Joras Ferwerda

Gravity Models of Trade-based Money Laundering

Several attempts have been made in the economics literature to measure money laundering. However, the adequacy of these models is difficult to assess, as money laundering takes place secretly and, hence, goes unobserved. An exception is trade-based money laundering (TBML), a special form of trade abuse that has been discovered only recently. TBML refers to criminal proceeds that are transferred around the world using fake invoices that under- or overvalue imports and exports. This article is a first attempt to test well-known prototype models proposed by Walker and Unger to predict illicit money laundering flows and to apply traditional gravity models borrowed from international trade theory. To do so, we use a dataset of Zdanowicz of TBML flows from the US to 199 countries. Our test rejects the specifications of the Walker and Unger prototype models, at least for TBML. The traditional gravity model that we present here can indeed explain TBML flows worldwide in a plausible manner. An important determinant is licit trade, the mass in which TBML is hidden. Furthermore, our results suggest that criminals use TBML in order to escape the stricter anti moneylaundering regulations of financial markets.

The Economic and Legal Effectiveness of the European Union’s Anti-Money Laundering Policy

Official government policies against money laundering in the EU have been in place for roughly 25 years, after much concerted effort and a great deal of time and money invested. This volume examines the anti-money laundering policy of the EU Member States in connection to the threat of money laundering they face.

Money Laundering in the Real Estate Sector

In many countries, the real estate sector is vulnerable to money laundering due to a high number of factors including; the high value of assets, price fluctuations and speculation within the market, difficulties in assessing the true value of a house, and the fact that the legal owner is not necessarily the economic owner. In this book, the authors identify a total of 25 characteristics which render a property susceptible to money laundering. The more such characteristics a property exhibits, the more suspicious it becomes. The authors also discover that some of these characteristics weigh heavier than others. Combining economic, econometric and criminological analysis, this multidisciplinary approach shows how to detect criminal investment in the real estate sector.

The Real Estate Sector

The International Accounting Standards Board (IASB) has published a new Standard, IFRS 15 Revenue from Contracts with Customers (‘the new Standard’). The new Standard outlines a single comprehensive model of accounting for revenue arising from contracts with customers and supersedes current revenue recognition guidance, which is found currently across several Standards and Interpretations within IFRSs. The core principle is that an entity recognises revenue to reflect the transfer of goods or services, measured as the amount to which the entity expects to be entitled in exchange for those goods or services. However, the new Standard does not apply to transactions that are instead within the scope of the leasing standard.

Threat of money laundering

This chapter presents a Walker gravity model to calculate the amount of money laundering threat for 27 EU Member States. It is found that the threat of money laundering is greatest in the United Kingdom, Luxembourg and other west-European countries, as a result of their relatively sophisticated financial markets, their relatively high GDP per capita levels, their trade, as well as cultural links to a wide range of proceeds of crime-generating countries. The picture changes dramatically, however, when expressed as a percentage of each countrys GDP. The threats can be very high - particularly for the smaller countries, such as Estonia, Latvia, Malta and Luxembourg. These countries are bordering or related to much larger countries that generate large amounts of money potentially available for laundering. They therefore face threats equivalent to a significant proportion of their total GDP, even - in those four countries - greater than their entire GDP. The threat assessment presented in this study, based on the Walker gravity model, appears to be quite robust.

The Effectiveness of Anti-Money Laundering Policy: A Cost-Benefit Perspective

Basically all countries in the world have an anti-money laundering framework in place based on the 40 recommendations of the Financial Action Task Force (FATF), an intergovernmental body established by the G-7 countries in 1989. Now that all these countries are spending tax money to fight money laundering, a natural question to ask is how effective is this policy. Do taxpayers receive value for the money spent? In this chapter we discuss the effectiveness and efficiency of anti-money laundering policies and perform a measurement for countries in the European Union. We use the common policy evaluation tool of a cost-benefit analysis to inform us about the efficiency.

Soccer jersey sponsors and the world cup

The market for soccer jerseys is a multibillion market dominated by Adidas, Nike and Puma. This paper investigates whether jersey sponsorship has a non-arbitrary effect on the outcomes of World Cup knockout matches. The results show that in the knockout stages of the last four World Cup tournaments, especially national teams sponsored by Adidas perform significantly better than expected, while teams sponsored by any other company than Adidas, Puma or Nike perform worse. The average advantage per knockout match for the Adidas teams is to raise the probability to win by 10 percent point.

Effectiveness: threat and corresponding policy response

This chapter explores to what extent the policy response towards money laundering is effective in relation to the money laundering threat the EU Member States face. It is argued that AML policy response can be captured by several indicators: FATF compliance, legal effectiveness, timeliness of implementation, FIU response, international cooperation, information flows and the number of convictions for money laundering. The exploratory analysis is based on a set of figures which have a policy response indicator on the horizontal axis and the threat measure on the vertical axis. The chapter considers the diagonal area in these figures to mark an appropriate policy response - i.e. a policy response that is more or less proportional to the AML threat a country is facing. The chapter shows that most Member States have proportional AML policy responses. Nevertheless, all of them can improve on at least one aspect of their policy response with the positive exception of Denmark, that has, in the analysis of the chapter, relatively low levels of threat and relatively high policy response scores.

Cost-benefit analysis

The lack of hard data makes any country-by-country cost-benefit analysis of AML policy impossible at the moment. But by using the estimates that are available, and correcting these estimates for the price level and size of the countries, the chapter is able to estimate almost all cost components and some benefits for each EU Member State. This study estimates that the total costs of the 27 EU Member States are about 2 billion Euros, together with an immeasurable reduction in privacy and some inefficiency in the operation of society. Since most of the benefits of AML/CTF policy are hard or impossible to estimate, the cost benefit dilemma is basically reduced to the question: Does the EU want to spent about 2 billion Euros to obtain potential benefits, which include an unquantifiable reduction in money laundering, less crime in general, a reduced damage effect on the real economy and less risk for the financial sector?