The paper provides an empirical analysis of the discrepancies in bilateral ('mirror') statistics on Italian foreign trade to identify anomalous flows potentially connected to illicit cross-border transfers of funds carried out by over-reporting imports or under-reporting exports. To this end, the paper estimates an econometric model using mirrored data on Italy's external trade displaying a highly disaggregated goods classification for each partner country and covering the period 2010-13.
On the basis of the regression estimates it is possible to identify a component of the discrepancies potentially connected to false declarations. This makes it possible to build money-laundering risk indicators at country and macro-sector level. The preliminary results appear encouraging with respect to the model's ability to assist the Italian Financial Intelligence Unit and other authorities in detecting potentially illicit flows.
Published in 2019 in: The World Economy, v. 42, 11, pp. 3120-3147
