This paper quantifies and compares the influence of two modes of transport on tourism, namely, high-speed rail (HSR) and air travel, and explores their substitute or complementary relationships. To facilitate the analysis, we apply data from 291 prefectural administrative cities in China from 2003 to 2019. Empirical tests show that both modes have a significant positive influence on the development of tourism. Moreover, the effect of air travel is greater than that of HSR. The findings remain robust and reliable with changes in the explanatory variables and sample size, and with regard to time window adjustment and endogeneity. Further, we explore the differences in the strength of the influences and find the two modes exhibit various effects according to regional heterogeneity. Finally, we investigate the joint effect of the two modes and find the existence of a substitute relationship. However, the relationship changes to complementary in specific areas. The findings of this paper provide important implications for the development of the regional tourism economy and the spatial layout of the transport infrastructure.

Although the special economic zones (SEZs) are considered the backbone of rapid economic development in China, it is unclear whether they contribute to green economic development. From the perspective of the localized industrial chains formed as a result of the SEZ policy, this paper aims to analyze and explain how the development of SEZs influences carbon emissions in Chinese cities by promoting green technologies’ vertical spillover along the industrial chain. Based on the panel data of 264 prefecture-level cities from 2011 to 2016 and a relatively new and mostly disaggregated city-level MRIO (multi-region input–output) table in China, this paper constructs green technology vertical spillover as a mechanism variable and discusses the influence theoretically and empirically. The results show that the development of SEZs can reduce a city’s carbon emissions. More specifically, for every 10 m² increase in the size of the SEZ area, the carbon dioxide emission can be reduced by 0.882 g per m² of the city area. Moreover, mechanism analysis shows that the development of SEZs promotes green technology vertical spillover inside the city, through which the SEZs reduce the city’s carbon emissions. The mediation effect occupies 21.96% of the total effect. Furthermore, the impact of the development of SEZs on carbon emissions has regional heterogeneity due to the city’s industry structure, green technology stocks, and the zones’ administrative hierarchies. The finding of this study could provide several important implications for regional green development, especially in China.

This paper aims to analyze and explain how urban centrality influences tourism development in a city. Based on the panel data of 295 prefecture-level cities in China from 2005 to 2018, the paper develops explanatory mechanisms and discusses the influence theoretically and empirically. To advance the analysis, this paper constructs a new index for urban centrality. Our empirical findings are as follows: (1) urban centrality promotes tourism income significantly. (2) Mechanism analysis illustrates that urban centrality fosters tourism through the agglomeration and industrial structure effects. (3) Heterogenous analysis suggests that the influence of urban centrality on tourism varies with city sizes and locations.

Scholars have attempted to compile various multi-region input-output (MRIO) tables for different countries. However, due to city-level data scarcity and methodology constraints, almost no MRIO table covers a large number of cities with more disaggregated sectors in countries with large economies, such as China. Based on two large-scale firm-level datasets, the China Annual Survey of Industrial Firms (CASIF) survey and the China Customs Data (CCD) database, from 2000 to 2013, this paper uses China as a case study and presents a new compilation method to construct an MRIO table covering 284 prefecture-level administrative cities and 334 four-digit sectors, which is by far the most comprehensive MRIO table with the largest number of cities and the most segmented industries in China. Unlike existing MRIO tables constructed based on provincial single-region IO (SRIO) tables, we use information along with various linear constraints implied by sector-level and firm-level statistics. This paper expands on the direct decomposition method by developing auxiliary econometric models necessary for estimations and consistency adjustment. In addition, a comparative analysis shows the reliability of our method, which guarantees better coherence and comparability with the MRIO officially published by the National Bureau of Statistics of China (NBS). Therefore, our proposed methodology provides the possibility of producing more disaggregated MRIO tables in other similar contexts.