NBER WORKING PAPER SERIES

MODEST, SECURE AND INFORMED:SUCCESSFUL DEVELOPMENT IN CONFLICT ZONES

Eli BermanJoseph Felter

Jacob N. ShapiroErin Troland

Working Paper 18674http://www.nber.org/papers/w18674

NATIONAL BUREAU OF ECONOMIC RESEARCH1050 Massachusetts Avenue

Cambridge, MA 02138January 2013

We thank Morris Breitbart, Mathilde Emeriau and L. Choon Wang for outstanding research assistanceand Aila Matanock for comments. Carrie Lee shared data on troop strength. We thank Michael Meesefor discussion at the ASSA session “Economics of National Security.” Seminar participants providedhelpful comments at the University of Warwick, the Department for International Development (London),LUISS University, the Einaudi Institute, IFPRI (Addis Ababa), UNOUA(Addis Ababa), Tel AvivUniversity, the Hebrew University (Jerusalem), and the University of Haifa. This material is basedupon research supported by the Air Force Office of Scientific Research (AFOSR) under Award No.FA9550-09-1-0314, and the Department of Homeland Security (DHS) under award 2010ST-061-RE0001through the Center for Risk and Economic Analysis of Terrorism Events (CREATE) at the Universityof Southern California. Any opinions, findings, and conclusions or recommendations expressed inthis publication are those of the authors and do not necessarily reflect those of any institution or ofthe National Bureau of Economic Research.

NBER working papers are circulated for discussion and comment purposes. They have not been peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies officialNBER publications.

© 2013 by Eli Berman, Joseph Felter, Jacob N. Shapiro, and Erin Troland. All rights reserved. Shortsections of text, not to exceed two paragraphs, may be quoted without explicit permission providedthat full credit, including © notice, is given to the source.

Modest, Secure and Informed: Successful Development in Conflict ZonesEli Berman, Joseph Felter, Jacob N. Shapiro, and Erin TrolandNBER Working Paper No. 18674January 2013JEL No. F52,F63,F68,H41,H56,K42,N45,O1,O17,Z1,Z12

ABSTRACT

Most interpretations of prevalent counterinsurgency theory imply that increasing government serviceswill reduce rebel violence. Empirically, however, development programs and economic activity sometimesyield increased violence. Using new panel data on development spending in Iraq, we show that violencereducing effects of aid are greater when (a) projects are small, (b) troop strength is high, and (c) professionaldevelopment expertise is available. These findings are consistent with a "hearts and minds" model,which predicts that violence reduction will result when projects are secure, valued by community members,and implementation is conditional on the behavior of non-combatants.

Eli BermanDepartment of Economics, 508University of California, San Diego9500 Gilman DriveLa Jolla, CA 92093and NBERelib@ucsd.edu

Joseph FelterCISAC and Hoover InstitutionStanford UniversityEncina Hall, C222Stanford CA 94305-6165felter@hoover.stanford.edu

Jacob N. ShapiroWoodrow Wilson School of Public Policyand International AffairsPrinceton UniversityRobertson HallPrinceton, NJ 08544-1013jns@princeton.edu

Erin TrolandUniversity of CaliforniaSan Diego Department of Economics9500 Gilman Drive #0508La Jolla, CA 92093-0508etroland@ucsd.edu

1

Theeconomicanalysisofcivilwarsandinsurgencieshasbecomeatopicofgrowing

interestinboththeacademicandpolicycommunities(BlattmanandMiguel2010;

WorldDevelopmentReport2011).Accordingtothe2011WorldDevelopment

Report(WDR),abillionandahalfpeopleliveincountriesaffectedbyfragility,

conflictorviolence,thelastbeingaseriousimpedimenttolong‐runeconomic

development(WDR2011).2Inthosecontexts,developmentprogramsarenowoften

taskednotonlywithimprovinghumanwelfareandenablingdevelopment,butalso

withhelpinglocalgovernmentsstabilizeinsecureenvironments(Berrebiand

Olmstead2011).3

Mostinterpretationsofprevailingcounterinsurgencytheoryimplythat

increasingthequantityorqualityofgovernmentserviceswillreduceviolence(U.S.

Army2007).Yettheoppositeeffectisalsoplausible:increasedeconomicactivityin

poorlycontrolledspacesmightraisethereturnstopredatoryviolence,therefore

motivatingevenmoreviolence(Hirshleifer1989;Collier2000).Bothanecdotaland

empiricalevidencearemixed.Suddendropsinaidflowscorrelatewithincrease

violenceacrosscountries(Nielsenet.al.2011)andcertainkindsofaidappeartobe

violencereducing(Berman,Shapiro,andFelter2011,hereafterBSF).Yet,exogenous

increasesineconomicactivityhavealsobeenshowntoleadtoincreasedviolence

againstcivilians(VandenEynde2012,Bermanet.al.2012)andevendevelopment

programssometimesyieldincreasedviolence,eitherbycreatingrentstocaptureor

bydisturbingthedistributionofpowerwithincommunities(Crost,Felter,and

Johnston2012a).Theliteraturehassofarnotexploredthequestionofoptimal

developmentprogramdesignforviolence‐reduction.Asstablegovernments

2Thelinkbetweenpropertyrights,security,andlong‐rungrowthineconomicsdatesbacktoatleastthepioneeringworkofDouglassNorth(1981).Svensson(1998),forexample,extendedNorth’sworkbymodelingtheeffectsofpoliticalinstabilityonpropertyrightsand,inturn,oninvestmentrates.Gradstein(2004)arguesthattheenforcementofpropertyrightsandeconomicgrowthareself‐reinforcing.GuillaumontandChauvet(20037‐10,16)findthataideffectivenessdeclineswithpoliticalinstability.Buildingonthisandrelatedresearch,theWDRhasemphasizedthecrucialroleofimprovedgovernanceinsecuringpeopleandpropertyifgrowthistobeachieved(WDR2001,1).3Forinstance,USAID’stoptenbenefitingcountriesin2012(obligations)wereAfghanistan($2.2B),Pakistan(0.9B),Jordan(0.5B),Ethiopia(0.4B),Haiti,KenyaandIraq(0.3Beach),DRCongo,UgandaandTanzania(0.2Beach)(USAID,2013).

2

graduateoutoftheclassofcountriesrequiringdevelopmentassistance,an

increasingshareofaidwillpredictablybespentinfragilestates,includingconflict

andpost‐conflictzones,sothisgapinknowledgeisdeeplyproblematic.

InthispaperweusedetailednewdataondevelopmentspendinginIraqto

beginclosingthatgap.Usingpaneldataondevelopmentassistanceandviolent

incidentscoveringthefirstfiveyearsoftheIraqwar,wecomparetheeffectsofU.S.

governmentspendingacrossseveraldevelopmentprograms,eachwithdifferent

characteristics.Weareguidedbythepredictionsofaninformation‐centric,or

“heartsandminds”theoryofcounterinsurgencyinlookingforcharacteristicsof

effectivedevelopmentprogramdesign.Weestimateinfirstdifferencesallowingfor

variouscontrolstoaccountforendogeneityandselectionintheprovisionof

developmentassistance(BSF,FloresandNooruddin,2009).

Consistentwiththetheory’spredictions,wefindthattheviolencereducing

effectsofaidaregreaterwhen(a)individualprojectsaresmall,(b)troopstrengthis

high,and(c)professionaldevelopmentexpertiseisavailable.Controllingforthe

presenceofcombattroopsandProvincialReconstructionTeams(PRT),thesmall9‐

15personteamswhichprovideddevelopmentexpertisetomilitaryunitsinIraq,an

additional$50percapitainspendingonaidprojectsbymilitaryunitsthroughthe

Commander’sEmergencyResponseProgram(CERP)predictedaboutsixlessviolent

incidentper100,000residentsoverthecourseofahalf‐yearintheaveragedistrict,

whichisequivalenttothesamplemean,orapproximatelyhalfthesamplemedianin

districtswithongoingfighting.4ForsmallCERPprojects(<$50,000inproject

spending)thatviolence‐reducingeffectissixtimesstronger(i.e.,$8/capitato

reduceviolencebythesamplemean).Incontrast,mostotherdevelopment

assistanceprograms,includingthosewithlargeinfrastructureprojects,showno

evidenceofviolence‐reduction,withtheexceptionofUSAID’ssmall‐scale

CommunityStabilizationProgram(CSP).

Aspredictedbythetheory,smallscalespendingandforcelevelscomplement

eachother;foreveryadditionalmaneuverbattalion(approx.800soldiers)present4Theseareobservations(i.e.,districts/half‐years)withnonzeromeasuredviolence.

3

inadistricttheviolence‐reducingeffectofsmallCERPprojectsisroughlydoubled.

Developmentexpertisealsocomplementstheviolence‐reducingeffectofsome

developmentprograms.ThepresenceofaPRTamplifiesviolencereductionofCERP

andCSPspendingbybetween50and200percent,dependingontheprogram.

Ourfindingsshouldbeusefulinthedesignofdevelopmentprogramsin

conflictandpost‐conflictenvironmentsandmayextendtofragilestatesingeneral,

whereassistancemaybecaptured,extorted,ordestroyed.

I.Theory:ComplementarityofServiceProvisionandSecurityinCounterinsurgencyThissectionexploreswhataninformation‐centricmodelofcounterinsurgency

impliesaboutthecomplementaritybetweenpublicserviceprovisionandsecurity

provisioningeneratingstability.Thatcomplementarityisintuitive:government

servicesshouldbeofmorevalueinasecureenvironmentandsecuritywillbeeasier

toprovideifthelocalpopulationgivesinformationtosecurityforces,whichismore

likelyifthegovernmentprovidesbasicservices.Toillustratehowthe

complementarityemergeswebuildonthethree‐sidedgamebetweengovernment,

rebels,andacommunity,presentedinBSF.Wefirststatetheassumptionsand

equilibrium,referringtotheoriginalformotivationandproofs,andthendevelop

theresultsoncomplementarity.

A.Assumptions

1.PlayersandActions

Thegovernment,G,seekstoreduceviolencethroughcounterinsurgencyeffortand

serviceprovision.Arebelgroup,R,seekstoimposecostsongovernmentby

attackingit.Autilitymaximizingcommunity,C,canhelpdelivercontrolofterritory

togovernmentbyanonymouslysharinginformationaboutrebels.

2.SequenceofPlay

InformationsharingbythecommunityrequiresnopreparationsoweassumethatC

moveslast.Playproceedsinfourstages.

4

(1)Naturedrawscommunitynormsfavoringrebelcontroloftheirterritory,

n,fromauniformdistributionU[nL,nU];nisprivatetoC.

(2)Gchoosesalevelofpublicgoodstoprovide,g,andalevelof

counterinsurgencyeffort,m.Rsimultaneouslychoosesalevelofviolence,v,

toattemptagainstG.(AssumenLandnUspanenoughofthereallinetoallow

nL≤v+g≤nU.)

(3)Cdecideshowmuchinformation,i,tosharewithG,havingobservedthe

actionsofGandR.

(4)Uncertaintyregardingcontrolofterritory,a,isresolved,andpayoffs

occur.

3.Technologyofcontrol

Controlofterritoryisabinarystate.Thevariable,a,isoneifthegovernment

controlstheterritory,andzeroiftheterritoryiscontrolledbyrebels.The

probabilityofgovernmentcontrolis

P(a=1)=h(m)i,

wheremiscounterinsurgencyeffortbyG,(m≥0),h(m):R+→[0,1]isa

monotonicallyincreasing,concavecontestsuccessfunction,withh(0)=0andh→1

asm→∞.HereiisthelevelofinformationthatCchoosestosharewithG,(1≥i≥0).

(Allvariablesarerealnumbersunlessotherwisespecified.)

4.Payoffs

Community:Communityutilityisgivenby

UC(a,g,n,v)=u(c+g–n)a+u(c–v)(1‐a).

Ifa=1(governmentcontrol)thenthecommunityconsumesc≥0,andbenefitsfrom

governmentservices,g≥0,soitattainsutilityUC=u(c+g–n),whereu(.)is

continuouslydifferentiableandmonotonicallyincreasing.Servicesarelocalpublic

goodssuchaspolicing,disputeresolution,education,healthclinics,utilities,and

infrastructure.Communitynorms,n,generatedisutilitywhengovernmentisin

control.

5

Alternatively,ifa=0,rebelsmaysuccessfullycarryoutviolence,v≥0,against

governmenttargets.InthatcasecommunitymemberswillattainutilityUC=u(c–v).

Rebelviolence,v,isnotdirectedagainstcommunitymembersperse,butweassume

thattheysufferfromitnonetheless,becausetheyareaccidentallyaffectedby

crossfire,empathizewithgovernmentemployees,orvaluegovernmenttargets.In

thecaseofrebelcontrolthecommunitydoesnotbenefitatallfromgovernment

services,g,eitherbecausethegovernmentwithdrawsserviceswhenitcannot

protectitsemployeesandcontractors,orbecauseitconditionslocalpublicgood

provisiononcontrol,ascollectivepunishment.Conditionalitywouldbeunusualfora

socialwelfaremaximizinggovernmentbutisU.S.militarypolicyinadministering

CERP(U.S.Army,2006).SurveyevidencerevealsthatamajorityofCERP

implementersinAfghanistanpracticeconditionality.5Thisassumptionisclearly

extreme;itcannotfullyapplytoalltypesofservices,suchasroadswhichcannotbe

easilywithdrawn.Itcouldfullyapplytoservicessuchaspolicingandjustice,and

mightwellpartiallyapplytoservicessuchashealthandeducation.Wediscussthe

implicationsofrelaxingconditionalitybelow.

IncorporatingtheuncertaintythatCfacesabouta,C’sexpectedpayoffis

(1) EUC(g,v,n,p)n=u(c+g–n)h(m)i+u(c–v)(1‐h(m)i).

Rebels:Rebelsuseviolencetoimposecostsongovernment,eitherinanattemptto

extractconcessions,orinanefforttooverthrowthegovernmentaltogether(Tilly,

1978).IntheIraqicontexttheseattackswouldbemostlyimprovisedexplosive

device(IED)anddirectfireattacksagainstIraqigovernmentorCoalitionforces.Let

G’scostofrebelviolencebe

A(v)(1‐a),whichaccountsforthedamagecausedbyanattack.R’sbenefitfrom

violenceisthenUR=A(v))(1‐a),whereweassumethatA(0)=0andthatAisan

increasing,concavefunction.Rebels’costofviolenceisB(v),whichisincreasingand

convex.(Henceforth,allfunctionsareassumedtobetwicecontinuously

differentiable.)SoR’sexpectedpayoffis

5SeeBSFfordetails.

6

(2) EUR(v,a)=E[A(v)(1‐a)–B(v)]=A(v)(1‐p)–B(v),

wherep≡h(m)E(i).

Notethatp=P(a=1)forrebels,forwhomiisarandomvariable.

Government:Thegovernmentbearsthecostsofviolenceaswellasthecostsof

violencemitigation(counterinsurgency),m,andofserviceprovision,g,andgets

expectedutility

(3) ECG(v,m,g,a)=E[A(v)(1‐a)+D(m)+H(g)]=A(v)(1‐p)+D(m)+H(g).

WeassumethatD(0)=H(0)=0,thatcostfunctionsD(.)andH(.)aremonotonically

increasing,andthatA(nU)>D'(0),sothatthefixedcostsofmareneversohighthat

communitiesmaximallypredisposedtonotshareinformationarenevercost

effectiveforGtoengage.

B.Equilibrium

WefocusonsubgameperfectNashequilibriuminpurestrategies,solvingby

backwardsinduction,startingwiththecommunity(step#3).

Community:Thecommunitychoosesiontheclosedinterval[0,1]tomaximize,

max EUC(i,g,n,v,m)n=u(c+g–n)p(m,i)+u(c–v)(1‐p(m,i)).

Anticipatingresultsoncomplementarity,notethatsincetheprobabilityofcontrolis

proportionaltoinformationshared,publicgoodprovisionandinformationare

complements,asarecounterinsurgencyeffortandinformation.SinceCchoosesi

=h(m),so

0≥ u(c+g–n)h(m)‐u(c–v)h(m),

whichimpliesthateitherm=0orthatthebestresponsefunctionofthecommunity

is

4 ∗ 0ifu u ↔ 1ifu u ↔

.

Consumptionisneutral;itoccurswhetherinformationissharedornot.Norms

favoringrebelcontrolreduceincentivestoprovidei.

7

Recallingourdiscussionofconditionality,wecannowseewhyitmatters.

HigherginducesCtoshareinformationin(4).Intheabsenceofconditionalityg

wouldbeenjoyedunderbothgovernmentandrebelcontrol,andwouldprovideno

incentiveforinformationsharing(i.e., ∗ 1 ↔ ).Sointheabsenceof

conditionality,gwillhavenoeffectoninformation‐sharing,andthereforenorolein

themodel.Inthecontextofthemodel’sassumptions,then,anyestimatedeffectswe

findofgareevidenceofconditionality.

Definep*≡p(i*,m),theprobabilityofgovernmentcontrolanticipating

optimalinformationsharingbythecommunity.Ifm>0thenE(i*)=P(i*=1)=P(n<

g+v)=F(g+v)=(g+v‐nL)f,wheref= ,thedensityoftheuniformdistribution,

sothat

(5) p*=(g+v‐nL)fh(m)ifm>0,p*=0ifm=0

Government:Continuingbackwardsthroughthesequenceofplay,thegovernment

anticipates(4)andsolves

min,

ECG(v,m,g,p*)=A(v)[1‐p*]+D(m)+H(g).

G’sfirstorderconditionformis0≤ ‐A(v)(g+v‐nL)fh'(m)+D'(m).Underthe

mildassumptionthatA(nU)>D'(0)m=0cannotbeaNashequilibrium,which

simplifiestheanalysisasitimpliesthatp*>0in(5).SeeBSFforproof.

Turningtoasolutionform*, ‐A(v)(g+v‐nL)fh''(m)+D''(m)>0,so

mhasauniqueinteriorsolutionforsomem*>0,givenvandg,definingabest

responsefunctionm*(v,g).

Thegovernmentalsochoosesalevelofservices,g*,thatsolvesthefirstorder

condition0≤ ‐A(v)fh(m)+H'(g). H''(g)>0,whichensuresa

uniqueinteriorsolutionatsomeg*>0,definingabestresponsefunctiong*(v,m).

SolvingcrosspartialsandinvokingtheimplicitfunctiontheoremBSFshow

thatbestresponsefunctionsareupwardslopinginviolence:∗ >0,and

∗ >0.

8

Rebels:Rebelssimultaneouslychoosealevelofviolencetomaximizeexpected

violencecostsimposedongovernment,anticipatingoptimalbehaviorofC,asin(4).

max EUR(v,g,m,p*)=A(v)[1‐p*]–B(v).

Solvingthefirstorderconditionforv,0≥ A'(v)[1‐p*]–A(v)fh(m)–B'(v).

Thesecondordercondition, A''(v)[1‐p*]–2A'(v)fh(m)‐B''(v)<0,sothat

v*isauniquemaximum,givengandv,thusthefirstorderconditiondefinesR’sbest

responsefunctionv*(g,m).

R’schoiceofviolenceisdecreasinging.( =‐A'(v)fh(m)<0,

whichimpliesthat∗ <0bytheimplicitfunctiontheorem.)BSFconfirmthat

partialequilibriumpredictionempirically,aresultthatwewillrevisitbelow.R’s

choiceofviolencealsodecreasesinm,(since∗ <0,since =‐A'(v)(

g+v‐nL)fh'(m)‐A(v)fh'(m)<0).

Existence:Assemblingresults,wehaveaclosedformsolutionforoptimal

informationsharingbyCinstage#3,andthreeequationsinthreeunknownsthat

determinebestresponsefunctionsm*(v,g)andg*(v,m)forG,andv*(g,m)forRin

stage#2:

4 ∗ 0ifu u ↔ 1ifu u ↔

;

(5) 0= ‐A(v)(g+v‐nL)fh'(m)+D'(m*),

0= ‐A(v)f+H'(g*),and

0= A'(v*)[1‐p*]–A(v*)fh(m)–B'(v).

Inthegeneralcasewecannotsolveforclosedformsolutionsform*,g*andv*,but

theconcavityofEURandtheconvexityofECGensureexistenceofauniqueNash

equilibrium(i,v,c,g).6

6SeeMas‐Colleletal,proposition8.D.3.

9

[Figure1abouthere]

Figure1illustratesthatequilibriumaspointAinviolence–enforcementspace,and

inviolenceservicesspace,astheintersectionofdownwardslopingv*curvesandan

upwardslopingg*curve,(allconditionalonthechoicevariableintheomitted

dimension).

C.Complementarityofserviceprovisionandenforcement

Howshouldgovernmentapplyscarceresourcestoservicesandcounterinsurgency

effort?Theanswerdependsonthecomplementarityofthoseinputs,whichrequires

alittleexplanationinastrategiccontext.ExaminingFigure2a,weaskhowtheslope

oftheoptimalresponsefunctionv*willchangewhengisincreased,ifitbecomes

steeper(i.e.,morenegative)thenwewillsaythatservicescomplement

counterinsurgencyeffortininducingrebelstoreduceviolence.

Proposition1:

Proof:SeeAppendix.

Notethatthiscomplementaritygoesbeyondatechnologicalpropertysuchasthe

complementarityofinputsinaproductionfunction.Itreflectsinsteadtheeffectofg

inenhancingtheviolencereducingeffectofmontheoptimalchoiceofviolenceby

R.Theintuitionbehindthiscomplementarityistechnological,though.Itfollows

fromthefactthatgcomplementsmintheprobabilityofinformationsharingin(4).

Theproofshowsthatothercountervailingforcesaredominatedbythat

technologicalcomplementarity.

Thesameintuitionunderliesthesymmetriceffectofmontheviolence

reducingeffectsofg,asillustratedinFigure2b,andstatedinProposition2:

∗

<0.

Proof:SeeAppendix.

Notethatthetwincomplementaritypropositionsdescribepartial

equilibriumeffects,whichomitanyadditionalshiftinthem*curve,say,asaresult

ofachangeing,.Thisdoesnotcomplicatetheanalysissincemandgarestrategic

∗

0 .

10

complements(inthegovernment’scostminimization).Thus,thegeneral

equilibriumeffectofanexogenousincreaseingisafurtherreductioninviolence,v,

duetotheinducedincreaseinm,andthesameistrueofanexogenousincreasein

m.

Returningtothequestionofoptimalallocationofresourcesforgovernment,

theproblemisanalogoustothatofaproductionpossibilitycurve,inwhichthe

violentstrategicresponseofrebelsisconsiderednegativeproduct.Ifwerecastthe

government’sproblemasmaximizingstability(negativeviolence)atminimalcost,

Figure3reflectstheiroptimumatpointA.Complementarityimpliesthatthe

productionpossibilitycurveisconcavetotheorigin:neitherenforcementnorservice

provisionwouldeveroptimallybeprovidedalone,butalwaystogether.7

Thisresultisquitegeneral.Alessrestrictivesocialwelfarefunctionmight

includedirectutilityfromserviceprovisionandutility(ordisutility)from

enforcement,whichwouldgeneralizeourlinearindifferencecurveinFigure3by

addingsomecurvature.Graphically,aslongasthatcurveisnottooconcavetothe

origin(diminishingreturnswouldimplyconvexity)thebasicresultholds:

enforcementandserviceprovisionshouldalwaysoptimallyappearincombination.

InsectionIIIbelow,wejointlytestthosetwopropositionsusingdataon

troopstrengthanddevelopmentspendingduringtheIraqwar.

II.DataandInstitutionsDevelopmentassistancewasprovidedbyanunusuallywiderangeofU.S.

governmentactorsinIraq,mostofwhoseactivitiesarecapturedinourdata.We

measureaidspendingusingdatafromtheU.S.ArmyCorpsofEngineersGulfRegion

Division’sIraqReconstructionManagementSystem(IRMS).Theseunclassifieddata

includethestartdate,enddate,projectdescription,fundingsource,andamount

spentfor62,966aidprojectsprojectsawardedthroughDecember2008.They

includeapproximately$23billioninaidprojectsfundedunderavarietyof

7Giventheprincipleofcomplementarity,theoptimalratioofenforcementandserviceprovisionwillreflectlocalconditions,varyingacrosstimeandspace.

11

programs,includinglarge‐scalereconstructionspendingthroughDODadministered

programssuchastheCERP,theIraqReliefandReconstructionFund(IRRF),and

variousStateDepartmentprogramsincludingUSAIDactivitiesfundedthroughthe

EconomicSupportFund(ESF).8

TheU.S.militaryallocatedroughly$3BinaidthroughitsCERPprogram.

CERPfundswereallocatedinsmallamounts,mostlybyunitsatthebrigadelevel

(approx.3,000soldiers)andbelow,withoutlayersofsubcontractingthatmadethe

relationshipbetweendollarsspentandworkdonetenuousforotherreconstruction

spendingprogramsinIraq.CERPspendingwasdesignedtoworklikeginour

model,byprovidingmilitarycommanderswithresourcestoengageinsmall‐scale

projectstomeettheneedsoflocalcommunities,withtheaimofgarneringthe

population’ssupportandcooperation.Inpractice,CERPfundswereusedtofunda

broadrangeofprojects,fromsalarypaymentstomajorinfrastructureprojects,

thoughthemajoritywenttosmall‐scalelocalpublicgoods.Incontrast,non‐CERP

projectswereoftenquitelarge,withatypicalprojectbeinginfrastructureforwater

andsanitation,ortransportation.9

BesidesDOD,theU.S.AgencyforInternationalDevelopment(USAID)also

providedsmall‐scaleaidfundsinIraq,throughtwomainprograms,the$560M

CommunityActionProgram(CAP)andthe$644MCommunityStabilization

Program(CSP).CAPranfromMay2003throughMarch2010andfacilitatedthe

creationandtrainingoflocalcommunitygroupswhichthenidentifiedsmall

infrastructureprojectssuchascreatingpotablewaterstoragetanks,wastewater

andirrigationsystems,andsmallconstructionprojects,averagingapproximately

$101kinspendingover91days.Thetheorybehindtheprogramwasthat

communitieswithweakcivicinstitutionsweremorevulnerabletoinsurgent

influenceandlessabletodemandtheservicestheyneededfromthegovernment.

CSPranfromMay2006throughAugust2009andfocusedonfundingjobcreation

throughtrainingandsmallinfrastructureprojectsinkeycities,withtheaverage

projectcosting$77k,andlasting238days.Importantly,CSPcontractorstriedto8SeeBSFforfulldetails.9Formoreinformationondatasources,seeBSF.

12

brandtheirprojectsasbeingconductedbythelocalgovernment,notbyUSAIDor

theforeignNGOthatimplementedtheprogram.Whilenotexplicitlytiedtothe

militarycampaign,aswasCERP,CAPandCSPrepresentedthecivilian‐administered

programsmostlikeCERPintermsofprojectsizeandduration.

Ourkeydependentvariableistheintensityofinsurgentactivitymeasuredas

therateofattackspercapitaagainstCoalitionandIraqigovernmentforces.The

attackdataisbasedon‘significantactivity’(SIGACT)reportsbyCoalitionforcesthat

captureawidevarietyofinformationabout“…executedenemyattackstargeted

againstcoalition,IraqiSecurityForces(ISF),civilians,Iraqiinfrastructureand

governmentorganizations.”10Thesedataprovidethelocationanddateofattack

incidentsbetweenFebruary2004andFebruary2009.

WehavedataonforcelevelsfromtheLee(2011)OrderofBattleDataset,

whichidentifiesthenumberofmaneuverbattalions(a.k.a.forcesthatare

responsiblefordefinedphysicalterritory)presentinadistrictforeachmonthfrom

February2004throughDecember2008.Lee’sdatawerecompiledusingpress

reportsandaredescribedindetailinLee(2012).ForceallocationdecisionsinIraq

weredrivenbyacombinationofstrategicimperativesandpracticalconstraints.At

thestrategiclevelcommandersmovedbattalionsforanumberofreasons,including

removingthemfromareasdeemedtobepacified.Forinstance,afterthelarge3rd

ArmoredCavalryRegiment(approx.4,700soldiers)reducedtheviolenceinTalAfar

fromspring‐2005throughspring‐2006itwasreplacedbyacavalrysquadron

(approx.800soldiers).Alternatively,battalionsweremovedtoareasdeemedtobe

morestrategicallyvital,aswhentheadditionalforcessenttoIraqaspartofthe

2007SurgeweredeployedinBaghdadandneighboringdistricts.Tounderstandthe

possibleendogeneityofforcelevelsinaparticulardistrictxhalfyear,it’simportant

tonoteorganizationalconstraints.Whiletherewassurelyanintentiontoallocate

battalionsdynamicallytotheareaofgreatestneed,thecombinationoftroop

rotationschedules,andanorganizationalinterestinmaintainingunitcohesionand

10GAO(2007),DOD(2008).TheinformationprovidedintheUnclassifiedSIGACTdataarelimitedtothefactofandtypeofterrorist/insurgentattacks(includingIED's)andtheestimateddateandlocationtheyoccurred.SeeBSFforfulldetails.

13

developinglocalknowledgeamongdeployedbattalionswouldtightlyconstraina

commanders’abilitytoreallocatetroopsingroupsoflessthanabout800.Thus,in

thecontextofourmodelthemarginalcostofadditionalmtoadistrictwasquite

high.

ProvincialReconstructionTeamlocationsarecodedusinginformation

gatheredfromasetofmapsprovidedbytheStateDepartmentPRToffice.USPRTs

werefirstestablishedinlate2005,andthatnumberrosetotwentybythesecond

halfof2008,eachinaseparatedistrict.WedonotcountPRTsofotherCoalition

forces,assumingthattheywouldbelessrelevantforUSdevelopmentprogram

spending.

AppendixTable1providesdescriptivestatistics.

III.ResultsOurempiricalstrategyisastraightforwardfirst‐differencesdesigninwhichwe

regresschangesonconflictonchangesinvariouskindsofaidspending,controlling

forlaggedchangesinviolenceandchangesinCoalitionforcelevels.

Ourbasicestimatingequationis:

, , , , , , , , , ,

where , isthenumberofinsurgentattacks(incidents)indistrictiinperiodt, ,

istheamountofdevelopmentspendingofagiventype, isayearfixedeffectto

accountforthebroadseculartrendsinthewar,and , capturesthenumberof

maneuverbattalionsindistrictiinperiodt.Thelaggedchangeinviolence, , ,is

includedtoaccountforshortterm,district‐specifictrends.Sincebroadtrendsin

violencedifferedforSunniareas,wealsoincludeaseparateyearfixedeffect

interactedwiththeproportionofSunnivoters.11

Ourempiricalstrategywillidentifythecausalimpactofchangesinaid

spendingifeithertheomittedvariableslinkingaidspendingtoinsurgentviolence

areentirelyafunctionofunit‐specifictrendsoriftheirinfluenceonaidspendingis

accountedforbypastchangesinviolenceandchangesintrooplevels.Themajor

11SeeBSF(2011)foramoredetaileddiscussion.

14

challengeisthepossibilityofapositiveendogeneitybiasif,conditionalontrends

andothercontrols,increasesinresidualviolenceareanticipatedandrespondedto

byapplicationofmoregorm,inahalf‐yearinterval.Thatwouldcauseour

estimatestounderstatetheviolence‐reducingeffectsofbothgandm.Thelogistic

constraintsandlagsbuiltintotheallocationandimplementationofboth

developmentspendingandeffectivepatrolstoadistrictmakethattypeofrapid

response(withinahalf‐year)difficultbutnotimpossible.Forthatreasonwetried

specificationswithvariouscontrolstoinvestigaterobustness.

Table1describesourfirstsetofresults,showingthatsmallscale

reconstructionspendingisviolencereducingonaverage( <0)butothertypesof

reconstructionspendingareoftennot.Column(1)replicatesthemainempirical

resultofBSF,thatCERPisviolence‐reducing.Column(2)demonstratesthatthe

CERPcoefficientisrobusttoincludingtroopstrength(m)ontherighthandside,

whichBSFdidnot,indicatingthatviolence‐reductionisnotduetoCERPspending

actingasaproxyforthepresenceofcoerciveforce,m.Notethatthecoefficienton

troopstrengthdoesnotindicateviolencereduction–ifanythingthepositive

coefficientoncontemporaneoustroopstrengthindicatesthattroopsincrease

violence,whichisinconsistentwiththepredictionsofourtheory.Wedon’tthink

thatthisfindingoverturnsthevalidityofthetheoryfortworeasons:First,the

incidentdataarereportedbythetroopsthemselves,sothatthereisabuiltin

upwardbiasinlocationswhichhavetroopspresent.Second,thereappearstobea

shorttermincreaseinviolenceonarrivalwhichfadesafterabouthalfayear,which

wesuspectisduetoashorttermlearningprocessinwhichnewtroopsareinitially

challengedbyinsurgents,whothenwithdrawasthetroopsdevelopsituational

awarenessintheirareaofoperations.Thesumofthecoefficienton

contemporaneoustroopstrengthandthatonthelagisalmostalwaysstatistically

zero,andwillbenegativeinsomeofthespecificationsreportedbelow.Thus,once

theupwardreportingbiasisaccountedfor,andallowingforapositiveendogeneity

bias–asdescribedabove,thecumulativeeffectoftroopstrengthappearstobe

violencereduction(byanunknownamount)afteraboutsixmonths.(Includinga

15

third–oneyear—lagoftroopstrengthdoesnotsubstantivelyalteranyofthose

conclusions.)

Returningtoourdiscussionofdevelopmentspending,columns(3)and(4)

replicateanothermainresultofBSF,thatsmallCERPissixtimesasviolence‐

reducingperdollarspentthanislargeCERP,anddemonstratethatthoseresultsare

alsorobusttotheinclusionoftroopstrength.Theremainingcolumnsreportthe

effectofotherprograms,showingthatonlyoneofthem,theCommunity

StabilizationProgram(CSP),showsevidenceofbeingviolence‐reducing.Neither

changesinlargenon‐CERPreconstructionproject,changesinsmallnon‐CERP

reconstructionprojects,changesinUSAIDspendingthroughtheCAPprogram,nor

changesinoverallUSAIDspendingaresignificantlycorrelatedwithchangesin

insurgentattacks.Whilenoneofthoseprograms(non‐CERPlargeorsmall,CAPor

USAIDspendingingeneral)showeffectsthatarestatisticallydifferentfromzero,

withtheexceptionofCSP,theyareallstatisticallylessviolence‐reducingthanis

smallCERP(atα=.05),includinglarge‐CERP(asreportedinthefinalrowofTable

1).

WhyareCERPandCSPviolence‐reducingwhileotherprogramsarenot,and

whyissmallCERPespeciallyso?Firstly,it’sworthnotingthatthiscontrastreflects

thelargerliterature,inwhicheconomicactivity,andevenaidprograms,are

sometimesassociatedwithincreasedviolence(i.e.,predation,asBermanetal2012

findinthePhilippines,forexample)andsometimeswithdecreasedviolence,asthe

theoryinsectionIIpredicts.Recallingthedrivingforcesofthattheory:programs

mustbeconductedinterritorysecureenoughtobeimplementable,theirdesign

mustbesufficientlyinformedaboutlocalpreferencestobenefitthelocal

community;andtheymustbeconditionaloncooperation(i.e.,informationsharing).

ThosecriteriaareconsistentwiththepatternofresultsinTable1.CERPprograms

areunusualinthattheyaresecurebydesign,astheyareadministeredbymilitary

unitsoperatinginthearea.SmallerprogramssuchasCSP,CAPandCERPtendtobe

betterinformed,becausetheyaremorelikelydesignedinconsultationwiththe

localcommunity.Andsmallerprogramsaremoreeasilyconditionedonthe

cooperationofcommunities,incontrasttolargeinfrastructureprojects(suchas

16

buildingawaterorseweragesystem)whichcannoteasilyberevoked.Moreover,

surveyevidencefromAfghanistanrevealsthatCERPwasgenerallyimplemented

conditionally(seeBSF,footnote11),incontrasttohowadevelopmentagencysuch

asUSAIDwouldtypicallyimplementprograms,inaccordancewithadevelopment

objectiveratherthanasecurityobjective.

HavingdiscussedhowthosecriteriacanrationalizetheresultsinTable1,we

turnnowtotestingtheimplicationsofthattheory.Weexaminewhethersecurity

anddevelopmentexpertisecomplementprogramsforwhichwehaveevidenceof

effectivenessfromTable1,namelyCERPandCSP.

Table2teststhehypothesisthatsecurityanddevelopmentarecomplements,

atthedistrictlevel.Recallthattheseareactuallytwoconceptuallydistinct

hypotheses(Propositions1and2),sinceinthecontextofmodelcomplementarity

neednotbesymmetric.Notwithstandingthatsubtlety,wecantestthesehypotheses

onlyjointly,byestimatingthecoefficientγontheinteractionofmandginthe

followingestimatingequation.

, , , , , , , ,

, , , , , .

Shouldbothpropositionsholdthenγ1willbenegative.

Beforeturningtoresults,anissueofmeasurementrequiresattention.The

modelprovidesnoguidanceastohowmshouldbemeasured(anddoctrineisalso

unclear).Whatweseekisthecapacityofthegovernmenttoapplycoerciveforcein

ordertosuppressrebelactivity.Untilnowwe’vemeasuredtroopstrengthin

battalionsperdistrict,whichwouldbeanadequateapproximationiftroopsper

physicalareawereappropriate,followingthelogicoftheresponsetimetoatipor

incidentbeingcritical.Alternatively,troopspercapitawouldbeagood

approximationoftheabilityofthegovernmenttopoliceandprotectindividuals.In

Table2wereportresultsusingbothapproaches.12

12TheresultsinTables1and3arequalitativelyrobusttoreplacingbattalionsperdistrictwithbattalionspercapita,asreportedinAppendixTables2and3.

17

TheleftpanelofTable2reportsbothmainandinteractioneffectsof

spendingonsmallCERP,largeCERPandCSP(columns(1),(2)and(3)).As

predictedbythecomplementaritypropositions,theestimatedinteractiontermis

negativeineachcase.Allthreecoefficientsarepreciselyenoughestimatedtoreject

thehypothesisofazerocoefficientinfavorofthealternativeofcomplementarity.

Therightpanelchecksrobustnesstomeasuringtroopstrengthinbattalionsper

capita(asopposedtoperdistrict),againforeachofthethreeprograms.The

evidenceforcomplementarityinthiscaseisweaker,butconsistentwiththe

previousresults:twoofthethreecoefficientsarenegative,andtheonewhichis

statisticallysignificant(theCSPxtroopstrengthinteractionincolumn(6))is

negativeaspredicted.Theidealmeasureofmwouldsomehowaveragetroop

densityoverphysicalareaandpopulation,soaroughaveragingofthethree

preciselyestimatednegativecoefficientsintheleftpanelwiththethreeestimates

ontheright(twonegativeandoneimpreciselyestimatedpositive)indicatestous

fairlyrobustevidenceofcomplementarity.Recallingourdiscussionofthepossible

endogeneityofbothgandm,sinceanyendogeneitybias(despiteourbestefforts)

wouldbepositive,theseestimates,ifanything,understatecomplementarity.This

evidenceofcomplementaritybetweendevelopmentspendingandtroopstrengthis

illustratedinFigure4,whichplotsthepredictedmarginaleffectsestimatedfor

smallandlargeCERP(inacombinedregression)accordingtothenumberof

battalionspresent.Spendingbecomesmoreviolence‐reducingasthenumberof

battalionsperdistrictincreases.Thedensityofbattalionsisalsoplottedinarug

plot,toillustratethepredictedeffectforatypicaldistrict.

Afinaltestableimplicationofthemodelconcernstheroleofdevelopment

expertise.Hereourinterestisindistinguishingthemechanisminthemodel–which

reliesondeliveringaservice,g,ofvaluetothecommunity,fromaclassof

“opportunitycost”modelsthatinjectwagesandemploymentintothecommunity

regardlessofwhetheraserviceofvalueisgenerated.13Inotherwords,fora

13Bermanetal(2012)distinguishesbetweentheseargumentsinthecontextofanomnibusmodel.

18

programtobesuccessfulatreducingviolence,itmustbeadevelopmentsuccessas

well,bydeliveringdesiredservicestocommunitymembers.14

Wetestthehypothesisthatexpertisemattersbyexaminingtheinteractionof

spendinginthethreeprogramswiththepresenceofaProvincialReconstruction

Team(PRT)inthedistrict.Ourworkingassumptionsisthatwhenprogramsare

informedbydevelopmentexpertstheyaremorelikelytoinvolveconsultationwith

thecommunityontheirrequestedprojects,andwillbebetterdesignedand

implementedtoeffectivelymeetthecommunity’srequest.Formally,ourhypothesis

isthatthecoefficientγ2ontheinteractiontermofgandPRTisnegative,wherePRT

isabinaryindicator.

, , , , , , , ,

+ , , + , , , , , .

Table3reportsresults.Columns(1)reportsthemaineffectofPRTpresence

inisolation,whichisviolencereducing(i.e.,negative)butnotpreciselyenough

estimatedtoconstituteevidenceofeffectiveness.Twentyninepercentofthe

populationlivedindistrictswithaUSPRTpresentduringthesampleperiod.Asin

ourdiscussionofmandg,endogeneitybiasofthePRTcoefficientwouldbeaway

fromfindingaviolence‐reducingeffect(i.e.,positive),ifwethoughtthatPRTswere

institutedinanticipationofincreased , .(NoPRTsarewithdrawnduringour

sampleperiodsoinferenceisentirelybasedonthefirsthalf‐yearofPRTpresence.)

EstablishingaPRTwouldofteninvolveassemblingateam,assigningthemasecurity

detail,andsometimesevencreatingaseparatebase–iftherewasnonealready

available,whichwouldmakeresponsewithinahalfyearunlikelybutnot

impossible.Thereportedcoefficientisrobusttoremovingthetroopstrength

variable,andthelaggedviolencemeasure(notshown).Column(2)reportsthatthe

estimatedviolence‐reducingmaineffectofCERP(inTable1)isrobusttoaddinga

PRTindicator.

14Inamoregeneralmodelwithindividualcommunitymembersratherthanarepresentativeagent,aprogramwouldonlyhavetosuccessfullydeliverdesiredservicestoindividualsmostlikelytoshareinformationwithgovernment.

19

Columns(3),(4),(5)and(6)reportourinteractiontests.Inallcases(CERP,

smallCERP,largeCERPandCSP)theinteractionofPRTwithdevelopmentspending

yieldsanegativecoefficient,indicatingthattheviolence‐reducingeffectsofthese

programsareenhancedbyPRTpresence.Thoseinteractionseffectsarestatistically

significantatthe10%forlargeCERP,andatthe1%levelforsmallCERP.Small

CERPprojectsarealmostthreetimesasviolence‐reducing(‐.067+‐0.36vs.‐.036)

whenaPRTispresentinthedistrict.Thatpatternofcomplementarityisillustrated

inFigure5,whichshowstheincreaseinviolencereduction(theslope)whenaPRT

ispresent.

TakingtheevidenceinTables1‐3together,wecandrawsomeconclusions.

Developmentspendingismostviolence‐reducingwhenitissecure,whichaddresses

thepuzzleposedbyTable1bytherelativeeffectivenessofsmallCERPprograms.

Developmentspendingisalsomoreviolencereducingwhenitisinformedbylocal

developmentexperts.Smallprojectsaremorelikelytobeviolence‐reducing,which

mayreflectthefactthattheyarebetterinformed,ormaybeduetotheirlending

themselvesmorereadilytoconditionalimplementation.15Conversely,troop

strengthismoreviolence‐reducing(oratleastlessviolence‐increasing,as

measured)whensmall‐scaledevelopmentspendingispresent.Finally,thedata

suggestthatsmallerprojectsshowstrongercomplementaritieswithexpertiseand

withsecurity,whichmayreflectafurthercomplementaritybetweenconditionality

andbothsecurityontheonehandandexpertiseontheother.

IV.ConclusionOveralltheevidencefromIraqsuggeststhat,inaccordancewiththeinformation‐

centric(or“HeartsandMinds”)frameworklaidout,aidspendingwhichissmall,

conditional,secure,andeffectiveasadevelopmentprogramcreatesincentivesfor

15InresultsnotreportedwefindnostatisticallysignificantcomplementaritiesbetweeneithertroopstrengthorPRTsontheonehand,andanyoftheotherprogramsmeasuredinTable1ontheother.Wecautiouslyinterpretthatasevidencethattheconditionalityandsecuritythatsmallprojectsallowisanecessaryconditionforviolence‐reductionindevelopmentspending.

20

cooperationwithgovernmentthatlarge,lesssecureandlessinformedprojectsdo

not.

Moregenerally,ourtheoreticalperspectivesuggestsanumberofpractical

lessonsforaidprograms.Complementarity,asillustratedbyFigure3,indicatesthat

agovernmentwishingtosuppressviolenceatminimalcostwouldmixtheuseof

developmenteffortsandcoerciveforce,ratherthanexclusivelyuseoneortheother.

Evidencesuggeststhatmostrebelgroupsrecognizethatlogicandlikewisemix

governanceinitiativeswithcoercion.16

TheseinsightsaredrawnfromtheU.S.andCoalitionexperienceinIraqasan

occupyingforce,andthenlaterinsupportofadomesticgovernmentcombatinga

veryviolentinsurgency.Yetbasedonourexperienceapplyingthesamemodelto

otherfragileenvironments,wehypothesizethattheselessonsmaywellapplymore

generallytodomesticgovernmentsortointernationalassistancetolocalallies.

Sufficientconditionsfordevelopmentassistancetobestabilityenhancinginplaces

wherearebelofcriminalelementcancaptureordestroyprojectsareapparently

these:theyshouldbemodest,secure,conditional,andinformedbylocal

preferences.Moreoverengagingdevelopmentexpertise,ratherthansimply

spendingfunds,augmentsthestabilizationeffect.Forinstance,keeping

developmentexpertshunkereddownfarfromprojectssitesisunlikelytobe

violence‐reducing.Alogicalcorollaryofcomplementaritybetweendevelopmentand

securityprovisionisthatforeignassistancetogovernmentsfightinginsurgencies

willbemoreeffectivewhenitincludescapacitybuildinginbothgandm.Investing

intrainingsecurityforcesisastandardcomponentof“smallfootprint”intervention,

yetgovernanceassistanceistypicallylimitedtotrainingforthosewhowillmanage

governmentagencies.Ouranalysissuggeststhattrainingthosewhowould

implementlocalserviceprovisionmayhaveagreaterimmediateviolence‐reduction

effect.Inthesamevein,securityforces,oncetrained,willbemoreeffectiveif

redeployedoutoflarge,insulatedbasesandinsteadengagingthelocalpopulationin

awaythatcomplementsdevelopmentefforts.

16SeeBSFfordiscussion.

21

Finally,itisworthputtingtheseresultsincontext.Modest,secure,informed

andconditionalshouldbethoughtofassufficientconditionsforviolence‐reduction.

Furtherresearchisrequiredtoestablishwhereandtowhatextenttheyareall

necessary.Furtherresearchmayalsorevealtheextenttowhichamixofcapacity

buildinginbothcoerciveandbenigngovernancecangeneratemediumandlongrun

stabilization–beyondahalf‐yearoroneyearhorizon.Theiso‐stabilitylinesof

Figure3aredrawnforagivensetofnormsandexpectations.Asexpectationsof

qualityofgovernanceimprove,includingpoliticaldevelopmentandrepresentation,

enhancedlegitimacyshouldimprovenormsofcooperationwithgovernment‐‐

ratherthanwithrebelsorcriminals.Thatwouldshiftiso‐stabilitylinestolower

levelsofviolenceatthesamecosttogovernmentinthemediumandlongterm,and

allowgovernments(andallies)theoptionofshiftingspendingawayfromcoercive

forceandtowardtraditionaldevelopmentprograms.

22

Figure 1: Best Response Functions for Violence and Development Spending

Violence(v)

GovernmentServices(g)

v*(g,m)

g*(v,m)

A •

'

23

Figure 2a: Services Complement Enforcement

Note:Increasinggtog’makestheslopedv*/dm|gmorenegative.

Violence(v)

Enforcement(m)

v*(g,m)

m*(v,g)

A •

v*(g’,m)'

24

Figure 2b: Enforcement Complements Services

Note:Increasingmtom’makestheslopedv*/dg|mmorenegative.Thisisnotthesamecross‐partialeffectasinFigure2aabove,asthederivativesareconditionedondifferentvariables.Thechangeintheslopeofdv*/dm|gisactuallylarger.

Violence(v)

GovernmentServices(g)

v*(g,m)

g*(v,m)

A •

'

v*(g,m’)

25

Figure 3: Complementarity in Stability Production

Enforcement (m)

GovernmentServices(g)

A •

StabilityIsoquantA(v0)

Iso‐Cost Curve

26

Figure 4: Troop Strength Complements Development Spending

27

Figure 5: Development Expertise Complements Spending

28

Table 1: Development Programs and Violence Suppression – Alternative Programs DependentVariable: (1) (2) (3) (4) (5) (6) (7) (8) (9) VariableIncidentspercapita MeanCERP ‐0.0122** ‐0.0122** $10.07

(0.00548) (0.00562)CERP<$50K ‐0.0639*** $1.32

(0.0186)CERP>$50K ‐0.0108* $8.75

(0.00559)NonCERP>$100K 0.000899 $33.18

(0.000565)NonCERP<$100K 0.00636 $0.31

(0.0228)CSP ‐0.0470* $0.44

(0.0242)CAP ‐0.0118 $0.18

(0.0279)USAID ‐0.00248 $12.51

(0.00334)TroopStrength 0.0489 0.0479 0.0451 0.0386 0.0349 0.0466 0.0354 0.0301 1.12

(0.0399) (0.0349) (0.0400) (0.0325) (0.0337) (0.0328) (0.0333) (0.0339)LaggedTroopStrength

‐0.0255 0.0162 ‐0.0373 ‐0.0411 ‐0.0421 ‐0.0205 ‐0.0424 ‐0.0400 1.13

(0.0675) (0.0602) (0.0704) (0.0729) (0.0732) (0.0705) (0.0728) (0.0731)LaggedIncidents 0.177** 0.173* 0.172* 0.173* 0.173* 0.172* 0.157 0.171* 0.172* 0.589

(0.0883) (0.0893) (0.0957) (0.0904) (0.0973) (0.0979) (0.0980) (0.0971) (0.0969)Constant 0.0907** 0.0969** 0.0720* 0.0897** 0.0557 0.0585 0.0604 0.0574 0.0560

(0.0436) (0.0427) (0.0376) (0.0416) (0.0359) (0.0370) (0.0364) (0.0363) (0.0365) Observations 824 824 824 824 824 824 824 824 824R‐squared 0.213 0.215 0.222 0.204 0.180 0.179 0.194 0.179 0.180EqualitywithCERP<$50Kslope(pvalue)

‐ ‐ ‐ .0002*** .0002*** .002*** .338 .030** .0004***

Notes:Anobservationisadistrict(N=103)xhalfyear.DistrictKarkh isexcludedasnationalCSPprogramsareconfoundedwithlocalthere.Meansareforlevels(NT=927)thoughregressionsareestimatedinfirstdifferences(NT=824).Incidentsaremeasuredper1000population.Theirmeanis0.587.Troopstrengthismeasuredinbattalionsperdistrict.Regressionsareweightedbypopulationandincludeyeareffects,andSunnivote‐yearinteractions.***p<0.01,**p<0.05,*p<0.1.Standarderrorsareclusteredatthedistrictlevel.

29

Table 2: Complementarity of Development Spending with Troop Strength

DependentVariable: (1) (2) (3) (4) (5) (6)Incidentspercapita TroopLevels Troopspercapita CERP<$50K ‐0.0145 ‐0.0447***

(0.0262) (0.0157)CERP<$50KxTroops ‐0.0120** ‐0.0140

(0.00542) (0.0155)CERP>$50K 0.000353 ‐0.0122**

(0.00438) (0.00565)CERP>$50KxTroops ‐0.00639*** 0.00120

(0.00228) (0.000752)CSP 0.0325* 0.0146

(0.0172) (0.0187)CSPxTroops ‐0.0291*** ‐0.102**

(0.00480) (0.0422)

Troops 0.0655* 0.136** 0.0746* 0.229 0.112 0.245(0.0389) (0.0517) (0.0393) (0.284) (0.270) (0.252)

LaggedTroops 0.0106 ‐0.0335 ‐0.0164 ‐0.493 ‐0.537 ‐0.613*(0.0607) (0.0684) (0.0693) (0.370) (0.370) (0.355)

Laggedincidents 0.188* 0.190** 0.162 0.181* 0.177* 0.165(0.0992) (0.0934) (0.0993) (0.0998) (0.0940) (0.103)

Constant 0.0669* 0.0842** 0.0629* 0.0615 0.0832* 0.0519(0.0382) (0.0380) (0.0364) (0.0412) (0.0460) (0.0399)

Observations 824 824 824 824 824 824R‐squared 0.231 0.231 0.217 0.234 0.223 0.225Notes:Anobservationisadistrict(N=103)xhalfyear.DistrictKarkhisexcludedasnationalCSPprogramsareconfoundedwithlocalthere.Incidentsaremeasuredper1000population.Theirmeanis0.587.Troopstrengthismeasuredinbattalionsperdistrictintheleftpanel(columns(1)‐(3))withmean1.12.Troopstrengthismeasuredinbattalionsper100Kpopulationintherightpanel(columns(4)‐(6))withmeanof0.22.Regressionsareweightedbypopulationandincludeyeareffects,andSunnivote‐yearinteractions.***p<0.01,**p<0.05,*p<0.1.Standarderrorsareclusteredatthedistrictlevel.

30

Table 3: Expertise Complements Development Programs

DependentVariable: (1) (2) (3) (4) (5) (6) VariableIncidents Mean CERP ‐0.0122** ‐0.00672 $10.07

(0.00561) (0.00472)CERPxPRT ‐0.0172* $3.84

(0.00912)CERP<$50K ‐0.0357** $1.32

(0.0174)CERP<$50KxPRT ‐0.0667*** $0.42

(0.0176)CERP>$50K ‐0.00594 $8.75

(0.00476)CERP>$50KxPRT ‐0.0164* $3.42

(0.00958)CSP ‐0.0222 $0.44

(0.0152)CSPxPRT ‐0.0354 $0.31

(0.0397)PRT ‐0.0136 ‐0.0228 0.137 0.0750 0.109 ‐0.00337 0.29

(0.0829) (0.0822) (0.131) (0.0885) (0.121) (0.0840)Troops 0.0345 0.0480 0.0751* 0.0731* 0.0638 0.0496 0.22

(0.0327) (0.0400) (0.0449) (0.0414) (0.0410) (0.0338)LaggedTroops ‐0.0424 ‐0.0260 ‐0.0168 0.00877 ‐0.0286 ‐0.0185 0.23

(0.0741) (0.0687) (0.0669) (0.0613) (0.0703) (0.0731)LaggedIncidents 0.171* 0.173* 0.154* 0.170* 0.155* 0.156 0.59

(0.0971) (0.0895) (0.0889) (0.0964) (0.0903) (0.0986)Constant 0.0594* 0.100** 0.0887** 0.0701** 0.0838** 0.0614*

(0.0328) (0.0382) (0.0354) (0.0316) (0.0353) (0.0335)Observations 824 824 824 824 824 824R‐squared 0.179 0.216 0.233 0.236 0.217 0.196 Notes:Anobservationisadistrict(N=103)xhalfyear.DistrictKarkhisexcludedasnationalCSPprogramsareconfoundedwithlocalthere.Meansareforlevels(NT=927)thoughregressionsareestimatedinfirstdifferences(NT=824).Incidentsaremeasuredper1000population.Theirmeanis0.587.Troopstrengthismeasuredinbattalionsperdistrict.Regressionsareweightedbypopulationandincludeyeareffects,andSunnivote‐yearinteractions.***p<0.01,**p<0.05,*p<0.1.Standarderrorsareclusteredatthedistrictlevel.

31

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32

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WorldBank,2011.WorldDevelopmentReport2011:Conflict,SecurityandDevelopment.WorldBankGroup,WashingtonDC.

33

Appendix: Proofs of Propositions 1 and 2

The proofs of both propositions rely on partial differentiation of the slopes of the optimal

response functions of R in choosing v*.

Proposition 1:

∗

0 .

Proof: ∗ = - / and by the implicit function theorem,

= - [-A'(v)( g + v - nL )f h'(m) -A(v)f h'(m)] / A''(v)[1-p*] – 2A'(v)f h(m) - B''(v) .

Denoting the numerator Δ and the denominator Ω,

∗

∆ < 0 ,

since Δ' = A'(v)f h'(m) >0 , Ω <0, Δ > 0, and Ω' = -A''(v)f h(m) >0 , and Ω2 >0.

Proposition 2: :

∗

< 0 .

Proof: ∗ = - / by the implicit function theorem,

= - (-)A'(v)f h(m) / A''(v)[1-p*] – 2A'(v)f h(m) - B''(v) .

Denoting the numerator Δ and the denominator Ω,

∗

∆ .

Δ'Ω - Ω'Δ = A'(v)f h'(m) A''(v)[1-p*] – 2A'(v)f h(m) - B''(v)

34

- A'(v)f h(m)-A''(v) (g + v - nL )f h'(m) – 2A'(v)f h'(m)

= A'(v)f h'(m) A''(v)[1-p*] – 2 A'(v)f h'(m) A'(v)f h(m) - A'(v)f h'(m) B''(v)

+A'(v)f h(m)A''(v) (g + v - nL )f h'(m) +2A'(v)f h(m) A'(v)f h'(m) .

The second and fifth terms cancel. The other three terms are negative (since A''(v) < 0 ),

so the expression is negative. Ω2 >0 , which implies that ∆ < 0 .

35

Appendix Table 1: Summary Statistics (Changes)

Observations Weight Mean Std.Dev. Min Max

Incidents 927 246754372 ‐0.0025253 0.7192714 ‐14.30548 9.791145

LaggedIncidents 824 221459256 0.0246278 0.7529446 ‐14.30548 9.791145

CERP 927 246754372 0.8975824 11.75703 ‐252.7587 264.7626

CERP<$50K 927 246754372 0.0978531 2.637987 ‐43.8516 34.17538

CERP>$50K 927 246754372 0.7997293 10.81382 ‐252.7587 302.5766

NonCERP 927 246754372 ‐2.044234 79.77404 ‐10735.33 892.7099

NonCerp<$100,000 927 246754372 ‐0.1364265 1.977181 ‐45.27344 14.09699

NonCERP>$100,000 927 246754372 ‐1.907807 79.62294 ‐10724.78 892.3289

CAP 927 246754372 0.0339391 0.6284991 ‐8.891963 16.47236

CSP 927 246754372 0.0539443 2.029424 ‐18.23231 29.00582

USAID 927 246754372 ‐1.833554 72.81415 ‐10757.88 66.87154

PRT 927 246754372 0.0503777 0.2188411 0 1

TroopStrength 927 246754372 ‐0.008259 0.6462308 ‐3 2.333333

LaggedTroopStrength 824 221459256 ‐0.0033438 0.645426 ‐3 2.333333

CERPxTroopStrength 927 246754372 1.71061 37.70935 ‐512.5932 725.2957

CERP<$50,000xTroopStrength 927 246754372 0.1375683 12.52012 ‐165.8702 93.96977

CERP>$50,000xTroopStrength 927 246754372 1.573042 29.48188 ‐482.8429 729.1677

CSPxTroopStrength 927 246754372 0.0700144 7.186853 ‐74.87498 77.8888

CERP<$50,000xPRT 927 246754372 0.0390839 1.764686 ‐25.60038 18.19453

CERP>$50,000xPRT 927 246754372 0.4654902 6.177386 ‐80.17256 58.67921

CSPxPRT 927 246754372 0.0228998 1.721804 ‐13.36795 14.78048

Notes:Anobservationisadistrict(N=103)xhalfyear.DistrictKarkhisexcludedasnationalCSPprogramsareconfoundedwithlocalthere.Meansareinchanges,weightedbypopulation.RegressionsincludeNT=824observations.Incidentsaremeasuredper1000population,spendingvariablesarepercapita.Troopstrengthismeasuredinbattalionsperdistrict.

36

Appendix Table 2: Robustness of Table 1 results to inclusion of per capita troop strength DependentVariable: Incidentspercapita (1) (2) (3) (4) (5) (6) (7) (8) (9)

CERP ‐0.0122** ‐0.0116**(0.00548) (0.00560)

CERP<$50K ‐0.0569***(0.0197)

CERP>$50K ‐0.0103*(0.00557)

NonCERP<$100K 0.00436(0.0213)

NonCERP>$100K 0.000677(0.000611)

CSP ‐0.0443*(0.0227)

CAP ‐0.0151(0.0281)

USAID ‐0.00223(0.00295)

TroopStrengthPerCapita 0.207 0.165 0.200 0.157 0.161 0.179 0.159 0.150(0.265) (0.272) (0.263) (0.249) (0.248) (0.250) (0.250) (0.250)

LaggedTroopStrengthPerCapita ‐0.534 ‐0.472 ‐0.569 ‐0.617* ‐0.610* ‐0.583 ‐0.619* ‐0.612*(0.364) (0.361) (0.359) (0.349) (0.349) (0.354) (0.348) (0.349)

LaggedIncidents 0.177** 0.177* 0.178* 0.176* 0.177* 0.177* 0.163 0.177* 0.177*(0.0883) (0.0938) (0.1000) (0.0948) (0.102) (0.101) (0.103) (0.101) (0.101)

Constant 0.0907** 0.0869* 0.0627 0.0805* 0.0508 0.0485 0.0520 0.0500 0.0493(0.0436) (0.0465) (0.0412) (0.0454) (0.0405) (0.0394) (0.0404) (0.0398) (0.0400)

Observations 824 824 824 824 824 824 824 824 824R‐squared 0.213 0.231 0.233 0.221 0.198 0.199 0.212 0.198 0.199Notes:Anobservationisadistrict(N=103)xhalfyear.DistrictKarkh isexcludedasnationalCSPprogramsareconfoundedwithlocalthere.Meansareforlevels(NT=927)thoughregressionsareestimatedinfirstdifferences(NT=824).Incidentsaremeasuredper1000population.Theirmeanis0.587.Troopstrengthismeasuredinbattalionsperdistrictpercapita.Regressionsareweightedbypopulationandincludeyeareffects,andSunnivote‐yearinteractions.***p<0.01,**p<0.05,*p<0.1.Standarderrorsareclusteredatthedistrictlevel.

37

Appendix Table 3: Robustness of Table 3 (PRTs and Spending) to inclusion of per capita troop strength Dependent Variable: (1) (2) (3) (4) (5) Incidents

CERP ‐0.0116**

(0.00559) CERP < $50K ‐0.0266

(0.0168) CERP < $50K x PRT ‐0.0705***

(0.0171) CERP > $50K ‐0.00572

(0.00451) CERP > $50K x PRT ‐0.0155*

(0.00931) CSP ‐0.0222

(0.0151) CSP x PRT ‐0.0313

(0.0378) PRT ‐0.0419 ‐0.0542 0.0346 0.0649 ‐0.0395

(0.0843) (0.0813) (0.0808) (0.115) (0.0842) Troop Strength per Capita 0.156 0.206 0.237 0.227 0.188

(0.250) (0.265) (0.266) (0.278) (0.252) Lagged Troop Strength per Capita ‐0.621* ‐0.538 ‐0.519 ‐0.559 ‐0.577

(0.351) (0.366) (0.358) (0.366) (0.359) Lagged Incidents 0.176* 0.176* 0.175* 0.160* 0.162

(0.101) (0.0942) (0.100) (0.0954) (0.103) Constant 0.0564* 0.0951** 0.0644** 0.0788** 0.0582*

(0.0338) (0.0402) (0.0321) (0.0362) (0.0347)

Observations 824 824 824 824 824 R‐squared 0.198 0.231 0.249 0.233 0.214 Notes:Anobservationisadistrict(N=103)xhalfyear.DistrictKarkh isexcludedasnationalCSPprogramsareconfoundedwithlocalthere.Meansareforlevels(NT=927)thoughregressionsareestimatedinfirstdifferences(NT=824).Incidentsaremeasuredper1000population.Theirmeanis0.587.Troopstrengthismeasuredinbattalionsperdistrictpercapita.Regressionsareweightedbypopulationandincludeyeareffects,andSunnivote‐yearinteractions.***p<0.01,**p<0.05,*p<0.1.Standarderrorsareclusteredatthedistrictlevel.