ICA and ICS-based rankings of EU countries according to quality of mirror data on intra-Community trade in goods in the years 2014?2017
DOI:
https://doi.org/10.24136/oc.2019.003Keywords:
official statistics data quality, mirror data, intra-Community trade, EUAbstract
Research background: As a system of official EU statistics, Intrastat contains data collected by Member States aggregated by Eurostat on the Union?s level in the form of COMEXT database. Country-level data are based on declarations made by businesses dispatching or acquiring goods from other EU Member States. Since the same transaction is declared twice ? as an ICS in one country and at the same time as an ICA in another country by the partner ? the database contains mirror data. Analysis of mirror data lets us assess the quality of public statistics data on international trade.
Purpose of the article: The aim of the article is to rank EU Member States according to quality of data on intra-Community trade in goods collected by Intrastat. Foreign trade stimulates economic development on one hand and is the development?s reflection on the other. Thus it is very important that official statistics in this area be of good quality. Analysis of mirror data from partner states in intra-Community trade in goods allows us to claim that not every Member State pro-vides data of satisfactory quality level.
Methods: We used the authors? methodology of assessing quality of mirror data. These include data asymmetry indices, both proposed by Eurostat and the authors? own proposals. We have also examined the changes in the above mentioned rankings over time.
Findings & Value added: The result of the survey is ordering of EU Member States according to the quality of data on intra-Community trade in goods. The rankings are presented for the period of 2014?2017, during which there were 28 Member States of the EU. Changes in distinct countries? positions were shown as a result of changes in overall quality of statistical data collected in these countries. The research methodology can be used in the process of monitoring data quality of the Intrastat system.
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