Exploring the correlation between temperature and crime:A case-crossover study of eight cities in America

作     者：Jinming Hu Xiaofeng Hu Xin’ge Han Yan Lin Huanggang Wu Bing Shen 

作者机构：School of Information Technology and Cyber SecurityPeople’s Public Security University of ChinaBeijing 100038China Center for Capital Social SafetyPeople’s Public Security University of ChinaBeijing 100038China China Association for Public SafetyBeijing 100084China School of Emergency Management and Safety EngineeringChina University of Mining and TechnologyBeijing 100083China School of International Police StudiesPeople’s Public Security University of ChinaBeijing 100038China 

出 版 物：《Journal of Safety Science and Resilience》 (安全科学与韧性（英文）)

年 卷 期：2024年第5卷第1期

页      面：13-36页

核心收录：

学科分类：03[法学] 1004[医学-公共卫生与预防医学(可授医学、理学学位)] 0306[法学-公安学] 

基　　金：support for this study by the National Natural Science Foundation of China(Grant No.72174203 No.41971367). 

主　　题：Time series decomposition Crime Temperature Kalman filter Fast fourier transform 

摘      要：Recent years have seen increasing academic interest in exploring the correlation between temperature and crime.However,it is uncertain whether similar long-term trends or seasonality(rather than causal effect)of temper-ature and crime is the major reason for the observed correlation between them.To explore whether there is still a correlation between temperature and crime when long-term trends and seasonal cycles are filtered out,we use the Kalman filter to decompose the time series of temperature and crimes,and then the fast Fourier transform is used to calculate the exact circle of their seasonality separately.Based on that,the box-plot method and linear regression are used to explore the correlation between temperature residuals and crime residuals.The results show that more than half of the crime types have similar seasonal cycles(approximately 1 year)to that of temperature.Moreover,the daily residual analyses show that temperature residuals have a positive correlation with assault and robbery residuals in all cities,whose average slopes are more than 0.1.The other four types of crimes vary greatly from case to case.The temperature residuals show a weak correlation with the residuals of some crime types.