Quantitative analysis of trade networks: data and robustness

Abstract

A common issue in trade network analysis is missing data, as some countries do not report trade flows. This paper explores what constitutes suitable data, how to deal with missing data, and demonstrates the results using key network measures. All-to-all potential connectivity of trade between countries is considered as a starting point, in contrast to the common approach of analyzing trade networks using only the countries that actually report trade flows. In order to fill the gap between the two approaches, a more complete dataset than just the dataset of trade between reporting countries is reconstructed and the robustness of studying this bigger dataset is examined. The difference between imputed and actual network adjacency matrices is evaluated based on several centrality measures. The results are illustrated using ten commodity groups from the United Nations Database, which demonstrate that under the proposed reconstruction procedure the ranks of the countries do not change significantly as the size of the imputed network becomes bigger or smaller. Further, the degree distributions of networks based on reporting countries and trading partners are the same to within their uncertainties. So, it is robust to study the imputed bigger network that provides richer insights into trade relations, particularly for nonreporting countries.