This study provides an answer to the question of how much cash deposited via a financial institution can be traced back to criminal activities, by developing a new approach to measure money laundering and proposing an application to Italy. We define a model of cash\ud in-flows on current accounts considering, besides “dirty money” to be laundered, also the legal motivations to deposit cash and the role of the shadow economy. We find that the average amount of cash laundered in Italy is around 6% of GDP. These findings are coherent with estimates of the non-observed economy obtained in previous studies

We contribute to the debate on how to assess the size of the underground (or shadow) economy by proposing a reinterpretation of the traditional Currency Demand Approach (CDA) à la Tanzi. In particular, we introduce three main innovations. First, we take a direct measure of the value of cash transactions -the flow of cash withdrawn from bank accounts relative to total noncash payments -as the dependent variable in the money demand equation. This allows us to avoid unrealistic assumptions on the velocity of money and the absence of any irregular transaction in a given year, overcoming two severe critiques to the traditional CDA. Second, in place of the tax burden level, usually intended as the main motivation for non-compliance, we include among the covariates two direct indicators of detected tax evasion. Finally, we control also for the role of illegal production considering crimes like drug dealing and prostitution, which -jointly with the shadow economy -contributes to the larger aggregate of the non-observed economy and represents a significant component of total cash payments. We propose then an application of this 'modified CDA' to a panel of 91 Italian provinces for the years 2005-2008.

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We contribute to the debate on how to assess the size of the underground (or shadow) economy by proposing a reinterpretation of the traditional Currency Demand Approach (CDA) à la Tanzi. In particular, we introduce three main innovations. First, we take a direct measure of the value of cash transactions -the flow of cash withdrawn from bank accounts relative to total noncash payments -as the dependent variable in the money demand equation. This allows us to avoid unrealistic assumptions on the velocity of money and the absence of any irregular transaction in a given year, overcoming two severe critiques to the traditional CDA. Second, in place of the tax burden level, usually intended as the main motivation for non-compliance, we include among the covariates two direct indicators of detected tax evasion. Finally, we control also for the role of illegal production considering crimes like drug dealing and prostitution, which -jointly with the shadow economy -contributes to the larger aggregate of the non-observed economy and represents a significant component of total cash payments. We propose then an application of this 'modified CDA' to a panel of 91 Italian provinces for the years 2005-2008.

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