IDEAS home Printed from https://ideas.repec.org/a/eee/joepsy/v40y2014icp119-133.html
   My bibliography  Save this article

An agent-based model of network effects on tax compliance and evasion

Author

Listed:
  • Andrei, Amanda L.
  • Comer, Kevin
  • Koehler, Matthew

Abstract

Agent-based models are flexible analytical tools suitable for exploring and understanding complex systems such as tax compliance and evasion. The agent-based model created in this research builds upon two other agent-based models of tax evasion, the Korobow, Johnson, and Axtell (2007) and Hokamp and Pickhardt (2010) models. The model utilizes their rules for taxpayer behavior and apprehension of tax evaders in order to test the effects of network topologies in the propagation of evasive behavior. Findings include that network structures have a significant impact on the dynamics of tax compliance, demonstrating that taxpayers are more likely to declare all their income in networks with higher levels of centrality across the agents, especially when faced with large penalties proportional to their incomes. These results suggest that network structures should be chosen selectively when modeling tax compliance, as different topologies yield different results. Additionally, this research analyzed the special case of a power law distribution and found that targeting highly interconnected individuals resulted in a lower mean gross tax rate than targeting disconnected individuals, due to the penalties inflating the mean gross tax rate in the latter case.

Suggested Citation

  • Andrei, Amanda L. & Comer, Kevin & Koehler, Matthew, 2014. "An agent-based model of network effects on tax compliance and evasion," Journal of Economic Psychology, Elsevier, vol. 40(C), pages 119-133.
  • Handle: RePEc:eee:joepsy:v:40:y:2014:i:c:p:119-133
    DOI: 10.1016/j.joep.2013.01.002
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167487013000044
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. repec:cup:cbooks:9780511771576 is not listed on IDEAS
    2. Montgomery, James D, 1991. "Social Networks and Labor-Market Outcomes: Toward an Economic Analysis," American Economic Review, American Economic Association, vol. 81(5), pages 1407-1418, December.
    3. Frey, Bruno S. & Torgler, Benno, 2007. "Tax morale and conditional cooperation," Journal of Comparative Economics, Elsevier, vol. 35(1), pages 136-159, March.
    4. Alan P. Kirman, 1992. "Whom or What Does the Representative Individual Represent?," Journal of Economic Perspectives, American Economic Association, vol. 6(2), pages 117-136, Spring.
    5. Allingham, Michael G. & Sandmo, Agnar, 1972. "Income tax evasion: a theoretical analysis," Journal of Public Economics, Elsevier, vol. 1(3-4), pages 323-338, November.
    6. Albin, Peter & Foley, Duncan K., 1992. "Decentralized, dispersed exchange without an auctioneer : A simulation study," Journal of Economic Behavior & Organization, Elsevier, vol. 18(1), pages 27-51, June.
    7. Robert Axtell, 2007. "What economic agents do: How cognition and interaction lead to emergence and complexity," The Review of Austrian Economics, Springer;Society for the Development of Austrian Economics, vol. 20(2), pages 105-122, September.
    8. James Andreoni & Brian Erard & Jonathan Feinstein, 1998. "Tax Compliance," Journal of Economic Literature, American Economic Association, vol. 36(2), pages 818-860, June.
    9. Korobow, Adam & Johnson, Chris & Axtell, Robert, 2007. "An Agent–Based Model of Tax Compliance With Social Networks," National Tax Journal, National Tax Association, vol. 60(3), pages 589-610, September.
    10. Sascha Hokamp & Michael Pickhardt, 2010. "Income Tax Evasion in a Society of Heterogeneous Agents - Evidence from an Agent-based Model," International Economic Journal, Taylor & Francis Journals, vol. 24(4), pages 541-553.
    11. Georg Zaklan & Frank Westerhoff & Dietrich Stauffer, 2009. "Analysing tax evasion dynamics via the Ising model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 4(1), pages 1-14, June.
    12. Alm, James & Sanchez, Isabel & de Juan, Ana, 1995. "Economic and Noneconomic Factors in Tax Compliance," Kyklos, Wiley Blackwell, vol. 48(1), pages 3-18.
    13. Brian Erard & Jonathan S. Feinstein, 1994. "Honesty and Evasion in the Tax Compliance Game," RAND Journal of Economics, The RAND Corporation, vol. 25(1), pages 1-19, Spring.
    14. Juan Molero & Francesc Pujol, 2012. "Walking Inside the Potential Tax Evader’s Mind: Tax Morale Does Matter," Journal of Business Ethics, Springer, vol. 105(2), pages 151-162, January.
    15. Zaklan, Georg & Lima, F.W.S. & Westerhoff, Frank, 2008. "Controlling tax evasion fluctuations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(23), pages 5857-5861.
    16. Easley,David & Kleinberg,Jon, 2010. "Networks, Crowds, and Markets," Cambridge Books, Cambridge University Press, number 9780521195331, May.
    17. N. Lesca, 2010. "Introduction," Post-Print halshs-00640602, HAL.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Benno Torgler, 2014. "Can Tax Compliance Research Profit from Biology?," CREMA Working Paper Series 2014-08, Center for Research in Economics, Management and the Arts (CREMA).
    2. Nigar Hashimzade & Gareth Myles & Frank Page & Matthew Rablen, 2015. "The use of agent-based modelling to investigate tax compliance," Economics of Governance, Springer, vol. 16(2), pages 143-164, May.
    3. Muñoz, Francisco & Nuño, Juan Carlos & Primicerio, Mario, 2015. "Effects of inspections in small world social networks with different contagion rules," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 432(C), pages 76-86.
    4. Hashimzade, Nigar & Myles, Gareth D. & Rablen, Matthew D., 2016. "Predictive analytics and the targeting of audits," Journal of Economic Behavior & Organization, Elsevier, vol. 124(C), pages 130-145.
    5. Sascha Hokamp & Götz Seibold, 2014. "Tax Compliance and Public Goods Provision. An Agent-based Econophysics Approach," Central European Journal of Economic Modelling and Econometrics, CEJEME, vol. 6(4), pages 217-236, December.
    6. Gao, Li, 2015. "Evolution of consumption distribution and model of wealth distribution in China between 1995 and 2012," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 429(C), pages 76-86.
    7. repec:spr:qualqt:v:52:y:2018:i:1:d:10.1007_s11135-017-0471-1 is not listed on IDEAS
    8. Semjén, András, 2017. "Az adózói magatartás különféle magyarázatai
      [Various explanations for tax compliance]
      ," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(2), pages 140-184.
    9. repec:bla:rdevec:v:21:y:2017:i:3:p:713-730 is not listed on IDEAS

    More about this item

    Keywords

    Social networks; Social influence;

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • H26 - Public Economics - - Taxation, Subsidies, and Revenue - - - Tax Evasion and Avoidance

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:joepsy:v:40:y:2014:i:c:p:119-133. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: http://www.elsevier.com/locate/joep .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.