ECONOMETRIC ASSESSMENT OF THE TAX BURDEN’S EFFECT ON THE PERFORMANCE OF INDUSTRIAL ENTERPRISES USING PANEL DATA

Abstract

The article presents a comprehensive econometric study assessing the impact of tax burden, innovation activity, and financial characteristics on the performance of industrial enterprises using panel data. The relevance of the research arises from the need for quantitative evaluation of the interaction between fiscal and innovation-related factors within the industrial sector, where the tax environment and technological development largely determine firms’ competitiveness. Theoretical studies confirm the significant role of innovation in productivity growth, while a high tax burden may limit financial resources and constrain production modernization. Therefore, panel modelling makes it possible to account for both temporal and cross-firm variability, ensuring a more accurate measurement of the effects of key determinants on enterprise performance.

The study applies fixed-effects and random-effects models adapted to the structure of panel data. Statistical tests were conducted to justify the model choice and confirmed the presence of autocorrelation of residuals alongside the absence of heteroskedasticity. To enhance the reliability of the estimates, cluster-robust standard errors were employed. The constructed econometric model, which includes an interaction term (taxes × innovation), allows for analysing the potential modification of the R&D effect depending on the level of tax burden. The findings reveal a statistically significant negative effect of tax burden and a positive effect of innovation activity on enterprise performance, while the interaction between these factors is statistically insignificant.

The practical significance of the study lies in providing an informative analytical basis for improving tax and innovation policies, particularly in identifying threshold levels of tax burden that influence the effectiveness of innovation. The results can be used by public authorities and enterprise management for strategic planning, evaluation of innovation projects, and the development of monitoring systems for industrial sector performance.