Oil price shocks and domestic inflation in Thailand

Transcription

1 MPRA Munich Personal RePEc Archive Oil rice shocks and domesic inflaion in Thailand Komain Jiranyakul Naional Insiue of Develomen Adminisraion March 205 Online a h://mra.ub.uni-muenchen.de/62797/ MPRA Paer No , osed 3. March 205 3:35 UTC

2 Oil rice shocks and domesic inflaion in Thailand Komain Jiranyakul School of Develomen Economics Naional Insiue of Develomen Adminisraion Bangkok, Thailand Absrac: This aer emloy monhly daa o examine he emirical relaionshi beween oil rice shocks and domesic inflaion rae during 993 and 203. The resuls show ha oil rice, domesic or inernaional, does no have he long-run imac on consumer rices. However, oil rice shocks cause inflaion o increase while oil rice uncerainy does no cause an increase in inflaion. Furhermore, inflaion iself causes inflaion uncerainy. The findings of his sudy encourage he moneary auhoriies o formulae a more accommodaive olicy o resond o oil rice shocks. Keywords: Oil shocks, inflaion, bivariae GARCH, causaliy JEL Classificaion: E3, Q43. Inroducion One of ineresing oics on he relaionshi beween oil shocks and macroeconomic variables is he imac of oil rice shocks on domesic inflaion rae. The rise of oil rice can cause he coss of roducion of firms o increase. Therefore, he ass-hrough of oil rice hike is refleced in an increase in he general rice level of an economy. In addiion, changes in oil rice in he las five decades exhibi oil rice volailiy ha can disor he decisions by economic agens. Lee and Ni (2002) find ha oil rice shocks affec economic erformances via boh demand and suly channels. Earlier sudies by Mork and Hall (980) and Mork (989) oin ou ha inflaion induced by oil rice shocks can reduce real balances, a measure urchasing ower, in he economy and hus cause a recession. Bernanke e al. (997) argue ha he sagflaion hrea from he oil shocks in he 970s should no be underesimaed. The Federal Reserve adoed oo high ineres rae olicy and hus did no resond o oil rice shocks accuraely. This resuled in decreased ouu or recession in he US. Hamilon (2003) indicaes ha oil shocks maer because hey disru sending by consumers and firms on key secors, and hus reduce ouu growh. On he suly channel, oil rice shocks can cause consumer rices o increase. This deends on he share of oil rice in he rice index. Hooker (2002) examines he effecs of oil rice changes on inflaion in he US under a Phillis curve framework ha allows for asymmeries, nonlineariies and srucural breaks. The resuls show ha oil rice shocks seem o affec inflaion hrough he direc share of oil rice in consumer rices. Furhermore, moneary olicy has become less accommodaive of oil rice shocks and hus revens oil rice changes from assing direcly ino core inflaion. Ewing and Thomson (2007) find ha oil rices lead he cycle of consumer rices in he US. The oil rice ass-hrough ino inflaion in indusrialized counries can decline due o some facors. De Gregono and Lanerreche (2007) find ha he ass-hrough decline because of he fall in energy inensiy while Chen (2009) indicaes ha a decline in he ass-hrough is due o a higher rade oenness. Huang and Chao (202) examine he effecs of inernaional and domesic oil rices on he rice indices in Taiwan using monhly daa from January 999 o December 20. They find

3 ha changes in inernaional oil rices have more crucial imacs on he rice indices han changes in domesic oil rices. Chu and Lin (203) find ha oil rice shocks have boh longerm and shor-erm ass-hrough effecs on Taiwan s roducer rice index. Gao e al. (204) he degree of osiive ass-hrough from oil rice shocks o disaggregae US consumer rices is observed only in energy-inensive consumer rice indices. In addiion, he main causes of he ass-hrough are increases in he rices of energy-relaed commodiy. The main urose of he resen sudy is o invesigae he imac of oil rice shocks on domesic inflaion in Thailand. Monhly daa from January 993 o December 203 are used. This sudy does no use srucural vecor auoregression or oher mehods ha caure he ass-hrough from oil rice o consumer rice as used in revious sudies. In sead, he mehods used are he bounds esing for coinegraion and he wo-se aroach o deec he imac of oil rice shocks on inflaion and inflaion uncerainy. The main findings are ha oil rice shocks, defined as movemens in oil rice, osiively cause inflaion o increase, bu oil rice uncerainy does no affec inflaion. Furhermore, inflaion iself causes inflaion uncerainy in he Thai economy. The nex secion resens he daa and esimaion mehods ha are used in he analysis. Secion 3 resens emirical resuls. Secion 4 discusses he resuls found in his sudy. The las secion gives concluding remarks and some olicy imlicaions based on he resuls of his sudy. 2. Daa and Mehodology 2. Daa The daase used in his sudy comrises monhly daa during 993 and 203. The consumer rice index, indusrial roducion index and he US dollar exchange rae (bah/dollar) series are obained from The Bank of Thailand s websie. The series of Bren crude oil so rice exressed in he US dollar er barrel is obained from he US Energy Informaion Adminisraion. The oil rice series is inernaional oil rice. By mulilying he oil rice series by he US dollar exchange rae, he domesic oil rice series is obained. All series are ransformed ino logarihmic series. The samle size comrises 252 observaions. The PP uni roo ess roosed by Phillis and Perron (988) are erformed on firs differences of he hree series. The resuls are shown in Table. Table Resuls of PP ess for firs difference of all variables: 993M-203M2 Variables Tes A Tes B ci (changes in consumer rice index) [] [0] oil (changes in nominal oil irce: domesic) oil (changes in nominal oil irce: inernaional) i (changes in indusrial roducion index) [24] [0] [3] (0.00)*** [25] [0] [3] Noe: The levels of he hree variables are exressed in he logarihmic series. Tes A includes inerce only while Tes B includes inerce and a linear rend. The number in bracke is he oimal bandwidh. ***, ** and ** denoe significance a he, 5 and 0 ercen level, resecively. The number in arenhesis is he robabiliy of acceing he null hyohesis of uni roo. 2

4 The resuls from uni roo ess show ha he degree of inegraion of all series does no exceed one because he null hyohesis of uni roo is rejeced a he ercen level of significance. This is suiable in erforming he bounds esing for coinegraion and he esimae of a bivariae GARCH model as well as he sandard airwise causaliy es described in he nex sub-secion. 2.2 Esimaion Mehods 2.2. Coinegraion es The exisence of coinegraion beween nominal oil rice, indusrial roducion index and consumer rice index imlies ha here is a long-run relaionshi beween hese variables. Pesaran e al. (200) roosed an alernaive rocedure in esing for coinegraion called a condiional auoregressive disribued lag (ARDL) model and error correcion mechanism. The ARDL (:, q, r) model is secified as: i i q ci = µ + α ci + β oil + γ i + u () j= 0 i j where ci is he log of consumer rice index, oil is he log of nominal oil rice and i is he log of indusrial roducion. The lag orders are, q and r, resecively. They may be he same or differen. To deermine he oimal numbers of lagged firs differences in he secified ARDL model, he grid search can be used o selec a arsimonious model ha is free of serial correlaion. By adding lagged level of he wo variables ino equaion () as shown in equaion (2), he comued F-saisic for deecing coinegraion can be obained. r k= 0 k k q r ci + δ 2 oil + δ 3i + α i ci i + βi oil j + γ k j= 0 k= 0 ci = µ + δ i + v (2) The comued F-saisic is comared wih he criical values. If he comued F-saisic is greaer han he uer bound criical F-saisic, coinegraion exiss. If he comued F- saisic is smaller han he lower bound F-saisic, coinegraion does no exis. In case he comued F-saisic is beween he uer and lower bound F-saisic, he resul is inconclusive. Unlike oher echniques ha can be used o es for coinegraion, rearameerizing he model ino he equivalen vecor error correcion is no required. Furhermore, his rocedure can an be alied o he mixed beween I(0) and I() series resuled from uni roo ess, bu no for I(2) series. The resuls of uni roo ess from Table show ha he order of inegraion of he wo series does no exceed one The wo-se aroach The wo-se aroach is emloyed o exlain he relaionshi beween nominal oil rice and is uncerainy (or volailiy) as well as inflaion and is uncerainy. In he firs se, a bivariae generalized auoregressive heeroskedasic model wih consan condiional correlaion (ccc-garch) model roosed by Bollerslev (990) is emloyed o generae real exchange rae and oil rice volailiies. In he second se, hese generaed series along wih real effecive exchange rae change and he rae of change in real oil rice series emloyed in he sandard Granger (969) causaliy es. Pagan (984) criicizes his rocedure because i roduces he generaed series of volailiy or uncerainy. When hese generaed series are used as regressors in Granger causaliy es, he model migh be missecified. I can be argued k The inclusion of indusrial roducion index can lead o he deecion of ineracion beween he hree variables in a mulivariae coinegraion es. This is similar o he model used by Chen (2009) who examines he oil rice ass-hrough ino inflaion in indusrialized counries. 3

5 ha he main advanage of he wo-se rocedure is ha i rovides room for he abiliy o esablish causaliy beween variables. 2 The sysem equaions in a ccc-garch(,) model comrises he following five equaions. = a,0 + a, i i + b, io i + e, (5) o = a2,0 + a, io i + e2, (6) 2, h = µ + α,ε + β,h (7) = µ α ε β (8) o 2, o o h 2 + 2, + 2,h h, o ρ / 2 o / 2 = 2 ( h ) ( h ) (9) where is he rae of change in consumer rice index or inflaion rae, and o is he rae of change in nominal oil rice, h is he condiional variance of inflaion rae, h o is he condiional variance of nominal oil rice change, and h,o is he condiional covariance of he wo variables. The consan condiional correlaion is ρ 2. The sysem equaions can be esimaed simulaneously. The airwise Granger causaliy es is erformed in he following equaion. y k k = a+ i y i + β i x i α + η where y is a deenden variable, and x is an indeenden variable. If any indeenden variable causes he deenden variable, here should be a leas one significan coefficien of ha lagged indeenden variable. This also indicaes ha he F-saisic in he sandard causaliy es mus show significance for each air of variables. In he resen sudy, he sequences of variables ha will be esed are {o,}, {o, h }, {h o, }, {h o, h }, {and, h }. The oimal lag lengh is deermined by SIC. I should be noed ha all variables in he es mus be saionary. An unresriced vecor auoregressive (VAR) model is used o deec he sign of lagged variables. 3. Resuls The models exressed in equaions () and (2) are used for esing he exisence of level relaionshi beween consumer rice index, indusrial roducion index and nominal oil rice (boh domesic and inernaional) using arsimonious models. The resuls from bounds esing for coinegraion are shown in Table 2. Table 2 Resuls from bounds esing for coinegraion: 993M0-203M2 Model Comued F ARDL model χ 2 (2) a. ci vs. o and i 3.38 (,,).972 (=0.373) b. ci vs. o and i (,,).343 (=0.5) Noe: The LM es for serial correlaion in he secified ARDL models is reresened by χ 2 (2). Three variables: ci, o and i he logs of CPI, oil rice and indusrial roducion index, resecively. O in (a) is domesic oil rice and o in (b) is inernaional oil rice. (0) 2 The curren value of one variable migh no affec he curren value of anoher variable, bu some of is lags migh do. 4

6 The resuls from bounds ess indicae ha coinegraion does no exis in boh models. The comued F-saisics of 3.38 and are smaller han he lower bound criical values of 4.94 and 4.04 a he 5 and 0 ercen level of significance (Table CI (iii) Case III in Pesaran e al., 200). Therefore, i can be concluded ha here is no long-run equilibrium relaionshi beween he rice level and oil rices (domesic or inernaional). Before erforming a bivariae GARCH esimae, he descriive saisics for he full samle eriod are reored in Table 3. Table 3. Descriive saisics, 993M-203M2 o Mean Sandard deviaion Skewness Kurosis Jarque-Bera saisic (-value=0.000) (-value=0.005) Noe: sands for he ercenage change in consumer rice index, and o sands for he ercenage change in domesic oil rice as defined earlier. The number in arenhesis is he robabiliy of acceing he null of normaliy. The average monhly inflaion rae is ercen, whereas he average monhly oil rice change is.24 ercen. The Jarque-Bera normaliy es rejecs he null hyohesis of a normal disribuion of he wo series, indicaing ha he leas squares esimaion is no suiable. The bivariae GARCH esimaion for he sysem equaions (5) o (9) o obain volailily or uncerainy series are reored in Table 4. Table 4 Resuls from he bivariae ccc-garch(,) esimaion Mean equaions: = 0.57*** + 0.5* ** * o (4.259) (.774) (3.446) o = ** o (0.430) (2.94) (-saisic in arenhesis) Variance and covariance equaions: 2, h = *** *** ε *** h (2.759) (3.40) (6.55) o 2, o o h = ** ε *** h (.305) (2.289) (2.65), o / 2 o / 2 h = *** ( h ) ( h ) (3.925) (-saisic in arenhesis) Sysem diagnosic es: Q(4) =3.597 (-value=0.629) Noe: o and o sands for he ercenage raes of change in consumer rice index and nominal oil rice, resecively. The condiional variances, h for inflaion rae and h o for nominal oil rice. The condiional covariance is h,o. ***, ** and * denoes significance a he, 5 and 0 ercen, resecively. Q(k) is he Box-Pierce saisic es for he residuals obained from sysem residual Pormaneau ess for auocorrelaions. 5

7 The assumion of consan condiional correlaion faciliaes he simliciy of he sysem esimaion. The model erforms quie well in he daase. The mean equaion for domesic inflaion rae is assumed o be deenden on he lag of domesic oil rice change while he mean equaion for domesic oil rice change is assumed o be indeenden of inflaion rae. 3 The lags are chosen so ha he sysem equaions are free of serial correlaion. Panels A and B conain he resuls of he condiional means and variances for inflaion rae and oil rice change, resecively. Referring o Panel A, he inflaion rae is osiively affeced by he oneeriod lag of oil rice change. In Panel B, oil rice change is osiively affeced by is oneeriod lag. The coefficiens in he wo condiional variance equaions are non-negaive. Boh condiional variance equaions give significan ARCH and GARCH erms (α and β ). The sum of he coefficiens of he ARCH and GARCH erms for inflaion rae is 0.97 whereas he sum of coefficiens for oil rice change is These resuls show ha he GARCH variance series as measures of volailiy or uncerainy is saionary. The consan condiional correlaion in Panel C is 0.262, which is low and saisically significan. 4 The sysem diagnosic es using residual ormaneau es for auocorrelaion acces he null of no auocorrelaion as indicaed by Q(4) saisic. Therefore, he sysem equaions are free of serial correlaion. The volailiy series are generaed so as o examine heir imacs on inflaion and volailiy in he sandard Granger causaliy es. The resuls of airwise Granger causaliy es are reored in Table 5. Table 5 Resuls of airwise Granger causaliy es Hyohesis F-saisic P-value Lag lengh o does no cause 7.45 ***(+) o does no cause h.44 (+) h o does no cause.696 (-) h o does no cause o 2.93** (-) h o does no cause h.690 (-) does no cause h 4.206*** (+) h does no cause 4.76*** (-) Noe: o and o sands for he ercenage raes of change in consumer rice index and nominal oil rice, resecively. The condiional variances, h for inflaion rae and h o for nominal oil rice. ***, ** and * denoes significance a he, 5 and 0 ercen, resecively. The lag lengh in he airwise causaliy es is deermined by AIC. The resuls in Table 5 show ha oil rice change ends o cause he inflaion rae o increase, bu ends o cause is volailiy or uncerainy o decrease. The laer imac is insignifican. In addiion, oil rice volailiy ends o cause he inflaion rae o decrease, bu is no saisically significan. Furhermore, oil rice uncerainy does no cause inflaion uncerainy. Finally, here exis bidirecional causaliy beween inflaion and inflaion uncerainy. I is obvious ha inflaion causes higher inflaion uncerainy while inflaion uncerainy causes inflaion o decline. 4. Discussion Previous sudies find ha oil rice shocks ass hrough domesic inflaion. Furhermore, here is a non-linear adjusmen beween oil rice changes and rice indices. The resen sudy reveals ha domesic oil rice shocks Granger cause domesic inflaion and his resul is 3 The counry is a small oil-imoring counry. Therefore, is inflaion rae should no affec world oil rice. 4 This resul shows ha inflaion and oil rice change are osiively correlaed. 6

8 conradicory o he finding by Huang and Chao (202) who find ha inernaional oil rice lays more imoran role han domesic oil rice on rice indices. Even hough oil rice uncerainy does no affec inflaion, inflaion iself osiive causes inflaion uncerainy, which suors Friedman (977) hyohesis. On he conrary, inflaion uncerainy lowers inflaion rae, which is conradicory o Cukierman and Melzer (986) hyohesis. However, he imac of oil rice shocks on inflaion migh surass he negaive imac of inflaion uncerainy on inflaion. Therefore, he inflaion induced by oil rice shocks should no be ignored by he moneary auhoriies. 5. Concluding Remarks and Policy Imlicaion This sudy invesigaes he imac of oil rice shocks on domesic inflaion in Thailand. Monhly daa from January 993 o December 203 are used. This sudy does no use srucural vecor auoregression or oher mehods ha caure he ass-hrough from oil rice o consumer rice as used in revious sudies. In sead, he mehods used are he bounds esing for coinegraion and he wo-se aroach o deec he imac of oil rice shocks on inflaion and inflaion uncerainy. The main findings are ha oil rice shocks, defined as movemens in oil rice, osiively cause inflaion o increase, bu oil rice uncerainy does no affec inflaion. Furhermore, inflaion iself osiively causes inflaion uncerainy in he Thai economy. The imlicaion based uon he resuls of his sudy is ha besides inflaionargeing ha has been imlemened by he moneary auhoriies, moneary measures should also be designed o accommodae inflaion induced by oil rice shocks. References Bernanke, B. S., Gerler, M. and Wason, M. W., 997. Sysemaic moneary olicy and he effecs of oil rice shocks, Brooking Paers on Economic Aciviy, (), Bollerslev, T., 990. Modelling he coherence in shor-run nominal exchange raes: a mulivariae generalized ARCH model, Review of Economics and Saisics, 73(3), Chen, S. S., Oil rice ass-hrough ino inflaion, Energy Economics, 3(), Chou, K-W. and Lin, P-C., 203. Oil rice shocks and roducer rices in Taiwan: an alicaion of non-linear error-correcion models, Journal of Chinese Economic and Business Sudies, (), Cukierman, A. and Melzer, A., 986. A heory of ambiguiy, credibiliy, and inflaion under discreion and asymmeric informaion, Economerica, 54(5), De Gregono, J. D. and Landerreche, C. N., Anoher ass-hrough bies he dus? oil rices and inflaion, Working Paer, Cenral Bank of Chile. Ewing, B. T. and Thomson, M. A., Dynamic cyclical comovemens of oil rices wih indusrial roducion, consumer rices, unemloymen and sock rices, Energy Policy, 35(), Friedman, M., 977. Inflaion and unemloymen, Journal of Poliical Economy, 85(3), Gao, L., Kim, H. and Saba, R., 204. How do oil rice shocks affec consumer rices, Energy Economics, 45(C), Granger, C. W. J., 969. Invesigaing causal relaions by economeric models and cross secral mehods, Economerica, 37(3),

9 Hamilon, J. D., Wha is an oil shock?, Journal of Economerics, 3(2), Hooker, M. A., Are oil shocks inflaionary? Asymmeric and nonlinear secificaion versus changes in regime, Journal of Money, Credi, and Banking, 34(3), Huang, W-H. and Chao, M-C., 202. The effecs of oil rices on he rice indices in Taiwan: inernaional or domesic oil rices maer?, Energy Economics, 34(), LeBlanc, M., and Chinn, M. D., Do high oil rices resage inflaion?: he evidence from G-5 counries, Business Economics, 39(), Lee, K. and Ni, S., On he dynamic effecs of oil rice shocks: a sudy using indusry level daa, Journal of Moneary Economics, 49(4), Mork, K. A., 989. Oil and he macroeconomy when rices go u and down: an exension of Hamilon resuls, Journal of Poliical Economy, 97(3), Mork, K. A. and Hall, R. E., 980. Energy rices, inflaion, and recession, , Energy Journal, (3), Pagan, A., 984. Economeric Issues in he analysis of regressions wih generaed regressors, Inernaional Economic Review, 25(2), Pesaran, M. H., Shin, Y, Smih, R. J., 200. Bounds esing aroaches o he analysis of level relaionshis, Journal of Alied Economerics, 6(3), Phillis, P. C. B., Perron, P., 988. Tesing for a uni roo in ime series regression, Biomerika, 75(2),