IDEAS home Printed from https://ideas.repec.org/a/kap/rqfnac/v57y2021i4d10.1007_s11156-021-00984-3.html
   My bibliography  Save this article

Evaluating risks-based communities of Mafia companies: a complex networks perspective

Author

Listed:
  • Nicola Giuseppe Castellano

    (University of Pisa)

  • Roy Cerqueti

    (Sapienza University of Rome
    London South Bank University)

  • Bruno Maria Franceschetti

    (University of Macerata)

Abstract

This paper presents a data-driven complex network approach, to show similarities and differences—in terms of financial risks—between the companies involved in organized crime businesses and those who are not. At this aim, we construct and explore two networks under the assumption that highly connected companies hold similar financial risk profiles of large entity. Companies risk profiles are captured by a statistically consistent overall risk indicator, which is obtained by suitably aggregating four financial risk ratios. The community structures of the networks are analyzed under a statistical perspective, by implementing a rank-size analysis and by investigating the features of their distributions through entropic comparisons. The theoretical model is empirically validated through a high quality dataset of Italian companies. Results highlights remarkable differences between the considered sets of companies, with a higher heterogeneity and a general higher risk profiles in companies traceable back to a crime organization environment.

Suggested Citation

  • Nicola Giuseppe Castellano & Roy Cerqueti & Bruno Maria Franceschetti, 2021. "Evaluating risks-based communities of Mafia companies: a complex networks perspective," Review of Quantitative Finance and Accounting, Springer, vol. 57(4), pages 1463-1486, November.
  • Handle: RePEc:kap:rqfnac:v:57:y:2021:i:4:d:10.1007_s11156-021-00984-3
    DOI: 10.1007/s11156-021-00984-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11156-021-00984-3
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s11156-021-00984-3?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Mastrobuoni Giovanni & Patacchini Eleonora, 2012. "Organized Crime Networks: an Application of Network Analysis Techniques to the American Mafia," Review of Network Economics, De Gruyter, vol. 11(3), pages 1-43, September.
    2. Gianni Pola, 2016. "On entropy and portfolio diversification," Journal of Asset Management, Palgrave Macmillan, vol. 17(4), pages 218-228, July.
    3. Matthew Elliott & Benjamin Golub & Matthew O. Jackson, 2014. "Financial Networks and Contagion," American Economic Review, American Economic Association, vol. 104(10), pages 3115-3153, October.
    4. Letizia Paoli, 2004. "Italian Organised Crime: Mafia Associations and Criminal Enterprises," Global Crime, Taylor & Francis Journals, vol. 6(1), pages 19-31, February.
    5. Clemente, G.P. & Grassi, R., 2018. "Directed clustering in weighted networks: A new perspective," Chaos, Solitons & Fractals, Elsevier, vol. 107(C), pages 26-38.
    6. Xavier Gabaix, 2009. "Power Laws in Economics and Finance," Annual Review of Economics, Annual Reviews, vol. 1(1), pages 255-294, May.
    7. Marcel Ausloos & Roy Cerqueti, 2016. "A Universal Rank-Size Law," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-15, November.
    8. Briant, A. & Combes, P.-P. & Lafourcade, M., 2010. "Dots to boxes: Do the size and shape of spatial units jeopardize economic geography estimations?," Journal of Urban Economics, Elsevier, vol. 67(3), pages 287-302, May.
    9. Villani, Salvatore & Mosca, Michele & Castiello, Mauro, 2019. "A virtuous combination of structural and skill analysis to defeat organized crime," Socio-Economic Planning Sciences, Elsevier, vol. 65(C), pages 51-65.
    10. Anil Bera & Sung Park, 2008. "Optimal Portfolio Diversification Using the Maximum Entropy Principle," Econometric Reviews, Taylor & Francis Journals, vol. 27(4-6), pages 484-512.
    11. Zhiyan Cao & Fei Leng & Ehsan Feroz & Sergio Davalos, 2015. "Corporate governance and default risk of firms cited in the SEC’s Accounting and Auditing Enforcement Releases," Review of Quantitative Finance and Accounting, Springer, vol. 44(1), pages 113-138, January.
    12. Arcagni, Alberto & Grassi, Rosanna & Stefani, Silvana & Torriero, Anna, 2017. "Higher order assortativity in complex networks," European Journal of Operational Research, Elsevier, vol. 262(2), pages 708-719.
    13. Bartram, Sohnke M. & Wang, Yaw-Huei, 2005. "Another look at the relationship between cross-market correlation and volatility," Finance Research Letters, Elsevier, vol. 2(2), pages 75-88, June.
    14. Ramchand, Latha & Susmel, Raul, 1998. "Volatility and cross correlation across major stock markets," Journal of Empirical Finance, Elsevier, vol. 5(4), pages 397-416, October.
    15. Dimitrios Koutmos & Konstantinos Bozos & Dionysia Dionysiou & Neophytos Lambertides, 2018. "The timing of new corporate debt issues and the risk-return tradeoff," Review of Quantitative Finance and Accounting, Springer, vol. 50(4), pages 943-978, May.
    16. Firth, Michael & Smith, Andrew, 1995. "Auditor Quality, Corporate Risk, and the Valuation of New Issues," Review of Quantitative Finance and Accounting, Springer, vol. 5(3), pages 241-251, September.
    17. Ozgul, Fatih, 2016. "Analysis of topologies and key players in terrorist networks," Socio-Economic Planning Sciences, Elsevier, vol. 56(C), pages 40-54.
    18. Litterio Mirenda & Sauro Mocetti & Lucia Rizzica, 2019. "The real effects of 'ndrangheta: firm-level evidence," Temi di discussione (Economic working papers) 1235, Bank of Italy, Economic Research and International Relations Area.
    19. Jangho Yang, 2018. "Information Theoretic Approaches In Economics," Journal of Economic Surveys, Wiley Blackwell, vol. 32(3), pages 940-960, July.
    20. Duncan J. Watts & Steven H. Strogatz, 1998. "Collective dynamics of ‘small-world’ networks," Nature, Nature, vol. 393(6684), pages 440-442, June.
    21. M. Ausloos, 2013. "A scientometrics law about co-authors and their ranking: the co-author core," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(3), pages 895-909, June.
    22. Francesco Calderoni, 2011. "Where is the mafia in Italy? Measuring the presence of the mafia across Italian provinces," Global Crime, Taylor & Francis Journals, vol. 12(1), pages 41-69, February.
    23. Paolo Pinotti, 2015. "The Economic Costs of Organised Crime: Evidence from Southern Italy," Economic Journal, Royal Economic Society, vol. 125(586), pages 203-232, August.
    24. Karagiannis, Roxani & Karagiannis, Giannis, 2020. "Constructing composite indicators with Shannon entropy: The case of Human Development Index," Socio-Economic Planning Sciences, Elsevier, vol. 70(C).
    25. Fabio La Rosa & Sergio Paternostro & Loredana Picciotto, 2018. "Exploring the determinants of anti-mafia entrepreneurial behaviour: an empirical study on southern Italian SMEs," Entrepreneurship & Regional Development, Taylor & Francis Journals, vol. 30(1-2), pages 81-117, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Michele Battisti & Andrea Mario Lavezzi & Roberto Musotto, 2022. "Organizing Crime: an Empirical Analysis of the Sicilian Mafia," Papers 2205.02310, arXiv.org.
    2. Luigi Balletta & Andrea Mario Lavezzi, 2019. "The Economics of Extortion: Theory and Evidence on the Sicilian Mafia," Discussion Papers 2019/242, Dipartimento di Economia e Management (DEM), University of Pisa, Pisa, Italy.
    3. Paulo Ferreira & Éder J.A.L. Pereira & Hernane B.B. Pereira, 2020. "From Big Data to Econophysics and Its Use to Explain Complex Phenomena," JRFM, MDPI, vol. 13(7), pages 1-10, July.
    4. Francesco N. Moro & Salvatore Sberna, 2018. "Transferring Violence? Mafia Killings in Nontraditional Areas," Journal of Conflict Resolution, Peace Science Society (International), vol. 62(7), pages 1579-1601, August.
    5. Ylenia Brilli & Marco Tonello, 2015. "The contemporaneous effect of education on adolescent crime. Mechanisms and evidence from regional divides," CHILD Working Papers Series 41 JEL Classification: I2, Centre for Household, Income, Labour and Demographic Economics (CHILD) - CCA.
    6. Marco Le Moglie & Giuseppe Sorrenti, 2022. "Revealing "Mafia Inc."? Financial Crisis, Organized Crime, and the Birth of New Enterprises," The Review of Economics and Statistics, MIT Press, vol. 104(1), pages 142-156, March.
    7. Tamara Fioroni & Andrea Mario Lavezzi & Giovanni Trovato, 2023. "Organized Crime, Corruption and Economic Growth," Discussion Papers 2023/298, Dipartimento di Economia e Management (DEM), University of Pisa, Pisa, Italy.
    8. Gaetano Perone, 2020. "The impact of agribusiness crimes on food prices: evidence from Italy," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 37(3), pages 877-909, October.
    9. Chia-Hao Lee & Pei-I Chou, 2012. "Trading Activity and Financial Market Integration," The Financial Review, Eastern Finance Association, vol. 47(3), pages 589-616, August.
    10. Lonsky, Jakub, 2020. "Gulags, Crime, and Elite Violence: Origins and Consequences of the Russian Mafia," GLO Discussion Paper Series 711, Global Labor Organization (GLO).
    11. Roy, Rudra Prosad & Sinha Roy, Saikat, 2017. "Financial contagion and volatility spillover: An exploration into Indian commodity derivative market," Economic Modelling, Elsevier, vol. 67(C), pages 368-380.
    12. Glenn Magerman & Karolien De Bruyne & Emmanuel Dhyne & Jan Van Hove, 2016. "Heterogeneous firms and the micro origins of aggregate fluctuations," Working Paper Research 312, National Bank of Belgium.
    13. Drago, Francesco & Calamunci, Francesca, 2020. "The economic impact of organized crime infiltration in the legal economy: evidence from the judicial administration of organize," CEPR Discussion Papers 14326, C.E.P.R. Discussion Papers.
    14. Roberto Ganau & Andrés Rodríguez†Pose, 2018. "Industrial clusters, organized crime, and productivity growth in Italian SMEs," Journal of Regional Science, Wiley Blackwell, vol. 58(2), pages 363-385, March.
    15. Francesca Calamunci & Francesco Drago, 2020. "The Economic Impact of Organized Crime Infiltration in the Legal Economy: Evidence from the Judicial Administration of Organized Crime Firms," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 6(2), pages 275-297, July.
    16. Huaibing Yu, 2019. "An Econometric Analysis on Influential Power Across Global Stock Markets," Journal of Finance and Investment Analysis, SCIENPRESS Ltd, vol. 8(3), pages 1-1.
    17. Mustafa Caglayan & Alessandro Flamini & Babak Jahanshahi, 2017. "Organized Crime and Technology," DEM Working Papers Series 136, University of Pavia, Department of Economics and Management.
    18. Alfredo Del Monte, 2016. "Le cause della differente diffusione della criminalit? organizzata nel Mezzogiorno," STUDI ECONOMICI, FrancoAngeli Editore, vol. 2016(118-119-1), pages 271-311.
    19. Cerqueti, Roy & Lupi, Claudio & Pietrovito, Filomena & Pozzolo, Alberto Franco, 2022. "Rank–size distributions for banks: A cross-country analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 585(C).
    20. Ficcadenti, Valerio & Cerqueti, Roy & Ausloos, Marcel & Dhesi, Gurjeet, 2020. "Words ranking and Hirsch index for identifying the core of the hapaxes in political texts," Journal of Informetrics, Elsevier, vol. 14(3).

    More about this item

    Keywords

    Companies financial risk indicator; Organized crime; Complex networks; Clustering coefficient; Entropy; Rank-size analysis;
    All these keywords.

    JEL classification:

    • M19 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Other
    • M49 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Other
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kap:rqfnac:v:57:y:2021:i:4:d:10.1007_s11156-021-00984-3. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.