ECONOMETRIC MODELING OF THE IMPACT OF TAX BURDEN AND INNOVATION IMPLEMENTATION ON THE OUTPUT OF AN INDUSTRIAL ENTERPRISE
DOI:
https://doi.org/10.31891/2307-5740-2025-346-5-26Keywords:
econometric modeling, correlation analysis, regression analysis, tax burden, innovation activity, industrial enterpriseAbstract
The study presents a comprehensive economic and mathematical modeling of sales volumes of industrial enterprises, focusing on the combined influence of innovation development and tax burden on market performance. The research aims to identify and quantify the key determinants that shape sales dynamics in a competitive industrial environment. A multiple regression model was developed, enabling the evaluation of both internal and external factors affecting enterprise performance. The model incorporates variables such as per capita income, product pricing, innovation activity level, and the effective tax rate.
The empirical analysis revealed that per capita income and the intensity of innovation activity have a statistically significant and positive impact on sales volumes, reflecting the growing role of technological advancement and consumer purchasing power in stimulating industrial demand. Conversely, higher product prices were found to negatively influence sales, underscoring the sensitivity of market demand to price fluctuations. Although the tax burden was statistically insignificant at conventional confidence levels, it demonstrated a restraining tendency on sales growth, suggesting its indirect effect on business competitiveness.
The constructed model was rigorously tested for multicollinearity, autocorrelation, and heteroskedasticity to ensure statistical validity and robustness. Correlation analysis confirmed strong interdependencies between sales volumes and selected macroeconomic indicators, particularly those reflecting consumer demand and innovation dynamics. The obtained results contribute to a deeper understanding of the mechanisms driving industrial market behavior.
The findings can be effectively applied in forecasting market trends, supporting strategic managerial decision-making, and enhancing the operational efficiency and adaptability of industrial enterprises under conditions of technological transformation and fiscal policy changes.
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Copyright (c) 2025 Гертруда ГОЙ, Олена ЮНЬКОВА (Автор)

This work is licensed under a Creative Commons Attribution 4.0 International License.
