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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

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

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