Volume 28, Issue 48 (2021)
J Tax Res 2021, 28(48): 33-60 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Assadollahzadeh Bali S R, Damankeshideh M, Hadinejad M, Geraeinejad Q, Momeni Vesalian H. Determination of Optimal Value Added Tax Rate Based on the Size of Underground Economy. J Tax Res 2021; 28 (48) :33-60
URL: http://taxjournal.ir/article-1-1924-en.html
URL: http://taxjournal.ir/article-1-1924-en.html
Seyed Rostam Assadollahzadeh Bali * 
, Marjan Damankeshideh , Manijeh Hadinejad , Qolamreza Geraeinejad , Hooshang Momeni Vesalian
, Marjan Damankeshideh , Manijeh Hadinejad , Qolamreza Geraeinejad , Hooshang Momeni Vesalian
Abstract: (6317 Views)
Nowadays it is obvious that higher share of tax revenues in budgeting and its role in developing dynamic economy has been a main criterion of growth in each country. The value added tax has been focused by policy makers due to its transparent collection. It is crucial to determine optimal and appropriate tax rates to achieve economic objectives. The underground economy and its activities which are accompanied by false information declaration affect the level of government tax revenue collections. This paper seeks to determine optimal tax rates in three introduced models by using the Particle Swarm Optimization (PSO) Algorithm and the current data during the period 2008-2017 in two different conditions of underground economy and its absence. The results indicate that government collects near optimal value added tax by VAT rate optimization. On the other hand, the higher changes in value added tax rates have significantly positive effect on underground economy.
Keywords: Tax, Value Added Tax (VAT), Underground Economy, Particle Swarm Optimization (PSO) Algorithm
Type of Study: Research |
Subject:
Management
Received: 2021/04/11 | Accepted: 2021/02/28 | Published: 2021/04/20
Received: 2021/04/11 | Accepted: 2021/02/28 | Published: 2021/04/20
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
