International Automotive Production Networks: How the web comes together. serie. Leticia Blázquez and Belén González-Díaz WP-EC

Transcription

1 sere ec WP-EC Interntonl Automotve Producton Networks: How the web comes together Letc Blázquez nd Belén González-Díz

2 Los documentos de trbjo del Ive ofrecen un vnce de los resultdos de ls nvestgcones económcs en curso, con objeto de generr un proceso de dscusón prevo su remsón ls revsts centífcs. Al publcr este documento de trbjo, el Ive no sume responsbldd sobre su contendo. Ive workng ppers offer n dvnce the results of economc reserch under wy n order to encourge dscusson process before sendng them to scentfc journls for ther fnl publcton. Ive s decson to publsh ths workng pper does not mply ny responsblty for ts content. L Sere EC, coordnd por Mtlde Ms, está orentd l plccón de dstntos nstrumentos de nálss l estudo de problems económcos concretos. Coordnted by Mtlde Ms, the EC Seres mnly ncludes pplctons of dfferent nlytcl tools to the study of specfc economc problems. Todos los documentos de trbjo están dsponbles de form grtut en l web del Ive sí como ls nstruccones pr los utores que desen publcr en nuestrs seres. Workng ppers cn be downloded free of chrge from the Ive webste s well s the nstructons for uthors who re nterested n publshng n our seres. Versón: julo 2013 / Verson: July 2013 Edt / Publshed by: Insttuto Vlencno de Investgcones Económcs, S.A. C/ Gurd Cvl, 22 esc. 2 1º Vlenc (Spn)

3 WP-EC Interntonl Automotve Producton Networks: How the web comes together * Letc Blázquez nd Belén González-Díz ** Abstrct Ths pper ms to contrbute to the lterture on New Economc Geogrphy by provdng emprcl evdence for the connectons between new trde theory nd the sptl dstrbuton of economc ctvtes. To do ths, we pply Socl Network Anlyss specfclly to the World Automotve Trde Network. We explore the structurl fetures of the uto network for the yers 1996 nd 2009 usng dt on trde flows for 172 countres. Our fndngs suggest tht the uto network hs become denser, more extensve nd more ntegrted over tme, depctng centerperphery structure n whch regonl clusters ply promnent role. In ths confgurton, strong gglomerton forces generted by compnes desre for lrge nd rch mrket ccess wth mnmum trnsportton costs re blnced by the serch for new hgh-potentl mrkets. Keywords: World Automotve Trde Networks, New Economc Geogrphy, Socl Network Anlyss, Prts nd Components. JEL Clssfcton: F10, F14, F15. Resumen El objetvo de este trbjo es contrbur l ltertur bsd en l Nuev Geogrfí Económc mednte l portcón de evdenc empírc sobre l nterrelcón entre ls nuevs teorís del comerco y l dstrbucón espcl de ls ctvddes económcs. Pr ello emplemos l metodologí de ls redes socles plcds concretmente l red mundl de comerco de l ndustr del utomóvl. Con nformcón estdístc de los flujos comercles de 172 píses, se nlzn ls crcterístcs estructurles más mportntes de l red del utomóvl pr los ños 1996 y Los resultdos ponen de mnfesto que l red de comerco mundl del utomóvl se h hecho más dens, más ntegrd y más extens con el pso del tempo reflejndo un clr estructur centro-perfer donde los clusters regonles desempeñn un ppel muy relevnte. En l confgurcón de est red, l mportnc de ls fuerzs de glomercón generds por el deseo de ls empress de cceder los mercdos más mportntes con los menores costes de trnsporte posbles, se ven contrrrestds por l búsqued de nuevos mercdos con un elevdo potencl de crecmento. Plbrs clve: Red mundl del comerco del utomóvl, Nuev Geogrfí Económc, Análss de ls redes socles, Prtes y componentes. Clsfccón JEL: F10, F14, F15. * The uthors thnk Rosro Gndoy nd Crmen Díz-Mor for helpful comments nd lso cknowledge the fnncl support from the Regonl Government of Cstll-L Mnch (PPII ). ** L. Blázquez nd B. González-Díz: Unversty of Cstll-L Mnch (Toledo, Spn). Correspondng uthor: L. Blázquez, e-ml: Letc.blzquez@uclm.es.

4

5 1. Introducton Trde theores bsed on New Economc Geogrphy (NEG) hve stressed the mportnce of tkng nto ccount the nterconnecton of regons n the nlyss of the sptl dstrbuton of economc ctvtes. They hghlght how ny chnge tht drectly nvolves only two regons re unlkely to leve the remnng regons unffected. Addtonlly, NEG hs emphszed tht the reltve poston of the regon/country wthn the whole network of nterctons s key ssue fced by frms when choosng where to locte nd thus lso nfluences the wy they orgnze ther producton, mngement nd outsourcng (Krugmn, 1993; Thoms, 2002; Fujt nd Thsse, 2009). One of clerest sgns of how the complex nterctons between countres nd regons nfluence the wy compnes orgnze ther producton nd vce-vers hs been the emergence of nterntonl producton networks n most mnufcturng sectors. In ths sense, the mn objectve of ths pper s to study the structurl evoluton of the sptl dstrbuton of economc ctvtes for one of the sectors wth the hghest ncdence of globl producton shrng, the utomotve ndustry, n the lght of some of the ssumptons nd results obtned from New Economc Geogrphy. As lterntve to more trdtonl theoretcl models, we wll use n ths nlyss n emprcl pproch by pplyng the methodology proposed by the Socl Network Anlyss. The extent to whch these shrng strteges hve been mplemented n the uto ndustry s reflected by the spectculr ncrese n the world s utomotve trde n generl durng the pst decde (from , t grew t cumultve nnul rte of 5.4 percent n nomnl terms) nd by the prtculrly hgh dynmsm of ts ntermedte commodty flows, wth n nnul cumultve growth rte of 6.2 percent (lmost two percentge ponts more thn fnl goods), ncresng ts shre of the overll world uto trde from 50 to 56 percent. These hghly ntense nterntonl trde flows gve us cler de of the complexty of the uto ndustry orgnzton, evdencng the relevnce of ts network chrcterstcs n ts nlyss. Accordng to NEG, the sptl dstrbuton of economc ctvtes cn be vewed s the outcome of complex blnce between two types of opposng nd mutully renforcng forces: gglomerton (or centrpetl) nd dsperson (or centrfugl) forces (Bldwn et l., 2003; Fujt nd Thsse, 2009). 1 In ths regrd, snce the utomotve ndustry cn be consdered frgmented nd to operte under ncresng returns to scle n globlly mperfect compettve mrket, the locton of uto compnes cross spce should presumbly be explned prmrly n terms of the serch for prvleged ccess to lrge, welthy mrkets nd the desre to relx the compettve pressures mposed by other frms. 1 Two stble spredng equlbr result from the smplest 2x2x2 model (Krugmn, 1991): gglomerton of one of the sectors n one regon when trnsportton costs re very low, nd dsperson of ths sector n two regons when trnsportton costs re very hgh. In ths model, Krugmn bsclly dds the nterregonl moblty fctor (workers nd frms choose locton) to hs new trde theory model (Krugmn, 1980). From ths stylzed model, dfferent nd more complex ssumptons hve been dded. For dscusson of the core model nd severl of ts extensons, see, for exmple, Ottvno nd Thsse (2004). 5

6 Therefore, we expect lrger economes n terms of populton nd purchsng power to ttrct more thn proportonl shre of uto compnes; n other words, for the home mrket effect to be one the most sgnfcnt gglomerton forces n the conformton of the uto network. Intermedte trnsportton costs ncurred by the uto ndustry would led frms to seek to locte close to ther end mrkets, thus renforcng the mrket effect. As result, we lso expect deeper ntegrton wthn the uto network to ctully led to more regonl mblnce n the sptl dstrbuton of the ndustry nd for some degree of economc speclzton to rse. Addtonlly, n hghly frgmented sector lke the uto ndustry, the presence of nput-output lnkges between frms s expected to be one strong gglomerton force (Krugmn nd Venbles, 1995). On the other hnd, trdtonl uto mrkets re frly mture nd the competton between compnes n ther terrtores could be lbeled s ferce. Therefore, we would expect dsperson force generted by ech frm s desre to vod mrket crowdng (correspondng to the prce effect n sptl competton) to emerge. Fostered by ths dsperson force, some frms would relocte from the trdtonl core to the perphery, yeldng bell-shped curve of sptl development à l Kuznets. In order to evlute the extent to whch the evoluton of the uto ndustry structure responds to these ssumptons set by the NEG, we wll pply Socl Network Anlyss tools nd grph theory to the world trde web rther thn the trdtonl generl equlbrum models ppled by the NEG. The reson s tht, lthough the contrbuton of NEG to ntroducng sptl fctors nto rgorous models s unquestonble, ts own precursors hve ponted out tht these models re too stylzed nd smple to dequtely represent the rel economc geogrphy nd thus become relevnt from polcy-mkng stndpont (Krugmn, 2001, p.59). In the nlyss of these cross-border producton blocks, multple fctors should be tken nto ccount. It s not only queston of ntensfyng the openness of countres, but lso of developng networks of drect nd ndrect reltons between ndvduls, compnes nd countres t dstnce from ech other (Arrbs-Pérez nd Tortos-Ausn, 2009). Network pproch s n pproprte method for studyng such ssues s t provdes methodology tht enbles us to mesure the nture of these reltons nd how nd to whch extent nd they evolve over tme n wys tht other mesures do not cpture. By pplyng network nlyss to nterntonl trde, we cn complement other emprcl nlyses of trde tht put countres chrcterstcs t the forefront (e.g. the grvty model of nterntonl trde) snce t plces more emphss on the reltonshp between unts n the grph nd on the structure of the system tself thn on the unts ttrbutes, whch re generlly left n the bckground. Although these technques hve not been very extensvely used n economcs to dte, the pproch s not new n nterntonl economcs (see, for nstnce, the recent pper by Chnzz et l., 2013) nd specfclly n trde nlyss. Recent exmples nclude Grlschell nd Loffredo (2005), Kl nd Reyes (2007), Kl et l. (2007), Arrbs et l. (2009), Fgolo et l. (2008), Fgolo (2010), nd De Benedcts nd Tjol (2011). All of these studes focus 6

7 on nlyzng the world trde network nd ccurtely nlyze the propertes of the system n terms of trde flows, prtners nd lnks. Most of them suggest tht there s strong heterogenety between countres, wth ntons plyng very dfferent roles n the network structure, but there s only very lmted effort n these studes to expln these fndngs on the bss of trde or locton theores. Moreover, none of them nlyzes specfclly the chrcterstcs of shrng producton networks nor consders the dfferentted fetures of sectors whch use these strteges s we do n ths pper by focusng on one specfc sector. The structurl chrcterstcs of the world utomotve trde network hve been nlyzed n severl mertorous studes (e.g., Humphrey nd Memedovc, 2003; Sturgeon et l. 2008, 2009; Amghn nd Gorgon, 2010; Sturgeon nd Vn Beserbroeck, 2010, 2011). However, most of these ppers do not offer n emprcl nlyss wth sold nlytcl frmework tht mkes t possble to fnd stronger ffntes wth trde theores nd nterntonl economcs. In ths sense, ths pper complements these more descrptve contrbutons. The rtcle s orgnzed s follows. In secton 2, we brefly expln the mn network nlyss tools nd the dt source used n the reserch. Secton 3 descrbes the evoluton of structurl fetures of the world utomotve trde network nd nlyzes the gglomerton nd dsperson forces behnd ths evoluton. Secton 4 offers some concludng remrks. 2. Socl Network Anlyss nd Dt Socl Network Anlyss s bsed on mthemtcl grph theory. In the grph representng the world utomotve trde network (WATN, herefter), the vertces of the network represent the trdng countres nd the lnes represent the trde flows between ny two prtners: exports nd mports. We consder the WATN from two complementry stndponts. Frst, we buld weghted network where ech drected lnk represents the vlue of export from the country of orgn (the exporter) to the trget country (the mporter) s reported by the mporter 2. Whle we re nterested n comprng the structure of the WATN t two dfferent moments n tme, we lso defne rescled weghts reltve to the totl yerly trde flows. 3 In ths wy, trend effects re elmnted nd we obtn dmensonl weghts tht re utomtclly deflted, llowng for consstent comprsons cross dfferent yers nd commodty types (Squrtn et l., 2011b). Addtonlly, we hve lso explored the propertes of the bnry projecton of the weghted generc mtrx by nlyzng the mere presence or bsence of trde reltonshp between two countres. The sequence of bnry nd weghted mtrces fully descrbes the wthn-smple dynmcs of the WATN, nd ts mn chrcterstcs cn be summrzed by topologcl 2 The drected nture of the WATN s bsed n the clculus of the symmetry ndex, S, proposed n Fgolo (2006). Snce the symmetrc ptterns hve been sttstclly dentfed, drected nlyss of the network s necessry. w(t) 3 j w' j(t) w (t) where w (t) re exports from country to country j n perod t nd w (t) Σ Σ w (t). j tot j j tot 7

8 mesures nd pths. 4 To ths extent, we hve clculted both ggregte nd node-specfc network sttstcs. The ggregte topologcl mesures provde evdence for the structurl propertes of the whole network. In ths ven, the number of prtners nd the ntercton ntensty of countres, s well s the wy these ptterns hve chnged over tme, wll gve cler de bout the evoluton of the connectvty of countres n the WATN. The wdest mesure of the connectvty or cohesveness of network s ts densty (.e. the frcton of ll possble lnks tht re ctully present). Addtonlly, we hve nlyzed the shpe of the network by mesurng the extent to whch t hs (or hs not) center. The degree centrlzton ndex C D (.e. the vrton n the number of trde lnks tht gven country hs estblshed dvded by the mxmum degree of vrton possble) provdes ths nformton. And the group rndom betweenness centrlzton ndex BCN descrbes nd compres dfferent networks wth respect to the heterogenety of the role of ther members s ntermedres n the network. Together wth these ggregte mesures, node-specfc network sttstcs consder ndvdul countres postons wthn the WATN. We thus determne how mny trde lnks country hs estblshed (.e. node degree mesures), dstngushng between the number of countres tht the country mports from (ndegree) nd the number of countres tht receve exports from ths prtner (outdegree). Correspondngly, we cn ssess the weghts ssocted wth the trde lnks mntned by ech country (.e. node strength mesures). The lrger the node strength of country, the hgher the ntensty of the nterctons t medtes. In ths sense, t s lso nterestng to dentfy uthortes nd hubs wthn the network. Usng the HITS lgorthm developed by Klenberg (1999), we cn determne whch countres re (v strongly weghted n-lnks) more ponted-to by hubs, becomng uthortes; nd whch countres pont (v strongly weghted out-lnks) to more uthortes, becomng hubs. 5 Furthermore, n ssessng the centrlty of countres wthn the network, we exmne ther closeness centrlty ndex CL tht mesures how esly country cn trde wth ll the others tkng nto ccount the geodesc dstnces between them; nd ther rndom betweenness centrlty ndex tht revels how mportnt country s s n ntermedry n the network. The bnry verson of the ltter ndex RWBC would ndcte the extent to whch country s crucl for the ntegrton of the network wheres ts weghted verson RWWBC cptures the effects of the mgntude of the reltonshps tht ech node hs wth ts prtners, s well s the strength of the node n queston. 6 4 A more extensve nd detled descrpton of the topologcl mesures ncluded n ths secton cn be found n the semnl book by Wssermn nd Fust (1994). The correspondng nlytcl descrpton of ths secton s presented n Tble A3 of the Sttstcl Appendx. 5 Note tht n uthorttve country my lso be hub, nd vce vers. It s lso mportnt to be wre tht HITS hub/uthorty rnkngs tend to be strongly correlted wth the out-/n-degrees of the correspondng nodes (Benz et l, 2013). 6 In prtculr, we use n ths study the Rndom-wlk betweenness centrlty ndex proposed by Newmn (2005) nd Fsher nd Veg-Redondo (2006). 8

9 Another mportnt feture of network structure concerns the extent to whch gven country s clustered (.e. how much the prtners of country re themselves prtners). In order to dentfy clusters of countres tht re closely connected nsofr s they ll shre prtculr mnmum degree wthn the cluster, we pply the so-clled k-cores nlyss. 7 These frst-order ndctors ndcte the extent to whch the WATN shows coreperphery structure;.e. to whch the gglomerton forces prevl n the conformton of the network. Addtonlly, we cn nlyze second-order reltons, whch ndcte how nd how much ech country s prtners re themselves connected wthn the network. In dong so, we cn evlute the nfluence of dsperson forces on the network shpe nd ts evoluton. To do ths, we hve computed the verge nerest-neghbor degree (ANND),.e. the verge number of prtners of the neghbors (prtners) of country. We hve lso clculted how much the prtners of node re themselves chrcterzed by hgh strength by computng the weghted verge of nerest-neghbor node degrees (WANND) nd the rthmetc verge of nerest neghbor strengths (ANNS). Note tht n both the bnry nd the weghted network we cn consder seprtely the dfferent drectonl trde reltons,.e. the trde reltons between the country consdered nd ts prtners s well s the reltonshps of the trde prtners of the country nlyzed. The mn dt source employed n the nlyss hs been the Unted Ntons COMTRADE Dtbse. The trde dt used s blterl exports/mports s reported by the mportng country nd mesured n nomnl U.S. dollrs. 8 Followng the HS1996 ctegores dentfed by Türkcn (2009) nd the SITC Rev.2 ctegores recognzed by Kmnsk nd Ng (2001) for uto P&C, we provde more extensve nd complete code lst for utomotve fnl goods nd ther P&C correspondng to HS1992 (Tble A2 n the Sttstcl Appendx). Wth these dt, we hve creted seprte trde mtrxes between countres for the exchnge of utomotve fnl goods nd ther correspondng prts nd components (henceforth, P&C). The mtrxes nclude 172 countres nd hve been constructed for the yers 1996 nd The use of P&C trde s sutble proxy for prtcpton n nterntonl producton networks s commonplce. Becuse of ther ntermedte nture, P&C foregn exchnges must necessrly be trgeted t ssembly n the mporter country or for ncorporton nto further stge of producton n nother economy (except spre prts). Furthermore, lthough n cptl nd technology-ntensve ndustres such s ths, the producton of P&C s consdered to be reltvely cptl-ntensve whle ther ssembly s reltvely more lbor-ntensve (Km, 2002; Athukorl, 2009), there re consderble 7 A k-core s mxml subnetwork n whch ech vertex hs t lest degree k. It therefore dentfes reltvely dense subnetworks nd thus cohesve subgroups wthn the whole network. 8 We restrcted our nlyss to those mport flows whose vlues re hgher thn or equl to 3 per cent of the country s totl mports of the specfc commodty consdered. 9 The selecton of the number of countres ws bsed on the vlblty of dt for both of the perods nlyzed. See Tble A1 n the Sttstcl Appendx. 9

10 dfferences between utomotve P&C n terms of fctorl ntensty. These dfferences wll, n turn, nfluence trnsportton costs, trnscton cost nd the extent to whch scle economes cn be exploted. These fctors re very much tken nto ccount by uto compnes n ther outsourcng nd locton decsons. It s nterestng, then, to explore whether the structurl trnsformtons nd chnges n countres speclzton lso depends on the fctorl ntensty of uto P&C. In order to do ths nd followng Peneder (1999), we hve dfferentted four P&C subnetworks ccordng to ther fctorl ntensty: mnstrem-drven, cptl ntensve-drven, technology-drven nd lbor-ntensve-drven. 10 The fnl ssembly tsks should lso be consdered n the nlyss for two mn resons. Frstly, from the stndpont of nterntonl producton networks, study of the fnl utomotve goods export network s prtculrly relevnt, snce n dong so we re consderng those countres opertng n the lst stges of the vlue chn,.e. n ssembly of P&C nto the fnl goods nd ther subsequent export. Secondly, n recent yers there hs been notble expnson of network ctvtes from pure producton nd ssembly of P&C to fnl ssembly (Athukorl, 2011). 3. The Interntonl Automotve Producton Network 3.1. Frst-order ndctors: Agglomerton forces The ggregte network sttstcs revel tht the P&C network hs become denser nd more extensve over tme snce countres hve, on verge, ncresed the number of prtners wth whch they hve trde reltons (Tble 1). However, the results for centrlty mesures permt the rgument tht the uto P&C network hs mntned centre-perphery structure n terms of connectvty nd ntensty. The hgher degree centrlzton ndex would suggest unevenly ncresng ntegrton wthn the network. And the ncresng betweenness centrlzton ndexes, mnly the weghted ndex, would ndcte the growng mportnce of hubs n the WATN. The pttern of heterogenety between countres wthn the WANT s clerly vsble n Fgure 1. We cn pprecte smll group of hghly connected countres n the centre hvng trde reltons wth the vst mjorty of the other countres, nd wth most countres hvng very smll number of prtners tht, n prtculr, only hve trde reltons wth those centrl countres. Nevertheless, t should be noted tht only the P&C export network exhbts cler nd ncresngly str-shped structure, wheres the P&C mport network looks rther lke regulr grph (Fgures 2). It s lso remrkble to note tht, ccordng to the closeness centrlty ndex, dstnces between trdng economes seem to be shortened nsofr s more 10 Peneder (1999) dentfed fve groups rther thn four. The ffth group refers to mrketng-drven P&C. Snce, n the cse of the utomotve ndustry, ths ctegory ncludes only two tems whch ccount for only 0.3% of the totl trde n utomotve P&C we hve decded not to nlyze ths ctegory seprtely. The mnstrem-drven ctegory refers to those tems n whch nput combntons do not shre mjor relnce on ny prtculr nput fctor. 10

11 Tble 1. Topologcl Mesures of the World Automotve Trde Network Bnry Network Indexes P&C Fnl Goods P&C Fnl Goods Weghted Network Indexes Arcs Densty Averge Node Degree (number of lnes) Averge Node Strength Indegree/Outdegree (Averge) Instrength/Outstrength (Averge) Averge Nerest-Neghbor Degree (ANND) Averge Nerest-Neghbor Strength (ANNS) Degree Centrlzton Indegree Centrlzton Outdegree Centrlzton Closeness Centrlty Input Closeness Centrlty Output Closeness Centrlty Rndom Wlk Betweenness Centrlty (RWBC) Rndom Wlk Weghted Betweenness Centrlty (RWWBC) Rndom Wlk Betweenness Centrlzton Rndom Wlk Weghted Betweenness Centrlzton Export k-cores 8 (k=4) 12 (k=4) 7 (k=4) 7 (k=5) There re sttstclly sgnfcnt dfferences (5% sgnfcnce) between the mesures for P&C nd Fnl Goods n the Indegree s ndctors for 1996 nd 2009 nd the ANND for 1996, whle for the rest (Outdegree, Degree, Instrength, Outstrength, Node Strength, ANND for 2009, ANNS, RWBC) no sttstclly sgnfcnt dfferences re found between the verges for P&C nd Fnl Goods. The hghest core of the P&C export network ws formed by Belgum-Luxemburg, Frnce, Germny, Itly, Spn, the Unted Kngdom, Jpn nd USA. Frnce, Germny, Itly, Spn, the Unted Kngdom, Jpn, USA, Chn, Kore, Czech Republc, Hungry nd Polnd. Belgum-Luxembourg, Frnce, Germny, Itly, Jpn, Spn, Unted Kngdom. Source: uthors clculton, bsed on UN COMTRADE. 11

12 drect trdng reltons hve emerged. Therefore, we cn sy tht the trde ntegrton of the P&C uto network hs ncresed over tme. Fgure 1. Automotve P&C. Outdegree Network (2009) Source: uthors clculton, bsed on UN COMTRADE usng PAJEK. The sze of vertces s relted to ther outdegrees Fgure 2. Automotve P&C. Indegree Network (2009) Source: uthors clculton, bsed on UN COMTRADE usng PAJEK. The sze of vertces s relted to ther ndegrees 12

13 Addtonlly, Fgure 3 shows tht hghly connected nd ntegrted countres re lso the most (on verge) ntensely connected It s nterestng to observe how the vrblty n verge strength s frly hgh for those countres wth reltvely low degree, whle from certn degree onwrds, countres re ble to mntn ntense trde reltonshps. Moreover, we observe tht not only re there few countres wth hgher number of lnks, but there re even fewer tht re ntensely connected. We hve lso detected tht those few countres wth ncresngly ntense reltonshps re lso the ones tht ply more promnent role s ntermedres wthn the network (Fgure 4) nd tht these gtekeeper countres hve ntensfed ther role over tme. Fgure 3. Correlton between Degree nd Averge Node Strength for P&C WATN (1996 nd 2009) Log (Averge Node Strengh) CC=0.8267* CCLow= CCUp= Node Degree Log (Averge Node Strengh) CC=0.7498* CCLow= CCUp= Node Degree Source: uthors clculton, bsed on UN COMTRADE. CCLow nd CCUp re the correlton coeffcents t 5% nd 95% confdence ntervls Fgure 4. Correltons Degree vs Closeness Centrlty nd Strength vs Rndom Wlk Betweenness Centrlty (RWBC) for P&C WATN, 2009 Closeness Centrlty 1 0,9 0,8 0,7 0,6 0,5 0,4 0,3 0,2 0, CC= * CCLow= CCUp= ,5 1 1,5 2 2,5 log (Degree) RWBC (bnry) CC= * 140CCLow= CCUp= Strength Source: uthors clculton, bsed on UN COMTRADE. CCLow nd CCUp re the correlton coeffcents t 5% nd 95% confdence ntervls. Addtonlly, the HITS lgorthm (Tble 2) nd the k-core ndctors nlyss (Tble 1) suggests tht n ths centre-perphery structure, regonl, locl nd/or trdtonl tes ply very mportnt nd ncresng role n the shpng of the network. The smll number of centrl countres tht re t the sme tme hubs nd uthortes ndcte tht these countres not only sell ther P&C to those non-producer countres but tht there s lso n ntensve flow of P&C from them towrds other (less powerful) P&C producers n the centre of the network. 13

14 Tble 2. Weghted Hub nd Authorty Centrlty n the utomotve P&C Rnk Weghted Hub Centrlty Weghted Authorty Centrlty US CHN CA US 2 JP MX US CHN 3 MX JP MX CA 4 CA CA UK JP 5 DE KO JP MX 6 FR DE DE HK 7 IT US KO FR 8 UK FR TH UK 9 ES IT FR DE 10 SE PL B&L KO Argentn (AR); Austrl (AU); Austr (AT); Belgum-Luxembourg (B&L); Brsl (BR); Cnd (CA); Chn (CHN); Colomb (CO); Czech Rep.(CZ); Denmrk (DK); El Slvdor (SV); Fnlnd (FI); Frnce (FR); Germny (DE); Hondurs HN); Hong Kong (HK); Hungry (HU); Ind (IN); (Indones (ID); Isrel (IL); Itly (IT); Jpn (JP); Mlys (MY); Mexco (MX); Netherlnds (NL); Pnm (PA); Phlppnes (PH); Polnd (PL); Portugl (PT); Kore (KO); Romn (RO); Russn F. (RU); Sud Arb (SA); Sngpore (SG); Slovk (SK); Sloven (SI); Spn (ES); Sweden (SE); Swtzerlnd (CH); Thlnd (TH); Tuns (TN); U.A. Emrtes (AE); Unted Kngdom (UK); USA (US) nd Venezuel (VE). Source: uthors clculton, bsed on UN COMTRADE The forementoned structure for the P&C network s bsclly repeted for the fnl goods export network. 11 Ths mens tht only smll group of countres re hghly-connected nd ntense exporters of fnl goods nd those exporters hve hghly dverse portfolo of prtners (Fgure 5). In fct, the most ntense P&C mporters nd exporters were lso the most ntense exporters of fnl goods. And, s expected, we hve found tht the hevest P&C exporters were lso the most hghly connected countres n the export mrkets of fnl goods. However, t seems tht the hevest exporters of fnl goods do not necessrly hve hgh number of foregn provders of P&C, even though they ntensely buy P&C from them. Ths prllelsm n the confgurton of both networks sgnls n mportnt structurl chnge n the uto network from the nnetes to the present. Trdtonlly, the P&C sector hs been less concentrted (less centrlzed) thn the fnl ssembly sector (Wells nd Rwlnson, 1994; Sdler, 1997), but over tme, the ntense concentrton nd nterntonlzton process experenced by the component sector n order to be ble to source to ssembly frms on world-wde bss hs brought the centrlzton ndces of both networks closer. In ths sense, we cn observe how the P&C network hd become even more centrlzed thn the fnl goods network by 2009 (see Tble 1). Nevertheless, P&C frms re stll more geogrphclly scttered n ther producton nd sles ptterns thn fnl uto goods compnes. 11 No sttstclly sgnfcnt dfferences were found between both networks for most of the structurl ndctors. 14

15 Fgure 5. Automotve Fnl Goods. Outdegree Network (2009) Source: uthors clculton, bsed on UN COMTRADE usng PAJEK. The sze of vertces s relted to ther outdegrees. The dynmcs descrbed so fr by the frst-order ndctors of Socl Networks Anlyss, n whch centre-perphery structure domntes the WATN, rse mnly from the cton of the gglomerton forces. In the next secton, we wll nlyse those centrpetl forces tht mke ths structure prevl. When we exmne n more detl the composton of the WATN centre, t seems cler tht one of the mn gglomerton forces tht s ctng n ts structure s the mrket effect. The centrl nucleus of ths str-shped uto network ws mde up n 1996 of such economes s Jpn, Germny nd the USA (Tble 3). Together wth these three, Itly, Frnce, the Unted Kngdom, Kore 12, Spn, Belgum-Luxembourg, nd the Netherlnds were the most centrl, rechble, nd go-between countres n the network. Other mportnt economes n the WATN, locted close to lrge mrkets were Cnd nd Mexco, whch both hd very sgnfcnt outstrengths n both the P&C nd fnl goods export mrkets lthough they were very nrrowly lnked. All these economes contnue to be prt of ths centrl nucleus, lthough together wth other countres (see below). Accordngly, n 1996, the densest k-core ws composed of Europen cluster (Belgum-Luxembourg, Frnce, Germny, Itly, Spn, nd the Unted Kngdom) plus Jpn nd the USA. One of the resons why the composton of the WANT centre s mde up of those countres s tht the ntermedte trnsportton costs n the utomotve ndustry led utomkers to locte close to the end mrkets. But n ddton, the explotton of the dvntges of the nterntonl dvson of lbour requres extensve mrkets, wth the mrket sze determnng the optmum degree of producton frgmentton (Jones et l., 2005). Therefore, the centre-perphery structure s generted by compnes desre for lrge mrket 12 When we sy Kore, we men South Kore. 15

16 Tble 3. The Role of Countres n the Interntonl Automotve Producton Network (ordered by 2009 outdegree P&C) Automotve Prts nd Components Automotve Fnl Goods Automotve Prts nd Components Automotve Fnl Goods Outdegree Outstrength Indegree Instrength Outdegree Outstrength Outdegree Outstrength Indegree Instrength Outdegree Outstrength Chn Germny Jpn USA Kore Frnce Itly Ind UK B&L Hungry Netherlnds Polnd Spn Brzl UAE Fnlnd Mexco Thlnd SACU Turkey Sweden Russ Czech Rep Sngpore Romn Indones Austr Cnd Portugl Argentn Slovk Source: uthors clculton, bsed on UN COMTRADE. 16

17 ccess n terms of populton nd purchsng power coupled wth mnmzton of trnsportton costs. 13 In fct, ths comprtve dvntge of some economes, bsed more on mrket sze thn on producton costs, s wht, ccordng to NEG, should be expected for ndustres such s ths tht operte n segmented mrkets under mperfect competton nd wth ncresng returns to scle nd ntermedte trnsportton costs. When these economes re lrge enough to engge ther producton, the domestc mrket s the mn consumer; however, when economes ttrct more thn proportonl shre of frms, they lso become export pltforms. Moreover, the prllelsm n the confgurton of P&C nd fnl good networks seems to ndcte tht second gglomerton force s consequence of the reltonl form of the lnkges between P&C supplers nd between them nd ssemblers, cused by the hgh complexty nd modulrty of the uto P&C. In ths sense, crmkers preference for developng locl suppler bses through mxture of encourgng follow-sourcng by mjor trnsntonl compnes n P&C, where lrge supplers follow ther customers nvestment brod, nd the upgrdng of exstng locl supplers (Humphrey nd Memodovc, 2003), foster the synchronzed structurl evoluton of the fnl nd P&C networks. These strteges re lso reflected n the ncresng role of (regonl) hubs n the network tht we hve seen n the prevous secton. The ncresng role of the centrl countres s ntermedres n the network s consequence of the development of centrl sector-specfc knowledge nd nnovtve ctvty n these economes. Most of the sector s economc ctvty must pss through ther terrtory becuse most of the crtcl techncl nd engneerng tsks re developed wthn or ner them (Sturgeon et l., 2008). In order to further nvestgte the results of the development of these nput-output lnkges wthn the WATN, nd the extent to whch t reflects compnes serch for the explotton of sptl heterogenety mong regons n terms of more effcent producton through speclzton nd trde (s clsscl nterntonl trde theores would post), Tble 4 offers the trdtonl Blss ndexes ppled to P&C exports nd mports nd lso to fnl uto goods exports. For P&C exports, vlues hgher thn one ndcte speclzton n the producton nd export of these P&C. In the cse of mports, vlues hgher thn one men speclzton n P&C ssembly, snce mported P&C wll necessrly be ncorported nto other hgher dded-vlue P&C or nto fnl goods. When the mport speclzton s ndeed prt of vertcl speclzton strtegy, menng tht the destnton of the fnl goods s export, then the country lso benefts from comprtve dvntge n the export of fnl goods. Accordng to ths rgument, we cn clssfy countres nto three mn ctegores or groups. The frst group (G1) s mde up of pure producers nd exporters of P&C. The second group (G2) contns those countres tht re speclzed n lbour-ntensve ssembly tsks. The thrd group ncludes those countres tht re dully speclzed (Kmnsky nd Ng, 2001). 13 In ths respect, t s mportnt to ber n mnd the explnton of the dstnce puzzle gven n Arrbs et l. (2011) from the constructon of nterntonl trde ntegrton ndctors; the uthors fnd tht the role of dstnce n blterl trde, on verge, stll mtters despte the reductons n the cost of trde, lthough t vres cross countres. 17

18 Ths ltter behvour could result from two crcumstnces. The frst possblty s tht the country mports P&C tht re trnsformed nto other more downstrem P&C, whch re then exported (G3). The second possblty s to export upstrem P&C, whch re trnsformed nto more complex P&C brod nd re-mported from the country for ssembly nto the fnl product, whch s then exported (G4). Berng n mnd ts shortcomngs, the nlyss of the trde blnce cn be n ndctor of whch of the two stutons prevls. Tble 4. Speclzton of mn countres n the utomotve sector G1 G2 G3 G P&C Fnl Goods P&C Fnl Goods Import Export Export Import Export Export Jpn Kore Chn UK USA B&L Hungry Mexco Czech Rep Polnd Germny Frnce Brzl Spn Cnd Sweden Argentn Thlnd Turkey Source: uthors clculton bsed on UN COMTRADE. In Tble 3 we see tht Jpn ws n the md-nnetes nd stll s pure producer of P&C whch re destned for both export nd domestc ssembly. The fnl utomotve goods produced t home re of course very much consumed domestclly, but they re lso hevly trgeted t export. Its ndustry hs followed cler vertcl speclzton strtegy t the hghest technologcl stges. On the other hnd, countres such s the Unted Sttes nd the Unted Kngdom seem to follow very dfferent strtegy: they re speclzed n the ssembly of P&C, whch they mostly mport or re-mport (the ltter s very much the cse wth the Unted Sttes), mnly nto fnl goods tht they ether consume domestclly or export. Of course, the lrge US domestc mrket bsorbs reltvely hgher proporton of the fnl 18

19 ntonl utomotve producton, lthough we should ber n mnd tht ths country s the thrd lrgest world exporter of utomotve fnl goods. It s lso nterestng to observe how n the md-nnetes the Unted Sttes ws dul speclzed, whle tody t hs lost ts comprtve dvntge s producer nd exporter of P&C nd s ncresngly focused on the ssembly of fnl goods to be sent brod. We cn lso see ths effect n the downwrd movement n the hubs-centrlty ndex rnkng (Tble 2) The other promnent countres n the WATN both n 1996 nd 2009 show dul speclzton nd ll of them re lso speclzed n fnl exports. It therefore seems tht these economes hve dvntges n ll stges of the vlue chn, nd the compnes locted n these countres follow vertcl speclzton strteges. However, there re some dfferences between them. Countres such s Germny, Frnce nd Mexco mport P&C, whch re ether trnsformed nto other more downstrem P&C destned for foregn mrkets or re ssembled nto the fnl product n ther terrtores nd then exported. In ths sense, Germny s role s remrkble. Not only does t mport P&C to be trnsformed nto hgher dded-vlue goods, but t s lso the mn exporter of fnl goods, so t plys promnent role s n ssembler. On the other hnd, economes such s Spn nd Cnd, though lso dully speclzed, show hgher dvntges n ssembly. They export P&C tht re trnsformed nto hgher dded-vlue P&C brod nd then re-mported for ssembly nto the fnl goods, whch re then consumed domestclly or exported. They cn be consdered export pltforms of fnl utomotve goods. Once gn, we cn see how the combnton of the mrket effect nd the reltonl lnkges between the dfferent stges of the vlue chn mke countres lke the Unted Sttes, the Unted Kngdom, Germny, Spn nd Cnd very powerful ssemblers despte not beng economes wth low lbour costs or hvng, pror, pprent lbour cost dvntges n the world economy Second-order ndctors: Dsperson forces Accordng to the frst-order ggregte network ndctors n Tble 1, t seems cler tht n 2009 the WATN contnued showng cler centre-perphery structure. However, t s lso possble to pprecte tht the verge nerest-neghbor degree (ANND) s much hgher thn the verge node degree nd hs ncresed slghtly over tme. Ths dfference ndctes tht the centrl, hghly connected countres re ncresngly extendng those reltons towrds poorly-connected countres. In other words, the utomotve network s grdully expndng round the world, ncludng new countres tht trdtonlly dd not use to ctvely tke prt n the network. Ths s lso confrmed by the moderte lthough grdully dsssorttve nture of the bnry network nsofr s the correlton between ANND nd node degree s not very hgh (Fgure 6). The drectonl nlyss rtfes ths dsssorttvty. Nevertheless, when the weghted network s consdered, the correlton between node strength nd the verge 19

20 nerest-neghbor strength (ANNS) s negtve nd ncresng but frly wek n mgntude (Fgure 7). Ths mens tht prtners of countres wth ntense reltonshps do not necessrly hve ntense trde lnks themselves. In other words, not ll countres n the network hve strengthened ther lnks to the sme degree; only one group of countres hs ntensfed ther flows. Addtonlly, the non-correlton between the node degree nd the weghted verge nerest-neghbor degree (WANND) ndctes tht well-connected countres prtners do not necessrly hve ntense trde lnks wth ll ther prtners. Tht s to sy tht wht we perceve s n ncpent strtegy n whch by expndng ther producton networks to new, low-trde countres, compnes re tryng to tke dvntge of scle economes nd lower lbour costs, especlly for the most stndrdzed nd low dded-vlue P&C, whle the bulk of P&C s stll produced nd sold by smll number of centrl countres. Wth ths strtegy, compnes re tryng to mnmze the sptl dfferentton for those ctvtes tht re common to the whole rnge of products tht they sell nd tht re concentrted n clustered loctons ner to the compnes hedqurters nd trdtonl lrge mrkets. At the sme tme, they re tryng to dfferentte ther products to better ft ther consumers preferences nd mnmze trnsportton costs, so they re choosng to locte some prts of the process close to the fnl mrkets. Fgure 6. Correlton between ANND nd Node Degree for P&C WATN (1996 nd 2009) ,5 2,5 2 2 log(annd) 1,5 1 log(annd) 1,5 1 0,5 CC= * CCLow= CCUp= ,5 1 1,5 2 2,5 log(degree) 0,5 CC= * CCLow= CCUp= ,5 1 1,5 2 2,5 log(degree) Source: uthors clculton, bsed on UN COMTRADE. CCLow nd CCUp re the correlton coeffcents t 5% nd 95% confdence ntervls. Fgure 7. Correlton between ANNS nd Node Strength for P&C WATN (1996 nd 2009) ANNS CC= * CCLow= CCUp= ANNS CC= * CCLow= CCUp= Strength Strength Source: uthors clculton, bsed on UN COMTRADE. CCLow nd CCUp re the correlton coeffcents t 5% nd 95% confdence ntervls. 20

21 Therefore, the nlyss of the second-order relton mesures ndctes tht even together wth domnnt gglomerton forces, the serch for new nd remote mrkets wth hgh potentl n terms of demnd tht would llow compnes to vod mrket sturton n trdtonl mrkets re ctng s powerful dsperson force. In the next secton we nlyse these centrfugl forces n more detl. When we nlyse the composton of the WATN centre n 2009 nd compre t wth tht of 1996, we observe tht, lthough the promnent countres n the networks hve mntned ther mportnce wthn the WATN, sgnfcnt new plyers hve entered tht hve redstrbuted the uto mrket. In ths ven, Chn hd emerged overwhelmngly n the P&C network centre n 2009: t hd rsen to the top postons n ll centrlty ndexes. Not only hd t ncresed ts lnks spectculrly over the perod but those lnks were strong enough to overtke Germny n outstrength (see Tble 3). It s lso worth mentonng the escltng behvour of Kore. Ths country ws lredy hghly connected n 1996 lthough ts ntensty ws wek, but by 2009 ts numerous trde lnks hd trnslted nto hgh export ntensty. Addtonlly, some Estern Europen countres, such s Hungry, Polnd, nd the Czech Republc hve lso gned mportnce n the P&C export network, forgng numerous nd ntense trde lnks. Note tht Polnd nd Hungry were mong the most mportnt ntermedry economes n the network n 2009 nd dsply two of the hghest weghted hub-centrlty scores (Tble 2). Therefore, n spte of ths process of relocton towrds new lrge nd/or low-cost perpherl countres nd the loss of producton nd trde flows mong some core nd trdtonl perpherl countres, we cnnot sy tht we re wtnessng dendustrlzton process n the sector à l Kuznets. When frms set up ther opertons n new plces, they rrely bndon ther home bses completely; they remn rooted there to serve the home mrket nd to supplement offshore producton through exports. Intermedte trnsportton costs nd locton hysteress, plus the weght of hstory, ply promnent role n keepng compnes ted to the sme country (or regon) for long perods of tme. The exstence of longstndng regonl clusters tht try to obtn the mxmum gglomerton rents s cler evdence of ths. Wht hs hppened s tht these new groups of countres hve joned the old clusters nd the ltter hve creted new lnks wth them, expndng the scle nd scope of the network. In 2009, some of these countres were prt of the densest nd most cohesve group of exporters, s reveled by the k-core nlyss (Tble 1). Addtonlly, we should note tht only lrge (huge n some cses) emergng mrkets wth n ntermedte level of development or economes tht re very close to nd/or ntegrted n lrge mrkets re beng ncluded n the more extensve nd ntegrted uto network. In ths sense, the mrket effect hs mntned the trdtonl mblnces n the sptl dstrbuton of the utomotve ndustry. 21

22 Ths reorgnzton of the uto mrket tht s blncng gglomerton nd dsperson forces s observed n ll fctorl P&C networks (Tble 5 nd 6). Two common dynmcs, regrdless of fctorl ntensty, hve been observed. The frst s n ntense trnsfer of ctvty from the Unted Sttes nd Jpn to new economes, mnly Asn countres. As long s the North Amercn nd Asn networks re closely lnked, the movement of ther respectve centrl countres hs resulted n both regonl networks experencng prllel trnsformtons. Whle ths strtegy s hghly typcl of Amercn utomkers, whch tend to systemtclly brek reltonl tes fter the necessry collbortve engneerng work wth ther supplers hs been ccomplshed nd very frequently open re-bd processes n n effort to lower nput costs, t sgnls profound chnge n the strtegy of Jpnese utomotve compnes, whch hve trdtonlly been hghly reluctnt to move ther producton brod nd for whom predtory suppler swtchng used to be lmost unherd of (Sturgeon et l., 2008). In fct, ths outsourcng process hs tken plce n Jpn lter nd less ggressvely thn mong North Amercn nd even Europen crmkers. Nevertheless, n recent yers, Jpnese compnes hve been further expndng ther lredy-hgh locl cpcty n North Amerc nd Europe nd hve relocted ther plnts to serve loclly Chn, other South-Est Asn countres, nd other developng countres (Shmokw, 2010). As result of those movements, over the perod nlysed, Kore nd Chn hve hosted mportnt uto multntonls tht hve mde them pure producers nd exporters of P&C (see Tble 4). Both countres re mong the fve countres wth the hghest weghted hub-centrlty ndex (Tble 2). Kore s lso consoldtng ts poston n the globl network s n ssembler nd exporter of fnl goods, wheres gven Chn s huge domestc mrket, for the tme beng most of the P&C t produces nd mports re ssembled nsde the country nd trgeted t stsfyng ts own demnd. Nevertheless, the hgh number of trde lnks tht the country s cretng leds us to expect the export mrket to be future gol of the ssemblers settled n Chn. Fgures for nstrength n Tble 3 nd mport speclzton ndexes (see Tble 4) ndcte tht the two Asn countres (nd lso Jpn) reltvely mport nd re-mport very low mounts of components, ttchng mportnce to the domestc component ndustry, whch hs trdtonlly been hghly protectve (Ng et l., 2007). The second dynmc s Germn-led extenson of the Europen networks mnly towrds the new EU members (lso to Chn). Estern Europen countres re comng to the fore n the utomotve network by trnsformng mported P&C nto other downstrem P&C, whch re ether exported drectly for ssembly brod or re ssembled domestclly nto fnl goods nd then exported from ther terrtores. Ths s clerly the strtegy of the Czech Republc. Other countres, such s Hungry, mnly trnsform mported P&C nto hgher dded-vlue P&C, whch re re-exported bck for ssembly. 22

23 Tble 5. Mn Destnton nd Orgns of Automotve P&C. Centrl Countres n Automotve Network Automotve Totl P&C Germny Jpn USA Exports Import Export Import Export Import UK 13,0% FR 8,6% FR 12,9% CZ 10,2% US 37,1% CHN 20,6% US 35,2% CHN 43,7% CA 46,3% CA 35,9% JP 28,2% MX 24,8% FR 10,1% ES 7,1% AT 12,3% AT 8,8% TH 9,6% US 20,4% DE 9,1% KO 9,3% MX 18,5% MX 25,4% CA 24,0% CHN 22,9% B&L 8,5% UK 6,8% IT 9,7% HU 8,5% UK 4,6% TH 7,0% CHN 8,4% TH 8,1% JP 4,6% CHN 3,3% MX 21,8% CA 12,4% ES 8,2% US 6,7% UK 9,6% FR 8,0% ID 4,2% DE 4,0% SE 6,6% US 7,1% KO 2,9% DE 3,2% DE 5,9% JP 10,7% US 7,2% CHN 6,5% ES 7,4% PO 7,8% DE 3,9% KO 3,7% TH 5,9% DE 6,4% DE 2,3% UK 2,6% BR 2,3% KO 10,3% IT 6,4% AT 5,8% JP 6,3% IT 7,2% HK 3,7% CA 3,4% PH 5,7% PH 4,5% UK 2,2% JP 2,1% FR 2,2% DE 5,6% AT 5,8% B&L 5,3% US 4,5% UK 5,6% CA 3,5% UK 2,8% MY 3,6% ID 4,4% AU 2,0% AU 2,0% CHN 2,2% BR 1,3% SE 5,0% IT 5,2% HU 4,4% CHN 4,8% KO 3,4% MX 2,6% KO 3,5% MY 2,1% BR 1,6% VE 1,8% UK 2,1% UK 1,2% NL 4,1% CZ 4,9% CZ 3,6% ES 4,6% SG 2,8% ID 2,5% FI 3,2% FR 1,8% AT 1,4% BR 1,6% KO 1,6% FR 1,1% CH 2,2% PO 4,7% PT 3,5% SK 3,9% AU 2,6% BR 2,5% UK 2,9% UK 1,8% HK 1,2% FR 1,6% IT 1,5% IT 1,1% PT 1,9% HU 3,9% B&L 3,4% JP 3,3% CHN 2,4% FR 2,4% IT 2,3% MX 1,5% B&L 1,2% KO 1,3% SE 0,8% TH 1,0% MX 1,9% MX 3,4% NL 2,7% RO 3,1% B&L 1,6% AE 2,0% ID 2,1% NL 1,2% FR 1,2% SG 1,1% TH 0,7% MY 0,7% Argentn (AR); Austrl (AU); Austr (AT); Belgum-Luxembourg (B&L); Brzl (BR); Cnd (CA); Chn (CHN); Colomb (CO); Czech Rep.(CZ); Denmrk (DK); El Slvdor (SV); Fnlnd (FI); Frnce (FR); Germny (DE); Hondurs HN); Hong Kong (HK); Hungry (HU); Indones (ID); Isrel (IL); Itly (IT); Jpn (JP); Mlys (MY); Mexco (MX); Netherlnds (NL); Pnm (PA); Phlppnes (PH); Polnd (PL); Portugl (PT); Kore (KO); Romn (RO); Russn F. (RU); Sud Arb (SA); Sngpore (SG); Slovk (SK); Sloven (SI); Spn (ES); Sweden (SE); Swtzerlnd (CH); Thlnd (TH); Tuns (TN); U.A. Emrtes (AE); Unted Kngdom (UK); USA (US) nd Venezuel (VE). Source: uthors clculton, bsed on UN COMTRADE 23

24 Tble 6. Prts nd Components Automotve Subnetworks Mnstrem Drven Prts nd Components Network Outdegree Outstrength Indegree Instrength Outdegree Outstrength Indegree Instrength Chn Germny Jpn USA Itly Kore Frnce UK Belg.& Lux Thlnd Netherlnd Polnd Spn Czech Rep Mexco Cnd Cptl Intensve Prts nd Components Network Germny Jpn Chn USA Frnce Itly UK Kore Spn Belg.& Lux Polnd Sweden Czech Rep Mexco Cnd Lbour Intensve Prts nd Components Network Chn Germny Jpn Itly USA Frnce UK Polnd Belg.& Lux Czech Rep Austr Mexco Spn Hungry Cnd Slovk Technology Drven Prts nd Components Network Chn Kore USA Germny Hungry Ind Fnlnd Jpn Frnce UK Sweden Mexco Spn Austr Polnd Cnd