atefeh dehghani; Maryam shafie kakhaky
Abstract
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 ...
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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.
hoda askary; Maryam shafie kakhaky
Abstract
Regional agreements can facilitate the integration of world economies by opening the borders to the trade development while accelerating technological changes and maintaining the economic growth. Trade potential is defined as the trade that could be achieved at an optimum trade frontier with the open ...
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Regional agreements can facilitate the integration of world economies by opening the borders to the trade development while accelerating technological changes and maintaining the economic growth. Trade potential is defined as the trade that could be achieved at an optimum trade frontier with the open and frictionless trade possible through regional agreements based on the current level of trade, transport, and institutional technologies. Earlier studies have estimated the trade potential by using the gravity equation through OLS estimates as the potential trade. From the beginning of the gravity model of trade, the space is taken into account by considering the impact of distance variable and other relevant variables on the volume of trade, such as geographic contiguity, common language, and the common currency. However, these variables could not be satisfied alone if the aim is to consider the dependence on space. The Econometric literature suggests to model this phenomena with the appropriate spatial econometric models and methods.
Methodology
The literature shows how, at an empirical level, the classical Gravity Model brings good results to explain the international trade. Since the gravity model has physical roots, the trade flow depends on the dimension of both the origin and the destination country as well as the distance between them. Recently, several studies have highlighted that an additional effect which should be taken into consideration is the spatial dependence. In the international trade, spatial dependence can be justified by the role of the third country effect. The so called third country effect is connected with two different phenomena: the location factor theory that fosters the spatial spillover effects and the persistence phenomena. For the first phenomena, it is asserted that if some structural changes happen in one country in a way that they affect its trade flow, they will affect the trade flow of the neighbors as well, thus, producing positive effects on the volume of flows. On the other side, the third country can foster persistence effect, which is based on the relative trade cost between countries i and j compared with the cost between i and k, where k is the third country. Assuming this phenomena, an increase in the competitiveness of the third country lowers its trade cost and, consequently, lowers the flow between the couple ij.
There are two econometric motivations for the use of spatial regression model that involves the spatial lag. The first motivation comes from viewing spatial dependence as a long-run equilibrium of an underlying spatio-temporal process; the second motivation shows that the omitted variables that exhibit the spatial dependence lead to a model with spatial lags of both the explanatory and the dependent variable. The first motivation results in a Spatially Autoregressive Model (SAR) that contains spatial lags of the dependent variable. The second econometric motivation leads us to a model with a spatial lag of both the explanatory and the dependent variables which is called Spatial Durbin Model (SDM). In this study, we modeled the country-to-country trade flow over the period from 2005 to 2014 for the Economic Cooperation Organization (ECO) using a dynamic spatial regression model. The sample was restricted to the 10 ECO countries for n=10 years, resulting in a n*n*T = 1000 observations. In order to choose between random versus fixed effect specification, a spatial Hausmann test was performed. This test highlights the strong preference for the fixed effect model. Also, we modified Wald test for groupwise heteroskedasticity in the fixed effect regression model and Durbin-Watson test for the Residual autocorrelation detection.
Results and discussion
Results of SDM confirm the assumption of the effectiveness of spatial effects. In other words, there is a positive spatial relationship between the observations on the trade potential of ECO member countries.
The results shows that the sign in the basic components are similar to the existing literature. GDP of the origin as well as the destination country is significant, as predicted. Furthermore, the inverse distance has the predicted positive impact on the trade flow. Common language plays a positive role, thus, increasing the trade flow.
Conclusion
The results show a good fit of the spatial gravity model to the related data on the trade between ECO countries, hence, confirming the importance of the structural variables of the theoretical model through the presence of spatial dependence that motivates the choice of a SDM model with both the lagged dependent and the independent variable. This results in the confirmation of the theory relating to spillovers and locational factors. The results represent the importance of a common language, GDP origin, the destination countries, and the distance between the two countries and adjacency on trade flow between ECO member countries. Also, in this study spillovers are estimated by both the spatial autocorrelation coefficient and the indirect impact of the explanatory variables. The results shows significant spillover effects of trade and insignificant spillover effects of the explanatory variables.
Accordingly, select trade partners and new members from industrialized countries, with a GDP higher than the average of ECO members, is suggested.
