Tax Compliance, Rational Choice, and Social Influence: An Agent-Based Model

2014 ◽  
Vol 55 (4) ◽  
pp. 765 ◽  
Author(s):  
Francisco J. Miguel Quesada ◽  
Eduardo Tapia ◽  
Toni Llàcer ◽  
José A. Noguera
Keyword(s):  
Social Influence ◽  
Rational Choice ◽  
Tax Compliance ◽  
Agent Based Model ◽  
Agent Based

AN AGENT-BASED MODEL OF TAX COMPLIANCE: AN APPLICATION TO THE SPANISH CASE

2013 ◽  
Vol 16 (04n05) ◽  
pp. 1350007 ◽  
Author(s):  
TONI LLACER ◽  
FRANCISCO J. MIGUEL ◽  
JOSÉ A. NOGUERA ◽  
EDUARDO TAPIA
Keyword(s):  
Social Influence ◽  
Tax Evasion ◽  
Behavioral Outcomes ◽  
Internal Validity ◽  
Tax Compliance ◽  
Relative Effect ◽  
Agent Based Model ◽  
Agent Based ◽  
Filter Approach ◽  
Evasion Behavior

In this paper, we present a new agent-based model for the simulation of tax compliance and tax evasion behavior (SIMULFIS). The main novelties of the model are the introduction of a "behavioral filter approach" to model tax decisions, the combination of a set of different mechanisms to produce tax compliance (namely rational choice, normative commitments and social influence), and the use of the concept of "fraud opportunity use rate" (FOUR) as the main behavioral outcome. After describing the model in detail, we display the main behavioral and economic results of 1,920 simulations calibrated for the Spanish case and designed to test for the internal validity of SIMULFIS. The behavioral outcomes show that scenarios with strict rational agents strongly overestimate tax evasion, while the introduction of social influence and normative commitments allows to generate more plausible compliance levels under certain deterrence conditions. Interestingly, the relative effect of social influence is shown to be ambivalent: it optimizes compliance under low and middle deterrence conditions, but not when deterrence is made harder. Finally, SIMULFIS economic outcomes are broadly in line with theoretical expectations, thus supporting the reliability of the model.

An Agent–Based Model of Tax Compliance with Social Networks

2007 ◽  
Vol 60 (3) ◽  
pp. 589-610 ◽  
Author(s):  
Adam Korobow ◽  
Chris Johnson ◽  
Robert Axtell
Keyword(s):  
Social Networks ◽  
Tax Compliance ◽  
Agent Based Model ◽  
Agent Based

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

2014 ◽  
Vol 40 ◽  
pp. 119-133 ◽  
Author(s):  
Amanda L. Andrei ◽  
Kevin Comer ◽  
Matthew Koehler
Keyword(s):  
Network Effects ◽  
Tax Compliance ◽  
Agent Based Model ◽  
Agent Based

scholarly journals Cultural Dissemination: An Agent-Based Model with Social Influence

2021 ◽  
Vol 24 (4) ◽  
Author(s):  
Ngan Nguyen ◽  
Hongfei Chen ◽  
Benjamin Jin ◽  
Walker Quinn ◽  
Conrad Tyler ◽  
...  
Keyword(s):  
Social Influence ◽  
Agent Based Model ◽  
Agent Based ◽  
Cultural Dissemination

scholarly journals Enhanced or distorted wisdom of crowds? An agent-based model of opinion formation under social influence

2021 ◽  
Author(s):  
Pavlin Mavrodiev ◽  
Frank Schweitzer
Keyword(s):  
Social Influence ◽  
Correct Answer ◽  
Wisdom Of Crowds ◽  
Full Information ◽  
Agent Based Model ◽  
Opinion Formation ◽  
Agent Based ◽  
Factual Question ◽  
True Answer ◽  
The Wisdom Of Crowds

AbstractWe propose an agent-based model of collective opinion formation to study the wisdom of crowds under social influence. The opinion of an agent is a continuous positive value, denoting its subjective answer to a factual question. The wisdom of crowds states that the average of all opinions is close to the truth, i.e., the correct answer. But if agents have the chance to adjust their opinion in response to the opinions of others, this effect can be destroyed. Our model investigates this scenario by evaluating two competing effects: (1) agents tend to keep their own opinion (individual conviction), (2) they tend to adjust their opinion if they have information about the opinions of others (social influence). For the latter, two different regimes (full information vs. aggregated information) are compared. Our simulations show that social influence only in rare cases enhances the wisdom of crowds. Most often, we find that agents converge to a collective opinion that is even farther away from the true answer. Therefore, under social influence the wisdom of crowds can be systematically wrong.

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