Game Theory in Organized Crime
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WHAT IS IT?
This model simulates the relation between Government and Organised Crime from a micro-interactive point of view. The actions that the Government can take to fight against organised crime (or cooperate with it, and then share the benefits that arise from unethical agreements) depend on cultural aspects of the society studied, on the economic context in which global market is inserted, going through the State’s need to control this problem in a way that criminal organizations could not lead to society negative externalities (violence, constant clashes with government forces, parallel power’s competition), nor become more powerfull than the State itself (supposing a corruptive, or better saying, coerced Government that decides to cooperate with organised crime). Recent studies in Korea conducted by professor Jonson Porteux verified that these kind of agreements with parallel power forces reduces the negative effects of illegal activies in the society – thus, organised crime is “better” than disorganized - it occurs because, by negotiating with these groups, Government can keep them under control and limit their influence over the welfare sphere. It also contributes to spur the lack of jurisdiction when a weak (politically or economically) government cannot itself take care of all society issues efficiently. The purpose of this model is spur the studies of Professor Porteux in demonstrating graphically his studies. This is an environment coupounded by two criminal organizations and by government agents, who can work together with criminals or fight against them. It will be perceived that a non-cooperative behavior increases negative externalities over society and can amplify criminal organisations influence over welfare – and consequently reduce this.
HOW IT WORKS
The initial interaction is non-cooperative. It will be perceived on “Criminal Activites” chart a continuous layout modification generated by upswings and downswings. Each downswing can be interpreted as a clash between a criminal firm and government, and each upswing is a criminal organization expansion over the market. Generally, illegal firms will expand their power jointly in the market simulated, as a result of the government’s refuse in cooperating with them. When one of the firms is more influent than another, the weaker firm will cause a negative externality (faction clashes, increases in drugs traffic etc) to increase its power to become as powerful as the other – thus, with this simplification the social effects of competition between rivals to increase power can be well represented. Always when government seems less propense to cooperate with criminals,illegal organizations will feel propense to expand their activities and influences. In the “Wealth Flow” chart, the two mafious firms will compete head by head with government to economic power and political influence. Turning the statepropensitytoCONTINUEtocooperatewithcriminals slider, a cooperative behavior starts and then changes in the graphic layouts will be perceived. Conflicts will be reduced, and also the competition for political influence. Government wealth will increase without harming criminal firms activities, just controlling their significance on well-being. The statepropensitytoSTARTtocooperatewithcriminals slider must be calibrated before starting the interaction, and must not be turned during it, otherwise the results cannot be analysed uniformly in the temporal horizon.
HOW TO USE IT
The interactive variables
Benefit-cooperation: This variable adjusts how much of profits are supposed the criminals would earn to from having cooperation with a corruptive government. It represents an increase in their usual earnings arising from cooperation, and varies from 0 to 1. It will be perceived that, in a non-cooperative interaction, that the higher the benefit of cooperation for criminals, the higher will be the negative externalities in society, thus, simulating the trade-off for the government in refusing a join in a cooperation.
StatepropensitytoSTARTtocooperatewithcriminals: This variable is a cultural variable, in which the effectiveness of the jurisdiction in relations among agents can be controlled. The stronger this variable is, the weaker a state jurisdiction will be since the beginning of the interactions.
StatepropensitytoCONTINUEtocooperatewithcriminals: This is a transitional variable, in the sense that you can control how your government would be willing to keep cooperating with organized crime indefinitely. This is independent if the initial condition at the beginning of the interactions. (Basically, it signifies that the government can get less or more opened to agreements with criminals in the course of the simulation).
Endowment?: This is an exogenous variable, which can be used or not to simulate the dynamics of the economy.
Endowment-rate: This variable controls the ‘flow of profits’ that a criminal can have. Basically, 0 simulates a market in relative good conditions and 10 a period of relative crisis.
Initial-number-criminals: Controls the number of criminals in the beginning of the simulation.
Initial-number-governmentagents: Controls the number of government agents in the beginning of the simulation.
Initial-state-strength: This variable controls simulated government’s wealth. A rich government can fight against organized crime more effectively than a less favored one. This can be tested by conducting the interactions.
Charts:
Criminal Activities: Controls the negative externalities the criminal firms can cause over society, like clashes or expansions.
Wealth Flow: Controls the money flow during the interactions among criminals and government agents, and also their increases or decreases in economic and political power.
In both charts, red and blue labels simulate the two criminal firms, and the black simulates the Government.
Monitors: The three monitors follow the aggregated wealth of the three agentes – both criminals firms and government. Always when the Government will be less oppulent than the criminals, a period of instability will be verified in the Criminal Activities chart, and its fading will be visualized in the Wealth Flow chart – it will signify that government will not be cooperating with organised crime, and then the firms will feel free to expand their illegal actions and cause negative effects in well-being, concomitantly getting a higher political influence.
THINGS TO NOTICE
The model is quite sensible to changes, so must be accurately calibrated to generate the expected results. It follows the CMM approach to simulate criminal behavior, in accordance to professor Porteux’s observations.
THINGS TO TRY
• To have a proxy to reality, do not use more criminals than government agents as input. In a usual market, there are more government agents - as police, for example - than criminal people. • This model has a more complex code than the macro interactive one, then its equilibrium requires more time on adjustments until the results searched can be obtained. • Change the sliders during the interactions. From cooperation to non-cooperation and vice-versa. Quickly the changes in the chart layout will be observed. • Depending on the calibration used, the ticks necessary to generate results and show the micro interactions and trends can vary. It’s strongly suggested to use also the macro interactions model.
RELATED MODELS
"The Mafia Model - Interaction between police, mafia and storewoners" also named "Affecting Mafia With Social Norms" http://ccl.northwestern.edu/netlogo/models/community/The%20Mafia%20Model%20-%20Interaction%20between%20police,%20mafia%20and%20storewoners
"Mafianomics" http://web.econ.unito.it/terna/tesine/mafianomics.htm
CREDITS AND REFERENCES
Adrian Haugen Ordemann - University Of Oslo
Benedito Faustinoni Neto - University of Sao Paolo
Based on the work of Professor Jonson Porteux - Hosei University
The CMM in chapter 10 in the book "The Economics of organized crime" by Gianluca Fiorentini and Sam Peltzman
Comments and Questions
globals [endowment] breed [criminals a-criminal] breed [governmentagents a-governmentagent] breed [criminals2 a-criminal2] criminals-own [money] criminals2-own [money] governmentagents-own [money] patches-own [countdown] to setup clear-all ask patches [set pcolor green] if endowment? [ask patches [ set countdown random-normal 0 1 endowment-return set pcolor one-of [green red] ] ] set-default-shape criminals "criminals" create-criminals initial-number-criminals [ set color black set size 2 setxy random-xcor random-ycor ] set-default-shape criminals2 "criminals2" create-criminals2 initial-number-criminals2 [ set color blue set size 2 setxy random-xcor random-ycor ] set-default-shape governmentagents "governmentagents" create-governmentagents initial-number-governmentagents [ set color white set size 2 set money initial-state-strength setxy random-xcor random-ycor ] set endowment count patches with [pcolor = green] reset-ticks end to go if not any? turtles [ stop ] ask criminals [ take-money ; Should we not make a slider to adjust this threshold? So we can show that dependent on state-strengt you can get different equilibriums? move ; I think, according to the paper, that that can be of great value to look at different cases death cheat multiply-criminals fight lie ] ask criminals2 [ take-money ; Should we not make a slider to adjust this threshold? So we can show that dependent on state-strengt you can get different equilibriums? move ; I think, according to the paper, that that can be of great value to look at different cases death cheat multiply-criminals2 fight2 lie ] ask governmentagents [ move cooperate cooperate2 catch-criminals catch-criminals2 ] if endowment? [ ask patches [ endowment-return ] ] set endowment count patches with [pcolor = green] if benefit-cooperation < 0.5 [ask criminals [lie]] if benefit-cooperation < 0.5 [ask criminals2 [lie]] tick end to take-money if pcolor = green [ set pcolor red set money money + 1 ] end to move rt random 50 lt random 50 fd 1 end to death if money < 0 [die] end ;; to catch-storeowners ;; let mafia-power sum ([money] of mafious in-radius 20) / 100 ;; let ProbRefuse-myself sum ([money] of cops in-radius 20) / 100 ;; let prey one-of storeowners-here ;; if prey != nobody ;; [ask prey [ifelse (((ProbRefuse-myself * ((storeowners-thrust-in-govs-ability-to-fight-mafia * police-power) / 2 ))) < mafia-power ) ;; [set money money - 3 ask patches in-radius 5 [endowment-return]] [set money money - 1 ask patches in-radius 2 [stop endowment-return]]]] ;; ifelse (((ProbRefuse-myself * ((storeowners-thrust-in-govs-ability-to-fight-mafia * police-power) / 2 ))) < mafia-power ) ;; [set money money + 3] [set money money + 0] ;; end ; to catch-criminals ; let market-profit sum [money] of criminals ; let government-power sum [money] of governmentagents ; let prey one-of criminals-here ; if prey != nobody ; [ask prey [ifelse market-profit > government-power and random-float 100 > 90 ;; According to paper ; [set money money - (sum [money] of criminals-here)] [set money money + 0]]] ; If true, criminals gets reduced money, if not there no change ; ifelse market-profit > government-power [set money money + (sum [money] of criminals)] [set money money + 0] ; end ; If true the government gets the money of the criminals, if not, nothing happens to cooperate let market-profit sum [money] of criminals let government-power sum [money] of governmentagents let prey one-of criminals-here if prey != nobody [ask prey [ifelse market-profit > government-power * ( statepropensitytoCONTINUEtocooperatewithcriminals / 10 * statepropensitytoSTARTtocooperatewithcriminals ) and ( statepropensitytoCONTINUEtocooperatewithcriminals / 10 * statepropensitytoSTARTtocooperatewithcriminals ) != 0 [set money money + (sum [money] of criminals-here / 1000) * (1 + benefit-cooperation) ] [set money money + (sum [money] of criminals-here) / 1000 * benefit-cooperation / 2.5 ]]] ; Funker ikke ; If true, criminals gets reduced money, if not there no change ifelse market-profit > government-power * ( statepropensitytoCONTINUEtocooperatewithcriminals / ( 10 * statepropensitytoSTARTtocooperatewithcriminals) ) and ( statepropensitytoCONTINUEtocooperatewithcriminals / 10 * statepropensitytoSTARTtocooperatewithcriminals ) != 0 [set money money + (sum [money] of criminals-here) * (1 + benefit-cooperation) * pi] [set money money + 0] ; Funker end to cooperate2 let market-profit2 sum [money] of criminals2 let government-power sum [money] of governmentagents let prey one-of criminals2-here if prey != nobody [ask prey [ifelse market-profit2 > government-power * ( statepropensitytoCONTINUEtocooperatewithcriminals / 10 * statepropensitytoSTARTtocooperatewithcriminals ) and ( statepropensitytoCONTINUEtocooperatewithcriminals / 10 * statepropensitytoSTARTtocooperatewithcriminals ) != 0 [set money money + (sum [money] of criminals2-here / 1000) * (1 + benefit-cooperation) ] [set money money + (sum [money] of criminals2-here) / 1000 * benefit-cooperation / 2.5 ]]] ; Funker ikke ; If true, criminals gets reduced money, if not there no change ifelse market-profit2 > government-power * ( statepropensitytoCONTINUEtocooperatewithcriminals / ( 10 * statepropensitytoSTARTtocooperatewithcriminals) ) and ( statepropensitytoCONTINUEtocooperatewithcriminals / 10 * statepropensitytoSTARTtocooperatewithcriminals ) != 0 [set money money + (sum [money] of criminals2-here) * (1 + benefit-cooperation) * pi] [set money money + 0] ; Funker end to catch-criminals let prey one-of criminals-here if prey != nobody [ask prey [ifelse ( statepropensitytoCONTINUEtocooperatewithcriminals / 10 * statepropensitytoSTARTtocooperatewithcriminals ) = 0 and benefit-cooperation = 0 and random-float 100 > 90 ;; According to paper [set money money - (1 + benefit-cooperation) * (sum [money] of criminals-here)] [set money money + 0]]] ifelse ( statepropensitytoCONTINUEtocooperatewithcriminals / 10 * statepropensitytoSTARTtocooperatewithcriminals ) = 0 and benefit-cooperation = 0 and random-float 100 > 90 [set money money + (sum [money] of criminals-here)] [set money money + 0] end to catch-criminals2 let prey one-of criminals2-here if prey != nobody [ask prey [ifelse ( statepropensitytoCONTINUEtocooperatewithcriminals / 10 * statepropensitytoSTARTtocooperatewithcriminals ) = 0 and random-float 100 > 90 ;; According to paper [set money money - (1 + benefit-cooperation) * (sum [money] of criminals2-here)] [set money money + 0]]] ifelse ( statepropensitytoCONTINUEtocooperatewithcriminals / 10 * statepropensitytoSTARTtocooperatewithcriminals ) = 0 and random-float 100 > 90 [set money money + (sum [money] of criminals2-here)] [set money money + 0] end to cheat let prey one-of governmentagents-here if prey != nobody [ask prey [ifelse ( statepropensitytoCONTINUEtocooperatewithcriminals / 10 * statepropensitytoSTARTtocooperatewithcriminals ) = 0 and random-float 100 > 90 ; [set money money - (sum [money] of governmentagents-here)] [set money money + 0]]] ;always when they start to become more powerful ifelse ( statepropensitytoCONTINUEtocooperatewithcriminals / 10 * statepropensitytoSTARTtocooperatewithcriminals ) = 0 [set money money + (sum [money] of governmentagents-here)] [set money money + 0] end to endowment-return if pcolor = red [ ifelse countdown <= 0 [set pcolor green set countdown endowment-rate ] [set countdown countdown - 1 ] ] end to multiply-criminals let my-money sum [money] of criminals-here let enemy-money sum [money] of criminals2 if my-money > 100 * (enemy-money / (benefit-cooperation + 0.01)) and ( statepropensitytoCONTINUEtocooperatewithcriminals / 10 * statepropensitytoSTARTtocooperatewithcriminals ) <= (benefit-cooperation * 10) or count criminals < count criminals2 [hatch 1 rt random-float 360 fd 1 set money money - (sum [money] of criminals-here)] end to multiply-criminals2 let my-money sum [money] of criminals2-here let enemy-money sum [money] of criminals if my-money > 100 * (enemy-money / (benefit-cooperation + 0.01)) and ( statepropensitytoCONTINUEtocooperatewithcriminals / 10 * statepropensitytoSTARTtocooperatewithcriminals ) <= (benefit-cooperation * 10) or count criminals2 < count criminals [hatch 1 rt random-float 360 fd 1 set money money - (sum [money] of criminals2-here)] end to fight let my-profit sum [money] of criminals let enemy-profit sum [money] of criminals2 let prey one-of criminals2-here if prey != nobody [ask prey [ifelse my-profit < enemy-profit and random-float 100 > 90 ;; According to paper [set money money - (sum [money] of criminals2-here)] [set money money + 0]]] ifelse my-profit < enemy-profit [set money money + (sum [money] of criminals2-here) ] [set money money + 0] end to fight2 let my-profit sum [money] of criminals2 let enemy-profit sum [money] of criminals let prey one-of criminals-here if prey != nobody [ask prey [ifelse my-profit < enemy-profit and random-float 100 > 90 ;; According to paper [set money money - (sum [money] of criminals-here)] [set money money + 0]]] ifelse my-profit < enemy-profit [set money money + (sum [money] of criminals-here) ] [set money money + 0] end to lie let government-power sum [money] of governmentagents let enemy-profit sum [money] of criminals let enemy2-profit sum [money] of criminals2 let prey one-of governmentagents-here if prey != nobody [ask prey [ifelse ( statepropensitytoCONTINUEtocooperatewithcriminals / 10 * statepropensitytoSTARTtocooperatewithcriminals ) != 0 and benefit-cooperation < 0.5 and (enemy-profit + enemy2-profit) * benefit-cooperation = initial-state-strength * government-power and random-float 100 > 90 ; [set money money - (sum [money] of governmentagents-here)] [set money money + 0]]] ;always when they start to become more powerful ifelse ( statepropensitytoCONTINUEtocooperatewithcriminals / 10 * statepropensitytoSTARTtocooperatewithcriminals ) != 0 and (enemy-profit + enemy2-profit) * benefit-cooperation = initial-state-strength * government-power and random-float 100 > 90 [set money money + (sum [money] of governmentagents-here)] [set money money + 0] end
There is only one version of this model, created about 11 years ago by Benedito Neto.
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