IDEAS home Printed from https://ideas.repec.org/a/eee/ecanpo/v88y2025icp1482-1501.html

Revealing nexus between crime and inequality: Application of artificial neural network with bootstrapping approach

Author

Listed:
  • Zeng, Tingting
  • Cheong, Tsun Se
  • Shum, Wai Yan
  • Wan, Guanghua
  • Wu, Haitao
  • Ma, Ning

Abstract

The social structure theory posits that crime is a consequence of inequality. However, an expanding body of research indicates that crime can also emerge from affluence and equality. This study used an artificial neural network approach (ANN) and a bootstrapping approach (RAB) to study the relationship between crime and inequality, incorporating various influencing factors into the model. Results reveal an asymmetric inverted U-shaped pattern, with crime at its minimum when the Gini coefficient is 0.35. This observation implies that crime is promoted at elevated levels of inequality or excessive equality. Furthermore, the study acknowledges the influence of diverse factors, including human capital, population density, inflation, unemployment, urbanization, and civil liberties, on the dynamics of the relationship between inequality and crime rates. These findings provide pragmatic policy implications for countries at different stages of economic development, aiming to achieve economic growth with social equity and crime reduction.

Suggested Citation

  • Zeng, Tingting & Cheong, Tsun Se & Shum, Wai Yan & Wan, Guanghua & Wu, Haitao & Ma, Ning, 2025. "Revealing nexus between crime and inequality: Application of artificial neural network with bootstrapping approach," Economic Analysis and Policy, Elsevier, vol. 88(C), pages 1482-1501.
    • Handle: RePEc:eee:ecanpo:v:88:y:2025:i:c:p:1482-1501
    DOI: 10.1016/j.eap.2025.10.045
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0313592625004461
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.eap.2025.10.045?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

    for a different version of it.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:eee:ecanpo:v:88:y:2025:i:c:p:1482-1501. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/economic-analysis-and-policy .

    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.