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Contributions to Game Theory and Management, 2012, Volume 5, Pages 156–167
(Mi cgtm156)
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This article is cited in 5 scientific papers (total in 5 papers)
Tax Auditing Using Statistical Information about Taxpayers
Suriya Sh. Kumacheva St. Petersburg University, Faculty of Applied Mathematics and Control Processes, Bibliotherapy pl. 2, St. Petersburg, 198504, Russia
Abstract:
A model of tax auditing in assumption, that tax authority have
some statistical information about the distribution of income among
population, is considered.
It is supposed that the true tax liability of each taxpayer takes
its value from finite set. Dividing the range of possible tax
payments on intervals, we make a correspondence between each
interval and some group of taxpayers. The reported tax liability is
the function of the true tax liability, which takes its values from
the set of its argument's values. If the evasion was revealed, the taxpayer must
pay the level of his evasion and penalty (marginal penalty rate
assumed to be a constant). Tax evasions of the groups of taxpayers
with the same level of income and the same level of rationality are
investigated.
The tax authority assumed to get some statistical information,
which can be considered as an indicator of the existing tax evasion.
The information, mentioned above, is called a signal.
A taxpayer’s strategy is to make a decision to evade or not to
evade, i.e. to declare his income level less or equal to his true
income. A tax authority's strategy is to choose the audit
probability.
The following results were obtained: the optimal audit strategies
for each income-level group; the optimal audit strategies with
consideration of the signals; the proposition about the optimal
budget for tax auditing.
Keywords:
tax auditing, tax evasion, statistical information, income distribution, optimal audit strategies, optimal budget.
Citation:
Suriya Sh. Kumacheva, “Tax Auditing Using Statistical Information about Taxpayers”, Contributions to Game Theory and Management, 5 (2012), 156–167
Linking options:
https://www.mathnet.ru/eng/cgtm156 https://www.mathnet.ru/eng/cgtm/v5/p156
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Abstract page: | 202 | Full-text PDF : | 81 | References: | 54 |
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