IDEAS home Printed from https://ideas.repec.org/a/eee/irlaec/v72y2022ics0144818822000564.html
   My bibliography  Save this article

Spatial and temporal correlations of crime in Detroit: Evidence from spatial dynamic panel data models

Author

Listed:
  • Lin, Xu
  • Zhang, Jihu
  • Jiang, Shanhe

Abstract

Since the infamous riot of 1967, high crime rates and negative media reports have labeled the city of Detroit as one of the most dangerous cities in the United States. Using a Spatial Dynamic Panel Data model with both individual and time fixed effects to capture the unobserved heterogeneity as well as the time varying common factors, we investigate the spatial and temporal interactions of criminal activities among the block groups in Detroit. The results indicate that the crime incidents in a block is correlated with the average crime incidents in neighboring block groups contemporaneously, with an estimated coefficient of 0.4758, and the block crime incidents is also correlated with the average crime incidents in neighboring blocks from the previous year, with an estimated coefficient of 0.1572. And crime incidents in a block are positively correlated with its own crime incidents in the previous year. The findings are robust against different model specifications based on alternative spatial weights matrices. The results for both violent crimes and property crimes also suggest strong spatial and temporal correlations among neighboring blocks, providing suggestive and preliminary evidence for policy implementation.

Suggested Citation

  • Lin, Xu & Zhang, Jihu & Jiang, Shanhe, 2022. "Spatial and temporal correlations of crime in Detroit: Evidence from spatial dynamic panel data models," International Review of Law and Economics, Elsevier, vol. 72(C).
  • Handle: RePEc:eee:irlaec:v:72:y:2022:i:c:s0144818822000564
    DOI: 10.1016/j.irle.2022.106100
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0144818822000564
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.irle.2022.106100?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. Gary S. Becker, 1974. "Crime and Punishment: An Economic Approach," NBER Chapters, in: Essays in the Economics of Crime and Punishment, pages 1-54, National Bureau of Economic Research, Inc.
    2. Maria Cracolici & Teodora Uberti, 2009. "Geographical distribution of crime in Italian provinces: a spatial econometric analysis," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 29(1), pages 1-28, February.
    3. Stephen Machin & Olivier Marie & Sunčica Vujić, 2011. "The Crime Reducing Effect of Education," Economic Journal, Royal Economic Society, vol. 121(552), pages 463-484, May.
    4. Baltagi, Badi H. & Jung, Byoung Cheol & Song, Seuck Heun, 2010. "Testing for heteroskedasticity and serial correlation in a random effects panel data model," Journal of Econometrics, Elsevier, vol. 154(2), pages 122-124, February.
    5. Stephen Gibbons & Henry G. Overman, 2012. "Mostly Pointless Spatial Econometrics?," Journal of Regional Science, Wiley Blackwell, vol. 52(2), pages 172-191, May.
    6. Eric D. Gould & Bruce A. Weinberg & David B. Mustard, 2002. "Crime Rates And Local Labor Market Opportunities In The United States: 1979-1997," The Review of Economics and Statistics, MIT Press, vol. 84(1), pages 45-61, February.
    7. J. H. Ratcliffe & M. J. McCullagh, 1999. "Hotbeds of crime and the search for spatial accuracy," Journal of Geographical Systems, Springer, vol. 1(4), pages 385-398, December.
    8. Scorzafave, Luiz Guilherme & Soares, Milena Karla, 2009. "Income inequality and pecuniary crimes," Economics Letters, Elsevier, vol. 104(1), pages 40-42, July.
    9. Wim Bernasco & Thomas de Graaff & Jan Rouwendal & Wouter Steenbeek, 2017. "Social Interactions and Crime Revisited: An Investigation Using Individual Offender Data in Dutch Neighborhoods," The Review of Economics and Statistics, MIT Press, vol. 99(4), pages 622-636, July.
    10. Tadao Hoshino, 2018. "Semiparametric Spatial Autoregressive Models With Endogenous Regressors: With an Application to Crime Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 160-172, January.
    11. Wei Shi & Lung-fei Lee, 2018. "The effects of gun control on crimes: a spatial interactive fixed effects approach," Empirical Economics, Springer, vol. 55(1), pages 233-263, August.
    12. Lindquist, Matthew J. & Zenou, Yves, 2019. "Crime and Networks: 10 Policy Lessons," IZA Discussion Papers 12534, Institute of Labor Economics (IZA).
    13. H. Naci Mocan & Hope Corman, 2000. "A Time-Series Analysis of Crime, Deterrence, and Drug Abuse in New York City," American Economic Review, American Economic Association, vol. 90(3), pages 584-604, June.
    14. Lance Lochner & Enrico Moretti, 2004. "The Effect of Education on Crime: Evidence from Prison Inmates, Arrests, and Self-Reports," American Economic Review, American Economic Association, vol. 94(1), pages 155-189, March.
    15. Charles F. Manski, 1993. "Identification of Endogenous Social Effects: The Reflection Problem," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 60(3), pages 531-542.
    16. Badi H. Baltagi & Peter Egger & Michael Pfaffermayr, 2013. "A Generalized Spatial Panel Data Model with Random Effects," Econometric Reviews, Taylor & Francis Journals, vol. 32(5-6), pages 650-685, August.
    17. Anselin, Luc, 2002. "Under the hood : Issues in the specification and interpretation of spatial regression models," Agricultural Economics, Blackwell, vol. 27(3), pages 247-267, November.
    18. Lee, Lung-fei & Yu, Jihai, 2010. "A Spatial Dynamic Panel Data Model With Both Time And Individual Fixed Effects," Econometric Theory, Cambridge University Press, vol. 26(2), pages 564-597, April.
    19. Kakamu, Kazuhiko & Polasek, Wolfgang & Wago, Hajime, 2008. "Spatial interaction of crime incidents in Japan," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 78(2), pages 276-282.
    20. Lung-fei Lee, 2003. "Best Spatial Two-Stage Least Squares Estimators for a Spatial Autoregressive Model with Autoregressive Disturbances," Econometric Reviews, Taylor & Francis Journals, vol. 22(4), pages 307-335.
    21. Roy M. Howsen & Stephen B. Jarrell, 1987. "Some Determinants of Property Crime: Economic Factors Influence Criminal Behavior But Cannot Completely Explain the Syndrome," American Journal of Economics and Sociology, Wiley Blackwell, vol. 46(4), pages 445-457, October.
    22. Edward L. Glaeser & Bruce Sacerdote & José A. Scheinkman, 1996. "Crime and Social Interactions," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 111(2), pages 507-548.
    23. Lee, Lung-fei & Yu, Jihai, 2010. "Estimation of spatial autoregressive panel data models with fixed effects," Journal of Econometrics, Elsevier, vol. 154(2), pages 165-185, February.
    24. Cui, Lin & Walsh, Randall, 2015. "Foreclosure, vacancy and crime," Journal of Urban Economics, Elsevier, vol. 87(C), pages 72-84.
    25. Spelman, William, 1993. "Abandoned buildings: Magnets for crime?," Journal of Criminal Justice, Elsevier, vol. 21(5), pages 481-495.
    26. Lee, Lung-fei, 2007. "Identification and estimation of econometric models with group interactions, contextual factors and fixed effects," Journal of Econometrics, Elsevier, vol. 140(2), pages 333-374, October.
    27. Lung-Fei Lee, 2004. "Asymptotic Distributions of Quasi-Maximum Likelihood Estimators for Spatial Autoregressive Models," Econometrica, Econometric Society, vol. 72(6), pages 1899-1925, November.
    28. Menezes, Tatiane & Silveira-Neto, Raul & Monteiro, Circe & Ratton, José Luiz, 2013. "Spatial correlation between homicide rates and inequality: Evidence from urban neighborhoods," Economics Letters, Elsevier, vol. 120(1), pages 97-99.
    29. Parent, Olivier & LeSage, James P., 2012. "Spatial dynamic panel data models with random effects," Regional Science and Urban Economics, Elsevier, vol. 42(4), pages 727-738.
    30. Lee, Lung-fei, 2007. "GMM and 2SLS estimation of mixed regressive, spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 137(2), pages 489-514, April.
    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. Leiva, Mauricio & Vasquez-Lavín, Felipe & Ponce Oliva, Roberto D., 2020. "Do immigrants increase crime? Spatial analysis in a middle-income country," World Development, Elsevier, vol. 126(C).
    2. Manea, Roxana Elena & Piraino, Patrizio & Viarengo, Martina, 2023. "Crime, inequality and subsidized housing: Evidence from South Africa," World Development, Elsevier, vol. 168(C).
    3. Lee, Lung-fei & Yu, Jihai, 2010. "Some recent developments in spatial panel data models," Regional Science and Urban Economics, Elsevier, vol. 40(5), pages 255-271, September.
    4. Lastauskas, Povilas & Tatsi, Eirini, 2017. "Spatial Nexus in Crime and Unemployment in Times of Crisis," Working Paper Series 2/2017, Stockholm University, Swedish Institute for Social Research.
    5. Kwok, Hon Ho, 2019. "Identification and estimation of linear social interaction models," Journal of Econometrics, Elsevier, vol. 210(2), pages 434-458.
    6. Herrera Gómez, Marcos, 2017. "Fundamentos de Econometría Espacial Aplicada [Fundamentals of Applied Spatial Econometrics]," MPRA Paper 80871, University Library of Munich, Germany.
    7. Liu, Xiaodong & Patacchini, Eleonora & Zenou, Yves & Lee, Lung-Fei, 2011. "Criminal Networks: Who is the Key Player?," Research Papers in Economics 2011:7, Stockholm University, Department of Economics.
    8. Liu, Xiaodong & Lee, Lung-fei, 2010. "GMM estimation of social interaction models with centrality," Journal of Econometrics, Elsevier, vol. 159(1), pages 99-115, November.
    9. Lin, Xu & Lee, Lung-fei, 2010. "GMM estimation of spatial autoregressive models with unknown heteroskedasticity," Journal of Econometrics, Elsevier, vol. 157(1), pages 34-52, July.
    10. Liangjun Su & Xi Qu, 2017. "Specification Test for Spatial Autoregressive Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(4), pages 572-584, October.
    11. Kripfganz, Sebastian, 2014. "Unconditional Transformed Likelihood Estimation of Time-Space Dynamic Panel Data Models," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100604, Verein für Socialpolitik / German Economic Association.
    12. William C. Horrace & Hyunseok Jung & Shane Sanders, 2022. "Network Competition and Team Chemistry in the NBA," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(1), pages 35-49, January.
    13. Pesaran, M. Hashem & Tosetti, Elisa, 2011. "Large panels with common factors and spatial correlation," Journal of Econometrics, Elsevier, vol. 161(2), pages 182-202, April.
    14. Yang, Zhenlin, 2015. "A general method for third-order bias and variance corrections on a nonlinear estimator," Journal of Econometrics, Elsevier, vol. 186(1), pages 178-200.
    15. Bindler, Anna, 2016. "Still unemployed, what next? Crime and unemployment duration," Working Papers in Economics 660, University of Gothenburg, Department of Economics.
    16. Luc Anselin, 2010. "Thirty years of spatial econometrics," Papers in Regional Science, Wiley Blackwell, vol. 89(1), pages 3-25, March.
    17. Martellosio, Federico & Hillier, Grant, 2020. "Adjusted QMLE for the spatial autoregressive parameter," Journal of Econometrics, Elsevier, vol. 219(2), pages 488-506.
    18. O’Flaherty, Brendan & Sethi, Rajiv, 2015. "Urban Crime," Handbook of Regional and Urban Economics, in: Gilles Duranton & J. V. Henderson & William C. Strange (ed.), Handbook of Regional and Urban Economics, edition 1, volume 5, chapter 0, pages 1519-1621, Elsevier.
    19. Shew Fan Liu & Zhenlin Yang, 2015. "Asymptotic Distribution and Finite Sample Bias Correction of QML Estimators for Spatial Error Dependence Model," Econometrics, MDPI, vol. 3(2), pages 1-36, May.
    20. Kangoh Lee, 2018. "Unemployment and crime: the role of apprehension," European Journal of Law and Economics, Springer, vol. 45(1), pages 59-80, February.

    More about this item

    Keywords

    Spatial dynamic panel data model; Fixed effects; Crime; Spatial and temporal correlations;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • K49 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - Other
    • R19 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Other

    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:irlaec:v:72:y:2022:i:c:s0144818822000564. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/irle .

    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.