Abstract
This article draws from an ongoing debate over explanations of homicide. Within this debate, we investigate the pro-social effects of civil society and social capital. Few cross-national studies explore whether elements of social capital either increase or decrease homicide. The cross-national work that does is often characterized by small, homogeneous samples and the use of inappropriate statistical techniques. Replicating elements of Lederman et al.’s (Econ Dev Cult Change 50:509–539, 2002) original study but with wave IV World Values Survey data and negative binomial regression, we find weak support for the beneficial consequences of social capital on homicide. One dimension of social capital, however, does exhibit a significant negative association with homicide rates, net of other influences: social activism. We also fail to support the Durkheimian hypothesis that the negative effect of social capital on homicide is conditional on modernization. We explore the implications of the findings along with avenues for future research.
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Notes
While we acknowledge that individuals can increase their social capital through criminal organizations or deviant subgroups, which can facilitate criminal activity, we focus, instead, on objective associations that are exclusively civic and political in nature. Thus, when we invoke social capital we are excluding objective associations that promote a common interest in criminal and deviant behavior.
The WVS has a total of 56 countries that match on the individual-level social capital and cross-national homicide measures. We only explore 52 because of influential case and outlier analyses discussed below.
We examined alternative measures of crime, such as burglary, fraud, robbery, car theft, and total crime rates, as either discrete non-latent variables or as latent dimensions. Regardless of the measure and method, the results were congruent with those presented here. We chose homicide as our measure of violent crime for the reasons that it produces the largest sample and is the most reliable cross-national measure of crime.
The question is as follows: “Please look carefully at the following list of voluntary organizations and activities and say…which, if any, do you belong to?” The list contains 14 different organizations and activities ranging from social welfare service for elderly, labor unions, human rights group, to sports and recreation groups. We do not include religious organizations.
The question is as follows: “I’m going to read out some different forms of political action that people can take, and I’d like you to tell me, for each one, whether you have actually done any of these things, whether you might do it or would never, under any circumstances, do it?” The actions include signing a petition, joining in boycotts, attending lawful demonstrations, joining unofficial strikes, and occupying buildings or factories.
It is often difficult to find exact measures of concepts when dealing with cross-national data. This is especially the case when researchers favor a wide range of countries to ensure variability. Unfortunately, the WVS does not contain questions measuring norms against violence, and as a result we cannot include such a measure. This is a common limitation not only of the current study but of all cross-national investigations as well. Therefore, we assume that norms tolerating such behavior as tax evasion and corruption will parallel norms for other crimes like theft and homicide.
We code the following countries as FSE: Albania, Bosnia and Herzegovina, Bulgaria, Belarus, Croatia, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Republic of Moldova, Poland, Romania, Russian Federation, Slovakia, Slovenia, Ukraine, Republic of Macedonia, and Serbia and Montenegro. In alternative analyses, we explored other geopolitical regions outlined by Cole and Gramajo (2009) including dummies for Sub-Saharan African countries and Middle Eastern Crescent countries (also see Ortega et al. 1992). None of these alternative geopolitical dummy variables were statistically significant when paired with FSE or the other controls. As a result, we only include FSE in the present analysis. As a further robustness check, we ran the models presented herein using hierarchical generalized linear models with the Cole and Gramajo (2009) geopolitical regions as random intercepts (i.e., level-1 countries embedded within level-2 geopolitical regions). The results were similar to using negative binomial regression except for only minor deviations in the control variables. We also investigated the impact of sex ratios on homicide since low sex ratios (more women than men) may expand the incidence of lethal violence against women or capture a country’s prior history of war (see Avakame 1999; Messner and Rosenfeld 1997; O’Brien 1991; Pratt and Godsey 2003; Savolainen 2000). Yet we exclude sex ratios from the final analysis since it (a) is highly correlated with FSE (r > 0.60), and (b) FSE renders sex ratios insignificant regardless of model specification. As a result, we exclude the sex ratios measure in favor of FSE in order to avoid issues of multicollinearity.
With respect to multicollinearity, only GDP and social activism are highly correlated with each other (r = 0.79), which we address in the results. And although the secular membership and church attendance variables are highly correlated (r = 0.65), we do not include these and other social capital measures in the same model. Note that all other correlations between independent variables are well below a conservative cutoff value of 0.60; slightly different parameter specifications did not produce noticeable shifts in the results (i.e., no changes in the signs of effects); and drawing 5 randomly chosen 30 country samples did not produce dramatic differences in the coefficients across models. All of this suggests that multicollinearity is not an issue in the present investigation.
With respect to the partialling fallacy—which is when one of two moderately collinear regressors is slightly more correlated with an outcome variable than the other and, as a result, is assigned all of the explained variance (see Gordon 1968; Land et al. 1990)—we explored model sensitivity to the following moderately correlated independent variables (see Table 2): (1) secular memberships and FSE, (2) generalized trust and all other control variables, and (3) church attendance and FSE. That is, we investigated models without the fallacious control variable (e.g., FSE) while including all other controls and the social capital indicator of interest (e.g., secular memberships). Only one such model re-specification yielded statistical significance for a social capital variable—secular memberships without FSE. Following Baron and Kenny (1986), we then explored whether the relationship between FSE, secular memberships, and total homicides was either spurious or one of mediation. We did so following prior theoretical and empirical work showing that the transition from communism to capitalism likely undermined civic engagement in former Soviet economies (e.g., Mondak and Gearing 1998; Rosenberg 1995). Although FSE is significantly associated with secular memberships (results available upon request), model 2, Table 3 suggests that the relationship between secular memberships and total homicides in a country is spurious. All of this suggests that the partialling fallacy is likely not an issue with respect to the present investigation.
With respect to influential cases, China, South Africa, USA, and Venezuela consistently produced either (a) CooksD values above the cutoff value of 4/N regardless of the model, (b) skewed deviance residuals, and/or (c) both large diagonal “hat” matrix and studentized residuals. Without these four influential cases, all CooksD values regardless of the model are below the cutoff value of 4/N, the distribution of the deviance residuals is approximately normal (McCullah and Nelder 1989), and none of the remaining cases produce large diagonal “hat” matrix and studentized residuals. This suggests that all of the models are fit correctly when excluding these four cases.
China was further excluded since translation errors were made with respect to some of the social capital dimensions (e.g., secular memberships) (see codebook for World Values Study Group 1999).
The AIC (not shown) reveals similar results: model 1 explains more variation than the others.
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Acknowledgments
The authors thank Trey Causey, Katie Corcoran, Robert Crutchfield, Jerald Herting, Edgar Kiser, Derek Kreager, Ross Matsueda and Jacob Young for helpful suggestions. Earlier versions of this research were presented at the 2009 annual meeting of the American Sociological Association, the 2008 annual meeting of the American Society of Criminology, and the Deviance Seminar series at the University of Washington. We thank the presenters and attendees for their comments.
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Robbins, B., Pettinicchio, D. Social Capital, Economic Development, and Homicide: A Cross-National Investigation. Soc Indic Res 105, 519–540 (2012). https://doi.org/10.1007/s11205-011-9785-x
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DOI: https://doi.org/10.1007/s11205-011-9785-x