The spatiotemporal dynamics and structural covariates of homicide in the Republic of Korea, 2008-2017: A dynamic spatial panel data approach

Submitted: 21 July 2021
Accepted: 10 December 2021
Published: 9 May 2022
Abstract Views: 650
PDF: 344
HTML: 21
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Authors

This study examined the relationship between the homicide rate and diverse indicators of social disorganization in the Republic of Korea (South Korea) using datasets collected between 2008 and 2017. Due to the statistical limitations of previous homicide research, which used either cross-sectional or longitudinal methodology, this study applied the dynamic spatial panel data model to explore both the spatial and temporal aspects of homicide. The results demonstrate that the homicide rate is spatially and temporally dependent on those of neighbouring units and the time-lagged homicide rate. Moreover, this study found that divorce rate, unemployment rate, number of males in the neighbourhood and ethnic heterogeneity have a statistically significant impact on the homicide phenomenon. This study contributes to the existing literature by taking a new approach - the dynamic spatial panel data model - to investigate the homicide phenomenon in Korea. In doing so, several suggestions are made for policymakers to respond to homicide rates. Based on the social disorganization theory, these indicators have been found to impact the social network and community members' willingness to engage in social control. This study suggests that customized policies should be implemented to alleviate the level of social disorganization and promote social control over lethal violence.

Dimensions

Altmetric

PlumX Metrics

Downloads

Download data is not yet available.

Citations

Akers RL, 2013. Criminological theories: introduction and evaluation. Chicago, IL, USA: Fitzroy Dearborn Publishers.
Baller RD, Shin DJ, Richardson KK, 2005. An extension and test of Sutherland’s concept of differential social disorganization: The geographic clustering of Japanese suicide and homicide rates. Suicide Life Threat Behav 35:343-55. DOI: https://doi.org/10.1521/suli.2005.35.3.343
Baltagi BH, Blien U, Wolf K, 2012. A dynamic spatial panel data approach to the German wage curve. Econ Model 29:12-21. DOI: https://doi.org/10.1016/j.econmod.2010.08.019
Belotti F, Hughes G, Mortari AP, 2016. Spatial panel data models using Stata. Stata J 17:139-80. DOI: https://doi.org/10.1177/1536867X1701700109
Breuer C, 2015. Unemployment and suicide mortality: Evidence from regional panel data in Europe. Health Econ 24:936-50. DOI: https://doi.org/10.1002/hec.3073
Bussu A, Detotto C, Sterzi V, 2013. Social conformity and suicide. J Soc Econ 42:67-78. DOI: https://doi.org/10.1016/j.socec.2012.11.013
Cohen J, Tita G, 1999. Diffusion in homicide: Exploring a general method for detecting spatial diffusion process. J Quant Criminol 15:451-93. DOI: https://doi.org/10.1023/A:1007596225550
Feldmeyer B, 2009. Immigration and violence: The offsetting effects of immigrant concentration on Latino violence. Soc Sci Res 38:717-31. DOI: https://doi.org/10.1016/j.ssresearch.2009.03.003
Graif C, Sampson RJ, 2009. Spatial heterogeneity in the effects of immigration and diversity on neighborhood homicide rates. Homicide Stud 13:242-60. DOI: https://doi.org/10.1177/1088767909336728
Joo Y, 2017. Spatiotemporal study of elderly suicide in Korea by age cohort. Public Health 142:144-51. DOI: https://doi.org/10.1016/j.puhe.2016.07.016
Kong D, Yoon K, Yu S, 2010. The social dimensions of immigration in Korea. J Contemp Asia 40:252-74. DOI: https://doi.org/10.1080/00472331003600473
Korea Citation Index, 2020. Article search. Available from: https://www.kci.go.kr/kciportal/po/search/poArtiSear.kci
KOSIS, 2020. Suicide Statistics. Available from: http://kosis.kr/
Mancik AM, Parker KF, Williams KR, 2018, Neighborhood context and homicide clearance: Estimating the effects of collective efficacy. Homicide Stud 22:88-213. DOI: https://doi.org/10.1177/1088767918755419
McCall PL, Land KC, Parker KF, 2010. An empirical assessment of what we know about structural covariates of homicide rate: a return to a classic 20 years later. Homicide Stud 14:219-43. DOI: https://doi.org/10.1177/1088767910371166
Lizzi EAS, Garrido MVG, Xavier LDS, Moraes GP, 2021. Homicides of black people in Brazil: A study of different regions, using generalized additive regression models-with a geo-spatial component. Geospat Health 16:966-75. DOI: https://doi.org/10.4081/gh.2021.966
Menezes T, Silveira-Neto R, Monteiro C, Ratton JL, 2013. Spatial correlation between homicide rates and inequality: Evidence from urban neighborhoods. Econ Lett 120:97-9. DOI: https://doi.org/10.1016/j.econlet.2013.03.040
Nivette AE, 2011. Cross-national predictors of crime: A meta-analysis. Homicide Stud 15:103-31. DOI: https://doi.org/10.1177/1088767911406397
Ousey GC, Kubrin CE, 2014. Immigration and the changing nature of homicide in US cities, 1980-2010. J Quant Criminol 30:453-83. DOI: https://doi.org/10.1007/s10940-013-9210-5
Pereira DVS, Mota CMM, Andresen MA, 2015. Social disorganization and homicide in Recife, Brazil. Int J Offender Ther Comp Criminol 61:1570-92. DOI: https://doi.org/10.1177/0306624X15623282
Phillips JA, 2006. Explaining discrepant findings in cross-sectional and longitudinal analyses: An application to U.S. homicide rates. Soc Sci Res 35:948-74. DOI: https://doi.org/10.1016/j.ssresearch.2005.07.002
Porter JR, Purser CW, 2010. Social disorganization, marriage, and reported crime: A spatial econometrics examination of family formation and criminal offending. J Crim Justice 38:942-50. DOI: https://doi.org/10.1016/j.jcrimjus.2010.06.011
Pridemore WA, 2002. What we know about social structure and homicide: A review of the theoretical and empirical literature. Violence Vict 17:127-56. DOI: https://doi.org/10.1891/vivi.17.2.127.33651
Ruther M, 2013. The effect of growth in foreign born population share on county homicide rates: A spatial panel approach. Violence Vict 93:1-23. DOI: https://doi.org/10.1111/pirs.12045
Sampson RJ, 2013. The place of context: A theory and strategy for criminology’s hard problems. Criminol 51:1-31. DOI: https://doi.org/10.1111/1745-9125.12002
Sampson RJ, 2011. Great American city: Chicago and the enduring neighborhood effect. Chicago, IL, USA: University of Chicago Press. DOI: https://doi.org/10.7208/chicago/9780226733883.001.0001
Sampson RJ, Groves WB, 1989. Community structure and crime: Testing social-disorganization theory. Am J Sociol 94:774-802. DOI: https://doi.org/10.1086/229068
Sampson RJ, Raudenbush SW, Earls F, 1997. Neighborhoods and violent crime: A multilevel study of collective efficacy. Science 277:918-24. DOI: https://doi.org/10.1126/science.277.5328.918
World Bank, 2019. Republic of Korea Data. Available from: https://data.worldbank.org/country/korea-rep
Wang F, Arnold MT, 2008. Localized income inequality, concentrated disadvantage and homicide. Appl Geogr 28:259-70. DOI: https://doi.org/10.1016/j.apgeog.2008.07.004
Ye X, Wu L, 2011. Analyzing the dynamics of homicide patterns in Chicago: ESDA and spatial panel approaches. Appl Geogr 31:800-7. DOI: https://doi.org/10.1016/j.apgeog.2010.08.006
Yeom Y, 2021. Analyzing the spatial and temporal dynamics of suicide in South Korea: An application of dynamic spatial panel data model. Geospat Health 16:964-71. DOI: https://doi.org/10.4081/gh.2021.964

How to Cite

Yeom, Y., & Choi, J. (2022). The spatiotemporal dynamics and structural covariates of homicide in the Republic of Korea, 2008-2017: A dynamic spatial panel data approach. Geospatial Health, 17(1). https://doi.org/10.4081/gh.2022.1040