Social Structure,Anomie,and National Levels of Homicide

Abstract

Merton’s “Social Structure and Anomie” seeks to explain how “socio-cultural” influences exert “definite pressures” to engage in non-conformity. Despite having a significant influence, few studies have assessed the degree to which Merton’s propositions explain cross-national variation in levels of crime. Using data on national levels of homicide, data from the World Values Survey, and other structural controls, the present study assesses the degree to which deinstitutionalization, demoralization, and blocked opportunity interact to explain crime cross-nationally. Results provide a high degree of support for Merton’s assertion that societal types characterized by relatively high levels of materialism and/or demoralization or deinstitutionalization suffer from higher levels of homicide. However, there is less support for Merton’s assertion that inequality interacts with various societal patterns of means/ends integration in a meaningful way. Findings and implications for the utility of classical anomie as a general macro-level theory are discussed.

Keywords

cross-national criminology homicide strain anomie Merton culture

Merton’s (1938; revised in 1949, 1957, 1964, and 1968) “Social Structure and Anomie” is among the most significant criminological articles ever published, promoting substantial debate, empirical research, and inspiration for several prominent contemporary theoretical frameworks. Despite this, relatively little empirical literature has directly addressed the propositions of classical anomie theory. Specifically, although some studies have examined the widely recognized micro-level “deviant adaptations” (conformity, innovation, ritualism, retreatism, and rebellion), few studies, to date, have directly examined Merton’s macro-level propositions, and none have assessed how social structures and cultural attributes of societies identified by Merton jointly produce different levels of crime.

At the core of Merton’s macro-level arguments regarding societal levels of crime is the notion that societies with a relative balance between cultural pressures for success and institutional control of the means for success, should benefit from lower levels of deviance. In contrast, inasmuch as societies suffer from an imbalance between their culturally prescribed means and the pressures for success, Merton suggests that “antisocial behavior” is likely to “ensue on a considerable scale.” In seeking to clarify these societal level relationships, Merton (1938) explicitly identifies a number of “cultural patterns” of means/goals integration (p. 673), likely to result in different levels and types of societal crime. These types have not yet been explored or discussed in the empirical literature, but they would seem to have considerable value in understanding how opportunity is likely to interact with cultural and structural features of various societies.

Using data on national levels of homicide, data from the World Values Survey (WVS), United Nations, World Bank, World Health Organization, International Labour Office, and CIA World Factbook, the present study assesses hypotheses regarding the explanation of societal levels of crime central to Merton’s (1938) seminal statement in “Social Structure and Anomie.” Specifically, we assess how several “cultural patterns” of means/ends (mal)integration identified by Merton influence levels and patterns of crime at the national level both independently and in interaction with measures of opportunity, while controlling for other relevant factors. Findings and implications for the utility of Merton’s typology of societies as a general macro-level and cross-national theory are discussed.

A Re-Examination of Merton’s Anomie Theory

A key tenet of classical anomie theory is that cultural pressures to pursue material goals result in the subordination of means for attaining these. Drawing on this tenet, the dominant approach in the literature has been to suggest that the degradation of means by over-emphasis on goals is almost invariant—that is, it is virtually impossible for a society to have both a strong value of material goals and strongly institutionalized means for achieving those (Baumer, 2007; Baumer & Gustafson, 2007; Bernard, 1987; Messner, 1988; Messner & Rosenfeld, 1994; Messner, Thome, & Rosenfeld, 2008). However, Merton (1938) takes a softer view of the causal relationship than is ordinarily recognized, stating,

To say that these two elements, culture goals and institutional norms, operate jointly is not to say that the ranges of alternative behaviors and aims bear some constant relation to one another. The emphasis upon certain goals may vary independently of the degree of emphasis upon institutional means. (p. 673)

Thus, Merton implies that although there likely is a strong connection, various combinations of means and goals do inevitably exist in the cultural and structural variation observed across societies. Consistent with this premise, Merton (1938) further acknowledges three possible “cultural patterns” (p. 673) that societies are likely to fall into: stable, deinstitutionalized, and ritualist. Consideration of each of these types raises interesting questions about their implications for explaining various outcomes, especially with regard to how they interact with opportunity structures.

According to Merton, in “stable” societies, a relative balance exists between the emphasis on material goals and the acceptable means for attaining them. Such societies neither over-emphasize material success goals, nor compel members of such societies to defiantly adapt when goals are unfulfilled. Although some individuals may aspire to and pursue more lofty material goals—the general pressures to achieve wealth (e.g., “The American Dream”) are likely subordinated and only heralded inasmuch as they are a product of virtuous means. Similarly, when one is blocked from attaining goals, the deviant adaptations identified by Merton (innovation, retreatism, ritualism, and rebellion) are minimized as viable options—because conformity is valued in balance with achievement. As such, individuals are compelled to pursue success by accepted and conventional means (i.e., education, hard work, etc.), without feeling undue pressure to “win”—that is, it is not so much about whether you win or lose, it is about how you play the game. As a benefit, these societies are likely to be characterized by a relatively stable social order, and lower levels of antisocial behavior. In contrast to stable societies, Merton suggests that two types of imbalance between goals and means are likely to produce divergent consequences in interaction with other factors, especially opportunity.

In “deinstitutionalized” societies, pursuit of material goals is “limited only by technical rather than institutional considerations” (Merton, 1938, p. 673). Moreover, Merton (1938) argues,

The process whereby exaltation of the end generates a literal demoralization, i.e., a deinstitutionalization, of the means is one which characterizes many groups in which the two phases of the social structure are not highly integrated. The extreme emphasis upon the accumulation of wealth as a symbol of success in our own society militates against the completely effective control of institutionally regulated modes of acquiring a fortune. (p. 675)

This conforms to most traditional and contemporary interpretations of Mertonian theory, which argue that excess emphasis on material goals generally corresponds with the subordination of conventional means for achieving these. Thus, it is argued, amid strong pressures for material success, members of deinstitutionalized societies freely deviate from conventional means to achieve material symbols of status and success. This is particularly true when conventional means for attaining success are structurally blocked for considerable portions of the population. Specifically, blocked or limited opportunity plays a clear and central role as a conditioning factor—in other words, amid a strong emphasis on material success, actors are compelled to engage in deviant adaptations inasmuch as they are blocked from achieving success by conventional means.

Beyond the more familiar “stable” and “deinstitutionalized” types of societies, Merton also offers the possibility of “ritualist” societies, in which rigid adherence to means without concern for material goals produces a “tradition-bound, sacred society characterized by neo-phobia” (i.e., strict observance of accepted means and traditional roles is the goal; Merton, 1938, p. 673). The possibility of such a “cultural pattern” raises interesting questions. Of particular interest is how the central concept of opportunity is likely to interact within such a cultural context. Seeking to provide some insights into this conundrum, Merton (1938) states as follows:

A high frequency of deviate behavior is not generated simply by “lack of opportunity” or by this exaggerated pecuniary emphasis. A comparatively rigidified class structure, a feudalistic or caste order, may limit such opportunities far beyond the point which obtains in our society today. It is only when a system of cultural values extols, virtually above all else, certain common symbols of success for the population at large while its social structure rigorously restricts or completely eliminates access to approved modes of acquiring these symbols for a considerable part of the same population, that antisocial behavior ensues on a considerable scale. (p. 680)

Here, Merton suggests that the specific cultural patterns of means/goals integration observed in a society are likely to be critical in determining whether blocked opportunity matters as a crime generating force. This means that in “ritualist” societies, that do not emphasize material success for all (i.e., universalism) and, in fact, strongly emphasize observance of traditional roles, blocked opportunities are theoretically rendered neutral as a criminogenic force. In fact, when examined globally, we may expect these societies, despite their inegalitarian social structures, to benefit from relatively low levels of “antisocial behavior” or patterns of crime. Alternatively, they may reflect a different emphasis or substantive pattern than is observed in other societies (e.g., honor killings in enforcement of rigid norms intended to reinforce the existing social order).

Taken together, Merton’s notion of cultural patterns suggests interesting implications for both theory and research that have not yet been explored. Specifically, contrary to past research and theoretical development, it suggests that the relationship between means and goals is not invariant. Furthermore, it suggests that different patterns of means/goals integration are likely to substantively condition the effects of key intervening variables such as blocked opportunity. Stated another way, although blocked opportunity may be highly consequential in deinstitutionalized societal types, it may have relatively benign effects in either stable or ritualistic types of societies, which both have a stronger emphasis on preserving traditional means. Thus, drawing on Merton’s thinking, it seems important to account for cultural context (means/goals integration), when cross-nationally examining the effects of opportunity structures on levels of crime. We now turn our attention to a discussion of extant research on classical anomie theory.

Empirical Studies of Anomie

Despite the prominence of classical anomie theory, there have been few macro-level tests (Pratt & Cullen, 2005). Most research has focused on the micro-level processes specified by Merton, especially his typology of deviant adaptations. Only a few macro-level studies have explicitly tested Merton’s propositions (Baumer & Gustafson, 2007); however, as a result of the lack of suitable data, no study has assessed the cross-national relevance of Merton’s macro-level propositions.

Of the existing cross-national research, much of it has focused on the measurement and causes of Durkheimian anomie or normlessness, which closely resembles Merton’s notion of the breakdown of institutionalized means. For example, Cao (2004) found that demographic measures influenced rates of anomie across nations and that anomie in the United States did not differ significantly from other English-speaking nations. In another article, Cao (2007) found that employment, having children, and life satisfaction were negatively associated with anomie among respondents in China. In addition, R. Zhao and Cao (2010) found that individuals living in nations undergoing rapid societal change experienced higher levels of anomie. Similar conclusions were drawn by Thorlindsson and Bernburg (2004), who found that community political participation influenced levels of anomie among juveniles in Iceland. More importantly, none of the research discussed above directly informs the relationship between anomie and crime.

Existing macro-level tests of the relationship between anomie and crime rates fall into three categories. The first involves national case studies that examine how rapid social change has influenced crime rates within individual nations. For example, Liu (2005) found that crime rates increased in China from 1978 to 1999, a peak period of economic growth and change in China, for both economically and non-economically motivated crimes. Interestingly, Liu (2005) found that rates of economically motivated crimes rose faster than rates of non-economically motivated crime. Similarly, L. Zhao (2008) found that rapid social change in China was associated with an explosion in property crime and political corruption. Taken together, these studies suggest that rapid social transformations lead to increases in many different types of crime. Examination of data from other nations yields similar conclusions. Recent research also reveals that socio-political changes in former Soviet Bloc nations correspond with increased rates of crime (Kim & Pridemore, 2005; Stamatel, 2009). Admittedly, these studies are not direct tests of classical anomie theory. They do, however, inform our understanding of the theory if we assume that one outcome of the social changes occurring in these nations is the emergence of a culture of self-interest and pursuit of material wealth.

Indirect support for classical anomie can also be drawn from cross-national research on theories that share conceptual overlap with classical anomie. For example, Baumer and Gustafson (2007) note that both classical and institutional anomie assert that crime will be higher in societies characterized by a strong cultural emphasis on monetary success goals and a weak emphasis of pursuing those goals through legitimate means. Thus, the robust effects revealed in research on institutional anomie theory (i.e., Messner & Rosenfeld, 1997; Pratt & Cullen, 2005; Savolainen, 2000) provide indirect support that a cross-national examination of Merton’s original arguments should receive empirical support. Relatedly, in a recent test of Bonger’s (1916) theory, Antonoccio and Tittle (2007) found that nations with higher levels of demoralization have higher rates of homicide. Bonger’s (1916) notion of demoralization, which is characterized by an egoistic moral environment where individuals place their selfish interests over the needs of others, shares remarkable resemblance to Merton’s arguments.

Perhaps, the most comprehensive test of classical anomie theory has been performed by Baumer and Gustafson (2007), who examined Merton’s core propositions using 77 geographic units within the General Social Survey (GSS). Baumer and Gustafson (2007) found support for the proposition that instrumental crime was higher in geographic areas characterized by a high commitment to monetary success and a low commitment to legitimate means to attain that success. Less support was found, however, for the proposition that the interaction between commitment to monetary success and low commitment to legitimate means is moderated by other features of the social structure. More specifically, job availability, economic attainment, and economic inequality were all found not to moderate the commitment to monetary success/low commitment to legitimate means interaction. Support for the notion that Baumer and Gustafson’s (2007) findings can be generalized to the cross-national level is found in recent research by Chamlin and Sanders (2013). Their research did not include a direct measure of anomie but found that measures of acceptance of material success interacted with levels of relative and absolute deprivation, respectively, to influence cross-national variation in drug trafficking. These findings lend support to Merton’s argument that the cultural and structural components of the social system interact to influence macro-level variation in crime.

Taken together, the existing macro-level research on classical anomie lends support to several key tenets of classical anomie theory. Specifically, societies with high anomie, or a decline in observance of institutional means, tend to suffer from relatively higher levels of crime. Similarly, societies dominated by an egoistic or materialistic environment also suffer from higher levels of crime. However, the research remains ambiguous on other key factors. Specifically, although inequality and other indicators of structural obstacles are consistent predictors of aggregate crime rates, studies have been inconsistent regarding the hypothesized interaction between blocked opportunities, institutionalized means, and materialism. Furthermore, no study to date has examined the degree to which different patterns of means-ends integration affect levels of crime in a cross-national sample that has sufficient variation to represent the various types identified by Merton. Given this, the present study seeks to begin to fill this gap and further develop Merton’s theoretical project started almost 80 years ago.

Hypotheses

Based on the theory and empirical research presented above, we hypothesize the following:

Hypothesis 1 (H1): Stable societal types, which are characterized by a balanced emphasis on material goals and means for achieving them, will benefit from lower levels of homicide.

Hypothesis 2 (H2): Deinstitutionalized or demoralized societal types, which are characterized by an over-emphasis on material goals and the subordination of traditional means for achievement, will suffer from higher levels of homicide.

Hypothesis 3 (H3): Ritualistic societies, which have a strong emphasis on traditional means and a de-emphasis of material goals, will not exhibit a significant relationship with levels of homicide (due to the possibility of high levels of intra-family violence, which offset the benefits of traditionalism in reducing interpersonal violence).

Hypothesis 4 (H4): Measures of inequality in the opportunity structure will only significantly interact with deinstitutionalized or demoralized societal types to produce multiplicatively higher levels of homicide.

Data and Method

To assess the degree to which Mertonian anomie theory explains variation in homicide rates at the national level, we utilize aggregated indicators from the most recent year relevant data are available (WVS, 2009; see also Inglehart & Baker, 2000).¹ The WVS is a data collection effort begun by the European Values Survey group in 1981 and expanded from roughly 25,000 respondents from 21 countries in Wave 1 (1981-1984) to more than 100,000 respondents from 87 countries across all waves.¹ Individual participants were contacted by a professional survey organization in their home countries and asked to respond to a series of questions about their values and beliefs toward a range of local, regional, and national issues and institutions. Demographic information was also solicited from participants. All interviews were conducted in the native language of respondents, after which the data were coded and compiled into publicly available data sets.² Samples within each country are intended to be representative of the national adult (18 and older) population, with weights provided to correct for over-sampling of under-represented groups and cross-national differences in sample size (intra-nation responses scaled to n = 1,500). Although the sample is disproportionately Western and developed, a significant number of less developed and non-Western nations are represented.

To control for correlates of cross-national homicide, data from WVS aggregated to the national level as weighted averages were merged into a data set with other structural indicators commonly used in past studies (e.g., Bjerregaard & Cochran, 2008a, 2008b; Messner & Rosenfeld, 1997; Savolainen, 2000). Structural indicators were drawn from the United Nations, World Bank, World Health Organization, International Labour Office, and CIA World Factbook. Despite limitations discussed widely elsewhere, these data provide sufficient consistency to permit analysis of variation between nations (LaFree, 1999; Neapolitan, 1997). Consistent with past cross-national research on homicide, the number of nations for which most data were available was 35. This sample size is comparable with other published cross-national studies (Nivette, 2011). Data used in the analysis have been provided in the Appendix.

Dependent Variable

The bulk of cross-national research has examined homicide rates (per 100K) as a dependent variable, because less serious forms of instrumental crime are likely to suffer from inconsistencies in legal definitions and reporting across cultural contexts. In contrast, homicide is considered to be the most reliable indicator of antisocial behavior across historical and cultural units, as its definition has remained relatively consistent. Moreover, given its seriousness, it is very likely to be reported or detected and reflected in official statistics. Paradoxically, most critiques of Mertonian anomie theory have noted one of its primary limitations as the inability to account for non-instrumental crime (Kornhauser, 1978); however, Merton offers a much broader scope for classical anomie theory than has traditionally been recognized. Specifically, although the driving theoretical forces are deeply intertwined with economic factors, and have consequently been presumed to primarily drive “instrumental” crime, Merton (1938) suggests that “antisocial behavior ensues on a considerable scale” (p. 680) when cultural emphases on material goals is blocked by structural inequality. This viewpoint resonates with developments in the contemporary literature exploring anomie theory and its intellectual progeny, which have only recently started to seriously explicate how anomie can account for other forms of non-instrumental criminal violence via their impact on societal institutions (see especially, Messner & Rosenfeld, 2007; Stults & Baumer, 2008). Considering Merton’s concern with “anti-social behavior” noted in the quote above and contemporary efforts to expand beyond instrumental crime—critiques of anomie theory being limited to instrumental crimes take on less relevance (Stults & Baumer, 2008). Specifically, inasmuch as a society lacks sufficient social constraints resulting from structural imbalances, this is likely to have broad consequences for all types of crime. Consider, for example, the relationship between concentrated disadvantage and homicide rates in the United States. Furthermore, previous research on institutional anomie theory—which shares considerable overlap with classical anomie—has examined homicide as the dependent variable; thereby establishing the utility homicide as a dependent variable in tests of anomie theories (Bjerregaard & Cochran, 2008a, 2008b; Messner & Rosenfeld, 1997; Savolainen, 2000). Thus, consistent with the cross-national literature and recent developments in research on anomie theory, we treat the national homicide rate (per 100K) as our outcome measure. Specifically, we utilize the average United Nations (UN) homicide rate (per 100K) for the years 2005 to 2008 (the most recent years of availability for WVS data).

Measuring Materialism and Anomie

As discussed earlier, Merton’s notion of cultural patterning has not been empirically assessed. To operationalize this concept, we developed two unique sets of typologies representing the three types of societies discussed in Merton’s seminal work (stable, deinstitutionalized, and ritualistic). To create these typologies, it was first necessary to identify variables measuring the independent dimensions of materialism (goals) and anomie (means), which combine to define the aforementioned societal types.

The first step in developing the typologies was to carefully examine the variables available in WVS data. Using theory to guide inclusion of items in factor analysis with varimax rotation (not presented here in the interest of space), three variables were identified as capturing the independent dimensions of materialism and anomie critical to Merton’s definition of societal types. One item measures materialism (single item), and two items measure alternative dimensions of anomie that are consistent with Merton’s theory and subsequent empirical measurement—demoralization (eigenvalue = 3.13) and deinstitutionalization (eigenvalue = 2.76). These measures of societal dimensions and the process for combining them into typologies are discussed in detail below.

Materialism

Societal value of economic success is featured prominently in Merton’s theoretical framework. However, when considered in a contemporary global context, measurement of materialism is complicated. Here, we use a single item from the WVS that asked respondents to report the degree to which they felt increased future emphasis on money and material possessions was good (2), didn’t mind (1), or bad (0). In doing so, we capture the full range of possible cultural emphases on materialism, including the possibility of antimaterialistic values that might be associated with more traditional or ritualistic societies.

Dimensions of anomie

Equally prominent in Merton’s theoretical framework is the concept of anomie. In as much as a society has de-emphasized conventional methods of attaining culturally prescribed goals, anomie is indicated. A number of items within WVS measure the degree of acceptance or rejection of institutionalized means. Factor analyses (available on request) indicated that two separate dimensions of anomie characterized the data. As such, summated scales were created to measure each of these distinct conceptual operationalizations of anomie—demoralization and deinstitutionalization (as discussed below).

Demoralization

Drawing on the work of R. Zhao and Cao (2010) and supported by factor analysis using varimax rotation, we operationalize demoralization as the level of support for minor infractions that avert economic costs or afford economic benefits to those who undertake them. Specifically, respondents were asked the degree to which each of the following was “justifiable” (1-10): claiming undeserved benefits, avoiding fares on public transport, cheating on taxes, and accepting a bribe in the course of one’s duties. This is consistent with Merton’s notion that in unstable societies, individuals are willing to compromise means when pursuing economically beneficial ends. When combined, these indicators comprise a scale with an alpha reliability of .867 (eigenvalue = 3.13).

Deinstitutionalization

Within the WVS, a number of indicators assess the degree to which hard work is considered essential for individuals and society. A stronger work ethic, as evidenced by these measures, is indicative of a society that has a strong value of institutionalized means as envisioned by Merton. After reversing the coding to reflect deinstitutionalization (5 = strongly disagree; 1 = strongly agree), we combine the following Likert-type items into a summated scale of deinstitutionalized means (eigenvalue = 2.76, α = .892): need a job to develop talents, humiliating to receive money without working for it, people who do not work turn lazy, work is a duty toward society, and work should come first even if it means less spare time. This is consistent with Merton’s notion that stable societies are characterized by a relatively strong emphasis on pursuing material ends through conventional means.

Operationalizing Societal Types

Utilizing the indicators of cultural materialism, and the two dimensions of anomie (demoralization and deinstitutionalization) described above, two separate sets of typologies were developed to capture each dimension of anomie. The general approach to operationalization entailed identifying societies that had imbalances between materialism and anomie—which, when combined, define the respective societal types identified by Merton (deinstitutionalized OR demoralized | stable | ritualist).

Given that our goal was to assess societal deviations from normal, all three variables were examined for normality prior to creation of typologies (using histograms and Tukey’s, 1977, ladder of powers). It was determined that the base measures of demoralization and deinstitutionalization were statistically normal; however, materialism was negatively skewed. To normalize materialism, the variable was cubed (^3), prior to creation of the typologies utilized in the analysis. Two sets of typologies were created using the variables noted above—one set based on the demoralization indicator and paired with the materialism^3 variable and another set based on the deinstitutionalization indicator and paired with the transformed materialism variable (see detailed discussion below). This resulted in two sets of dummy variables for each societal type. Taken together, these six dummy variables have the benefit of parsimoniously capturing the joint influences of both materialism and anomie and capturing alternative conceptualizations of anomie reflected in the empirical literature.³ Operationalization of each type is discussed, respectively, as the “demoralization-based” typology (includes demoralization indicator discussed above) and the “deinstitutionalization-based” typology (includes deinstitutionalization indicator discussed above).

Demoralization-Based Typology

Using the materialism^3 and demoralization variables, dichotomies representing each societal type were created as follows.

Demoralized

Any society exhibiting a value one standard deviation above the mean on either materialism or demoralization was coded as 1, with all other values being coded as 0. This captures the existence of a societal level imbalance in which either materialism or the acceptability of engaging in deviant behaviors for personal gain is abnormally high. Of all nations included in the sample, 28.6% (n = 10) fell within this typology.

Stable (using demoralization)

All societies, within one standard deviation of the mean on both materialism and demoralization were coded as 1, with all other values being coded as 0. This captures the existence of a relative balance between cultural goals of materialism and constraints on the means for achieving those goals. Of all nations included in the sample, 45.7% (n = 16) fell within this typology.

Ritualist (using demoralization)

Any society exhibiting a value one standard deviation below the mean of either materialism or demoralization was coded as 1, with all other values being coded as 0. This captures the existence of a means/goals balance that either de-emphasizes material goals or over-emphasizes strong prohibition of deviant means for achieving these goals. Of all nations included in the sample, 25.7% (n = 9) fell within this typology.

Deinstitutionalization-Based Typology

Using the materialism^3 and deinstitutionalization variables, dichotomies representing each societal type were created as follows.

Deinstitutionalized

Any society exhibiting a value one standard deviation above the mean on either materialism or demoralization was coded as 1, with all other values being coded as 0. This captures the existence of a societal level imbalance in which either over-emphasis of materialism or the de-emphasis of achieving these goals through conventional means has occurred. Of all nations included in the sample, 20% (n = 7) fell within this typology.

Stable (using deinstitutionalization)

All societies, within one standard deviation of the mean on both materialism and demoralization, were coded as 1, with all other values being coded as 0. This captures the existence of a relative balance between cultural goals of materialism and conventional means for achieving those goals. Of all nations included in the sample, 54.3% (n = 19) fell within this typology.

Ritualist (using deinstitutionalization)

Any society exhibiting a value one standard deviation below the mean of either materialism or demoralization was coded as 1, with all other values being coded as 0. This captures the existence of a means/goals imbalance that either de-emphasizes material goals or over-emphasizes conventional means for achieving these goals. Of all nations included in the sample, 25.7% (n = 9) fell within this typology.

Measuring Inequality and Opportunity

Classical anomie theory posits a critical role for inequality. Specifically, inasmuch as a society has an inequitable distribution of wealth, this indicates a potentially uneven opportunity structure that is likely to contribute to anomie and higher levels of crime. All published macro-level studies of classical anomie have used indicators of inequality of opportunity as a proxy for blocked opportunity (Bennett & Basiotis, 1991; Chamlin & Cochran, 2005, 2006; Cochran & Bjerregaard, 2012; Nivette, 2011). In seeking to assess the influence of opportunity specified by anomie theory, past studies have used a variety of indicators to assess inequality: the Gini coefficient, ratio of income between the richest and poorest segments of the population, Gross Domestic Product (GDP) or Gross National Income (GNI) per capita, and purchasing power parity (Altheimer, 2007, 2008; P. Blau, 1977; J. Blau & Blau, 1982; Krohn, 1976; Pratt & Godsey, 2003; Savolainen, 2000). A debate exists in the literature about which measure is superior, and any measure is likely to have its own unique problems.

Seeking to assess diverse indicators of inequality, we combine two common indicators of inequality: the Gini coefficient and a ratio-based measure of income inequality. A past problem with the Gini coefficient has been that it is not widely available across nations for a consistent block of years; however, the Standardized World Income Inequality Database (SWIID) has compiled data on the Gini coefficient for 171 nations. Corresponding with the time frame for which the homicide rate and WVS data were most recently available, the average of Gini coefficients for data available between 2005 and 2008 was used. As an additional measure of inequality, we use the ratio of median incomes between the richest and poorest 20% used by Pratt and Godsey (2003) and Altheimer (2007, 2008). Seeking to maximize the number of data points available, we combine these indicators into a scale (α = .90, eigenvalue = 1.7).

Control Variables

Sex ratio

Merton takes no clear position on the role of demographic factors in crime; however, sex ratio has been shown to be an important predictor of cross-national rates of crime (Barber, 2000; Guttentag & Secord, 1983; Messner & Sampson, 1991; Schacht, Rauch, & Mulder, 2014; South & Messner, 1987). Specifically, although counter-intuitive, it has been found that a higher ratio of females-to-males leads to higher levels of crime when examined cross-nationally. As such, it is standard practice to include sex ratio (males to females) as a control variable within cross-national analyses of homicide (Altheimer, 2007, 2008; Guttentag & Secord, 1983; Messner & Sampson, 1991; Pratt & Godsey, 2003; Savolainen, 2000; Schaible & Hughes, 2011; South & Messner, 1987).

Development

Although Merton does not posit a clear role for development per se, variability in development is likely to have an impact within a modern global context. This has been widely supported in the cross-national literature, which has found consistent effects of modernization and development on anomie (R. Zhao & Cao, 2010) and levels of crime (Bennett, 1991; LaFree & Drass, 2002; Messner, 1982, 1986). Our measure of modernity parallels Chamlin and Cochran’s (2006). Using factor analysis with varimax rotation, a single component with an eigenvalue of 4.7 was identified. The following items loaded highly on this scale (α = .95): % urban, % 15-24, phone lines per capita, electricity consumption (KWH per capita); average years of education for adults; Human Development Index (HDI) components (2005): GDP per capita; % of GDP spent on health, social, education programs; life expectancy index. In addition, infant mortality, which Pridemore (2008, 2011) has identified as an important indicator of poverty/absolute deprivation, also loaded highly with the factors above and was included in the scale. Because a population estimate of individuals in their crime prone years is included, it also serves as an important control for the influence of the age structure of the population (Gartner, 1990; Gartner & Parker, 1990; Pampel & Gartner, 1995).

Analytical Procedures

The process underlying the generation of crime is more likely a Poisson process than a random one (D’Unger, Land, McCall, & Nagin, 1998; Land, McCall, & Nagin, 1996; Osgood, 2000). Moreover, because homicide is among the rarest of all criminal events, both the number and rate are likely to take on a Poisson distribution. In other words, within a discrete period of time, most aggregate units will have both a small count and rate of homicide, while a few will have unusually high rates of homicide. Consider, for example, the distribution of homicide across census tracts in the United States—within any given year, most have a very low or zero value, although a very small minority have a very high count and/or rate (see Lee & Ousey, 2001; Osgood, 2000; Osgood & Chambers, 2000). The same applies to homicide rates examined cross-nationally. In other words, most countries have very low rates of homicide in any given year; however, a very small fraction of countries has very high levels of homicide. Thus, the distribution of homicides, whether expressed as a rate or count, tends to approximate a Poisson distribution more than they do a normal distribution (Chamlin & Cochran, 2006). This poses a number of problems from a statistical perspective.

The primary consequence of the skewed distribution of rare events such as homicide rates is that it produces abnormal error and covariance structures that are likely to be non-linear, contribute to heteroskedasticity, and violate traditional assumptions of normality. As such, traditional ordinary least squares (OLS) methods are inappropriate. Although OLS with log transformed homicide rates have been utilized to overcome the problems noted above, such approaches risk failing to capture the complex and non-linear error structures that are likely to exist within rare event data (Gardner, Mulvey, & Shaw, 1995; Wooldridge, 1997). As such, contemporary criminologists have looked to the broader family of generalized linear models (GLM or GLiM), which are specifically designed to address the more complicated error structures of rare event data (McCullagh and Nelder, 1989). The following quote from Maume and Lee (2003, p. 1158) succinctly summarizes the rationale:

Current practice in the macrolevel criminological literature is to employ a Poisson-based estimation strategy (see Lee & Ousey, 2001; Osgood, 2000; Osgood & Chambers, 2000). Poisson estimators are well suited for rare event data because even in the face of skewed distributions, they still provide more efficient estimates than ordinary least-squares regression.

Although Poisson and negative binomial models (both extensions of GLM) are generally deemed superior for handling rare event data, there is very little guidance on which variant is best for any given situation. Key considerations are whether equidispersion exists in the data (variance is equal to the mean) and which model best accounts for error that cannot be explained by the model. To address the problem of over-dispersion and model error with count data, most criminologists have utilized negative binomial regression. Chamlin and Cochran (2006) note,

Because there is no a priori reason to assume that cross-national differences in homicide rates can be completely accounted for by the conventional Poisson regression model, it is considered prudent to also calculate the negative binomial variant of this regression model. (p. 244)

Although negative binomial regression has generally been utilized to examine count data, it has also been adapted to rate data (Hilbe, 2011; Long 1997). This is done through a relatively simple transformation, which involves including a term in the equation that logs the deflator that would ordinarily be utilized for count data (i.e., population). Given the strong positive skew of our dependent variable, the superior capabilities of GLM models to account for resultant complex error structures, and the capacity for negative binomial models to account for rate data and error not explained by the model, we use negative binomial regression to examine homicide rates (per 100K) as the dependent variable.

Drawing on the literature and reasoning noted above, we apply negative binomial regression to assess the degree to which coefficients for the relationship between societal types and homicide rates are significant in the expected directions, while controlling for known covariates of homicide.⁴ Based on H1, we expect a significant negative relationship between “stable” types and homicide. Based on H2, we expect a significant positive relationship between “demoralized or deinstitutionalized” types and homicide. Based on H3, we expect no significant relationship between “ritualist” type societies and homicide. Similarly, we expect inequality and other indicators of blocked opportunity to exhibit significant independent effects on levels of homicide; however, we expect that effects of inequality will be conditioned by the societal patterns of means-ends integration, in a manner consistent with Merton’s discussion noted previously. Specifically, consistent with H4, we expect a significant effect for the multiplicative interaction between both demoralized and deinstitutionalized types and inequality, but no significant interactions between inequality and stable or ritualist types. Thus, inequality is only likely to have a strong and clear conditioning effect in deinstitutionalized/demoralized societies.

Results

Descriptive statistics and bivariate correlations are presented in Table 1. Descriptive statistics indicate that all variables (except homicide) were approximately normally distributed after transformations were applied. Most societies were categorized as “stable” across both measures of means/ends integration. When utilizing the demoralization-based indicator of societal type, 45.7% of societies were classified as “stable”; similarly, when utilizing the deinstitutionalization-based indicator, 54.3% of societies were stable. Only 20% of societies were categorized as deinstitutionalized, although 28.6% fell into the demoralized category. In all, 25.7% of societies fell into the “ritualist” category under both measures.

Table 1.

Descriptive Statistics and Correlations.

		M	SD	Minimum	Maximum	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)	(10)	(11)	(12)
(1)	UN homicide rate (2005-2008)	8.04	11.24	0.67	44.10	1.00
(2)	Inequality Scale ((1 − Max)³ − 1)	−288.3	94.1	−485.9	−61.1	.60**	1.00
(3)	Development index	0.13	0.71	−1	1.81	−.42*	−.36*	1.00
(4)	Sex ratio (females:males)	50.63	1.17	48.12	53.85	.05	.07	.29	1.00
(5)	Materialism³ (continuous)	9.13	3.78	1.14	15.97	−.27	.11	.49**	.19	1.00
(6)	Demoralization (continuous)	−0.08	0.84	−1.76	1.55	.31	.35*	.00	.14	−.02	1.00
(7)	Deinstitutionalization (continuous)	−0.10	0.80	−1.59	2.02	.08	.16	−.72**	−.36	−.24	−.35	1.00
(8)	Stable type (demoralization-based)	0.40	0.50	0	1	−.18	−.12	.23	−.14	.11	−.12	−.11	1.00
(9)	Stable type (deinstitutionalization-based)	0.49	0.51	0	1	.19	.40*	−.03	.13	.11	.46*	−.09	.26	1.00
(10)	Demoralized type	0.29	0.46	0	1	.35*	.18	−.27	.14	−.39*	.70**	−.06	−.52**	.14	1.00
(11)	Deinstitutionalized type	0.20	0.41	0	1	.03	−.34*	.07	.10	−.49**	−.01	−.35*	−.12	−.49**	.32	1.00
(12)	Ritualist type (demoralization-based)	0.26	0.44	0	1	−.13	−.02	.16	.12	.53**	−.39*	.09	−.48*	−.31	−.37*	−.29	1.00
(13)	Ritualist type (deinstitutionalization-based)	0.26	0.44	0	1	−.17	−.10	−.04	−.18	.32	−.37*	.42*	−.08	−.57**	−.37*	−.29	.55*

Note. UN = United Nations.

All control variables were significantly correlated with the UN homicide rate (2005-2008) in the expected direction, except sex ratio that did not emerge as a significant variable in the bivariate correlations. Only the deinstitutionalized societal type was significantly correlated with the UN homicide rate. The bivariate correlations with the two indicators of “stable” societies were in opposite directions but not significant. Both indicators of “ritualist” (demoralization- and deinstitutionalization-based) societies were correlated with homicide but non-significant. Both development and deinstitutionalization were significantly negatively correlated with the inequality index. Dummies for societal type were significantly negatively correlated with one another. As such, it was necessary to enter the type of dummies separately in subsequent equations to avoid multicollinearity. No variance inflation factor (VIF) test exceeded three for any of the regression equations.⁵

Further analyses were conducted to select the appropriate statistical procedure. Likelihood ratio tests of the assumption that α = 0 were all beyond p < .001, indicating that over-dispersion was present, and that negative binomial models were the most appropriate for addressing underlying data issues. Similarly, Akaike information criterion (AIC) levels were low comparable with alternative models (results not shown) and indicate that the model fit was superior for these data. As further support for our findings, results from OLS with Huber–White correction of standard errors, over-dispersed Poisson models, and negative binomial results were all nearly identical and led to the same substantive conclusions.

In the models presented in Table 2, each societal type is entered separately with all controls. Control variables exert effects on homicide in the expected directions across all models. Consistent with past literature (Altheimer, 2007, 2008; Bennett, 1991; P. Blau, 1977; J. Blau & Blau, 1982; Chamlin & Cochran, 2005, 2006; LaFree, 1999; Messner, 1982, 1986; Neapolitan, 1997; Nivette, 2011; Pratt & Cullen, 2005; Savolainen, 2000), higher inequality consistently predicts higher homicide rates when controlling for other factors; similarly, higher levels of development correspond with lower rates of homicide across societies. Consistent with the counter-intuitive finding of past literature (Antonoccio & Tittle, 2007; Messner & Sampson, 1991, Schaible & Hughes, 2011; South & Messner, 1987), sex ratio is a strong and consistent predictor of levels of homicide with a higher ratio of females to males predicting higher levels of homicide.

Table 2.

Negative Binomial Regression for Independent Effects.

	M1	M2	M3	M4	M5	M6	M7
	coef/se	coef/se	coef/se	coef/se	coef/se	coef/se	coef/se
Inequality Scale ((1 − Max)³ − 1)	0.008***	0.008***	0.008***	0.008***	0.009***	0.008***	0.008***
Inequality Scale ((1 − Max)³ − 1)	(0.001)	(0.001)	(0.001)	(0.001)	(0.001)	(0.001)	(0.001)
Development index	−1.266***	−1.234***	−1.239***	−1.227***	−1.186***	−1.264***	−1.259***
Development index	(0.237)	(0.242)	(0.239)	(0.240)	(0.232)	(0.237)	(0.234)
Sex ratio (females:males)	0.229***	0.181**	0.235***	0.190***	0.202***	0.230***	0.222***
Sex ratio (females:males)	(0.103)	(0.098)	(0.101)	(0.096)	(0.099)	(0.104)	(0.104)
Stable type (demoralization-based)		−0.428**
Stable type (demoralization-based)		(0.228)
Stable type (deinstitutionalization-based)			−0.243
Stable type (deinstitutionalization-based)			(0.257)
Demoralized type				0.433***
Demoralized type				(0.201)
Deinstitutionalized type					0.624***
Deinstitutionalized type					(0.275)
Ritualist type (demoralization-based)						−0.019
Ritualist type (demoralization-based)						(0.259)
Ritualist type (deinstitutionalization-based)							−0.166
Ritualist type (deinstitutionalization-based)							(0.263)
Intercept	−7.790*	−5.043	−7.739*	−5.978	−6.248	−7.834*	−7.430
Intercept	(5.251)	(5.049)	(5.173)	(4.863)	(5.057)	(5.289)	(5.307)
/lnalpha	−1.712***	−2.063***	−1.775***	−2.064***	−1.934***	−1.708***	−1.702***
/lnalpha	(0.505)	(0.621)	(0.526)	(0.615)	(0.558)	(0.506)	(0.498)
AIC	184.590	183.451	185.707	182.363	181.468	186.584	186.191
Observations (n)	35	35	35	35	35	35	35

Note. AIC = Akaike information criterion.

p < .15. **p < .10. ***p < .05.

The effect of societal types is consistent with the effects hypothesized by Merton. Specifically, in support of H1, those societies with the most balanced integration of means and ends—the stable types—benefit from lower levels of homicide when controlling for other known correlates. However, only the demoralization-based indicator of “stable” type societies emerges as significant. Similarly, in support of H2, homicide rates are significantly higher in societies that have high materialism paired with either excessive levels of demoralization or deinstitutionalization. Finally, in support of H3, neither typology for ritualist societies exhibits a significant relationship with homicide rates. Taken together, the findings are consistent with Merton’s notion that imbalance in the social and cultural structure need not necessarily result in higher homicide rates, but only tends to do so when there is an imbalance in which either means are de-emphasized or materialism excessive.

In Table 3, we examine support for H4, or the degree to which cultural patterns multiplicatively interact with inequality in the opportunity structure. The patterns of relation between control variables and homicide rates remain consistent with the previous models and past research. Similarly, the independent effects of cultural patterns are largely unchanged by the entry of interaction variables (although independent effects of deinstitutionalization are no longer significant). However, contrary to H4, deinstitutionalization and inequality interact to have a significant negative effect on homicide rates, rather than the expected positive effect. Taken together, these findings are contrary to Merton’s propositions, but consistent with past findings examining lower units of analysis (Baumer & Gustafson, 2007). This suggests that the effects of inequality are largely independent of the means/ends integration. In other words, the effects of inequality do not vary significantly by the cultural patterns of means/ends mal-integration. This is consistent with past literature, which has consistently failed to provide clear support for the existence of relationship between inequality and anomic conditions at the macro-level.

Table 3.

Negative Binomial Regressions for Interaction Effects.

	M1	M2	M3	M4	M5	M6
	coef/se	coef/se	coef/se	coef/se	coef/se	coef/se
Inequality Scale ((1 − Max)³ − 1)	0.008***	0.008***	0.007***	0.007***	0.007***	0.008***
Inequality Scale ((1 − Max)³ − 1)	(0.001)	(0.001)	(0.002)	(0.002)	(0.001)	(0.002)
Development index	−1.236***	−1.229***	−1.240***	−1.223***	−1.449***	−1.276***
Development index	(0.244)	(0.239)	(0.233)	(0.221)	(0.246)	(0.246)
Sex ratio (females:males)	0.181**	0.193***	0.244***	0.256***	0.231***	0.220***
Sex ratio (females:males)	(0.099)	(0.097)	(0.103)	(0.104)	(0.096)	(0.104)
Stable type (demoralization-based)	−0.416*
Stable type (demoralization-based)	(0.275)
Stable (demoralization-based) × Inequality	−0.000
Stable (demoralization-based) × Inequality	(0.002)
Demoralized type		0.397**
Demoralized type		(0.228)
Demoralized type × Inequality		0.001
Demoralized type × Inequality		(0.002)
Ritualist type			0.016
Ritualist type			(0.258)
Ritualist type × Inequality			−0.004
Ritualist type × Inequality			(0.004)
Stable type (deinstitutionalization-based)				−0.280
Stable type (deinstitutionalization-based)				(0.262)
Stable type (deinstitutionalization-based)				0.005
Stable type (deinstitutionalization-based)				(0.004)
Deinstitutionalized type					0.359
Deinstitutionalized type					(0.281)
Deinstitutionalized type × Inequality					−0.012***
Deinstitutionalized type × Inequality					(0.005)
Ritualist type (deinstitutionalization-based)						−0.167
Ritualist type (deinstitutionalization-based)						(0.263)
Ritualist type (demoralization-based) × Inequality						0.001
Ritualist type (demoralization-based) × Inequality						(0.005)
Intercept	−7.650*	−8.215**	−10.744***	−11.430***	−10.244***	−9.545**
Intercept	(4.997)	(4.910)	(5.221)	(5.284)	(4.905)	(5.292)
/lnalpha	−2.053***	−2.034***	−1.767***	−1.738***	−2.158***	−1.710***
/lnalpha	(0.632)	(0.609)	(0.519)	(0.498)	(0.591)	(0.502)
AIC	185.444	184.236	187.818	185.804	179.325	188.134
Observations (n)	35	35	35	35	35	35

Note. All variables were centered prior to creation of interaction terms; AIC = Akaike information criterion; se = standard error; coef = coefficient.

p < .15. **p < .10. ***p < .05.

Discussion

This study examined Merton’s anomie theory in a cross-national sample of nations. Four hypotheses were tested on the link between the patterns of means/end integration discussed by Merton and homicide. The findings were generally supportive of Merton’s propositions. In partial support of H1, stable societies benefit from lower levels of homicide with both typologies for “stable” possessing a negative valence but only the demoralization-based stable type achieving significance. In support of H2, deinstitutionalized and demoralized societies were found to have significantly higher rates of homicide. H3 was supported by the absence of a significant relationship between ritualist types and homicide. However, in clear contradiction to H4, interactions between inequality and cultural type did not support the existence of interactive effects. We believe that these findings contribute to the advancement of classical anomie and cross-national criminology and have implications for research in this area.

The findings from this exploratory study, when considered with those recently reported by Baumer and Gustafson (2007), suggest that Merton’s theory merits further examination in the criminological literature. Although revisions of the theory have garnered attention in recent years, the macro-level propositions of classical anomie theory have not received adequate attention. Our results suggest that Merton’s theory still holds promise for expanding knowledge about cross-national variation in crime and should not yet be thrown in the criminological dustbin.

Particularly noteworthy was strong support for Merton’s proposition that homicide is higher in deinstitutionalized and demoralized societies and lower in stable societies, with ritualist societies exhibiting no clear relationship to levels of homicide. This provides credence to the notion that cultural patterns have direct implications for societal levels of homicide and raises questions about what other cultural patterns might be important for explaining cross-national variation in homicide. Our typology of cultural patterns explained homicide as well as other well-established correlates of violence. This suggests that both cultural and structural factors are important in explaining macro-variation in homicide, especially at the societal level. Earlier cross-national research has been particularly effective at identifying the structural predictors of homicide, but less is known about cultural predictors or their intersections. This may be due to underdeveloped theoretical articulations of the cultural process that influence homicide rates, as well as the fact that it has been difficult to operationalize the important predictors of cultural processes at the cross-national level. Results of this study suggest that researchers can continue to look to classical anomie theory for guidance on understanding the link between macro-level processes and homicide. Furthermore, the development of the WVS and other data sets is making the examination of such processes more feasible. Greater consideration of cultural processes will provide a more complete understanding of the relationship between social organization and violence (Karstedt, 2001).

The findings also provide support for the methodological approach taken in this study. The small samples, commonly used in cross-national criminological research, often limit degrees of freedom and the ability of researchers to test for complex statistical interactions. Similarly, they necessitate special statistical treatment. This necessitates innovative approaches to examining such relationships. One way to get around this problem—and the approach taken here—is to create typologies that combine complex theoretical constructs while also increasing degrees of freedom. The increasing statistical sophistication of the field may cause some to view simpler approaches suspiciously, but making greater use of typologies provides a practical solution to the small sample dilemma that researchers often face in cross-national analyses.

Although deinstitutionalization directly affected homicide, interactions with inequality in the opportunity structure did not emerge as significant, as predicted by classical anomie. These findings mirror those recently reported by Baumer and Gustafson (2007) and lead to questions concerning why no such interactions were found. Two explanations are provided here. First, it is possible that the likelihood of an interaction between deinstitutionalization and blocked opportunity is contingent on the nature of the blocked opportunity. Merton (1938) suggests the manner that that social structure predisposes toward crime in deinstitutionalized societies is contingent on two factors:

First, such antisocial behavior is in a sense “called forth” by certain conventional values of the culture and by the class structure involving differential access to the approved opportunities for legitimate, prestige-bearing pursuit of the culture goals . . . The second consideration is of equal significance. Recourse to the first of the alternative responses, legitimate effort, is limited by the fact that actual advance toward desired success-symbols through conventional channels is, despite our persisting open-class ideology, relatively rare and difficult for those handicapped by little formal education and few economic resources. (p. 679)

This statement suggests that high levels of economic inequality may not elevate rates of crime in deinstitutionalized societies if there is some degree of opportunity to advance toward prestige-bearing culturally defined success symbols. This may also suggest that measures of economic inequality used here, as well as in most cross-national criminological research, do not adequately account for the type of blocked opportunity noted by Merton. The second possible explanation for why no interaction was found is that deinstitutionalization simply does not interact with blocked opportunity to influence rates of homicide in the manner proposed by Merton. If this finding continues to emerge in research on classical anomie theory, then it may be necessary for the theory to be refined.

Limitations

Despite the contribution that this study provides to the criminological literature, several important limitations should be noted. First, this study examined total rates of homicide as the dependent variable. Merton’s original propositions, however, specifically linked anomie to instrumental crimes. Future research on this topic should examine more precise indicators of homicide that are disaggregated by motive, as well as other forms of instrumental crime. Second, it is plausible that the degree to which crime is reported across societies is a function of structural and cultural processes. Thus, the approach to crime reporting may be different in demoralized or deinstitutionalized societies when compared with more stable societies. In light of this fact, future research on anomie should examine crime data from self-report surveys and other unofficial sources data. Third, as noted above, more sophisticated measures of social stratification may be necessary to tease out potential interactions between blocked opportunity and deinstitutionalization. Future research should use alternative indicators of blocked opportunity that better account for societal levels of social stratification. Fourth, the number of nations examined, although similar to previous cross-national studies, was small. This inevitably limits the ability to conduct statistical tests and risks failing to detect real effects because of weak power. Although we did find significant effects, future research should look to examine Merton’s propositions in a larger sample of nations. Finally, the data from WVS utilized to operationalize cultural features of societies were only available for one time span. As such, time-series analysis was precluded. Future analyses should seek to examine how transitions in societal types over time have a differential influence on levels of homicide and other types of crime.

Conclusion

Notwithstanding these limitations, we believe that our study makes an important contribution to the extant cross-national criminological literature. To our knowledge, this study represents the first attempt to test the cross-national propositions of classical anomie theory. Undoubtedly, Merton was a scholar with profound insights and much to offer in understanding macro-level processes in crime. Unfortunately, these insights have remained relatively unexplored. Although the present study tests some of these insights, many questions remain to be answered, especially about the relationship between cultural patterns identified by Merton, their interaction with opportunity structures, and consequences for crime and other social problems. We hope that in addressing a number of important questions here, the present study will serve as base and fount for such an exploration.

Footnotes

Appendix

	UN Homicide Rate (2005-2008)	Inequality index ((1 − Max)³ − 1)	Sex ratio (females:males)	Development index	Stable type (demoralization-based)	Stable type (deinstitutionalization-based)	Demoralized type	Deinstitutionalized type	Ritualist type (demoralization-based)	Ritualist type (deinstitutionalization-based)
Albania	3.300	−344.029	50.559	−0.246	0	0	1	1	0	0
Argentina	5.475	−162.279	50.957	0.518	1	1	0	0	0	0
Bangladesh	2.750	−326.464	49.410	−0.796	0	0	0	0	0	0
Bosnia and Herzegovina	1.800	−295.977	51.887	0.192	0	1	0	0	1	0
Brazil	22.550	−95.582	50.705	0.250	0	1	1	0	0	0
Bulgaria	2.400	−340.887	51.544	0.517	0	0	1	1	0	0
Chile	3.575	−210.618	50.537	0.451	0	0	0	0	1	1
China	1.325	−269.359	48.124	−0.154	1	1	0	0	0	0
Finland	2.375	−428.039	51.025	1.350	1	0	0	1	0	0
Georgia	7.450	−246.677	52.848	−0.157	0	1	0	0	1	0
Germany	0.975	−418.874	51.051	1.344	1	1	0	0	0	0
Guatemala	44.100	−140.195	51.240	−0.472	0	1	1	0	0	0
India	3.450	−351.094	48.283	−0.766	0	1	1	0	0	0
Indonesia	8.100	−281.630	50.055	−0.423	0	0	0	1	0	0
Jordan	1.550	−335.995	48.621	−0.128	1	0	0	0	0	1
Kyrgyzstan	8.650	−248.272	50.676	−0.472	1	1	0	0	0	0
Mexico	9.950	−169.597	50.698	0.208	0	1	1	0	0	0
Republic of Moldova	6.850	−283.585	52.458	−0.158	0	0	1	1	0	0
Morocco	1.550	−306.871	50.829	−0.452	1	0	0	0	0	1
Norway	0.675	−375.010	50.364	1.805	0	0	0	0	1	1
Peru	11.125	−165.278	49.865	−0.073	1	1	0	0	0	0
Philippines	6.950	−279.049	49.620	−0.356	0	1	1	0	0	0
Poland	1.350	−310.121	51.698	0.495	1	1	0	0	0	0
Vietnam	1.600	−331.685	50.741	−0.372	1	0	0	0	0	1
Slovenia	0.825	−425.459	51.194	0.945	1	1	0	0	0	0
South Africa	38.300	−61.075	50.750	−0.156	1	1	0	0	0	0
Spain	1.075	−331.634	50.757	1.190	0	0	0	0	1	0
Sweden	1.000	−485.845	50.426	1.572	1	0	0	1	0	0
Turkey	4.100	−289.313	49.736	0.161	0	0	0	0	1	1
Uganda	36.300	−293.734	49.963	−1.004	0	0	1	1	0	0
Ukraine	6.550	−324.399	53.848	0.372	0	1	1	0	0	0
Macedonia, TFYR	2.250	−280.596	50.037	0.191	1	1	0	0	0	0
Egypt	0.750	−358.883	49.692	−0.296	0	0	0	0	1	1
United Republic of Tanzania	24.500	−320.055	50.209	−0.939	0	0	0	0	1	1
Uruguay	6.050	−200.825	51.747	0.556	0	0	0	0	1	1

Note. UN = United Nations; TFYR = The Former Yugoslavian Republic.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Notes

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