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postgraduate thesis: Economic analysis of industrial clustering in China

TitleEconomic analysis of industrial clustering in China
Authors
Issue Date2015
PublisherThe University of Hong Kong (Pokfulam, Hong Kong)
Citation
Yang, X. [杨锡怡]. (2015). Economic analysis of industrial clustering in China. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5610980
AbstractOne of the most striking developments during China’s economic reforms is the emergence of specialized industrial clusters in rural towns and villages with each contributing to a substantial share of the global product market. Different from the concepts of “clustering” or “geographical agglomeration” defined in existing studies, these clusters are developed under the unique institutional constraints to factor mobility and to entrepreneurship in China. Given the shortcomings of existing measurements, I construct an original measure of clustering which indeed can capture the major features from the reality. Based on this measurement, by using a combination of firm-level and county-level datasets from 1998-2007, I systematically test the economic impacts of clustering on regional growth and inequality, and on firm innovation and exporting. Along with the record-breaking growth, income inequality in China has increased so rapidly that China has become one of the most unequal economies in the world. How the development of clusters interacts with local economic growth and inequality, however, is unknown in the literature. Based on panel estimations, I find that industrial clusters, especially strong clusters or those with a more developed non-state sector, can enhance local economic and employment growth. More importantly, the higher growth does not lead to enlarged income inequality. Instead, counties with clusters consisting of a more developed non-state sector will have a substantially lower urban-rural inequality, driven by the increased income of local rural residents. The results stay robust after addressing the endogeneity issues by thepropensity score matching approach and the instrumental variable (IV) regression approach. On the other hand, though China has long been the factory floor that churns out popular gadgets for companies world-wide,the country’s own technology were rarely viewed as leading edge. However, agrowing literature has pointed to the existence of distinctforms of industrial innovationin China that usually involvethe redefinition of existing technologies and the commercialization of new inventions.Given that a large proportion of the country’s manufacturing is concentrated within these specialized industrial clusters, how this clustering environment interacts with industrial innovation and exporting of firms is an important but unanswered question. Using a combination of data from the State Intellectual Property Office Patent Database and the Chinese Manufacturing Firm Survey Database, I find that firms within industrial clusters are more likely to generate patent and this effect is amplified if there is a higher density of firms within the cluster, or if there are state-owned enterprises operating in the cluster. Moreover, firms located in industrial clusters will have a higher probability of exporting, especially if there are more private firms or foreign-invested firms within the clusters. Moreover, this effect of clustering on export is likely to operate through the channel of improved firm productivity. Finally, I use instrument variable regression to address the identification issue and establish causality between clustering and improved firm productivity.
DegreeDoctor of Philosophy
SubjectIndustrial clusters - China
Dept/ProgramEconomics and Finance
Persistent Identifierhttp://hdl.handle.net/10722/221203
HKU Library Item IDb5610980

 

DC FieldValueLanguage
dc.contributor.authorYang, Xiyi-
dc.contributor.author杨锡怡-
dc.date.accessioned2015-11-04T23:11:59Z-
dc.date.available2015-11-04T23:11:59Z-
dc.date.issued2015-
dc.identifier.citationYang, X. [杨锡怡]. (2015). Economic analysis of industrial clustering in China. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5610980-
dc.identifier.urihttp://hdl.handle.net/10722/221203-
dc.description.abstractOne of the most striking developments during China’s economic reforms is the emergence of specialized industrial clusters in rural towns and villages with each contributing to a substantial share of the global product market. Different from the concepts of “clustering” or “geographical agglomeration” defined in existing studies, these clusters are developed under the unique institutional constraints to factor mobility and to entrepreneurship in China. Given the shortcomings of existing measurements, I construct an original measure of clustering which indeed can capture the major features from the reality. Based on this measurement, by using a combination of firm-level and county-level datasets from 1998-2007, I systematically test the economic impacts of clustering on regional growth and inequality, and on firm innovation and exporting. Along with the record-breaking growth, income inequality in China has increased so rapidly that China has become one of the most unequal economies in the world. How the development of clusters interacts with local economic growth and inequality, however, is unknown in the literature. Based on panel estimations, I find that industrial clusters, especially strong clusters or those with a more developed non-state sector, can enhance local economic and employment growth. More importantly, the higher growth does not lead to enlarged income inequality. Instead, counties with clusters consisting of a more developed non-state sector will have a substantially lower urban-rural inequality, driven by the increased income of local rural residents. The results stay robust after addressing the endogeneity issues by thepropensity score matching approach and the instrumental variable (IV) regression approach. On the other hand, though China has long been the factory floor that churns out popular gadgets for companies world-wide,the country’s own technology were rarely viewed as leading edge. However, agrowing literature has pointed to the existence of distinctforms of industrial innovationin China that usually involvethe redefinition of existing technologies and the commercialization of new inventions.Given that a large proportion of the country’s manufacturing is concentrated within these specialized industrial clusters, how this clustering environment interacts with industrial innovation and exporting of firms is an important but unanswered question. Using a combination of data from the State Intellectual Property Office Patent Database and the Chinese Manufacturing Firm Survey Database, I find that firms within industrial clusters are more likely to generate patent and this effect is amplified if there is a higher density of firms within the cluster, or if there are state-owned enterprises operating in the cluster. Moreover, firms located in industrial clusters will have a higher probability of exporting, especially if there are more private firms or foreign-invested firms within the clusters. Moreover, this effect of clustering on export is likely to operate through the channel of improved firm productivity. Finally, I use instrument variable regression to address the identification issue and establish causality between clustering and improved firm productivity.-
dc.languageeng-
dc.publisherThe University of Hong Kong (Pokfulam, Hong Kong)-
dc.relation.ispartofHKU Theses Online (HKUTO)-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.rightsThe author retains all proprietary rights, (such as patent rights) and the right to use in future works.-
dc.subject.lcshIndustrial clusters - China-
dc.titleEconomic analysis of industrial clustering in China-
dc.typePG_Thesis-
dc.identifier.hkulb5610980-
dc.description.thesisnameDoctor of Philosophy-
dc.description.thesislevelDoctoral-
dc.description.thesisdisciplineEconomics and Finance-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.5353/th_b5610980-
dc.identifier.mmsid991014065879703414-

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