Results of spatial lag regression analysis comparing interactions among Polish local governments in three regions for property tax rates and water provision tariffs (2016).
| Dependent variable . | Ln Tariffs for water provision (households) . | Ln Property tax rates on residential buildings . |
|---|---|---|
| Spatial effect Rho | 0.465*** (0.057) | 0.423*** (0.057) |
| Ln Affluence of local community | −0.030 (0.021) | −0.145 (0.122) |
| Ln Population size | 0.213*** (0.040) | 0.656*** (0.228) |
| Ln Distance to agglomeration | 0.049 (0.043) | −0.044 (0.226) |
| Altimetric variation | 0.286*** (0.076) | |
| Constant | −0.555*** (0.107) | −1.948*** (0.340) |
| Log likelihood | 115.61 | −479.52 |
| Number of observations | 344 | 344 |
| Dependent variable . | Ln Tariffs for water provision (households) . | Ln Property tax rates on residential buildings . |
|---|---|---|
| Spatial effect Rho | 0.465*** (0.057) | 0.423*** (0.057) |
| Ln Affluence of local community | −0.030 (0.021) | −0.145 (0.122) |
| Ln Population size | 0.213*** (0.040) | 0.656*** (0.228) |
| Ln Distance to agglomeration | 0.049 (0.043) | −0.044 (0.226) |
| Altimetric variation | 0.286*** (0.076) | |
| Constant | −0.555*** (0.107) | −1.948*** (0.340) |
| Log likelihood | 115.61 | −479.52 |
| Number of observations | 344 | 344 |
Note: Regression coefficients are quoted, standard errors are in parentheses. Cross-sectional estimates using data from 2016. All variables have been logged. Weights for all surrounding municipalities according to distance from municipality i's centroid (municipalities with a distance of more than 20 km receive a weight of 0). Significance level: *p < 0.1, **p < 0.05, ***p < 0.01.