{"title":"Mirror data asymmetry in international trade by commodity group: the case of intra-Community trade","authors":"I. Markowicz, P. Baran","doi":"10.24136/oc.2021.029","DOIUrl":null,"url":null,"abstract":"Research background: Transactions in international trade of goods are recorded in two sources, on the side of the seller's country and on the side of the buyer's country. The confrontation of such data makes it possible to measure their quality. An inconsistency between the data is called mirror data asymmetry. \nPurpose of the article: The aim of the paper is to adapt the methods developed by the Authors to study mirror data asymmetry to commodity group markets examination. The quality of data on trade within specific commodity groups (CN chapters) in intra-Community trade was compared. The data were aggregated by country. The indicators used allow for the indication of commodity groups with high mirror data compatibility and those with data asymmetry between intra-Community supplies (ICS) and acquisitions (ICA). Moreover, the commodity groups for which the value-based and quantity-based approaches give different results have been identified. \nMethods: Based on the literature on the subject and their own research, the Authors have developed a group of methods for studying the asymmetry of mirror data. The proposed indicator formulas are based on various data aggregation approaches. The research used data on intra-Community supplies and acquisitions of goods broken down into 97 chapters of the Combined Nomenclature (CN). Differences between the ICS and ICA in particular commodity groups were aggregated for all pairs of EU countries. The data comes from the Comext database, provided by Eurostat. \nFindings & value added: The results of the analysis are rankings of the Combined Nomenclature (CN) chapters by the quality of data on ICS and ICA. Lists of CN chapters have been created for discrepancies both in value and weight of goods. Thus, areas of necessary intensification of the work of public statistics services to improve data reliability were identified.","PeriodicalId":46112,"journal":{"name":"Oeconomia Copernicana","volume":" ","pages":""},"PeriodicalIF":7.6000,"publicationDate":"2021-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Oeconomia Copernicana","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.24136/oc.2021.029","RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 1
Abstract
Research background: Transactions in international trade of goods are recorded in two sources, on the side of the seller's country and on the side of the buyer's country. The confrontation of such data makes it possible to measure their quality. An inconsistency between the data is called mirror data asymmetry.
Purpose of the article: The aim of the paper is to adapt the methods developed by the Authors to study mirror data asymmetry to commodity group markets examination. The quality of data on trade within specific commodity groups (CN chapters) in intra-Community trade was compared. The data were aggregated by country. The indicators used allow for the indication of commodity groups with high mirror data compatibility and those with data asymmetry between intra-Community supplies (ICS) and acquisitions (ICA). Moreover, the commodity groups for which the value-based and quantity-based approaches give different results have been identified.
Methods: Based on the literature on the subject and their own research, the Authors have developed a group of methods for studying the asymmetry of mirror data. The proposed indicator formulas are based on various data aggregation approaches. The research used data on intra-Community supplies and acquisitions of goods broken down into 97 chapters of the Combined Nomenclature (CN). Differences between the ICS and ICA in particular commodity groups were aggregated for all pairs of EU countries. The data comes from the Comext database, provided by Eurostat.
Findings & value added: The results of the analysis are rankings of the Combined Nomenclature (CN) chapters by the quality of data on ICS and ICA. Lists of CN chapters have been created for discrepancies both in value and weight of goods. Thus, areas of necessary intensification of the work of public statistics services to improve data reliability were identified.
期刊介绍:
The Oeconomia Copernicana is an academic quarterly journal aimed at academicians, economic policymakers, and students studying finance, accounting, management, and economics. It publishes academic articles on contemporary issues in economics, finance, banking, accounting, and management from various research perspectives. The journal's mission is to publish advanced theoretical and empirical research that contributes to the development of these disciplines and has practical relevance. The journal encourages the use of various research methods, including falsification of conventional understanding, theory building through inductive or qualitative research, first empirical testing of theories, meta-analysis with theoretical implications, constructive replication, and a combination of qualitative, quantitative, field, laboratory, and meta-analytic approaches. While the journal prioritizes comprehensive manuscripts that include methodological-based theoretical and empirical research with implications for policymaking, it also welcomes submissions focused solely on theory or methodology.