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The Non-Linear Effect of Income on the Shadow Economy

Authors: Maria Rosaria Alfano; Salvatore Capasso; Salvatore Ciucci; Nicola Spagnolo;

The Non-Linear Effect of Income on the Shadow Economy

Abstract

Abstract We study the relationship between individual’s income and tax evasion and show that this is convex, suggesting the existence of an income threshold value. Given the level of public goods provision and the perceived fairness of public services, individual’s income negatively affects tax evasion up to the point where people feel they are paying the right amount of taxes compared to the value of the goods and services they receive from the public sector. After that point, individuals consider the tax burden to be unfair and the impact of income on the level of tax evasion turns out to be positive. We also show that the income threshold value depends on the tax rate and tax enforcement system. We empirically test or hypothesis and by using a panel data-set of 143 countries over the period 1996–2015, we provide evidence of a convex relationship between income and the aggregate level of underground economy.

Country
Italy
Keywords

Shadow economy; Public expenditure; Tax fairness; Non-linearity

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Top 10%
Average
Top 10%
hybrid