Self-reporting in optimal law enforcement with criminal teams, multiple stages and ex post asymmetric information [Elektronische Ressource] / vorgelegt von Markus Walzl

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Self-Reporting in Optimal Law Enforcementwith Criminal Teams, Multiple Stages, and ExPost Asymmetric InformationMarkus WalzlSelf-Reporting in Optimal Law Enforcement withCriminal Teams, Multiple Stages, and Ex PostAsymmetric InformationVon der Fakult˜at fur˜ WirtschaftswissenschaftenderRheinisch-Westf˜alischen Technischen HochschuleAachenzur Erlangung des akademischen Grades einesDoktors derWirtschafts- und Sozialwissenschaftengenehmigte Dissertationvorgelegt von Markus Walzlaus K˜onigswinter am RheinBerichter: Univ.-Prof. Dr.phil. Eberhard FeessUniv.-Prof. Dr.rer.pol. Wolfgang BreuerTag der mundlic˜ hen Prufung:˜ 11. Dezember 2003Diese Dissertation ist auf den Internetseiten derHochschulbibliothek online verfugbar˜Meinen ElternContents1 Introduction 11.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.2 Contribution. . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 Legal Situation 62.1 Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62.2 General Remarks . . . . . . . . . . . . . . . . . . . . . . . . . 62.3 Tax Amnesties . . . . . . . . . . . . . . . . . . . . . . . . . . 82.4 Leniency Programs in Cartel Prosecution . . . . . . . . . . . . 93 Review of the Literature 123.1 Overview and Structure . . . . . . . . . . . . . . . . . . . . . 123.2 Literature on Self-reporting . . . . . . . . . . . . . . . . . . . 153.3 on Plea Bargaining . . . . . . . . . . . . . . . . . . 243.

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Informations

• Publié par: rheinisch-westfalischen_technischen_hochschule_-rwth-_aachen
• Publié le: 01 janvier 2003
• Nombre de lectures: 17
• Langue: English

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Self-ReportinginOptimalLawEnforcementwith
CriminalTeams,MultipleStages,andExPost
InformationAsymmetric

VonderFakult¨atf¨urWirtschaftswissenschaften
derRheinisch-Westf¨alischenTechnischenHochschule
henAaczurErlangungdesakademischenGradeseines
derDoktorsWirtschafts-genehmigteundSozialwissenscDissertationhaften

vorgelegtvonMarkusWalzl

ausK¨onigswinteramRhein

Berichter:Univ.-Prof.Dr.phil.EberhardFeess
Univ.-Prof.Dr.rer.pol.WolfgangBreuer

Tagderm¨undlichenPr¨ufung:11.Dezember2003

DieseDissertationistaufdenInternetseitender
Hochschulbibliothekonlineverf¨ugbar

Meinen

Eltern

tstenCon

ductiontroIn11.1Motivation.............................
1.2Contribution............................

SituationLegal22.1Overview..............................
2.2GeneralRemarks.........................
2.3TaxAmnesties..........................
2.4LeniencyProgramsinCartelProsecution............

LiteraturetheofReview33.1OverviewandStructure.....................
3.2LiteratureonSelf-reporting...................
3.3LiteratureonPleaBargaining..................
3.4LiteratureonSettlements....................
3.5Conclusions............................

4HeterogeneityandSelf-Reporting
4.1Introduction............................
4.2TheModel.............................
4.3AnalysisforagivenDegreeofHeterogeneity..........
4.4TheImpactofHeterogeneity...................
4.5Discussion.............................

5MultipleStagesandOptionValues
5.1Introduction............................
5.2TheModel.............................
5.3NoFineReduction........................

3

112

66689

121215242732

343435363846

47474849

5.4FineReductions..........................50
5.5HarmDependenceofFineReductions..............54
5.6Discussion.............................56

6LawEnforcementforCriminalTeams58
6.1Introduction............................58
6.2BasicModel............................59
6.3EndogenousProbabilityofCooperation.............64
6.4ImperfectSelf-ReportingTechnologies..............67
6.5Discussion.............................69

7CorporateLeniencyPrograms72
7.1Introduction............................72
7.2TheModel.............................74
7.3ConvictionStage.........................75
7.4Pre-DetectionStage........................76
7.5ViolationDecisionandtheAuthority’sOptimalPolicy....78
7.6ComparativeStatics.......................81
7.7Discussion.............................83

8Conclusion

86

89ofsProAA.1Chapter4.............................89
A.2Chapter5.............................98
A.3Chapter6.............................102
A.4Chapter7.............................105

FiguresB

TheCyBibliograph

Danksagung

4

108

113

122

5

NotationaABb)u(bbb)u(ccC(i)(p)
De)b(f)b(Fg(j)(θ)
G(j)(θ)
h(m=1,2,3)
Hkl)j(LnnsN)j(N=NH/NL
p)i(P)i(qr((ji))
ssS)j(S=SH/SL
CStt

suppmarginalortforbenefitsuniformfromself-repdistributionsorting
ortingself-repofcostsmarginalprivatebenefitfromviolation(forplayeru=1,2)
subscriptforfinesifbothself-report
maximumprivatebenefit
borderlinetypewhoonlyjustviolates
estigatedvincaseerpcostsunit

superscriptforoceropativeteamsmonitoringcosts(inself-reportingstagei=1,2)
marginalcostsduetonon-illicitcrime
subscriptforextendedmodel
densityofprivatebenefits
cumulativedistributionofprivatebenefits
densityofindividualdetectionprobabilities
(instagej=1,2orforplayerj=H,L)
cumulativedistributionofindividualdetectionprobabilities
harm(instagem=1,2,3)
subscriptforhighevidenceprovider
self-reportingfineforreportingteams
self-reportingfineforsimultaneousreportingteammembers
supsubscripterscriptforforlownoncoevidenceoperativeproviderteams
superscriptforthecasewithoutself-reporting
(strategy)ortingself-repnotuple)(strategyortingself-repnomonitoringmonitoringfrequencyfrequencyforforsinglecriminalviolatorsteams
rateerationopcoortersself-repforreductionfinefineummaximsubscriptforfinesifasingleviolatorself-reports
(strategy)ortingself-reptuple)(strategyortingself-repcostscialsomaximtransactionumcoststransactioncosts
6

α(o=1,2,H,L)
Δφ)j(Φλ((ii))
µΩπ)θ(σθθ((jj))
∗

imperfectconvictionprobability(ofplayero=1,2,H,L)
erationopcofromgainexpectedfineforasingleviolator
(maximum)expectedfineforcriminalteams
frequencyortingself-repultipliermLagrangeauthority’spolicyvector
frequencyviolationstandarddeviationofindividualdetectionprobabilities
yprobabilitdetectionindividualborderlinetypewhoonlyjustself-reports
aluevoptimaltheindicates

7

Abbreviations

AOArt.CLACER

EUOCFIRSKronzG1994KSoStGB¨SOCStGBStPOUS(A)

ArtikAbgabelenOrdnung
ComprehensiveEnvironmentalResponse,
Compensation,andLiabilityAct
UnioneanEuropConditionOrderFirstInternalRevenueService
KronzeugenregelungKaplowandShavell(1994)
¨osterreichischesStrafgesetzbuch
ConditionOrderSecondhStrafgesetzbucUnitedStrafprozessordnStates(ofungAmerica)

8

1Chapter

ductiontroIn

ationMotiv1.1

Itisapartofalmosteverylegalsystemthatconfessingviolatorspaylower
fines.Punishmentsforcriminalswhoprovideevidenceagainstcollaborators
inalegallitigationaretypicallyreduced,tax-evadershavetheopportunity
toself-reporttherebehavior,criminalteamslikecartelsorinstitutionsof
organizedcrimeareprosecutedwithleniencyprogramsthattrytoinduce
mistrustamongtheteammembersbygrantinghighfinereductionsoreven
subsidiesforconfessingcriminals.Intheeconomicanalysistwofundamental
casesneedtobedistinguished.Inthesocalledsingleviolatorcase,each
individualactsonhisown,anditcaneasilybeshownthatreducingthefines
forconfessing(orself-reporting)violatorswillthenalwaysleadtoalower
expectedfineiftheauthority’sinvestigationeffortisnothigherthaninthe
situationwithoutself-reporting.Thisfollowssimplyfromthefactthat(risk
aversionexcluded)aviolatorwillnevercomeforwardifthisincreaseshisex-
pectedfine.Infact,theliteraturehasshownthattheincentivetoviolatewill
alwaysbehigherwiththepossibilityofself-reportingifaviolatordoesnot
knowwhetherhewillself-reportornotatthemomentwhenhecommitsthe
crime(i.e.inthepresenceofasymmetricinformation)-andthisisclearly
therelevantcaseinmany,ifnotinalmostall,circumstances.Nevertheless,
eveninthesingleviolatorcase,therearemanygoodreasonstoacceptthis
weaknessoffinereductionsastherearealsomanyadvantages.First,self-
reportingviolatorsdonothavetobedetected,andthissavesinvestigation
costs.Second,theauthoritymaygethigher(expected)revenues,whichhas

1

ODUCTIONINTR1.CHAPTER

2

widelybeenemphasizedinthecaseoftaxamnesties,forinstance.Third,it
maybeimportantthattheauthoritylearnsaboutthecriminalcaseasearly
aspossibleinordertoundertakecost-reducingcountermeasures.Fourth,
I-errorconfessionsthatmaguiltyyhelptodefendanreducetsarebothtexoneratedypesofanderrorstheintypecourtII-error(i.e.thethattypin-e
nocentdefendantsareconvicted).Finally,theincentiveofviolatorstoinvest
in(soThiscially)maycostlyillustrateevasionthatthestrategiesauthoritmayyfacesdiminish.atrade-offwhendesigning
self-reportingschemesinthesingleviolatorcase:Althoughtherearemany
toadvanviolatetagesaoflawfineifthereductions,authorittheyy’sinvinevitablyestigationenhanceefforttheisextheantesame.incentivThise
situationchangesdrasticallywhencriminalteamsareconsidered.Then,the
strategicinterdependencebetweentwoormoreviolatorscanbeexploitedto
decrincreaseeases.theTheexpideaectedisfinecloselyofeachrelatedviolatortotheevenifPrisoner’stheDilemmamonitoring-prsinceobeacabilityh
participantofacriminalteamknowsthathisriskofbeingconvictedincreases
itifhismaybeaccompliceanequilibriumconfesses,hethatmaallyhavteameanmemincenberstivetrytotoconfess,bethetoo.firstHence,one
toself-report,althoughallofthemcouldbebetteroffiftheywereable
tocrediblycommitthatnooneofthemself-reports.Clearly,theoriginal
beenPrisoner’sdetected,Dilemmabuttherefersbasictoideathecarriessituationsovertowherethethepre-detectionviolatorshavstageealreadyunder
certaincircumstances.Thisisexactlytheideaofaracetothecourtroom
thatToisexploitedsummarize,inancorpeconomicorateleniencyanalysisofprogramsself-rep(seeortingchapterin2).optimallawen-
forcementhastoincorporateasymmetricinformation(abouttheindividual
detectionprobabilitiesofeachviolator)andstrategicinteractions(among
membersofcriminalteams).Thisisthecentralissueofthethesis.

tributionCon1.2Ofcourse,understandingourcontributionsandtheirmotivationrequiresfirst
aincdescriptionhapters2ofandthe3,legalrespectivsituationely.andThethesubsequenliteraturetcwhichaptershwill4-7bewillprovidedthen
violatorsummarizecasefour(chaptersresearch4papanders5)anddealingthewithmultipleself-reportingviolatorbothcasein(cthehapterssingle6
7).and

1.CHAPTERODUCTIONINTR

3

Inthefirstmodelforthesingleviolatorcase(describedinchapter4),
weanalyzetheimpactofexpostasymmetricinformationontheauthority’s
optimalbehaviorthatconsistsofcostlymonitoringandfinereductionfor
self-reportingindividuals.Byexpostasymmetricinformation,weaccount
forthefactthatviolatorswillonlycomeforwardiftheyrealizeafterthe
violationthattheirindividualdetectionprobabilities(the