TAX EVASION IN THE IMPORT SECTOR IN ECONOMY OF IRAN COMBINATORIAL MODEL APPROACH OF ARTIFICIAL NEURAL NETWORK AND SIMULATED ANNEALING ALGORITHMS

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MADDAH MAJID; KHLEGHPANAH ZAHRA

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Paper Information

Journal: THE JOURNAL OF PLANNING AND BUDGETING Year:2015 | Volume:20 | Issue:2 Page(s): 85-102

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Title

TAX EVASION IN THE IMPORT SECTOR IN ECONOMY OF IRAN COMBINATORIAL MODEL APPROACH OF ARTIFICIAL NEURAL NETWORK AND SIMULATED ANNEALING ALGORITHMS

Author(s)

MADDAH MAJID | KHLEGHPANAH ZAHRA | Issue Writer Certificate

Keywords

TAX EVASIONQ2

IMPORTQ2

ARTIFICIAL NEURAL NETWORKQ2

MULTILAYER PERCEPTRONQ2

SIMULATED ANNEALING ALGORITHMSQ2

IRANIAN ECONOMYQ2

Abstract

Import tax is one of the government revenue sources that some of its portion is not accessible to government due to TAX EVASION. In this study, the factors affecting TAX EVASION in IMPORT, have been identified by using the combinatorial model of ARTIFICIAL NEURAL NETWORK and SIMULATED ANNEALING ALGORITHMS that is capable to analyze the nonlinear systems. For this purpose, four explanatory variables representing TAX EVASION in the Iran’s economy include tax burden on IMPORTs, the size of governments, tax payers’ real income and trade were considered in specified final model. The results from optimization of TAX EVASION using SIMULATED ANNEALING ALGORITHMS indicate that the optimum of the burden tax on IMPORTs, government size, economic openness and real income per capita are 6.18 percent, 13.2, 6.69 Million Rials, 1.29 percent, respectively; Also, the minimum TAX EVASION in the period under analysis amounts to 21.48 percent.

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APA: Copy

MADDAH, MAJID, & KHLEGHPANAH, ZAHRA. (2015). TAX EVASION IN THE IMPORT SECTOR IN ECONOMY OF IRAN COMBINATORIAL MODEL APPROACH OF ARTIFICIAL NEURAL NETWORK AND SIMULATED ANNEALING ALGORITHMS. THE JOURNAL OF PLANNING AND BUDGETING, 20(2), 85-102. SID. https://sid.ir/paper/241028/en

Vancouver: Copy

MADDAH MAJID, KHLEGHPANAH ZAHRA. TAX EVASION IN THE IMPORT SECTOR IN ECONOMY OF IRAN COMBINATORIAL MODEL APPROACH OF ARTIFICIAL NEURAL NETWORK AND SIMULATED ANNEALING ALGORITHMS. THE JOURNAL OF PLANNING AND BUDGETING[Internet]. 2015;20(2):85-102. Available from: https://sid.ir/paper/241028/en

IEEE: Copy

MAJID MADDAH, and ZAHRA KHLEGHPANAH, “TAX EVASION IN THE IMPORT SECTOR IN ECONOMY OF IRAN COMBINATORIAL MODEL APPROACH OF ARTIFICIAL NEURAL NETWORK AND SIMULATED ANNEALING ALGORITHMS,” THE JOURNAL OF PLANNING AND BUDGETING, vol. 20, no. 2, pp. 85–102, 2015, [Online]. Available: https://sid.ir/paper/241028/en

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