(untitled) (Economics and region, 2025)
Changes in the spatial polarization coefficient values of budget tax revenues per capita in the territorial communities of Sumy and Chernihiv regions, as well as Lviv region, during 2021-2024 were studied. Statistical significance of the calculated polarization coefficient values and its intertemporal changes in the periods 2021-23, 2023-24 and 2021-24 was assessed using bootstrap method of confidence intervals construction, as well as the specific binomial test for significance of median changes in the revenue distribution. Higher statistical power of the specific test for establishing intertemporal effects compared to the universal bootstrap method was confirmed. A sharp increase of the polarization coefficient accompanied the relative stability of the real tax revenues in the deoccupied regions during 2023, and its deep decrease in 2024 can be considered a sign of their tax capacity decline. Given a number of socio-ecological, ecological-economic and socio-economic challenges, it is necessary to apply the principle of spatial structural balance as the basis for sustainable post-war recovery of the national economy. Accordingly, identification and critical selection of quantitative methods for classifying spatial structures of sustainable development indicator distributions within regions, as well as for assessing presence and depth of spatial structural disparities in development, should be one of the priority issues for research. We conducted a quantitative assessment of spatial differentiation in territorial communities’ local tax revenues using a distribution polarization coefficient according to the OECD methodology. To achieve higher statistical power during assessment of intertemporal changes in polarization, a specific null hypothesis test can be proposed, based on estimation of changes in the median of the distribution under study. The nonparametric sign test allows estimation of statistical significance of the difference between the distribution median and a predefined value. Values of the polarization coefficient in 2021 were about 0.5 for Sumy and Chernihiv regions, and about 0.6 for Lviv. In 2023, a sharp increase of the coefficient values for all the regions occurred. In 2024, the coefficient for Sumy region reverted to a value close to the initial; a drop below the 2021 value is observed for Chernihiv (0.414), and an excess compared to the initial value for Lviv. Given the baseline value of the polarization coefficient, the hypothetical median value of the tax revenue distribution was calculated. The result of the binomial test, corresponding to probability of the given observation under null hypothesis, is denoted P(k,N). The results indicate statistical significance of polarization coefficient change with confidence above 99% in the 2021-23 (increasing polarization) and 2023-24 (decreasing polarization) time intervals. During the 2021-24 range, significance of the polarization coefficient increase can only be noted for Lviv region (confidence above 99%). Chernihiv region is notable for the lowest historical level of tax revenues per capita polarization, but also for the greatest sensitivity to spatial proportionality threats. The 2023 increase of the polarization coefficient is associated with stability of the real tax revenues in the communities of the region; on the other hand, the 2024 coefficient decrease, combined with both real and nominal revenues falling, can be interpreted as an additional sign of economic decline during the year. A less pronounced 2023 increase in revenues’ polarization for Sumy region accompanied a more noticeable decrease of their real amount. Lviv region, remote as it is from the zone of hostilities, demonstrated higher polarization during the period of study, coupled with an increase in real community budget revenues. This study can be considered an example application of improved significance testing to spatial structural dynamics of national and regional sustainable development indicators. The prevalent differences in geographical structure of tax revenue distribution between the deoccupied regions, as well as nonlinearity of relationship between the dynamics of real tax capacity and the coefficient of its spatial polarization, require further methodological improvements with an aim of classification of development indicators’ spatial distributions.