Can the internet reshape the national city size distribution? Cross‐country evidence

Abstract

This paper examines the effect of the internet on city size distribution at a global level based on city identification in nearly 100 countries. The results show that the internet first promotes the decentralization of the national city size distribution and then promotes the concentration with an increase in the internet penetration rate. These results differ from those found in the existing literature and help deepen the understanding of the internet's impact on city size distribution by providing new evidence with more reliable data and unified city definitions. The findings also have important policy implications for predicting population distribution and planning human habitations at the national level.

Information communication technology and manufacturing decentralisation in China

“…We employ an IV‐GMM estimation technique to estimate the models using a combination set of internal (lagged values of ICT) and external (the predicted ICT value) instrumental variables, to control for the reverse causality and alleviate potential bias. Lagged values of ICT arise from our long time series of data, and the external instrumental variable is based on a logistic model of technology diffusion, inspired by the work of Griliches (1957) and abundant subsequent research (Czernich, Falck, Kretschmer, & Woessmann, 2011; Geroski, 2000; Wang, Sun, Li, & Zhang, 2021). It is widely confirmed that the diffusion of new technologies could be perfectly described through a logistic curve, as follows, and thus used the logistic function to construct IV for ICT.…”

“… where is the ICT level; , , and represent the saturation level of ICT, the diffusion speed of ICT and the inflection point of the diffusion progress, respectively; is an error term; is a linear function of the ICT level of the initial year (we set the year of 2000 as the initial year, named ); is the inflection point, where the diffusion speed of the logic curve reaches the maximum. As the parameters in the logistic function are exogenous, we could believe that the predicted values of (that is, ) may be a valid IV which satisfies the exogeneity requirements (Wang, Sun, Li, & Zhang, 2021).…”

Big in the neighbourhood: Identifying local and regional centres through their network position

“…There have been numerous efforts to rank settlements objectively, based on their relative global or national sizes, mainly focusing on city size distribution (see e.g. Gabaix, 1999; Wang et al, 2021) and returns to scale (see e.g., Bettencourt et al, 2007). Other classification attempts focus on global or continental city networks (Hall, 2004; Taylor & Derudder, 2016).…”

The New Geography of Manufacturing in China: The Internet and Manufacturing Agglomeration

“…On the one hand, the Internet facilitates firms to identify market entry opportunities by improving the information matching of the industrial chain [17][18][19], thus enhancing the centripetal force of agglomeration. On the other hand, the Internet allows for better alignment of supply and demand on online platforms by improving the matching of product market information [20], thereby diminishing the importance of geography agglomeration and leading to dispersion. Thirdly, the innovation effect of the Internet acts as a centripetal force for agglomeration.…”

“…Compared with the previous literature, the contribution of this paper is mainly threefold. First, we provide new evidence that the Internet affects the spatial layout from the perspective of manufacturing agglomeration, while most of the existing literature focuses on the role of the Internet on the overall spatial structure [1,10,20,26]. However, these studies ignore the industry heterogeneity of the Internet's impact on agglomeration.…”