پژوهشنامه مالیات
سال سی و یکم شماره 106 (تابستان 1402)

Reducing the vulnerability of the economy by creating stable government revenues and also improving the distribution of revenues are important policy components in the upstream documents and general policies of the system. Considering the importance of improving the efficiency of the tax system in line with paragraph 17 of the resistance economy, this study investigates the possibility of developing the tax system and the stability of government revenues using provincial statistical evidence over 2011-2019 and using the quantile regression approach and Non-linear Autoregressive Distributed Lag. The results of the estimates show that in high tax quantile, the elasticity of all types of taxes has increased and is greater than unity, and the increase in the share of taxes on goods and services, along with the high elasticity of this type of tax relative economic growth, indicates the stability of the government's income. Finally, the low tax efficiency, along with the non-significance of the asymmetry of positive and negative economic growth shocks on all types of taxes, indicates the unfavorable situation of the current tax system, therefore, identifying new tax capacities and establishing a strong relationship between economic growth and tax bases is the most important policy in line with the vision of  the general policies of the system.

Tax revenues are one of the most important sources of funding for governments, and one of the reasons why the realized tax revenue is lower than the expected amount is tax fraud. In order to reduce tax frauds, tax audits should be done in the tax organization, so in this research, a tax audit model has been presented with regard to the effects of psychological safety and knowledge of tax audits during the detection of tax frauds. The method used in this research is qualitative, foundational data and inductive analysis. The statistical population of this research includes experts in the tax audit profession, which includes 25 experts. The questionnaire information was completed in 1401. And according to the analysis, it was observed that smart and digital provincial tax, psychological safety of tax auditors, knowledge of tax audit, detection of tax frauds, sharing information related to fraud, audit knowledge of the tax director general and psychological security created by the director general. The results show that the biggest impact on tax audit is related to the psychological safety of tax auditors and then the discovery of tax frauds.

The objective of this study is to examine the effect of imposing agricultural tax on macroeconomic variables, sectoral output and households’ welfare. To get the objective, a Social Accounting Matrix based CGE model was applied. The findings showed that imposing tax rate of 20% on agricultural land and natural resources will increase government tax revenues by more than 5 percent; however it has a negligible effect on other variables. As for value added (output) tax, a 15% tax will result in 15% (more than 20%) increase in government tax revenues while it induces a reduction in GDP by less than 2% (more than 3.2%) as well as prices increase by 3.2% (around 4%). However, 15% value added tax is expected to reduce output in some agricultural activities by more than 10% as well as by less than 3% in no-agricultural sectors. The same pattern of output changes is expected to be realized for output tax scenario. The rural households’ welfare will decrease by more than 4% under land and agricultural natural resources tax of 15% while those of the urban households tend to increase slightly. The corresponding values for 15% value added tax in rural and urban areas are 7-9% and 4-5% welfare reduction, respectively. Imposing this tax rate on agricultural output will lower the rural households’ welfare by 10-12% while the corresponding range for urban households is half of the rural households’ one.

The share of tax revenues in providing the government's current expenses which is known as the tax coverage index, has always been one of the important indicators for evaluating the performance of the country's tax system, which can play an effective role in the country's economy at the macro level. Experience has shown that financing a large part of current expenses through unstable oil revenues in Iran, in the conditions of sanctions or the fluctuation of global oil prices, the government faces a basic challenge such as a budget deficit. Therefore, the need to cover the government's current expenses through tax revenues becomes increasingly apparent. Therefore, in this research, the effect of the effective factors on the share of tax revenues in financing the government's current expenses is investigated using the Autoregressive Distributed Lag in the time period of 1980-2021. The results show that the ratio of the government budget deficit to current expenses has a positive and significant effect, and the share of oil revenues in providing the current expenses of the government, the share of added value of the agricultural sector in the GDP and the degree of openness of the economy have a negative and significant effect on the tax coverage index. Also, the special conditions related to the years of imposed war have also had a negative effect on the amount of the mentioned index.

The current study is descriptive-survey research that was conducted with the aim of investigating the potential of blockchain in realizing tax revenues in Iran. The statistical population of this study consists of the employees of the General Department of Tax Affairs of Fars, which number is equal to 110 people. According to the Morgan's table, the sample size was determined to be 86 males. Due to the possibility of some questionnaires being unusable, 95 questionnaires were distributed by simple random sampling, of which 88 questionnaires were returned. Also, in order to prioritize the indicators, the opinions of seven experts were used. In order to reach the donation of the research, first by reviewing the theoretical research literature, fifteen primary indicators were identified as the potentials of blockchain in realizing tax revenues; Then, using the binomial distribution technique, eight indicators were determined as the most important potentials of blockchain in realizing tax revenues, and seven indicators were eliminated. In the next step, the fit of the proposed model was confirmed through confirmatory factor analysis. Finally, using the OPA technique, indicators were prioritized; based on this, the indicators of  increasing trust in the tax system, non-manipulation, speeding up the tax collection mechanism, no need for third party intervention and approval, higher flexibility than current systems, higher encryption, saving and maintaining all transactions and viewing transactions as "on the spot" ranked one to eight respectively.

Governments need stable and reliable financial resources to carry out their public duties, and taxes have long been one of the most important sources of funding for governments to carry out their duties. Preventing or reducing the amount of tax evasion has been one of the important concerns of governments in the economic field in recent years. In this research, the category of tax evasion using artificial intelligence and focusing on a set of 57 financial and non-financial indicators at the macro-economic level, taxpayers and tax auditors, in a sample including 978 legal taxpayers' files of the General Directorate of Tax Affairs of Mazandaran. It has been examined for the years 2011 to 2018. In this research, in order to extract effective features, sine cosine and gray wolf optimization algorithms were used, and decision tree and artificial neural network algorithms were used to model tax evasion and test features. Based on the results, the sine-cosine optimization algorithm along with the decision tree predictor has a lower error value than other models and provides a more accurate model for predicting tax evasion.