necessary ha polcy makers should encourage frms o rely more on new energy (hydroelecrc and wnd power) so ha crude ol prce wll no be he man cause of real exchange rae volaly. In addon, some measures ha wll enhance compeveness of exporng frms may deem necessary. Encouragng energy effcency nsead of energy nensy can reduce coss of producon. Expor dversfcaon should also be mplemened. 4. Concludng Remarks Ths sudy employs hree echnques of me seres analyss o examne he relaonshp beween real ol prce and real effecve exchange rae n Thaland, whch s an emergng marke economy. The resuls from conegraon es n a bvarae framework show ha here s no long-run relaonshp beween real ol prce and real effecve exchange rae. An alernave echnque o examne he causal relaonshp beween hese wo varables s he non-causaly es ha reles on an augmened VAR model. Ths approach allows for deecng causaon beween he levels of varables. However, he resuls from non-causaly es fals o pass dagnosc ess. Therefore, he resuls should no be relable. The resuls from he wo-sage approach show ha here s no causaly runnng from a change n real ol prce o a change n real effecve exchange rae. Addonally, real ol prce volaly does no cause real effecve exchange rae o apprecae as found n prevous emprcal sudes. An mporan fndng s ha an ncrease n real ol prce volaly causes an ncrease n real exchange rae volaly, whch can harm he rade balance of he counry. Polcymakers should be aware of he volaly or uncerany n he foregn exchange markes 3

15 caused by uncerany n he prce of ol. I mgh be necessary o mplemen some measures ha encourage frms o rely more on new energy (hydroelecrc and wnd power) so ha crude ol prce wll no be he man cause of real exchange rae volaly. In addon, some measures ha wll enhance compeveness of exporng frms may deem necessary. Encouragng energy effcency nsead of energy nensy can reduce coss of producon. Expor dversfcaon should also be mplemened o preven he rade balance o deerorae n he fuure. References Akram, Q. F., Ol prces and he rse and fall of he US real exchange rae, Journal of Inernaonal Money and Fnance, 7(2), Amano, R. A. and van Norden, S., 998. Ol prces and he rse and fall of he US real exchange rae, Journal of Inernaonal Money and Fnance, 7(2), Beckman, J. and Czudaj, R Ol prces and effecve dollar exchange raes, Inernaonal Revew of Economcs and Fnance, 27(C), Bollerslev, T., 990. Modellng he coherence n shor-run nomnal exchange raes: a mulvarae generalzed ARCH model, Revew of Economcs and Sascs, 72(3), Chen, S-S. and Chen, H-C Ol prces and real exchange raes, Energy Economcs, 29(3), Chaudhur, K. and Danel, B. C Long-run equlbrum real exchange raes and ol prces, Economcs Leers, 58(2), Ello, G., Rohenberg, T. J. and Sock, J. H., 996. Effcen ess for an auoregressve un roo, Economerca, 64(4), Englama, A., Duke, O. O., Ogunleye, T. S., and Ismal, F. U., 200. Ol prces and exchange rae volaly n Ngera: an emprcal nvesgaon, Cenral Bank of Ngera, Economc and Fnancal Revew, 48(3), Ghosh, S., 20. Examnng crude ol prce-exchange rae nexus for Inda durng he perod of exreme ol prce volaly, Appled Energy, 88(5), Granger, C. W. J., 969. Invesgang causal relaons by economerc models and crossspecral mehods, Economerca, 37(3), Hasanov, F., 200. The mpac of real ol prce on real effecve exchange rae: he case of Azerbajan, DIW Berln, Dscusson Paper No

16 Huang, Y. and Guo, F., The role of ol prce shocks on Chna s real exchange rae, Chna Economc Revew, 8(4), Research Insue of Indusral Economcs. Krugman, P., 980. Ol and he dollar, NBER Workng Paper No Lzardo, R. A. and Mollck, A. V Ol prce flucuaons and U. S. dollar exchange raes, Energy Economcs, 32(2), Pagan, A., 984. Economerc ssues n he analyss of regressons wh generaed seres, Inernaonal Economc Revew, 25(), Pesaran, M. H., Shn, Y. and Smh, R. J., 200. Bounds esng approaches o he analyss of level relaonshp, Journal of Appled Economercs, 6(3), Rambald, A. N. and Doran, H. E., 996. Tesng for Granger non-causaly n conegraed sysem made easy, Workng Papers n Economercs and Appled Sascs, No. 88, Unversy of New England. Reboredo, J. C Modellng ol prce and exchange rae co-movemens, Journal of Polcy Modelng, 34(3), Rckne, J. K., Ol prces and real exchange rae movemens n ol-exporng counres: he role of nsuon, IFN Workng Paper No. 80. Toda, H. Y. and Yamamoo, T., 995. Sascal nferences n vecor auoregressons wh possbly negraed process, Journal of Economercs, 66(/2), Turhan, I., Hachasanoglu, E. and Soyas, U Ol prces and emergng marke exchange raes, Emergng Markes Fnance and Trade, 49(S),