Public sector economics
Ahmadreza Ahmadi; Ghahreman Abdoli; Fatemeh Azhari
Abstract
The present study examines the impact of globalization on Iran’s underground economy over the period 1979–2020. In this regard, the size of the underground economy was estimated using the MIMIC method. Subsequently, the effects of the three main dimensions of globalization—economic, ...
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The present study examines the impact of globalization on Iran’s underground economy over the period 1979–2020. In this regard, the size of the underground economy was estimated using the MIMIC method. Subsequently, the effects of the three main dimensions of globalization—economic, social, and political—as well as the dual components of each dimension (de facto and de jure), were analyzed using the autoregressive distributed lag (ARDL) approach. The findings from the long-run estimations indicate that the economic and social dimensions of globalization have a negative effect on the underground economy, whereas the political dimension exerts a positive effect. Further analysis of the components of each globalization dimension reveals that both the de facto and de jure components of social globalization negatively influence the underground economy. Although the de jure component of economic globalization also has a negative impact, its de facto component does not have a significant effect. Regarding the political dimension, de facto component has a significant positive effect on the underground economy, while the de jure component does not show a meaningful impact. Additionally, the results demonstrate that, in all four estimated models, unemployment has a positive effect and financial deepening has a negative effect on the underground economy. These findings offer useful guidance for policymakers aiming to reduce the size of the underground economy and enhance economic transparency in the country.
Financial Economics
Ahmadreza Ahmadi; Mohammad Boushehri
Abstract
The expansion and deepening of the financial sector-one of the most critical sectors of any economy-can influence tax evasion. The present study aimed to examine the effect of the deepening of financial institutions and markets on tax evasion in Iran. First, the multiple indicators multiple causes (MIMIC) ...
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The expansion and deepening of the financial sector-one of the most critical sectors of any economy-can influence tax evasion. The present study aimed to examine the effect of the deepening of financial institutions and markets on tax evasion in Iran. First, the multiple indicators multiple causes (MIMIC) method was used to estimate the relative size of tax evasion in Iran, revealing an average rate of 8.1% in Iran’s economy. Then, relying on the indicators published by the International Monetary Fund (IMF) for the period 1980–2022, the study used the autoregressive distributed lag (ARDL) approach to examine the effect of the deepening of financial institutional and markets on tax evasion. The long-run estimates indicated that both financial institutional deepening and financial market deepening have a negative effect on tax evasion. In terms of size (absolute value), the effect of financial institutional deepening on reducing tax evasion is greater than that of financial market deepening. Among the control variables, the tax burden exhibits an inverted U-shaped relationship with tax evasion, while oil rents have a positive effect on it. It was also noted that tax evasion significantly decreased during the post-JCPOA period (2017–2022).IntroductionAddressing tax evasion in Iran is of critical importance, particularly given the government’s long-standing dependence on oil revenues-a concern frequently emphasized by economists and policy experts. Reducing the dependence through oil rents and shifting toward tax-based revenue through the expansion of the tax base and the reduction of tax exemptions can be considered a vital step toward accelerating economic development and societal well-being. While the scholarly literature on tax evasion has examined various aspects of this hidden segment of the economy, most studies have focused on estimating its size and scope. Few have investigated the effects of the deepening of financial institutions and financial markets on tax evasion separately. To address the gap, the present research aimed to examine the separate effects of the deepening of financial institutions and financial markets on tax evasion in Iran. The research questions are as follows: Do the deepening of financial institutions and financial markets have a significant effect on tax evasion? And if so, in what way?Materials and MethodsThe study estimated the relative size of tax evasion by using the multiple indicators and multiple causes (MIMIC) method over the period from 1980 to 2022. The autoregressive distributed lag (ARDL) model was also employed to examine the effect of financial institutions and markets on tax evasion. The analysis used the Financial Development Index published by the International Monetary Fund (IMF). This index ranks countries based on the depth, efficiency, and accessibility of their financial institutions and markets, on a scale from 0 (lowest) to 100 (highest). Concerning the research model, TaxEva was the dependent variable representing the level of tax evasion as a proportion of GDP. FID and FMD denoted the financial deepening indicators for financial institutions and financial markets, respectively. OilRR referred to oil rents as a percentage of GDP, calculated as the difference between the value of crude oil production at global market prices and total production costs. Moreover, TaxB represented the total tax burden, defined as the ratio of total direct and indirect taxes to GDP; its squared term was also included in the model. The research model was explained based on the specified variables as follows: Results and DiscussionThe results of the estimation of the long-run model confirmed several key points. First, both the deepening of financial institutions and the deepening of financial markets have a negative effect on tax evasion. Second, in terms of size (absolute value), the inverse effect of financial institution deepening on tax evasion is greater than that of financial market deepening. According to theoretical foundations, the deepening of financial institutions and markets reflects the broader development of a country’s financial sector. This development narrows the gap between lenders and borrowers, reduces information asymmetry, and decreases the financial requirements of companies-all of which contribute to a decrease in tax evasion. Another important finding is the inverse U-shaped relationship between the tax burden and tax evasion. Specifically, up to a threshold of 4.203% of GDP, an increase in the tax burden leads to higher tax evasion. Beyond this point, however, further increases in the tax burden are associated with a reduction in tax evasion. Finally, the results showed that oil rent has a positive effect on tax evasion, providing empirical support for the resource curse hypothesis. This suggests that reliance on resource revenues can weaken the government’s tax income.Table 1. Results of Estimated Long-Run Coefficients VariableCoefficientStd.ErrorT-StatisticProv. -0.0790.033-2.420.025 -0.0370.007-5.060.000 -8.1201.044-7.770.000 0.9660.1277.630.000 0.0930.00712.790.000*Source: Research estimatesConclusionIn light of the findings, it is recommended that policymakers adopt policies to increase the deepening of financial institutions and markets in Iran. These policies may include reformulating and amending the laws governing financial institutions and markets to improve transparency, as well as establishing appropriate mechanisms for monitoring. In addition, the development of information and communication technology (ICT) infrastructure is essential to increase access to financial services across the country. Given the observed negative impact of oil rent on tax evasion, it is also advisable to adopt policies to reduce the government’s dependence on oil rents. Instead, greater emphasis should be placed on the role of the tax system as a source of public revenue. The present study has several limitations. These include the simplicity of the model used, constraints related to data availability over time, and the limitations inherent in the chosen estimation method.
