Impacts of Network Topology on Tax Evasion in a Complex Artificial Social System Attila Szab ó 1,2 , László Gulyás 1,2 ,  ...
Overview <ul><li>The tax evasion model </li></ul><ul><li>Previous results using random graphs </li></ul><ul><li>Results us...
The  TAXSIM Model <ul><li>An agent-based tax evasion (compliance) model </li></ul><ul><ul><li>Employees, employers, tax au...
Main Model Components Audits, Governmental services Model of the market Information from social networks Taxpayer strategy...
Taxpayers’ Social Networks <ul><li>Agents exchange information (experiences) on their social network </li></ul><ul><li>Ass...
Model  Results <ul><li>We continued previous work: a ‘pessimistic’ sector was examined earlier </li></ul><ul><li>Three sce...
 
Network Topologies <ul><li>The selected topologies are: </li></ul><ul><li>Two-dimensional grid  </li></ul><ul><ul><li>spat...
Model Results and Topology <ul><li>500 employees </li></ul><ul><li>An average agent have 4 neighbors in all networks </li>...
No scenario
Governmental improvement
Legalization
Preferential Taxes
Summary <ul><li>We found that results depend on the social network topology </li></ul><ul><ul><li>Using random graph or Wa...
<ul><li>Thank you! </li></ul><ul><li>Any questions? Comments? </li></ul><ul><li>[email_address] </li></ul>
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Impacts of Network Topology on Tax Evasion in a Complex Artificial Social System

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Impacts of Network Topology on Tax Evasion in a Complex Artificial Social System

  1. 1. Impacts of Network Topology on Tax Evasion in a Complex Artificial Social System Attila Szab ó 1,2 , László Gulyás 1,2 , István J. Tóth 3 1 Eötvös Loránd University, Budapest 2 AITIA International Inc., Budapest 3 Research Institute of Economics and Enterprises, Hungarian Chamber of Commerce and Industry
  2. 2. Overview <ul><li>The tax evasion model </li></ul><ul><li>Previous results using random graphs </li></ul><ul><li>Results using various topologies </li></ul><ul><li>Summary </li></ul>
  3. 3. The TAXSIM Model <ul><li>An agent-based tax evasion (compliance) model </li></ul><ul><ul><li>Employees, employers, tax authority, government, market </li></ul></ul><ul><li>Evasion or (compliance) depends on taxpayer decision that is </li></ul><ul><ul><li>Rational ( maximizing a utility function ) </li></ul></ul><ul><ul><li>Accords to the environment ( evasion/compliance might be impossible or taxpayer overrides the optimal solution ) </li></ul></ul><ul><ul><li>Many options between total compliance and total evason mapped into 3 groups: legal/mixed/hidden type employments </li></ul></ul><ul><li>An important assumption: only a homogeneous sector is modeled (social networks) </li></ul>
  4. 4. Main Model Components Audits, Governmental services Model of the market Information from social networks Taxpayer strategy Decision
  5. 5. Taxpayers’ Social Networks <ul><li>Agents exchange information (experiences) on their social network </li></ul><ul><li>Assumption : network topology affects the simulation results </li></ul><ul><ul><li>It is to be confirmed </li></ul></ul><ul><ul><li>Q: on what level? </li></ul></ul>
  6. 6. Model Results <ul><li>We continued previous work: a ‘pessimistic’ sector was examined earlier </li></ul><ul><li>Three scenarios: </li></ul><ul><ul><li>Improving governmental services ( taxpayers more often overrides optimal decisions ) </li></ul></ul><ul><ul><li>Voluntary shift to total legalization ( one company, cca. 15% market share ) </li></ul></ul><ul><ul><li>Preferential taxes for companies ( can afford higher wages at legal employment type ) </li></ul></ul>
  7. 8. Network Topologies <ul><li>The selected topologies are: </li></ul><ul><li>Two-dimensional grid </li></ul><ul><ul><li>spatial/geographical </li></ul></ul><ul><li>Erdős-Rényi random graph ( used in previous research ) </li></ul><ul><ul><li>small world </li></ul></ul><ul><li>Watts-Strogatz network </li></ul><ul><ul><li>spatial/geographical </li></ul></ul><ul><ul><li>small world </li></ul></ul><ul><ul><li>clustered </li></ul></ul><ul><li>Real topologies depends on the modeled sector (construction, telco, etc.) </li></ul>
  8. 9. Model Results and Topology <ul><li>500 employees </li></ul><ul><li>An average agent have 4 neighbors in all networks </li></ul><ul><li>Nobody has a job in the beginning </li></ul>
  9. 10. No scenario
  10. 11. Governmental improvement
  11. 12. Legalization
  12. 13. Preferential Taxes
  13. 14. Summary <ul><li>We found that results depend on the social network topology </li></ul><ul><ul><li>Using random graph or Watts-Strogatz network results converge to the same equilibrium, but W-S is faster </li></ul></ul><ul><ul><li>Using a two dimensional grid agents don’t reach the optimal solution </li></ul></ul>
  14. 15. <ul><li>Thank you! </li></ul><ul><li>Any questions? Comments? </li></ul><ul><li>[email_address] </li></ul>

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