Sarah B. Lawsky, Modeling Uncertainty in Tax Law, 65 Stan. L. Rev. 241 (2013).
Each year, the government faces a massive shortfall in tax collections: the annual difference between the amount taxpayers owe the government and the amount the government actually receives is nearly $400 billion dollars. The questions of when and why taxpayers choose to comply with the tax law are thus pressing ones for scholars and policymakers. Many legal scholars rely on economic models better to understand these issues. However, none of the models that legal scholars use can accommodate the reality that taxpayers face unknown probabilities when they decide whether to comply. A taxpayer does not know, for example, the probability that he will be selected for audit, the probability that the government will identify a particular questionable position on his tax return, or the probability that the IRS or a court will strike the position down.
This Article presents a formal model of tax compliance that, unlike other models of tax compliance used in legal scholarship, takes unknown probabilities into account. The model presented incorporates both the extent of a taxpayer’s uncertainty and the taxpayer’s attitude toward uncertainty, and thus provides new insights into problems as disparate as how the government should reveal information about its approach to audits, whether the government should use antiabuse rules to attack tax shelters, and whether tax professionals should be subject to penalties for providing certain kinds of tax advice.