ECONOMIC MODELING OF ENTREPRENEURSHIP ECOSYSTEM DEVELOPMENT IN TERRITORIAL COMMUNITIES

Abstract

This article proposes an econometric approach to explaining entrepreneurship ecosystem development at the level of Ukrainian territorial communities under wartime uncertainty and limited local statistics. The purpose is to identify and quantify the factors that are statistically associated with entrepreneurial ecosystems and community-level economic outcomes captured by five result dimensions: fiscal revenues (personal income tax and single tax), entrepreneurial activity (number of registered businesses), employment, exports, and business income. The empirical base covers 55 territorial communities of Ternopil region and an integrated dataset of fiscal, demographic, business-demography and institutional indicators. The methodology combines indicator screening and grouping, hypothesis formulation, and estimation of a series of multiple linear regression models. To reduce mechanical scale effects and improve interpretability, each model is tested in three specifications: absolute values, per capita indicators, and per area indicators, and model quality is assessed via adjusted R² and overall significance. The results show a set of robust models with high explanatory power across specifications. The strongest relationships are linked to business performance metrics and access to short-term bank lending, as well as to the presence of human-capital “anchors” and transport accessibility. In addition, investment readiness and proactive public communication tend to be associated with higher entrepreneurial activity. The practical value of the study is a decision-oriented set of priorities for local governments and policy designers: expand instruments that improve SMEs’ access to finance, invest in education and workforce development, strengthen economic-development institutions and donor partnerships, and transparently communicate investment opportunities to accelerate post-war recovery at the community level. The proposed modeling approach transforms fragmented local statistics into a structured system for evidence-based management, allowing for the optimization of resource allocation and the strengthening of the economic capacity of territorial communities during the recovery period. The approach can be replicated for other regions and updated as new local data become available.