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Globalization, socio-institutional factors and North-South knowledge diffusion: Role of India and China as Southern growth progenitors

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dc.contributor.authorDas, Gouranga Gopal-
dc.date.accessioned2021-06-23T07:41:45Z-
dc.date.available2021-06-23T07:41:45Z-
dc.date.created2021-01-21-
dc.date.issued2012-05-
dc.identifier.issn0040-1625-
dc.identifier.urihttps://scholarworks.bwise.kr/erica/handle/2021.sw.erica/33065-
dc.description.abstractNexus between income inequality and technology capture is explored in a global CGE model to explore the ricochet effect of technology transmission and its capture. In particular, the model shows that exogenous technology shock from developed North, vehicled via trade, transmits to developing Souths and induces productivity growth. This spillover capture, aided by human capital based adoptive capability, better governance and institution, causes increase in income and welfare and subsequently, leads to decline in income inequality. Dynamism of Southern Engines of Growth - India and China - caused them to emerge as 'core' South. Thus, triangular innovation diffusion between dynamic and peripheral South is also simulated to show how the backward or peripheral South could catch up via South-South Cooperation in a declining North-South trends in trade. This accrual of benefits could lead to sustained productivity growth and consequential relief of incidence of poverty in low-income countries. (C) 2011 Elsevier Inc. All rights reserved.-
dc.language영어-
dc.language.isoen-
dc.publisherElsevier BV-
dc.titleGlobalization, socio-institutional factors and North-South knowledge diffusion: Role of India and China as Southern growth progenitors-
dc.typeArticle-
dc.contributor.affiliatedAuthorDas, Gouranga Gopal-
dc.identifier.doi10.1016/j.techfore.2011.05.013-
dc.identifier.scopusid2-s2.0-84858286417-
dc.identifier.wosid000303087700003-
dc.identifier.bibliographicCitationTechnological Forecasting and Social Change, v.79, no.4, pp.620 - 637-
dc.relation.isPartOfTechnological Forecasting and Social Change-
dc.citation.titleTechnological Forecasting and Social Change-
dc.citation.volume79-
dc.citation.number4-
dc.citation.startPage620-
dc.citation.endPage637-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassssci-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaBusiness & Economics-
dc.relation.journalResearchAreaPublic Administration-
dc.relation.journalWebOfScienceCategoryBusiness-
dc.relation.journalWebOfScienceCategoryRegional & Urban Planning-
dc.subject.keywordPlusDEVELOPMENT SPILLOVERS-
dc.subject.keywordPlusTRADE-
dc.subject.keywordPlusTECHNOLOGY-
dc.subject.keywordPlusIDEAS-
dc.subject.keywordPlusPRODUCTIVITY-
dc.subject.keywordPlusINEQUALITY-
dc.subject.keywordPlusPOVERTY-
dc.subject.keywordAuthorSpillover-
dc.subject.keywordAuthorHuman capital-
dc.subject.keywordAuthorGovernance-
dc.subject.keywordAuthorHub-and-spokes-
dc.subject.keywordAuthorInnovation and absorptive capacity-
dc.subject.keywordAuthorGini-
dc.subject.keywordAuthorPoverty gap-
dc.identifier.urlhttps://www.sciencedirect.com/science/article/pii/S0040162511001363?via%3Dihub-
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