Introduction
Since the mid-1990s, a growing body of research has investigated the relationship between global networks of international trade, information flows, and migrations. Whereas traditional trade theory (e.g., the standard Heckscher-Ohlin model) suggests that the movement of goods across borders can substitute for the movement of production factors, the bottom line of this branch of research is that the two complement each other. However, there is sizeable empirical literature (e.g., Felbermayr & Toubal, 2012; Felbermayr & Jung, 2009; and Parsons & Vezina, 2018) suggesting a positive nexus between migration and bilateral trade.
Theoretical framework
Two main arguments have been used in the literature to explain such a positive link. Firstly, international migrants provide additional information on their origin country and reduce the bilateral cost of a trade, stimulating the host country's exports towards the origin country of immigrants. In this regard, migrants help domestic firms overcome cultural barriers to trade (e.g., language and local taste of consumers) and create international business relationships (Figueiredoa, 2020: 406). In recent empirical and theoretical studies, information costs have been introduced as a deterrent to trade (Steinwender, 2013; Allen, 2014; Chaney, 2014). In addition to immigrants' knowledge about informal institutions in the origin country, immigration prevents the opportunistic behaviors of some that are weak institutions in international trade. Therefore, it is expected that further migration will facilitate bilateral trade. (Parsons & Vezina, 2018; 210) Secondly, immigrants have preferences for consuming goods/varieties produced in their own country of origin (Figueiredoa, 2020: 408).
Most of the literature has a common empirical strategy, based on the estimation of a log-linear gravity model where bilateral trade flows are regressed over standard explanatory variables (economic mass and distance), the stock of immigrants from specific partner countries, and other controls aiming at capturing various types of trade costs (common language, colonial relationships and the like). Other standard control variables include neighborhoods, language sharing, and free trade agreements.
Methodology
This paper investigates the impacts of migration on trade networks between Iran and 25 of its trade partners in 2015, using the spatial regression method. The statistical population of this study is Iran's trading partners, including 25 countries with the highest trade value with Iran in 2015, respectively China, UAE, India, Turkey, South Korea, Switzerland, Germany, Italy, Pakistan, Netherlands, France, Russia, Singapore, Brazil, United Kingdom, Oman, Thailand, Spain, Vietnam, Belgium, Japan, Egypt, Malaysia, Kuwait, and Azerbaijan. 
Results and Discussion
The estimated model in spatial regression form is as follow:
 
 is log sum of export and import from origin i to destination j country,  is log stock of immigrant from origin i to destination j country,  and  are origin and destination population,  and  are origin and destination gross domestic product,  is dummy variable for having a common border,  is a dummy variable for having a common language and is the inverse amount of geographic distance between origin i and destination j country. W is the matrix of commercial networks that calculate from a hypergeometric distribution, which is used in various fields from genetics to network theory. According to the estimated trade network matrix, Iran has trade networks with eight countries: Azerbaijan, China, India, Kuwait, Oman, Pakistan, Turkey, and the UAE. It also has an immigration network with three countries: Germany, Turkey, and England. In other words, Iran and Turkey have not only trade networks but also migration networks.
  Conclusion and suggestions
Due to the variable coefficient of migration, a one percent increase in immigrant stock caused an increase in bilateral trade flow by 0.28 percent. In other words, in contrast with H-O theory, migration and trade complement each other, which is consistent with most recent empirical studies. The development of regional trade agreements is a way to prepare countries for the globalization process and protect the economies of developing countries from global competition. Therefore, facilitating migration in the countries of the region and trade agreements leads to regional growth. It can also strengthen countries' competitive advantage in various markets and increase intra-regional investment.
The results show that trade networks between countries lead to strengthening bilateral trade flows and leading countries to increase trade relations.  The existence of various fields of cooperation, including cultural, religious, linguistic, and everyday religious fields, has provided cooperation. Nevertheless, to direct the trade activities, creating a trade bloc can also result in regional growth. Almost worldwide, homogeneous blocs and trade unions have been formed at different levels, and regionalism becomes an incentive for countries to have a corporation with each other, regardless of their sizes.
Also, due to the significant coefficient of spatial error, the effect of external shocks in countries with trade networks on other countries' bilateral trade flow is significant. Therefore, efforts to increase security in trading partner countries alongside trade relations and help eliminate tensions and create calm will reduce Iran's trade risks.