Research Article
Digital Economy’s Spatial Implications on Urban Innovation and Its Threshold: Evidence from China
Table 7
Results of the robustness tests for impact of the digital economy on urban innovation.
| Variable | Replace the explained variable | Replace the explanatory variable | Replacing the spatial weight matrix | Adjusted sample period | (1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) |
| DE | 0.259∗∗ | 1.147∗∗∗ | 1.047∗∗∗ | 0.192∗∗∗ | 1.029∗∗∗ | 1.013∗∗∗ | 0.578∗∗ | 1.392∗∗∗ | (2.38) | (5.51) | (4.39) | (5.19) | (5.55) | (5.48) | (2.19) | (4.56) |
| Wx_DE | 0.846∗∗∗ | 1.354∗∗∗ | 0.577 | 0.137∗ | 0.563∗ | 0.593∗ | 0.923∗ | 0.562 | (4.15) | (3.20) | (1.26) | (1.81) | (1.83) | (1.83) | (1.69) | (0.91) |
| Rho | 0.772∗∗∗ | 0.661∗∗∗ | 0.711∗∗∗ | 0.695∗∗∗ | 0.577∗∗∗ | 0.620∗∗∗ | 0.695∗∗∗ | 0.688∗∗∗ | (26.51) | (24.70) | (27.49) | (27.58) | (30.65) | (31.72) | (17.83) | (18.04) |
| DE-direct effect | 0.390∗∗∗ | 1.340∗∗∗ | 1.187∗∗∗ | 0.220∗∗∗ | 1.169∗∗∗ | 1.155∗∗∗ | 0.712∗∗∗ | 1.543∗∗∗ | (3.46) | (6.43) | (4.90) | (5.91) | (6.43) | (6.34) | (2.69) | (5.05) |
| DE-indirect effect | 4.605∗∗∗ | 6.164∗∗∗ | 4.567∗∗∗ | 0.880∗∗∗ | 2.641∗∗∗ | 3.130∗∗∗ | 4.368∗∗ | 4.882∗∗ | (4.70) | (4.87) | (2.82) | (3.57) | (3.97) | (3.98) | (2.36) | (2.51) |
| DE-total effect | 4.995∗∗∗ | 7.504∗∗∗ | 5.754∗∗∗ | 1.099∗∗∗ | 3.811∗∗∗ | 4.285∗∗∗ | 5.081∗∗∗ | 6.425∗∗∗ | (4.92) | (5.78) | (3.43) | (4.34) | (5.57) | (5.33) | (2.68) | (3.23) |
| Control variable | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Individual-FE | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Year-FE | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Yes | Adj. R-sq | 0.7046 | 0.7674 | 0.6697 | 0.7105 | 0.7157 | 0.7157 | 0.7012 | 0.7373 | N | 1685 | 3033 | 2696 | 3033 | 3033 | 3033 | 1348 | 1348 |
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Note. ∗∗∗, ∗∗, and ∗ represent the significance level at the 1%, 5%, and 10% levels, respectively. The numbers in brackets are the test values t.
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