IDEAS home Printed from https://ideas.repec.org/a/pal/palcom/v9y2022i1d10.1057_s41599-022-01393-0.html
   My bibliography  Save this article

Empirical evidence of the impact of mobility on property crimes during the first two waves of the COVID-19 pandemic

Author

Listed:
  • Kandaswamy Paramasivan

    (Government of Tamil Nadu)

  • Rahul Subburaj

    (Indian Institute of Technology)

  • Saish Jaiswal

    (Indian Institute of Technology)

  • Nandan Sudarsanam

    (Indian Institute of Technology)

Abstract

This paper seeks to evaluate the impact of the removal of restrictions (partial and complete) imposed during COVID-19-induced lockdowns on property offences such as robbery, burglary, and theft during the milder wave one and the more severe wave two of the pandemic in 2020 and 2021, respectively. Using 10-year data of the daily counts of crimes, the authors adopt an auto-regressive neural networks method to make counterfactual predictions of crimes, representing a scenario without the pandemic-induced lockdowns. The difference between the actual and forecast is the causal impact of the lockdown in all phases. Further, the research uses Google Mobility Community Reports to measure mobility. The analysis has been done at two levels: first, for the state of Tamil Nadu, which has a sizeable rural landscape, and second for Chennai, the largest metropolitan city with an urban populace. During the pandemic-induced lockdown in wave one, there was a steep decline in the incidence of property offences. On removing restrictions, the cases soared above the counterfactual predicted counts. In wave two, despite the higher severity and fatality in the COVID-19 pandemic, a similar trend of fall and rise in property cases was observed. However, the drop in mobility was less substantial, and the increase in the magnitude of property offences was more significant in wave two than in wave one. The overall trend of fluctuations is related to mobility during various phases of restrictions in the pandemic. When most curbs were removed, there was a surge in robberies in Tamil Nadu and Chennai after adjusting for mobility. This trend highlights the effective increase in crime due to pandemic-related economic and social consequences. Further, the research enables law enforcement to strengthen preventive crime work in similar situations, when most curbs are removed after a pandemic or other unanticipated scenarios.

Suggested Citation

  • Kandaswamy Paramasivan & Rahul Subburaj & Saish Jaiswal & Nandan Sudarsanam, 2022. "Empirical evidence of the impact of mobility on property crimes during the first two waves of the COVID-19 pandemic," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-14, December.
    • Handle: RePEc:pal:palcom:v:9:y:2022:i:1:d:10.1057_s41599-022-01393-0
    DOI: 10.1057/s41599-022-01393-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41599-022-01393-0
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1057/s41599-022-01393-0?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. Raphael, Steven & Winter-Ember, Rudolf, 2001. "Identifying the Effect of Unemployment on Crime," Journal of Law and Economics, University of Chicago Press, vol. 44(1), pages 259-283, April.
    2. Shubhangi Agrawal & Tom Kirchmaier & Carmen Villa-Llera, 2022. "Covid-19 and local crime rates in England and Wales - two years into the pandemic," CEP Covid-19 Analyses cepcovid-19-027, Centre for Economic Performance, LSE.
    3. Mohler, George & Bertozzi, Andrea L. & Carter, Jeremy & Short, Martin B. & Sledge, Daniel & Tita, George E. & Uchida, Craig D. & Brantingham, P. Jeffrey, 2020. "Impact of social distancing during COVID-19 pandemic on crime in Los Angeles and Indianapolis," Journal of Criminal Justice, Elsevier, vol. 68(C).
    4. Amy E. Nivette & Renee Zahnow & Raul Aguilar & Andri Ahven & Shai Amram & Barak Ariel & María José Arosemena Burbano & Roberta Astolfi & Dirk Baier & Hyung-Min Bark & Joris E. H. Beijers & Marcelo Ber, 2021. "A global analysis of the impact of COVID-19 stay-at-home restrictions on crime," Nature Human Behaviour, Nature, vol. 5(7), pages 868-877, July.
    5. Salinas, David & Flunkert, Valentin & Gasthaus, Jan & Januschowski, Tim, 2020. "DeepAR: Probabilistic forecasting with autoregressive recurrent networks," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1181-1191.
    6. Perez-Vincent, Santiago M. & Schargrodsky, Ernesto & García Mejía, Mauricio, 2021. "Crime under Lockdown: The Impact of COVID-19 on Citizen Security in the City of Buenos Aires," IDB Publications (Working Papers) 11423, Inter-American Development Bank.
    7. Mikaela Meyer & Ahmed Hassafy & Gina Lewis & Prasun Shrestha & Amelia M. Haviland & Daniel S. Nagin, 2022. "Changes in Crime Rates during the COVID-19 Pandemic," Statistics and Public Policy, Taylor & Francis Journals, vol. 9(1), pages 97-109, December.
    8. Anna Öster & Jonas Agell, 2007. "Crime and Unemployment in Turbulent Times," Journal of the European Economic Association, MIT Press, vol. 5(4), pages 752-775, June.
    9. Hyeon-Woo Kang & Hang-Bong Kang, 2017. "Prediction of crime occurrence from multi-modal data using deep learning," PLOS ONE, Public Library of Science, vol. 12(4), pages 1-19, April.
    10. Justin Sirignano & Rama Cont, 2019. "Universal features of price formation in financial markets: perspectives from deep learning," Quantitative Finance, Taylor & Francis Journals, vol. 19(9), pages 1449-1459, September.
    11. Carbonneau, Real & Laframboise, Kevin & Vahidov, Rustam, 2008. "Application of machine learning techniques for supply chain demand forecasting," European Journal of Operational Research, Elsevier, vol. 184(3), pages 1140-1154, February.
    12. Gian Maria Campedelli & Alberto Aziani & Serena Favarin, 2020. "Exploring the Effects of COVID-19 Containment Policies on Crime: An Empirical Analysis of the Short-term Aftermath in Los Angeles," Papers 2003.11021, arXiv.org, revised Oct 2020.
    13. Ymir Mäkinen & Juho Kanniainen & Moncef Gabbouj & Alexandros Iosifidis, 2019. "Forecasting jump arrivals in stock prices: new attention-based network architecture using limit order book data," Quantitative Finance, Taylor & Francis Journals, vol. 19(12), pages 2033-2050, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kandaswamy Paramasivan & Brinda Subramani & Nandan Sudarsanam, 2022. "Counterfactual analysis of the impact of the first two waves of the COVID-19 pandemic on the reporting and registration of missing people in India," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-14, December.

    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. Hodgkinson, Tarah & Andresen, Martin A. & Frank, Richard & Pringle, Darren, 2022. "Crime down in the Paris of the prairies: Spatial effects of COVID-19 and crime during lockdown in Saskatoon, Canada," Journal of Criminal Justice, Elsevier, vol. 78(C).
    2. Milo Bianchi & Paolo Buonanno & Paolo Pinotti, 2012. "Do Immigrants Cause Crime?," Journal of the European Economic Association, European Economic Association, vol. 10(6), pages 1318-1347, December.
    3. Simon Luechinger & Stephan Meier & Alois Stutzer, 2010. "Why Does Unemployment Hurt the Employed?: Evidence from the Life Satisfaction Gap Between the Public and the Private Sector," Journal of Human Resources, University of Wisconsin Press, vol. 45(4), pages 998-1045.
    4. Altindag, Duha T., 2012. "Crime and unemployment: Evidence from Europe," International Review of Law and Economics, Elsevier, vol. 32(1), pages 145-157.
    5. Piopiunik, Marc & Ruhose, Jens, 2017. "Immigration, regional conditions, and crime: Evidence from an allocation policy in Germany," European Economic Review, Elsevier, vol. 92(C), pages 258-282.
    6. Bignon, Vincent & Caroli, Eve & Galbiati, Roberto, 2011. "Stealing to Survive: Crime and Income Shocks in 19th Century France," CEPREMAP Working Papers (Docweb) 1111, CEPREMAP, revised Feb 2013.
    7. Paolo Buonanno & Leopoldo Fergusson & Juan Fernando Vargas, 2014. "The crime kuznets curve," Borradores de Investigación 11043, Universidad del Rosario.
    8. Siwach, Garima, 2018. "Unemployment shocks for individuals on the margin: Exploring recidivism effects," Labour Economics, Elsevier, vol. 52(C), pages 231-244.
    9. Roberto Galbiati & Aurélie Ouss & Arnaud Philippe, 2021. "Jobs, News and Reoffending after Incarceration [Examining the generality of the unemployment–crime association]," The Economic Journal, Royal Economic Society, vol. 131(633), pages 247-270.
    10. Ioannis Laliotis, 2016. "Crime and unemployment in Greece: Evidence before and during the crisis," Economics and Business Letters, Oviedo University Press, vol. 5(1), pages 10-16.
    11. Brandyn F. Churchill & Andrew Dickinson & Taylor Mackay & Joseph J. Sabia, 2022. "The Effect of E-Verify Laws on Crime," ILR Review, Cornell University, ILR School, vol. 75(5), pages 1294-1320, October.
    12. Carlos Díaz & Sebastian Fossati & Nicolás Trajtenberg, 2022. "Stay at home if you can: COVID‐19 stay‐at‐home guidelines and local crime," Journal of Empirical Legal Studies, John Wiley & Sons, vol. 19(4), pages 1067-1113, December.
    13. Povilas Lastauskas & Eirini Tatsi, 2017. "Spatial Nexus in Crime and Unemployement in Times of Crisis," Bank of Lithuania Working Paper Series 39, Bank of Lithuania.
    14. Panu Poutvaara & Mikael Priks, 2011. "Unemployment and gang crime: can prosperity backfire?," Economics of Governance, Springer, vol. 12(3), pages 259-273, September.
    15. Jens Ruhose, 2015. "Microeconometric Analyses on Economic Consequences of Selective Migration," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 61.
    16. Carter, Travis M. & Turner, Noah D., 2021. "Examining the immediate effects of COVID-19 on residential and commercial burglaries in Michigan: An interrupted time-series analysis," Journal of Criminal Justice, Elsevier, vol. 76(C).
    17. Vincent Bignon & Eve Caroli & Roberto Galbiati, 2017. "Stealing to Survive? Crime and Income Shocks in Nineteenth Century France," Economic Journal, Royal Economic Society, vol. 127(599), pages 19-49, February.
    18. Matthew Valasik & Shannon E. Reid, 2021. "East Side Story: Disaggregating Gang Homicides in East Los Angeles," Social Sciences, MDPI, vol. 10(2), pages 1-17, February.
    19. Langton, Samuel & Dixon, Anthony & Farrell, Graham, 2021. "Small area variation in crime effects of COVID-19 policies in England and Wales," SocArXiv cw6a4, Center for Open Science.
    20. Niclas Kruger, 2011. "The impact of economic fluctuations on crime: a multiscale analysis," Applied Economics Letters, Taylor & Francis Journals, vol. 18(2), pages 179-182.

    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:9:y:2022:i:1:d:10.1057_s41599-022-01393-0. 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.