Mirror Data Asymmetry In International Trade. Insights From Research On INTRASTAT Data

Abstract:

Objectives: The main goal is to evaluate the accuracy of intra-Community trade data. An additional goal is to assess whether there is a structural difference in the quality of data reported by the ‘old’ and the ‘new’ Member States, i.e. those countries that joined the EU in 2004 or later. Background: The data on international trade are stored in the form of mirror data. It appears, however, that the data collection processes in different EU Member States are incompatible and that is why mirror data (regarding the same transactions revealed in statistics of both the acquirer and supplier country) often do not match. The discrepancies between recorded values may cause numerous problems in various macroeconomic analyses. Fortunately, there exist ways to spot data inconsistency and to partially resolve the problems arising. The Authors used methods of testing the accuracy of the data on intemational trade found in the literature and their own. Data and Methods: We used data from the COMEXT database provided by Eurostat. Data regarding intra-Community trade in 2016, 2017 and 2018 were used. We calculated data discrepancy indices for individual Member States and for groups of countries and performed Kruskal-Wallis tests to confirm the differences between them. Results: The study reveals a significant, structural difference between the ‘old’ and the ‘new’ Member States in respect to intra-Community trade data accuracy. We named those countries which affected the data quality the most. Some ‘new’ Member States, however, quickly adopted the high data quality standards which we also pointed out. In the latter part of the work a comparison of the data on intra-Community acquisitions (ICA) and their mirror intra- Community supplies (ICS) was done for the EU Member States divided into groups of ‘old’ EUl5 countries that were members before 2004 and the ‘new’ EUI3 countries. Policy Implications: The results of this research can be used by both public statistics and tax administrations. They can also provide a value to researchers conducting macroeconomic analyses in a broader sense.