IDEAS home Printed from https://ideas.repec.org/p/fau/wpaper/wp2026_08.html

Estimating the Scale of Illicit Financial Flows: The Abnormality Method

Author

Listed:
  • Daniel Coll Sol

    (Tax Justice Network, London, United Kingdom)

  • Mario Cuenda Garcia

    (Tax Justice Network, London, United Kingdom)

  • Bathusi Gabanatlhong

    (Institute of Economic Studies, Faculty of Social Sciences, Charles University, Prague,)

  • Miroslav Palansky

    (Institute of Economic Studies, Faculty of Social Sciences, Charles University, Prague,)

  • Tijmen Tuinsma

    (Tax Justice Network, London, United Kingdom)

Abstract

This paper introduces the abnormality method to estimate illicit financial flows (IFFs) using a bilateral gravity model complemented by a machine learning technique to analyse unexplained financial flows to offshore centres. The findings provide robust evidence linking abnormal flows to offshore financial centres with tax avoidance and evasion and offer new estimates of their scale, costs, and geographical distribution. In 2023, abnormal flows to tax havens and secrecy jurisdictions reached US$2.8 trillion, resulting in foregone tax revenues exceeding US$60 billion. These flows originated mainly from Europe, the Americas, and Asia, flowing mostly to European tax havens. Random Forest analysis confirms that tax haven and secrecy jurisdiction status are key determinants of abnormal financial flows. Furthermore, the analysis of the Automatic Exchange of Information (AEOI) regulation indicates an increase in abnormal flows held in secretive jurisdictions.

Suggested Citation

  • Daniel Coll Sol & Mario Cuenda Garcia & Bathusi Gabanatlhong & Miroslav Palansky & Tijmen Tuinsma, 2026. "Estimating the Scale of Illicit Financial Flows: The Abnormality Method," Working Papers IES 2026/08, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised May 2026.
  • Handle: RePEc:fau:wpaper:wp2026_08
    as

    Download full text from publisher

    File URL: https://ies.fsv.cuni.cz/en/estimating-scale-illicit-financial-flows-abnormality-method
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • H26 - Public Economics - - Taxation, Subsidies, and Revenue - - - Tax Evasion and Avoidance
    • F21 - International Economics - - International Factor Movements and International Business - - - International Investment; Long-Term Capital Movements
    • F23 - International Economics - - International Factor Movements and International Business - - - Multinational Firms; International Business
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics

    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:fau:wpaper:wp2026_08. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Natalie Svarcova (email available below). General contact details of provider: https://edirc.repec.org/data/icunicz.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.