When Homicide Statistics Contradict Themselves: A Reproducible Simulation of Within–Between Reversals in Comparative Criminology

Main Article Content

Zul Khaidir Kadir

Abstract

International homicide comparisons routinely place countries with different income levels on the same graph. The association across those countries is sometimes discussed as though it described what happens when income changes inside a country. The two comparisons, however, draw on different information. We examine their distinction through a reproducible simulation, alongside published regional homicide estimates from the United Nations Office on Drugs and Crime. The experiment contains 120 synthetic units observed over 14 periods. A negative between-unit coefficient and a positive within-unit coefficient are imposed in the generating process, then estimated under sampling noise and alternative analytic choices. The reference estimates are −0.606 and +0.516, with a within-minus-between contrast of +1.122 and a unit-bootstrap 95% interval of +1.041 to +1.203. Further simulations examine sampling precision, incomplete coverage and specification changes. The UNODC estimates establish that homicide rates vary across regions. They do not identify an income–homicide relationship. Opposing coefficients in the generated panel demonstrate an inferential possibility, not a reversal observed among actual countries. The resulting contribution is a replicable test of whether the statistical comparison reported in comparative homicide research matches the proposition used to interpret it.

Article Details

Section

Articles

References

Abadie, A., Athey, S., Imbens, G. W., & Wooldridge, J. M. (2023). When should you adjust standard errors for clustering? Quarterly Journal of Economics, 138(1), 1–35. doi.org/10.1093/qje/qjac038

Arellano, M., & Bond, S. (1991). Some tests of specification for panel data — Monte Carlo evidence and an application to employment equations. Review of Economic Studies, 58(2), 277–297. doi.org/10.2307/2297968

Beck, N., & Katz, J. N. (1995). What to do (and not to do) with time-series cross-section data. American Political Science Review, 89(3), 634–647. doi.org/10.2307/2082979

Bell, A., Fairbrother, M., & Jones, K. (2019). Fixed and random effects models — Making an informed choice. Quality & Quantity, 53, 1051–1074. doi.org/10.1007/s11135-018-0802-x

Bell, A., & Jones, K. (2015). Explaining fixed effects — Random effects modeling of time-series cross-sectional and panel data. Political Science Research and Methods, 3(1), 133–153. doi.org/10.1017/psrm.2014.7

Bollen, K. A., & Brand, J. E. (2010). A general panel model with random and fixed effects — A structural equations approach. Social Forces, 89(1), 1–34. doi.org/10.1353/sof.2010.0072

Buil-Gil, D., Pina-Sánchez, J., & Aebi, M. F. (2026). The effect of counting rules on cross-national comparisons of homicide. Social Indicators Research, 181, Article 44. doi.org/10.1007/s11205-025-03802-8

Cameron, A. C., & Miller, D. L. (2015). A practitioner’s guide to cluster-robust inference. Journal of Human Resources, 50(2), 317–372. doi.org/10.3368/jhr.50.2.317

Chon, D. S. (2012). The impact of population heterogeneity and income inequality on homicide rates — A cross-national assessment. International Journal of Offender Therapy and Comparative Criminology, 56(5), 730–748. doi.org/10.1177/0306624X11414813

Curran, P. J., & Bauer, D. J. (2011). The disaggregation of within-person and between-person effects in longitudinal models of change. Annual Review of Psychology, 62, 583–619. doi.org/10.1146/annurev.psych.093008.100356

Eisner, M. (2003). Long-term historical trends in violent crime. Crime and Justice, 30, 83–142. doi.org/10.1086/652229

Fajnzylber, P., Lederman, D., & Loayza, N. (2002a). Inequality and violent crime. Journal of Law and Economics, 45(1), 1–40. doi.org/10.1086/338347

Fajnzylber, P., Lederman, D., & Loayza, N. (2002b). What causes violent crime? European Economic Review, 46(7), 1323–1357. doi.org/10.1016/S0014-2921(01)00096-4

Hamaker, E. L., Kuiper, R. M., & Grasman, R. P. P. P. (2015). A critique of the cross-lagged panel model. Psychological Methods, 20(1), 102–116. doi.org/10.1037/a0038889

Harrendorf, S. (2018). Prospects, problems, and pitfalls in comparative analyses of criminal justice data. Crime and Justice, 47(1), 159–207. doi.org/10.1086/696042

Imai, K., & Kim, I. S. (2019). When should we use unit fixed effects regression models for causal inference with longitudinal data? American Journal of Political Science, 63(2), 467–490. doi.org/10.1111/ajps.12417

Kadir, Z. K. (2026a). Are We Safer, or Just Older? Testing the Demographic Trap Through Cross-National Homicide Rates and Age-Conditional Ranking Instability. Punggawa Global Research – Jurnal Multidisiplin, 1(6). doi.org/10.67707/pgr.v1i6.489

Kadir, Z. K. (2026b). The Cleared-Case Canon – Investigative Selection as a Structural Limit on General Homicide Theory Building. LEXARA – Journal of Law and Legal Studies, 1(2). doi.org/10.67707/lexara.v1i2.197

Kadir, Z. K. (2026c). Criminological Doppelgängers? Similar Starting Homicide Rates and Divergent Change in Six Latin American Countries. LEXARA – Journal of Law and Legal Studies, 1(3). doi.org/10.67707/lexara.v1i3.490

Kadir, Z. K. (2026d). Does Islam Explain Homicide? A Paired Cross-National Comparison of Religion, State Capacity, and Lethal Violence. SIMURGA – Journal of Islamic Studies and Muslim Societies, 1(1). punggawajournal.com/simurga/article/view/89

Kadir, Z. K. (2026e). The Geography of Lethal Violence Escalation – Cross-National Differences in Recorded Homicide and Serious Assault across Structural Contexts. Punggawa Law Review, 1(4). doi.org/10.67707/plr.v1i4.158

Kadir, Z. K. (2026f). The Homicide Hysteresis Problem and Persistent Lethal Violence after Temporary Macroeconomic Shocks. SOCILEXIA – Journal of Social Sciences and Humanities, 1(2). punggawajournal.com/socilexia/article/view/176

Kadir, Z. K. (2026g). The Homicide Visibility Gap – Cross-National Discrepancies between UNODC-Recorded Intentional Homicide and Mortality-Based Violence. Punggawa Global Research – Jurnal Multidisiplin, 1(4). doi.org/10.67707/pgr.v1i4.157

Kadir, Z. K. (2026h). The Social Anatomy of Homicide – Relationships, Situations, and Legal Categories in Indonesia. SOCILEXIA – Journal of Social Sciences and Humanities, 1(1). punggawajournal.com/socilexia/article/view/115

Kadir, Z. K. (2026i). The State Does Not Count the Same Dead – The Politics of Homicide Measurement Across Criminal Justice and Public Health Systems. Punggawa Global Research – Jurnal Multidisiplin, 1(5). doi.org/10.67707/pgr.v1i5.245

Kadir, Z. K. (2026j). The World's Most Dangerous Country May Be a Statistical Illusion – Reassessing the Evidence Behind Homicide Rankings. SOCILEXIA – Journal of Social Sciences and Humanities, 1(4). doi.org/10.67707/socilexia.v1i4.487

King, G., & Roberts, M. E. (2015). How robust standard errors expose methodological problems they do not fix, and what to do about it. Political Analysis, 23(2), 159–179. doi.org/10.1093/pan/mpu015

LaFree, G., & Tseloni, A. (2006). Democracy and crime — A multilevel analysis of homicide trends in forty-four countries, 1950–2000. Annals of the American Academy of Political and Social Science, 605(1), 25–49. doi.org/10.1177/0002716206287169

Lederman, D., Loayza, N., & Menéndez, A. M. (2002). Violent crime — Does social capital matter? Economic Development and Cultural Change, 50(3), 509–539. doi.org/10.1086/342422

Levchak, P. J. (2019). Clarification and refinement of modernization theory — How the global economy impacts homicide rates. Sociological Focus, 52(4), 309–323. doi.org/10.1080/00380237.2019.1668319

Little, R. J. A. (1988). A test of missing completely at random for multivariate data with missing values. Journal of the American Statistical Association, 83(404), 1198–1202. doi.org/10.1080/01621459.1988.10478722

Messner, S. F. (1982). Poverty, inequality, and the urban homicide rate — Some unexpected findings. Criminology, 20(1), 103–114. doi.org/10.1111/j.1745-9125.1982.tb00450.x

Messner, S. F. (1989). Economic discrimination and societal homicide rates — Further evidence on the cost of inequality. American Sociological Review, 54(4), 597–611. doi.org/10.2307/2095881

Messner, S. F., Raffalovich, L. E., & Sutton, G. M. (2010). Poverty, infant mortality, and homicide rates in cross-national perspective — Assessments of criterion and construct validity. Criminology, 48(2), 509–537. doi.org/10.1111/j.1745-9125.2010.00194.x

Mundlak, Y. (1978). On the pooling of time series and cross section data. Econometrica, 46(1), 69–85. doi.org/10.2307/1913646

Neumayer, E. (2003). Good policy can lower violent crime — Evidence from a cross-national panel of homicide rates, 1980–97. Journal of Peace Research, 40(6), 619–640. doi.org/10.1177/00223433030406001

Nivette, A. E. (2011). Cross-national predictors of crime — A meta-analysis. Homicide Studies, 15(2), 103–131. doi.org/10.1177/1088767911406397

Nivette, A. E. (2012). Spatial patterns of homicide and political legitimacy in Europe. International Journal of Comparative and Applied Criminal Justice, 36(3), 155–171. doi.org/10.1080/01924036.2012.670928

Nivette, A. E. (2014). Legitimacy and crime — Theorizing the role of the state in cross-national criminological theory. Theoretical Criminology, 18(1), 93–111. doi.org/10.1177/1362480613499793

Nivette, A. E., & Eisner, M. (2013). Do legitimate polities have fewer homicides? A cross-national analysis. Homicide Studies, 17(1), 3–26. doi.org/10.1177/1088767912452131

Paré, P.-P., & Felson, R. (2014). Income inequality, poverty and crime across nations. British Journal of Sociology, 65(3), 434–458. doi.org/10.1111/1468-4446.12083

Pridemore, W. A. (2011). Poverty matters — A reassessment of the inequality–homicide relationship in cross-national studies. British Journal of Criminology, 51(5), 739–772. doi.org/10.1093/bjc/azr019

Rogers, M. L., & Pridemore, W. A. (2017). How does social protection influence cross-national homicide rates in OECD nations? Sociological Quarterly, 58(4), 576–594. doi.org/10.1080/00380253.2017.1367265

Rogers, M. L., & Pridemore, W. A. (2022). Perceived inequality and cross-national homicide rates. Justice Quarterly, 39(2), 225–251. doi.org/10.1080/07418825.2020.1729392

Rogers, M. L., & Pridemore, W. A. (2023). A review and analysis of the impact of homicide measurement on cross-national research. Annual Review of Criminology, 6, 447–470. doi.org/10.1146/annurev-criminol-030521-102909

Rubin, D. B. (1976). Inference and missing data. Biometrika, 63(3), 581–592. doi.org/10.1093/biomet/63.3.581

Rudolph, M., & Starke, P. (2020). How does the welfare state reduce crime? The effect of program characteristics and decommodification across 18 OECD-countries. Journal of Criminal Justice, 68, 101684. doi.org/10.1016/j.jcrimjus.2020.101684

Santos, M. R., Testa, A., & Weiss, D. B. (2018). Where poverty matters — Examining the cross-national relationship between economic deprivation and homicide. British Journal of Criminology, 58(2), 372–393. doi.org/10.1093/bjc/azx013

Schunck, R. (2013). Within and between estimates in random-effects models — Advantages and drawbacks of correlated random effects and hybrid models. Stata Journal, 13(1), 65–76. doi.org/10.1177/1536867X1301300105

Simonsohn, U., Simmons, J. P., & Nelson, L. D. (2020). Specification curve analysis. Nature Human Behaviour, 4, 1208–1214. doi.org/10.1038/s41562-020-0912-z

Steegen, S., Tuerlinckx, F., Gelman, A., & Vanpaemel, W. (2016). Increasing transparency through a multiverse analysis. Perspectives on Psychological Science, 11(5), 702–712. doi.org/10.1177/1745691616658637

Tuttle, J. (2018). Specifying the effect of social welfare expenditures on homicide and suicide — A cross-national, longitudinal examination of the stream analogy of lethal violence. Justice Quarterly, 35(1), 87–113. doi.org/10.1080/07418825.2017.1293711

United Nations Office on Drugs and Crime. (2025). Levels and trends of criminal and other intentional killings since the UNTOC was adopted in 2000. Research Brief on Transnational Organized Crime, Special Points of Interest, Figure 7, p. 13. United Nations Office on Drugs and Crime.

Similar Articles

You may also start an advanced similarity search for this article.