Rethinking tax avoidance: Introducing a novel metric for assessing tax compliance

Tax avoidance remains a critical area of research, particularly in understanding its determinants and developing reliable detection models. This study introduces a novel approach to measuring tax avoidance through tax efficiency, calculated using Stochastic Frontier Analysis. By comparing firms with similar inputs, the tax efficiency metric captures variations in tax compliance. This addresses limitations of traditional measures such as the Effective Tax Rate and Book-Tax Differences, which fail to account for concealed revenues and fictitious expenses. The research utilizes financial data from Slovak retail firms to examine the relationship between tax efficiency and various determinants, including firm size, ownership structure, and social responsibility proxies. Key findings reveal that firms with foreign ownership, larger management teams, and robust capital exhibit higher tax efficiency, while smaller firms and those with fragmented ownership structures are more prone to tax avoidance. Furthermore, compared to traditional proxies, this tax efficiency measure demonstrates superior performance in distinguishing between tax-reliable and tax-unreliable firms. The study also highlights the impact of external shocks, such as the COVID-19 pandemic, on reducing tax efficiency. The proposed tax efficiency metric provides a comprehensive tool for identifying tax avoidance behavior and offers practical implications for improving risk-based tax audit selection processes.