A strand of the literature on money laundering applies gravity specification to investigate illicit money flows (e.g. Walker 1999 and Walker and Unger, 2009 empirical applications to Australia and to the Netherlands). However, the existent literature presents several limitations not providing theoretical grounded justifications that gravity equations actually apply to illicit flows too and because of the lack of reliable data. We will test whether the theoretical frameworks provided by Anderson and van Wincoop (2003) for trade flows and Okawa and van Wincoop (2013) for asset flows are suitable for the assessment of illicit money flows. To this end, we perform a two-stage procedure: first, we apply the above theoretical frameworks to the actual bilateral trade and financial flows across countries worldwide by using the usual set of observable and unobservable country-time and country pairs controls. We model multilateral resistance terms alternatively as bilateral trade costs and as financial frictions/informational asymmetries. We use aggregate merchandise trade imports for 170 partner countries provided by UNSD Commodity Trade database and data on cross-border equity flows from IMF Coordinated Portfolio Investment Survey. Second, following Cassetta et al. (2014) experiment on Italian provinces, we use the studentized residuals of the above gravity estimates to identify unpredicted flows and build up a worldwide dataset anomalies of actual vs potential flows. Then, we rank countries measuring which places attract more funds than expected and test for the presence of significant correlations between anomalies and the set of standard measures and controls on illicit activity provided by the relevant literature.
We expect that geographic characteristics of source and destination countries matter for size and direction of dirty money flows and that substantial anomalies are linked to Offshore financial centres activity.
We expect to demonstrate that gravity models can be used to assess both the size and the direction of dirty money flows but that have been used improperly until now. With solid theoretical and empirical underpinnings, we expect to be able to demonstrate that geographic characteristics of source and destination countries matter for size and direction of dirty money flows. Regarding destination countries, we expect to find substantial anomalies linked to OFCs activity and to be able to explain these with some common characteristic shared by these territories. We will reflect on the conceptual difference between OFCs, Small Island Economies (SIEs), Money Launderers and Tax Havens, to understand on a solid empirical basis what determines their different perception of risk and trustworthiness. Based on previous works on this topic (Rose and Spiegel, 2007) we believe that it is likely that many of the anomalies for financial flows will be OFCs or countries with high values of financial secrecy. If this will be the case, we would study what are the factors that better explain this kind of anomalies, giving a quantitative-economic-geography contribution to the studies on geography of finance and of licit/illicit spaces.
Regarding origin countries, we expect to find a positive correlation between the rate of high-profit crimes and the size of flows directed abroad. Also, confirming the work of Gnutzmann et al. (2010) we believe that will result a negative correlation between Country size and Money Laundering (ML) risk perception and between bilateral distance and size of financial flows (as in gravity literature in general). In general, even if OFCs might be more prone to tolerate ML, we think that a significant share of dirty money flows first to the bigger and closer financial centers (respect to the place where the crime generating revenues is committed). Taking into account the type of crimes committed in the source country, we also might be able to empirically confirm the difference between OFCs, tax havens and Money Launderers.