## 4 Results
### Driving Forces of the CCD
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & & **(I)** & **(3)** & **(4)** \\
**Determinants** & **Variables** & **Pooled OLS** & **Spatial Fixed** & **Time-Period** & **Spatial and Time-Period** \\  & & **(1)** & **Squares)** & **Effects** & **Fixed Effects** & **Fixed Effects** \\ \hline  & Commercial units per thousand of the urban population (CU) & Log (_CU_) & 0.0100 (0.16) & 0.0224 (0.39) & 0.0376 (0.43) & 0.1903 (0.25) \\ \hline Level of economic development & Registered enterprises per thousand of the urban population (_RE_) & Log (_RE_) & 0.0602 ** (2.71) & 0.3085 ** (2.95) & 0.4462 *** (3.46) & 0.3004 ** (2.61) \\ \hline  & Vehicles per thousand of the urban population (_VH_) & Log (_VH_) & \(-\)0.3015 ** (\(-\)2.29) & 0.1082 (1.11) & 0.3285 ** (2.54) & 0.2056 ** (0.1014) \\ \hline Level of industrial development & Secondary industry share (_SE_) & Log (_SE_) & 0.3872 ** (3.15) & 0.3244 *** (4.86) & 0.4285 *** (6.24) & 0.3962 *** (0.7194) \\ \hline Government policymaking actions & Urban construction and repair capital/km\({}^{2}\) (_CR_) & Log (_CR_) & 0.3541 (0.93) & \(-\)0.0037 (0.09) & 0.1182 (1.45) & \(-\)0.0390 (0.0406) \\ \hline  & Expenditures of local government per person (_EX_) & Log (_EX_) & 0.0913 (1.17) & \(-\)0.1209 (1.62) & \(-\)0.2149 (1.25) & \(-\)0.0451 (0.0907) \\ \hline  & Degree of linkage between cities & Number of telephone lines/km\({}^{2}\) (_TE_) & Log (_TE_) & 0.4047 *** (6.21) & 0.0082 (0.15) & 0.3387 *** (4.48) & \(-\)0.0152 (0.0585) \\ \hline  & & Intercept & 0.3485 ** (2.87) & & & \\ \hline  & & \(\sigma^{2}\) & 0.4181 (0.0891 0.4191 0.0825 0.5781 0.9281 0.5963 0.3543 0.5908 0.1096 0.1096 0. In the nonspatial model, the coefficients of the four explanatory variables \(RE\), \(VH\), \(SE\), and \(TE\) were significantly different from zero. In the time-period fixed effects of this model (the penultimate column of Table 3), the variables of \(RE\), \(SE\), \(VH\), and \(TE\) all had positive effects on the CCD. The elasticities of the four variables were 0.4462, 0.4285, 0.3285, and 0.3387, respectively. However, because the SDM specification of this model was more appropriate, these elasticities were biased. In the SDM with random spatial effects and fixed time-period effects, only the two variables RE and SE had a significantly positive effect on the CCD. Moreover, the coefficient estimates in the nonspatial model represented the marginal effects of a change in the explanatory variables on the explained variables, whereas the coefficients in the SDM did not. Thus, we needed to compare the parameter estimates in the nonspatial model in Table 3 with their counterparts in the direct and indirect effects estimates in Table 5. Because of the feedback effects generated by the impacts passing through adjacent regions and back to the regions themselves, the coefficient estimates of the explanatory variables in Table 4 were different from their direct effects in Table 5 [86]. The feedback effects were partly caused by the positive and significant coefficient of the spatially lagged dependent variable [\(W^{*}\)Log (\(C\))] and partly caused by the negative and significant coefficients of the spatially lagged values of the explanatory variables, such as [\(W^{*}\)Log (\(RE\))] and [\(W^{*}\)Log (\(SE\))] (see Table 4).