The purpose of this research is to provide a methodological framework that is able to enhance our capability to detect illegal waste shipment with particular reference to waste plastics. Based on a very large cross-sectional dataset covering 187 countries over the period 2002-2012, our study aims to do this by using both the mirror statistics method and the network analysis. Specifically, by using mirror statistics, we identify the existence of a set of “suspicious” trade relations between pairs of countries. Then, we employ social network analysis in order to define the position of each country in this illegal trade structure, and to have a clear exposition of the connections between them. Our main findings reveal the central positions of the USA, Germany and the UK as sources and China and Malaysia as outlets of illegal shipments of waste plastics. Moreover, our methodology allows us to highlight the presence of other countries, which carry out an intermediary role within the global trade network, and to detect the changes in traditional illegal shipment routes. Therefore, this paper shows how social network analysis provides a useful instrument by means of which crime analysts and police detectives can develop effective strategies to interdict criminal activities.
How to detect illegal waste shipments? The case of the international trade in polyethylene waste / Pittiglio, R.; Reganati, F.; Toschi, Luca. - In: ECONOMICS BULLETIN. - ISSN 1545-2921. - ELETTRONICO. - 37:4(2017), pp. 2625-2640.
How to detect illegal waste shipments? The case of the international trade in polyethylene waste
Pittiglio, R.;Reganati, F.;TOSCHI, LUCA
2017
Abstract
The purpose of this research is to provide a methodological framework that is able to enhance our capability to detect illegal waste shipment with particular reference to waste plastics. Based on a very large cross-sectional dataset covering 187 countries over the period 2002-2012, our study aims to do this by using both the mirror statistics method and the network analysis. Specifically, by using mirror statistics, we identify the existence of a set of “suspicious” trade relations between pairs of countries. Then, we employ social network analysis in order to define the position of each country in this illegal trade structure, and to have a clear exposition of the connections between them. Our main findings reveal the central positions of the USA, Germany and the UK as sources and China and Malaysia as outlets of illegal shipments of waste plastics. Moreover, our methodology allows us to highlight the presence of other countries, which carry out an intermediary role within the global trade network, and to detect the changes in traditional illegal shipment routes. Therefore, this paper shows how social network analysis provides a useful instrument by means of which crime analysts and police detectives can develop effective strategies to interdict criminal activities.File | Dimensione | Formato | |
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