فهرست نشریات علمی دسترسی آزاد ایران

Tax evasion is a multifaceted issue influenced by a range of political, economic, and sociocultural factors. This study examines the dynamics of tax evasion in Iran using a hybrid methodological framework. Utilizing annual data from 1991 to 2022, we apply the Weighted Average Least Squares (WALS) approach to identify the most robust determinants of tax evasion, followed by a time-frequency analysis using Continuous Wavelet Transform (CWT) to examine their temporal behavior. The WALS results highlight inflation as the most influential factor in driving tax evasion. Furthermore, wavelet-based analysis reveals that while economic variables exert more substantial short-term effects, social and cultural variables demonstrate more sustained, long-term impacts. This temporal distinction suggests that behavioral and value-based reforms take longer to influence taxpayer behavior than policies based on monetary incentives or punitive enforcement. Given the variability in both the strength and timing of these influences, the findings underscore the importance of designing a multi-layered policy response. Policymakers are advised to implement an integrated strategy that combines short-, medium-, and long-term interventions, with a particular focus on non-fragile variables that consistently shape tax evasion patterns.