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Ghosts in the Income Tax Machinery

Author

Listed:
  • Erard, Brian
  • Langetieg, Patrick
  • Payne, Mark
  • Plumley, Alan

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.

Suggested Citation

  • Erard, Brian & Langetieg, Patrick & Payne, Mark & Plumley, Alan, 2020. "Ghosts in the Income Tax Machinery," MPRA Paper 100036, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:100036
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    References listed on IDEAS

    as
    1. Brian Erard & Chih-Chin Ho, 1999. "Searching for Ghosts: Who Are the Nonfilers nd How Much Tax Do They Owe?," Carleton Economic Papers 99-11, Carleton University, Department of Economics, revised Jul 2001.
    2. Lancaster, Tony & Imbens, Guido, 1996. "Case-control studies with contaminated controls," Journal of Econometrics, Elsevier, vol. 71(1-2), pages 145-160.
    3. Erard, Brian & Ho, Chih-Chin, 2001. "Searching for ghosts: who are the nonfilers and how much tax do they owe?," Journal of Public Economics, Elsevier, vol. 81(1), pages 25-50, July.
    4. Erard, Brian, 2017. "Modeling Qualitative Outcomes by Supplementing Participant Data with General Population Data: A New and More Versatile Approach," MPRA Paper 99887, University Library of Munich, Germany, revised 26 Apr 2020.
    5. Meiselman, Ben S., 2018. "Ghostbusting in Detroit: Evidence on nonfilers from a controlled field experiment," Journal of Public Economics, Elsevier, vol. 158(C), pages 180-193.
    6. Allingham, Michael G. & Sandmo, Agnar, 1972. "Income tax evasion: a theoretical analysis," Journal of Public Economics, Elsevier, vol. 1(3-4), pages 323-338, November.
    7. John Guyton & Pat Langetieg & Day Manoli & Mark Payne & Brenda Schafer & Michael Sebastiani, 2017. "Reminders and Recidivism: Using Administrative Data to Characterize Nonfilers and Conduct EITC Outreach," American Economic Review, American Economic Association, vol. 107(5), pages 471-475, May.
    8. Alm, James & Bahl, Roy & Murray, Matthew N, 1991. "Tax Base Erosion in Developing Countries," Economic Development and Cultural Change, University of Chicago Press, vol. 39(4), pages 849-872, July.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Tax Compliance; Tax Evasion; Nonfilers; Ghosts; Income Tax; Qualitative Response Models; Discrete Choice Analysis;
    All these keywords.

    JEL classification:

    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • H24 - Public Economics - - Taxation, Subsidies, and Revenue - - - Personal Income and Other Nonbusiness Taxes and Subsidies
    • H26 - Public Economics - - Taxation, Subsidies, and Revenue - - - Tax Evasion and Avoidance
    • H31 - Public Economics - - Fiscal Policies and Behavior of Economic Agents - - - Household

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