IDEAS home Printed from https://ideas.repec.org/a/pes/ieroec/v12y2021i4p889-905.html
   My bibliography  Save this article

Mirror data asymmetry in international trade by commodity group:the case of intra-Community trade

Author

Listed:
  • Iwona Markowicz

    (University of Szczecin, Poland)

  • Pawel Baran

    (University of Szczecin, Poland)

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.

Suggested Citation

  • Iwona Markowicz & Pawel Baran, 2021. "Mirror data asymmetry in international trade by commodity group:the case of intra-Community trade," Oeconomia Copernicana, Institute of Economic Research, vol. 12(4), pages 889-905, December.
    • Handle: RePEc:pes:ieroec:v:12:y:2021:i:4:p:889-905
    DOI: 10.24136/oc.2021.029
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.24136/oc.2021.029
    Download Restriction: no
    File URL: https://libkey.io/10.24136/oc.2021.029?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Javorcik, Beata S. & Narciso, Gaia, 2008. "Differentiated products and evasion of import tariffs," Journal of International Economics, Elsevier, vol. 76(2), pages 208-222, December.
    2. Carton, Christine & Slim, Sadri, 2018. "Trade misinvoicing in OECD countries: what can we learn from bilateral trade intensity indices?," MPRA Paper 85703, University Library of Munich, Germany.
    3. Robert C. Feenstra, 1999. "Discrepancies in International Data: An Application to China-Hong Kong Entrepot Trade," American Economic Review, American Economic Association, vol. 89(2), pages 338-343, May.
    4. Raymond Fisman & Shang-Jin Wei, 2004. "Tax Rates and Tax Evasion: Evidence from "Missing Imports" in China," Journal of Political Economy, University of Chicago Press, vol. 112(2), pages 471-500, April.
    5. Emmanuel Ekow Asmah & Francis Kwaw Andoh & Edem Titriku, 2020. "Trade misinvoicing effects on tax revenue in sub‐Saharan Africa: The role of tax holidays and regulatory quality," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 91(4), pages 649-672, December.
    6. Ferrantino, Michael J. & Wang, Zhi, 2008. "Accounting for discrepancies in bilateral trade: The case of China, Hong Kong, and the United States," China Economic Review, Elsevier, vol. 19(3), pages 502-520, September.
    7. Iris Day, 2015. "Assessing China’s Merchandise Trade Data Using Mirror Statistics," RBA Bulletin (Print copy discontinued), Reserve Bank of Australia, pages 19-28, December.
    8. Iwona Markowicz & Pawel Baran, 2019. "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," Oeconomia Copernicana, Institute of Economic Research, vol. 10(1), pages 55-68, March.
    9. Hayakawa, Kazunobu, 2020. "Departure months and discrepancy in mirror trade data," IDE Discussion Papers 795, Institute of Developing Economies, Japan External Trade Organization(JETRO).
    10. Ferrantino, Michael J. & Liu, Xuepeng & Wang, Zhi, 2012. "Evasion behaviors of exporters and importers: Evidence from the U.S.–China trade data discrepancy," Journal of International Economics, Elsevier, vol. 86(1), pages 141-157.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Iwona Markowicz & Paweł Baran, 2022. "Duration of Trade Relationships of Polish Enterprises on the Intra-Community Market: The Case of Vehicles and Automotive Parts Trade," Sustainability, MDPI, vol. 14(6), pages 1-17, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Iwona Markowicz & Paweł Baran, 2022. "Duration of Trade Relationships of Polish Enterprises on the Intra-Community Market: The Case of Vehicles and Automotive Parts Trade," Sustainability, MDPI, vol. 14(6), pages 1-17, March.
    2. Mohammad Farhad & Michael Jetter & Abu Siddique & Andrew Williams, 2018. "Misreported Trade," CESifo Working Paper Series 7150, CESifo.
    3. Kee, Hiau Looi & Nicita, Alessandro, 2022. "Trade fraud and non-tariff measures," Journal of International Economics, Elsevier, vol. 139(C).
    4. Xinzheng Shi & Zhufeng Xu, 2023. "Export tax refund and the misreporting by Chinese exporters," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 56(4), pages 1469-1489, November.
    5. Renliang Liu & Thanasis Stengos, 2023. "What Drives Illicit Financial Flows? An Empirical Study of Trade Data Discrepancies," Open Economies Review, Springer, vol. 34(2), pages 371-409, April.
    6. Cyril Chalendard, 2015. "Use of internal information, external information acquisition and customs underreporting," Working Papers halshs-01179445, HAL.
    7. Joel CARIOLLE & Cyril CHALENDARD & Anne-Marie GEOURJON & Bertrand LAPORTE, 2016. "Décloisonner l’analyse des données pour appuyer la modernisation des douanes : une illustration à partir du Gabon," Working Papers 201618, CERDI.
    8. Temesgen Worku & Juan P. Mendoza & Jacco L. Wielhouwer, 2016. "Tariff evasion in sub-Saharan Africa: the influence of corruption in importing and exporting countries," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 23(4), pages 741-761, August.
    9. Joel CARIOLLE & Cyril CHALENDARD & Anne-Marie GEOURJON & Bertrand LAPORTE, 2017. "Going beyond analysis of internal data to support customs modernization: A case study in Gabon," Working Papers 201723, CERDI.
    10. Jon Bakija & Ivan Badinski, 2014. "Evidence on the Responsiveness of Export-Related VAT Evasion to VAT Rates in the EU," Department of Economics Working Papers 2014-06, Department of Economics, Williams College.
    11. Biswas, Amit K. & von Hagen, Jürgen & Sarkar, Sandip, 2022. "FDI Mismatch, trade Mis-reporting, and hidden capital Movements: The USA - China case," Journal of International Money and Finance, Elsevier, vol. 120(C).
    12. Sven Steinkamp & Frank Westermann, 2022. "Development aid and illicit capital flight: Evidence from Nepal," The World Economy, Wiley Blackwell, vol. 45(7), pages 2305-2336, July.
    13. Liu, Renliang & Sheng, Liugang & Wang, Jian, 2023. "Faking trade for capital control evasion: Evidence from dual exchange rate arbitrage in China," Journal of International Money and Finance, Elsevier, vol. 138(C).
    14. Céline Carrère & Christopher Grigoriou, 2014. "Can Mirror Data Help To Capture Informal International Trade?," UNCTAD Blue Series Papers 65, United Nations Conference on Trade and Development.
    15. Cheung, Yin-Wong & Steinkamp, Sven & Westermann, Frank, 2020. "Capital flight to Germany: Two alternative measures," Journal of International Money and Finance, Elsevier, vol. 102(C).
    16. Shaar, Karam & Baharumshah, Ahmad Zubaidi, 2016. "US-China trade: Who is telling the truth?," Working Paper Series 5146, Victoria University of Wellington, School of Economics and Finance.
    17. Ferrantino, Michael J. & Liu, Xuepeng & Wang, Zhi, 2012. "Evasion behaviors of exporters and importers: Evidence from the U.S.–China trade data discrepancy," Journal of International Economics, Elsevier, vol. 86(1), pages 141-157.
    18. Demir, Banu & Javorcik, Beata, 2020. "Trade policy changes, tax evasion and Benford's law," Journal of Development Economics, Elsevier, vol. 144(C).
    19. Bussy, Adrien, 2021. "Tariff evasion with endogenous enforcement," Economics Letters, Elsevier, vol. 207(C).
    20. Liu, Xuepeng & Shi, Huimin & Ferrantino, Michael, 2016. "Tax evasion through trade intermediation: Evidence from Chinese exporters," International Review of Economics & Finance, Elsevier, vol. 42(C), pages 518-535.

    More about this item

    Keywords

    intra-Community trade; mirror data; Comext; quality of data;
    All these keywords.

    JEL classification:

    • F14 - International Economics - - Trade - - - Empirical Studies of Trade
    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pes:ieroec:v:12:y:2021:i:4:p:889-905. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Adam P. Balcerzak (email available below). General contact details of provider: https://edirc.repec.org/data/ibgtopl.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.