Measuring Organised Crime Presence at the Municipal Level


While indicators assessing the quality of life often comprise measures of crime or fear of crime, these components usually refer to property or violent crimes. More complex crimes, which may significantly impact on the social, economic, and political conditions of local communities, are often overlooked, mostly due to problems in adequately measuring the levels of e.g. organised crime and corruption. Indeed, despite the growing scholarly attention, measurements of organised crime are rare and frequently affected by important methodological limitations. This study addresses this issue by proposing the Mafia Presence Index (MPI), a composite indicator measuring the presence of the mafias in Italy. The MPI aggregates variables measuring different dimensions of mafia presence, namely the presence and activities of mafia groups, mafia violence, and infiltration in politics and the economy. Furthermore, the analysis explores the validity and robustness of the MPI by considering possible alternative variables and by assessing the impact of different calculation strategies. Results show that the MPI is a parsimonious and consistent measure of mafia presence, relying on a core set of five variables directly related to mafia presence. The index is also robust to different calculation methods and is negatively associated with the most popular indexes measuring the quality of life in Italy.

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  1. 1.

    Data on reported crimes have been obtained in the framework of an agreement between Università Cattolica del Sacro Cuore-Transcrime and the Italian Ministry of the Interior.

  2. 2.

    All the values obtained from the logarithm transformation are linearly transposed by adding the absolute of the minimum values for each transformed indicator plus a constant equal to 0.001. This procedure avoids the presence of negative and null values without altering the distribution of the transformed indicators allowing the next steps of the methodology.

  3. 3.

    The rotations of the factors also allow the identified latent factors to be potentially correlated. This is positive as Mafia Presence may be correlated with other criminal behaviours.

  4. 4.

    The chosen method was a spline interpolation with barriers (i.e., the smooth surface calculated is constrained by the input barrier features) available in the ArcMap 10.4.1 software. The barriers considered were the Italian national borders. This procedure requires a small adjustment to amend the distortion caused by the edge effect in the municipalities at the borders or along the coastlines.

  5. 5.

    Describing each of these alternatives falls outside the scope of this paper. Full details can be found in OECD (2008).

  6. 6.

    Four potential combinations are excluded, since the Z-score normalization is not compatible with non-additive transformations.


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The article is the result of the joint contributions by all authors. The design and methodology of the study were developed by all authors. Francesco Calderoni and Gian Maria Campedelli wrote the introduction and background, Gian Maria Campedelli and Marco Dugato prepared the data, Marco Dugato conducted the analysis. All authors contributed to the discussion of the results and to the revision of the manuscript. All authors have approved the final revised version of the article.

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Dugato, M., Calderoni, F. & Campedelli, G.M. Measuring Organised Crime Presence at the Municipal Level. Soc Indic Res 147, 237–261 (2020).

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  • Mafia
  • Organised crime
  • Composite indicators
  • Quality of life
  • Crime