This paper implements a methodology that exploits firms and households' optimality conditions to measure money laundering for the Italian economy. This approach, first implemented by Ingram et al. (J Monet Econ 40:435-436, 1997) to the household production sector, and by Busato et al. (Using theory for measurement: an analysis of the behaviour of underground economy working paper, Aarhus University, 2006) for measuring the underground economy, allows to generate high frequency time-series for money laundering using a theoretical two-sector dynamic general equilibrium model calibrated over the sample 1981:01-2001:04. The analysis of the generated series suggests two main results. First, money laundering accounts for approximately 12 percent of aggregate GDP; second, money laundering is more volatile than aggregate GDP and it is negatively correlated with it.
Money laundering in a two-sector model: using theory for measurement
BUSATO, Francesco
2008-01-01
Abstract
This paper implements a methodology that exploits firms and households' optimality conditions to measure money laundering for the Italian economy. This approach, first implemented by Ingram et al. (J Monet Econ 40:435-436, 1997) to the household production sector, and by Busato et al. (Using theory for measurement: an analysis of the behaviour of underground economy working paper, Aarhus University, 2006) for measuring the underground economy, allows to generate high frequency time-series for money laundering using a theoretical two-sector dynamic general equilibrium model calibrated over the sample 1981:01-2001:04. The analysis of the generated series suggests two main results. First, money laundering accounts for approximately 12 percent of aggregate GDP; second, money laundering is more volatile than aggregate GDP and it is negatively correlated with it.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
