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作 者:刘君洋 朱晟君[1] LIU Junyang;ZHU Shengjun(College of Urban and Environmental Sciences,Peking University,Beijing 100871,China;Peking University-Lincoln Institute Center for Urban Development and Land Policy,Beijing 100871,China)
机构地区:[1]北京大学城市与环境学院,北京100871 [2]北京大学-林肯研究院城市发展与土地政策研究中心,北京100871
出 处:《地理研究》2021年第12期3302-3313,共12页Geographical Research
基 金:国家自然科学基金项目(41971154、41701115);国家自然科学基金重点项目(41731278)。
摘 要:当前时代,中国的出口企业面临出口市场维度和产品维度的两大风险。前者体现为贸易政策不确定性对企业生产组织和出口决策的影响,后者体现为高技术品出口对企业技术水平和生产能力的高要求,其可被纳入GPN 2.0框架中的"监管风险"和"产品风险"两个维度进行分析。本文指出,面对上述风险,企业会寻求集聚分布,以受益于信息溢出效应和生产率效应,从而实施相应的企业策略以抵御风险。本文基于2008—2016年中国海关进出口贸易数据获取企业位置信息,测度企业集聚水平,同时基于非关税壁垒和产品复杂度数据测度企业所面临的监管风险和产品风险。实证结果表明,当企业的出口市场贸易政策不确定性越高、企业所生产的产品复杂度越高,企业在本地越集聚,一定程度上验证了上述假设。本文尝试融合GPN 2.0和经典的集聚理论,对于风险环境下企业空间重构的模式和机制进行定量测度,并给予全球生产网络的空间组织机制更为动态且微观的解释,具有一定的理论和实践意义。Nowadays, China’s export firms face two major risks from export market dimension and product dimension. The former is embodied in the reflection of trade policy uncertainty on firms’ production organization and export decisions, while the latter is embodied in the tough requirements on firms’ technical level and production capacity when they aim at exporting hightech products. Risks mentioned above can be understood as“regulatory risk”and“product risk”in the GPN 2.0 framework. This paper points out that in the face of the above risks, firms will seek local agglomeration in order to benefit from information spillover effect and productivity effect, and launch specific strategies to handle the risks. Based on the data of China Customs Trade Statistics from 2008 to 2016, this paper obtains the location information of firms, measures the agglomeration level of firms, as well as measures the regulatory risks and product risks faced by firms based on data about non-tariff barrier and product complexity.The empirical results show that the higher the uncertainty of the trade policy in the export market and the higher the technical complexity of the products produced by the firm, the more clustered the firms are, which verifies the above hypothesis to a certain extent. This paper attempts to integrate GPN2.0 framework and the classical agglomeration literature, and carries out a quantitative measure on the patterns and mechanisms of firms’ spatial restructuring under risk environment, and presents a more dynamic and micro explanation on the mechanisms of spatial organization of global production network, which has certain theoretical and practical value.
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