3在全球价值链的地位、贸易收益与竞争力分析

1、中国在全球价值链的地位、贸易收益与竞争力分析基于增加值贸易核算方法陈雯赵萍房晶晶内容摘要：本文基于增加值贸易核算方法，利用 1995-2011 年 WIOD 数据库，测算了中国参与全球价值链的程度、所处地位和增值能力，并分析了中国在全球价值链中的贸易收益和竞争力。结果表明，中国在全球价值链分工中处于下游，入世的头几年由于加工贸易的，在全球价值链的地位下降了，而且增值能力也减弱了。随着企业竞争力的逐步增强，加工贸易的升级，中国后几年在全球价值链的地位和增值能力有所上升。随着参与全球价值链程度的深化，中国在全球价值链中的贸易收益持续提高。中国制造业在全球价值链中的竞争力强于服务业，而且所获得的贸易

2、收益也高于服务业。： 全球价值链 贸易收益 竞争力 增加值贸易Chinasition, Trade Revenue and Competitiveness on the Global Value Chains:Anysis Based on Trade in Value Added Accounting FrameworkWen Chen,Zhao JingjingAbstract：Based on the value added trade accounting method，this pr tries to employ 1995-2011WIOD dao measure the degr

3、ee of Chinas participationhe global value chains (GVC) and toyze its GVCition, value added competence, trade revenue and competitiveness on GVC. Theresults showt China kept spelizing in downstream activities.hefew years after enteringo the WTO, Chinas GVCition was getting lower and value added compe

4、tence getting weakerdue to a greater share of prosing trade. In recent years, China has seen an increase in its GVCition and value added competence. With deepening of its participation in the GVC, China hasgained more trade revenue. The results also showt China has stronger competence inmanufacturin

5、g sector compared with servimanufacturing sector.ector, and has also gained more trade revenue from theKey words: global value chains (GVC), trade revenue, competitiveness, trade in value added基金项目：教育部哲会科学研究课题攻关项目“要素成本上升背景下中国外贸中长期发展趋势研究”（13JZD010）；福建省社科规划项目“异质性企业的生产率、出口行为与劳动技能”（2014B106）。作者简介：陈 雯: 女

6、，经济学博士，厦门大学国际经济与贸易系教授、博士生导师。研究方向为国际贸易与产业发展。、房晶晶：厦门大学国际经济与贸易系联 系 人：陈 雯联系地址：厦门大学经济学院国际经济与贸易系。：361005：电子邮箱：w1专题 3：价值链分工与全球生产网Chinasition, Trade Revenue and Competitiveness onthe Global Value Chains: Anysis Based on Trade inValue Added Accounting Framework*Wen CHEN,ZHAO, JingjingAbstractBased on the val

7、ue added trade accounting method，this pr tries to employ 1995-2011WIOD daand too measure the degree of Chinas participationhe global value chains (GVC)yze its GVCition, valueadded competence, trade revenue andcompetitiveness on GVC. The results showactivities. In thefew years after enteringt China k

8、ept spelizing in downstreamo the WTO, Chinas GVCition wasgetting lower and value added competence getting weaker due to a greater share ofprosing trade. In recent years, China has seen an increase in its GVCition and valueadded competence. With deepening of its participationhe GVC, China has gained

9、moretrade revenue. The results also showt China has stronger competenceanufacturingsector compared with service sector, and has also gained more trade revenue from themanufacturing sector.Key words: global value chains (GVC), trade revenue, competitiveness, trade in value addedJEL codes: F10, F14, F

10、40I.roductionSince the implemenion of the export-oriented foreign trade strategy, Chinas foreign tradehasdeveloped so fastt ise the worlds largest country foods trade. However, the resultwas based on the traditional customs sistics, failing to reflect real trade scale. As a major prosingtrading coun

11、try, Chinas prosing trade volume reached 8.65 trillion yuan in 2014, accounting for32.7%1 of total foreign trade volume of the same period. Since traditional trade s istics doesnt* Wen Chen, Professor, Department ofernational Trade and Business, School of Economics, XiamenUniversity, Xiamen, China.:

12、 w;Zhao, MA Student, Department ofernational Trade and Business, School of Economics, Xiamen University, Xiamen, China.:zp1; Jingjing, MA Student, Department ofernational Trade and Business,School of Economics, Xiamen University, Xiamen, China.: k. The research isfunded by the Key Project of ChiMini

13、stry of Education (No. 13JZD010 ) and Fujian Sol ScienceFund Project (NO. 2014B106). The authors are also grateful to Dr. Zhi Wang from United S esernational Trade Commisand Professor Fei Wang from University ofernational Business andEconomics for the data and other professors who gave lectures at 2

14、014 Global Value-Chain Training and Research Workshop./xinwen/2015-01/13/content_2803769.htm.21distinguish prosing trade from total foreign trade, and thus will exaggerate Chinas trade volumeand revenues. With GVC spelization, traditional customs s istics cannot answer the question of“Who produce fo

15、r Whom” (Daudin et al., 2011). And the impact of trade on economic growth and e is not as important as the customs sistical results showed, just like Maurer and Degain in20102 said “What You See is not What You Get”. At the same time, with theensification ofeconomic globalization, theernational spel

16、ization is getting deepern before. Economiccompetition among countriess not onlyhe product level, but also extends to the GVC. Althoughalmost every country has got the opportunity to geto the global market due to extenandexpanof GVC, the GVC participation degree, GVCition, trade revenue and realcomp

17、etitiveness present some differenamong countries. Under the TiVA accounting method, howmuch depth China has participated in GVC? What about its GVCition and trade revenue? Andwhats Chisignificance.real competitiveness on GVC? So a true understanding of the above aspects is of greatTraditional trade

18、s istics is based on the s istical exporting and importing data provided by each countrys customs. Under this accounting framework, for any goods, as long as it enters or leaves a countrys border, it will be regarded as import or export to be calculated. While the TiVA accounting method focuses on a

19、 countrys real value added part on GVC, which is calculated by tracing back acountrys value-added part directly or indirectly embodied in each countrys final consumption (Stehrer,2012; Chen and Li, 2014). Since there iseed to calculateermediate trade separay, the TiVAmethod can avoid the double-coun

20、ting problem which is due to multiple transborder activities ofermediates. Under the TiVA accounting framework, exporting and importing data can reflect acountrys real trade scale. In fact, similar to the idea proed by Daudin et al. in 2011, Grossman andRossi-Hansberg (2008) poed outt if a country h

21、as participated in global supply chains, then thetraditional trade accounting method based on the gross trading volume is not accurate, instead, one should focus on where the value-added embodied in the product comes from and where it is usedfinally. Baldwin and Robert-Nicoud (2010)3 tried toegrate

22、the TiVA concepto goods tradetheories. Mattoo et al. (2011) collated the methods of estimating foreign and domestic value-addedembodied in a countrys exports, and gave some proals toegrate the TiVA accounting methodo the existingernational trade accounting framework. Grossman (2013) s ed the importa

23、nce ofTiVA method from threes of why we need a new theory, what the new theory is andwhether it is effective. The new trade accounting method was also approved by Dean (2013), who maainedt TiVA can avoid resurgence of protectionists, and to promote the formation of a moreopen market.In recent years,

24、 GVC spelization hase one of the key areas receiving great attention ernments of many countries. Koopman et al. (2010)ition indicator to measure a countrys participationfrom academia,ernationalanizations and(KPWW) built GVC_Participation and GVC_degree and itsitioGVC. They also measured the GVC_itio

25、n of 12 sectorch as electricalequipment and metal goods of 24 countries and regions including China, Japan and the United S es,etc in 2009. Backer and Miroudot (2012) measured the GVC_Participation of 55 countries in 2009using KPWW method. Banga (2013) also employed the KPWW indicators toGVC partici

26、pation degree. While Costino (2013) built a general equilibrium myze some countries of GVC productione. Jensen et al.to showt GVC spelization pattern will influence the distribution of global23This p This pr is then published in Journal ofernational Commerce, Economics and Policy in 2012. r is then

27、published in Journal of ernational Economics in 2014.3(2013) studied the relations betn GVC participation and anti-dumsuits. Timmer et al. (2013)built GVCe and Revealed Comparative Advantage (RCA) in GVC indicators toyze thecompetitiveness of European countries. Domestic scholars have also begun to

28、adopt TiVA accountingyze Chinas GVCition and competitiveness.4 Zhang (2013) adopted indicators ofmethod todomestic value-added ratio and sectors openness index toyze Chinas sectorsernationalcompetitiveness based on TiVA method. Nie and Li (2014) employed indicators of GVCe andof RCA in GVC built by

29、Timmer et al. (2013) to measure benefit distribution on GVC ofmanufacturing sector and Chinas competitiveness. Dai (2015)yzed export competitiveness ofChinas service industry using the same RCA in GVC indicator. Fan and Huang (2014) madeysisof Chiindustries value creation and structural change on GV

30、C based on Koopman et al. (2012).Cen (2015)yzed the Chinas participation anditioGVC using KPWW indicators. Liu(2015)yzed Chinas exports value comition and its variation from two dimens of productfunction and embedding function. In fact, when KPWW created GVC_Participation and GVC_itionindicators, Pu

31、re Double Counting (PDC) problem existing in theition of traditional grossexports has not been thought of. Considering the limi ions of KPWW indicators,his pr, wetried to make some improvements based on gross exportsition framework proed by Wanget al. (2013), and employed the revised indicators to m

32、easure Chinas GVC participation, GVCvalue-added competence, trade revenue and competitiveness on GVC.ition,The contributions of this pr are as follows:, its thepr toyze Chinas GVCparticipation, GVCition, value-added competence, trade revenue and competitiveness from theof TiVA accounting framework i

33、n one pr. Although some scholars have measuredChinas GVC participation and GVCition (Nie and Li, 2014; Cen, 2015) and Chinascompetitiveness on GVC (Zhang, 2013; Dai, 2015), they didnt conduct an overallysis and themethod adopted remains open to question. Whats more, previous studies were mainly base

34、d on traditional customs trade data and indicator ch as Export Sophistication Index (Qiu et al., 2012; Yu and Deng, 2014; Lu, 2014), Export Price (Shi, 2010; Hu and Song, 2013) and RCA or TradeCompetitiveness Index (TCI) (Zhang and Sun, 2006; Wen and Xian, 2009) 5. Second, KPWWindicators ignore the

35、factst domestic value added embodied in re-export is also involved in GVCproduction, and foreign value added also contains PDC. Considering this, we made someimprovements. Third,his pr, we built EXGRDVA indicator to present domestic value added ratioin a countrys gross exportss, and use it toyze a c

36、ountrys value-added competence on GVC.Besides, sinceadded embodiede indicator proed by Timmer et al. (2013) contained domestic valuehe final consumption produced by home country which doesnt belong to GVCproduction, we built a new GVCe indicator. The last contributionshat weyzed thevariation of Chim

37、anufacturing sectors competitiveness over 1995-2011 and made a contrastamong 40 countries and regions based on the new RCA in GVC.mployed the WIOD Database, which contains trade data of 35 sectors from 40 countries and regions (including EU 27 countries, Turkey, Canada, the United S es, Mexico, Japa

38、n, South Korea, Australia, Brazil, Russia, Indonesia and China) and the Rest of the World (RoW) over1995-2011. The total trade volume of these 40 countries and regions occupied 85%6 of the world GDP.45We have consulted Zhi Wang (one of the co-authors of KPWW), and he saidt their indicators are under

39、 revi.Other studies adopted value-added ratio (and Huang, 2013) and industry upstreamness (Ju and Yu, 2014) toyzeChinas GVCsition. The industry upstreamness was proed by Fally (2011) and Antrs (2012), and it is measured byweighted average distance betn a sector and the final goods.6This data is esti

40、mated by authors based on related data from UN COMTRADE Database.4The rest of this pr isanized as follows: In section 2, we build indicators ofGVC_Participation, GVC_ition and value-added competence, and employ these three indicators toyze Chinas GVCition from national and sectoral level. In section

41、 3,e indicator isset up to show Chinas trade revenue on GVC and its variation. Section 4 shows Chinas manufacturing sectors competitiveness through the indicator of GVC competitiveness. And section 5 providesremarks and policy suggestions.II.ysis of Chinas GVCition1. Indicator Measurementition1.1 Gr

42、oss exportsWang et al. (2013)ed the gross exportso four parts (DVA, RDV, FVA and PDC). Detailsare as follows (taking 3 countries and N sectors as a case):Define Vr as a 1 N direct value-added coefficient vector with the subscript representing country.Each element of Vr shows the share of direct dome

43、stic value addedhe total output, which equals 1minus theermediate share from all countries (includingermediates produced at home). Define V .V0Vs000rV 00Vas a 3 3N direct domestic value-added matrixtMultiplying the directvalue-added matrix by Leontief inverse L, we get a 33N value-added share matrix

44、 (VAS):VAS =VL= In equation (1),V LV LV Lr rrr rsr rtVs LsrVs LssVs Lst(1)V LV LV Lt trt tst ttthe sum of domestic andforeign value added shares in a countrys finalle, we have the following relationship:consumption equals to 1. Take country r as an exVr Lrr Vs Lsr Vt Ltr Iwhere I is a identity matri

45、x.(2)Wefurthere gross exportso three parts:o final demand andermediate goods, and the latter can beed Frs Ars Xs Frs Ars Xss Ers(3)where Frs is the final goods of country r exporting to country s, Ars is the N Nermediates inputermediates produced in country r used in country s. Xs is N 1 totalcoeffi

46、cient matrix, meaningoutput vector, thusArsXst is country rArsXssrepresents country rermediates exports absorbed by direct country s,ermediates exports prosed by country s and re-exported to third country t, andArsXsr represents country rermediates exports prosed by country s and finally returned to

47、 countryr. Xsk (k=s,t,r) is country s output absorbed by country k, and it is the arithmetic product of Leontiefinverse L and final demand matrix F.Toe gross exports, we need toe ArsXs according to where they are finallyt X=LF. And final demand is the sum of eachabsorbed. The Leontief input-output m

48、ethod shows5countrys final demand,t is F=Fs+Fr+Ft. So:Xs Lss Fs Lsr Fr Lst Ft(4) (L F L F L F ) (LF L F L F ) (LF L F L F )ss ssss srss stsr rssr rrsr rtst tsst trst ttEquation (4) illustrates the detailedition of country s total output according to the flowof final goods. Here(k= s, r, t) denotes c

49、orresponding block matrix of the Leontief inverse L.Further we get；Lskt Ars Lsts Ars Lsrt Ars Xs Ars Lss(5)On the other hand, according to X=AX+F, we can get:Xs Ass Xs Asr Xr Ast Xt Ass Xs Fss Es*t(6) 1 A 1 A1 E1From equation (6) we can get XF)1. Denote B=( ssssssssss*as the local Leontief inverse m

50、atrix7. Then theermediate exports from country r to s can beedo two parts according to where it is consumed:Ars Xs Ars Bss Fss Ars Bss Es*(7)According to equation (2), (VrLrr)T#Ers + (VsLsr)T#Ers + (VtLtr)T#Ers = Ers8. Combined withequation (3), (5) and (7), the core equation tocan be derived:e a co

51、untrys gross exportso sixteen termsE (V L )T #( f A X ) (V L )T #( f A X ) (V L )T #( f A X )rsr rrrsrs ss srrsrs st trrsrs s (V L )T # f (V B )T # A X (V L V B )T # A Xr rrrsr rrrs sr rrr rrrs s(V L )T # f (V L )T # A X (V L )T # f (V L )T # A Xs srrss srrs st trrst trrs sL f ) (V B )T #L f ) (V B

52、)T # A (V L )T # f + (V B )T # AAL f )r rrrsr rrT1rs ss ssr rrrs st ttr rrrs ss stT2T3T4(V B )T #( Af ) (V B )T #( Af ) (V B )T #( ALLLf )r rrrs s tsr rrrs ss srr rrrs st trT5T6T7(V B )T #( Af ) (V B )T # A L ( f f ) V ( L B )T #( ALr rrrs srrrr rrrs srrsrtT9rrrrrT10rsT8(V L )T # f (V L )T #( A Bf )

53、 (V L )T #( A B E )s srrss srT11rs ss sss srrs ss s*T13T12(V L )T # f (V L )T #( A Bf ) (V L )T #( A B E )t trrst trT14rs ss sst trrs ss s*T15T16o five categories according to the(8)ermediates flow andThese sixteen terms can be classifiedwhere final goods are consumed.category FDV represents domesti

54、c value added embodied in7Local inverse matrix refers to the total inpoefficient matrix of home countrys sectors. Its difference from inverse matrixcan be foundhe appendix D9 of Wang et al. (2013).8Sign “#” represents element-wise matrix multiplication operation, which is different from direct matri

55、x multiplication.6importing countries final consumption or domestic-value added in the final goods exports. FDV iscomed of T1. Second category IV, including T2, T3, T4 and T5, represents domestic value added intheermediates used by other countries for production of final goods consumed by foreign co

56、untries.t is domestic value addedheermediates exports for other countries consumption. The sum ofthetwo categories forms domestic value-added exports absorbed abroad (DVA). Third categoryRDV or re-imported value-added, including T6, T7 and T8, refers to domestic value added in theermediate exports u

57、sed by direct importers to produce exportst are shipped back to the sourcecountry and are absorbed at home. The sum of DVA and RDV forms domestic value added (DV).Fourth category FVA, including T11, T12, T14 and T15, represents foreign value-added in thecountrys exportst are finally absorbed abroad.

58、 The last category Phows pure double-countingpart due toermediates trade. It contained domestic value-added double-counting part (DDC) andforeign value-added double-counting part (FDC), and is comed of T9, T10, T13 and T16. The sumof foreign value-added double-counting in FVA and PDC equals foreign

59、value-added in the grossexports (FV).1.2 GVC_Participation Indicator and GVC_ition IndicatorIn order to measure a countrys GVCition (upstream or downstream) and its participation degree,KPWW (2010) built GVC_Participationr and GVC_comparison betn the share of a countrysitionr indicator. GVC_itionr i

60、ndicator makesermediates exportsfor other countries exportsproduction andt of the countrysermediates imports. If a countryshe upstream GVC, thenits participation pattern is to provide inputs, materials (such as Russia),ermediates (such as Japan),or both of them for other countries exports production