Modeling Aggressive Tax Policies Dynamic Variable Selection Markov Chain Monte Carlo Simulation

Articles in Press

Document Type : Original Article

Authors
Morid Aalipour birgani 1
Ali Rezaeian 2
Alireza Jorjorzadeh 3
Allah Karam, Salehi 4
1 Ph.D. Student in Accounting, Department of Accounting, Islamic Azad University, Ahvaz, Iran.
2 Department of accounting and management, Ahv.C., Islamic Azad University, Ahvaz, Iran.
3 Department of Economics, Islamic Azad University, Ahvaz, Iran.
4 Department of Accounting, MaS.C., Islamic Azad University, Masjed-soleiman, Iran
10.22034/jik.2026.79065.4891
Abstract
Tax is a cost imposed by the government on all profit-making units that generate income; bold financial reports are in contrast to conservative financial reports, and its concept is the use of a low degree of conservatism in preparing financial statements. Bold tax policy has recently received more attention from economic enterprises; but several factors affect the adoption of tax policy; Accordingly, the main objective of the present study is to model bold tax policies in the Tehran capital market. The method of the present study is exploratory. The research period is 1402-1390. The model was estimated using information from 221 companies. In this study, 80 variables affecting bold tax policies were examined in the framework of selective dynamic Markov chain Monte Carlo simulation modeling. Based on the results obtained, 16 variables were identified as the most important variables affecting bold tax policies; Also, based on the results, intra-company variables were more important than extrinsic variables in adopting this type of strategy. Company size was determined to be the most important effective variable in adopting a bold tax policy. Given that company size has a negative effect on adopting a bold tax strategy; as a result, the theoretical perspective of political power theory in the field of adopting bold tax policies in listed companies was confirmed.
Keywords
Taxation
Aggressive Tax Policies
Capital Market
Dynamic Variable Selection Markov Chain Monte Carlo Simulation

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