abhijit banerjee, rema hanna, and sendhil mullainathan · 27 corruption abhijit banerjee, rema...

27

CorruptionAbhijitBanerjee,RemaHanna,andSendhilMullainathan

1.Introduction

Corruptionisrampantinmanypoorcountries.Assuch,anticorruptionpoliciescontinuetobea central component of development strategies. For example, since 1996, the World Bankalonehassupportedmorethan600anticorruptionprograms.

Unfortunately, this is one areawhere researchhas laggedpolicy.Researchon corruptionfaces twoimportantobstacles—oneempiricalandonetheoretical.Ontheempiricalside, theprimarychallengeismeasurement.Corruption,byitsverynature,isillicitandsecretive.Howdoesonestudysomethingthatisdefinedinpartbythefactthatindividualsgotogreatlengthstohideit?Howdoesonedealwiththefactthatattemptstomeasurecorruptionmaycausetheactors involvedtoeitherreducetheir illicitbehaviorsduringtheperiodsofmeasurementorfindnewways toobscure theirbehavior? Ifwecannotaccuratelymeasurecorruption,howcan we test among different theories, measure its impacts, or even produce suggestivecorrelations?

Inrecentyears,someprogresshasbeenmadetodealwiththesechallenges.Inparticular,whilethepreviousgenerationofcorruptionmeasuresweremainlybasedontheperceptionofcorruptionbyparticipants(withvariousassortedproblemsininterpretingthesemeasures),thecurrentgenerationofstudieshavefocusedoncollectingandreportingobjectiveinformation,obtainedeitherfromdirectmeasurementorfromotherinformation.

Thetheoreticalchallengecomesinpartfromtheneedtogobeyondthinkingofcorruptionasagenericformofmoralhazardinorganizationstothepointwherewecanmapdifferentmanifestations of corruption to different underlying environments. Here the word“environment” is interpreted to cover both the usual focus of the corruption literature (thenature of the monitoring and the punishments) as well as the intrinsic motivation of thebureaucrats(e.g.,howcorruptionfitsintotheirmoralcompass)—andwhatislessemphasized,thenatureof theparticulareconomicdecision that thebureaucratsareparticipating in.Thisexpansion is important for two reasons. First, from thepointofviewof empirical research,differencesinthenatureofcorruptionindifferenteconomicsettingsisanimportantsourceoftestable predictions. Second, for policy design, it is vital that we are able to think of howchanging the environment might be an effective substitute for simply adjusting the

Gibbons, R., & Roberts, J. (Eds.). (2012). The handbook of organizational economics. Retrieved from http://ebookcentral.proquest.comCreated from uchicago on 2018-11-15 12:41:15.

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punishment(whichmaynotbefeasible).An example might clarify the second point. Bandiera et al. (2009) study waste in

governmentprocurementinItaly,acountrythatisoftenratedasoneofthemostcorruptinEurope. Using detailed data, they show that different branches of government pay verydifferentpricesforthesameproduct(downtothebrandandcolor).Thesepricediscrepanciescandifferby50%ormore.Infact,theyestimatethatthegovernmentcouldsaveupto2%ofGDPifmostpurchaseofficerspaidthesamepriceasthatobtainedbythemostfrugalofficers.

Theyalsoshow,however, that thepricedifferencesareafunctionofwherethepurchaseofficers buy. They can either obtain their supplies from the market or from an approvedsupplier, Consip. Consip charges a publicly announced price, which leaves no scope forkickbacks.Goingtothemarket,incontrast,potentiallyallowsthebuyertonegotiatehisowndeal, which might include something extra for himself. If buyers go to the market to getkickbacks,wewouldexpecttheleast-corruptofficers(i.e.,thosewhowerepreviouslypayingthelowestprices)tobetheoneswhoswitchtotheConsipoptionwhenitbecomesavailable.Infact,thedatasuggesttheopposite.WhenanewitemisaddedtoConsip’slistofavailableitems, thebureaucratspaying thehighestprices turn toConsip.Moreover, thesepurchasingofficers are also the ones that were, by all accounts, the best monitored—members of thecentralizedbureaucraciesrather than themoreautonomoushospitalsanduniversities.Theseobservationssuggestadifferentnarrative.Theseofficerspaymuchhigherpricesthanothersnotonlybecauseofkickbacks.Theissueisalsooneof justifiability.Buyingfromtheofficialsupplier requires no justification—and no effort. Bandiera et al. (2009) argue that a majorsourceofthewastehereisthefearofbeingprosecutedforcorruption.Bureaucratspayhighpricestoavoidanytaintofcorruption.Noticethatunderthislogic,changingthebureaucraticrules togive thebureaucrata fixedprocurementbudgetbut fulldiscretion—so that shecaneven pocket anymoney she saves, may generate both less waste and less corruption. Shemightevenpocketmoremoney,butthatwouldbeperfectlylegal,andbeingfreetokeepthemoneymaygiveherastrongreasontoavoidwaste.

This argument does not imply that full discretion is always a good idea. Think of theallocation of hospital beds. If need is not related to ability to pay, giving a bureaucrat fulldiscretionabouthowtoallocatebedsmayleadtoalargeproportionofthemgoingtothosewhodonotreallyneedthem.Makingstringentrulesabouthowthebureaucratissupposedtoallocate thebedswillgeneratecorruption,as thegreediestbureacratswillbend therules tomake more money, but also, potentially, a better allocation, because the more honestbureaucratswilladheretotherules.

Themore general point is that corruption is the result of the task that the bureaucrat isassigned to carry out.We can usually get rid of it by setting the appropriate task (givingdiscretion),butthatisnotalwaysdesirablefromsociety’spointofview.Theoptimalresponsetothepossibilityofcorruptionmayoftenbetochangethenatureofthetask.Notethatthechangeinthetaskmaynotalwaysreducecorruption:itmightjustaddressthemisallocationordegradationofservicesthatcorruptionoftencauses(e.g.,thathospitalbedsweregoingtotherichorthatthewaitforabedwasunacceptablylong).

Starting from the premise that the corruptionwe observemay be the result of the taskassignedtothebureaucratgivesusawaytogeneratetestableimplications.Inparticular,we


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willthenbeabletomapthespecificproblemthegovernmentistryingtosolveintoavectorofoutcomes(e.g.,bribes,lines,ormisallocationofbeds).Thequestionsweseektoanswerareoftheform:Arethewaitslikelytobelongerwhenthegovernmentistryingtotargethospitalbedstotheverypoorratherthantothelesspoor?Arebribeslikelytobegreaterwhentryingtotargethospitalbedstotheverypoor?

Thisrepositioningof thecorruption literatureawayfromapurelycrime-and-punishmentapproachtowardamoretask-focusedapproachconnects itmorecloselytotheliteratureonthe internal economics of organizations that has emerged over the past two decades. Thisliteratureexplicitlyrecognizesthatmostorganizationsusebureaucraticmechanismssimilartotheonesassociatedwithgovernmentbureaucratsformanyoftheirinternaldecisions,whichcreatesscopeforcorruption(Tirole1986).However,thereismuchtobegainedfromfocusingon the specific characteristics of the kinds of settings in which governments work. Forexample,onesourceofcorruptioningovernmentisthatgovernmentsareexpectedtodelivergoodsandservicestothosewhocannotpayfortheirfullvalue.Thisissueislessimportantinfor-profitorganizations.WereturntotherelationshipbetweencorruptioningovernmentandsimilarissuesinprivatefirmsinSection3.5.

Thischapterhighlightstheprogressmadeinthecorruptionliteratureoverthepastdecadeorso,withafocusonthedoorsthisprogressopensforfutureresearch.Inthiswayitaimstobe more forward than backward looking, less of a comprehensive review of corruptionresearch andmore of a guide towhere it appears to be headed.1 It provides a theoreticalframework to illustrate the tasks approach and an overview of the tools now available forempirically analyzing corruption. It then lays out the open questions we think are bothinterestingandwithinreach.

Westartwithadiscussionofwhatwemeanby“corruption”inSection2.Thekeypointisthatcorruptioninvolvesbreakingrules,not justdoingsomethingthat isunethicaloragainstthecollectiveinterest.Thisapproachleadsusnaturallytothinkofthetaskthatthebureaucrathas been assigned (which includes the rules). This is the subject of Section 3, where wedevelop a simple theoretical framework for thinking about corruption and its manymanifestations.We then discuss strategies formeasuring corruption in Section 4. Section 5discusses a recent empirical study that provides a clear test of the model, and Section 6reviewsthegrowingliteratureonhowtocombatcorruption.Weconcludewithadiscussionofthemainareaswethinkimportantforfutureresearch(Section7).

2.DefiningCorruptionWe define corruption as the breaking of a rule by a bureaucrat (or an elected official) forprivategain.Thisdefinitionincludesthemostobvioustypeofcorruption—abureaucrattakinganovertmonetarybribetobendarule,therebyprovidingaservicetosomeonethathewasnot supposed to. However, it would also encompass more nuanced forms of bureaucraticcorruption. For example, it would include nepotism, such as if a bureaucrat provided agovernmentcontracttoafirmownedbyhernephewratherthantoafirmthatoughttowinacompetitive, open procurement process. This definition would also cover the case of abureaucratwho“stealstime”:shemay,forexample,notshowuptowork,butstillcollecther


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paycheck.2

Under this definition, the rules definewhat is corrupt. As a result, the same act can beclassifiedascorruptioninonesettingbutnotinanother.Forexample,inmanycountries(theUnitedStates,India,etc.)acitizencanobtainpassportservicesmorequicklyifhepaysafee.While this actwouldnotbe consideredcorruption in these countries, itwouldbe inothers,where no such provision in the law exists. In contrast, many important political economyissues may not necessarily be considered corruption under this definition. For example, agovernment official providing patronage to supporters may have important ethical andallocative implications, but this actwouldnot necessarily be corruption if no formal rule istechnicallybroken.3

Thedefinitionofcorruptionused in thischapter is similar to thoseusedbyothers in theliterature,butthereareimportantdistinctions.Forexample,ourdefinitionisquitesimilartothatdiscussedbySvensson (2005:20)—“themisuseofpublicoffice forprivategain”—and toShleiferandVishny(1993:599),whodefinecorruption“asthesalebygovernmentofficialsofgovernment property for personal gain.” All three definitions imply that the official gainspersonally from her particular position. Moreover, as Shleifer and Vishny (1993) definepropertyquitelooselytoincludebothphysicalassets(e.g.,land)andassetsthathaveanoptionvalue (e.g., a business license), their definition encompasses many of the same acts ofcorruption discussed in this chapter and in Svensson (2005). However, there are slightdifferences inwhat qualifies as corruption across the definitions. For example, supposeweassume that a government official has the final say over whom to allocate a governmentcontract to.Hemaychoosetosell it tohisnephew,andgaingreatpersonalhappiness fromdoing so. Thus, thismay be considered corruption under Svensson (2005) and Shleifer andVishny(1993).However,iftheofficialhasthefinalsay,andhasnotbrokenanyofficialrules,this would not be considered corruption under our definition, despite being morallyquestionable.

We have chosen to use this definition for a combination of pragmatic and conceptualreasons.Pragmatically,theemphasisonbreakingformalrules(asopposedtomoralorethicalones)sidestepstheneedtomakesubjectiveethicaljudgmentsandtherebyavoidstheneedtohaveadeeperdiscussionofculturaldifferences.4Theemphasisonallkindsofgainratherthanjust monetary sidesteps a measurement problem: bribes by their very nature are hard tomeasure,whereasrulebreakingiseasiertomeasure.Conceptually,thesedistinctionsarealsoinlinewiththeframeworkwedescribeinthenextsection.

3.AFormalFrameworkforUnderstandingCorruptionThechallengeofmodelingcorruptioncomesfromtheverydefinitionofcorruption.AsstatedinSection2,corruption iswhenthebureaucrat (orelectedofficial)breaksarule forprivategain.Thisimmediatelyraisessomequestions,becausetherulesthemselvesarechosenbythegovernment.Specifically,whyhavetheserules,whichweknowaregoingtobeviolated,beenputinplace?Whynotchangetherulessothatthereisnoincentivetoviolatethem?Thisidealeads to an ancillary question: can you change the rules costlessly and eliminate corruption


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withoutaffectinganythingelsethatyoucareabout?Tounderstandtheseissues,webeginbythinkingabouttheunderlyingtask.Ourmodelof

tasksissimple,andyetitcapturesmanyofthetasksbureaucrats(andalsothoseintheprivatesector) typicallycarryout.Wefocusonanassignmentproblem.Abureaucratmustassignalimitednumberofslots toapplicants.Theapplicantsdiffer intheirsocialvaluationofaslot,theirprivatevaluationof it, andalso theircapacity topay for it.This simple setupcapturesmanyimportantcases.Consideraprofit-maximizingfirmsellingagood.Inthiscase,theslotisthegood,andprivateandsocialvaluescoincideperfectly.Next,considerthecaseofacreditofficer assigning loans at a government bank. Here, the private ability to paymay be thelowestpreciselyamongthosewhohavethehighestsocialreturnsfromtheloan.Thispotentialfordivergencebetweenprivateandsocialreturnsisnotincidental—itmaybethereasonthegovernmentwas involved in providing the loans in the first place. However, it is also thereasonthereiscorruption.

The bureaucrat’s taskhere goes beyond just allocating the slots: shemay also face rulesabout what prices she can charge for them and whether she can engage in “testing” todetermineanagent’stype.Thegovernmentsetsboththeserulesandtheincentivesfacingthebureaucrat.

Althoughthisframeworkdoesencompassmanymodelsofbureaucraticmisbehaviorintheliterature, we make no claims of generality for it. We make a large number of modelingchoicesthatarepointedoutaswedevelopthemodel.Thesearemademostlyintheinterestsofsimplicityandclarity,butmanyofthemcanalsohavesubstantiveimplications.

3.1.Setup

We analyze the problem of a government allocating slots through a bureaucrat whoimplements the allocation process. There is a continuum of slots of size 1 that need to beallocatedtoapopulationofsizeN>1.Agents(i.e.,citizens)havedifferingprivateandsocialvaluesforslots.Specifically,therearetwotypesofagents:HandLwithmassNHandNL,such

thatNH+NL>1.ThesocialvalueofgivingaslottotypeHisHandLfortypeL.Weassume

thatH>L. Private benefits canbedifferent,with eachgroupvaluing their slots ath and l.Agents’ types are private information and unknown by either the government or thebureaucrat, though the bureaucrat has a technology for learning about type that is called“testing,”whichwedescribebelow.Agentsalsodifferintheirabilitytopayforaslot,whichwe denote by yh and yl: because of credit constraints, agents may not be able to pay full

privatevalue,soyh≤handyl≤l.Thereisagenerictestingtechnologytodetectagenttypesthatthebureaucratcanuse.If

used on someone of type L (who is trying to pass the test) for a period of time t, theprobability that he will fail the test (i.e., get an outcome F) is ϕL(t), ϕ′L(t) ≥ 0. ThecorrespondingprobabilityforatypeHwhowantstopassis0;healwayspassesifhewantsto(i.e.,getstheoutcomeS).Eithertypecanalwaysopttodeliberatelyfail.Thecostoftestingfort hours isνt for thebureaucrat.The cost of being tested for theperson for t hours isδt. A


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simpleexampleoftestingwouldbeadrivingexamtoverifythatonecandrive.Testingistheonlycostlyactiontakenbythebureaucratinourmodel.Weassumethatthe

bureaucrat does not put in any effort to give out the slots. We capture much of what isrelevantaboutbureaucratshirkingthroughthisdevice,buttherearenodoubtsomenuancesthatthemodelmisses.

3.1.1.PossibleMechanismsThebasicproblemforthebureaucratisthechoiceofamechanism.Thebureaucratannouncesadirectmechanismthatshecancommittoexante.5EachmechanismconstitutesavectorR=(txpxr,πxr),where tx is the amountof testing for eachannounced typex =H,L;πxr is theprobability that someone acquires a slot conditional on announcing type x = H, L andachieving result r = F, S; and pxr is the price this individual will pay in the corresponding

condition.Werestrictthisdiscussiontowinner-paymechanismshere(mechanismswheretheapplicantdoesnotpaywhenhedoesnotreceiveaslot).Foranalysisofthemoregeneralcasewhereanonrefundablefeeisrequiredtoenterthebidding,see,forexample,Banerjee(1997).

Because thebureaucratonlychoosesdirectmechanisms,anyR is supposed to satisfy theincentiveconstraints:

πHS(h−pHS)−δtH≥πLS(h−pLS)−δtL

and

Moreover, the clients are allowed to walk away. This is captured by the participationconstraints:

Thereisalsoatotalslotconstraint:

NHπHS+NLπLS(1−ϕL(tL))+NLπLFϕL(tL)≤1.

Finally,thereisaffordability:agentscannotpaymorethantheyhave:

pHr≤yH,r=F,PpLr≤yL,r=F,P.


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DefineRtobethesetofvaluesofRthatsatisfytheseconditions.

3.1.2.RulesThegovernmentchoosesasetofrulesforthebureaucratthattaketheform =(Tx,Pxr,Πxr),

whereTx isthesetofpermittedvaluesforamountoftesting(tx),Pxr is thesetofpermitted

prices,andΠxristhesetofpermittedvaluesfortheprobabilitythatsomeoneacquiresaslot

(πxr) forx=H,Landr=F,S.Althoughweassume that thegovernmentdoesnotobserve

everyindividual’s type,wedoallowPxrandΠxr todependon thebuyer’s type.The idea is

thatifthereisagrossmisallocationofslotsorlarge-scalebriberybyonetype,theremaybesomeway for the government to find out (the pressmight publish a story stating that thehospital beds were all being occupied by cosmetic surgery patients who are paying highprices,or thegovernmentmightsamplea fewpeoplewhoreceivedslots).However,wedonot assume that being able to observe violations ofPxr automatically implies being able to

observeviolationsofΠxr:itmaybeeasytofindoutthatsomepeoplearebeingchargedmore

thanthepermittedpriceswithout learninganythingmoregenerallyabouthowtheslotsarebeingallocated.

Weassumethat isfeasibleinthesensethatthereexistsatleastoneR=(tx,pxr,πxr)∈Rsuch that tx ∈Tx,pxr ∈Pxr, andπxr ∈ Πxr. If is not a singleton, then the bureaucrat has

discretion.Thegovernmentalso choosesp,which is theprice that thebureaucrathas topay to the

governmentforeachslothegivesout.Assumethatthisisstrictlyenforced,sothatthepriceisalwayspaid.Thisassumptioncanberelaxedeasily,buttheresultoffersnonewinsights.

In specific examples, we make specific assumptions about what the government cancontracton,whichwillgivestructureto .Forexample,iftxisnotcontractible,thentheruleswillnotaddressit—inotherwords,Txwillbe[0,∞]×[0,∞].

3.1.3.TheBureaucrat’sChoiceForeachmechanismR∈R∩ ,thebureaucrat’spayoffis

However, ifR is inR∩ c,weassumethatabureaucratpaysacost forbreaking therules,whichisγ.Hence,thebureaucrat’spayoffforanyRinR∩ cis


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Weassumethatthecostγisunknowntothegovernmentwhensettingrules,thoughitknowsthatitisdrawnfromadistributionG(γ).Acorruptiblebureaucratisoneforwhomγisfinite.6

Asaresult,wewriteR( ,γ)asthemechanismchosenbyabureaucratwithcostofcorruptionγwhentheruleis .7

3.1.4.TheGovernment’sChoiceWe assume that the bureaucrat is the agent of what we call the “government” (but whatothershavecalledthe“constitutionmaker”),aprincipalwhosepreferenceistomaximizethesocialwelfaregeneratedbytheallocationoftheslots.Thisassumptionispartlyanartifactofthewaywemodelthings.Whatiskeyisthatthebureaucrathasabosswhoseobjectivesaredifferentfromhersandwhoisinapositiontopunishher.Otherwise,shewouldneverhavetobreakanyrules,becauseshe, ineffect,wouldmakeherownrules.Theassumption thatherbosscaresonlyaboutsocialwelfareisconvenientbutnotnecessary.Muchofwhatwehavetosaywouldpertain if theprincipal cares less about thebureaucrat’swelfareandmoreaboutthatof theotherbeneficiaries,whichmaybe trueeven ifone thinksof theprincipalas thestandard issue,partlyvenal, politician.After all, thepolitician caresabout staying inpower,andmakingthebureaucrathappymaynotbethebestwaytodoso.Ofcourse,itispossiblethatthebureaucratistheonewhocaresaboutbeneficiariesandistryingtoprotectthemfromherboss.This isan interestingandperhaps importantpossibility thatwedonot investigatehere.More generally, a setup like ours deliberately rules out themore interesting strategicpossibilities thatarise inmodelsofpoliticaleconomy, to focuson the implementation issuesthatariseevenwithoutthem.8Thegovernmentthereforemaximizes

bychoosing .

3.1.5.InterpretationWe intend for thismodel to be the simplest one that can illustrate all features of interest.Specifically,itallowsthebureaucrattohavemultipledimensionsofmalfeasance:

•Corruption.Thebureaucratbreakstherules.

•Bribetaking.Thebureaucratchargeshigherpricesthanthosemandated.

•Shirking.Thebureaucratfailstoimplementmandatedtesting.

•Redtape.Thebureaucratimplementsmorethanthemandatedamountoftesting.

•Allocative inefficiency. The wrong people obtain the slots (according to the rules), orsomeslotsremainunallocatedwhentherulesrequirethatallslotsbegivenout.


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Thereiscorruptioninequilibriumbecausethegovernmentdoesnotobservethecostγ.Ifthegovernment knew the particular bureaucrat’sγ, itwould knowwhat the bureaucratwouldchoose, given the rules that are set; hence, the governmentwould be able to set rules thatwould not be broken. However, when γ can take different values, the government has tochoose between rules that give the bureaucrat a great deal of discretion (so that theywillalmostneverbebroken)andrulesthataremorerigid(toinducethebureaucrattoactinthesocialinterest)andthereforewillbebrokenbysomebureaucrats(preciselybecausetheyaremorestringent).

Thisstraightforwardproblemgoesbeyondthestandardresourceallocationproblemunderasymmetric information in two important ways. First, we do not assume that the privatebenefittothepersonwhoobtainstheslotisnecessarilythesocialbenefit.Suchadivergenceischaracteristic of many situations involving the government. For example, society wants togivelicensestogooddrivers(H>0)andnottobadones(L<0),but theprivatebenefitsofgettinga license areprobablypositive forboth types.Or suppose the slot is avoidinga jailsentence.H typesareinnocent.L typesarenot.H>0 is thesocialbenefitofnotsendinganinnocent to jail. L < 0 is the social benefit of not sending a criminal to jail. However, theprivatebenefitsarepositiveforbothtypes:h lbuth,l>0.Second,weallowthepotentialbeneficiariestohaveanabilitytopaythatislessthantheirprivatebenefits(orwillingnesstopay) (l >yL orh > yH). This condition is conventionally treated as being equivalent to thebeneficiary being credit constrained, but it is worth emphasizing that it covers a range ofsituations(includingthecredit-constraintcase).Forexample,considerthepersonwhowantsto takehischild to thehospital tobe treated,buthispermanent incomedoesnotcover thecost.Hewould,however,bewillingtopayhisentireincome(lesssurvivalneeds,say)tosavehischild’slifeandalsowouldbewillingtoadditionallystandinlinefor4hoursadayeverymorning.Inthiscase,histotalwillingnesstopay(inmoneyandtime)isclearlygreaterthanhisabilitytopay.Clearly,ifhecouldfreelybuyandselllabor,thiscasewouldreducetothestandard credit-constraint case, but given themany institutional features that govern labormarkets,thiswouldbeanextremeassumption.9

However, the formulationembodiesanumberof important simplifyingassumptions.Weimpose,forexample,thatrulebreakingofanytypehasthesamecost,whichobviouslyneednotbethecase.Forexample,whenabureaucratandanagentcolludeinsuchawaythattheagent is better off thanunder the official rules, therewill probably be less chance of beingcaughtthanwhenthebureaucratattemptstomaketheagentworseoff.Wealsodonotdealwithdistributionalissues:thegovernmentisindifferenttowho—betweenthebureaucratandhisvarioustypesofclients—getstokeephowmuchmoney.Wereturntowhythisissuemaybeimportantlaterinthechapter.

3.2.AUsefulTypology

Beforejumpingintotheanalysisofthismodel,itishelpfultounderlinesomeofthedifferentpossibilitiesthatcanariseinourframework(Table1).Thefollowingtypologywillprovetobeparticularlyhandy.The labelsof the cases shouldbe self-explanatory,butmoreexplanation


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emergesasweanalyzeeachcase.10

Table1.Possibilitiesarisingfromthecorruptionmodel

3.2.1.ExamplesofCaseI:BidsAlignedwithValueInthiscase,socialandprivatevaluerankingsalign.Althoughthepuremarketcase,H=h=yH,L=l=yL,belongstothiscategory,thiscaseisultimatelybroaderthanthat,becauseeven

though the rankingsmayalign, theactual ability topaymaynotmatch socialvalue. Someotherexamplesthatfallintothiscaseinclude:

1. Choosing efficient contractors for road construction. Type H are the more efficientcontractors. For the same contract, they make more money (h > l): Within ourframework, contractors asking a lower price for theirwork is the same thing as thempayingmoreupfronttosecureacontractthatwilleventuallypaythemafixedamount.Becausethecontractorswillbepaidfortheirwork,thepricethattheypaytoobtainthecontractcanbeseenasjustadiscountonhowmuchtheywilleventuallybepaidratherthanviewedasanout-of-pocketexpense.ItisplausiblethereforethatyH=handyL=l.

2.Allocating licenses to import goods to thosewhowillmake the socially optimal use ofthem. Inanotherwiseundistortedeconomy, theprivatebenefits shouldbe thesameasthesocialbenefits,asintheroadconstructionexample,butinthisexample,theremaybecreditconstraints,becausethelicenseisfirstpaidforandtheprofitscomelater.However,itisplausiblethattypeHagentsshouldbeabletoraisemoremoneythantypeLagents.Thus,yH<h=H>L=l>yL,andyL<yH.

3.2.2.ExamplesofCaseII:UnwillingnesstoPayThis case is the least likely of the four cases, and so we do not spend much time on it.However, one possible example is amerit good, such as subsidized condoms for protectionagainstHIVinfection:Harehigh-risktypes.Theyliketakingrisks.Hence,h<l.However,theymayalsobericherthantypeL(e.g.,becausetheycanaffordtobuysex):yH>yL.

3.2.3.ExamplesofCaseIII:InabilitytoPayIn thiscase, there isalignmentofvalues: thehightypevalues thegoodmore thandoes thelowtype,butthereisaninabilitytopay.


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1.Howtoallocatehospitalbeds?TheH typesmoreurgentlyneedthehospitalbeds(e.g.,comparedtothosewhojustwantcosmeticsurgery).Thesocialvaluationprobablyshouldbetheprivatevaluationinthiscase:H=h>L= l>0.However, there isnoreasontoassumethattheHtypescanaffordtopaymore.WecapturethissituationbyassumingyH=yL=y.

2.Howtoallocatesubsidizedfoodgrainstargetedtothepoor?Presumably,theHtypesarethepoorwhobenefitmorefromsubsidizedfoodgrains,andthesocialbenefitisplausiblyjusttheprivatebenefit(H=h>L=l>0).However,thepoormaynotbeabletopayasmuchforthegrainascanthenonpoor:yH<yL.

3.Howtoallocategovernmentjobstothebestcandidates?TheprivategainsfromlandingthejobmaybehigherfortheHtypes(becausethejobsoffersomuchmorerentsthanthe next-best alternative, and the better candidate may get more out of the job).However,everyoneisconstrainedbyhowmuchtheycanpayforthejobupfront(yH=yL=y).

3.2.4.ExamplesofCaseIV:ValuesMisalignedInthiscase,thereissimplemisalignmentbetweensocialandprivatevaluation:thosetowhomthegovernmentwouldliketogivetheslotvalueittheleast:

1.Lawenforcement.Wehavealreadymentioned thisexample,where theslot isavoidingjailtime:H>0>L,yH=yL=y,h=l>0.

2. Driver’s licenses. We discussed the setup of this example previously. However, thisexamplewouldfallunderCaseIVifbaddriversvaluethelicensemore,becausetheyaremorelikelytobepickedupbythepolice:H>0>L,yH=yL=y,h<l.

3.Procurement. The governmentwants to procure a fixed number ofwidgets and has afixedbudget for them (e.g.,Bandieraetal. 2009).Suppose therearehigh-quality firmsand low-quality firms. It is socially efficient to procurewidgets from the high-qualityfirm,eventhoughthesefirmshavehighercosts.Inthiscasetheslotisthecontract,whichneeds to be allocated among firms. The gains from getting the contract are obviouslyhigherforthelow-qualityfirm,whichhaslowercosts.Sol>h.Aslongasthesefirmsarenotcreditconstrained,thatwouldalsomeanthatyH=handyL=l.

3.3.AnalyzingtheModel

This very simplemodelnevertheless allows for a richvariety of possibilities and situations.Hereweconfineourselves tosome illustrativeexamplesof thekindof incentive issues thatcanariseinthisframework,thecorrespondingpatternsofruleschosen,andtheviolationsoftherules.Specifically,wefocusonasetofspecialinstancesofCasesI,III,andIV,whichyield


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manyoftheinsightswearelookingfor.Wethenbrieflydiscusstheothercases.

3.3.1.AnalysisofCaseIInthiscase,privateandsocialrankingsarealigned.AssumeinadditionthatNH<1,butL>0,sothatitisoptimaltogivetheleftoverslotstoLtypes.Tosolvethegovernment’sproblem,westartwiththemechanismdesignproblem.Considerthefollowingcandidatesolution(wedropthesuccessorfailuresubscriptswhenaparticulartypeisnotbeingtested):

Noticethatthelowtypeswouldnotwanttopretendtobehightypes.TheycannotpaypH.Whataboutthehightypes?Iftheypretendtobethelowtypes,theycouldpay∈less,buttheywouldreceivetheslotwithprobabilitylessthan1.Aslongas

thehightypeswouldprefertopaythepriceandbeguaranteedaslot.Wecanalwaysset∊lowenoughtoensure that this is thecase.Therefore, themechanismis incentivecompatible forsmall enough ∊. Because both types receive positive expected benefits, the participationconstraints are also satisfied. The solution is feasible, because the ratio was chosen

precisely to exhaust the total number of slots. Finally, it is affordable, as long as ∊ is smallenough,becauseyH>yLinthiscase.DefineEtobethesetof∊suchthatthismechanismisin

.Thissolutionisalsosocial-welfaremaximizing,becauseeveryHtypereceivesaslot,every

slot is taken,andnoone is tested.Thekeyquestion iswhether thebureaucratwillwant tochoosethismechanismforsome∊∈E:ifhewillchooseit,thenthegovernment’sproblemissolved.However,itispossiblethathemightpreferanalternativemechanism.

Givenourassumptionthat there isa fixedcostofbreakingtherules, if thebureaucrat iscorruptibleandchoosestobreaktherules,hewillchoosethemechanismthatmaximizeshispayoff given by (1). Therefore, he will want to maximize the amount of revenue he canextract.Themechanismalreadyallowshimtoextractallpossiblerevenues fromtypeL.Tomaximizehispayoff(inthisclassofmechanisms),hewillset∈toitsmaximalvalueinE.Thatis,hewillset


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Letus,withsomeabuseofterms,callthefollowingthe“auctionmechanism”:

However,inthisscenario,heisnotextractingalltherentsfromtypeH,becausepHmightbe

lowerthanyH.Whataretheothermechanismsthatcouldpotentiallygivehimhigherpayoffs?

Oneistheclassofmonopolymechanisms.Set

Thesemechanismsareconstructedso that theprobabilityofgetting theslotasanL type islowenoughthatnoHtypewillwanttopretendtobeanLtype.NoLtypecanaffordtheslotat theH type’s price, so that incentive constraint also doesnot bind.By construction, thesemechanisms also satisfy the slot constraint, as well as the participation and affordabilityconstraints.However,theygenerateaninefficientoutcome,assomeslotsarewasted.

Obviously, this class of mechanisms will only interest the bureaucrat if .Thecondition that itmakesmoremoney than theauction

mechanismisthattheexpression

isincreasingin ,becausefor ,thisisexactlythepayofffromthe

auctionmechanism.Therelevantconditionistherefore

If this condition holds, themonopolymechanism thatmaximizes the bureaucrat’s earnings


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willhave =yH.Otherwise,theauctionmechanismdominates.

Finally,thelastalternativeweconsideristhetestingmechanism:

The exact construction of thismechanism is less obvious, so let us look at it in a bitmoredetail.Theideaofthismechanismistousetestingjusttoreducetherentsoftheself-declaredL types, so thatH typeswould notwant to pretend to beL types. It is inefficient, becausetestingiswasteful.BecauseHtypesaremorelikelytopassatestthanLtypesare,itwouldbecounterproductivetoreward“passing”:thegoalistodiscourageH typesfrompretendingtobeLtypes.Torewardfailingthetestalsodoesnotwork:Htypescanalwaysfailonpurpose.Therefore,thereisnoadvantagetoconditioningontestoutcomes.

ToseethattestingrelaxestypeH’sincentiveconstraint,notethatnowitbecomes

Clearly, pH can go up when tL increases, which is why the bureaucrat might want it to.

However,thereisobviouslynopointindrivingtLpastthepointwherepH=yH.ThisdefinesonelimitonhowlargetLshouldbe:

Anotherlimitcomesfromthefactthat,byimposingtesting,theLtypeismadeworseoff.SotLmustsatisfyIRL:

AslongasIRLisnotbinding,raisingtLalwayspaysoffintermsofallowingpHtoberaised.Onceitbinds,itispossibletocontinuetoincreasetLbyreducingpLbelowyL.However,this

will never pay off, because reducing pL also forces the bureaucrat to reduce pH. Setting

andpluggingthisintotypeH’sincentiveconstraintgivesusthelimitonGibbons, R., & Roberts, J. (Eds.). (2012). The handbook of organizational economics. Retrieved from http://ebookcentral.proquest.comCreated from uchicago on 2018-11-15 12:41:15.

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howhighwecandrivepHbytestingLtypes:

Puttingtheseobservationstogetherexplainswhyweconstructthetestingmechanisminthisway.

It isalsoworthobservingthattL=0whenyL=l.Thisresultoccursbecausewhen IRL isbinding,redtapewillneverbeused.Thus,thefactthatthebureaucrat’sclientsareunabletopaythefullvalueofwhattheyaregettingiskeyfortheresultthatthereisredtape(thatiswhytheypayin“testing”ratherthanmoney).

Thesethreemechanismsdonotexhausttheclassoffeasiblemechanisms.Forexample, itmay be possible to combine the testing andmonopolymechanisms.However, it is easy tothinkofsituationswhereeachofthemmaybechosenbysomebureaucrats,dependingontherulesthatthegovernmentsetsandotherparameters.Thetrade-offsthatthismodelgeneratesaremainlywhatweneedtounderstand.

Scenario1Supposethat .Then,theauctionmechanismextractsasmuchrentaspossible.Thegovernmentcangivethebureaucratfulldiscretion(norules)andexpecttheoptimaloutcome.Itcanthensetptoappropriatelydividethesurplusbetweenitselfandthebureaucrat.Thebureaucratchoosestheauctionmechanism.

Scenario 2 Suppose that . Assume that πxr, pxr, and tx arecontractible.Therulesdonotimposeanyrestrictionsonthechoiceoftx.Also,assumethatthebureaucrathasnocostoftesting(ν=0)andthatitispossibletoextractmaximalrentsfromtypeHbytestingthetypeL,whichwillbetruewhen11

Supposefirstthatthegovernmentsetsnorules.Becausethebureaucratpaysnocostfortestingand testing allows her to extract maximal rents, she will choose the testing mechanismdescribedaboveasawaytocreateartificialscarcity.

One alternative for the government is to set the rules so that the maximum price thebureaucrat can charge is and all testing is forbidden. For thosebureaucratsnotprepared tobreak the rules, the optimalmechanism in this casewill be theauction mechanism (because they were deviating from it precisely to charge the H type ahigherprice,whichisnownotallowed).

However,thosebureaucratswhohavealowcostofbreakingtherules(lowγ)willdeviate


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fromtheauctionmechanismandchoosethetestingorthemonopolymechanism.12Thetestingmechanism tends to extract lessmoney from eachL type (because they also pay the cost ofbeing tested), but more L types get slots. Which of the two will be chosen depends on theparameter values. For example, an increase in yH − yL, keeping l − yL fixed, makes themonopoly mechanism relatively more attractive (intuitively, when the H type can payrelatively more, the cost of including the L type increases). If the monopoly mechanism ischosen, therewillbenored tape,but largebribes (priceabove themaximumallowedprice)willoccur. If the testingmechanism ischosen,wewillobservebothbribery (priceabove themaximumallowedprice)andredtape.Nevertheless,fromthesocialwelfarepointofview,thisoutcome is strictly better than the no-rules outcome, because a fraction of the bureaucrats(those with high γ) choose the auction mechanism. What is particularly interesting here,though,isthattherulesthemselvesarenowaffectedbythepotentialforcorruption.Adifferentsetofrulesmakesensewhenthebureaucratsaremorecorruptible.

Scenario3Suppose that .Assumepxr and tx are contractible, but

πxrisnot.13However,letνbeveryhigh,sothatthebureaucratisnotpreparedtouseredtape.

Intheabsenceofanyrules,thebureaucratwilleitherchoosetheauctionorthemonopolymechanism.Wealreadygeneratedtheconditionunderwhichthemonopolymechanismmakesmoremoney:

Interestingly,thisconditionislesslikelytoholdifpislower—thegovernmentmaybebetteroffnotchargingthebureaucratsfortheslots.However,evenwithp=0,itispossiblethattheaboveconditionholds(especiallyifyLisverylow),andthebureaucrat,unconstrained,wouldchoosethemonopolymechanism.Supposethatthisisthecase.Thentheno-rulesoutcomewillleavemanyslotsunallocated.

Thegovernmentmayprefertosetarulewherethepricesthatcanbechargedarecappedby. Then the bureaucrats who have high γ will choose the auction

mechanism,while the low-γbureaucratswillchoosethemonopolymechanism.Therewillbebribery,becausethemonopolypriceishigherthanthepricecap.

3.3.2.AnalysisofCaseIIILetusfocusononespecialcase:L>0,NH<1,h>l,yH=yL(whicharetheassumptionsunder

whichthiscaseisanalyzedinBanerjee1997).Tolimitthenumberofcases,letyH=yL=y<landϕL(t) = 0; that is, noone ever fails the test. In this case, once again there is an auction


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mechanism:

where issuchthat14

Thismechanism implements the efficient outcome, because the high types, though theycannotpaymore,valuetheslotmore(h>l)andhencewouldratherpaythehighprice(alltheycanafford)andensureaslotratherthanrisknotgettingoneatthelowprice.Thelogicofauctionsstillworks.

However,nowconsideranalternativetestingmechanism:

where isgivenby

AsinScenario2,testingonlyhappenswhenl−y>0.Athirdisalotterymechanism,givenby

Thebureaucratchargeseveryoneyandsimplyholdsalotterytoallocatetheslots.

Scenario4Supposethatπxr,pxr,andtxareallcontractible,andν=0.Gibbons, R., & Roberts, J. (Eds.). (2012). The handbook of organizational economics. Retrieved from http://ebookcentral.proquest.comCreated from uchicago on 2018-11-15 12:41:15.

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Whatwouldhappenifthegovernmentsetnorules?Thebureaucratwouldalwayspreferthelottery,withaverysignificantmisallocationofslots.

Now,supposethegovernmentsetstherulessothatthebureaucratisrequiredtochoose

butthereisnoruleforwhatpriceshecanchargeortheamountoftesting.Everybureaucratwillchoosethetestingmechanism,becauseitgivesthemthesamepayoffasthelotterywithoutbreakinganyrules.

Supposethegovernmentwantstostopthisunnecessarytesting.Thenitcansetrulessothatthebureaucratisrequiredtosettheauctionmechanism:

Thismechanismwillbechosenby thosebureaucratswhohavehighenoughγ.However, thelow-γbureaucratswillchoosethetestingmechanism,andtherewillbebothbriberyandredtape.15

Alternatively, the government could choose the lottery as the rule.All bureaucratswouldthen choose it and there would be no corruption and no red tape, but the outcome thateveryone chooses would involve misallocation. However, because there is no testing, thisoutcomemightbebetterthanthatfromtesting,ifthecostofbeingtested,δ,ishighenough.Moreover,thetestingmechanismisonlybetterbecauseitmakesthehigh-γbureaucratschoosetheoptimalmechanism.Therefore, ifmostbureaucrats facea lowvalueof γ, representingagovernment that cannot enforce the rules verywell, then the lotterymechanism is likely todominate.

3.3.3.AnalysisofCaseIVLetusrestrictourattentiontothespecificsituationNH>1,yL= l>h=yH,andL<0.Thegoodsarescarce,buttheprivatevaluationofthehightypesislowerthanthatoflowtypes.The low types should ideally not obtain the slots.16 The analysis in this section draws onGuriev(2004).Considerthefollowingtesting+auctionmechanism:


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where and solvethetwoequations17

It is easy tocheck that thismechanismsatisfiesall theconstraints.Ofparticular interestaretypeL’struth-tellingconstraint:

whichstatesthattypeLindividualvotersweaklyprefernotgettingtheslottopretendingtobeatypeHandgettingitwithsomeprobability.Itisclearthatforthisconditiontohold, >0, because without testing, the L types always want the slot if theH types do. Testing isnecessaryinthiscase.

Thismechanismalso implements theoptimalallocation (onlyH typesget the slots)withtheleastamountoftesting.

However, the bureaucrat may consider other mechanisms. One possibility is a straightauction:

Anotherisalottery.Nooneistested,buttheallocationisallwrong—onlyLtypesreceivetheslots:

Scenario 5 Suppose that πxr, pxr, and tx are contractible, and ν > 0. Consider what wouldhappen without any rules. The auction mechanism maximizes the bureaucrat’s earningswithoutanytestingandwillbechosen.Nowsupposethegovernmentsetsrulesabouttx,πxr,


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andpxrexactlyatthelevelgivenbythetesting+auctionmechanism.Bureaucratswhodonotwanttobreaktheruleswillthenchoosethetesting+auctionmechanism.Theoneswhoarepreparedtobreaktheruleswillchoosetheauctionmechanism.Thereisbribetaking,shirking,andmisallocationofresources(similartoBandieraetal.2009).

However, the government could also give up on trying to implement the ideal testing +auction mechanism. It could set the rules corresponding to the lottery mechanism. Theadvantageofthismechanismisthatthebureaucratsaremakingmoremoneyfromtheslots,because h > , and spending less effort on testing; hence, the gains from deviating aresmaller.Thedisadvantage is that some slots go to theL types, even if thebureaucrat isnotcorrupt.However,fewerofthemdeviatefromtherulesandgiveallslotstotheLtypes.

3.4.InterpretationofResults

Theaboveanalysismakesclear theessenceofourapproach.Governmentsare interested insettingruleswhenthelaissez-faireoutcomedoesnotmaximizesocialwelfare.Putsimply:inthis model, governments only interfere to improve an inefficient situation. Corruption,however, results when these rules do not extract maximum surplus for the bureaucrat.Sometimestherulesallowthebureaucrattoextractsurplusexactlyasshewants(e.g.,CaseIinSection3.3.1),but inmanyothercasestheymaynot.Thetaskassignedtothebureaucratand the rules are chosen by a government cognizant of the possibility for corruption. Inseveralofthecases, it isclearthatthepresenceofcorruptiblebureaucratschangestherulesand tasks. The government chooses those rules, and the task is assigned to the bureaucrat,recognizingthattheruleswillsometimesbebroken.Theoveralloutcomeisstillimprovedbysettingthoserules.Thisistheessenceofthetasksapproach.

However, themodelalsooffersother,morespecific, insights.Thefirstobservationisthatred tape goes hand in handwith bribery.Given that testing is costly, there is no reason tooveruseit,unlessthereisextramoneytobemade.However,therearetwodistinctreasonsforusingit.Whenthewillingnesstopayisalignedwithabilitytopayandsocialvaluation(CaseI;specifically,Scenario2),redtapeisfacedbyLtypes,thatis,thosewhohavealowprobabilityofobtainingthegood,andisdesignedtocreatesomeartificialscarcityandextractmorerentsforthebureaucrat(alongthelinessuggestedbyShleiferandVishny1994).Inotherwords,thepurposeoftheredtapeistoscreeninthetypeswithahighwillingnesstopay.Whenabilitytopay is not related to the willingness to pay (Case 3, Scenario 4), then red tape emerges,because even corrupt bureaucrats prefer to generate as efficient an allocation as possible,conditional on notmaking lessmoney. The red tape is then placed on theH type, and thepurposeistoscreenoutthetypeswithalowwillingnesstopay.

ThesecondpointisthatredtapeonlyemergeswhenyL<l.Moreover, it iseasytocheck

thatinbothcases,redtapeincreasesinthegapbetweenthewillingnesstopayandtheabilitytopay.Theintuitionissimple.Itispreciselybecausethisgapexiststhatitispossibletoimposeredtape.Iftherewerenosuchgap,theclientwouldsimplywalkawayiffacedwithagreatdealof red tape.This reasoningmakes it clearwhypeopledonothave to endure red tape


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whenthey try tobuymostmarketedgoods (i.e.,goods forwhich l=yL).Governments are

associated with red tape, in this view, because governments often supply goods to peoplewhose ability to pay is less than their willingness to pay. For that reason, this problem isparticularlyacuteforgovernmentsservingthepoor.

A third point,which is related to the first, is that red tape doesnot have to result fromscarcity.Scarcitymayhaveapositiveoranegativeeffectonredtape,dependingonwhetherwearetryingtodiscouragetheH type frompretending tobeanL type (Scenario2,wherescarcityreducesredtape)ortheopposite(Scenario4,wherescarcityincreasesredtape).

A fourthpointcomes fromthinkingabout thecorrelationbetweenred tapeandbribery.Thiscorrelation isemphasizedbyLaPortaetal. (1999),who, lookingatcross-countrydata,argue that the positive correlation of testing with bribery is evidence that much testing isunnecessaryandhence is red tape.Asalreadyobserved, red tapeonlyoccurswhenthere isbribery.However,wecannotassumethatthereisalwaysmoreredtapewhenthereismorebribery—thatdependsonwhatistheunderlyingsourceofvariationaswellastheunderlyingeconomicproblem.Forexample,bothinScenarios2and4,theincentivetomoveawayfromthe auction outcome toward the testing outcome is always strongerwhen l − yL is larger.Therefore, there will be more red tape and corruption when yL is lower, as long as the

governmentsetsrules thatcorrespondtothesociallyefficientmechanism.Incontrast,whenyH − yL goes up, keeping l − yL fixed, corrupt bureaucrats will switch from testing to

monopoly(seeScenario2).Thereisanincreaseinthesizeofbribesandafallinredtape.18

AfifthpointfollowsfromScenario5.Briberycanbeassociatedwithredtape,butitisalsoassociatedwithshirking,which,inasense,istheoppositeofredtape.

A sixth point follows from the observation in Scenario 4 that a rightward shift in thedistributionofγwillleadthegovernmenttoswitchfromrulesthatcorrespondtothelotterymechanism to those that correspond to the testingmechanism.This switch leads to greaterbribery andmore red tape but to less misallocation and is therefore worthwhile. In otherwords,greaterstatecapacitymightbeassociatedwithmoreredtapeandbribery.Conversely,alackofbriberycannotbeinterpretedasevidencethatalliswell.

Aseventhobservationisthatcorruptionmightforcethegovernmenttogiveupontryingto maximize its revenues from the sale of slots. In Scenarios 1 and 3, we saw that thegovernment should set theprice of the slots to thebureaucrat as lowaspossible to reducecorruption.

Finally, it is clear that the government often faces a choice between more desirablemechanismsthataremoresubjecttocorruptionandlessdesirableonesthatarelessso.ThisisexactlythechoiceinScenario4butalsoinScenario5.Corruptionisthereforeanoutcomeofthischoice.

3.5.FirmsandGovernments:ADigression

The broad framework developed above would apply, mutatis mutandis, to any situationwheretheprincipalcaresabouttheassignmentofslotstotherightpeoplebutnothowmuch


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moneyhemakesfromtheslots,buttheslotallocationisimplementedbyanagentwhodoesnotcareaboutwhogets theslotsbut isconcernedabouthowmuchmoneyshemakes.Thefirstassumptioncomesdirectlyfromourframework.

However,muchofwhatisinterestingherealsoreliesontwoadditionalassumptions.First,theprivatevaluationofthosewhoreceivetheslots isnotnecessarilyequaltothevaluetheprincipalputsongivingthemtheslots.Second,theprivatevaluationmaynotbethesameastheabilitytopay.

These assumptions are quite natural in the context of thinking about governments andsimilar organizations, such asnonprofit organizations.However, in the conventionalwayoflooking atmarket transactions (think of the principal as themanufacturer, the agent as theretailer,and theclientsasbuyers),noneof these threedefiningassumptionsprobablyapply.We now recognize that there aremany transactions involving firmswhere the firm is notseeking tomaximize short-run profits, because ofmultitasking, reputation, or signaling, forexample,orbecausethetransactionisinternaltothefirm(e.g.,whoshouldbepromoted).Insuch cases, our first two assumptions are likely to be satisfied. However, the third keyassumption (about the divergence between the willingness and the ability to pay) is lessobviouslyapplicable.

Thus,CasesIandIVprobablyfittheprivatesectorbest(seeSections3.3.1and3.3.3).Weknowthattherecanbecorruptioninboththesecases(Scenario2orScenario5),eveniftheabilityandthewillingnesstopayarethesame(yL=l,yH=h).However,asalreadyobserved,

therewillnotberedtapeinsuchcases,thoughshirkingmayoccur.Otherpotentialsourcesofcorruptionthatdonotariseinourmodelmayoccurinprivate

firms. There may be conflicts over the division of the surplus with a profit-maximizingprincipal—foravarietyofreasons(e.g., theagentsmaybecreditconstrained), thefirmmaywant to share enoughof its realized revenueswith its agents to align their incentives.Thismaybeevenmoreofanissueforprivatefirmsthanforgovernments,thoughasdiscussedinSection3.6,itiscentraltosomethingsthatgovernmentsdo,suchastaxcollection.

Many reasons not in our model account for why the government may have morecorruptionthanprivatefirmsdo.Onebigdifferencebetweenfirmsandthegovernmentisthateven when many of the transactions take place within the firm, there is still an ultimateprincipal(orprincipals)whosebusinessismaximizingprofits.Thiscouldplacealimitonthelevelofrentsthatcouldpossiblybecaptured.Considercorruptioninpromotiondecisions.Thiscontextoffersopportunities forcorruption inbothsectors. In thegovernmentcontext, thereare jobs that one would like to capture because they offer rents in terms of bribes fromcustomers(e.g.,thejobofapoliceman).Thus,boththecapacitytoengageincorruptionandawillingnesstodosoexist(therearebigrents).Thefirmcontextallowsroomforcorruption,becausepromotionsarealsonotallocatedthroughamarketmechanism.However,theupsidegainsfromcapturingthejobarefarmorelimited:thecustomersarepayingmarketprices,andhence, there are no rents to be had from them. At best, one gets the rents from a higherpayingjoband,inmostcases,thesearenowhereneartherentstobehadfromhavingaccesstocustomerswhoarewillingtopayabribe.

A related point is that governments and firms are held accountable through different


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mechanisms.Governments have to convince voters to reelect them, but thewelfare of thevotersdependsonacombinationofmanyoutcomes.Asaresult,theelectoratecannotsimplyuse single metrics, such as revenues or taxes collected, to evaluate performance. Firms,however, are (much more easily) evaluated along a single dimension—profitability. Thisdifferencegeneratesopportunityforcorruptioningovernmentthatdoesnotexistinfirms.Forexample, consider procurement procedures. In firms, a clear mapping connects fromcorruption in procurement to lower profitability, which the boss typically does not like.Whereasinthegovernment,theresultantriseincostsisprobablysubmergedsomewhereinthegeneralbudget,andwhilethelossofqualitymightbenoticedbysomevoters,theywouldmostlikelyplacesmallweightonitintheirdecisionofwhomtovotefor.Indeed,wemightspeculate that thosewhoare in favor of corruption in governmenthave a stake in arguingagainstanysinglemetricofperformance.

Insummary,firmshavelessslackattheedgesthangovernments.Thislackofslacklimitstheroomforcorruptionwithintheorganization.Ofcourse, itdoesnotcompletelyeliminatecorruption.Nordoesitmeanthatallfirmsfacelittleslack.Forinstance,poorlygovernedfirmsor thosewithmonopolypowerorother factorsgenerates slack.Wearemerely speculatingthatqualitatively, governments experiencemuchmore slackwhendealingwith clients, andthisslacktranslatesintomoreopportunityforcorruptionintheorganization.

3.6.LimitationsoftheFramework

3.6.1.MonitoringAclearlimitationofourframeworkismadeclearfromthediscussioninSection3.5aboutthedifferences between external incentives faced by governments and private firms. It tells usvery little aboutmonitoring structures, other than the obvious point that bettermonitoringwouldreducecorruption.Theemphasisonmonitoringintheorizingcorruptiongoesback,ofcourse,totheclassicpaperbyBeckerandStigler(1974).Althoughtheinsightsfromthispaperremain fundamental, we see it more as a paper on agency problems generally and notparticularlyaboutcorruption.

There is also now a literature that emphasizes the institutional aspects of monitoring.Clearly, a choice exists for who monitors (the superior bureaucrats, the community, thevoters?)andhowintensively(shouldtherebepro-activepublicdisclosuresofpublicaccounts,of the performance of individual bureaucrats, etc.?). Even though the Bardhan andMookherjee(2006)modelcapturestheimportantandbasicideathatcommunitiesmayhavean informational advantage in monitoring (and therefore in controlling) corruption, thetheoretical literatureon this subjecthasnot advancedverymuchbeyond thispoint, thoughthereisalotofinterestingempiricalmaterialavailable.

An important theoretical literature emphasizes the endogeneity of the effectiveness ofmonitoring. Lui (1986) makes the point that corruption may be harder to detect wheneveryoneelseiscorrupt.Tirole(1996)showsthatinamodelwhereexperimentationiscostly,when enough bureaucrats are corrupt, everyone acts as if all of themwere corrupt,whichremovestheincentivetobehonest.Thereisalsotheideathatpeoplefeellessbadaboutbeingcorruptwhen everyone else is corrupt.Toourknowledge, little rigorous empirical research


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hasbeendonebasedontheseideas,thoughtheyareobviouslyimportant.

3.6.2.ReintroducingDistributionalConcerns:UnderstandingExtortionAnotherlimitationofourframeworkisthatitassumesthatthegovernmentmaximizestotalsocialwelfare.However,ignoringthedistributionofwelfarebetweenthebeneficiariesandthebureaucrats is clearlywrong inmany instances.Oneobvious example is tax collection.Taxcollection is all aboutwho pays. In such cases, the governmentmight prefer an inefficientoutcome, because it achieves the distributional outcome better andmay therefore create amorecomplexsetoftrade-offsthanareotherwisepermitted.

Similarly, the fact that the outside option in ourmodel allowspeople towithdraw fromobtainingaslotisalsopotentiallyproblematic,especiallybecausethisoutsideoptiondoesnotvarybytype.Considerataxcollectionexample.Supposeyouaretryingtogetatax-exemptcertificate,becauseyouhavenomoney.Anundeservingtaxpayer(atypeL),whoactuallycanaffordtopaythetaxes,doeshavetheoptiontowalkaway:ifshedoesnothavethecertificate,shecanalwayspaythetaxesandbedonewithit.Incontrast,thedeservingtaxpayer(typeH)cannotpaythetaxes.Asaresult, ifhewithdrawsfromtryingtoget thecertificate,herisksprison.HisoutsideoptionisworsethanthatofthetypeL.

More generally, our assumption about outside options limits the possibility of extortion.However,ithaslongbeenrecognizedthatonereasonmanygovernmentfunctionscannotbeprivatizedisbecauseofthepotentialforextortion.Weneedaframeworkthathelpsexploretheseissues.

3.6.3.ScreeningonMultipleDimensionsInourframework,theassumptionthatthereisonlyonedimensionofasymmetricinformationis very restrictive. The bureaucrat may want to know about both the beneficiary’s type(becausemisallocation is punished) and his ability to pay (because the bureaucratwants tomakethemostmoney),andthetwotraitsmaynotbeperfectlycorrelated.Asimpleexampleof what can happen in such situations is worked out in Banerjee (1997), but the generalmultidimensionalscreeningcaseisnotwellunderstood.

3.6.4.ModelingCorruptionOur framework also embodies one specific viewofwhy there is corruption in equilibrium.Corruptionoccursbecause thecostofviolating rulesvariesacrossbureaucrats.However,asdiscussed at some length in Tirole (1986), there are other reasons. For example, thegovernmentmayrecognizethatinsomestatesoftheworld,thebureaucratandhisclientsareinpositiontocutaprofitableprivatedealthatthegovernmentwouldliketopreventbutlackstheinformationtodoso.

Whynotthensimplyrecognizethatthisdealwillhappenandmakeitlegal?Onepossibleanswer is that there are many other states of the world where the same deal would beavailable,butintheseotherstatesoftheworld,thegovernmentisinapositiontodetectsuchbehavior, prosecute the bureaucrat, and thereby prevent the transactions. However, if the


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courts cannotdistinguishbetween those statesof theworldwhere suchprivate transactionsareproscribedandotherstatesoftheworldwheretheyarenot,thebureaucratcouldalwaysclaim that the transaction was allowed and get away with it. By banning all transactionsbetweenthebureaucratandhisclient,thegovernmentiscreatingthepossibilitythattheruleswill be violated from time to time, but it gains in terms of being able to prosecute thebureaucratifhegoestoofar.

4.MeasuringCorruptionMeasuring corruption is the primary challenge in the empirical literature. Without robustmeasures, the theories cannotbe tested, themagnitudesof corruption cannotbequantified,anticorruption policies cannot be assessed, and so forth. However, measuring corruption ischallenging,andeventoday,relativelyfewstudiesareabletocrediblydescribetheextentoftheproblem.AsBardhan(1997:1320)notesinhisreviewofcorruption,“ourapproachinthispaperisprimarilyanalyticalandspeculative,giventheinherentdifficultiesofcollecting(andhencenonexistenceof)goodempiricaldataonthesubjectofcorruption.”

The measurement challenges are driven by several problems. First, the very fact thatcorruptionisillegalmakespeoplereluctanttotalkaboutitforfearofgettingintotroubleand,possibly,forshame.Second,theexistingliterature—becauseofthetheoryitdrawsonandhowit defines corruption—takes a transactional viewof corruption.Measurementmeans findingoutwhobribedwhomandbyhowmuch,which is inherentlyharder toquantify.Third, thetraditional narrow focus on monetary transactions also makes it more difficult.19 When agovernment official benefits by stealing “time”—she decides not to show up for work—random spot checks can be very revealing (e.g., see Chaudhuri et al. 2006). Finally,measurementsystemswillevokeresponsesthatmakethemeasurementsystemlessreliable.Ifthegovernmenthasamonitoringsysteminplace,peopleadjusttoitandfindwaysaroundit.Asaresult,thesemeasurementsystemswillunderestimatecorruption.

Despite these difficulties, many early attempts at measuring corruption relied on richqualitativedataandwereoccasionallybackedupbynumbers.Thesestudiesgavethefirstrealevidence about the channels through which corruption occurred and possible methods toeliminate it. Wade (1982) in particular provides a detailed description of how irrigationengineersreaprevenuefromthedistributionofwaterandcontractsinavillageinSouthIndia.Themostfascinatingaspectofthisstudywasthedocumentationofafairlyformalsysteminwhich the engineers redistributed revenue to superior officers and politicians. To obtaintransfers to lucrative posts, the junior officers paid bribes based on expectations about theamount of bribe money that can be collected from the post. Thus, the value of the bribepayment in the transfer process was higher for jobs that had greater potential for bribeextraction.Inessence,theabilitytotakebribesinajobinducesbureaucratstobribeotherstoget it.Thishighlydetailedstudygivesaglimpseintothepervasivenessofcorruptioninthisareaandthemechanicsofhowitoperates.Italsoillustrateshowcorruptionisinterconnectedthroughouttheentireorganizationandraisesthepossibilitythatratherthantryingtoremoveoneaspectofcorruption, itmaybenecessaryto invokecoordinatedpolicies tostampitoutthroughout the system. However, like all case studies, the study raises questions of


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generalizability. Is there as much corruption in other contexts? Under what set ofcircumstancesdothesesystemscomeintobeing?

Other early studies focused on anticorruption policies. For example, Klitgaard (1988)providesseveralcasestudiesofsuccessfuleliminationofcorruption,suchasintheHongKongPolice Force, Singapore Excise Department, and the Bureau of Internal Revenue of thePhilippines. In all these cases, the levers used are intuitive from the perspective of agencytheory—moreintenseorbettermonitoring,replacingindividualactors,andsoforth.Theyalsoallseemtoinvolveapersonatthetopofeachinstitutionwhowaseagertoimplementthesechanges. On the one hand, these cases represent a vindication of an agency theory ofcorruption.Ontheotherhand, theyraise themorefundamentalquestion: if these levers foreliminatingcorruptionareinthechoicesetsofgovernments,whyaretheynotimplemented?Although they spark hope that corruption can be fought, these examples leave lingeringquestionsaboutwhyconditionswereripefortheseinterventionsbutnotforthoseelsewhere.Is what we observe due to particular institutional factors in these settings or to moregeneralizable features of how governments function? What particular combinations ofinstitutions,policies,orconditionswouldleadtosimilarstepsbeingtakenelsewhere?Shouldweexpectthesameconsequencesofsimilaranticorruptionpoliciesindifferentsettings?

To address these inherent problems of case studies, the next attempts to measurecorruptiontriedtoprovideconsistentmeasuresofcorruptionacrosscountries.However,giventhedifficultyofinducingpeopletotalkaboutcorruption,thesemeasuresfocusoncollectingperceptionsofcorruptionratherthanontheactualbribespaidortheactualtheftofresources.This perception-based approach has been carried out at quite a large scale, generatinginterestingcross-countryandcross-timedatasets.TheEconomistIntelligenceUnitcreatedoneofthefirstsuchdatasets.20Thedatacollectioneffortconsistedoffactorassessmentreportsthatwere filled inby theUnit’snetworkof correspondents andanalysts.The reportswere thenaggregatedintoriskfactorsforabout70countries.Thefactorassessmentreportsincluded,forexample,aquestionwheretherespondentsrated“thedegreetowhichbusinesstransactions(in that country) involve corruptionorquestionablepayments”ona scaleof 1–10,whereahigh value implies good institutions (Mauro 1995: 684). Other cross-country measures onsubjectiveperceptionsofcorruptionfollowed,includingtheControlofCorruptionmeasuresinthe World Bank Governance Indicators (a description of the measures can be found inKaufmann et al. 2004), andmeasures by Transparency International (2008).21 Each of theseindicatorsusesadifferentmethodologywithitsownadvantagesanddisadvantages,whichwedonotdiscusshereduetospaceconstraints.22Therealadvantageofsuchdataistheirbreadth,whichallowsonetorunlargecorrelationalstudies.Mauro(1995)isanoften-citedexampleofthiskindofstudy.HeusestheEconomistIntelligenceUnitmeasuresinacross-countrygrowthregression equation to study the relationships amongeconomicgrowth, corruption, and redtape.

While these perception-based measures of corruption provided evidence on whichcountriestendtoreportmoreorlesscorruption,manyhavepointedouttheirlimitations.First,asRose-Ackerman(1999)noted, it isunclearwhat thecorruption indicesactuallymeanandwhat a particular rank implies about the type and level of corruption in a country. For


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example, in the Transparency International Corruption Perceptions Index for 2008, Brazil,BurkinaFaso,Morocco,SaudiArabia,andThailandallhavethesameindexvalue.However,thevaluedoesnot telluswhat the formofcorruption in thesecountriesentails,nordoes itindicate whether the types of corruption observed in these very different countries havedifferentefficiencyimplications.Forexample,inthetheoreticalframeworkdevelopedinthischapter,bribetakingcanactuallypromoteefficiency,iftheproblemisthatthegovernmentiscommitted, forpoliticalor ideologicalreasons, toset thepricecapbelowwhat it shouldbe.Moreover,corruptionoftenemergesasaresultofgovernmentinterventionsdesignedtodealwithsomeotherdistortion(seeSection3).Thesecountriesmayhaveverydifferentproblems—whywouldthegapbetweenlandyLorbetweenhandyHbethesameinSaudiArabiaand

BurkinaFaso,giventheirverydifferentlevelsofpercapitawealth?Orcorruptionmaybearesultofthegovernment’sattempttofightsomeotherformofmisbehaviorbyitsbureaucrats—forexample, inCase I (Section3.3.1),absentapricecap, thebureaucratmightchoose themonopolyoutcome,andmanyslotsmaybewasted.Apricecapmightmovetheoutcometomorevisiblemalfeasancebythebureaucrats(redtapeandbribetaking)butlessmisallocationandlessinefficiencyoverall.Greatercorruptioninonecountrycouldsimplybeareflectionofa greater willingness to fight corruption in that country. Because they do not supplyinformation about the sources of corruption, these corruption indices actually tell us littleaboutwhat types of governance interventionswould help dealwith the problems or evenwhether we should reward or praise governments that have less corruption by thesemeasures.

Second,perceptionsmayindicate littleabouttheactualrealityofsituations,becausetheyareinfluencedbythewayweseeeverythingelse.Forexample,perhapswhentheeconomyisgood,weperceivelesscorruption,becausewearemoresatisfiedwiththegovernment.Olken(2009), for example, compares the perception of corruption in a roads project with actualmissingexpenditures.Hefindsthatalthoughthereisrealinformationinperceptions,reportedcorruption is not particularly responsive to actual corruption. For example, “increasing themissingexpendituresmeasureby10percent isassociatedwith justa0.8percent increase intheprobabilityavillagerbelievesthatthereisanycorruptionintheproject”(Olken2009:951).He also finds that the bias in perceptions is correlated with demographic characteristics,implying that perceptions of a nonrandom sample of the population may not adequatelyreflect real corruption levels. This bias is particularly problematic, as many perceptionmeasuresarenotnecessarilybasedonrandomsamples.Forexample,themeasuresfromtheEconomistIntelligenceUnitarebasedontheperceptionsofforeignanalysts,whomayhavedifferentperceptionsofcorruptionthantheaveragecitizenofthecountry.Finally,andperhapsprobablymost importantlyforourpurposes, thesedataaremostuseful forcross-countryorcross-geographyanalysis.Theyarelessusefulfortestingmicrotheoriesofcorruption.

Newmethodsformeasuringcorruptionhavebeendevelopedthatsolvethesmall-sampleproblemandmovetomoreconcretemeasuresofcorruption.Thefirstsuchmethodfocusesonrefiningsurveyanddatacollectiontechniquestoimprovetheabilitytoassembledataonself-reportedbribesandservicedeliveryquality.Forexample,Svensson(2003)analyzesadatasetthatprovidesinformationonbribespaidbyfirmsinUganda.Toencouragetruthtellinginthesurvey, itwasconductedbyatrustedemployers’association; italsoaskedcarefullyworded,


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hypothetical questions to measure corruption.23 Hunt (2007) uses the International CrimeVictimsSurveysandPeruvianHouseholdsurveys,bothofwhichcontaininformationonbribestopublicofficialsiftheindividualhasbeenthevictimofacrime.24Otherstudiescollectpricespaidforservicesthatshouldbefree.Forexample,Banerjeeetal.(2004)collectsdataonfeespaid at government health centers in India (that shouldmostly be free), Atanassova et al.(2008)collectdataonpricespaidandquantitiesreceivedfromthepublicdistributionsysteminIndiaandcomparethemtotheofficialpricesforthesecommodities.Themainbenefitofthesemethodsisamovetomeasuresthathaveactualmeanings.Forexample,usingthemeasureinBanerjeeetal. (2004),wecanestimatethebribeamountspaidat thehealthcentersandusethisinformationtounderstandhowthebribesaffecttheallocationofhealthservices.Wecanalso use it as an outcome measure to study the effectiveness of anticorruption policies ingovernment health centers.However, these types ofmeasures are limited if individuals areunderreporting bribes, and particularly if this underreporting is biased by corruption levels.Moreover,mostofthetime,thesemeasuresareoftenlimitedtopettycorruption,becauseitisdifficulttoaskindividualsaboutthelargerbribesthattheymayhavepaid.Indeed,inmanyofthesecases,thereportsareassumedtobereliablepreciselybecausetheagentsdonotknowhowmuchtheyshouldhavepaid,andthereforedonotseethemselvesaspayingbribes.Itisalsoclearthatpeoplemightbemorewillingtorevealbribesthattheypaidinsettingswherethegoodtheyreceiveisabundant(sothattheyarenotdisplacinganyoneelsebypayingthebribe).

Thesecondmethodistheuseofphysicalauditsofgovernmentalprocesses.Forexample,Chaudhuryetal.(2006)conductedamulticountrystudyofteacherandhealthworkerabsence,where they performed spot checks to determinewhether bureaucratswere showingup forwork.25Similarly,Bertrandetal.(2007)followedindividualsthroughtheprocessofobtainingadriver’slicenseinIndiaandrecordedallextra-legalpaymentsmadeandtherulesthatwerebrokeninexchangeforthesepayments.BarronandOlken(2007)designedastudyinwhichsurveyorsaccompaniedtruckdriverson304tripsalongtheirregularroutesintwoIndonesianprovinces.Thesurveyorsobservedtheillegalpaymentsthetruckdriversmadetothetrafficpolice,militaryofficers,andattendantsatweighingstations.

Oneofthekeychallengestotheauditstudiesiswhethertheobservedoutcomesactuallyreflect corruption rather than some less intentional form of bureaucratic ineffectiveness,becauseoftenthereisnosmokinggun(bribeovertlypaid,jobleftentirelyunattended,etc.).Forexample,Bertrandetal.(2007)findthatthereisamisallocationoflicenses—peoplewhocannotdrive are able toobtain them.Could this bedue to anoverworkedbureaucratwhodoes not have time to screen license candidates or due to an incompetent onewho cannotdistinguish between good and bad drivers? To understand this issue, Bertrand et al. collectdetailedquantitativeandqualitativedataonhowthebureaucratsbehaveduringthelicensingprocess.Theydocumentextremebehaviors (e.g., simplyneveradministeringadriving test),whichwouldbehardtolabelas“incompetence.”Similarly,Dufloetal.(2012)measureteacherabsenteeisminruralIndiausingauditmethods.Doesthefactthatteachersoftendonotcometoschoolimplythattheyareconsciouslybreakingtherulesforprivategain?Orarelivesoftheseteacherssodifficultthattheyjustcannotmakeittoschooloftenenough,despitetryingas hard as they can? The research design provides information that allows the authors to


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answerthesequestions.Specifically,theyevaluateaprogramthatmonitorstheteachersandprovides incentives to them based on their attendance. They find that teachers are veryresponsivetotheincentives.Thatteachersrespondtotheincentivessostronglyimpliesthattheteacherswerepreviouslyignoringtherulesandwerenotincapableofattending.

Werefertothethirdtechniqueas“cross-checking.”Theideabehinditistocompareofficialrecordsofsomeoutcomewithanindependentlycollectedmeasureofthesameoutcome.Oneexample of cross-checking is to comparehowmuchmoneywas released to thebureaucratwithhowmuchtheultimatebeneficiariesofthefundingreporthavereceived.Forexample,Reinikka and Svensson (2005) compare data from records on central governmentdisbursements and a public expenditure tracking survey tomeasure dissipation in a schoolcapitation grant in Uganda. They find that the average school received only about 20% ofcentralgovernmentspendingontheprogram.FismanandWei(2004)compareHongKong’sreportedexportstoChinaattheproductlevelwithChina’sreportedimportsfromHongKongtounderstandtheextentof taxevasion.Anotherwaytoconductacross-checkwouldbetocollectrecordsfromthebureaucratdocumentinghowthegovernmentresourceswerespentinachievinga taskand thencompare themwithanobjectivemeasureofhowmuch it shouldhavecosttoconductthetask.Thedifferencebetweenthetwomeasuresis,then,theestimateof how much was stolen. Olken (2007) uses this method. He calculates corruption in thecontextofroadprojectsbycomparingtheactualexpendituresreportedwithanindependentmeasureofwhat it shouldhavecost tobuildaroadof thatparticularquality.Toobtain theindependentmeasure,hesampledeachroadtodeterminethematerialsand laborused,andthen used local prices to cost these elements. He finds that, on average, about 24% ofexpendituresacrosstheprojectvillagesweremissing.26

Aswithanyothermethod,thisonehasbothstrengthsandlimitations.Itsinnovationliesinthefactthatitcreativelyallowsthemeasurementofdissipatedgovernmentresourceswithoutaskingtheactorsinvolvediftheyhavepaidorreceivedanactualbribe,reducingthechanceofunder- ormisreporting.Thus, it often allowsus tomovepast petty corruptionandperhapslookat larger scale corruption.However, it isdifficult tounderstandwhether thedissipatedrecoursesareactuallycorruptionorsimplymismeasurement in the indicatorsoreven justasignof bureaucrat incompetence. For example, inOlken (2007), it remains possible (thoughunlikely) that roadquality ismismeasuredor that the bureaucrats arenot good at buildingroads. It is possible (though again unlikely) that the missing resources indicate that thebureaucrats are trying to reallocate funds to better uses. For example, in Reinikka andSvensson (2005), it is possible (although again unlikely) that the resources that should havegone to the school capitation programwere actually spent on services that the communitydeemedmoreimportantanddidnotendupinthepocketsofgovernmentofficials.Wouldthisresulthavenecessarilybeenbad?

Oneway to get around these concerns is to look for correlations (motivated by theory)between the extent of dissipation and some other variable. For example, to show that thedifferencesinreportedshipmentsiscorruptionandnotjustmismeasurementintheshipments,FismanandWei(2004:471)documentthatthedifferencesare“negativelycorrelatedwithtaxrates on closely related products, suggesting that evasion takes place partly throughmisclassificationof importsfromhigher-taxedcategoriesto lower-taxedones, inadditionto


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underreportingthevalueofimports.”27

In addition to thesemethods recentlyused in the literature, there are several innovativemethodsbeingexploredincurrentstudies.Althoughsomeoftheworkisnotyetpublished,such methods will surely contribute to the tools available for studying corruption. Forexample, Banerjee and Pande (2009) attempt to use second-hand data onwhich politicianshave gotten rich since they entered politics to identify those who have profited fromcorruption.28 They find that this measure correlates strongly with other, more direct(perceptual), measures of corruption (e.g., the answer to the question “do you think thepolitician used his office for private gain?”). Cai et al. (2009) use predictions from auctiontheory to argue that certain types of land auctions inChina are used to promote collusionbetweentheauctioneerandtheparticipants,fortheirmutualbenefit.

All thesemethodspickup thedirectcorrelatesofcorruption, suchasbribesandabsencefrom work, rather than its more indirect ramifications. In some cases, such as teacherabsenteeism, thedirectconsequencemaybe themost important.However, thepointofourframework is toargue that inmanysituations, thebribemay justbe the tipof the iceberg,withthemoreseriousrepercussionsshowingupintermsofmisallocationandredtape.Thenextsectiondiscussesanexampleofempiricalresearchthattriestocapturethebureaucrat’sentiredecisionprocessanditsvariousramifications.

5.UnderstandingtheStructureofCorruptionMostempiricalresearchhasbeenbasedonmeasuringtheextentofbriberyorshirkingandonhowincentivesaffectthesebehaviors.Bertrandetal.(2007)differsfrommuchoftheempiricalresearchby focusingon the entire resourceallocationproblem facedby thebureaucrat andtherefore lookingbeyondbribe taking as themeasure ofwelfare.Thebasic strategyof thepaper is to experimentally vary the underlying types a bureaucrat faces and use thebureaucrat’sresponsestoinfertheirchosenallocativemechanism.

Specifically, Bertrand et al. (2007) compare three randomly chosen groups of licensecandidates.Thefirstgroupwastoldtoobtainalicenseasusual,thesecondgroupwasgivenalargeincentivetoobtainthelicenseintheminimumlegaltimeallowed(30days),andathirdgroupwasofferedfreedrivinglessons.Inourmodel,thesecondgrouprepresentsasituationwherehandlhavebothincreasedbythesameamount.Thethirdgrouprepresentsasituationwheresomeofthosewhowerelowtypesbecomehightypes.

Thedriver’slicensecasecorrespondstoCaseIV(seeSection3.3.3).Toreducethenumberof possible cases, assume thatyH =h < l = yL (which, as always, is interpreted as the case

whereasubstantialfractionofLtypesarewillingandabletopaymorethanalargefractionofHtypesare).Moreover,assumeN<1butL<0.

Weassumethatthebureaucratfacespeopledrawnfromthisaltereddistributionoftypes.However, because he does not know the environment has changed, both he and thegovernmentusemechanismsthatmatchthepriortypedistribution.Ofcourse,consumerscanchangetheirbehaviorasaresultofthetreatment:subjectswhoaremoredesirousofalicensecan offer higher bribes, for example. In principle, this changemay allow the bureaucrat to


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learnoftheexperimentandadjusthisoverallstrategy.Inpractice,weassumethatthesamplesinvolvedaretoosmallforthebureaucrattochangehisbehavior.Ineffect,ininterpretingthisexperiment,weassumethatitchangespeople’stypesratherthanmodifyingthebureaucrat’santicipatedtypedistribution.

ItiseasytocheckthatinCaseIV,anequalincreaseinhandl,withoutanychangeintherules, will have several different effects. L types will now want to apply even if they areassigned to abureaucratwho is beinghonest (i.e., a bureaucratwhose cost of breaking therulesistoohighcomparedtothebenefitfrombreakingtherules).Therefore,thefractionofthose who apply to an honest bureaucrat and end up getting a license should decrease.However, just becausemanymoreL types apply,manymorewill (just by chance) end uppassing,and theaveragequalityof thosewhoobtaina licensewoulddecline.However, thegainsfrombeingcorruptwouldalsobehigher,whichwillreducethefractionofbureaucratswhochoosetobehonest.

Thecorruptbureaucrats(i.e.,theoneswhoopttobreaktherules),ofwhomtherearenowmore, will raise their prices. The fraction of L types getting through, conditional on beingallocatedtoacorruptbureaucrat,shouldnotchange,butbecausetherearenowmorecorruptbureaucrats, the average quality of driving among those who get a license should decline.Moreover, because there are nowmore corrupt bureaucrats, the average amount of testingshouldalsodecrease.

In contrast, converting some of the high types in the population (the second treatmentgroup)tolowtypesshouldimprovethefractionofdriverswhoobtainalicensewhentheyareallocated to an honest bureaucrat, aswell as the average quality of licensed drivers. Thosewhoareallocatedtoacorruptpersonshouldreceivemoreor less thesametreatment,withthelicensesgoingtothehighestbiddersandperhapssomeredtapeexperiencedbythosewhowant topay less (H types) todiscourage thosewhoarewilling topaymore fromclaimingotherwise.

Empirically, individualswhowereoffered the incentivewere 42percentagepointsmorelikely to obtain it in 32days or fewer.However, theypaid about 50%more to obtain theirlicenses, and theyweremore likely tobreaka ruleduring theprocess (e.g., theywere13%morelikelytonottakeadrivingtest).Intheend,theseextrapaymentstranslatedtoagreaternumberofbaddriversontheroad:thoseofferedtheincentivewere18%morelikelytoobtainalicensedespitenotknowinghowtooperateacar.Theseresultsareentirelyconsistentwiththeoreticalpredictionsdiscussedabove,aslongasthereareenoughbureaucratsaroundwhohave a relatively low cost of breaking the rules. In particular, although the decline in thequality of driving among those who have a license would happen both with honest andcorruptbureaucrats,thereductionintestingcanonlyoccurinourmodelifthebureaucratiscorrupt.

Itisworthpointingoutthatonewouldnotobservethesamepatternifthebureaucratsdidknowthat thedistributionofhand lhas shifted. In this case, ifhand l go up by the sameamount, both types would now want to be tested when they encountered an honestbureaucrat.Iftheyinsteaddealwithacorruptperson,bothtypesjustpayandgetthelicensewithout being tested. The average price would not change, and the fraction being tested


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wouldgoup.However,thequalityofdrivingamongthosewhogetalicensewoulddecline,becausetheLtypeswhodealwiththehonestbureaucratnowwanttobetested.Thisclearlydoesnotfitthefactsaboutpriceandtesting.29

The results of the driving-lessons treatment are also broadly consistentwith the theory.Thoseinthisgrouparetestedmoreoftenandaremorelikelytohaveobtainedalicensebasedonpassingthetest.Thislastfact,inparticular,suggeststhattherearesomehonestbureaucrats.Theyalsopaylessforthelicense,thoughmuchmorethantheyshouldhavelegally.Thisisapredictionofourmodel,butonlybecauseweassumed(forconvenience)thatallHtypeshavea lowerwillingness topay thanallL types.Amoreplausible argument is that theH typesactuallyhaveanincentivetoshoparound(i.e.,gotomultiplebureaucratsuntiltheyfindonewhoishonest).Infact,Bertrandetal.(2007)didobserveshoppingaroundinthedata,anditisthereforeaplausibleexplanationforwhytheincreaseinthefractionofH typesreduces theaverageamountpaid.

Betrand et al. (2007) also provide evidence that there is a lot of red tape (i.e., pointlesstesting).Theyshowthatofthoseexperimentparticipants,who,atleastinitially,triedtofollowthe rules (i.e., get tested, not pay bribes, etc.), there is a higher success rate among thoseindividuals found to be unqualified to drive based on the independent test (74% comparedwith62%).Inotherwords,theprobabilityofobtainingalicenseislessthan1evenforthosewho can drive, and it is not any higher for them than for those who cannot drive. Thus,passing the test is uncorrelated (at best) with driving ability. The testing serves no directscreeningpurpose.

Both these features—a probability of winning less than 1 and pointless testing—areconsistentwithCaseIVinthescenariowhereslotsareabundant.However,toinducepointlesstesting, it is importantthatyH<h;otherwise, thepricemight justaswellberaisedup toh.Thisdivergencebetween theability topayand thewillingness topay seems implausible inthis context.The amountofmoney involved (about $25) is not large for thepoor inDelhi,whichiswheretheexperimentwascarriedout.

Amoreplausiblestorymightbethattheapplicantsdonotfullyunderstandtherulesofthegameandthereforethinkthatit iseasiertousetheofficialchannelthanitactuallyis,whilethe bureaucrat is not in a position to directly explain to them how things really work;therefore sheuses the fruitless testing to signal to the applicants that theyneed to readjusttheir expectations. This storywould be consistentwith the fact that no one directly pays abribe to the bureaucrat. Thosewhowant to use bribery go to an agentwho facilitates thetransaction. When someone directly approaches a corrupt bureaucrat through the officialroute,thebureaucratdoesnotaskforabribeandinsteadgoesthroughthemotionsofwhatsheissupposedtodo,whilepresumablytryingtomakesurethattheapplicantsubsequentlydealsthroughanagent.

Thesetypeofempiricalresultsareanintriguingcomplementtothetheoreticalframeworkwehavelaidout.Theyfocusattentionontheallocativeoutcomesandnotjustonthebribes.Theyfocusonthedetailsoftestingandnotonlyonthetransfersmade.Inshort,theyillustratethebroaderviewoncorruptionthatweadvocateinthischapter.


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6.CombatingCorruptionThere is a large and growing empirical literature that studies the effect of efforts to fightcorruption.Forexample,FismanandMiguel (2007) find thatan increase inpunishments forparkingviolationsinNewYorkCityreducedtheviolationsamongthesetofdiplomatsmostlikelytoviolatetherules.Usingexperimentaltechniques,Olken(2007)findsthattheftinroadprojects isgreatlyreducedbyraisingtheprobabilityofbeingcaught.Banerjeeetal. (2008a)andDufloetal.(2012)findthatstrengtheningincentivesreducesabsenteeism.Usinganaturalexperiment inBuenosAireshospitals,DiTella andSchargrodsky (2003) findeffectsofbothmorestringentmonitoringandhigherwagesonprocurementprices.

Severalmorerecentpapersonthistopichavealsotriedtogoastepfurtherandunderstandwhether a reduction in corruption through monitoring and incentives improves the finalallocation of services. In the case of theDi Tella and Schargrodsky (2003) study, less bribetakingmeansbetterprocurementprices,whichistheoutcomeofinterest.Olken(2007)looksattheeffectofauditingnotonlyontheftbutalsoonthequalityoftheroadsthatwerebuilt.Duflo et al. (2012) study whether incentives can create distortions stemming frommultitasking.Inotherwords,theyareconcernedthattocompletethetaskasspecifiedbytheincentives,theagentreduceshiseffortalongotherdimensions.Specifically,theyaskwhetherproviding incentives for teachers to attend schoolwill cause the teachers to compensate byteachingless.Toanswerthisquestion,theymeasurenotonlyteacherattendanceasthefinaloutcomebutalsothelearninglevelsofthechildren.Theyfindthatthemultitaskingproblemiscertainlynotlargeenoughtooutweighthebenefitsofbetterincentives.

6.1.InstitutionalStructuresforMonitoring

Corruption exists because there are not enough monitoring and incentives to eliminate it.Whatthendeterminestheextentofmonitoringandincentives?

One challenge of looking at this issue empirically is essentially methodological. Whatshouldweassumeabouttheextenttowhichtheserulesaretheproductofoptimizationbythegovernment?Governmentsmaymakerulestocombatmalfeasancebygovernmentofficials,buthowwelldotheyunderstandtheconsequencesoftheserulesforcorruption?

There are two possible approaches to answering these questions. One iswhatmight becalled the “political economy approach.” This approach is taken in the theory section here(Section3).Weassumesomepreferencesforthegovernmentandfigureouthowtherulesandthe nature and extent of corruption should vary as a function of the underlying economicenvironment if thegovernmentwereoptimizingbasedon thosepreferences.Wecould thenlook for evidence for the comparative static implications of thatmodel and jointly test themodelandourassumptionaboutwhatisbeingoptimized.

Thealternativeistoassumethattheforcesofpoliticaleconomy,althoughimportant,leavea significantamountundetermined, andasa result, changes in rules canoftenariseaspureorganizational innovations, without changes in the fundamentals. This approach leadsnaturallytoanexperimentalapproachtostudyingtheeffectsoftherules.

Banerjee et al. (2001) implement a version of the first approach in the context of the


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governance of localized sugar cooperatives. They assume that the cooperativemaximizes aweightedaverageoftheprofitsofthevariousprincipalsofthesecooperatives—thedifferenttypes ofmember farmerswhogrow the cane that the cooperative turns into sugar—takingintoaccount thedesireof themanagementof thecooperative to siphonoff asmuchof theprofitsaspossible.Banerjeeetal.(2001)thengenerateasetofcomparativestaticspredictionsthatmapthepricingofcaneandtheproductivityofthecooperativeontotheunderlyingmixof farmers in the cooperative. These implications are then tested and seem to be broadlyconfirmed.

However, corruption in these cooperatives is essentially private sector corruption,embodied primarily by the underpricing of cane.Wehave yet to come across a paper thatcombines this political economy approach with the more complex manifestations ofcorruptionidentifiedinSection3.

More importantly, in many instances, theories of political economy are simply tooincomplete tobeusefulguides towhatrulesareactuallychosen.Theobjectiveofaspecificgovernmentataspecificpointintimeissomecomplexproductofitslong-termgoalsanditsshort-term compulsions. Moreover, the way it chooses rules must take into account thecompulsionsofallfuturegovernments.Althoughthereisaninterestingandgrowingliteratureonthissubject,itisnotclearthatitisreadytobetakentothedata.

It is also not clear how much governments understand about the consequences of thevarious policy choices they make or about the policy options available to them. A moreevolutionary approach to policy change,where changes happen because political actors aretryingtosolvesomelocalproblembutthesolutionsoftenhaveunanticipatedandoftenglobalconsequences,maybemoredescriptivelyaccurate.CertainlythisapproachfitsbetterwiththekindsofstoriesthatonehearsabouthowchangecametoChina.

Anadvantageof this secondapproach is that it permitsus to thinkofpolicy changes asorganizational innovations that are therefore at least initially exogenous in a way thattechnologicalinnovationsareusuallythoughtofasbeingexogenous.Thatis,theassumptionisthattheneedtosolveproblemsisaproductofvariousforcesofsociety,buttheadoptionofaparticularsolutionataparticularpoint intimeis lessso.30Theapproachalsomakes itclearthatgovernmentsmightchoosebadrules(rulesthatgoagainstitsownobjectives),becauseitdoesnotunderstandtheconsequencesofitschoices.

Severalrecentempiricalexercisesstartfromthispointofview.Forexample,Besleyetal.(2005) find that, inSouth India, thereexistsarelationshipbetweenholdingvillagemeetings(i.e.,more community participation in the process) and better allocations of BelowPovertyLinecards,whichprovideprivilegedaccess tosubsidiesandgovernmentservices.BjorkmanandSvensson(2009)studydecentralizationinanexperimentalcontext.Ratherthanimposingall centralized rules on health centers, community meetings are held to decide the mostimportantrulesthathealthcentersshouldfollowandthemechanismsforthecommunitytomonitor thehealthcenters.They findhuge impacts: infantmortality rateswerecutbyone-third.However,Banerjee et al. (2008b) evaluate a similar decentralizationprogram in Indiaandfindthatitperformsnobetterthanthecivilservice–basedsystemofmonitoringteachers.

Itisdifficulttomakeanythingofthesevastlydifferentempiricalfindings,giventhatwedonot have a particularly good theory of how decentralization affects corruption and the


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distortionsassociatedwithcorruption.31Howdoesdecentralizationchangethekindsofrulesthat are optimal and the way in which they are violated? How does the exact nature ofdecentralizationfactorintoallthis?

Asitis,thepresumptionbehindtheempiricalliteratureisthatdecentralizationisashiftofcontrol rights into thehandsof thosewhohavemore local information.Thebasicnotion isthat the community now has more information and therefore can limit the extent ofmalfeasance by the bureaucrat. We do see some evidence that the easy availability ofinformationmatters.Inthedriver’slicenseexperiment,Bertrandetal.(2007)reportthatthereare two obstacles that bribes cannot get around: one is the requirement of showing someproofofaddressandtheotheristherequirementofwaitingatleast30daysaftermakingtheinitialapplicationforalearner’spermit.Neitheroftheseseemsasimportantasbeingabletodrive,especiallyinIndia,wherethedriver’slicenseisnotalwaysacceptedasanidentification.However,violationsoftheserulesareeasytoobserve,whereastheinabilitytodriveproperlyis something that requires another test to verify. Therefore, these are the rules that areenforced.

However, the answer to the question ofwhat rules are violated inwhatwaymust alsodependonwhoexerciseswhichtypeofcontrolrightsandwhat informationreacheswhom,which all turns on the exactmodel of decentralization adopted.More generally, theoreticalwork mapping the effects of alternative organizational forms on the choice of rules andcorruptionoutcomesmustbeahighpriorityifthisliteratureistomakeprogress.

7.ConclusionWhereshouldtheliteraturegonext?Wehavealreadydiscussedanumberofthegapsintheliterature. In Section 6, we discussed the need to more tightly model learning about thesystem.Here,wediscussotherimportantgaps.

7.1.CorruptionandCompetition

Thinking about organizational forms naturally leads to the role of competition in reducingcorruption,asemphasizedbyRose-Ackerman(1978).Thewaywemodeledcorruptiontakesas given the idea that the assignment of the applicants to the bureaucrats is random. Thiseffectivelyplacestheapplicantsandthebureaucratinabilateralmonopolysetting.However,the nature of competition among bureaucrats ought to be a policy choice governed by thenatureoftheunderlyingincentiveproblems.Thisareaofstudyneedsfurtherexploration.

Inparticular,competitionisnotalwaysaplus.AspointedoutbyShleiferandVishny(1994),competition among corrupt distinct and uncoordinated authorities, each of whom has thepowertoblocktheapplication,mightbeworsethanasinglemonopolisticrentseeker.BarronandOlken (2007) document this phenomenon using a unique dataset that they collected inIndonesia of the bribes paid by truck drivers at road blocks. Reduction in the number ofcheckpointsalongtheroadreducesthetotalamountofbribescollectedfromthem.Credibleevidenceonthesalutaryeffectsofcompetitionhassofarbeenhardtofind,thoughnodoubttherightsettingtolookforthemwillemergesoon.


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7.2.ImplicationsofIllegalityandNontransparency

One reason that corrupt bureaucrats find it hard to coordinate with one another is thatcorruption is illegal. This essential nontransparency has several important implications thatdeservefurtherstudy.First,iftheapplicantsfortheslotsdifferintheirabilitytomakeillegaldeals foreither intrinsicorextrinsicreasons, thentheplayingfield isno longer level,whichintroducesimportantdistortions.Thisconcernisnotmerelytheoretical.Manycountrieshavelawsthatforbidtheirfirmstopaybribesinforeigncountries,whichcouldpotentiallyactasaconstraintonforeigninvestmentincountrieswithhighlevelsofcorruption(seeHines1995).

Another fallout of this nontransparency thatwe already noted is the reliance on agentswhofacilitatebribetaking(seeRoseen1984;Bertrandetal.2007,2008).Thetheoryonhowthe use of agents alters the nature of corruption is yet to be developed. Barron andOlken(2007) provide an interesting insight into this relationship. They observe that in Indonesia,truckers can either pay a bribe at every checkpost or pay a single bribe to an agent at thestartingcity.However,thecontractwiththeagenttendstobeverysimple—theamountofthesinglebribedoesnotdependontheloadcarriedbythetruck—probablybecauseofthesamelackoftransparency.Thus,onlythemostoverloadedtruckspaythefixedbribe,andtheshapeofthetotalbribepaidasafunctionofthetruck’sloadisconcave,whereastheorysuggeststhattheoptimalpenaltyfunctionoughttobeconvex.

A third issue is that many drivers who try to get a license without paying an agentprobablydonotknowtherulesofthegame.Thishappensbecausecorruptionismeanttobesecret.Inotherwords,understandingtheprocessbywhichtherealrulesofthegamebecome(orfailtobecome)commonknowledgebetweenthebureaucratandtheapplicantsshouldbeanintegralpartofthestudyofcorruption.

Bertrandetal.(2007)actuallygatherdataaboutwhatindividualswhoaretryingtoobtainadriver’s licenseknowabout the licensingprocess.They find thatnotmuch is known, andmore surprisingly,many applicants believe that the official process ismore onerous than itactually is. They also found in their qualitativework that discovering the actual rules wassurprisinglydifficult,giventhattheychangeperiodically.

These observations lead Bertrand et al. (2007) to speculate on whether the bureaucratsdeliberatelytrytomaketherulesmorecomplicatedthantheyshouldbetoextractmore inrents.Atanassova et al. (2008) find that individualswho are supposed to receive subsidizedallocations of foodgrains in India are misinformed about their exact entitlements, and thequalitativeevidenceinthiscasesuggeststhattheshopkeeperoftenmanufactures“rules”thatincreasethescopeforhiscorruption,suchasthatallgrainmustbeboughtononeoftwodays.

Thinkingaboutthisissueleadsustoaninterestingtheoreticalpossibility.Isitpossiblethatthegovernment’sattemptstochangetherules,perhapstofightcorruption,generatesomuchconfusionamongthecitizensthatcorruptionactuallyincreases?

7.3.LearningamongBureaucrats


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Theemphasisonlearningbringsupanotherimportantissue.Althoughmuchoftheworkinthefieldhasfocusedoninnovationsinfightingcorruption,therehasbeenlittlefocusontheinnovationsincorruption.Achangeinpolicyand/orinstitutionsmayreducetheprevalenceofcorruption to startwith, but over time, thebureaucratmay learnhow to adapt to thenewpolicy or institutions. For example, Camacho and Conover (2011) provide evidence thatindividuals were better able to game the eligibility rules for social welfare programs inColombiaasrulesforeligibilitybecamebetterknownovertime.Moregenerally,howmuchof the knowledge regarding how to conduct corruption is general knowledge, versusknowledgeaboutaspecificinstitution?

7.4.NormsofCorruption

Theideathattherulesmaybeimportantforestablishingasimplenormthatthecourtscaneasilyinterpretsuggestsafurtherlineofinquiry.Perhapstherulesthatthegovernmentmakesfor bureaucrats have a signaling role. The bureaucrat or the citizen uses them to infer thesociety’s preferences and therefore to decide what they should and should not do. If thegovernment formally allows its bureaucrats to extort money from its citizens, the citizensmighttakethisasasignalthatthemoralstandardsofsocietyarelow,andthereforecitizensfeelcomfortableaboutextortingothers.Thisideacouldexplainwhygovernmentscontinuetohaverulesontheirbooksthatareviolatedallthetime.

However,agovernmentthathasrulesonthebooksbutdoesnotmanagetoenforcethemisalsosignalingsomethingaboutitsviewofrulesandrule-governedbehaviorthatmightspilloverintootherwalksoflife.Forthisreasonandothers,corruptionmayhaveadirectsocialcost,whichissomethingourmodeldoesnottakeintoaccount.

7.5.TheSocialPsychologyofCorruption

Tofullyunderstandhowcorruption(orlackofcorruption)becomesthenorm,thereisaneedtotrytounderstandthepsychologyofwhenandwherepeoplefeelmoreorlesscomfortableaboutengagingincorruption.Forexample,atendencytotrytolegitimizecorruptionisoftenobserved. Itcould takethe formof“excusemaking” (i.e., thebureaucratnotdirectlyaskingforabribebutinsteaddiscussingthecostsofhertimeinprovidingaservicetoacitizen).Oralternatively,thecitizenmaysuggestmakingapaymentinkind,ratherthanamonetarybribe,tomakethebureaucratfeelasifsheweresimplyacceptingagiftfromahappycitizenratherthanengaginginanillegalact.

Theconceptof legitimizationmaybeapowerfulpartofourunderstandingwhy there isnotasmuchcorruptionintheworldastherecouldbe.Forinstance,eveninthemostcorruptcountries,empiricalantidotessuggestthatbureaucratswilloftenaskforabribetobreakarulethatimpedesagivencitizenbutwillnotthreatentopunishhimfornoreason.Forexample,trafficpolicemenoftenaskforabribe ifacitizenhascommittedaviolation.However, theywillnotnecessarilyaskforabribeifthepersonhasdonenothingwrong,andyetitisnotclearthattheenforcementinthesetwocasesisverydifferent.Locatingthestudyofcorruptioninthebroadercontextofhowpeoplerelatetooneanotherandtothestatemaybeimportantin


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gettingahandleonwhycorruptionexistsinsomesettingsbutnotinothers.

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1.Summarizingaliteratureaslargeandmultidisciplinaryascorruptionposesuniquechallenges.Inthischapter,wehaveerred on the side of being forward looking, trying to paint a picture ofwhere this literature is headed. Thoughwe haveaimedtocoverall importantexistingliterature,somegapsareanunfortunatenecessitytokeepthischaptermanageableinlength:ourapologiestoauthorswhoseworkwecouldnotcoverinmuchdetail.

2.Quiteoften,weseethesameformsofcorruptioninthenonprofitsector,whereasocialgoodisbeingprovided,andtheprivateandsocialvaluemaynotnecessarilycoincide.Themodelspresented in thischapterwouldnaturallyextendto thenonprofitsector.

3.Foradeeperdiscussionofpoliticalcorruption,seePande(2007).4.Ofcourse,cultureisdiscussedexplainingcorruption,simplynotwhendefiningit.5.Werecognizethattheactualmechanismusedwilloftenbeverydifferentfromthedirectmechanism.Wediscusssome

oftheissuesthisraisesinSection3.6.6.Thisformulationisquitespecific,andthecostofviolatingtherulesisindependentoftheextentofviolation.7.Weassumethatwhenindifferent,thebureaucratchooseswhatthegovernmentwants.8.Itisalsoworthmakingclearthattheassumptionofwelfaremaximization,althoughstandard,isquiteparticular.The

government could care, for example, about the distribution of welfare between the bureaucrats and the potentialbeneficiaries. In this case the government may prefer an inefficient outcome, because it achieves distributional outcomesbetterandmaythereforecreateamorecomplexsetoftrade-offsthanarepermittedhere.WereturntothisissueinSection3.6.

9. Another example that exploits a different rigidity in labormarkets is the following. There is a womanwho is notallowedbyherfamilytowork,butsheiswillingtowalk3mileseverydaytomakesurethatherchildgetsaneducation.Herabilitytopay(assumethattherestofthefamilydoesnotcareabouteducation)isclearlylessthanherwillingnesstopay.

10.Thatwehaveonlyfourcases isanartifactof theassumptionthatallH typesare identical intheirwillingnessandabilitytopayandlikewiseforLtypes.However,thebasicdistinctionwearetryingtomakehereisbetweenthecasewhereHtypesarewillingand/orabletopaymoreandthecasewheretheymaynotbe(capturedbyh≤landyH≤yL).Thesituation

wherealargefractionofL typesarewillingand/orabletopaymorethana largefractionofH types isqualitativelyverysimilartothecasewhereallLtypesareable/willingtopaymorethanallHtypes.

11.AslongasyL<l,thisconditionisconsistentwiththecondition imposedabove.

12.Itistruethatinourmodelwewouldgetthesameresultwitheitheraruleontestingoracapontheprice,butthisref lectsourextremeassumptionthatbreakingoneruleisthesameasbreakingthemall.Anepsilonextracostofbreakingtworulesinsteadofonewouldmakeitstrictlyoptimaltohavebothrules.

13.Inourmodel,becausethebureaucratalwayspaysthegovernmentfortheslots,thegovernmentactuallyknowshowmanyslotshehasusedandthereforeshouldabletocontractonπx.However,itiseasytothinkofanextensionofthemodel

toastateoftheworldwherethedemandforslotsislowerandthegovernmentdoesnotobservethisstate.14.Thisonlyworksifyishighenough.Otherwise,pLmighthavetobenegative.

15.Onceagainweassumethatthebureaucrat(atleastweakly)preferstobreakoneruleratherthantwo.16.Forexamples,seeLaffontandTirole(1993).17.Weassumethatasolutionwith ≥0exists,whichistruewhenl−hisnottoolarge.18.Anegativecorrelationwouldalsoresultifwewerepreparedtogooutsidetheworldofthemodelandassumethatthe


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http://www.transparency.org/policy_research/surveys_indices/cpi

government has other unmodeled reasons for setting a price cap that do not have to do with promoting efficiency. Forexample, thegovernmentmaybesensitive todistributionalor ideologicalconcerns—governmentbureaucrats shouldnotbeseenasbecomingtoorich,evenifthatiswhatefficiencydemands.Ortheremaybesomepoliticalorsymbolicargumentformakingallpublicgoodsfreeorverycheap.ThismightleadthegovernmenttosetthepricecapbelowyL.Taketheextreme

casewherethegoodissupposedtobefree(thecapiszero).Inthiscase,thegovernmentwouldactuallywantthebureaucratto test thosewho apply for the slots (because the pricemechanismwill not do any screening).Here a bureaucratwho iscorruptmightactuallydosomegood:allheneedstodoistoraisethepricefortheHtypestoyH+εandscraptheredtape,

andsocialwelfarewouldunambiguouslygoup.Insuchcases,bribetakingwouldbeanantidotetoredtape,andtheywouldmove in opposite directions. This is the old idea that corruption greases thewheels and increases efficiency (Huntington1968),butnotethatitcanonlyhappenwhenthegovernmentisnotusingitschoiceofrulestomaximizewelfare.

19.Thereareexceptions.Forexample,Tran(2008)gathersacomprehensivesetofinternalbriberyrecordsfromafirminAsiatodocumentthecostofbribepaymentsovertime.

20.Thesedatasetsarealsocalledthe“BusinessInternationalIndicators.”21.Papersthatuseperception-basedmeasuresofcorruptionincross-countryregressionsincludeMauro(1995),Knackand

Keefer(1995),LaPortaetal.(1999),Treisman(2000),Adseraetal.(2003),FismanandGatti(2002),FredrikssonandSvensson(2003),RauchandEvans(2000),andPerssonetal.(2003).

22.Svensson(2005)providesathoroughdescriptionofthedifferencesamongthemostcommoncross-countryindicatorsofcorruption.

23.Forexample,“Manybusinesspeoplehavetoldusthatfirmsareoftenrequiredtomakeinformalpaymentstopublicofficials todealwith customs, taxes, licenses, regulations, and services, etc.Canyou estimatewhat a firm inyour line ofbusinessandsimilarsizeandcharacteristicstypicallypayseachyear?”(Svensson2003:213).

24.Mocan (2008) also uses the International Crime Victims Surveys to determinewhat characteristicswere associatedwithgreatercorruption.

25.OthersuchstudiesincludeDufloetal.(2012),whomeasureteacherabsence,andBanerjeeetal.(2008a),whomeasureabsenteeismamongmedicalproviders.

26.Otherexamplesofcross-checkinginthedevelopingworldincludetheHsiehandMoretti (2006)estimateofbribesinIraq’sFoodforOilProgram;Olken(2006)andAtanassovaetal.(2008)measuretheftinfooddistributionprogramsusingthesamemethod,andDiTellaandSchargrodsky(2003)useittomeasurecorruptioninhospitalprocurements.

27.Duggan andLevitt (2002) provide an interesting example of cross-checking in sumowrestling.Theybasically showthatawrestlerhasahigherprobabilityofwinningthanexpectedwhenthematchiskeytohisrank.Todistinguishmatchthrowingfromeffort,theyusetheoryasaguide:theeffectgoesawaywhenthereisgreatermediascrutiny,suggestingthatit is not effort.Moreover, thenext time the same twowrestlersmeet, the opponent ismore likely towin, suggesting thatthrowingfuturematchesisaformofthebribepaidforwinningakeymatch.Similarly,Antanassovaetal.(2008)cross-checkreceiptofaBPLcard(whichinIndiaidentifiessomeonetobepoorandallowsthemaccesstoasetofredistributiveprograms)againstactualincomelevels.Theycorrelatetheerrorratewithsuchfeaturesasthecasteoftherecipientandhisorherplaceincertainsocialnetworks,andtheyarguethatthecorrelationsarewhatasimpletheoryofcorruptionwouldpredict.

28. Di Tella andWeinschelbaum (2008) provide a theoretical framework for thinking about unexplainedwealth as anindicatorforcorruption.

29.However,ourassumptionthatbureaucratsarerandomlyassignedtoapplicantsplaysaveryimportantrolehere.Onealternativeassumptionwouldbethatapplicantscaneitherchooosetogothroughtheofficialsystemknowingthatanhonestbureaucratwillbeassignedtothemwithsomeprobability,butotherwisetheyendupdealingwithacorruptindividualwhowill always fail the applicant (because in the official channel there are no bribes, the corrupt bureaucrats find it at leastweakly optimal to fail everyone who comes through the system). Or applicants can choose to go through the unofficialchannel,whichguaranteesthattheypayabribeandobtainthelicense.Intheoriginalequilibriumofthisgame,itislikelythatallHtypeswilltrytheofficialchannel,whiletheLtypeswillchoosetheotherway.Inthisscenario,onlyH typesevertakethetestandfail.

Inthiscase,duringtheexperiment,Htypeswillshifttowardthecorruptrouteandthereforeenduppayingmore,testingless,andhavinganincreasedprobabilityofreceivingalicense.However,counterfactually,averagelicenseddriverqualitywillincrease,becausethefractionofHtypeswhofaildeclines.

30.Banerjee(2002)discussesmanyofthesemethodologicalissuesingreaterdetail.31.BardhanandMookherjee(2006)providearareexception.


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