STUDY ON COMPUTATIONAL EXPERIMENTS OF C2C TAX COMPLIANCE BASED ON INFORMATION OF CYBERMEDIARIES

Feng Xiong (), Shaojie Xiang () and Peng Jin
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Feng Xiong: School of Business Administration, Zhongnan University of Economics and Law Nanhu Road, Wuhan 430073, P. R. China
Shaojie Xiang: School of Business Administration, Zhongnan University of Economics and Law Nanhu Road, Wuhan 430073, P. R. China
Peng Jin: #x2020;Business Department, Ningbo University, Fenghua Road, Ningbo 315211, P. R. China

Advances in Complex Systems (ACS), 2019, vol. 22, issue 02, 1-29

Abstract: The impact of cybermediaries’ information on Consumer to Consumer (C2C) tax compliance is investigated by using a computational experiment approach and three conclusions are drawn. First, cybermediaries’ information assists tax authorities in selecting audit objects and discovering unregistered taxpayers, and the second signaling role is the main reason for the improvement of the C2C tax compliance rate in the case of low audit probability. Second, the signaling role of cybermediaries’ information is quite limited if the audit probability is low; the increase of the audit probability can directly improve the C2C tax compliance rate as well as indirectly by enhancing the signaling role of cybermediaries’ information; in addition, if the proportion of honest taxpayers is lower than a certain threshold, the lower the proportion is, the lower the signaling role is, ceteris paribus. Finally, the signaling role of cybermediaries’ information on the selection of audit objects rises with the increase of the correlation degree between cybermediaries’ information and taxable income of taxpayers, and a critical value of the correlation degree exists, below which the signaling role of cybermediaries’ information is negative. We also discuss how to enhance the signaling role of cybermediaries’ information to improve the C2C tax compliance rate.

Keywords: Tax compliance; C2C; cybermediaries’ information; computational experiment (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1142/S0219525919500036

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