Simulating a Fraud Mechanism in Public Service Delivery



This chapter illustrates a use of agent-based modeling to simulate how the dynamics of fraud occur in a public service delivery program. While fraud is a well-known problem in the public sector, the study of fraud is challenging because the behavior is subtle and adaptive. Underlying mechanisms are often not explicitly revealed. Crime data collected from investigations are biased downward because they include only those who are detected. In this chapter, I focus on modeling a fraud mechanism based on theories of crime and compare simulation outputs with results from a previous empirical study. I end this chapter with the discussion of the utility of agent-based modeling for policy inquiry.


Participant Agent Store Size Food Stamp Program Risk Propensity Public Service Delivery 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Bunge, M. (2006). A systemic perspective on crime, In P. H. Wikström and R. J. Sampson (eds.), The Explanation of Crime: Context, Mechanisms and Development (pp. 8–30). Cambridge: Cambridge University Press.Google Scholar
  2. Becker, G. S. (1968). Crime and punishment: An economic approach. In R. Febrero & P. S. Schwartz. (eds.), The Essence of Becker (pp. 463-517). Stanford: Hoover Institution Press.Google Scholar
  3. Cooter, R.D., & Ulen, T. (2007). Law and economics (5th ed.). Boston: Pearson Addison Wesley.Google Scholar
  4. Epstein, J. M. (2006). Generative social science: Studies in agent-based computational modeling. Princeton: Princeton University Press.Google Scholar
  5. Haynes, K. E., & Fotheringham, A. S. (1984). Gravity and spatial interaction models. Beverly Hills, CA: Sage Publications, Ltd.Google Scholar
  6. Heath, B., Hill, R., & Ciarallo, F. (2009). A survey of agent-based modeling practices (January 1998 to July 2008). Journal of Artificial Society and Social Simulation, 12(4), 9.
  7. Huff, D. L. (1964). Defining and estimating a trading area. Journal of Marketing, 28(3), 34–38.CrossRefGoogle Scholar
  8. Kim, Y. (2006). Analysis for adaptive complex public enterprises. Doctoral Dissertation. Columbus: Ohio State University.Google Scholar
  9. Kim, Y. (2007). Using spatial analysis for monitoring fraud in a public delivery program. Social Science Computer Review, 25(3), 287–301.CrossRefGoogle Scholar
  10. Kim, Y., & Xiao, N. (2008). FraudSim: Simulating fraud in a public delivery program. In L. Liu & J. Eck. (eds.). Artificial Crime Analysis Systems: Using Computer Simulations and Geographic Information Systems (pp. 319–338). Hershey, PA: IGI Global.Google Scholar
  11. Miller, J. H., & Page, S. E. (2007). Complex adaptive systems: An introduction to computational models of social life. Princeton: Princeton University Press.Google Scholar
  12. Pogarsky, G., Piquero, A.R., & Paternoster, R. (2004). Modeling change in perceptions about sanction threats: The neglected linkages in deterrence theory. Journal of Quantitative Criminology, 20(4), 343–369.CrossRefGoogle Scholar
  13. Sutherland, E. H. (1940). White-collar criminality. American Sociological Review, 5(1), 1–12.CrossRefGoogle Scholar
  14. USDA. (2001). WIC vendor management study 1998 (Report No. WIC-01-WICVM).Google Scholar
  15. Wikström, P. H. (2005). The social origins of pathways in crime: Towards a developmental ecological action theory of crime involvement and its changes, In D. P. Farrington (ed.), Integrated Developmental & Life-Course Theories of Offending (pp. 211–245). New Brunswick: Transaction Publishers.Google Scholar
  16. Wikström, P. H. (2006). Individuals, settings, and acts of crime: Situational mechanisms and the explanation of crime, In P. H. Wikström and R. J. Sampson (eds.), The Explanation of Crime: Context, Mechanisms and Development (pp. 61–107). Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  17. Wikström, P. H. (2009). Crime propensity, criminogenic exposure and crime involvement in early to mid adolescence. MschrKrim, 92, 253–266.Google Scholar
  18. Wikström, P. H. (2010). Activity fields and the dynamics of crime: Advancing knowledge about the role of the environment in crime causation. Journal of Quantitative Criminology, 26, 55–87.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  1. 1.School of Public Affairs, Arizona State UniversityPhoenixUSA

Personalised recommendations