This paper explores the ability of a class of two-sector dynamic general equilibrium models to generate equilibrium time series for Money Laundering (ML), through numerical simulations in accordance with the works of Ingram, Kocherlakota and Savin (1997), Busato, Chiarini and Di Maro (2006), and Argentiero, Bagella and Busato (2008). The paper adopts this approach for the US and the EU-15 economies. The simulations show that ML accounts for 19 percent of GDP in the EU-15 economy, while it accounts for 13 percent in the US economy over the sample 2000:01-2007:04. Moreover, the ML simulated for the EU-15 is less volatile (relative standard deviation to GDP is 0.288 compared to a figure of almost 0.4 for the US economy), and negatively correlated with respect to GDP. The latter statistic is positive for the US economy.
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