Perception of Crime and Actual Data: A Spatial and Temporal Analysis of Crime in Chicago
Abstract
There is an increasing level of concern about crime and violence in most countries, especially in urban areas. However, data on crime rates have been in a decreasing trend in most countries, especially in the USA. The goal of this paper is to study of the prevalence of violent crimes in Chicago, their spatial neighborhood dependence structure and effect of laws and police enforcement on the rates of crime through time. We analyze thousands of registered cases between 2003 and 2017. In contrast with perceived crime in America, time series data analysis using ARMA models demonstrated that the rates of most violent crimes in Chicago have been decreasing steadily since 2003, and are much lower compared to the beginning of the millennium. The only exception is aggravated assault, which presented a slight increase in the past couple years.
References
Alonso, A., Sipols, A. E. G., and de Blas, C. S. (2018). Forecasting nancial short time
series. Electronic Journal of Applied Statistical Analysis, 11:42-57.
Austin, D. M., Furr, L. A., and Spine, M. (2002). The eeffects of neighborhood conditions
on perceptions of safety. Journal of Criminal Justice, 30:417-427.
Baumer, E. and Wol, K. (2014). Evaluating contemporary crime drop(s) in america,
new york city, and many other places. Justice Quarterly, 31:5-38.
Bernini, C., Matteucci, M., and Mignani, S. (2015). A bayesian multidimensional irt
approach for the analysis of residents' perceptions toward tourism. Electronic Journal
of Applied Statistical Analysis, 8:272-287.
Bivand, R. S., Pebesma, E. J., and Gomez-Rubio, V. (2008). Applied spatial data
analysis with r. Second Edition. Springer.
Blumstein, A. and Rosenfeld, R. (2008). 2 factors contributing to u.s. crime trends.
Understanding Crime Trends: Workshop Report, pages 13-44.
Box, G. E. P. and Tiao, G. C. (1975). Intervention analysis with applications to economic
and environmental problems. Journal of the American Statistical Association, 70:70-79.
Callanan, V. J. (2012). Media consumption, perceptions of crime risk and fear of crime:
Examining race/ethic dierences. Sociological Perspectives, 55:93-115.
Cantor, D. and Land, K. C. (2001). Unemployment and crime rate
fluctuations: A
comment on greenberg. Journal of Quantitative Criminology, 17:329-342.
Chandra, K. S. and Prabakaran, S. (2019). Forecasting an explosive time series. Electronic Journal of Applied Statistical Analysis, 12:674-35.
de Smith, M. J. (2015). Car models. statistical analysis handbook. Available at
http://www.statsref.com/HTML/index.html?car models.html.
Dowler, K. (2003). Media consumption and public attitudes toward crime and justice:
the relationship between fear of crime, punitive attitudes, and perceived police eeffectiveness. Journal of Criminal Justice and Popular Culture, 10:109-126.
el Mezouar, Z. C. and Attouch, M. (2012). Using iterative linear regression model to
time series models. Electronic Journal of Applied Statistical Analysis, 5:137-150.
Engelhardt, B. (2010). The effect of employment frictions on crime. Journal of Labor
Economics, 28:677-718.
Fallahi, F. and Rodriguez, G. (2014). Link between unemployment and crime in the u.s.:
A markov-switching approach. Social Science Research, 45:33-45.
Field, S. (1992). The effect of temperature on crime. British Journal of Criminology,
:340-351.
Forde, D. (1993). Perceived crime, fear of crime, and walking alone at night. Psychological
Reports, 73:403-407.
Gottfredson, M. R. (1986). Substantive contributions of victimization surveys. Crime
and Justice, 7:251-287.
Greenberg, D. F. (2001). Time series analysis of crime rates. Journal of Quantitative
Criminology, 17:291-327.
Hamilton, J. D. (1994). Time series analysis. Princeton University Press., first edition.
Hartley, C. C. and Frohmann, L. (2003). Cook county target abuser call (tac): An
evaluation of a specialized domestic violence court, revised final report. Available at
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.140.28&rep=rep1&type=pdf.
Hipp, J. R. (2010). Resident perceptions of crime: How much is bias and how much is
micro-neighborhood effects? Criminology, 48:475-508.
Hipp, J. R. (2013). Assessing crime as a problem: The relationship between resident's
perception of crime and official crime rates over 25 years. Crime and Delinquency,
:616-648.
Kirk, D. S. and Laub, J. H. (2010). Neighborhood change and crime in the modern
metropolis. Crime and Justice, 39:441-502.
Landau, S. F. and Fridman, D. (1993). The seasonality of violent crime: The case
of robbery and homicide in israel. Journal of Research in Crime and Delinquency,
:163-191.
Lin, M. (2008). Does unemployment increase crime? evidence from u.s. date 1974-2000.
The Journal of Human Resources, 43:413-436.
Linden, L. and Rocko, J. (2008). Estimates of the impact of crime risk on property
values from megan's laws. American Economic Review, 98:1103-1127.
Ljung, G. M. and Box, G. E. P. (1978). On a measure of a lack of t in time series
models. Biometrika, 65:297-303.
Loftin, C., Heumann, M., and McDowall, D. (1983). Mandatory sentencing and rearms
violence: evaluating an alternative to gun control. Law and Society Review, 17:287-318.
Lott, J. R., J. and Mustard, D. B. (1997). Crime, deterrence, and right-to-carry concealed
handguns. The Journal of Legal Studies, 26:1-68.
Mahdi, E., Provost, S. B., Salha, R. B., and Nashwan, I. I. H. (2017). Multivariate time
series modeling of monthly rainfall amounts. Electronic Journal of Applied Statistical
Analysis, 10:65-81.
Mauro, L. and Carmeci, G. (2007). A poverty trap of crime and unemployment. Review
of Development Economics, 11:450-462.
McCleary, R. and Hay, R. J. (1980). Applied time series analysis for the social sciences.
Sage, Beverly Hills.
McDowall, D., Loftin, C., and Wiersema, B. (1995). Easing concealed rearm laws:
Effects on homicide in three states. Journal of Criminal Law and Criminology, 86:193-206.
Pope, D. G. and Pope, J. C. (2012). Crime and property values: Evidence from the
s crime drop. Regional Science and Urban Economics, 42:177-188.
Prescott, J. and Rocko, J. E. (2011). Do sex oender registration and notication laws
affect criminal behavior? Journal of Law and Economics, 54:161-206.
Saunders, J., Hunt, P., and Hollywood, J. (2016). Predictions put into practice: a quasi-experimental evaluation of chicago's predictive policing pilot. J. Exp. Criminology,
:347-371.
Shumway, R. H. and Stoer, D. S. (2015). Time series analysis and it's applications with r examples. Springer Texts in Statistics.
Sindall, K., Sturgis, P., and Jennings, W. (2012). Public confidence in police: A time
series analysis. British Journal of Criminology, 52:744-764.
Socia, K. and Harris, A. (2016). Evaluating public perceptions of the risk presented
by registered sex oenders: Evidence of crime control theater? Psychology, Public
Policy, and Law, 22:375-385.
Soh, A.-N., Puah, C.-H., and Arip, M.-A. (2019). Construction of tourism cycle indicator:
a signalling tool for tourism market dynamics. Electronic Journal of Applied Statistical
Analysis, 12:477-490.
Tompson, L. and Bowers, K. (2012). A stab in the dark?: A research note on temporal
patterns of street robbery. Journal of Research in Crime and Delinquency, 50:616-631.
Vogel, M. and South, S. J. (2016). Spatial dimensions on the effect of neighborhood
disadvantage on delinquency. Criminology, 54:434-458.
Wallace, D. (2015). Do neighborhood organizational resources impact recidivism? Sociological Inquiry, 85:285-308.
Warner, T. D. and Kramer, J. H. (2009). Closing the revolving door?: Substance abuse
treatment as an alternative to traditional sentencing for drug-dependent oenders.
Criminal Justice and Behavior, 36:89-109.
Full Text: pdf