Ghosts in the Income Tax Machinery

Erard, Brian and Langetieg, Patrick and Payne, Mark and Plumley, Alan (2020): Ghosts in the Income Tax Machinery.

Abstract

Much of the tax compliance literature focuses on taxpayers who choose to underreport their income when they file their tax returns. In this paper, we instead concentrate on those individuals who take the ultimate compliance shortcut of not filing a return at all – a group commonly referred to as “ghosts” by academics, tax administrators, and policy-makers. To learn more about this relatively understudied population, we undertake a detailed analysis of administrative data and Census survey data spanning the period from 2001 through 2013. Our results indicate that 10-12 percent of taxpayers with a US federal filing requirement fail to submit a timely income tax return in any given year, and 6.5-8 percent never file at all. The federal tax gap associated with these ghosts is substantial, amounting to an estimated $37 billion per year. We employ a novel pooled time-series cross-sectional econometric methodology to examine the drivers of late filing and nonfiling behavior. The results establish that filing compliance is influenced by income visibility as well as financial incentives, such as refundable credits, tax rebates, and the monetized filing burden. In addition, we find strong evidence of socio-economic and demographic influences. Our results also reveal substantial persistence in filing behavior. The estimated likelihood of filing a timely return for the current tax year is estimated to be 45 percentage points higher if the taxpayer filed a return for the preceding year. At the same time, we find that one-time financial incentives have only a temporary impact on filing compliance, overturning the prevailing view that, once an individual is brought into the tax system, that individual will continue to file in subsequent years.

• Item Type: MPRA Paper
• Language: English
• Keywords: Tax Compliance, Tax Evasion, Nonfilers, Ghosts, Income Tax, Qualitative Response Models, Discrete Choice Analysis
• Subjects: C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C35 - Discrete Regression and Qualitative Choice Models ; Discrete Regressors ; Proportions; H - Public Economics > H2 - Taxation, Subsidies, and Revenue > H24 - Personal Income and Other Nonbusiness Taxes and Subsidies; H - Public Economics > H2 - Taxation, Subsidies, and Revenue > H26 - Tax Evasion and Avoidance; H - Public Economics > H3 - Fiscal Policies and Behavior of Economic Agents > H31 - Household

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