000147879 001__ 147879
000147879 005__ 20250109162738.0
000147879 0247_ $$2doi$$a10.1080/17421772.2021.2012584
000147879 0248_ $$2sideral$$a125681
000147879 037__ $$aART-2022-125681
000147879 041__ $$aeng
000147879 100__ $$0(orcid)0000-0001-8215-3227$$aJiménez, Sofía$$uUniversidad de Zaragoza
000147879 245__ $$aThe geographical and sectoral concentration of global supply chains
000147879 260__ $$c2022
000147879 5060_ $$aAccess copy available to the general public$$fUnrestricted
000147879 5203_ $$aDue to international fragmentation, production increasingly occurs in global supply chains (GSC). The common belief is that this leads to more specialization, which implies more concentration of imports and exports over time. In this paper, we empirically test this hypothesis by analysing the geographical and sectoral concentration of GSC over the period 1995–2011. We adapt the traditional Herfindahl’s concentration indexes to a multi-regional input–output framework. Taking the information on intersectoral and interregional linkages into full account gives the concentration indexes of GSC. The indexes are at different aggregation levels, which enables us to examine both geographical and sectoral concentration patterns. After that, we analyse the effect a country’s geographical and sectoral concentration on its gross domestic product (GDP) per capita. Our findings are: an increase of geographical and sectoral concentration of GSC from 1995 to 2011; a growing role in global production chains played by China and other Asian countries; less concentration for European Union countries; a significant positive effect of geographical concentration on GDP per capita; and a significant negative effect of sectoral concentration.
000147879 536__ $$9info:eu-repo/grantAgreement/ES/DGA/S40-20R$$9info:eu-repo/grantAgreement/ES/MCINN/PID2019-106822RB-I00
000147879 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
000147879 590__ $$a2.3$$b2022
000147879 591__ $$aECONOMICS$$b169 / 380 = 0.445$$c2022$$dQ2$$eT2
000147879 592__ $$a0.626$$b2022
000147879 593__ $$aEconomics, Econometrics and Finance (miscellaneous)$$c2022$$dQ1
000147879 593__ $$aStatistics, Probability and Uncertainty$$c2022$$dQ2
000147879 593__ $$aGeography, Planning and Development$$c2022$$dQ2
000147879 593__ $$aEarth and Planetary Sciences (miscellaneous)$$c2022$$dQ2
000147879 594__ $$a4.9$$b2022
000147879 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion
000147879 700__ $$aDietzenbacher, Erik
000147879 700__ $$0(orcid)0000-0003-3113-1698$$aDuarte, Rosa$$uUniversidad de Zaragoza
000147879 700__ $$0(orcid)0000-0001-9521-4156$$aSánchez-Chóliz, Julio$$uUniversidad de Zaragoza
000147879 7102_ $$14000$$2415$$aUniversidad de Zaragoza$$bDpto. Análisis Económico$$cÁrea Fund. Análisis Económico
000147879 773__ $$g17, 3 (2022), 370-394$$pSpat. Econ. Anal.$$tSPATIAL ECONOMIC ANALYSIS$$x1742-1772
000147879 8564_ $$s382301$$uhttps://zaguan.unizar.es/record/147879/files/texto_completo.pdf$$yPostprint
000147879 8564_ $$s1744469$$uhttps://zaguan.unizar.es/record/147879/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint
000147879 909CO $$ooai:zaguan.unizar.es:147879$$particulos$$pdriver
000147879 951__ $$a2025-01-09-14:41:06
000147879 980__ $$aARTICLE