IDEAS home Printed from https://ideas.repec.org/a/wly/intsec/v20y2025i2p195-210.html

The Effect of Income Polarization on Crime: Evidence From Court Judicial Documents in China

Author

Listed:
  • Jingqi Liu
  • Chen Wang
  • Yuzhou Wang

Abstract

Crime affects social stability and people's safety, and directly increases the cost of urban development. Existing literature shows that income distribution affects crime, but it mainly focuses on the effect of income inequality and poverty, with scant evidence addressing the impact of income polarization on crime. Applying data from the China Household Finance Survey (CHFS) and judicial documents from 2014 to 2018, this paper demonstrates that rising income polarization significantly increases crime in cities. The result still holds after a series of robustness checks. Heterogeneity analyses show that income polarization has a more pronounced effect on criminal activities related to violence, robbery and stealing, drug and financial fraud. Moreover, cities with a higher proportion of young and migrant populations would be more adversely affected by income polarization. Mechanism analyses indicate that income polarization exacerbates crime by increasing alienation, reducing job‐seeking willingness and happiness of residents.

Suggested Citation

  • Jingqi Liu & Chen Wang & Yuzhou Wang, 2025. "The Effect of Income Polarization on Crime: Evidence From Court Judicial Documents in China," International Studies of Economics, John Wiley & Sons, vol. 20(2), pages 195-210, June.
    • Handle: RePEc:wly:intsec:v:20:y:2025:i:2:p:195-210
    DOI: 10.1002/ise3.70012
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/ise3.70012
    Download Restriction: no
    File URL: https://libkey.io/10.1002/ise3.70012?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
    ---><---

    References listed on IDEAS

    as
    1. Enamorado, Ted & López-Calva, Luis F. & Rodríguez-Castelán, Carlos & Winkler, Hernán, 2016. "Income inequality and violent crime: Evidence from Mexico's drug war," Journal of Development Economics, Elsevier, vol. 120(C), pages 128-143.
    2. Morgan Kelly, 2000. "Inequality And Crime," The Review of Economics and Statistics, MIT Press, vol. 82(4), pages 530-539, November.
    3. Guy Michaels & Ashwini Natraj & John Van Reenen, 2010. "Has ICT Polarized Skill Demand? Evidence from Eleven Countries over 25 years," NBER Working Papers 16138, National Bureau of Economic Research, Inc.
    4. Carr, Joel & Clifton-Sprigg, Joanna & James, Jonathan & Vujic, Suncica, 2020. "Love Thy Neighbour? Brexit and Hate Crime," IZA Discussion Papers 13902, IZA Network @ LISER.
    5. Norman Loayza & Pablo Fajnzylber & Daniel Lederman, 2000. "Crime and Victimization: An Economic Perspective," Economía Journal, The Latin American and Caribbean Economic Association - LACEA, vol. 0(Fall 2000), pages 219-302.
    6. Grogger, Jeff, 1998. "Market Wages and Youth Crime," Journal of Labor Economics, University of Chicago Press, vol. 16(4), pages 756-791, October.
    7. Richard B. Freeman, 1991. "Crime and the Employment of Disadvantaged Youths," NBER Working Papers 3875, National Bureau of Economic Research, Inc.
    8. Joan Esteban & Debraj Ray, 2011. "Linking Conflict to Inequality and Polarization," American Economic Review, American Economic Association, vol. 101(4), pages 1345-1374, June.
    9. Guy Michaels & Ashwini Natraj & John Van Reenen, 2014. "Has ICT Polarized Skill Demand? Evidence from Eleven Countries over Twenty-Five Years," The Review of Economics and Statistics, MIT Press, vol. 96(1), pages 60-77, March.
    10. Hu, Xiaoshan & Song, Jie & Wan, Guanghua, 2024. "Transborder spillover effects of poverty on crime: Applying spatial econometric models to Chinese data," China Economic Review, Elsevier, vol. 85(C).
    11. Li, Jing & Wan, Guanghua & Wang, Chen & Zhang, Xueliang, 2019. "Which indicator of income distribution explains crime better? Evidence from China," China Economic Review, Elsevier, vol. 54(C), pages 51-72.
    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. Paolo Buonanno, 2003. "The Socioeconomic Determinants of Crime. A Review of the Literature," Working Papers 63, University of Milano-Bicocca, Department of Economics, revised Nov 2003.
    2. Paolo Buonanno, 2003. "Identifying the Effect of Education on Crime. Evidence from the Italian Regions," Working Papers 65, University of Milano-Bicocca, Department of Economics, revised Nov 2003.
    3. Marcel Fafchamps & Christine Moser, 2003. "Crime, Isolation and Law Enforcement," Journal of African Economies, Centre for the Study of African Economies, vol. 12(4), pages 625-671, December.
    4. Li, Jing & Wan, Guanghua & Wang, Chen & Zhang, Xueliang, 2019. "Which indicator of income distribution explains crime better? Evidence from China," China Economic Review, Elsevier, vol. 54(C), pages 51-72.
    5. Paolo Buonanno, 2006. "Crime, Education and Peer Pressure," Rivista di Politica Economica, SIPI Spa, vol. 96(5), pages 89-110, September.
    6. Kausik Chaudhuri & Payel Chowdhury & Kevin Reilly, 2013. "A New Perspective on Violent Crime Burden Index: Evidence from Indian Districts," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 110(2), pages 771-789, January.
    7. Hu, Xiaoshan & Song, Jie & Wan, Guanghua, 2024. "Transborder spillover effects of poverty on crime: Applying spatial econometric models to Chinese data," China Economic Review, Elsevier, vol. 85(C).
    8. 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.
    9. Pazzona, Matteo, 2024. "Revisiting the Income Inequality-Crime Puzzle," World Development, Elsevier, vol. 176(C).
    10. Goh, Lim Thye & Law, Siong Hook, 2023. "The crime rate of five Latin American countries: Does income inequality matter?," International Review of Economics & Finance, Elsevier, vol. 86(C), pages 745-763.
    11. van Ours, Jan C. & Williams, Jenny & Ward, Shannon, 2015. "Bad Behavior: Delinquency, Arrest and Early School Leaving," CEPR Discussion Papers 10755, Centre for Economic Policy Research.
    12. Schulte, Patrick, 2015. "Does skill-biased technical change diffuse internationally?," ZEW Discussion Papers 15-088, ZEW - Leibniz Centre for European Economic Research.
    13. Loebbing, Jonas, 2018. "An Elementary Theory of Endogenous Technical Change and Wage Inequality," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181603, Verein für Socialpolitik / German Economic Association.
    14. Marelli Enrico & Sciulli Dario & Signorelli Marcello, 2014. "Skill mismatch of graduates in a local labour market," Экономика региона, CyberLeninka;Федеральное государственное бюджетное учреждение науки «Институт экономики Уральского отделения Российской академии наук», issue 2, pages 181-194.
    15. Hjalmarsson, Randi & Machin, Stephen & Pinotti, Paolo, 2024. "Crime and the labor market," Handbook of Labor Economics,, Elsevier.
    16. T. Gries & R. Grundmann & I. Palnau & M. Redlin, 2017. "Innovations, growth and participation in advanced economies - a review of major concepts and findings," International Economics and Economic Policy, Springer, vol. 14(2), pages 293-351, April.
    17. Dale Jorgenson & Mun Ho & Jon Samuels, 2019. "Educational Intensity and the Sources of, and Prospects for, U.S. Economic Growth," International Productivity Monitor, Centre for the Study of Living Standards, vol. 36, pages 161-186, Spring.
    18. repec:plo:pone00:0233034 is not listed on IDEAS
    19. Vahagn Jerbashian, 2019. "Automation and Job Polarization: On the Decline of Middling Occupations in Europe," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 81(5), pages 1095-1116, October.
    20. Ekaterina Prytkova, 2021. "ICT's Wide Web: a System-Level Analysis of ICT's Industrial Diffusion with Algorithmic Links," Jena Economics Research Papers 2021-005, Friedrich-Schiller-University Jena.
    21. Georg Graetz & Guy Michaels, 2017. "Is Modern Technology Responsible for Jobless Recoveries?," American Economic Review, American Economic Association, vol. 107(5), pages 168-173, May.

    More about this item

    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:wly:intsec:v:20:y:2025:i:2:p:195-210. 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: Wiley Content Delivery (email available below). General contact details of provider: .

    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.