Potentiality of Benford’s law in deriving a firm-level evasion indicator for Italy

This paper investigates the potential of Benford’s Law (BL) to detect corporate tax evasion, with a focus on Italy, where tax non-compliance remains a persistent economic challenge. BL predicts the expected distribution of leading digits in naturally occurring numerical data, and significant deviations from this pattern may indicate irregularities, including tax evasion. We apply BL to financial statement data for the years 2014–2022. A firm is classified as potentially non-compliant if its financial data deviate from BL in at least one year. This approach yields a firm-level indicator that can support tax audit targeting and serve as a proxy for tax evasion in empirical research. Such a proxy may help address the scarcity of firm-level data and enable the study of how tax evasion affects firm growth and market distortions. To evaluate its validity, we compare the distribution of potentially non-compliant firms—identified via BL—across regions, sectors, and firm sizes with aggregated data from the Italian Ministry of Economy and Finance and the Revenue Agency, including Synthetic Tax Reliability Indices and other official estimates of tax evasion and the shadow economy. The findings reveal a strong alignment between BL-based results and official indicators, highlighting the potential of BL as a cost-effective, data-driven tool for identifying and studying tax evasion at the firm level.