Crime, particularly violent crime, has been shown to impose a variety of economic costs on individuals, communities, and society as a whole. These costs include increased health care costs (Howell et al., 2014; Miller et al., 1993), costs associated with lost productivity (Cook et al., 1999), costs associated with police, courts, and correctional institutions (Cook & Ludwig, 2000; Shapiro & Hassett, 2012), reduced property values (Hipp et al., 2009; Irvin-Erickson, Lynch, et al., 2017; Kirk & Laub, 2010; Lynch & Rasmussen, 2001; Shapiro & Hassett, 2012; Tita et al., 2006), lost time from work (Cook & Ludwig, 2000; Perkins et al., 1996), and costs associated with victims’ efforts to avoid revictimization such as relocation of victims (Dugan, 1999).
Noticeably absent from the literature on the economic impacts of crime is the impact of gun violence on local businesses. This is partially due to the lack of available micro-geographical level data sources on business activity until very recently. The scarcity of research on this topic is also in line with the omission of businesses from studies on the impact of crime on neighborhoods, despite the importance of local business activity as an indicator of the local economy and of the quality of life for residents, non-residents, and investors (Fisher, 1991; Skogan, 1986). This omission is surprising considering that the lack of legitimate local jobs for youth, and especially minority youth, has been shown to increase the likelihood that these youth engage in criminal activity (Ihlanfeldt, 2002). Furthermore, economic development efforts within Business Improvement Districts have been shown to be related to reductions in community-level incidences of interpersonal violence, which is largely experienced by youth and young adults (MacDonald et al., 2009).
Business revenues can be affected by gun violence through a variety of mechanisms. People have been shown to be afraid of places where they know violent crimes happen or where they perceive that they have a high likelihood of victimization from violent crime (see Fisher, 1991 and Skogan, 2012 for a detailed discussion) and this can affect business revenues. Although the research on the impacts of fear of crime on individuals’ behavior and routine activities is somewhat inconsistent, it nonetheless suggests that some individuals may alter their routine activities and constrain their outdoor activity in response to increased perceived risk of crime (see Foster et al., 2014; Foster & Giles-Corti, 2008; Irvin-Erickson, Lynch, et al., 2017b; Liska et al., 1988; Lorenc et al., 2012; Markowitz et al., 2001; Mesch, 2000; Oh & Kim, 2009; Otis, 2007; Ross, 1993; Skogan & Maxfield, 1981; Stafford et al., 2007). However, it is important to note that individuals’ perceptions of social disorder can moderate the relationship between perceived risk and routine activities (Rengifo & Bolton, 2012). Rengifo and Bolton (2012) found that individuals who perceive a higher level risk of victimization and a lower level of disorder engage in significantly more voluntary activities in comparison to individuals who perceive a higher level risk of victimization and a higher level of disorder. Wesley Skogan (1986; 2012) also provides context into the relationship between social disorder on fear of crime. According to Skogan (1986; 2012), disorder can independently, but in parallel with crimes in communities, increase fear of crime and discourage investments in neighborhoods. On the topic of business patronage, Skogan (1986; 2012) and other authors (Bowes, 2007; Fisher, 1991) suggest that crime and fear of crime can reduce business revenues due to residents in high-crime neighborhoods limiting their activities and not patronizing businesses. Unsurprisingly, when business revenues are reduced, there are fewer jobs at businesses for local residents (Hamermesh, 1999; Levi, 2001).
Business owners can also change business operations and business decisions in response to crime (Bowes, 2007; Fisher, 1991; Hamermesh, 1989, 1999; Levi, 2001; Skogan, 1986; 2012). Businesses have been shown to be negatively impacted by reduced business hours, difficulty hiring employees or having employees work at undesirable evening and night business hours, and increased insurance costs due to crime. For instance, a study by Fisher (1991), based on interviews with business owners in the Hilltop Community in Columbus, Ohio, demonstrated business owners’ difficulty in hiring or retaining employees who are worried about working in an environment where they perceive that they are likely to be victimized. The same study showed further harmful impacts of crime on business operations such as reduced business hours and increased business insurance costs (Fisher, 1991). Another study by Hamermesh (1989), linking Current Population Survey (CPS) data to FBI crime reports, studied time use as a nonmonetary cost of time and found that higher homicide rates in large metropolitan areas are related to a lower propensity of workers to work evenings and nights. Other studies further showcase that crime and the fear of crime can be related to decreased business investment (such as the opening of new businesses or the expansion of existing businesses) in areas with a reputation as high-crime areas (Bowes, 2007; Fisher, 1991; Skogan, 1986; 2012).
The aforementioned studies on the economic impacts of crime, along with the wider literature on the impact of crime and fear of crime on routine activities, suggest that local businesses may have difficulty attracting customers, attracting and retaining employees, or maintaining regular hours in response to heightened gun violence. To the best of our knowledge, only three studies have estimated the impact of violent crime on local businesses using business data. Rosenthal and Ross (2010) estimated the impact of violent crime on the location of businesses in Atlanta, Chicago, Houston, Indianapolis, and Seattle at the Census tract level via a cross-sectional study. The authors used two datasets for their analysis: reported crime data from local police agencies and business activity data from Dunn and Bradstreet, a for-profit firm. According to this study, an increase in violent crime during prime dinner hours (5 pm to 9 pm) reduced the presence of high-end restaurants by roughly 40 percentage points when considering the spread of minimum and maximum number of violent crimes in Census tracts observed in the study period. In this study, restaurants are defined as high-end “if they have 1–24 employees and sales are greater than $0.5 million, 25–49 employees and sales are greater than $1.0 million, or 50–99 employees and sales are greater than $2.5 million” (Rosenthal & Ross, 2010, p. 142).
In addition to Rosenthal and Ross (2010) cross-sectional study, only two longitudinal studies have been conducted on the effects of violent crime on local business. Greenbaum and Tita (2004) used longitudinal business and homicide data at the ZIP code level to explore the impact of homicide surges on the creation, closing, and growth of businesses in Chicago, Houston, Miami, Pittsburgh, and St. Louis between 1987 and 1994. The authors found that local increases in lethal violence caused existing businesses to downsize and led to fewer new businesses forming. These effects were concentrated in ZIP codes where homicides were less frequent, suggesting that surges in violence in neighborhoods that already have high levels of violence may not increase the perceived risk of violence to the point of affecting business activity. The study also found that established businesses were less affected, as surges in violence had no significant impact on prompting business closures. Finally, the impact of homicide crime was greatest among personal service and retail businesses, indicating that jobs relying on face-to-face interaction between employees and customers may be most susceptible to the effects of increased violent crime (Greenbaum & Tita, 2004).
Irvin-Erickson, Lynch, et al. (2017) estimated the impact of a sudden increase in gun homicides and gunshots on local business growth, home values, homeownership rates, and credit scores in five US cities at the Census tract level. The authors found that gun homicide surges in Census tracts reduced the growth rate of new retail and service establishments by 4% in Minneapolis, Oakland, San Francisco, and Washington, DC. The same study also found that gun homicide surges in Census tracts slowed home value appreciation by 3.9% in Baton Rouge, Minneapolis, Oakland, San Francisco, and Washington, DC. Similarly, the authors found that gunshot surges in Census tracts slowed home value appreciation by 3.6% in Oakland, Rochester, San Francisco, and Washington, DC.
We expand upon these previous studies by estimating the relationship between detected gunshots and business births, deaths, sales, and number of employees at the Census block level using data from the National Establishment Time Series Database and ShotSpotter, a gunshot detection system. While we acknowledge that gunshot detection technology has its own limitations in detecting gunshots at certain times of the day and the year and at a farther distance from acoustic sensors, data from gunshot detection technology has been shown as a valuable new data source on gun violence in the recent literature (Irvin-Erickson, La Vigne, et al., 2017a). In our study, the availability of data directly from gunshot detection technology allows us to measure the impact of actual gunshots on businesses, rather than the impact of reported gunshots on businesses, in which overreporting or underreporting are likely endogenous to neighborhood characteristics and business activity.