Estimations of the Price Transmission and Market Power in Canola Export Market: Implication to Canola Import of Japan

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1 Paper Tle: Esmaons of he Prce Transmsson and Marke Power n Canola Expor Marke: Implcaon o Canola Impor of Japan Conference: 55h Annual AARES (Ausralan Agrculural and Resource Economcs Socey) Naonal Conference Dae and Place: 8-11 February 2011, Melbourne, Crown Conference Cenre Auhor: Toru Nakajma Ph.D. Suden, Deparmen of Agrculural and Resource Economcs, Graduae School of Agrculural and Lfe Scences, The Unversy of Tokyo Research Fellow of he Japan Socey for he Promoon of Scence (JSPS) E-mal: n.hrough@gmal.com Keywords: asymmerc prce ransmsson, TAR, marke power, dynamc programmng, canola

2 Esmaons of he Prce Transmsson and Marke Power n Canola Expor Marke: Implcaon o Canola Impor of Japan Toru Nakajma * Absrac Ths paper analyzes he prce ransmsson of canola n he nernaonal marke, he marke power of canola exporng counres over Japan, and he relaonshp beween hem. In he esmaon of prce ransmsson, asymmerc prce ransmsson from fuures prces n Wnnpeg o expor prces of Canadan canola mporers was esmaed usng hreshold auoregressve model wh conegraon ess. Sgnfcan asymmery was found n he Canadan canola expor o Japan n such a way ha Canada enjoyed long-lasng excess profs over Japan. Meanwhle, he resuls also showed ha Mexco and he U.S. enjoyed he long-erm excess profs over Canada. In he esmaon of marke power, consderng he exsence of adjusmen process n Canada and Ausrala, lnear-quadrac (LQ) dynamc duopoly model was employed. Accordng o he resuls, * Ph.D. suden, Deparmen of Agrculural and Resource Economcs, Graduae School of Agrculural and Lfe Scences, The Unversy of Tokyo, and research fellow of he Japan Socey for he Promoon of Scence (JSPS). E-mal: n.hrough@gmal.com

3 Canada had more marke power han does Ausrala, he laer of whose marke power s close o compeve level. The mplcaon for Japan s canola mpor s ha Japan should dversfy he orgns of canola or mpor more from such counres ha have less marke power lke Ausrala. Ths paper conrbues n ha emprcally showed he relaonshp beween APT usng TAR model and marke power usng LQ model. Keywords: asymmerc prce ransmsson, TAR, marke power, lnear-quadrac model, canola 1. Inroducon Canola ol consumpon has been he larges among vegeable ols n Japan. Ol made of canola, he low ercc acd rapeseed, s consdered o be a healhy ol and s mos preferred of all vegeable ols n Japan. The annual supply of fas and ols n Japan s roughly 3 mllon ons every year and ha of canola ol s 1 mllon ons. Almos all canola ol s produced n Japan, and almos all canola s mpored. Japan has been he world larges mporer of canola, whose mpored quany s more han 2 mllon ons a year. Japan mpors canola manly from Canada, whose share s nearly 90% on average from 1988 o Japan also mpors canola from Ausrala, bu he share s less han

4 10% on average. Wha s he effec of he heavy dependence of Japan s canola mpor on Canada? And wha sraeges should Japan develop on canola mpor? The purpose of hs sudy s o esmae he asymmerc prce ransmsson (APT) and marke power n he nernaonal canola expor marke, especally focusng on Japan as an mporer. Threshold auoregressve (TAR) model s employed n esmang APT and lnear- quadrac (LQ) model s used o esmae marke power. Comparng he resuls of APT and marke power, he relaon beween APT and marke power s analyzed. Because he relaon has no been shown wh rgorous heorecal underpnnngs (Meyer and von Cramon-Taubadel, 2004), hs paper res o offer some emprcal evdence of. Ths paper s organzed as follows. In secon 2, he concep and he model of APT are explaned, hen he emprcal analyss usng TAR model s conduced. In secon 3, marke power of exporng or mporng counres s esmaed usng LQ model. Fnally, he relaon beween APT and marke power s consdered, hen hs sudy s closed wh some concludng remarks. 2. Asymmerc prce ransmsson 2.1 Overvew

5 APT s a popular research opc, as menoned n he survey paper by Meyer and von Cramon-Taubadel (2004). Prce ransmsson s sad o be asymmerc f he speed of adjusmen of he oupu prce s dfferen afer he npu prce ncreases or decreases. In parcular, APT s posve f he oupu prce adjuss more rapdly when he npu prce ncreases han when decreases. A posve APT means ha he squeezed margn resores more quckly han does he sreched margn. I also ndcaes ha he prce ransmsson has downward rgdy. In conras, negave APT denoes ha he oupu prce adjuss more rapdly when he npu prce decreases han when ncreases. Thus, he sreched margn s resored more quckly han he squeezed margn, and he prce ransmsson has upward rgdy. Followng he mehod of Enders and Granger (1998), many emprcal sudes have been conduced usng a TAR model o esmae APT wh conegraon ess. The coverage of prevous emprcal sudes of APT ha use he TAR model for agrculural producs ncludes he Ghanaan maze marke n Abdula (2000), he Swss pork marke n Abdula (2002), whea expor prces n major whea-producng counres n Ghoshray (2002), he French marne producs n Gonzales e al. (2003), he French vegeable marke n Hassan and Smon (2001), he U.S. dary marke n Awokuse and Wang (2009), he Nepalese rce marke n Sanogo and Amadou (2010), and Indonesan ol

6 palm marke n Nakajma e al. (2010). 2.2 TAR model Below, he TAR model based on Enders and Sklos (2001) s explaned. Denoe p and p o as he npu and oupu prces a me. The long-run relaonshp beween p and p o s represened usng ordnary leas squares (OLS) regresson as follows: p (1) o p where and are parameers, and s he dsurbance erm, whch may be serally correlaed. Accordng o Engle and Granger (1987), f p and p o are par of a non-saonary process and p and o p are par of a saonary process (ha s, f hey are frs-dfference saonary (I(1)) varables), hen Eq. (1) may ndcae a spurous regresson. If he resdual seres ˆ s saonary, however, hen p and p o are sad o be conegraed. Therefore, s necessary o conduc un roo ess and conegraon ess on p and p o o avod a spurous regresson. In a TAR model, a conegraon es s performed usng ˆ from Eq. (1) n he followng equaons (Enders and Sklos, 2001): I I 21 T (2) 1

7 1 f 1 I (3) 0 f 1 where I s he Heavsde ndcaor funcon, and s he super-conssen esmaor of hreshold 1 calculaed followng Chan (1993). s he whe nose dsurbance erm and sasfes he followng condons: E 0 2 2, E, E 0 j j. (4) The necessary and suffcen condon for ˆ o be saonary s as follows (Perucell and Woolford, 1984): 0, 0 1 2, and for any. (5) T s he lag order ha sasfes he condons of Eq. (4) and (5) and mnmzes he BIC (Bayesan nformaon crera). A conegraon es s performed by esng 0 ;.e., f he null 1 2 hypohess of 0 s rejeced, hen p and 1 2 p o are sad o be conegraed. APT can be esed n he same model o compare he absolue values of 1 and 2. If s rejeced and , hen he negave dscrepances from he equlbrum error adjus more rapdly han he posve dscrepances, whch ndcaes posve APT. On he oher hand, f 1 2 s rejeced and 1 2, hen he posve devaons adjus oward he equlbrum error more rapdly han do he negave devaons, whch ndcaes negave APT.

8 There s anoher approach o represen he adjusmen process, ha s, he momenum TAR (M-TAR). The M-TAR model s he same as n Eq. (2) and (3) excep ha 1 n Eq. (3) s replaced wh 1. The TAR model and M-TAR model correspond o he wo asymmerc adjusmen processes, Deepness and Seepness (Schel, 1993). In boh models, however, 1 2 ndcaes posve APT and 1 2 ndcaes negave APT. The model selecon may be based on nformaon crera such as Bayesan nformaon crera (BIC). 2.3 Emprcal resuls Daa The npu prce was hree monh lags of canola fuures prces for he neares conrac monh n he Wnnpeg marke, whch was obaned from Cereals and Olseeds Revew n Sascs Canada. Three monh lags were aken because conracs beween buyers and sellers are generally made n several monhs before he commody clears hrough cusoms n he exporng counry. In he emprcal analyss below, wo and four monh lags were also employed o check he sensvy of he lags. The oupu prces were Canada s canola expor prces o Japan, he U.S. and he sum of counres whou Japan (represened by he res of he world, ROW). The daa were obaned from

9 Canadan Inernaonal Merchandse Trade Daabase n Sascs Canada. Boh daases ncluded monhly daa from January 1988 o December The oal sample sze was 264. The fuures prces and expor prces o Japan were shown n Fg. 1. I seems ha fuures prces of several monh pror correspond o he acual expor prces, whch s conssen wh he descrpon above. The orgnal daa of boh he npu and oupu prces are n Canadan dollar per merc ons. In he TAR esmaons, hese seres were ransformed no naural logarhmc form as s always done n emprcal analyses of TAR models (Ben-Kaaba and Gl, 2007) Un roo ess To es wheher he prce seres are I(1) varables, augmened Dckey-Fuller (ADF) ess were conduced. The resuls are shown n Table 1. The null hypohess ha he seres have a un roo s no rejeced for he level seres, bu s for he frs-dfference seres. Therefore, he prce seres menoned above can be sad o be I(1) varables. The es sascs shown n Table 1 are hose acheved by ncludng nerceps (bu no rends) n he es equaons. Smlar resuls were obaned by ncludng nerceps and rends n he es equaons, whch are no shown here o save space.

10 2.3.3 TAR esmaons The resuls are shown n Table 2. The lag order for each model was deermned by mnmzng he BIC when he condons of Eq. (4) and (5) are sasfed. Based on boh he TAR model and he M-TAR model, I can conclude ha he fuures prces and expor prces o each counry are conegraed because he sascs n each model are much larger han hose a he crcal 1% sgnfcance level n Enders and Sklos (2001). Accordng o ha paper, he sascs a a 1% sgnfcance level for 250 observaons and four lagged changes are for TAR and 8.47 for M-TAR. As shown n Enders and Sklos (2001), he sasc ends o decrease as he number of observaon ncreases, and ends o ncrease as he number of lags ncreases. Therefore, s reasonable o conclude ha he null of no conegraon s rejeced a he 1% level n each model. In fac, he sascs obaned n hs paper are far beyond he values shown above. Regardng he resuls for Japan, alhough he null hypohess ha 1 2 s no rejeced a he 10% level based on he TAR model, he null s rejeced a he 1% level based on he M-TAR model, and 1 2. I follows ha prce ransmsson from Canadan canola prces o expor prces for Japan s symmerc n he TAR model and ha here s posve APT n he M-TAR model. Based on he BICs, he value s

11 lower n M-TAR han ha n TAR model. Hence, he concluson may be ha Canada enjoys long-sandng excess profs n erms of prce ransmsson over Japan by exporng canola, ha s, ncreased margn s resored more slowly han s decreased margn. I mples ha Canada has more power o deermne he expor prces o Japan. However, s no analyzed ha Canada has marke power over Japan usng TAR model. Therefore, marke power esmaons are conduced n he nex secon. Regardng he resuls for ROW, he null hypohess ha 1 2 s no rejeced a he 10% level based on he TAR model, bu s rejeced a e 5% level based on he M-TAR model, and 1 2, whch means negave APT. Accordng o he BICs, M-TAR model s preferred and he concluson may be ha mporng counres oher han Japan enjoys long-lasng excess profs n erms of prce ransmsson over Canada. The mplcaon s ha mporng counres oher han Japan has more power o deermne canola prces han does Canada. The resuls for he U.S., whch s he represenave counry n ROW, shows ha he null s rejeced a he 1% level based on boh he TAR and M-TAR model. Negave APT 1 2 was found sgnfcanly, and he resuls are conssen wh ha of ROW. To check sensvy of choosng lags n fuures prces, TAR esmaons usng fuures prces wh wo and four lags were also conduced. Alhough he parameer

12 values changed slghly, he concluson of he sgnfcance of APT was oally he same as hose wh hree lags. 3. Marke power 3.1 Movaon As marke power s defned by prce-cos margn, he exsence of APT do no necessarly mean he exsence of marke power, alhough he relaon was referred n leraure. Hence, hs paper s movaed by nvesgang he relaon. Perloff e al. (2007) surveyed varous mehodology of esmang marke power. There are wo assumpons regardng he games ha frms play, ha s, sac and dynamc. In a sequence of sac games, each frm maxmzes s curren prof gven s belef abou rvals behavor and he assumpon ha acons n oher perods do no affec behavor n hs perod. Meanwhle, n a dynamc game, each frm maxmzes s expeced presen dscouned value of he sream of s fuure profs. Consderng he possbly of dynamc aspec of Canada and Ausrala n canola expors o Japan, hs paper employed he dynamc model o esmae marke powers of he exporers. Prevous sudes of esmang marke power wh dynamc model focused on he use of LQ model because offers closed-form soluons n a dynamc problem.

13 Such sudes nclude Karp and Perloff (1989), Karp and Perloff (1993), and Deodhar and Sheldon (1996) for ndusry level approach, and Chall (2009) for frm level approach. The models employed are he same, whch s explaned n he nex subsecon. There are wo ypes of dynamc sraeges, ha s, open-loop and Markov perfec (Perloff e al., 2007). Wh open-loop sraeges, frms beleve ha her rvals sraeges do no depend on sae varables, such as a level of capal or a sock of loyal cusomers, ha affecs rval s fuure acons. On he oher hand, wh Markov sraeges, frms undersand ha her curren acons affec he sae varables. Frms ake her rvals sraeges as gven and undersand ha by alerng he sae varables hey can affec rvals fuure acons. The open-loop equlbrum (OLE) can be obaned by solvng a one-agen opmal conrol problem, whle he Markov perfec equlbrum (MPE) requres he soluon o a game. 3.2 Lnear-quadrac dynamc model Assume ha Japan mpors canola from Canada and Ausrala, and Canadan canola and Ausralan canola are close subsues. Japan s nverse lnear demand funcon s wren as:

14 2 p a b q, (6) j1 j j where p ndcaes real mpor prce of Japan from counry ( 1, 2, whch ndcae Canada and Ausrala, respecvely) n perod, q j ndcaes mpor quany of Japan from counry j ( j 1, 2, whch ndcae Canada and Ausrala, respecvely), and a and b j are parameers. Each counry has consan margnal coss c wh respec o conemporaneous expors q. The change n oupu from one perod o he nex s defned as: u, (7) q q where s he duraon of a perod, whch s assumed o be 1 n hs paper. Then he cos of changng oupu s quadrac n he rae of change: u 2u 0. (8) 0 0 n hs paper, whch s generally assumed n leraure. Adjusmen coss are assumed o be posve whenever he change n he sae varable s non-zero. For dynamc problems, s necessary ha 0, whle 0 means he problem s sac. In perod, counry wans o maxmze s expecaon of he presen dscouned value of profs mnus adjusmen coss: u p c q u 1 E 0 1 2, (9) where s a dscoun facor, whch s assumed o be known. Hence, value funcon s

15 wren as: V 1 u q p c q u 2 max 0 u 1 s.. q, 1 q u, 1., (10) Here q s a sae varable and u s a conrol varable. Then, he Bellman equaon s wren as: u V q p c q u V q~ 0, (11) 2 u q q. (12), 1 where q ~ q, 1. (11) s wren n marx noaon as: E 1 1 e q u q u K q u us u , (13) where e s a column vecor of zeroes wh a one n he h poson, e s an n -dmensonal column vecor conssng enrely of ones, K s an n n marx of zeroes wh b s on he h column and he h row, excep for he, elemen, whch conans 2 b, and S s an n n marx conssng of zeroes excep for he, elemen, whch conans. conans a and c, and β x and x, 1 Φx, where x are exogenous varables and s an..d. random varable wh zero mean. (12) s also wren n marx noaon as: q g Gq, (14) 1 for some g and G.

16 3.3 Esmaon mehod In an emprcal analyss, he demand equaons (6) and he adjusmen equaons (14) are o be esmaed. Then G and he demand slope paramees b ha conss of K are derved. Gven, and usng b and K, marke power parameers and adjusmen parameers can be calculaed. The frs-order condon for prof maxmzaon s solved usng Eq. (13) and (14). However, he soluons are dfferen accordng o he sraeges menoned above. The soluons for OLE and MPE are shown as follows Soluon for OLE Gven a value of, he frs-order condon correspondng o (13) and (14) s: K v 1 G I GI G e y, (15) where v s an n dmensonal column vecor wh one n he h poson and v j elsewhere. v j q q (, j 1,2, j ) ndcaes counry s conjecures for he j oupus of he rval. Usng esmaed G and demand slope paramees b ha conss of K, each frm s conjecural varaon s solved as follows: v v 12 y11 y12 2b11 b12, 21 y22 y21 2b22 b21. (16)

17 are also solved as follows:, 1 b12 y12. 2 b21 y21 (17) For he esmaed dynamc sysem o make sense, mus have properes as follows. Frs, he dynamc sysem of conrol s asympocally sable f he absolue egenvalues of marx G are less han one. Second, he adjusmen parameer n each of he models s posve (dynamc propery): Soluon for MPE To esmae v and n he MPE case, defne he vecors w 1 I G G G Gvec, (18) K z 1 I G G G G I G G I Ivec e e, (19) where s Kronecker produc and vec operaor sacks he columns of he marx. The nverse vec operaon s hen used o remarcze w and z o oban he 2 2 marces W and Z. In MPE, he necessary condon correspondng o (13) and (14) s: 1 * K W e e Z v G e y, (20)

18 3.4 Emprcal resuls Daa p and q are Japan s mpor un prces and quany of canola (low erucc acd rapeseed), respecvely, from Canada and Ausrala. The daa are obaned from Trade Sascs of Japan, Mnsry of Fnance. In he demand equaons, he popuolaon of Japan s ncluded as an exogenous demand shfer. Tme rend and a dummy varable are also ndluded, he laer of whch s one n he years 2007 and 2008 when he canola prces were much hgher han oher years. The prce daa were deflaed usng Japan s CPI (2005=100), whch s obaned from IMF-IFS (Inernaonal Fnancal Sascs). These daa are annual seres from 1992 o The sarng year was seleced as 1992 because canola mpors from Ausrala o Japan was very few before 1992 (less han 100 ons) and he un values were very expensve Resuls Frs, he lnear demand sysem of Eq. (6) wh he exogenous varables were esmaed usng Zellner s seemngly uncorrelaed regressons (SUR). The resul s shown n Table 3. Nex, he adjusmen equaons (Eq. (14)) wh rend and he dummy varable were esmaed usng SUR. The resul s shown n Table 4.

19 For he esmaed dynamc sysem o make sense, mus have hree properes: () sable sysem propery: G G 2 and G G G G 1, () marke power ndex: 1 v 1, j () adjusmen parameer: 0. Chall (2009) showed he sably condon () n he case of wo frm model, whch s he same as hs sudy. () ndcaes ha he marke srucure les beween colluson and prce akng. If v 1, frm has no marke power, whch means ha he frm s j prce aker. On he oher hand, f v 1, frm has a monopolsc power. And f j 1 v 1, he frm has an nermedae level of marke power. j Imposng hese properes usng a classcal approach s analyzed o be exremely dffcul, f no possble (Karp and Perloff, 1993). Raher han esmang he unconsraned sysem and hopng ha he pon esmaes le n he desred range, prevous sudes employed Bayesan echnques o mpose he resrcons. The mehodology used here s he same as he prevous sudes, where Mone Carlo numercal negraon wh mporance samplng s employed. The resul of he Bayesan esmaons of he parameers usng 100,000 random sample are shown n Table 5. The resul ndcaes ha v j for Canada s hgher han ha of Ausrala boh n OLE and MPE, whch mples ha Canada has more marke power

20 han does Ausrala. 4. Concluson The emprcal resuls of APT and marke power lead us o he concluson ha Canada has marke power over Japan n exporng canola, and ha prce ransmsson from Canadan canola domesc prces o expor prces o Japan s asymmerc so ha he excess margn of Canada s no resored o he equlbrum level more quckly han s s excess loss. I follows from hs fndng ha possesson of marke powr s conssen wh posve APT. On he oher hand, Ausrala, whose share n Japan s canola mpors has been one nneh of Canada, does no have marke power over Japan. The mplcaon of hs s ha s reasonable for Japan o mpor more canola from Ausrala, or o dversfy he orgns. The conrbuons of hs paper nclude ha APT from Canadan canola domesc prces o expor prces were esmaed usng TAR model, ha marke powers of Canada and Ausrala were esmaed usng LQ model, and ha gave an emprcal evdence ha posve APT s relevan o he exsence of marke power. A furher drecon of hs sudy wll be o consruc such a way ha prce ransmsson and marke

21 power are jonly esmaed. In addon, furher research on heorecal connecon of hem wll be needed. References Abdula, A. (2000). Spaal Prce Transmsson and Asymmery n he Ghanaan Maze Marke, Journal of Developmen Economcs 63, Abdula, A. (2002). Usng Threshold Conegraon o Esmae Asymmerc Prce Transmsson n he Swss Pork Marke, Appled Economcs 34, Awokuse, T.O. and Wang, X. (2009). Threshold Effecs and Asymmerc Prce Adjusmens n U.S. Dary Markes, Canadan Journal of Agrculural Economcs 57, Ben-Kaaba, M. and Gl, J.M. (2007). Asymmerc Prce Transmsson n he Spansh Lamb Secor, European Revew of Agrculural Economcs 34, Chall, D. (2009). Marke Power: Emprcal Analyss n he Indonesan Crude Palm Ol Indusry. VDM Verlag Dr. Muller Akengesellschaf & Co. KG. Chan, K.S. (1993). Conssency and Lmng Dsrbuon of he Leas Squares Esmaor of a Threshold Auoregressve Model, Annals of Sascs 21,

22 Deodhar, S.Y. and Sheldon, I.M. (1996). Esmaon of Imperfec Compeon n Food Markeng: A Dynamc Analyss of he German Banana Marke, Journal of Food Dsrbuon Research 27, Enders, W. and Granger, C.W.J. (1998). Un-Roo Tess and Asymmerc Adjusmen Wh an Example Usng he Term Srucure of Ineres Raes, Journal of Busness & Economc Sascs 16, Enders, W. and Sklos, P.L. (2001). Conegraon and Threshold Adjusmen, Journal of Busness & Economc Sascs 19, Engle, R.F. and Granger, C.W.J. (1987). Co-Inegraon and Error Correcon: Represenaon, Esmaon, and Tesng, Economerca 55, Ghoshray, A. (2002). Asymmerc Prce Adjusmen and he World Whea Marke. Journal of Agrculural Economcs 53, Gonzales, F., Gulloreau, P., Le Grel, L., and Smon, M. (2003). Asymmerc Prce Transmsson wh Conssen Threshold along he Fsh Supply Chan, INRA Workng Paper Hassan, D. and Smon, M. (2001). Prce Lnkage and Transmsson beween Shppers and Realers In he French Fresh Vegeable Channel, INRA Workng Paper

23 Karp, L.S. and Perloff, J.M. (1989). Dynamc Olgopoly n he Rce Expor Marke, The Revew of Economcs and Sascs 71, Karp, L.S. and Perloff, J.M. (1993). A Dynamc Model of Olgopoly n he Coffee Expor Marke, Amercan Journal of Agrculural Economcs 75, Meyer, J. and von Cramon-Taubadel, S. (2004). Asymmerc Prce Transmsson: A Survey, Journal of Agrculural Economcs 55, Nakajma, T., Masuda, H., and Rfn, A. (2010). The Srucural Change n he Supply Chan of Ol Palm: A Case of Norh Sumara Provnce, Indonesa, Proceedngs of he 116h Semnar of European Assocaon of Agrculural Economss, Oc 2010, Unversy of Parma, Ialy. Perloff, J.M., Karp, L.S., and Golan, A. (2007) Esmang Marke Power and Sraeges. Cambrdge. Perucell, J. and Woolford, S. (1984). A hreshold AR(1) model, Journal of Appled Probably 21, Sanogo, I. and Amadou, M.M. (2010). Rce marke negraon and food secury n Nepal: The role of cross-border rade wh Inda, Food Polcy 35, Schel, D. (1993). Busness Cycle Asymmery: A Deeper Look, Economc Inqury 31,

24 Acknowledgemens I would lke o hank Professor Masayosh Honma, Dr. Kasuhro Sao, Dr. Hroaka Masuda, and parcpans of semnar classes a he Unversy of Tokyo for commens and suggesons. Ths research s a par of projec The Economc Research Regardng he Measures for Securng a Sable Food Impor of he Polcy Research Insue, Mnsry of Agrculure, Foresry and Fsheres, Japan.

25 Tables Table 1 Un roo es resuls ADF Fuures Prce level (1) * 1s dff (0) *** Expors o Japan level (1) 1s dff (0) *** Expors o he U.S. level (10) 1s dff (9) *** Expors o ROW level (10) 1s dff (7) *** Noe: 1. Values are sascs for ADF es. 2. Values n parenheses ndcae lag order based on he Akake Informaon Crera (AIC). 3. In he equaons for all ess, he nercep (no rend) s ncluded. 4. ***, **, and * represen 1%, 5%, and 10% sgnfcance, respecvely.

26 Table 2 TAR esmaon resuls Model 1 2 lags Asym. Q(6) BIC Japan TAR -0.25*** -0.39*** 17.22*** (0.07) (0.08) [0.14] [0.58] 2nd Japan M-TAR -0.24*** -0.56*** 20.34*** 7.75*** (0.06) (0.11) [0.01]+ [0.64] 2nd ROW TAR -0.78*** -0.65*** 32.44*** (0.12) (0.10) [0.32] [0.15] 3rd 0.12 ROW M-TAR -0.93*** -0.64*** 34.63*** 4.46** (0.14) (0.09) [0.04]- [0.13] 3rd 0.13 U.S. M-TAR -0.76*** -0.39*** 70.60*** 8.73*** (0.07) (0.11) [0.00]- [0.93] 1s 0.13 U.S. M-TAR -0.78*** -0.43*** 70.40*** 8.46*** (0.07) (0.10) [0.00]- [0.95] 1s 0.15 Noes: 1. 1 and 2 are he adjusmen coeffcens n Eq. (2). 2. lags s he lag lengh n (2). 3. s he F sasc for he es of he null hypohess 0. The rejecon 1 2

27 regons are based on Enders and Sklos (2001). 4. Asym. s he F sasc for he es and - ndcae sgnfcan posve and negave APT, respecvely. 5. Q(6) represens he Q sascs from he Pormaneau es for whe nose, whose null hypohess s ha he error erm s whe nose up o 6 lags. 6. In BIC, 1s, 2nd, 3rd ndcae ha he value are he 1s, 2nd, 3rd smalles, respecvely. 7. s he hreshold n (3). 8. For each resul, he values n ( ) denoe sandard errors, and he values n [ ] denoe p values. 9. ***, **, and * represen 1%, 5%, and 10% sgnfcance, respecvely.

28 Table 3 Resuls of he demand equaons Prce of Canada Prce of Ausrala Impors from Canada (0.0099) (0.0108) Impors from Ausrala (0.0182) (0.0198) Populaon of Japan (6.4971) (7.0638) Tme rend ( ) * (1173.4) 2007 and 2008 dummy *** (5278.0) *** (5738.4) Consan (810201) Nunber of observaons R Durbn-Wason sasc Noes: 1. Values n parenheses denoe sandard errors. 2. ***, **, and * represen 1%, 5%, and 10% sgnfcance, respecvely.

29 Table 4 Resuls of he adjusmen equaons Impors from Canada Impors from Ausrala Impors from Canada (1 lag) (0.2485) (0.1981) Impors from Ausrala (1 lag) (0.2656) ** (0.2118) Tme rend * ( ) (9496.7) 2007 and 2008 dummy ( ) * ( ) Consan *** ( ) Nunber of observaons R Durbn-Wason sasc Noes: 1. Values n parenheses denoe sandard errors. 2. ***, **, and * represen 1%, 5%, and 10% sgnfcance, respecvely.

30 Table 5 Resuls of marke power and adjusmen parameers Sraegy v 12 v OLE MPE Noes: 1. The parameers are calculaed usng he mehodology menoned above wh 100,000 Mone Carlo replcaon.

31 Can$/on Fgure 1 Fuures prces and expor prces o Japan '88.1 '92.1 '96.1 '00.1 '04.1 '08.1 Fuures Japan Source: Cereals and Olseeds Revew and Canadan Inernaonal Merchandse Trade Daabase (Sascs Canada).