Abstract
Objectives
This study draws on an underused source of data on seasonality—victim surveys—to assess whether violent crime occurs with greater frequency during summer months or whether it simply becomes known to police more often, and to examine the extent to which seasonal patterns in violent crime are differentiated based on victim characteristics and location of crime.
Methods
Data used come from the 1993–2008 National Crime Victimization Survey. Time series regression models are estimated to describe seasonal differences in violent crime victimization and reporting rates.
Results
Seasonal trends in youth violence stand in contrast to the trends for young and older adults, primarily due to their high risk of victimization at and near school. No evidence of seasonality is found in the extent to which serious violence becomes known to the police. However, simple assault is significantly more likely to come to the attention of the police during the summer months, primarily due to increases in the reporting of youth violence.
Conclusions
Our findings confirm some of the previous work on seasonal patterns in violent crime, but also show that these patterns vary across age groups, locations, and type of violence.
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Notes
Property crime may also vary according to seasons. However, there appear to be contradictory arguments and findings as to when property crime rates are highest. Scholars such as Quetelet (1831/1984), Lombroso (1911) and Falk (1952) initially suggested that property crime should increase in winter, due to a scarcity of goods. More recent work by Farrell and Pease (1994) finds support for this. On the other hand, others suggest that property crime should peak in summer months when residences are more likely to be left unoccupied and personal belongings are more often left outside and unattended (see Cohn 1990; Yan 2004).
Hipp et al. (2004) recognize this problem and drop from their analyses data from police departments that appear to report crime inconsistently (e.g., only in December). In their analyses, McDowall et al. (2012) rely on a dataset assembled by Maltz (n.d.) which flagged months with missing, aggregated or questionable entries.
Personal email communication from the Criminal Justice Information Services at the FBI, August 9, 2010 stated that “The Uniform Crime Reporting Program no longer creates tables for monthly variations.” Monthly tables are available by special request, however in such tables “agencies that did not provide monthly totals were removed from the calculations.”
In his analyses, Dodge (1988) classifies crimes as highly seasonal (i.e., a deviation of at least 20 % above or below the overall average), moderately seasonal (a deviation averaging between 15 and 20 % from the mean), and demonstrating little or no seasonality (a deviation of less than 15 % from the average).
While the overall shape of the relation remains in question (i.e., whether it is linear, J-shaped, U-shaped, or some other possibility), the theory specifically posits a direct relationship. In other words, it suggests that temperature acts at the level of the individual (Anderson 1989, p. 75).
We use NCVS data made available through the National Archive of Criminal Justice Data at ICPSR (datasets 4699, 24644, 25141, 26382, and 28543): http://www.icpsr.umich.edu/icpsrweb/NACJD/NCVS/.
Because we define incidents that occur in December, January, and February as “winter” incidents, the data include incidents from December, 1992 through November, 2008.
Incidents reported to have occurred outside of the US are excluded from these analyses. “Series” incidents (victimizations that occur more than six times and for which the respondent is unable to provide details about each incident) are included but counted as one incident, and the month of the most recent incident is used to date the event. This decision was made because the data lack information about the month of occurrence of other events classified as part of the series victimization.
For example, one-sixth of the sample is contacted in early January to report about incidents for the previous July–December period, and these households are subsequently interviewed in early July to report on incidents for the January–June period. Another one-sixth of the sample is contacted in early February to report about their experiences for the previous August to January period and they are subsequently re-interviewed in early August; and so on.
Details about the exact day of the month on which the incident occurred are not obtained during the interview.
We examine tri-monthly periods for a number of reasons. First, because of the relative rarity of violent victimization, the estimates become increasingly unstable when using smaller temporal windows (i.e., examining monthly or even bi-monthly rates), particularly when further disaggregated by age of victim or location of the incident. Second, this definition of seasons most closely matches the social definition of seasons in the United States, allowing us to empirically examine the presumed summer peaks and winter troughs in violence. Finally, defining seasons in this manner corresponds with the annual school calendar; the June–August season in the United States is generally the period of time in which students are not attending school.
The rates are derived from an average of 43,439 interviews per season. The average number of interviews with persons 12–17, 18–24, and 25 above is 4,541, 4,423, and 34,475, respectively. It should also be noted that because of temporary changes in the administration of the survey, NCVS data for the year 2006 have been referred to as a “break-in-series” and thus not directly comparable with data from 2005 or 2007 (Rand 2008). We re-estimated all of our models with and without data from the year 2006 and the results were essentially the same, suggesting that even though data for 2006 produced some unusual annual rates, the seasonality in those rates maintained patterns that were consistent with other years. Visual inspection of the seasonal rate estimates confirms this as well.
For example, if the change in the population between 2 years was +6 %, then the interpolated population values would increase .5 % each month.
These percentages are obtained by comparing the coefficient for each season against the estimated summer rate (i.e., the constant). For example, −.33/5.56 × 100 = −6 % describes the average percent difference between winter and summer rates of serious violence.
In the first-difference model for simple assault, the spring coefficient is positive and significant, and approximately half the size of the fall coefficient.
The apparently greater difference between the observed and predicted rates in 2006 is related to the ‘break-in-series’ issue, discussed in note 12.
When Newey-West standard errors are used to assess significance, the fall coefficient is significant at p = .07 (two-tail test). For serious violence among youth, the series is stationary only in first differences, suggesting that the winter rates are probably significantly higher than the summer rates.
Each of the series reported in Table 3 is stationary in both levels and first-differences. The results based on Newey-West standard errors are similar, though the spring-summer difference in percent total violence reported is significant at p = .06 (two-tail test).
Length of residence has been shown to be negatively related to neighborhood violence risk: Net of other individual- and neighborhood-level factors, youth who have lived in their neighborhoods for shorter periods of time are more likely to be victims of violent crime (Lauritsen 2003).
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The authors would like to thank the editors and reviewers and Richard Rosenfeld for their useful comments and suggestions.
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Kristin Carbone-Lopez and Janet Lauritsen contributed equally to the manuscript.
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Carbone-Lopez, K., Lauritsen, J. Seasonal Variation in Violent Victimization: Opportunity and the Annual Rhythm of the School Calendar. J Quant Criminol 29, 399–422 (2013). https://doi.org/10.1007/s10940-012-9184-8
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DOI: https://doi.org/10.1007/s10940-012-9184-8