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Tax Evasion Indices and Profiles

Author

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  • Dino Rizzi

Abstract

The aim of this article is to adapt definitions and tools currently used in the economic literature on poverty to individual data on tax evasion. The article presents composite indices and profiles of tax evasion based on the three I’s of tax evasion: incidence, intensity, and inequality, following the approach of Shorrocks’s study and Jenkins and Lambert’s study that proposed the three I’s of poverty. In the field of tax evasion, one stream of literature produces a potentially large amount of individual microdata using tax benefit and agent-based models: the article enriches the analysis offered by these models with indices that take into account the entire distribution of taxpayer evasion rates. Particularly, the article presents a new composite index of tax evasion that incorporates a concentration index of individual tax evasion rates. A final section shows a sensitivity analysis of tax evasion indices and profiles through numerical simulations.

Suggested Citation

  • Dino Rizzi, 2017. "Tax Evasion Indices and Profiles," Public Finance Review, , vol. 45(6), pages 771-791, November.
    • Handle: RePEc:sae:pubfin:v:45:y:2017:i:6:p:771-791
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    Cited by:

    1. Duc Hong Vo & Ha Minh Nguyen & Tan Manh Vo & Michael McAleer, 2020. "Information Sharing, Bank Penetration and Tax Evasion in Emerging Markets," Risks, MDPI, vol. 8(2), pages 1-16, April.
    2. Andrea Albarea & Michele Bernasconi & Anna Marenzi & Dino Rizzi, 2020. "Income Underreporting and Tax Evasion in Italy: Estimates and Distributional Effects," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 66(4), pages 904-930, December.

    More about this item

    Keywords

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    JEL classification:

    • H26 - Public Economics - - Taxation, Subsidies, and Revenue - - - Tax Evasion and Avoidance

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