Social-Status Ranking: A Hidden Channel to Gender Inequality under Competition Arthur Schram, Jordi Brandts, Klarita Gërxhani January 14, 2018 Abstract Competition involves two main dimensions, a rivalry for resources and the ranking of relative performance. If socially recognized, the latter yields a ranking in terms of social status. The rivalry for resources resulting from competitive incentives has been found to negatively affect women’s performance relative to that of men. However, little is known about gender differences in the performance consequences of social-status ranking. In our experiments we introduce a novel design that allows us to isolate the effects of status ranking from those caused by a rivalry for resources. Subjects do a time-limited task where they need to search for numbers and add them up. Performance is straightforwardly measured by the number of correct summations. When there is no status ranking we find no gender differences in the number of attempted summations or in performance. By contrast, when there is status ranking men significantly increase the number of attempted summations as well as the number of correct summations. Remarkably, when women are subjected to status ranking, they significantly decrease the number of attempted summations. The net result is striking. With status ranking men attempt more summations and correctly solve many more than women. These differences are markedly large and statistically highly significant. Our results suggest that increased participation in competitive environments could harm women’s labor market success along a hidden channel. Keywords: Status, competition, gender, experiments JEL codes: C91, J16 Acknowledgments Much of the work reported in this paper was done while the first and third authors were visiting the University of Pompeu Fabra and the Institut d’Anàlisi Econòmica in Barcelona. We are grateful to both institutions for their hospitality. We also thank the Research Priority Area Behavioral Economics of the University of Amsterdam, the Spanish Ministry of Economics and Competitiveness through Grant: ECO2014-59302-P and through the Severo Ochoa Program for Centers of Excellence in R&D (SEV2015-0563) and the Generalitat de Catalunya (Grant: 2014 SGR 510) for financial support, Veronica Benet-Martinez for providing us access to the laboratory of the Universitat Pompeu Fabra in Barcelona, and Pablo Lopez-Aguilar, Eva Maciocco, Elia Soler Pastor, Silvia Soriano and Imma Triano for help in organizing the experiments. We are grateful to seminar participants at University Ca’ Foscari in Venice, University of Padua, University of Amsterdam, Heidelberg University, European University Institute, and the Universidad Carlos III de Madrid, and Jos Bosch, Thomas Buser, Marii Paskov, Christina Rott, Aljaz Ule, and Matthijs van Veelen for comments at various stages of this project. Authors Arthur Schram (corresponding author) Jordi Brandts Klarita Gërxhani Robert Schumann Center for Advanced Studies, EUI, Italy and CREED, Amsterdam School of Economics University of Amsterdam, P.O. Box 15867 1001 NU Amsterdam The Netherlands Institut d’Anàlisi Econòmica (CSIC) and Barcelona GSE Campus UAB 08193 Bellaterra (Barcelona) Spain Department of Political and Social Sciences European University Institute Via dei Roccettini 9 50014 San Domenico di Fiesole (FI), Italy phone +31-20-525.4252 [email protected]phone +34-93-580.6612 [email protected]phone +39-055-468.5470 [email protected]
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Social-StatusRanking:
AHiddenChanneltoGenderInequalityunderCompetition
ArthurSchram,JordiBrandts,KlaritaGërxhani
January14,2018
AbstractCompetition involves twomaindimensions, a rivalry for resources and the ranking of relativeperformance. If socially recognized, the latter yields a ranking in terms of social status. Therivalry for resources resulting from competitive incentives has been found tonegatively affectwomen’sperformancerelativetothatofmen.However,littleisknownaboutgenderdifferencesin the performance consequences of social-status ranking. In our experimentswe introduce anoveldesignthatallowsustoisolatetheeffectsofstatusrankingfromthosecausedbyarivalryfor resources. Subjectsdoa time-limited taskwhere theyneed to search fornumbersandaddthem up. Performance is straightforwardly measured by the number of correct summations.When there is no status ranking we find no gender differences in the number of attemptedsummations or in performance. By contrast, when there is status ranking men significantlyincrease the number of attempted summations aswell as the number of correct summations.Remarkably, when women are subjected to status ranking, they significantly decrease thenumberof attempted summations.Thenet result is striking.With status rankingmenattemptmoresummationsandcorrectlysolvemanymorethanwomen.Thesedifferencesaremarkedlylarge and statistically highly significant. Our results suggest that increased participation incompetitiveenvironmentscouldharmwomen’slabormarketsuccessalongahiddenchannel. Keywords: Status, competition, gender, experiments JEL codes: C91, J16 Acknowledgments Muchoftheworkreportedinthispaperwasdonewhilethefirstandthirdauthorswerevisitingthe University of Pompeu Fabra and the Institut d’Anàlisi Econòmica in Barcelona. We aregrateful to both institutions for their hospitality. We also thank the Research Priority AreaBehavioral Economics of theUniversity ofAmsterdam, the SpanishMinistry of Economics andCompetitiveness throughGrant:ECO2014-59302-Pand through theSeveroOchoaProgram forCentersofExcellenceinR&D(SEV2015-0563)andtheGeneralitatdeCatalunya(Grant:2014SGR510)forfinancialsupport,VeronicaBenet-MartinezforprovidingusaccesstothelaboratoryoftheUniversitat Pompeu Fabra inBarcelona, andPablo Lopez-Aguilar, EvaMaciocco, Elia SolerPastor,SilviaSorianoandImmaTrianoforhelpinorganizingtheexperiments.Wearegratefultoseminar participants at University Ca’ Foscari in Venice, University of Padua, University ofAmsterdam,HeidelbergUniversity,EuropeanUniversityInstitute,andtheUniversidadCarlosIIIdeMadrid,andJosBosch,ThomasBuser,MariiPaskov,ChristinaRott,AljazUle,andMatthijsvanVeelenforcommentsatvariousstagesofthisproject. Authors Arthur Schram (corresponding author)
Jordi Brandts Klarita Gërxhani
Robert Schumann Center for Advanced Studies, EUI, Italy and CREED, Amsterdam School of Economics University of Amsterdam, P.O. Box 15867 1001 NU Amsterdam The Netherlands
Institut d’Anàlisi Econòmica (CSIC) and Barcelona GSE Campus UAB 08193 Bellaterra (Barcelona) Spain
Department of Political and Social Sciences European University Institute Via dei Roccettini 9 50014 San Domenico di Fiesole (FI), Italy
performanceisnotmadesalient(i.e.,thestatusdimensionofcompetitionisnot 2Of course, the status related to certainpositionsmightyield futuremonetarybenefits. Statusperse,however,canbean importantmotivatingfactor forperformance.Forevidencefromthefield,seeBlanes-i-Vidal&Nossol(2011)andBarankay(2012).
outbyHeffetzandFrank2008).Importantly,inbothtreatmentsallparticipants 3Part3 consists of dictator games (Hoffmanet al. 1994).Thiswasdesigned to investigate theconsequencesofhavingbeenpubliclyrankedforsubsequentbargainingenvironments.Becauseitisbeyondthescopeofthepaper,thispartisdescribedandanalyzedinappendixB.
4
who have to report to a peer are informed about this before starting on the
threats’, i.e., situations where the social self in humans is endangered. Such
threatsgiverise to large levelsof individualcortisolresponsesduetoa fearof
4 Subsequent research has shown that these performance effects depend on the task underconsideration(Güntheretal.2010,Shurchkov2012,Bohnetetal.2016).5 Various policies have been suggested to address the gender gap in entry into competition.Theseincludequota(BalafoutasandSutter2012,Niederleetal.2013),theprovisionoffeedbackon relative performance (Wozniak et al. 2014), reduced time pressure (Shurchkov 2012),participation in teams (Dargnies 2012), advice (Brandts et al. 2015), and ‘evaluation nudges’(Bohnetetal.2016).Alloftheseaddresstheeffectsobservedwhenthereisrivalryforresources.
rates and received private ranking information on their pay and productivity.
Using a quasi-experimental research design they find that providing this
information leads to a large increase in workers’ productivity. In contrast,
6Inongoingresearch,twooftheauthorscollaboratewithCarstendeDreutolookmorespecifi-callyatwhethervariation inperformancecanbeexplainedbyphysiologicalreactionstostatusranking.Inalaboratoryenvironmentsimilartotheoneusedhere,implementedattheUniversityof Amsterdam, saliva samples were collected to enable a study of hormonal reactions. SeeAppendixCformoreinformation.
7TheexperimentalsoftwarewasdevelopedinDelphiattheCenterforResearchinExperimentalEconomics and political Decision making (CREED) by CREED programmer Jos Theelen. It isavailableuponrequest.
two-digit numbers. Thesematrices appear at the lower half of their computer
monitor(Figure1).
Figure1:ScreenshotPart1
Notes. The instructions inform participants that the numbers in the cells were ‘randomlygenerated’(cf.SM).Drawingfromauniformdistributionwouldhaveledtoahighprobabilityofveryhighsums.Toavoidthis,foreachcell,wefirstdrewarandomnumberbetween40and99,sayX.Then,wedrewa randomnumber (uniformly)between10andX.This gives a far lowerprobabilityofhighnumbers(thechanceofanumberbeing75ormoreisapproximately0.06).
8 Alternatively, we could have used the summation task applied in Niederle and Vesterlund(2007).Shurchkov(2012, fn21),however, reportsevidenceofastereotype threat in this task,wherewomenfeelapriorithatmenhaveanadvantage.Toavoidthis,wedecidedtouseataskthatoneofushassuccessfullyappliedbefore(WeberandSchram2016).InthispreviousstudytherewasnoevidenceofgenderdifferencesandourdataforB-playersconfirmthis.Thisiswhywebelieve there tobenostereotype threat for the taskweused.Thisbelief findssupport inarecentapplicationofthesametaskinanexperimentweraninBologna.There,wealsoelicitedbeliefsaboutmaleandfemaleperformanceinthistaskbylettingsubjectsguesswhethermenorwomenhadthehighermeanscore(witha fiveeuroprize foracorrectguess).Thisshowednoevidence of expected performance differences; out of 30 participants, 17 (13) thoughtwomen(men)wouldscorebetter.9Thisemphasiswasmadetostresstheimportanceofstatusrankingbasedontheperformancein the particular task we used. After an analysis of results obtained in early sessions, somecolleaguessuggestedthat the fact thatA-playersbutnotB-playersweregiventhis informationmightcauseastereotypethreatthataffectsgenderdifferencesobservedamongstA-players.Forthisreason,inlatersessionstheB-playerswerealsoprimedwiththistextinthesamewayastheA-players.Theydidnotparticipateinpart2(hence,didnotreporttotheirpeers).Weobservednogendereffectsfortheseparticipants(moredetailsareavailableuponrequest).Weconcludethattheemphasisdoesnotinitselfinducestereotypethreat.Thisalsosuggeststhatinretrospectitwasunnecessarytoprovidethisinformationaltogether.
10 We believe the term ‘conformity’ to be adequate to capture the idea that people may beinfluencedbyothers’opinionsindependentlyfromanystatusconcerns.
11
Figure2:ExperimentalDesign
Notes.A-andB-playersindividuallydothesummationtask.ThenA-playersreportprivatelytoC-player(s)(indicatedbyarrows).PanelAshowstheStatusRanking(SR)treatmentwhereeachA-player individually goes to the (same) C-player and reports his or her own score and rankamongst A-players. Panel B shows the Conformity (CF) treatment where each A-playerindividuallygoestohisorher‘own’C-playerandreportsthescore.
task.We introduced this tomake the reporting of their result to a peermore
prominent.
11WedonotinformC-playersaboutthetaskinordertoavoidthemformingopinionsaboutwhatisa‘good’score.SuchopinionscouldgenerateafeelingofrankingevenintheCFtreatments,inthesenseofaperformancelevelabove/belowacertainlevelbeingjudgedasgood/bad.12 Social rankingmight conceivably also occur via the experimenters. The sessionswere orga-nized in away, however, thatmade it obvious to the participants that no experimenter couldobservetheirrank.Moreinformationisavailableuponrequest.13 As suggested by an anonymous reviewer, the face-to-face encounter between the twoparticipantsmightcreatearivalry forresources in theSR treatment ifA-playersbelieve thatahighrankinthetaskmightaftertheexperimentbringthemfavorsbytheC-player.Thoughwedonot believe that thiswould cause the large treatment effects thatwe report below,we cannotexcludethispossibility.
comparesattempsandperformanceacrossgender for these two treatments. It
showsthattheorderingbetweenmenandwomenonbothmeasuresisreversed 14See,forexample,Moir(1998).Wepreferthepermutationt-testoverthemorecommonMann-Whitneytestbecausethelattertestsfordifferencesindistributionsoftwoindependentsamples.Wearemorepreciselyinterestedindifferencesinthemeansofthedistributions.Nevertheless,the results presented here are robust to using Mann Whitney or t-tests instead of thepermutationt-test.
Notes. Bars show number of attempts at calculating summations (left) andperformance (number of correct summations, right), separately for women andmen.CF-NR:Conformitytreatmentwithoutknowingownrank;CF-PR:Conformitytreatmentwithknowingownrank.Errorbarsshow95%confidenceintervals.
Notes.Barsshowthenumberofattemptsatcalculatingsummations(leftpanel)andperformance(number of correct summations, right panel), separately for women andmen. CF: Conformity(CF-NRandCF-PRpooled);SR:StatusRanking.Errorbarsshow95%confidenceintervals.
The most remarkable result is observed for the treatment where A-players
report to a C-player and know that this peer will be able to compare their
16 In the follow-up experiments in Amsterdam (see fn. 6), the patterns observed here wereconfirmed(cf.AppendixC).17AsimilarlackofsignificanteffectsisobservedwhenconsideringtheCFtreatmentsseparately(inCF-NR:p=0.731,p=0.428,N=62,respectively;inCF-PR:p=0.163,p=0.854,N=62).18 Similarly, there areno significant effectswhen considering theCF treatments separately (inCF-NR:p=0.163,p=0.370,N=28,respectively;inCF-PR:p=0.875,p=0.411,N=28).
17
for correct, p = 0.221, N = 26). For men, the numbers of attempts and
that they would reinforce each other in creating more advantageous
environmentsformenthanforwomen.
19
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Table A1 shows that the fractions of participants with a major in economics andbusinessaresimilaracrosstypes.Wedistinguishbetweenthesemajorsbecausethesearethefieldsinwhichstudentsaremostlikelytohaveexperiencedtaskssimilartothesummation task. The differences are statistically insignificant (Fisher’s exact test,p=0.11). The average age is also statistically indistinguishable across types (Kruskal-Wallis,p=0.44).The distribution of women is similar across A-types. The differences are statisticallyinsignificant (Fisher’s exact test, p=0.86). Women seem somewhat over-representedamongst B-types however. Across all four categories, the differences are marginallysignificant(Fisher’sexacttest,p=0.07).Notethatthisdoesnotcauseproblemsforouranalyses,becausetheyalleithercomparegenderswithintypesorcomparetypeswithingender.
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B.ExperiencedStatusRankingandBargaining
Themaintextfocusesontheeffectsofananticipatedstatusranking.Here,wediscusstheeffectsofexperiencedstatusranking.Theliteratureonsucheffectsisscarce.MostinfluentialineconomicshasbeentheworkbyBallandEckel(1996,1998)andBalletal(2001).Intheirexperiments,highstatusisinducedtosomeparticipantsbycallingthemforward and awarding themwith a gold star. In subsequent interactions, high-statusparticipantsobtainalargershareoftheresourcesthanlow-statusparticipants.Thisisobservedbothintheultimatumgame(BallandEckel1996,1998)andinmarkets(Balletal.2001).Theinterpretationgiveninthesepapersisthatahighsocialstatuscreatesafeelingof‘entitlement’toresources,evenifthestatusisunrelatedtothetaskinwhichthe resources are generated (Ball et al. 2001). These studies do not address possiblegenderdifferencesinthiseffect.DesignInpart3ofourexperiment,eachA-playerispairedwithaB-playerandeachB-playerispairedwithadifferentA-player.This is illustrated inFigureB.1.Thispairing schemeaims at avoiding direct-reciprocity influences on participants’ behavior. Each partici-pant plays two dictator games, once as a dictator, once as a recipient. The dictatordivides€10betweenherselfandtherecipientwithwhichsheispaired.Forexample,A2divides€10betweenherselfandB2andB6divides€10betweenherselfandA1.Afteralldecisionshavebeenmade,arandomdrawdetermineswhetherdictatordecisionsbytheA-playersortheB-playersarepaidout.
ResultsWe first investigate whether our data replicate Ball et al. (1996, 1998, 2001)’s‘entitlement’ results. In our experiment bargaining is represented in its most simpleform: the dictator game. The Ball et al. entitlement results predict that having beenrankedhighly in thesummationtaskwillmakeoneoffer lessasadictator.Wewouldthen expect lower offers by the top-ranked participants of type A-SR than for top-ranked typesBorA-CF.This isbecause the former typeknows that they scoredwellwhen being socially ranked and the latter types scored well but were not sociallyranked(infact,typesA-CF-NRandtypesBdidnotevenknowtheirranks).Onaverage,theamountofferedbythesetop-rankedtypesis3.00,3.33and1.88fortypeB,typeA-CF and type A-SR, respectively. As predicted, we find that those who were socially
A1 A2 A3 A4 A5 A6
B1 B2 B3 B4 B5 B6
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rankedofferedleastinthesubsequentbargaining.iThepairwisedifferencesindictatorgiving between the socially ranked (and top-3) dictators and each of the other twocategoriesismarginallystatisticallysignificant(PtT,p=0.065,N=55whencomparingtypeA-SRtotypeB;p=0.095,N=34whencomparingtypeA-SRtotypeA-CF).ThisisinlinewiththeentitlementresultsbyBalletal.(1996,1998,2001).FigureB.2showsperplayertypetheaverageamount(outof€10)givenbymenand
Notes.Barsindicatetheamountineurosgivenbythedictatortotherecipient(s)hewaspairedto.Rank1,2,3(4,5,6)indicatesthattheparticipantwasamongstthetop3(bottom3)inowngroup in terms of performance. Recall that only type A-SR and type A-CF-PR players knewtheir rank. The numbers of observations are larger than or equal to eight in all categories,exceptmen in typeA-SRwithrank4-6(N=5)andwomenintypeA-SRwithrank1-3(N=3).Tieswere treatedas follows. InCFandSR theparticipant that reached the (tied)numberofcorrect solutions firstwas rankedabove theother. For typeB, all those tiedweregiven thesamerank.Errorbarsshow95%confidenceintervals.
At first sight, the largest differences between men and women are observed forparticipantswhohadbeensubjectedtosocialranking(notethatthenumbersofhighlyrankedwomenandlowlyrankedmeninSRarelow,however).Irrespectiveofwhetherthey scored highly or lowly, men seem to give less than women after having beensocially ranked.We again test for genderdifferencesusingpermutation t-tests. TableB.1presentsthep-valuesthatthesetestsyield.
iKnowing (only)privately thatonehasahighrankdoesnotmakeonegive less.Thenineparticipantswithatop-3rankintypeA-CF-PRgaveonaverage4.0inthedictatorgame,whilethenineparticipantswithatop-3rankintypeA-CF-NRgave2.67.Thisdifferenceisstatisticallyinsignificant(PtT,p=0.363,N= 18). This suggests that the social aspect of ranking is important for Ball et al’s entitlement effect tooccur.NotethatthesocialaspectisakeypartofthestatusinducementprocedureinBalletal.(2001).
The results in Table B.1 show only few gender effects in dictator giving. The oneimportant exception is thatmenwho have scored badly in the summation task (i.e.,lower half in the ranking) offer significantly less than women after having beensubjectedtosocialranking.Thesizabledifferencebetweenmenandwomenobservedfortop-rankedsubjects(cf.FigureB.2)inSRisstatisticallyinsignificant,possiblyduetothe lownumberofwomen in thesample. Inshort,mentendtogive less thanwomenwhenranked,butespeciallysoafterhavingbeenpubliclyrankedlowly.
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AppendixC:RobustnessofourResultsThe numbers of observationswe use for our statistical tests are at the lower end ofwhat one typically observes in the experimental literature. In this appendix, we firstarguethattheyneverthelessallowforvalid inferencewhenusingpermutationt-tests.Then, we use additional data obtained from a related experiment to show that ourconclusionsarerobusttoenlargingthedataset.Permutationt-testsPermutation (a.k.a. randomization) tests (Fisher 1935) are based on reshufflingtreatmentlabelsinadataset.Considerthecaseofat-testfordifferencesinmeans.Theideaforreshufflingstartsfromnotingthatanobservedt-statisticmaybeseenasadrawfromall possible t-statistics. TableC.1provides an example.Assume thatweobservetheheight(incm)ofthreemenandthreewomenasdepictedinthefirstrow.Wewanttoinvestigatewhethermenaretallerthanwomen.
TableC.1:Anexampleofpermutationt-tests Men Women t-statistics p-valueObserved 176,182,190 164,168,170 3.47 0.03Shuffle2 164,182,190 176,168,170 0.91 0.41….. Shuffle20 176,168,170 176,182,190 3.47 0.03Applying a t-test to the observed heights would lead us to believe that men aresignificantlytalleratthe5%-level.Thelownumberofobservations(six)shouldmakeone doubt the normality assumption underlying this t-test, however. There are 20possibledistributionsofthesixheightsbetweenthreemenandthreewomen.Ofthese(only)theobserveddistributionand‘shuffle20’giveat-valueof3.47orhigher.Evenifheightsaredistributedrandomlybetweenmenandwomen,thereisthena10%chancethatat-testwouldconcludethatmenaretaller.Thisisanexactprobability.ThisFishertestshowsusthat–basedonthesesixobservations–wecannotconcludethatmenaretallerthanwomen.iiForoursample, thereare toomanyobservations tocheckallpossiblereshufflesof
thedata.Inthiscase,onecanrandomlydrawasetofthese(inourcasewetook5000reshuffles, or ‘permutations’) and use the distribution of the resulting t-statistics toinvestigate how likely the observed value is to occur. Because of this Monte-Carloresampling,p-values are estimatedwith amargin of error. In caseswhere the upperboundof the95%confidence interval for thep-valueexceeded thechosensizeof thetest,wethereforeincreasedthenumberofreplicationsuntilthestandarderrorofpwasbelow0.0015.Becausethistestisbasedonexactstatistics,thenumbersofobservationsneededis
muchlowerthanintraditionalparametricandnon-parametrictests.Forgivensamplesize, the testhas thehighestpower in comparison to related tests (Siegel1956,Moir1998).Moir(1998)reportsaMonte-Carlostudythatshowsveryreliableresultsforasfewaseightobservationspertreatmentcategory.Thesmallestcellcountwebaseourtestsonis16.
TheAmsterdamSessionsWeranarelatedexperimentattheCREEDlaboratoryinAmsterdaminJune,2015.Themainpurposeof this study is to investigate thephysiologicalmechanisms involved inthe effects of status ranking. For this reason, we also gathered saliva samples.Otherwise, the sessions and treatmentswere structured exactly like in theBarcelonaexperiment.Theresultsof theAmsterdamexperimentwillbepresented inaseparatestudy. We thank our co-author Carsten de Dreu for agreeing to let us report somebehavioralfindingshere.96subjectsparticipatedineightsessions(fourCF-PRandfourSR).Addingtheseto
Bothforattemptedsummationsandperformance,whenthereissocial-statusranking,thedifferencebetweenmenandwomen ishighlysignificant (PtT,p<0.01,N=58 inboth cases). The biggest difference between Figure E.1 and Figure 4 in themain textappearstobethata(smaller)genderdifferencemayalsoexistfortypesBandA-CF.Forattempts,thedifferencesobservedinFigureE.1arenotsignificant,however(PtT, p=0.25,N =119 for typeB;PtT, p = 0.66,N =60 for typeA-CF).Forperformance, thegendereffectsaremarginallysignificant(PtT, p= 0.09,N=119 for typeB;PtT, p=0.09,N=60fortypeA-CF).Whenaggregatingthedataacrossthetwolocations,oneneedstotakeintoaccount
that there were differences between the two subject pools. In particular, Dutchparticipantswereacross-the-boardbetter atdoing the summation taskand relativelymoreeconomistsparticipatedinAmsterdamthaninBarcelona.Becausesuchdifferen-cesmight interactwith gender effects,we ran linear regressionsof performance (i.e.,thenumberofcorrectsummations)onaseriesofbackgroundvariables,includinggen-der.Wedidsoseparatelyforeachtypeofplayer.TheresultsarepresentedinTableC.2.These results provide further evidence of the effects observed in the Barcelona
experiment.Aftercorrectingforbackgroundvariables,weonly findsignificantgenderdifferences when participants were subjected to social-status ranking. There are nogendereffects inperformancewhensubjectsdonotreport theirscore toanyone,norwhen they each report todifferentC-players.When there is ranking of social status,women performmuchworse thanmen. Themarginal effect is more than five fewer
14 16 18 20 22 24 26 28
CF SR
type B type A
women men
9 10 11 12 13 14 15 16 17 18
CF SR
type B type A
viii
correct summations. The results also show that Spanish participants have lowerperformancethantheDutchinallroles.
TableC.2:Performance
TypeB TypeA-CF TypeA-SRConstant 12.47*** 14.74*** 17.73***Economist 2.63*** 1.33 –2.16Barcelona –1.67*** –3.35** –3.13*Female 0.99 –0.76 –5.29**FemaleEconomist –3.00* –2.23 5.54N 102 60 40Notes. Cells report the coefficients of linear regressions of the number of correct summations on theindependentvariablesdepictedintherows.*/**/***depictsstatisticalsignificanceatthe1%/5%/10%-level.Thetotalnumberofobservationsisreducedduetomissingobservationsonbackgroundvariables.All in all, the additional data from Amsterdam provide further evidence that ourconclusionsinthemaintextcannotbeattributedtothenumbersofobservations.Reference(notincludedinthemaintext)Siegel,S.(1956).NonparametricStatisticsfortheBehavioralSciences,McGraw-Hill,Toronto.