How Reliably Do Financial Statement Proxies Identify Tax Avoidance?

Lisa De Simone, Jordan Nickerson, Jeri K. Seidman and Bridget Stomebrg
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Lisa De Simone: Stanford University
Jordan Nickerson: Boston College
Jeri K. Seidman: University of VA
Bridget Stomebrg: University of GA

Research Papers from Stanford University, Graduate School of Business

Abstract: Can financial statement proxies reliably identify tax avoidance? This is an important question because our understanding of the determinants of tax avoidance largely depends on results generated using such proxies. We seed Compustat data with three tax avoidance strategies and test how reliably effective tax rates and book-tax differences identify the seeded tax avoidance. We find permanent tax avoidance is more easily detected than deferral strategies, and that financial reporting choices can reduce statistical power. We also conclude that no single proxy most powerfully detects all types of tax avoidance. These findings are robust to changes in assumptions about the magnitude and pervasiveness of tax avoidance in the sample and are validated using a sample of tax shelters. We also offer evidence on how research design choices, firm performance and accounting for tax risk affect power. We contribute to the literature by using a controlled environment to examine the effectiveness of financial statement proxies for tax avoidance.

Date: 2016-07
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