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Comparing apples to apples: an environmental criminology analysis of the effects of heat and rain on violent crimes in Boston

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  • Alice J. Sommer

    (Harvard University)

  • Mihye Lee

    (St. Luke’s Int’l University)

  • Marie-Abèle C. Bind

    (Harvard University)

Abstract

Weather characteristics have been suggested by many social scientists to influence criminality. According to a recent study, climate change may cause a substantial increase in criminal activities during the twenty-first century. The additional number of crimes due to climate have been estimated by associational models, which are not optimal to quantify causal impacts of weather conditions on criminality. Using the Rubin Causal Model and crime data reported daily between 2012 and 2017, this study examines whether changes in heat index, a proxy for apparent temperature, and rainfall occurrence, influence the number of violent crimes in Boston. On average, more crimes are reported on temperate days compared to extremely cold days, and on dry days compared to rainy days. However, no significant differences in the number of crimes between extremely hot days versus less warm days could be observed. The results suggest that weather forecasts could be integrated into crime prevention programs in Boston. The weather-crime relationship should be taken into account when assessing the economic, sociological, or medical impact of climate change. Researchers and policy makers interested in the effects of environmental exposures or policy interventions on crime should consider a causal inference approach to analyze their data.

Suggested Citation

  • Alice J. Sommer & Mihye Lee & Marie-Abèle C. Bind, 2018. "Comparing apples to apples: an environmental criminology analysis of the effects of heat and rain on violent crimes in Boston," Palgrave Communications, Palgrave Macmillan, vol. 4(1), pages 1-10, December.
    • Handle: RePEc:pal:palcom:v:4:y:2018:i:1:d:10.1057_s41599-018-0188-3
    DOI: 10.1057/s41599-018-0188-3
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    References listed on IDEAS

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    1. Ranson, Matthew, 2014. "Crime, weather, and climate change," Journal of Environmental Economics and Management, Elsevier, vol. 67(3), pages 274-302.
    2. Dennis Mares & Kenneth Moffett, 2016. "Climate change and interpersonal violence: a “global” estimate and regional inequities," Climatic Change, Springer, vol. 135(2), pages 297-310, March.
    3. Dennis M. Mares & Kenneth W. Moffett, 2016. "Climate change and interpersonal violence: a “global” estimate and regional inequities," Climatic Change, Springer, vol. 135(2), pages 297-310, March.
    4. James J. Heckman & Hidehiko Ichimura & Petra Todd, 1998. "Matching As An Econometric Evaluation Estimator," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(2), pages 261-294.
    5. Imbens,Guido W. & Rubin,Donald B., 2015. "Causal Inference for Statistics, Social, and Biomedical Sciences," Cambridge Books, Cambridge University Press, number 9780521885881, January.
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    Cited by:

    1. Ujjal Kumar Mukherjee & Benjamin E. Bagozzi & Snigdhansu Chatterjee, 2023. "A Bayesian framework for studying climate anomalies and social conflicts," Environmetrics, John Wiley & Sons, Ltd., vol. 34(2), March.
    2. Vanessa Azevedo & Mariana Magalhães & Daniela Paulo & Rui Leandro Maia & Gisela M. Oliveira & Maria Simas Guerreiro & Ana Isabel Sani & Laura M. Nunes, 2021. "Temporal Variability of Theft Types in the Historic Centre of Porto," Social Sciences, MDPI, vol. 10(10), pages 1-12, October.
    3. Kimpton, Anthony & Loginova, Julia & Pojani, Dorina & Bean, Richard & Sigler, Thomas & Corcoran, Jonathan, 2022. "Weather to scoot? How weather shapes shared e-scooter ridership patterns," Journal of Transport Geography, Elsevier, vol. 104(C).

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