Modeling Iran's foreign trade with emphasis on sanctions and geopolitical risk indicators

In the past few years, Bayesian econometrics has provided suitable solutions to overcome uncertainties regarding the selection of parameters and models. This research seeks to identify and prioritize the variables affecting Iran's foreign trade with an emphasis on sanctions and geopolitical risk indicators. For this purpose, Bayesian, dynamic, and selective averaging modeling has been applied using 45 variables affecting foreign trade between 1370 and 1400 (solar year). According to the results, among BMA, TVP-DMA, and TVP-DMS, BVAR, and OLS models; the BMA model was determined as the most efficient model.Based on the BMA model, 11 non-fragile variables affecting foreign trade were identified, which are: sanctions, structural institutional index, real effective exchange rate, export complexity, interest rate, business climate, economic openness, economic growth rate, geopolitical risk, inflation and trade integration index (Grobel and Lloyd index). A sanction, geopolitical risk, and interest rate had a negative effect on foreign trade, and other variables had positive effects. The volume of Iran's foreign trade is facing a high fluctuation because of the high probability of the occurrence of non-fragile variables. To improve the performance of Iran's foreign trade indicators, considering the impact of geopolitical risks and sanctions on the country's foreign trade, improving economic flexibility and resilience policies should be ordered by policymakers.