RUHR. Long-run Trends or Short-run Fluctuations What Establishes the Correlation between Oil and Food Prices? ECONOMIC PAPERS #357

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1 RUHR ECONOMIC PAPERS Karoline Kräschell Torsen Schmid Long-run Trends or Shor-run Flucuaions Wha Esablishes he Correlaion beween Oil and Food Prices? #357

2 Imprin Ruhr Economic Papers Published by Ruhr-Universiä Bochum (RUB), Deparmen of Economics Universiässr. 15, 1 Bochum, Germany Technische Universiä Dormund, Deparmen of Economic and Social Sciences Vogelpohsweg 7, 227 Dormund, Germany Universiä Duisburg-Essen, Deparmen of Economics Universiässr., 5117 Essen, Germany Rheinisch-Wesfälisches Insiu für Wirschafsforschung (RWI) Hohenzollernsr. 1-3, 5 Essen, Germany Ediors Prof. Dr. Thomas K. Bauer RUB, Deparmen of Economics, Empirical Economics Phone: +9 () 23/ , homas.bauer@rub.de Prof. Dr. Wolfgang Leininger Technische Universiä Dormund, Deparmen of Economic and Social Sciences Economics Microeconomics Phone: +9 () 231/ , W.Leininger@wiso.uni-dormund.de Prof. Dr. Volker Clausen Universiy of Duisburg-Essen, Deparmen of Economics Inernaional Economics Phone: +9 () 21/ , vclausen@vwl.uni-due.de Prof. Dr. Chrisoph M. Schmid RWI, Phone: +9 () 21/ , chrisoph.schmid@rwi-essen.de Ediorial Offi ce Joachim Schmid RWI, Phone: +9 () 21/ , joachim.schmid@rwi-essen.de Ruhr Economic Papers #357 Responsible Edior: Chrisoph M. Schmid All righs reserved. Bochum, Dormund, Duisburg, Essen, Germany, 2 ISSN (online) ISBN The working papers published in he Series consiue work in progress circulaed o simulae discussion and criical commens. Views expressed represen exclusively he auhors own opinions and do no necessarily reflec hose of he ediors.

3 Ruhr Economic Papers #357 Karoline Kräschell and Torsen Schmid Long-run Trends or Shor-run Flucuaions Wha Esablishes he Correlaion beween Oil and Food Prices?

4 Bibliografische Informaionen der Deuschen Naionalbibliohek Die Deusche Bibliohek verzeichne diese Publikaion in der deuschen Naionalbibliografie; deailliere bibliografische Daen sind im Inerne über: hp://dnb.d-nb.de abrufbar. hp://dx.doi.org/1.19/6711 ISSN (online) ISBN

5 Karoline Kräschell and Torsen Schmid 1 Long-run Trends or Shor-run Flucuaions Wha Esablishes he Correlaion beween Oil and Food Prices? Absrac In his paper we use he frequency domain Granger causaliy es of Breiung/Candelon (26) o analyse shor and long-run causaliy beween energy prices and prices of food commodiies. We find ha he oil price Granger causes all he considered food prices. However, when conrolling for business cycle flucuaions his link exiss especially a low frequencies. Thus, shor-run phenomena like herd behaviour and speculaion do no seem o have a considerable effec on he sudied food prices. The relaion beween oil and food prices is raher esablished by long-erm developmens. A possible explanaion for his could be he producion of biofuel. JEL Classificaion: C32, E3 Keywords: Granger causaliy; specral analysis; commodiy prices July 2 1 Karoline Kräschell, RWI and Ruhr-Universiä Bochum; Torsen Schmid, RWI. We hank Chrisoph M. Schmid for valuable commens and suggesions. All correspondence o Karoline Kräschell, RWI, Hohenzollernsr. 1-3, 5 Essen, Germany, karoline.kraeschell@rwiessen.de.

6 1. Inroducion Rising food prices have gained much aenion in he public debae. Increasing demand for food commodiies from emerging economies and he increasing imporance of food commodiies for biofuel producion are ofen seen as he main facors behind he recen surge in food prices (Headey/Fan 2). I is well documened in he lieraure ha a srong correlaion beween food prices and energy prices exiss (e.g. Unied Naions Conference on Trade and Developmen 29). Clearly, if biofuel became a noiceable subsiue for peroleum boh prices should move ogeher (Figure 1). Anoher reason for his correlaion migh be he imporance of chemical and peroleum derived inpus in agriculural producion (Harri e al. 29). In boh cases oil and food prices should move ogeher over longer periods. Bu if his correlaion refleced one of hese fundamenal reasons, i should dissipae, when he developmen of macroeconomic growh is aken ino accoun. In conras, Pindyck/Roemberg (199) find ha he link holds even afer conrolling for changes in economic aciviy. They argue ha his co-movemen exceeds he degree ha can be explained by common macroeconomic facors. Alhough hey did no disinguish beween shor- and long-erm causaliy in heir analyical approach, hey concluded ha his excess comovemen was driven by herd behaviour. This view was challenged by recen empirical sudies (Lescaroux 29, Vanseenkise 29), hough, ha do no find srong evidence for he excess co-movemen hypohesis saed by Pindyck and Roemberg.

7 Figure 1: Oil and food prices from 1991 o Food (lef scale) Oil (righ scale) Source: IMF primary commodiy prices daabase. None of he numerous oher papers relaed o he link beween energy prices and he prices of oher commodiies has ye aemped o disenangle shor-, medium- and long-run effecs in a join approach. In his paper we analyze he link beween crude oil and food commodiy prices more closely by using he frequency domain Granger causaliy approach (Breiung/Candelon 26; Lemmens e al. 2). This esing procedure allows new insighs because ess are performed for paricular frequencies. Hence, i is possible o see direcly wheher he link resuls from long-run rends, business cycles or shor-run dynamics. 1 To provide our conclusions wih a more solid empirical basis, we use a wide range of food commodiies and heir prices as our daa series. Absracing from he issue of frequency, our resuls are in line wih findings of oher sudies. We find for all food prices considered ha hey are Granger caused by oil prices. Thus, he oil price seems o be a good indicaor o predic he prices of oher commodiies. 1 A growing number of sudies (e.g. Assenmacher-Wesche, Gerlach 2; Gronwald 29; Croux, Reusens 211) show he usefulness of hese ess. 5

8 However, our resuls reveal some imporan differences wih respec o he frequencies involved. In he bivariae VAR he oil price Granger causes he overall food index wih a lag of abou 6 monh. In addiion, if we conrol for global indusrial producion i becomes visible ha he link is much sronger a longer cycles. The resuls are similar for soybean oil and maize. In he case of barley and sugar we find ha conrolling for indusrial producion also removes a link a higher frequency bu he ess remain significan for longer cycles. For rice, sunflower oil and palm oil he ess became insignifican if we conrol for economic aciviy. Thus, by and large, we do no need o discuss speculaion as a source of excess co-movemen, because a he relevan frequencies here does no seem o be such excess for mos of he considered food commodiies. The paper is organized as follows. Secion wo gives an overview on he relevan lieraure. Secion hree ses ou he esing procedure. Secion four presens he empirical resuls and secion five concludes. 2. Lieraure Review The empirical lieraure pays much aenion o he link beween energy prices and he prices of oher, especially food commodiies. Generally one can disinguish diverse reasons for he co-movemen of commodiies ha correspond o differen ime periods. In he shor run, herd behaviour and shor-erm speculaion can explain why he prices of commodiies oscillae ogeher. Herd behaviour refers o he phenomenon when invesors are eiher opimisic or pessimisic on all commodiies (Pindyck/Roemberg 199). Thus, an increase in e.g. he price of crude oil would lead o an increase in he prices of oher commodiies jus because raders would expec hem o rise as well and herefore would have a higher demand for hese commodiies. Shor-erm speculaion may lead o an excess co-movemen beween energy and food commodiies because invesors allocae funds o commodiy indexes raher han o specific commodiies (UN 29; Silvennoinen/Thorp 21). Thus, an (expeced) increase in he oil price could lead o higher invesmens in commodiy indexes and herefore resul in an increase in he prices of oher commodiies, oo, alhough heir fundamenals may have sayed he same. 6

9 In he medium run common macroeconomic shocks can explain why differen commodiy prices end o move ogeher. Increasing demand from emerging markes and higher oil and ferilizer prices are ofen seen as main facors driving his co-movemen (Vanseenkise 29, Harri e al. 29). Long-run facors like economic developmen may also inensify he comovemen of oil and food commodiy prices. In wha follows we do no disinguish mediumand long-run co-movemen because in boh cases i is driven by macroeconomic fundamenals. Many empirical sudies refer o he excess co-movemen hypohesis saed by Pindyck and Roemberg (199) and analyse wheher he co-movemen arises from common macroeconomic shocks aribuing or is due o herd behaviour or speculaion. On a daabase ha includes various non-energy commodiies, Baffes (27, 21) shows ha especially food commodiies end o move ogeher wih he oil price even afer conrolling for macroeconomic variables. He uses OLS regressions o esimae he pass-hrough of changes in he oil price o he prices of oher commodiies. This approach does no address any causaliy a low frequencies, hough. In paricular, for he recen economic crisis here is some evidence ha he co-movemen beween oil and food commodiy prices increased due o financial invesmens (UN 29; Silvennoinen/Thorp 21). Lescaroux (29) uses a marke-oriened approach o idenify common macroeconomic shocks by aking he role of invenories ino accoun. He argues ha macroeconomic shocks affec he invenory levels of commodiies, he cos of sorage and hrough his channel also he prices of commodiies. Afer conrolling for changes in invenory levels Lescaroux does no find srong evidence for excess co-movemen. Vanseenkise (29) derives similar resuls using a dynamic facor model, finding ha various common macroeconomic facors cause he prices of he commodiies o oscillae ogeher. As a consequence of heir analyical approaches, all hese papers provide imporan insighs ino he co-movemen beween differen commodiy prices in he shor and medium run. Ye hey do no ake he long run ino accoun. In he long run he producion of biofuel can be an explanaion for he co-movemen especially beween he prices of energy and food 7

10 commodiies (Arshad/Hameed 29), and he curren sae of he economic cycle migh arguably be quie irrelevan. Wih he rising imporance of biofuel producion he agriculural and energy markes became more conneced and prices should indeed move ogeher over longer periods. However, Cashin/McDermo (22) find ha many commodiy prices exhibi small rends and big variabiliy a business cycle frequencies suggesing ha he link beween oil and food prices should be sronges a his frequencies. This is evidence agains he hypohesis ha long-run economic developmens are imporan for his co-movemen. Some oher empirical sudies ry o filer ou he long-run componen using he VAR framework o perform Granger causaliy ess. Coinegraed VAR models allow disinguishing shor- and long-run comovemen. Arshad/Hameed (29) and Harri e al. (29) show ha here is a link beween he oil price and he prices of oher commodiies in he long-run. However, Harri e al. (29) do no find evidence for such a link in he case of whea. Saghainan s (21) resuls are mixed, he can deec a long-run price relaion beween oil and agriculural commodiies only for some of he considered commodiies. In conras, Zhang e al. (21) do no find evidence for a co-movemen beween he prices of oil and agriculural commodiies a all. While hese co-inegraed VAR models give some informaion abou he sources of he co-movemen, hey provide no clear definiion of shor-run and long-run. In paricular wha is mean by longrun in each specific model depends on he characerisics of he unobserved sochasic rend. In conras, he frequency domain Granger causaliy es of Breiung/Candelon (26) offers an inuiive inerpreaion of shor- and long-run co-movemen because i provides he lengh of he cycle for each es-saisic. 3. Tesing procedure Mos empirical resuls on he link beween oil and food commodiy prices are generaed using Granger Causaliy ess in he ime domain. Therefore, we presen resuls of his es as a saring poin of our analysis. This allows us o compare our resuls direcly wih he findings of oher sudies.

11 A variable Y is said o Granger cause X, if Y conains informaion o predic X ha is no available oherwise (e.g. Lükepohl 25: 1pp.). The idea of esing for Granger causaliy in he ime domain can be easily illusraed in he following VAR model of order p. X Y = 11,1X θ11, p X p + θ,1y θ, py p θ (1) = 21,1X θ21, p X p + θ22,1y θ22, py p θ (2) Using he lag operaor (L) his model can be wrien in marix noaion as Θ ( L) X θ11 = Y θ21 ( L) θ( L) X = ε ( L) θ ( L) Y 22 (3) where Θ p ( L ) = I Θ L... Θ L 1 p is he lag polynomial and Θ k are 2 2 coefficien maricies. Under cerain condiions Y does no Granger cause ha pas values of Y are no relaed o coefficiens X if ( ) Θ L, which means = X. This can be esed by using an F-Tes for he Θ, i for i = 1,, p. Due o he fac ha Granger causaliy ess in mos cases are based on one period ahead predicions i is no well suied o disinguish shor and long run effecs. 2 To ge a more precise picure of he shor- and long-run effecs we use a frequency domain Granger causaliy es (Ding e al. 26). Geweke (192) argue ha in mos empirical relevan cases i is possible o perform he causaliy es a differen frequencies wihou loss of explanaory power, which means ha his measure of causaliy ( ) follows π Y X F = 1 Y X f π ( ω) dω F can be decomposed as. () Several proposals have been made o consruc such ess in he frequency domain (Geweke 192; Hosoya 1991; Breiung, Candelon 26; Lemmens e al. 2). In wha follows we use he es proposed by Breiung/Candelon (26). They consruc an F-es for he coefficiens Y X 2 Dufour e al. (26) propose an approach o disinguish shor and long-run causaliy based on several period ahead predicions. 9

12 ( L) Θ a differen frequencies by imposing an addiional resricion. To ge an idea where his resricion comes from we wrie sysem (3) in he following moving average represenaion Ψ ( L) ( L) Ψ( L) η1 ( ) ( ) L Ψ22 L η 2 Ψ11 η = (5) Ψ21 where Ψ( ) = [ Θ( L) G] 1 GG ' L and G is he lower riangular marix of he Cholesky decomposiion 1 =Σ such ha Gε following specral densiy of 1 iω 2 iω ( ω) Ψ ( e ) + Ψ ( e ) = η and E( ηη ) = I. Fourier ransforming his sysem we ge he { } 2 11 X which consiss of wo pars f X =. (6) 2π The firs elemen in equaion (6) which is relaed o he auoregressive coefficiens of equaion (1) is called he inrinsic erm (Barne, Seh 211). The second elemen is relaed o he exogenous variable in equaion (1) and is called he causal erm of he specrum. Breiung/Candelon (26) use his causal elemen Ψ ( e iω ) o consruc heir frequency domain Granger causaliy es. Due o he fac ha ( L) ( L) 22 g Θ ( L) = (7) Θ Ψ where 22 g is he lower diagonal elemen of coefficiens a each frequency by ransforming ( L) I follows from De Moivre s heorem (Hamilon 199) ha p p iω ( e ) = θ, k cos( kω) θ, k ( kω) Θ sin k= 1 Therefore, Θ ( e iω ) p k= 1 and = ( kω) k= 1 implies ha 1 1 G i is possible consruc a es on he Θ ino he frequency domain: ( e iω ) Θ. i. () θ, cos = (9) k

13 p k= 1 ( kω) θ, sin =. (1) k The null hypohesis of no Granger Causaliy a frequency ω can be esed by using a sandard F-es on a se of coefficiens of equaion (1). ( ) Θ ( L) H ω (11) : R = wih R ( ω) cos = sin ( ω) cos( 2ω ) ( ω) sin( 2ω ) cos sin ( pω) ( ) pω This es has an F(2, T-2p) disribuion. I can also easily be applied o VAR models wih more han wo variables. A crucial sep in his esing procedure is o deermine he lag order of he VAR because i deermines he dynamic srucure of he model (Lemmens e al. 2). To ge sufficien dynamic srucure in he model o perform he frequency decomposiion i is necessary o include a leas hree lags in he VAR. 3 (). Empirical Resuls To perform he Granger causaliy ess we firs esimae bivariae and rivariae VAR models for oil prices, several food price indices, one a a ime, and indusrial producion as a measure for global economic aciviy. For oil and food prices we use monhly commodiy price indices from he IMF primary commodiy prices daabase. The sudied commodiies are crude oil (US-Dollar per barrel), he overall food index, soybean oil (US-Dollar per meric on), maize (US-Dollar per meric on), barley (US-Dollar per meric on), EU sugar (US cens per pound), rice (US-Dollar per meric on), sunflower oil (US-Dollar per meric on) and palm oil (US-Dollar per meric on). The sample depends on he daa availabiliy. In mos cases i ranges from January 19 o April 211. For he overall food index and EU sugar we use daa from January 1991 o April 211. In addiion, we use indusrial producion daa from he Inernaional Financial Saisics daabase of he IMF. We seasonally adjus hese daa before using hem in he esing procedure. To deermine he lag lengh we use he LR crierion. 3 We are graeful o Jörg Breiung for his hin. The GAUSS code can be downloaded from Jörg Breiung s homepage. 11

14 Before using he frequency domain Granger causaliy es of Breiung/Candelon (26) we perform simple Granger causaliy ess o gain firs insighs ino he effec of he oil price on he prices of he oher commodiies. The ess are performed for bivariae and rivariae VAR models in levels and firs differences. The resuls are shown in Table 1. Table 1: Granger Causaliy Tess (Oil Food) Bivariae Bivariae Trivariae Trivariae Level 1s differences Level 1s differences Food Index ** 1.9 Barley.57* Maize.37*** Palm Oil.79** ** 19.5 Rice Soybean Oil 13.3*.76* Sugar EU.*** 17.3*** 19.* 19.2** Sunflower Oil 1.76* * chi-square values, * significan a 1% level, **significan a 5% level, *** significan a 1% level. As can be seen in Table 1, he oil price Granger causes more of he considered commodiies in he models in levels compared o hose in firs difference. This implies ha rends play a role in generaing he co-movemen beween he oil price and he prices of he considered commodiies. However, he Granger causaliy ess for hese models do no provide clear evidence wheher he co-movemen is due o shor-run flucuaions e.g. caused by herd behavior/shor-erm speculaion or longer cycles no capured by indusrial producion. In some cases he ess become insignifican (barley, maize and soybean oil) or significan a a lower significance level (EU Sugar) when conrolling for indusrial producion, indicaing ha a leas par of he co-movemen is due o common macroeconomic shocks. In oher cases he ess are significan a he same significance level in he bivariae as well as in he rivariae model (palm oil and sunflower oil) or is only significan in he rivariae model in levels (food index). This implies ha here seems o be oher facors han rends and common macroeconomic shocks ha drive he co-movemen. To derive furher insighs ino he possible causes of he co-movemen we perform he frequency domain Granger causaliy es of Breiung/Candelon (26) o disenangle shor- and long-run effecs. The es saisics for 31 frequencies as well as he 5 percen criical values (dashed line) are shown for each food price index in Figure 2.

15 Two graphs are shown for each commodiy: he firs depics he resuls of he bivariae sysem, he second he resuls of he rivariae sysem ha includes indusrial producion besides crude oil and he sudied commodiy. The frequencies on he horizonal axis range from o 2. They can be ranslaed ino periodiciies of T monhs by T=2 /. This means ha frequencies smaller han.5 corresponds o cycles longer han 1 years. Business cycles are ypically assumed o las beween 2 ½ and 7 years. The respecive frequencies are roughly.2 and.7. Frequencies around.5 belong o cycles of monhs which capure seasonal effecs (Hamilon 199: 7-17) and a frequency of wo corresponds o cycles of hree monhs. 13

16 Figure 2: Causaliy ess beween oil and food prices Bivariae model Food Trivariae model Food Soybean oil Soybean oil Mai ze Mai ze Barley Barley

17 Figure 2 (coninued) Bivariae model Sugar EU Trivariae model Sugar EU Rice Rice Sunflower oil Sunflower oil Palm oil Palm oil

18 Firs of all, he resuls show ha a leas a some frequencies he crude oil price index Granger causes he overall food price index as well as many of he subindices a leas in he bivariae case. These resuls are roughly in line wih oher empirical sudies. One excepion is Baffes (27) who finds no significan relaion beween oil and rice prices. However, if indusrial producion is included we also find no significan effecs beween boh prices. Anoher excepion is Zhang e al. (21). They find no Granger causal relaion effec from oil o sugar prices. Nex, we ake a closer look a which frequencies he Granger causaliy is significan. The resuls reveal subsanial differences beween food commodiies which remain undeeced oherwise. We pool he resuls in hree groups, corresponding o he frequencies a which we can deec a significan link beween he oil price and he considered food prices. To sar wih, he oil price is esimaed o Granger cause he overall food price index in he range [., 1.1] in he bivariae sysem, corresponding o a cycle lengh beween 6 and monhs. This resul would sugges ha he link beween oil and food prices is driven by calendar effecs or as Pindyck/Roemberg (199) propose by shor-erm speculaion. However, if we conrol for global economic aciviy by including indusrial producion in he VAR we also deec such a link a frequencies wih a wave lengh of more han 9 monhs. This means ha in he bivariae approach he correlaion of oil prices and indusrial producion hides he link beween oil and food prices a lower frequencies in he bivariae sysem. I is herefore more likely ha he correlaion beween oil and food prices is esablished a frequencies ha are relaed o long-erm economic developmens. The resuls are similar for maize and soybean oil. The resuls for soybean oil are o some exen in conras o he findings of Gilber (2) who concludes ha soybean oil prices show an explosive behaviour beween 26 and 2 driven by speculaion. Moreover, he ess reveal a differen picure for barley and sugar. The oil price Granger causes he price of barley in he bivariae sysem a frequencies less han.9 which corresponds o cycle lenghs of more han 7 monhs. If we conrol for indusrial producion he Granger causaliy ess become insignifican for cycle lenghs beween 7 and 15 monhs. Thus, only he low frequencies seem o be imporan. For EU sugar we receive a similar

19 picure. The ess deec a link beween he oil price and he price of EU sugar in he wovariable VAR a frequencies corresponding o cycles of more han 6 monhs. In he rivariae sysem he oil price Granger causes he price of EU sugar only a cycle lenghs of more han monhs. In addiion, he link in he bivariae sysem beween 3 and monhs does no vanish when conrolling for indusrial producion. Hence, even if we conrol for global economic aciviy he oil price Granger causes barley and EU sugar prices a higher frequencies. This finding suggess ha he oil price Granger cause he prices of a leas some commodiies a business cycle frequencies when conrolling for economic aciviy. Finally, we ge similar resuls for rice, sunflower oil and palm oil. While he oil price Granger causes he price of all hree commodiies a lower frequencies in he bivariae case we canno deec such a link when conrolling for indusrial producion. This means ha he link beween oil and hese commodiy prices is driven by economic aciviy. 5. Conclusions The high correlaion beween prices of oil and food is well esablished in he lieraure. However, i is an imporan quesion wheher his relaion arises from he long-run rend, business cycles or very shor-run flucuaions. So far empirical sudies use Granger causaliy ess in he ime domain o disinguish shor-run and long-run causaliy. A drawback of his approach is ha i is difficul o see wha shor-run and long-run exacly means. In his paper we use he relaively new frequency domain Granger causaliy es by Breiung/Candelon (26). This allows us o es Granger causaliy a specific frequencies which can be ranslaed ino he associaed cycle lengh. We apply his es o an overall food price index as well as o several indices of food commodiy prices. If only oil and food prices are considered he ess indicae ha oil Granger causes food prices for all hese indices. However, if we conrol for indusrial producion Granger causaliy vanishes in some cases suggesing ha he link resuls solely from flucuaions in economic aciviy. In mos of he oher cases Granger causaliy is indicaed a lower frequencies even when conrolling for indusrial producion. This finding suggess ha he relaion beween oil 17

20 and food prices is esablished by long-erm developmens no direcly relaed wih economic aciviy. Therefore herd behavior and speculaion, considered o be shor-run phenomena, do no seem o have a considerable effec on he sudied food prices. Wha hese developmens are is sill an open quesion. A possible explanaion for his could be he producion of biofuel. However, we find only weak evidence for some commodiies ha oil prices Granger cause food prices a very high frequencies. References Arshad, F. M. and A. A. A. Hameed (29), The Long Run Relaionship Beween Peroleum and Cereals Prices, Global Economy & Finance Journal 2(2): Assenmacher-Wesche, K. and S. Gerlach (2), inerpreing Euro Area Inflaion a high and Low Frequencies, European Economic Review 52: Baffes, J. (27), Oil Spills on Oher Commodiies, Resource Policy 32(3): Baffes, J. (21), More on he Energy/Non-Energy Commodiy Price Link, Applied Economics Leers 17(), Barne, L. and A. K. Seh (211), Behavior of Granger Causaliy under Filering: Theoreical Invariance and Pracical Applicaion, Journal of Neuroscience Mehods 21(2): -19. Breiung, J. and B. Candelon (26), Tesing for shor- and long-run causaliy: A frequency domain approach, Journal of Economerics 132: Cashin, P. and C. J. McDermo (22), The Long-Run Behavior of Commodiy Prices: Small Trends and Big Variabiliy, IMF Saff Papers 9(2): Croux, C. and P. Reusens (211), Do Sock Prices Conain Predicive Power for he Fuure Economic Aciviy? A Granger Causaliy Analysis in he Frequency Domain, Kaholieke Universiei Leuven - Faculy of Business and Economics Working Paper. Ding, M., Y. Chen and S.L. Bessler (26), Granger Causaliy: basic Theory and Applicaion o Neuroscience, B. Scheler, M. Winerhalder and J. Timmer (eds.) Handbook of Time Series Analysis. Wiley: Dufour, J.-M., D. Pelleier and E. Renaul (26), Shor Run and Long Run Causaliy in Time Series: Inference, Journal of Economerics 132: Geweke, J. (192), Measuremen of Linear Dependence and Feedback Beween Muliple Time Series, Journal of he American Saisical Associaion 77(37): Gronwald, M. (29), Reconsidering he Macroeconomics of he Oil Price in Germany: Tesing for Causaliy in he Frequency Domain, Empirical Economics 36: Hamilon, J. D. (199), Time Series Analysis, Princeon Universiy Press. Harri, A., L. Nalley and D. Hudson (29), The Relaionship beween Oil, Exchange Raes, and Commodiy Prices, Journal of Agriculural and Applied Economics 1(2):

21 Headey, D. and S. Fan (2), Anaomy of a crisis: he causes and consequences of surging food prices, Agriculural Economics 39(Supplemen): Hosoya, Y. (1991), The Decomposiion and Measuremen of he Inerdependence Beween Second-order Saionary Processes, Probabiliy Theory and Relaed Fields : 29-. Lemmens, A., C. Croux and M. G. Dekimpe (2), Measuring and Tesing Granger causaliy over he specrum: An Applicaion o European Producion Expecaion Surveys, Inernaional Journal of Forecasing 2: Lescaroux, Francois (29), On he excess co-movemen of commodiy prices - A noe abou he role of fundamenal facors in shor-run dynamics, Energy Policy 37: Lükepohl, H. (25), New Inroducion o Muliple Time Series Analysis. Heidelberg: Springer. Pindyck, R. S. and J. J. Roemberg (199), The Excess Co-Movemen of Commodiy Prices, Economic Journal 1(3): Saghaian, S. H. (21), The Impac of he Oil Secor on Commodiy Prices: Correlaion or Causaion?, Journal of Agriculural and Applied Economics 2(3): Silvennoinen, A. and S. Thorp (21), Financializaion, Crisis and Commodiy Correlaion Dynamics, Quaniaive Finance Research Cenre Universiy of Technology Sydney, Research Paper 267.Unied Naions Conference on Trade and Developmen (29), Trade and Developmen Repor, Geneva. Vanseenkise, I. (29), How Imporan are Common Facors in Driving Non-fuel Commodiy Prices? A Dynamic Facor Analysis, ECB Working Paper Series 172. Zhang, Z., L. Lohr, C. Escalane and M. Wezsein (21), Food versus Fuel: Wha do Prices Tell Us?, Energy Policy 3:

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