IDEAS home Printed from https://ideas.repec.org/a/pal/palcom/v10y2023i1d10.1057_s41599-023-01706-x.html
   My bibliography  Save this article

Does commerce promote theft? A quantitative study from Beijing, China

Author

Listed:
  • Yutian Jiang

    (Beijing Jiaotong University)

  • Na Zhang

    (Beijing Jiaotong University
    Beijing Jiaotong University)

Abstract

Commerce, as both an environmental and a social factor, is essential to the study of the causes of urban crimes. This paper aims to comprehensively propose research hypotheses based on these two types of commercial factors and optimise statistical tools with which to analyse commerce’s impact on the level of theft in Beijing. Combining criminal verdicts, census data, points of interest, and information on nighttime lighting, this paper first applies a hierarchical regression model to verify the effectiveness of using commercial environmental and social factors to explain theft statistics and then constructs a structural equation model to analyse the joint influence of multiple commercial factors on those statistics. This paper finds that Beijing’s commerce does not significantly promote theft, verifies the effectiveness of two types of commercial variables and the corresponding Western theories in explaining commerce’s impact on theft in Beijing, and provides empirical data for the study of the causes of theft in a non-Western context.

Suggested Citation

  • Yutian Jiang & Na Zhang, 2023. "Does commerce promote theft? A quantitative study from Beijing, China," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-14, December.
    • Handle: RePEc:pal:palcom:v:10:y:2023:i:1:d:10.1057_s41599-023-01706-x
    DOI: 10.1057/s41599-023-01706-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41599-023-01706-x
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1057/s41599-023-01706-x?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. Najaf, Pooya & Thill, Jean-Claude & Zhang, Wenjia & Fields, Milton Greg, 2018. "City-level urban form and traffic safety: A structural equation modeling analysis of direct and indirect effects," Journal of Transport Geography, Elsevier, vol. 69(C), pages 257-270.
    2. John Gibson & Susan Olivia & Geua Boe‐Gibson, 2020. "Night Lights In Economics: Sources And Uses," Journal of Economic Surveys, Wiley Blackwell, vol. 34(5), pages 955-980, December.
    3. Cheng, Zhiming & Smyth, Russell, 2015. "Crime victimization, neighborhood safety and happiness in China," Economic Modelling, Elsevier, vol. 51(C), pages 424-435.
    4. John Gibson, 2021. "Better Night Lights Data, For Longer," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(3), pages 770-791, June.
    5. repec:lic:licosd:41920 is not listed on IDEAS
    6. Gibson, John & Olivia, Susan & Boe-Gibson, Geua & Li, Chao, 2021. "Which night lights data should we use in economics, and where?," Journal of Development Economics, Elsevier, vol. 149(C).
    7. Anders Skrondal & Sophia Rabe‐Hesketh, 2007. "Latent Variable Modelling: A Survey," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 34(4), pages 712-745, December.
    8. Fengrui Jing & Lin Liu & Suhong Zhou & Guangwen Song, 2020. "Examining the Relationship between Hukou Status, Perceived Neighborhood Conditions, and Fear of Crime in Guangzhou, China," Sustainability, MDPI, vol. 12(22), pages 1-19, November.
    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. GIBSON, John & ZHANG, Xiaoxuan & PARK, Albert & YI, Jiang & XI, Li, 2024. "Remotely measuring rural economic activity and poverty : Do we just need better sensors?," CEI Working Paper Series 2023-08, Center for Economic Institutions, Institute of Economic Research, Hitotsubashi University.
    2. Bonggeun Kim & John Gibson & Geua Boe‐Gibson, 2024. "Measurement errors in popular night lights data may bias estimated impacts of economic sanctions: Evidence from closing the Kaesong Industrial Zone," Economic Inquiry, Western Economic Association International, vol. 62(1), pages 375-389, January.
    3. Roberts,Mark, 2021. "Tracking Economic Activity in Response to the COVID-19 Crisis Using Nighttime Lights — The Case of Morocco," Policy Research Working Paper Series 9538, The World Bank.
    4. John Gibson & Bonggeun Kim & Geua Boe-Gibson, 2022. "How effective are sanctions on North Korea? Popular DMSP night-lights data may bias evaluations due to blurring and poor low-light detection," Working Papers in Economics 22/06, University of Waikato, revised 14 Nov 2022.
    5. Omoniyi Alimi & Geua Boe-Gibson & John Gibson, 2022. "Noisy Night Lights Data: Effects on Research Findings for Developing Countries," Working Papers in Economics 22/12, University of Waikato.
    6. repec:ags:aaea22:335528 is not listed on IDEAS
    7. Linsenmeier, Manuel, 2021. "Temperature variability and long-run economic development," LSE Research Online Documents on Economics 110499, London School of Economics and Political Science, LSE Library.
    8. Miguel Puente-Ajovín & Marcos Sanso-Navarro & María Vera-Cabello, 2022. "The distribution of urban population and economic activity in the European Union and the United States," Letters in Spatial and Resource Sciences, Springer, vol. 15(3), pages 517-522, December.
    9. John Gibson & Yi Jiang & Xiaoxuan Zhang & Geua Boe-Gibson, 2024. "Are Disaster Impact Estimates Distorted by Errors in Popular Night-Time Lights Data?," Economics of Disasters and Climate Change, Springer, vol. 8(3), pages 391-416, November.
    10. Gibson, John & Jiang, Yi & Susantono, Bambang, 2023. "Revisiting the role of secondary towns: How different types of urban growth relate to poverty in Indonesia," World Development, Elsevier, vol. 169(C).
    11. John Gibson & Susan Olivia & Geua Boe‐Gibson, 2020. "Night Lights In Economics: Sources And Uses," Journal of Economic Surveys, Wiley Blackwell, vol. 34(5), pages 955-980, December.
    12. Idriss Fontaine & Sabine Garabedian & Hélène Vérèmes, 2022. "The current and future costs of tropical cyclones: A case study of La Réunion," TEPP Working Paper 2022-10, TEPP.
    13. Shapiro, Daniel & Oh, Chang Hoon & Zhang, Peng, 2023. "Nighttime lights data and their implications for IB research," Journal of International Management, Elsevier, vol. 29(5).
    14. Haoqi Qian & Zhengyu Shi & Libo Wu, 2021. "Inferring Economic Condition Uncertainty from Electricity Big Data," Papers 2107.11593, arXiv.org, revised May 2023.
    15. Jules Gazeaud & Victor Stephane, 2023. "Productive Workfare? Evidence from Ethiopia's Productive Safety Net Program," American Journal of Agricultural Economics, John Wiley & Sons, vol. 105(1), pages 265-290, January.
    16. Jesson A. Pagaduan, 2022. "Do higher‐quality nighttime lights and net primary productivity predict subnational GDP in developing countries? Evidence from the Philippines," Asian Economic Journal, East Asian Economic Association, vol. 36(3), pages 288-317, September.
    17. Bruno Morando, 2024. "Testing the GAEZ agronomic model in the fields:Evidence from Uganda," Economics Department Working Paper Series n320-24.pdf, Department of Economics, National University of Ireland - Maynooth.
    18. Linsenmeier, Manuel, 2023. "Temperature variability and long-run economic development," Journal of Environmental Economics and Management, Elsevier, vol. 121(C).
    19. Katarzyna Anna Bilicka & André Seidel, 2022. "Measuring Firm Activity from Outer Space," CESifo Working Paper Series 9701, CESifo.
    20. Chen, Liming & Lu, Yang & Nanayakkara, Aruna, 2023. "Rural road connectivity and local economic Activity: Evidence from Sri Lanka’s iRoad program," Transport Policy, Elsevier, vol. 144(C), pages 49-64.
    21. John Gibson, 2021. "Better Night Lights Data, For Longer," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(3), pages 770-791, June.

    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:pal:palcom:v:10:y:2023:i:1:d:10.1057_s41599-023-01706-x. 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: https://www.nature.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.