Abstract

It is important to understand the amounts and types of money laundering flows, since they have very different effects and, therefore, need different enforcement strategies. Countries that mainly deal with criminals laundering their proceeds locally, need other measures than countries that mainly deal with foreign illegal investments or dirty money just flowing through the country. This paper has two main contributions. First, we unveil the country preferences of money launderers empirically in a systematic way. Former money laundering estimates used assumptions on which country characteristics money launderers are looking for when deciding where to send their ill-gotten gains. Thanks to a unique dataset of transactions suspicious of money laundering, provided by the Dutch Institute infobox Criminal and Unexplained Wealth (iCOV), we can empirically test these assumptions with an econometric gravity model estimation. We use this information for our second contribution: iteratively simulating all money laundering flows around the world. This allows us, for the first time, to provide estimates that distinguish between three different policy challenges: the laundering of domestic crime proceeds, international investment of dirty money and money just flowing through a country.

Highlights

  • It is important to understand the amounts and types of money laundering flows, since they have very different effects and, need different enforcement strategies

  • Investment of dirty money in an economy, such as real estate being bought up by criminals, needs experts to check the justification of money spent on these o­ bjects[1]

  • This paper tests these assumptions using a unique dataset of transactions suspicious of money laundering. This is the first paper to unveil country preferences of money launderers. We use this information for our second contribution: simulating all money laundering flows around the world, providing the first estimates that distinguish between domestic money laundering, international investment of dirty money and money just flowing through

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Summary

Conceptual framework

When a criminal is so successful that he makes more money than he regularly spends on consumption, he is faced with the issue of money laundering. Legal definitions generally use a very broad definition of money laundering, which even consider situations in which no actual money laundering activities have taken place as money laundering, such as when the criminal merely has the criminal assets in his possession This is, for example, the case in the ­Netherlands[26], the country from which we got the data for this paper. According to international anti-money laundering standards, obliged entities (such as banks, notaries, accountants and dealers in high-value goods) have to file a report to the Financial Intelligence Unit (FIU) in their country, when they encounter unusual or suspicious transactions in their business. The data in the STR database is of higher quality because the Dutch FIU went over these transactions and in the process cleaned up input inconsistencies of reporting entities Due to these input inconsistencies, the amount of money involved in UTRs is not always known and could not be reliably aggregated. The general hypothesis in gravity models is that flows are larger between larger and closer countries

Tax haven
Econometric results for money laundering gravity model
Modeling international flows
STRij and n
Simulation results
Conclusions and discussion
Author contributions
Findings
Additional information
Full Text
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