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Research Handbook on Money Laundering

Research Handbook on Money Laundering

Elgar original reference

Edited by Brigitte Unger and Daan van der Linde

Although the practice of disguising the illicit origins of money dates back thousands of years, the concept of money laundering as a multidisciplinary topic with social, economic, political and regulatory implications has only gained prominence since the 1980s. This groundbreaking volume offers original, state-of-the-art research on the current money laundering debate and provides insightful predictions and recommendations for future developments in the field.

Chapter 17: Using dynamic macroeconomics for estimating money laundering: a simulation for the EU, Italy and the United States

Michele Bagella, Francesco Busato and Amedeo Argentiero

Subjects: economics and finance, economic crime and corruption, law - academic, corruption and economic crime, politics and public policy, terrorism and security


Money laundering (ML) is a by-product of the criminal economy, which has a size of approximately 5 percent of upon the world GDP (Napoleoni 2005). An efficient (and realistic) measure of this phenomenon may help authorities discover the actual origin of the resources that are laundered, and through this the right size of criminal economy. In this sense, ML is located downstream with respect to illegal acts from which dirty money is derived. In 1996, the International Monetary Fund (IMF) stated that the aggregate size of ML in the world could be somewhere between 2 and 5 percent of the world’s Gross Domestic Product (GDP). In the previous ten years (1997–2006), ML discovered in Italy consisted of 0.1 percent of 2006 GDP. The dataset from which these results are extracted is constructed by considering the kinds of goods used to launder money, the class of penal violations contested, and for each transgression indicates the amount of money laundered. Nevertheless, this figure hardly corresponds to the actual value of ML. In Italy, as well as in the majority of developed countries, Judicial authorities find it very hard both to detect ML transactions and to sentence definitively convicted guilty subjects.

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