Study of Fuzzy Logic to Estimate the Size of the Underground Economy in Iran
Keywords:
Underground economy, economic sanctions, fuzzy logic, fuzzy inference system, autoregressive distributed lag modelAbstract
The presence of underground economic activities in a society constitutes a major source of social and economic dysfunction. Operating through opaque and unregulated channels, these activities undermine the effectiveness of social and economic policies, contribute to fiscal and monetary imbalances, and distort policy outcomes. Furthermore, economic sanctions imposed on Iran—beginning with the Islamic Revolution and intensifying in recent years—have posed significant challenges to the country's economy, influencing both domestic and international economic dynamics. Accordingly, this study employs a multi-stage fuzzy modeling approach to estimate the size of Iran’s underground economy during the period 1991–2024. Utilizing Iranian time series data, the study also introduces a composite index of sanctions by quantifying and weighting various historical sanctions. These sanctions are incorporated into an Autoregressive Distributed Lag (ARDL) model as dummy variables to evaluate their effect on the underground economy. The findings indicate that the average size of the underground economy in Iran during the study period was approximately 37 percent of GDP. In the short-term analysis, weak sanctions were found to have no statistically significant effect on the underground economy, whereas moderate and strong sanctions exhibited positive and significant effects, with coefficients of 0.056 and 0.86, respectively. The long-term analysis revealed that weak and strong sanctions had no significant impact, while moderate sanctions were associated with a positive and statistically significant effect, with a coefficient of 0.72.
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