ASSESSMENT OF THE FINANCIAL CAPACITY OF TERRITORIAL COMMUNITIES OF LVIV REGION BASED ON THE ADAPTED MODEL OF THE K. BROWN TEST

Abstract

This article examines the financial capacity of territorial communities in Lviv region within the framework of contemporary processes of decentralization and fiscal autonomy. The authors analyze scientific approaches to defining the category of “financial capacity,” highlighting its core dimensions, including revenues, expenditures, and capital investments of communities, as well as the significance of local taxation in shaping their resource base. Special attention is devoted to the adapted Ken Brown test model, which enables a comprehensive assessment of community financial conditions through a system of indicators. The study draws on statistical data for 2024, which facilitated the evaluation of revenues, expenditures, capital investments, budget subsidies, the structure of financing administrative apparatuses, and the share of local taxes in total income. Application of the methodology made it possible to rank communities into quartiles and construct an integral indicator of financial capacity. The results reveal that 22 communities belong to the high-level category, 15 to the optimal category, 19 to the satisfactory category, 11 to the low category, and 6 to the critical category. The strongest performance was demonstrated by large urban communities, satellite municipalities of Lviv, and tourist-attractive areas, while remote rural communities exhibited weaker financial positions. The findings suggest that the principal determinants of financial sustainability include population size, the presence of economically significant enterprises, and proximity to the regional center. The study emphasizes the necessity for rural communities to strengthen efforts in accumulating local taxes and fees as a means of enhancing fiscal autonomy. The practical significance of the research lies in its potential to inform local governments in developing financial development strategies and improving resource management mechanisms.