Research on the Spatial Spillover Effect of Provincial Final Consumption Level in China Based on the Complex Network

Abstract

A spatial spillover correlation network is an excellent representation for expressing the relationship of consumption levels among regions, which provides a way to study the evolution mechanism of the spatial influence of the consumption level. Using data on the consumption levels of 29 provinces (or municipalities or autonomous regions) during the global stage (1978–2020) and two separated stages (1978–2001 and 2002–2020) after China’s reform and opening up, this paper analyzes the topological characteristics and driving factors of provincial residents’ consumption level spatial spillover network by applying the Granger causality test of Vector Autoregression (VAR) model and a complex network analysis method. The results show that the number of spatial spillover relationships of provincial residents’ consumption level in the second stage increases significantly in comparison with that in the first stage and the scope of mutual influence among provinces increases rapidly in the second stage; that eastern coastal regions play a net spillover role in the network and some central and western provinces play an increasingly important broker role; and that the members of the network compose four communities with different gradients, with Beijing, Shanghai, and Jiangsu in the leading positions. The network shows neighborhood spillover and club convergence, and these characteristics are more evident in the second stage; moreover, spatial adjacency, residents’ disposable income, urbanization level, consumer credit, and consumption environment similarity have significant driving effects on the spillover correlation of the consumption level.