ECO Trade Potential: The Application of Dynamic Spatial Regression by Considering Spatial Spillover Effects

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.
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 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.
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.