Financial Data for Schools

7/24/2019 Financial Data for Schools

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Research Report DFE-RR183

Understanding schoolfinancial decisions

Rebecca Allen, Institute of Education, University of London

Simon Burgess, Centre for Market and Public Organisation, University

of Bristol

Imran Rasul, University College London

Leigh McKenna, Centre for Market and Public Organisation, University

of Bristol

With thanks to Aastha Mantri for additional research assistance, and

to the DfE for providing access to the NPD, CFR and SWC datasets.


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This research report was commissioned before the new UK Government tookoffice on 11 May 2010. As a result the content may not reflect current

Government policy and may make reference to the Department for Children,Schools and Families (DCSF) which has now been replaced by the Department

for Education (DFE).

The views expressed in this report are the authors and do not necessarilyreflect those of the Department for Education.


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Contents

ExecutiveSummary.............................................................................................................................3

ResultsCommentary....................................................................................................................3

ResultsSummary..........................................................................................................................4

Introduction ........................................................................................................................................ 5

ReviewoftheEvidence.......................................................................................................................8

Theoverallrelationshipbetweenschoolincomeandquality........................................................8

Classsize,thequantityanddeploymentofteachers .....................................................................9

Teacherquality................................................................................................................................9

TeachingAssistants.......................................................................................................................10

Resources......................................................................................................................................10

Data...................................................................................................................................................11

NationalPupilDatabaseandEdubase ..........................................................................................11

ConsistentFinancialReporting200910 .......................................................................................12

SchoolWorkforceCensus .............................................................................................................12

ResultsSummary............................................................................................................................14

DetailedResults ................................................................................................................................ 15

Part1:Howmuchvariationinspendingisthereforlikeschools?.............................................15

Part2:Howistheresidualincomethatsomeschoolsreceivespent? ......................................22

Part3:Whereincomechangesbetweentwoyears,howisitspent?..........................................23

Conclusions ....................................................................................................................................... 25

Difficultieswithcurrentpolicyapproachofdisseminationofbestpractice................................26

Usingbehaviouraleconomicstohelpimprovefinancialdecisions ..............................................27

References ........................................................................................................................................ 30

DataAppendix.......................................................................................................................................56


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ExecutiveSummary

Withover30bnofpublicmoneyspenteveryyear,Englishschoolsface complexfinancialdecisions

thatrelatealmostexclusivelytotheirspending.InthisReport,weanalysethedegreeofvariationin

expenditureitemsbetweenschools,andexaminehowmuchofthatvariationisduetotheir

circumstances,andhowmuchreflectsspecificdecisionsmadebytheschool.Lastly,weconsiderthe

potentialforimprovementsinresourceutilisation.Althoughtheseissueshavebeenaddressed

before,mostoftheexistingliteraturefocusesonoverallschoolexpenditure.Thuswecontributeina

numberofways:

1. Byexploitinganewdataset,wecanexamineschoolsataverydisaggregatedlevelandisolate

someoftherealoperationaldecisionsthattheymakeonhowtoallocatetheirbudgets.Thenew

SchoolWorkforceCensuscoversallemployeesinallschoolsinthecountry,andincludes

informationsuchasage,payandtenure;

2. Wecontrolinconsiderabledetailfortheschoolscircumstancestoensurethatwearefocusing

onschoolsthatarefacingthesameoperationalenvironment;

3. Tobetterunderstanddiscretionoverexpenditure,weanalysewhatschoolsdowiththeir

residualincome.Thatis,incomewhichisnotaccountedforbytheircircumstances;

4.

Weusedataovertwoyearstoexaminehowschoolsadjusttheirspendinginresponseto

changesintheirincome.

ResultsCommentary

Ourresultsshowthatthereishugevariationintheallocationofexpenditurebyschools.Even

controllingingreatdetailforthespecificindividualcircumstancesofeachschool,muchofthat

variationremains.Forsomecomponentsofexpenditure,thedecisionsappeartobelargely

unexplainedbyanyobservablefeaturesoftheschool.Theresultsshowthatevenmanyofthe

importantoperationalfinancialdecisionsofschoolsarelargelyidiosyncratic.Thedegreeof

differenceinexpenditureissuchthatitseemsveryhardtointerpretthisasoptimalresponsestothe

differentperceivedlocalratesofreturntoparticularfactorsintheeducationproductionfunction.Of

coursemanyofourconclusionsarereliantontheSchoolWorkforceCensus,andouranalysisemphasisesthegreatimportanceofmaintainingthisnewlongitudinaldatabase.

Whydontschoolstakeamorestrategicapproachtotheirspending?Therewillbeanumberof

answerstothisquestion.Oneimportantfactorisconstraintsthatreducefreedomoverwhatto

spendincomeon.Inthepast,governmentshaveearmarkedmoneyforspecificinitiatives,thereby

allowingnoopportunityforlongtermplanningonthepartofschools.Theinteractivewhiteboard

fundingandExcellenceinCitieswereexamplesofthis.Implicitintheintroductionoftheseschemes

isthatschoolsarenottobetrustedinmakingchoicesaboutspending,andthatpolicymakersknow

howbesttospendtheschoolsbudget.Itwouldindeedbeinterestingtocomparethefinancial

decisionsofthoseschools,suchasacademies,thatarenowoutsidelocalauthoritycontrol.


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Anotherimportantsetofrestrictionscomesfromtheinstitutionalsettingaroundteacherpayand

conditions,negotiatedbetweentradeunionsandgovernment.Whilesomeoftheserestrictions

havebeenrelaxedinrecentyearsforsomeschools,therehasbeenlittlechangetodateinpractice.

Butperhapsmoreimportantthantheconstraintsisthelackofincentiveforschoolleaderstoget

spendingdecisionsright.Acarefulandconsideredallocationofspendingthatapproximatesan

optimalallocationmakeslittledifferencetoaheadteacherandher/hisleadershipteam,whotendto

befocusedonoverallpupilachievementanoutcomethatweknowreflectslittleoninput

decisions.Severefinancialmismanagementisobviouslyaseriousissue,butspending(say)three

timesasmuchascomparatorschoolsonsupportstaffisnot.

ThesimplestanswertothequestionHowcanweimproveschoolsfinancialdecisions?isMake

themmatter.Byusinginsightsfromeconomics,psychologyandbehaviouraleconomics,we

attempttoshedlightonthisquestion

Results

Summary

Theresultsshowthatthereisaverysubstantialamountofvariationinsomeexpendituredecisions

takenbyschoolsfacingasimilaroperatingenvironment.Thisappearstobethecaseinbothprimary

andsecondaryphases.Theresultsalsoshowthattheamountofvariationandthedegreetowhich

thesereflectrealdecisionsdiffersacrossawiderangeofoperationaldecisions.

Intheitemsthataccountforalargeshareofthebudgetthereisratherlessdisparity,butitisstill

nontrivial.Takingteachingexpenditureperpupil(whichaccountsforcloseto60%oftotal)asan

example,variationinthisexpenditureitemtranslatesintoagapofabout1000perpupilbetweena

schoolatthebottomquartile(25thpercentile)andaschoolatthetopquartile(75thpercentile).

60%ofthisvariationcanbeexplainedbythestructuralanddemographiccharacteristicsofthe

school,risingto70%ofvariationifweincludevariationintotalincome.Nevertheless,thisleaves

some30%ofthevariationinteachingexpenditureunexplainedoridiosyncratic.

Wealsoanalysemeasuresofdetailedoperationaldecisionsthatrevealtheschoolsdecisionmaking.

Thesearegenerallylessbudgetconstrainedgivingtheschoolsmorescopefordiscretion.For

example,wefindthat,controllingfortheschoolcontext,threequartersofthevariationinthe

numberofseniormanagersisidiosyncratic.Essentiallyequivalentschoolsaremakingverydifferent

decisionsonhowmanyseniorpositionstohave,alsoonthenumbersofsupportstaff,andsoon.

Themoredisaggregatedthefactoris,themoreidiosyncratictheexpenditurelevelsare.Accounting

ingreatdetailfortheschoolscircumstances,wecanexplainverylittleofthevariationsin

expenditureonseniorschoolleaders,supportstaff,Headteacherpay,teacherturnover,andthe

deploymentofteachersbysubject(thatis,howmanyhoursofasubjectaretaughtbyspecialists).

Thiscoincideswithouranalysisofunexplainedorresidualincome,whichsuggeststhatdiscretion

isprincipallyassociatedwithexpenditureonteachers,educationalsupport,theHeadteacherssalary

andtheschoollevelpaypremium.

Usingdatafrom20082010,wefindthatschoolsreactverydifferentlytochangesinincome.Only

42%ofsecondaryschoolsincreaseexpenditureonteachersaboveanyotheritem.Theremaining


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58%ofschoolschoosetoincreasethemajorityoftheirexpenditureonotheritems,orallowtheir

budgetbalancetochangethemost.

Introduction

EachyearschoolsinEnglandspendover30bnofpublicmoney.Putanotherway,thestatespends

over50kperpupiloverherorhistimeinschool,andthisexpenditureismanagedbyschools.

Schoolsaremuchmorethansimplyateamofteachersinclassrooms,withthetypicalsecondary

schoolemployingover100peopleofwhomonlyaroundhalfmightberegularclassroomteachers.In

theprivatesectoranorganisationwith100employeeswouldcountasamediumsizedfirm,andjust

likesuchafirm,schoolshavecomplexmanagerialdecisionstomake.

Thefinancialdecisionsthatschoolshavetotakearealmostexclusivelyabouttheirspending.Toa

largedegree,schoolssimplyreceiveincomeonthebasisofthenumberandcharacteristicsoftheir

pupils(thoughtoasmallanddecreasingextenttheycanalsoseekandreceivespecificgrantstodo

specificthings).Schools,byandlarge,thenspendwhattheyregivenalthoughasshownlaterinthis

report,someschoolschoosetobuildtheirbalancesratherthanincreaseexenditures,inresponseto

increasesintheirincome.Soananalysisofschoolsfinancialdecisionsisessentiallyabouthow

budgetsareallocatedbetweendifferentitemswithinaparticularyear.

Itshouldbeobviousthatitmattershowmoneyisspentonadditionalresources.TheDepartments

ImprovingEfficiencyinSchoolsnotes:Whatmattersisnttheamountofmoneyspentperpupil,but

howthatmoneyisspent(para11).Schoolshaveagreatdealofdiscretionoverexpenditureon

capitalandlabourinputs,butaretheyspendingthemoneyeffectively?Thereisalargeliteratureon

overallschoolexpenditureandschooloutcomes,andoncertainindividualspendingitemssuchas

numberofteachersperpupil,butmuchlessonanalysingthedetailsofschoolexpenditurepatterns

andtheextentofschoolsdiscretionoverexpenditure.

Thisreportisconcernedwiththevariationinexpenditurebetweenschoolsandthepotentialfor

improvementsinresourceutilisation.Itexploitsanewdatasourcetoanalyseatavery

disaggregatedlevel, howschools allocatetheirfinancialbudgetsbetweendifferentinputs.Weare

abletousethisnewdatasourcetoask:Howmuchvariationisthereinexpenditurepatternsfor

schoolswhichappeartobeinverysimilaroperationalcircumstances?Dotheiractionsrevealan

implicitagreementonbestpractice?Orisdiversityofresponsethekeymessage?

Weanalysethedegreeofvariationinexpenditureitemsbetweenschools.Thishasbeenaddressed

beforeforsomeheadlinespendingtotals,forexampleintheDepartmentspublicationImproving

EfficiencyinSchools(DfE,undated),andbytheAuditCommission(2011).Weaddtothisevidencein

anumberofways:

1.Mostimportantly,weexploitanewdatasetthatallowsustodrilldowntosomeofthereal

operationaldecisionsthatschoolsmakeonhowtoallocatetheirbudgets.Thisisthefirstfullsweep


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oftheSchoolWorkforceCensus,coveringallemployeesinallschoolsinthecountry.Thismeanswe

can,forexample,considerthefollowingfactors:

Expenditureonclassroomteachersandonseniormanagersperpupil;

Proportionofsupportstaffonshorttermcontracts;

Proportionofteachingstaffwithtenurelessthanoneyear;

AgeandpayoftheHeadteacher;

Proportionofteacherswithqualificationintheirmainteachingsubject;

Proportionofhoursofmathstaughtbyqualifiedsubjectteachers;

Estimatedschoollevelpaypremium.

2.Wecontrolinconsiderabledetailfortheschoolscircumstancessothatweareconfidentweare

focusingonschoolsthatarefacingthesameoperationalenvironment;

3.Weanalysewhatschoolsdowiththeirresidualincome,explainedbelow;

4.Welookathowschoolsadjusttheirspendinginresponsetochangesintheirincomeovertime.

Canweuseevidenceondifferencesinexpendituretoimproveschoolefficiency?Thisisdifficult

becausetheevidence(brieflyreviewedbelow)showsthatthereisatbestasmallandstatistically

weakrelationshipbetweenschoolsexpenditureandtheiroutcomes,thelevelofpupilattainment.

Thisisaproblemandapuzzle.

Itisaproblembecausetheallocationoflargergovernmentbudgetsistheusualmeansbywhich

governmentsattempttoimprovethepublicservicestheyvaluemost.Forexample,thefirstdecade

oftheLabourgovernmentintheUKproduceda56percentrealincreaseinschoolbudgetswithvery

largerisesforthemostdeprivedschools;yet,theempiricalevidencesuggeststhatthisattemptto

improveschoolsandtoclosethesocialclassgapinattainmentmaynotreachitspolicygoals.

Indeed,theincreasedexpenditurehasnotseenoutputsriseatthesamerate,andsoschool

productivityhasfallen(Wildetal.,2009).

Itisalsoapuzzle.Whydoesincreasedspendingnotnecessarilyraiseoutputsbymuch?Ittendstoin

othercontexts.Bydefinition,schoolsmustbespendingthemoneyineffectively.Aretheyspending

moneyonthewrongthings?Ifso,why?BeforethispublicationoftheSchoolWorkforceCensusit

wasnotpossibletoanalyseworkforcecompositionproperly,whichiscriticalinorganisationswhere

staffspendingaccountsforalmost80%ofcurrentexpenditure.Thisiswhywebelievethistypeof

analysisiscriticaltounderstandingopportunitiestoinfluencethebehaviourofschoolmanagers.

Thisreportcontributestotheanswertothispuzzlebyanalysingingreatdetailthethingsthat

schoolsbuy,andconsideringthepossiblereasonsbehindthepatternsthatemerge.

Ourresultsshowthatthereishugevariationintheallocationofexpenditurebyschools.Even

controllingingreatdetailforthespecificindividualcircumstancesofeachschool,muchofthat

variationremains.Forsomecomponentsofexpenditurethedecisionsappeartobelargely


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unexplainedbyanyobservablefeaturesoftheschool.Theresultsthereforeshowthatmanyofthe

importantoperationaldecisionsarelargelyidiosyncratic.Thedegreeofdifferenceinexpenditureare

suchthatitseemsveryhardtointerprettheseasoptimalresponsestodifferentperceivedlocal

ratesofreturntoparticularfactorsintheeducationproductionfunction.Ofcoursewedrawthese

conclusionsonthebasisofthedataavailabletousandouranalysisemphasisesthegreat

importanceofmaintainingthenewlongitudinaldatabaseonschoolworkforce,theSWC.

Ifwearecorrectinassertingtheimportanceofdecisionsmadelessreflectively,perhapsdecisions

arebetterunderstoodassimplycontinuingtodothingsthewaytheyhavebeeninearlieryears.If

weseeaschoolsexpenditurepatternasareflectionoftheaccumulatedandcontinuedidiosyncratic

decisionsofitsrecentpast,thenitiseasiertoseehowschoolsmanagedtodivergesomuchintheir

expenditure.

Ifschoolsareindeedspendingmoneyinalargelyidiosyncraticfashion,thenwhydonttheydo

somethingaboutthis,suchastakingamorestrategicandoptimisingapproachtotheirbudgetsand

spendingplans?Therewillbeanumberofanswerstothisquestion.

Oneimportantfactorisconstraintsthatreducefreedomoverwhattospendincomeonandthat

pushschoolstowardsineffectiveexpenditures.Inthepastgovernmentshaveplacedconstraintson

howmoneycanbespentthroughpiecemealmoneyearmarkedforspecificgovernmentinitiatives

withnoopportunityforlongtermplanningonthepartofschools.Theinteractivewhiteboard

fundingandExcellenceinCitiesareexamplesofthis.Implicitintheintroductionoftheseschemesis

thatschoolsarenottobetrustedinmakingchoicesaboutspending,andpolicymakersknowbetter

thanschoolleadershowtheschoolsbudgetisbestspent.

Anotherimportantsetofrestrictionscomesfromtheinstitutionalsettingaroundteacherpayandconditions,negotiatedbetweentradeunionsandgovernment.Whilesomeoftheserestrictions

havebeenrelaxedinrecentyearsforsomeschools,therehasnotbeenarushtoexploittherelease

fromthoserestrictions.Thatispossiblybecausethereareinstitutionalconstraintsonheadteachers

too,arisingfromthedifficultythroughoutthelabourmarketofimplementingnominalpaycutsor

forcingstafftoacceptreducedhours,forexample.

Butperhapsmoreimportantthantheconstraintsisthelackofincentiveforschoolleaderstoget

spendingdecisionsright.Acarefulandconsideredallocationofspending,approximatinganoptimal

allocation,makeslittledifferencetoaheadteacherandher/hisleadershipteamwhotendtobe

focusedonoverallpupilachievementanoutcomethatseemsverydistantfromresourceinputdecisions.Severefinancialmismanagementisobviouslyaseriousissue,butspending(say)three

timesasmuchascomparatorschoolsonsupportstaffisnot.

ThisissuehasalreadybeenhighlightedbyTheAuditCommission(2009),whonotethelackof

incentivesforschoolstobeeconomicalandefficient.Theysuggestschoolscouldachievebetter

valueformoneyasillustratedbythefactthatschoolsoftenholdexcessivebalances(greaterthan

8%and5%oftotalyearfundingforPrimaryandSecondaryschoolsrespectively),whichthey

considertobepoorvalueformoney.


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ThesimplestanswertothequestionHowcanweimproveschoolsfinancialdecisions?isMake

themmatter.WeprovideamoredetailedcommentaryonthisintheConclusion,bringingin

insightsfromeconomics,psychologyandbehaviouraleconomics.

Review

of

the

Evidence

Theoverallrelationshipbetweenschoolincomeandquality

Theimpactofschoolresourcesonschooloutcomesisacomplexandcontroversialone.Itseems

obviousthatmoreresourcesforschoolsshouldimprovepupilattainment,andanemphasison

providinggreaterfundingforschoolsisalmostagivenforpoliticalplatforms.Andyetthisobvious

propositionisnotingeneralstronglysupportedbytheevidence.Therelationshipbetweenmoney

andschoolqualityhasbeenshowntobeweak,bothinthegeneralcasewhereschoolsaregiven

moremoneytospendastheychooseandinspecificcaseswheregovernmentsdictatehowthe

moneyshouldbespent.Thisstatisticallysignificant,yetnotablysmall,associationhasbeenfoundinthefewstudiesthatdosupportcausalstatements.

ThesystemoffundingschoolsinEngland,withfundingdeterminedbypupilcharacteristics,makesit

almostimpossibletouseobservationaldatatoestimatethecausalimpactofresourcesonpupil

attainment.Thesimplecorrelationoffundinglevelsandaverageschoolattainmentisstrongly

negative,reflectingthegreaterresourcesdivertedtomoredeprivedschools.Evensimpleregression

analysisthatcontrolsforpriorattainmentandsocialbackgroundofthepupilstendstoreporta

negativeeffectoffundingduetounobservedschoolcharacteristics.However,severalstudiesinthe

UKandelsewherehaveattemptedtofindandisolatesomerandomorexogenouschangeinthe

levelofschoolresourcesandusethistomeasuretheresourceeffect.

TherecentstudiesintheUKhavefoundsucheffectstobesmall.Holmlundetal.(2008)exploit

randomdifferencesinhowlocalauthoritiesdistributetheirfundstoinvestigatetheimpactofextra

resourcesonKeyStage2examsinprimaryschools.Overall,theyfindthatanincreaseof1,000in

averageperpupilspendingwouldincreasetheproportionsofpupilsachievingexpectedlevelsatKS2

byaround2percentagepointsinEnglishandmaths.Levai etal.(2005)andJenkinsetal.(2006)

bothusethepoliticalaffiliationofthelocalauthorityasaninstrumenttopredictvariationinper

pupilspending,arguingitisnotrelatedtothedemographiccharacteristicsofpupilsinschools.They

findthatpositivebutverysmallimpactsofresourcesonKeyStage3andKeyStage4attainment,

respectively.

Morebroadly,inaseriesofliteraturesummariesHanushek(1986,1989,1996a,1997,1998,2003)

conductsametaanalysisofover400estimatesinmorethan50studiesintheliteratureand

invariablyconcludesthatresourcebasedpolicieshavebeenineffective,remarkinginhis2003study

Byconcentratingoninputsandignoringtheincentives,theresourceshaveyieldedlittleintheway

ofgeneralimprovementinstudentachievement.Hanushek(2004)suggeststhislackofrelationship

mayalsobeduetoteacherqualityandresourcesinteractingintheeducationproductionfunction,

withtheresultthatthereisnoconsistentbestpracticeintheresourcingofschools.Krueger(2003)

reanalysesthestudiesusedinHanushek(1997)butappliesdifferentweightinginhismetaanalysis

essentiallygivingonevotetoeachstudyasopposedtoonevotetoeachestimateineachstudy


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andconcludesthatreducingtheteacherpupilratiowasaneffectivewaytoimprovestandards.The

implicationsofKruegersstudyarethatresourcescanimproveeducationalstandardsifutilised

effectively.

Fortheremainderofthissection,wefocus onindividualitemsofschoolexpenditure.Aswillbe

evidence,forsometypesofinputtherearelargeliteratures,andamuchweakerevidencebasefor

theeffectivenessofexpendituresonothertypesofinput.

Classsize,thequantityanddeploymentofteachers

Theimpactofpupilteacherratiosonstudentperformancehasbeenextensivelystudiedinmany

countries.SomestudieshavebeenabletouseexperimentaldatasuchasintheTennesseeSTAR

experiment.Intheproject,theperformanceofstudentsinlargerclasses(2425students)was

comparedtothatofstudentsinsmallerclasses(1517students).Whilstthereisstillsome

controversyovertheclasssizefindingsintheSTARexperiment,oneoftheauthorsoftheoriginal

study

(Kreuger

and

Whitmore,

2001)

argues

that

Overall,

Project

STAR

indicates

that

reducing

class

sizeisareasonableeconomicinvestment:thebenefitsaresizeableandlonglasting,especiallyfor

blackstudents,andtheoverallbenefitsoutweighthecosts.(Schanzenbach,2006).Itisimportantto

notethattheexperimentandtheevidencerelateonlytoyoungpupils,injuniorelementaryschool.

Someinterestingnewresearchhowever,suggeststhatthereallessonofprojectSTARmightliein

teacherandpeergroupqualityratherthanclasssize(Chettyetal,2010).

TurningspecificallytoUKevidence,asetofstudiesusetheNationalChildDevelopmentStudy

(NCDS),acohortofindividualsbornin1958,toestimatetheimpactofclasssizesonattainmentand

stayingonrates.Theestimatedimpactsarealleitherzero(e.g.FeinsteinandSymons,1999;

Deardenet

al,

2002)

or

relatively

small.

For

example,

Dustmann,

Rajah

and

van

Soest,

2003,

find

a

onestandarddeviationincreaseinaverageclasssizedecreasestheprobabilitythatpupilsstayonin

educationbyabout4percentagepoints;Deardenetal.,2002,findsomewageimpactforwomen

only.

Thereisalittleevidenceontheimpactoflearningsupportandindividualisedlearning.Machinetal.

(2007a)useadifferenceindifferenceframeworktoanalysetheeffectsoftheExcellenceinCities

(EiC)programmeintheUKonKeyStage3outcomes.Theprogrammeallocatedadditionalresources

todisadvantagedschoolswithinparticipatingLocalEducationAuthorities(LEAs),withschools

requiredtospendthemoneyononeormoreofthreecoreareas:learningmentorstoovercome

educationalor

behaviour

problems;

Learning

Support

Units

to

provide

short

term

teaching

and

supportfordifficultstudents;aGiftedandTalentedprogramme,toprovideextrasupportfor510

percentofpupilsineachschool.Theauthorsfindthatovertimetheprogrammehadapositive

effectonschoolattendanceaswellperformanceinmathematics,althoughnotinEnglish.

Teacherquality

Evidenceonthelargevariationinteachereffectivenessmakesitclearthatalmosteveryschool

resourcingdecisionismarginalcomparedtolargepotentialgainsfromimprovingteacherquality(for

exampleAaronsonetal.2007andRivkinetal.2005intheUSandSlateretal.2009fortheUK).The

problemcomesintryingtoachievethosegains,sinceschoolsareunabletoobserveteacherquality;

particularlyatthetimeofhiring(Hanushek,2010).Howtoattracteffectiveteacherstoaschoolis


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oneareawheremoreresearchisclearlyneeded,butwedoknowthatteachers,likeallworkers,are

attractedtohigherwageopportunities,withstudiesconfirmingthatsalariesandworkingconditions

affecttheprobabilityofapplyingforajobandleavingaschool(e.g.,DoltonandVanderKlaauw

1999).Economistsarenowstartingtoquantifyclassroompracticesandcorrelatethesewith

measuresofstudentattainmentandteachereffectiveness(seeKaneetal(2010)andLavy,2011).

TeachingAssistants

ThenumberofTeachingAssistants(TAs)trebledfromaround60,000in1997overthenextdecade.

AsubstantialfractionoftheadditionalresourcesavailabletoschoolswasspentonTAs,inpartin

responsetotheWorkloadAgreementaimedatremovingsomedutiesfromteachers.Whiletoour

knowledgetherehavebeennorandomisedcontroltrialsevaluatingtheirrole,aseriesofstudies

thathavebeencarriedbyBlatchfordandothershaveconcludedthatthepresenceofTAshaslittle

directimpactonthegradesachievedbytheirpupils(Blatchfordetal(2007).Theremaybeindirect

effectsontheeffectivenessofteachers,forexamplemoreindividualisedteacherattentionbutitis

unclearwhetherthishasanymeasurableimpactonattainment.

Resources

Machinetal.(2007b)usesaninstrumentalvariablestrategytoinvestigatetheeffectofICT

investmentoneducationalstandardsandfindsapositiveimpactofincreasedICTexpenditureon

primaryschoolperformanceinEnglishandScience(butnoeffectinMaths).Thiscontradictsthe

previousliteraturewhichtendstofindnoeffectofextraICTfunding(AngristandLavy(2002),Fuchs

andWoessman(2004),GoolsbeeandGuryan(2006)).OfparticularnoteisLeuvenetal.(2004),

whichusedaregressiondiscontinuitydesignframeworktoanalysetheeffectofapolicyinthe

Netherlands.Thepolicyprovidedprimaryschools(whereatleast70percentofethnicminority

pupilsor70percentwerefromdifferentdisadvantagedgroups)withextrafundingforpersonnel

andcomputers(andsoftware)respectively.Theyfindnoeffectoftheadditionalpersonnelfunding

onattainmentandfindevidenceofnegativeeffectsofthecomputersubsidy.Theauthorsdoexplain

intheirconclusionthatthepersonnelfundingwasunlikelytoreduceclasssizes(duetolowpupil

teacherratiosinpredominantlyminorityschoolsalready).


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Data

Ouranalysiscombinesfourdatasets,Edubase,theNationalPupilDatabase(NPD),theConsistent

FinancialReporting(CFR)accountsdatabaseandthefirstfullcollectionoftheSchoolWorkforce

Census(SWC). Thedataislinkedusingtheschoolestablishmentnumberwhichiscommonacrossall

datasets.OurcriteriaforinclusionissimplythattheschoolmusthaveeitheranSWCrecordin

November2010oraCFRrecordfor2009/10.Manyschoolsweincludedonothaveboth:notably

academiesarenotrequiredtosubmitCFRaccountsandnewlyopenedschoolsinSeptember2010

willnotyethaveCFR.WecategoriseallschoolsaseitherprimaryorsecondaryusingtheDfE

standardapproachfornonstandardentryschools.Allspecialschoolsareexcludedfromthe

analysis.

NationalPupilDatabaseandEdubase

Edubasecontainsanadministrativerecordforallschools,whethermaintainedorprivate,inEngland.Weusethistoconstructinformationonthestructuralcharacteristicsofeachschoolsothat

weareabletocompareschoolstosimilarschoolsinouranalysis.Thedistributionofthestructural

factorsweusefromEdubasearesummarisedinDataAppendixTable1andinclude:

governmentregionindicators(withadditionalindicatorsfortheInner,OuterandFringeLondon

payregionssincetheseareimportantunavoidablefactorsthatdeterminecostsforaschool);

fourindicatorsforwhetherschoolisrural,inavillage,townordenseurbanarea;

schoolagespan(highestandlowestagesofpupils);

schoolgovernancetypeandwhetheritisasinglesex,grammarorboardingschool;

thenumberoffulltimeequivalentpupils(alsosquared,cubedandtopowerfour)andalsotheofficialschoolcapacity;and

nurseryschoolpresenceindicatorandsize,sixthformindicatorandsize.

WeusetheNPD,aDfEadministrativedatabaseofallpupilsinstatemaintainedschoolsinEngland,

tomeasurethedemographicbackgroundoftheschool.TheNPDcontainsawiderangeof

informationonpupilcharacteristicsincludingtestscorehistories,ethnicityandage.Pupil

characteristicsandtesthistoriesareaggregatedattheschoolleveltoallowustogroupsimilar

schoolstogether.ThedistributionofthedemographicfactorsweusefromtheNPDaresummarised

inDataAppendixTable2andinclude:

fractionsofpupilswithEnglishasanadditionallanguage;

thefractionandtypeofspecialeducationalneedsofpupilsattheschool;

theproportionfemale(alsosquared)andethniccompositionoftheschool;

thefractionofpupilseligibleforfreeschoolmeals(alsosquared);

measuresoftheaverageneighbourhooddeprivationoftheschoolspupils(alsosquared);

themeanpriorattainmentofpupilsinmathsandEnglishattheschool(usingKeyStagetwo

scoresforsecondaryschoolsandFoundationStageprofilemeasuresforprimaryschools)


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ConsistentFinancialReporting200910

DfEhaspubliclyreleasedtheCFRaccountsfor2009/10infullforthefirsttime.Thedatacontains

informationonincomeandexpenditureinallstatemaintainedprimaryandsecondaryschoolsin

EnglandwiththeexceptionofAcademies.Theincomeandexpendituredataaresplitinto17and32

categoriesrespectively;allexpenditureorincomeofaschoolisincludedinexactlyonecategory.Duetothelimitednumberofstreamsofincomeschoolsreceive,theincomecategoriesare

generallyspecific(e.g.incomedelegatedbytheLA,SENFunding,andsoon),whereasthe

expenditurecategoriesoftencompriseofmanysimilaritemsgroupedtogether(e.g.teaching

assistants,learningmentorsandbehaviouralmanagersstaffcostsareallgroupedintotheeducation

supportstaffcategory).

SomeitemsintheCFRarecensoredwhentherearesmallnumbersofemployeesinaroleinaschool

orwhenschoolsspend(orreceive)lessthansomethresholdinastaffrelatedcategory.Asaresultof

thisthereisamissingdataproblemforsomeprimaryschoolsbutsecondaryschoolsremainlargely

unaffected.Duetothelimitationsofthedata,whenwewishtoconductanalysisonspecificroles(e.g.expenditureonteachingassistantsorseniormanagementstaff)wemustrefertotheSWC

dataset,describedbelow.

WeuseCFRdataintwowaysinouranalysis.Firstly,weoftenwanttocompareschoolswithsimilar

incomesandwherewedothisweusethetotalincomefromallsourcesperpupil,withpowersof

two,threeandfourincludedwhererelevant.Secondly,wecreateaseriesoffinancialcharacteristics

oftheschoolthataresummarisedinDataAppendixTable3andinclude:

Totalincomeperpupil;

Totalexpenditureperpupil;

Teachingexpenditureperpupil;Expenditureoneducationsupportperpupil.

SchoolWorkforceCensus

TheSchoolWorkforceCensus(SWC)isindividualleveldataonallstafffromlocalauthorities,state

maintainedschoolsandacademiesinEngland.ThecensuswastakeninNovember2010andthisis

thefirstyearinwhichthecensushasincludedallschools.Theunitofobservationisanindividual

role,soitispossibleforanindividualwhoisbothaclassroomteacherandDeputyHeadtohavetwo

observationsinthedata.However,theredoesnotappeartobeconsistenttreatmentofthesplitting

ofrolesacrossschools.

ThefullSWChas1,292,494observationsfrom21,423primaryandsecondaryschoolsincluding

informationonover400,000teachersand270,000teachingassistants.Thecensusincludescontract

informationsuchasthestartandenddate,hoursworked,annualpayandallrolesanindividualhas

withinaschool(teacher,headofdepartment,lunchtimesupervisoretc.)aswellasanindicatorfor

whetherthememberofstaffisemployedbythelocalauthorityortheschooltheyareworkingat.It

alsoincludespersonalcharacteristicssuchasdateofbirth,genderandethnicity.Thedataincludes

anindicatorofwhetherateacherhasattainedqualifiedteacherstatus(QTS);informationonother

qualificationssuchassubjectstudiedandthelevelofthequalification(degree,PGCEetc.);and

informationontheamountoftimespentintheclassroomteachingeachsubject.


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13

TherearetwomajordataqualityproblemswithSWC:somevariablesaremissing,andforother

variablesincluded,thereareapparentlymissingobservations.Themissingnessonvariablesisa

particularproblemforindicatorssuchasteachersqualification(65%missing)andsubjectstaughtin

theclassroom(68%missing).AlthoughtheSWCincludesinformationonallstaff,detailedpay

informationwasonlymadeavailableforteachers(includingheadteachers)andteachingassistants.

Asaresultofthispayinformationismissingforaround90%ofsupportstaffand10%ofteaching

assistants.Theverylargevariationinstaffpupilratiosacrossschoolsleadustosuspectthatsome

schoolshavefailedtosubmitareturnforeverymemberofstaffandthisshouldbeborneinmind

duringtheanalysissection.ThismayalsobeanaspectforfuturewavesofSWCtotightenupon.

WeuseSWCtocreateaseriesoffinancialandoperatingcharacteristicsoftheschoolthatare

summarisedinDataAppendixTable3andinclude:

Expenditureonclassroomteachersperpupil,definedasthesumofgrosspay,adjustedbyfull

timeequivalentindicators,forclassroomteacherswhoarenotassistant,deputyorhead

teachers;

Expenditureonseniormanagementperpupildefinedasthesumofgrosspay,adjustedbyfull

timeequivalentindicators,forassistant,deputyandheadteachers;

Number(FTE)ofseniormanagersinschool;

Proportionofteachingstaffunderage30;

Proportionofteachingstaffwithqualifiedteacherstatus(QTS);

Proportionofsupportstaffonshorttermcontracts;

Proportionofteachingstaffwithtenurelessthanoneyear;

AgeoftheHeadteacher;

PayoftheHeadteacher; Proportionofteacherswithqualificationintheirmainteachingsubject;

Proportionofhoursofmathstaughtbyqualifiedsubjectteachers;

ProportionofhoursofEnglishtaughtbyqualifiedsubjectteachers;

Proportionofhoursofsciencetaughtbyqualifiedsubjectteachers;Estimatedschoollevelpay

premium,calculatedbyaveragingacrosstheschooltheresidualfromateacherpayregression

thatcontrolsforyearsoftenure(includingsquaredandcubed),sex,age(inaveryflexibleform),

whetherQTS,whetherparttime,phaseofeducation.


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14

ResultsSummary

1.Thefocusofouranalysisisonthedegreeofvariationinexpendituredecisionsandonhowmuch

ofthatvariationisduetotheschoolsoperatingenvironment,broadlydefined,andhowmuch

reflectsidiosyncraticdecisionsmadebythatschoolthatcannotbeexplainedbyobservablefactors.

Wedothisforseventeendifferenteducationalparametersthattheschoolhasleverageoverand

whichmightbeexpectedtobeimportanttotheschoolseffectivenessinraisingattainment.

2.Theresultsbelowshowthatthereisaverysubstantialamountofvariationinsomeexpenditure

decisionstakenbydifferentschools.Thisistrueinbothprimaryandsecondaryphases.Theresults

alsoshowthattheamountofvariationandthedegreetowhichthesereflectrealdecisionsareboth

differentacrosstherangeofoperationaldecisionswemodel.

3.Intheitemsthataccountforalargeshareofthebudgetthereisratherlessvariation,butitisstill

nontrivial.Takingteachingexpenditureperpupil(whichaccountsforcloseto60%oftotal)asanexample,itsstandarddeviationis13.5%ofthemeanvalueof3,043insecondaryschools.This

translatesintosubstantialvariationwithagapofabout1000perpupilbetweenaschoolatthe

bottomquartile(25thpercentile)andaschoolatthetopquartile(75thpercentile).60%ofthis

variationcanbeexplainedbythestructuralanddemographiccharacteristicsoftheschool,risingto

70%ofvariationifweincludevariationintotalincome.Nevertheless,thisleavessome30%ofthe

variationinteachingexpenditureunexplainedoridiosyncratic.

4.Attheotherendofthescale,weanalysemeasuresofdetailedoperationaldecisionsthatreveal

theschoolsdecisionmaking.Thesearegenerallylessbudgetconstrainedgivingtheschoolsmore

scopeforchange.Forexample,thenumberofseniormanagersinaschoolvariesenormously,withtheinterquartilerangeforallsecondaryschoolsexceedingthemean(of17).Controllingforthe

schoolcontext,wefindthatthreequartersofthisvariationisidiosyncratic.Essentiallyequivalent

schoolsaremakingverydifferentdecisionsonhowmanyseniorpositionstohave,alsoonhowmany

supportstafftohave,andsoon.

5.Ourresultsshowthatthemoredisaggregatedthefactoris,themoreidiosyncraticthe

expenditurelevelsare.Accountingingreatdetailforschoolcontext,wecanexplainverylittleofthe

variationsinexpenditureonseniorschoolleaders,supportstaff,Headteacherpay,teacherturnover,

andthedeploymentofteachersbysubject(thatis,howmanyhoursofasubjectaretaughtby

specialists).

6.Ouranalysisofunexplainedorresidualincomesuggeststhatthisisprincipallyassociatedwith

expenditureonteachers,educationalsupport,theHeadteacherssalaryandtheschoollevelpay

premium.

7.Schoolsreactinverydifferentwaystochangeinincomebetweentwoyears.Only42%of

secondaryschoolsincreaseexpenditureonteachersmorethananyotheritem.Theremaining58%

ofschoolschoosetoincreaseexpenditurethemostonotheritems,orallowtheirbudgetbalanceto

changethemost.Essentially,almosteverypossibledecisiononexpenditurechangeisobserved

somewhereinthedata.


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15

DetailedResults

Wefirstcharacterisethedifferencesinschoolsdecisionsontheirspendingpatterns.We

supplementthatwithananalysisofhowtheresidualincomeschoolsreceiveisspent,andan

analysisofhowachangeinincomeisallocatedacrossspendingitems.

Part1:Howmuchvariationinspendingisthereforlikeschools?

Inthismainbodyofanalysisforthereportweanalysethevariationinschoolexpenditurepatterns

forschoolsfacingverysimilarcircumstances..Weanalyseschoolexpenditurepatternsforthe17

variablesderivedfromCFRandSWCthataredescribedinthedatasection.Thequalityofthedatain

SWCrestrictstheindicatorsweareabletocreatefromit.Forexample,thedataonthegrosspayof

teachingassistantsandonthenumberofteachersandteachingassistantswasnotofsufficiently

goodqualitytouse.Otherssuchasthegrosspayofteachers,seniorstaffandthequalificationsof

teachersarelikelytohaveconsiderableinaccuraciesandthisshouldbeborneinmindwheninspectingthedistributionofthesevariables.

Methodology

Wedescribetheamountofvariationineachvariableofinterest,separatelyforprimaryand

secondaryschools,throughaboxplotandreportsofthemeanandstandarddeviation.Ineachchart

weprovidedataonallschoolstakentogether,andalsoongroupsofschools.Itneedstobe

emphasisedthatwhenweconsiderlikeschoolswecontrolinfargreaterdetailfortheschools

circumstanceswithineachofthesegroups.Thegroupsare:

Allschools

Largeandsmallschools;schoolseithersideofthemediansize(separatelyforprimaryand

secondaryschools);

Disadvantagedschoolsandnondisadvantagedschools;schoolseithersideofthemedian

percentageofstudentseligibleforFSM(separatelyforprimaryandsecondaryschools);

LondonschoolsandnonLondonschools.

Wealsoconsideredasplitbyschoolperformance,definedintermsofexamresults.Thekeyisthat

schoolsize,locationanddegreeofdisadvantagearegenerallyfixedformostschoolsandcanbe

thoughtsofasgiven.Obviouslythereissomeyeartoyearvariationinthepercentageofstudents

eligibleforFSMandinthenumberofpupils,butitisveryrareforschoolstodramaticallychange

theircategoryhere.Thuswecanusethesegroupsasasoundbasisforthebriefofthisstudytrying

tounderstandschoolsfinancialdecisionsonthebasisofthereasonablyfixedcharacteristicsofthe

school.Asweaddfurtherexplanatoryvariablesinthemodel,whilewecertainlydonotmakeany

strongclaimofcausality,thesevariablesarenotobviouslyoutcomemeasures.However,asplitby

schoolperformanceisclearlyanoutcome,andislikelytodependdirectlyontheexpenditure

variationsweareanalysing.Thisdirectendogeneitywouldmakeanyinterpretationofsuchfigures

extremelyproblematic.Itwouldbeatleastasmuchaboutunderstandingschoolacademic

performanceasunderstandingschoolfinancialdecisions.Thisisthereforecompletelydifferentto

ourchoiceofthethreegroupings,andourviewisthataperformancesplitwouldnotbehelpful.


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Theboxplotisastandardtoolforgivingasenseofthedegreeofvariation.Itdisplaysthemedian,

andtheupperandlowerquartilesofthedistribution,thusshowingbothvariation(theinterquartile

range,IQR)andlocation(wherethemiddlehalfofthedatalie).Inadditiontheboxplotalso

indicatesthelocationofpointsfurtheroutfromthebulkofthedata.Thelinesextendingfromthe

boxfinishattheupperandloweradjacentvalues.Theupperadjacentvalueisthelargest

observationthatislessthanorequaltothethirdquartileplus1.5*IQR.Theloweradjacentvalueis

thesmallestobservationthatisgreaterthanorequaltothefirstquartileminus1.5*IQR.Outliersare

allvaluesthatfalloutsideeitherofthesepoints,andtheplotshowssomeoutliervaluestooto

illustrateveryextremeoutcomes.

Nexttoeachboxplotwesummarisehowmuchvariationinthevariableofinterestisexplainedby

schoolsstructuralfactors,thedemographicprofileoftheschools,andtheschoolsactualincome.

Wewanttodothistoassesshowmuchvariationisduetotheschoolscircumstancesandhowmuch

istheresultofdiscretion,decisionsthatschoolshavetakenonhowtodeploytheirresources.Todo

this,wepresenttheR2statisticfromaseriesofregressions,foreachvariableofinterest,foreach

groupandforprimaryandsecondaryschools.TheR2statisticmeasureswhatpercentageofthe

variationinthedependentvariableisaccountedforexplainedbytheexplanatoryvariable.Ahigh

value,closeto100%,showsthatthereislittlediscretionandmostofthedifferencesbetween

schoolsintheirspendinginthisparticularcategoryaresimplydrivenbytheirobservable

characteristics.AvalueoftheR2nearzerosuggeststhatdifferencesinexpenditureareessentially

idiosyncraticthatschoolsinthesamecircumstancesarespendingverydifferentamounts.TheseR2

statisticsarethereforekeyinansweringthequestionweareaddressinghere.WeuseR2ratherthan

(Rbar2)becauseweareinterestedinthetotalcumulatedexplanatorypowerofallthevariables

atourdisposal.

Foreachexpenditurevariableandeachschoolgroupwerunthreeregressions.Thefirstis

conditionalonwhatwecallstructural(S)factors,thesecondregressionaddsdemographic(S&D)

factors,andthethirdaddstheschoolsincome(S,D&I).Asdescribedinthedatasection,the

structuralfactorsarecreatedfromEdubaseandincludesizeandtypeofschool.Thedemographic

factorsarecreatedfromNPDandincludetheaveragepriorattainmentandaveragesocial

characteristicsofthepupils.TheschoolincomefromCFRistotalincomefromallsourcesperpupil,

withpowersoftwo,threeandfourincluded.

Theideaisthatwewanttoisolateandremovevariationconditionalonunavoidablestructural

characteristicsthat

impose

costs

on

the

school.

Second,

we

want

to

also

take

out

variation

conditionalondemographiccharacteristicsthatschoolsneedresourcestohelpdealwith1

.Finally,

wewanttoconditionontheincomethatschoolsactuallyreceive,givingthemtheopportunityto

spendmoney.

Thereareanumberofpreliminarypointstomakeabouttheseregressionsthatapplytoallthe

chartsbelow.First,weexpectthatingeneralthefinalregression,whichaddsactualincomeontop

ofstructuralanddemographicfactors,willnotaddagreatdealofexplanatorypower.Thismay

1Obviously,thesecharacteristicsarenotexogenousandareinpartafunctionoftheschoolsdecisions;so

thesearenottobethoughtofasfullycausalcostfunctionestimates.

16


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17

seemcounterintuitivesinceincomeconstrainsexpenditure,buttheschoolsincomedependsquite

heavilyonthesestructuralanddemographicfactors,andthereforeimplicitlythesecondregression

iscontrollingforexpectedincome.SotheinterpretationofthefinalR2ishowmuchmoreofthe

variationinexpenditurecanweexplainifweknowtheschoolsresidualincomeaswell.Becauseof

theimportanceofthisissue,weundertakeamoreexplicitanalysisofthisinpart2oftheResults.

Second,addingfurtherexplanatoryvariableshastoalwaysincreaseexplanatorypower.Intermsof

theregressionsthen,thevalueoftheR2shouldalwaysincreasefromthefirst(S)tothethird(S,D&

I)regression.Inpracticethisdoesnotalwayshappenasthesamplevaries,particularlywhenweadd

income(whichismissingfornewschoolsandacademies).Wechosetoallowthistohappenandto

maintainthemaximumsampleperregressionratherthanusearestrictedsampleacrossall

specifications.

Results

Wepresentouranalysisofvariationinexpenditure,demonstratingdifferentapproachesto

measuringparticularexpenditureitems.Ourfirstresultsareforoverallexpenditure,andthenshow

resultsforteachingstaff,seniormanagementteamsandsupportstaff.

Variationintotalincomeandexpenditure

Incomeisclearlynotanexpenditureitembutweincludeitheretobenchmarktheoverallamountof

variationintheresourcesavailabletoschools.Followingtheapproachinthemethodology,Figure1

combinestheboxplotsoftotalincomeandtheR2resultsof3regressionspergroup.

Lookingfirstatsecondaryschools,thelevelsofincomeareasexpected:higherinpoor,smalland

Londonschools(thereisobviouslysomeoverlapbetweenthesecategories).Thereisalsomuch

greatervariationinincomeperheadamongsmallschoolsandschoolswithhigherfractionsofpoorpupils.Theregressionanalysisshowsthatabouthalfofthevariationinincomeisduetostructural

factors,ratherlessinlargeandnondeprivedschools.Demographicfactorsaddanother20

percentagepoints(ppts)orso.Overallabout30%ofthevariationinincomeperpupilisunrelatedto

structuralordemographicfactors(thethirdcolumnis100%byconstructionasincomeisregressed

onincome).NotethatinlowFSMschools,demographicsaddverylittleexplanatorypoweratall,

andingeneralgroupswithhighervarianceofincomeperpupilalsoseeahigherfractionexplained

bythefactors. Inprimaryschoolsweseemuchthesamepatternsthoughperhapsslightlyless

marked.

Onereasonthevariationinincomeissogreatandisunexplainedbytheschoolscurrentdemographicandstructuralcharacteristicsisthathistoricallevelsofschoolfundinghavealways

beenusedtodeterminecurrentlevelsoffunding.Thishasbeenparticulartrueoverthepastdecade

becausestabilitymechanismswereintroducedtoprotectschoolsfromlargefallsinincome

(Chowdryetal.,2010).Twomechanismsareresponsibleforincreasinginertiaanddiminishing

responsivenessofschoolfundingtochangingneeds.TheMinimumFundingGuarantee(MFG)

guaranteeseachschoolaminimumincreaseinfundingperpupileachyear,thusreducingtheimpact

oflocalauthoritiesfairfundingformulae.Thespendplusmethodologycurrentlyusedbymost

localauthoritiestodeterminedistributionofgrantstendstofavouraflatrateincreaseonprevious

yeardistributions,plusanextraincreasedeterminedonthebasisofaformula.Whilethereissome


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(Notethatintheregressionsample,theoverallmeaneffectiszero,butisnothereasschoolshave

hadtobedroppedfromthisanalysissample.)

Figure18showsthatthereislittledifferenceintheaveragepaypremiumotherthanforLondon

schools,butsomevariationwithingroups.Theoverallstandarddeviationof2.5kissmallrelativeto

meanteacherpayofaround40k.Thisisperhapsnotsurprisinggiventheveryhighuseofthe

standardteacherpayscales.Abouthalfofthisvariationisexplainedbystructuralanddemographic

factorsandbyincome,sothereisevidenceofsomeuseofdiscretioninthis.

Thereareanumberofmeasuresforthelikelylevelsofqualificationsandexperienceoftheteacher

workforce.Firstly,Figure9showstheproportionofteacherswithqualifiedteacherstatus(QTS).

Thereisverylittlevariationinthisacrossschools.Theaveragesareallinthehigh90s,andthereare

onlyoutliersbelow90%.ThisisslightlylesstrueinLondon,andindeprivedschools.

Figure8showstheproportionofteachingstaffunderage30andFigure11showstheproportionof

teacherswithtenurelessthanayear.BoththesemightactasgoodproxiesforteachersoverallexperienceintheabsenceofaSWCvariablethatmeasurestotalnumberofyearsinteaching.In

Figure8therearesmalldifferencesbetweengroupaveragesandrelativelylessvariation.Thereis

morevariationandmostlyunexplainedamongprimaries.Theseschoolsaresmallersomore

susceptibletorandomvariationinteacherage.

Figure10showstheproportionofnonteachingstaffonshorttermcontracts,butagainwehave

concernsaboutthedataqualityhereintheSWCasmuchofthisinformationisnotreported.The

meanis91%inallthegroupsinsecondaryschoolsandalittlebitlowerinprimaries.Overall,thereis

littlevariation.

TheshorttenurevariableshowninFigure11includesseniormanagementteamteachers.Quite

differenttowhatmighthavebeenexpectedgivenreceivedwisdom,wefindverylittlevariationin

theaveragesbetweenthegroupsofschools.Forexample,thereareonlyslightlymoreshorttenure

teachersinhighpovertyschoolsthanlow.Thisisafindingthatweconfirminourmoreextended

investigationoftenuredistributions.Thereisalsoquitealotofvariationwithingroupsandvariation

ismarginallygreateramongsmallschoolsandpoorschools.Thevariationisnotexplainedbythe

structuralfactors,norexplainedbydemographics,norincome(again,notethatthesamplevaries

considerablyinthefinalcolumnexplainingthefallintheR2).

Schoolsthathavedifficultyrecruitinggoodteachersmightbeexpectedtohavehighproportions

teachinginasubjectthattheydonotpossessaqualificationin.Herewedonotdistinguishbetween

thesubjectstudiedatundergraduateandtheteachertrainingspecialistsubject.Therearefewer

observationsforthesevariablesbecausesomeschoolsdidnotfillinthequalificationsand

curriculumpartoftheCensus(whichappliestosecondaryschoolsonly).

Figure14showstheproportionofteacherswithaqualificationintheirmainsubject.Thereisa

considerablerangeinthedatatakingschoolsasawhole,therangebetweentheupperandlower

adjacentvaluesisover60percentagepoints.Thereislessdifferenceinthemeanbetweengroups.

Thisisnotstraightforwardtointerpret:itisnotsimplyastatementaboutthequalificationsofthe

teachers,butalsoaboutthechoicestheschoolshavemadeabouttheircurriculum.Forexample,the


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20

relativeimportanceofcoresubjectsagainstmorespecialistsubjects(suchasphotography,or

citizenship).

Figures15,16and17showtheproportionofpupilhourstaughtbyspecialistteachersinmaths,

Englishandscience,respectively.Againthereisasmallersampleofschoolshere.Thelevelsare

lowerinsmallschools,typicallytheywillneedmoreflexibleteachersandfewerspecialists.Figure17

showsthatthereareslightlymorespecialistsinscience.Thereisconsiderablevariationwithinallthe

groupswiththeinterquartilerangecoveringmuchoftheentirerangeofdata.Nomorethana

quarterofthevariationisexplained.

Variationinseniormanagementdeployment

WeareabletouseSWCtodistinguishbetweenstandardclassroomteachersandseniormanagers

suchasassistant,deputiesandheadteachers.Thedataqualityisnotashighaswewouldlikeitto

beandasaresultwecannotreliablyassesshowmuchtimetheseseniorteachersspendinthe

classroomasopposedtoonmanagementduties.Figure6showsthevariationofexpenditureon

seniormanagers,calculatedfromthegrosspaydatainSWC.Unfortunatelymanyindividualshave

paydatamissingoratafigureofzero,whichmayexplainwhythereisagreatdealofvariation

betweenschoolsthatismostlyunrelatedtotheschoolscircumstances.

Themeasureofnumberofseniormanagers(fulltimeequivalents)showninFigure7ispossibly

morereliableasitdoesnotusethepatchypaydata.Itisnotscaledthisisliterallythe(FTE)

numberofseniormanagerssothereareboundtobemoreinbigschools,althoughsizeis

controlledforinthestructuralfactors.Theresultsshowverysubstantialvariation,thestandard

deviationisapproximatelyequaltothemean.Onlyaboutaquarterofthevariationisexplained,so

againidiosyncraticdecisionsareveryimportant.Therearefewerseniormanagersandthereisless

variationinprimaryschools,principallyasprimariesarealotsmallerandhavefewermanagement

jobtitlestohandout.

WeareinterpretingageofheadteacherasproxyforexperienceinFigure12.Dataqualityishigh

withveryfewmissingvalueshere.However,thereareanumberofambiguouscasesonwhoisthe

schoolheadteacher.Inthesecaseswehavetakenthehighestpaidpersondesignatedas

headteacherwhoisworkingattheschoolforatleast50%FTE.Remarkably,therearenodifferences

inthemeanageacrossthesecategories,noralotofvariationwithineachgroup.Itisthesamestory

inprimaryschools.Essentiallynoneofthevariationisexplained.Thiscanbeinterpretedassaying

thatchoosingtoemployexperiencedorinexperiencedheadteachersseemstobeadecisionthat

schoolstakeinanunsystematicwaytheyarenottypicallymoreexperiencedinbiggerorpoorer

schools,orasexplainedbyanyofthefactorsincludedinourregressorgroups.

Thereisareasonableamountofdiscretiononthepayscaleastohowmuchgovernorschooseto

paytheirheadteachers.Figure13showsthevariationinthisheadteachersalary.Itisarawsalary

figurethatdoesnotcontrolfortheheadteacherpersonalcharacteristics,age,qualifications,andso

on.Nordowecontrolforschoolperformanceotherthanindirectlythroughthedemographics.

Thereareanumberofinterestingpointshere.Therearebigdifferencesbetweengroups:salaries

arehigherinlargeschoolsthansmall,higherinLondonthanoutside,thoughdisadvantagedand

nondisadvantagedschoolspayaboutthesame.Thereisconsiderablevariationwithingroupstoo

withastandarddeviationof16kinsecondaryschools,andmanyveryhigh(andlow)values.


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Overall,abouthalfofthisvariationisidiosyncratic,thoughthisfractionishigherinthehighvariation

groups.Forexample,inlargesecondaryschools,only27%ofthevariationisexplained.Again,the

patternisthesameinprimaryschools,thoughtheR2ishigher.


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Part2:Howistheresidualincomethatsomeschoolsreceivespent?

Adifferentwayofconceptualisingschoolsdiscretioninspendingistoconsiderhowtheyspendthe

incomethattheyhavethatisnotaccountedforbytheircircumstances.Wedescribethisastheir

residualincomebutitcouldequallybecalledunexpectedincomesincethetypicallikeschooldoes

notreceivethismoney.Onereasonthatthisresidualincomemightbeinterestingisthatitmighttellussomethingaboutthemarginaldecisionsschoolsmakeaboutspendingtheirlastpounds.So,it

mighthelpusunderstandwhathappensifaschoolisgivenalittleextramoney.

Wecalculateresidualincomebyregressingeachschoolstotalincomeonthestructuraland

demographiccharacteristicsdefinedabove,andextractingtheresidualfromtheregression

estimates.Wethenregresseachexpenditureitemwedefinedaboveonthisresidualincomeandall

thestructuralanddemographiccharacteristicsdefinedabove.Ineachregressionweusethe

coefficientonresidualincomeasameasureofhowtheextrapoundofincomeisspent.Aswe

noted,thisexerciseissimilartocomparingtheimpactontheR2ofaddingincometotheregressions

above,butherewefocusonwhichitemsseethegreatestchangeinexpenditure.

Table1columnApresentstheresultsoftherelationshipbetweenresidualincomeandexpenditure

itemsinsecondaryschool.Foreachexpenditureitem,wepresentinthetablethecoefficienton

residualincome,theestimatedstandarderrorandtheR2.Theremainderofthecoefficientsarenot

presented.

Thetoprowfortotalexpenditurehasacoefficientcloseto1,asitshouldhave.Thisimpliesthat

almostalltheresidualincomethatisgiventoaschoolisspentinthatyear.Manyotherexpenditure

itemshaveestimatesclosetozero,buttheitemswithsubstantialandsignificantcoefficientsare:

Expenditureonteachingstaffwherethecoefficientis0.2,meaningthatforevery1ofresidual

incomeaschoolgets,theyspendabout20ponteachingstaff;

Expenditureoneducationalsupportwherethecoefficientis0.08or8pinevery1ofresidual

incomereceived;

ExpenditureonclassroomteachersintheSWChasacoefficientof0.1implyingthatonly10pina1

ofresidualincomeisspentonclassroomteachers;

ExpenditureonseniormanagementintheSWChasacoefficientof0.01implyingthatonly1pin1

is

spent

here

(though

note

our

concerns

about

data

quality);

Schoollevelpaypremiumcoefficientis0.29,suggestingthataboutathirdoftheresidualincomeis

associatedwithahigherpaypremiumintheschool.

ThepayoftheHeadteachercoefficientis1.9.Takenliterally,thismeansthatmorethantheextrais

spentontheHeadteacherssalary.However,theseregressionsarenotintendedtobeunderstoodas

causal,theysimplymeasureassociation.Forexample,itcouldbeinpartthathighlypaid

Headteacherscanattractmoreincome.Also,bothcurrentresidualincomeandcurrentstaffing

structuresmightbeexplainedbyhistoricalincomeandstaffingstructures.


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Table1columnBpresentsthesameanalysisforprimaryschools.Weseeasimilarpatternhere,

thoughwithsomeinterestingdifferences.Themoresubstantialcoefficientsare:

Expenditureonteachers(0.32)

Expenditureoneducationsupport(0.18)

ExpenditureonclassroomteachersintheSWC(0.13)

Expenditureonseniormanagement(0.07)

ThepayoftheHeadteacher(1.38)

Schoollevelpaypremium(0.28).

Inbothcases,thepayoftheHeadteacheristhemosthighlyassociatedwiththeresidualincome.

Part3:

Where

income

changes

between

two

years,

how

is

it

spent?

Wecomparedschoolincomeandexpenditurein2008/9and2009/10.Onlyafewschoolsseestable

income;forexample,only11%ofschoolsexperiencedanabsolutechangeinincomeoflessthan1%,

while22%sawafallinincomeand61%hadarisegreaterthan5%(allinnominalterms).Wearenot

chieflyconcernedabouthoworwhytheincomeincreased,butwewillusetheCFRdatatoanalyse

howthechangeisdeployed.NotethatasweonlyhaveoneSWC,wecanonlyconsiderchangesin

theCFRdata.Thisanalysisrelatesonlytosecondaryschools.

TomakethingsmanageablewegrouptheCFRexpenditureitemsasfollows:

Group1,"Teachers":Teachingstaffcosts

Group2,"EdSupport":Educationsupportstaffcosts

Group3,"Otherstaffandstaffrelated":Supplystaffcosts,Premisesstaffcosts,Administrative

andClericalstaffcosts,Cateringstaffcosts,Costsofotherstaff,Indirectemployeeexpenses,

Developmentandtrainingcosts,Supplyteacherinsurancecosts,andStaffrelatedinsurance

costs.

Group4,"Buildingsrelated":Buildingmaintenanceandimprovementcosts,Grounds

maintenanceandimprovementcosts,Cleaningandcaretakingcosts,Waterandsewagecosts,

Energycosts,Nondomesticratesexpenditure,andOtheroccupationcosts.

Group5,"LearningandICTresources":Learningresourcescosts(notICTequipment)andICTLearningresourcescosts.

Group6,Other:ExamFees,Administrativesupplycosts,Otherinsurancepremiums,Special

facilitycosts,Cateringsupplycosts,Agencysupplyteachingstaffcosts,Boughtprofessional

servicescurriculum,Boughtprofessionalservicesother,Communityfocusedextendedschool

staffandCommunityfocusedextendedschoolcosts.

Group7,Balance:Totalincomeminustotalexpenditure

Wefocusfirstonaverageresponses,beforeconsideringtheheterogeneityofdecisionsmade.Table

2looksataveragechangesinschoolincomeandexpenditureitems.Inordertomakealltheitems

adduptothechangeinincome,wemeasurethechangeinexpenditureongroupKasfollows:


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(expenditureonKin2010expenditureonKin2009)*100/(incomein2009).Summingupoverall

theseitemsplustheresidualbalanceaddsuptothepercentageincomechange:(incomein2010

incomein2009)*100/(incomein2009).Wesplitschoolsupintoquintilesofincomechangeand

displaytheresultsseparatelyforthesequintiles.

Changeinexpenditureonteachersisthebiggestsingleitem,butisbynomeansthewholestory.

ThedifferenceinthepercentagechangeonteachersshowsthebiggestgradientbetweenQ5andQ1

atabout4percentagepoints,butisconsiderablysmallerthanthegradientinincomechangesof

about15percentagepoints.Schoolsalsousetheirresidualbalancetotakethestrainofincreases

anddecreases.Expenditureonresourcesandonbuildingsfalls,eveninsomeschoolswithrising

income.Allquintilegroupsshowanaverageincreaseinspendingoneducationalsupportstaff,

thoughsomewhatgreaterinthequintileswithrisingincome.Spendingonteachersdoesfallinthe

schoolswiththelargestfallsinincome,butnotbyagreatdeal.

Itisinterestingthatthereisanasymmetrybetweenschoolswithsubstantialincreasesinincomeand

thosewithsubstantialfalls.Theformeronaverageincreaseexpenditureonteachersquite

substantially,thelatterdonotdecreaseitonaverage. Thisisbothamajortotalofexpenditureand

alsoonethatisdifficulttocut.

Wenowlookattherangeofdifferentresponsesschoolsmaketochangesintheirincome.Table3

exploreswhichexpenditureitemsschoolschoosetomakethebiggestchangein.Foreachincome

changequintile,wereportthepercentageofschoolsthatmakethebiggestincreaseinexpenditure

foreachgroup.Forexample,lookingatthebottomleftnumberinthetable,27.85%oftheschools

inthebottomquintilemadetheirlargestincreaseinexpenditureonteachers.

Table3arevealssomeinterestingfacts.Inparticularitshowsahugerangeofdifferentdecisionstakenbyschools.Fewerthanhalfofschools,42%onaverage,madeanincreaseinspendingon

teacherstheirlargestchange.Thispercentageisconstantacrossallthetopfourquintiles.Thenext

mostpopulardecisionineachquintileandoverallwastoletthebudgetbalanceadjust,22%of

schoolsoverall.Notethatgiventhedefinitionoftheexpenditurechange(asafractionof2009

incomelevel)theyareallinthesameunits.Betweenahalfandathirdofschoolsineachquintile

madeotherdecisionsonwhattoincreasespendingonthemost,withnooverallpatternamongthe

othergroupsofitems.Itisworthrepeatingthatonly41%ofschoolswiththebiggestriseinincome

chosetomakethebiggestspendingincreaseonteachers.Thepatternagainfitstheemerging

findingsofalotofvariationinschoolsdecisions.

Table3bshowstheexpenditureitemswiththelowestriseorbiggestfall,i.e.whichitemeachschool

makesthelowestincreaseinexpenditureon.Forthetopthreequintiles,themostcommon

decisionsareforresources,buildingsandotherstaffcosts,butthedistributionisfairlyflat:thereisa

widesetofdecisionsmade.

Figure19showsthefullvariationinthedecisionstakenbyschoolsinresponsetoachangein

income.Itusestheboxplotsintroducedabovetoshowthedistributionofthechangeinexpenditure

(asdefinedabove)foreachoftheexpendituregroupsacrossthefiveincomechangequintiles.


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AswehaveseenfromTable3,expenditureonteachersshowsthebiggestaverageacrossall

quintiles.Butitalsoshowsthebiggestvariationintermsoftheinterquartilerangeandthebiggest

rangebetweentheupperandloweradjacentvalues.AsTable4shows,around60%ofschools

increaseexpenditurebymoreonotherfactorsthanonteachers. Inparticular,thevariationon

teacherexpenditureisgreatestinthetopandbottomquintiles.LookingatQ1schools,themedian

changeisaboutzero,butthereisverysubstantialvariationaroundthat.

Figure20adoptsthesameoveralllayoutasFigure19,butplotsthedistributionofthechangein

expenditureonanitemrelativetothechangeinincome:(expenditureonKin2010expenditureon

Kin2009)*100/(incomein2010incomein2009).Itislikelythatsomeelementswillbesubjectto

denominatoreffects:whenthedenominator(incomein2010incomein2009)isapproximately

zero,thevariablewillbecomeverylarge.Notethatnegativenumbersareperfectlypossiblehere,

andindeedthefigureshowstobeverycommon.Theseariseforexampleifaschoolseesarisein

incomebutreducesexpenditureonacertainitem.

Themessageofthefigureisagainthatthereisgreatvariationinthedecisionsthatschoolstakeon

howtodeploytheincreaseintheirbudget.Focussingonthetoptwoquintileswheredenominator

effectsarelessofanissue,weseenorealcommonalityofresponseinthesharesaccordedtothe

differentgroups.Someschoolswiththebiggestincreasesspenditallonteacherswhileothers

reduceteacherspending.Theevengreaterrangeofvariationinthelowerquintilesreflectswider

differencesindecisionsbutprobablyalsoderivefromthedenominatoreffect.

Figure21plotsthenormalisedpercentageexpenditurechange,(expenditureonKin2010

expenditureonKin2009)*100/(incomein2009),againstthepercentagechangeinincome,(income

in2010incomein2009)*100/(incomein2009)foreachK,alongwiththebestlinearfit.Each

observationrepresentsonesecondaryschool.Therearestrongpositiverelationshipsfor

expenditureonteachers,andfortheresidualbudgetbalance.Thereareonlyweakpositive

relationshipsforotherstaffexpenditureandforbuildingsrelatedexpenditure.Theselinearfitlines

capturetheaveragerelationship,butagainperhapsthemainfindingofthesechartsisthevarietyof

relationshipsbetweenbudgetchangesandspendingchanges.Therearemanyschoolsinoff

diagonalcellsforteacherexpenditureandothers.

Conclusions

Moneydoesmattertoschoolsbecausetheybuytheresourcesthatallowteachingandlearningtotakeplaceandthisreportwehavestudiedthespendingdecisionsofschools.Oneofthemain

contributionsistoexploitanewdataset,thefirstfullsweepoftheSchoolWorkforceCensus,which

enablesustoidentifyveryspecificstaffexpendituredecisionsmadebyschools.Wehaveshownvery

substantialvariationsinoperationaldecisions,andalsoshownthatmuchofthisvariationis

idiosyncraticratherthanexplainedbytheschoolscircumstances.Thishighvariabilityinresource

utilisationhasalsobeenshowninternationally(OECD,2008).

Inthisfinalsectionweconsiderwhethertherearepolicyresponsestothisknownvariationin

spendingpatternsthatmightbemoreeffectiveinimprovingschoolsfinancialdecisions.Thecurrent

policyapproachistoprovideschoolswithinformationtocomparespendingpatternswithlike


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schoolsandtousepolicybriefingstodisseminatebestpractice.Webelievethereareanumberof

problemswiththisapproachandsuggesthowabehaviouraleconomicsapproachmightbecapable

ofimprovingschoolfinancialdecisions.

Difficultieswithcurrentpolicyapproachofdisseminationofbestpractice

Thecurrentapproachtohelpingschoolsmakeefficientfinancialdecisionsconsistsofatwofold

approachofbenchmarkingandbestpracticeadvice.TheDfESchoolFinancialBenchmarking

website2allowsschoolstocomparetheirCFRreturnstothoseofsimilarschoolsacrossthecountry

toseewheretheirownspendingissignificantlydifferentfrompeers.However,thewebsites

usefulnesstoschoolsisclearlylimitedbecauseitcannotdisaggregateteachingstaffexpenditure

betweenmanagementandclassroomteachers,andissilentonwhichofthesecomparisonschoolsis

asuccessfulschool.

Thewebsitedoesnotallowuserstoeasilyrelatethesehighlevelexpendituredatatoschool

outcomes.

It

is

therefore

an

inadequate

tool

for

giving

any

explicit

advice

on

best

practice

on

spendingpatterns.Perhapsthislackofdirectedadviceexplainswhyonlyaminorityofheadteachers

andmanagershaveeveraccessedthiswebsite;inasampleof38schools,Dodd(2008,p.38)finds

that:Fewoftheschoolstakeagenuineinterestinorseemuchvalueinbenchmarkingtheir

performanceusingeitherparentlocalauthoritydataortheDfESbenchmarkingwebsite.Thisis

slightlysurprisingasoneofthecharacteristicsofthesampleschoolsisarefusaltoacceptthat

currentlevelsofperformancecannotbeimproved.TheDfEreportsthatusagehaspickedupin

morerecentyears(201011).

Therearemanysourcesofideasavailabletoschoolsonhowtospendtheirmoney(althoughsome

aremore

firmly

backed

by

evidence

than

others),

in

the

UK

and

further

afield

3

.Some

recent

exampleswhicharebasedonanalysisincludeaseriesofbriefsreleasedbytheAuditCommission

(2011a,2011b,2011c,2011d)outliningpotentialareasforcostsavingsandefficiencies.Thereports

coveredareasincludingclassroomdeployment,thecurriculum,andmanagingstaffabsenceand

cover.Althoughthereportssuggestedthereweremanyareasinwhichsavingsmaybemade,the

authorsconcludedmostareasheldlimitedscopeforcostreductionandsuggestedbetterutilisation

ofteachingassistantswastheareawhichmayholdthemostscopeforsavings.

Inasecondexample,theSuttonTrustreleaseddetailedguidance(Higginsetal,2011)onhowto

spendthepupilpremium,whichcitedresearchfindings.Thedocumentlistedpossiblechoiceswith

anevaluation

of

the

likely

impact

on

test

scores

and

the

cost

effectiveness.

Theseguidancedocumentsonbestpracticearenecessarilylimitedbythelackofastrongandrobust

evidencebasefromwhichwecanspecifywhatbestpracticeis,eitheringeneralorvaryingwith

circumstances.Thisisaseriousimpedimenttoimprovingschoolsfinancialdecisions.Aswenoted

above,whileitseemsunlikelythatthepatternsofsubstantialandlargelyidiosyncraticvariationwe

seeareoptimaldecisions,thereisnoagreedandwellsupportedviewofwhatwouldbeoptimal.

2http://www.education.gov.uk/sfb

3Forexample,someexplicitquantifiedguidanceforUSschoolsinImprovingTeachingandLearningWhen

BudgetsAreTight:http://www.edweek.org/ew/articles/2011/09/01/kappan_odden.html .
http://www.education.gov.uk/sfbhttp://www.edweek.org/ew/articles/2011/09/01/kappan_odden.htmlhttp://www.edweek.org/ew/articles/2011/09/01/kappan_odden.htmlhttp://www.education.gov.uk/sfb


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Thelackofanyfirmrecommendationsatanaggregateiscompoundedbythefactthatschoolsdo

faceverydifferentoperationalenvironments.Thequalityofinstructionandaschoolsclimateare

complexandabstract.Whereascentralizedsystemsaregoodatimpartingsimplespendingrules,itis

notobviousthatremotelydesignedrulesareeffectiveindealingwithcomplexresourceuse.

Governmentagenciesdohavearoleinfacilitatinganalysisofaggregatedschoolsdataand

implementingcarefulstudies,bothofwhichshouldinfluenceunderstandingonbestpractice.

However,theyarelikelytobelessgoodatunderstandingthatcomplexresourcedevelopmentis

necessarilysensitivetospecificcontexts,sothelearntexperiencesofschoolswillalwaysbecritical.

Bottomupdevelopmentofknowledgeinthiswayalsoholdsthepotentialofsubstantiallongrun

productivitygrowththroughradicalinnovationatschools.Furthermore,teachersmayrespondmore

positivelytoasystemthatempowersthemtomakechoicesratherthanimposesrestrictions.

Usingbehaviouraleconomicstohelpimprovefinancialdecisions

Thebehaviouraleconomicstraditioniswellsuitedtoanalysinghowtoencourageheadteachersand

financialmanagerstotakeamoreproactiveroleinimprovingschoolefficiency.Interestingly,Dodd(2006)reportsthatthemajorityofheadteachersbelievetheirschoolisefficient,butthisseems

unlikelygivingthatmanyheadsdevolveschoolresourceplanningtobursarswhosimplyproduce

budgetsbasedonrollingforwardhistoricalexpenditure.

Dolanetal(2010)characterisetheinnovationsprovidedbybehaviouraleconomicsas:Drawingon

psychologyandthebehaviouralsciences,thebasicinsightofbehaviouraleconomicsisthatour

behaviourisguidednotbytheperfectlogicofasupercomputerthatcananalysethecostbenefitsof

everyaction.Instead,itisledbyourveryhuman,sociable,emotionalandsometimesfalliblebrain.

Itisnow

clear

that

we

make

decisions

in

two

ways:

reflective

and

automatic

(see

Thaler

and

Sunstein,2008).Thefirstiswhattraditionaleconomicsfocusesonandwedescribedtowardsthe

startofthisreport,basedoninformation,constraintsandincentives.Thesecondisbasedonmore

immediatestimuliandreflectsmuchmoreautomaticandseeminglyirrationalandinconsistent

decisions.Ithasbeendescribedaschangingbehaviourwithoutchangingminds.

Thereisadifficultyhere,mentionedabove,inthattheresearchbasedoesnotprovideabest

allocationthatwecanusethetoolsofbehaviouraleconomicstonudgepeopletowards.Unlike,

forexample,intryingtoaffectobesity,thereisnoobviousbestbehaviourtoadopt.Thegoalinstead

hastobetogetschoolstobemorereflectiveandthoughtfulindecidingtheirspendingpatterns.

Thistrend

towards

encouraging

schools

to

think

more

about

spending

isevident

in

the

School

FinancialBenchmarkingwebsite.Herewemakefivesuggestions(drawingonDolanetal.,2010)asto

howbehaviouraleconomicscanhelptakethisapproachfurther:

1.Gettherightmessenger

Thereceptionthatpeoplegiveamessage,suchassuggestionsonschoolspending,dependsonthe

natureofthemessenger.Peoplearegenerallymoreopentoinformationfromotherswith

demographicandbehaviouralsimilarities,andwhoarecredibleexperts.Thissuggeststhat

headteachersofsimilarschoolspeoplegrapplingwiththesamedailyproblemsmightbepotent

messengers.Ofcourse,headteachersarenotcredibleexpertsintheresearchevidenceonbest


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practice.However,whereaschoolisrequiredtocutitsbudget,theheadteacheroftheverysimilar

schoolthatalreadyoperatesonthelowerbudgetisacredibleexpertinhowthisisachievable.

2.Giveexplicitincentivesforschoolstosavemoney

Thecurrentfinancialsystemforschoolsoffersnoincentivestosavemoney.Indeed,forlocal

authoritymaintainedschoolsitisimportanttospendallincomereceivedtoavoidthebudgetbeing

reducedinfutureyears.Whiletherearereasonablyimportantincentivesforimprovingoutcomes

(viaschoolperformancetablesetc),theyareratherdistantfromthefinancialdecisionsandmay

evenbedisconnectedinthemindsofschoolleaders.Whilewedonotwanttoencouragearaceto

thebottomtoprovidethecheapesteducationpossible,schoolgovernorsmightbeencouragedto

offerbonuspaymentstoheadteachersandfinancialmanagersundercertaincircumstances.One

situationmightbewhereaschoolisidentifiedashavinghighercoststhanotherschoolsinidentical

structuralanddemographiccircumstances,andsoashareofanycostreductionachievedcouldbe

passedtoschoolleadersinbonuspayments.Anothersituationwherebonuspaymentsmightbe

appropriateiswhereaschoolisrunningadeficitandsohaslittleoptionbuttoreducecosts.Itmay

soundcounterintuitivetopaybonusesinthissituation,andwouldbepoliticallydifficultinatimeof

austerity,butbyaligningtheincentivesofschoolleadersandgovernorsitmayencouragedifficultor

eveninnovativecutstobemade.

3.Schoolsareattractedtofollowingtypicalbehaviourornorms

Schooloughttobeinterestedinwhatotherschoolsdo,andreportingpositivenormshasbeen

foundtoencourageindividualsinachievingdesirableoutcomes.Onceagain,ourproblemisalackof

understandingastowhatconstitutesbestpracticeinschools.However,encouraginghighcost

schools(giventheircircumstances)toexploredataonspendinginsimilarschoolsislikelytoimprove

theefficiencyofthesystemoverall.Thismaynothappenautomaticallybecausethebenchmarking

websiteisnotcurrentlyveryheavilyused.Oneapproachcouldbetousedatatoidentifyschools

withunexpectedlyhighcostsandproactivelytransmitwithinformationtotheirschoolleadership

teams,withtherequirementthattheybeconsideredbyschoolgovernors.Allschoolscouldalsobe

encouragedtocarryoutroutinewasteauditstoseewhetherfundsarebeingspentinefficiently

(seeforexample,GrubbandTredway,2010,andtheAuditCommission,2009).Clearly,these

suggestionsrelysomewhatontraditionalregulationratherthanbehaviouralnudges.

4.Preventrollingforwardhistoricalspendingbeingthedefaultbudgetplan

Almostallschoolbursarssetatentativebudgetforthefollowingyearbyrollingforwardcurrent

spending(adjustingforinflationandknownpayincrements).Thistraditionalincrementalbudgeting

approachmeansthatmanagersonlyneedtojustifyvariancesversuspastyearstothegoverning

body,basedontheassumptionthatthebaselineisautomaticallyapproved.Changingthisdefault

budgettosomeotherbudgethasbeenshowninbehaviouraleconomics,andindeedintheworldof

business,tobeaneffectivedeviceforforcingindividualstooptimisetheirspendingdecisions.The

problemisdecidingwhatthenewdefaultbudgetshouldbe.Themostpopularalternativeiszero

basedbudgetingwhereeverylineitemmustbeapprovedwithreferencetopreviouslevelsof

expenditure,butthisapproachcanbeverytimeconsuming.Analternativewouldbetotweakthe

budgetsoftwaretoencourageschoolstotakeamorereflectiveattitudetotheirspending.For

example,thesoftwarecouldreporttheaverageforpresetcomparatorschoolsalongsidethe


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schoolsowndata.Thishasdangersofcourse:showingtheaverageforcomparatorschoolsmay

undermineahighperformingschooldoingsomethingverywell.

5.Nurturetheselfimageofheadteachersasoutstandingfinancialmanagers

Liketherestofus,theheadteachersegomakesthemwanttohaveagoodreputationintheir

school.Egodrivessomeheadteacherstoimprovetheirleaguetablepositionyearafteryear;others

wanttoincreaseschoolcapacityasasignalofsuccessortakeoverotherschools.Egomakessome

headteachersnurtureanimageasaradicalinnovatororagamechanger,butcurrentlytherearefew

plauditsupholdingtheeffortsofthosewhoachieveexcellenceonrelativelymodestbudgetsorwho

findinnovativewaystoreducecostsinaparticulararea.Givenconfidencebytheirgovernors,itmay

bethatattemptstonurturesuchaselfimagecanhelpsupportgreaterproactivecarebeingtaken

withfinancialdecisions.


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