Intra-community trade asymmetries-based clustering and linear ordering of combined nomenclature chapters using Generalized Distance Measure (GDM)

Statistical data on foreign trade are collected in all EU member states separately and then passed on to Eurostat where the data are aggregated. Continuous actions are to ensure that all datasets collected at national level are fully comparable. The aim of the paper is to provide a classification as well as an ordering of CN chapters (2-digit codes) according to the quality of data on intra-Community trade of goods. Data were taken from Eurostat’s COMEXT database. In ordering the chapters, we utilized the distance from the ideal solution with GDM as the distance measure. The study reveals a structure of goods subject to intra-Community trade that is supplementary to the official nomenclature. In addition, we provided CN chapters ordering according to the overall level of irregularities in reported mirror values of ICS and ICA. The results we obtained are of practical value for both researchers and authorities interested in foreign trade