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This paper discusses whether high‐speed rail (HSR) construction in China promotes urban economic growth, and it uses social network analysis (SNA) and a panel threshold model. We provide robust evidence that HSR networks have non‐linear effects on the urban economy. Urban location and transportation hub status change as the density of HSR networks increases, and from 2008 to 2017, the national average annual growth rate of the weighted degree centrality (WDC) was 44.93%. We find the WDC and betweenness centrality (BC) have positive influences on urban economic growth. However, HSR network expansion reduces the economic benefits of HSR because the marginal contribution of new HSR lines to economic productivity decreases and there is a crowding out effect caused by excessive agglomeration. HSR networks can promote the economy of Western China to a greater extent and can promote the economy more in small cities than in large and medium‐sized cities. These findings can help the government rationalize its strategy for designing HSR lines in various regions. [ABSTRACT FROM AUTHOR]

Regional inequality in the process of economic growth has recently been a popular topic. This paper creatively proposes contribution decomposition methods to divide various regions' contributions into economic contribution and population contribution. The methods consider not only economic growth but also population change, which may be more effective than the traditional method that uses the per capita GDP (gross domestic product) as its single measurement indicator. Moreover, the objective is to take a step forward and reveal the spatio‐temporal evolution characteristics of regional disparities by integrating barycentre model and economic development equilibrium model. Lastly, the applicability of the research method proposed in this paper is verified by a case study of Jiangsu province, China; the results show a new regional economic pattern in Jiangsu province. [ABSTRACT FROM AUTHOR]