An Agent-Based Model of Ethnocentrism and the Unintended Consequences of Violence

Abstract

We repurpose an agent-based model of ethnocentrism to show how violence affects people’s willingness to cooperate with members of other groups. We account for extra benefits which arise from interacting with a member of the same culture (‘cultural boosts’) and for mutual gains from cooperative activities (‘public goods’). In environments where one person gains at another’s expense, violence decreases ethnocentrism. However, violence increases ethnocentric behavior when cooperation produces shared benefits. These results point to new empirical questions and contribute to policy discussions regarding the use and reduction of violence.

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Notes

  1. 1.

    Leeson (2005, p. 76) discusses possible reverse causality in the context of institutions and fractionalization, addressing ‘Easterly (2001) who considers the role of institutions in mitigating fractionalization’ by considering ‘the arrow of causation running from low-quality government (i.e., one with poor institutions) to increased fractionalization.’ The current study similarly seeks to answer the question of flow with the narrower focus of violence as it relates to fractionalization along ethnic lines.

  2. 2.

    See Zak and Knack (2001) and Beugelsdijk et al. (2004).

  3. 3.

    For example, Landa (1981, p. 350) suggests that an ‘ethnically homogenous middle man group’ functions as ‘a low-cost club-like institutional arrangement, serving as an alternative to contract law and the vertically integrated firm, which emerged to economize on contract enforcement and information costs in an environment where the legal infrastructure was not well developed.’ Leeson (2005, p. 162) also notes that in ‘small, homogeneous social groups, in which the social distance between actors is minimal, individuals can rely on reputational mechanisms of ex post enforcement to ensure cooperation. The smallness and homogeneity of the group enable the effective flow of information about individuals’ past conduct among its members.’

  4. 4.

    ‘Worse outcomes’ in this sense refer to injuries which could have been treated were there no shortage in the availability of health care go untreated, resulting in more costly future treatment or permanent disability. This affects those with ailments not related to violence as well.

  5. 5.

    Studies such as Nafziger and Auvinen (2002), Abadie and Gardeazabal (2003), Blomberg et al. (2004) and Gates et al. (2012) show empirically that GDP growth and economic development are lower in violent environments. The causal link is difficult to establish: Does violence lead to poor economic outcomes, or do poor economic outcomes produce violence, or both? We do not attempt to identify causality here, we only point out that the negative consequences of violence are consistent with causing worse economic performance.

  6. 6.

    Children that grow up in a violent atmosphere are more likely to have discipline problems; a ‘culture of violence’ is accepted.

  7. 7.

    For example, R&D in firearm production may produce new technologies that can be used in the metalworking industry. However, spending in these areas may have offsetting costs associated with technological adoption (see Duncan and Coyne 2013).

  8. 8.

    A text by Westneat and Fox (2010) on behavioral ecology provides a concise introduction to this field of study.

  9. 9.

    Mihalyi (1984–1985, p. 101) posits that ‘the basic motivations and reasonings for group identification and cohesion may have been formed chiefly as defensive measures against the past, present and expected future negative experiences. In this context, a specific ethnic group is best defined as a social community sharing a common culture which, when the chips are down, commands the loyalty of the members.’

  10. 10.

    There are 2601 patches in the torus used here, which is the population maximum.

  11. 11.

    Lima et al. (2009) show that the ethnocentric strategy prevails even if agents are provided the ability to reproduce sexually according to decision pairs.

  12. 12.

    There is an equal (25%) probability of being assigned each of the four colors. There is also an equal probability (50%) of receiving a C or a D for each of the positions in the strategy pair. (Therefore, there is an equal 25% chance of receiving each of the four strategy combinations.)

  13. 13.

    Immigration ensures the population of the virtual world is never zero. Immigrants are assigned a random color and strategy pair as was done for the initial population.

  14. 14.

    In the gridded virtual world, an agent has a maximum of four direct neighbors which are located in the patches above, below, to the right and to the left. Agents located on the diagonal are excluded. For example, the agent in the center patch (black) below is surrounded by five other agents, three of which are direct neighbors (white).

    figurea
  15. 15.

    Mutation is determined also by random draw. A random number between 0 and 1 is drawn; if that number is less than m, then mutation will occur.

  16. 16.

    Balliet et al (2014) and Caporael (2007) note the importance of group activity for reproduction and sustaining within the human group, suggesting that a social species does receive benefit from in-group behaviors.

  17. 17.

    The activities that occur during the transition periods (1500–2500) are left for a separate study.

  18. 18.

    The activities that occur during the transition periods (1500–2500) are left for a separate study.

  19. 19.

    Every ten periods between period 2500 and 4000.

  20. 20.

    This must be done with care as increasing the radius too much will kill too many agents, resulting in near extinction. Investigating this is left for future work.

  21. 21.

    In the Hammond and Axelrod (2006) model of what we term ‘charity environments,’ ethnocentric behavior functions as a solution to the problem of free riding. In the public goods or ‘investment environments,’ free riding will be less of a concern as both the giver and the receiver benefit.

  22. 22.

    The perception can either be a perceived benefit to cooperation with like types or a perceived cost to cooperation with non-like types; it is the relative difference that matters.

  23. 23.

    We considered a preliminary modification to our model. The modification changed the bombing algorithm so that bombs are launched by types that do not cooperate with outsiders. These bombs hit nearby agents of a different color than the agent that launched the bomb. The bombing originates with aggressive types and hits only local ‘outsiders.’ The results show that cooperation eventually emerges in this modification as bombs ultimately kill all the agent types that would be launching bombs. The result of this modification is not a significant departure from the base model, though the dynamics of equilibration differ.

  24. 24.

    Mihalyi (1984–1985, p. 98) notes similar increases in ethnocentric attitudes in Germany following both the France–Prussian war of 1870 and following Germany’s defeat in World War I.

  25. 25.

    For example, we considered a modification that imposed some spillover where agents located near a bomb zone become less cooperative with outsiders (switch their type to no-cooperation-with-outsiders). As expected, ethnocentrism comes to dominate in this specification. As a bomb explodes, many agents near the vacant space become ethnocentric, and these agents then reproduce to fill the area. The output for this modification supports the statement that ‘violence worsens ethnocentrism,’ but this result is somewhat forced by design. Incorporating this type of spillover without predetermining the model’s results is a challenge requiring further study.

References

  1. Abadie, A., and J. Gardeazabal. 2003. The economic costs of conflict: A case study of the Basque Country. American Economic Review 93(1): 113–132.

    Article  Google Scholar 

  2. Alesina, A., R. Baqir, and W. Easterly. 1999. Public goods and ethnic divisions. The Quarterly Journal of Economics 114(4): 1243–1284.

    Article  Google Scholar 

  3. Balliet, D., J. Wu, and C.K.W. De Dreu. 2014. Ingroup favoritism in cooperation: A meta-analysis. Psychological Bulletin 140(6): 1556–1581.

    Article  Google Scholar 

  4. Bauer, M., C. Blattman, J. Chytilova, J. Henrich, E. Miguel, and T. Mitts. 2016. Can war foster cooperation? Journal of Economic Perspectives 30(3): 249–274.

    Article  Google Scholar 

  5. Beugelsdijk, S., H.L. De Groot, and A.B. Van Schaik. 2004. Trust and economic growth: A robustness analysis. Oxford Economic Papers 56(1): 118–134.

    Article  Google Scholar 

  6. Blomberg, S.B., G.D. Hess, and A. Orphanides. 2004. The macroeconomic consequences of terrorism. Journal of Monetary Economics 51(5): 1007–1032.

    Article  Google Scholar 

  7. Buvinic, M., and A. Morrison. 1999. Violence as an obstacle to development. Inter-American Development Bank. Technical Note 4.

  8. Caporael, L. 2007. Evolutionary theory for social and cultural psychology. In Social Psychology: Handbook of Basic Principles. 2nd ed, ed. A.W. Kruglanski and E.T. Higgins, 3–18. New York: The Guilford Press.

    Google Scholar 

  9. De, S., M.J. Gelfand, D. Nau, and P. Roos. 2015. The inevitability of ethnocentrism revisited: Ethnocentrism diminishes as mobility increases. Scientific Reports 5: 17963. https://doi.org/10.1038/srep17963.

    Article  Google Scholar 

  10. Duncan, T.K., and C.J. Coyne. 2013. The overlooked costs of the permanent war economy: A market process approach. The Review of Austrian Economics 26(4): 413–431.

    Article  Google Scholar 

  11. Easterly, W. 2001. Can institutions resolve ethnic conflict? Economic Development and Cultural Change 49: 687–706.

    Article  Google Scholar 

  12. Easterly, W., and R. Levine. 1997. Africa’s growth tragedy: Policies and ethnic divisions. The Quarterly Journal of Economics 112(4): 1203–1250.

    Article  Google Scholar 

  13. Epstein, J.M. 1999. Agent-based computational models and generative social science. Complexity 4(5): 41–60.

    Article  Google Scholar 

  14. Gates, S., H. Hegre, H.M. Nygård, and H. Strand. 2012. Development consequences of armed conflict. World Development 40(9): 1713–1722.

    Article  Google Scholar 

  15. Greif, A. 1994. Cultural beliefs and the organization of society: A historical and theoretical reflection on collectivist and individualist societies. Journal of Political Economy 102: 912–950.

    Article  Google Scholar 

  16. Hammond, R.A., and R. Axelrod. 2006. The evolution of ethnocentrism. Journal of Conflict Resolution 50(6): 926–936.

    Article  Google Scholar 

  17. Hartshorn, M., A. Kaznatcheev, and T. Shultz. 2013. The evolutionary dominance of ethnocentric cooperation. Journal of Artificial Societies and Social Simulation 16(3): 7. http://jasss.soc.surrey.ac.uk/16/3/7.html.

  18. Humphreys, M. 2003. Economics and violent conflict. Cambridge, MA. https://www.unicef.org/spanish/socialpolicy/files/Economics_and_Violent_Conflict.pdf.

  19. Kam, C.D., and D.R. Kinder. 2007. Terror and ethnocentrism: Foundations of American support for the war on terrorism. The Journal of Politics 69(2): 320–338.

    Article  Google Scholar 

  20. Knack, S., and P. Keefer. 1997. Does social capital have an economic payoff? A cross-country investigation. The Quarterly Journal of Economics 112(4): 1251–1288.

    Article  Google Scholar 

  21. Landa, J.T. 1981. A theory of the ethnically homogenous middleman group: An institutional alternative to contract law. The Journal of Legal Studies 10(2): 349–362.

    Article  Google Scholar 

  22. Landa, J.T. 1994. Trust, Ethnicity, and Identity. Ann Arbor: University of Michigan Press.

    Google Scholar 

  23. Landa, J.T. 2008. Social distance and self-enforcing exchange. Journal of Legal Studies 37: 161–188.

    Article  Google Scholar 

  24. Lee, B.X. 2016a. Causes and cures VI: The political science and economics of violence. Aggression and Violent Behavior 28: 103–108.

    Article  Google Scholar 

  25. Lee, B.X. 2016b. Causes and cures IX: Consequences of violence. Aggression and Violent Behavior 30: 110–114.

    Article  Google Scholar 

  26. Leeson, P.T. 2005. Endogenizing fractionalization. Journal of Institutional Economics 1(1): 75–98.

    Article  Google Scholar 

  27. Lima, F.W.S., T. Hadzibeganovic, and D. Stauffer. 2009. Evolution of ethnocentrism on undirected and directed Barabasi–Albert networks. Physica A: Statistical Mechanics and its Applications 388(24): 4999–5004.

    Article  Google Scholar 

  28. Lucas, P., A.C.M. de Oliveira, and S. Banuri. 2014. The effects of group composition and social preference heterogeneity in a public goods game: An agent-based simulation. Journal of Artificial Societies and Social Simulation 17(3): 5.

    Article  Google Scholar 

  29. Macy, M.W., and R. Willer. 2002. From factors to factors: computational sociology and agent-based modeling. Annual Review of Sociology 28(1): 143–166.

    Article  Google Scholar 

  30. Mathieu, P., B. Beaufils, and O. Brandouy (eds.). 2005. Artificial Economics: Agent-Based Methods in Finance, Game Theory and Their Applications, vol. 564. Berlin: Springer.

    Google Scholar 

  31. Mihalyi, L. 1984–1985. Ethnocentrism versus nationalism: Origin and fundamental aspects of a major problem for the future. Humboldt Journal of Social Relations 12(1): 95–113.

  32. Nafziger, E.W., and J. Auvinen. 2002. Economic development, inequality, war, and state violence. World Development 30(2): 153–163.

    Article  Google Scholar 

  33. Rachlin, H. 2004. The behavioral economics of violence. Annals of the New York Academy of Sciences 1036(1): 325–335.

    Article  Google Scholar 

  34. Railsback, S.F., and V. Grimm. 2011. Agent-Based and Individual-Based Modeling: A Practical Introduction. Princeton: Princeton University Press.

    Google Scholar 

  35. Tesfatsion, L. 2002. Agent-based computational economics: Growing economies from the bottom up. Artificial Life 8(1): 55–82.

    Article  Google Scholar 

  36. Westneat, D. and C.W. Fox (eds.). 2010. Evolutionary Behavioral Ecology. Oxford: Oxford University Press.

    Google Scholar 

  37. Zak, P.J., and S. Knack. 2001. Trust and growth. The Economic Journal 111(470): 295–321.

    Article  Google Scholar 

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Correspondence to Thomas K. Duncan.

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Tilson, W.D., Duncan, T.K. & Farhat, D. An Agent-Based Model of Ethnocentrism and the Unintended Consequences of Violence. Eastern Econ J 46, 483–503 (2020). https://doi.org/10.1057/s41302-019-00151-6

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Keywords

  • Violence
  • Ethnocentrism
  • Agent-based modeling

JEL Classification

  • B55
  • D74
  • D90