Mohamad Barzegari, Ashkan Harati, Roya Behboudi, Fereshteh Hajmohamadi, Nasim Babaee,
Volume 0, Issue 0 (2-2024)
Abstract
In this research, the driving forces of tax evasion in Iran have been compared using time series data from 1357 to 1400 from three different methods. One of these methods is the multiple-indicators-multiple-causes MIMIC approach based on structural equation model estimation. Another model is based on Tanzi's CDA and vector error correction model (VECM). The last one is based on a dynamic general equilibrium (DGE). Based on the calculation results, the driving forces of tax evasion obtained using the MIMIC show that the ratio of tax evasion to tax collection is 29% on average during the period under review. Also, according to the Tanzi's money demand model, the ratio of tax evasion to tax collection is 36% on average during the period under review. Based on the DGE, the ratio of tax evasion to tax collection is 34%. These findings emphasize the pressing need for comprehensive measures to address tax evasion and its detrimental impact on the economy. Without a clear understanding of the underground economy and accurate assessments of tax evasion, effective corrective measures and appropriate strategies cannot be implemented. Therefore, it is imperative for policymakers to utilize such estimations and findings to develop targeted interventions and policies aimed at curbing tax evasion and reinforcing tax structures in Iran. We find that the structural validity of the MIMIC for measuring trends in the shadow economy is nearly similar to the DGE and CDA. This similarity removes the skepticism that some previous literature had towards these methods.
