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

100%
Markowicz I., Baran P.
Econometrics. Ekonometria. Advances in Applied Data Analytics
|
2019
|
issue vol. 23 no. 3
50-58
EN
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.
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Jakość danych statystycznych dotyczących obrotów towarowych między krajami Unii Europejskiej

72%
Markowicz I., Baran P.
Wiadomości Statystyczne. The Polish Statistician
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2019
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vol. 64
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issue 1
7-19
EN
The objective of presented analysis is to assess quality of data on foreign trade within the Union. Data from Eurostat’s COMEXT database was used. The differences between declared export quantities of foods from a given country and data on imports from this country to other member states gathered by Eurostat have been analyzed. These differences partly result from the adopted statistical thresholds and reflect the quality of the collected data. The authors have compared EU member states based on convergence of data on dispatches and arrivals of goods from each country. Using data discrepancy measures member states were ranked with regard to statistical data quality, which is an innovation in foreign trade research.
PL
Celem przedstawionego w artykule badania jest ocena jakości danych dotyczących handlu zagranicznego wewnątrz Unii Europejskiej (UE). W badaniu wykorzystano dane za 2017 r. pochodzące z bazy Comext, udostępnianej przez Eurostat. Zbadano różnice między deklarowanymi wartościami wywozu towarów z danego kraju a danymi o przywozie z tego kraju do innych krajów UE. Różnice te częściowo wynikają z przyjętych progów statystycznych i odzwierciedlają jakość zgromadzonych danych. Kraje unijne porównano także pod względem zbieżności danych o wywozie i przywozie towarów z poszczególnych krajów. Wykorzystując miary rozbieżności danych, uszeregowano kraje pod względem poziomu jakości danych statystycznych, co stanowi element innowacyjny w badaniach handlu zagranicznego.
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