How Reliably Do Empirical Tests Identify Tax Avoidance?

• 成果类型: Article
• 署名作者: De Simone, Lisa; Nickerson, Jordan; Seidman, Jeri; Stomberg, Bridget
• 署名单位: Stanford University; Boston College; University of Virginia; Indiana University System; Indiana University Bloomington
• 刊物名称: CONTEMPORARY ACCOUNTING RESEARCH
• ISSN/ISSBN: 0823-9150
• DOI: 10.1111/1911-3846.12573
• 发表日期: 2020
• 页码: 1536-1561
• 关键词: income; incentives; irs; learn

摘要

Research on the determinants of tax avoidance have relied on tests using GAAP and cash effective tax rates (ETRs) and total and permanent book-tax differences. Two new proxies have emerged that overcome documented limitations of these proxies: one, developed by Henry and Sansing (2018), allows for more meaningful interpretation of results estimated in samples that include loss observations. The other, reserves for unrecognized tax benefits (UTB), provides new data on tax uncertainty. We offer empirical evidence on how well tests using these new proxies perform relative to those extensively used in prior research. The paper finds that tests using the proxy developed by Henry and Sansing (2018) have lower power relative to those using other proxies across all samples, including a sample that includes loss observations. In contrast, when firms accrue reserves for uncertain tax avoidance, tests using the current-year addition to the UTB have the highest power across all proxies, samples, and levels of reserves. In the absence of reserves, tests using the GAAP ETR best detect uncertain tax avoidance, on average. This study contributes to the literature by using a controlled environment to provide the first large-scale empirical evidence on how the power of tests varies with the use of relatively new proxies, the inclusion of loss observations, and the advent of FIN 48.