# Does Intensive Land Use Contribute to Energy Efficiency?--Evidence Based on a Spatial Durbin Model
## 4 Results
### Spatial Threshold Regression Results  
We incorporated the spatial lag of intensive land use level into the threshold model. Table 4 shows the threshold effect test. It can be found in Table 5 that whether it is a single threshold model, a double threshold model, or a three-threshold model, they all exist significantly. Therefore, this paper uses the above three threshold models to verify the impact of intensive land use on energy efficiency under different spatial integration levels [43,44]. The regression results of the spatial threshold model are shown in Table 6. It can be found that with the improvement of the integration level, the impact of the intensive use of land in a particular city on the surrounding areas has changed from a negative value to a positive value. Only at the level of integration of the space will the intensive use of land cause a decline in energy efficiency in the surrounding areas. Based on this, the state and local governments should pay attention to the sharing of resources, technology, and information in the region to realize the coordinated development of the regional economy and strengthen joint prevention and control in the region. In turn, it will realize the benign interaction and coordinated development of the region, give full play to the scale effect, \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & \multicolumn{3}{c}{**Durbin Model**} & \multicolumn{3}{c}{**Dynamic Durbin Model**} \\
**Variables** & **Direct Effect** & **Indirect Effect** & **Total Effect** & **Direct Effect** & **Indirect Effect** & **Total Effect** \\ \hline \multirow{3}{*}{_Liu_} & 2.125 *** & \(-\)1.242 *** & 0.883 *** & 2.784 *** & \(-\)1.723 *** & 1.061 *** \\  & (3.22) & (\(-\)4.73) & (2.94) & (4.96) & (\(-\)4.95) & (3.52) \\  & 0.272 *** & 0.183 *** & 0.455 *** & 0.193 *** & 0.231 *** & 0.416 *** \\  & (\(-\)6.63) & (\(-\)9.06) & (\(-\)3.92) & (\(-\)9.46) & (\(-\)6.13) & (\(-\)9.29) \\  & 0.226 *** & 0.211 *** & 0.437 *** & 0.147 *** & 0.221 *** & 0.368 *** \\  & (\(-\)4.47) & (\(-\)4.60) & (\(-\)4.96) & (\(-\)5.57) & (\(-\)3.74) & (\(-\)3.32) \\  & -1.924 *** & \(-\)2.182 *** & \(-\)4.124 *** & \(-\)2.536 *** & \(-\)1.632 *** & \(-\)1.668 *** \\  & (\(-\)5.76) & (\(-\)4.88) & (\(-\)2.64) & (\(-\)4.69) & (\(-\)5.89) & (\(-\)4.55) \\  & 3.011 *** & 2.453 *** & 5.464 * & 3.088 & 2.760 & 5.848 *** \\  & (7.48) & (11.55) & (1.91) & (1.40) & (1.21) & (2.61) \\  & \(-\)0.125 & \(-\)0.094 & \(-\)0.219 *** & \(-\)0.082 & \(-\)0.133 & \(-\)0.215 \\  & (\(-\)1.04) & (\(-\)1.24) & (\(-\)2.27) & (\(-\)0.81) & (\(-\)1.06) & \(-\)1.87 \\  & \(-\)0.082 & \(-\)0.083 & \(-\)0.165 & \(-\)0.103 & \(-\)0.082 & \(-\)0.175 \\  & (\(-\)0.44) & (\(-\)0.44) & (\(-\)0.89) & (\(-\)0.51) & (\(-\)0.39) & \(-\)0.90 \\  & \(-\)0.113 *** & \(-\)0.114 *** & \(-\)0.227 *** & \(-\)0.123 *** & \(-\)0.121 *** & \(-\)0.244 \\  & (\(-\)4.30) & (\(-\)6.57) & (\(-\)5.38) & (\(-\)6.26) & (\(-\)5.34) & \(-\)11.60 \\  & & 10.76 *** & & & 8.78 *** & \\  & & (6.61) & & & (3.63) & \\  & \(R^{2}\) & & 0.7804 & & & 0.7676 & \\  & _likelihood_ & & & & 1295,620 & \\  & _ratio_ & & & & & \\ \hline \hline \end{tabular} Note: *, **, and *** represent significant at the 10%, 5%, and 1% levels, respectively, and the hypothesis test statistics are in parentheses.  
\end{table} 
Table 4: Spatial regression results. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & **F-Value** & \(p\)**-Value** & **1\% Critical** & **5\% Critical** & **10\% Critical** \\  & & **Value** & **Value** & **Value** \\ \hline Single threshold & 18.937 *** & 0.003 & 15.303 & 7.955 & 5.922 \\ Double threshold & 40.923 *** & 0.007 & 34.044 & 18.871 & 11.045 \\ Third thresholds & \(-\)11.530 * & 0.090 & 11.707 & \(-\)6.286 & \(-\)12.327 \\ \hline \hline \end{tabular} Note: *, **, and *** represent significant at the 10%, 5%, and 1% levels, respectively, and the hypothesis test statistics are in parentheses.  
\end{table} 
Table 5: Threshold effect test.