Imperfect Detection of Tax Evasion in a Corrupt Tax Administration
AbstractThis article models the imperfect detection of tax evasion motivated by the existence of a corrupt tax administration. Consistent with previous literature, fines and audit probabilities both have a positive effect on compliance. Moreover, the model shows that they have a negative effect on the bribes paid to corrupt tax officials. More corruption decreases compliance levels, giving honest auditors incentives to work harder to detect evasion. Giving inspectors a share of the detected evasion (tax farming) makes auditors work harder; however, increasing their wages reduces their exerted effort to discover evasion. Higher compliance can as well be achieved by hiring more efficient inspectors.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 39198.
Date of creation: 27 Jul 2011
Date of revision:
Taxation; Evasion; Corruption;
Other versions of this item:
- Diego Escobari, 2012. "Imperfect Detection of Tax Evasion in a Corrupt Tax Administration," Public Organization Review, Springer, vol. 12(4), pages 317-330, December.
- D73 - Microeconomics - - Analysis of Collective Decision-Making - - - Bureaucracy; Administrative Processes in Public Organizations; Corruption
- J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
- H83 - Public Economics - - Miscellaneous Issues - - - Public Administration
- H26 - Public Economics - - Taxation, Subsidies, and Revenue - - - Tax Evasion
This paper has been announced in the following NEP Reports:
- NEP-ACC-2012-06-13 (Accounting & Auditing)
- NEP-ALL-2012-06-13 (All new papers)
- NEP-IUE-2012-06-13 (Informal & Underground Economics)
- NEP-PBE-2012-06-13 (Public Economics)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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