数据流空间视角下知识溢出的内生经济增长机制

郑安邦　冯华

（北京交通大学经济管理学院）

内容提要：数据流空间是数字经济时代非竞争的数据在各网络节点之间不断复制共享与往复传输所形成的虚拟空间场域。本文基于两部门的内生经济增长模型，将数据视为研发活动的“副产品”，分析有数据流动参与的内生经济增长机制；继而使用社会网络分析方法，验证发现中国的数据流空间网络结构呈现“核心-外围”特征，数据流空间中的数据流动联系弥补了现实空间的距离联系的不足。进一步，本文利用2014—2020年面板数据，构建空间杜宾模型对数据流空间中知识溢出对经济增长的促进效应进行实证分析。结果显示，在数字经济时代，虚拟的数据流空间能够成为知识溢出的新载体，研发活动所产生的知识溢出以数据流动的方式体现，促进了经济增长。　　

　　关键词：数据；流空间；知识溢出；内生经济增长；数字经济；“核心-外围”特征

　　作者简介：郑安邦，北京交通大学经济管理学院博士研究生，北京，100044；冯华，北京交通大学经济管理学院教授、博士生导师，通信作者。

　　基金项目：北京市社会科学基金重点项目“北京全球数字经济标杆城市建设研究”（22JJA003）

　　引用格式：郑安邦,冯华.数据流空间视角下知识溢出的内生经济增长机制[J].经济与管理研究,2024,45(2):3-20.DOI:10.13502/j.cnki.issn1000-7636.2024.02.001.

　　

　　

Endogenous Economic Growth Mechanism of Knowledge Spillovers from the Perspective of Space of Data Flow

ZHENG Anbang, FENG Hua

(Beijing Jiaotong University, Beijing 100044)

　　

　　Abstract: Wide connectivity and high dynamism are key features of the digital economy, and the reciprocating transmission of data between network nodes constitutes the connection of the space of data flow. Different from previous studies discussing the impact of knowledge spillovers on economic growth in physical space, this paper investigates whether the virtual space of data flow can form a new carrier of knowledge spillover effects and its impact of knowledge spillover effects on economic growth.

　　From the theoretical perspective, this paper regards data as a byproduct of R&D activities, incorporates the knowledge spillover effects of data flow into Romer's endogenous growth model, and derives the endogenous growth mechanism of two sectors with the involvement of knowledge spillover effects in the space of data flow. At the empirical level, this paper constructs a spatial network model of data flow based on the gravity model and uses social network analysis methods to analyze the network structure of the space of data flow. Then, it constructs a weight matrix based on the spatial connectivity strength of data flow, builds a spatial Durbin model, and conducts empirical research using provincial panel data in China from 2014 to 2020.

　　The conclusions are as follows. Theoretical derivation indicates that the knowledge spillover effects generated by R&D activities promote economic growth by utilizing the data flow space as a carrier. This process satisfies Romer's endogenous economic growth mechanism, and the economy converges towards a steady-state endogenous growth path. The empirical results indicate that the network structure of the space of data flow in China exhibits a core-periphery feature, with some provincial-level regions serving as core nodes, supporting the entire space of data flow, and others participating in the division of data flow space by establishing connections with core nodes. The data flow connections in the virtual space simultaneously compensate for the limited distance connections in real space, thereby reflecting a renewed understanding of spatial accessibility.

　　The marginal contributions of this paper lie in three aspects. First, it proposes the definition of the space of data flow, which refers to the virtual spatial field formed by the continuous replication, sharing, and reciprocating transmission of non-competitive data between network nodes in the digital economy era. Second, it describes the core-periphery network structure of space of data flow in China. Third, it breaks through the limitation that knowledge spillover only occurs in real space in previous research and recognizes that the virtual data flow can become another carrier of knowledge spillover effects. It also uses an endogenous growth model to examine the knowledge spillover effects carried by the space of data flow and its impact on economic growth.

　　Keywords: data; space of flow; knowledge spillover; endogenous economic growth; digital economy；core-periphery feature

下载全文