Journal of Economic Modeling Research

One of the factors that have a significant impact on the economic development of countries is reliance on foreign trade, and due to the dependence of countries on export earnings and the import of foreign trade, it plays an essential and indisputable role in the growth and development of different sectors. Foreign trade in agricultural products has an important role in expanding the export and import of various countries due to its high and stable value. Among the agricultural products, saffron is one of the most important export commodities of agriculture, which contributes greatly to the creation of agricultural value added. This study examines and analyzes Saffron's foreign trade network among 11 active countries including Iran in this area. The required data and statistics were collected during the years 2007-2016. Considering the geographical dispersion of the studied countries, a spatial panel model was used to analyze the factors affecting the value of saffron trade. The results of estimating OLS methods, spatial interruption and spatial error showed that import price variables per gram, export price per gram, export volume, export standards index, gross domestic product, exchange rate and government support index in agricultural sector is significant and has a positive effect on the value of trade. Positive and significant spatial dependency coefficient shows that neighborhood is an important role in increasing or decreasing trade. This means that, as long as the value of saffron trade in neighboring countries increases, the value of trade in the target country will increase as the size of the coefficient.

The existing trade models suggest that for tradable goods potential partners can be many, but eventually only one (the one offering the best price) should be selected, therefore relatively few (unidirectional) trade links will appear between countries. If the structure of international trade flows describes as a network, trade link would give rise between countries. This paper exploit recently-developed indicators based on network analysis such as node-degree, node-strength and node-disparity, and second-degree characteristics such as node-clustering and centrality indicators to investigate the pattern of international trade pattern followed by Iran and its Asian partner. The results of this study show that East Asian countries, have had a greater increase in the number of trade partners. Iran and its trading partners in Asia, is growing trade links with countries that have more trading partners. Nearest neighbor degree index show that selected countries are looking to improve relations with countries that have more similarities with his own country. Based on the centrality, it was found that only China with the centrality index of .97 is in the core of global trade network. Emirates, Taiwan, Korea and Thailand respectively with values of .94, .92, .94 and .91 are in the inner-periphery and Turkey with a value of 0.87 is in secondary-periphery. Iran with a value of 0.72 is in outside of the global trade network