Dynamic Scoring, Tax Evasion, and the Shadow Economy

Abstract

Measuring the impact of tax policy on tax evasion is crucial in estimating government revenues. In the United States, the government estimates that $300—$400 billion is lost each year to tax evasion. This article combines dynamic scoring with household preferences for tax evasion à la Feige and McGee to measure the macroeconomic feedback effects from tax cuts to changes in output and government revenues. Using a simple dynamic scoring model based on Mankiw and Weinzierl (2006), the feedback effects are divided into their constituent substitution, income, and evasion effects for an analysis of individual behavior at the microeconomic level. Calibrating the model to U.S. data reveals that the growth effects of income tax rate cuts can offset a significant percentage of the potential revenue losses.