The Influence of Gun Ownership and State Gun Laws on Citizen Justifiable Homicides in Large U.S. Cities

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We perform the first fixed-effects city level analysis of this homicide outcome. We find gun ownership measured by a proxy, firearm suicide rate, to be a positive and significant predictor for justifiable homicides. State gun laws are also assessed including Stand Your Ground, Conceal Carry Weapon, Permit to Purchase, and Universal Background Check laws. All four state gun laws are significantly associated with justifiable homicides. Finally, we disaggregate justifiable homicides by race of the victim and find differences in predictors for Black Victim and White Victim justifiable homicides. Introduction From 2000 to 2010, the U.S. experienced a rise in protections for citizen self-defense including the use of deadly force without criminal sanction, with 26 states enacting castle doctrine expansions and 18 states passing a Stand Your Ground (SYG) law during this period (1). Castle doctrine laws originate from English common laws that specify that a person has no duty to retreat beyond their own castle walls (2). For decades, virtually all states have allowed for deadly force to be used by citizens with no duty to retreat inside a person’s own home (3). Stand Your Ground laws extend the no duty to retreat clause of castle doctrine outside of the home and to ‘any place where a person has a legal right to be’ (1). This is a rather substantial expansion to the circumstances where a citizen can use deadly force without fear of prosecution and may explain why citizen justifiable homicides increased from 2000 to 2010. From this study’s analysis sample of 167 large U.S. cities, we find the mean number of citizen justifiable homicides increased from a 3-year sum of 4.77 for 2001-2003 to 4.85 for 2011-2013. While this increase is small, it reverses a downward trend since 1980 for this homicide outcome and is in contrast to downward trends observed for both police justifiable homicides and total homicides over this same time period in our sample. In addition to SYG laws, the U.S. has enacted Conceal Carry Weapon (CCW) laws that allow citizens to carry guns in public. In 1980, only 4 states had these laws compared to 38 states in 2010 (4). State level studies report the positive effect SYG and CCW laws have on total and justifiable homicides (1, 2, 4). One study finds the passage of a state SYG law results in an 8-10% increase in total homicides and while this increase is not solely attributable to an increase in citizen justifiable homicides, they are also drastically increased by between 28-57% depending on model specification (2). While the link between SYG and CCW laws and justifiable homicides has been established at the state level, there is limited research on how these laws trickle down to the city level. Laws that restrict access to firearms have also received less attention for justifiable homicides. We investigate the influence of four state gun laws on justifiable homicides including SYG, CCW, and two restrictive gun laws Permit to Purchase and Universal Background Check. Our analysis sample consists of 167 large U.S. cities, which allows us to control for several community level factors that have not been previously assessed including racial segregation and gun ownership measured by a proxy, firearm suicide rate. The majority of past studies on justifiable homicides at the city level have either been descriptive or confined to one jurisdiction, which makes them unable to identify community level influencers (5-8). This research generally finds that the victims of justifiable homicides are disproportionately Black males (5, 6, 8). In one study that examines justifiable homicides from 2005-2010 using FBI Supplementary Homicide Reports (SHR) data, the authors find when considering all homicides, White on Black homicides are the most likely to be ruled justified (11.4%) (8). The least likely to be ruled justified is Black on White homicides (1.2%) and this observed racial disparity is exacerbated in SYG law states (16.85% vs. 1.4%). The study also notes that overall, 2.57% of all homicides are ruled justified and in SYG law states this percentage rises to 3.67% (8). Finally, justifiable homicides are more likely to be committed by a firearm than criminal homicides (5-7, 9). One descriptive study reports 88% of justifiable homicides involve the use of a firearm compared to 59% of criminal homicides (9). These descriptive studies are informative, but they do not consider how macro level factors, such as crime rates or gun ownership rates, may influence justifiable homicides committed by citizens. The only previous study to assess the determinants of justifiable homicides at the city level across multiple jurisdictions did so on a sample of 188 large U.S. cities using a five-year sum of justifiable homicides from 1990 to 1994 using SHR data (10). The explanatory variables are measured in 1990 and overlap by one year with the dependent variable. This cross-sectional study finds cities with higher criminal murder rates and more divorced citizens to experience more justifiable homicides. A negative correlation is observed for the number of police per capita. The authors also find cities located in Conceal Carry Weapon law states to experience more justifiable homicides (10). The cross-sectional research design makes it hard to establish the temporal order of these observed relationships and this is further hindered by the time overlap of independent and dependent variables. The SHR data the dependent variable is based on is not adjusted for missing values despite only having information for 70% of total possible reporting months in our analysis sample. This study builds on prior research by re-examining how state gun laws, such as SYG and CCW laws, are associated with justifiable homicides at the city level. There are several statistical limitations that we attempt to address in this study. First, we impute SHR estimates to correct for missing data. Second, we include a proxy for gun ownership, firearm suicide rate, that has not been included in prior research and find this proxy to be positively associated with justifiable homicides. Third, we examine not only SYG and CCW laws, but two additional laws that restrict access to firearms, Permit to Purchase and Universal Background Check laws. We find all four state gun laws examined in this study to be significantly associated with justifiable homicides. Fourth, we perform the first city level longitudinal analysis for this homicide outcome. By utilizing negative binomial fixed-effects estimation from 1980 to 2010, we hope to better establish the temporal order between explanatory and dependent variables compared to cross-sectional techniques (11-12). Finally, we are the first study to control for both racial/ethnic minority presence and segregation. When we disaggregate by race of the victim to analyze total, Black victim, and White victim justifiable homicides, we observe different effects for racial/ethnic composition in a city that appear to be dependent on victim race. We hope this study helps to advance the research on citizen justifiable homicides. Data and Methods Our sample consists of 167 U.S. cities that had populations greater than 100,000 in 1980 and that had information on justifiable homicides in FBI SHR data. Missing data on explanatory variables reduces the analysis sample to 653 out of a possible 668 observations. We do not impute explanatory variables as the amount of missing data is small (2% missing). Independent variables are analyzed across four waves in the census years of 1980, 1990, 2000, and 2010. Dependent variables are measured as 3-year sums and are evaluated one year after the decennial census, making the observation years 1981-1983 and so on. Dependent variables include total, Black Victim, and White Victim citizen justifiable homicides obtained from SHR data. Poisson multiple imputation is used to correct for missing data on these variables (13). We employ imputation because these are not typical dependent variables based on one observation, but rather a 3-year sum of justifiable homicides based on monthly data (36 observations). SHR only contained 70% of total possible months in our sample and imputation is used to fill in the values for missing months so that the 3-year sums are not dependent on the number of reported months, which would introduce biased estimates. Ten iterations of imputations are averaged to fill in values for unreported months in SHR. Previous studies have not corrected for missing data in SHR. We acknowledge the limitations of this data and attempt to correct for them with the imputation methods described above. We recommend to future researchers who use this data to also try to correct for the missing data problem and offer one potential solution in this study. Explanatory variables are specified based on prior research on justifiable and criminal homicides (10, 14-16). Racial/ethnic composition in a city is measured by the percentage of Black and Hispanic residents in a city. Black-White residential segregation is measured using the index of dissimilarity that measures how evenly distributed these two populations are in a city. This index ranges from 0 to 100, with higher dissimilarity indexes representing greater racial segregation. A similar measure that captures Hispanic-White residential segregation is also included. Violent crime rates are obtained from FBI Uniform Crime Reports (UCR) and consists of the number of violent crimes known to police per 100,000 residents. Police rate captures the number of police officers per 100,000 residents obtained from UCR. Gun ownership rates are measured by a proxy, firearm suicide rate, which is the proportion of suicides committed with a firearm (17). Data is obtained from the CDC and measured at the county level due to this information not being publicly available at the city level. State gun laws are assessed by four dummy variables that measure whether a city is located in a Permit to Purchase (PP), Universal Background Check (UBC), Conceal Carry Weapon (CCW), or Stand Your Ground (SYG) law state. PP law is coded as 1 for cities located in a state that requires a permit to purchase a handgun (18). UBC law is coded as 1 for cities located in states that require universal background checks for handgun purchases (18). CCW law states are coded as 1 for any state that is designated as a ‘shall-issue’ or ‘unrestricted’ conceal carry state (4). SYG law states are coded as 1 for any state that has in its castle doctrine legislation a provision that allows for citizens to use deadly force in self-defense ‘in any place that a person has a legal right to be’ with no duty to retreat (1). Additional controls include economic and social disorganization indexes. The economic index is estimated using factor analysis on three economic variables: unemployment rate, median family income, and Gini index. The social disorganization index is computed using factor analysis on percent divorced, percent female headed households, and percent of dwelling units with more than 1.01 residents per room (crowding). We include two measures, drug arrest rate and police killings, to control for potential drug war violence that may spillover to citizen justifiable homicides in select models. Drug arrest rate consists of the number of drug arrests per 100,000 residents obtained from UCR. Police killings are measured by a 2-year sum of the number of police officers killed in a city using National Law Enforcement Officers Memorial Fund (NLEOMF) data. This measure is evaluated in the two years before the dependent variable is observed (1979-1980 and so on). Year dummies are included in all models. Some variables are logged to adjust for skewed distributional effects. Table 1 presents descriptive statistics and data sources for all independent and dependent variables. Negative binomial fixed-effects estimation is employed for all presented models because the dependent variable is a count variable and alpha tests indicate that the data are over-dispersed (11-12). Fixed-effects estimation has been utilized in prior state level studies to assess how the passage of SYG laws is associated with justifiable homicides, which we analyze in this study (1-2). Fixed-effects presents within-effects and estimates how changes within a city in explanatory variables are related to changes in justifiable homicides. Benefits of fixed-effects include automatically controlling for any time-invariant variables which reduces omitted variable bias and being better suited at establishing the temporal order between variables compared to cross-sectional estimations (11-12). City population is specified as an exposure variable in all models to account for the number of times the outcome (event) could have happened. Specifying the number of potential victims (city population) as an exposure variable accounts for differences in the opportunities of this event by including the log of the exposure variable in the model with the coefficient constrained to one (19). The use of exposure variables is superior in many instances to analyzing rates as an explanatory variable because it corrects for differences in the probability distributions of the event across, in this case, cities (19). Results Table 2 presents negative binomial fixed-effects models on total justifiable homicides. Model 1 finds a significant negative coefficient for both Black-White (BW) and Hispanic-White (HW) segregation, consistent with benign-neglect theory that predicts less social control when segregation is higher (15). Justifiable homicides are a type of informal social control. We explain this finding further in the discussion section. Percent Hispanic and social disorganization index are negatively associated with total justifiable homicides. The negative sign for social disorganization is unexpected as this index is usually positively related to criminal homicides (16). It may be the case that law enforcement agents are less likely to classify homicides as justified in socially disorganized areas, but any theoretical explanation is merely speculative at this point. We welcome any future research that further explores this finding. Firearm suicide rate is the only significant positive predictor in model 1 and implies that increases in gun ownership are associated with increases in total justifiable homicides. Model 2 in Table 2 adds potential indicators of drug war violence in a city, drug arrests and police killings, and finds both to be positive predictors of total justifiable homicides. Other significant relationships from model 1 are unchanged in model 2 with the inclusion of these variables. In model 3, percent Black and Hispanic are interacted with segregation terms. Both interaction terms are negatively significant and their inclusion results in percent Black and Hispanic main terms being positively significant. Model 3 is the best fitting model in Table 2 according to AIC statistics (2073.95). Table 3 displays results for Black victim and White victim justifiable homicides using the same model specifications from Table 2. The reduction in sample size to 645 for White victim justifiable homicides is due to two cities not experiencing any of these homicides in the four analysis waves. Fixed-effects estimation requires at least one change in the dependent variable and automatically drops cities that never experience a change. Overall, the sample mean is twice as high for Black victim justifiable homicides (3.88) compared to White victim justifiable homicides (1.87), consistent with descriptive analysis that finds homicides are more likely to be classified as justified when the victim is Black compared to White. The results are similar for Black victim justifiable homicide as they were for total justifiable homicides, which may be attributable to the majority of total justifiable homicides consisting of Black victims. The only difference observed in Table 3 for Black victim justifiable homicides compared to total justifiable homicides is the main term for BW segregation is not significant in model 3. White victim justifiable homicides have several differences from total and Black victim justifiable homicides. First, firearm suicide rate is not a significant predictor for this homicide outcome. Second, drug arrests are not significant while police killings remain a significant and positive predictor. Social disorganization index is only significant in model 4 and violent crime rates are significant for the first time in this model. Finally, racial/ethnic minority presence and segregation effects are different. Percent Black and Hispanic are not significant in any models for White victim justifiable homicides. BW segregation remains negatively associated in all models, while the interaction term for percent Hispanic and HW segregation is significant in model 6. Table 4 presents negative binomial fixed-effects models for state gun laws on total, Black victim, and White victim justifiable homicides. Models 1, 3, and 5 omit firearm suicide rate as this variable may be endogenous to state gun laws (20-21). Models 2, 4, and 6 include firearm suicide rate as a robustness check. All four state gun laws are significant across all six models in Table 4. The two state gun laws that restrict access to firearms, Permit to Purchase and Universal Background Check laws, are negatively associated with justifiable homicides as predicted. On the other hand, the two state gun laws that encourage public firearm carry and use, Conceal Carry Weapon and Stand Your Ground laws, are positively associated with justifiable homicides. The inclusion of firearm suicide rate leads to modest reductions (or increases in two cases) in state gun law coefficients. Discussion This is the first city level study to control for gun ownership rates through a proxy, firearm suicide rate. This proxy performed as expected with firearm suicide rate being positively associated with total and Black victim justifiable homicides, while no effect was found for White victim justifiable homicides. All four state gun laws examined in this study had significant effects on total, Black victim, and White victim justifiable homicides. The results provide evidence that these laws perform as expected with laws restricting firearm access (PP and UBC) reducing these homicides and laws encouraging public firearm carrying and use (CCW and SYG) increasing these homicides. This is consistent with prior research that finds a significant effect for SYG and CCW laws on justifiable homicides (1-2, 10). In particular, the significant results for SYG laws are not surprising as these laws extend the number of homicide incidents that can be ruled as ‘justified’. It is also consistent with prior state level research that finds SYG laws to increase total homicide and justifiable homicide rates (1-2). This study confirms that SYG law effects trickle down to the city level for justifiable homicides. The presence of a shall-issue or unrestricted Conceal Carry Weapon law had a positive effect on justifiable homicides, which has been previously found at the city level in a cross-sectional study (10). The authors of that study claimed the positive effect for CCW laws was likely due to these laws increasing gun availability and public firearm carrying. Citizen justifiable homicides are distinct from other homicide types with nearly 9 out of 10 cases involving a firearm. This is why we also assessed two state gun laws that are posited to reduce gun availability, Permit to Purchase and Universal Background Check laws. We find that both PP and UBC laws that restrict access to firearms, and likely reduce gun availability, to be negatively associated with justifiable homicides. This result is consistent with theoretical predictions. Finally, this study is the first to include measures of both racial/ethnic minority presence and segregation when analyzing justifiable homicides. The negative effect of segregation on citizen justifiable homicides supports benign-neglect theory that posits segregation reduces interracial interactions, which will decrease demand for both formal and informal social control (15). Justifiable homicides are a type of informal social control. Descriptive analysis finds homicides are more likely to be classified as justified when a White suspect kills a Black victim (5, 6, 8). These interracial homicides are less likely when segregation is high. Minority presence and segregation effects appear to be contingent on each other for total and Black victim justifiable homicides as indicted by the significance of interaction terms for percent Black (Hispanic) and BW (HW) segregation. Minority presence and segregation had less of an effect on White victim justifiable homicides. Few studies have extensively analyzed the determinants of justifiable homicides committed by citizens (1-2, 10). The significant findings for firearm suicide rate, Permit to Purchase laws, and Universal Background Check laws, had not been previously established for this homicide outcome. It appears that gun availability and state gun laws that encourage or discourage this availability in public settings are strong predictors for justifiable homicides. We also find racial/ethnic composition in a city, social disorganization, drug arrests, and police killings to be significant determinants. References McClellan C, and Tekin E. Stand Your Ground Laws, Homicides, and Injuries. Journal of Human Resources 2016;52: 621-653. Cheng C, Hoekstra M. Does Strengthening Self-Defense Law Deter Crime or Escalate violence? Evidence from Expansions to Castle Doctrine. Journal of Human Resources 2013;48: 821-854. Butz A, Fix M, and Mitchell J. Policy Learning and the Diffusion of Stand-Your-Ground Laws. Politics and Policy 2015;43: 347-377. Chval C. Concealed Carry Laws: Violent Crime Deterrent or Stimulant? University of Notre Dame, Department of Economics, Essay. 2015. Copeland, Arthur. The Right to Keep and Bear Arms: A Study of Civilian Homicides Committed Against Those Involved in Criminal Acts in Metropolitan Dade County from 1957 to 1982. Journal of Forensic Sciences 1984;29: 584-590. Griswold D, and Massey C. Police and Killings of Criminal Suspects: A Comparative Analysis. American Journal of Police 1985;4: 1-19. MacDonald J, and Tennenbaum A. Justifiable Homicide by Civilians. In Advances in Criminological Theory, eds.W.S. Laufer & Adler. New Brunswick, NJ: Transaction. 1999. Roman J. Race, Justifiable Homicide, and Stand Your Ground Laws: Analysis of FBI Supplementary Homicide Report Data. The Urban Institute. 2013. Alvarez, A. Trends and Patterns of Justifiable Homicide: A Comparative Analysis. Violence and Victims 1992;7: 347-356. MacDonald J, and Parker K. The Structural Determinants of Justifiable Homicide: Assessing the Theoretical and Political Considerations. Homicide Studies 2001;5: 187-205. Wooldridge J. Econometric Analysis of Cross Section and Panel Data. 1st ed. Cambridge: MIT Press; 2002. Allison P. Fixed Effects Regression Models. Vol. 160. Thousand Oaks: Sage Publications; 2009. Allison P. Missing Data. Vol. 136. Thousand Oaks: Sage Publications; 2001. Blau J, and Blau P. The Cost of Inequality: Metropolitan Structure and Violent Crime. American Sociological Review 1982;47: 114-129. Liska A, Lawrence J, Benson M. Perspectives on the Legal Order. American Journal of Sociology 1981;87: 412-26. McCall P, Land K, and Parker K. An Empirical Assessment of What We Know About Structural Covariates of Homicide Rates: A Return to a Classic 20 Years Later. Homicide Studies 2010;14: 219-243. Kleck G. The Impact of Gun Ownership Rates on Crime Rates: A Methodological Review of the Evidence. Journal of Criminal Justice 2015;43: 40-48 Schell T, Peterson S, Vegetabile B, Scherling A, Smart R, and Morral A. State-Level Estimates of Household Firearm Ownership. Rand Corporation. 2020. Osgood DW. Poisson-based Regression Analysis of Aggregate Crime Rates. Journal of Quantitative Criminology 2000;16: 21-43. Wallace L. Castle Doctrine Legislation: Unintended Effects for Gun Ownership? Justice Policy Journal 2014;11(2): 1-17. Steidley T. The Effect of Concealed Carry Weapons Laws on Firearm Sales. Social Science Research 2019;78: 1-11 Tables Tables 1 to 4 are available in the Supplementary Files section. Supplementary Files Table1.docx Table2.docx Table3.docx Table4.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Castle doctrine laws originate from English common laws that specify that a person has no duty to retreat beyond their own castle walls (2). For decades, virtually all states have allowed for deadly force to be used by citizens with no duty to retreat inside a person’s own home (3). Stand Your Ground laws extend the no duty to retreat clause of castle doctrine outside of the home and to ‘any place where a person has a legal right to be’ (1). This is a rather substantial expansion to the circumstances where a citizen can use deadly force without fear of prosecution and may explain why citizen justifiable homicides increased from 2000 to 2010. From this study’s analysis sample of 167 large U.S. cities, we find the mean number of citizen justifiable homicides increased from a 3-year sum of 4.77 for 2001-2003 to 4.85 for 2011-2013. While this increase is small, it reverses a downward trend since 1980 for this homicide outcome and is in contrast to downward trends observed for both police justifiable homicides and total homicides over this same time period in our sample.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn addition to SYG laws, the U.S. has enacted Conceal Carry Weapon (CCW) laws that allow citizens to carry guns in public. In 1980, only 4 states had these laws compared to 38 states in 2010 (4). State level studies report the positive effect SYG and CCW laws have on total and justifiable homicides (1, 2, 4). One study finds the passage of a state SYG law results in an 8-10% increase in total homicides and while this increase is not solely attributable to an increase in citizen justifiable homicides, they are also drastically increased by between 28-57% depending on model specification (2). While the link between SYG and CCW laws and justifiable homicides has been established at the state level, there is limited research on how these laws trickle down to the city level. Laws that restrict access to firearms have also received less attention for justifiable homicides. We investigate the influence of four state gun laws on justifiable homicides including SYG, CCW, and two restrictive gun laws Permit to Purchase and Universal Background Check. Our analysis sample consists of 167 large U.S. cities, which allows us to control for several community level factors that have not been previously assessed including racial segregation and gun ownership measured by a proxy, firearm suicide rate.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe majority of past studies on justifiable homicides at the city level have either been descriptive or confined to one jurisdiction, which makes them unable to identify community level influencers (5-8). This research generally finds that the victims of justifiable homicides are disproportionately Black males (5, 6, 8). In one study that examines justifiable homicides from 2005-2010 using FBI Supplementary Homicide Reports (SHR) data, the authors find when considering all homicides, White on Black homicides are the most likely to be ruled justified (11.4%) (8). The least likely to be ruled justified is Black on White homicides (1.2%) and this observed racial disparity is exacerbated in SYG law states (16.85% vs. 1.4%). The study also notes that overall, 2.57% of all homicides are ruled justified and in SYG law states this percentage rises to 3.67% (8). Finally, justifiable homicides are more likely to be committed by a firearm than criminal homicides (5-7, 9). One descriptive study reports 88% of justifiable homicides involve the use of a firearm compared to 59% of criminal homicides (9). These descriptive studies are informative, but they do not consider how macro level factors, such as crime rates or gun ownership rates, may influence justifiable homicides committed by citizens. \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe only previous study to assess the determinants of justifiable homicides at the city level across multiple jurisdictions did so on a sample of 188 large U.S. cities using a five-year sum of justifiable homicides from 1990 to 1994 using SHR data (10). The explanatory variables are measured in 1990 and overlap by one year with the dependent variable. This cross-sectional study finds cities with higher criminal murder rates and more divorced citizens to experience more justifiable homicides. A negative correlation is observed for the number of police per capita. The authors also find cities located in Conceal Carry Weapon law states to experience more justifiable homicides (10). The cross-sectional research design makes it hard to establish the temporal order of these observed relationships and this is further hindered by the time overlap of independent and dependent variables. The SHR data the dependent variable is based on is not adjusted for missing values despite only having information for 70% of total possible reporting months in our analysis sample.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study builds on prior research by re-examining how state gun laws, such as SYG and CCW laws, are associated with justifiable homicides at the city level. There are several statistical limitations that we attempt to address in this study. First, we impute SHR estimates to correct for missing data. Second, we include a proxy for gun ownership, firearm suicide rate, that has not been included in prior research and find this proxy to be positively associated with justifiable homicides. Third, we examine not only SYG and CCW laws, but two additional laws that restrict access to firearms, Permit to Purchase and Universal Background Check laws. We find all four state gun laws examined in this study to be significantly associated with justifiable homicides. Fourth, we perform the first city level longitudinal analysis for this homicide outcome. By utilizing negative binomial fixed-effects estimation from 1980 to 2010, we hope to better establish the temporal order between explanatory and dependent variables compared to cross-sectional techniques (11-12). Finally, we are the first study to control for both racial/ethnic minority presence and segregation. When we disaggregate by race of the victim to analyze total, Black victim, and White victim justifiable homicides, we observe different effects for racial/ethnic composition in a city that appear to be dependent on victim race. We hope this study helps to advance the research on citizen justifiable homicides.\u003c/p\u003e"},{"header":"Data and Methods","content":"\u003cp\u003eOur sample consists of 167 U.S. cities that had populations greater than 100,000 in 1980 and that had information on justifiable homicides in FBI SHR data. Missing data on explanatory variables reduces the analysis sample to 653 out of a possible 668 observations. We do not impute explanatory variables as the amount of missing data is small (2% missing). Independent variables are analyzed across four waves in the census years of 1980, 1990, 2000, and 2010.\u0026nbsp;Dependent variables are measured as 3-year sums and are evaluated one year after the decennial census, making the observation years 1981-1983 and so on.\u003c/p\u003e\n\u003cp\u003eDependent variables include total, Black Victim, and White Victim citizen justifiable homicides obtained from SHR data. Poisson multiple imputation is used to correct for missing data on these variables (13). We employ imputation because these are not typical dependent variables based on one observation, but rather a 3-year sum of justifiable homicides based on monthly data (36 observations). SHR only contained 70% of total possible months in our sample and imputation is used to fill in the values for missing months so that the 3-year sums are not dependent on the number of reported months, which would introduce biased estimates. Ten iterations of imputations are averaged to fill in values for unreported months in SHR.\u0026nbsp;Previous studies have not corrected for missing data in SHR. We acknowledge the limitations of this data and attempt to correct for them with the imputation methods described above. We recommend to future researchers who use this data to also try to correct for the missing data problem and offer one potential solution in this study. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eExplanatory variables are specified based on prior research on justifiable and criminal homicides (10, 14-16). Racial/ethnic composition in a city is measured by the percentage of Black and Hispanic residents in a city. Black-White residential segregation is measured using the index of dissimilarity that measures how evenly distributed these two populations are in a city. This index ranges from 0 to 100, with higher dissimilarity indexes representing greater racial segregation. A similar measure that captures Hispanic-White residential segregation is also included. Violent crime rates are obtained from FBI Uniform Crime Reports (UCR) and consists of the number of violent crimes known to police per 100,000 residents. Police rate captures the number of police officers per 100,000 residents obtained from UCR.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGun ownership rates are measured by a proxy, firearm suicide rate, which is the proportion of suicides committed with a firearm (17). Data is obtained from the CDC and measured at the county level due to this information not being publicly available at the city level. State gun laws are assessed by four dummy variables that measure whether a city is located in a Permit to Purchase (PP), Universal Background Check (UBC), Conceal Carry Weapon (CCW), or Stand Your Ground (SYG) law state. PP law is coded as 1 for cities located in a state that requires a permit to purchase a handgun (18). UBC law is coded as 1 for cities located in states that require universal background checks for handgun purchases (18). CCW law states are coded as 1 for any state that is designated as a ‘shall-issue’ or ‘unrestricted’ conceal carry state (4). SYG law states are coded as 1 for any state that has in its castle doctrine legislation a provision that allows for citizens to use deadly force in self-defense ‘in any place that a person has a legal right to be’ with no duty to retreat (1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAdditional controls include economic and social disorganization indexes.\u0026nbsp;The economic index is estimated using factor analysis on three economic variables: unemployment rate, median family income, and Gini index. The social disorganization index is computed using factor analysis on percent divorced, percent female headed households, and percent of dwelling units with more than 1.01 residents per room (crowding).\u0026nbsp;We include two measures, drug arrest rate and police killings, to control for potential drug war violence that may spillover to citizen justifiable homicides in select models. Drug arrest rate consists of the number of drug arrests per 100,000 residents obtained from UCR. Police killings are measured by a 2-year sum of the number of police officers killed in a city using National Law Enforcement Officers Memorial Fund (NLEOMF) data. This measure is evaluated in the two years before the dependent variable is observed (1979-1980 and so on). Year dummies are included in all models. Some variables are logged to adjust for skewed distributional effects. Table 1 presents descriptive statistics and data sources for all independent and dependent variables.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNegative binomial fixed-effects estimation is employed for all presented models because the dependent variable is a count variable and alpha tests indicate that the data are over-dispersed (11-12). Fixed-effects estimation has been utilized in prior state level studies to assess how the passage of SYG laws is associated with justifiable homicides, which we analyze in this study (1-2). Fixed-effects presents within-effects and estimates how changes within a city in explanatory variables are related to changes in justifiable homicides. Benefits of fixed-effects include automatically controlling for any time-invariant variables which reduces omitted variable bias and being better suited at establishing the temporal order between variables compared to cross-sectional estimations (11-12).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCity population is specified as an exposure variable in all models to account for the number of times the outcome (event) could have happened. Specifying the number of potential victims (city population) as an exposure variable accounts for differences in the opportunities of this event by including the log of the exposure variable in the model with the coefficient constrained to one (19). The use of exposure variables is superior in many instances to analyzing rates as an explanatory variable because it corrects for differences in the probability distributions of the event across, in this case, cities (19).\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eTable 2 presents negative binomial fixed-effects models on total justifiable homicides. Model 1 finds a significant negative coefficient for both Black-White (BW) and Hispanic-White (HW) segregation, consistent with benign-neglect theory that predicts less social control when segregation is higher (15). Justifiable homicides are a type of informal social control. We explain this finding further in the discussion section. Percent Hispanic and social disorganization index are negatively associated with total justifiable homicides. The negative sign for social disorganization is unexpected as this index is usually positively related to criminal homicides (16). It may be the case that law enforcement agents are less likely to classify homicides as justified in socially disorganized areas, but any theoretical explanation is merely speculative at this point. We welcome any future research that further explores this finding. Firearm suicide rate is the only significant positive predictor in model 1 and implies that increases in gun ownership are associated with increases in total justifiable homicides.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eModel 2 in Table 2 adds potential indicators of drug war violence in a city, drug arrests and police killings, and finds both to be positive predictors of total justifiable homicides. Other significant relationships from model 1 are unchanged in model 2 with the inclusion of these variables. In model 3, percent Black and Hispanic are interacted with segregation terms. Both interaction terms are negatively significant and their inclusion results in percent Black and Hispanic main terms being positively significant. Model 3 is the best fitting model in Table 2 according to AIC statistics (2073.95). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 3 displays results for Black victim and White victim justifiable homicides using the same model specifications from Table 2. The reduction in sample size to 645 for White victim justifiable homicides is due to two cities not experiencing any of these homicides in the four analysis waves. Fixed-effects estimation requires at least one change in the dependent variable and automatically drops cities that never experience a change. Overall, the sample mean is twice as high for Black victim justifiable homicides (3.88) compared to White victim justifiable homicides (1.87), consistent with descriptive analysis that finds homicides are more likely to be classified as justified when the victim is Black compared to White. The results are similar for Black victim justifiable homicide as they were for total justifiable homicides, which may be attributable to the majority of total justifiable homicides consisting of Black victims. The only difference observed in Table 3 for Black victim justifiable homicides compared to total justifiable homicides is the main term for BW segregation is not significant in model 3.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWhite victim justifiable homicides have several differences from total and Black victim justifiable homicides. First, firearm suicide rate is not a significant predictor for this homicide outcome. Second, drug arrests are not significant while police killings remain a significant and positive predictor. Social disorganization index is only significant in model 4 and violent crime rates are significant for the first time in this model. Finally, racial/ethnic minority presence and segregation effects are different. Percent Black and Hispanic are not significant in any models for White victim justifiable homicides. BW segregation remains negatively associated in all models, while the interaction term for percent Hispanic and HW segregation is significant in model 6.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 4 presents negative binomial fixed-effects models for state gun laws on total, Black victim, and White victim justifiable homicides. Models 1, 3, and 5 omit firearm suicide rate as this variable may be endogenous to state gun laws (20-21). Models 2, 4, and 6 include firearm suicide rate as a robustness check. All four state gun laws are significant across all six models in Table 4. The two state gun laws that restrict access to firearms, Permit to Purchase and Universal Background Check laws, are negatively associated with justifiable homicides as predicted. On the other hand, the two state gun laws that encourage public firearm carry and use, Conceal Carry Weapon and Stand Your Ground laws, are positively associated with justifiable homicides. The inclusion of firearm suicide rate leads to modest reductions (or increases in two cases) in state gun law coefficients. \u0026nbsp;\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis is the first city level study to control for gun ownership rates through a proxy, firearm suicide rate. This proxy performed as expected with firearm suicide rate being positively associated with total and Black victim justifiable homicides, while no effect was found for White victim justifiable homicides. All four state gun laws examined in this study had significant effects on total, Black victim, and White victim justifiable homicides. The results provide evidence that these laws perform as expected with laws restricting firearm access (PP and UBC) reducing these homicides and laws encouraging public firearm carrying and use (CCW and SYG) increasing these homicides. This is consistent with prior research that finds a significant effect for SYG and CCW laws on justifiable homicides (1-2, 10). In particular, the significant results for SYG laws are not surprising as these laws extend the number of homicide incidents that can be ruled as ‘justified’. It is also consistent with prior state level research that finds SYG laws to increase total homicide and justifiable homicide rates (1-2). This study confirms that SYG law effects trickle down to the city level for justifiable homicides. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe presence of a shall-issue or unrestricted Conceal Carry Weapon law had a positive effect on justifiable homicides, which has been previously found at the city level in a cross-sectional study (10). The authors of that study claimed the positive effect for CCW laws was likely due to these laws increasing gun availability and public firearm carrying. Citizen justifiable homicides are distinct from other homicide types with nearly 9 out of 10 cases involving a firearm. This is why we also assessed two state gun laws that are posited to reduce gun availability, Permit to Purchase and Universal Background Check laws. We find that both PP and UBC laws that restrict access to firearms, and likely reduce gun availability, to be negatively associated with justifiable homicides. This result is consistent with theoretical predictions.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFinally, this study is the first to include measures of both racial/ethnic minority presence and segregation when analyzing justifiable homicides. The negative effect of segregation on citizen justifiable homicides supports benign-neglect theory that posits segregation reduces interracial interactions, which will decrease demand for both formal and informal social control (15). Justifiable homicides are a type of informal social control. Descriptive analysis finds homicides are more likely to be classified as justified when a White suspect kills a Black victim (5, 6, 8). These interracial homicides are less likely when segregation is high. Minority presence and segregation effects appear to be contingent on each other for total and Black victim justifiable homicides as indicted by the significance of interaction terms for percent Black (Hispanic) and BW (HW) segregation. Minority presence and segregation had less of an effect on White victim justifiable homicides.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; Few studies have extensively analyzed the determinants of justifiable homicides committed by citizens (1-2, 10). The significant findings for firearm suicide rate, Permit to Purchase laws, and Universal Background Check laws, had not been previously established for this homicide outcome. It appears that gun availability and state gun laws that encourage or discourage this availability in public settings are strong predictors for justifiable homicides. We also find racial/ethnic composition in a city, social disorganization, drug arrests, and police killings to be significant determinants.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eMcClellan C, and Tekin E. Stand Your Ground Laws, Homicides, and Injuries. Journal of Human Resources 2016;52: 621-653.\u003c/li\u003e\n \u003cli\u003eCheng C, Hoekstra M. Does Strengthening Self-Defense Law Deter Crime or Escalate violence? Evidence from Expansions to Castle Doctrine. Journal of Human Resources 2013;48: 821-854.\u003c/li\u003e\n \u003cli\u003eButz A, Fix M, and Mitchell J. Policy Learning and the Diffusion of Stand-Your-Ground Laws. Politics and Policy 2015;43: 347-377.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eChval C. Concealed Carry Laws: Violent Crime Deterrent or Stimulant? University of Notre Dame, Department of Economics, Essay. 2015.\u003c/li\u003e\n \u003cli\u003eCopeland, Arthur. The Right to Keep and Bear Arms: A Study of Civilian Homicides Committed Against Those Involved in Criminal Acts in Metropolitan Dade County from 1957 to 1982. Journal of Forensic Sciences 1984;29: 584-590.\u003c/li\u003e\n \u003cli\u003eGriswold D, and Massey C. Police and Killings of Criminal Suspects: A Comparative Analysis. American Journal of Police 1985;4: 1-19.\u003c/li\u003e\n \u003cli\u003eMacDonald J, and Tennenbaum A. Justifiable Homicide by Civilians. In Advances in Criminological Theory, eds.W.S. Laufer \u0026amp; Adler. New Brunswick, NJ: Transaction. 1999.\u003c/li\u003e\n \u003cli\u003eRoman J. Race, Justifiable Homicide, and Stand Your Ground Laws: Analysis of FBI Supplementary Homicide Report Data. The Urban Institute. 2013.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eAlvarez, A. Trends and Patterns of Justifiable Homicide: A Comparative Analysis. Violence and Victims 1992;7: 347-356.\u003c/li\u003e\n \u003cli\u003eMacDonald J, and Parker K. The Structural Determinants of Justifiable Homicide: Assessing the Theoretical and Political Considerations. Homicide Studies 2001;5: 187-205.\u003c/li\u003e\n \u003cli\u003eWooldridge J. Econometric Analysis of Cross Section and Panel Data. 1st ed. Cambridge: MIT Press; 2002.\u003c/li\u003e\n \u003cli\u003eAllison P. Fixed Effects Regression Models. Vol. 160. Thousand Oaks: Sage Publications; 2009.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eAllison P. Missing Data. Vol. 136. Thousand Oaks: Sage Publications; 2001.\u003c/li\u003e\n \u003cli\u003eBlau J, and Blau P. The Cost of Inequality: Metropolitan Structure and Violent Crime. American Sociological Review 1982;47: 114-129.\u003c/li\u003e\n \u003cli\u003eLiska A, Lawrence J, Benson M. Perspectives on the Legal Order. American Journal of Sociology 1981;87: 412-26.\u003c/li\u003e\n \u003cli\u003eMcCall P, Land K, and Parker K. An Empirical Assessment of What We Know About Structural Covariates of Homicide Rates: A Return to a Classic 20 Years Later. Homicide Studies 2010;14: 219-243.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eKleck G. The Impact of Gun Ownership Rates on Crime Rates: A Methodological Review of the Evidence. Journal of Criminal Justice 2015;43: 40-48\u003c/li\u003e\n \u003cli\u003eSchell T, Peterson S, Vegetabile B, Scherling A, Smart R, and Morral A. State-Level Estimates of Household Firearm Ownership. Rand Corporation. 2020.\u003c/li\u003e\n \u003cli\u003eOsgood DW. Poisson-based Regression Analysis of Aggregate Crime Rates. Journal of Quantitative Criminology 2000;16: 21-43.\u003c/li\u003e\n \u003cli\u003eWallace L. Castle Doctrine Legislation: Unintended Effects for Gun Ownership? Justice Policy Journal 2014;11(2): 1-17.\u003c/li\u003e\n \u003cli\u003eSteidley T. The Effect of Concealed Carry Weapons Laws on Firearm Sales. Social Science Research 2019;78: 1-11\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 4 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7228877/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7228877/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"This study examines community level influencers for citizen justifiable homicides in 167 large U.S. cities from 1980 to 2010 using panel estimation techniques. We perform the first fixed-effects city level analysis of this homicide outcome. We find gun ownership measured by a proxy, firearm suicide rate, to be a positive and significant predictor for justifiable homicides. State gun laws are also assessed including Stand Your Ground, Conceal Carry Weapon, Permit to Purchase, and Universal Background Check laws. All four state gun laws are significantly associated with justifiable homicides. Finally, we disaggregate justifiable homicides by race of the victim and find differences in predictors for Black Victim and White Victim justifiable homicides.","manuscriptTitle":"The Influence of Gun Ownership and State Gun Laws on Citizen Justifiable Homicides in Large U.S. Cities","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-30 08:52:17","doi":"10.21203/rs.3.rs-7228877/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"739d6107-8f75-4f02-9c77-b09f0857a98a","owner":[],"postedDate":"July 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-24T20:40:55+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-30 08:52:17","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7228877","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7228877","identity":"rs-7228877","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}