Nonlinear and Spatial Effects of Tourism on Carbon Emissions in China: A Spatial Econometric Approach

Abstract

Reducing carbon emissions is crucial to the sustainable development of tourism. However, there are no consistent conclusions about the nexus between tourism and carbon emissions. Considering the possible nonlinear and spatial effects of tourism on carbon emissions, this paper employed spatial econometric models combined with quadratic terms of explanatory variables to explore the nexus between them using Chinese provincial panel data from 2003 to 2016. The main results are as follows: (1) There is a significant inverse U-shaped relationship between tourism development and carbon emissions. In the provinces whose tourism receipts are relatively low, the effects of tourism on carbon emissions are positive but decrease gradually as the tourism receipts increase and then shifts to negative and continues decreasing gradually when the tourism receipts beyond the critical value. (2) For the geographical proximity and industrial relevance, one province’s tourism development not only affects its carbon emissions but also affects its neighbors’ carbon emissions through spatial lag effect (indirect effect) which is also inverse U-shaped. (3) Carbon reduction policies, sustainable education, and transportation infrastructure all have significant moderating effects on the relationship between tourism and carbon emissions, but the moderating effect of the management efficiency of tourism is not statistically significant. Furthermore, improvements to the sustainable education and transportation infrastructure not only strengthen the direct negative effect of tourism on carbon emissions but also strengthen the indirect negative effect of tourism on carbon emissions. This study not only advances the existing literature but is also of considerable interest to policymakers.

Coupling Coordination and Influencing Factors among Tourism Carbon Emission, Tourism Economic and Tourism Innovation

“…Bi combined with the spatial econometric model to discuss the impact of tourism on carbon emissions. It is found that there is a significant inverted “U” shaped relationship between them, and tourism has an obvious spatial lag effect on carbon emissions, which is also an inverted “U” shaped relationship [ 38 ]. Paramati used panel econometric techniques to find that tourism played an important role in promoting economic growth, while tourism’s effect on CO 2 was largely dependent on sustainable tourism policies [ 39 ].…”

Analysis and Prediction of the Coupling Coordination Relationship between Tourism and Air Environment: Yangtze River Economic Zone in China as Example

“…For instance, 1% of increase in tourism revenue contributes to the 0.105% reduction of CO 2 emissions [30], and the developing countries have slower reduction speeds than the developed countries [31]. Furthermore, being considered as the low-carbon industry [32], tourism activities contribute to the upgrade of industrial structures and the renewal of urban functions, which helps better air environment protection [33,34]. Cases from the regions characterized as the traditional manufacturing industry centers prove that tourism industry, as a new economy growth mode, contributes to restructuring of the urban functional structures and to the protection of the air environment [35,36].…”

The impacts of human migration and city lockdowns on specific air pollutants during the COVID-19 outbreak: A spatial perspective

“…Scientists from around the world are expected to work on more detailed analyses as satellite data or images have many uncertainties ( Schwandner et al, 2017 ). Another reason is that recent emerging studies lose sight on the presence of spillover effects and regional effects in air pollution ( Bi and Zeng, 2019 ; Chen et al, 2016 ; Du et al, 2020 ; Feng et al, 2020 ; Gong and Zhang, 2017 ; Yue et al, 2019 ; Zeng et al, 2019 , 2021 ), which may invalidate the results ( Kolak and Anselin, 2019 ). Many questions remain, including: Do spillover effects in air pollution exist in China during the pandemic?…”