Tax Amnesty as Price-discriminating Behavior by a Monopolistic Government

Marchese, Carla; Cassone, Alberto

doi:10.2139/ssrn.128250

“…Standing amnesties may then furnish an escape against unexpected shocks and provide taxpayers with social insurance. Marchese e Cassone (1992) and Franzoni (1995b). The¯rst paper depicts amnesties as a form of intertemporal price discrimination: depending on their evasion opportunities, some taxpayers prefer to purchase their \¯scal liberation" at the outset by paying their statutory taxes, while others prefer to wait and pay the amnesty fee.…”

Section: Prosecution Amnestymentioning

confidence: 99%

Punishment and Grace: On the Economics of Permanent Amnesties

Franzoni

¹

1996

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This paper extends the literature on tax amnesties by considering two special grace programmes. The¯rst is an o®er by the government not to investigate taxpayers' accounts, the second not to prosecute indicted evaders. I analyse the impact of both measures on the taxpayers' optimal behaviour and the government's net revenue, and derive the conditions under which it would be desirable to implement them on a permanent basis. JEL Nos. H26 (Tax Evasion) and K42 (Illegal Behavior and the Enforcement of Law).

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“…A permanent and perfectly anticipated tax amnesty can offer this opportunity. In the Marchese and Cassone (2000) model taxpayers differ in their visibility for tax auditors; taxpayers who Dept. of Public Policy and Public Choice Polis, Univ.…”

Section: Introductionmentioning

confidence: 99%

Tax Amnesties and the Self-Selection of Risk-Averse Taxpayers

Marchese

¹

,

Privileggi

²

2004

European Journal of Law and Economics

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In this paper we model taxpayers participation in an unexpected tax amnesty, which can be entered by paying a fixed amount. Taxpayers are characterized by a Constant Relative Risk Aversion (CRRA) utility function and differ in relative risk aversion coefficient and in income. We show that amnesties may fail as a self-selective device to fully separate big from small evaders and to extract resources from the former. Only taxpayers whose relative risk aversion falls within a given interval participate, while those whose evasion is too small or too large do not enter. The model is used to estimate relative risk aversion and tax evasion of participants in 1991 and 1994 Italian income tax amnesties.

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“…A permanent and perfectly anticipated tax amnesty can offer this opportunity. In the Marchese and Cassone (2000) model taxpayers differ in their visibility for tax auditors; taxpayers who are immediately visible are more willing to pay taxes. Anticipated temporary tax amnesties introduce a kind of intertemporal price discrimination, as less visible taxpayers evade and wait until a "sales amnesty" becomes available.…”

Section: Introductionmentioning

confidence: 99%

Tax Amnesties and the Self-Selection of Risk-Averse Taxpayers

Marchese

¹

,

Privileggi

²

2004

Self Cite

View full text Add to dashboard Cite

In this paper we model taxpayers participation in an unexpected tax amnesty, which can be entered by paying a fixed amount. Taxpayers are characterized by a Constant Relative Risk Aversion (CRRA) utility function and differ in relative risk aversion coefficient and in income. We show that amnesties may fail as a self-selective device to fully separate big from small evaders and to extract resources from the former. Only taxpayers whose relative risk aversion falls within a given interval participate, while those whose evasion is too small or too large do not enter. The model is used to estimate relative risk aversion and tax evasion of participants in 1991 and 1994 Italian income tax amnesties.

show abstract

Tax Amnesty as Price-discriminating Behavior by a Monopolistic Government

Cited by 5 publications

References 17 publications

Punishment and Grace: On the Economics of Permanent Amnesties

Punishment and Grace: On the Economics of Permanent Amnesties

Tax Amnesties and the Self-Selection of Risk-Averse Taxpayers

Tax Amnesties and the Self-Selection of Risk-Averse Taxpayers

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