learning about real economics in virtual worlds microeconomics/spring... · learning about real...

LearningAboutRealEconomicsinVirtualWorlds

DavidS.AbramsUniversityofPennsylvania

April5,2011

[Preliminary]

Virtualworldsprovideanopportunityforanentirelyneweconomicresearchmethodology.

With tens of millions of users, billions of dollars (US) in virtual production, and many

characteristics of real‐world economies, for the first time economists have access to a

venue with the realism of the field and control of the laboratory. Virtual worlds

additionallyprovideaccess toasubjectpool farmorediversethan ispossible inasingle

physicallaboratory.Inordertoextrapolatefromvirtualworldresultstorealeconomics,it

is imperative tounderstandeconomicbehavior invirtualworlds. Thispaperdoessoby

investigatingtwocommoneconomicgamesandonepuzzleinthevirtualworldofSecond

Life. Comparedwithnumerousstudiesfromaroundtheworld,individualsinSecondLife

exhibitbehaviorindistinguishablefromlabexperimentsintheultimatumandtrustgames

andMontyHallproblem. PlayerswithgreaterexperienceandattachmenttoSecondLife

exhibitgreaterother‐regardingbehaviorinsomeofthegames.Thesefindingsshouldhelp

allay concerns about the external validity of findings on economic behavior in virtual

worlds.

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I.Introduction

Inthepast5years,therehasbeenadramaticincreaseinparticipationinwhatareknown

asMassivelyMultiplayerOnlineGames(MMOGs)orVirtualWorlds.Thesearesimulated

worldsthatexistbyvirtueofnetworkedcomputersandtheindividualswhousethem.In

thispaperIreportresultsfromtwoclassiceconomicexperimentsandonestatistical

problemruninavirtualworld.Thegoalistoinvestigateeconomicbehaviorinvirtual

worldswithaneyetowardsusingthemasnewvenuestogainrealworldinsightsabout

economics.

VirtualWorldsholdthepromiseofexperimentsthathavetherealismofthefieldandthe

controlofthelaboratory.Criticsallegethatthelaboratorysettingisunnaturalandlimits

theabilitytogeneralizeto“real‐world”economicsettings.Whileanelectroncaughtina

laboratorytrapwillstillactlikeanyotherelectron,apersonbeingpaidtositinfrontofa

computerforanhourinaneconomicexperimentmaynotbehavethesamewayasinareal

jobormarket.

Thecompositionofsubjectpoolsisanothertopicofcriticismofeconomicexperiments.

Experimentalsubjectsaretypicallyrecruitedfromtheundergraduatepopulationsof

researchuniversitieswheretheexperimenterswork.Thisspecializedbackgroundmay

substantiallyinfluencethegeneralizabilityofthefindings:aCaltechundergraduateseated

infrontofacomputerscreenmaynotcloselyresembleatraderinthefuturespitofthe

ChicagoMercantileExchange.

RunningexperimentsinVirtualWorldsissubstantiallyeasierthantraditionallaboratory

experiments.VirtualWorldsprovidealloftheessentialelementsofcurrentlaboratory

environmentsready‐made:ascriptinglanguageinwhichtodesigntheexperiments;a

computernetworkoverwhichsubjectsintheexperimentmayinteract;apoolofsubjects,a

data‐collectionsystem,andamethodofincentivizingsubjects.Forexample,inSecondLife,

anexperimentercancreateaprivate(orpublic)laboratorywithobjectsthatindividuals

canbuyorselltootherindividuals;orgamblestheycanchoosetopartakeof.Thereare

somestart‐upcoststolearninganynewlanguage,butoncemastered,thescripting

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languagesallowmuchmoreflexibilitythancommonlyusedexperimentalsoftware

packages.

AllVirtualWorlds,bytheirnature,havelargepopulationsofindividualsinteractingover

networkedcomputers.Someofthegames(seeFigure1andTable2)havemillionsof

potentialexperimentalsubjects,withlowcoststoexperimentalparticipation.Economic

experimentsarelikelytobeattractivetoVirtualWorldresidents,whoviewthemas

anotheruser‐generatedactivityinwhichtoparticipate.InSecondLife,thescripting

languagemakesiteasytoexportresultsfromin‐gameexperimentintoanout‐of‐game

database.Finally,allVirtualWorldshavesomeformofin‐gamecurrencywhichcanbe

usedtoincentivizeexperimentalsubjects.

ButwithallofthepotentialbenefitsofperformingeconomicresearchinVirtualWorlds,it

willbelittlemorethancuriosityifitdoesnotgeneralizetoreal‐worldeconomicsettings.

Themoststraightforwardwaytotestthisistocompareexperimentswithwell‐known

resultsinmultiplesettingstothoseinavirtualworld.IchooseSecondLifeasthevirtual

worldinwhichtoruntheseexperimentsbecauseofitsdiverseuserbase,easeofuse,and

resemblancetorealeconomies.

ThreeexperimentswereruninSecondLifetoinvestigatetheimpactofthevenueon

economicbehavior:theultimatumgame,thetrustgame,andtheMontyHallproblem.Inall

threegamesthebehaviorexhibitedbysubjectsinSecondLifeisindistinguishablefromthat

foundinothersettings.Inaddition,relativetomosteconomicexperiments,thesubject

poolswerevastlymorediversealongseveraldimensions,includingageandnationality.

Thesefindingssuggestfurthereconomicresearchinvirtualworldsmaybeprofitable,

giventhatbehaviorseemstoreflectthatobservedintherealworld.

Therestofthepaperproceedsasfollows.InsectionII,Iprovideabriefbackgroundon

virtualworldsingeneralandSecondLifemorespecifically.SectionIIIpresentsthe

experimentalsetupoftheultimatumgame,itsimplementationinsecondlife,results,and

comparisonwiththeliterature.SectionsIVandVdothesameinturnforthetrustgame

andMontyHallproblem.SectionVIdiscussesthefindingsandrelatedliteratureand

sectionVIIconcludes.

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II.Background

IntroductiontoVirtualWorlds

AVirtualWorldisapersistent,interactiveonlineenvironment,inwhichmanyindividuals

mayparticipatesimultaneously.VirtualWorldsresembletherealworldtovaryingdegrees

ApersonaccessesandparticipatesintheseVirtualWorldsthroughan“avatar,”whichisa

digitalrepresentationoftheuserintheVirtualWorld.VirtualWorlds,asIusethetermin

thispaper,datetoapproximately1996.Likethephysicalworld,theVirtualWorldismade

upofsocialnetworksandcommunities,inwhichplayersmustmakedecisions,interact

socially,andlivewithintheboundssetbythegame’sdeveloperorwithinthosesetbythe

online“society.”

ManyofthelargestvideogamemakersareinvolvedincreatingVirtualWorlds,including

Sony,Vivendi,andElectronicArts.Althoughrevenuefiguresarenotfullyavailable,

subscriptionestimatesareimpressive.Themostpopulargamealone(WorldofWarcraft)

generatesannualsubscriptionrevenueinexcessof$1billion,fromsevenmillionusers.

Table2detailsusernumbers,subscriptionfees,softwareretailprice,andother

informationforallofthetopVirtualWorlds.

VirtualWorldsmaybesplitintotwobroadcategories:role‐playinggames(i.e.,MMORPGs),

andanotherclasswhichIcallenhanced‐realitygames.Role‐playinggameshaveclearly

definedobjectivesforplayers,andtaskstheymayperformforreward.Thesegamesoften

havefantasysettings,suchasmedievaldragon‐slaying(FinalFantasy)orspacetravel(Star

WarsGalaxies).Someofthemostpopulartitlesintherole‐playinggenreareWorldof

Warcraft,Everquest,andFinalFantasy.

Whiletherole‐playinggamesweretheentireuniverseofVirtualWorldsforthefirst

severalyearsoftheirexistence,theenhanced‐realitygameshavebeengainingmarket

shareinthepastthreeyears(seeFigure1).Unlikeinrole‐playinggames,thereisnoclear

objectivetoenhanced‐realitygames,anymorethanthereisaclearobjectivetoreallife.In

enhanced‐realitygames,usersengageinmanyofthesameactivitiesasintherealworld:

socialize,shop,producegoods,performservices,ownland,andevendance.These

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enhanced‐realitygamesalsoattractademographicthatmorerepresentativeoftheoverall

populationthanrole‐playinggames,whichtendtoattractmostlyyoungermales(seeTable

1).SecondLifeisthemostpopulargameinthiscategoryofVirtualWorlds.

WhileuserdemographicsaredifficulttoacquireitisapparentthatsomeVirtualWorlds

havedemographicsthatfairlycloselyresembletherealworld.InTable1wefindthatthe

meanageofthegame‐playersrangesfrom24.3forEverquestin2001to32forSecondLife

inMarch,2006.Themorerecentfigurestendtobehigher,perhapsbecauseearlyadopters

ofthistechnologytendtobeteenagersandcollegestudents.TheSecondLifefigureisnot

veryfarfromthecurrentU.S.medianageof36.4.Moreover,medianhouseholdincomeof

Everquestplayersin2000‐2001isnotfarfromtheU.S.level.Thefractionofplayersof

popularMMOG’swhoaremarriediswellbelowthenationalaverage,butthisis

unsurprisinggiventheloweraverageage.AsurveybyYee(2006a)foundthatalmost

three‐quartersofusersarestudentsorholdfull‐timejobs,which,conditioningonage,is

fairlyrepresentative.Finally,genderratiosareskewedtowardmalesformostgames,

althoughSecondLifeandSimCityareveryclosetoaratioofone.Altogether,itseemsclear

thatVirtualWorldshavemorerepresentativepopulationsthantheundergraduate

populationsoflargeresearchuniversitiesinseveralimportantobservabledimensions.

IntroductiontoSecondLife

SecondLifeisavirtualworldthatresemblestherealworldinmanyimportantways.There

isemployment,homeownership,acurrency,production,andmanyotheraspectsofreal

lifeandtherealeconomyinSecondLife.ThecurrencyiscalledtheLindenDollar($L)and

ittradesonanexchangecalledtheLindex.ThereisaspotmarketfortheLindenDollar

againstanumberofmajorcurrencies.Theexchangeratehasgenerallyrangedbetween

240to260LindenDollarsperU.S.dollarforthepastseveralyears.Theexchangeand

currencyarenamedforLindenLab,thecompanythatcreatedSecondLife.

SecondLifeusersmayplayforfree,butmustpayasubscriptionfeeofaround$15per

monthiftheywishtoownland.Realestateandhousingareimportantcentersofeconomic

activityinSecondLife,andexperiencedabubble,muchasintherealworld.Fashionis

anotherareaofsignificantactivity.

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Likeothervirtualworlds,individualsinteractinSecondLifethoughavatarsandmay

communicatethroughtextchatsaswellasvoice.Thereareseveralwaystoestimatethe

game’sreach.SeveralmillionindividualshaveusedSecondLifeatsomepoint,but

simultaneoususersisprobablyabettermetricofactiveplayersandiscloserto90,000.

Thislikelyimpliesagroupofseveralhundredthousandwhohaveloggedoninthepast

month.AnumberofindividualsworkfulltimeinSecondLife,andatleastoneU.S.dollar

millionairehasbeenmintedthere.TheannualGDPofSecondLifemeasuresinthe

hundredsofmillionsofdollars(US).

WhereDoVirtualWorldExperimentsFitintheExperimentalTaxonomy?

Someofthecriticismsoflaboratoryexperimentshaveledtoanincreaseinpopularityof

fieldexperiments,whereresearchersincorporateexperimentaldesignintoasettingthatis

morenaturalforthesubjects.Thetradeoffofcourseisthatingaininggreaterrealism,the

experimentersoftensacrificesomedegreeofcontrol,reproducibility,orprecision.

HarrisonandList(2004)andLevittandList(2006)laythegroundworkforthe

classificationofdifferenttypesofexperimentsandtheirrelativestrengths.VirtualWorlds

offertheopportunitytotakeadvantageofthe“naturalness”offieldexperiments,while

retainingcontrolandoperability.Byrunninganexperimentwithinanenvironmentin

whichusersaresocomfortablethatmanyrefertothemselvesasresidents,oneshould

expectresultstobemorereproducibleandlesssensitivetosmallvariationsin

experimentaldesign.SincemostVirtualWorldshavevariedpuzzles,challenges,and

games,manycommoneconomicexperimentswouldseemquitenaturaltoauser.

Severalrecentstudieshaveindicatedtheimportanceofusingexperimentalsubjectpools

thataremorerepresentativeofthepopulationofinterest.HaighandList(2005)find

significantlydifferentbehavioraldifferencesbetweenstudentsandprofessionaltradersin

atradingexperiment.FehrandList(2004)alsofindsubstantialdifferencesbysubjectpool

fortrustexperimentsrunonCEO’sandstudents.Anumberofexperimentshaveshown

genderdifferencesineconomicexperiments,forexampleasreportedbyGneezyand

coauthors(2003)forpuzzlecompetitionsandGuillenandVesteg(2006)foralargearray

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ofexperiments.Replicatingwell‐knownexperimentsinVirtualWorldscanincreasethe

understandingofsubjectpooleffects,andhelpvalidateresultsthatseemrobusttothem.

GneezyandList(2006)describeanexampleofarecentfieldexperimentthatcould

potentiallybenefitfromtranslationintoaVirtualWorld.Theytesttheimpactofgift

exchangeinalabor‐marketsetting,byhiringshort‐termworkerstodotwodifferenttasks.

Forexample,inaVirtualWorld,onecouldhirealargenumberofindividualslong‐termto

producevirtualwidgets,thathavearealin‐gamevalue,andrandomizewhichworkers

receivethe“gift”wage.Thissetuphasseveraladvantages.Theincreaseddurationof

employmentaddstherealisticpossibilityofsubjectsbeingfired,whichcouldhavean

importantimpactontheeffectofgiftexchange.Withhundredsofthousandsofvirtual

residentsaspotentialsubjects,thesubjectpoolcouldbesubstantiallylargerthanthatof

thereal‐worldstudy(wheren=19and23inthetwopartsoftheGneezyandListstudy).

Finally,theVirtualWorldstudywouldretainoneofthemostimportantvirtuesoffield

experiments,namely,aneconomicenvironmentwhichisnaturalandfamiliartothe

subject.

III.UltimatumGame

Theultimatumgameisthedrosophilaofeconomicexperimentsandassuchitis

perfectmechanismforcomparingeconomicbehavioracrosssettings.Theultimatumgame

hasbeenruninalargenumberofgeographiclocations,withdifferentsubjectpools,and

variedstakes.Likethefruitfly,thewidespreaduseoftheultimatumgamemakestherange

ofresultswell‐knownandthusitiseasytoevaluatenewimplementationsofit.

IcreatedalaboratoryinSecondLifewiththegoalofmakingtheultimatumgame

experimentsrunthereascomparabletolaboratoryexperimentsaspossible.1

Recruitment

1 As will be seen, some things will inevitably differ in Second Life.

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Subjectswererecruitedintwoways,eitherviadirectapproachbyaresearchassistant

avatarorthroughin‐worldadvertisement.Thedirectapproachrecruitmentwas

performedbyRAavatarsapproachingindividualschosenatrandomfrompopularareasin

SecondLife.Thebeginningofthescriptisasfollows:

Hey, would you like to participate in a decision making experiment for

UniversityofChicagoresearch?It’llonlytake10‐20minutesandyougetL$

500 just for participating. You could earn a significant amount more

dependingonhow it goes.All youneed todo is teleport to the landmark I

sendyouandthenplayashortgame.You’llgetinstructionsthattellyouhow

toplay.Onceyou’redonetherewillbeashortsurveyandthenyougetpaid!

IM2meifyou’reinterested.

Ifindividualsexpressinterest,theyaregivena“landmark”whichallowsthemtobe

transporteddirectlytotheinsideofthelaboratory.

SecondLifealsohasacentralizedclassifiedadvertisementsystemwithvariouscategories,

includingemployment.Theposteroftheadvertisementmaypayanyamountofmoneyfor

theservice,andtheamountdeterminestheorderinwhichtheadsaredisplayed.Forthe

experimenttheadwasalwaysdisplayedinthetop5or10,ensuringitappearedonthefirst

pageofresultsforemploymentclassifiedads.Thetextfollows:

AreyouinterestedinearninguptoseveralthousandLindenDollarsfor10‐

20minutesof your timebyparticipating inaneconomicexperiment? You

are guaranteed 500 Linden Dollars for participating, and can earn several

thousand more depending on your performance. Please email

[email protected].

Individualswhoemailedaresponsetotheseadswereoftencontactedviainstantmessage

whentheywereobservedtobeonline.Regardlessofrecruitmentmethod,stepswere

alwaystakentoensurethatthetwoplayersinthegamedidn’tknoweachother.Ifin‐

worldrecruitmentwasused,twoplayerswererecruitedsimultaneouslyintwodifferent

2 Instant Message

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areasofSecondLife.Individualswhorespondedtoadswereoftenpairedagainst

individualsrecruitedin‐world,tominimizelikelihoodofcoordinationwithaconfederate.

Oncethepairofplayerswasrecruited,theywerebothtoldtotransportthemselvestothe

experimentallab,describedbelow.

LaboratoryDesign

Inreal‐worldeconomiclaboratories,oneofthechallengesisensuringthatsubjectsdonot

knoweachotherorinteractsignificantlypriortotheexperiment.Thisisrelativelyeasyto

accomplishinSecondLife,bycreatingalaboratoryconsistingoftwophysicallyseparate

spaces,withcommunicationbetweenthetwoaccomplishedonlythroughthegame.Itis

alsopossibletoteleportdirectlyintothelaboratory,anditslocationisonlyrevealedto

recruitedsubjects.Inaddition,SecondLifehaslandaccesspoliciesthatmakeitpossibleto

prohibitsubjectsfromreturningtothelaboratoryassoonastheexperimentends.

Inordertoimplementthissetup,Icreatedtwocubescontainingtheexperimentalsetupon

landpurchasedinSecondLife(Figure2A).3Theinteriorswerekeptsparse,withan

identicalcouchandcoffeetableplacedineach(Figure2B).Onthecoffeetableisaredball,

andthesubjectistoldtoclickonittobeginthegame.Clickingtheballactivatesthe

programscriptthatimplementstheultimatumgameexperiment.

GameStructure

Inorderfortheexperimenttobeginbothplayer1(theproposer)andplayer2(the

responder)mustclickontheredball,whichbeginstheexperiment.Thisissimilartomany

laboratorysettingswhereindividualsatdifferentcomputerterminalsmustacknowledge

readinessbeforetheexperimentbegins.Subjectsreceiveinstructionsthrougha“notecard”

whichisadigitalblockoftextthatisgiventoeachplayeroncethegamehasbegun.Asin

standardimplementationsoftheultimatumgame,playersaregivenidenticalinstructions

andarefullyinformed.4

3 Unbeknownst to the subjects, the cubes actually floated in the air, something irrelevant to the experimental design, but particularly difficult to accomplish in real‐world laboratories. 4 The full instructions are provided in Appendix A.

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Inordertoensurethatplayersfullyunderstandthestructureofthegameandminimize

spuriousresults,subjectsaregiventwoconcreteexamplesandthenaskedwhatpayoffs

wouldresultfromahypothetical.Oncethehypotheticaliscompletedcorrectly,themain

experimentbegins;ifitisnotansweredcorrectlywithinthreetries,thesubjectsaretold

theywillnotbeabletoparticipate.Subjectsprovideresponsesbytypingintoachat

window.

Theultimatumgamesetupisstandard:thefirstplayerisgivenasumofmoneytoallocate

betweenhimselfandplayer2,thenplayer2decideswhetherornottoacceptthe

allocation.Ifplayer2acceptsit,bothplayersarepaidaccordingtoplayer1’sallocation;if

not,bothplayersreceivenothing(beyondasmallamountforshowingup).Inthis

implementation,eachsubjectispaid$L500forshowingup,andplayer1dividesasumof

$L1500,worthabout$6(US).TheNashEquilibriumtothesequentialone‐shotgameis

well‐known:player1allocatesthesmallestincrementpossibletoplayer2(here,$L1)and

player2acceptstheoffer.

Results

Asinvirtuallyalllaboratoryimplementationsoftheultimatumgame,subjectsinSecond

Lifeplaystrategiesfarfromgametheorypredictions.Themedianofferis$L700(47%of

thepie)withameanof$L602(Table3).Theofferisonlyrejected6%ofthetime,and

rejectedoffersaverageonly$L392.ThefulldistributionofoffersmaybeseeninFigure3.

OneofthemajoradvantagesofSecondLifeasanexperimentalvenueistheunprecedented

breadthofsubjectcharacteristics(Table4).Aftercompletionoftheultimatumgame,

subjectswereaskedtoanswerashortsurveyabouttheirreal‐worldcharacteristicsbefore

theywerepaid.Subjectsrangefrom17‐55yearsofage,withameanof32.Themajority

(58%)areAmerican,butaboutathirdarefromEurope.The106subjectsinthe

experimentrepresent19differentcountries(Table5).Femaleparticipantsmakeup

almosthalf(45%)ofthesubjectsandalmostallarefluentinEnglish.

ThreedifferentquestionswereaskedinordertogetameasureofattachmenttoSecond

Life.Thereiswidevariationinweeklyhoursspentinthegame,from0toamaximumof

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80,withamedianof15.Whilethesenumbersmayappearhigh,oneshouldkeepinmind

thatforsomeSecondLifehasdisplacedwatchingtelevision(whichaverages34hoursper

week,accordingtoNielsen,butonly20hoursperweekaccordingtotheBLS).Asurveyof

MMOGuserssupportsthissubstitutionexplanation,findingonly7hoursoftelevision‐

watchingperweek(Yee,2005).ManyofthesubjectsarerelativenewcomerstoSecond

Life,withlessthanhalfayearexperiencewiththevirtualworldonaverage.About20%of

usersownlandinSecondLife,whichrequiresthepaymentofamonthlyfee.

InTable6theoffersarebrokendownbyusercharacteristics.Nationalitydoesn’thavea

significantimpactonoffersize,nordoesgender.Butolderuserstendtomakehigher

offers(p<0.05)asdothosewithmoreattachmenttoSecondLifebyseveralmeasures.

Landownersoffersubstantiallymorethannon‐owners,althoughthedifferenceisnot

statisticallysignificant.ButindividualswhohaveusedSecondLifeformorethanamonth

offeronaverageabout50%morethanthosewhohavelessthan1monthofexperience(p

<.01).Asimilarpatternofgreatergenerosityemergeswhencomparingthosewhoplay

overanhourperdaywiththosewhoplaylessthanonehour(p<.10).

ComparisonwithPriorWork

Theprimaryreasonforyetanotherimplementationoftheultimatumgameistocompare

theresultsobtainedinSecondLifewiththosefoundinexperimentsruninexperimental

settingsaroundtheworld.Fortunately,thegameiseasytoquantifyandcomparisonsmay

bemadealongtwodimensions:meanofferandrejectionrate.Oosterbeek,etal(2004)

collectthisdatafrom75studies,whichmakesthecomparisonstraightforward(Tables7A

&7Bwhichreportthesamedata,butsorteddifferently).

FromTable8onecanobservethatthevastmajorityofoffersarebetween35and45%of

thepie.ThemeanofferinSecondLifeiswithinonepercentagepointoftheoverallmean.

Study‐leveldataisnotreportedinOosterbeek(2004)soIamunabletocalculatetheexact

standarddeviationofthedistribution.ButifIweighteachcountrybyfrequency,the

standarddeviationisabout4percentagepoints.ThemainfindingisthatoffersbySecond

Lifesubjectsarenotsignificantlydifferentfromthosefoundinlaboratorystudies.

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Whenexaminingrejectionrates(Table7B),theSecondLiferesultsappeartobeonthelow

end.However,thereismuchgreatervariationinrejectionratesthanofferrates.A

calculationofrejectionratesfromtheOosterbeekmetastudyyieldsameanof16%anda

standarddeviationof7%.Thustheobservedrejectionrateof6%iswellwithinthenormal

rangereportedinultimatumgamestudies.

Tosummarize:TheultimatumgameinSecondLifeappearstohaveresultsthatarenot

significantlydifferentfromthosefoundinlaboratorygamesrunaroundtheworld.Asin

mostlaboratoryresults,Ifindthatsubjectsaremoregenerousthangametheory

predictionsandrejectmorefrequently.Ialsofindthatolderplayersandthosewith

greaterattachmenttothegametendtobemoregenerouswiththeiroffers.Oneofthe

majoradvantagesofSecondLifeasanexperimentalvenueistheabilitytoquicklyand

easilyassemblearemarkablydiversepoolofsubjects,makinganalysisbysubject

characteristicssimple.

IV.TrustGame

Aftertheultimatumgame,thetrustgameislikelythemostwidelyreplicatedeconomic

game.Liketheultimatumgame,italsoyieldschoicesthatdeviatesubstantiallyfromgame

theorypredictionsandwhichtendtoexhibitsometypeoffairnesspreferences.Inorderto

provideanothermethodofevaluatingeconomicbehaviorinSecondLife,Iimplementedthe

trustexperiment.

Muchofthesetupforthetrustgameisidenticaltothatfortheultimatumgame.

Recruitmentofplayerswasboththroughclassifiedadsandin‐worldcontactandidentical

laboratorieswereused.

GameStructure

Asintheultimatumgame,subjectsreceiveinstructionsthrougha“notecard”andthen

respondbytypinganswersintoachatwindow.5Subjectsarerequiredtoanswera

hypotheticalcorrectlywithinthreeattempts;otherwisetheyareremovedfromthegame.

5 See full instructions in Appendix A.

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Thetrustgamesetupisstandard:thefirstplayerisgiven$L1500toallocatebetween

himselfandplayer2.Whateverheallocatesistripledandgiventoplayer2whothenhas

theopportunitytosendbacksomeportionofwhatshehasreceivedtoplayer1.TheNash

Equilibriumtothesequentialone‐shotgameiseasilyarrivedatthroughbackward

induction:player1allocatesnomoneytoplayer2andplayer2sendsnomoneyback.Each

playerreceives$L500asashow‐upfeeinadditiontowhattheyearnthroughthegame.

Results

Subjectsplayingthetrustgameinthelaboratoryrarelyexhibitequilibriumplay,nordo

theyintheSecondLifeimplementation.InTable8wefindthatthemedianoffermadeby

thefirstplayeris$L500,33%ofthemaximum,withastandarddeviationof$L430.The

medianreturn($L475)issimilar,about32%oftheinitialstakes,withastandarddeviation

of$L801.Only8of56playersinthesecondpositionreturnednothing,andthreeofthose

couldnothavedoneotherwise,sincetheyreceivednothingfromthefirstplayer.

ThefullsetofoffersandreturnsisdisplayedgraphicallyinFigure4.Ifallplayer2’swere

purealtruists,allofthedatawouldlieonthetopline,asthesecondplayerreturnedthefull

sumreceivedtothefirst.Ifthesecondplayerbelievedinevenlysplittingthemoney,the

datawouldlieonthelowerline.Onecanseethatthereisapositivecorrelationbetween

offersandreturns,butmostplayer2’sreturnlessthananevensplit.

Subjectcharacteristicsaresimilartothosefoundintheultimatumgame(Table9).About

halfaremale,meanageis32,and60%areAmericansandaquarterareEuropean.The

112subjectsintheexperimentrepresent19differentcountries,notallthesameasthose

representedintheultimatumgame(Table10).TheyspendagooddealoftimeinSecond

Life(meanof22hoursperweek)andhaveplayedthegamefor5monthsonaverage.

Thereissubstantialvariationinamountoffered,soeventhoughtherearelargedifferences

bysubjectcharacteristics(Table11)theyareallstatisticallyinsignificant,exceptfor

weeklyusageofSecondLife.There,individualswhoplay1‐3hoursperweekofferan

averageof$L250morethanthosewhoplaylessthan1hourperweek(p<.10).

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Theamountreturnedbyplayer2variesevenmoregreatlythanamountofferedbyplayer

1.Still,therearesomesubjectcharacteristicsthatarecorrelatedwithamountofreturn

(seeTable12).Americansreturnabouthalfasmuchasindividualsfromothercountries(p

<.05)andwomenreturnfarlessthanmen(p<.10).Olderplayersreturnsubstantiallyless

onaverage,althoughthisdifferenceisnotstatisticallysignificant.Thefindingsby

attachmenttoSecondLifearenotasunambiguousasintheultimatumgame,wherethose

withgreaterattachmentbyseveralmeasurestendedtoexhibitmoreother‐regarding

behavior.Inthetrustgame,landownersreturnmoremoneyasdothemostintense

players(thoseaveragingoverthreehoursperday),butthesedifferencesarenot

statisticallysignificant.Further,playerswiththegreatestexperiencewiththegameappear

tobetheleastgenerous,althoughthedifferencesbyexperienceinreturnratesare

relativelysmallandstatisticallyinsignificant.

ComparisonwithPriorWork

ForcomparisonofSecondLifetrustgameresultswithpreviouswork,Irelyonarecent

metastudybyJohnsonandMislin(2009).Theauthorsreporton85different

implementationsofthetrustgame.Theirprimaryoutcomevariablescorrespondtothose

reportedabove,namelyamountofferedbyplayer1andamountreturnedbyplayer2.

JohnsonandMislinreportthereturnratenormalizedbytheamountavailabletoreturn.

Forthisstudythemeanofthismeasurewillsimplybethemeanreturndividedbythree

timesthemeanoffer,whichis35.1%.Themeanofferrateof39%maybefoundinTable8.

Thesevaluesarebothwellwithinonestandarddeviationofthemeanratesreportedinthe

metastudy.Themeanofferis50.9%ofthestakes,withastandarddeviationof13.8%.The

meanreturnis36.5%oftheamountavailable,withastandarddeviationof9.4%.In

Figures5and6IoverlaytheSLresultsonthedistributionsreportedinJohnsonandMislin.

Mostoftheofferratesfallbetween30and65%.Whilethe39%offerrateintheSecond

Lifetrustgameisslightlyonthelowend,itisclearlywellwithinthebulkofthe

distributionreportedintheliterature.Thedistributionofthereturnedfractionisalso

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relativelydispersed,rangingfromabout20–50%.Here,theSecondLifereturnfractionis

rightinthemiddleofthedistributionfoundintheliterature.

Aswiththeultimatumgame,individualsplayingthetrustgameinSecondLifeappearto

behaveinwaysindistinguishablefromthoseinothersettings.Asintheultimatumgame,

individualswithgreaterattachmenttoSecondLifegenerallyappeartoexhibitmoreother‐

regardingbehaviorinthetrustgame.Americansappeartobelesstrustworthy,asdo

women,witheachgroupreturningabouthalfofthecomparisongroup.Iexploresomeof

theseresultsfurtherinthediscussion.

V.MontyHall

Unlikethefirsttwoexperiments,theMontyHallproblemisnotaneconomicgame,but

ratheraone‐persondecisionproblem.Itisawell‐knownpuzzlethatprimarilytests

Bayesianupdating.ItwaschosenforreplicationinSecondLifebecauseitisamongthe

mostwidely‐knownone‐playerproblemsintheeconomicsliterature.

GameStructure

TheMontyHallplayerispresentedwithachoiceofthreedoors,behindoneofwhichliesa

valuableprize(seeFig2C).Theplayermustchooseadoor,andsubsequentlyoneofthe

unopeneddoorsisopenedtorevealthatitdidnotholdtheprize.Thecontestantisthen

giventheopportunitytoswitchhischoice,whichwillthenbefinal,andthelocationofthe

prizerevealed.Theimportantdecisioninthisproblemiswhetherornottoswitchdoors

whengiventheopportunity.Reasoningthroughthebestchoiceisdifficult,butwriting

downtheprobabilitiesusingBayesrulerevealsthatitisalwaysoptimaltoswitch

(increasingtheprobabilityofwinningfrom1/3to½).

Recruitmentandlaboratory

SubjectswererecruitedfortheMontyHallprobleminthesamewaysasfortheultimatum

gameandtrustgame.Subjectcharacteristics(notreported)areverysimilarasforthe

ultimatumandtrustgames.AseparatelaboratorywasbuiltfortheMontyHallproblemto

15

physicallyrepresenttheproblem(Figure2c).Thesubjectstandsbeforethethreedoors,

clicksoneforhisfirstchoice;oneoftheremainingdoorsopenstorevealnothingbehindit,

andtheuserthenhastheoptiontoclickontheoriginaldoorortheotherunopenedone.

Thechosendoorisopenedandsuccessisindicatedbyanimageofgoldcoins.Thestakes

are$L500perround,andeachsubjectplays10rounds.TheinstructionsfortheMontyHall

problemarepresentedinAppendixA.

ResultsandComparisonwithPriorWork

TherearetwomainfindingsfromtheimplementationoftheMontyHallprobleminSecondLife.First,asinotherstudies,subjectsgetbetterwithexperience(Figure7).Thatis,theyaremorelikelytoswitchthehighertheround.Theresultisstatisticallysignificantatthe5%level.

InTable13,IreportthemainresultsoftheSecondLifeimplementationoftheMontyHallproblem.Themeanswitchrateoverallroundsis33%,whichisinthesamerangefoundinanumberofotherstudies.ThereisnometastudyoftheMontyHallproblemthatIamawareof,soinordertocomparetheSecondLiferesultstotheliterature,Icollectedotherstudiesbyhand.Thereissubstantialamountofvariationintheswitchrateinthesestudies(from19to53%),andtheresultsfromthisstudyarefirmlyinthemiddle.Thuseveninaone‐playerproblem,SecondLifesubjectsresultsareconsistentwiththatfoundintheliterature.

VI.Discussion

[Tobeadded]

VII.Conclusion

Virtualworldsholdthepromiseofanewtypeofexperimentallaboratoryforthesocialsciences.Theyholdthepotentialtotestamuchbroaderrangeofeconomictheorythaninthetraditionallaboratories,fromlaboreconomicstomacroeconomics.Butinorderfortheseexperimentstobeundertaken,theremustbesomeexpectationthatthesystemsstudiedareinformativeofreal‐worldeconomics.

Towardthisend,Ihavereplicatedtwowell‐knowngamesandonepuzzleinthevirtualworldofSecondLife.Ifindsubjectplayintheultimatumgame,trustgame,andMontyHallproblemisindistinguishablefromthatobservedinalargenumberofreal‐worldstudies.Further,Ifindsubjectpoolsthatareincrediblydiverseacrossanumberofcharacteristics.Thisallowsfortheexaminationofheterogeneityofeffectsacrossanumberofdimensions.

16

References Angeletos,George‐Marios,DavidLaibson,AndreaRepetto,JeremyTobacman,Stephen

Weinberg."TheHyperbolicConsumptionModel:Calibration,Simulation,andEmpiricalEvaluation."InTimeandDecision:EconomicandPsychologicalPerspectivesonIntertemporalChoice,517‐43:NewYork:RussellSageFoundation,2003.

Browning,MartinandAnnamariaLusardi.“HouseholdSaving:MicroTheoriesandMicro

Facts.”JournalofEconomicLiterature32(1996):1797‐1855.Castronova,Edward.“Virtualworlds:Afirst‐handaccountofmarketandsocietyonthe

cyberianfrontier.”Availableathttp://ssrn.com/abstract=294828.(2001)________.“Thepriceof'man'and'woman':Ahedonicpricingmodelofavatarattributesinasyntheticworld.”Availableathttp://ssrn.com/abstract=415043.(2003)________.“OntheResearchValueofLargeGames:NaturalExperimentsinNorrathand

Camelot.”Availableathttp://ssrn.com/abstract=875571(2005)________.“ACost‐BenefitAnalysisofReal‐MoneyTradeintheProductsofSynthetic

Economies.”Info,Vol.8no.6(2006).Deaton,Angus.UnderstandingConsumption.Oxford:OxfordUniversityPress,1992.EmergingTechnologyConference.QuotationsfromMarch6‐9,2006conference.Retrieved

November,2006fromhttp://conferences.oreillynet.com/etech/Fehr,ErnstandJ.List.“TheHiddenCostsandReturnsofIncentives–Trustand

TrustworthinessamongCEOs.”JournaloftheEuropeanEconomicAssociation.Vol.2(5),pp.743‐771(2004).

Gneezy,UriandJ.List.“PuttingBehavioralEconomicstoWork:TestingforGiftExchangeinLaborMarketsUsingFieldExperiments.”Econometrica,Vol.74(5),pp.1365‐1384(2006).

________,M.Niederle,andA.Rustichini.“PerformanceinCompetitiveEnvironments:GenderDifferences.”TheQuarterlyJournalofEconomics.Vol.118,pp.1049‐1074(2003).

Grimmelmann,James.“VirtualWorldsasComparativeLaw.”Vol.49NewYorkLawSchool

LawReview,pp.147‐184(2004).Guillen,PabloandR.Veszteg.“SubjectPoolBiasinEconomicExperiments.”Availableat

http://econpapers.repec.org/paper/grawpaper/06_2F03.htm(2006).

17

Haigh,MichaelandJ.List.“DoProfessionalTradersExhibitMyopicLossAversion?AnExperimentalAnalysis.”JournalofFinance,Vol.60(1),pp.523‐534(2005).

Hof,Rob.“MyVirtualLife.”BusinessWeek,May1,2006.Krotoski,Aleks.“ChicksandJoysticks:AnExplorationofWomenandGaming.”Whitepaper

forTheEntertainment&LeisureSoftwarePublishersAssociation(2004).Noveck,Beth.“InstituteforInformationLawandPolicySymposium,StateofPlay.

Introduction:TheStateofPlay.”NewYorkLawSchoolLawReview,Vol49,Number1(2004).

Gneezy,Uri,M.Niederle,andA.Rustichini.“PerformanceinCompetitiveEnvironments:

GenderDifferences.”TheQuarterlyJournalofEconomics,Vol.3,pp.1049‐1074,2003.Rosedale,Philip.TalkatGoogleLabs,MountainView,CA.March1,2006

AvailableonGoogleVideo.RetrievedNovember,2006fromhttp://video.google.com/.Roth,Alvin.,V.Prasnikar,M.Okuno‐Fujiware,andS.Zamir“BargainingandMarket

BehaviorinJerusalem,Ljubljana,PittsburghandTokyo:anExperimentalStudy”,AmericanEconomicReview,Vol.81,pp.1068‐1095,1991.

Secondlife.com.“EconomicStatistics.”RetrievedDecember,2006from

http://secondlife.com/whatis/economy_stats.php.Whitehouse.gov.“HouseholdIncome.”RetrievedNovember,2006from

http://www.whitehouse.gov/fsbr/income.html.Yee,Nick.“TheDemographics,MotivationsandDerivedExperiencesofUsersofMassively‐

MultiuserOnlineGraphicalEnvironments.”Presence,Vol.15,pp.309‐329,2006.(a)________.Availablefromhttp://www.nickyee.com/.(b)

18

AppendixA

Ultimatum Game Instructions

Note card 1: WELCOME! You have been asked to participate in an economics experiment. You will be paid 500 Linden Dollars for participating and you may earn additional money in the experiment. You will be paid at the end of the experiment. This experiment is part of university research to help understand how people make decisions. Do not use the chat bar or instant messenger (IM) during the experiment, except when you are asked to do so. Please click ‘next’ when you are finished reading a card. Note card 2: THE GAME You will be paired with another person who is in another room. You and your partner will remain anonymous. You will be assigned to be either Player A or Player B. Player A will be given 1500 real Linden Dollars at the beginning of the game. Player A may choose to send some, all or none of this money to Player B by typing the amount into the chat bar when prompted to do so. Player B will be told how much money Player A sent and will decide whether to accept or reject the offer. If Player B rejects the offer, both Player A and Player B receive nothing beyond the participation fee. If Player B accepts Player A's offer, then, in addition to the participation fee, Player B receives whatever Player A offered him. Player A receives 1500 Linden dollars minus the amount sent to Player B. Note card 3: EXAMPLES Here is an example: Player A starts with 100 Linden Dollars and decides to send 5 to Player B. Player B rejects the offer of 5 Linden Dollars. In addition to the participation fee, Player A is paid 0 Linden Dollars and Player B is paid 0 Linden Dollars. Here is another: Player A receives 200 Linden Dollars and decides to send 150 to Player B. Player B accepts the offer of 150 Linden Dollars. In addition to the participation fee, Player A is paid 50 Linden Dollars and Player B is paid 150 Linden Dollars.

19

Note card 4: TEST In order to make sure you understand, please work out this example. You cannot play the game if you do not answer correctly. Player A receives 500 Linden Dollars and decides to send 75 to Player B. Player B accepts the offer. In addition to the participation fee, how many Linden Dollars is Player A paid? _____ Please type the answer into the chat bar. You have 3 chances to answer correctly. Note card 5: Your decisions in this game are private and we ask that you do not tell anyone your decision either during, or after, the experiment. Your participation is voluntary and you may leave at any time. Once you have read and understood the instructions please type "Ready" in the chat box. The game will begin as soon as both players have completed the instructions. Note card 6: SURVEY Thanks for participating! The game is now ended and you will be paid immediately after completing a short survey. There are seven questions about your background in real life which will help in the understanding of the data. All responses will be kept confidential, and your avatar name will not be recorded. Click ‘next’ to start the survey. Note card 7: THANKS! Thank you for your responses. You will now receive your payment for participating. You may only participate in this experiment one time, but look on the employment message board for future experiments. Thank you again for participating! If you have any further questions, please email David Abrams: [email protected] If you have any questions about your rights as a participant in this research, you may contact the Social and Behavioral Science Institutional Review Board at the University of Chicago: [email protected] Please teleport to another location.

20

Trust Game Instructions Note card 1: WELCOME! You have been asked to participate in an economics experiment. You will be paid 500 Linden Dollars for participating and you may earn additional money in the experiment. You will be paid at the end of the experiment. This experiment is part of university research to help understand how people make decisions. Do not use the chat bar or instant messenger (IM) during the experiment, except when you are asked to do so. Please click ‘next’ when you are finished reading a card. Note card 2: THE GAME You will be paired with another person who is in another room. You and your partner will remain anonymous. You will be assigned to be either Player A or Player B. Player A is given 1500 Linden Dollars at the beginning of the game. Player A may choose to send some, all or none of this money to Player B by typing the amount into the chat bar when prompted to do so. Whatever amount Player A chooses to send to Player B is tripled. Player B will be told the tripled amount and then may send back some, all, or none of the money to Player A. The game then ends. In addition to the participation fee, Player A receives 1500 Linden dollars minus the amount sent to Player B plus the amount sent from Player B to Player A. Player B receives the participation fee plus three times the amount sent by Player A minus the amount sent from Player B to Player A. Note card 3: EXAMPLE Here is an example of the experiment, where Player A is initially given 100 Linden Dollars: Player A is asked “How much would you like to send to Player B?” He responds “15”. Player B is told “You have been sent 45 Linden Dollars. How much would you like to send to Player A?” Player B types “0”. In addition to the participation fee, Player A is then paid 100 – 15 + 0 = 85 Linden Dollars and Player B is paid 45 – 0 = 45 Linden Dollars. Note card 4: TEST

21

In order to make sure you understand, please work out this example. You cannot play the game if you do not answer correctly. Player A is given 500 Linden Dollars and decides to send 100 to Player B. Player B receives 300 Linden Dollars and decides to send back 50. In addition to the participation fee, how many Linden Dollars is Player B paid? ____ Please type the answer into the chat bar. You have 3 chances to answer correctly. Note card 5: Your decisions in this game are private and we ask that you do not tell anyone your decision either during, or after, the experiment. Your participation is voluntary and you may leave at any time. Once you have read and understood the instructions please type "Ready" in the chat box. The game will begin as soon as both players have completed the instructions. Note card 6: SURVEY Thanks for participating! The game is now ended and you will be paid immediately after completing a short survey. There are seven questions about your background in real life which will help in the understanding of the data. All responses will be kept confidential, and your avatar name will not be recorded. Click ‘next’ to start the survey. Note card 7: THANKS! Thank you for your responses. You will now receive your payment for participating. You may only participate in this experiment one time, but look on the employment message board for future experiments. Thank you again for participating! If you have any further questions, please email David Abrams: [email protected] If you have any questions about your rights as a participant in this research, you may contact the Social and Behavioral Science Institutional Review Board at the University of Chicago: [email protected] Please teleport to another location.

22

Monty Hall Game Instructions Note card 1: WELCOME!

You have been asked to participate in an economics experiment. You will be paid 500 Linden Dollars for participating and you may earn additional money in the experiment. You will be paid at the end of the experiment. This experiment is part of university research to help understand how people make decisions. Please do not use the chat bar or instant messenger (IM) during the experiment. Please click “next” when you are finished reading a card. Note card 2: THE GAME A prize is hidden randomly behind one of the three doors before you. You must guess which door you think holds the prize. After choosing a door, one of the two remaining doors which does not hold the prize is opened. You may then change your choice of door to the other remaining closed door or keep your original choice. The prize is then revealed. If you chose the right door, you win L$ 250. If not, you win nothing. You will play ten times, with the prize hidden randomly each time. Note card 3: PRACTICE Let’s try one game now just for practice. Note card 4: After the experiment is over, you will be asked to fill out a short survey, and then you will be paid. You will receive 500 Linden Dollars for participating, plus 250 Linden Dollars for each round you chose the correct door. You will then be asked to leave the experimental lab. You will not be able to return to the lab after the experiment is over. Your participation is voluntary and you may leave at any time. Once you have read and understood the instructions please click "Ready". Note card 5: SURVEY Thanks for participating! The game is now ended and you will be paid immediately after completing a short survey.

23

There are eight questions about your background in real life which will help us understand the data. All responses will be kept confidential, and your avatar name will not be recorded. Click “next” to start the survey. Note card 6: THANKS! Thank you! You will now receive your payment. You may only participate in this experiment once, but look on the employment message board for future experiments. If you have any questions, please email David Abrams: [email protected] If you have any questions about your rights as a participant in this research, you may contact the Social and Behavioral Science Institutional Review Board at the University of Chicago: [email protected] Please teleport to another location. Dialog: Please touch the door you think holds the prize. <repeat every 10 seconds until click. Timeout at 5 minutes> I will now open one of the doors you did not choose and show you that it does not hold the prize. <Open one of two non-clicked doors that doesn’t contain gold> Now, with the information you have, touch the door you think holds the gold. <display win/loss message>

24

Figure1A:PaidUserGrowthinVirtualWorlds–Largest

0

500,000

1,000,000

1,500,000

2,000,000

2,500,000

3,000,000

3,500,000

4,000,000

4,500,000

5,000,000

5,500,000

6,000,000

6,500,000

7,000,000

Jan-97 Jul-97 Jan-98 Jul-98 Jan-99 Jul-99 Jan-00 Jul-00 Jan-01 Jul-01 Jan-02 Jul-02 Jan-03 Jul-03 Jan-04 Jul-04 Jan-05 Jul-05 Jan-06 Jul-06 Jan-07 Jul-07

Paid

Use

rs

Lineage

RuneScape

Star WarsGalaxies

World of Warcraft

25

Figure1B:PaidUserGrowthinVirtualWorlds–Medium

0

50,000

100,000

150,000

200,000

250,000

300,000

350,000

400,000

450,000

500,000

550,000

600,000

650,000

700,000

Jan-97 Jul-97 Jan-98 Jul-98 Jan-99 Jul-99 Jan-00 Jul-00 Jan-01 Jul-01 Jan-02 Jul-02 Jan-03 Jul-03 Jan-04 Jul-04 Jan-05 Jul-05 Jan-06 Jul-06 Jan-07 Jul-07

Paid

Use

rs

Ultima Online

Dark Age of Camelot

EverQuest

Final Fantasy XI

Asheron's Call 2

Mankind

Toontown Online

Second Life

Dofus

Fi

26

igure2A

Fi

Fi

27

igure2B

igure2C

28

Figure3

Figure4

05

1015

2025

Fre

quen

cy

0 500 1000 1500Linden Dollars

Ultimatum Game Offers (out of 1500)

010

0020

0030

0040

0050

00P

laye

r 2

Ret

urn

0 500 1000 1500Player 1 offer

Trust Game Offers and Returns

F

F

29

Figure5

Figure6

30

Figure7

.2.3

.4.5

Sw

itch

rate

0 2 4 6 8 10Round

Switch rate vs Round

31

Table1

Game Date Age Married Children Student American

Second Life March, 2006 0.57 32 0.75World of Warcraft June, 2005 0.84 28.3 22.7

(8.4) (14.1)obs. 1019 1019 1019

The Sims Online 2004 0.4Popular MMOGs* 2000-2003 0.854 26.57 0.363 0.221 0.500 0.222 22.7

(9.19) (15.0)obs. 5547 5509 2846 2846 2846 2846 5471

Everquest 2000-2001 0.84 25.6 0.68 0.19 0.32 ~$50,000 22.4obs. 1240 1240 2473 2475 1099 2525 1216

Everquest 2001 0.922 24.3 0.228 0.15 0.534 0.350 0.813obs. 3619 3619 3619 3619 3619 3619 3619

Median Household

Income

Hours played per

week

Table 1: Virtual World User Demographics

MaleIn a

relationshipFull-time

job

*Ultima Online, EverQuest, Dark Age of Camelot, and Star Wars Galaxies

Sources: Survey data reported in Yee (2006), http://www.nickyee.comQuotations from talks at Emerging Technology Conference, March 6-9, 2006 found on http://conferences.oreillynet.com/etech/Speech by Philip Rosedale, CEO of Linden Labs at Google, March 1, 2006 (available on Google Video).Krotoski (2004); Castronova(2001)

32

Table2

Table3

Title # UsersYear of

PublicationPurchase

Price

Monthly Subscription

Fee Classification

Market Share by Revenue*

Monthly Subscription

RevenueWorld of Warcraft 11,500,000 2009 $59.98** $14.99 Fantasy 62.4% $172,385,000RuneScape 10,000,000 2002 Free $5.00 Fantasy MMORPG 7.4% $50,000,000Second Life 1,761,927 2009 Free $9.95 Social MMOG <1.0% $17,531,174Final Fantasy XI 1,500,000 2003 $19.99 $12.95 Fantasy MMORPG 3.1% $19,425,000Lineage: The Blood Pledge 1,399,909 1998 Free $15.00 Fantasy MMORPG 6.5% $20,998,635Lineage II: The Chaotic Chronicle 1,300,000 2004 $29.99 $14.99 Fantasy MMORPG 6.2% $19,487,000Eve Online 300,000 2003 Free $14.95 Science Fiction MMORPG 1.5% $4,485,000EverQuest 200,000 1999 $19.99 $14.99 Fantasy MMORPG 1.1% $2,998,000City of Heroes/Villains 200,000 2004 $19.99 $14.99 Comic Book Fantasy 0.8% $2,998,000EverQuest II 185,000 2004 $29.99 $14.99 Fantasy 1.2% $2,773,150Star Wars Galaxies 170,000 2003 $29.99 $14.99 Science Fiction MMORPG 1.4% $2,548,300Ultima Online 135,000 1997 $29.95 $12.99 Fantasy MMORPG 1.1% $1,753,650Dark Age of Camelot 125,000 2001 $19.99 $14.95 Fantasy MMORPG ≈1% $1,868,750Toontown Online 110,000 2003 Free $9.99 Children's MMORPG 0.9% $1,098,900Dungeons & Dragons Online: Stormre 90,000 2006 $49.99 $14.99 Fantasy 0.7% $1,349,100PlanetSide 65,000 2003 Free $12.99 Shooter MMOG <1.0% $844,350The Sims Online 35,500 2002 Free $9.99 Social MMOG <1.0% $354,645Yohoho! Puzzle Pirates 34,000 2003 $19.99 $9.99 Puzzle MMOG <1.0% $339,660The Matrix Online 30,000 2005 $29.99 $14.99 Science Fiction <1.0% $449,700Asheron's Call 30,000 1999 $19.95 $12.95 Fantasy MMORPG <1.0% $388,500There 17,000 2003 Free $9.95 Social MMOG <1.0% $169,150WWII Online 12,000 2001 Free $14.99 Shooter MMOG <1.0% $179,880Anarchy Online 12,000 2001 Free $14.95 Science Fiction MMORPG <1.0% $179,400Auto Assault 11,000 2006 $49.99 $14.99 Action <1.0% $164,890Horizons: Empire of Istaria 10,000 2003 Free $12.95 Fantasy MMORPG <1.0% $129,500

Total 29,233,336 $324,899,334

Table 2: Virtual World Descriptive Statistics

*Market share is calculated from paying users, and therefore may not match aggregate user numbers**$19.99 + $39.99 (expansion pack)Revenue figures reflect only monthly subscription revenues and therefore understate the games' actual revenues. Source: MMOGChart.com, mmogdata.voig.com, individual game web pages, sources cited in

Variable Mean Median Mode Min Max St. Dev ObsOffer 602 700 750 (n=20) 5 1500 288 53

Offer (percent of maximum)

40% 47% 50% (n=20) 0% 100% 19% 53

Accepted 0.94 1 1 (n=50) 0 1 0.23 53

Offer (conditional on rejected)

392 500 500 75 600 279 3

26% 33% 33% 5% 40% 19% 3Offer (accepted) 615 700 700 5 1500 286 50

41% 47% 47% 0% 100% 19% 50

Total pie is $L 1500 = $6

Virtual Ultimatum Game Results

33

Table4

Table5

Variable Mean Median Min Max St. Dev ObsAge 32 30 17 55 11.3 106Male 0.55 1 0 1 0.50 106

European 0.32 0 0 1 0.47 106American 0.58 0 0 1 0.49 106

Other Country 0.09 0 0 1 0.29 106English Fluency 0.94 1 0 1 0.23 106

Weekly Hours in SL 17.0 15 0 80 13.9 103Experience with SL (months) 5.57 2 0.03 48 8.23 106

SL Land Owner? 0.20 0 1 1 0.40 106

Ultimatum Game Demographics

Country Frequency Percentaustralia 1 0.9brazil 1 0.9canada 5 4.7denmark 1 0.9finland 1 0.9germany 4 3.8greece 1 0.9israel 1 0.9italy 4 3.8mexico 1 0.9netherlands 4 3.8portugal 1 0.9romania 1 0.9russia 1 0.9scotland 1 0.9spain 1 0.9trinidad and tobago 1 0.9uk 14 13.2usa 62 58.5

total 106 100

Ultimatum Game Country of Residence

34

Table6

Status Mean Median Min Max ObsAmerican 601 700 75 1500 32European 600 600 5 1500 17

Other 625 625 500 750 4

Male 634 600 200 1500 25Female 574 725 5 900 28

32 or under 528 500 5 900 31Over 32 years old 707 750 150 1500 22

No Land 576 600 5 1500 43Land Owner 715 750 150 1500 10

Less than 1 month 467 500 5 900 201 to 6 months 690 750 92 1500 16

More than 6 months 679 750 200 1500 17

Under 1 hour/day 493 500 5 750 131-3 hours/day 636 725 75 1500 24

Over 3 hours/day 682 750 92 1500 14Offers are out of $L1500

Ultimatum Game Offers

35

Table7A

Country N Mean offer Mean rejectPeru 1 26.00 4.80Spain 1 26.66 29.17Chile 1 34.00 6.70UK 2 34.33 23.38

Ecuador 2 34.50 7.50Sweden 1 35.23 18.18

Mongolia 2 35.50 5.00Germany 1 36.70 9.52Romania 2 36.95 23.50Bolivia 1 37.00 0.00

Tanzania 4 37.50 19.25Austria 1 39.21 16.10

Second Life 1 40.15 5.66France 3 40.24 30.78

Papua New-Guinea 2 40.50 33.50US East 22 40.54 17.15

Israel 5 41.73 17.73Netherlands 2 42.25 9.24

US West 6 42.64 9.41Zimbabwe 2 43.00 8.50Slovakia 3 43.17 12.67Kenya 1 44.00 4.00

Yugoslavia 1 44.33 26.67Japan 3 44.73 19.27

Honduras 1 45.70 23.05Indonesia 4 46.63 14.63Paraguay 1 51.00 0.00

Source: Oosterbeek, et al (2004)

Ultimatum Game Offer and Rejection Rates

36

Table7B

Country N Mean offer Mean rejectBolivia 1 37.00 0.00

Paraguay 1 51.00 0.00Kenya 1 44.00 4.00Peru 1 26.00 4.80

Mongolia 2 35.50 5.00Second Life 1 40.15 5.66

Chile 1 34.00 6.70Ecuador 2 34.50 7.50

Zimbabwe 2 43.00 8.50Netherlands 2 42.25 9.24

US West 6 42.64 9.41Germany 1 36.70 9.52Slovakia 3 43.17 12.67Indonesia 4 46.63 14.63

Austria 1 39.21 16.10US East 22 40.54 17.15

Israel 5 41.73 17.73Sweden 1 35.23 18.18Tanzania 4 37.50 19.25

Japan 3 44.73 19.27Honduras 1 45.70 23.05

UK 2 34.33 23.38Romania 2 36.95 23.50

Yugoslavia 1 44.33 26.67Spain 1 26.66 29.17

France 3 40.24 30.78Papua New-Guinea 2 40.50 33.50

Source: Oosterbeek, et al (2004)

Comparison with Literature

37

Table8

Table9

Variable Mean Median Mode Min Max St. Dev ObsOffer 584 500 500 (n=16) 0 1500 430 56Offer

(% of max)39% 33% 33% (n=16) 0% 100% 29% 56

Return 615 475 0 (n=8) 0 4500 801 56Return (% of initial stakes) 41% 32% 0% 0% 300% 53% 56

Virtual Trust Game Results

Variable Mean Median Min Max St. Dev ObsAge 32 29 18 60 11 112Male 0.47 0 0 1 0.5 112

European 0.25 0 0 1 0.43 112American 0.60 1 0 1 0.49 112

Other Country 0.15 0 0 1 0.36 112English Fluency 0.95 1 0 1 0.23 112

Weekly Hours in SL 21.9 14 0 100 20.8 107Experience with SL (months) 5.00 2.5 0.03 36 18.75 110

SL Land Owner? 0.15 0 1 1 0.36 112

Trust Game Summary Statistics

38

Table10

Country Frequency Percentaustralia 3 2.7belgium 1 0.9canada 5 4.5colombia 1 0.9france 1 0.9germany 5 4.5india 1 0.9ireland 1 0.9israel 1 0.9italy 4 3.6jamaica 1 0.9mexico 2 1.8netherlands 2 1.8philippines 2 1.8portugal 4 3.6singapore 1 0.9slovenia 1 0.9uk 9 8.0usa 67 59.8total 112 100

Trust Game Country of Residence

39

Table11


Other 358 350 0 750 6

Male 639 500 0 1500 27Female 534 500 0 1500 29



Less than 1 month 556 500 0 1500 171 month to 6 months 584 500 0 1500 19More than 6 months 616 500 0 1500 19


Over 3 hours/day 542 500 100 1500 19Offers are out of $L1500

Trust Game Offers

40

Table12

Table13


Other 833 500 0 3000 11

Male 823 600 0 4500 26Female 434 250 0 3000 30



Less than 1 month 657 475 0 4500 261 month to 6 months 591 500 0 3000 19More than 6 months 535 250 0 2000 10


Over 3 hours/day 662 400 0 3000 20Maximum return is 3x offer ($L4500 absolute maximum)

Trust Game Returns

Authors (year) N Rounds Switch rate (percent) Stakes per roundMueser and Granberg (1999) 54 1 19.00 0Krauss and Wang (2003) 67 1 21.00 0Second Life 51 10 33.72 $L 500Friedman (1998) 104 7 39.80 $0.30Palacios-Huerta (2002) 217 10 35.10 $0.40Morone and Fiore (2006) 20 10 41.50 €0.50Kluger and Wyatt (2004) 72 12 53.00 $1.00

Monty Hall Comparison with Literature

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