DYNAMICS OF WORLD TRADE NETWORK

Abstract

This study aims to explain the dynamic changes in the world trade from the network perspective. For this purpose, we use a gravity model of international trade and try to explore the trade effects of country-specific properties and the network indices for these countries. We combine gravity, network, and trade datasets from CEPII for the years between 1995 and 2010. Country-specific properties used in this study are GDP, population, and other geographical properties of the countries. Moreover, to analyze the differences among countries in terms of development, we also divide data into developed and developing countries. Network indices employed apart from the country-specific properties as explanatory variables in this paper are local centrality measures such as degree and strength, and global centrality measures which are closeness and eigenvector. We find that centrality measures positively and significantly affect countries' bilateral trade. Since these measures are actually related to the position of the countries in the network, we conclude that countries with high centralities tend to have higher trade volumes.