Abstract: It is of great significance to measure and analyze China’s carbon emissions efficiency of tourism and its spatial heterogeneity scientifically to promote the sustainable development of tourism. This paper estimate the carbon emissions efficiency of tourism of 30 provinces in mainland China from 2000 to 2015 by using the Slack-Based Measure (SBM) considering the unexpected output. On this basis, the method of the non-parametric Kernel density estimation is applied to characterize the dynamic evolution of carbon emissions efficiency of tourism. The results found that there are obvious differences of carbon emissions efficiency of tourism among the 30 regions in China, and it is normal to see that the carbon emissions efficiency of tourism of the eastern region is higher than that of the western region. However, most of provinces are still in the state of carbon emissions inefficiency of tourism. Furthermore, the density curve reveals that an increasing trend of China’s carbon emissions efficiency of tourism is emerged as the time went by, and the distribution of carbon emissions efficiency of tourism changed from “single peak” to “three peaks” to “twin peak” over time, facing the problem of uncoordinated development; Besides, the spatial Durbin model is used to study the spatial correlation characteristics of carbon emissions efficiency of tourism among each provinces. Results show that the carbon emissions efficiency of tourism has apparent spatial spillover effects, that is to say, Not only is the carbon emissions efficiency of tourism affected by its own characteristics of each province, but also it is relevant to the development of the surrounding provinces. Specifically, the level of tourism technology, the level of economic development, the industrial structure and the degree of openess exert significantly positive impact on the tourism carbon emissions efficiency of both its own province and the surrounding provinces, The property right structure of tourism has a significant negative impact on the province’s own carbon emissions efficiency of tourism, while the impact on that of the surrounding provinces is not obvious. The tourism economy scale and the urbanization level have a negative external influence on the carbon emissions efficiency of tourism, but the effect of education on the carbon emissions efficiency of tourism is not significant.
Key words：carbon emissions efficiency of tourism; SBM model; kernel density estimation; spatial Durbin model; China