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Cross-National Homicide Trends in the Latter Decades of the Twentieth Century: Losses and Gains in Institutional Control?

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Control of Violence

Abstract

This study explores cross-national trends in homicide rates over the 1950–2005 period. At a descriptive level, we apply spline regression to address the following questions: How prevalent were appreciable, sustained increases or decreases in levels of homicide? Among nations characterized by increasing or decreasing homicide levels, how prevalent were reversals in the trends, suggesting homicide cycles? Which nations exhibited homicide cycles, and what can be learned from the timing of increases, decreases, and reversals in homicide levels? Our second overarching objective is to assess Gary LaFree’s hypothesis that national trends in crime reflect changes in the legitimacy of the basic institutions of a society. We focus on the institution that traditionally has been assigned primary responsibility for informal control—the family. The results of our spline regression analyses indicate that sustained, substantial increases in lethal violence were virtually universal in the latter decades of the twentieth century for the sampled nations. At the same time, the majority of nations that exhibited an appreciable upturn in homicide rates also exhibited a distinct turnaround, suggestive of homicide cycles. With respect to the timing of the phases of homicide cycles, we observe that Nordic and northern European nations were in the vanguard for increasing homicides, whereas Central/South American and Caribbean nations exhibited a rise in homicides decades later. Finally, the results of fixed-effects regression models for the pooled, cross-sectional time-series dataset reveal that the divorce rate is a significant, robust predictor of homicide rates, which is supportive of LaFree’s arguments concerning institutional legitimacy, institutional control, and changes in levels of crime.

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Notes

  1. 1.

    For reviews of the cross-national research on homicide up through the mid-1980s, see LaFree and Kick (1986) and Neuman and Berger (1988). Gartner (1995), LaFree (1999), Messner (2003), and Neapolitan (1997) update these earlier reviews with citations to studies conducted in the late-1980s through the 1990s. More recent research is cited below in conjunction with model specification.

  2. 2.

    LaFree and Drass (2002) examined pooled, cross-sectional time-series data to identify “crime booms” for a large cross-national sample. They report that only about a third (35%) of the nations in their sample satisfy all three of their criteria for a “boom:” positive direction, rapid growth, and sustained change. As explained below, we relax the criterion of “rapid growth” given our focus on “appreciable, sustained increases” in homicide in contrast with “booms.”

  3. 3.

    Gary LaFree generously provided us with WHO homicide data from 1950 to 2000. We updated this data file with observations for additional years extending to 2005 where available. The ICD—currently in its tenth revision (ICD-10)—is periodically updated and categories are often changed in these revisions. This occurred for homicide deaths with the implementation of ICD-10. In ICD-10, there is a separate category entitled “Sequelae of assault,” which indicates, “the cause of death, impairment or disability [is] sequelae or ‘late effects,’ which are themselves classified elsewhere. The sequelae include conditions reported as such, or occurring as ‘late effects’ 1 year or more after the originating event.” This category had previously been grouped with the other deaths that were classified as “homicide” (ICD-9 and before). In ICD-10 this category was moved to a separate sub-category under the broader heading of “Sequelae of intentional self-harm, assault and events of undetermined intent.” For our purposes, we have included in the analyses those deaths classified as “Sequalae of assault.” We combined across categories when updating LaFree’s homicide data to encompass more recent years. An account of the development of ICD is available at: http://www.who.int/classifications/icd/en/HistoryOFICD.pdf.

  4. 4.

    Gartner does not include a category for the “political context.” Subsequent research has considered the effects of democracy and democratization on homicide rates. See Karstedt (2006) and LaFree and Tseloni (2006).

  5. 5.

    We are very grateful to the UN Demographic Yearbook team at the United Nations Statistics Division for providing us with electronic files containing data on divorce rates, infant births and deaths, population size, sex ratio, and age structure to supplement figures retrieved online from the United Nations Demographic Yearbook. We also appreciate their expert technical assistance concerning the interpretation of these data. The demographic data from the UN are available from the authors upon request. Information on age structure for the United Kingdom for the years prior to 1982 were obtained from the Office for National Statistics, the executive office of the UK Statistics Authority (United Kingdom 2008).

  6. 6.

    See the extensive review of the literature by Parker et al. (1999) for evidence on the effect of the divorce rate on homicide rates in the United States. See Stretesky et al. (2004) for more recent evidence of the divorce effect on homicide rates for US cities.

  7. 7.

    We recognize that cross-national variation in divorce rates reflects to a large extent the legal and regulatory context. For an extensive discussion of these issues, see the essays in Adams and Trost (2005). A striking example of the impact of legal change in our dataset is an abnormally low number of divorces in Germany in 1978, which reflects the impact of Germany’s Marriage Law Reform Act, passed in 1976. The law established longer “waiting periods” for divorces, which created a 1-year artificial suppression of the divorce rate. We re-estimated the regression analyses reported below with this data point omitted, and the findings for the divorce rates are unchanged. It is of course possible that there are other anomalies in the data that have gone undetected and which bear upon substantive conclusions. We note, however, that the divorce rate is one of the few indicators of family structure that can be used for cross-national, longitudinal analysis, and as noted, there is suggestive evidence that despite measurement error, it may indeed be a useful predictor of homicide trends. Moreover, legal changes pertaining to divorce can themselves be regarded as manifestations of the changing meaning of marriage. Increases in divorce rates concomitant with revisions of the law are thus in some instances indicative of important cultural transformations in the institution of the family. See Cherlin (2004, 852).

  8. 8.

    The specific measure of GDP per capita is the Laspeyeres Index, which is a fixed-base index with 1996 serving as the reference year.

  9. 9.

    The recorded sex ratios for Trinidad and Tobago for 1992, 1993, and 1994 diverge widely from that nation’s time series and are implausible. We accordingly omitted these observations.

  10. 10.

    Following the advice of UN personnel, we used estimated data—including population figures—wherever possible, given that these are best for time-series analyses (personal correspondence). When such data are not available, census and other representative survey data have been used instead. Technical details about data sources and estimation procedures used by the UN are provided in the individual data tables of Demographic Yearbook (http://unstats.un.org/unsd/demographic/products/dyb/dyb2.htm). We used linear interpolation for total population size and age structure when there were gaps in the UN data of less than 4 years. With larger gaps, we used population data from WHO where possible or treated the data as missing.

  11. 11.

    LaFree focuses on declining legitimacy in two institutional realms in addition to the family: the polity and the economy. He maintains that distrust and collective protests undermined political legitimacy, while inequality and inflation undermined faith in the economy.

  12. 12.

    Differencing the variables (measuring them as annual change) removes all trend components. Therefore, we are analyzing short-run relationships between independent and dependent variables. This is necessary to mitigate the problem of spurious regression: regression with difference-stationary variables will find “significant” relationships even when the variables are in fact independent. An exception is if the variables are “co-integrated” (i.e., share the same random-trend component). We conducted co-integration tests. The results indicate that divorce rates and homicide rates may be co-integrated, suggesting that divorce rates increase homicide rates in the long-run as well as in the short-run (the latter results are reported below). The implications (if any) of this tentative finding are not immediately apparent to us, but the issue warrants further attention in the future. We thank Christoph Birkel for bringing this to our attention.

  13. 13.

    In a pooled, cross-sectional time-series analysis based on data for nine nations in east-central Europe 1990–2003, Stamatel (2009) finds no significant effect of divorce rates on homicide rates. She speculates that the discrepancy between her findings and those of Gartner reflects distinctive features of household arrangements for these nations during the communist era (Stamatel 2009, 1442).

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Acknowledgments

We are grateful to Susanne Karstedt, Christoph Birkel, and an anonymous reviewer for comments on earlier drafts of this chapter.

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Authors and Affiliations

  1. Department of Sociology, University at Albany, S. U. N. Y., Albany, NY, USA

    Steven F. Messner & Lawrence E. Raffalovich

  2. Indiana University-Purdue University, Fort Wayne, IN, USA

    Benjamin Pearson-Nelson

  3. University of Albany, S.U.N.Y., Albany, NY, USA

    Zachary Miner

Authors
  1. Steven F. Messner
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  2. Benjamin Pearson-Nelson
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  3. Lawrence E. Raffalovich
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  4. Zachary Miner
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Corresponding author

Correspondence to Steven F. Messner .

Editor information

Editors and Affiliations

  1. Inst. Interdisziplinäre Konflikt- und, Gewaltforschung, Universität Bielefeld, Universitätsstr. 25, Bielefeld, 33615, Germany

    Wilhelm Heitmeyer

  2. European University Institute, Firenze, 50133, Firenze, Italy

    Heinz-Gerhard Haupt

  3. Inst. Interdisziplinäre Konflikt- und, Gewaltforschung, Universität Bielefeld, Universitätsstr. 25, Bielefeld, 33615, Germany

    Stefan Malthaner

  4. Inst. Interdisziplinäre Konflikt- und, Gewaltforschung, Universität Bielefeld, Universitätsstr. 25, Bielefeld, 33615, Germany

    Andrea Kirschner

Appendix: Nations Included in the Sample

Appendix: Nations Included in the Sample

Australiaa

Japana

Austriaa

Luxembourgb

Belgiuma

Mauritiusa

Bulgariaa

Mexicoa

Canadaa

Netherlandsa

Chilec

New Zealanda

Colombiac

Nicaraguab

Costa Ricaa

Norwaya

Czech Republicb

Panamab

Denmarka

Polanda

Dominican Republica

Portugala

El Salvadorb

Singaporea

Estoniab

Spaina

Finlanda

Swedena

Francea

Switzerlanda

Germanya

Thailandb

Greecea

Trinidad and Tobagoa

Hungarya

United Kingdoma

Icelanda

United Statesa

Irelandc

Uruguayb

Israela

Venezuelaa

Italya

 
  1. a Included in both dynamic regressions and spline regressions
  2. b Included in dynamic regressions only
  3. c Included in spline regressions only
  4. Note: Data for Germany prior to reunification pertain to West Germany

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Messner, S.F., Pearson-Nelson, B., Raffalovich, L.E., Miner, Z. (2011). Cross-National Homicide Trends in the Latter Decades of the Twentieth Century: Losses and Gains in Institutional Control?. In: Heitmeyer, W., Haupt, HG., Malthaner, S., Kirschner, A. (eds) Control of Violence. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-0383-9_3

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