Research Article
Developing a Framework for Spatial Effects of Smart Cities Based on Spatial Econometrics
Table 3
Results of classical linear regression based on cross-section data in 2017.
| Explanatory variable | Regression coefficients | Standard error | T statistics | value |
| β0 | 1.009878 | 0.07068253 | 1.828752 | 0.90880 | LnEXP | 0.2502343 | 0.1652885 | 1.930965 | 0.05712 | LnPA | 0.6714353 | 0.1660166 | 4.044386 | 0.00012 | LnGDP | 0.2199934 | 0.1764379 | 1.24686 | 0.21618 | LnTEA | −0.4646746 | 0.1207545 | −3.848095 | 0.00024 | R-squared: 0.605558 | Adjusted R-squared: 0.585330 | Log likelihood: −78.6621 | AIC: 167.324 | SC: 181.418 | Spatial dependence test | Test | Statistics | value | Moran’s I (error) | 1.0157 | 0.30978 | LM (lag) | 3.1720 | 0.07491 | Robust LM (lag) | 3.9277 | 0.04750 | LM (error) | 0.4250 | 0.51446 | Robust LM (error) | 1.4032 | 0.27722 | LM (SARMA) | 4.3527 | 0.11345 |
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Note. , , and indicate the significance test at 1%, 5%, and 10%, respectively. |