## 4 Analysis of Results
#### 4.2.3 Analysis of Spatial Panel Measurement Results Based on Economic Matrix
0.0217 and 0.0359, respectively, indicating that each one-unit increase in the two variables of agricultural technology R&D and agricultural technology application in neighboring provinces will have a positive effect of 0.0217 and 0.0359 percentage points, respectively. This also provides a basis for further establishing the spatial spillover effect of agricultural science and technology innovation on agricultural green development through partial differential equations. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Variable**} & \multicolumn{3}{c}{**Agricultural Technology R\&D**} & \multicolumn{3}{c}{**Application of Agricultural Technology**} \\ \cline{2-7}  & **Time Fixed** & **Individual** & **Double Fixed** & **Time Fixed** & **Individual** & **Double Fixed** \\  & **Effect** & **Fixed Effect** & **Effect** & **Effect** & **Fixed Effect** & **Effect** \\ \hline \multirow{2}{*}{Inast} & 0.0367 *** & 0.0116 *** & 0.0176 *** & 0.0128 *** & 0.0110 *** & 0.0107 *** \\  & (9.80) & (3.00) & (4.13) & (8.04) & (5.96) & (5.32) \\ \multirow{2}{*}{Infsa} & 0.0328 *** & 0.0004 & \(-\)0.0042 & 0.0270 *** & 0.0016 & 0.0002 \\  & (7.40) & (0.05) & (\(-\)0.49) & (7.73) & (0.23) & (0.02) \\ \multirow{2}{*}{Inmii} & 0.0089 & 0.0375 *** & 0.0486 *** & 0.0319 *** & 0.0213 * & 0.0421 *** \\  & (1.16) & (3.34) & (4.44) & (3.43) & (1.94) & (3.91) \\ \multirow{2}{*}{Inadr} & \(-\)0.0020 & \(-\)0.0023 & \(-\)0.0021 & \(-\)0.0103 ** & \(-\)0.0004 & \(-\)0.0019 \\  & (\(-\)0.46) & (\(-\)1.11) & (\(-\)1.05) & (\(-\)1.07) & (\(-\)0.18) & (\(-\)0.94) \\ \multirow{2}{*}{Incps} & 0.0013 & \(-\)0.0252 *** & \(-\)0.0247 *** & 0.0016 & \(-\)0.0249 *** & \(-\)0.0302 *** \\  & (0.30) & (\(-\)3.67) & (\(-\)3.72) & (1.58) & (\(-\)3.75) & (\(-\)4.85) \\ \multirow{2}{*}{Imci} & \(-\)0.0122 & 0.0308 *** & 0.0354 *** & 0.0119 & 0.0380 *** & 0.0382 *** \\  & (\(-\)0.99) & (2.61) & (2.86) & (0.34) & (3.26) & (3.22) \\ \multirow{2}{*}{w * Inast} & 0.0217 ** & \(-\)0.0361 *** & \(-\)0.0014 & 0.0359 *** & \(-\)0.0150 *** & \(-\)0.0111 ** \\  & (1.78) & (\(-\)6.28) & (\(-\)0.12) & (\(-\)4.20) & (\(-\)5.63) & (\(-\)2.10) \\ \multirow{2}{*}{w * Infsa} & \(-\)0.0031 & \(-\)0.0475 *** & \(-\)0.0624 *** & \(-\)0.0316 ** & \(-\)0.0518 *** & \(-\)0.0592 *** \\  & (\(-\)0.28) & (\(-\)5.61) & (\(-\)3.04) & (\(-\)4.58) & (\(-\)6.21) & (\(-\)2.92) \\ \multirow{2}{*}{w * Inmi} & 0.0843 *** & 0.2480 *** & 0.275 *** & 0.1084 *** & 0.1822 *** & 0.2631 *** \\  & (5.25) & (9.10) & (9.24) & (6.01) & (7.29) & (9.06) \\ \multirow{2}{*}{w * Inadr} & 0.0282 *** & \(-\)0.0017 & \(-\)0.0038 & 0.0402 *** & 0.0017 & \(-\)0.0068 \\  & (2.65) & (\(-\)0.39) & (\(-\)0.79) & (\(-\)1.73) & (0.40) & (\(-\)1.45) \\ \multirow{2}{*}{w * Incps} & 0.0082 & \(-\)0.0701 *** & \(-\)0.0573 *** & \(-\)0.0291 ** & \(-\)0.0577 *** & \(-\)0.0614 *** \\  & (0.70) & (\(-\)4.49) & (\(-\)3.69) & (\(-\)0.56) & (\(-\)3.76) & (\(-\)4.19) \\ \multirow{2}{*}{w * Inmci} & 0.1300 *** & 0.0895 *** & 0.1006 *** & 0.0482 & 0.0472 * & 0.0713 ** \\  & (4.50) & (3.56) & (3.24) & (\(-\)1.16) & (1.93) & (2.34) \\ \multirow{2}{*}{sigma\({}^{2}\)} & 0.0027 *** & 0.0005 *** & 0.0004 *** & 0.0028 *** & 0.0005 *** & 0.0005 *** \\  & (14.49) & (14.49) & (14.40) & (14.47) & (14.49) & (14.48) \\ \multirow{2}{*}{N} & 420 & 420 & 420 & 420 & 420 & 420 \\  & 0.5428 & 0.1595 & 0.1871 & 0.4847 & 0.1196 & 0.1477 \\ \multirow{2}{*}{Log-likelihood} & 641.8840 & 1005.2727 & 1027.9040 & 619.7385 & 1007.9326 & 1038.3224 \\ \hline \end{tabular} Note: \(Z\) statistics are in parentheses; **, **, * represent significance levels of 1%, 5% and 10% in turn.  
\end{table} 
Table 11: Spatial panel econometric regression results of agricultural science and technology innovation on green agricultural development under the economic matrix.