Skip to main content
SpringerLink
Log in

A Spatial Analysis of Drug Dealing in Mexico City

  • Conference paper
  • First Online:
Interdisciplinary Statistics in Mexico

Part of the book series: Springer Proceedings in Mathematics & Statistics ((PROMS,volume 397))

  • 155 Accesses

Abstract

This paper presents an application of global and local Moran’s I measures of spatial association in the detection of drug dealing hotspots in Mexico City. This exploratory case study focuses on the findings derived from the univariate and bivariate local measures for the years 2019 and 2020 to determine the existence of autocorrelation with respect to drug dealing for sale purposes and of the correlation between this and other spatially lagged variables of crimes associated to organized crime, taking as units of analysis the city’s neighborhoods. Therefore, the purpose of this paper is to contribute to the study of drug dealing in Mexico City on the basis that a data-driven approach should be the starting point of any empirical analysis that aims to study the distribution and patterns of reported crimes.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. RAND Europe.: Understanding illicit drug markets, supply-reduction efforts, and drug-related crime in the European Union. RAND Corporation, Cambridge (2010)

    Google Scholar 

  2. UNODC.: World Drug Report 2021. United Nations, Vienna (2021)

    Google Scholar 

  3. Reuter, P.: Drug Markets and Organized Crime. The Oxford Handbook of Organized Crime, 359–380. Oxford University Press, New York (2014)

    Google Scholar 

  4. UNODC.: The Globalization of Crime. A Transnational Organized Crime Threat Assessment. United Nations, Vienna (2010)

    Google Scholar 

  5. Comisión Nacional contra las Adicciones.: Informe sobre la Situación del Consumo de Drogas en México y su Atención Integral 2019. Gobierno de México, Mexico City (2019)

    Google Scholar 

  6. Cámara de Diputados del H. Congreso de la Unión.: Ley General de Salud. (2021). http://www.diputados.gob.mx/LeyesBiblio/pdf_mov/Ley_General_de_Salud.pdf

  7. SESNSP.: Incidencia delictiva. Gobierno de México, (2021). https://www.gob.mx/sesnsp/acciones-y-programas/incidencia-delictiva-87005?idiom=es

  8. UNODC.: World Drug Report 2021. COVID-19 and Drugs: Impact Outlook. United Nations, Vienna (2021)

    Google Scholar 

  9. Cámara de Diputados del H. Congreso de la Unión.: Ley Federal contra la Delincuencia Organizada. (2021). http://www.diputados.gob.mx/LeyesBiblio/pdf/101_200521.pdf

  10. Paoli, L., Beken, T.V.: Organized Crime: A Contested Concept. The Oxford Handbook of Organized Crime, 13–31. Oxford University Press (2014)

    Google Scholar 

  11. Zamudio, A., Carlos, A.: “Qué es el narcomenudeo?” Un acercamiento etnológico. Revista Liberaddictus (103), 3–7 (2008). http://dx.doi.org/10.30972/geo.17334426

  12. UNODC.: Global Study on Homicide 2019. United Nations, Vienna (2019)

    Google Scholar 

  13. Infobae.: “Mapa del “cobro de piso” en CDMX: dónde se han reportado extorsiones del crimen organizado.” Infobae, (01/12/2020). https://www.infobae.com/america/mexico/2020/12/01/mapa-del-cobro-de-piso-en-cdmx-donde-se-han-reportado-extorsiones-del-crimen-organizado/

  14. La Redacción.: “Extorsiones y cobro por derecho de piso aumentan en tres alcaldías de CDMX: Canaco.” Proceso, (10/09/2021). https://www.proceso.com.mx/nacional/2021/9/10/extorsiones-cobro-por-derecho-de-piso-aumentan-en-tres-alcaldias-de-cdmx-canaco-271753.html

  15. Vilalta, C., Lopez-Ramirez, P., Fondevila, G.: The spatial diffusion of homicide in Mexico City: a test of theories in context. Global Crime 22(3), 222–239 (2021). https://doi.org/10.1080/17440572.2021.1909480

  16. Rosen, J.D., Zepeda Martinez, R.: La guerra contra el narcotráfico en México: una guerra perdida. Reflexiones 94(1), 153–168 (2015). https://doi.org/10.15517/rr.v94i1.20889

  17. Clarke, R.V., Cornish, D.B.: Modeling Offenders’ Decisions: A Framework for Research and Policy. Crime and Justice: An Annual Review of Research, vol. 6 (1985)

    Google Scholar 

  18. Cohen, L.E., Felson, M.: Social Change and Crime Rate Trends: A Routine Activity Approach. Am. Sociol. Rev. 44(4), 588–608 (1979)

    Google Scholar 

  19. Shaw, C.R., McKay, H.D.: Juvenile Delinquency and Urban Areas. University of Chicago Press, Chicago (1942)

    Google Scholar 

  20. Eck, J.E.: A General Model of the Geography of Illicit Retail Marketplaces. Crime and Place: Crime Prevention Studies, vol. 4, pp. 67–93. Police Executive Research Forum, Washington, D.C (1995)

    Google Scholar 

  21. Cisneros, J.L.: La neta somos así. Violencia cotidiana, espacio y juventud: el caso de la colonia Desarrollo Urbano Quetzalcóatl, Ciudad de México. Poliíticas de seguridad y entornos violentos en Colombia y México, 181–198. Universidad de Medelliín, Medellín (2018)

    Google Scholar 

  22. Zamudio, A., Carlos, A.: Jóvenes en el narcomenudeo: el caso Ciudad de México. URVIO, Revista Latinoamericana de Seguridad Ciudadana 13, 111–123 (2013). https://doi.org/10.17141/urvio.13.2013.1185

  23. Vilalta, P., Carlos, J.: El robo de vehículos en la ciudad de México. Patrones espaciales y series de tiempo. Gestión y Política Pública 20(1), 97–139 (2011)

    Google Scholar 

  24. Barnum, J.D., Campbell, W.L., Trocchio, S., Caplan, J.M., Kennedy, L.W.: Examining the Environmental Characteristics of Drug Dealing Locations. Crime Delinq. 63(13), 1731–1756 (2017). https://doi.org/10.1177/2F0011128716649735

  25. Chen, J., Liu, L., Liu, H., Long, D., Xu, C., Zhou, H.: The spatial heterogeneity of factors of drug dealing: A case study from ZG, China. ISPRS Int. J. Geo-Inf. 9(4) (2020). https://doi.org/10.3390/ijgi9040205

  26. Blanco, H.D.: Análisis Espacial de Patrones Delictivos en la Ciudad de Formosa, Argentina. Actas Científicas Congreso Internacional de Geografía - 78\(^{\circ }\) Semana de la Geografía, 43–58 (2017)

    Google Scholar 

  27. Vilalta P., Carlos J.: La geografía local del narcomenudeo: patrones, procesos y recomendaciones de política urbana. Estudios Demográficos y Urbanos 24(1), 49–77 (2009). https://doi.org/10.24201/edu.v24i1.1344

  28. Weisburd, D., Bruinsma, G.J., Bernasco, W.: Units of Analysis in Geographic Criminology: Historical Development, Critical Issues, and Open Questions in Putting Crime in its Place, vol. 3–31. Springer (2009)

    Google Scholar 

  29. Weisburd, D., Groff, E.R., Yang, S.-M.: The Criminology of Place: Street segments and our understanding of the crime problem, Oxford University Press, 40–41 (2012)

    Google Scholar 

  30. Tita, G.E., Greenbaum, R.T.: Crime, Neighborhoods, and Units of Analysis in Putting Crime in its Place, pp. 145–170. Springer (2009)

    Google Scholar 

  31. Fiscalía General de Justicia (FGJ) de la Ciudad de México.: Carpetas de investigación FGJ de la Ciudad de México. Portal de Datos Abiertos de la CDMX, (2021). https://datos.cdmx.gob.mx/dataset/carpetas-de-investigacion-fgj-de-la-ciudad-de-mexico

  32. UNODC.: Comisión Económica de las Naciones Unidas para Europa. Manual Para Encuestas de Victimización. Naciones Unidas, Ginebra (2010)

    Google Scholar 

  33. de Smith, M.J., Goodchild, M.F., Longley, P.A.: Geospatial Analysis. A Comprehensive Guide to Principles, Techniques and Software Tools. de Smith, Goodchild, Longley and Associates (2018–2021)

    Google Scholar 

  34. ArcGIS.: Data classification methods—ArcGIS Pro Documentation. Esri, (2021). https://pro.arcgis.com/en/pro-app/latest/help/mapping/layer-properties/data-classification-methods.htmESRI_SECTION1_B47C458CFF6A4EEC933A8C7612DA558B

  35. Anselin, L.: Basic Mapping. GeoDa, (2021). https://geodacenter.github.io/workbook/3a_mapping/lab3a.htmlthematic-maps-overview

  36. Anselin, L.: Global Spatial Autocorrelation. GeoDa, (2020). https://geodacenter.github.io/workbook/5a_global_auto/lab5a.html

  37. Anselin, L.: Local Spatial Autocorrelation (1). Geoda, (2020). https://geodacenter.github.io/workbook/6a_local_auto/lab6a.html

  38. Lloyd, C.D.: Local Models for Spatial Analysis. CRC Press (2007)

    Google Scholar 

  39. Anselin, L.: Local Indicators of Spatial Association—LISA. Geogr. Anal. 27(2), 93–115 (1995) https://doi.org/10.1111/j.1538-4632.1995.tb00338.x

  40. Tiefelsdorf, M.: The saddlepoint approximation of Moran’s I’s and local Moran’s Ii’s reference distributions and their numerical evaluation. Geogr. Anal. 34(3), 187–206 (2002). https://doi.org/10.1111/j.1538-4632.2002.tb01084.x

  41. Anselin, Luc.: Global Spatial Autocorrelation (2): Bivariate, Differential and EB Rate Moran Scatter Plot. Geoda, (2019) https://geodacenter.github.io/workbook/5b_global_adv/lab5b.html

  42. Anselin, Luc.: Local Spatial Autocorrelation (3): Multivariate Local Spatial Autocorrelation. Geoda, (2020). https://geodacenter.github.io/workbook/6c_local_multi/lab6c.htmlbivariate-local-moran

  43. Hernández, S.A.: Spatial-analysis/drug-dealing-Mexico-City. GitHub, (2021). https://github.com/shani-alvarez/Spatial-analysis/tree/main/drug-dealing-Mexico-City

Download references

Author information

Authors and Affiliations

  1. Justice Program, UNODC Mexico, Mexico City, Mexico

    Shaní Alvarez Hernández

Authors
  1. Shaní Alvarez Hernández
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Shaní Alvarez Hernández .

Editor information

Editors and Affiliations

  1. Department of Environmental Sciences, Informatics and Statistics, Ca' Foscari University of Venice, Venice, Italy

    Isadora Antoniano-Villalobos

  2. Department of Mathematics, Facultad de Ciencias, UNAM, Mexico City, Mexico

    Ruth Fuentes-García

  3. Department of Mathematics, Facultad de Ciencias, UNAM, Mexico City, Mexico

    Lizbeth Naranjo

  4. Department of Statistics, ITAM, Mexico City, Mexico

    Luis E. Nieto-Barajas

  5. Department of Probability and Statistics, IIMAS, UNAM, Mexico City, Mexico

    Silvia Ruiz-Velasco Acosta

Appendix

Appendix

Table 1 Number of crimes reported in Mexico City, 2019–2020
Full size table
Table 2 Number of hotspots per borough, univariate local Moran I of drug dealing for sale purposes, 2019–2020
Full size table
Table 3 Number of hotspots per borough, bivariate local Moran I of drug dealing for sale purposes and intentional homicide, 2019–2020
Full size table
Table 4 Number of hotspots per borough, bivariate local Moran I of drug dealing for sale purposes and illicit carrying of firearms, 2019–2020
Full size table
Table 5 Number of hotspots per borough, bivariate local Moran I of drug dealing for sale purposes and extortion, 2019–2020
Full size table
Table 6 Number of hotspots per borough, bivariate local Moran I of drug dealing for sale purposes and kidnapping, 2019–2020
Full size table
Table 7 Number of hotspots per borough, bivariate local Moran I of drug dealing for sale purposes and drug dealing (simple possession), 2019–2020
Full size table
Table 8 Examples of hotspots identified in both 2019 and 2020, univariate local Moran’s I, drug dealing for sale purposes
Full size table
Table 9 Examples of hotspots identified in both 2019 and 2020, bivariate local Moran’s I, drug dealing for sale purposes and intentional homicide
Full size table
Table 10 Examples of hotspots identified in both 2019 and 2020, bivariate local Moran’s  I, drug dealing for sale purposes and illicit carrying of firearms
Full size table
Table 11 Examples of hotspots identified in both 2019 and 2020, bivariate local Moran’s  I, drug dealing for sale purposes and extortion
Full size table
Table 12 Examples of hotspots identified in both 2019 and 2020, bivariate local Moran’s  I, drug dealing for sale purposes and drug dealing (simple possession)
Full size table

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Alvarez Hernández, S. (2022). A Spatial Analysis of Drug Dealing in Mexico City. In: Antoniano-Villalobos, I., Fuentes-García, R., Naranjo, L., Nieto-Barajas, L.E., Ruiz-Velasco Acosta, S. (eds) Interdisciplinary Statistics in Mexico. Springer Proceedings in Mathematics & Statistics, vol 397. Springer, Cham. https://doi.org/10.1007/978-3-031-12778-6_2

Download citation

Publish with us

Policies and ethics

Search

Navigation