3. SHORTER- RUN CRIMINAL CYCLES IN COUNTERFEITING 3.1 The Issue and the Data Set 3.1.1 Our peculiar data set In this part our chapter we deal with the shorter- run cycles relating to the crimes of counterfeiting of goods. The data on the international diffusion of counterfeiting are sometimes unreliable and misleading because of the variety of definitions of the phenomenon. We, in this chapter, work with a unique data set of monthly data for Italy, disaggregated for the 20 Italian Regions, relating to the investigations of the Italian Fiscal Police (Guardia di Finanza, GDF) into counterfeiting crimes for the five- year period 2006–2010.16 The data set includes the monthly number of interventions in the 20 Regions and their results in terms of goods confiscated and of individuals indicted. The data are disaggregated in four categories or subcategories of anti- crime interventions by the GDF: counterfeiting of ‘Made in Italy’,17 counterfeiting of branded goods,18 counterfeiting of branded goods in the fashion sector,19 and counterfeiting in relation to the safety and health requirements of European Union and Italian laws.20 In Table 22.4 we have normalized the data on the population. We do not have the monthly changes of population. But the changes in the population between the various years are modest and while in the first years there is a slight increase, in the last year there is a small decrease. Unlike in the previous part where we examined the long- run cycles of corruption and frauds, we shall not consider the cycles of the counterfeiting crimes, normalized to the population. But this would not significantly change the fluctuations in the observed values.

SHORTER- RUN CRIMINAL CYCLES IN COUNTERFEITING

MANTOVANI, Michela;
2014

Abstract

3. SHORTER- RUN CRIMINAL CYCLES IN COUNTERFEITING 3.1 The Issue and the Data Set 3.1.1 Our peculiar data set In this part our chapter we deal with the shorter- run cycles relating to the crimes of counterfeiting of goods. The data on the international diffusion of counterfeiting are sometimes unreliable and misleading because of the variety of definitions of the phenomenon. We, in this chapter, work with a unique data set of monthly data for Italy, disaggregated for the 20 Italian Regions, relating to the investigations of the Italian Fiscal Police (Guardia di Finanza, GDF) into counterfeiting crimes for the five- year period 2006–2010.16 The data set includes the monthly number of interventions in the 20 Regions and their results in terms of goods confiscated and of individuals indicted. The data are disaggregated in four categories or subcategories of anti- crime interventions by the GDF: counterfeiting of ‘Made in Italy’,17 counterfeiting of branded goods,18 counterfeiting of branded goods in the fashion sector,19 and counterfeiting in relation to the safety and health requirements of European Union and Italian laws.20 In Table 22.4 we have normalized the data on the population. We do not have the monthly changes of population. But the changes in the population between the various years are modest and while in the first years there is a slight increase, in the last year there is a small decrease. Unlike in the previous part where we examined the long- run cycles of corruption and frauds, we shall not consider the cycles of the counterfeiting crimes, normalized to the population. But this would not significantly change the fluctuations in the observed values.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.12318/9665
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