Industrial agglomeration externalities, city size, and regional economic development: Empirical research based on dynamic panel data of 283 cities and GMM method

Abstract

Local governments have long been ardently pursuing the industrial specialization effect (MAR externalities) and industrial diversification effect (Jacobs externalities). Such a pursuit has resulted in severe distortion of resource allocation and negative effect on sustainability of local economic development. Regarding the effect from both MAR and Jacobs externalities on local economic development existing literature records notable disputes. Therefore, for local economic development, one important issue is which externality (MAR or Jacobs) can better bring the effect into play. By studying a panel data of 283 Chinese cities from 2003 to 2012 and applying dynamic plane data GMM method, this paper conducted a regression analysis of the relationship among industrial agglomeration externalities, city size, and regional economic development. The result indicates that with regard to the whole nation, MAR externalities are conducive to regional economy development whereas Jacobs externalities will, to an extent, restrain regional economic development. As regards eastern, middle, and western regions, MAR externalities are conducive only to the economic development of the eastern region; their effects on middle and western regions are insignificant. Moreover, the interaction item between MAR externalities and city size has a significant negative synergistic effect on national economic development and a certain acceleration effect on eastern region as well as a strong negative synergistic effect on the middle region and an insignificant effect on the western region. The interaction item between Jacobs externalities and city size has a positive synergistic effect on only the middle region and has an insignificant synergistic effect on both eastern and western regions. Capital stock and labor input have significant accelerating effects on GDP growth per capita of Chinese cities, whereas material capital and labor input remain primary driving forces for Chinese local economic development. Furthermore, human capital contributes to accelerating urban economic development, whereas government intervention restrains urban economic development.

Influence Mechanism of High-Tech Industrial Agglomeration on Green Innovation Performance: Evidence from China

“…Cheng et al (2016) [47] believe that after the development of high-tech industry agglomeration to a certain extent, its negative externalities will gradually emerge, and environmental pollution will be further aggravated. Dong et al (2020) [15] believe that industrial agglomeration leads to the increase of energy consumption and pollution emissions, and the expansion of output also brings pollution agglomeration. However, there is also a view that the relationship between industrial agglomeration and green innovation is uncertain.…”

“…It will lead to the expansion of industry and the increase of energy consumption, accompanied by the increase of pollutant emissions, thus aggravating the agglomeration of environmental pollution [12,14]. However, some scholars believe that the positive externalities of high-tech industrial agglomeration are greater than the negative externalities [12,15]. Under these positive externalities, unnecessary waste of resources is reduced, and green innovation performance is improved.…”

Influence of Different Industrial Agglomeration Modes on Eco-Efficiency in China

“…Henderson [ 21 ] and Klein and Crafts [ 22 ] show that the specialized agglomeration effect is more significant than the diversified one in promoting American manufacturing industry development. Zhu et al [ 23 ] also suggest that specialized agglomeration is beneficial to economic development using data on Chinese cities, while diversified agglomeration hinders economic development to a certain extent. Other scholars find that both specialized and diversified agglomeration promote economic growth significantly.…”

Developing Methods to Assess and Monitor Cluster Structures: The Case of Digital Clusters

“…Marshall (1890) was the first to address this topic; he studied the formation of groups comprising industrial enterprises in certain geographic locations, which led to an increase in labor productivity and economic development. Relying on this work and its extensions, today's researchers delve into the economy of agglomeration or co-location to assess the efficiency of cluster structures (Zhu et al, 2017;Fracasso and Vittucci Marzetti, 2018). On the other hand, research dedicated to the exploration and assessment of the economy in view of competition and diversification found more evidence of their positive influence on regional economy (Caragliu et al, 2016).…”