3.1.4. Mediating Effect Model

To test whether tourism development affects urban green economic efficiency through carbon emission intensity, a mediating effect model is constructed by drawing on the related research [14,21].

$$\begin{array}{c} \ln \text{GEE}\_{\text{it}} = \alpha\_0 + \alpha\_1 \ln \text{TC}\_{\text{it}} + \sum\_{j=2}^{n} \alpha\_j \ln \text{CONN}\_{\text{it}} + \eta\_{\text{i}} + \varepsilon\_{\text{it}}\\ \ln \text{CL}\_{\text{it}} = \beta\_0 + \beta\_1 \ln \text{TC}\_{\text{it}} + \sum\_{j=2}^{n} \beta\_j \ln \text{CONN}\_{\text{it}} + \eta\_{\text{i}} + \varepsilon\_{\text{it}}\\ \ln \text{GEE}\_{\text{it}} = \delta\_0 + \delta\_1 \ln \text{TC}\_{\text{it}} + \delta\_2 \ln \text{CI}\_{\text{it}} + \sum\_{j=3}^{n} \delta\_j \ln \text{CONN}\_{\text{it}} + \eta\_{\text{i}} + \varepsilon\_{\text{it}} \end{array} \tag{4}$$

η<sup>i</sup> is the individual fixed effect.

#### 3.1.5. Exogenous Shock Testing Model of the Low-Carbon City Pilot Policy

1. Endogenous Relationship between Low-carbon Cities and Tourism Development

Low-carbon cities achieve green development by adjusting the industrial structure, reducing disposable energy use, using renewable resources as much as possible, and developing low-carbon transportation systems. Tourism can influence industrial optimization, clean energy use and low-carbon transportation. Under the "double carbon" strategy, low-carbon tourism is undoubtedly one of the paths for low-carbon city reform, and in addition to the low consumption of tourism itself and the low carbonization of the tourism process, the strong correlation of tourism itself with a reduction in carbon emissions can lead to the low-carbon transformation of more industries. Tourism development is in line with the essence and connotation of low-carbon city development, and low-carbon tourism can also be an effective path for green economic development in low-carbon cities [45]. Therefore, this paper uses the exogenous shock of low-carbon city pilots to evaluate the existing model and test the robustness of the spillover effect of tourism development on the green economic efficiency and carbon emission intensity of cities.

2. Model Setting and Testing

The dummy variable is constructed as to whether the city is a "low-carbon city" pilot or not, and takes the value of 1 if the city is already a "low-carbon city" pilot at the end of the year and 0 otherwise [56].

Based on the spatial Durbin model, a multitemporal spatial DID expansion estimation was constructed based on relevant studies [56], and the coefficients of the variables were estimated by randomly selecting cities and any year as the sample size and rerunning the model test. Comparing whether there is a significant difference between the true value and the estimated interval can indicate whether the model estimation is biased by omitting city-time-level variables.
